Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUZBA Proceedings of the 25th International Multiconference INFORMATION SOCIETY Slovenska konferenca o umetni inteligenci Kognitivna znanost Slovenian Conference on Artificial Intelligence Cognitive Science Mitja Lustrek, Matjaz Gams, Rok Piltaver Toma Strle, Borut Trpin, Olga Markic Odkrivanje znanja in podatkovna skladisca - SiKDD Kognitonika Data Mining and Data Warehouses - SiKDD Cognitonics Dunja Mladenic, Marko Grobelnik Vladimir A. Fomichov, Olga S. Fomichova 15. mednarodna konferenca o prenosu tehnologij Demografske in druzinske analize 15th International Technology Transfer Conference Demographic and Family Analyzes Spela Stres, Robert Blatnik Janez Malacic, Mari Joze Osredkar, Matjaz Gams Vzgoja in izobrazevanje v informacijski druzbi Vseprisotne zdravstvene storitve in pametni senzorji Education in Information Society Pervasive Health and Smart Sensing Uros Rajkovic, Borut Batagelj Nina Rescic, Oscar Mayora, Daniel Denkovski Srednjeevropska konferenca o uporabnem Legende racunalnistva in informatike teoreticnem racunalnistvu Legends of Computing and Informatics Middle-European Conference on Applied Borut Zalik, Matjaz Gams Theoretical Computer Science Andrej Brodnik, Gabor Galambos, Branko Kavsek Ljubljana, Slovenija 10.–14. oktober 10–14 October Ljubljana, Slovenia httpis.ijs.si Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 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 Kognitonika Cognitonics 15. mednarodna konferenca o prenosu tehnologij 15th International Technology Transfer Conference Demografske in družinske analize Demographic and Family Analyzes Vzgoja in izobraževanje v informacijski družbi Education in Information Society Vseprisotne zdravstvene storitve in pametni senzorji Pervasive Health and Smart Sensing Srednjeevropska konferenca o uporabnem teoretičnem računalništvu Middle-European Conference on Applied Theoretical Computer Science Legende računalništva in informatike Legends of Computing and Informatics Uredniki / Editors Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Borut Trpin, Olga Markič, Dunja Mladenić, Marko Grobelnik, Vladimir A. Fomichov, Olga S. Fomichova, Borut Žalik, Špela Stres, Robert Blatnik, Janez Malačič, Mari Jože Osredkar, Uroš Rajkovič, Borut Batagelj, Nina Reščič, Oscar Mayora, Daniel Denkovski, Andrej Brodnik, Gábor Galambos, Branko Kavšek http://is.ijs.si 10.–14. oktober 2022 / 4–8 October 2022 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, Outfit7 in Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana Toma Strle, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Borut Trpin, Filozofska 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 Vladimir A. Fomichov, Department of Intelligent Monitoring Systems, Institute No. 3 Control Systems, Informatics and Electric Power Industry, Moscow Aviation Institute (National Research University), 121552 Moscow, Russia Olga S. Fomichova, Centre of Social Competences "Dialogue of Sciences", State Budget Professional Educational Institution “Sparrow Hills”, Universitetsky prospect 5, 119296 Moscow, Russia Špela Stres, 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 Mari Jože Osredkar, Teološka fakulteta Poljanska 4, 1000 Ljubljana Uroš Rajkovič, Fakulteta za organizacijske vede, Univerza v Mariboru Borut Batagelj, Fakulteta za računalništvo in informatiko, Univerza v Ljubljani Nina Reščič, Department of Intelligent Systems, Institut »Jožef Stefan«, Ljubljana Oscar Mayora, Digital Health Lab, Fondazione Bruno Kessler, Trento, Italy Daniel Denkovski, Computers Science and Computer Engineering, Faculty of Electrical Engineering and Information Technologies, Skopje, North Macedonia Andrej Brodnik, Univerza na Primorskem in Univerza v Ljubljani Gábor Galambos, Univerza v Szegedu Branko Kavšek, Univerza na Primorskem Borut Žalik, Fakulteta za elektrotehniko, računalništvo in informatiko, Univerza v Mariboru, Maribor 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 2022 Informacijska družba ISSN 2630-371X Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID 129579779 ISBN 978-961-264-255-6 (PDF) PREDGOVOR MULTIKONFERENCI INFORMACIJSKA DRUŽBA 2022 Petindvajseta multikonferenca Informacijska družba je preživela probleme zaradi korone. Zahvala za skoraj normalno delovanje konference gre predvsem tistim predsednikom konferenc, ki so kljub prvi pandemiji modernega sveta pogumno obdržali visok strokovni nivo. Pandemija v letih 2020 do danes skoraj v ničemer ni omejila neverjetne rasti IKTja, informacijske družbe, umetne inteligence in znanosti nasploh, ampak nasprotno – rast znanja, računalništva in umetne inteligence se nadaljuje z že kar običajno nesluteno hitrostjo. Po drugi strani se nadaljuje razpadanje družbenih vrednot ter tragična vojna v Ukrajini, ki lahko pljuskne v Evropo. Se pa zavedanje večine ljudi, da je potrebno podpreti stroko, krepi. Konec koncev je v 2022 v veljavo stopil not raziskovalni zakon, ki bo izboljšal razmere, predvsem leto za letom povečeval sredstva za znanost. Letos smo v multikonferenco povezali enajst odličnih neodvisnih konferenc, med njimi »Legende računalništva«, s katero postavljamo nov mehanizem promocije informacijske družbe. IS 2022 zajema okoli 200 predstavitev, povzetkov in referatov v okviru samostojnih konferenc in delavnic ter 400 obiskovalcev. Prireditev so spremljale okrogle mize in razprave ter posebni dogodki, kot je svečana podelitev nagrad. Izbrani prispevki bodo izšli tudi v posebni številki revije Informatica (http://www.informatica.si/), ki se ponaša s 46-letno tradicijo odlične znanstvene revije. Multikonferenco Informacijska družba 2022 sestavljajo naslednje samostojne konference: • Slovenska konferenca o umetni inteligenci • Izkopavanje znanja in podatkovna skladišča • Demografske in družinske analize • Kognitivna znanost • Kognitonika • Legende računalništva • Vseprisotne zdravstvene storitve in pametni senzorji • Mednarodna konferenca o prenosu tehnologij • Vzgoja in izobraževanje v informacijski družbi • Študentska konferenca o računalniškem raziskovanju • Matcos 2022 Soorganizatorji in podporniki konference so različne raziskovalne institucije in združenja, med njimi 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. S podelitvijo nagrad, še posebej z nagrado Michie-Turing, se avtonomna stroka s področja opredeli do najbolj izstopajočih dosežkov. Nagrado Michie-Turing za izjemen življenjski prispevek k razvoju in promociji informacijske družbe je prejel prof. dr. Jadran Lenarčič. Priznanje za dosežek leta pripada ekipi NIJZ za portal zVEM. »Informacijsko limono« za najmanj primerno informacijsko potezo je prejela cenzura na socialnih omrežjih, »informacijsko jagodo« kot najboljšo potezo pa nova elektronska osebna izkaznica. Čestitke nagrajencem! Mojca Ciglarič, predsednik programskega odbora Matjaž Gams, predsednik organizacijskega odbora i FOREWORD - INFORMATION SOCIETY 2022 The 25th Information Society Multiconference (http://is.ijs.si) survived the COVID-19 problems. The multiconference survived due to the conference chairs who bravely decided to continue with their conferences despite the first pandemics in the modern era. The COVID-19 pandemic from 2020 till now did not decrease the growth of ICT, information society, artificial intelligence and science overall, quite on the contrary – the progress of computers, knowledge and artificial intelligence continued with the fascinating growth rate. However, the downfall of societal norms and progress seems to slowly but surely continue along with the tragical war in Ukraine. On the other hand, the awareness of the majority, that science and development are the only perspective for prosperous future, substantially grows. In 2020, a new law regulating Slovenian research was accepted promoting increase of funding year by year. The Multiconference is running parallel sessions with 200 presentations of scientific papers at eleven conferences, many round tables, workshops and award ceremonies, and 400 attendees. Among the conferences, “Legends of computing” introduce the “Hall of fame” concept for computer science and informatics. Selected papers will be published in the Informatica journal with its 46-years tradition of excellent research publishing. The Information Society 2022 Multiconference consists of the following conferences: • Slovenian Conference on Artificial Intelligence • Data Mining and Data Warehouses • Cognitive Science • Demographic and family analyses • Cognitonics • Legends of computing • Pervasive health and smart sensing • International technology transfer conference • Education in information society • Student computer science research conference 2022 • Matcos 2022 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 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. The award for life-long outstanding contributions is presented in memory of Donald Michie and Alan Turing. The Michie-Turing award was given to Prof. Dr. Jadran Lenarčič for his life-long outstanding contribution to the development and promotion of information society in our country. In addition, the yearly recognition for current achievements was awarded to NIJZ for the zVEM platform. The information lemon goes to the censorship on social networks. The information strawberry as the best information service last year went to the electronic identity card. 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 Mitja Lasič Vladimir Fomichov, Russia Blaž Mahnič Vesna Hljuz Dobric, Croatia Alfred Inselberg, Israel Jay Liebowitz, USA 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 Toby Walsh, Australia Sergio Campos-Cordobes, Spain Shabnam Farahmand, Finland Sergio Crovella, Italy Programme Committee Mojca Ciglarič, chair Nikola Guid Andrej Ule Bojan Orel, Marjan Heričko Boštjan Vilfan Franc Solina, Borka Jerman Blažič Džonova Baldomir Zajc Viljan Mahnič, Gorazd Kandus Blaž Zupan Cene Bavec, Urban Kordeš Boris Žemva Tomaž Kalin, Marjan Krisper Leon Žlajpah Jozsef Györkös, Andrej Kuščer Niko Zimic Tadej Bajd Jadran Lenarčič Rok Piltaver Jaroslav Berce Borut Likar Toma Strle Mojca Bernik Janez Malačič Tine Kolenik Marko Bohanec Olga Markič Franci Pivec Ivan Bratko Dunja Mladenič Uroš Rajkovič Andrej Brodnik Franc Novak Borut Batagelj Dušan Caf Vladislav Rajkovič Tomaž Ogrin Saša Divjak Grega Repovš Aleš Ude Tomaž Erjavec Ivan Rozman Bojan Blažica Bogdan Filipič Niko Schlamberger Matjaž Kljun Andrej Gams Stanko Strmčnik Robert Blatnik Matjaž Gams Jurij Šilc Erik Dovgan Mitja Luštrek Jurij Tasič Špela Stres Marko Grobelnik Denis Trček Anton Gradišek 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 Initial Results in Predicting High-Level Features of Constrained Multi-Objective Optimization Problems / Andova Andrejaana, Vodopija Aljoša, Krömer Pavel, Uher Vojtěch, Tušar Tea, Filipič Bogdan .................................... 7 Learning the Probabilities in Probabilistic Context-Free Grammars for Arithmetical Expressions from Equation Corpora / Chaushevska Marija, Todorovski Ljupčo, Brence Jure, Džeroski Sašo ......................................... 11 Prediction of the Inflow in Macedonian Hydropower Plants, Using Machine Learning / Kizhevska Emilija, Gjoreski Hristijan, Luštrek Mitja ........................................................................................................................ 15 Naslov / Kolar Žiga, Erzar Blaž, Čelan Nika, Hrastič Aleksander, Leskovec Gašper, Konečnik Martin, Prestor Domen, Susič David, Skobir Matjaž, Gams Matjaž .......................................................................................... 19 Unified Question Answering in Slovene / Logar Katja, Robnik-Šikonja Marko .................................................... 23 Social Media Analysis for Assessing Resilience / Osojnik Aljaž, Ženko Bernard, Žnidaršič Martin .................... 27 Urban Mobility Policy Proposal Using Machine-Learning Techniques / Shulajkovska Miljana, Smerkol Maj, Gams Matjaž .................................................................................................................................................... 31 IMF Quality Assurance of Mammograms Using Deep Convolutional Neural Networks and Transfer Learning / Slapničar Gašper, Us Peter, Alukić Erna, Mekiš Nejc, Mlakar Miha, Žibert Janez .......................................... 35 Vehicle Axle Distance Detection From Time-series Signals Using Machine Learning / Susič David, Erzar Blaž, Čelan Nika, Leskovec Gašper, Kolar Žiga, Konečnik Martin, Prestor Domen, Skobir Matjaž, Gams Matjaž .. 39 Študija učinkovitosti algoritma za razporejanje terenskega dela / Tušar Tea, Sever Nace, Vodopija Aljoša, Filipič Bogdan ................................................................................................................................................... 43 Interaktivno eksperimentiranje z besednimi vložitvami v platformi ClowdFlows / Žnidaršič Martin, Pol ak Senja, Podpečan Vid ................................................................................................................................................... 47 Kognitivna znanost / Cognitive Science ................................................................................................................ 51 PREDGOVOR / FOREWORD ............................................................................................................................... 53 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................... 54 Into the Constant Now—Comparing DES and micro- phenomenology, two methods for exploring consciousness / Bass-Krueger Julian, Wiedemann Elisa, Demšar Ema ................................................................................. 55 LTP and LTD dependence on spontaneous activity in hippocampal and cortical glutamate synapses and the role of anaesthetics in the study of plasticity and learning / Bratuša Maša ............................................................ 60 Trusted sources and disinformation: studying the limits of science / Gsenger Rita ............................................. 64 Opacity and understanding in artificial neural networks: a philosophical perspective / Justin Martin .................. 68 Politizirana znanost in zaupanje v znanost kot politična uniforma / Marušič Jar Žiga ......................................... 72 Filozofski in psihološki vidiki človeške racionalnosti / Tomat Nastja .................................................................... 77 Joint history of play provides means for coordination / Voronina Liubov, Heintz Christophe .............................. 83 Predicting Trust in Science in the Context of COVID-19 Pandemic: The Role of Sociodemographics and Social Media Use / Zelič Žan, Berič Martin, Kobal Grum Darja ................................................................................. 87 Odkrivanje znanja in podatkovna skladišča - SiKDD / Data Mining and Data Warehouses - SiKDD ............... 91 PREDGOVOR / FOREWORD ............................................................................................................................... 93 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................... 94 Emotion Recognition in Text using Graph Similarity Criteria / Komarova Nadezhda, Novalija Inna, Grobelnik Marko ................................................................................................................................................................ 95 SLOmet – Slovenian Commonsense Description / Mladenić Grobelnik Adrian, Novak Erik, Grobelnik Marko, Mladenić Dunja ................................................................................................................................................. 99 Measuring the Similarity of Song Artists using Topic Modelling / Calcina Erik, Novak Erik ............................... 103 Exploring the Impact of Lexical and Grammatical Features on Automatic Genre Identification / Kuzman Taja, Ljubešić Nikola ............................................................................................................................................... 107 Stylistic features in clustering news reporting: News articles on BREXIT / Sittar Abdul, Webber Jason, Mladenić Dunja .............................................................................................................................................................. 111 Automatically Generating Text from Film Material – A Comparison of Three Models / Korenič Tratnik Sebastian, Novak Erik ...................................................................................................................................................... 116 The Russian invasion of Ukraine through the lens of ex-Yugoslavian Twitter / Evkoski Bojan, Mozetič Igor, Kralj Novak Petra, Ljubešić Nikola ......................................................................................................................... 120 v Visualization of consensus mechanisms in PoS based blockchain protocols / Baldouski Daniil, Tošić Aleksandar ...................................................................................................................................................... 124 Using Machine Learning for Anti Money Laundering / Kržmanc Gregor, Koprivec Filip, Škrjanc Maja ............. 128 Forecasting Sensor Values in Waste-To-Fuel Plants: a Case Study / Brecelj Bor, Šircelj Beno, Rožanec Jože Martin, Fortuna Blaž, Mladenić Dunja ............................................................................................................ 132 Machine Beats Machine: Machine Learning Models to Defend Against Adversarial Attacks / Rožanec Jože Martin, Papamartzivanos Dimitrios, Veliou Entso, Anastasiou Theodora, Keizer Jelle, Fortuna Blaž, Mladenić Dunja .............................................................................................................................................................. 136 Addressing climate change preparedness from a smart water perspective / Gucek Alenka, Pita Costa Joao, Massri M.Besher, Santos Costa João, Rossi Maurizio, Casals del Busto Ignacio, Mocanu Iulian ................ 140 SciKit Learn vs Dask vs Apache Spark Benchmarking on the EMINST Dataset / Zevnik Filip, Fortuna Carolina, Mušić Din, Cerar Gregor................................................................................................................................. 144 An Efficient Implementation of Hubness-Aware Weighting Using Cython / Buza Krisztian ............................... 148 Semantic Similarity of Parliamentary Speech using BERT Language Models & fastText Word Embeddings / Meden Katja ................................................................................................................................................... 151 Kognitonika / Cognitonics ..................................................................................................................................... 155 PREDGOVOR / FOREWORD ............................................................................................................................. 157 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 159 Theoretical Foundations and Experience of Six All-Russian Creative Web-based School-contests “Portrait of Your Town” / Fomichov Vladimir, Fomichova Olga ....................................................................................... 161 The Case of the Civic University of Landscape/Living Environment as a Model of Learning/ Process/ Action for Ternary Systems Human/Society/Life Environment / Micarelli Rita, Pizziolo Giorgio ................................... 167 Were the Principles of Cognitonics Met in Online Education During the Covid-19 Pandemic? / Panev Ida ..... 171 The Method of Cognitive Painting as an Effective Tool for Constructing a Positive Cognitive-Emotional Space for Children and Adolescents under Conditions of the COVID-19 Pandemic / Fomichova Olga, Fomichov Vladimir ........................................................................................................................................................... 175 Chess as a Tool for Developing 21st Century Skills with a Deliberate Practice Approach / Krivec Jana .......... 181 Karma and Dharma: Two Ways of Human Living / Kim Joonho ........................................................................ 185 15. mednarodna konferenca o prenosu tehnologij / 15th International Technology Transfer Conference .. 189 PREDGOVOR / FOREWORD ............................................................................................................................. 191 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 192 ZAHVALE / ACKNOWLEDGEMENTS ................................................................................................................ 196 Technology transfer offices as a facilitator of knowledge triangle integration in the knowledge valorisation era: focus group discourse analysis / Vuka Ivana, Balić Nikola, Havasi Andras, Mifsud Marie ........................... 197 Proof of Concept typology: a method for classification of PoC activities according to a technology cycle timeframe / Eriksonas Linas .......................................................................................................................... 200 The “Incubator of Innovativeness” program driving technical readiness levels of the Cracow University of technology innovations / Kasz Jacek ............................................................................................................ 205 Science meeting the needs of entrepreneurs / Kukowska-Kaszuba Magdalena, Piotrowska-Kirschling Agnieszka, Kołakowski Paweł, Rutkowski Grzegorz ...................................................................................... 209 Commercialization of R&D results created with public funds in the National Academy of Sciences of Belarus / Uspenskiy Alexander, Uspenski Aliaksei, Prybylski Maxim ........................................................................... 213 Selection and evaluation of technologies for the transfer to the industry / Iatchevici Vadim ............................. 217 Subsidizing Knowledge Transfer with Public Funds / Belusky Michal ............................................................... 221 Effective collaboration and IP management / Pal Levin, Blatnik Robert, Stres Špela ....................................... 226 Project support services of a technology transfer office / Lutman Tomaž, Stres Špela ..................................... 228 Challenges of Legal and Regulatory Framework for Blockchain Technology in the EU / Fric Urška, Urbančič Jurij ................................................................................................................................................................. 233 Technology Transfer: Start and Stop of Deep Well Pumping Through GSM System / Maldonado Pedro, Sarabia Silvestre, Costilla Emmanuel, Avelino Roberto .............................................................................................. 238 Advanced 3D sensor system for visual control of geometrically complex products / Florjančič Urška, Žganec Mario, Malnarič Vili, Kurbegović Hidajet, Nikonov Anatolij, Žganec Gros Jerneja, Sevšek Tomaž ............... 241 DODATEK / APPENDIKS .................................................................................................................................... 245 INTRODUCTION AND AIM OF THE CONFERENCE ................................................................................... 246 ACKNOWLEDGEMENTS ............................................................................................................................... 249 OVERVIEW OF THE PROGRAMME ............................................................................................................. 251 WELCOME ADDRESSES .............................................................................................................................. 252 vi KEYNOTE SPEECH: CEA’s experience in effective collaboration with industry ........................................... 255 PITCH COMPETITION: BEST INNOVATION WITH COMMERCIAL POTENTIAL ....................................... 259 Course of the competition ......................................................................................................................... 260 Abstracts of the competing teams and their technologies .............................................................................. 263 Innovative equipment of intervention/service watercraft: Mobile Electromagnetic Mooring System and Batychron ............................................................................................................................................. 264 Antiviral surgical masks, gowns and drapes ............................................................................................. 266 MEEVA - Measurable Enhanced Virtual Reality platform for teens with Autism and Neurodevelopment Disorders .............................................................................................................................................. 268 From polyurethane waste to high value added raw materials ................................................................... 270 Water soluble cannabinoids with increased stability ................................................................................. 272 Rational y designed lutein esters: “The onset of improved and sustainable eye health remedy” ............. 274 Award announcement Best innovation with commercial potential ................................................................. 275 Award announcement: WIPO IP Enterprise Trophy ....................................................................................... 276 Opportunities arising from publicly funded research projects / presentations of successful scientific projects ................................................................................................................................................................... 277 Award announcement: WIPO Medal for Inventors ......................................................................................... 278 Connecting education system with academia: Presentations of selected research topics from the Jožef Stefan Institute and proposals for cooperation ..................................................................................................... 279 Paper presentations: research papers on technology transfer and intellectual property ............................... 281 The Conference closing ............................................................................................................................ 283 CONFERENCE CEREMONY ................................................................................................................... 285 Demografske in družinske analize / Demographic and Family Analyzes ......................................................... 289 PREDGOVOR / FOREWORD ............................................................................................................................. 291 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 292 O nekaterih dilemah interpretacije podatkov o družini : ankete javnega mnenja in podatki statističnega urada Republike Slovenije / Bahovec Igor ............................................................................................................... 293 Demographic developments in Kosovo in two decades of the century XXI / Behrami Sami, Bajraktari Fadil ... 297 Politična korektnost pokopavanja ali pravica do groba / Čepar Drago .............................................................. 303 Nekaj primerov demografskega zmanjševanja / Gams Matjaž .......................................................................... 306 Obremenjujoče izkušnje v otroštvu: primerjalna študija med odraslimi otroci alkoholikov in nealkoholikov / Jerebic Sara, Jerebic Drago ........................................................................................................................... 311 Razlike v predpisovanju zdravil v obdobju pred in med pandemijo bolezni COVID-19 / Kasesnik Karin .......... 315 Coalovi indeksi v sloveniji v letih 1991, 2011 in 2021 / Malačič Janez .............................................................. 319 Odločitev za življenje / Osredkar Mari Jože ....................................................................................................... 322 Pomen izkušenj iz izvorne družine za razumevanje povezave med obrambnimi mehanizmi in tveganim uživanjem alkohola / Poljak Lukek Saša ....................................................................................................... 326 Zasvojenosti v odraslosti v povezavi z zlorabami v otroštvu / Repič Slavič Tanja ............................................. 331 Poznejše umikanje iz zaposlitve in nižja indeksacija za izboljšanje dolgoročne vzdržnosti pokojninskega sistema / Sambt Jože .................................................................................................................................................. 335 Vpliv izboljševanja izobrazbene strukture prebivalstva na javnofinančno vzdržnost / Sambt Jože, Istenič Tanja ........................................................................................................................................................................ 339 Funkcionalnost družinskega življenja v družinah z alkoholizmom in odrasli otroci alkoholikov / Simonič Barbara ........................................................................................................................................................................ 342 Nevrobiološko ozadje težav v čustveni regulaciji in tveganje za odvisnost od alkohola / Valenta Tanja ........... 347 Vzgoja in izobraževanje v informacijski družbi / Education in Information Society ........................................ 353 PREDGOVOR / FOREWORD ............................................................................................................................. 355 KONFERENČNI ODBORI / CONFERENCE COMMITTEES .............................................................................. 356 Sistem za spremljanje stresa preko prevodnosti kože med reševanjem testa / Albreht Jaka ........................... 359 Vizualizacija sinteze 2D abstraktnih teksturnih vzorcev z naključnostjo / Babič Davorin ................................... 363 Malokodno programiranje in razvoj spletnih aplikacij / Baggia Alenka, Leskovar Robert, Rajkovič Uroš, Baeva Motušić Andreana ........................................................................................................................................... 370 Pouk na daljavo: e-kulturni dan / Blatnik Živa .................................................................................................... 375 Razvijanje digitalnih kompetenc po vertikali / Blaznik Dunja .............................................................................. 379 Soba pobega pri pouku zgodovine / Carmona Natalija ...................................................................................... 383 Poučevanje glasbene umetnosti na daljavo / Čebulj Zajc Petra ........................................................................ 387 Uporaba interaktivnih kvizov pri pouku angleščine / Delovec Urška .................................................................. 390 vii E-vzgojni vikend »Bod' na kavču!« / Držanič Petra ............................................................................................ 394 Biti z mladimi tudi v času izobraževanja na daljavo / Držanič Petra .................................................................. 397 Uporaba spletne ankete pri izbirnem predmetu filmska / Gruden Reya Kristina ............................................... 401 Učenje svetlobe na daljavo / Hudi Primož .......................................................................................................... 405 Učna akademija – skupnost učiteljev, ki temelji na kolegialnem sodelovanju in skupnem učenju / Jagič Katarina ........................................................................................................................................................................ 409 Problem zasebnosti in varnost uporabnikov na družbenih omrežjih / Jakopič Veronika, Tomšič Nika, Horvat Laura, Jakomini Žiga, Podgorelec Vili, Kožuh Ines ........................................................................................ 412 Analiza rezultatov tretjega poskusnega tekmovanja v programiranju z delčki Pišek / Jelenec Ines, Nančovska Šerbec Irena ................................................................................................................................................... 418 Učencem prijazno poučevanje na daljavo / Jevšnik Barbara ............................................................................. 425 Kako narediti virtualno učno pot? / Jurač Vesna ................................................................................................ 428 Dileme in rešitve poučevanja na daljavo / Keser Ranka .................................................................................... 432 Podpora staršem in učencem pri šolanju na daljavo s pomočjo spletnega orodja Weebly / Kokec Barbara .... 437 Digitalna zbirka kamišibajev / Kokelj Martina ..................................................................................................... 440 Uporaba aplikacije Nexto pri terenskem delu na področju likovne umetnosti / Kosi Tina .................................. 443 “International Masterclasses” iz fizike osnovnih delcev / Lozar Andrej, Pestotnik Rok ...................................... 447 Uporaba portala Franček v osnovni šoli / Miljković Mateja................................................................................. 452 Kvalitetno učenje na daljavo – izziv za učitelja in učenca / Minić Miroslava ...................................................... 456 KIZ na prostem / Mlakar Tina ............................................................................................................................. 460 Uporaba Google Drive za usklajevanje med učitelji in delo z učenci / Močilar Mitja .......................................... 464 Spletni vodnik Plečnik v Kamniku v obliki sobe pobega / Nagode Burger Andreja ............................................ 467 Razvoj digitalnih kompetenc pri delu z učenci z učnimi težavami / Ozvatič Jure ............................................... 471 Digitalna pismenost kot sestavni del razrednih ur v osnovni šoli / Pajnik Tina, Strgar Sonja ............................ 476 Pandemija COVID-19 in digitalne kompetence študentov / Pičulin Pia, Žnidaršič Anja, Marolt Marjeta ........... 482 Sodobni pristopi poučevanja na daljavo pri poučevanju kardiovaskularnega sistema v srednji šoli / Povšič Miha, Janežič Lea .................................................................................................................................................... 486 Fizikalni poskusi z in brez informacijsko-komunikacijske tehnologije / Presetnik Katja ..................................... 490 Recept, navodilo, algoritem / Purg Peter ............................................................................................................ 494 Protokoli za preverjanje pristnosti uporabnikov / Rehberger Roman ................................................................. 499 Finančno opismenjevanje v osnovni šoli / Strgar Sonja ..................................................................................... 504 Oglaševanje in izdelava oglasov na STŠ ŠC Kranj / Strniša Gašper, Strniša Iva ............................................. 508 Učenje risanja in spoznavanje novega IKT orodja / Šebenik Tina ..................................................................... 511 Razvijanje digitalne pismenosti na razredni stopnji s pomočjo aplikacije BookCreator / Škrabl Nastja ........... 514 Spodbujanje in razvijanje bralnega razumevanja pri pouku angleščine s tehnologijo / Škrlec Rok ................... 517 Izobraževanje šolskih knjižničarjev na daljavo v Narodni in univerzitetni knjižnici / Škrlj Gregor ...................... 520 Airnominal / Štamcar Filip, Kralj Jakob, Mozer Alenka ....................................................................................... 524 Vpliv osebnostnih lastnosti starejših ljudi na zadovoljstvo uporabe ADC sistema za mobilno upravljanje senčil / Todorović Tanja, Dojčinović Aleksandar ........................................................................................................ 527 Igrifikacija v visokošolskem izobraževanju: primer visokošolskih učiteljev in sodelavcev / Urh Marko, Jereb Eva ........................................................................................................................................................................ 535 Pozitiven impulz IKT otroku s čustveno vedenjskimi težavami? / Zabukovec Alenka, Lorenčič Tadej .............. 541 Programski vzorci v rešitvah nalog iz uvodnega programiranja / Zapušek Matej, Nančovska Šerbec Irena .... 546 Animacija, ustvarjena z orodjem Stop Motion / Žmavc Sonja ............................................................................ 552 Vseprisotne zdravstvene storitve in pametni senzorji / Pervasive Health and Smart Sensing ...................... 557 PREDGOVOR / FOREWORD ............................................................................................................................. 559 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 561 Optimized method for walking detection by wristband with accelerometer sensor / Hrastič Aleksander, Kranjec Matej, PI3 ....................................................................................................................................................... 563 Android Integration of a Machine Learning Pipeline for Human Activity Recognition / Srbinoski Viktor, Denkovski Daniel, Kizhevska Emilija, Gjoreski Hristijan ................................................................................ 567 Speaking Recognition with Facial EMG Sensors / Nikoloski Antonio, Poposki Petar, Kiprijanovska Ivana, Stankoski Simon, Gjoreski Martin, Nduka Charles, Gjoreski Hristijan ........................................................... 571 Machine-learning models for MDS-UPDRS III Prediction: A comparative study of features, models, and data sources / Lobo Vítor, Branco Diogo, Guerreiro Tiago, Bouça Raquel, Ferreira Joaquim ............................. 575 Elements of a System for Holistic Monitoring of Mental Health Characteristics at Home / Kirsten Kristina, Arnrich Bert ..................................................................................................................................................... 579 viii Towards Multi-Modal Recordings in Daily Life: A Baseline Assessment of an Experimental Framework / Anders Christoph, Moontaha Sidratul, Arnrich Bert .................................................................................................... 583 Assessing Sources of Variability of Hierarchical Data in a Repeated-Measures Diary Study of Stress / Lukan Junoš, Bolliger Larissa, Clays Els, Šiško Primož, Luštrek Mitja..................................................................... 587 Academic Performance Relation with Behavioral Trends and Personal Characteristics from Wearable Device Perspective / Saylam Berrenur, Ekmekci Ekrem Yusuf, Altunoğlu Eren, Durmaz İncel Özlem.................... 591 Detection of postpartum anemia using machine learning / Susič David, Bombač Tavčar Lea, Hrobat Hana, Gornik Lea, Lučovnik Miha, Gradišek Anton .................................................................................................. 596 Covid symptoms home questionnaire classification and outcome verification by patients / Jakimovski Goran, Nikolova Dragana ........................................................................................................................................... 600 Piloting ICT Solutions for Integrated Care / Luštrek Mitja, Angelopoulou Efthalia, Guzzi Pietro Hiram, Drobne Samo, Matkovic Roberta, Miljkovic Miodrag, Papageorgiou Sokratis G, Blažica Bojan ................................ 604 Network Anomaly Detection using Federated Learning for the Internet of Things / Cholakoska Ana, Jakimovski Bojan, Pfitzner Bjarne, Gjoreski Hristijan, Arnrich Bert, Kalendar Marija, Efnusheva Danijela ...................... 608 Srednjeevropska konferenca o uporabnem teoretičnem računalništvu / Middle-European Conference on Applied Theoretical Computer Science .......................................................................................................... 613 PREDGOVOR / FOREWORD ............................................................................................................................. 615 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 617 A Neural Network Based Classification Algorithm for Asthma Using Capnography / Békési József, Galambos Gábor, Kelemen András, Papp Imre, Tolnai József ....................................................................................... 619 Online Bin Covering with Exact Advice / Brodnik Andrej, Nilsson Bengt J., Vujovic Gordana........................... 623 Subsets without arithmetic subsequences: computational experiments and unsatisfiable cores / Čibej Uroš, Győri Ervin ...................................................................................................................................................... 627 Exact time measuring challenges / Dobravec Tomaž ........................................................................................ 631 Systematic generation of precedence based MILP models with P-graphs for multipurpose scheduling problems / Hegyháti Máté ................................................................................................................................................ 635 On relations of Watson-Crick finite automata to other computational paradigms / Nagy Benedek ................... 639 Surrogate Component Approach for a Synchronization Problem / Olivas González Alejandro, Quil iot Alain, Toussaint Hélène ............................................................................................................................................ 643 Local reflection symmetry detection in Earth observation data / Podgorelec David, Lukač Luka, Žalik Borut .. 647 Approximate Keys and Functional Dependencies in Incomplete Databases With Limited Domains--Algorithmic Perspective / Sali Attila, Alatar Munqath ....................................................................................................... 651 Building energy demand regression / Storcz Tamás, Kistelegdy István, Ercsey Zsolt ...................................... 656 Clique relaxations of zero-one linear programs / Szabo Sandor, Zavalnij Bogdan ............................................ 660 Legende računalništva in informatike / Legends of Computing and Informatics ............................................ 665 PREDGOVOR / FOREWORD ............................................................................................................................. 667 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 668 Dosežki kandidata Rudija Brica / Bric Rudi ........................................................................................................ 669 Dosežki kandidata M. Gamsa / Gams Matjaž .................................................................................................... 672 Opis dosežkov Tomaža Gornika / Gornik Tomaž ............................................................................................... 676 Opis dosežkov Tomaža Kalina / Kalin Tomaž .................................................................................................... 679 Evolucija predmeta Računalništvo in informatika v obdobju dveh desetletij / Leskovar Robert ........................ 681 Dosežki kandidata Domna Mongusa / Mongus Domen ..................................................................................... 685 Prispevek za zgodovino slovenske informatike / Schlamberger Niko ................................................................ 688 Pregled mojega raziskovalnega dela / Solina Franc .......................................................................................... 692 Informatika narodu / Stanovnik Tone .................................................................................................................. 696 Omrežne varnostne storitve, zasebnost in računalniško obvladovanja zaupanja – strnjena kronologija (Slovenija od učenke do mednarodne partnerice) / Trček Denis .................................................................. 700 Dosežki kandidata Žiga Turka / Turk Žiga .......................................................................................................... 704 Indeks avtorjev / Author index .............................................................................................................................. 705 ix x Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek A Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume A Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Uredniki / Editors Mitja Luštrek, Matjaž Gams, Rok Piltaver http://is.ijs.si 11. oktober 2022 / 11 October 2022 Ljubljana, Slovenija 1 2 PREDGOVOR Umetna inteligenca še vedno hitro napreduje, so pa glavni dosežki lanskega leta na področjih, kjer smo jih že vajeni. Avtonomna vozila so vedno bolj avtonomna in se že uporabljajo za prevoz potnikov, čeravno v zelo omejenem obsegu. Jezikovni modeli, kot so izboljšani GPT- 3, postajajo zreli za praktično uporabo, zato se njihovi stvaritelji začenjajo ukvarjati s tem, kako jih odvračati od tvorbe politično nekorektnih besedil. Po eni strani razumljivo, po drugi strani pa – ob problemu omejevanja svobode govora na spletu, ki si je letos prislužil nominacijo za informacijsko limono – tudi nekoliko skrb zbujajoče. Modeli za generiranje slik iz opisov, katerih prvi vidnejši predstavnik je bil DALL-E, so se letos namnožili, in videli smo več poizkusov njihove uporabe za izdelavo stripov. Potlej pa so tu še aplikacije v robotiki, medicini, računalniški varnosti in seveda zvitemu streženju spletnih reklam. Ko umetna inteligenca postaja vedno zmožnejša in bolj razširjena, se pojavljalo pomisleki o njeni varnosti ter prizadevanja za uporabo, ki bo družbi v korist in ne v škodo. Ta škoda se začne z nepotrebnimi nakupi zaradi preveč zvitih reklam, ki nas spremljajo že dolgo in smo se z njimi sprijaznili, nadaljuje pa s še resnejšimi problemi, kot so denimo slabe medicinske in zaposlovalne odločitve. Zaradi tovrstnih problemov vse več držav sprejema zakonodajo o umetni inteligenci, ki bo raziskovalcem bržkone povzročila nekaj sivih las, a če bo dobra – in k temu skušajmo prispevati, kolikor lahko – bo tudi pomagala, da naše delo ne bo dobilo zloveščega pridiha. Vse več je tudi razmišljanja o splošni umetni inteligenci z zmožnostmi, ki presegajo človeške. Njen vpliv na človeško družbo utegne biti dramatičen. A če želimo zagotoviti, da bo dramatično dober, se bomo morali v prihodnjih letih resno lotiti raziskovalnega področja zagotavljanja, da kompleksni modeli umetne inteligence zares počno tisto, kar mislimo in želimo, da počno, ki je zaenkrat še precej v povojih. Za konec pa poglejmo, kako je letos z našo konferenco. 11 prispevkov, ki smo jih prejeli, sicer ne opisuje tako visokoletečega dela, kot ga obravnavata prejšnja dva odstavka, so pa vseeno kakovosti in morda začetek česa pomembnega. Število je zmerno in Institut Jožef Stefan še malo bolj prevladujoč, kot običajno, za kar do neke mere krivimo COVID-19 – ne ker bi nas še vedno hudo pestil, ampak ker sta dve konferenčno klavrni leti raziskovalce konferenčenja malo odvadili. A upajmo, da bo tudi to minilo. Prirejamo pa letos v okviru konference Data Science Meetup – dogodek z lepo tradicijo in dobro udeležbo, kjer imajo strokovnjaki iz industrije kratke predstavitve svojega dela. Na to smo ponosni, saj rešuje težavo pomanjkanja prispevkov iz industrije, ki smo se je dotaknili že v preteklih predgovorih. 3 FOREWORD Artificial intelligence is still making good progress, but the major achievements of the past year are in the areas where we have grown to expect them. Autonomous vehicles are increasingly autonomous and already being used to carry passengers, albeit in a very limited way. Language models, such as the improved GPT-3, are becoming ready for practical use. Because of that, their authors are starting to work on preventing them from generating politically incorrect texts. This is on one hand understandable, but on the other hand – considering the problem of censorship on the internet, which was nominated for the Information Lemon this year – somewhat concerning. Models that generate images from text descriptions, whose first prominent representative was DALL-E, are proliferating. We have seen several attempts of using them to generate comics. There are also applications in robotics, medicine, cybersecurity and of course cunning delivery of online ads. With artificial intelligence becoming ever more capable and pervasive, concerns about its safety and use for the benefit of the society rather them harm are increasingly raised. The harm starts with unnecessary consumption due to insidious advertising, but these is old news we have become accustomed to. However, there are potentially more serious problems, such as bad medical or employment decisions. Because of these, a number of countries are drafting legislation about artificial intelligence. This will surely be a headache for researchers, but if the legislation is good – and we should help make it such if we can – it will benefit the reputation of our work. Superhuman general artificial intelligence is also increasingly entering professional and public debate. Its impact on the humanity could be dramatic. To ensure it is dramatically good, we will have to tackle the very much open research problem of ensuring that complex artificial-intelligence models indeed do what we think and want them to do. Let us finally take a look at our conference. The 11 papers we received are not describing work as ambitious as that described in the previous paragraphs, but they are nevertheless good and perhaps the beginning of something important. The number is modest and Jožef Stefan Institute even more overrepresented than usual, which we partially blame on COVID-19. Not that it is still a major problem, but in the two years without truly good conference the researchers seem to have lost the habit of going to conferences to some degree. We hope that this, too, shall pass. On a brighter note, we are organizing Data Science Meetup as a part of our conference. This is an event with a longstanding tradition and good attendance in which experts from the industry give short talks on their work. We are quite proud of this achievement, since it addresses the lack of papers from the industry which we bemoaned in past forewords. 4 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Mitja Luštrek Matjaž Gams Rok Piltaver Cene Bavec Marko Bohanec Marko Bonač Ivan Bratko Bojan Cestnik Aleš Dobnikar Erik Dovgan Bogdan Filipič Borka Jerman Blažič Marjan Krisper Marjan Mernik Biljana Mileva Boshkoska Vladislav Rajkovič Niko Schlamberger Tomaž Seljak Peter Stanovnik Damjan Strnad Miha Štajdohar Vasja Vehovar Martin Žnidaršič 5 6 Initial Results in Predicting High-Level Features of Constrained Multi-Objective Optimization Problems Andrejaana Andova Pavel Krömer Tea Tušar Aljoša Vodopija Vojtěch Uher Bogdan Filipič Jožef Stefan Institute and Department of Computer Science Jožef Stefan Institute and Jožef Stefan International VSB - Technical University of Jožef Stefan International Postgraduate School Ostrava Postgraduate School Jamova cesta 39 17. listopadu 2172/15 Jamova cesta 39 Ljubljana, Slovenia Ostrava-Poruba, Czech Republic Ljubljana, Slovenia andrejaana.andova@ijs.si pavel.kromer@vsb.cz tea.tusar@ijs.si aljosa.vodopija@ijs.si vojtech.uher@vsb.cz bogdan.filipic@ijs.si ABSTRACT needs to be treated as constrained or unconstrained. Moreover, Trying numerous algorithms on an optimization problem that we Ma et al. [5] showed which constraint handling techniques are encounter for the first time in order to find the best-performing more successful in solving CMOPs, depending on the problem algorithm is time-consuming and impractical. To narrow down type. Similarly, the connectivity of the feasible region (or problem the number of algorithm choices, high-level features describing connectivity for short) defines the multimodality of the problem important problem characteristics can be related with algorithm violation landscape and, therefore, crucially affects the choice of performance. However, characterizing optimization problems for algorithms that can solve the problem efficiently [5]. this purpose is challenging, especially when they include multiple High-level features of a new problem can be predicted using objectives and constraints. In this work, we use machine learning automatically calculated low-level problem features. The most (ML) to automatically predict high-level features of constrained widely known low-level features in evolutionary optimization multi-objective optimization problems (CMOPs) from low-level, are the exploratory landscape analysis (ELA) features. They were exploratory landscape analysis features. The results obtained on initially introduced to characterize single-objective optimization the MW benchmark show a significant difference in classification problems and implemented in the flacco package [2]. More re- accuracy depending on the applied evaluation approach. The poor cently, Liefooghe et al. [4] proposed a set of ELA features for performance of the leave-one-problem-out strategy indicates multi-objective optimization problems, and Vodopija et al. [10] the need for further investigation of the relevance of low-level introduced additional ELA features for CMOPs. features in CMOP characterization. In this work, we use the ELA features from [4] and some from [10] to investigate whether they are useful for predicting problem KEYWORDS type and connectivity. To the best of our knowledge, this is the first attempt to predict the high-level features of CMOPs. A simi- constrained multi-objective optimization, exploratory landscape lar study was performed by Renau et al. [7] on single-objective analysis, sampling methods, problem characterization, machine optimization problems. They used ELA features to classify the op- learning timization problem. When splitting the data into training and test sets, instances from the same problem were used for both training 1 INTRODUCTION and testing. The first of our three experiments follows this setup. Predicting high-level features of constrained multi-objective op- However, because this evaluation methodology is not useful in timization problems (CMOPs) is important as it can help de- practice (the class of a new real-world problem is unknown), a cide which algorithm to use when faced with a new (real-world) second experiment is performed using the leave-one-problem- CMOP. The structure of the objective and constraint functions are out methodology. Finally, the third experiment varies the number usually unknown for such problems. Moreover, the evaluation of of target problem instances used for training to gain further in- problem solutions might be very time-consuming. In such cases, sight in the difficult task of predicting high-level features from it is beneficial to know certain high-level features of the CMOP, low-level ones. which eases the selection of an appropriate multi-objective op- The paper is further organized as follows. In Section 2, we in- timization algorithm or constraint handling technique to solve troduce the theoretical background of constrained multi-objective the problem efficiently. optimization. In Section 3, we explain the features used in this Two frequently considered high-level features of CMOPs are study. In Section 4, we present the considered test problems, and the problem type and connectivity of the feasible region. The in Section 5 the experimental setup. In Section 6, we report on the problem type characterizes whether and how the constraints obtained results. Finally, in Section 7, we provide a conclusion change the Pareto front of the problem. As pointed out by Tanabe and present the ideas for future work. et al. [8], this feature is useful as it indicates whether the problem 2 THEORETICAL BACKGROUND 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 A CMOP can be formulated as: distributed for profit or commercial advantage and that copies bear this notice and minimize 𝑓 (𝑥 ), 𝑚 = 1, . . . , 𝑀 𝑚 the full citation on the first page. Copyrights for third-party components of this (1) work must be honored. For all other uses, contact the owner/author(s). subject to 𝑔 (𝑥 ) ≤ 0, 𝑘 = 1, . . . , 𝐾, 𝑘 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia where 𝑥 = (𝑥 ) is a search vector of dimension 𝐷, 𝑓 : © 2022 Copyright held by the owner/author(s). 1, . . . , 𝑥𝐷 𝑚 𝑆 → R are objective functions, 𝑔 : 𝑆 → 𝑘 R constraint functions, 7 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Andova et al. 𝐷 Table 1: High-level features of the MW test problems. 𝑆 ⊆ R is the search space, and 𝑀 and 𝐾 are the numbers of objectives and constraints, respectively. A solution 𝑥 is feasible, if it satisfies all constraints 𝑔 (𝑥) ≤ 0 𝑘 Problem Type Connectivity for 𝑘 = 1, . . . , 𝐾. For each constraint 𝑔 we can define the con- 𝑘 MW1 II Disconnected straint violation as 𝑣 (𝑥) = max(0, 𝑔 (𝑥)). The overall constraint 𝑘 𝑘 MW2 I Disconnected violation is defined as MW3 III Connected 𝐾 MW4 I Connected ∑︁ 𝑣 (𝑥 ) = 𝑣 (𝑥 ). (2) 𝑘 MW5 II Connected 𝑖 MW6 II Disconnected A solution 𝑥 is feasible iff 𝑣 (𝑥) = 0. MW7 III Connected A feasible solution 𝑥 ∈ 𝑆 is said to dominate another feasible MW8 II Disconnected solution 𝑦 ∈ 𝑆 if 𝑓 (𝑥) ≤ 𝑓 (𝑦) for all 1 ≤ 𝑚 ≤ 𝑀, and 𝑓 (𝑥) < MW9 IV Connected 𝑚 𝑚 𝑚 ∗ 𝑓 (𝑦) for at least one 1 ≤ 𝑚 ≤ 𝑀. A feasible solution 𝑥 ∈ 𝑆 is a MW10 III Disconnected 𝑚 Pareto-optimal solution if there exists no feasible solution 𝑥 ∈ 𝑆 MW11 IV Disconnected that dominates ∗ 𝑥 . All feasible solutions constitute the feasible MW12 IV Disconnected region, 𝐹 = {𝑥 ∈ 𝑆 | 𝑣 (𝑥) = 0}, and all nondominated feasible MW13 III Disconnected solutions form the Pareto set, 𝑆o. The image of the Pareto set in MW14 I Connected the objective space is the Pareto front, 𝑃o = {𝑓 (𝑥) | 𝑥 ∈ 𝑆o}. 3 EXPLORATORY LANDSCAPE ANALYSIS They are the minimum and maximum correlations between the objectives and the overall constraint violation. ELA is a selection of techniques able to analyze the search and objective space of a problem, their correlation and their charac- 4 TEST PROBLEMS teristics with the goal of identifying the features important for the performance of optimization algorithms. To extract the ELA We base this study on 14 CMOPs proposed by Ma et al. [5] and features, one needs to first generate a sample of solutions. The called MW1–14. In addition to proposing the problems, the au- ELA features use statistical methods to characterize the problem thors also describe them with high-level features, such as the landscape. Thus, one can use an arbitrary sample size. However, problem type and connectivity of the feasible region. The values the ELA features are generally more accurate for large sample of these two high-level features for each MW problem are listed sizes. The ELA features proposed by Liefooghe et al. [4] and in Table 1. used also in this work can be divided into four categories: global, Many of the ELA features proposed by Liefooghe et al. [4] multimodality, evolvability, and ruggedness features. can only be calculated for bi-objective optimization problems. The global features capture certain global problem properties, Therefore, we investigate only the bi-objective versions of the for example, the correlation between the objective values, average MW problems although three of them are scalable in the number and maximum distance between solutions in the search space and of objectives. All MW problems are also scalable in the num- the objective space, the proportion of non-dominated solutions, ber of variables. We use 5-dimensional problems to match the the average and maximum rank of solutions, etc. experimental setup from [7]. The multimodality features assess the number of local optima in the objective space. They are computed for the bi-objective 5 EXPERIMENTAL SETUP space and also for each objective separately, in both cases by In preliminary experiments, we used six sampling methods from analyzing the neighbourhood of each solution. If a solution domi- the ghalton [1] and scipy [9] Python libraries: gHalton, Halton, nates its neighbors (or has a better objective value than its neigh- Sobol, Latin hypercube sampling, optimized Latin hypercube bors), it is defined as a local optimum. The multimodality features sampling, and uniform sampling [3]. The results have shown comprise the proportion of solutions that are locally optimal, the that similar prediction accuracies are obtained when using data average and maximum distances between local optima, etc. provided by any of these sampling methods. For this reason, The evolvability features describe how fast a local optimizer we only present the results obtained using the Sobol sampling would converge towards an optimum. They are calculated by method in the rest of the paper. analyzing how many neighboring solutions are dominated by, The Sobol sampling method generates a sample set by parti- dominating, or incomparable with a given solution. tioning the search space and filling each partition with a sample The ruggedness features measure the correlation between the solution. We generate additional Sobol sample sets using the information and quality from neighboring solutions – larger cor- Cranley-Patterson rotation [3]. The solutions from the original relation means a smoother landscape. The features are calculated sample set are rotated using a random shift of each dimension, by using Spearman’s correlation coefficient on the evolvability thus creating new sample sets that preserve the properties of features between each pair of neighboring solutions. the Sobol sampling. The modulo operation keeps the shifted val- In addition, we include four ELA features from [10] that de- ues within the unitary interval. This approach was also used by scribe the violation landscape and its relation with the objective Renau et al. [7]. space. The first feature is the feasibility ratio. It is expressed as Following this approach, we generate 100 sets of samples, the proportion of feasible solutions in the sample and is one each with 512 solutions, which we then evaluate on all 14 MW of the most frequently used features in categorizing violation benchmark problems. For each problem and sample set pair, we landscapes. The second feature is the maximum value of overall compute 46 ELA features, which represent a single instance in constraint violation values in the sample. The last two features the data. As a result, by evaluating the 100 sample sets on each measure the relationship between the objectives and constraints. of the 14 test problems, we get 1400 data instances. We then use 8 Initial Results in Predicting High-Level Features of CMOPs Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia these data instances and the corresponding high-level problem Table 2: Classification accuracy when 50% of all data is used features (problem type and connectivity) to train a classifier for for training and 50% for testing (first experiment). predicting the high-level problem features. We use two widely used machine learning (ML) methods for Learning method Problem type Problem connectivity classification: the Random Forest (RF) classifier and the k-Nearest RF 98% 99% Neighbors (KNN) classifier. The reason for choosing these classi- KNN 100% 100% fiers instead of some others is that, usually, RF performs favorably compared to other ML classifiers. KNN, on the other hand, uses the distance between solutions as a performance metric, which is useful when analyzing the obtained classification results visually. the problem type prediction, and to 41–57% for the problem con- For both RF and KNN, we apply the implementation from the nectivity prediction (see the leftmost points corresponding to 0% scikit-learn library [6]. For KNN, we keep the default settings, on the plots in Figure 2). This is comparable to the classification while for RF we train 100 trees. accuracy of the stratified classifier, which achieves 19% for the We perform three experiments that differ in the classifier eval- problem type prediction and 45% for the problem connectivity uation methodology. In the first experiment, we base the evalua- prediction. We can look at the results of the third experiment to tion methodology on the work by Renau et al. [7], where the data help us understand this decline in classification accuracy. As seen is split by using instances from the same problem for both train- from Figure 2, adding just a few instances of the target problem to ing and testing. There, 50% of all instances are used for training, the training set drastically increases the classification accuracy. and the remaining 50% for testing. Furthermore, we take care When the training data contains no instances from the target of dividing the instances into training and test sets so that the problem, the classifier is forced to find information about the proportion of instances from each problem is equal in both sets. high-level feature from other problems. However, this is a much However, this methodology does not correspond to the real- harder task given that similar problems often have different high- world scenario where we want to learn the high-level features of level features (see the middle and right plots in Figure 1). a problem encountered for the first time. Therefore, we use the In the visualizations in Figure 1 the points indicating the cor- leave-one-problem-out evaluation methodology in the second rectly classified instances have black edges. As we can see, for experiment. Here, the instances from a single problem are used many problems, RF has a 0% classification accuracy (top middle for testing, and the instances from all other problems for training. and top right plot). There are, however, some problems for which The procedure is repeated for all problems and the classification RF finds the correct class for a number of instances. Nonethe- accuracy is calculated as the average over all train-test splits. less, from these 2-D plots it is hard to understand why certain Finally, the third experiment is performed to see how adding instances are misclassified by RF. This is because RF detects de- target problem data to the training set influences the resulting tails in the data that the dimensionality reduction visualization classification accuracy. In this experiment, we vary the percent- method is unable to capture. age of target problem data that is used for training between 0% Similar behavior can be observed for KNN. Given that KNN and 99% with the step of 1%. When it equals 0%, no target problem classifies an instance depending on the classes of its most similar data is used for training, which corresponds to the leave-one- instances, the visualization from Figure 1 can help interpret its problem-out methodology of the second experiment. Note that poor results on the leave-one-problem-out methodology. We can this setup never equals the one from the first experiment because see that the clusters created by PacMAP are not well-aligned here the data of all other (non-target) problems is always used with the high-level features of problem type and connectivity. for training. Again, this procedure is repeated for all problems This makes predicting them a hard task for KNN. The cluster- and we report the average classification accuracy. ing by PacMAP suggests that the applied ELA features are not To better understand the task we are trying to solve, we visu- descriptive enough for predicting problem type and connectivity. alize the classes by first reducing the dimensionality of the fea- ture space from 46-D to 2-D using Pairwise Controlled Manifold 7 CONCLUSION AND FUTURE WORK Approximation Projection (PaCMAP) [11]. We use the Python In this work, we tried to predict high-level features of CMOPs. package pacmap with default parameter values. More specifically, using low-level ELA features, we constructed the classifiers to predict the problem type and connectivity. Two ML classifiers were utilized, RF and KNN. 6 RESULTS We employed three evaluation methodologies. The first one The results of the first experiment, where 50% of all data is used follows the related work and splits the data into two halves, one for training and 50% for testing, show that both RF and KNN serving as the training set and the other as the test set (instances achieve a classification accuracy above 98% (see Table 2). An ex- from the same problem are used in both sets). The second evalu- planation for such good results can be derived from the two left- ation methodology uses all instances from the target problem for most plots in Figure 1. Here, we can see that PacMAP finds many testing, and none for training. The third method gradually adds clusters in the data. However, the clusters are highly correlated to the target problem data to the training set. We achieved excellent the problems themselves. Thus, leaving some instances from the classification accuracy with the first evaluation methodology, but target problem in the training set results in a high classification very poor ones with the second one. The drop in classification ac- accuracy because the classification task is now transformed into curacy was checked by the third methodology, which has shown identifying to which cluster the new sample belongs, which is a that already a small number of instances of the same problem much easier task to perform. increases the classification accuracy. The more realistic scenario of having to predict the high-level Visualizations of the data in the form of 2-D plots show that feature of a yet unseen problem is tested in the second experi- CMOP instances form clusters that are highly correlated to the ment. Here, the classification accuracy drops to only 7–19% for problem instances, but not to the high-level problem features. For 9 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Andova et al. Figure 1: Dimensionality reduction of the ELA feature space using the PacMAP method. Points are colored based on their true values with correct classifications denoted by a black point edge. The top and bottom rows show the results for Random Forest and KNN, respectively, while the different classification targets are arranged in columns: the left column displays the results for the problem, the middle for problem type and the right for problem connectivity. N2-0254) and the Czech Science Foundation (grant no. GF22- 34873K). The Slovenian authors acknowledge additional financial support from the Slovenian Research Agency (young researcher program and research core funding no. P2-0209). 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Characterization of benchmark suites may also improve classifier performance. constrained continuous multiobjective optimization problems: A feature space perspective. Information Sciences, 607, 244–262. [11] Yingfan Wang, Haiyang Huang, Cynthia Rudin, and Yaron Shaposhnik. ACKNOWLEDGMENTS 2021. Understanding how dimension reduction tools work: An empirical approach to deciphering t-sne, umap, trimap, and pacmap for data visual- The authors acknowledge the project “Constrained multi-objective ization. Journal of Machine Learning Research, 22, 201, 1–73. Optimization Based on Problem Landscape Analysis” was finan- cially supported by the Slovenian Research Agency (project no. 10 Learning the Probabilities in Probabilistic Context-Free Grammars for Arithmetical Expressions from Equation Corpora Marija Chaushevska Ljupčo Todorovski Jure Brence & Sašo Džeroski marija.chaushevska@ijs.si ljupco.todorovski@fmf.uni-lj.si jure.brence@ijs.si|saso.dzeroski@ijs.si Jožef Stefan Int. Postgraduate School Jožef Stefan Institute & Jožef Stefan Institute & & Jožef Stefan Institute Faculty of Mathematics and Physics Jožef Stefan Int. Postgraduate School Jamova cesta 39 Jadranska cesta 21 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT Machine learning methods for supervised regression assume a A core challenge for both physics and artificial intelligence (AI) is fixed class of models, such as linear regression or neural networks symbolic regression: finding a symbolic expression that matches with a particular architecture, and find the one that provides the data from an unknown function. Symbolic regression approaches best fit to the training data. Equation discovery methods typi- are largely data-driven and search an unconstrained space of cally consider broader classes of mathematical equations. These mathematical expressions, often employing genetic algorithms. classes may be vast and many (often infinitely many) equations On the other hand, equation discovery approaches incorporate can be found that provide excellent fit to the training data. The domain knowledge to constrain the structure space and search it challenge of symbolic regression is therefore twofold. On one using local or exhaustive search methods. In this paper, we adopt hand, one can easily overfit the training data with an unnecessar- the use of probabilistic context-free grammars (PCFG) in equation ily complex equation. On the other hand, the space of candidate discovery and propose a method for learning the probabilities equations is huge and grows exponentially as equation complex- of production rules in such PCFGs. We take a universal PCFG ity increases, posing serious computational issues to equation with an initial set of manually assigned probabilities for each discovery methods. production rule. We learn new probabilities by parsing each Equation Discovery systems explore the hypothesis space of expressions in a given corpus of expression, such as the Feynman all equations that can be constructed given a set of arithmetic dataset. operators, functions and variable. They search for equations that fit given input data best. The number of all possible candidate KEYWORDS equations can be infinite. Early equation discovery systems used parametric approaches equation discovery, grammar, probabilistic context-free grammar, to specify the space of polynomial equations considered. LA- parsing, learning probabilities, probability distribution GRAMGE [13] uses context-free grammars (CFG) [9] to specify 1 INTRODUCTION the language of equations considered. The recent system ProGED [2] uses probabilistic context-free grammars (PCFG), where a Equation discovery is an area of machine learning that develops probability is associated with each production rule. In this paper, methods for automated discovery of quantitative laws, expressed we propose a method for learning these probabilities for a given in the form of equations, in collections of measured numeric PCFG by using a given corpus of expressions. data [5] [11]. More precisely, equation discovery methods seek to automate the identification of equation structure as well as pa- rameters. Traditionally, domain experts derive equation structure based on the theory in the domain and use standard numerical optimization methods to estimate their parameters. Equation 2 GRAMMARS FOR EQUATION DISCOVERY discovery methods often use domain knowledge to specify the space of equations they consider. The key questions in the field A grammar is a finite specification of a language. A language can are how to best represent the symbolic language of mathematics, contain an infinite number of strings, or even if it is finite, it can how to incorporate domain knowledge in the process of equa- contain so many strings that it is not practical to list them all. tion discovery, as well as how to perform the search for optimal Originating from computational linguistics, grammars are used equation structures. Symbolic regression methods are largely as formal specifications of languages and use a set of production data-driven and search an unconstrained space of mathematical rules to derive valid strings in the language of interest. A gram- expressions, often employing evolutionary algorithms. On the mar mainly consists of a set of production rules, rewriting rules other hand, equation discovery methods, such as process-based for transforming strings. Each rule specifies a replacement of a modeling [4], incorporate domain knowledge to constrain the particular string (its left-hand side) with another (its right-hand structure space and search using greedy-local [12] or exhaustive side). A rule can be applied to each string (equation) that contains search methods on the constrained space. The task of equation its left-hand side and produces a string in which an occurrence discovery is closely related to the task of supervised regression. of that left-hand side has been replaced with its right-hand side. A grammar further distinguishes between two kinds of symbols: Permission to make digital or hard copies of part or all of this work for personal non-terminal and terminal symbols; each left-hand side must 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 contain at least one non-terminal symbol. It also distinguishes a the full citation on the first page. Copyrights for third-party components of this special non-terminal symbol, called the start symbol. In equation work must be honored. For all other uses, contact the owner/author(s). discovery, we are interested in using grammars as generative Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia models, as opposed to their common use for parsing, i.e., discrim- © 2022 Copyright held by the owner/author(s). inating between legal and illegal strings in a language. 11 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Chaushevska, Todorovski, Brence, and Džeroski 2.1 Context-Free Grammar (CFG) ∑︁ In formal language theory, a context-free grammar [9] is a for- 𝑃 → (𝐴 → 𝛼 ) = 1 (2) mal grammar which is defined as a tuple G = (N, T, R, S). It is (𝐴→𝛼 ) ∈𝑅 used to generate all possible patterns of strings in a given for- The probability of a derivation (parse) is defined as the product mal language. The syntax of the expression on the right-hand of the probabilities of all the production rules used to expand side of the equation is prescribed with a context-free grammar. each node in the parse tree (derivation). These probabilities can The set T contains terminal symbols, i.e.,words for composing be viewed as parameters of the model. The probabilities of all sentences in the language or variables in the arithmetical ex- productions with the same non-terminal symbol on the left hand pressions. The terminals are primitive grammar symbols that side sum up to one, i.e., we impose a probability distribution on can not be further rewritten, i.e., no productions are affiliated the productions with the same symbol on the left hand side. As with them. Non-terminal symbols (syntactic categories) in the each parse tree, derived by a grammar 𝐺, is characterized by a set N represent higher-order terms in the language, such as noun sequence of productions, its probability is simply the product of or verb phrases. Each of the non-terminals represents expres- the probabilities of all productions in the sequence [11]. sions or phrases in a language. The production rules in the set We can extend the example context-free grammar 𝐺 above to 𝑀 R are rewrite rules of the form A → 𝛼, where the left-hand side a PCFG by assigning a probability to each of the six productions, is a non-terminal, 𝐴 ∈ 𝑁 , while the right-hand side is a string given below in brackets after each production: of non-terminals and terminals, 𝛼 ∈ (𝑁 ∪ 𝑇 )* . In natural lan- guage, a rule 𝑁 𝑃 → 𝐴𝑁 specifies that a noun phrase 𝑁 𝑃 has 𝐸 → 𝐸 + 𝑉 [𝑝 ] |𝐸 ∗ 𝑉 [𝑞] |𝑉 [1 − 𝑝 − 𝑞] an adjective 𝐴 and a noun 𝑁 . 𝐴 and 𝑁 represent the subsets of (3) adjectives and nouns, which are both terminals. No matter which 𝑉 → 𝑥 [𝑝 ] |𝑦 [𝑞 ] |𝑧 [1 − 𝑝 − 𝑝 ] 𝑣 𝑣 𝑣 𝑞 symbols surround it, the single non-terminal on the left hand Here we have parameterized the probability distributions over side can always be replaced by the right hand side. This is what productions for 𝐸 and 𝑉 with the parameters 0 < 𝑝 < 1; 0 < 𝑞 < distinguishes it from context-sensitive grammar. When deriving 1; 0 < 𝑝 < 1; and 0 < 𝑞 < 1, respectively. 𝑣 𝑣 a sentence, a grammar starts with a string containing a single Context-free grammars are typically used to parse sentences. non-terminal 𝑆 ∈ 𝑁 and recursively applies production rules to Probabilistic context-free grammars provide an estimate of the replace non-terminals in the current string with the strings on probability of a parse tree, in addition to the tree itself. Prob- the right-hands sides of the rules. The final string contains only abilistic context-free grammars also allow for another type of terminal symbols and belongs to the language defined by 𝐺. application — stochastic generation of sentences or, in our case, In equation discovery, grammars represent sets of expressions mathematical expressions. The probabilities, assigned to the pro- that can appear in the right hand side of equations. These gram- ductions, provide a great amount of control over the probability mars use several symbols with special meanings. For example, distribution of individual parse trees. In our example in Eq. 3, the the terminal 𝑐𝑜𝑛𝑠𝑡 ∈ 𝑇 is used to denote a constant parameter in parameters 𝑝 and 𝑞 control the probability of a larger number of an equation that has to be fitted to the input data. terms in an expression, while the parameters 𝑝 and 𝑞 tune the 𝑣 𝑣 A simple context-free grammar 𝐺 = (𝑁 ,𝑇 ,𝑅 ,𝑆 ) deriv- 𝑀 𝑀 𝑀 𝑀 𝑀 ratio between the number of occurrences of variables 𝑥, 𝑦 and 𝑧. ing linear expressions from variables 𝑥, 𝑦, 𝑧 is as follows: An important concept to consider when working with gram- mars is ambiguity. A grammar is formally ambiguous if there 𝑁 = {𝐸, 𝑉 } exist sentences (expressions) that can be described by more than 𝑀 one parse tree, generated by the grammar. Grammars for arith- 𝑇 = {𝑥, 𝑦, 𝑧, +, ∗} 𝑀 metic expressions can express another type of ambiguity, called 𝑅 = {𝐸 → 𝐸 + 𝑉 |𝐸 ∗ 𝑉 |𝑉 𝑀 (1) semantic ambiguity. All but the simplest arithmetic expressions 𝑉 → 𝑥 |𝑦 |𝑧 } can be written in many mathematically equivalent, but grammat- 𝑆 = 𝐸 ically distinct ways. It is generally useful to adopt a canonical 𝑀 representation that each generated equation is converted into. This allows us to compare expressions to each other and check We write multiple production rules with the same non-terminal whether they are mathematically equivalent in addition to com- on the left hand side using a compact, single-line representation, paring their parse trees. In our work, we use the Python symbolic e.g., 𝐸 → 𝐸 + 𝑉 | 𝐸 ∗ 𝑉 | 𝑉 stands for the set of rules {𝐸 → mathematics library SymPy [8] to simplify expressions, convert 𝐸 + 𝑉 , 𝐸 → 𝐸 ∗ 𝑉 , 𝐸 → 𝑉 }. them into canonical form, and compare them symbolically. 2.2 Probabilistic Context-Free Grammar 3 LEARNING PROBABILITIES IN PCFGS FOR (PCFG) ARITHMETICAL EXPRESSIONS Grammar formalisms are not new to the field of equation discov- Parameter learning approaches for PCFGs assume a fixed set of ery [4] [3] [13], but probabilistic grammars are. A probabilistic production rules and try to learn the probabilities assigned to grammar assigns probabilities to productions and thereby al- them. Some approaches encourage sparsity and remove rules lows one to use the grammar as a stochastic generator [10] [6] with very small probabilities. Parameter learning approaches [15]. Probabilistic Context-Free Grammars (PCFGs), are a sim- are typically more scalable than structure search approaches, be- ple model of phrase-structure trees. They extend context-free cause parameter learning is a continuous optimization problem grammars (CFGs) similarly to how hidden Markov models extend which is in general easier than the discrete optimization problem regular grammars. A grammar can be turned into a probabilistic of structure search. Therefore, most of the state-of-the art algo- grammar by assigning probabilities to each of its productions, rithms for unsupervised learning of natural language grammars such that for each 𝐴 ∈ 𝑁 : are parameter learning approaches. 12 Learning the Probabilities in PCFGs for Arithmetical Expressions from Equation Corpora Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 3.1 The Approach The second corpus consists of 4080 scientific expressions from In this paper, we propose a parameter learning approach for Wikipedia. Those mathematical expressions are named after peo- PCFGs, based on parsing a corpus of expressions. We adopt the ple and they are parsed from Wikipedia. Compared to the Feyn- universal PCFG probabilistic context-free grammar for arithmetic man dataset, Wikipedia’s corpus contains more functions such expressions used by ProGED [2]. While ProGED uses manually as: 𝐴𝑏𝑠, 𝑓 𝑎𝑐𝑡𝑜𝑟𝑖𝑎𝑙, 𝑡𝑎𝑛, 𝑠𝑖𝑛ℎ, 𝑐𝑜𝑠ℎ and 𝑝𝑜𝑤 (which do not exist assigned probabilities in this grammar, we use an initial set of in the Feynman database) as well as irrational constants (𝑒 and randomly assigned probabilities to each production rule. The 𝜋 ) and numerical constants, which have to be replaced by a con- universal grammar is composed of production rules that include stant ‘C’(const) in the grammar. The equations in Wikipedia’s the four basic operations (+,-,*, /), basic functions (such as sin or dataset contain between one and fifteen variables, which is twice log), constant parameters and variables. as much compared to the Feynman dataset and the maximum Our method for learning probabilities from a given corpus of number of ‘C’ terminal symbols is 16 per equation. expressions is designed on the assumption that the probability 3.3 The Learned Probabilities of a production rule in the grammar is proportional to the inci- dence of the production in the parse trees for the expressions in By using the proposed approach on the two corpora of arithmetic the corpus. It uses a parser from the NLTK (Natural Language expressions described above, we obtain two sets of probabilities, Toolkit) Python library [1] to parse the expressions in the given with each probability assigned to one of the production rules in corpus using the universal PCFG. NLTK contains classes to work the PCFG. More precisely, we now have three universal PCFGs: (1) with PCFGs and there are different types of parsers implemented with the initial probabilities, manually assigned by the authors in the NLTK Python library. In particular, we use the InsideChart- of ProGED, (2) with probabilities fine-tuned (learned) on the Parser(), a bottom-up parser for PCFG grammars that tries edges Feynman dataset, and (3) with probabilities fine-tuned (learned) in descending order of the inside probabilities of their trees. The on the Wikipedia corpus of arithmetical expressions. "inside probability" of a tree is simply the probability of the entire In this section, we first present the three sets of probabilities, tree, ignoring its context. In particular, the inside probability of a for each of the above mentioned PCFs: these are given in Table 1. tree generated by production We then compare the probability distributions across the rules 𝑝 with children 𝑐 [1], 𝑐 [2], ..., 𝑐 [𝑛] is for each non-terminal symbol (𝑆,𝐹 ,𝑇 and 𝑅) in the PCFGs. 𝑃 (𝑝 )𝑃 (𝑐 [1])𝑃 (𝑐 [2])...𝑃 (𝑐 [𝑛]); and the inside probability of a token is 1 if it is present in the text, and 0 if it is absent. For a As compared to the initial grammar, the grammar learned on given string (expression) and a grammar, the parser determines the Feynman database reduces the probabilities of the recursive whether the string can be derived using the grammar and if yes, production rules (𝑆 → 𝑆 + 𝐹 and 𝑆 → 𝑆 − 𝐹 ) and increases returns the appropriate parse tree. After parsing the equations the probability of the non-recursive rule (𝑆 → 𝐹 ): This leads to we count the number of times each production rule appears in simpler expressions with fewer additive terms. In contrast, the the set of parsing trees, for all parsed equations (except for rules grammar learned on the Wikipedia corpus has a probability for directly resulting in terminal symbols (variables)). We then group the rule 𝑆 → 𝑆 + 𝐹 very comparable with the probability in the production rules by left non-terminal symbol and derive the prob- initial grammar. It also decreases the probability of the recursive abilities for each production rule as the number of appearances production rule 𝑆 → 𝑆 − 𝐹 and increases the probability of the of a given production rule divided by the sum of such numbers non-recursive rule 𝑆 → 𝐹 by approximately 0.1 in each case. for all production rules for the same non-terminal. The probabilities of the recursive production rules for the 𝐹 non-terminal symbol (𝐹 → 𝐹 ∗ 𝑇 and 𝐹 → 𝐹 /𝑇 ) are mostly larger than the ones in the initial grammar. An exception is the rule 𝐹 → 𝐹 /𝑇 with the Wikipedia corpus. The probability of the 3.2 The Corpora non-recursive production rule (𝐹 → 𝑇 ) is smaller, slightly for the We apply the proposed approach to two corpora of expressions Wikipedia corpus, more substantially for the Feynman dataset. (that appear on the right hand side of equations). The first one is In the learned probability distributions over the production the Feynman Symbolic Regression Database, which includes a rules for the non-terminal 𝑇 , the probability of the rule 𝑇 → 𝑉 diverse sample of equations from the three-volume set of physics is much higher (goes from 0.4 to 0.7). In both learned grammars, textbooks by Richard P. Feynman [7] and has been previously the probabilities of the 𝑇 → 𝑅 and 𝑇 → ‘𝐶’ production rules used as a benchmark for equation discovery [14]. It was con- are substantially reduced. This is more noticeable for 𝑇 → ‘𝐶’, structed by Udrescu and Tegmark [3] to facilitate the develop- where the probability goes from 0.4 to slightly above 0.1. ment and testing of algorithms for symbolic regression. The We finally discuss the probability distributions over the pro- equations from Feynman database contain between one and nine duction rules for the non-terminal symbol 𝑅 in the initial gram- variables, the four basic operations (+, −, /, ∗), the functions exp, mar and the two learned grammars. A probability with value 0 for √ , sin, cos, tanh, arcsin and ln, as well as a variety of constants a production rule here means that that function for the particular – mostly rational, but also 𝑒 and 𝜋 . There are three components production rule is not present either in the Feynman corpus or the to an arithmetic expression: variables, constants and operators. Wikipedia corpus of mathematical expressions. For example, the Numerical values and constants are typically treated as free pa- functions 𝑙𝑛 and 𝑎𝑟𝑐𝑠𝑖𝑛 are not present in the arithmetical expres- rameters (terminal symbols) to be optimized when evaluating an sions from the Wikipedia dataset, but are present in the Feynman equation for its fit against given data. We replaced all constants, database. On the other hand, the functions 𝑙𝑜𝑔, 𝑝𝑜𝑤 , 𝐴𝑏𝑠, 𝑠𝑖𝑛ℎ, such as 𝑒, 𝜋 and rational constants with the terminal ‘C’(const), 𝑐𝑜𝑠ℎ, 𝑓 𝑎𝑐𝑡𝑜𝑟 𝑖𝑎𝑙 and 𝑡𝑎𝑛 do not exist in the arithmetic expressions because we treat them as free parameters. The minimum number from the Feynman database, that’s why their probability is 0. of constants (‘C’), in the Feynman database is 0, which means that The grammar learned on the Feynman database increases the there are a some equations that have only variables as terminal probabilities of the production rules 𝑅 → (𝑆), 𝑅 → 𝑠𝑖𝑛(𝑆) and symbols. On the other hand the maximum number of constants 𝑅 → 𝑠𝑞𝑟 𝑡 (𝑆 ) as compared to the probabilities of the initial gram- in the Feynman database is five constants in only one equation. mar. In contrast, the probabilities of the remaining production 13 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Chaushevska, Todorovski, Brence, and Džeroski Table 1: Probabilities of the production rules for the non- is expressive enough to encode these properties and that the terminal symbols in the initial grammar, the grammar learning algorithm is able to discover them. The results show a trained on the Feynman database and the grammar trained great deal of promise for the goals of inferring domain knowledge on the Wikipedia corpus of expressions. from equation corpora and improving the efficiency of grammar- based equation discovery through the fine-tuning of production Production rule Initial Feynman Wikipedia probabilities. As further work we would like to perform equation discovery S -> S + F 0.2 0.1034 0.2004 experiments using the three universal grammars: the universal S -> S - F 0.2 0.1552 0.1108 grammar with initial (default) probabilities, with probabilities S -> F 0.6 0.7414 0.6888 learned on the Feynman dataset and probabilities learned on the F -> F * T 0.2 0.3635 0.3349 Wikipedia corpus. For this purpose, we will use the equation F -> F / T 0.2 0.2446 0.1098 discovery system ProGED, which uses a Monte-Carlo approach F -> T 0.6 0.3919 0.5553 of sampling equation structures from a given PCFG and evalu- ating their fit to the given data. We expect that the number of T -> R 0.2 0.1554 0.1746 successfully reconstructed equations from the Feynman dataset, T -> ‘C’ 0.4 0.1338 0.1174 when using the learned (fine-tuned) universal PCFGs, will be T -> V 0.4 0.7108 0.7082 higher as the number of equations successfully reconstructed R →( S ) 0.3 0.5391 0.6841 with the universal grammar with manually set probabilities. R → sin( S ) 0.1 0.113 0.0249 R → arcsin ( S ) 0.1 0.0173 0 REFERENCES R → ln ( S ) 0.1 0.0087 0 [1] Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural Language Pro- R → tanh ( S ) 0.1 0.0087 0.0045 cessing with Python. (1st ed.). O’Reilly Media, Inc. [2] Jure Brence, Ljupčo Todorovski, and Sašo Džeroski. 2021. Probabilistic gram- R → cos ( S ) 0.1 0.0956 0.0435 mars for equation discovery. Knowledge-Based Systems, 224, (Apr. 2021), 1– R → sqrt ( S ) 0.1 0.1304 0.0831 12. R → exp ( S ) 0.1 0.0872 0.0780 [3] Will Bridewell and Pat Langley. 2010. Two kinds of knowledge in scientific discovery. Topics in Cognitive Science, 21, 36–52. R → log( S ) 0 0 0.0479 [4] Will Bridewell, Pat Langley, Ljupčo Todorovski, and Sašo Džeroski. 2008. R → Abs( S ) 0 0 0.0211 Inductive process modeling. Machine Learning, 71, 1, 1–32. R → ( S ) ‘**’ ( S ) 0 0 0.0032 [5] Sašo Džeroski, Pat Langley, and Ljupco Todorovski. 2007. Computational Discovery of Scientific Knowledge. Vol. 4660. (Aug. 2007), 1–14. R → sinh( S ) 0 0 0.0032 [6] Brian C. Falkenhainer and Ryszard S. Michalski. 1990. Integrating quanti- R → cosh( S ) 0 0 0.0026 tative and qualitative discovery: the abacus system. In Machine Learning. Yves Kodratoff and Ryszard S. Michalski, editors. Morgan Kaufmann, San R → factorial( S ) 0 0 0.0019 Francisco (CA), 153–190. R → tan( S ) 0 0 0.0019 [7] R.P. Feynman, R.B. Leighton, and M. Sands. 2015. The Feynman Lectures on Physics, Vol. I: The New Millennium Edition: Mainly Mechanics, Radiation, and Heat. Basic Books. [8] Aaron Meurer et al. 2017. Sympy: symbolic computing in python. PeerJ rules learned on the Feynman database have lower probabilities Computer Science, 3, (Jan. 2017), e103. as compared to the initial grammar. The grammar learned on [9] Alan P. Parkes. 2008. A Concise Introduction to Languages and Machines. (1st ed.). Springer Publishing Company, Incorporated. the Wikipedia corpus increases the probability of the 𝑅 → (𝑆) [10] Cullen Schaffer. 1993. Bivariate scientific function finding in a sampled, production rule and decreases the probabilities of the remaining real-data testbed. In Machine Learning, 167–183. rules as compared to the initial grammar. [11] Michael Schmidt and Hod Lipson. 2009. Distilling free-form natural laws from experimental data. Science, 324, 5923, 81–85. [12] Jovan Tanevski, Ljupčo Todorovski, and Sašo Džeroski. 2020. Combinatorial 4 CONCLUSIONS AND FURTHER WORK search for selecting the structure of models of dynamical systems with equation discovery. Engineering Applications of Artificial Intelligence, 89, In this paper, we have proposed an approach to learn the param- (Mar. 2020), 103423. eters, i.e., production rule probabilities, in probabilistic context- [13] Ljupčo Todorovski and Sašo Dzeroski. 1997. Declarative bias in equation dis- covery. In Proceedings of the Fourteenth International Conference on Machine free grammars for arithmetic expressions. We demonstrated the Learning (ICML ’97). Morgan Kaufmann Publishers Inc., San Francisco, CA, proposed approach by learning the probabilities in a universal USA, 376–384. grammar for arithmetic expressions from two corpora of expres- [14] Silviu-Marian Udrescu and Max Tegmark. 2020. Ai feynman: a physics- inspired method for symbolic regression. Science Advances, 6, 16, eaay2631. sions. The learned probabilities differ substantially from their [15] R. Zembowitz and J Zytkow. 1992. Discovery of equations: experimental initial values. Most notably, the initial settings underestimated evaluation of convergence. In Proceedings of Tenth National Conference on Artificial Intelligence. Morgan Kaufmann Publishers Inc., San Mateo, CA, the frequency of variables in favor of numerical constants, over- USA, 101–117. estimated the need for recursion with addition and subtraction, while setting the probability of recursion with multiplication too low. These observations show how difficult it is to set probabili- ties manually and highlight the utility of the learning algorithm. The comparison of the learned probability values for the two corpora also hints towards differing properties of the two col- lections of equations. The Wikipedia corpus seems to favor mul- tiplication over division to a greater extent than the Feynman dataset. In terms of expression complexity, we observed a pref- erence for high-order terms in the Feynman dataset, in contrast to a preference for higher numbers of low-order terms in the Wikipedia corpus. The observed differences between the proper- ties of the two corpora demonstrate that the universal grammar 14 Prediction of the Inflow in Macedonian Hydropower Plants, Using Machine Learning Emilija Kizhevska Hristijan Gjoreski Mitja Luštrek emilija.kizhevska@ijs.si hristijang@feit.ukim.edu.mk mitja.lustrek@ijs.si Jožef Stefan Institute Ss. Cyril and Methodius University Jožef Stefan Institute Jožef Stefan International Faculty of Electrical Engineering Jožef Stefan International Postgraduate School and Information Technologies Postgraduate School Jamova cesta 39 Rugjer Boskovic 18 Jamova cesta 39 Ljubljana, Slovenia Skopje, R.N.Macedonia Ljubljana, Slovenia ABSTRACT more electrical devices and less and less non-renewable electric- As weather conditions become more complex and unpredictable ity sources. One of the solutions is to optimize electricity losses as a consequence of global warming and air pollution, humans due to erroneous power consumption forecasts. First, from the find it increasingly difficult to predict the amount of precipitation standpoint of world non-renewable electricity savings consump- in the coming period, thus predicting the inflow into hydroelec- tion, as the coal or oil are, and then from the standpoint of public tric basins. Different types of hydropower plants (HPP), soil com- spending, because the later you purchase electricity, the more position, how dry the soil is at the moment, the composition of expensive it becomes. [3][5]. precipitation, etc., also influence the inflow, making it even more Hydropower now provides around 6.5% of the world’s elec- difficult to be predicted. This research looks into the problem of tricity needs. In Republic of North Macedonia the total installed predicting inflow in hydroelectric basins in Republic of North capacity of hydropower is 556.8 MW, which is over 40% of the Macedonia and building machine learning models to do so. The total capacity, ranking first among renewable energy sources. main contribution of this research is the models for the largest Hydroelectricity is used the most to meet daily variations in five hydropower plants in Republic of North Macedonia (RM) electricity consumption and to provide system services for regu- that could optimize the loss and shortage of purchased electricity. lation, allowing the power system to be more flexible and reliable. Historical data from the closest meteorological station to each The peaks of electricity consumption are always regulated (i.e. hydropower plant that we were working on, as well as historical supplemented) by hydroelectric energy while coal-fired power data from the inflows at the hydropower plants, were used to plants produce the majority of electricity. Predicting the quantity build regression models that predict the inflow one day in ad- of electricity available from each hydropower plant in the future vance for each hydropower plant separately. After deriving 19 (the longer the period, the better) leads not only to the most effi- new features, of which the majority are statistical, the predic- cient use of finances, but also to protection from natural disasters tive models’ error was reduced. In the final step, we analyze the such as river and lake overflows. The amount of inflow in the results empirically and qualitatively and comparing the models foreseeable time to be predicted by humans becomes increasingly generated using different machine learning algorithms. For in- difficult, if not impossible, as meteorological conditions become stance, one of the best models is the model for HPP Vrben, with more complex and unpredictable as a result of global warming the mean absolute error of around 8% of the average daily inflow. and air pollution [4][1][9]. We built models using eight different regression algorithms for The inflow prediction in hydropower plants is mainly based each hydropower plant, including linear regression and gradient on human judgement, however, it is not always accurate. Primar- boosting regression models as the models that make the smallest ily, because it is about nature. There are two major issues with errors in predicting. These models could also help to prevent predicting future inflow accurately: river and lake overflows in areas where hydropower facilities are (1) Weather forecasting inaccuracy in the coming days. The located, with timely warnings minimizing the severity of natural issue is that the forecasting models get less accurate as disasters. the forecast gets further out in time [6]. (2) Different types of hydropower plants, especially the con- KEYWORDS struction of pumped-storage hydropower plants, the com- machine learning, regression models, hydropower plants, opti- plexity of geology, etc. In this research, we consider run- mization of hydroelectric energy loss of-river and storage hydropower plants. Run-of-river hy- dropower plant includes a facility that channels flowing water from a river through a canal or pen-stock to spin 1 INTRODUCTION a turbine, and rain influences the inflow almost immedi- The global trend for producing electricity from renewable sources ately. Storage hydropower plants that include a dam and is increasing at an exponential rate. On the other hand, the world a reservoir to accumulate water, which is stored and re- aims to reduce world’s electricity losses, as there are more and leased later when needed, providing flexibility to generate electricity on demand and reducing dependence on the Permission to make digital or hard copies of part or all of this work for personal variability of inflow. But whatever the hydropower plant 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 type, the inflow is not directly related to weather condi- the full citation on the first page. Copyrights for third-party components of this tions. For instance, the snow and hail do not accumulate work must be honored. For all other uses, contact the owner/author(s). straight away; it does require a time of melting, soil wet- Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia ting, and for storage plants, additionally, conducting the © 2022 Copyright held by the owner/author(s). water through the pipes to reach the basin, etc. [7]. 15 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia E.Kizhevska, et al. The inflow into hydroelectric basins can be predicted more the details that affect it, 19 new features were created from the easily when using machine learning than by analyzing geology, original two. The ’date’ feature was divided into three new fea- satellite monitoring, pollution monitoring, and changes in global tures: day, month, and year, and they were added to the original warming. Developing a machine learning model that connects features. Regarding the amount of precipitation and inflows into all of these features, allows the prediction to be made. Otherwise, the hydroelectric basins, the derived features are the average, it is quite difficult to perform it empirically, owing to a lack of variance, p-variance, minimum and maximum values from the resources for repeating the method for each existing hydroelectric previous five days, and values from the previous day of both plant. In this study, we built models using collected data from original features are also added as new features. Also, additional hydropower plants and the nearest meteorological stations with features are derived as sine and cosine functions of the days and the aim of developing an application that would help to monitor months. The purpose of the trigonometric functions is to reduce the daily inflow one day in advance (Figure 1)[2]. the difference between December 31 and January 1, for instance. Random Forest features ranking demonstrate that the features derived from the latest five days of both original features have the highest score. If we consider the correlation matrix, we can realize the same. The derived statistical features have the high- est correlations with the inflow. Also it is interesting that while trigonometrically generated date features have the same corre- lation as the features from which they were derived, in terms of inflow, they do not correlate to each other with a degree of correlation of 1. For instance, HPP Vrben’s sine function of the month, as well as the month itself (from which the sine function is derived), get a correlation index of -0.01 with the inflow, but a value of -0.04 with each other (Figure 2). Figure 1: Graphical representation of the process: predict- ing inflow in the hydroelectric basins 2 METODOLOGY 2.1 Preprocessing The daily inflow into the hydroelectric basins as labels and the amount of precipitation observed at the nearest meteorological station as descriptive features are merged by date. Then, because missing values represent less than 1% of the total data, they are filled using the average of each feature’s values. For most hydropower facilities, we could find only two de- scriptive features at first: the daily amount of precipitation [l] and the date. There were 11 additional available features in the data for HPP Tikvesh: time of moonrise and moonset (times- tamp), intensity of precipitation [ 2 𝑙 /𝑚 ] , duration of precipitation [min], time of sunrise and sunset (timestamp), the highest and lowest temperature of the day [K], absolute humidity [ 3 𝑔/𝑚 ] , cloud cover [oktas]. For HPP Tikvesh, missing values in the ad- ditional features are filled in with the average of the instances that have the same value in the most meteorologically related feature. For instance, ’humidity’ and ’cloud cover’. The procedure is as follows: for a missing value in the feature ’cloud cover,’ the corresponding value of ’air humidity’ is X; find all the values Figure 2: Correlation matrix after scaling for HPP Vrben from the feature ’cloud cover’ that have the value X in the feature ’air humidity’, calculate their average value and substitute for the missing value in the ’cloud cover’ feature. In conjunction with the ’maximum temperature’ feature, the same procedure is 3 EXPERIMENTS AND RESULTS used to replace missing values in the ’lowest temperature’ feature. Scaling the values in the descriptive features between 0 and 1 3.1 Dataset Description was the final step in the prepossessing process. For each of the five hydropower plants in the Republic of North Macedonia that have been analyzed, the data processing and 2.2 Feature Engineering approach to the problem are the same. HPP Kozjak, HES Mavrovo Using only the date and amount of precipitation as descriptive power plants (consisting of HPP Vrutok and HPP Vrben), HPP features, different regression models can be developed, but all Tikvesh, and HPP Shpilje are part of this study. The datasets are of these predictive models have a low accuracy. Due to the com- time-series, they were collected at daily intervals throughout an puter’s inability to understand the inflow pattern, including all 11-year period (1/1/09 – 12/31/19) for each hydroelectric facility. 16 Prediction of the Inflow in Macedonian Hydropower Plants, Using ML Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia ESM1 and UHMR2 have collected the initial two variables, the SelectKBest, which selects the best features based on univariate amount of precipitation [ 2 𝑙 /𝑚 ] and inflows into the hydropower statistical tests and the best numbers of features for each HPP basin (Figure 3). The inflow is expressed as the maximum amount were chosen based on the predictive models’ errors. The experi- of electricity [MWh] it could be used to produce. ment was divided into four parts: using all features, the best 15 features, the best 10 features, and the best 5 features, out of a total of 20 features. Time-series can be troublesome for splits where with the shuf- fling process we get different train and test sets across different executions, for cross-validation, or when the test subset is be- fore or somewhere in the middle of the train subset, etc. For instance, if a pattern appears in year 3 and persists for years 4-6, the model can detect it, even though it was not present in years 1 and 2. Because the datasets we use in this research are continuous time-series at the daily level, we split the evaluation datasets contentiously, without shuffling the subsets [8]. 3.3 Results For each of the four parts of the experiment for selecting the best n features, we calculated and plotted the mean absolute error [MWh] for each model (Figure 4, Figure 5). As we can see in Figure 4 and Figure 5, the differences in the errors are similar regardless of how many features the model is trained with. The best results are provided by different models developed using various algorithms and various number of features for each hydropower plant, but one thing that all of them have in common Figure 3: Top to bottom: (a) Amount of precipitation (me- is that dummy regressor is the worst, while linear regression or teorological station Debar) and (b) amount of electricity gradient boosting produce the smallest errors. For example, if production (HPP Shpilje) during an 11-year period (2009 - we choose HPP Vrben as one of the best outcomes, we can see 2019) that while the average daily input is 3.7 MWh, the error of the model developed using linear regression and selected 15 features Equation 1 describes how to calculate the electricity that could is 0.34 [MWh]. Because the errors, with the exception of dummy be produced by hydropower plants, knowing that it is a product and lasso, are not particularly big, ranging between [0.345, 0.40], of power and working time [4]. all of the features listed after the five most influential features contribute a negligible percentage to improving or decreasing accuracy (Figure 5). 𝐸 = 𝜌𝑄𝑔𝐻 𝑡 [𝑊 ℎ] (1) where, electricity is equal to water density 3 𝜌 [1000𝑘𝑔/𝑚 ], multiplied by water flow (inflow) Q [ 3 𝑚 /𝑠], acceleration of grav- ity g [ 2 𝑚/𝑠 ] and gross height drop H [m]. Inflow refers to water flowing into accumulation basins of hydropower plants. The in- flow is measured in cubic meters per second [ 3 𝑚 /𝑠], but it can also be expressed as the quantity of electricity that the same amount of inflow could supply. When electricity is a projection of the inflow, the inflow is computed using Equation 1 and ex- pressed in watt-hours [Wh]. 3.2 Experimental Setup To build models for one day in advance inflow prediction, we used eight different regression algorithms: Support Vector Machine, Figure 4: Graphical representation of the mean absolute Random Forest, Linear Regression, Lasso, Gradient Boosting, Ex- error of the eight machine learning regressors used in the treme Gradient Boosting, K-nearest neighbours, Decision Tree study, selecting different numbers of best features for HPP and Dummy that always predicts the mean of the training tar- Vrben as a run-of-river diversion hydropower plant get values. Four evaluation metrics were used to evaluate the regression models for the prediction of inflow in hydropower plants: mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and R-Squared (R2) as a stan- 4 CONCLUSIONS dardized version of MSE. Using eight different machine learning regressors, we built mod- Different numbers of selected features for each hydropower els for predicting inflow in Macedonian hydroelectric basins. A plant were considered using a class from sklearn library called solution for predicting the daily inflow in hydropower plants has been proposed if the daily amount of precipitation and the 1ESM - Elektrani na Severna Makedonija (litt. "Power plants of North Macedonia") 2UHMR - Uprava za Hidro-Meteoroloski raboti (National Hydrometeorological amount of precipitation for the previous five days for the nearest Service - Republic of North Macedonia) meteorological stations are known. 17 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia E.Kizhevska, et al. temperature, soil moisture, and therefore the amount of inflow into the hydropower plant are significant for storage hydropower plants because it raises the river level, and thus the amount of inflow into the hydroelectric basins, but not immediately. Because of the differences in the location, construction, and operation of hydropower plants, we can only build hydropower plant specific models. For some, the daily quantity of precipitation or the amount of precipitation from the previous day is the most essential factor, while for others, the amount of precipitation over a longer period is the most important factor. Based on this fact, which is also supported by our results for various hydropower facilities, we may conclude that we cannot build general model that can estimate the inflow for all hydropower plants. Because of the geological properties of the soil along the rivers and the temperature fluctuations in the past, we also cannot create a general model for hydropower plants of the same type. Linear regression and gradient boosting models produce the best results. We can solve the inflow problem as a linear problem, because the relations between precipitation and inflow to the basins are simple. The precision of projected weather conditions is the key drawback for obtaining even lower errors. The more accurate the weather conditions are and the longer the time pe- riod of projected weather conditions is, the better the prediction of inflow in hydroelectric basins would be. We built predictive models for the next day’s inflow in this study. The next step is to create predictive models for as far in the future as possible, so that the model can assist in power man- agement decisions. However, accurate projected meteorological conditions are required to develop such a model, and the further the time point, the greater the error. Hourly or minute time-series would predict more precisely in terms of time intervals. REFERENCES [1] Arsenov A. 2003. Proizvodstvo na elektricna energija. (1st. edi- Figure 5: Top to bottom: Graphical representation of the tion). ETF, Skopje. mean absolute error of the eight machine learning regres- [2] A. P. Verma A. Kusiak X. Wei and E. Roz. 2013. Modeling sors used in the study, selecting different numbers of best and prediction of rainfall using radar reflectivity data: a features for: HPP Shpilje, HPP Tikvesh, HPP Kozjak as data-mining approach. IEEE Transactions on Geoscience and storage hydropower plants Remote Sensing, 2337–2342. [3] Jianzhou Niu Tong Du Pei. ang Wendong Wang. 2019. A hybrid forecasting system based on a dual decomposition strategy and multi-objective optimization for electricity According to the results, the daily amount of precipitation price forecasting. Applied Energy, 1205–1225. and other inflow-related elements from the preceding days are [4] Djordjevic B. [n. d.] Koriscenje vodnih snaga: Objekti hidroelek- the most important factors that explain inflows in hydroelectric trana. (1st. edition). Naucna knjiga, Beograd. basins. Of course, there are other variables to consider, such [5] Yazidi A. Goodwin M. 2014. A pattern recognition approach as temperature, cloud cover or humidity. Considering that the for peak prediction of electrical consumption. IFIP Advances errors in prediction for HPP Tikvesh are not much smaller than in Information and Communication Technology, Springer. the ones for the other HPPs where we have only the precipitation [6] S. Makridakis. 2013. Accuracy measures: theoretical and and inflow as original data and of course, the most important practical concerns. International Journal of Forecasting, 9 part - the derived features about last days, we may conclude that (4), 1, 527–529. precipitation takes a certain amount of time to reach the basins [7] Joshua S. and Coblenz. 2015. Using machine learning tech- as an inflow, depending on daily temperatures, the nature of the niques to improve precipitation forecasting. PLoS One. soil where the hydropower plant is located, and other factors. [8] D. Fernando S. De Silva S. Perera S. Dissanayake and W. Also, we can confirm hydrological and geological assump- Rankothge. 2019. Supply and demand planning of electric- tions that continuity in the data is far more important in storage ity power: a comprehensive solution. IEEE Conference on hydropower plants than in run-of-river diversion hydropower Information and Communication Technology. plants. For the first type of data, weather characteristics from [9] Stoilkov V. 2015. Predavanja po predmetot Osnovi na ob- previous days have no significant impact, but all original and novlivi izvori na energija. (2nd. edition). FEEIT, Skopje. derived attributes related to inflows and precipitation for the same day are crucial, because the rains are accumulated immedi- ately. Otherwise, factors such as the period for melting the snow, 18 Peak Detection for Classification of Number of Axles Žiga Kolar Blaž Erzar Nika Čelan Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ziga.kolar@ijs.si blaz.erzar@gmail.com nika.celan8@gmail.com Aleksander Hrastič Gašper Leskovec Martin Konečnik Jožef Stefan Institute Jožef Stefan Institute Cestel Cestni Inženiring d.o.o Jamova cesta 39 Jamova cesta 39 Špruha 32 Ljubljana, Slovenia Ljubljana, Slovenia Trzin, Slovenia ah3001@student.uni-lj.si leskovecg@gmail.com martin.konecnik@cestel.si Domen Prestor David Susič Matjaž Skobir Cestel Cestni Inženiring d.o.o Jožef Stefan Institute Cestel Cestni Inženiring d.o.o Špruha 32 Jamova cesta 39 Špruha 32 Trzin, Slovenia Ljubljana, Slovenia Trzin, Slovenia domen.prestor@cestel.si david.susic@ijs.si matjaz.skobir@cestel.si Matjaž Gams Jožef Stefan Institute Jamova cesta 39 Ljubljana, Slovenia matjaz.gams@ijs.si ABSTRACT spectrometry [4], signal processing [7, 8], image processing [10], A common requirement in scientific data processing is to detect astrophysics [13] – require peak detection. peaks in a signal and to measure their positions, heights, widths, Peak detection algorithms are also used for classification of and/or areas. In this paper, the problem of peak detection from a the number of peaks or axles. For example, when a vehicle places raw signal is defined and presented. Providing the example, we one of its tyres on a weight sensor, a peak is detected in the signal. showed how the problem of peak detection can be translated into Each peak represents one vehicle axle. Therefore, the algorithm detecting the number of axles in vehicles. Various algorithms detecting how many peaks occur in a given signal in this way for predicting the number of peaks (axles) were presented. So- detects the number of axes. For the purpose of this study, 16 lution with derivatives, the solution with encoder and decoder different signals for two driving lanes were provided by company and the solution with convolution neural network produced the Cestel. Sensors were placed under a bridge near Obrežje. Sensors 1 best result, 99% accuracy with a certain percentage of skipped and 2 were placed at the beginning and end of measuring area for instances. lane 1. Sensors 15 and 16 were placed on lane 2 in a similar fashion. The rest were placed perpendicular on the road between the pairs. KEYWORDS The main goal of this paper is to predict the number of axles as accurately as possible with the use of mathematical models and peak detection, neural networks, machine learning, signal, sen- machine learning algorithms given signals. We introduce the sors, number of axles solution using deep neural networks (artificial neural network 1 INTRODUCTION and convolution neural network), regular derivatives, predefined library find_peaks and a package 𝑡𝑠 𝑓 𝑟𝑒𝑠ℎ for peak detection. In Identifying and analyzing peaks in a given time-series is impor- theory, peak detection is formally a trivial task, however, in reality tant in many applications, because peaks are useful topologi- the task can be performed only with some degree of accuracy. cal features of a time-series. In power distribution data, peaks The rest of the paper is organized as follows. Section 2 presents indicate sudden high demands. In server CPU utilization data, related work. Main methodology and algorithms are described in peaks indicate sharp increase in workload. In network data, peaks section 3. Finally, section 4 concludes the paper with summary correspond to bursts in traffic. In financial data, peaks indicate and ideas for future work. abrupt rise in price or volume. Troughs can be considered as inverted peaks and are equally important in many applications. Many other application areas – e.g., bioinformatics [2], mass 2 RELATED WORK Permission to make digital or hard copies of part or all of this work for personal Peak detection is a common task in time-series analysis and sig- 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 nal processing. Standard approaches to peak detection include (i) the full citation on the first page. Copyrights for third-party components of this using smoothing and then fitting a known function (e.g., a poly- work must be honored. For all other uses, contact the owner/author(s). nomial) to the time-series; and (ii) matching a known peak shape Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia to the time-series. Another common approach to peak-trough © 2022 Copyright held by the owner/author(s). detection is to detect zero-crossings (i.e., local maxima) in the 19 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Žiga Kolar, et al. differences (slope sign change) between a point and its neigh- the first signal had less noise than other signals. Each signal has bours. However, this detects all peaks-troughs, whether strong different length. Therefore, the signals that had length less that or not. To reduce the effects of noise, it is required that the local maximum time had to be extended to maximum signal time in signal-to-noise ratio (SNR) should be over a certain threshold [8, order to create features with the same length. To achieve this, 11]. The key question now is how to set the correct threshold so additional zeros were filled to the positions up to the maximum as to minimize false positives. Ma, van Genderen and Beukelman signal time. Maximum time is 6113, which is equal to the number et al. [10] compute the threshold automatically by adapting it to of features. Figure 1 shows a signal from Sensor 1 which has 𝑚𝑎𝑥 +𝑎𝑏𝑠 the noise levels in the time-series as 𝑎 𝑣𝑔 maximum sensor time. ℎ = + , 2 𝐾 ∗ 𝑎𝑏𝑠𝑑𝑒 𝑣 where Each method uses classification accuracy for evaluation of the 𝑚𝑎𝑥 is the maximum value in the time-series, 𝑎𝑏𝑠 is 𝑎 𝑣𝑔 the average of the absolute values in the time-series, model. Classification accuracy is a metric that summarizes the 𝑎𝑏𝑠 is 𝑑 𝑒 𝑣 the mean absolute deviation and K is a user-specified constant. performance of a classification model as the number of correct Azzini et al. [2] analyze peaks in gene expression microarray predictions divided by the total number of predictions. In this time-series data (for malaria parasite Plasmodium falciparum) us- study, correct predictions are correctly predicted peaks(number ing multiple methods; each method assigns a score to every point of axles). in the time-series. In one method, the score is the rate of change (i.e., the derivative) computed at each point. In another method, the score is computed as the fraction of the area under the candi- date peak. Top 10 candidate peaks are selected for each method; peaks detected by multiple methods are chosen as true peaks. The detected peaks are used to identify genes; SVM are then used to assign a functional group to each identified gene. Key problems in peak detection are noise in the data and the fact that peaks occur with different amplitudes (strong and weak peaks) and at different scales, which result in a large number of false positives among detected peaks. Based on the observation that peaks in mass spectroscopy data have characteristic shapes, Du, Kibbe and Lin et al. [5] propose a continuous wavelet transform (CWT) based pattern-matching algorithm for peak detection. 2D array of CWT coefficients is computed (using a Mexican Hat mother wavelet which has the basic shape like a peak) for the time-series at multiple scales and ridges in this wavelet space representation are systematically examined to identify peaks. Coombes et al. [4] Figure 1: Signal with maximum sensor time. and Lange et al. [9] present other approaches for peak detection using wavelets and their applications to analyze spectroscopy data. Zhu and Shasha et al. [13] propose a wavelet-based burst 3.1 Peak Detection with Derivatives (not peak) detection algorithm. The wavelet coefficients (as well Since peaks are local maxima, we can use mathematical methods as window statistics such as averages) for Haar wavelets are for finding them. But because we are not working with functions organized in a special data structure called the shifted wavelet but rather noisy discrete signals, we need to modify them slightly. tree (SWT). Each level in the tree corresponds to a resolution Let us define th 𝑠 as 𝑖 signal value. First we remove noise at the or time scale and each node corresponds to a window. By auto- 𝑖 beginning and the end of the signal where there are no axes. To matically scanning windows of different sizes and different time do so we find the horizontal line with maximum support, where resolutions, the bursts can be elastically detected (appropriate support for line at height 𝑦 is defined as the number of signal window size is automatically decided). Zhu and Shasha et al. [13] values 𝑠 for which |𝑦 − 𝑠 | < 𝑚𝑎𝑟𝑔𝑖𝑛. For line height 𝑦 we take apply their technique to detecting Gamma Ray bursts in real- 𝑖 𝑖 𝑛 equally spaced values from interval [𝑚𝑖𝑛, 𝑚𝑎𝑥 ] and half the time in the Milagro astronomical telescope, which vary widely distance between consecutive 𝑦 values is used as 𝑚𝑎𝑟𝑔𝑖𝑛. Here in their strength and duration (from minutes to days). Harmer 𝑚𝑖𝑛 and 𝑚𝑎𝑥 represent minimum and maximum value of the et al. [7] propose a momentum-based algorithm to detect peaks. signal. To remove noise and normalize signal, we now define: The idea is compute velocity (i.e., rate of change) and momentum (i.e., product of value and velocity) at various points. A “ball” (0, if 𝑠 < 𝑦 + 2 ∗ 𝑚𝑎𝑟𝑔𝑖𝑛. 𝑖 dropped from a previously detected peak will gain momentum ˆ𝑠 = 𝑖 𝑠 −𝑚𝑖𝑛 𝑖 , otherwise. as it climbs down and lose momentum as it climbs the next peak; 𝑚𝑎𝑥 −𝑚𝑖𝑛 the point where it comes to rest (loses all its momentum) is the On signal ˆ𝑠 we calculate first and second derivative - ¤𝑠 and ¥𝑠 - next peak. Simple analogs of the laws in Newtonian mechanics using finite difference, which is implemented using convolution are proposed (e.g., friction) to compute changes in momentum with kernels [−0.5, 0, 0.5] and [1, −2, 1]. Finally peaks can be as the ball traverses the time-series. acquired by finding indices 𝑖 for which ˆ𝑠 > 0.25, | ¤𝑠 | < 0.01 𝑖 𝑖 and |¥𝑠 | < 0 while only taking peaks which are local minima, i.e. 𝑖 𝑠 > max{𝑠 𝑖 𝑖 −1, 𝑠𝑖 +1 }. 3 METHODOLOGY This procedure achieves accuracy ≈ 90% when using sensor In this section, algorithms for peak detection are described. Each 1. When using other sensors, accuracy is lower, but it can be machine learning method uses 62076 samples (vehicles) and up improved by choosing the correct sensor for every instance. We to 16 signals for classification of number of axles. Typically, only do this by training nine models: one regression model 𝑀 for 𝑎 the first signal was chosen for training the model. This is because predicting number of axes and eight models 𝑀 , 𝑘 = 1..8, for 𝑘 20 Peak Detection for Classification of Number of Axles Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia predicting whether prediction on sensor 𝑘 is correct. We only filters and sizes reversed and max pooling layers replaced with use sensors from lane 1, since sensors on the other lane give poor up sampling. This model is then trained using Adam optimizer accuracy. and binary cross entropy loss function. First we define (𝑖 ) 𝑝 as correct number of peaks for instance After model is trained, peaks on new instance can be detected (𝑖 ) by feeding sensor 1 signal 𝑠 to it to obtain prediction vector 𝑝. 𝑖 and 𝑝 as number of peaks detected by procedure described 𝑘 in this section for instance Peaks are now located at indices for which prediction value is 𝑖 using sensor 𝑘 . Now we create matrix a strong enough local maximum and signal amplitude is high 𝑋 and vector 𝑦 on which we train gradient boosting regression. This model predicts number of axes from number enough: of peaks detected on all sensors. Matrix 𝑋 contains one row 𝑝𝑒𝑎𝑘𝑠 = {𝑖 | 𝑝 ≥ max{𝑝 > 𝑇 > 0.15}, 𝑖 𝑖 −5:𝑖 +5 } ∧ ˆ 𝑝𝑖 1 ∧ ˆ 𝑠𝑖 ( ( ( ( 𝑖 ) 𝑖 ) 𝑖 ) 𝑖 ) 𝑥 = [𝑝 , 𝑝 , . . . , 𝑝 ] for each instance 𝑖 with one column 1 2 8 while skipping instances for which max{𝑝 | 𝑖 ∈ 𝑝𝑒𝑎𝑘𝑠 } < 𝑇 𝑖 2. for every sensor, while vector 𝑦 contains ground truth values for Here ˆ 𝑝 , ˆ 𝑠 are normalized to contain values in [0, 1] and 𝑇1, 𝑇2 are number of axes: thresholds that need to be selected. For 𝑇1 = 0.01 and 𝑇2 = 0.5 h (1) (2) ( h 𝑚 ) i𝑇 (1) (2) (𝑚 ) i𝑇 accuracy 99.6% is achieved with 20% skipped instances. 𝑋 = 𝑥 , 𝑥 , . . . , 𝑥 , 𝑦 = 𝑝 , 𝑝 , . . . , 𝑝 . Here 𝑚 is number of all instances. Other eight models use the 3.3 Peak Detection with Artificial Neural same matrix 𝑋 , but different vector 𝑦. Model 𝑀 which predicts 𝑘 Network whether detection using sensor 𝑘 produces correct number of Neural networks, also known as artificial neural networks (ANNs) peaks uses: or simulated neural networks (SNNs), are a subset of machine h (1) (1) (2) (2) (𝑚 ) (𝑚 ) i𝑇 learning and are at the heart of deep learning algorithms. Their 𝑦 = 𝑝 = 𝑝 , 𝑝 = 𝑝 , . . . , 𝑝 = 𝑝 , 𝑘 𝑘 𝑘 𝑘 name and structure are inspired by the human brain, mimicking where equality comparison evaluates to 1 when true and 0 when the way that biological neurons signal to one another [12]. false. Gradient boosting classifiers are used for these models. Artificial neural networks (ANNs) are comprised of a node After all nine models are trained, peaks on a new instance layers, containing an input layer, one or more hidden layers, 𝑚 + 1 can be detected by first using the described peak detection and an output layer. Each node, or artificial neuron, connects procedure on all eight sensors to obtain input vector (𝑚+1) 𝑥 : to another and has an associated weight and threshold. If the (𝑚+1) (𝑚+1) (𝑚+1) (𝑚+1) output of any individual node is above the specified threshold 𝑥 = [𝑝 , 𝑝 , . . . , 𝑝 ]. 1 2 8 value, that node is activated, sending data to the next layer of the This vector is then first fed into 𝑀 model to predict number 𝑎 network. Otherwise, no data is passed along to the next layer of of axes and the result is rounded to closest integer value to get the network [12]. 𝑎. Furthermore models 𝑀 are used to get confidence 𝑐 for 𝑘 𝑘 In this method, artificial neural network was used to predict each sensor. Now valid sensors are the ones using which correct the number of peaks. Neural networks were a viable solution for number of peaks were detected and have confidence higher than this problem, because we had enough data at our disposal for some threshold 𝑇 : deep learning. Whole signal from sensor 1 was provided as input (𝑚+1) layer. Architecture of the neural network contains two hidden 𝑠𝑒𝑛𝑠𝑜𝑟 𝑠 = {𝑘 | 1 ≤ 𝑘 ≤ 8 ∧ 𝑝 = 𝑎 ∧ 𝑐 > 𝑇 }. 𝑘 𝑘 layers, with 16 and 12 neurons, respectively. Output data (number If 𝑠𝑒𝑛𝑠𝑜𝑟𝑠 = ∅, instance 𝑚 + 1 is skipped, otherwise 𝑎 axes are of peaks) was one-hot encoded, therefore softmax activation func- predicted and min{𝑠𝑒𝑛𝑠𝑜𝑟𝑠 }is the best sensor for detection. For tion was used in the output layer. Model returned the probability 𝑇 = 0.95 this system has accuracy 99.5% while skipping 20% of for each class. In the end, an algorithm picked the column with instances. the highest probability (𝑖-th column depicts 𝑖 number of peaks). This model achieved 91% accuracy for predicting the number of 3.2 Peak Detection with Encoder/Decoder peaks. Since we know where peaks are located in every signal, we can train a model that will for every instance predict locations of 3.4 Peak Detection with Convolution Neural peaks. Because we are working with time series data, we can Network use a one dimensional convolutional neural network with au- Convolutional neural networks are distinguished from other neu- toencoder architecture. This allows us to predict locations for ral networks by their superior performance with image, speech, variable number of peaks. Inputs and outputs have the same or audio signal inputs. They have three main types of layers, dimensions, while the model consists of two parts: encoder, to which are: create low dimensional embedding in latent space, and decoder, to reconstruct output from it. • Convolutional layers which convolve the input and pass As inputs we use signals from sensor 1. On output we want its result to the next layer. This is similar to the response to predict a vector of the same dimension, which has ones in of a neuron in the visual cortex to a specific stimulus. Each time slots containing a peak and zeros everywhere else. Because convolutional neuron processes data only for its receptive CNNs take inputs of the same length, we pad all input and output field. vectors to maximum length. To make maximum length smaller, • Pooling layers which reduce the dimensions of data by we use the noise removal method from section 3.1 to crop noise combining the outputs of neuron clusters at one layer into at the beginning and at the end from the signals. a single neuron in the next layer. Encoder is made of 3 convolutional layers. Each is followed • Fully-connected layers which connect every neuron in by batch normalization and max pooling of size 2. Convolutional one layer to every neuron in another layer. layers use ReLU activation, 8, 16 and 32 filters and sizes 5, 2 and With each layer, the CNN increases in its complexity, identify- 3 respectively. Decoder has the same structure with number of ing greater portions of the required information [1]. 21 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Žiga Kolar, et al. Convolutional neural network was utilized to predict the num- (time series) [3]. After the features were extracted, they were used ber of peaks. The motivation for the usage of this type of network by gradient boost classifier for predicting the number of peaks. comes from a fact that convolutional neural networks work well This approach produced 89% accuracy predicting the number of with time series data. Whole signal from sensor 1 was used as peaks. input layer. Architecture of the network contains three 1D con- volution layers and three 1D pooling layers. At the end we used 4 CONCLUSION AND DISCUSSION the fully connected layer with 100 neurons. Output layer has We defined and presented the problem of peak detection from a a softmax activation layer. Similarly than in subsection 3.3, the raw signal. Providing the example, we showed how the problem model returned the probability for each class and in the end, algo- of peak detection can be translated into detecting the number of rithm picked the column with the highest probability. This model axles in vehicles. Various algorithms for predicting the number achieved 97% accuracy. If we decide to skip 6.5% samples that are of peaks (axles) were presented. The solution with derivative, the below the 99% probability threshold, we achieve the accuracy of solution with encoder and decoder and the solution with convo- 99.1%. lution neural network produced the best results, 99% accuracy with a certain percentage of skipped instances. In future work, 3.5 Peak Detection with Predefined Method the mentioned results can be tweaked and improved by using dif- Find_peaks ferent learning parameters, e.g. different learning rate, different Another method for peak detection is by using the predefined number of neurons, different activation function. Furthermore, function named better results can be achieved by changing the architecture of 𝑓 𝑖𝑛𝑑 _𝑝𝑒𝑎𝑘𝑠 . This function takes a 1-D array and finds all local maxima by simple comparison of neighboring val- the neural network, e.g. different or more convolution or pooling ues. In the context of this function, a peak or local maximum layers. The results of peak detection can also be extended into is defined as any sample whose two direct neighbours have a determining the axle distances. Once the axle number is accu- smaller amplitude [6]. Because each signal has different maxi- rately predicted, a new set of algorithms can be implemented to mum height, the parameter in function find_peaks named solve this new task. ℎ𝑒𝑖𝑔ℎ𝑡 differs from sample to sample. Height parameter is defined as minimal required height for peaks to be detected. Peaks below ACKNOWLEDGMENTS that threshold are not detected. Height was calculated by formula: This study received funding from company Cestel. The authors height = | |max(sensorHeight)| - |min(sensorHeight)| | / 10. The acknowledge the funding from the Slovenian Research Agency above described method achieved 89% accuracy and also returned (ARRS), Grant (PR-10495) and Basic core funding P2-0209. the position of every peak. An example can be seen on Figure 2 on which 2 peaks are detected. They are marked with 2 oranges REFERENCES crosses. [1] Saad Albawi, Tareq Abed Mohammed, and Saad Al-Zawi. 2017. Understand- ing of a convolutional neural network. 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Springer, 81–100. regression or classification tasks. 𝑡𝑠 𝑓 𝑟𝑒𝑠ℎ is used for systematic [13] Yunyue Zhu and Dennis Shasha. 2003. Efficient elastic burst detection in data feature engineering from time-series and other sequential data. streams. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, 336–345. These data have in common that they are ordered by an indepen- dent variable. The most common independent variable is time 22 Unified Question Answering in Slovene Katja Logar and Marko Robnik-Šikonja University of Ljubljana, Faculty of Computer and Information Science Ljubljana, Slovenia kl2164@student.uni- lj.si, marko.robnik@fri.uni- lj.si ABSTRACT on the multilingual mT5 model [13], using English and Slovene datasets. Finally, we perform a qualitative analysis of the obtained Question answering is one of the most challenging tasks in lan- models. The results show that our system is currently the best guage understanding. Most approaches are developed for English, performing QA system for Slovene. We make its source code while less-resourced languages are much less researched. We 1 freely accessible . adapt a successful English question-answering approach, called The paper is split into four further sections. In Section 2, we UnifiedQA, to the less-resourced Slovene language. Our adapta- outline the related work on QA in Slovene. Section 3 presents our tion uses the encoder-decoder transformer SloT5 and mT5 models adaptation of UnifiedQA methodology and the applied Slovene to handle four question-answering formats: yes/no, multiple- QA datasets, and Section 4 discusses different evaluation settings choice, abstractive, and extractive. We use existing Slovene adap- and their results. In Section 5, we present the findings and ideas tations of four datasets, and machine translate the MCTest dataset. for further improvements. We show that a general model can answer questions in different formats at least as well as specialized models. The results are fur- 2 RELATED WORK ther improved using cross-lingual transfer from English. While we produce state-of-the-art results for Slovene, the performance The QA in Slovene is relatively unexplored. In the pre-neural still lags behind English. setting, Čeh et al. [1] developed a closed-domain QA system for answering common questions that arise during students’ studies KEYWORDS at the University of Maribor, Faculty of Electrical Engineering, question answering, Slovene language, deep neural networks, Computer Science and Informatics. The translation of the Su- encoder-decoder models, natural language processing perGLUE benchmark suite to Slovene in 2021 [14] provided four partially human, partially machine translated QA datasets (BoolQ, 1 INTRODUCTION COPA, MultiRC, and ReCoRD) and evaluation of Slovene BERT models. Ulčar et al. [11] adapted the SloT5 model for the yes- Most studies for the question answering (QA) task deal with no and multiple-choice questions. Finally, Zupanič et al. [15] the English language. This leaves many language specifics, not translated the SQuAD 2.0 dataset from English and adapted dif- present in English, potentially inadequately addressed. E.g., some ferent multilingual models. They achieved the best result with problematic language specifics in morphologically-rich Slovene the SloBERTa 2.0 model [12]. In contrast to the above works, we language are noun and adverb declension, three different genders, apply the transfer learning paradigm within the encoder-decoder three counts, the person or pronoun being hidden in a verb, etc. SloT5 and mT5 models and provide a unified approach to different An additional problem for less-resourced languages is the lack of QA formats, obtaining the best results so far. suitable datasets for QA. Khashabi et al. [5] argue that building specialized models 3 METHODOLOGY for each QA dataset or QA format is unnecessary, as they all require a similar inference capability. Therefore, it is possible to Our methodology follows Khashabi et al. [5] UnifiedQA method- develop one model capable of answering questions in different ology. The authors define four QA formats (extractive, abstractive, formats. They call their approach UnifiedQA, and we adapted multiple-choice, and yes/no) and unify the learning approach to this approach to Slovene. these formats. The extractive format requires that the answer is The number of QA datasets in Slovene is much lower than directly stated in the supplied context as a substring. The abstrac- used in the original UnifiedQA. We found four partially human- tive format requires paraphrasing of the given context and the translated but mostly machine-translated datasets. To improve answer may require linking information from several sentences. that, we first machine translate the additional MCTest dataset The multiple-choice datasets have possible answers listed and [9] into Slovene and fix translation errors. the aim is to select the given option correctly. Finally, the yes/no Our method is based on the pretrained Slovene encoder-decoder questions require only yes or no as an answer. transformer model SloT5 [11]. We finetune the model on the five The datasets with different QA formats are converted to text QA datasets and analyze its performance. We also test the role format, with parts of the input separated by the "\n" sepa- of uppercase and lowercase letters, the impact of unanswerable rator. Extractive, abstractive and yes/no questions are coded questions, and the contribution of each dataset to the perfor- as "question \n context" and multiple-choice questions as mance of the unified model. Next, we test the cross-lingual trans- "question \n possible choices \n context". Here, the fer and train a multilingual question answering model based possible choices are indicated in capital letters from A onwards (A) choice 1 (B) choice 2.... Permission to make digital or hard copies of part or all of this work for personal We initially considered four QA datasets. Three stem from 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 translation of the SuperGLUE benchmark to Slovene [14]: the full citation on the first page. Copyrights for third-party components of this MultiRC [4] (abstractive), COPA [10] (multiple-choice) and BoolQ work must be honored. For all other uses, contact the owner /author(s). [2] (yes/no). We also used the SQuAD 2.0 [8] (extractive) Slovene Information Society 2022, 11–14 October 2022, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 1 https://github.com/klogar/QAslovene 23 Information Society 2022, 11–14 October 2022, Ljubljana, Slovenia Katja Logar and Marko Robnik-Šikonja translation [15]. SQuAD 2.0 contains unanswerable questions, dataset in [5]). The results are presented in Table 2. The results and some are also present in MultiRC. As we focus on the reading for BoolQ and MCTest are slightly worse than originally reported, comprehension task, all selected datasets have a context. COPA which could be attributed to slightly different parameters for text is a commonsense reasoning dataset, which is not our primary generation. We achieved a much worse result for the SQuAD 2.0 focus, but we included it due to being human translated into dataset, with 𝐹 only 46.1% rather than 67.6%. Trying to replicate 1 2 Slovene. BoolQ, MultiRC, and SQuAD 2.0 are partially human the published scores with the original code , we obtained similar translated [14, 15]. results to ours . However, we analyzed the difference and believe To have a non-commonsense multiple-choice dataset, we ma- that at least some of them are due to unanswerable questions, as chine translated the MCTest dataset [9] and fixed some transla- the 𝐹 score is 84.5% for questions that have an answer and only 1 tion errors. To reduce the cost of translation, we partially used 7.8% for unanswerable questions. The UnifiedQA model, there- the commercial solution DeepL [3] and partially an internal neu- fore, does a poor job of detecting if a question is unanswerable ral machine translator of a bit lesser quality. Later, we translated from the context. the entire MCTest dataset with the DeepL translator and made it publicly available in our repository. However, the reported Table 2: Our and published results of the UnifiedQA results are obtained using the initial mixed translation setting. (UniQA) approach on English datasets using the T5small As the starting training model for monolingual Slovene Uni- model. fiedQA models, we used the monolingual Slovene variant of the T5 transformer encoder-decoder model [7], called SloT5 [11]. For Dataset BoolQ COPA MCTest MultiRC SQuAD 2.0 the cross-lingual transfer experiments, we applied the multilin- Metric CA CA CA ROUGE-L 𝐹1 gual variant of T5, called mT5 [13]. Due to computational time UniQA(publ.) 0.771 / 0.800 / 0.676 and GP U memory limitations, we used the SloT5 and mT5 mod- UniQA(ours) 0.757 0.560 0.762 0.536 0.461 els of the smallest size (60M and 300M parameters, respectively). Originally, Khashabi et al. used the T5 model [7] of the largest possible size (11B parameters) and the BART model [6] as large 4.3 Slovene Monolingual Results Using SloT5 a starting point for the UnifiedQA model. However, they also report results for the T5 model, which we report for com- In the Slovene monolingual setting, we compare different vari- small parison, so all models are of comparable sizes. Table 1 lists the ants of Slovene UnifiedQA models and report the results in Table parameters used to finetune our models. 3. We adapted the models for each QA format separately and obtained so-called specialized models. These provided a baseline Table 1: Parameters for finetuning UnifiedQA models. for what could be achieved with each individual QA format. We then trained the SloUnifiedQA model using all available Slovene datasets. We also investigated the impact of unanswerable ques- Parameter Value tions (SloUnifiedQA-NA, SloUnifiedQA-NA2, explained below) Maximum input size [tokens] 512 and the use of only lower case letters (SloUnifiedQA-LC). Maximum output size [tokens] 100 Number of epochs 25 Table 3: Comparing variants of Slovene UnifiedQA ap- Batch size 8 proach (based on the SloT5 model). Besides the unified Number of beams 4 model, we report the results of specialized models for each Learning rate 5e-5 QA format (specialized), the best results published so far on these datasets (published), and the default classifier. The ef- fect of unanswerable questions and lowercasing is analyzed 4 EXPERIMENTS AND RESULTS in the bottom part of the table. Note that SloUniQA-NA is tested on modified datasets without unanswerable ques- In this section, we report our work on empirical evaluation. We tions, so the results for this model are incomparable. present the evaluation metrics, original English results, experi- ments and results in the monolingual Slovene setting, and in the Dataset BoolQ COPA MCTest MultiRC SQuAD 2.0 cross-lingual transfer setting. Metric CA CA CA ROUGE-L 𝐹 Avg. 1 4.1 Evaluation Metrics SloUniQA 0.683 0.532 0.463 0.310 0.555 0.509 specialized 0.688 0.486 0.439 0.255 0.554 0.484 For each dataset, we use a different evaluation metric. For BoolQ, published 0.666 0.500 / / 0.739 / default 0.623 0.500 0.269 / / / we report the classification accuracy; for SQuAD 2.0, the 𝐹1 SloUniQA-NA 0.675 0.524 0.454 0.319 0.637 0.522 score; for MultiRC, we use ROUGE-L; and for the multiple-choice SloUniQA-NA2 0.695 0.554 0.474 0.321 0.556 0.520 datasets (MCTest and COPA), we calculate the best match be- SloUniQA-LC 0.686 0.530 0.449 0.259 0.533 0.491 tween the generated text and the offered options and compute the classification accuracy. In all cases, the answers are first Comparing the SloUnifiedQA model with specialized models, normalized (removing punctuation and unnecessary spaces and the models achieve better results for the multiple-choice datasets converting the text to lowercase). (COPA and MCTest) and the abstractive dataset (MultiRC). The 4.2 English UnifiedQA Results Using T5 improvement for the extractive dataset is minimal, and we ob- small serve a slight decrease in accuracy for the yes/no dataset (BoolQ). First, we replicated the results of the original English UnifiedQA Better results are also obtained compared to all main classifiers. [5] and also obtained the results for the datasets not originally used, i.e. COPA and MultiRC (the latter was only used as a yes/no 2 https://github.com/allenai/unifiedqa 24 Unified Question Answering in Slovene Information Society 2022, 11–14 October 2022, Ljubljana, Slovenia Comparing SloUnifiedQA on Slovene with the English Uni- on which models were not trained. Overall, the COPA dataset fiedQA model on English datasets (in Table 2), the English model contributes the least to the performance of SloUnifiedQA, the gives better results for all selected formats except SQuAD 2.0. corresponding model achieving almost the same performance. Interestingly, the English and Slovene models have different prob- lems with SQuAD 2.0. The Slovenian one predicts unanswerable Table 4: Contribution of datasets in the unified model by questions too often (it has 𝐹 score of 60,3% for unanswerable omitting one dataset at a time. The red color indicates the 1 questions and only 50,4% for answerable ones, while incorrectly two largest performance drops for each dataset. identifying 13% of answerable questions as unanswerable), the English one too rarely. At the same time, the English model never Dataset BoolQ COPA MCTest MultiRC SQuAD2.0 wrongly predicts that a question is unanswerable. This is likely Metric CA CA CA ROUGE-L 𝐹 Avg. 1 due to unanswerable questions making up a larger proportion SloUniQA 0.683 0.532 0.463 0.310 0.555 0.509 of the dataset in the Slovene training dataset than in the English no BoolQ 0.001 0.522 0.486 0.319 0.561 0.378 no SQuAD 2.0 0.664 0.516 0.451 0.258 0.120 0.402 one. For other datasets, the biggest difference in metrics can be no MCTest 0.676 0.510 0.351 0.317 0.560 0.483 observed in the MCTest multiple-choice dataset, where the dif- no MultiRC 0.690 0.536 0.457 0.209 0.552 0.489 ference is 33%. We attribute the worse result of SloUnifiedQA to no COPA 0.683 0.510 0.456 0.319 0.554 0.504 machine translations and a much smaller training dataset, espe- cially for the multiple-choice questions; as in the original work, the authors use three additional datasets in addition to MCTest. 4.4 Cross-Lingual Transfer Using mT5 Compared to other published works on the same datasets, There are only a few QA datasets in Slovene, so we checked if we achieve better results with the SloUnifiedQA on the BoolQ using transfer from additional English datasets can improve the and COPA datasets compared to Ulčar and Robnik-Šikonja [11], Slovene results. We used three different collections of datasets. while on the SQuAD 2.0 dataset, Zupanič et al. [15] achieve a • SLO: Slovene datasets BoolQ, COPA, MCTest, MultiRC significantly better result (almost 20%). Here, Ulčar and Robnik- and SQuAD 2.0 (described in Section 3). Šikonja [11] also use the SloT5 model with the textual output, • ANG5: English datasets BoolQ, COPA, MCTest, MultiRC, while Zupanič et al. [15] use the SloBERTa model and only predict and SQuAD 2.0 (the English dataset, whose translations the span of the answer, which is an easier task. form the SLO collection). 4.3.1 The Effect of Unanswerable Questions. • ANG9: English datasets BoolQ, COPA, MCTest, MultiRC, Unanswerable questions account for about one-third of all train- and SQuAD 2.0 and all datasets, used by Khashabi et al. ing examples, and models could overfit such questions. To ad- [5], except SQuAD 1.1, i.e. NarrativeQA, RACE, ARC, and dress this issue, we train two models, SloUnifiedQA-NA and OBQA. SloUnifiedQA-NA2. For the SloUnifiedQA-NA model, we removed We trained five models using the multilingual mT5 model all unanswerable questions. As evident from Table 3, for yes/no on these dataset collections and tested them on the SLO test questions and multiple-choice questions the accuracy deterio- sets. The first model, mSloUnifiedQA, was trained only on SLO rates, while for abstractive and extractive questions the metrics datasets and gives a baseline performance of mT5, also enabling improve. The biggest improvement occurred for the SQuAD 2.0 comparison to monolingual SloT5. The mSloUnifiedQA models 1 dataset, where the 𝐹 metric for answerable questions improved 1 were trained on both English and Slovene datasets simultane- to 63.7%. ously (only one phase), with the English dataset collection being The SloUnifiedQA-NA was the basis for the SloUnifiedQA- either ANG5 or ANG9. Only the SLO dataset group was used NA2 model, which we trained on complete datasets, including for validation. The mSloUnifiedQA models were trained in two 2 unanswerable questions. The metrics slightly improved for BoolQ, phases, first on the English datasets (ANG5 or ANG9), using the COPA, and MCTest but may be due to the longer training time. No ROUGE-L metric to select the best model, and the obtained model improvement is observed for SQuAD 2.0; the 𝐹 for answerable 1 was then finetuned on the SLO dataset collection. questions even drops to 51.5%. The results of the five multilingual models are presented in Table 5. Comparison between the monolingual SloUnifiedQA 4.3.2 The Effect of Using Lower Case Letters. model (in Table 3) and the multilingual mSloUnifiedQA shows To analyze the effect of using only lower case letters, we trained that they perform on average equally well, with SloUnifiedQA the SloUnifiedQA-LC model. The results are comparable for performing better on the BoolQ, COPA and MultiRC datasets, and BoolQ and COPA, but for MCTest, MultiRC, and SQuAD 2.0, mSloUnifiedQA performing better on the MCTest and SQuAD the results are worse. The uppercase letters, therefore, contain 2.0 datasets. relevant information in Slovene. Adding additional knowledge in English improved the aver- 4.3.3 Contribution of Datasets in the Unified Model. age metrics by 3-4%, but the training time increased by about To assess the impact of each dataset in the SloUnifiedQA model, we dropped each training dataset in turn. The results are shown Table 5: Results of cross-lingual transfer using additional in Table 4. The largest individual performance drop is observed English datasets and multilingual models based on mT5. for the model without BoolQ, as the yes/no questions become unanswerable (the CA for the BoolQ dataset is almost 0%). This Dataset BoolQ COPA MCTest MultiRC SQuAD 2.0 also strongly affects the average impact but causes even slight Meric CA CA CA ROUGE-L 𝐹 Avg. 1 improvements on MCTest, MultiRC, and SQuAD 2.0. The sec- mSloUniQA 0.646 0.488 0.515 0.298 0.571 0.504 mSloUniQA (ANG5) 0.672 0.486 0.582 0.308 0.587 0.527 1 ond largest average performance drop is achieved by the model mSloUniQA (ANG9) 0.676 0.508 0.579 0.340 0.598 0.540 1 without SQuAD 2.0, where a drop is observed on all datasets. mSloUniQA (ANG5) 0.682 0.504 0.564 0.313 0.593 0.531 2 mSloUniQA (ANG9) 0.683 0.486 0.602 0.323 0.604 0.540 2 For other models, the drops are observed mainly on datasets 25 Information Society 2022, 11–14 October 2022, Ljubljana, Slovenia Katja Logar and Marko Robnik-Šikonja four times for the models with the most datasets (ANG9). A the Association for Computational Linguistics: Human Lan- slight improvement can be observed for models using nine Eng- guage Technologies, Volume 1 (Long and Short Papers). 2019, lish datasets (ANG9) relative to those with only five English pp. 2924–2936. datasets (ANG5). The additional datasets contribute the most [3] DeepL Translator. [18 July 2022]. url: https://www.deepl. to the MCTest multiple-choice results, but the performance on com/translator. MultiRC and SQuAD 2.0 also improved. On the other hand, de- [4] Daniel Khashabi et al. “Looking beyond the surface: A spite the additional datasets, the results for BoolQ and COPA are challenge set for reading comprehension over multiple worse than for the monolingual model. Using one or two-phase sentences”. In: Proceedings of the 2018 Conference of the training does not make a difference on average, but there are North American Chapter of the Association for Computa- differences in individual datasets. tional Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018, pp. 252–262. 4.5 Qualitative Analysis [5] Daniel Khashabi et al. “UnifiedQA: Crossing Format Bound- Qualitative analysis of our models showed that the generated an- aries With a Single QA System”. In: Proceedings of the 2020 swers are mostly substrings or given choices in multiple-choice Conference on Empirical Methods in Natural Language Pro- questions. Models cannot paraphrase, rephrase or provide an- cessing: Findings. 2020, pp. 1896–1907. swers in the correct Slovene case. They also have problems with [6] Mike Lewis et al. “BART: Denoising Sequence-to-Sequence multi-part questions requiring multiple answers that are not Pre-training for Natural Language Generation, Transla- listed in the same place in the context. Machine translations, tion, and Comprehension”. In: Proceedings of the 58th An- which are not always grammatically correct or do not make it nual Meeting of the Association for Computational Linguis- clear what the question is asking for, also make answering the tics. 2020, pp. 7871–7880. questions difficult. The models performed best on factoid ques- [7] Colin Raffel et al. “Exploring the Limits of Transfer Learn- tions that require a short answer. ing with a Unified Text-to-Text Transformer”. In: Journal of Machine Learning Research 21 (2020), pp. 1–67. 5 CONCLUSION AND FUTURE WORK [8] Pranav Rajpurkar, Robin Jia, and Percy Liang. “Know What You Don’t Know: Unanswerable Questions for SQuAD”. The main contributions of this work are the generative unified In: Proceedings of the 56th Annual Meeting of the Associa- QA models based on SloT5 and mT5 encoder-decoder transformer tion for Computational Linguistics (Volume 2: Short Papers). models, which set new state-of-the-art results for QA in Slovene. 2018, pp. 784–789. An additional contribution is the machine-translated and cor- [9] Matthew Richardson, Christopher J.C. Burges, and Erin rected MCTest dataset. Renshaw. “MCTest: A Challenge Dataset for the Open- We identify three possible directions for further work. First, Domain Machine Comprehension of Text”. In: Proceedings better translations or dedicated Slovenian datasets would im- of the 2013 Conference on Empirical Methods in Natural prove upon currently mainly machine-translated datasets. Sec- Language Processing. 2013, pp. 193–203. ond, larger T5 models and longer training times have shown [10] Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S better performance in English. In our work, we used only the Gordon. “Choice of Plausible Alternatives: An Evaluation smallest available T5 models due to the limited memory of the of Commonsense Causal Reasoning.” In: AAAI spring sym- GP U; we also limited training sessions to a maximum of 25 epochs. posium: logical formalizations of commonsense reasoning. Third, by using new datasets, especially additional multiple- 2011, pp. 90–95. choice datasets, as evidenced by the improvement brought by [11] Matej Ulčar and Marko Robnik-Šikonja. “Sequence to se- the introduction of English multiple-choice datasets. Further, ad- quence pretraining for a less-resourced Slovenian lan- ditional abstractive datasets could teach the models to rephrase guage”. In: arXiv preprint arXiv:2207.13988 (2022). better or that answers shall not be just substrings of the provided [12] Matej Ulčar and Marko Robnik-Šikonja. “SloBERTa: Slovene context. monolingual large pretrained masked language model”. In: ACKNOWLEDGMENTS Proceedings of the 24th International Multiconference Infor- mation Society - IS 2021, Data Mining and Data Warehouses Marko Robnik-Šikonja received financial support from the Slove- - SiKDD. 2021. nian Research Agency through core research programme P6-0411 [13] Linting Xue et al. “mT5: A Massively Multilingual Pre- and projects J6-2581 and J7-3159, as well as the Ministry of Cul- trained Text-to-Text Transformer”. In: Proceedings of the ture of Republic of Slovenia through the project Development of 2021 Conference of the North American Chapter of the As- Slovene in Digital Environment (RSDO). sociation for Computational Linguistics: Human Language REFERENCES Technologies. 2021, pp. 483–498. [14] Aleš Žagar and Marko Robnik-Šikonja. “Slovene Super- [1] Ines Čeh and Milan Ojsteršek. “Slovene language ques- GLUE Benchmark: Translation and Evaluation”. In: Pro- tion answering system”. 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[20 June 2022]. url: https : / / github . com / of the 2019 Conference of the North American Chapter of mtzcorporations/NLP_TeamJodka. 26 Social Media Analysis for Assessing Resilience Aljaž Osojnik Bernard Ženko Martin Žnidaršič aljaz.osojnik@ijs.si bernard.zenko@ijs.si martin.znidarsic@ijs.si Jožef Stefan Institute Jamova cesta 39 1000 Ljubljana, Slovenia ABSTRACT The key element of the RESILOC framework is a methodology for assessing resilience structured along six dimensions: Gover- In this paper, we describe tools developed to investigate the nance, Social, Economic, Infrastructure, Disaster Risk Reduction potential use of social media analysis for resilience assessment. and Environmental. Each dimension is described in terms of its We focus on tweets as a data source and apply sentiment analysis, attributes or indicators, the values of which are assessed with topic detection and filtering approaches. We present computed proxies, which are empirically measurable quantities. Indicators aggregates with potential information on resilience, and a web and proxies need to have associated scales and aggregation func- application that was made for the use of domain experts. Finally, tions that allow their calculation within the RESILOC tool [5]. For we discuss preliminary user feedback and lessons learned about example, the social dimension of the resilience of a community the applicability of our approach. could be described with indicators such as Community engage- KEYWORDS ment, Social connectedness, Trust in authority and Risk awareness. The Community engagement indicator could then be assessed social media, sentiment analysis, resilience, disaster management with proxies such as % of population who vote in local elections, Number of NGOs for pre- and post-disaster response per capita 1 INTRODUCTION and % of population undertaking voluntary work. Notably, the Resilience is generally understood as the ability to adapt and resilience assessment of different communities may include dif- recover after a disruptive event. In this work, we focus on re- ferent indicators and proxies. The RESILOC platform seeks to silience of communities in the context of disaster management, provide an initial set of indicators and proxies, allow for the addi- and adopt the following UN definition: Resilience is the ability of tion of new ones, and enable their aggregation and visualization. a system, community or society exposed to hazards to resist, absorb, As some of the indicators mentioned above can also be as- accommodate, adapt to, transform and recover from the effects of sessed through proxies based on social media analysis, we devel- a hazard in a timely and efficient manner, including through the oped a tool for investigating this approach. For example, proxies preservation and restoration of its essential basic structures and (or their components) assessing the indicator Trust in authority functions through risk management [7]. Resilience research aims could be assessed with techniques such as sentiment analysis. In to develop strategies not focused on isolated risks, such as earth- particular, we could hypothesize that a more positive sentiment quakes or fires, but on approaches that subsume and address all in social media posts related to public authorities, e.g., disaster relevant risks, both natural and man-made. The strategies need to response authorities, is related to higher trust in them (and con- identify and account for different human, social, environmental, sequently better adoption of any disaster relief measures they economic and technological factors that influence behavior of a introduce). This is the primary motivation that led the investiga- community when facing a disaster. The goal is that, by adopting tion presented in this paper. As our social media data source, we 2 these strategies, communities can perform their intended func- use tweets, posts on the Twitter microblogging platform. These tions in normal and adverse times. A key element of a resilient are public, abundant and have well supported APIs for collection community is active involvement of local citizens and their active and filtering. role in a decision making process. The rest of the paper is organized as follows. Section 2 briefly The EU-funded project RESILOC (Resilient Europe and Soci- presents the the related work, Section 3 presents the social media eties by Innovating Local Communities, https://www.resilocpro data used in our analysis and Section 4 presents the results of said ject.eu/) aims to develop a holistic framework of studies, methods analyses. Section 5 presents our web tool for resilience assess-and software tools that can be used to assess the resilience of a ment, which is part of the RESILOC framework. The final section 1 community in practice by Local Resilience Teams (LRT). The concludes our presentation, summarizes lessons learned during final goal is to use this framework to identify new strategies for our analysis and provides some avenues for further research. improving the processes of preparedness of local communities against any kind of hazards. 2 RELATED WORK Our work relates to two main fields of research. The first one 1 An LRT is a team in charge of resilience assessment and risk management of a is research on community resilience in the context of disaster given community, typically organized within a civil protection organization. management. Parker et al. Parker [14] addresses the problems of measuring and assessing resilience and warns that past attempts Permission to make digital or hard copies of part or all of this work for personal to define comprehensive resilience assessment frameworks fre- or classroom use is granted without fee provided that copies are not made or quently led to simplifications and focus on a single risk. Particular 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 assessments of resilience can be found in the literature review work must be honored. For all other uses, contact the owner /author(s). conducted in the scope of the RESILOC project [11]. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 2 https://twitter.com/ 27 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Osojnik, Ženko, Žnidaršič, The second related field is social media sentiment analysis approach described below, in Section 4.1. Frequent tokens are and associated techniques. Sentiment analysis [9] is a machine commonly appearing words, numbers or emojis, that we identify learning field, that has benefited from the current rapid devel- on a monthly basis according to the procedure in Section 4.2. The opment of natural language processing techniques [6] based on volume and sentiment aggregates are also calculated for specific large corpora and deep learning developed in the recent years. subsets of tweets called topics, which can be either automatically Sentiment analysis of social media posts has previously been inferred by the mechanism in Section 4.3, or provided by the applied to resilience adjacent domains, such as disaster response users. and management [12, 1]. Research in the cross-section of both fields, i.e., resilience 4.1 Sentiment Analysis and social media, has mostly focused on investigations on how The goal of the sentiment analysis is to assess the sentiment social media affects community and self resilience [8], including of tweets in a given community, its trends, and variations in recent examples during the COVID-19 pandemic [16]. Using sentiment in general and in specific resilience-related topics. social media analysis to assess resilience is, to the best of our To assess the sentiment of tweets we use two machine-learned knowledge, novel, and we were not able to find any similar tools classifiers. The first is a three-class classifier, denoted as LO- to the one presented in this paper. GREG, that classifies tweets as positive, neutral, or negative, and employs logistic regression. It is trained on high-dimensional 3 DATA vector representations of Italian tweets that include weighted The data used in our analyses and visualizations are tweets that words, pairs of consecutive words, 4-character sequences and specifically mention target communities (using a predefined key- emoji characteristics as representation elements, as presented word), which were collected through the Twitter API for Aca- in [10]. The second classifier is the two class (positive, negative) 3 5 demic Research . This allowed us to collect all tweets of interest, FEEL-IT sentiment classifier [2] for Italian that uses word or including those from the past. subword series of character representation in a high dimensional Notably, a tweet is not only the posted text, but rather meta- vector space. It is a fine-tuned BERT-based model [6] for Italian. data-rich data object containing a pleathora of information, such 4.2 Frequent Tokens as its language, geolocation, author code, etc., and relations to other tweets, e.g., if it is a response to another tweet or a retweet. In addition to the information on volume and sentiment, we also For our purposes, however, we only gather the unique tweet provide the most frequent tokens (words, numbers or emojis) that code/id (field id), creation time (field created_at), language (field appear during any given month. These are provided separately lang) and text (field text). for subsets of tweets, which are classified as positive, negative The selected tweets are collected in dataset that we use for our and neutral (when available). analysis. The dataset is recreated during each repetition of the Frequent tokens relate to the concepts mentioned in the tweets analysis, due to potential tweet removal according to Twitter’s and could, as such, be used do discover aspects of resilience privacy mechanisms. Hence, the results shown in the online app relevant to the community, thus potentially serving as proxy are not static but can change with renewed analysis. candidates. Frequent tokens are computed using the following In RESILOC, four communities are studied as use-cases: Go- procedure: (1) the text of all tweets is whitespace split into tokens rizia (Italy), Catania (Italy), West Achaia (Greece) and Tetovo and cast to lower case, (2) unwanted tokens are removed, (3) (Bulgaria). These four communities vary widely in size, which is tokens are sorted by frequency of occurrence, and (4) the most reflected in the amount of tweets in which they are mentioned. frequent tokens are selected for presentation. As the latter two communities are mentioned only in a couple of Unwanted tokens, mentioned in the second step, are the Italian tweets per month, the social media analysis was executed only stop-words. These are filtered using the nltk library [3], as well for the first two. We considered extending the pool of tweets by as using a custom unwanted tokens list, such as punctuation including tweets that are geo-tagged to the selected communities, characters and various versions of the names of the communities. 4 but only a small fraction of tweets contain such information. In the final step, we check that the frequent tokens appear in The data gathering process consists of collection and filtering. enough different tweets. Namely, repeated tokens in a single In particular, we collect all tweets that contain the name of the tweet all count towards token frequency, but count only once community (Gorizia or Catania) in the text of the post during a in terms of tweet appearance. We prevent presenting frequent given time period. These tweets are then filtered based on the tokens that do not appear in enough individual tweets, with a language (lang=it) to gather local posts and to filter out some of occurrence check using a predefined threshold. the noise, e.g., caused by posts mentioning people (particularly celebrities) with names that match the two communities. 4.3 Topic Modeling To identify potential resilience-related topics, we wanted to au- 4 METHODS tomatically model topics in the collected tweets. Our motiva- There are four main data analysis results the online app: (1) tion was that, given such topics, resilience experts could analyze volume and sentiment, (2) frequent tokens, (3) data for specific the corresponding tweets and extract information useful for re- topics and (4) sentiment aggregates and trends. silience assessment and proxy construction. Volume is the amount of tweets in a given time period, yearly or Topic detection or modeling [13] is a common task in natural monthly, while sentiment refers to the yearly or monthly positive, language processing and aims at discovering topics, e.g., politics, neutral or negative sentiment detected in the tweets with the sports, cycling, etc., that appear in a set of text documents, such as news articles or tweets. The assumption is that if a document dis- 3 https://developer.twitter.com/en/products/twitter-api/academic-research cusses a specific topic, some words will appear more frequently. 4 In particular, out of 364531 tweets that mention Catania in 2020, only 8777 (ap- 5 proximately 2.4%) were labeled with geo-location meta-data. Available at https://github.com/MilaNLProc/feel- it. 28 Social Media Analysis for Assessing Resilience Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Topic modeling is an unsupervised classification method, similar who can use them as inputs for proxy construction. The aggre- to soft or fuzzy clustering, since a document can belong to more gates are calculated monthly and yearly. The list of aggregates than one topic or cluster. One popular algorithm for topic model- and their descriptions is as follows. ing is Latent Dirichlet Allocation (LDA) [15, 4], which takes the Positive ratio. Ratio of positive tweets vs the total number of number of topics as an input parameter. total tweets in the current time period. After standard preprocessing of tweets required for topic mod- Neutral ratio. Ratio of neutral tweets vs the total number of eling (upper to lower case, removal of URLs, tokenization into total tweets in the current time period. words, removal of stopwords and other irrelevant words), we ap- Negative ratio. Ratio of neutral tweets vs the total number of 6 plied the LDA algorithm with a preset number of topics ranging total tweets in the current time period. from 3 to 15. We visualized the resulting topics as word clouds and Relative change of volume. Ratio of the number of tweets in manually inspected them. We sought to identify topics related to the current time period and previous time period. resilience, such as sets of tweets discussing actions of authorities Relative change of positive tweets. Ratio of the number of in response to natural disasters (floods, fires, etc.) or citizens positive tweets in the current and previous time period. perception of authorities’ ability to act in case of such disasters. Relative change of neutral tweets. Ratio of the number of Our inspection was inherently subjective and mostly focused neutral tweets in the current and previous time period. on the top-ranked words, although we also considered standard Relative change of negative tweets. Ratio of the number of measures for topic evaluation (perplexity and coherence). negative tweets in the current and previous time period. Absolute change in volume. Difference of the number of tweets in the current and previous time period. Absolute change in positive tweets. Difference of the number of positive tweets in the current and previous time period. Absolute change in neutral tweets. Difference of the number of neutral tweets in the current and previous time period. Absolute change in negative tweets. Difference of the number of negative tweets in the current and previous time period. 5 WEB APPLICATION We make the collected summaries of volume and sentiment anal- yses, frequent tokens and topic data available through a simple web interface. To access the tool, which is intended for internal use, a user provides a security access token, which determines which community data the user is privileged to view. Figure 1: An example of a detected topic. It focuses on COVID-19 measures and conditions for crossing the border between Italy and Slovenia. The most interesting topic is presented in Figure 1 and includes tweets discussing the COVID-19 measures (mascherine is Italian for masks) and conditions (condizioni) for crossing the border between Italy and Slovenia, as Gorizia is a border town. Unfortu- nately, we did not find any topics directly related to resilience, which could be used by resilience experts to assess resilience. This analysis seems to infer that automatic topic modeling from tweets is likely not very useful for assessing resilience, at least not in the context that we tried to use it, though this might be due to the nature of topic modeling. Namely, the topics that we get obtained were general, in that they cover general, rather than Figure 2: An example of a sentiment distribution as dis- resilience specific, concepts, and unpredictable in a sense that in played in the web application. some circumstances (and locations) we might obtain resilience All community data is split into sections based on available related topics and in others not. Ultimately, the automatically classifiers and time intervals. The application provides two op- constructed topics were not very informative, and, as such, we tions for the time interval, i.e., monthly and yearly views. used topics constructed manually by resilience experts from the The monthly view is composed of the following sections: a involved communities. total tweet count, tweet count by sentiment accompanied with 4.4 Aggregates and trends a corresponding pie chart (as seen in Figure 2), a table of fre- quent tokens per classified sentiment (as seen in Table 1), a table To support facilitate the use of the results of our analyses in the with the calculated aggregates and trends and, finally, a topics RESILOC platform, several aggregates are explicitly calculated. section, that shows values for particular topics. In the final sec- These aggregates seek to capture the overall sentiment and senti- tion, each defined topic has a subsection, where the user can see ment trends over various time periods and are available to LRTs, which tokens define the topic, its sentiment distribution and a 6We selected 15 topics as an amount that can be inspected manually. corresponding pie chart, as shown in Figure 3. 29 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Osojnik, Ženko, Žnidaršič, Table 1: An example set of detected frequent tokens. resilience assessment models, but to be considered and prepared for use by the users, i.e., employed with human oversight. (a) Positive (b) Negative Analyses such as the ones presented in this paper are only use- Token Occurence Token Occurence ful for large enough communities that get mentioned in tweets edizioni 174 stato 102 frequently. Furthermore, tweets often do not represent the opin- europea 141 recarsi 77 ion of the population at large. While they are suitable for analysis, oggi 139 solo 57 even in real time, their representativity is an issue that needs to nova 128 x 47 be considered when using such data. capitale 119 ospedali 39 ACKNOWLEDGMENTS This work has been supported by the RESILOC, which has re- ceived funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 833671. We acknowledge also the financial support from the Slovenian Re- search Agency for research core funding for the programme Knowledge Technologies (No. P2-0103). REFERENCES [1] Ghazaleh Beigi, Xia Hu, Ross Maciejewski, and Huan Liu. 2016. An overview of sentiment analysis in social media and its applications in disaster relief. Sentiment analysis and ontology engineering, 313–340. [2] Federico Bianchi, Debora Nozza, and Dirk Hovy. 2021. "FEEL-IT: Emotion and Sentiment Classification for the Italian Language". 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BERT: pre-training of deep bidirectional transformers for language un- derstanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computa- tional Linguistics, Minneapolis, Minnesota, (June 2019), 4171–4186. doi: 10.18653/v1/N19- 1423. [7] United Nations Office for Disaster Risk Reduction. 2012. Terminology. Re- trieved Aug. 24, 2022 from https://www.undrr.org/terminology/resilience. [8] Manon Jurgens and Ira Helsloot. 2018. The effect of social media on the dynamics of (self ) resilience during disasters: a literature review. Journal of Figure 4: An example of a yearly view of relative sentiment. Contingencies and Crisis Management, 26, 1, 79–88. doi: 10.1111/1468-5973 .12212. [9] Bing Liu. 2015. Sentiment Analysis: Mining Opinions, Sentiments, and Emo- The yearly view is composed of the same sections as the tions. Cambridge University Press. [10] Matej Martinc, Iza Skrjanec, Katja Zupan, and Senja Pollak. 2017. Pan 2017: monthly view, however, it concerns data for the entire year. In ad- author profiling-gender and language variety prediction. In CLEF (Working dition to the global pie charts (for sentiment distribution), graphs Notes). [11] Sjirk Meijer, Jon Hall, Rut Erdelyiova, Marcello Sabanes, Abby Onencan, for the progression of absolute and relative sentiment are shown and Kerstin Junge. 2022. RESILOC Project Deliverable 2.6 – Analysis of based on month by month data, as shown in Figure 4. different approaches to resilience also outside EU, Section 6. Tech. rep. The RESILOC Consortium. Retrieved Aug. 24, 2022 from https://www.resilocpr 6 CONCLUSION oject.eu/wp- content/uploads/2021/04/RESILOC_D2.6- v6.0_Final.pdf . [12] Ahmed Nagy and Jeannie A Stamberger. 2012. Crowd sentiment detection We propose a novel approach to resilience assessment based during disasters and crises. In ISCRAM. [13] Christos H. Papadimitriou, Hisao Tamaki, Prabhakar Raghavan, and San- on social media datasets. The analyses and tools described in tosh Vempala. 1998. Latent semantic indexing: a probabilistic analysis. In the paper were developed and presented to potential users in Proceedings of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium preliminary try-out sessions, i.e., as sprints in Agile software on Principles of Database Systems (PODS ’98). Association for Computing Machinery, Seattle, Washington, USA, 159–168. doi: 10.1145/275487.275505. development, as well as discussed with the project consortium’s [14] Dennis J Parker. 2020. Disaster resilience–a challenged science. Environ- domain experts. The approach is currently being evaluated in the mental Hazards, 19, 1, 1–9. [15] Jonathan K Pritchard, Matthew Stephens, and Peter Donnelly. 2000. Infer- project trials, to quantify its usefulness based on expert feedback. ence of Population Structure Using Multilocus Genotype Data. Genetics, 155, While automatic topic modeling resulted in some meaningful 2, (June 2000), 945–959. doi: 10.1093/genetics/155.2.945. topics, these were mostly general and very few of them were [16] Lola Xie, Juliet Pinto, and Bu Zhong. 2022. Building community resilience on social media to help recover from the covid-19 pandemic. Computers in related to resilience. The users expressed preference for more Human Behavior, 134, 107294. doi: 10.1016/j.chb.2022.107294. focused topics, which can now be defined manually, and find the new results interesting and potentially relevant. Interestingly, there is a general preference to not directly use the automatically calculated aggregates of volume and sentiment as inputs to the 30 Urban Mobility Policy Proposal Using Machine-Learning Techniques Miljana Shulajkovska Maj Smerkol Matjaž Gams miljana.sulajkovska@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 increasing the usage of public transport, the system outputs the most appropriate policy that satisfies those requirements. The world’s demography is constantly increasing and most peo- The rest of the paper is organised as follows. First, an overview ple move to big cities. This growth in urbanization affects people’s of the proposed system is given. Then Section 3 describes the daily activities by encountering congestion, air and noise pol- process of collecting the data by giving a brief overview of the lution, water and energy usage etc. To deal with such issues, simulation tool used, the implemented scenarios and the key city authorities are taking various actions in order to provide performance indicators (KPIs). In Section 4 the machine learning the most optimal solution. In that terms testing, evaluating and approach is discussed followed by a description of the applied implementing different scenarios are of great importance that methods and the experimental results. Finally in Section 6 a cost money and time at the same time. Therefore, in the era of conclusion is given. artificial intelligence, different approaches can be used to auto- mate this process. In this paper, we propose a system that has the potential to automatically propose mobility policies based 2 SYSTEM on previously defined city changes. The decision-makers input The key concept of the proposed system is to collect data from the required city changes, while the system outputs a mobility the microscopic traffic simulator. All the components are shown policy that satisfies that specification. To implement the idea, in Figure 1. The microscopic traffic simulator emulates the be- machine-learning algorithms are trained on data produced by a haviour of all the people interacting on the mobility infrastruc- microscopic traffic simulator. The system is tested on data rep- ture. To run the simulator several input files are required such as resenting the city of Bilbao, where the policies are related to network and travel demand. Then the output of the simulator is closing the Moyua square in the city centre at a specific time and used to calculate the KPIs and later both are used to train the ML for different duration, while the city changes are related to air model as part of the ML module. The ML module takes as input pollution and usage of different means of transport. a required city change defined by the decision-makers and using the trained model outputs a mobility policy that satisfies those KEYWORDS requirements. traffic simulation, artificial intelligence, mobility policy 1 INTRODUCTION According United Nations report [7] by 2050 two in three people will live in urban areas. However, as cities continue to grow they may face many challenges that affect the daily mobility services and people’s movement in general. Therefore, finding a solution that satisfies people’s needs is a crucial step toward building a more sustainable mobility system. Currently, many traditional approaches exist that rely on experts’ knowledge using results from microscopic simulations. Those approaches include simula- tion of different mobility policies which are then analysed by the decision-makers. The key issue is how to choose the most appro- priate mobility policy that will satisfy the requirements defined Figure 1: System description by the decision-makers that meet the user’s needs. Achieving this goal is impossible without using the help of modern technologies such as machine learning. In this paper, we propose a system that makes usage of ma- 3 DATA COLLECTION chine learning methods to automate the process of mobility policy Building a ML module/model that predicts the most suitable suggestions. As decision-makers are interested in achieving a mobility policy requires a sufficient amount of data related to a particular set of goals (KPIs) such as reducing 𝐶𝑂 emissions or 2 particular set of policy actions and their consequences. In that Permission to make digital or hard copies of part or all of this work for personal terms, the main source of data for the proposed system comes or classroom use is granted without fee provided that copies are not made or from a microscopic traffic simulator as a very common research 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 method for testing and evaluating different mobility situations. In work must be honored. For all other uses, contact the owner /author(s). the following sections, a brief overview of the simulation tool is Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia given, and then different scenarios representing specific policies © 2022 Copyright held by the owner/author(s). are discussed. Finally, the KPIs used for this study are presented. 31 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia M. Shulajkovska, M. Smerkol, M. Gams Figure 2: System for Urban mobility policy design architecture. 3.1 Simulation 3.2 Scenarios In this study, MATSim was used as the most suitable microscopic simulation tool [3]. The main concept behind this tool is shown in Figure 3. It consists of an iterative process where plans from the travel demand are executed simultaneously in the mobsim and scored in the scoring module. The score is a metric to evaluate whether a plan is good or bad. It takes into account travelling and waiting time, activity duration etc. More about scoring can be read here [5]. Then a certain number of plans are chosen and modified in the replanning step. After a sufficient number of iterations (in our case 200) an equilibrium is reached where no more plans are evolving, producing higher scores. Figure 3: MATSim cycle Figure 4: Scenarios 𝐶𝑂2 A crucial step before running the simulator is to provide data representative of the study area of our interest. The input data is related to the city network map, public transit schedules, travel demand etc. The most challenging part is to construct the travel demand as demographic and other people’s movement data is hard to find. Therefore different techniques exist to solve the issue. One approach is to replicate a real population (construct synthetic population) using sample data and marginal distribu- tion, and then assign activity location using origin-destination (OD) matrices. The iterative proportional fitting (IPF) [1] algo- rithm is used to construct the synthetic population using sample data from EUSILC [2] and demographic data provided by the city. The IPF algorithm is one of the most widely used algorithms for synthetic population reconstruction that combines both datasets (sample data and marginal distributions) to produce weights that show the number of replication of a specific person from the sample data to a specific geographical zone while maintaining the marginal distributions. The simulation outputs a large amount of data that describes people’s movements in form of events. Each event has a type such as “vehicle enters traffic", “vehicle enters/leave link", “per- son starts activity" etc., time and person’s id that performs it. Figure 5: Scenarios Public Transport Other output files also exist as histograms of travel/wait times, usage of different transport modes etc. All this data is used in the We have tested 40 different situations of one policy represented calculation of KPIs for the ML module. by the closure of the Moyua square from 8 am to 5 pm with a 32 Mobility Policy Proposal Using ML Techniques Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia different duration from one to four hours. Results of the applied 4.1 Methods and Results policy are shown in Figure 4 and Figure 5. Since the target variables are continuous and there are multi- On both plots, the x-axis represents the start time of closure, ple of them, we deal with a multi-output regression problem. while the y-axis represents the duration of closing the square This involves predicting more numerical values at the same time for transport in hours. On the first bar plot, the z-axis shows which limits the usage of many algorithms that are designed in the changes in percents of CO warm emissions and the z-axis 2 predicting only a single numerical value. However, to solve the on the second bar plot shows the changes in percents in public problem several solutions exist: transport usage compared to a situation when no changes in the city are applied. In terms of reducing the CO emissions, the best 2 scenario is if we close the square at 9 am for 1 hour. In that case • Multi-output regression algorithms the CO has lowered for 0.9%. On the other hand, if the square is 2 • Wrapper multi-output regression algorithms closed from 5 pm to 6 pm for traffic, the city gets congested in – Direct multi-output regression the surrounding areas and the CO warm exhausts are increased 2 – Chained multi-output regression by 26% even though the public transport usage has increased and car usage has decreased as shown on the second bar plot. One approach is to use regression algorithms that support 3.3 KPIs Calculation multiple outputs directly such as linear regression, k-nearest The key performance indicators (KPIs) represent the objectives neighbours, decision tree, random forest etc. The other approach defined by the decision makers that need to be achieved. In col- is to divide the multi-output regression problem into multiple sub- laboration with the city, a set of KPIs was defined as follows: problems (wrapper multi-output regression) and then deal with • Air pollution single regression problems. On one hand, there is direct multi- : 𝐶𝑂 , 2 𝑁 𝑂 𝑥 , 𝑃 𝑀 cold/warm emissions. • Usage of different modes output regression where independent models are developed for : car, bicycle, public transport, the prediction of each numerical value. On the other hand, the walk. • Bike safety, bikeability chained multi-output regression consists of dependent models when predicting each numerical value. The first set of KPIs related to air pollution is modelled using To evaluate the models a cross-validation technique was used. MATSIm additional emission package [6]. The emissions are The mean absolute error (MAE) performance metric is used as a calculated using HBEFA (Handbook on Emission Factors for score. The mean and standard deviation of the MAE are calculated Road Transport) database [4] in combination with the simulation across all the folds and all repeats. Table 2 shows the results of output. As air pollution is caused by different contributions of inherently multi-output regression algorithms. K-Nearest Neigh- road traffic the emissions module considers both warm and cold bours proved the best results with a mean value of MAE of 3.743 emissions. Warm emissions are emitted while driving and depend and a standard deviation (SD) of 0.852, which means that the on driving speed, stop duration, and vehicle characteristics while difference between the predicted and true value is approximately cold emissions are emitted during the warm-up phase and are 4-time intervals or 2 hours for start hour and 1 hour for the dependent on the engine’s temperature. duration. The second set of KPIs related to the usage of different modes The plot on Figure 6 depicts the difference between true (blue of transport is produced during the simulation, while bike safety dots) and predicted (red dots) values for 30% of the data. The and bikeability are calculated from the simulation results. x-axis represents the start hour, while the y-axis represents the 4 MACHINE-LEARNING FOR POLICY duration of the closure. The smallest error (best-predicted in- stance) between a true and predicted value is marked with black PROPOSAL and yellow dot respectively. Table 3 and Table 4 show results for The developed system proposes a ML module that helps decision- direct and chained multi-output regression respectively where makers in suggesting mobility policies that satisfy a set of pre- random forest and k-nearest neighbours proved the best results defined KPIs. As mentioned before, the main source to train the in both cases. ML models comes from the microscopic traffic simulator. The By applying different ML models, we examined which algo- data used to train the models is shown in Table 1. The KPIs rep- rithm can prove the best results in predicting a mobility policy resent the features, while the policies, i.e., scenarios are treated that satisfies a set of predefined city changes. On the other hand, as target variables where the start time and duration of closure when discussing the simulation results in Section 3.2 we con- are discretized into 30 and 15 minutes intervals respectively. By cluded that closing the Moyua square in the afternoon (from doing so, the most suitable scenario will be predicted according 4 pm to 7 pm) decreases the 𝐶𝑂 for 1%. Also if the square is 2 to the pre-selected KPIs values. closed at 11 am, the car usage decreases by 0.12% reducing the 𝐶𝑂 emissions by 0.3%. Both situations can be implemented to 2 Table 1: Features and target variables achieve a more sustainable city but which one is better depends on the goals that the city wants to accomplish. If the aim is to Features Target variables decrease the 𝐶𝑂 in the afternoon peak hours, the first situa- 2 CO warm CO cold start time of closure 2 2 tion is better. The latter situation provides better results if the NOx warm NOx cold duration of closure city is interested in reducing car usage and increasing the usage PM warm PM of public transport. Therefore, selecting the best option when car trips bike trips having multiple criteria that need to be satisfied is hard when PT trips walk only human knowledge is included. Additionally, the number of bikeability bike safety scenarios included in this work is limited as not every possible situation can be tested due to computational and time costs. 33 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia M. Shulajkovska, M. Smerkol, M. Gams Table 2: Inherently Multi-Output Regression Algorithms 6 FUTURE WORK In order to provide the decision-makers with more options when Model MAE (mean) MAE (SD) implementing different strategies, in future work different areas Linear Regression 4.472 2.565 around Moyua square will be closed. Closing multiple streets K-Nearest Neighbours 3.743 0.852 around the square might help in reducing the air pollution in Decision Tree Regression 4.367 1.083 the centre and in the city in general. Also, it can contribute to reducing congestion and other relevant KPIs during peak hours. Therefore, additional target variables such as the city areas to be closed and the length of the streets inside will be added. Since more simulation needs to be executed, three servers will be used to reduce the computational time. By doing this, the dataset will be expanded and more options will be available to the decision- makers in implementing the best scenario that meets the people’s needs. Moreover, a mobility expert validation will be included in testing the ML module which will contribute to a more detailed analysis of the ML results. ACKNOWLEDGMENTS This work is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870338. The authors also acknowledge the financial support from the Slovenian Research Figure 6: True vs Predicted Data Agency (research core funding No. P2-0209). REFERENCES Table 3: Direct Multi-Output Regression [1] Abdoul-Ahad Choupani and Amir Reza Mamdoohi. 2016. Population syn- thesis using iterative proportional fitting (ipf ): a review and future research. Transportation Research Procedia, 17, 223–233. International Conference on Model MAE (mean) MAE (SD) Transportation Planning and Implementation Methodologies for Developing Linear Support Vector Regression 5.684 4.709 Countries (12th TPMDC) Selected Proceedings, IIT Bombay, Mumbai, India, Random Forest Regression 3.590 0.967 10-12 December 2014. doi: https://doi.org/10.1016/j.trpro.2016.11.078. [2] Eurostat. 2020. Eu statistics on income and living conditions microdata 2004- Linear Regression 4.472 2.565 2019, release 2 in 2020. en. (2020). doi: 10.2907/EUSILC2004- 2019V.1. K-Nearest Neighbors Regression 3.743 0.852 [3] 2016. Introducing matsim. The Multi-Agent Transport Simulation MATSim. Ubiquity Press, (Aug. 2016), 3–8. Decision Tree Regression 4.333 1.274 [4] Mario Keller, Stefan Hausberger, Claus Matzer, Philipp Wüthrich, and Benedikt Notter. 2017. Hbefa version 3.3. Background documentation, Berne, 12. [5] Kai Nagel, Benjamin Kickhöfer, Andreas Horni, and David Charypar. 2016. Table 4: Chained Multi-Output Regression A closer look at scoring. (Aug. 2016). doi: 10.5334/baw.3. [6] 2016. Emission modeling. The Multi-Agent Transport Simulation MATSim. Ubiquity Press, (Aug. 2016), 247–252. doi: 10.5334/baw.36. Model MAE (mean) MAE (SD) [7] 2017. Population Facts No. 2017/4, October 2017: The impact of population Linear Support Vector Regression 5.718 4.364 momentum on future population growth. https://population.un.org/wpp/Publi cations/Files/PopFacts_2017- 4_Population- Momentum.pdf . Random Forest Regression 3.607 0.931 Linear Regression 4.472 2.565 K-Nearest Neighbors Regression 3.690 0.829 Decision Tree Regression 4.325 1.118 5 CONCLUSION In this paper, we presented an approach for proposing mobility policies in an automatic way. First, an overview of the system was given. Then the simulation tool was described. 40 variations of one policy for closing the Moyua square in the centre of Bilbao for transport were simulated and evaluated. The variations refer to the start hour and duration of the closure. On the simulation data, the desired KPIs were calculated which together with other simulation output data were used as input to the ML models. Since the ML models output multiple variables (start hour and duration of closure) the problem becomes multi-output regression and limits the usage of many ML algorithms that are developed to deal with a single target. Therefore, two approaches were presented: multi-output and wrapper multi-output regression algorithms. Applying both sets of algorithms, the best results proved random forest regression using the chained method from the second approach. 34 IMF Quality Assurance of Mammograms Using Deep Convolutional Neural Networks and Transfer Learning Gašper Slapničar Peter Us Erna Alukić gasper.slapnicar@ijs.si peter@u- s.si erna.alukic@zf .uni- lj.si Jožef Stefan Institute UpDev d.o.o. Faculty of Health Sciences Jožef Stefan International Kranj, Slovenia University of Ljubljana Postgraduate School Ljubljana, Slovenia Jamova cesta 39 Ljubljana, Slovenia Nejc Mekiš Miha Mlakar Janez Žibert nejc.mekis@zf.uni- lj.si miha@kaiber.si janez.zibert@zf.uni- lj.si Faculty of Health Sciences kAIber d.o.o. Faculty of Health Sciences University of Ljubljana Ljubljana, Slovenia University of Ljubljana Ljubljana, Slovenia Ljubljana, Slovenia Figure 1: Pipeline of our proposed system. MLO mammograms are taken as input, fed into a chosen CNN architecture, which then outputs a quality grade in an ordinal regression task. ABSTRACT 1 INTRODUCTION Quality assurance (QA) of mammograms is of vital importance, Mammography is the process of using low-energy X-rays to ex- since they are the de-facto method used by doctors for detec- amine human breast tissue for diagnosis and screening, with tion of breast cancer and other tissue abnormalities. Despite this, the typical goal being early detection of breast cancer through there is a distinct lack of both experts and tools for this task. We detection of anomalies in the tissue [3]. The procedure consists thus investigated a deep-learning-based approach using convolu- of compression of breast tissue using a dedicated mammography tional neural networks for prediction of the inframammary fold device with the aim of reducing and evening out the tissue thick- (IMF) quality grade, which cannot be measured and determined ness that X-rays must penetrate, in turn reducing the required quantitatively with rules (e.g., if some point 𝑥 cm from edge, radiation dose. There are two common views in which a mam- then grade 𝑦 ). We showed in a 5-fold cross-validation experiment mogram is recorded, namely craniocaudal (CC) and mediolateral that a relatively simple model can achieve respectable perfor- oblique (MLO). The former captures the breast tissue in a top- mance in terms of root mean squared error (RMSE), area under down direction along the pectoral muscle plane, while the latter the ROC curve (AUC) and accuracy, predicting the IMF grade captures it at an angle sideways. with 3 possible values. Finally we also showed that the model in The importance of regular mammographic screening can not fact derives features from the relevant ROI also looked at by the be overstated, as it the de-facto method used by doctors for early experts, hinting at real-world usefulness of such a QA model. breast cancer or other tissue-anomaly detection (e.g., tumors). However, the procedure itself is rather involved and can be te- KEYWORDS dious for the patient. Subsequently, it is of utmost importance to ensure high quality of taken images, as it is highly undesirable for mammography, quality assurance, ordinal regression, neural net- a patient to have to revisit and repeat the procedure. To this end works, deep learning there are a number of guidelines available that are being followed by the radiologists with the aim of minimizing the amount of Permission to make digital or hard copies of part or all of this work for personal low-quality images taken. Some quality metrics can be quantified or classroom use is granted without fee provided that copies are not made or and measured precisely, while others are more subtle and often distributed for profit or commercial advantage and that copies bear this notice and left to the expertise of the professionals. One such elusive metric 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). is the Inframammary Fold (IMF). IMF is the inferior border of the Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia breast and the crease between the breast and abdominal tissue. © 2022 Copyright held by the owner/author(s). 35 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Slapničar and Us, et al. It serves as an important anatomical landmark on an MLO mam- 3 DATA DESCRIPTION AND mogram to provide assurance to the radiographer that all of the PREPROCESSING posterior breast tissue has been included. The dataset used in our work was collected in the previously In Slovenia, only a single radiographer is responsible for weekly mentioned DORA program between 2011 and 2013 and graded by grading of randomly sampled mammographic segments from that the single expert using a modified PGMI (Perfect, Good, Moderate, week, as a part of the DORA oncology program. This is inefficient Inadequate) grading system, where there were just three grades and the grade itself can be subjective, especially the metrics that (Good, Moderate, Inadequate/Poor). All the mammograms were are not clearly defined, such as IMF. There is thus a need for auto- anonymized and held by the Faculty of Health Sciences. In total mated tools that would help radiologists with quality assurance there were 4928 mammograms, 2424 in the CC view and 2424 in (QA), optimizing the process while also potentially serving as a the MLO view, each view in turn having a left (L) and right (R) training tool for improvements in quality of mammograms being image, each with a corresponding ground truth label. Example collected. images can be seen as input in Figure 1. In this paper we highlight the importance and lack of QA Initially these images were saved in the widely-used Digi- methods for mammograms, and develop two deep convolutional- tal Imaging and Communications in Medicine (DICOM) format, neural-network (CNN) computer vision models, aiming to recog- which contains the image itself with a lot of corresponding meta- nize and successfully predict the IMF quality metric. The latter is data. These initial images are grayscale and come in varying known to be especially tricky and subjective. We evaluate and resolutions, which is problematic for CNN inputs, which are ex- compare the performance of our proposed models on a custom pected to be of a constant shape. Subsequently we first extracted dataset collected in Slovenia. the images and standardized the resolution to 256 x 256 pixels, re- The rest of this paper is organized as follows: we first high- saving them in lossless .png format. Some information loss can light related work about QA in mammography, together with not be avoided however, since we are substantially decreasing existing computer vision methods that are important for QA in resolution in this step. Section 2; in Section 3 we describe our dataset; Section 4 details Each image is by default also equipped with letters in the top-our methodology and experimental results; and in Section 5 we right or top-left corner of the image itself, denoting the view and summarize and discuss the implications with future directions side (e.g., CC-L or MLO-R). Since our computer vision models for our work. might use this information to learn some data-specific pattern 2 RELATED WORK between the view and quality, we semi-manually removed these letters by zeroing pixels in an empirically determined region, To ensure the key goals of mammography are achieved, qual- leaving only the breast tissue in each image. ity assurance must be adopted in order for the mammograms Finally, some of the images have important keypoints or ar- to be suitable for diagnosis. In the past decades, several stan- eas that are very difficult to see, especially with the naked eye. dards have been developed nationally and internationally to this We thus investigated Adaptive Histogram Equalization methods, end. A review study by Reis et al. [3] presents an overview of more specifically Contrast-Limited AHE (CLAHE), which was these, showing importance of both technical and clinical aspects, reported in related work to help substantially with visibility of especially with the development of digital mammography. important regions in mammograms [2]. The effects can be seen In terms of QA, there are specific keypoints or region segmen- in Figure 2. tations that are often required for individual grades. One such is the segmentation of pectoral muscle in the MLO view, which was traditionally segmented using pixel thresholding and region growing algorithms. Recently however, with the rise of deep learning, this task was successfully resolved. Soleimani et al. [6] proposed a two-stage algorithm that predicts precise pectoral muscle boundary using a CNN. Evaluating on three datasets they achieved average values of dice similarity and accuracy of 97% and 99% respectively. Other researchers focused on the final task directly - predic- tion of anomalies related to cancer. For instance Abel et al. [1] proposed a CNN architecture for detection of abnormal axillary lymph nodes, which is a specific abnormality in the tissue. They reported accuracies of 96% for detection of suspicious lymph nodes. Shen et al. [5] have importantly shown that such end-to- end networks are not only performing well, but can be trans- ferred between different datasets, for instance CBIS-DDSM and INBreast, hinting at good generalization capabilities. Despite all existing work, we noticed a distinct lack of research dealing with machine learning QA prediction, meaning models that output grades of mammograms rather than try to predict some other subsequent outcome. The quality itself is however vital both for physicians or other models taking mammograms as Figure 2: Effects of CLAHE image preprocessing on mam- inputs, as good quality mammograms are useful for detections, mograms in both views. Top row are originals, bottom rows while poor quality is not only difficult for diagnosis, but requires a are preprocessed. repeat measurement which is “expensive” for everyone involved. 36 IMF Quality Assurance of Mammograms Using Deep CNNs and Transfer Learning Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Table 1: Numeric results from the 5-fold CV using our For our class label we used the one given by the expert for simple model and transfer learning with VGG19. the IMF. It is a numeric value from 1 to 3, where 1 = good, 2 = moderate and 3 = poor. It is problematic since it is known to be subjective, but still the best we could obtain. It is also Simple model quite difficult to visualize clearly for a non-expert, but we show Fold Nr. RMSE AUC 1v3 AUC 1v2 AUC 2v3 Accuracy the relevant region of interest (ROI) looked at by the experts in Figure 1. Ideally the ground truth grade would be a voted 1 0.26 0.90 0.79 0.78 0.93 value obtained by several experts, but that was not feasible. Since 2 0.25 0.98 0.80 0.92 0.95 IMF is only evaluated on the MLO view, we used just those 3 0.24 0.98 0.79 0.95 0.91 mammograms in further analysis. 4 0.23 0.97 0.78 0.89 0.96 5 0.24 0.94 0.78 0.84 0.95 4 METHODOLOGY AND RESULTS Avg. 0.24 0.95 0.79 0.88 0.94 The learning problem itself seems like a typical classification, Transfer VGG19 model however, after giving it some thought, we realized it is better to 1 0.29 0.78 0.73 0.60 0.79 set it up as an ordinal regression problem, as we are predicting 2 0.27 0.89 0.73 0.77 0.75 a range of grades. We thus mapped our class label values from 3 0.28 0.85 0.70 0.71 0.66 discrete 1, 2 and 3 to the [0.0, 1.0] interval, where grade 1 = 0.0, 4 0.28 0.94 0.65 0.92 0.70 grade 2 = 0.5 and grade 3 = 1.0. We thus obtain a numeric value 5 0.30 0.85 0.69 0.73 0.77 from the network which gives us not only the class information Avg. 0.28 0.86 0.70 0.75 0.73 but also the distance between prediction and ground truth (e.g., prediction of 0.96 is much better compared to prediction of 0.76, given ground truth 1.0). separation between poor images and everything else, since those Once our data was finalized in terms of inputs and outputs, are the most problematic, while moderate images could be close we focused our attention towards a model. Related work dealing to either good or poor. Numeric results are given in Table 1 with visual tasks in general, as well as with mammograms specif- and the ROC curves for all three cases (of the better performing ically, shows convincing dominance of CNNs in the past decade. model) are given in Figures 3, 4 and 5. Subsequently we decided to investigate such architectures. Our aim was to start with a simple architecture consisting of three 2D Conv layers with 16, 16 and 8 kernels (each of size 9 x 9), intermediate max pooling layers with kernel size 2 and stride 2, and one fully connected layer with 1000 neurons on top. We used batch normalization and dropout as commonly-used mechanisms to prevent overfitting. ReLU was used as the activation function and the network was trained for 100 epochs. We then wanted to compare such a simple architecture with a more complex CNN. We decided to attempt a transfer learning approach, where we based it on the known VGG19 model trained on ImageNet. We replaced the final layer with two fully connected layers to instead predict our IMF grade, while keeping the bulk of the model intact with existing weights. Hyperparameters were mostly left at default values, except for learning rate which had a linear decay implemented in our simple architecture. Initially the full data was split into training (80%), validation (10%) and test sets (10%), as traditional. However, using a random train-validation-test split can be volatile and is undesirable in terms of making any conclusions about robustness of the model. We thus instead used the 5-fold cross validation (CV) evaluation setup, where k-1 groups are taken for training and the remaining group is left for testing in each of the 5 iterations. Additionaly it was ensured that the distribution of labels is kept in each group, Figure 3: ROC curve of the better performing (simple) meaning we did a stratified split. This was important in our model for 1v2 class combination. experiment since the class label distribution is relatively skewed (good / 1 / 0.0 = 65%, moderate / 2 / 0.5 = 30%, poor / 3 / 1.0 = 5%) and we are especially interested in the bad examples, which are 5 DISCUSSION AND CONCLUSION in vast minority. For evaluation metrics we used root mean squared error (RMSE) Looking at the results, we can initially observe the overall better and area under the curve (AUC of ROC curve), while also looking performance of our simple model compared to the pre-trained at the classificaion accuracy (transforming from ordinal regres- VGG19 transferred to our domain. All the metrics are more stable sion back to classification) as it is the most intuitive metric. In across fold while also achieving better overall values. Since we terms of AUC, we always compared all possible pairs of grades, were especially interested in the separation of the good and poor meaning 1v2, 1v3 and 2v3. The most important is to have good mammograms (grade 1 vs. grade 3), we can also see that this 37 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Slapničar and Us, et al. where we can see the model commonly focused on the relevant IMF ROI that is also focused by the experts. However, this focus was not exclusive, meaning it did not focus just that region and also it wasn’t the same on all images, but still rather consistent, which is a good indicator that the model actually learned the relevant features for IMF QA. Figure 6: Grad-CAM heatmap showing the areas on the Figure 4: ROC curve of the better performing (simple) mammogram that were focused by the model to derive model for 1v3 class combination. features. To summarize, we investigated the possibility of CNN-based IMF QA for mammograms, looking at a simple CNN model and a transferred slightly-modified VGG19 model. The simple CNN architecture achieved respectable results in terms of several met- rics and importantly also focused on the correct part of the image without any guidance, hinting that it learned the relevant fea- tures also looked at by the experts. Extensions to prediction of other QA grades might allow for a system that could help with continuous QA, as well as expert training. ACKNOWLEDGMENTS We would like to acknowledge the DORA program for provid- ing us with the dataset. Additionally we would like to thank colleagues from the Faculty of Health Sciences for helping with understanding and interpretation of data. Finally a special thanks goes to kAIber d.o.o. and UpDev d.o.o. for participating in the data analysis and modelling. REFERENCES [1] Frederik Abel, Anna Landsmann, Patryk Hejduk, Carlotta Ruppert, Karol Borkowski, Alexander Ciritsis, Cristina Rossi, and Andreas Boss. 2022. De- tecting abnormal axillary lymph nodes on mammograms using a deep con- volutional neural network. Diagnostics, 12, 6, 1347. [2] Etta D Pisano, Shuquan Zong, Bradley M Hemminger, Marla DeLuca, R Figure 5: ROC curve of the better performing (simple) Eugene Johnston, Keith Muller, M Patricia Braeuning, and Stephen M Pizer. model for 2v3 class combination. 1998. Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms. Journal of Digital imaging, 11, 4, 193–200. [3] Cláudia Reis, Ana Pascoal, Taxiarchis Sakellaris, and Manthos Koutalonis. separation is indeed consistently successful and seems relatively 2013. Quality assurance and quality control in mammography: a review of robust. As expected the separation of moderate (grade 2) mam- available guidance worldwide. Insights into imaging, 4, 5, 539–553. [4] Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna mograms from others is more challenging, but still can be done Vedantam, Devi Parikh, and Dhruv Batra. 2019. Grad-CAM: visual expla- reasonably well. nations from deep networks via gradient-based localization. International Deep learning models are often criticized for being black- Journal of Computer Vision, 128, 2, (Oct. 2019), 336–359. doi: 10.1007/s11263- 019- 01228- 7. box and not offering explainability for their decisions. We also [5] Li Shen, Laurie R Margolies, Joseph H Rothstein, Eugene Fluder, Russell wanted to do a quick investigation of this by using the Grad- McBride, and Weiva Sieh. 2019. Deep learning to improve breast cancer CAM approach [4], which is a popular technique for producing detection on screening mammography. Scientific reports, 9, 1, 1–12. [6] Hossein Soleimani and Oleg V. Michailovich. 2020. On segmentation of pec- “visual explanations” for decisions from a large class of CNN- toral muscle in digital mammograms by means of deep learning. IEEE Access, based models in the form of a heatmap showing where the model 8, 204173–204182. doi: 10.1109/ACCESS.2020.3036662. focused the most on an image. An example is shown in Figure 6, 38 Vehicle Axle Distance Detection From Time-series Signals Using Machine Learning David Susič Blaž Erzar Nika Čelan david.susic@ijs.si blaz.erzar@gmail.com nika.celan8@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 Gašper Leskovec Žiga Kolar Martin Konečnik leskovecg@gmail.com ziga.kolar@ijs.si martin.konecnik@cestel.si Jožef Stefan Institute Jožef Stefan Institute Cestel cestni inženiring d.o.o Jamova cesta 39 Jamova cesta 39 Špruha 32 Ljubljana, Slovenia Ljubljana, Slovenia Trzin, Slovenia Domen Prestor Matjaž Skobir Matjaž Gams domen.prestor@cestel.si matjaz.skobir@cestel.si matjaz.gams@ijs.si Cestel cestni inženiring d.o.o Cestel cestni inženiring d.o.o Jožef Stefan Institute Špruha 32 Špruha 32 Jamova cesta 39 Trzin, Slovenia Trzin, Slovenia Ljubljana, Slovenia ABSTRACT The authors of Marszalek et al. [5] measured vehicle axle dis- tances based on multifrequency impedance measurement of a In this study, we compare a signal decomposition and a con- slim inductive loop sensor. Using test vehicles, they were able volutional autoencoder approach in determining vehicle axle to confirm that their method can successfully determine the dis- distances. Our dataset consists of 62076 instances of vehicles tances. In the work by Chatterjee et al. [1] they used data from crossing a bridge. Each vehicle is detected by eight identical sen- sensors on the bridge and a wavelet-based analysis to determine sors placed under the bridge that record time series vibration the axle distances. In the work of Khalili et al. [3], piezoelectric data. We compare our results to those computed using an ex- elements were used for a system to detect the weight of vehicles pert’s model, which we consider to be the ground truth. The in motion. They used the weight-in-motion system to determine signal decomposition approach achieves accuracies of up to 0.89, both the axle distances and vehicle weights with sufficient ac- 0.98, and 1, with the calculated distances matching the expert curacy. Rujin et al. [4] developed a deep learning system for model within 2%, 5%, and 10%, respectively. The convolutional vehicle recognition based on strain sensor data. They were able autoencoder, on the other hand, achieves accuracies of up to 0.97, to classify 11 different vehicle types with a very high average 0.99, and 1 with the same error margins compared to the expert precision. model. In this work, we use data collected from a single bridge to KEYWORDS test two machine learning approaches for vehicle axle distance detection. The first approach is based on signal decomposition vehicle detection, axle distance, neural network, peak detection, and the second approach is based on the convolutiona neural machine learning network autoencoder. We begin in section 2 with a description of the dataset used 1 INTRODUCTION in this study. In section 3, we explain our approaches and illus- trate them with examples. Results are presented and discussed In order to accurately weigh the vehicles crossing the bridge in section 4. The paper concludes with section 5. and determine if they weigh too much and damage the road, the vehicle speed, the number of vehicle axles, and their in-between distances must first be determined. 2 DATASET In recent years, many types of sensors have been used for Our dataset consists of sensor data from vehicles crossing the vehicle detection. These include acoustic sensors, inductive loop bridge. The sensors are placed under the bridge in the configura- sensors, strain sensors, magnetic sensors, and imaging sensors. tion shown in the Figure 1. The sensors are identical and record Researchers around the world have developed various methods the vibrations of the crossing vehicles at a sampling rate of 512𝐻 𝑧 . for using sensor data for vehicle axle detection, weight detection, In this study, only data from vehicles travelling in lane 1 were and classification. used (orange sensors 1–8 in Figure 1). The vibration data from the sensors in the first and last columns (1 and 2) are also used Permission to make digital or hard copies of part or all of this work for personal to calculate the vehicle speed. The vehicle speed is calculated by or classroom use is granted without fee provided that copies are not made or superimposing the signals using a cross-correlation method. Our 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 dataset consists of 62076 instances, where each instance contains work must be honored. For all other uses, contact the owner /author(s). data for one vehicle. In addition, each instance also contains the Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia axle distances calculated by the expert model and the times at © 2021 Copyright held by the owner/author(s). which each vehicle axle crossed the signal. 39 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia David Susič, et al. We compare our results with those of the expert model, which has a measured accuracy of 98% in practise. Our results are con- sidered correct if all calculated axle distances match those of the expert model within the specified margin of error. In addition, we have the option to skip the predictions of the results whose confidence level is below a certain threshold. 3.1 Signal Decomposition The first step of a signal decomposition approach was to de- termine the most appropriate signal for each instance. For this purpose, peak detection was performed for all eight signals, cal- culating the first and second derivatives. A 62076 × 8 matrix was then created, with the eight columns indicating the number of detected peaks from each of the signals. A gradient boosting regression model was then trained on this matrix, the output of which was an array with the correct number of peaks. In addition, eight gradient boosting classifiers were trained, one for each of the signals. The output of each classifier was an array giving the Figure 1: Placement of the sensors on the bridge. probabilities that the number of detected peaks was correct for that signal. An example of sensor data for a vehicle with 5 axles is shown For each test instance, the regression model first predicted the in Figure 2. The signal peaks correspond to the vehicle axles cross- axis number, rounding the result to the nearest integer. All eight ing the sensor, while the amplitude corresponds to the weight signals were then run, starting with the signal from sensor one. of the vehicle on that axle. Although the peaks in the signal For each signal, a check was made to see if the number of peaks correspond to the vehicle axles, the intervening spacing of the determined matched the number predicted by the regression peaks generally does not represent the actual axle spacing. Due model. If it did, we checked whether the probability that the to interference between the signals from the individual axles, number of detected peaks, as predicted by the classifier for that the peaks shift relative to the position of the peaks if the signals signal, was above a confidence threshold. Iteration was stopped from the individual axles were isolated. A small effect of this if both criteria were met, and the signal was selected as the most can be seen in the peak triplet in the right part of the signal in appropriate for that instance. This means that in most cases not Figure 2. In some cases, where two of the adjacent vehicle axes all signals were checked. Although in principle there could be a are very close to each other, the peaks may overlap and become signal that would be even more suitable, we found experimentally indistinguishable from each other, resulting in a single peak. that in more than 90% of cases signal 1 was the best, followed by signals 2, 5, and 6, in that order. If none of the eight signals met the criteria, the instance was skipped. In our experiments, we used confidence values between 0 and 0.997. After the best signal for each instance was determined, the signals were decomposed into what are called base waves. A base wave is a function designed to have the form of an isolated wave, and can be constructed with three parameters: x-location, scaling in the x-direction, and scaling in the y-direction. The signal decomposition can be defined as an optimization problem where we want to find the best parameters for the base waves. The objective function we want to minimize is the mean square error between the original signal and the sum of the base waves. Once the signal was optimally decomposed, the peaks of the base waves were used to calculate the axle distances. The base wave peaks now correspond to the actual axle times and represent isolated waves, thus their peaks are not shifted by interference. Figure 2: Example sensor data for a vehicle with 5 axles. This can also be seen in Figure 3: the green and black vertical The green markings correspond to the crossing points of lines do not exactly coincide, which is most obvious in the triplet the vehicle axles as calculated by the expert model. on the right. Peak detection and models’ training was performed using Python 3.7 and libraries Scikit 0.24.2 [7] and Numpy 1.18.5 [2]. 3 METHODOLOGY 3.2 Convolutional Autoencoder The objective of this study is to evaluate the performance of signal decomposition and convolutional autoencoder approaches The second approach is a convolutional neural network as an in computing vehicle axle distances from sensor data. In our two autoencoder. The schematic of the model is shown in Figure 5. approaches, the signal timing of the axles is first determined The first layer is the input layer. It consists of 4000 nodes, since and then their intermediate distances are computed based on the this was the number of samples of the longest signal, and takes vehicle speed. the raw signal as input. The signals with length less than 4000 40 Vehicle Axle Distance Detection Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia at least T2, the axle distances were calculated, otherwise the in- stance was skipped. In our experiments, T1 was fixed at 0.01, while we tried values between 0 and 0.7 for T2. Convolutional autoencoding was performed using Python 3.7 and library Tensorflow 2.9.1 [6]. 4 RESULTS Both approaches were tested with 5-fold cross-validation, and the folds were the same in both experiments. The results are shown in tables 1 and 2. They are given for a percentage of skipped instances between 0 and 50 %. The "±𝑥 " values in the brackets of the accuracy columns represent percentages within which the calculated axle distances must match those given by the expert models for the prediction to be considered correct. In the Table1, the confidence column corresponds to the confidence threshold Figure 3: Example of signal decomposition. The black ver- of the prediction model for the number of peaks, while the T2 tical lines represent the peaks as detected during peak column in Table 2 corresponds to the minimum peak probability detection, while the green lines represent the peaks after of the peak with the highest probability. If these criteria are decomposition. not met, an instance is skipped. The corresponding amounts of skipped instances are given in the skipped columns. We see that the signal decomposition approach achieves ac- were padded with zeros. For all instances, signal 1 was chosen as curacies up to 0.89, 0.98, and 1, with the calculated distances the input signal, since it worked best in most cases. The encoding matching the expert model within 2%, 5%, and 10%, respectively. part of the autoencoder consists of three convolutional layers The convolutional autoencoder, on the other hand, achieves ac- with sizes 5, 2 and 3 and the number of filters 8, 16 and 32. Each curacies of up to 0.97, 0.99, and 1 compared to the expert model, convolutional layer is followed by a batch normalization and a with the same error margins. max-pooling of size 2. The decoder has the opposite structure It can also be seen that for both approaches, the accuracies compared to the encoder and the max-pooling layers are replaced start to converge when about 15% of the instances are skipped, by up-sampling layers. The output layer has the same size as the and do not improve significantly even when the percentage of input layer. The loss function used for model training was a skipping is 50. The convolutional autoencoder generally has binary cross entropy. higher accuracy than the signal decomposition approach, except The output for each training instance was a binary array, in cases where the margin of error is 10 %, in which case the with ones at the sample locations containing a peak and zeros performances of both approaches are similar. everywhere else. Thus, for the unseen (test) instances, the model outputs the probabilities for each of the input signal samples to 5 CONCLUSION include a peak. An example output for a test instance is shown In this work, we tested a signal decomposition and convolutional in Figure 4. It can be seen that the probabilities for the peaks are autoencoder approach for vehicle axle distances detection using almost always less than one, but the number of probabilities that data from eight sensors mounted under the bride. We used a are not zero (or not very close to zero) is equal to the number of dataset of 62076 vehicles travelling in the same lane. We compared actual peaks. It can also be seen that the model has learned to our results to those computed by an expert’s model, which we shift the peaks where necessary (triplet on the right). considered to be the ground truth. Using the signal decomposition approach, we achieved accuracies of up to 0.89, 0.98, and 1 for the cases where each vehicle axle distance matched the expert model within 2%, 5%, and 10%, respectively. For the convolutional autoencoder, the accuracies obtained were 0.97, 0.99, and 1 for the same error margins compared to the expert model. The models will be improved in future work to include detection of vehicle axle weights. ACKNOWLEDGMENTS This study received funding from company Cestel. The authors acknowledge the funding from the Slovenian Research Agency (ARRS), Grant (PR-10495) and Basic core funding P2-0209. REFERENCES [1] Pranesh Chatterjee, Eugene OBrien, Yingyan Li, and Arturo González. 2006. Wavelet domain analysis for identification of vehicle axles from bridge mea- Figure 4: Example output of convolutional autoencoder. surements. Computers & Structures, 84, 28, 1792–1801. doi: https://doi.org/10 .1016/j.compstruc.2006.04.013. [2] Charles R. Harris, Jarrod K. Millman, Stefan J. van der Walt, Ralf Gom- After decoding, we selected lower and upper probability thresh- mers, Pauli Virtanen, and David Caurnapeau. 2020. Array programming with olds, T1 and T2 (red and blue dashed lines in Figure 4). If all peaks numpy. Nature, 585, 357–362. doi: https://doi.org/10.1038/s41586- 020- 2649- 2. had a probability of at least T1 and the highest probability was 41 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia David Susič, et al. Figure 5: Scheme of the convolutional autoencoder structure. Table 1: Results for the signal decomposition approach. Confidence Skipped Accuracy (± 2%) Accuracy (± 5%) Accuracy (± 10%) 0.0 0.01 0.79 0.88 0.91 0.75 0.05 0.82 0.92 0.95 0.865 0.1 0.84 0.95 0.97 0.915 0.15 0.86 0.96 0.98 0.95 0.2 0.87 0.96 0.99 0.974 0.25 0.88 0.98 0.99 0.977 0.3 0.88 0.98 0.99 0.982 0.35 0.88 0.98 0.99 0.988 0.4 0.88 0.98 0.99 0.996 0.46 0.89 0.98 1.0 0.997 0.5 0.89 0.98 1.0 Table 2: Results for the signal convolutional autoencoder approach. T2 Skipped Accuracy (± 2%) Accuracy (± 5%) Accuracy (± 10%) 0.0 0.0 0.85 0.88 0.89 0.021 0.06 0.91 0.94 0.95 0.12 0.1 0.94 0.97 0.98 0.431 0.15 0.95 0.98 0.99 0.488 0.2 0.96 0.99 0.99 0.53 0.25 0.96 0.99 0.99 0.566 0.3 0.96 0.99 0.99 0.601 0.35 0.96 0.99 0.99 0.636 0.4 0.97 0.99 1.0 0.665 0.45 0.97 0.99 1.0 0.7 0.5 0.97 0.99 1.0 [3] Mohamadreza Khalili, Gopal Vishwakarma, Sara Ahmed, and Athanassios multi-frequency impedance measurement of a slim inductive-loop sensor. Thomas Papagiannakis. 2022. Development of a low-power weigh-in-motion Measurement, 169, 108525. doi: https://doi.org/10.1016/j.measurement.2020.1 system using cylindrical piezoelectric elements. International Journal of Trans- 08525. portation Science and Technology, 11, 3, 496–508. doi: https://doi.org/10.1016 [6] Martín Abadi et al. 2015. TensorFlow: large-scale machine learning on het- /j.ijtst.2021.06.004. erogeneous systems. Software available from tensorflow.org. (2015). https: [4] Rujin Ma, Zhen Zhang, Yiqing Dong, and Yue Pan. 2020. Deep learning based //www.tensorf low.org/. vehicle detection and classification methodology using strain sensors under [7] F. Pedregosa et al. 2011. Scikit-learn: machine learning in Python. Journal of bridge deck. Sensors, 20, 18. https://www.mdpi.com/1424- 8220/20/18/5051. Machine Learning Research, 12, 2825–2830. http://www.jmlr.org/papers/volu [5] Zbigniew Marszalek, Waclaw Gawedzki, and Krzysztof Duda. 2021. A re- me12/pedregosa11a/pedregosa11a.pdf . liable moving vehicle axle-to-axle distance measurement system based on 42 Študija učinkovitosti algoritma za razporejanje terenskega dela A Study of the Performance of a Fieldwork Scheduling Algorithm Tea Tušar Nace Sever Aljoša Vodopija Institut “Jožef Stefan” in Univerza v Ljubljani Bogdan Filipič Mednarodna podiplomska šola Fakulteta za računalništvo in Institut “Jožef Stefan” in Jožefa Stefana informatiko Mednarodna podiplomska šola Jamova cesta 39 Večna pot 113 Jožefa Stefana Ljubljana, Slovenija Ljubljana, Slovenija Jamova cesta 39 tea.tusar@ijs.si nace.sever@gmail.com Ljubljana, Slovenija aljosa.vodopija@ijs.si bogdan.f ilipic@ijs.si POVZETEK KEYWORDS Razporejanje terenskega dela je zahteven optimizacijski problem. scheduling problem, evolutionary algoirthm, heuristic algorithm, Za njegovo reševanje smo razvili trinivojski algoritem. Na prvem branch-and-bound algorithm, mixed-integer linear programming, nivoju evolucijski algoritem razporedi naloge po delavcih, na efficiency drugem nivoju hevristika za vsakega delavca razporedi naloge po dnevih, na tretjem nivoju pa algoritem razveji in omeji rešuje pro- 1 UVOD blem mešanega celoštevilskega linearnega programiranja (angl. Razporejanje terenskega dela je optimizacijski problem, ki zah- Mixed-Integer Linear Programming, MILP), kjer nalogam za vsa- teva dodelitev delavca in časa začetka opravljanja vsaki terenski kega delavca in vsak dan posebej dodeli čas njihovega začetka. nalogi tako, da je zadoščeno vsem omejitvam razporejanja in V tem prispevku se posvečamo študiji učinkovitosti algoritma je cena celotnega urnika čim nižja. Obstajajo številne različice na tretjem nivoju. Izkaže se, da ta nalog ne more razporediti tega problema, ki se razlikujejo tako po omejitvah kot po na- dovolj hitro za praktično uporabo, zato za povečanje njegove činu izračuna cene razporeda. Posledično obstajajo tudi različni učinkovitosti MILP poenostavimo. Rezultati poskusov kažejo, da pristopi za njegovo reševanje [6]. Študija [3] primerja dve formu- poenostavitev izboljša učinkovitost algoritma na tretjem nivoju, laciji problema, in sicer v obliki problema usmerjanja vozil (angl. medtem ko je učinek na celoten algoritem načeloma ugoden, a Vehicle Routing Problem, VRP) in v obliki problema mešanega odvisen od problema. celoštevilskega linearnega programiranja (angl. Mixed-Integer Linear Programming, MILP). Rezultati poskusov študije nakazu- KLJUČNE BESEDE jejo, da je oblika MILP za zapis razporejanja nalog terenskega problem razporejanja, evolucijski algoritem, hevristika, algoritem dela ustreznejša od oblike VRP, zato tudi naš pristop uporablja razveji in omeji, mešano celoštevilsko linearno programiranje, obliko MILP. učinkovitost Vendar pa je učinkovitost reševanja takšnih kombinatoričnih problemov zelo odvisna od njihove velikosti. Že pri relativno ABSTRACT majhnih problemih se namreč pogosto zgodi, da jih ni moč re- šiti v doglednem času. Zato se v našem pristopu zgledujemo po Fieldwork scheduling is a demanding optimization problem. To podobnih prijemih iz sorodnega dela (glej npr. [1]) in problem solve it, we developed a three-level algorithm. At the first level, an razdelimo na manjše, lažje obvladljive podprobleme. Problem evolutionary algorithm distributes tasks to workers, at the second razporejanja terenskega dela tako rešujemo s trinivojskim opti- level, a heuristic algorithm distributes tasks of each worker over mizacijskim algoritmom, pri katerem na prvem nivoju evolucijski days, and at the third level, a branch-and-bound algorithm solves algoritem razporedi naloge po delavcih, na drugem nivoju hevri- the problem in the form of mixed-integer linear programming stika za vsakega delavca razporedi naloge po dnevih, na tretjem (MILP), where the starting times of tasks need to be scheduled for nivoju pa algoritem razveji in omeji rešuje problem v obliki MILP, each worker and each day separately. In this paper, we study the tj. nalogam za vsakega delavca in vsak dan posebej dodeli čas efficiency of the algorithm at the third level. Because it cannot njihovega začetka. schedule the tasks fast enough for practical use, we try to increase Tak trinivojski algoritem je sposoben v uri zadovoljivo rešiti its efficiency by simplifying the MILP. Experimental results show tudi nekoliko večje probleme (npr. z 20 delavci, 20 dnevi in več sto that the simplification improves the performance of the algorithm nalogami), a je ta čas za praktično uporabo predolg. Zato želimo at the third level, while the effect on the overall algorithm is in algoritem pohitriti. Ozko grlo predstavlja reševanje problema principle favorable, but depends on the problem. MILP, saj sta evolucijski algoritem in hevristika zelo hitra, tako da lahko največjo pohitritev celotnega algoritma dosežemo s pohitritvijo na tretjem nivoju. Permission to make digital or hard copies of part or all of this work for personal V nadaljevanju prispevka v 2. razdelku najprej predstavimo or classroom use is granted without fee provided that copies are not made or našo različico problema razporejanja terenskega dela, nato pa 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 v 3. razdelku na kratko opišemo trinivojski algoritem za njeno work must be honored. For all other uses, contact the owner /author(s). reševanje. V 4. razdelku analiziramo učinkovitost algoritma na Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia tretjem nivoju, v 5. razdelku pa predlagamo poenostavitev pro- © 2022 Copyright held by the owner/author(s). blema MILP in preverimo njen učinek najprej na algoritem na 43 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Tea Tušar, Nace Sever, Aljoša Vodopija, and Bogdan Filipič tretjemu nivoju in končno na celoten trinivojski algoritem. Pri- • Dnevno aktivnih delavcev naj bo čim manj. spevek sklenemo z zaključki v 6. razdelku. • Aktivni delavci naj bodo čim bolj enakomerno obreme- njeni. 2 PROBLEM RAZPOREJANJA TERENSKEGA • Skupno trajanje potovanj med lokacijami naj bo čim krajše. DELA • Izvede naj se čim več nalog. • Naloge naj se izvedejo čim prej. Problem razporejanja terenskega dela opišemo s scenarijem raz- • Delavci naj imajo čim manj neaktivnega časa. porejanja, spremenljivkami problema, omejitvami in optimiza- • Nadur naj bo čim manj. cijskim kriterijem (podrobne formalne definicije tu ne moremo • Naloge z višjo prioriteto naj se začnejo izvajati pred nalo- zapisati zaradi pomanjkanja prostora). Obravnavamo najbolj splo- gami z nižjo prioriteto. šno različico problema, v kateri želimo razporediti večino nalog, • Naloge, ki zapadejo prej, naj se začnejo izvajati pred nalo- saj ta pokriva tudi posebni primer, ko je zaradi spremembe v gami, ki zapadejo kasneje. zadnjem trenutku treba prerazporediti samo nekaj nalog. • Naloge naj se izvedejo čim bliže želenemu časovnemu 2.1 Scenarij razporejanja oknu. • Nalogo, ki ima želene delavce, naj opravi eden izmed žele- Časovno obdobje razporejanja je razdeljeno na dneve, znotraj njih nih delavcev. je čas obravnavan zvezno. Za vsak dan poznamo začetek in konec • Nalogo z želenim razporedom naj se izvede čim bliže temu rednega delovnika ter trajanje morebitnih nadur (bodisi na za- razporedu. četku bodisi na koncu dneva). Dane imamo tudi množico lokacij, Uteži posameznih delnih kriterijev so zelo pomembne, saj časovne oddaljenosti za vsak par lokacij ter množico kompetenc, določajo njihova medsebojna razmerja in drastično vplivajo na ki so skupne nalogam in delavcem. Scenarij razporejanja vse- dobljene rešitve. Nastavili smo jih s pomočjo ekspertnega znanja buje tudi podatke o delavcih, in sicer za vsakega kompetence, in poskusov na številnih različnih scenarijih. dovoljeno število nadur ter začetno in končno lokacijo. Podatki o nalogah pa za vsako obsegajo njeno trajanje, želeno in obvezno časovno okno, prioriteto, zahtevane kompetence in morebitne 3 TRINIVOJSKI OPTIMIZACIJSKI želene delavce. Malice so posebne naloge, za katere lokacija ni ALGORITEM definirana (malica se vedno izvaja na isti lokaciji kot predhodna V nadaljevanju na kratko predstavimo vse tri nivoje optimizacij- naloga in se ne more prekrivati z drugimi nalogami). skega algoritma. Dodatno lahko scenarij razporejanja vsebuje že vnaprej pripra- vljene razporede posameznih nalog, ki so dveh tipov. Obveznih razporedov 3.1 Prvi nivo: razporejanje nalog po delavcih se ne sme spreminjati, a jih je treba vseeno upoštevati, saj postavljajo omejitve k razporejanju ostalih nalog. Po drugi Na tem nivoju z evolucijskim algoritmom [5] vsaki nalogi dode- strani pa se želene razporede lahko spreminja, a to vpliva na ceno limo delavca, ki jo bo izvedel. Evolucijski algoritem začetno po- končnega urnika. pulacijo 𝑁 rešitev ustvari naključno, vendar tako, da vse rešitve p ustrezajo omejitvam za delavce (prve tri omejitve v razdelku 2.3). 2.2 Spremenljivke Potem algoritem izvaja naslednje korake največ 𝑁 generacij. V g vsaki generaciji algoritem najprej izbere 𝑁 staršev s turnirsko Spremenljivke optimizacijskega problema v celoti določijo urnik, p selekcijo. Nato pare staršev križa in mutira (pri mutaciji upo- saj za vsako nalogo povedo ali je razporejena ali ni (ni namreč rabimo različne strategije zasnovane po meri delnih kriterijev treba razporediti vseh nalog) in če je, kateri delavec jo bo opravil (glej razdelek 2.4), ki jih izbiramo tako, da se pogostost uporabe ter kdaj se bo začela izvajati. sklada z njihovimi utežmi). Tako dobljeno populacijo evolucijski 2.3 Omejitve algoritem ovrednoti tako, da za vsako rešitev izvede drugi in tretji nivo algoritma. Nato staro populacijo prepiše z novo (najboljšo Urnik, ki predstavlja rešitev problema, je dopusten samo, če iz- staro rešitev ohrani) in nadaljuje z enakimi koraki. polnjuje vse naslednje omejitve: • Delavec lahko izvaja samo eno nalogo hkrati (v časovnem 3.2 Drugi nivo: razporejanje nalog delavca po razporejanju nalog je treba poskrbeti tudi za upoštevanje dnevih trajanja potovanja med lokacijami). • Delavec lahko izvaja naloge le znotraj delovnega časa in Hevristika na drugem nivoju naloge vsakega delavca razporedi po ima omejeno število nadur. dnevih. Po vrsti vsem nalogam, urejenim naraščajoče po številu • Delavec mora imeti zahtevane kompetence za opravljanje dni, v katerih se lahko izvedejo, dodelimo zanje najugodnejši naloge. dan. Ugodnost dne določimo z glasovanjem, ki poteka tako, da • Naloge morajo biti razporejene znotraj svojih obveznih različni delni kriteriji (glej razdelek 2.4) glasujejo za dneve, ki so časovnih oken. zanje najugodnejši. Glasovi so uteženi z utežmi delnih kriterijev, • Nalog z obveznim razporedom se ne sme prerazporejati. nalogi pa dodelimo dan z največ glasovi. 2.4 Optimizacijski kriterij 3.3 Tretji nivo: določitev časa začetka nalog za Optimizacijski kriterij oz. cena urnika, ki jo želimo minimizirati, en dan enega delavca je definirana kot utežena vsota naslednjih delnih kriterijev (prve Na tretjem nivoju z algoritmom razveji in omeji nalogam za en tri postavke so si v nasprotju, zato je smiselno upoštevati samo dan enega delavca dodelimo začetni interval. Problem torej za- eno od njih naenkrat): pišemo v obliki MILP tako, da upoštevamo samo tiste omejitve • Vsi delavci naj bodo čim bolj enakomerno obremenjeni. in delne kriterije, ki so na tem nivoju še smiselni (npr. na tem 44 Študija učinkovitosti algoritma za razporejanje terenskega dela Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 103 tevilo spremenljivk 600 tevilo omejitev 500 102 400 300 as [s] 101 200 100 0 100 1 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 tevilo nalog tevilo nalog Slika 1: Odvisnost števila spremenljivk in omejitev v for- Slika 2: Povprečen čas, potreben za optimalno rešitev pro- mulaciji problema MILP na tretjem nivoju od števila nalog. blema glede na njegovo velikost. sekund, kar pomeni, da je za naše potrebe algoritem neučinkovit nivoju se ne ukvarjamo več s kompetencami, enakomerno obre- že za probleme s sedmimi ali več nalogami. menjenostjo delavcev in podobnimi delnimi kriteriji, saj je zanje Preverimo še, kako dobro deluje algoritem, če mu omejimo poskrbljeno na prvih dveh nivojih). čas, ki ga ima na voljo za iskanje rešitev. Poskuse izvedemo z Podobno kot pri predstavitvi problema tudi tu zaradi omeje- naslednjimi časovnimi omejitvami: 0.5 s, 1 s, 2 s, 4 s, 8 s, 16 s in nega prostora ne moremo navesti celotne formulacije problema 32 s. Pri tem opazujemo, koliko nalog je algoritem razporedil, in MILP. Za razumevanje nadaljevanja je najpomembneje vedeti, da to število primerjamo z optimalnim številom razporejenih nalog 2 imamo pri takšni formulaciji za problem z 𝑛 nalogami 3𝑛 + O (𝑛) (dobljenim v prejšnjem poskusu, ko algoritem ni bil časovno ome- 2 spremenljivk in 5𝑛 + O (𝑛) omejitev, kot prikazuje slika 1. jen). Čeprav cilj algoritma ni samo razporediti čim več nalog, je število razporejenih nalog dober pokazatelj kakovosti delovanja 4 PREIZKUS UČINKOVITOSTI algoritma. Kot je razvidno iz slike 1, je število spremenljivk problema MILP Na sliki 3 vidimo, da ob prekratkem času na problemih z veliko zelo veliko že za probleme z majhnim številom nalog, kar ote- nalogami algoritem odpove (večino nalog zavrne, čeprav bi jih žuje nalogo optimizacijskemu algoritmu. Čas, ki ga potrebuje lahko razporedil). Na primer, ko ima algoritem na voljo le 0,5 s, za najdbo optimalne rešitve, preverimo s poskusom na množici primerno deluje le za probleme z do štirimi nalogami, za večje testnih problemov, ki imajo lastnosti podobne problemom iz pra- problema pa njegova uspešnost pade in ko je nalog osem ali kse. več, v povprečju razporedi le eno nalogo. Delovanje algoritma Ta množica vsebuje 180 testnih problemov (20 za vsako ve- je nekoliko boljše, če ima na voljo daljši čas, a šele pri 32 s se likost problema od dveh do desetih nalog), pri katerih je treba določiti čas izvajanja nalog za enega delavca v enem dnevu. Ne- kateri problemi imajo samo navadne naloge, lahko pa imajo tudi malico, eno nalogo z obveznim razporedom ali pa oboje. Trajanje 4.0 malice je vedno pol ure, trajanje ostalih nalog pa je izbrano na- ključno iz porazdelitve, ki skuša posnemati probleme iz prakse. 3.5 Tako je večina nalog krajših od 90 minut, nekaj pa jih ima dolžino ejenih nalog do štirih ur. Prioriteta vsake naloge je izbrana naključno med 1 in 3.0 9. Prav tako so lokacije izvajanja nalog in začetna lokacija delavca 2.5 izbrane naključno izmed lokacij nekaterih večjih slovenskih mest. t = 0.5 s Večina nalog ima neomejeno časovno okno, pri nekaterih pa je tevilo razpor t = 1 s 2.0 okno skrajšano na začetku ali koncu dneva. Trajanje delovnega no t = 2 s e t = 4 s časa je izbrano naključno med 6 in 10 ur, lahko pa delavec vedno 1.5 t = 8 s opravlja do dve naduri. Povpr t = 16 s Vse testne probleme rešujemo z algoritmom razveji in omeji t = 32 s 1.0 t = neomejen iz reševalnika SCIP [2] preko knjižnice OR-Tools [4]. Pri tem be- ležimo čas, ki ga algoritem potrebuje, da najde optimalno rešitev. 2 3 4 5 6 7 8 9 10 tevilo nalog Reševanje poteka na osebnem računalniku s 16 GB pomnilnika in frekvenco procesorja 3,60 GHz. Slika 3: Povprečno število razporejenih nalog pri različ- Rezultati poskusa so prikazani na sliki 2. Vidimo, da algoritem nih časovnih omejitvah in velikostih problemov (s črtkano praviloma potrebuje eksponentno več časa z dodajanjem vsake črno črto je prikazano optimalno število razporejenih na- naloge. Če želimo, da je celoten trinivojski algoritem koristen v log). praksi, si lahko za reševanje problema MILP privoščimo le nekaj 45 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Tea Tušar, Nace Sever, Aljoša Vodopija, and Bogdan Filipič P1, trajanje potovanja P1, obremenitev delavcev število razporejenih nalog na problemih z devetimi in desetimi t = 1 s t = 1 s nalogami približa optimalnemu številu razporejenih nalog. 310000 t = 2 s 335000 t = 2 s a t = 1 s, poenostavitev t = 1 s, poenostavitev 305000 t = 2 s, poenostavitev a 330000 t = 2 s, poenostavitev 5 POENOSTAVITEV PROBLEMA nik nik 300000 325000 Cena ur Cena ur Ker z delovanjem algoritma nismo zadovoljni, poskusimo pro- 295000 320000 blem poenostaviti. Za zapis delnih kriterijev za prioriteto in čas 290000 315000 2 2 zapadlosti potrebujemo 2 0 1000 2000 3000 𝑛 + O (𝑛) spremenljivk ter 4𝑛 + O (𝑛) Trajanje optimizacije [s] 0 1000 2000 3000 Trajanje optimizacije [s] omejitev, kar je zelo veliko, sploh ker ta dva delna kriterija ni- P2, trajanje potovanja P2, obremenitev delavcev sta zelo pomembna. Zato preizkusimo, kako algoritem deluje, če ju izpustimo (zanju lahko do neke mere poskrbimo na zgornjih 50000 50000 dveh nivojih optimizacijskega algoritma). Število spremenljivk a a t = 1 s nik nik t = 2 s in omejitev se še vedno povečuje kvadratično s številom nalog, 40000 40000 t = 1 s, poenostavitev t = 1 s t = 2 s, poenostavitev vendar pa smo koeficienta pred kvadratnim členom s 3 oziroma Cena ur t = 2 s Cena ur 30000 30000 t = 1 s, poenostavitev 5 zmanjšali na 1. t = 2 s, poenostavitev Za poenostavljeni problem izvedemo podoben test kot v raz- 20000 0 500 1000 1500 2000 2500 0 500 1000 1500 2000 2500 Trajanje optimizacije [s] Trajanje optimizacije [s] delku 4, le da testiramo samo pri časovnih omejitvah 0.5 s, 2 s, 8 s in 32 s. Na sliki 4 primerjamo število razporejenih nalog pri osnovnemu ter poenostavljenemu problemu. Vidimo, da na večjih Slika 5: Rezultati optimizacije za štiri različice algoritma poenostavljenih problemih algoritem deluje mnogo bolje. na dveh problemih (P1 zgoraj in P2 spodaj) z dvema raz- ličnima delnima kriterijema (trajanje potovanja levo in enakomerna obremenitev delavcev desno). Manjše vredno- 4.0 sti so boljše. 3.5 6 ZAKLJUČKI ejenih nalog 3.0 V prispevku smo analizirali učinkovitost algoritma za razporeja- nje terenskega dela. Posvetili smo se le časovno najzahtevnejšemu 2.5 t = 0.5 s t = 2 s delu trinivojskega algoritma – reševanju problema MILP na tre- tevilo razpor t = 8 s tjem nivoju. Z dvema poskusoma smo pokazali, da algoritem 2.0 no t = 32 s razveji in omeji ni dovolj učinkovit za reševanje praktičnih pro- e t = 0.5 s, poenostavitev blemov, zato smo problem MILP poenostavili. To ne spremeni 1.5 t = 2 s, poenostavitev Povpr t = 8 s, poenostavitev kriterijev celotnega problema, algoritmu na tretjem nivoju pa t = 32 s, poenostavitev 1.0 omogoči, da učinkovito reši tudi probleme z desetimi nalogami t = neomejen (več jih v praksi ne pričakujemo). Primerjali smo tudi, kako poe- 2 3 4 5 6 7 8 9 10 nostavitev vpliva na delovanje celotnega algoritma, in ugotovili, tevilo nalog da čeprav obstajajo problemi, za katere poenostavitev ni koristna, v splošnem daje dobre rezultate in se je bomo posluževali tudi v Slika 4: Primerjava delovanja algoritma na izvirni (polne praksi. črte) in poenostavljeni formulaciji problema (črtkane črte) pri različnih časovnih omejitvah in velikostih problemov ZAHVALA (s črno črtkano črto je prikazano optimalno število razpo- To delo je nastalo v okviru projekta Inteligentno in okolju pri- rejenih nalog izvirne formulacije problema). jazno razporejanje terenskega dela – MF-Scheduler, katerega naročnik je Comland d.o.o., sofinancerja pa Ministrstvo za gospo- S poenostavitvijo torej dosežemo, da algoritem na tretjem darski razvoj in tehnologijo Republike Slovenije in Evropski sklad nivoju deluje zadovoljivo tudi za praktične potrebe. Vendar pa za regionalni razvoj Evropske unije, ter raziskovalnega programa to še ne pomeni nujno, da poenostavitev izboljša delovanje ce- P2-0209, ki ga financira Javna agencija za raziskovalno dejavnost lotnega trinivojskega algoritma. To preverimo s poskusom na Republike Slovenije iz državnega proračuna. dveh testnih problemih, P1 in P2, pri katerih damo enkrat večjo utež delnemu kriteriju trajanja potovanja, drugič pa enakomerni LITERATURA obremenitvi delavcev. Na ta način dobimo štiri različne testne [1] S. Bertels in T. Fahle. 2006. A hybrid setup for a hybrid scenario: Combining probleme. P1 obsega 220 nalog, deset delavcev in sedem dni, P2 heuristics for the home health care problem. Computers & Operations Research, 33, 10, 2866–2890. doi: 10.1016/j.cor.2005.01.015. pa 114 nalog (vsebuje tudi malice), pet delavcev in tri dni. Za vsak [2] K. Bestuzheva in sod. 2021. The SCIP Optimization Suite 8.0. Technical Report. testni problem poženemo štiri različice trinivojskega algoritma, Optimization Online, (dec. 2021). http : / / www . optimization - online . org ki se razlikujejo samo na tretjem nivoju – ta uporablja bodisi /DB_HTML/2021/12/8728.html. [3] J. A. Castillo-Salazar, D. Landa-Silva in R. Qu. 2016. Workforce scheduling izvirni bodisi poenostavljeni problem, izvajanje algoritma pa je and routing problems: Literature survey and computational study. Annals of omejeno bodisi na 1 s bodisi na 2 s. Operations Research, 239, 1, 39–67. doi: 10.1007/s10479-014-1687-2. Slika 5 kaže rezultate teh poskusov. Na problemu P1 (zgornja [4] Google Developers. 2021. About OR-Tools. Retrieved 19. avg. 2022 from https://developers.google.com/optimization/introduction/overview. dva grafa na sliki) lahko jasno vidimo, da poenostavitev problema [5] A. E. Eiben in J. E. Smith. 2015. Introduction to Evolutionary Computing. na tretjem nivoju koristi učinkovitosti celotnega algoritma. Tega (2. izd.). Springer. doi: 10.1007/978- 3- 662- 44874- 8. [6] D. C. Paraskevopoulos, G. Laporte, P. P. Repoussis in C. D. Tarantilis. 2017. ne moremo trditi za problem P2, na katerem je delovanje izvirne Resource constrained routing and scheduling: Review and research prospects. in ponostavljene različice zelo podobno, vidimo pa veliko boljše European Journal of Operational Research, 263, 3, 737–754. doi: 10.1016/j.ejor delovanje v primeru omejitve izvajanja na 2 s. .2017.05.035. 46 Interaktivno eksperimentiranje z besednimi vložitvami v platformi ClowdFlows Interactive Experimentation with Word Embeddings in the ClowdFlows platform Martin Žnidaršič Senja Pollak Vid Podpečan martin.znidarsic@ijs.si senja.pollak@ijs.si vid.podpecan@ijs.si Institut "Jožef Stefan" Jamova cesta 39 1000 Ljubljana, Slovenija POVZETEK rabo tovrstnih metod med drugim otežuje potrebno predznanje, V članku predstavimo spletno platformo ClowdFlows, ki je na- ki je potrebno za njihovo smiselno uporabo, včasih pa tudi po- menjena analiziranju podatkov in strojnemu učenju in omogoča stopki namestitve in nastavitev programske opreme. Prototipno uporabo interaktivnih delotokov. Posebej predstavimo značilno- raziskovalno orodje ClowdFlows, ki ga razvijamo na Odseku za sti platforme, ki lajšajo njeno uporabo programiranja neveščim tehnologije znanja na Institutu "Jožef Stefan", naslavlja ti dve uporabnikom in elemente platforme, ki omogočajo analizo teksta oviri in kaže potencial za praktično uporabo. V sklopu projekta z najsodobnejšimi pristopi vektorskih vložitev. Poročamo tudi o EMBEDDIA [14, 13, 16] smo razširili nabor zmogljivosti tega praktičnem preizkusu uporabnosti platforme in njenih orodij z orodja predvsem na področju analize naravnega jezika, zato se v vektorskimi vložitvami za izbrane ciljne uporabnike s področij tem prispevku osredotočamo na metode in končne uporabnike humanistike in družboslovja. s tega področja. Natančneje, predstavimo primer učenja in upo- rabe modelov za besedne vektorske vložitve in izkušnje novih KLJUČNE BESEDE uporabnikov s področja humanistike in družboslovja. procesiranje naravnega jezika, besedne vložitve, spletna aplika- V razdelku 2 predstavimo osnovno sorodno delo. Platforma cija, delotoki ClowdFlows je opisana v razdelku 3. Razdelek 4 predstavi primer uporabe vektorskih vložitev in uporabniške izkušnje. Zaključki ABSTRACT so podani v razdelku 5. The paper presents the ClowdFlows web platform for machine learning and data analysis using interactive workflows. In par- 2 OZADJE IN SORODNO DELO ticular, we highlight selected features that facilitate its use by 2.1 Platforme za vizualno programiranje in non-programmers as well as selected elements of the platform deljenje rešitev that enable text analysis using state-of-the-art word embedding approaches. We also report on a hands-on evaluation of the us- Programsko orodje ClowdFlows, ki je predstavljeno in upora- ability of the platform and its word embedding components in bljeno v tem prispevku, je podobno nekaterim drugim orodjem a selected group of end users from the fields of humanities and za upravljanje delotokov podatkovnega rudarjenja. Slovenskim social sciences. uporabnikom je verjetno najbolj poznano orodje Orange [2], po- dobni pa sta orodji tudi Weka [18] in RapidMiner [8, 5]. Vsa ta KEYWORDS orodja omogočajo vizualno programiranje s programskimi gra- dniki in upravljanje tako izdelanih programov. Manj razširjene so natural language processing, word embeddings, web application, rešitve za skupno rabo delovnih tokov. To recimo ponuja portal workflows myExperiment [15] ali spletna stran pobude OpenML [17]. Je pa uporabnost teh rešitev omejena predvsem na dobro podprto 1 UVOD javno deljenje rešitev, za izvajanje ali urejanje delovnih tokov pa Področja, povezana z metodami umetne inteligence, kot so rudar- mora uporabnik še vedno namestiti posebno programsko opremo, jenje podatkov, strojno učenje in avtomatska obdelava naravnega v kateri so bili le-ti zasnovani. ClowdFlows, po drugi strani, omo- jezika, v zadnjih letih doživljajo razmah v praktični uporabi. Naj- goča tako izdelavo kot tudi deljenje in izvajanje delotokov. novejši metodološki dosežki so običajno najprej na voljo v obliki programskih knjižnic ali spletnih storitev (angl. web services), po- zneje v platformah za razvijanje rešitev z udobnim uporabniškim 2.2 Besedne vložitve vmesnikom in običajno še pozneje v namenskih orodjih, ki to Besedne vektorske vložitve, ki so strojno naučene z uporabo metodologijo uporabljajo interno in omogočajo njeno uporabo nevronskih mrež, so predstavitve besed v prostoru, kjer vsako brez ali z zelo omejenim vplivom na način delovanja tudi upo- besedo opisuje vektor z veliko dimenzijami (tipično od nekaj rabnikom brez računalniškega predznanja. Slednjim samostojno deset do nekaj sto). Besede, ki so si blizu v vektorskem pro- storu (kar lahko merimo s kosinusno razdaljo), so si tudi se- Permission to make digital or hard copies of part or all of this work for personal mantično podobne. Med vektorskimi vložitvami je mogoče raču- 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 nati tudi odnose, ki presegajo enostavno sorodnost besed, npr. the full citation on the first page. Copyrights for third-party components of this preko analogij. Na primer, odnos Madrid:Španija je podoben od- work must be honored. For all other uses, contact the owner/author(s). nosu Pariz:Francija [10]. Pri statičnih vložitvah, kot so modeli Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). word2vec [9] in fastText [1], je posamezna beseda v korpusu predstavljena z enim vektorjem. Pri metodi fastText je vsaka 47 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Žnidaršič, Pollak, Podpečan Slika 1: Glavni pogled v ClowdFlows. beseda predstavljena kot vsota vektorskih vložitev znakovnih Po prijavi v ClowdFlows imamo na voljo kratek tečaj o osno- n-gramov, ki jih beseda vsebuje. V praksi to pomeni, da metoda vah, izdelavo novega delotoka ali pregled javno dostopnih rešitev. pri modeliranju semantične bližine upošteva tudi morfološko Glavni pogled je namenjen izdelavi, pregledu in poganjanju de- podobnost besed, zaradi česar je ta metoda še posebej uporabna lotokov. Prikazan je na sliki 1. Večji del tega pogleda predstavlja za izračun besednih vložitev v morfološko bogatih jezikih, kot je delovna površina, na katero lahko potegnemo (ali uvrstimo z slovenščina. Za razliko od statičnih vložitev pa pri kontekstualnih dvoklikom) željeni programski gradnik (angl. widget) iz seznama vložitvah, kot sta na primer modela ELMo [12] in BERT [3], vsako razpoložljivih gradnikov na levi strani pogleda. Smiselno po- pojavitev besede opisuje svoj vektor. To je pomembno predvsem vezani gradniki predstavljajo delotok, ki ga lahko poženemo z z vidika večpomenskih besed pa tudi v primerih, kjer analiziramo nadzornim gumbom Play. razlike med besedami v različnih kontekstih. Za veliko jezikov Povezave med gradniki vzpostavimo s klikom na izhod enega obstajajo prednaučeni modeli na velikih jezikovnih korpusih [4, gradnika in vhod drugega. Vhodi so predstavljeni kot svetlo mo- 3], ki jih je mogoče priučiti za posamezne domene in naloge. dri pravokotniki na levi strani gradnika in izhodi kot tovrstni pravokotniki na desni. Povezave lahko odstranimo tako, da z de- 3 CLOWDFLOWS sno tipko miške kliknemo povezavo in izberemo možnost Remove. Delotoki se shranjujejo samodejno, lahko pa jih tudi eksplicitno ClowdFlows [6, 7] je spletna platforma za analiziranje podatkov shranimo s pritiskom na kontrolnik za shranjevanje, kar nam in strojno učenje z grafičnim uporabniškim vmesnikom, ki omo- omogoča tudi lastno poimenovanje shranjenega dela. Shranjene goča izvajanje v brskalniku brez zahtev po lokalni namestitvi delotoke lahko pregledujemo, kopiramo, brišemo, izvažamo ali programske opreme, ponuja pa tudi preprosto javno deljenje izde- javno delimo na pogledu, ki se pokaže ob izbiri lanih rešitev. Gre za odprtokodno raziskovalno orodje, katerega Your workflows. Javno objavljeni delotoki dobijo nespremenljiv URL naslov, ki ga zadnja stabilna različica ClowdFlows 3 je na voljo na naslovu: lahko delimo in vsakemu uporabniku ClowdFlows omogoča, da https://cf3.ijs.si/. ustvari svojo kopijo tako deljenega dela. Grafičen način sestave delovnih tokov in uporaba javno de- ljenih rešitev brez nameščanja dodatne programske opreme sta značilnosti, ki lajšata uporabo tudi uporabnikom, ki nimajo pro- gramerskega predznanja, imajo pa zanimive podatke in razisko- 4 UPORABA VEKTORSKIH VLOŽITEV valne probleme, pri katerih bi jim prav prišle metode, ki so na voljo v ClowdFlows. Za raziskovalce je poleg tega pomembno tudi 4.1 Učenje modela vložitev v ClowdFlows preprosto deljenje in preprostost ponavljanja ali nadgrajevanja Za pridobitev predstavitve teksta v obliki vektorskih vložitev obstoječih eksperimentov. lahko uporabimo predpripravljene modele ali pa take modele Elementi v ClowdFlows 3 vsebujejo vrsto programskih gra- sami strojno naučimo. Tovrstno strojno učenje je običajno ra- dnikov, ki ponujajo delo z vektorskimi vložitvami. Vsebujejo čunsko zelo zahtevno in za smiselne rezultate potrebuje velike prednaučene statične in kontekstualne modele za več jezikov količine podatkov. V praksi se zato pogosto uporablja predhodno kakor tudi nekaj orodij, ki na njih temeljijo, kot so na primer naučene modele. ClowdFlows ponuja več prednaučenih modelov, klasifikatorji za analizo sentimenta novic [11] in prepoznavanje naprimer ELMo, Word2Vec in razne modele pristopa BERT in sovražnega govora [11]. fastText, tudi za slovenščino. 48 Interaktivno eksperimentiranje z besednimi vložitvami v platformi ClowdFlows Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Slika 2: Delotok, ki je bil uporabljen na delavnici s ciljnimi uporabniki. Dostopen je na: https://cf3.ijs.si/workflow/283 . Učenje lastnih modelov je smiselno, ko gre za posebna bese- min_count - najmanjše število pojavitev besede, pri katerem dila ali naloge, pri katerih jih želimo uporabljati. Velika računska se beseda še upošteva. zahtevnost, velike količine podatkov in z njima povezani daljši časi obdelave namreč niso združljivi z interaktivno uporabo, ki Kjer je primerno, opis parametra vključuje namig, ali je v primeru je značilna za ClowdFlows. Pri uporabnikih digitalne humani- majhnih učnih podatkov priporočljivo povečati oz. zmanjšati stike in družboslovja smo zaznali potrebo za učenje vložitev na vrednost parametra. majhnih, specifičnih korpusih, kot so pesniške zbirke, specializi- rani novičarski članki ipd. Takšni korpusi so pogosto bistveno 4.2 Izkušnje uporabnikov manjši od tipičnih korpusov, ki se uporabljajo za učenje vektor- Uporabnost platforme ClowdFlows in najpomembnejših kompo- skih vložitvev. Glede na potrebe uporabnikov in zmogljivosti nent za analizo naravnega jezika z vidika ciljnih končnih uporab- platforme smo se odločili za implementacijo gradnika za učenje nikov smo preverjali v okviru enodnevne delavnice, ki je potekala modelov train fastText, saj je algoritem fastText eden najučinko- (na daljavo) 27. januarja 2022. Delavnica je bila namenjena eni vitejših in najmanj računsko zahtevnih. Implementacija gradnika od naših primarnih ciljnih skupin: raziskovalcem z različnih po- v ClowdFlows vsebuje tudi namige, kako prilagoditi privzete dročij humanistike in družboslovja, ki (predvidoma) niso vešči parametre za učenje na majhnih korpusih. Za sprejemljivo hi- programiranja. tro interaktivno delo vseeno priporočamo, da vhodni korpus ne Za potrebe delavnice smo pripravili primer delotoka za anali- presega dveh milijonov besed ali približno 10 MB neobdelanega ziranje besedil z vektorskimi vložitvami. Prikazan je na sliki 2. besedila. Delotok se začne z dvema možnima načinoma vnosa vhodnih Gradnik train fastText z uporabo algoritma fastText nauči nov podatkov, nadaljuje z opcijsko uporabo tokenizatorja in lema- vektorski model na vhodnem korpusu. Tak model lahko nato po- tizatorja (ta kot vhodni podatek sprejema tudi oznako jezika), sredujemo drugim gradnikom. Vhod v train fastText je besedilni čemur sledi učenje modela fastText. Naučeni model nato v delo- korpus, kot je na primer izhod gradnika Load Corpus from CSV. toku uporabimo na dva načina: v gradniku fastText neighboring Korpus je mogoče tokenizirati, lematizirati ali pa uporabiti tudi words pregledujemo okolico (sosednje besede) izbranih besed, v brez tovrstne predobdelave. gradniku Evaluate word expressions with fastText pa na modelu train fastText uporabniku ponuja nastavljanje sledečih para- preizkušamo uporabo izrazov (seštevanje, odštevanje) na vek- metrov: torskih predstavitvah besed. Ogled rezultatov v obeh primerih omogočimo z gradnikom Object viewer. bucket - število skupin (značilke besednih in znakovnih 𝑛- Delavnica se je začela s skupno uvodno predstavitvijo plat- gramov so zgoščene v fiksno število skupin); forme ClowdFlows in primera delotoka s slike 2, ki je trajala epoch - število epoh učenja; 20 minut in v kateri smo izbrane primere prikazali z uporabo lr - hitrost učenja; besedila novele Deseti brat Josipa Jurčiča. dimension - velikost besednih vektorjev; Temu je sledilo osem 20-minutnih sej, v katerih je vsak uporab- window - velikost kontekstnega okna; nik ustvaril svoj primerek delotoka, naložil svoj korpus in preizku- model - vrsta nenadzorovanega fastText modela (cbow ali sil izbrane komponente ClowdFlows. Ena seja je bila namenjena skipgram) ter enemu uporabniku in njegovim podatkom, drugi uporabniki pa 49 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Žnidaršič, Pollak, Podpečan so lahko prisostvovali kot opazovalci. Uporabnikom smo pri nji- ZAHVALA hovem delu pomagali, če so imeli težave pri uporabi platforme Prispevek je rezultat raziskovalnih projektov Računalniško pod- ali pri pripravi svojih vhodnih podatkov. Udeležba na delavnici prta večjezična analiza novičarskega diskurza s kontekstualnimi be- je bila na povabilo. Udeleženci, ki so bili povabljeni na delavnico, sednimi vložitvami (št. J6-2581), Sovražni govor v sodobnih koncep- so raziskovalci s področij literarnih ved, sociologije, socialnega tualizacijah nacionalizma, rasizma, spola in migracij (št. J5-3102) dela in sorodnih področij. Pripravili so lastne korpuse s svojih in programa Tehnologije znanja (št. P2-0103), ki jih je sofinanci- področij, kot so na primer tematski korpusi migracij, korpus del rala Javna agencija za raziskovalno dejavnost Republike Slovenije slovenskih literatov, korpus francoske poezije, LGBT, novice, ki iz državnega proračuna, ter evropskega projekta EMBEDDIA (št. govorijo o socialnem delu in podobno. Nekateri udeleženci so 825153), ki ga v okviru okvirnega programa za raziskave in ino- bili vabljeni v okviru interdisciplinarnih projektov SOVRAG in vacije Obzorje 2020 financira EU. CANDAS. Nihče od udeležencev pa ni imel predhodnih izkušenj s ClowdFlows. Zaradi velikega zanimanja smo število sej povečali LITERATURA s predvidenih 8 na 10. [1] Piotr Bojanowski, Edouard Grave, Armand Joulin in Tomas Mikolov. 2017. Uporabljeni korpusi so bili zelo raznoliki, udeležence pa so Enriching word vectors with subword information. Transactions of the Asso- zanimali različni vidiki obdelave besedil. V večini primerov so ciation for Computational Linguistics, 5, 135–146. [2] Janez Demšar in sod. 2013. Orange: data mining toolbox in python. Journal bili začetnemu delotoku dodani dodatni gradniki, da bi rešili of Machine Learning Research, 14, 1, 2349–2353. določeno težavo ali zadovoljili posebne interese. 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Morgan Kaufmann. s področij, ki niso povezana z računalništvom. 50 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek B Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume B Kognitivna znanost Cognitive Science Uredniki / Editors Toma Strle, Borut Trpin, Olga Markič http://is.ijs.si 13. oktober 2022 / 13 October 2022 Ljubljana, Slovenija 51 52 PREDGOVOR Na tokratni konferenci Kognitivna znanost sodelujejo avtorice in avtorji, ki se raziskovalno ukvarjajo s kognitivno znanostjo, in predstavljajo tako empirične rezultate svojih raziskav kot tudi teoretska raziskovanja z najrazličnejših področij – od psihologije in nevroznanosti do filozofije in umetne inteligence. Poseben poudarek na letošnji konferenci posvečamo kognitivnim vidikom zaupanja v znanost, kar avtorice in avtorji naslavljajo tako z družbenega, političnega, psihološkega in filozofskega vidika. Upamo, da bo letošnja disciplinarno in metodološko bogata konferenca odprla prostor za povezovanje pronicljivih idej ter povezala domače in tuje, mlade in izkušene znanstvenice in znanstvenike, ki se ukvarjajo z vprašanji kognicije. Borut Trpin Toma Strle Olga Markič FOREWORD At this year’s Cognitive Science conference, the authors who actively research in scope of cognitive science present their empirical studies as well as theoretical research from a diverse range of disciplinary backgrounds – from psychology and neuroscience to philosophy and artificial intelligence. A special focus of this year’s conference is on cognitive aspects of trust in science. The authors address this topic from a social, political, psychological, and philosophical viewpoint. 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 local and international, junior and senior scientists from a diverse range of areas related to the exploration of the human mind. Borut Trpin Toma Strle Olga Markič 53 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Toma Strle, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Borut Trpin, Filozofska 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 54 Into the Constant Now—Comparing DES and micro- phenomenology, two methods for exploring consciousness Julian Bass-Krueger Elisa Wiedemann Ema Demšar MSc University of Vienna Department of Cognitive Science Centre for Consciousness and Vienna, Austria Central European University PU Co ntemplative Studies julianbassk@gmail.com Vienna, Austria Monash University wiedemann_elisa@phd.ceu.edu Melbourne, Australia em a.demsar@monash.edu ABSTRACT critiques and attempt to limit biases. Although validity cannot yet Here we compare two methods of examining conscious be proven, here we test the limits and constraints of these experience—Descriptive Experience Sampling (DES) and methods. Specifically, we look at Descriptive Experience micro-phenomenology. Both look at short episodes of Sampling, founded by Russell Hurlburt and refined with the aid experience. Both have safeguards to limit biases and distortions of fellow researchers [1]. And we’ll look at micro- from first-person reporting. But these methods are still different phenomenology—adapted by Claire Petimengin from Pierre in terms of how they deal with memory, questioning, and Vermersch’s explicitation interview [2]. analysis. In this pilot study (n=4), we use both methods in the Descriptive Experience Sampling uses random beeps to direct context of a common task. Participants were interviewed about participants towards specific, concrete episodes of experience. their experience of a mental imagery task using both methods. Micro-phenomenology guides participants to a state in which DES results focused more on fine-grained details of visual memory becomes immediate and lived. experiences. Micro-phenomenology results focused more on Both methods then use different means to aim for a common how experience extended over time, and how participants goal, of revealing short episodes of experience. Experience engaged with the task. These differences in results show that the described in the abstract is an amalgamation of warped memory, investigated methods differ in scope. To further address this, we self-perception, conceptual frames, and fleeting impressions. encourage a critical methodological pluralism where methods ‘This morning I had breakfast and felt sleepy.’ In the concrete, can continue to be improved and tested for validity. however, experience manifests as a flow of vivid nows. ‘ Now I’m watching the cream dissolve in my coffee. Now I’m picturing KEYWORDS what would happen if gravity reversed overnight and I had to Consciousness, inner experience, empirical phenomenology, rearrange my furniture on the ceiling.’ These nows, so vivid DES, micro-phenomenology when lived, can dissolve in memory like cream in coffee, so that we might forget their original color. Methods of empirical 1 BACKGROUND phenomenology aim for that color. Despite similar intentions, there has been some contention The study of first-person experience has had a difficult time. In between methods. Akhter and Hurlburt have questioned the the early 20th century a prolonged disagreement between two validity of micro-phenomenology [6]. Petitmengin has argued rival introspectionist camps led to the field’s essential banishing about DES that “the beeper is not suitable for observing very from psychology [1, 2]. A later influential study by Nisbett and brief or very fine subjective events” [7]. Is this disagreement Wilson [3] further solidified the notion that first-person data is warranted? Do methods really reveal different aspects of flawed and distorted by heuristics, overgeneralizations, and experience when used with a common task? And if so, does this memory problems. People simply don’t know what’s in their call into question the validity of one method or the other? consciousness. To give a pragmatic definition, for a conscious Methods might just have different scopes, yielding different person, there is something that it is like to be that person [4]. A results [8]. To address these questions, we compared methods conscious person might be sipping coffee noticing the rich smell with a shared task. and hearing birds chirp. An unconscious person could for example be in dreamless sleep. 2 METHODS Conscious experience takes up most of our day (presumably) and influences our identity and understanding of the world. It lies 2.1 DES behind our sensations, emotions, and thoughts. It is important. DES uses random beeps through the day to help participants And yet it’s often either assumed as trivial, approachable through better grasp their own experience. This can involve a specialized naive methods, or else unattainable, not worth even seeking to beeper or a smartphone. The participant must have an earpiece understand. New methods reject both premises–consciousness is directly in their ear throughout the procedure. The beeps are neither trivial nor unattainable. These methods attempt to delivered at randomized intervals ranging between five minutes systematize consciousness research, in a field that has been to one hour [9]. Six beeps are delivered a day. This usually takes dubbed “empirical phenomenology” [5]. They deal with past around three or four hours. In most studies, they occur during the 55 Information Society 2022, 13 October 2022, Ljubljana, Slovenia J. Bass-Krueger, E. Wiedemann, & E. Demšar participant’s daily life, not in a lab, to increase ecological elements in turn and ask questions to elicit greater specificity. validity. Micro-phenomenology aims for nuance. Questioning can often After each beep, the participant jots down notes on their inner focus on subtle emotional shifts of even shifts in body or posture experience right before the beep. So not inner experience during that contribute to experience. the beep (e.g., darn that’s annoying!) but right before. The goal There are no firm guidelines for how long a micro- is to describe that last uninterrupted moment before the beep. phenomenology interview lasts. However, it is not uncommon Usually this moment is much shorter than what participants first for short segments of experience to elicit hour-long interviews. have in mind, and can last a fraction of a second. The aim of micro-phenomenology is to uncover the complexity Questioning and training is needed in order to apprehend this and nuance of the experiential episode both at a particular moment. At the end of each day of sampling, participants are moment (synchronic dimension) and its development over time interviewed about the six beeps they collected. The interviews (diachronic dimension),with the focus of the interview last an hour and any samples not discussed within that time are depending on the research question of the particular study. discarded. There are always multiple days of sampling, usually around 5 or 6, but occasionally many more. The first day of 2.3 Main differences sampling is always discarded and considered training. Time - Micro-phenomenology typically deals with longer Subsequent days are often discarded as well, if they don’t hew to sections of time. Researchers can observe how elements change. validity criteria. Petitmengin writes, “To enter into contact with one’s experience, Validity depends primarily on participants’ ability to clearly it is necessary to respect its fluid and dynamic character” [11]. describe specific moments of experience with little hesitation and DES does also incorporate time though. Experience is not frozen equivocating language. Questioning aims to lead participants into a static snapshot. For example, if a person is innerly speaking away from generalizations. For example, a participant might first “I need to call mom” this might extend over time. And a fuzzy say, “I was driving and kinda nervous I think. I’m always nervous feeling in their chest might increase in strength over the moment. when I drive.” The use of the term ‘always’ may indicate that the The difference here is thus of degree, not of type. participant was generalizing. The use of terms ‘kinda’ and ‘I Retrospection - Micro-phenomenology, in general, involves think’ could indicate uncertainty stemming from lack of contact substantially more retrospection. The target experience could be with direct experience. Further questioning may reveal that years before the interview [11]. In DES, the target experience is experience before the beep was something completely a few seconds before the notetaking and less than 24 hours before different—perhaps a mental image of a fat squirrel with the inner the interview. There are still memory demands but they are speaking “munchy munch.” It is common in DES for results to fewer. However, as mentioned, micro-phenomenology can also go against participants’ initial expectations [9, 10]. be done with the target experience shortly before the interview 2.2 Micro-phenomenology [12]. This is the case for our comparison study. Micro-phenomenology aims to guide the participants towards Directing attention - Micro-phenomenology aims for an vividly reliving and precisely describing a past conscious episode evocation state in which participants re-live the original [7]. This episode is of underdetermined length, ranging from a experience. DES takes a more skeptical approach. DES questions few minutes to a few seconds. The episode can be in the recent encourage the participant to doubt if reported elements were past or have occurred many years ago. For the sake of bringing really part of their direct experience. DES acknowledges that this our methods as close as possible to compare them, here we’ll skepticism might lead it to miss out on elements of experience. apply micro-phenomenology to the recent past and to short But Hurlburt sees this as preferable to reporting elements that episodes (10 seconds). weren’t there [9]. Micro-phenomenology prefers having as full Memories can be indistinct, so micro-phenomenology aims to an impression of experience as possible. It offers participants guide the participant to an “evocation state” where past opportunities to revise and clarify their reports, but in service of experience is ‘re-lived’ [7]. Participants have direct contact with maintaining an evocation state, doesn’t ‘grill’ participants to the what they saw, heard, or felt at the time of the target experience. extent that DES does. Questions aim to ‘stabilize’ this evocation state and maintain the Questioning – Micro-phenomenology questioning is “non- participant’s contact with their experience. For example, inducive but directive” [7]. DES questioning is non-inducive and participants are periodically asked to return to the beginning of non-directive. For example, micro-phenomenology asks about the episode. If the participant digresses, the interviewer can specific sensory modalities in turn, i.e. ‘Do you hear anything?’ repeat the participant’s earlier descriptions. It holds that this is necessary to elicit greater detail since As in DES, participants are asked for greater specificity about participants may not know where to direct their attention. DES the elements they reveal. For example, if a participant has a would instead ask, ‘Was there anything else in your experience?’. mental image, an interviewer might ask, “Is it in colour or in In general, micro-phenomenology is more trusting of black and white? Is it detailed or fuzzy? Is it dark or light?” [7]. participant reports. DES places a greater emphasis on skepticism, Micro-phenomenology begins by eliciting the context and training participants in order to get greater fidelity. For example, sensory modalities of past experience—what participants saw, the first day of training is always discarded with DES. This is not heard, felt, etc. This helps the participant enter the evocation the case with micro-phenomenology. Training interviews are state. Once in this state, questions can be more open ended. occasionally used but optional. Interviewers can ask about the sequence of experience and how Validity - There is agreement between methods about how to different elements change over time. They then focus on specific judge validity. Both acknowledge that rules and explanations of 56 Into the Constant Now Information Society 2022, 13 October 2022, Ljubljana, Slovenia the method make their own case for validity. A successful the prompt to form mental images. They were interviewed sample/interview then depends on these guidelines being following the guidelines for micro-phenomenological interviews followed, and questions being suitably content-neutral and non- [7] after each prompt. E.W. conducted these interviews [Fig. 2]. leading. Other points of agreement include situating methods in a net of third-person observables—for example, can first-person Training data link with behavioral data? Can correlations be found with neuroimaging? No one correlation can address validity but networks of connections can help lead to first- and third- person methods informing each other through “mutual constraints” [13]. Differences include differing methods for judging veracity. Both methods rely on both verbal and non-verbal cues. But DES leans more heavily on verbal cues, like subjunctification [9]. Is the participant saying umm, I think, kindof, maybe, sorta, I Task guess? Then it’s likely they’re not describing direct experience. Micro-phenomenology relies more on visual cues—for example a participant’s eyes pointing upwards indicating that they’re in an evocation state. Petitmengin also advocates checking a participant’s reported experience against the researcher’s own experience, calling this the “kingpin of all validation” [7]. Is it similar or at least plausible? Hurlburt and Akhter [6] see this as harmful—a participants’ experience may be radically different from the Figure 1: DES training and task researcher’s, and so should be ‘bracketed’ as much as possible. 3 PROCEDURE This study involved four participants—a small sample size aimed at highlighting certain method contours rather than generalizing or making claims of statistical significance. All four were female students residing in Slovenia, aged 23 to 26. They are referred to here using pseudonyms. Each participant underwent both the DES and micro-phenomenology procedure. However, two started with micro-phenomenology and two started with DES (to limit biasing). There was a break (at least six days) before Figure 2: Micro-phenomenology training and task switching methods. To facilitate comparison, the interviews concerned participants’ experience of a task. We used a mental imagery 4 RESULTS elicitation task, in which participants were given descriptive 4.1 Similarities prompts and 10 seconds to form mental images. Examples of prompts include: “A child holds an ice cream cone with three Image characteristics - Both methods uncovered common visual scoops. The ice cream falls onto the hot pavement.” “A storm phenomena. One example of this is with GIF-like repetition. This cloud gathers over a city. A lightning bolt strikes.” may be something specific to our current digital age. These short, Before the task came training. For DES, this involved three repeating moving images are common on social media. Many days of DES sampling during the participant’s everyday life— older people in DES sampling have mental images in black and going to class, cafés, etc. Participants received six beeps a day, white [14]. The technologies of our age may shape our perception jotted down their consciousness experience in the moment before and perceptual cognition. the beep, and received hour-long interviews within 24 hours of Other commonalities include elements changing over time. sample collection [Fig. 1]. For both methods, images didn’t always emerge fully formed. For micro-phenomenology, training was much shorter. And micro-phenomenology further shows how images morphed Participants were given a task shortly before the main task—to or how new elements entered. For both methods, images could spell the word octopus. Participants were then interviewed to either be moving or static. give them some practice and familiarity with micro- With both methods, mental images had differing levels of phenomenology and the interview procedure [Fig. 2]. detail—inter- and intrasubject. Images were sometimes clear. For the task, the DES portion involved 32 pre-recorded Sometimes they were fuzzy, indistinct, ghostly, or blurry. Visual prompts. 10 seconds followed each prompt, allowing for mental elements were sometimes realistic and sometimes cartoonish. imagery formation. Five random beeps were interspersed Interactions with other modalities - Inner images could interact throughout the task, ranging from 1-10 seconds after the prompt with other types of experience. Both methods revealed words and concluded. There was a DES interview after each beep. J.B.-K. images interacting. Micro-phenomenology revealed participants conducted these interviews [Fig. 1]. sometimes innerly repeating words from the prompt. In one case, The micro-phenomenology task involved 2 prompts. These these words were a distraction from forming images. In another were on separate days. Participants again had 10 seconds after case, they spurred on a new visual perspective. 57 Information Society 2022, 13 October 2022, Ljubljana, Slovenia J. Bass-Krueger, E. Wiedemann, & E. Demšar For DES one participant misheard the word ‘chirp’ as ‘gerb’. —The task could involve constrained freedom or constraint. At the moment of the beep, she was innerly repeating it, Jelka felt constrained at times. She had to imagine things she wondering what it meant, and had a visual impression without wasn’t interested in. Anna, especially, felt freedom. She could any visual elements explicitly present—just a large mass. imagine whatever she wanted. Anna also played with the Images could also interact with feelings. DES found that 1/5 of prompts. For example, given a prompt about a boy with three samples involved feelings. These were sometimes positive in scoops of ice-cream, Anna imagined three ice-cream scoop tools. valence (‘calm’) or sometimes negative (‘dislike’). Certain We can see how she engaged with the task, lightheartedly testing prompts correlated with negative feelings—like the prompt “A how far she could push the prompts. DES could not have family gathers around the dinner table. The father starts serving revealed this entire sequence of trying out different visual food.” components. Micro-phenomenology also found feelings. For example, for a prompt about two children skating on a pond, Jelka added a 5 DISCUSSION mother to the scene and projected her own worry onto the Despite similarities, these methods have different scopes and mother. reveal different results. Micro-phenomenology revealed more temporal dynamics. We saw how images evolved over time, and 4.2 Differences how participants interacted with the prompts. DES revealed more Visual differences - While there were similarities concerning visual characteristics of images. This is contrary to Petitmengin’s mental imagery formation, there were differences as well. With comment concerning DES’s limited experiential detail: “I doubt DES, for Jelka, all 5 prompt samples involved imagery with a whether the beep enables the interviewee to direct his attention dual vantage point. She was both looking at the image from a from ‘what’ to ‘how’, unless by chance” [7]. It also goes against distance but at the same time had another vantage point of being claims from Froese, Seth, and Gould that DES adheres only to a surrounded by the scene. Think of simultaneously watching a “shallow conception of consciousness” [15]. movie on a screen and being in the movie as the main character. Note that methods differed in the treatment of fine-grained Since this dual vantage point was found in all of her samples, one details. DES revealed dual aspect imagery and micro- might expect it to be a generalizable feature of her mental phenomenology did not. This could have been the result of images. But micro-phenomenology didn’t find it. It found differing experience or a product of the research design where instances of 3rd and 1st person inner images for Jelka, but never training with one method alters reporting with the other method.1 both at the same time. Perhaps the dual vantage point was present It could also be a result of one or another method hewing more but not apprehended. closely to experience. If this is the case, we need to make sure DES findings focused more on characteristics of mental our methods are faithful. Methods that distort experience may images. lead to disagreements and stall progression of the study of —Images can have borders, no borders, or focus can be on the consciousness. For this reason, issues with retrospection, center so the participant is unsure of whether or not the image memory distortion, presuppositions, and biases need to be has edges. handled carefully. Practitioners of any method need to question —Images can be in a separate mental space or positioned over what its intent is, whether its guidelines are coherent, and what the real world, for instance on a “3D screen.” research questions it can and can’t answer. —Mental images can involve aspects that would be impossible Horizons are open for refinement of methods and in real physical space. experimentation. Emerging research is even combining elements —Two simultaneous visual spaces can be present at the same from micro-phenomenology and DES [16-19]. Oblak, for time. For example, Anna had one visual space of children skating example, combined influences from both methods for interviews on a frozen pond, and a separate space where she was creating a investigating experience during a visual-spatial memory task face to add to the children. [16]. Springinsfeld conducted micro-phenomenology inspired interviews shortly after targeted experience–aiming for Time – Micro-phenomenology focused more on experience interviews on the same day as a bulimic individual’s vomiting evolving over time. We can see how imagery changes. We can episodes, to minimize retrospection demands [17]. Caporusso see how participants interact with prompts, referring back to used DES-style beeps with an interview method hewing more them, and playing with them. We see the broader experience of closely to micro-phenomenology in order to better understand the task. sense of self and boundaries in daily life and compare this to —Some elements came naturally, others required concentration. experiences of boundary dissolution [18]. And Bass-Krueger —Elements could be disproportionate and not fit with the scene. adapted DES to a slightly wider temporal scope to investigate For example, Jelka imagined a tree with birds that didn’t fit with what is really meant by a ‘moment’ of experience [19]. Critical the rest of the scene. It was too big, and a different color. We see methodological pluralism is important going forward. We must how new elements enter and how they relate to previous acknowledge differing avenues of exploring lived experience, elements. while questioning where exactly these avenues lead us. 1 Procedurally, there seemed to have been an effect of experience with one method participant who started with the micro-phenomenological interviews and then on participants’ approach to the other (new) method of investigating experience. moved on to DES at first found the latter method ‘too skeptical’ and both required For instance, participants who started with DES and then moved on to the micro- at least as much training as participants with no prior experience with first-person phenomenological interviews approached their experience with more skepticism reporting. However, with such a small sample, it is hard to disentangle how and caution than those who started with micro-phenomenology. 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Phenomenology and the Cognitive Sciences, 1-29. https://doi.org/10.1007/s11097-021-09767-6 59 LTP and LTD dependence on spontaneous activity in hippocampal and cortical glutamate synapses and the role of anaesthetics in the study of plasticity and learning Maša Bratuša† MEi:CogSci University of Ljubljana Ljubljana Slovenia bratusa.masa@gmail.com ABSTRACT dendritic spines [2] and stimulate new AMPAr integration [3], with both of these processes being key criteria for The following article is a condensed version of a review successful LTP. paper which was motivated by the hypothesis put forward In their seminal work, Abraham and Goddard [4] showed by Benuskova and her colleagues that an ongoing pre- that there is otherwise a notable difference between and postsynaptic spontaneous activity (SA) determines homosynaptic and heterosynaptic plasticity: not only the degree of input-specific LTP elicited by “Homosynaptic plasticity occurs at synapses that were various plasticity-inducing protocols, but also the degree active during the induction. It is also called input-specific of associated LTD in neighbouring non-tetanized inputs. It or associative, governed by Hebbian-type learning rules. appears that understanding regularities of spontaneous Heterosynaptic plasticity can be induced by episodes of activity can help us define boundary conditions for both strong postsynaptic activity also at synapses that were not LTP/LTD induction and maintenance. We look into LTP active during the induction, thus making any synapse at a and LTD induction in excitatory glutamate synapses, their cell a target to heterosynaptic changes. Both forms can interrelatedness and connected non-glutamate plasticity. be induced by typical protocols and operate on the same We then assess the role of SA in plasticity and consider time scales but have differential computational properties what it means for in vitro studies where SA is limited. We and play different roles in learning systems. inquire how anaesthetics affect the general capacity for Homosynaptic plasticity mediates associative LTP and LTD induction and maintenance and we join this modifications of synaptic weights. Heterosynaptic with results on their effects on SA. All of this is taken plasticity counteracts runaway dynamics introduced by together in order to suggest protocols of notable Hebbian-type rules and balances synaptic changes." [5]. ecological validity and to provide an argument in favour of A conceptual shift in our understanding of “activity procedure standardization in the field. dependence” in heterosynaptic plasticity occured after the following experiment: Prior to stimulation the medial perforant pathway (MPP) and the lateral perforant path KEYWORDS (LPP) were equally weighted. With low-frequency Hippocampus, Cerebral Cortex, Anaesthesia, Sleep, stimulation spontaneous input activity was largely Spontaneous Activity, Synaptic Long-Term Potentiation correlated and only simultaneous or closely successive (LTP), Synaptic Long-Term Depression (LTD) spikes at these two inputs could fire the postsynaptic granule cell. Meanwhile high-frequency stimulation of the MPP decorrelated the activity between LPP and MPP, INTRODUCTION which lead to lower postsynaptic activity. Notably, there In the process of learning, there is both an increase of was no heterosynaptic LTD when the presynaptic electrochemical signalling in some synapses and a spontaneous activity was blocked [6]. This became known decrease thereof in others. Potentiation and depression as the Benuskova-Abraham model which explains include many physiological changes and are therefore "heterosynaptic" LTD as a homosynaptic phenomenon more stable over time in comparison to facilitation and due to presynaptic activity. inhibition [1]. The general understanding of Meanwhile, the baseline difference between LTP- and NMDA-dependent LTP is as follows: presynaptic LTD-inducing protocols can most simply be illustrated with stimulation opens postsynaptic NMDA channels which a difference in stimulation protocols: " 900 pulses of stimuli cause a rise in postsynaptic Ca2+. Strong depolarizations induced LTD when applied at lower frequencies (1–3 Hz), displace magnesium ions, which open more NMDA and induced LTP when applied at a higher frequency (30 channels in a positive feedback loop manner. The Hz).“ [7] postsynaptic neuron accepts even more Ca2+ ions, and All of the aforementioned considerations led researchers this superfluous concentration of Ca2+ then activates [8, 9] to investigate the role of background SA in memory CAMKII, increases cAMP and PKAII concentrations. formation. It should be noted that any activity which is not Activated CAMKII is known to increase the volume of the 60 Information Society 2022, 10–14 October 2022, Ljubljana, M. Bratuša Slovenia evoked by immediate sensory processing can be other, non-glutamate synapses – since these signalling considered as spontaneous [10, 11, 12]. The goal of our chains are extensively interdependent. Along with the review was to integrate evaluations of all known previously mentioned norepinephrine and dopamine processes that affect the animals ability to “create a receptors, endocannabinoid, GABA and various memory trace”, whether it is the physiological condition of acetylcholine receptors should be accounted for in order the animal or how the inquiry into physiological change is for us to be able to interpret and generalize our findings performed. [25]. Surveillance of tyrosine [25], serine [26], adenosine/ATP [27] and Ca2+ secretion [28] whether it be METHODS from neighbouring neurons or glial cells also appears to Data was collected from 232 peer-reviewed studies on play a vital role in outcomes of synaptic plasticity. excitatory glutamate synapses of granule cells in the Especially in the case of astrocytes, close monitoring of dentate gyrus, CA1 neurons of the hippocampus (HPC), glutamate secretion should not be neglected. As far as and cortical (CTX) networks, including those that dealt the author is aware, all of these recordings are not with developmental, pathophysiological and behavioural possible simultaneously - so a full analysis would require data. We also included computational studies of synaptic iterations of the same paradigm with different plasticity. In the process of integration, various types of permutations of controlled variables. Although genetic methodological differences had to be kept in mind. similarity of laboratory animals is regular practice, we have found evidence that conditions regarding nutrition, RESULTS and DISCUSSION activity, sleep and stress should be matched as closely as possible, as they all play a role in establishing baseline At the onset of writing we wanted to achieve a sound, stress levels and ionic/aminoacid signalling [29, 30]. precise and conclusive multivariate analysis. Yet this Stress/norepinephrine [31] minimization through ensuring numerical approach proved to be impossible due to environments that best resemble the ecological niche and overarching disparities in experimental protocols. The allow for natural behaviours is crucial both in terms of differences in methods and materials make these deriving inferences on physiological plasticity in humans experiments dissimilar to the point of barely studying the and ethical concerns. Due to dendrite [32] and button [33] same phenomenon at all, not to mention the consideration restructuring that occurs in synapses after the process of that plasticity phenomena are not a uniform class to begin learning, it would be advised to scan for their baseline with [13]. In the following sections, we are nevertheless structure since an intricate confluence of signalling chains able to provide some conclusions about which variables appears to take place at that scale. ought to be controlled for so that the experimental work is Thirdly, we have taken a stance that if we are to study ecologically valid while also giving results that are memory itself, we should focus on studies where it is available for inferences on subsequent, more complex represented as a "fully learned association with practical paradigms within the study of memory. effects" which can be doubtlessly confirmed only with Firstly, the evidence that SA plays a key role in induction experiments within behavioural paradigms [34, 35]. This and maintenance of proper strength of LTP and functionalist approach requires multiple-synapse learning concurring, homeostatic LTD is overwhelming [14, 15, with behavioural timescales (seconds-to-minutes). Not 16]. In order to provide a realistic picture of synaptic only that, but it is also unquestionably dependent on plasticity (in which SA is as natural as possible), replay during sleep [36], which means that an experiments on intact tissues should be given preference understanding of phosphorylations [37] and gene [17], since all nerve ablation limits physiological SA input. expression [38] is an indispensable part of the puzzle. If For example, when studying the CA1 region, its we are to understand memory, we ought to control for connections to CA3 [18], the dentate gyrus [19], the post-learning sleep duration and composition, but also for entorhinal CTX [20] and the medial prefrontal CTX [21] the quantity of operative gap junction [39] channels that ought to be maintained. Considering norepinephrine [7] extensively contribute to the plasticity-related signalling in and dopamine [22] modifications on glutamate-synapse sleep, both through slow oscillations and sharp-wave plasticity, there is good reason to believe that both the ripples [40]. amygdala and nucleus accumbens should remain In short, there is overwhelming evidence that SA within or connected to the HPC area under study. But when it outside the region of interest is crucial to synaptic comes to the CTX, the scope of kept projections largely plasticity in a myriad of forms (post-tetanic spiking [41], depends on the cortical region in question. Unsurprisingly, bursting [42], theta oscillations [43], slow oscillations [44] and in accordance with many authors referenced in the and sharp wave ripples [45, 46]) and that all of them full paper, a preference for in vivo recordings is advised should be taken into consideration. The more complex the [17, 23, 24]. Nevertheless, many authors agree that type of learning (declarative vs. nondeclarative, thoughtful attention to in vitro conditions could still prove behavioural sequences vs. single behaviours, simple fruitful. classical conditioning vs. nonassociative learning), the Secondly, no matter the nature of the preparation, we larger the region of interest and the more notable the would do best to also keep track of what is happening on effect of these sleep phenomena. This compounding of 61 LTP and LTD dependence on spontaneous activity in glutamate synapses of the HPC and CTX and the role of Information Society 2022, 10–14 October 2022, Ljubljana, anaesthetics Slovenia complexity also applies to most previously mentioned Aplysia.” Journal of Neuroscience 30 (16): 5781–91. signalling, as the area of messenger perfusion also https://doi.org/10.1523/jneurosci.4947-09.2010. [2] Pi, Hyun Jae, Nikolai Otmakhov, Farida El Gaamouch, David grows. 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Reid, and Alan Fine. 2001. _on_spontaneous_activity_in_glutamate_synapses_of_the_HPC_ “Calcium Stores in Hippocampal Synaptic Boutons Mediate and_CTX_and_the_role_of_anaesthetics Short-Term Plasticity, Store-Operated Ca2+ Entry, and 63 Trusted sources and disinformation: studying the limits of science* Rita Gsenger Weizenbaum Institute, Humboldt University Berlin Berlin, Germany rita.gsenger@hu-berlin.de ABSTRACT Disinformation often speaks to human emotions and touches upon controversial or ideologically charged topics [5] as “people During the Covid-19 pandemic, the spread of disinformation have a taste, a predisposition even, for it” [5, p. 57], and virality became more apparent. Much of that disinformation focused on helps content to be distributed widely [6]. As soon as such topics health-related topics and the current health crisis, often claiming are concerned, the content is often not that important to be to be scientific information. Trusting scientists became crucial to empirically correct and reasonable. However, a social identity is counter the pandemic effectively as a society; however, science- afforded by believing that content is valuable [7]. Making certain related disinformation and so-called pseudoscience provided beliefs their identity does not only lead to an ignorance of facts new challenges for societies. These beliefs often overlap with (ibid.), but it also enables people to think along ideologically other types of disinformation and conspirational thinking, polarised lines with affective disdain for outgroup beliefs [8]. making them very attractive to human cognition. Twenty semi- Therefore, believing, for instance, that the earth is flat goes structured interviews were done in 2020 to investigate beyond holding a belief but is used to form identities. Around individuals' trust in science, governments, and media. The these identities, movements are formed, and, in the case of flat interviews focused on information sources and the conclusions earthers, for instance, people are willing to lose their jobs, drawn from the situation to determine how individuals estimate friends, and family relations to be part of the group [7]. information sources' trustworthiness. A kind of disinformation that has become crucial, especially during the Covid-19 pandemic, has been dubbed pseudoscience. KEYWORDS Pseudoscience, disinformation, Covid-19, trust 1.2 What is pseudoscience? 1 DISINFORMATION AND PSEUDOSCIENCE Distinguishing science from pseudoscience is not a simple endeavour. Some paradigmatic cases might exist where 1.1 Dimensions of disinformation philosophers and scientists agree, but other examples remain undecided or on the fringes of science. Ultimately, the question Disinformation is most commonly defined as false information of defining science and delimitating it from non-science comes that is deliberately propagated and distributed [1, 2, 3, 4]. The down to a fundamental question of philosophy, mainly what concept of disinformation includes various dimensions and knowledge is and how we attain it [9]. Pseudoscience can be aspects, which often overlap and influence each other [1, 3]. understood as a discourse about a specific subject matter, and Kapantai et al. (2020) developed a taxonomical framework to what is considered pseudoscience, like science, changes [10]. include important types of disinformation, including the motive Defining pseudoscience often “involves subjects that are either (profit, ideological, psychological, and unclear), facticity, and on the margins or borderlands of science and are not yet proven, verifiability as dimensions. That resulted in eleven kinds of or have been disproved, or make claims that sound scientific but disinformation, including, for instance, conspiracy theories, in fact have no relationship to science” [11, p. 203]. Several pseudoscience, hoaxes, trolling, or clickbait. Disinformation can characteristics can be identified to designate the likelihood of also be partly true to make it more credible [5]. adherence to pseudoscientific or non-scientific claims. For example, the language used to describe the phenomenon or ∗This abstract is partly based on the author’s Master thesis: Digital Literacy and Pseudoscience in Crisis Response. The Case of COVID-19 in Austria (University of research results often indicates the credibility of the reported Vienna 2021). results or evidence. The excessive use of technical terms and scientifically sounding language, for instance, in press releases, 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 might lead to trust and acceptance of the presented results due to for profit or commercial advantage and that copies bear this notice and the full the impression of smart people doing important work. These are, 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). however, not doing a great job in communicating science, and Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 64 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Rita Gsenger more importantly, some elements of good scientific practice can 2.2 Results: “I don’t know what to believe be commonly understood [12]. Pseudoscientific theories often anymore”: doubt and trust in times of crises use language full of epithets and refer to emotions and religion or use ideological markers.The presentations often include theses Participants used various sources of information about the and evaluations presented as unequivocal [13]. The method used Covid-19 pandemic, including online sources, TV, radio and might not be scientifically sound. For instance, anecdotal conversations with friends and family. When asked about the evidence and not controlling for other variables, very small or sources participants considered trustworthy or not to provide unrepresentative sample sizes in establishing causal information about the Covid-19 pandemic, various categories relationships, lack of control groups, or blind testing might were mentioned, including the media, social media, social indicate unsound methods. Moreover, many pseudoscientific contacts, and the government. However, the trust did not seem to studies tend to select parts of their evidence, which allows for a be easily acquired or granted among participants. Social aspects very charitable interpretation of studies to support a predefined were considered influential in attributing trustworthiness (P3, conclusion [12]. As there is not one comprehensive definition of P6). Therefore, a reason to trust a source would be that people pseudoscience, issues fall more or less under its spectrum. I will from an individual’s social circle would also trust it (P3, P6, P19). consider the above-outlined characteristics during my empirical Furthermore, authenticity and “thinking outside the box” (P13) investigation. Pseudoscience and science are historical were considered trustworthy traits of people. Some said they phenomena that inform the decisions societies make about what would trust family members, doctors or journalists they knew is considered the truth. Attempting to define pseudoscience personally (P2, P11). involves making claims about the nature of science. Overall, no methodology has been developed that allows for a general and comprehensive distinction [10], with Popper’s principle of Participants trust media if they provide sources with more falsifiability [14] not solving the problem satisfactorily [15]. In a information about the topic in question (P3), including links to culture that highly values science, other domains such as religion, other trusted websites (P4). Furthermore, if the information could politics, or literature are often closely associated with science and be cross-referenced with scientific sources (P14), and if scientists, seem to borrow scientific language, theories, or methods [11]. experts, or studies are included (P20), the trust in media sources Later, theories might be reevaluated and reclassified as science is increased. Furthermore, including various opinions was or pseudoscience [10]. Pseudoscientific beliefs are not a considered a sign of trustworthiness (P6, P1). These opinions marginal phenomenon and influence public policies [9, 16]. For permit looking at a subject from multiple viewpoints (P3) and example, during the Covid- 19 pandemic, pseudoscientific discussions by different people (P3, P14). The content would not explanations for the causes and cures of the virus surged [17]. be considered trustworthy if a personal opinion were presented Therefore, these beliefs, especially in crises, when public as objective truth (P3). Furthermore, the presentation of policies might be more crucial to follow, and such beliefs could information in the media and on the internet influences the be detrimental to society. However, belief acquisition is not attribution of trustworthiness. Accordingly, the way people post always easy, as human beings are prone to biases and faulty something, specifically the language (P14), if they write whole conclusions. sentences and if they explain the context of an article (P4) or if something is not formulated blatantly (P18) and frequently based on emotion (P5) it is considered more trustworthy. However, 2 STUDYING THE LIMITS OF SCIENCE trust was not attributed without reservation for many participants as they perceived the media as having their agenda (P8, P13) and 2.1 Method and participants being prejudiced (P14), but still more trustworthy than social media (P8). On the other hand, some did not consider the media Twenty semi-structured [18] and problem-centred qualitative “a source to find out what is really happening” (P13), and one interviews [19] were conducted in November and December participant mentioned that they “don’t believe anything anymore” 2020 with Austrian volunteers (N=20, 16 female, age 19-65, SD because “[...] it is not explained what the numbers mean at all or = 13.8). Interviews were led in German, and the author translated put into a context from which area the numbers come from and quotes. Interview participants were volunteers. Therefore, the how they were created at all” (P16). Social media was not researcher did not have much influence on their gender. However, considered trustworthy because a lot of information originates gender was determined not to be a crucial influence on the study. from private individuals (P19). Moreover, assessing the The discussions included several topics. However, only one part trustworthiness of information on social media is challenging focusing on trust and attitude towards the government, scientists (P1), even though most participants considered some people they and media is contained in this paper. Some limitations must be were friends with on Facebook trustworthy (P3, P4, P15). Some outlined when doing qualitative interviews online. Conducting participants based their trust on intuition and how they felt interviews online limits the information transmission compared regarding the media and online information. One participant to real life interviewing face-to-face. The qualitative study was described it as follows: “When I open that, how does it ‘feel’ if I done at a specific moment of the pandemic and thus only reflects move towards a platform, then I read how the information is participants’ attitudes during that time. Furthermore, participants structured, and I read the first paragraphs, and when something might be hesitant to share pseudoscientific beliefs or denial of is in there that seems a bit strange to me, then I would get out of science with a researcher. Therefore, no outright questions about there and look it up somewhere else. So, it depends on how it is such ideas were asked. in a textual sense and how the information lies in front of me” 65 Trusted sources and disinformation Information Society 2022, 10-14 October 2022, Ljubljana, Slovenia (P15). More specific descriptions of that feeling included if Moreover, participants observed how people changed and something seemed “out of touch with reality” (P5), what sounds suddenly believed entirely different things (P16, P2, P8). reasonable (P3), to use one’s common sense or if it appears According to participants, everybody should state their opinion strange (P18). Participants furthermore attributed trustworthiness but has the responsibility to do it respectfully (P15). An to sources or information that would confirm a worldview. individual’s history is crucial to consider to make respectful Accordingly, a participant described that other people with interaction easier (P2). Participants elaborated more in detail on differing worldviews would find different information how they formed their own opinions about the measures, the trustworthy and objective (P6). Additionally, reputation was a communication, and the pandemic in general. Some attributed source of trustworthiness, especially in the media (P10, P19). the decision to believe the information from a source to intuition Some participants mentioned the government and ministries as (P12) or if it seems strange (P20), as highlighted previously in trustworthy sources of information. One participant said, “in the section 6.4.1. Furthermore, they highlighted the influence of last months, I have experienced things where I was not sure in social factors, such as the influence of people they would talk to the moment can I trust anyone, and this is now a purely emotional (P5), for instance, in their workplace or people who had the thing because you cannot know anything anyway” (P8). illness (P14), even if they disagreed with them (P5). They would Furthermore, a participant claimed that “somebody is telling me, like to discuss these issues among their circle of friends as some I cannot go to university anymore, that I cannot see people would be more active and critical and might introduce other anymore, who is that somebody who would permit that, who perspectives (P14). If some- thing seems strange, however, they decides about me, that I cannot do that anymore” (P5). Some would try to find other opinions (P20), and online they would participants showed understanding of the difficult decisions the follow links from friends (P9) or try and consume contrary government needs to take right now, claiming as they would not opinions (P5). Overall, participants would form their opinions by want to be in their position or get involved, they would need to combining various other opinions (P8), questioning their comply with measures (P11). worldview, and staying open for new information (P14), and reflect on it (P5). Participants highlighted difficulties with Furthermore, some participants claimed that everybody would opinion formation about the Covid-19 pandemic, as one need to find their way of dealing with the situation and meet as participant summarized: “I believe a big problem is that there are many people as they would think appropriate (P14), emphasizing so many people, where it is claimed, ok, I am a doctor in that area, the responsibility of individuals (P5, P14). Many participants and I say this and that. And the doctor then says that and you mentioned the adverse consequences of the measures. Some don’t know, is that person really a doctor, do they really know agreed that these consequences, including the dangers of a about that. I mean, probably they are doctors but did they actually lockdown (P1), were not discussed enough (P1, P2, P16, P17). engage with that issue, or are they just saying anything? There Some were worried about restricting civil rights during the are so many doctors that have different areas of expertise and, of lockdown and possible dangers to democracy (P9, P1), claiming course, various experiences and a different level of knowledge, that the government could not implement a curfew as it violated so you don’t know where the information is coming from” (P16). human rights (P1). Participants wished that people were given more credit (P20, P13), which included telling them to take care 3 DISCUSSION AND CONCLUSION of their immune system and take vitamins (P13). Another participant would have wanted different perspectives on the Participants highlighted some specific topics as instilling the transformation happening in 2020, as communication is most significant doubts about trustworthy sources considering changing and more telepathy will be possible due to that change the Covid-19 pandemic. Science was considered a trusted source, (P5). According to participant 13, not discussing alternative ways but various indications showed that participants had significant of handling the pandemic can be attributed to international doubts regarding the scientific consensus about Covid-19, for pressure (P13). instance, that they would not know what it really was (P1) and that it was the flu, which is unpleasant but not particularly The plurality of opinions is generally valued highly among dangerous (P13). Tests to determine infections were doubted in participants as it is essential that everybody can share their their validity and efficacy (P16) and are considered inaccurate standpoint and how they arrive at their conclusions because (P13). Even though the interviews were led before Covid-19 everybody has a good reason to think as they do (P2, P1). vaccinations were widely available, mandatory vaccinations However, according to some participants, not all opinions and were already a big concern for some participants, which are standpoints were listened to somewhat during the pandemic. For thought to change society (P11) and should be well prepared to instance, the questions “masks yes or no these questions are not take people’s fears about the vaccinations (P20) as chaos might allowed to be asked because we are being beaten down by all ensue if vaccinations become mandatory (P12). Furthermore, the these numbers” (P13), and they should listen to people who have topic of not being told everything was present regarding the issue other methods (P14). Some observed that a division between of vaccinations. Participants worried about what would happen opinions and people was taking place in the general society. In to the Austrian culture and the country if vaccinations were that regard, only two contrary camps seemed to exist, and only mandatory (P11). An electronic compulsory vaccination to “be for Corona or against, a middle course or a differentiated certificate was mentioned as a source of worry for a functioning account was not possible” (P17). That means, participants were peaceful democracy (P9). Various conspirational elements worried that a nuanced debate about issues regarding the seemed to be present during interviews. For example, some pandemic was more difficult. participants were worried about democracy and the rule of law in 66 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Rita Gsenger Austria. One mentioned that a friend who is a doctor told them [3] E. Kapantai, A. Christopoulou, C. Berberidis and V. 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Specifically, I focus on the problem briefly introduce the problem of opaqueness or the so-called back- of opacity in such systems and argue that although using deep box problem. Then, I will present a paper by Erasmus et al. [6] neural networks in cognitive science can produce better results, which provides a detailed analysis of the notions of explanation it can also acts as a barrier to gaining new understanding of and understanding that are central to thinking about the problem. cognitive processes. After that, I will present Florian J. Boge’s [3] argument that we KEYWORDS can talk about two distinct dimensions of opacity in ANNs. In the last section, Mazviita Chimirmuuta’s [5] argument about explanation, understanding, scientific discovery, artificial neural the implications of the trade-off between predictive accuracy networks, black-box problem and opacity for research in computational neuroscience will be presented. 1 INTRODUCTION Early on in their inception, connectionist approaches in cog- 2 BLACK BOX PROBLEM nitive science faced challenges from proponents of competing Let us first turn to the problem of opaqueness. Authors of one approaches. One of the leading theorists of the classical symbolic of the review papers [10] from the field of explainable AI (XAI) approach, J. Fodor and Z. Pylyshyn [7], for example, argued that note that the “predictive accuracy [of machine learning systems] connectionism could not account for four essential properties has often been achieved through increased model complexity.” of cognition – i.e., productivity, systematicity, compositionality, This increased complexity, “combined with the fact that vast and coherence – and thus was not a sufficient theory of the mind. amounts of data are used to train and develops such complex We now have good reasons to believe that their argument does systems” has inherently reduced researches’ ability to “explain not hold [11]. Indeed, in their demonstration of the supposed the inner workings and mechanisms” of these systems. As a inadequacy of connectionist models, Fodor and Pylyshyn only result, “the rationale behind decisions [of these systems] becomes considered very simple models with local representations. But it quite hard to understand and, therefore, their predictions hard turns out that more complex models with distributed represen- to interpret.” Therefore, they say that “there is clear trade-off tations can satisfactorily solve the explanatory task. Contrary between the performance of a machine learning model and its to what Fodor and Pylyshyn claimed, we can therefore show ability to produce explainable and interpretable predictions.” The that even connectionist cognitive models are powerful enough authors of anther review paper [1] reached a similar conclusion: to exhibit the required properties. “Indeed, there are algorithms that are more interpretable than Fast forward forty or so years in the future, scientists using others are, and there is often a tradeoff between accuracy and artificial neural networks (ANNs) and deep learning to study interpretability: the most accurate AI/ML models usually are cognitive functions now face a different problem. One of the not very explainable (for example, deep neural nets, boosted key advantages of present day ANNs that use deep learning is trees, random forests, and support vector machines), and the their increased complexity and depth [4]. But because of their most interpretable models usually are less accurate (for example, increased complexity, such systems can become opaque in a way linear or logistic regression).” that even the researchers developing them do not understand Authors of [10] thus distinguish between "black-box" models, some key aspects of how they work [10]. Present day ANNs can which have state-of-the-art performance but are opaque, and thus be used to model cognitive functions much more successfully "white-box" or "glass-box" models, which are more easily in- than before, but because of their opaqueness, it is unclear what terpretable, but not as powerful. In her paper, Chirmuuta [5] 1 new insights such successes are generating [5]. If researchers in also specifies which aspects of deep neural networks suffer from opaqueness. She argues that scientists have a good understanding 1 In contrast to this, Sullivan [14] argues that the problem of contemporary ANNs of “internal architecture and workings” of the systems, i.e., they is not their opacity, but “a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon.” But see Räz and Breisbart know the activation values of the units, the learning rule, the depth of the network and the connectivity between the layers. Permission to make digital or hard copies of part or all of this work for personal But they do not know exactly how an already trained network or classroom use is granted without fee provided that copies are not made or arrives at a prediction or classification. 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). [13] for an argument that her point rests on a weak and thus undesirable notion of understanding. 68 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Martin Justin 3 EXPLANATION AND UNDERSTANDING world”, and thus involves giving information about the causal process and the causal interaction that leads to the emergence The black box problem or the problem of opaqueness has re- of the explanandum. (IV) New Mechanist model which takes as sulted in increased attention to research in explainable AI. But explanans the entities and their activities that are responsible for one salient feature of the literature on explainable AI is the impre- 3 the emergence of the explanandum. cise or even interchangeable use of the concepts of explainability, Erasmus et al. [6] then argue (b) that the increased complexity intelligibility and interpretability. This is also recognized by the of the phenomenon we are trying to explain (or of the concepts researchers themselves. For example, the authors [10] observe and data we use to explain it) does not affect our ability to offer that there is “no concrete mathematical definition of the concepts an explanation for the phenomenon. And (c) that deep neural net- of explainability and interpretability.” Nevertheless, they make a works can be explained in all four of the ways described above. conceptual distinction between these two terms. Interpretability, The argument for (b) is quite simple: Deductive Nomological on the one hand, is understood in connection to the ability of explanation, for example, requires only that the explanans con- researchers to intuitively understand the relationship between tains a law, and that the process of explanation takes the form inputs and outputs of a system. Explainability, on the other hand, of deductive reasoning. It does not matter how complex the two is understood in relation to the ability to understand the inner elements are. Thus, an explanation that contains a more complex workings of a system. In contrast, authors of a different similar explanans and requires more complex reasoning may be less study [9] define explainability as possibility to provide a satis- desirable, but it is no less an explanation. factory answer to the "why" question regarding the functioning The argument for (c) is a bit more technical. To demonstrate of a system. They also make a difference between two levels of this point, the authors provide an example of an explanation of explanation, connected to two different questions scientists can how an ANN, trained to identify dense breast tissue on X-ray ask about a system. Namely, “why does this particular input lead images, classify these images [6]. Let us see how a Deductive to that particular output?” i.e., a question about the relationship Nomological explanations of such ANN could work. As the em- between inputs and outputs, and “what information does the pirical content of the explanans, we could use all the information network contain?” i.e., a question about the internal workings of about the activation values of the individual units in the network a system. and about the weights between them, as well as the numerical In their paper, Erasmus et al. [6] point to this shortcoming values of the input data. We could also form a law-like proposi- of the literature on explainable AI and argue that this imprecise tion of the form “outputs with such and such numerical value use of the terms leads to a misunderstanding of the trade-off are classified as such and such.” In this way, the explanandum, between performance and explainability of AI systems. Their i.e., the classification of the photograph F into the class r, would argument proceeds in three steps. First, they offer a more pre- be explained using an explanans consisting of a law-like prepo- cise analysis of the notions of explanation and understanding. sition and empirical content. In other words, we would have a Second, they show that the increased complexity of systems af- 2 Deductive Nomological explanation. Although the arguments for fects their undersandability rather than their explainability. And (b) and (c) were presented only for the case of Deductive Nomo- third, they offer a typology of possible explanatory methods that logical explanation, authors argue they apply mutatis mutandis could also increase the intelligibility of systems. Here, I will be to other models of explanation as well. interested mainly in the first and the second step. Therefore, in Let us now turn to (d), the definition of understanding. As the remainder of this section I will first present (a) their defini- Erasmus et al. [6] point out, authors who study understanding tion of explanation, (b) their arguments that the possibility of do not, of course, entirely agree on its exact definition, but they explanation is independent of the complexity of the phenomenon commonly observe that, while explanation is necessary for un- itself, and (c) the argument that ANNs can be explained. Then derstanding, it is not sufficient for it. So to gain understanding I will present (d) their definition of understanding and (e) their of a phenomenon, some other conditions besides having an ex- argument that complexity affects the ability to understand. planation must be met. There are several candidates for these Let us start with (a). In defining the notion of explanation, additional conditions in the literature, but, as Erasmus et al. argue, Erasmus et al. [6] draw on a longer tradition in philosophy of they all have in common that they are “psychological traits of the science which holds that explanation consists of three elements: user of the explanation.” One such condition is the criterion of (1) the explanandum, i.e., what we want to explain, (2) the ex- planans intelligibility. It states that a theory T is intelligible to a scientist , i.e., with what we are explaining, and (3) the process of explanation in a context C if the scientist is able to recognize the qualitatively . Different models of explanations differ in one or distinct consequences of T without doing the exact calculations more of these elements. Four such models feature prominently 4 [5, 6]. Given this, it is obvious that increased complexity of an in the literature. (I) Deductive Nomological model, in which the explanation or a phenomenon makes it less intelligible and thus explanans includes empirical content plus a law-like preposition, less understandable. Thus, it can be concluded that (e) complexity and the process of explanation takes the form of deductive rea- affects the ability to understand. soning. (II) Inductive Statistical model, in which the explanans includes a statistical law about behavior of the variables, and 4 TWO DIMENSIONS OF OPACITY the process of explanation takes the form of inductive or proba- bilistic reasoning. (III) Causal Mechanical model which aims to Erasmus et al. [6] argue that while the workings of deep neural show “how the explanandum fits into the causal structure of the networks are explainable, they are often not understandable for 2 3 See Beisbart and Räz [2] for a critique of this point. They say that “the distinction Woodword and Ross [17] present a slightly different typology. In particular, they that Erasmus et al. draw between interpretability and explainability in this way add Salmon’s statistical relevance model and pragmatic models of explanation. 4 seems rather stipulative.” In contrast, they argue that we should use these terms as Chirimuuta [5] also lists four properties of a theory (or an explanation) that affect synonyms. Nevertheless, I think that Erasmus et al. [6] point to an important and its intelligibility. Those are: (1) the possibility of visualization, (2) the simplicity of well established concetpual distinction between these two terms which should not included theoretical assumptions, (3) the linearity of mathematical operations, and be so easily dismissed. (4) functional transparency. 69 Opacity and understanding in ANNs Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia human users. In other words, they conclude that we should talk using a w-opaque deep neural network; (c) finally, I will present about a trade-off between the performance of AI systems and Chirimuuta’s version of the trade-off between performance and their understandability or intelligibility, not their explainability. understanding that arises when using ANNs in science. Nevertheless, they seem to overlook another important aspect Let us start with (a). Chirimuuta [5] defines computational of the trade-off. As it is apparent from the definitions of explain- neuroscience as “a tradition of research that builds mathematical ability and understandability in Gilpin et al. [9] and Linardatos models of neurons’ response profiles, aiming both at predictive et al. [10], there seem to be different ways in which ANNs can accuracy and at theoretical understanding of the computations be opaque to humans. performed by classes of neurons.” It is based on the assumption This point is explicated and extended upon by Boge [3]. In that information about the external world is ‘encoded’ in the elec- his paper, he presents the following three theses: (1) deep neural trical and chemical signals of the neurons. It attempts to solve the networks are instrumental, and their instrumentality is distinct so-called ‘decoding problem’, i.e., it tries to find a mathematical from that of other mathematical models; (2) deep neural networks function that could successfully link neuron spikes to outside are opaque in two different ways; and (3) the combination of (1) information. Specifically, according to Chirimuuta, scientists try and (2) means that in the future, we may not be able to understand to devise a theory of how neurons encode information about the potential new discoveries made by deep neural networks. In the outside world and then write a program, called an encoder, that rest of this section, I will be primarily interested in (2). performs the translation operation between the stimuli and the Boge [3] begins his exposition of the two aspects of opacity neural activity. by defining opacity. He defines it as follows: “a process P is Thus, as Chirimuuta [5] points out, computational neuro- epistemologically opaque to a subject X at time t if and only if science pursues two separate epistemic goals. On the one hand, it X does not know all the epistemically relevant elements of the aims at accurately predicting the relations between neural activ- process P at time t.” He then distinguishes between two aspects of ity and external stimuli (e.g., to predict how neurons will fire if the opacity of deep neural networks. First, he describes h-opacity. we show a picture of a square to a primate). On the other hand, it It concerns the operation of a system: a system is h-opaque if tries to understand how this translation takes place. Chirimuuta it is the process of its operation that is not not intelligible to its thus argues that in the past, when even very simple linear models human users. This is the opacity that results from the complexity have proved surprisingly accurate in certain contexts, there has of deep neural networks and hiders the understanding of the been a convergence between these two goals. However, with the connection between input and output data. But as Boge notes, development of deep neural networks, which are much more this type of opacity is not qualitatively different from, say, the accurate but w-opaque, these two goals started to diverge. opacity of other complex computational simulations, e.g., climate Chirimuuta [5] presents two examples of such divergence, simulations. He therefore identifies another aspect of opacity one from modeling the functioning of the motor cortex and an- that is specific to deep neural networks. This is w-opacity, which other from modeling the visual perception system. I will limit my concerns the representational content of the system (what was presentation to the former, i.e., to her comparison between two learned). According to Boge, in deep neural networks, not just the studies that tried to model motor cortex activity, Georgopoulos process that takes a neural network from an input to an output, et al. [8] and Sussillo et al. [15]. In both of these two experiments, but also the properties of the input data that guide this process researchers measured the activity of individual neurons in non- are opaque. human primates while the primates were performing given tasks. This difference is important as it points to a specific problem Georgopoulos et al. [8] present an experiment in which a monkey that the use of deep neural networks introduces to scientific was surrounded by eight buttons, with another button straight research. H-opacity only hinders the understanding of the com- ahead. In the experiment, first the button in front of the monkey putational model itself, as it prevents researchers from seeing lit up. After the monkey held it for one second, one of the other how it gets from input to output data. Such opacity can thus be eight buttons lit up, and the monkey had to press it with the problematic form an ethical point of view, as it makes it harder same hand. Meanwhile, the scientists measured the activity of a to justify the decisions made on the basis of a recommendation population of neurons in her motor cortex, and tried to establish by an AI system. In contrast to this, w-opacity reduces the po- a correlation between this activity and the direction of her arm tential of deep neural networks to bring new understanding to movement. They did this by simply converting the activity of a the processes studied by the scientists. Even in the case where neuron into a vector in three-dimensional space according to a promising results would suggest that an ANN represents a given formula they devised, and then summing the vectors of the indi- problem space in a better way than existing theories, w-opacity vidual neuronal cells to obtain one vector that represented the would leave this representation incomprehensible to scientists. whole neuron population. They found out that the direction of Thus, w-opacity has important implications for the use of neural this vector quite closely matched the direction of arm movement. networks in scientific research. Because of the fairly simple math they used, their model was completely transparent. In addition, the researchers themselves determined which information about the neural activity is im- 5 PREDICTION VERSUS UNDERSTANDING portant and should be used to calculate the movement vector. The implications of w-opacity for research in computational neu- The accuracy achieved by the model can thus be seen as a partial roscience are convincingly presented by Chirimuuta [5]. In this confirmation that these features of neural activity are indeed section, I will summarize her findings. I will do this in the fol- important for directing arm movement. lowing steps: (a) first, I will briefly outline the research program The experiment reported by Sussillo et al. [15] is a bit different. of computational neuroscience; (b) then, I will present exam- They also had non-human primates, this time two, implanted ples of two studies from the field, one in which scientists ap- with electrodes that measured the activity of individual neurons proached their problem using a transparent mathematical model, in their motor cortex. But the monkeys did not press buttons; and another in which they approached a very similar problem rather, they had to move a cursor on a screen from a central 70 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Martin Justin position to a marked position in one of the corners of the screen. shown in more detail what philosophers mean when they talk Each monkey performed three series of experiments. First, they about the trade-off between performance and intelligibility (or moved the cursor by moving their hand. Then, they moved the understandability) of AI systems in science. cursor using a brain-machine interface (BMI) that used a encoder, based on a mathematical model, similar to the one described in ACKNOWLEDGMENTS the previous example. In the last series, they used a BMI that en- I would like to thank Olga Markič for her useful suggestions and coded information using a trained neural network. Each monkey encouragement. I would also like to thank Nejc for his help with performed each of the three experiments hundreds of times. The the more technical aspects of the literature. researchers found that using this ANN based encoder significanty improved monkey’s performance vis-à-vis the older model. This REFERENCES suggests that the BMI with an ANN was more successful in trans- [1] Amina Adadi and Mohammed Berrada. 2018. Peeking Inside the Black-Box: lating between neuronal activation and information about the A Survey on Explainable Artificial Intelligence (XAI). IEEE Access, 6, 52138– 52160. doi: 10.1109/ACCESS.2018.2870052. outside world. We can thus assume that the ANN either approxi- [2] Claus Beisbart and Tim Räz. 2022. Philosophy of science at sea: Clarifying mated the mathematical function linking neuronal activation and the interpretability of machine learning. 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(2021). is not hard to see how focusing on predictive accuracy, rather Retrieved Jan. 29, 2022 from https://plato.stanf ord.edu/entries/scientif ic- ex planation/. than understanding, could further increase the unwanted hype surrounding scientific research. 6 CONCLUSION In this paper, I reviewed some of the emerging literature on the epistemological aspects of the problem of opaqueness in deep neural networks. First, I used Erasmus et al. [6] to point out that we need to distinguish between explainability and understand- ability of AI systems. I also presented their argument that the increasing complexity of these systems has a particular impact on our ability to understand them, not on their inherent explanaibil- ity. Then, with the help of Boge [3], I distinguished between two dimensions of opacity of these systems. Finally, following Chir- imuuta [5], I presented this problem using a concrete example of two studies in computational neuroscience. In this way, I have 71 Politizirana znanost in zaupanje v znanost kot politična uniforma Politicized science and trust in science as a political uniform Jar Žiga Marušič† Famnit, Univerza na Primorskem Oddelek za psihologijo Koper, Slovenija jar.marusic@famnit.upr.si POVZETEK of trust in science in practice – endorsement of the process of scientific research, or an expression of political conformity? Zaupanje v znanost je dandanes, sploh po dveh letih pandemije Covida-19, posebej družbeno relevanten problem. Izraz pa je KEYWORDS nekoliko dvoumen, saj lahko znanost razumemo na več načinov, med drugim kot raziskovalni proces in kot institucije, na katerih Politicization of science, Covid-19, trust in science, social se ta proces odvija. Zato je izraz zaupanje v znanost lebdeči reasoning, psychological inoculation označevalec, oznaka brez jasnega referentnega objekta.. Težava lebdečih označevalcev se pokaže, ko postanejo tarča politizacije. 1 Kaj pomeni zaupati v znanost? V tem primeru zaradi nejasnosti semantičnega pomena sociopolitične konotacije izraza postanejo njegov primarni Vse večjo relevantnost pojma “zaupanja v znanost” v sodobni pomen. V politizirani znanosti bi zato “zaupati v znanost” v družbi lahko jemljemo kot posledico poznanstvenjenja družbe in resnici pomenilo podpirati obstoječi politični režim, izražanje družbenih praks – vse večjega soodvisnost znanstveno- tega zaupanja (ali njegovega pomanjkanja) pa bi služilo kot tehnološkega razvoja in vodenja sodobnih družbenh praks [22]. politična uniforma, ki izraža pripadnost enemu ali drugemu Še posebej pomemben pa je postal v zadnjih dveh letih, odkar se političnemu polu. V prispevku analiziram znanstveni diskurz je svet soočil s pandemijo Covida-19. Narodne, mednarodne ali zadnjih dveh let z namenom ugotavljanja, kaj je bil v tem celo globalne zdravstvene krize, kamor spadajo tudi pandemije, obdobju družbeni pomen zaupanja v znanost – podpora procesa so pogosto zaznamovane z določeno mero vključevanja znanstvenega raziskovanja ali izraz politične konformnosti? medicinske znanosti v vodenje družbe in usmerjanje družabnega življenja in Covid kriza je bila še posebej izrazit primer tega. KLJUČNE BESEDE Tako smo bili priča vsesplošni uporabi slogana “zaupajmo v znanost” (včasih “zaupajmo znanosti”), v angleščini “trust the Politizacija znanosti, Covid-19, zaupanje v znanost, socialno science” z namenom upravičevanja in izpostavljanja znanstveno presojanje, psihološka inokulacija podprtega značaja uradno sprejetih ukrepov za spopadanje s ABSTRACT Covid epidemijo. Kaj natanko pomeni zaupati v znanost? Drugače povedano, Trust in science is especially relevant in today’s society, given kateri znanosti naj bi se zaupalo? Znanost lahko razumemo kot that we are living in the wake of the 2-year Covid-19 pandemic. metodo (znanstvena metoda), proces (znanstveno-raziskovalni The term itself is somewhat vague, as science has multiple proces), socialni sistem (skupnost znanstvenikov) ali institucijo definitions, mainly the process of scientific research as well as (skupek akademskih institucij, kjer se izvaja znanstveno the institutions that engage in said process. Thus, trust in science raziskovanje). Vidimo torej, da pojem zaupanja v znanost nima is a floating signifier, a label without a clear referent. Such labels enoznačnega pomena – lahko pomeni zaupati kateri koli can be problematic if targeted by politicization. The vagueness kombinaciji zgoraj naštetih vidikov znanosti – zato ga je tudi of the floating signifier’s semantic meaning allows the socio- težko enoznačno vrednotiti in proučevati. Zaupanje v znanost je political connotations to acquire primacy. In times of politicized Hackingova človeška vrsta, je posplošitev oziroma klasifikacija science, “trusting in science” would then actually mean to neke človeške lastnosti oziroma vedenjske tendence, ki v svoji endorse the established political regime. As for actions that prisotnosti ali odsotnosti definira posebno kategorijo človeka signal this trust (or lack thereof), they would act as a political [10]. Človeške vrste so podvržene učinku zanke, zaradi refleksije uniform – an expression of political allegiance to one’s chosen in samo-refleksije identifikacija neke socialne entitete z side. This article analyses the state of scientific discourse during določeno človeško vrsto vpliva na lastnosti te socialne entitete, the pandemic, with the goal of establishing the precise meaning kar posledično vpliva tudi na pomen človeške vrste – oznake, s Permission to make digital or hard copies of part or all of this work for personal or katero jo poimenujemo. Pomen besede “znanost” je relativen in classroom use is granted without fee provided that copies are not made or distributed dinamičen tudi v odsotnosti zankanja, zato to velja tudi 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 “zaupanje v znanost” – ko se spreminja pomen znanosti, se be honored. For all other uses, contact the owner/author(s). spreminja tudi pojem »zaupanje v znanost«. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Zato lahko trdimo, da je zaupanje v znanost lebdeči © 2022 Copyright held by the owner/author(s). označevalec (ang. floating signifier), oznaka brez točnega ali splošno-sprejetega pomena, torej brez točnega referentnega 72 objekta [13]. Ravno v tej značilnosti se skriva moč lebdečih za osebo, ki presoja. Če je politika razločevanje med prijatelji in označevalcev – nejasnost njegovega pomena dopušča sovražniki, potem je znanost politična kadarkoli primarni kriterij individualno konstrukcijo pomena. Tako je točen pomen za razločanje med znanstveno in neznanstveno trditvijo ni lebdečega označevalca relativen – za eno osebo ali skupino ljudi kvaliteta argumentacije in podprtost z dokazi, temveč status pomeni nekaj, za drugo nekaj drugega. njenega sporočevalca. Z drugimi besedami, dihotomija Zaupanje v znanost torej nima enoznačnega pomena, kljub prijatelj/sovražnik se v znanosti odraža, ko je “kdo je to rekel?” temu pa lahko to idejo ovrednotimo na podlagi različnih možnih pomembnejše vprašanje od “kako je bila izjava argumentirana?”. definicij. Najprej si zamislimo dva ekstrema, znanstveni V podrobnosti argumentacije se morda ne moremo popolnoma dogmatizem in radikalni skepticizem do znanosti. Dogmatik bo spustiti, lahko pa vsaj presodimo ali je argumentacija formalno- najverjetneje trdil, da smo dolžni zaupati vsem aspektom logično ustrezna. znanosti – v uporabnost znanstvene metode, zanesljivost Lebdeči označevalci so zaradi svoje nejasnosti in dvoumnosti znanstveno-raziskovalnega procesa pri odgovarjanju na idealna tarča za politizacijo. Politizirana oznaka poleg svojega raziskovalna vprašanja, verodostojnost znanstvenikov in semantičnega pomena dobi še sociopolitični pomen – prisotnost nevtralnost oziroma apolitičnost znanstvenih institucij. Radikalni referentnega objekta označuje prijatelja ali sovražnika (režima) skeptik, v kolikor njegova pozicija ne temelji na a-priornem oziroma pripadnika ingrupe ali outgrupe. Ravno zaradi zavračanju, pa se bo najbrž skliceval na uvide Foucaulta [8] in nejasnosti semantičnega pomena (oznaka pomeni različne stvari Lyotarda [14], ki sta izpostavljala neko mero relativnosti različnim skupinam) sociopolitični pomen nadvlada znanstvenega spoznanja. Posledično bo trdil, da znanstvene semantičnega in postane primarni. Tako potem lebdeči institucije niso apolitične, znanstveniki niso racionalni in zato označevalec postane univerzalna oznaka za sovražnika režima – niti verodostojni, znanstveno-raziskovalni proces in znanstvena točen semantični pomen besede sicer vsak razume po svoje, metoda pa nista univerzalno orodje za dostopanje do resnice, njena čustvena in moralna valenca pa sta enoznačni. Znanost je temveč orodje za perpetuacijo specifične jezikovne igre. v naši družbi pozitivna, torej bi primeru politizacije “zaupanje v Na srečo lahko uberemo vmesno pot, ki ustreza klasični znanost” v svoji lebdeči obliki označevalo pripadnike ingrupe koncepciji razsvetljenske znanosti in temelji na egalitarnem oziroma prijatelje režima, njegova odsotnost pa njegove odnosu do znanja in zavračanju dolžnosti laika, da zaupa sovražnike oziroma pripadnike outgrupe. intelektualni avtoriteti. To stališče dobro povzame izjava S tega vidika je bila Covid kriza zelo zanimiva. Moja analiza Richarda Feynmana, da je znanost verjetje v nevednost se bo sicer osredotočala predvsem na dogajanje v mednarodni in strokovnjakov [7]. Potemtakem “zaupanje v znanost” pomeni ameriški znanosti, vendar so bili enaki ali podobni vzorci prisotni priznavanje uporabnosti znanstvene metode in zanesljivosti tudi v Sloveniji. Ekipa znanstvenikov iz MIT-ja je leta 2021 raziskovalnega procesa, hkrati pa ohranitev zdravega dvoma v objavila pre-print študije Viral Visualizations: How Coronavirus verodostojnost znanstvenikov in institucij. Če strokovnjak ali Skeptics Use Orthodox Data Practices to Promote Unorthodox institucija trdi da p, ni potrebno da temu slepo verjamemo, Science Online, ki je poročala o navadah, značilnostih, stališčih temveč lahko zahtevamo argumentacijo in vpogled v in vrednotah spletnih skupnosti Covid-skeptikov oziroma anti- raziskovalni proces. maskerjev, ljudi, ki so tako ali drugače nasprotovali uradnim Covid ukrepom [12]. Intuitivno bi se nam zdelo, da so to skupine, ki ne “zaupajo znanosti”, avtorji uporabijo termin “anti-znanost” 2 Politična znanost (anti-science), obstaja tudi variacija “zanikalec znanosti” Zagovarjam stališče, da bi “zaupanje v znanost” moralo pomeniti (science-denier). Vendar se je izkazalo, da ti ljudje niso klasični zaupanje v znanost kot proces in metodo, ne pa v njen človeški oziroma stereotipni zanikalci znanosti, v resnici sploh ne element (znanstveniki in institucije), ki je dovzeten za razne nasprotujejo znanosti kot taki in da so nadpovprečno znanstveno pristranosti in konflikte interesa, zaradi katerih trpi pismeni. Nasprotovali so uradni (politično podprti) znanosti, verodostojnost znanstvenih zaključkov. Znanstvenega procesa v razlikovanju med uradno in neuradno znanostjo ter praksi seveda ni brez človeškega elementa, ki ta proces izvaja, avtoritarnemu odnosu stroke do laikov. Zagovarjali so torej vendar človeški element v tej izvedbi tudi ni nezmotljiv. Zato egalitarno znanost, kjer ima vsakdo dostop do podatkov in velja zaupati v process, v človeški element pa ne povsem. možnost oblikovanja svojih zaključkov [12]. Posledično moramo ugotoviti, ali se uporaba tega slogana v Avtorji študije se s tem niso strinjali in so trdili, da Covid- zahodni družbi sklada s tovrstnim razumevanjem ali ne. V skeptiki “spodkopavajo uradne znanosti s spretno manipulacijo kolikor se ne, in za tem stoji pričakovanje slepega zaupanja podatkov”. Ta trditev se mi zdi bizarna – kako lahko želja po znanstvenikom in institucijam, je to znak dogmatizma in intersubjektivnem preverjanju s strani visoko znanstveno institucionalizacje znanosti, ki sta močno povezani s politizacijo. pismenih posameznikov, ki želijo nepristransko ovrednotiti Carl Schmit je znan po svoji definiciji politike kot presojanju podatke 1 “spodkopava uradno znanost”? Ni to kvečjemu na podlagi dihotomije prijatelj/sovražnik, pri čemer je prijatelj koristno, saj je po Popperju 2 ravno falsifikacija gonilo nekdo s komer si delim interese, sovražnikovim interesom pa znanstvenega napredka, ki je v času pandemije še toliko bolj nasprotujem [18]. Politično vrednotenje dogajanj in dejanj torej ključen? Rekel bi, da načeloma je, vendar ne v ne temelji na splošnih načelih, temveč poteka na podlagi institucionalizirani znanosti, kjer akademske institucije želijo identitete udeleženih subjektov in uporabnosti njegovih posledic obdržati monopol nad produkcijo znanja. Institucionalizacijo 1 Lee et al (2021): “These users want to understand and analyze the information for 2 Popperjev model falsifikacije ima sicer svoje težave, vsekakor pa gonilo themselves, free from biased, external intervention.”, str. 12 znanstvenega napredka ni izogibanje možnostim falsifikacije. 73 sicer lahko razumemo kot mehko obliko politizacije, vendar to postavil teorijo kognitivne disonance – ljudje se držimo očitno še ni indikator politizacije v pravem pomenu besede. neresničnih stališč, ker težimo k ujemanju stališč, vedenja in Žal pa je med Covid krizo prišlo tudi do slednje. V samopodobe [6]. Za naštete fenomene predlagam nadpomenko institucionalizirani znanosti vlada kredencializem – merilo ideje socialnega presojanja in sklepanja5 – presojanja in sklepanja v je znanstveni in akademski prestiž znanstvenika, ki jo predlaga. skladu s svojo skupinsko identiteto, konsenzom ingrupe ali Vendar med Covid krizo niti znanstveni prestiž avtorja ni bil stališčem ingrupne intelektualne avtoritete, kar pogosto vodi do zadosten pogoj za sprejemanje neke ideje. Tako se je npr. dr. fenomena, ki ga Perkins (po navedbi Barona) poimenuje myside Robert Malone moral soočiti z deplatformiranjem zaradi bias [1]. Socialnega presojanja se po mojem mnenju “širjenja dezinformacij” – Twitter mu je deaktiviral račun [15] poslužujemo na vseh družbeno-relevantnih področjih, kjer po nastopu na Roganovem podcastu, kjer je izrazil nestrinjanje z nimamo motivacije, sposobnosti ali predznanja za sistematično uradnim konsenzom glede Covida in zajezitvenih ukrepov, ter oblikovanje lastnega stališča. svoje stališče znanstveno argumentiral 3 . Malone je sicer V to kategorijo zaradi svoje kompleksnosti spada večina znanstvenik – mednarodnega renomeja 4 – vendar očitno ni znanstvenih tem, še posebej tistih, ki so družbeno oziroma izpolnjeval kriterijev za “zaupanje znanosti”. Kaj je torej znanost, politično relevantne, vključno s pandemijo Covida-19 in z njo na katero se je med Covid krizo nanašal slogan “zaupajmo povezanimi ukrepi. Pinker govori o fokusnih točkah, javno znanosti”? Ugotovili smo, da se ne nanaša na proces vidnih in relevantnih dogodkih in dogajanjih, ki jih vidi znanstvenega raziskovanja in niti na individualne znanstvenike z posameznik in se hkrati zaveda, da so vidni tudi drugim dovoljšno mero prestiža. Moja teza je torej, da se je beseda prebivalcem družbe [17]. Fokusne točke, oziroma spektakli, “znanost” nanašala na uradno, torej politično-podprto znanost pogosto postanejo politizirane – to so močno družbeno oziroma znanost režima. Tukaj se lahko navežem na Foucaltov relevantna dogajanja, do katerih se je potrebno opredeliti. Že režim resnice, kjer je ideja resnice politično in ideološko sama potreba po opredelitvi je političnega značaja, ker ne umeščena – diskurz in metode produkcije resnice so omejeni, dopušča nevtralnosti, zgolj izbiro enega izmed dveh polov. Ko je hkrati obstaja skupina ljudi, ki ima monopol nad razglašanjem prisotna binarna polarizacija, pa je prisotna tudi dihotomija družbene resnice [8]. prijatelja (podpornika uradnih ukrepov) in sovražnika Med Covid krizo so vlogo razsodnika resnice prevzeli (nasprotnika uradnih ukrepov). Fokusne točke torej aktivirajo in znanstveniki režima – uradni Covid komentatorji (kot npr. dr. okrepijo vrojeno tendenco človeka po socialnem presojanju, v Fauci v Ameriki, dr. Krek in dr. Beović v Sloveniji), vlogo tem primeru o vsebini same fokusne točke. Ko je zaupanje “čuvaja” resnice pa mediji in socialni mediji, ki so tako ali znanosti postalo fokusna točka, kar se je zgodilo med Covid krizo drugače utišali znanstvenike, ki so želeli izraziti kakršno koli (če ne še prej), se je torej navzelo političnih konotacij in postalo nestrinjanje z uradnim konsenzom. Covid krizo je torej označevalec za prijatelje in sovražnike režima – definirane kot zaznamovala močna politizacija znanosti, saj je pravico do zaupnike in zanikalce znanosti (včasih teoretike zarote). širjenja (znanstvenih) resnic nudila predvsem podpora Zaupanje v znanost je torej družbenopolitični problem. Stran, na (prijateljstvo) režima, ki se je odražala v podpori uradnega kateri se nekdo nahaja, je prej merilo politične opredeljenosti kot konsenza glede spopadanja s pandemijo. Posledično trdim, da samega zaupanja v znanost v klasičnem pomenu izraza, ali odraz slogan “zaupajmo znanosti” ni predstavljal klica k epistemski globljih filozofskih načel. Drugače povedano, izražanje racionalnosti in sistematičnemu presojanju znanstvenih izjav, (ne)zaupanja v znanost v kakršnem koli socialnem kontekstu je temveč ravno nasprotno – emocionalno in politično prežet sklic politična uniforma, zato je to prej signal privrženosti ustaljeni na avtoriteto. Cilj je bil sprejemanje stališč intelektualnih politiki kot pokazatelj odnosa do raziskovalne dejavnosti, ki ji avtoritet režima, ne pa samostojni razmislek. pravimo znanost. 3 Socialno presojanje 4 Politični in spoznavni razhod Tematika letošnje konference je “kognitivni vidiki zaupanja v V obdobju politične polarizacije zaradi socialnega presojanja in znanost”. Moj cilj je pokazati, da je zaradi politizacije znanosti politizacije znanosti pogosto pride do spoznavnega razhoda – na in zaupanja v znanost večina teh kognitivnih vidikov pod eni strani imamo množico ljudi, ki takorekoč zaupa znanosti vplivom socialnih pritiskov. oziroma uradnim virom in zgodbam, na drugi pa množico ljudi, V socialni psihologiji obstaja veliko raziskav in teorij na temo ki “zanika znanost” – torej zavrača uradne vire in zgodbe, ter oblikovanja in spremembe stališč ter presojanja novih informacij. oblikuje svoja stališča s pomočjo alternativnih virov. Giner-Sorolila in Chaiken sta poimenovala koncept motiviranega Pojavita se vsaj dve različni “socialni resničnosti”, dve sklepanja, kjer sistematično sklepamo z namenom potrditi točno različni interpretaciji vsebine fokusne točke. Imamo torej ljudi, določeno stališče [9]. Caccioppo in Petty sta postavila ki v grobem sprejemajo uradno zgodbo in ljudi, ki jo v grobem dvoprocesni model spremembe stališč, kjer centralno zavračajo (seveda pa sta to sprejemanje in zavračanje procesiranje upošteva predvsem vsebino sporočila, periferno pa kontinuum), v primeru Covida se to nanaša na stališča do mask, lastnosti sporočevalca in socialni kontekst [2]. Festinger pa je cepljenja in drugih uradnih ukrepov. To je v veliki meri posledica 3 https://open.spotify.com/episode/3SCsueX2bZdbEzRtKOCEyT 5 Ta koncept sem podrobneje razdelal v članku Social Reasoning and the 4 Malone na https://www.rwmalonemd.com: “I am an internationally recognized Politicization of Science During the Covid Pandemic, ki bo objavljen Decembra v scientist/physician and the original inventor of mRNA vaccination as a technology- reviji Mankind Quarterly [16]. I have approximately 100 scientific publications with over 12,000 citations of my work (per Google Scholar with an “outstanding” impact factor rating committees).” 74 razlik v zaznavanju zaupanja vrednih oziroma verodostojnih Odgovor je, seveda, režim in “znanost” režima. Vidimo torej, virov v obeh (ali vseh) skupinah ljudi. Vir, ki je verodostojen za da je spoznavni razhod med podporniki uradne narative in eno skupino nikakor ni verodostojen za drugo, to presojanje o kontranarative posledica aktivno ustvarjenega političnega verodostojnosti pa je politične narave. Torej, spoznavni razhod razhoda s strani režima in njegovih ideoloških aparatov, ki v je posledica političnega razhoda, ne obratno. Oziroma, kot bi interakciji z javnostjo ustvarjajo koncept zaupanja znanosti, rekel Foucault, znanje izvira iz moči. In šele nato spoznavni zanikanja znanosti in teorij zarote. Akademiki in drugi razhod perpetuira političnega – sprejemanje ene ali druge raziskovalci imamo edinstveno možnost izpostavljanja napak interpretacije (označeno kot zaupanje znanosti ali teoriziranje režima, ampak lahko to dosežemo zgolj, če znanost zaščitimo zarote) je politična uniforma, ki signalizira pripadnost enemu od pred politizacijo. Prvi korak k depolitizaciji znanosti pa je po političnih polov. mojem mnenju prepoznavanje koncepta zaupanja v znanost kot Kljub temu pa pomanjkljivo znanje, do katerega pride v politične uniforme in posledično zavračanje vseh dihotomij, ki primeru cenzure nasprotujočih stališč, nosi svoje posledice – jih ustvari. pogosto negativne. V zadnjih mesecih prihaja vedno več raziskav in medijskih objav, ki izpostavljajo destruktivne posledice LITERATURA določenih Covid ukrepov – ekonomska škoda, ki so jo povzročili [1] Baron, J. (2000), Thinking and deciding (3rd ed.), New York: Cambridge lockdowni [20], zaviranje razvoja otrok zaradi obveznega University Press [2] Cacioppo, J.T. in Petty, R.E. (1984). The Elaboration Likelihood Model nošenja mask [23] in njihova splošna neučinkovitost [19], of Persuasion. NA - Advances in Consumer Research, 11, 673-675. neučinkovitost cepiv pri zaščiti pred okužbo s Covidom [5] in [3] CDC (2022). CDC streamlines COVID-19 guidance to help the public možnost nevarnih stranskih učinkov pri določenih demografskih better protect themselves and understand their risk. Sneto iz https://www.cdc.gov/media/releases/2022/p0811-covid-guidance.html skupinah, npr. nosečnicah [4]. Ameriški CDC je sicer pred [4] Clark County Today (2022). FDA knew huge percentage of women in kratkim spremenil svoje smernice za spopadnje s Covidom – zdaj Pfizer trial suffered miscarriages. Sneto iz: https://www.clarkcountytoday.com/news/fda-knew-huge-percentage-of- so enake za cepljene in necepljene posameznike, kar implicira women-in-pfizer-trial-suffered-miscarriages/ enako stopnjo tveganosti obeh skupin [3]. Vendar se moramo [5] Comber, J. in Madhava, S. (2022). After Data Show Vaccinated at Higher vprašati, zakaj šele zdaj? Različni ljudje in institucije po svetu so Risk of Dying from COVID, Canadian Province Ends Monthly Reports. Global Research. Sneto iz: https://www.globalresearch.ca/after-data- tako ali drugače opozarjali na morebitne negativne posledice show-vaccinated-higher-risk-dying-from-covid-canadian-province-ends- uradnih Covid ukrepov, vendar so bili tako ali drugače utišani. monthly-reports/5790795 [6] Festinger, L. (2022). A Theory of Cognitive Dissonance (Anniversary ed.). Tukaj torej vidimo, da imata politizacija znanosti in dogmatični Stanford University Press. odnos do tako-imenovanega “strokovnega konsenza” v naši [7] Feynman, R. (n.d.). What is Science? Sneto iz: http://www.feynman.com/science/what-is-science/ poznanstvenjeni družbi obsežne negativne posledice. [8] Fontana A. & Pasquino, P. (n.d.) Truth and Power (interview with V svetu, kjer se zdi, da lahko motiviran laik z dovoljšno mero Foucault). Sneto iz znanstvene pismenosti v enem tednu iskanja člankov na Google https://www2.southeastern.edu/Academics/Faculty/jbell/foucaulttruthpo wer.pdf Scholar doseže osnovno razumevanje (ali vsaj aproksimacijo le- [9] Giner-Sorolila, R., & Chaiken, S. (1997). Selective Use of Heuristic and tega) nekega znanstvenega področja, uradne znanstvene Systematic Processing Under Defense Motivation. Personality and Social Psychology Bulletin, 23(1), 84–97. doi:10.1177/0146167297231009 institucije niso več edini možni vir znanja. In v skladu s tem se [10] Hacking, I. (1995). The looping effects of human kinds. In D. Sperber, D. moramo tudi ravnati in priznavati veljavnost izvenkonsenzualnih Premack, & A. J. Premack (Eds.), Causal cognition: A multidisciplinary stališč, v kolikor so podprta z argumenti in dokazi. debate (pp. 351–394). Clarendon Press/Oxford University Press. [11] Jigsaw (2021). Psychological Inoculation: New Techniques for Fighting Na žalost pa Googlov think tank Jigsaw in Svet za Online Extremism. Medium. Sneto iz: družboslovno raziskovanje (Social Science Research Council, https://medium.com/jigsaw/psychological-inoculation-new-techniques- for-fighting-online-extremism-b156e439af23 SSRC), tako kot Lee in kolegi povlečeta ravno obraten zaključek. [12] Lee, C., Yang, T., Inchoco, G. D., Jones, G. M., & Satyanarayan, A. Laikom ne želita prepustiti, da si sami ustvarijo stališče in sami (2021). Viral Visualizations: How Coronavirus Skeptics Use Orthodox presojajo med informacijami in dezinformacijami, oziroma med Data Practices to Promote Unorthodox Science Online. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. znanjem in lažnimi novicami. Nasprotno, Jigsaw predstavlja https://doi.org/10.1145/3411764.3445211 koncept “pre-bunkinga” oziroma psihološke inokulacije, [13] Lévi-Strauss, C. (1987). Introduction to Marcel Mauss. Routledge. [14] Lyotard, J.-F. (1984). The Postmodern Condition: A Report on vnaprejšnjega zavračanja možnih heterodoksnih stališč v obliki Knowledge. University of Minnesota Press. kratkih sporočil, ki predstavijo protiargumente in poslušalcu [15] Malone, R. (2021). Permanently suspended on Twitter. Who is Robert Malone. Sneto iz: https://rwmalonemd.substack.com/p/permanently- olajšajo zavračanje tega stališča v prihodnosti [11]. SSRC pa suspended-on-twitter skuša ugotoviti kako maksimizirati povpraševanje po Covid [16] Marušič, J. Ž. (2022). Social Reasoning and the Politicization of Science cepivih – tako da dijake in študente nauči prepoznavati During the Covid Pandemic. Mankind Quarterly. Sprejeto v objavo. [17] Pinker, S. (2021). Rationality: What Is It, Why It Seems Scarce, Why It “dezinformacije o cepivih”. sporočevalce opremi z ustreznimi Matters. Viking Press. “sporazumevalnimi strategijami” in na družbenih omrežjih [18] Schmitt, C. (2007) The Concept of the Political. University of Chicago Press. oblikuje “(demografsko in geografsko) prilagojena sporočila” [19] Spira B (April 19, 2022) Correlation Between Mask Compliance and [21]. COVID-19 Outcomes in Europe. Cureus 14(4): e24268. Spet se moramo vprašati, kdo razlikuje med informacijo in doi:10.7759/cureus.24268 [20] Sumption, J. (2022). Little by little the truth of lockdown is being dezinformacijo, med ortodoksnimi in heterodoksnimi stališči. Je admitted: it was a disaster. The Times. Sneto iz: to znanost, politika ali politizirana znanost? In nadalje, ne bi to https://www.thetimes.co.uk/article/little-by-little-the-truth-of-lockdown- is-being-admitted-it-was-a-disaster-5b5lrlgwk morala biti pravica in dolžnost vsakega odraslega državljana v [21] The Rockefeller Foundation. Mercury Project to Boost Covid-19 demokratični in egalitarni državi? Če si posameznik ne more, Vaccination Rates and Counter Public Health Mis- and Disinformation in 17 Countries Worldwide. Sneto iz: oziroma ne sme sam ustvariti mnenja, čemu potem služi https://www.rockefellerfoundation.org/news/mercury-project-to-boost- demokracija? 75 covid-19-vaccination-rates-and-counter-public-health-mis-and- disinformation-in-17-countries-worldwide/ [22] Ule, A. (2006). Znanost, družba, vrednote. Aristej. [23] Watson, S. (2022). CNN Medical Analyst Who Fiercely Advocated Masking Now Admits It ‘Harmed’ Her Own Son’s Development. Summit News. Sneto iz: https://summit.news/2022/08/24/cnn-medical-analyst- who-fiercely-advocated-masking-now-admits-it-harmed-her-own-sons- development/ 76 Filozofski in psihološki vidiki človeške racionalnosti Philosophical and psychological aspects of human rationality Nastja Tomat Oddelek za filozofijo Filozofska fakulteta UL Ljubljana, Slovenija nastja.tomat@ff.uni-lj.si POVZETEK to the shift from the idealized view of human rationality to a more moderate one. In addition to research on rational action, study of Človeška racionalnost je kompleksen pojem, ki se nanaša na rational beliefs is another field of inquiry that connects široko paleto našega spoznavanja in delovanja. Obstajajo investigation of rationality with fundamental questions in številne opredelitve racionalnosti; Ronald de Sousa razlikuje epistemology. med kategorično in normativno racionalnostjo, govorimo lahko o instrumentalni ali široki racionalnosti ali o racionalnosti kot KEYWORDS logičnem sklepanju. Vprašanja o racionalnosti so tesno bounded rationality, ecological rationality, rationality of belief, prepletena s preučevanjem odločanja. Normativne teorije odločanja racionalno vedenje opredelijo kot tisto, ki vodi do izida heuristics and biases z največjo pričakovano koristnostjo, deskriptivne teorije pa preučujejo, kako se odločanje v vsakdanjem življenju dejansko 1 UVOD poteka. K odmiku od idealiziranega pogleda na racionalnost so pripomogli program hevristik in pristranosti, ki sta ga osnovala Vprašanje, ali smo ljudje racionalna bitja, še zdaleč ni enostavno. Daniel Kahneman in Amos Tversky, koncept omejene Odgovor se že stoletja izmika znanstvenikom različnih disciplin racionalnosti, ki ga je predstavil Herbert A. Simon, ter delo od ekonomije in psihologije do filozofije in kognitivne znanosti. Gerda Gigerenzerja in sodelavcev, ki preučujejo ekološko Človeška racionalnost je tema, ki se je lahko lotevamo iz racionalnost. Poleg racionalnosti dejanj lahko govorimo tudi o številnih vidikov in z uporabo različnih metod, zato ni racionalnosti prepričanj, kar preučevanje racionalnosti poveže s nenavadno, da danes na tem področju obstaja ogromno polje temeljnimi vprašanji s področja epistemologije. razprav in raziskav. V veliki razpravi o racionalnosti, kot so to poimenovali v kognitivni znanosti, obstajata dva nasprotujoča si KLJUČNE BESEDE pogleda. Na enem polu so avtorji, ki zagovarjajo, da so človeško sklepanje, presojanje in odločanje, ki so del racionalnega omejena racionalnost, ekološka racionalnost, racionalnost vedenja, polni pomanjkljivosti in pristranosti ter da jih je mogoče prepričanj, hevristike in pristranosti izboljšati; zagovorniki takšnega pogleda v veliki meri izhajajo iz ABSTRACT programa hevristik in pristranosti, ki sta ga osnovala psihologa Daniel Kahneman in Amos Tversky. Raziskovalci na drugem Human rationality is a complex topic that encompasses a wide polu pa takšnemu pogledu na racionalnost nasprotujejo in trdijo, range of cognitive processes and behavior. Many definitions of da so kriteriji normativnih teorij racionalnosti neustrezni ter da rationality exist, one of them being Ronald de Sousa's notion of izsledki empiričnih raziskav, ki pričajo o sistematičnih odklonih categorical and normative rationality. Some authors distinguish od omenjenih kriterijev, še ne zadostujejo za sklep, da smo ljudje between instrumental and broad conception of rationality, while iracionalni [1, 2, 3]. others define rationality in terms of logical reasoning. The study Namen prispevka je podati pregled izbranih pogledov na of rationality is intertwined with research in the field of decision človeško racionalnost. Začela bom z definicijo filozofa Ronalda making. Normative theories define rationality as behavior that de Sousa, nadaljevala pa z dvema opredelitvama racionalnosti, leads to the outcome with the greatest expected utility, while med katerima se v literaturi pogosto razlikuje: instrumentalno in descriptive theories examine how people actually make decisions široko. Na primeru Wasonove naloge izbire kart – ene najbolj in everyday life. Kahneman and Tversky's heuristics and biases uporabljenih nalog pri empiričnem preučevanju sklepanja – bom program, Herbert A. Simon's concept of bounded rationality and opisala pogled, ki racionalnost povezuje z logičnim sklepanjem Gerd Gigerenzer's study of ecological rationality all contributed ter je še vedno vpliven zlasti na področju filozofije. Poleg logike je področje, ki je prav tako prepleteno s preučevanjem Permission to make digital or hard copies of part or all of this work for personal or racionalnosti, odločanje. Opisala bom, kakšno sliko racionalnosti 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 prikazujejo normativne teorije odločanja ter kako se je kot kritika citation on the first page. Copyrights for third-party components of this work must takšnega pogleda izoblikoval program hevristik in pristranosti, ki be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia je še danes eden najvplivnejših okvirjev za preučevanje © 2022 Copyright held by the owner/author(s). odločanja in presojanja. Nato bom predstavila koncept omejene racionalnosti, ki ga je oblikoval Herbert A. Simon in je 77 pomembno vplival na razumevanje in pojmovanje racionalnosti, postavlja. Prednost takšnega pristopa je v tem, da lahko ter koncept ekološke racionalnosti, ki ga preučujejo Gerd postavimo norme, ki služijo kot kriterij racionalnosti, ter Gigerenzer in sodelavci ter se naslanja na Simonovo delo. V spremljamo, v kolikšni meri in pod kakšnimi pogoji ljudje od njih zadnjem delu se bom odmaknila od empiričnih raziskav odstopamo. Po drugi strani pa se zdi preučevanje racionalnosti le odločanja in presojanja ter opisala nekatera vprašanja, ki jih iz instrumentalnega vidika preozko – če se osredotočamo samo odpira raziskovanje racionalnosti prepričanj – teme na presečišču na ciljno usmerjeno vedenje, izpustimo pa vprašanja o ciljih, preučevanja racionalnosti in epistemologije. normah in vrednotah, zanemarimo velik in pomemben del človeškega delovanja [1]. John Searle v svoji knjigi o racionalnosti navaja primer znanih raziskav o inteligentnosti 2 DE SOUSOVA OPREDELITEV opic, ki jih je psiholog Wolfgang Köhler izvajal na Tenerifih. V RACIONALNOSTI eksperimentih se je izkazalo, da so opice sposobne reševanja Filozof Ronald de Sousa najprej razlikuje med kategorično in problemov z vpogledom; da bi dosegle na strop obešene banane, normativno racionalnostjo. Pri kategorični racionalnosti je do katerih niso mogle priti s skakanjem, so uporabile škatle in nasprotje racionalnega aracionalno vedenje. Racionalno je palico [6]. Iz intrumentalnega vidika so se opice torej vedle takšno vedenje, ki ga vodijo določeni razlogi, aracionalno pa racionalno in Searle meni, da tudi racionalnost človeka še vedno takšno, ki ga ne vodi mišljenje ali izbira. Pri kamnu, ki ga vržemo presojamo na podoben način. V klasičnih modelih racionalnosti skozi okno, ali človeku, ki se spotakne in pade v grm kopriv, ne je človeška racionalnost pravzaprav le kompleksnejša verzija govorimo o (i)racionalnosti – pri prvem gre namreč za pojav, ki šimpanzje. Searle v nadaljevanju opozarja na pomanjkljivosti uboga zakone fizike, pri drugem pa za dejanje, ki ga ni vodila takšnega pojmovanja racionalnosti in opozarja na pomembnost izbira. Pri normativni racionalnosti pa razlikujemo med ločevanja vedenja na podlagi želja in na podlagi razlogov [7]. racionalnim in iracionalnim vedenjem. Racionalno vedenje je V odgovor na pomanjkljivosti instrumentalnega pristopa so tisto, ki je ustrezno utemeljeno z določenimi razlogi, normami ali se pojavila širša pojmovanja racionalnosti, ki upoštevajo tudi vrednotami, iracionalno pa tisto, ki se od temu pogoju na tak ali cilje, prepričanja, norme in vrednote, ki usmerjajo naše vedenje. drugačen način ne zadostuje. De Sousa pravi, da lahko o ljudeh Te teorije se med drugim ukvarjajo z vprašanji o racionalnosti kot o racionalnih živalih govorimo samo, če sprejmemo, da smo samih ciljev [5] ter o vedenju, ki nima samo instrumentalne ljudje racionalni v kategoričnem smislu in kot taki tudi sposobni funkcije [1]. Filozof Robert Nozick na primer govori o konceptu iracionalnega vedenja [4]. simbolne koristnosti in pravi, da imajo naša dejanja neodvisno Če kategorične racionalnosti ne pripisujemo dogodkom, ki jih od instrumentalne tudi simbolno vrednost, ki bi jo morale lahko zadostno razložimo z naravnimi zakoni, ali to pomeni, da vključevati vse formalne teorije racionalnosti in odločanja. Ker z njimi ne moremo razložiti človeškega vedenja? Zmernejša živimo v socialno in simbolno kompleksnem okolju, naša dejanja interpretacija pravi, da je človeško vedenje podvrženo naravnim služijo tudi namenom, ki presegajo doseganje ozko zastavljenih zakonom, vendar ti ne ponujajo zadostne razlage. Kot primer de ciljev, na primer temu, da sebi in drugim sporočamo, kakšne Sousa navaja igro šaha, ki ga moramo razložiti s pravili igre – in osebe smo [8]. Podobno ekonomist Shaun H. Heap kot protipol ta niso naravni zakoni. Močnejša interpretacija pa pravi, da instrumentalni racionalnosti postavlja ekspresivno racionalnost. vedenje racionalnih bitij, vključno s človekom, na nek način Ko izvajamo dejanja, ki so ekspresivno racionalna, presega zakone narave. De Sousa meni, da je tako stališče opredeljujemo in raziskujemo lastna prepričanja in vrednote. Ne absurdno, saj bi predpostavljalo čudež ali pa vsaj to, da zakonov gre torej za enosmerno povezavo med vrednotami in delovanjem, narave ne razumemo pravilno. Zagovarja, da moramo človeka temveč za povratno zanko, kjer z dejanji vrednote tudi obravnavati kot bitje, ki je kot vsa ostala podvržen zakonom konstruiramo, spremljamo in prilagajamo [9]. narave; razliko med človekom in ostalimi bitji je potrebno iskati v zakonih narave in ne v lastnostih, ki bi le-te na nek način presegale. Če privzamemo, da se racionalnost nanaša na misli in 4 RACIONALNOST IN LOGIČNO dejanja, lahko razlikujemo med dvema ključnima spremembama MIŠLJENJE tako na nivoju evolucije kot razvoja posameznika: prva je razvoj Najbrž eden od najstarejših kriterijev racionalnosti je sledenje od golega zaznavanja objektov do zmožnosti tvorbe pravilom logičnega sklepanja in verjetnostnega računa [1]. Ena reprezentacij, druga pa razvoj od avtomatskih vedenjskih od najbolj preučevanih nalog, ki se uporablja v empiričnih odzivov do zmožnosti oblikovanja namer ter želja ter vedenja na raziskavah sklepanja, je Wasonova naloga izbire kart [10, 11], ki podlagi le-teh [4]. ima naslednjo obliko: »Na mizi so štiri karte. Vsaka ima na eni strani številko, na drugi pa barvo. Katere karte je potrebno obrniti, da testiraš pravilo: če je na eni strani sodo število, je na 3 INSTRUMENTALNA IN ŠIROKA drugi strani rdeča barva?« RACIONALNOST V literaturi se pogosto pojavlja razlikovanje med ožjim, instrumentalnim in širokim pojmovanjem racionalnosti [1, 4]. Instrumentalno racionalnost opredelimo kot vedenje, ki nas približa doseganju zastavljenega cilja glede na mentalne in fizične vire, ki so nam na voljo. Povedano drugače, racionalno je tisto vedenje, ki optimizira doseganje ciljev, pri čemer se ne ukvarjamo s tem, kakšni ti cilji so in kako si jih posameznik 78 Slika 1: Primer Wasonove naloge izbire kart. primeru, ko posameznik preferira alternativo A pred B in B pred C, preferira tudi A pred C. Če aksiomi držijo, lahko vsaki V zgoraj navedenem primeru je pravilni odgovor, da je alternativi pripišemo določeno koristnost in racionalno odločanje potrebno obrniti karto s številko 8, s čimer preverimo modus je tisto, ki privede do izida z najvišjo koristnostjo [22]. ponens, in karto rjave barve, s čimer preverimo modus tollens. Normativne teorije pred odločevalce torej postavljajo stroge Večina udeležencev pri takšni nalogi poda odgovor, da je zahteve in kmalu so se začela pojavljati vprašanja, če se ljudje v potrebno obrniti karto s številko 8 in karto z rdečo barvo, vendar vsakdanjem življenju resnično odločamo na tak način. gre pri slednjem za napako zatrjenega konsekvensa. V več kot Kahneman in Tversky sta leta 1979 objavila članek, v katerem petdesetih letih od izvirne objave je bila naloga uporabljena v sta pokazala, da ljudje sistematično kršimo aksiome racionalnosti, ogromnem številu raziskav, kjer so avtorji manipulirali z na katerih slonijo normativne teorije. Svoje ugotovitve sta strnila različnimi spremenljivkami, ki bi lahko vplivale na izvedbo v teorijo obetov, ki nadgrajuje teorijo pričakovane koristnosti in naloge, še danes pa ni enotne razlage za majhen delež pravilnih razlaga, kako se ljudje odločamo pod pogojem tveganja [23]. rešitev; ena od interpretacij je, da se večinoma osredotočamo na Kahneman in Tversky sta dolga leta preučevala presojanje in potrjevanje hipoteze, manj pa preverjanje pogojev, ki bi hipotezo odločanje in osnovala raziskovalni okvir, ki ga poznamo pod ovrgli [12, 13, 14]. Še ena ugotovitev je, da so udeleženci imenom »program hevristik in pristranosti«. V številnih pogosto nagnjeni k izbiri kart, ki so eksplicitno omenjene v raziskavah sta pokazala, da ljudje v negotovih pogojih pogosto navodilu [15]. Eno od opažanj je, da se delež pravilnih rešitev uporabljamo hevristike – miselne bližnjice, ki olajšujejo poveča, če namesto abstraktnih uporabimo konkretne primere, reševanje problemov, so hitre, varčne in zahtevajo manj napora kar nakazuje na to, da se pri logičnem sklepanju oz. tesitranju – kar vodi do sistematičnih napak v presojanju in odločanju, ki hipotez ne zanašamo le na obliko argumentov, temveč tudi na sta jih poimenovala kognitivne pristranosti. Ljudje pogosto ne vsebino [16]. Delež pravilnih rešitev je še večji, če uporabimo upoštevamo pravil logike in verjetnostnega računa, smo slabi deontična pravila. Če morajo udeleženci na primer preverjati intuitivni statistiki, zaključujemo brez ustreznih dokazov, slabo pravilo »Če piješ alkohol, moraš biti starejši od 18 let«, na mizi napovedujemo lastne prihodnje preference in smo podvrženi pa imajo karte s številkami 16 in 25 ter z napisi »pivo« in številnim dejavnikom, ki na tak ali drugačen način »kokakola«, večina pravilno izbere karti s številko 16 in napisom »neupravičeno« vplivajo na naše presoje. Doprinos programa »pivo«. Testiranje hipotez nam gre očitno torej bolje, ko moramo hevristik in pristranosti je ravno v poudarjanju tega, da ljudje preverjati morebitne kršitve socialnih pravil [17]. Ena od nismo racionalni v okviru normativnih teorij, temveč da interpretacij, ki temelji na evolucijski psihologiji, je, da sklepanje odločanje in presojanje v vsakdanjem življenju potekata drugače ni le splošen, od vsebine neodvisen proces, temveč je v ozadju [24, 25, 26]. več specializiranih procesov, eden izmed katerih je namenjen Delo Kahnemana in Tverskyja je bilo skozi leta deležno reševanju problemov v kontekstu socialnih izmenjav in kršitev različnih kritik. Če smo ljudje resnično tako podvrženi socialnih pogodb [17]; ta interpretacija je deležna številnih kritik sistematičnim napakam v presojanju in odločanju, kako je sploh [18]. Nekateri avtorji pa menijo, da je logično pravilna rešitev mogoče, da se dovolj učinkovito odzivamo na okolje, da Wasonove naloge v konfliktu z načinom, kako v vsakdanjem preživimo? Različni avtorji so ponudili alternativne življenju testiramo hipoteze, ter zagovarjajo, da je način, kako se interpretacije izsledkov, ki naj bi izražali pristranosti v mišljenju. udeleženci lotijo reševanja, v resničnem življenju adaptiven. Po Ena vrsta interpretacij se ukvarja z razlago odgovorov na naloge njihovem neuspešno reševanje naloge torej ne služi kot dokaz znotraj laboratorijskih pogojev, druga pa z vprašanjem, kaj nam iracionalnosti [19, 20]. To se sklada s pogledom, da logičnega ti odgovori povedo o sklepanju, presojanju, odločanju in mišljenja ne gre vedno in apriori enačiti z racionalnostjo, temveč reševanju problemov v vsakdanjem življenju. Že znotraj je ustreznost takšnega mišljenja odvisna tudi od konteksta [1]. laboratorijskega konteksta ni vedno enoznačno, ali je določen odgovor na nalogo pravilen ali napačen. Primer tega so različne interpretacije že omenjene Wasonove naloge izbire kart. 5 RACIONALNOST IN ODLOČANJE Oaksford in Chater na primer menita, da naloga ne ocenjuje Pojem racionalnosti je tesno prepleten s preučevanjem odločanja deduktivnega sklepanja, temveč verjetnostno. Če privzamemo, in presojanja. Znotraj vedenjskega preučevanja odločanja ločimo da kriterij za pravilne odgovore ni upoštevanje pravila med normativnimi, deskriptivnimi in preskriptivnimi pristopi. falsifikacije, temveč izbira najbolj informativnih kart v skladu s Normativne teorije se osredotočajo na to, kako bi se ljudje morali teorijo optimalne selekcije podatkov (ang. optimal data odločati, da bi prišli do izida, ki ima zanje največjo koristnost, selection), lahko nekatere odgovore udeležecev smatramo kot deskriptivne teorije preučujejo, kako človeško odločanje v pravilne, tudi če ne sledijo pravilom formalne logike [19, 20]. resničnem življenju dejansko poteka, preskriptivne pa želijo Zagovorniki druge vrste interpretacij pa segajo izven laboratorija zmanjšati vrzel med prvima dvema in osnovati predloge za in menijo, da so »napačni« odgovori udeležencev iz izboljšanje odločanja [21]. evolucijskega, adaptivnega vidika pravzaprav smiselni. Prevladujoč model normativnega odločanja pod pogojem Odgovori, ki jih v umetno ustvarjenih problemih v tveganja je bila dolgo časa teorija pričakovane koristnosti, ki sta laboratorijskem eksperimentiranju razlagamo kot napake, imajo jo v knjigi Theory of Games and Economic Behaviour leta 1944 v vsakdanjem življenju prilagoditveno vlogo in zato morda ni predstavila John von Neumann in Oskar Morgenstern. Teorija upravičeno, da jih jemljemo kot dokaz človeške iracionalnosti temelji na aksiomih, ki se nanašajo na odločevalčeve preference. [27, 28, 29]. Med drugim predpostavljajo, da ima posameznik popoln, urejen in tranzitiven nabor preferenc; to pomeni, da lahko za vsak par alternativ določi, v kakšnem odnosu sta, velja pa tudi, da v 79 6 OMEJENA RACIONALNOST ostri kritiki programa hevristik in pristranosti. Zagovarjajo, da so hevristike lahko učinkovita orodja mišljenja in da poseganje po Še en koncept, ki je pomembno vplival na odmik od njih v nekaterih situacijah, sploh takšnih z visoko stopnjo idealiziranih, normativnih teorij odločanja, je bil koncept negotovosti, lahko pojmujemo kot racionalno. Ukvarjajo se s omejene racionalnosti, ki ga je v 50. letih prejšnjega stoletja tako imenovano ekološko racionalnostjo, kjer je poglavitno predstavil Herbert A. Simon. Simon je menil, da je pojem vprašanje, katera strategija v določeni situaciji vodi do boljših globalne racionalnosti, ki naj bi jo posedoval človek v izidov kot druge. Boljše kot je ujemanje med strategijo, na primer ekonomskih teorijah odločanja, potrebno nadomestiti s pojmom določeno hevristiko, in strukturo naloge, bolj ekološko racionalni racionalnega vedenja, ki je kompatibilno z računskimi smo [35, 36]. sposobnostmi in dostopnostjo do informacij, kot jo ima človek v lastnem okolju v resnici. Racionalnost po njegovem ne pomeni iskanje najboljše možne, temveč zgolj dovolj dobre rešitve, kar 7 RACIONALNOST PREPRIČANJ je poimenoval satisficing. Uporabil je prispodobo škarij, kjer eno rezilo ponazarja računske zmožnosti akterja, drugo pa strukturo Poleg racionalnosti dejanj lahko govorimo tudi o racionalnosti okolja; zagovarjal je, da je pri preučevanju človeške prepričanj. Prepričanje je eden od temeljnih pojmov v racionalnosti pomembno upoštevanje in razumevanje obeh epistemologiji in je del klasične tripartitne definicije znanja, ki »rezil« [30, 31, 32, 33]. le-tega opredeli kot upravičeno resnično prepričanje. Eno od Simon je v svojih delih podrobno razdelal tako omejitve osrednjih vprašanj epistemologije je, kako priti do resničnih človekovega kognitivnega sistema kot značilnosti okolja. Menil prepričanj. Vprašanje je neločljivo povezano s preučevanjem je, da ni dokazov, ki bi pričali v prid temu, da človeško odločanje racionalnosti. Kakšen je odnos med racionalnostjo, poteka na način, kot to predpostavljajo normativne teorije, in da upravičenostjo in resničnostjo prepričanj ter znanjem? So ljudje v kompleksnih odločitvenih situacijah uporabljamo racionalna prepričanja tista, ki so upravičena, ali gre za ločena poenostavitve. Ena od njih je, da ne iščemo najboljše možne, pojma? Kako ljudje oblikujemo svoja prepričanja in kako bi jih optimalne rešitve, temveč si postavimo kriterij in izide nad njim morali [37, 38]? obravnavamo kot zadovoljive, pod njim pa kot nezadovoljive. Tradicionalni pogled je, da je vprašanje, kako bi ljudje morali Seveda se ob tem poraja vprašanje, na kakšen način si oblikovati prepričanja, v domeni epistemologije, vprašanje, kako postavljamo kriterij. Poleg tega pogosto nimamo popolnih dejansko jih, pa v domeni psihologije, in da naj bi disciplini informacij o tem, do kakšnih izidov bodo privedle različne delovali ločeno ena od druge. Do neke mere drži, da so alternative. Simon je zagovarjal, da v samem procesu odločanja normativna vprašanja epistemologije ločena od deskriptivnih postopoma pridobivamo informacije o tem in posodabljamo naše vprašanj psihologije - če bi določena psihološka spoznanja na poznavanje odnosa med alternativami in izidi. Vrednotenje primer pričala o tem, da je proces oblikovanja prepričanj alternativ po njegovem mnenju poteka postopoma, zaporedno, in pretežno nezaveden in da ljudje večinoma stremimo k tem, da odločevalec lahko preprosto izbere prvo zadovoljivo. Kriterij za sprejmemo prepričanja, ki spadajo v že obstoječo mrežo to, kaj je zadovoljiva rešitev, lahko po potrebi prilagajamo – če prepričanj, to samo po sebi ne daje dodatne teže koherentistični je previsok, ga znižamo in obratno, s čimer zagotovimo, da bomo teoriji upravičenja v epistemologiji. Vprašanji sta se začeli v vsakem primeru prišli vsaj do ene rešitve [30]. povezovati v 60. letih prejšnjega stoletja, ko je Willard V. O. Poleg zmožnosti organizma je za razumevanje racionalnosti Quine predstavil program naturalistične epistemologije, ki potrebno upoštevati tudi strukturo okolja. Simon je menil, da se poudarja, da so pri preučevanju prepričanj in znanja potrebne moramo osredotočiti na lastnosti okolja, ki so za odločevalca tudi metode, izsledki in teorije empiričnih znanosti [38]. pomembne in ki predstavljajo njegov življenjski prostor. Ne gre V literaturi se pogosto pojavlja izraz epistemska racionalnost. torej preprosto za preučevanje fizičnih lastnosti sveta, ki nas Pritchard jo opredeli kot obliko racionalnosti, katere cilj je obdaja; to, kaj smatramo kot okolje, je odvisno od zaznavnih pridobivanje resničnih prepričanj [37]. Po njegovem lahko sposobnosti, želja, potreb in ciljev organizma. Po Simonovem človek, ki stremi k epistemski racionalnosti, privzame različne mnenju odločevalci nimajo le enega, temveč več različnih strategije. Ena od njih je maksimizacija števila resničnih mehanizmov odločanja, ki so hierarhično urejeni, in vprašanje, prepričanj, druga pa minimizacija števila napačnih prepričanj, ki si ga moramo zastaviti, je, katere procese odločanja bomo v vendar pri obeh naletimo na težave: najboljši način za posameznih situacijah še lahko označili za prilagoditvene [31]. maksimizacijo števila resničnih prepričanj je, da verjamemo kar Vprašanje, kaj pomeni racionalno obnašanje, je torej koli, s čimer neizogibno pridobivamo tudi napačna prepričanja, drugačno, če ga zastavimo z upoštevanjem omejitev odločevalca najboljši način za minimizacijo števila napačnih prepričanj pa, in njegovega okolja ali pa iz perspektive normativnih teorij da ne verjamemo skoraj ničesar. Zdi se, da bi bilo najbolj racionalnosti. Ob upoštevanju vseh omejitev človeka, zlasti smiselno privzeti vmesen, uravnotežen pristop med verjetjem glede računskih in napovednih sposobnosti, je dejanska, vsemu in radikalnim skepticizmom [37]. Cilj epistemske človeška racionalnost lahko v najboljšem primeru le racionalnosti pa ni postavljen v prihodnost, temveč v sedanjost – poenostavljen približek t. i. globalne racionalnosti, na kateri večino epistemologov zanima, kakšno je stanje naših resničnih slonijo npr. modeli teorije iger [30]. prepričanj v tem trenutku, ne pa na primer čez eno leto. Za primer Koncept omejene racionalnosti se je od izvirnih Simonovih lahko vzamemo osebo, ki je brez ustreznih dokazov prepričana, del do danes razvijal in nadgrajeval ter še vedno močno vpliva da je dobra v matematiki. To prepričanje vodi v obiskovanje na preučevanje odločanja in racionalnosti [34]. Na njem temelji dodatnih ur matematike in zvišuje motivacijo ter količno učenja, tudi delo psihologa Gerda Gigerenzerja in sodelavcev, ki so kar na dolgi rok dejansko pripomore k večjemu številu resničnih osnovali raziskovalni program hitrih in varčnih hevristik ter so prepričanj o matematiki. Kljub temu bi večina epistemologov 80 zavrnila idejo, da je posedovanje prvega prepričanja epistemsko racionalnosti in epistemologije. Racionalnost prepričanj ali racionalno [38]. teoretsko racionalnost se pogosto prikazuje kot protipol praktični, Do zdaj omenjeni pogled prepričanja pojmuje kategorično, instrumentalni racionalnosti in menim, da je za razumevanje pri čemer imamo le tri možnosti: lahko smo prepričani, da p, celotne slike pomembno poznavanje obeh pogledov ali »vrst« prepričani, da ne-p, ali pa se prepričanja vzdržimo. Nekatera racionalnosti. Osredotočila sem se predvsem na odnos med področja epistemologije, na primer bayesovska epistemologija, racionalnostjo in različnimi temeljnimi pojmi epistemologije, pa prepričanja obravnavajo kot stopenjska – prepričanje torej ni zlasti upravičenjem, ter na povezavo med racionalnostjo in več propozicionalno stanje v smislu »vse ali nič«, temveč smo epistemskimi normami. Seveda pa na področju racionalnosti lahko v neko propozicijo prepričani bolj ali manj. V tem primeru prepričanj obstajajo še številna druga vprašanja in pogledi, opis se odpirajo številna nova vprašanja, na primer kakšen je odnos katerih presega namen prispevka. med dokazi za določeno propozicijo in našo stopnjo prepričanja vanjo ter kakšno stopnjo prepričanja potrebujemo, da lahko trdimo, da je posedovanje nekega prepričanja epistemsko 8 ZAKLJUČEK racionalno [39, 40, 41]. S tem povezana so tudi vprašanja o tem, Racionalnost je kompleksen pojem, ki zajema široko paleto kako prepričanja posodabljamo ali spreminjamo, ko človeškega spoznavanja in delovanja. Opredelitve racionalnosti, pridobivamo nove informacije. Obstajajo različni modeli, ki kriteriji zanjo in metode, s katerimi jo preučujemo, so tako opisujejo te procese, na primer AGM model revizije prepričanj številne in raznolike, da kategoričnega odgovora na vprašanje, [42] in teorija rangiranja [43, 44]. ali smo ljudje racionalni, ni pričakovati. Hkrati so praktično vsa Nadaljnja vprašanja, povezana z epistemsko racionalnostjo, področja našega življenja prepredena vsaj z implicitnimi se dotikajo epistemskih norm in odgovornosti. Pravila, ki nam prepostavkami o lastni (i)racionalnosti in tako je preučevanje le- narekujejo, kako oblikovati prepričanja, se imenujejo epistemske te pomembno ne le iz teoretskega, ampak tudi iz aplikativnega norme. Poraja se vprašanje, ali lahko agenta, ki prepričanja vidika. Preučevanje racionalnosti kot optimalnega doseganja oblikuje v skladu z napačnimi epistemskimi normami, še vedno ciljev lahko služi kot podlaga za oblikovanje spodbud in strategij, smatramo za epistemsko racionalnega. Šibkejši, deontični pogled ki bi tako posameznikom v vsakdanjem življenju kot na epistemsko racionalnost pravi, da ja – agentova prepričanja so strokovnjakom z različnih področij, kot so zdravstvo, epistemsko racionalna, če so v skladu z epistemskimi normami, gospodarstvo in pravo, pomagale pri učinkovitem sprejemanju ki jim agent sledi. V hipotetični situaciji, kjer bi bil agent dobrih odločitev. Tu pa pridemo do naslednjega vprašanja, ki se sistematično zaveden glede epistemskih norm, ni odgovoren za odpre, ko presežemo instrumentalno pojmovanje racionalnosti – morebitna napačna prepričanja; nasprotno pa v situaciji, kjer je kaj so »dobre« odločitve ali »racionalni« cilji? In nenazadnje, bil seznanjen s pravimi epistemskimi normami, pa vseeno sledi zakaj bi si pravzaprav želeli biti racionalni – ker menimo, da je napačnim, odgovornosti za napačna prepričanja ni razrešen. tako prav, ker racionalno delovanje izboljšuje naše možnosti za Močnejši, ne-deontični pogled pa kot kriterij za epistemsko preživetje in uspeh, ker vodi v srečo in blagostanje? Tudi pri racionalnosti postavlja, da agent sledi pravim epistemskim racionalnosti prepričanj se odpirajo podobna vprašanja; eno od normam, torej tistim, ki dejansko vodijo do resnice. Težava ne- njih je, ali je doseganje resnice vedno primarni epistemski cilj. deontičnega pogleda je v tem, da agent nikoli ni odgovoren za Pojmovanje racionalnosti je pomembno tudi pri razmislekih napačna prepričanja – če sledi napačnim epistemskim normam, o različnih vidikih zaupanja v znanost. Na kakšen način je sicer ni epistemsko racionalen, vendar tudi ni odgovoren za svoje znanje, ki ga pridobivamo z znanstveno metodo, drugačno od zmote [37]. znanja, ki ga pridobivajo laiki v vsakdanjem življenju? Koliko Predmet razprave je tudi vprašanje o odnosu med epistemsko prostora za napake in kolikšno stopnjo negotovosti je smiselno racionalnostjo in upravičenjem. Nekateri izraza »epistemsko dovoliti, ko preverjamo hipoteze? Kakšni dokazi so dovolj dobri, racionalna prepričanja« in »epistemsko upravičena prepričanja« da bomo neko trditev sprejeli ali ovrgli? Odgovori na ta in uporabljajo kot sinonima, drugi ju ločujejo. V drugem primeru ni podobna vprašanja so deloma odvisni od tega, kakšen pogled na jasno, kakšen je odnos med epistemsko racionalnim racionalnost privzamemo. prepričanjem in znanjem. Ena od možnih pozicij je, da tudi če Menim, da sta pri preučevanju racionalnosti pomembni tako sprejmemo upravičenje vsaj kot nujen, če ne že zadosten pogoj filozofska analiza kot metode empiričnih znanosti, ki nam dajejo za znanje, za epistemsko racionalnost to ne velja. Epistemsko vpogled v procese in mehanizme v ozadju človeškega racionalna prepričanja torej z znanjem niso povezana na enak oblikovanja prepričanj, sklepanja, presojanja in odločanja. način kot upravičena prepričanja. Če prekinemo povezavo med Integracija spoznanj različnih disciplin lahko pripomore k znanjem in epistemsko racionalnostjo, nam to omogoča, da zmanjševanju vrzeli med normativnimi in deskriptivnimi slednjo preučujemo tudi izven okvirja epistemologije in jo teorijami ter pripomore k oblikovanju karseda celostne slike povežemo z drugimi vidiki racionalnosti, na primer človeške racionalnosti. racionalnostjo odločitev in dejanj. 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Routledge, New York 82 Joint history of play provides means for coordination Liubov Voronina† Christophe Heintz MEi:CogSci Department of Cognitive Science University of Ljubljana Central European University Ljubljana, Slovenia Vienna, Austria voronina.liuba@gmail.com HeintzC@ceu.edu ABSTRACT In pure coordination games (Schelling games) participants are asked to choose the same option from the set of equally attractive ones. Surprisingly, people tend to converge on one In this study we investigate how joint history shapes strategic particular option at a rate significantly higher than chance. For decisions for solving coordination problems. We show that example, choosing between «heads» or «tails» reveals coordinating partners use the history of their past interactions to consistent preference for «heads», much higher than select their strategies. More precisely, people accurately predict mathematically implied equiprobability. Such recognisable that a winning strategy used in the past is mutually salient and prominence of one alternative over another, that results in a can be successfully used again in similar situations. Thus, joint stable solution, is called a focal point or salience. history helps players form accurate mutual expectations about each others’ choices and increase the rate of successful Pure coordination games therefore pose a question how to coordination. identify a unique solution to avoid coordination failure [4]. Although the exact reasoning behind the coordination process is We demonstrate that precedence is strongly relied upon and open for debate [5, 6, 7, 8], Schelling’s suggestion is to look for provides insights into the psychological bases of the social such selection rule among many, which can single out a processes through which conventions emerge. By investigating successful coordination strategy. This rule should be mutually the path dependence of the individual behaviour in the context recognised by the interacting parties to be able to provide of coordination, we experimentally confirm that conventions reliable means for coordination [1]. A focal point, emerged by emerge because people systematically rely on their past applying such selection rule, is called Schelling salience. interactions in order to coordinate successfully. Building on the logic of coordination games, David Lewis KEYWORDS convincingly argued for the emergence of (linguistic) conventions [9]. According to his account, observed coordination games, path dependence, Schelling salience behavioural regularities that are commonly known among the population, create accurate mutual expectations that facilitate 1. INTRODUCTION coordination by providing unambiguous solution to social coordination problems, resulting in stable equilibria. Coordination is the process of tacit convergence on a mutual We hypothesise that these behavioural regularities become strategy in the context of interdependent decisions. salient by virtue of repeating precedence, which is used as Coordinating partners can choose to do exactly same thing Schelling salience, once the agents are confronted with the (drive on the right side of the road), exactly the opposite thing coordination problem. (wait while another person is calling back after the line is cut) or complement each other’s actions to produce a common The goal of the study is to show how the joint history of outcome (division of the household chores). In many everyday interactions in coordination problems shapes the choice of cases coordination is achieved by following an existing coordination strategies. At the cognitive level, this means that convention, by making an explicit verbal agreement or by joint history is used by people as relevant information for performing actions in sequence, when the person initiating the choosing their strategy for coordination. interaction has the opportunity to make the first choice and The following hypotheses were tested: express their preference. However, even in the absence of communication, successful coordination can be accomplished H1: Joint history facilitates accurate mutual expectations. with the probability much higher than chance. Thomas Players choose a coordination strategy in view of what they Schelling first draw attention to this apparent paradox of expect their partner to do. These expectations are informed by coordination with his informal experiments [1], that were later the knowledge they have of their joint history, which makes successfully replicated in the controlled settings [2, 3]. their prediction more accurate. H2: Joint history determines coordination strategies. When the situation does not provide any unambiguous clues for Permission to make digital or hard copies of part or all of this work for personal or coordination, players choose a specific strategy that resulted in classroom use is granted without fee provided that copies are not made or successful coordination in the past to resolve the ambiguity and distributed for profit or commercial advantage and that copies bear this notice and avoid coordination failure. 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 83 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia L.Voronina et al. 2. METHOD 2.2. Experimental conditions This research is based on the empirical methodology of We used a between-subject design to examine the research experimental game theory. The economic game chosen for the hypotheses. Participants were presented with the experimental experiment is pure coordination game [1, 2, 3]. scenarios under the following three conditions: In the experiment, participants were presented with various (1) no joint history (baseline condition) layouts of coloured tokens and asked to coordinate on the token Baseline data reveals the rate of coordination in the absence of of the same colour. Both sets of tokens were visible to both joint history of play. The baseline condition also helps to partners and the choice was simultaneous. The result of every empirically differentiate various types of rounds that are used to interaction and individual players' choices were logged online construct scenarios in the experimental conditions. Rounds that in real time. The analysis was carried out for the particular type reveal preference for one particular colour will become history of rounds (at individual or dyadic level) with the condition as rounds. Rounds, where the colour choices are equally an independent variable. distributed, will become test rounds. Coordination index [2, 3] 2.1. Participants is calculated to show the hypothetical coordination rate of the unpaired participants based on their individual responses. One hundred and thirty-three participants took part in the Experimental setting: Participants play single rounds in pairs “Mobile Coordination Games” experiment, which was with their player IDs hidden. They connect with the new partner conducted online in two parts. Game sessions for the baseline after each round and are aware of this. The participants pool is condition were organised during June and July, 2021 with a set to 2 players to allow random pairing. total of 51 participants (mean age = 26.2 years; 16 females and 35 males). Game sessions for the experimental conditions took Experimental stimuli: 30 individual rounds of various difficulty. place in January, 2022 with a total of 82 participants (mean age Each round could be played for up to 2 times by any player (but = 24.1 years; 24 females and 58 males). Participants were not in sequence). recruited online via the Sona Research Participation System of (2) random joint history (experimental condition) Central European University. There were no restrictions on Participants have the opportunity to build a joint history of play, participation for the adult participants, who needed basic consisting of randomly assigned rounds. This history of mutual English skills for understanding the instructions and a mobile interactions can provide them with the clues for successful device for accessing the Coordy research application. All the coordination in the test round. Its coordination rate will be participants received compensation based on their performance compared to the corresponding baseline rate and the level (average amount = 4,9 euros) in the form of an online coordination index. voucher of their preference, either Amazon or PayPal. Experimental setting: Participants play games, consisting of 2.2. Materials four random rounds and a test round, in dyads with their player IDs shown. They change their game partner after each game. To enable empirical investigation of the real-time coordination The participants pool is set to 8 players to allow fixed pairing in between the pairs of participants, a proprietary mobile research order to avoid repetitions. application named Coordy has been developed for both Android and iOS based mobile devices. Coordy was officially released Experimental stimuli: 36 games of 5 rounds from the baseline and became available for download on Google PlayMarket and condition (6 unique histories of four rounds combined with AppStore. each of the 6 test rounds). Each game was played just once In the experiment, we used two different kinds of experimental during the game session. scenarios: (3) specified joint history (experimental condition) • 30 single rounds of various difficulty in the baseline Joint history, provided by the designed scenario, increases the condition: probability that a certain strategy is used during this history A. easy rounds with the symmetrical clues for coordination; and, subsequently, in the test round. Individual player’s B. hard rounds with the clashing clues; strategy, operationalised as a choice of the specific colour, will C. equiprobable rounds with no coordination clues; be compared between different histories that end up with the • 46 games of five rounds (experimental conditions). same test round. Experimental setting: Participants play games, consisting of four predefined rounds and a test round, in dyads with their player IDs shown. They change their game partner after each game. The participants pool is set to 8 players to allow fixed pairing in order to avoid repetitions. Experimental stimuli: 10 games of 5 rounds (5 unique histories of four rounds combined with the corresponding test rounds). Each game was played twice during the game session. All the scenarios (both single round and games of five rounds) appeared during the game sessions in the randomised order to avoid order effects. The order of rounds within a particular game was fixed. Both experimental conditions were tested Figure 1: Examples of A, B and C rounds. together during the same game sessions. 84 Joint history of play provides means for coordination Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 3. RESULTS Participants were more likely to successfully coordinate in the test rounds after the joint history of play than without it. Before reporting the results of the study, we would like to clarify the issue of the players’ expertise and its potential influence on the outcome of coordination. In both conditions, all the participants would start playing without any prior experience (match number 0). We analysed the outcome of the coordination in the last round (success or failure) for match numbers below and above 7 (half of the experimental game sessions) and found no evidence for the improvement of the coordination success at the dyadic level. Coordination in the last round was successful in about half of the games irrespective of the participants’ level of experience with the task. 3.1. Baseline results A chi-square test of goodness-of-fit was performed to determine Figure 3: Change in the coordination rate and coordination whether each of the three colours were equally chosen by the index across conditions (group-level). Levels of significance: participants in the particular round. **: p < .01, ***: p < .001. A two-proportion z-test was conducted to calculate the difference between the CR and coordination index (CI) in the last round of the games with random history. For the group of test B rounds CR was found to be significantly higher than CI after the joint history of play z (N = 1029 ) = 4.26, p < .001; r = .13. Therefore the actual coordination rate exceeds the rate of the expected coordination, when the choices are made by the randomly paired participants. 3.3. Specified history results Figure 2: Baseline coordination rates for the A, B rounds. A chi-square test of independence was performed to examine the relation between the individual player’s choice in the same A preference for a specific colour was found in the majority of test round and the specific history preceding that round. A rounds (except for A15) and some B rounds (B3, B11, B12). The corresponding dots on the graph are coloured with the colour that was chosen the most (over ⅔ of the individual choices) in the particular round. Also the coordination rates (CRs) for those rounds were very high (mean CR = 0.72). These rounds were used to constitute history rounds. A preference for the specific colour was not found in the four B rounds (B1, B8, B17, B18) and one A round (A15). While the choices for the three colours were not equally distributed in the rounds B2, B4, B7 and B9, the proportion of any particular colour did not exceed 60%. Their corresponding dots on the graph are therefore coloured in black. Also their CRs were significantly lower (mean CR = 0.43) than in the previous Figure 4: Individual player’s choice of colour for group of rounds with the focal points. These rounds were used coordination in the last round after the specified history. as test rounds in the random history condition. For the majority of C rounds (C1, C3, C4, C6) a colour For some pairs of histories, the relation between these variables preference was not established. Also the CRs for C rounds were was significant: not significantly higher than chance (mean CR = 0.57). Hence • for the test round C4 after the histories Red and Blue they are not depicted on the graph. These rounds were used as X² (1, N = 74) = 7.29, p < .01; r = .3; test round in the specified history condition. • for the test round C2 after the histories Green and Blue X² (1, N = 74) = 15.69, p < .0001; r = .45. 3.2. Random history results In the same test round, participants were more likely to choose A chi-square test of independence was performed to examine the modal colour of the history rounds (e.g. in the test round C4 the relation between the coordination rate in the test rounds (at participants were more likely to choose red colour after the the group level) and the history of previous interactions. The history Red and blue colour after the history Blue). relation between these variables was significant, X² (1, N = 592) For the histories Red and Green the relation between these = 8.39, p < .01; r = .12. variables was statistically insignificant. 85 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia L.Voronina et al. 4. DISCUSSION Overall, in our experiment we managed to observe how participants make use of the precedence by applying the In this study we aimed to investigate how previous interactions following rule for coordination: «choose the colour that brought can influence the outcome of coordination for the pair of us successful coordination before». Though studying path players. First, we let the participants play single rounds dependence in the lab setting poses certain challenges [10], anonymously. Even though the participants played several some researchers found the way to address them using the rounds, they could not constitute joint history of interaction economic games [11]. In the future, it could be fruitful to because they were — knowingly — paired with a new random empirically investigate the robustness of the coordination rules participants for each round. This set-up helped us identify and the amount of common knowledge required for their rounds with the «natural» focal points, i.e. colours that appealed emergence [12, 13, 14, 15]. to the participants as obvious to coordinate upon due to the specific layout of the scenario, irrespective of other factors. ACKNOWLEDGMENTS We noticed that in the absence of communication and any explicit coordination rules, participants did manage to The authors acknowledge financial support by the European coordinate more than rational choice theory would predict. This Research Council, under the European Union‘s Seventh is in line with previous results showing that people are able to Framework Programme (FP7/2007-2013)/ERC grant agreement rely on Schelling salience in order to coordinate successfully. no. 609819 (Somics project). In our experiment participants converged on a tacit rule for REFERENCES coordination, which was «choose colour with the most tokens 1. Thomas Schelling. 1960. The strategy of conflict (1st. ed.). Harvard present on both players’ layouts». Those rounds, where this rule University Press, Cambridge, MA. could not be unmistakably applied, demonstrated lower 2. Judith Mehta, Chris Starmer, and Robert Sugden, 1994. The Nature of coordination rates and were chosen to be the test rounds for the Salience: An Experimental Investigation of Pure Coordination Games. subsequent experimental conditions. We wanted to explore the The American Economic Review 84, 3 (Jun, 1994), 658–73. 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This mixed result calls for the replication study with the different set of stimuli. 86 Predicting Trust in Science in the Context of COVID-19 Information Society 2022, 10–14 October, Ljubljana, Slovenia Predicting Trust in Science in the Context of COVID-19 Pandemic: The Role of Sociodemographics and Social Media Use Žan Zelič Martin Berič Darja Kobal Grum Department of Psychology Department of Psychology Department of Psychology University of Ljubljana University of Ljubljana University of Ljubljana Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia zan.zelic@gmail.com martinberic@yahoo.com darja.kobal@ff.uni-lj.si ABSTRACT will perform an assigned task with a certain level of competence and expertise, while moral norms are related to the anticipation Research in the context of COVID-19 pandemic has consistently that by doing so, they will also act in a way that puts the interest shown that scientific distrust adversely affects health-related of the community before their personal advances. Similarly, behavior. Therefore, the aim of our study was to identify the risk Wintterlin et al. [4] argue that trust in science is rooted in factors for the development of scientific distrust, with emphasis expectations that scientists’ claims are epistemically sound and on the role of sociodemographic variables and social media use. that science has a prosocial stance. Overall, perhaps the most A convenience sample of 490 Slovene speaking individuals was comprehensive definition of trust in science has been provided used to perform hierarchical linear regression analysis. In line by Nadelson et al. [5], describing it as a multifaceted construct, with our hypotheses, the results showed that trust in science was which includes affective components, credibility and negatively correlated with age, religiosity and use of social media trustworthiness perceptions, knowledge and epistemic beliefs. as an information source about COVID-19, while it was Since scientists were the main source of information on positively correlated with male gender and total years of formal COVID-19 and its adverse consequences, and also the ones that education. When only sociodemographic variables were entered helped governments develop preventive measures and vaccines, into the prediction model, each of them explained a significant the findings that low trust in science negatively impacts health- proportion of the variance in trust in science. However, after the related behavior [2] should not come as a complete surprise. inclusion of social media use, religiosity was no longer a However, not much has been researched about the predictors of significant predictor. In contrast to our expectations, the results trust in science in the context of the pandemic. As we believe this also showed no significant interaction between education and kind of knowledge is crucial to implement communication social media use when predicting trust in science. Our findings changes, which could accurately address those who are are further discussed and additional implications are provided. particularly prone to developing scientific mistrust, we conducted a study focusing on the sociodemographic predictors KEYWORDS of trust in science as well as its connection to social media use. COVID-19, trust in science, social media use, education, religiosity 1.1 Predictors of Trust in Science Previous research on the relationship between trust in science and 1 INTRODUCTION age has shown somewhat mixed results. For example, some researchers reported on non-significant correlations [6], while When the new coronavirus (Sars-CoV-2) started to spread in others found that scientists were more likely to be trusted by 2020 it has quickly become evident that the world as we knew it those who are younger [7]. The latter result could in part be was about to change. Ever increasing number of infections led to explained by higher average levels of education among younger health system overloads, high mortality rates, mental health individuals, however age remained an important predictor even difficulties and great economic burden [1]. As adoption of social when education was accounted for [7]. distancing measures and newly developed vaccines was crucial Regarding gender, previous research has consistently shown for reducing the spread of the new coronavirus and its adverse that men generally have more positive attitudes towards science consequences, identification of factors influencing health-related than women [6][8]. However, when possible reasons for these behavior became of utmost importance. One of the variables that results were examined, other sociodemographic variables, such has been consistently found to predict preventive behavior as as education, religiosity and work status were found to explain well as vaccine acceptance is trust in science [2]. this gender gap [8]. According to Barber [3] public trust in science depends on the Throughout history, religion and science were often seen as perceptions of scientists’ compliance with technical and moral epistemologically conflicted [9], which may have resulted in norms. Technical norms consist of expectations that the scientists lower trust in science by those who are more religious. Indeed, previous research has shown that religiosity was associated with 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 negative attitudes towards science as well as lower science for profit or commercial advantage and that copies bear this notice and the full literacy [5][10]. 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). Another sociodemographic factor that has been consistently Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia shown to predict trust in science is education [6]. One of the most © 2022 Copyright held by the owner/author(s). prevalent explanations for the described relationship was that 87 Information Society 2022, 10-14 October, Ljubljana, Slovenia Ž. Zelič et al. education indirectly influences positive attitudes towards science 0 and 100 to estimate the percentage of information about the by increasing scientific knowledge [11]. However, further new coronavirus they obtained through social media. research showed that education remained an important predictor Trust in Science was measured by the Trust in Science and of trust even when controlling for scientific knowledge [12]. Scientists Inventory [5], which contains 21 items (e.g., We can Although previous research has indicated that social media trust science to find answers that explain the natural world. ). use positively predicts trust in science [13], we believe that the Participants were asked to rate their agreement with the provided results might be different in the times of COVID-19 pandemic. statements on a 5-point Likert scale with anchors, 1 ( Strongly Since social platforms enabled rapid misinformation dispersion disagree) and 5 ( Strongly agree). Confirmatory factor analysis [14], extensive social media use could lower trust in science by (CFA) showed poor one-factor model fit, so we excluded item increasing conspiracy beliefs about scientists’ involvement in the 11, which was semantically very similar to items 9 and 10. pandemic. Indeed, our previous research [15] showed that the Additionally, we allowed for some residual covariances extent of using social media as an information source predicted according to modification indexes. The fit of the modified 20- COVID-19 conspiracy beliefs, which were also highly inversely item scale was acceptable: χ 2(166) = 484.642, p < .001, CFI correlated with trust in science. = .939, TLI = .930, RMSEA = .070, 90% CI: [.063, .078], SRMR = .042. The shorter version of the scale also showed excellent 1.2 The Present Research internal consistency ( α = .95). The aim of our study was to examine the importance of several sociodemographic variables and social media use in predicting 3 RESULTS trust in science. Based on the previous findings we hypothesized that trust in science will be higher among younger individuals Firstly, the factor structure of the translated Trust in Science and (H1), men (H2), those who are less religious (H3), more educated Scientist Inventory was assessed by confirmatory factor analysis (H4) and those who obtained less information about the (CFA), using R package lavaan [17]. Since the data were non- coronavirus from the social media (H5). Additionally, we normally distributed, we used the robust maximum likelihood hypothesized that education would have a moderating role in the method (MLM) of model estimation. After minor modifications relationship between social media use and trust in science (H6). were implemented to achieve an acceptable one-factor model fit, Since critical thinking has been found to develop through the total trust in science score was calculated as a mean value of education [16], we assumed that even extensive social media use all items. All further analyses were done in IBM SPSS version would not reflect in high levels of scientific distrust as long as 25.0 [18]. individuals would be capable to critically evaluate the quality of Secondly, descriptive statistics and intercorrelations were obtained information. Furthermore, we also aimed to investigate calculated for all measured variables. The results showed that the amount of the variance in trust in science that a combination trust in science was negatively correlated with age ( r = -.14, p of these variables could explain as well as their relative = .002), religiosity ( r = -.16, p < .001) and use of social media as importance when entered into a multivariate prediction model. an information source about COVID-19 ( r = -.35, p < .001), while it was positively correlated with male gender ( rpb = .21, p < .001) and total years of formal education ( r = .29, p < .001). 2 METHOD Thirdly, when we determined that all assumptions for multiple linear regression were met, hierarchical linear 2.1 Sample regression analysis was conducted. Trust in science was entered Data collection took place between March 29 and April 7, 2021, into the analysis as a criterion variable, while all other measured using an online survey. Convenience sample was used, variables were consecutively added as predictors (see Table 1). consisting mostly of students at the University of Ljubljana and In the first step age and gender together explained 6.5% of members of different COVID-19 related Facebook groups. variance in trust in science with younger individuals and men Responses of 490 participants (397 women, 92 men and one non- exhibiting more trust. Both predictors were significant, although binary), aged from 18 to 70 years ( M = 35.7, SD = 13.2), were the relative importance of gender was greater. In the second step analyzed. The majority (56.5%) of the participants had a college religiosity explained only 1.8% of additional variance in trust in degree, 41.8% reported on having a high school diploma and science, however the change in R2 was statistically significant. 1.6% completed only elementary school. Furthermore, 31.6% of Those who were less religious showed significantly higher levels them were students, 54.7% were employed, 9.0% were of trust even when age and gender were accounted for. unemployed and 4.7% were retired. Furthermore, both age and gender remained significant predictors of trust despite slight decrease of gender's b value. In 2.2 Measures the third step the years of formal education turned up to be the Demographic data was obtained through a series of questions on most important positive predictor of trust in science, additionally age, gender, years of education and employment status. explaining 6.7% of its variance. Inclusion of education slightly Religiosity was measured by the participants’ level of lowered the b values of age and religiosity, however all included agreement with the statement “I would define myself as a predictors remained statistically significant. In the fourth step the religious person.” on a 7-point Likert scale with anchors, 1 share of COVID-19 information obtained from social media was ( Strongly disagree) and 7 ( Strongly agree). added into the equation, explaining an additional 5.8% of Use of social media as an information source about COVID- variance in trust in science. The results showed that those who 19 was measured by moving an interactive slider between values relied more on social networks to obtain information were less likely to trust in science. Altogether, a combination of five 88 Predicting Trust in Science in the Context of COVID-19 Information Society 2022, 10–14 October, Ljubljana, Slovenia Table 1: The results of the hierarchical linear regression analysis Step 1 Step 2 Step 3 Step 4 Step 5 Variable B SE b B SE b B SE b B SE b B SE b Age -.01 .00 -.14 ** -.01 .00 -.14 ** -.01 .00 -.11 ** -.01 .00 -.11 ** -.01 .00 -.11 ** Male gender .46 .10 .21 *** .42 .10 .19 *** .41 .09 .19 *** .28 .09 .13 ** .28 .09 .13 ** Religiosity -.07 .02 -.14 ** -.05 .02 -.11 * -.03 .02 -.07 -.03 .02 -.07 Education .10 .02 .26 *** .08 .02 .21 *** .09 .03 .22 ** SM information -.01 .00 -.26 *** -.01 .01 -.21 Edu x SM info .00 .00 -.05 R2 .064 .083 .149 .207 .207 △ R2 .064 *** .018 ** .067 *** .058 *** .000 Note. * p < .05. ** p < .01. *** p < .001. predictors explained 20.7% of variance in trust in science. significant predictor of trust in science even when age, religiosity However, after the variable of social media use was included, b and years of education were controlled. One possible explanation values of gender, education and religiosity decreased, thus for this result may be that on average women have less specific designating religiosity as a non-significant predictor. Finally, science-related knowledge than men. Although in our research analysis in the fifth step showed that there was no significant male gender was not significantly related to years of total interaction between education and social media use when education ( rpb = .04, p = .440), education of men and women predicting trust in science. might differ in terms of its type and field of interest. For example, Global Gender Gap Report 2022 showed that only 33% of STEM graduates in Slovenia are female [23]. In line with the above, Fox 4 DISCUSSION AND CONCLUSIONS & Firebaugh [24] also found that years of education did not The aim of our research was to examine the predictors of trust in explain the gender gap in science confidence. Moreover, their science in the context of COVID-19 pandemic since such research pointed out that gender differences can in large part be knowledge could be used to implement communication changes attributed to lower perceived utility of science by women. that might motivate higher compliance with preventive measures Based on previous studies, which showed that religiosity and protect public health. predicts negative attitudes towards science [10], we also Regarding age, the results were in line with our assumption hypothesized that religiosity would be negatively associated with that younger individuals are more likely to trust in science (H1). trust in science (H3). The results were in line with our Although our finding is supported by some of the previous assumption, however when in addition to all other research [7], it is still somewhat surprising, since general trust is sociodemographic variables, social media use was inserted into known to increase with age [19]. Negative relationship between the model, religiosity was no longer a significant predictor of trust in science and age could be explained by lower average trust in science. Indeed, an unusual positive correlation could be educational levels among the elderly, as both knowledge about observed between religiosity and social media use as an science and certain cognitive skills, which are thought to be information source about COVID-19 ( r = .21, p < .001). A related to higher trust in science [6][20] are developed through possible explanation for this phenomenon may be that social education [16][21]. Indeed, in our study age and education were media use is highly prevalent among religious individuals since negatively correlated ( r = -.12, p = .010), however age remained social networks are often seen as channels that can be used to a significant predictor even when education was controlled for. effectively minister to others [25]. Obtaining (mis)information Another possibility may be that the relationship between age and from social media may thus be a side effect of extensive use of trust in science is underlaid by religiosity, as previous research social networks for other purposes. An alternative explanation showed that older individuals are more likely to be religious [22] may also be that religious individuals are more likely to adopt and that religiosity also predicts lower trust in science [10]. conspiracy beliefs [15]. Since conspiracy ideation is likely to However, our results showed that religiosity and age were not influence the perception of traditional media as deceiving [26], significantly correlated ( r = -.03, p = .504), therefore those who are more religious may thus be inclined to use undermining the described reasoning. informal sources of information, such as social media. The results of our study were also in line with the assumption Regarding education and social media use, the results that male gender would be positively related to trust in science supported both of our hypotheses that trust in science would be (H2). Even though some of the previous studies [8] indicated that positively related to years of education (H4) and negatively this relationship could be entirely accounted for by other related to perceived share of information about COVID-19 that sociodemographic variables, we found that gender remained a was obtained on social media (H5). Although more educated 89 Information Society 2022, 10-14 October, Ljubljana, Slovenia Ž. Zelič et al. individuals were also less religious ( r = -.10, p = .023) and [4] Florian Wintterlin, Friederike Hendriks, Niels Mede, Rainer Bromme, obtained smaller share of information on social media ( r = -21, p Julia Metag and Mike Schäfer, 2022. Predicting public trust in science: The role of basic orientations toward science, perceived trustworthiness of < .001), education remained an important predictor of trust in scientists, and experiences with science. Frontiers in Communication 6 science even when other variables were controlled. As (Jan, 2022). DOI: 10.3389/fcomm.2021.822757 [5] Louis Nadelson, Cheryl Jorcyk, Dazhi Yang, Mary Jarratt Smith, Sam previously suggested, this could be explained by the fact that Matson, Ken Cornell and Virginia Husting, 2014. Trust in science and critical thinking, which is thought to interrelate with trust in scientists. School Science and Mathematics 114 (Jan, 2014), 76–86. DOI: science [20], develops through education [16]. Furthermore, in 10.1111/ssm.12051 [6] Fabienne Crettaz von Roten, 2004. Gender differences in attitudes toward contrast to previous research that reported on the positive science in Switzerland. Public Understanding of Science, 13 (Apr, 2004) relationship between social media use and trust in science [13], 191–199. DOI: 10.1177/0963662504043870 [7] Paul Brewer and Barbara Ley, 2013. Whose science do you believe? our results showed that in the times of the COVID-19 pandemic Explaining trust in sources of scientific information about the obtaining information from social media might in fact be environment. Science Communication 35, 1 (Feb, 2013), 115–137. DOI: 10.1177/1075547012441691 detrimental for trust in science. Since social media’s regulations [8] Bernadette C. Hayes and Vicki N. Tariq, 2000. Gender differences in on shared content are less strict compared to the traditional media, scientific knowledge and attitudes toward science: a comparative study of we believe the quick dispersion of COVID-19 conspiracy beliefs four Anglo-American nations. Public Understanding of Science 9 (Oct, 2000), 433–447. DOI: 10.1088/0963-6625/9/4/306 through social media could lower trust in science. Additionally, [9] John Evans and Michael Evans, 2008. Religion and science: Beyond the we hypothesized that social media use would not reflect in high epistemological conflict narrative. Annual Review of Sociology 34 (Aug, 2008), 87–105. DOI: 10.1146/annurev.soc.34.040507.134702 levels of scientific distrust as long as the individuals would be [10] Jonathon McPhetres and Miron Zuckerman, 2018. Religiosity predicts sufficiently educated (H6). We assumed that well educated negative attitudes towards science and lower levels of science literacy. individuals would be able to critically evaluate the quality of PLoS ONE 13, 11 (Nov, 2018), Article e0207125. DOI: 10.1371/journal.pone.0207125 obtained information due to their advanced critical thinking skills [11] Amitai Etzioni and Clyde Nunn, 1974. The public appreciation of science [16]. In contrast to our expectations, the results showed that there in contemporary America. Daedalus 103, 3 (Jan, 1974), 191–205. DOI: 10.1007/978-94-010-1887-6_15 was no significant interaction between education and social [12] Hee-Je Bak, 2001. Education and public attitudes toward science: media use when predicting trust in science. In our opinion, this Implications for the “Deficit Model” of education and support for science and technology. Social Science Quarterly 82, 4 (Dec, 2001), 779–795. finding could be based on the fact that: a) years of education are DOI: 10.1111/0038-4941.00059 not a valid indicator of critical thinking skills, or b) that critical [13] Brigitte Huber, Matthew Barnidge, Homero Gil de Zúñiga and James Liu, thinking abilities are somewhat irrelevant in the case when one’s 2019. Fostering public trust in science: The role of social media. Public understanding of science 28, 7 (Sep, 2019), 759–777. DOI: information space is so limited that they do not have any relevant 10.1177/0963662519869097 data upon which information from social media could be judged. [14] Ramez Kouzy, Joseph Abi Jaoude, Atif Kraitem, Molly B. El Alam, Basil Karam, Elio Adib, Jabra Zarka et al., 2020. Coronavirus goes viral: To conclude, our findings suggest that in order to restore trust Quantifying the COVID-19 misinformation epidemic on Twitter. Cureus in science and reinforce health-related behavior in the context of 12, 3 (Mar, 2020), Article e7255. DOI: 10.7759/cureus.7255 the pandemic, it would be expedient to develop communication [15] Žan Zelič, Martin Berič and Darja Kobal Grum, 2022. Examining the role of Covid-19 conspiracy beliefs in predicting vaccination intentions, strategies that would specifically target older women, who are preventive behavior and willingness to share opinions about the less educated, more religious and are extensive social media coronavirus. Studia Psychologica 64, 1 (Mar 2022), 136–153. DOI: 10.31577/sp.2022.01.844 users. However, these findings are subjected to some limitations [16] Christopher R. Huber and Nathan R. Kuncel, 2016. Does college teach of our research design. Firstly, the data may not be entirely critical thinking? A meta-analysis. Review of Educational Research 86, 2 representative due to the convenience sampling method. (Jun, 2016), 431–468. DOI: 10.3102/0034654315605917 [17] Yves Rosseel, 2012. lavaan: An R package for structural equation Secondly, correlational design of our study does not allow for modeling. Journal of Statistical Software 48, 2 (May, 2012), 1–36. DOI: causal inferences. And thirdly, the used trust in science measure 10.18637/jss.v048.i02 [18] IBM Corp. 2017. IBM SPSS Statistics for Windows, Version 25.0. IBM was one-dimensional, although some researchers argue that it is Corp., Armonk, NY. necessary to differentiate between trust in scientific methods and [19] Michael Poulin and Claudia Haase, 2015. Growing to trust: Evidence that trust increases and sustains well-being across the life span. Social trust in scientific institutions [27]. Therefore, our suggestion for Psychological and Personality Science 6, 6 (Mar, 2015), 614–621. DOI: future research would be to examine how these two distinct 10.1177/1948550615574301 forms of trust in science relate to health behavior and to identify [20] John Kleinig, 2016. Trust and critical thinking. Educational Philosophy and Theory 50, 2 (Jun, 2016), 1–11. DOI: which are the most important risk factors for either of them. 10.1080/00131857.2016.1144167 [21] Bryan Kennedy and Meg Hefferon, 2019. What Americans know about science? Pew Research Center, Washington, DC. Available at: ACKNOWLEDGMENTS https://www.pewresearch.org/science/2019/03/28/what-americans-know- Research was supported by the Slovenian research agency [grant about-science/ [22] Vern L. Bengtson, Merril Silverstein, Norella M. Putney and Susan C. number P5-0110]. Harris, 2015. Does religiousness increase with age? Age changes and generational differences over 35 years. Journal for the Scientific Study of Religion 54, 2 (Sep, 2015), 363–379. DOI: 10.1111/jssr.12183 REFERENCES [23] Global Gender Gap Report 2022. World Economic Forum, Geneva. [1] Office for National Statistics, 2021. Leaving no one behind – a review of Available at: https://www.weforum.org/reports/global-gender-gap-report- who has been most affected by the coronavirus pandemic in the UK: 2022/ December 2021. Office for National Statistics, Newport. Available at: [24] Mary F. Fox and Glenn Firebaugh, 1992. Confidence in science: The https://www.ons.gov.uk/economy/environmentalaccounts/articles/leavin gender gap. 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Minerva 25 (Mar, 1987), 123–134 science confidence gap: Education, trust in scientific methods, and trust in DOI: 10.1007/BF01096860 scientific institutions in the United States, 2014. Public understanding of science 26, 6 (Dec, 2015), 704–720. DOI: 10.1177/0963662515617367 90 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek C Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume C Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Urednika / Editors Dunja Mladenić, Marko Grobelnik http://is.ijs.si 10. oktober 2022 / 10 October 2022 Ljubljana, Slovenija 91 92 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. 93 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Janez Brank, Jožef Stefan Institute, Ljubljana Marko Grobelnik, Jožef Stefan Institute, Ljubljana Jakob Jelenčič, Jožef Stefan Institute, Ljubljana Branko Kavšek, University of Primorska, Koper Besher M. Massri, Jožef Stefan Institute, Ljubljana Dunja Mladenić, Jožef Stefan Institute, Ljubljana Erik Novak, Jožef Stefan Institute, Ljubljana Inna Novalija, Jožef Stefan Institute, Ljubljana Jože Rožanec, Qlector, Ljubljana Abdul Sitar, Jožef Stefan Institute, Ljubljana Luka Stopar, Sportradar, Ljubljana Swati Swati, Jožef Stefan Institute, Ljubljana 94 Emotion Recognition in Text using Graph Similarity Criteria Nadezhda Komarova, Inna Novalija, Marko Grobelnik Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia nadezhdakomarova7@gmail.com ABSTRACT In Section 2, it is further explained how the graph of 𝑛-grams is constructed for a given text and how an emotion label is assigned In this paper, a method of classifying text into several emotion cat- to the text based on the similarity with the emotion category egories employing different measures of similarity of two graphs graphs. Afterwards, in Section 3, the method is compared with is proposed. The emotions utilized are happiness, sadness, fear, related approaches. surprise, anger and disgust, with the latter two joined into one In Section 4, an overview of results is focused on differences category. The method is based on representing a text as a graph between the performance of the model when different graph of 𝑛-grams; the results presented in the paper are obtained using similarity criteria are used. It is followed by the discussion of the the value of 5 for 𝑛: the 𝑛-grams were the sequences of 5 charac- model’s limitations in Section 5. ters. The graph representation of the text was constructed based on observing which 𝑛-grams occur close together in the text; 2 PROPOSED METHOD additionally, frequencies of their connections were utilized to assign edge weights. To classify the text, the graph was compared 2.1 Constructing the Graph of 𝑛-grams with several emotion category graphs based on different graph The method used in the paper to obtain text representation in similarity criteria. The former relate to common vertices, edges, the form of the graph of 𝑛-grams is the following. and the maximum common subgraphs. The evaluation of the • The given text was separated into 𝑛-grams of characters. model on the test data set shows that utilizing the construction Also, different values of 𝑛 have been tested. The results of the maximum common subgraph to obtain the graph similar- in Section 4, use 𝑛 = 5. The 𝑛-grams into which the given ity measure results in more accurate predictions. Additionally, text was split were overlapping. employing the number of common edges as a graph similarity cri- • The 𝑛-grams obtained in this way were utilized to repre- terion yielded more accurate results compared to employing the sent the labels of vertices of the graph. number of common vertices to measure the similarity between • The edges of the graph were created in the following man- the two graphs. ner. The ends of edges were the vertices that corresponded KEYWORDS to 𝑛-grams that occurred close to each other in the text, e.g., the edge is connecting the first 𝑛-gram at the beginning emotion recognition, text classification, machine learning, graphs, of the text with the second 𝑛-gram (these two 𝑛-grams graph similarity would overlap with each other), as seen in Figure 1. Different values have been tested for the maximal distance 1 INTRODUCTION between the two vertices allowed for these two vertices to Emotion recognition is a problem that can be connected to differ- still be connected with the edge. The results in Section 4, ent fields such as natural language processing, computer vision, use the value of 7. deep learning, etc. [4] In this paper, the focus is on the task of • Performance of the model with both, the directed and the recognizing emotions in texts. undirected graphs, has been tested. In the literature, several approaches have been introduced that target this problem. Some of them employ vertex embedding vectors for emotion detection and recognition from text. The embedding vectors grasp the information related to semantics and syntax; however, a limitation of such approaches is that they do not capture the emotional relationship that exists between words. Some methods attempting to alleviate this issue include building a neural network architecture adopting pre-trained word representations. [3] Some text classification approaches employ 𝑛-grams to construct the text representation, e.g., to deal with Figure 1: Constructing the edges between the 5-grams that the task of language identification. [9] occur close to each other In this paper, the approach to emotion recognition employs 𝑛- grams to obtain graph representation of text. The text is viewed as In Figure 2, it is depicted how the edges are constructed be- a sequence of characters that is divided into 𝑛-grams, i.e., shorter tween the vertices labelled with 𝑛-grams. For the clarity of rep- overlapping sequences of characters as presented in Figure 1. resentation, each 𝑛-gram is shown connected to 3 other 𝑛-grams Permission to make digital or hard copies of part or all of this work for personal instead of 7. It is important to note that if the same 𝑛-grams oc- or classroom use is granted without fee provided that copies are not made or curred in the text more than once, there was still only one vertex 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 with this 𝑛-gram as a label: the connections of the 𝑛-gram have work must be honored. For all other uses, contact the owner /author(s). been aggregated at a single vertex. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Additionally, the graph constructed is weighted. The weights © 2022 Copyright held by the owner/author(s). of the edges are obtained utilizing the frequencies of connections 95 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Nadezhda Komarova, et al. of 𝑛-grams in the given text. In other words, the edge weights are In other words, it is tested, to which of the 5 graphs the graph initialized to 0. Then, when constructing the graph of 𝑛-grams of the given text is most similar and the corresponding emotion for a text, every time a certain edge would be added, instead of is assigned to the given text. adding it, the weight of the edge is increased by 1. Several similarity criteria of the two graphs have been ex- Afterwards, the edge weights are normalized to be in the range plored. (0, 1); hence, the edge weights are more comparable among the (1) The number of vertices common to both graphs: the ver- graphs of 𝑛-grams for different texts. tices are considered common if they share the same label (the 𝑛-gram they represent) in both graphs. (2) The number of edges common to both graphs: the edge is considered common if the same vertices (vertices with the same labels) are the endpoints of the edge in both graphs and the edge weights are the same. (3) The number of vertices in the maximum common subgraph (MCS) of the two graphs. Finding the maximum common subgraph is equivalent to finding a graph with the maxi- mum number of vertices so that it is a subgraph of each of the two graphs. [8] (4) The number of edges in the maximum common subgraph (MCS) of the two graphs. ¤(𝑚−1) (5) 𝑧 = 𝑚 − 𝑒, where 𝑚 denotes the number of vertices 2 in the maximum common subgraph of the two graphs, and 𝑒 denotes the number of edges in the maximum common subgraph. Figure 2: Constructing the edges between the 5-grams in 3 RELATED WORK the text fragment "oh how funny" In the literature describing related approaches to text classifica- tion and emotion recognition, deep learning models are often utilized to obtain high-quality predictions. [7] 2.2 Constructing the Emotion Category Apart from the approaches that employ word embedding vec- Graphs tors [6], there are also methods that connect neural networks and graphs. Such approaches may be similar to the method de- The core of the method is the construction of the graph of 𝑛- scribed in this paper since the graph representation of text may grams as described in Section 2.1. In the data set used to tune the be obtained in a similar way based on the semantic connections model, there were shorter texts labelled with one of the following between words. One example of this kind of model is the graph 5 emotions: happy, sad, surprised, fearful, or angry-disgusted. neural network that is enhanced by utilizing BERT to obtain Overall, there were 1207 sentences included in the data set; out semantic features. [11] of this, the model was trained using 1086 sentences (to construct The crucial part of the method in this paper is the graph the emotion category graphs) and evaluated on 121 sentences similarity criterion that is used when comparing the graph of the (the split proportion is 90 : 10). given text with different emotion category graphs. The similar The process of obtaining the emotion category graphs is pre- way as the construction of the maximum common subgraph is sented below. used in this method, it can be employed in combination with the (1) The data set was split into 5 parts containing only the text probabilistic classifiers. [10] labelled with the same emotion. The approach in this paper, on the other hand, does not employ (2) Then, the texts in each part of the data set were used to probabilistic classifiers such as Bayes Classification or Support obtain 5 graphs corresponding to each emotion. Vector Machine. [2] Instead, the emotion for which the similarity (a) This process can be viewed as for each text labelled with measure between the corresponding emotion category graph and a certain emotion, constructing the graph of 𝑛-grams as the graph of the given text is maximised is assigned to the text. explained in Section 2.1. Additionally, it is important to note that it is possible to in- (b) Afterwards, merge these graphs separately for different corporate alternative graph similarity criteria, e.g., related to emotions to obtain 5 larger graphs of 𝑛-grams; during subgraph matching, edit distance, belief propagation, etc. [5] the merging process, the edges are aggregated in such a way that there are not any two vertices in the emotion 4 RESULTS category graph sharing the same label (the character 𝑛-gram to which they correspond). 4.1 Experimental Setup The data set used to train and evaluate the model was the one dis- 2.3 Assigning an Emotion to a Given Text tributed by Cecilia Ovesdotter Alm. [1] It included the sentences Utilizing the 5 emotion category graphs corresponding to differ- each labelled with one of the following emotions: happiness, sad- ent emotions, for a given text, it is determined, to which emotion ness, fear, surprise, anger, and disgust. The latter two emotions the text most likely corresponds. For that, the pairwise similarity were joined into one category. measures of the graph of the given text and of the 5 emotion During the evaluation stage, for each sentence, a correspond- category graphs are employed. ing emotion was predicted, e.g., the text "then the servant was 96 Emotion Recognition in Text using Graph Similarity Criteria Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Table 1: Results of text classification using directed graphs Table 3: Confusion matrix: directed graph, number of edges in the MCS as the similarity criterion Similarity criterion Accuracy Precision Recall F1 Actual/pred. Happy Fearful Surpr. Sad Angry-Disg. Common vertices 0.488 0.506 0.332 0.323 Common edges 0.537 0.683 0.408 0.432 Happy 43 1 0 0 1 𝑧 0.372 0.074 0.200 0.108 Fearful 7 6 1 3 0 Vertices in the MCS 0.570 0.622 0.426 0.446 Surprised 6 1 2 1 1 Edges in the MCS 0.579 0.625 0.454 0.478 Sad 12 1 0 12 1 Angry-Disg. 11 2 0 2 7 Table 2: Results of text classification using undirected graphs Table 4: Confusion matrix: undirected graph, number of edges in the MCS as the similarity criterion Similarity criterion Accuracy Precision Recall F1 Actual/pred. Happy Fearful Surpr. Sad Angry-Disg. Common vertices 0.488 0.506 0.332 0.323 Common edges 0.554 0.669 0.429 0.460 Happy 42 1 0 1 1 𝑧 0.372 0.074 0.200 0.108 Fearful 8 6 1 2 0 Vertices in the MCS 0.545 0.527 0.399 0.406 Surprised 6 1 1 1 2 Edges in the MCS 0.570 0.581 0.439 0.453 Sad 11 1 0 13 1 Angry-Disg. 11 2 0 2 7 greatly frightened and said it may perhaps be only a cat or a dog" Table 5: Confusion matrix: directed graph, number of com- was labelled fearful, while the text "he looked very jovial did little mon edges as the similarity criterion work and had the more holidays" was recognized to be related to the emotion of happiness. Actual/pred. Happy Fearful Surpr. Sad Angry-Disg. The value of 𝑛 that appeared to yield the best results and was also used to obtain the results in Tables 1 and 2 was 5. Fur- Happy 42 1 0 2 0 thermore, each 5-gram (except those at the end of the text) is Fearful 10 4 0 3 0 connected to 7 5-grams further in the text. Surprised 6 0 2 3 0 In Tables 1 and 2, the "common edges" criterion means that Sad 13 0 1 12 0 the two edges from both graphs are considered common if they Angry-Disg. 16 1 0 0 5 have the same weight and the same endpoints. Additionally, in Table 1, 𝑧 denotes the difference between the Table 6: Confusion matrix: undirected graph, number of the actual number of edges in the maximum common subgraph common edges as the similarity criterion and the number of edges in the complete graph with 𝑚 vertices, where 𝑚 is the number of vertices in the maximum common Actual/pred. Happy Fearful Surpr. Sad Angry-Disg. subraph. In the trials that yielded the results in Table 1, the edges were Happy 41 1 0 2 1 directed and in the trials that yielded the results in Table 2, the Fearful 11 4 0 2 0 edges were undirected. Surprised 6 0 2 3 0 Sad 12 0 1 13 0 4.2 Analysis Angry-Disg. 14 1 0 0 7 From the results in Table 1 and 2, it may be noticed that the highest accuracy on the test data set was achieved when the Furthermore, the accuracy corresponding to the similarity number of edges in the maximum common subgraph was used criterion being the number of the common edges (considering as the similarity measure. In Table 1, the second highest accuracy both the endpoints and the weight of the edge) is higher by was achieved when the number of vertices in the maximum 0.017 when the graphs are undirected than when the graphs are common subgraph was utilized. directed (0.554 compared to 0.537). When the graphs utilized are From this, it may be observed that the construction of the max- undirected, the model might be more flexible regarding the exact imum common subgraph reflects the similarity better in certain order of the words that occur together. cases; possible reasons may be that deeper semantic relationships In Tables 5 and 6, confusion matrices are presented for the can be captured this way since connections between multiple trials when the number of edges common to both graphs, consid- 𝑛-grams are considered at the same time. ering the endpoints and the weights of the edges, was used as In Tables 3 and 4, the confusion matrices are presented for the the criterion of graph similarity. the trials when the number of edges in the maximum common subgraph was used as the criterion of graph similarity. 5 DISCUSSION From the Tables 1 and 2, it is evident that this similarity cri- terion corresponded to the highest accuracy of predictions for A strength of the approach presented in this paper is the ability both undirected and directed graphs. However, the accuracy cor- to capture the context of the given words on different levels; this responding to this similarity criterion is higher when the graphs is related to the process of constructing the edges of the graph by are directed (0.579 compared to 0.570). connecting 𝑛-grams that occur together in the text. Additionally, 97 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Nadezhda Komarova, et al. the breadth of the contextual frame considered may be varied by (vertices labelled with the same 𝑛-gram) are contained in both altering the number of 𝑛-grams with which a certain 𝑛-gram is graphs resulting in more noisy data. connected when constructing the edges. To conclude, the future work on the task of emotion recogni- However, overall, the accuracy values noted in Tables 1 and tion related to the proposed method may, on the one hand, be 2, were not very high possibly indicating that the training data focused on employing alternative graph similarity measures in set was not large enough. Moreover, the data set did not include addition to those described in this paper, e.g., those connected texts corresponding to different emotions in even proportions to deriving the edit distance or to the belief propagation. [5] resulting in an imbalance which could have also had a detrimental Furthermore, clustering algorithms may be used to obtain the influence on the quality of predictions. The confusion matrices patterns characteristic to the emotion categories and further em- (Tables 3, 4, 5, and 6) indicate, e.g., that the texts were often ploy them for the emotion recognition task. To this end, both, the falsely assigned the emotion of happiness since it was the most vertex clustering algorithms as well as the clustering of graphs abundant class in the data set. as objects, might be utilized. Additionally, graph neural network One of the limitations of the design of the model described architecture may be built along with incorporating the graphs of it that although it may be reasonable to expect that to obtain 𝑛-grams as the input for the network. more accurate predictions on the test data set, training the model (obtaining the emotion category graphs) on a larger corpus of 7 ACKNOWLEDGEMENTS texts is needed, this may bring a significant rise in computational This work was supported by the Slovenian Research Agency complexity since the category graphs would possess significantly under the project J2-1736 Causalify and the European Union larger amounts of vertices and edges. through Odeuropa EU H2020 project under grant agreement No This is especially important if the maximum common sub- 101004469. graphs are constructed when obtaining a similarity measure, since for each text in the test data set, a maximum common sub- REFERENCES graph would have to be constructed several times: between the [1] Alm, E. C. O. Affect in text and speech, 2008. graph of 𝑛-grams for a given text and each emotion category [2] Bahritidinov, B., and Sanchez, E. Probabilistic classifiers and statistical dependency: The case for grade prediction. pp. 394–403. graph (5 such graphs in this case). [3] Batbaatar, E., Li, M., and Ryu, K. H. Semantic-emotion neural network for A possible solution to the problem of having too large category emotion recognition from text. IEEE Access 7 (2019), 111866–111878. [4] Guo, J. Deep learning approach to text analysis for human emotion detection graphs might be reducing the length of 𝑛-grams, i.e., using smaller from big data. Journal of Intelligent Systems 31, 1 (2022), 113–126. values of 𝑛, and hence reducing the number of vertices in the [5] Koutra, D., Ramdas, A., Parikh, A., and Xiang, J. Algorithms for graph graph. similarity and subgraph matching, 2011. [6] Li, S., and Gong, B. Word embedding and text classification based on deep Also, reducing the number of 𝑛-grams with which a certain 𝑛- learning methods. MATEC Web of Conferences 336 (01 2021), 06022. gram is connected when constructing the edges of the graph may [7] Prasanna, P., and Rao, D. Text classification using artificial neural networks. be investigated as a possible solution. However, if this value is too International Journal of Engineering and Technology(UAE) 7 (01 2018), 603–606. [8] Quer, S., Marcelli, A., and Sqillero, G. The maximum common subgraph low, too much contextual information may be lost; therefore, it problem: A parallel and multi-engine approach. Computation 8, 2 (may 2020), appears necessary that for each value of n, the optimal number of 48. [9] Tromp, E., and Pechenizkiy, M. Graph-based n-gram language identification 𝑛-grams with which a certain 𝑛-gram is connected is determined on short texts. Proceedings of Benelearn 2011 (01 2011), 27–34. experimentally. [10] Violos, J., Tserpes, K., Varlamis, I., and Varvarigou, T. Text classification us- ing the n-gram graph representation model over high frequency data streams. Frontiers in Applied Mathematics and Statistics 4 (2018). [11] Yang, Y., and Cui, X. Bert-enhanced text graph neural network for classifica- tion. Entropy (Basel) 23 (11 2021). 6 CONCLUSION In this paper, the model that utilizes graph similarity criteria to classify a given text into one of the emotion categories is described. The core of the method is to construct a graph of 𝑛- grams for a given text and to compare this graph to each of the emotion category graphs. The text is classified into the emotion category, the graph of which yielded the highest similarity value when compared to the graph of the given text. From the results of the trials noted in Tables 1 and 2, it may be concluded that among the graph similarity criteria described, that number of edges in the maximum common subgraph resulted in the highest quality of predictions. Furthermore, it may also be noted that employing the number of edges common to both graphs resulted in higher prediction accuracy than using the number of common vertices (0.537 and 0.488 accuracy for the directed graphs). This may appear to be intuitively reasonable as using edges may seem to incorporate more contextual information. Addition- ally, it may be important to investigate the effect of the difference between the size of the graph of 𝑛-gram for the given text and the size of the emotion category graph on the probability that the same connections between the two 𝑛-grams are found in both graphs. Moreover, it may be more probable that the same vertices 98 SLOmet – Slovenian Commonsense Description Adrian Mladenic Erik Novak Dunja Mladenic Marko Grobelnik Grobelnik Department for Artificial Department for Artificial Department for Artificial Intelligence, Intelligence, Intelligence, Department for Artificial Jozef Stefan Institute, Jozef Stefan Institute, Jozef Stefan Institute Intelligence, Jozef Stefan International Ljubljana Slovenia Ljubljana Slovenia Jozef Stefan Institute Postrgraduate School dunja.mladenic@ijs.si marko.grobelnik@ijs.si Ljubljana Slovenia Ljubljana Slovenia adrian.m.grobelnik@ijs.si erik.novak@ijs.si ABSTRACT English, we anticipate a noticeable drop in performance across all metrics for the Slovenian language models. This paper presents Slovenian commonsense description models The main contributions of this paper are (1) the comparison based on the COMET framework for English. Inspired by of the performance of commonsense description models using MultiCOMETs approach to multilingual commonsense description, we finetune two Slovenian GPT-2 language models. different Slovenian language models and the English model, (2) a Experimental evaluation based on several performance metrics comprehensive evaluation using a variety of performance metrics. shows comparable performance to the original COMET GPT-2 An additional contribution (3) is the Slovene ATOMIC-2020 model for English. dataset acquired by machine translation from the original English dataset [6]. KEYWORDS The rest of this paper is organized as follows: Section 2 deep learning, commonsense reasoning, multilingual natural provides the data description. Section 3 describes the problem and language processing, slovenian language model, gpt-2 the experimental setting. Section 4 exhibits our evaluation results. The paper concludes with discussion and directions for future work 1 Introduction in Section 5. Recent research [1] into commonsense representation and reasoning in the field of natural language understanding has 2 Data Description demonstrated promising results for automatic commonsense To train the Slovenian commonsense description models, we use generation. Given a simple sentence or common entity, such data from the ATOMIC-2020 dataset, as proposed in the COMET technology can generate plausible commonsense descriptions framework for English. The ATOMIC-2020 dataset consists of relating to it. However, further testing on complex sentences, English sentences and entities, labelled by up to 23 commonsense uncommon entities, or by increasing the quantity of requested relation types describing their semantics. commonsense descriptions usually gives nonsensical results. Following the recent success on the automatic generation of commonsense descriptions proposed in COMET-ATOMIC 2020 [1], we focus on extending the COMET framework to the Slovenian language. We investigate the impact of different Slovenian language models on the overall performance of commonsense description generation. In our previous research [2], we expanded on an existing approach for automatic knowledge base construction in English [3] to work on different languages. We utilized the original ATOMIC dataset [4]. This was performed by finetuning the original English GPT model from COMET 2019 on automatically translated Slovenian data and evaluated based on exact overlap for the generated commonsense descriptions. Evaluations were performed on a small subset of 100 sentences. In this work we use the updated ATOMIC-2020 dataset [1] and finetune two Slovenian GPT-2 language models. We evaluate the models’ performance using several performance metrics including BLEU, CIDEr, METEOR and ROUGE-L. The evaluation is performed on several thousand sentences and entities; we Figure 1 Close-up of “Event-Centered” descriptor values investigate how the predicted commonsense descriptions’ predicted for an example Slovene sentence “PersonX is sad” performance relates to the language model used. Furthermore, (“OsebaX je žalostna” in Slovenian) given the complexity of the Slovenian language compared to 99 We refer to them as descriptors, 9 of which are identical to METEOR — Metric for Evaluation of Translation with those used in our previous research [2]. The 23 descriptors are Explicit Ordering is a metric initially used for evaluating machine organized into 3 categories: “Physical-Entity”, “Event-Centered”, translation input. The metric is based on the harmonic mean of and “Social-Interaction”. The “Physical-Entity” descriptors capture unigram precision and recall with other features such as stemming knowledge about the usage, location, content, and other properties and synonymy matching. [10] of objects. The “Event-Centered” descriptors include IsAfter, Causes and other descriptors describing events. The “Social- ROUGE-L — Recall-Oriented Understudy for Gisting Interaction” descriptors include xIntent, xNeed, oReact to Evaluation is a metric used for evaluating machine produced distinguish between causes and effects in social settings. An example of a part of a labeled sentence is shown in Figure 1. summaries or translations against a set of human-produced Sentences and entities were manually labelled by human references. The score is calculated using Longest Common workers on Amazon Turk; they were assigned open-text values for Subsequence based statistics, which involves finding the longest 23 commonsense descriptors, reflecting the workers' subjective subsequence common to all sequences in a set. [11] commonsense knowledge. For instance, when workers were given Comparison of the Slovene commonsense models was performed the sentence “PersonX chases the rabbit” and asked to label it for the “xWant” descriptor, one wrote “catch the rabbit” and another by finetuning two state-of-the-art Slovene GPT-2 language models: wrote “cook the rabbit for dinner”. A more detailed explanation can macedonizer/sl-gpt2 [12], gpt-janez [13]. As a reference model, we be found in the ATOMIC-2020 paper. There are 1.33 million used the original COMET-2020 GPT2-XL English language model (possibly repeating) descriptor values. The distribution of data [1]. Moving forward, we will refer to our Slovenian finetuned across the descriptors is depicted in [1]. models as “COMET sl-gpt2” and “COMET gpt-janez”. To finetune our Slovenian language models, we have automatically translated the sentences, entities, and descriptor 4 Experimental Results values from the ATOMIC-2020 dataset from English to Slovenian. The translation was done using DeepL’s Translate API [7]. We We performed a train, test, and development split on the ATOMIC- have found that while the majority of inspected translations were of 2020 dataset identical to the split used in COMET-2020. Our good quality, there were also incorrect translations due to word evaluation split consisted of over 150,000 descriptor values with disambiguation problems. Nevertheless, we conclude that the their corresponding sentences and entities. dataset is of good enough quality to be used for our experiments. We finetuned our Slovene commonsense models on our The translated dataset is publicly available [6]. training set consisting of over 1 million descriptor values. Both models were trained for 3 epochs under the same parameters; the 3 Problem Description and Experimental Setting maximum input length was set to 50, the maximum output length The addressed problem is predicting the most likely values for each was set to 80; the training was performed using a train batch size of descriptor in the Slovene-translated ATOMIC-2020 dataset, given 64. The model updates were performed using the weighted adam a Slovenian input sentence or entity. We take inspiration from the optimizer [14] with the starting learning rate set to 10−5 . The approach proposed in MultiCOMET [2]. experiment’s implementation can be found on our GitHub To compare the performance of the models, repository [5]. we utilize a variety of performance metrics described BLEU- BLEU- BLEU- BLEU- ROUGE- below. Each performance metric is a value between Model Language 1 2 3 4 CIDEr METEOR L 0 and 1 indicating the quality of a generated commonsense descriptor value. Values closer to 1 COMET represent higher quality descriptions. sl-gpt2 Slovene 0.297 0.150 0.086 0.058 0.487 0.207 0.383 BLEU — Bilingual Evaluation Understudy was COMET first used to evaluate the quality of machine gpt- translated text by examining the overlap of candidate janez Slovene 0.324 0.174 0.108 0.076 0.508 0.225 0.397 text n-grams in the reference text. BLEU-1 only uses 1-grams in the evaluation, while BLEU-4 only COMET considers 4-grams. [8] (GPT2- CIDEr — Consensus-based Image Description XL) English 0.407 0.248 0.171 0.124 0.653 0.292 0.485 Evaluation was originally used to measure image description quality. It first transforms all n-grams to their root form, Table 1: Comparison of the two Slovene commonsense models then calculates the average cosine similarity between the candidate with the English model at the bottom. and reference TF-IDF vectors. [9] Experimental results show performance comparable to the original COMET-2020 English model. Both Slovene models were 100 comparable to the English model across all metrics, “COMET gpt- Avto (car) janez” consistently outperformed “COMET sl-gpt2” achieving a METEOR score of 0.225 compared to 0.207. The performance gap Descriptor COMET sl- COMET COMET gpt2 gpt-janez (GPT2-XL) was smallest for BLEU-4, as all models struggled to produce ObjectUse Vožnja do Priti do hiše Drive to the generations whose 4-grams overlapped with those in the reference trgovine store set. The gap in performance between the Slovene and English Vožnja do Priti do hiše Get to the store models could be attributed to multiple factors. The English model hiše from COMET-2020 was trained for longer on more capable Vožnja do Priti do hiše Drive to the hardware and is larger. Moreover, the machine translation done to cilja restaurant acquire our dataset can be erroneous at times. HasProperty Noro Najden v Found in To illustrate the performance of the models, we investigate avtomobilu parking lot their generated descriptor values on the same inputs. Table 2 shows Vrata Najden v Found on road a side-by-side example comparison of the descriptor values avtomobilu generated by our three models, given the same input sentence in Pohištvo Najden v Found in car their respective language. Table 3 compares the models on an avtomobilu dealership example entity. For the example sentence “Marko went to the Table 3: Illustrative example comparing the output of the three shop”, the descriptor “oWant” indicates what the others want as a models on the same input entity across two descriptors. result of the event. “COMET gpt-janez” generates a valid output “None” but fails to provide alternatives. The other two models In our example sentence and entity, COMET gpt-janez agree on the most likely descriptor value being “None” (“nič” in returns the same output when different commonsense descriptors Slovenian) and provide plausible alternatives. The “IsBefore” are requested. We have observed this for all input sentences and descriptor relates to possible events following the input event. In entities thus far. We presume such results are due to the trained our case, “COMET gpt-janez” gives the most plausible output of parameters in the original gpt-janez model, as macedonizer/sl-gpt2 “Buys something”. The other two models provide still plausible was finetuned using the same workflow and returns different outputs including “Is in the pet store” and “PersonX buys a new descriptor values. While unsure of the exact cause, we reason it car”. could be due to an insufficient vocabulary or unoptimized choice Marko je šel v trgovino (Marko went to the shop) of parameters during training. Descriptor COMET sl-gpt2 COMET COMET gpt- (GPT2-XL) janez oWant Nič Nič None Se zahvaliti Nič To give him a osebiX receipt se zahvaliti Nič To give him a discount IsBefore Zaslužiti denar Kupiti PersonX buys nekaj a new car V trgovino za Kupiti PersonX takes hišne ljubljenčke nekaj the car back home V trgovino z živili Kupiti PersonX buys nekaj a new one Table 2: Illustrative example comparing the output of the three models on the same input sentence across two descriptors. Figure 2 Close-up of “Social-Interaction” descriptor values predicted for an example Slovene sentence “John is very For our example entity “car”, the descriptor “ObjectUse” important” (“Janez je zelo pomemben” in Slovenian) describes possible usages for that entity. Table 3 shows all models Figures 1, 2 and 3 show the outputs generated by “COMET are capable of generating plausible descriptor values for such sl-gpt2” for three different inputs. Figure 2 visualizes the output for common entities. Nevertheless, the descriptor “HasProperty” the sentence “John is very important”. Outputs include “PersonX is proves challenging for the Slovenian models, suggesting a car is then accomplished, happy, proud” and “As a result, others want “crazy” and is “found in the car”. The English model gives none, to thank PersonX”. We can see that for many descriptors the reasonable outputs such as “Found in parking lot”. highest ranked output is “None” (“nič” in Slovenian), indicating no commonsense inference can be made. 101 in the holes” for the “IsBefore” descriptor. While both labels are plausible for some context, they are not necessarily true. Possible directions for future work include evaluating the models’ performance for individual descriptors, as there are drastic differences in quantity of training data and lengths of values across them. After achieving results comparable to the original English commonsense model COMET-2020 GPT2-XL, we intend to finetune and evaluate models for other languages. ACKNOWLEDGMENTS The research described in this paper was supported by the Slovenian research agency under the project J2-1736 Causalify, the RSDO project funded by the Development of Slovene in a Digital Environment project, and the Humane AI Net European Unions Horizon 2020 project under grant agreement No 952026. REFERENCES [1] Hwang, J.D., Bhagavatula, C., Le Bras, R., Da, J., Sakaguchi, K., Figure 3 Close-up of “Physical-Entity” descriptor values Bosselut, A., & Choi, Y. (2021). COMET-ATOMIC 2020: On Symbolic predicted for an example Slovene entity “banana” and Neural Commonsense Knowledge Graphs. AAAI. Figure 3 exhibits the output for the entity “banana”, the [2] Mladenic Grobelnik, A., Mladenić, D., & Grobelnik, M. (2020). MultiCOMET - Multilingual Commonsense Description. In Proc. SiKDD model claims the banana can be used to prepare food, is located in 2020, Ljubljana, Slovenia (pp. 37–40). a building or shop, desires to be eaten for dinner and does not desire [3] Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, to be frozen. On the other hand, the model claims the banana is Asli Celikyilmaz, Yejin Choi. (2019). COMET: Commonsense made up of clothes and is capable of going to a restaurant. This is Transformers for Automatic Knowledge Graph Construction. [4] Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, likely due to the overall significantly lower number of physical- Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin entity descriptor values provided in the ATOMIC-2020 dataset. Choi. (2019). ATOMIC: An Atlas of Machine Commonsense for If-Then In Figure 1 we can see the “Event-Centered” descriptors for Reasoning. Paul G. Allen School of Computer Science & Engineering, the sentence “PersonX is sad”. Top descriptor values are again University of Washington, Seattle, USA. Allen Institute for Artificial Intelligence, Seattle, USA. “None”, but the model also claims it is more difficult for PersonX [5] SLOmet-ATOMIC 2020 Github https://github.com/eriknovak/RSDO- to be sad, if PersonX has no money. SLOmet-atomic-2020#slomet-atomic-2020-on-symbolic-and-neural- commonsense-knowledge-graphs-in-slovenian-language Accessed 5 Discussion 30.08.2022 [6] ATOMIC-2020 Slovene Machine Translated Data This paper applied an existing approach to multilingual https://www.dropbox.com/sh/gs8iqcwpwkaqkuf/AAAmnCqG89JOz_umtq commonsense description to the Slovene language. To implement 42MMxxa?dl=0 Accessed 30.08.2022 our approach, we machine translated the ATOMIC-2020 dataset to [7] DeepL Translate API https://www.deepl.com/pro-api Accessed 30.08.2022 Slovene and finetuned two Slovene commonsense models. We [8] Papineni, Kishore & Roukos, Salim & Ward, Todd & Zhu, Wei Jing. compared our models to the original English commonsense model (2002). BLEU: a Method for Automatic Evaluation of Machine from COMET-2020 and achieved comparable experimental results Translation. across multiple performance metrics. Among others, our models [9] Vedantam, R., Lawrence Zitnick, C., & Parikh, D. (2015). Cider: Consensus-based image description evaluation. In Proceedings of the achieved a 0.487 CIDEr score, a 0.383 ROUGE-L score, and a IEEE conference on computer vision and pattern recognition (pp. 4566- BLEU-1 score of 0.297. 4575). Through examination of individual examples, we observed [10] Lavie, Alon & Denkowski, Michael. (2009). The METEOR metric that while “COMET gpt-janez” has the highest performance scores for automatic evaluation of Machine Translation. Machine Translation. 23. 105-115. on the Slovene language, it fails to provide alternative descriptor [11] Lin, C.-Y. 2004. ROUGE: A Package for Automatic Evaluation of values. “COMET sl-gpt” provides multiple values for the same Summaries. In Text Summarization Branches Out. descriptor, but in average has lower performance. It is important to [12] Documentation page for “macedonizer/sl-gpt2” on HuggingFace emphasize the models were trained on subjective commonsense https://huggingface.co/macedonizer/sl-gpt2 Accessed 1.09.2022 [13] gpt-janez supporting project: RSDO knowledge provided by individual humans. For example, workers https://www.cjvt.si/rsdo/en/project/ Accessed 30.08.2022 labelled the sentence “PersonX digs holes” with the descriptor [14] I. Loshchilov, F. Hutter, Decoupled weight decay regularization, in: values “PersonX plants a garden” and “PersonX places fence posts International Conference on Learning Representations, 201 102 Measuring the Similarity of Song Artists using Topic Modelling Erik Calcina Erik Novak Jožef Stefan Institute Jožef Stefan International Postgraduate School Jamova cesta 39 Jožef Stefan Institute Ljubljana, Slovenia Jamova cesta 39 Ljubljana, Slovenia ABSTRACT 2 RELATED WORK In music streaming platforms, it is necessary a recommendation Related works to our topic modeling approach use Latent Dirich- system to provide users with similar songs of what they already let Allocation (LDA) [1]. One work uses a topic modeling tech- listen and also recommend new artists they might be interested nique for sentiment classification, classifying between happy in. In this paper, we present a method to find similarities between and sad songs, by using generated topics created with LDA and artists that uses topic modelling. We have evaluated the method Heuristic Dirichlet Process [12]. From a data set consisting of 150 using a data set with music artists and their lyrics. The results lyric they’ve been able to retrieve the sub-division of two defined show the method finds similar artists, but also is dependant on sentiment classes [3]. Another work used LDA and Pachinko the quality of the generated topic clusters. allocation [7] on a large data set for assessing the quality of the generated topics with applying supervised topic modeling ap- KEYWORDS proach. [8]. In our paper we use topic modeling to generate a set of topic clusters used to calculate the similarity between artists. song lyrics, topic modelling, clustering, sentence embeddings, language models 3 METHODOLOGY 1 INTRODUCTION In this section, we present the methodology used in this paper. We present the topic modeling approach used to generate the Nowadays, there are a plenty of music platforms to choose from topic clusters, followed by a description of how the topic clusters and listen to music. There, new artists appear every day and are used to measure the similarity between the artists. many different songs are published. If we take into account all that have been created, we get a large selection of songs which 3.1 Topic Modeling can increase the difficulty of finding suitable songs or artists to To create the topic clusters we use BERTopic [5], a method which listen to. uses document embeddings with clustering algorithms to create To find a suitable artist or songs, different aspects can be topic clusters. While BERTopic is described in a separate work, considered. One such aspect can be the topic of the song; a song we present a brief description of its workflow. The workflow is topic can be interpreted as the main subject of the song, for also presented in Figure 1. example it can be an emotion, an event, a message, or something else. When searching for suitable artists one could decide to search for artists who have songs on similar topics. In this paper, we propose an topic modeling-based approach for measuring the similarity of the music artists based only on their song lyrics. The approach uses language models for gener- ating song embeddings used to create the topic clusters. These topic clusters are then analyzed to find the similar artists. The experiment was performed on a data set of songs corresponding to fourteen (14) music artists. While the experiment shows that similar artists can be detected using the approach, there is still room for improving its performance. The main contribution of this paper is a novel approach for detecting similar music artists using topic modelling. The reminder of the paper is structured as follows: Section 2 contains the overview of the related work on using topic mod- elling on song data sets. Next, we present the methodology in Section 3, and describe the experiment setting in Section 4. The experiment results are found in Section 5, followed by a discus- sion in Section 6. Finally, we conclude the paper and provide ideas for future work in Section 7. 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 Figure 1: The BERTopic methodology workflow. The high- the full citation on the first page. Copyrights for third-party components of this lighted part is used in our approach. The image has been work must be honored. For all other uses, contact the owner /author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia designed using resources from Flaticon.com. © 2022 Copyright held by the owner/author(s). 103 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Erik Calcina and Erik Novak Document Embeddings. Document vector representations are The attributes used in our analysis are song name, artist and generated using a sentence-transformer [11] model. The model lyrics. creates a semantic representation of the documents, which al- Data Processing. For our experiment we took fourteen (14) lows measuring the semantic similarity. The available models artists of various degrees of similarity. This reduces the data set support creation of both monolingual and multilingual vectors. to 4,470 rows which is 2.05% of the whole data set. Since the embeddings will be used as an input of a clustering After reviewing the lyrics, we realized that the data set has algorithm, dimensionality reduction is performed to improve the many song variations by the same artist, which can be seen as clustering results. The dimensionality reduction algorithm used duplicates. To find and remove the duplicates, we created the is UMAP [10]. TF-IDF representations for the songs, and calculated the cosine Document Clustering. Once the document embeddings are pre- similarity with all other songs of the same artist; if the similarity pared, they are input into a clustering algorithm to create the is greater than 50% it was labeled as a duplicate and removed topic clusters. The algorithm used is HDBSCAN [9], an optimized from the data set. This resulted in a smaller data set containing extension of the DBSCAN [4] algorithm. The chosen algorithm 3,455 song lyrics. creates clusters based on the density of the document embedding The final data set statistics used for our experiments is shown space, which allows the documents to not be assigned to a cluster in Table 1. if it’s not similar to any of the neighbouring documents. Table 1: The experiment data set statistics. For each artist Topic Word Description. Once the topic clusters are created, a we denote the music genre of the artist (genre), the num- topic word description is generated using the document’s text. ber of their songs in the data set (songs), and the average For each cluster the TF-IDF score is calculated for each word number of words in the song’s lyrics (avg. length). found in any of the cluster’s documents; the scores are called cluster TF-IDF (c-TF-IDF). The words with the highest c-TF-IDF Artist genre songs avg. length score are then chosen as the topic word description. Furthermore, maximal marginal relevance (MMR) is performed to diversify black-sabbath Rock 160 184 the selected words by measuring both the words relevance to bon-jovi Rock 320 266 the documents, and its similarity to the other selected words. dio Rock 127 203 Note that the topic word description were used only for the aerosmith Rock 208 226 preliminary analysis of our work, but not for measuring artists ac-dc Rock 171 193 similarity. coldplay Rock 138 174 50-cent Hip-Hop 318 502 3.2 Artists’ Similarity using Topic Clusters 2pac Hip-Hop 259 648 Once the topic clusters are created, the similarity between artists eminem Hip-Hop 369 640 can be measured. First, for each topic we count the songs that cor- black-eyed-peas Hip-Hop 119 463 responds to a particular artist. This gives us the number of songs celine-dion Pop 182 230 an artist has in a particular topic. To ensure that the presence is britney-spears Pop 225 313 strong enough, we decide to remove the artists from a topic if the frank-sinatra Jazz 356 133 number of their associated songs is below some threshold. The ella-fitzgerald Jazz 503 156 threshold is set to five (5) in order to ensure that the songs were Together - 3,455 319 not assigned to a cluster by coincidence. Afterwards, for each pair of artists we calculate their similarity using the following equation: |𝐴 ∩ 𝐵| 4.2 Implementation details sim (𝑎, 𝑏) = , (1) |𝐴| In this section, we present the details of how the approach is where 𝐴 is the set of topics of artist 𝑎, and 𝐵 is the set of topics developed. of artist 𝑏 . Language model. The method uses the pre-trained Sentence 1 Transformer model, more precisely the all-mpnet-base-v2 model , 4 EXPERIMENT available via the HuggingFace’s transformer library [13]. It can We now present the experiment setting. First, we introduce the take up to 384 tokens as one input, which is more than the average data set used and its pre-processing steps. Next, we describe the number of words in our data set, and returns a 768 dimensional implementation details. dense vectors. The vectors have been shown to be appropriate for task such as clustering and semantic search. 4.1 Dataset Dimensionality reduction. To perform dimensionality reduc- To test our approach, we use a dataset with raw lyrics data [2]. tion, we set the UMAP parameters as follows: Fist, the number of The dataset consists of 218,210 rows containing the following neighboring sample points used when making the manifold ap- attributes: proximation is set to five (5), to make the algorithm use the local • Song name. The name of the song. proximity of the documents. Second, we set the dimensionality • Release year. The year when the song was released. of the embeddings to one (1). This values were selected using • Song artist. The name of the artist. hyper-parameter tuning. • Artist genre. The genre of the song. • Song lyrics. The lyrics text of the song. 1 https://huggingface.co/sentence-transformers/all-mpnet-base-v2 104 Measuring the Similarity of Song Artists using Topic Modelling Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Clustering algorithm. Absolute co-occurrence of artists in topic clusters. In the HDBSCAN algorithm, the mini- mum number of documents in a cluster is set to five (5). 5 RESULTS In this section, we present the experiment results. We analyze the topic clusters, followed by the description of the finding on artist’s similarity. Topic Cluster Analysis. The experiment has generates 215 topic clusters, out of which only 107 have at least one artist with more than five (5) songs in it. The cluster containing songs that are deemed as outliers is not included in the analysis. The statistics of the topic clustering is shown in Table 2. Ev- idently, artists with a larger number of songs are spread over several topic clusters than those with less songs. Table 2: Topic clustering results. For each artist we show the number of different topics the artist is asociated with (topics), and the average number of their songs in the asso- Figure 2: The absolute co-occurrence of artists in topic ciated topics (avg. songs). clusters. Artist topics #avg. songs Relative co-occurrence of artists in topic clusters. black-sabbath 6 5 bon-jovi 10 6 dio 4 7 aerosmith 9 6 ac-dc 7 5 coldplay 2 5 50-cent 17 9 2pac 13 9 eminem 18 9 black-eyed-peas 3 12 celine-dion 8 6 britney-spears 12 6 frank-sinatra 16 8 ella-fitzgerald 28 8 Artists’ Similarity Analysis. The artists’ similarity is shown in Figures 2 and 3, which show the heatmaps of the absolute and Figure 3: The relative co-occurrence of artists in topic clus- relative co-occurrence of artists in topic clusters, respectively. ters. Artists with smaller number of topics can result in By looking at rows of Figure 2, we see the number of common higher similarity with other artists. topics with other artists. For example, by taking 50-cent with his 17 topics, we see that he shares five (5) of them with 2pac, one (1) with black-eyed-peas, one (1) with ac-dc, and six (6) with Language Models Limitations. The chosen language model eminem. From this we conclude that 50-cent, 2pac and eminem all-mpnet-base-v2 supports a maximum sequence length of have more topics in common than the rest of the artists. In other 384 tokens which is the downside of this model for our experi- words, 50-cent is more similar to the 2pac and eminem than to ment. Although the average number of words in the song lyrics is the rest of the artists. below the input limit, some artist have songs that are longer than Figure 3 shows the similarities calculated using Equation 1. that. However, songs have repeating sections, e.g. chorus, which The similarities become more visible, but at the same time can be is most likely inside the first 384 words. Therefore, the language also misleading. Artists with smaller number of topics can result models may not create a representation out of the whole song’s in higher similarity with other artists with higher number of lyrics, but it might capture the majority because of the song’s topics. For example, Coldplay have two (2) topics, one of which repeated text. is shared with Bon Jovi. Despite the fact that only one topic is in common, it is unlikely they have a similarity of 50%. Clustering Algorithm Selection. The clustering algorithm HDB- SCAN can create a cluster consisting of examples, which do not 6 DISCUSSION fall into any of the topic clusters. It is convenient when instead of In this section we discuss the advantages and disadvantages of forcing songs into clusters, it labels them as outliers. The down- the proposed methodology, and its possible improvements. side is when the majority of songs are labeled as outliers. To 105 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Erik Calcina and Erik Novak avoid this, other clustering algorithms that assign a cluster to [8] Alen Lukic. A comparison of topic modeling approaches every document can be used, for example K-means clustering [6]. for a comprehensive corpus of song lyrics. Tech. rep. Tech report, Language Technologies Institute, School of Com- 6.1 Topic Cluster Discussion puter Science . . ., 2015. Some artists with a small number of songs have a lower number [9] Leland McInnes and John Healy. “Accelerated Hierarchical of topics assigned, which is a problem for finding similarities. Density Based Clustering”. In: 2017 IEEE International Con- On the other side artists with higher number of songs tend to ference on Data Mining Workshops (ICDMW). 2017, pp. 33– have more topics. Additionally, to avoid taking into account small 42. doi: 10.1109/ICDMW.2017.12. number of artist co-occurrances, which can be a product of data [10] Leland McInnes, John Healy, and James Melville. UMAP: noise, a filter threshold can be considered to remove them from Uniform Manifold Approximation and Projection for Dimen- the final analysis. sion Reduction. 2018. doi: 10.48550/ARXIV.1802.03426. url: https://arxiv.org/abs/1802.03426. 7 CONCLUSION [11] Nils Reimers and Iryna Gurevych. “Sentence-BERT: Sen- tence Embeddings using Siamese BERT-Networks”. In: In this paper we present a way to measure similarity between Proceedings of the 2019 Conference on Empirical Methods music artists using topic modeling. We cluster lyrics and compare in Natural Language Processing. Association for Computa- artists based on the generated topic clusters. The results have tional Linguistics, Nov. 2019. url: https://arxiv.org/abs/ shown that the approach finds similar artists. However, it is 1908.10084. heavily dependent on the number and quality of the topic clusters. [12] Chong Wang, John Paisley, and David Blei. “Online varia- In the future, we intend to apply the methodology on a larger tional inference for the hierarchical Dirichlet process”. In: data set of song lyrics and artists. In addition, we intend to use Proceedings of the fourteenth international conference on all of the topic cluster information (including topic word descrip- artificial intelligence and statistics. JMLR Workshop and tions) in order to improve the methodology’s performance. Conference Proceedings. 2011, pp. 752–760. ACKNOWLEDGMENTS [13] Thomas Wolf et al. “Transformers: State-of-the-Art Natu- ral Language Processing”. In: Proceedings of the 2020 Con- This work was supported by the Slovenian Research Agency and ference on Empirical Methods in Natural Language Pro- the Slovene AI observatory under proposal no. V2-2146. cessing: System Demonstrations. 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[4] Martin Ester et al. “A density-based algorithm for discov- ering clusters in large spatial databases with noise”. In: AAAI Press, 1996, pp. 226–231. [5] Maarten Grootendorst. “BERTopic: Neural topic modeling with a class-based TF-IDF procedure”. In: arXiv preprint arXiv:2203.05794 (2022). [6] Xin Jin and Jiawei Han. “K-Means Clustering”. In: Ency- clopedia of Machine Learning. Ed. by Claude Sammut and Geoffrey I. Webb. Boston, MA: Springer US, 2010, pp. 563– 564. isbn: 978-0-387-30164-8. doi: 10 . 1007 / 978 - 0 - 387 - 30164 - 8 _ 425. url: https : / / doi . org / 10 . 1007 / 978 - 0 - 387 - 30164- 8_425. [7] Wei Li and Andrew McCallum. “Pachinko allocation: DAG- structured mixture models of topic correlations”. In: ICML ’06: Proceedings of the 23rd international conference on Ma- chine learning. New York, NY, USA: ACM, 2006, pp. 577– 584. isbn: 1595933832. doi: 10.1145/1143844.1143917. url: http://portal.acm.org/citation.cfm?id=1143917. 106 Exploring the Impact of Lexical and Grammatical Features on Automatic Genre Identification Taja Kuzman Nikola Ljubešić taja.kuzman@ijs.si nikola.ljubesic@ijs.si Jožef Stefan Institute and Jožef Stefan International Jožef Stefan Institute Postgraduate School Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT As learning on lexical features can introduce bias towards topic, Laippala et al. (2021) recently experimented with combin- This study analyses the impact of several types of linguistic fea- ing lexical with grammatical features, which are represented as tures on the task of automatic web genre identification applied part-of-speech tags, conveying information on the word type (e.g., to Slovene data. To this end, text classification experiments with noun, verb). This showed to yield better results than using solely the fastText models were performed on 6 feature sets: original lexical features, and provided more stable models, i.e., models lexical representation, preprocessed text, lemmas, part-of-speech that are able to generalize beyond the training data. Further- tags, morphosyntactic descriptors, and syntactic dependencies, more, their analysis revealed that the importance of feature sets produced with the CLASSLA pipeline for language processing. varies between genre categories, and that while some are most Contrary to previous work, our results reveal that the grammati- efficiently identified when learning on lexical features, others cal feature set can be more beneficial than lexical representations benefit more from grammatical representations. for this task, as syntactic dependencies were found to be the most However, these experiments were in past mostly performed informative for genre identification. Furthermore, it is shown on English datasets. This article is the first to analyse the impact that this approach can provide insight into variation between of various feature sets on automatic genre identification applied genres. to Slovene data. This research was made possible by the recent KEYWORDS development of the first Slovene dataset, manually annotated with genre, as well as the creation of state-of-the-art language language processing, linguistic features, automatic genre identi- processing tools for Slovene. To compare textual representations, fication, web genres, Slovene additional feature sets were created from a selection of texts an- notated with genre, presented in Section 2, by using common 1 INTRODUCTION preprocessing methods and language processing (see Section 3). Automatic genre identification (AGI) is a text classification task Thus, in this paper, 6 textual representations are compared: 1) where the focus is on genres as text categories that are defined original, running text that we consider as our baseline, 2) pre- based on the conventional function and/or the form of the texts. processed text, i.e. lowercase text without punctuation, digits In text classification tasks, texts are generally given to the ma- and stopwords, 3) lemmas, i.e. base dictionary forms of words, chine learning models in form of words or characters that are 4) part-of-speech (PoS) tags, i.e. main syntactic word types (e.g., then further transformed into numeric vectors by using bag-of- noun, verb), 5) morphosyntactic descriptors (MSD), i.e. extended words representations, or word embeddings created by training PoS tags which include information on morphosyntactic features deep neural networks on the surface text. However, recent devel- (e.g., number, case), 6) syntactic dependencies, i.e. types of depen- opment of tools for linguistic processing for numerous languages, dency relations between words (e.g. subject, object). The feature including Slovene, allows transformation of the original running sets are compared based on their impact on the performance text into various other sets of features to which further transfor- of the fastText models on the automatic text classification task. mation into numeric representations can be applied. By learning The results of the experiments, presented in Section 4, give in- on these linguistic sets, we get insight into the importance of fea- sights into the role of linguistic feature sets on this task and the tures that cannot be analysed separately when given the running differences in performance between genre categories. text, i.e., word meaning, function of a word, and its relation to other words. 2 DATASET When previous work compared importance of various textual feature sets on the performance of the models in automatic genre For performing experiments in automatic genre identification, identification, lexical features, i.e., word or character n-grams, the Slovene Web genre identification corpus GINCO 1.0 [2] was mainly provided the best results ([6], [7]). However, it was noted used. The dataset consists of the “suitable” subset, annotated with that by learning on lexical features, the models could learn to genre, and the “not suitable” subset that comprises texts which classify texts based on the topic instead of genre characteristics, can be deemed as noise in the web corpora, e.g., texts without and would not be able to generalize beyond the dataset. full sentences, very short texts, machine translation etc. In this research, only the “suitable” subset, containing 1002 texts, was Permission to make digital or hard copies of part or all of this work for personal used. or classroom use is granted without fee provided that copies are not made or The GINCO schema consists of 24 genre labels. However, pre- 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 vious experiments, performed with the fastText model on the work must be honored. For all other uses, contact the owner /author(s). entire dataset, showed that the model is not potent enough to Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia differentiate between a large number of labels that are mostly © 2022 Copyright held by the owner/author(s). represented by less than 100 texts, reaching micro and macro 107 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Taja Kuzman and Nikola Ljubešić Table 1: The original GINCO categories (left) included in 3 FEATURE ENGINEERING the reduced set, and the reduced set of labels (right), used Feature engineering is a process of identifying features that are in the experiments, with the total number of texts (later most useful for a specific task with the goal of improving per- divided between the train, dev and test split) in the paren- formance of a machine learning model. In text classification ex- theses. periments, basic preprocessing methods are often used to reduce the number of unique lexical features (words or characters) with- GINCO Reduced Set out losing much information which could provide better results. To test whether preprocessing the text improves the results for News/Reporting News (198) this task, the first additional feature set was created by prepro- Opinionated News cessing the running text as extracted from the GINCO dataset. Information/Explanation Preprocessing consisted of the following steps: converting text to Information/Explanation (127) Research Article lowercase, and removing digits, punctuation and function words Opinion/Argumentation known as stopwords, e.g., conjunctions, prepositions etc. Opinion/Argumentation (124) Review In addition to this, various linguistic representations were cre- ated by applying linguistic processing to the texts, and replacing Promotion words with corresponding lemmas or grammatical tags. The lan- Promotion of a Product Promotion (191) guage processing was performed with the CLASSLA pipeline [5]. Promotion of Services The following text representations were produced: lexical feature Invitation set, consisting of lemmas, and three grammatical feature sets: Forum Forum (48) part-of-speech (PoS) tags, morphosyntactic descriptors (MSD), and syntactic dependencies. The realisation of the created feature sets is illustrated on an example sentence in Table 2. 4 MACHINE LEARNING EXPERIMENTS 4.1 Experimental Setup F1 scores of 0.352 and 0.217 respectively (see [3]). Therefore, to The experiments were performed with the linear fastText [1] be able to infer any meaningful conclusions, this article focuses model which enables text classification and word embeddings only on the most frequent genre labels, created by merging some generation. The model is a shallow neural network with one hid- labels. Instances of less frequent labels that could not be merged, den layer where the word embeddings are created and averaged namely Instruction, Legal/Regulation, Recipe, Announcement, Cor- into a text representation which is fed into a linear classifier. The respondence, Call, Interview, Prose, Lyrical, Drama/Script, FAQ, model takes as an input a text file where each line contains a and the labels Other and List of Summaries/Excerpts, which can separate text instance, consisting of a label and the corresponding be considered as noise, were not used. To focus only on the in- document. Thus, for each feature set, appropriate train, test and stances that are representative of their genre labels, texts that dev files were created, and the model was trained on each repre- were manually annotated as hard to identify (parameter hard) 1 sentation separately . To observe the dispersion of results, five were not used in the experiments. Furthermore, paragraphs that runs of training were performed for each feature set. To measure were deemed to be noise in the text, e.g., cookie consent text, and the model’s performance on the instance and the label level, the were marked by the annotators with the keep parameter set to micro and macro F1 scores were used as evaluation metrics. False, were left out of the final texts. The hyperparameter search was performed by training the Thus, the final set of labels, used in the experiments, shown in model on the training split of the baseline text and evaluating Table 1, consists of 5 genre categories, Information/Explanation, it on the dev split. The automatic hyperparameter optimisation News, Opinion/Argumentation, Promotion and Forum. As shown in provided by the fastText model did not yield satisfying results, as the Table, the dataset is imbalanced, with News and Promotion be- three runs of automatic hyperparameter optimisation produced ing the most frequent classes, consisting of almost 200 instances, very different results in terms of proposed optimal hyperparame- while Forum is the least represented class, consisting of about 50 ter values and yielded micro F1 0.479 ± 0.02 and macro F1 0.382 texts. The subset, consisting of 688 texts in total, followed the ± 0.06. Therefore, we continued searching for optimal hyperpa- original stratified split of 60:20:20, encoded in the GINCO 1.0 rameters by manually changing one hyperparameter at a time dataset, and the models were trained on the training set, tested on the test set, while the dev split was used for evaluating the 1 The code for data preparation and machine learning experiments is published here: hyperparameter optimisation. https://github.com/TajaKuzman/Text- Representations- in- FastText. Table 2: An example of the feature sets used in the experiments. Feature Set Example Baseline - Running Text V Laškem se bo v nedeljo, 21.4.2013 odvijal prvi dobrodelni tek Veselih nogic. Preprocessed Baseline laškem nedeljo odvijal dobrodelni tek veselih nogic Lemmas v Laško se biti v nedelja , 21.4.2013 odvijati prvi dobrodelen tek vesel nogica . PoS ADP PROPN PRON AUX ADP NOUN P UNCT NUM VERB ADJ ADJ NOUN ADJ NOUN P UNCT MSD Sl Npnsl Px——y Va-f3s-n Sa Ncfsa Z Mdc Vmpp-sm Mlomsn Agpmsny Ncmsn Agpfpg Ncfpg Z Dependencies case nmod expl aux case obl punct nummod root amod amod nsubj amod nmod punct 108 Exploring the Impact of Linguistic Features on AGI Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Table 4: Average micro and macro F1 scores obtained from and conducting classification experiments. The optimum number five runs of training and testing on each representation of epochs revealed to be 350, the learning rate was set to 0.7, separately. and the number of words in n-grams to 1. For the other hyperpa- rameters, the default values were used. Manual hyperparameter search revealed to be considerably more effective than automatic Representation Micro F1 Macro F1 optimisation, as it yielded the average micro and macro F1 scores Baseline Text 0.560 ± 0.00 0.589 ± 0.00 of 0.625 ± 0.004 and 0.618 ± 0.003 respectively, which is in aver- Preprocessed Baseline 0.596 ± 0.00 0.597 ± 0.00 age 0.15 points better micro F1 and 0.24 points better macro F1 Lemmas 0.597 ± 0.01 0.601 ± 0.00 compared to the results of automatic optimisation. PoS 0.540 ± 0.01 0.547 ± 0.01 To analyse whether our choice of technology is the most ap- MSD 0.563 ± 0.01 0.536 ± 0.02 propriate one, we compared the performance of the fastText Dependencies 0.610 ± 0.00 0.639 ± 0.00 model, which uses the hyperparameters mentioned above, with the performance of various non-neural classifiers, commonly used in text classification tasks: dummy majority classifier which 1 reveals that preprocessing especially improves the identifica- predicts the most frequent class to every instance, support vec- tion of Promotion and News. The two labels are the most frequent tor machine (SVM), decision tree classifier, logistic regression genre classes in the dataset which explains larger improvement classifier, random forest classifier, and Naive Bayes classifier. We of the micro F1 scores. If we compare the baseline text and the used the default parameters for the classifiers. The models are preprocessed text to the third lexical set, i.e., lemmas, the results compared based on their performance on the baseline text which show that by using lowercase words, reduced to their dictionary was transformed into the TF-IDF representation where necessary. base form, the performance is further improved, although only As shown in Table 3, fastText outperforms all other classifiers slightly, as can be seen in Table 4. with a noticeable difference especially in the macro F1 scores, Secondly, we compared various lexical and grammatical fea- reaching 17 points higher scores than the next best classifier, the ture sets, obtained with language processing tools. In previous Naive Bayes classifier. work, which analysed English genre datasets, lexical features yielded better results than grammatical feature sets ([4], [6], [7]). Table 3: Micro and macro F1 scores obtained by various Our results revealed that this conclusion holds also for Slovene classifiers, trained and tested on the baseline text. when training on part-of-speech tags. Similar conclusion can be made for the extended part-of-speech tags (MSD) which only Classifier Micro F1 Macro F1 slightly improve the micro F1 scores compared to the baseline while there is a decrease in the macro F1 scores (see Table 4). Dummy Classifier 0.24 0.08 However, the third grammatical feature set, consisting of tags for Support Vector Machine 0.49 0.33 syntactic dependencies, which was not used in previous work, Decision Tree 0.34 0.35 significantly outperformed the baseline text and all other fea- Logistic Regression 0.52 0.38 ture sets. As shown in Figure 1, the improvement is especially Random Forest classifier 0.51 0.41 noticeable for the categories Forum, Opinion/Argumentation and Naive Bayes classifier 0.54 0.42 News. By learning on the dependencies instead on lexical fea- FastText 0.56 0.59 tures, the model learns from the structure of the sentences in the text, i.e., the syntax, instead of word meanings that can be more related to topic than genre, which could be the reason why 4.2 Results of Learning on Various Linguistic this representation was revealed to be the most beneficial for the Features task. As in previous work (see [4]), the experiments have revealed a To explore the role of various textual representations on the au- dependence between the text representation and performance on tomatic genre identification of Slovene web texts, we conducted specific genre labels, which is illustrated in Figure 1. The results text classification experiments with the fastText models on 6 show that Promotion and Information/Explanation can be most feature sets: successfully identified when learning purely on the meaning of • three lexical sets: a) baseline text, i.e., the original run- the words, i.e., on lemmas. In contrast to that, for identifying ning text, b) preprocessed baseline text, i.e., baseline text News, grammatical representations are more useful than lexical converted to lowercase and without punctuation, digits ones. Similarly, Opinion/Argumentation benefits more from gram- and function words, c) lemmas, i.e., words reduced to their matical feature sets than lexical representations, except in case base dictionary forms; of the MSD tags which significantly decreased the results for this • three grammatical sets: a) part-of-speech (PoS), i.e., main class, yielding F1 scores below 0.3. Interestingly, although Forum word types, b) morphosyntactic descriptors (MSD), i.e., is the least frequent label, its features seem to be the easiest to extended PoS tags, c) syntactic dependencies, i.e., types of identify in the majority of representations. This genre benefits words defined by their relation to other words. the most from learning on syntactic dependencies tags, which yielded F1 scores of almost 0.9. First, by comparing the baseline representation and the prepro- cessed representation, we aimed to determine whether common 5 CONCLUSIONS preprocessing methods can improve the results in the AGI task. As shown in Table 4, the results reveal that applying preprocess- In this paper, we have investigated the dependence of automatic ing methods improves the performance, especially on the micro genre classification on the lexical and grammatical representation F1 level. Analysis of the F1 scores obtained for each label in Figure of text. Our experiments, performed on three lexical and three 109 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Taja Kuzman and Nikola Ljubešić Figure 1: The impact of various linguistic features on the F1 scores of genre labels (Information/Explanation, Promotion, News, Forum and Opinion/Argumentation). grammatical feature sets, revealed that the choice of textual rep- ACKNOWLEDGMENTS resentation impacts the results of automatic genre identification. This work has received funding from the European Union’s Con- Similarly to previous work, it was revealed that part-of-speech necting Europe Facility 2014-2020 - CEF Telecom, under Grant features give worse results than lexical features. However, a gram- Agreement No. INEA/CEF/ICT/A2020/2278341. This communica- matical feature set, consisting of syntactic dependencies, that has tion reflects only the author’s view. The Agency is not responsible not been studied in previous work, revealed to be the most ben- for any use that may be made of the information it contains. This eficial for the automatic genre identification task. Furthermore, work was also funded by the Slovenian Research Agency within the experiments revealed variation between genres regarding the the Slovenian-Flemish bilateral basic research project “Linguistic impact of feature sets on the F1 scores of each label. While some landscape of hate speech on social media” (N06-0099 and FWO- genres, such as Promotion, benefit more from learning on lexical G070619N, 2019–2023) and the research programme “Language features, others, such as Opinion/Argumentation, benefit more resources and technologies for Slovene” (P6-0411). from grammatical representations. 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This is why we plan to continue [3] Taja Kuzman, Peter Rupnik, and Nikola Ljubešić. 2022. The genre annotation campaigns to enlarge the Slovene genre dataset, GINCO Training Dataset for Web Genre Identification of which would allow extending the analysis to all genre labels. In Documents Out in the Wild. In Proceedings of the Language addition to this, as we are interested in cross-lingual genre iden- Resources and Evaluation Conference. European Language tification, in the future, we plan to analyse the importance of Resources Association, Marseille, France, 1584–1594. https: linguistic feature sets on the Croatian and English genre datasets //aclanthology.org/2022.lrec- 1.170. to analyse whether the characteristics of genre labels are lan- [4] Veronika Laippala, Jesse Egbert, Douglas Biber, and Aki- guage independent. Juhani Kyröläinen. 2021. 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Association for Computa- base-sized XLM-RoBERTa model reached micro and macro F1 tional Linguistics, Florence, Italy, (August 2019), 29–34. scores 0.816 and 0.813, which is 22–26 points more than the fast- doi: 10 . 18653 / v1 / W19 - 3704. https : / / www. aclweb . org / Text model. Based on the findings from this paper, one of the anthology/W19- 3704. reasons why the Transformer models perform better could also [6] Dimitrios Pritsos and Efstathios Stamatatos. 2018. Open set be that the Transformer text representations incorporate infor- evaluation of web genre identification. Language Resources mation on syntax as well. In the future, we plan to investigate and Evaluation, 52, 4, 949–968. this further, adapting the classifier heads so that the syntactic [7] Serge Sharoff, Zhili Wu, and Katja Markert. 2010. The Web information has a larger impact on the classification than the Library of Babel: evaluating genre collections. In LREC. lexical parts of the representation. Citeseer. 110 Stylistic features in clustering news reporting: News articles on BREXIT Abdul Sittar Jason Webber Dunja Mladenić abdul.sittar@ijs.si jason.webber@bl.uk dunja.mladenic@ijs.si Jožef Stefan Institute and Jožef British Library Jožef Stefan Institute and Jožef Stefan Postgraduate School London, United Kingdom Stefan Postgraduate School Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT Table 1: List of all the stylistic features that are used for clustering. We present a comparison of typical bag-of-words features with stylistic features. We group the news articles published from No. Feature No. Feature three different regions of the UK namely London, Wales, and 1. Percentage of Question Sentences 2. Average Sentence Length Scotland. Hierarchical clustering is performed using typical bag- 3. Percentage of Short Sentences 4. Average Word Length of-words and stylistic features. We present the performance of 5. Percentage of Long Sentences 6. Percentage of Semicolons Percentage of Words with Six 25 stylistic features and compare them with the bag-of-words. 7. 8. Percentage of Punctuation marks and More Letters Our results show that bag-of-words are better to be used while Percentage of Words with Two 9. 10. Percentage of Pronouns and Three Letters clustering news reporting at the regional level whereas stylistic Percentage of Coordinating 11. 12. Percentage of Prepositions features are better to be used while clustering news reporting at Conjunctions the level of news publishers/newspapers. 13. Percentage of Comma 14. Percentage of Adverbs 15. Percentage of Articles 16. Percentage of Capitals Percentage of Words with 17. 18. Percentage of Colons KEYWORDS One Syllable 19. Percentage of Nouns 20. Percentage of Determiners news reporting, topic modeling, stylistic features, clustering 21. Percentage of Verbs 22. Percentage of Digits 23. Percentage of Adjectives 24. Percentage of Full stop 25. Percentage of Interjections 1 INTRODUCTION The role of content is an essential research topic in news spread- ing. Media economics scholars especially showed their interest features from the raw features, including low-level features, high- in a variety of content forms since content analysis plays a vital level features, and semantic features [16]. role in individual consumer decisions and political and economic The news coverage registers the occurrence of specific events interactions [6]. The content basically refers to the type of lan- promptly and reflects the different opinions of stakeholders [4]. guage that is used in the news. It is used to convey meaning and We take Brexit as an event to be researched on the topic of news it can impact social and psychological constructs such as social reporting differences across the different regions of the UK. On relationships, emotions, and social hierarchy [8]. The everyday 23 June 2016, the British electorate voted to leave the EU. This act of reading the news is such a big area in which small dif- event has already been studied following different aspects such ferences in reporting may shape how events are perceived, and as fundamental characteristics of the voting population, driver ultimately judged and remembered [5]. of the vote, political and social patterns, and possible failures in News reporting across different regions requires methods to communication [2, 9]. In this paper, we explore how different find reporting differences. [7] characterize the relationship be- stylistic features help in clustering news articles related to Brexit tween the volume of online opioid news reporting and measures than bag-of-words (BOW). differences across different geographic and socio-economic lev- Following are the main scientific contributions of this paper: els. Scholars across disciplines have explored the institutional, (1) We present a comparison of clustering (using two different organizational, and individual influences that study the quality textual features: bag-of-words and stylistic features) for and quantity of coverage [3]. news reporting about Brexit in three different regions Features that could classify news reporting across different (London, Scotland, and Wales) of the UK. regions can be adapted to classify the news. A detailed analysis of (2) We show in our experiments that the bag-of-words are textual features is performed by [1] where they derived multiple better to be used while clustering news reporting at the features for creating clusters of news articles along with their regional level whereas stylistic features are better to be comments. These features include terms in the title, terms in used while clustering news reporting at the level of news the first sentence, terms in the entire article, etc. Multi-view publishers/newspapers. clustering on multi-model data can provide common semantics to improve learning effectiveness. It exploits different levels of 2 RELATED WORK Permission to make digital or hard copies of part or all of this work for personal In this section, we review the related literature about topic mod- or classroom use is granted without fee provided that copies are not made or elling, and different types of textual features. 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). 2.1 Topic Modelling Information Society 2022, 10 October 2022, Ljubljana, Slovenia Topic modelling is used to infer topics from the collection of text- © 2022 Copyright held by the owner/author(s). document. Some techniques used only frequent words whereas 111 Information Society 2022, 10 October 2022, Ljubljana, Slovenia Abdul Sittar, Jason Webber, and Dunja Mladenić Table 2: Total number of news articles about Brexit pub- 3 DATA COLLECTION lished in three different regions (London, Scotland, and We collected news articles reporting on Brexit in the English lan- Wales). guage from the UK Web Archive (UKWA). The dataset consists of 5061 news articles after pre-processing. Due to the unavailability Regions Newspapers News articles Total of news articles from other regions of the UK, we selected only bankofengland.co.uk 8 the regions (London, Scotland, and Wales) which have a sufficient bbc.com 2209 amount of news articles. Table 2 presents the number of news dailymail.co.uk 768 articles published from different regions and by different news Independent.co.uk 191 publishers. inews.co.uk 52 metro.co.uk 1 4 METHODOLOGY neweconomics.org 1 The presented research focuses on clustering news articles. To rspb.org.uk 8 this end, we experiment clustering with the combination of dif- theguardian.com 1167 London 4248 ferent features observing their performance. Our methodology theneweuropean.co.uk 1 consists on four steps and compares the performance of stylistic thesun.co.uk 235 features and bag-of-words in clustering news articles, as shown cityam.com 3 in Figure 1. conservativewomen.uk 1 In the first step, we select Brexit under topic and themes on dailypost.co.uk 1 UK web archive1. After crawling the list of news articles, we ex- ft.com 2 tracted the meta data of news publishers from Wikipedia-infobox. mirror.co.uk 9 The meta-data extraction process is explained in our previous raeng.org.uk 1 work [15]. In this process, we extracted the headquarters of news standard.co.uk 20 publishers. Due to the unavailability of news articles from other Scotland news.stv.tv 533 533 regions of the UK, we selected only the regions (London, Scot- gov.wales 3 land, and Wales) which have a sufficient amount of news articles. Wales nation.wales 122 280 In the second step, we perform parsing of the html web pages Walesonline.co.uk 156 and extract the body text. some use pooling to generate relevant topics and maintain co- herence between topics [14]. Topics are typically represented by UKWA London Wales a set of keywords. Examples of such algorithms are the Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA) and Brexit - News Articles Scotland Probabilistic Latent Semantic Analysis (LSA). Clustering-based topic modelling is another solution. Meta-data Extraction 2.2 Stylistic Features News reporting differences can be reflected through one’s speech, writing, and images etc [10, 12]. A language independent features Preprocessing have been used for different tasks of NLP such as plagiarism de- tection, author diarization. These features considers the text of documents as a sequence of tokens (i.e. sentences, paragraphs, documents). On the basis of these tokens, various types of sta- Stylistic Features Bag-of-words tistics could be drawn from any language [13]. Stylistic features represent the writing style of a document and have been used for LSA LSA understanding the author writing styles in the past [10]. We use it to explore the clustering of the news articles based on their re- porting differences across different regions. Table 1 shows the list Hierarchical of 25 stylistic features used for the development of our proposed Clustering clustering of news articles. 2.3 Bag-of-words BCubed A bag-of-words model is a way of extracting features from text. It is basically a representation of text that describes the occurrence of words within a document. It firstly identifies a vocabulary of known words and then measures the presence of known words. Topic modelling is typically based on the bag-of-words (BOW). Figure 1: Methodology to clustering regional news using The essential idea of the topic model is that a document can bag-of-words and stylistic features. be represented by a mixture of latent topics and each topic is a distribution over words [11]. 1https://www.webarchive.org.uk/en/ukwa/collection/910 112 Stylistic features in clustering news reporting Information Society 2022, 10 October 2022, Ljubljana, Slovenia Since the third step required pre-processing for bag-of-words, London respectively. Blue and red lines represent bag-of-words we convert the text to lowercase and remove the stop words and (BOW) and stylistic features. punctuation marks. In the third step for the stylistic features, We can see that for all three graphs, the silhouette score of we extract the stylistic features(see Table 1) for all three regions stylistic features is significantly high for all three regions except and perform LSA (Latent Semantic Analysis). Similarly, for the at one point for Scotland. It means that cohesion is higher and the bag-of-words, we use the pre-processed text and perform LSA. distance between the clusters is more significant using stylistic We also perform LSA on the combination of both types of fea- features than BOW which is mostly too close to 0. It suggests tures. 100 latent dimensions have been used for LSA because that these features are better at partitioning news articles into it is recommended. We perform LSA and hierarchical cluster- clusters than BOW. ing using the python library SciPy, and scikit-learn and use the weighted distance between clusters. After performing the LSA, we apply hierarchical clustering and utilize two different types of evaluation measures namely BCubed F1 and Silhouette Scores. For LSA and hierarchical clustering, we use the python library SciPy, and scikit-learn. 5 EXPERIMENTAL EVALUATION We have performed experimental evaluations using intrinsic (Silhouette) and extrinsic (BCubed-F) evaluation measures. The intrinsic evaluation metrics are used to calculate the goodness of a clustering technique whereas extrinsic evaluation metrics are used to evaluate clustering performance. For extrinsic evalua- tion, we consider clusters generated by k-means clustering using typical bag-of-words as ground truth clusters. The value of k in k-means clustering ranges from 2 to 20. K-means identifies k cen- troids, and then allocates every data point to the nearest cluster while keeping the centroids as small as possible. We cannot set the value of k to 1 which means there are no other clusters to allocate the nearest data point. Silhouette is used to find cohesion. It ranges from -1 to 1. 1 means clusters are well apart from each other and clearly distinguished. 0 means clusters are indifferent, or we can say that the distance between clusters is not significant. -1 means clusters are assigned in the wrong way. BCubed F-measure defines precision as point precision, namely how many points in the same cluster belong to its class. Similarly, point recall represents how many points from its class appear in its cluster. • Silhouette Score: 𝑆 (𝑖) = 𝑏 (𝑖 ) −𝑎 (𝑖 ) 𝑚𝑎𝑥 (𝑎 (𝑖 ),𝑏 (𝑖 ) ) where S(i) is the silhouette coefficient of the data point i, a(i) is the average distance between i and all the other data points in the cluster to which i belongs, and b(i) is the average distance from i to all clusters to which i does not belong. • BCubed Precision and Recall:     𝐶𝑜𝑟 𝑟 𝑒𝑐𝑡 𝑛𝑒𝑠𝑠 (𝑖, 𝑗 ) = 1, 𝑖 𝑓 𝐿(𝑖) = 𝐿( 𝑗) 𝑎𝑛𝑑 𝐶 ( 𝑗) = 𝐶 ( 𝑗)   0, 𝑖 𝑓 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒  Í𝑁 Í 𝐶𝑜𝑟 𝑟 𝑒𝑐𝑡 𝑛𝑒𝑠𝑠 (𝑖, 𝑗 ) 𝐵𝐶𝑢𝑏𝑒𝑑 𝑃 𝑟 𝑒𝑐𝑖𝑠𝑖𝑜𝑛 = 1 𝑁 𝑖 =1 𝑗 𝜖𝐶 (𝑖 ) |𝐶 (𝑖) | Í𝑁 Í 𝐶𝑜𝑟 𝑟 𝑒𝑐𝑡 𝑛𝑒𝑠𝑠 (𝑖, 𝑗 ) 𝐵𝐶𝑢𝑏𝑒𝑑 𝑅𝑒𝑐𝑎𝑙𝑙 = 1 𝑁 𝑖 =1 𝑗 𝜖 𝐿 (𝑖 ) |𝐿 (𝑖) | where |C(i)| and |L(i)| denote the sizes of the sets C(i) and L(i), respectively. L(i) and C(i) denote the class and clusters of a point i. • BCubed-F Score: 𝐹 = 2×𝐵𝑐𝑢𝑏𝑒𝑑𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛×𝐵𝑐𝑢𝑏𝑒𝑑𝑅𝑒𝑐𝑎𝑙𝑙 Figure 2: The line graphs represent average silhouette 𝐵𝑐𝑢𝑏𝑒𝑑 𝑃 𝑟 𝑒𝑐𝑖𝑠𝑖𝑜𝑛 ∔𝐵𝑐𝑢𝑏𝑒𝑑𝑅𝑒𝑐𝑎𝑙𝑙 scores across a different number of clusters. The blue line 6 RESULTS AND ANALYSIS represents the score generated using bag-of-words and the Figure 2 shows the three line graphs. Each graph shows Silhouette red line represents the score generated using stylistic fea- scores across a different number of clusters (from 2 to 20) repre- tures. The three-line graphs are generated for three differ- senting different regions of the UK such as Scotland, Wales, and ent regions Scotland, Wales, and London respectively. 113 Information Society 2022, 10 October 2022, Ljubljana, Slovenia Abdul Sittar, Jason Webber, and Dunja Mladenić Table 3: The group of news articles published from three features are better to be used while clustering news reporting at different regions of the UK is considered as ground truth the level of news publishers/newspapers. clusters and the Bcubed-F score is calculated using three types of features including bag-of-words, stylistic features, ACKNOWLEDGMENTS and a combination of both types of features. The research described in this paper was supported by the Slove- nian research agency under the project J2-1736 Causalify and No. Features Bcubed-F Score by the European Union’s Horizon 2020 research and innovation 1. Bag-of-words 0.75 programme under the Marie Skłodowska-Curie grant agreement 2. 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Journal of Intelligent Information Systems, 58, 1, 119–152. 115 Automatically Generating Text from Film Material – A Comparison of Three Models Sebastian Korenič Tratnik Erik Novak Jožef Stefan International Postgraduate School Jožef Stefan Institute Faculty of Computer and Information Science Jožef Stefan International Postgraduate School Večna pot 113 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT 2 PROBLEM DESCRIPTION The paper focuses on audio analysis and text generation using In recent years, audio-visual data has become as influent if film material as an example. The proposed approach is done not more influent as traditional text-based information. With by using three different models (Wav2Vec2, HuBERT, S2T) this, the task of extracting information from the former and to process the sound from different audio-visual units. A transforming it into the latter is becoming useful for different comparative analysis shows the strengths of different models purposes [1, 2]. One example is that text annotations enable and factors of different materials that determine the quality of better comprehension in cases of bad sound quality or even text generation for functional film annotation applications. allow the material to be understood in situations where sound consumption is impossible. Another one is a possible speed KEYWORDS up of the video that the annotations provide due to their ability Text generation, automated transcription, cinema, film, video to keep the content integral in a clear graphic form. The consumption process can be made more time efficient with 1 INTRODUCTION textual information compensating for the distortions of audio- Applications like automatic text captions for video materials visual quality that can be brought about with the have become more and popular and extensively used by users manipulations of playing options. Furthermore, in a general on different media, spanning from the computer, television, sense, combining audio-visual material with text can solve smartphones and other technologies that enable audio-visual many problems on different levels of film or video consumption. However, even though these applications have production. This can span from the preparing phases of pre- to an extent already become a staple in our everyday lives, production such as writing the script, to the post-production their performance often varies and still has not reached phases where one needs good orientation over a vast quantity optimal functionality. There are many challenges when we of material. Proper text generation can facilitate easier work with text generation out of audio-visual materials. orientation in such work and allows for more efficient These span from the structure and quality, the type or organization of the media materials. category of sound, the age of the recordings and the models In this paper, we will focus on those components that on which such translation is based on. The main goal of this contribute to the quality of proper automated text generation paper is to provide a practical demonstration of a few basic as a prerequisite of such developmental strategies. The main models for automatic annotation. The goal is to take into contributions of this paper are: (1) an analysis of the factors account the currently most common procedures of such an that influence automatic transcription of film or video endeavour and figure out how to minimize the loss function material (2) implementation and comparison of a few of the models to allow an optimal generation of text out of different models for sound annotation (3) reflection on how film or video more sufficiently. this process can be used for more complex tasks The rest of this paper is organized in the following way. Section 2 provides a description of the problem in the context 3 METHODOLOGY of contemporary consumption of audio-visual materials via The problem we are solving is to take a piece of audio-visual most popular information and communication technologies. material, convert it into a code that a model for automatic text Section 3 delineates the methodology used and describes the generation can take as input and then generate output of text approach used to tackle the problem in a concrete that matches the sound recording of the input in an optimal demonstration. Section 4 presents the models being used and way. An optimal result should provide a close describes our implementation of them, specifying the correspondence of the utterances in the film material and dynamics of the obtained results. A conclusion is reached in eventually identify different types and categories of sound section 5, where the paper offers a discussion on the outcome such as dialogue, noise, music etc. We will do an analysis of and possible directions for future work. the factors that influence the quality of automatically generated transcriptions in the following steps: 1) a comparison of different models for generating text from audio files, 2) an analysis of how the quality of transcriptions differs in relation to noise in the background (silence, music, 116 dialogues), 3) an evaluation of how the clarity of speech influences the quality of transcriptions, and 4) an assessment to what extent it is more difficult to generate quality transcriptions from older audio-inscriptions (films). Reflecting on the results of our procedure, we will think about how to improve the quality in cases when quality of transcriptions is bad. Aside from quality we will measure the time demands of models, that is how much time do the models need to generate transcriptions from the audio writing. The following model were used: 1) Wav2Vec2 [4] is a framework for self-supervised representation learning from raw audio that was made open- source by Facebook. It is the first Automatic Speech recognition model included in Transformers as one of the Figure 2. HuBERT predicts hidden clusters assignments using central parts of Natural Language Processing. Figure 1 shows masked frames (y2, y3, y4 in the figure) generated by one or more the model’s architecture. iterations of k-means clustering [7]. 3) S2T [5] (Speech2Text) is a transformer-based encoder- decoder (seq2seq) model that uses a convolutional downsampler to dramatically reduce the length of audio inputs over one half before they are fed into the encoder. It generates the transcripts autoregressively and is trained with standard autoregressive cross-entropy loss. 4 EXPERIMENT SETTING 4.1 Evaluation metric Figure 1. Wav2Vec2 learns speech units from multiple languages We have used WER (Word error rate) as the metric of the using cross-lingual training [4]. performance of the models which computes the error rate on the comparison of substitutions, deletions, insertions and The model starts by processing the raw waveform with a correct words. Original text was used for each of the model multilayer convolutional neural network. This yields latent and each film example, removing the punctuation. audio representations of 25ms that are fed into a quantizer and a transformer. From an inventory of learned units, the quantizer chooses appropriate ones, while half of the representations are masked before being used. The transformer then adds information from the whole of the audio sequence and with the output leads to solving the contrasting task with the model identifying the correct quantized speech units for the masked positions. 4.2 Data set 2) HuBERT [3] (Hidden-Unit BERT) is an approach for self- supervised speech representation that uses masking in a The dataset was formed with clips of different films. The similar way and in addition adds an offline clustering step that films used were classics of world cinema ( The Godfather, provides aligned target labels for a prediction loss. This 2001: A Space Odyssey, Star Wars, Frankenstein, Fight Club, prediction loss is applied over the masked regions, which Paris, Texas, Scent of A Woman, Tomorrow and Tomorrow leads the model to learn a combined language and acoustic and Tomorrow). 14 clips of sizes spanning from 5 to 30 model over the continuous inputs. By focusing on the seconds were used with the lengthier ones incorporating consistency of the unsupervised clustering step rather than the different sound contents (like speech, shouting, whispering intrinsic quality of the assigned cluster labels, HuBERT can etc.). The first step was to prepare the audio in such a format either match or improve the Wav2Vec2 model. Figure 2 that the models will be able to read it, so the clips were shows the model’s architecture. changed from mp4 to wav. An online converter, cloudconvert [https://cloudconvert.com], was used as the clips were fairly short and the results could be directly added to the Kaggle dataset from the browser itself. 117 N WITH GUNS WHO'S GON TO DO IT YOU YOU LIEUTENANT WINEBERG HuBERT: OMARTER TE CORET YOU DON'T HAVE TO ANSWER THAT Q UESTION I'LL ANSWER THE QUESTION YOU WANT ANSWERS I THINK I'M ENTITLED YOU WANT ANSWERRTHE TRUTH YO U CAN'T HANDLE THE TRUTH SON WE LIVE IN A WORLD TH AT HAS WALLS AND THOSE WALLS HAVE TO BE GUARDED B Figure 3: A superposition of waveform graphs of all the examples. Y MEN WITH GUNS WHO'S GOING TO DO IT YOU YOU LIEUT ENANT WINBURG 4.3 Implementation details Programming was done on Kaggle, where code was written S2T: in Python and after the experiments were set up, and the GPU DEAR LORD THE CORRET YOU DON'T HAVE THE ANSWER T was activated for faster computation. The general process HAT QUESTION I'LL ANSWER THE QUESTION YOU WANT AN using each of the models is the following. First, an encoder SWERS BUT THEY CAN'T ENTITLE YOU ONE AND THE TRUTH takes raw data and puts it in the model. In our demonstration, YOU CAN'T HANDLE THE TRUTH SOME WE LIVE IN A WORL D THAT HAS WALLS AND THOSE WALLS HAVE TO BE GUARD tokenizers were used at the start, but as S2T tokenizers was ED BY MEN WITH GUNS WHOSE TENANT DO IT YOU LIEUTE not equipped to get the audio, it had to be changed to a NANT WINEBURG THOSE HAVE TO BE GUARDED BY MEN WI processor. To retain consistency, the same step was applied TH GUNS WHOSE CANNON DO IT YOU YOU LIEUTENANT WI to the other two models as well. Once data gets in the model, NEBURG YOU LIEUTENANT WINEBURG the model predicts particular syllables for each sound with certain probabilities and then in an additional step selects those with the highest probability based in the context of the semantic whole of the sentence. In the final step, the decoder (again the tokenizers / the processors) takes the output of the model and transforms it into text. 5 EXPERIMENT RESULTS The ground rules for our project were that each model had a particular function that took sound as input and produced text Figure 4. A scene from A Few Good Men (1992), a still and as output with each audio having the text extracted separately. waveform graph from the used sequence. Subsequently different models were compared according to The lower the WER number, the better the results. The the accuracy of the results according to different criteria and models did not have a noticeable variation of speed, while a variety of scenarios (noise, music, number of characters, the quality of their performance varied due to different tempo of speech etc.). We will illustrate the obtained results factors. Hubert gave overall the best results from the point of via a concrete example. We will take a clip with relatively view of readability. According to the rate of correspondence clear sound from the film A Few Good Men (1992), a between input audio and output text, HuBERT comparably digitized version of a well preserved celluloid film. The sound gave the better rate of the transcription in case of videos with is clear and the dialogue takes places in a court practically in poor audio quality from Wav2Vec2, i.e. that from older or complete silence of the surroundings with the speech damaged films, while Wav2Vec2 gave better performance in changing from normal tone to screaming. The clip is 22 case of background music, but had the tendency of adding seconds long and its waveform is shown in Figure 4. The too much insertions. S2T had the tendency to produce original text is as following: mistakes, seen in peaking numbers over 1.0. The overall A: Did you order the Code Red?! results are given in Table 1. B: You don't have to answer that question! It is important to note that the average given does not reflect C: I’ll answer the question. You want answers? the better overall accuracy, but is the sum of different factors. A: I think I’m entitled! So the models can be good at transcribing particular words, C: You want answers!? but can add or drop extra words in the process and therefore A: I want the truth! make the overall text less comprehensible. An important C: You can’t handle the truth! Son, we live in a world that has factor is the way the original text that is used for comparison walls, and those walls have to be guarded by men with guns. is written – omitting punctuations and properly writing the Who's gonna do it? You? You, Lieutenant Weinberg? words even if they are mispronounced will improve the The produced transcriptions are as follows: results. Finally, it is crucial that all the texts are in caps lock, or the comparison won’t work and will produce misleading Wav2Vec2: results. YOU WAR THE CORA YOU DON'T HAVE TO ANSWER THE QU ESTION I'LL ANSWER THE QUESTION YOU WANT ANSWERS I As the used example shows, it is mostly clarity of speech that THINK I'M ENTITLE YOU WANT ANT A AT THE TRUE YOU CA will determine how the models perform. As the models were N'T HANDLE THE TRUTH SON WE LIVE IN A WORLD THAT H pre-trained and were not trained according to the specific data AS WALLS AND THOSE WALLS HAVE TO BE GUARDED BY ME used, they were in general surprisingly efficient. The 118 discrepancies in different treatments of the same audio are speaking, then person B, then person A has a long visible, but in general as long as the dialogue was clear, the monologue, person C answers” etc.). Another important task results were comparable. Music seemed to cause bigger would be identifying the sounds of different categories and problems for the model than background noise, while providing fitting audio-signs (sound of squeaking steps, additional speech in the background proved most playing of music etc.). From these steps one could eventually problematic. Emotional influences on speech did not prove at least to some extent automatically generate scripts for films that problematic and even affective utterances were or find ways to develop tools for easier text-based transcribed comparably with neutral speech if the sound data classification of audio-visual material. was of high quality. CONCLUSIONS Table 1. The WER scores for each model. The bold values represent the best performances on the given clip. The best In this paper we explored ways to generate text out of audio performing model is HuBERT. information presented in film and video material. We used three different models to evaluate various film units, Clip number Wav2Vec2 HuBERT S2T Wav2Vec2, HuBERT, and S2T. We found that the model 1 69% 53% 91% HuBERT achieved best results, while the remaining two 2 100% 0% 100% methods performed similarly. 3 100% 95% 95% 4 27% 30% 36% 5 17% 17% 17% ACKNOWLEDGMENTS 6 39% 18% 43% The research described in this paper was supported by 7 28% 28% 64% International Postgraduate School Inštitut Jožef Štefan, 8 70% 46% 55% Ljubljana, Slovenia in the class Textual/ Multimedia mining 9 50% 25% 100% and semantic technologies held by dr. Dunja Mladenič under 10 57% 37% 73% 11 62% 38% 51% the mentorship of Erik Novak. We also thank Besher Massri, 12 100% 95% 100% Aljoša Rakita and Martin Abram for additional feedback. 13 60% 33% 73% 14 9% 4% 9% REFERENCES Average 56% 37% 65% 1 A. Ramani, A. Rao, V. Vidya and V. B. Prasad, "Automatic Subtitle Generation for Videos," 2020 6th International The WER usually shows the results in a metric between 0 and Conference on Advanced Computing and Communication 1, however in case the annotation results were extremely Systems (ICACCS), 2020, pp. 132-135, doi: unsuccessful, the higher extreme may surpass the limit. In our 10.1109/ICACCS48705.2020.9074180. case, up to 1.6 was reached, however in the chart, it was 2 Rustam Shadiev, Yueh-Min Huang, Facilitating cross- limited down to 1.0 for purposes of clarity. cultural understanding with learning activities supported by speech-to-text recognition and computer-aided translation, 5 DISCUSSION AND FURTHER WORK Computers & Education, Volume 98, 2016, Pages 130-141 So as a general principle, when taking clips from films, the 3 Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, main factor that can potentially influence the quality of the Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman generated text in a negative way is the background noise. As Mohamed. HuBERT: Self-Supervised Speech one can expect, the model will work best when nothing is in Representation Learning by Masked Prediction of Hidden the background and worst when people are talking in the Units. [arXiv:2106.07447v1 [cs.CL], Submitted on 14 Jun background. Ideally, to improve the quality one would train 2021]. the models for the specific material, using a similar type of material and accordingly doing a pre-classification according 4 Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, to the main categories of sound analysis (ie. monologue, Michael Auli. wav2vec 2.0: A Framework for Self- dialogue, background noise, music, echo, normal speech, Supervised Learning of Speech Representations.. loud speech, shouting, whispering etc.) - especially when [arXiv:2006.11477v3, Submitted on 20 Jun 2020 (v1), last using older or less preserved material, which drastically revised 22 Oct 2020 (this version, v3)]. differs in sound data from newer or more preserved works. 5 Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Dmytro In our research we expanded on and adapted existing work on Okhonko, Juan Pino. fairseq S2T: Fast Speech-to-Text automated text generation models, providing an analysis of Modeling with fairseq. [arXiv:2010.05171v1, Submitted on the factors that determine the quality of such results from film 11 Oct 2020] . material. As an example, we applied our approach on 6 Wav2vec2.0: Learning the structure of speech from raw different film material, ranging in the quality and age of the audio. [https://ai.facebook.com/blog/wav2vec-20-learning- clips and the structure of the sound data. the-structure-of-speech-from-raw-audio Submitted on 24 Sep 2020, Access. 9.1.2022 A useful strategy for the future from the perspective of film practice would be to find ways to link transcriptions with a 7 Hsu, Wei-Ning, et al. "Hubert: Self-supervised speech script. A precondition of such an endeavour would be to representation learning by masked prediction of hidden implement an algorithm for recognizing the person speaking units." IEEE/ACM Transactions on Audio, Speech, and and identifying the source with descriptions (“person A is Language Processing 29 (2021): 3451-3460. 119 The Russian invasion of Ukraine through the lens of ex-Yugoslavian Twitter Bojan Evkoski Igor Mozetič bojan.evkoski@ijs.si igor.mozetic@ijs.si Jozef Stefan Institute, and Jozef Stefan Institute Jozef Stefan Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Petra Kralj Novak Nikola Ljubešić petra.kralj.novak@ijs.si nikola.ljubesic@ijs.si Central European University Jozef Stefan Institute, and Vienna, Austria, and Faculty of Computer and Information Science, Jozef Stefan Institute University of Ljubljana Ljubljana, Slovenia Ljubljana, Slovenia Serbian Serbian left-wing opposition right-wing opposition Serbian Pro-Russia Tweetosphere Serbian right-wing opposition Croatian + Bosnian + Montenegrin tweetosphere Serbian populist coalition Serbian populist coalition Pro-Ukraine Croatian + Bosnian + Montenegrin Serbian tweetosphere left-wing opposition Serbian Tweetosphere Figure 1: Pre-invasion (left) and invasion (right) ex-Yugoslavian retweet networks. Node colors represent communities. Labeled arrows point to the main communities, with labels inferred from the community users. The in-network labels represent the names of the most retweeted accounts. ABSTRACT orientations. Some communities detected after the start of the The Russian invasion of Ukraine marks a dramatic change in Russian invasion also show clear pro-Ukrainian or pro-Russian international relations globally, as well as at specific, already stance. Such analyses of social media help in understanding the unstable, regions. The geographical area of interest in this paper role and effect of this conflict at the regional level. is a part of ex-Yugoslavia where the BCMS (Bosnian, Croatian, Montenegrin, Serbian) languages are spoken, official varieties of KEYWORDS a pluricentric Serbo-Croatian macro-language [4]. We analyze social network analysis, community detection, Twitter 12 weeks of Twitter activities in this region, six weeks before the invasion, and six weeks after the start of the invasion. We 1 INTRODUCTION form retweet networks and detect retweet communities which closely correspond to groups of like-minded Twitter users. The The Russian invasion of Ukraine brings about dramatic changes communities are distinctly divided across countries and political to the world. Analysing the structure and content of the commu- nication on social media, such as Twitter, can give more insight into the causes, developments and consequences of this conflict. Permission to make digital or hard copies of part or all of this work for personal The geographical area of interest in our research is a part of 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 ex-Yugoslavia where the BCMS (Bosnian, Croatian, Montenegrin, the full citation on the first page. Copyrights for third-party components of this Serbian) languages are spoken, official varieties of the pluricentric work must be honored. For all other uses, contact the owner/author(s). Serbo-Croatian macro-language. This area is strongly politically Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). divided by diverging influences of NATO (Croatia, Montenegro, North Macedonia, Bosniak and Croatian entity in Bosnia and 120 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Evkoski et al. Pre-Invasion network Invasion network communities communities RS Tweetosphere 55% part 1 RS tweetosphere part 1 RS sports 43% +43% 15% ME tweetosphere 49% Pro-Ukraine BA + HR + ME 54% BA + HR + ME tweetosphere tweetosphere +53% MK tweetosphere 36% 11% RS left-wing opposition RS left-wing opposition 57% +33% RS tweetosphere International 11% part 2 tweetosphere 20% (South Serbia) +42% RS tweetosphere 54% part 2 Pro-Russia RS right-wing RS right-wing 51% opposition +55% opposition Bosnian Serbs +40% 11% Bosnian Serbs 43% RS populist coalition +19% RS 68% populist coalition Figure 2: A Sankey diagram showing the transitions of users from the pre-invasion network communities (left) to the invasion network communities (right). Rectangle height is proportional to the community sizes. Percentages near the pre-invasion communities show the portion of users found in the corresponding invasion communities. Percentages on the right-hand side of the invasion communities show the portion of users not previously present in the large communities of the pre-invasion network. Gray rectangles depict the communities tightly related to politics, with the yellow and red denoting the detected pro-Ukraine and pro-Russia leaning communities, respectively. Herzegovina) and Russia (Serbia, Serbian entity in Bosnia and 2 RESULTS Herzegovina). While Croatia is full EU member since 2013, Mon- The data analysed in this study were collected with the TweetCat tenegro, North Macedonia and Serbia are EU candidate members, tool [3], focused on harvesting tweets of less frequent languages. while Bosnia and Herzegovina is a potential candidate. Regarding TweetCat is continuously searching for new users tweeting in military alliances, NATO members are Croatia (since 2007), Mon- the language of interest by querying the Twitter Search API for tenegro (since 2017) and North Macedonia (since 2020), while the most frequent and unique words in that language. Every user Serbia does not aspire to join NATO, primarily due to a complex identified to tweet in the language of interest is continuously Serbia-NATO relationship caused by the NATO intervention in collected from that point onward. This data collection proce- Yugoslavia in 1999. dure is run for the BCMS set of languages since 2017. During To shed light on the impact of the Russian invasion on this the 12 weeks of our focus, we collected 1.2M tweets and 3.8M brittle and complex geographical and political area, we use social retweets from 45,336 users. A rough estimate of the per-country network analysis over available Twitter data, 6-weeks before and production of tweets via URL usage from country-specific top- 6-weeks during the invasion. We discover a complex landscape level domains (upper part of Table 1) shows for Twitter to be of ideology-specific and country-specific communities (see Fig- much more popular in Serbia and Montenegro than in Croatia or ure 1), and analyse the transition into evident pro-Ukraine and Bosnia and Herzegovina. This has to be taken into account while pro-Russia leanings. We also present a method to measure the analysing the communities of the underlying tweetosphere. similarity of the communities before and during the invasion by We created pre-invasion and invasion retweet networks analyzing URL and hashtag usage. As the communities show very (users as nodes, retweets as edges) from the collected data. We divergent properties, we echo concerns of the heavy polarization applied community detection (Ensemble Louvain [1]) on the two and possible destabilization of this area of the Balkans. 121 Russian invasion of Ukraine — ex-Yugoslavian Twitter Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Country Population URLs Serbia (RS) 7.2M (47.3%) 106K (44.2%) Croatia (HR) 3.9M (25.6%) 19.6K (8.1%) Bosnia and Herzegovina (BA) 3.5M (23.0%) 14.9K (6.2%) Montenegro (ME) 620K (4.1%) 24.7K (10.2%) Total 15.2M 242K Pre-invasion communities Users Tweets Retweets Intra-com. RTs RS tweetosphere part 1 13K (29.0%) 125K (24.9%) 300K (18.9%) 80.3% RS tweetosphere part 2 2.5K (5.6%) 35.8K (7.1%) 63.2K (4.0%) 62.3% RS sports 1.6K (3.6%) 12.6K (2.5%) 25.6K (1.6%) 53.8% ME tweetosphere 1.7K (3.8%) 22.7K (4.5%) 44.6K (2.8%) 74.5% BA + HR + ME tweetosphere 5.6K (12.4%) 37.8K (7.5%) 59K (3.7%) 75.3% Macedonian tweetosphere 200 (0.4%) 721 (0.1%) 771 (0.1%) 77.7% International tweetosphere 934 (2.0%) 8.5K (1.7%) 11.5K (0.7%) 62.3% RS populist coalition 2.0K (4.8%) 52.4K (10.4%) 396K (24.9%) 98.7% RS left-wing opposition 9.3K (20.6%) 105K (20.9%) 408K (25.5%) 80.5% RS right-wing opposition 7.6K(16.8%) 87.8K (17.4%) 247K (15.5%) 72.1% Bosnian Serbs 139 (0.3%) 2.2K (0.4%) 3.8K (0.2%) 83.1% Total 45.3K 502.9K 1590K Invasion communities Users Tweets Retweets Intra-com. RTs RS tweetosphere part 1 16.9K (29.5%) 160K (22.4%) 387K (16.8%) 71.1% RS tweetosphere part 2 4.5K (7.7%) 57.3K (8.1%) 118K (5.1%) 58.1% Pro-Ukraine BA + HR + ME tweetosphere 12.4K (21.7%) 76.1K (10.6%) 235K (10.2%) 64.7% Pro-Russia RS right-wing opposition 11.1K (19.4%) 129K (17.9%) 508K (22.1%) 65.1% RS populist coalition 1.8K (3.1%) 208K (29.1%) 450K (19.5%) 95.6% RS left-wing opposition 9.8K (17.2%) 191K (26.7%) 590K (25.6%) 72.6% Bosnian Serbs 356 (0.6%) 5.4K (0.7%) 7.1K (0.3%) 62.3% Total 57.4K (+26.7%) 717K (+42.8%) 2302K (44.8%) Table 1: The first part shows general population of each BCMS country and their respective tweet URL shares (.rs, .hr, .ba and .me). The second part shows the pre-invasion network communities with the number of users, tweets, retweets and intra-community retweets. The third part shows the same statistics for the invasion network communities. Grey rows depict political communities, while yellow and red show the pro-Ukraine and pro-Russia communities, respectively. networks and analysed the community properties and user tran- With this, we created a subset in which more than 99% of the sitions [2]. We identified and named the large communities (more URLs were news media, making it ideal for media polarization than 100 users) by a careful analysis of their most influential users analysis. Once we extracted the domain of the URLs, we then cre- and hashtag/URL usage. Figure 2 depicts the user transitions be- ated sorted lists of the top 50 URL domains and top 50 hashtags tween the two networks, while Table 1 shows general statistics for each community, sorted by the usage counts. Finally, in order of each community. We discovered the following peculiarities: to calculate the similarities between communities, we used the • The BCMS tweetosphere is dominated by Serbian (RS) Rank-biased overlap (RBO) measure for indefinite rankings [5]. users and content. We found out that the matchings between the pre-invasion • The political communities are more active compared to and invasion communities based on highest-user-overlap transi- the non-political ones. tions are also visible through the URL and hashtag similarities • RS populist coalition community (led by the Serbian presi- (see Figure 3). In fact, for each pre-invasion community, its re- dent Aleksandar Vučić) forms a very strong echo chamber, spective highest-user-overlap invasion community is also the with less than 2% of all users, yet more than 25% of tweets highest RBO pair for both URLs and hashtags. In other words, and retweets and more than 95% of intra-community retweets. there is a strong positive correlation between the user transition • RS populist coalition and left-wing opposition remain neu- percentages (Figure 2) and the RBO scores. E.g., 68% of the users tral on the invasion topic. from the pre-invasion "RS populist coalition" community tran- • RS right-wing opposition and the Bosnian Serbs show a sition in the "RS populist coalition" community in the invasion clear pro-Russia stance. network. Meanwhile, The URL RBO of this pair is 0.64, while • Croatian, Bosnian and Montenegrin communities show a the hashtag RBO is 0.43, both as the highest combination for the clear pro-Ukraine stance. pre-invasion "RS populist coalition" community, clearly match- In order to compare the pre-invasion and invasion commu- ing it with its invasion transition-based counterpart. This shows nities in terms of content and political leanings, our following that our simple similarity method based on URLs and hashtags goal was to compare the pool of hashtags used and URLs shared can even help in better matching communities in the task of by the community users. Therefore, we developed a simple com- community evolution [6]. munity similarity method. First, we preprocessed the URLs by manually filtering out the ones coming from social media sources like Twitter, Facebook, Youtube etc., as well as URL shorteners. 122 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Evkoski et al. Pre-invasion communities URLS Hashtags 1.0 RS tweetospehere part 1 RS tweetosphere part 2 RS left-wing opposition 0.8 RS populist coalition ME tweetosphere 0.6 RS right-wing opposition International tweetosphere 0.4 BA + HR + ME tweetosphere MK tweetosphere 0.2 RS sports Bosnian Serbs 0.0 Pro-Russia Pro-Ukraine Pro-Russia Invasion communities Pro-Ukraine Bosnian Serbs Bosnian Serbs RS populist coalition RS populist coalition RS left-wing opposition RS tweetosphere part 1 RS tweetosphere part 2 RS left-wing opposition RS right-wing opposition RS tweetosphere part 1 RS tweetosphere part 2 RS right-wing opposition BA + HR + ME tweetosphere BA + HR + ME tweetosphere Figure 3: Domain and hashtag community similarities. A heatmap showing the similarities between the pre-invasion and invasion network communities based on the top 50 URLs (left) and hashtags (right). Similarities are calculated using the Rank-biased overlap (RBO) measure for indefinite rankings [5]. 3 CONCLUSION ACKNOWLEDGMENTS In this work, we investigated the Russian invasion of Ukraine The authors acknowledge financial support of the Slovenian through the lens of Twitter in the ex-Yugoslavian region where Research Agency (research core funding no. P2-103 and no. P6- Bosnian, Croatian, Montenegrin and Serbian are spoken. We an- 0411). alyzed 12 weeks of Twitter activities in this region, six weeks before the invasion, and six weeks after the start of the inva- REFERENCES sion. For each period, we created retweet networks and detected [1] B. Evkoski, I. Mozetič, P. Kralj Novak. Community evolution with Ensemble retweet communities. We followed the transition of users from Louvain. In 10th Intl. Conf. on Complex Networks and their Applications, Book of abstracts, pp. 58–60, Madrid, Spain, 2021. the pre-invasion to the invasion period and analyzed these groups [2] B. Evkoski, I. Mozetič, N. Ljubešić, and P. Kralj Novak. Community evolution of like-minded Twitter users, discovering that they are distinctly in retweet networks. PLoS ONE, 16(9):e0256175, 2021. Non-anonymized version divided across countries and political orientations. For the inva- available at https://arxiv.org/abs/2105.06214. [3] N. Ljubešić, D. Fišer, and T. Erjavec. TweetCaT: a tool for building Twitter sion network, we were also able to detect communities which corpora of smaller languages. In Proc. 9th Intl. Conf. on Language Resources and show clear pro-Ukrainian and pro-Russian stance. Evaluation, pp. 2279–2283, ELRA, Reykjavik, Iceland, 2014. Another contribution was a simple method for comparing [4] N. Ljubešić, M. Miličević Petrović, and T. Samardžić. Borders and boundaries in Bosnian, Croatian, Montenegrin and Serbian: Twitter data to the rescue. Journal retweet network communities based on the content of the tweets. of Linguistic Geography 6:2, DOI 10.1017/jlg.2018.9, pp 100-124, Cambridge The method showed a strong correlation with the most prominent University Press, 2018 [5] W. Webber, A. Moffat, Alistair, and J. Zobel. A similarity measure for indefinite user transitions we formerly discovered. rankings. ACM Trans. Information Systems 28(4):20, 2010. A continuation of this work is to expand it to a multidisci- [6] G. Rossetti and R. Caxabet. Community discovery in dynamic networks: a plinary research, with the aim to meticulously analyze the po- survey. ACM computing surveys (CSUR) 51.2 (2018): 1-37. larized content between the communities in collaboration with domain experts who are knowledgeable in ex-Yugoslavian poli- tics. Beyond obtaining interesting insights, we also aim to explore two frequent issues in using social media for societal analyses: (1) uptake bias of specific social networks across countries and communities, and (2) entanglement of the main event with other large-scale events. 123 Visualization of consensus mechanisms in PoS based blockchain protocols Daniil Baldouski Aleksandar Tošić University of Primorska University of Primorska Koper, Slovenia Koper, Slovenia d.baldovskiy@mail.ru Innorenew CoE Izola, Slovenia aleksandar.tosic@upr.si ABSTRACT provide spam resistance through the use of tokens representing value. The use of digital value within the protocol enables the In the past decade, decentralized systems have been increasingly protocol to enforce a level of security through economic incen- gaining more attention. Much of the attention arguably comes tives, and game theoretical aspects that make most attack vectors from both financial, and sociological acceptance, and adoption of economically infeasible or impractical for the attacker. A good blockchain technology. One of the frontiers has been the design example of this is the Proof of Stake (PoS) consensus mechanism, of new consensus protocols, topology optimisation in these peer where nodes in the decentralized protocol secure the consensus to peer(P2P) networks, and gossip protocol design. Analogue mechanism by requiring nodes to stake and lock up a consider- to agent based systems, transitioning from the design to imple- able amount of value, which can be deducted (usually refereed mentation is a difficult task. This is due to the inherent nature to as slashing) by the protocol in case the node misbehaves. The of such systems, where nodes or actors within the system only economic aspect of public blockchains poses a very high secu- have a local view of the system with very little guarantees on rity risk. With such strong economic incentives to identify and availability of data. Additionally, such systems often offer no exploit potential bugs, and system faults, it is of upmost impor- guarantees of a system wide time synchronisation. This research tance for the developers to thoroughly test and examine potential offers insight into the importance of visualisation techniques in problems. However, the aforementioned difficulties in debugging the implementation phase of vote based consensus algorithms, distributed and decentralized protocols require developers to be and P2P overlay network topology. We present our custom visual- equipped with tools that supports their efforts. isations, and note their usefulness in debugging, and identifying In this study, we review the state of the art approaches in potential issues in decentralized networks. Our use case is an testing and debugging voting based consensus mechanisms and implementation of a blockchain protocol. decentralized networks. We develop a visualisation specifically KEYWORDS designed for researchers and developers to test such networks and compare real-time observed data with the expected. We con- Grafana, visualisation, consensus mechanism, blockchain proto- clude that visualisation techniques can be complementary to cols, P2P, overlay network traditional log based debugging, and testing techniques. More- 1 INTRODUCTION over, we provide our tools as open source software as plugins for popular visualisation platform Grafana. Both tools make no Distributed systems are notoriously difficult to inspect and their assumptions on the data storage implementation. The plugins problems difficult to identify. The difficulty stems from the fact can be configured via Grafana plugin configuration interface to that predominant issues can be stochastic and difficult to repro- fit the specifics of the protocol implementation. We validate our duce, and from the inability to easily observe, compare, and test tools by applying them to a custom developed blockchain, and multiple programs running on separate machines at the same then explain how successful they turned out to be in identifying time. Another important aspect in distributed systems is that they anomalies and bugs in the protocols. inherently make heavy use of the network. The use of various net- work protocols imposes additional complexity, which increases 2 THE ROLE OF VISUALIZATIONS IN the search space in identifying bugs. In recent years, distributed DEBUGGING COMPLEX DISTRIBUTED systems have been gaining more attention both in academia and private sector. This increasing interest can be largely attributed SYSTEMS to the rapid development of distributed ledger technology, and Distributed and decentralized systems are difficult to debug as blockchain. In recent years, many new consensus mechanisms, developers are working on the third layer. Which includes L1 blockchain protocols, network protocols, improvement in gossip (code level bugs), issues with concurrency on L2 (individual run- protocols have been proposed. Many of them are transitioning time), and finally the third dimension for potential bugs arising from a theoretical framework to a practical implementation. How- from the message exchange between nodes. In general, it is often ever, public distributed ledgers (or distributed ledger technology hard to capture the state in a distributed system as debuggers or DLT) and blockchains secure their consensus mechanisms and cannot be attached to all nodes’ run-times. Additionally, it is often difficult to reproduce errors when they are inherently stochastic. 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 We consider several methods, such as Logging, Remote debugging, distributed for profit or commercial advantage and that copies bear this notice and Simulations and Visualisations. 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). • Logging is the most common debugging method for all Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia three layers. However, in distributed systems it is impor- © 2022 Copyright held by the owner/author(s). tant to aggregate logs, and analyze them as a time series. 124 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Daniil Baldouski and Aleksandar Tošić Additionally, aggregating distributed logs assumes the sys- distributed systems, while our tools are created specifically tem has some method of clock synchronization protocol. for monitoring PoS voting based consensus mechanisms Log collection has been proven to be effective in detecting and underlying network topology of the distributed sys- performance issues for systems such as Hadoop [12] and tem. Darkstar [13]. The aggregation can be done with specific tools for log collection such as InfluxDB [8], Logstash [10], 3 RESEARCH OBJECTIVES etc. Aggregated logs then can be viewed in a form of a The main goal of this research is to build visualisation tools that dashboard using tools like Grafana (see Figure 1). offer more insight into a running distributed system using the time series log collection data. The targeted system is a custom proof of stake based blockchain. Such tools should visualize if nodes contributing to the consensus learned about their correct roles, and if they perform their roles accordingly. In the consensus algorithms this is done by sending messages, so the tools should visualise messages exchanged between nodes. In the structured P2P networks information spreads using gossip protocols and network topology changes every time slot. Our tools should visualize such changes in the network topology by drawing nodes and their cluster representatives, while at the same time indicating the consensus roles for each node. Figure 1: Part of the Grafana dashboard used by developers In our implementation time series data comes from InfluxDB, to gain insight into a running PoS based blockchain net- but we want our tools to have no assumption on the data storage work. implementation and there are other popular databases, such as kdb+ and Prometheus, that work well with time series data. Be- • Remote debugging is a technique where a locally running cause of that we choose Grafana as a platform for visualizations, debugger is connected to a remote node in the distributed which supports all of the aforementioned databases and many system. This allows developers to use the same features more at the time of writing. as if they were debugging locally. However, it is difficult In this work we implement two Grafana plugins built to vi- to determine which remote node should be debugged. Ad- sualize PoS based blockchains, and decentralized network topol- ditionally, in case of Byzantine behaviour due to network ogy. Our tools are designed with generality in mind, and are faults connecting the debugger could fail. hence applicable to other PoS voting based blockchains and other • Distributed deterministic simulation and replay is a tech- distributed ledger implementations. We evaluate our tools by nique that attempts to address the issues of reproducibility applying it to the custom developed blockchain and note their in distributed systems. Tools like Friday [5] and liblog [6] usefulness in debugging and identifying potential issues in de- can be used to record the specific state of the network centralized networks. to use and analyze it later. The technique suggests imple- menting an additional layer that abstracts the underlying 4 GRAFANA PLUGINS FOR VISUALISING hardware and the network interfaces to allow for an exact VOTE BASED CONSENSUS MECHANISMS replay of all the state changes and messages exchanged be- AND P2P OVERLAY NETWORKS tween nodes. Tools such as FoundationDB or even custom systems are built on containerisation software. We have developed two plugins that extend the functionality of • Visualisation and time series analysis attempts at captur- Grafana. Figure 2 outlines the architecture used in production. ing the state of the system, and all the nodes by visual- A server running a database instance (preferably time series i.e. ising the collected logs. Tools like Prometheus [11] and InfluxDB), and the Grafana platform. Depending on the underly- Grafana [2] are used extensively. Tools like Theia [4] and ing blockchain implementation, nodes can insert their telemetry Artemis [3] are designed for monitoring and analyzing directly to the database, or if possible have an archive node gather performance problems in distributed systems and support telemetry from nodes, and report them. In this example, a cluster built-in visualization tools for data exploration. However, was used to run multiple nodes. A coordinating node is responsi- such tools provide logs aggregated based summaries of ble for maintaining an overlay network and serving the nodes the distributed systems and are not capable of observing within the overlay with a DHCP, DNS, and routing. Nodes are underlying low-level network properties, e.g. monitoring packed within docker containers and submitted to the coordina- network communication, especially in real-time while the tor, which uses built in load balancing and distributes them to system is running. ShiViz [1] on the other hand displays other cluster nodes. distributed system executions as an interactive timespace The telemetry inserted is timestamped to create a time series diagram. With this tool all the necessary events and inter- stream of data that is consumed by Grafana. Figure 1 shows a actions can be viewed in an orderly manner and inspected small part of the dashboard created within Grafana using the built- in detail. ShiViz visualization is based on logical order- in plugins for typical visualisations. These visualisations are time ing, meaning that unlike our tools, it is not capable of series data of a running blockchain showing telemetry reported running in real-time, together with the considered dis- by the nodes. However, rendering telemetry from hundreds of tributed network. ShiViz also works with aggregated logs nodes as factors is hardly informative. about various types of events of the distributed system Both plugins were developed as React components, using a and unlike our tools does not support direct database con- well-known D3.js JavaScript library for animations and life-cycle nections. ShiViz is generalized and works with all kind of of the plugins is managed by Grafana 125 Visualization of consensus mechanisms in PoS based blockchain protocols Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Docker Swarm their correct roles, and if they perform their roles accordingly. In Master Node order to have a scalable visualisation, nodes are placed around a Grafana circle, and scaled according to the size of the network. Roles are Cluster Cluster Cluster Cluster Node 1 Node 2 Node 3 Node n visualized with a color map. Each slot, nodes change their roles, and execute the protocol accordingly. To visualise the execution, InfluxDB the plugin visualises messages exchanged between nodes in a Web Server form of animated lines flying from an origin node to the desti- T nation node. The animations are time synchronous, and transfer P2P Overlay Network Telemetry times, and latencies are taken into account. Additionally, every message is logged with a type, indicating the sub protocol within Figure 2: System architecture. which it was created. As an example, messages being sent from committee members to the block producer are attestations for 4.1 Network Plugin the current block. The animated lines are coloured indicating the message type. P2P networks propagate information using gossip protocols. The thickness of the animated lines indicates the size of the There are many variations of the general and implementation payload transferred between nodes. Figure 4 shows the consensus specifics but in general the family of protocols aims at gossiping plugin running live visualising a test network of 30 nodes. The the fact that new information is available in the network. Should green coloured node indicates the block producer role for the a node hear about the gossip, and require the information it will current slot, nodes coloured violet are part of the committee, and contact neighbouring nodes asking for the data. In general, gos- blue nodes are validators. sip protocols make no assumptions about the topology of the overlay network. However, with structured networks, the infor- mation exchange can be made much more efficient. The observed blockchain implementation utilized a semi structured network topology for propagating consensus based information. This is made possible by using a seed string shared between nodes that is used for pseudo-random role election every block. Using the seed, nodes self-elect into roles without the need to communicate. However, when performing roles, committee members must at- test to the candidate block produced by the block producer. The seeded random is therefore also used to cluster the network using Figure 4: Consensus plugin (with legend) visualising a test a k-means algorithm. The clustering is again performed by each network of 30 nodes in real time. node locally. The shared seed guarantees that nodes will produce the same topology, which is then used to efficiently propagate attestations to the block producer. The network topology hence changes every slot. The plugin 4.3 Generality aims to visualize the changes in the network topology by draw- In order to use the above plugins, users have to provide certain ing nodes, and their cluster representatives. Additionally, the data to the Grafana dashboard and this can be done through consensus roles for each node are indicated with the vertex color. Grafana GUI. For the plugins to work all of the data should follow Figure 3 shows the network plugin rendering a test network of a specific naming policy. For example, for the Consensus plugin 30 nodes in real-time. The node in the center coloured green is there is one necessary query to visualize data about the nodes of the elected block producer for the current slot, nodes surrounded the network. It can be provided using SQL or Grafana GUI: by the red stroke are cluster representatives, the rest of the nodes SELECT "slot", "node", "duty" FROM "" are coloured based on their role in the current slot. WHERE $timeFilter Both plugins can be customized from the Grafana options menu. For example, users can add new roles, name and color them. Figure 5 shows the consensus plugin options menu, where users can additionally turn on or off display of messages, nodes or containers labels and so on. For both plugins, users have to manually provide the slot time of the network in the plugins options menus. Figure 3: Network topology plugin visualising a test net- work of 30 nodes in real time. 4.2 Consensus Plugin The aim of visualising the consensus mechanism is to quickly Figure 5: Consensus plugin options menu. evaluate if nodes contributing to the consensus learned about 126 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Daniil Baldouski and Aleksandar Tošić By using our tools we can visualize other protocols. For exam- We conclude that visualisation is an important tool in design ple with the consensus plugin we can visualize the famous Paxos and implementation of decentralized, and distributed systems. algorithm, first introduced in [7] by Leslie Lamport. For that, we The methods serve a complementary role to existing debugging should provide the plugin with the Nodes and Messages queries. methods, and are very powerful at observing unexpected be- For the Nodes query, parameters slot, node and duty should be haviour of the system as a whole. Visualisation techniques are provided, which represent the slot number, node id and the role specifically important in detecting stochastic faults that are non- of the node respectively. From the point of nodes and slots, for trivial to reproduce. Our tools are open-source and available for this visualization Paxos works in the same way as the example researchers and engineers to use. They are suitable for testing of the PoS based consensus we mentioned before. For the duty any kind of voting-based consensus protocol with little effort. parameter, nodes can have one of the three roles: proposer, ac- For future work we would like to further develop our tools ceptor or learner. That is why in the options menu of the plugin to accommodate other consensus protocols and help developers we should create 3 roles and name them according to the names visualize and debug other types of issues related to distributed from the data table. systems. Also, we would like to explore other types of visualiza- We should specify slot time (in seconds) in the plugin options tions and other existing tools that can help developers as well. menu and at this point we can set the Grafana dashboard refresh Since Grafana is rapidly evolving, our developed plugins can be time and see the results, since all the necessary conditions are updated and new technologies can be integrated with our tools fulfilled. But in order to gain more information from the plugin, to improve their performance. we should add the Messages query. For the data we should have the following parameters: id, source, target and endpoint, which 6 ACKNOWLEDGMENTS represent the message id, node id that sends the messages, node The authors gratefully acknowledge the European Commission id that receives the message and the type of the message. For for funding the InnoRenew CoE project (H2020 Grant Agreement the additional information we can specify parameters delay (in #739574) and the Republic of Slovenia (Investment funding of the seconds) and size of the message. Republic of Slovenia and the European Union of the European If we know the expected amount of nodes for some role, we Regional Development Fund) as well as the Slovenian Research can put it in the in plugin options menu to see this information in Agency (ARRS) for supporting the project number J2-2504 (C). the plugin legend. In a similar way we should be able to visualize other consensus protocols, for example 2PC or Raft [9]. REFERENCES Source code for both plugins is open source, licensed under [1] Beschastnikh, I., Wang, P., Brun, Y., and Ernst, M. D. Debugging distributed the MIT license and available on GitLab, where users can find systems. Commun. ACM 59, 8 ( jul 2016), 32–37. [2] Chakraborty, M., and Kundan, A. P. Grafana. In Monitoring Cloud-Native the installation procedure of the plugins: Applications. Springer, 2021, pp. 187–240. • [3] Creţu-Ciocârlie, G. F., Budiu, M., and Goldszmidt, M. Hunting for prob- Network plugin - https://gitlab.com/rentalker/topology- lems with artemis. In Proceedings of the First USENIX Conference on Analysis visualization-plugin, of System Logs (USA, 2008), WASL’08, USENIX Association, p. 2. • Consensus plugin - https://gitlab.com/rentalker/consensus- [4] Garduno, E., Kavulya, S. P., Tan, J., Gandhi, R., and Narasimhan, P. Theia: Visual signatures for problem diagnosis in large hadoop clusters. In Proceedings visualization-plugin. of the 26th International Conference on Large Installation System Administration: Strategies, Tools, and Techniques (USA, 2012), lisa’12, USENIX Association, 5 CONCLUSION p. 33–42. [5] Geels, D., Altekar, G., Maniatis, P., Roscoe, T., and Stoica, I. Friday: Global We developed two Grafana plugins for visualising PoS based comprehension for distributed replay. vol. 7. [6] Geels, D., Altekar, G., Shenker, S., and Stoica, I. Replay debugging for blockchains, and the underlying overlay network topology. The distributed applications. In 2006 USENIX Annual Technical Conference (USENIX plugins were used to identify critical bugs, and faults in the ATC 06) (Boston, MA, May 2006), USENIX Association. protocol. With the help of visualisations, we were able to detect [7] Lamport, L. The part-time parliament. ACM Transactions on Computer Systems 16, 2 (May 1998), 133-169. Also appeared as SRC Research Report 49. This paper two problems when running test-nets. was first submitted in 1990, setting a personal record for publication delay that • Network congestion: has since been broken by [60]. (May 1998). ACM SIGOPS Hall of Fame Award for every slot, validators must re- in 2012. port their statistics to the block producer. Prompt delivery [8] Naqvi, S. N. Z., Yfantidou, S., and Zimányi, E. Time series databases and is desired but not critical. However, as the network grew in influxdb. Studienarbeit, Université Libre de Bruxelles 12 (2017). [9] Ongaro, D., and Ousterhout, J. In search of an understandable consen- size, reporting statistics to a single node (block producer) sus algorithm. In Proceedings of the 2014 USENIX Conference on USENIX An- became increasingly latent as all nodes attempted to prop- nual Technical Conference (USA, 2014), USENIX ATC’14, USENIX Association, p. 305–320. agate messages in tandem, and even more importantly, [10] Sanjappa, S., and Ahmed, M. Analysis of logs by using logstash. In Proceedings the network topology required a lot of routing for mes- of the 5th International Conference on Frontiers in Intelligent Computing: Theory sages to arrive to the block producer. The network plugin and Applications (Singapore, 2017), S. C. Satapathy, V. Bhateja, S. K. Udgata, and P. K. Pattnaik, Eds., Springer Singapore, pp. 579–585. helped us identify what the problem was by looking at the [11] Turnbull, J. Monitoring with Prometheus. Turnbull Press, 2018. topology. [12] Xu, W., Huang, L., Fox, A., Patterson, D., and Jordan, M. Online system • State synchronisation: at random, nodes failed to per- problem detection by mining patterns of console logs. In 2009 Ninth IEEE International Conference on Data Mining (2009), pp. 588–597. form their roles. This resulted in missing votes even on [13] Xu, W., Huang, L., Fox, A., Patterson, D., and Jordan, M. I. Detecting large- small test-nets, and sometimes a chain halt where no scale system problems by mining console logs. In Proceedings of the ACM SIGOPS 22nd Symposium on Operating Systems Principles (New York, NY, USA, blocks were produced for the slot. We observed the likeli- 2009), SOSP ’09, Association for Computing Machinery, p. 117–132. hood of this happening grows in correlation with network size. However, it was infeasible to debug the state of all nodes in a large network. Visualising the state of nodes at a given slot we observed that states were not always synchronized and hence, some nodes did not learn about their consensus role. 127 Using Machine Learning for Anti Money Laundering Gregor Kržmanc Filip Koprivec Maja Škrjanc gregor.krzmanc@ijs.si filip.koprivec@ijs.si maja.skrjanc@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia IMFM Ljubljana, Slovenia Ljubljana, Slovenia Figure 1: Example transaction network visualization ABSTRACT to strengthen its anti money laundering and terrorist financ- ing regulatory framework and expects the same from financial Here we present early results of a network component for anom- institutions and supervisory authorities. aly detection in an attributed heterogeneous financial network. Given a pseudonymized dataset of financial transactions, can Utilizing both externally provided features and generated topo- we use machine learning to detect interesting, perhaps novel, logical features, we train different models for a simple link pre- patterns that should be inspected manually? In this paper, we try diction task. We then evaluate the models using initial dataset to answer this question. corruption. We show that gradient boosting and multi-layer per- ceptron generally have the best anomaly detection performance, despite graph neural network models initially showing better 2 RELATED WORK results in the link prediction task. Both supervised [7, 6, 12] and unsupervised or self-supervised [2, KEYWORDS 14] learning approaches have been proposed to deal with the task of detecting money laundering. Due to the lack of labelled data Anti Money Laundering (AML), machine learning, networks, link and the closed nature of financial data and, therefore, the lack prediction of standardised datasets, approach evaluation can be difficult. 1 INTRODUCTION Despite that, cryptocurrency datasets such as [13] have been published, explored, and labelled to some extent. Observing complex real-world graphs, be it a social, financial, Usually, synthetic oversampling or other strategies of sampling biochemical, or physics-related network, is an interesting task. need to be employed in cases where labelled entities are used for Given a time-evolving network and rich information about the evaluation [12, 13]. nodes and edges, can we assume that there are some regular dynamics in the network? 3 DATA Fraud and financial crime are important issues of our time. According to the United Nations Office on Drugs and Crime, an In this study, we use a snapshot of the transaction data processed estimated 2-5 % of the world GDP is laundered each year. To through the international payment system Target2-Slovenija [11]. keep pace with evolving trends, the European Union has decided The dataset spans from November 2007 to December 2017, con- taining around 8 million financial transactions. No live data was Permission to make digital or hard copies of part or all of this work for personal used when performing this research - only archived datasets or classroom use is granted without fee provided that copies are not made or were used. 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 For some nodes, the data about the sending or receiving party work must be honored. For all other uses, contact the owner /author(s). is additionally linked to data from the Slovenian Business Register Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia (ePRS) [1] and the Slovenian Transaction Account Registry (eRTR) © 2022 Copyright held by the owner/author(s). [3] in order to provide additional context about each transaction. 128 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia G. Kržmanc et al. feature level degree node-level deg (𝐴) = |𝑁 (𝐴) | PageRank [9] node-level Í 𝑃 𝑅 ( 𝐽 ) 𝑃 𝑅 (𝐴) = 1−𝑑 + 𝑑 ( ; 𝑑 = 0.85 𝑁 𝐽 ∈𝑁 𝐴) 𝑖𝑛 |𝑁 ( 𝐽 ) | 𝑜𝑢𝑡 Jaccard coefficient |𝑁 (𝐴)∩𝑁 (𝐵) | edge-level 𝐽 (𝐴, 𝐵) = |𝑁 (𝐴)∪𝑁 (𝐵) | Adamic-Adar Index 1 edge-level 𝐴 (𝑥 , 𝑦) = Í𝑢 ∈𝑁 (𝑥)∩𝑁 (𝑦) log |𝑁 (𝑢) | Table 1: The structural features used for the link prediction task. 𝑁 (·) represents the set of neighbours of the given node. 𝑁 and 𝑁 represent the sets of the nodes from 𝑖𝑛 𝑜𝑢𝑡 which there is an edge to the given node (𝑖𝑛), or to which there is an edge from the given node (𝑜𝑢𝑡). | · | represents cardinality of the given set. 5 ANOMALY DETECTION PROBLEM Figure 2: Degree distribution by node type. DEFINITION We corrupt the original graph by rewiring the total of 𝑝 = 1% randomly picked edges of each edge type. Due to the sensitive nature of the data, all personal and confi- Let 𝑓 : 𝑉 ×𝑉 → [0, 1] be a binary link prediction classifier that dential data about individuals and legal entities provided to JSI is trained to predict the probability that a directed edge between is pseudonymized. the two given nodes exists. We define the anomaly score of edge (𝑖, 𝑗 ) ∈ 𝐸 as 4 DATA REPRESENTATION AS A HETEROGENEOUS GRAPH 𝜙 (𝑖, 𝑗 ) = 1 − 𝑓 (𝑖, 𝑗 ) (1) The intuition behind equation 1 is that links that are typical to There are large differences in the availability of data across differ- the model would have a smaller anomaly score than links for ent entities performing the transactions. In order to fully utilize which the model predicts they would not exist (and are, thus, all available features, we model the network as a heterogeneous anomalous). temporal graph. Here, we treat the snapshot of the transaction graph from 𝑡 to ) as a heterogeneous graph con- 0 𝑡1 𝐺 = 𝐺 (𝑡0, 𝑡1 6 RESULTS sisting of 3 discrete node types representing each entity’s legal We train several models for the downstream task of link predic- status. The types of accounts are those belonging to companies tion and then use the predictions for anomaly detection. (node type s), natural persons (node type p), and all other accounts (node type o). Each transaction is represented as a directed edge 6.1 Experiment details from its source account to its destination account. The traditional (non-GNN) machine learning approaches are 4.1 Network statistics trained to predict whether the given edge exists or not. For each edge, the feature vector fed into the model is constructed by Due to different legislative bases for different types of entities, concatenating source node features, destination node features, inherent differences regarding data availability are expected. Nat- and edge features. For traditional models, a model for each edge urally, it is also expected that different categories usually act type is constructed separately, while the graph neural network- differently in a network - for example, companies usually trans- based models are the same across all edge types. act more than individuals. While the degree distribution (Figure 2) The GNN (graph neural network) models are constructed of 2 closely resembles the power law, significant differences in dis- layers of GraphSAGE aggregations [8, 5] using parametric ReLU tributions between different node types can be observed, which activations and embedding dimensions of 128 for the first and can be attributed to varying amounts of data available for our 64 for the second layer. As messages are passed in the direction specific data source across account profiles. of edges, we construct another model to facilitate information It can be seen from Figure 2 that companies (node type s) diffusion both ways. We do this by adding edges of opposite perform most of the transactions. directionality than existing edges and marking them as a separate 4.2 Feature generation edge types. We still, however, only train for the downstream link prediction objective only on the existing (non-transposed) edges. + Categorical features are one-hot encoded. Rare categories with We mark this approach as GNN . < 2% incidence are marked as other. Additionally, node features The traditional ML models used are gradient boosting (Grad- encoding the role of a node in the network (Table 1) are generated. Boost), decision tree (DecTree), multi-layer perceptron (MLP) and The node-level features for each node are computed on the whole logistic regression (LogReg). The hidden layer sizes of the MLP network as well as for the subgraph induced by the node’s own are 20 and 10, using ReLU activation in all layers except the last type. one, where softmax activation is used. Different combinations of 129 Using Machine Learning for Anti Money Laundering Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia + reasonable hidden layer sizes were tested (32+16, 64+32, 256+128, edge non-GNN no str. f. GNN GNN 128+128, 20+10) and the best one was selected. The training of ss 0.19 ± 0.02 0.16 ± 0.02 0.01 ± 0.00 0.01 ± 0.00 MLP models was performed with a batch size of 200. oo 0.11 ± 0.02 0.02 ± 0.01 0.05 ± 0.02 0.03 ± 0.02 so 0.11 ± 0.02 0.06 ± 0.01 0.01 ± 0.01 0.01 ± 0.01 6.2 Link prediction os 0.14 ± 0.02 0.06 ± 0.01 0.01 ± 0.00 0.01 ± 0.01 sp 0.08 ± 0.04 0.02 ± 0.02 0.02 ± 0.01 0.02 ± 0.02 Traditional ML models for link prediction map concatenated ps 0.05 ± 0.02 0.05 ± 0.02 0.01 ± 0.01 0.01 ± 0.01 source and destination node features and edge features to the po 0.07 ± 0.04 0.07 ± 0.05 0.02 ± 0.02 0.01 ± 0.02 probability that a link between such nodes exists. The models are op 0.18 ± 0.04 0.02 ± 0.01 0.02 ± 0.01 0.03 ± 0.02 implemented using scikit-learn [10] and are trained and evaluated Table 3: Anomaly detection performance comparison in 𝐹 using 5-fold cross-validation. 1 score (mean ± standard deviation). Best non-GNN score, as As a preprocessing step, each feature is scaled individually well as best non-GNN score without using any structural using a standard scaler such that it has a mean of 0 and a standard features, are reported next to the GNN results. Bold results deviation of 1 across the training set. highlight the best performance across observed methods. When training and evaluating each model, an approximately equal number of positive and negative links is given to the classi- fier. The provided edge features such as transaction amount are sampled randomly for negative edges. Additionally, we train a 2-layer graph neural network (GNN) −1 −1 − precision + recall 1 for link prediction. The GNN model is trained jointly for all edge 𝐹 = (2) 1 2 types using weighted binary cross-entropy loss. The model has A naive classifier that assigns the same positive score (recall ReLU activations in all layers except the last one, where it has 1) to each edge has 𝐹 score of ≈ 0 1 .02. However, the underrepre- softmax activation. The hidden layer sizes are 64 and 32. The sented edge types typically have higher variance in 𝐹 score and 1 graph neural network is implemented using PyTorch Geometric performance insignificantly different from the naive baseline, as [4]. seen from Table 3. The same goes for the GNN-based models. See We use a random link split for link prediction and not a tempo- Appendix A for more detailed non-GNN model results. ral one, as our end goal is not to predict future links, but rather to learn what kinds of transactions are typical in the given network. 7 DISCUSSION AND FUTURE WORK Table 2 shows the aggregated link prediction results. Bold We have constructed and evaluated a self-supervised approach results highlight the best performance across observed methods. to anomaly detection in financial networks. Due to the lack of The GNN does slightly improve link prediction performance in labelled data, this is in most cases the most straightforward ap- some cases. See Appendix A for more detailed non-GNN method proach to tackle the problem with machine learning. There are results. The data here is computed across multiple year-long time significant differences in performance across different edge types. windows. Using this approach yields almost comparable results with both + raw features and structural features when evaluated on company- edge non-GNN no str. f. GNN GNN to-company transactions only. This may be explained by compa- ss 0.92 ± 0.01 0.89 ± 0.01 0.92 ± 0.02 0.94 ± 0.01 nies in our dataset having the most insightful features of all node oo 0.80 ± 0.02 0.57 ± 0.01 0.79 ± 0.02 0.53 ± 0.04 types such as the broader sector and also more precise company so 0.83 ± 0.01 0.75 ± 0.01 0.88 ± 0.02 0.74 ± 0.04 industry type classification. os 0.76 ± 0.01 0.64 ± 0.01 0.81 ± 0.01 0.83 ± 0.02 This paper has mainly focused on the use of unsupervised sp 0.85 ± 0.02 0.69 ± 0.03 0.78 ± 0.05 0.73 ± 0.02 learning for anomaly detection. In the future, we plan to extend ps 0.74 ± 0.02 0.67 ± 0.01 0.87 ± 0.02 0.75 ± 0.04 our work to supervised and semi-supervised learning approaches po 0.78 ± 0.02 0.66 ± 0.01 0.84 ± 0.04 0.54 ± 0.08 to try to utilize the few labelled data points. The following ma- op 0.89 ± 0.01 0.53 ± 0.01 0.78 ± 0.05 0.50 ± 0.05 chine learning strategies (or a combination of them) could be all 0.84 ± 0.01 0.72 ± 0.01 0.86 ± 0.02 0.89 ± 0.01 tested: Table 2: Link prediction performance comparison mea- sured in area under the receiver operating characteristic • Active learning. Human-assisted active learning approach curve (AUC) (mean is a natural way to incorporate domain knowledge into ± standard deviation). Edge types are marked with two letters, representing the source and des- the decision-making process. tination node type in this order. Best non-GNN score, as • Synthetic oversampling. Due to a small number of the well as best non-GNN score without using any structural positive examples, we could sample new examples that features, are reported next to the GNN results. are similar to them and assign them positive labels. • Model pretraining and few-shot learning. Update model parameters with a self-supervised pretraining strategy first, and then optimize it further on the few labeled data points. 6.3 Anomaly detection ACKNOWLEDGMENTS For comparison between different methods, the 2% of edges with the highest anomaly scores are flagged as positive. Precision and The research leading to the results presented in this paper has recall are calculated by using the corrupted 1% of edges as true received funding from the European Union’s funded Project IN- positives. FINITECH under grant agreement no. 856632. To summarize precision and recall in a single metric, 𝐹 score (2) The financial transaction data used in the presented research 1 is calculated and reported. was collected and pseudonymized by the Bank of Slovenia. 130 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia G. Kržmanc et al. 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Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia blaz.fortuna@qlector.com dunja.mladenic@ijs.si ABSTRACT to such processes can improve quality and yield and help engineers In this research, we develop machine learning models to predict predict anomalies to control the factory better. future sensor readings of a waste-to-fuel plant, which would enable We modeled the JEMS waste-to-fuel plant, which produces high- proactive control of the plant’s operations. We developed models quality diesel from organic waste. The plant has numerous sensors that predict sensor readings for 30 and 60 minutes into the future. that measure temperature, and pressure, among other variables. The models were trained using historical data, and predictions were It is operated by experts who must control the process. Since the made based on sensor readings taken at a specific time. We compare chemical process is complex and, therefore, difficult to control, we three types of models: (a) a näive prediction that considers only built forecasting models that can predict future sensor readings the last predicted value, (b) neural networks that make predictions based on historical data and the current state of the plant. based on past sensor data (we consider different time window sizes The model will be used to give plant operators additional infor- for making a prediction), and (c) a gradient boosted tree regressor mation about the future state of the plant, which will allow them to created with a set of features that we developed. We developed and make an informed decision about changing the plant’s parameters tested our models on a real-world use case at a waste-to-fuel plant and, therefore, adjust the process before it is too late. in Canada. We found that approach (c) provided the best results, while approach (b) provided mixed results and was not able to 2 RELATED WORK outperform the näive consistently. Organic wastes in energy conversion technologies are an active area of research aimed at reducing dependence on fossil fuels, optimiz- CCS CONCEPTS ing production costs, improving waste management, and control- • Computing methodologies → Machine learning; • Applied ling emissions. Biochemical, physiochemical, and thermochemical computing; processes produce different biofuels, such as bio-methanation, bio- hydrogen, biodiesel, ethanol, syngas, and coal-like fuels, which are KEYWORDS studied by Stephen et al. [8]. Work is also being done on optimiza- Smart Manufacturing, Machine Learning, Feature Engineering tion, such as catalyst selection, reactor design, pyrolysis tempera- ture, and other important factors [5]. ACM Reference Format: Many ML methods have been developed to address waste man- Bor Brecelj, Beno Šircelj, Jože M. Rožanec, Blaž Fortuna, and Dunja Mladenić. agement and proper processing for biofuel production, focusing 2022. Forecasting Sensor Values in Waste-To-Fuel Plants: a Case Study.. In on energy demand and supply prediction [3]. Aghbashlo et al. [2] Ljubljana ’22: Slovenian KDD Conference on Data Mining and Data Ware- houses, October, 2022, Ljubljana, Slovenia. ACM, New York, NY, USA, 4 pages. provided a systematic review of various applications of ML technol- ogy with a focus on ANN (Artificial Neural Network) in biodiesel 1 INTRODUCTION research. They provided an overview of the use of ML in modeling, optimization, monitoring, and process control. Models that pre- There is a wide range of applications of ML (machine learning). dict the conditions of the biofuel production process that have the One of them is the modeling and control of chemical processes, highest yield were created by Kusumo et al. [6] and Abdelbasset et such as the production of biodiesel. Introducing machine learning al. [1]. The models used in these studies were kernel-based extreme learning machines, ANN, and various ensemble models. ∗Both authors contributed equally to this research. Permission to make digital or hard copies of part or all of this work for personal or 3 USE CASE 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 The JEMS waste-to-fuel plant produces synthetic diesel (SynDi) on the first page. Copyrights for third-party components of this work must be honored. from any hydrocarbon-based waste, such as wood, biomass, pa- For all other uses, contact the owner/author(s). per, waste fuels and oils, plastics, textiles, rubber, and agricultural SiKDD ’22, October, 2022, Ljubljana, Slovenia residues. The plant uses a chemical-catalytic de-polymerization © 2022 Copyright held by the owner/author(s). process, the advantage of which is that the temperature is too low 132 SiKDD ’22, October, 2022, Ljubljana, Slovenia Brecelj et al. to produce carcinogenic gasses. It operates continuously and pro- all sensors with less than 6.000 data points and kept only those that duces about 150 liters of fuel per hour. Although it uses the latest corresponded to chambers B100 and B200, giving us data from 39 software available and allows remote control, there is no anomaly sensors. detection, prediction, or optimization. As a result, there is a great Analysis of the dataset we received revealed that many values need for better understanding, optimization, and decision-making, were missing. In particular, we noted that there were day-long given data availability. The company plans to sell and install over intervals with a tiny number of measurements. We also noticed 1.500 SynDi systems over the next ten years. In practice, this means that specific sensor values remained constant at low temperatures - many SynDi plants in different locations worldwide. a condition best described by the waste-to-fuel plant’s inactivity. There are three main chambers in the pipeline, which are named We, therefore, decided to remove such values. Because there were B100, B200, and B300. The plant can be conceptually split into four many ten-minute gaps, we decided to resample the data at fifteen- stages minute intervals, taking the last value of each interval and assuming (1) Feedstock inspecting and feeding; that conditions had not changed in the short time since the last (2) Drying and mixing (chamber B100); measurement - a reasonable assumption for sensor values. The (3) Processing (chamber B200); resulting data set contained an average of 7.884 data points per (4) Distilling (chamber B300). sensor. Since there are no sensors in the feedstock inspecting and feeding We divided the dataset into a train and a test dataset, split on stage, we focused on the later stages, each of which takes place in October 31st 2016. The resulting train set included a total of 11.000 one of the main chambers. samples, and the test set included 3.000 samples. In the drying and mixing stage (B100), the starting material is mixed with process oil, lime, and catalyst and is heated. During 4.2 Model training mixing, the material is broken down into smaller particles, and the In this research, we compare models that we develop using two water is evaporated. The primary chemical reaction occurs in the different approaches. We first tried the neural network approach, in processing stage (B200). The material is fed to a turbine, and the which the model makes predictions based only on sensor readings reaction product evaporates through the diesel distillation column. from the last five hours. Since the model did not perform better than If the diesel obtained is not of sufficient quality, it is redistilled in the baseline, we began the second approach, developing features the second distillation stage (B300). to describe the time series and capture its patterns. We used linear Currently, the plants are operated with highly skilled person- regression and gradient-boosted tree regressor. All the developed nel and high costs for personnel training. Implementing automa- models were compared with the last-value model, which we used tion, remote control, optimization, and interconnection among the as a benchmark. plants would greatly facilitate their operation. Therefore, the main challenge to be solved by integrating AI is the self-control of the 4.2.1 Neural network approach. We used the model developed for chemical process and the plant itself by minimizing the human forecasting Tüpras’ sensor values. Tüpras is an oil refinery, which resources required to operate the plants. Furthermore, operating is very similar to the JEMS use case. The model was used to forecast many SynDi plants also means a significant challenge for ensuring sensor values in different units of LPG production. Some of Tüpras’ remote control for troubleshooting, maintenance, and repair. AI units are distillation columns, similar to JEMS’ chamber B200. The integration aims to minimize the workforce required to operate the model takes only past sensor values as input and predicts values for plants, minimize the resulting downtime due to human interaction, the future together with the prediction interval. More specifically, enable self-control and predictive maintenance of the SynDi plants, it predicts 10th, 50th and 90th percentile, which is the case in all our and achieve less downtime and higher production efficiency. models that give prediction interval. In modeling the waste-to-fuel processes, we decided to model each chamber separately. No model was developed for chamber B300 because it was not active during the period for which we obtained the data. As described above, a second distillation of the fuel is performed in chamber B300 only if the fuel in chamber B200 is not pure enough. 4 METHODOLOGY Figure 1: Architecture of the neural network model, which 4.1 Data analysis gives the prediction interval. The sensor measurements are from the experimental JEMS plant, which is located in Canada. The data consists of 154 sensors from January 2016 to January 2017. The measurements are taken at Figure 1 shows the architecture of the neural network. The model one-minute intervals and mostly measure temperature or pressure, is a feedforward neural network with two layers. First, there is a but there are also sensors for motor current and valve position, linear layer with ReLU activation. The second layer has a separate among others. Since the data is from the prototype version of the linear layer for each quantile. The hidden dimension of the model waste-to-fuel plant, it contains many missing values. Our data set is calculated from the number of features and the number of targets contained an average of 61.607 data points per sensor. We discarded using the formula ⌊ 𝑛features ⌋ + 2 𝑛targets. 133 Forecasting Sensor Values in Waste-To-Fuel Plants: a Case Study. SiKDD ’22, October, 2022, Ljubljana, Slovenia During training, we used the quantile loss function, which is Using developed features, we trained a linear regression model, defined as and a gradient boosted tree regressor from the CatBoost library [4]. n o We used root mean squared error (RMSE) for the loss function. max 𝑞 · 𝑦true − 𝑦pred , (1 − 𝑞) · 𝑦pred − 𝑦true , where 5 RESULTS AND ANALYSIS 𝑞 is the observed quantile (in our case, it can be 0.1, 0.5 or 0.9), 𝑦true is the true target value and 𝑦pred is the corresponding We built models for main chambers B100 and B200 with two fore- quantile of the prediction. In the case of 𝑞 = 0.5, the loss is equal casting horizons (30 and 60 minutes). Tables 1 and 2 show mean to the mean absolute error divided by two. When calculating the squared error (MSE) and mean absolute error (MAE) on chambers loss of 10th percentile (𝑞 = 0.1), a prediction that is greater than B100 and B200, respectively. There are three different neural net- the true value is heavily penalized, while a prediction that is lower work models (NN), which differ in the size of the window from than the true value has a smaller loss and is therefore encouraged. which it gets the data. The model is implemented in the PyTorch library [7]. Since sensors measure different quantities, the values have to be scaled horizon = 30min horizon = 60min before learning. Here we used Min-Max scaler from the scikit-learn MSE MAE MSE MAE library, scaling all values between zero and one. last-value model 21.0533 1.4320 50.6636 2.5128 NN, window = 5h 21.7525 1.6512 47.0545 2.5413 4.2.2 Feature engineering. The neural network model described NN, window = 3h 19.7441 1.6109 45.3450 2.4127 above did not outperform the benchmark model. As a result, we NN, window = 2h 18.9717 1.6023 46.5047 2.5357 decided to try another approach, where we developed features that Linear regression 19.4264 1.4634 49.2268 2.5145 better describe past sensor values and capture their patterns. One of Catboost 16.9030 1.4478 38.3066 2.3164 the problems of the neural network model was that it had too many features. We decided to build a separate model for each sensor to Table 1: MSE and MAE on the test set of models when pre- tackle this problem. Each model uses only features calculated from dicting for chamber B100. the values of the sensor being predicted. With the help of plant operators, we decided to consider at most five hours of data before the prediction point to issue a forecast. Since the latest data is usually more important in determining future horizon = 30min horizon = 60min sensor values, we created features on seven different time windows: MSE MAE MSE MAE 30, 45, 75, 120, 180, 240, and 300 minutes. For each time window, last-value model 52.3380 2.0577 124.9735 3.3768 we computed the following features: NN, window = 5h 69.4678 3.8227 129.0330 4.9927 • average sensor value, NN, window = 3h 57.9902 3.3601 121.1315 4.7431 • fraction of peaks in the window, NN, window = 2h 55.8769 3.1797 117.4154 4.7146 • percentage change between first and last value in the time Linear regression 55.0218 3.2293 115.7457 4.5888 window, Catboost 49.3329 2.5305 109.5303 3.9745 • slope (coefficient of the least squares line through the points in the window), Table 2: MSE and MAE on the test set of models when pre- • simple prediction (extension of the least squares line to the dicting for chamber B200. future), • slope ratio (slope on the smaller window divided by the slope From the tables 1 and 2 we can see that the five-hour window’s on the bigger window). neural network performed worse than the benchmark. The main Besides features mentioned above, which depend on the window reason for such poor results was too many features for the amount size, we also included features that were calculated only on the of data that we have. More precisely, the neural network model biggest time window (300 minutes): uses the values of all sensors in the chamber we are predicting. This means that there are six hundred features resulting in more • last value, than two hundred thousand trainable parameters for the model of • maximal value, chamber B200. We also have to consider that the neural network • last value relative to the maximal value. predicts future sensor values and prediction intervals. Therefore, The features above attempt to capture different time series charac- there are too many features and target values for the amount of teristics: data that we have. • trend: described by percentage change and slope; We included results of two more neural network models with • growth pattern: described by the fraction of peaks, which three hours and two-hour windows since reduced window size indicate whether the growth is steady or it has ups-and- results in a smaller number of features and trainable parameters. For downs. Furthermore, the slope indicates how aggressive such example, the neural network model with a two-hour time window growth is; for chamber B200 had two hundred and forty features and almost • expected value: an approximation of the expected value is fifty thousand trainable parameters. Neural network models with given through the average, last value, maximal value, and smaller window sizes performed better, which confirms that we simple prediction. had too many features. 134 SiKDD ’22, October, 2022, Ljubljana, Slovenia Brecelj et al. The features that we developed using the second approach were However, there is no problem with models not being able to pre- used with two models, linear regression and the Catboost model. dict significant changes resulting from a manual change in plant Comparing those two models, the Catboost model performed better setpoint parameters, which our data does not capture. Overall, we because it can capture more than just linear relationships between consider the best model was the Catboost model, given in all cases the features and the target. The Catboost model also outperformed it outperformed the rest of the models when considering MSE, and the neural networks, where one of the main differences is that also achieved the best MAE when predicting chamber B100 with a the neural network uses all sensors from the chamber while the time horizon of 60 minutes. Catboost model uses only sensor values of the sensor which is being predicted. This results in forty-five features for the model 6 CONCLUSION that predicts one sensor, which solves the problem of too many We compared a set of models to predict sensor values for a waste- features. In addition, the Catboost model produced better results to-fuel plant: a neural network, linear regression, gradient-boosted than the benchmark when comparing the mean squared error (MSE). tree regressor, and the last-value model. The last-value model was During the training, we used RMSE as a loss function, meaning used as a benchmark. We developed three neural network models that RMSE was minimized and, therefore, also MSE. which were different in time window size. The neural network The tables show that although most models outperform the models were built based on the hypothesis that a simple neural benchmark regarding MSE, almost all of them do not surpass the network and raw sensor readings as features are enough to model benchmark when considering MAE. When measuring MSE, pre- the process. The results showed that this is not the case because the dictions with strong spikes where such spikes do not take place process is too complicated for the amount of data that we obtained. are penalized more. Therefore, models with a competitive MSE Lastly, we used feature engineering to develop features that better are considered to rarely predict spikes when such spikes do not describe the time series. Features were used for learning linear take place. This is a key feature for our use case, given that we are regression, and the gradient boosted tree regressor, where the latter interested to understand whether an irregularity will take place or produced the best results in our case. not. Therefore, the models give valuable information even though the average prediction is not entirely accurate. ACKNOWLEDGMENTS This work was supported by the Slovenian Research Agency and the European Union’s Horizon 2020 program project FACTLOG under grant agreement number H2020-869951. REFERENCES [1] Walid Kamal Abdelbasset, Safaa M Elkholi, Maria Jade Catalan Opulencia, Tazed- dinova Diana, Chia-Hung Su, May Alashwal, Mohammed Zwawi, Mohammed Algarni, Anas Abdelrahman, and Hoang Chinh Nguyen. 2022. Development of multiple machine-learning computational techniques for optimization of heteroge- Figure 2: True value and prediction of the Catboost model nous catalytic biodiesel production from waste vegetable oil. 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Figure 3: True value and prediction with a confidence interval [6] F Kusumo, AS Silitonga, HH Masjuki, Hwai Chyuan Ong, J Siswantoro, and TMI of the neural network model with a two-hour window for a Mahlia. 2017. Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and temperature sensor in chamber B100. artificial neural networks. Energy 134 (2017), 24–34. [7] Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Figure 2 shows the Catboost model prediction on the test set Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan together with the true values of the temperature sensor in chamber Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith B100. The neural network model’s prediction of the same sensor is Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32, H. Wallach, presented in Figure 3. Since the neural network model also outputs H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett (Eds.). Curran prediction interval, it is shown in the abovementioned Figure. Associates, Inc., 8024–8035. http://papers.neurips.cc/paper/9015-pytorch-an- imperative-style-high-performance-deep-learning-library.pdf From the plots, we can see that both models can closely pre- [8] Jilu Lizy Stephen and Balasubramanian Periyasamy. 2018. Innovative develop- dict future sensor values. In the case of the neural network model, ments in biofuels production from organic waste materials: a review. Fuel 214 the actual value is mainly inside the predicted confidence inter- (2018), 623–633. val, except when there is a significant change in the sensor value. 135 Machine Beats Machine: Machine Learning Models to Defend Against Adversarial Attacks. Jože M. Rožanec∗ Dimitrios Papamartzivanos Entso Veliou Jožef Stefan International Ubitech Ltd Department of Informatics and Postgraduate School Chalandri, Athens, Greece Computer Engineering, University of Ljubljana, Slovenia dpapamartz@ubitech.eu West Attica joze.rozanec@ijs.si Athens, Greece eveliou@uniwa.gr Theodora Anastasiou Jelle Keizer Blaž Fortuna Ubitech Ltd Philips Consumer Lifestyle BV Qlector d.o.o. Chalandri, Athens, Greece Drachten, The Neatherlands Ljubljana, Slovenia tanastasiou@ubitech.eu jelle.keizer@philips.com blaz.fortuna@qlector.com Dunja Mladenić Jožef Stefan Institute Ljubljana, Slovenia dunja.mladenic@ijs.si ABSTRACT 1 INTRODUCTION We propose using a two-layered deployment of machine learning Artificial Intelligence (AI) solutions have penetrated the Industry models to prevent adversarial attacks. The first layer determines 4.0 domain by revolutionizing the rigid production lines enabling whether the data was tampered, while the second layer solves a innovative functionalities like mass customization, predictive main- domain-specific problem. We explore three sets of features and tenance, zero defect manufacturing, and digital twins. However, three dataset variations to train machine learning models. Our re- AI-fuelled manufacturing floors involve many interactions between sults show clustering algorithms achieved promising results. In the AI systems and other legacy Information and Communications particular, we consider the best results were obtained by applying Technology (ICT) systems, generating a new territory for malevo- the DBSCAN algorithm to the structured structural similarity in- lent actors to conquer. Hence, the threat landscape of Industry 4.0 is dex measure computed between the images and a white reference expanded unpredictably if we also consider the emergence of adver- image. sary tactics and techniques against AI systems and the constantly increasing number of reports of Machine Learning (ML) systems CCS CONCEPTS abuses based on real-world observations. In this context, Adversar- ial Machine Learning (AML) has become a significant concern in • Information systems → Data mining; • Computing method- adopting AI technologies for critical applications, and it has already ologies → Computer vision problems; • Applied computing; been identified as a barrier in multiple application domains. AML is a class of data manipulation techniques that cause changes in the be- KEYWORDS havior of AI algorithms while usually going unnoticed by humans. Cybersecurity, Adversarial Attacks, Machine Learning, Automated Suspicious objects misclassification in airport control systems [7], Visual Inspection abuse of autonomous vehicles navigation systems [11], tricking of healthcare image analysis systems for classifying a benign tumor as ACM Reference Format: malignant [15], abnormal robotic navigation control [23] are only Jože M. Rožanec, Dimitrios Papamartzivanos, Entso Veliou, Theodora Anas- a few examples of AI models’ compromise that advocate the need tasiou, Jelle Keizer, Blaž Fortuna, and Dunja Mladenić. 2021. Machine Beats for the investigation and development of robust defense solutions. Machine: Machine Learning Models to Defend Against Adversarial Attacks.. Recently, the evident challenges posed by AML have attracted In Ljubljana ’22: Slovenian KDD Conference on Data Mining and Data Ware- the attention of the research community, the industry 4.0, and houses, October, 2022, Ljubljana, Slovenia. ACM, New York, NY, USA, 4 pages. the manufacturing domains [20], as possible security issues on AI systems can pose a threat to systems reliability, productivity, and safety [2]. In this reality, defenders should not be just passive 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 spectators, as there is a pressing need for robustifying AI systems for profit or commercial advantage and that copies bear this notice and the full citation to hold against the perils of adversarial attacks. New methods are on the first page. Copyrights for third-party components of this work must be honored. needed to safeguard AI systems and sanitize the ML data pipelines For all other uses, contact the owner/author(s). SiKDD ’22, October, 2022, Ljubljana, Slovenia from the potential injection of adversarial data samples due to © 2021 Copyright held by the owner/author(s). poisoning and evasion attacks. 136 SiKDD ’22, October, 2022, Ljubljana, Slovenia Rožanec et al. We developed a machine learning model to address the above- by various transformations and contaminated by different noises mentioned challenges, detecting whether the incoming images are to foster robustness using adversarial training. adversarially altered. This enables a two-layered deployment of On top of the above, several standalone solutions have been machine learning models that can be used to prevent adversar- proposed. CARAMEL system in [13] offered a set of detection ial attacks (see Fig. 1): (a) the first layer with models determining techniques to combat security risks in automotive systems with whether the data was tampered, and (b) a second layer that operates embedded camera sensors. Hybrid approaches and more general with regular machine learning models developed to solve particu- alternatives intrinsically improve the robustness of AI models. A lar domain-specific problems. We demonstrate our approach in a defensive Distillation mechanism against evasion attacks is pro- real-world use case from Philips Consumer Lifestyle BV. This paper posed in [16] being able to reduce the effectiveness of adversarial explores a diverse set of features and machine learning models sample creation from 95% to less than 0.5% on a studied DNN. Sub- to detect whether the images have been tampered for malicious set Scanning was presented in [19] to give the ability to DNNs to purposes. recognize out-of-distribution samples. 3 USE CASE The Philips factory in Drachten, the Netherlands, is an advanced factory for mass manufacturing consumer goods (e.g., shavers, OneBlade, baby bottles, and soothers). Current production lines are often tailored for the mass production of one product or product series in the most efficient way. However, the manufacturing land- scape is changing due to global shortages, manufacturing assets and components are becoming scarcer [1], and a shift in market Figure 1: Two-layered deployment of machine learning mod- demand requires the production of smaller batches more often. To els can be used to prevent adversarial attacks. adhere to these changes, production flexibility, re-use of assets, and a reduction of reconfiguration times are becoming more critical This paper is organized as follows. Section 2 outlines the current for the cost-efficient production of consumer goods. One of the state of the art and related works, Section 3 describes the use case, topics currently investigated within Philips is quickly setting up and Section 4 provides a detailed description of the methodology automated quality inspections to make reconfiguring quality con- and experiments. Finally, Section 5 outlines the results obtained, trol systems faster and easier. Next to working on the technical while Section 6 concludes and describes future work. challenges of doing this, safety and cyber-security topics are ex- plored, aiming to implement AI-enabled automated quality systems 2 RELATED WORK with state-of-the-art defenses, the latter of which is the focus point discussed in this paper. AML attacks are considered a severe threat to AI systems, and, that The dataset used contains images of the decorative part of a is, the research community seeks new robust defensive methods. Philips shaver. This product is mass-produced and important for the Image classifiers, those analyzed in this work, are the focal point of visual appearance of the shavers. Next to that, the part is very close the vast majority of the AML literature, as those have been proved to or in direct contact with the user’s skin, where any deviations in prone to noise perturbations. According to the literature, promi- its quality could impact shaver performance or even shaver safety. nent solutions focus on denoising the image classifiers, training The dataset contains 1.194 images classified into two classes: (a) the target model with adversarial examples, known as adversarial attacked with the Projected Gradient Descent attack [5], and (b) training, or applying standalone defense algorithms. not attacked. Yan et. al. [21] proposed a new adversarial attack called Observation- based Zero-mean Attack, and they evaluated the robustness of var- ious deep image denoisers. They followed an adversarial training 4 METHODOLOGY strategy and effectively removed various synthetic and adversarial We framed adversarial attack detection as a classification problem. noises from data. In [17], pre-processing data defenses for image We experimented with three kinds of features: (a) image embed- denoising are evaluated, highlighting the advantages of such ap- dings (obtained from the Average Pooling Layer of a pre-trained proaches that do not require the retraining of the classifiers, which ResNet-18 model ([9])), (b) histograms reflecting grayscale pixel is a computationally intense task in computer vision. frequencies (with pixel values extending between zero and 255), and However, the robustness of adversarial training via data augmen- (c) structural similarity index measure (SSIM) computed against a tation and distillation is advocated by the majority of the works white image. While the embeddings provide information about the in the domain. Specifically, Bortsova et al. [3] have focused on image as a whole, we considered the histograms and SSIM metric adversarial black-box settings, assuming that the attacker does could be useful given the apparent difference between the origi- not have full access to the target model as a more realistic sce- nal and perturbed images. Furthermore, we computed the features nario. They tuned their testbed to ensure minimal visual percepti- across three different datasets (see Fig. 2 for sample images): (a) bility of the attacks. The applied adversarial training dramatically original set of images, (b) images cropped considering an image decreased the performance of the designed attack. Hashemi and slice extending from top to bottom (coordinates (160, 0, 200, 369) - Mozaffari [8] trained CNNs with perturbed samples manipulated we name this dataset set "Cropped (v1)"), and (c) images cropped 137 Machine Beats Machine: Machine Learning Models to Defend Against Adversarial Attacks. SiKDD ’22, October, 2022, Ljubljana, Slovenia well, it would be useful to generalize the approach toward detecting new cyberattacks where no labeled data exists yet. We consider such a characteristic to be fundamental to production environments. For the models resulting from the three abovementioned datasets, we measured the estimated number of clusters, estimated number of noise points, homogeneity (whether the clusters contain only samples belonging to a single class), completeness (whether all the data points members of a given class are elements of the same cluster), V-measure (harmonic mean between homogeneity and completeness), adjusted Rand index (similarity between clusterings obtained by the proposed and random models), and the Silhouette Coefficient (estimates the separation distance between the resulting Figure 2: Three sets of images: (a) indicates the original image, clusters). We ran the DBSCAN algorithm measuring the distance while (b) indicates the images attacked with the Projected between clusters with the Euclidean distance, considering the max- Gradient Descent attack. The subsets I, II, and III indicate (I) imum distance between two samples for one to be considered as in the whole image, (II) cropped image (v1 (considering coordi- the neighborhood of the other to be 0,3. Furthermore, we consid- nates (160, 0, 200, 369))), and cropped image (v2 - (considering ered that at least ten samples in a neighborhood were required for coordinates (160, 50, 200, 319))). a point to be considered as a core point. 5 RESULTS AND ANALYSIS considering a slice of the central part of the image (coordinates (160, 50, 200, 319) - - we name this dataset set "Cropped (v2)"). By com- Model Catboost KMeans Logistic regression paring the original image dataset against those obtained by slicing Original image 0.0167 1.0000 0.0228 the central part, we sought to understand if the models’ predictive Embeddings Cropped (v1) 0.0014 1.0000 0.0003 Cropped (v2) 0.0181 1.0000 0.0213 power increased by looking at a specific area of the image rather Original image 0.0152 1.0000 0.0184 than the whole. SSIM Cropped (v1) 0.0008 1.0000 0.0004 Cropped (v2) 0.0179 1.0000 0.0195 We first trained three machine learning models: Catboost [18] Original image 0.0016 1.0000 0.0030 with Focal Loss [14] (trained over 150 iterations, and considering a Histograms Cropped (v1) 0.0003 1.0000 0.0011 tree depth of ten, while evaluating the performance during training Cropped (v2) 0.0018 1.0000 0.0031 with the logloss metric), Logistic Regression (the dataset was scaled between zero and one, considering the train set, and transformed to Table 1: Results obtained across classification experiments. ensure zero mean and unit variance), and KMeans (the dataset was We measure models’ performance with Eq. 1. Best results are transformed to ensure zero mean and unit variance, and the model bolded, second-best are italicized. initiated with random initialization and seeking to generate two clusters). We evaluated our experiments with a ten-fold stratified We present the results obtained in our classification experiments cross-validation ([12, 22]), using one fold for testing and the rest in Table 1. We found the KMeans models achieved perfect discrimi- of the folds to train the model. Furthermore, to avoid overfitting, nation in all cases, while the second-best model was the Logistic we performed a feature selection using the mutual information regression, which had second-best results in all but two cases. Nev- to evaluate the most relevant ones and select the top K features, √ ertheless, the Logistic regression and the Catboost models achieved with 𝐾 = 𝑁 , considering 𝑁 to be equal to the number of data a low discriminative power, almost unable to distinguish between instances in the train set [10]. Finally, we measured our models’ tampered and non-tampered images. Regarding the features, we performance with a custom metric (𝐷𝑃 ) that summarizes 𝐴𝑈 𝐶 𝑅𝑂𝐶 found that the best average performance was obtained when train- the discriminative power as computed from the area under the ing the models on the Cropped (v2) dataset, followed by those receiver operating characteristic curve (AUC ROC, see [4]) (see trained on the whole images. Eq. 1). The metric ranges from zero (no discriminative power) to When running the DBSCAN algorithm (see results in Table 2), one (perfect discriminative power) and it preserves the AUC ROC we found the best results were obtained considering the SSIM mea- desirable properties of being threshold independent and invariant sure. Furthermore, using the SSIM issued excellent results in all to a priori class probabilities. cases. The best ones were obtained considering the Cropped (v1) dataset, while the second-best was achieved with the Cropped (v2) dataset. Using the SSIM only, the DBSCAN algorithm was able to 𝐷 𝑃 = 2 · |(0.5 − 𝐴𝑈 𝐶𝑅𝑂𝐶)| (1) 𝐴𝑈 𝐶 𝑂𝐶 𝑅 correctly group the instances into two groups and misclassified at most a single instance. However, the performance achieved either Based on the good results obtained in the clustering setting, we with embeddings or histograms was not satisfactory. When consid- decided to conduct additional experiments, running the DBSCAN ering histogram features, the DBSCAN algorithm was not able to algorithm [6] over all existing data. The advantage of such an algo- discriminate between instances, creating a single cluster. On the rithm is that it can estimate the clusters with no prior information other hand, when considering embeddings, DBSCAN created three regarding the number of expected clusters. Therefore, if working clusters that issued a bad performance, considering most of the 138 SiKDD ’22, October, 2022, Ljubljana, Slovenia Rožanec et al. Embeddings SSIM Histograms Original image Cropped (v1) Cropped (v2) Original image Cropped (v1) Cropped (v2) Original image Cropped (v1) Cropped (v2) Number of clusters 3 1 1 2 2 2 1 1 1 Number of noise points 1010 794 887 1 0 1 621 603 606 Homogeneity 0.1770 0.4550 0.3170 1.0000 1.0000 1.0000 0.8550 0.9290 0.9150 Completeness 0.2090 0.4940 0.3860 0.9910 1.0000 0.9910 0.8560 0.9290 0.9150 V-measure 0.1920 0.4740 0.3480 0.9960 1.0000 0.9960 0.8550 0.9290 0.9150 Adjusted Rand index 0.0710 0.4350 0.2540 0.9980 1.0000 0.9980 0.9020 0.9600 0.9500 Silhouette coefficient 0.0750 0.4310 0.2660 0.8980 0.9590 0.9070 0.8330 0.8970 0.8800 Table 2: Results obtained across clustering experiments. Best ones are bolded, second-best are italicized. points to be noisy. We, therefore, conclude that the only promising Processing (ICIP). IEEE, 1241–1245. results were those obtained considering the SSIM. Nevertheless, we [6] Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al. 1996. 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In 2020 IEEE International Conference on Image 139 Addressing climate change preparedness from a smart water perspective Alenka Guček *, Joao Pita Costa ** ***, M.Besher Massri * ** *******, João Santos Costa *, Maurizio Rossi ****, Ignacio Casals del Busto *****, Iulian Mocanu ****** * Institute Jozef Stefan, Slovenia, ** IRCAI, Slovenia, *** Quintelligence, Slovenia, **** Ville de Carouge, Switzerland, ***** Aguas de Alicante, Spain, ****** Apa Braila, Romania, ******* Jozef Stefan International Postgraduate School ABSTRACT economy through green technology over a new framework to understand and position water resource management in the Observing the world on a global scale can help us understand context of the challenges of tomorrow [1]. In the context of better the role of water and water resource management the NAIADES project [3] we repurpose and customize the utilities in a climate change context that engage us all. The NAIADES Water Observatory, adding a measurements usage of machine learning algorithms on open data dimension to its text mining capabilities to allow for forecasts measurements and statistical indicators can help us on, e.g., water level and temperature to complete the understand the behavioral changes in seasons and better perspective on the impact of climate change for the prepare. These are complemented by powerful text mining preparedness both of water management utilities and users algorithms that mine worldwide news, social media, as in, e.g., smart agriculture. This will improve the climate published research and patented innovation towards best change preparedness of water resource management practices from success stories. In this paper, we propose a facilities and local authorities in a global context, in particular data-driven global observatory that puts together the in European regions where water scarcity or extreme different perspectives of media, science, statistics and sensing weather events are predicted. The water-related climate over heterogeneous data sources and text mining algorithms. change topics that we are already addressing include, e.g., We also discuss the implementation of this global water reuse, wastewater management, saline intrusion and observatory in the context of epidemic intelligence, groundwater contamination. monitoring the impact of climate change, and the value of this In this paper we will discuss our contribution to this cause, global solution in local contexts and priorities. through the NAIADES Water Observatory (accessible at naiades.ijs.si) [12], focusing on water-related aspects, allowing the user to explore a combination of perspectives CCS CONCEPTS offered over layers of information sourced in statistics, • Real-time systems • Data management systems • Life and historical measurements, multilingual news and social media medical science to published science, weather models and indicators. It is also being used in the context of extreme weather events to analyze worldwide trends and best practices in water topics like, e.g., floods, landslide, and contamination [9], building KEYWORDS Climate Change Preparedness, Data-driven business intelligence from the available open data in Decision-making, Water Resource Management, Smart Water, combination with data streams [11]. Observatory, Water Digital Twin, Deep Learning, Text Mining, The NAIADES Water Observatory is not only contributing to Interactive Data Visualization the improvement of European sustainability in water-related activities and business intelligence but it is also providing an active role to local actors in improving together with 1 Introduction municipalities and water resource management utilities the efficient use of resources [13]. This local perspective is In the present decade, Climate Change has become positioned especially important for providing information at the local as one of the world priorities, a global problem with great granularity, which enables communities or municipalities to socio-economic impact. It has been in the focus of European build solutions that are relevant for their specific cases. and Worldwide strategies, rapidly changing priorities towards sustainability and environmental efficiency, transversely to most domains of action. The European Commission’s Green Deal [5] is a good example of this, aiming for a climate neutral Europe in 2050, and boosting the 140 SIKDD’22, October 2022, Ljubljana, Slovenia A.Guček et al. Figure 2: The weather across seasons over the past 20 Figure 1: Long‐term forecast of 10 years (average per years distinguished by seasons, exhibiting high year) built on 20 years of data to understand the temperature periods earlier in the year. behavior of air temperature, water levels and temperature and the consequent changes within seasons. To further explore the relations of multivariate timeseries data, we have developed the State analysis tool [14]. With this technology we automatically abstract data as states of the 2 Understanding behaviors from data Markov chain and transitions between them. This allows for In the era of Big Data where technologies and sensors are ingestion of large datasets, and due to hierarchical clustering every day cheaper and more efficient, a wide range of useful the data can be observed on several levels. This tool works especially well for observing long term behavior and exposing measurements is available and can be used to forecast recurrent patterns. In the context of climate change weather and water resource behaviors and to identify preparedness, the aim was to better understand the reality of environmental trends with local granularity. the seasons as defined by the weather parameters as well as With the motivation to grasp a realistic perspective on the the water level and temperature over the past 20 years. impact of climate change in the region of Carouge, Depicted in Figure 3 are the transitions between seven states Switzerland, we obtained 20 years of water levels and water we can already depict in the municipality of Carouge, temperature data (sourced by Meteoswiss Data Portal Switzerland and the surrounding area. Five of those states IDAWEB), and we were able to build a 10-year forecast that correspond to a passage between Spring-Summer and allows us to see a signal of the global trend. Summer-Autumn, and to Summer itself, characterized by the For this aim, we have developed a Long Short Term Memory states indicating a high water temperature. With the impact of climate change in redefining seasons this tool can help to (LSTM) neural network, which is a type of Recurrent Neural plan ahead, having in mind the granularity of the data that can Network, widely used for predicting sequential data. In order be customized to predefined geographic regions where to optimize the performance and accuracy of the LSTM, we relevant water resources are located. used some results from Differential Geometry and Chaos Theory such as Takens’ Embedding Theorem, Shannon Entropy, Conditional Shannon Entropy, Markov Chains, etc. This theoretical support was key for obtaining the optimal number of timesteps [4] and to produce a long-term forecast aiming to observe the weather behavior across the historical data collected and a perspective on the future seasons based on the derived prediction, represented by the three parameters - temperature, humidity and rainfall - or the water levels in rivers, lakes and basins in the area determined by the geolocation provided by the NAIADES use cases. The time series of historical data in Figure 1 indicates that already the air temperature yearly averages are increasing, and this increase is predicted also for the next 10 years. Comparing our model with the Meteoswiss model for the area, the differences were minimal. To emphasize the changes throughout the year, we added a per year visualization (Figure 2), where one can compare the seasonal trends for the Figure 3: The analysis of the impact of climate change on local weather and water parameters. water levels and temperature across seasons using Markov chains 141 Addressing climate change preparedness from a smart water SIKDD’22, October 2022, Ljubljana, Slovenia perspective 3 Enrichment with local indicators To better understand the comparative progress of each Water is fundamental to all human activity and ecosystem region on the selected water-related topics, we also enable health, and is a topic of rising awareness in the context of the representation of the time-series curves (see Figure 5) to climate change. Water resource management is central to identify transitions, peaks and other behaviors (per those concerns, with the industry accounting for over 19% of parameter in analysis) that are otherwise not seen in the global water withdrawal, and agricultural supply chains are bubble chart animation. responsible for 70% of water stress [10]. In 2015 the UN established "clean water and sanitation for all" as one of the 17 Sustainable Development Goals, aiming for eight targets to be achieved by 2030 [2]. To exploit the functionality for the customization at the level of local regional providers, news monitoring, and exploration of scientific research can be customized to observed problems, e.g., groundwater contamination. Moreover, ingestion of local indicators can be customized also. These agencies (e.g. Aguas de Alicante) are collecting data on their water resource management services to improve the customer satisfaction and optimize their system, aiming for a smart water [6] approach for the optimization of resources and means, often deploying intelligent systems close to the Figure 5: The curves comparing regional indicators on idea of a water digital twin [7]. water topics (as, e.g., reused water in Spain) Together with the municipality of Carouge, Switzerland, and 4 Knowledge extracted from news, social with the water management utilities of Alicante, Spain, and media and scientific research Braila, Romania, we have collected open data from national data portals and environmental agencies with a regional The NAIADES Water Observatory also allows for a news granularity to be able to assess the comparative progress of monitoring perspective with global and local coverage on regions through the visual data representation of indicators topics like, e.g., water scarcity and water quality. It is (see Figure 4). Through this interactive data visualization we particularly relevant in the surrounding regions of the water can investigate the progress on a variety of topics (with three resource management agencies, but also at a worldwide level simultaneous parameters represented over a bubble chart) recurring to its multilingual capacity to access success stories that are much relevant to the analysis of climate change, and best practices form similar scenarios happening including water availability, reused and treated water, or worldwide. This is based on the Event Registry news engine water usage by populations and industry. With the [8] that collects over 300 thousand news articles daily in over appropriate combination of variables in comparison, the user 60 languages. In the past 3 months we were able to capture can identify the most efficient regions over the country. almost 33 thousand articles relating both with water and with the climate crisis, 1500 of them happening in Spain and relating to concepts such as, e.g., draught, wildfire heat wave, irrigation and extreme weather. Figure 4: The comparison of indicators in the Spanish regions across time 142 SIKDD’22, October 2022, Ljubljana, Slovenia A.Guček et al. Although the predictions are in accordance with IPCC’s and Meteoswiss forecasting, this preliminary work needs to be extended with ingesting several other data variables and compared to the existing widely used models to bring more accurate insight specially for the weather data, but also the water-relevant resources. ACKNOWLEDGMENTS We thank the support of the European Commission on the H2020 NAIADES project (GA nr. 820985). Figure 6: The combined perspective of multilingual news, social media and scientific research on water scarcity and REFERENCES extreme weather aiming to identify best practices and success stories [1] A. Akhmouch, C. Delphine and P. G. Delphine Clavreul. Introducing the OECD principles on water governance. Water International, 43: 5–12, 2018 This global system is also capturing the filtered Twitter feed [2] V. Blazhevska. United Nations launches framework to speed up progress on 10% of the signal, to identify posts related to heat wave on water and sanitation goal. United Nations Sustainable Development, and drought (see Figure 6). 2020 [3] CORDIS, "NAIADES Project". [Online]. Available: https://cordis.europa.eu/project/id/820985 [Accessed 1 9 2020]. The scientific research on climate change topics can bring an [4] Costa J., Kenda K., Pita Costa J. (2021). Entropy for Time Series Forecasting. In: Slovenian Data Mining and Data. 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Understanding the seasonality changes and forecasting the availability of resources at the local levels is therefore crucial to enable relevant adaptation at the correct granularity. 143 SciKit Learn vs Dask vs Apache Spark Benchmarking on the EMINST Dataset Filip Zevnik, Din Music, Carolina Fortuna, Gregor Cerar Department of Communication Systems, Jozef Stefan Institute Ljubljana, Slovenia zevnikfilip@gmail.com Abstract—As datasets for machine learning tasks can become [4] and on various image processing and learning scenarios very large, more consideration to memory and computing re- [5]–[7]. The work in [7] is the closest to this one, however source usage has to be given. As a result, several libraries for they focused on evaluating the tradeoffs in parellelizing feature parallel processing that improve RAM utilization and speed up extraction and clustering while this work focuses on evaluating computations by parallelizing ML jobs have emerged. While SciKit Learn is the typical go to library for practitioners, Dask data loading and merging and subsequent classification. is a parallel computing library that can be used with SciKit In this paper, we benchmark the three solutions for devel- and Apache Spark is an analytics engine for large-scale data oping ML pipelines with respect to data merging and loading processing that includes some machine learning techniques. In and subsequently for training and predicting on the extended this paper, we benchmark the three solutions for developing ML pipelines with respect to data merging and loading and MNIST (eMNIST) dataset under Linux and Windows OS. Our subsequently for training and predicting on the extended MNIST results show that Linux is the better option for all of the (eMNIST) dataset under Linux and Windows OS. Our results benchmarks. For low amounts of data plain SciKit learn is show that Linux is the better option for all of the benchmarks. the best option for machine learning, but for more samples, we For low amounts of data plain SciKit learn is the best option would choose Apache Spark. On the other hand, when it comes for machine learning, but for more samples, we would choose Apache Spark. On the other hand, when it comes to dataframe to dataframe manipulation Spark is behind Dask, and Dask manipulation Dask beats a normal pandas import and merge. beats a normal pandas import and merge. The contribution of Index Terms—Apache Spark, Dask, machine learning, Pandas, this paper is the benchmarking of three ML libraries across import various data sizes and two operating systems on two parts of the ML model development pipeline. I. INTRODUCTION The remainder of the paper is structured as follows. Section II discusses related work. Section III presents the methodology As datasets for machine learning tasks can become very used in the benchmarking. Section IV evaluates the compari- large, more consideration to memory and computing resource son. Finally, Section V presents our conclusions. usage has to be given. As a result, several libraries for parallel processing that improve RAM utilization and speed up II. RELATED WORK computations by parallelizing ML jobs have emerged. While Chintapalli et al. (2016) [8] compared streaming platforms SciKit Learn [1] is the typical go to library for practitioners, Flink, Storm and Spark. The paper focuses on real-world Dask [2] is a parallel computing library that can be used streaming scenarios using ads and ad campaigns. Each strem- with SciKit to improve memory and CPU utilization. Dask ing platform was used to build a pipeline that identifies improves memory utilization by not immediately loading all relevant events, which were sources from Kafka. In addition, the data, but only pointing to it. Only part of the data is loaded Redis was used for storing windowed count of relevant events on a per need basis. It also enables using all available cores on per campaign. The test system contained 40 nodes, where each a system to train a model. Apache Spark is an analytics engine node contained 2 CPUs with 8 cores and 24GB of RAM. All written in Java and Scala for processing large-scale data that nodes were interconnected using a gigabit ethernet connection. incorporates some machine learning techniques and is tightly The experiment encompassed Kafka producing events at set integrated with the Spark architecture. rate with 30 minutes interval between each batch was fired. While there are other libraries [3] that enable paralleliza- The results showed that both Flink and Storm were almost tion of ML, when it comes to distributed computing tools equal in terms of event latency, while Spark turned out to be for tabular datasets, Spark and Dask are the most popular the slowest of the three. choices today. Even though Spark is an older, more stable Dugré et al. (2019) [4] compared Dask and Spark on the solution, Dask is part of the vibrant Python ecosystem and both neuroimaging big data pipelines. As neuroimaging requires a technologies excel at parallelization. While the two solutions large amount of images to be processed, Spark and Dask were have been already been benchmarked on big data pipelines in the time of writing the best suited Big Data engines. The This work was funded by the Slovenian Research Agency ARRS under paper compares the technologies with three different pipelines. program P-0016. First is incrementation, second is histogram and the final 144 Fig. 1. Workflow of the Machine learning test example used for benchmarking. one is a BIDS app example (a map-reduce style application). time the data importing and merging process, referred to as All comparisons were done on BigBrain and CoRR datasets, Benchmark 1 in the figure, followed by model training and with sizes of 81GB and 39GB respectively. The authors have evaluation denoted by Benchmark 2. While the time required concluded that all platforms perform very similarly and that to train the model is usually the most important metric because the incrementation of worker nodes is not always the optimal it takes up most of the computation time, importing and solution due to the transfer times and overall overhead. While merging the input data cannot be ignored. As described in all platforms yielded similar results, the Spark is claimed to Algorithm 1, for Benchmark 1, training data was imported and be the fastest out of the three platforms. then merged. For SciKit Learn dataframes were used all along Nguyen et al. (2019) [6] evaluated SciDB, Myria, Spark, and no parallelization was used while for Dask and Spark Dask and TensorFlow to figure out which system is best suited parallelization was turned on. for image processing. Similarly to [4], the authors compared the systems using different pipelines. For comparison, the Algorithm 1: Import and merge benchmarking process. authors used 2 datasets, both over 100GB in size. The com- parison reveled that Dask and Spark are comparable in the performacnce as well as the ease of use. Enable parallelization Mehta et al. (2016) [5] presented the satellite data process- Require: data a and data b ing pipeline. The pipeline consists of two steps, a feature Merge the DataFrames extraction step and a clustering step. The baseline pipeline Convert data to a pandas DataFrame used the Caffe deep learning library and SciKit. The improved pipeline used Keras along with Spark and Dask for multi- Algorithm 2: Train/fit and evaluate benchmarking process. node computation. They found that while Spark was the fastest in terms of computational time required per task, Dask used almost half the memory compared to Spark due to Enable parallelization recalculation of the intermediate values. SciKit Learn was not Import and setup data able to complete the task and was excluded from the final train = [80% of the samples], test = [20% of the samples] comparison. It was concluded that Spark is the best performer, Define ML algorithm while Dask is the easiest to use. Fit the data Cheng et al. (2019) [7] presented a comparison of the Predict the samples RADICAL-Pilot, Dask and Spark for image processing. All Evaluate - F1 three systems were tested using watershed and a blob detector algorithms. Each test was split into two parts, a weak scaling As described in Algorithm 2, for Benchmark 2 in Figure algorithm where the amount of data to be processed was 1, an example of machine learning with a decision tree increased alongside the number of nodes, and a strong scaling classifier depicts the workflow of the machine learning test algorithm where the amount of data stayed the same and the example. First, parellelization is enabled for Dask and Spark number of nodes increased. The evaluation showed that Dask and immediately after that the data is imported and modified outperformed Spark on weak scaling, while Spark excelled in accordingly to fit the test scenario. Next, the decision tree the strong scaling part. classifier is trained using various training data size, dividing the data set into a training subset and a test subset. The III. METHODOLOGY training subset represents 80% of the original dataset and for To benchmark the three solutions, namely SciKit learn, the training subset the remaining data is used, representing Dask and Spark, we single out two parts of the end-to-end 20% of the original dataset. Each task is run with 5 different model development process depicted in Figure 1. We first sample sizes, ranging from 50k to 250k samples, with a step of 145 50k samples. Finally, the execution report with the calculation testing Spark on the import and merge benchmark, both Win- times of each task is generated. dows and Linux ran out of memory with two and four workers. To realize these benchmarks1, we used the extended MNIST Swap memory could be used to overcome this shortcoming, or EMNIST dataset2. The data set contains approximately however, the resulting comparison would not be fair because 250k samples of handwritten digits, resulting in total size of the Dask benchmarks didn’t need the swap memory. 516MB. The size of all images is exactly the same, 28 by 28 pixels and each pixel has a value ranging from zero to 255. The dataset is represented in the CSV (Comma Separated Values) format with the first column being the label and the rest of the columns representing 784 pixels. For the benchmarks, different data set sizes, ranging from 50k to 250k samples with a 50k step were generated. In addition, each data set size was tested on Dask and Spark with 1, 2 and 4 workers. Therefore, the programs used to test computation time on Windows and Linux operating systems have the same complexity. All tests were performed on equivalent Windows and Linux virtual machines running on the 6 CPU core machine with 10 GB of RAM. IV. RESULTS In this section we provide the results of the benchmarks Fig. 2. Benchmark results of import and merge times at 100k samples: raw data to Pandas. collected using the methodology described in Section III. A. Import and merge First, we present in Figure 2 the import and merge times for 100k samples on Linux without parallelization across the the three platforms. In the first bar, it can be seen that importing (i.e. loading the data into memory) takes most of the time with Pandas. Merging (i.e. concatenation) is relatively negligible while computation is not relevant in this case as after merging it already returns the desired data structure. The total import and merge time is slightly above 4s. From the second bar, it can be seen that importing and merging is negligible with Dask as doesn’t load anything into memory at these steps, rather it prepares only recipes that will be executed during the most time consuming compute phase. During compute, Dask turns a lazy collection into its in-memory equivalent, in our case, the Dask dataframe turns Fig. 3. Benchmark results two operating systems, Dask with import and into a Pandas dataframe. Overall, it can be seen that on a single merge on 250k samples. node, Dask is comparable to Pandas, with a total import and merge time slightly below 4s. B. Machine learning Finally, from the last bar, it can be seen that Spark import Figure 4 shows the comparison of computation time be- and merge are very fast and efficient, taking below 2s. How- tween Dask, Spark, and SciKit on the Windows operating ever, when transforming the internal data structure of Spark system for different dataset sizes. Each column in the figure into pandas (i.e. during the compute phase in this case) is very represents the average computation time of 5 test runs. The time consuming. We added this step so that the final outcome results show that Dask and Spark are almost equivalent when is consistent with the other two (i.e. Pandas data structure), the input dataset size is around 150k samples. Dask performs however in the end-to-end ML pipeline the ML algorithm will better on smaller datasets, while Spark’s performance is best be trained directly using Spark’s internal data structure. on larger datasets. Interestingly, SciKit outperforms both Dask Figure 3 shows how the import and merge times fare as a and Spark on all dataset sizes, although it is not able to function of worker nodes for Dask across Linux and Windows. parallelize tasks. This is most likely because of the transfer As expected, a decreasing tendency of the import/merge times times between nodes and the overall overhead of Dask and with the increase of the working nodes can be seen. When Spark. Since the datasets fit completely into the computer’s memory, SciKit has no problems computing them, while Dask 1Scripts for the benchmarks, https://github.com/sensorlab/parMLBenchmarks 2EMINST dataset - https://www.kaggle.com/crawford/emnist (accessed: and Spark only cause unnecessary overhead. However, Dask 30.07.2022) and Spark are meant for large clusters with hundreds or even 146 thousands of nodes, while SciKit is meant for computations The machine learning benchmark measured the time to cast on a single computer. all columns into smaller data types. It seems that Dask has a dedicated function to cast all of the columns of a Dask dataframe at once whereas with the Spark function you have to cast each column one by one. The Dask casting was faster (0.06s) than Sparks (7.2s). V. CONCLUSIONS In this paper we benchmarked two parallel computing technologies, Dask and Apache Spark, against each other and against the single node SciKit Learn. The benchmarks were computed on the EMNIST dataset for various subsets from 50k to 250k samples on different operating systems and various degrees of parallelization. The results show a slight advantage on running the training pipeline on Linux rather than on Windows. Dask is seen as superior in dataframe manipulation while Apache Spark has a superior end-to-end Fig. 4. Computational time for different dataset sizes on Windows operating processing performance on larger datasets with comparable system. final F1 scores. Figure 5 shows the results of the same experiment per- ACKNOWLEDGMENTS formed on the Linux operating system. Compared to the Figure This work was funded in part by the Slovenian Research 4, the results are very similar, with only difference that on Agency under the grant P2-0016. Linux operating system Dask performs better then Spark even when input data set contains 150k samples. REFERENCES Table I shows the F1 scores. An F1 score is the harmonic [1] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, mean (alternative metric for the arithmetic mean) of precision O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, et al., and recall. The precision gives information on how many of “Scikit-learn: Machine learning in python,” the Journal of machine Learning research, vol. 12, pp. 2825–2830, 2011. the predicted samples that have been predicted as positive [2] M. Rocklin, “Dask: Parallel computation with blocked algorithms and are correct. The recall gives information on how many of all task scheduling,” in Proceedings of the 14th python in science conference, positive samples the model managed to find. vol. 130, p. 136, Citeseer, 2015. [3] S. Celis and D. R. Musicant, “Weka-parallel: machine learning in paral- lel,” in Carleton College, CS TR, Citeseer, 2002. [4] M. Dugré, V. Hayot-Sasson, and T. Glatard, “A performance comparison of dask and apache spark for data-intensive neuroimaging pipelines,” in 2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), pp. 40–49, 2019. [5] P. Mehta, S. Dorkenwald, D. Zhao, T. Kaftan, A. Cheung, M. Balazinska, A. Rokem, A. Connolly, J. Vanderplas, and Y. AlSayyad, “Comparative evaluation of big-data systems on scientific image analytics workloads,” vol. 10, p. 1226–1237, VLDB Endowment, aug 2017. [6] M. H. Nguyen, J. Li, D. Crawl, J. Block, and I. Altintas, “Scaling deep learning-based analysis of high-resolution satellite imagery with distributed processing,” in 2019 IEEE International Conference on Big Data (Big Data), pp. 5437–5443, 2019. [7] M. T. S. J. William Cheng, Ioannis Paraskevakos, “Image processing using task parallel and data parallel frameworks,” pp. 1–7, 2019. [8] S. Chintapalli, D. Dagit, B. Evans, R. Farivar, T. Graves, M. Holderbaugh, Z. Liu, K. Nusbaum, K. Patil, and B. J. Peng, “Benchmarking streaming computation engines: Storm, flink and spark streaming,” 2016. Fig. 5. Computational time for different dataset sizes on Linux operating system. TABLE I TABLE OF F1 SCORES FOR WINDOWS BENCHMARKS FOR VARIOUS SAMPLE SIZES (SIMILAR FOR LINUX). Number of samples (x1000) 50 100 150 200 250 Spark 0.71 0.73 0.73 0.71 0.71 Dask 0.71 0.72 0.73 0.71 0.70 Scikit 0.70 0.71 0.70 0.71 0.73 147 An Efficient Implementation of Hubness-Aware Weighting Using Cython Krisztian Buza buza@biointelligence.hu BioIntelligence Group, Department of Mathematics-Informatics Sapientia Hungarian University of Transylvania Targu Mures, Romania ABSTRACT In case of the aforementioned hubness-aware classifiers, the Hubness-aware classifiers are recent variants of computationally most expensive step of the training is to deter- 𝑘 -nearest neighbor. When training hubness-aware classifiers, the computationally most mine the hubness scores of training instances, i.e., how frequently expensive step is the calculation of hubness scores. We show that they appear as (bad) nearest neighbors of other instances. In this this step can be sped up by an order of magnitude or even more if paper, we address this issue by a Cython-based implementation. it is implemented in Cython instead of Python while the accuracy Cython [1] aims to combine the advantages of Python (rapid proto- is the same in both cases. typing and clarity thanks to concise code) with the efficiency of C. In particular, we implement the computation of hubness scores in KEYWORDS Cython. Compared with a standard implementation in Python, we observed up to 25 times speedup on the Spambase dataset2 from nearest neighbor, hubs, cython the UCI repository (and the speedup is likely to be even more in case of larger datasets). 1 INTRODUCTION Nearest neighbor classifiers are simple, intuitive and popular, there 2 BACKGROUND: HUBNESS-AWARE are theoretical results about their accuracy and error bounds [6]. WEIGHTING However, nearest neighbors are affected by bad hubs. An instance We say that an instance ′ is called a bad hub, if it appears surprisingly frequently as nearest 𝑥 is a bad neighbor of another instance 𝑥 if (i) ′ and (ii) their class neighbor of other instances, but its class label is different from 𝑥 is one of the 𝑘 -nearest neighbors of 𝑥 labels are different. In case of hubness-aware weighting [9], first we the labels of those other instances. Bad hubs were shown to be determine how frequently each instance responsible for a surprisingly large fraction of the total classification 𝑥 appears as bad neighbor of other instances. This is denoted as ( error [10]. 𝐵 𝑁 𝑥 ). Subsequently, the 𝑘 normalized bad hubness score ( In order to reduce the detrimental effect of bad hubs, hubness- ℎ 𝑥 ) of each instance 𝑥 is calculated 𝑏 as follows: aware classifiers have been introduced, such as Hubness-Weighted 𝐵 𝑁 (𝑥 ) − 𝜇 (𝐵𝑁 ) 𝑘 𝑘 𝑘 -Nearest Neighbor (HWKNN) [9], Naive Hubness Bayesian Near- ℎ (𝑥 ) = (1) 𝑏 𝜎 (𝐵𝑁 ) est Neighbor (NHBNN) [16] and Hubness-based Fuzzy Nearest 𝑘 Neighbor (HFNN) [14]. Hubness has also been studied in context of where 𝜇 (𝐵𝑁 ) and 𝜎 (𝐵𝑁 ) denote the mean and standard devia- 𝑘 𝑘 collaborative filtering [8], regression [3], clustering [15], instance tion of the 𝐵𝑁 (𝑥) values over all instances of the training data. 𝑘 selection and feature selection [13]. Recently, hubness-aware en- HWKNN performs weighted 𝑘-nearest neighbor classification, the −ℎ (𝑥 ) 𝑏 sembles have been proposed [17] and used for the classification of weight of each training instance is 𝑤 (𝑥) = 𝑒 . For a detailed breast cancer subtypes [12]. illustration of HWKNN we refer to [13]. Other prominent applications of hubness-aware methods include music recommendation [7], time series classification [11], drug- 3 CYTHON-BASED IMPLEMENTATION OF target prediction [4] and classification of gene expression data [2]. HUBNESS CALCULATIONS Last, but not least, we mention that even neural networks may Python code is usually run by an interpreter which makes the benefit from hubness-aware weighting [5]. execution relatively slow. Much of the inefficiency originates from Hubness-aware classifiers may be implemented in various pro- dynamic typing: for example, the actual semantic of the ’+’ symbol gramming languages, one of the most prominent implementation depends on the types of the operands. It may stand for addition of is probably the Java-based HubMiner1 library. numbers, concatenation of strings or lists, element-wise addition of arrays, etc. Which of the operations to perform, will be determined 1https://github.com/datapoet/hubminer by the interpreter at execution time. Permission to make digital or hard copies of part or all of this work for personal or The core idea of Cython3 is to annotate variables according to classroom use is granted without fee provided that copies are not made or distributed their types and to compile the resulting code into C which will for profit or commercial advantage and that copies bear this notice and the full citation further be compiled into binary code for efficient execution. In on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). case of computationally expensive functions, this may results in Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 2https://archive.ics.uci.edu/ml/datasets/spambase 3https://cython.org/ 148 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia K. Buza the training instances have to be determined. Thus the resulting overall complexity is quadratic. We note that, both in case of Cython and Python, indexing tech- niques may be used to speed up the determination of the nearest neighbors. However, we omitted indexing in our implementation for simplicity. 4 DISCUSSION In order to calculate distances effectively, we used pairwise dis- tances from scikit-learn in our experiment. However, in case of large datasets, it may be necessary to calculate distances on the fly, as the distance matrix may be too large to be stored in RAM. In such cases, it may be worth considering to implement the distance calculations in Cython as well. In our previous works, we observed that the calculation of dynamic time warping distance was several Figure 1: Runtime (in second, vertical axis) of hubness score orders of magnitudes faster when we implemented it in Cython calculation in case of Python-based (dashed line with ’x’) and instead of Python. Cython-based (solid line with bullets) implementations for In case of very large datasets, straight forward calculation of various number of instances (horizontal axis). hubness scores may be infeasible due to its quadratic complexity even if the calculations are implemented in Cython. In such cases, the aforementioned indexing techniques and/or calculation of ap- several orders of magnitude speedup. At the same time, functions proximate hubness scores (e.g. using a random subset of the data) implemented in Cython can be called from Python code just like may be necessary. Python functions. As future work, we plan an exhaustive evaluation of both im- We implemented the calculation of hubness scores both in Python plementations with respect to various datasets with different sizes and Cython, and made the code available in our github repository: and number of features. https://github.com/kr7/cython . We evaluated both implementations on the Spambase dataset ACKNOWLEDGEMENT from the UCI repository. The dataset contains 4601 instances and The author thanks to the Reviewers for their insightful comments 57 features (without the class label). Each instance corresponds to and suggestions. an e-mail. For each e-mail, the same features were extracted. The associated classification task is to decide whether the e-mail is spam REFERENCES or not. [1] Stefan Behnel, Robert Bradshaw, Craig Citro, Lisandro Dalcin, Dag Sverre Sel- We used 100 instances as test data and 4500 instances as training jebotn, and Kurt Smith. 2010. Cython: The best of both worlds. 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Journal of Intelligent & Fuzzy Systems 39, 1 (2020), 133–144. 150 Semantic Similarity of Parliamentary Speech using BERT Language Models & fastText Word Embeddings Katja Meden Department of Knowledge Technologies E8, Jožef Stefan Institute katja.meden@ijs.si ABSTRACT We measured sentence similarity with four BERT-based language models (Language agnostic BERT Sentence Encoder - The main objective of this paper is to present the work done on LaBSE model [7], Sentence-LaBSE [8], Sentence-BERT [14], comparing the two methods for measuring semantic similarity of multilingual BERT – mBERT [1]) and compared the scores of parliamentary speech between coalition and opposition regarding most similar and least similar sentences. the adoption of the first COVID-19 epidemic response package. To facilitate the intended scope of our initial research, i.e., We first measured sentence similarity using four BERT-based researching similarity of full-text parliamentary speech, we used language models (Language agnostic BERT Sentence Encoder - fastText [5] and presented results using descriptive analysis to LaBSE model, Sentence-LaBSE, Sentence-BERT, multilingual gain additional insight into the characteristics of coalition and BERT - mBERT) and compared the results amongst them. Using opposition parliamentary speech. Lastly, we highlighted some of the word embedding method, fastText, we then measured the the advantages and disadvantages of each method for measuring semantic similarity of full-text parliamentary speech and semantic similarity of parliamentary speech. presented the results using descriptive analysis. Lastly, we The paper is structured as follows: Section 2 contains an compared the usage of both methods and highlighted some of the overview of the related work on word embeddings and language advantages and disadvantages of each method for measuring the models. Section 3 presents the methodology and we describe the semantic similarity of parliamentary speech. experiment setting in Section 4. The experiment results are found in Section 5. Finally, we conclude the paper and provide ideas KEYWORDS for future work in Section 6. parliamentary speech, semantic similarity, sentence similarity, BERT language models, fastText 2 RELATED WORK Two blocks of texts are considered similar if they contain the 1 INTRODUCTION same words or characters. Techniques like Bag of Words (BoW), “National parliamentary data is a verified communication Term Frequency - Inverse Document Frequency (TF-IDF) can be channel between the elected political representatives and society used to represent text as real value vectors to aid calculation of members in any democracy. It needs to be made accessible and Semantic Textual Similarity (STS) [3]. STS is defined as the comprehensive - especially in times of a global crisis.” [13] In measure of semantic equivalence between two blocks of text and parliamentary discourse, politicians expound their beliefs and usually give a ranking or percentage of similarity between texts, ideas through argumentation and to persuade the audience, they rather than a binary decision as similar or not similar [3]. Word highlight some aspect of an issue. If we are to understand the role embeddings are one of the methods developed to aid in of parliamentary discourse practices, we need to explore the measuring semantic similarity. They provide vector recurring linguistic patterns and rhetorical strategies used by representations of words where vectors retain the underlying MPs that help to reveal their ideological commitments, hidden linguistic relationship between the similarities of the words. agendas, and argumentation tactics [11]. One of the ways to Word embeddings consist of two types: static and contextualized study the aforementioned linguistic patterns can be done by word embeddings. With static word embeddings, words will researching similarities of parliamentary speeches using different always have the same representation, regardless of the context methods for measuring semantic similarity of text. where it occurs, while with contextualized word embedding, The aim of this paper is to present the work done on representation depends on the context of where that word occurs comparing the two methods for measuring semantic similarity of – meaning, that the same word in different contexts can have parliamentary speech between coalition and opposition regarding different representations. the adoption of the first COVID-19 epidemic response package. FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers [5]. It i s a representative of the static word embedding technique, 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 where a vector representation is associated to each character n- for profit or commercial advantage and that copies bear this notice and the full gram; words being represented as the sum of these citation on the first page. Copyrights for third-party components of this work must representations [2]. The fundamental problem of word be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia embeddings is that they generate the same embedding for the © 2022 Copyright held by the owner/author(s). same word in different contexts, failing to capture polysemy [4]. 151 Language models are contextualized word representations We used the same settings for the second part of the experiment that aim at capturing word semantics in different contexts to (comparing sentence similarity with the four BERT-based address the issue of polysemy and the context of words [4]. models) with one difference. Since all BERT-based models BERT, or Bidirectional Encoder Representations from support max_lenght input in the size 512 tokens, we decided to Transformer, is a language model, designed to pre-train deep filter out sentences that refer explicitly to the response package bidirectional representations from an unlabeled text by jointly (keyword for selection being zakon). To facilitate the conditioning on both left and right context in all layers [6]. BERT visualisations and balance out our dataset, we randomly chose 20 word representations are therefore contextual sentences for each group (coalition/opposition). 3.3 Experiment settings 3 METHODOLOGY As mentioned, BERT-based models have restrictions on the 3.1 Dataset maximum length of input documents. For most, this is 512 tokens, and in the case of Sentence-BERT, this restriction is even Dataset contains 230 documents (speeches) from the more severe (128 word tokens). Most speeches in the dataset are Extraordinary Session 33 from the corpora of the Slovenian longer than the maximum length – this limitation did not allow parliamentary debates (ParlaMint-SI) [9] from 2014 to mid-2020, us to conclude semantic similarity measurement on full linguistically annotated and represented in the CoNNL-U format parliamentary speech. The first part of the experiment therefore (which include POS, lemmatized and NER tags). We chose an focuses on sentence similarity. From previously described extraordinary session in a time of crisis for two reasons: firstly, BERT-based models, three of the models were fine-tuned for regular sessions deal with multiple problems (such as MP sentence similarity tasks: Sentence-LaBSE [7], LaBSE [8], questions), which makes a comparison between speeches mBERT [1] and Sentence-BERT [14]. For easier comparison, we difficult. Similarly, we chose only one specific theme (the used mean pooling and cosine distance to measure the similarity. adoption of the first epidemic response package), which helped To achieve the intended scope of our initial research in the initial analysis and comparison of documents. (researching the semantic similarity of parliamentary speech), we used the fastText-based Orange widget Document embedding (using mean as the aggregation method) to embed our documents 3.2 Data analysis and pre-processing and calculate cosine similarity to achieve comparison between For the initial data analysis, we used the Orange data-mining tool coalition and opposition parliamentary speech. With these two [12] that helped us with the data understanding and initial dataset experiments, we can compare measuring semantic similarity pre-processing. with language models to the word embedding method (fastText). For full speech measuring with fastText we removed This comparison would be better with Longformer language speeches by Chairperson to avoid adding noise to the dataset in model (which can take up to around 1000+ word tokens as the form of procedural speech that would make measuring max_input) as we could compare methods for measuring semantic similarities almost impossible. We also removed semantic similarity of full-text documents (speeches), but as of Slovene stopwords and manually added a list of four additional time of writing this paper, Longformer [10] does not yet support stopwords: hvala, danes, l epa and beseda, which excluded the Slovene language. very common phrase Hvala za besedo (eng. Thank you for the word) and its variations. Some of the documents were missing the party_status labels (values: coalition and opposition). The 4 RESULTS missing values (17 documents) were thus removed from the dataset. The pre-process gave us a total of 97 documents, 4.1 Results of the sentence similarity measure presented in Table 1. Looking at the distributions of the speeches with BERT-based models in the session, almost 1/3 of the speeches belongs to the As stated previously, we used four different BERT-based models opposition. Both coalition and opposition consists of four to measure semantic similarity of 40 sentences (20 sentences for political parties: LMŠ, Levica, SAB and SD are part of the each group - coalition and opposition) and visualized the results opposition, all of mostly left and centre-left political orientation. using heat maps (example in Figure 1). Initially, we first selected Similarly, the coalition consists of DeSUS, NSi, SDS and SMC well-known BERT-based models that were optimized for political parties1, all mostly right-winged and centre-right parties. Slovene (trilingual model CroSloEngual BERT and monolingual model SloBERTa), that did not produce reliable results - as Table 1: Preprocessed dataset shown in Table 2, CroSloEngual [15] and SloBERTa [16] produce extremely high similarity scores, since, as we later discovered, were not fine-tuned for sentence similarity task. Sample Number of Total documents Coalition 30 (30.93%) 97 Opposition 67 (69.07%) 1 Technically, the opposition consists of 5 political parties, but SNS (Slovenska Nacionalna Stranka) does not have any speeches in the dataset. 152 Table 2: Similarity scores of language models for most 4.2 Results of the document similarity with similar and least similar sentences fastText Model Most similar Least similar For the second part of our experiment, we used fastText for word embedding and measured cosine distance to get semantic Sentence-LaBSE 0.6184 0.1235 similarity score of our documents. Figure 2 shows visualized LaBSE 0.7610 0.3649 results comparing speeches between coalition and opposition mBERT 0.8930 0.5377 speakers: Sentence-BERT 0.6677 -0.0792 CroSloEngual 0.9931 0.9480 SloBERTa 0.9867 0.8899 Figure 2: Document similarity with fastText, visualized using MDS Figure 1: Example of heat map using Sentence-LaBSE Documents (or speeches) are connected closely together – model this could be attributed mostly to the fact that they are addressing the same issue – the adoption of the first epidemic release When comparing the models, it does not surprise that package. The most similar speeches were made by the members Sentence-LaBSE and Sentence-BERT show very similar results of the political party SDS (coalition) and SD (opposition), (see Table 2), as they come from the same family of models and followed closely by SMC and Levica. All speeches are long and thus have similar model architecture (and are both fine-tuned for focus on the topic of the session – the proposed law (most this specific task). What is interesting is the fact that Sentence- speeches include keywords such as “zakon” (law), “zakonski BERT is the only model that produced a negative score for the paket” (law packet), “amandma” (amendment), “ukrepi” least similar sentence (similarity score of -0.0792), while (measures). mBERT model showed the highest similarity scores (outside of Outlier detection analysis showed 8 speeches (7 made by the CroSloEngual and SloBERTa). Some of the highest scored opposition, 1 by coalition), which are all very short and focus sentences showed that speakers from different party statuses tend solely on parliamentary procedures. We also observed some to use similar language patterns, for example: trends in the usage of the words, concatenated from the word “korona”: “koronakriza”, “koronazakon”, “antikoronazakon”, Coalition : “Ob hitrem sprejemanju zakona je potrebno “koronaobveznica”, “koronapomoči”, “protikoronapaket” etc. zagotoviti, da ne bodo spregledane posamezne ranljive skupine (used mostly by the opposition). posameznikov.” In Figure 3, we compared speech between the members of the (Eng. “With the rapid adoption of the law, it is necessary to opposition. The visualization showed a cluster of similar ensure that individual vulnerable groups of individuals are not speeches. Members of Levica seemed to be most vocal during overlooked.") the session (by having more than 50% of all opposition speeches), while also having several similar speeches, with the central sub- Opposition : “Še enkrat, ostaja še cela vrsta ranljivih skupin v topic being proposed amendments to the law and financial zakonu, ki je nenaslovljena.” consequences of it. The least similar speech was made by Violeta (Eng. “Once again, there is a whole range of vulnerable groups Tomić, member of Levica, in regard to the date the epidemic was in the law that remain unaddressed.”) declared. 153 semantic similarity/sentence similarity tasks and thus do not produce accurate results. Limitation on maximum length of input text that most BERT-based models have is probably one of the biggest disadvantages of the language models for semantic similarity measures (this is being alleviated with new emerging language models, such as Longformer, that allow over 1000+ tokens as maximum input length). For sentence similarity task language models from Sentence-BERT family show the most accuracy and are easier to use as standard BERT models (such as mBERT). Even though BERT contextualizes word embeddings (and therefore might produce better results because of it), fastText solved the problem of text-input length and combined with Orange data mining tool allowed us to explore similarities between speeches as we originally intended to do. From the document similarity analysis, we saw that most speeches were relatively connected (similar) to one another. Speeches amongst the members of the opposition were more similar in comparison to the speeches made amongst coalition members. There were a Figure 3: Document similarity with fastText (opposition) few outlier speeches in both opposition and coalition – they were all shorter speeches and less related to the original topic of the In Figure 4, we compared speech between the members of discourse. For future work, some limitations of this research coalition: speeches are less connected; with most similar divided should first be addressed (e.g., comparing language models to among SDS members, closely connected to the SMC, NSI and word embedding techniques on a full-text basis) and repeat the DeSUS members. The common sub-topic to all of the speeches experiments with fine-tuned SloBERTa and CroSloEngual made is the financial crisis as a direct result of the epidemic. Two model on full ParlaMint-SI corpora. of the most far-away speeches belong to the member of DeSUS (Franc Jurša). Both speeches are among the shortest ones in the dataset, with a focus on the topic of pensions and registration of REFERENCES a parliamentary group, and thus are not explicitly connected to [1] BERT multilingual base model (cased): https://huggingface.co/bert-base- the central topic of the discourse. multilingual-cased [2] Bojanowski, Piotr, Grave, Edouard, Joulin, Armand and Mikolov, Tomas. (2017). Enriching word vectors with subword information. In Transactions of the Association for Computational Linguistics, 5, 135- 146. DOI: https://doi.org/10.1162/tacl_a_00051 [3] Chandrasekaran, Dhivya, and Vijay Mago. 2021. Evolution of Semantic Similarity—A Survey. In ACM Computing Surveys, 1-37. [4] David S. Batista. 2018. Language Models and Contextualised Word Embeddings. https://www.davidsbatista.net/blog/2018/12/06/Word_Embeddings/ [5] FastText - Library for efficient text classification and representation learning. https://fasttext.cc/ [6] Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805. 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[16] Ulčar, Matej and Robnik-Šikonja, Marko, 2021, Slovenian RoBERTa Those that were made explicitly with Slovene in mind (such as contextual embeddings model: SloBERTa 2.0, Slovenian language resource repository CLARIN.SI, http://hdl.handle.net/11356/1397 SloBERTa and CroSloEngual BERT) were not fine-tuned for 154 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek D Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume D Kognitonika Cognitonics Urednika / Editors Vladimir A. Fomichov, Olga S. Fomichova http://is.ijs.si 10. oktober 2022 / 10 October 2022 Ljubljana, Slovenia 155 156 FOREWORD / PREDGOVOR Seventh International Conference on Cognitonics - the Science about the Human Being in the Digital World (Cognit-2022) Since October 2009, the international scientific conference on Cognitonics (“Kognitonika” in Slovenian) is a part of the international scientific multiconference INFORMATION SOCIETY (Slovenia, Ljubljana, Jozef Stefan Institute). In the Preface to the Proceedings of the Sixth international conference Cognit-2019, we formulated the following expanded definition of Cognitonics: it is the science about the trajectories of raising the human being to such level of intellectual and spiritual height where the scale of his/her personality becomes proportional to the scale of the digital world. The first objective of Cognitonics, or the Science about the Human Being in the Digital World, is to explicate the distortions in the perception of the world caused by the information society and globalization. The second, principal objective of Cognitonics is to cope with these distortions in different fields by means of elaborating systemic solutions for compensating the negative implications of the kind for the personality and society, in particular, for creating cognitive-cultural preconditions of the harmonic development of the personality in the information society and knowledge society and for ensuring the successful development of national cultures and national languages. The goal of the conference is to combine the efforts of the scholars from numerous scientific fields and educators in order to establish a new synergy aimed at ensuring the harmonic, well- balanced development of the personality, national cultures, and national languages in the forming knowledge society (smart society) and, as a consequence, to compensate a number of broadly observed negative distortions. From the standpoint of educational practice, Cognitonics suggests an answer to the following question: what precious ideas and images accumulated by the mankind, at what age, and in what a way are to be inscribed into the world's conceptual picture of a person in order to harmonize his/her intellectual and spiritually-coloured emotional development and to contribute to the successful development of national cultures and national languages? Cognitonics formulates a new, large-scale goal for the software industry and Web science: to develop a new generation of culture-oriented computer programs and online courses (in the collaboration with educators, linguists, art historians, psychologists) - the computer programs and online courses intended for supporting and developing positively-oriented creativity, cognitive-emotional sphere, the appreciation of the roots of the national cultures, the awareness of the integrity of the cultural space in the information and smart society (knowledge society), and for supporting and developing symbolic information processing and linguistic skills, associative and reasoning abilities of children and university students. Being a relatively young scientific discipline, Cognitonics both is of high social significance just now and has great prospects of the kind. It is due to the fact that it suggests new, deep and constructive ideas, new angles of look and original, effective solutions to a number of socially 157 significant problems emerged in adjacent fields, including education. The examples of such solutions are as follows. During last decade, big international companies, fulfilling the casting of the specialists for vacant positions, have been paying a high attention to the level of emotional intelligence (EI) of the pretenders. Cognitonics suggested a highly effective system of teaching methods aimed at supporting and developing EI of the learners. This system includes, in particular, a many-staged method of early children's socialization in information and knowledge society and a method of developing creativity, figurative thinking, the skill of integrating information from numerous dispersed sources. Cognitonics enriched psychology by means of introducing the notion of Thought-Producing Self and of suggesting the most deep today (on the world level) model of developing conscious control in the childhood: control of thought, emotions, and actions. Art cognitonics - one of the most developed branches of cognitonics - makes a considerable contribution to cultural studies and theory of up-bringing. It develops a complex method of using the works of art for positive development of the child's, adolescent's, and university student's personality. Art cognitonics suggests a new paradigm of delivering lectures on art. Cognitonics is a quickly developing scientific discipline being ready to answer the emerging challenges of time. A new example is given by one of our papers below. It introduces the Method of Cognitive Painting as an effective tool for constructing a positive cognitive-emotional space for children and adolescents under conditions of the COVID-19 pandemic. The Programme Committee accepted for the conference 6 papers from 5 countries: Croatia, Italy, Japan, Russia, Slovenia. The editors would like to thank the authors of the papers for their contributions and the members of the Program Committee for their precious comments ensuring the high quality of the accepted papers and making the reading as well the editing of this volume a rewarding activity. Editors and Programme Presidents / Urednika • Vladimir A. Fomichov • Olga S. Fomichova 158 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Dr. Vladimir A. Fomichov, Co-President (Russia) Dr. Olga S. Fomichova, Co-President (Russia) Dr. Maria Bontila (Greece) Dr. Angela Christofidou (Cyprus) Dr. Paul Craig (PR China) Dr. Vassilis Dagdilelis (Greece) Dr. Joonho Kim (Japan) Dr. Jana Krivec (Slovenia) Dr. Rita Micarelli (Italy) Dr. Ida Panev (Croatia) Dr. Giorgio Pizziolo (Italy) 159 160 Theoretical Foundations and Experience of Six All- Russian Creative Web-based School-contests “Portrait of Your Town” Vladimir A. Fomichov Olga S. Fomichova Department of Intelligent Monitoring Systems, Centre of Social Competences "Dialogue of Sciences", Institute No. 3 “Control Systems, Informatics and State Budget Professional Educational Institution Electric Power Engineering”, “Sparrow Hills”, Moscow, Russia” Moscow Aviation Institute (National Research University), Moscow, Russia olga.s.fomichova@gmail.com vfomichov@gmail.com ABSTRACT It is a delicate opportunity for the child at the age from 7 to 18 years to tell about the beauty and peculiarity of her/his town The paper sets forth the theoretical foundations and experience being for the child the place of living, to feel the own roots, to of six All-Russian creative school-contests (the years 2017 – perceive herself/himself as a link in the chain of generations, to 2022) “Portrait of your town” for children and adolescents at the have a sophisticated look at her/his world and find her/his age from 7 to 18 years. The methodological basis of this school- personal look at the outstanding or usually not noticed facets of contest is the ideas of cognitonics, or the science about the human her/his town - such facets without which, according to her/his being in the digital world. This school-contest emerged as a civic opinion, the complete portrait of the country can't be formed. The initiative of this paper’s authors. The winners of the school- technical support (Web-platform) was provided to our school- contest are awarded by a Letter of Gratitude signed by a senator contest by the Association of Living Cities, supported by the of Russian Federation (RF) in accordance with a subject of RF. Public Chamber of the Russian Parliament. The number of the school-contest winners in 2022 is 518. A The most bright, beautiful thoughts from the compositions of special attention in the paper is given to the tracks “Say thank the winners of the school-contests 2017 - 2022 were presented at you” and “World, nature, universe’s essence (Nature oriented the first and second exhibitions "Country as an Orchestra" and behavior)”. In the year 2022, the school children from 58 subjects the third and fourth exhibitions “Portrait of the country depicted of RF (68% of all RF subjects) participated with the essays in this by children with all their heart” in the Federation Council of school-contest. It is concluded that every-year school-contest Russian Federation (RF) - the upper chamber of the RF “Portrait of your town” can be interpreted as the third Parliament ("it is called "State Douma"). The authors of the implementation of the student-self oriented learning model essays presented (partially) at the first – fourth exhibitions were introduced by the authors several years ago and as smart learning awarded by a Letter of Gratitude signed by a senator (a member environment of a new kind. of the RF Federation Council) in accordance with a region. In the beginning of 2019, the new tracks "Say thank you" and KEYWORDS “World, nature, universe’s essence” (it is a line from the poem Creative school-contest, cognitonics, art cognitonics, smart “When it clears up” by Boris Pasternak) were included into the learning environment, student-self oriented learning model, school-contest "Portrait of your town". The diapason of ages was nature oriented behavior, creativity development, soft skills, considerably expanded: it is from 7 years to 18 years. The transversal skills, personality development, system of emotional- participants are to realize what persons from their native towns imaginative teaching have made a difference in their life, who have influenced them a lot in their choice of future occupation, who has given the model of behavior children would like to emulate. 1 INTRODUCTION The participants of the track "Say thank you" submit the One of the significant social problems in modern Russia is as essays explicating their feeling of gratitude to the persons of the follows. The most gifted and highly motivated students of high kind. Our first working hypothesis was that this track will be able schools enter the leading universities in biggest cities of the to considerably contribute to developing in young people the country (mainly, in Moscow and Saint-Petersburg), receive an sense of belonging to the native town. Then, after receiving an excellent education and never return to their native towns and academic degree in a university, a part of young specialists will villages. A part of them finds jobs in abroad. As a consequence, return to their native region or will regularly do something useful the population of middle and small towns has been diminishing. for their region. In the beginning of 2017, we launched an All-Russian Web- The school-contest "Portrait of your town" has a methodical based creative school-contest for school children "Portrait of provision in the form of five written lectures posted on the Web. your town"; it took place for the sixth time in January - June 2022. These lectures are prepared by the second author of this paper 161 and are oriented at the adult specialists (from a school or a Russian Federation during a festive reception in a region capital library) helping children to prepare the sketches for the school- organized for the winners of the school-contest. contest. This interaction with an adult helps children and It is important that the school-contest contributes to coming adolescents a lot to better explicate their feelings. back to the society of the perception of a bright, beautiful (but Since the year 2017, we have found and successfully non-commercial) thought as a value. implemented two original ways of using modern information and communication technologies for developing a broad spectrum of soft skills in children and adolescents. During last decade it has been broadly realized that education in knowledge society (or smart society) is to pay a particular attention to supporting and developing in the learners the significant, domain independent skills called soft skills [2, 30] or transversal skills [1, 31], first of all, analytical and critical thinking, creativity, out of box thinking, thinking and acting in terms of public good. The significance of creativity perceived by the world leading experts has been quickly increasing. The experts of the World Economic Forum (WEF) in Davos, Switzerland published in [25] the list of top 10 skills for the year 2015 and a forecast of the similar list for the year 2010. It is sufficient to say that the position of creativity shifted from the position No. 10 in 2015 to the position No. 3 in 2020. The forecast of the WEF list – 2020 includes also new skills in comparison with the WEF list 2015: emotional intelligence (the position No. 6) and cognitive flexibility (the position No. 10). Our second working hypothesis was that the school-contest "Portrait of your town" and, in particular, the track "Say thank you" will contribute not only to developing the sense of belonging but also to supporting and developing a number of significant soft skills. The analysis of the submitted best essays shows that the school-contest supports and improves emotional intelligence of the participants and develops such significant transversals (or soft skills) as analytical thinking, critical thinking, figurative thinking, creativity, out of box thinking, the ability to think and act in terms of public good. The first track "Say thank you" (February - June 2019) attracted the participants from 18 subjects Figure 1: Dynamics of school – contest (2017 – 2022) of Russian Federation, including the subjects in Siberia, North and South of the country. The next sections describe the scientific background and 2 GENERAL INFORMATION ABOUT THE ALL- educational objectives of this school-contest. RUSSIAN CREATIVE SCHOOL-CONTEST The significant benefits for the personality development of “PORTRAIT OF YOUR TOWN” AND ITS TRACK children and adolescents – the participants of the All-Russian “SAY THANK YOU” creative school-contest “Portrait of your town” have caused a quick growth of the school-contest’s popularity. The figure 1 The school-contest "Portrait of your town" has a methodical shows the dynamics of the number of Russian Federation provision in the form of five written lectures posted on the Web. subjects participating in the school-contest during the years These lectures are prepared by the second author of this paper 2017-2022. It should be underlined that the growth of this and are oriented at the adult specialists (from a school or a number during the year 2022 reached 50%. library) helping children to prepare the essays for the school- The result of the step-by-step evolution of the All-Russian contest. This interaction with an adult helps children and creative school-contest “Portrait of your town” during six year is adolescents a lot to better explicate their feeling. as follows. Now it is a unique education and up-bringing oriented The statistical results of the third school-contest “Portrait of platform realizing a dialogue between the bright, deeply feeling your town” (January – June 2019) are as follows: the participants children and adolescents from even remote regions and the were from 18 subjects of Russian Federation, they lived in 39 representatives of the state. The forms of the feedbacks received places, including 27 towns and 12 settlements in country side. by children and participants are the comments of the teachers, the 240 sketches became the winners of the school-contest, including comments in analytical every-year reports prepared by the 72 sketches from the new track “Say thank you”. scientific advisors of the school-contest (the volume of each In the year 2022, the school children from 58 subjects of RF annual report is from two to four hundred pages), the comments (68% of all RF subjects) participated with the essays in this in the mass media, and the words pronounced by the senators of school-context. 518 participants received a letter of Gratitude from a senator of RF (in accordance with a region). 162 The fourth exhibition “Portrait of the country depicted by Today the children throughout the world study the nature children with all their heart” in the Federation Council of the RF from the standpoints of botanic, biology, geography, chemistry, Parliament (June 2022) consisted of 56 pictures containing the and physics. Our accumulated experience shows that this fragments with the brightest ideas from the essays of the winners. approach is too narrow, it is not assuming a philosophy of The analysis of the essays submitted to the track “Say thank understanding the nature, of grasping the whole spectrum of you” enabled us to construct an unexpectedly rich classification knowledge about the world and about the behavior of a person in of the persons receiving “Thank you” from the participants. This the world of people, this philosophy is encoded in the phenomena classification is as follows: 17% - friend; 15% - school teacher; of nature. 12% - mother; 10% - teacher of extra education; 10% - inspiring Outstanding poets, writers, and painters give numerous person; 7% - father; 7% - relatives; 7% - manager; 5% - examples of decoding deep meanings of nature’s phenomena, the grandmothers and grandfathers; 5% - unknown person; 3% - examples of expressing these deep meanings by means of verbal tutor; 2% - school employee. The constructed classification was and visual images being comprehensible for the human beings. used as a system of nominations. We are convinced that it is possible and necessary to use the Let’s consider several examples of home compositions. lessons of literature, poetry, and the arts as the possibilities of a Example 1 (analytical thinking). The 8 year old girl Kate dialogue between the person and the nature, while searching for writes: "One autumn day the parents led me to a ballet school. the answers to acute questions during the period of personality’s Yana K. became my teacher. She seemed to me being just, kind, maturing. and beautiful. She is teaching us good but rigorously. She wants The habit to conduct a dialogue of the kind creates cognitive everything to be OK in our life and that is why we are to preconditions of forming a principally new level of ecological undertake efforts. I've realized that it is necessary to make much consciousness when the nature becomes your permanent efforts for achieving a result. I've realized that if one undertakes dialogue partner which is able to listen to you and to give the much efforts and works very much then the world and the people answers. This is the true meaning of the broadly known phrase in this world will become better. “It is necessary to be able to read the book of nature”. Thank you, my teacher, for evoking in me the belief that I will The most important result of forming this new level of be able to cope with everything, and it means that I'll be able to ecological consciousness is the creation of strong inner do everything”. restrictions concerning the destroying impact of the human being Example 2 (empathy, mindfulness). A 11 years old girl Maria on the nature: you can’t destroy something that is in your writes: “One spring day a young men opened a door of his car, consciousness a life prompter and assistant. intending to drive away. Suddenly he noticed a young girl who Analyzing the essays submitted to the considered nomination was crying, because her cat was unable to climb down to her from in the years 2019 - 2022, we concluded that the idea of nature- the top of a high tree. The young men reached the top of the tree, oriented behavior was broadly perceived by young children and grasped the cat, and returned back with the cat. The young girl teenagers and became a part of their conceptual world’s picture. was happy”. Example 1 (the girl Alexandra E.). “Let’s consider the Example 3 (empathy, thinking and acting in terms of public emergence of the leaves on the trees in spring and the shedding good). A 8 years old boy Andrey writes: "I would like to say of leaves in autumn. I selected this phenomenon, because it is THANK YOU VERY MUCH to my teacher Maria K. She is a similar to the situation as people emerge in our life: some time very kind person and a person of ready sympathy. One autumn they are close to you and then, in autumn, their interest in you day we with my class had an excursion in Kremlin. It was fades, your relations are fading, and such people lose the November, and it was cold. I lost my hat in school. At the connection with you, just as the leaves during the shedding. Only moment when all the classmates were dressed and were waiting those people stay near you, who interlock with the tree and are for me, I was looking for my hat, but all my efforts failed. Then fading together with it”. my classmates started to help me to find my hat, but we failed to Example 2 (the boy Ilya K.). “A leaf from a tree fell in the do it. Then our teacher gave me her hat and went on excursion water of a river, the river grasped it and carried away. May be, it without hat. Everything was good, we successfully went on will stop on the beach of the river, but, may be, it will put on excursion, and nobody from us became ill". weight and sank. The same situation can be observed in the life. If a person has no own opinion, he/she will “flow” across the life, achieving nothing. It is necessary to have the own opinion”. Taking the above said into account, we suggest a new 3 REALIZATION OF A NEW fundamental approach to upbringing of young children and FUNDAMENTAL APPROACH TO UP- adolescents (considering up-bringing as directed socialization): BRINGING to systematically establish the parallels between the phenomenon Since the year 2019, the school-contest “Portrait of your town” of nature and social agreements, life situations. includes the track “World, Nature, Universe’s Essence”. The rationale for introducing this track is as follows. The broad prospects of developing the personality of children and adolescents not understood, not used by modern education as a whole are opened by systematic, starting in early childhood, establishment of a correspondence between the situations observed in the nature and everyday situations. 163 4 THE SCHOOL-CONTEST “PORTRAIT OF YOUR TOWN” AC establishes the links between the objects, situation, AS THE THIRD IMPLEMENTATION OF THE STUDENT- processes, views of a person (a beholder) and the work of art that SELF ORIENTED LEARNING MODEL becomes a metaphor or a vivid illustration (vivid mental representation) of something the beholder is considering about. It is possible to indicate an interesting interpretation of the That is why the consciousness of the beholder receives a school-contest “Portrait of your town” in the context of the considerable impulse to developing the ability of establishing achievements of modern education theory. During last decade, diverse analogies and consequently to finding a new look at a the peculiarities of knowledge society have created the need for situation. a new paradigm of educational process. One of the most Example. For enriching the colour of their canvases, the significant peculiarities of the kind is the necessity to change a impressionists made use of what is known as division of colour profession several times during the working period of life. and optical blending. E.g., to represent a green meadow, they put Proceeding from broadly accepted role of emotional little tabs of blue and yellow on the canvas which are supposed intelligence (EI) in professional and personal life, we suggested to be combined to form green in the eye of the beholder – a far a new learning model (LM) called Student-Self Oriented LM more intense green than one taken straight from the artist’s (SSOL-model). It is defined as the model being beneficial for palette. That is why it is impossible to understand the idea of a self-cognition and self-construction through the prism of the picture standing close to the canvas. We have to step aside and acquired knowledge and life experience [15-17, 24]. look at it from a certain distance to enjoy it and to have the The scientific literature describes two successful desired effect. implementations of the SSOL-model. The first one is the System The same situation we have in every-day life. “Multiple debs, of Emotional-Imaginative Teaching ( the EIT-system), based on reflections” prevent us from grasping the sense of what is the Theory of Dynamic Conceptual Mappings (the DCM-theory). happening. As in case with impressionists’ canvases, we have to The EIT-system is aimed at systematic development of EI, have a look at the situation from a distance, and distance in this reasoning skills, sound creativity, figurative thinking, language case is equal to time distance. We need some time to better skills, and communication culture at the lessons of language - understand what has happened, and this will help us to cope with mother tongue and SL, literature and poetry in two languages (on the situation. the example of Russian and English), symbolic languages of The following principal factors provide the possibility to painting, sculpture, garden-park art, classic dance. We have interpret the All-Russian creative school-contest “Portrait of accumulated the 32-year-long successful experience of using the your town” as the third implementation of the SSOL-model of EIT-system in extra education in Moscow, Russia. Many aspects educational process. As it was mentioned above, the main idea of the DCM-theory and the EIT-system are described, in underpinned the creation of the SSOL-model was, while particular, in [4 – 17, 19 – 24]. interacting with the learners, to take into account and to improve The DCM-theory and the EIT-system belong to the emotional intelligence of the learners. constructive core of cognitonics, or the science about the human We indicate a spectrum of the themes’ facets but not the being in the digital world [11 – 24]. We organized as the co- theme. The children and adolescents participating in the main chairs seven international conferences on cognitonics in track of the school-contest are to ask the question about the conjunction with the international scientific multiconferences existence in their towns of such precious peculiarities that the “Information Society” (Slovenia, Ljubljana, Jozef Stefan portrait of the whole country would be incomplete without Institute, October 2009, 2011, 2013, 2015, 2017, 2019, 2022, see describing these peculiarities. Every participant of the track “Say https://is.ijs.si/?page_id=903). Totally, the researchers from 24 thank you” is to ask herself/himself whether there are such counties participated with the papers in seven international people in her/his surroundings that the interaction with whom conferences on cognitonics. turned out to be a defining experience for the participant. The ideas and methods of cognitonics underpinned a number Children discover the delighting traits of character, the manner of educational projects in several countries, in particular, in of speech, the ability to attentively listen to for a long time, etc. Croatia and Macedonia [29], Croatia [28], United Kingdom [26, After having delighted, a child or an adolescent is to critically 27], and Mexico, United Kingdom and PR China [3]. have a look inside herself/himself and ask herself/himself In [16, 18, 24], we formulated the following expanded whether she/he possesses the traits of the character delighted definition of cognitonics: it is the science about the trajectories her/him and whether she/he wants to improve her/his character. of raising the human being to such level of intellectual and The participants of the track receive the possibility to understand spiritual height where the scale of his/her personality becomes and to appreciate what they do know. We create a thought- proportional to the scale of the digital world. provoking situation which stimulates children and adolescents to The second successful implementation of the SSOL-model is analyze facts, to think over, to develop critical thinking (when a Art Cognitonics (AC) [14 – 17, 24]. AC is one of the principal school girl or boy understands that she/he doesn’t possess an branches of cognitonics. AC aims at tuning the EI of the young attractive trait of the character). children and adolescents with the help of well-known works of The transfer of an experience from one situation to another art. The goal is to create a bright semantic trace in the world’s situation contributes in many cases to developing cognitive conceptual picture of the learner corresponding to an idea flexibility. explaining or illustrating a moral value, communicative situation, a situation of making a decision, cognitive process itself, the process of self-cognition and consideration, the seething cocktail of emotions, a way of viewing the world around, etc. 164 5 GOODNET: THE GROWTH OF SELF-ESTIMATION IN to this lecture is distributed via e-mail by the responsible PEOPLE OF USUAL, MASS PROFESSIONS specialists from various subjects of Russian Federation. That is why there are reasons to say that every year school- In every country, a great majority of people have the professions contest “Portrait of your town” can be interpreted as a small which don’t attract public attention so much. 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October https://unevoc.unesco.org/go.php?q=TVETipedia+Glossary+A- 7th-8th, 2019, Ljubljana, Slovenia. Jozef Stefan Institute, Ljubljana, 15- Z&filt=all&id=602 18. [31] Transversal skills. 2019. TVETipedia Glossary, Accessed December 21, [24] Fomichova, Olga and Fomichov, Vladimir. 2020. “Education with the 2019. Focus on Up-bringing in Knowledge Society” . Moscow, Publishing House MAKS Press (in Russian). https://unevoc.unesco.org/go.php?q=TVETipedia+Glossary+A- [25] Gray, A. 2016. “The 10 skills you need to thrive in the fourth industrial Z&id=577 revolution”, Accessed December 17h, 2019. 166 Natural Environments, this sense of belonging is The Case of th gradu e Ci all vy wea ic kenin Ung. i versity of Landscape/Living Environment as a Model of Learning/ Process/ Action for Ternary Systems Human/Society/Life Environment prof. Rita Micarelli prof. Giorgio Pizziolo International Institute for Advanced Studies International Institute for Advanced Studies in System Research and Cybernetics (IIAS), in System Research and Cybernetics (IIAS), Ontario, Canada Ontario, Canada European Division Florence, Italy European Division, Florence, Italy rita.mica@gmail.com pizziologiorgio@gmail.com ABSTRACT Thus the deep relational structure typical of any The hypothesis expressed in this article is the possibility ecosystem is being replaced by mechanical and digital of linking in an evolutionary dynamic, beyond conflict, technological structures that now dominate most of their the world of nature to the world of digital information, spontaneous dynamics. whose entities are detached from natural constraints, distant from the reality of life and evolution but deeply The relationships spontaneously produced within the rooted in it and now dominant. In spite of all this, living world, thus weakened and overwhelmed by the Humanity - even though thus affected - remains an integral external influence of the mechanical and digital world, part of the Human/Society/Environment Ternary Systems, also progressively disturb the learning dynamics and the which are now facing the new Digital World, detached transitional modes of all human and natural ecosystems on from Nature but capable of heavily influencing it, the planet. depriving them of their evolutionary prerogatives. All this In them, the accumulation, hetero-controlled preservation is happening while increasingly dramatic crises affect the of "data" is opposed to their self- management and entire Biosphere, and while Science is getting closer to the autonomous processing of natural learning that stimulates deeper origins of Nature's dynamics and the self-creating the evolutionary dynamics of the systems on which all life roots of its evolution. in our world depends. We propose to put in place Relational Structures of Since the last century, the relational structure that Research-Action and Learning, modelled on the complex Human/Society/Environment ecosystems have revealed disordered Systems of People, Human Societies and the to us through the approach of human ecology has been Environment (in our case the H/S/E Ternary Systems) and recognized as a structure common to all systems in our the new Hybrid Human/Society// Living/Digital world, from physical to natural and human. Environment Systems, where the disordered and complex World of Nature remains the protagonist of evolution, 1.1 The Complex Disordered Systems collaborating with the Digital World but not subordinating to it. We ground the concept of the Civic University of The Physics of Complex Disordered Systems has led us Landscape/Living Environment as a means of promoting to discover the common roots of all the evolutionary and reconstructing relational and research-action in the dynamics of the world, and to recognize complexity and disordered complex systems of our contemporary world. disorder as prerogatives shared by physical disordered systems, biological systems, and the most complex human and social ecosystems; all of which leads us today KEYWORDS to recognize the world as a living totality in which all the Disordered complex systems, evolutionary processes, dynamics of evolutionary transitions are mutually ternary relationships Man/Society/Life // Digital connected. Environment, experiential learning The latest outstanding achievements in Physics (Giorgio 1 INTRODUCTION Parisi, Nobel Prize in Physics 2021) [7] teach us that the (evolutionary) transitions of nature's complex disordered The sense of belonging to one's own community and living Systems occur due to "various stimuli" due to certain environment is common to all living beings and constitutes parameters that in turn, during the system transitions, the Relational Structure that enables the formation and become more and more complex, depending on the evolutionary becoming of every Ecosystem (see, in characteristics of the systems with which they interact. particular, [1]). Today the parameters that have stimulated the transition In contemporary, increasingly exasperated Human and dynamics of Human/Society/Living Environment 167 and experiences (personal and social) originated in the ecosystems, usually from the natural environment, are multiplicity of human and natural dynamics that have instead artificially produced in the digital environment characterized and transformed them over time. and tend to dominate the evolutionary dynamics (which Today all these environments have been pervaded by had previously brought systems to higher and higher artificial dynamics (technological, cultural, financial) levels of complexity) leading them to an increasing produced by the globalized/digital world that tends to simplification their configurations, which become- dominate them all, creating in them another unexpected paradoxically- more and more complicated. hybrid living environment. This environmental, In this new condition, it becomes urgent to keep these economic, cultural and social crisis is reflected and heterodirected mechanisms in control and to protect leaves traces in individuals, societies and living complex and disordered Systems by supporting their environments, where processes of degradation and evolutionary processes, in contrast to the mechanical shattering are triggered from which new crises are simplifications imposed by the Digital World. generated and multiplied. Human/Society/Living Environment Ternary Systems gradually lose their capacity for self-control and their evolutionary 1.2 Transition Dynamics of Human/Society/Living autonomy, failing to counter the linear mechanics of the Environment dominant globalized-technological-digital world and Taking all this as the foundation of our research/action international finance. within the ternary systems of Human/Society/Life The administrative, economic and territorial policies on Environment, we can reconstruct favourable conditions which the transformations of H/S/E ecosystems are based for multiple experiential learning processes, achievable are themselves conditioned by the pressures of the through territorial Ecosystemic Laboratories. globalized world to which the Administrations fail to These laboratories consist of a whole structure of counteract the interests of citizens, who in turn are relationships that support diverse experiences and non- conditioned and overwhelmed by the uncontrollable hierarchical information exchanges. This whole in turn intrigues of the dominant mechanics of globalization, becomes an increasingly complex relational structure in down to the personal, behavioral and interpersonal level. which new knowledge and stimuli are processed and produced. 2.1 Ecological Dynamics versus Digital Mechanics In this condition, information exchange occurs between In these situations, there is no possibility of direct the natural and digital environments, while this new environment accommodates the elaborations produced opposition between the ecological dynamics of within the Laboratories and intensifies exchanges on a Human/Society/Environment and the invasive larger scale. technological, financial and digital mechanics that tend to dominate the planet, to the point of destruction. This whole in turn becomes a relational structure in At present, a global opposition to these phenomena is which new knowledge is processed and new almost unthinkable, while it would instead be possible to evolutionary dynamics towards new levels of ecosystem sustain and promote multiple forms of resilience in ternary complexity are activated. systems-already recognized as such-and activate new ones. The case of the Civic Landscape//University can be This can be realized through new forms of experiential emblematic as a research/process/action model for the practices addressed to different Ternary Systems, in a ternary systems to which the participants belong. This multiplicity of unpredictable stimuli and relationships. can also be emblematic as a learning process model for These can in turn give rise to new transitional phases and ternary systems within which everyone can practice configurations in a succession of dynamic equilibria different types of action/research, strengthening the typical of all complex disordered systems, as occurs in sense of belonging between participants and their living Nature. environments.1 This approach becomes strategic at a time when climate 2.2. The Relational Fields change is disrupting every environment, every human This open-ended relationality can create new and ever society and every living environment. At this step we can changing Relational Fields, whose dynamics go beyond reformulate all ecosystem relationships and consequently the preconceived rules on which Artificial/Digital Games all modes of social- are usually structured (as opposed to the relational environmental learning in its becoming. dynamics of Nature) toward new Plays of collective invention and joy, capable of stimulating new 2 THE SIGNIFICANCE OF CIVIC evolutionary transitions of ternary complex Systems LANDSCAPE UNIVERSITY composed of different interacting Entities, such as: This university is an experiential learning structure that - People, with their desires, availability, competencies can operate in any civic society that feels an active part and active skills. of its life environment. - Social groups interacting and practicing friendly mutual In each of these environments the affections, memories learning, a fundamental condition for the activation and self- regulation of processes; - the Landscape/Living Environment identified from time 1 The Landscape is intended as Life Environment, according to European to time as the Field in which the Action Research Landscape Convention , Florence, 2000 168 neighborhood cultivation, care and maintenance of takes place and the evolutionary transformations are ecosystem relationships typical of any living environment, perceptible and directly appraisable by the participants. self-management of interactive digital environments) From their reciprocal and continuous dynamic -In the impossibility of recovering degraded contexts by interactions originate relational Fields, which give rise activating specific modes of lasting interaction between to new ternary Human/Society/Living Environment people and the environment Ecosystems, still complex, disordered and in continuous -In the impossibility of producing new ways of working transition. and circular economies in connection between local societies and living environments. 2.3 The Relational Interface - In the political arrogance of "Large Public Works" and The Civic Landscape University constitutes a relational the profound alterations they induce. Interface that, by interacting with these Ternary Systems, ensures that they maintain their own evolutionary 2.6 How can the University be useful to Ternary dynamics in the face of the growing and oppressive abuses Ecosystems of power of the globalized/digital world. In any condition of socio-environmental distress where Wholeness, circularity, dynamic H/S/Environment interactive ecological processes are activated or formed balances and equal interaction with the globalized/digital and where new stimuli, energy and creativity can come world are the basis of every activity of the Civic into play, escaping the traditional planning methods and University of Landscape whose name already expresses problem-solving procedures (sanitation, health, waste, the wholeness and multiplicity of Knowledge and public transportation, etc.) usually chosen by government Research Action differently expressed by its members: departments, the University is welcome. - University, expresses the boundless wholeness of knowledge (with science, art and philosophy being part of 2.7 Who can be involved in its activities it) Experts from different disciplines who contribute to the - Civic, expresses the totality of knowledge, values and knowledge of the complex systems interacting in each desires present in every person, and in every society ternary H/ S/ E System and participate in learning and - Landscape, expresses the totality of the living action-research processes modeled on each specific environment in all its natural, human, technological and context. even digital articulations. Participants who, on a personal and/or social level, have had spontaneous experiences of action or struggle for the 2.4 The Common Good environment with groups, associations and committees in These three components in turn express a concept of various social realities. Common Good articulated in the different Environments Exponents of cultural, scientific, educational and support of Life, a Field in which specific Research and Actions institutions, in their national and local articulations, can be developed for the formation of stable participatory willing to activate and/or contribute to Participatory Social structures, differently rooted in each context, through Learning Processes on the various Life Environments of specific methods to manage, protect and promote the reference. different Environments of Life. National-regional administrative institutions already present and active in local contexts and willing to support 2.5 Where the Civic University can work innovative participatory processes aimed at the The conditions of discomfort, protest and awareness management, protection and promotion of the living shared by the inhabitants of the many different environments under their competence. environments of contemporary living, almost ignored or denied by political decisional structures, constitute fertile 3 THE WORKING GROUPS ground on which the activity of the Civic University can Within the Civic Landscape University, different working grow and articulate. groups are formed from time to time to establish friendly These conditions manifest themselves in different places and equal interactions among the heterogeneous actors and ways: involved in participatory processes. - In mountain environments already recognized by law but They support and encourage mutual learning and often usurped (excavation, theft of pastureland) or project/laboratory experiences on the changing dynamics mismanaged by public agencies (municipalities, regions). of human /society/living environments systems and to - In usurped or privatized public lands independently address and control the pervasive -In the sale of public housing complexes valued as phenomena coming from the globalized digital world. commodities in a speculative sense Thus, a new, unexpected Life Environment is formed in -In the poor planning of urban/metropolitan areas that which the Digital World interacts-without overwhelming deny citizens civic services fundamental to their quality of them-with the H/ S/ E ecosystems, which remain life protagonists in their evolutionary processes. -In the abandoned agricultural areas adjacent to In these new conditions multiple dynamic processes of population centers, exploited in favor of the development ecological protection and promotion of the participants' of private wellness centers and luxury sports facilities living environments coexist, as well as self-management -In the denial of any prospect of management of Services of the new living environments in connection with the essential to the ecological vitality of densely populated Digital Environment. areas (public transportation, food, sanitation, 169 Florence Metropolitan Area). In order to achieve more complex levels of mutual 0.2 Second cycle - Relational reactivation in complex exchange and knowledge among all components of the (consolidated or exacerbated) Systems. new Living Environments, the Civic Landscape Experiences of rediscovering or reconstructing University is organized as a Structure of Relation and relationships in Ternary Microsystems to foster or Propagation of scientific elaborations and experiences highlight their evolutionary potential. among concrete territorial realities that confront the - Long-term (successful) experiential cases - La Pica abstraction of the digital world. All this can take place Garden - Mirandola (Emilia Romagna). through the continuous interconnection between the - Experiences of contrasted participatory processes theoretical elaborations, experiential realizations Palmaria Island (Liguria) the denial and destruction of developed in the Ternary Systems and the digital the ecosystem. components involved in this new "Hybrid - The usurped pastures of the Apennines (Abruzzo); Environment." - the legal claim to collective ownership of their marble The University thus becomes a complex interface between quarries (Apuan Alps, Tuscany). Digital World and Ternary Ecosystems, in a continuous 0.3 Third round - General discussion on the intertwining of digital/virtual and concrete realities that contributions produced. work in synergy and stimulate each other toward new - Ecological/Systemic balance of contributions stages of transition and dynamically balanced integrated and proposed in previous cycles. configurations. - Fragility, stability, balance highlighted in the cases discussed. 4 THE MODEL OF THE ORGANIZATION AND - Comparative (critical) assessment of the state of OPERATION OF THE UNIVERSITY Research-Learning Action in the presented cases. - Proposals for the next cycle activities. This model can be summarized as follows. Online publication and extensive final discussion on the 0.0 General Introduction - Development of social activities carried out. participation in ecosystems and the entire relational sphere Contributions and proposed problems discussed can be (cf. Italian Constitution - Article 9). requested from experts and participants who have spoken or 0.1 First round of meetings - general themes and lived are interested in providing their suggestions and support for cases future activities. - Human Ecology and Democracy in the living environments of contemporary societies 5 CONCLUSION - The principles and criteria of the Ecological Approach We would like to emphasize that the Civic University compared with the principles and criteria practiced by structure we have devised can become a fertile Research - territorial Administrations and Public Managers Learning - Action Environment aimed at implementing new established in the territories according to the current frontiers of knowledge and experience, both towards the democratic and economic "rules." most significant scientific elaborations of the 20th and 21st - Presentation of experiences already practiced, in centuries and the implementation of new forms of progress or proposed by local groups, compared with the experiential democracy opposite approaches of local Institutions and Inhabitants (Collective Domains; Simeto-Panaro River Contracts; Metropolitan Crisis Management and Alternatives - REFERENCES [1] O.S. Fomichova and V.A. Fomichov. The Web-based Lectures as Leverage for Developing the Sense of Belonging in the All-Russian Creative School- Contests. In: 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), September 28 – October 2, 2020, Opatija, Croatia. Proceedings. Rijeka: Croatian Society for Information, Communication and Electronic Technology - MIPRO, 2020, pp. 855-860. [2] R.Micarelli, G.Pizziolo. L’arte delle Relazioni and Dai margini del caos,l’ecologia del progettare, it.ed., Alinea, Firenze, 2003. [3] M.Pascucci. Causa Sui, it. ed.Ombre Corte, 2009 . [4] M.Pascucci. La Potenza della Povertà, it. ed. Ombre Corte, Verona, 2006. [5] M.Pascucci. Macchina Capitale, it Ombre Corte, Verona, 2022. [ 6] K. Hiwaki, Culture and Economics in the Global Community. A Framework for Socioeconomic Development. UK and USA, Gower Publishing Company, 2011. [7] G.Parisi. In un volo di storni it. Ed. Feltrinelli, Milano , 2021. [8] E.Marinari. La Fisica dei sistemi complessi, by Corriere della Sera, Milano, 2022 [9] K. Hiwaki. From Growing to Maturing Integral Harmony and Global Integrity, International Journal of Human Sciences and Education, (IJHSSE), Vol.8, February 2021. [10] The site of association GRASPTHEFUTURE.EU, www.graspthefuture.eu 170 Were the Principles of Cognitonics Met in Online Education During the Covid-19 Pandemic? Ida Panev Business Department Polytechnic of Rijeka Rijeka Croatia ipanev@veleri.hr ABSTRACT The question of this research was whether distance education during the Covid – 19 pandemic was conducted according to Cognitonics is a scientific discipline developed with the aim of some principles of Cognitonics. studying the human being in the digital world. The aim of this study is to investigate through survey and to analyse whether e- learning in which students suddenly found themselves, due to Covid - 19 pandemic, was conducted in accordance with some 2 RESEARCH ABOUT IMPLEMENTING principles of cognitonics. THE PRINCIPLES OF COGNITONICS IN KEYWORDS ONLINE EDUCATION DURING COVID-19 LOCKDOWN Cognitonics, e-learning, online education, distance education, Covid - 19, pandemic, lockdown, survey The aim of this research is to evaluate the realization of some of the Cognitonics' goals in online education during Covid - 19 lockdown in Croatia. With the closure of educational institutions, 1 INTRODUCTION the need for a rapid and unexpected transformation from onsite to online learning emerged. The created survey shows to what Cognitonics is the science about human being in the digital world extent online education due to Covid - 19 affected the mental and [4]. “It is the science about the trajectories of raising the human physical condition of students and was it conducted according to being to such level of intellectual and spiritual height where the some principles of Cognitonics. scale of his/her personality becomes proportional to the scale of Created survey included 23 closed questions. The obligation the digital world” [5]. It, among other things, questions the of the respondents was to answer each question. The survey was impact of information and communication technology on the created using Google Forms platform and distribution was identity (personality) of an individual, a particular group, or a conducted through the outreach of social media and messaging society as a whole. Cognitonics seeks to point out the need for services. Clear instructions were provided to ensure that the development of person’s creativity and independent thinking, respondents must be from a student population. No individual sense of harmony and beauty, awareness of belonging to a was forced against their will to fill in the survey and no particular national culture or social heritage, language skills identifying information was collected. When analyzing the (primarily skills of quality use of the official language of the results of the survey, descriptive statistical data analysis was culture to which a person belongs), ethical behavior, abilities for used. self-regulation (i.e. monitoring and controlling one's own Total 50 answers were gathered through survey, so this paper behavior),… within the society of rapidly developing can be a stimulus and can give an idea for further research. information and communication technologies and globalization [10]. 2.1 Survey questions As we all witness, with the growing popularity of ICT – Information and Communications Technology, the popularity of 1. Gender. online learning, especially in higher education, also arises [1]. 2. Age group. Despite this, online (distance) education (e-learning) has not 3. Select your current level of education. been involved in the educational process to such an extent. With 4. What is your perception of the situation in which you suddenly the advent of the Covid - 19 pandemic, this changed so online found yourself during the "lockdown" referring to the transition education suddenly became the main mode of education. In to distance education? general, educational institutions were not prepared for the sudden 5. During distance education, was your creativity in different shift to online teaching, so as we witness this became a topic of spheres mostly encouraged (e.g. creativity in expression, many researches. learning, communication, problem solving, etc.)? 6. If the answer to the 5th question was "Yes", choose in which spheres your creativity was encouraged during distance 171 education: creative expression, creative ways of using Regarding the current level of education, 72% of the technology, creative ways of learning, creative ways of respondents are in the higher level of education, 24% are in high communication, creative task / problem solving, my creativity school and 4% are in elementary school. was not encouraged, I can’t estimate. When stating what is their perception of the situation in 7. If the answer to the 5th question is "Yes", evaluate whether which they suddenly found themselves during the "lockdown", your creativity was more stimulated during distance education and it refers to the transition to distance education, 56% of the than during classroom education? respondents answered that it was positive perception. 24% of the 8. During distance education, were you mostly encouraged to respondents answered neither positive nor negative, and 20% think independently and solve tasks / problems? answered that their perception was negative. These positive 9. During distance education, was the development of your findings have also been confirmed in other researches [3] [13]. language skills mostly encouraged (was your spelling and When talking about the creativity in different fields like grammatical correct expression in written/oral communication, creativity in expression, learning, communication, problem creativity and task/problem solving encouraged)? solving, etc., 48% of the respondents answered that their 10. During distance education, was your ethical behavior mostly creativity was mostly encouraged during online education, 36% encouraged in communication, cooperation, solving tasks / answered that their creativity was not encouraged, and 16% of problems? the respondents could not estimate. Among respondents who 11. During distance education, were you mostly encouraged to answered that their creativity was mostly encouraged, 12% of behave responsibly towards yourself and others when using them answered that their creative expression was encouraged, information and communication technology? 44% answered that the creative ways of using technology were 12. Do you think that you have gained the same amount of encouraged, 36% answered that the creative ways of learning knowledge and experience through distance education as you were encouraged, 40% answered that the creative ways of would have gained through classroom education? communication were encouraged, 28% answered that the 13. Do you think that distance education has affected your mental creative task / problem solving was encouraged, while the rest of state? the respondents where those who did not answer positively about 14. Do you think that distance education has affected your creativity encouragement, or they could not estimate. It can be physical condition? concluded that the creative ways of using technology were 15. During distance education, did you experience a more encouraged to the greatest extent and creative expression was individual approach to you as a student by the teacher than during least encouraged. classroom education? When asking whether students creativity was more 16. During distance education, were you mostly a passive stimulated during distance education than during classroom observer or were you encouraged to actively participate in the education, 40% of the respondents could not estimate, 32% of learning process? the respondents answered positive, 12% of them answered 17. During distance education, did you feel connected to the negative, and the rest of the respondents were in population community in which you live (such as a community of fellow which stated that their creativity was mostly not encouraged students; a community of friends; a community of residents of during distance learning. your city, etc.) or did you feel isolated? When asking respondents were they mostly encouraged to 18. During distance education, did you mostly encounter the think independently and solve tasks / problems independently understanding and empathy of the teacher for the situation you during distance education, 68% of them responded positively, found yourself in? 28% of them responded negatively and 4% could not estimate. 19. Did you have enough prior knowledge to use technology Other researchers also gathered the results which speak in favour during distance education? that students were encouraged to take the responsibility for their 20. During distance education, were you able to better organize own learning during distance education [13]. your study time and free time? Interestingly, the same amount of the respondents (40%) 21. During distance education, was your curiosity to acquire new stated positively and negatively to the question if during distance information / knowledge / skills mostly encouraged? education the development of their language skills was mostly 22. How much time per day (during the working week) did you encouraged, and 20% of the respondents could not estimate. spend at the computer during distance education (to attend When asking if during distance education their ethical classes or to fulfil school / college obligations or to study)? behavior was mostly encouraged in communication, cooperation, 23. During distance education, were you as motivated to learn / solving tasks / problems, 52% of the respondents answered complete your duties as during classroom education? positively, 28% of them answered negatively, and 20% could not estimate. This is a positive indicator and points to the fact that it is possible to influence the ethical behavior of students so that, 3 SURVEY RESULTS EXPLANATION among other things, for example, the writing of online exams is The results of the survey analysis show that there were 60% of in accordance with the principles of the educational system. male respondents, 32% of female respondents, while 8% of When asking if during distance education the respondents respondents did not want to make a statement about their gender. were mostly encouraged to behave responsibly towards The majority of the respondents (64%) were in the age group themselves and towards others when using information and 19-24, 28% were in the age group 25 and more, and the rest of communication technology, 48% of the respondents answered the respondents (8%) were younger than 19. yes, 28% of the respondents answered no, and 24% of the respondents could not estimate. For example, the need to 172 encourage responsible behavior among students during online for the situation they found themselves in, 60% of the communication is also emphasized in a paper written by respondents answered positively, 24% answered negatively and Martinez [8]. 16% of the respondents could not estimate. In the next question, the respondents were asked do they feel The only question answered 100% positively was the that they have gained the same amount of knowledge and question asking did the respondents have enough prior experience through distance education as they would have gained knowledge to use technology during distance education. This through classroom education. 56% of the respondents answered proves that today’s students are digital natives. It means that they positively, 40% responded negatively and 4% could not estimate. use technology as an integral part of their everyday lives where When talking about mental and physical state, 36% of the they use it for internet searching, socializing, and communication respondents stated that distance education had a negative impact [2]. on their mental state, the same percentage – 28% stated or that it 80% of the respondents answered that during distance had a positive effect, or that it did not have any impact on their education they were able to better organize their study time and mental state. 8% of the respondents could not estimate. This can their free time, 16% answered negatively to this question and 4% support the statement that there is evident academic – related of the respondents could not estimate. In other researches the stress or anxiety which effects mental health and well - being of same result was given – students were able to study at their own the students during distance learning caused by the pandemic pace [13]. However, this is supported by the fact that the majority [7][9][13]. Researchers also find out that although before of respondents are between 19 and 24, so they have already mentioned issues, students were free of depression during acquired working and organizational habits. distance education [13]. Interestingly, Zhou & Shang [13] stated When asking the respondents has their curiosity to acquire in their study that students showed improved mental health new information / knowledge / skills been stimulated during during pandemic. distance education, 60% of the respondents answered yes, 32% As for physical state, 44% of the respondents answered that of the respondents answered no and 8% of the respondents could distance education did not have impact on their physical state, not estimate. 28% of the respondents answered that it had a positive impact, As the answer to the question how much time per day (during 24% of the respondents answered that it had negative impact, and the working week) did the respondents spend at the computer 4% of the respondents could not estimate. This can be explained during distance education (to attend classes or to fulfill school / by the fact that the majority of respondents are in the age group college obligations or to study), 60% of the respondents that has already acquired habits related to physical activity, so answered 1 – 4 hours a day, 28% of the respondents answered 5 the lockdown did not have a negative impact on that aspect of – 8 hours a day, 8% of the respondents answered more than 8 their lives. hours a day and 4% of the respondents answered less than 1 hour When answering if during distance education respondents a day. experienced more individual approach from the teacher to them The last question of the survey was asking the respondents as a student, than during classroom education, 48% of were they as motivated to learn / do their homework during respondents answered no, 28% answered yes and 24% of the distance education as they were motivated during classroom respondents could not estimate. This shows that, unfortunately, education. 40% of the respondents answered that they were less there are not enough human, time and material resources for an motivated, 32% answered they were equally motivated, 20% of individual approach, which is often a problem with traditional the respondents answered that they were more motivated and 8% education, let alone with online education. Similar results were could not estimate. As already emphasized, during online found in other researches where the lack of interaction between education it is necessary to make students active participants in student and teacher was found [3][13]. the educational process, and it is also necessary to motivate them Furthermore, 60% of the respondents answered that they to participate and learn in an online environment. were passive observers during distance education, 32% of the respondents answered that they were encouraged to actively participate in the learning process during distance education and 4 CONCLUSION 8% of them could not estimate. This is the topic that must be In this study, the survey was conducted with the aim of reaching addressed. Percentage in this answer has to be changed because a conclusion as to whether online education was carried out in one of the main goals of the online education must be to actively accordance with some principles of Cognitonics. Findings in big involve students to participate in the educational process. There part show that it was. Students mostly had positive perception are a lot of papers that specify how to actively engage students about distance learning, their creativity and curiosity were during distance education. For example: [12][14] etc. encouraged, they were encouraged to think independently, their When asking if the respondents felt connected to the ethical and responsible behavior was encouraged. Also, most of community in which they live during distance education, 40% of the respondents stated that distance learning did not have impact the respondents answered positively, 28% responded that they on their physical state, that they felt connected to their felt isolated from the community, and 32% of the respondents community despite online communication, that they encounter could not estimate. Zhou and Zhang also stated in their research the understanding and empathy of the teachers and that they were that students felt belongingness to their learning community able to better organize their study and free time. The negative during online education due to the pandemic [13]. sides of distance education in this study were: slightly negative When answering if during distance education respondents impact on the mental state of the respondents and lack of mostly encounter the understanding and empathy of the teachers teacher’s individual approach. Also, the respondents mostly 173 perceived themselves as passive observers in educational process [4] O. Fomichova & V. Fomichov (2021). Cognitive Painting as a Broadly and less motivated to learn and do their educational obligations Applicable Method of Constructing a Positive Cognitive - Emotional Space for Young Children and Adolescents under Conditions of the while attending online learning. Coronavirus Pandemic. Proceedings of MIPRO 2021 (pp. 659-664). At the beginning of Covid-19 pandemic, educational Opatija, MIPRO. [5] V. Fomichov & O. Fomichova (2019). Predgovor/Foreword. In institutions were not prepared for sudden need for distance Informacijska druzba - IS 2019. Zvezek E. Proceedings. of the 22nd education. Researchers [11] show that at the beginning of the International Multiconference - IS 2019, Edited by V. A. Fomichov, O. S. Fomichova. Vol. E, Kognitonika. International Conference on lockdown due to Covid – 19 pandemic, educational institutions Cognitonics. October 7th-8th, 2019, Ljubljana, Slovenia. Jozef Stefan were not prepared regarding ICT infrastructure, grading policy, Institute, Ljubljana, pp. 3-4. student support etc. Students were in a worry about the efficiency [6] T. Gonzalez, M. De La Rubia, K. Hincz, M. Comas-Lopez, L. Subirats, S. Fort et al. (2020). 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Ayoob, A. Malik, & S. Memon (2020.). Perceptions of [12] M. Valente, & M. MacMahon (2020). Virtual communication for student students regarding E-learning during Covid-19 at a private medical group projects: the COVID-19 effect. ALL IRELAND JOURNAL OF college. Pak J Med Sci. vol. 36, pp. doi: HIGHER EDUCATION, 3. https://doi.org/10.12669/pjms.36.COVID19-S4.2766. [13] J. Zhou, & Q. Zhang (2021). A Survey Study on U.S. College Students’ [2] D. A. Akuratiya & D. N. Meddage (2020, September). Students’ Learning Experience in COVID-19. Educ. Sci. doi: Perception of Online Learning during COVID-19 Pandemic: A Survey https://doi.org/10.3390/educsci11050248 Study of IT Students. International Journal of Research and Innovation in [14] D. Zuidema, & R. Zuidema (2021). From Passive Observers to Active Social Science (IJRISS), pp. 755-758. Participants: Using Interactive Remote Demonstrations to Increase [3] R. Chang, Y. Hung, & C. Lin (2015). Survey of learning experiences and Student Involvement in Online Chemistry Instruction. Journal of influence of learning style preferences on user intentions regarding Chemical Education, 3. MOOCs. Br. J. Educ. Technol., 46. 174 The Method of Cognitive Painting as an Effective Tool for Constructing a Positive Cognitive-Emotional Space for Children and Adolescents under Conditions of the COVID- 19 Pandemic Olga S. Fomichova Vladimir A. Fomichov Centre of Social Competences "Dialogue of Sciences”, Department of Intelligent Monitoring Systems, State Budget Professional Educational Institution Institute No. 3 “Control Systems, Informatics and “Sparrow Hills”, Moscow, Russia Electric Power Engineering”, Moscow Aviation Institute (National Research University), Moscow, Russia olga.s.fomichova@gmail.com vfomichov@gmail.com ABSTRACT only by the adults but also by children and adolescents increased several times in comparison with previous value. This situation The paper expands the authors’ theory of dynamic conceptual caused a number of negative impacts not only on physical health mappings by means of introducing an original, broadly of the person but also on his/her emotional state and mental applicable method of creating a highly useful online method (or health. prop) being appropriate for the particular situation when children During last year and the first months of the year 2021, many and adolescents find themselves in the pandemic restrictions scholars from different countries analyzed the influence of the launched into the digital cosmos without being trained to bear a corona virus pandemic on moral state of children and flight lasting almost half a year, being a member of a busy crew, adolescents, on the development of their negative attitude to the though they have never had an experience of being together with world. In particular, the papers [1], [2], [3] explicate, first of all, for twenty four hours a day. This method is called cognitive such negative phenomena as high rates of anxiety, depression, painting. Within an original online course “Cognitive-emotional stress. personality development” in addition to the usual tasks the authors started up a project dealing with creating a new year story Proceeding from the fulfilled analysis of the situation, the underpinned by students’ own perception of snow (in case of authors of [1] indicate the necessity of creating the activities for snowy winters), their love towards their favorite Christmas toys, improving “the individual health of children and adolescents and their Christmas wishes and hopes and underpinned by sound their families, the health of the community, and the intellectual reasoning about Christmas gift in general, Christmas miracles a and working capacity of these individuals over the long term, and Santa Clause. 62 school children took part in this work (the with positive economic and social results for each nation”. age from 7 to 18 years). As a result, a 92-pages printed book is Similarly, the authors of [2] underline the significance of helping obtained as an output of that co-creative work. A very precious children and adolescents to deal with mental health burden of the feature of the introduced method is that it can be effectively pandemic. applied in arbitrary countries, taking into account the peculiarities The study described in the present paper just satisfies these of national culture and nature. demands, the paper is of constructive character. KEYWORDS Our analysis has shown that cognitive danger of corona virus Cognitonics, constructing a positive cognitive-emotional pandemic is a consequence of the following principal factors: space, cognitive painting, cognitive-colour scheme, cognitive - Children and adolescents are bereft of their maturity, emotional maturity, creativity, student-self oriented usual surroundings (school life, strolls with their learning model, personality development, theory of dynamic friends, off-line education, extracurricular activity); conceptual mappings, little “C” creativity, big “C” creativity - They are bereft of co-creative off-line activity, which is underpinned with strong emotions, discussions, brainstorming sessions in which all the 1 INTRODUCTION members of a group suggest the ideas and then discuss them; - Children and adolescents are bereft of off- The interpretation of cognitonics as the science about the line group activities, such as round table discussions, human being in the digital world emerged one and half decade sport events, creative contests, balls, parties, museums; before the COVID-19 pandemic. This global dangerous event added new significant facets to the concept of the human being - Their interaction with the parents is an illusion, in the digital world. The average number of hours spent every because parents are at home but in fact they are not. The are day for interaction with computer systems (including Web) not 175 working online all the day. It disappoints children’s hopes circumstances, their vision of the situation is negative or and looks like the fraud, it doesn’t meet their expectations. mainly negative. Children have to make peace with it, but it is difficult, even Recommended way out (the most general impossible in particular age. formulation): In this connection let’s try to have a look at the work of Step 1. Try to find in the CWP of the learners certain astronauts on board of the cosmos station during a long bright, positively coloured fragments. period of time (half a year, for example); Step 2. Invent a kind of intellectual, emotional activity - Astronauts are grown-up people who know beforehand closely linked with found bright, positive fragments of the how long they would stay on board of the station; CWP and transporting the positive colour of such fragments - They are trained well how to cope with the restrictions (or a fragment) to the perception of the current situation. of all kinds; The next sections describe our successful implementation - The members of the crew are well matched of this method by means of distance education. Besides, we psychologically and roughly equal in ability, they are well set forth the theoretical foundations of our method in addition motivated and are inspired by what they are doing; to the ideas stated above. - Each of them is highly involved in the activity he/she 2 SCIENTIFIC FOUNDATIONS OF is carrying out, and it helps to overcome the restrictions. COGNITIVE PAINTING We may assume that children and adolescents were launched into the “digital cosmos” without any preparations 2.1 The Method of Drawing Together Little and, due to their small age, they were lack of highly “C” and Big “C” Creativity motivated creative activity and ability to initiate creative The paper [4] presented a new look at little "C" and big work which could be overwhelming. "C" creativity. Big "C" creativity (BCC) is regarded in Negative response to the situation of restrictions and the connection with the creative ability of outstanding scientists, necessity to work hard without improved ability to think over musicians, painters, writers, poets [2]. Smart society and then put forward his/her own ideas, without being demands little "C" creativity (LCC). It reveals the smart propped up by the creative surroundings makes it clear that society's necessity of creative thinking [3, 4] and creative children and adolescents need an emotional and creative approach to solving the every-day tasks. LCC improves prop. problem solving skill, which is one of most important skills. We have invented a broadly applicable method of BCC is defined by two main characteristics. It is regarded creating a highly useful online prop being appropriate for the as original and highly significant creative activity for big particular situation, when children and adolescents find groups of people. Creativity of children (LCC) usually is themselves in the pandemic restrictions launched into the subjective and is defined by their previous knowledge. The digital cosmos without being trained to bear a flight lasting main characteristics of LCC is their imagination [8]. Smart almost half a year, being a member of a busy crew, though society demands the necessity of supporting and improving they have never had an experience of being together with LCC in order to create the preconditions for increasing the twentyfour hours a day. This method called cognitive proportion of the specialists in significant application painting is stated below. domains who possess BCC. The main impulse to the birth of cognitonics was given Our paper [4] suggests a method of combining as early as by our Theory of Dynamic Conceptual Mappings (the DCM- possible LCC and BCC in the process aimed at realizing the theory). During the first decade of its development the central Thought-Producing Self (see [9], [10]) of the child. idea was as follows: while thinking over how to inscribe a piece of theoretical materials into the conceptual world’s The first step of the method suggests the understanding by the children of the significance of thought. It helps to picture (CWP) of a learner, it is useful to find (or to create return the notion "value of thought" to the world's conceptual during a lesson) in his/her CWP a bright, positively coloured picture of the school children. fragment and to establish a correspondence between the entities and relationships from the considered piece of theory The second step suggests the awareness of the school and the entities and relationships from this selected (or children of the fact that their ideas, metaphors, way of created) fragment of CWP [9, 10, 23-28]. viewing nature, communicative situations, the pictures, etc. Last year we faced a new problem: not to introduce a may be highly significant for relatively big groups of people certain piece of theory but to initiate positive changes in the in case of sharing their ideas with the others. The reason is children’s attitude to the world, in their moral state. That is that they have given a sophisticated look at something and why we transformed the central idea of the DCM-theory and have revealed an example of serendipity (the ability to make suggested the following method called the Method of pleasant and unexpected discoveries entirely by chance). It Cognitive Painting: happens due to their natural ability to see out of the way things in usual things and usual things in out of the way Starting situation: The learners (the children or things. It might be thought provoking for grown-up people. adolescents) are morally suppressed by certain 176 Example (one of the examples of nature inspired 2009, 2011, 2013, 2015, 2017, 2019, 2022, see behaviour). “The crown is sitting on the twig. The crown is https://is.ijs.si/?page_id=903). Totally, the researchers form heavy and big, the twig is thin. But the crown is no nervous. 24 countries participated with the papers in six international It is not afraid of the fact that the twig may break, because conferences on cognitonics. the bird doesn't think about the twig, it trusts its swings” In [13], [15], [22], the authors formulated the following (Anne, a seven year girl). expanded definition of cognitonics : it is the science about the The third step is to make children aware of the beauty and trajectories of raising the human being to such level of wisdom they have discovered, because in most cases they do intellectual and spiritual height where the scale of his/her it without a second thought, intuitively. It just dawned upon personality becomes proportional to the scale of the digital them. They need encouragement to continue mental and world. spiritual work on that level. Their efforts and their inspiration Cognitonics provides the methods to reach cognitive should be discussed and appreciated by the community. engagement of the learners at the lessons and to arise their The fourth step is to show the examples of BCC revealing curiosity. the same idea to make children believe that the value of The ideas and methods of cognitonics underpinned a thought doesn't depend on age and experience, but age and number of educational projects in several countries, in experience help us to penetrate the very essence of the particular, in Croatia and Macedonia [29], Croatia [30], thought, to comprehend it. United Kingdom [31], [32], and Mexico, United Kingdom In the case considered in the present paper, we work with and PR China [33]. little “C” creativity, and, as a result, it reaches the level of the big “C” creativity. That means the situation when the written storis of the children, adolescents, and even grown-ups reveal 3 THE METHOD OF COGNITIVE the images and the way of consideration on such level that it PAINTING is possible to put them together with images and ideas of such Let’s consider our successful implementation of this great poets as Alexander Pushkin and Boris Pasternak. method. Within an online course “Emotional-imaginative 2.2 Student-Self Oriented Learning Model personality development’ in addition to the usual tasks, we have started up a project dealing with creating a new year Our method of cognitive painting introduced in the story underpinned by students’ own perception of snow (in present paper is based on the Student-Self Oriented Learning case of snowy winters), their love towards their favorite Model (SSOL-model). The principal motive for its creation Christmas toys, their Christmas wishes and hopes and was the idea that educational processes in knowledge society underpinned by sound reasoning about Christmas gift in (or smart society) should be based much more on taking into general, Christmas miracles and Santa Clause. account and improving emotional intelligence (EI) of the This story aimed at evoking their emotions, reminiscence learners. of childhood, memories of Christmas and New Year parties, The SSOL-model is defined as the model being beneficial favorite Christmas decorations and toys, the recalling of past for self-cognition and self-construction through the prism of events and pleasant experiences, penetrance into the magic the acquired knowledge and life experience [11], [12], [13], world of whirling snow and even the world of heavy [14], [15]. The principal distinguished features of the SSOL- Christmas snowfalls, Christmas holidays when children can model are as follows: (a) it takes into account and bases enjoy the snow in lots of way, can put on skates and have a slide across the ice may somehow “outwit” the exhausted educational process on EI of the learners; (b) it aims at reaching cognitive engagement of the learners; for this, it brain and let it have an inspiring rest, plunging into proposes a conceptual learning environment instead of the reminiscence of favorite things. environment based on mechanical remembering (it means The similar idea underpins the well-known song “My addition of emotional color to the studied notions and, as a favorite things from the wonderful film “The Sound of consequence, makes much easier the comprehension of these Music” (1965): notions). “Girls in white dresses with blue satin sashes, 2.3 The Role of Cognitonics Snowflakes that stay on my nose and eye-lashes, The SSOL-model is one of the fundamental results of a Silver white winters that melt into spring, new scientific discipline called cognitonics, or the science These are a few of my favorite things. about the human being in the digital world [13], [15], [16], [17], [18], [19], [20], [21], [22]. The birth of cognitonics was prepared by the authors’ papers [23], [24], [25], [26], [27], When the dog bites, when the bee stings, [28]. When I am feeling sad, The authors organized as the co-chairs seven international I simply remember my favorite things, conferences on cognitonics in conjunction with the international scientific multiconferences “Information And then I don’t feel so bad”. Society” (Slovenia, Ljubljana, Jozef Stefan Institute, October 177 This approach has nothing to do with virtual reality, on other ways of viewing the usual things (out of box thinking based the one hand, but it is used with the help of the opportunities on putting together little “C” and big “C” creativity. provided by the digital space in general and online education, We received 62 descriptions of snow. in particular. With the help of virtual reality, human try to outwit the brain, but they immediately face the danger of Example 1 (Katja G., 11 years old). addiction (like drug addiction) with all possible “… You are keeping a snowflake on your palm It is not consequences ahead. melting, because it trusts you. If it doesn’t melt, it means that you In November, we distributed via e-mail an initial version have tamed it. And it has nothing to do with the fact that you are of a new year story, it consisted of four pages and contained wearing a glove”. the slots on the themes listed below for inserting later the students’ compositions. By the middle of December, we Example 2 (Katja F., 10 years old). obtained a printed book “Wonderful New Year Story” “In the morning I looked out of the window. The whole sky composed by 62 students (from 7 to 18 years old) and was covered with snowflakes, they were whirling as if they were consisting of over 90 pages. The book includes also several dancing. I went out to enjoy the snow. I stepped on the colourful Christmas pictures done by the students. Printing a snowflake, and it took me up to the heaven above the clouds. I book was aimed at showing vividly to the students and their looked up and saw the blue dome of the infinite sky where the parents the results of their intellectual and emotional efforts, snowflakes were born”. the power of creativity, its possibility to transfigure the Example 3 (Alyona V., 17 year sold). reality. “The snowfall is crying quietly In the considered case, the children were given a four- page frame of a specially invented new year story with three Whipping off the face of the day. slots introduced as follows: The sunset’s enfolding the garden - Describe the snow, snowflakes, snowfall, snow like a carpet of resplendent hue; And the peace is spread above”. - Describe your favorite Christmas toy and Example 4 (Herman N., 9 years old). explain why it is your favorite toy; “White snowflakes are spreading afar, covering colourful - Write about your Christmas wishes, what are autumn leaves, making a carpet of resplendent hue, it is you dreaming about at Christmas time. crunching pleasantly. I looked up and found that the snowflake The story itself describes one Christmas Eve when two which was the fairest of all. I called her Snowy. She was dancing children (brother and sister) were at home alone. They were gracefully. She was very delicate. She was the miracle created by looking at the window painted silver by frost and waiting for their Nature”. parents. And outside it was solemn snowfall. Then children and Example 5 (Savely O., 17 years old). adolescents were asked to write about the snow. “I like snowstorm, because it is the only element that can Children were given the poetical examples of viewing the dance. I like to dance with snow in pair, matching the speed and snow when the rhythm of falling snow and whirling snow is rhythm of music. compared with the pace of life: a solemn snowfall like the slow pace of life in the country; heavy snowfall when it is stormy I like to learn new dance steps and to dance to the music of outside, and the windows is roaring like the perception of life the snow and the wind with delight. When the storm dies down, when it seems to quicken its space, and it is difficult to keep up and the dance is over, I have my red cheeks not due to the fact with it. that the frost is hard, and the snowfall is heavy, but as a reminder of my excitement and pleasure, because the partner is perfect, The falling snow seems to reveal the pace of life which is and we have been dancing all the way to my school”. going on with the same laziness or with the same swiftness keeping pace with heavy snowfall or walking in step with the The obtained results allow us to say that a new, broadly falling or whirling snow. applicable method of constructing a positive cognitive-emotional space for young children and adolescents is created. It may be Boris Pasternak made an assumption that the year is following called the method of cognitive painting. the year like the snow is falling or like a word is following another word in the poem. In one of the poems Pasternak gave During the last decade, it has been broadly realized that the following metaphor: “In the gate a snowstorm is knitting the education in knowledge society (or smart society) is to pay a net out of the swiftly following snowflakes”. particular attention to supporting and developing in the learners the significant, domain independent skills called soft skills [34], It is possible to say that the children were given some space [35] or transversal skills [36], [37], first of all, analytical and drawn by the world known poet Boris Pasternak (big “C” critical thinking, creativity, out of box thinking, thinking and creativity) to express their way of viewing and perceiving the acting in terms of public good. snow to reveal little “C” creativity. The idea is to inspire children and adolescents to hover about the reality and give birth to some The examples received from children and adolescents show the revealing of creative thinking, out of box thinking, analytical 178 thinking, and figurative reasoning. The application of the SSOL- [3] U. Ravens-Sieberer, A. Kaman, M. Erhart, J. Devine, R. Schlack model supports and improves emotional intelligence and and C. Otto, “Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany”. imagination. That co-creative work underpinned with the SSOL- European Children and Adolescents Psychiatry. 2021 Jan 25:1- model helps to transfigure the reality (which is the property of 11. doi: 10.1007/s00787-021-01726-5. Online ahead of print. the big “C” creativity). [4] O. S. Fomichova and V. A. 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Jozef Stefan Institute, Ljubljana, 2019, pp. 50-53. [31] T. B. Kane, “Using cognitive tunnels in a new approach to building social elevators in the information society”, Informatica. An International Journal of Computing and Informatics (Slovenia ), 2014, vol. 38, p. 263-271. [32] T. B. Kane, “A Cognitonics methodology for artificial persons”, in Zbornik 20. mednarodne multikonference INFORMACIJSKA DRUZBA - IS 2017. Zvezek D. Proceedings of the 20th International Multiconference INFORMATION SOCIETY - IS 2017, Volume D. Kognitonika/Cognitonics. Uredila / Edited by Vladimir A. Fomichov, Olga S. Fomichova. 9.-13. oktober 2017/ 180 Chess as a Tool for Developing 21st Century Skills with a Deliberate Practice Approach Jana Krivec School of Advanced Social studies Slovenia jana.krivec@fuds.si ABSTRACT skills" or "soft skills," are non-academic thinking skills that involve managing oneself and available resources to achieve a How to study to achieve the highest quality of acquired goal [9]. They are necessary to develop successful work habits, knowledge? Modern pedagogical approaches have extended organization, time and materials management, project planning, classical learning of specific content and propose to learn general and mental control with self-regulation. Examples include skills applicable to specific needs through targeted practice. adaptability, time management, impulse control, collaboration, Chess is a good tool for this purpose. It allows the simultaneous organizational skills, decision making, and project management development of many skills that can be transferred to different [1]. Most definitions of 21st century skills include critical areas of life in the 21st century. Chess training includes several thinking with problem solving, creativity, and communication aspects and protocols of deliberate practice approach, which with collaboration. makes it a modern educational tool. The 21st Century Learning Model (see Figure 1) is a unified vision for learning to ensure student success in a world where KEYWORDS change is constant and learning never stops. It defines and Chess, 21st century skills, deliberate practice illustrates the skills, knowledge, expertise, and support systems students need to succeed in work, life, and society [2]. 1 MODERN PEDAGOGICAL APPROACH Christodoulou [7] points out that experts in all fields rely on extensive and detailed knowledge structures stored in their long- term memory. These structures, often referred to as schemas or mental models, enable the expert to encounter new problems and solve them with ease. How can one reach the highest level of this knowledge, which can be applied to various areas of life? 1.1 Deliberate practice approach Modern pedagogical approaches favor the generic competencies and, in particular, deliberate practice over memorization, which focuses on specific knowledge and regular practice. The main problem with the generic skills approach is that the skills learned under this term are usually specific rather than generic. The goal is to teach the desired skill directly, with activities reflecting the Figure 1: 21st century skills with learning model desired end product. However, the educational process should develop general skills such as problem solving or critical thinking that can be applied in many different areas of life. 1.3 Obstacles to instructing and assessing 21st Deliberate practice is an appropriate approach for this purpose. It Century skills means practicing with a clear awareness of the specific The challenges and considerations for assessing 21st century components of a skill we want to improve and knowing exactly skills that the educational community must resolve are: poorly how to improve it. While regular practice involves mindless defined constructs, limited understanding of how students repetition, deliberate practice requires focused attention and is develop these skills over time (e.g., learning progressions), lack done with the specific goal of improving performance. of understanding of the interactions and relationships among the Deliberate practice is a way to improve a skill through a series of various skills, the appropriateness of separating skills from planned activities, reflection, and collaboration. This includes content and context. The 4 C's are not adequately addressed in setting personal goals, targeted practice and feedback, observing the core curriculum [11]. Can chess in education be the solution? and discussing lessons, and monitoring one's progress [21]. 1.2 21st Century Skills 2 EDUCATIONAL VALUE OF THE 21ST What should be the content of modern learning? The experts' CENTURY CHESS answer is: "21st century skills, sometimes called "executive Although the game of chess is over 1500 years old, it seems relevant to address the challenges of modern centuries. Chess, a 181 highly motivating and potentially competitive game, can be a chess player is a self-determined, persistent problem solver who valuable tool for developing many of the 21st century skills, as is ready to face any challenge [19]. Mikhalchishin [22], a top they are central factors in successful play. These skills are needed chess grandmaster and one of the best coaches, describes the by future citizens who must be adaptive problem solvers. In the thinking and decision making of chess players on the three levels: study by Chitiyo et.al. [6], 62 teachers assessed eight skills of 1,502 students in the chess group and 634 students in the non- 1. Based on precise acquired knowledge (e.g. openings) chess group. Teachers rated higher improvement in problem- 2. Logical reflection (calculation of variants) solving skills (3.9 versus 3.5 out of 5) at all grade levels among 3. Intuitive decision (gut feeling/implicit decision based on a the chess players. Students in the chess group were rated as better large knowledge base) problem solvers (78%), critical thinkers (73%), and strategic thinkers (75%). Students in a chess class reported working harder Jelen [17] defines the process of move selection with the on their schoolwork (82%), enjoying learning more (76%), and following steps: now being able to solve the most difficult problems when they try (80%). Results from the Chess in Education program (CIE) 1. After each opponent’s move, before each intended move, [8] showed increased enthusiasm for learning, an increase in sometimes even during variant calculation, a chess player overall knowledge, an increase in student attendance, an increase asks himself: Which move is a threat and over which in self-confidence, an increase in parent involvement, etc. important squares has the opponent gained control? What According to the studies presented in McDonald [20], chess has the move overlooked or given up control of? develops several generic skills such as concentration, patience 2. The evaluation of the position. and perseverance (with careful and concentrated observation), 3. Based on the evaluation of the position, the chess player visualization (imagining the sequence of moves before they makes a plan for further play. actually happen), planning (thinking a move in advance; in chess 4. On the basis of the evaluation and the plan, the player you must think first and then act. There should be no selects all candidate moves that should be considered in choosing the best move. impulsiveness. You need to see the possible consequences of 5. He calculates all the candidate moves and makes an your actions), weighing options (you do not have to do the first evaluation of each move based on the calculations. thing that comes to mind. There are other options as well. We 6. He selects the best move, i.e. the move with the best need to consider them), accurate analysis, systematic, scientific evaluation. When he re-checks it, the move can be played. thinking, precision, logical reasoning, abstract thinking (a chess player needs to see the big picture), curiosity. A chess player must also learn to manage time (he plays against the clock or against a time limit set by the coach, with rapid chess Sala and Gobet conducted a meta-study [24, 25] to verify the being the most challenging). He not only knows mathematically validity of several previous studies showing the beneficial effects the difference between five and ten minutes, but he also knows of chess and its transfer to other domains. They concluded that how these different periods of time feel. Chess players need to chess practice enhances some general cognitive skills, such as control impulses (holding back a move until both players' short- and long-term memory, executive functions, positions have been assessed, and considering cause and effect metacognition, visuospatial skills, critical appraisal, and general when making multiple moves) and organize materials (pieces on intelligence, which in turn improves students' academic the board) [4]. These are crucial skills for standardized testing performance. The analysis also showed a direct correlation situations, in which experienced chess players generally feel between the duration of the chess intervention and the magnitude more comfortable because they have a lot of practice in dealing of the effect. Costello [10] argued that the positive effects of with different amounts of time and stressful situations [8]. chess also depend on the appropriateness of the approach and the developmental period of the training (the best period is early 2.2 Creativity and flexibility childhood). Further, we present studies showing that chess Creativity is a phenomenon in which something new and develops some of the core skills of the 21st century, as shown in somehow valuable emerges, usually based on existing Figure 1. knowledge. In chess, almost every move is creative because no two games are the same, but a lot of chess knowledge is required. 2.1 Critical thinking and problem solving Former world chess champion Gary Kasparov said, " Chess is not Ferguson's systematic study [14] shows that chess was more about being an inventor with occasional flash of creativity, but effective in developing critical and creative thinking than any about being constantly innovative in your decision-making other "enrichment" activity he tested. An innovative, process." In chess, you also have to be flexible because the groundbreaking initiative to promote child development through position changes with each move and you have to adjust your chess in schools, Alabama Chess in Schools [1], similarly calculations and evaluations. Creativity adds a motivational note showed that critical thinking skills (measured with Cornell to the game of chess. As former world champion Kramnik said Critical Thinking Test) improved more for students playing chess " a chess player feels beauty when he succeeds in creating in the lower grades, but not as much in the upper grades. situations that contradict expectations and the rules, and when he manages to master that situation". According to Ferguson Chess players are problem solvers. Every day they practice [15], chess players are better than non-chess players in various solving chess problems. In this way, they develop not only aspects of creativity: fluency, flexibility, and originality (Figure analytical and problem-solving skills, but also perseverance to 2). find the right solution [3]. From a functional point of view, a 182 with it? What is my short- and long-term goal? Both the training process and playing require a high level and long lasting focus. In chess, one bad move may nullify 40 good ones. - targeted feedback, observation and discussion of lessons: evaluation of one's game is inevitable in chess. Moreover, each game of a chess player is carefully analyzed with the computer and the trainer from different aspects (chess, psychology, time management), so that a chess player can progress. - monitoring your progress: chess progress can be easily measured not only by the result, but also by the ELO Figure 2: Comparison of the increase in creativity aspects rating. This is an objective measure of the chess player's with chess players and non-chess players [15] strength. - modelling: if you want to advance, you need to learn 2.3 Communication and collaboration from the best. During training, a chess player must Chess emphasizes the importance of good sportsmanship and analyze hundreds of games of better grandmasters to respect for others. The nature of chess as a "gentleman's game" improve his performance. He must understand why they contributes to the development of positive interpersonal are so good - what do they do differently, how do they relationships as well as the formation of lifelong friendships think, etc. The process of recreating excellence is called based on a common interest, despite participation in modelling. It starts with finding a suitable expert who competitions. Chess also teaches players to listen well [23]. best fits your learning objective (e.g., the best player of a Many sales managers recommend the 80-20 rule of listening 80% particular chess opening). Then you should collect the of the time and talking 20% of the time. Educators from the relevant information (instructive chess games). As with Chess in Education (CIE) program [5] have found that chess deliberate practice the complex behaviors should first be creates a bond between students and teachers and improves the broken down into smaller meaningful parts (called classroom and school environment. In a year when the pandemic chunks), transparent components, following the rule "as and distance learning have caused many students to miss out on simple as possible and as complex as necessary"(e.g., the social learning that occurs during a normal school year, CIE chess motif). Any task is manageable if it is broken down can help overcome this deficit. Chess is also good socialization into sufficiently small parts and trained step by step from training. A study by McDonald [20] showed that introducing an early age (see Figure 3). These units are later chess to children with special needs reduced suspensions for recognized during play and recalled when deciding on misbehavior by 60%. the best move (see Figure 4). The player then organizes the patterns into logical, coherent structures (opening 2.4 Chess as deliberate practice tree), tests the effectiveness of the model (plays a game), if possible, reduces the model to the simplest form that Chess has been shown to be a powerful pedagogical tool by leads to the desired result (deletes irrelevant lines), making deliberate connections for transferring skills to other identifies the model to transfer the knowledge to other domains. Educators attribute the depth and breadth of chess's (similar) situations (understand in which position a effectiveness to many factors: Chess accommodates all learning particular motif works and where it doesn’t), evaluate the modalities and requires the integrated use of multiple skills model (results) and understands its limitations (where the simultaneously. In chess, there is an almost infinite variety and particular position and adequate move does not quality of problems to solve. There is always a problem that has correspond to the learned line) [13]. not been seen before. Some are simple, while others are difficult and complex. Chess provides immediate punishments and rewards for students' choices (during play) on the one hand, and requires the ability to delay the reward between practice time and play on the other. The game of chess causes players to develop a particular style of thinking in which they are always looking for more and different alternatives. Competition in chess increases motivation and mental alertness [18]. Chess training in many ways follows the protocol of deliberate practice: - Goal setting and focused practice: no chess training can begin without setting goals. Among the inevitable questions in chess training are: Will the training focus be on the opening, the middle game, or the endgame? Which opening will we train, and what do we want to achieve Figure 3: Step by step learning [26] 183 [8] Code to the Future. Retrieved on 13.9.2022 from: https://www.codetothefuture.com/parents/classes/chess) [9] Cooper-Kahn, J., & Dietzel, L. C. (2008). Late, lost and unprepared: A parents' guide to helping children with executive functioning. Bethesda, MD: Woodbine House. [10] Costello, P. J. (2013). The gymnasium of the mind: teaching chess in early childhood. Early Child Development and Care, 183(8), 1133-1146. [11] Dawson, P. & Guare, D. (2010). Executive skills in children and adolescents: A practical guide to assessment and intervention, 2nd Edition. New York: The Guilford Press. [12] Etkina, E., Brookes, D. T., & Planinsic, G. (2019). Investigative science learning environment. Morgan & Claypool Publishers. [13] Excellenceassured (2019). NLP Retrieved on 12.9.2022 from: https://excellenceassured.com/nlp-training/nlp-certification/nlp- modelling [14] Ferguson, R. (1986, April). Developing critical and creative thinking through chess. In report on ESEA Title IV-C project presented at the annual conference of the Pennsylvania Association for Gifted Education, Pittsburgh, Pennsylvania. [15] Ferguson, R. (1998). Study I. The ESEA Title IV-C project: Developing critical and creative thinking through chess. [16] Gobet, F., & Simon, H. A. (1996). Templates in chess memory: A mechanism for recalling several boards. Cognitive psychology, 31(1), 1- Figure 4: Example of a pattern in a chess position [16] 40. [17] Jelen, I. (2006). Delavnica: postopek izbiranja poteze. Ljubljana: Zavod Chess is an active teaching tool that leads to comprehensive za šolstvo. [18] Langen, R. (1992). Putting a Check to Poor Math Results. The Reporter. acquisition and development of higher skills, independent [19] Liaskos, L. (2019). 7 reasons you should hire a chess player. Retrieved on learning methods, comprehensive acquisition and higher 14.9.2022 from: https://en.chessbase.com/post/7-1-reasons-why-you- motivation to work. However, it is extremely important to create should-hire-a-chess-player [20] McDonald, P. S. (2008). The benefits of chess in education. A collection a classroom environment where students feel safe and accepted, of studies and papers on chess and education. Unpublished manuscript. respect diversity and differences, allow for differing opinions [21] Miami-Dade County Public Schools (M-DCPS): retrieved 14.9. 2022 https://mdcdhr.entest.org/pdf/PDE/Module%204- and criticism, and where mistakes challenge learning and %20Deliberate%20Practice.pdf collaboration. The way in which knowledge is acquired should [22] Mikhalchishin, A. (2018). Decision making process. Blitz chess and rapid follow the circular experiential learning from critical games [12] chess video. https://www.youtube.com/watch?v=uDW74zZvw- s&t=12s&fbclid=IwAR3cmokqohOYFSPPqIjWkizpGwJAps8kMdE3Yh in the following protocol: DzKVJxRaBjRnVrtzyfW20 [23] Rabin, E. (2019). Making a difference in Africa. en.chessbase.com. https://en.chessbase.com/post/making-a-difference-in-africa 1. Concrete experience: we first select a critical game, where [24] Sala, G., Burgoyne, A. P., Macnamara, B. N., Hambrick, D. Z., Campitelli, G., & Gobet, F. (2017). Checking the “Academic Selection” argument. we encounter problems or lack of understanding. Chess players outperform non-chess players in cognitive skills related to 2. Reflective observation: analysis of thought processes and intelligence: A meta-analysis. Intelligence, 61, 130–139. experiences during the game (written down immediately [25] Sala, G., & Gobet , F. (2016). Do the benefits of chess instruction transfer after the game) together with a time consumption analysis. to academic and cognitive skills? A meta-analysis. Educational Research Review, 18, 46-57. 3. Theoretical analysis: chess-psychological analysis of [26] Zaretsky, V. (2019). Internal material. critical games after the tournament based on data from chess books and other sources of knowledge. 4. Active experimentation: in unimportant games we can test new insights, ideas and skills gained in earlier stages of learning. Last, but not least, the learning environment is a game, but the effects can be transferred to other areas. Studies and projects on chess as an educational tool are underway, one of which is the project CGS: Chess: a Game to be Spread in schools, funded by Erasmus+ and ECU. REFERENCES [1] Alabama State Department of Education - ASIE (2016). Gifted Standards and Student Outcomes. Retrieved on 12.9.2022 from: (https://chessplus.net/research/the-alabama-school-chess-initiative/) [2] Battelle For Kids. Retrieved 13.9.2022 from https://www.battelleforkids.org/networks/p21 [3] Burgoyne, A. P., Sala, G., Gobet, F., Macnamara, B. N., Campitelli, G., & Hambrick, D. Z. (2016). The relationship between cognitive ability and chess skill: A comprehensive meta-analysis. Intelligence, 59, 72-83. [4] Chess in education. Retrieved on 12.9.2022 from: https://chessineducation.org/21st-century-skills/ [5] Chess in education. Retrieved on 12.9.2022 from: https://chessineducation.org/life-skills [6] Chitiyo., G:, Zagumny, L., Akenson, A.B., Littrell, M., Davis, K., Besnoy, K., 2019. Teaching with Chess: Exploring the Relationship between Chess and Student Learning Outcomes. ACIS Years 1-3 Report. [7] Christodoulou, D. (2017). Making good progress? The future of assessment for learning. Oxford University Press-Children. 184 Karma and Dharma : Two ways of human living Joonho KIM Department of International Relations Tokyo International University Matoba 1-13-1, Kawagoe, Saitama, Japan toko9a@gmail.com ABSTRACT Karma is causality beyond life and death. One may suffer the effects in this paired concept and set it as the central principle of life. life due to the causes in the previous lives. Dharma is the principle of In this paper, I analyze the two concepts with a focus on the relation overcoming this karma. This article tries to make clear the structure and between the two, and categorize two individual or social logic of life process of karma. And through understanding these two concepts of living a concerning the overcoming of the ego. life, one may find a solution for self-development. 2. KARMIC LOGIC KEYWORDS 2.1 Reincarnation as the precondition of karma karma, dharma, reincarnation, causality, karmic structure, karmic process If we try to understand the karmic logic, we must recognize the reality of reincarnation1 of the human being as its precondition because karma 1 INTRODUCTION: TWO CONTRASTING develops its logic through rebirth. You should suffer, but you must not know CONCEPTS IN THE RELIGIOUS AND SOCIAL the reason why. That which connects this gap between ontological CONTEXT Grenzsituation and epistemological agnosticism is rebirth; that's why no Indian philosophy is abundant in religious concepts and thoughts which can reincarnation, no karma. be applicable to contemporary human society. Above all, karma and In the 18th century, Swedenborg made a significant contribution to the dharma are essential and have many implications for human life. These understanding of the afterlife based on Christian mysticism. In the early concepts are used in broader religious, social, and cultural environments 20th century, Evans-Wentz made a decisive interpretation of death and with the background, not only of Hinduism or Buddhism but also of rebirth by introducing the Tibetan Bardo Thodol [2]. Christianity or Islam. Bardo Thodol's process is precisely described as below, in modern The word karma has been understood as fate and has become a general and terminology: “The first contest of the soul in each incarnation is other souls popular term in the West as well as in the East. Karma is understood as the seeking rebirth. With the union of sperm and ovum to begin the formation law of cause and effect. But this law has continuity beyond life and death, of a new human body, a flash of light appears in the astral world, the which is reincarnation. Sufferings resulting from sin in previous lives, called heavenly home of souls between incarnations. That light transmits a pattern karma, are almost synonymous with fate. But the term karma originally which attracts a soul according to that soul's karma- the self-created means action in Sanskrit. And at the same time, it signifies the result of the influences from actions of past lives. In each incarnation, karma works itself action. It hints that human activity intrinsically includes negative characteristics. 1 The process of reincarnation has been described in not a few mystical religious books. And recently, Dharma is an ethical concept, and it has been developed and formulated as a the reality of reincarnation has been reported by those who have extraordinary talents in this field. But moral ordinance, especially in the Buddhist doctrine, which is not based it is still terra incognita, the scientific test of which is not completed. Science may criticize this issue as upon the idea of God. The concept of dharma is related to the righteous unscientific or superstitious because it does not know much about that. But that means that science is value criteria, law, and religious symbols. Historically, it has been used as not so much advanced as to understand that. the name of Buddhist saints, idol, and in the Indian national flag. Socially Evans-Wentz mentioned a similar point: Thus while the Occidental may not question the validity of and spiritually, dharma signifies the ideal law requiring men's ideational this law of cause and effect when applied to physics, he does question it when applied to psychics, he lives. does question it when applied to universally to psychics. In assuming such an attitude, the Occidental, There are so many references with a profound analysis of each concept in in the eyes of the Oriental, ceases to be scientific, inasmuch as he fails to see that in any complete the field of humanities, but I could not find one that considers them as a science of man the physical cannot be separated from the psychic ([3], p. 47). 185 out partly through hereditary forces; the soul of a child is attracted into a Reincarnation line family in which heredity is in conformance with the child's past karma. Many souls vie to enter this new cell of life; only one will be victorious (in 1 a 2 a the case of a multiple conception, more than one primal cell is present) ([4] A B C p.7).” This shows once more again that reincarnation is deeply related to karmic Figure 2: Causal reincarnation law. 2.2 The structure and process of karma When 1 a transited to 2 a in the next life, a more complicated causality Many people in the East Asian social culture often say, when they suffer appears. 1 a died and is reborn as 2 a , because he adheres to the seriously from something beyond their capability: What sin had I physical world of A , B , C …. committed in the previous life? They believe that there must be some reason 1 2 a → a transition (=reincarnation) is performed with the ontological for this hardship the reason why they don't know. Karma is usually paired identity of 1 2 a = a . Across the reincarnation line, 2 a has the same with reincarnation. If there is no reincarnation, there is no karma. The identity as 1 a , so that the result of 1 B → a is succeeded as the hardship, the cause of which one can understand, is no karma. The essence 2 B → a . 2 a succeeded B as well as 1 a . This reincarnative identity of karma lies in the continuity of being beyond the lives by which one is karma. transforms oneself into another identity. B is applied to 2 a , because 2 a is 1 a . Stimulated by B , 2 a 1 a in the previous life is 2 a in this life (Figure 2). What connection reacts, and produces C . This triangular relation 2 B → a → C is does the identity of 1 a in the last life have with that of 2 a in this life? simplified as B → C . So the A → B → C causality continues. Why should 2 a pay the price of 1 a ? This process is based upon two structures: the causal triangle and the Accept the premise that the suffering in this life is due to the sin in the incarnative identity triangle. 1 a − A− B forms the causal triangle and previous life and suffer the pain: is this the right way of living? Should we 1 2 B − a − a forms the incarnative triangle. In the former, 1 a is make redemption for the debt we can't remember whether we borrowed it influenced by A → B causality. In the latter, B is applied evenly to or not? It is a mental pressure that makes us compensate for the sin, which is 1 a and 2 a on the ground that not directly linked to I as it is now in this life. Original sin in Christianity is 1 2 1 2 a = a  B → a = B → a something similar to this religious, psychological pressure. Humankind suffers the burden that Adam and Eve had made. Human being must suffer Here by B , an existential transformation of 1 2 a → a is mediated, and in this life or be born again spiritually to compensate for this original sin. the action 2 B → a brings about the reaction 2 a → C , which gives Karma forms a unique worldview by merging several factors: the casual process B → C , which can be called karmic causality. And causality+action +feedback+reincarnation. 2 B → a → C forms the karmic causality triangle. The unique karmic worldview begins with two categories (Figure 1): This resulted in two processes: ontological continuity of the actor (ego), Elements: actor( a ), object of the action( A ), the result of action( B ) 1 2 n a → a → → a → , and the causal continuity of the object of the Function: action( a → A ), causality relation( A → B ), feedback of action A → B → → Z → (Figure 3). the result to the actor( B → a ) a 1 a 2 a 3 a n a Continuity of the ego beyond life and death A B Continuity of A B C D Z the cause and effect Figure 1: Simple causality triangle Figure 3: Truss structure of the karmic bridge a is an actor (ego) who acts A , which results in B , and this B The truss has been traditionally thought to be the most robust bridge returns its effect to a . Action is feedbacked to the actor through causality, structure. The continuity of the ego line and that of the cause and effect line that is, cause and effect. Here A is the cause and B the effect. So this go side by side forever in Figure 3. This is the basic concept of karmic triangle shows the action of a and its result to a , and the cause-effect structure and process. In Figure 3. the truss of two triangles solidifies the relation between A and B . karmic structure, from which only few can escape. 3 DECONSTRUCTION OF KARMA How can we deconstruct this karmic truss? It lies in dismantling the process 186 and the structure of karma, in other words, in disassembling the triangles characteristics of karma include the process of the feedback of the result to and, as a result, in removing the causality line and the ego line. the actor. One's action necessarily returned to oneself: this is the karmic The first one, which is the removal of the causality, is basically the causality. The problem is that this consequence of the action is applied to a discontinuation of the reaction. The most effective response to nullify this person (ego) beyond life and death. If the consequence is happiness, that's cause-effect relation is to stop the reaction to the evil cause. good, but if it were hardship, then the ego suffers without knowing the Jesus said that "You have heard that it was said, 'Eye for eye, and tooth for reason why. tooth.' But I tell you, do not resist an evil person. If anyone slaps you on the Let's suppose one ( 1 a ) goes through A → B → C with the identity right cheek, turn to them the other cheek also (Matthew 5:38-39). This is not of 2 a in the next life (Figure 3). He who did A is reborn with B , a masochistic behavior but a call for the cessation of the continuity of action and suffers from the painful reality B . He, who cannot understand the and reaction based upon the egoistic causality, "by yourself." causality A → B , shouts' why?.' This 'why?' is karmic fate. He said again: "You have heard that it was said, 'Love your neighbor and The name of the game through incarnation is karma, and the rule of the hate your enemy.' But I tell you, love your enemies and pray for those who game is that the actor must accept his own action's result, which he doesn't persecute you, (Matthew 5:43-45). The continuity of revenge brings about a know the meaning of why beyond life and death, therefore beyond his vicious cycle in human society. understanding. The action was free, but the result is binding. The second one regarding the removal of the ego line is the other aspect of Then should all the hardships in this world be justified? the first one. a is bound to the causality of A → B , because he What he did to others returns to himself. In effect, he did it to himself. expects B , which is the result of A . In the background of action and Other's suffering cannot be felt unless he himself becomes that other. He reaction exists ego. According to various religious scripts, such as himself, who became that other through reincarnation, experiences that Buddhist's or Hindu's, the feedback B → a is said to be due to a 's feeling, not knowing the reason why. If the state in this world is the result of adherence to B (Figure 1,2,3). B is feedbacked to A when a the action in the previous life, then this state is justified as it is, and there is requires B as the result of A . Where there is ego, there is attachment to no need to sympathize with the suffering, and one should accept one's the result of an action. By expecting B , a accepts the causality of suffering as it is. A→ B , that is, the feedback from B . If a doesn't desire B , then Is this the realization of justice beyond life and death? Or a dextrous trick of causality does not function. a → A is all. This is an orientational duty. God to make us feel the same feeling that we made others feel in our There is no feedback B → a . previous lives. Through the indifferent viewing of one's suffering, just like Bhagavad Gita teaches the pursuit of pure action as its essential lesson, others', we can get out of that suffering. Then we may conclude that karma's which can be expressed as below: Do your duty without expecting the significance lies in the realization of justice beyond life and death reward for it. To attach to the result of the action is to damage the In that sense, karma is dharma, dharma is karma, and the meaning of life significance of the action in its pure form. If one attaches too much to the lies in enjoying the game of karma through repeated reincarnation. result of an action in the pursuit of ego-centric interest, he loses the significance of the action as a duty. Duty is not an investment for the ego's 4 FROM KARMA TO DHARMA profit; it is a dedication to something beyond the ego. By performing duty There are two ways of living; karmic and dharmic (Table 1), in other words, beyond ego, you behave as the Absolute. causal or orientational. About karma, much has been said in the previous A dutiful action means a performance denying the spillover to the ego. Is part. The dharmic way of living is the antithesis of the karmic way. there any action that ends in itself? One of the actions, which is not bound to Table 1. Characteristics of karma and dharma the result of the action, is meditation practiced with the absolute orientation. Ontological Motivation Principle of Behavioral Geometrical Meditation means the orientation in general towards the Absolute, through characteristic of action behavior characteristic characteristic which one is rerecognized. By this recognition, an orientational action that ego-centric triangular Karma ego-centric causal attachment does not regress to oneself is possible in the consciousness as the act of interest causality Absolute, not ego. Therefore, meditation is said to be the best way of Dharma Self-centric duty teleological orientational linear escaping from karmic life and the ultimate expression of dharma. Meditation brings about the collapse of the ego, and the equality of ‘I = The essence of dharma lies in orientation. The orientation means being apart other’ appears in the orientation towards the Absolute. from ego-centric existence. Karma is causal, dharma is teleological and Thirdly, karmic destruction may be possible by fully experiencing karma, orientational. Dharmic action is done by deciding the deed based upon the which can be called karmic justice. fundamental value criteria, which makes the actor free from the result of the As was said previously, karma begins with the action. Here the 187 action. This can be interpreted that if one is free from oneself, then he is 5 CONCLUSION: THE SUN AND THE SHADOW freed from the result of his action. Overcoming ego by turning to the right direction is the essence of dharmic In a → A , dharma has the mono-linear relationship between the actor life. a and its orientational purpose A (Figure 1). Here A is for A , When you have the sun at your back, you see the shadow of yourself. And whereas in karmic triangular structure, A is for B . A is relativized you find it impossible to erase your shadow on the ground. The body is ego, to B . a has the direct object A and indirect object B . B is and the sun is dharma. The shadow is the reflection of the ego appearing the purpose of A and at the same time the result of A . This mixed and when you defy the sun. Shadow is pain and hardship. Shadow is karma. To complicated relation between a and B by way of A makes a see the dark side of ego is suffering. attached to B , and B rules a . The unfulfilled desire of 1 a is Being against the sun visualizes the dark side of ego, and however hard we attached to 2 a in the next life. try to erase it, it does not disappear. The only way to erase it is to orientate You reap as you sow the seed. This is a universal truth. If you follow the sun again. The sun is dharma, the righteous direction. The shadow dharma in the original cause, receive the dharmic result. The dharmic disappears of itself. The ontological orientation deletes the epistemological orientation of sowing the seed brings about salvation from karma. Karma is shadow. Orientation to dharma makes karma disappear naturally. The the result of a dharmic response to the individual, egoistic claims which shadow itself ceases to exist. Therefore the direction is the ultimate solution. despise the universality. When one resolves to stand up from the shadow and proceed to the sun, A → B darkness dissolves. If A is dharmic, then B is happiness. If A is ego-centric, then B We can make some analogical interpretations of karmic or dharmic action is unhappiness. Karma and dharma are closely related. Dharma functions as in relation to the international order and human society. Therefore, the cause setting of karma. We are asked every moment: Self-centered life overcoming a small ego for the universal Self can be adapted to or ego-centered life? An orientational act of a causal act? international society. We are witnessing continuous action, revenge, and We can do the cause but cannot control the result. The result is decided reaction, due to the historical and political causality. We must get out of this following the cause, and we cannot but accept it. That's why the international karma attributed to the national ego towards the global dharma. righteousness of the cause is salvation. The idea that the best way to get out Right direction from ego to Self, this will put an end to the karma of of hardship is to get out of the ego, to where the hardship returns, is logical humankind, individually, socially, and globally. and fundamental and rational or even utilitarian. And it goes without saying that dharmic orientation is the essence of The universal expression of karma is dharma. The individual application of education, which can be applied to children as well as adults. dharma is karma. So that the universal orientation beyond individuality is Until the 16th century, Ptolemaic theory prevailed. According to that, the sun the dharma of overcoming karma. It's a matter of the whole or the moves around the earth. This planetary ego was justified by religious belief. individual. And then heliocentrism proved to be true. Not that the sun (Self) turns Karmic law is applied mathematically beyond life and death, which is a around the earth (ego), but that the earth (ego) turns around the sun mystical ontology. Reincarnation is the ultimate expression of ontology. (Dharma); this Copernican turn must be introduced to our lives to overcome When the causality continues with reincarnation, it is transformed into the karmic bondage. ontological issues from logical, epistemological issues. Therefore, the karmic idea resulted in the question 'who am I ?'. Karmic shout 'why am I REFERENCES suffering?' is, in turn, transformed into 'who am I that is suffering?' and [1] Brunton, Paul and Munagala Venkataramaiah (1996) Conscious immortality: beyond 1 a and 2 a , an approach towards the real Self begins. This Conversations with Ramana Maharshi, Sri Ramana Asramam. transformation of question from 'why?' to 'who?' is the dramatic turning [2] Evans-Wentz, W. Y. (1927) The Tibetan Book of Death, Oxford University Press. point in the long journey of karma because the wanderer in the darkness [3] Evans-Wentz, W. Y. (1958) Tibetan yoga and secret doctrines, Oxford University Press. asked the right question to be answered, that is, the right step towards the [4] Yogananda, Paramahansa (1996) God Talks With Arjuna: The Bhagavad Gita, Self light. At last, reincarnation begins to lose its significance2. Realization Fellowship 2 Ramana Maharshi says: the body is born again and again. We wrongly identify ourselves with the body, and hence imagine we are reincarnated constantly. No. We must identify ourselves with the true Self. The Realised One enjoys unbroken consciousness, never broken by death — how can he die? — or by birth. Only those who think ‘I am the body’ talk of reincarnation. To those who know “I am the Self” there is no rebirth. Reincarnations exist only so long as there is ignorance. There is no incarnation, either now, before or hereafter. This is the truth (Talk 363) [1]. 188 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek E Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume E 15. mednarodna konferenca o prenosu tehnologij 15th International Technology Transfer Conference Urednika / Editors Špela Stres, Robert Blatnik http://is.ijs.si 10.–14. oktober 2022 / 10–14 October 2022 Ljubljana, Slovenia 189 190 PREDGOVOR / FOREWORD Spoštovani generalni direktor direktorata za znanost dr. Tomaž Boh, spoštovani direktor Instituta »Jožef Stefan«, prof. Boštjan Zalar, spoštovani udeleženci, lepo pozdravljeni in dobrodošli na 15. Mednarodni konferenci za prenos tehnologij. Today we are gathered technology transfer experts, researchers, students and post-graduate students with entrepreneurial ambitions, established and future entrepreneurs, investment managers, innovators and also representatives from governmental institutions and policy- making organizations. Najlepše se zahvaljujemo soorganizatorjem ter drugim partnerjem, ki so podprli konferenco. Začetni del konference s pozdravnimi nagovori bo v slovenščini, nadaljevali pa bomo v angleščini. Part of the participants is here in the hall at the Jožef Stefan Institute, the other part is with us on Zoom. The event, except the pitch section, is being recorded. Its parts will be made public in the next days. The welcome addresses will be held in Slovenian, later sections will be in English. Po pozdravnih nagovorih bo spoštovani gost Michele Neu predstavil kako sodeluje s podjetji The French Alternative Energies and Atomic Energy Commission. Sledilo bo tekmovanje raziskovalno-podjetniških ekip, ki se potegujejo za naziv najboljše inovacije iz javnih raziskovanih organizacij, nato bo razglasitev nagrade Svetovne organizacije za intelektualno lastnino WIPO IP Enterprise Trophy. Sledili bodo predstavitve odličnih projektov slovenskih znanstvenikov, razglasitev WIPO nagrade Medal for Inventors ter raziskovalni prispevki o prenosu tehnologij in intelektualni lastnini. Vzporedno bo izvedena še sekcija o povezovanju Instituta s šolstvom. Program je, kot vidite, res bogat, saj se dotika množice aktivnosti, pri katerih smo v pisarnah za prenos tehnologij osrednjega pomena. Organizacijski odbor 15.ITTC / Organizing Committee of the 15.ITTC 191 ORGANIZACIJSKI ODBOR, PARTNERJI IN SPONZORJI / ORGANIZING COMMITTE, PARTNERS AND FINANCERS The main organizer of the 15 ITTC Conference is Jožef Stefan Institute. The organizing committee: Dr. Špela Stres, MBA, LLM, Jožef Stefan Institute Robert Blatnik, M. Sc., Jožef Stefan Institute Marjeta Trobec, M. Sc., Jožef Stefan institute Urška Mrgole, Jožef Stefan Institute The scientiffic programme committee: Scientific papers on technology transfer and intellectual property Niko Schlamberger, President of Slovenian Society INFORMATIKA Doc. Dr. Tamara Besednjak Valič, Faculty of Information Studies in Novo Mesto Prof. Alexandru Marin, University POLITEHNICA of Bucharest Co-financing The event is organized and co-financed in the frame of the Enterprise Europe Network (GA project number 101052776). 192 Collaboration The 15th ITTC Conference is organized in collaboration with the International multiconference Information Society (IS2022). Partners THE 15th ITTC CO-ORGANIZERS Slovenian Research Agency - ARRS Slovenian Intellectual Property Office Lithuanian Innovation Centre Camera di Commercio Industria Artigianato e Agricoltura di Torino 193 THE PROGRAMME PARTNER Slovenian Association of Technology Transfer Professionals THE ASSOCIATED PARTNERS Faculty of Information studies National Institute of Biology University of Ljubljana National Institute of Chemistry THE PROMOTION PARTNERS Center odličnosti za integrirane pristope v kemiji in biologiji proteinov 194 Razvojni center Novo mesto RRA Koroška – Regionalna razvojna Agencija za Koroško Inkubator Sežana ZRS Bistra Ptuj SIS EGIZ Namaste – Centre of Excellence 195 ACKNOWLEDGEMENTS The editors and organizing committee of the Conference would like to express cordial thanks to all who helped make the 15th International Technology Transfer Conference a success. We would like to acknowledge the valuable contributions to the members of the SCIENTIFIC PROGRAMME COMMITTEE: • Niko Schlamberger, President of Slovenian Society INFORMATIKA • Doc. Dr. Tamara Besednjak Valič, Faculty of Information Studies in Novo Mesto • Prof. Alexandru Marin, University POLITEHNICA of Bucharest 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: • Alexandre Massart, co-founder and director, Blend Ventures, • Jurij Giacomelli, Investment Manager, META Ingenium, • Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission, • Nina Urbanič, Adviser for equity investment monitoring and reporting, Slovene Enterprise Fund, • Vladimir Jančič, CEO, Publikum Korpfin, 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 WIPO EVALUATION COMMISSION: • Alojz Barlič, Slovenian Intellectual Property Office (SIPO) • Nina Urbanič, Slovene Enterprise Fund • Christoph Kempf, IPEK – Institut für Produktentwicklung, Karlsruher Institut für Technologie (KIT), for their evaluation and selection of the awardees of the WIPO IP ENTERPRISE TROPHY and WIPO MEDAL FOR INVENTORS. Special thanks go also to Slovenian intellectual property office for their help with the organisation, communication with WIPO and presence at the Award ceremony. We thank also to ARRS for their presence at the Award ceremony and WIPO for their video for the Award ceremony. 196 Technology transfer offices as a facilitator of knowledge triangle integration in the knowledge valorisation era: focus group discourse analysis * Ivana Vuka† Nikola Balić Andras Havasi Marie Mifsud Leandra Vranješ Department of Department of Corporate Corporate Markić Science and Science and Research and Research and Department of Innovation, Innovation, Knowledge Knowledge Physics Technology Technology Transfer Transfer University of Transfer Office Transfer Office University of University of Split Faculty of University of University of Malta Malta Natural Sciences Split Split Msida, Malta Msida, Malta Split, Croatia Split, Croatia Split, Croatia andras.havasi@u marie.mifsud@ leandra@pmfst. ivana.vuka@uni nikola.balic@un m.edu.mt um.edu.mt hr st.hr ist.hr ABSTRACT / POVZETEK stimulate its integration. Furthermore, TTOs are in the best position when it comes to the new European commission Knowledge triangle integration, together with knowledge knowledge valorisation policy aiming to transform the excellent valorisation era, positions technology transfer offices (TTOs) as research results and data produced in Europe into sustainable a central point in transforming research results into the products products and solutions for the benefit of society and economy. and solutions for the benefit of economy and society. The present TTOs, as intermediary organizations, are in a position of creating study was qualitative focus group analysis to explore issues and a channel for knowledge valorisation by improving the obstacles in communication, how they network and keep conditions for knowledge and technology transfer and serving as relationships with different stakeholders. Analysis showed that the first contact point for industry and researchers in the the majority of TTOs faced similar problems when it comes to commercialization process. Through the networking, mentoring, the communication and networking such as lack of resources and low interest or skipping TTOs in the innovation lifecycle. coaching and best practices exchange TTOs can also boost Showcasing success stories and storytelling are suggested as best research innovation potential [3]. tools to attract new beneficiaries in the knowledge triangle while Information flow and good communication are one of the key cultural change and top-down approach are key to gaining more enabling factors for building sustainable and long-term impact and success. cooperation and achieving social and economic benefits of knowledge triangle integration [2]. However, successful and KEYWORDS / KLJUČNE BESEDE effective communication largely depends on mechanisms of Technology transfer office, knowledge triangle, knowledge information, promotion and dissemination in addition to the valorization, focus group commercialization activities and setting ground for new collaborations [4]. Traditional activities to foster collaboration between universities and businesses are usually focused on 1 INTRODUCTION networking and matchmaking events. Recently, an ecosystem The knowledge triangle involves different stakeholders with approach including co-creation and open innovation platforms various interests trying to cover three main missions of higher was introduced, to achieve more concrete outputs [5]. However, education institutions: education, research and innovation. TTOs face the challenge of having to communicate with various Knowledge triangle as a concept also tackles different audiences, which includes businesses, other research interconnections and relations within the knowledge triangle [1]. organizations, governmental bodies, external partners, NGOs Finding synergies and creating new opportunities is of immense and other decision makers that require distinct key messages and importance for the successful knowledge triangle integration [2]. a different approach. TTOs should be the main contact point and Technology transfer offices (TTOs) are in the center of the the facilitators of these partnerships, however, this is not yet as knowledge triangle and therefore are in the best position to relevant to the external partners. The contribution of a TTO is crucial and brings value [3]. ∗Article Title Footnote needs to be captured as Title Note † The aim of the present study was to better explore different Author Footnote to be captured as Author Note aspects and situations of TTO functioning, how they network and Permission to make digital or hard copies of part or all of this work for personal or how they form and keep relationships with different stakeholders. 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 Furthermore, the aim of the study was to detect main obstacles citation on the first page. Copyrights for third-party components of this work must and opportunities for better communication within the be honored. For all other uses, contact the owner/author(s). knowledge triangle. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 197 2 METHODOLOGY TTOs (1-2 employees), or very big with more than 15 employees (Table 1). The present study was qualitative focus groups discourse analysis and was done as a part of the EIT funded project called Table 1: Baseline characteristics of included participants CHIC - Creating holistic innovation capacity. Specifically, focus groups were part of the E3 initiative intending to explore issues and obstacles in communication within the knowledge triangle and empowering participating TTOs with the right communication strategies, tools, content and plan that could enhance their outreach. The three Es stand for three essential values: ENGAGE – networking and matchmaking people within the knowledge triangle by equipping TTOs with communication strategies that will; ENABLE – to raise their outreach and strength ties with stakeholders by giving them the right information and the necessary knowledge and actively participating in the knowledge triangle to EVOLVE – by facilitating interactions within the ecosystem and achieving higher engagement. The E3 initiative represents a set of activities and best practices with the main aim of driving the change for a more creative, constructive, collaborative and competitive innovation ecosystem. Focus groups were held during the international ASTP conference in Lisbon, from 18th till 20th of May 2022. Participants were recruited through a convenient sampling, after submission of an online registration form published on the Text analysis was done separately for each of the discussed official ASTP webpage. Prior to the focus group discussion, topics. Regarding the networking and KTT system participants participants were introduced to the CHIC project and the E3 stressed out the importance of organization of different events initiative and were asked to anonymously answer several serving as an opportunity to include different stakeholder groups. baseline questions using Mentimeter.com online tool. Furthermore, showcasing the success stories and storytelling was Participants were randomly distributed in 4 groups with an mentioned a number of times (Table 2). even number of participants discussing one of the following For the TTO added value services the majority of participants, topics: i) Networking and KTT ecosystem, ii) TT added value no matter how big or small TTO provides networking and activities, iii) Communication activities, iiii) Stakeholders matchmaking activities, access to finance and having teaching relationship. Each group participated in two discussions on activities on different topics, mostly innovation and different topics, to have the overall better input for each entrepreneurship, following managing of innovation funds and discussed topic. Each topic had one moderator, experienced in organizing specialized events such as hackathons (Table 2). the tech transfer field and one volunteer reporter taking notes When it comes to the communication activities participants during the discussion. Discussions lasted about 30 minutes after were very active in terms of defining main barriers in effective which the moderator changed the table and started the same set communication and suggesting the best tools to overcome those of questions with another group. barriers. Lack of resources in terms of time and people and Discussions were audio recorded and all participants were skipping the TTOs completely in the innovation ecosystem were asked to sign informed consent including recording the suggested as common barriers. Direct one on one communication, discussions. Efforts were made to elicit responses from all storytelling and having a system of awards or recognized participants. Recordings were transcribed for coding and all individuals at the university can help in communicating TTO participant information were anonymized to protect values (Table 2). confidentiality. Text analysis was done using Atlas.ti Web For the stakeholder relationship participants came up with the (version 4.0.0-2022-07-26) [6] while results were reported using conclusion that TTOs usually have very little impact on the COREQ 32-items checklist for qualitative studies [7]. policy making and funding mechanisms unless there are joint efforts on the i.e country level. Majority of the smaller TTOs are 3 RESULTS driven bottom-up while top-down approach is needed for cultural change and success (Table 2). Overall 40 participants were included in the focus groups, 27 female and 13 males, while each group had from 9 to 12 participants. Participants were from all over the world, mostly Europe, but also USA and South Africa (Table 1). Majority of participants, approximately 30% were from TTOs having between 6-10 employees, 22,5% were form TTOs having either from 3-5 or 11-15 employees, while rest were from very small 198 Table 2: Summary of topics with examples ACKNOWLEDGMENTS / ZAHVALA Authors would like to thank Petra Karanikić for helping in moderating focus group and Sara Lucija Dragičević and Tea Barbir for helping with transcripts. The research was funded under the EIT HEI Innovate initiative project CHIC-Creating Holistic Innovation Capacity. REFERENCES [1] Lassnigg, L. et al. (2017) Higher Education Institutions and Knowledge Triangle: Improving the interaction between education, research and innovation. Institut für Höhere Studien - Institute for Advanced Studies (IHS) (IHS Sociological Series, 118). [2] Meerman, A. and Kliewe, T. (2014) UIIN Good Practice Series 2014: Fostering university-industry relationships, entrepreneurial univeristies and collaborative innovation. [3] European Commission (2020) Research & innovation valorisation channels and tools: boosting the transformation of knowledge into new sustainable solutions. Available at: https://op.europa.eu/publication/manifestation_identifier/PUB_ KI0120038ENN (Accessed: 29 July 2022). [4] Smol, M. and Kulczycka, J. (2019) ‘Towards innovations development in the European raw material sector by evolution of the knowledge triangle’, Resources Policy, 62, pp. 453–462. Available at: https://doi.org/10.1016/j.resourpol.2019.04.006. [5] Katzy, B. et al. (2013) ‘Innovation intermediaries: a process view on open innovation coordination’, Technology Analysis & Strategic Management, 25(3), pp. 295–309. Available at: https://doi.org/10.1080/09537325.2013.764982. [6] ‘ATLAS.ti Scientific Software Development GmbH’ (2022). Available at: retrieved from https://atlasti.com 4 CONCLUSION (Accessed: 29 July 2022). TTOs can serve as valuable intermediaries in the knowledge [7] Tong, A., Sainsbury, P. and Craig, J. (2007) ‘Consolidated valorisation era and can be a first contact in establishing criteria for reporting qualitative research (COREQ): a 32-item networks and creating ecosystems. Showcasing success stories checklist for interviews and focus groups’, International Journal and storytelling are suggested as best tools to attract new for Quality in Health Care, 19(6), pp. 349–357. Available at: beneficiaries in the knowledge triangle. However, cultural https://doi.org/10.1093/intqhc/mzm042. change and a top-down approach are crucial for the healthy ecosystem and success that will be to the benefit of the entire society. 199 Proof of Concept typology: a method for classification of PoC activities according to a technology cycle timeframe FirstName Surname Linas Eriksonas FirstName Surname Department Name Technology and Innovation Department Name Institution/University Name Office Institution/University Name City State Country Center for Physical Sciences and City State Country email@email.com Technology (FTMC) email@email.com Vilnius, Lithuania linas.eriksonas@ftmc.lt ABSTRACT metaphorical expression) “Valley of Death”, which designates an initial stage in the technology life cycle where a gap between the The paper presents the results of an experimental study aimed at development of new scientific knowledge and the commercial creating a typology for the Proof of Concept (PoC) activities that development of new products can become fatal to new ideas [5]. could be more domain-specific and help practitioners to develop more effective PoC schemes. The typology has been developed 1.1 Study aims and research objectives by using real cases from the sample of the European Research Council (ERC) funded PoC projects. The automated subject The presented study has aimed to analyse one of the funding indexing helped to generate keywords that were matched with instruments that public funding institutions and, increasingly, technology descriptors from the Gartner Hype Cycles for also research and technology organizations plan, design, and Emerging Technologies to identify the timeframes for the employ to help scientific research-based inventions overcome funding gap according to a Hype Cycle. Accordingly, the PoC the funding gap and move closer to market. The funding scheme activities have been categorized into Pathbreaking PoCs, Mature in question is called the PoC programme or instrument, which PoCs and Catching-Up PoCs. The main characteristics have been provides on a competitive basis a certain fixed amount of money identified, and further steps for the typology validation presented. in the form of a grant, a subsidy, or an investment for the projects that need funds to validate and commercialize new technology. KEYWORDS The amounts can vary from ca. 20 to 60 thousand euros for initial PoC grants to more than 100 thousand for more advanced ones. Technology, innovations, finance, technological development, transfer of technology, typologies, research and development. Two research objectives have been established for this study. First, to create a method that could help categorize the PoC activities according to the logic of the technological life cycles. 1 INTRODUCTION Second, to test the approach on selected cases of the ERC PoC The quickening pace of technology developments has created an projects using publicly available data and create a typology of additional impetus to make the knowledge generation and PoCs providing the basic descriptors for individual PoC types. commercialization processes that lead to the creation of innovations faster, more agile and aligned with technological cycles. McKinsey predicts that more technological progress will 2 METHODOLOGY AND DATA come in the decade ahead than in a century [1], hence the urgency for assessing funding for upcoming technologies ahead of time. 2.1 Research design Any analysis of the PoC projects has a priori limitations due to It is a broad consensus among academics and practitioners [2,3,4] the confidentiality of the source material (let alone its availability that the main hurdle for increasing the generation and transfer of on a scale to allow a representative sample) and the complexity scientific knowledge resulting in intellectual property with a of the scientific, most often interdisciplinary, fields addressed. potentially high value to be realized in the emerging and existing Hence, the approach adopted for this pilot study on the typology markets is a funding gap. A gap stands between the need for of the PoCs has been based on using the following mechanistic funding to validate inventions on one side and the lack of market causal inference. If one can assume that the PoC activities can be demand for high-risk undertakings on the other. Both popular related to a specific technology life cycle timeframe, then one and academic literature often associate this gap with the term (a could categorize PoCs against the time expectancy of that cycle. Permission to make digital or hard copies of part or all of this work for personal or Three subsequent tasks have been formulated to meet these classroom use is granted without fee provided that copies are not made or distributed objectives. The first task was to explore, using the existing for profit or commercial advantage and that copies bear this notice and the full literature, the relationship between time and expectations that 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). define a funding gap and find a way of measuring a timeframe Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia for the current or perceived gap. The second task was to analyse © 2020 Copyright held by the owner/author(s). the actual cases of the ERC PoC projects (using the publicly available limited information about the project duration and 200 scope) and categorize them according to different timeframes of These and other academic contributions helped to map out the the expected funding gaps in each case. The third task was to rationale behind the PoC schemes and their current uses by describe the categories and discuss avenues for further research institutions from the perspective of a generic approach to the in validating the proposed typology and its uses for practitioners. R&D life cycle and innovation. The research completed to date helped to assess individual PoC instruments according to the 2.2 Data sets scope and size of funding, yet did not attempt to categorize PoCs. Three datasets have been compiled to complete the tasks. Below is a brief description of each. Due to the space limitation for this The academic interest in PoC schemes has mirrored the paper, the data has not been included in an appendix. They could institutionalization of this public funding instrument, which has be provided upon request or shared through a public repository. also been adopted by leading RTOs and universities. France has been the first to introduce PoC funding in its “Investing in the Dataset 1 in an Excel file contains details about 1225 PoC Future Programme” (2009-2011). The idea has been picked up projects covering the period from 2014 to 2023 [6]. The by other EU Member States (e.g., EXIST programme in following variables in the dataset have been used for analysis: Germany) before being adopted EU-wide. Since 2011 the project title, a project abstract, fields of science, and project start European Research Council has been running a PoC scheme as a and end dates. Dataset 2 in an Excel file contains the information top-up funding opportunity for the ERC grantees aiming to bring about the upcoming technology areas taken from the Gartner their research results closer to market. From 2011 until June 2022 Hype Cycles for Emerging Technologies for the period from ERC funded 1469 PoCs (the success rate stood at almost 30%). 2011 to 2022 (altogether 425 entries, of which 134 are unique ones); all accessed through Google search. The following At the same time, the research and technology organizations variables in this dataset have been used for analysis: technology (RTO), both public and private, have started experimenting with descriptor, year of appearance on a Gartner hype cycle, the different approaches to foster academic entrepreneurship and minimum and the maximum years remaining to reach “the commercialization by adopting a mixture of traditional product Plateau” (to be referred to as a market maturity) on a hype curve. development methods such as stage-gate processes and agile processes taken from lean management and startup development. Dataset 3 is a subset of Dataset 1 in an Excel file containing CEA, TNO, SINTEF, Tecnalia and other major RTOs have set information about 10 PoCs projects covering the period from up internal PoC schemes to provide extra funding and additional 2016 to 2022. The cases for analysis were selected from the first support (including mentorship and guidance with industry 300 search results filtered down by the scientific fields of expertise) to the selected teams of their researchers with credible “engineering and technology/electrical engineering, electronic ambition to create a viable commercial product or a spin-off [12]. engineering, information engineering/electronic engineering”. The following variables in the dataset have been used further: project title, URL (a reference to the project description on the 4 ANALYSIS Cordis website), five most relevant keywords generated from the 4.1 Timeframes in the technology life cycles abstract using a web-based automated subject indexing service Finto AI (see below), project start date, the matching emerging The literature shows that a funding gap for PoC activities can be technology descriptor, the earliest and the latest year for reaching expressed and measured in terms of technology or investment a market maturity (the latter two taken from Database 2). readiness levels, time-to-market, person-months, and other performance indicators [7, 8]. However, for simplicity, this study uses a single indicator: a PoC timeframe. A PoC timeframe is a 3 CURRENT STATE OF RESEARCH AND period from the start of the PoC activity until the market maturity DESIGN OF PoCs of the relevant emerging technology field. A mature market is considered a stage where the growth rate slows to almost zero. The existing PoC schemes, their design and their basic characterisation, have been recently quite extensively analysed According to the generally accepted definition, a funding gap is [7-11]. Bataglia et al. (2021a) analysed the operationalisation of the amount of money needed to fund the ongoing operations or PoC instruments in a selected higher education institution and future development of a business or project that is not currently looked at different enablers that contribute to implementing funded with cash, equity, or debt [13]. Funding gaps can be PoCs. Further, Bataglia et al. (2021b) compared different PoCs covered by investment from venture capital or angel investors, and analysed the determinants influencing commercialisation equity sales, debt offerings, bank loans, and public funding outputs in these cases. Munari and Toschi (2021) compared the programmes. Public and private investments attracted to address valorisation outcomes of those obtained with a PoC grant to a a particular funding gap are driven by various factors, of which group of projects that applied to the PoC scheme but were not the expectations about the potential of realising a substantial funded. The authors confirmed that the instrument was effective value out of the results of the R&D activities are of prime in the early valorisation of scientific discoveries. Munari and importance. Hence, one can argue that a funding gap is a function Wessner (2017) conducted an in-depth analysis of the ERC PoC of the perceived and experienced trajectory of the technological programme to understand better how well the PoC scheme cycle associated with technological breakthroughs and markets. contributes to maximising the value of ERC-funded research by facilitating its commercial and social potential development. 201 A hype cycle model introduced by Gartner Inc. in 1995 has online tool, and the obtained five most relevant keywords were become a standard approach to outline how the development of added to the project entry in Dataset 3. Then the keywords were technologies is perceived [14, 15]. It plots a generally applicable searched in Dataset 2 containing the Gartner Hype Cycle path a technology takes in terms of expectations or visibility of emerging technologies. The descriptor of the corresponding the value of the technology (y-axis) as related to time (x-axis). technology was included in Dataset 3 to identify the match. The The model incorporated two distinct equations/curves adopted keywords have been manually cross-checked with the emerging from behavioural psychology and technology management technology descriptors in Dataset 2, searching for matches. The studies, that is a hype curve shape for human expectations about matches have been identified if the wording was synonymous or any new technology and a classical technology diffusion S-curve related. The EuroSciVoc taxonomy has been consulted, where showing the proliferation of the technology on the market [16]. there was an additional need to clarify individual keywords. Most recently, a new approach based on the insights from The PoCs have been categorized according to the following neuroscience has been taken into consideration when analysing procedure. First, the start dates of the analysed PoC projects have the Gartner Hype Cycle [17]. The latest research has focused on been correlated with the remaining years of the corresponding exploring expectation dynamics in early-stage innovations to matching emerging technologies using the latest reported data explain the hype cycle phenomenon that precedes innovation from the annual Gartner Hype Cycles of Emerging Technologies. adoption. Different types of expectations (emotional and logical) The PoCs have been classified according to the following and speed of acceptance or abandonment of new technology have principle. If the start of the year of the PoC activity was behind been observed as being dependent upon time [17]. The faster the the estimated year for reaching the market maturity of the time-to-market, the more emotional and rapid the acceptance of corresponding emerging technology, then the PoC was assigned technology, which creates logical expectations and drives the to the category of “Catching Up PoC” (Type 3). If the start of the hype cycle of emerging technology. Hence, the duration of any PoC activity was ahead of the emerging technology reaching technology validation is hype cycle time and domain-dependent. market maturity by the earliest estimated date, then the PoC activity was assigned to the category of “Mature PoC” (Type 2). Any technology development is always a design process. The If the start of the PoC activity was ahead of the emerging philosophers of science agree that new technology becomes technology reaching market maturity by the latest estimated date accepted through five types of experiments, efforts aimed at by more than ten years, then the PoC activity was assigned to the empirically demonstrating the proper development and working category of “Pathbreaking PoC” (Type 1). of technology, including feasibility experiments, trial experiments, field experiments, comparative experiments, and Finally, to validate the approach, each categorized PoC activity controlled experiments [18]. The results of individual from Dataset 3 has been additionally researched using publicly experimentations thus lead to obtaining proof of concept, available sources, trying to find details about the follow-up understood as an artifact that acts in this role to demonstrate the activities confirming one of the patterns associated with these technology at a required level of complexity. The PoC activities categories. Namely, in the cases of Pathbreaking PoCs, include verification tasks and actions (evaluation of risk numerous scientific activities had to be observed, which are assessment, product and process capabilities, compliance with associated with the early stages of technology development. In requirements, proof of concept through analysis, modelling and the cases of Mature PoCs, more applied research activities could simulation, demonstrations and tests) and validation methods be expected, while in the case of Catching-up PoCs, the follow- (prototyping, demonstration, market tests, field trials) [19]. up in terms of research activities expected to be relatively minimal. Thus, a typology of PoC has been created consisting of 4.2 Subject indexing and categorization of PoCs three categories. Table 2 summarizes their main characteristics. The categorization of PoCs is an open-ended and ad hoc process. It relies on applicants' self-reporting and keyword assignment by Table 1: A preliminary typology of PoCs funding agencies' staff and expert bodies. The interdisciplinary and inter-sectorial nature of the PoC projects creates difficulties PoC Type in categorizing the PoCs due to their multidisciplinary, cross- Hype Cycle stage Time to market sectorial and both scientific research and market-oriented nature. maturity Type 1: Innovation/Technology Trigger 7-13 years Thus, for this study, the use of an automated AI-driven subject Pathbreaking Peak of Inflated Expectations indexing tool has been sought. The used system (Finto AI) is Type 2: Peak of Inflated Expectations 2-8 years based on the open-source AI-driven tool Annif for indexing and Mature Trough of Disillusionment classification developed by a national library consortium to Type 3: Trough of Disillusionment 0-4 years categorise text in several languages, including English [20]. The Catching Up Plateau of Productivity tool uses text classification algorithms and a neural network model based on TensorFlow trained on the General Finnish Ontology (linked to the US Library of Congress Classification). The subject indexing was done as follows. The text of each full abstract of the project in Dataset 3 was entered into Finto AI 202 Table 2: Main details of the analysed PoCs of a representative sample of PoCs. However, one can only achieve that on a limited scope due to confidentiality limitations. PoC No. Keywords generated by Gartner PoC Finto AI descriptor Type ACKNOWLEDGMENTS 196345 EEG, brain, signal Brain- Type The knowledge of the subject area would not be possible without processing, diagnostics, computer 1 the opportunity I had to participate in the ERC PoC evaluations measurement interface and meetings to understand better the design of this funding 200027 mobile communication Machine-to- Type instrument. 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DOI: 10.4403/jlis.it-12740. 204 The ''Incubator of Innovativeness '' program driving technical readiness levels of the Cracow University of Technology Innovations Jacek Kasz† Center for Technology Transfer Cracow University of Technology, Kraków, Poland jacek.kasz@pk.edu.pl ABSTRACT implementation. This is well known from the literature [1] and the tech transfer practice in various TTO environments. This paper presents the implementation of the Polish The road from idea to innovation leads through Proof-of- governmental “Incubator of innovativeness” program at the Concept, which is TRL level 3. Cracow University of Technology. It deals with the methodology As commonly defined by EU institutions [2] Proof-of-Concept of projects’ selection, management of Proof-of-Concept research, (PoC) is “1. the realization of a method or idea in order to intellectual property protection, and commercialization process. demonstrate its feasibility, or to verify that a concept or theory It presents the barriers and challenges encountered in the process has practical potential; 2. evidence, typically deriving from an and recommends the improvements for the next editions of the experiment or pilot project, which demonstrates that a design program. concept, business proposal, etc. is feasible; 3. a small exercise to KEYWORDS test a design idea or assumption. A desirable effect of PoC research is transition from prototype to innovation, technology, transfer, TRL, technical readiness level, a Minimum Viable Product (MVP) on the way to a fully blown Proof-of-Concept, research funding commercial product. 1 BACKGROUND AND RATIONALE 2 InIn PROGRAM OF THE POLISH One of the objectives of the Center for Technology Transfer MINISTRY OF EDUCATION AND (CTT) of the Cracow University of Technology (CUT) in SCIENCE Kraków, Poland, is maximizing impact of scientific research Ministry of Education and Science in Poland has addressed through its successful commercialization. The capability of this issue by creating and maintaining the program called technology to be practically implemented is highly dependent on “Incubator of Innovativeness” (InIn), which started in 2014 and its development stage and is measured by the TRL level is currently continued in the 4th edition. (Technical Readiness Level). The objective of the program is to support entities active in the The critical advancement on the way of solution development is field of commercialization of the results of scientific research and moving from the basic technology readiness level TRL 1-2 (basic R&D, in initiating cooperation of academia with the business principles observed, technology concept formulated) to a higher environment and application in the specific market solutions. level, preferably 5-6 (technology validated and demonstrated in The "Incubator of Innovation 4.0" program initiated in 2020 relevant environment). While the former is typically financed by provides support to “Innovation Incubators”, i.e., universities universities and governmental scientific and R&D funds, the and their special purpose vehicles (SPVs) – wholly owned latter is just the beginning of VC and industry interest in university companies - or consortia established by universities, technology. This gap in funding of technology development is SPVs, scientific institutes of the Polish Academy of Sciences, often referred to as a “death valley”, since public institutions’ research institutes or international scientific institutions. The funding focuses on scientific results, while business investment support is provided for the following activities: is justifiable only in case of technologies ripe for • conducting pre-implementation (PoC) research, including additional laboratory tests or adapting the † invention to the needs of the interested buyer, the cost Dr. Jacek Kasz is Director of the Center for Technology Transfer of the Cracow University of Technology in Kraków, Poland. of which may not exceed PLN 100 k; • the analysis of the market potential of inventions and 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 the analysis of their readiness for implementation, as for profit or commercial advantage and that copies bear this notice and the full well as the valuation of intellectual property rights citation on the first page. Copyrights for third-party components of this work must (IPR management); be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia • identifying entities interested in implementing the © 2020 Copyright held by the owner/author(s). research results and development works; 205 • technology portfolio management. commercialization work before the deadline. CTT has been working closely with the Patent Attorneys Office at CUT to In 2014 Center for Technology Transfer of CUT created a assure timely and effective IP protection. Potential international consortium with the SPV of CUT Intech PK (Intech) and patent extensions (PCT and protection in particular countries) since then has successfully applied for the governmental will be considered at the later stage depending on funding in all 4 editions of the InIn program. commercialization results. In 4 editions of the InIn program CTT has received 85 applications from the CUT research teams, out of which 43 3.4 Brokers and commercialization have been granted research funding up to 100 k PLN (Eur Apart from increasing the TRL level of the university 25k). Total program budget per edition at CUT was 2 MM technologies, the InIn program’s objective was improving the PLN (Eur 500k) on average. effectiveness of the activities of TTOs and SPVs in research organizations in the field of cooperation with business, including 3 IMPLEMENTATION OF THE InIn 4.0 commercialization of the results of R&D works. This involved also investing in Technology Brokers by their high-quality PROGRAM AT THE CRACOW training and by hiring the new ones. UNIVERSITY OF TECHNOLOGY Broker’s major task in the InIn project successful direct and indirect commercialization of the technologies Already at the 3.1 PoC projects selection stage of PoC proposals selection by the Committee has been The PoC projects applications have been received and selected looking for the potential spin-off (start-ups with university/SPV by the Selection Committee, which comprised of the 4 external co-ownership) and spin-out (start-ups with university/SPV co- (non-CUT) members of the University Council (the controlling ownership) founders. Among 14 technologies we have identified body approving the university budget and discharging the Rector 2, which were showing the industrial potential of the solution and for his term), Vice-Rector for Science, CTT Director, SPV interest of scientists in running the business. The Ministry President, Head of Commercialization and Head of the accepted our proposal and our project indicators became 12 Academic Innovation Incubator. As one of the important InIn direct and 2 indirect commercializations. project indicators was successful direct and indirect Currently the technology transfer process is underway and we are commercialization of the technologies, the selection criteria were considering applying all forms of commercialization, including not only the uniqueness, novelty and feasibility of the proposed licensing, sale of patents and know-how as well as creating start- research idea, but also its commercialization potential. Out of 35 ups. The tangible results of the InIn project at CUT have been so applications in the 4th edition 14 PoC research proposal have far 4 spin-offs founded and 2 licenses granted. It is a lengthy and granted funding in the range of PLN 65-90 k (Eur 15-20 k). As a unpredictable process and it may (and certainly will) extend rule, the Committee did not grant the full amount applied for, but beyond the projects’ end. typically 90% of it, which allowed to accommodate more PoC projects. 3.5 Barriers and challenges 3.2 Research management 3.5.1. Barriers In the course of the project, we have encountered the following Within the course of the project, it was critical that research work barriers, that we were not able to break: has been carried out according to the planned schedule and at the steady pace. This allowed for the uniform money spending • Researchers’ conflict between fundamental science throughout the project term, which in turn guaranteed timely and applied research – publish or patent payments of installments by the Ministry, which were only made • Scientists’ lack of understanding of technology upon reaching the research spending milestones. Thus the CTT transfer – its objectives and methods; much training job was not only responsiveness to the researchers needs and needed requirements, but also exercising some discipline in money • Purchasing procedures in public institutions – slow, spending by the scientists. This was of special importance due to restrictive and complicated the fact that not only research cost, but also project management • Reporting – too detailed, too bureaucratic, too time remuneration was financed from the fund. Consequently, timely consuming salary payments of CTT employees were dependent on regular • Funding - the limit of Eur 20-25 k was in many cases researchers’ spending. too low. While in some disciplines this may be enough (SSHA – Social Sciences, Humanities and Arts) in 3.3 Intellectual property rights some technical disciplines it does not allow for the One of the critical issues was assuring timely protection of the fulfillment of the research plan. More flexible intellectual property of the university, According to Polish law spending limits should be considered. all IP resulting from employees’ work belong to the university (no “professor’s privilege”). Here the conundrum was applying for protection at the Polish Patent Office at the right time, i.e., 3.5.2. Challenges when all the important attributes of the technology have been In the course of the project, we have encountered the following already discovered, but early enough to be able to start challenges, which have been mitigated partially or in full: 206 • Different or opposed interests of the consortium • analysis of the possibility of obtaining patent protection and the members – internal competition possibility of commercializing the results of scientific research • Focus on customers and their needs - the concept not and development works before their publication liked by scientists, who value freedom of research. • targeted analyzes and business plans for a potential investor (up • Know-how vs. patent - the nuances often disregarded to 50% of costs) by scientists 7. Conducting PoC works, including additional laboratory tests • International IP protection – PCT procedures are rigid or adapting the invention to the needs of the interested buyer, the and costly. cost of which may not exceed PLN 100 k. The legal regulations at the different levels are generating This proposal has been a subject of discussion within the Polish most of the barriers and we are not able to change them technology transfer organization PACTT, whose member is CTT without legislative initiatives. As far as challenges, we have of CUT. mitigated or even liquidated some of them thanks to tech PACTT is an association of 82 major universities in Poland, transfer education and training of scientists. including technology and medical universities. It gathers together representatives of tech transfer offices (TTOs) responsible for protection, management and commercialization 4 RECOMMENDATIONS FOR THE NEXT of universities intellectual protection. PACTT is the voice of EDITIONS OF THE PROGRAM technology transfer community in Poland. As a result of internal discussion, the comments and Based on the experience and results of the 4 editions of the InIn recommendations to the Ministry of Science and Education have program Polish Ministry of Science and Education came up with the proposal of the new program called “Development been formulated by PACTT, which are currently being Incubator” (DI), which is an extension and expansion considered. of the Our major stipulations pertained to: existing InIn program [4]. Its objective is support for the management of commercialization • Unit finding in excess of PLN 100k (Eur 25 k) per of R&D results in research organizations. The project will consist technology of 2 modules: • Spending allowed at any given moment of the project 1. CTT and SPV direct support module - program implemented • Simplified reporting in partnership – “Development Incubator” (DI); • Increased funding for training of brokers 2. Training module - E-learning platform prepared by the • PCT patents financing allowed from grant money. Ministry, customized training program. The current InIn 4.0 project ends April 30, 2023 and we expect The main tasks under the project have been formulated as the new edition, called “Development Incubator”, to start May 1, follows: 2023. 1. Initiating and strengthening cooperation between the scientific This governmental program has proven to be very effective in community and the economic environment, including searching supporting the Proof-of-Concept research at the Polish for entities interested in joint implementation of research projects universities and became a major instrument in financing and implementation of the results of scientific research and commercialization of the university technologies. development works, 2. Mapping the potential of research organizations to conduct ACKNOWLEDGMENTS joint research projects in industrial and scientific consortia. The comments of Ms. Marlena Marek and Ms. Joanna Szypułka 3. Promotion of research organization services aimed at the as well as assistance of Dr. Irena Śliwińska are greatly economic sector appreciated. 4. Preparation of commercialization projects for the results of scientific research and development works, including in REFERENCES particular the valuation of industrial property rights, analysis of [1] Leban Marijan, Stres Špela “Technology Transfer Fund - Central Eastern the market potential of inventions and analysis of their readiness European Technology Transfer (CEETT) platform”, 14th International for implementation. Technology Transfer Conference, Institut “Jožef Stefan”, Ljubljana, 5. Substantive preparation to conduct independent activity for Slovenia [2] Introduction to Proof of Concept, EU JRC project EU4TechPoC, 2020, research teams whose optimal commercialization path is the https://eu4tech.eu/wp-content/uploads/2020/05/EU4TECH-Podcast-1- establishment of a spin-off company Introduction-to-PoC.pdf [3] Ministry of Education and Science (Poland), “Inkubator Innowacyjności 6. Managing the R&D portfolio of a given research organization, 4.0” (in Polish), https://www.gov.pl/web/edukacja-i-nauka/inkubator- including in particular: innowacyjnosci-40 • maintaining a database on ongoing research projects, including [4] “Koncepcja MEiN Inkubatora Innowacyjności”, PACTT document, 28.07.2022 monitoring and analysis of the results of scientific research or development works in terms of their practical usefulness, On the next page: • analyzes of market needs to select topics of research or development work and research on the state of the art before Figure 1: Technology Transfer Model in the “Incubator of starting research or work, Innovativeness 4.0” project at the Cracow University of Technology 207 208 Science meeting the needs of entrepreneurs Magdalena Agnieszka Paweł Kołakowski Grzegorz Kukowska- Piotrowska- Faculty of Navigation Rutkowski Kaszuba† Kirschling Gdynia Maritime Faculty of Navigation Technology Transfer Technology Transfer University Gdynia Maritime Office Jana Pawla II av. 3 Office University Gdynia Maritime Gdynia Maritime 81-345 Gdynia, Poland Jana Pawla II av. 3 University p.kolakowski@wn.um University 81-345 Gdynia, Poland 81-87 Morska St., g.edu.pl 81-87 Morska St., g.rutkowski@wn.umg. 81-225 Gdynia, Poland 81-225 Gdynia, Poland edu.pl biznes@umg.edu.pl biznes@umg.edu.pl ABSTRACT inextricably requires the involvement of an inventor. To obtain funds for the implementation of any project, scientists often use The rapid development of new technologies and innovations that various grant competitions. The idea itself is not enough to obtain we are seeing today means that it is most important that such a grant, but a thoroughly prepared action plan and, more inventions meet the long-term needs of industry. Without this, often than not, an industry partner are crucial. In other cases, there is a little chance for the successful commercialisation and some entrepreneurs have the required financial means but lack appearance of the innovation on the market. Research ideas to bring their business to the next level. Companies are to Business meetings and interviews are good practice for often in the market for new ideas or for the scientists who will allowing the representatives of companies and universities develop a given concept. This is where the relationship between to fully discuss inventions and commercially interesting science and enterprise comes in, like a system of connected technologies. The innovations dedicated to industrial partners, vessels, supported by Technology Transfer Offices together with together with interesting financial tools that enable higher TRLs innovation brokers. It is crucial to ensure that the core values for inventions and technologies to be achieved, ensure of both organizations promote the types of behaviour that an excellent basis for the development of future research strengthen and not hinder the development of trust-based cooperation and business synergy. relationships. It is worth highlighting that all research, The aim of this paper is to discuss the relationship between technology, and product development as well as professional science and enterprise in respect of science's response to the staff are becoming an element of competitiveness and needs of industry, and is presented in the form of a case study competence building enterprises oriented for innovation [1, 2]. of a project by scientists from Gdynia Maritime University The European Innovation Council (EIC) Advisory Board said (Poland). All the innovations within the framework of this that researchers must work closely with entrepreneurs to make project concern equipment for a mobile diving base, in particular, breakthrough research in Europe successful business the flexible diving bell Batychron and the mobile opportunities [3]. If so, the innovations coming from science will electromagnetic mooring system. not only meet the needs here and now, but also those in the future, which are more important for business from the economic point KEYWORDS of view. needs of industry, research to business, relationship between Great innovation should respond to the entrepreneurial need science and enterprise, knowledge & technology transfer so that it can be successfully commercialised. Furthermore, activities Aliasghar et al. highlighted that the entrepreneurs are really looking for both knowledge and innovation in science [4]. Therefore, scientific research must respond to the needs 1 INTRODUCTION of enterprises. The development of mutual benefits which facilitates scientific knowledge commercialisation is absolutely It is often claimed that it is the idea behind an invention that crucial [5] (Figure 1). is the most important, however, there is a long road from the A World of Knowledge Transfer is an international knowledge initial conception of an idea to its implementation. Creating new, transfer community gathering organization. In July 2022, the innovative inventions almost always involves investment and latest ASTP 2021 Survey Report on Knowledge Transfer †Author Footnote to be captured as Author Note Activities in Europe was published [6]. The data source for the report was 519 Knowledge Transfer Offices (KTOs) from 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 26 countries for the financial year 2019. The ASTP 2020 Survey for profit or commercial advantage and that copies bear this notice and the full Report on Knowledge Transfer Activities in Europe from 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). 512 KTOs (from 27 countries) for the financial year 2018 was Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia presented [7]. The main conclusions are presented in Figure 2 © 2020 Copyright held by the owner/author(s). 209 [6, 7]. The headline numbers from the ASTP 2021 Report are The total number of contract & collaborative research promising [6]. agreements and the total number of revenues for intellectual property has grown with time [6, 7]. The result is inspiring for the future. European KTOs indicated a total of 177, 784 agreements with the industry of which 69% were Consultancy Agreements, 21% Contract Research Agreements, and 10% Collaborative Research Agreements [6]. The total number of agreements in the financial year 2019 was slightly higher than in 2018 at about 7 020 agreements [6, 7]. In the financial year 2018, the distribution of the number of agreements was similar: 70% Consultancy Agreements, 21% Contract Research Agreements, and 9% Collaborative Research Agreements [7]. Among commercial contracts, KTOs reported more licenses, options, and assignments in the financial year 2018 [6, 7]. The biggest difference was in the case licenses (1, 853 in 2018 [7] Figure 1: The diagram presents the innovation occurs and 1, 338 in 2019 [6]). This fact could be the result of global directly as an industry need economic uncertainty. These observations confirmed the effective cooperation between industry and academic centers in commercialisation. However, in relation to the intellectual property aspect in the financial year 2019, the results were a bit worse. The total number of invention disclosures and the total number of priority patent applications had decreased [6, 7]. This trend may be due to the coronavirus pandemic, but innovation brokers from technology transfer offices are taking an increasing number of different steps to promote science in the economy and to encourage entrepreneurs to cooperate with universities [1]. Last year, the same innovation brokers from the Technology Transfer Office of Gdynia Maritime University as part of creating a network of relations between science and enterprises were actively involved in activities aimed at recognizing the needs of the industry environment. This action was carried out on various issues as part of: 1. Invitation to a meeting of companies from the database of companies run by Technology Transfer Office of Gdynia Maritime University. 2. Cooperation with the “Instytut Autostrada Technologii i Innowacji” consortium, which brings together scientific entities and entrepreneurs. Figure 2: Overview of Survey Main Outputs and Findings for 3. Launch of a new initiative of Pomeranian academic centers the financial year 2019 [6] – the black font (in compared under the name “Discovering needs for innovation” carried to the financial year 2018 [7] – the navy font) out in cooperation with different companies. In general, a cooperation between companies and universities As part of the third initiative, eight science and enterprise should generate economic activities such as purchasing meetings were held with micro, small and medium-sized or licensing research results, patents, etc. [1]. companies, in particular from the Pomeranian region. The KTOs’ staff in the financial year 2019 performed mainly The undertaken new action was to serve the development functions such as research support (31%), commercialisation of cooperation in the local innovation ecosystem. The main (24%), others (24%), entrepreneurship support (11%), and proposal of the action was to understand the needs of the business development (10%) [6]. This sees a change from the Pomeranian enterprises, identify their innovation potential, and financial year 2018 when KTO’s staff was more focused assess the barriers that prevent the growth of this potential. on commercialisation (31%) than research support (24%) [5]. Additionally, the opening of companies to the Pomeranian This reverse relationship could be the result of the COVID-19 academic centers is a new kind of communication between crisis. Additionally, the observation also confirmed the business and science. importance of Technology Transfer Offices in creating and In the next section of this paper, an example of increased maintaining relationships between science and entrepreneurs. cooperation science-enterprise will be described in more detail. 210 2 A CASE STUDY make all kindsof training, tourist, internship, recreational, and sports dives more attractive. This section presents a case study of a project by scientists from Gdynia Maritime University (GMU) (Poland). Innovations within the framework of this project concern the equipment of a mobile diving base, in particular, the flexible diving bell Batychron and the Mobile Electromagnetic Mooring System (MEMS). In December 2020, a micro company from Gdansk (Poland) was looking for a scientific unit to prepare an R&D report on technological innovation for the contracting authority on its Mobile Base of the Marine Emergency Diving Service Figure 3: a Batychron (MoB MEDS) project. Under the assumption, the MoB MEDS The second invention proposed in the mentioned project have to enable diving teams to quickly reach the vessel in danger, is the MEMS. The MEMS is an innovative mooring system as a result of various random maritime accidents (e.g., collision, designed to fit a small intervention/service vessel that moors contact, grounding). Without performing effective repairs related to the sides of larger vessels requiring intervention for repair, to the need to carry out control inspections of the underwater part servicing, or the transfer of cargo or people, without the need of the hull, and quick protection of the water area against to involve a large number of crew members during mooring potential oil and/or chemical spillage, a high-speed boat could operations (Figure 4). seriously endanger the safety of human life, the environment, The main disadvantages of the known electromagnetic or marine navigation [8]. The research group from the or vacuum mooring systems are, on the one hand, their extensive Navigational Department of the GMU, along with members dimensions, which prevent them from being used on smaller of the Student Special Interest Group of Underwater Research vessels and, on the other hand, the inability to move the moored “Sea Quest” undertook the task of creating the report. vessel horizontally along the other vessel. The MEMS solution, The research group proposed two solutions as innovative using a system of electromagnetic grippers with a unique set equipment for MoB MEDS. The company expressed its interest of mooring lifts ensuring constant rope tension, tackles the in implementing these systems in its newly built watercraft, problems and requirements of small intervention/service which resulted in the signing of a letter of intent. watercraft, including working dive boats, during mooring As a consequence of acquiring a business partner, in April 2021, to a larger serviced unit. The key elements in this solution are the GMU Research Group applied and was accepted into a grant not only mobility, time, and lower energy consumption but, programme called “Innovation Incubator 4.0″, implemented above all, safety - the risk of an accident with ropes on a serviced under the programme of the Ministry of National Education vessel is reduced. of the Republic of Poland (earlier the Ministry of Science and Higher Education of the Republic of Poland) as part of the non-competition project entitled „Support for scientific research management and commercialisation of the R&D work results in scientific units and enterprises” under the Intelligent Development Operational Programme 2014-2020 (measure 4.4). The project reference number for the pre-implementation work is UMG-03. The project name is The Innovative Equipment of the Mobile Intervention Unit and contains two inventions the Batychron flexible diving bell and the Mobile Electromagnetic Figure 4: a MEMS Mooring System. Batychron is a flexible underwater bell patented by Gdynia The application to the Polish Patent Office was filed by GMU Maritime University as a device applicable in hydro-technics for (No. P.437572) on 13/04/2021. In April 2022, the European underwater transport and diving while maintaining the safety application number EP22000102 was filed. Currently, as part of human life [9]. There are several solutions for diving bells of the project, the simulation and laboratory/model tests are in hydroengineering [10], however, the disadvantage of the carried out to develop a plan for the construction known solutions is the large construction of the bell and the of a demonstration model. weight. These devices were very heavy and needed to be moved Both inventions have been promoted externally at several trade together with the vessel, which required several people to be exhibitions and industry shows (e.g., at the 14th International serviced. Under this assumption, the Batychron should be light, Conference on Marine Navigation and Safety of Sea handy, and portable. One of the goals of the above-mentioned Transportation Gdynia 16-18/06/2021, XXI International project was to build a new device called the Batychron Maritime Exhibition and Conference BALTEXPO 2021, Gdansk in a modular form with the new materials (Figure 3). The utility 6-8/09/2021). At the 15th Edition of International Invention and model for this device was submitted to the Polish Patent Office Innovation Show INTARG® 2022 Katowice 11-12/05/2022, (No. W.130766) on 05/05/2022. As a result of the research, the GMU Research Group presented ‘Innovative Floating it was confirmed that the Batychron device can be used not only Intervention Unit Equipment: A Mobile Electromagnetic as the equipment for intervention units but also to secure and Mooring System and a Batychron for which they were awarded a silver medal in the category Transport and Logistics. 211 At the same time, one of the small local companies from economy. In this respect, the relationship between science and Gdynia offered to cooperate with GMU by offering enterprise is of prime importance. Science is important to meet apprenticeships. The company was also looking for a wider the needs of entrepreneurs because it is precisely this that cooperation related to R&D projects in their field. The stimulates their interest in the development of new technologies. company’s marine automation department is involved These dependencies are crucial to conducting R&D focused in wide-ranging cooperation with shipyards and directly with on the needs of entrepreneurs. shipowners around the world. They design and manufacture their A good example of cooperation between science and enterprises. systems in the field of power engineering and ship automation, is the project referred to in this paper involving GMU scientists. as well as in servicing existing systems. Once acquainted with the Mobile Electromagnetic Mooring System, the company had Innovations within the framework of this project concern the no doubt that this was a project closely related to their industry, equipment of the mobile diving base, in particular, the flexible and one in which they wanted to be involved. The cooperation diving bell Batychron and MEMS. The cooperation between agreement was signed as part of the R&D activities. Currently, science and enterprise contributed to the creation of new the level of technological maturity was determined innovations, their protection by patents, and further plans for as 5 – validation of the technology was performed in a near their commercialisation. This case study highlights the real-world environment (prototype) thanks to support from the importance of scientific work that corresponds to the needs “Innovation Incubator 4.0” grant programme. The small local of industry. company specializing in marine automation in order to scale the solution and demonstrate the willingness to conduct joint implementation works as part of applying for external funds. ACKNOWLEDGMENTS GMU extensively work together with Gdynia company to obtain Research financed by the “Innovation Incubator 4.0″ grant funding to carry out an R&D project, as a consequence of which programme implemented under the programme of the Ministry a fully certified MEMS device is to be created. of National Education of the Republic of Poland (earlier the As shown in this case study, ideas for technological solutions Ministry of Science and Higher Education of the Republic can be developed and realized by effective cooperation between of Poland) as part of the non-competition project entitled science and enterprises. Such a relationship is a win-win situation “Support for scientific research management and - the scientists from the University can conduct scientific commercialisation of the R&D work results in scientific units research and realize their ideas, the entrepreneurs can generate income and develop their brand, and in this case, a Gdynia-based and enterprises” under the Intelligent Development Operational construction company can be the first to build the invention, and Programme 2014-2020 (measure 4.4). the previously mentioned company can use it. Working together they can offer a new technology to the market. The enterprises REFERENCES have noticed that those ground-breaking solutions have a global [1] Dariusz Trzmielak, 2012. Współpraca ośrodków naukowych reach. Both devices can be used in sectors such as marine i przedsiębiorstw we wdrażaniu wyników badań. 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Dover Publications, Inc., New York. teams ready to take on the difficult challenges of the current 212 Commercialization of R&D results created with public funds in the National Academy of Sciences of Belarus Alexander Uspenskiy Aliaksei Uspenski Maxim Prybylski Republican Centre for Republican Centre for Republican Centre for Technology Transfer Technology Transfer Technology Transfer Center for System Analysis and Center for System Analysis and Center for System Analysis and Strategic Research of the National Strategic Research of the National Strategic Research of the National Academy of Sciences of Belarus Academy of Sciences of Belarus Academy of Sciences of Belarus Minsk, Belarus Minsk, Belarus Minsk, Belarus uspenskiy@mail.ru auspen79@gmail.com m.pribylsky@hotmail.com ABSTRACT The paper informs on organizational structure, the current state Table 1 – Obtained national patents in 1993–2020 of commercialization of R&D results created with public funds in the National Academy of Sciences of Belarus (NASB), Establishment No. of patents Pct., % difficulties to involve private capital in the process of NASB 5 132 34,0 commercialization and proposes ways to address these Ministry of Education 4 600 30,5 problems. Ministry of Health 2 763 18,3 Ministry of Industry 1 520 10,1 KEYWORDS Ministry of Agriculture and Food 1 057 7,0 Technology transfer (TT), legislation, intellectual property Total: 15 072 100 rights (IPR), spin-off, start-ups, R&D contracts Table 2 – Registered with the National Center of 1 INTRODUCTION Intellectual Property license agreements in 1993–2020 Founded in 1922, the NASB is the primary state scientific No. institution and the leading R&D center of Belarus. It Establishment of Pct., % agreements incorporates over 110 organizations (incl. production, design, NASB and 80 R&D institutions), and employs about 14 550 19,8 000 persons Ministry of Industry (incl. 5 501 18,0 000 researchers, 100 academicians, 120 corresponding Ministry of Agriculture and Food members, 400 doctors of sciences and 1 499 18,0 600 candidates of Food sciences) [1, 2]. industry concern 468 "Belgospishcheprom" 16,8 Between 1993–2020 the NASB registered nationally and Ministry internationally over 8 of Transport and 800 objects of industrial property rights: 71 Communications 2,6 inventions (66,3%), utility models (25,2%), plant varieties Ministry of Education (4,6%), trademarks (3%), industrial designs (0,7%). At the end 66 2,4 Light of 2020, only 558 objects remained in force [3]. industry concern "Bellegprom" 60 2,2 Other state bodies and state NASB ranks first by the number of national patents (table 1) -owned 563 enterprises 20,3 and the number of registered license agreements (table 2) [3]. Total: NASB licensing income for 12 years (2009–2020) amounted 2 778 100 to 6 mln USD or about 500 000 USD per year, and as shown in table 3, the plant variety is licensed the most – 59%. In recent Table 3 – Number of license agreements in NASB years, NASB exported annually ca. 50 mln USD of goods and organizations in 1994–2020 services, which means that licensing revenue amounts to 1% of total export [3]. Licensed IP No. of agreements Pct. , % Inventions 52 9,5 Utility models 41 7,5 Industrial designs 5 0,9 Permission to make digital or hard copies of part or all of this work for personal or Trademarks 28 5,1 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 Plant varieties 328 59,6 the full citation on the first page. Copyrights for third-party components of this Know-how (until 2013) 96 17,5 work must be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Total: 550 100 © 2020 Copyright held by the owner/author(s). 213 The reason for such low licensing income is that the results - Execution level includes organizations of the NASB. of scientific and technological activities (STA), created with The Expert council on IP management exists since 2010. Its government funding, de facto belong to the state, and not to main activities, specified by the Regulations on the Council organizations of the NASB [4, 5]. This is also the reason why (approved in 2014) are to: the NASB does not create spin-off and start-up companies. - develop and update IP management strategy of the NASB; The best results of the NASB in patenting and licensing - coordinate organization's activities in the field of IP activities is due to the organizational structure of the intellectual protection and management; property (IP) management system in the NASB. - considerate proposals by NASB organizations to improve legal mechanisms for IP protection and management; 2 ORGANIZATONAL STRUCTURE OF IP - examine issues related to acquisition of IP rights, and the MANAGEMENT SYSTEM disposal of those rights; Organizational structure of IP management, technology transfer - approve payment of remuneration to the heads of and commercialization of STA results in the NASB consist of organizations; four levels (see figure 1): - contemplate other IP issues that require collegial decision- making. - Top management level is the Chairman of the Presidium of NASB and the Deputy Chairman, supervising IP matters; The structure also includes: - two WIPO Technology and Innovation Support Centers - Regulation and coordination performs Expert council on IP management; (TISC): on the basis of Yakub Kolas Central Scientific Library of the NASB (since 18 Nov 2021) and on the basis of RCTT - Management and control is carried out by the Main department of scientific, scientific (since 31 Jan 2022) [6, 7]; -technical, and innovative- production activities, the Main department of international - specialized structural divisions in organizations (patent scientific and technical cooperation, the State scientific service, scientific and innovation division, marketing division); institution "Centre for System Analysis and Strategic Research" - specialists of non-specialized structural divisions with (CSASR), which includes the division "Republican Centre for advanced professional training in the field of IP and technology Technology transfer" (RCTT), the Departments of sciences (7) transfer. and the Departments of the NASB apparatus; Figure 1: Organizational structure of IP management, technology transfer and commercialization of STA results in the NASB 214 Services offered by the TISC based on RCTT include: (according to internal regulation approved in 2014). - access to online patent and non-patent (scientific and Organizations, not later than 15th April, provide the results of technical) resources and IP-related publications; inventory to NASB apparatus on five sheets: - assistance in searching and retrieving technology - Sheet No. 1 "Sole rights on objects of industrial property"; information; - Sheet No. 2 "Sole rights on objects of copyright"; - training in database search; - Sheet No. 3 "Organization's rights on STA results obtained - on-demand searches (novelty, state-of-the-art and via agreements"; infringement); - Sheet No. 4 "Organization's rights on potentially patentable - monitoring technology and competitors; STA results"; - basic information on industrial property laws, management - Sheet No. 5 "Organization's rights on STA results, which and strategy, and technology commercialization and marketing; are not objects of exclusive rights" (know-how). - support of training seminars on TISC activities organized After the adoption of Presidential Decree No. 59 in 2013, by NCIP, WIPO, European IP Helpdesk and others, including almost all STA results subject to mandatory commercialization assistance in the appointment of external speakers from the are commercialized at state enterprises. After mandatory network of European IP Helpdesk partners (for example, the commercialization for STA results begins period of indefinite European Network of National Intellectual Property Offices – use – organization does not know when and who will show INNOVACCESS, European Patent Office / Academy) for interest in created technology, and for what amount the specific activities in the field of intellectual property. organization will be able to sell it. From accounting point of view the STA results represent intangible assets. Putting STA 3 COMMERCIALIZATION ISSUES results on accounting can proof that they belong to When commercializing the STA results the NASB organization. This procedure is described in the Law of the organizations follow: Republic of Belarus "On accounting and reporting" No. 57-Z from 12 Jul 2013 and in National standard of accounting and reporting "Individual Accounting Statements" (approved by 1. Regulation on the commercialization of the results of scientific and technical activities created at the expense of Decree of the Ministry of Finances No. 104 from 12 Dec 2016). state funds (approved by the Presidential Decree No. The above documents do not allow putting the STA results 59 on 5 Feb. 2013, amended in 2018); (intangible assets with an indefinite useful life) on accounting 2. Strategy of the Republic of Belarus in the field of with zero value, and if any private organization wants to intellectual property until 2030 (approved by the Decree of purchase the technology, then the minimal license cost should the Council of Ministers No. 672 on 24 Nov. 2021). The be the sum of all expenses for creation and patenting the Strategy specifies main directions for improving the technology. As a result, organizations have no interest putting national IP system, the goals and objectives of the state STA results on accounting and concluding license agreements. policy in this area, which provide for the transformation of Technology transfer with private enterprises and foreign IP into an effective tool for innovative and socio-cultural companies occurs under commercial agreements with technical development of the Republic of Belarus. assistance, technical cooperation agreements, R&D agreements, and joint ventures. Belarusian legislation also does not allow The Regulation defines commercialization as "introduction "gratuitous" transfer of technologies created with public funds into civil circulation and (or) use for own needs of the results of to SMEs to attract private investments. scientific and technical activity or goods (services) created (performed, rendered) using these results, ensuring the 4 FURTHER DEVELOPMENT achievement of economic and (or) social effects". The Regulation stipulates strict deadlines for the commercialization In order to proper and on-time implement the Strategy of the of STA results (created with public funds) subject to mandatory Republic of Belarus in the field of intellectual property until commercialization, i.e. within three years after the creation. 2030, the NASB approved "Plan of the National Academy of Failure to commercialize means violation of budget legislation, Sciences on the execution of priority measures in 2022–2023 and so received public funds should be recovered from legal for Strategy's implementation" (NASB Order No. 18 from 19 entities in an indisputable manner to the budget with interest Jan. 2022). The Plan contains actions directed at the: that equals to refinancing rate of the National Bank set on the - development of institutional system in the field of IP; date of collection. - development of IP infrastructure; To keep the list of IP rights on STA results subject to - improvement of incentive mechanisms for the creation, mandatory commercialization and its outcomes the State legal protection and use of IP; Committee on Science and Technology (SCST) and the - development of IP management system; subordinate organization – Belarusian Institute of System - improvement of legal culture and education in the field of Analysis and Information Support for Scientific and Technical IP. Sphere (BelISA) – maintain the State register of rights to the The improvement of IP management system, in particular, results of scientific and scientific and technical activities. State provide for "Development and adoption of institutional IP customers supervise the commercialization and maintain local policies in scientific organizations of the NASB". According to registers of STA results. Plan's schedule, all 80 R&D institutions should adopt IP Committee, created by order of organization's head, carries policies: 24 in 2022, 18 in 2023, 17 in 2024, and 21 in 2025. out annual inventory of SDA results in the NASB in 1st quarter 215 5 CONCLUSIONS ACKNOWLEDGMENTS After the adoption of Presidential Decree No. 59 in 2013 in We would like to thank the National Academy of Sciences of Belarus, almost all STA results subject to mandatory Belarus and the State Committee on Science and Technology of commercialization are commercialized at state enterprises. the Republic of Belarus for their constant support of RCTT After mandatory commercialization for STA results begins activities and express gratitude to all our colleagues who work period of indefinite use – organization does not know when and in technology transfer for their help and advice. who will show interest in created technology, and for what amount the organization will be able to sell it. REFERENCES To allow de facto access of private SMEs to technologies [1] National Academy of Sciences of Belarus, Available from: developed with public funds, after their mandatory https://nasb.gov.by/eng/about/glavnaya/ (visited October 5, 2022). [2] Национальная академия наук Беларуси / А.И. Иванец [и др.]; под commercialization at state enterprises, and attract private capital общ. ред. В.Г. Гусакова. – Минск: Беларуская навука, 2020. – 92 с. to adoption of such technologies in SMEs, it is necessary, in [3] Нечепуренко Ю.В. Рынок объектов промышленной собственности, addition to recommendation given in [4], to enact legislation созданных в Республике Беларусь. – Минск: БГУ, 2022. – 147 с. [4] Alexander Uspenskiy, Aliaksei Uspenski, Maxim Prybylski Technology that: Transfer in Belarus // Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume E – 7 October 2021 Ljubljana Slovenia. – p. 62–64. – ISBN 978-961-264-224- 1. allows putting the STA results (intangible assets with an 2. indefinite useful life) on accounting with zero value, [5] Политика и законодательство в сфере трансфера технологий: зарубежный и национальный опыт / Д.М. Вильтовский, Е.П. similar to Generally Accepted Accounting Principles Машонская, А.А. Успенский; под общ. ред. А.А. Успенского. – (GAAP) and International Financial Reporting Standards Минск : Ковчег, 2010. – 60 с. – ISBN 978-985-6950-40-0. (IFRS); [6] TISC Derectory: Belarus, Available from: 2. https://www.wipo.int/tisc/en/search/search_result.jsp?country_id=27 gives the contractor-organization the right to (visited October 5, 2022). independently determine the cost of license agreements [7] The WIPO Technology and Innovation Support Center was established based on the market value of the created technologies; on the basis of RCTT, Available from: 3. stimulates the involvement of private capital to https://www.ictt.by/eng/home/news/4804/ (visited October 5, 2022). commercialization of technologies in SMEs. 216 Selection and evaluation of technologies for the transfer to the industry Vadim Iatchevici Department of innovative projects National Agency for Research and Development Chisinau, Republic of Moldova vadim.iatchevici@gmail.com ABSTRACT to reflect and can only produce an optimal result in its own particular framework. The paper refers to the study of the issue of selection and A technology screening method can thus be a valuable tool for evaluation of technologies for their transfer to the industry. For an organization to help choose technologies, especially if it can low-income countries such as the Republic of Moldova, where generate useful information in a timely manner and at an the potential for technology generation is low, it is very important acceptable cost. There are various concerns to consider when to create policies for selecting and evaluating technologies that selecting a method, as well as several different types, which are would facilitate the transfer of technologies that can be discussed below. assimilated in that country, taking into account human resources and existing technological and financial potential. This article highlights 27 methods used to select and evaluate 2 CHARACTERISTICS AND PRINCIPLES technologies, the decision-making issues for which those OF TECHNOLOGY SELECTION AND methods are applied, and the strengths and weaknesses of some EVALUATION METHODS methods. Some challenges arise in the process, because the After studying the literature presented in references, the available methods are usually too simple or too elaborate for following five aspects are considered the most important in a most managers and companies to be systematically understood method of selection and evaluation of technologies, which and applied. To continue the research, there is a need to combine propose the following characteristics and definitions: methods or develop a new method. KEYWORDS Table 1: Characteristics and definitions of technology Innovation, technology transfer, methodology, criteria, selection and evaluation methods descriptors of performance Characteristics Definitions 1 INTRODUCTION Realism The accuracy of the representation of The process of selecting and evaluating technologies is an the real world and in the reflection of indispensable component of technology transfer and responds to the company's decision on the situation, the issue of identifying the most optimal technologies proposed objectives, limitations, risks, etc. for transfer within enterprises and industries. This statement is Capacity Ability to analyze different types of made by the author of this article based on his experience in decision variables and deal with technology selection and evaluation for at least 10 years. several factors (multiple time periods, Various methods of selecting and evaluating technologies from changes in interest rates, etc.) simple ones, such as financial methods, to the most complex Flexibility Applicability to different types of ones, such as mathematical programming, have been developed technologies and issues and ease of and used to address this issue. change in response to changes in the The methods are used to extract and process relevant information business environment about a problem, because the reality is also too complex to Use Ease of understanding and application manage in its entirety. Therefore, any method, no matter how of the method. Clear, easy to sophisticated, will always be only a part of the reality it intends understand by all members of the organization and executed quickly Cost The costs of setting up and using the method should be less than the potential 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 benefits of the technology and relatively for profit or commercial advantage and that copies bear this notice and the full low in the cost of the technology 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 217 Easy Easy collection, storage and handling Multiatributive analysis in Selection and evaluation of computerization of information with readily available combination with regression technologies for the public software (such as Excel®) models sector Multicriteria selection and Aggregation of expert In the literature there is an extensive list of "good practice" evaluation judgments principles for technology management tools observed by several The method of fuzzy Technology selection and authors, some of which apply in particular to technology preferences evaluation selection and evaluation tools, such as: Fuzzy logic Selection and evaluation of • Robust (theoretically possible and reliable) software technologies • Economical, simple and practical to implement Mathematical programming The decision to select and • Integrated in other business processes and tools evaluate the technology • Flexible (adaptable to suit the particular context of the business provider and its environment) Gray Selection and evaluation of There are a wide range of methods that have been used to select the technology offer and evaluate technologies, from simple cost analysis to full and TOPSIS Decision making for tenders linear programming or more flexible methods such as fuzzy Fuzzy stochastic Technology selection and mathematical programming. evaluation Research on the selection and evaluation of technologies dating ELECTRE I Technology selection and back to 1959, where several criteria and methods of evaluation mathematical programming were already used. Reference is The theory of possibility Technology investment made to works that use the following methods: scoring, ranking, decision decision trees, theoretical approach to the game, Delphi Mathematical programming Selection and evaluation of technique, fuzzy logic, hierarchical analytical process (AHP), research and development goal programming, dynamic programming, linear programming technologies 0-1, programming quadratic and nonlinear programming. Some Network Analytical Process Selection and evaluation of methods can even be used together, which further increases the (ANP) research and development number of possible techniques to be used for the selection and technologies evaluation of technologies. Fuzzy-logic Selection and evaluation of The table below shows several methods for selecting and new product development evaluating technologies, which have been used in various technologies decision-making issues, such as evaluating technology offerings, ANP Technology selection and information systems, and research and development. evaluation Packing method - several Selection and evaluation of Table 2: Various types of technology selection and boxes research and development evaluation methods for certain decision-making issues technologies AHP and multi-attribute Selection and evaluation of Technology selection and The decision-making decision making technique industrial technologies evaluation method problem Mixed integrated Optimal selection and Programming the selection of programming method evaluation of the research Net present value method investments in technologies and development portfolio Zero-one integer Random selection and Cost analysis (e.g. VNV, Technology selection and programming methods with evaluation of technologies DCF and reimbursement) evaluation limited chance Unweighted ranking and Decision to select and model evaluate investments in As can be seen, there are different methods that are used for technologies different decision issues. Therefore, it can be concluded that The analytical ranking Selection and evaluation of there is no specific method for a particular situation, but rather process (AHP) industrial technologies that there is a wide range of possibilities and applications. The Multiatributive utility theory Technology selection and advantages and disadvantages of the methods must be weighed in combination with PRICE evaluation against the particular issue of the available decision, in order to Linear and full programming Technology selection and choose the most appropriate method. The table below explains evaluation some of the above methods, the corresponding advantages and Utility method-theory Bidding decisions disadvantages. The fuzzy overtaking method Technology evaluation Competitive bidding strategy Technology selection and model evaluation 218 Table 3: Comparison of technology selection and evaluation decisions to process is methods be taken into harsh, account which Decision Description of Advantage Disadvant cannot be method the method age used for Cost analysis Use Controls high (eg VNV, accounting costs and It focuses precision DCF and data and other prevents only on in return on relevant waste and costs and decision investment) information to losses ignores making identify ways the cost- ANP It is a It can deal It to reduce Easy for benefit mathematical with requires costs and then decision principle decision- technology large choose the makers making evaluation amounts technology technique issues of data that works similar to and the best AHP decision Linear Get the best depends Linear programming result in a An on the programming is a technique mathematic optimal experienc for optimizing al model, solution e of the an objective give a list of may not experts linear requirement be found Gray Target Gray Target It does not function, s decision decisionhas need a large subject to represented some original number of linear equality as linear effect on the samples and and inequality equations problem of the samples constraints recognizing do not need Integrated Type of It greatly More the model to be The programming mathematical reduces difficult with small regularly optimal programming time and to solve samples, distributed solution whose space for than insufficient It can may not variables are solution linear information describe in be a (in whole or program and data and more depth global in part) ming in uncertain the nature of optimizat integers in the conditions things with ion problem low situation Fuzzy logic Fuzzy logic is It is a Fuzzy computation a form of powerful logic al load multivalent tool for difficult The results logic derived managing to of the from fuzzy inaccurate achieve quantitative theory, it data on a large and deals with scale qualitative reasoning that analysis will is be more approximate consistent rather than It can be accurate used for AHP A Reduce It short and mathematical complex depends long term decision- decisions in on the predictions making a series of experienc and is technique that individual e of the highly allows the comparisons expert accurate qualitative and then The and summarize comparis While return on investment (ROI) is one of the primary factors quantitative the results on and for prioritizing technology, other issues should be considered, aspects of the trial 219 such as alignment with strategy, balance between maintenance evaluation and selection approach, the new method permits to technologies and technology investments, allocation efficient use obtain of complex results with fewer efforts and special skills of resources and other non-financial benefits. from the company technology managers. It is impossible to define a set of criteria suitable for all To avoid further selection of technologies "Losers", the key lies circumstances, as they will differ greatly from one another in in the objectivity of the selection and evaluation process, through different companies and technologies. As a result, there are an a method that incorporates both financial and non-financial endless number of criteria mentioned in the technology selection criteria and by the awareness that each method may be and evaluation literature, which vary depending on the type of appropriate in certain situations for a particular company and for technology and methods used for selection and evaluation, where the circumstances of the technology. Such a method is proposed scoring methods present the most extensive and extensive set of in the research conducted by the author of this article in his PhD criteria, including more than just financial and strategic issues. Thesis „Selection and evaluation of technology for the There are also different ways in which criteria can be organized, technological transfer”. such as by the type of criterion, which is the most common. REFERENCES [1] Badri, M., Davis, D., Davis, D., 2001. A Comprehensive 0-1 Goal 3 CONCLUSIONS Programming Model for Project Selection. International Journal of Project Management, 19(4):243 – 252. Studying the literature has allowed us to understand the [2] Bretschneider, S., 1993. Evaluating R&D Impacts: Methods and importance of selecting and evaluating technologies for the Practice. Chapter Operations Research Contributions to Evaluation of R&D Projects (Chapter 7). Springer Science+Business Media, LLC, success of innovation and technology transfer in companies, but New York. also the decision-making issues they face in applying the [3] Kerr, C., Farrukh, C., Phaal, R., Probert D., 2013. Key principles for methods of selection and evaluation of technologies. The developing Industrially Relevant Strategic Technology Management Toolkits. Technological Forecasting and Social Change, 80(6):1050 – challenges arise because the methods available are usually too 1070. simple or too elaborate for most managers and companies to be [4] Souder, E. W., 1972. A Scoring Methodology for Assessing the Suitability of Management Science Models. Management Science, systematically understood and applied. In order to tackle these 18(10). challenges, the author developed a proprietary method, that [5] Souder, E. W., 1972. Comparative Analysis of R&D Investment Models. AIIE Transactions, 4(1):57–64. includes criteria divided into several groups like financial, [6] Wang, J., Xu, Y., Li, Z., 2009. Research on Project Selection System of strategical, technological, marketing, and external factors, which Pre-evaluation of Engineering Design Project Bidding. International could be adjusted for a concrete case. Due to the multicriteria Journal of Project Management, 27(6):584 – 599. 220 Subsidizing Knowledge Transfer with Public Funds Michal Belusky Technology Transfer Center Czech Academy of Sciences Prague, Czechia michal.belusky@pm.me ABSTRACT organizations to society. I believe that this obstacle is mostly superficial, and the aim of my paper is to convince the reader of European state aid law is an important cornerstone enabling the this as well. functioning of the European single market and thus the I suggest the main aim of the paper is to contribute to realization of the four basic European freedoms (the movement understanding the reality of the state aid law of the European of goods, persons, services, and capital within the EU). At the Union. This issue is already, in my opinion, sufficiently same time, as the EU strives to stay competitive in the globalized elaborated in the works of other authors like Wendland, world ruled by rapid technological advancements, it needs to find Nicolaides and Schwendinger2. This paper may conversly serve ways of facilitating interactions between traditionally publicly as a state aid reference intended for experts in the field of funded research and the private sector, which could accelerate knowledge transfer and management of public research our economy and fuel it with new inventions and technologies. institutions, but also for experts oriented to the issue of industrial This, of course, invokes the ‘specter of state aid’ as the typically property within the academia and also for patent representatives non-profit organizations start to enter the market, albeit only and lawyers whose professional activity falls in this area. offering their knowledge as a product. To balance these forces, a complex system of rules and exemptions is emerging. In this paper I argue that sometimes the ‘spectre’ is being summoned by 2 STATE AID the research organizations themselves and that the current rules Many authors consider the doctrine of neoclassical political of state aid law regulating the field of research, development and economy to be the fundamental ideological source of state aid innovation do not present a major obstacle in knowledge transfer law [1]. A fundamental place in this ideology is occupied by the efforts of the European public research sector. phenomenon of a self-regulating market, which should be KEYWORDS protected from the efforts of states to intervene in it with public subsidies. Such interventions are justified only in borderline state aid, research, development, innovation, European union, cases, such as market failure or the pressing need to level certain competition law, European single market, public subsidies, geographical and especially social inequalities. knowledge transfer, effective collaboration, contract research, The first and arguably most important arena in which the licensing negative externalities of selective favoring of international competitors are manifested is the global trade. For this reason, state aid is regulated in relative detail by the World Trade 1 INTRODUCTION Organization, particularly on the basis of the Agreement on The aim of this paper is to bring the regulation of state aid in the Subsidies and Compensatory Measures, which deals on the one European Union closer to readers working in the field of publicly hand with the rules governing the provision of subsidies, i.e. state funded research and knowledge transfer. In addition to the aid, and on the other hand with the application of so-called introductory general interpretation of the law of state aid, the compensatory measures to compensate for the damage caused paper focuses on the issue of state aid of research organizations, subsidized imports, both in order to maintain healthy especially in connection with their interactions with companies, international competition. particularly when dealing with intellectual property belonging to The European Union (‘Union’), unlike the World Trade these organizations. These issues raise a number of practical Organization, has more effective tools for enforcing its standards problems that are relevant for research organizations, especially and similarly uses state aid regulation as a tool to protect the from the point of view of fulfilling their role in the dissemination health of economic competition. Articles 107 and 108 of the of knowledge1 . These problems also affect those corporations Treaty on the Functioning of the European Union (‘TFEU’) and entities that seek to collaborate with research organizations governing the provision of state aid by member states can be in the area of knowledge dissemination or transfer. I plan to found in the chapter dedicated to the competition law. Those address this subject in relative detail in this paper and subsequent subsidies that bring negative externalities manifested in the work. In the field of knowledge transfer, at least in Czechia, the property right of competitors from other member countries are European regulation of state aid is perceived as an obstacle to the identified as problematic. The main goal here is the protection of effective transfer of knowledge from public research the European single market. 1 Knowledge dissemination, according to Framework, means to widely disseminate 2 See references below. the results of research activities by way of teaching, publication or knowledge transfer. 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 2022, 10–14 October 2022, Ljubljana, Slovenia 221 © 2020 Copyright held by the owner/author(s). The European single market is based on four fundamental market. This fact is also reflected in the wording of the old freedoms that enable the free movement of people, goods, framework for state aid for research and development and services and capital. It is precisely the above-mentioned Article innovation, or its point 4, regulating the compatibility of support 107 and 108 of the TFEU which, through the prohibition of state according to Article 87 paragraph 3 letter b) of the EC Treaty aid, creates the environment for its unobtrusive operation. For (today's Article 107 paragraph 3 letter b) of the TFEU). example, the realization of the free movement of goods will not Typically, however, state aid for R&D&I will be evidenced by be quite possible in a situation where the goods in question are an exception pursuant to Article 107 paragraph 3 letter b), competing with an alternative that the subsidized entrepreneur according to which aid intended to facilitate the development of can afford to sell at prices that do not reflect the costs of its certain economic activities or economic areas can be considered production. compatible with the European single market, if they do not On the other hand, there is a need to clearly define the rules change the conditions of trade to such an extent that it would be applicable to all (member states) for exceptions to the above state contrary to the common interest. aid ban. This happens, for example, in areas where there is an The beginnings of state aid regulation of R&D&I go back to obvious market failure, i.e. for example when supporting the so- the 1980s, when the Commission issued the first framework called Services of General Economic Interest (SGEI). In defining the conditions for the compatibility of public R&D&I connection with the system of exceptions to the prohibition of support with the common market. The importance of research public aid, this area of legal regulation is thus enriched by an and development as a general interest of the Union has also been essentially political aspect. These aspects appear both at the level enhanced by the revision of the founding treaties, the of the Union (for example, the exception for significant projects consequence of which is the above-mentioned wording of Article of common European interest listed in Article 107(3)(b) of the 179 of the TFEU. The political dimension of the importance of TFEU) and at the level of the Member States. R&D&I is the reason for the Commission's favorable approach to authorizing public subsidies in this area. This is manifested on the one hand within the current Framework for State aid for 3 STATE AID OF R&D&I R&D&I (‘Framework’) 4 which represents and examplary of The European Union generally favors research, development soft-law instrument, in which the Comission reveals its opinions and innovation (‘R&D&I’). In its Article 179, the TFEU contains regarding the interpretation and application of R&D&I state aid a provision according to which the Union aims to "strengthen its law. According to the current wording of the Framework, state scientific and technological foundations by creating a European support for R&D&I can thus be compatible with the European research area in which scientists, scientific knowledge and single market if it can be expected to mitigate market failure by technology move freely". For this purpose, according to this supporting an important project of common European interest or article, it is necessary to support businesses and research by facilitating the development of certain economic activities, organizations in their efforts to cooperate. However, this and if the subsequent distortion of economic competition and objective may be in conflict with another important objective of trade is not contrary to the common interest [2]. the Union. It is the above-mentioned effort to build and protect In 2012, the Commission also decided to modernize state aid the health of the European single market, protected from the law. The aim of this modernization was to regulate those state negative impact of state or public subsidies. and public aids, that have the greatest impact on the European R&D&I subsidies can therefore potentially distort single market, so that even after limiting the negative effects of competition in the European single market. This happens aid, it is still possible to achieve the main priorities of the Union, especially in cases where the state aid does not induce additional which are the growth and competitiveness of the Union. At the activities on the part of the beneficiaries beyond those that the same time, the new rules were supposed to be “streamlined”. The recipient would have carried out even if such aid did not exist. logic behind this justification is that the regulation of state aid The effect of state aid can thus be perceived as an increase on the can help the efficiency of public budgets and correct the so-called input side (i.e. supported companies invest more of their own market failure. The process of revising the existing rules lasted resources in R&D&I as a result of state aid) or an increase on the almost two and a half years, from the first public consultations at output side (i.e. more outputs or R&D&I results are created the end of 2011 until the adoption of the new rules in May 2014. precisely as a result of state aid). Regulation of state aid can Recently, Commission launched a public consultation ensure its increased effectiveness by requiring providers to focus inviting all interested parties to comment on a proposed targeted state aid on projects that would not have occurred in the absence revision of the Framework. Interested parties were called to of their state aid[1]. participate in a public consultation which lasted eight weeks According to the Commission 3 , State aid of R&D&I is (until 3. June 2021). The goal of this new revision is, according enabled by the wording of the TFEU itself, specifically in two Vice-President Margrethe Vestager, further simplyfication of places. State aid of European R&D&I is enabled by Article 107 existeing State aid rules. New framework, which shall be the paragraph 3 letter b), according to which aid intended to help the result of this latest modernization effort, shall concern itsfef with implementation of a significant project of common European the following: interest can be considered compatible with the European single 3 The European Commission is the executive of the European Union. This text uses 4 Framework for State aid for research and development and innovation was the abbreviation “Commission” hereinafter. published by the Commission in the Official Journal of the European Union (2014/C 198/01) on 27.6.2014. 222 • Clarification of definitions, particulary public financing of RO’s economic activities can also be • innovation clusters, allowed. These are cases where the economic activity is purely • industrial research and experimental secondary (ancillary). According to the Commission, such development as well as organizational secondary economic activity is an activity that meets the innovation, following conditions: • innovation activities of SMEs. • the same inputs (e.g. material, equipment, labor and fixed • Compatibility criteria to allow support for technology capital) used for this economic activity are used for other infrastructures to reflect market and technology non-economic activities, evolution and to incentivize research, development and • the economic activity in question is directly related to the innovation investments [3]. operation of the research organization and • is necessary for its operation or • is inextricably linked to its main non-economic use, 4 RESEARCH ORGANIZATION AND • the scope of this activity will not exceed 20% of the total KNOWLEDGE TRANSFER annual capacity of the given entity. Accordign to EU law a ‘research and knowledge-dissemination According to Wendland, we can classify the above criteria into organisation’ (‘RO’) means an entity (such as universities or qualitative criteria and quantitative criteria [5]. The result of the research institutes, but also technology transfer agencies or othe qualitative view is thus the answer to the question whether the innovation intermediaries, etc.), irrespective of its legal status research organization is really used almost exclusively for non- (organised under public or private law) or way of financing, economic activity and the economic activity is directly related to whose primary goal is to independently conduct R&D&I or to and necessary for the operation of the research organization, or it disseminate the results of such activities (e.g. by teaching, is intrinsically linked with its main non-economic use. Based on publications or knowledge transfer activities) [4]. As stated a quantitative perspective, we then determine whether economic above, these can be private organizations as well. Nevertheless, activities consume exactly the same inputs (such as material, companies that can exert a decisive influence upon a private RO, equipment, labor and fixed capital) as non-economic activities in the quality of, for example, shareholders or members, shall not and the capacity allocated each year to economic activity does enjoy preferential access to the results generated by it [4]. not exceed the above-mentioned 20% of total capacities. In addition to the primary activities of the RO (education, basic In this context, however, Wendland, in my opinion, rightly research, etc.), according to the Commission, the public reminds us that it is necessary to assess quantitative and dissemination of research results (typically in the form of qualitative criteria cumulatively and that the 20% limit has no publications, open access databases, or open software) also has a support in the decision-making activities of the Commission or non-economic nature and can be thus subsidised [2]. Part of the EU courts5 . In the end, the qualitative criteria mentioned knowledge dissemination activities are activities in knowledge above will always be decisive. transfer (‘KT’). However, according to the Framework, KT activities are considere non-economic, only if the profit from these activities is reinvested in the primary activities of the ROs. 5 (NON) ECONOMIC INTERACTIONS OF Knolwedge transfer is definied in the Framework very ROs AND COMPANIES extensively as any process which has the aim of acquiring, According to the Framework, independent research conducted collecting and sharing explicit and tacit knowledge, including with the aim of obtaining new knowledge and a better skills and competence in both economic and non-economic understanding of a given topic is the primary activity of a activities such as research collaborations, consultancy, licensing, research organization, which is considered non-economic. spin-off creation, publication and mobility of researchers and However, according to the Framework, under certain other personnel involved in those activities. Besides scientific circumstances it is considered permissible that even research that and technological knowledge, it includes other kinds of is financed by private means is not considered an economic knowledge such as knowledge on the use of standards and activity in the sense of the state aid rules. Such situations are in regulations embedding them and on conditions of real life the case of research that takes place within the framework of operating environments and methods for organisational effective collaboration between a research organization and a innovation, as well as management of knowledge related to company or companies (i.e. in the words of the Comission identifying, acquiring, protecting, defending and exploiting “undertakings”). intangible assets [2]. In such research cooperation, both partners contribute to the The most important takeaway here is that ROs meeting the success of a joint research project. Both partners in these projects conditions set out in the GBER and the Framework are, de-facto, also share the risks and subsequently also the outputs (i.e. project outside of the scope of state aid law regulation. However, the results). Compared to the above, contract research is conditions here are, (1) the above mentioned reinvestment and characterized by the fact that the industrial partner (undertaking) (2) no cross-susidization of their economic activities. Even this unilaterally assigns research tasks to the RO and bears the full rule though, has its exemptions. Under certain circumstances costs of this activity, including the usual margin. 5 Court of Justice of the European Union (CJEU) consists of two separate courts: the Court of Justice and the General Court. Hence the abbreviation “EU courts” is used. 223 Collaboration is considered to be ‘effective’ if at least two may consider documents that were created (and are being independent parties cooperate: created) within the professional circles of organizations dealing • for the purpose of exchanging knowledge or technology or with the cultivation of relations between the academic and • to achieve a common goal. private sectors. As an example, the Commission's In order for the qualitative sign of effectiveness according to recommendation of 10 April 2008 on the management of the Framework to be fulfilled, the above-mentioned purpose intellectual property in knowledge transfer activities and on the should be achieved on the basis of the division of labor between code of good practice for universities and other public research the parties involved. Collaborating parties should jointly organizations (notified under number K (2008) 1329) is given, as determine the scope of the joint research project, jointly well as the recommendation entitled "Responsible partnerships ” contribute to its implementation and share not only its results, but published by European associations of universities (EIRMA and also the associated risks. On the other hand, according to the EUA), non-university research organizations (EARTO) and Commission, the collaboration is effective even if the costs of the knowledge transfer professionals (ASTP – Proton). aforementioned research project are borne in full by only one or Another example of non-economic interaction of RO and more parties, thus effectively relieving the other parties of their business (i.e. undertakings) is knowledge transfer. Knowledge financial risks. Contractual research and the provision of transfer in its current form is closely related to the adoption of research services are not considered forms of cooperation. the so-called Bayh-Dole Act in 1980 in the United States of In contrast to effective collaboration, research carried out on America. For the first time in that environment, this law allowed behalf of a company is usually carried out on the basis of an universities to own the results of state-funded research and assignment, or contractual conditions set by the company, or by development. The transfer of knowledge thus resulted from the the customer. The company also owns the results of research obligation of proper management of the newly acquired property. activities and bears the risk of the potential failure of the research The passage of this law was part of a long-term vision of the or the possibility of non-application of the results. Such research United States government, in addition to the Bayh-Dole Act, a will therefore be the economic activity of the RO and its, even number of new laws were adopted (for example, the Stewenson- partial financing from public budgets (typically in connection Wydler Act on Technological Innovation), and the goal of this with the use of equipment or employees' working time), is only reform was to increase the rate of use of publicly funded research possible if it is a purely anciliary activity (see above). Otherwise and their transfer to the private sector. the status of an RO (i.e. non-undertaking, exempted from the The aim of knowledge transfer activities is to convey state aid rules) could not be maintained. knowledge, ideally protected by some sort of intellectual The Issue Paper to the Framework also brings a more detailed property, into new or improved products and services. consideration to the topic of the definition of collaborative Schematically, the above-described path from an idea to a real research. According to the Commission, effective cooperation innovation can be described, for example, using the well-known does not happen in cases where clearly defined tasks are Technology Readiness Level ('TRL') scheme. Following this performed within the framework of a contract. Collaborative scheme, it could be said that the mission of knowledge transfer research is usually of a long-term nature. It is an "open-ended" is the transformation of knowledge into technologies and/or collaboration. The Commission emphasizes that it is practically products and the subsequent increase of their technological (and impossible to talk about collaborative research in cases where it market) maturity. was not preceded by a proper contract. Otherwise, the risk or, Pracitically, most of the knowledge trasnfer deals are enabled conversely, the benefit of the given cooperation could be by some sort of a license agreement in which the RO grants the retroactively allocated to the more powerful of the cooperating business partner rights, enabling it to use the knowledge partners [6]. generated by the RO legally. Especially with regard to the In my view, the key feature of contract researsch is that, provision of licenses, the Commission's statement contained in unlike in research collaboration, the company solely determines the so-called Issues Paper on the Framework can be considered the research assignment. The fact that the ownership of the slightly confusing. According to the paper, the transfer of results remains with the research organization and the company knowledge should primarily take place on a non-exclusive basis. was "only" granted access rights does not deprive such Non-exclusive licensing is, or should most certainly be the cooperation of the character of contractual research, but on the research organization's preferred way of commercializing other hand justifies the reduction of its price. The same is true in intellectual property. Especially when this type of licensing has cases of co-ownership of results. These considerations flow from the potential to maximize the economic benefits. In practice, the text of the Framework, which in point 26, within the chapter however, the situation where several partners are willing to dedicated to research on behalf of businesses (and in this context, compete with each other as non-excklusive licensees occurs only contract research or research services), deals with issues of rarely. In addition, it follows from the above consideration retention of ownership rights to intellectual property. The contained in the explanatory report that the non-exclusivity of the Framework literally states that "if the research organization or transfer is meant in relation to the primary activity, or the mission research infrastructure retains ownership of the intellectual of the research organization, which is the public dissemination of property rights or the relevant access rights, their market value research results on a non-exclusive and non-discriminatory basis may be deducted from the price to be paid for the services - for example through teaching, open access databases, publicly concerned". accessible publications or open software. The Commission also suggests that for the interpretation, or the definition of the term "effective collaboration in research" it 224 6 CONCLUSION Finally, it can be recommended that the RO should always reserve at least the right to use licensed invetions for its internal The enforcement of the european definition of RO and the ,non-commercial research and educational activities. Licensing emphasis on compliance with the state aid rules brought with it should also not jeopardize the fulfillment of the primary mission an interesting benefit (at least in Czech Republic where the of RO’s, which is the dissemination of knowledge in the true author is based) in that the organizations are forced to prove the sense of the word, i.e. to the general public. existence of their IPR norms and processes, which typically also deal with the application of rights to inventions. However, the REFERENCES state aid law continues to remain a scarecrow that keeps domestic research organizations in uncertainty regarding the acceptable [1] Bacon, Kelyn and QC, Kelyn Bacon, 2017. European Union Law of State Aid. . Oxford University Press. ISBN 978-0-19-878736-5..Google-Books- level of their knowledge transfer and application-oriented ID: p1njDQAAQBAJ. activities. [2] European Commission, 2014. Communication from the Commission — Framework for State aid for research and development and innovation. Public dissemination of R&D&I results is the mission of a Online. 2014.. Available from: https://eur-lex.europa.eu/legal- research organization. Therefore, the goal of knowledge transfer content/EN/ALL/?uri=CELEX%3A52014XC0627%2801%29. cannot be only the achievement of profit, but a wider, societal [3] European Commission, 2021. Explanatory note - Revision of the State aid rules for RDI Online. European Union. Available from: effect. In-house lawyers of universities, but also lawyers and https://competition-policy.ec.europa.eu/document/download/5cf6ccf6- legal proffesionals working for ROs, as well as in-house lawyers e46e-44ca-8ca3- d4ee5370f642_en?filename=RDIF_consultation_background_note.zip. and representatives of the industry, should thus honor this higher [4] Commission Regulation (EU) No 651/2014 of 17 June 2014 declaring goal and allow modern technology and new knowledge to reach certain categories of aid compatible with the internal market in application of Articles 107 and 108 of the Treaty Text with EEA relevance, 2014. places neglected by the market. These activities should certainly Online. [Accessed 7 September 2022]. Available from: not be hindered by the bureaucracy (whether European or http://data.europa.eu/eli/reg/2014/651/oj/eng domestic), especially through the formalistic interpretation of [5] Wendland, Bernhard von, 2015. New Rules for State Aid for Research, Development and Innovation. European State Aid Law Quarterly. 2015. competition law. Vol. 14, no. 1, p. 25–50 Non-exclusive licensing is, or should most certainly be the [6] European Commission, 2012. Issues paper - Revision of the state aid rules for research and development and innovation Online. Brussels: European research organization's preferred way of commercializing Commission - Competition DG intellectual property. In my view though, an exclusive patent [7] Wendland, Bernhard von, 2015. New Rules for State Aid for Research, license which resulted from ‘arm’s length’ negotiation, i.e. the Development and Innovation. European State Aid Law Quarterly. 2015. Vol. 14, no. 1, p. 25–50.; transaction between the contracting parties does not differ from [8] Nicolaides, Phedon, 2016. The Pricing of Access to Publicly-Funded those which would be concluded between independent Research Infrastructure and State Aid Rules. European State Aid Law Quarterly. 2016. Vol. 15, no. 1, p. 9–15. enterprises and with no element of collusionm, is perfectly non- [9] Schwendinger, Gerd, 2013. State Aid and Intellectual Property in Contract economic in nature. As mentioned above, all profits from such Research and R&D&I Collaboration. European State Aid Law Quarterly. activities need to be reinvested in the primary activities of the 2013. Vol. 12, no. 4, p. 685–698.. RO. 225 Effective collaboration and IP management Levin Pal Robert Blatnik Špela Stres Center for technology transfer Center for technology transfer Center for technology transfer and innovation and innovation and innovation Jozef Stefan Institute Jozef Stefan Institute Jozef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia levin.pal@ijs.si robert.blatnik@ijs.si spela.stres@ijs.si ABSTRACT innovation (R&D&I) [3], which has a status of EC communication and as such does not have a direct legal impact. This article summarizes the main findings of the national project As the content of the R&D&I framework is based on the GBER, entitled “Evaluation of IP as a basis for proposing a long-term it makes sense to consider the points of the R&D&I framework sustainable state aid model to promote science-business as if they were legally binding in practice. cooperation” (project V7-2145 of the targeted development According to the terminology of GBER [2] and R&D& I [3] the programme - CRP 2021) supported by the Slovenian Research term "undertaking" is used describing an entity carrying out an Agency and the Slovenian Ministry of Education, Science and economic activity consisting of offering products or services on Sport) [1]. a given market (point 17 in R&D& I [3]) such as small, medium- The research was focused to the situations related to the sized and large enterprise (point 15 in R&D& I [3]). Intellectual Property (IP) management in collaborative projects The abbreviation “RKDO” stands for "Research and Knowledge of the following characteristics: Dissemination Organization or Research Organization” as (i) effective collaboration between undertakings and RKDOs defined in article 2, paragraph 83 of GBER [2] and point 15 (ee) takes place and; of R&D& I [3]. (ii) the project is financed by the state (e.g. cohesion funds The phrase “collaborative project” means the project carried out through ministries, agencies etc.) and; through “effective collaboration” as defined in point 27 of (iii) the results of project are expected to contain IP that due to R&D& I [3] (see the full definition in the following text). possible commercial interest may or may not be published and The “aid intensity” is the maximum gross amount of state aid widely disseminated, but rather protected (e.g. as a business that can be granted per beneficiary (undertaking or RKDO), secret, patent application or other form of IP).The aim of this expressed as a percentage of eligible costs, before any deduction study was to determine (i) meaningful guidelines for intellectual of tax or other charge (point 15 c in R&D& I [3]). property (IP) management in collaborative projects and (ii) the For the purpose of this article the term “consortium” means a most typical way of assessing the market price of IP for the case group consisting of at least one or more undertakings and one or of licensing or selling IP to third parties interested in using it for more RKDOs that “effectively collaborate” among each other in commercial purposes. the framework of national collaborative project funded to certain KEYWORDS extent by the state (the type of collaboration as described in article 25, paragraph 6 (b) (i) in GBER [2]). Effective collaboration, collaborative projects, IP - Intellectual Property, Background IP, Results, Foreground IP, State Aid, 2. RESULTS AND DISCUSSION Undertaking, RKDO - Research and Knowledge Dissemination Organization, GBER - General Block Exemption Regulation [2], Key characteristics of collaborative projects taking place through R&D&I - Research & Development & Innovation framework [3] effective collaboration between research and knowledge dissemination organizations (RKDO) and companies 1. INTRODUCTION (undertakings) associated to the maximum allowed intensities of The General Block Exception Regulation (GBER) of EC [2] state aid funding were followed by general guidelines regarding declares certain categories of aid compatible with the internal management of IP in such projects and more detailed description market in application of Articles 107 and 108 of the Treaty on referring to the management of Background IP – owned by one the Functioning of the European Union (TFEU). Aid for research or more project partners before the beginning of collaborative and development and innovation is one of the GBER categories project; and Foreground IP – jointly created by the partners in the and the principles of its proper implementation are explained in course of the collaborative project. Typical and less common Framework for State aid for research and development and ways of IP commercialization in accordance with the state aid rules were schematically represented along with the types of recommended agreements at individual steps 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 distributed commercialization. Different options are further described for profit or commercial advantage and that copies bear this notice and the full regarding the IP transfer and market price determination. 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 2022, 10–14 October 2022, Ljubljana, Slovenia 3. CONCLUSIONS © 2020 Copyright held by the owner/author(s). The most important findings are: (i) the relations between the partners regarding the ownership and access of Background IP 226 have to be well regulated in advance prior to the start of the Articles 107 and 108 of the Treaty. https://eur-lex.europa.eu/legal- content/EN/TXT/PDF/?uri=CELEX:02014R0651-20170710&from=EN collaborative project; (ii) the typical and most useful path for the (last accessed August 7 2022) transfer of IP includes the following steps: valuation of IP, [3] R&D&I - Framework for State aid for research and development and effective negotiations; determination of the IP market price and innovation. Information from European Union institutions, bodies, offices and agencies. European Commission. Communication from the conclusion of IP license or IP sales and/or IP exploitation and/or commission. (2014/C 198/01). https://eur-lex.europa.eu/legal- new collaborative project consortium agreement. content/EN/TXT/PDF/?uri=CELEX:52014XC0627(01)&from=EN (last accessed August 7 2022) [4] Guidance How to draw up your H2020 consortium agreement. 2020. European Commission. Directorate-General for Research & Innovation. https://ec.europa.eu/research/participants/data/ref/h2020/other/gm/h2020 -guide-cons-a_en.pdf (last accessed September 30, 2022) ACKNOWLEDGEMENTS: [5] Kaiser L., Neu M., Teernstra, F. 2020. State Aid on R&D&I – The Right Way. EARTO - European Association of Research and Technology Slovenian Research Agency and the Slovenian Ministry of Organisations. Brussels. https://www.earto.eu/wp- Education, Science and Sport are greatly acknowledged for content/uploads/EARTO-Report-on-State-Aid-on-RDI-The-Right-Way- Final.pdf (last accessed August 7 2022) supporting the project CRP 2021 Nr. V7-2145. In addition, we [6] Kebapci, H., Von Wendland, B., Kaymaktchiyski, S., State Aid Rules in would like to thank sincerely to the project content supervisor Research, Development & Innovation. Addressing Knowledge and Mateja Struna and the legal experts, especially Lorenz Kaiser, Awareness Gaps among Research and Knowledge Dissemination Organisations. Decision Tree, Kaiser, L. (Ed.), Neu, M. (Ed.), Teernstra, Michel Neu, Folkert Teernstra and Stoyan Kaymaktchiyski for F. (Ed.), Nicolaides, P. (Ed.), EUR 30436 EN, Publications Office of the valuable and useful discussions, patience and help in European Union, Luxembourg, 2020, ISBN 978-92-76-25081-4, understanding the complex state aid rules and pleasant company doi:10.2760/675525, JRC122304: at the workshop in Bratislava [15]. https://publications.jrc.ec.europa.eu/repository/bitstream/JRC122304/kjn a30436enn.pdf (last accessed September 11 2022) [7] Andonova, E., Barrada, M., Bole, D., Gulda, K., Hudson, J., Jimenez, V., LEGAL DISCLAIMER: Karanikic, P., Kaymaktchiyski, S., Kokorotsikos, P., Koycheva, C., The authors of this paper used reasonable efforts to include accurate Mladenov, T., Rizzuto, C., Shvarova, O., Taylor, S., Teernstra, F., Strategic evaluation of the Bulgarian Centres of Competence and Centres information on the state aid rules related to the collaborative projects, of Excellence and recommendations for their further development: but we, however, make no warranties as to the accuracy of the content https://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/bulgari and statements and assume no liability or responsibility for an error or an_centres/bulgarian_centres_report.pdf (last accsessed September 11 omission in the content of this article. 2022) [8] Law on employment related inventions (ZPILDR), Uradni List RS, št. Please be advised that nothing in this article constitutes legal advice. If 15/07. http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO361. (last there are any particular concerns to be addressed, please contact a accessed October 4, 2022) lawyer directly so that your specific circumstances can be evaluated. The [9] Slovenian accounting standard – SRS, Uradni List RS, šr. 95/15. authors of this article will not be held liable for any decisions one may http://www.pisrs.si/Pis.web/pregledPredpisa?id=DRUG4192. (last take pursuant to the information and observations provided in this accessed October 4, 2022) [10] International Valuation Standards Council. 2022. International valuation article. The content of this article will not constitute an official position, standards,.https://propertyinstitute.nz/Attachment?Action=Download&A decision, legal advice or guidance from the authors, nor from the “Jozef ttachment_id=5117 (last accessed October 4, 2022) Stefan” Institute, nor from the experts listed in the acknowledgments [11] Flignor P., Orozco, P., 2006. Intangible Assets & Intellectual Property section. Valuation: A Multidisciplinary Perspective, IPthought.com, https://www.wipo.int/export/sites/www/sme/en/documents/pdf/ip_valuati on.pdf. (last accessed October 4, 2022) REFERENCES [12] Trade Secrets Act (ZPosS), Uradni List, št. 22/19. http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO7758. (last [1] Pal L., Stres Š., Blatnik R., Lutman T., Justin T. 2022. Evaluation of IP as accessed October 4, 2022) a basis for proposing a long-term sustainable state aid model to promote [13] Copyright and Related Rights Act (ZASP), Uradni List, št. 16/07. science-business cooperation. Final report of the project nr. V7-2145 of http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO403. (last the targeted development programme - CRP 2021. Jozef Stefan Institute, accessed October 4, 2022) University of Primorska, Slovenian Research Agency and the Slovenian [14] Industrial Property Act (ZIL-1), Uradni List RS, št. 51/06. Ministry of Education, Science and Sport. (Slovenian language only and http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO1668 not published yet) [15] Innovation and Technology Transfer in Central and Southeast Europe, [2] GBER – General Block Exemption Regulation. COMMISSION European Commission, Knowledge4Policy. Bratislava, 19.5.2022 REGULATION (EU) No 651/2014 of 17 June 2014 declaring certain https://knowledge4policy.ec.europa.eu/event/innovation-technology- categories of aid compatible with the internal market in application of transfer-central-southeast-europe_en 227 Project support services of a technology transfer office Tomaž Lutman Špela Stres Center for Technology Transfer and Innovation Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia tomaz.lutman@ijs.si spela.stres@ijs.si ABSTRACT 1 INTRODUCTION The Center for Technology Transfer and Innovation (CTT) at the Technology transfer offices and project support offices at the Jožef Stefan Institute (JSI) offers not only services related to technology transfer, but also project support services. Database public research organizations are sometimes two units (i.e. of project calls established by CTT serves as an important tool to National Institute of Chemistry, Slovenia) and sometimes inform researchers about relevant calls. Establishing a merged in one unit (i.e. KU Leuven, Belgium). Experience in consortium of project partners or joining one that is already creating impact, management with intellectual property, established is also an important step in project work. Further technical background and good connections with researchers support such as writing of project proposals, identifying and should be values of each technology transfer unit. These kinds of planning impact of the project, managing data, providing gender expertise are useful also in preparing R&D project proposals and equality, management, financial, legal and administrative management of the project consortia. Using national/regional support is crucial for successfully acquiring and running a project. funding is also one of the most common pathways to raise In June 2022 we performed a survey which targeted researchers Technology Readiness Level and transfer technology to industry. at the institute. It provided quantitative and qualitative analysis of project support services available at the JSI. If technology transfer support and project services are carried out at one unit, a one-stop-shop service can be offered to researchers, KEYWORDS which we see as an advantage. Further specialized knowledge in project management is needed, such as legal, financial and other project support services, management, technology transfer, expertise. project’s impact, public funding POVZETEK 2 PROJECT SUPPORT SERVICES The following project support services are offered at the CTT, Center za prenos tehnologij in inovacij (CTT) na Institutu Jožef JSI. Stefan (IJS) poleg storitev, povezanih s prenosom tehnologij, ponuja tudi storitve za podporo projektom. Baza projektnih 2.1 Finding right call razpisov, ki jo je vzpostavil CTT, je pomembno orodje za obveščanje raziskovalcev o relevantnih razpisih. Pomemben Getting a project can result from two options. In the first option korak pri projektnem delu je tudi vzpostavitev konzorcija ali the organisation identifies a call, suitable for its expertise and pridružitev k že vzpostavljenemu konzorciju. Nadaljnja podpora, builds a project idea and project partner consortium based on kot je pisanje projektne prijave, prepoznavanje in načrtovanje guidelines in the call. The second option occurs when a vpliva projekta, upravljanje s podatki, zagotavljanje enakosti consortium is already established and the project prepared. In spolov, upravljanje, finančna, pravna in administrativna podpora, that case the consortium looks for a call that would fit their je ključnega pomena za uspešno pridobitev in izvedbo projekta. consortium and project proposal. Often modifications are made Junija 2022 smo izvedli anketo, ki je bila namenjena in order to correspond to the call. raziskovalcem inštituta. Z njo smo pridobili kvantitativno in In both cases a good overview of published and forthcoming calls kvalitativno analizo storitev projektne podpore, ki so na voljo na as well as their conditions and deadlines is needed. This can be IJS. delivered to researchers in different ways – using internal KLJUČNE BESEDE database, newsletters, direct communication, etc. In 2017 CTT established database of research and innovation storitve projektne podpore, upravljanje, prenos tehnologij, vpliv calls, which is still active [1]. The database is searchable and projekta, javno financiranje different filters such as technical field, financer, deadline, opening data, can be applied in order to optimize the set of calls a user is looking for. The database includes calls which are 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 directly relevant for JSI which means that JSI can apply as an for profit or commercial advantage and that copies bear this notice and the full applicant. Furthermore, indirectly relevant calls where JSI’s role citation on the first page. Copyrights for third-party components of this work must could be in subcontracting are included in the database. The be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia database contains calls published by Slovenian, European and © 2020 Copyright held by the owner/author(s). other authorities and bodies. It is designed in a way that calls are automatically archived when the deadline passes. In order to 228 keep the database up to date, once per month relevant sources are Enterprise Europe Network and it represents an important tool reviewed and new calls inserted in the database. It is offered only for establishing partnerships. to JSI’s employees, which is arranged by limited access with Partners can be found also by several other means such as institutional Internet Protocol address. other networks, platforms and communities, brokerage events, Beside the infrastructure (database) relevant information about direct contact by email/phone – targeted or by e-blast – and other. the suitable calls should be delivered to researchers. This is done Once contacts between possible partners are established, in different ways – through more systematic way using video-call or personal meeting is advised to be organized in order newsletter and mailing lists or for specific technology. to establish personal relationship and discuss cooperation It is necessary that conditions of the calls are studied and most directly. suitable are identified. It is also advisable to establish a link with The further discussions can require concluding written a contact person or national contact point (usually ministries and agreements such as non-disclosure agreements, letters of intent, agencies) in order to discuss the compatibility of expertise, material transfer agreements etc. which requires legal support in organisation status and other characteristics with the call. For drafting, negotiating and signing such contracts. example, the Horizon Europe programme has a helpful and well organized network of National Contact Points. This is useful for 2.3 Writing the project proposal companies as well as research organizations. Usually it is crucial Public authorities expect very well prepared project proposals for for small companies without experience in project proposals and published calls. One of the reason is that a financer doesn’t want dedicated units. to take the risk of financing unclear and not well planned projects. 2.2 Establishing partnership A project proposal can be defined in different ways. It can be: Most of the research and innovation projects are done in • A document which includes all the information needed by cooperation with more partners. Sometimes JSI is in position to relevant stakeholders to make management decisions. coordinate the project and in other cases its role is more suitable • A document that transforms an “idea” or “policy” into an as a partner, associated partner or subcontractor. The partnership effective/doable project. for project proposals can be established with existing partners • A document used to convince a “sponsor” to finance a from past projects or other types of cooperation. It is also good project or to let you implement it. to look for new partners in order to bring new ideas to the project. • A document which serves as a key management tool (“road- This can be done in different ways. map”) for the implementation of a project. Enterprise Europe Network is the largest European network that connects industry with research organizations, operated by Project proposals of Horizon Europe and other research and the chambers of commerce, technology transfer offices, innovation funding calls normally consist of three parts: 1) innovation agencies and similar nodes [1]. Its main tool is a Excellence; 2) Impact; and 3) Quality and efficiency of the publicly available anonymized brokerage database with implementation. As a rule, researchers prepare scientific parts of business/technology offers/requests as well as partner search the proposal in part 1) and 3). In part 1) it is usually expected to publications. Specific guidelines must be followed in order to explain also how the data will be managed and how gender prepare such publications. This results in well prepared equality will be provided. Sometimes also some other non- publications so dissemination activities are normally easy and technical content is expected such as interaction with initiatives, suitable companies, research institutions and other organizations living lab concepts etc. Researchers are often not familiar with across Europe are quickly informed. CTT-JSI is a member of these parts. This is usually the case also with chapter 2) Impact. Figure 1: Pathway to impact, example by European Commission [3] 229 A one-stop-shop service to support these sections of the project In order to achieve expected impact, suitable measures must is needed. It should be noted that there is no single standardized be taken. Dissemination, communication and exploitation must way/text suitable for all projects. In order to prepare these parts be effective and well coordinated. Public dissemination and to fit well into the project, suitable partners with relevant communication is normally an obligation in publicly funded expertise should be found and the strategy prepared with projects. This request is reasonable, since the public (including effective communication. For a successful project proposal relevant stakeholders) funds the research and development different analysis such as state-of-the art and market analysis activities and should be informed about them. The Open Science should be prepared. Often a research group already has a lot of principles are gaining on importance. Not just publications about important information gathered, so having an interview with research, but also related data that was acquired during the them is a good start. project is expected to be published. With the help of open science, all stakeholders in society will gain important access to 2.4 Impact knowledge. Generally, a project applicant should describe the qualitative and Communication activities are constantly changing and quantitative impact of the project as well as what measures will adapting to new trends. In the past, physical promotion materials be implemented to reach it. such as flyers and brochures were more significant. Nowadays, The term impact describes all the changes which are expected social networks, new internet platforms and other forms are to happen due to the implementation and application of a given gaining importance. This trend was accelerated during the intervention. Such impacts may occur over different timescales, COVID19 pandemic. affect different actors and be relevant at different scales (local, Although dissemination is expected from project partners, national, etc.). Impact is the last link in the results chain suitable protection of intellectual property (IP) and exploitation according to the theory of change: inputs–>activities– of results should also be accomplished. In order to accomplish >outputs(results)–>outcomes–>impact. An illustrative example both dissemination and protection of IP, the best way is to file with artificial intelligence for a forecasting system in airports is patent applications for developed inventions. Sometimes the shown in Figure 1. generated knowledge is not patentable or patent protection is not Project proposals usually include scientific, economical, reasonable. In case such know-how has a big commercial value societal, and environmental impacts. Scientific impact includes or is expected to have one, it should be protected as a secret creating quality new knowledge, strengthening human capital in know-how. Important part of exploitation activities is to have a research and development, and encouraging the spread of suitable business model, partners and end-users which are knowledge and open science. In EU projects, societal and interested in accepting new technologies. environmental impacts are expected to be reached by addressing EU policy priorities and global challenges through research and 2.5 Data management innovation as well as strengthening the acceptance of research In comparison with Horizon 2020 projects, it is expected to better and innovation in society. Economic impact involves creating manage data in Horizon Europe projects. The data management growth based on innovation, creating more and better jobs, and should follow FAIR (Findable, Accessible, Interoperable, utilization of investments in R&I. Reusable) principle. Already in the project proposal, the project consortium should have a good picture of what type and size of Figure 2. Need for project support service by JSI researchers according to internal survey 230 data will be generated in the project. The data generated in with financial reporting and support with project management laboratories and other locations should be well structured and when JSI is coordinator. labelled. Metadata should be generated. An appropriate trustworthy repository with possibility to assign persistent Table 1. Project support of different units at the JSI. Service identifiers should be chosen and used to upload the data. Good providers at the JSI in the survey were as follows: U1 - Director's practices for these activities are advised to be reviewed and Office; U6 - International Project Office; CTT; SRIP TOP - Strategic followed. By consistent upload of data to repository, an effective Research & Innovation Partnership Factories of the Future; SRIP PMiS dissemination is accomplished. These activities should be well - Strategic Research & Innovation Partnership Smart Cities and Communities. Other*: 1) They haven't needed help so far. 2) They were aligned with IP protection strategy. An important aspect is also not aware of the possibility of internal assistance. 3) Help from external safety which has to be assured in order to protect sensible data consultants. 4) They did not apply to this group of calls. ERC - including personal data from cyber attacks. European Research Council; EIC - European Innovation Council; MSCA - Marie Skłodowska-Curie Actions; ESA - European Space Agency; ARRS - Slovenian Research Agency; MIZŠ - Ministry of 2.6 Gender equality Education, Science and Sport; MGRT - Ministry of Economic Articles 2 & 3 of the Treaty of Amsterdam (1997) and other EU Development and Technology. policy directives (i.e. COM (96) 67 final) foresee principles of gender mainstreaming which should be incorporated in every project [4], [5]. Gender equality in projects is targeted in two ways. Firstly, the consortium team is expected to be gender balanced in the terms of equal number of women and men. Secondly, the content of the project must take into account gender balance. An example is assuring gender balance of tested persons in clinical trials during validation of a new drug. Another example would be to design an algorithm for car safety which corresponds to a man and woman driver. Gender equality is also empowered by stimulation to establish a gender equality plan. Beginning with Horizon Europe calls in 2022, public bodies, We were also interested to get feedback from research organisations or higher education establishments surveyees, from which units at the JSI they get most support for (including private research organisations and higher education a specific group of projects. The results are shown in Table 1. establishments) must have an established gender equality plan Based on the survey, major project support providers are CTT, [6]. Different projects, initiatives and platforms such as U6 and U1 and in a smaller portion SRIP TOP. The notable results not shown in Table 1 are following: There is no need for ATHENA, RePower Women are established to promote gender support within the JSI: most prominently in ARRS calls (49%), equality [6], [8]. MIZŠ/MGRT calls and other Slovenian agencies and ministries (39%), and projects from other agencies (21%). Researchers are 2.7 Management, financial and administrative familiar with the possibility to turn to someone within the JSI support for help: between 93% (ERC calls) and 77% (ARRS calls). Use Management of the project is an important task in performing the of external consultants’ services is following: a) mostly for Horizon Europe 3rd pillar (EIC, Pathfinder) and the ARRS project, especially for a coordinator. Planning, monitoring, scheme (8%) b) rarely for MIZŠ/MGRT calls and other executing and reporting are activities which should be mastered Slovenian agencies and ministries (3%). When external by a good manager. In case of bigger projects, tasks should be consultants were sought, researchers used different approaches divided and researchers should be supported with management. to find them (Figure 3). Different IT tools can be used for the management such as Microsoft Project. Finances should be well planned and expenditure tracked. 3 DEMAND FOR SERVICE, SURVEY AT THE JSI In June 2022 we performed a survey, in which we asked JSI researchers which project support services they use and by which JSI’s unit, which services are important to them and what improvements do they suggest for the future. 44 researchers have filled out the survey. 90% of them expressed their need for Figure 3. Looking for external consultants to prepare the support and 95% said that they would like to have an overview project application of services available at the JSI. 44% of researchers expressed their willingness to Figure 2 shows the rate of importance of each service participate in the design of future project support at the JSI. They for researchers on scale 1-5, where 1 is not important and 5 is also proposed some suggestions for improvements: very important. As most important the researchers have • identified support with the writing section ‘impact’, assistance Better definition of the services of individual providers of project support services at the JSI. 231 • Providing comprehensive support in the "non-scientific" REFERENCES parts of the application (impact, finance, GEP, promotion) and faster response regarding contracts (e.g. NDA). [1] OVERVIEW AND SEARCH OF CURRENT PUBLIC CALLS. Center for Technology Transfer and Innovation at the Jožef Stefan In • stitute. Available Possibility of internal review of the entire project 2.9.2022 on webpage http://tehnologije.ijs.si/?page_id=3028 application and advice for improvements by a person with [2] ENTERPRISE EUROPE NETWORK. Available 2.9.2022 on webpage experience in EU project reviews. List/analysis of the most https://een.ec.europa.eu/ common reasons for project rejection. [3] Horizon Europe Programme Guide. Version 2.0. 11 April. 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Official Journal C 340, 10/11/1997 P. 0001 – 0144 Main findings of the survey are that (i) researchers need support [5] COMMUNICATION FROM THE COMMISSION "INCORPORATING with project management, (ii) CTT is recognized as the main EQUAL OPPORTUNITIES FOR WOMEN AND MEN INTO ALL COMMUNITY POLICIES AND ACTIVITIES Available 2.9.2022 on service provider, but also other units at the JSI are very webpage https://op.europa.eu/en/publication-detail/- important, (iii) project support services of JSI’s units should be /publication/3fc7ca58-d2a7-418c-b02d-1f075b50619c/language-en better represented and communicated. [6] Horizon Europe Work Programme 2021-2022. 13. General Annexes. The pre-grant project support services provided by (European Commission Decision C(2022)2975 of 10 May 2022). Available CTT are currently not charged to researchers. Financing of this 2.9.2022 on webpage https://ec.europa.eu/info/funding- is not adequately addressed and is expected to be properly tenders/opportunities/docs/2021-2027/horizon/wp-call/2021-2022/wp-13- general-annexes_horizon-2021-2022_en.pdf resolved. In October 2022 Slovenian Ministry of Education, [7] Implementing gender equality plans to unlock research potential of RPOs Science and Sport published a call for project support service, and RFOs in Europe (ATHENA). Grant agreement ID: 101006416. which is a good start to improve this field. European Commision. Available 2.9.2022 on webpage https://cordis.europa.eu/project/id/101006416 [8] RePower Women. Possibilities for Women in Technologies and Innovation. Available 2.9.2022 on webpage https://www.gov.pl/web/ncbr- ACKNOWLEDGMENTS / ZAHVALA en/repower-women-possibilities-for-women-in-technologies-and- innovation We acknowledge the colleagues at the Center for Technology Transfer and Innovation CTT, Director's Office U1, International Project Office U6 for preparing the survey and exchanging views in suitable project support services at the Jožef Stefan Institute. 232 Challenges of Legal and Regulatory Framework for Blockchain Technology in the EU Izzivi zaščite tehnologije veriženja podatkovnih blokov v EU Urška Fric Jurij Urbančič Knowledge and Technology Transfer Office Laboratory of Organic Matter Physics Faculty of Information Studies in Novo mesto University of Nova Gorica Rudolfovo – Science and Technology Centre Novo mesto Nova Gorica, Slovenia Novo mesto, Slovenia jurij.urbancic@ung.si urska.fric@fis.unm.si ABSTRACT KLJUČNE BESEDE While blockchain is one of the crucial emerging technologies Tehnologija veriženja podatkovnih blokov, pravice shaping Europe’s digital future, blockchain protection in the intelektualne lastine, zaščita, izzivi, EU domain of IPR is not clearly defined. This status quo, therefore, necessitates an examination of this field – to arrive at a clear legal basis which would regulate blockchain 1 INTRODUCTION technology protection it is necessary to define and address Blockchain technology as one of the technologies of the crucial points. The following paper presents the Industry 4.0 significantly affects how businesses operate challenges of blockchain protection in the EU. It starts by while revolutionizing numerous innovation ecosystems1 [1]. introducing blockchain technology from theory to practice, In 2018, 21 Member States and Norway agreed to sign a followed by the existing conditions of the current legal and declaration to establish a European Blockchain Partnership regulatory framework and the most common challenges for (EBP) and to work together to establish a European blockchain technology protection, and concludes with Blockchain Service Infrastructure (EBSI) to support the proposals for further research in this field. delivery of cross-border digital public services with the highest standards of security and privacy. Since then, eight KEYWORDS more countries have joined the partnership [3]. EBP Blockchain Technology, Intellectual Property Rights (IPR), nowadays consists of the EU 27 Member States, Protection, Challenges, EU Liechtenstein, and Norway. The European Union (EU) and Europe have taken a step POVZETEK forward in balancing the legal, regulatory and policy Četudi je blockchain tehnologija oz. tehnologija veriženja frameworks of the EU Member States in crypto assets [4]. In podatkovnih blokov na eni strani ena izmed ključnih (še 2020, the European Commission (EC) has published a new vedno nastajajočih) tehnologij, ki oblikuje digitalno proposal for " Regulation of the European Parliament and the prihodnost Evrope, na drugi strani njena zaščita na področju Council on markets in crypto assets" [5]. This proposal is part pravic intelektualne lastnine še vedno ni povsem jasno of the Digital Finance Package, a comprehensive package of opredeljena. Da bi v prihodnosti prišli do vsem deležnikom measures to further enable and support the potential of jasne pravne podlage, ki bi urejala zaščito tehnologije digital finance in terms of innovation and competition while veriženja podatkovnih blokov, je zato treba opredeliti in mitigating risks [6]. In addition to the proposal, the Digital obravnavati najpomembnejše kritične točke. V prispevku Finance Package also includes a proposal to pilot the predstavljamo izzive na področju zaščite tehnologije regulation of market infrastructures using " Distributed veriženja podatkovnih blokov, ki jo predvideva trenutni Ledger Technology" (DLT), a proposal for digital operational pravno-formalni okvir EU. Najprej se osredotočamo na resilience and a proposal to clarify or amend specific related tehnologijo veriženja podatkovnih blokov od teorije do EU financial services rules. The EC’s priorities ensure that the prakse, nato na obstoječe pogoje veljavnega pravno- EU regulatory framework for financial services is innovation- formalnega okvira ter najpogostejše izzive pri zaščiti, na friendly and does not produce barriers to use of new koncu pa podajamo predloge za nadaljnje kritične točke, ki technologies. The proposal to pilot DLT regulation zahtevajo raziskave tega področja . represents the first concrete action in this field. [4] The World Intellectual Property Organization (WIPO) points out that blockchain technology affects all industries and it is in the interest of the intellectual property (IP) 1 Given that this paper is written in the context of the innovation substitute relations, that are important for innovative operation of an actor ecosystem it should be understood as the evolving set of actors, activities, or a population of actors [2]. and artifacts, the institutions and relations, including complementary and 233 community to investigate the impact of blockchain which is shared among and agreed upon a peer-to-peer technology on IP and to find appropriate models for the network. It consists of a linked sequence of blocks, holding application of blockchain technology in the field of IP [7]. timestamped transactions secured by public-key Blockchain technologies impact every industry and have cryptography and verified by the network community. Once been extensively used in IP; the WIPO Member States have an element is appended to the blockchain technology, it established a blockchain technology task force under the cannot be altered, turning a blockchain technology into an Committee on WIPO Standards (CWS). Its purpose is to immutable record of past activity". The concept of develop reference models for the use of blockchain decentralized blockchain technology has been firstly technology in the field of IP and to propose a new WIPO introduced by Satoshi Nakamoto in 2008 to provide standard that would support the potential use of blockchain technological support for Bitcoin – a peer-to-peer (P2P) technology in IP ecosystems. [1] electronic cash system [11]. Even though blockchain technology is recognized as a A schematic illustration of the blockchain technology technology with a relatively low maintenance cost, increased basics is shown in Figure 1, based on a very general transparency, reduced administrative burden, resilience to introduction [12]. One can broadly define blockchain fraud, and as versatile technology deployed in many sectors technology as a distributed system to record transactions. and businesses [8]; there are crucial questions which guide After a transaction is issued, it is announced inside the P2P us in this review-oriented paper: network made of nodes that record transactions in 1. How is blockchain technology prepared for IP? blockchain technology. The validator nodes decide if the 2. How is IP prepared for blockchain technology? transaction is valid or not based on the consensus protocol, 3. How can blockchain technology help protect IP? i.e., a set of defined rules implemented by all nodes that Irrespective of the three questions above and crucial for the regulate how new transactions are added. If the transaction paper is the status quo, as follows: the number of inventions is deemed valid, it is grouped with other recently approved involving blockchain technology (in the EU) is increasing [9]. transactions inside a new block linked to the previously At the EU level, those responsible for this field have taken this approved block. A completed transaction is made public on status quo seriously – even though the growth of blockchain blockchain technology. patent applications started in 2016. The official beginnings of blockchain technology Figure 1: The flow of the transaction confirmation protection in the EU date back to 2018 when the European process in the blockchain [12]. Patent Office (EPO) organized the first conference on blockchain technology [9]. At the conference, the EPO expressed its desire for organization of blockchain technology to ensure that patent-granting authorities grant blockchain patents that are legally robust in a predictable manner [9]. The EPO has highlighted computer-implemented inventions (CII) as the challenge researchers in this field face today regarding IPR. When we talk about blockchain inventions, we are talking about CII. The EPO has therefore developed stable criteria in this respect based on the case law The primary and most known application of blockchain on CII. " Blockchain patent applications" refer to a group of technology is in the field of cryptographic digital currency. generic patent applications related to blockchain technology There are over 10 thousand cryptocurrencies as of 2022 [13] [9]. This group can be divided into two sub-groups: (Figure 2a) with the total market cap of all currencies 1. patent applications related to core blockchain reaching more than 1 trillion dollars (as of August 2022 technologies (e.g., public key decryption, access [14]). The two leading cryptocurrencies Bitcoin (BTC) and control and block construction), and Etherium (ETH) alone both have market caps above 200 2. patent applications related to application (use) of billion dollars and have a market share of 38 % and 19 %, blockchain technologies (e.g., drug tagging, audit respectively (Figure 2b). These data show a growth of registration and food tagging). blockchain-based cryptocurrencies. In the following part of paper we, therefore, pay attention to both sub-groups – chapter 2 contains the introduction of blockchain technology from theory to practice. 2 BLOCKCHAIN TECHNOLOGY: FROM THEORY TO PRACTICE Based on the available peer-review literature, blockchain technology can be defined as [10]: "A distributed database, 234 enabled markets are to mature, policymakers and businesses must create the rules of engagement together [22]. EC emphasizes that the EU supports an EU-wide rule for blockchain to avoid legal and regulatory fragmentation. The EC, therefore, adopted a comprehensive package of legislative proposals for regulating crypto-assets to increase investments and ensure consumer and investor protection. This package updates specific financial market rules for crypto-assets and creates a legal framework for regulatory Figure 2: a) Number of cryptocurrencies and b) market sandboxes of financial supervisors in the EU for using cap (in billion dollars) of Bitcoin and Etherium, together blockchains in trading and post-trading securities. [23] with their respective percentages of the total market cap As noted by Timsit and Herian (2019), while the overall (as of August 2022) [13, 14]. goal in the EU is clear, there is the crucial question of how to achieve the goal [22]. These proposals in the context of legal Since the technological benefits of blockchain and regulatory relate, as a matter of priority, to the need for technology can be implemented into many services, it has legal and regulatory clarity for blockchain technology and stimulated the interest of many industries. Some proposals less to blockchain protection – a field with recognized for applications of blockchain technology also include [15] challenges. We therefore briefly present some of these the Internet of Things (IoT), Healthcare, Supply Chain and challenges which from our perspective are crucial for even Tourism [16]. However, despite the growing interest, clarifying legal and regulatory framework in the future [22]: there are few business solutions [17]. Examples of promising 1. Challenge no. 1: Legal Value of Blockchain live blockchain solutions are presented in Table 1. Technology as Registers Slovenia is, for example, recognized worldwide for its This challenge assumes the prerequisites for blockchain companies. The Member State promotes its blockchains acquiring legal status would be the economy as "Green, Creative, Smart" and one that leans legal recognition of blockchain-based signatures, towards higher adoption of blockchain technology. Slovenia timestamps, validations, and "documents". ranks second in the world for the number of searches for the 2. Challenge no. 2: Territoriality term Initial Coin Offering (ICO) – surpassed only by This challenge assumes that cross-jurisdictional Singapore. The country is also home to the second-largest harmonization is crucial. In turn, it requires bitcoin scene within Europe based on Google search queries. regulators and legislators to work together across [4] borders to harmonize legal and regulatory regimes and manage potential risks, including monopolies Table 1: Examples of successful blockchain technology and market manipulation. Addressing them would applications outside cryptocurrencies [17, 20, 21]. require significant legal and organizational changes and a cooperation mechanism to ensure Name Application Field Reference harmonization. 3. Challenge no. 3: Enforceability TradeLen Supply Chain [17] This challenge assumes the possibility of Solve Care Healthcare [20] pseudonymity and, in some cases, complete Slock.it IoT [21] anonymity in blockchains has given rise to the impression in some quarters that they can be used One of the reasons for this backlog in other areas is that to create law-free zones for the benefit of criminals. – from a development point of view – blockchain technology 4. Challenge no. 4: Liability is in its early rudimentary stage, still actively seeking new This challenge assumes core developers make cryptographic algorithms to build reliable, flexible, secure, attractive access points for enforcement laws and and stable systems [18]. Another issue is the handling of regulations. Depending on their role in the design, sensitive data that is highly regulated to ensure the privacy development, and maintenance of the blockchain of the customer (for example medical patients). Thus, for platform, they are also accessible enforcement blockchain applications to operate within the EU, they are targets for accountability issues. Although it is required to be compliant with regulatory frameworks such generally – not always – possible to identify the as General Data Protection Regulation (GDPR) [19]. actors in a blockchain network, this takes time and The status quo in this field is presented in the following effort and is therefore not always practical. This can chapter no. 3. consequently be an obstacle to enforcing accountability for actors in blockchain-based networks. 3 STATUS QUO OF LEGAL AND REGULATORY 5. Challenge no. 5: Data Protection FRAMEWORK FOR BLOCKCHAIN Although the GDPR is supposed to consider TECHNOLOGY IN EU: CHALLENGES significant developments in the field of the online world, it was written before blockchain was The EU is convinced that blockchain technology can implemented and was therefore designed with play a crucial role in building Europe’s Single Digital Market more traditional, centralized data processing and drive essential market innovations. If blockchain- paradigms. This has led to, what many believe, 235 several tensions between blockchains and the technologies, its legal and regulatory foundation is still in the GDPR. early phase of development. 6. Challenge no. 6: Competition From the EU perspective, the crucial challenge is the Should competition policy be implemented, new lack of a single legal and regulatory framework for protecting norms or tools will depend on the nature and IP, resulting in disputes between countries. effects of economic activity that will take place in While it is difficult to predict all potential IP-related blockchains. No two cases are likely to be the same, applications of blockchain technology (especially if we don't so in any case the assessment of competition law know all the pitfalls of IPR), we found three specific fields of will depend entirely on the specific circumstances application pertinent to technology transfer and IP of each blockchain and the relevant market. professionals and relevant for our further work [8]: As blockchain technology becomes increasingly widely 1. Blockchain technology can help with IP rights used to support new types of decentralized applications and management and technology transfer and platforms, legislators and regulators will increasingly be commercialization practices. confronted with the complex issues dictated by the above 2. Blockchain as an IP registry. challenges [22]. The challenges illustrated above 3. Establishing authorship, proving ownership and undoubtedly result in challenges related to the protection of provenance of creative works. blockchain technology – especially when it comes to the Although the idea of creating a more efficient following cases where we address CII: blockchain-based system for managing and monetizing IPR 1. Patent applications related to core blockchain is still new, new applications of blockchain-based IPR technologies, and management continue to emerge with remarkable frequency 2. Patent applications related to application (use) of [8]. blockchain technologies. However, several challenges remain unresolved, As a reminder, the CII presents any invention that especially the necessary processing power of blockchains, involves the computer, computer network, or other the compatibility and interoperability of different blockchain programmable apparatus, the invention having one or more platforms, legal issues such as data ownership, privacy, features that are realized wholly or partly using a computer liability, and one of the crucial challenges – jurisdiction [8]. program or computer programs [24]. In the EU there is still However, on the one hand, it should also be borne in no appropriate legal instrument governing such inventions mind that technology transfer created using blockchain which are highly specific and for which demonstrating technology positively impacts company performance. In technical contribution and industrial applicability may pose 2021, Ceptureanu and colleagues, in a study entitled different interpretations – for the inventor and the end user. ‘ Influence of Blockchain Adoption on Technology Transfer, The lack of such a legal and regulatory framework results, Performance and Supply Chain Integration, Flexibility and among other things, in challenges related to blockchain Responsiveness: A Case Study from IT&C Medium-Sized technology protection. Enterprises’ showed that entrepreneurs have a perception There is no single legal and regulatory framework for that the adoption of blockchain technology will help them protecting intellectual property rights and this can lead to increase technology transfer, they will have better potential disputes between different countries. Blockchain traceability of research, development and production phases, technology does not necessarily provide a check on the and reduce the likelihood of technology transfer failures that integrity of the information initially entered – it only can lead to better business performance [26]. provides assurances that this information has not been On the other hand, Technology Transfer Offices (TTOs) compromised or altered. [25] are closely involved in technology and knowledge transfer At the outset, a certain level of internal trust needs to activities and, as such, are key link members between be established between the parties to ensure that there are research organizations and companies. We believe TTOs no underlying issues with the original information that based on their experience in helping researchers with triggered the blockchain. As industries continue to rely on inventions, IP protection and capitalization of inventions blockchain technology, IP law will need to address the could also contribute to the development of legal and relevant legal issues arising from this new "language" of regulatory frameworks. Initially, could provide practical authentication and verification. [25] examples of researchers developing CIIs and thus contribute Although the idea of creating a more efficient to a constructive decision-making process on the future of blockchain-based system for managing and monetizing IPR blockchain technology protection in the EU. However, it is still new, new applications of blockchain-based IPR would be necessary to further explore how they could management continue to emerge with remarkable contribute to the development of legal and regulatory frequency. However, several issues remain unresolved, such frameworks at the EU level with their knowledge and as the necessary processing power of blockchains, the experience. Undoubtedly, we would like to explore this compatibility and interoperability of different blockchain further in the remainder of this work. platforms, and legal issues such as data ownership, privacy, liability, and jurisdiction. [8] REFERENCES 4 [1] World Intellectual Property Organization. 2022. Blockchain CONCLUSION Technologies and IP Ecosystems: A WIPO White Paper. https://www.wipo.int/export/sites/www/cws/en/pdf/blockchain- While blockchain technology has already demonstrated for-ip-ecosystem-whitepaper.pdf its potential to be one of the promising emerging 236 [2] Granstrand, O. and Marcus Holgersson. 2020. Innovation [15] Abou Jaoude, J. and Raafat G. Saade. 2019. Blockchain Applications – Ecosystems: A Conceptual Review and the New Definition. Usage in Different Domains. IEEE Access, 20 (2019), 45360–45381. 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Today’s Cryptocurrency Prices by Market Cap. https://coinmarketcap.com/ 237 Technology Transfer: Start and Stop of Deep Well Pumping Through GSM System Pedro Maldonado† Silvestre Sarabia Emmanuel Costilla Mechanotronics Mechanotronics Mechanotronics University of Tecamachalco University of Tecamachalco University of Tecamachalco Puebla, México Puebla, México Puebla, México psuarez7449@gmail.com silversarabia@hotmail.com emmanuel.costilla.perez@gmail.c om Roberto Avelino Mechanotronics University of Tecamachalco Puebla, México ravelinojr@hotmail.com ABSTRACT economic cost and the lack of resources. However, when the project and the appropriate materials are chosen to cover a need, The aim of this project was to create a long-distance control the project turns out to be viable. The project developed in through a cell phone in order to turn on a water pump or any kind collaboration between students and teachers, was an automated of machine. The present work documents the low-cost start-up system via remote using (Global System for Mobile technology transfer (TT) project of a three-phase deep-well Telecommunications GSM technology, for a three-phase deep pumping system for drinking water supply at the Technological well pumping equipment, which is a considerable distance away, University of Tecamachalco, (TUT) this project was achieved and which supplies drinking water to the Technological through the collaboration of teachers and students of the University of Tecamachalco*. At first place, the importance of Technological University of Tecamachalco of the Mechatronics the TT, the concept, and the considerations to have according to career, in itself of daily interaction, focused on solving a need for different authors and perspectives, the communication system the benefit of the university community, taking advantage of the via GSM is described. Then, its characteristics as, applications, experience of the teachers and the impetus and attitude of the standards, and their comparison with other communication students who collaborated, It also managed to make learning protocols. Finally, the methodology for the development of the significant and thereby strengthen professional academic training, project is described, starting with the identification of the successfully achieving and, where appropriate, reproducibility of problem, the bibliographical research, the technical proposal of the project. It is important to mention the use of the Arduino the solution, the operation tests, improvement actions and finally platform and devices for the design and development of the the start-up of the communication and control system for the project with which the cost was accessible, since for budget deep well three-phase pumping equipment. In conclusion, the reasons it was necessary to optimize economic resources. commissioning of the system was successfully achieved, KEYWORDS remaining in operation without any problems except for a failure of the GSM network and a power outage, which makes it GSM Communication, Arduino Platform, Technology Transfer. necessary for the system to be restarted. 1 INTRODUCTION 2 TECHNOLOGY TRANSFER The development of collaborative projects in the Public Higher TT is strongly related to knowledge transfer. [1] The country's Education Institutions (PHEI, where the collaboration of teachers public PHEI seek, to the extent of the availability of material and and students, to obtain both an academic impact and also solve a human resources, to promote the development of the area of need, is usually not very common, especially because of the influence, and to achieve this effectively, it is necessary to ∗ Tecamachalco Puebla Mexico efficiently carry out technology transfer activities, all PHEI must † Principal Author distinguish the next five items [2] • The generator of knowledge or technology, being the institution 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 that has generated and seeks its transfer. for profit or commercial advantage and that copies bear this notice and the full • The beneficiary of the knowledge, in this case the beneficiary 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). will be some public institution if the objective of the project is a Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia social benefit © 2020 Copyright held by the owner/author(s). 238 • The resources used to carry out the transfer, which can be a operation, such as integrating components to be able to make a license, creation of a company, etc. control card at the same time. Customized and with a unique • The object of transfer, which can be scientific knowledge, design, it can be programmed in Windows, macOS and equipment, know-how, etc. GNU/Linux. • The intermediary agent, which is the body in charge of putting A project that promotes the philosophy 'Learning by doing' the parties in contact. (Interactive Design Institute of IVREA) [6] • The facilitators of the process, being the institutions that do not intervene directly in the transfer process, but that stimulate or service it. [3] 3 METHODOLOGY Technology transfer can take place between universities, companies, government in a formal and informal way with the 3.1 The Problem aim of sharing skills, knowledge, technology, manufacturing processes and more. [4] The area where the Technological University is located is part of the Tecamachalco Valley aquifer, according to data from the National Water Commission (CONAGUA), the aquifer has 2.1 Communication System through GSM severe problems of contamination, overexploitation. For this System (global system for mobile reason, it is considered a water risk, so it is important to consider communication) actions for water care, in the case of the University to have a constant supply. Actions have been considered to supply water They are digital systems capable of supporting voice, short for the service of the students and collaborators of the University, messages (SMS) and data transmission, which allows; large user at some point water pipes were bought, but the cost was high and capacity, wide coverage, efficient use of the spectrum, based on the supply insufficient, so it was considered to bring the water cellular technology, allows the use of a SIM card (Subscriber from a well that is removed from the premises. Identity Mode). At the moment GSM cells are not being This implies that University personnel will have to travel to put deactivated, there are too many security and automation applications based on this technology, [4] in use, in Figure 1 we into operation and after supplying the vital liquid return to close the well, this gives an opportunity for Mechatronics career can see the characteristics of the different technologies. collaborators and students to collaborate on a knowledge transfer proposal. that implies the collaboration between teachers, students and the administration to carry out the implementation of a solution that simplifies the task of turning the well on and off. In figure 2, in the first stage the students supported by a teacher, identify the problem, analyze the solution and make the technical proposal, in the next stage the proposal is compared with the existing technical solutions and a feasibility analysis is carried out. Finally, once the proposal is made, the prototype is made, functionality tests and experimental tests are carried out to detect areas for improvement, once the prototype is tested, it is implemented in the system to be solved. Figure 1: Standards used for Mobile communications (taken from Mobile Communications. GSM, UMTS and LTE Systems, José Manuel Huidobro Moya) Figure 2: Development process diagram 2.2 Arduino Platform It is a low-cost, free access technology that allows the implementation of electronic projects through the use of predesigned boards, with the advantage of using free access 3.2 Starting and stopping system of a pumping software. It has a graphical development environment that uses a system via GSM, based on the Arduino processing/wiring programming language and a bootloader; Platform (IEEE specctrum 2011) regarding the hardware is composed of a microcontroller and input and output ports, through the Arduino IDE (Integrated Development Environment) software. [6] It is Due to the need to bring the water supply to the University from possible to develop automation projects, one of the a considerable distance, a remote start-up system is necessary for disadvantages that it presents is that when using free access tools, the personnel in charge of maintaining the water service to the it is not possible to patent a development based on this type of facilities from their cell phone with wireless technology. [8] platform, it is recommended for its low cost and a not so complex 239 Therefore, the objective of the technology transfer project is to not simple due to the needs that had to be covered. This part of develop a remote control system based on the GSM the programming code for the microcontroller was modified communication platform capable of turning on the well to pump several times to fulfill with the functions required for the correct water to the University, from the cell phone of the technician operation of the pumping system. responsible for the pumping equipment or the staff of the During the development of the project, involving the students Technological University of Tecamachalco, by means of a text turns out to be a strategy that, through constructivism, achieves message, from any location within the range that the technology significant learning in them and that this low-cost technology allows, which must be effective, easy to use and low cost. transfer project also meets the needs that exist in this institution. For this system, the GSM 800l module was used, this allows a Managing to successfully develop and apply to a need in global communication network to be connected to the GSM collaboration between teachers and students to investigate, network, the module has a tray where a SIM card is placed, which document and execute a remote start-up system using free will allow coverage of a mobile telephone company, this depends platforms and GSM technology that although many of the on which company telephone is the SIM card. industrial automation applications are based on this is why there is still time left that, although in the medium term, will give an opportunity to the process of improving and updating the system. 3.3 Materials We learned that the technology development with materials For the development of the project, materials and devices were available of low cost y human resources in formation, is feasible used for the implementation of the power, control, to applied to cover our need and to low cost. communication and protection stages of the starting system and for remote means using GSM communication technology, for the communication stage a DC Voltage Converter was used. -DC, 6 FUTURE WORKS GSM 800l Module, Arduino Uno Card, LED display, for the As a result of this project, the stated objective was achieved, but communication and control stages, in the power stage the use of GSM technology that, although it is still in force due Thermomagnetic Switches, Contactors, Fuses, single-phase and to the enormous number of industrial applications that are three-phase, were selected, according to the specifications of the developed under this technology, it will be necessary in the short pumping equipment that is held for operation or medium term to update the system. of communication according to the availability and characteristics of the project to be necessarily accessible, viable, economic and functional. 4 RESULTS change the Arduino devices for Microcontrollers to be able to Once the materials and equipment to be used were selected, they carry out the patent application, this is because these devices are were all integrated to proceed with operation tests, but not in site generic and their programming is done in free access software, due to the problem of not having the availability of the well, once as an experience in Mexico, a university generated a project the operation tests were carried out, improvements were made to based on Arduino devices and the company when patenting they the system, once these improvements were made, the operation made the observation of the use of free platforms. tests were carried out to verify the operation and that it was in accordance with what was required, these tests turned out to be satisfactory since the device did not present any failure with a REFERENCES repeatability of 100%. [7] [1] WIPO, «World Intellectual Property Organization,» [En línea]. Available: https://www.wipo.int/portal/en/index.html. [Último acceso: 11 After carrying out the operation tests and improvements to the 05 2022]. system, the assembly of the system continued in the cabinet that [2] B. B, «Technology Transfer and Public Policy: A Review of Research contains the entire system, communication, control and power and Theory,» Research Policy, vol. 29, pp. 627-655, 2000. [3] W. S. X. P. X. S. Xiaopei Gao, «Technology Transferring Performance stage to be protected and functional. of Chinese Universities: Insights from Patent Licensing Data,» Advances Once the above was done, on-site tests were carried out, because in Applied Sociology, vol. 4, nº 12, 2014. [4] J. M. H. Moya, « Sistemas GSM, UMTSy LTE,» de Comunicaciones the pumping system was already in operation and the proposal moviles. Sistemas GSM, UMTSy LTE, Ra-Ma, 2012. was made subsequently, it was not possible to carry out these [5] twi-global, «TWI LTD,» TWI Ltd (Head Office), [En línea]. Available: tests, so they had to be carried out and verify the proper https://www.twi-global.com/. [Último acceso: 14 06 2022]. [6] IVREA, «interactionivrea,» [En línea]. Available: operation. of the integrated system, which was satisfactory, being https://interactionivrea.org. [Último acceso: 16 06 2022]. able to turn on the pumping equipment remotely using [7] W. A. L. German L. Cuzco, «Sistema de Alarma, Automatizacion y control de equipos a distancia a traves de linea telefonica y pagina web,» communication via GSM. Universidad Politecnica Salesiana, Ecuador, 2012. [8] D. J. Bolaños, «APUNTES DE ELECTRONICA - INFORMATICA - TECNOLOGIA,» 15 03 2021. [En línea]. Available: https://www.bolanosdj.com.ar/index2.htm. [Último acceso: 05 02 2022]. [9] J. B. Conejos, «Sistema de seguridad perimetral Inteligente,» UPV, 5 CONCLUSIONS Valencia, 2014. Finally, we conclude that the development of the project was hard work since the development of the programming code, was 240 Advanced 3D sensor system for visual control of geometrically complex products Urška Florjančič† Mario Žganec Vili Malnarič Center for Technology Transfer Alpineon d.o.o. TPV Automotive d.o.o. and Innovation Golnik, Slovenia Novo mesto, Slovenia Jožef Stefan Institute mario.zganec@alpineon.si v.malnaric@tpv.si Ljubljana, Slovenia urska.florjancic@ijs.si Hidajet Kurbegović Anatolij Nikonov Jerneja Žganec Gros TPV Automotive d.o.o. Faculty of Industrial Engineering Alpineon d.o.o. Novo mesto, Slovenia Novo mesto Golnik, Slovenia h.kurbegovic@tpv.si Novo mesto, Slovenia jerneja.gros@alpineon.si anatolij.nikonov@fini-unm.si Tomaž Savšek TPV Automotive d.o.o. Novo mesto, Slovenia t.savsek@tpv.si ABSTRACT 3D scanning technologies are increasingly being used as suitable for quality control in industrial environments [2,3]. Most A prototype of an advanced 3D sensor system for visual bypass scanning procedures for 3D geometry control of the products, quality control of geometrically complex products was currently present on the market, work on the principle of 3D developed using an innovative combination of 2D and 3D image derivation by means of trigonometric processes of machine vision methods. We present this optical measuring triangulation [4], using a large number of cameras, e.g., FARO system named EAGLE and its implementation into a simulated [5], Smarttech 3D [6]. As a source of lighting, lasers systems, industrial environment. We emphasise the importance of e.g., ZEISS [7] are used in active procedures, while in most cases vibration analysis for efficient quality control. the projection of structured light patterns on the scene is made with a projector, e.g., Shining 3D [8], GOM [9]. The technology KEYWORDS has already been actively integrated in production processes and visual control, geometry, 3D sensor system, machine vision, quality control as part of smart factories [10]. vibration 2 PROBLEM STATEMENT 1 INTRODUCTION An important part of industrial processes is constant inspection The automotive industry took up the smart factory initiative (i) of products to assure required quality. The leading partner of the to improve the productivity of old factories through modernizing EAGLE project, TPV Automotive d.o.o., uses geometry and and digitizing their operations, (ii) to deal with the quality issues visual surface control of their products on a daily basis. In the that are difficult for people to detect, (iii) to incorporate made- production of stamping parts, being geometrically highly to-order or mass-customization capabilities [1]. Repetitive and complex objects with cavities, embossments and notches, the exhausting work operations are being replaced by automated and dimensional control is demanding and time-consuming process. robotized systems. At the same time, customers' habits have The established procedure for periodic verifications of the changed as customers give more priority to quality and reliability product dimensions requires specially-made and maintained of vehicles. This is the reason why the assurance and automated mechanical inspection instruments. The weakness of this method quality control of components have become of the utmost is a time-consuming and expensive manufacturing of measuring importance. instruments, periodic wear testing of these tools, and rather long testing time for each inspected product. The stamping parts, †Corresponding author made of sheet metal, are sometimes also painted. Despite an Permission to make digital or hard copies of part or all of this work for personal or accurate examination, controllers are facing big problems due to classroom use is granted without fee provided that copies are not made or distributed light reflection, e.g., missing a poor-quality part, which may in 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 turn lead to a quality claim. This is the reason why needs have be honored. For all other uses, contact the owner/author(s). arisen for new approaches and concepts in terms of visual quality Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). management of products. 241 The objective of the EAGLE project was to develop a prototype object in specific positions according to the optical image of an advanced 3D sensor system for automated frequency acquisition system. geometry control of complex products, by using novel machine The system allows the accuracy of distance measurement of 20 vision approaches. μm order. The product verification is carried out in 10 sec order time and involves storage of measurements for further statistical analysis and reporting. This procedure does not affect the 3 RESULTS AND DISCUSSION inspected product and contain wear resistant elements which do not require frequent maintenance or recalibration. The 3.1 Machine vision EAGLE system preparation of the procedure for new type of product to be Optical measurement methods represent a modern approach in inspected takes less than 1 hour and does not require assigned dimensional and geometrical inspection. The project partner equipment. Dimensions not visible on the parallel projections of Alpineon d.o.o. has got rich experience in developing innovative the product shall be checked by additional optical measurement user interfaces and machine vision systems, being a patent holder procedures, which are slightly slower and less precise, but they of geometry control of tubular objects and innovative 3D sensor record the entire 3D model of the product. [11,12]. In the EAGLE project we explored the usefulness of the combination of 2D and 3D measurement methods. The 2D 3.2 Sensor system EAGLE in industrial measurement method is based on a parallel projection of the environment product image on the camera image plane (see Fig. 1). Such a The prototype of the measuring system EAGLE consists of the projection is achieved by using a system of telecentric lenses and following components: 2D and 3D scanning and measuring transmissive lighting with parallel light beams. The 3D systems, robotic arm with grips (mechanical and magnetic tongs, measurement method is based on a binary pattern projection quick rotation clutch), measuring system base, carriers for using an industrial HD projector, two high-resolution cameras components, dump for inspected parts, and computer with and blue LED lighting (see Fig. 1). The 2D method allows communication, process and measurement software. accurate measurement of cut-outs and comparison with 2D In addition to the measuring system, we virtually designed the drawing, and the 3D method enable shape and surface periphery of the future industrial measuring cell, which intends measurement and comparison with 3D model. to be placed into industrial environment, namely: the energetic system (electricity, compressed air), the protection rail and conveyor belt for delivering inspected parts. We also envisaged the possibility of integrating the EAGLE measuring cell with the system for picking inspected parts from the conveyor belt, resulting from joint development between TPV and Alpineon. Figure 2: A virtual model of advanced sensor system EAGLE in industrial environment In Tecnomatix, a tool for modelling and simulation of production processes, a model system according to the following assumptions was designed (Figure 2): - inspected products are transported by conveyor belt, - the system for picking scattered inspected parts recognizes Figure 1: (up) 2D and (down) 3D measuring method and locates products on a conveyor belt, - a robot with magnetic grip picks a product from a conveyor The computer analyses the acquired images, determines the belt and place it onto a special base, specific areas of interest on the product, measures predetermined - a robot with mechanic grip picks a product from the base and tolerance distances, and determines whether the product is within transfer it to the sensor system EAGLE to perform geometry the tolerance range. In order to register the corresponding and surface measurements, projections of the measured object, the robotic arm places the 242 - a product with desired specifications is placed to the working process. It is crucial to understand the vibrations conveyor belt, while the unsuitable product is removed. propagation process over the whole production area also for proper design and manufacturing of improved industrial building 3.3 The influence of environment on the constructions and hardware of industrial processes. measuring method The specific conditions of real industrial environment in which Before the mechanical integration of the components, we the EAGLE system is supposed to be operating, pose a serious integrated components in a virtual environment. We simulated challenge in ensuring the appropriate quality and reliability of different environmental influences, such as light and vibration. optical measurements. This advanced 3D sensor system, We also simulated different paths of the robotic arm and designed to carry out quality control of geometrically complex accelerations. Optimal movements and turns of the robotic arm products, shall be subjected, for example, to vibrations caused by depending on the mass of inspected object were determined with heavy devices (e.g., presses) continuously operating in the the aim of making the measurement as fast as possible and industrial surrounding in which the sensor system is installed. minimizing vibration. The model was prepared using the final A basic starting point for planning and implementation actions in element method (FEM) on the basis of the 3D Solid robot model, industrial environment is established methodology for and simulations were performed using the Abaqus software tool. determining vibrations which includes the determination of the The results of the simulations were tested using measurements following characteristics: on the prototype measuring system (Figure 3). A single-axle - eigen frequencies of the ground, accelerator was installed on the robotic arm in the directions of - the levels of acceleration amplitudes, all three axes, which is connected to the computer with - locations in the industrial area, most suitable for the appropriate software for capture and display measurements via a installation of measuring equipment as regards vibrations, data acquisition and processing device (DAQ). - vibrations at the point of measuring equipment installation. We established a measurement methodology to analyze the impact of vibrations or disturbances on the quality of product optical control by implementing a system for simulation of disturbances propagation in the industrial environment. A model system, developed at laboratory level, was developed to simulate key elements from the industrial environment that cause vibrations, transmit vibrations and respond to vibrations. It consists of piezoelectric accelerometers, signal analyzer and experimental data evaluation system. As a basic model, simulating the ground in the industrial area, we used a measuring plate of 150 cm in length and 75 cm in width, with the thickness of 18 mm. The plate consists of a chipboard base to which the plastic plate is glued. The simulator of the press allows falling of the weights from five different positions, which are 10 cm incremental. The lowest position is Figure 3: Vibrations during motion of robotic arm for single mass (1x) and triple mass (3x) at half speed (50%) thus at 10 cm and the highest at 50 cm. The location of the and full speed (100%) attachment of the impulse exciting simulator to the base plate is shown as a red frame in Figure 4. We measured and analyzed the vibrations of the robot's motion, the robot's eigenfrequencies for different masses of inspected object, and the impact of vibrations caused by the robot's servo drives, on the accuracy of measurements. A comparison with the situation when the robot's brakes are turned on for resting was also made. In this way, we were able to compare the results from the simulation model and the prototype. 3.4 Experimental investigation of industrial vibrations with simulator The vibrations which occur in an industrial environment cannot be completely avoided, therefore it is important to control and manipulate them properly. This requires appropriate vibrations levels determination and further consideration of structural dynamics in the evaluation of quality of products or processes. Figure 4: The location of an impulse excitation simulator and signal acquisition on the measuring plate In the area where some devices cause vibrations, while others require stable surrounding due to precise measurement At impulse excitation of the measuring plate, caused by the techniques, it is necessary to understand how these vibrations weight falling on the plate, the energy that causes wave propagate throughout the room and how they can affect the propagation over the plate surface is released. The measurements 243 of oscillation which occurs after the impulse excitation with two eigenfrequencies do not affect the speed and the accuracy of the different loading masses, i.e., 632 g and 1085 g, having the same measurement method. height, were performed at four measuring points in accordance We also established an experimental methodology for with the mapping shown in Figure 4. The black dots in Figure 4 multiparametrical analysis of structural dynamics which enables represent signal acquisition locations with coordinates E12, E18, investigation and evaluation of the effect of vibrations on the H12 and H18. technological processes in the industrial environment. For that By analyzing the measured signals of response, it was observed purpose, a model system for simulating disturbance sources and that the intensity of the impulse, caused by heavier weight, is monitoring disturbances, which propagate over the base plate, as higher in comparison to the intensity of the impulse, caused by appear in different locations in real time, was developed. This lighter weight, as expected (see Figure 5). Figure 5 shows the model system, developed at the laboratory level, enables measured average acceleration values which correspond to the simulation of the key elements from the industrial environment maximum impulse amplitudes at each measuring point for lighter that cause vibrations, transmit vibrations and respond to and heavier weight. Higher amplitudes of impulse excitation vibrations. increase the final accelerations which consequently affect the operation of simulated device, representing optical measuring ACKNOWLEDGMENTS system in real industrial environment. The research work within the EAGLE project was financially supported by European Regional Development Fund in the Operational Programme for the Implementation of the EU Cohesion Policy in the period 2014 – 2020. The authors thank student Bojan Lupše for his involvement in vibration experimental analysis with simulator. REFERENCES [1] Chris Middleton. 2020. Smart factories - driving the automotive industry into the fast lane. Diginomica (Feb 14, 2020). https://diginomica.com/smart-factories-driving-automotive-industry-fast- lane (cited: Aug 10, 2022) [2] K. R. Srinivas. 2017. Blue Light Optical Scanning for High Resolution 3D Measurement. Quality magazine (Sept 1, 2017). https://www.qualitymag.com/articles/94202-blue-light-optical-scanning- for-high-resolution-3d-measurement (cited: Aug 10, 2022) Figure 5: The influence of the location of signal acquisition [3] Andrei Vakulenko. 2017. The Future of 3D Scanning and Its Impact on Industrial Quality Control. Manufacturing Business Technology (July (E12, E18, H12, H18) and the weight mass on the dynamic 18, 2017). response of the measuring plate https://www.manufacturing.net/industry40/article/13227099/the-future- of-3d-scanning-and-its-impact-on-industrial-quality-control (cited: Aug The experimental analysis shows that the eigenmodes of 10, 2022) [4] Francesco Malapelle, Diego Dall’Alba, Denis Dalla Fontana, Ivano measuring plate oscillation affect the experimental results, and Dall’Alba, Paolo Fiorini, Riccardo Muradore, 2017. Cost Effective therefore the measured values of the oscillation accelerations at Quality Assessment in Industrial Parts Manufacturing via Optical Acquisition. Procedia Manufacturing, 11, 1207-1214. the impulse excitation with the same weight differ in measuring https://doi.org/10.1016/j.promfg.2017.07.246 points. The eigenmodes of measuring plate oscillation therefore [5] http://factory-metrology.faro.com/us/ (cited: Aug 10, 2022) [6] have significant influence on the development of the resonance http://smarttech3dscanner.com/ (cited: Aug 10, 2022) [7] http://optotechnik.zeiss.com/ (cited: Aug 10, 2022) oscillation response. [8] https://www.shining3d.com/ (cited: Aug 10, 2022) [9] https://www.gom.com/ (cited: Aug 10, 2022) [10] Bruce Morey. 2016. Why Optical Metrology Is on the Move. Advanced Manufacturing. SME (Mar 16, 2017). 4 CONCLUSSIONS https://www.sme.org/technologies/articles/2017/march/optical- metrology-move/ (cited: Aug 10, 2022) The EAGLE measurement robot cell represents a complete [11] Mario Žganec, Jerneja Žganec Gros, Alpineon. 2016. Method and novelty in the global market. It enables visual bypass quality equipment for monitoring suitability of a tubular object geometry. Patent EP2950042 (B1) - 2016-12-14. Munich: European Patent Office control of the geometry of complex objects using the innovative [12] Mario Žganec, Jerneja Žganec Gros, Alpineon. 2011. Active 3D design of the machine vision system. As a use case we chose triangulation-based imaging method and device. Patent EP 1997322 metal stamping parts, i.e., geometrically complex products in the (B1), 2011-12-28. Munich; Hague; Vienna: European Patent Office. US7483151 (B2) automotive industry which are technologically attractive due to [13] Mario Žganec, Aleš Mihelič, Stanislav Gruden, Boštjan Vesnicer, Žiga their innovative lightweight design. Some breakthrough Golob, Jaka Kravanja, Černe Tomaž, Žganec Gros Jerneja. 2021. Priprava za samodejno preverjanje dimenzij kovinskih odpreškov, solutions, contributing to the significant state-of-the-art progress Zahteva za podelitev patenta, št. 202100067, Urad RS za intelektualno in technology, were developed [13,14]. lastnino, Ljubljana, April 2021 [14] The advantages of the advanced 3D sensor system EAGLE for Anton Juratovac, Mateja Koblar, Jurij Kranjc, Hidajet Kurbegović, Vili Malnarič, Rajko Marinčič, Anton Petrič, Boštjan Piletič, Tomaž Savšek, geometric inspection of complex products are: (i) successive Urška Florjančič, Anatolij Nikonov, Stanislav Gruden, Jaka Kravanja, implementation of several optical measurement methods on the Aleš Mihelič, Boštjan Vesnicer, Jerneja Žganec Gros, Mario Žganec, Žiga Golob et al. Robotska merilna celica za nadzor kakovosti EAGLE. same inspected object without intermediate intervention by the Produktna inovacija. Novo mesto: TPV AUTOMOTIVE, 2021. Srebrno operator, (ii) fully autonomous operation, (iii) accuracy and time priznanje za inovacije Gospodarske zbornice Dolenjske in Bele Krajine, Otočec, 2021. stability due to fixed optical measuring components, (iv) a https://www.gzdbk.si/media/pdf/projekti/inovacije/2021/gzdbk_katalog_i robotic arm movement and measurement system novacije_2021_webpdf.pdf (cited: Aug 10, 2022) 244 DODATEK / APPENDIX 245 INTRODUCTION AND AIM OF THE CONFERENCE Conference topic: The role of TTOs in maximizing impact of science, technology and innovation on society. Objectives of the Conference The Conference brings the awareness of importance of professional technology transfer activities which must be appropriately placed in a national innovation system. The Conference program includes exchange of knowledge, good practice, and opportunities for collaboration between representatives of academia, industry and government about cooperation and transfer of knowledge and innovations from publicly funded 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. Since 2008, we hosted more than 2600 participants from Slovenia, Europe and the world, including researchers, students, inventors, technology commercialization and intellectual property experts, investors, start-up funders, industrial development experts etc. Since 2009 we have successfully organized fourteen annual international competitions in which till this year have participated a total of ninety-three (93) teams from PROs throughout Europe with their technology and business proposition with the biggest commercial potential. We are particularly proud some of them made their first steps at the Conference and have later advanced to spin-out companies and licensing agreements. Biannually we organise pre- scheduled Research2Business (R2B) meetings. The meetings are additional matchmaking opportunity for representatives of industry and researchers to meet and identify opportunities for collaboration, cooperation and business synergies. Additionally, in a special session, the researchers are presenting their work which is being financed by Slovenian Research Agency (ARRS). This is another opportunity for enterprises to get insight to recent discoveries in the PROs and development opportunities. Conference prize for the best innovations in 2022 The main objective of the special prize for innovation is to encourage commercialization of inventive/innovative technologies developed at PROs and to promote cooperation with industry. One of the main objectives is also promoting the entrepreneurship possibilities and good practices in the PROs. Researchers are presenting their technologies and business models 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 fourteen years led to the establishment of a spin-out company, conclusion of a licensing agreement or further development of a business opportunity in at least one case per competition each year. In many cases, young researchers that participated in the pitch competition in the past years, have been involved for the first time in an organized and structured development of a business model around their technology 246 and preparation and delivery of the targeted (pitch) presentation about their planned venture to investors and technology commercialization experts. 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. Opportunities arising from publicly funded research projects / presentations of successful scientific projects Researchers are presenting their work that is being financed by Slovenian Research Agency. Scientific papers on technology transfer (TT) and intellectual property rights (IPR) Experts on TT, IPR, researchers that cooperate with industry and others have been invited to submit their scientific papers. The accepted papers have been presented by the authors. This year’s topics were: Key factors for successful technology transfer from different points of view (researchers, knowledge transfer experts, enterprises); The role of TTOs in maximizing impact of science, technology and innovation on society; IP value vs price; Incentives for contract and collaborative research / cooperation with industry; IP negotiation with industry; State Aid in contract and collaborative research; Current status of public investments into research and technology infrastructures; European or national frameworks to transform breakthrough technologies developed for fundamental research purposes into breakthrough innovations with strong industrial applications and societal added value; Examples of IP protection in Artificial Intelligence; Other, chosen by the contributor Connecting the education system with academia A parallel section “Connecting the education system with academia: Presentations of selected research topics from the Jožef Stefan Institute and proposals for cooperation” took place. The section was aimed at primary and high school teachers where selected research topics from the Jožef Stefan Institute (JSI) and proposals for cooperation were presented. 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, development banks), SMEs, international enterprises, private innovators, and others. The key stakeholders co-create the conference and share with other co-organisers, partners and audience their knowledge, expertise and thoughts. They also spread the word about the conference among their contacts. Through their activities the awareness about knowledge transfer and IPR is rising in their organisations, in Slovenian and European innovation eco-system. 247 Target audience and benefits Target audience of the conference are researchers, students and post-graduate students with entrepreneurial ambitions, technology transfer managers, representatives of industry, established and future entrepreneurs, innovators and also representatives from governmental institutions and policy-making organizations. Organization of 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 15th 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 (IS2022), organized by the Jožef Stefan Institute. The Conference has been organized with the support of partners from the Enterprise Europe Network project (EEN). The project's mission is to help businesses innovate and grow on an international scale. It is the world’s largest support network for small and medium-sized enterprises (SMEs) with international ambitions. The Network is active worldwide. It brings together experts from member organisations that are renowned for their excellence in business support. The ITTC is complementary to the mission of the EEN project which is to support SMEs and researchers through a) finding appropriate business partner, b) international technology transfer and c) finding partners/coordinators to apply to EU calls, while providing support on IPR, Access to finances, regulation and legal support. 248 ACKNOWLEDGEMENTS The editors and organizing committee of the Conference would like to express cordial thanks to all who helped make the 15th International Technology Transfer Conference a success. We would like to acknowledge the valuable contributions to the members of the SCIENTIFIC PROGRAMME COMMITTEE: • Niko Schlamberger, President of Slovenian Society INFORMATIKA • Doc. Dr. Tamara Besednjak Valič, Faculty of Information Studies in Novo Mesto • Prof. Alexandru Marin, University POLITEHNICA of Bucharest 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: • Alexandre Massart, co-founder and director, Blend Ventures, • Jurij Giacomelli, Investment Manager, META Ingenium, • Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission, • Nina Urbanič, Adviser for equity investment monitoring and reporting, Slovene Enterprise Fund, • Vladimir Jančič, CEO, Publikum Korpfin, 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 WIPO EVALUATION COMMISSION: • Alojz Barlič, Slovenian Intellectual Property Office (SIPO) • Nina Urbanič, Slovene Enterprise Fund • Christoph Kempf, IPEK – Institut für Produktentwicklung, Karlsruher Institut für Technologie (KIT), for their evaluation and selection of the awardees of the WIPO IP ENTERPRISE TROPHY and WIPO MEDAL FOR INVENTORS. Special thanks go also to Slovenian intellectual property office for their help with the organisation, communication with WIPO and presence at the Award ceremony. We thank also to ARRS for their presence at the Award ceremony and WIPO for their video for the Award ceremony. 249 Day 1 250 OVERVIEW OF THE PROGRAMME 12 October 2022 (hybrid teleconference, virtual and live) MAIN SESSION 08.30 – 09.00 Registration Welcome address (in Slovene language) Dr. Tomaž Boh, Director-General Science Directorate, Ministry of Education, Science and Sport 09.00 – 09.15 Prof. Dr. Boštjan Zalar, director, Jožef Stefan Institute Dr. Špela Stres, Jožef Stefan Institute, EIC Board member Keynote speech: CEA’s experience in effective collaboration with industry 09.15 – 10.00 Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission 10.00 – 12.00 Best innovation with commercial potential: pitch competition 12.00 – 13.00 Lunch break Award announcement: Best innovation with commercial potential 13.00 – 13.20 Award announcement: WIPO IP Enterprise Trophy Opportunities arising from publicly funded research projects / presentations of successful scientific projects (partly in Slovene, partly in 13.20 – 14.30 English) Award announcement: WIPO Medal for Inventors Paper presentations: scientific papers on technology transfer and 14:30 – 16:50 intellectual property 16.50-17:00 Closing PARALLEL SESSION Connecting high-school education system with academia: Presentations 13:20 – 14:30 of selected research topics from Jožef Stefan Institute and proposals for cooperation 251 WELCOME ADDRESSES From 9:00 to 09:15 Honourable Speakers: Dr. Tomaž Boh, Director-General Science Directorate, Ministry of Education, Science and Sport / generalni direktor Direktorata za znanost, Ministrstvo za izobraževanje, znanost in šport Povzetek uvodnega pozdrava / Abstract of the Welcome address Hvala lepa za povabilo. Spoštovani direktor, spoštovana kolegica Špela, spoštovani raziskovalci in raziskovalke, spoštovani domači gostje in gostje iz tujine. V veliko veselje in čast mi je, da sem lahko danes tule v imenu Ministrstva za izobraževanje, znanost in šport in vas pozdravim na 15. Mednarodni konferenci o prenosu tehnologij. Pomembno je oboje, petnajst in prenos tehnologij. Število petnajst pomeni, da je vaša institucija ena tistih, ki na področju prenosa tehnologij, inovacij in znanja že dolga leta orje ledino, postavlja nove standarde in nenazadnje postavlja protokole kako in na kakšen način povezovati raziskave z gospodarstvom. Iz vašega znanja in iz sadov preteklih konferenc se lahko vsi iz širše raziskovalne sfere v Sloveniji marsikaj naučijo. S tega vidika je izjemno pomembno, da sodelujete, da ste ena izmed vodilnih institucij tudi v inštrumentih, ki jih ministrstvo v tem kontekstu financira in ki jih bo podpiralo tudi v prihodnje. V naslednji kohezijski perspektivi si zelo želimo, da povečamo obseg, da damo novo kvaliteto temu, kar je bilo v dosedanjem obdobju že narejeno in naredimo še pomemben korak naprej. Prenos tehnologij kot drugi del besedne skovanke je ključnega pomena zaradi tega, ker v zadnjem času vedno bolj pridobiva na pomenu, čeprav je moje prepričanje, da za raziskovalce in tiste, ki se s prenosom tehnologij ukvarjate na institucijah, pravzaprav to ni nekaj novega, s čimer bi se začeli ukvarjati in s čemer bi sledili temu kar je politično zaželjen besedni termin na področju raziskav. Ravno zaporedna številka petnajst v imenu konference kaže, da je zavedanje o pomenu prenosa tehnologij bistveno daljše kot pa je to postala moderna politična beseda. Pa vendar, tudi politični odločevalci se vedno bolj zavedajo, da je potrebno podpirati ne samo bazične raziskave, ki so brez dvoma osnova in temelj vsega, in ne samo gospodarstvo v smislu direktnih spodbud nepovratnih sredstev, ampak da je polje prenosa tehnologij tam nekje v sredini. To mejno področje oz. področje na sredini, ki se ga žal pogosto obravnava kot da ni pristojnost nikogar (a upamo, da se stvari izboljšujejo), je pravzaprav pristojnost obeh, tistih ki podpirajo gospodarstvo in tistih, ki imamo pristojnosti financiranja znanosti. Ravno tovrstne konference kot je današnja pokažejo, da je svet tam vmes še kako živ, da še kako dobro veste kako in kaj početi v tem kontekstu. Tudi današnji program, ki je sestavljen iz predstavitev dobrih primerov, tekmovanja, ocenjevanja najboljših dosežkov kaže na to kako zelo je to področje živo. Z vidika Ministrstva za izobraževanje, znanost in šport in predvsem z vidika našega Direktorata za znanost lahko rečem, da bo tudi v prihodnje prenos tehnologij oz. prenos znanja ena izmed 252 pomembnih aktivnosti in sestavni del znanstveno-raziskovalne dejavnosti. V kontekstu stabilnega financiranja raziskovalnih institucij verjamemo, da bomo v letih, ki sledijo, vzpostavili tudi ustrezne načine sodelovanja kako to zapisati v strateške cilje institucij, kaj od tega lahko tudi centralno država, ministrstva v procesu pogajanj oz. bolj v dogovoru naredimo kot pomemben korak k stabilnosti financiranja, k stabilnosti upravljanja tega področja in k stabilnosti podpore, ki jo v tem kontekstu potrebujete. Želim vam uspešno konferenco in uspešno delo še naprej. Before I finish I would like to welcome all the guests from abroad while it is important to also have a mirror to compare our national system with systems abroad and learn from your experiences. Because of that I would in the name of the Ministry of Education, Science and Sport warmly welcome you in Slovenia and thank you for all the work, for all the cooperation with Slovenian institutions. Prof. Dr. Boštjan Zalar, Director, Jožef Stefan Institute Povzetek uvodnega pozdrava / Abstract of the Welcome address Dear guests, dear researchers, dear technology transfer experts, we are very glad to have you here again at this annual event. Two years ago, we were fighting with the covid epidemy, last year there’s the situation in Europe that has changed a lot the geostrategic points of view of development of our scientists. So, it seems to be that we will be encountering different troubles on and on. Maybe you read a few weeks ago there was a report that NASA was trying to crash a satellite into an asteroid so one would think that probably it’s the next crisis that is coming that an asteroid would hit our earth. Anyway, from the technology transfer view crashing a bunch of pounds of high technology into a rock this is what you call technology transfer I would say. Our institute has been hosting this event for several years and we are really glad to have you here again. I wish you a lot of fruitful discussions and as a part of the technology transfer debates I anticipate and I really hope that there will also be in all these debates suggestions how to improve the transfer of common sense that our humanity really needs in recent years. Thank you very much. I am glad to have you here again and I wish you all the best in your work. Dr. Špela Stres, Jožef Stefan Institute, EIC Board member Povzetek uvodnega pozdrava / Abstract of the Welcome address I would like to welcome everyone from my heart. Through the years we had a lot of collaboration in particular with many famous institutions from the western part of Europe or from the USA. We had guests from MIT, Leuven RD, Cambridge. I am very pleased to see that in particular our scientific section is expanding a lot towards the widening countries. The 253 internationalization of the efforts in the field of professionalization of knowledge transfer is really an important step for all of us, because knowledge transfer in itself is not just a profession, it’s a scientific field in itself. As soon as we are ready to acknowledge that fully also in the widening countries it will be much easier to establish a professional system of knowledge transfer and valorization. We’ve had fifteen years of this conference and not all events that happened during that time were totally happy. For example, I remember when we’ve first asked whether we can organize such an event in the field of technology transfer and whether we can award a prize for best innovation from public research organizations the answer was - a simple no. But here we are fifteen years later and we’ve organized numerous business to research meetings. We’ve published many scientific articles in this field. We’ve had twenty-eight teams awarded. And those teams did not just receive an award here, they went on and received several other awards elsewhere and they attracted venture capital and they took the name of all the major public research organizations that they came from in the first place to the Slovenian economy and also wider, some of them even won very prominent European funding. But the story does not end here. As we’ve heard from the Director General I do also acknowledge the fact that knowledge transfer and valorization is in a transitional period right now. That’s also influenced by the fact that we have the new legislation. The new legislation does imbed knowledge transfer a bit more into the system of the public research organizations, but it does not assure that it’s going to really be imbedded. So, I think that in this transitional period it’s really important that additional funds are available for knowledge transfer that should be used in particular to connect different efforts and to professionalize those efforts. Also, it would make so much easier if the Slovenian system of financing the research would follow the steps that were taken by the European Commission. The European Innovation Council is an example of that how the research throughout the technology readiness levels can be supported in an integrative connected way throughout the TRLs. Improving our own system in such a way would give our researchers much needed security to become more imbedded in the innovation part of their efforts. And last but not least it’s important that the Center for Technology Transfer and Innovation keeps up the good work at the institute in whichever form it will continue because the researchers need the professional assistance in this field. In fact, in Slovenia we don’t have the gap between academia and industry, we just somehow need to learn how to shake hands between the two fields and that’s also a question of the professionalization that I spoke before about. So welcome everyone here and I hope that after fifteen more years we’ll be looking at the totally different situation. Thank you. 254 KEYNOTE SPEECH: CEA’s experience in effective collaboration with industry From 09:15 to 10:00 Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission Abstract of the Keynote speech The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation collaborative partnerships in defence and security, low carbon energies (nuclear and renewable energies), technological research for industry and fundamental research in the physical sciences and life sciences. CEA comprises of 9 research centres with 21.148 employees CEA filed 710 priority patents filed in 2019, created 228 start-ups since 1972 and operates a 5,6-billion-euro budget. The CEA is one of the leading patent applicants in France and Europe having 6,980 active patent families. CEA is 1st patent-granting research organization in France and 1st French patent applicant in Europe. As a major player in innovation, the CEA promotes the technologies it develops and transfers them to industry. CEA supports business competitiveness, job creation and national and European technological sovereignty. By encouraging spin-offs, it has supported and promoted creation of start-ups for the past twenty years. Management of intellectual property is a key element of CEA’s strategy, used for the benefit of innovation transfer to companies. CEA has chosen to retain ownership of the results (Foreground) obtained by its sole researchers during collaborative partnerships financed by industry. The Foreground created in a given RDI collaborative partnership with one company is therefore added to CEA’s IP portfolio and can be used by CEA as Background for other collaborative partnerships with other companies, for very diverse applications. The model of Industrial RDI Collaborative Partnerships enables a wide technological dissemination, not only benefiting strategic industrial sectors but also smaller enterprises (SMEs, start-ups) that gain easy access to technological IP Portfolio without having to finance their development. The company finances only the new RDI collaborative partnerships where new Foreground is created from CEA’s Background. This model contributes to CEA’s autonomy in its research and valorisation policy, while preserving its industrial partners’ competitive advantage through the implementation of adapted and secured exploitation rights. “Post RD” licence after a collaborative RDI Partnership, covering results of the collaboration carried out with a partner, as well as the pre-existing knowledge required to use these results, is the most frequent mean of transferring CEA’s technologies to industry. It represents more than 70% of CEA’s commercial licences whilst licences to start-up companies represent 20% and 10% regarding “straight” licences” with existing companies, where no prior RDI collaboration has taken place . 255 CEA licensing terms (field of use, exclusivity, duration, etc.) are adapted on a case by case basis to meet the needs and exploitation prospects of its partners. CEA grants a licence to the partner on the Foreground and Background needed to exploit the Foreground after a given collaborative Partnership. Licences may also be granted where no prior collaboration has taken place (“straight” licences). Access to Foreground (or a part of it) can be exclusive in a particular field, with mandatory exploitation thresholds. In the case of insufficient exploitation, the licensee loses exclusivity in its domain. In the event of absence of exploitation, the license is terminated and CEA can then seek a new partner in the Public Interest. In general, access to Background needed to exploit particular Foreground, is non-exclusive. Commercial and industrial exploitation licences always give rise to payment. The budgets of CEA's collaboration activities only take into account the costs of the R&D work. Licence remuneration must therefore not only cover CEA's IP costs but also contribute to a fair return, for CEA and its inventors, on the value created by the exploitation. This also enables CEA to comply with European legislation on State aid. CEA royalties’ policy is very compliant to the article 28 d) of the EC Framework: “The research organisations or research infrastructures receive compensation equivalent to the market price for the IPR which result from their activities and are assigned to the participating undertakings, or to which participating undertakings are allocated access rights. The absolute amount of the value of any contribution, both financial and non-financial, of the participating undertakings to the costs of the research organisations or research infrastructures’ activities that resulted in the IPR concerned, may be deducted from that compensation”. CEA shares royalties with researchers whilst participating in licensed knowledge. CEA envisages different payment modalities (lump sum, proportional royalties, minimum, caps, conditional upon an event, etc.) and combine them to meet its partners’ business prospects. Large enterprises with sufficient financial resources prefer lump sum payment term whilst start-ups and SMEs prefer proportional royalties. CEA undertakes to apply preferential remuneration conditions for post R&D licenses compared to “straight” licenses to ensure a differentiation with a licensee who has not participated in the R&D program. In order to comply with point 29 (compensation at market price), CEA uses generally point 29 c). In those cases, the arm’s length negotiation is often based either on a method of comparable royalty fees in the field of the license (there are international databases for that) or by carrying out a detailed study of the provisional exploitation of the company: turn over, margin…. Generally, the international good practice is that the amount of the compensation for CEA (owner) is 1/3 of the margin of the licensee when exploiting IP. The valorisation of CEA’s technologies has also occurred through the creation of new companies, with 228 spin-offs created (89 over the last 10 years) including 2 with more than 1.000 employees (SOITEC and LYNRED) that enabled 5.500 direct jobs created. CEA start-ups accomplished record fundraising in 2018 accounting to 144 million euros whilst record fundraising of 120 million euros in 2020 was achieved by only one (Aledia). 256 7 start-ups arising from the CEA are listed on the stock exchange: Soitec, Kalray, Theranexus, Fermentalg, Tronics, Pixiumand Arcure. 70% of the 200 start-ups created over the past 20 years are still active. Since 2000, 50% of CEA start-ups have raised funds, for a total of nearly 1,2 billion euros (excluding SOITEC). CEA invests significant sums, directly via its internal development/incubation programme (before creation of the start-up) or, at the creation of the start-up by taking equity in the start- up via its CEA Investissement private subsidiary. CEA is therefore a significant stakeholder in the creation and development of these start-ups and shares in the risks. Success story of CEA start-ups is based on challenging requirements for creating a start-up: • Innovation must be disruptive and protected by strong exclusive IP (patents, secret know how, copyright for software…); • Marketing study must have been done showing good market prospects (sometimes start-up creates a new market); • Research organization must have a sound process to support the creation of the start- up; • Researchers who participated in the development of the technology transferred to the start-up when it was created and who wish to carry out the start-up project, must have a strong entrepreneurial spirit. For an R&D partnership with a start-up, CEA applies the same principles of strong IP management and protection as for its other partners with regard to attributing ownership of research results. CEA keeps the ownership of this IP and grants a license on it to the start-up, generally exclusive in a field (for a part of the technology) since most often start-ups don’t have financial resources to pay IP fees for patent costs. On the other hand, start-ups may be developing very fast and be counterfeited by their competitors. In this case, CEA protects (and enforces when needed), its patents effectively. In the event of an infringement lawsuit, the exclusive licensee (the start-up) has the same rights as an owner to assert its rights. The advantage for the exclusively licensed start-up is that in this case, the CEA could also be part of the lawsuit where it intervenes to defend its patents with convergent interests with the start-up. The CEA was thus able to defend several of its start-ups in lawsuits for infringement by big international companies of its patents used exclusively by its start-ups. Of course, a single start-up would have had a much harder time defending itself in these lawsuits in the case where CEA would have waived its ownership to the start up. CEA has an internal marketing department carrying out a detailed marketing study for each start-up creation. CEA runs regular (4 times per year) internal seminars to increase awareness of researchers in start-up creation and empowering their entrepreneurial spirit. CEA internal PoC fund may be engaged if necessary, depending on the TRL of the technology. CEA has an 100% owned affiliate CEA Investissement that takes equity in the start-up at creation. Most of CEA’s start-ups have a RDI collaborative partnership with CEA and enjoy RDI support post-creation. Therefore, improvements of the first licensed technologies or additional technologies can be licensed later to the start-up. 257 Collaborative partnerships may be very different regarding IP background and foreground, having very versatile content or government rules. Thus, CEA does not have developed model contract/ articles for collaborative partnerships or a model process for creating start-ups. 258 PITCH COMPETITION: BEST INNOVATION WITH COMMERCIAL POTENTIAL From 10:00 to 12:00 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission: Alexandre Massart, co-founder and director, Blend Ventures Jurij Giacomelli, Investment Manager, META Ingenium Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission Nina Urbanič, Adviser for equity investment monitoring and reporting, Slovene Enterprise Fund Vladimir Jančič, CEO, Publikum Korpfin Presentation of six (6) selected business model proposals from public research organizations to the members of the evaluation commission. 259 Course of the competition Robert Blatnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) The 14th annual competition for the best innovation in 2022 at public research organizations (PROs) aims at stimulating the researchers from PROs to develop business models for commercialization of their inventions. Each year the competition is initiated with a public call for the teams with inventive technologies. Eligible authors are individuals, employed at PROs, which are developing innovative technologies into a viable business model. The proposed business models are either licensing the technology to industrial partners or commercialization in their spin-out company. The teams have prepared description of their technology and the key discoveries that underpin the commercial activity (licensing or spinning-out). An important part of description is the proposed business model and customer value proposition. The pitch presentations are following the guidelines, which were introduced by the Organizer of the Conference at the dedicated preparatory webinar and individual consultancy which was organized for the teams. At the webinar and consultancy, the researchers learned the guidelines to prepare their pitch presentation and improvements of their business model. In a series of individual consultation and rehearsal of the pitch session 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: Alexandre Massart, co-founder and director, Blend Ventures, Jurij Giacomelli, Investment Manager, META Ingenium, Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission, Nina Urbanič, Adviser for equity investment monitoring and reporting, Slovene Enterprise Fund, and Vladimir Jančič, CEO, Publikum Korpfin. 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 Application with weight of 10 points, Value Chain with weight of 3 points, Market size and development costs with weight of 2 points, Competition with 1 point, the Team with 3 points, IPR and Regulatory with one point. All criteria together bring at the most 20 points for written application. After the pitch 260 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 14th anniversary, motivated six innovative and entrepreneurial research teams to prepare their pitch and apply for competition. Members of the teams have participated in the preparatory workshop and rehearsal to develop their pitch and receive comments for improvements of their proposed business model. The workshop was organized by Center for Technology Transfer and Innovation as part of the Enterprise Europe Network (EEN) project, financed by European Commission. Members of the teams are entirely or partly employed at the following PROs: Fondazione Bruno Kessler, Gdynia Maritime University, National Institute of Chemistry, National Institute of Biology, University of Ljubljana and its Faculty of Chemistry and Chemical Technology and Jožef Stefan Institute. Max. Criteria Short description of the criteria points Which problem is the technology solving? Has this been verified with end users? What is the Technology Readiness Level (TRL)? How many different applications can the technology be used for? Is there a well-defined end-user for this technology? Is there any barrier to the end-user adopting this solution? Application 10 Is there a clear existing end user need for this solution? How well does this solution match the users’ needs? When will this solution be ready for market? Will this solution have a social impact or bring other benefits to people? Where does the technology fit in? Value chain 3 How well does the technology fit the existing value chain? How is the market size in relation to the development costs? How large is the potential customer community for this product? 1000, 100K, 1M, 100M? How strong is the competition in this market? How receptive will the market be to your idea? What total market share do you expect to get in 5 years? How aligned are the market drivers to the proposed solution? What Is the perceived value by the end user? Market size What is the perceived Strength level overall? and What is the perceived Weakness level overall? 2 development What is the perceived Opportunity level overall? costs What is the perceived Threat level in your overall? Only limited development is required before an investor will commit. Funds are available to complete the development investor or other sources (e.g. PoC). The time to market Is shorter or comparable to the time scale for any competition. For VC’s: The costs associated with taking the product to market is at least 25 times smaller than the value of the market. 261 What do the end users use today? Any other technology underway? Which is the expected competition level when you will hit the market How good is the present solution (not yours) in solving the Competition 1 problem? How good will any expected future solutions (not yours) be in solving the problem? How good will your solution be in solving the problem? How strong is your market differentiator? Are the inventors, members of the team, dedicated to the idea? The researchers have unique skills, have experience with tech transfer, and are enthusiastic about following the project through The team 3 The team has the technical, business, marketing, financing skills needed to understand and develop the idea into a marketable product? Can the intellectual property of the technology be protected? How strong is the patent likely to be? How dense is the IPR landscape in this technology area in terms of IPR & pending and granted patents? 1 Regulatory How strong is the IPR competition? How complex is the regulatory system in this area Is the technology ready for investment? Table 1: Criteria for evaluating the applications (source: Jon Wulff Petersen, TTO A/S, Denmark) 262 Abstracts of the competing teams and their technologies 263 Innovative equipment of intervention/service watercraft: Mobile Electromagnetic Mooring System and Batychron Authors/inventors: Paweł Kołakowski, Grzegorz Rutkowski PRO: Gdynia Maritime University Abstract: The innovative equipment is designed for use on a floating intervention unit coming to the aid of a vessel in danger (collision, grounding) or a ship requiring a specific service (underwater inspection, cleaning, or cargo and crew transfer). This comprehensive solution includes two inventions: a Mobile Electromagnetic Mooring System and a Batychron. The Mobile Electromagnetic Mooring System is used for mooring the service unit at the side of the serviced ship using a system of electromagnetic grippers with a unique set of mooring lifts ensuring constant rope tension. The invention enables the service unit to move quickly along the side of the serviced vessel, shortening the time needed for mooring and unberthing, limiting the crew's involvement in mooring operations, improving safety, and accelerating intervention to provide proper service. The Batychron is a flexible underwater bell used for underwater transport and diving with high safety standards. Thanks to the lightness and portable structure resulting from the use of new generation materials and integrated systems, it can be used in open and internal waters for underwater transport and various types of diving. These ground-breaking solutions have a global reach and no competition in this field yet. Despite improvements in maritime safety, maritime accidents occur daily around the world. Moreover, both devices can be used in sectors such as marine services, repair interventions, cargo and/or people transfer offshore, diving services - recreational, training, repair or excavation work, and underwater transport. The wide range of use of these devices creates promising opportunities for their manufacturers. Figure 1: The Batychron. G.Rutkowski. 2022. 264 Figure 2: Batychron main components A) transparent dome, B) openwork mesh, and C) flexible diving bell – the Batychron. P.Kolakowski. 2022. Figure 3: Research conducted in a real environment on the invention of Batychron. G. Rutkowski. 2022. Figure 4: Mobile Elecromagnetic Mooring System (MEMS) – laboratory model in scale 1;30. P.Kolakowski. 2022. 265 Antiviral surgical masks, gowns and drapes Authors/inventors: Mark Zver, Rok Zaplotnik, Miran Mozetič, Alenka Vesel, David Dobnik, Arijana Filipić, Polona Kogovšek, Maja Ravnikar and Gregor Primc. PROs: Jožef Stefan Institute, National Institute of Biology Abstract: The COVID-19 pandemic showed we lack methods to prevent the spreading of airborne pathogens. Face masks and covers are currently employed to protect the wearer from pathogenic organisms. The issue lies in the survivability of pathogens, which remain viable on medical textiles for several hours or even days, serving as a potential source of infections. Our team has developed a technique to prepare functional textiles which successfully inactivate viruses upon contact. These are standard materials (non-woven textiles) for production of disposable medical masks, which are treated according to our method of invention. The treatment does not disrupt the filtering efficiency. We performed biological tests, demonstrating that the final product is safe. The innovative method is safe, low-cost, and scalable, addressing the single-use medical face mask market with a total size of over 5 billion EUR (Y2029, futurebusinessinsights.com). We believe that our innovative technology will be instrumental in combating current and future airborne infectious diseases, resulting in over 1 million mortalities yearly (World Health Organization, 2022). As experts in plasma technologies, developing custom plasma systems, and virology, we are an excellent partner for co-developing a commercial-scale production system and see that it fulfils the necessary regulatory requirements of the medical sector. At present, the technology is at TRL 4. The current team consists of academic staff at the Jozef Stefan Institute (JSI) and the National Institute of Biology (NIB). We seek for a partner to possibly establish a joint venture or to license the technology to producers of respiratory masks and medical textiles. Alternatively, we consider establishing a company for producing medical textiles according to our method – the patent application was filed recently. Figure 1: Facial masks value chain. Our solution is implemented in the space marked in red (Adapted from Findlay et al. 2021). 266 Figure 2:Proposed treatment process for producing antiviral textiles. Gregor Primc. 2022. Figure 3: Our department at JSI is a great partner for designing robust and precise plasma treatment systems. Showcase: quadruple inductively coupled plasma system. Dane Lojen. 2022. 267 MEEVA - Measurable Enhanced Virtual Reality platform for teens with Autism and Neurodevelopment Disorders Author/inventor: Elio Salvadori PRO: Fondazione Bruno Kessler Abstract: The rate of kids diagnosed with Autism and Neurodevelopment Disorders (NDD) is increasing worldwide together with the demand for psycho-behavioral therapies provided by Specialised Centers (SC). However, the current operation of SC suffers from lack of scalability both in term of therapists involved and space occupied. Moreover, the recent pandemic has accelerated the adoption of digital technologies in all sectors; in healthcare, novel solutions for telemedicine are emerging where Virtual & eXtended Reality (VR/XR) is expected to play a major role, e.g. to perform mental health therapies from remote. VR-based mental health therapy (VRT) for people with NDD is a well-studied subject in research which has proved to be effective in improving their life quality. MEEVA is building a teletherapy platform exposing children and teens with NDD to role-play XR games aimed at improving their social skills. The solution increases the geographical reach of SC and optimizes their operations, while families of NDD individuals can save travel time and costs. The unmet need addressed by MEEVA is twofold: (i) excess demand of psycho- behavioral therapies to people with NDD (ASD, ADHD,...), not matched by capacity for therapeutic services by the Specialised Centers; (ii) current teleconference systems are highly ineffective with these individuals, as demonstrated in the experiences during the pandemic. The developed platform is composed by: (i) an app running on top of a VR headset exposing NDD teens to role-play games aimed at improving their social & emotional skills in a playful environment; (ii) a data-analytics software analysing biometrics data collected via wearables and correlating the emotional status of an NDD teen with the experience s/he is having during the session. The aim is facilitating ex-post session assessment by the therapist while enabling predictive therapy methodologies based on quantified data. Compared to existing VR-Therapy tools (like C2Care, Amelia Virtualcare, Floreo) dealing with general mental health issues in settings where the patient is alone, we focus on NDD- specific treatments by engaging small groups of patients in VR based multi-player games performed under the supervision of a therapist properly tuning the scenarios. MEEVA business model is based on subscription agreements with SC (such as private clinics, Foundations and social cooperatives) which provide tele-therapy service to families of NDD teens. For each teen receiving the remote therapy, MEEVA will charge a monthly fee (pay-per- use) to the SC plus a flat yearly fee to cover maintenance and updates of the service. The economic benefits obtained by both SC (in terms of additional earnings enabled by the extended reach, without increasing their headcount) and the families (in terms of time & transportation costs savings) can compensate the costs incurred by adopting our solution. The team behind MEEVA is currently involved in a project supported by EIT Digital (XR4A, www.xr4a.eu) coordinated by FBK with the involvement of Xenia Reply (Italy) and iED (Greece). An MVP has been released at the end of June 2022 (TRL4-5) and a preliminary validation pilot has been organised already which involved 30+ kids and teens with the support 268 of a rehabilitation center. The MVP is currently being enriched with new functionalities and we plan to organise further pilots in Italy and in Greece within the end of 2022. Figure 1. An excerpt of VR scenes from MEEVA platform: (left) Coin hunt (right) Space station. E. Salvadori, M. Dianti. 2022. 269 From polyurethane waste to high value added raw materials Authors/inventors: Maja Grdadolnik, Blaž Zdovc, David Pahovnik, Ema Žagar PRO: National Institute of Chemistry, Department of Polymer Chemistry and Technology Abstract: Extensive use of inherently non-biodegradable plastic leads to an excessive accumulation of plastic waste in the environment, which is associated with related climate change. In Europe, the production of about 1.1 million tonnes of polyurethane foams (PUFs) results in more than 600,000 tonnes of PUF waste per year. PUFs are used in a variety of durable applications such as upholstered furniture and insulation. The most common way of PUF waste disposal is landfilling, which is, along with incineration, unacceptable from environmental pollution point of view. An alternative is chemical recycling, which converts PUF waste into high value-added raw materials. Our solution for PUF waste management is an energy- and cost-efficient microwave-assisted chemical recycling process using a small amount of specialty reagents. Our innovative process enables highly efficient PUF degradation in a short time, which results in about 80% lower energy costs compared to recycling processes based on conventional heating of reaction mixtures. State-of-the-art chemical recycling technologies for PUF waste produce low-quality recycled polyols, while our technology is distinguished by high-quality polyols with properties comparable to the corresponding commercially available polyols. This enables production of high-quality flexible PUFs exclusively from recycled polyols, which has not been possible up to now. Behind the innovation is a team of experts in polymer synthesis, degradation and characterization, with extensive experience in working with industrial and research partners. Our plan is to transfer IPR to companies dealing with PUF recycling and/or manufacturers of polyols or PUFs. 270 Figure 1: Recycling of polyurethane foams as proposed in our innovation. Maja Grdadolnik. 2022. Figure 2: The high quality of recycled polyols produced by our method was confirmed by Repsol in Spain, a multinational company that produces commercial polyols for the synthesis of polyurethanes. Repsol synthesized flexible PUFs that were tested for their mechanical properties. The mechanical properties of PUFs made from our recycled polyols are comparable to PUFs made from virgin polyols. Company Repsol. 2021. 271 Water soluble cannabinoids with increased stability Authors/inventors: Mitja Križman, Jure Zekič, Primož Šket, Alojz Anžlovar, Barbara Zupančič, Jože Grdadolnik PRO: National Institute of Chemistry Abstract: Our technology relates to the field of water-soluble cannabinoids. Cannabinoids have become an important global commodity, and found their place in the food & beverage, food supplement and cosmetics industry, but also elsewhere (e.g. pharmaceutical industry). The major inherent problem related to cannabinoids is their very low water solubility. Our invention provides cannabinoid and hemp resin water solutions, with increased stability and bioavailability. We seek to commercialize the technology through spin-out company on EU market (waterborne cannabinoids and hemp resin with increased stability), taking our share of the 2 billon USD worth EU market (2021) with expected annual growth of 30 % (CAGR), and through licensing with technical assistance for US, Canadian, Australian and Asian markets (selling knowledge and IPR so companies in these geographic areas can utilize local hemp production and develop their own products). The global market is estimated at 13 billion USD (2021) with CAGR at 20 %. Since the market for cannabinoids is well established and growing we will be able to take the advantage of existing marketing and distribution routes to reach our customers and business partners. The team of highly qualified scientists that has developed present patent pending technology is supported by NIC’s Knowledge Transfer Office, by Ljubljana University Incubator and by a local CBD utilizing company. The technology is currently at TRL 5. We also have the capability and facility for production quantities of the final product(s) in multi-kilogram quantities. Figure 1: Schematics of our process. Mitja Križman. 2022. 272 Figure 2: Comparison in water solubility between unmodified (left) and modified (right) hemp resin. Mitja Križman and Jure Zekič. 2022. 273 Rationally designed lutein esters: “The onset of improved and sustainable eye health remedy” Authors/inventors: Alen Albreht, Valentina Metličar, Krištof Kranjc PROs: National Institute of Chemistry; University of Ljubljana, Faculty of Chemistry and Chemical Technology Abstract: Lutein and other carotenoids are natural antioxidants with many beneficial effects on human health. Lutein is especially efficient in the prevention of age-related macular degeneration, which currently affects 15% of the EU population alone (67 million). The global lutein market was valued at $354 million in 2022 and is predicted to double by 2032.1 The existing lutein- containing products are sold mainly as food supplements, but owing to lutein’s intrinsic physicochemical properties, these products have limited shelf-life and bioavailability. Additionally, the main ingredient is obtained through processes that are harmful to humans and to the environment. The overarching motivation behind our innovation is the production of an improved line of lutein supplements that overcome the above hurdles by chemically tweaking lutein’s structure in a sustainable manner through esterification. The main targeted partners (customers) are large food supplement producers that aim to introduce improved products into their portfolio and/or integrate a green, inexpensive, and sustainable technology into their manufacturing process, reducing carbon footprint. The partners’ financial and market gain stems also from the revenues of unique, efficient, and trustworthy lutein-based ingredients, backed by scientific research. The founding team, consisting of three scientific researchers from two PRO’s backed by their TTOs, established a means to various lutein ester compounds with improved chemical stability (over 20-times). Future efforts will be focused on the determination of activity and bioavailability of lutein esters which will drive further technology development and demonstration at a higher TRL level, promoting technology transfer and product commercialization, predicted for 2026. Figure 1: Sustainable platform for the production of lutein esters; Step 1: Extraction, Step 2: Synthesis, Step 3: Purification. Authors: Alen Albreht, Valentina Metličar, Mirica Karlovits. 2022. 1 https://www.futuremarketinsights.com/reports/lutein-market 274 Award announcement Best innovation with commercial potential 13:00 to 13:10 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission members: Alexandre Massart, co-founder and director, Blend Ventures, Jurij Giacomelli, Investment Manager, META Ingenium, Michel Neu, International Technology Transfer Expert, CEA Alternative Energies and Atomic Energy Commission, Nina Urbanič, Adviser for equity investment monitoring and reporting, Slovene Enterprise Fund, Vladimir Jančič, CEO, Publikum Korpfin. ANNOUNCEMENT OF THE WINNERS The evaluation commission weighed all the criteria in the evaluation process and selected two equally ranked winning teams. The award of 2000 Euro goes to the team members: Maja Grdadolnik, Blaž Zdovc, David Pahovnik and Ema Žagar, National Institute of Chemistry for from polyurethane waste to high value added raw materials. The award of 500 Euro goes to the team members: Paweł Kołakowski and Grzegorz Rutkowski, Gdynia Maritime University for Innovative equipment of intervention/service watercraft: Mobile Electromagnetic Mooring System and Batychron. Congratulations! 275 Award announcement: WIPO IP Enterprise Trophy From 13:10 to 13:20 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) ANNOUNCEMENT OF THE WINNER WIPO IP ENTERPRISE TROPHY By celebrating the achievements of inventors, creators and innovative companies around the world, the WIPO Awards aim to foster a culture in which innovation and creativity are encouraged and appreciated at every level of society. Two years ago, at the 13th International Technology Transfer Conference the WIPO awards were given in Slovenia for the first time. The members of the selection committee were Mrs. Nina Urbanič, Slovene Enterprise Fund, Mr. Alojz Barlič from the Slovenian Intellectual Property Office and Christoph Kempf, Karlsruher Institut für Technologie (KIT). The WIPO IP Enterprise Trophy is awarding a Slovenian enterprise for its good practice in constant and methodological use of the IP system in its business activities. The main criteria for the selection were the following for the last 10 years: - the number of cooperations with public research organisations, - no. of employments of your PhDs from public research organisations, - new products or services launched to the market based on TT and IP protected, - public campaigns to promote the appreciation of companies’ IP assets, - encouragements for creative and inventive activity among staff, - programs to use the IP-based business also for public goals and - commercial/marketing strategies based on effective use of the IP system. Among the applications, the jury has decided to give the IP Enterprise Trophy to company Elan, d. o. o. . Short justification: Elan is actively cooperating with several public-research organisations. Their products have a suitable IP protection and are promoted at different fairs and events. Through the social responsibility programs, they cooperate with schools and youth clubs and are having a Reducing carbon footprints program. And finally, they constantly and methodologically encourage the creativity and innovativeness among their staff. 276 Opportunities arising from publicly funded research projects / presentations of successful scientific projects From 13:20 to 14:20 Moderators: Tomaž Lutman, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) France Podobnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Katja Cergol, University of Ljubljana, Knowledge Transfer Office Successful Slovenian scientific projects were presented in short popular lectures. The goal of the presentations is to further promote the science to economy and general public. The future steps towards higher TRLs were also discussed in order to stimulate researchers to bring their technologies closer to the market with different steps that can take place like networking with other PROs to create interdisciplinary teams, by applying for additional EU or national funds. Title Presenter(s) Organization Assoc. Prof. Nataša Karst Research Institute, Karstology in the Classical karst Ravbar, PhD ZRC SAZU Antecedents of environmentally and Prof. Žabkar Vesna, Faculty Of economics, socially responsible sustainable PhD University of Ljubljana consumer behaviour Institute of Slovenian Why the World Needs Anthropologists Prof. Dan Podjed, PhD Ethnology, ZRC SAZU Faculty of pharmacy, New halogen bonds in biological Assoc. Prof. Martina University of Ljubljana & systems Hrast National institute of Chemistry Faculty of Mathematics and Ionically charged topological defects in Physics, University of Prof. Miha Ravnik, PhD nematic liquids Ljubljana, Jožef Stefan Institute Table 1: List of presentations of successful scientific projects 277 Award announcement: WIPO Medal for Inventors From 14:20 to 14:30 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) ANNOUNCEMENT OF THE WINNER WIPO IP MEDAL FOR INVENTORS The WIPO Medal for Inventors is awarding a Slovenian public researcher for his contribution to the national wealth and development. The selection committee members were Mrs. Nina Urbanič, Slovene Enterprise Fund, Mr. Alojz Barlič from the Slovenian Intellectual Property Office and Christoph Kempf, Karlsruher Institut für Technologie (KIT). The entry criteria for the selection were granted patents or utility models in the last 10 years. Further the patented invention had to show a significant economic and technological impact in Slovenia via: - creation of a new company or - creation of new jobs in the companies that cooperate with the researcher or - the number of new products and services launched to the market. The committee ranked all applications and decided that the "WIPO Medal for Inventors" goes to Prof. Dr. Miran Mozetič. Short justification: Prof. Mozetič has over 10 granted patents with examination in the last 10 years and additional 5 without the examination. He is a co-founder of a company Plasmadis. His inventions had impact also on 4 new jobs created in different companies. 278 Connecting education system with academia: Presentations of selected research topics from the Jožef Stefan Institute and proposals for cooperation Parallel session from 13:20 - 15:00 Moderator: Urška Mrgole, Center for Technology Transfer and Innovation, Jožef Stefan Institute About In accordance with the Jožef Stefan Institute’s mission, the Center for Technology Transfer and Innovation promotes scientific work and research accomplishments among young people and the rest of the interested public. The event At the 15th International Technology Transfer Conference a parallel section “Connecting education system with academia: Presentations of selected research topics from Jozef Stefan Institute and proposals for cooperation” took place. The section was aimed at primary and high school teachers where selected research topics from the Jožef Stefan Institute (JSI) and proposals for cooperation were presented. For the introduction the development of breakthrough technologies at the Jožef Stefan Institute video was presented. After the video, activities for the promotion of science and research work, which Center for Technology Transfer and Innovation at the Jožef Stefan Institute carries out independently or in cooperation with the research departments at JSI, were presented. School visits: every Thursday during the school year, the Center for Technology Transfer and Innovation, with the help of other JSI departments, organizes visits to the Institute that are intended for primary and high schools, faculties and everyone else from the school sphere. Open day at JSI: each year at the end of March, traditional Stefan’s Days take place at the Institute, marking the birthday (24 March) of the great Slovenian scientist, Jožef Stefan. In the scope of Stefan’s Days, the Center for Technology Transfer and Innovation, in cooperation with the JSI research departments, organizes the Open Day at JSI. Visitors can choose from a number of visit programmes and look at the laboratories at Jamova cesta in Ljubljana and at the Reactor Center near Ljubljana. Open Week at JSI: In the scope of Stefan’s Days an open week at JSI is organized, where every day of the week one school is welcomed to JSI for a visit. Participation in various European projects and initiatives such as “Science with and for Society”: the Center for Technology Transfer and Innovation at the Jožef Stefan Institute enthusiastically participates in various European projects and initiatives with the aim of promoting science and research work among Youth, e.g. the research festival Znanstival, the European Researchers’ Night, and European projects such as STEM4Youth. Within the STEM4Youth project nine chemistry modules were prepared and implemented in 19 Slovenian primary and secondary schools, with 20 mentors and over 500 elementary and 279 high school students participating. The modules are now available online for all schools to implement them. In the second part researchers from various research departments presented their work. Rok Novak, mag. inž. teh. var. okolja, Department of Environmental Sciences, O2: The multidisciplinary research of the Department of Environmental Sciences focuses on the combination of physical, chemical and biological processes that influence the environment, man and human activities. One of the presented ongoing research projects was related to the investigation of the presence of mercury in the environment. As part of the presentation, various possibilities for cooperation with schools were presented, such as: mentoring, technical day and similar. Žiga Ponikvar, mag. kem, Materials Synthesis Department, K8: The research at the Department is devoted to the development of advanced materials. Their main focus of the research are nanoparticles, especially magnetic nanoparticles which can be easily influenced from a distance with a magnet. dr. Janez Kokalj, The Reactor Engineering Division, R4: The Division, who plays a leading role on the nuclear energy stage in Slovenia, is focused mainly on fundamental and applied nuclear engineering and safety research, with special emphasis on the safe operation of the Krško nuclear power plant. At the conference various interdisciplinary researches were presented, that integrate thermal-hydrodynamical, structural and probabilistic safety analyses. Mark Zver, MSc, Department of Surface Engineering, F4: The main activities are focused on plasma generation, sustenance and characterization of the plasma which is later used for tailoring surface properties of various materials. Plasma is the most common state of matter in the visible universe. Low-temperature plasmas are usable for substance removal, surface cleaning, compound application, etc. Junoš Lukan, MSc, Department of Intelligent Systems, E9: The principal goals of the Department are to contribute to the computational theory of intelligence and to develop high- impact practical applications in various areas such as intelligent information systems, data analysis, intelligent web retrieval, intelligent agents, language technologies, etc. Main focus of the presentation was about the Artificial intelligence and its use in the education. Center for Technology Transfer and Innovation at the Jožef Stefan Institute and similar organisations in Europe represent a bridge in connecting researchers on the one hand and education system on the other. One of our goals is to bring the scientific work and accomplishments as close to the youth, teachers and other interested public as possible, believing that nothing can beat the personal experience and direct contact with the laboratories and top-level researchers. The event proved to be very useful and instructive for teachers who gained new ideas for the implementation of lessons at schools and learned new opportunities to cooperate with the Jožef Stefan Institute. 280 Paper presentations: research papers on technology transfer and intellectual property From 14:30 to 16:50 Moderator: Tomaž Lutman, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Technology transfer officers presented the research papers on technology transfer and intellectual property. The research papers comprised the following topics: • Key factors for successful technology transfer from different points of view (researchers, knowledge transfer experts, enterprises) • The role of TTOs in maximizing impact of science, technology and innovation on society • IP value vs price • Incentives for contract and collaborative research / cooperation with industry • IP negotiation with industry • State Aid in contract and collaborative research • Current status of public investments into research and technology infrastructures • European or national frameworks to transform breakthrough technologies developed for fundamental research purposes into breakthrough innovations with strong industrial applications and societal added value • Examples of IP protection in Artificial Intelligence • Other, chosen by the contributor The papers as presented in the Table 1 are published in the main part of the 15.ITTC proceedings. Title Authors Technology transfer offices as a facilitator of Ivana Vuka, Nikola Balić, Andras Havasi, knowledge triangle integration in the knowledge Marie Mifsud, Leandra Vranješ Markić valorisation era: focus group discourse analysis Proof of Concept typology: a method for classification of PoC activities according to a Linas Eriksonas technology cycle timeframe The “Incubator of Innovativeness” program driving technical readiness levels of the Cracow University Jacek Kasz of technology innovations 281 Magdalena Kukowska-Kaszuba, Science meeting the needs of entrepreneurs Agnieszka Piotrowska-Kirschling, Paweł Kołakowski, Grzegorz Rutkowski Commercialization of R&D results created with Alexander Uspenskiy, Aliaksei public funds in the National Academy of Sciences of Uspenski, Maxim Prybylski Belarus Selection and evaluation of technologies for the Vadim Iatchevici transfer to the industry Subsidizing Knowledge Transfer with Public Funds Michal Belusky Effective collaboration and IP management Levin Pal, Robert Blatnik, Špela Stres Project support services of a technology transfer Tomaž Lutman, Špela Stres office Challenges of Legal and Regulatory Framework for Urška Fric, Jurij Urbančič Blockchain Technology in the EU Technology Transfer: Start and Stop of Deep Well Pedro Maldonado, Silvestre Sarabia, Pumping Through GSM System Emmanuel Costilla, Roberto Avelino Urška Florjančič, Mario Žganec, Vili Advanced 3D sensor system for visual control of Malnarič, Hidajet Kurbegović, Anatolij geometrically complex products Nikonov, Jerneja Žganec Gros, Tomaž Savšek Table 1: List of research papers on technology transfer and intellectual property Scientific Review Programme Committee representative has selected and ranked the best three papers of the Conference: 1st place: Advanced 3D sensor system for visual control of geometrically complex products for a great example of knowledge transfer. 2nd place: Subsidizing Knowledge Transfer with Public Funds for deep and wide knowledge and understanding of technology transfer processes 3rd place: Challenges of Legal and Regulatory Framework for Blockchain Technology in the EU for competent insight into the perspective area of blockchain technology. 282 The Conference closing From 16:50 to 17:00 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Overview of the conference: In 2022 the conference took place at the Jožef Stefan Institute and via Zoom and attracted 100 participants. Among them 30 attended the section Connecting education system with academia. The key note speaker, Mr. Michel Neu from CEA French Alternative Energies and Atomic Energy Commission presented their experiences in collaboration with companies and spin-out creation. Two awards for the best innovation with the business potential from PROs were given to the two winning teams (out of six competing). The six competing teams consisted of 25 team members all together. Two teams came from the PROs abroad. This year, for the first time, the team from abroad was awarded. WIPO IP Enterprise Trophy and WIPO Medal for Inventors were given. 12 research papers on TT and IPR from several countries and 5 successful scientific projects of Slovenian researchers were presented. 283 Day 2 284 CONFERENCE CEREMONY 285 Overview of the Conference Ceremony 14 October 2022 Jožef Stefan Institute, Ljubljana, Slovenia Location: Main Lecture room at the Jožef Stefan Institute (A-building) 12:00 – 12:05 Musical performance / Glasbena točka 12:05 – 12:10 Welcome Speech Prof. Dr. Boštjan Zalar Director of Jožef Stefan Institute 12:10 – 12:20 Opening Speech / Slavnostni govor dr. Igor Papič Minister za digitalno preobrazbo Republike Slovenije Minister for Education, Science and Sport 11:20 – 12:25 Greetings / Pozdravni govor prof. dr. Mojca Ciglarič Chair of the Programme Committee of IS2022 / Predsednica PO IS 2022 Dean of Faculty of Computer and Information Science / Dekanica FRI Ljubljana 12:25 – 12:55 Awards of IS2022 / Nagrade IS2022 prof. dr. Mojca Ciglarič, IS Programme Chair prof. dr. Matjaž Gams, IS Organization Chair prof. dr. Sašo Džeroski, SLAIS President Niko Schlamberger, President of Slovenian Society Informatika prof. dr. Andrej Brodnik, President of ACM Slovenia dr. Mark Pleško, President of Slovenian Academy of Engineering Awards “Hall of fame of Slovenian Computer Science and Informatics” prof. dr. Borut Žalik, president of “Hall of Fame” 15. ITTC: Awards ceremony – competition for the best innovation with commercial potential in the year 2022, WIPO Medal for Inventors and WIPO IP Enterprise Trophy 286 15. ITTC Organising Committee World Intellectual Property Organisation representative / Slovenian Intellectual Property Office representative 12:55 – 13:00 Musical Performance / Glasbena točka 287 288 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek F Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume F Demografske in družinske analize Demographic and Family Analyzes Uredniki / Editors Janez Malačič, Mari Jože Osredkar, Matjaž Gams http://is.ijs.si 12. oktober 2022 / 12 October 2022 Ljubljana, Slovenija 289 290 PREDGOVOR Število prebivalcev Zemlje zadnja desetletja raste linearno in dosega 7.9 milijarde, novembra letos pa naj bi doseglo 8 milijard. Leta 2023 bo Indija postala številčnejša kot Kitajska. Deset najštevilčnejših držav: Kitajska, Indija, Združene države, Indonezija, Pakistan, Brazilija, Nigerija, Bangladeš, Rusija in Mehika. 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 200 let, podobno kot drugi mali evropski narodi. Demografske spremembe so običajno dolgotrajne. Vsako leto in vsak dan pa čutimo posledice depopulacije: število starejših raste, število mlajših upada, razmerje med delovno in vzdrževano populacijo se poslabšuje. Nekaj napotkov je jasnih: potrebno je poskrbeti za dovolj veliko delovno populacijo in vzdržnost pokojninskega sistema, za krepitev družine in skrbi za otroke in starše za povečanje rodnosti, za spodbujanje starejših, da nadaljujejo z delom, dokler gre. Nihče pa ne ve, kaj bodo prinesla prihodnja stoletja, ali bodo Slovenci res izumrli čez nekaj generacij, ali bomo skupaj našli primerne rešitve. Vsekakor so pred nami težki časi, ko so odprta znanstvena debata in analize ključnega pomena za iskanje dobrih rešitev v slabi situaciji in še slabši perspektivi. Slika kaže rast svetovne populacije in letne rasti. Vir: Max Roser, Lucas Rodés-Guirao: Future Population Growth. Janez Malačič, Mari Osredkar in Matjaž Gams 291 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Janez Malačič, predsednik Jože Sambt, sopredsednik Mari Osredkar, sopredsednik Matjaž Gams, organizator Drago Čepar Christian Gostečnik Majda Černič Istenič Boštjan Kerbler Karin Kasesnik Dušan Kidrič Marko Krevs Tomaž Merše Janja Pečar Janja Povhe Jože Ramovš Milivoja Šircelj Petronela Vertot Božidar Voljč 292 O nekaterih dilemah interpretacije podatkov o družini : ankete javnega mnenja in podatki statističnega urada Republike Slovenije On some dilemmas of interpreting data about family: public opinion polls and data from the Statistical Office of the Republic of Slovenia Igor Bahovec † Faculty of Theology University of Ljubljana, Slovenia Ljubljana, Slovenia igor.bahovec@guest.arnes.si ABSTRACT / POVZETEK Empirično raziskovanje stanja družinskega življenja sestavljata dva temeljna vira podatkov: ankete javnega mnenja in podatki, Podatki anket javnega mnenja in Statističnega urada RS in so ki jih zbira Statistični urad. Čeprav imajo ti podatki veliko mero temeljni viri razumevanja stanja družine in trendov spreminjanja. zaupanja, pa vendar v javnosti, včasih pa tudi v strokovni Namen prispevka je pokazati na pomembnost pravilnega literaturi prihaja do dilem ali celo napak interpretacij razumevanj razumevanje vprašanj in odgovorov, saj se pojavljajo podatkov. V prispevku se osredotočamo na dva vidika napak: 1) interpretacije, ki so le deloma točne ali so celo napačne. V dileme in (potencialno) napačno interpretacijo anketnih vprašanj ospredju sta dve vrsti dilem: 1) dileme, ki so povezane s branjem in 2) napake zaradi nerazumevanja razlik med definicijami. posameznega oziroma več anketnih vprašanj; 2) dileme, ki Najprej bomo podali nekaj konkretnih primerov, v zadnjem delu obstajajo zaradi razlik v definicijah. Analizirali bomo vprašanja, prispevka pa podajamo povezano interpretacijo celotne vsebine ki se nanašajo na otroke in starše ter na družino v celoti. prispevka.. KEYWORDS / KLJUČNE BESEDE Družina, ankete javnega mnenja, rodnost, otroci, antropološka 2 Otroci in vzgoja, otroci kot izpolnitev in statistična definicija družine. življenja oziroma želja ABSTRACT Med najbolj zaupanja vrednimi mednarodnimi raziskavami Data from public opinion polls and the Statistical Office of the javnega mnenja gotovo spadata Evropska raziskava vrednot Republic of Slovenia are the basic sources of understanding the (EVS) in svetovna raziskava vrednot (WVS). Obe potekata v state of the family and changing trends. The purpose of the daljšem časovnem obdobju, tako da imamo za večino vprašanj paper is to show the importance of a correct understanding of odgovore iz več let. Za Slovenijo imamo podatke EVS za leta the questions and answers, as interpretations appear that are 1992, 1999, 2008 in 2017. only partially correct or even incorrect. Two types of dilemmas Vse raziskave kažejo, da je družina bolj pomembna kot are at the fore: 1) dilemmas related to reading a single or prijatelji, delo, prosti čas in druge vsebine. Vendar to ne pomeni, several survey questions; 2) dilemmas that exist due to da vsi, ki si želijo družinsko življenje to tudi uresničijo. Vseeno differences in definitions. We will analyze the issues that relate to children and parents and to the family as a whole. mnogi še vedno povezujejo otroke in družino kot del izpolnjenega življenja. Vendar se je pogled javnega mnenja na to OPTIONAL: KEYWORDS v zadnjih desetletjih zelo spremenil. Tabeli 1. in 2. kažeta koliko ljudi meni, da je izpolnitev življenja žensk in moških še vedno Family, public opinion polls, birth rate, children, anthropological precej povezana z otroki. Podatki se nanašajo na Slovenijo – and statistical definition of family. enako kasneje. 1 Uvod Tabela 1: Ali mislite, da ženska za izpolnitev svojega življenja mora imeti otroke, ali to ni nujno? (EVS, v %, podatki za Slovenijo) 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 1992 1999 2008 2017 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 potrebuje Vprašanje ni be honored. For all other uses, contact the owner/author(s). otroke 54,3 36,5 33,7 bilo zastavljeno Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). ni nujno 39,7 59,5 63,1 ne vem 6 3,7 3 b.o. - 0,3 0,2 293 Opomba: V raziskavi EVS 2017 tega vprašanja ni bilo. V Odgovori jasno kažejo, da se je glede interpretacij treba omejiti, vseh naslednjih tabelah so izpuščeni stolpci za leta, ko vprašanje in da je primerno postaviti več vprašanj o istem vidiku ni bilo zastavljeno. družinskega življenja, ker šele iz odgovorov na vsa lahko presodimo, ali so odgovori vprašanih celovito notranje koherentni ali ne. Tabela 2: Moški mora imeti otroke, da bo njegovo življenje izpolnjeno (EVS, v %) Tabela 4: Je že v redu, če je ženska zaposlena, toda tisto, kar si ženske najbolj želijo, so dom in otroci (EVS, v %). 1999 2008 potrebuje otroke 36,3 37,6 1992 1999 2008 2017 NITI-NITI 29,5 23,9 Soglašam 70,0 61,5 61,5 51,1 ni nujno 31,3 36,5 ne soglašam 21,5 33,5 33,6 44,8 ne vem 2,8 1,8 (ne vem) 8,4 4,8 4,7 3,6 b.o. 0,1 0,2 (b.o.) 0,0 0,2 0,3 0,5 Vidimo dve zanimivi zadevi: velik padec mnenja, da mora ženska za izpolnitev svojega življenja imeti otroke (iz več kot 50% leta 1992 na okoli 35% v letih 1999 in 2008). Še bolj Tabela 5: Če bi ženska sama rada imela otroka, ob tem pa zanimivo je, da celo nekaj več vprašanih otroke povezuje z si ne želi stalnega odnosa z moškim, ali vi to odobravate? izpolnitvijo moškega kot izpolnitvijo ženske (2008: moški (EVS, v %) zaokroženo 38%, ženske 34%). Podatki po drugih evropskih državah zajetih v raziskavo sicer v veliko večji meri kot v 1992 1999 2008 Sloveniji povezujejo izpolnitev življenja z otroci (1999: za ženske 55%, za moške 48%). To kaže, da je Slovenska situacija odobravam 55,7 54,3 59,1 daleč pod evropskim povprečjem. ne odobravam 22,4 19,3 31,9 Vseeno pa ljudje v prevladujoči meri vzgojo otrok povezujejo odvisno 14,9 23,8 7 z domom obeh staršev. Soglašanje o tem, da otrok za odraščanje potrebuje dom obeh staršev je sicer nekoliko padlo, a vseeno je ne vem 7 2,5 1,8 po zadnjih znanih podatkih (2008) okoli 86%. b.o. - 0,2 0,2 Glede tega vidika družinskega življenja je primerno pogledati Tabela 3: Otrok potrebuje dom tako z očetom kot tudi z materjo, da bo srečno odrasel podatke statističnega urada R Slovenije. S kratkih preračunom - ali s tem soglašate ali ne soglašate (EVS, v %)? lahko sestavimo tabelo koliko otrok živi v dvostarševskih in koliko v enostarševskih družinah (Tabeli 6 in 7). Podatki kažejo, da je po podatkih zadnjega popisa na terenu leta 2002 velika 1992 1999 2008 večina otrok (80%) živela v dvostarševskih družinah, in to če soglašam 92,2 87 85,7 gledamo na otroke mlajše od 6 let ali na otroke mlajše od 25 let. ne soglašam Dobro desetletje kasneje se je delež nekoliko zmanjšal: po 6 11,8 12,5 podatkih Statističnega urada R Slovenije (SURS) je živelo leta ne vem 1,8 1,2 1,2 2015 okoli 75%. Dejansko jih je nekoliko več, kajti podatki brez odgovora - - 0,7 odražajo stanje glede na podatke upravnih enot in ne stanje na terenu. Strokovnjaki na slovenskem SURSu poudarjajo, da je Samo ti podatki so premalo za celoviteje utemeljeno enostarševskih družin dejansko manj kot kaže statistični podatek, interpretacijo. Kot kažejo ankete, je v letu 2017 dobra polovica ker nekateri pari žive skupaj, prijavljeni so pa na različnih vprašanih odgovorila, da »so tisto, kar si ženske najbolj želijo, naslovih [1; 2]. dom in otroci« (Tabela 4). Odgovori niso povsem skladni z odgovori na vprašanje o izpolnitvi življenja zgoraj! Tabela 6: Deleži otrok (mlajših od 6 in od 25 let), ki žive v Še večja razlika pa obstaja, ko odgovore na vprašanje glede različnih tipih družin (popis 2002, vir SURS, lastni pomena doma z očetom in materjo za vzgojo otrok primerjamo z izračuni). vprašanjem o tem, da skoraj 60% vprašanih odobrava naj ima ženska otroka tudi v primerih, ko »si ne želi stalnega odnosa z moškim« (Tabela 5). do 6 let do 25 let Kako pojasniti precej velike razlike v odgovorih? Zakaj ljudje Poročena starša z otroci 64,6% 72,0% po eni strani v menijo, da je za otroka boljša dvostarševska družine (2008: 86%), po drugi pa v skoraj 60% odobravajo željo Izvenzakonska skupnost z otroci 15,3% 8,5% ženska po otroku, ki bi rastel v enostarševski družini? Zdi se, da Mati z otroci 18,1% 16,9% v prvem primeru ljudje vidijo dobrobit otroka, v drugem pa pravice žensk – mnogi ljudje obeh vprašanj ne vidijo skupaj. Oče z otroci 2,0% 2,6% Dvostarševska družina (skupaj) 79,9% 80,5% Dvostarševska družina (skupaj) 20,1% 19,5% 294 živijo skupaj v skupnem gospodinjstvu (domu), "a skupno bivališče ni določujoča značilnost družin" [3, str. 329]. Tabela 7: Število otrok v starostnih skupinah 0 do 4 leta in 0 do 24 let po različnih oblikah družin, 1.1.2015. (Vir: SURS, Prebivalstvo po gospodinjskem statusu, petletnih starostnih skupinah in spolu, Slovenija, lastni izračuni) Vse druge Otrok v Otrok v Otrok v Otrok v oblike - otroci Otrok v enostarševski enostarevski zunaj- istospolni niso člani družin- zakonski družini živi z družini živi z zakonski partnerski skih gospo- skupnosti mamo očetom skupnosti zvezi dinjstev Vsi otroci Število otrok 0 do 4 leta 46354 22166 6491 33013 10 1280 109314 Št. Otrok do 24 let 263339 94615 20419 91794 20 20564 490751 Delež (%) otrok od vseh otrok 0 do 4 leta 42,4% 20,3% 5,9% 30,2% 0,0% 1,2% 100,0% 0 do 24 let 53,7% 19,3% 4,2% 18,7% 0,0% 4,2% 100,0% Deleži po tipih družin Dvo-starševske družine Enostarševske družine Druge oblike 0 do 4 leta 72,6% 26,2% 1,2% 0 do 24 let 72,4% 23,4% 4,2% Različnost razumevanja se jasno vidi v primerih ko v Deleži otrok, ki živijo v dvostarševskih družinah se morda gospodinjstvu živijo tri generacije ali je gospodinjstvo zdijo zelo veliki, saj se v Sloveniji že veliko let okoli 60% otrok enočlansko (tako gospodinjstvo ne more biti družinsko). Dolenc rodi zunaj sklenjene zakonske skupnosti. Vendar ni težko najti [2, str. 11] opisuje primer: pojasnila. Zdi se, da delež otrok, ki živijo v enostarševskih " V stanovanju št. 1 živi gospa Marija, ki je stara 78 let. Odkar družinah, ni tako velik, ker imata oba starša odgovoren in skrben ji je umrl mož, […] živi sama. Vsi trije otroci so se odselili že odnos do otrok in otrok v veliki večini (ocenjujemo na več kot prej in živijo v lastnih gospodinjstvih. Tako kot gospa Marija tudi 70%, če upoštevamo tudi vzpostavljene družine). Čeprav se ne 40% žensk njene starosti živi samih. […] Gospa Marija je seveda poročita, kmalu živijo skupaj. Z drugimi besedami, za pare je tudi že babica, saj ima 3 vnuke in 2 vnukinji. Čeprav je mama in veliko »lažja« naloga, da skupaj skrbijo za otroke, kot pa da bi babica, v statističnem smislu ni družina ampak enočlansko se poročili. gospodinjstvo." Pomembno je dodati: tudi če bi v istem gospodinjstvu živela poročen sin ali hči (ali sin ali hči z vsaj enim otrokom), ovdovela babica in mama po statistični definiciji ni član (osnovne) družine. 3 Opomba glede dveh tipov definicije družine Večina razširjenih družinskih gospodinjstev (okoli 60%) je sestavljeno iz treh generacij. Potrebno je opozoriti tudi na napake, ki so posledica »V veliki večini teh gospodinjstev (94 %) samo en član ni neupoštevanja dejstva, da se podatki zbirajo glede na dve različni pripadal nobeni družini, najpogosteje je bil to eden od ovdovelih definiciji družine – žal pa le redko najdemo opozorila na to, da staršev (pretežno mati) ali pa neporočen brat/sestra enega od so podatki zbrani po določeni definiciji in jih je zato treba družinskih članov, zato so v teh gospodinjstvih med interpretirati po tisti definiciji. V čem je težava? Antropološka, nedružinskimi člani prevladovale ženske […]. Vsak četrti član sociološka, pravna in definicija »običajnega človeka«, pa tudi razširjenega družinskega gospodinjstva je bil vnuk.« (ibid. 7) religiozna (npr. krščanska) družino razume kot najmanj Z drugimi besedami, čeprav vsakdanje razumevanje ovdovele dvogeneracijsko skupnost. Zakonska skupnost v tem pomenu ni babice in dedke šteje med člane družine (trigeneracijske), jih družina, ampak je eden njenih temeljnih namenov zasnovanje statistična definicija opredeljuje drugače. Podobno je z družine. Vemo, da vsi pari ne morejo imeti otrok. Statistična statistično opredeljenimi poročenimi ali zunajzakonskimi pari definicija je, če jo beremo ohlapno, širša: družina so tudi brez otrok, ki je vse pogostejši tip statistične opredelitve družine. zakonske in zunajzakonske skupnosti brez otrok. Vendar ni tako Nekateri teh parov otrok (še) nimajo, drugi pa otroke imajo, a so preprosto. Opredelitev definicija statističnega urada R Slovenije oblikovali svoje družine ali zapustili skupno gospodinjstvo. Brez (statistična definicija) se začenja takole: "Družina je življenjska upoštevanje teh vidikov statistične opredelitve družin lahko skupnost oseb v okviru zasebnega gospodinjstva.« Antropološka napačno sklepamo vrsto stvari. Podajmo samo en primer: definicija nasprotno poudarja, da večinoma člani družine res povprečno število otrok v statistično opredeljenih družinah ni 295 povprečno število otrok na mati ali družino, ampak povprečno potrebna dvojna previdnost. Ne preseneča, da so mnogi vprašani število otrok, ki živi v družinskih gospodinjstvih. pri vprašanju ali odobravajo, da bi žena imela otroka tudi če si ne želi stalnega odnosa z moškim, v ospredju videli pravico žensk – in so tako odgovorili. Podobno so pri vprašanju ali je za otrokovo odraščanje bolje, da živi v domu obeh staršev, videli dobro 4 Sklep otroka. Čeprav sta vprašanji vsebinsko povezani, sta zastavljeni tako, da v ospredje postavita različne akterje – mnogi vprašani V prispevku smo pokazali na nekaj dilem pravilnega branja zato niso prepoznali njune povezanosti in so na vsako vprašanje podatkov empiričnih anketnih raziskovanj in statističnih odgovarjali kot oni mislijo ali kot je »družbeno najbolj primerno« podatkov o družini. Omenili smo tudi na nekaj napačnih - ne pa tako, da bi pri obeh vprašanjih upoštevali dobro vseh interpretacij, ki jih lahko najdemo tudi v strokovni literaturi. Zdi vpletenih akterjev (obeh staršev in otrok). se, da je treba biti pozoren predvsem na sledeče vidike: 1) Ko uporabljamo podatke zbrane po obeh definicijah družine, je potrebno jasno poudariti za katero definicijo v katerem primeru gre. REFERENCE 2) Za mnoge podatke posameznih anketnih vprašanj in [1] Dolenc, Danilo. 2011. "Gospodinjstva in družine, Slovenija, 1. januar podatki statističnega urada lahko rečemo, da so veljavni znotraj 2011 - končni podatki" (SURS), (Prva objava : 30. junij 2011) http://www.stat.si/novica_prikazi.aspx?id=4029, dostop 1.2.2012.. nekih »meja«. Ne smemo jih uporabljati preko njih. Zgoraj smo [2] Dolenc, Danilo. 2016. Ata, mama, babi, dedi… Gospodinjstva in družine podali nekaj konkretnih primerov, ki kažejo na potrebno v Sloveniji. Ljubljana: Statistični urad Republike Slovenije. http://www.stat.si/StatWeb/File/DocSysFile/8914/ata-mama-dedi- previdnost. Eden izmed načinov, da razrešimo dileme, ki babi.pdf (dostop 20. januar 2018). nastanejo v primerih, je ta, da ima anketni vprašalnik več [3] Ember, Carol R. in Melvin Ember. 1988., Antropology, New Jersey: vprašanj, ki vprašajo o »istem«, a nekoliko drugače. V raziskavi Prentice Hall. [4] Zulehner, Paul M.; Tomka, Miklós. 2008. Religionen und Kirchen in Aufbruh so tako za vsako izmed treh načinov izražanja Ost(Mittel)Europa : Entwicklungen nach der Wende. Ostfildern : (ne)solidarnosti (medosebna, družbeno-sistemska, Schwabenverlag, cop. individualizem) uporabili tri vprašanja [4]. Na ta način lahko tudi precej dobro preverimo, ali ljudje odgovarjajo koherentno. VIRI 3) Zlasti pri delikatnih anketnih vprašanjih je treba biti pozoren na to, da ljudje ne bi odgovarjali tako, kot menijo da je Evropska raziskava vrednot, podatki iz Arhiva družboslovnih podatkov za »družbeno« pravilen odgovor in ne kot oni sami menijo. Zato je raziskave EVS 1992, EVS 1999, EVS 2008 in EVS 2017. https://nesstar2.adp.fdv.uni-lj.si/webview/?language=sl (dostop 2015 do zelo pomembno kako je vprašanje zastavljeno. Pri interpretaciji 2022). odgovorov na vprašanja, ki imajo velik »vrednostni naboj«, pa je 296 DEMOGRAPHIC DEVELOPMENTS IN KOSOVO IN TWO DECADES OF THE CENTURY XXI Dr.sc. Sami Behrami Msc. Fadil Bajraktari Kosovo Environment Protection Agency Kosovo Environment Protection Agency Str. Luan Haradinaj (ex- media palace) Str. Luan Haradinaj (ex- media palace) 14th floor, 10000 Pristina 14th floor, 10000 Pristina Tel:+381 (0) 38 33 236, mob: +377 (0) 44 146 861 Tel: mob: +377 (0) 44 146 861 E-mail: samibehrami@gmail.com, E-mail: fadilbajraktari@gmail.com, Abstract: 1. INTRODUCTION Demographic processes do not develop isolated from outside of social flows but in mutual dependence on Resources and demographic potential are the biological, economic, social, political, historical, most important component of the human psychological, spatial, and other factors. The development of a country, including the influence of these factors is different in space and time, qualitative and quantitative characteristics and thus causing significant differences in demographic the social and biological potential of the development. Kosovo after the 80s and especially after the 90s of the population. last century is characterized by the deterioration of the Kosovo is characterized by specific demographic general economic, political, security, and other development compared to other countries and situation, which escalated into open war at the end of other populations in the region and Europe in the 90s, and it was accompanied by great general. Such a development was primarily a consequences in the demographic sphere as well. consequence of the low and late level of As a result, today Kosovo is at the beginning of a economic development (industrialization), demographic crisis, which is deepening day by day urbanization of life as well as the very one-sided and the emigration of the population has an and unfavorable economic structure (extractive extraordinary contribution. industry). Thus, Kosovo was delayed in the From the analysis of the current trends and future demographic developments in Kosovo, it can be stages of demographic transition, presenting the concluded that if no concrete population policy last demographic transition in Europe. measures are taken, the demographic trends will However, the demographic situation in Kosovo in worsen further with the deepening of the depopulation the last three decades is unfavorable and has process, demographic aging, and deterioration of all worsened significantly, which can also be defined demographic structures and socio-economic of the as a demographic crisis. The main contributor to population, which would jeopardize not only the stable the disadvantages of demographic trends during demographic development but also the general these three decades is undoubtedly emigration. stability in Kosovo, since, for the sustainable If there won`t be actions taken, the demographic development of countries, it is necessary to ensure trends will worsen even more, therefore demographic stability in the first place. Ignoring the demographic processes or their population policies have become necessary in unconstrained (spontaneous) development will order to reduce the consequences of negative undoubtedly lead to a further deepening of the developments that are transmitted in all segments demographic, economic and social crisis, which poses of life. a threat to sustainable development and the fulfillment of the Sustainable Development Goals - Agenda 2030. 2. DEMOGRAPHIC DEVELOPMENTS Keywords: demographic developments, population, 2.1. Dynamics in the total population fertility, natural increase, structure by age, emigration Kosovo, etc. The movement of the general population of Kosovo shows that many times that Kosovo went through peaceful phases of development, there 297 was an increase in the population, while in war of 1999, the population of Kosovo for the periods of political, and economic crises and first time in the period 1991-2011 is characterized wars, there was a decrease in the population with by a tendency to decrease the total population. the loss of people or emigration. In the first two decades of the XXI century, the After the Second World War, with the population is characterized by an accelerated improvement of socio-economic and sanitary trend of decline. Compared to the year 2000, conditions, the total number of the population has when Kosovo was estimated to have 2,304,000 been constantly increasing (until the beginning of (1) (KAS estimate since there was no population the XXI century), even though emigration register), at the end of 2020 the number of continued with different intensity throughout the inhabitants decreased to 1,798,186, which period to reach a peak in the last 10 years of the represents a decrease of -505,814 inhabitants, or 20th century, when it is estimated that 30-35% of - 21.9%. During this period, Kosovo lost more the total population of Kosovo emigrated. As a than 1/5 of its population. consequence of mass emigration and losses in the 3000000 2500000 2000000 1500000 1000000 500000 0 1948 1953 1961 1971 1981 1991 2006 2011 2021 2031 2041 2051 2061 U/L M/M L/H Graph 1. Dynamics in the total number and projections of the population in Kosovo 1948-2061(2 and 3) After the XX century, when the population of 2.2. Indicators of natural increase in Kosovo increased by 139.6% (1948-1991). In the Kosovo 2000- 2020 first half of the century XXI, the first phase will be characterized by stagnation or slow population As a long-term (historical) process, the growth of 2.1% (2011-2031), while the second characteristics of the natural movement are a phase (2031-2061) will be the phase of the consequence of the early socio-economic and depopulation process with negative growth of demographic development, while the later trends -17.9%. Until the end of the century, the process will be a reflection of today's socio-economic, of depopulation will deepen even more, cultural, and demographic situation, as well as the understandably, if no unexpected positive or natural dynamics of the population (4). negative developments occur. Fertility trends in -2019, 2020, and 2021, were recorded as the lowest number of births in Kosovo since 1920 and 1939 respectively. The 298 number of births in Kosovo in the period 2000- the number reaches 12,641(5) deaths, which 2020 has decreased from 38,687 (2000, births shows an increase of 46.6%. only in Kosovo), to 21,952 (2020) and 22,630 Natural increase- is characterized by the trend of (2021) (5), which means almost half of births (- falling even faster than the birth rate. Thus, 43.2% and -41.5%, respectively). compared to the year 2000, when the natural Mortality trends - mortality is the only increase was 30,063 people, in 2021 it decreases component of the natural movement of the to 9,989, which represents a decrease of 20,074 population that is characterized by growth trends people, or a decrease of almost 3 times. The in the observed period. Thus in the year 2000 natural increase in 2021 is almost similar to the when Kosovo had registered 8624 deaths in 2021, second half of the XXs of the last century. 40000 35000 30000 25000 20000 15000 10000 5000 0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 L/F V/M SHN/NI Graph 2. The trend of fertility, mortality and natural increase in Kosovo 2002-20211 As can be seen from graph 2, the Covid 19 2.3. Population structure by age - pandemic effects were high, in Kosovo for the demographic aging 2000-2021 first time the number of deaths was higher than the natural increase of the population which as a In Kosovo, the process of demographic aging phenomenon (since the end of the second world appears as a phenomenon from the 70s of the last war) from the vital statistics in Kosovo was century (the period when the participation of registered himself in 1951 (6). young age groups in the general population The pandemic has accelerated the deterioration begins to decrease). (of the ratios) of the natural movement of the Important (negative) changes in this aspect occur population in 2020 for: in the last decade of the XXth century, when for • 10.4 years in terms of mortality and the first time this participation decreases below • 8.3 years in terms of natural increase. 50%, even though the young age group made up the majority of the population. It should be noted that although the participation of the young age 1 Explanation: The data of 2021 were used by the ASKDATA platform, since in the publication Statistics of Births, Deaths, Marriages and Divorces, the data also includes births, deaths, marriages and divorces from outside Kosovo. 299 group has decreased since the 70s, the overall also negatively manifested in the structure of the number has increased until the beginning of the population according to age, affecting the 90s. The situation of the 90s, in addition to the increase in the participation of the older age demographic and socio-economic sphere, as a group. result of the war and selective emigration, was 60 50 40 30 % 20 10 0 1948 1961 1971 1981 1991 2011 2021 2031 2041 2051 2061 0-19 20-59 60+ Graph 3. Participation of age groups in the population of Kosovo 1948-2061 The very rapid decline of natural increase and emigrant territory. The main causes that forced selective emigration (age groups of 20-39 the population to emigrate were and remain still: compose nearly half of emigrants) have the low level of economic development, the accelerated the aging process of the population. destruction caused by wars, as well as the Thus, until 2011, the age group over 60 unfavorable political situation, and other related constituted 9.6% of the population, in 2021 this factors. Other reasons are related to emigration, participation has increased to 13.5%. At the same such as the dissatisfaction of the citizens of time, the 0-19 age group showed a tendency to Kosovo with the current state of the socio- decrease participation from 38.1% to 32.3% (7). economic perspective and the general level of Population aging as a phenomenon is well-being, manifested by a high rate of accompanied by negative consequences for unemployment, especially among young people, demographic, economic, social, and other and the high percentage of people living in developments. poverty. In the period 2000-2021, 422,761 inhabitants have left Kosovo (according to KAS statistics), 2.4. Emigration trends 2000-2021 with an average of over 21,000 inhabitants per year, even though there was previously the belief Population emigration from Kosovo to European that with freedom and independence, Kosovo countries is not a new phenomenon. Throughout would also recover from this centuries-old the XXth century and the beginning of the XXIst wound. century, Kosovo was and remained a typical 300 80000 70000 60000 e 50000 ntvraig 40000 i emr. 30000 N 20000 10000 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Graph 4. Emigration trends in Kosovo 2000-2021 Even more inconvenient is the fact that based on 3. CONCLUSION various surveys carried out in the country, about 60% of the respondents have expressed the desire Today, Kosovo is facing radical changes in its to leave Kosovo, mainly the new generations (20 demographic profile. This is best argued by the to 40 years old) who make up the main fact that: on the one hand, we have a drastic demographic and birth cohort, the main group of reduction in the number of births and a natural work, security, causing a decline in "human increase, while on the other hand, as a result of capital", as the main carrier of socio-economic selective emigration, the population is aging with development. accelerated trends. The situation is so Given the current progress but also what is unfavorable that it can be defined as a expected in economic development, employment demographic crisis. opportunities, and other unfavorable The demographic problems that Kosovo will face circumstances, migratory movements of the during the two decades of the XXI century can be population with undiminished intensity should be prevented or mitigated through population expected for a while. Unfortunately, Kosovo's policies. institutions have not done much to address the Since emigration is the most important factor in factors driving emigration, such as economic the decline or stagnation of the population of development, unemployment, and prospects for a Kosovo, the state must act to influence the safe, better, more dignified life. reduction of the causes that encourage The situation regarding emigration could worsen emigration. Establishing better conditions for even more in the case of visa liberalization and people, especially the youth, to have confidence the union of Kosovo with the EU, which could in building a future in their country is the key to stimulate a massive wave of emigration, given the stopping the emigration and the demographic fact that Kosovo lags behind the EU countries in crisis in Kosovo. the socio-economic sphere since one of the main If the causes driving the population to emigrate factors of migration is the difference in income are not addressed, other provisions aimed at between the countries of origin and host. 301 increasing fertility may simply result in more developments, but immediate population policy people leaving the country. measures must be taken with the aim of Demographic developments and the sustainable demographic development, which is a consequences of these developments, both the condition for overall sustainable development current ones and those that the Kosovar society and the fulfillment of the Sustainable will face in the future, do not allow the indifferent Development Goals - Agenda 2030 attitude of the society and the state to these 4. LITERATURE 1) “Kosovo Vital Statistics, 2002/2003 “, demografike-te-popullsise-se-kosoves-ne- Kosovo Agency of Statistics. Prishtina 2004, periudhen-1948-2006.pdf pg 6. in English available at https://ask.rks- 4) Islami H.(1981). “Popullsia e Kosovës”. gov.net/media/1822/kosovo-vital-statistics- Studim demografik. Enti i Teksteve dhe 2002-2003.pdf Mjeteve Mësimore., Prishtinë fq 39 “Statistikat vitale të Kosovës”, Agjencia e 5) Preliminary data, available at: Statistikave të Kosovës, Buletini nr.4, http://askdata.rks Prishtinë 2005, fq. 6 in Albanian available gov.net/pxweb/sq/ASKdata/ASKdata__Pop :https://ask.rks- ulation__Demography%20and%20Migratio gov.net/media/1823/statistikat-vitale-te- n/ kosoves-2004.pdf 6) Behrami S., Bajraktari F., Zogaj N., (2021) 2) “Kosovo population projection 2017 – “The impact of the Covid 19 pandemic on 2061. Kosovo Agency of Statistics. demographic development in Kosovo”., Prishtina 2017, fq21, in English available International Conference- "Geographical https://ask.rks-gov.net/media/6287/kosovo- changes during the Covid-19 pandemic”., population-2010-2061.pdf University of Tirana, Faculty of History and Philology, Department of Geography, 3) “ Demographic changes of the population of Tirana 2021. Kosovo in the period 1948-2006 ”, Kosovo Agency of Statistics, Pr. 2008. fq7, in 7) Behrami S., "The demographic crisis of Kosovo in the two decades of the century Albanian available at https://ask.rks- XXI”, in Albanian available at https://www.albinfo.ch/kriza-demografik- gov.net/media/1834/ndryshimet- ne-kosoves-ne-dy-dekadat-e-shek-xxi/) 302 Politična korektnost in spoštovanje teles umrlih Political correctness and the respect of human body after death Drago Čepar Tomažičeva 34 Ljubljana, Slovenija drago.cepar@gmail.com To hitro spremembo bomo ilustrirali z nekaj dejstvi in se vprašali, ali bi morebiti lahko bila posledica prostorske stiske, POVZETEK ekonomskih, ekoloških, etičnih ali verskih razlogov. Članek opozarja na neverjetno hitro in temeljito spremembo tisočletja stare kulture pokopavanja in spoštovanja teles umrlih v Sloveniji. V nekaj desetletjih je delež sežigov poskočil od 0 do 2 Neverjetno povečanje upepelitev 84%, ponekod tudi preko 97%. Z analizo možnih vzrokov kot so »Slovenija je fenomen od fenomenov, ker je tako visok odstotek prostorska stiska, ekonomski, ekološki, etični in verski razlogi, upepelitve. ….Mi smo v 30 letih prišli iz 0 na 97 %,« je povedal ne pridemo do razlage tega fenomena. Nasprotno, podatki kažejo, gospod Domen Kokalj s pogrebnega podjetja Žale [1] , Jože da bi se bilo treba upepeljevanju izogibati. Vendar nas mediji s Homar, direktor podjetja Menina pa: »Trenutno jih je blizu 75 temi podatki ne seznanjajo, kot da bi se pokoravali neki politični odstotkov, kar nas umešča v evropski vrh, skupaj z Veliko “korektnosti”. Ostaja vprašanje, kdo podpira tak razvoj in zakaj. Britanijo. Najbolj osupljivo pri tem je, da smo mi ta odstotek, za razliko od Britancev, dosegli v zelo kratkem času, v zadnjih KLJUČNE BESEDE petnajstih letih, in da ta odstotek še narašča. V tem pogledu smo družina, pokopavanje, politična korektnost, spoštovanje Slovenci edinstveni v evropskem prostoru" [2] . Po besedah mag. človeškega telesa, upepelitev, pokop v krsti, ekologija, etika, Lidije Pliberšek, direktorice Pogrebnega podjetja Maribor je verska svoboda, prostorska stiska porast upepelitev v Sloveniji "naravnost osupljiva". Leta 2020 smo sežgali 83.84% pokojnikov. Med članicami EU ABSTRACT sta nas takrat prekašali le Češka 84,08% in Danska 85,84%.[3] This paper warns of unbelievably rapid and thorough change of Marsikje v Sloveniji je odstotek upepelitev krepko nad 90. V thousands of years old culture of burying and respecting the body Večeru 4. 12. 2021 [4] na primer beremo, da so v Slovenj Gradcu of the death in Slovenia. In some decades the share of cremations leta 2021 do sredine novembra imeli 4,5 odstotkov klasičnih jumped from 0 to 84%, in some locations also 97%. The analysis pokopov, v Mežici 10 odstotkov, na območju JKP Log (občine of possible causes such as lack of space, economic, ecological, Ravne, Prevalje in Črna) v letu 2020 pa 4 odstotke. Je tako zaradi ethical and religious reasons does not give a satisfactory prostorske stiske, ekonomskih, ekoloških, etičnih ali verskih explanation of this phenomenon. On the contrary, the data shows, razlogov? that cremation should be avoided. However, media do not inform us about these data, like being obedient to a political “correctness”. The question, who supports such a trend and why, 3 Prostorske stiske remains unanswered. posameznik, ki se odloča za vrsto pogreba, ne čuti. Varčno gospodarjenje s prostorom je lahko tema razmisleka za občinske KEYWORDS urbaniste, svetnike in župane. Za površine vsake občine, posebej family, burying, political correctness, respect of human body, mestne, tekmujejo različni nameni. Tudi avtomobili in grobovi. cremation, burial in a coffin, ecology, ethics, religious freedom, Vsak avtomobil, tudi če nima garaže v hiši, potrebuje in dobi vsaj lack of space. tri parkirna mesta (blizu mesta bivanja lastnika, pri njegovem delovnem mestu ter pred uradi, nakupovalnimi središči, …). Če je parkirni prostor velik za štiri klasične grobove, torej 1 UVOD avtomobilu namenimo površino 12 grobov. Pri mirovalni dobi groba 10 let v isti grob v človekovi življenjski dobi zaporedoma Spoštovanje človeškega dostojanstva pred rojstvom, po rojstvu pokopljemo na primer 4 svojce: prostor za klasičen pokop enega in tudi po smrti ter varno okolje trdne družine sta močno človeka tako predstavlja približno 2 odstotka prostora za en povezana s pogumom za sprejemanje novih življenj. Zato je avtomobil. treba opozoriti na neverjetno hitro in temeljito spreminjanje Žarni grob res zavzema dober kvadratni meter manj površine kot tisočletja stare kulture pokopavanja in spoštovanja teles umrlih. klasični, vendar v Sloveniji ni občine, tudi mestne ne, ki bi ji za Pokop telesa vzpodbuja trajno povezanost družine, stik z lastnimi žarne ali klasične grobove zmanjkalo prostora. Toliko koreninami in narodnim izročilom, ki nam govori o pomenu spoštovanja do svojih pokojnikov, da bomo za grobove družine. zagotovili potrebne površine, bomo vedno premogli. Dežela, katere polja in travnike preraščajo gozdovi, ki jih je več kot 60 303 odstotkov, in bi jih bilo še več, če država ne bi plačevala kmetom peč. Sproščajo se vodikov klorid, zelo nevarni dioksini in furani, košnje travnikov ob njih, lahko zagotovi svojim prebivalcem živo srebro (vse iz amalgamskih zalivk se sprosti v okolje; prostor za zadnji počitek v slovenski zemlji. Če bi bilo emisije živega srebra iz upepeljevalnic so pomemben vir pomanjkanje prostora razlog, da bi oblasti podpirale sežiganje onesnaženja okolja) ter druge kovine. [7] umrlih, bi ga morala najbolj podpirati tista članica EU, ki ima V Sloveniji s sežiganjem mrtvih obogatimo zrak s tri tisoč tonami med vsemi članicami največjo gostoto prebivalstva. To je Malta, CO2 letno, pokurimo skoraj sto tisoč kubikov vedno bolj katere gostota prebivalstva je petnajstkrat večja od slovenske. dragocenega plina (za vsakega pokojnika, po podatkih podjetja Vendar Malta do leta 2019 sežiga ni dovoljevala, sedaj ga Žale, 5 kubikov), obenem pa učimo otroke prihraniti kakšno dopušča, vendar krematorija na Malti ni in ga še nekaj let ne bo. kalorijo in hvalimo dobavitelje zelene elektrike. Na Konferenci [5] ZN o podnebnih spremembah v Glasgowu si je nekaj sto predstavnikov in voditeljev 197 držav novembra 2021 dva tedna belilo glavo, kako zmanjšati izpuste CO2. Zaradi okoljskih razlogov je Civilni iniciativi Aljažev hrib pred leti uspelo 4 Ekonomski razlogi preprečiti zgraditev krematorija v Celju. V časopisih beremo so lahko cena pokopa, ki je v Ljubljani 647 evrov za osnovni članke, kot na primer »Energetska ura resnice za evropsko pogreb v krsti in 482 za pogreb v žari (če upoštevamo tudi 85 politiko« [8] , mediji pozivajo k ukrepom za (tudi še tako evrov za upepelitev), ter najemnina groba (v Ljubljani 38 evrov majhno) znižanje porabe plina. za klasični in 23 evrov za žarni grob). [6] A. Mernik med težavami, ki jih je imel z zbiranjem podatkov Cene pogrebov so v različnih slovenskih občinah različne, navaja tudi raziskavo [9] , v kateri avtorja ugotavljata, da je posebej se razlikujejo cene pogrebov z upepelitvijo, saj mora število raziskav o emisijah iz upepeljevalnic v primerjavi z naročnik, ki ni iz Ljubljane ali Maribora, pokriti prevoz nekaterimi drugimi raziskavami, predvsem tistimi, ki pokojnika v Ljubljano ali Maribor in potem prevoz žare nazaj, obravnavajo emisije iz sežigalnic odpadkov, zelo omejeno in to kar lahko znese tudi nekaj sto evrov. V Mežici je žarni pogreb za kljub dejstvu, da število upepeljevalnic po svetu ni majhno in da 50 evrov dražji od klasičnega, v Dravogradu za 136 evrov, na še narašča. Ptuju pa za 186 evrov. V Mariboru je pogreb s krsto za 21 evrov dražji od žarnega, v Kranju sta ceni približno enaki. Celo v Ljubljani in Mariboru tako množičnega odločanja za 6 Etični razlogi. upepeljevanje ne moremo pripisati razliki v ceni pogrebov, posebno pa ne v drugih krajih, kjer je cena pogreba z žaro višja Bogomir Štefanič [10] je navedel naslednjo misel velikega kot cena pogreba v krsti – tudi tam so namreč odstotki pogrebov človeka in pravnika dr. Lovra Šturma:« Človeško dostojanstvo v krsti prav tako nizki ali še nižji kot v obeh mestih s krematoriji. je čisto posebna temeljna človekova pravica, ki za razliko od Poglejmo še grobnine oziroma cene letnega najema grobov. V drugih pravic, ni priznana samo živim osebam, temveč tudi Ljubljani nas enojni grob stane 38 evrov na leto, žarni pa 60 pokojnim.« Poglejmo kakšno je dostojanstvo pokojnika v odstotkov tega zneska, torej 22.80 evrov, v Mariboru 30 in 21,5, nadaljevanju postopka upepelitve. v Kopru 31 in 22, v Kranju 27 in 24, v Velenju 34 in 23, Slovenj »Po sežigu se pepel pograbi v posebno posodo. Kosti, ki ostanejo Gradec 28 in 23, v Radljah 30 in 24; v Mežici in Dravogradu sta po sežigu, kot so lobanja, prsni koš, kolki in kolena, se zmeljejo obe ceni enaki. Razlike v letnem strošku se torej gibljejo od 15 v mlinu«. [11] evrov v Ljubljani, 11 v Kopru in Velenju 8,5 v Mariboru, 6 v Lobanja, prsni koš, kolki in kolena, gredo torej v drobilec - Radljah, 5 v Slovenj Gradcu, 3 v Kranju, do nič v Mežici in krogelni mlin, kjer pokojniku polomijo in strejo vse kosti. V Dravogradu. Na Blokah nimajo žarnih grobov in žare zapisih se mnogi izogibajo besedam drobilec, mlin, mletje, pokopavajo v enojne ali večje grobove. S tako majhnimi drobljenje, ampak zapišejo, da se kostem »zmanjša prostornina«. razlikami ni mogoče obrazložiti tako hude rasti sežigov posebej Kdor je bil priča temu manjšanju prostornine in je poslušal tudi, ker kraji z manjšo razliko v grobninah ne kažejo manjših pokanje in hreščanje ob lomljenju in trenju kosti pokojnika, se odstotkov žarnih pokopov. V Mežici in Dravogradu sta ceni letne bo iz spoštovanja do svojega ali sorodnikovega telesa odločil za najemnine žarnega in klasičnega groba enaki, cena žarnega pokop v krsti. »Postopek kremiranja je precej zastrašujoč, pokopa je višja od cene klasičnega, kljub temu pa so v krste predvsem mletje ostanka kosti…« [12] položili v Mežici le 10, v Dravogradu pa le 7 odstotkov pokojnikov, kar je celo manj kot v Ljubljani. Tako niti cene pogrebov, niti cene grobnin, niti obojne skupaj ne morejo 7 Verski razlogi. pojasniti trendov zadnjih desetletij. Ali epidemijo žarnih pokopov lahko pojasnimo z vplivom vere? 5 Ekološki razlogi. Zakonik cerkvenega prava [13] določa, da »Cerkev zelo priporoča, naj se ohrani pobožna navada pokopavanja teles rajnih, vendar ne prepoveduje sežiganja, razen če je bilo izbrano Človeško telo pri sežigu gori poldrugo uro pri temperaturi okrog 1000 stopinj, v peči, ki se kuri z zemeljskim plinom. Pri tem iz razlogov, ki so nasprotni krščanskemu nauku«. Katoliški gredo v zrak prašni delci, strupeni ogljikov monoksid. Me duhovniki opravijo pogrebni obred in iz mrliške vežice do groba d upepelitvijo človeškega telesa nastane 160, po nekaterih virih pa pospremijo tudi žaro s pepelom pokojnika, vendar pa cerkveni celo več kg tega toplogrednega ogljikovega dioksida. Tu je dokumenti zelo priporočajo pogreb telesa. upoštevan tudi CO2, ki nastane pri zgorevanju plina, ki segreva 304 Muslimani, pravoslavni, evangeličani in Jehovove priče so mi prijazno posredovali vire, podatke in pojasnila; pa tistim, ki so svoja stališča povedali po telefonu ali sporočili po elektronski mi dostop do podatkov omogočili z objavo na spletu pošti. Muslimani, pravoslavni kristjani in judje odločno podpirajo pokop telesa. Pri zavračanju sežiga so najstrožji muslimani, ki ne dovolijo svojim imamom opraviti verskega LITERATURA IN VIRI pogreba, če je telo upepeljeno. Povedna je utemeljitev Islamske skupnosti v RS, da se telesa ne sme poškodovati - ima »svojo [1] T. Arzenšek, N. Šardi, Pogled ljudi na vrsto pokopa umrlega, Raziskovalna naloga, Srednja zdravstvena šola CELJE, 2015 str. 48). svetost in po islamskem nauku je lomljenje kosti umrle osebe kot [2] Prav tam, str. 54 lomljenje kosti žive osebe«. »Tako je«, sem pomislil. Pa ni samo [3] https://www.effs.eu/info-corner.html tako, ampak še bolj tako: nasilje nad truplom je še bolj [4] J. Detela, Klasični pokopi so vse bolj preteklost nesprejemljivo kot nasilje nad živim; da živega udariš ali [5] https://www.camillerifuneraldirectors.com/cremation-in-malta/ [6] Podatki so s spletne strani podjetja Žale. Tudi drugi podatki v tem razdelku so poškoduješ, se v skrajnih primerih še da opravičiti, kaj takega iz spletnih strani posameznih podjetij in občin, iz že omenjenega članka J. Detele v narediti mrtvemu, pa ni predstavljivo, niti opravičljivo. In zelo Večeru, telefonskih pogovorov in spletnega dopisovanja avtorja s posameznimi težko oprostimo tistim, ki so kaj takega naredili našim pokojnim. podjetji in občinami. Pravoslavni ne dovoljujejo duhovnika pri pokopu žare. [7] Zobavnik, M. Pristavec Đogić, Upepeljevanje pokojnikov in sežiganje biološkega materiala, DZRS, 2016 in A. Mernik, Družbeno ekonomski vidiki Opozarjajo, da s pokojnikom sežgemo relikvije morebitnega delovanja upepeljevalnic, Univerza v Mariboru, 2010 svetnika. Odločno pokop telesa podpirajo tudi judje. [8] Peter Žerjavič, Delo, 9.9. 2022 Evangeličanska cerkev AV v RS je do načina pokopa nevtralna. [9] Mari Montse, Domingo José L. Toxic emissions from crematories: A review. Environmental International, 36/2010, str. 131. Nevtralne so tudi Jehovove priče. Ni pa nobene vere, katere [10] In memoriam dr. Lovro Šturm (1938-2021), Družina, 12. decembra 2021. število vernikov bi se približalo odstotku prebivalstva, in bi se [11] A. Bedek, Za zidovi krematorija v Mariboru, 28. 2. 2020, zavzemala ali zahtevala sežig pokojnikov. Vera bi torej vplivala https://vestnik.si/clanek/aktualno/foto-za-zidovi-krematorija-v-mariboru-kjer-so- kvečjemu v nasprotno smer: več pogrebov v edinega-kitajca-za-zdaj-upepelili-z-denarjem-vred-761231 krstah. [12] N.J., Ni za občutljive, https://www.moskisvet.com/zanimivo/ni-za-obcutljive- Je pa ob omembi vere prav omeniti še svobodo vere. Veram je tako-je-videti-upepeljevanje.html način pokopa zelo pomemben. S ceno pokopov, najemov grobov [13] Kan.1176, § 3 in drugimi ukrepi lahko država ali občina vodi politiko pospeševanja enega ali drugega načina pokopa in s tem širi ali oži prostor verske svobode. Posebej pri verah, ki vernikom zelo jasno določajo način pokopavanja, bi favoriziranje enega načina (na primer: odrekanje prostora za klasični grob; odločitev občine, da pogrebi, ki gredo na občinske stroške, ne morejo biti klasični; predpis, da se v tujini umrli domačini lahko pokopljejo doma, vendar samo, če so v žari, …) lahko predstavljalo diskriminacijo na osnovi vere in kršitev pravice do verske svobode. Ko smo že pri pravicah. Pred nedavnim sem izvedel za primer, ko se je desetletja pred osamosvojitvijo po smrti neke osebe pojavil sum na umor in so sum potrdili na osnovi rezultatov naknadne obdukcije. Telo človeka je tudi bogat in dragocen arhiv podatkov. Ob množičnem sprotnem sežiganju teh arhivov marsikdo ne bo mogel do pravice in pravica do marsikoga ne. 8 Sklep. Med različnimi možnimi vzroki torej nismo našli takega, da bi z njim lahko pojasnili tako globoko in tako hitro spremembo večinske kulture. Nasprotno, podatki govorijo bolj v prid klasičnemu pokopu telesa v krsti. Vendar se o prikazanih podatkih ne ve dosti. V medijih ne boste našli tega področja med možnostmi za izboljšanje okolja ali energetsko varčevanje, posebej s plinom. Niti o lomljenju kosti ne boste brali. Raziskav je, kot smo videli, malo. Politična korektnost, proti kateri s tem zapisom grešimo? Iz tega zapisa ne izvemo za prave vzroke, niti za skupine ali osebe, ki stojijo za njimi. Ne glede nanje pa privoščimo sebi in svojim, kar je Prešeren privoščil prijatelju Andreju, namreč v zemlji domači, da truplo leži! Drago Čepar Zahvaljujem se pogrebnim in komunalnim podjetjem, občinam, veleposlaništvom, cerkvam in drugim verskim skupnostim, uradu evropskega poslanca F. Bogoviča in drugim , ki so mi 305 Nekaj primerov demografskega zmanjševanja Examples of demographic schrinking Matjaž Gams Odsek za inteligentne sisteme Institut “Jožef Stefan” Ljubljana, Slovenija matjaz.gams@ijs.si 1 UVOD POVZETEK Predstavljenih je nekaj primerov zmanjševanj prebivalstva v V tem prispevku se ukvarjamo z analizo držav z nizko Južni Koreji, na Japonskem, v Sloveniji itd. v primerjavi z rastjo rodnostjo – kakšne so nekatere značilne oziroma odmevne svetovnega prebivalstva. Vzorec je znan: ob premajhni rodnosti projekcije. Najprej si bomo ogledali svet in nato Južno Korejo in eksponentni naravi demografskih gibanj se število [1](23). Vsakič bomo poleg projekcije dodali še analizo stanja in prebivalstva eksponentno zmanjšuje. Prav tako je znano, kaj perspektiv. Pomembno je razumeti, da gre za eksponentno vpliva na večjo ali manjšo rodnost ali dogajanja ob večji rodnosti. upadanje prebivalstva v mirnem stanju, praktično blagostanju, V zgodovini človeštva pa še nismo imeli zabeleženega široko podobno kot gre pri več kot 2.1 otroka na žensko za eksponentno razširjenega pojava prostovoljnega zmanjševanja prebivalstva, rast, kar je ugotovil že Malthus. Podobno kot v demografiji oz. v nekateri viri celo govorijo o nevarnostih za izumrtje, brisanje živalskem svetu je problem tudi rast obremenitev planeta, ki ni genetskih podskupin, kultur, jezikov in v skrajni meri človeštva. vzdržna, zato je nujna preusmeritev v trajnostno rast Kaj torej lahko ugotovimo z analizo pojava in napovedjo za [2,3,4]( (Meadows 1972, 14, 15, 24). Glede demografije pa - naprej? zgodovinsko gledano strokovnjaki zelo dolgoletne negativne rasti še niso mogli empirično obsežno analizirati, ker takih KLJUČNE BESEDE primerov še ni bilo v moderni človeški zgodovini. Demografski trendi, zmanjševanje prebivalstva, analiza demografskih posledic 2 SVETOVNA POPULACIJA ABSTRACT Demographic events and its consequences are presented for a couple of countries with under-sustainable birth rate, such as South Korea, Japan, Slovenia, etc., compared to the world population growth. Several patterns are established: when the birth rate is too low, the number of inhabitants decreases exponentially. Also, the reasons and mechanisms influencing the birth rate are to a certain extend known. However, there is no report about a country free-willingly decreasing its population and the consequences; there are even dire predictions about potential extinctions of nations, genetic subgroups, cultures and in the worst case even the humanity. Hence, what can be analysed and predicted in this period of time? KEYWORDS Life achievements, science, industry, dictionaries, relevancy Slika 1: Gibanje svetovnega prebivalstva od leta 1000 dalje. Vir: writing in Slovene, add English keywords below the Slovene Populationmatters.org. ones, keyword, keyword, keyword Slika 1 kaže dolgoročno gibanje svetovnega prebivalstva in kaže značilnosti eksponentne rasti. Predvideno gibanje svetovnega prebivalstva je povzeto po: "World Population Prospects: The Permission to make digital or hard copies of part or all of this work for personal or 2022 Revision", objavljeno pri Združenih narodih [5]( (27). Iz 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 grafa na Sliki 1 je očitna osnovna zakonitost - eksponentna rast citation on the first page. Copyrights for third-party components of this work must prebivalstva v zadnjih 100 letih. Taka rast bi slej ko prej be honored. For all other uses, contact the owner/author(s). preplavila planet in uničila okolje, rastlinstvo in živalstvo, planet Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). in človeško civilizacijo. Primer: pri rodnosti 5, kot je bila na svetu v letih 1950-55, bi v 10 generacijah na našem planetu živelo 40.000 milijard ljudi, pri rodnosti 2.5 bi v 13 generacijah 306 prišli na gostoto 1 človeka na m2, pri 40 generacijah pa na 1 predstavljala skoraj polovico celotnega svetovnega prebivalstva človeka na kg Zemlje. Pri rodnosti 2.5 pa bi v 10 generacijah leta 2100. prišli »le« na 40 milijard, in pri 13 generacijah 10x več kot Slika 3 prikazuje demografske piramide za Kitajsko, Italijo in vzačetka [6]( (20). Afriko. Pomembno je opaziti iz slik 2 in 3, da se prebivalstvo hitro povečuje le v Afriki, vse ostale celine v povprečju nazadujejo. Nekaj zanimivih prebivalstvenih piramid si je možno ogledati tudi na »The World's Craziest Population Pyramids« (https://www.youtube.com/watch?v=keUaC-oyXWU). Slika 4 kaže spremembe rodnosti v nekaj največjih državah sveta do 2100. V vseh prikazanih državah je očiten trend velikega padca rodnosti. Na »The Countries With the Lowest Birth Rate in the World« (https://youtu.be/4QwHGBBZB6w) si je možno ogledati najnižje rodnosti držav po svetu v letih. Okoli leta 2002 je med njimi tudi Slovenija z malo nad 1.2. Po tem obdobju je ta demografska konferenca organizirala nekaj dogodkov in obiskov pri najpomembnejših nacionalnih voditeljih in rodnost se je dvignila nad 1.5, kar daje misliti, da je možno povečati rodnost s primernimi ukrepi in pozornostjo vodilnih. Obsežnejše in kvalitetnejše analize avtorja in sodelavcev z metodami umetne inteligence pa so prišle nekaj kasneje [7,8,9](2,4,5) in nato Slika 2: Projekcije števila prebivalcev po kontinentih v letih pripeljale do hipotez o nevarnosti izumiranja malih narodov 2022, 2050 in 2100. Vir: Populationmatters.org. [10,11,12]( (1, 8, 9). Če vse države kažejo na padec rodnosti, zakaj število prebivalstev po svetu narašča? Precej ima s tem opraviti časovni zamik med rodnostjo in dejanskim številom prebivalcev. A na daljše obdobje je ključno, koliko se jih rodi in koliko jih umre. Slika 4: Rodnost v najštevilčnejših državah sveta v 5-letnih obdobjih do 2000, 2020, 2050, 2100. Trajna rodnost je pri 2.1. Vir: Populationmatters.org. Prevelika rast prebivalstva v bližnji zgodovini je sprožila odzive v večini držav sveta. Recimo Kitajska je kar predpisala dovoljeno maksimalno število otrok, enega v mestih in nekaj dodatnih pravil recimo na podeželju, če prvi otrok ni moški, nato dvignila na 2 in 3. Zahodna civilizacija, kamor štejemo ZDA, Kanado, Evropo, Avstralijo in Novo Zelandijo pa nima možnosti Slika 3: Prebivalstvene piramide za Kitajsko, Italijo in Afriko predpisati kaj podobnega, saj v demokraciji formalna omejitev – zaporedoma. Pri tem je levi grafikon za leto 2019 za Kitajsko otrok ni izvedljiva. Zato so začeli razširjati miselnost in vrednote in Italijo, spodnji za Afriko pa 1950. Desno je vedno projekcija preko spletnih omrežij in večinskih medijev, ki so ljudi za 2100. Vir: https://www.populationpyramid.net/. prepričevali, da svojo pozornost usmerjajo v druge smeri, recimo kariero, pridobivanje kapitala, egoistično potrošništvo in Slika 2 prikazuje velikost populacije po kontinentih v letih podobno, pa tudi razkroj družine, ki najbolj učinkovito okolje za 2022, 2050, 2100. Daleč izstopa Afrika, ki bo skupaj z Azijo 307 dosegati večjo rodnost. Posledično je padlo število porok zaskrbljujoč svetovni pojav: upadanje prebivalstva! Posledice [13]( (26), porastle so druge oblike recimo istospolnih porok, ki zmanjševanja prebivalstva v Južni Koreji pa so vse prej kot imajo statistično gledano bistveno nižjo rodnost. Propagiranje enostavne. združenj kot LGBT [14]( (3) je skozi demografski pogled Po projekcijah bo leta 2065 polovica prebivalcev veljala za propagiranje nižje rodnosti. Osnovno zniževanje rodnosti pa »starejšo«, ker bo delež mladih tako upadel. Leta 2017 je bilo le pride preko destrukcije patriarhalne ali verske družine, kjer je 14% starejših kot 65 let. Tudi drugi pokazatelji so problematični: vloga ženske tudi vloga matere, katera poglavitna skrb je imeti 58% moških se ne poroči do 44. leta. Padanje kvalitete življenja in skrbeti za otroke in ne odloča o številu otrok. Način in gospodarstva zaradi prenizke rodnosti je empirično pokazana prepričevanja za oba nivoja destrukcije družine ni točno znan, to [15]( (Sambt 2014 =21 ). Med leti 2016 in 2018 je država je, koliko gre za spontano / emergentno dogajanje in v kolikšni namenila preko 100 milijard dolarjev za povečanje stopnje meri za dirigirano s strani svetovnih elit, ki jih skrbi za rodnosti, a se je padanje nadaljevalo pod magično številko 1 prihodnost človeštva. Morda so v zvezi s tem zanimive izjave (https://asia.nikkei.com/Economy/South-Korea-fertility-rate-at- Billa Gatesa ali Davida Attenborougha »The planet can’t cope new-lows-dipping-below-1.0-threshold) in je sedaj pod 0.9, kar with overpopulation« je absolutni rekord v mirnodobnem času. (https://www.weforum.org/agenda/2018/10/david- Južno Korejo in razviti svet čakajo težki časi, morda pa tudi attenborough-warns-planet-cant-cope-with-overpopulation/). človeško civilizacijo, če se bo tovrstni trend nadaljeval. V Posledice prevelike rodnosti so nesporne, saj bi z rodnostjo Thestreet (https://www.thestreet.com/technology/elon-musk- dejansko preplavili planet, kot opisano malo prej, zato se zdi sounds-a-new-alarm-on-south-korea) Elon Musk opozarja na zniževanje prevelike rodnosti bolj nuja kot možnost za cel planet demografske probleme. Južna Koreja je skupaj z Japonsko ena in za države z veliko rodnostjo. izmed nosilcev tehnološkega svetovnega napredka. Podjetja kot Samsung, Hyundai in LG so globalni velikani. V tvitu je sporočil: »Important. South Korea is currently tracking to lose 3 JUŽNA KOREJA about half its population roughly every generation. Long lifespan Južna Koreja se je v 2022 nekajkrat znašla med svetovnimi hides the dire nature of the problem.” 5.9.2022. V prevodu: Južna novicami. Osnovni razlog je razviden s Slike 5: projekcija Koreja bo v eni generaciji izgubila polovico prebivalcev, kar neverjetno hitrega upadanja prebivalstva [1]( (23). The Korea zamegljuje dolga življenjska doba. Times je objavil, da bo leta 2070 v Južni Koreji le 38 milijonov prebivalcev (NIKKEIAsia; https://asia.nikkei.com/Economy/South-Korean-population-on- cusp-of-steep-decline). Medtem ko bo svetovna populacija rastla, 4 JAPONSKA IN SLOVENIJA se bo v Južni Koreji število prebivalstev začelo eksponentno zmanjševati. 7. maja 2022 je Musk tvitnil, da bo s sedanjo rodnostjo Japonska populacija enostavno nehala obstajati in da bo to ogromna škoda za cel svet. Japonska doživlja podobne probleme »Elon Musk Sounds The Alarm About Japan« (https://www.thestreet.com/technology/elon-musk-sounds-the- alarm-about-japan?dicbo=v2- 6a3286b833840b4355954162bb674199). Po Musku je japonska populacija v 2021 upadla za 644,000 na 125.5 mil. CNN je podobno objavil »Number of children in Japan shrinks to new record low« (https://edition.cnn.com/2018/05/07/health/japan- child-population-record-low-intl/index.html), saj je število otrok upadlo 37 let zaporedoma. Slika 5: Druga projekcija prebivalstva Južne Koreje in primerjava s svetovnim prebivalstvom. Vir: (https://www.koreatimes.co.kr/www/biz/2022/09/602_335593.h tml). Podobne projekcije najdemo v raznih virih, zato ni veliko dvomov, da gre demografsko dogajanje v tej smeri (slika 5). Seveda so možne spremembe v eni ali drugi smeri, recimo jedrska vojna s hitrejšim zmanjševanjem in emigracija, ki bi pokrila primanjkljaj, a potrebno se je zavedati, da bo posebej drugo pomenili zmanjševanje in izginotje korejske genetske podskupine. Morda velja ob tem omeniti, da je Južna Koreja ena izmed tehnološko najbolj razvitih držav sveta in bi izostanek znanosti in razvoja v Južni Koreji pomembno vplival na razvoj Slika 6: Demografske projekcije za Japonsko. Vir: celotnega sveta. Torej ne gre le za lokalna dogajanja, ampak https://www.nippon.com/en/japan-data/h01310/ 308 osebnost, ki ji ljudje načeloma prisluhnejo precej bolj kot Slika 6 prikazuje podobne razmere in perspektive za politikom, ki so začeli širiti ideološke in seksualne konflikte z Japonsko. Tako Japonska kot Južna Koreja se zavedata problema zahtevami, da se moški lahko brez vsakega testa proglasijo za in za rešitev so predlagali precejšnje finančne spodbude. Te moške, da so ženske »osebe, ki lahko rodijo«, uničevanjem spodbude so imele dokaj omejene učinke v drugih državah, zato otroštva [18]( (12) in podobno. Večina prebivalstva kljub so bili nekateri, skupaj z avtorjem tega članka, skeptični. Če si pritiskom preko spleta in medijev tovrstne pojave še vedno vidi pogledate osnovne mehanizme za zmanjševanje populacije, ki so kot nekaj za lase privlečenega in ne vidijo, zakaj se pojavljajo: se izkazali za izredno empirično učinkovite, je dokaj verjetno, da za krotenje rasti prebivalstva. Vseeno se velik del prebivalstva da finančne spodbude ob uveljavljenih načelih razkroja družine itd. naivno prepričati v tovrstne anti-demografske teze. A vseeno ne bodo prinesle ključnih rezultatov. Muskove misli dosežejo precej večji učinek kot od kateregakoli politika. Med drugim ima okoli 100 milijonov sledilcev na Twiterju. Druga pomembna sprememba je, da se tudi svetovne elite počasi začenjajo zavedati, da proces ustavljanja rodnosti po svetu prinaša zelo negativne posledice v precejšnjem delu sveta. Seveda pa je potrebno rast v Afriki še na nek način ustaviti in očitno ti sistemi anti-družinskih vrednost ne dosežejo pravega učinka v Afriki. Ključna meja rodnosti je 2.1, a v 38 razvitih državah članicah OECD je rodnost v povprečju 1.59, kar pomeni izginotje v nekaj sto letih v povprečju. Nekateri strokovnjaki opozarjajo, da bo s tako rodnostjo vrsta držav doživela tako imenovani »age quake«, kar bi lahko prevedli kot starostni ali demografski potres Slika 7: Slovenska rodnost se zadna leta giblje okoli 1.5 [9,20]( (16, 18). oziroma 1.6, kar je še vedno precej premalo oz. pelje v eksponentno izginevanje domorodnih skupin. Vir: https://www.ceicdata.com/en/slovenia/health-statistics/si- REFERENCES fertility-rate-total-births-per-woman. [1] Choi, Y. 2022. A decomposition of declining crude birth rate in South V Sloveniji na videz rodnost ni tako grozljivo slaba kot v Korea, Journal of Population Research volume 39, pages373–389 (2022) Južni Koreji, saj je rodnost 1.5 precej večja kot 0.8. A vse pod [2] Meadows, Donella H; Meadows, Dennis L; Randers, Jørgen; Behrens III, William W (1972). The Limits to Growth; A Report for the Club of 2.1 vodi v eksponentno upadanje in med demografi velja 1.8 za Rome's Project on the Predicament of Mankind (PDF). 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Trije otroci bi nas rešili : demografska gibanja Slovencev. Znanost : štirinajstdnevna znanstvena priloga časnika Delo, razkritje škodljivosti tovrstnih trendov v Sloveniji »blasfemično« 04.10.2007, letn. 49, št. 229, str. 19. in ga je potrebno zatreti. A znanost temelji na tem, da odkriva [13] Melissa S. K., Phillip B. Levine, P. B., and Luke Pardue. 2022. "The dejanske zakonitosti in opozarja na probleme, da se jih lahko Puzzle of Falling US Birth Rates since the Great Recession." Journal of Economic Perspectives, 36 (1): 151-76. Spremenjene vrednote in način pravočasno izognemo. Na svetovnem nivoju se je veliki premik življenja krivi za padce rodnosti v ZDA zgodil šele z Elonom Muskom, ko je začel omenjati demografske [14] Gams, M., Grabnar, J., Vidulin, V. 2013. Vpliv pravic istospolno usmerjenih na stopnjo rodnosti. V: MALAČIČ, Janez (ur.), GAMS, svetovne probleme. Njega se ni dalo »raztrgati« po spletnih Matjaž (ur.). Soočanje z demografskimi izzivi : zbornik 16. mednarodne omrežjih. Poleg tega je Elon Musk najbolj vplivna svetovna multikonference Informacijska družba - IS 2013, 7.-8. oktober 2013, Ljubljana, str. 13-17. 309 [15] Lee, R., Sambt, J., et al. 2014. Is low fertility really a problem?: population aging, dependency, and consumption. Science, ISSN 0036-8075, 10. Oct. 2014, vol. 346, iss. 6206, str. 229-234, doi: 10.1126/science.1250542. [16] Gams, M., J. Malačič, J. (ur.). 2019. Bela knjiga slovenske demografije. http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20demografije%20 DS%202018.pdf [17] Delo 2018, Jozef Stefan Institute does not support scientific theses of Matjaz Gams, in Slovene, https://www.delo.si/novice/slovenija/institut- jozef-stefan-ne-podpira-stalisc-matjaza-gamsa-55676.html [18] Postman, M. 1994. The Disappearance of Childhood, First vintage book edition. [19] Pearce, F. 2008. Peoplequake, Mass Migration, Ageing Nations and the Coming Population Crash, Transworld Publishers. [20] Bricker, D., Ibbitson, J. Empty Planet. 2019. Robintson, UK. 310 Obremenjujoče izkušnje v otroštvu: primerjalna študija med odraslimi otroci alkoholikov in nealkoholikov Adverse Childhood Experiences: A Comparison Study of Adult Children of Alcoholics and Non- Adult Children of Alcoholics Doc. dr. Sara Jerebic, spec. ZDT, doc. dr. Drago Jerebic, spec. ZDT Katedra za zakonsko in družinsko terapijo ter psihologijo in sociologijo religije Teološka fakulteta, Univerza v Ljubljani Ljubljana, Slovenija sara.jerebic@teof.uni-lj.si, drago.jerebic@teof.uni-lj.si POVZETEK* adverse childhood experiences by clients and knowledge of them is Alkohol je v Sloveniji najbolj zlorabljena droga in poleg zdravstvenih particularly important for psychotherapists. A questionnaire about in ekonomskih težav močno zaznamuje medosebne odnose. V adverse experiences in childhood should be included in the medical družinah s prisotnim alkoholom najbolj trpijo otroci, katere posledice history, not only of adult children of alcoholics but also adult children spremljajo v odraslo dobo. V klinični praksi se prepogosto srečujemo of non-alcoholics or of all clients. z odraslimi otroki alkoholikov, ki so doživeli različne obremenjujoče izkušnje v otroštvu in se spopadajo s posledicami na individualni in KEYWORDS sistemski ravni. Temeljni cilj raziskave je bil ugotoviti razlike v Adverse childhood experiences, alcohol, adult children of alcoholics, doživetih obremenjujočih izkušnjah v otroštvu med odraslimi otroci adult children of non-alcoholics, addiction alkoholikov in odraslimi otroci nealkoholikov Rezultati raziskave so pokazali statistično pomembne razlike na vseh postavkah lestvice o obremenjujočih izkušnjah v otroštvu (ACE-IQ). Informacija o doživetih obremenjujočih izkušnjah v otroštvu pri klientih in 1 UVOD poznavanje le-teh je še posebno pomembno za psihoterapevte. Alkohol je v Sloveniji najbolj zlorabljena droga, obenem pa je Vprašalnik o obremenjujočih izkušnjah v otroštvu bi bilo potrebno Slovenija po zdravstvenih posledicah zaradi alkohola nad povprečjem vključiti v anamnezo, ne samo odraslih otrok alkoholikov, temveč tudi Evropske unije. Poleg zdravstvenih in ekonomskih težav alkohol odraslih otrok nealkoholikov oz. vseh klientov. močno zaznamuje medosebne in družinske odnose [1, 2]. Otroci, ki odraščajo v družinah s prisotnim alkoholom, se spopadajo s številnimi KLJUČNE BESEDE dolgoročnimi posledicami, ki jih spremljajo v odraslo dobo in odnose, ki jih ustvarjajo [3]. Za tiste posameznike, ki so odraščali v Obremenjujoče izkušnje v otroštvu, alkohol, odrasli otroci nefunkcionalni družini, kjer je bil prisoten alkohol, se v strokovni alkoholikov, odrasli otroci nealkoholikov, zasvojenost literaturi uporablja izraz odrasli otroci alkoholikov [4]. Vsi odrasli otroci alkoholikov ne doživljajo enakih težav, imajo pa mnogo ABSTRACT skupnih značilnosti. Te se ne nanašajo samo na odnos do alkohola, Alcohol is the most abused drug in Slovenia and, in addition to health temveč tudi na doživljanje, izražanje in reguliranje čustev [5]. Številne and economic problems, strongly affects interpersonal relationships. raziskave so pokazale statistično pomembne razlike med odraslimi In families struggling with alcohol abuse, children are those who otroci alkoholikov in odraslimi otroci nealkoholikov na področjih suffer the most, the consequences of which follow them into težav v odnosih [6] zlorabe substanc [7] in zanikanja [8]. Odrasli adulthood. In clinical practice, we too often encounter adult children otroci alkoholikov so bolj izpostavljeni ranljivosti pred stresorji in of alcoholics who have experienced various troublesome events in imajo večje prilagoditvene težave [9]. Prisotne je tudi več childhood and are struggling with the consequences on an individual psihopatologije [10] in slabe samopodobe za razliko od odraslih otrok and systemic level. The primary goal of the research was to determine nealkoholikov [11]. Kot otroci so se ob nekontroliranem pitju staršev differences in adverse childhood experiences between adult children počutili nemočne ali prestrašene. S skrbjo za starše pa so si pridobili of alcoholics (and adult children of non-alcoholics. The results of the občutek nadzora v sicer neobvladljivi situaciji, katere ni bilo možno survey showed statistically significant differences on all items of the nadzirati [12]. Ko odrastejo se to kaže v njihovi potrebi po nadzoru adverse childhood experiences scale (ACE-IQ). Information about nad drugimi, spopadanju z zavrženostjo in zapuščenostjo, ki rezultira * Doseženi rezultati so nastali v okviru projekta št. J5-2570, ki ga je financirala Javna agencija za raziskovalno dejavnost Republike Slovenije iz državnega proračuna. 311 v močnih občutkih sramu. Skušajo nadzirati tisto, česar se dejansko ne v otroštvu med odraslimi otroci alkoholikov in odraslimi otrodi da, druge osebe, obenem pa se veliko ukvarjajo s tem kaj si bodo drugi nealkoholikov. mislili o njih. Zaradi občutka nepripadnosti se počutijo manjvredne, kar lahko prikrivajo z mnogimi vlogami kot je pretirano odgovorna 2 METODA oseba ali perfekcionist. V partnerske odnose lahko vstopajo z osebami, 2.1 Udeleženci za katere imajo občutek, da jim lahko pomagajo, saj zamenjujejo V celotni raziskavi je sodelovalo 619 anketirank in anketriancev. V ljubezen z usmiljenjem [13]. V strokovni literaturi se v povezavi z analizo je bil vključen ustrezen vzorec zato je pri posameznih zasvojenostjo enega izmed staršev, kjer je drug starš s svojimi vedenji vprašanjih lahko vzorec nekoliko nižji a še vedno ustrezen. Moških je zavedno in nezavedno podpiral partnerjevo zasvojenost, uporablja bilo v vzorcu 27 odstokov, žensk 73 odstotkov (N=619). Večina izraz »soodvisnost« (ang. Codependency). Kaže se v čustvenem in anketirancev je starih med 21 in 30 let (34,4 %), sledijo stari med 31 vedenjskem vzorcu interaktivnega obvladovanja, kar izhaja iz in 40 let (18,2 %) ter stari med 41 in 50 let (18,0 %). Nad 51 let je dolgotrajne izpostavljenosti omejevalnemu okolju, ki ne dovoljuje odkritega ali neposrednega izražanja čustev do sebe ali drugih starih 17,4 odstodka anketirancev. Pod 20 let pa 12,0 odstotkov anketirancev. Večina anketiran družinskih članov cev je zaposlenih (42,7 %), sledijo [14]. Otrok je med staršema vzpostavljal most študentje (35,4 %). Brezposelnih anketirancev je 8,0 odstokov, 11,0 komunikacije in odigraval vlogo čustvenega starša, navadno odstotkov je upokojenih. Največ anketirancev je partnerski zvezi a so nezasvojenemu staršu oz. s svojo skrbjo za oba starša ohranjal neporočeni (32,2 %). 30,1 odstokov je poročenih, sledijo samski (29,2 čustveno ravnovesje v družini. Empirična raziskava s sistemske %). Velika večina anketirancev pripada katoliški veri (79,8 %). 14,3 perspektive je pokazala, da so bili udeleženci iz skupine z višjo stopnjo odstotka anketirancev ne pripada nobeni veri. Večina anketirancev ni soodvisnosti, v otroštvu priče zlorabljanju alkohola s strani staršev, v otrok alkoholika (57,5 %). Prav tako jih večina ni nikoli nevarno odraslem odnosu pa so se osebe z izraženo višjo stopnjo soodvistnosti, pogosteje znašle v odraslem intimnem odnosu z zasvojenim uporabljala alkohol (72,0 %) in pri njih ni prisotna odvisnost od alkohola (88,7 %). Nizko stopnjo ocene tveganja in škodljivo rabo partnerjem [15]. V klinični praksi se je pokazalo, da pari, od katerih je odvisnosti dosega v obeh primerih 71,3 odstotka anketirancev. Večina eden izmed partnerjev odrasel otrok alkoholika, pogosto poiščejo anketirancev tudi ni iskala, trenutno ali v preteklosti, pomoči zaradi terapevtsko pomoč prav zaradi tovrstnih zapletov v partnerskem zasvojenosti (81,0 %). Med tistimi za katere anketiranci menijo, da je odnosu. imel v družini težave je odgovor »le oče« dosegel 39,2 odstotka, mama Odraščanje v družini, kjer je bil eden izmed staršev ali morda celo oba (4,9 %) in oba starša (4,9 %). Da so živeli v skupnem gospodinjstvu zasvojena z alkoholom, pa povečuje tveganje za različne živeli s članom, ki je bil problematičen pivec ali alkoholik oziroma obremenjujoče izkušnje v otroštvu [16]. Obremenjujoče izkušnje so uporabnik prepovedanih ali dovoljenih drog je odgovorili 62,9 med drugim opredeljene kot različne vrste nasilja in sicer spolno, odstodka anketirancev. 76,6 odstodka anketirancev je živelo v fizično in psihično nasilje ter izpostavljenost nefunkcionalnemu skupnem gospodinjstvu s članom, ki je bil depresiven, duševno bolan družinskemu okolju [17]. Poleg presejalnega testa odraslih otrok ali nagnjen k samomoru. Pri 27,1 odstotka anketiranih so se starši alkoholikov smo se v raziskavi osredotočili na pet obremenjujočih razvezali ali kdaj živeli ločeno. Pri 24,0 je mama, oče ali skrbnik umrl. izkušenj v otroštvu, katere opisujemo v nadaljevanju: - čustveno zanemarjanje, ki se nanaša na neprepoznavanje in 2.2 Pripomočki nezadovoljevanje čustvenih potreb otroka; Za namen raziskave je bil ustvarjen sklop vprašalnikov. Poleg - fizično zanemarjanje, ki se nanaša na neprepoznavanje in demografskih vprašanj na začetku so udeleženci izpolnili še dva nezadovoljevanje fizičnih potreb otroka (npr. potreba po samoocenjevalna merska inštrumenta: hrani); - čustveno zlorabo, ki se nanaša na verbalni vzorec zlorabe Presejalni test otrok alkoholikov (Children of Alcoholics Screening (npr. kričanje, žaljenje, poniževanje); test CAST-6) [20, 21]. Sestavljen je iz šestih postavk, ki se navezujejo na posameznikove občutke, izkušnje in obnašanje, povezane s pitjem - fizično zlorabo, ki se nanaša na fizično nasilje nad otrokom (npr. klofutanje, brcanje, šeškanje, udarjanje s predmeti); staršev in omogoča možnost odkrivanja ali je anketiranec otrok - spolno zlorabo, ki se nanaša na spolna dejanja nad otrokom alkoholika. (npr. prisilno občevanje, siljenje v občevanje, dotikanje) Mednarodni vprašalnik o obremenjujočih izkušnjah v otroštvu (ang. - družinsko nasilje nad drugim članom družine [18]. Adverse Childhood Experiences International Questionnaire – ACE- IQ) vsebuje trditve, ki se navezujejo na obremenjujoče izkušnje iz V Sloveniji je bila prva reprezentativna raziskava o obremenjujočih otroštva. Vprašalnik identificira 13 kategorij obremenjujočih izkušenj izkušnjah v otroštvu izvedena leta 2019 na vzorcu 4940 odraslih v otroštvu, od katerih smo v našo raziskavo vključili šest naslednjih: oposameznikov. Med najpogostejšimi obremenjujočimi izkušnjami so čustveno zlorabo v družini, fizično zlorabo v družini, spolno zlorabo, navajali čustveno nasilje (55,4%) in telesno nasilje (42,7). 67% tistih, doživljanje nasilja nad drugim družinskim članom, čustveno ki so poročali o čustvenem nasilju, pa je poročalo tudi o fizičnem zanemarjanje, fizično zanemarjanje. Nižji rezultat pomeni večjo nasilju. Čustveno zanemarjanje je doživelo 25% udeležencev, fizično pogostost posamezne izkušnje v otroštvu [18]. Koeficient zanemarjanje 24,2% udeležencev. Fizično nasilje med odraslimi člani zanesljivosti (Cronbachov alfa) v naši raziskavi znaša za spolno gospodinjstva je doživelo 16,2% udeležencev. 6% anketirancev je zlorabo ɑ=0,929; za čustveno zanemarjanje ɑ=0,735; za fizično doživelo spolno zlorabo, ob odraslem članu gospodinjstva, ki je bil zanemarjanje ɑ=0,591; za družinsko nasilje ɑ=0,724; za psihično zasvojen, pa je odraščalo 21,1% udeležencev. V raziskavi so poročali nasilje ɑ=0,669; za fizično zlorabo ɑ=0,677. tudi o težavah v duševnem zdravju odraslega člana gospodinjstva, vključno s samomorom (13%), o kriminalnem dejanju odraslega člana gospodinjstva (3,3) in o izgubah/zapustitvah/razvezah staršev (30,4%) 2.3 Postopek [19]. Povezavo do vprašalnikov smo objavili na različnih spletnih straneh, V navedeni raziskavi niso ugotavljali razlik med odraslimi otroci forumih in spletnih omrežjih, anketiranci pa so vprašalnike alkoholikov in nealkoholikov, zato se je pojavila potreba po nadaljnem raziskovanju. Z raziskavo smo želeli izpolnjevali tudi v pisni obliki na eni izmed ustanov za zdravljenje zapolniti vrzel in odvisnosti od alkohola. Izpolnjevalnje vprašalnikov je potekalo preveriti ali se pojavljajo razlike v doživetih obremenjujočih izkušnjah 312 pomladi 2021 do pomladi 2022. Pridobljene statistične podatke smo družinskim članom, čustvenem in fizičnem zanemarjanju. Naši obdelali s statističnim programom SPSS 20. rezultati se skladajo z ugotovitvami tujih raziskav, kjer so odrasli otroci alkoholikov retrospektivno poročali o fizičnem in psihičnem 3 REZULTATI zanemarjanju, družinskem nasilju, ki so ga doživeli med staršema in fizičnem nasilju nad njimi s strani staršev [22, 23]. Raziskave pa so Zanimalo nas je ali se pojavljajo razlike v zanemarjanju in nasilju pokazale tudi večjo verjetnost za spolno zlorabo [24, 25], saj je ACE-IQ lestvice glede na to ali so anketiranci kot otroci odraščali z družinsko okolje pomemben dejavnik tveganja. Otroci kjer sta eden alkoholikom. Podatki niso bili normalno porazdeljeni zato smo analizo izvedli z neparametričnim testom Mann ali oba starša zasvojena z alkoholom, so prikrajšani za zdravo -Whitney, ki ga uporabimo kadar želimo ugotov odraščanje, obenem pa so izpostavljeni večjemu tveganju za različne iti razlike med dvema neodvisnima skupina. Rezultati analize so pokazali, da se statistično vrste zlorab. Raziskave so pokazale, da je pri spolnih zlorabah v pomembne razlike pojavljajo pri vseh oblikah zanemarjanja (čustveno in fizično) otroštvu družinsko okolje pomemben dejavnik tveganja [26]. Pri in nasilja (družinsko, psihično, fizično, spolna zloraba). Statistična posameznikih, ki so doživeli spolno zlorabo v otroštvu in njihovih intimnih partnerjih v odrasli dobi, obstaja statistično pomembna pomembnost je pri vseh dimenzijah pod 0,05. Povprečja rangov so prav tako višja pri vseh oblikah zanemarjanja in nasilja pri razlika v doživljanju fizične oz. spolne varnosti, za razliko od parov, kjer nihče v paru ni doživel spolne zlorabe [27]. Doživeta spolna anketirancih, ki kot otroci niso odraščali ob alkoholiku. zloraba v otroštvu tako predstavlja posledice za intimne odrasle partnerske odnose, kar se med drugim odraža tudi v spolni anoreksiji. Tabela 1: Razlike v obremenjujočih izkušnjah v otroštvu [28]. Odpor do spolnosti in izogibanje spolnosti lahko povezujemo otrok alkoholika N Povprečje Vsota tudi z zmanjševanjem števila rojstev. V Slovenski raziskavi se je ranga ranga izkazalo tudi, da obremenjujoče izkušnje v otroštvu lahko prispevajo k poskusu samomora pri odraslih otrocih alkoholikov, ugotovljena pa čustveno_zanemarjan Ne 275 283,15 je bila tudi pozitivna povezava med čustvenim zanemarjanjem in je občutkom, da je oseba drugim v breme [29]. Teža posledic Da 213 194,60 0,000 obremenjujočih izkušenj v otroštvu pa se povezuje tudi s slabšo Skupa 488 delovno zmožnostjo. Udeleženci so poročali o težavah v službi, j finančnih težavah in pogostim odhodom v bolniški stalež, prav tako fizično_zanemarjanje Ne 272 279,86 so dosegali nizke rezultate na lestvici zdravja in dobrega počutja [30]. Slabo zdravstveno stanje bi lahko povezali z umrljivostjo, obenem pa Da 209 190,42 slabša delovna zmožnost prispeva 0,000 tudi k omejeni ponudbi delovne sile kar lahko postane omejitveni dejavnik gospodarske rasti. Na eni strani Skupa 481 manjše število delovno aktivnih omejuje vire financiranja, na drugi j družinsko_nasilje strani pa podaljšani bolniški staleži povečujejo pritisk na javnofinačne Ne 271 290,95 izdatke [31], zaradi česar je potrebno ustezno pristopiti k Da 209 175,08 demografskim spremembam in njihovim ekonomskim in 0,000 zdravstvenim posledicam. Skupa 480 Prednost raziskave predstavlja raznolikost udeležencev, kot j pomankljivost izpostavljamo vzorec, ki ni reprezentativen in ne ravno psihično_nasilje Ne 270 281,99 visoka zanesljivost za podlestvico fizičnega zanemarjanja. Da 209 185,75 V nadaljnih raziskavah bi bilo potrebno ne reprezentativnem vzorcu 0,000 udeležence povprašati ali so doživeli incest oz. spolno zlorabo znotraj Skupa 479 ali zunaj družinskega kroga in ugotoviti razlike pri odraslih otrocih j alkoholikov in sicer glede na to kdo je imel težave z alkoholom – oče, fizična_zloraba Ne 271 271,54 mama ali oba starša in kako se tovrstve razlike kažejo tudi v ostalih obremenjujočih izkušnjah v otroštvu in v povezavi z razlikami glede Da 209 200,26 0,000 na spol. Zgodnejše informacije o obremenjujočih izkušnjah v otroštvu Skupa 480 bi koristile družinskim terapevtom pri načrtovanju terapevtske j obravnave, predvsem pa bi lahko s čimprejšnim ustreznim spolna_zloraba Ne 267 247,70 zdravljenjem preprečili mnogotere težave v mladostništvu in odrasli dobi, predvsem na področju ekonomskih in zdravstvenih posledic. Da 207 224,35 0,000 Vprašalnik o obremenjujočih izkušnjah v otroštvu bi bilo potrebno Skupa 474 vključiti v anamnezo, ne samo odraslih otrok alkoholikov, temveč tudi j odraslih otrok nealkoholikov oz. vseh klientov. Vsi strokovnjaki, ki se ukvarjajo z duševnim zdravjem oz. se pri svojem delu srečujejo z odraslimi otroci alkoholikov ali odraslimi, ki so v otroštvu doživeli obremenjujoče izkušnje, bi morali pridobiti ustrezno znanje s področja 4. RAZPRAVA IN SKLEP razumevanja dinamike družinskih odnosov in posledic odraščanja ob Naši rezultati potrjujejo hipotezo v kateri smo predvidevali statistično starših, zasvojenih z alkoholom. pomembne razlike med odraslimi otroci alkoholikov in odraslimi otroci nealkoholikov v doživetih obremenjujočih izkušnjah v otroštvu. Nižji rezultat pri vseh oblikah zanemarjanja, fizičnega in spolnega REFERENCE nasilja pri odraslih otrocih alkoholikov, kaže na večjo pogostost posamezne izkušnje v otroštvu. Odrasli otroci alkoholikov so tako do [1] Rehm, J., Shield, KD, Rehm, MX, Gmel, G., Frick, U. Alcohol consumption, dopolnjenega 18. leta starosti pogosteje poročali o čustveni in fizični alcohol dependence and attributable burden of disease in Europe: potential gains from effective interventions for alcoholdependence. 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Relevanca znanosti in izobraževanja : zbornik povzetkov 314 Razlike v predpisovanju zdravil v obdobju pred in med pandemijo bolezni COVID-19 Differences in prescribing of medicines before and during the COVID-19 pandemic Karin Kasesnik SPC NIJZ Ljubljana, Slovenija karin.kasesnik@nijz.s POVZETEK 1 UVOD Obsežne zdravstvene, ekonomske, socialne in demografske Pandemija koronavirusne bolezni 2019 (COVID-19) ima posledice so povezane s pandemijo koronavirusne bolezni 2019 obsežne zdravstvene, ekonomske, socialne in demografske (COVID-19), ki jo je Svetovna zdravstvena organizacija posledice v globalnem merilu. Razvidna je bila presežna razglasila 11. marca 2020. Zdravstvene posledice bolezni se umrljivost, zaradi pandemije so tudi v bodoče možne kažejo v preko 600 milijonov potrjenih primerih bolezni, zaradi demografske spremembe. Raziskovalci [1] so ugotovili, da je posledic bolezni COVID-19 je v globalnem merilu umrlo že lahko anksioznost, ki izhaja iz pandemije, v veliki meri odvisna okrog 6,5 milijona oseb. Zaradi spremenjenih pogojev ter načina od demografskih in zdravstvenih značilnosti. Predvsem starejši življenja in vedenja prebivalcev so bile pričakovane tudi razlike mladostniki in osebe z nižjimi prihodki so bili posebej v predpisovanju zdravil na recept. Pregled podatkov za Slovenijo zaskrbljeni zaradi dolgotrajnih posledic pandemije, osebe s je pokazal, da se predpisovanje zdravil iz večine glavnih skupin kroničnimi boleznimi pa zaradi same bolezni. Zaradi številnih anatomsko-terapevtsko-kemične (ATC) klasifikacije med zdravstvenih obravnav oziroma hospitalizacij pacientov so bili letoma 2019 in 2020 ni bistveno spremenilo. V dveh letih obremenjeni celotni zdravstveni sistemi. Na osnovi zasedenosti pandemije se je glede na predhodni leti znatno zmanjšal obseg določenih zdravstvenih ustanov je zagotovitev ustreznih predpisovanja zdravil iz ATC skupine J, zdravil za sistemsko zdravstvenih storitev za vse paciente predstavljala velik izziv. zdravljenje infekcij, kar se pripisuje vzdrževanju fizične razdalje Poleg številnih oseb z blažjim potekom bolezni je v obdobju in upoštevanju higienskih ukrepov. pandemije določen delež oseb izkusil resen potek bolezni, tudi s smrtnim izzidom. Konec leta 2020 so bila uvedena cepiva, KLJUČNE BESEDE namenjena doseganju imunosti proti bolezni. Določena zdravila Predpisovanje zdravil, pandemija, COVID-19, ATC so namenjena zdravljenju simptomov bolezni COVID-19, klasifikacija, cepiva, monoklonska protitelesa posebej resnejših simptomov. Ta prispevek je osredotočen na razlike v predpisovanju zdravil v ABSTRACT letih pred pandemijo bolezni COVID-19 in v letih pandemije, Extensive health, economic, social and demographic glede na posamezne ATC skupine zdravil. implications have been related to the coronavirus disease 2019 (COVID-19) pandemic, declared by the World Health 2. POVZROČITELJ, PREPREČEVANJE IN Organization on March 11, 2020. Health implications have been ZDRAVLJENJE BOLEZNI COVID-19 shown in over 600 million of confirmed disease cases, 6,5 million persons have died due to the impact of the COVID-19 2.1 Osnovni podatki o zbolevnosti in umrljivosti globally. Because of the changed conditions and way of life and zaradi bolezni COVID-19 ter o uporabljenih behaviour of the inhabitants also the differences in prescribing of odmerkih cepiva medicines have been expected. Review of the Slovene data has shown that prescribing of medicines from a majority of the main Povzročitelj bolezni COVID-19 je virus SARS-Cov-2 [1]. Kot groups of the Anatomical Therapeutic Chemical (ATC) vsi virusi se tudi virus SARS-Cov-2 tekom časa spreminja. classification hasn’t changed essentially between 2019 and 2020. Večina sprememb nima, ali ima le malo vpliva na lastnosti In two year pandemic periods, a scale of prescribing of medicines virusa. Določene spremembe pa lahko vplivajo na lastnost virusa from the ATC group J with antiinfectives for systemic use has in povezano širjenje okužbe, resnost poteka bolezni ter significantly decreased, in comparison with the previous two preventivne in druge zdravstvene in socialne ukrepe. years, assigned to maintaining the physical distance and to a Novejši podatki (iz prve polovice septembra 2022) kažejo [3] consideration of the hygienic measures. skupno 603.711.760 potrjenih primerov bolezni COVID-19, umrlo je 6.484.136 oseb. Še vedno je razviden trend rasti, tako KEYWORDS glede števila potrjenih primerov bolezni, kot tudi števila umrlih Prescribing of medicines, pandemic, COVID-19, ATC oseb. Glede na regije, opredeljene skladno s Svetovno classification, vaccines, monoclonal antibodies zdravstveno organizacijo (SZO, World Health Organization, 315 WHO), je bilo primerjalno največ primerov zaznanih v Evropi simptomi bolezni COVID-19, pri katerih je zdravljenje (249.105.808), sledi področje Severne in Južne Amerike indicirano [9]. Uvedena je bila farmacevtska oblika s (176.342.137). V Sloveniji je bilo evidentiranih 1.136.236 kombinacijo zdravilnih učinkovin kasirivimab in imdevimab, primerov bolezni COVID-19 [4], 8.161 oseb je zaradi posledic dveh monoklonskih protiteles, ki z vezavo na dve različni mesti bolezni umrlo. na beljakovini bodice virusa SARS-CoV-2 virusu preprečita Podatki [4] o številu oseb, ki so bile polno cepljene, kažejo vstop v telesne celice. Učinkovine, ki jih vsebujejo zdravila za vrednost 62,84 na 100 prebivalcev v globalnem merilu; celotno zdravljenje, oziroma za profilakso bolezni, so tudi tiksagevimab, število odmerkov na 100 prebivalcev je bilo 160,88. V Sloveniji sotrovimab, molnupiravir, remdesivir, regdanvimab. je bilo polno cepljenih 57,46 oseb na 100 prebivalcev, celotno število odmerkov cepiva na 100 prebivalcev pa je znašalo 141,3. 3. RAZLIKE V PREDPISOVANJU ZDRAVIL V LETIH 2020 IN 2021, GLEDE NA 2018 in 2019 2.2 Preprečevanje in zdravljenje bolezni Na osnovi pregleda podatkov so izhajale ugotovitve o povečanju 2.2.1. Cepiva ali zmanjšanju predpisovanja zdravil iz več ATC skupin, med leti 2018 in 2021. V ATC klasifikacijskem sistemu so zdravila razvrščena v različne skupine Cepiva in specifični imunoglobulini so opredeljeni [5] kot visoko [10]. Merilo za razvrščanje so regulirani celostni biološki pripravki mesto delovanja, terapevtske lastnosti in kemične lastnosti. Prva . Učinkovito in varno ustvarjajo zaščitni imunski odziv na okužbo pri cepljeni osebi. raven obsega 14 glavnih, anatomskih skupin. Sledijo skupine in Tekom registracije regulatorne ustanove presojajo in izdajo podskupine glede na terapevtsko, farmakološko oziroma kemično razvrstitev. Zadnjo, peto raven predstavlja učinkovina dovoljenje po potrjeni varnosti in učinkovitosti cepiv. Tudi v času (mednarodno nezaščiteno ime uporabe cepiv se spremljata učinkovitost in varnost cepiv. , International Nonproprietary Cepiva proti bolezni COVID-19 delujejo kot mRNK oziroma Name, INN). Celotno ATC oznako vsakega zdravila sestavlja vektorska cepiva [6]. Vsebujejo navodila za celice organizma, kombinacija sedmih številčnih in črkovnih znakov. kako naj tvorijo antigensko beljakovino. Navodila so v obliki molekule, ki se imenuje sporočilna ribonukleinska kislina 3.1 Metode (mRNK), oziroma v obliki genetskega zapisa v neškodljivem Pregled predpisovanja zdravil je temeljil na podatkih Zavoda za vektorskem oziroma prenašalnem virusu, ki je spremenjen tako, da ne povzroča bolezni. Določene celice cepljene osebe zdravstveno zavarovanje Slovenije (ZZZS), za leti pred preberejo navodila in krajši čas proizvajajo antigensko pandemijo bolezni COVID-19 (2018 in 2019) in za leti 2020 in 2021, v času pandemije. SZO je razglasila izbruh bolezni kot beljakovino. Imunski sistem organizma proti antigenski javnozdravstvene izredne razmere v mednarodnem obsegu 30. beljakovini ustvarja protitelesa. januarja 2020 in pandemijo 11. marca 2020 [11]. Predpisovanje zdravil je prikazano glede na ATC klasifikacijo 2.2.2. Monoklonska protitelesa zdravil. Razlike v predpisovanju zdravil so razvidne glede na število škatel, število receptov in število definiranih dnevnih Za zdravljenje so bila uvedena zdravila proti bolezni COVID-19, odmerkov ( Defined Daily Dose, DDD). V uporabljeni tabeli ki olajšajo predvsem resen potek bolezni. ‘Receptna lista’ [12] so zajeti podatki o številu škatel, številu Monoklonska protitelesa se uporabljajo za spopad organizma z DDD, številu DID, številu predpisanih receptov, celotni okužbo. Pomagajo lahko v primeru visokega tveganja za resne vrednosti receptov, in vrednosti osnovnega zdravstvenega simptome ali hospitalizacijo [7]. Zdravljenje s protitelesi ne zavarovanja (OZZ) za posamezno zdravilo predpisano na recept nadomesti potrebe po ustvarjanju imunosti, ki jo dajejo cepiva; a v breme OZZ po ATC skupinah. po dajanju cepiv traja določen čas, da se razvije dovolj protiteles proti virusu. Večje tveganje za razvoj bolezni COVID-19 obstaja 3.2 Rezultati pri starejših osebah oziroma pri osebah z zdravstvenimi stanji kot so kronična obstruktivna pljučna bolezen, bolezni srca oziroma 3.2.1. Razlike v predpisanih zdravilih v letu pred pandemijo in v oslabljen imunski sistem [8]. Cepljenje je učinkovit preventivni letu začetka pandemije bolezni COVID-19 ukrep. Vendar nekaterim cepljenim osebam, posebej starejšim od 65 let oziroma osebam z drugimi dejavniki tveganja za razvoj Pri primerjavi rezultatov o predpisovanju zdravil med leti 2019 resnega poteka bolezni, lahko koristi zdravljenje. O ustreznosti in 2020 lahko ugotovimo, da se pri zdravilih iz večine glavnih in načinu zdravljenja odloča zdravnik. V ZDA je Urad za hrano ATC skupin predpisovanje zdravil, izraženo v številu škatel, v in zdravila (F ood and Drug Administration, FDA) odobril odsotnem deležu ni bistveno spremenilo [12]. Povečan obseg določena antivirusna zdravila oziroma monoklonska protitelesa predpisovanja med 2019 in 2020 je razviden pri ATC skupinah za zdravljenje oseb, pri katerih je resen potek bolezni bolj A, B, H, L, N, V. V manjši meri pa so se v 2020, glede na 2019, verjeten. Cilj antivirusnega zdravljenja je zaustavitev predpisovala zdravila iz ATC skupin C, D, G, J, M, P, R, S razmnoževanja virusa v organizmu. Monoklonska protitelesa (Tabela 1). Primerjalno največ škatel zdravil je bilo predpisanih pomagajo imunskemu sistemu, da razpozna in bolj učinkovito v okviru zdravil za bolezni srca in ožilja, ki tvorijo ATC skupino odgovori na virus. C. Zdravila za bolezni srca in ožilja se v veliki meri kot kronično Tudi v Sloveniji so razpoložljiva nekatera zdravila za paciente s zdravljenje predpisujejo starejšim osebam. Čeprav v odstotnem 316 deležu zmanjšanje predpisovanja med 2019 in 2020 ni bilo veliko Znatno odstotno zmanjšanje v številu škatel predpisanih zdravil (1,92 %), pa v številu škatel to pomeni preko 233 tisoč. je bilo med letoma 2019 in 2020 [12] razvidno pri ATC skupini D (za 10,87 %), predvsem pa pri ATC skupini J (za 22,38 %). Tabela 1: Število predpisanih škatel zdravil, po posameznih ATC skupinah, 2019 in 2020 (ZZZS, 2022 [12]) 3.2.2. Zmanjšanje predpisovanja zdravil iz ATC skupine D in ATC skupine J, med leti 2018-2019 in 2020-2021 ATC klasifikacija Število Število Razlika v zdravil: predpisanih predpisanih predpisanih Tabela 2: Število škatel predpisanih zdravil in število receptov z glavne skupine škatel škatel škatlah zdravili iz ATC skupine D in J, 2018-2021 zdravil, zdravil, zdravil, 2019 2020 2019 – 2020 ATC skupini Leto Število Število Rp (%; število škatel škatel) D 2018 752.611 482.233 A – Zdravila za 5.697.001 5.706.633 + 0,17 % Zdravila za 2019 748.077 484.734 bolezni prebavil (9.632) bolezni kože in 2020 666.786 438.138 in presnove podkožnega tkiva 2021 686.315 455.316 B – Zdravila za 1.665.302 1.674.544 + 0,55 % J 2018 1.442.610 1.026.236 bolezni krvi in (9.242) krvotvornih Zdravila za 2019 1.429.694 1.014.217 organov sistemsko zdravljenje 2020 1.109.677 783.300 C – Zdravila za 12.121.499 11.888.342 - 1,92 % infekcij 2021 1.096.573 780.084 bolezni srca in (233.157) V okviru ATC skupine D, ki zajema zdravila za bolezni kože in ožilja podkožnega tkiva, je v 2018 in 2019 razviden podoben obseg D – Zdravila za 748.077 666.786 - 10,87 % predpisovanja zdravil [12]. Predpisovanje zdravil iz skupine D bolezni kože in (81.291) pa je bilo v 2020 in 2021 primerjalno manjše. Zmanjšanje podkožnega tkiva predpisovanja zdravil je bilo razvidno pri upoštevanju števila G – Zdravila za 1.929.503 1.886.508 - 2,23 % škatel in števila receptov. bolezni sečil in (42.995) Prav tako je bilo predpisovanje zdravil za sistemsko zdravljenje spolovil ter spolni infekcij, ki sodijo v ATC skupino J, v letih 2021 in 2020 manjše hormoni od predpisovanja zdravil v 2018 in 2019 [12], če upoštevamo H – Hormonska 960.441 1.007.928 + 4,94 % število škatel, število receptov, oziroma število definiranih zdravila za (47.487) dnevnih odmerkov (DDD). V 2018 je bilo v ATC skupini J sistemsko predpisanih 9.406.517 DDD, v 2019 pa 9.397.850 DDD, kar je zdravljenje – več kot leta 2020 in leta 2021 (7.479.037 oziroma 7.398.997). razen spolnih hormonov in insulinov 4. RAZPRAVA J – Zdravila za 1.429.694 1.109.677 - 22,38 % sistemsko (320.017) Na letni ravni je v Sloveniji v 2020, letu razglasitve pandemije, zdravljenje glede na 2019 pri večini ATC skupinah zdravil razviden infekcij podoben obseg predpisovanja zdravil, z določenimi odstopanji. L – Zdravila z 393.292 406.286 + 3,30 % Pri določenih ATC skupinah je predpisovanje zdravil v dveh letih delovanjem na (12.994) pandemije znatno odstopalo od predpisovanja v prejšnjih dveh novotvorbe in letih oziroma pričakovanih vrednosti. imunomodulatorji Raziskovalci [13] so opazovali podrobne razlike pri izdaji M – Zdravila za 1.883.524 1.778.089 - 5,60 % zdravil, ki sovpadajo z dogodki in ukrepi v prvi polovici leta bolezni mišično- (105.435) 2020 na Švedskem. Razlike v obsegu izdaje predpisanih zdravil, skeletnega sistema glede na predviden vzorec izdaje zdravil, so opazili v delu N – Zdravila z 8.388.477 8.444.636 + 0,67 % meseca februarja in marca 2020, ko se je izdaja zdravil delovanjem na (56.159) signifikantno povečala, v različnih starostnih skupinah, pri obeh živčevje spolih in v različnih okoljih. Prav tako se je v tem obdobju znatno P – Antiparazitiki, 91.980 84.758 - 7,85 % povečala prodaja zdravil brez recepta. Največji obseg izdaje insekticidi in (7.222) zdravil so opazili v tednu, ki se je začel 11. marca 2020, kar je repelenti skladno z objavo SZO o pandemiji. Kmalu nato je sledilo R – Zdravila za 1.929.627 1.876.975 - 2,73 % zmanjšanje izdaje zdravil, pa tudi prodaje zdravil brez recepta, bolezni dihal (52.652) kot posledica vladnih priporočil o omejitvi izdaje oziroma S – Zdravila za 1.160.825 1.093.982 - 5,76 % prodaje zdravil. Izdaja zdravil je v začetku aprila 2020 že bolezni čutil (66.843) sovpadala s predvidenimi ravnmi. Kot možni razlog za začetno V – Razna 479.568 507.169 + 5,76 % zdravila (27.601) 317 povečevanje zalog zdravil so poročali [13], da so se pacienti s prenos okužbe. Elektronski recept omogoča predpisovanje kroničnimi boleznimi kot so sladkorna bolezen in bolezni srca in zdravil brez neposrednega stika z ambulanto. ožilja odločili za dodatne zaloge zdravil za primer morebitnega Ugotavljali [13] so tudi znaten porast prodaje zdravil brez oteženega obiska lekarne, povezanega z ukrepi v pandemiji. recepta, vključno z vitamini, zdravili za lajšanje bolečin, za Predvidoma so osebe z zdravstvenimi stanji, zaradi katerih nižanje povišane telesne temperature, za lajšanje simptomov v veljajo tveganja za resnejše oblike koronavirusne bolezni 2019, nosu in grlu, za lajšanje kašlja in drugimi zdravili brez recepta. dodatno kopičile zdravila. Ta pojav je bil razviden pri zdravilih za zdravljenje astme, saj je bila astma v začetku 2020 opredeljena 5. ZAKLJUČEK kot možen dejavnik tveganja za resen potek bolezni COVID-19. V Sloveniji je bilo v ATC skupini P, ki zajema antiparazitike, V času pandemije bolezni COVID-19 so bile razvidne znatne insekticide in repelente, med 2019 in 2020 razvidno nekoliko demografske spremembe, kot je presežna umrljivost. Po zmanjšano predpisovanje zdravil [12], za 7,85 %, izraženo v spremljanju nadaljnjih, globalnih demografskih razmer bodo številu škatel zdravil. Raziskovalci na Švedskem [13] so v marcu znane tudi morebitne druge demografske spremembe. 2020 opazili povečano uporabo zdravilnih učinkovin klorokin in Ugotovitve kažejo, da so se v Sloveniji zdravila iz večine glavnih hidroksiklorokin iz ATC skupine P. Sprva so učinkovinama ATC skupin v dveh letih pandemije predpisovala v podobnem pripisovali koristne učinke pri zdravljenju bolezni COVID-19; obsegu kot v dveh letih pred pandemijo, z določenimi odstopanji vendar kasnejše raziskave tovrstne učinkovitosti niso pokazale, pri posameznih ATC skupinah. Tudi v ATC skupinah z velikim skrb je veljala tudi možnim neželenim učinkom [13]. V Sloveniji deležem zdravil za kronično zdravljenje je bil obseg se klorokin in hidroksiklorokin prav tako uporabljata za določene predpisovanja zdravil podoben in skladen s predvidevanji. indikacije. Med 2019 in 2020 [12] se je predpisovanje Znatno zmanjšanje obsega predpisovanja zdravil v letih 2020 in hidroksiklorokina povečalo, ne pa tudi predpisovanje klorokina. 2021, glede na 2018 in 2019, je bilo razvidno v ATC skupini J, V Sloveniji je bilo glede na 2018 in 2019 v letih pandemije 2020 ki zajema zdravila za sistemsko zdravljenje infekcij. Pripisan in 2021 razvidno zmanjšanje predpisovanja zdravil za sistemsko razlog je vzdrževanje fizične razdalje in upoštevanje higienskih zdravljenje infekcij iz ATC skupine J [12]. To zmanjšanje je med ukrepov v času pandemije. 2019 in 2020 v številu škatel znašalo 22,38 %, v številu receptov 22,77 % in v številu DDD 20,42 %. Ti rezultati soglašajo z LITERATURA IN VIRI rezultati objavljene raziskave [13]. Čeprav se je v tednu po 11. marcu 2020 predpisovanje zdravil iz skupine J nekoliko [1] Eoin McElroy, Praveetha Patalay, Bettina Moltrecht, Mark Shevlin, povečalo, je v nadaljevanju leta sledilo znatno zmanjšanje števila Adrienne Shum, Cathy Creswell in Polly Waite, 2020. Demographic and health factors associated with pandemic anxiety in the context of COVID- DDD, glede na predvidene vrednosti. Ugotovili so zmanjšano 19. British Journal of Health Psychology 25 (2020), 934–944. DOI: uporabo antibiotikov zaradi padca pojavnosti resnih infekcij, https://discovery.ucl.ac.uk/id/eprint/10109259/1/bjhp.12470.pdf. predvsem v dihalih. Navedli so, da je bil razlog vzdrževanje [2] Tracking SARS-CoV-2 variants. 2022. WHO. DOI: https://www.who.int/activities/tracking-SARS-CoV-2-variants. večje fizične razdalje in izboljšane higienske navade v pandemiji. [ 3] W HO C or onav ir us ( C O V I D-19) Dashboard. 2022. WHO. DOI: Na osnovi slovenskih podatkov [12] lahko zaključimo, da se je v https://covid19.who.int. [4] WHO Coronavirus (COVID-19) Dashboard, Situation by Region, dveh letih pandemije zmanjšal obseg predpisanih zdravil iz ATC Country, Territory & Area, Table View. 2022. WHO. DOI: skupine D, z zdravili za bolezni kože in podkožnega tkiva. V letu https://covid19.who.int/table. 2020 je bilo predpisanih 10,87 % manj škatel [5] Informacije o cepivih – cepiva in specifični imunoglobulini. 2022. NIJZ. oziroma 9,61 % DOI: https://www.nijz.si. manj receptov s temi zdravili kot leto prej. Vendar v absolutnih [6] Kako cepiva delujejo. 2022. Evropski portal za cepljenje. DOI: vrednostih razlike niso velike (81.291 v številu škatel oziroma https://vaccination-info.eu/sl/dejstva-o-cepivih/kako-cepiva-delujejo. [7] What is monoclonal antibody?. 2022. United States Department of 46.596 v številu receptov). Zmanjšan obseg predpisovanja teh Health and Human Services. DOI: zdravil bi lahko pripisali spremenjenemu številu pacientov v https://combatcovid.hhs.gov/what-are-monoclonal-antibodies. [8] COVID-19, zdravljenje in zdravila. 2022. CDC. DOI: ambulantah v pandemiji, oziroma delno tudi s fizično razdaljo https://www.cdc.gov/coronavirus/2019-ncov/your-health/treatments-for- povezanim učinkom na širjenje določenih kožnih bolezni. severe-illness.html. Kljub nekaterim razlikam v letih pandemije, z oziroma na leti [9] Interni viri. 2022. NIJZ (vključno s podatki iz povzetkov glavnih značilnosti zdravil). pred pandemijo, lahko zaključimo, da predpisovanje zdravil za [10] Struktura klasifikacijskega sistema ATC. 2022. JAZMP. DOI: kronične bolezni ni bilo bistveno spremenjeno. Tem ugotovitvam https://www.jazmp.si/humana-zdravila/podatki-o-zdravilih/atchum- pritrjujejo tudi ugotovitve švedske raziskave klasifikacija/struktura-klasifikacijskega-sistema-atc. [13], v kateri so [11] UN News. 2022. United Nations. DOI: raziskovalci zaključili, da pri večini najbolj uporabljenih zdravil https://news.un.org/en/node/1039401/date/2020-04-11. [12] Receptna lista 2012-2021. 2022. Zavod za zdravstveno zavarovanje ni bilo opazne spremembe v vzorcih izdaje zdravil v 2020, glede Slovenije. DOI: https://partner.zzzs.si/wps/portal/portali/aizv/zdravila. na obdobje med 2017 in 2019. Raziskovalci iz ZDA [14] pa so [13] Pär Karlsson, Aya Olivia Nakitanda, Lukas Löfling in Carolyn E. ugotovili, da je začetnemu povečanju predpisovanja zdravil Cesta, 2021. Patterns of prescription dispensation and over-the-counter medication sales in Sweden during the COVID-19 pandemic. PLoS ONE sledilo zmanjšano predpisovanje zdravil za kronično zdravljenje. 16(8), e0253944. DOI: 10.1371/journal.pone.0253944. Ta pojav pripisujejo manjšemu obsegu komuniciranja z [14] Muthiah Vaduganathan, Jeroen van Meijgaard, Mandeep R. Mehra, Jacob Joseph, Christopher J. O’Donnell in Haider J. Warraich, 2020. zdravnikom, omejenemu dostopu do lekarn, zmanjšanim Prescription Fill Patterns for Commonly Used Drugs During the zalogam zdravil v lekarnah, izgubi zavarovanja zaradi nezaposlenosti COVID-19 Pandemic in the United States. JAMA (June 23/30 2020) oziroma temu, da so pacienti povečali svoje zaloge zdravil. 323(24), 2524-2526. DOI: 10.1001/jama.2020.9184. Ambulante v obdobju pandemije v Sloveniji delujejo na drugačen način, z več komuniciranja na daljavo in omejenim številom istočasno prisotnih pacientov, da se čim bolj prepreči 318 Coalovi indeksi v Sloveniji v letih 1991, 2011 in 2021/ Coale's indexes of fertility in Slovenia in the years 1991, 2011 and 2021 Janez Malačič Ekonomska fakulteta Univerze v Ljubljani Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija Elektronska pošta: janez.malacic@ef.uni-lj-si POVZETEK sekte Huteriti. V tej populaciji bi ženska, ki bi se poročila Coalovi indeksi so bili definirani in uporabljeni za analizo pri 15. letu in bi ostala poročena do 49. leta starosti v dejavnikov rodnosti in njihovih sprememb v času povprečju rodila 12,4 otrok. demografskega prehoda v Evropi. Kljub starosti pa še A.J. Coale je v svoji analizi izhajal iz splošno zmeraj lahko pokažejo, kako pomembni sta zakonska sprejetega stališča med demografi, da je bilo za prehod od rodnost in rodnost izven zakonske zveze ter primerjavo visokih stopenj rodnosti, ki so bile značilne za dejanske rodnosti z maksimalno rodnostjo Huteritov. tradicionalni demografski režim, na nizke stopnje rodnosti, Coalovi indeksi za Slovenijo kažejo, da se je med letoma ki so se uveljavile v modernem demografskem režimu po 1991 in 2021 povečal pomen tako poročnosti kot rojevanj končanem demografskem prehodu, najpomembnejše izven zakonske zveze. Vse to pa ni vodilo do povečanja dogajanje na področju rodnosti znotraj zakonske zveze. To naše splošne rodnosti, saj je prišlo do izrazitih strukturnih dogajanje se je zelo lepo pokazalo na ravni manjših regij. sprememb v smeri od poročanja k ne-poročanju. Pokazalo pa se je tudi, da so se z uveljavitvijo modernega demografskega režima začeli dogajati novi procesi, ki so Ključne besede: mlade postopoma osvobodili vpliva tradicionalnih Coalovi indeksi, Slovenija, zakonska reproduktivnih norm. Rojevanje otrok izven zakonske in izvenzakonska rodnost zveze postopoma ni bilo več tabu in se je temu primerno v evropskih državah vse bolj razširilo. Ta trend je bil najprej ABSTRACT bolj izrazit v protestantskih državah Zahodne in Severne American demographer A.J. Coale defined four Evrope, nato pa se je vse bolj širil tudi v tradicionalne fertility indexes to study the demographic katoliške države Južne Evrope. transition in Europe at the level of micro Danes še ni mogoče reči, da se je zgoraj opisana regions. The indexes show the importance of liberalizacija razširila tudi izven Evrope. V nerazvitem delu sveta demografski prehod še ni končan. Zato so tam childbearing inside and outside marriage. In tradicionalne reproduktivne norme še močne. Za zunaj Slovenia, during the last thirty years marital and evropske razvite države pa velja, da se liberalizacija non-marital fertility have increased. However, postopoma širi tudi vanje. To še posebej velja za anglo overall fertility has not increased due to saksonski svet. Tam, kjer pa so tradicionalne patriarhalne norme posebej močne, kot npr. v Južni Koreji in nekaterih structural changes in favour of extra marital sosednjih državah Vzhodne Azije, pa imamo danes couples. najnižje stopnje rodnosti. V Južni Koreji je bila stopnja celotne rodnosti v letu 2021 le 0,81. Key words: Coale's indexes, Slovenia, marital V tem besedilu bom analiziral Coalove indekse za Slovenijo v letih 1991, 2011 in 2021. Še posebej me and non-marital fertility zanima, ali so ti indeksi še uporabni v družbi, kjer pravni sistem izenačuje pravno formalno sklenjene zakonske 1 UVOD zveze z izven zakonskimi skupnostmi in kjer je število Ameriški demograf A.J. Coale je sredi dvajsetega stoletja otrok rojenih v zakonski zvezi veliko manjše od števila s svojo raziskovalno skupino zelo podrobno analiziral otrok rojenih zunaj zakonske zveze. Hkrati pa bodo potek demografskega prehoda v Evropi na ravni relativno Coalovi indeksi pokazali primerjavo dejanske rodnosti v majhnih regij (Coale, 1965, str. 205-207). Pri tem ga je Sloveniji v izbranih letih z rodnostjo Huteritov. posebej zanimalo, kaj se je v času prehoda dogajalo z rodnostjo znotraj zakonske zveze, izven zakonsko 2 COALOVI INDEKSI V SLOVENIJI V rodnostjo in poročenostjo. Hkrati pa je dejanske ravni rodnosti v zakonski zvezi in izven nje primerjal z najvišjo LETIH 1991, 2011 IN 2021 kadarkoli zabeleženo rodnostjo človeških populacij. V Coalovi indeksi najprej razčlenijo dejavnike rodnosti na demografski literaturi je splošno sprejeto, da je najvišja tiste, ki delujejo v zakonski skupnosti in izven nje ter na rodnost, ki je bila kadarkoli ugotovljena v primeru vpliv poročenosti, nato pa dejansko rodnost v konkretni konkretne človeške populacije, rodnost ameriške verske populaciji z upoštevanjem prej omenjenih dejavnikov 319 standardizirajo z najvišjo kadarkoli zabeleženo rodnostjo Poglejmo sedaj za prebivalstvo Slovenije, v konkretni človeški populaciji. Samo za ponazoritev kakšno je bilo število vseh živorojenih ter živorojenih navedimo petletne starostno specifične stopnje rodnosti staršem v zakonski zvezi in tistim zunaj nje v letih 1991, Huteritov v starostnih razredih od 15-19 pa vse do 45-49. 2011 in 2021. Ti podatki so skupaj z indeksom 2021/1991 Te stopnje so zaporedoma 0,300, 0,550, 0,502, 0,447, za navedene tri kategorije podatkov o živorojenih 0,406, 0,222 in 0,061 (Malačič, 2006, str. 53). prikazani v tabeli 1. Tabela 1: Število vseh živorojenih (N) ter živorojenih v zakonski zvezi (Nz) in izven nje (Nnz) v Sloveniji v letih 1991, 2011 in 2021. Vir: Malačič, 2006, str. 53-54 in SISTAT, dostop 25. 8. 2022. N Leto, I 1991 2011 2021 I2021/1991 1 2 3 4 5 N 21.583 21.947 18.984 88,0 Nz 15.881 9.484 8.026 50,5 Nnz 5.702 12.463 10.958 192,2 Število živorojenih v izbranih letih nam ne pokaže dobro, bi te rojevale kot ženske pri Huteritih. Četrti indeks pa je kaj se je dogajalo s slovensko rodnostjo v zadnjih indeks poročnosti Im , ki pokaže prispevek poročnosti k tridesetih letih, čeprav podatki v tabeli kažejo, da je splošni rodnosti v Sloveniji v izbranih letih. Im je v resnici rodnost padla in je bil indeks za število vseh živorojenih razmerje med živorojenimi poročenim ženskam ob 88,0. Veliko bolj zanimiva in jasna sta indeksa za maksimalni rodnosti in številom živorojenih v primeru, da zakonsko in izven zakonsko rodnost. Prvi indeks kaže, da bi bile poročene vse ženske in bi hkrati imele tudi je bilo število živorojenih znotraj zakonske zveze leta 2021 maksimalno rodnost. Navedeni štirje Coalovi indeksi so samo polovica tistega števila iz leta 1991. V nasprotju s med seboj povezani tako kot kaže naslednji obrazec tem številom pa se je število otrok rojenih izven zakonske (zvezdica pomeni pri obrazcu množenje): zveze tako do leta 2011 kot do leta 2021 zelo povečalo. Za If = Ig * Im + (1 – Im ) * Ih tridesetletno obdobje je indeks kar 192,2. Delež Za izračun vseh štirih indeksov potrebujemo za živorojenih otrok v Sloveniji, ki so bili rojeni izven posamezna izbrana leta število žensk rodnega kontingenta zakonske zveze je bil leta 1991 26,4 %, do let 2011 in 2021 in število poročenih žensk tega kontingenta po petletnih pa je zaporedoma narastel na 56,8 in 57,7 %. starostnih razredih od 15-19 do 45-49 let, število A.J. Coale je definiral štiri indekse, ki jih bom živorojenih v zakonski zvezi in izven nje v izbranih letih tukaj samo na kratko vsebinsko opredelil, ne bom pa ter petletne starostno specifične stopnje rodnosti Huteritov navajal obrazcev za njihov izračun. Ti obrazci so na voljo za razrede od 15-19 do 45-49 let. Dodajmo še, da indeks Ih v literaturi (Malačič, 2006, str.53-54). Prvi indeks If je izračunamo s pomočjo zgornjega obrazca, saj dobimo z indeks splošne rodnosti, ki kaže, kolikšna je splošna vrednostmi ostalih indeksov enačbo z eno neznanko. rodnost v Sloveniji v izbranih letih v primerjavi s Konkretni izračuni posameznih indeksov so na voljo pri hipotetično rodnostjo ženski v Sloveniji, če bi te rojevale avtorju in jih tukaj ne bom navajal. Vzorec izračuna za leto tako kot pri Huteritih. Naslednja dva indeksa sta indeks 1991 pa je na voljo v literaturi (Malačič, 2006, str. 54-55). zakonske rodnosti Ig in indeks nezakonske rodnosti Ih , ki Vrednosti izračunanih Coalovih indeksov za Slovenijo za sta definirana enako kot prvi indeks, vendar posebej za leta 1991, 2011 in 2021 so prikazane v tabeli 2, ki vsebuje zakonsko in nezakonsko rodnost v Sloveniji. Zakonska in tudi časovni indeks 2021/1991 za vse štiri Coalove nezakonska rodnost se primerja s tisto hipotetično indekse. rodnostjo poročenih in neporočenih žensk v Sloveniji, če Tabela 2: Coalovi indeksi za Slovenijo v letih 1991, 2011 in 2021 ter časovni indeks 2021/1991 za vsakega izmed njih. Vir: Malačič, 2006, str. 54-55 in SISTAT, dostop 25. 8. 2022. Leto I If Ig Im Ih 1 2 3 4 5 1991 0,117 0,148 0,582 0,074 2011 0,131 0,186 0,306 0,102 2021 0,132 0,204 0,274 0,105 I2021/1991 112,8 137,8 47,1 141,9 320 Coalovi indeksi v tabeli 2 za Slovenijo v letih 1991, 2011 zadnjih treh desetletjih prišlo do velikega znižanja in 2021 kažejo, da so se deleži splošne, zakonske in poročnosti, pa tudi do velikega povečanja razvez pri nezakonske rodnosti v Sloveniji v primerjavi z rodnostjo poročenih. Zakonske zveze so postale zelo nestabilne in Huteritov za te tri skupine povečali. Obseg povečanja trajajo v povprečju manj časa kot v preteklosti. Vse to pa kažejo indeksi v zadnji vrstici tabele v stolpcih 2, 3 in 5. se izrazito kaže v ravni in v trendih rodnosti v Sloveniji. Največje povečanje je pri indeksu nezakonske rodnosti, vendar vrednost tega indeksa v letu 2021 še zmeraj 3 SKLEP zaostaja za vrednostjo indeksa splošne rodnosti. To nam Ob velikih spremembah na področju poročnosti in razvez tudi razloži, zakaj se je indeks splošne rodnosti v tridesetih ter pomena izven zakonskih partnerskih skupnosti v letih povečal le za 12,8 %. Dejansko je to posledica tega, Sloveniji v zadnjih tridesetih letih bi pričakovali, da nam da se v Sloveniji že dalj časa večina otrok rojeva izven Coalovi indeksi, ki so bili uporabljeni za analizo zakonske zveze. Indeksa za leto 2021 v tretjem in petem demografskega prehoda v Evropi, ne bodo povedali veliko stolpcu nam kažeta, da je rodnost poročenih žensk v novega. Vendar temu ni tako. Coalovi indeksi za Slovenijo Sloveniji bila tega leta na ravni petine rodnosti Huteritov, v izbranih letih zadnjih treh desetletij kažejo, da se je do medtem ko je bila rodnost neporočenih žensk znotraj leta 2021 povečal pomen tako poročnosti kot rojevanj rodnega kontingenta na ravni desetine rodnosti Huteritov. izven zakonske zveze. Vse to pa ni vodilo do povečanja Relativno največjo spremembo v zadnjih tridesetih letih v naše splošne rodnosti, saj je prišlo do izrazitih strukturnih Sloveniji pa kaže indeks poročnosi. V tej spremembi se sprememb v smeri od poročanja k neporočanju. skriva veliko razlogov za drastičen padec slovenske rodnosti daleč pod raven, ki bi zagotavljala dolgoročno nemoteno obnavljanje prebivalstva. V zadnjih nekaj letih slovenska rodnost zagotavlja manj kot tri četrtine ravni, ki LITERATURA IN VIRI bi bila potrebna za enostavno obnavljanje modelskega 1. Coale, A.J.: Factors Associated with the Development of Low prebivalstva. V konkretnih podatkih je to razmerje 1,56 Fertility: An Historical Summary. V knjigi: United Nations proti 2,1 na primeru stopnje celotne ali totalne rodnosti. Še World Population Conference, Belgrade, 1965, Vol. 2. New York 1965, str. 205-207. posebej zaskrbljujoče pri naši rodnosti pa je, da bodo v 2. Coale, A.J.: The Demographic Transition, International prihodnjih letih strukturne spremembe, ki se skrivajo v Population Conference, Liege 1973, IUSSP, Vol. I, Liege starostno spolni strukturi slovenskega prebivalstva izrazito 1973, str. 53-72. 3. Coale, A.J., Hoover, M.E.: Population Growth and Economic negativno vplivale na število živorojenih v Sloveniji. Development in Low Income Countries, Princeton University Indeks poročnosti Im v tabeli 2 za leto 2021 kaže, Press, Princeton 1958. da bi se ob maksimalni rodnosti poročenih žena v Sloveniji 4. Coale, A.J., Watkins, S.C., eds.: The Decline of Fertility in Europe, Princeton University Press, Princeton 1986. realiziralo le 27,4 % maksimalne možne rodnosti rodnega 5. Malačič, J.: Demografija. Teorija, analiza, metode in modeli, kontingenta našega prebivalstva. To je samo 47,1 % 6. izdaja, Ekonomska fakulteta Univerze v Ljubljani, vrednosti tega indeksa v letu 1991 v Sloveniji. Poročeni Ljubljana 2006. 6. SISTAT, dostop 25. 8. 2022, Statistični urad Republike pari imajo v povprečju pri nas še zmeraj precej višjo Slovenije, Ljubljana. rodnost kot neporočeni pari ali posamezniki. Vendar je v 321 Odločitev za življenje A decision for life izr. prof. 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@teof.uni-lj.si POVZETEK Demografska zima se je iz starega kontinenta razširila na ves Demografska stroka in statistika v zadnjih letih ugotavljata, da svet. Zadnjih deset let se število novorojenih otrok nikjer na svetu nataliteta pada po vsem svetu, tudi na afriškem kontinentu, ki je več »zibelka človeštva« v dveh pomenih besede: tam naj bi bili ne povišuje, temveč se zmanjšuje. Število prebivalstva (še) raste izključno zahvaljujoč podaljševanju človeškega življenja začetki človeške vrste in tam se rodi največ otrok na svetu. Ker , se v zadnjih desetih letih število novorojenih otrok na svetu ne nikjer pa ne zaradi rodnosti. Politiki, ki se zavedajo tragičnosti tega demografskega dejstva, v svojih državah ukrepajo na povečuje več1, temveč se zmanjšuje, je stanje zaskrbljujoče. Pri različne načine. V demokratični družbi nobena zunanja prisila na nekaterih narodih je nataliteta padla krepko pod mejo državljane ne more demografske krivulje reprodukcije, ki je 2,1 otroka na žensko. Ob tem dejstvu se usmeriti navzgor; ne politiki sprašujejo, kaj narediti, da bi se število rojstev povečalo zakonodaja, ne religijski nauki in ne materialne stimulacije. Ljudje se moramo za rodnjo odločiti sami. Zdi se, da je za in bi se tako izognili izginotju narodov in, v najslabšem primeru, odločitev za rodnjo otrok celega človeštva. V prispevku najprej predstavljamo učinkovita vzgoja za spoštovanje svetosti življenja. demografski položaj na svetu, nato pa nanizamo nekaj ukrepov politike v različnih državah, ki želijo povečati nataliteto, reakcije Ključne besede: demografska zima, rodnost, abortus, civilne javnosti na demografsko stanje in nauk Katoliške Cerkve ekstremizem, osebna svobodna odločitev o spoštovanju življenja . . Razmišljanje zaključimo s spoznanjem, da v sodobni demokratični družbi nihče ne more prisiliti mater in parov, da bi sprejeli otroka ali več otrok. Za rodnjo se morajo svobodno sami odločiti. ABSTRACT The demographic winter has spread from the old continent to the whole world. For the last ten years, the number of new-born Prvo poglavje: Demografska zima na našem children has not increased anywhere in the world, but rather planetu2 decreased. The population is (still) growing exclusively thanks to the extension of human life, and nowhere due to the birth rate. Politicians, who are aware of the tragic nature of this V medijih stalno prebiramo novice o klimatskih spremembah na demographic fact, act in different ways in their countries. In a našem planetu in javno mnenje je sprejelo dejstvo, predvsem democratic society, no external coercion on citizens can direct zaradi vse bolj vročih poletnih mesecev, da se zemeljsko ozračje the demographic curve upwards; not legislation, not religious segreva. Redko pa v javnih medijih preberemo, da človeštvu teachings, and not material stimulation. People have to make grozi zima; demografska zima namreč. Na videz je to their own decisions about the birth of their children. To accept kontradiktorna trditev, toda demografska zima lahko še hitreje od life, an education to respect the sanctity of life seems to be vročega ozračja ogrozi obstoj človeške vrste. Znanstveniki effective. ugotavljajo, da izumirajo živalske vrste3. Čeprav število ljudi eksponentno še narašča, je žal v trendu izumiranja tudi človeška Keywords: demographic winter, birth rate, abortion, extremism, vrsta. Ko govorimo o demografski sliki človeštva, namreč ne personal free decision. moremo ne opaziti, da kljub naraščanju prebivalstva radikalno pada rodnost. Razlog za to trditev lahko najdemo v okolju4 in v kulturno-socioloških razlogih. Število novorojenih otrok se v Uvod zadnjih 10 letih v svetu praktično ne povečuje več.5 Gams in 1 Pearce, Fred. 2008. Peoplequake, Mass Migration, Ageing Nations and the Reproduction 30, št. 6:1287– 1289 in Swan, Shanna H., in Stacey Colino. 2021. Coming Population Crash. London: Transworld Publishers Count Down: How Our Modern World Is Threatening Sperm Counts, Altering Male 2 Belo knjigo Slovenske demografije so avtorji podnaslovili »Evropska and Female Reproductive Development, and Imperiling the Future of the Human demografska zima«. Zdi se nam primerno, da ta pojem ne omejujemo samo na stari Race. New York: Scribner. kontinent, temveč da v skladu s statističnimi podatki govorimo o demografski zimi 5 Pearce, Fred. 2008. Peoplequake, Mass Migration, Ageing Nations and the celotnega našega planeta. Coming Population Crash. London: Transworld Publishers 3 Kolbert, Elizabeth. 2014. The Sixth Extinction: An Unnatural History. New York: Bloomsbury. 4 Levine, Hagai, in Shanna H. Swan. 2015. Is dietary pesticide exposure related to semen quality? Positive evidence from men attending a fertility clinic. Human 322 Osredkar sta zapisala, da se je rodnost v svetovnem merilu od ideološkega pritiska pa ni znan, morda se pojavlja sam od sebe, leta 1955, ko je beležila 4,97 otroka na žensko, do leta 2020 tj. emergentno, kot del moderne informacijske družbe. Pritisk je zmanjšala na 2,476. Večanje števila prebivalstva je zavajajoče, nesporno globalen, torej ni opazen samo v Sloveniji, ampak tudi ker ga beležimo le na račun podaljšane življenjske dobe ljudi, v Evropi in po svetu. Ve se tudi, s katerimi ukrepi ustaviti torej zahvaljujoč boljši zdravstveni oskrbi, v resnici pa se število preveliko število rojstev: razbiti družino, omogočiti lahke rojstev po vseh kontinentih drastično zmanjšuje7. V zahodnem ločitve, razbiti poroko in druge ustanove družine, propagirati svetu je rodnost v večini držav padla pod stopnjo 2,1 rojenega svobodno izbiro partnerjev, otežiti starševstvo, povečati strošek otroka na žensko in gospodarstvo v teh državah »rešujejo« in ceno otrok, trgati tradicionalne oblike socialnih vezi, povečati priseljenci iz dežel tretjega sveta, kjer rodnost še lahko ohranja lahkotnost ločitev.12 ali celo nekoliko povečuje prebivalstvo. Vsekakor moramo Tam, kjer se politika zaveda nevarnosti demografski priznati, da demografski problem na svetu ni (več) preveliko zime in »obrnjene demografske piramide«, države in različne število prebivalcev (ki v resnici nikoli ni bil pravi problem), ustanove iščejo različne načine, kako bi obrnili demografski temveč vse manjša rodnost, ki lahko človeški rod resnično pahne trend. v izumrtje, če se bo tak trend rodnosti nadaljeval. Navedli bomo nekaj tipičnih primerov demografske zime. V Evropi že nekaj desetletij beležimo negativni naravni Drugo poglavje: Zakonodaja za povečanje prirastek. »Na začetku stoletja se je v Evropi začela skupna natalitete stopnja rodnosti zniževati. V letih 2001 in 2002 je stopnja znašala 1,46 živorojenega otroka na žensko. Do leta 20 10 se je sicer povišala na 1,62, nato se je do leta 2013 znižala na 1,54, leta 2014 Potrebno je poudariti, da imajo samo politične entitete, torej pa znova povišala na 1,58. V razvitih delih sveta se za stopnjo države, vzvode prisile, ki lahko vplivajo na nataliteto. V primeru neposlušnosti jih namreč lahko sankcionirajo. Verske skupnosti naravnega obnavljanja prebivalstva, tj. za raven, na kateri bi bilo število prebivalstva brez priseljevanja in druge civilne ustanove teh vzvodov nimajo. V prejšnjem ali izseljevanja dolgoročno stabilno, šteje skupna stopnja rodnosti 2,10 poglavju smo omenili, kako je kitajska oblast z zakonodajo živorojenega otroka na žensko.« prisilila svoje prebivalce v zmanjšanje rodnosti. Ko pa so 8 Na starem kontinentu nobena država ne izvaja zunanje fizične ali pravne prisile glede rojevanja demografski kazalci v začetku tretjega tisočletja začeli otrok, toda liberalistično hedonistične težnje ustvarjajo javno opominjati kitajske voditelje, da njihova demografska politika mnenje, ki ni naklonjeno povečanju natalitete. To mnenje preko deželo pelje proti katastrofi, je spremenila zakonodajo. Število klasičnih in spletnih medijev vpliva na pare, da se odločajo za starostnikov je namreč skokovito naraščalo, demografska minimalno število otrok, ali se celo ne odločajo za otroke. piramida se je začela obračati in stanje je ogrozilo gospodarstvo. Posledica zmanjšane natalitete je staranje prebivalstva in Leta 2016 so odpravili politiko enega otroka, vendar novi zakon, izumiranje narodov 9 . Nasprotno pa v primeru kitajske ki omenja tri otroke v družini, ni pospešil večje natalitete. demografske zime lahko govorimo o državni pravni prisili, ki je Izgleda, da je bila kitajska zakonodajna prisila učinkovita zgolj deželo pahnilo v sedanji težek demografski položaj. pri »prepovedi rojevanja«. Nima pa moči, da bi dvignila rodnost. Kitajsko prebivalstvo je v zadnjih šestdesetih letih Stopnja rodnosti je namreč na Kitajskem leta 2021 padla na 1,3 močno naraslo. Leta 1960 je bilo 6 živorojenega otroka na žen 60 milijonov Kitajcev, leta sko. Kitajska vlada je zato v avgustu 2020 pa milijardo in 400 milijonov. Ob informacijah o hitri rasti 2022 napovedala nove motivacijske ukrepe za spodbujanje prebivalstva in uničevanju človekovega okolja, ki je s to rastjo višanja rodnosti. Kitajska državna komisija za zdravje je pozvala vlado, naj poveča izdatke za reproduktivno zdravje ter izboljša povezano, je vlada moderne Kitajske sprejela sklep, da je otroško varstvo. Ministrstvo za zdravje tako priporoča, da se potrebno omejiti demografsko rast. Leta 1979 je kitajska oblast, iz strahu pred hitrim večanjem števila prebivalcev zapovedala, odločanje staršev za več otrok podpre s subvencijami in davčnimi da ima vsaka kitajska družina lahko samo enega otroka. Kitajski olajšavami za mlade družine ter s pomočmi na področjih komunistični partiji je uspelo zmanjšati nataliteto z zakonodajno izobraževanja, stanovanjske politike in zaposlovanja. V kitajskih prisilo. Še več, število prebivalcev se je na Kitajskem, prvič po provincah morajo do konca leta tudi zagotoviti dovolj vrtcev za prevzemu njihove oblasti v letu 1949, v letu 2018 zmanjšalo. otroke od dveh do treh let starosti. Kitajske oblasti so se za te Raziskovalec YI Fuxian, ki deluje na ameriški univerzi ukrepe odločile, potem ko so v nekaterih najbolj razvitih kitajskih mestih take spodbude za mlade družine padle na plodna Wisconsin-Madison, je navedel podatek, da se je v letu 2018 prvič v zgodovini moderne Kitajske zgodilo, da se je število tla. Z objavljenimi smernicami želijo kitajske oblasti tako prebivalcev na Kitajskem zmanjšalo – politiko razširiti na vso državo, poročanje AFP povzema STA.13 za 1,27 milijona. Število smrti je za toliko preseglo število rojstev. Primerno je, da se v našem razmišljanju nekoliko 10 Glede na skoraj milijardo in pol prebivalcev v tej državi je milijon skoraj zaustavimo pri zakonodaji, ki dovoljuje ali prepoveduje »prekinitev nosečnosti« v zdravstvenih ustanovah. Vprašanj zanemarljiv, toda pomenljiv. e zakonodaje glede abortusa je namreč danes zelo aktualno. Na Zdi se, da svetovne elite, pogosto preko dobrodelnih organizacij forsirajo sistem vrednot potrošništva in proti tem mestu želimo zgolj omeniti nekaj dejstev glede politike do - vprašanja abortusa, ki vsekakor vpliva na nataliteto. Zagovorniki rodnosti. Med njimi je gotovo tudi fundacija Billa in Melinde Gates, ki deluje prioritetno v dobro človeštva in zato predvsem v zakonsko dovoljenega opravljanja splava navajajo celo vrsto Afriki širi izobraževalne programe, ki imajo za cilj širiti razlogov, zakaj mora zakonodaja tovrstni poseg dovoliti. kontracepcijo in posledično zmanjšanje rojstev Predvsem pa ga razumejo kot »pravico« ženske. Po vsej 11 Del tega verjetnosti se je splav prakticiral skozi celotno zgodovino 6 Gams, Matjaž, in Osredkar, Mari Jože. 2021, v: Bogoslovni vestnik, Katoliški nauk 11 Gams, Matjaž, in Osredkar, Mari Jože. 2021, v: Bogoslovni vestnik, Katoliški in znanost o demografskih vprašanjih, str. 555-567. nauk in znanost o demografskih vprašanjih, str. 555-567. 7 Svetovna populacija – temeljni demografski podatki. Vir: 12 Gams, Matjaž, in Osredkar, Mari Jože. 2021, v: Bogoslovni vestnik, Katoliški https://www.worldometers.info/world-population. nauk in znanost o demografskih vprašanjih, str. 555-567. 8 Eurostat: https://ec.europa.eu/eurostat/statistics-explained/pdfscache/19886.pdf 13 STA: https://www.sta.si/3070806/kitajska-ob-upadanju-rodnosti-z-novimi- 9 Gams, Matjaž, in Osredkar, Mari Jože. 2021, v: Bogoslovni vestnik, Katoliški nauk spodbudami-za-mlade-druzine in znanost o demografskih vprašanjih, str. 555-567. 10 Dnevnik: https://www.dnevnik.si/1042855773 323 človeštva. Politika pa ga je dovoljevala ali prepovedovala. Evropi pa se je najprej začelo prakticirati v Veliki Britaniji. V Začnimo s primerom Romunije, kjer je komunistični diktator Sloveniji tovrstne proteste organizira zavod »Božji otroci«. Nocolae Ceausescu v 60-tih letih prejšnjega stoletja želel Podobne primere imamo tudi drugod po Evropi oz. zahodnem spodbuditi rast romunskega prebivalstva in je zakonsko svetu. Več ali manj je njihov protest utemeljen na krščanskem prepovedal splav, ki je bil predhodno dovoljen, prav tako je nauku. prepovedal uporabo kontracepcij. 14 Politika je tam uspela Mnogi kritiki, predvsem iz levega pola slovenske povečati rodnost od 1,9 na 3,7 živorojenega otroka na žensko.15 politike, te skupine in njihove dejavnosti opredeljujejo kot »V ZDA se danes kaže trend politike, da bi zakonsko omejila ekstremistične. Primerno je, da tudi mi na tem mestu opravljanje abortusa. Medtem ko so na Irskem, v tradicionalno spregovorimo o fundamentalizmu in ekstremizmu. Če se vernik, katoliški državi, pred leti na referendumu podprli spremembo kristjan ali musliman, odloči, da bo svoje življenje utemeljil na ustave in legalizirali splav, gre trend v nekaterih drugih Božji besedi oz. na nauku v katerem prepoznava Božje razodetje evropskih državah v obratni smeri. Na Hrvaškem ima ugovor in Božjo voljo ter vsa svoja dejanja utemeljuje na Božji besedi, vesti okrog 60 odstotkov ginekologov v Splitu, na Poljskem pa ga imenujemo fundamentalist. Temelj njegovega življenja je poskušajo splav popolnoma prepovedati, celo v primeru incesta Božja beseda. Takoj, ko bo želel prisiliti tudi ljudi v svoji okolici, ali posilstva.«16. V Sloveniji zakonodaja dovoljuje abortus. V 55. da bi živeli kot živi on, pa se njegov fundamentalizem spremeni členu slovenske ustave je zapisano, da je odločanje o rojstvu v ekstremizem. Verski ekstremizem je prisila drugih k otrok svobodno. To ustavno pravico ureja zakon, ki dovoljuje sprejemanju vrednot, ki jih spoštuje ekstremist. opravljanje splava na zahtevo razsodne ženske (pri mladoletnih Fundamentalizem je v svoji osnovi nekaj dobrega, ekstremizem ni potrebno soglasje staršev) od 10. tedna nosečnosti. Kasneje pa pa je nekaj slabega, ker vključuje prisilo, nasilje nad drugimi. lahko opravijo splav takrat, ko komisija na ginekoloških klinikah Vsekakor pa izpovedovanje vere oz. življenje po Božjih odloči, da nosečnost ogroža življenje oz. zdravje matere ali če je zapovedih ni ekstremizem. za to utemeljen socialni razlog. V večini evropskih držav, kjer je splav zakonsko omogočen vsem, ki ga želijo opraviti, ne Četrto poglavje: Primer religijskega nauka za poznamo neposrednih zakonodajnih ukrepov za zvišanje natalitete. Na temelju različnih teorij rodnosti pa države povečanje natalitete izpeljujejo načrte in spodbude za povečanje rodnosti. Več ali manj se večina teorij »vrti« okoli ekonomskega položaja staršev. Pred odločitvijo za družino pari preračunajo V strokovni literaturi pogosto najdemo opombo, da imajo koristi in ekonomske stroške in se glede na spoznanja odločajo katoliške družine več otrok kot tiste, ki se ne držijo verskega za otroke oz. o številu otrok, ki jih bodo v družini sprejeli. Če nauka. Tadej Strehovec je v svojem predavanju na stroški presegajo koristi, se pari ne odločijo za otroke. Nekatere demografskem posvetu v Državnem svetu RS, maja 2018, države zato z materialnimi stimulacijami in davčnimi olajšavami pokazal, da v nasprotju z upadanjem prebivalstva v Sloveniji in motivirajo svoje državljane za rodnjo otrok.17 Evropi, verno prebivalstvo ohranja dovolj visoko stopnjo rodnosti za ohranjanje števila članov verskih skupnosti. 19 To drži, vendar je potrebno priznati, da so se tudi mnoge moderne Tretje poglavje: Izražanje volje ljudstva katoliške družine prepustile družbenemu trendu, ki daje materialnim vrednotam prednost pred verskimi vrednotami oz. Omenili smo primere različnih zakonodaj, ki želijo dvigniti pred otroki. Podobno lahko govorimo tudi o muslimanskih družinah. Toda, pri katoliškem nauku o družini ne gre nataliteto v posameznih državah, spregovorili pa smo tudi o prvenstveno za ohranjevanje narodov in človeštva. Gre za zakonodajah, ki v večini držav materam omogoča prekinitev spoštovanje svetosti življenja. Posledično pa »sprejetje« nosečnosti. Predvsem glede slednje je v zahodnem svetu javnost življenja vsekakor pripelje do večje natalitete. zelo odzivna. Na eni strani imamo veliko demonstracij v podporo Katoliški nauk prepoznava človeško osebo od zakonu, ki dovoljuje abortus, na drugi strani pa mu mnogi združenja moške in ženske spolne celice pri spočetju zarodka, pa izražajo nasprotovanje. do človekove biološke smrti. Nihče se ni odločil, da bo živel in Na Hrvaškem se že nekaj časa organizira »Pohod za nihče nima nobene zasluge, da živi. Življenje nam je bilo vsem življenje«, na katerem udeleženci pozivajo k zakonski zaščiti podarjeno. Ker krščanski nauk uči, da je življenje Božji dar, je nerojenih otrok. Gibanje za življenje vsekakor vpliva na življenje sveto v etimološkem pomenu besede. Kar pa je sveto, odločitev mater in ginekologov, ali bo prišlo do splava ali bo tega se človek »ne sme dotakniti«! Ne dotakniti se življenja pa otrok rojen. Od 29 javnih bolnišnic na Hrvaškem v šestih nimajo ginekologa, ki bi opravil splav na zahtevo ženske, ker uveljavlja pomeni sprejeti vsakega spočetega človeka in ohranjati njegovo življenje do biološke smrti. To pomeni, da Bog, in ne človek, možnost ugovora vesti.18 V Sloveniji se od leta 2016 organizirajo odloča o življenju in smrti. Iz te predpostavke sledi, da »želja tako imenovane molitve pred ginekološk po imi klinikami, kjer se opravljajo abortusi. Skupine »Božjih otrok« se zberejo pred materinstvu in očetovstvu ne upravičuje nobene »pravice do otroka«, porodnišnico, v rokah imajo transparente in molijo. S svojim pač pa so očitne pravice tistega, ki prihaja na svet. Temu početjem nikogar ne motijo, so pa opazni in tako izražajo svoje je treba zagotoviti najustreznejše bivanjske razmere s trdno – na nasprotovanje abortusu. Tak način izražanja nasp zakonu in komplementarnosti dveh podob, očetovske in rotovanja zakonodaji, ki omogoča prekinitev nosečnosti, izvira iz ZDA, v materinske – utemeljeno družino«20. Isti dokument nadaljuje, da morajo biti »Otrokove pravice zavarovane s pravnim 14 Pejič Nina, http://ipes-si.org/blog/2019/06/05/kdo-se-bo-postavil-za-naso- 17 To tematiko predstavlja Milivoja Šircelj v delu Rodnost v Sloveniji od 18. do 21. pravico-do-splava/ stoletja, Statistični urad RS, Ljubljana 2006. V svojem delu se nanaša na Mcdonald. 15 Horga M, Gerdts C, Potts M The remarkable story of Romanian women’s 18 DELO : https://www.delo.si/novice/svet/v-zagrebu-pohod-za-zivljenje-vedno- struggle to manage their fertility Journal of Family Planning and Reproductive vec-ginekologov-z-ugovorom-vesti/ Health Care 2013;39:2-4. Dostopno na: https://srh.bmj.com/content/39/1/2.full 19 Strehovec, Tadej. 2019, v: Gams, Matjaž, in Janez Malačič, ur. Bela knjiga 16 Intihar, Anja dostopno na: https://www.delo.si/sobotna-priloga/prepoved- slovenske demografije. Ljubljana: Inštitut Jožef Stefan, str. 92-95. abortusa-ima-v-resnici-zelo-kratko-zgodovino/ 20 Kompendij družbenega nauka Cerkve, čl. 235. 324 redom… Prva otrokova pravica pa je, da se rodi v družini z preživetje? V bistvu se lahko vprašamo: Kaj je vrednota? To je materjo in očetom , pravica, katere spoštovanje je bilo vedno cilj, ki omogoča življenje in preživetje; ne le posamezniku, težavno in ki pozna danes zaradi razvoja genetske tehnologije temveč vsem posameznikom in družbi kot celoti. V bistvu je nove oblike kršitev«21 Katoliška Cerkev je prepričana, da ima vrednota samo to, kar omogoča preživetje. Če neka drža vodi v država dolžnost, da varuje družino in otroke : »Politična izumrtje, to ni vrednota. skupnost ima dolžnost, da družino spoštuje, jo podpira in ji Res je, da si katoličani prizadevamo, da bi zakonodaja zagotavlja predvsem sledeče: svobodo, da si osnuje svoje ščitila življenje še nerojenih otrok. Toda, ne glede na zakonodajo ognjišče, da ima otroke in jih vzgaja v skladu s svojimi nravnimi in javno mnenje, je vsak človek lahko svoboden in se odloča po in religioznimi prepričanji; zaščito trdnosti zakonske zveze in svoji vesti in kakor spozna, da je dobro; torej, da je odprt za družinske ustanove; svobodo, da izpoveduje svojo vero, jo življenje. K temu nas spodbuja Deklaracija človekovih pravic24, predaja naprej, vzgaja v njej svoje otroke s potrebnimi sredstvi dokument Drugega vatikanskega koncila o Verski svobodi in in ustanovami ; pravico do zasebne lastnine, svobodo, da osnuje Kristus sam je zagovarjal, da se je zanj in za evangeljski nauk podjetje, dobi delo, stanovanje, pravico, da se izseli; na podlagi potrebno odločiti. institucij dežele pravico do zdravstvenega varstva, do pomoči za ostarele in do družinskih doklad; zaščito varnosti in zdravstva, zlasti z ozirom na nevarnosti kot so mamila, pornografija, alkoholizem, itd. svobodo, da skupaj z drugimi družinami REFERENCE osnujejo združenja in da so tako zastopane tudi pri civilnih oblasteh« 22. Jeseni 2010 je evropska škofovska konferenca Blangiardo, Giancarlo, in Simona Maria Mirabelli, ur. 2012. I Vescovi europei su demografia e famiglia in Europa. Siena: Edizione Cantagalli. povabila vse evropske katoliške škofe na posvet z naslovom Katoliška cerkev je vznemirjena zaradi »demografske zime« v Deklaracija človekovih pravic. Evropi23. Zavedajoč se, da koeficient 1,5 otroka na žensko še DELO : https://www.delo.si/novice/svet/v-zagrebu-pohod-za-zivljenje-vedno-vec- zdaleč ne zadošča za ohranjanje evropske populacije, ki se stara, ginekologov-z-ugovorom-vesti/ so škofje zaključili, da je edina rešitev za Evropo trdna in za Dnevnik: https://www.dnevnik.si/1042855773 življenje odprta družina. Rezultat posveta je knjiga I vescovi Eurostat: https://ec.europa.eu/eurostat/statistics-explained/pdfscache/19886.pdf europei su demografia e famiglia in Europa, v kateri je izražena spodbuda evropskim državam, da bi stimulirale družino. V bistvu Gams, Matjaž, in Janez Malačič, ur. 2019. Bela knjiga slovenske demografije. so samo povzeli nauk, ki ga Katoliška cerkev oznanja že 2000 Ljubljana: Inštitut Jožef Stefan. let. Gams, Matjaž, in Osredkar, Mari Jože. 2021, v: Bogoslovni vestnik, Katoliški nauk in znanost o demografskih vprašanjih, str. 555-567. Sklep Horga M, Gerdts C, Potts M The remarkable story of Romanian women’s struggle to manage their fertility Journal of Family Planning and Reproductive Health Care 2013;39:2-4. Dostopno na: https://srh.bmj.com/content/39/1/2.full Nobena politika ali zakonodaja, sama na sebi, ne more Intihar, Anja dostopno na: https://www.delo.si/sobotna-priloga/prepoved-abortusa- dvigniti natalitete oz. prisiliti žensko ali par, da bi rodila otroka. ima-v-resnici-zelo-kratko-zgodovino/ Tudi nobena druga zunanja prisila, verski vpliv ali ekstremistične težnje nimajo odločilnega vpliva na nataliteto. Zdi se, da tako Katekizem Katoliške Cerkve početje zgolj povzroča razkole v družbi in nima željenega učinka. Koncilski odloki, Odlok o verski svobodi Za rodnjo otrok se morajo starši, konec koncev, odločiti sami. Na odločitev pa bolj kot nek Kompendij družbenega nauka Cerkve, čl. 235. i zakonski predpisi ali priložnostni zunanji vplivi, odloča vzgoja za starševstvo, ki lahko mladim Kolbert, Elizabeth. 2014. The Sixth Extinction: An Unnatural History. New York: ljudem omogoči sprejetje življenja. Ne le zato, da se ohrani narod Bloomsbury. in človeški rod, temveč predvsem zaradi spoštovanja do življenja – Levine, Hagai, in Shanna H. Swan. 2015. Is dietary pesticide exposure related to ker je življenje sveto. Imamo družine, ki se odločajo za veliko semen quality? Positive evidence from men attending a fertility clinic. Human število otrok kljub zakonski pravici do abortusa. Ker se za to Reproduction 30, št. 6:1287– 1289. odločijo sami. Da bi še bolj utemeljili naše sklepno spoznanje, se Pearce, Fred. 2008. Peoplequake, Mass Migration, Ageing Nations and the Coming vrnimo k primeru Kitajske. S svojo zakonodajo je kitajska Population Crash. London: Transworld Publishers politika zavrgla življenje kot vrednoto. S političnim odlokom je lahko zmanjšati nataliteto. Ne da pa se z lahkoto zakoncev Pejič Nina, http://ipes-si.org/blog/2019/06/05/kdo-se-bo-postavil-za-naso-pravico- prepričati, da bi bili odprti za življenje svojih otrok. Ekonomska do-splava/ rast in kitajsko potrošništvo je razlog, da Kitajci tudi po odpravi STA: https://www.sta.si/3070806/kitajska-ob-upadanju-rodnosti-z-novimi- »zakonodaje omejevanja rodnosti« ostajajo pri enem otroku ali spodbudami-za-mlade-druzine celo brez njih. Tragedija kitajskih političnih odločitev je ta, da so uničili vrednote, sedaj pa jih ne morejo kar tako, čez noč, uvesti Strehovec, Tadej. 2019, v: Gams, Matjaž, in Janez Malačič, ur. Bela knjiga slovenske demografije. Ljubljana: Inštitut Jožef Stefan, str. 92-95. v človekovo mentaliteto. Za življenje kot vrednoto vzgaja tudi Katoliška Cerkev. Nekateri jo zaradi tega okarakterizirajo kot Sveto pismo zaostalo, pravijo, da živi še v srednjem veku, ker zagovarja življenje kot vrednoto. Toda, ne gre za vprašanje, ali Svetovna populacija – temeljni demografski podatki. Vir: neka https://www.worldometers.info/world-population vrednota izhaja iz Biblije, iz »srednjega veka« ali pa se je rodila ŠIRCELJ, Milivoja. Rodnost v Sloveniji od 18. do 21. stoletja. Statistični urad med komunistično revolucijo. Vprašanje, ki je pomembno, je Republike Slovenije, Ljubljana, 2006. naslednje: Katera vrednota človeštvu omogoča življenje in 21 Kompendij družbenega nauka Cerkve, čl . 244. 23 Blangiardo, Giancarlo, in Simona Maria Mirabelli, ur. 2012. I Vescovi europei 22 Katekizem Katoliške Cerkve, čl. 2211 . su demografia e famiglia in Europa. Siena: Edizione Cantagalli. 24 Deklaracija človekovih pravic, člen 19. 325 Pomen izkušenj iz izvorne družine za razumevanje povezave med obrambnimi mehanizmi in tveganim uživanjem alkohola* The importance of experiences from the family of origin for understanding the link between defense mechanisms and hazardous alcohol use Saša Poljak Lukek Katedra za zakonsko in družinsko terapijo ter psihologijo in sociologijo religije Teološka fakulteta/Univerza v Ljubljani Ljubljana, Slovenija sasa.poljaklukek@teof.uni-lj.si POVZETEK KLJUČNE BESEDE Tvegano uživanje alkohola je pereč in razširjen pojav v naši družbi in mu je zato potrebno nameniti posebno pozornost. alkoholizem, obrambni mehanizmi, izvorna družina, zloraba, čustvena regulacija Obrambni mehanizmi naj bi se povezovali s tveganim vedenjem, v naši raziskavi pa nas zanima ali lahko razložimo vlogo ABSTRACT obrambnih mehanizmov pri vzdrževanju tveganega uživanja alkohola z neugodnimi izkušnjami iz izvorne družine. V Hazardous alcohol use is a pressing and widespread raziskavo je bilo vključenih 623 udeležencev. Kot merski phenomenon in our society and needs special attention. Defence pripomočki so bili uporabljeni Vprašalnik o stopnji tveganosti mechanisms are thought to be associated with risky behaviour, pitja alkohola (AUDIT - The Alcohol Use Disorders and in our study we are interested in whether the role of defence Identification Test), Mednarodni vprašalnik o negativnih mechanisms in maintaining hazardous drinking can be izkušnjah v otroštvu (ACE explained by adverse family of origin experiences. The study -IQ - Adverse Childhood included 623 participants. The measures used were the Alcohol Experiences International Questionnaire), Lestvica izvorne Use Disorders Identification Test (AUDIT), the Adverse družine (Family of Origin) vprašalnika STIC (Systemic Childhood Experiences International Questionnaire (ACE-IQ), Therapy Inventory of Change) in Vprašalnik obrambnih stilov the Family of Origin Scale of the Systemic Therapy Inventory (DSQ 40 - Defense style questionnaire). Z raziskavo smo of Change (STIC), and the Defense Style Questionnaire (DSQ potrdili razlike med posamezniki glede na stopnjo tveganega 40). The study confirmed differences between individuals in the uživanja alkohola v uporabi nezrelih obrambnih mehanizmov use of immature defence mechanisms (devaluation, dissociation, (devalvacija, disociacija, razcep in racionalizacija). Nadaljnje splitting and rationalisation) according to their level of raziskovanje korelacij teh obrambnih mehanizmov pa so hazardous alcohol use. Further exploration of the correlations of pokazale statistično pomembne pozitivne povezave: zloraba these defence mechanisms revealed statistically significant positive associations: substance abuse in the family of origin is substanc v izvorni družini se pozitivno povezuje z pogostostjo positively associated with the frequency of use of devaluation uporabe devalvacije in razcepa v odraslosti, izkušnja zlorabe in and splitting in adulthood, the experience of abuse and negative negativno vzdušje v izvorni družini se pozitivno povezuje z atmosphere in the family of origin is positively associated with uporabo disociacije kot obrambnega mehanizma, vsiljivost v the use of dissociation as a defence mechanism, and izvorni družini se pozitivno povezuje z racionalizacijo. V intrusiveness in the family of origin is positively associated prispevku podamo možno interpretacijo pomena izkušenj iz with rationalisation. In this paper, we provide a possible izvorne družine za razumevanje tveganega uživanja alkohola. interpretation of the relevance of the family of origin experience for understanding risky drinking. ∗ Doseženi rezultati so delno nastali v okviru projekta št. J5-2570, ki ga je financirala Javna agencija za raziskovalno dejavnost Republike Slovenije iz KEYWORDS državnega proračuna. alcoholism, defence mechanisms, family of origin, abuse, 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 emotional regulation 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 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 326 1 TVEGANO UŽIVANJE ALKOHOLA postanejo nefunkcionalni [11]. Posameznik v tem primeru lahko doživlja nevarnost, kjer je realno ni ali pa se ne odzove Glede na nacionalno raziskavo o uporabi alkohola v Sloveniji primerno na dejansko nevarnost, pred katero se je potrebno [1] 68% oseb zmerno pije, vsak drugi se je v zadnjem letu vsaj zaščititi. V naši raziskavi izhajamo iz razdelitve obrambnih enkrat visoko tvegano opil in vsak deseti Slovenec(ka) pije mehanizmov na tri osnovne skupine: zreli obrambni mehanizmi alkohol v čezmerni količini, med katerimi so bolj pogosti (odražajo zdrav in zaveden odnos z realnostjo), moški nevrotični ; med ranljive skupine pa spadajo moški in ženske z osnovnošolsko obrambni mehanizmi (odražajo izogibajoče vedenje) in nezreli izobrazbo ali manj, moški in ženske v starosti obrambni mehanizmi (odražajo zaviranje čustvenega zavedanja) 15-17 in 18-24 let, moški in ženske, ki živijo brez partnerja, šolajoči se ženske [13]. Predhodne raziskave [9,10,11] kažejo predvsem na in moški in moški iz spodnjega povezavo med tveganim pitjem alkohola in nezrelimi socialnoekonomskega razreda. Tvegano uživanje alkohola je obrambnimi mehanizmi, zaradi česar smo v našo raziskavo tako razširjen pojav in mu je zato potrebno nameniti posebno vključili le dimenzijo nezrelih obrambnih mehanizmov. pozornost in razumevanje. Raziskave kažejo, da zasvojeni posamezniki v primerjavi s Duševne motnje povezane s tveganim uživanjem alkohola opredeljujemo kot odvisniško vedenje, ki je motivirano bodisi z kontrolno skupino pogosteje uporabljajo pasivno agresijo, izolacijo, zanikanje, disociacijo in racionalizacijo [11] ter iskanjem užitka ali z somodestruktivnimi motivi. Z vidika duševnega zdravja diagnosticiramo alkoholizem kot vzorec odigravanje in razcep [10]. škodljivega uživanja psihoaktivne snovi (alkohola), ki povzroča okvare zdravja in sindrom odvisnosti, za katerega je značilna 3 IZKUŠNJE IZ IZVORNE DRUŽINE močna želja po zaužitju alkohola, vztrajanje pri uživanju kljub škodljivih posledicam, večje posvečanje uživanju alkohola kot Zgodnje travmatične izkušnje vplivajo na razvoj možganov in povzročajo disregulirane odzive na biološki stres, zaradi česar drugimi aktivnostim in obveznostim, povečano toleranco in včasih telesne motnje zaradi odtegnitve snovi povečujejo možnost razvoja zasvojenosti z alkoholom [2]. Čeprav [5]. tvegano uživanje alkohola pogos Odnosi v zgodnjem razvoju namreč obl to povezujemo z odvisniškim ikujejo samoregulativne vedenjem, pa sodobne paradigme poudarjajo, da je v ozadju mehanizme, ko starši igrajo pomembno vlogo v čustveni takega vedenja močna psihična bolečina [3] in da lahko regulaciji otrok kot zunanji podporni sistem, ki pomaga alkoholizem razumemo tudi kot kronično fizično bolezen, saj uravnavati nova čustvena stanja [14]. Odrasel človek je tako uporaba alkohola trajno spremeni in tudi poškoduje biološko sposoben regulacije čustvenega stanja, ki jo kot spremembo ravnovesje v možganih [4]. Tvegano uživanje alkohola tako telesnega stanja prepoznamo v sebi (regulacija afekta v sebi) in lahko razumemo kot način n tudi vplivanja na doživljanje, čustvovanje in vedenje drugega eprimerne regulacije notranje napetosti oziroma motnjo samoregulacije, katero lahko (regulacija afekta v drugem) [15]. Osebe, ki so bile povezujemo s travmatično izkušnjo izpostavljene travmi pa imajo težave pri integraciji travmatičnih [5,6], z oblikami ne-varne izkušenj in navezanosti [3], kot sistemsko prilagoditev odnosov na tudi motnje v sistemu regulacije afekta [16], ki jo prepoznamo kot pretirano doživljanje afekta oziroma odsotnost nefunkcionalne vzorce vedenja [7] oziroma kot način soočanja afekta. Močno psihično bolečino, ki jo posameznik doživlja oziroma kot posledico uporabe nezrelih obrambnih zaradi disregulacije, pa lahko ublaž mehanizmov [8,9,10]. Psihodinamska teorija predpostavlja, da i s hitro spremembo zasvojenost sprva služi doseganju užitka in lajšanju psihične razpoloženja oziroma z uporabo obrambnih mehanizmov. bolečine, v naslednjem koraku v osredje stopi izogibanje Odvisno vedenje tako v tem kontekstu razumemo kot tesnobi in nazadnje samotolažbi in ohranjanju navidezne samozdravljenje notranje bolečine [3,6] oziroma kot nezavedno psihične stabilnosti [11]. Obrambni mehanizmi pa v vseh uporabo nezrelih obrambnih mehanizmov [10]. Odvisno primerih služijo kot poskus razrešitve neobvladljive psihične vedenje nato nadalje uničuje možganske celice in okvari bolečine. nevrotransmiterske sisteme v možganih [4], kar povzroči kronično motnjo samoregulacije zaradi česar posamezniki niso sposobni funkcionalno regulirati lastnih čustev, se ne primerno 2 OBRAMBNI MEHANIZMI odzivajo na čustva drugih in ne morejo čustveno poskrbeti zase [3] ter se vedno znova zatekajo k nezrelim obrambnim Obrambni mehanizem najpogosteje opisujemo kot relativno nezavedni psihični mehanizem, ki mehanizmom [11]. ščiti pred bolečimi čustvi, mislimi ali situacijami. Sprožajo jih notranji ali zunanji stresorji. Perry [12] definira sedem nivojev obrambnega 4 RAZISKAVA delovanja, od nezrelih do bolj zrelih. Čeprav nezreli obrambni mehanizmi ščitijo osebo pred stisko oziroma notranjim 4.1 Metoda konfliktom, so le-ti manj prilagojeni, oseba se jih pogosto ne S predstavljeno raziskavo smo preverjali na kakšen način lahko zaveda, in pogosto vodijo v negativne izide čustvovanja in povezujemo travmatično izkušnjo iz izvorne družine z razvojem vedenja. Nezreli obrambni mehanizmi so rigidni in zmanjšujejo občutek fleksibilnosti in sposobnost odločanja obrambnih mehanizmov ter na kakšen način lahko s po [8]. Zreli povezavo razložimo tvegano uživanje alkohola. Uporabljeni obrambni mehanizmi so bolj prilagojeni, oseba se jih bolj merski instrumenti so: pogosto zaveda, jih zavestno izbira in uporablja, kar povečuje možnost pozitivnega Vprašalnik o stopnji tveganosti pitja alkohola (AUDIT - The izida. Čeprav imajo obrambni mehanizmi na zač Alcohol Use Disorders Identification Test) [17] . Meri tri vidike etku vedno adaptacijsko funkcijo, lahko s časom izgubijo svoj namen zaščite in zaradi popačenega doživljanja sedan zlorabe alkohola, od katerih bomo v raziskavo vključili josti dimenzijo tveganega uživanja alkohola (nizko tveganje, 327 tveganje ali nevarno pitje, visoko tveganje ali škodljivo pitje, psihično nasilje 5.9 1.8 5.8 1.7 višje tveganje ali odvisnost). fizična zloraba 6.3 1.6 6.6 1.6 Mednarodni vprašalnik o negativnih izkušnjah v otroštvu spolna zloraba 15.9 0.4 15.1 2.3 (ACE-IQ - Adverse Childhood Experiences International Questionnaire). Vprašalnik identificira 13 kategorij negativnih STIC-FOO - skupaj 85.5 15.3 84.7 17.6 izkušenj v otroštvu, od katerih bomo v našo raziskavo vključili pozitivno vzdušje 23.1 0.4 22.2 6.6 naslednje: fizično zlorabo v družini, spolno zlorabo, doživljanje negativno vzdušje 11.9 4.5 13.1 5.3 nasilja nad drugim družinskim članom, čustveno zanemarjanje, vzajemnost 7.7 1.9 7.7 1.8 fizično zanemarjanje in psihično nasilje. zloraba 5.3 2.7 5.1 2.8 Lestvica izvorne družine (Family of Origin) vprašalnika STIC vsiljivost 4.4 2.1 4.4 2.1 (Systemic Therapy Inventory of Change) [18], ki vsebuje 22 zloraba substanc 7.6 3.1 6.3 2.8 postavk, razdeljenih na naslednja področja: pozitivnost vzdušja v izvorni družini, negativnost vzdušja v izvorni družini, DSQ - skupaj 85.1 23.2 79.9 21.9 vzajemnost in jasnost pričakovanj v izvorni družini, prisotnost idealizacija 6.6 4.6 9.2 4.7 fizične zlorabe v izvorni družini, vsiljivost in zlorabo substanc v projekcija 5.4 3.3 5.8 3.8 izvorni družini. pasivna agresija 6.8 4.1 5.5 3.4 Vprašalnik obrambnih stilov (DSQ 40 - Defense style odigravanje 6.1 4.2 6.7 3.6 questionnaire) [13] vsebuje 40 vprašanj, ki so zasnovana za devalvacija 6.1 3.5 5.0 3.2 merjenje psihičnih obrambnih mehanizmov oz. stilov, ki se sanjarjenje 7.4 4.8 7.2 4.6 delijo tri sklope: zreli, nevrotični in nezreli obrambni stili. V zanikanje 7.4 3.6 6.0 3.3 raziskavi bo uporabljen samo del vprašalnika, ki meri nezrele disociacija 8.3 3.8 7.3 3.6 obrambne mehanizme (idealizacija, projekcija, pasivna agresija, razcep 9.6 3.6 8.2 3.9 odigravanje, devalvacija, sanjarjenje, zanikanje, disociacija, racionalizacija 12.9 3.8 13.3 2.9 razcep, racionalizacija, somatizacija). somatizacija 5.4 3.5 6.1 3.6 V raziskavi preverjamo naslednje hipoteze: Opombe: M – aritmetična sredina, SD – standardni odklon H1: Obstajajo statistično pomembne razlike v uporabi nezrelih obrambnih mehanizmov med posamezniki z različnimi Primerjava značilnosti razlik med povprečji s testom ANOVA stopnjami tveganega uživanja alkohola. je pokazala, da obstajajo statistično pomembne razlike med H2: Neugodne izkušnje iz izvorne družine se pozitivno skupinami glede na oceno stopnje tveganega pitja alkohola v povezujejo s pogostostjo uporabe nezrelih obrambnih uporabi nezrelih psihičnih obrambnih mehanizmov devalvacije mehanizmov. (sig. 0,004), disociacije (sig. 0,039), razcepa (sig. 0,002) in racionalizacije (sig. 0,002). Ugotavljamo, da obstajajo 4.2 Udeleženci statistično pomembne razlike v uporabi nezrelih obrambnih Raziskava vključuje 623 udeležencev. 27 % moških in 73 % mehanizmov med posamezniki z različnimi stopnjami žensk, 64,6 % udeležencev je starih manj kot 40 let, 29,2 % tveganega uživanja alkohola. S POST-HOC testom smo udeležencev je samskih, 62,3 % udeležencev je v zakonska ugotavljali pomembnost in smer razlik med posameznimi oziroma izvenzakonski skupnosti, 35,4 je študentov in 42,7 je skupinami (Tabela 2). Ugotavljamo statistično pomembno zaposlenih. povezanost skupine z nizkim tveganjem uživanja alkohola in ostalimi skupinami. Smer povezanosti pa kaže na dejstvo, da v 4.3 Rezultati primeru obrambnega mehanizma devalvacije skupina z nizkim tveganjem dosega statistično pomembno nižjo stopnjo devalvacije; skupina z škodljivim pitjem dosega statistično Tabela 1: Opisne statistike za lestvice tveganega pitja pomembno višji nivo disociacije kot ostale skupine, skupina z alkohola (AUDIT), lestvice negativnih izkušenj v otroštvu odvisnostjo pa dosega višje višji nivo razcepa od skupine z (ACE-IQ), lestvica izvorne družine (STIC-FOO) in lestvice nizkim tveganjem ter nižji nivo racionalizacije od skupine z obrambnih mehanizmov (DSQ) nizkim tveganje in od skupine z nevarnim pitjem. Lestvica Moški Ženske M SD M SD Tabela 2: Prikaz statistično pomembni razlik v uporabi AUDIT - skupaj 13.3 12.1 3.4 2.7 obrambnih med skupinami glede na stopnjo tveganega tvegano uživanje uživanja alkohola 5.7 3.9 0.5 1.6 odvisnost 2.8 3.8 1.4 3.0 posledice 4.8 5.4 5.2 6.4 MD SD Sig. deval- nizko nevarno -1.196* 0.478 0.013 ACE-IQ vacija tveganje pitje čustveno zanema. 6.6 2.2 6.7 2.1 odvisnost -1.262* 0.458 0.006 fizično zanema. 11.1 1.6 11.2 1.5 disoci- škodljivo nizko 3.542* 1.230 0.004 družinsko nasilje 9.1 2.4 9.2 2.4 acija pitje tveganje 328 nevarno nost 3.224* 1.302 0.014 pitje zloraba -0.001 .114* 0.021 -0.001 .137** odvisnost 3.355* 1.296 0.010 razcep odvisnost nizko 1.764* 0.536 0.001 vsiljivost 0.008 0.020 0.093 -.102* .219** tveganje Racio- odvisnost nizko zloraba -1.558* 0.429 0.000 .107* 0.093 .110* -0.054 .182** nalizacija tveganje substanc nevarno -1.437* 0.565 0.011 pitje Opombe: * pomembnost na nivoju 0,05; ** pomembnost na Opombe:* razlika je pomembna z 0.05% tveganjem, MD – nivoju 0,01; DSQ - lestvice obrambnih mehanizmov; ACE-IQ - razlika med aritmetičnimi sredinami; SD – standardni odklon. lestvice negativnih izkušenj v otroštvu; STIC-FOO lestvica izvorne družine vprašalnika STIC. Nadaljnja analiza korelacij nezrelih obrambnih mehanizmov, za katere smo dokazali razlike, z izkušnjami iz izvorne družine pa 5 RAZPRAVA je pokazala nekatere statistično pomembne povezave (glej Tabela 3). Ugotavljamo, da hipoteze o tem, da se neugodne Tako kot predhodne raziskave [10,11], tudi predstavljeni izkušnje iz izvorne družine pozitivno povezujejo s pogostostjo rezultati potrjujejo razlike v uporabi nezrelih obrambnih uporabe nezrelih obrambnih mehanizmov ne moremo v celotni mehanizmov med osebami z odvisniškim vedenjem in med potrditi. Poleg pozitivnih povezav med nezrelimi obrambnimi osebami z nizkim tveganjem uporabe alkohola. Razlike so se mehanizmi in neugodnimi izkušnjami iz izvorne družine (npr. pokazale le pri nekaterih nezrelih obrambnih mehanizmih devalvacija in razcep se pomembno statistično pozitivno (devalvacija, disociacija, razcep in racionalizacija), medtem ko povezujeta z zlorabo substanc v izvorni družini), ugotavljamo za ostale ne moremo dokazati statistično pomembnih razlik tudi nekatere pozitivne povezave med nezrelimi obrambnimi glede na stopnjo tveganega uživanja alkohola. Tako mehanizmi in ugodnimi izkušnjami iz izvorne družine (npr. ugotavljamo, da osebe z večjo stopnjo tveganega uživanja racionalizacija se pomembno statistično pozitivno povezuje z alkohola bolj pogosto uporabljajo obrambni mehanizme pozitivnim vzdušjem in vzajemnostjo v izvorni družini) in devalvacije pri obrambni pred nezaželenimi čustvenimi nekatere negativne povezave med obrambnimi mehanizmi in doživljanji oziroma tesnobo. Devalvacija je obrambni neugodnimi izkušnjami iz izvorne družine (npr. devalvacija se mehanizem, ki vključuje zanikanje pomembnosti nečesa ali statistično pomembno negativno povezuje s fizičnim nekoga, vključno s samim seboj [12]. V povezavi s tveganim zanemarjanjem in psihičnim nasiljem v izvorni družini). uživanjem alkohola lahko predvidevamo, da osebe z bolj tveganim vedenjem svojo tesnobo bolj pogosto poskušajo umiriti z razvrednotenjem odnosov, v katere so vključeni in tudi Tabela 3: Korelacije med obrambnimi mehanizmi in z razvrednotenjem samega sebe. Devalvacija pa je lahko tako izkušnjami iz izvorne družine posledica odvisnega vedenja ali pa izvor le tega. Relacijska paradigma devalvacijo razume kot posledico prekinitve stika DSQ [19] oziroma kot nezadovoljene relacijske potrebe [20], ko se deval- disoci- razcep racio- SKU posameznik zaradi pretirane tesnobe v odnosu zateče v vacija acija naliza- AJ doživljanje razvrednotenja. Ugotavljamo tudi, da skupina s cija škodljivim pitjem alkohola bolj pogosto doživlja disociacijo od ACE-IQ vseh ostalih skupin (tudi od skupine visokega tveganja oziroma čustveno -0.050 -0.048 -0.061 0.022 -.114* odvisnost). Disociacija je obrambni mehanizem kjer se zanemar. nasprotujoči se impulzi razcepijo oziroma se ogrožajoči občutki fizično ločijo od -.133** -0.036 -0.033 0.031 -0.088 ostalega psihičnega doživljanja [12] in iz rezultatov zanemar. lahko predvidevamo, da je najbolj ogrožajoča za razvoj družinsko škodl -0.049 -0.036 -0.028 0.026 -.113* jivega pitja alkohola, ne pa tudi odvisnosti. Razcep nas. pomeni delitev doživljanja v skrajno dobrega ali negativnega in psihično -.098* -0.058 -0.023 0.045 -.133** racionalizacija pomeni dajanje racionalnih razlogov nasilje nesprejemljivemu doživljanju [12] in rezultati kažejo, da je bolj fizična 0.021 -0.040 0.035 -0.068 -0.018 pogost pri osebah z odvisnostjo kot pri osebah z nizkim zloraba tveganjem pitja alkohola. Racionalizacija pa se glede na spolna rezultate bolj pogosto povezuje z nižjim tveganjem p 0.048 -0.025 0.074 -0.003 0.013 itja zloraba alkohola, saj osebe z nižjim tveganjem dosegajo statistično pomembno višje rezultate od skupine z odvisnostjo. STIC- -0.045 -0.078 -0.032 .105* -.176** Racionalizacij kot iskanje logičnih razlogov za utemeljitev FOO nesprejemljivega vedenja [12] se tako kaže kot najbolj pogost pozitivno -0.024 -0.011 0.034 .119* 0,080 obrambni mehanizem škodljivega pitja alkohola. vzdušje Korelacije v raziskavi pa kažejo na povezavo teh obrambnih negativno 0.082 .098* 0.046 -0.059 .212** mehanizmov z izkušnjami iz izvorne družine. Zloraba substanc vzdušje v izvorni družini se pozitivno povezuje z pogostostjo uporabe vzajem- 0.027 -0.009 -0.009 .183** -0.071 devalvacije in razcepa v odraslosti. 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Travmatične izkušnje zlorabe v zgodnjem otroštvu nedvomno povečujejo možnost, da bodo te osebe v Doseženi rezultati so nastali v okviru projekta odraslosti razvile katero zasvojenost, saj zgodnja travma št. J5-2570, ki ga je financirala Javna agencija za podpira neustrezno čustveno regulacijo in regulacijo raziskovalno dejavnost RS iz državnega proračuna. avtonomnega živčnega sistema. V tem kontekstu imamo v mislih t. i. odvisne možgane, ki ves čas iščejo način, kako bi dosegli regulacijo, stabilnost in pomiritev (amigdale) 1 KDAJ GOVORIMO O ZASVOJENOSTI? [1]. V teoretičnem prispevku bomo najprej predstavili glavne komponente, ki so značilne za vsako zasvojenost Zasvojenost je način bega, iskanja sprostitve, varnosti in ter nadaljevali z opisom stopenj, v katerih se izmenjuje nadzora. Otopi bolečine in močne občutke, potlači dinamika sramu s fazo izživljanja in fazo zadrževanja. Za spomine, ki niso sprejemljivi, in je lahko eden od načinov, lažje razumevanje, zakaj se zlorabljeni največkrat vedno kako preživeti s posledicami travme, kot je tudi zloraba znova vrtijo v začaranem krogu sramu, strahu, gnusa, jeze [2]. Raziskava narejena v Sloveniji [3] kaže, da je bilo med in podobnih težkih čutenj, ki spominjajo na izvorno vključenimi 18% spolno zlorabljenih, povprečno vsaka zlorabo, bomo osvetlili dinamiko kompulzivnega šesta oseba. Od tega 19% žensk (približno vsaka peta) in ponavljanja v kontekstu kemično-hormonske 15% moških (približno vsak sedmi). zasvojenosti. Pogoj za prekinitev zasvojenosti je popolna Različni avtorji [4, 5, 6, 7] različno definirajo abstinenca in razreševanje psihičnih stisk, zaradi katerih je zasvojenosti, vsem opisom pa je skupnih pet komponent: zasvojeni vedno znova posegel po zasvojenosti, da je 1. Nadaljevanje zasvojitvene aktivnosti ali vedenja zapolnil čustveno praznino. ne glede na negativne posledice. 2. Preokupacija oziroma obsesija z zasvojitveno KLJUČNE BESEDE: zasvojenost, zloraba, aktivnostjo, substanco ali vedenjem. kompulzivno ponavljanje, regulacija afekta. 3. Zasvojeni nima nadzora nad zasvojitveno aktivnostjo, substanco ali vedenjem, ampak Abstract: Traumatic experiences of abuse in early ravno obratno – zasvojenost ima nadzor nad childhood undoubtedly increase the possibility that these njim. individuals will develop an addiction in adulthood, as 4. Nivo tolerance se spreminja: za isti učinek je early trauma supports inadequate emotional regulation potrebna vedno večja doza. and regulation of the autonomic nervous system. In this 5. Abstinenčna kriza oz. simptomi umika. Če context, we mean so called dependent brain that is oseba ne dobi ustrezne doze, se pojavijo psihični constantly looking for a way to achieve regulation, in telesni simptomi (tesnoba, nemir, nespečnost, stability and reassurance (amygdala) [1]. In the theoretical strah, jeza, …), ki največkrat ponovno vodijo v contribution, we will first present the main components zasvojitveno aktivnost ali vedenje, ki pomiri that are characteristic of each addiction and continue with posameznika. Bolj kot se zasvojeni trudi, da bi a description of the stages in which the dynamics of shame abstiniral, hujše postajajo njegove težave. alternate with the phase of experiencing and the phase of retention. In order to better understand why the abused Zasvojenost je tako psihična kot organska. Na organskem often turn again and again in a vicious circle of shame, nivoju govorimo o kemični in hormonski zasvojenosti, na fear, disgust, anger and similar difficult feelings that psihičnem nivoju pa predstavlja nesposobnost remind of the original abuse, we will shed light on the posameznika, da bi reguliral težka čustva, hkrati pa tudi dynamics of repetition compulsion in the context of nesposobnost, da bi vzpostavil pristne odnose z drugimi chemical-hormonal addiction. The condition for breaking [8]. the addiction is total abstinence and the resolution of the psychological distress that caused the addict to reach for Smith [9] opredeli zasvojenost kot kompleksno kronično the addiction again and again to fill the emotional bolezen možganov v področjih, ki ustvarjajo občutke emptiness. nagrade, motivacije in spomina, z možnimi recidivi, kar predpostavlja, da je bolnik vedno v nevarnosti, saj se pričakuje, da se bo bolezen ponovila. Vsaka zloraba 331 zasvojitvenih substanc vedno aktivira isto nevronsko pot hrane, alkohola, drog, zapravljanja, tveganja in dela …). – dopaminski mezolimbični center za nagrajevanje [10] in Na ta način se sprosti napetost, ublaži bolečina in občutek nevarno spreminja delovanje možganov, dolgoročno pa prikrajšanosti za osnovne življenjske potrebe. povzroči velike spremembe v strukturi in delovanju Zasvojenega v trenutku olajšanja njegovo vedenje možganov, ki zmanjšujejo zavestni nadzor [11]. Podobno popolnoma prevzame, kar onemogoči njegovo sposobnost kot pri drugih kroničnih boleznih, tudi zasvojenost presojanja. V večini primerov se takrat pojavijo sram, pogosto vključuje cikluse zdrsov nazaj v zasvojenost (faza razočaranje in občutek izgubljenosti ter ničvrednosti. Ko recidiva) in remisije bolezni (faza abstinence). Če ne pride izgubi nadzor nad svojim vedenjem, se zasvojeni trudi, da do zdravljena in posameznik ni vključen v proces bi ga spet vzpostavil. To počne na vse mogoče načine, ki okrevanja, postane zasvojenost progresivna in lahko predstavljajo drugo skrajnost zasvojitvenega vedenja. povzroči trajne posledice ali prezgodnjo smrt [12]. Faza se imenuje acting in (npr. kompulzivnost glede diet, Številni avtorji [13, 14, 15, 16] se strinjajo, da travmatične varčevanja, izogibanja seksualnosti, nagibanja k religiji, izkušnje iz otroštva in mehanizmi spoprijemanja s abstinence) – to je faza nadzora. travmatičnimi situacijami, ki so zaznamovale posameznika, lahko vodijo v zasvojenost. Dejstvo je, da zasvojeni ni v stiku s tem, kar je resnično, ali bolje rečeno s svojo bolečino, kadar se preda, popusti zasvojitveni substanci ali vedenju. Podobno je bilo med 2 STOPNJE VSAKE ZASVOJENOSTI zlorabo, ko sta se telo in psiha zavarovala pred bolečino tako, da je prišlo do odklopa, disociacije, sicer kot otrok Zasvojenost se ne zgodi čez noč, ampak pot do nje traja ne bi preživel vseh stisk [2, 19]. Zasvojenost mu vedno tudi več let, z vsemi izkušnjami, ki jih posameznik bolj škoduje in mu le začasno zapolni praznino, ki je v doživlja in odnosi, ki ga oblikujejo. Bradshaw [17] opisuje njegovi notranjosti. Zdržati z vsemi intenzivnimi občutki, stopnje, cikel vsake zasvojenosti. ki prihajajo na dan, s sindromi umika, pa je za zasvojenega 1. Cikel se začne, ko se v notranjosti posameznika največja groza, a edini izhod na pot do okrevanja [19]. začne ustvarjati in naraščati čustven pritisk. Zasvojeni začne razmišljati o svoji zasvojenosti. 2. Nekaj se zgodi, kar še dodatno izzove 3 ZASVOJENOST KOT ANASTEZIJA zasvojitveno (npr. kak konflikt). ALI REGULACIJA AFEKTA 3. Notranji pritisk postane tako neznosen, da zasvojeni teh občutij ne zmore več prenašati in poseže po substanci ali obnašanju (npr. zlorabi Knauer [6] v povezavi z zasvojenostjo uporablja izraz anestezija, s katerim opisuje načine oziroma sredstva, ki nekoga ali se pusti zlorabiti). S tem dejanjem pomiri čustva in zapolni praznino, utiša jih uporabljajo osebe, ki so preživele zlorabo, da lahko bolečino, ki bi jo sicer čutil. funkcionirajo iz dneva v dan s čustveno, včasih celo fizično bolečino. Nekateri so navzven zelo funkcionalni in 4. Zaključni del te stopnje je, ko je oseba, bodo opravljali vsa mogoča dela, bili odgovorni za zasvojeni, popustil, se predal substanci, nekemu vedenju in začne ob tem čutiti krivdo, nizko ogromno nalog in zadolžitev, lahko bi celo rekli, da bodo zasvojeni z delom, da le preusmerijo in ublažijo bolečine samopodobo, sram, strah ... Na tej stopnji lahko zasvojeni celo začuti, da ga je sram, in obljublja, ali le misli na zlorabo. Drugi bodo padli v depresijo in da tega ne bo nikoli več počel, se b bodo brez volje, motivacije in energije, da bi kaj naredili. o opravičeval. Prespali bodo cele dneve, se tolažili s hrano in odpovedovali na vseh področjih. Tako eni kot drugi bodo 5. Obstaja možnost, da bi lahko prišlo do intervencije. Zasvojeni največkrat spozna, da potrebovali ogromno energije in moči, da bodo zadrževali oziroma prikrivali bes in nemoč, ki sta med drugim vsa hrana, droge, alkohol, pornografija ali posledica zlorabe. Avtorica govori o več vrstah anestezije, katero drugo vedenje (npr. zlorabljanje), do katerega pride, ker mora utišati, pomiriti pritisk vsem pa je skupno, da je žrtev, kadar koli se zaplete v neko čustev, ne pomaga in ni prava rešitev za vedenje, tako prevzeta, prav kot suženj gnana od te anestezije, da bi lahko celo rekli, da je v stanju, ki je zelo probleme. Ob tem lahko pride do spoznanja in ukrepanja, da začne pravo rešitev iskati drugje. podobno transu, ki ga povzroči hipnoza. Različne osebe se Nekateri zasvojeni zelo hitro dosežejo ta nivo, bodo različno vedle, da bi si olajšale bolečino zlorabe. Namen anestezije je preusmeritev, odvrnitev pozornosti, pridejo do tega spoznanja, drugi lahko porabijo večino življenja, da naredijo spremembo i žarišča bolečine zlorabe. Načinov, kako žrtve omamijo n se začnejo zdraviti, tretji pa tega ne storijo nikoli in bolečino zlorabe, je toliko, kolikor je načinov zlorabljanja. lahko celo umrejo zaradi zasvojitvene substance Čeprav poznamo razne oblike zasvojenosti, pa je skupni (npr. zbolijo zaradi alkohola, vzamejo imenovalec vsem, da služijo zelo podobnim namenom – prekomeren odmerek droge ...). regulaciji neznosnih psihobioloških stanj v človeku, ki so lahko posledica doživete zlorabe v otroštvu [20]. V tem kontekstu Fossum in Mason [18] govorita o notranji izkušnji sramu pri zasvojeni osebi, ki jo imenujeta »ciklus Zasvojenost dejansko predstavljajo kompulzivno iskanje sramu«. Zasvojeni se izmenično gibljejo od ene skrajnosti rešitve preko ponavljanja določenih vzorcev vedenja, k drugi, kar pa izhaja najpogosteje iz izvirne družine, kjer razmišljanja, čutenja in v svojem najglobljem bistvu so kot otroci morali »delati vse prav«, skušali doseči pomenijo hrepenenje po razrešitvi strahu in groze, nemogoče, da bi le izpolnili potrebe in zahteve staršev, praznine, negotovosti, pomanjkanja samozavesti in samospoštovanja. Gre za globoko željo po odnosu in vendar je bila kljub temu ljubezen do otrok pogojevana. Otroci so tako potlačili svoje želje in potrebe, ki pa kasneje hkrati grozo pred njim, pred čemer se posameznik umika v življenju silijo na površje prek raznih oblik izživljanja v odvisnost, ki kljub svoji destruktivnosti, vseeno prinaša iluzijo varnosti pred občutki izničenja [19]. Težko je ali acting out-a (npr. kompulzivnost glede seksualnosti, 332 razumeti, zakaj globoko ranjeni ljudje največkrat psihoterapija, saj le-ti močno olajša kreacijo novih ponavljajo prav tisto, kar jih še bolj prizadene in rani. nevronskih povezav in pripomorejo k celjenju Odgovor bi lahko iskali tudi v kemično-hormonski travmatičnih izkušenj in k spreminjanju strukture in dinamiki zasvojenosti, ki je pri osebah z zgodovino funkcij možganov [25]. zlorabe lahko zelo močno prisotna. 4.2 Biokemična razlaga kompulzivnega 4 KEMIČNO-HORMONSKA ponavljanja ZASVOJENOST IN KOMPULZIVNO PONAVLJANJE Biokemična razlaga kompulzivnega ponavljanja [19, 26] pa temu dodaja še zasvojitvene hormone, ki se sproščajo Nihče ne ponavlja istih vzorcev zato, ker bi se zaradi njih med samo travmo zlorabe. Ko pride do travmatičnega dobro počutil, ampak zato, ker ne zna, ne more ali še ne dogodka, nevrotransmiterja epinerfin in kortizol sprožita želi drugačne poti, ki je največkrat težja. Ponavljati alarmni sistem telesa. Istočasno se možgani odzovejo s domače, poznano in staro pomeni »cono udobja«, čeprav povečano količino nevrotransmiterjev norepinerfina in se lahko posameznih pritožuje nad svojim življenjem. endorfina v korteksu in limbičnem sistemu. Norepinerfin Narediti novo, drugače pa je tveganje in strah pred opozori možgane na krizo in korteks začne iskati najboljši spremembo [2]. odziv. Približno trideset sekund kasneje, ko se sprosti norepinerfin, možgani poženejo v tek endorfine, ki na 4.1 Psihološka razlaga kompulzivnega osebo delujejo pomiritveno in sprostitveno. Endorfini imajo 2 vlogi: ponavljanja 1. omogočajo jasnejše mišljenje in pomnjenje ter usposobijo osebo, da ostane mirna, in Zelo pomembno je razumeti, da je ponavljanje pretekle 2. delujejo kot analgetik ali sredstvo proti travme prek vseh možnih simptomov (npr. motnje bolečinam. Ko so osebe v šoku, ne čutijo bolečine. Ta šok hranjenja, konfliktni odnosi, psihosomatika, nasilje, je lahko prometna nesreča, izguba uda, fizične zlorabe, zasvojenosti ...) za travmirane ljudi prisila. Četudi si spolne zlorabe ali kaki drugi močni stresi. Bolečina se zavestno želijo potlačiti ta spomin, v njihovi psihi obstaja običajno pojavi šele potem, ko je boleča, vznemirjujoča nasprotna potreba po ozaveščanju potlačenih vsebin. Na ta situacija že mimo. Ko prvi šok mine, se, gledano z način se potlačene in razcepljene izkušnje pojavljajo v biokemičnega stališča, količina norepinerfina, endorfinov novi situaciji na nov način. Chu [21] je to potrebo po in serotonina zmanjša in pojavijo se simptomi umikanja, ponavljanju celo primerjal z biološko potrebo po kot npr. depresija in občutek nemoči. Dolgotrajen stres ali mokrenju, ki je, ko se pojavi, tako nujna, da človek ponavljajoča se travma lahko povzroči umik vase, ki je razmišlja le še o tem, kako bi čim prej lahko pomiril telo podoben tistemu, kakršnega povzroča opij (zanj je in uriniral. Podobno bo tisti, ki ga ženejo afekti, povezani značilna raztresenost, vznemirjenost, šibko tresenje celega s spolno zlorabo, tako dolgo iskal situacijo, osebo, telesa itd.). To pa lahko pripelje do kompulzivnega vzdušje, da bo sprostil to napetost v telesu. Podobne ponavljanja in drugih oblik zasvojenosti. PTSD ali intervale je zlorabljena oseba doživljala ob tistem, ki je ponavljajoča se zloraba lahko dokončno ali trajno zlorabljal. Potem ko je spolno zlorabil, se je vsaj za nekaj spremeni limbični sistem. Temu simptomu pravimo časa umaknil in je morda za žrtev to pomenilo edino mirno ponovno prižiganje. Ko se pojavijo simptomi umika, se obdobje, ki pa se je seveda končalo, ko se je storilec mnoge žrtve prestrašijo, s čimer ponovno povzročijo ponovno približal in ponovil zlorabo. Zloraba gre lahko povišanje količine norepinerfina, pojavi se ponovno celo tako daleč, da spremeni kemično-hormonski sistem prižiganje in žrtev začne spet doživljati začetne fizične in zlorabljene osebe in potem ta znova in znova nezavedno vsiljene simptome. Tako se krog sklene in kompulzivno išče oziroma se zapleta v odnose, v katerih se ponovi ponavlja [2]. zloraba [2, 19]. Lahko bi rekli, da so te osebe dobesedno zvezane oziroma zavezane preteklosti in ti travmatični Na tak način lahko postane nekdo, ki je žrtev hudih travm, dogodki oziroma vzdušja in afekti, ki izhajajo iz teh travm, zasvojen s temi hormoni ter prav zaradi ugodja nenehno oblikujejo njihovo sedanjost. To se dogaja s tako zasvojenosti, ki ga nudijo hormoni, ko se sprostijo, se močjo, da travmirane osebe doživljajo, kot da nimajo težko odreče pravi adrenalinski privlačnosti iskanja izbire, da se jim preteklost enostavno samo ponavlja [22, novih situacij in okoliščin, kjer se travma ali le 23]. Ponavljanje starega je nezavedno edino privlačno, vzdušje lahko ponovi. Tovrstna zasvojenost je poznano, domače, vendar vsakič z upanjem in željo, da se zloraba ne bi ponovila, ampak da bi prišlo do nečesa podobna zasvojenosti z alkoholom ali mamili [27]. novega, do razrešitve in odrešenja – da bi dobili tisto pravo varnost, spoštovanje in ljubezen, ki so jih vedno pogrešali [24]. 5 ZAKLJUČEK Da novo vedenje postane avtomatično, je potrebnih vsaj Zlorabe v otroštvu vsekakor predstavljajo poseben tisoč ponovitev vedenja. Na nevroplastičnost možganov dejavnik tveganja za zasvojenosti v odraslosti, saj se ob (vseživljenjske zmožnosti možganov, da na podlagi novih uživanju substanc ali kompulzivnem ponavljanju izkušenj prerazporejajo nevronske poti), lahko določenega vedenja, sproža izločanje velikih količin posameznik deluje na različne načine: z novimi dopamina, kar posledično prinaša občutke ugodja, izkušnjami, novim učenjem, spreminjanjem starih pomiritve in užitka. spominov z novimi informacijami. Najbolj pa so Klinična praksa, pa tudi raziskave [20] kažejo, da ne glede pomembne nove čustvene izkušnje, kot so osebni in varni na to, kakšno vrsto zlorabe so doživeli posamezniki kot odnosi (partnerski, terapevtski, prijateljski) in otroci ali mladostniki, so v zgodnji odrasli dobi (med 18. 333 in 25. letom) nagnjeni k večjemu tveganju, da bodo [15] G. Maté. Ko telo reče ne. Skriti stres terja davek. Brežice: Primus. zlorabljali psihoaktivne snovi, in sicer ne le eno, ampak 2019. [16] R. West. "Prime theory of motivation and its application to addiction." celo več vrst kot njihovi nezlorabljeni vrstniki. Pri SSA Annual Conference, York, London. 2006. kemičnih zasvojenostih gre najpogosteje za zlorabo [17] J. Bradshaw. Bradshaw on: The family. A new way of creating solid alkohola, nikotina in kanabisa, pri nekemičnih pa za self-esteem. Deerfield Beach, FL: Health Communications. 1996. zasvojenost z odnosi, s hrano, z igrami na srečo, s [18] M. A. Fossum. in J. M. Marilyn. Facing shame: Families in recovery. New York: W. W. Norton & Company. 1986. spolnostjo ter raznimi oblikami nasilja in avotdestrukcije [19] C. Gostečnik. Nevroznanost in relacijska družinska terapija. (npr. samopoškodovanjem). Na podobna spoznanja kažejo Ljubljana: Brat Frančišek in Frančiškanski družinski inštitut. 2021 . tudi izkušnje tistih, ki so bili v otroštvu zanemarjeni. [20] G. Buljan-Flander in D. Kocijan-Hercigonja. Zlostavljanje i zanemarivanje djece. Zagreb: Marko M. usluge d.o.o. 2003. V raziskavi mladostnic [28] se je izkazalo, da so imele [21] J. A. Chu. The repetition compulsion revisited: Reliving dissociated spolno zlorabljene ženske 1,65-krat večjo verjetnost trauma. Psychotherapy 28, št. 2:327-32. 1991. uživanja alkohola, 1,48-krat večjo verjetnost uživanja [22] R. Cvetek. Bolečina preteklosti: travma, medosebni odnosi, družina, terapija. Celje: Celjska Mohorjeva družba. 2010. marihuane in 1,50-krat večjo verjetnost uživanja drugih [23] A. N. Svhore. Early relational trauma, disorganized attachment, and drog kot nikoli spolno zlorabljene ženske. Podobno the development of a predisposition to violence. V: J. D. Siegel in M. F. Hannan s sodelavci [29] meni, da je prav zaradi velike Solomon, ur. Healing trauma: Attachment, mind, body, and brain, 107-67. verjetnosti, da bodo spolno zlorabljene ženske doživele v New York: W. W. Norton & Company. 2003. [24] C. Gostečnik. Relacijska paradigma in travma. 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Psych Central. 2018. accessed 31. januarja 2020. https://psychcentral.com/lib/what-is-sexual- addiction/. 334 Poznejše umikanje iz zaposlitve in nižja indeksacija za izboljšanje dolgoročne vzdržnosti pokojninskega sistema Later withdrawing from the employment and lower indexation for improving long-term sustainability of the pension system Jože Sambt Ekonomska fakulteta, Univerza v Ljubljani Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija Tel: +386 1 5892515; fax: +386 1 5892698 e-pošta: joze.sambt@ef.uni-lj.si POVZETEK KEYWORDS Evropska komisija je leta 2021 objavila Poročilo o staranju – »The Pension expenditures, Population ageing, Slovenia, Indexation of 2021 Ageing Report« [1], kjer je predstavila, da bi bila že v letu 2060 pensions, Staying longer in employment Slovenija država z drugimi najvišjimi izdatki za pokojnine glede na bruto domači proizvod (BDP). V prihodnje bomo namreč priča hitremu naraščanju deleža starih 65 let in več, ki so praviloma v 1 UVOD pokoju, na drugi strani pa zmanjševanju deleža prebivalcev v Evropska komisija je leta 2021 objavila Poročilo o staranju – »The delovni starosti 20-64 let. V tem članku predstavimo domet dveh 2021 Ageing Report« [1], kjer je predstavila, da bi do leta 2070 bila možnih ukrepov za izboljšanje dolgoročne vzdržnosti pokojninskega Slovenija država z drugimi najvišjimi izdatki za pokojnine glede na sistema. Zagovarjamo predvsem daljše ostajanje v zaposlitvi, saj se bruto domači proizvod (BDP). Hitro povišanje je rezultat izrazito glede na druga države v Sloveniji hitro umikamo iz zaposlitve in zaostrenih demografskih razmer, ki jim bomo priča v Sloveniji, hkrati pa ima daljše ostajanje v zaposlitvi močan oziroma dvojno vendar se jim zaenkrat nismo dovolj prilagodili s spremembo pozitiven učinek, saj posamezniki še naprej prispevajo v pokojninske zakonodaje. pokojninsko blagajno namesto da bi začeli iz nje prejemati pokojnino. Močan pozitiven učinek na vzdržnost pokojninskega sistema bi imelo tudi znižanje usklajevanja rasti pokojnin z rastjo 2 DEMOGRAFSKE SPREMEMBE plač. V ozadju pritiska na vzdržnost pokojninske blagajne je hitro staranje prebivalstva Slovenije, ki se bo glede na demografske projekcije KLJUČNE BESEDE nadaljevalo tudi v prihodnjih treh desetletjih. Tudi druge razvite države so soočene s hitrim staranjem prebivalstva, vendar pa je v Izdatki za pokojnine, Staranje prebivalstva, Slovenija, Indeksacija Sloveniji staranje še posebej hitro. Prvič zaradi tega, ker smo imeli pokojnin, Daljše ostajanje v zaposlitvi v 1990-ih in 2000-ih še posebej nizko rodnost, ko je v letu 2003 znašala stopnja celotne rodnosti zgolj 1,2 otroka na žensko, kar je bila ena najnižjih ABSTRACT vrednosti v svetu nasploh. To je bilo skoraj smo In 2021, the European Commission published The 2021 Aging pol toliko kot je potrebno za obnavljanje prebivalstva, to je 2,1 Report [1], where they presented that already by 2060, Slovenia otroka na žensko. Stopnja celotne rodnosti kaže, koliko otrok bi would be the country with the second highest public pensions morala roditi ena ženska tekom svoje rodne dobe, da bi se število expenditures relative to gross domestic product (GDP). In the prebivalstva na dolgi rok obnavljalo. Zahtevana vrednost je v razvitih državah 2,1 rahlo višja future, we will witness a rapid increase in the share of people aged kot povprečno dva otroka na žensko. 65 and over, who will be in retirement, and on the other hand, a Malo več kot dva otroka mora ženska roditi zato, ker mora v decrease in the share of the working age population between age 20 povprečju roditi eno deklico in s tem nadomestiti samo sebe. Med živorojenimi je namreč deklic nekoliko manj kot dečkov, saj znaša and 64. In this article, we present the impact of two possible delež deklic okrog 48,5 measures to improve the long-term sustainability of the pension %, delež fantkov pa okrog 51,5 % vseh system. We advocate above all a longer stay in employment, živorojenih. Hkrati pa tudi v primeru, če ženska rodi eno deklico, ta because compared to other countries, in Slovenia we withdraw from lahko umre preden se ona reproducira tekom svoje rodne dobe. Ker employment early, and at the same time, staying longer in je umrljivost v razvitih državah zelo nizka, je zahtevana višja rodnost employment has a strong or double positive effect, as individuals zaradi tega dejavnika minimalna. Najnovejše tablice umrljivosti za continue to contribute to the pension fund instead of starting to Slovenijo kažejo, da po podatkih za leto 2021 kar 99,1 % žensk receive a pension from it. Reducing the indexation of the pension dočaka starost 40 let, ko je večina rodnosti že realizirana, 98,2 % pa growth to the wage growth would also have a strong positive effect starost 50 let [2], ko je rodna doba povsem zaključena, zato ni on the sustainability of the pension system. potrebno, da bi bila za obnavljanje prebivalstva iz tega naslova rodnost kaj bistveno višja. V državah v razvoju pa tudi npr. vrednost 335 2,3 lahko ni dovolj za obnavljanje prebivalstva, saj je lahko v teh 2050 vrednost tega kazalnika narasla že na 70, torej na več kot državah umrljivost žensk še zelo visoka. dvakrat toliko kot je bila v letu 2019. Drugi dejavnik, ki vpliva na hitro staranje prebivalstva, je hitro podaljševanje življenjskega pričakovanja. Najdaljše življenjsko pričakovanje ob rojstvu na svetu so v letu 1940 imele ženske na 3 UKREPI ZA IZBOLJŠEVANJE Švedskem, in sicer okrog 45 let. V letu 2010 so bile to ženske na DOLGOROČNE VZDRŽNOSTI Japonskem, in sicer že 87,5 let [3]. To pomeni, da se že 180 let POKOJNINSKEGA SISTEMA najvišje življenjsko pričakovanje ob rojstvu podaljšuje za skoraj 2,5 Prikazano zaostrovanje razmerja med starimi 65 let in več ter tistimi leti na desetletje. V Sloveniji v zadnjih nekaj desetletjih je v delovni starosti bo imelo v prihodnje številne ekonomske poviševanje življenjskega pričakovanja ob rojstvu še nekoliko večje, posledice. Med drugim bomo priča močnemu pritisku na saj se je npr. od leta 1982 do 2019 za oba spola skupaj povišalo s javnofinančne izdatke za pokojnine. Gre za velik del 71,0 na 81,6 leta, kar pomeni za 2,9 leti na desetletje [4]. V zadnjih javnofinančnega sistema, ki je v Sloveniji skoraj izključno dveh letih se je zaradi covid-19 nekoliko znižalo, in sicer na 80,6 v financiran skozi javnofinančni sistem, kjer tekoče generacije letu 2020 in 80,9 v letu 2021. zaposlenih skozi prispevke financirajo pokojnine upokojencev. V Tretji, najpomembnejši dejavnik hitrega staranja prebivalstva v sistemih oziroma državah, kjer je financiranje v pomembnem deležu prihodnjih treh desetletjih pa je obstoječa starostna struktura tudi naložbeno, bodo pritiski demografskih sprememb na vzdržnost prebivalstva. Številčno večje generacije se bodo namreč iz delovne pokojninskega sistema v prihodnjih desetletjih manjši. V tem starosti pomikale v starost 65 let in več, na drugi strani bodo v primeru namreč privarčevana sredstva čakajo posameznika ob delovno starost vstopale številčno manjše generacije otrok in mladih. upokojitvi na njegovem računu in za ta del finančno ne obremenjuje Hkrati bodo s tem mlade ženske vstopale tudi v rodno dobo, kar bo kohort zaposlenih. vodilo do zmanjševanja števila živorojenih otrok, kljub temu, da se Evropska komisija na vsaka tri leta objavi projekcije pokojninskih v projekcijah predpostavlja, da bo stopnja celotne rodnosti tekom izdatkov na osnovi najnovejših Eurostatovih demografskih projekcij obdobja projekcij naraščala. Obstoječa starostna struktura in na osnovi makroekonomskih predpostavk, pri oblikovanju katerih prebivalstva je dana, zato so projekcije glede prihodnjega hitrega staranja prebivalstva zelo robustne tudi ob različnih predpostavkah izhaja iz njihovega gibanja v preteklosti. Zadnje poročilo je bilo objavljeno leta 2021 [1]. Slovenija je bila glede javnofinančnih glede prihodnjega gibanja rodnosti, umrljivosti in selitev. izdatkov za pokojnine, ki so znašali 10,0 % BDP, v letu 2019 Selitve, na drugi strani, naj bi v prihodnje blažile staranje približno v sredini razvrstitve EU-27 držav – in sicer na 12. mestu prebivalstva Slovenije, saj naj bi se letno v Slovenijo priseljevalo med 27 članicami EU. Najvišji odstotek sta imeli Grčija z 15,7 % in nekaj čez 5 tisoč prebivalcev [5]. Selijo se pretežno mladi, zato Italija s 15,4 %, najnižjega pa Nizozemska s 6,8 % in Irska s 4,6 %. predpostavljeno neto priseljevanje v demografskih projekcijah blaži Zaskrbljujoče pa so projekcije prihodnjega gibanja javnofinančnih staranje prebivalstva Slovenije. Hkrati so v demografskih izdatkov za pokojnine glede na BDP. Upoštevaje obstoječo projekcijah selitve najbolj negotova kategorija. Zato v Sliki 1 pokojninsko ureditev, Eurostatove demografske projekcije in prikazujemo poleg osnovnega scenarija tudi rezultate za scenarij, če makroekonomske predpostavke Evropske komisije naj bi že do leta selitev ne bi bilo. 2050 javnofinančni izdatki za pokojnine v Sloveniji narasli na kar 15,7 %, kar bi bila druga najvišja vrednost med EU-27 državami, takoj za Luksemburgom z 16,2 % [1]. 80 Podobno kot v drugih EU državah so za hitro povečanje javnih ih 70 izdatkov za pokojnine razlog predvsem demografske spremembe, ki pa se jim z obstoječo pokojninsko ureditvijo zaenkrat še nismo 60 sti staro dovolj prilagodili. Slovenija izstopa z nižjo zaposlenostjo v višjih sn 50 vi starostnih razredih, predvsem v starosti 60-64 let in 65-69 let. V do skladu z veljavno zakonodajo se lahko posameznik upokoji že s 60 40 e leti starosti, če ima 40 let pokojninske dobe. stn 30 o Hkrati je glede na druge države visoka tudi indeksacija pokojnin. Scenarij brez selitev 20 Indeksacija oz. usklajevanje pokojnin z rastjo plač namreč znaša kar t star Osnovni scenarij 60:40, kar pomeni, da se pokojnine povečajo za 60 % rasti 10 povprečne bruto plače in 40 % z inflacijo. Če bi se npr. povprečna eficieno 0 plača v Sloveniji povečala za 4 %, inflacija pa bi znašala 1 %, bi se K 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 pokojnine obstoječim upokojencem povišale za 2,8 % Leto (4*0,60+1*0,40=2,8). Glede na druge države je to zelo visoko usklajevanje, saj jih je v luči dolgoročne vzdržnosti medtem veliko Slika 1: Koeficient starostne odvisnosti starih (število prebivalcev, sprejelo odločitev, da se jim pokojnine usklajujejo samo še inflacijo. starih 65 let in več na 100 prebivalcev v starosti 20-64) [5]. To pomeni, da se upokojencem po upokojitvi življenjska raven ohranja, ne participirajo pa več pri višji produktivnosti zaposlenih, V Sliki 1 vidimo, da bomo v prihodnje v Sloveniji priča zelo ki se zrcali v rasti plač, ki je višja od inflacije. Da so ohranja močnemu povečanju razmerja med starimi 65 let in več na eni strani življenjska raven upokojencev, velja v primeru, če se cene ter številom prebivalcev v delovni starosti (20-64 let) na drugi strani. proizvodov in storitev, ki jih kupujejo upokojenci, gibljejo približno Po najnovejših demografskih projekcijah Eurostata [5] naj bi se to enako kot cene povprečnega potrošnika. V nasprotnem primeru se razmerje, ki se imenuje »koeficient starostne odvisnosti starih« že lahko življenjska raven tekom obdobja upokojitve zvišuje ali do leta 2050 skoraj podvojilo. Leta 2019 je namreč na 100 znižuje, odvisno od gibanja cen v njihovi »porabniški košarici« prebivalcev delovne starosti prišlo 33 prebivalcev v starosti 65 let in glede na porabniško košarico zaposlenih, študentov in drugih več, v letu 2050 pa naj bi to bilo že 60. Če pa ne bi bili deležni podskupin potrošnikov. pozitivnih neto selitev, ki blažijo staranje prebivalstva, bi do leta 336 Glede na opisano sta daljše ostajanje v zaposlitvi in znižanje posameznike, ki še niso upokojeni, medtem ko se za obstoječe indeksacije lahko dva aktualna ukrepa za izboljšanje dolgoročne upokojence ničesar ne spremeni. vzdržnosti slovenskega pokojninskega sistema. V nadaljevanju zato Ukrep, ki pri izboljševanju dolgoročne vzdržnosti pokojninskega prikazujemo nekaj scenarijev možnih sprememb, da dobimo sistema porazdeli breme čez vse generacije pa je indeksacija oz. občutek, kakšen je domet teh dveh ukrepov glede velikosti in usklajevanje rasti pokojnin z rastjo plač. Kot že povedano, se po tempiranja sprememb. Pri tem uporabimo model generacijskih trenutni ureditvi rast plač v 60 % usklajuje z rastjo povprečne bruto računov, razvit s strani Inštituta za ekonomska raziskovanja [6], ki plače, v 40 % pa z rastjo cen življenjskih potrebščin, torej inflacijo. se uporablja tudi pri izračunih, predstavljenih v poročilu od Če gledamo v realnem izrazu, to pomeni, da realna rast pokojnin Evropske komisije [1]. Rezultati osnovnega scenarija so tako enaki znaša 60 % realne rasti povprečne bruto plače. rezultatom, objavljenim v njihovem poročilu »The 2021 Ageing Report« V izračunih predpostavljamo dva scenarija. V prvem indeksacijo v [1], rezultati ostalih scenarijev pa so usklajeni s tem letu 2025 znižamo s sedanje 60 % realne rasti povprečne bruto plače modelom in predpostavkami, pri čemer pa velikosti in tempiranje na 30 %, v drugem scenariju pa na 0 %, kar pomeni da bi se po vzoru ukrepov po posameznih scenarijih oblikujemo sami. številnih drugih evropskih držav pokojnine poviševale samo še V Sliki 2 prikazujemo rezultate efektivnega poznejšega izstopanja iz nominalno z inflacijo, realno pa ne bi več naraščale. zaposlitve glede na osnovni scenarij. Pri tem se ne spuščamo v to, za 18 koliko bi morali spremeniti kombinacijo zahtevane starosti in Osnovni scenarij (sedanja ureditev glede indeksacije, tj. 60:40) pokojninske dobe za upokojitev, da bi dosegli to efektivno daljše 17 Indeksacija 30:70 od 2025 naprej e Indeksacija 0:100 od 2025 naprej ostajanje v zaposlitvi, temveč navedeno efektivno podaljšanje 16 ostajanja v zaposlitvi kar predpostavljano. ojnin 15 pok Vidimo lahko (Slika 2), da bi podaljšanje ostajanja v zaposlitvi za a z 14 dve leti med 2025 in 2032 (za 3 mesece na leto) preprečilo tki DP)B naraščanje javnofinančnih izdatkov za pokojnine da 13 glede na BDP vse iz v % ( do leta 2032. Dolgoročni pozitivni učinek tega ukrepa je nekaj manj 12 čni kot eno odstotno točko, saj bi javnofinančni izdatki za pokojnine v 11 letu 2060 namesto na 16,1 % (osnovni scenarij) narasli na 15,1 %. nofinanv 10 Postopno podaljšanje ostajanja v zaposlitvi za štiri leta med 2025 in Ja 9 2040 (prav tako za 3 mesece na leto) bi javnofinančne izdatke za pokojnine v letu 2060 znižalo na 14,1 %, kar je za dve odstotni točki 8 2020 2025 2030 2035 2040 2045 2050 2055 2060 manj kot v osnovnem scenariju. Leto Slika 3: Javnofinančni izdatki za pokojnine kot % BDP ob znižanju 18 Osnovni scenarij indeksacije s sedanjih 60:40 (rast povprečne bruto plače:inflacija) 17 Dve leti daljše ostajanje v zaposlitvi (obdobje prehoda 2025-2032) na 30:70 oz. 0:100 od leta 2025 naprej [6]. e Štiri leta daljše ostajanje v zaposlitvi (obdobje prehoda 2025-2040) inn 16 Končno prikazujemo še kombinacijo obeh ukrepov – torej ojok 15 podaljševanja ostajanja v zaposlitvi in znižanju indeksacije rasti p za 14 pokojnin na rast povprečne bruto plače. Pri tem prikazujemo samo atki DP)B dve kombinaciji prikazanih posameznih učinkov. Prvi je manj 13 i izd ambiciozen scenarij s podaljšanjem ostajanja v zaposlitvi za dve leti (v % 12 čn in indeksacijo 30:70 od leta 2025, bolj ambiciozen scenarij pa ann 11 fi predpostavlja podaljšanje ostajanja v zaposlitvi za dve leti in 10 indeksacijo 0:100 (torej rast plač zgolj z inflacijo). Javno 9 18 Osnovni scenarij 8 17 Dve leti daljše ostajanje v zaposlitvi in indeksacija 30:70 od 2025 e 2020 2025 2030 2035 2040 2045 2050 2055 2060 Štiri leta daljše ostajanje v zaposlitvi in indeksacija 0:100 od 2025 in 16 Leto ojn 15 Slika 2: Javnofinančni izdatki za pokojnine kot % BDP ob poka z podaljševanju ostajanja v zaposlitvi za dve oz. štiri leta 14 [6]. ki t DP) da B 13 To torej pomeni, da za štiri leta daljše ostajanje v zaposlitvi izi v % ( 12 dolgoročno za približno dvakrat bolj zniža izdatke za pokojnine kot nčn za dve leti daljše ostajanje v zaposlitvi. Učinek je pričakovano 11 proporcionalen, kar pomeni, da eno leto efektivno daljše ostajanje v vnofina 10 zaposlitvi dolgoročno zniža izdatke za pokojnine Ja (glede na BDP) za 9 okrog pol odstotne točke. 8 Ukrep, ki bi z višjo starostjo za upokojitev in/ali zahtevano 2020 2025 2030 2035 2040 2045 2050 2055 2060 pokojninsko dobo povzročil daljše ostajanje v zaposlitvi bi bil Leto logičen ukrep, glede na to, da se nam pričakovano trajanje življenja Slika 4: Javnofinančni izdatki za pokojnine kot % BDP ob znižanju hitro podaljšuje in glede na to, da Slovenija v mednarodnih indeksacije s sedanjih 60:40 (rast povprečne bruto plače:inflacija) primerjavah izstopa po tem, da se hitro umikamo iz zaposlitve [7], na 1) 30:70 in dve leti podaljšano ostajanje v zaposlitvi od leta 2025 [8]. Daljše ostajanje v zaposlitvi ima dvojno pozitiven učinek, saj ter 2) 0:100 in štiri leta podaljšano ostajanje v zaposlitvi od leta posamezniki še naprej delajo in plačujejo prispevke v pokojninsko 2025 [6]. blagajno namesto da bi iz pokojninske blagajne prejemali pokojnine. Daljše ostajanje v zaposlitvi je ukrep, ki prizadene samo 337 V Sliki 4 tako vidimo, da se učinki posameznih ukrepov približno seštevajo, zato ostali dve kombinaciji indeksacije in podaljšanja ostajanja v zaposlitvi ne prikazujemo. Ugotovili smo, da bi že kombinacija podaljšanja ostajanja v zaposlitvi za dve leti in indeksacije 30:70 od leta 2025 naprej dolgoročno znižala javnofinančne izdatke za pokojnine glede na BDP s 16,1 % v letu 2060 na okrog 14 %. Ob tem bi še več kot desetletje izdatki ostajali na približno enaki ravni oz. celo nekoliko nižji ravni kot so sedaj. Kombinacija podaljšanja ostajanja v zaposlitvi za štiri leta in indeksacija 0:100 od leta 2025 pa bi javnofinančne izdatke za pokojnine glede na BDP znižala na okrog 12 % BDP v letu 2060, ob tem ko bi vse do okrog leta 2043 izdatki ostajali na nižji ravni kot so trenutno. 4 ZAKLJUČEK Demografska struktura prebivalstva Slovenije se hitro spreminja. Razmerje med številom starih 65 let in več na eni strani in prebivalci v delovni starosti (20-64 let) se bo hitro poviševalo tudi v prihodnje in bo leta 2060 predvidoma skoraj dvakrat višje kot v letu 2019. Ukrepa, ki bi imela močan pozitiven učinek na dolgoročno vzdržnost, sta podaljševanje ostajanja v zaposlitvi in znižanje indeksacije, torej usklajevanja rasti pokojnin z rastjo plač. Efektivno podaljšanje ostajanja v zaposlitvi za eno leto dolgoročno zniža javnofinančne izdatke za pokojnine glede na BDP za okrog pol odstotne točke. Tako bi se ob štiri leta daljšem ostajanju v zaposlitvi javnofinančni izdatki za pokojnine glede na BDP v letu 2060 znižali s 16,1 % na 14,1 %. Če pa bi hkrati še znižali indeksacijo s sedanjih 60:40 (rast povprečne bruto plače:inflacija) na 0:100 (torej bi bila rast plač samo še z inflacijo, ki naj bi realno ohranjala življenjsko raven), kakor imajo številne druge evropske države, bi javnofinančni izdatki za pokojnine v letu 2060 znašali samo še 12,2 %, kar je porast za zgolj dobri dve odstotni točki glede na leto 2019, ko so javnofinančni izdatki za pokojnine znašali 10 % [6]. LITERATURA IN VIRI [1] European Commission, “The 2021 Ageing Report: Economic and Budgetary Projections for the EU Member States (2019-2070),” 2021. [Online]. Available: https://ec.europa.eu/info/publications/2021-ageing-report-economic-and- budgetary-projections-eu-member-states-2019-2070_en [2] Statistični urad RS, “Skrajšane tablice umrljivosti prebivalstva po spolu, Slovenija, letno,” https://pxweb.stat.si/SiStat/sl/Podrocja/Index/100/prebivalstvo, 2022. https://pxweb.stat.si/SiStatData/pxweb/sl/Data/-/05L4004S.px [3] M. Roser, “Breakdown of life expectancy at birth in total and by gender in Japan from 2001 to 2019.” 2022. Accessed: Nov. 12, 2019. [Online]. Available: https://www.statista.com/statistics/611813/japan-life-expectnancy-total-gender/ [4] Eurostat, “Life expectancy by age and sex,” 2022. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=demo_mlexpec&lang =en (accessed Sep. 13, 2022). [5] Eurostat, “Population projections EUROPOP2019,” 2020. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=proj_19np&lang=en (accessed Aug. 20, 2020). [6] Inštitut za ekonomska raziskovanja, “Model generacijskih računov.” 2022. [7] J. Sambt, B. Hammer, and T. Istenič, “The European National Transfer Accounts: Data and Applications,” Econ. Bus. Rev. , vol. 23, no. 3, p. 4, 2021. [8] J. Sambt and J. Malačič, “Slovenia : independence and the return to the family of European market economies,” in Population aging and the generational economy : a global perspective, R. D. Lee and A. Mason, Eds. Cheltenham, Northampton: Edward Elgar, 2011, pp. 340–353. 338 Vpliv izboljševanja izobrazbene strukture prebivalstva na javnofinančno vzdržnost The impact of improving the educational structure of the population on the financial sustainability of the public sector Jože Sambt† Ekonomska fakulteta, Univerza v Ljubljani Ljubljana, Slovenija joze.sambt@ef.uni-lj.si Tanja Istenič Ekonomska fakulteta, Univerza v Ljubljani Ljubljana, Slovenija tanja.istenic@ef.uni-lj.si POVZETEK tertiary education. Thus, the results show that tertiary-educated individuals pay more into the public financial system than they Prispevek prikazuje rezultate metodologije računov nacionalnih receive from it and therefore they improve the financial transferjev, ki so poleg po starosti razčlenjeni tudi po stopnji sustainability of the public sector that will be in the following izobrazbe. Rezultati kažejo, da imajo višje izobraženi bistveno višji decades under heavy pressure of population ageing. dohodek iz dela kot nižje izobraženi, hkrati je višja tudi njihova potrošnja, vendar je slednje manj izrazito. Višje izobraženi v javno- finančni sistem vplačujejo več davkov in socialnih prispevkov, na KEYWORDS drugi strani pa so deležni višjih prilivov javnih transferjev, predvsem v obliki pokojnin. Izkaže se, da je razmerje med plačanimi in Long-term sustainability of the public system, intergenerational transfers, National Transfer Accounts (NTA), education, Slovenia. prejetimi javnimi transferji enako 0,71 za osnovno izobražene, 0,93 za srednješolsko izobražene in 1,43 za terciarno izobražene. Terciarno izobraženi torej v javnofinančni sistem vplačujejo več kot iz njega prejemajo in tako izboljšujejo finančno vzdržnost 1 UVOD javnofinančnega sistema, ki bo v prihodnjih desetletjih pod močnim Otroci in stari prebivalci porabijo več, kot proizvedejo s svojim pritiskom staranja prebivalstva. delom. Razlika se lahko financira z javnimi in zasebnimi transferji s strani posameznikov v delovni dobi ali pa s sodelovanjem KLJUČNE BESEDE posameznikov na finančnem in kapitalskem trgu (v obliki kredita, prejetih obresti, dividend itd.). V tem prispevku uporabljamo Dolgoročna vzdržnost javnofinančnega sistema, medgeneracijski metodo računov nacionalnih transferjev (angl. National Transfer transferji, računi nacionalnih transferjev (NTA), izobraževanje, Accounts, NTA) za celovito analizo transferjev med starostnimi Slovenija. skupinami. Pretekle raziskave so pokazale, da imajo lahko države zelo različne ureditve za financiranje potrošnje posameznikov v ABSTRACT starosti, ko je potrošnja višja od proizvodnje. Na splošno so v manj razvitih državah sorazmerno pomembnejši zasebni transferji, The paper presents the results of the National Transfer Accounts medtem ko je v razvitih državah veliko funkcij družine prevzel methodology, decomposed not only by age but also by education javni sektor. Vendar pa so tudi med razvitimi državami lahko level. The results show that the higher educated earn more than the ureditve zelo različne. Na primer, v ZDA se starejši v večji meri less educated, and at the same time their consumption is also higher, zanašajo na varčevanje in posledično premoženje kot vir dohodka, but the latter is less pronounced. The more highly educated pay more medtem ko se na Švedskem ekonomsko odvisni posamezniki taxes and social contributions into the public financial system, and močno zanašajo na javni sektor. V tem prispevku razširimo on the other hand, they receive higher public transfer inflows, mainly standardne rezultate NTA z razčlenitvijo rezultatov po stopnji in the form of pensions. It can be seen that the ratio between public izobrazbe. Posamezniki z osnovno, srednješolsko in terciarno transfers paid and received is 0.71 for those with primary education, izobrazbo namreč različno prispevajo v javnofinančni sistem in iz 0.93 for those with secondary education, and 1.43 for those with njega različno prejemajo. 339 Slika 1: Dohodek iz dela (YL) in potrošnja (C) za osnovno, 2 METODOLOGIJA IN PODATKI srednješolsko in terciarno izobražene; Slovenija, 2010 Za analizo ekonomskih tokov med različnimi starostnimi skupinami moramo oceniti velik nabor starostnih profilov (t.j. povprečnih vrednosti posameznih ekonomskih kategorij v posameznih starostih), ki sestavljajo standardni nabor rezultatov NTA. Javni transferji na strani prilivov vključujejo javne transferje v denarju in naravi, kot so npr. javno financiranje izobraževanja, zdravstva in pokojnin [1], [2]. Na strani odlivov pa javni transferji vključujejo davke in socialne prispevke, ki jih posamezniki plačujejo. Zasebni transferji vključujejo tokove znotraj gospodinjstev (t.j. med člani gospodinjstva) in tokove med (različnimi) gospodinjstvi. Javne in zasebne prerazdelitve sredstev vključujejo dohodke od kapitala, zasebne prihranke, obresti, ki se plačajo na javni dolg itd. Starostni profili se ocenjujejo na osnovi Viri: APG 2010, Eurostat , drugi viri. anketnih in administrativnih podatkov. V tem prispevku predstavljamo rezultate NTA za Slovenijo v letu 2010, kjer večina starostnih profilov temelji na Anketi o porabi gospodinjstev (APG) Tudi Slika 2 prikazuje močno prerazporejanje v okviru javnega [3]. Izračunani relativni starostni profili (relativna razmerja med sektorja. Razlike v vplačilih v javni sistem so tudi tokrat velike. V posameznimi starostnimi razredi) se nato prilagodijo s faktorjem delovni starosti terciarno izobraženi prispevajo v javni sistem skoraj popravka. Ta faktor je tolikšen, da se povprečja posameznih trikrat toliko kot tisti z osnovno izobrazbo in skoraj dvakrat toliko ekonomskih kategorij po starosti (t.j. starostni profili), pomnožena kot tisti s srednješolsko izobrazbo. Hkrati so razlike v prilivih, ki s porazdelitvijo posameznikov po starosti in temi faktorji popravka, jih posamezniki s posamezno stopnjo izobrazbe prejmejo od ravno izenačijo z vrednostjo makroekonomskih agregatov. javnega sektorja, odvisne od starosti. V nižji starosti so prilivi enaki Makroekonomski agregati so prevzeti ali izračunani iz sistema za vse izobrazbene skupine, saj so vsi posamezniki vpisani v nacionalnih računov (angl. System of National Accounts, NTA). osnovnošolsko izobraževanje, hkrati pa tudi predpostavljamo, da Javnofinančne prilive in odlive tako razčlenimo na tri stopnje prejemajo enako zdravstveno oskrbo. Po končani osnovni šoli se izobrazbe: osnovno (ravni ISCED 0-2), srednješolsko (ravni javni prilivi močno zmanjšajo za osnovno izobražene, nekaj let ISCED 3-4) in terciarno (ravni ISCED 5-6). Tiste starostne profile pozneje še za tiste s srednješolsko izobrazbo (ko dosežejo svojo NTA, ki so ocenjeni z uporabo anketnih podatkov, je mogoče stopnjo izobrazbe) in po nadaljnjih nekaj letih še za terciarno razčleniti po stopnji izobrazbe relativno preprosto. Namesto da bi izobražene, ko še oni zaključijo z izobraževanjem. V delovni za posamezne ekonomske tokove izračunali povprečja samo glede starosti skoraj ni razlike med izobrazbenimi skupinami v prejetih na starost, izračunamo povprečja glede na starost in stopnjo prilivih iz javnega sistema. Nekateri javni programi so namreč izobrazbe hkrati. Na drugi strani pa agregatni podatki, razčlenjeni sorazmerni s tistim, kar ljudje prispevajo v javni sistem (npr. po stopnji izobrazbe, običajno niso na voljo. Starostni profili, nadomestila za brezposelnost), drugi pa so celo obratno sorazmerni razčlenjeni po stopnji izobrazbe, so zato prilagojeni na način, da (npr. otroški dodatek). Po upokojitvi pa postanejo javni prilivi (kjer dosežemo skladnost z (nerazčlenjenimi) agregatnimi vrednostmi večino predstavljajo pokojnine) za terciarno izobražene mnogo višji NTA. v primerjavi s tistimi s srednješolsko izobrazbo in še bolj v primerjavi s posamezniki z osnovno izobrazbo. Slika 2: Javni odlivi (TGO) in javni prilivi (TGI) za 3 REZULTATI osnovno, srednješolsko in terciarno izobražene; Slovenija, 2010 Slika 1 prikazuje povprečno potrošnjo in povprečni dohodek iz dela na prebivalca po stopnji izobrazbe. Kot pričakovano, je dohodek iz dela najvišji za terciarno izobražene. Dohodek iz dela terciarno izobraženih je relativno visok, saj terciarno izobraženi zaslužijo več, hkrati pa je višja tudi njihova stopnja zaposlenosti. Dohodek iz dela je najnižji pri posameznikih z osnovno izobrazbo. Enako zaporedje velja tudi za potrošnjo, vendar so razlike tu manjše zaradi davčne progresivnosti, socialnih programov v javnem sektorju in nagnjenosti k varčevanju. Viri: APG 2010, Eurostat, drugi viri. Zasebni transferji potekajo predvsem od staršev k otrokom. Starostni vzorci odlivov zasebnih transferjev so zelo podobni starostnim profilom dohodka iz dela (Slika 1), vendar so zneski manjši, saj posamezniki plačujejo javnemu sistemu le del svojega dohodka. Prilivi v obliki zasebnih transferjev so 340 koncentrirani v nižjih starostnih skupinah. Pri terciarno izobraženih je bila povprečna starost prejemanja 48 let, medtem ko je bila posameznikih so zasebni transferji zanimivo visoki v zgodnjih 50- povprečna starost plačevanja davkov in prispevkov 45 let. Ta razlika ih letih starosti. je približno enaka na vseh ravneh izobraževanja, vendar je bila velikost transferjev (zlasti javnih) za terciarno izobražene veliko večja. Razmerje med plačanimi in prejetimi javnimi transferji je bilo Slika 3: Zasebni odlivi (TFO) in zasebni prilivi (TFI) za 0,71 za osnovno izobražene, 0,93 za srednješolsko izobražene in osnovno, srednješolsko in terciarno izobražene; Slovenija, 2010 1,43 za terciarno izobražene. Spodbujanje višje izobrazbene ravni prebivalstva je tako lahko kanal za izboljševanje finančne vzdržnosti javnega sektorja, ki bo v prihodnjih desetletjih pod močnim pritiskom staranja prebivalstva. Rezultati za Slovenijo so predstavljeni kot prikaz razširitve NTA analize na stopnjo izobrazbe in izpeljavo kazalnikov na podlagi pridobljenih rezultatov. V prihodnosti načrtujemo primerjalno analizo rezultatov vseh EU držav, ki imajo na voljo vse potrebne podatke za te izračune. LITERATURA IN VIRI [1] United Nations, National Transfer Accounts manual: Measuring and Analysing the Generational Economy. New York: United Nations, 2013. [2] T. Istenič, A. Šeme, B. Hammer, A. Lotrič Dolinar, and J. Sambt, “The Viri: APG 2010, Eurostat, drugi viri. European NTA Manual,” AGENTA Public Deliv. Download Httpwwwagenta- Proj.-14-Submitt. Accessed 13 Sept. 2016, 2016. [3] Statistični urad Republike Slovenije, Anketa o porabi v gospodinjstvih 2010. Raven in starostna porazdelitev dohodka iz dela in potrošnje Ljubljana: Statistični urad Republike Slovenije, 2016. imata zelo pomembne gospodarske posledice. Izračunali smo povprečno starost dohodka iz dela, potrošnje, prilivov (javnih in zasebnih) ter odlivov (javnih in zasebnih) za vse tri stopnje izobrazbe. V Tabeli 1 je prikazana povprečna starost za navedene glavne kategorije NTA - razčlenjena glede na stopnjo izobrazbe. Tabela 1: Povprečna starost dohodka od dela (YL), potrošnja (C), javni odlivi (TGO), javni prilivi (TGI), zasebni odlivi (TFO) in zasebni prilivi (TFI) po stopnji izobrazbe; Slovenija, 2010 Slovenija YL C TGO TGI TFO TFI Osnovna 40,6 41,4 42,0 47,3 42,0 26,6 Srednješolska 41,8 42,3 44,9 49,3 42,4 26,7 Terciarna 45,5 43,5 48,3 51,7 48,3 32,3 Viri: APG 2010, Eurostat, drugi viri. V letu 2010 je bil potek zasebnih transferjev po starosti »navzdol«, saj je bila povprečna starost prejemanja zasebnih transferjev 28 let, povprečna starost dajanja zasebnih transferjev pa 45 let. V nasprotju s tem so javni transferji potekali »navzgor«, saj je bila povprečna starost prejema 48 let, medtem ko je bila povprečna starost plačevanja davkov in prispevkov 45 let. Ta razlika je približno enaka na vseh ravneh izobraževanja, vendar je bila velikost transferjev (zlasti javnih) za terciarno izobražene veliko večja. Razmerje med plačanimi in prejetimi javnimi transferji je bilo 0,71 za osnovno izobražene, 0,93 za srednješolsko izobražene in 1,43 za terciarno izobražene. 4 ZAKLJUČEK Metoda Računov nacionalnih transferjev (NTA) se uporablja za celovito analizo tokov med starostnimi skupinami. V tem prispevku uporabimo razčlenitev NTA rezultatov za Slovenijo v letu 2010 glede na stopnjo izobrazbe. Smer poteka zasebnih transferjev (predvsem staršev, ki financirajo potrošnjo svojih otrok) je bila po starosti »navzdol«, saj je bila povprečna starost prejemanja zasebnih transferjev 28 let, povprečna starost dajanja zasebnih transferjev pa 45 let. V nasprotju s tem so javni transferji potekali »navzgor«, saj 341 Funkcionalnost družinskega življenja v družinah z alkoholizmom in odrasli otroci alkoholikov Functionality of family life in alcoholic families and adult children of alcoholics prof. dr. Barbara Simonič Katedra za zakonsko in družinsko terapijo ter psihologijo in sociologijo religije Teološka fakulteta, Univerza v Ljubljani Ljubljana, Slovenija barbara.simonic@teof.uni-lj.si POVZETEK* reasonable need for psychosocial and therapeutic support in their Alkoholizem predstavlja velik javnozdravstveni in družbeni problem. adulthood. Posledice škodljive rabe alkohola prizadenejo posameznika, njegovo družino in širšo okolico in družbo. V družini, kjer je prisoten KEYWORDS alkoholizem, se spremeni družinska dinamika in razvijejo Alcoholism, addiction, family, children, development spremljajoči pojavi, ki so škodljivi za psihosocialni razvoj otroka, posledice tega pa so vidne tudi v odraslosti. Rezultati raziskave, v katero je bilo vključenih 187 odraslih otrok alkoholikov (OOA) in 244 oseb, ki niso OOA, kažejo, da je v primarnih družinah OOA bilo prisotnih statistično pomembno več nefunkcionalnih vidikov 1 ALKOHOLIZEM STARŠEV IN DRUŽINSKO družinskega življenja kot v družinah oseb, ki niso OOA. Več ŽIVLJENJE nefunkcionalnosti v primarni družini pa je statistično pomembno Po podatkih Nacionalnega inštituta za javno zdravje [1] 43 % povezano z vidiki funkcionalnosti v odraslosti, kjer je prisotnih več individualni problemov in manj moči, slabša je regulacija čustev, prav prebivalcev Slovenije, starih 25–64 let, pije visoko tvegano (pije alkohol v količinah ali na način, ki lahko kratko tako je slabša kvaliteta družinskega življenja v trenutnih družinah in - in/ali dolgoročno vodijo do razvoja škodljivih posledic z nižje je zadovoljstvo s partnerskim odnosom. OOA so zaradi slabših aradi alkohola). V času epidemije se je pitje še povečalo, saj naj bi 7,8 do 13,9 odnosov v primarnih družinah bolj ranljivi za razvoj problematičnih % oseb pilo več [2]. Ob takih številkah je veliko tudi oseb, ki jih škodljiva raba okoliščin, zato je utemeljena in smiselna potreba po psihosocialni in alkohola posredno prizadene in zaznamuje. Med njimi so predvsem terapevtski podpori tudi v njihovi odrasli dobi. partnerji in otroci oseb s problematičnim uživanjem alkohola. KLJUČNE BESEDE Alkoholizem staršev ima dolgoročen in uničujoč vpliv na celoten družinski sistem – tako na partnerski odnos, kot na otroke. Alkoholizem, zasvojenost, družina, otroci, razvoj Alkoholične družine imajo v primerjavi z nealkoholičnimi višji nivo konfliktov, borbenosti, obtoževanj in nasprotovanj ter nižji nivo ABSTRACT povezanosti in družinske bližine. Prav tako je prisotna nižja stopnja Alcoholism is a major public health and social problem. The telesnega in verbalnega izražanja pozitivnih čustev, manj čustvene consequences of harmful alcohol use affect the individual, the whole podpore, topline in skrbi med družinskimi člani [4, 5]. Prekomerno family, the wider community and society. In a family where pitje in odvisnost od alkohola negativno vplivata na zadovoljstvo in alcoholism is present, family dynamics are changed and stabilnost v zakonu. Partnerji odvisnih od alkohola izkušajo več stresa accompanying phenomena develop which are harmful to the v zakonu, fizične in psihične zlorabe, pogoste pa so tudi ločitve [6], psychosocial development of the child, with consequences that kar pušča posledice tudi pri otrocih. continue into adulthood. The results of the study, which included 187 Izrazita raba alkohola pri staršu pomembno povečuje tveganje, da bo adult children of alcoholics (ACoA) and 244 non-ACoA, show that in do otroka na nek način zlorabljajoč. Več kot je v družini članov, ki ACoA’s families of origin significantly more dysfunctional aspects of zlorabljajo ali so odvisni od alkohola, bolj bo verjetno, da bodo otroci family life were present than in non-ACoA’s families. However, more v družini zlorabljeni ali zanemarjeni [7]. Prav tako se znatno poveča dysfunctionality in the primary family is significantly associated with tudi tveganje, da bo otrok v odraslosti postal problematičen pivec, kar aspects of functionality in adulthood, where there are more individual potrjujejo rezultati študij o obremenjujočih izkušnjah v otroštvu, ki so problems and less strengths, more difficulties in emotion regulation, velikokrat prisotne v družinah s starši alkoholiki [8]. Prisotnost lower quality of family life in current families and lower satisfaction alkoholizma staršev tudi zelo poveča možnost, da se bo pri potomcih with the partner relationship. ACoA are more vulnerable to the razvila neka oblika mentalne motnje [9]. Otroci alkoholikov pogosto development of problematic circumstances due to less functional kažejo veliko vedenjskih težav, npr. prestopništva, odvisniškega relationships in their primary families, and there is a justified and vedenja, odpora do družbenih norm [10]. Številne družine, ki jih * Doseženi rezultati so nastali v okviru projekta št. J5-2570, ki ga je financirala Javna agencija za raziskovalno dejavnost Republike Slovenije iz državnega proračuna. 342 prizadene pitje staršev, tako utrpijo ekstremno in direktno škodo, lahko pa je ta tudi bolj indirektne oblike, vedno pa je škoda prisotna 3 OPREDELITEV PROBLEMA IN HIPOTEZE [8]. Zloraba alkohola ne vpliva negativno le na posameznika, ki uživa alkohol, temveč tudi na družinski sistem, v katerem alkoholik živi. 2 ODRASLI OTROCI ALKOHOLIKOV Zaradi disfunkcionalnosti staršev alkoholikov, kot je pomanjkanje Odraščanje v družini, ki je zaznamovana z alkoholno zasvojenostjo odgovornosti in neprimerno prevzemanje družinskih vlog, lahko družinsko okolje postane bolj kaotično in nestabilno. V teh razmerah enega ali obeh staršev, ima za otroka težke posledice. V takšni družini se ob travmatičnih okoliščinah pogosto izoblikuje nefunkcionalen se težave pojavijo tudi pri družinskih članih, ki niso alkoholiki. Še starševski pristop, v katerem starši otroku ne nudijo podpore in posebej ranljivi so pri tem otroci, kjer razmere, ki se zaradi odvisnosti zdravega okolja za rast in razvoj, kar pri otroku pušča medosebne, vzpostavijo v družinskem sistemu, vplivajo na njihov psihosocialni čustveno razvoj. Družina je najpomembnejši dejavnik v procesu socializacije -vedenjske in socialne posledice, ki lahko vztrajajo še v odrasli dobi otroka. T. i. »odrasli otroci alkoholikov« (OOA), ki so del otrok, pozitivno družinsko okolje pa je nujno za dobro počutje in ali celo svoje otroštvo odraščali v disfunkcionalni družini, kjer je bil razvoj otrok, kjer se otroci lahko naučijo in razvijejo nekatere osnovne največji problem alkoholna zasvojenost enega ali obeh staršev, so bolj spretnosti, kot je razvoj občutka zdravega jaza, strategij spoprijemanja občutljivi na življenjske stresorje in imajo več prilagoditvenih težav s stresom, kako uravnavati svoja čustva ter vstopati in ohranjati zdrave [11]. V sebi nosijo številna nerešena vprašanja iz otroštva, potlačene in zadovoljujoče intimne odnose (družinske, partnerske). in nerazrešene vsebine, ki sooblikujejo njihovo funkcioniranje v V zvezi s tem nas je v pričujoči raziskavi zanimalo, kakšna je ocena odrasli dobi, ki se velikokrat izkaže za čustveno in socialno nezrelo funkcionalnosti družinskega življenja v primarnih družinah OOA v [12]. Vse to je posledica odraščanja ob starših, ki otroku niso nudili primerjavi z osebami, ki niso OOA in kako se funkcionalni ter varnega in zdravega razvojnega okolja. nefunkcionalni vidiki družinskega življenja povezujejo z nekaterimi Odrasli otroci staršev alkoholikov poročajo o kaotičnem in stresnem vidiki funkcioniranja v odraslosti, kot je doživljanje individualnih otroštvu, ki jih je prikrajšalo za številne potenciale zdravega problemov in moči, regulacija čustev, kvaliteta trenutnega razvoja. Za njihovo otroštvo so bili značilni nepredvidljivost in travme, saj v družinskega življenja in zadovoljstvo s partnerskim odnosom. disfunkcionalnem alkoholičnem družinskem sistemu njihove osnovne Preverjali smo dve hipotezi: potrebe po skrbi in čustveni podpori (razvijanje zdrave samopodobe, 1. OOA so v izvorni družini doživljali več nefunkcionalnosti kot občutka, da so dragoceni in ljubljeni, občutek varnosti) niso mogle biti osebe, ki niso OOA. zadovoljene [13, 14]. Mnogi poročajo o primerih zanemarjanja in slabega ravnanja, na primer o tem, da so ostali sami brez starševskega 2. Bolj kot je nefunkcionalno družinsko življenje v izvorni družini, več nadzora in oskrbe; da so bili izpostavljeni manipulativnemu, je v odraslosti individualnih problemov in manj moči, več je težav v kritičnemu ali odklonilnemu vedenju staršev, odvisnih od alkohola; regulaciji čustev, slabša je kvaliteta trenutnega družinskega življenja bili so priče starševskim konfliktom in partnerskemu nasilju; lahko so in slabše je zadovoljstvo s partnerskim odnosom. bili sami žrtve fizičnega nasilja s strani staršev [13]. Poleg tega OOA pogosto poročajo o izkušnjah neprimernih razmejitev in zamenjave družinskih vlog, kjer je za družinsko življenje značilna večja 4 METODA nepredvidljivost in negotovost zaradi sprememb v vedenju od 4.1 Udeleženci alkohola odvisnega starša in kjer otroci na koncu prevzamejo vloge in odgovornosti odraslih (postaršeni otroci) [15, 16]. V raziskavi je sodelovalo 431 udeležencev, od tega 187 (43,4 %) OOA in 244 (56,6 %) oseb, ki niso OOA. V skupini OOA je bilo 141 žensk Vse to so družinski stresorji, ki pojasnjujejo razvoj in pojavnost in 46 moških, v skupini, ki niso OOA, pa 179 žensk in 65 moških. številnih psihosocialnih zapletov pri OOA. Seveda pa je treba Povprečna starost vseh udeležencev je bila 36 let (min = 18 let; max = opozoriti, da številni otroci staršev, ki imajo težave z alkoholom, 74 let; SD = 14,73). odrastejo v zdrave in funkcionalne osebe, ki se zmorejo v odrasli dobi učinkovito soočati z ranami iz otroštva in obvladovati posledice zgodnjih negativnih izkušenj [17, 18]. Vseeno pa raziskave ugotavljajo, da OOA zaradi izkušnje odraščanja v družini z 4.2 Pripomočki in postopek alkoholizmom staršev gredo skozi življenje s čustvenimi Udeleženci so poleg splošnega vprašalnika o demografskih podatkih brazgotinami. Imajo tudi več fizičnih težav kot osebe, ki so odraščale (spol, starost) izpolnjevali še naslednje vprašalnike: v nealkoholičnih družinah [19]. Prisotne so višje stopnje depresije in 1. Presejalni test otrok alkoholikov (Children of Alcoholics Screening anksioznosti [20], motenj hranjenja, številni živijo v konstantnem test - CAST-6) [24, 25]. CAST-6 samoocenjevalni merski instrument, strahu, da bi tudi sami postali alkoholiki, kar se velikokrat dejansko ki ocenjuje otrokove občutke, vedénje ter izkušnje, povezane z zgodi [21]. V primerjavi z odraslimi iz nealkoholičnih družin imajo uporabo oziroma zlorabo alkohola s strani staršev in kaže, ali obstaja OOA višje stopnje anksioznosti in izogibanja v partnerskih odnosih, možnost, da je anketirani otrok alkoholika. na splošno se lahko bojijo oblikovati navezanost z drugimi odraslimi [22]. Pogosto se čutijo negotove, samoobsojajoče in se bojijo intime. 2. Lestvico izvorne družine (Family of Origin Scale - FOS), ki je del Imajo težave z zaupanjem, odvisnostjo v odnosih, samokontrolo, instrumenta STIC (Systemic Therapy Inventory of Change) [26]. identiteto in izražanjem občutkov [21]. OOA imajo velikokrat težave Ocenjuje naslednja področja družinske funkcionalnosti: pozitivnost na področju doživljanja in reguliranja svojih čustev, saj so v vzdušja v izvorni družini, negativnost vzdušja v izvorni družini, disfunkcionalni družini doživljali veliko čustvenih bremen, obenem vzajemnost in jasnost pričakovanj v izvorni družini, prisotnost zlorabe pa ni bilo prave možnosti za zdrav razvoj regulacije teh čustev. Na v izvorni družini, vsiljivost in zlorabo substanc v izvorni družini. Višji osnovi tega so oblikovali specifične načine doživljanja sebe, drugih in rezultat na skupnem seštevku pomeni več funkcionalnosti v izvorni odnosov [23], ki običajno pomenijo zaplete v vsakdanjem družini. Koeficient zanesljivosti (Cronbachov alfa) za celotni funkcioniranju. vprašalnik v naši raziskavi znaša ɑ=0,938. 343 3. Lestvico individualni problemi in moči (Individual problems and strenghts - IPS), ki je del instrumenta STIC (Systemic Therapy OOA Ni OOA Inventory of Change) [26]. Uporablja se za oceno posameznikovih problematičnih in močnih področij. V skupino problemov se uvrščajo 30 dimenzije: izraženost negativnih afektov, odsotnost inhibicije močnih 24,6 impulzov, fleksibilnost/odpornost, nerazumevanje samega sebe, 25 zloraba substanc. Višji kot so rezultati na teh lestvicah, več težav oz. 19,4 individualnih problemov imajo posamezniki. V skupino osebnih moči 20 se uvrščajo dimenzije: življenjska funkcionalnost, odprtost 14,91 samoizražanja, samosprejemanje. Višji kot so rezultati na teh 15 lestvicah, več individualnih moči imajo posamezniki. Koeficient 11,15 zanesljivosti (Cronbachov alfa) za lestvico posameznikovih 8,51 10 7,9 8,12 problemov v naši raziskavi je sprejemljiv in znaša ɑ=0,682, za 6,42 5,25 dimenzijo posameznikovih moči pa znaša ɑ=0,776. 5,15 4,27 5 3,98 4. Lestvico težav pri regulaciji čustev – krajša verzija (Difficulties in emotion regulation scale – Short form - DERS – SF), ki je kratek 0 samoporočevalni instrument za oceno različnih vidikov čustvene POZITIVNO NEGATIVNO VZAJEMNOST PRISOTNOST VSILJIVOST ZLORABA VZDUŠJE VZDUŠJE IN JASNOST ZLORABE SUBSTANC disregulacije oz. neprimerne regulacije čustev [27, 28] na šestih PRIČAKOVANJ področjih: nesprejemanje čustvenih odzivov, težave pri vedenju, usmerjenemu k določenemu cilju, težave pri kontroli impulzov, Slika 1: Srednje vrednosti na posameznih dimenzijah funkcionalnosti pomanjkanje čustvenega zavedanja, omejen dostop do strategij družinskega življenja v izvornih družinah pri OOA in osebah, ki niso čustvene regulacije in pomanjkanje čustvene jasnosti. Višji rezultat OOA. kaže na večjo prisotnost problemov v čustveni regulaciji. Koeficient Vidimo lahko, da so ocene povprečnih vrednosti pri vidikih zanesljivosti (Cronbachov alfa) za celotni vprašalnik v naši raziskavi funkcionalnosti družinskega življenja v izvorni družini pri OOA v znaša ɑ=0,823. primerjavi z udeleženci, ki niso OOA, višje pri nefunkcionalnih vidikih družinskega življenja (negativno vzdušje, prisotnost zlorabe, 5. Lestvico sedanje družine (Family/Household Scale - FH) ), ki je del vsiljivost, zloraba substanc) in nižje pri funkcionalnih vidikih instrumenta STIC (Systemic Therapy Inventory of Change) [26], s družinskega življenja (pozitivno vzdušje, vzajemnost in jasnost katero smo ocenjevali naslednje dimenzije družinske funkcionalnosti: pozitivno vzdušje v sedanji družini, negativno vzdušje v sedanji pričakovanj). družini, fizično zlorabo v sedanji družini, odločanje v sedanji družini, Statistično pomembnost razlik med skupinama smo zaradi jasnost mej v sedanji družini in občutenje nerazumevanja v sedanji nenormalne distribucije spremenljivk (ugotovljeno s Kolmogorov- družini. Višji rezultat na skupnem seštevku pomeni več Smirnov testom) preverili z Mann-Whitney U-testom za neodvisne funkcionalnosti v sedanji družini. Koeficient zanesljivosti vzorce. Rezultati so pokazali, da obstajajo statistično pomembne (Cronbachov alfa) za celotni vprašalnik v naši raziskavi znaša razlike med obema skupinama v vseh dimenzijah. OOA so v izvornih ɑ=0,866. družinah doživljali statistično pomembno manj funkcionalno družinsko življenje kot osebe, ki niso OOA (U=9986,500; p=0,000). 6. Kansaško lestvico zadovoljstva v zakonski zvezi (Kansas Marital Pri OOA je v primerjavi z osebami, ki niso OOA, bilo v izvornih Satisfaction Scale - KMSS) [29], ki je namenjena ocenjevanju zadovoljstva v zakonski/partnerski zvezi. Višji rezultat pomeni večje družinah prisotnega statistično pomembno manj pozitivnega vzdušja (U=12020,000; p=0,000), več negativnega vzdušja (U=12899,000; zadovoljstvo s partnerskim odnosom. Koeficient zanesljivosti (Cronbachov alfa) za vprašalnik v naši raziskavi znaša ɑ=0,951. p=0,000), manj vzajemnosti in jasnosti pričakovanj (U=15616,500; p=0,000), več zlorabe (U=13660,000; p=0,000), več vsiljivosti Udeleženci so vprašalnik reševali v spletni obliki (povabilo za (U=15385,000; p=0,000) in več zlorabe substanc (U=6452,500; sodelovanje v raziskavi s povezavo do vprašalnika je bilo poslano na p=0,00). različne naslove in forume) in pisno (te udeležence smo pridobili na Hipoteza 2: Bolj kot je nefunkcionalno družinsko življenje v izvorni eni izmed klinik za zdravljenje alkoholizma). Anketiranje je potekalo od junija 2021 do maja 2022. Rezultate smo izračunali z uporabo družini, več je v odraslosti individualnih problemov in manj moči, več je težav v regulaciji čustev, slabša je kvaliteta trenutnega programskega paketa SPSS 20. družinskega življenja in slabše je zadovoljstvo s partnerskim odnosom. 5 REZULTATI Nadalje smo na celotnem vzorcu preverjali, kako se funkcionalnost Hipoteza 1: OOA so v izvorni družini doživljali več družinskega življenja v izvorni družini (skupna dimenzija) pri posameznikih v odraslosti povezuje s posameznimi vidiki nefunkcionalnosti kot osebe, ki niso OOA. funkcionalnosti (individualni problemi in moči, težave v regulaciji Primerjali smo podatke, ki se nanašajo na dimenzije funkcionalnosti čustev, kvaliteta trenutnega družinskega življenja in zadovoljstvo s družinskega življenja v izvorni družini glede na to, ali so udeleženci partnerskim odnosom). Zaradi nenormalne distribucije spremenljivk OOA, ali pa ne (razdelitev v ti dve skupini je bila narejena na osnovi (ugotovljeno s Kolmogorov-Smirnov testom) smo za ugotavljanje vprašalnika CAST-6). Primerjava povprečnih vrednosti teh dimenzij povezanosti uporabili Spearmanov korelacijski koeficient. Iz pri OOA in osebah, ki niso OOA, so prikazane na Sliki 1. rezultatov (Tabela 1) je razvidno, da obstaja trend, da bolj kot je bilo funkcionalno družinsko življenje v izvorni družini, več je pri posameznikih v odraslosti prisotnih osebnih moči (večji so življenjska funkcionalnost, odprtost samoizražanja, samosprejemanje) in manj je osebnih problemov (manj je izraženosti negativnih afektov, odsotnosti inhibicije močnih impulzov, fleksibilnosti/odpornosti, nerazumevanja 344 samega sebe, zlorabe substanc). Obstaja tudi trend, da več kot je je izrazito negativna [32]. Kot poročajo tudi druge raziskave [3, 33], funkcionalnosti v izvorni družini, v manjši meri imajo osebe težave v je tudi po naših rezultatih v družinah z alkoholizmom staršev regulaciji čustev (razen pri dimenziji pomanjkanje čustvenega prisotnega več zlorabljajočega vedenja, ki ga spremlja tudi višja zavedanja, kjer korelacija ni statistično pomembna). Višja stopnja zlorabe substanc pri družinskih članih. Izrazita raba alkohola funkcionalnost izvorne družine je statistično pomembno negativno pri staršu npr. pomembno povečuje tveganje, da bo do otroka na nek povezana z vidiki nefunkcionalnosti v sedanji družini (negativno način zlorabljajoč. Več kot je v družini članov, ki zlorabljajo ali so vzdušje, fizična zloraba, nerazumevanje) in pozitivno z vidiki odvisni od alkohola, bolj bo verjetno, da bodo otroci v družini funkcionalnosti v sedanji družini (pozitivno vzdušje, vključenost v zlorabljeni ali zanemarjeni [7]. odločanje, jasnost mej) ter zadovoljstvom s partnerskim odnosom. Vse te družinske okoliščine predstavljajo dejavnik tveganja za zdrav Tabela 1: Korelacijski koeficienti (Spearmanov rho) med razvoj otrok, ki so izrazito ranljivi na vzdušje v družinski klimi. funkcionalnostjo družinskega življenja v izvorni družini in Družina z dinamiko odnosov je namreč temeljno okolje njihovega individualnim problemi ter močmi, težavami v regulaciji čustev, psihosocialnega razvoja [34]. Aktivnosti in dinamike v družinah, kjer funkcionalnostjo trenutnega družinskega življenja in zadovoljstvom v je prisoten alkoholizem staršev, so podrejene odvisniškemu vedenju. partnerskem odnosu (N = 431). S podrejenostjo odvisnosti je zaznamovana celotna družinska klima. Starševska drža odvisnih staršev je običajno nefunkcionalna, FOS-SKUPAJ nekonsistentna in kaotična, kar za otroke pomeni živeti v nenehni IPS-moči ,303** napetosti in strahu, saj nikoli ne vedo, kaj lahko pričakujejo iz trenutka v trenutek. V teh primerih imajo tudi neprestano občutek, da karkoli IPS-problemi -,326** naredijo, ni prav, na osnovi tega pa se oblikuje občutek, da je nekaj DERS-nesprejemanje čustvenih odzivov -,241** narobe z njimi [6]. Otroci so čustveno zasedeni in podrejeni vzdušju v DERS-težave pri usmerjenosti k cilju -,213** družini. Tipičen odraz tega je prevzemanje različnih vlog v družini (npr. postaršenje), za katere otroci čustveno niso dozoreli [16]. V DERS-težave pri kontroli impulzov -,254** prilagajanju družinskemu stanju poskušajo otroci na svojo škodo DERS-pomanjkanje čustvenega zavedanja -0,061 narediti vse, da ohranjajo ravnovesje v družini in njeno delovanje [35]. DERS-omejene strategije čustvene regulacije -,256** Ti otroci te izkušnje in dojemanje družinskih pravil nosijo s seboj v najstništvo in odraslost in verjetneje zgradijo izkrivljene temelje, na DERS-pomanjkanje čustvene jasnosti -,256** katerih delujejo naprej. Kot otroci so se namreč naučili obnašati na DERS-SKUPAJ -,300** različne načine, ki so jim omogočali preživeti. To vedenje se lahko giblje od kljubovanja avtoriteti do zatiranja lastnih potreb in pretirane FH-pozitivno vzdušje ,495** pozornosti na potrebe drugih [6]. Nefunkcionalna družinska klima FH-negativno vzdušje -,419** (tudi v družinskem sistemu, kjer ni alkoholizma) tako odmeva v FH-fizična zloraba -,265** odraslosti, kar potrjujejo tudi rezultati naše raziskave. Obstaja namreč trend, da več kot je bilo disfunkcionalnosti družinskega življenja v FH-vključenost v odločanje ,264** družinah, kjer so posamezniki odraščali, več težav imajo na različnih FH-jasnost mej ,225** področjih funkcioniranja v odraslosti (na področju osebnih problemov in moči, pri regulaciji čustev, pri doživljanju kvalitete življenja v FH-nerazumevanje -,438** trenutnem družinskem okolju in doživljanju zadovoljstva v FH-SKUPAJ ,484** partnerskem odnosu). KMSS ,275** Čeprav vsi otroci alkoholikov ne odrastejo v odrasle, ki bi ne bili funkcionalni, z našo raziskavo, ki se pridružuje tudi drugim Opombe: FOS – Lestvica izvorne družine; IPS – Lestvica individualni problemi in moči; DERS – obstoječim raziskavam tega področja, izpostavljamo vidno in nevidno Lestvica težav pri regulaciji čustev; FH – Lestvica sedanje družine; KMSS – Kansaška lestvica zadovoljstva v zakonski zvezi; ** – tveganje, ki so mu izpostavljeni otroci alkoholikov v svojih primarnih statistično pomemben rezultat na nivoju 1 % tveganja. družinah, posledice pa so vidne tudi v odrasli dobi. Rečemo lahko, da so OOA (skrite) žrtve alkoholizma staršev in zato je utemeljena potreba po psihosocialni in terapevtski podpori tudi takrat, ko so že 6 RAZPRAVA IN SKLEP zapustili svoje primarno družinsko okolje in ustvarili novega. 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Tanja Valenta Katedra za zakonsko in družinsko terapijo ter psihologijo in sociologijo religije Teološka fakulteta, Univerza v Ljubljani Ljubljana, Slovenija tanja.valenta@teof.uni-lj.si POVZETEK1 body, as they upset the entire hormonal system. Because Odvisnost od alkohola in njegova tvegana raba je pogosto individual lacks functional emotional regulation skills, povezana z manj funkcionalno regulacijo čustvenih they often tried to compensate for the lack of functional odzivov [1]. Alkoholizem pa predstavlja velik družbeni in regulation with a form of dysfunctional regulation. Our zdravstveni problem. Ko ima oseba funkcionalne research statistically significantly shows that one of the sposobnosti čustvene regulacije, lahko prepoznava čustva forms of dysfunctional regulation of an individual's in lahko kontrolira njihovo izražanje. Nasprotno, oseba z emotional state is the risky use of alcohol. nefunkcionalnimi veščinami čustvene regulacije se svojih In our paper, we present the results of the research, which čustev ne zaveda, zato so njihova dejanja lahko zelo show statistically significant connections between impulzivna. Nefunkcionalno regulirani čustveni odzivi different dimensions of dysfunctional emotional povzročajo v telesu neobvladljivo stisko, saj vznemirijo regulation and risky alcohol use. 478 adults participated in celoten hormonski sistem (hipotalamus-hipofizo- the research. The correlation between individuals who are nadledvično (HPA) os). Kadar posameznik nima less aware of emotions (DERS emotional awareness funkcionalnih veščin čustvene regulacije, nezavedno dimension) and risky alcohol use is particularly strong. poskuša nadomestiti pomanjkanje funkcionalne regulacije The results shown indicate the need for psychotherapeutic z obliko nefunkcionalne regulacijske oblike. Naša treatment, as it could enable individuals to face problems raziskava statistično pomembno kaže, da je ena od oblik in emotional regulation and regulate their emotions more nefunkcionalne regulacije čustvenega stanja posameznika functionally and resort less to the risky use of alcohol. tvegana raba alkohola. V našem prispevku predstavljamo rezultate raziskave, ki KEYWORDS kaže na statistično pomembne povezave med različnimi emotional regulation, neurobiological background, dimenzijami nefunkcionalne čustvene regulacije in alcohol abuse tvegano rabo alkohola. V raziskavi je sodelovalo 478 odraslih posameznikov. Še posebej močna je korelacija med posamezniki, ki se čustev manj zavedajo (DERS 1 NEVROBIOLOŠKO OZADJE TEŽAV V dimenzija zavedanje čustev) in tvegano rabo alkohola. ČUSTVENI REGULACIJI Prikazani rezultati kažejo na potrebo po psihoterapevtski obravnavi saj le-ta lahko omogoči posameznikom, da se Raziskovalci [2] ugotavljajo povezavo med čustveno soočijo s težavami v čustveni regulaciji in bolj kontrolo in HPA (hipotalamus-hipofiza-nadledvična funkcionalno regulirajo svoja čustva ter se manj zatekajo žleza) osjo. HPA os je nevroendokrini sistem, ki se k tvegani rabi alkohola. aktivira ob stresu. Ob travmatičnih izkušnjah in stresnih situacijah pride v delovanju HPA osi do funkcionalnih KLJUČNE BESEDE sprememb, ki se kažejo kot hipo ali hiperaktivnost čustvena regulacija, nevrobiološko ozadje, zloraba določenih hormonov v centralnem živčnem sistemu [2, alkohola 3], z namenom da se telesno stanje pripravi na boj ali beg. Iz tega se da sklepati, da je disregulirana HPA os, ABSTRACT zaradi akutnih ali dolgoročnih sprememb, bolj ranljiva in Alcohol dependence and its risky use are often associated vpliva na slabše telesne in posledično čustvene odzive na with less functional regulation of emotional responses [1]. stresna stanja [2, 4, 5], kar lahko prepoznamo kot težave Alcoholism is a major social and health problem. When a pri čustveni regulaciji. person has functional emotional regulation skills, they can recognize emotions and can control their expression. Motnje pri delovanju HPA osi kažejo na težave v Conversely, a person with dysfunctional emotional čustveni regulaciji, saj so, med drugim, povezane z regulation skills is not aware of their emotions, so their razvojem depresije ali PTSM, ter so obenem povezane z actions can be very impulsive. Dysfunctional regulated večjo verjetnostjo uživanja alkohola, kar kažejo emotional responses cause uncontrollable distress in the ugotovitve avtorjev [2, 6]. PTSM je povezana z 1 Doseženi rezultati so nastali v okviru projekta št. J5-2570, ki ga je financirala Javna agencija za raziskovalno dejavnost Republike Slovenije iz državnega proračuna. 347 zmanjšano reaktivnostjo HPA osi, vključno s stanja ko delujejo na receptorje gama-aminomaslene hipokortizolizmom , medtem ko je za depresijo značilna kisline (GABAA) v hipokampusu in kortikalnih regijah. povečana reaktivnost HPA osi, vključno s Avtorji [12, 2] kot eno od fizioloških posledic alkohola hiperkortizolizmom [3]. Bolj natančno povezanost med opisujejo tudi zmanjšanje negativnih čustev, kot so uživanjem alkohola in mehanizmi HPA osi še vedno anksioznost, jeza in strah; zmanjša pa se tudi čustveno raziskujejo, vendar nekatere ugotovitve kažejo, da vzburjenje. oslabljena aktivnost adrenokortikotropnega hormona (ACTH) in kortizola lahko predstavlja ranljivost za Alkohol namreč, kot mnoge druge vrste drog, sproži uživanje alkohola [2] Čustvena stanja v posamezniku se sproščanje dopamina iz ventralnega tegmentalnega namreč prevajajo v jezik kortizola, digitalni signali misli področja (VTA), ki vpliva na mezolimbične možganske in čustev se v posameznikovem telesu prevedejo na strukture, kot npr. medialni prefrontalni korteks (mPFC), analogno in enostavno raven kortizola, ki jo izražamo v nucleus accumbens (NAcc) bazolateralna amigdala in številkah. različni prefrontalni predeli [22]. Ta vpliv dopamina pri posamezniku povzroči občutek sreče in pomiritve. V prisotnosti akutnega stresa (pretirana vročina, mraz, poškodbe, infekcije, stres, močna čustva), aktivirana HPA Dopamin igra pomembno vlogo pri razvoju odvisnosti os vpliva na sproščanje povečane ravni sprostilnega (posameznik želi več alkohola, droge). Občutki, da hormona kortikotropina (CRH) iz hipotalamusa, ki je posameznik uživa v alkoholu ali drogi pa so v telesu stimulator za izločanje hormona kortikotropina - vzpostavljeni s striatnim opioidergičnim adrenokortikotropnega hormona (ACTH), ki se izloča iz nevrotransmiterjem oziroma endorfinom, ki se ob srednjega dela hipofize. ACTH spodbuja izločanje uživanju alkohola prav tako sprošča [23]. glukokortikoidov, vključno s kortizolom (pri ljudeh), da Stres in alkohol namreč delujeta po isti poti, oba povečata prepreči odziv na stres v predelih, kot sta hipotalamus, reaktivnost HPA osi, povišane ravni hormonov HPA pa kot tudi hipokampus, prefrontalni korteks in hipofize spodbujajo sproščanje endorfina, ki je povezan z drugimi preko negativne povratne zveze [2,14] možganskimi področji (npr. ventralno tegmentalno V raziskavi se je pokazalo, da imajo npr. posamezniki s območje) in ojačevalnimi učinki alkohola oziroma drog PTSM oslabljen ACTH ob stresu [7]. Obenem je neka [13, 15]. Z večjimi količinami zaužitega alkohola se druga raziskava pokazala, ob kratkotrajni abstinenci pri poveča reaktivnost HPA osi, vključno z ACTH in posameznikih odvisnih od alkohola, oslabljeno aktivnost kortizolom ter se dosežejo želeni učinki krepitve v HPA osi ob izpostavljenosti stresu [8] in nižjim ACTH, sistemu, ki pa ima za posledico povečano aktivnost zaradi česar so bolj ranljivi za ponovno uporabo alkohola, ACTH in kortizola. kot posamezniki z visokim odzivom ACTH. [9]. Kot rečeno mnoge študije kažejo na povezanost težav pri Ugotovitve kažejo, da lahko zmanjšana ACTH in kortizol uravnavanju in delovanju čustev ter uživanjem alkohola pomenita ranljivost za uporabo alkohola pri in težavami povezanimi s tem [16, 12]. Raziskava je posameznikih s PTSM. Kar zadeva depresijo, je uživanje pokazala, da je bila visoka stopnja negativnih emocij in alkohola povezano s povečanimi ravnmi ACTH in pa impulzivnosti, kot odziva na negativne emocije, v kortizola pri ljudeh in živalskih modelih [8, 10,11]. pozitivni korelaciji z rizično uporabo alkohola in pitjem Disregulirano stanje HPA osi in hormonsko neravnovesje do popolne omamljenosti [17]. Tudi čustvena namreč kažeta na težave pri čustveni regulaciji. nestabilnost je bila povezana z nevarno rabo alkohola [18]. Opredeljeni so bili namreč trije indikatorji čustvenega funkcioniranja in sicer: impulzivnost, 2 TVEGANA RABA ALKOHOLA V čustvena (ne)stabilnosti in toleranca na stres. POVEZAVI S TEŽAVAMI PRI ČUSTVENI Raziskovalci so ugotovili, da je višja stopnja odpornosti REGULACIJI na stres in bolj pozitivno afektivno stanje posameznika v negativni korelaciji z uporabo alkohola in je lahko neke Zmanjšana zavestna kontrola emocionalnih stanj poveča vrsta zaščita pred tvegano rabo alkohola [17]. občutljivost za težave pri uravnavanju čustev in s tem se poveča verjetnost, da bodo ti posamezniki uživali alkohol do opojnih stanj z namenom doseči kratkotrajno regulacijo čustev. Raziskave so namreč pokazale, da je 3 OPREDELITEV PROBLEMA IN konzumacija alkohola pri lajšanju negativnih občutkov najbolj učinkovita, ko so bile zaužite doze alkohola, ki HIPOTEZE imajo omamen učinek [12]. Težave pri čustvenem funkcioniranju pogosto vodijo v manj zadovoljivo vsakdanje življenje. Poleg tega, da Uživanje alkohola kot kratkoročni mehanizem za lahko negativno vplivajo na medosebne odnose, težave v uravnavanje čustev je dobro dokumentirano; alkohol čustveni regulaciji zelo močno obremenjujejo namreč lahko ponudi "priložnost za obvladovanje" za posameznika samega. Kot smo videli v uvodnem delu, so posameznike, pri katerih je zaznati težave na področju mnoge študije [2,3,4, 8,11, 16] neregulirane emocije zavestne kontrole čustvenega stanja [12]. povezale z večjo ranljivostjo nevrobiološkega odziva Fiziološki učinki alkohola vplivajo na povečanje telesa, še posebej HPA osi, ki se odziva in uravnava stres aktivnosti dopaminogeničnih, noradrenalinih in opioidih pri posamezniku. Ker taka ranljivost na stresne situacije peptidov ter s tem lahko pozitivno okrepijo afektivna lahko v telesu povzroči veliko neobvladljivih emocij in stanja. Obenem pa lahko negativno okrepijo afektivna telesnih občutkov, pogosto posamezniki nezavedno 348 poskušajo to stanje uravnati s pomočjo alkohola Hipoteza 1: Posamezniki z več težavami pri čustveni [22,12,23].. regulaciji bolj tvegano uživajo alkohol. Glede na to nas je v konkretni raziskavi zanimala Na našem vzorcu smo preverjali, kako se težave pri povezanost med težavami pri čustveni regulaciji, na čustveni regulaciji v šestih dimenzijah ter skupni različnih dimenzijah ter tvegano uporabo alkohola. dimenziji pri posameznikih povezujejo s tvegano uporabo alkohola na treh dimenzijah ter skupni dimenziji. Ker so Preverjali smo naslednjo hipotezo: naši podatki nenormalno distribuirani (test Kolmogorov- Smirnov), smo za ugotavljanje povezanosti uporabili Hipoteza 1: Posamezniki z več težavami pri čustveni Spearmanov korelacijski koeficient. regulaciji bolj tvegano uživajo alkohol Rezultati (Tabela 1) kažejo, da obstaja statistično pomembna povezava med posamezniki z več težavami 4 METODA pri čustvenem regulaciji in bolj tvegana uporaba alkohola. 4.1 Udeleženci Na našem vzorcu smo preverjali kako se tvegana raba alkohola (skupna dimenzija) povezuje z različnimi vidiki V raziskavi je sodelovalo 476 udeležencev, od tega 348 težav pri čustveni regulaciji, ki smo jih merili na šestih (73,1 %) žensk in 128 (26,9 %) moških. Povprečna dimenzijah ter skupno dimenzijo (nesprejemanje starost vseh udeležencev je bila 35 let (SD=14,5). čustvenih odzivov, težave pri usmerjenosti k cilju, težave 4.2 Pripomočki in postopek pri kontroli impulzov, pomanjkanje čustvenega zavedanja, omejene strategije čustvene regulacije, Udeleženci so poleg splošnega vprašalnika o pomanjkanje čustvene jasnosti in skupna dimenzija) demografskih podatkih (spol, starost) izpolnjevali še naslednje vprašalnike: Iz tabele 1 je razvidno da se tvegana raba alkohola statistično pomembno pozitivno povezuje z vsemi 1. Lestvico težav pri regulaciji čustev – krajša verzija dimenzijami težav pri čustvenem funkcioniranju. Obstaja (Difficulties in emotion regulation scale – Short form - trend, da več kot je pri posamezniku nesprejemanja DERS – SF), ki je kratek samoporočevalni instrument za čustvenih odzivov, težav pri usmerjenosti k cilju, težav oceno različnih vidikov čustvene disregulacije oz. pri kontroli impulzov ter omejene strategije čustvene neprimerne regulacije čustev [19, 20] na šestih področjih: regulacije, več je tvegane rabe alkohola. Še posebej nesprejemanje čustvenih odzivov, težave pri vedenju, statistično pomembna pozitivna povezava obstaja med usmerjenemu k določenemu cilju, težave pri kontroli dimenzijo pomanjkanje čustvenega zavedanja in tvegano impulzov, pomanjkanje čustvenega zavedanja, omejen rabo alkohola (rho =.173**, p = .000) . Statistično dostop do strategij čustvene regulacije in pomanjkanje pomembna je tudi povezava med dimenzijo pomanjkanje čustvene jasnosti. Višji rezultat kaže na večjo prisotnost čustvene jasnosti in tvegano rabo alkohola, vendar na problemov v čustveni regulaciji. Koeficient zanesljivosti nivoju 5% tveganja. (Cronbachov alfa) za celotni vprašalnik v naši raziskavi znaša ɑ=0,823. Tabela 1: Korelacijski koeficienti (Spearmanov rho) med težavami pri regulaciji čustev (vse dimenzije) in tvegano 2. Vprašalnik o stopnji tveganosti rabe alkohola AUDIT rabo alkohola (skupna dimenzije) (N = 476). (The Alcohol Use Disorders Identification Test AUDIT (WHO) je test, ki omogoča prepoznati trenutne težave s AUDIT SKUPAJ pitjem alkohola (npr. škodljivo rabo alkohola, zlorabo alkohola in odvisnost od alkohola) [21]. Meri tri vidike DERS - rho .134** zlorabe alkohola: tvegano uživanje alkohola (količina in nesprejemanje_čust_odzivov p .003 pogostost), simptome odvisnosti od alkohola (toleranca, sposobnost kontrole) in z uživanjem alkohola povezane r DERS - cilji ho .134** probleme. Višji rezultat kaže na bolj tvegano rabo p .003 alkohola. Koeficient zanesljivosti (Cronbachov alfa) za celotni vprašalnik v naši raziskavi znaša ɑ=0,935. DERS - rho .154** impulzi Udeleženci so vprašalnik reševali v spletni obliki p .001 (povabilo za sodelovanje v raziskavi s povezavo do DERS - rho .173** vprašalnika je bilo poslano na različne naslove in forume) Pomanjkanje čustevenega in pisno (te udeležence smo pridobili na eni izmed klinik zavedanja p .000 za zdravljenje alkoholizma). Anketiranje je potekalo od DERS - rho .149** junija 2021 do maja 2022. Rezultate smo izračunali z omejene_strategije_regulacije uporabo programskega paketa SPSS 20. p .001 DERS - rho .107* čustvena_jasnost p .016 5 REZULTATI DERS rho .164** 349 SKUPAJ [4] Majewska, M.D. (2002). HPA axis and stimulant p .000 dependence: An enigmatic relationship. Opombe: DERS – Lestvica težav pri regulaciji čustev; AUDIT - Psychoneuroendocrinology, 27, 5–12. 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European Journal of Neuroscience. doi:10.1111/ejn.14160 351 352 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek G Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume G Vzgoja in izobraževanje v informacijski družbi Education in Information Society Urednika / Editors Uroš Rajkovič, Borut Batagelj http://is.ijs.si 14. oktober 2022 / 14 October 2022 Ljubljana, Slovenija 353 354 PREDGOVOR Letošnja konferenca Vzgoja in izobraževanje v informacijski družbi je že 25., kar pomeni, da se odvija vsako leto v okviru multikonference Informacijska družba. Že četrt stoletja iščemo sinergijo med človekom in informacijsko tehnologijo v procesih vzgoje in izobraževanja. Vsako leto je posebno in tudi letošnje ni izjema. Zakorakali smo v novo šolsko leto brez posebnim zdravstvenih omejitev, ki so veljale v preteklih letih, hkrati pa smo bogatejši za izkušnje, ki smo jih pridobili pri izobraževanju na daljavo. Ostalo je še veliko neodgovorjenih vprašanj, predvsem v povezavi s hibridnimi načini poučevanja. Vabimo vas, da se udeležite letošnje konference, na kateri se bomo učili ob deljenju naših izkušenj. Uredniški odbor FOREWORD This year's conference Education in Information Society is the 25th, which means that it takes place every year as a part of the Information Society Multi-Conference. For a quarter of a century, we have been seeking synergies between people and information technology in the processes of education. Every year is special and this year is no exception. We have entered a new school year without any special health restrictions of previous years, and at the same time, we are richer for the experience we have gained in distance learning. There are still many unanswered questions, especially in relation to hybrid teaching methods. We invite you to attend this year's conference, where we will learn while sharing our experiences. Editorial Board 355 KONFERENČNI ODBORI / CONFERENCE COMMITTEE 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 Tadeja Batagelj, Svetovalni center za otroke, mladostnike in starše Maribor 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 356 Recenzenti / Reviewers Alenka Baggia, Univerza v Mariboru, Fakulteta za organizacijske vede Branka Balantič, Šolski center Kranj, Višja strokovna šola Zvone Balantič, Univerza v Mariboru, Fakulteta za organizacijske vede Borut Batagelj, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko Tadeja Batagelj, Svetovalni center za otroke, mladostnike in starše Maribor Branka Jarc Kovačič, Šolski center Kranj, Srednja tehniška šola Robert Leskovar, Univerza v Mariboru, Fakulteta za organizacijske vede Marko Novaković, Univerzitetni klinični center Ljubljana Uroš Rajkovič, Univerza v Mariboru, Fakulteta za organizacijske vede Gašper Strniša, Šolski center Kranj, Strokovna gimnazija Iva Strniša, Gimnazija Franceta Prešerna, Kranj Iztok Škof, Osnovna šola Toma Brejca Kamnik Marko Urh, Univerza v Mariboru, Fakulteta za organizacijske vede Vladislav Rajkovič, Univerza v Mariboru, Fakulteta za organizacijske vede Borut Werber, Univerza v Mariboru, Fakulteta za organizacijske vede Jasmina Žnidaršič, Univerza v Mariboru, Fakulteta za organizacijske vede 357 358 Sistem za spremljanje stresa preko prevodnosti kože med reševanjem testa System for Monitoring Stress Through Skin Conductance During an Exam Jaka Albreht Šolski center Kranj Kranj, Slovenija jaka.albreht@sckr.si POVZETEK the sweat glands in stressful situations. Therefore, we can monitor the movement of the stress level by measuring skin V prispevku nas je zanimalo kaj se dogaja z dijaki med conductivity. reševanjem testa. Vsako preverjanje znanja predstavlja za dijake stresno situacijo. Poiskati smo želeli način kako bi spremljali The paper describes the creation of a system that allows us to nivo stresa med reševanjem testa. Verjetno vsi vemo, da se nam, measure the conductivity of the skin, through which we can ko smo v stresni situaciji, običajno začnejo potiti roke. Gre za monitor the level of stress that the student is exposed to while avtonomni odziv živčnega sistema, ki ob stresni situaciji aktivira solving the test. The measuring system consists of electrodes that žleze znojnice. Zato lahko preko merjenja prevodnosti kože touch the fingers during the test and other electronic elements. spremljamo gibanje nivoja stresa. An application was also developed in the Labview software environment, which allows choosing the correct answer while V prispevku je opisana izdelava sistema, ki nam omogoča recording the movement of skin conductance. merjenje prevodnosti kože, preko katere lahko spremljamo nivo stresa, ki mu je dijak izpostavljen med reševanjem testa. Merilni The last part also shows the results of some measurements and sistem sestavljata elektrodi, ki se med testom dotikata prstov ter findings. The starting points for further work are also given, ostali elektronski elementi. V programskem okolju Labview je which mainly relate to the design of experiments and the analysis bila razvita tudi aplikacija, ki omogoča izbiro pravilnega of results. odgovora, medtem ko beleži gibanje prevodnosti kože. This kind of use of the field of psychophysiology opens the door V zadnjem delu so prikazani tudi rezultati nekaj meritev in to the development of adaptive learning methods, which will ugotovitve. Podana so tudi izhodišča za nadaljnje delo, ki se include the monitoring of physiological parameters and through predvsem nanašajo na načrtovanje eksperimentov in analizo a feedback loop help the learner to learn more effectively rezultatov. KEYWORDS Tovrstna uporaba področja psihofiziologije odpira vrata v razvoj adaptivnih metod učenja, ki bodo vključevala spremljanje Stress, conductivity of the skin, psychophysiology, test, Labview fizioloških parametrov in preko povratne zanke pomagala application, electrodes učečemu pri bolj učinkovitem učenju. 1 UVOD KLJUČNE BESEDE Vsako preverjanje znanja predstavlja za dijake določeno stopnjo Stres, prevodnost kože, psihofiziologija, test, Labview stresa. Dijaki so pod časovnim pritiskom saj imajo za reševanje aplikacija, elektrode omejeno količino časa. Včasih se nepravilni odgovori celo ABSTRACT točkujejo z negativnimi točkami in tako še povečajo pritisk. Zanimalo nas je kaj se dogaja z dijaki med reševanjem testa. In the article, we were interested in what happens to the students S tem namenom je bil razvit sistem, ki nam omogoča spremljanje while solving the test. Each knowledge test represents a stressful prevodnosti kože, preko katere zaznavamo stopnjo stresa, ki ga situation for students. We wanted to find a way to monitor the doživlja dijak. V nadaljevanju bo predstavljena zasnova sistema, stress level during the test. We probably all know that when we ki vsebuje aplikacijo, ki je bila razvita v programskem okolju are in a stressful situation, our hands usually start to sweat. It is Labview, ter merilno vezje z elektrodami. Na koncu pa bomo an autonomous response of the nervous system, which activates podali primer uporabe sistema med reševanjem testa z vprašanji izbirnega tipa. 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 359 2 PREVODNOST KOŽE Elektrode priključimo na šibko napetost (0.64 V). Preko kazalca in sredinca bo stekel električni tok, ki je sorazmeren prevodnosti Vsak se je že kdaj nahajal v situaciji, kjer se nam je zaradi stresa kože, kar lahko enostavno izračunamo preko spodnje enačbe. povečal srčni utrip, začeli smo hitreje dihati, krvni tlak nam je (Slika 3) narastel in začele so se nam potiti roke. Področje, ki se ukvarja s tem, kako naše telo reagira na različne psihološke dražljaje 𝐼 𝐺 = (1) imenujemo psihofiziologija [1]. Eden izmed parametrov, ki ga 𝑈 lahko spremljamo med stresno situacijo je prevodnost kože [2, 3]. Ob nastopu dražljaja bodo naši možgani poslali signal, ki aktivira žleze znojnice. Tega procesa ne moremo kontrolirati, saj se zgodi samodejno. Oglejmo si kako izgleda tipičen signal prevodnosti kože SCR (skin conductance response) (Slika 1). Vidimo lahko, da po pojavu dražljaja običajno traja od ene do treh sekund, da se žleze znojnice aktivirajo. Ta čas imenujemo latenca. Signal nato doseže najvišjo točko in se potem začne postopoma spuščati na predhodno raven. Prednost spremljanja signala prevodnosti kože je ta, da lahko relativno hitro zaznamo vpliv dražljaja. Ravno zaradi tega razloga smo se odločili, da bomo spremljali nivo stresa preko prevodnosti kože. Slika 3: Koncept merjenja prevodnosti kože Slika 1: Signal prevodnosti kože Poleg elektrod potrebujemo še nekaj komponent, ki so prikazane na Sliki 4 in Sliki 5. Merilno vezje vsebuje operacijski ojačevalnik, ki poskrbi, da šibak napetostni signal ojačamo. V vezje je dodan tudi kondenzator, ki odpravlja visokofrekvenčne motnje. Izhod operacijskega ojačevalnika je povezan na analogni 3 SISTEM ZA MERJENJE PREVODNOSTI vhod (A0) mikrokrmilnika, ki se nahaja na razvojni plošči KOŽE Arduino UNO. Vrednost prevodnosti kože se nato preko serijske povezave 3.1 Merilni sistem USB prenese do računalnika, kjer je nameščeno programsko Oglejmo si preprost merilnik prevodnosti kože. Osnovno vezje okolje Labview oz. v njem razvita aplikacija. za merjenje prevodnosti kože vsebuje elektrode (Slika 2). Odločili smo se za baker, saj le-ta dovolj dobro prevaja električni tok. Slika 4: Shema merilnega sistema Slika 2: Bakrene elektrode 360 Slika 5: Merilni sistem Slika 7: Sproščanje in priprava na reševanje 3.2 Programska aplikacija V programskem okolju Labview je bila razvita aplikacija, ki V nadaljevanju se zaporedoma prikaže 10 vprašanj. Pri nam omogoča prikazovanje prevodnosti kože med reševanjem vsakem vprašanju je na voljo 30 sekund časa za izbiro odgovora. testa z vprašanji izbirnega tipa. Odgovor je možno izbirati preko spustnega seznama. Testirancu Najprej testiranec vpiše svoje podatke in opredeli trenutno se prikazuje tudi čas, ki ga ima še na voljo, da izbere ustrezen počutje (Slika 6). odgovor ter zaporedna številka vprašanja (Slika 8). Na koncu se pokaže uspešnost reševanja testa in gibanje prevodnosti kože. Tako lahko vidimo pri katerem vprašanju se je zgodila opaznejša sprememba prevodnosti kože in odgovori na katera vprašanja so bili pravilni. Slika 8: Reševanje testa 3.3 Rezultati testiranja Merilni sistem smo zaradi časovne stiske uspeli preizkusiti le na manjšem vzorcu dijakov (N=5). Prav tako je bil naš namen zgolj preizkusiti delovanje sistema, ne pa poglobljeno Slika 6: Nastavitev parametrov in vnos podatkov načrtovanje eksperimenta in analiza rezultatov. Poglejmo si primer dijaka, ki je reševal test (Slika 9). Nato sledi približno minuta umirjanja, da se prevodnost kože stabilizira (Slika 7). 361 Slika 10: Primerjava umirjenega (spodaj) in aktivnega (zgoraj) stanja Iz analize več grafov lahko podamo nekaj zaključkov oz. opažanj. Pri iztekanju časa za posamezen odgovor bo prevodnost kože običajno naredila skok, saj se bo dijak trudil izbrati pravilen odgovor preden se mu izteče čas. Nivo je med reševanjem testa višji kot pri umirjenem stanju. Znotraj povišanega nivoja prevodnosti se pojavljajo skoki, ki so posledica reakcij na posamezna vprašanja. Slika 9: Rezultat testiranja 4 ZAKLJUČEK Na grafu je z modro barvo prikazana zaporedna številka S trenutnimi rezultati dela smo lahko zadovoljni, saj nam je vprašanja, rdeča barva pa prikazuje potek prevodnosti kože. V uspelo narediti delujoč sistem, ki nam omogoča spremljanje spodnjem delu okna je rdeč oz. zelen indikator, ki nam pokaže stresa med reševanjem testa. Z izvedbo nekaj testiranj na dijakih pravilnost odgovora. Prav tako vidimo kakšna je bila uspešnost smo dobili povratno informacijo o delovanju sistema. Celotna v %. Pri primeru na Sliki 9 vidimo, da so bili med reševanjem aplikacija je dovolj robustna in modularna, da omogoča stalno prisotni skoki prevodnosti, kar nakazuje, da je bil dijak prilagajanje časa za odgovor, rotacijo in izbiro različnih vprašanj, stalno pod stresom. Opaznejši premik opazimo pri sedmem izvoz grafov v program, kjer lahko delamo analize signalov. vprašanju, ko ob iztekanju časa prevodnost izrazito naraste. Kljub temu pa imamo še veliko možnosti za izboljšave. Sam Dijak je na to vprašanje sicer odgovoril pravilno. Če bi želeli merilni sistem lahko vgradimo v ohišje, ki je natisnjeno s 3D dobiti več informacij, bi morali pogledati na katero vprašanje tiskalnikom ter izdelamo tiskano vezje. Dodati je možno tudi konkretno je odgovarjal. Lahko bi se tudi na koncu z dijakom povratno zanko, ki nam omogoča, da lahko glede na gibanje pogovorili in tako dobili še večji vpogled kaj se je dogajalo in prevodnosti prilagajamo težavnost vprašanj oz. čas za odgovor. zakaj je reagiral tako kot je. Na ta način lahko dijaku omogočimo, da bolje izkoristi svoje Za primerjavo si poglejmo dva grafa, ki prikazujeta potenciale pri reševanju in mu omejimo stres, ki ga reševanje gibanje prevodnosti kože. V enem primeru je dijak ves čas testa povzroča. Nižji nivo stresa namreč poveča učinkovitost sproščen, v drugem pa rešuje test (Slika 10). Pri aktivnem stanju učenja [4]. je nivo prevodnosti višji. Prav tako je opaziti več skokov oz. Ključno pri nadaljnjem delu pa je načrtovanje in izvedba sprememb v prevodnosti. Pri umirjanju pa nivo prevodnosti ves eksperimentov, kjer na večjem številu dijakov preizkusimo čas upada s sicer manjšimi skoki. različno težavnost vprašanj in časovne omejitve. Pri interpretaciji rezultatov in načrtovanju eksperimentov bo vsekakor potrebna interdisciplinarnost in s tem vključitev psihologa. Z razvojem in preizkusom našega sistema smo naredili prve korake v smeri povezovanja psihofiziologije in procesa učenja. Menimo, da ima adaptivno učenje z uporabo psihofiziologije v prihodnosti še veliko potenciala. LITERATURA IN VIRI [1] Psihofiziologija. Dostopno na naslovu https://en.wikipedia.org/wiki/Psychophysiology (27. 7. 2022) [2] George I. Christopoulos, Marilyn A. Uy, Wei Jie Yap, 2016. The Body and the Brain: Measuring Skin Conductance Responses to Understand the Emotional Experience. DOI: https://doi.org/10.1177/1094428116681073 [3] Gregor Geršak. 2013. Enostavni nizkocenovni merilniki prevodnosti kože. Dostopno na naslovu https://ev.fe.uni-lj.si/1-2-2013/Gersak.pdf (27. 7. 2022) [4] Tacy L. Holliday, Sukhaynah H. Said. Psychophysiological Measures of Learning Comfort: Study Groups’ Learning Styles and Pulse Changes. Dostopno na naslovu https://files.eric.ed.gov/fulltext/EJ818223.pdf (27. 7. 2022) 362 Vizualizacija sinteze 2D abstraktnih teksturnih vzorcev z naključnostjo Visualization of the Synthesis of 2D Abstract Textural Patterns With Randomness Davorin Babič Srednja medijska in grafična šola Ljubljana Ljubljana, Slovenija davorin.babic@smgs.si POVZETEK model of randomness. Even without considering these theoretical ideas, pseudorandomness and procedural number generators V prispevku bomo orisali konceptualno uporabo naključnosti za such as Perlin noise provide us with simple yet powerful ways to ustvarjanje zaporednih in ponavljajočih se vsebinskih struktur produce effective and varied visual results. Any conclusions digitalnih vizualnih podobotvorij znotraj digitalne generativne drawn from this paper are expected to lead to a better umetnosti, v nadaljevanju pa računalniško generirano understanding of the creative process in the context of code- naključnost in njeno vlogo v sodobni umetniški praksi v medijski based visual work, since for the most part the visual outcomes of produkciji. Programiranje, še posebej kreativno kodiranje v creative coding are not directly predictable in advance. kontekstu umetnosti in oblikovanja, je proces usklajevanja in prehajanja med individualno ustvarjalno mislijo in togimi KEYWORDS konceptualnimi modeli kode. Zato smo posebej oblikovali učne oblike, metode in aktivnosti pri seznanjanju dijakov z Procedural literacy, algorithmic thinking, randomness, random matematičnim modelom naključnosti. Tudi brez upoštevanja teh numbers, noise, digital generative system teoretičnih idej nam psevdonaključnost in generatorji proceduralnih števil, kot je Perlinov šum, nudijo preproste, a 1 UVOD zmogljive načine za ustvarjanje učinkovitih in raznolikih vizualnih rezultatov. Pričakuje se, da bodo kakršni koli zaključki, Uporaba različnih analognih tehnik spreminjanja naključnosti in ki izhajajo iz tega prispevka, vodili k boljšemu razumevanju negotovosti v opredeljujoča dejavnika v procesih umetniškega ustvarjalnega procesa v kontekstu vizualnega dela, ki temelji na ustvarjanja na likovnem področju sega v začetke dvajsetega kodi, saj večinoma vizualni rezultati kreativnega kodiranja niso stoletja in je bistvena upodobitvena značilnost dadaistov 1 in neposredno predvidljivi vnaprej. konceptualistov 2 . S pojavom računalnikov in različnih računalniških platform se je izražanje ustvarjalne subjektivnosti KLJUČNE BESEDE skozi programsko kodo preneslo v umetniško prakso in vizualno raziskovanje uporabe stohastičnosti na področju digitalne Proceduralna pismenost, algoritmično mišljenje, naključnost, generativne umetnosti, tako na konceptualni kot tehnični ravni. naključna števila, šum, digitalni generativni sistem Ob tem seveda velja poudariti, da obstaja temeljna razlika med ABSTRACT naključnostjo znotraj dadaistične umetnosti in kasnejše računalniške umetnosti. Medtem, ko se naključnost v dadaizmu In this paper, we will outline the conceptual use of randomness nanaša na čisto naključje, se naključnost v računalniški for the creation of sequential and repetitive content structures of umetnosti uporablja kot psevdonaključnost, kjer je v smislu digital visual sub-creations within digital generative art, and in digitalne logike naključje delno nadzorovano. the following, computer-generated randomness and its role in Uporaba računalniških metod v digitalni generativni contemporary artistic practice in media production. umetnosti se namreč odvija v nizu ustvarjalnih metodologij za Programming, especially creative coding in the context of art and zavestno interakcijo vnaprej določenih sistemov z različnimi design, is a process of matching and transitioning between dejavniki nepredvidljivosti skozi konceptualizacijo, produkcijo individual creative thought and rigid conceptual models of code. in predstavitvijo umetniškega dela. Kreativno kodiranje [1] kot That is why we have specially designed learning forms, methods programiranje v kontekstu računalniške umetnosti in digitalnega and activities to familiarize students with the mathematical oblikovanja je proces usklajevanja in prehajanja med Permission to make digital or hard copies of part or all of this work for personal or individualno ustvarjalno mislijo in konceptualnimi modeli classroom use is granted without fee provided that copies are not made or distributed programske kode. S prevajanjem abstraktnih idej v konkretne 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 vizualne rezultate s pomočjo preprostih algoritmov in be honored. For all other uses, contact the owner/author(s). programske kode je mogoče ustvariti ogromno vizualnih Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia računalniških interpretacij, ki omogočajo razcvet novih © 2022 Copyright held by the owner/author(s). 1 Dadaizem, oblika umetniške anarhije, ki je izzivala družbene, politične in kulturne 2 Konceptualizem je umetniško gibanje, pri katerem je ideja (ali koncept) v ozadju vrednote tistega časa. dela pomembnejša od končnega umetniškega objekta. 363 vizualnosti, s čimer se formalizira neobvladljivost ustvarjalnega naslednje vrednosti v zaporedju ponovljive, če je začetno seme procesa, a hkrati poudarja in estetizira kontekstualna narava znano. Poleg tega je zaradi preproste rekurzivne definicije računalniške umetnosti. Za doseganje estetskih rezultatov v zaporedja mogoče učinkovito generirati psevdonaključna števila. produkciji likovnih form znotraj računalniško generiranih Enakomerno porazdeljena zaporedja se lahko v razširitvi dvorazsežnih podob ustvarjalci posegajo po kombiniranju strogo uporabijo za generiranje števil iz poljubnih porazdelitev. načrtovane strukturne in likovne logike ter metod matematične Generatorji premorejo lastnosti determinizma in učinkovitosti, naključnosti programskega okolja. To jim omogoča razumevanje zato imajo prednost pred pravimi naključnimi števili. inherentne generativnosti vsakega ustvarjalnega procesa, ki ga Da bi izkoristili prednost naključnosti, je treba v generativni narekujejo naključni pojavi, in eksplicitnega generativnega sistem uvesti funkcije za vzorčenje hitro spreminjajočih se pristopa, ki ceni in razvija umetniško delo kot dinamičen podatkov. S preprostim dodajanjem naključnih števil vizualnim dogodek, navdihnjen z radovednostjo, dovzeten za naključje in parametrom so lahko izhodni rezultati nenaravni in vizualno togi, odprt za spremembe. Logično-numerična transpozicija vendar običajno pričakujemo bolj gladek prehod v teksturnih generiranih grafičnih podatkov v vizualni prostor, včasih s vzorcih kot razpoložljivo možnost v grajenju vizualne estetike. ponavljajočimi se geometrijskimi vzorci, včasih z zlomljenimi strukturami, včasih izoliranimi snopi tokovnic ali gručami točk. Ustvarjalne metodologije, ki temeljijo na algoritemskih 2 METODA DELA procesih, implementirajo estetske zmožnosti naključnosti v proces ustvarjanja digitalne postopkovne generativne grafike, pri 2.1 Razvijanje algoritmičnega mišljenja in kateri nastanejo različni vizualni rezultati z odstopanjem od proceduralne pismenosti nadzora ustvarjalca v omejenem okviru. Različni dejavniki Težnja po prekrivanju znanosti in umetnosti je aktualna tudi v naključnost kot konstitutivni faktorji predstavljajo vhodne izobraževanju. Določen učni sklop pri kreativnem kodiranju je parametre v algoritmu pri vizualizaciji strukturiranega bil zato posvečen vprašanju simbioze znanosti in umetnosti v grafičnega sistema in s tem neposredno vplivajo na kakovost izobraževalnem kontekstu. Poleg teoretičnih obravnav sorodnih njegovih vizualnih rezultatov, ki ne premorejo predvidljivih vprašanj (načini preseganja dihotomije znanstvenega in vzorcev. Iz tega izhaja, da uporaba naključnosti spremeni umetniškega pristopa k svetu, vloga učitelja v tem procesu, ustvarjalni proces iz popolnoma načrtovanega v bolj naključnega. ustvarjalno povezovanje izoliranih izobraževalnih vsebin) tudi Ustvarjalcem omogoča, da nekatere svoje intuitivne, subjektivne ponuja konkretne primere izvedenih kratkih izobraževalnih odločitve, prenesejo na ustvarjalni proces, ki ga ne morejo v projektov. Skupna lastnost teh projektov je povezovanje celoti nadzorovati. Stopnja naključja je odločitev ustvarjalca. izobraževalnih vsebin različnih študijskih področij (tako Uvajanje naključnosti in negotovosti v vizualno vsebino umetniških kot naravoslovnih). digitalne postopkovne generativne grafike kaže na dva vidika Generativna umetnost obravnava proceduralnost kot osrednji njene umetniške produkcije. Sprva se lahko izvor umetniške koncept znotraj umetniških performativnih praks, pri čemer prakse premakne od rezultatov povsem načrtovanega koncepta k obravnava vlogo in pomen človeškega izvajalca pri uprizarjanju bolj naključnim in celo lažje dostopnim rezultatom znotraj algoritemskih umetniških del. Kot zmožnost izvajanja pravil, ki produkcijskega procesa. Po drugi strani pa ta vrsta naključnosti izhaja iz opisa procesov v formalna navodila (kot so algoritmi), izzove opazovalca, da spremeni točko gledišča s tehnično- lahko proceduralnost konceptualno zajema tako računalnike kot tehnološkega pristopa v ustvarjalnem procesu na bolj ljudi kot entitete, ki izvajajo ta pravila. V likovni umetnosti je bil intelektualne ravni dojemanja vsebin njegove realizacije. Prav ta pojem uvožen iz glasbe (kot ena od njenih inherentnih tako je v umetniški produkciji digitalne postopkovne generativne lastnosti), konceptualiziran in rekonceptualiziran znotraj širšega grafike naključnost povezana z zaporednostjo in ponavljanjem. obsega performativnih praks, ki vključujejo postopke kot Generativni proces skupaj z ogromnimi možnostmi navodila za delovanje [2]. kombinatorike rezultira v razredu grafik namesto posamezne Pomemben del učnega procesa pri kreativnem kodiranju grafike. Potreba po izbiri med vsemi možnimi rezultati vključuje namenjamo preučevanju kognitivnih zahtev za učinkovito naključnost na veliko različnih načinov. Nepredvidljivost, generativno ustvarjalnost. Obsegajo dva načina mišljenja: variacije, ponavljanje, kaos, šum, napetost med redom in povezovanje algoritemskih in nepredvidljivih elementov v neredom so koncepti, povezani z naključnostjo. Digitalna koherenten sistem ter konstrukcijo preprostih algoritmov kot generativna umetnost vključuje te koncepte z velikim naborom večnamenskih orodij, ki zahtevajo proceduralno pismenost in matematičnih tehnik in metod ter predstavlja umetno vrsto, ki je veščine osnov programiranja za izdelavo enostavnih digitalnih sposobna ustvariti neskončno zaporedje posameznih dogodkov, generativnih projektov. K tem načinom smo pristopili od katerih je vsak drugačen, edinstven in neponovljiv, vendar sistematično, s poudarkom na kritičnih podrobnostih pripada isti prepoznavni oblikovalski ideji in estetski formaciji. proceduralne pismenosti, kar nam je omogočilo branje in Velik del generativne umetnosti uporablja naključna števila opisovanje procesov, vključitev proceduralne reprezentacije ter prek računalniških generatorjev psevdonaključnih števil. vizualne in računske estetike, neodvisno od tehnološkega okolja, Računalniški generatorji psevdonaključnih števil so oblikovani, v katerem so dijaki ustvarjali. da se izognejo pomanjkljivostim pravih naključnih števil. Ti Proceduralno mišljenje vključuje tri osnovne korake: generatorji proizvajajo zaporedja števil, ki približujejo neodvisne dematerializacijo določenega pojava v nabor objektov, ki ga enakomerno porazdeljene naključne spremenljivke. Poleg tega ustrezno opisujejo, razrešitev tega nabora objektov v čisto so dobljena zaporedja ustvarjena deterministično. Ustvarjeno sintakso (odstranitev semantične plasti) in prevajanje sintakse v zaporedje števil je pogosto definirano rekurzivno z začetno niz operacij (elementi programskega jezika). Trivialnost vrednostjo, ki se običajno imenuje seme. To pomeni, da so osnovnih korakov zahteva niz kognitivnih sposobnosti: intuicijo 364 ali čut za prepoznavanje pojava, ki ga je mogoče algoritmizirati Dijaki so skozi praktične vaje spoznavali razliko med pod določenimi pogoji, domišljijo in prožnost sklepanja, rezultati grafičnih vsebin digitalnih vizualnih podobotvorij, razlikovanje med racionalnimi in iracionalnimi vidiki v ustvarjenimi z generatorji naključnih števil, katerih vrednosti so mentalnih konceptih naravnih pojavov ter pozornost do obsega enakomerno porazdeljene skozi čas, in šuma, kjer vrednosti niso in neprilagodljivost algoritemskega (računalniškega) sistema. popolnoma naključne, ampak so vedno blizu tistim njihovih Proceduralno mišljenje se sooča z nekaterimi izzivi, zlasti pri neposrednih sosedov. Dijaki so se seznanili z generatorjema kreativnem kodiranju. Konceptualne omejitve (sintakse) naključnih števil v p5.js, funkcijama random() in programskih jezikov in strojne arhitekture lahko vsilijo določene randomGaussian(), kjer lahko prehodi med sosednjimi točkami rešitve in nehote zavrtijo umetniški proces. divje nihajo, in funkcijo noise(), kjer je mogoče ustvariti gladke Med učnim procesom je bila razlaga in demonstracija prehode v eni, dveh ali treh dimenzijah. Funkcija r andom() je konceptov programiranja podprta z uporabo vizualnih grafik, generator naključnih števil, ki vrne psevdonaključno število ali vsebinsko vezanih na naključnost. Na podlagi izkušenj, zaporedje psevdonaključnih števil, praviloma enakomerno pridobljenih pri poučevanju kreativnega kodiranja, smo ugotovili, porazdeljenih na intervalu [0, 1). Funkcija randomGaussian() da uporaba tehnik vizualizacije posameznih programskih okolij vrne psevdonaključne vrednosti, ki ustrezajo Gaussovi ali in orodij pomaga pritegniti pozornost dijakov in podpira učenje normalni porazdelitvi, za katero sta kot parameter navedena ključnih konceptov programiranja. Primeri, ki so se povprečje in standardni odklon. Z uporabo računalniško demonstrirali v razredu, so služili kot vstopna točka za analizo ustvarjenih naključnih funkcij lahko umetniki nadzorujejo računske in likovne logike, razgradnjo algoritmov ter odkrivanje količino naključnosti v celotnem proizvodnem procesu in lahko vzorcev ali podobnosti znotraj programskih skicirk in njihovih uporabljajo veliko bolj nekorelirano naključnost glede na njeno vizualizacij. Praktične vaje so imele običajno navdih kot predvidljivost. izhodišče, kjer so bili dijaki izzvani, da eksperimentirajo in ustvarijo nekaj novega, ali odpravljajo napake, da najdejo in 2.3 Naključni sprehajalec popravijo napake, ali celo sodelujejo pri iskanju rešitve. Bistveni Ena najpreprostejših tehnik, ki se uporablja v digitalni del vizualne forme in identitete tekstur je bil osredotočen na generativni umetnosti, je naključni sprehajalec. Naključni uporabo algoritmov, implementiranih v p5.js kot osnovnim sprehajalec je model preprostega dinamičnega procesa, ki ga programskim jezikom, saj je zaradi njegovih dinamičnih zlahka opredelimo kot sprehod z naključnimi koraki. Sled poti, jezikovnih lastnosti ter zmožnosti združevanja funkcionalnih in ki jo geometrijski objekt zariše med sprehajanjem, je sestavljena objektno usmerjenih tehnik programiranja še posebej primeren iz odtisa njegovih številnih vmesnih stanj znotraj meja slikovne za raziskovalno ustvarjalno prakso. Z uporabo poenostavljene površine, določenih z uporabo generatorjev naključnih števil, v sintakse in modela grafičnega programiranja nam je oblikovanje našem primeru funkcije random(). Vmesna stanja naključnega z algoritmi dalo skoraj neomejene variacije znotraj parametrov, sprehajalca so običajno sestavljena iz njegove trenutne lege in ki smo jih določili na začetku ustvarjalnega procesa. Medtem ko funkcije, ki lahko to lego spremeni. Naključne sprehajalce je smo lahko nadzorovali meje ustvarjenih vizualnih elementov, mogoče uporabiti na različne načine, kot je risanje črt ali oblik nismo imeli nadzora nad rezultati. Ta nepredvidljivost se je ali manipuliranje s podatki. pokazala kot močna analogija za prihodnost tehnologije, ob tem Najenostavnejši pristop za ustvarjanje naključnega pa se je izpostavilo vprašanje: kako nadzorujemo tisto, kar smo sprehajalca je ustvarjanje naključne smeri premikanja objekta pri ustvarili? vsakem koraku, ki pa lahko ustvarja zelo zapletene likovne Ustvarjanje množice različnih preprostih in zapletenih oblik formacije z visoko stopnjo vizualnega šuma. V izogib visoki iz matematičnih formul tako daje procesu oblikovanja znanstveni stopnji vizulanega šuma se opremo na bolj gladek pristop, ki pridih, ki omogoča, da se oblikovanje predstavi kot rezultat temelji na ustvarjanju naključnega sprehajalca, ki sledi smeri strogega in objektivnega procesa. Med drugim smo skozi učni zasuka v prejšnjem stanju. Novo smer ustvarimo tako, da prejšnji proces želeli izvedeti, kako lahko uporaba naključnosti kot kot zasuka spremenimo z naključnim številom. Pri vsakem generativnega načela medijskemu tehniku v vlogi oblikovalca koraku naključnega sprehajalca se trenutni kot zasuka izračuna digitalnega vizualnega podobotvorja ponudi kreativno na podlagi prejšnjega kota zasuka in naključnega števila ter se oblikovalsko okolje. nato premakne za določeno dolžino v smeri trenutnega kota. Razpon izbranega naključnega števila je mogoče zmanjšati ali 2.2 Tehnike kreativnih in funkcionalnih povečati glede na količino želene variacije. Vsak pristop daje pristopov v sintezi vzorcev drugačen vizualni rezultat z različnimi lastnostmi. Številne V prispevku bomo prikazali več tehnik, ki se uporabljajo v parametre je mogoče prilagoditi, da s sprehajalci ustvarimo digitalni generativni umetnosti za ustvarjanje teksturnih vzorcev. različne rezultate. Velikost koraka lahko povečujemo ali Naslednje tehnike so le nekatere izmed mnogih različnih zmanjšujemo glede na velikost formata vizualnega polja procesov, ki se uporabljajo v digitalni generativni umetnosti. umetniškega dela. Povečanje velikosti koraka lahko ustvari poti Izbrali smo jih zato, da pokažemo na široko paleto digitalnega z ostrimi vogali na vsakem koraku, zmanjšanje velikosti koraka vizualnega podobotvorja, ki ga je mogoče ustvariti s preprostimi pa lahko ustvari pot z več krivuljami. Logični in algoritemski del algoritmi. Nekatere izmed jih so prijazne dijakom začetnikom v naključnega sprehajalca je pomemben pri ustvarjanju vizualno kodiranju teksturnih vzorcev, druge, naprednejše, pa so zanimivih rezultatov. Vendar pa obstaja veliko stvari, ki niso namenjene dijakom, ki si izberejo teme iz kreativnega kodiranja logično ali algoritemsko zapletene in lahko prispevajo k za maturo. generativnemu delu. Tako kot tradicionalna umetnost je tudi pri naključnih sprehajalcih pomembno uporabiti elemente umetnosti na učinkovit način. 365 2.4 Vrste šumov strukturo vzorca opazimo na Sliki 3 z vizualizacij sinteze abstraktnega teksturnega vzorca s Worleyevim šumom. Beli šum je zelo preprosta oblika šuma, pri kateri ima vsaka Slika 4 prikazuje eno izmed vizualizacij sinteze abstraktnega slikovna točka naključno izbrano vrednost med 1 in 0. Ker je beli teksturnega vzorca s Voronoijevim šumom. šum nekoherenten šum, bi bil teren, ustvarjen z njim, videti preveč neraven in koničast, da bi bil podoben naravnemu terenu. Perlinov šum [3], pogosto imenovan tudi klasični šum, je razvil Ken Perlin leta 1983. Perlin ga je prvotno ustvaril za film TRON (1982), vendar je hitro postal priljubljen algoritem za proceduralno generiranje, ki temelji na njegovi večnamenski uporabnosti in ker ni bilo patenta na njem. Leta 1996 je Perlin prejel oskarja za svoje delo z računalniško ustvarjenimi podobami v filmih. Perlinov šum dobro posnema naravne oblike in njegovo ponavljanje je težko zaznati. Idealen je za predstavitev kompleksnosti naravnih pojavov. Perlinov šum je mogoče implementirati v n številu dimenzij. Kar zadeva grafiko iger, se običajno uporabljajo samo 1-4 dimenzije. Vendar pa ima nekaj vizualno pomembnih smernih artefaktov. V nasprotju s standardno funkcijo naključnosti, random(), je Perlinov šum koherenten, kar pomeni, da bosta dve sosednji točki imeli podobno vrednost šuma. Zaradi tega so vse naključne variacije enakih velikosti in približno izotropne – videte bodo podobne v vseh smereh in legah. Simpleksni šum je prav tako razvil Ken Perlin leta 2001 kot naslednika Perlinovega šuma, tokrat patentiranega. Rešuje težavo z vizualno pomembnimi smernimi artefakti šuma Perlin. Njegove druge prednosti so hitrejši čas obdelave in nižja računska kompleksnost, kar pride bolj do izraza pri višjih Slika 1: Vizualizacija sinteze abstraktnega teksturnega dimenzijah [3]. vzorca s Perlinovim šumom Worleyjev šum, imenovan tudi celični šum, je razvil Steven Worley leta 1996. To je funkcija, ki zapolni prostor z naključno razporejenimi točkami in poišče razdalje do najbližjih točk. Tako razdeli prostor v naključno zaporedje celic. Zaradi celične lastnosti se pogosto uporablja za simulacijo organskih stvari, kot so razpokan kamen, blato, voda ali biološke celice [4]. Voronojev šum je prilagoditev Worleyjevega hrupa in prav tako deluje tako, da točke naključno razporedi po prostoru, kar povzroči celicam podobne vzorce [5]. Kar zadeva računalniško zapletenost, je Voronojevo ustvarjanje nekoliko dražje od Worleyjevega šuma. Zagotavlja pa dodaten nadzor nad porazdelitvijo točk. Obstaja nekaj različic Voronojevega šuma z nekoliko drugačnimi formulami za izračun. Fraktalni šum je izraz, ki se uporablja za opis kombinacije šumov. Če bi uporabili samo en šum, recimo Perlinov, bi dobili precej enakomerno gladek gorski teren. Tako je običajna praksa mešanja in kombiniranja različnih vrst šumov z različnimi lestvicami in ločljivostmi, da se doseže bolj zanimiva variacija. Uporaba fraktalnih šumov vodi do bolj naravnega videza terena. Konceptualna uporaba kreativnih in funkcionalnih pristopov naključnosti v sintezi abstraktnih vzorcev je prikazana na naslednjih slikah. Slika 1 prikazuje eno izmed vizualizacij sinteze abstraktnega teksturnega vzorca s Perlinovim šumom. Slika 2: Vizualizacija sinteze abstraktnega teksturnega Slika 2 prikazuje eno izmed vizualizacij sinteze abstraktnega vzorca s simpleksnim šumom teksturnega vzorca s simpleksnim šumom. Z dodajanjem različnih iteracij šuma (oktav), kjer zaporedoma povečujemo frekvence v zaporednih korakih (lakunarnost) in zmanjšujemo amplitude (ojačanje) šuma, lahko dosežemo boljšo zrnatost v vizualni strukturi šuma in s tem več finih podrobnosti same strukture abstraktnega vzorca. Takšno 366 Pri implementaciji naključnosti v digitalno vizualno podobotvorje so se dijaki osredotočali predvsem na raziskovanje generativne vizualne estetike, ki temelji na plastičnem eksperimentiranju s kodo. Njihova preprosta grafična dela raziskujejo potencial programiranja kot ekspresivnega jezika v okviru generativnosti in procesne umetnosti. Z eksperimentiranjem v kombiniranju različnih osnovnih geometrijskih oblik, linij in barv, so raziskovali možna razmerja med kaosom in redom, organskim in umetnim, naključnostjo in nadzorom, a hkrati pristopali k 5igitalin površini kot plastičnemu prostoru z uporabo kode kot umetniške materialnosti. Določena mera naključja v postavitvi motiva slikovnih prvin znotraj neke, s formatom omejene digitalne postopkovno generirane grafike, prikazuje vizualno kompleksnost zapletenih geometrijskih vzorcev, sistemov delcev in drugih močnih programskih struktur (rekurzija) v neki strukturirani dinamični kompoziciji, ki je lahko geometrično organizirana ali pa organsko kaotična. Šum zagotavlja prilagodljiv, močan in estetski vir variacije, ki pogosto deluje bolje kot uporaba navadnega generatorja naključnih števil. Obvladovanje psevdonaključnih funkcij je odločilni dejavnik stopnje predvidljivosti rezultatov pri vsaki njegovi ponovitvi ali Slika 3: Vizualizacija sinteze abstraktnega teksturnega celo med enkratno izvedbo, in to je v nekem smislu tisto, kar daje vzorca z Worleyevim šumom umetniškemu delu občutek, da je nekaj živo in živi znotraj same vsebine. Ustvarjanje v polju digitalne generativne umetnosti je iterativni proces digitalnega načrtovanja z vključenim programskim okoljem, ki bo ustvarilo določeno število izhodov, ki ustrezajo določenim omejitvam, in ustvarjalca, ki bo natančno prilagodil izvedljivo območje digitalno ustvarjenega podobotvorja z izbiro določenega izhoda ali spreminjanjem vhodnih parametrov, razponov in porazdelitev. Ustvarjalec se nauči izboljšati program (običajno vključuje algoritme) z vsako ponovitvijo, ko njegovi načrtovalski cilji sčasoma postanejo bolje definirani (Slika 5). Slika 4: Vizualizacija sinteze abstraktnega teksturnega vzorca z Voronoijevim šumom 3 REZULTATI IMPLEMETACIJE NAKLJUČNOSTI Sinteza vizualnih teksturnih 2D vzorcev je splošna tehnika, ki jo uporabljamo pri računalniško podprtem oblikovanju in ustvarjanju digitalnih vsebin. Teksturne vzorce lahko razumemo kot vizualne konfiguracije različnih geometrijskih struktur, ki Slika 5: Proces načrtovanja v digitalni generativni kažejo na visoko stopnjo naključnosti katerih vizualna kakovost umetnosti je določena s tem, kako zvesto poustvarijo izvorni vzorec. 367 Na naslednjih slikah (Slika 6, 7, 8, 9 in 10) so prikazane digitalne grafike, ki praktično vizualizirajo sinteze abstraktnih teksturnih vzorcev z različnimi tehnikami, od preproste funkcije random() do različnih generirarnih šumov. Slika 8: Vizualizacija sinteze abstraktnega teksturnega vzorca z Worleyevim šumom Slika 6: Vizualizacija sinteze abstraktnega teksturnega vzorca s funkcijo random() Slika 9: Vizualizacija sinteze abstraktnega teksturnega vzorca z Voronoijevim šumom Slika 7: Vizualizacija sinteze abstraktnega teksturnega vzorca z naključnim sprehajalcem 368 Implementacija naključnosti v digitalno podobotvorje je od dijakov zahtevala določeno mero spoznavanja in razumevanja dololočenih matematičnih vsebin ter eksperimentiranja v različnih situacijah. Kreativno delo v parih in/ali skupinah je omogočalo razvijanje tako naravoslovne kot digitalne komunikacije. Interpretacija možnih konfiguracij abstraktnih tekstur in njihove morebitne napovedi so puščala dijakom veliko prostora za nova spoznanja. Ob izmenjevanju idej, situacij in razprav po opravljenih vizualizacijah se je krepile ustvarjalnost dijakov, kajti njihovo sodelovanje pri pripravi ustreznih programskih kod je delo na področju računalniške grafike naredilo še bolj zanimivo in raziskovalno. Ob tem so nenazadnje spoznali, da lahko vizualizacija tekstur s proceduralno generacijo ob pomoči nekaj ročno zapisanih pravil in računalniško generiranega naključja ustvarja neskončno množico podobnih, a vseeno še raznolikih konfiguracij, ki jo uporabijo kot samostojno podobotvorje ali pa konstruktivno vsebino za generacijo svetov v računalniških animacijah ali igricah. Izkušnje, pridobljene s pisanjem preprostih računalniških programov za generiranje abstraktnih teksturnih vzorcev, ali medsebojne izkušnje, ki so jih dijaki pridobili med razvijanjem naravoslovne in digitalne komunikacije, so pripomogle k razvoju digitalne pismenosti in Slika 10: Vizualizacija sinteze abstraktnega teksturnega razumevanju uporabe računalniških metod v ustvarjanju vzorca z Worleyevim šumom in sistemom delcev digitalne umetnosti. 4 ZAKLJUČEK 5 VIRI Proces generativne umetnosti kaže dualno naravo: po eni strani zahteva tako razvoj sistema, po drugi pa tudi razvoj metode [1] Babič, D. (2019). Kreativno kodiranje v medijski produkciji. V U. Rajkovič, vizualizacije za rezultat sistema. En sam sistem lahko povzroči B. Batagelj (ur.), Zbornik 22. Mednarodne multikonference Informacijska družba. Zvezek J. Ljubljana: Institut »Jožef Stefan«. Pridobljeno na zelo heterogene rezultate, če uporabljamo različne pristope http://library.ijs.si/Stacks/Proceedings/InformationSociety/2019/IS2019_Vo vizualizacije. Mešanje in ujemanje obstoječih sistemov in metod lume_J%20-%20VIVID.pdf [2] Kyunghyun K., Tek-Jin N. (2013). Designing Unique Products with Self- vizualizacije ter razvoj novih skozi čas je temelj ustvarjanja v morphing Randomness. Department of Industrial Design, KAIST, Daejeon, generativni umetnosti. Digitalna generativna umetnost ni nobena Korea. Pridobljeno na http://aodr.org/xml/01482/01482.pdf izjema. Vizualizacija lepote preprostih dinamičnih sistemov [3] Perlin, K. (2001). Standard for perlin noise. Pridobljeno na http://www.google.com/patents/US6867776 skozi preprosto programsko kodo, pri kateri cilj ni vnaprej [4] Ebert, D., Musgrave, K., Peachey, D., Perlin, K., & Worley, S. (2003). določen, sam ustvarjalni proces pa temelji na odkrivanju, Texturing & modeling: A procedural approach (3. ed.). San Francisco: Morgan Kaufman Publishers. spreminjanju in raziskovanju večinoma nepričakovanih [5] Short, T. & Adams, T. (2017). Procedural generation in game design. Boca rezultatov, je tipičen primer uporabe naključnosti v računalniški Raton: CRC Press, Taylor & Francis Group. umetnosti. Lahko potrdimo, da naključni faktor le omogoča umetnikom, da dobijo rezultate, ki bi jih z ročnim postopkom precej težko dosegli, kar se nanaša na ustvarjanje abstraktnih teksturnih vzorcev. 369 Malokodno programiranje in razvoj spletnih aplikacij Low–Code Programming and Web Application Development Alenka Baggia Robert Leskovar Fakulteta za organizacijske vede Fakulteta za organizacijske vede Univerza v Mariboru Univerza v Mariboru Kranj, Slovenija Kranj, Slovenija alenka.baggia@um.si robert.leskovar@um.si Uroš Rajkovič Andreana Baeva Motušić Fakulteta za organizacijske vede European Business Association Univerza v Mariboru Zagreb, Hrvaška Kranj, Slovenija aba@epu.hr uros.rajkovic@um.si POVZETEK ABSTRACT Malokodno programiranje in razvoj spletnih aplikacij je eden od Low-code programming and web application development is one načinov kako pospešiti digitalno poslovno transformacijo. Med of the modes to accelerate digital business transformation. There zahtevami po hitrem razvoju zanesljivih in stroškovno is a huge gap between the requirements for the rapid sprejemljivih aplikacij ter zmogljivostjo razvijalskih kapacitet v development of reliable and cost-effective applications and the sektorju IT zeva ogromen prepad. Za uspešno obvladovanje teh capacity of development personel in the IT sector. To zahtev je potrebno usposobiti več domenskih strokovnjakov successfully manage these requirements, it is necessary to train (specifične poslovne funkcije) za delo z novimi razvojnimi several domain experts (specific business functions) to work with programskimi orodji. Ta tako njim kot tudi razvojnim new development software tools. This enables new, innovative specialistom s področja IT omogočajo nove, inovativne poslovne business solutions for both them and IT development specialists. rešitve. Orodja za malokodno programiranje se od orodij za Low-code programming tools differ from no-code programming brezkodno programiranja ločijo po tem, da so slednja namenjena tools in that the latter are intended for non-professional laičnim razvijalcem. Posledično so rešitve zamrznjene v okvir developers. As a result, solutions are frozen within the samega orodja. Malokodna orodja pa omogočajo tudi zelo framework of the tool itself. On the contrary low-code tools also detajlno prilagajanje z določenimi programskimi jeziki. allow very detailed customization with specific programming Malokodno programiranje v primeru preprostih spletnih aplikacij languages. Low-code programming in the case of simple web ne zahteva poglobljenega znanja s področja modeliranja baz applications does not require in-depth knowledge of database podatkov in uporabniškega vmesnika. Zato ga lahko kreativno modeling and user interface. Therefore, it can be used creatively uporablja širši krog ljudi. V okviru projekta Erasmus+ Better by a wider range of people. As part of the Erasmus+ Better Employability for Everyone with APEX (BeeAPEX) bomo Employability for Everyone with APEX (BeeAPEX) project, we razvili elektronska gradiva, ki bodo študentom različnih will develop electronic materials that will enable students of usmeritev (družboslovje, tehnika, naravoslovje, medicina, itd.) in various orientations (social sciences, engineering, natural zainteresiranim posameznikom izven univerze (zaposlenim in sciences, medicine, etc.) and interested individuals outside the nezaposlenim) omogočila: a) učenje malokodnega orodja za university (employed and unemployed) to: a) learn of a low-code inovativno uporabo v procesih poslovne digitalne transformacije tool for innovative use in business digital transformation in b) povečati digitalne kompetence udeležencev. processes and b) to increase the digital competences of the participants. KLJUČNE BESEDE Malokodno programiranje, razvoj aplikacij, e-izobraževanje, KEYWORDS zaposljivost Low code programming, application development, e-education, employability 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 1 UVOD 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). Kot v svoji viziji in poti za digitalno preobrazbo Evrope do leta Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 2030 ugotavlja Evropska komisija, Evropa potrebuje večje 370 število IKT strokovnjakov, višjo stopnjo digitalnega znanja predstavljata primer razvoja aplikacije automatizacijo dostopa v prebivalstva ter večjo uravnoteženost spolov na področju IKT okolju Oracle APEX. Baggia, Leskovar in Rodič [4] [1]. Eden od pristopov, s katerim lahko v kratkem času razširimo predstavljajo pozitivne izkušnje z uvajanjem pristopa znanje s področja razvoja aplikacij ter povečamo stopnjo malokodnega programiranja v visokošolski izobraževalni sistem. digitalnega znanja prebivalstva, je vsekakor razvoj aplikacij s Malokodni pristop so uporabili tudi za razvoj aplikacij za nadzor pristopom malokodnega programiranja. Zanimanje za platforme, širjenja COVID-19, pri čemer je bil posebej izpostavljen izziv, ki omogočajo razvoj rešitev s pristopom malokodnega da je potrebno aplikacijo razviti hitreje, kot pa se širi virus [13]. programiranja, narašča [2], saj s tovrstnim pristopom lahko z minimalnim znanjem programiranja razvijemo učinkovite poslovne spletne aplikacije. 3 BOLJŠA ZAPOSLJIVOST Z ORACLE V skladu s programom Evropske komisije za posodobitev APEX evropskih visokošolskih sistemov [3] bi moralo visoko šolstvo okrepiti posameznikove potenciale ter opremiti diplomante z 3.1 Malokodno programiranje in razvoj znanjem in temeljnimi prenosljivimi kompetencami, ki jih aplikacij potrebujejo za da bi bili uspešni v poklicih, ki zahtevajo visoka znanja in spretnosti. V praksi imajo danes diplomanti EU težave Pristop malokodnega programiranja najpogosteje uporabljamo pri iskanju kakovostne zaposlitve s polnim delovnim časom na za razvoj aplikacij v oblačnih storitvah [7]. Na ta način nam svojem področju študija. Po drugi strani delodajalci ne morejo ponudniki omogočajo ne le razvoj z malo znanja programiranja, zadovoljiti potreb po visokokvalificiranem osebju, ki ima znanja pač pa tudi možnost za razvoj aplikacij brez dodatne IKT s področja informatike ter praktične digitalne spretnosti. V opreme. Na sliki 1 so prikazani sloji tipične malokodne razvojne programu Evropske komisije [3] je kot eden od izzivov navedeno platforme. tudi posodabljanje učnih načrtov glede na spreminjajoče se potrebe, pri čemer so problem predvsem počasni odzivi institucij. V okviru projekta BeeAPEX naslavljamo problem neskladja med znanjem diplomantov in IT veščinami, ki se zahtevajo na trgu dela, z vključevanjem delodajalcev (podjetje Oracle in lokalna MSP) pri oblikovanju in izvajanju tečajev s področja malokodnega programianja. Glede na pozitivne predhodne izkušnje z okoljem za malokodno programiranje Oracle Application Express (APEX) [3, 4], smo se projektni partnerji iz 6 držav odločili, da v okviru Erasmus+ projekta Better Employability for Everyone With APEX (BeeAPEX), pripravimo elektronski učbenik, s katerim bi spodbudili uporabo ter razširili znanje malokodnega razvoja aplikacij tudi na kader, ki ni specializiran na področju informacijske tehnologije (IT). Kot kažejo podatki je v Sloveniji delež organizacij, ki uporabljajo pristope z malo ali nič programiranja zelo nizek [6], kar še dodatno nakazuje na potrebo po tovrstnem izobraževanju. 2 PREGLED LITERATURE Malokodne razvojne platforme so enostavne za uporabo in jih večja tehnološka podjetja vedno bolj promovirajo, da bi omogočila posameznikom in organizacijam razvoj programskih rešitev z minimalnim znanjem programiranja [7]. Med bolj Slika 1: Sloji malokodne razvojne platforme znanimi razvojnimi platformami tako lahko omenimo Mendix (povzeto po [7]) [8], Microsoft PowerApps [9], Google App Sheet [10] in Oracle APEX [11]. Čeprav pristop malokodnega programiranja še Komponente posameznih slojev malokodne razvojne vedno zahteva nekaj osnovnega znanja programiranja, pa je platforme lahko razvrstimo v tri nivoje [7]. Na prvem nivoju tovrsten razvoj aplikacij hitrejši, cenejši, predvsem pa se ga lahko imamo orodje za razvoj aplikacije, na drugem orodja za enostavneje naučimo. Gartner [12] ocenjuje, da bodo do leta upravljanje strežniškega sistema, na tretjem pa orodja za 2024 večino poslovnih aplikacij razvijali strokovnjaki izven upravljanje z zunanjimi storitvami integriranimi na platformo. področja IT. Na sliki 2 je prikazano osnovo orodje za razvoj aplikacij v Oracle Kot ugotavljajo Rek, Beranič in Heričko [6], se orodja za APEX. razvoj aplikacij z malo ali nič programiranja uporabljajo v najrazličnejših industrijah. V literaturi zasledimo vedno več primerov aplikacij razvitih s pristopom malokodnega programiranja. Talesra in Nagaraja [2] v svojem prispevku 371 osredotočili samo na osnovna orodja. V nadaljevanju podrobneje predstavljamo aktivnosti, ki bodo izvedene v okviru projekta. 3.3 Aktivnosti v okviru projekta BeeAPEX Znanje s področja malokodnega programiranja bomo v okviru projekta BeeAPEX širili na različne načine. V prvi vrsti bomo pripravili kratek spletni tečaj malokodnega programiranja v Slika 2: Izsek orodja za razvoj aplikacij v Oracle APEX okolju Oracle APEX. Tečaj bo vključeval vsebine od oblikovanja in razvoja baze podatkov, do osnovnega razvoja 3.2 Oracle APEX aplikacij. V prvotni obliki bo tečaj razvit v angleškem jeziku, nato pa preveden v vseh 6 jezikov: slovenski, hrvaški, slovaški, Oracle APEX je spletno razvojno okolje, ki ga je Oracle najprej nemški, poljski in grški. Vsebina tečaja bo prosto dostopna, ponudil kot dodatek k bazi podatkov, ki omogoča enostaven hkrati pa jo bo mogoče uporabljati v okviru študijskega procesa razvoj aplikacij na bazi podatkov [14]. Danes lahko Oracle sodelujočih institucij. Da bi informacijo o možnosti vključitve v APEX uporabljamo tudi kot oblačno storitev, za izobraževalne tečaj razširili med študenti, izobraževalnimi institucijami in namene je možna brezplačna registracija delovnega prostora, v delodajalci, bomo pripravili 6 kratkih spletinarjev (angl. katerem lahko v omejenem obsegu ustvarjamo svojo bazo webinar), ki bodo prav tako prevedeni v vseh 6 jezikov. Poleg podatkov, določamo tabele, vnašamo podatke ter seveda kratkega tečaja, bomo pripravili vsebino za napredni tečaj razvijamo spletne aplikacije. Osnovna orodja, ki so na voljo v oziroma izbirni predmet v obsegu 75 ur oziroma 3 ECTS. Učni spletnem vmesniku vidimo na sliki 1. Uporabljamo lahko App načrt predmeta bo vseboval tako predavanja, praktične vaje, Builder za izdelavo, uvoz in urejanje aplikacij, SQL Workshop naloge ter omogočal ocenjevanje dela študenta. Vključenih bo za delo z bazo podatkov in objekti na bazi podatkov, Team tudi 12 študij primerov, ki bodo razvite v sodelovanju s Development za učinkovitejše delo v skupini ter Gallery, v kateri predstavniki poslovnega sektorja, da bodo odraz dejanskih si lahko ogledamo nekaj pred pripravljenih delov aplikacij. rešitev v praksi. Predmet bo prosto dostopen, hkrati pa bodo V okviru projekta BeeAPEX bomo za udeležence sodelujoče ustanove pripravile dokumentacijo za priznanje izobraževanja pripravili elektronski učbenik in primere s izbirnega predmeta v posamezni državi. Pri obeh tečajih bomo katerimi se bodo lahko seznanili z nekaterimi od enostavnejših vsebino testirali na pilotnih aktivnosti, ki se jih bodo udeležili možnosti, ki jih ponuja Oracle APEX. V začetni fazi bo potrebno srednješolci in študenti. definirati ali pa uvoziti tabele v bazi podatkov in jih po potrebi Poseben poudarek bomo v okviru projekta namenili tudi napolniti s testnimi podatki. Na sliki 3 je prikazano okno SQL izobraževanju visokošolskih učiteljev. Na delavnico v obsegu 30 Workshop, ki omogoča pregled objektov v bazi podatkov ter ur bomo povabili visokošolske učitelje iz 6 držav, prednostno izvajanje SQL ukazov in skript. učitelje s področja družboslovja, ter jim prikazali možnosti uporabe Oracle APEX za razvoj enostavnih aplikacij, ki jih bodo lahko uporabili v svojem študijskem procesu. Posebno pozornost bomo namenili tudi temu, da bo v delavnico vključenih tudi vsaj polovico učiteljic, saj je ženski spol na področju IT izobraževanja slabše zastopan. V okviru promocijskih aktivnosti projekta, bomo naše rezultate predstavili tako srednješolskim ustanovam, Slika 3: Oracle APEX SQL Workshop visokošolskim ustanovam ter tudi delodajalcem. Eno ključnih orodij, ki jih bomo uporabili v okviru 3.4 Vsebina izobraževanja izobraževanja je tudi App Builder, v katerem izdelamo ali uvozimo aplikacijo, ter jo nato tudi urejamo. Na sliki 4 je Eden od ključnih rezultatov projekta BeeAPEX je tudi gradivo prikazano okno za urejanje aplikacije. za izvedbo izbirnega predmeta oziroma kreditno ovrednotene obštudijske dejavnosti v obsegu 3 ECTS. Osnovno gradivo za samostojni študij študenta bo elektronski učbenik, ki bo poleg pisnega gradiva vključeval še skripte za pomoč pri gradnji modelov ter video posnetke s primeri. Prvi del učbenika bo vseboval navodila s primeri, kako začnemo z Oracle APEX, kako modeliramo podatke, kako se orientiramo v razvojnem okolju, kako uvozimo podatke, oblikujemo prvi osnutek aplikacije, kakšna je razlika med obrazci in poročili, kako oblikujemo grafične prikaze, kako Slika 4: Urejanje aplikacije v Oracle APEX upravljamo z meniji. Udeležencem izobraževanja bodo prikazane tudi nekatere naprednejše teme ko je sodelovanje V malokodni razvojni platformi Oracle APEX imamo veliko skupine v razvojnem okolju, kako si lahko pomagamo z galerijo možnosti za razvoj aplikacij, vendar se bomo zaradi potreb predpripravljenih aplikacij in vtičnikov ter kako razvijemo projekta BeeAPEX, ki katerega ciljna skupina so razvijalci z aplikacijo v več jezikih. Na sliki 5 je prikazana delovna verzija minimalnim znanjem s področja informacijske tehnologije, kazala elektronskega učbenika. 372 Slika 7: Primer relacijskega podatkovnega modela Udeležencem izobraževanja bo na voljo skripta z ukazi za kreiranje tabel v bazi podatkov ter ukazi z osnovnimi testnimi podatki. Izsek videoposnetka z navodili za uvoz skripte z ukazi za kreiranje in testnimi podatki je prikazan na sliki 8. Slika 5: Delovna verzija kazala elektronskega učbenika V drugem delu priročnika bomo udeležence izobraževanja seznanili z 12 različnimi primeri razvoja aplikacij. Vsebino primerov bomo oblikovali skupaj s poslovnimi partnerji, da bodo vključevali dejanske probleme iz prakse. Med predlogi primerov so tako intranet aplikacija za zaposlene, katalog rastlin, platforma za sodelovanje okoljske organizacije, sistem za prijavo inovacij, sistem za upravljanje dokumentov, spletna trgovina, sistem za razporejanje tečajev, oblikovanje kosovnice in stroškovnik, sistem za izposojo avtomobilov in podobno. Vsak primer bo na začetku opisan in predstavljen tudi v obliki diagrama primera uporabe. Na sliki 6 je prikazan diagram primera uporabe za Slika 8: Izsek posnetka za uvoz skripte v Oracle APEX intranet aplikacijo. Posnetki, ki bodo prikazovali razvoj aplikacije v vsakem od 12 primerov bodo opremljeni z navodili, ki bodo prevedena v vseh 6 jezikov. Na sliki 9 je prikazana intranet aplikacija za zaposlene, v kateri so pravice vpogleda v posamezne obrazce določene glede na pravice uporabnika, ki se lahko razvrsti v eno od 3 skupin uporabnikov: upravljalec aplikacije, uporabnik s pravico objavljanja novic in običajni uporabnik s pravico pregledovanja intranetnih novic. Na sliki 9 je prikazan vpogled upravljalca aplikacije, ki ima dostop do vseh obrazcev in poročil v aplikaciji. Slika 6: Diagram primera uporabe za intranet aplikacijo Opisu primera bo sledila predstavitev baze podatkov, najprej v obliki logičnega modela, nato pa še v obliki relacijskega podatkovnega modela. Na sliki 7 je prikazan relacijski podatkovni model, ki služi kot osnova za razvoja intranetne aplikacije za zaposlene. Slika 9: Intranet aplikacija za zaposlene Na podoben način kot primer intranet aplikacije bodo predstavljeni tudi ostali primeri v elektronskem priročniku. V zaključku elektronskega priročnika bomo za izobraževalne ustanove pripravili tudi obrazce za akreditacijo učnih vsebin v državah partnerjev projekta BeeAPEX. 373 4 ZAKLJUČEK LITERATURA IN VIRI [1] Evropska komisija, “Evropska deklaracija o digitalnih pravicah in načelih za Predlagani projekt bo podprl digitalno poslovno transformacijo digitalno desetletje,” Bruselj, 2022. visokošolskih institucij z razvojem digitalne pripravljenosti, [2] K. Talesra and G. S. Nagaraja, “Low-Code Platform for Application odpornosti in zmogljivosti tako akademskega osebja kot tudi Development,” Int. J. Appl. Eng. Res. , vol. 16, no. 5, pp. 346–351, 2021. študentov. Pripeljal bo do posodobitve učnih načrtov in [3] Evropska komisija, “Spodbujanje rasti in delovnih mest – program za posodobitev evropskih visokošolskih sistemov,” Bruselj, 2011. predmetov s področja informacijske tehnologije na področjih, [4] A. Baggia, R. Leskovar, and B. Rodič, “Low code programming with oracle malokodnega programiranja, oblikovanja aplikacij in baz APEX offers new opportunities in higher education,” in 3rd International podatkov. Takšen pristop bo študentom ne tehničnih smeri Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture, 2019. omogočil, da se izpopolnijo na področju IT, kar bo povečalo [5] A. Baggia, A. Mali, A. Grlica, and R. Leskovar, “Oracle APEX in Higher njihovo zaposljivost in zapolnilo vrzel med povpraševanjem in Education,” in Proceedings of the 37th International Conference on ponudbo razvijalcev IT. Organizational Sciences Development, 2018, pp. 27–38. Kot ugotavljajo [6], je delež organizacij, ki v Sloveniji [6] P. Rek, T. Beranič, and M. Heričko, “Študija pričakovanj in uporabnosti orodij za razvoj aplikacij z malo ali nič programiranja,” Uporab. Inform. , no. SE- uporabljajo pristope z malo ali nič programiranja, nizek, kar se Znanstveni prispevki, Jul. 2022. razlikuje od globalne slike. V svetu je tovrstnih podjetij bistveno [7] A. Sahay, A. Indamutsa, D. Di Ruscio, and A. Pierantonio, “Supporting the več (41 %). Predvidevamo, da bo tudi priprava učnih gradiv, ki understanding and comparison of low-code development platforms,” in 2020 46th Euromicro Conference on Software Engineering and Advanced bodo nastala v okviru Erasmus+ projekta Better Employability Applications (SEAA), 2020, pp. 171–178. for Evernyone with APEX, spodbudila izobraževalne ustanove [8] Mendix Technology BV, “No Title,” Mendix: Go make it, 2022. [Online]. ter tudi posameznike k večji uporabi malokodnih razvojnih okolij Available: https://www.mendix.com/. [9] Microsoft, “Power Apps,” The world needs great solutions. Build yours ter s tem približala Slovenijo in ostale sodelujoče države faster. , 2022. [Online]. Available: https://powerapps.microsoft.com/en-us/. globalnemu trendu na področju malokodnega razvoja aplikacij. [10] Google, “AppSheet,” The fastest way to build apps and automate work, 2022. [Online]. Available: https://about.appsheet.com/home/. ZAHVALA [11] Oracle, “Oracle APEX,” Build enterprise apps 20x faster with 100x less code, 2022. [Online]. Available: https://apex.oracle.com/en/. Prispevek je nastal ob podpori Evropske komisije z nepovratnimi [12] Gartner Inc., “Gartner Says the Majority of Technology Products and Services sredstvi v okviru ključnega ukrepa 2: Sodelovanje med Will Be Built by Professionals Outside of IT by 2024,” 2021. [Online]. Available: https://www.gartner.com/en/newsroom/press-releases/2021-06- organizacijami in institucijami – Sodelovalna partnerstva za 10-gartner-says-the-majority-of-technology-products-and-services-will-be- projekt KA220-HED-15/21 Better Employability for Everyone built-by-professionals-outside-of-it-by-2024. with APEX (BeeAPEX). Vsebina tega prispevka ne odraža nujno [13] J. Varajão, “Software Development in Disruptive Times: Creating a Software Solution with Fast Decision Capability, Agile Project Management, and stališča ali mnenja Evropske komisije. Za izražena mnenja Extreme Low-Code Technology,” Queue, vol. 19, no. 1, pp. 94–103, Feb. odgovarjajo samo avtorji in se zato ta ne morejo šteti za uradno 2021. stališče Evropske komisije. [14] A. Geller and B. Spendolini, Oracle Application Express: Build Powerful Data-Centric Web Apps with APEX 5. New York: McGraw-Hill Education, 2017. 374 Pouk na daljavo: e-kulturni dan Distance Learning: An E-Cultural Day Živa Blatnik OŠ Toma Brejca Kamnik, Slovenija ziva.blatnik@gmail.com POVZETEK that pupils visit a cultural and artistic institution (cinema, theater, museum, archive, gallery, concert hall, etc.) at least once a year. Dnevi dejavnosti so tisti del obveznega programa osnovne šole, With the help of ICT, we tried to bring the aforementioned ki medpredmetno povezujejo discipline in predmetna področja, institutions and their activities closer to the pupils even during vključena v predmetnik osnovne šole. Med dneve dejavnosti distance learning. sodijo tudi kulturni dnevi, v sklopu katerih je priporočeno, da bi osnovnošolci vsaj enkrat letno obiskali kulturno-umetniško The article presents the planning and execution of a cultural day ustanovo (kino, gledališče, muzej, arhiv, galerija, koncertna entitled Theater Workshops. Pupils from the 6th to the 9th grade dvorana …). Omenjene ustanove in njihove dejavnosti smo watched the drama Kit on the Beach online, adapted from učencem s pomočjo IKT skušali približati tudi v času pouka na Möderndorfer's youth novel. Watching the drama was followed daljavo. by the expression of impressions and opinions in the form of an online questionnaire in an online classroom. The second part of V prispevku je predstavljeno načrtovanje in izvedba kulturnega the cultural day required more active participation from the dne z naslovom Gledališke delavnice. Učenci od 6. do 9. razreda pupils. The 6th and 7th grade pupils recreated a dramatic scene, so si na spletni povezavi ogledali dramsko igro Kit na plaži, made literary characters in the form of shadow puppets and prirejeno po Möderndorferjevem mladinskem romanu. Po imaginatively designed shadow theaters. They acted out the ogledu je sledilo izražanje vtisov in mnenja v obliki spletnega scene and uploaded photos and videos to the online classroom as vprašalnika v spletni učilnici. Drugi del kulturnega dne je od evidence of active participation in the cultural day. The 8th and učencev zahteval več aktivne udeležbe. Učenci 6. in 7. razreda 9th grade students demonstrated and improved their literary so poustvarili dramski prizor, v obliki senčnih lutk izdelali knowledge by solving challenges in the online escape room, književne osebe in domiselno oblikovali senčna gledališča. which we designed using the Google Forms web tool. They were Prizor so odigrali in fotografije ter posnetke naložili v spletno quite motivated to solve the escape room. They also looked for učilnico kot dokaze aktivnega udejstvovanja na kulturnem dnevu. information online and connected with their classmates. Despite Učenci 8. in 9. razreda pa so svoje literarnovedno znanje the activities adapted to the online environment, the students dokazovali in nadgrajevali ob reševanju izzivov v spletni sobi liked the cultural day, so we can summarize that the methods and pobega, ki smo jo oblikovali v spletnem orodju Google Forms. forms of work were chosen accordingly. Za reševanje sobe pobega so bili precej motivirani. Podatke so iskali tudi na spletu in se povezali s sošolci. Kljub spletnemu KEYWORDS okolju prilagojenim dejavnostim je bil kulturni dan učencem všeč, zato lahko povzamemo, da so bile metode in oblike dela Distance learning, cultural day, Google Forms, online escape ustrezno izbrane. room KLJUČNE BESEDE 1 UVOD Pouk na daljavo, kulturni dan, Google Forms, spletna soba Dnevi dejavnosti vzpodbujajo vedoželjnost, ustvarjalnost in pobega samoiniciativnost učenk in učencev, jih usposabljajo za ABSTRACT samostojno opazovanje in pridobivanje izkušenj in znanja, za razvijanje spretnosti ter za samostojno reševanje problemov. Ob Activity days are that part of the compulsory primary school teh dejavnostih učenci in učenke znanje različnih področij med program that cross-curricularly connects the disciplines and seboj povezujejo v celoto. Dnevi dejavnosti so namenjeni vsem subject areas included in the primary school curriculum. Activity učenkam in učencem, so vsebinsko pestri in smiselno razporejeni days also include cultural days, during which it is recommended skozi vse šolsko leto. Vsebinsko se nadgrajujejo iz leta v leto oziroma iz triletja v triletje [1].V okviru pouka na daljavo je bilo Permission to make digital or hard copies of part or all of this work for personal or za učitelje ali zunanje izvajalce pravi izziv pripraviti dan 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, ki bi bil učencem v izziv, v katerem bi bili aktivni in citation on the first page. Copyrights for third-party components of this work must bi ob tem tudi uživali ter razvijali svoji vedoželjnost in be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia sposobnost samostojnega reševanja problemov. Še posebej pri © 2022 Copyright held by the owner/author(s). pripravi kulturnih dni je največ težav predstavljalo vprašanje, 375 kakšne naloge oz. izdelke naj zahtevamo od učencev kot dokazilo o sodelovanju in učenju za namene spremljanja napredka učencev. Ker je Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji pokazala [2], da so učitelji predmetnega pouka kot dokazilo o učenju in napredovanju od učencev zahtevali, naj jim posredujejo izpolnjene učne liste, rešene naloge v delovnem zvezku in ustne odgovore na zastavljena vprašanja prek videokonference; smo se v drugem valu izdatno trudili pridobivati raznolike dokaze o učenju in napredku, kot bi jih zbrali tudi realnem okolju (v učilnici). Načrtovalci kulturnih dni smo se trudili upoštevati smernice in priporočila [1]: »Učenke in učenci spoznavajo različna jezikovna, družboslovna in umetnostna področja, naravne vrednote in vrednote človeške družbe ter jih med seboj Sliki 1, 2: Navodila za izvedbo kulturnega dne povezujejo. V izvajanju kulturnih dni so učenke in učenci aktivni, to je dejavnosti načrtujejo ter sprejemajo, doživljajo in se Drugo navodilo je učence po ogledu igre usmerilo na izražajo. /…/ Razvijajo ustvarjalnost, sposobnost dojemanja vprašalnik o vtisih v spletni učilnici (Slika 3). spoznanj družboslovnih ved in jezikoslovja, doživljanje umetniške besede, barv, oblik, zvoka in giba ter prepoznavanje, razumevanje in vrednotenje pokrajine in njenih sestavnih delov.« Odločili smo se, da učence od 6. do 9. razreda povabimo k ogledu gledališke predstave, ki je primerna za vse učence omenjenega starostnega razpona. Po ogledu so vsi učenci odgovarjali o svojem doživljanju gledališke predstave, izrazili so vtise in mnenja. Nato pa so učenci 6. in 7. razreda literarno in likovno poustvarjali, starejši učenci pa so se lotili zahtevnejšega spletnega izziva. Zavedali smo se namreč, da imajo starejši učenci že več znanja o gledališki umetnosti. V obzir smo vzeli usmeritve o zmernosti raznolikosti metod in dejavnosti, saj kljub temu, da raznolikost metod in aktivnosti prispeva k ohranjanju radovednosti učencev in njihovi notranji motiviranosti, pa v spletnih učnih okoljih ni dobro preveč eksperimentirati in vanje vnašati preveč novosti, saj lahko to sproži občutke tesnobe in napetosti pri učencih [3]. Slika 3: Vprašalnik o vtisih po ogledu dramske igre V nadaljevanju prispevka bo natančneje predstavljen potek kulturnega dneva na daljavo za učence od 6. do 9. razreda, ki smo Ustvarjalni del kulturnega dne je od učencev 6. in 7. razreda ga poimenovali Gledališke delavnice. Natančneje bo prikazan zahteval zapis kratkega dramskega prizora (poustvarjanje igre, ki postopek izdelave spletne sobe pobega z brezplačnim spletnim so si jo ogledali, ali avtorski prizor), izdelavo senčnih lutk in orodjem Google Forms. preprostega senčnega gledališča. Nato so svoj prizor uprizorili in ob pomoči družinskih članov posneli. V spletno učilnico so 2 NAČRTOVANJE IN IZVEDBA naložili fotografije scenarija, izdelanih lutk in posnetke KULTURNEGA DNE uprizorjenih dramskih prizorov (Sliki 4, 5). 2.1 Načrtovanje kulturnega dne Dva dneva pred kulturnim dnevom so bili učenci preko spletne učilnice obveščeni, kdaj bo potekal kulturni dan in o temi le-tega. Dan pred kulturnim dnevom so bila v spletno učilnico dodana navodila za izvedbo, natančno opisana po korakih (Sliki 1, 2). Prvo navodilo je učencem razkrilo, da si bodo na spletu ogledali dramsko igro Kit na plaži, ki je prirejena po mladinskem romanu Vinka Möderndorferja in so jo odigrali dijaki Škofijske klasične Sliki 4, 5: Fotografiji senčnih lutk in scenarija gimnazije. Spodbujeni so bili, da se uredijo, kot bi bili v gledališču in si predstavo ogledajo zbrano, brez prekinitev. Učenci zadnjih dveh razredov tretje triade so se v tretjem delu kulturnega dne pomerili v miselno-ustvarjalnem izzivu – podali so se v spletno sobo pobega Jaz in gledališče – sem le pozoren gledalec ali tudi pravi poznavalec? Soba pobega (Slika 376 6) je bila oblikovana v spletnem orodju Google Form in je bila sestavljena iz različnih nalog, ki so preverjale: - ali so si natančno ogledali gledališko predstavo, - kako dobro poznajo soustvarjalce gledaliških iger in značilnosti dramatike - in kako blizu jim je gledališki bonton. Slika 7: Nastavitev točnega ključa vrat Slika 6: Vstop v spletno sobo pobega 2.2.2 Statistika. Prva naloga za učence v spletni sobi pobega Učenci so imeli možnost, da si aktivnosti razporedijo skozi je bil zapis imena, priimka in oddelka. Tako lahko učitelj v celoten dan in dokaze svojega kulturnega udejstvovanja razdelku »Odzivi« sledi, kdo je uspešno razrešil vse izzive sobe učiteljem posredujejo do poznega večera. pobega. Nekateri učenci so reševali v parih oz. skupinah. Sledi statistika ostalih rešitev (Slika 8). Orodje beleži tudi nepravilne 2.2 Spletna soba pobega rešitve (učenci so napačno odgovorili, zmotili so se v pravopisu Soba pobega (angleško escape room) je igra, ki poteka v ipd.) prostoru, v katerem je zaprta skupina ljudi, ki mora s pomočjo ugank, računov, namigov ter raznih drugih vrst pomoči poskusiti čimprej (navadno v 1 uri) priti na prostost. Njen nastanek so navdihnile tudi knjige, televizijski šovi in računalniške igre [4]. Igra je priljubljena po vsem svetu, saj udeleženci s kreativnim mišljenjem, iznajdljivostjo, raznolikimi strategijami reševanja problemov in sodelovanjem razrešijo vrsto nalog ter se prebijejo na prostost. Občutek brezizhodnosti in nezmožnost napredovanja brez najdene rešitve udeležence neverjetno notranje motivirata. Nekatera spletna orodja, v našem primeru Google Forms, omogočajo, da znanje učne snovi ne preverjamo z običajnimi vprašanji ali kvizi, temveč vprašanje preoblikujemo v zanimivejšo obliko izziva, ki od udeleženca zahteva točno določeno rešitev ali ključ, ki odpira naslednji izziv in ob zaključku tudi končen izhod iz spletne sobe pobega. Spletno sobo pobega učencem enostavno posredujemo kot vse ostale google dokumente, v obliki spletne povezave. 2.2.1 Oblikovanje točnega ključa. Snovalec sobe pobega (v našem primeru učitelj) pri vsaki nalogi oz. »vratih« nastavi naslednje nastavitve (Slika 7): - kratek odgovor; - besedilo (rešitev je besedilo); - vsebuje (vsebuje točno tisto zaporedje črk, ki jih Slika 8: Statistika rešitev zapišemo na tretjo črto; - na zadnjo črto lahko zapišemo, katero besedilo naj se 2.2.3 Odziv starejših učencev. Kulturni dan je bil organiziran pojavi, če se udeleženec pri zapisu rešite zmoti; aprila 2021, po velikonočnih praznikih, ko je bil za nekaj dni - ne pozabimo označiti, da je odgovor obvezen; ponovno uveden pouk na daljavo, zato smo učitelji predvidevali, - novo nalogo oz. »sobo« pridobimo s kreiranjem da starejši učenci pri izvajanju aktivnosti ne bodo najbolj odzivni. novega razdelka. Učenci so nas pozitivno presenetili, saj se je skozi spletno sobo 377 pobega prebilo kar dve tretjini učencev. Zvedamo se, da so se 4 ZAKLJUČEK med seboj obveščali o rešitvah nalog, vendar jih je spletna soba V času pouka na daljavo je bilo smiselno in zaželeno, da smo pobega kljub temu toliko pritegnila in motivirala, da so želeli izvedli tudi nekaj dni dejavnosti, ki so učence sprostili in priti do konca. Vsekakor pa so za visoko udeležno poskrbeli tudi ustvarjalno zaposlili z aktivnostmi, ki so se razlikovale od elementi brezizhodnosti in tekmovalnosti. običajnih ur pouka na daljavo. Posegali smo po spletnih orodjih, ki učne vsebine popestrijo, medpredmetno povezujejo in učence 3 REZULTATI spodbudijo k aktivni udeležbi. Izkazalo se je, da so si učenci z veseljem ogledali dramsko Učenci predmetne stopnje so si skoraj vsi ogledali gledališko igro, pa čeprav le preko spletne povezave. igro, kar dokazujejo rešeni vprašalniki v spletni učilnici. Večini Mlajši učenci so se odzvali z domiselnimi poustvarjalnimi se je igra dopadla in so v veliki meri razbrali nekaj sporočil. rešitvami, ki so jih dokumentirali v obliki fotografij in videov. Učenci 6. in 7. razreda so bili nadvse ustvarjalni pri zapisu Velik del starejših učencev je spletna soba pobega motivirala, avtorskih dramskih prizorov in so ustvarili preproste, a da so razmišljali o literarnovednih pojmih, poklicih v gledališču domiselne senčne lutke in gledališča. Izkazali so se tudi pri in oliki. Nekateri izmed njih so se skozi naloge prebili s pomočjo snemanju prizorov z mobilnimi telefoni in posnetke uspešno lastnega znanja, drugi pa so razvijali sposobnost iskanja naložili v spletne učilnice. Z dovoljenjem učencev smo nekaj podatkov v zapiskih, na spletu ali v pogovoru s sošolci. najizvirnejših objavili na šolski spletni strani: Uporaba spletnega orodja Google Forms se je izkazala kot https://www.youtube.com/watch?v=b6K9eewbtOI&t=5s&ab_c enostavna in učinkovita metoda za osvajanje, preverjanje in hannel=O%C5%A0TomaBrejca. utrjevanje znanja, še bolj pa kot sredstvo za spodbujanje Osmošolci in devetošolci so morali za uspešno rešitev sobe motivacije učencev in učenje na inovativen in igriv način. pobega dobro poznati in razumeti vsebino dramske igre, natančno slediti navodilom, da so odkrili posamezne ključe, si pozorno ogledati nekaj posnetkov, ponoviti literarnovedne 5 LITERATURA IN VIRI pojme, ki se navezujejo na dramatiko. Osvežili so tudi, kdo vse [1] Dnevi dejavnosti. Ministrstvo za znanost, izobraževanje in šport. Dostopno sodeluje pri uprizoritvi gledališke predstave in pravila kulturnega na naslovu vedenja v gledališču. Marsikdo je bil pri reševanju nalog v sobi https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- sola/Ucni-nacrti/Drugi-konceptualni-dokumenti/Dnevi_dejavnosti.pdf (7. 8. pobega aktivnejši, kot je navadno pri izkazovanju znanja v 2022). učilnici. [2] dr. Tanja Rupnik Vec (ur.) 2020. Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji. Ljubljana: Zavod Republike Slovenije za šolstvo. Dostopno na naslovu: https://www.zrss.si/pdf/izobrazevanje_na_daljavo_covid19.pdf (7. 8. 2022). [3] Kastelic N., Kmetič E., Lazić T., Okretič L. 2021. Kako motivirati učence pri poučevanju na daljavo? Priročnik za učitelje. Ljubljana: Filozofska fakulteta, Oddelek za psihologijo. Dostopno na naslovu: https://resitve.sio.si/wp- content/uploads/sites/7/2021/12/Kako-motivirati-ucence.pdf (7. 8. 2022). [4] Wikipedija: Soba pobega. Dostopno na naslovu: https://sl.wikipedia.org/wiki/Soba_pobega (7. 8. 2022). 378 Razvijanje digitalnih kompetenc po vertikali Developing Digital Competencies Across Verticals Dunja Blaznik Osnovna šola Vide Pregarc Ljubljana, Slovenija dunja.blaznik@osvp.si POVZETEK As students are increasingly using digital content at home, we thought it would make sense to make the development of digital V povzetku je predstavljeno razvijanje digitalnih kompetenc competences a bit more meaningful, planned and later evaluable. učencev na Osnovni šoli Vide Pregarc. Teachers wrote down which digital skills they think pupils in Učitelji na Osnovni šoli Vide Pregarc skrbimo, da imajo vsi each class need and which they intend to develop in the coming učenci možnost obiska računalniške učilnice in s tem uporabe year. računalniške opreme. Učitelji razredne stopnje se odločajo za uporabo matematičnih platform za utrjevanje znanja, uporabo Based on the suggestions, we wrote a plan to develop the skills programa Slikar, predmetni učitelji za iskanje informacij na by grade or subject, and the necessary software. spletu, ki jih učenci potrebujejo za pripravo projektnih nalog, reševanje interaktivnih nalog, uporabo slovarjev in še kaj bi se KEYWORDS našlo. Developing digital competences, digital literacy, information Glede na to, da učenci vedno več uporabljajo digitalne vsebine technology, teaching across vertical tudi doma, se nam je zdelo smiselno, da razvijanje digitalnih kompetenc nekoliko bolj osmislimo, načrtujemo in kasneje lahko 1 DIGITALNE KOMPETENCE tudi ovrednotimo. Digitalne kompetence so ena izmed ključnih življenjskih znanj Učitelji so po strokovnih aktivih zapisali za katera digitalna med katera spadajo tudi pismenost, večjezičnost, matematična, znanja in spretnosti menijo, da bi jih učenci v posameznem naravoslovna, tehniška in inženirska kompetenca, osebnostna, razredu potrebovali in katere imajo namen v naslednjem letu državljanska, podjetnostna ter kulturna zavest in izražanje. razvijati. Na podlagi predlogov smo zapisali načrt razvijanja Digitalne kompetence združujejo samozavestno, kritično in znanj po posameznih razredih oziroma predmetih in potrebno odgovorno uporabo digitalnih tehnologij. V okvir digitalne programsko opremo. kompetence lahko vključimo informacijsko in podatkovno pismenost, sporazumevanje, sodelovanje, izdelavo samostojnih KLJUČNE BESEDE digitalnih vsebin, varnost, avtorske pravice, reševanje problemov Razvijanje digitalnih kompetenc, digitalna pismenost, in seveda kritično mišljenje [1]. informacijska tehnologija, poučevanje po vertikali Številni avtorji imajo različna mnenje. Nekateri kompetence in pismenost enačijo, nekateri menijo, da ob usvojenih ABSTRACT kompetencah postanemo pismeni, nekateri menijo, da je This summary presents the development of digital competences pismenost širše področje. of pupils at the Vide Pregarc Primary School. Teachers make sure that all pupils have the opportunity to visit 2 ZAČETKI the computer science classroom and use the computer equipment. Teachers are choosing to use maths platforms to consolidate their V želji, da učence čim bolj opolnomočimo z znanjem digitalnih knowledge, using Painter, searching the web for the information vsebin, smo se na šoli odločili, da na šoli digitalne kompetence students need to prepare project assignments, solve interactive razvijamo in nadgrajujemo od 1. do 9. razreda. tasks, use dictionaries and etc. Leta 2020, ko se je začelo nakazovati obdobje dela na daljavo in večina deležnikov na to ni bilo dovolj pripravljenih, smo lahko samo upali, da so naši učenci dovolj opolnomočeni za delo. Do takrat so učenci med poukom redko prihajali v računalniško učilnico. Ko so prišli, so imeli jasna navodila za Permission to make digital or hard copies of part or all of this work for personal or delo, naj preberejo, naj poiščejo, naj narišejo, naj napišejo. Smo classroom use is granted without fee provided that copies are not made or distributed se vprašali ali znajo? 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 Z namenom, da bo delo na daljavo čim bolje izpeljano, smo be honored. For all other uses, contact the owner/author(s). organizirano vabili učence v računalniško učilnico in jim Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). poskušali olajšati delo. Nekaterim delo z računalnikom ni 379 predstavljalo težav, potrebovali so le majhne napotke, drugim je V začetku šolskega leta smo se z učiteljicami uskladile kateri predstavljal stres že prižig računalnika. Ugotovili smo, da vsi termini jim najbolj odgovarjajo in katere teme bi si želeli, da naši učenci niso pripravljeni na delo. Po odzivih jim je bilo v podpremo z digitalnim znanjem. Nekatere učiteljice so bile še pomoč, da smo jim pripravili testno učilnico, kjer so lahko vadili vedno mnenja, da bodo bolj prepričane v delo, če bo pri delu v objavljanje nalog, raziskovanje brez strahu, da se zgodi nekaj računalniški učilnici prisotna še učiteljica računalništva, kar smo neprijetnega. ugodili. Šolsko leto s šolanjem na daljavo smo zaključili, še vedno pa nismo bili prepričani, če so učenci računalniško pismeni. Učenje računalniških veščin, kulturnega vedenja na spletu, varnosti, 4 UČENCI izdelavo digitalnih vsebin smo nadaljevali. Razvijanje veščin učencev je temeljilo na nadgradnji učne V preteklem šolskem letu smo se srečali z novim izzivom. snovi posameznega razreda. V preteklem šolskem letu smo želeli, Računalniško učilnico smo uporabljali tudi za pouk drugih da vsak razred obišče računalniško učilnico vsaj dvakrat v letu. predmetov in je bila večino ur zasedena. Prost so bile le 4 šolske Žal nam to ni uspelo in bomo nadaljevali v letošnjem letu. ure. Z učitelji, ki so poučevali v njej, smo se dogovorili, da za Z učenci prvega razreda smo prvo uro, ko so prišli v učilnico potrebe računalniškega opismenjevanja, učilnice menjamo in najprej spoznali učilnico, pravila dela v njej in spoznali temeljna tako lahko izvedemo ure digitalnih kompetenc. informacijska znanja. Pogovorili smo se, če so že kdaj kaj delali z računalnikom. Večina digitalne naprave (računalnik, prenosni računalnik, tablice, telefone) uporablja dnevno. Uporabljajo jih 3 UČITELJI predvsem za ogled video posnetkov in igranje igric. Na navodilo Ko smo začeli z načrtovanjem razvijanja digitalnih »prižgi računalnik« je imela večina učencev velike težave. V kompetenc, je nemalo učiteljev prišlo do dileme, če so računalniški učilnici imamo stacionarne računalnike, v večini pa usposobljeni za vodenje ur v računalniški učilnici. Ugotovili smo, imajo doma prenosnike in so zato prižigali le monitorje in njihov da se vse kompetence ne razvijajo samo v računalniški učilnici odziv je bil, da računalnik ne dela. Zato je bila naša prva naloga, ter da imamo učitelji dovolj znanja. da se naučimo prižgati računalnik in ga kasneje po končanem Učitelji lahko že ogromno naredimo, ko pri pouku naletimo delu tudi pravilno ugasniti. na neznane pojme in jih s pomočjo spleta razložimo. Pri tem Ure, ki so sledile so bile namenjene preprosti uporabi upoštevamo kritično razmišljanje glede veljavnosti podatkov in programa za utrjevanje matematičnega znanja. Poleg tega so pravila varnega brskanja. Ko potrebujemo fotografijo za objavo usvojili še delo z miško (groba in fina motorika), nadgradili na digitalnih predstavitvah, ne pozabimo na avtorske pravice. koordinacijo oko-roka, tipkanje (kar smo lahko medpredmetno Strinjali smo se, da učitelji varne in kritične rabe tehnologije, ne povezali s poukom slovenščine). moremo naučiti le z zgledom, ampak potrebujemo tudi V juniju, ko je bila učilnica več ur prosta, so učenci prvih specifične kompetence [2]. razredov obiskali učilnico z namenom, da se naučijo programa Slikar. Z učiteljico smo se dogovorili, da program predstavi učiteljica računalništva, same zahteve kaj naj bo na njihovi risbi pa so se z učenci dogovorili že v razredu. Preden so končali delo, so risbo tudi shranili s svojim imenom. Risbe, ki so jih učenci narisali so natisnili in jih odnesli domov. Učenci tretjega razreda že več let prihajajo v računalniško učilnico z namenom iskanja podatkov za pripravo govornega nastopa o slovenskem pesniku ali pisatelju. Letos smo izkoristili še dodatno možnost in so pred to uro imeli še predavanje o varnosti na spletu. Obiskala jih je zunanja Slika 1: Digitalne kompetence za učitelje predavateljica in jim predstavila spletne pasti. Po tej uri so imeli pogovor z učiteljico računalništva, ki so ji lahko zastavili dileme Poskrbeli smo, da je pogovor o delu v računalniški učilnici in vprašanja o delu z računalnikom, varnosti, poukom. Zanimiv stekel. Če sta v učilnici poučevala dva učitelja, sta se o delu je bil pogovor z učencem, ki jo je želel prepričati, da mu dovoli dogovorila, si izmenjala ideje, mnenja kaj učenci znajo, kaj so na šolskem računalniku igrati spletno igrico. Učiteljici se je zdela delali preteklo leto, preteklo uro v računalniški učilnici, s koliko ideja zanimiva in je dovolila. Učenec najbrž ni bil pripravljen, znanja prihajajo. Poskrbeli smo za dogovor o strokovnem znanju njihova razredničarka tudi ne in so bili nekoliko šokirani. učitelja. Učitelj, ki se ne čuti sposobnega predati snov, je lahko Učiteljica računalništva in učenec sta se dogovorila, da igra 3 čudovita podpora drugemu učitelju za pomoč učencem. minute, igra ne sme biti strelska in igro lahko predvajamo na Vsekakor pa je potrebno poskrbeti za stalno strokovno projektorju. Učenec se je usedel za računalnik, odtipkal izpopolnjevanje učiteljev. povezavo, kliknil »ok« na vsa vprašanja in začel z igranjem igre. Na šoli smo v ta namen organizirali »Tržnice znanja«, kjer Po končani igri so izpeljali pogovor. Kaj je potrdil v začetku, kaj smo z učitelji poglabljali računalniška znanja. S tržnicami smo je pisalo, se je z vsem strinjal. Ugotovili smo, da učenec začeli med delom na daljavo in jih nadaljevali tudi v lanskem začetnega besedila ni razumel, a je vseeno potrdil, saj drugače ne šolskem letu. Za tematike smo se dogovarjali sproti. Od osnovnih bi mogel igrati. Uro je učiteljica izkoristila za poglobljen pisarniških programov do programov za urejanje fotografij, pogovor kakšne igre igramo, kaj klikamo in kaj ne, če ne videoposnetkov in kasneje reševanjem izzivov na katere so razumemo vprašamo starejše, da nam obrazložijo, saj lahko hitro naleteli med svojim delov. naletimo na težave. 380 Po tej uri so sledile ure v računalniški učilnici, kjer so učenci hkrati ponovimo tudi uporabo spletne učilnice, ki jo učiteljice iskali podatke za pripravo govornega nastopa. Običajno so matematike redno uporabljajo pri svojem delu. podatke poiskali in si naredili zapiske v njihove zvezke. Tokrat V času ur slovenščine in angleščine je poudarek na iskanju sta se njihova razredničarka in učiteljica računalništva dogovorili, in preverjanju informacij, ki jih najdemo na spletu in s tem da na računalniku naredijo mape, jih poimenujejo in vanje kritično presojanje o verodostojnosti zapisanega. Naučijo se shranijo vse kar se jim bom zdelo uporabno (fotografije in uporabe slovarjev in s tem pomoči pri vsakdanjem delu. Wordov dokument, kamor so zapisovali podatke). Med urami obveznih izbirnih predmetov s področja Ker so se v šoli prvič srečali z urejevalnikom besedila računalništva so ure namenjene poglabljanju splošnega Microsoft Word, jim ga je učiteljica računalništva predstavila. računalniškega znanja. Učenci se naučijo oblikovanja besedila Naučili so se tudi dokument shraniti. Besedilo so nekoliko tudi po lastni temi. Pri zapisovanju so potrebno tako kritično oblikovali. presojanje o vsebini, ki jo učenec najde na spletu. Podatke lahko Učenci petega razreda prihajajo v računalniško učilnico z poišče tudi doma, si jih shrani na zunanji disk ali oblačno storitev namenom učenja za kolesarski izpit in kasneje teoretičnega izpita. ali si jih pošlje preko elektronske pošte ter jih v šoli zna poiskati Pred tem večkrat poudarimo delo v spletnih učilnicah. Učitelji, in jih uporabi v svojem dokumentu. ki poučujejo v petem razredu, uporabljajo spletne učilnice še pri rednem pouku za oddajo nalog, dodatne naloge pri utrjevanju znanja in utrjevanje znanja s pomočjo kvizov. Učiteljica računalništva je v zvezi z učitelji petega razreda in ure v računalniški učilnici so idealna priložnost, da se učenci naučijo nekaj novega in obnovijo znanje. Učenci v petem razredu so ravno v starosti, ko začnejo uporabljati družbena omrežja in prav je, da takrat slišijo poglobljene vsebine o spletnem bontonu. Učenci četrtega, petega in šestega razreda že lahko obiskujejo neobvezni izbirni predmet Računalništvo. Interes na naši šoli je kar velik. V okviru neobveznega predmeta se večino časa ukvarjamo z algoritmičnim načinom razmišljanja, ki ga kasneje zapeljemo v uvod v programiranja s programom Scratch. Učenci petih in šestih razredov za zaključno nalogo naredijo krajšo igro za mlajše učence (največkrat za prvo triletje). S pomočjo programa Scratch hitro in uspešno razumejo in kasneje znajo uporabiti svoje znanje. Svoje izdelke in izdelke sošolce se naučijo kritično ovrednotiti. Slika 3: Urejanje besedil Učenci se naučijo povezovanja z digitalno napravo (največkrat telefon) in si prenesejo fotografije, zvok ali video posnetke, v šoli jih obdelamo in izdelamo izdelke pri pouku multimedije. Urejene fotografije so velikokrat razstavljene na šolskih hodnikih, glasba pa predvajana na šolskem radiu. Slika 2: Zaključna naloga Učenci predmetne stopnje obiskujejo računalniško učilnico predvsem v času dni dejavnosti, ur obveznih izbirnih predmetov in v času slovenščine, matematike, kemije ter tehnike in tehnologije. Vsak izmed razredov ima matematični dan dejavnosti in takrat učiteljice matematike poskrbijo, da učenci spoznajo in se naučijo uporabljati program Microsoft Excel. V Excelu se učenci naučijo urejanje večje količine podatkov, uporabo osnovnih matematičnih in statističnih formul, uporabo in spreminjanje grafikonov, filtriranje podatkov in pripravo strani za tiskanje. Glede na učno snov jim predstavimo spletne aplikacije, ki jim olajšajo delo pri matematiki (MathLab, GeoGebra, spletne kvize), Slika 4: Urejanje fotografij 381 5 ZAKLJUČEK ZAHVALA V današnjem času opažamo, da vedno bolj potrebujemo dobro Iskreno bi se zahvalila vodstvu Osnovne šole Vide Pregarc za razvite digitalne kompetence. Poleg ključnih kompetenc, ki jih podporo pri delu, učiteljem, ki so pripravljeni na »moje nore učenci potrebujejo za razvoj, socialno vključenost, zdrav način ideje« pri delu z učenci. življenja, so digitalne kompetence tiste, ki so v vedno bolj digitaliziranem svetu še kako zaželene. LITERATURA IN VIRI Pri posredovanju znanj smo se osredotočali, da smo lahko [1] Ključne kompetence za vseživljenjsko učenje. Dostopno na naslovu sledili opisnikom digitalnih pismenosti [3] in ravnem, ki http://www.movit.si/fileadmin/movit/0ZAVOD/Publikacije/Tematske/2018 _Kljucne_kompetence_za_vsezivljenjsko_ucenje.pdf (3. 8. 2022) opisujejo doseganje kompetenc po standardu DigComp [4]. [2] Inovativna pedagogika. Dostopno na naslovu https://www.inovativna- Pri delu je še vedno ogromno možnosti za izboljšave, zato sola.si/digitalne-kompetence-za-ucitelje-digcompedu/ (3. 8. 2022) smo si za letošnje šolsko leto zastavili celoletni šolski projekt [3] Digitalna pismenost. Opisniki temeljne zmožnosti. Dostopno na naslovu https://pismenost.acs.si/wp-content/uploads/2018/09/Digitalna-pismenost-e- opismenjevanja. verzija.pdf (4. 8. 2022) [4] ZRSŠ, DigCompEdu – Evropski okvir digitalnih kompetenc izobraževalcev. Dostopno na naslovu https://www.zrss.si/digitalna_bralnica/digcompedu- evropski-okvir-digitalnih-kompetenc-izobrazevalcev/ (3. 8. 2022) 382 Soba pobega pri pouku zgodovine Escape Room in History Class Natalija Carmona OŠ Prežihovega Voranca Maribor Maribor, Slovenija natalija.carmona@ospvmb.si POVZETEK optional theme in the eighth grade of elementary school, rural riots, epidemics and natural disasters. Učitelj zgodovine se vedno sprašuje, na kakšne načine učencem dvigniti motivacijo za aktivno spoznavanje preteklosti. Kot The preparation of the material took a long time, as it was first učiteljica imam med pripravo aktivnosti posameznega učnega necessary to familiarise yourself with One Note, and then it was sklopa, pred očmi generacijo učencev. Takrat razmišljam o necessary to explore the contributions that dealt with editing in dejavnostih, ki jih najbolj motivirajo in so pri pouku zgodovine OneNote before it was possible to create material to enable najbolj aktivni. Šolsko leto 2020/21, v času pouka na daljavo, je students to learn about new learning content. od učitelja zahtevalo še več izvirnosti, saj so aktivnosti za učence OneNote is a tool that is very transparent and, when you shake it morale biti zanimive, hkrati pa poučne. over several, it becomes very easy to work in. The paper will V prispevku je predstavljena soba pobega, ki je bila oblikovana show how the escape room was composition and the work done v Microsoftovem orodju OneNote. Za oblikovanje sobe pobega by the students. sem izbrala izbirno temo v 8. razredu osnovne šole kmečki upori, epidemije in naravne nesreče. KEYWORDS Priprava gradiva je zahtevala veliko časa, saj se je bilo najprej Escape room, history, rural riots, One Note potrebno seznaniti z orodjem OneNote, nato je bilo potrebno raziskati prispevke, ki so obravnavali urejanje v orodju One Note, 1 UVOD šele nato je bilo možno oblikovati gradivo, s katerim so učenci spoznavali novo učno vsebino. Učitelji se pred pripravo gradiva za obravnavo učnih enot vedno sprašujemo, na kakšen način pripraviti dejavnosti, da bomo za OneNote je orodje, ki je zelo pregledno in ob večkratnem delo in učenje motiviral čim večje število učencev. V šolskem rokovanju z njim postane delo v njem zelo enostavno. V letu 2020/21 je bil to še posebno velik izziv za učitelje, saj smo prispevku bo predstavljen način sestave sobe pobega in delo, ki zaradi epidemije izvajali pouk od doma. Znašli smo se v so ga opravili učenci. popolnoma novi situaciji, ki je od učiteljev in učencev zahtevala veliko notranje motivacije, da smo se zjutraj usedli pred KLJUČNE BESEDE računalnike in delali ali se učili. Soba pobega, zgodovina, kmečki upori, One Note Pouk zgodovine temelji na analiziranju raznoraznih zgodovinskih virov, saj želimo doseči, da učenci te vire ABSTRACT spoznavajo, ob njih razvijajo kritično mišljenje in si ustvarjajo A history teacher always wonders how to raise students' poglede na pretekle dogodke. V času dela na daljavo, smo motivation to actively learn about the past. As a teacher, I have a uporabljali veliko avdio-vizualnih virov, zato sem se pri generation of pupils in front of my eyes during the preparation of obravnavanju kmečkih uporov na Slovenskem odločila uporabiti the learning activities. I think about the activities that motivate tudi knjižne vire, ki sem jih vstavila v posamezne sobe. Moj cilj them the most and are most active in history lessons. je bil ohranjati bralno razumevanje učencev. V prispevku je predstavljeno, kako sem se kot učiteljica The 2020/21 school year, during distance learning, required even zgodovine soočila z iskanjem načinov, da bodo učne ure pestre, more originality from the teacher, as activities had to be da bodo aktivirale učence za učenje in da bodo pripravljene tako, interesting for pupils. da bodo učenci od doma in samostojno lahko delo opravili. Drugi This article presents the escape room, which was created in cilj, ki sem si ga postavila, je bil motivirati učence za aktivno Microsoft's One Note tool. To create an escape room, I chose an učenje, saj je takrat njihovo pridobljeno znanje veliko trajnejše. Kot učiteljica se zavedam vedno večjega pomena digitalnih Permission to make digital or hard copies of part or all of this work for personal or kompetenc, ki jih v sodobnem svetu vedno bolj potrebujemo, classroom use is granted without fee provided that copies are not made or distributed zato je bil pri izbiri takšne učne ure moj cilj tudi razvijanje 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 digitalnih kompetenc učencev, hkrati pa jim omogočiti be honored. For all other uses, contact the owner/author(s). sodelovanje z vrstniki, čeprav niso bili v skupnem prostoru. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 383 2 TEORETIČEN PREGLED 2.2 Učenje s sodobno tehnologijo Šolanje na daljavo je učitelje in učence potisnilo v novo 2.1 Motivacija za učenje obliko učenja in poučevanja. Tehnologija, kot so računalniki, V času šolanja na daljavo sem se kot učiteljica srečala s tablice in internet so bili stalnica, ki jih v času pred epidemijo popolnoma novim načinom poučevanja. Svojo vlogo sem videla nismo tako pogosto vključevali v pouk. Takšno učenje je kot osebo, ki učencem pripravlja gradivo, ki jih bo za delo od omogočilo v poučevanje vključevati več različnih digitalnih doma motiviralo, prav tako da se bodo naučili novih vsebin pri kompetenc in veščin, ki smo se jih tako učitelji kot učenci morali predmetu zgodovina ter da se seznanijo z različnimi načini naučiti razvijati. uporabe računalnika, tablic in telefonov. Postavljena sem bila v Pri poučevanju s tehnologijo moramo upoštevati novo vlogo, v kateri sem se tudi sama veliko naučila. Postati sem naslednje: morala fleksibilna in radovedna. Pomembna veščina učitelja v  učno okolje moramo ohranjati čim bolj preprosto, z sodobni šoli, mora biti tudi fleksibilnost. Prilagajati je potrebno namenom, da zmanjšamo nepomembno procesiranje, poučevanje individualnim in skupinskim razlikam med učenci.  učenje s tehnologijo se mora načrtovati tako, da s Inovativnost učitelja omenja tudi M. Boekaerts, ki poudarja, da tehnologijo obvladujemo bistveno procesiranje, mora učitelj zavestno prilagajati svoje načrtovanje in poučevanje  učenje s tehnologijo mora spodbujati generativno tako, da pripravi za učence zanimive didaktične dejavnosti, ki procesiranje, ustrezajo namenu in ki jih učenci z veseljem opravljajo. Tako  s tehnologijo moramo podpirati učenčevo aktivno učenje postane učinkovitejše. [1] kognitivno procesiranje med učenjem, ne da bi pri tem V sodobnem svetu so začeli prevladovati bolj celostni in preobremenili njegovo spoznavno zmožnost. [3] integrirani modeli spodbujanja učne motivacije. Med najbolj znanimi je model TARGET. Po tem modelu učitelji spodbujajo učno motivacijo učencev, kot na primer lastnosti učnih nalog, 3 SOBA POBEGA – KMEČKI UPORI NA organizacijo učnih dejavnosti, z odnosom med učiteljem in SLOVENSKEM učenci, učiteljevimi pričakovanji, socialnimi interakcijami … Sodobnim konceptom je skupen cilj spodbuditi učence k učenju 3.1 Microsoftov OneNote in obvladovanju ter da pri tem upoštevajo različne kontekstne Za izdelavo sobe pobega za učence 8. razredov sem se odločila dejavnike šolskega prostora. [2] uporabiti Microsoftovo orodje OneNote. V šolskem letu 2020/21 V povezavi s tem modelom lahko na tem mestu navedemo smo vsi zaposleni in vsi učenci prejeli uporabniški račun v Oblak tudi osem načel, na katerih temelji motivacija za učenje: 365, zaradi česar sem se odločila, da sobo pobega ustvarim v tem  motivacija se izboljša, ko se učenci počutijo zmožne orodju. Prav tako sem z učenci pri pouku na daljavo že narediti tisto, kar se od njih pričakuje, uporabljala OneNote za oblikovanje skupnih zapiskov.  učenci so bolj motivirani za učenje, ko zaznajo Orodje OneNote je zelo preprost za uporabo, saj vizualno dosledno usklajenost med določenimi dejanji in spominja na Microsoft Word, kar učenci že zelo dobro poznajo. dosežki, Orodje pa ima tudi veliko prednosti:  učenci so bolj motivirani za učenje, ko predmet cenijo  ustvariš lahko več strani, ki jih med seboj povežeš, in ko jim je jasen namen učenja,  vstavljaš datoteke, slike in spletne povezave,  učenci so bolj motivirani za učenje, ko doživljajo  do dokumenta lahko dostopaš kadarkoli in iz pozitivna čustva v zvezi z didaktičnimi dejavnostmi, različnih naprav in  učence negativna čustva odvrnejo od učenja,  hkratno lahko v ustvarjen dokument vpisuje več  učenci sprostijo svoje kognitivne potenciale za učenje učencev. [4] takrat, ko imajo možnost vplivati na intenziteto, trajanje in izražanje svojih čustev,  učenci so vztrajnejši pri učenju, ko lahko sami uravnavajo svoje potenciale in se znajo učinkovito spopadati z oviram in  učenci so bolj motivirani za učenje in za uporabo strategij za uravnavanje motivacije, ko čutijo, da je okolje naklonjeno njihovemu učenju. [1] Raziskave so pokazale, da učna motivacija ni v tako tesni zvezi z učnimi dosežki, kot z kognitivnimi in metakognitivnimi Slika 1: Uvodna stran skupnega zvezka v orodju One Note. procesi in učenjem samim. Učna motivacija naj bi se izražala (slika zaslona; lasten vir). predvsem v odnosu do učenja in v različnosti pristopov k učenju. Zato se v sodobnih konceptih učenja in poučevanja motivacija 3.2 Potek priprave sobe pobega definira kot mediatorsko (posredniško) spremenljivko učne uspešnosti. Kljub temu je ključna, saj se brez nje učenje sploh ne Za izdelavo sobe pobega v OneNote sem si najprej pogledala more zgoditi. [2] posnetke na Youtube kanalu. Nato sem se lotila oblikovanja skupnega zvezka. V nadaljevanju v korakih predstavljam ustvarjanje sobe pobega: 384 1 Učence v oddelku sem razdelila v 6 skupin in ustvarila uvodno stran z osnovnimi informacijami. 2 Vsaki skupni sem ustvarila 7 sob z dodajanjem odsekov. Vsaka soba je bila posvečena enemu kmečkemu uporu, ki ga morajo osmošolci spoznati. 3 Nato sem se lotila oblikovanja vsebinskega dela vsake sobe posebej. Prednost orodja OneNote je, da lahko vse strani, ki Slika 5: Primer naloge za ugotavljanje ključa, ki odpira so ustvarjene v odseku, kopiraš. naslednjo sobo. (slika zaslona; lasten vir). 4 V vsaki sobi sem ustvarila nalogo, ki so jo učenci s sodelovanjem in predelavo učnega gradiva lahko rešili. Rešitev naloge je vodila do ključa s katerim so lahko odprli naslednjo sobo. 5 Ustvarjeno sobo pobega sem dala v skupno rabo in jo v Microsoft Teamsu delila z učenci pri uri zgodovine. Na pričetku učne ure sem učencem pojasnila, kako bo potekalo njihovo delo. Slika 6: Primer naloge za ugotavljanje ključa, ki odpira naslednjo sobo. (slika zaslona; lasten vir). 3.3 Izvedba učne ure in povratna informacija V času pouka na daljavo smo imeli v 8. razredu 1 uro na teden zgodovine, preko videokonference v Teamsu. Pouk sem načrtovala tako, da so bili učenci čim bolj aktivni, velikokrat je delo potekalo v skupinah, ki smo jih oblikovali v Microsoft Teamsu. Učenci so skupaj obdelovali pripravljeno gradivo, jaz Slika 2: Osnovni pogled na sobo pobega v OneNote. (slika pa sem imela možnost obiskovati vsako skupino posebej in zaslona; lasten vir). pregledovati njihove izdelke. Ob koncu ure smo se dobili v skupni sobi in takrat sem od učencev na različne načine Pri izdelavi gradiva za učenje sem uporabila učbenik in pridobivala povratno informacijo, o pridobljenem znanju ali o različne spletne vire (Fran, puntarske pesmi na Youtube kanalu, načinu dela, ki so ga opravili. Svoje izdelke so morali še zemljevide). Vsako sobo sem ustvarila malo drugače, da sem samostojno urediti in jih nato oddati v spletno učilnico. ohranila pozornost učencev. Učenci so ob nalogah urili tudi Učni sklop kmečki upori na Slovenskem, ki smo ga bralno razumevanje, saj so se rešitve nalog skrivale v besedilih, obravnavali v sobi pobega, sem načrtovala za dve šolski uri. Prvo ki so se skrivala v sobah. uro smo se dobili v Microsoft Teamsu, kjer sem učencem predstavila potek dela. Učenci so se sami razvrstili v šest skupin, izbiro sem jim prepustila, saj sem predvidevala, da bodo lažje delali v skupini, ki si jo sami izberejo. Učence sem seznanila z možnostjo klica na pomoč, kar je pomenilo, da so me lahko povabili v skupino, če so naleteli na težavo in sem jih usmerila pri reševanju naloge ali iskanju ključa za naslednjo sobo. Učenci so delo opravljali z veliko zanimanja in interesa. Učenci so aktivno delali celotni dve uri, nekatere skupine so se dobile tudi po pouku, saj so želele čimprej poiskati izhod iz sobe Slika 3: Primer posnetka v prvi sobi. pobega. (https://www.youtube.com/watch?v=zERbtzizRp0) Ko so vse skupine z delom zaključile in našle izhod iz sobe pobega, so imeli v zadnji sobi učenci navodilo, da na kratko zapišejo povratno informacijo o načinu dela. Eden pomembnih elementov formativnega spremljanja je pridobiti odzive učencev o načinu dela, ki si ga pripravil za njih. Učenci so zapisali, da jim je bil takšen način dela zanimiv in da so imeli večjo motivacijo, da opravijo zastavljene naloge. Nekaj zapisov skupin je vidnih na sliki 7. Slika 4: Primer odseka iz knjižnega vira, ki je bil zapisan v eni izmed sob (slika zaslona; lasten vir). 385 ključa za naslednjo sobo. Edina pomanjkljivost, ki jo lahko izpostavim je, da se sobe zaklenejo vedno znova, ko zapustimo OneNote, zato so učenci imeli navodilo, da geslo zapišejo na določeno mesto v že odklenjeni sobi in še na list papirja. Organiziranje takšne učne ure od učitelja zahteva osnovna digitalna znanja in predvsem veliko volje, saj za pripravo Slika 7: Povratne informacije učencev zapisne v OneNote. takšnega zvezka potrebuješ več časa, kot za klasičen način pouka. (slika zaslona; lasten vir). Odziv učencev, ki so se aktivno vključili v pouk, čeprav so bili doma, pa dokazuje, da se je potrebno tudi učiteljem aktivno ukvarjati z dejavnostmi, ki jih pripravljajo za sodobne generacije. 4 ZAKLJUČEK V prispevku sem predstavila obravnavo učnega sklopa pri ZAHVALA predmetu zgodovina v času pouka na daljavo. Soba pobega, ki Zahvaljujem se vodstvu šole, ki podpira in spodbuja vse moje sem jo ustvarila v Microsoft OneNote je nastala z mislijo, da za ideje o vključevanju sodobnih konceptov poučevanja. učence, ki so zaradi epidemioloških razmer ostali doma, pripravim takšno učno uro, kjer bodo lahko sodelovali in s LITERATURA IN VIRI skupnimi močmi pridobivali nova znanja. [1] M. Boekaert. (2013). »Motivacija in čustva imajo ključno vlogo pri učenju.« Ob zaključku sem ugotovila, da so učenci zaradi tako majhne V O naravi učenja: uporaba raziskav za navdih prakse. [Online]. Dosegljivo: 3_o naravi ucenja e-oblika.pdf (zrss.si) [5. 8. 2022]. spremembe načina pouka bili veliko bolj motivirani za učenje. [2] M. Jurševič, Motiviranje učencev v šoli, Ljubljana: Pedagoška fakulteta v Spoznali so kmečke upore na Slovenskem, si pri delu pomagali Ljubljani, 2012. in sodelovali, razvijali pa so tudi digitalne kompetence, ki jih [3] E. R. Mayer. (2013). »Učenje s tehnologijo.« V O naravi učenja: uporaba raziskav za navdih prakse. [Online]. Dosegljivo: 3_o naravi ucenja e- bodo v sodobnem svetu morali zelo dobro obvladati. oblika.pdf (zrss.si) [5. 8. 2022]. Soba pobega v orodju OneNote je preprosta za izdelavo in [4] Microsoft One Note. Dostopno na naslovu: Microsoft OneNote – digitalna aplikacija za zapiske | Microsoft 365. [1. 8. 2022]. tudi uporabo, kar sem ugotovila s spremljanjem dela učencev, ki [5] OneNote Escape rooms! Dostopno na naslovu OneNote Escape Rooms! - so mojo pomoč potrebovali predvsem pri vsebini in iskanju YouTube [1. 8. 2022]. 386 Poučevanje glasbene umetnosti na daljavo Distance Learning Music Petra Čebulj Zajc Osnovna šola 16. decembra Mojstrana, Slovenija petra.cebulj@gmail.com POVZETEK glasbe, ustvarjanjem … Vse to je bilo pomembno pri načrtovanju pouka glasbene umetnosti na daljavo. Didaktični napotki, ki Čas epidemije je postavil šolski sistem na glavo. Dobesedno čez vodijo k uspešnemu pouka glasbe na daljavo, so: noč se je pouk iz učilnic preselil na splet. Učitelji smo iskali  realizacija le najnujnejših in elementarnih ciljev, rešitve za kar najbolj kvalitetno izvedbo pouka in predstavitev  dejavnostno naravnan pouk (poudarek je na učnih vsebin. V prispevku so predstavljeni praktični primeri ustvarjanju), poučevanja glasbene umetnosti na daljavo v času epidemije, ter  učenje naj bo čim bolj življenjsko, njihove pomanjkljivosti in seveda tudi prednosti. Na koncu je  predstavljena primerjava vseh idej po kriterijih, ki prikažejo naloge naj ne bodo predolge in prezahtevne [2]. njihovo uporabno vrednost. Za marsikatero rešitev se je na koncu Pri uresničevanju sodobnih učnih pristopov je pomembna namreč izkazalo, da ponuja še celo boljšo izvedbo učne teme in tudi učna tehnologija, s pomočjo katere lahko dosegamo boljše je primerna za uporabo tudi pri klasičnem pouku v učilnici, kar učne rezultate. Takšen učni proces je dinamičen in za učence lahko bralcem služi kot izhodišče za nadgradnjo njihovih ur. zanimivejši. Glavne značilnosti multimedijske tehnologije so, da je osnovana na računalniški tehnologiji, je interaktivna in KLJUČNE BESEDE komunikativna [1]. Seveda pa je treba paziti na smiselno vključevanje IKT v Glasbena umetnost, šola na daljavo, spletna orodja pouk, saj se lahko zelo hitro zgodi, da tak način postane ABSTRACT prevladujoč. Ta oblika dela je le dopolnilo za ostale dejavnosti v okviru glasbenega pouka. Učenci imajo delo z računalnikom zelo Restrictions in the time of the epidemic turned the school system radi, kljub temu pa to ne sme postati razlog za vključevanje upside down. Virtually overnight the teaching was moved to računalnika v pouk. Pouk glasbene umetnosti je v prvi vrsti virtual online environments. Teachers had to find solutions that namenjena spodbujanju razvoja na glasbenem področju. IKT igra enabled us to continue teaching and delivering the high-quality pri tem pomembno vlogo, saj predstavlja učni pripomoček, ki contents to pupils. This article presents eight practical examples pomaga realizirati cilje glasbene vzgoje [4]. of distance learning music during the epidemic together with V času šolanja na daljavo smo bili k uporabi IKT tehnologije their advantages and disadvantages. They are then compared prisiljeni, kar pa se je na koncu pokazalo kot dobra spodbuda based on different criteria to present their usefulness. It turned nam učiteljem, da svoje ideje za pouk v razreda prilagodimo ali out that many of the new teaching techniques, introduced during celo nadgradimo. the pandemic actually bring added value for the pupils and therefore should be used even during the ordinary teaching in classroom. Readers are encouraged to implement presented ideas 2 IDEJE ZA POČEVANJE NA DALJAVO as part of their teaching. Za uresničevanje učnih ciljev je bilo treba pri poučevanju na KEYWORDS daljavo spremeniti načine poučevanja in izvedbe posameznih nalog. Spodaj je naštetih in opisanih nekaj idej za izvedbo pouka Music, distance learning, online tools glasbene umetnosti na daljavo. Predstavljene so tudi njihove prednosti in slabosti. 1 UVOD 2.1 Razlaga snovi preko video vsebin Glasba ima v vzgoji in izobraževanju velik pomen z vidika Urnik učnih ur v živo je bil precej natrpan, zato sem ure v živo zdravja ter odnosov, saj glasba zdravi in nas povezuje. Zato so izvedla bolj redko. Termine sem raje prepustila predmetom, ki so cilji glasbene vzgoje navduševati, sprostiti se s poslušanjem za učence težji za razumevanje. Učencem sem tako razlago snov posredovala preko video posnetkov, ki sem jih ustvarila s Permission to make digital or hard copies of part or all of this work for personal or pomočjo Power Pointa. Videi so vsebovali glasbene primere, classroom use is granted without fee provided that copies are not made or distributed slikovni material in mojo razlago. Videe sem naložila na spletno 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 platformo Youtube, učencem pa povezavo posredovala preko be honored. For all other uses, contact the owner/author(s). spletne učilnice. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 387 2.1.1 Prednosti in slabosti. Slabost takšnega načina je, da tudi posneti na diktafone svojih mobilnih telefonov. Naloga je učenci ob morebitnih vprašanjih o obravnavani temi le teh ne postala zanimiva ravno zaradi ustvarjanja zvočnega posnetka, ki morajo postaviti takoj. Na drugi strani pa je tak način razlage so ga učenci ustvarili z mobilnim telefonom, ki jih učencem snovi bil učencem všeč, saj so si lahko določen del o temi drugače ne dovolimo za uporabo pri pouku. poslušali večkrat, predvsem pa so si sami izbrali, kdaj bodo snov 2.4.1 Prednosti in slabosti. Naloga je bila učencem všeč, saj poslušali. je bila ustvarjalna, hkrati pa jim je dovolila uporabo mobilnih telefonov. Edina slabost te naloge je, da jo je v celoti težko izvesti 2.2 Grafična tablica pri pouku, saj učenci (tudi če bi jim dovolili uporabo telefona pri Kot že omenjeno, sem v živo izvedla precej malo ur, če pa sem uri) ne bi mogli posneti skladb pri pouku. Tako bi morali ta del se že poslužila razlage v živo, sem si pri razlagi pomagala z naloge še vedno opraviti doma. grafično tablico. Ta se je izkazala kot res krasen pripomoček sploh pri učenju not. Učencem se ja tako na njihovih ekranih v 2.5 Kulturni dan kot spletni koncert živo risala tabelska slika. Za čas epidemije so bili odpovedani vsi dnevi dejavnosti. 2.2.1 Prednosti in slabosti. Uporaba grafične tablice se je Kulturni, športni, naravoslovni in tehnični dnevi učencem na izkazala kot zelo uporabna pri pouku na daljavo, saj je dajala drugačen, večkrat bolj praktičen način pokažejo različne teme, ki možnost prikaza tabelske slike, ki so je učenci navajeni. Ta je jih obravnavamo pri učnih urah. S področja glasbe si učenci bila še boljša kot v šoli, saj je branje s table iz zadnje vrste kdaj največkrat ogledajo glasbeno predstavo (opero, balet, muzikal) že prezahtevno. Uporaba grafične tablice pri pouku v razredu se ali prisluhnejo tematskemu koncertu. Žive izkušnje sicer ne mora dobro obnese predvsem zato, ker je pisanje na tablico učitelju nadomestiti noben posnetek, a kljub vsemu smo bili tako učitelji precej bolj naravno, saj je razmerje zapisa na papirju in tabli kot učenci zelo hvaležni, da so se marsikatere kulturne inštitucije različno. Prav tako je uporabno tam, kjer učilnica nima posebne v Sloveniji odločile, da omogočijo oglede posnetkov njihovih table z notnimi črtami. predstav in koncertov. Tako so si učenci en dan med šolanjem na daljavo ogledali posnetek koncerta in spoznali nove glasbene 2.3 Rap o skladatelju primere in zanimivosti iz zgodovine. Po ogledu koncerta so Učenci v 8. razredu spoznajo skladatelje iz obdobja klasicizma učenci rešili kviz preko Google obrazca, ki sem jim ga pripravila in romantike. Spoznavanja smo se lotili tako, da je vsak učenec in s pomočjo Worda ustvarili koncertni list za ogledan koncert. predstavil skladatelja s pomočjo rapa. Podatke o njegovem 2.5.1 Prednosti in slabosti. Če otroke želimo navdušiti nad življenju in delih so učenci poiskali preko spleta in nato rap kulturnimi prireditvami, jih morajo učenci doživeti v živo v zapisali v Wordu. gledališču, operi, koncertni dvorani, tako da vse alternativne Ko je bil rap napisan, ga je bilo potrebno še izvesti. Na oblike niti približno ne dosegajo zahtevanega nivoja. Res pa je, youtube so poiskali inštrumentalno spremljavo in nanjo izvedli da je ogled prireditve preko spleta na drugi strani cenovno rap ter posnetek objavili v spletni učilnici. ugoden, saj ne zahteva stroškov za prevoz do lokacije in 2.3.1 Prednosti in slabosti. Pri pouku za iskanje podatkov vstopnice. Dobra stran ogleda prireditev preko spleta je tudi ta, uporabljamo knjige in učbenike, pri delu na daljavo smo za vir da lahko s temi vsebinami nadgradimo pouk v razredu in s tem imeli svetovni splet, kar je bilo učencem bolj všeč, kot pa listanje učencem pokažemo še več različnih umetniških projektov. po knjigah. Za pouk v razredu se je na koncu kot najboljša opcija izkazala kar kombinacija obeh virov. Edina lastnost, ki je bila pri 2.6 Proslava na daljavo tej nalogi slaba, je bila izvedba. Pri pouku v šoli učenci rape Ob dnevu šole in krajevnem prazniku na šoli vedno pripravimo izvedejo v živo pred sošolci. Na ta način lahko učenci krepijo prireditev. Ker izvedba v živo ni bila mogoča, smo se odločili, da tudi veščine nastopanja in se naučijo spopadanja s tremo, čemur prireditev posnamemo in jo na dan, ko bi prireditev potekala v pri snemanju posnetka doma niso izpostavljeni. živo, predvajamo preko spletne platforme. Učenci so točke za nastop in vnaprej pripravljeno vezno besedilo posneli doma, nato 2.4 Grafična notacija in zvoki iz okolja pa smo posnetke združili v prireditev. Odziv učencev, ki so želeli V 9. razredu učenci spoznavajo zgodovino glasbe 20. stoletja. V sodelovati na prireditvi, je bil zelo dober. tistem času so skladatelji iskali nove načine za glasbeno 2.6.1 Prednosti in slabosti. Učencem je bil takšen način izražanje. proslave všeč, saj se jim je zdelo, kot da snemajo film. Tisti, ki Ena izmed značilnosti tistega časa je bila konkretna glasba, pa so za proslavo prispevali glasbene točke, so se na ta način katere izhodišče so bili konkretni zvoki in šumi iz vsakdanjega srečali s tem, da lahko vnaprej posnete glasbene točke tudi življenja. Te zvoke so skladatelji uredili v smiselno celoto in popravijo v primeru napake, prav tako so na ta način dobili dober nastale so skladbe (primer Pierre Schaeffer: Etuda z železnico) način, da svoj glasbeni nastop na podlagi posnetka analizirajo in [3]. tako napredujejo. Snemanje svoje izvedbe in analiza le-te Druga novost tistega časa je bila uporaba grafične notacije, s pomaga glasbeniku k napredku. Vsekakor je ta metoda katero so skladatelji s pomočjo slikovnih predlog podajali dobrodošla pri pripravi npr. pevskega zbora za nastop. Vsekakor navodila za izvajanje. pa je prireditev v živo nekaj povsem drugega, saj se učenci s tem Učenci so pri obravnavi te snovi izdelali praktično nalogo. krepijo v veščini nastopanja in urijo obnašanje na odru. Izmisliti so se morali svojo skladbo, tako da so uporabili obe novosti tistega časa. Skladbo so zapisali tako, da so za prikaz 2.7 Zapis glasbe s pomočjo musescore posameznih zvokov uporabili simbole, zvoke pa so v tem V času šolanja na daljavo smo se z nekaterimi učenci pripravljali primeru predstavljali zvoki iz okolja. Zapis skladbe so morali na tekmovanje Glasbena olimpijada. Ena izmed nalog na 388 tekmovanju je tudi zapis lastne skladbe. V prejšnjih letih smo jih tablica), ki jih navadno nimamo, niti ne zahtevajo dodatnega pisali na notni papir, na daljavo pa je bilo zaradi izmenjevanja znanja (npr. znanje video montaže). skladbe med učenci in mano skladbo lažje pisati s pomočjo Posebej bi izpostavila rap o skladatelju in nalogo z uporabo brezplačnega programa za notacijo Musescore. Poleg tega ta grafične notacije, saj so zadostili vsem kriterijem in so zelo omogoča, da skladbo tudi zaigra. Ko smo bili v šoli, so mi smiselni za redno vključitev v pouk. Poleg tega se je kot odlično namreč učenci svoje skladbe zaigrali na svoje inštrumente, tokrat izkazala uporaba programa Musescore, a žal je ta ideja omejena pa to ni bilo mogoče. na uporabo v posebnih pogojih (npr. za Glasbeno olimpijado) in 2.7.1 Prednosti in slabosti. Čeprav je pri otrocih dobro ni primerna za celoten razred. spodbujati pisanje na roke in krepitev grafomotoričnih spretnosti, se je uporaba programa za zapisovanje not obnesla precej bolje kot pisanje na papir. S tem smo prihranili precej časa pri Tabela 1: Primerjava idej glede na različne kriterije morebitnih popravah, saj not ni bilo potrebno ponovno prepisovati, zapis je bil precej bolj čitljiv, zaradi možnosti predvajanja zapisanega pa tudi bolj zanimiv pri odkrivanju encev različnih zvočnih barv. izkušnja uč čnost ša iv ti selnost 2.8 Pevski zbor olj dz IKT B O Prak Smi Največji izziv pri poučevanju na daljavo je predstavljala izvedba Razlaga snovi preko video vsebin    ur otroškega in mladinskega pevskega zbora. Ure so za učitelja Grafična tablica    glasbe del njegove učne obveze, zato jih je bilo potrebno izvesti tudi na daljavo. Vaje preko spletnih učilnic niso prišle v poštev, Rap o skladatelju      saj je kakovost zvoka slaba, poleg tega prihaja do zakasnitev. Grafična notacija in zvoki iz okolja      Učenje novih pesmi smo se lotili s pomočjo posnetkov. Učencem sem poslala dva posnetka. Na prvem sem skladbo Kulturni dan kot spletni koncert  zapela, drugi pa je bil posnetek klavirske spremljave, ob kateri Proslava na daljavo   so učenci lahko prepevali doma. Zapis glasbe s pomočjo Musescore      2.8.1 Prednosti in slabosti. Petje v zboru zahteva skupno muziciranje v živo in ga ne moramo nadomestiti na noben način. Pevski zbor  Učencem je bilo sicer všeč, da so pesmi lahko tudi doma peli ob spremljavi (na tak način jih prepevamo v šoli), vendar so tudi oni pogrešali skupinsko petje, ki je bistvo pevskega zbora. 4 ZAKLJUČEK Čeprav je bilo o šolanju na daljavo izrečenega in zapisanega veliko slabega, je meni dal veliko dobrega. Marsikatera od zgoraj 3 PRIMEJAVA IDEJ opisanih rešitev se je namreč izkazala kot bolj učinkovita ali za Predstavljene ideje so si vsebinsko precej različne in tudi učence bolj zanimiva kot običajna pot. zahtevajo različno raven angažiranosti učitelja. V tem razdelku Tako smo z učenci pri pouku tudi letos (čeprav smo bili v predstavim primerjavo idej na podlagi različnih kriterijev, kar šoli) ustvarjali skladbe z grafično notacijo in zvoki iz okolja ter bralcu omogoča lažje odločanje, ali bo katero od idej vključil v pisali rap. S to razliko, da naloge učenci niso opravljali doma, svoj pouk. Kriteriji so določeni na način, da so ocenljivi in da so temveč so naloge ustvarjali v računalniški učilnici med urami smiselni vse ideje. glasbene umetnosti. Učenci, ki so se udeležili tekmovanja, so za Spodnja tabela (Tabela 1) prikazuje, kako se opisane ideje v zapis skladbe posegali po programu za notacijo, saj jim je članku obnesejo glede na določene kriterije: omogočal bolj enostavne popravke skladbe. Pevci pri pevskem  krepitev IKT znanj učencev, zboru so si zaželeli posnetih spremljav tudi letos, saj so si skladbe  enakovredna ali boljša izkušnja kot v razredu, želeli prepevati ob spremljavi tudi doma. Posneti koncerti in  pozitiven odziv učencev, predstave pa nam krajšajo čas na kakšen dan, ko učenci niso pri  praktičnost izvedbe (ni potrebe po dodatnih volji za nič drugega. pripomočkih, (pred)znanju) in Članek lahko služi kot ideja ali izhodišče ostalim pedagogom  smiselnost uporabe pri klasičnem pouku. za uporabo pri pouku. V primeru, da se še kdaj ponovi šolanje na daljavo, lahko vse ideje služijo kot popestritev vsebin, sicer pa Kot je razvidno iz Tabele 1, so bile vse ideje dobro sprejete so določene uporabne tudi za vpeljavo v klasični pouk, saj med učenci, večina pa omogoča enakovredno ali celo boljši dosegajo pozitiven odziv pri učencih. izkušnjo kot v razredu. Dejavnosti, ki tega ne omogočajo so tiste, kjer gre za nastopanje učencev in skupinsko dejavnost oziroma LITERATURA IN VIRI ogled kulturnih prireditev. [1] Blatič, M. idr. (2003). Didaktika. Novo mesto: Visokošolsko središče, Inštitut za raziskovalno in razvojno delo Večina idej, kjer so učenci vključen kot ustvarjalci vsebin [2] Breznik, I. (2021). Pouk glasbe na daljavo. Glasba v šoli in vrtcu, 24, št. 1, krepi njihove veščine IKT. Polovica idej je v celoti primerna za str. 2-8. [3] Čerič, J. in Šramel Vučina, U. (2008). Zgodovina glasbe II. Ljubljana: DZS. uporabo tudi pri pouku v razredu, saj gre za individualne naloge [4] Lango, J. (2011). Poučevanje glasbene vzgoje z uporabo informacijsko učencev z uporabo IKT. Te naloge so tudi za izvedbo precej komunikacijske tehnologije (Doktorska disertacija, Pedagoška fakulteta enostavne saj ne potrebujejo drugih pripomočkov (npr. grafična Ljubljana). Pridobljeno s http://pefprints.pef.uni- lj.si/535/1/Pou%C4%8Devanje_GVZ__z_IKT_Lango.pdf 389 Uporaba interaktivnih kvizov pri pouku angleščine Using Interactive Quizzes in English Lessons Urška Delovec Osnovna šola Matije Valjavca Preddvor Preddvor, Slovenija urska.delovec@os-preddvor.si POVZETEK 1 UVOD Sodobna tehnologija je postala del vsakdanjega življenja in S hitrim razvojem tehnologije se spreminjajo tudi generacije pomemben del pouka pri mnogih predmetih. Učenci izven pouka otrok. Sodobna tehnologija je postala del njihovega življenja in s uporabljajo različne spletne aplikacije, učitelji pa lahko pomočjo le-te lahko današnje učence bolj motiviramo za učenje tehnologijo uporabimo za poučevanje, tudi na otrokom privlačen in delo. Učenci s pomočjo IKT znanje sprejemajo po najmanj način. V prispevku bom predstavila možnosti za uporabo dveh kanalih, slušnem in vidnem, zato je delo učinkovitejše, interaktivnih kvizov pri pouku in prednosti njihove uporabe. informacije razumljivejše in znanje trajnejše.[1] Pri poučevanju Internet ponuja veliko različnih orodij za ustvarjanje kvizov. tujih jezikov se nam ponuja veliko možnosti za popestritev pouka Najpogosteje uporabljano orodje je Kahoot!, na kratko pa bom z uporabo različnih spletnih orodij. S tem lahko učencem opisala še dve zelo zanimivi platformi, Quizizz in Plickers, ki sta pokažemo, da se je možno ob učenju tudi zabavati. Odličen tudi prosto dostopni in sta se meni osebno izkazali za zelo način za dosego tega so interaktivni kvizi in igre. priročni. Opisane bodo brezplačne funkcije in prednosti posameznega orodja, predstavljena pa bo tudi primerjava med njimi. 2 UPORABA INTERAKTIVNIH KVIZOV Kvize lahko uporabljamo pri kateremkoli predmetu in v KLJUČNE BESEDE katerikoli starostni skupini. Seveda jih ne uporabljamo vsako Spletno učno orodje, interaktivni kviz, formativno spremljanje, uro, ampak presodimo, kdaj je uporaba smiselna. Uporaba IKT Kahoot!, Quizizz, Plickers orodij večinoma takoj pritegne pozornost učencev. Učenci so bolj motivirani, pozorni in ustvarjalni. Nad uporabo so večinoma ABSTRACT navdušeni, saj so orodja pogosto tekmovalnega značaja, Modern technology has become a vital part of our everyday life točkovanje pa vzdržuje napetost med igro. and an important part of lessons at school. While students use Kvize lahko uporabljamo za uvodno motivacijo, za different online tools and applications in their free time, teachers ugotavljanje predznanja učencev ali za predstavitev nove snovi. can use technology for educational purposes, also in a fun way. Z njimi lahko učence seznanimo s cilji določenega učnega sklopa The article aims to present different options for using interactive in jim vzbudimo radovednost. quizzes during lessons and the advantages they bring to the Ena izmed glavnih možnosti uporabe je po mojem mnenju students and the teachers. There are a lot of different online tools formativno spremljanje. Spletna orodja so namreč odlična za for creating such quizzes. Besides Kahoot!, which is probably the preverjanje in utrjevanje znanja učencev. Namesto uporabe most popular game-based learning platform, I will present two klasičnega preverjanja na papirju lahko znanje učencev other free access platforms that are easy to use, Quizizz and preverimo na bolj zabaven način. Učenci dobijo takojšnjo Plickers. The basic (free) features of each online tool will be povratno informacijo, učitelj pa dobi vpogled v njihovo znanje in presented and a comparison of them will be shown. napredek. Učencem lahko celo zadamo nalogo, da ob koncu KEYWORDS določenega učnega sklopa sestavijo vsak svoj kviz za utrjevanje Online learning tool, interactive quiz, formative assessment, snovi, se postavijo v vlogo učitelja in kviz v razredu tudi izpeljejo. Kahoot!, Quizizz, Plickers Ob sestavljanju kviza spoznavajo, kaj znajo in česa še ne. [2] Pri mnogih orodjih za izdelavo kvizov obstaja tudi možnost, da kviz učencem dodelimo kot domačo nalogo. Domača naloga lahko na tak način postane bolj privlačna za marsikaterega učenca, moramo pa se seveda prepričati, da imajo vsi učenci tudi doma dostop do interneta (preko računalnika ali pametnega Permission to make digital or hard copies of part or all of this work for personal or telefona). Čeprav učenci kviz rešujejo samostojno doma, ima 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 učitelj vseeno vpogled v odgovore in dosežke učencev. S tako citation on the first page. Copyrights for third-party components of this work must povratno informacijo lažje načrtuje potek naslednje ure pouka. be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 390 3 INTERAKTIVNI KVIZI brezplačno vključimo 10 slik na dan, drsnice in matematične enačbe, žal pa v brezplačni verziji ni možno vstavljati avdio in Na spletu obstaja veliko orodij oz. aplikacij, ki omogočajo video posnetkov. Pri vsakem vprašanju lahko določimo, koliko ustvarjanje interaktivnih kvizov in iger, s pomočjo katerih lahko časa bo imel učenec za odgovor in s kolikšnim številom točk naj popestrimo vsakodnevno rutino v razredu. Osnovni paket večine bo pravilen odgovor točkovan. Vidimo tudi prikaz vprašanja kot orodij je prosto dostopen in brezplačen, napredne funkcije pa so ga bodo videli učenci. Učenci na svojih napravah vidijo plačljive. Za uporabo je potrebna učiteljeva registracija, medtem vprašanje in vse možne odgovore. Nastavitve omogočajo tudi, da ko učenci za igranje potrebujejo le kodo. Večina teh orodij orodje učencem vprašanje glasno prebere. omogoča oblikovanje lastnih kvizov ali pa uporabo že Kviz lahko z učenci igramo v živo med poukom ali pa jim ga obstoječih, ki jih ustvarjalci delijo z drugimi uporabniki portala. dodelimo kot domačo nalogo. Rezultate bomo videli v obeh 3.1 Kahoot! primerih. V živo je kviz možno igrati na klasičen način, kar pomeni, da učitelj vodi kviz, prestavlja vprašanja in po vsakem Kahoot! je interaktivno digitalno orodje, ki je uporabno vprašanju poda razlago odgovora, lahko pa ga učenci igrajo vsak predvsem za izdelavo zanimivih spletnih kvizov in predstavitev. v svojem tempu. Tudi Quizizz ponuja skupinski način igranja. V Gre za eno najbolj priljubljenih aplikacij med učenci in učitelji. kvizih lahko sodeluje največ 100 udeležencev, ki se prijavijo le s Brezplačni paket učitelju omogoča ustvarjanje lastnega kviza ali kodo, brez registracije. V Quizizzu je možno ustvariti tudi uporabo in predelavo že obstoječih kvizov. V kviz lahko razrede, v katere se učenci prijavijo in jim na tak način dodelimo vstavimo vprašanja izbirnega tipa z največ 4 možnimi odgovori kvize. [4] (slika 1) in vprašanja tipa 'prav/narobe'. Vprašanja lahko Orodje je dostopno na https://quizizz.com/, učenci pa se vsebujejo YouTube posnetke, slike (shranjene na računalniku), povežejo preko povezave https://quizizz.com/join. slike namesto odgovorov in matematične enačbe. Orodje nudi možnost časovne omejitve. Poleg pravilnosti odgovorov se točkuje tudi hitrost odgovarjanja. Učenci na svojih napravah načeloma vidijo samo znake za odgovore, ne pa tudi vprašanj in dejanskih odgovorov, ima pa učitelj možnost, da učencem omogoči pogled tudi z vprašanji. Kviz lahko z učenci igramo v živo med poukom ali pa jim ga dodelimo kot domačo nalogo. Rezultate bomo videli v obeh primerih. V živo lahko učenci kviz igrajo individualno ali pa v skupinskem načinu. V skupinskem načinu obstajata dve možnosti: igranje na skupni napravi ali pa vsak udeleženec na svoji (do 5 skupin). Največje število igralcev v posameznem kvizu je 50. V Kahootu! lahko ustvarimo tudi razrede, v katere se učenci prijavijo, in jim na tak način dodelimo kvize.[3] Kahoot! je dostopen preko povezave https://kahoot.com/, učenci pa do kviza dostopajo na https://kahoot.it/. Slika 2. Vrste vprašanj, ki jih omogoča Quizizz (VIR: lasten, zajem zaslonske slike) 3.3 Plickers Aplikacija Plickers ravno tako omogoča oblikovanje interaktivnih kvizov, vendar je nekoliko drugačna od preostalih orodij za formativno preverjanje znanja. Učitelj se mora za Slika 1. Primer vprašanja izbirnega tipa v orodju Kahoot! dostop registrirati in naložiti aplikacijo na pametni telefon. Pred (VIR: https://www.monash.edu) uporabo je priporočljivo, da si v svojem računu ustvari razrede, vanje doda učence in vsakemu dodeli številko kartice. Učitelj nato pripravi kviz v spletnem orodju, ob igranju pa ga projicira 3.2 Quizizz na platno. Učenci za igranje ne potrebujejo računalnikov ali pametnih telefonov. Vse, kar potrebujejo, so plickers kartice, ki Quizizz je orodje za ustvarjanje kvizov in predstavitev. Z so dostopne na https://help.plickers.com/hc/en- orodjem Quizizz lahko ustvarimo zelo podoben kviz kot z us/articles/360008948034-Get-Plickers-Cards (slika 3). Učitelj orodjem Kahoot!, le da Quizizz v osnovnem paketu omogoča kartice natisne, priporočljivo je, da jih tudi plastificira, saj se v vstavljanje več različnih tipov vprašanj (slika 2). Na voljo imamo nasprotnem primeru hitro uničijo. Vsak učenec v razredu dobi vprašanja izbirnega tipa (dodamo lahko pet možnih odgovorov), svojo kartico, zato jih je potrebno natisniti toliko, kolikor je kjer je lahko pravilen le en odgovor ali pa je pravilnih odgovorov učencev v razredu (obstaja 40 različnih kartic). Na karticah je več. Ustvarimo lahko tudi vprašanja, ki zahtevajo zapis edinstvena koda, na vsakem robu pa ena črka (A, B, C ali D). Na manjkajočih besed. Orodje omogoča vključevanje ankete za njej je natisnjena tudi zaporedna številka kartice/učenca. Učenec pridobivanje mnenj in vprašanja odprtega tipa. V kviz lahko 391 pri odgovarjanju na vprašanje kartico obrne tako, da je na vrhu 3.4 Primerjava med kvizi črka odgovora, za katerega se je odločil. Preverjanje odgovorov Opisana orodja za izdelavo kvizov so si v marsičem podobna, poteka tako, da učitelj kartice optično prebere s svojim pametnim imajo pa tudi svoje posebnosti. Z aplikacijama Kahoot! in telefonom (slika 4). Ko s telefonom zajame kartico, se izpiše ime Quizizz lahko ustvarimo zelo podobne kvize, so pa vseeno učenca, krogec, ki je ob imenu, pa se obarva rdeče (napačen manjše razlike med njima, medtem ko je Plickers precej odgovor) ali zeleno (pravilen odgovor). Ko vsi učenci drugačen. V spodnji tabeli so naštete najbolj pogoste funkcije, ki odgovorijo, učitelj pokaže, kako je razred odgovarjal, nato pa jih interaktivni kvizi omogočajo v brezplačnem paketu, ob tem razkrije tudi pravilen odgovor. Če želi, lahko ob koncu kviza pa je zapisano, ali za omenjena tri orodja ti kriteriji veljajo učencem pokaže, kako uspešni so bili (v odstotkih). (Tabela 1). Vsak kviz ima do največ 5 vprašanj. Izbiramo med dvema vrstama vprašanj: vprašanja izbirnega tipa in vprašanja tipa 'prav/narobe' ter anketo. Vprašanja izbirnega tipa dovoljujejo Tabela 1: Primerjava orodij za izdelavo kvizov največ štiri možne odgovore. V vprašanja lahko vstavimo sliko, enačbo, avdio ali video posnetek, zvok iz knjižnice ali gif Kahoot! Quizizz Plickers animacijo. Vse omenjene možnosti lahko vključimo tudi v ustvarjanje lastnega kviza DA DA DA odgovore. Časovne omejitve pri vprašanjih ni. Učitelj dobi uporaba že obstoječih DA DA omejeno povratno informacijo, učenec pa to informacijo dobi le, če mu jo kvizov učitelj pokaže. [5] predelava obstoječih DA DA omejeno Ker ni časovne omejitve, učenci niso pod pritiskom, da kvizov morajo hitro odgovoriti, ampak lahko o svojem odgovoru malo vprašanja izbirnega tipa DA DA DA premislijo. To orodje je primerno za vse razrede in vse predmete, (4 možni (5 možnih (4 možni odgovori, en odgovorov, en odgovori, en še zlasti pa je uporabno pri mlajših učencih, ki večinoma nimajo pravilen ali več pravilnih pravilen svojih pametnih telefonov oz. v šolah s slabšim internetnim odgovor) odgovorov) odgovor) signalom. Orodje je dostopno na https://get.plickers.com/. vprašanja 'prav/narobe' DA NE DA vprašanja, ki zahtevajo NE DA NE zapis manjkajoče besede vstavljanje slikovnega DA DA DA materiala (le slike, ki so (10 slik na dan) naložene na računalniku) vstavljanje YouTube DA NE DA posnetkov vstavljanje matematičnih DA DA DA enačb časovna omejitev pri DA DA NE odgovarjanju glasno branje vprašanja NE DA NE vpogled v rezultate DA DA DA učencev uporaba pametnih DA DA NE telefonov ali računalnikov individualno reševanje – DA DA DA učitelj vodi kviz individualno reševanje – NE DA NE Slika 3. Primer Plickers kartice (VIR: lasten, zajem prilagojeno posameznim zaslonske slike) učencem skupinsko reševanje DA DA NE igranje preko DA DA NE videokonferenčnega sistema samostojno reševanje DA DA NE doma učenci vidijo svoj dosežek DA DA če jim učitelj to pokaže tekmovanje s sošolci DA DA NE število sodelujočih učencev do 50 do 100 do 40 4 ZAKLJUČEK Spletni orodji Kahoot! in Quizizz sta si zelo podobni, saj Slika 4. Plickers kviz v razredu (VIR: učiteljem omogočata precej podobnih funkcij. Kahoot! je med https://lauracandler.com/innovative-strategies-for-plickers/) 392 učitelji in učenci bolj poznan in posledično tudi bolj pogosto za najbolj uporabno orodje izkazal Plickers, saj učenci za igro ne uporabljen pri pouku. Meni osebno pa se je pri pouku angleščine potrebujejo računalnika ali telefona. orodje Quizizz izkazalo za bolj uporabno kot Kahoot!. Eden Orodij za ustvarjanje interaktivnih kvizov je veliko, zato izmed razlogov je, da v brezplačnem paketu nudi več različnih učitelji brez težav najdemo orodja primerna starosti otrok, tipov vprašanj. Pri pouku angleščine opažam, da imajo učenci njihovi jezikovni ravni in digitalnim kompetencam. veliko težav s pravilnim zapisom besed, zato je zelo uporaben tip vprašanja, kjer morajo udeleženci dopisati ustrezno besedo. Na ta način učenci na zabaven način utrjujejo besedišče ter vadijo LITERATURA IN VIRI pravilen zapis. Učenci pred ocenjevanjem znanja zelo radi kvize [1] K. Bučar. 2020. Uporaba digitalnih tehnologij pri angleščini v osnovni šoli. uporabljajo tudi doma in s tem ponavljajo snov. Zbornik Mednarodne strokovne konference Kreativna učna okolja (2020), 86-95 Quizizz večinoma uporabljam z učenci zadnje triade osnovne [2] P. Jelen. 2019. Uporaba aplikacije Kahoot! pri pouku in doma. Zbornik 22. šole, kjer ima veliko učencev že svoje pametne telefone. V drugi mednarodne multikonference Informacijska družba. Vzgoja in izobraževanje triadi pa je situacija nekoliko drugačna, saj ima precej manj otrok v informacijski družbi (2019), 103-104 [3] Kahoot! https://kahoot.com/ (8. 8. 2022) v lasti pametno napravo. Pri šestošolcih se mi je zato pri pouku [4] Quizizz https://quizizz.com/ (8. 8. 2022) [5] Plickers https://get.plickers.com/ (8. 8. 2022) 393 E-vzgojni vikend »Bod' na kavču!« E-Educational Weekend “Bod’ Na Kavču!” Petra Držanič Zavod sv. Frančiška Saleškega, Dom Janeza Boska Želimlje, Slovenija petra.drzanic@zelimlje.si POVZETEK KEYWORDS Dom Janeza Boska, v katerem sem zaposlena, deluje po Don Bosko preventive educational system, educator, education preventivnem vzgojnem sistemu, ki ga je zasnoval veliki for community, educational weekend, e-educational weekend pedagog Janez Bosko. V prispevku želimo predstaviti primer dobre prakse dela z dijaki v času izobraževanja na daljavo, ki se je zgodilo v času epidemije COVID-19. Eden temeljnih 1 UVOD elementov vzgoje v Domu Janeza Boska je vzgoja za skupnost. V strokovnem članku bomo predstavili don Boskov preventivni Vzgojitelj v Domu Janeza Boska ima vlogo usmerjevalca vzgojni sistem, sistem po katerem delujemo v Domu Janeza celotnega vzgojnega procesa. Ena izmed njegovih vlog je tudi Boska. Dom Janeza Boska sestavljajo vzgojne skupine, ločeno organizacija vzgojnega vikenda. Ta vikend je zelo pomemben za dekliške in fantovske skupine. razvoj in povezovanje vzgojne skupine. To je bil razlog za Osredotočili se bom zlasti na področje vzgoje za skupnost. odločitev, da organiziram e-vzgojni vikend tudi v času Ključni elementi, s katerimi ustvarjamo skupnost so: gradnja izobraževanja na daljavo. identitete vzgojne skupine preko vsakodnevnih pobud, večerna srečanja, vzgojni vikend in pozornost na vsakega posameznika Po koncu e-vzgojnega vikenda sem zbrala odzive dijakinj, preko osebnega spremljanja mladostnika. Na koncu bomo samoinicativno pa se je oglasilo tudi nekaj staršev dijakinj, ki so predstavili primer dobre prakse dela na daljavo, ki smo ga bili prav tako navdušeni nad idejo in samo izvedbo vikenda. poimenovala e-vzgojni vikend “Bod’ na kavču!”. Odločitev za izvedbo le tega je padla v letu 2020, ko so se vrata izobraževalnih KLJUČNE BESEDE ustanov v Sloveniji zaprla, z namenom preprečevanja širjenja Don Boskov preventivni vzgojni sistem, vzgojitelj, vzgoja za virusa Covid-19. Na odpoved izobraževalnega procesa, ki se je skupnost, vzgojni vikend, e-vzgojni vikend zgodil v letu 2020 zaradi pandemije korona virusa marsikdo ni bil pripravljen. Tukaj govorimo tako o krovnih šolskih ABSTRACT organizacijah, kot tudi šolah samih, učiteljih, učencih, starših in The Janez Bosko boarding school where I am employed operates institucijah, ki s šolami neposredno sodelujejo. [3] within preventive educational system, which was founded by the great Janez Bosko himself. In this article I wish to present a case of a good case study when dealing with students that study 2 DON BOSKOV PREVENTIVNI VZGOJNI remotely, that happened during the COVID-19 pandemic. SISTEM An educator at Janez Bosko boarding school controls an entire Utemeljitelj preventivnega vzgojnega sistema je Janez Bosko, ki educational process. One of its roles is also to organise an se je rodil leta 1815 blizu Torina. Torino je bil v tistih letih pod educational weekend, which is important for the development vplivom industrijske revolucije in v tej situaciji je bilo na cesti and connectivity of the group. This was the main reason why I veliko mladih, ki so bili revni, izkoriščeni in prepuščeni sami decided to organise it during the time of remote study. sebi. Janez Bosko je znal prepoznati njihove stiske ter poiskati odgovore nanje. Tako je ustanovil oratorij, ki je kraj zbiranja, After the online event I asked the students for some feedback. I igre in primerne zaposlitve. Je prostor, kjer je poskrbljeno za have also received some positive feedback from the parents who vsestransko rast mladega posameznika, ki ni prepuščen samemu were excited about the idea and execution of the online weekend sebi, temveč odrašča v družbi sovrstnikov ter ima ob sebi odrasle event. ljudi, ki zanj skrbijo in so vredni zaupanja. Svoje pedagoško delovanje je poimenoval preventivni vzgojni sistem. [1, 4] Don Bosko je zagovarjal stališče, da morajo biti za razvoj 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 pozitivne osebnosti zastopani štirje stebri družbe (to so glavne for profit or commercial advantage and that copies bear this notice and the full značilnosti oratorija): 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).  Dom, ki sprejema. Dom zaznamujejo ljubezen, Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia sprejemanje, domačnost in čustvena toplina. Obenem pa © 2022 Copyright held by the owner/author(s). pomeni doslednost, zahtevnost in odgovornost. 394  Župnija oz. duhovno okolje, ki vzgaja za vrednote. tega dijakom damo izziv, da sami poskrbijo za vsa Človek, če hoče živeti mora vedeti zakaj živi in imeti gospodinjska opravila (priprava jedilnika, nabava hrane, pred seboj vrednote, za katere želi živeti. kuhanje, pospravljanje), večkrat pa samoiniciativno  Šola, ki uvaja v življenje. Fantje, ki jih je don Bosko vzel poskrbijo tudi za prostočasne dejavnosti. Na ta način pod svoje okrilje so bili večinoma nepismeni in lahko dijakom pokažemo vse dobre plati sobivanja v neizobraženi. Zasnoval je šolo, ki je bila po meri skupnosti in pristnega stika z ljudmi. mladostnikov, predvsem pa je izobraževala za življenje. Namen je bil, da bodo mladi postali koristni členi družbe, v kateri živijo. 4 E-VZGOJNI VIKEND »BOD' NA KAVČU!«  Dvorišče za prijateljske stike in za življenje v veselju. V šolskem letu 2019/2020 sem prevzela novo vzgojno skupino, Veselje se izraža v igri, druženju, sproščenosti in katero je sestavljalo 16 deklet 1. letnika. Ob pripravah na novo ustvarjalnosti. [1, 2] šolsko leto sem načrtovala izvedbo vzgojnega vikenda v mesecu aprilu 2020.. Kot že omenjeno vzgojni vikend prinaša veliko pozitivnih plati tako za vzgojno skupino kot za posameznika. Če 3 VZGOJA ZA SKUPNOST V DOMU je to nova vzgojna skupina kot v mojem primeru, pa je ta vikend JANEZA BOSKA še toliko bolj pomemben. Ko se je začelo delo na daljavo sem V Domu Janeza Boska delujemo po preventivnem vzgojnem začela razmišljati kako bi lahko ne glede na situacijo vzgojni sistemu. Eden od naših glavnih ciljev je vzgoja za skupnost. To vikend uspela realizirati. In porodila se mi je ideja o e-vzgojnem želimo doseči preko ustvarjanja skupnosti na ravni celotnega vikendu. dijaškega doma kot na ravni vzgojne skupine. Naš namen je, da Sama ideja e-vzgojnega vikenda je bila identična tisti, ki bi bi se mladi v tej skupnosti čutili sprejete, slišane, ljubljene in se izvajal v živo, le da bi tu celotno delo potekalo preko Zoom razumljene. Želimo jim ponuditi varno okolje, kjer preživijo aplikacije. Idejo sem predstavila dekletom in takoj so bile za najstniška leta. Mladim nudimo priložnost za osebnostno in izvedbo. duhovno rast ter jim zagotavljamo okolje, kjer se lahko Tako sem se lotila načrtovanja e-vikenda, ki sem ga izobražujejo ter razvijajo v odgovorne odrasle posameznike. poimenovala “Bod’ na kavču!”. Z dekleti smo na samem začetku Nekaj naših najpomembnejših elementov vzgoje za izbrale vikend, ko naj bi svoj čas v večjem delu dneva namenile skupnost: našemu druženju. O tem e-vzgojnem vikendu sem obvestila tudi  vzgojna skupina: je osnovna celica, kjer se dogaja njihove starše. Pred samim začetkom e-vikenda so dekleta v vzgoja za skupnost. V našem dijaškem domu smo svoje poštne nabiralnike prejele obvestilo in navodila za izvedbo sprejeli nekaj usmeritev, da sledimo temu elementu-od vikenda. prostorov vzgojne skupine, ki združujejo, vsakodnevnih večernih srečanj, kjer ustvarimo sproščeno okolje in 4.1 Potek e-vzgojnega vikenda ponudimo vsebine za osebnostno in duhovno rast pa vse E-vzgojni vikend smo pričeli v petek ob 20.30 na skupnem Zoom do zunanjih znakov, ki spodbujajo pripadnost vzgojni srečanju. Sprva sem pripravila uvod v vikend, predstavila potek, skupini, kot so majice, puloverji. poskrbela za tehnične podrobnosti. Nato je sledil skupinski ogled  vloga vzgojitelja: don Boskov vzgojitelj ni zgolj v službi, filma z naslovom »Počutim se lepo« (angl. I feel pretty) preko ampak se trudimo, da bi vsak od vzgojiteljev ponotranjil aplikacije Rave. Po ogledu filma smo skupaj zaključile večer. don Boskovo karizmo in svoje delo razumel kot Naslednje jutro smo začele dan skupaj na Zoom aplikaciji ob poslanstvo. Ključna vzgojiteljeva vloga je, da se 10.00. V dopoldanskem druženju, ki je trajalo 2 uri sem dekleta dijakom približa na ljubezniv način, ki je njim razumljiv. razdelila v manjše skupine in jih razdelila v posamezne sobe na Eno izmed prioritetnih okolij vzgojnega delovanja so Zoom-u. Njihova primarna nalog ia je bila, da se znotraj skupine odmori, ko vzgojitelj preživi večino časa s svojo vzgojno bolje spoznajo. V pomoč so jim bila navodila, ki so jih dobile v skupino. Takrat se mladostniki najbolj sprostijo in lahko Zoom sobe po posameznih urah. Tako so na začetku prebrale največ izvemo o njih. Tako se ustvari zaupen odnos med navodila, katerim so kasneje sledile. Da sem dosegla večjo dijakom in vzgojiteljem. Dijaki dobijo občutek, da so dinamiko dela sem po določenem času združila po dve sobi nam pomembni in da smo vredni zaupanja. Kot skupaj in jim posredovala novo navodilo za delo. Na koncu so se vzgojiteljica v dijaku vedno iščem točko, občutljivo za zopet vse združile v eni sobi in prejele še zadnje navodilo za delo. dobro. Ko se opremo nanjo lahko dijaka motiviramo, Poanta dela po skupinah je bila v tem, da se dekleta med vodimo in usmerjamo k njegovim ciljem. [1, 2, 4] seboj spoznavajo, gradijo na zaupanju ter s tem krepijo skupnost Vzgojitelj je odgovoren za dobro vodenje vzgojne vzgojne skupine. skupine, obenem pa je pozoren na vsakega posameznika, Primeri dela po skupinah so naslednji: ki ga preko različnih načinov tudi osebno spremlja.  Pogovor. Da bi le ta lažje stekel sem jim napisala nekaj  vzgojni vikendi: so zelo pomembni za razvoj in vprašanj, katera so lahko služila lažjemu predstavljanju povezanost vzgojne skupine. S tem se krepi povezanost sebe. Primeri vprašanj: kakšno bi bilo tvoje življenje, če dijakov med seboj, razvija in oblikuje se nova dinamika ne bi poznala strahu, v kaj verjameš pri ljubezni, opiši skupine. Zaradi skupnega neobremenjenega bivanja so svoje najljubše preživljanje deževnega dne, po čem želiš, dijaki bolj sproščeni in se lahko pokažejo v drugačni luči da bi se te ljudje spominjali, če bi živela le še 5 let, bi kaj kot v dijaškem domu. Vzgojni vikend je vedno zasnovan spremenila in če ja, kaj? na izbrani temi, ki mladim pomaga pri osebni rasti. Poleg 395  Nekomu polepšati dan z gesto, ki si jo izmislite same. Dijakinja M.: “Petra, hvala, ker si si vzela čas za nas. Hvala, Tako je ena od skupin pripravila mini pevski nastop za da si pripravila e-vzgojni vikend, ki je bil noro dober. Res sem eno od sester dijakinje, ki je bila v naši vzgojni skupini. spoznala kaj novega še o kakšni punci, s katero se sicer ne bi Druga skupina je povabila dotičnega maturanta na Zoom zapletla v pogovor. In tisto osebno delo je bilo težko, ampak tako ter mu povedala zakaj jim je všeč. dobro. Res si bom shranila pismo in ga prebrala vsakič, k obo  Napisati zgodbo, ki vključuje v naprej pripravljene težko. Sedaj pa že odštevam dneve, da se vidimo v živo.” besede. Ko smo bile ponovno vse združene so skupine Dijakinja B.: “Tole je bila pa res dobra ideja, da smo izpeljale podelile svoje zgodbe in poskrbele za kar nekaj vzgojni vikend pa četudi na daljavo. Jaz sem res uživala. Hvala, izvabljenih nasmeškov na obraz. rada vas imam, punce.” Po ponovnem srečanju vseh deklet v eni sobi smo si podelile Dijakinja L.: “A imamo lahko še kakšen tak vikend, sej svoje misli in občutke, ki so jih spremljale pri spoznavanju druga vseeno, če na daljavo, samo da je?” druge ter opravljanju nalog. Sledil je odmor za kosilo. Dijakinja E.: “Meni je bilo res všeč osebno delo. Sploh tisti Po odmoru za kosilo smo se ponovno srečale na Zoomu. nagovor, da naj bom sama sebi najboljša prijateljica. Vem, da Popoldanski del je bil namenjen osebnemu delu. Pri pripravi le sem vedno najbolj stroga do sebe. Morda pa bo sedaj kaj drugače, tega sem izhajala iz filma, ki smo si ga pogledale večer prej. ker tole pismo sebi bom sigurno shranila. Hvala.” Dekleta so prejela navodila za osebno delo v Wordovem Samoiniciativno pa je prišlo tudi nekaj zahval staršev: dokumentu. Za osebno delo sem se odločila, ker je v vsaki Mami T.: “Res sem hvaležna za trud, da boste kljub vsemu skupini pomemben vsak posameznik. Pomembno je, da se tega izpeljali vikend. Vem, da bo J. to veliko pomenilo in tudi veliko zaveda ter da okrepi samega sebe. Osebno delo je zahtevalo dalo… od vas pa zahtevalo veliko energije. Zato res še enkrat napisati pismo samemu sebi. Iz navodil dekletom izhaja iskrena hvala in se vidimo v nedeljo na Zoomu.” naslednji odstavek: »Vzemi si čas in bod' na kavču. Napiši si Mami B.: “Petra, osebno bi se rada zahvalila za edinstveno pismo. Pri tem bodi… idejo, za skupno sv. mašo, pri kateri je bilo moč čutiti povezanost. Bodi sočutna do sebe. Bodi si najboljša prijateljica. Bodi tista, Lepo je bilo in še vedno odmeva. Hvala.” ki se sprejema v vsej svoji polnosti in šibkosti. Bodi si opora, Mami S.: “Še enkrat najlepša hvala za včerajšnje skupno bodi si oseba, ki te brezpogojno sprejema in ljubi. Bodi tista, ki srečanje. Nam je bilo lepo biti del neke take skoraj že družinske odpušča. Bodi tista, ki razume najglobljo bolečino, ko se obsojaš. skupnosti. Naša N. je bila navdušena nad celotnim vikendom.” Bodi tista, ki je prijazna, ki pomirja. Nato to pismo shrani na varno. Preberi si ga vsakič, ko boš dvomila vase. Ko se boš obsojala. Ko boš pri sebi iskala napake. 5 ZAKLJUČEK Ko boš žalostna. Ko boš razočarana. Ko boš …” V dneh e-vzgojnega vikenda je bilo čutiti željo dijakinj po Da je bilo dekletom lažje napisati pismo sebi so dobile tudi povezovanju, sklepanju novih prijateljstev, dela na sebi. Na nekaj iztočnic o čem lahko pišejo. Iztočnice so izhajale iz podlagi osebnega dela, ki sem jim ga pripravila, se je odprlo kar ogledanega filma. Za pisanje pisma si je vsaka punca vzela toliko nekaj dijakinj, ki so si kasneje želele individualnega dela z časa kot ga je potrebovala. menoj. Zaključimo lahko, da je e-vzgojni vikend doprinesel k Večer smo zaključile na Zoomu z družabnim večerom. Nekaj boljši povezanosti skupnosti vzgojne skupine, da se je poglobil deklet se je samoiniciativno javilo in pripravilo dve družabni igri: odnos dijakinja-vzgojiteljica, obenem pa so se tudi starši lahko kviz o članicah 9. vzgojne skupine ter Scrabble 9. vzgojne počutili kot del širše skupnosti, v katero so vključene njihove skupine. Preostanek večera smo preživele ob skupnem igranju mladostnice. spletnih iger, kot je npr. Codenmaes in Skribbl. Z lahkoto sicer trdimo, da obstaja kar nekaj preprek pri e- V nedeljo je sledil zaključek e-vzgojnega vikenda na vzgojnem vikendu, če le tega primerjam v vzgojnim vikendom, katerega so bile povabljene celotne družine dijakinj. V ki je sicer izveden v »živo«, a obenem se je izkazalo, da so vsi sodelovanju z ravnateljem dijaškega doma smo pripravili Zoom glavni nameni lahko doseženi tudi na način predstavljen v tem sv. mašo, pri kateri so sodelovale dijakinje in njihove družine. prispevku. 4.2 Odzivi dijakinj in njihovih staršev na e- LITERATURA IN VIRI vzgojni vikend [1] Tone Ciglar. 2004. Rad vas imam. Ljubljana, Salve. [2] Carlo Nanni. 2011. Don Boskov preventivni sistem. Ljubljana, Salve. Po zaključku e-vzgojnega vikenda sem povabila dekleta, da [3] Gašper Strniša in drugi. Discord kot platforma za izvedbo pouka na daljavo. podajo svoje videnje na izvedbo, vsebino samega e-vzgojnega Vzgoja in izobraževanje v informacijski družbi – zbornik 24. mednarodne multikonference. Uredila: U. Rajkovič in B. Batagelj, Ljubljana, 8. oktober vikenda. 2021. Institut »Jožef Štefan«, Ljubljana. [4] Peter Končan. 2015. Don Boskov preventivni vzgojni sistem: duhovna in vzgojna izkušnja. Vzgoja, let. 17, št. 67. Ljubljana. 396 Biti z mladimi tudi v času izobraževanja na daljavo How To Offer Assistance to Youth During Remote Study? Petra Držanič Zavod sv. Frančiška Saleškega, Dom Janeza Boska Želimlje, Slovenija petra.drzanic@zelimlje.si POVZETEK KEYWORDS V prispevku smo predstavili preventivni vzgojni sistem, sistem Preventive educational system, assistance, good case studies, po katerem delujemo vzgojitelji v Domu Janeza Boska. remote study Preventivni vzgojni sistem daje veliko vlogo vzgojitelju, kateremu so mladi zaupani v vzgojo. Janez Bosko, utemeljitelj preventivnega sistema je razvil obliko pomoči, ki jo je 1 UVOD poimenoval asistenca. Pomembno je, da imajo mladi ob sebi V šolskem letu 2019/2020 se je tako rekoč iz danes na jutri osebo, ki ji lahko zaupajo in se ji odprejo. zgodilo, da smo pričeli z izobraževanjem na daljavo, zaradi V nadaljevanju predstavimo primere dobre prakse, ki smo jih epidemije korona virusa. pripravili vzgojitelji v Domu Janeza Boska v času izobraževanja Lahko rečemo, da na kaj takšnega nismo bili pripravljeni, ne na daljavo. Dijaški domovi smo se prilagodili situaciji ter tudi v ustanove, ne posamezni pedagoški delavci. Situacija je od nas skladu z navodili in priporočili pripravili in oblikovali vrsto terjala hitro prilagoditev ter še hitrejše učenje uporabe novih spletnih vsebin. Glavni namen le teh je bil ostati v stiku z spletnih orodij. mladostniki, jim biti asistenca v teh nepredvidljivih in novih Vzgojitelji v Domu Janeza Boska smo v skladu s časih. Dijaki so izkazali velik interes za vsebine, ki so jim bile preventivnim vzgojnim sistemom, sistemom po katerem ponujene. Obenem pa se je z večino ohranil pristen stik. delujemo v dijaškem domu ter z navodili in priporočili ustvarili vrsto spletnih vsebin, preko katerih smo ohranjali stik z dijaki, ki KLJUČNE BESEDE so nam zaupani v vzgojo. Eden izmed namenov teh spletnih vsebin je bil tudi ta da ohranimo skupnost, ki smo jo ustvarjali v Preventivni vzgojni sistem, asistenca, dobra praksa, »živo«. izobraževanje na daljavo ABSTRACT 2 PREVENTIVNI VZGOJNI SISTEM The article showcases a preventive educational system, on which the Janes Bosko boarding school operates. It gives teaches, who’s Utemeljitelj preventivnega vzgojnega sistema je veliki pedagog responsibility is to educate the youth, an important and Janez Bosko. Živel je v bližini Torina v letih, ko je bilo mesto responsible role. Janez Bosko, the founder of the preventive pod velikim vplivom industrijske revolucije. Tako je bilo na cesti system had developed a means of support, which he called veliko mladih, ki so bili prepuščeni sami sebi, revščini ter “assistance”. It is important for the youth to have access to izkoriščanju. Janez Bosko je čutil njihovo stisko ter jim želel somebody they can trust and feel comfortable opening to. ponuditi prostor, kjer se bodo čutili ljubljene, vredne zaupanja. Za njih je ustanovil mesto zbiranja, igre in primerne zaposlitve. In the continuation, I will present cases of good practices that Ta kraj je poimenoval oratorij. Don Bosko je tako skrbel za were prepared by teaches of Janez Bosko boarding school during mlade na več ravneh: nudil jim je streho nad glavo, hrano in the time of remote study. The boarding schools adjusted to the druge nujne pogoje za preživetje, med njimi tudi občutek situation and in accordance with the received instructions and varnosti. Tako jih je pridobil na svojo stran in jih začel vzgajati recommendations, prepared variety of online contents. The main v samozavestne, odgovorne posameznike, ki lahko družbi reason was to stay in touch with the youth, and to be of assistance enakopravno dajejo vse svoje potenciale. to that during the challenging and unpredictable times. The Temeljni vodili preventivnega vzgojnega sistema sta students have expressed interest for the prepared content that was ljubezen in zaupanje. Brez ljubezni do mladih ni zaupanje v on offer and at the same time remain a genuine connection and odnosu mladi-vzgojitelj in brez tega zaupanja po njegovo vzgoja relationship. ni mogoča. [2] Preventivni vzgojni sistem temelji na budni navzočnosti Permission to make digital or hard copies of part or all of this work for personal or vzgojitelja, ki se z dijaki pogovarja kot ljubeč starš, je vodja pri 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 vsakem dogodku, daje nasvete in ljubeznivo opominja. citation on the first page. Copyrights for third-party components of this work must Pomembna je domačnost z mladimi (zlasti v njihovem prostem be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia času), ki postopoma preide v ljubezen in zaupanje. [3] © 2022 Copyright held by the owner/author(s). 397 Janez Bosko je predpostavljal, da je dober vzgojitelj čuteč, sproščeno in iskreno skupaj rešujejo izzive, ki jih prinaša podkovan v pedagoškem znanju, in dober poznavalec razvoja in življenje. [4] potreb otrok, z izostrenim smislom za podajanje znanja otrokom. »Ni dovolj, da živi za fante, ampak naj z njimi doživlja njihovo 4.1 Besedica na uho življenje.« [2] Don Bosko je s tem sistemom svoje vzgojitelje Kot posebnost v preventivnem sistemu je potrebno omeniti tudi spodbujal k temu, da mlade spoznajo in da oni spoznajo njih, besedico na uho ali kot jih imenuje, zaupne besede. Don Bosko medtem ko z njimi preživljajo prosti čas. [3] je to uporabljala kot vzgojno sredstvo za dosego poslušnosti in ubogljivosti, predvsem pa takrat, ko je želel podati nasvet. Bosko ni želel s strahom vplivati na svoje gojence. 3 ASISTENCA ALI BITI Z MLADIMI Janez Bosko je na takšen način gojencem približal Don Bosko je razumel, da mladi potrebujejo ob sebi osebo, ki jih »očetovsko figuro«, ki je hkrati avtoriteta in tudi prijatelj, bo lahko vodila, na katero se lahko obrnejo, ko so v težavah, in zaupnik, nekdo, h kateremu se obrneš po nasvet. Kadarkoli je preko katere projicirajo svoje znanje in izkušnje, predvsem pa da imel občutek, da je nekoga potrebno pohvaliti ali mu podati grajo, imajo ob sebi osebo, ki ji lahko zaupajo in se ji odprejo. Zato je ga je poklical na samo in mu grajo prišepnil na uho. Tako pa je razvil svojevrstno obliko pomoči, ki jo je poimenoval asistenca. tudi pohvalil. In pohvala z besedico na uho je imela veliko večji Asistenca je odraz odgovornosti za otroka in je sorazmerna z učinek, kot pa bi ga imela, če bi dejanje pohvalil na glas pred zrelostjo in samostojnostjo otrok. [2] vsemi. [2] Vodilo vzgojiteljev v salezijanskih ustanovah je biti z mladimi, kar pa je tudi glavno vodilo asistence. Ni namreč dovolj, da vzgojitelj živi za mlade, ampak je pomembno, da z njimi 5 DELO Z DIJAKI V ČASU doživlja njihovo življenje, tako da so oni v ospredju njegovega IZOBRAŽEVANJA NA DALJAVO V DOMU dela. JANEZA BOSKA Biti z mladimi pomeni združitev dveh svetov, saj si vzgojitelj V začetku meseca marca leta 2020 je bil potrjen prvi primer in mlad človek med seboj delita izkušnje, življenje, odnose. okužene osebe s COVID-19 v Sloveniji. Ni minilo dolgo kar je Mladi potrebujejo prijatelja, ki jih spremlja, razume, jim svetuje bila razglašena epidemija in je bilo sprejetih vrsto ukrepov za in pomaga. Vzgojitelj torej predstavlja tega prijatelja. zajezitev omenjenega virusa. Eden izmed ukrepov je bil tudi Asistenca pomeni tudi aktiven odnos, v katerem vzgojitelj popolno zaprtje šolskega prostora ter pričetek izobraževanja na deluje tako, da se z dijakom ukvarja, ga usmerja, mu pomaga. S daljavo za vse učence in dijake. tem izraža resnično odgovornost za mlade. Biti zraven ne pomeni Študij na daljavo je oblika indiferentnega izobraževanja, pri samo fizične prisotnosti, ampak označuje živo, čutečo katerem sta učitelj in učenec ločena, sam proces izobraževanja navzočnost, ki je zaznamovana z ljubeznivim odnosom. [2] organizira izobraževalna institucija, ki nudi možnost Asistenca je torej koncept vzgoje, pri katerem vzgojitelj dvosmernega komuniciranja ter organizira občasna srečanja. postane mlademu blizu, z njim vzpostavlja prijateljski odnos, z Velik pomen pri študiju na daljavo imajo mediji, ki so lahko namenom, da mladega lažje usmerja, mu pomaga, opominja in mehanski ali elektronski. [5] tako odgovorno pristopa k vzgoji. Na spletni strani NIJZ lahko dostopamo do Priporočil in Biti vsem vse je istočasno posebnost in prednost modelov za izvajanje izobraževanja na daljavo. V priporočilih za preventivnega sistema in tisto, zaradi česar je ta vzgojni sistem dijaški dom je navedeno, da je dijaški dom dolžen izvajati tako težak za vzgojitelje. S svojo prisotnostjo lahko vzgojitelj podporo dijakom na daljavo. Vzgojitelj naj bi dijake podpiral na vzpostavi veliko možnosti za vplivanje na mladostnika, ki so bolj daljavo preko dogovorjenih spletnih orodij, v primeru njihove učinkovite kot kazni, vendar pa to za vzgojitelja pomeni veliko neodzivnosti pa tudi preko drugih komunikacijskih kanalov. [6] več časa, ki ga posveti le posamezniku in ne skupini. Ugotovimo lahko, da smo bili vzgojitelji v dijaških domovih dolžni ohranjati stik z dijaki tudi v času izobraževanja na daljavo, 4 VZGOJNI ODNOS obenem pa je v Domu Janeza Boska asistenca vzgojitelja na prvem mestu že v osnovi. Vzgoja ni samo individualno delovanje vzgojitelja, ampak predvsem delo vzgojnega okolja, kjer so odnosi podobni 5.1 Facebook stran Dom Janeza Boska družinskim. Tak vzgojni odnos je prežet z ljubeznivostjo, prijateljstvom, zaupanjem, naklonjenostjo, sprejemanjem, Vzgojitelji Doma Janeza Boska smo na samem začetku asistenco, ki lahko traja tudi po tem, ko mladostnik ni več v izobraževanja na daljavo naredili načrt kako bomo ohranili stik z vzgojnem procesu. mladostniki, ki so nam zaupani v vzgojo. Tako smo se odločili, Skrb za dobre odnose pomeni prizadevati si za to, da te imajo da ustvarimo Facebook stran Dom Janeza Boska. Omenjena kot vzgojitelja radi. Konkretno to pomeni, da si jim blizu, da stran je bila namenjena celotni skupnosti dijaškega doma. pridobiš njihovo zaupanje, da te kljub drugačni starosti, vlogi ali Facebook stran smo uporabljali za spodbujanje aktivnega osebnosti sprejmejo takšnega kot si, prav tako pa seveda tudi ti preživljanja prostega časa dijakov v času izobraževanja na njih. [1] Dom, v katerem veljajo takšni odnosi, pomeni resničnost, daljavo. Tako smo jim postavljali različne izzive, jih vabili k ki jo zaznamujejo ljubezen, zaupanje, domačnost, prisrčnost. Z deljenju različnih fotografij, informacij … Nekaj bolj zanimivih vnašanjem teh vrednot v vzgojno delovanje zavračamo uradne, dogodkov, ki so se zvrstili na strani so npr. izvedba klubskega hladne odnose, ki temeljijo na avtoriteti. Prav ta namreč mlade večera, ko je eden od dijakov pripravil glasbeni večer in vrtel odvrača od sočloveka. Zato vzgojitelj ne pridiga ali daje ukaze, glasbo kot DJ, pica izziv – dijake smo povabili, da pripravijo ampak jim govori iskreno iz srca v srce. V takšnem okolju lahko tradicionalne pice ob don Boskovem prazniku in to tudi 398 posnamejo, izziv s hrenom – kdo lahko poje sveže nariban hren V začetku adventnega časa sem dijakinjam pripravila spletni ob praznovanju Velike noči in kasneje nominira nove pogumne adventni koledar. Ta je bil sestavljen iz različnih nalog in izzivov jedce, med bolj obiskanimi so bile tudi nedeljske sv. maše, ki so za vsak dan v decembru. Nekatere naloge so bile individualne, jih vodili salezijanci iz želimeljske kapele in vrsto drugih druge skupinske, spet tretje namenjene osebam, ki niso bile del dogodkov. Spletna stran se je obdržala in ostala aktualne tudi naše vzgojne skupine. naprej in služi objavljanju fotografij dogodkov, obveščanju o Namen adventnega koledarja je bil v spodbudi k dogodkih. individualnemu delu, krepitvi odnosa v vzgojni skupini, med cimrami, spodbuda k dobrim delom za ljudi v naši okolici. Dijakinje so bile navdušene nad spletnih adventnim koledarjem, prav tako nad nalogami. Podale so predlog, da bi ga pripravila še kdaj ne le v adventnem času. Da je bilo vse skupaj še bolj pristno smo istočasno žrebale osebo, kateri smo po pošti poslale simbolično darilo za praznike. Slika 1: Facebook stran Dom Janeza Boska 5.2 Vzgojno delo znotraj vzgojne skupine Slika 3: Primer spletnega adventnega koledarja Vzgojno delo vzgojitelja v vzgojni skupini poteka na skupinskem in individualnem nivoju. Skupinsko delo poteka s celotno Dijakom smo v času izobraževanja na daljavo ponudili ne le vzgojno skupino ali znotraj manjših podskupin, medtem ko je zabavne vsebine, a tudi poučne. Tako smo izvedli tudi kar nekaj individualni nivo usmerjen k individualnemu delu. debatnih večerov. Pobuda za njih je prišla iz strain dijakov. Prav Z namenom skupinskega dela smo se vzgojitelji v Domu to je tudi razlog, da so bili tako dobro obiskani, ter da smo vedno Janeza Boska dogovoril s svojo vzgojno skupino za tedenski odprli aktualne teme in imeli kvalitetne pogovore, ki so se termin srečevanja preko videokonference. Za ta namen smo zavlekli precej v pozne ure. uporabljali aplikacijo Zoom. Redna tedenska srečanja so večinoma potekala po ustaljenem redu. Sama sem video klic vedno pričela z obvestili za prihajajoči teden, sledil je kratek pregled preteklega tedna, čas za izmenjavo mnenj, informacij, praznovanja … Najbolj efektiven čas z vidika ohranjanja stika z vzgojno skupino in gradnjo vzgojnega odnosa pa je bil tedaj, ko smo pričele z družabnimi igrami preko spleta. To je bil moment, ko sem kot vzgojiteljica izkoristila prosti čas in krepila odnos z dijakinjami. Ta čas je bil pomemben, ker sem potem lažje dostopala do vsake posameznice in jo spremljala na individualnem nivoju. Tako smo npr. v tem času večkrat igrale spletno igro Skribbl, Codenames, občasno so dekleta pripravile različne kvize z uporabo aplikacije Kahoot… Slika 4: Online debatni večer Vzgojitelji smo pripravili večji del tem za debatne večere. Debatirali smo o evtanaziji, hitri modi, temperamentu, kako vrstni red rojstev v družini vpliva na posameznika, kako krotiti stres … Da so bili debatni večeri dobro sprejeti dokazuje tudi dejstvo, da smo z njimi nadaljevali tudi po tem, ko smo po Slika 2: Primer družabne igre Codenames dolgem času zopet začeli sobivati v dijaškem domu. 399 Ob Prešernovem kulturnem prazniku smo dijakom pripravili 6 ZAKLJUČEK “Prešernovo sobo pobega”. Le to sem oblikovala s pomočjo Na začetku izobraževanja na daljavo smo vzgojitelji hitro Google Obrazci. poprijeli za idejo, da z mladimi ostanemo v stiku preko spletnih Sama soba pobega je bila zastavljena tako, da so dijaki medijev. Zagon je bil zares velik in iz tega se je razvilo nekaj odgovarjali na v naprej zastavljena vprašanja. V primeru, da so zelo dobrih idej, ki jih z lahkoto prenesemo v dijaški dom tudi po odgovorili pravilno se jim je odprlo novo vprašanje, v tem, ko se je izobraževanje na daljavo že zaključilo. nasprotnem primeru se jim je izpisala spodbuda ali namig. Dijaki so na začetku zelo dobro sprejeli vsebine, ki smo jim Da je bilo reševanje bolj zanimivo smo dijake razvrstili v nekaj jih ponudili. Lahko rečemo, da je bila vsaka vsebina dobro sob na aplikaciji Zoom in so znotraj manjših skupin skupaj »všečkana«, dijaki do dajali odzive in pobude za spremembe, reševali online sobo pobega. Ko so sobo zaključili so se vrnili v dopolnitve ponujenih vsebin. Tudi dijaki so bili na začetku prvotno sobo Zoom-a. samoiniciativni in so nam posredovali svoje ideje. Dejstvo pa je, da je s časom ta začetna navdušenost začela hlapeti. Vzgojitelji smo se tako osredotočili zlasti na individualno delo z dijaki, skupinske vsebine niso bile več tako pogoste. A namen, da ostanemo v stiku z mladimi, ki so nam zaupani v vzgojo je bil zagotovo izpolnjen. Kako vemo? Tako, da smo z večino dijakov imeli stike vsaj 1x tedensko. Dodaten pokazatelj, da je to uspelo pa je bilo tudi zaključno srečanje vzgojne skupine v centru Ljubljane, kamor so prišle prav vse dijakinje, ki so bile tisto šolsko leto v moji vzgojni skupini. Vsebine, ki smo jih ustvarjali vzgojitelji v Domu Janeza Boska so se dotaknile tudi staršev. Le ti so samoiniciativno ob koncu šolskega leta pošiljali zahvale za asistenco. Marsikateri starši pa so tudi sami sodelovali pri posameznih vsebinah, ki so bile javno dostopne. Ob koncu šolskega leta 2020/21 smo vzgojitelji naredili refleksijo vseh dogodkov, vsebin, ki smo jih izvajali tako na Slika 5: Primer vprašanja v Prešernovi sobi pobega ravni dijaškega doma kot na ravni posameznih vzgojnih skupin. Hitro smo lahko videli kje nam je šlo dobro, kje pa ostajajo Dijakom je bila omenjena soba všeč. Večina skupin se je zelo možnosti za izboljšavo. In dejstvo je, da smo se do prihodnjega hitro rešila iz sobe pobega, le eni skupini je eno od vprašanj šolskega leta lahko že pripravili na ponovno izobraževanja na povzročalo večje preglavice in so zaprosili za pomoč. daljavo. V času izobraževanju na daljavo smo bili vzgojitelji V Domu Janeza Boska dijake spremljamo preko različnih primorani biti kreativni, učeči, saj smo bili zelo na hitro vrženi v metod. Ena izmed njih je tudi osebni načrt, ki ga skupaj z novo situacijo, kateri se je bilo potrebno hitro prilagoditi, če smo dijakom sestavimo na začetku šolskega leta, ob koncu leta pa ga želeli doseči osnovni namen, biti z mladimi tudi v času tudi evalviramo. Pomembno je, da je osebni načrt izraz dijakovih izobraževanja na daljavo. Lahko bi rekla, da nas je tu rešila lastna želja in ciljev. samoiniciativnost, dobro povezan kolektiv, kajti krovne Glede na to, da smo šolsko leto 2019/2020 zaključili na daljavo organizacije so pri tem zatajile, saj nam niso ponudile nobenega sem se odločila, da z vsako dijakinjo opravim individualni video »supporta«, da bi bilo delo v danih razmerah lažje in še bolj razgovor, kjer bova evalvirali osebni načrt. Da je bilo dekletom učinkovito tudi za nas pedagoške delavce. lažje reflektirati in nato razpravljati o samih dosežkih in možnostih za izboljšave v prihodnjem šolskem letu sem jim LITERATURA IN VIRI predhodno pripravila vprašalnik z usmeritvami za pogovor o osebnostnemm napredku, šolski uspešnosti. Ta vprašalnik sem [1] Carlo Nanni. 2011. Don Boskov preventivni sistem. Ljubljana, Salve. [2] Tone Ciglar. 2004. Rad vas imam. Ljubljana, Salve. pripravila s pomočjo spletne stran Padlet, ki omogoča [3] Braido. 2011. Pedagoška izkušnja Janeza Boska. Ljubljana, Salve. komentiranje večim ljudem. [4] Tone Ciglar. 2009. Vzgajamo z don Boskovim srcem. Ljubljana, Salve. [5] Manja Svajger. 2021. Vzgoja in izobraževanje v času epidemije covid-19 v Dijakinje so izpostavile, da jim je bil takšen način Sloveniji – Sistematični pregled raziskav. Maribor. reflektiranja blizu, saj je kasnejši pogovor lažje stekel, ker sva [6] Šolsko leto 2021/22 v Republiki Sloveniji v razmerah, povezanih s covidom- 19. Modeli in priporočila. Dostopno na naslovu: imeli obe pred seboj že zapisano refleksijo. Dobra stran Padlet-a [7] https://www.nijz.si/sites/www.nijz.si/files/uploaded/modeli_in_priporocila_ je tudi ta, da lahko kadarkoli vneseš dodatne komentarje. 2021_22.pdf (9. 8. 2022) 400 Uporaba spletne ankete pri izbirnem predmetu filmska Use of the Online Survey in the Elective Subject of Film Education Kristina Gruden Reya OŠ Dobrova Dobrova, Slovenija grudenreya@gmail.com POVZETEK on an online survey using the 1KA application. This included interdisciplinary work with subject matter from the elective V prispevku predstavljam eno od možnosti uporabe subject Multimedia. Students worked in groups in order to informacijsko-komunikacijske tehnologije pri pouku izbirnega improve their skills at teamwork and communication. Group predmeta filmska vzgoja. Otrok lahko predmet izbere zadnja tri leaders reported the groups’ results. leta osnovne šole. Izvaja se eno uro na teden, torej 35 ur v šolskem letu. Predmet je obiskovalo 15 učencev osmih razredov. Film is one of the youngest art forms. It includes the Učenci so se za evalvacijo dela odločili za spletno anketo 1KA characteristics of writing, visual arts, music, dancing and theatre. in jo tudi uspešno izvedli. Pri tem so medpredmetno sodelovali Its history has always been a combination of artistic and (z izbirnim predmetom multimedija). Izvajali so sodelovalno technological developments. Therefore, it is appropriate for učenje, ki krepi občutek za odgovorno timsko delo in students to combine different views and approaches whilst medsebojno komunikacijo. Delali so v skupinah, vodja pa je studying the theory and practice of film. rezultate povzel. Pri učencih se je povečala motivacija za delo, To implement the online survey, students used smartphones and obenem pa so se z uporabo digitalnega orodja kreativno lotili the Worldwide Web along with the aforementioned 1KA sodelovalnega in problemskega učenja in ob tem razvijali svoje application. They had fun while doing this and got results during digitalne kompetence, ki veljajo za skupino ključnih kompetenc the same school session. 21. stoletja. The students concluded that there are many more possibilities for Filmska umetnost je ena najmlajših umetnosti. Združuje besedno, using online surveys and that they could use them for presenting likovno, glasbeno, plesno in gledališko umetnost. Film se je evaluations of other subjects, too. razvijal in se razvija še danes tako na umetnostnem področju kot tudi na tehnološkem. Zato je smiselno, da tudi učenci povezujejo KEYWORDS različne ravni in področja, ko teorijo in prakso filma spoznavajo. Elective subject Film Education, 1KA online surveys, Pri izvedbi spletne ankete so si pomagali s pametnimi telefoni, interdisciplinary schoolwork, cooperative learning spletom in že prej omenjeno spletno aplikacijo. Delo se jim je zdelo zabavno in poučno, rezultati pa so bili vidni še isto šolsko uro. 1 OPERATIVNI CILJI IN VSEBINE Učenci in učenke so ugotovili, da je možnosti za različne spletne Izbirni predmet Filmska vzgoja obstaja šele od leta 2018 in ga ankete še kar nekaj in da bi jih lahko večkrat uporabljali za uvršamo med družboslovne izbirne predmete. Učenec zadnje predstavitev tudi drugih tem. triade osnovne šole ga lahko izbere v sedmem, osmem ali devetem razredu. Otrok lahko predmet izbere vsako leto eno za KLJUČNE BESEDE drugim ali samo poljubno leto [1]. Zasnovan je modularno in predvideva tri module po 35 ur: Kaj je film, Filmski žanri in Izbirni predmet filmska vzgoja, spletne ankete 1KA, Umetnost in družba. Moduli so lahko samostojni, lahko pa se tudi medpredmetna povezava, sodelovalno učenje dopolnjujejo in nadgrajujejo. Filmsko vzgojo poučujem dve leti ABSTRACT in jo bom tudi naslednje šolsko leto. V skupini, ki sem jo poučevala, je bilo 15 otrok osmošolcev. Pouk je potekal eno In this article, we present one way of using information- šolsko uro na teden. Ob koncu šolskega leta so učenci s spletno communication technology for teaching the elective subject Film anketo ugotavljali, kdo je njihov najljubši igralec/igralka, tuji in Education. Students may select this subject in the last three years domači film ter filmski žanr. of primary school. For the final evaluation, the students decided Permission to make digital or hard copies of part or all of this work for personal or 2 OPREDELITEV PREDMETA 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 Film je eno najbolj razširjenih področij umetnosti med mladimi. citation on the first page. Copyrights for third-party components of this work must V ospredju filmske vzgoje je obravnavanje filma kot umetnosti, be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia množičnega medija in tehničnega proizvoda. Predmet izpostavlja © 2022 Copyright held by the owner/author(s). doživetje filma, spoznavanje osnov filmske umetnosti in filmsko 401 ustvarjalnost. Film omogoča razmislek o življenjskih temah, Ključni standardi znanja so, da učenec/učenka zna razložiti, kaj posameznikovih in družbenih vrednotah ter spodbuja mlade, da sta film in avdiovizualna dejavnost, pozna različne filmske vrste si ustvarijo svoj pogled na svet. Filmska vzgoja zato vpliva na in jih predstavi na primeru, prepozna različne filmske žanre in učenčev družbeni, etični in čustveni razvoj, pripomore k njihove temeljne značilnosti ter jih razloži na primeru. Otrok ve, raziskovanju univerzalnih tem ter spodbuja k razlikovanju in kateri so osnovni filmski izrazni elementi in razume njihovo sprejemanju različnih pogledov na svet ter na družbene in vlogo; pozna in razloži osnovne filmske ustvarjalne postopke in kulturne korenine našega naroda. razvije pozitiven odnos do filmske kulture kot pomembnega Film predstavlja v današnjem času, ki je vse bolj podvržen dejavnika splošne razgledanosti. avdiovizualnemu dojemanju sveta, eno najbolj pomembnih in hkrati priročnih sredstev za soočanje mladih s temeljnimi dejavniki sodobne družbe in kulture. Predmet filmska vzgoja 5 OGLEDI FILMOV zajema širok spekter elementov, ki opredeljujejo film – Osrednja dejavnost vsakega modula je ogled filma z razpravo. obravnava ga kot umetniško delo, kot sestavino avdiovizualne Priporoča se ogled petih celovečernih filmov z razpravo v kulture, kot sredstvo obveščanja in kot element novih tehnologij. vsakem modulu. Za vsak ogled filma smo namenili tri šolske ure, Namenjen je spoznavanju osnov filmske umetnosti, filmskemu razprava je sledila takoj po ogledu filma. doživetju in filmski ustvarjalnosti. Poudarek predmeta je na vzgoji gledalca, ki film doživlja in ga razume kritično ter ustvarjalno. 6 MEDPREDMETNE POVEZAVE Film pomembno vpliva na doživljanje in razumevanje sveta Pomen filmske vzgoje pride še posebej do izraza v različnih v vsej mnogoplastnosti, ki se stopnjuje z vedno večjo vlogo oblikah medpredmetnega povezovanja. filmskih in avdiovizualnih vsebin v sodobnem življenju, Filmsko vzgojo lahko povezujemo z različnimi predmeti. Pri množičnih medijih in novih socialnih omrežjih. slovenščini kot primerjava z literarnimi deli in dramskimi uprizoritvami. Pri zgodovini in naravoslovju je film kot učni 3 SPLOŠNI CILJI PREDMETA pripomoček; učenci se učijo skozi film s posebnim poudarkom na dokumentarnih filmih. Pri pouku glasbene umetnosti lahko Navedla bom glavne cilje, ki jih učenci pri predmetu osvojijo. spoznavajo vloge filmske glasbe, glasbenega filma. Učenci in učenke spoznavajo, kaj sta film in avdiovizualna Pri pouku računalništva (multimedija) so možnosti različne: dejavnost, razumejo film kot ustvarjalni proces, umetniško poznavanje računalniških programov, predvsem montažnih; pri predstavljanje (filmska projekcija), vzpostavljajo neposredni stik filmskem ustvarjanju pa si lahko pomagajo tudi z viri s s filmom, filmskimi ustvarjalci in izvajalci na področju kulture svetovnega spleta. V našem primeru so si učenci pomagali pri in filma, krepijo doživetje filma in oblikujejo ter artikulirajo izdelavi spletne ankete. Sistem za spletno anketiranje je hiter, svoja merila za vrednotenje filma, spoznavajo filmske žanre in učinkovit, zanesljiv in praktičen sistem za evalviranje dela na šoli. najpomembnejša razvojna obdobja v filmski zgodovini. Razvijajo tudi veščine interpretacije filma in se učijo vizualno izražati svoja spoznanja. 7 IZDELAVA SPLETNE ANKETE IN REZULTATI 3.1 Operativni učni cilji Proti koncu šolskega leta smo se z učenci dogovorili za pripravo Razdeljeni so na tri širša poglavja, in sicer Kaj je film, Filmski ankete o filmski žanrih, igralcih in filmih, ki so jih najbolj žanri in Film in družba. prepričali in so jim najbolj všeč. Razdelili so se v različno velike Za oglede filmov, razpravo, doživetje in interpretacijo je skupine. Ker so bili nekateri vpisani tudi na izbirni predmet predvidenih 15 ur. Multimedija, so poznali spletne anket 1KA, En klik anketa [2]. V poglavju Filmski žanri raziskujemo temeljne vrste (igrani, Študenti, učenci, raziskovalci, učitelji in drugi z Arnes AAI dokumentarni, animirani in eksperimentalni) in osnovne oblike računom lahko na ločeni namestitvi 1KA.Arnes.si uporabljajo (kratkometražni, srednjemetražni, dolgometražni) filma, proces 1KA brezplačno in brez omejitev pod običajnimi pogoji. nastajanja filma, filmske poklice, učenci se seznanijo z osnovni Aplikacija 1KA je lahko nameščena na poljubnem strežniku. izrazni elementi filma (igra, scenografija, kostumografija, maska, Matična namestitev je na domeni1KA arnes.si na strežniku osvetljava, glasba). Spoznajo tudi zgodovinski razvoj filma, Centra za družboslovno informatiko, Fakultete za družbene vede, filmsko ustvarjalnost, predstavnike filmske umetnosti (slovenske Univerze v Ljubljani. in tuje). Kot je zapisano v splošnih pogojih uporabe 1KA, lahko Pri poglavju Film in družba smo se pogovarjali o načinih uporabnik e-maila vabila k sodelovanju pošilja le naslovnikom, sprejemanja filma: doživljanju, razumevanju, njegovem ki so na veljaven način pristali na to. interpretiranju in vrednotenju. Učenci so razmišljali o filmu tudi Vmesnik 1KA za odgovarjanje na anketo je prilagojen tudi tako, da so napisali oceno filma in jo predstavili sošolcem. mobilnim napravam (slika 1). Ko je učenec s klikom na URL naslov odprl anketo, se je vsebina avtomatsko prilagodila njegovi napravi. Za uporabnike androidnih telefonov pa je na voljo tudi 4 STANDARDI ZNANJA mobilna aplikacija 1KA, ki omogoča izdelavo enostavnih anket S standardi znanja je opredeljena stopnja doseganja učnih ciljev. in pregled odgovorov anket, izdelanih preko spletne aplikacije. Določajo obseg in zahtevnost znanja. Aplikacijo so si učenci naložili prek aplikacije Google Store. 402 Slika 1: Učenci so reševali anketo Učenci in učenke izbirnega predmeta so na tak način ustvarili Slika 4: Prikaz odgovorov na vprašanje o najljubšem tri ankete. Za predstavitev v tem članku sem izbrala eno. Najprej slovenskem igralcu ali igralki je vodja skupine vsem poslal URL naslov, ki je bil časovno omejen. Učenci so si na mobilne telefone naložili aplikacijo in prek telefona reševali anketo. Rezultati so se zbirali pri enem učencu v obliki tortnega prikaza ali stolpca (Slike 2‒6). Slika 2: Prikaz odgovorov na vprašanje o priljubljenem filmskem žanru Slika 5: Prikaz odgovorov na vprašanje o najljubšem tujem filmu Slika 6: Prikaz odgovorov na vprašanje o najljubšem slovenskem filmu Slika 3: Prikaz odgovorov na vprašanje o najljubšem tujem Analiza odgovorov je pokazala, da učenci, ki so bili vpisani igralcu na izbirni predmet filmska vzgoja, najrajši spremljajo filmske drame, manj pa druge filmske žanre, kot so akcijski filmi in komedije. Na zadnjem mestu so vojni filmi. Pri tem vprašanju je bilo možnih več odgovorov, pri drugih pa ne. Večina učencev bi izbrala katerega drugega tujega igralca ali igralko in ne tistega, ki je bil v anketi na voljo. Bojan Emeršič je po mnenju otrok njihov najljubši slovenski igralec (40 odstotkov), sledijo mu Nina Ivanič, Katarina Čas, Sebastian Cavazza, na repu sta Boris 403 Cavazza in Aleš Valič. Najljubši tuji film je Harry Potter, domači Izkazalo se je, da je uporaba informacijsko-komunikacijske pa Pr' Hostar, ki mu sledita Gremo mi po svoje in Košarkar naj tehnologije popestrila pouk, hkrati so učenci na hiter način prišli bo. Pri najljubšem tujem filmu gre najbrž za vpliv knjige v več do zanimivih rezultatov. Pri tem so uporabljali mobilne telefone delih, ki jo učenci radi berejo, Pr' Hostar pa je slovenska in računalnik, spletne aplikacije in lastno znanje. Zdelo se jim je komedija, ki je dosegla veliko gledanost. zabavno, poučno in koristno, saj so razvijali svoje digitalne kompetence ‒ tako informacijsko pismenost kot zmožnost sodelovanja in komuniciranja v spletnem okolju. Učenci so imeli 8 ZAKLJUČEK večjo motivacijo za nadaljnje delo. Spletne aplikacije in kvizi so Učenci izbirnega predmeta filmska vzgoja so predvideno snov iz se v pedagoškem procesu izkazali tudi pri osvajanju novih tem in učnega načrta za ta predmet nadgradili še z izdelavo ankete 1KA. utrjevanju snovi. To je spletna anketa, ki je učencem prosto dostopna. Med sabo V prihodnjem šolskem letu bi bila spletna anketa lahko so se povezali prek mobilne aplikacije 1KA in anketo rešili. Pri uporabljena že v uvodnih urah omenjenega izbirnega predmeta tem so medpredmetno sodelovali, saj so nadgradili znanje in bi z vprašanji preverjala predznanje učencev, njihova izbirnega predmeta multimedija. Medpredmetno povezovanje je pričakovanja in interese. Na ta način bi bili učenci aktivneje celosten didaktični pristop – pomeni horizontalno in vertikalno vključeni v načrtovanje konkretnih vsebin, ki bodo obravnavane povezovanje znanj, vsebin in učnih spretnosti. V skladu s pri filmski vzgoji. humanističnimi pogledi spodbuja samostojno in aktivno pridobivanje učnih izkušenj. Poteka v celoviti dejavnosti učenca, LITERATURA IN VIRI vključujoč njegove spoznavne, čustvene in telesne funkcije. [1] Učni načrt izbirnega predmeta Filmska vzgoja. https://www.gov.si/ Medpredmetne povezave določajo skupni nameni [3]. assets/ministrstva/MIZS/Dokumenti/Osnovna-sola/Ucni-nacrti/izbirni/3- letni-lahko-krajsi/Filmska_vzgoja_izbirni.pdf (1. 8. 2022) Ker so delali po skupinah, so izvajali tudi sodelovalno učenje. [2] 1KA (Verzija 17.05.02) [programska oprema]. (2017). Ljubljana: Fakulteta Skupaj so se dogovarjali glede vsebin vprašanj. Vsak učenec za družbene vede. Dostopno prek https://www.1ka.si. [3] SICHERL-KAFOL, Barbara, 2008, Medpredmetno povezovanje v osnovni torej opravi svojo nalogo ter nato pomaga drugim članom šoli. Didakta [na spletu]. 2008. Vol. 18/19, p. 7–9. (1. 8. 2022) Pridobljeno skupine, da jo tudi oni uspešno opravijo. Pri tem je ključnega na: http://www.didakta.si/doc/revija_didakta_2008_november.pdf. pomena ustrezno sodelovanje med učenci. Pomembno je, da vsak [4] Polak, Alenka, 2020, Sodelovalno učenje, Predstavitev za starše, Pedagoška fakulteta UL. 2020. učenec doseže najboljši učinek pri učenju ter hkrati pomaga drugim članom pri tem, da razumejo učno snov in da uspešno sodelujejo [4]. 404 Učenje svetlobe na daljavo Online Teaching About Light Primož Hudi II. Osnovna šola Celje Celje, Slovenija primozhudi@gmail.com POVZETEK ter urejajo vse potrebne zadolžitve. Med pandemijo Covid-19 sta se digitalno poučevanje in učenje pokazala kot nujen vir Pandemija je šokirala ves svet in spremenila marsikateri segment izobraževanja za učence in šole po vsem svetu. Digitalna našega življenja, tudi izobraževanje ni izvzeto. Klasične metode preobrazba družbe je seveda terjala svoj dolg tudi pri tovrstnem oz. bolje rečeno sistemi poučevanja so se morali čez dan poučevanju fizike. prilagoditi in spremeniti na način, da so bila človeška življenja Učenje fizike naj bi bilo življenjsko. Prepletanje teorije same zaščitena in da je bil hkrati izpad znanja čim manjši. V prispevku s seboj vodi v večinoma dolgočasne ure, ki razen teoretičnega so predstavljeni pozitivni in negativni učinki poučevanja na znanja ne prebudijo zanimanja za praktičen (eksperimentalni) del daljavo ter navedenih je nekaj konkretnih primerov učenja fizike, ki pogosto na enostaven način poveže razred z svetlobe na daljavo v okviru predmeta fizika. Na slikah so življenjskimi primeri. Pomembno je, da učenci prepoznajo fiziko prikazani eksperimenti in povezave različne IKT opreme tudi popoldne, ko se je ne učijo za oceno, ampak raziskujejo sto (računalnik, kamera, iPad, spletna kamera, magnetna tabla), brez in eno dejavnost, ki je vsaj deloma povezana z naravoslovjem. katere bi bilo raziskovanje svetlobe pri učenju fizike zelo Učitelji, ki kvalitetno predavajo fiziko na vseh stopnjah okrnjeno, dolgočasno. izobraževanja, uporabljajo poleg IKT tehnologije tudi eksperimentalni pouk. V zadnjih mesecih oz. bolje rečeno, zdaj KLJUČNE BESEDE že letih, se je poučevanje deloma spremenilo, ker so se morali IKT oprema, simulacija, eksperiment, poučevanje svetlobe predavatelji prilagoditi na poučevanje na daljavo ali na kombinirano poučevanje (v živo in na daljavo) [1]. V prispevku ABSTRACT bo v nadaljevanju predstavljenih nekaj različnih preprostih The COVID-19 pandemic shocked the whole world and changed poskusov, animacij in načinov, kako poučevanje svetlobe, med many segments of our lives, here also education is no exception. delom na daljavo, približati mladim fizikom [2]. Classical methods or better said, teaching systems had to adapt and changed over the night in a such a way that human lives were protected and that at the same time the loss of knowledge was as 2 JEDRO small as possible. The paper represents the positive and negative Poučevanje in tudi učenje sta kompleksna in povezana procesa. effects of distance learning and gives some concrete examples of Veliko dejavnikov se mora zvrstiti, da je prenos in zapomnitev online learning of title of light within Physics. The given pictures informacije na relaciji učitelj-učenec, uspešna. Učenje na daljavo illustrate experiments and useful connections of various ICT žal ni nova tema za vse udeležence, tako učence in učitelje kot equipment (such as computer, camera, iPad, web camera, tudi starše. Številni starši so se v zadnjih letih pogosto srečali v magnetic board), without which the learning Physics would have vlogi učitelja, kar ni nujno slabo, saj mnogi zdaj bolj cenijo been very limited and boring. učiteljski poklic, ki z leti izgublja ugled v družbi in je pogosto zapostavljen. Po internih pogovorih in anketah si velika večina KEYWORDS udeležencev; tj. otrok in staršev, želi, da bi izobraževanje v ICT equipment, simulation, experiment, teaching light prihodnje potekalo po »starih« ustaljenih smernicah; brez uporabe zaščitnih mask, samotestiranj, karanten ... Na začetku prispevka se bomo tako dotaknili nekaterih 1 UVOD pomembnih prednosti in slabosti v splošnem, ki jih prinese učenje na daljavo; v drugem delu pa bomo na praktičnem Spletno izobraževanje je oblika izobraževanja, ki se izvaja prek primeru obravnave Svetlobe, primerjali klasični in digitalni pouk interneta. Učenci pri tem uporabljajo svoje domače računalnike ali pametne naprave in prek njih obiskujejo spletna predavanja fizike, ki se zahteva v osmem razredu osnovne šole. Začnimo s prednostmi spletnega izobraževanja. Fleksibilnost je zagotovo tako staršem kot učencem pomenila nekakšno Permission to make digital or hard copies of part or all of this work for personal or komoditeto. Učenci so na naši šoli do 8. ure zjutraj dobili vsa 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 navodila, kaj učitelji pričakujejo, da bodo v tem dnevu storili, in citation on the first page. Copyrights for third-party components of this work must kdaj jih čakajo obvezne videokonference. Na podlagi teh be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia podatkov so si lažje organizirali dan in si individualno prilagodili © 2022 Copyright held by the owner/author(s). šolske in zunajšolske obveznosti. Predvsem vozači so 405 privarčevali predvsem pri času, ki so ga prej porabili, da so od da npr. pri mešenju rdeče, zelene in modre svetlobe dobimo belo doma prišli v šolo in nazaj. Starši so tako privarčevali nekaj barvo. Simulacija je prosto dostopna na spletni strani, zato jo evrov pri prevozu. Glavna prednost je, da so bili doma »varni«, lahko uporabimo tako pri rednem pouku kot pri delu na daljavo. saj se niso družili s sošolci in 500 ali več- učenci na šoli. S tem Ne škodi, če učitelj povezavo doda v spletno učilnico, tako da se je delež potencialnih okužb zagotovo zmanjšal. lahko radovedni učenci dodatne funkcije »stestirajo« doma. Kmalu pa se je na strani učencev (in tudi nekaterih učiteljev) pokazala prva šibkost v precej raznoliki IKT opremi in kompetenci uporabe le-te. Več deležnikov se je možno trudilo, da so zagotovili vsaj osnovno opremo, tako internetno povezljivost kot strojno opremo, ki je bila nujno potrebna za aktivno spremljanje in udeležbo v učno-vzgojnem procesu. Druga slabost je ta, da je do epidemije mnogo staršev mladostnike podila stran od ekranov, potem pa se je zgodba čez noč obrnila in so bili primorani veliko ur na dan preživeti na ta način. Neprijetne posledice bo družba občutila še dolgo. Interakcija s sočlovekom je bila zelo motena. Šola, ki ima kot Slike 1 in 2: Simulacija »Color vision« [3] ali v prevodu taka, več nalog, ne le, da mlade nauči novih znanj, ampak jih »Kako vidimo barve« hkrati tudi vzgaja. Interakcija na ravni učenec-učenec in učitelj- učenec je pri tej obliki šolanja zelo motena. Devetošolci so Pri spektru elektromagnetnega valovanja se pri svetlobi najprej postali apatični in jih je bilo najtežje motivirati za omenita infrardeča in ultravijolična svetloba. Obe sta za naše oči sodelovalno učenje. Izklop kamer je bil z njihove strani pogost nevidni. IR svetlobo je najbolj priročno opazovati z dotično odziv. Tako je bila »človeška« interakcija še dodatno otežena. kamero; UV svetlobo pa lahko demonstriramo z »nevidnim Mlajši učenci (konkretno šestošolci) so pokazali veliko več pisalom« in UV svetilko (slika 3). Poskus brez težav interesa in volje do videokonferenc in »online« druženja. Nadzor demonstriramo prek spletne kamere. poteka učne ure in spremljanje napredka učencev je prav tako zelo otežen. Oddana domača naloga v spletno učilnico še ne pomeni, da je avtor avtentičen. Starši so pogosto naredili levji delež obveznosti, da bi otroku pomagali, niso se pa zavedali, da s tem ne koristijo svojemu otroku. Vredno je omeniti še samodisciplino in motnje. Peščica otrok je bila sposobna, da so sami sestavili svoj urnik dela in se ga disciplinirano držali, oddajali potrebno in brez večjih zapletov zaključili ocene. Motenj doma je bilo precej. V družini je lahko več otrok, prostorov za videoklice pa premalo, tudi starši so morali delati od doma ali pa so preprosto gledali nogomet, tudi hišni ljubljenčki so nas znali nasmejati. Učitelji so s strani ministrstva dobili številne napotke, kako ocenjevati »druge oblike dela« in ne uporabljati klasičnega Slika 3: Nevidno UV pisalo ustnega in pisnega ocenjevanja znanja. Na ta račun so povprečne ocene letele v nebo. Povprečje za vpis v nekatere gimnazije ali V učnem načrtu je nekaj ur namenjenih obravnavi leč in zrcal. pogoji za pridobitev Zoisove štipendije so še vedno neživljenjski, Najboljši pristop učenja je kombinacija eksperimentiranja (slike lahko rečemo tudi smešni. 4, 5 in 6), razlage s pomočjo magnetne table in optične zbirke ter Mnogim učiteljem fizike, ki so kljub izrednim razmeram na uporaba namenske aplikacije na iPadu. Seveda pa je utrjevanje s šolah vztrajali pri eksperimentalnem in IKT pouku, se je priprava pomočjo delovnega zvezka in učbenika nujno, če želimo trajno na ure pošteno podaljšala. V učilnici za fiziko so naloženi številni znanje. Slika 4 prikazuje konkavno ali vbočeno zrcalo za ličenje programi, ki omogočajo izvedbo in analizo poskusov. Na vseh ali britje, ki ga mladina pozna, saj je pogost pripomoček v ostalih računalnikih te opreme seveda ni. Ker se je bilo treba kopalnicah. Sami povedo, da je slika povečana, prav obrnjena; vsako uro seliti v drugo učilnico, teh pa ni bilo malo, je bil ne moremo pa je ujeti na zaslon, zato je navidezna. Že med delovni dan daljši, da si je moral učitelj pripravil vse potrebno za, konferenco lahko za nekaj sekund zapustijo računalnike in sami že vpeljano in v prejšnjih letih preverjeno, učno uro. Da ne eksperimentalno ugotavljajo, kdo od njih je videl najbolj omenjamo kopice pripomočkov, ki jih je bilo treba iz ure v uro povečano sliko svojega obraza, razmislijo, od česa je to odvisno, prenašati, dobesedno, po celi šoli. Glede na to, da neugodne kdaj vidijo ostro sliko ipd. razmere trajajo že več let, je potrebno kar nekaj notranje motivacije, da zgornjega opisa dela učitelj ne zamenja za kredo in tablo. Sledi opis poučevanja svetlobe po klasičnem sistemu in primerjava z delom na daljavo. V uvodu pri obravnavi teme Svetloba se omeni primerjava mešanja barv pri fiziki in likovnem pouku. Učenci imajo več izkušenj z delom s čopičem in z barvami; simulacija »color vision« [3] na sliki 1 in 2 pa pokaže, 406 Osebni stik prek videokonference je zelo zaželen, kar v tem primeru pomeni, da učitelj med uro večkrat preklaplja med vsaj dvema kamerama (pogled na magnetno tablo; slika 9) in med kamero na računalniku, zato je pomembno, da je računalnik in posledično tudi mikrofon blizu mesta razlage. Sliki 4: Konkavno zrcalo za ličenje Če obrnemo ukrivljenost zrcala, dobimo konveksno ali izbočeno zrcalo. Pri njem se zorni kot poveča, na ta račun pa se slika zmanjša. Ne mestu je vprašanje, kje v življenju učenci srečajo takšno zrcalo, kje bi lahko bilo uporabno ali še drugače, kje dnevno rešuje številna življenja. Na sliki 6 je prikazan Van de Graaffov generator, ki ga lahko učitelj nosi po razredu. Učenci pri tem opazujejo, če se kdaj vidijo enako velike kot v ravnem Slika 9: Konveksno zrcalo na magnetni tabli v razredu in zrcalu, če lahko sliko ujamejo na zaslon, se kdaj vidijo megleno med videokonferenco na prenosnem računalniku ali vidijo narobe obrnjeno sliko. Pri delu na daljavo si lahko učitelji pomagamo s kamero ali pa učence spomnimo na zrcalo ob cesti (slika 5). Je pa »v živo« izkustveno učenje, v tem Dobrodošli so namenski programi (sliki 10 in 11) pri primeru, bistveno bolj produktivno. določeni temi, ki zelo nazorno in v kratkem času prikažejo bistvo ter nazorno povežejo eksperiment, razlago in vsakdanje življenje. To je pika na i, ki zaključi razlago snovi pri Svetlobi. Po potrebi lahko učitelj na tablo doriše (slika 11), kar meni, da je potrebno še posebej poudariti. Sliki 5 in 6: Konveksno zrcalo ob cesti in Van de Graaffov generator Osnovno poznavanje preprostih pojmov, kot so npr. goriščna Sliki 10 in 11: Aplikacija »Ray Optics«; povezava iPada, razdalja, teme, gorišče in navidezno gorišče so nujno potrebni. S računalnika, projektorja in spletne kamere pomočjo vzporednega snopa laserskih žarkov na magnetni tabli je razlaga preprosta. Pri šolanju na daljavo pa je v tem primeru nazornost poskusa še večja. Trditev prikazujeta sliki 7 in 8. 3 ZAKLJUČEK Poučevanje na daljavo se je zgodilo »čez noč« in takrat so bili vsi učitelji primorani se znajti po svojih najboljših močeh. Mlajši generaciji je bilo verjetno malo lažje, saj so bolj vešči dela z računalnikom in IKT opremo, saj so se predhodno več usposabljali na tem področju [4]. Se je pa zgodba precej podaljšala in zdaj imajo vsi precej izkušenj s takšnim delom. Kot smo že omenili v tem prispevku, so plusi in minusi pri obeh načinih učenja. Smiselno je, da za vsako posamezno temo razmislimo, katere pristope »na daljavo« je smotrno uvesti kot Sliki 7 in 8: Konkavno zrcalo na magnetni tabli v razredu in nekakšen podaljšek oz. dodatek v klasični pouk. Npr. bolj v videokonferenci pogosta uporaba spletne učilnice, oddaja pomembnih domačih nalog v spletno učilnico, konferenca za učitelje na daljavo idr. Sodobna tehnologija nam mora biti v pomoč. Osebno sem velik zagovornik le-te, moramo pa kritično presoditi, kolikšen del ur 407 namenimo takšnemu sistemu dela, da ure niso prenasičene in da [2] K. Ndihokubwayoa, J. Uwamahoroa, I. Ndayambajeb: Effectiveness of se bistvo ne izgubi. Priporočljivo je vsakih nekaj ur »presekati« PhET Simulations and YouTube Videos to Improve the Learning of Optics in Rwandan Secondary Schools (splet). 2021. Dostopno na naslovu ustaljeni način dela in za eno šolsko uro spet uporabiti samo [3] https://journals.co.za/doi/epdf/10.1080/18117295.2020.1818042 »kredo in tablo«. [4] Phet interactive simulations (University of Colorado Boulder), Color vision (splet). 2022. Dostopno na naslovu [5] https://phet.colorado.edu/en/simulations/color-vision (10.8.2022) LITERATURA IN VIRI [6] H. Beyazoglu: Psihologija pandemije; Posamezniki in družba v času koronske krize (splet). 2020. Dostopno na naslovu [1] J. Singh, K. Steele, L. Singh: Combining the Best of Online and Face-to-Face [7] https://dlib.si/stream/URN:NBN:SI:DOC-V1B59SOJ/33d1c335-e08e-4ac9- Learning: Hybrid and Blended Learning Approach for COVID-19 (splet). b1ed-e6b54c5e0d44/PDF 2021. Dostopno na naslovu https://journals.sagepub.com/doi/full/10.1177/00472395211047865 408 Učna akademija – skupnost učiteljev, ki temelji na kolegialnem sodelovanju in skupnem učenju Learning Academy – A Community of Teachers Based on Collegial Cooperation and Joint Learning Katarina Jagič ŠC Kranj, Medpodjetniški izobraževalni center Kranj, Slovenija katarina.jagic@sckr.si POVZETEK KEYWORDS Epidemija covida-19 je močno zarezala v življenje ljudi. Vpliv Affiliation, community, help, workshops, support, MC Teams, ni bil le fizične in psihološke narave, soočiti se je bilo potrebno experience tudi s (pre)hitrimi prilagoditvami na nov način dela. Učitelji so v pogojih zaprtja šol, večina prvič v karieri, morali izvajati izobraževanje na daljavo. Prehod na nove oblike dela je porajal 1 UVOD različne odzive – pozitivne in negativne. Nekateri so se pokazali Spremembe so stalnica. Vse bolj pa se navajamo na to, da se takoj, drugi z zamikom. Odvisno od starosti, zmožnosti dogajajo hitreje in so kompleksnejše. Poleg spreminjanja ciljev dojemanja in spoprijemanja s situacijo, preteklih izkušenj, pa izobraževanja, generacij učencev in pojmovanja znanja se tudi podpore. Članek opisuje novonastalo podporno okolje za spreminjajo tudi oblike dela. Posledično se spreminja vloga učitelje v Šolskem centru Kranj. Učna akademija je skupnost učitelja. Epidemija Covida-19 je še bolj zamajala že tako hitro učiteljev, ki je na način on-line delavnic, kjer so posamezniki spreminjajoče se temelje našega šolstva in povzročila kaotično primere dobre prakse kolegialno delili med sodelavce, povezala stanje. Države so v času pandemije sprejemale raznovrstne kolektiv in s skupnim učenjem ter deljenjem izkušenj rešila ukrepe. Le-ti so se odvijali tudi v našem šolskem sistemu in jih marsikatero učiteljevo dilemo in strah. je spodbujal tudi Zavod RS za šolstvo v sodelovanju z Ministrstvom za izobraževanje, znanost in šport. Med ključnimi KLJUČNE BESEDE dejavnostmi, ki jih navajajo avtorji v Analizi izobraževanja na Pripadnost, skupnost, pomoč, delavnice, podpora, MC Teams, daljavo v času prvega vala epidemije covida-19 v Sloveniji [1], izkušnje poleg spodbujanja k spremljanju ter nadzoru učencev, formativnemu spremljanju in podpori ranljivim skupinam, ABSTRACT navajajo tudi pomembnost dviga kapacitet nacionalnih platform The covid-19 epidemic has greatly affected people's lives. The za izobraževanje na daljavo, spodbujanja učiteljev k impact is not only of a physical and psychological nature, it was izobraževanju za poučevanje na daljavo ter medsebojnemu also necessary to deal with (too) quick adaptations to a new way sodelovanju in tudi vzpostavitev sodobnih odprtih informacijskih of working. In the conditions of the closed school, the teachers, virov. most of them for the first time in their careers, had to carry out Delo na daljavo je enakovredno delu v razredu, raba sodobne distance education. The transition to new forms of work informacijsko komunikacijske tehnologije (v nadaljevanju IKT) generated various reactions - positive and negative. Some pa je osnovni pogoj za njegovo uspešno izvedbo. Poleg izbrane manifested themselves immediately, others with a delay - tehnologije so za kvalitetno izvedbo pouka na medmrežju depending on age, ability to perceive and cope with the situation, ključne tudi digitalne kompetence učitelja. Le-te so med učitelji past experiences, as well as support. The article describes the različne, zato sta tehnična in sistemska podpora nujni. newly created support environment for teachers in the School Center Kranj. The learning academy is a community of teachers who, through online workshops where individuals shared 2 PODPORNO OKOLJE examples of good practice collegially among their colleagues, V času prvega vala epidemije je po rezultatih analize [2], connected the collective and solved many dilemmas and fears medsebojna pomoč učiteljev, v okviru izmenjave idej, gradiv in through joint learning and sharing experiences. primerov dobrih praks, intenzivno potekala v spletnih učilnicah Zavoda RS za šolstvo, veliko se je razpravljalo in objavljalo v Permission to make digital or hard copies of part or all of this work for personal or forumih. Poleg tega so bila organizirana različna izobraževanja, 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 ki so se nadaljevala tudi v času po epidemiji, delovale so citation on the first page. Copyrights for third-party components of this work must študijske skupine. Navkljub množični podpori so se učitelji še be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia vedno znašli v situacijah, ko so pri uporabi različnih spletnih © 2022 Copyright held by the owner/author(s). učnih okolij (spletna učilnica Moodle, Google Classroom …) ter 409 uporabi videokonferenčnega okolja za namene poučevanja na 2.2 Učna akademija daljavo, za preverjanja in ocenjevanja znanja na daljavo, Učna akademija je v aplikaciji Microsoft Teams nastala kot sestavljanja nalog in dejavnosti za samostojno učenje, izdelave odgovor na tehnična, pa tudi vsebinska vprašanja, ki so se posnetkov idr. potrebovali tehnično podporo. Na ŠC Kranj smo učiteljem porajala v času izvedbe dela na daljavo. Članstvo v njej z namenom tovrstne podpore, s pomočjo programske opreme je prostovoljno. Šolski center Kranj deluje v okviru petih Microsoft Teams, učiteljem ponudili vključitev v skupnost, ki jih organizacijskih enot, trenutno je v Učno akademijo vključenih medsebojno povezuje in jih s primeri dobrih praks opolnomoči 109 članov, tri osebe imajo status lastnika ekipe, kar je skoraj 2/3 za delo. Izhajali smo iz dejstva, da je medsebojna pomoč zaposlenih. najučinkovitejša pomoč. Pomeni, »da se učimo drug od drugega Kot že omenjeno v uvodu, se dileme razrešujejo v obliki spletnih in drug z drugim, z notranjimi močmi (sodelovalna seminarjev (webinarjev), ki jih Arnes poimenuje tudi predavanja organizacijska kultura šole, kolegialno učenje …) in z zunanjo na spletu. Izvajalec in udeleženci se seminarja udeležijo hkrati, podporo (medšolska sodelovanja na različnih ravneh, med seboj pa komunicirajo ali preko video in zvočne povezave usposabljanja …)«, kot v prispevku o sodelovanju piše Katja ali pa s pisnimi komentarji [6]. Uvodna stran Učne akademije je Pavlič Škerjanc [3]. Dandanes je na voljo sicer obilo spletnih predstavljena na sliki 1. pomočnikov, vendar je prav, da konkretne rešitve vsako šolsko okolje poišče in vzpostavi zase. 2.1 Programska oprema Microsoft Teams Z namenom dviga e-kompetentnosti se je celoten kolektiv ŠC Kranj, vključno s tehničnim osebjem, leta 2018 vključil v 60-urni izobraževalni program Razvoj digitalne pismenosti prek uporabe storitev v oblaku. Poudarek programa je bil na programski opremi Microsoft Tems v storitvi Office 365 [4], ki je naročniška storitev v oblaku, v kateri so poleg Teamsov, združena najboljša orodja za izvedbo dela na medmrežju (Excel, Word, Power Point, OneNote idr.). Storitev je v začetnem vodniku aplikacije [5] definirana kot delovni prostor, ki omogoča klepete in nudi različna orodja za ustvarjanje različnih vsebin in je tako digitalno središče za komunikacijo med učitelji in učenci, učitelji v kolektivu, med nadrejenimi in podrejenimi. Izkazalo se je, da je bila odločitev vodstva za tovrstno usposabljanje, kljub nekaterim pomislekom in kritikam, pravilna, saj se je pomanjkanje znanja uporabe IKT realno pokazalo šele s prisilnim prehodom na delo na daljavo. ŠC Kranj je kot programsko orodje za izvedbo pouka od doma tako izbral Microsoft Teams, vendar kljub temu, da so Slika 1 : Učna akademija ŠC Kranj (vir: lasten) učitelji znanje za uporabo Temsov že pridobili na usposabljanju, je bilo s prenekaterimi učitelji tečaj potrebno ponoviti ali Znotraj ekipe Učna akademija so se oblikovali štirje kanali: obnoviti.  Splošno 2.2.1 Delovanje programske opreme Teams. Office 365 so  Orodja za ocenjevanje storitve in orodja, ki omogočajo komunikacijo med vsemi  Orodja za delo na daljavo udeleženci v izobraževanju. Vsaka ustanova ima administratorja,  Predlogi, mnenja, komentarji ki uporabnikom dodeli uporabniški račun in geslo. Dostop pa V kanalu splošno se objavljajo vabila za spletne seminarje omogoča brezplačno uporabo. (webinarje) na različne teme, njihove kratke vsebine ter koledar Medmrežna komunikacija v programskem orodju Microsoft dogodkov. Slika 2 predstavlja eno od takšnih objav. Termini Teams se začne s postavitvijo ekipe. Lahko smo njen lastnik, posameznih usposabljanj se večinoma določajo s pomočjo lahko pa se že ustvarjeni ekipi zgolj pridružimo in postanemo aplikacije forms, kjer člani glasujejo za najprimernejšega. Izbran njen član. Lastnik ekipe določa, kdo bo njen član in lahko vključi je termin z največ glasovi, na ta način pa dosežemo čim večjo le željene posameznike. Obenem članom določi stopnjo udeležbo. Prav tako se v tem kanalu vnaprej zbirajo vprašanja za upravljanja ekipe (solastnik ekipe ali član) in pravice sodelovanja predavanja v napovedniku. Tisti, ki seminar pripravlja, se tako in moderiranja v ekipi (objava in deljenje dokumentov, uporaba lahko bolje pripravi in se že v predstavitvi podrobneje dotakne memov, nalepk …). Vsaka ekipa si ustvari svoje kanale. Prvi dotičnih težav in predstavi možne rešitve. kanal se imenuje »Splošno«, in se oblikuje ob stvaritvi ekipe. Je namenjen osnovnim informacijam in ga lastnik po potrebi lahko zaklene. Vsak naknadno dodan kanal poimenujemo poljubno glede na tematiko, znotraj kanala pa se odvijajo klepeti, videokonference, delijo se dokumenti, le-te pa lahko preko že omenjenih on-line aplikacij tudi skupno urejamo. 410 rast. Učna akademija je primer oblike povezovanja in sodelovanja učiteljev, kjer se vzpostavlja okolje medsebojnega zaupanja. S tem, ko si pomagamo, se povezujemo. Verjamemo in zaupamo v znanje drug drugega, pa tudi priznati si upamo, da ne vemo vedno vsega, četudi se od nas, učiteljev, marsikdaj pričakuje, da smo vsevedni. 2.2.2 Izzivi za prihodnost. Prvenstveno je Učna akademija nastala kot podporno okolje učiteljem v času soočanja s težavami ob delu na daljavo. Tematika videokonferenčnih seminarjev je bila v celoti vezana na to problematiko. Vsekakor bi bilo, glede na pozitiven odziv udeleženih, smiselno njeno idejo razširiti tudi na druge teme, ki niso usmerjene samo v pridobivanje veščin za delo, ampak tudi v kvalitetno preživljanje prostega časa ter fizično in psihično vzdržljivost. Razmisliti bi bilo potrebno tudi o morebitnem skrbniku ekipe, ki bi skrbel za kontinuirana usposabljanja, da ideja ne bi zamrla. S tem pa bi se verjetno Učna Slika 2 : Učna akademija - kanal Splošno (vir: lasten) akademija morala širiti tudi na izvajalce izven našega Centra – kolege iz drugih šol ter nepedagoške strokovnjake iz Slovenije in Videokonferenčni seminarji (webinarji) potekajo v kanalih tujine. orodja za ocenjevanje in orodja za delo na daljavo, razvrščeno glede na tematiko. Seminarji potekajo v živo, posnetki ter 3 ZAKLJUČEK prosojnice ali razna gradiva pa se shranjujejo v posameznem kanalu pod zavihkom datoteke. Uporabniki imajo tako vedno Spremenjen način poučevanja, ki ga je zahtevala epidemija možnost, da si seminar ogledajo ponovno ali pa si ogledajo le covida-19, je marsikaterega učitelja postavila v težak položaj. določene odseke, ki jih zanimajo. Obenem znotraj kanala, v Brez izjeme smo morali vsi, ne glede na stopnjo digitalne komentarjih, poteka tudi razprava na predstavitev. Na vprašanja, kompetentnosti, izvedbo svojega dela prenesti na medmrežje. pripombe ali dileme lahko odgovarjajo vsi uporabniki in delijo Zmeda, ki jo je v šolskem prostoru povzročila pandemija, nas je svoje znanje in izkušnje. Primer seminarja v kanalu s komentarji naučila, da je edina prava in trajna rešitev ta, da se naučimo to predstavlja slika 3. zmedo sprejeti in z njo živeti. Pri tem je najpomembneje, da se medsebojno povežemo in si medsebojno pomagamo. Interni učni centri, kot je Učna akademija, so primeri dobre prakse, ki lahko pomembno pripomorejo h kvaliteti dela kot tudi k profesionalnemu razvoju pedagoških delavcev. Pomembno je, da so vsebine raznolike in niso usmerjene le na eno področje. Učitelj namreč potrebuje širše podporno okolje, ki mu bo oporo nudilo pri pridobivanju IKT ter pedagoških kompetenc ter mu koristilo pri osebnih izzivih. VIRI IN LITERATURA [1] Rupnik Vec. T., Silvar. B., idr. (2020) Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji (online). (Najdeno 1. 8. 2022). Najdeno na spletnem naslovu https://www.zrss.si/pdf/izobrazevanje_na_daljavo_covid19.pdf [2] Rupnik Vec. T., Silvar. B., idr. (2020) Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji (online). (Najdeno 1. 8. 2022). Najdeno na spletnem naslovu https://www.zrss.si/pdf/izobrazevanje_na_daljavo_covid19.pdf [3] Pavlič Škerjanc K., Sodelovati, ne sodelovati: to ni tu vprašanje. (oneline). Slika 3: Učna akademija – Primer objave v kanalu Orodja Najdeno 5. 8. 2022 na spletnem naslovu http://publikacija.k56.si/strokovnjaki/4.%20Katja%20Pavlic%20Skerjanc. za delo na daljavo %20Sodelovati,%20ne%20sodelovati;%20to%20ni%20tu%20vprasanje.pdf [4] Začetni vodnik aplikacije Microsoft Teams za vodstvene delavce v šoli. V kanalu predlogi, mnenja, komentarji se objavljajo pobude Microsoft. (online). (Najdeno 1. 8. 2018). Najdeno na spletnem naslovu https://support.office.com/sl-si/article/za%C4%8Detni-vodnik-aplikacije- in ideje za nove seminarje ter raznorazne povezave na druge microsoft-teams-za-vodstvene-delavce-v-%C5%A1oli-f054451e-5c94- poučne in zanimive vsebine. 4023-9ac0-797981d10971 [5] Kaj je Office 365? (online). (Najdeno 2. 8. 2018). Najdeno na spletnem 2.2.1 Izvajalci spletnih seminarjev. Izvajalce spletnih naslovu https://products.office.com/sl-si/home seminarjev v Učni akademiji izbiramo znotraj kolektiva ŠC [6] Kaj je spletni seminar? (online) (Najdeno 8. 8. 2022) Najdeno na spletnem Kranj. S tem, ko učitelji delijo svoje znanje med sodelavci in naslovu https://www.arnes.si/kaj-je-spletni-seminar-webinar-in-kaj-je-most/ delujejo v timskem duhu, doživljajo profesionalno in osebnostno 411 Problem zasebnosti in varnost uporabnikov na družbenih omrežjih The Problem of the Privacy and Security of Users on Social Networks Veronika Jakopič Nika Tomšič Laura Horvat Univerza v Mariboru Univerza v Mariboru Univerza v Mariboru Maribor, Slovenija Maribor, Slovenija Maribor, Slovenija veronika.jakopic@student.um.si nika.tomsic@student.um.si laura.horvat2@student.um.si Žiga Jakomini Vili Podgorelec Ines Kožuh Univerza v Mariboru Univerza v Mariboru Univerza v Mariboru Maribor, Slovenija Maribor, Slovenija Maribor, Slovenija ziga.jakomini@student.um.si vili.podgorelec@um.si ines.kozuh@um.si POVZETEK perceptions of privacy and security. For this purpose, we designed a questionnaire and sent it to representatives of V prispevku raziskujemo problematiko dojemanja zasebnosti in Faculties and Secondary Schools in the Podravje region. It was varnosti slovenskih uporabnikov družbenih omrežij. Kljub več also distributed to students of these educational institutions. The raziskavam na tem področju zaznavamo v slovenskem prostoru results showed that women have a better perception of privacy manko raziskav, ki bi preučevale mlade uporabnike družbenih on social networks than men. The results also revealed that the omrežij v Sloveniji. Glavni namen raziskave je bil tako preučiti area in which users are educated has a statistically significant vpliv spola oz. izobrazbe uporabnika na dojemanje zasebnosti in impact on perceptions of security. On the other hand, the results varnosti. V ta namen smo zasnovali anketni vprašalnik in ga do not suggest that gender influences the perception of security, poslali predstavnikom fakultet in srednjih šol v podravski regiji. or that the field of education influences the perception of privacy Prav tako samo ga posredovali študentom in dijakom teh on social networks. The results may serve as a basis for future izobraževalnih ustanov. Rezultati so pokazali, da ženske bolje research in the area of the privacy and security perceptions of dojemajo zasebnost na družbenih omrežjih kot moški. Rezultati Slovenian students and social network users. so prav tako razkrili, da to, na katerem področju se uporabniki izobražujejo, statistično značilno vpliva na dojemanje varnosti. KEYWORDS Po drugi strani pa iz pridobljenih rezultatov ne moremo trditi, da bi spol vplival na dojemanje varnosti ali da bi področje Social networks, privacy, security, risk, user data izobraževanja vplivalo na dojemanje zasebnosti na družbenih omrežjih. Rezultati lahko v prihodnje služijo kot podlaga za 1 UVOD nadaljnje raziskovanje področja dojemanja zasebnosti in varnosti slovenskih študentov in dijakov oziroma uporabnikov družbenih Na družbenih omrežjih obstaja mnogo groženj zasebnosti in omrežij. varnosti, ki so ji uporabniki le-teh nenehno izpostavljeni. Družbena omrežja so izraz za spletno programsko opremo in KLJUČNE BESEDE storitve, ki uporabnikom omogočajo, da se družijo na spletu in izmenjujejo mnenja, razpravljajo, komunicirajo in sodelujejo v Družbena omrežja, zasebnost, varnost, tveganje, uporabniški kakršnikoli obliki družbene interakcije; ta lahko zajema različne podatki vrste medijev. Lahko vključuje ustvarjanje novih vsebin ali ABSTRACT priporočanje in izmenjavo že obstoječih [1]. V svoji raziskovalni študiji predstavljamo izsledke raziskave, v kateri smo preučevali In this paper, we explore the issue of Slovenian social network dojemanje pojmov zasebnosti in varnosti slovenskih users' perceptions of privacy and security. Despite several studies uporabnikov družbenih omrežij. in this area, we perceive a lack of research on young social V slovenskem prostoru zaznavamo manko na področju network users in Slovenia. The main aim of the research was to raziskav na temo zasebnosti in varnosti na družbenih omrežjih examine the impact of gender and education on users' med (mlajšimi) prebivalci Slovenije. Tako smo se s pomočjo obstoječe študije, ki je bila izvedena v Iraku [2], odločili raziskati Permission to make digital or hard copies of part or all of this work for personal or to področje. classroom use is granted without fee provided that copies are not made or distributed V svoji raziskavi smo preučevali dojemanje zasebnosti in 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 varnosti uporabnikov na družbenih omrežjih, raziskava pa je bila be honored. For all other uses, contact the owner/author(s). izvedena med slovenskimi mladimi. Druge študije, ki smo jih Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). zaznali na podobno temo, se od naše razlikujejo po dejstvih, da 412 so bile izvedene v drugih državah, na drugih starostnih skupinah dimenzij, med katerimi je tudi informacijska zasebnost ali na drugačnih družbenih omrežjih. (zasebnost na spletu). Kovačič [7] navaja, da je problem V prispevku smo najprej predstavili postopek razvijanja ideje računalniške tehnologije in interneta predvsem v tem, da za raziskavo ter opis strategije iskanja za konceptualni pregled tehnologija že sama po sebi omogoča možnost zlorabe raziskave. Temu sledi opredelitev temeljnih konceptov: zasebnosti. Obravnava tudi različne načine ogrožanja zasebnosti družbena omrežja, zasebnost na družbenih omrežjih in varnost na spletu. Tudi Lapenta in Jørgensen [8] omenjata več dimenzij na družbenih omrežjih, podali smo pa tudi relacije med temi zasebnosti, pri čemer izpostavljata, da pravica do zasebnosti koncepti. Nadalje je predstavljen pregled sorodnih del. velja tako za „offline” kot tudi „online” področje, torej ima Sledi opis metodologije, kjer so predstavljene spremenljivke zasebnost na spletu enako pomembno vlogo kot izven spleta. V in raziskovalna vprašanja. Sledi vzorčenje, kjer je opisano, kako skladu s preobrazbo javne sfere pravice do zasebnosti, se koncept smo prišli do udeležencev v raziskavi. Sam postopek raziskave spletne zasebnosti uporablja za predstavitev posebnih izzivov in je opisan v nadaljevanju. Sledi še opis uporabljenih merskih posledic na spletu. Posamezniki imajo pravico do zasebnosti ne instrumentov in predstavitev statistične analize podatkov. Nato samo v zasebni domeni, ampak tudi v javnem prostoru – sem so predstavljeni in interpretirani rezultati raziskovanja, tem pa lahko štejemo tudi družbena omrežja. Z družbenimi omrežji se sledita še diskusija in zaključek, kjer smo povzeli naše pojavijo nove skrbi v povezavi z zasebnostjo, o čemer pišejo ugotovitve. Ahn, Shehab in Squicciarini [9]. Na splošno je vprašanje zasebnosti na družbenih omrežjih povezano z določljivostjo in povezljivostjo informacij, ki so na voljo v tem družbenem okolju, 2 TEORETIČNI OKVIR IN OZADJE njihovih možnih prejemnikov in načinov uporabe. Zasebnost na družbenih omrežjih je tesno povezana z varnostjo [10]. 2.1 Spletna družbena omrežja Spletna družbena omrežja Kaplan in Haenlein [3] definirata kot 2.3 Varnost skupino internetnih aplikacij, ki temeljijo na ideoloških in S porastom uporabe družbenih omrežij je prišlo do pogostih tehnoloških temeljih spleta 2.0 in omogočajo ustvarjanje in težav pri ohranjanju varnosti posameznikov. Ključni dejavnik pri izmenjavo uporabniško generiranih vsebin. Ryan [1] označi spletni ali kibernetski varnosti je posamezni uporabnik [11]. družbena omrežja kot izraz za spletno programsko opremo in Posameznikove izkušnje in dojemanje varnosti na spletnih storitve, ki uporabnikom omogočajo, da se družijo na spletu in mestih v družbenih medijih so večplastne in vključujejo ne le izmenjajo mnenja, razpravljajo, komunicirajo in sodelujejo v digitalno zasebnost, varnost in nadlegovanje, temveč tudi varnost kakršni koli obliki družbene interakcije. Ta interakcija lahko in dobro počutje izven spleta [12]. Z uporabo izraza varnost na zajema besedilo, zvok, slike, video in druge medije, posamično družbenih omrežjih vključujemo tako kršitev varnosti, kot tudi ali v kateri koli kombinaciji. Lahko vključuje ustvarjanje novih drugih možnih zaznav groženj, na primer tistih, ki se nanašajo na vsebin ali pa priporočanje in izmenjavo že obstoječih. Lahko se fizično varnost. To je lahko še posebej pomembno za uporabnike uporabljajo za pregledovanje in ocenjevanje izdelkov, storitev in družabnih medijev, glede na odnos med družabnimi mediji in blagovnih znamk, za razprave o vročih temah, ukvarjanje s spletnim nadlegovanjem [13]. Več študij in nedavnih poročil hobiji, interesi in strastmi. Omogočajo tudi izmenjavo izkušenj novic je poudarilo povečano tveganje osebnih podatkov, ki jih in strokovnega znanja. Cao [4] zapiše, da je pojem družbena obdelujejo spletna družbena omrežja ter pomanjkanje omrežja prvič uporabljen v devetdesetih letih 20. stoletja, z ozaveščenosti uporabnikov [14]. razvojem računalnikov in tehnologije za splet. Popularna so Uporabljeni koncepti se med seboj ne izključujejo. Na postala leta 2008 in so za več milijonov oseb oziroma družbenih omrežjih si želimo predvsem komunikacije – uporabnikov spremenila način komuniciranja [4]. Mnogo izmenjavo mnenj, razprave in sodelovanja [1]. Kljub družbenih omrežij razvija razmerja na več ravneh (npr. več komunikaciji, pa sta zelo pomembni zasebnost in varnost na platform) [5]. Howard in Parks [6] sta podala bolj kompleksno družbenih omrežjih, ki se močno prepletata med seboj. Kot smo opredelitev družbenih omrežij, in sicer, da so sestavljena iz treh že prej omenili, je poleg varnosti, ki si je želimo tudi izven spleta delov: 1. Informacijska infrastruktura in orodja za proizvodnjo in [12], predvsem zasebnost tista, ki jo ne le da želimo, temveč jo distribucijo vsebin. 2. Vsebina v digitalni obliki osebnih sporočil, lahko tudi zahtevamo – na spletu ali drugod [8]. novic, idej in kulturnih izdelkov. 3. Osebe, organizacije in industrije, ki ustvarjajo in zajemajo digitalne vsebine. Zaradi enostavnosti uporabe, hitrosti in dosega so družbeni mediji hitro 3 PREGLED SORODNIH DEL spremili javni diskurz v družbi ter postavljajo trende in agende v Pregledali smo sorodna dela, raziskave, izvedene na področju temah, ki segajo od okolja in politike do tehnologije in zabavne družbenih omrežij, zasebnosti, ozaveščanja o varnosti na industrije. družbenih omrežjih ter jih v nadaljevanju podrobneje predstavili. Izpostavili smo tudi pomanjkljivosti raziskav, ki smo jih opazili. 2.2 Zasebnost Zeebaree, Ameen in Sadeeq [2] so želeli opozoriti na težave Zasebnost je temelj človeškega dostojanstva in drugih vrednot, z varnostjo, ki se pojavljajo z množično uporabo družbenih kot sta svoboda združevanja in svoboda govora, piše Kovačič [7]. omrežij in podali predloge, kako izboljšati s tem povezano Navaja, da so vse človekove pravice neke vrste vidiki pravice do kulturo uporabe (znanje, veščine in vedenje pri uporabi zasebnosti, kot trdijo nekateri drugi avtorji. Pravica do zasebnosti družbenih omrežij). Pri tem so se osredotočili na uporabo je temeljna, vendar ne absolutna, v sodobni družbi pa je postala pametnih telefonov, saj so ugotovili, da so ti v povezavi z ena najpomembnejših človekovih pravic. Zasebnost ima več družbenimi omrežji najbolj uporabljana elektronska naprava. 413 Izvedli so študijo s pomočjo kvantitativne metode (vprašalnika), Nemec Zlatolas [17] v svoji doktorski disertaciji (2015) kjer so ugotavljali, kako družbena omrežja uporabljajo ljudje iz preučuje zasebnost uporabnikov na družbenem omrežju pokrajine Kurdistan (Irak) in ali se zavedajo groženj in tveganj, Facebook. Na podlagi rezultatov anketnega vprašalnika, je ki so jim izpostavljeni z njihovo uporabo. V študiji je sodelovalo določila faktorje dojemanja zasebnosti, ki so: samorazkrivanje 350 ljudi s tamkajšnje javne univerze - uporabnikov družbenih informacij, vrednost zasebnosti, skrb za zasebnost, zavedanje o omrežij. Avtorji so ugotovili, da obstaja grožnja varnosti na zasebnosti, družbena norma zasebnosti, politika zasebnosti in družbenih omrežij, kar je nakazalo potrebo po programih nadzor zasebnosti. Cilj raziskave je bil povezanost vseh naštetih usposabljanja in ozaveščanja uporabnikov za varno uporabo oz. faktorjev. Zaključki dela so obrazložitev spremenljivk. povečanju t. i. kiberkulture. Podali so smernice za uporabo Spremenljivka zavedanja o zasebnosti, ki meri samo obveščenost družbenih omrežij, s poudarkom na zmanjševanju groženj in ljudi o zasebnosti, kršenju le te in postopkih na družbenih tveganj pri deljenju osebnih podatkov s strani uporabnikov. omrežjih. Piše tudi o družbeni normi, ki je vpliv drugih ljudi Menimo, da je slaba stran te študije, da so avtorji uporabili oziroma prijateljev na uporabnika in pa o politiki zasebnosti oz. premajhen vzorec ljudi glede na velik razpon starosti (15-63 let), kako se odraža zaščita njihove zasebnosti in s tem zaupanje zaradi česar rezultati morda niso najbolj zanesljivi. Temu bi se informacij. Spremenljivka nadzora zasebnosti meri, koliko mi izognili tako, da bi določili manjši razpon starosti ali povečali nadzora imajo uporabniki nad tem ter kdo vse lahko dostopa do vzorec, pri čemer je slednje težje izvedljivo. informacij uporabnika. Poleg tega so pomembne tudi vrednosti Zhang in Gupta [15] sta raziskovala ali se z rastjo zasebnosti, skrb za zasebnosti in razkrivanje osebnih informacij. popularnosti družbenih omrežij zvišuje tudi varnost posameznika Avtorica navaja, da je cilj dela bil upoštevati vse spremenljivke, med uporabo le-teh. V raziskavi sta se posvetila predvsem ki vplivajo na zasebnosti in razkrivanje informacij na družbenem meritvam varnosti in zaupanja družbenih omrežij. V začetku sta omrežju Facebook. Kot slabost študije bi šteli to, da je bila naredila pregled spletnih napadov na družbenih omrežjih ter z raziskava izvedena zgolj na enem družbenem omrežju, njimi povezane obveščevalne aplikacije. Družbena omrežja sta Facebooku. Smiselno bi bilo dodati še kakšno drugo družbeno analizirala na podlagi preučevanja posameznih uporabnikov in omrežje, na primer Instagram, ki je z leti postal (zlasti med skupin. Predstavila sta tudi motivacije za tovrstne napade. mladimi) še posebej priljubljen. Druga slabost je leto izida, ki je Ugotovila sta, da kršitev varnosti na družbenih omrežjih 2015, saj so se medtem družbena omrežja razvijala naprej, neposredno vpliva na gospodarsko rast organizacije, saj pride do pojavila pa so se že tudi nova. Prednost dela je velik vzorec nezaupanja z uporabnikove strani. V delu sta predstavila tudi anketirancev, zaradi česar so rezultati študije reprezentativnejši. možne načine izboljšanja varnosti na družbenih omrežjih. Krepitev zaupanja med uporabnikom in družbenim omrežjem zagotavlja višji nivo varnosti. To lahko omrežja dosežejo tako, 4 METODOLOGIJA da so o uporabi osebnih in finančnih podatkov popolnoma transparentna. Uporabniki lahko namreč nastavijo, s kom bodo 4.1 Raziskovalna vprašanja delili informacije, a vseeno bo družbeno omrežje te podatke Določili smo štiri raziskovalna vprašanja, ki so se dotikala naše zmeraj imelo. Prišla sta do ugotovitve, da bi uporabniki morali problematike. Zanimala nas je povezava med spolom uporabnika biti dobro ozaveščeni o načinih zavarovanja svoje spletne in dojemanjem zasebnosti (RV1) ter varnosti (RV2), prav tako identitete, čemur pa ni zmeraj tako. Zaupanje uporabnika pa tudi povezava med izobrazbo ter dojemanjem zasebnosti družbenemu omrežju lahko zelo pripomore k boljši varnosti in (RV3) ter varnosti (RV4). Vsa raziskovalna vprašanja so bila večji uspešnosti organizacije. Menimo, da bi v raziskavi morda inferenčnega tipa. lahko dodali še anketo, kjer bi uporabnike vprašali o njihovem RV1: Ali spol uporabnika vpliva na dojemanje zasebnosti na dojemanju varnosti in zaupanju na družbenih omrežjih. Tako bi družbenih omrežjih? lahko dodali dodatno perspektivo k tematiki. RV2: Ali spol uporabnika vpliva na dojemanje varnosti na Rathore, Sharma in drugi [16] so se v svoji raziskavi družbenih omrežjih? osredotočili predvsem na preučevanje varnostnih vprašanj in RV3: Ali področje izobrazbe uporabnika vpliva na izzivov pri družbenih omrežjih, predstavijo pa tudi zelo dojemanje zasebnosti na družbenih omrežjih? podrobno grožnje glede varnosti in zasebnosti pri le-teh. RV4: Ali področje izobrazbe uporabnika vpliva na Predstavijo tudi podrobno analizo več možnih rešitev za doseg dojemanje varnosti na družbenih omrežjih? zaščite na družabnih omrežij. Sledijo še smeri za prihodnost in predlogi za varnostne odzive. V zaključku poudarijo, da so 4.2 Vzorčenje in udeleženci raziskave družbena omrežja postala zaželen medij za komunikacijo za več V naši raziskavi smo se osredotočili na dojemanje zasebnosti in milijard uporabnikov interneta, vendar pa lahko te storitve varnosti slovenskih uporabnikov družbenih omrežij. V ta namen uporabnike izpostavijo resnim tveganjem, kar se tiče njihove smo določili našo ciljno skupino, ki so bili mladi [18], in iz nje spletne varnosti. V delu se avtorji sklicujejo na mnogo drugih del. dobili vzorec. Vključili smo dijake in študente podravskih Ta sorodna študija se ukvarja z varnostjo oziroma zasebnostjo na srednjih šol, višjih šol in fakultet. Odločili smo se za merski družbenih omrežjih in podrobno predstavi nevarnosti, do katerih instrument v obliki spletnega anketnega vprašalnika. lahko pride na le-teh. (Tem bi lahko bili potencialno žrtve tudi Pri raziskavi smo se poslužili se sistema večstopenjskega Slovenci.) Avtorji predstavijo tudi možnosti zaščite na družbenih vzorčenja in določili pet mariborskih srednjih šol ter pet fakultet omrežjih. Slabost članka je dejstvo, da je bil izdan leta 2017. V mariborske univerze, ki smo jim poslali dopis in k reševanju tem času je možno, da je prišlo do novih nevarnosti in groženj, povabili njihove dijake oz. študente. S tem smo želeli dosegati kot tudi do novih rešitev. Prednost študije pa je razsežnost le-te, različne izobraževalne skupine in smeri. Vprašalnik smo oziroma njena poglobitev v zgoraj navedene točke članka. 414 posredovali predstavnikom organizacij – srednjih šol in fakultet, Določeni latentni spremenljivki oziroma variabli sta: prav tako pa tudi predstavnikom dijakov in študentov. Izbrane dojemanje zasebnosti na družbenih omrežjih (V5) [17] in srednje šole so bile: Srednja elektro-računalniška šola Maribor, dojemanje varnosti na družbenih omrežjih (V6); prikazani sta v Srednja šola za oblikovanje Maribor, Biotehniška šola Maribor, Tabeli 1. III. gimnazija Maribor in Škofijska gimnazija AMS Maribor. Fakultete, na katere smo poslali dopis, so bile: Fakulteta za elektrotehniko, računalništvo in informatiko, Ekonomsko- Tabela 1: Seznam latentnih spremenljivk poslovna fakulteta, Fakulteta za kmetijstvo in biosistemske vede, Pedagoška fakulteta in Fakulteta za naravoslovje in matematiko. Ime spremenljivke Indikatorji 4.3 Postopek raziskave Dojemanje zasebnosti na Pomembnost zasebnosti1 družbenih omrežjih Deljenje podatkov2 Po definiranju teoretičnega okvirja, pregledu sorodnih del in Nadzor nad podatki3 določitvi spremenljivk ter raziskovalnih vprašanj, smo izvedli spletni anketni vprašalnik o dojemanju zasebnosti in varnosti na Dojemanje varnosti na Občutek varnosti4 družbenih omrežjih. Po zasnovi anketnega vprašalnika smo tega družbenih omrežjih Zavedanje nevarnosti5 preoblikovali in naložili na spletno stran 1ka Arnes, preko katere Poznavanje nevarnosti6 smo anketo nato tudi izvedli. Vprašalnik smo posredovali petim srednjim šolam in petim visokošolskim in visokošolskim fakultetam in jih povabili k reševanju. 5 REZULTATI Zbiranje podatkov je potekalo od 21. 12. 2021 do 10. 1. 2022. V nadaljevanju so prikazani rezultati analize podatkov izvedene Vprašalnik smo 10. 1. 2022 zaključili in nadaljevali z analizo raziskave na temo dojemanja zasebnosti in dojemanja varnosti na podatkov s pomočjo programa IBM SPSS Statistics. Podatke družbenih omrežjih. smo uredili, neustrezne izločili in s pomočjo uporabe ustreznih Pri prvem raziskovalnem vprašanju (RV1) smo najprej statističnih testov pridobili rezultate. naredili test zanesljivosti za indikatorje latentne spremenljivke “Dojemanje zasebnosti”. Uporabili smo test Cronbach Alpha. 4.4 Merski instrument Ker se ni izkazalo, da bi vsi indikatorji zanesljivo prispevali k Vprašalnik je bil zasnovan iz demografskih vprašanj in merjenju latentne spremenljivke, smo v analizi odstranili dva vsebinskega sklopa, navezujočega na dojemanje varnosti in indikatorja (“Nadzor nad podatki na družbenih omrežjih” in zasebnosti na družbenih omrežjih. Na začetku smo izmed “Nadzor nad podatki, ki se posredujejo družbenim omrežjem”) demografskih vprašanj zastavili le vprašanje o spolu in starosti. in tako dobili novo spremenljivko “Dojemanje zasebnosti”. Po vsebinskem sklopu vprašanj so na zadnji strani sledila še Izvedli smo test normalnosti porazdelitve podatkov za RV1 nekatera demografska vprašanja: trenutni status, področje (Kolmogorov-Smirnov test), kjer smo ugotovili, da podatki niso izobraževanja ter smer in regija izobraževanja. normalno porazdeljeni (p < 0,05). Glede na nastopajoči V vsebinskem sklopu smo vprašanja razdelili glede na to, če spremenljivki in nenormalno porazdelitev podatkov, smo izbrali so se navezovala na dojemanje zasebnosti ali dojemanje varnosti Mann-Whitneyjev U test. na družbenih omrežjih. Najprej je sledilo splošno vprašanje, če Rezultati testa so pokazali, da ženske boljše dojemajo sploh uporabljajo družbena omrežja. Vsi, ki so odgovorili z ne, zasebnost na družbenih omrežjih v primerjavi z moškimi (U = so vprašalnik zaključili, ostali so nadaljevali s sklopom vprašanj 295; Z = -3,37; p < 0,001). Povprečni rang za ženske je znašal (x o uporabi družbenih omrežij in dojemanju zasebnosti ter varnosti. = 46,32) za moške pa (y= 25,53). Pri sklopu vprašanj o družbenih omrežjih smo uporabili različne Pri drugem raziskovalnem vprašanju (RV2) smo najprej tipe odgovorov, medtem ko smo pri sklopu vprašanj o dojemanju naredili test zanesljivosti za indikatorje latentne spremenljivke zasebnosti na družbenih omrežjih in dojemanju varnosti na Dojemanje varnosti. Uporabili smo test Cronbach Alpha. družbenih omrežjih, uporabili petstopenjsko Likertovo lestvico Ker se ni izkazalo, da bi vsi indikatorji zanesljivo prispevali odgovorov, kjer so anketiranci odgovarjali koliko se strinjajo z k merjenju latentne spremenljivke, smo v analizi odstranili dva določenimi vprašanji oziroma trditvami. indikatorja (“Varnost na družbenih omrežjih”, “Potencialna tarča Najprej smo določili spremenljivke oziroma variable. nevarnosti”) in tako dobili novo spremenljivko “Dojemanje Merljive spremenljivke so: spol (V1), starost (V2), status (V3) in varnosti”. področje izobraževanja (V4). Vrednosti spremenljivke spol: Izvedli smo test normalnosti porazdelitve podatkov za RV2 moški, ženski. Vrednosti spremenljivke starost: do 15, 16-20, 21- (Kolmogorov-Smirnov test), kjer smo ugotovili, da podatki niso 25, 26-30, 31+. Vrednosti spremenljivke status: dijak, študent, normalno porazdeljeni (p < 0,05). Glede na nastopajoči zaposlen, brezposeln, drugo. Vrednosti spremenljivke področje spremenljivki in nenormalno porazdelitev podatkov, smo izbrali izobraževanja [19]: naravoslovne vede, tehniške in tehnološke Mann-Whitneyjev U test. vede, medicinske in zdravstvene vede, kmetijske vede, družbene vede, humanistične vede, splošno izobraževanje, ne vem. 1 Pomembnost zasebnosti: Menim, da je zasebnost na družbenih omrežjih pomembna. 2 Deljenje podatkov: Moti me, ko moram na družbenih omrežjih deliti osebne podatke. 4 Občutek varnosti: Na družbenih omrežjih se počutim varno. 3 Nadzor nad podatki: Menim, da lahko nadziram, katere osebne podatke prikazujem na 5 Zavedanje nevarnosti: Menim, da na družbenih omrežjih obstajajo nevarnosti; Skrbi me, družbenih omrežjih; Menim, da imam nadzor nad podatki, ki jih posredujem družbenim da sem lahko potencialna tarča nevarnosti na družbenih omrežjih. omrežjem; Skrbi me, da družbena omrežja zbirajo preveč mojih osebnih informacij; 6 Poznavanje nevarnosti: Na družbenih omrežjih poznam potencialne nevarnosti (npr. Trudim se obdržati zasebnost na družbenih omrežjih. phishing, kraja identitete, itd.). 415 Rezultati testa so pokazali, da ne moremo trditi, da spol družbenih omrežjih, temveč smo jih dodali le kot konstrukt pri vpliva na dojemanje varnosti na družbenih omrežjih, ker je p > dojemanju varnosti na družbenih omrežjih. 0,05 (sig. = 0,846). V četrti študiji [17] je avtorica imela večji vzorec Pri tretjem raziskovalnem vprašanju (RV3) smo najprej udeležencev, kot smo ga imeli v naši študiji. Osredotočila se je združili vrednosti neodvisne spremenljivke “Področje izobrazbe” na zasebnost uporabnikov družbenega omrežja Facebook. v nove konstrukte. Tako smo dobili naslednje vrednosti: Študija se osredotoča na več dejavnikov zasebnosti na “Splošno izobraževanje” (konstrukt 1), “Naravoslovne in Facebooku in ne toliko na dojemanje zasebnosti na družbenih kmetijske vede” (konstrukt 2) ter “Družbene, tehniške in omrežjih. V naši študiji smo tako dodali še dojemanje varnosti tehnološke vede” (konstrukt 3). V analizo nismo vključili na družbenih omrežjih. vrednosti “Humanistične vede”, “Medicinske in zdravstvene vede” ter vrednosti “Ne vem”, saj noben izmed udeležencev v raziskavi ni izbral teh vrednosti. Pri analizi smo vključili tudi prej 7 ZAKLJUČEK določeno spremenljivko “Dojemanje zasebnosti”. Z raziskavo smo želeli raziskati dojemanje zasebnosti in varnosti Izvedli smo test normalne porazdelitve podatkov za RV3 slovenskih uporabnikov družbenih omrežij. Pri tem nas je (Kolmogorov-Smirnov test), kjer smo ugotovili, da podatki niso predvsem zanimalo ali dejavniki, kot sta spol in področje normalno porazdeljeni (p < 0,05). Na podlagi nenormalne izobrazbe, vplivajo na posameznikovo dojemanje zasebnosti in porazdelitve smo izbrali Kruskal-Wallisov H test. varnosti na družbenih omrežjih. Pri naši študiji se je izkazalo, da ne moremo trditi, da Ugotovili smo, da je v naši raziskavi spol statistično značilno področje izobraževanja vpliva na dojemanje zasebnosti na vplival na dojemanje zasebnosti na družbenih omrežjih. V naši družbenih omrežjih, ker je p > 0,05 (sig. = 0,094). raziskavi se je izkazalo, da anketiranci ženskega spola bolje Pred statistično analizo pri četrtem raziskovalnem vprašanju dojemajo zasebnost na družbenih omrežjih. Pri tem je potrebno smo najprej izvedli test normalnosti porazdelitve podatkov izpostaviti, da bi se rezultati morda spremenili v primeru enakega (Kolmogorov-Smirnov test), kjer smo ugotovili, da podatki niso števila anketirancev obeh spolov. Naš vzorec je namreč zajemal normalno porazdeljeni (p < 0,05). Glede na nastopajoči 63 žensk in le 19 moških. Za razliko od dojemanja zasebnosti, pa spremenljivki in nenormalnost porazdelitev podatkov smo izbrali smo pri dojemanju varnosti na družbenih omrežjih ugotovili, da Kruskal-Wallisov H test. Pri analizi smo uporabili spremenljivki v naši raziskavi spol nanj ni statistično značilno vplival. “Področje izobrazbe” in “Dojemanje varnosti”, ki smo jih Pri analiziranju vpliva področja izobrazbe na dojemanje določili pri analizi prejšnjih raziskovalnih vprašanj. zasebnosti in varnosti smo prišli do obratnih rezultatov. Rezultati testa so pokazali, da področje izobraževanja vpliva Ugotovili smo namreč, da v naši raziskavi področje izobrazbe na dojemanje varnosti na družbenih omrežjih, H (2) = 9,08, p < statistično pomembno ne vpliva na dojemanje zasebnosti, hkrati 0,05. Povprečni rang za konstrukt 1 znaša 37,8; za konstrukt 2 pa se je pokazal vpliv področja izobrazbe na dojemanje varnosti znaša 34,53 in za konstrukt 3 znaša 53,93. na družbenih omrežjih. Glavna omejitev naše raziskave je, da je bil odziv na anketni vprašalnik razmeroma majhen (n=82) in tako vzorec ni 6 DISKUSIJA reprezentativen. Med anketiranci je prav tako prišlo do Vse obstoječe študije, ki smo jih vključili, smo z našo študijo neuravnoteženosti števila študentov in dijakov iz različnih poskusili nadgraditi. Nobena izmed njih ni zastavljena na enak študijskih smeri ter neravnovesja v številu moških in ženskih način, vendar se s tem vsaka posebej lahko dopolnjuje z našo. respondentov. Rezultati bi se morda spremenili v primeru večjih V prvi študiji [2] so avtorji ugotovili, da obstaja grožnja in bolj enakomernih števil vrst anketirancev. Kot drugo omejitev varnosti na družbenih omrežjih ter so podali smernice kako bi izpostavili še majhno geografsko področje v naši raziskavi. V zmanjšati grožnje. Tudi v naši študiji smo se osredotočali na primeru razširitve geografskega območja iz le ene regije na več dojemanje varnosti, pri čemer so rezultati testa pokazali, da ne bi morda dobili drugačne rezultate. Menimo, da bi v prihodnje moremo trditi, da spol vpliva na dojemanje varnosti na družbenih našo raziskavo lahko nadgradili z večjim vzorcem ter glede na omrežjih (RV2). Pri tem moramo poudariti, da sta obe študiji število različnih področij izobrazbe in spola čim bolj imeli majhen vzorec udeležencev. Tako rezultati obeh študij enakomernim. Predlagamo tudi razširitev geografskega območja. morda niso zanesljivi. Za večjo natančnost in lažje analiziranje vpliva bi lahko dodali Pri drugi študiji [15] so avtorji ugotovili, da tem boljše je ali spremenili tudi konstrukte pri Dojemanju varnosti. zaupanje uporabnikov družbenih omrežij in bolj kot so ozaveščeni o varnosti, tem bolj so varni. Že obstoječi študiji smo v pregledu sorodnih del predlagali, da bi avtorji lahko dodali ZAHVALA anketni vprašalnik o dojemanju varnosti uporabnikov na Zahvaljujemo se mentorjema dr. Viliju Podgorelcu in dr. Ines družbenih omrežjih. V naši študiji smo to storili mi; v naši Kožuh za izčrpna navodila, smernice in popravke pri izdelavi raziskavi smo torej želeli izvedeti, kakšen vpliv imata spol in naloge. Zahvaljujemo se tudi dr. Tini Tomažič za pomoč pri področje izobrazbe na dojemanje varnosti na družbenih omrežjih. končni pripravi članka. Hvala tudi vsem sodelujočim v raziskavi. Rezultati so pokazali, da področje izobrazbe (za razliko od spola, RV2) vpliva na dojemanje varnosti na družbenih omrežjih (RV4). LITERATURA IN VIRI V tretji študiji [16] so se avtorji prav tako ukvarjali z [1] Ryan, D. (2014). Understanding digital marketing. London: Kogan Page. varnostjo in zasebnostjo na družbenih omrežij. 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(2019, July). “I just want to feel safe”: A Diary Study of Safety Perceptions on Social Media. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 13, pp. 405-416). 417 Analiza rezultatov tretjega poskusnega tekmovanja v programiranju z delčki Pišek Analysis of the Results of the Third Pišek Block-Based Programming Competition Ines Jelenec Irena Nančovska Šerbec Univerza v Ljubljani, Pedagoška fakulteta Univerza v Ljubljani, Pedagoška fakulteta Ljubljana, Slovenija Ljubljana, Slovenija ij4536@student.uni-lj.si Irena.Nancovska@pef.uni-lj.si POVZETEK and software environment complexity that had the greatest impact on the performance of the participants in each V prispevku analiziramo značilnosti nalog, ki vplivajo na competition category. We characterise the tasks using a difficulty učenčevo uspešnost pri reševanju nalog v okolju Pišek. Za ta index and a discriminability index. These two measures are used namen z uporabo metod strojnega učenja modeliramo dosežke to assess which tasks were the biggest challenge for participants učencev iz tretjega poskusnega šolskega tekmovanja Pišek, ki je and which tasks best discriminated between participants' potekalo leta 2021 in je bilo organizirano pod okriljem društva performance, respectively. Within each competition category, ACM Slovenija. Opisujemo in ocenjeno težavnost in we categorize the tasks according to the tasks forms (tasks on the diskriminativnost tekmovalnih nalog v osnovnošolskih grid, turtle graphics, input-output tasks) and the programming tekmovalnih kategorijah ter navajamo oblike nalog in otežitve environment complexity (limited number of blocks, extended set programskega okolja, ki so imele največji vpliv na dosežke of blocks, tests). For each competition category, we use tekmovalcev znotraj posamezne tekmovalne kategorije. Z predictive models built using random forests to evaluate which indeksom težavnosti in indeksom diskriminativnosti ocenjujemo, variables (features) have the greatest impact on participants’ katere naloge so tekmovalcem v največji izziv za reševanje oz. performance. katere naloge najbolje ločijo med dosežki tekmovalcev. V nadaljevanju znotraj vsake tekmovalne kategorije KEYWORDS kategoriziramo naloge glede na predstavitvene oblike nalog (naloge na mreži, želvja grafika, vhodno-izhodne naloge) in Competition, Pišek, programming, blocks, concepts, forms, otežitve programskega okolja (omejeno število delčkov, complexity, tasks razširjen nabor delčkov, testi). Za vsako tekmovalno kategorijo z napovednimi modeli - zgrajenimi z uporabo naključnih gozdov - 1 UVOD ocenjujemo, katere spremenljivke (značilnosti) imajo največji vpliv na dosežke tekmovalcev. V digitalni družbi ima programiranje pomembno vlogo, saj je ustvarjanje programske opreme ključni element vseh digitalnih KLJUČNE BESEDE naprav. Vendar programiranje ni le pisanje kode, je mnogo več kot to. Z učenjem programiranja se naučimo reševati probleme, Tekmovanje, Pišek, programiranje, delčki, koncepti, oblike, kreativno, logično in abstraktno razmišljati. Znanje otežitve, naloge programiranja nam omogoča boljše razumevanje tehnologije, ABSTRACT njenih prednosti in omejitev. Zaradi vseh pozitivnih lastnosti učenja programiranja je pomembno, da programiranje postane In this paper, we analyse the task characteristics that influence del obveznega osnovnošolskega kurikula. students' performance in solving tasks in the Pišek environment. Z uveljavljanjem položaja računalništva v osnovnošolskih To this end, we use machine learning methods to model the kurikulumih so se v zadnjih dveh desetletjih ukvarjale številne performance of students in the third Pišek School Trial evropske države [1]. V slovenskih osnovnih šolah se Competition, which took place in 2021 and was organised under računalniške vsebine poučujejo v okviru neobveznega izbirnega the auspices of ACM Slovenia. We describe and evaluate the predmeta računalništvo v drugem triletju osnovne šole in difficulty and discriminability of the competition tasks in the obveznega izbirnega predmeta računalništvo v tretjem triletju primary school competition categories, and list the task formats osnovne šole, kar pomeni, da se zaradi izbirnosti mnogi učenci v času osnovnošolskega izobraževanja z računalništvom ne srečajo. Permission to make digital or hard copies of part or all of this work for personal or Učna načrta za oba osnovnošolska računalniška predmeta classroom use is granted without fee provided that copies are not made or distributed vsebujeta vsebine s področja programiranja, pri čemer 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 obveznem izbirnem predmetu računalništvo programiranje del be honored. For all other uses, contact the owner/author(s). izbirnih vsebin. S programiranjem se lahko učenci srečajo pri še Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). dveh izbirnih naravoslovnih predmetih, in sicer pri robotiki v 418 tehniki in pri elektroniki z robotiko. Izključenost oz. slaba vpogled vanje in v njihov vpliv na kognitivno zahtevnost nalog, zastopanost računalništva v osnovnošolskem in srednješolskem za katero domnevamo, da se pokaže pri tekmovalnem rezultatu izobraževanju pri učencih vodi do nepoznavanja temeljnih tekmovalcev. računalniških vsebin. To omejitev lahko delno presežemo z 2.2.1 Programski koncepti. Z modifikacijo nabora izvedbo računalniških tekmovanj in s tem pripomoremo k programskih konceptov, ki ga je predlagal programski svet boljšemu razumevanju delovanja digitalnega sveta ter verjetno k tekmovanja Pišek in naborom programskih konceptov iz odločitvi nekaterih dijakov za študij računalništva [2]. Jukić in Kongove, S. C. [8] in Brennan, K. in Resnick, M. [9] študije smo Matić trdita, da tekmovanja ustvarijo okoliščine, ki omogočijo opisali značilnosti tekmovanja Pišek in za potrebe naše raziskave računalništvu in drugim predmetnim področjem, da postanejo oblikovali sledeč nabor programskih konceptov. bolj zanimiva za učenje [3]. Tekmovanja iz računalništva  Zaporedje ukazov omogočajo uporabo novega znanja in predstavljajo dober način  Zanka: za medpredmetno povezovanje tehnologije, naravoslovja, o Končna zanka matematike in izobraževanja [4]. o Zanka s pogojem o Kompleksnejša zanka o Vgnezdene zanke 2 TEKMOVANJE PIŠEK  Pogojni stavek Društvo ACM Slovenija poleg univerzitetnega programerskega  Podatki: maratona (v nadaljevanju tekmovanje UPM), tekmovanja iz o Branje in izpis podatkov o spremenljivka računalništva in informatike (v nadaljevanju tekmovanje RTK)  Nizi in tekmovanja iz računalniškega mišljenja Bober (v  Operator: nandaljevanju tekmovanje Bober) organizira osnovnošolsko in o Logični in primerjalni operatorji srednješolsko tekmovanje iz programiranja z delčki Pišek (v  Senzorji nadaljevanju tekmovanje Pišek) [5]. Namen tekmovanja Pišek je  Funkcija spodbuditi zanimanje učencev za programiranje in ustvariti 2.2.2 Predstavitvene oblike nalog. Z modifikacijo nabora okolje, kjer učenci tekmujejo med seboj iz osnov programiranja predstavitvenih oblik nalog, ki jih je predlagal programski svet in razvijajo svoj talent za programiranje. Tekmovanje Pišek tekmovanja Pišek smo opisali značilnosti tekmovanja Pišek in za predstavlja most med tekmovanjema Bober, ki privabi veliko potrebe naše raziskave oblikovali sledeč nabor predstavitvenih tekmovalcev, in tekmovanjem RTK, ki privabi le malo oblik nalog. tekmovalcev [6]. Tekmovanje Pišek je bilo leta 2022 prvič Želvja grafika: tekmovalci z uporabo želvje grafike uradno izvedeno. Pred tem je od leta 2020 do leta 2021 potekalo ustvarijo program, ki izriše zahtevano grafično podobo. Takšne na poskusni ravni. Izvedena so bila tri poskusna tekmovanja. naloge pogosto vključujejo večkratne ponovitve določenega Zadnje od poskusnih tekmovanj je beležilo prek 1000 zaporedja ukazov (Slika 1). udeležencev. Vsa tekmovanja so potekala v programskem jeziku Blockly na francoskem strežniku, podobnem sistemu Algoreja, ki omogoča izvedbo tekmovanja z avtomatskim preverjanjem pravilnosti rešitev [6]. Tekmovalne naloge oblikuje Programski svet tekmovanja. 2.1 Tretje poskusno tekmovanje Pišek Tretje poskusno tekmovanje je potekalo od 1. 2. 2021 do 12. 2. 2021 in je beležilo prek 1000 udeležencev. Tekmovanje je trajalo 35 min in je bilo izvedeno v sledečih tekmovalnih kategorijah:  4.–6. razred osnovne šole - začetniki Slika 1: Želvja grafika  4.–6. razred osnovne šole - napredni  7.–9. razred osnovne šole - začetniki Vhodno-izhodna naloga: tekmovalci sestavijo program, ki  7.–9. razred osnovne šole - napredni prebere vhodne podatke in ob upoštevanju njihovih značilnosti  srednja šola - začetniki izpiše ustrezno vrednost na izhodu (Slika ).  srednja šola - napredni [7]. 2.2 Naloge na tretjem poskusnem tekmovanju Pišek Naloge na tekmovanju Pišek se razlikujejo v programskih konceptih v rešitvah nalog, predstavitvenih oblikah nalog in otežitvah programskega okolja. To so skupine dejavnikov, ki jih bomo v nadaljevanju podrobneje predstavili. Posamezne dejavnike1 bolj natančno opisujemo s ciljem, da bi dobili globlji Slika 2: Vhodno-izhodna naloga 1 Dejavniki, opisne karakteristike nalog. Pozneje pri modeliranju s strojnim učenjem nastopajo kot spremenljivke. 419 Naloga na mreži: tekmovalci sestavijo program, ki premika lik po mreži in z njim opravlja zahtevana opravila. Lik se premika bodisi relativno glede na pozicijo (naprej, nazaj, levo, desno, okoli), bodisi absolutno (sever, jug, zahod, vzhod).  Mreža brez aktivnosti: tekmovalci sestavijo program, ki premika lik od začetnega do ciljnega polja (Slika ).  Mreža z aktivnostmi: tekmovalci sestavijo program, ki premika lik od začetnega do ciljnega polja in medtem na označenih poljih izvede zahtevano aktivnost npr. pobere predmet, se obrne za 90° itd. (Slika ).  Mreža s prostorsko razpršenimi aktivnostmi: tekmovalci sestavijo program, ki premika lik od Slika 5: Mreža s prostorsko razpršenimi aktivnostmi začetnega do ciljnega polja na način, da obišče vsa polja na mreži in med potjo na označenih poljih izvede zahtevano aktivnost npr. pobere predmet, se obrne za 90° itd. (slika 5).  Mreža s prepovedanimi polji: tekmovalci sestavijo program, ki premika lik od začetnega do ciljnega polja, a le po poljih, na katerih ni ovire. Oviro lahko predstavlja reka, ograja, cesta itd. (Slika ).  Mreža z vzorcem: tekmovalci na mreži prepoznajo vzorec in sestavijo program, ki premika lik od začetnega do končnega polja, skladno z razpoznanim vzorcem (Slika ). Slika 6: Mreža s prepovedanimi polji Slika 3: Mreža brez aktivnosti Slika 7: Mreža z vzorcem 2.2.3 Otežitve programskega okolja. Z modifikacijo nabora otežitev programskega okolja, ki sta ga opredelila M. Lokar in M. Mujkić [10] smo opisali značilnosti tekmovanja Pišek in za Slika 4: Mreža z aktivnosti potrebe naše raziskave, oblikovali sledeč nabor otežitev programskega okolja. Brez otežitev: naloga ne vsebuje omejenega števila delčkov, testov ali razširjenega nabora delčkov. Omejeno število delčkov: omejitev določa največje možno število porabljenih delčkov za rešitev problema. Omejitev števila delčkov tekmovalce spodbudi k ustvarjanju krajše in kognitivno zahtevnejše rešitve (Slika ). 420  7.–9. razred osnovne šole - napredni Vzorec je sestavlja vsega 1494 osnovnošolskih tekmovalcev, ki so tekmovali na tretjem poskusnem tekmovanju iz programiranja z delčki Pišek. 3.2 Obdelava podatkov 3.2.1 Indeks težavnosti nalog. Težavnost nalog smo določili z izračunom indeksa težavnosti. Indeks težavnosti nalog je Slika 8: Omejeno število delčkov definiran kot povprečen delež doseženih točk tekmovalcev pri posamezni nalogi. Indeks težavnosti zavzema vrednost med 0 in Prisotnost testov: omejitev preverja splošnost rešitve in 1. Zahtevnejša ko je naloga, nižji je indeks težavnosti [11]. zagotavlja, da program celostno reši problem. Naloga s testi je Naloga je zahtevna, če ima indeks manjši ali enak 0,33 in lahka, uspešno rešena takrat, ko program prestane vse teste (Slika ). če ima indeks večji ali enak 0,70. 3.2.2 Indeks diskriminativnosti nalog. Diskriminativnost nalog smo določili z izračunom indeksa diskriminativnosti. Indeks diskriminativnosti je definiran kot razlika med indeksom težavnosti naloge zgornje tretjine vzorca in indeksom težavnosti naloge spodnje tretjine vzorca, pri čemer je vzorec razdeljen na tretjine glede na končni dosežek tekmovalcev. Indeks diskriminativnosti pove, v kolikšni meri naloga ločuje med dosežki tekmovalcev zgornje in spodnje tretjine. Indeks diskriminativnosti zavzame vrednost med -1 in 1 in je pozitiven, če so tekmovalci zgornje tretjine uspešneje rešili nalogo kot tekmovalci spodnje tretjine ter negativen, če so tekmovalci spodnje tretjine uspešneje rešili nalogo kot tekmovalci zgornje tretjine. Vrednost indeksa okoli nič ponazarja, da so tekmovalci obeh tretjin približno enako dobro rešili nalogo. 3.2.3 Napovedni modeli. Moč vpliva predstavnostnih oblik Slika 9: Prisotnost testov nalog in otežitve programskega okolja na dosežke tekmovalcev smo izmerili z metodo strojnega učenja, naključni gozdovi. Z Razširjen nabor delčkov: vsaka od nalog vsebuje zbirko naključnimi gozdovi smo ustvarili več modelov in iz njih razbrali, delčkov, ki jo je možno uporabiti med reševanjem naloge. kateri dejavniki so imeli največji vpliv na dosežek tekmovalca na Naloge z razširjenim naborom delčkov poleg nujno potrebnih tekmovanju. V napovednih modelih smo za ciljno spremenljivko delčkov vsebujejo tudi odvečne delčke, kar lahko zmede uporablili dosežek učenca na tekmovanju, izražen v obliki deleža tekmovalca in vpliva na uspešnost njegovega reševanja naloge doseženih točk na tekmovanju. Za neodvisne napovedne (Slika ). spremenljivke smo uporabili dosežek učenca pri nalogah, ki se ujemajo v predstavitvenih oblikah nalog in otežitvah programskega okolja. Napovedne modele smo oblikovani za vse tekmovalne kategorije. Preverili smo uspešnost vsakega napovednega modela in z interpretacijo napovednih modelov odkrili, kateri dejavniki so na tretjem poskusnem tekmovanju Pišek najbolj pomembni oz. imajo največji vpliv na dosežek tekmovalca na tekmovanju Pišek. 4 REZULTATI Slika 10: Razširjen nabor delčkov 4.1 Analiza težavnost in diskriminativnost nalog 3 ANALIZA 4.1.1 Način analize podatkov. Vse spodaj opisane rezultate smo dobili z izračunom indeksa težavnosti in diskriminativnosti 3.1 Vzorec nalog v izbrani tekmovalni kategoriji. 4.1.2 Ugotovitve. V vseh tekmovalnih kategorijah je najlažja V raziskavi smo analizirali tekmovalne naloge, ki so bile prva naloga in najtežja zadnja naloga, kar je razvidno iz indeksov uporabljene na šolski ravni tretjega poskusnega tekmovanja težavnosti nalog (Tabela ). Pišek v šolskem letu 2020/21. Preučili smo dosežke V tekmovalni kategoriji od 4. do 6. razreda (začetniki), je tekmovalcev, ki so tekmovali v tekmovalnih kategorijah za najtežja naloga Skriti tartufi (5. naloga), ki je hkrati tudi najbolj osnovno šolo: diskriminativna (Tabela in Tabela 2). V ostalih tekmovalnih  4.–6. razred osnovne šole - začetniki kategorijah je najtežja naloga najmanj diskriminativna. Od tod  4.–6. razred osnovne šole - napredni lahko sklepamo, da so bile v preostalih tekmovalnih kategorijah  7.–9. razred osnovne šole - začetniki 421 5. naloge zelo težke za reševanje, saj jih je rešilo majhno število [12]. Menimo, da je zmožnost prepoznavanja in uporabe tekmovalcev (Tabela 2). programskih vzorcev povezana z izkušnjami posameznika z reševanjem tipičnih problemov, ki izzovejo uporabo ustreznega Tabela 1: Indeks težavnosti tekmovalnih nalog vzorca [13]. Analiza uporabe programskih vzorcev v rešitvah nalog in njihov vpliv na težavnost naloge je predmet nadaljnjih raziskav. Naloga Od 4. do 6. Od 4. do 6. Od 7. do 9. Od 7. do 9. razreda razreda razreda razreda Tabela 3: Indeks težavnosti nalog Neznani element in Skriti (začetniki) (napredni) (začetniki) (napredni) tartufi 1. naloga 0,969 0,747 0,870 0,533 2. naloga 0,945 0,399 0,829 0,476 3. naloga 0,856 0,399 0,602 0,286 Naloga Indeks težavnosti 4. naloga 0,869 0,283 0,554 0,381 Neznani element (3. naloga) 0,856 5. naloga 0,733 0,134 0,078 0,076 Skriti tartufi (5. naloga) 0,733 Tabela 2: Indeks diskriminativnosti tekmovalnih nalog Naloga Od 4. do 6. Od 4. do 6. Od 7. do 9. Od 7. do 9. razreda razreda razreda razreda (začetniki) (napredni) (začetniki) (napredni) 1. naloga 0,095 0,724 0,344 0,943 2. naloga 0,170 0,908 0,467 0,971 3. naloga 0,396 0,931 0,911 0,800 4. naloga 0,435 0,770 0,956 0,771 5. naloga 0,802 0,391 0,233 0,229 Slika 11: Naloga Neznani element Indeksa težavnosti naloge Ubbi dubbi (5. naloga) iz tekmovalne kategorije od 7. do 9. razreda (začetniki) in naloge Ježek pospravlja (5. naloga) iz tekmovalne kategorije od 7. do 9. razreda (napredni) sta zelo nizka, kar nakazuje na preveliko zahtevnost obeh nalog (Tabela ). Najbolje so bile zasnovane naloge v kategoriji od 4. do 6. razreda (napredni). Glede na indeks težavnosti je tekmovalna kategorija imela eno lahko nalogo, dve srednje zahtevni nalogi in eno težko nalogo (Tabela ). Vse ostale kategorije so imele preveč lahkih nalog. 4.2 Analiza programskih konceptov v rešitvah nalog Slika 12: Naloga skriti tartufi 4.2.1 Način analize podatkov. Spodaj navedene rezultate smo dobili z izračunom indeksa težavnosti nalog Nezani element 4.3 Analiza predstavitvenih oblik nalog in Skriti tartufi iz tekmovalne kategorije od 4. do 6. razreda 4.3.1 Način analize podatkov. Spodaj navedene rezultate (začetniki) in povezovanjem dobljenih podatkov s prisotnostjo in smo dobili z interpretacijo napovednih modelov, zgrajenih z razporeditvijo programskih konceptov v rešitvah obeh nalog. naključnimi gozdovi. Za ciljno spremenljivko smo uporabili 4.2.2 Ugotovitve. V tekmovalni kategoriji od 4. do 6. razreda dosežek učenca na tekmovanju in za neodvisne napovedne (napredni) sta prisotni tekmovalni nalogi Neznani element in spremenljivke dosežek učenca pri nalogah, ki se ujemajo v Skriti tartufi. Naloga Skriti tartufi ima nižji indeks težavnosti kot predstavitvenih oblikah nalog. naloga Neznani element, kar pomeni, da je bila slednja naloga 4.3.2 Ugotovitve. Na tekmovanju Pišek ima v tekmovalni tekmovalcem lažja za reševanje (Tabela ). kategoriji od 4. do 6. razreda (začetniki) dejavnik mreža z Nalogi v rešitvah vsebujeta enake programske koncepte: aktivnostmi večjo napovedno moč in posledično večji vpliv na zaporedje ukazov, pogojni stavek in končno zanko, pri čemer so dosežek učenca kot dejavnik mreža brez aktivnosti (Tabela ). programski koncepti v rešitvi naloge Neznani elementi (Slika 11) V tekmovalni kategoriji od 4. do 6. razreda (napredni) drugače razporejeni kot v rešitvi naloge Skriti tartufi (Slika 12). analiza dosežkov ni pokazala pomembnih rezultatov. Napovedni Na podlagi različnih indeksov težavnosti nalog in različne model je obema dejavnikoma (mreža z vzorcem in mreža s razporeditve enakih programskih konceptov v obeh nalogah, prepovedanimi polji) pripisal skoraj enako napovedno moč, iz lahko sklepamo, da imajo programski vzorci vpliv na uspešnost česar smo sklepali, da sta v preučevani tekmovalni kategoriji reševanja nalog, pri čemer so programski vzorci formalizirane imeli obe obliki nalog podoben vpliv na dosežek učencev rešitve oz. sklopi med seboj povezanih programskih konceptov, (Tabela ). ki jih lahko programer večkrat uporabi za reševanje problemov 422 V kategoriji od 7. do 9. razreda (začetniki) je bil vpliv oblik 4.5.2 Ugotovitve. V nobeni od tekmovalnih kategorij nismo nalog na dosežek učencev izrazitejši. Napovedni model je opazili, da bi dejavniki iz ene skupine (npr. predstavitvene oblike dejavnika želvja grafika in mreža z vzorcem označil kot nalog) izstopali pred dejavniki iz druge skupine (npr. otežitve najpomembnejši. Sledili sta jima mreža z aktivnostmi in vhod- programskega okolja). Od tod smo predpostavili, da imajo oblike izhod (Tabela ). nalog in otežitve programskega okolja približno enak vpliv na V tekmovalni kategoriji od 7. do 9. razreda (napredni) je dosežke učencev na tretjem poskusnem tekmovanju Pišek model največjo napovedno moč dodelil dejavniku mreža s (Tabela ). prostorsko razpršenimi aktivnosti, sledili sta ji želvja grafika in vhod-izhod (Tabela ). Tabela 5: Razporeditev dejavnikov iz skupine otežitve programskega okolja od najbolj pomembnega do najmanj Tabela 4: Razporeditev dejavnikov iz skupine pomembnega predstavitvene oblike nalog od najbolj pomembnega do najmanj pomembnega Od 4. do 6. Od 4. do 6. Od 7. do 9. Od 7. do 9. razreda razreda razreda razreda Od 4. do 6. Od 4. do 6. Od 7. do 9. Od 7. do 9. (začetniki) (napredni) (začetni) (napredni) razreda razreda razreda razreda Omejitev Prisotnost Omejitev Omejitev (začetniki) (napredni) (začetni) (napredni) števila testov števila števila Mreža z Mreža s Želvja Mreža s delčkov delčkov delčkov aktivnostmi prepovedanimi grafika prostorsko Brez otežitev Omejitev Brez otežitev Prisotnost polji razpršenimi števila testov aktivnostmi delčkov Mreža brez Mreža z Mreža z Vhod-izhod Prisotnost Razširjen Prisotnost Razširjen aktivnosti vzorcem vzorcem testov nabor delčkov testov nabor delčkov Mreža z Želvja grafika aktivnostmi Tabela 6: Razporeditev dejavnikov iz skupin predstavitvene Vhod-izhod oblike nalog in otežitve programskega okolja od najbolj pomembnega do najmanj pomembnega 4.4 Analiza otežitev programskega okolja Od 4. do 6. Od 4. do 6. Od 7. do 9. Od 7. do 9. 4.4.1 Način analize podatkov. Spodaj navedene rezultate razreda razreda razreda razreda smo dobili z interpretacijo napovednih modelov, zgrajenih z (začetniki) (napredni) (začetniki) (napredni) naključnimi gozdovi. Za ciljno spremenljivko smo uporabili Mreža z Prisotnost Omejitev Omejitev dosežek učenca na tekmovanju in za neodvisne napovedne aktivnostmi testov števila števila spremenljivke dosežek učenca pri nalogah, ki se ujemajo v delčkov delčkov otežitvah programskega okolja. Omejitev Omejitev števila Mreža z Prisotnost 4.4.2 Ugotovitve. Na tekmovanju Pišek imata v tekmovalni števila delčkov aktivnostmi testov kategoriji od 4. do 6. razreda (začetniki) dejavnika omejitev delčkov števila delčkov in brez otežitev največji vpliv na dosežke Mreža brez Mreža z Želvja Razširjen tekmovalcev (Tabela ). aktivnosti vzorcem grafika nabor delčkov Prisotnost Mreža s Mreža z Mreža s V tekmovalni kategoriji od 4. do 6. razreda (napredni) imata testov prepovedanimi vzorcem prostorsko največji vpliv dejavnika prisotnost testov in omejeno število polji razpršenimi delčkov. V preučevani kategoriji je imel najmanjši vpliv na aktivnostmi dosežke učencev dejavnik razširjen nabor delčkov (Tabela ). Razširjen nabor Vhod-izhod Želvja grafika V kategoriji od 7. do 9. razreda (začetniki) sta imela največji delčkov vpliv na dosežke tekmovalcev dejavnika omejeno število Prisotnost Vhod-izhod delčkov in brez otežitev, sledil jima je dejavnik prisotnost testov testov (Tabela ). V kategoriji od 7. do 9. razreda (napredni) so imeli na dosežke učencev največji vpliv dejavniki omejeno število delčkov in 5 ZAKLJUČEK prisotnost testov. Manjši vpliv je imel dejavnik razširjen nabor V magistrskem delu smo raziskovali, katere naloge, prisotne na delčkov (Tabela ). tretjem poskusnem tekmovanju Pišek, so tekmovalci najbolje reševali. Zanimal nas je vpliv programskih konceptov, 4.5 Analiza predstavitvenih oblik nalog in predstavitvenih oblik nalog in otežitev programskega okolja na otežitev programskega okolja dosežke učencev na tekmovanju. 4.5.1 Način analize podatkov. Spodaj navedene rezultate Ugotovili smo, katere naloge so bile znotraj tekmovalnih smo dobili z interpretacijo napovednih modelov, zgrajenih z kategorij najtežje in najbolj diskriminativne ter katere naključnimi gozdovi. Za ciljno spremenljivko smo uporabili predstavnostne oblike nalog in otežitve programskega okolja so dosežek učenca na tekmovanju in za neodvisne napovedne imele največji vpliv na dosežke tekmovalcev. Z analizo primerov spremenljivke dosežek učenca pri nalogah, ki se ujemajo v smo spoznali, da imata lahko dve nalogi z enakimi programskimi predstavitvenih oblikah nalog in otežitveh programskega okolja. koncepti, ki so znotraj prve naloge drugače razporejeni kot znotraj druge naloge, različna indeksa težavnosti. Na podlagi 423 tega smo sklepali, da imajo programski vzorci vpliv na uspešnost ZAHVALA reševanja nalog. Hvala članom programskega sveta Pišek za omogočen dostop do Modeli, ki smo jih zgradili s statistično analizo in strojnim rezultatov tretjega poskusnega tekmovanja v programiranju z učenjem, so nam zadovoljivo pojasnili vpliv izbranih dejavnikov delčki Pišek. na dosežek tekmovalca na tretjem poskusnem tekmovanju Pišek znotraj tekmovalnih kategorij. 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Competition in Information Technology – learning in an v vpliv posameznih dejavnikov na dosežek tekmovalca in attractive way. Informatics in Education, 5 (1), 37 – 46. opazovanje odnosov med dejavniki. https://www.researchgate.net/publication/220396214_Information_Technol ogy_Contests_Introduction_to_Computer_Science_in_an_Attractive_Way [5] ACM Tekmovanja. (b. d.). https://tekmovanja.acm.si/ [6] Lokar, M. (2020). Pišek – Programming with Blocks Competition A new 6 RAZPRAVA Slovenian Programming Competition. Kori, K., Laanpere, M. (ur.) Proceedings of the International Conference on Informatics in School: Z raziskavo smo dobili boljši vpogled v vpliv programskih Situation, Evaluation and Perspectives: ISSEP 2020 (zv. 2755, str. 1 – 12). CEUR-WS. http://ceur-ws.org/Vol- 2755/ konceptov, predstavitvenih oblik nalog in otežitev programskega [7] ACM Tekmovanja – Pišek. (b. d.). https://tekmovanja.acm.si/?q=pisek okolja na dosežke učencev. V nadaljevanju bi bilo smiselno [8] Kong, S. C. (2019). Components and methods of evaluating computational analizirati vpliv še drugih dejavnikov kot so: thinking for fostering creative problem-solvers in senior primary school education. V S. C. Kong (ur.) in H. Abelson (ur.), Computational Thinking - značilnosti tekmovalcev (starost, predznanje, zanimanje Education (str. 119 – 141). Singapur: Springer. za računalništvo), https://link.springer.com/chapter/10.1007/978-981-13-6528-7_8 [9] Brennan, K. in Resnick, M. (2012). New frameworks for studying and - značilnosti nalog (število besed v nalogi, kompleksnost assessing the development of computational thinking. AERA. jezika, kompleksnost grafičnih elementov) ipd. http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_AERA2012_C Z analizo raznolikih dejavnikov bi dobili še boljši vpogled v T.pdf [10] Lokar, M. in Mujkić, M. (2021). Računalniško tekmovanje Pišek – oblika tekmovalne naloge. vzpodbujanja učenja programiranja za vse. Uporabna informatika 29 (1) 3 – Smiselno bi bilo izvesti tudi kvalitativno raziskavo, v kateri 15. https://uporabna-informatika.si/index.php/ui/issue/view/2021-01/2021- 01 bi uporabili metodo glasnega razmišljanja pri tekmovalcih, ki so [11] Cankar, G., Hauptman, A., Urank, M. in Zupanc, D. (2010). Priročnik za različno uspešno reševali srednje težke naloge. Z njo bi opazovali uporabo » Orodja za analizo izkazanega znanja ob zaključku srednje šole«. Državni izpitni center. način razmišljanja tekmovalcev in odkrili morebitne napačne [12] Amanullah, K. in Bell, T. (2019). Analysis of Progression of Scratch Users miselne predstave, ki se pojavijo med reševanjem nalog. based ontheir Use of Elementary Patterns. 14th International Conference on Predvidevamo, da smo z do sedaj pridobljenimi rezultati Computer Science & Education: ICCSE 2019, (str. 573–578). https://ieeexplore.ieee.org/document/8845495 članom Programskega sveta tekmovanja Pišek omogočili oboljši [13] Zapušek, M. (2022). Domenska ontologija programskih vzorcev pri vpogled v tekmovalne naloge in posledično lažjo sestavo uvodnem programiranju [doktorska disertacija]. Univerza v Ljubljani, Pedagoška fakulteta. nadaljnjih tekmovanj Pišek. V bodoče upamo, da bodo rezultati [14] David Kosiur. 2001. Understanding Policy-Based Networking (2nd. ed.). analize v pomoč sestavljavcem učnih načrtov pri izbiri Wiley, New York, NY kognitivno ustrezno zahtevnih vsebin za obvezni predmet računalništva. Obenem si želimo, da bodo učitelji na podlagi pojasnjenih rezultatov pridobili koristne informacije, ki jim bodo omogočile kakovostnejše oblikovanje učnih ur. 424 Učencem prijazno poučevanje na daljavo Student-Friendly Distance Learning Barbara Jevšnik I. OŠ Žalec Žalec, Slovenija barbarajevsnik@gmail.com POVZETEK knowledge, and to keep in touch with their peers and school. A whole range of products, explanations, and examples of good Med poučevanjem na daljavo je bil učitelj primoran iskati nove practice have been created and they can be used by teachers metode in oblike dela, s katerimi bi popestril pouk ter podal without difficulty in both traditional and remote classes. kakovostno znanje učencem. Pri tem je moral najti ustrezno izobraževalno tehnologijo, ki je bila učencem v pomoč pri KEYWORDS doseganju vsebin in ciljev v vzgojno-izobraževalnem procesu. To od učitelja zahteva nenehen razvoj in raziskovanje tega Distance teaching, Information and Communication področja. Preko različnih vsebin smo izvajali učenje ter Technology, digital literacy samostojno delo s pomočjo PowerPointa, Geniallya, Padleta, Vibra, Xooltima, Zooma ter Worda. Uporaba zgoraj omenjenih 1 UVOD računalniških in spletnih aplikacij je bila učencem v pomoč pri razumevanju snovi ter pridobivanju novih znanj. Hkrati pa jim je Zadnji dve leti sta prinesli veliko sprememb, še posebno v omogočala večkratno razlago nove snovi in utrjevanje le-te. šolstvu, kjer se je prevetril celotni sistem izobraževanja, ki je Uporabljene aplikacije so učencem omogočale, da so bili v času potekalo bodisi v šoli, doma ali hibridno. Od učitelja se je izobraževanja na daljavo aktivni, da so pridobili in utrdili nova vseskozi pričakovalo, da je inovativen, prilagodljiv, predvsem znanja ter da niso izgubili stika s sovrstniki ter šolo. Nastala je pa, da venomer išče rešitve, kako izpeljati pouk na daljavo, da bo cela paleta izdelkov, razlag, primerov dobrih praks, ki jih učitelji učencem predal čim več znanja. Čeprav danes živimo v digitalni lahko brez večjih težav uporabimo pri klasičnem pouku kot pri dobi, kjer se na vsakem koraku srečujemo z različnimi oblikami pouku na daljavo. tehnologije, je digitalno pismenih le okoli 50 % Slovencev, povprečje v EU je 53 % [9]. Po podatkih Statističnega urada KLJUČNE BESEDE Slovenije ima dostop do interneta kar 93 % gospodinjstev v Sloveniji, kar je za nekaj odstotkov več v primerjavi z letom pred Poučevanje na daljavo, IKT tehnologija, digitalna pismenost epidemijo. ABSTRACT Zadnji dve leti je opazen napredek v digitalni pismenosti med učenci. Le-ti so v zadnjih dveh letih pridobili velik spekter During distance teaching, the teacher was forced to look for new tehnološkega znanja na področju digitalne pismenosti. methods and forms of work, which would enrich the lessons and Večja digitalna pismenost med učenci pa je učitelju transfer quality knowledge to the students. In doing so, he had to omogočila pestrejši, inovativnejši in zanimivejši izbor spletnih find the appropriate educational technology that could help programov tako pri pouku na daljavo kot v šoli. students to grasp the contents and achieve the goals in the educational process. Therefore, the teacher is required to constantly develop and research in the field of distance learning. 2 METODE DELA Through various contents, we carried out group and individual learning with the help of PowerPoint, Genially, Padlet, Viber, Delo je potekalo v domačem okolju. Zaradi varstva osebnih Xooltime, Zoom and Word. The use of the above-mentioned podatkov bomo v prispevku uporabljali samo moško obliko computer and online applications helped the students to učenca. understand the material and acquire new knowledge. At the same Če smo se prvo leto šolanja na daljavo učitelji najbolj time, it enabled them to listen or watch the explanation for the ukvarjali s problemom, kako vešči so učenci z računalnikom ter new learning topic more times and consolidate it. The above- kakšno je njihovo poznavanje osnovnih računalniških programov, mentioned applications enabled the students to be active during je delo v drugem letu šolanja na daljavo temeljilo na tem, da the distance education, to acquire and consolidate new učencem ponudimo čim bolj kakovosten pouk, s katerim bi učenci pridobili kvalitetno znanje. Pri tem so si lahko učitelji Permission to make digital or hard copies of part or all of this work for personal or sami izbirali spletno aplikacijo za avdio in video komunikacijo, classroom use is granted without fee provided that copies are not made or distributed prav tako so si sami urejali spletne učilnice. Na naši šoli 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 posluževali ZOOM-a ter spletne učilnice XOOLTIME, v okviru be honored. For all other uses, contact the owner/author(s). easistenta. Kljub temu, da imajo v razredu skoraj vsi petošolci Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia pametne telefone ter da vsakodnevno dostopajo do spleta, bodisi © 2022 Copyright held by the owner/author(s). 425 zaradi komunikacije s sošolci ali pa zaradi igranja igric, so imeli čim več trebušnjakov v 1 min). Vsi ti izzivi so bili namenjeni na začetku kar nekaj težav z vpisovanjem v spletno učilnico in sami popestritvi pouka ter zabavi. pregledovanjem gradiv, zato smo prvi dostop opravili skupaj v Pri pouku na daljavo smo strmeli, da se učenci čim več gibajo, šoli. V okviru aktiva petošolcev smo vsaka dva dni naložili zato smo ob petkih učence zadolžile, da opravijo daljši sprehod domačo nalogo v spletno učilnico, kar se nam je kasneje, v času ali se odpravijo na bližnji hrib. pouka na daljavo, tudi obrestovalo. Znotraj aktiva petošolcev smo strmeli k enotnemu sistemu dela, imeli smo enak urnik, enak čas videokonferenc, enako zadolžitev učencev ter enotno podajanje znanja ter ocenjevanja. Poleg rednega pouka smo učencem ponudile tudi dodatni in dopolnilni pouk, poročanje knjig za bralno značko ter svetovalne ure, ki so bile namenjene učencem, ki snovi niso najbolje razumeli ter so rabili dodatno pomoč. Skušali smo pouk na daljavo organizirati tako, da je postal rutina, saj smo s tem močno zmanjšali vlogo staršev, učenci pa so postali samostojnejši in bolj vešči ravnanja z različnimi aplikacijami. Pri podajanju znanja smo se posluževali različnih spletnih Slika 2. Genially aplikacij, kot so Zoom, Xooltime, Padlet, PowerPoint, X- mind, Genially in Youtube. Sledilo je samostojno delo s pomočjo IKT v domačem okolju. Primer slike 1 prikazuje tedensko zadolžitev učencev na daljavo. Slika 3. Uporaba programa Padlet Slika 1. Urnik dela Kot je razvidno iz slike zgoraj smo s poukom pričeli vsak dan ob 8.00. Učenci so imeli na dan dve videokonferenci, kjer je Slika 4. Športna zadolžitev učitelj podajal snov preko ZOOM aplikacije. Razlaga snovi je potekala s pomočjo drsnic, posnetkov ali frontalno s pomočjo bele table. Pri tem so učenci delali individualno, v parih ali 3 REZULTATI skupinah s pomočjo Breakout Rooms. Poleg videokonferenc so Pomembno se nam zdi, da so bili v času šolanja na daljavo bile pod tabelo z rumeno bravo označene tudi zadolžitve učencev. aktivni vsi učenci, tudi učenci tujci. Na naši šoli imamo že kar Kadar je podajanje in razlaga snovi potekala brez četrtino učencev tujcev v posameznem oddelku. Učenci so videokonferenc, smo se posluževali predvsem razlage snovi s podajali svoje šolske zadolžitve na različne načine, s pomočjo pomočjo Genially, PowerPointa ter objavljanjem posnetkov na različnih spletnih programov. Youtube kanalu. Največkrat so uporabili Word, PowerPoint ali pa so izdelek Primer slike 2 prikazuje razlago snovi s pomočjo programa bodisi slikali ali posneli ter ga poslali v spletno učilnico. Kadar Genially. je delo doma potekalo praktično (npr. naravoslovni poskusi), so Za uvodno motivacijo pri pouku smo uporabljali tudi rezultate predstavi na videokonferenci. program Padlet. Učenci tujci so se pri tem največkrat posluževali aplikacije Primer slike 3 prikazuje učenčeve asociacije na besedo Viber, naložene na telefon, saj največkrat niso imeli ne Eskim, pri obravnavi eskimske ljudske pravljice To ti je sreča. računalnika ali tablice. V nekaterih primerih so do spleta Poleg rednega pouka smo imeli še tri izzive, jezikovni izziv dostopali s pomočjo mobilnih podatkov. (npr. najdi čim več asociacij na besedo šola), matematični izziv (utrjevanje računskih operacij) ter gibalni izziv (npr. kdo naredi 426 Podano snov smo preverjali s pomočjo spletnih kvizov v 4 DISKUSIJA spletni učilnici Xooltime predvsem pri slovenščini, družbi in Vsi zgoraj omenjeni programi, aplikacije, omogočajo, da učenci naravoslovju in tehniki. razvijajo digitalno pismenosti, ki jim omogoča lažje doseganje želenih ciljev. Tako kot učitelji so tudi učenci v sam pouk na daljavo vložili veliko truda ter iznajdljivosti. Nekateri že na začetku samostojno, drugi ob pomoči odraslih. Pri tem je nastala res cela paleta izdelkov, razlag, primerov dobrih praks, ki jih brez večjih težav uporabimo pri pouku. Pomembno je, 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. S tem poskrbi tako za pestrost pouka kot tudi lastno promocijo svojega načina podajanja znanja. Pri tem je zelo pomembno, da dobro presodi, kateri programi so primerni za mlajše učence ter jim v veliki meri olajšajo delo. Učitelj se mora nenehno izobraževati, raziskovati ter iskati nove Slika 5. Primer spletnega kviza aplikacije, s katerimi bi lahko izboljšal svoje podajanje znanja. Ti kvizi so nam služili, da smo ob vsakem zaključku poglavja 5 ZAKLJUČKI ugotovili napredek učenca. Kvizi so bili pri učencih dobro sprejeti, saj od njih niso zahtevali veliko pisanja. Še vedno velja, da je znanje velika vrednota in moč. Učenci bodo Učenci so imeli najraje praktično delo. Pri tem so bili aktivni lahko uporabljene aplikacije in programe uporabljali in vsi učenci, tudi učenci tujci. Pri tem v ospredju niso bile njihove nadgrajevali tudi v prihodnje, bodisi pri pouku kot v vsakdanjem težave z jezikom, zato so bili zelo motivirani za delo in so se zelo življenju. izkazali pri sami izdelavi končnega izdelka in pri tem pokazali Prav v času šolanja na daljavo, karanten, smo zelo dobro veliko mero ustvarjalnosti. občutili, kako je digitalna pismenost pomembna tako za učitelja kot za učence. Spoznali smo, da klasičen pouk ni več dovolj, da je potrebno digitalno znanje, ki so ga učenci v teh letih pridobili nadgrajevati in razvijati, saj jim bo omogočil lažje premagovanje ovir. REFERENCE [1] Zupanc Grom, R, Slivar, B., Holcar Brunauer, A. in Rojc, J. (2022). Smernice za izvajanje izobraževanja na daljavo za vzgojno-izobraževalne zavode na področju osnovnega in srednjega šolstva. Ljubljana: ZRSŠ. [2] www.zrss.si/pdf/smernice_izobrazevanje_na_daljavo.pdf [3] Javrh, P., Možina, E., Bider, K., Kragelj, K., Volčjak, D., Sepaher, G., Gjerek, L., Matavž, H., Rejec, P., Babič Ivaniš, N. in Brecelj, V. (2018). Digitalna pismenost. Na poti do življenjske uspešnosti. Ljubljana: Andragoški center Slovenije. [4] https://pismenost.acs.si/wp-content/uploads/2018/09/Digitalna-pismenost-e- verzija.pdf. [5] Jurišič, M. (1999). Samopodoba šolskega otroka. Ljubljana: Pedagoška fakulteta. Slika 6. Praktični izdelki [6] Marentič Požarnik, B. , Magajna, L. , Peklaj, C. (1995). Izziv raznolikosti: stili spoznavanja, učenja, mišljenja. Psihologija učenja in pouka. Nova Vsem učencem smo s pomočjo odprtih možnosti ponudili Gorica: Educa. [7] Sonck, N., Livingstone, S., Kuiper, E., in de Haan, J. (2011). Digitalna različne načine predstavitve, kjer so lahko izkazali svoje znanje, pismenost in veščine varne rabe interneta . pridobili nove spretnosti in izkušnje. Tako, so vsi učenci, ne DOI=https://safe.si/sites/default/files/digitalskillsreport- eukidsonlineprevod_0.pdf. glede na učne ali govorne težave izdelali svoj končni izdelek. [8] Statistični urad Republike Slovenije [SURS]. 2018. Osnovnošolsko Vso gradivo, ki smo ga v teh dveh letih izdelali, nam je v izobraževanje. DOI=Uporaba IKT v gospodinjstvih (stat.si) letošnjem šolskem letu pri hibridnem načinu poučevanja zelo [9] Železnik, R. (2018). Uvajanje digitalnih tehnologij in spoznavanje računalniške pismenosti pri osnovnošolskih otrocih v Sloveniji. Magistrsko koristilo ter nam v veliki meri olajšalo delo. Učenci se zaradi delo. Ljubljana: Pedagoška fakulteta. bolezni velikokrat niso mogli priključiti k rednemu pouku. Tako [10] Novi ukrepi za spodbujanje ključnih kompetenc in digitalnih spretnosti ter evropske razsežnosti izobraževanja. (2018) EU. IP/18/102. zadolžitve kot samo razlago so imeli naloženo v spletni učilnici, DOI=https://ec.europa.eu/commission/presscorner/detail/sl/IP_18_102 kjer so jo opravili kasneje. Še vedno se poslužujemo preverjanju [11] Žontar, R. (2022). Following the path of digitalization in Slovenia and znanja s pomočjo spletnih kvizov, saj se nam zdi pomembno, da Europe: Are you digitally literate? Where does Slovenia rank in EU? DOI=Following the path of digitalization in Slovenia and Europe: Are you so učenci v razredu digitalno spretni. digitally literate? Where does Slovenia rank in the EU? (inak.si) 427 Kako narediti virtualno učno pot? How To Make a Virtual Educational Nature Trail? Vesna Jurač Osnovna šola Antona Martina Slomška Vrhnika Vrhnika, Slovenija vesna.jurac@gmail.com POVZETEK KEYWORDS Živimo v času digitalizacije, ko tudi vzgojno-izobraževalno delo Virtual educational trail, municipality of Vrhnika, ThingLink postaja vse bolj digitalizirano. K temu pa nas je nedaleč nazaj dodatno spodbudilo tudi šolanje na daljavo. Da bi bil pouk čim bolj zanimiv, učitelji in učenci posegamo tudi po različnih 1 UVOD digitalnih orodjih in programih. Na osnovni šoli Antona Martina Pri vzgojno-izobraževalnem delu se vse pogosteje spogledujemo Slomška Vrhnika smo se lotili projekta izdelave učne poti, s z digitalizacijo. K temu nas je v preteklem obdobju spodbudilo katero smo ob dvajsetletnici naše šole želeli širši javnosti tudi šolanje na daljavo. Onemogočen je bil neposreden kontakt predstavili naravne in kulturne značilnosti naše domače občine, učiteljev in učencev. Vzgojno-izobraževalno se je tako rekoč čez občine Vrhnika. Pri projektu so sodelovali učenci od šestega do noč prestavilo na splet. Pojavila se je potreba po sorazmerno devetega razreda in njihovi mentorji. V prispevku bomo hitrih prilagoditvah pouka, ki je vključeval informacijsko predstavili, kako smo se lotili omenjenega projekta, na kakšne komunikacijsko tehnologijo ter računalniška orodja in programe, težave smo pri tem naleteli, in kako smo jih rešili. Našo učno pot s katerimi si lahko pomagamo pri takšnem načinu dela. smo nato pretvorili v virtualno obliko s pomočjo brezplačnega Na osnovni šoli Antona Martina Slomška Vrhnika smo si ob spletnega orodja za izdelavo interaktivnih predstavitev dvajsetletnici naše šole zastavili cilj izdelati učno pot v fizični ThingLink. V nadaljevanju bomo predstavili tudi korake obliki, s katero bi širši javnosti predstavili naravne in kulturne izdelave omenjene virtualne učne poti ter končni rezultat našega značilnosti občine Vrhnika. Zamislili smo si, da jo uredimo v dosedanjega dela, ki pa ga želimo v prihodnje še nadgraditi. neposredni okolici naše šole, v šolskem arboretumu. Naše načrte pa je sredi dela prekrižalo šolanje na daljavo. Ta težava je nato KLJUČNE BESEDE postala naš izziv. Da bi naša učna pot vendarle ugledala luč sveta, Virtualna učna pot, občina Vrhnika, ThingLink smo se odločili, da jo pretvorimo v virtualno obliko in jo tako približamo še večjemu krogu ljudi. ABSTRACT V prispevku predstavljamo, kako smo se lotili projekta We are living in a digital era when educational work is becoming izdelave učne poti, korake izdelave naše učne poti v brezplačnem increasingly digitalised as well. Not long ago, our society was spletnem orodju za izdelavo interaktivnih predstavitev encouraged to digitalize by the use of distance learning. In order TrhingLink in končni rezultat našega dela. to make lessons as interesting as possible, teachers and students are turning to various digital tools and programmes. At the Anton Martin Slomšek Vrhnika Primary School, we have taken on a 2 PROJEKT IZDELAVE UČNE POTI project to create an educational trail to present to the general Na Osnovni šoli Antona Martina Slomška Vrhnika smo se že dlje public on the occasion of the 20th anniversary of our school the časa poigravali z zamislijo, da bi uredili svojo učno pot. natural geographic and socio-geographic features of Vrhnika Obogatitev praznovanja dvajsetletnice naše šole na takšen način municipality. The project involved pupils from the sixth to the se nam je zdela odlična priložnost, da svojo zamisel uresničimo. ninth grade, and their tutors. In this article, we are presenting the Občina Vrhnika, kjer se nahaja naša šola, leži na stiku project start, the problems we encountered, and how these have Ljubljanske kotline in kraškega sveta in tukaj je veliko naravnih been solved. In the end, we converted our educational trail into a znamenitosti. Prav tako se naša občina ponaša s številnimi virtual form by using ThingLink, the free computer software. In znanimi osebnostmi, prireditvami, arhitekturnimi posebnostmi in addition, we present the steps in creating the virtual educational drugimi kulturnimi znamenitostmi. Vse to je botrovalo k trail, and the final results of our work so far, which we hope to odločitvi, da bomo z našo učno potjo predstavili in promovirali expand in the future. prav naravne in kulturne znamenitosti domače občine. Izdelava te učne poti je obsežnejši projekt, kamor smo Permission to make digital or hard copies of part or all of this work for personal or vključili vse učence od šestega do devetega razreda in njihove 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 mentorje, povezali pa smo se tudi z ostalimi prebivalci naše citation on the first page. Copyrights for third-party components of this work must občine. Tako je to postal eden od dvajsetih projektov, s katerim be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia smo obeležili dvajsetletnico naše šole. © 2022 Copyright held by the owner/author(s). 428 Omenjeno učno pot smo si sprva zamislili kot fizično učno Delo znotraj skupin je potekalo samostojno. Učenci so si sami pot, ki bo speljana v neposredni okolici naše šole, v šolskem izbrali metode dela (študij virov in literature, terensko delo, arboretumu. V mislih smo imeli izdelavo dvajsetih učnih tabel, anketa, intervju ipd.), s katerimi so dobili zahtevane podatke, ki v besedi in sliki prikazujejo naravne in kulturne znamenitosti mentorji pa so jim pri tem svetovali in jih usmerjali. našega domačega kraja z okolico. Učenci so plakate nato opremili s povzetki svojih raziskav in Naš prvotni načrt pa nam je prekrižalo širjenje virusa slikovnim gradivom. Na koncu je vsaka izmed skupin svoj plakat Covid-19 in uvedba omejitvenih ukrepov. Ravno v času, ko smo še predstavila, vse predstavitve pa smo tudi posneli in zbrali vse podatke in izdelali plakate kot osnutke za izdelavo dokumentirali. učnih tabel, se je pričelo izobraževanje na daljavo, ki ga Unesco [1] opredeljuje kot vzgojno-izobraževalni proces in sistem, v katerem pomemben delež pouka izvaja nekdo ali nekaj, ki je 4 PRETVORBA V VIRTUALNO OBLIKO časovno in prostorsko odmaknjeno od učenca. Zadnji korak izdelave zamišljene učne poti je bil njena pretvorba V našem prostoru je bila uporaba tehnologije za namene v virtualno obliko. Pri pridobivanju podatkov, fotografiranju in poučevanja do prvega vala epidemije raziskovana predvsem kot oblikovanju besedil je bilo v ospredju samostojno delo učencev, del pouka v živo [2]. Zato smo morali razmisliti o možnosti, kako pri pretvorbi v virtualno obliko pa so na pomoč priskočili bi učno pot vendarle lahko končali v novih okoliščinah. To je mentorji. postalo naš izziv. Odločili smo se, da jo pretvorimo v virtualno Z našo virtualno učno potjo smo uporabnikom želeli ponuditi obliko. V skladu s tem smo jo naslovili Virtualna učna pot virtualni sprehod po neposredni okolici in delno tudi po naravnih in kulturnih znamenitosti občine Vrhnika. notranjosti naše šole. Odločili smo se, da si pri tem pomagamo s 360-stopinskimi posnetki šole in njene okolice. Da bi se izognili težavam z avtorstvom, smo za slikovni del učnih tabel izbrali 3 OD IDEJE DO IZVEDBE izključno avtorske fotografije, ki so nastale na terenskem delu Ker smo s pomočjo naše učne poti želeli predstaviti naravne in oziroma so jih prispevali učitelji in učenci. kulturne znamenitosti občine Vrhnika, smo se najprej lotili Po posvetovanju s šolskim računalničarjem smo se odločili, raziskovanja naše naravne in kulturne dediščine. Raziskali smo da našo virtualno učno pot oblikujemo v brezplačnem spletnem dvajset različnih tem: barje, kras, Ljubljanico, razgledne in orodju za izdelavo interaktivnih predstavitev ThingLink [3], ki je izletniške točke, stare obrti in znanja, prazgodovinsko Vrhniko, relativno enostaven za uporabo, končni rezultat pa ustreza našim legende in zgodbe, kulinariko, javne in kultune ustanove, predhodnim predstavam o virtualni učni poti. Prednost tega sakrakne objekte, arhitekturne posebnosti, spominska obeležja, orodja je tudi, da je izdelano virtualno učno pot možno v vsakem književnike, slikarje, gospodarstvo, prireditve, šport, šolstvo na trenutku spremeniti oziroma nadgraditi. Vrhniki in Osnovo šolo Antona Martina Slomška. Po oblikovanju uporabniškega računa je bilo v ThingLink Delo je potekalo v dvajsetih različnih skupinah in vsaka od najprej potrebno uvoziti 360-stopinjske posnetke notranjosti in skupin je raziskovala eno od naštetih tem. Cilj vsake skupine je okolice naše šole, ki smo jih izdelali s pomočjo šolske kamere bil oblikovati plakat (Slika 1), na katerem bi z besedo in sliko (Slika 2). Posnetke smo naredili na več šolskih lokacijah z predstavili svojo raziskovalno temo. namenom, da bi uporabniki o njih dobili čim boljšo predstavo. Slika 2: Uvoz 360-stopinjskih posnetkov v spletno orodje ThingLink Slika 1: Primer plakata Izbrali smo najboljše posnetke, jih zložili po vrsti in med Nastali plakati pa bi služili kot osnutki za oblikovanje njimi uredili možne prehode tako, da smo nanje iz podanega dvajsetih informativnih tablel za opremo naše učne poti. nabora ikon v ThingLinku namestili izbrane ikone s puščicami Navodila so učenci in mentorji dobili že vnaprej, tako da so (Slika 3). Ob kliku na posamezno ikono s puščico je tako možen se lahko predhodno pripravili in dogovorili, kako si bodo sprehod med posameznimi 360-stopinjskimi posnetki. Na razdelili delo, na kakšen način bodo raziskovali svojo temo ipd. posnetke smo namestili tudi ikone, preko katerih uporabniki 429 dostopajo do predstavitev posameznih predstavljenih vsebin. V vnaprej podane predloge smo v za to določena mesta Vsak 360-stopinjski posnetek smo opremili z več ikonami, pri vstavili besedilo in fotografije (Slika 5). tem pa se poskušali izogniti prenasičenosti in pazili na Ko smo vnesli vse fotografije in besedilo, je bilo potrebno preglednost. urediti še dostop do izdelane virtualne učne poti. Na šolski spletni Osnovne šola Antona Martina Slomška Vrhnika [4] smo nato objavili še spletno povezavo [5], s pomočjo katere lahko dostopamo do nje. 5 REZULTATI Virtualna učna pot naravnih in kulturnih znamenitosti občine Vrhnika je projekt učencev in učiteljev Osnovne šola Antona Martina Slomška Vrhnika, ki smo ga uresničili ob praznovanju dvajsetletnice naše šole. S tem, ko smo prvotno načrtovano fizično obliko naše učne poti spremenili v virtualno obliko, lahko do nje v vsakem trenutku dostopa še večji krog ljudi kot bi lahko do prvotno mišljene fizične postavitve. To pa je še ena od Slika 3: Naslovna stran Virtualne učne poti naravnih in prednosti, ki jih ta učna pot ima. Je tudi relativno enostavna za kulturnih znamenitosti občine Vrhnika uporabo, saj se lahko s preprostim klikom na posamezne ikone prosto sprehajamo med 360-stopinjskimi posnetki notranjosti šole in njene okolice ter si ogledamo predstavljene vsebine. Učenci so v veliki meri z zanimanjem sodelovali pri izdelavi naše učne poti. Seznanjanja z naravnimi in kulturnimi znamenitostmi svoje domače občine so se lotili samostojno, učitelji pa so jim pri tem nudili podporo in nasvete. Kot prednost takšnega dela so učenci izpostavili samostojno delo, kjer so imeli proste roke glede izbire metod in načinov dela pri pridobivanju podatkov in oblikovanju osnutkov za učne table. Pozitivno je tudi, da so sodelovali z drugimi, se med seboj povezovali, iskali skupne rešitve, logično razmišljali, bili iznajdljivi in ustvarjalni. Več podpore učiteljev pa so rabili pri pretvorbi učne poti v virtualno obliko. Slika 4: Urejanje virtualne učne poti 6 ZAKLJUČEK Besedilo na plakatih, ki je bilo pretežno napisano na roko, Virtualna učna pot naravnih in kulturnih znamenitosti Občine smo pretipkali in uredili s pomočjo programa Microsoft Word. Vrhnike je izdelana, povezava do nje pa objavljena in prosto Sledil je jezikovni pregled. Nato smo besedilo uvozili na dostopna na spletni strani Osnovne šole Antona Martina Slomška ustrezno mesto na virtualnih učnih tablah. Dodali smo tudi Vrhnika. Po omenjeni učni poti se lahko virtualno sprehodi širši ustrezne avtorske fotografije. krog ljudi, primerna pa je tudi za uporabo v šolskem vsakdanu Pri oblikovanju virtualnih učnih tabel v orodju TrhingLink (npr. uporaba vsebin za različne predstavitve pri pouku, smo lahko izbirali med več različnimi predlogami. Izbrali smo utrjevanje znanja o domačem kraju in okolici, umestitev v dneve tiste, ki so najbolj ustrezale predstavljenim tematikam (Slika 4). dejavnosti, šolske prireditve ipd.). Izdelana je v prostodostopnem spletnem orodju za izdelavo interaktivnih predstavitev ThingLink, ki je relativno enostavno za uporabo in omogoča tudi spremembe in njeno nadgradnjo. Tudi to je dobra lastnost tega orodja, saj želimo obstoječo virtualno učno pot v prihodnje še nadgraditi z dodatnimi vsebinami oziroma že obstoječe vsebine prevesti v različne tuje jezike, ki jih poučujemo na naši šoli, da bo ta pot dostopnejša še večjemu krogu uporabnikov. LITERATURA IN VIRI [1] Burns, M. 2011. Distance Education for Teacher Training: Modes, Models, and Methods. Washington, DC: Education Development Center, Inc. [2] Tanja Rupnik Vec, Branko Slovar, Renata Zupanc Grom et. Al. 2020. Analiza izobraževanja na daljavo v času prvega vala epidemije Covid-19 v Sloveniji. Dostopno na nasovu: Slika 5: Primer virtualne učne table z besedilom in https://www.dlib.si/stream/URN:NBN:SI:DOC-X3BSQ9IN/d1f7defb-e0fa- fotografijo 4ad5-a9c5-975068de1020/PDF (9. 8. 2022) [3] Računalniški program ThingLink. Dostopno na naslovu: https://www.thinglink.com (9. 8. 2022) 430 [4] Spletna stran Osnovne šole Antona Martina Slomška Vrhnika. Dostopno na naslovu: https://www.osams.si/2022/05/30/virtualna-ucna-pot-naravnih-in- kulturnih-znamenitosti-obcine-vrhnika/ (9. 8. 2022) [5] Virtualna učna pot naravnih in kulturnih znamenitosti občine Vrhnika. Dostopno na naslovu: https://www.thinglink.com/video/1587877622233169922 (9. 8. 2022) 431 Dileme in rešitve poučevanja na daljavo Dilemmas and Solutions of Distance Learning Ranka Keser Osnovna šola Antona Martina Slomška Vrhnika Vrhnika, Slovenija ranka.keser@a1mail.si POVZETEK level of reading literacy and keep the students in regular daily work for the school. The extract from the 7th grade literature V tretjem tednu pouka na daljavo aprila 2020 učitelji še nismo textbook was the starting point for our assignment. We followed dobili nobenih konkretnih navodil za poučevanje na daljavo. Na the instructions in the reading material and highlighted the Osnovni šoli Antona Martina Slomška Vrhnika je pouk potekal interesting task of creative writing. Interesting stories were po spletni strani šole, kar pomeni, da smo učitelji nalagali created – "handouts", which the students wrote by sending each navodila in naloge na spletno stran šole. Pred nami je bil problem, other excerpts via e-mail. The student continued where his kako zastaviti tako zanimivo nalogo, da bi se je učenci lotili z classmate left off. We decided on a current topic – the time of the veseljem in hkrati ne bili preveč obremenjeni. Tukaj je treba corona virus. Individuals responded. With such a way of working, poudariti, da niso še vsi učenci imeli enake možnosti digitalnih students, classmates connected with each other, they started komunikacij. Cilj naloge je bil vsekakor slediti učnemu načrtu, correspondence; they also connected with their parents, as some vzdrževati raven bralne pismenosti in obdržati učence pri rednem created stories together with their parents.We published the vsakodnevnem delu za šolo. Odlomek iz berila za 7. razred je bil students' products in the school newsletter, and the new way of izhodišče naše naloge. Sledili smo navodilom v berilu in working encouraged us to tackle other "remote" projects in the izpostavili zanimivo nalogo ustvarjalnega pisanja. Nastale so future. zanimive zgodbe – »podajanke«, ki so jih učenci pisali tako, da so si podajali odlomke, in sicer po elektronski pošti. Učenec je KEYWORDS nadaljeval tam, kjer je je njegov sošolec končal. Določili smo aktualno temo – čas corona virusa. Odzvali so se posamezniki. Slovene, creative writing, short story – handout, corona, E-mail Pri takem načinu dela so se učenci, sošolci povezali med seboj, correspondence začeli so z dopisovanjem; povezali so se tudi s starši, saj so nekateri oblikovali zgodbe skupaj s starši. Izdelke učencev smo 1 UVOD objavili v šolskem glasilu, nov način dela pa nas je vzpodbudil, da smo se v prihodnje lotili tudi drugih projektov »na daljavo«. Drugačen način šolskega dela je v novonastalih razmerah in ob tehnoloških primanjkljajih pri učiteljih in učencih zahteval nov, KLJUČNE BESEDE drugačen pristop. Ob danem učnem načrtu in z ustrezno motivacijo je bilo Slovenščina, ustvarjalno pisanje, povest – podajanka, corona, potrebno pridobiti učence za delo na daljavo. dopisovanje preko elektronske pošte Učitelji se zelo dobro zavedamo težav, ki so jih imeli naši ABSTRACT učenci pri obvladovanju vseh šolskih obveznostih v okoliščinah dela na daljavo, posebej zaradi izgube jasnega vpogleda v In the third week of distance learning in April 2020, teachers kontinuirani napredek učenja in pridobivanja znanja. have not yet received any concrete instructions for remote Zato smo se lotili ustvarjalnega pisanja, s katerim smo teaching. At the Anton Martin Slomšek Vrhnika Elementary poskušali vzpostaviti ustvarjalno komunikacijo z učenci. To je School, classes were held on the school's website, which means bil eden od poskusov premostitve pomanjkljivosti uporabljene that the teachers uploaded instructions and assignments to the tehnologije pri delu na daljavo. school's website. The challenge in front of us was how to set such an interesting task so that the students would tackle it with pleasure and at the same time not be too burdened. It should be 2 POUK NA DALJAVO emphasized here that not all students have had the same opportunities for digital communications.The goal of the V tretjem vzgojno-izobraževalnem obdobju [1, str.32] pri assignment was definitely to follow the curriculum, maintain the učencih na področju književnosti razvijamo recepcijske zmožnosti z branjem, poslušanjem, gledanjem uprizoritev Permission to make digital or hard copies of part or all of this work for personal or umetnostnih besedil in z govorjenjem ter pisanjem o njih [1, str. classroom use is granted without fee provided that copies are not made or distributed 39]. 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 Na spletni strani šole so učenci dobili navodilo, da preberejo be honored. For all other uses, contact the owner/author(s). odlomek iz berila za 7. razred, in sicer odlomek iz mladinske Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia povesti »Bela past« Bogdana Novaka [2]. © 2022 Copyright held by the owner/author(s). 432 Sedmošolci so izbrani odlomek prebrali in odgovorili na 2.2 Podajanka vprašanja ter odgovore v celih stavkih zapisali v zvezek za V virih smo poskušali poiskati razlago pojma podajanka. književnost. Postopek odgovarjanja je bil učencem znan že od Ustrezne razlage nismo našli. V »Slovarju novejšega besedja prej, saj na ta način vadimo pravilen besedni red v povedi in slovenskega jezika« izraza ni zaslediti. Pojem izhaja iz besede krepimo naše izražanje. Učenci so odgovore na vprašanja poslali podajanje, kar je glagolnik od podajati. Izraz je razširjen na v vpogled na učiteljičin elektronski naslov. Vse naloge – področju športa: napake pri podajanju žoge in streljanju. Pogosta odgovore je učiteljica prebrala in pregledala ter napisala je besedna zveza: naravno podajanje besedila, kar pomeni, da komentar. Tako je vsak učenec prejel povratno informacijo govorec lepo, sproščeno pripoveduje ali bere besedilo. V SSKJ učiteljice, hkrati pa se je tudi učiteljica prepričala, da so besedilo najdemo pojem podaja, kar je glagolnik od podati. Zopet tipična razumeli. Pomembno je, da učenci razumejo in vidijo, kje so raba v športu: namesto meta na koš se je odločil za podajo; točna delali napake in kakšne so bile. Na ta način ohranjamo določen podaja ali podaja s krila [3]. V »Predlogu učnega načrta za pouk slovenščine v tretjem nivo bralne pismenosti in rednega dela. triletju« piše, da učenci pišejo realistično povest in realistični Učni načrt za slovenski jezik v nadaljevanju predvideva, da roman s tematiko iz vsakdanjega življenja; pustolovsko povest, učenci doživljajo, razčlenjujejo, vrednotijo različne književne kriminalno povest, kriminalni roman. V skupini sodelujejo pri zvrsti in vrste; opazujejo in predstavijo vlogo slogovnih prvin v pisanju podajanke. Svojo kolektivno povest postopoma umetnostnem besedilu; najdejo primere, s katerimi ponazorijo, dograjujejo, vsak pisec pa nadaljuje tam, kjer je predhodnik kaj je opis, oris, oznaka, pripoved [1, str. 41, 42]. Vse to smo zaključil [11]. preskočili in se že v prvotnem navodilu [6] usmerili v ustvarjalno Zasledili smo, da se pojem pojavlja kot branje po odlomkih. pisanje – razvijanje zmožnosti sprejemanja in tvorjenja proznih V razvojni nalogi Zavoda za šolstvo z naslovom »Uvajanje besedil [1, str. 43]. Sledili smo didaktičnemu instrumentariju v informativnega spremljanja in inkluzivne paradigme« je opisan berilu [2, str. 107], ki vzpodbuja k pisanju povesti – »podajanke«. primer »knjige podajanke« - celoletnega procesa v oddelku 9. Učenci so tudi s pomočjo učbenikov sledili navodilu za razreda. S tem projektom učiteljica krepi sodelovanje, kritično ustvarjalno pisanje. Določili sem temo – čas corona virusa in razmišljanje učencev, v ospredju je ustvarjanje in kreativno posledic položaja in okoliščin, v katerih smo se znašli vsi – pisanje. Med sošolci ves čas krožijo povratne informacije. učenci, učitelji in starši. Učenci sami okvirno določijo žanr svoje knjige, oznake Nenavadne življenjske situacije vzbudijo v človeku književnih oseb, določijo kraj in čas dogajanja. Razdelijo si vloge nenavadna dejanja, spremenijo se medsebojni odnosi – in v tem – kdo bo pisal, kdo ilustriral. Napisana poglavja sproti preberejo, sta si vsebina odlomka in novo zastavljena tema podobni. se pogovorijo. Učiteljica poglavja slovnično sproti popravlja, z Odlomek iz berila »Bela past« govori o medsebojnih odnosih odraščajoče mladine. Nevarni položaj se v povesti uspešno napakami seznani učence. Rezultati so izjemni, odzivi učencev razreši, ko glavni junak javno prizna svojo napako. Prijatelji ga pozitivni [10]. razumejo in mu oprostijo. Podobno izkušnjo je doživela tudi naša skupina učencev, vendar pri pouku na daljavo! 2.1 Povest 2.3 Motivacija Z brskanjem po različnih virih so učenci ugotovili, da je povest krajše, vsebinsko in izrazno manj zahtevno pripovedno delo, Pouk književnosti je sestavljen iz več zaporednih korakov. Vsak navadno v prozi [3]. Profesor Miran Hladnik razlaga, da je povest korak ima svoje značilnosti in vsaka značilnost zahteva v šolski poetiki umetniško manj pomembno delo v prozi s diferenciran pristop. poudarkom na zgodbi [4]. Opisuje predvsem zunanje dogodke, v Učenci pri pouku književnosti literarno besedilo zaznavajo katerih nastopa več oseb, avtor v ospredje postavi eno ali dve in doživljajo, razumejo in vrednotijo. Koraki šolske osebi, vendar se vanju ne poglablja pretirano. Pripoved je interpretacije literarnega besedila so: uvodna motivacija, najava usmerjena v zgodbo samo. Povest je napisana preprosto in besedila, umestitev v čas in prostor ter interpretativno branje; nazorno, konec je predvidljiv in navadno srečen. Povest je sledi premor po branju, izražanje doživetij ter analiza, sinteza in namenjena preprostemu človeku in ga kratkočasi pa tudi etično vrednotenje. Na koncu sledi ponovno branje in nove naloge. vzgaja. Avtor to doseže navadno tako, da ponazori kako misel z zgledom iz življenja in nato moralno jedro dokaže z zgodbo. Vseh teh korakov seveda nismo mogli izvesti pri naši uri Glede na to, da so povesti po vsebini različne (mladinske, »pouka na daljavo«. Kljub spremenjenemu načinu dela pa je kmečke, zgodovinske), so učenci ugotovili, da je odlomek iz treba poudariti pomen motivacije, za katero se je izkazalo, da je berila odlomek iz mladinske povesti. Značilno za povest je naš velik problem. predvsem to, da sledi dogajanju – zgodbi, kar je učencem Motivacija je eden izmed najpomembnejših dejavnikov uglavnem tudi uspelo [5]. uspešnega učenja pa tudi poučevanja, saj vpliva na otrokovo V navodilu so bili učenci opozorjeni na pisateljev »recept«, pozornost, mišljenje, pomnenje in čustva ter jih usmeri v učenje. kako naj pišejo, kaj vse naj upoštevajo – kako naj »iz testa in Se pravi, da gre za psihični proces, ki pa je nujen za vsa področja nadeva naredijo dobro potico«, ki ga je zaupal pisateljici Berti človekovega delovanja. Če učitelj dobro motivira učence, je Golob v knjigi »Do zvezd in nazaj« [2, str. 107] in se nahaja v opravil več kot polovico dela. Pomembne so besede, s katerimi berilu kot motivacija za pisanje. bo učitelj pripravil učence k delu, učenju, besede, s katerimi bo Na navodilo na spletni strani šole so se odzvali posamezni pokazal, kako koristno je učenje, vredno in hkrati prijetno, učenci. En učenec se je povezal kar s svojo mamo, ker je izgubil zabavno. Za to je potreben osebni stik. Kako naj to dosežemo na stike s sošolci. Povezala sta se še dva para sošolk in nastale so daljavo? zgodbe – »podajanke«. Eden začne in drugi nadaljuje. 433 Izkušnje so nas, učitelje, naučile, da mora biti motivacija potrditev s strani sošolcev in s strani učiteljice, saj so uspešno stalnica pouka, vendar glede na populacijo učencev različna in opravili svoj del naloge [9]. različno dolga. Vsaka motivacija mora biti načrtovana. Med učenci je potekala uspešna komunikacija, saj so večkrat Predvidevamo, da se bodo učenci odzvali na dano nalogo, se poudarili, da so se ob pisanju zabavali, vsakič z nestrpnostjo pravi, da bodo motivirani, če se bodo počutili sposobne narediti pričakovali nove odlomke, na katere bodo pripeli svoje odlomke. tisto, kar se od njih pričakuje; za nekatere učence vemo, da imajo Izdelke učencev smo upoštevali pri tisti eni oceni, ki smo jo radi slovenščino kot šolski predmet in jim tudi je bilo takoj jasno, morali učitelji pridobiti v drugem polletju šolskega leta kaj želimo; nekateri so zvedavi in imajo radi novosti, kot je 2019/2020. Nagrada v obliki dobre ocene je učence še posebej recimo pisateljev »recept« za dobro pisanje. Za pisanje povesti – razveselila. Ob koncu šolskega leta 2020 smo izdelke objavili v podajanke so imeli učenci dovolj časa, da so lahko razmislili in šolskem glasilu. razvili svojo domišljijo. Pri motivaciji je treba ločevati med uvodno in učno motivacijo. Uvodno motivacijo smo lahko delno izvedli, učna 3 PRISPEVKI UČENCEV motivacija pa je bila v tistem trenutku onemogočena. Učna Podajanka učenca, ki se je povezal z mamo, se začne v času motivacija je ožji pomen in pomeni motivacijo v procesu učenja, začetka corona virusa in se po maminem nadaljevanju nadaljuje ki pa ga mi sploh nismo mogli razviti. v leto 2024. Fant jo le zaključi, s srečnim koncem, saj so ljudje Učno uro »na daljavo« smo začeli z navodilom na spletni združili moči in premagali virus. Čutiti je vpliv novodobnih strani šole – branje odlomka iz berila, nadaljevali smo z grozljivk. odgovori na vprašanja, s katerimi smo preverili njihovo razumevanje, doživljanje in vrednotenje literarnega odlomka. Dodatna motivacija, s katero smo želeli obdržati nek redni šolski ritem, je bila ustvarjalna naloga, ki jo je ponujalo berilo samo [7]. Odziv učencev ni bil velik, vendar je bil pozitiven. Po zaključku tega malega projekta smo bili veseli, zadovoljni, saj smo delali drugače, bilo nam je zanimivo, zraven smo se zabavali in hkrati tudi nekaj naučili. Učenci so začeli z dopisovanjem tudi na drugih predmetnih področjih, mobilni telefoni so za trenutek stopili v ozadje. S pisanjem podajanke smo nevede ponovno vzpostavili vrstniško sodelovanje, ki je bilo čez noč prekinjeno. Na poseben način se je oblikovalo timsko delo, saj so se učenci skupaj z učiteljico povezali v skupino s skupnim namenom, za uresničitev skupnega cilja, in sicer nastanek zgodbe – podajanke. Učenci so se sami organizirali, sprejeli nalogo, medse razdelili vloge; komunikacija je potekala samo preko elektronske pošte, preko katere so prejemali učiteljičine usmeritve in povratno informacijo, in to vsak posebej. Skupaj smo dosegli cilj – nove zgodbe, podajanke. Verjamem, da je med sošolci vladalo posebno razpoloženje, saj jim je bila naloga zanimiva in so bili pripravljeni delati več kot sicer. Vemo, da je timsko delo skupinsko delo samostojnih članov. Vsak član ima svoje znanje, ideje in odločitve, ki pa so podrejene skupnemu cilju neke naloge. Vse člane obvezuje delovna naloga. Med sabo so različni, vendar prav ta različnost jih povezuje in ustvarja kreativne rešitve. Prav to se je zgodilo tudi pri našem pouku na daljavo. Na tem mestu moramo spet opozoriti, da so sošolci sodelovali med sabo samo preko elektronske pošte. Tim je skupina ljudi z istim ciljem, ki ga dosežejo z delitvijo nalog. Vsi člani skupine si prizadevajo doseči isti cilj tako, da delijo znanje, naloge izkušnje in pomoč [8]. Slika 1: Podajanka – učenec Leon Luzar Skupinska dinamika ima pomembno vlogo v razredu, v Druga podajanka dveh učenk je postavljena v vaško okolje.V učilnici, na čelu katere je učitelj, ki želi z učenci opraviti ospredju sta dve različni družini. Ena je skrbna, pazi nase, ne določeno nalogo. Delovanje skupine je seveda odvisno od hodi ven med ljudi, vse si pridelajo doma, izogibaju se druženju osebnosti članov, ki sestavljajo skupino. Naša skupina učencev – se pravi, sledijo navodilom »oblasti«. Druga družina se obnaša je očitno vzpostavila uspešno sodelovanje. Naloga se jim je zdela in živi bolj svobodno, mogoče celo nepremišljeno in ravno te nenavadna in zanimiva, počutili so se varne, ker so razumeli zadane corona virus. Tri pikice na koncu zgodbe očitno navodila in so lahko načrtovali svoje delo. Bili so sprejeti od napovedujejo, da bi se podajanka lahko nadaljevala – mogoče sošolca/sošolke oz. soavtorice in so lahko izražali svoje misli, prav z moralno noto, ki je prisotna v povesti »Bela past«, in sicer, čustva in občutke. Postali so bolj samozavestni, saj so doživeli 434 da vsakemu lahko ponudimo še eno, novo, priložnost. Kljub namigu učenka ni nadaljevala. Slika 2: Podajanka – učenki Tia Filipič, Neža Dovjak Miha, junak tretje podajanke, se v novi situaciji dolgočasi, življenje se mu obrne na glavo, v nobeni stvari ne najde smisla. V zgodbi svojo energijo in zvedavost usmeri v odkrivanje pohlepa pri svoji teti, ki izkoristi novonastalo situacijo in si zaželi materine dediščine. Zgodba ima srečen konec, saj Miha pravočasno odkrije tetine naklepe in pokliče policijo. Pri tej podajanki prehodi od ene do druge avtorice niso ravno dobro razviti – težko jima je bilo slediti dogajanju, vsekakor pa sta hoteli ustvariti napeto zgodbo, ki bi bila lahko resnična. Učenci so svoje zgodbe pošiljali po odlomkih, tako kot so si jo podajali. Odlomki so bili sproti lektorirani, obenem so si učenci v komentarjih pomagali z manjšimi namigi. Na tem mestu je potrebno ponovno poudariti, da je vse potekalo po elektronski pošti, med nami ni bilo nobenih drugih stikov. Slika 3: učenki Alenka Verbič, Lucija Vrhovec 435 4 ZAKLJUČEK Učitelji smo bili deležni različnih izobraževanj, da bi bili čim bolj usposobljeni za poučevanje na daljavo. Kaj pa je z učenci? Dilema učiteljice je bila, kako oblikovati navodila za delo, za pouk na daljavo, pri tem pri učencih vzbuditi zanimanje, slediti Mogoče ne bi bilo napačno razmišljati o rednem predmetu učnemu načrtu, ne zapostaviti branje in pisno izražanje oz. informatike in računalništva v osnovni šoli?! pridobiti učence za redno vsakdanje šolsko delo in jih pri vsem tem ne preveč obremenjevati. Dilema je bila toliko večja, kolikor je bila digitalna komunikacija še nerazvita oz. neosvojena s strani LITERATURA IN VIRI učencev in učiteljev. [1] Program osnovna šola, Slovenščina, Učni načrt [posodobljena izdaja], 2018. Učiteljica je v tistem času našla primerno rešitev, saj so bili Dostopno na naslovu učenci, ki so se odzvali, zadovoljni, bili so zaposleni z [2] https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- sola/Ucni-nacrti/obvezni/UN_slovenscina.pdf (1. 6. 2018), 32, 39, 41, 42, drugačnim delom, uspešno so sledili navodilom. Pri tem so se 43. zabavali, povezali med seboj, zgodbe so snovali tudi skupaj s [3] Berilo za sedmi razred devetletne osnovne šole »Sreča se mi v pesmi smeje«, 2002. Založba Mladinska knjiga, 104-107. starši in na koncu bili še nagrajeni za svoje delo. [4] Povest. Dostopno na naslovu https://fran.si/iskanje?View=1&Query=povest Učiteljici je v novo nastali situaciji uspelo navezati stike z Različica 9.0 (3. 12. 2021) učenci, se dopisovati z njimi. Letos so se ti isti učenci brez [5] Miran Hladnik, Povest. Dostopno na naslovu http://lit.ijs.si/povest.html (10. 11. 2004) zadrege obračali na elektronske naslove učiteljev in vprašali vse, [6] Povest. Dostopno na naslovu https://sl.wikipedia.org/wiki/Povest (3. 2. kar jim ni bilo jasno, izražali svoja mnenja, pošiljali 2021) [7] Navodilo s spletne strani šole OŠ Antona Martina Slomška Vrhnika. naloge v pregled. Letos so zaključili devetletno osnovno šolo Dostopno na naslovu https://www.osams.si/2020/03/19/slovenscina-7-a-2- in ta generacija učencev je na Nacionalnem preverjanju znanja prispevek/ (19. 3. 2020) [8] Leonida Novak, 2016. Spodbujanje razvoja bralne kompetence na literarnem dosegla nadpovprečen rezultat. Izkazalo se je, da je bilo zelo področju v prvem triletju. Pouk književnosti in motivacija. Dostopno na pomembno vzdrževati stike z učenci, pa čeprav samo preko naslovu https://core.ac.uk/download/pdf/79462288.pdf (6. 6. 2016), 175, elektronske pošte. 176, 177. [9] Nataša Tovornik, 2016. Kaj je timsko delo. Dostopno na naslovu Ti borni začetki so bili velika vzpodbuda, da se lahko vsi še https://www.datalab.si/blog/kaj-je-tim-in-timsko-delo/ (19. 7. 2016) veliko naučimo. Tako smo že ob naslednjem »zaprtju« šole [10] Skupinska dinamika. Dostopno na naslovu https://sl.wikipedia.org/wiki/Skupinska_dinamika (8. 6. 2018) pripravili radijsko igro »Pehar suhih hrušk« Ivana Cankarja, [11] Uvajanje informativnega spremljanja in inkluzivne paradigme, 2022. Zavod pripravili proslavo ob 20. obletnici šole, skupaj s pesniško zbirko RS za šolstvo. Knjiga podajanka. Dostopno na naslovu učencev, ki je nastajala na enak način, na daljavo, in pripravili še [12] https://www.zrss.si/wp-content/uploads/2022/02/ razvojna_naloga_uvajanje_FS-1.pdf (28. 2. 2022), 93, 94. marsikatero virtualno prireditev. [13] Predlog učnega načrta za pouk slovenščine v tretjem triletju, 1997/98. Jezik in slovstvo, kazalo letnika 43. Dostopno na naslovu https://www.jezikinslovstvo.com/ff_arhiv/lat1/043/12c06.htm (26. 3. 1999) 436 Podpora staršem in učencem pri šolanju na daljavo s pomočjo spletnega orodja Weebly Support to Parents and Pupils in Distance Schooling Using the Weebly Online Tool Barbara Kokec OŠ Prežihovega Voranca Maribor Maribor, Slovenija barbara.kokec @guest.arnes.si POVZETEK on the website is designed to be relevant during the isolation period and many of the activities are being used at school as well. V prispevku so predstavljeni nekateri izzivi, s katerimi smo se srečali v času izolacije in naše spopadanje z njimi. Gre predvsem KEYWORDS za aktivno preživljanje prostega časa v času izolacije, organizacijo dela, zmanjševanje in obvladovanje čustvenih stisk, Isolation, free time, motivation, organisation, support, weebly sproščanje, ohranjanje motivacije za učenje ter pomoč staršem v novonastali situaciji. S kolegicami v svetovalni službi smo 1 UVOD ustvarile spletno stran, na kateri smo na enem mestu zbrale različne aktivnosti in dejavnosti, ki so učencem in njihovim Izobraževanje na daljavo je predstavljalo velik izziv za vse staršem olajšale dneve preživete v izolaciji. Spletno stran je bila učitelje na naši šoli. Vsak izmed nas je iskal načine, kako izpeljati ustvarjena s pomočjo spletnega orodja Weebly. Na njej se lahko učinkovit pouk in čimbolj kvalitetno in trajnostno predstaviti vsebine svojega predmeta. Novembra 2020 smo bili že vsi bolj najdejo različne ideje, kako si organizirati svoj čas, kako se učiti ali manj vpeljani in smo na novo pridobljene izkušnje že z veliko ter kako preživeti prosti čas. Poleg tega lahko učenci posegajo manj stresa uporabljali v novem obdobju šolanja na daljavo. tudi po dodatni razlagi snovi, dodatnih gradivih in vajah. Starši Skupaj in en drugemu v podporo smo poskrbeli za kvaliteten pa lahko najdejo povezave do različnih člankov, vezane na pouk ob uporabi različnih spletnih orodij. Ko je delo kolikor družinsko življenje v času izolacije. Vsebine na spletni strani so toliko gladko steklo, pa smo se začeli spraševati, kaj še lahko pripravljene tako, da so bile aktualne v času izolacije, veliko naredimo, da v dejavnosti čimbolj aktivno vključimo res vse aktivnosti pa s pridom uporabljamo tudi v šoli. učence. Sodelavke v svetovalni službi smo začele opažati, da so učenci in starši v vedno večjih stiskah zaradi izolacije, motivacija KLJUČNE BESEDE za učenje je zaradi izrednih razmer začela padati, še posebej pa so bili izpostavljeni učenci s posebnimi potrebami in tisti z Izolacija, prosti čas, motivacija, organizacija, podpora, weebly učnimi težavami, ki samostojnega učenja ne zmorejo in ABSTRACT potrebujejo prisotnost in nadzor odrasle osebe. Tako se je porodila ideja o nekoliko drugačni spletni strani, kjer bi našli The paper presents some of the challenges we encountered različne vsebine na enem mestu, kjer bi imeli možnost during the isolation and our struggle dealing with them. It is komunikacije in kamor bi imeli lahek dostop tudi starši, za katere mainly about active leisure pursuits in times of isolation, pa bi prav tako pripravili material za pomoč pri šolanju na organising work, reducing and managing emotional distress, daljavo. Spletna stran je bila v prvi vrsti namenjena učencem z relaxing, maintaining motivation to learn and helping parents in dodatno strokovno pomočjo, izkazalo pa se je, da je bila koristna za prav vse učence, saj jim je nudila nekoliko drugačno podporo a new situation. Together with our colleagues at the school in pokrivala še ostala področja njihovega življenja. counselling service we have created a website that brings together in one place a variety of activities that have helped to make the days spent in isolation easier for pupils and their parents. 2 PODPORNE DEJAVNOSTI ŠOLANJA NA The website was created using the Weebly web tool. On the DALJAVO – spletno orodje WEEBLY website you can find different ideas on how to organize your time, Izobraževanje na daljavo je oblika izobraževanja, kjer sta učitelj how to study and how to spend your free time. In addition, in učenec med poučevanjem prostorsko ločena, komunikacijo students can also find additional explanations, additional med njima ter komunikacijo med učenci samimi pa omogočajo materials and exercises. Parents, however, can find links to različne vrste tehnologij. Učinkovito izobraževanje na daljavo various articles tied to family life during isolation. The content zahteva strukturirano načrtovanje, dobro strukturirane učne enote, specialne didaktične strategije ter komunikacijo preko Permission to make digital or hard copies of part or all of this work for personal or elektronskih in drugih tehnologij. Unesco poudarja, da classroom use is granted without fee provided that copies are not made or distributed izobraževanje na daljavo zahteva »visok nivo samouravnavanja 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 in veščin učenja, kar naj bi učitelji podprli z novimi be honored. For all other uses, contact the owner/author(s). poučevalnimi, učnimi in usmerjevalnimi strategijami«.[1] Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 437 Učitelji smo se najprej usmerili predvsem v kvalitetno Zato smo razmišljale naprej ter s pomočjo spletnega orodja izvajan pouk na daljavo, saj smo se še sami morali veliko naučiti weebly[5] ustvarile veliko bolj zanimivo in bolje organizirano na tem področju. Analiza dela na daljavo iz šolskega leta spletno stran, ki smo jo predstavile učencem s posebnimi 2019/2020 je pokazala, da so se učitelji trudili, da so delo potrebami, s katerimi smo delale in učiteljem, ki so jo potem organizirali tudi v skupinah ali dvojicah, vendar najbolj so naprej predstavili svojim učencem, nekateri pa so jo tudi sami s učence spodbujali k samostojnemu, individualnemu delu. pridom uporabljali. Poimenovale smo jo DODATNA Individualno delo predstavlja obliko pouka, pri kateri vsak STROKOVNA POMOČ[7] in jo postavile na vidno mesto na učenec sam izvaja določeno nalogo ali dejavnost in učencem šolski spletni strani. Na tej strani je pod razdelkom omogoča, da tempo dela prilagajajo svojim sposobnostim. Je pa SVETOVALNICA. Razdeljena je po naslednjih področjih. za uspešno realizacijo samostojnega dela v praksi pomembno, da imajo učenci razvite tudi sposobnosti načrtovanja, organiziranja, 2.1 Domov vodenja, kontroliranja in prilagajanja lastnega procesa učenja[2]. Naslovna stran ali Domov je prva stran naše spletne kreacije. Na Ugotavljali smo, da zaradi daljšega trajanja izolacije ni bilo tej strani smo se predstavile, kdo smo, kaj delamo in zapisale, več dovolj le kvalitetno izvajan pouk, temveč je bilo potrebno kako je organizirana dodatna strokovna pomoč v času dela na delati tudi na ostalih področjih razvoja. Učenci so bili namreč daljavo. veliko časa prepuščeni sami sebi, saj so tudi starši morali svoj način dela prilagoditi novim razmeram in je to terjalo čas, ki bi 2.2 Organizacija dela ga sicer lahko namenili svojim otrokom. Čisto naravno so učenci začeli izkoriščati to novo svobodo in kmalu je bila učinkovitost V tem delu smo pripravile aktivnosti, ki učencem omogočajo pouka veliko manjša. lažjo organizacijo dela v času šolanja na daljavo. Vseboval je Svetovalna služba na naši šoli si je zato zadala novo nalogo podporo in ustvarjalne ideje, kako si samostojno in z vizualnimi in sicer učencem ponuditi dejavnosti za čas, ko učenci niso pripomočki organizirati delo skozi cel dan ter tako dneve aktivno delali za šolo. Torej, kako aktivno in zdravo preživeti osmisliti in čimbolj zdravo in aktivno preživeti. prosti čas v okviru omejitev, ki jih je prinesla izolacija ter tako ohraniti energijo in motivacijo za ostalo delo. Na naši šoli 2.3 Učenje učenja uporabljamo Arnes Učilnice (moodle)[3] in videokonferenčno V tretjem razdelku smo učencem ponudile različne učne okolje Teams. Vsak razred od četrtega razreda naprej je imel strategije, s katerimi lahko izboljšajo svoje učenje, si ga naredijo svojo spletno učilnico, znotraj vsakega razreda pa je bila učilnica zanimivejšega, predvsem pa je učenje s pomočjo teh strategij razdeljena po predmetih. Najprej smo si omislile svoj kotiček v učinkovitejše. Zavedamo se, da se različni učenci učijo na vsaki posamezni spletni učilnici, torej razdelek, ki smo ga različne načine ter da vsaka strategija ni primerna za vsa poimenovale Razredna ura. V ta razdelek smo nalagale material področja, zato smo učencem pripravile različne vsebine s tega predvsem s področja, kako se učiti, sprostiti ter ideje, kako lahko področja. Na sliki 2 je nekaj vsebin iz te strani. Če učenec klikne učenci kvalitetno preživijo svoj prosti čas. Material smo na Strategije učenja-ČINKVINA, se mu odpre na kratko in oblikovale s pomočjo spletnega orodja Canva[4], saj so izdelki, barvito opisana metoda učenja, ki jo lahko takoj enostavno izdelani v tem programu barviti, zanimivi in pritegnejo preizkusi na svojem gradivu. Če mu metoda odgovarja, jo še kdaj pozornost. Spodaj je na sliki 1 prikazana mapa SPROŠČANJE iz uporabi. Če ne, preizkusi kakšno drugo. spletne učilnice sedmega razreda razdelka RAZREDNA URA, kamor smo na začetku shranjevale dopolnilne aktivnosti za učence. Tako smo opremile spletne učilnice za vse razrede. Ugotovile smo, da učenci poleg vseh ostalih vsebin, ki jih morajo dnevno pregledati in obdelati, ne posegajo po tem razdelku in zelo malo uporabljajo ponujene aktivnosti. Poleg tega so bile spletne učilnice vedno bolj polne in tudi ne več tako pregledne kot na začetku. Slika 2: Učenje učenja 2.4 Motivacija Tukaj se nahaja veliko didaktičnih iger, s katerimi si učenci lahko zapolnijo vmesni čas med učenjem. Igre so zanimive, učencem predstavljajo izziv, nekatere pa so tudi interaktivne. Učencem Slika 2: Razdelek RAZREDNA URA, mapa SPROŠČANJE ponujajo zabavo, hkrati pa z njimi razvijajo tudi druge veščine, na primer pozornost, koncentracijo, vidno-motorično 438 koordinacijo in še kaj. Pri urah dodatne strokovne pomoči smo te 4 ZAKLJUČEK aktivnosti s pridom uporabljali tudi, ko smo se izobraževali v šoli. Verjamem, da je bilo v času izolacije veliko stisk, osamljenosti, čustvenih motenj, depresij, malodušnosti tako med otroki kot 2.5 Šolanje na domu med odraslimi. Vloga nas učiteljev je kljub izrednim razmeram še vedno izredno pomembna. Edino prav je, da učitelji v V tem delu lahko učenci najdejo veliko gradiv, koristnih pri vsakršnih razmerah iščemo rešitve in nove možnosti, da pridemo šolanju na daljavo. Na začetni strani se nahaja nekaj povezav in v stik s svojimi učenci in jih vodimo ter spremljamo pri njihovem idej za prostočasne aktivnosti, posnetki lutkovnih predstav ter razvoju. Aktivnosti in vsebine na spletni strani so bile interaktivne igre. Za mlajše smo zbrali dejavnosti v podporo pripravljene z namenom ohraniti duševno zdravje otrok. Glede začetnemu opismenjevanju in računanju, starejši pa posegajo po na odzive učencev in staršev lahko rečemo, da smo svoj namen dodatni razlagi snovi, e-učbenikih po predmetnih področjih ter dosegli. Še posebej so bili navdušeni učenci s posebnimi dodatnih gradivih za učenje. potrebami, s katerimi smo skupaj pregledali vsebine, se z njimi tudi na učni uri kaj poigrali, pokazali smo jim razdelke, ki so za 2.6 Sprostitev njih še prav posebej koristni ter jih načrtno usmerile na delo s Ta razdelek je namenjen aktivnostim, ki učencem nudijo pomočjo spletne strani tudi po naši uri. Prednost podajanja sprostitev po učenju. Za mlajše so pripravljeni posnetki pravljic, vsebin na takšen način pred klasičnimi spletnimi učilnicami je vodenih meditacij, lutkovnih predstav in animiranih serij. Starši tudi dostopnost, saj z lahkoto in brez kakršnihkoli gesel lahko do in starejši otroci pa lahko dobijo kakšno idejo, kako preživeti svoj nje dostopajo učenci, starši in učitelji. Vse je na enem mestu in prosti čas z otrokom v družinskem krogu. vsak lahko hitro poišče vsebine, ki ga zanimajo. Veliko vsebin in aktivnosti je tudi po vrnitvi v šolo še vedno aktualnih in jih z 2.7 Gradiva za starše učenci pogosto uporabljamo. Spletno orodje Weebly je enostavno za uporabo, na voljo je veliko različnih možnosti, ki ti jih Zaradi vse večjih stisk staršev in njihovih otrok pa smo del naše program tudi jasno in sproti predstavi. Spletna stran se lahko spletne strani namenile tudi staršem, ki imajo možnost posegati dopolnjuje z materialom, pripravljenim v različnih oblikah, po aktualnih člankih na teme povezane s trenutno situacijo, nalagati je možno videoposnetke, fotografije, različne internetne vzgojo svojih otrok in ohranjanjem svojega lastnega zdravja. povezave, ustvariti je možno tudi interaktivne aktivnosti. Znotraj programa je možna tudi uporaba videokonferenčnega okolja ali komunikacija preko elektronske pošte. Poleg tega je uporaba 3 SOCIALNI VIDIK IN KOMUNIKACIJA S tega programa brezplačna. STARŠI Seveda je res, da je bila spletna stran ustvarjena z najboljšim namenom. Poskrbljeno je za barvitost, raznolikost aktivnosti in VIRI IN LITERATURA področij. Vsak lahko najde kaj zase, tako učenci, kot tudi starši [1] T. Rupnik Vec, S. Preskar, B. Slivar, R. Zupanc Grom, S. Kregar, A. Holcar in ostali učitelji. Potrudile smo se, da je stran sistematična, Brunauer, V. Bevc, M. Mithaus, M. Grmek, K. Musek Lešnik. (2020). Analiza izobraževanja na daljavo v času epidemije Covid-19 v Sloveniji, organizirana in pregledna. Vendar je to še vedno vsebina na delno poročilo [Online]. Ljubljana: Zavod Republike Slovenije za šolstvo. računalniku in je njena uporabnost omejena. Dosegljivo: www.zrss.si/pdf/analiza_izobrazevanja_na_daljavo.pdf [28. 7. Rezultati raziskave SI-PANDA so pokazali, da je 2022]. [2] S. Kustec, V. Logaj, M. Krek, A. Flogie, P. Truden Dobrin, M. Ivanuš pandemija covida-19 med otroki povzročila okrnjene stike s Grmek. (2020). Vzgoja in izobraževanje v Republiki Sloveniji v razmerah, sovrstniki, kar se je nadaljevalo tudi v obdobju po sprostitvi povezanih s covid-19, Modeli in priporočila [Online]. Ljubljana: Zavod ukrepov. Prav tako se je med mladostniki povečal čas, preživet Republike Slovenije za šolstvo. Dosegljivo: pred ekrani. Veliko staršev je tudi poročalo, da se otroci tudi po www.zrss.si/pdf/modeli_in_priporocila.pdf [28. 7. 2022]. [3] Arnes Učilnice. Dosegljivo: https://sio.si/vodici/moodle/#kompilacija-sio- pandemiji niso toliko vključevali v obšolske dejavnosti.[6] MDL-VOD Zavedamo se, da čustvenih stisk zaradi preobremenjenosti [4] Canva for windows. Dosegljivo: https://www.canva.com in osamljenosti ne moremo reševati le s pomočjo spletnih vsebin, [5] Weebly. Dosegljivo: https://www.weebly.com [6] A. Grom Hočevar, T. Truden Dobrin, A. Belščak Čolaković, T. Pibernik, M. zato smo staršem in učencem preko te spletne strani omogočili Rehberger, D. Lavtar, J. Kožar, S. Dravec. (2022). »Kako je pandemija tudi stik in komunikacijo s šolsko svetovalno službo preko covida-19 vplivala na življenjski slog otrok in mladostnikov v Sloveniji?« spletnega orodja TEAMS. Na vsakem razdelku je možnost Mladostnik na prepihu časa: zbornik prispevkov in izvlečkov: VIII. kongres KONTAKT, kjer lahko starši ali učenci vpišejo svoje podatke, na šolske, študentske in adolescentne medicine Slovenije: Medicinska fakulteta Maribor, 17. in 18. 6. 2022. [Online]. Dosegljivo: PDF (dlib.si) [27. 7. 2022]. kratko opišejo težavo ozirom izziv, ki bi ga želeli razreševati s [7] Dodatna strokovna pomoč. Dosegljivo:https://dspospvmb.weebly.com katero izmed nas in tako se začne komunikacija med nami. Enkrat tedensko (po vnaprej določenem urniku) pa je bila tudi možnost vstopa v konferenčno okolje TEAMS, kjer smo bile na voljo v živo in smo prav tako odgovarjale na vprašanja, starši so imeli možnost posveta ali pogovora v zvezi s svojimi otroki. Pravzaprav so bile to nekakšne govorilne ure svetovalne službe, kjer so imeli možnost stika z nami tako učenci kot starši. Urnik in predstavitev spletne strani staršem je potekala preko sporočila v eAsistentu in učiteljev, katerim smo me predstavile dejavnosti na eni izmed tedenskih srečanj vseh učiteljev. Sam obisk te možnosti (govorilne ure) sicer ni bil zelo obsežen, vendar verjamemo, da je že sam občutek, da smo na voljo, staršem in učencem dajal varnost in jim olajšal vsakodnevne izzive, ki jih je prinesla izolacija. 439 Digitalna zbirka kamišibajev A Digital Collection of Kamishibai Martina Kokelj Osnovna šola Antona Martina Slomška Vrhnika Vrhnika, Slovenija martina.kokelj@gmail.com POVZETEK 1 UVOD Na Osnovni šoli Antona Martina Slomška Vrhnika želimo, da so V Učnem načrtu za slovenščino [1] so zapisana besedila, ki jih učenci pri pouku ustvarjalni, inovativni in samostojni. Pri pouku moramo pri pouku slovenščine obravnavati v določenem slovenščine lahko to najlažje dosežemo pri obravnavi in analizi razredu. Med obvezna besedila v 7. razredu sodi tudi ljudsko literarnih del. Vsako leto opažamo, da imajo učenci težave z besedilo Pegam in Lambergar. razumevanjem starejših književnih besedil, zato damo poudarek Vsako besedilo, ki ga obravnavamo, najprej glasno prebere na razlagi in razumevanju vsebine besedila. To se je pokazalo pri učiteljica. Po prvem branju najprej strnemo prve vtise, razložimo sedmošolcih, ko smo obravnavali ljudsko pesnitev Pegam in neznane besede in vsebino besedila, nato besedilo še enkrat Lambergar. Odločili smo se, da pesnitev spremenimo v glasno berejo učenci. Pri vsakem besedilu določamo temo, kamišibaj. Pri ustvarjanju in oblikovanju kamišibaja so se učenci dogajalni kraj in čas ter napišemo kratko obnovo besedila. Če je naučili sodelovanja, hkrati pa so bili tudi likovno ustvarjalni. besedilo pesem, določimo tudi zunanjo in notranjo zgradbo Delo jih je navdušilo, zato smo se odločili, da poskušamo čim pesmi ter poiščemo pesniška sredstva, ki jih je avtor uporabil v več knjižnih del spremeniti v kamišibaj, zgodbo posneti in tako besedilu. Za urjenje domišljije in tehnike pisanja na določena ustvariti digitalno zbirko kamišibajev, ki bo v pomoč kasnejšim besedila poustvarjamo. Letošnji sedmošolci so zelo vedoželjni. generacijam za razumevanje vsebine književnih besedil. Poskušamo jih vključiti v proces načrtovanja pouka. Po obravnavi besedila smo učence vprašali, kako bi lahko besedilo KLJUČNE BESEDE Pegam in Lambergar preoblikovali oz. kako bi poustvarjali. Ena Slovenščina, kamišibaj, gledališče, digitalna zbirka od učenk je predlagala kamišibaj, ki ga je videla v splošni knjižnici in se ji je zdel zanimiv. Nihče od ostalih učencev za ABSTRACT kamišibaj še ni slišal, zato so morali za domačo nalogo raziskati, At the Anton Martin Slomšek Vrhnika Primary School, we want kaj to je. Naslednji dan so bili vsi navdušeni in so se veselili students to be creative, innovative and independent in their ustvarjanja. lessons. In Slovenian language classes, this can be achieved most Jenko [2] piše, da zaman iščemo strokovne izraze, povezane easily in the consideration and analysis of literary works. Every s kamišibajem, v različnih slovarjih, saj so ti pojmi na year, we notice that students have problems with understanding Slovenskem novejši od zadnje slovarske izdaje. Tominc [3] pravi, older literary texts, so we emphasize the interpretation and da je kamišibaj v Slovenijo pripeljal Igor Cvetko in je v naši understanding of the content of the text. This was evident in državi prisoten od leta 2013. Cvetko [4] razloži, da kamišibaj seventh-graders when we discussed the Pegam and Lambergar izvira z Japonske. Beseda »kami« pomeni papir, »shibai« pa folk poem. We decided to change the poem into kamishibai. In gledališče, torej bi dobesedni prevod pomenil papirnato the creation and design of the kamishibai, the students learned to gledališče. Gre za način pripovedovanja zgodb ob slikah v cooperate, and at the same time they were also artistically malem lesenem odru, ki se imenuje butaj. Butaj je sestavljen iz creative. They were impressed by the work, so we decided to try okvirja, vratc in prostora, v katerega vložimo ilustracije. Osebi, to turn as many book works as possible into kamishibai, record ki se ukvarja s kamišibajem, rečemo kamišibajkar. the story and thus create a digital collection of kamishibai, which will help later generations to understand the content of literary texts. 2 PEGAM IN LAMBERGAR KEYWORDS 2. 1 Obravnava besedila Slovene, kamishibai, theatre, digital collection Besedilo Pegam in Lambergar je najprej glasno prebrala učiteljica. Prvi vtisi na prebrano so bili zmedeni, saj so učenci trdili, da besedila niso razumeli. Začeli smo z razlago. Klicali Permission to make digital or hard copies of part or all of this work for personal or smo učence, da je vsak prebral eno kitico in jo poskušal s svojimi 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 besedami razložiti. Besedilo smo še enkrat glasno prebrali in citation on the first page. Copyrights for third-party components of this work must razumevanje je bilo boljše. be honored. For all other uses, contact the owner/author(s). V drugem delu smo se ukvarjali z besedilom. Izpisovali smo Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). glavne in stranske osebe, določali temo, dogajalni kraj in čas ter 440 pesniška sredstva. Določilo smo tudi vrsto in zvrst besedila. Z učenci smo se začeli pogovarjati, kaj bi lahko poustvarjali na temo obravnavanega besedila. Učenka je predlagala kamišibaj, ki ga je videla v splošni knjižnici in se ji je zdel zanimiv. Nihče od sošolcev za besedo kamišibaj še ni slišal, zato so morali za domačo nalogo raziskati pomen te besede. Nad idejo so bili navdušeni, zato smo se takoj lotili dela. 2. 2 Izdelava kamišibaja Na začetku so se vse stvari zdele zelo preproste. Ko smo začeli z načrtovanjem, smo hitro ugotovili, da bo potrebno veliko sodelovanja in usklajevanja, da bomo s končnim izdelkom zadovoljni. Učenci so najprej načrtovali, iz koliko slik bo kamišibaj, in kaj mora slika glede na besedilo vsebovati (Slika 1). ) Slika 2: Barvanje ilustracij 3 IDEJA O DIGITALNI ZBIRKI KAMIŠIBAJEV Danes smo ljudje navajeni, da do podatkov dostopamo preko spleta. Na spletu najdemo Digitalno knjižnico Slovenije, v kateri najdemo različne knjige, periodiko, rokopise, slike, glasbo, Slika 1: Načrt za ilustracije zemljevide … Prišli smo na idejo, da bi na naši šoli ustvarili svojo digitalno Učenci so načrtovali osem slik, zato so se razdelili v osem zbirko posnetkov kamišibajev. Digitalno zbirko bi hranili na skupin. Ugotovili so, da preden začnejo z delom po skupinah, se računalniku v šolski knjižnici. Do zbirke bi lahko dostopali morajo dogovoriti, kakšen bo izgled junakov in predmetov, ki jih učitelji. S posnetki bi lahko popestrili pouk učencem, ki prihajajo na risbah upodabljajo, saj ne more biti na vsaki sliki isti junak v višje razrede, in jim tako olajšali razumevanje prebranega. drugačen. Na spletu so poiskali ilustracije določenih junakov in Učence je izdelava kamišibaja navdušila. Po analizi dela in predmetov, s katerimi so si pomagali pri risanju. Svoje risbe so ogledu posnetka so učenci prišli na idejo, da lahko izdelamo pobarvali z barvicami (Slika 2). kamišibaj za več literarnih besedil, ki jih pri pouku obravnavamo, Vsaka skupina je svojo ilustracijo opremila z besedilom, ki in ga posnamemo, s čimer bi učenci lažje razumeli vsebino ga je ilustracija predstavljala. Ko so besedilo napisali, so se vodje literarnih besedil. skupin med seboj uskladili, da je bilo besedilo vsebinsko Učenci so takoj pričeli z iskanjem novega besedila, ki bi ga ustrezno. preoblikovali v kamišibaj. Na naši šoli vsako leto organiziramo Vsaka skupina je izbrala svojega predstavnika, ki je ob risbi, kulturni teden, na katerega povabimo tudi starše in vse ki so jo narisali in pobarvali, povedal besedilo. Za zaključek smo obiskovalce, ki si želijo ogledati naše prireditve. Učenci se pripovedovanje celotne zgodbe v tehniki kimišibaj tudi posneli predstavijo na različne načine. Tudi s svojim razredom smo iskali ideje, kako bi lahko na kulturnem tednu sodelovali. V letu 2022 ter analizirali svoj izdelek. mineva 100 let od rojstva Ele Peroci, zato so se učenci odločili, Pri snemanju smo naleteli na več težav. Med sabo so se da bo drugo literarno delo v naši digitalni zbirki njena pravljica morali uskladiti, saj mora eden od učencev iz butaja premikati Moj dežnik je lahko balon. sličice. Na začetku so učenci snemali s svojimi telefoni in so Učenci so knjigo prebrali in izdelali načrt za ilustracije. Vsako ugotovili, da je kvaliteta posnetka slaba. Učiteljica jim je jutro so zahajali v knjižnico, kjer so ustvarjali in izdelali predlagala, da zgodbo posnamejo s šolsko kamero. Učenci so kamišibaj. Pri delu so jih opazovali tudi učenci drugih razredov, morali do učitelja računalništva, ki jih je najprej naučil rokovanja predvsem z razredne stopnje, ki so hodili v knjižnico. Vse je s kamero. Učenci so bili zadovoljni šele s petim posnetkom, ki zanimalo, kaj počnejo. Učenci so jim razložili in vzbudili v njih so ga nato oblikovali v video urejevalniku Filmora, ki jih ga je zanimanje. Spodbudili smo jih, da svojim učiteljicam predlagajo naučil uporabljati učitelj računalništva. izdelavo svojega kamišibaja. 441 Učenci so se skrbno pripravljali na nastop v tednu kulture. Svojo Po opravljenem delu smo se pogovarjali ter analizirali svoj predstavitev so urili tudi tako, da so odšli na razredno stopnjo k izdelek in ugotovili, da so morali učenci pri izdelavi kamišibaja prvošolčkom in jim predstavili pravljico, ki jo obravnavajo tudi veliko sodelovati in se usklajevati. Med risanjem in barvanjem pri pouku slovenščine. Bili so konstruktivni kritiki, ki so jim so se učenci zelo zabavali, saj zelo radi ustvarjajo. Dogovorili pomagali izboljšati nastop. smo se, da končni izdelek posnamemo, da bodo lahko tudi naslednje generacije gledale in si lažje predstavljale romanco Pegam in Lambergar. Z izdelavo kamišibaja smo pri učencih krepili različne sposobnosti. Spodbujali smo umetniško ustvarjalnost, ko so risali in barvali ilustracije, krepili jezikovno ustvarjalnost, ko so morali zapisati besedilo oz. povzetek literarnega besedila za vsako ilustracijo, javno nastopanje in govorjenje, ko so pred razredom povedali zgodbo, in krepili odnose v razredu, saj je delo od njih zahtevalo veliko usklajevanj in dogovarjanj, da smo prišli do končnega izdelka. Na koncu pa vedno največ pomenijo nasmejani obrazi in zadovoljstvo učencev, ko si skupaj ogledamo posnetek. Učenci ne bodo nikoli pozabili, kaj je kamišibaj, in vsi bodo do podrobnosti poznali vsebino besedila Pegam in Lambergar. Na koncu so prišli do ideje, da skupaj izdelamo digitalno zbirko kamišibajev, ki jo bomo vsako leto dopolnjevali in bodo v pomoč tako učiteljici kot učencem pri razumevanju vsebine. Učenci bodo obiskali različne razrede in jim predstavili idejo, da bo naša digitalna zbirka kmalu obsegala večje število literarnih besedil. Slika 3: Nastop učenk na šolski prireditvi LITERATURA IN VIRI 4 ZAKLJUČEK [1] Učni načrt, Slovenščina. 2018. Ljubljana: Ministrstvo za izobraževanje, znanost in šport, Zavod Republike Slovenije za šolstvo. Dostopno na Vsako leto znova nas preseneti, ko učenci ne razumejo naslovu: https://www.gov.si/teme/programi-in-ucni-nacrti-v-osnovni-soli/ (Pridobljeno 10. 8. 2021). prebranega besedila, če pa je besedilo starejše, je razumevanje še [2] Jenko S. (2019). Kamišibaj v znamenju kakovosti in umetnosti. Amfiteater: toliko slabše. Prav zato smo učitelji primorani iskati nove rešitve, revija za teorijo scenskih umetnosti. Letn. 7, št. 1, 100–105 nove načine obravnav literarnih besedil, pri čemer želimo, da so https://www.slogi.si/wp-content/uploads/2019/12/Amfiteater- 7_1_TB_Jenko_Sitar_SI.pdf (Pridobljeno 10. 8. 2021).. učenci samostojni in kreativni. [3] Tominc M. (2021). Japonsko pripovedovanje zgodb je priljubljeno tudi v Pri pouku slovenščine obravnavamo različne vrste besedil: Sloveniji. Časoris. https://casoris.si/japonsko-pripovedovanje-zgodb-je- priljubljeno-tudi-v-sloveniji/ (Pridobljeno 10. 8. 2021). poezijo, prozo in dramatiko. Vsako besedilo večkrat preberemo, [4] Cvetko I. (2018). Slovenski kamišibaj v luči kulturne antropologije. V M. ga razložimo in poustvarjamo. Učence smo vključili v Čepeljnik (ur.), Umetnost kamišibaja. Zbornik prispevkov, Mednarodni načrtovanje pouka. Sami so predlagali izdelavo kamišibaja. simpozij Umetnost kamišibaja: Beseda podobe in podoba besede (str. 33– 34). Ljubljana: Slovenski gledališki inštitut. 442 Uporaba aplikacije Nexto pri terenskem delu na področju likovne umetnosti The Use of Application Nexto in Fieldwork in Art Classes Tina Kosi Osnovna šola Komenda Moste Komenda, Slovenija kosi.tina@oskomenda-moste.si POVZETEK application is designed very broadly and allows the user individual deviations from the designed path. The students Uporaba različnih aplikacij pri pouku likovne umetnosti realized that appropriately selected and presented information velikokrat pritegne širšo skupino učencev. Velikokrat tudi tiste, and communication technology is also useful for educational ki niso posebno likovno nadarjeni. Zato smo se ob obeleževanju purposes. Teachers learned that students have fewer prejudices Plečnikovega leta odločili, da za delo na terenu uporabimo when using various applications. Here, it is important that we aplikacijo Nexto Ljubljana. Na ta način smo raziskovali offer them the opportunity to use various innovations in the Plečnikove neuresničene projekte v Ljubljani. Ogledali smo si school environment, but at the same time we teach them to seveda tudi obstoječe. Aplikacija je učence vodila od spomenika recognize applicable and useful applications. do spomenika našemu velikemu arhitektu. S pomočjo izzivov, ki so jih reševali s pomočjo namigov v realnosti, so opravili naloge KEYWORDS in se tako poučili o slogu in ambicijah Plečnika. Učenci so samostojno raziskovali, razvijali sposobnosti in na ta način ICT, application Nexto, art gradili svojo samozavest ob uporabi novih aplikacij. Aplikacija je zasnovana zelo široko in uporabniku dopušča individualne 1 UVOD odstope od zasnovane poti. Učenci so spoznali, da je primerno izbrana in predstavljena informacijsko-komunikacijska V sodobni šolski situaciji se učitelji, učenci in drugi udeleženci tehnologija uporabna tudi v izobraževalne namene. Učitelji pa, učnega procesa srečujemo z invazijo ponudbe različnih aplikacij, da imajo učenci manj predsodkov pri uporabi raznih aplikacij. ki spodbujajo učenčevo vključenost v učni proces. Slednji je Pri tem je pomembno, da jim tudi v šolskem prostoru nudimo postal zelo pester v času epidemije, ko je veliko ustvarjalcev možnost uporabe različnih novosti, a jih hkrati učimo prepoznati ponujalo informacijsko-komunikacijo tehnologijo kot pomoč pri uporabne in koristne aplikacije. izvajanju pouka na daljavo. Pouk tako postaja vse bolj dinamičen, vključujoč in predvsem za učenca zelo stimulativen. KLJUČNE BESEDE Z aktivnim sodelovanjem in manjšim deležem frontalne oblike dela so učenci soočeni z novimi situacijami, v katerih IKT, aplikacija Nexto, likovna umetnost razvijajo samostojnost uporabe različnih aplikacij. V kolikšni ABSTRACT meri so izpostavljeni novim izkušnjam, zavisi od učiteljeve pripravljenosti raziskovanja in preizkušanja novosti na njegovem The use of various applications in art classes often attracts a lastnem področju. Velikokrat se pri uvajanju novih aplikacij wider group of students. Often even those who are not pojavi strah pred neizkušenostjo učitelja, saj so učenci velikokrat particularly artistically talented. That's why we decided to use the spretnejši pri uporabi le-teh. Odgovornost za uporabo in nudenje Nexto Ljubljana application for field work in commemoration of možnosti spoznavanja novosti na področju informacijsko- Plečnik's year. In this way, we researched Plečnik's unrealized komunikacijske tehnologije učencem tako nosi vsak učitelj sam. projects in Ljubljana. Of course, we also looked at the existing Aplikacija Nexto Ljubljana je za uporabo pri terenskem delu ones. The app guided students from monument to monument of v šoli zelo primerna, saj na učencem zanimiv in interaktiven our great architect. With the help of challenges, which were način približa umetnost, predvsem pa pokaže možnosti, ki jih solved with the help of clues in reality, they completed the tasks realna situacija na terenu ne more. Učenci s pomočjo aplikacije and thus learned about the style and ambitions of Plečnik. spontano raziskujejo okolico, v svojem tempu opravljajo naloge Students independently researched, developed skills and in this in tako širijo ter poglabljajo svoje znanje. Aplikacija od njih ne way built their self-confidence when using new applications. The zahteva likovne nadarjenosti, kar pripomore k njeni širši uporabi. 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 443 2 INFORMACIJSKO-KOMUNIKACIJSKA 2.2 Aplikacija Nexto v mestu Ljubljana TEHNOLOGIJA V ŠOLI V mestu Ljubljana lahko sledimo več ločenim doživetjem. Informacijsko-komunikacijska tehnologija (IKT) je že nekaj Aplikacije nas vodi po Ljubljanskem gradu, Arhitekturnih desetletij sestavni in nepogrešljivi del procesa poučevanja in biserih, pričaramo si lahko Sproščen dan v Ljubljani, se učenja v tehnološko razvitih državah [1]. Sprehodimo ob reku Ljubljanici in nabiramo nova znanja v Sodobna tehnologija dopolnjuje tradicionalno izobraževanje paketu Za radovedne raziskovalce … Vsako od teh doživetij nas z interaktivnimi vajami in dejavnostmi, povezanimi z IKT-jem. vodi po mestu in približa različne kulturne znamenitosti. O Učitelj lahko z uporabo IKT-ja približa pouk in snov učencem na znamenitostih si lahko preberemo opise, rešimo uganke in druge zanimivejši način [2]. zanimive igre in izzive. Z uporabo IKT v šoli učencem omogočimo izkustveno učenje in učenje praktičnih veščin, ki jih lahko prenašajo tudi v druga spletna okolja. Na ta način pridobijo izkušnje v različnih 3. UPORABA NEXTO LJUBLJANA PRI DELU aplikacijah in spletnih okoljih. S tem gradimo njihovo IKT NA TERENU pismenost in samozavest uporabe novih spletnih okolij ter zmožnost prepoznave kvalitetnih in uporabnih aplikacij. 2.1 Platforma Nexto Nexto je platforma za kulturno angažiranje, ki omogoča ustvarjanje in dostavo interaktivnih lokacijskih pripovedi, ki obiskovalcem spremenijo doživetje kulturnih turističnih destinacij (muzeji, naravni parki, zgodovinska mesta, arheološka najdišča ...) v igrifikacijske dogodivščine z elementi razširjene realnosti. Je edinstvena kombinacija racionaliziranega pogovornega vmesnika, mehanika igre, ki temelji na lokaciji, tehnike igrafikacije in najnovejši napredek v navidezni resničnosti [3]. Aplikacija Nexto je spletno orodje, ki nam omogoča spoznavati kulturne in krajevne znamenitosti. Omogoča več funkcij:  ustvarjanje vsebine v več jezikih,  dodajanje zvočne pripovedi v zgodbe,  podpira uporabo brez povezave,  različne možnosti monetizacije,  podporo notranjim izkušnjam,  osem različnih možnosti mini igre in štetje,  ustvarjanje razvejanih zgodb z več možnostmi,  podporo za videoposnetke in gif-e,  integracijo filtrov razširjene resničnosti Facebooka, Instagrama in Snapchata,  integracija izkušenj z razširjeno resničnostjo po meri, zgrajenih v enotnosti,  povezavo do videoposnetkov na youtube ter  dostop v trgovini Apple App Store in Trgovini Google Play [4]. Zaradi zgornjih značilnosti aplikacije Nexto uporablja vedno večje število upraviteljev večjih muzejev, galerij in ostalih kulturnih in naravnih znamenitosti Slovenije, npr. Mesto Slika 1: Plečnikove vizije - aplikacija Nexto Ljubljana, Ljubljanski grad, Bled, Piran, Portorož, Narodna galerija … Če povzamemo zelo preprosto, Na raziskovanje Ljubljane smo se s pomočjo aplikacije aplikacija Nexto uporabniku daje bistvene informacije o njegovi Nexto Ljubljana odpravili v Plečnikovem letu. Ob 150. obletnici neposredni okolici. Mobilna naprava informacije sprejema prek so v Nexto Ljubljana ustvarili program Plečnikove vizije, ki nas posebnih oddajnikov Bluetooth, ki z njo začnejo komunicirati, vodi po Plečnikovih neuresničenih projektih v Ljubljani (Slika ko se jim uporabnik dovolj približa. Nexto je zaradi tega kot 1). nalašč za uporabo med obiski muzejev in naravnih V aplikaciji si sledijo kulturne znamenitosti, razdeljene na znamenitosti ali pa raziskovanjem novih krajev [5]. postaje Tromostovje, Mesarski most, Novi magistrat, Magistratni vhod, Čevljarski most in Novi trg, Križanke, Vegova ulica in NUK, Kongresni trg, Katedrala svobode. 444 3.1 Pridobitev aplikacije uporabo niso imeli. Posamezne težave smo z učenci reševali individualno. Aplikacija je dosegljiva v trgovini Apple App Store in Trgovini Google Play. Za uporabnika je brezplačna. Naložbo sofinancirata Republika Slovenija in Evropska unija iz Evropskega sklada za regionalni razvoj [6]. Za uporabo potrebuješ telefon z operacijskim sistemom Android 5.0 ali novejši in možnost uporabe Bluetootha. Dostop do interneta oziroma mobilne podatke potrebuješ le za nakup aplikacije. Za samo uporabo aplikacije spletne povezave ne potrebuješ. Učenci so se razdelili v skupine, saj vsi učenci niso imeli mobilnih naprav. Nato so aplikacijo naložili na telefone in sledili korakom prijave. Prijava je enostavna, zato veliko dodatnih navodil učitelja skoraj niso potrebovali. 3.2 Uporaba aplikacije Uporaba aplikacije je zasnovana zelo enostavno. Postaje so vnesene v Google zemljevid, s pomočjo katerega sledimo posameznim postajam na poti. S pomočjo Google zemljevida se orientiramo v samem mestu. Ko se s telefonom približamo posamezni postaji, opremljeni z oddajniki Bluetooth, prejmemo razlago oziroma nalogo. Uporabnik sledi navodilom avatarja »mojstra«, ki te vodi s pomočjo ugank in nalog od ene do druge mojstrovine. (Slika 2) Ogledali smo si: Tromostovje, Mesarski most, Novi magistrat, Magistratni vhod, Čevljarski most in Novi trg, Kongresni trg ter Vegovo ulico z NUK. Po poti si v aplikaciji ogledamo neuresničene projekte v tridimenzionalni obliki, ki v realnosti nikoli niso bili izvedeni. Tako je za nas narisan Mesarski most, Novi magistrat, Magistratni vhod, Katedrala svobode. Stavbe na ekranu lahko zavrtimo okoli osi in si jih ogledamo z vseh strani. Na Čevljarskem mostu, Križankah in Kongresnem trgu nas čaka izziv, ki nam pomaga poiskati pot naprej. Podoba mojstra nam je v aplikaciji postavila naloge, s pomočjo katerih smo še podrobneje spoznali Plečnikova dela in njegov slog. Naloge so zasnovane tako, da poiščeš podatke na sami lokaciji – preštej, najdi, razišči …, ki jih potem vpišeš v samo aplikacijo. Zaradi zadanih nalog so si učenci podrobneje ogledali arhitekturo in tako samostojno ugotavljali posamezne lastnosti Plečnikovega stila. Zaradi lastne izkušnje in truda, ki so ga morali vložiti v rešitev uganke ali naloge, je njihovo znanje kvalitetnejše in bolj poglobljeno. Slika 2: Uporaba aplikacije Nexto Zaradi pomankanja časa si nismo ogledali Križank in Katedrale svobode, kar aplikacije ni zmotilo. Lahko se držimo 4 ZAKLJUČEK predvidene poti s strani ustvarjalcev, saj si sledijo v nekem smiselnem zaporedju. Lahko pa znamenitosti obiskujemo tudi v Uporaba aplikacije Nexto je bila za učence zelo stimulativna. Kot naključnem vrstnem redu, kar nam omogoča uporaba Google smo ugotovili že v uvodu, je uporaba sodobne tehnologije in zemljevidov. Po opravljeni nalogi na posamezni postaji se na spoznavanje novih aplikacij, ki so zasnovane kvalitetno in zemljevidu pojavi zelena kljukica, neopravljene naloge pa so primerno starosti učencev, za učence zelo pomembna. Na ta zaznamovane z rdečim klicajem. Tako imamo tudi ob način umetnost približamo tudi manj likovno nadarjenim neupoštevanju predvidene poti izvrsten pregled nad že učencem. Pridobili so izkušnjo uporabe mobilnega telefona za opravljenimi postajami. izobraževalne namene, gradili samozavest in zavedanje, da nam Če ne zaključimo celega doživetja v enem dnevu, se naš sodobna informacijska tehnologija lahko nudi več kot le zabavo. napredek v aplikaciji shrani in neopravljene postaje lahko Samostojno oziroma z le nekaj usmeritvami učitelja so opravimo ob drugi priložnosti. naložili aplikacijo na svoje telefone in se seznanili z njenim Učenci so imeli največ težav na začetku uporabe aplikacije. delovanjem. S pomočjo Google zemljevidov so se samostojno Ko so ugotovili, na kakšen način je zasnovana, večjih težav z orientirali po mestu. Poglobili so znanje o Plečniku in spoznali njegovo genialnost ter velike vizije za mesto Ljubljana. 445 Učenci so bili nad uporabo aplikacije navdušeni, saj je bila LITERATURA IN VIRI uporaba le-te povezana z delom na terenu. Nekateri so poskušali [1] Biljana Mišič Ilič in Ljiljana Mihajlović. 2013. Try IT! Using information naloge zaobiti in z ugibanjem priti do rešitev. To jim ni uspelo, and communication Technology in an English Classrom. Filozofski saj so bile uganke in izzivi zasnovani precej eksplicitno in so se Fakultet Univerziteta u Nišu [2] Irena Gole in Mateja Hadler. 2015. Učenje s tablicami na razredni stopnji. res morali poglobiti v arhitekturo Plečnika, da so lahko opravili Primeri iz prakse. V: Kaj nam prinaša e-Šolska torba: zbornik zaključne izzive aplikacije. konference projekta e-Šolska torba. Ljubljana: Zavod RS za šolstvo. Dostopno na naslovu https://www.zrss.si/pdf/kaj-nam-prinasa-esolska- torba.pdf (3. 8. 2022) ZAHVALA [3] Spletna stran agencije Proxima. Dostopno na naslovu https://proxima.si/project/nexto/ (2. 8. 2022) Posebna zahvala velja gospe Andreji, naši šolski knjižničarki, ki [4] Spletna stran Nexto. Dostopno na naslovu https://nexto.io (2. 8. 2022) s svojim svežim pristopom in stalno pripravljenostjo pomagati, [5] Spletna stran Siol. Nexto slovenska aplikacija, ki lahko zamenja turističnega vodiča. Dostopno na naslovu: spodbuja k preizkušanju in uporabi novih aplikacij. https://siol.net/digisvet/novice/nexto-slovenska-aplikacija-ki-lahko- zamenja-turisticnega-vodnika-62593 (15. 9. 2022) [6] Spletna stran Visit Ljubljana. Plečnikova Ljubljana. Dostopno na naslovu: https://www.visitljubljana.com/sl/obiskovalci/odkrivajte/dozivetja/zname nitosti/clanek/plecnikova-ljubljana (3. 8. 2022) 446 “International Masterclasses” iz fizike osnovnih delcev “International Masterclasses” in Particle Physics Andrej Lozar Rok Pestotnik Institut “Jožef Stefan” Institut “Jožef Stefan” Ljubljana, Slovenija Ljubljana, Slovenija andrej.lozar@ijs.si rok.pestotnik@ijs.si POVZETEK predstavitve o osnovah fizike osnovnih delcev, zaznavanju delcev in raziskovalnih metodah ter popoldanski praktični del, V eksperimentalni fiziki osnovnih delcev raziskujemo lastnosti kjer pridobljeno znanje tudi uporabijo pri izvajanju meritev na najmanjših gradnikov snovi in reakcije med njimi. Za pravih podatkih iz eksperimentov osnovnih delcev. Delavnice razumevanje redkih procesov potrebujemo veliko količino vzporedno potekajo na različnih institucijah v maternem jeziku, podatkov, da lahko iz njih izluščimo statistično signifikantne po koncu praktičnega dela pa se učenci preko videokonference rezultate. Za obdelavo tako zajetih podatkov, so potrebni povežejo s tremi do petimi sodelujočimi institucijami, kjer na kompleksni rekonstrukcijski algoritmi in računalniška orodja. V mednarodni ravni predstavijo in razpravljajo o svojih rezultatih prispevku so predstavljene delavnice International Masterclasses, v angleškem jeziku. ki želijo z nazornimi predstavitvami in prilagojenimi in Delavnice organizira mednarodna kolaboracija namenjena poenostavljenimi analizami udeležencem predstaviti cilje in širjenju znanja o fiziki osnovnih delcev »International Particle metode dela v fiziki osnovnih delcev. Physics Outreach Group« (IPPOG / https://ippog.org/ ), katere glavni cilj je vzgajati in spodbujati spoštovanje temeljnih KLJUČNE BESEDE znanstvenih raziskav; vzpostaviti razumevanje znanstvenega IPPOG, Belle II, ATLAS, outreach, International Masterclasses procesa in sklepanja, ki temelji na dokazih, gradnja zaupanja s ABSTRACT širokim in raznolikim naborom svetovnih skupnosti in informiranje ter motiviranje prihodnjih generacij znanstvenikov In the experimental particle physics, we investigate the in državljanov. International Particle Physics Outreach Group si properties of the smallest building blocks of matter and the že od leta 1997 usklajeno in sistematično prizadeva za interactions between the constituents. To understand rare predstavitev in popularizacijo fizike delcev vsem občinstvom in processes, we need a large amount of data in order to extract starostnim skupinam. statistically significant results from them. Complex Glavni cilj International Particle Physics Outreach Group je reconstruction algorithms and computer tools are needed to čim bolj povečati učinek izobraževanja in prizadevanj za process such collected data. The paper presents the International ozaveščanje v zvezi s fiziko delcev. Kolaboracija prispeva h Masterclasses workshops, which aim to present the goals and globalnim prizadevanjem pri krepitvi kulturne zavesti pri methods of work in elementary particle physics to the razumevanju in podpori fizike delcev in sorodnih ved, pri participants with graphic presentations and sensible and dvigovanju znanstvene pismenosti v družbi, izobraževanju simplified analyses. javnosti o vrednotah temeljnih raziskav ter pri razvoju in usposabljanju naslednje generacije raziskovalcev, znanstvenikov KEYWORDS in inženirjev. IPPOG, Belle II, ATLAS, outreach, International Masterclasses Člani kolaboracije so države in mednarodne kolaboracije v visokoenergijski fiziki, ki predstavljajo delo raziskovalcev na področju visoko energijske fizike, strokovnjaki za znanstveno 1 UVOD komunikacijo iz različnih mednarodnih raziskovalnih institutov, »International Masterclasses« so mednarodne delavnice za univerz in laboratorijev, ki so vključeni pri raziskovanju fizike srednješolske učence, ki za en dan želijo postati raziskovalci osnovnih delcev. Sodelujoči eksperimenti in tematike delavnic, fizike osnovnih delcev [1,2]. Delavnice potekajo enkrat letno na ki jih učenci lahko spoznajo, so: ATLAS, ALICE, CMS, LHCb, univerzah in raziskovalnih inštitutih v 60 državah, kjer se skupaj Belle II, MINERvA in Particle Therapy. zbere 13000 učencev. Delavnice vključujejo dopoldanske Znanstveniki za raziskovanje osnovnih delcev uporabljamo pospeševalnike delcev, kjer delce pospešimo do skoraj svetlobne Permission to make digital or hard copies of part or all of this work for personal or hitrosti in zelo visoke energije, in trkalnike, kjer delce trčimo classroom use is granted without fee provided that copies are not made or distributed med seboj. Ob trku se sprosti velika količina energije, ki se lahko 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 pretvori v maso novo nastalih delcev. Ti so zelo nestabilni in zelo be honored. For all other uses, contact the owner/author(s). hitro razpadejo na bolj dolgožive delce, ki jih nato zaznamo in Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia lahko pomerimo njihove lastnosti. © 2022 Copyright held by the owner/author(s). 447 Dva eksperimenta, pri katerih sodelujemo in organiziramo 2 METODE DELA delavnice na odseku za eksperimentalno fiziko osnovnih delcev Struktura delavnic International Masterclasses je podobna, v Instituta Jožefa Stefana, sta Belle II v Cukubi na Japonskem [3] nadaljevanju se bomo osredotočili na primer delavnice Belle II. in ATLAS v Ženevi v Švici [4]. Delavnice so razdeljene na dva dela. V dopoldanskem času Eksperiment Belle II se nahaja na inštitutu za visoko potekajo 45 minutna predavanja, popoldan pa se udeleženci energijsko fiziko KEK. Postavljen je bil z namenom raziskovanja preizkusijo v praktičnem raziskovalnem delu. Dogodek redkih razpadov mezonov B, D in leptonov tau, ki jih ustvarjamo oglašujemo s pomočjo sistema za načrtovanje in organizacijo s trkanjem pozitronov in elektronov v pospeševalniku dogodkov indico, ki je v skupnosti za eksperimentalno fiziko SuperKEKB. Z merjenjem in analizo razpadnih produktov osnovnih delcev zelo razširjen. Primer strukture letošnjega želimo poiskati odstopanja od teoretičnih napovedi, ki jih dogodka je predstavljen na naslovu napoveduje Standardni model. Ta model je zelo uspešen pri https://indico.ijs.si/event/1412/. opisu osnovnih delcev in njihovih medsebojnih interakcij, ki jih Po registraciji udeležencev začnemo z uvodno predstavitvijo, imenujemo elektromagnetna, šibka in močna jedrska sila. kjer predstavimo fiziko osnovnih delcev. Udeležence seznanimo Ker pri trkih visokoenergijskih delcev nastaja ionizirajoče z razumevanjem osnovnih gradnikov skozi čas in o tem, kako jih sevanje, je dostop do detektorja med delovanjem pospeševalnika opisujemo s Standardnim modelom danes. Seznanimo jih z prepovedan. Za kontrolo delovanja vseh detektorskih sklopov odprtimi vprašanji, s katerimi se ukvarjamo. Standardni model skrbijo kontrolni sistemi, ki omogočajo oddaljeno priklapljanje osnovnih delcev je skorajda popoln. Vse meritve na in odklapljanje delov detektorja in nadzor napajalnih napetosti in spektrometrih se z njim skladajo, eksperimentalni fiziki osnovnih tokov. Šele ko vsi sistemi usklajeno delujejo, je mogoč zajem delcev si prizadevajo, da bi odkrili procese, kjer Standardni podatkov. model narave ne opiše zadovoljivo. Za tako iskanje imamo več ATLAS je ravno tako eksperiment za odkrivanje in kot dobro osnovo. Standardni model ne vključuje ene od razumevanje osnovnih delcev in se nahaja v velikem hadronskem osnovnih šol - gravitacije, poleg tega pa posredne meritve iz trkalniku (LHC) na inštitutu za jedrske raziskave CERN. Za astrofizike kažejo na obstoj temne snovi in energije, o kateri ne razliko od eksperimenta Belle II, tam trkamo protone v protone vemo nič, predstavlja pa 95% mase vesolja. pri bistveno višjih energijah in z manjšo pogostostjo. V nadaljevanju predstavimo pristope, kako trkamo med Pri obeh eksperimentih poteka zajem podatkov s seboj gruče delcev in nato razložimo eksperimentalne metode, ki spektrometrom, ki obdaja mesto trka (interakcijska točka). jih uporabljamo pri opazovanju trkov in razpadov delcev: kako Spektrometer sestavljajo različni detektorski podsistemi s opišemo trke, kakšne naprave potrebujemo in kako delujejo. specifičnimi nalogami, kot so merjenje trajektorije, gibalne Osnovne delce, ki jih raziskujemo, proizvedemo s trkanjem količine ali energije delcev. visokoenergijskih curkov delcev v pospeševalniku. Nastali delci Razumevanje procesov v fiziki osnovnih delcev in so večinoma kratkoživi in razpadejo zelo blizu mesta nastanka obvladovanje standardnih orodji za analizo je dolgotrajen in na lažje delce, ki jih lahko zaznamo v detektorjih za osnovne kompleksen proces saj zahteva določena predznanja iz fizike, delce, ki zaznavajo delce preko interakcij z okoliško snovjo. statistike in računalništva. »International Masterclasses« smo Nastali delci odletijo na vse strani, zato je detektor podoben izoblikovali tako, da na razumljiv način predstavimo osnovne čebuli, detektorski sistemi pa si tesno eden za drugim sledijo v fizikalne koncepte in analitske metode, zato da jih lahko tudi lupinah. Notranje lupine detektorja obdaja močan superprevodni učenci sami uporabijo v praktičnem delu delavnice tako, kot to magnet, ki poskrbi, da se pot nabitih delcev ukrivi in da lahko iz počnejo raziskovalci pri svojem raziskovalnem delu. Vsebina nje določimo gibalno količino in naboj delcev. Milijone delavnic je dovolj poenostavljena, da učenci osvojijo novo električnih signalov iz detektorja je potrebno najprej pretvoriti v znanja v enem dnevu. digitalno obliko, zato da jih lahko potem z računalniškimi V delavnicah tako združujemo vsa zgoraj našteta področja. algoritmi obdelujemo. Iz zajetih podatkov na prvi stopnji analize Na ta način skušamo ponazoriti izjemno pomembno komponento rekonstruiramo sledi, izmerimo gibalno količino, določimo naboj sodelovanja v mednarodnih raziskovalnih skupinah, kjer pri in identiteto zaznanih delcev. Tako rekonstruirane delce lahko pripravi eksperimenta, zajemanju podatkov in analizi sodeluje od potem z različnimi metodami kombiniramo med sabo in nekaj sto do nekaj tisoč raziskovalcev različnih strokovnih pogledamo, iz katerega visokoenergijskega delca so nastali. Pri profilov. Temelj usklajenega delovanja predstavlja učinkovit in zajemu, rekonstrukciji in analizi podatkov uporabljamo različne večinoma prost pretok informacij znotraj raziskovalne skupine, kompleksne tehnologije. Hitrost trkanja delcev med seboj je ki vključuje večino elementov odprte znanosti, ki temelji na nepredstavljiva. Na velikem hadronskem trkalniku gruče delcev skupnih prizadevanjih in novih načinih razširjanja znanja ter trkajo med seboj vsakih 25 ns, kljub najsodobnejši tehnologiji je izboljšuje dostopnost do rezultatov raziskav in njihovo ponovno potrebno podatke čimprej ločiti na take, kjer je verjetnost, da se uporabo s pomočjo digitalnih tehnologij in novih orodij za je zgodil razpad, ki ga želimo opazovati, večja, in preostale, ki sodelovanje. jih zavržemo. Ta selekcija poteka na več nivojih, kjer se S prenosom delavnic v slovenski prostor želimo slovenskim kompleksnost opazovanih spremenljivk povečuje. Začetno srednješolcem omogočiti enakopraven dostop do izobraževalnih selekcijo večinoma opravimo že na manjših delih detektorja v vsebin, ki jih ponuja IPPOG. Poudariti je potrebno, da so elektronskih vezjih na detektorjih. Kasneje poteka selekcija na delavnico Belle II za celotno mednarodno raziskovalno skupino programskem nivoju. V zadnjem času na različnih delih pripravili slovenski raziskovalci in je doživela izjemno pozitiven obdelave podatkov uporabljamo metode strojnega učenja, ki sprejem v številnih državah. občutno izboljšajo izkoristke. 448 V nadaljevanju se udeleženci s pomočjo aplikacije za navidezno resničnost (slika 1) in virtualnimi očali Oculus Rift ter Oculus GO sprehodijo po detektorju Belle II [5]. V aplikaciji si lahko od blizu ogledajo njegovo notranjost in posamezne sestavne dele ter tako pridobijo predstavo o njegovem delovanju. Aplikacija omogoča tudi predvajanje in vizualizacijo posameznih dogodkov oziroma trkov elektrona s pozitronom ter novo nastale delce, ki med preletom interagirajo z detektorji. Med sprehodom lahko udeleženci podrobno preučijo detektorske sisteme in senzorje, za vsak nastali delec pa si lahko pogledajo, kakšne so njegove lastnosti in kakšen odziv pusti v detektorju. Slika 2: Aplikacija Belle II Lab. Slika 1: Interaktivna aplikacija za navidezno resničnost Belle II detektorja. Zadnje predavanje dopoldanskega dela je namenjeno uvodu v analizo podatkov v eksperimentalni fiziki, kjer predstavimo nekaj osnovnih relativističnih enačb, eksperimentalnih količin in Slika 3: Primer prikaza enega dogodka, ki ga udeleženci statističnih konceptov. S pridobljenim znanjem so udeleženci kategorizirajo. pripravljeni na popoldanski praktični del analize podatkov. Pri delavnici iz eksperimenta Belle II sta na voljo dve Na koncu delavnice poteka še videokonferenca, na katero se različici analize izmerjenih podatkov, ki jih je dala mednarodna priključimo udeleženci iz različnih univerz, raziskovalnih raziskovalna skupina Belle II v prosto uporabo. ustanov in institutov. Konferenco vodi moderator, ki povabi Prva je analiza podatkov preko spletne aplikacije Belle II Lab posamezne skupine, da predstavijo izbrano analizo in kaj so [6], ki je uporabniku prijazna saj je bila namensko razvita, da ni odkrili. Tekom spletne povezave se neposredno povežemo tudi v potrebno nobeno znanje o programiranju (slika 2). Aplikacija kontrolno sobo z raziskovalci, ki nadzorujejo delovanje uporablja grafični uporabniški vmesnik Blockly JavaScript, kjer detektorja Belle II, in jih udeleženci direktno vprašajo kar jih uporabnik interaktivno izbere in poveže funkcionalne gradnike zanima. Za zaključek in za sprostitev vsi priključeni rešujemo za nadzor analize in opis fizikalnih procesov. Naloga učencev je, zabavni kviz o znanosti in življenju na Japonskem (slika 6). da po navodilih rekonstruirajo nekaj najbolj zanimivih razpadov in jih iz histogramov tudi razberejo. Rezultati in uporabljena 3 REZULTATI konfiguracija blokov se shranjuje lokalno na osebnem računalniku in na strežniku, kjer je dostopna tudi za tutorje v Letos smo delavnico Belle II International Masterclasses izvedli primeru težav. v treh časovnih terminih na enajstih raziskovalnih ustanovah Druga je analiza posameznih trkov in nastalih sledi (slika 3), (IPHC, IFJ, INFN Padova, INFN Roma Tre, IJS, LMU, MPP, da eksperimentalno določimo število možnih barv kvarkov [7]. S CUNI, HEPHY, CPPM in METU) iz osmih evropskih državah. poznavanjem osnov oblike dogodka, udeleženci kategorizirajo Vzporedno na isti dan je sodelovale od tri do pet institucij, ki so več setov 50 trkov in vpišejo opažanja v spletno razpredelnico se ob zaključku delavnice skupaj povezale na videokonferenco, dostopno vsem sodelujočih. Tekom analize učenci spoznajo, da na kateri so dijaki predstavili dogajanje tekom delavnice. Še večje število podatkov pripomore k natančnosti končnega posebej je bilo udeležencem zanimivo in v izziv, če so učenci iz rezultata. Na koncu so vsi vnosi avtomatsko prešteti in druge ustanove predstavili analizo, ki je sami niso opravljali. preračunani v končni rezultat, ki predstavlja število možnih barv Skupno se je delavnice udeležilo okrog 230 udeležencev, od tega kvarkov. so štirje bili iz Institutu Jožefa Stefana. 449 Pri praktičnem delu analize podatkov s spletno aplikacijo dogodke; polinomsko pa za opis položnega dela histograma, ki Belle II Lab so udeleženci iskali in rekonstruirali težje in predstavlja dogodke iz ozadja. S pomikanjem drsnikov so dijaki kratkožive delce v pomerjenih Belle II podatkih. Skupaj so imeli spreminjali parametre funkcij in želeli doseči, da se je graf za opraviti 9 nalog in poiskati 7 delcev. Prvi dve nalogi sta bili le funkcije čim bolj prilegal histogramu. Pri tem so si pomagali tudi spoznavanje delovanja spletne aplikacije, kjer so dijaki izpisovali z računalniškim algoritmom prilagajanja, ki je implementiran v različne lastnosti delcev (gibalna količina, energija, električni aplikaciji. Na koncu so iz parametrov izluščili, pri kateri masi se naboj in identiteta delca) in vizualizirali fizikalne količine s signalna struktura nahaja in tako določili maso rekonstruiranega histogrami (slika 4). Vse nadaljnje naloge so zajemale delca. rekonstruiranje težjih kratkoživih delcev kot so mezoni 𝜙, K, D, Po zaključku delavnice smo izvedli anonimno anketo, kjer so B, … Prve tri naloge so dijaki izvedli po navodilih tutorjev in udeleženci podali kvantitativen odgovor, če se z vprašanjem tako tudi spoznali potek analize v aplikaciji, preostale naloge pa strinjajo (5) ali ne strinjajo (1), in opisni odgovor kaj jim je bilo so udeleženci reševali samostojno oz. v primeru težav so tutorji najbolj in najmanj všeč. podali namige. Naloge so si sledile po zahtevnosti od najlažje do Na vprašanje ali so bili udeleženci zadovoljni z uvodnimi najtežje. predstavitvami so se vsi strinjal (5) in na vprašanje, če so bile Prvi korak analize je bil, da so dijaki sestavili svojo “kodo” tudi razumljive, so trije odgovorili z oceno 5 in en z oceno 4. oziroma bloke, s katerimi so opisali željen razpad. Pomembno je Popoldanski praktični del je bil vsem zanimiv (5), ampak le bilo, da so pravilno izbrali končne stabilne delce, v katere je polovica jih je ocenilo, da jim je bila analiza razumljiva (5), razpadel težji delec. Ta del jim ni predstavljal večjih težav, saj so druga polovica pa so ocenili s 4. si pomagali z enačbo razpada iz navodila naloge. Dvema dijakoma sta bila najbolj všeč virtualni sprehod po Nato je sledila računsko zahtevna rekonstrukcija težjega Belle II detektorju in praktičen del analize podatkov, drugima delca na podlagi različnih kombinacij izbranih stabilnih delcev, dvema pa pogovor z raziskovalci in profesorji. En udeleženec je ki jo je izvedel centralni strežnik. Dijaki so spoznali, da redkejši še izrazil, da mu je bila najbolj všeč tudi uvodna predstavitev. Na kot je razpad nekega delca, več podatkov potrebujejo kar pa vprašanje kaj udeležencem ni bilo všeč, sta odgovorila le dva. zahteva več časa za računanje. Pri najzahtevnejšem razpadu, kjer Prvi je izrazil, da so bila predavanja dolga, drugi pa, da je, tekom so uporabili vse podatke, so lahko čakali tudi do pet minut, kar video povezave s kontrolno sobo detektorja Belle II na pa je še vedno zelo hitro v primerjavi s tipičnim časom Japonskem, potres prestrašil raziskovalca. procesiranja podatkov raziskovalcev osnovnih delcev. Slika 4: Prikaz enega izmed razpadnih kanalov. Zadnji del analize, ko so dijaki iskali signalne dogodke, jim je bil najtežji, vendar so se po dveh ali treh nalogah navadili postopka. V tem delu so morali iz porazdelitev fizikalnih količin poiskati in prešteti signalne razpade in jih ločiti od dogodkov, ki Slika 5: Analiza histograma in orodje za prilagajanje so predstavljali ozadje. Najpreprostejši način je bil neposredno funkcije. seštevanje vrednosti razdelkov v histogramu, za katerega se noben udeleženec ni odločil. Raje so uporabili bolj napredno metodo in to je prilagajanje grafa funkcije na histogram (slika 5). Metoda jim je bila na začetku dokaj tuja, saj so jo šele spoznali, in so na začetku potrebovali nekaj več pomoči s strani tutorjev. Na voljo so imeli Gaussovo in polinomsko funkcijo ter kombinacijo obeh. Gaussovo funkcijo so uporabili za opis kopaste strukture na histogramu, ta predstavlja signalne 450 VIRI IN LITERATURA [1] IPPOG - International Particle Physics Outreach Group: https://ippog.org/ [2] International Particle Physics Outreach Group, International Masterclasses: https://physicsmasterclasses.org/ [3] Belle II collaboration: https://www.belle2.org/ [4] ATLAS collaboration: https://atlas.cern/ [5] Detektor Belle II v virtualni resničnosti https://store.steampowered.com/app/810020/Belle_II_in_Virtual_Reality/ [6] Delavnica Belle II Lab https://belle2.ijs.si/public/home/reconstruct-b- mesons/ in https://belle2.ijs.si/masterclass/ [7] Delavnica barve kvarkov: https://belle2.ijs.si/public/home/quark- colors/how-many-colors-does-a-quark-come-in/ Slika 6: Zabavni kviz o fiziki osnovnih delcev in življenju na Japonskem. 4 ZAKLJUČEK Delavnice International Masterclasses so bile pri vseh sodelujočih izredno pozitivno sprejete. Čeprav je sredstvo komunikacije znotraj mednarodnih raziskovalnih skupin večinoma angleški jezik, so delavnice zaradi lažje komunikacije zasnovane v jeziku domačega okolja, na skupni videokonferenci pa uporabljamo angleščino. Večinoma sodelujoči prihajajo iz Evrope, v naslednji letih načrtujemo, da bomo delavnice izvedli tudi v ZDA in v Aziji. V načrtovanje delavnic so vključeni raziskovalci s posameznih eksperimentov, ponekod je dobrodošla podpora komunikatorjev znanost. Pomembno je, da bi bilo brez sodobnih informacijskih tehnologij takšno sodelovanje med raziskovalci in dijaki dosti težje. Ker se dijaki z raziskovanjem univerzalnih vprašanj, kot so od kod prihajamo in kam gremo, kako smo zgrajeni mi in kako svet okoli nas, kako merimo stvari, ki jih ne vidimo, v povezavi s fiziko osnovnih delcev ne srečajo vsak dan, delavnice predstavljajo pomemben prispevek k izobraževanju. 451 Uporaba portala Franček v osnovni šoli Use of the Franček Portal in Primary School Mateja Miljković OŠ n. h. Maksa Pečarja Ljubljana, Slovenija mateja.miljkovic@osmp.si POVZETEK 1 UVOD Učenci v osnovni šoli razvijajo sporazumevalno zmožnost, ki je Eden izmed temeljnih ciljev pouka slovenščine v osnovni šoli je pomemben del učnega procesa, ki se med šolanjem razvija razvijanje sporazumevalne zmožnosti. To je praktično in sistematično in načrtno, na kar vpliva tudi raba slovarskih ustvarjalno obvladovanje vseh štirih sporazumevalnih dejavnosti priročnikov. V slovenskem prostoru so že obstajala zbirna (poslušanje, branje, govorjenje, pisanje) pa tudi spletišča z jezikovnimi viri, portal Franček pa je prvo spletišče jezikovnosistemskih temeljev [1]. Sporazumevalna zmožnost in za uporabo slovarjev, prilagojeno posebej za učence in dijake. v okviru te poimenovalna zmožnost je pomemben del učnega Njegove vsebine se povezujejo s cilji in standardi učnega načrta procesa, ki se med šolanjem razvija sistematično in načrtno, na za slovenščino. V prispevku je prikazano, kako lahko učenci kar vpliva tudi raba slovarskih priročnikov. V času šolanja bi zato Frančka načrtno spoznavajo in praktično uporabljajo ter kakšna učenci morali spoznati vlogo in načine uporabe različnih je njegova širša uporabnost, ne le pri pouku slovenščine. slovarskih priročnikov [2]. Sistematična raba portala Franček že pri najmlajših učencih in Opremljenost slovenščine z jezikovnimi viri, priročniki, pri vseh šolskih predmetih učence navaja na uporabo slovarja in orodji in svetovalnimi ter podpornimi storitvami je eden ključnih drugih jezikovnih priročnikov, kar prinaša koristi za vse življenje. dejavnikov, od katerega je odvisno uresničevanje številnih ciljev jezikovne politike. Osnovno opremljenost na ravni opisa KLJUČNE BESEDE posameznega jezika predstavljata temeljni enojezični slovar in Portal Franček, sporazumevalna zmožnost, šolski slovar, učenci temeljna slovnica sodobnega knjižnega jezika, takoj za tem pa še raznovrstni specializirani jezikovni priročniki. Resolucija o ABSTRACT nacionalnem programu za jezikovno politiko 2021–2025 Students in in primary school develop communication skills, narekuje, da mora biti opis sodobne slovenščine prilagojen za which are an important part of the learning process. This process digitalno okolje in odprto dostopen. Viri morajo biti dostopni čim develops systematically and planned during schooling, being manj razpršeno. Različni primeri združenega dostopa do večjega also influenced by the use of dictionary manuals. In the past števila virov za slovenščino so na primer spletišče Fran websites with language resources existed in Slovenia, however, (https://www.fran.si/), stran z viri na spletišču Centra za the Franček portal is the first website for the use of dictionaries, jezikovne vire in tehnologije Univerze v Ljubljani adapted specifically for pupils and students. Its contents are (https://www.cjvt.si/viri-in-orodja/slovarji-in-leksikoni/), linked to the goals and standards of the curriculum for learning Predstavitveni portal spletnih jezikovnih virov za slovenščino na slovenian. The article shows how the students can get to know strani zavoda Trojina (https://viri.trojina.si/), Evroterm Franček in a planned way and use it practically. It also shows its (https://evroterm.vlada.si/evroterm) ter Termania wider applicability - not only in the lessons of slovenian. The (https://www.termania.net/). Treba je razvijati tudi podobna systematic use of the Franček portal starting with the youngest zbirna spletišča z jezikovnimi viri, prilagojenimi za posebne pupils and for all school subjects introduces students to the use ciljne skupine uporabnikov in uporabnic slovenščine, kot so of dictionaries and other language manuals - a skill, which brings šolarji ipd. [3]. Analiza učnih načrtov in šolskih gradiv je benefits for a lifetime. pokazala, da je delo s slovarji predvideno že na zgodnejših stopnjah osnovnošolskega šolanja, bolj izrazito (določeno tudi z KEYWORDS učnimi načrti) pa v tretjem triletju osnovne šole in v srednji šoli. Franček portal, communication ability, school dictionary, V preteklosti je bil na voljo edini splošni enojezični slovar students slovenščine, tj. Slovar slovenskega knjižnega jezika, ki je bil zaradi svoje akademske zasnove v marsičem neprimeren za šolsko uporabo pa tudi gradivno zastarel [2]. Nato je obdobje pospešene digitalizacije prineslo novosti v obliki spletnih Permission to make digital or hard copies of part or all of this work for personal or portalov jezikovnih virov, učitelj je lahko pri pouku uporabljal 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 npr. portal Fran, kjer so na voljo vsi temeljni jezikovni priročniki citation on the first page. Copyrights for third-party components of this work must za slovenščino. Prav posebej za učence ali dijake prilagojenega be honored. For all other uses, contact the owner/author(s). spletišča za uporabo slovarjev do nedavnega ni bilo na voljo. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 452 2 PORTAL FRANČEK (Slika 4). Črkozmed omogoča učitelju, da hitro sestavi učne liste z nalogami iz slovenskega jezika (Slika 5). Izbrati mora vrsto Na Inštitutu za slovenski jezik Frana Ramovša ZRC SAZU so ob naloge glede na učno vsebino, število primerov pri posamezni 30. obletnici samostojnosti Republike Slovenije objavili nov nalogi, lahko tudi prilagodi že dano navodilo za reševanje. Nato portal Franček (https://www.xn--franek- računalniški algoritem sestavi naloge, ki jih lahko učitelj ureja, l2a.si/grade_selection?target=%2F), ki je mlajši brat jezikovnega dopolnjuje z dodatnimi primeri ali ustvari povsem nove primere, portala Fran. Namenjen je osnovnošolcem in dijakom. Zasnovan če z danimi ni zadovoljen. Na koncu lahko učni list izvozi v pdf je tako, da omogoča razvijanje sporazumevalne zmožnosti. obliki in ga shrani na računalniku ali pa ga ima shranjenega v Vsebine, ki jih ponuja, se povezujejo s cilji in standardi v učnem aplikaciji in do njega dostopa ob vsakokratni prijavi, kjer ga načrtu za slovenščino iz leta 2018. Hkrati ustreza didaktičnemu lahko tudi naknadno ureja (Slika 6:). priporočilu, da naj učitelj pri pedagoškem delu načrtuje delo z Na koncu je dodana tudi povezava na portal Fran. informacijsko-komunikacijsko tehnologijo (IKT) in da naj vključuje kakovostne e-vsebine, med njimi tudi e-slovarje in druge jezikovne priročnike [4]. Elektronski dostop omogoča lažje in hitrejše iskanje pa tudi najrazličnejša zahtevnejša, zapletenejša in obsežnejša iskanja, s tem pa pridobivanje kvalitetnejših preglednih informacij o besedišču oziroma posameznih skupinah in množicah besed/besednih zvez [2]. Portal Franček je učencem prijazen učni pripomoček, ki predstavlja uvod v uporabo slovarja. Prav zaradi svoje raznovrstnosti je učni vir, katerega uporabo lahko učitelj načrtovano vključuje v obravnavo skozi večino učnih faz ali le v nekaterih fazah (npr. z uvodom ali zaključno ustvarjalno nalogo), še posebej ob ciljih, povezanih z razvijanjem poimenovalne, pravopisne in pravorečne pa tudi metajezikovne zmožnosti. Tako zaradi svoje vsebinske zasnove, ki omogoča večrazsežnostni pogled na izbrano geslo, kot zaradi prilagojenosti osnovno- in srednješolskemu naslovniku odpira številne nove možnosti neposredne uporabe pri pouku, ki jih dosedanji elektronski viri niso ponujali. Na besedo ne gleda le s stališča pomena in oblike, Slika 1: Iskalnik za skupino 6.–9. razred temveč se s predvidenimi položaji, v katerih jo uporabljamo, dotika tudi okoliščin oz. funkcije besede v njih, hkrati pa jo ob primerjavi z narečno rabo ter ob možnostih raziskovanja njenega izvora postavlja v širše prostorske in časovne jezikovne razsežnosti [4]. Vsebine na portalu so prilagojene starosti in jezikovnim zmožnostim učencev in dijakov. V skupini 1.–5. razred lahko učenci iščejo, kaj pomeni določena beseda, katere so besede s podobnim pomenom, kako pregibamo to besedo, in poslušajo, kako to besedo izgovarjamo v knjižnem jeziku. Ogledajo si lahko tudi podobne besede. V skupini 6.–9. razred učencem poleg že naštetih možnosti Franček ponuja še poizvedovanje po frazemih, v katerih nastopa iskana beseda, izvoru besede, času Slika 2: Kje je kaj v slovnici? začetka uporabe besede. Učenci lahko izvejo, kako se beseda uporablja v drugih narečjih, pogledajo na zemljevidu, kje govorijo tako, ponujena pa jim je tudi interaktivna možnost, da sami posnamejo svojo narečno različico in jo pošljejo prek povezave. Prav tako si lahko ogledajo podobne besede (Slika ). Enako je tudi v skupini srednja šola, le ikone so manj otroške. Portal nam poleg osnovnega iskanja ponuja še spoznavanje jezikovnih značilnosti, če kliknemo na povezavo Kje je kaj v slovnici? . Tu so narejene povezave na šolski slovnici Slika 3: Še več možnosti Kratkoslovnica (za osnovno šolo) ter Slovnica na kvadrat (za srednjo šolo) in vsebine, ki jih v njiju lahko najdemo (Slika 2. Slovnici opisujeta sodobni knjižni jezik [5]. To pa še ni vse. Pri vsaki temi si lahko ogledamo pogoste napake, vzete s korpusa Šolar. To je korpus besedil z učiteljskimi popravki, ki so jih učenci slovenskih osnovnih in srednjih šol samostojno tvorili pri pouku. V nadaljevanju lahko vidimo vsebine na izbrano temo, ki so se pojavile v jezikovni svetovalnici. Na voljo so tudi učni listi z vajami in rešitvami (Slika 3). Portal vsebuje tudi Jezikovno svetovalnico za učitelje, kjer so Slika 4: Jezikovna svetovalnica za učitelje zbrana vprašanja in odgovori na jezikovna vprašanja, po katerih lahko brskamo ali s pomočjo obrazca zastavimo novo vprašanje 453 3 FRANČEK PRI POUKU SLOVENŠČINE Učenci so že poznali portal Fran in ga uporabljali. Zlasti v sedmem razredu se v skladu z učnim načrtom podrobneje seznanijo z jezikovni priročniki, posebej s slovarjem slovenskega knjižnega jezika. Z zanimanjem pa so sprejeli novo pridobitev na področju jezikovnih virov, ki je prilagojena posebej njim in s tem enostavnejša za uporabo ter bolj všečna. Najprej jim Frančka predstavim in izpostavim možnosti, ki jih ta ponuja, nato ga Slika 5: Črkozmed raziskujejo sami. Po lastnem izboru v okviru že usvojene snovi in možnosti, ki jih Franček ponuja, jim pripravim naloge, ki zavzamejo širok nabor možnosti uporabe portala, ki jih lahko sami praktično preizkusijo in se tako seznanijo s Frančkom (Slika 9). Učenci s pomočjo slovarja odkrivajo pomene neznanih besed, odkrivajo, koliko pomenov ima določena beseda, ugotavljajo izvor besed, iščejo sopomenke in si z njimi pomagajo pri odpravljanju ponavljajočih besed v že obstoječem besedilu ali pri tvorjenju le-tega. Lahko si pomagajo pri pregibanju besednih vrst ali pri ugotavljanju lastnosti besed. V besedilu odkrivajo pravopisne napake in jih odpravljajo. V pomoč so jim posnetki izgovorov, npr. pri ugotavljanju mesta naglasa v besedah. Odkrivajo frazeme, njihov pomen in s pomočjo slovarja naštevajo nove. S pomočjo povezave na slovnico, prilagojeno za osnovnošolsko raven, lahko prikličejo v spomin in ponovijo določene že obravnavane slovnične vsebine. To je samo nekaj primerov pri načrtnem spoznavanju novo Slika 6: Primer nalog, ustvarjenih z aplikacijo Črkozmed. nastalega portala Franček, pri katerem učenci urijo poimenovalno, pravopisno, slovnično, slogovno in 2.1 Besedoboj metajezikovno zmožnost. Učitelj lahko pripravi še več nalog Dodatek k portalu Franček je aplikacija Besedoboj, ki si jo lahko različnih zahtevnosti ali za utrjevanje snovi uporabi že naložimo na pametne naprave (Slika 7). To je jezikovna igra, v pripravljene, ki jih portal ponuja na mestu, kjer si o izbrani temi kateri se pomerimo z iskanjem besed, ki se končajo ali začnejo lahko več preberemo v slovnici (Slika 8). Frančka je smiselno na določeno črko, besed, ki imajo več kot 6 črk, besed, ki so uporabljati tudi naključno pri sprotnih jezikovnih in pomenskih samostalniki ipd. Tekmujemo lahko z znanimi umetniki, kot so dilemah, tako pri jezikovnem kot književnem pouku, pri France Prešeren, Ivan Cankar, Lili Novy, Valentin Vodnik, tvorjenju in sprejemanju besedila, in sicer že pri najmlajših Zofka Kveder, Srečko Kosovel, ali z naključnim resničnim učencih, ki jim je ta posebej prilagojen. Na tak način bodo učenci nasprotnikom iz omrežja. Igre se med seboj razlikujejo po načinu seznanjeni s slovarjem in njegovo zgradbo, hkrati pa bodo igranja in stopnji težavnosti. Neznane besede si lahko ogledamo ponotranjili pripomoček, ki jim bo tudi kasneje v pomoč pri na portalu Franček, do katerega je narejena povezava. V igri razreševanju jezikovnih težav. zbiramo cekine, ki jih lahko vložimo v nakup modnih dodatkov Učence za konec povabim k igri Besedoboj, ki bi jo lahko za svoj lik v aplikaciji [6]. za popestritev kljub prepovedi uporabe telefonov odigrali tudi pri pouku na šolskih tablicah. Slika 8: Že pripravljene vaje Slika 7: Besedoboj 3.1 Širša uporabnost Frančka Franček je s svojim slovarjem uporaben tudi pri drugih šolskih predmetih, ne samo pri slovenščini, in sicer pri odkrivanju pomena neznanih besed z različnih predmetnih področij, ki jih 454 pokriva. Poleg tega skrb za slovenščino in bralna pismenost nista le stvar učitelja slovenščine, zato bi morali vsi učitelji spodbujati k uporabi slovarja in slovnice in s tem k učinkovitejši rabi strokovnega jezika in k poglabljanju splošne sporazumevalne zmožnosti [7]. Raba jezikovnih portalov, kot je Franček, pri pouku različnih predmetov pripomore k boljšemu in globljemu razumevanju snovi, hkrati pa prispeva k širjenju besedišča. Ta vpliva na učenčev uspeh in večjo bralno pismenost. Lahko je v pomoč učencem z izrazitejšimi narečji. Kadar učitelj opazi, da učenci določeno besedo izgovarjajo drugače, kot je v knjižnem jeziku, jih lahko spodbudi, da sami preverijo izgovor v slovarju [4]. Franček je uporaben tudi pri pouku na daljavo, pri katerem je manj interakcije med učiteljem in učenci. Ti lahko sami poiščejo razlage določenih novih pojmov, ki jih usvajajo pri pouku, ali tistih, ki so jim neznani. Prav tako pa je pri delu na daljavo ali v učilnici koristen tudi za učence, ki jim je slovenščina drugi oz. tuji jezik, saj jim poleg opisanega pomena besed omogoča tudi poslušanje pravilnega izgovora, preverjanje pravilnih oblik pri pregibanju različnih besednih vrst ali drugih jezikovnih lastnosti v šolski slovnici. Pri posamezni temi, razloženi v slovnici, so jim na voljo tudi preproste vaje z rešitvami. 4 ZAKLJUČEK V slovenskem prostoru do sedaj nismo imeli podobnega jezikovnega vira, prilagojenega posebej za osnovno- in srednješolce. Zlasti ne za najmlajše učence. Mladi dandanes odraščajo v svetu digitalizacije in pametnih naprav, ki jim v vsakem trenutku ponujajo na stotine bolj ali manj relevantnih informacij ter različnih oblik animacije in zabave. Knjižnih virov se poslužujejo vedno manj. Franček jim na simpatičen in všečen način približa orodje, ki jih uvaja v svet spletnih jezikovnih virov, ki so zamenjali slovarje in priročnike v fizični obliki. Če se bodo učitelji različnih predmetnih področij zavzeli za njegovo sistematično in načrtno uporabo, ga bodo učenci ponotranjili in bili deležni koristi, ki jim ta prinaša. Tako bodo tudi v odrasli dobi posegali po zapletenejših virih, ki jim bodo ponujali odgovore na njihove jezikovne dileme. LITERATURA IN VIRI [1] Učni načrt za slovenščino. 2018. Ljubljana: Zavod Republike Slovenije za šolstvo. [2] Stabej, M. idr. 2008. Jezikovni viri pri jezikovnem pouku v osnovni in srednji šoli. Dostopno na naslovu: https://www.trojina.si/wp- content/uploads/2019/08/StabejRozman.pdf (5. 7. 2022) [3] Resolucija o nacionalnem program za jezikovno politiko 2021–2025 (ReNPJP21–25). 2021. Dostopno na naslovu http://www.pisrs.si/Pis.web/pregledPredpisa?id=RESO123# (5. 7. 2022) [4] Strateški dokument na področju prožnih oblik učenja. 2021. Dostopno na naslovu https://www.scv.si/wp- content/uploads/2021/09/Strateski_dokument_prozne_oblike_ucenja_cistop is.pdf (5. 7. 2022) [5] Ahačič, K. (2018). Kratkoslovnica. Ljubljana: Založba Rokus Klett [6] Ahačič, K. (2018). Slovnica na kvadrat. Ljubljana: Založba Rokus Klett. [7] O igri besedoboj. Dostopno na https://www.youtube.com/watch?v=GfawzDcKAF8 (8. 7. 2022) [8] Franček, kaj pa slovnica pri matematiki? Dostopno na https://sio.si/2020/05/11/francek-kaj-pa-slovnica-pri-matematiki/ (25. 7. 2022) Slika 9: Učni list z vajami za spoznavanje Frančka 455 Kvalitetno učenje na daljavo – izziv za učitelja in učenca Quality Distance Learning – A Challenge for Teacher and Student Miroslava Minić IV. osnovna šola Celje, Slovenija mira.minic@facka.si POVZETEK Within the education system, solutions must be found to compensate for the shortcomings of distance learning, which Ta prispevek predstavlja priložnosti, kot tudi kritičen pogled na mainly refers to the reduced possibility of children's socialization. družbeno situacijo v kateri smo se znašli učitelji osnovnošolskih This year, our elementary schools already had good programov skupaj z našimi učenci ob pandemiji COVID-19, ki communication channels established and a number of ICT tools jo je povzročil korona virus in ki je zmotila normalno delovanje available to promote student participation in the form of virtual vseh družbenih sistemov ter tako tudi posledično zapletla classrooms and other tools available to us in them. Despite this, dogajanja v izobraževalnih osnovnošolskih procesih. many students (students, teachers, parents) are still dissatisfied, Znotraj izobraževalnega sistema je treba poiskati rešitve za learning results are not always satisfactory. There are problems nadomestitev pomanjkljivosti učenja na daljavo, kar se nanaša of not knowing how to use the tools or, in general, various predvsem na zmanjšano možnost socializacije otrok. V tem letu reasons why the participants of the learning process cannot or do smo osnovne šole imele že vzpostavljene dobre komunikacijske not dare to try to navigate the virtual environment. kanale in na voljo številna IKT orodja namenjena pospeševanju Therefore, in addition to presenting potential problems that sodelovanja učečih v obliki virtualnih učilnic in drugih orodij, teachers or students may encounter in their work in distance ki so nam v njih na voljo. Kljub temu je veliko učečih (učenci, education, in the paper I also offer suggestions for solving these učitelji, starši) še naprej nezadovoljnih, učni rezultati niso vedno problems, which I tried to collect together with my colleagues zadovoljujoči. Pojavljajo se problemi ne poznavanja uporabe and students in the form of infographics. orodij ali na splošno različni vzroki zakaj deležniki učnega procesa ne morejo ali si ne upajo poskusiti krmariti po virtualnem KEYWORDS okolju. Distance learning, primary education, students, teachers, digital Zato poleg predstavljanja morebitnih težav, na katere lahko tools naletijo učitelji ali učenci pri svojem delu pri izobraževanju na daljavo v prispevku ponujam tudi predloge za reševanje teh težav, ki sem jih skupaj s svojimi sodelavci in učenci poskusila 1 UVOD zbrati v obliki infografik. Izobraževanje na daljavo je spletno učenje, lahko mu rečemo tudi e-izobraževanje. Gre za učenje na daljavo, učenje preko KLJUČNE BESEDE interneta, učenje v virtualnih učilnicah ... Na prvi pogled se sliši Pouk na daljavo, osnovnošolsko izobraževanje, učenci, učitelji, zelo dobro načrtovano, vendar se postavlja vprašanje, koliko digitalna orodja učencev in učiteljev se dejansko potrudi ... Je učenje na daljavo prezahtevno? Ali vsi preživimo enako časa s knjigo kot prej? ABSTRACT Koliko časa, truda in živcev je bilo dejansko vloženega v This contribution presents opportunities, as well as a critical view določene naloge in projekte? Ali vsi učenci, kot tudi učitelji pri of the social situation in which we found ourselves as teachers of zastavljanju določenih nalog, delajo enako dobro ali nekateri elementary school programs together with our students during delajo malomarno? Kaj bo potem, ko se učenci vpišejo v srednje the COVID-19 pandemic, which was caused by the corona virus šole? Kakšna znanja bodo učenci odnesli naprej? Kaj je smisel and which disrupted the normal functioning of all social systems, tovrstnega poučevanja? Kaj bodo pridobili učenci prve triade, ki and thus also as a result complicated events in educational ob vstopu v osnovnošolske klopi šele začnejo oblikovati svoje primary school processes. delovne in socialne navade, kaj šele, da se prebijajo skozi izzive virtualnih nalog. Ali učitelji morajo delovati timsko pri zahtevah do učencev in ali lahko popolnoma ohranijo svoj individualizem pri podajanju snovi, zastavljanju nalog … Katera orodja in Permission to make digital or hard copies of part or all of this work for personal or metode naj uporabijo, da bo pouk na daljavo kakovosten za vse 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 (Slika )? 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 456 Slika 1: Učenec v središču [2] 2 NAČRTOVANJE POUKA Pri študiju na daljavo se razvijajo številne kompetence učencev. Podobno bi lahko rekli tudi za učitelje. Učeči sam ureja svoje učenje in organizira svoj čas (odloči se kdaj, koliko in na kakšen način se bo učil). Učenec se samostojno uči, raziskuje s samostojnim učenjem in z iskanjem informacij na internetu. Učenec se nauči kako poiskati informacije, ki jih potrebuje in na kakšen način mu najbolj ustreza. Ta koncept poučevanja spodbuja raziskovanje in študij ter strukturiranje v smiselno celoto. Razvija se učenčeva digitalna kompetenca, učenec se nauči poiskati informacije, ki jih potrebuje. V tem procesu uporabimo jezik kot orodje, ki lahko pomaga pri gradnji znanja posameznega učenca, zavedajoč se, da si vsak ustvari svoje znanje glede na njegove izkušnje [1]. Spodbujajo se tudi raziskovalne sposobnosti učečih, tehnične veščine in sposobnosti kritične analize. Učitelj je tudi pred izzivom: kaj želi, da učenci znajo, kako bodo dosegli načrtovane cilje, kako bodo merili in preverjali doseganje zastavljenega, kako bodo vključili učeče strukture in katera orodja bodo ustrezna? Tudi učitelj mora poiskati kakovostne podatke, ki jih bo posredoval učečim. Podatke mora pravilno in primerno oblikovati. Temelj učiteljevega dela je dobra komunikacija in dobro vzpostavljeni komunikacijski kanali (Slika ). V osnovni šoli je vsekakor pomembna kakovostna komunikacija tudi s starši. Učitelj k pouku na daljavo predvsem mora pristopiti brez predsodkov, izvajati na učečega usmerjen pouk in vsekakor poiskati dobra in ustrezna orodja za izvedbo takšnega pouka. 3 ORGANIZACIJA POUKA 3.1 Pogled učečega Kaj pa učenci menijo o tovrstnem konceptu poučevanja, ali se Slika 2: Učna okolja in učni pripomočki [3] sploh zavedajo njegovih prednosti? Ko učence vprašamo, kaj menijo o pouku na daljavo, bodo skoraj vsi odgovorili, da sploh No, za začetek, pri pouku na daljavo (govorim predvsem o ni zadovoljiv, da je prezahteven in da jim vzame preveč časa. Kaj osnovnih šolah) večinoma učencev nismo dovolj privzgojili se pravzaprav skriva za vsemi temi informacijami? takšnega samostojnega načina dela. Roko na srce, v osnovni šoli je to zelo zahtevno. Osnovna šola je sama po sebi zelo pomembna prelomnica za naše najmlajše. Ob vstopu v osnovno šolo se večinoma otroci prvič soočajo z nalogami organizacije samega sebe, lastnega časa in dela (sedenje, pisanje, poslušanje, organiziranje zvezka, delovnih navad …). In kaj se dogaja v slovenskih šolah? V času, ko je pandemija COVID-19 motila normalno delovanje vseh družbenih sistemov se je izobraževalni sistem čez noč preselil na splet in pričakovalo se je od učiteljev 457 in učečih, da te osnovne veščine poizvedujejo na daljavo. Učenci morajo predelati snov, ki bi jo sicer razložili učitelji v šoli, sami pa bi le prepisali »nekaj zapiskov« s table v svoje zvezke. Učeči trdijo, da je nalog veliko, a če bi vsi dobili natančna navodila, razlago in ustrezna učna gradiva, bi jih hitro in lažje končali, pa tudi več naučili. Vsekakor se več časa porabi za samostojno učenje iz učnih gradiv, a razlog za to je ravno samostojno učenje. Ne smemo pozabiti, da pri običajnem pouku tudi domače naloge samostojno delamo doma. Koliko so pri tem otroci uspešni in ažurni danes? Statistika delanja domačih nalog je v osnovnem šolstvu zadnja leta vse slabša. Opozorimo, da na kvalitetno učenje vpliva še efektivno izkoriščen čas, v katerem smo fizično prisotni dopoldan na šoli napram spremljanju pouka na daljavo po video konferenci. Večina mlajših učencev osnovnih šol še niso vajeni rutin učenja, ker šele pridobivajo te veščine in posledično težje delajo na daljavo. Za učence drugega in tretjega triletja pri šolskih nalogah in projektih se zahteva veliko, vendar se učitelji trudijo Slika 3: Učenec in pouk na daljavo [2] čim bolje razložiti, kako delati. Pri testih je majhna težava. Najpogosteje odličnjak iz razreda prvi reši test in pošlje rešitve 3.2 Pogled učitelja ostalim v razredu. Na ta način učenci, ki običajno nimajo Priča smo, da so se šole ob izbruhu epidemije in ob pojavu odličnih ocen, uspejo izboljšati svoje povprečje, a kljub temu ne nujnega prehoda na izobraževanja na daljavo hitro znašle – razumejo ničesar. Pogosto se vsi iz razreda povabijo preko organizirale so dodatne sestanke in vzpostavile najprej zasilna, določene spletne klepetalnice in tako rešujejo test - skupinsko. potem ustrezna spletna okolja in spletna orodja, prisluhnile in Domače naloge pa odličnjaki pišejo in pošiljajo drugim (Slika ). upoštevale nasvete in modele različnih pomembnih inštitucij Ostali le malo spremenijo koncept in ga pošljejo učiteljem. (MIZŠ, ZRSŠ), kot tudi različne inštitucije s katerimi je šola v Nekateri učitelji sploh ne pogledajo kaj učenci pošljejo in to nenehnem ozkem sodelovanju. Osnovna šola je morala vedoč, učenci potem pošljejo enako domačo nalogo nekoga upoštevati navodila mestne občine, kot šolsko ustanoviteljico, drugega. Zato učenci niti ne poskušajo prepisovati, samo pošljejo ter tudi prisluhniti navodilom NIJZ, kot tudi podjetjem vezanim tujo domačo nalogo s slikami. Ko pridemo do nacionalnega na šolski sistem, kot so easistent, Microsoft, različne založbe – preverjanja znanja na koncu šolskega leta smo splošno v zagati ponudnice e-gradiv in pripomočkov... Učitelji so poleg časovno in učitelji in učenci. Starši, kot tudi en izmed pomembnih in organizacijsko zahtevnega izvajanja pouka na daljavo bili deležnikov šolskega sistema postanejo razburjeni do skrajnosti pahnjeni še v nenehna izobraževanja in različne IKT projekte od ali popolnoma nezainteresirani in indiferentni. Prvi so takšni, ker strani omenjenih inštitucij ali različnih tržnih ponudnikov. bi želeli vplivati in pomagati, vendar ne vidijo globlje sistemske Zanimivo je, da so najbolj uporabljena digitalna orodja v napake, zaradi katerih to žal ni možno. Vsaj ne na način, kot bi šolah po večini PowerPoint, Wordwall, Kahoot, online orodja iz oni želeli, ker je pogosto njihova gonilna sila le lastni interes. Microsoft paketa o365 ter komunikacijska digitalna orodja Drugi pa so indiferentni zaradi nepoznavanja, ki ga priznajo ali Microsoft Teams, Gmail (Google) in Zoom srečanje, medtem, ko zaradi primanjkljaja časa, socialnih in drugih razmer ipd. veliko število drugih digitalnih orodij še vedno ostaja Pouk na daljavo ima svoje prednosti, a tudi slabosti. Za neizkoriščenih (Slika 4). učence, ki sicer delajo samostojno in vložijo veliko truda, živcev, energije in časa za opravljanje nalog, je to samo dodatek za nadaljnje izobraževanje. Ti učenci bodo lažje spremljali pouk v srednji šoli, v morda težjih in zahtevnejših razmerah, kasneje v življenju se bodo lažje spopadali s težkimi situacijami. Tisti učenci, ki delajo po »starem sistemu« – s prepisovanjem in goljufanjem, si delajo medvedjo uslugo in bodo v zahtevnejših razmerah težje sledili snovi, pri nadaljnjem izobraževanju pa se bodo izgubili. Pred kakšne izzive je po drugi strani postavljen učitelj? Slika 4: Načrtovanje in organizacija pouka na daljavo [2] 458 4 ZAKLJUČEK ZAHVALA Pouk na daljavo vsekakor poglobi učenčeve in učiteljeve Zahvaljujem se sodelavcem na IV. osnovni šoli, ki so me v sposobnosti in spretnosti, le malo dobre volje je treba imeti za prejšnjem šolskem letu toplo sprejeli v svoje vrste, kot delo. Največje prednosti takšnega dela so izključno učenje zase, pomočnico ravnateljice in učiteljico matematike in urejanje lastnega učnega procesa in razvijanje učnih kompetenc računalništva. Zahvala tudi gre mojim učencem, ki so mi v tem (Slika ). Nekje vmes pa se je zataknilo pri razvoju etičnih šolskem letu pomagali s svojimi mnenji glede epidemije in kompetenc in moralnih vrednot, kar pravzaprav vodi v glavni prispevali nastale inografike [2, 3]. problem naše družbe, to je, da se učenci učijo za ocene, ne zase in za življenje. Menim, da je ta koncept težko spremeniti in LITERATURA IN VIRI zagotovo izhaja večinoma iz močnih pričakovanj sodobnih [1] Hua Liu in Matthews, 2005. Vygotsky's philosophy: Constructivism and its staršev in družbenega okolja. criticisms examined. International Education Journal 6(3), 386-399 [2] Inografike učencev IV. osnovne šole, 2022. Dostopno na povezavi: https://www.easel.ly/infographic/xl5iti [3] Inografike učencev IV. osnovne šole, 2022. Dostopno na povezavi: https://www.easel.ly/infographic/r3aw80 459 KIZ na prostem KIZ Outdoors Tina Mlakar Gimnazija Moste Ljubljana, Slovenija tina.mlakar@gmoste.com POVZETEK outdoor learning in the form of research and discovery. I imagined a circular learning path that takes students around V osnovnih in srednjih šolah izvajamo tudi pouk Knjižnično Ljubljana past different types of libraries (school, general, informacijskih znanj. Gimnazije imajo določeno število ur, ki se special, university, national library), archives, printing houses izvedejo v tem sklopu in za organizacijo ter izvedbo ponavadi and similar institutions. The added value of the activity is that poskrbijo knjižničarji in učitelji informatike. Ta znanja se some of the locations are also content-related to the lessons povezujejo tudi z digitalno pismenostjo in so pomembna, da taught at school (printing with movable letters, Cobiss). The aim znamo priti do informacij in podatkov, ki jih iščemo. Ker je bilo of the whole activity is also to familiarize the first-year students šolsko leto 2021/22 še vedno nesigurno zaradi covida, smo with the urban surroundings of the school, since many students predvsem razmišljala kako naj zasnujemo dejavnosti, na način, come from suburban areas. da se bodo lahko izvedle kljub omejitvam. Seveda tako, da bodo dejavnosti načrtovane in izvajane na prostem, tako da se lahko KEYWORDS izvedejo tudi samostojno. Zato sem se odločila za uporabo aplikacije. Torej poskušala sem združiti Knjižnično Library information skills, information literacy, ICT, outdoor informacijska znanja z učenjem na prostem v obliki raziskovanja learning in odkrivanja. Zamislila sem si krožno učno pot, ki pelje dijake po Ljubljani mimo različnih tipov knjižnic (šolska, splošna, 1 UVOD specialne, univerzitetne, narodna knjižnica), arhiva, tiskarne in podobne ustanove. Dodana vrednost aktivnosti je ta da so Ure knjižnično informacijskih znanj (KIZ) so del nekatere lokacije vsebinsko povezane tudi z urami, ki se izvajajo gimnazijskega kurikula [2,3], ki jih izvede šolski knjižničar in v šoli (tiskanje s premičnimi črkami, Cobiss). Cilj celotne učitelj informatike. Ponavadi se izvedejo v obliki predavanja v dejavnosti je tudi ta, da se dijaki 1. letnika seznanijo z mestno učilnici in vsebujejo iskanje informacij ter navajanja virov, okolico šole, saj veliko dijakov prihaja iz primestnih območij. uporabo Cobissa, predstavitve različnih tipov knjižnic, zgodovino knjižnic, seznanitev z UDK sistemom ipd. KLJUČNE BESEDE Kot mnogi učitelji smo iskali način kako bi ure izvedli drugače brez videokonferenčnega okolja, tako, da bi bile za Knjižnično informacijska znanja, informacijsko opismenjevanje, dijake zanimive in da bi pridobili vsaj del teh znanj. To smo pouk na prostem, IKT izvedli z uporabo aplikacije CŠOD Misija [1], kamor lahko ABSTRACT vnašamo različne raziskovalne učne poti. Uporabnik si naloži aplikacijo in izbere učno pot, pri čemer se mu odpre zemljevid In primary and secondary schools, we also teach Library točk, ki jih mora obiskati. Šele ko je posameznik na sami lokaciji Information Skills. Gymnasiums have a certain number of hours točke, to aplikacija zazna in mu dovoli reševanje izziva. Z that are held in this group, and librarians and IT teachers usually reševanjem izzivov uporabnik pridobiva znanja in pa točke, ki se take care of the organization and implementation. These skills seštevajo. Aplikacija je v dveh jeziki, angleškem in slovenskem are also connected to digital literacy and are important to know jeziku, slednje se mi zdi za šolski prostor pomembno. Tudi how to get to the information and data we are looking for. Since oblikovno je aplikacija zelo lična, pregledna in preprosta za the 2021/22 school year was still uncertain due to covid, we uporabo. Naj še omenim, da je prednost aplikacije, ki omogoča, mainly thought about how to design activities in such a way that da je zemljevid naložen tako, da se lahko uporablja na they can be carried out despite the restrictions. Naturally, the brezpovezavni način. activities will be planned and carried out outdoors, so that they V nadaljevanju bom aplikacijo bolj podrobno predstavila can also be carried out independently. That's why I decided to skozi lasten konkreten primer, saj sem jo uporabila za izvedbo use the app. So I tried to combine library information skills with KIZ na način, da sem pripravila učno pot po mestnem središču. Permission to make digital or hard copies of part or all of this work for personal or Priprava vsebinskega dela (ideje, besedilo, video in avdio classroom use is granted without fee provided that copies are not made or distributed gradivo) je vzelo veliko časa, zatem pa je prišlo še vnašanje v for profit or commercial advantage and that copies bear this notice and the full aplikacijo ter postavitev koordinat točk. 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 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 460 2 UČNA POT KIZ Za reševanje izzivov dobijo različne namige, ki jih pregledujejo. Kot prikaže Slika 3 so to fotografije (ob kliku Aplikacija, ki smo jo uporabili omogoča vnos učnih poti, galerijo se odpre še več slik z opisom, kamor lahko tudi skrijemo tako imenovanih »misij«. Misije so lahko treh različnih tipov, odgovor), avdio (po želji dodamo zvočni posnetek, ki ga seveda uporabili smo tip raziskovanja, kar pomeni, da so vse točke na sami posnamemo), besedilni opis. Tudi uporaba spleta je zemljevidu že vnaprej vidne. Postavila sem jo pod skrito kodo, dovoljena pri iskanju odgovora, ni pa nujna. katero so dijaki vtipkali v iskanje misije in so si jo naložili, kot prikazuje slika 1. Slika 1: Prenos misije po korakih Začetna točka je bila postavljan na terasi naše šole, prikaz na sliki 2. To je bila nekako uvajalna točka, da se dijaki sprva seznanijo z aplikacijo, saj je vsebovala razlago poti v besedi, slike, zvočni posnetek in vse tipe nalog izzivov, s katerimi se bodo srečali na učni poti. Slika 3: Primer informacij, ki jih lahko vnesemo v aplikacijo Centralna tehniška knjižnica in Cankarjev spomenik se nahajata na isti ploščadi. Pri obisku CTK sem bila previdna, zato sem naloge oblikovala tako, da ne zahtevajo vstopanja v prostore knjižnice, da nebi ogromno število dijakov motilo obiskovalce pri učenju. Prav tako je za takšne vstope dobro pridobiti soglasje vodstva in opozoriti zaposlene. Enake pomisleke sem imela pri točki MKL, vendar sem ocenila, da je splošna knjižnica bolj odprta in pretočna z obiskovalci, zato sem izzive postavila tudi znotraj knjižnice. Tukaj so se dijaki sprehodili med police, v čitalnico, ter v kletno nadstropje mediateke. V opisu točke sem Slika 2: Prva točka nas seznani z aplikacijo predstavila UDK sistem in ga ponazorila s primeri, pri izzivu pa so sami poiskali polico na strokovnem oddelku in vpisali številko Vsega skupaj smo pripravili 17 točk, ki so jih dijaki obiskali UDK-ja v odgovor. Za izziv v čitalnici sem na uporabila revijo, in so sestavljale kar obsežen sprehod skozi mesto: Medicinska ki je tisti mesec ravno izšla, naloga pa je spraševala po naslovu knjižnica, Semenišče, Trubarjeva Hiša literature in Tromostovje, revije, katere beseda je sopomenka izrazu edinstven, enkraten Blaznikova tiskarna in Tiporenesansa, Arhiv Slovenije, NUK, (gre za revijo Unikat). Sprehodili so se tudi pri leposlovju in Cankarjev spomenik in Centralna tehniška knjižnica, Trubarjev poiskali avtorja, ki se začenja na črko M, primer izziva je spomenik, Mestna knjižnica Ljubljana Otona Župančiča, ponazorjen na Sliki 4. Kinoteka z mediateko in Muzejska ploščad. Za vsak slučaj sem vse namige do rešitev skrila tudi v Z začetno točko sem jih seznanila z različnimi načini kjer galerijo (vkolikor kateri od dijakov nebi mogel vstopiti v lahko pridobijo namige za reševanje izzivov, seveda pa so knjižnico, zaradi morebitnega pogoja PCT). Pri MKL sem tudi nekateri izzivi zahtevali pridobivanje informacije iz okolja uspela pridobiti tudi privolitev vodstva, ki so z obiskom dijakov lokacije same. Takšen primer je bila točka Semeniške knjižnice, seznanili zaposlene. Končna točka je bila na Muzejski ploščadi, ki se nahaja v samem centru mesta na tržnici. Ob vhodu v kjer sta dijake pričakala profesorja, da sta vodila seznam Semenišče je obokan portal, ki vsebuje več okrasnih in kiparskih prisotnosti. elementov. Iz tega so morali dijaki prepisati napis, ki je uokvirjen nad vrati v latinščini. Prav tako so morali poiskati detajl na kljuki, kjer je ikona škofa, ki v rokah drži predmet (knjigo). 461 učitelje na dan izvedbe, ter nenazadnje zaupanje za novo aktivnost. Pred izvedbo aktivnosti smo pripravili tudi navodila za dijake in za učitelje. Dijake in njihove starše sem že vnaprej obvestila o uporabi aplikacije za šolske namene, namreč nekaterim so morali starši odobriti nalaganje nove aplikacije, saj so imeli zaklenjen telefon. Razporeditev učiteljev je bila premišljena glede na časovne okvire obiska točk. Predvidevala sem približen čas ko bodo dijaki prehajali preko lokacij in tako razporedila učitelje. To se ni vedno izšlo, saj niso vsi ubrali predvideno krožno pot. Dijaki so imeli za končanje učne poti na boljo pribl. 2 uri časa in še dodatne pol ure za vrnitev na šolo. Želela bi si da bi s tega dne imeli več fotografij, vendar sem jih uspela dobiti le nekaj. Sama sem pri pošiljanju skupin s prve točke imela polne roke dela in zato nisem uspela obiskati točk na terenu ob samem poteku aktivnosti. V splošnem smo z izvedbo zadovoljni, so se pa ob tem pojavile nekatere posebnosti, ki so smiselne za upoštevanje pri načrtovanju takšne aktivnosti v prihodnje. Slika 4: Oddelek leposlovja, iščejo avtorja Murakami 5 ZAKLJUČEK 3 ZNAČKA KIZ Prva stvar, ki smo se jo naučili je, da vsak projekt in dejavnost, Pri reševanju izzivov se točke seštevajo za pravilne odgovore in ki se jo lotimo, v pripravah vzame veliko več časa kot je tudi odštevajo za nepravilno vnesene odgovore, kot lahko vidimo načrtovano, saj vmes pridejo nepredvideni zapleti. Prav tako je na sliki 5. Tako dijak nabira točke in ob določenem seštevku težko planirati koliko časa bo posameznik potreboval za izvedbo prejme značko. Izgled značke in opis uredimo sami, v našem učne poti, zato je najbolje, da zadevo rešujejo samostojno brez primeru sem izbrala ikono knjige in oblak. Značka je tudi služila nadzornih učiteljev in brez omejenega časa. To nas pripelje do preverjanju opravljene poti. naslednjega razmisleka, in sicer preverjanje opravljene misije. Namreč v ozadju aplikacije ne vidimo kdo od dijakov se je registriral in opravil misijo, zato smo preverjali pridobljene značke na telefonih. Pri tem smo pazili, da niso prikazovali zaslonske slike sošolcev, ali da si niso izposodili telefon od nekoga, ki je misijo opravil in ga prinesli v vpogled. Pri slednjem nismo imeli vpliva, tako so zamudniki lahko »goljufali«. Zadrego sem tudi sporočila na oblikovalce aplikacije in zagotovili so mi, da bodo uredili v prihodnje pregled nad opravljanjem misije, kar nam bo močno olajšalo samostojno izvedbo z manj nadzornimi učitelji. Na učno pot smo razporedili pet učiteljev. Na začetni in končni točki v mestu naj bi preverjali prisotnost dijakov. Sicer pa so nadzorni učitelji imeli nalogo, poleg vodenja seznamov dijakov na točkah imeli tudi vlogo pomoči in usmerjanja, če se jim je kje zataknilo ali če niso dobro poznali mesta. Nadzorni učitelj pri MKL je usmerjal in pomagal dijakom, saj so imeli tam kot predvideno največ vprašanj. Idealno bi bilo, da bi vsi nadzorni učitelji prej že opravili celotno pot in bi poznali Slika 4: Sprotno seštevanje levo in pridobljena značka aplikacijo ter potek, vendar tega vsi niso mogli zagotoviti, smo desno jih pa seveda podrobno informirali o točki na kateri so se nahajali in kakšne izzive skriva. 4 IZVEDBA KIZ NA PROSTEM Nepredvideno se je zgodilo, da so se nekateri dijaki kljub navodilu h kateri točki naj se napotijo v mestu, odpravili v drugo Dijaki so učno pot opravili na predviden dan v načrtovanem času smer krožne poti ali pa celo »cik-cak«, zato so se z nadzornimi in ne v svojem prostem času. Začeli so na šoli in so imeli 3 ure učitelji zgrešili, saj se niso ujeli časovno, namreč učitelji so bili časa da so opravili celotno učno pot. Z začetne točke na poli smo na točki le predvideni čas, ne cel dan dejavnosti. Tudi to težavo jih pošiljali po skupinah. Na učni poti so jih na nekaterih smo omenili snovalcem aplikacije in skupaj smo ugotovili, da bi lokacijah pričakali nadzorni učitelji, ki so preverili prisotnost in to rešili s preprosto pretvorbo učne poti iz tipa »Raziskovanje« v dijake usmerili v primeru težav. učno pot »Ekspedicija«. Glavna razlika je ta, da so pri Pomemben del izvedbe je podpora vodstva, ki mi je raziskovanju vse lokacije točk znane vnaprej, pri ekspediciji pa zagotovilo čas za pripravo, zbiranje gradiva na terenu, nadzorne se točke odpirajo v povezavi s prejšnjo (ko jo rešiš se odpre 462 naslednja). Prav tako pri ekspediciji pridobijo značko šele na Dijaki so torej skozi učno pot pridobivali knjižnično koncu opravljene poti, medtem ko pri raziskovanju značko informacijska znanja na prostem, namesto v učilnici in tako imeli prejmejo že ob visokem številu točk, kljub temu da vse točke niso drugačen potek učenja. Samostojno so iskali informacije, obiskane. odgovore in se orientirali po mestu. Seveda si vnaprej želimo Pri sestavljanju vsebinskega dela in pripravi fotografskega učno pot še dodelati, predvsem vsebinsko pri nalogah in izzivih. materiala je smiselno planirati več časa za testiranje končne Ob upoštevanju časa, ki je bil na voljo za pripravo in dejstva, da verzije in vnašanje popravkov. Med fotografiranjem lokacij za smo zadevo prvič uporabili, pa moram poudariti, da smo z pripravo gradiva nas je aktivnost popolnoma prevzela in sem izvedbo zadovoljni, saj smo pridobili izkušnjo za prihodnjo zamišljeno hodila po mestu in zapisovala zaznamke, ideje, priliko. Morda bi prihodnjič dodala še neke vrste anketo za fotografirala. V tem delovnem zagonu svojega prihoda in povratno informacijo, npr. Mentimeter, za preverjanje odziva fotografiranja nisem napovedala, tako, da so me na eni od lokacij kako je bila dejavnost sprejeta med dijaki. opomnili naj preneham. Pojasnila sem jim, da bodo fotografije uporabljene le za šolski projekt in da ne vsebujejo obrazov ljudi, vendar niso bili zadovoljni. Tako sem se naučila, da sem v hitenju LITERATURA IN VIRI pozabila na komunikacijo z ustanovami, ki je seveda zaželjena in [1] Aplikacija CŠOD Misija. Dostopno na naslovu http://misija.csod.si/si/ (29. jo bom naslednjič bolje izpeljala. Še en razlog zakaj se hitenje ne 6. 2022) [2] Fekonja. Romana, 2018. Povzetek stanja v šolskih knjižnicah. Naloge in delo izplača naj omenim na primeru napačno vnešenih koordinat, ki šolskega knjižničarja. Dostopno na naslovu so točko postavile v drugo državo. Na srečo smo testno verzijo https://home.izum.si/cobiss/konference/konf_2018/presentations/2_03_Ro manaFekonja.pdf (29. 6. 2022) večkrat preverili in rešili tudi to zagato. [3] Posodobitve pouka v gimnazijski praksi. Knjižnično informacijsko znanje, 2010. Zavod RS za šolstvo, Ljubljana. Dostopno na naslovu https://www.zrss.si/projektiess/gradiva/posgim/GRA_Knjiznicno_informaci jsko_znanje.pdf (29. 6. 2022) 463 Uporaba Google Drive za usklajevanje med učitelji in delo z učenci Use of Google Drive for Coordinating Between Teachers and Working With Pupils Mitja Močilar OŠ Antona Martina Slomška Vrhnika Vrhnika, Slovenija mitja.mocilat@guest.arnes.si POVZETEK inside the application with different types of files, that can be managed by teachers or students with editor status. Described Informacijsko Komunikacijske Tehnologije se po letu 2000, methods enhance coordination between teachers that teach same postopoma integrirajo v naš pedagoški proces. To je seveda subjects and enable better preparation for specific topic, because nujno, saj moramo tudi pedagoški delavci slediti razvoju, ker s teachers can correct and upgrade each other. For pupils, this tem povečamo zanimanje učencev za šolo in hkrati nadgradimo means better and easier work on common projects and access to naše poučevanje. Glede na vse večjo obremenjenost učiteljev s shared table of dates for oral examination, which they fulfil on dokumentacijo, pa lahko uporaba informacijske komunikacijske their own with previously set rules. All described procedures tehnologije tudi nam močno izboljša preglednost našega dela, ga have a lot more potential and can be used in different settings, bolje sistematizira in splošno olajša. V članku na kratko which innovative teachers will most definitely figure out. povzamem dve metodi uporabe programa Google Drive za delo z učenci in dve za lažjo komunikacijo znotraj aktivov. Pri obeh KEYWORDS uporabljamo skupne mape ustvarjene znotraj omenjene aplikacije, v katerih imamo shranjene dokumente, ki jih lahko ICT, Google Drive, shared folders, coordination between urejajo učitelji ali učenci z dodeljenim statusom urednika. teachers Opisane metode močno olajšajo komunikacijo učiteljev, ki poučujejo enake predmete ter z možnostjo vzajemnega 1 UVOD popravljanja in dopolnjevanja nadgradijo njihove urne priprave. Učencem pa olajšajo delo na skupnih projektih ter dostop do Uporaba Informacijsko Komunicijskih Tehnologij (IKT), se je preglednice datumov ustnih zagovorov, ki jih ob predhodno ob prehodu v 21. stoletje začela vse pogosteje in bolj intenzivno dorečenimi pravili dopolnijo sami. Vsi opisani postopki imajo integrirati v poučevanje znotraj izobraževalnih ustanov. To je ob seveda še mnoge druge možne uporabe, katerih se bodo bolj hitrosti razvoja IKT, potencialu, ki ga kaže za lažje učenje in inovativni učitelji zagotovo poslužili. pogostosti uporabe tovrstnih tehnologij, ne le za učenje ampak tudi komunikacijo z vrstniki [3], nujen korak, ki smo ga morali KLJUČNE BESEDE pedagoški delavci narediti in integrirati v svoj učni proces. Z uporabo IKT učencem približamo snov, jo seveda naredimo IKT, Google Drive, skupne mape, komunikacija v aktivu veliko bolj zanimivo in najbolj pomembno, ustvarjamo mlade ABSTRACT odrasle, ki se bodo znali in imeli interes za vseživljenjsko učenje [1,2,4]. Information and Communication Technology slowly started to Pogosto pa pozabljamo, da v današnjem času, ko smo integrate into our education system after the year 2000. This is pedagoški delavci iz leta v leto bolj obremenjeni s papirologijo, essential for teachers, because we must follow the progress to lahko IKT uporabimo tudi na načine, ki nam bi močno olajšali enhance the interest of our pupils for learning and at the same delo, omogočili večjo usklajenost znotraj aktivov in s pomočjo time to upgrade our approach towards teaching. Use of katerih bi si delo bolj organizirali ter naredili bolj pregledno. Information and Communication Technology can also lessen the V tem članku bom na kratko predstavil nekaj načinov, s burden of paperwork for teachers, which nowadays increases katerimi sem si v preteklih letih olajšal pedagoško delo, slednje annually, with better overview and better systematisation of naredil bolj pregledno in omogočil učencem večjo integracijo documents. In this article I shortly summarize two uses of Google IKT v pedagoški proces, na kar so se v veliki meri odzvali zelo Drive for working with students and two for better pozitivno. communication between teaches. In both we use shared folders 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 PREGLED LITERATURE for profit or commercial advantage and that copies bear this notice and the full Večina pedagoških delavcev je bilo tekom svoje kariere, že 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). seznanjenih s kopico različnih programov, ki jim seveda olajšajo Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia in obogatijo proces poučevanja. Težava pri veliki večini teh © 2022 Copyright held by the owner/author(s). programov je, da so do neke mere kompleksni in navadno 464 delujejo na povsem novi osnovi, kar za mnoge predstavlja prevelik izziv (posebno za starejše učitelje, ki imajo manj osnovnega IKT znanja) zaradi česar se slednjih ne poslužujejo. Zato sem se odločil, da pri uporabi IKT uberem enak pristop, kot pri poučevanju učencev, pri čemer že pridobljeno znanje nadgradimo z novim. Na ta način sem pridobil več pozornosti s strani učiteljev, ki v uporabi IKT niso tako vešči. Odločil sem se nadgraditi uporabo aplikacije Google Drive, ki jo ima večino učiteljev, saj navadno uporabljajo google mail in imajo zato že ustvarjen gmail račun. Google Drive je ena od Googlovih aplikacij, ki omogoča shranjevanje dokumentov na Slika 1 Skupna mapa za kemijo na Google Drive spletu. Večina učiteljev ima ustvarjen brezplačni račun, pri katerem imajo na razpolago 15GB prostora, kar je več kot dovolj za shranjevanje vseh pomembnih dokumentov, slik in povezav Ko učitelji poučujemo enake predmete se trudimo, da do poučnih gradiv. Poleg tega se lahko Google Drive namesti ostajamo karseda usklajeni pri hitrosti poučevanja in zaporedju direktno na namizje računalnika v obliki klasične mape v kateri predvidenih snovi pri dotičnem predmetu. Zato sem naredil imate shranjene vse dokumente. Prednosti te mape pa so, da se skupno Excelovo datoteko (ki sem jo v Google Drive pretvori na vsi naloženi dokumenti v njej avtomatsko shranjujejo na splet in Sheet file) v kateri sem za posamičen oddelek enega razreda prenašajo tudi na druge računalnike, kjer imate naloženo naredil razdelke za vsak oddelek in v vsakega vpisal glavna aplikacijo Google Drive. Poleg tega lahko ustvarjate tudi mape, poglavja, ki jih bomo tekom leta obravnavali. Ko učitelj zaključi ki jih uporablja in spreminja več uporabnikov, kar ima izjemno poglavje ga iz rdeče barve obarva v zeleno (Slika 2). Če aplikativno vrednost pri komunikaciji učitelj-učitelj in učitelj- vzamemo primer biologije osmih razredov, kjer imamo tri učenec. Znotraj aplikacije lahko ustvarjamo tudi različne oblike oddelke in jaz poučujem dva, druga učiteljica pa enega, bo lahko dokumentov, Google docs (podobno kot word dokumenti), na ta način učiteljica točno videla katera poglavja sem jaz že Google sheets (podobno kot Excel dokument) in Google slides obdelal ter katera še nisem, enako velja zame. Sicer se hitro (podobno kot Power point dokument). Prednost teh dokumentov vprašamo, zakaj se o tem ne pogovorimo na aktivu in določimo je da jih lahko urejamo tudi na spletu, tako da lahko učenci ali naslednjo snov? Kar vsekakor se in vse skupaj tudi učitelji, ki nimajo nameščene namizne aplikacije Google Drive, prediskutiramo na aktivih, vendar če skupaj poučujeta dva prav tako sodelujejo pri preoblikovanju ali ustvarjanju skupnega učitelja biologijo in kemijo v osmem in devetem razredu ter dokumenta [5]. naravoslovje v šestem in sedmem razredu, vse skupaj nanese šest različnih oddelkov, kjer se hitro kaj pozabi ali zameša. Zato nam tovrstna preglednica olajša pregled snovi in načrtovanje dela saj 3 REZULTATI natanko vemo, kaj še nismo obravnavali in koliko časa nam Usklajevanje znotraj naravoslovnega aktiva vzame vsaka snov. Poleg tega lahko kadarkoli preverimo Ker na naši šoli (sklepam da je na drugih večjih šolah prav dogovore iz aktiva, da ne pride do zmešnjave. tako), učiva biologijo, kemijo in naravoslovje dva učitelja, je zelo pomembno, da sva pri podajanju snovi karseda usklajena, ker obstaja verjetnost, da bo en od naju naslednje leto poučeval razred od drugega učitelja, pri čemer mora biti natančno seznanjen s snovjo, ki so jo že predelali oz. jo še niso natančno prediskutirali. Poleg tega se učenci in seveda tudi starši med seboj pogovarjajo in hitro opazijo že manjša odstopanja pri poučevanju snovi, kaj šele da en učitelj uči v popolnoma drugačnem vrstnem redu ali pa kaj celo spusti, drugi pa ne. S tem namenom sem ustvaril skupno datoteko v Google Drive, v kateri imava mape za vsak predmet in razred ločene. Znotraj vsakega predmeta (npr. 9. razred kemija) pa najdete aktualen LDN, Slika 2 Skupen Google sheet za usklajevanje poučevanja posamične urne priprave, PPT datoteke in uporabne dokumente (slike, videe, itd.), ki olajšajo razlago določene snovi (Slika 1). Na ta način lahko skupaj urejava LDN, piševa priprave, se Primeri prakse dela z učenci v Google Drive. dopolnjujeva, popravljava napake in najbolj pomembno ostajava Uporaba skupnih dokumentov v Google Drive nam in dosledna pri podajanju snovi, saj se konstantno primerjava s učencem lahko močno olajša delo. Pri tem bom opisal dve pripravami od lanskega leta. Tako nadgradiva najino fizično najpogosteje uporabljeni metodi dela. komunikacijo še v elektronski obliki in nisva odvisna le od Ker se sam poslužujem napovedanega ustnega ocenjevanja, skupnih aktivov (ki so seveda za dobro delo v aktivu še vedno mi je skupni dokument, kjer imamo tabelo datumov in imen izjemno pomembni). Olajša se tudi delo pri poučevanju v učencev določenih za nek termin, bil zelo priročen. O tabeli jih različnih učilnicah, saj ne potrebuješ IKT gradiv prenašati z usb obvestim na začetku leta, pri čemer imajo učenci 14 dni časa, da ključem ampak so vsa gradiva dostopna na spletni aplikaciji se sami vpišejo v njo in si določijo termin spraševanja. V kolikor Google Drive. to ne storijo sami, jim ga določim jaz. Pri tem jim omejim obdobje spraševanja in število vprašanih v eni uri. Vsak od 465 učencev si določi tudi rezervni termin. V kolikor je odsoten pri 4 ZAKLJUČEK obeh izbranih terminih, ga vprašam prvo uro ko pride. S tem so S tem člankom sem želel olajšati delo učiteljem ter jim na vsi seznanjeni na začetku leta, s čimer se izognem raznim enostaven način omogočiti boljšo preglednost njihovega dela in izgovorom med letom. Nad seznamom so zadovoljni vsi učenci, s tem optimizacijo celotnega učnega procesa. Prav tako opisani saj sami določijo termin in imajo avtomatsko zabeleženega na pristopi omogočajo integracijo IKT v pedagoški proces, olajšajo Google Drive, kar pomeni, da jim je slednji vedno pri roki hkrati skupinsko delo učencev in dostopnost pomembnih podatkov. pa ne morejo trditi, da so pozabili ali ga spregledali. Ta seznam Opisane metode dela imajo seveda še mnoge druge možnosti za seveda tudi nam olajša zadeve, saj nam je vedno dostopen. Take aplikacijo pri pouku, ki jih bodo učitelji, s pridobljenim znanjem sezname uporabljam tudi v primeru govornih nastopov in pisnih in malo inovativnosti razvili. preverjanj znanja (pri slednjih seveda sam določim termin). Uporabe skupnih dokumentov se poslužujem tudi pri kemiji v osmem razredu, kjer učenci tekom leta izdelujejo brošuro LITERATURA IN VIRI kemijskih elementov. Na začetku dokumenta so napisana pravila [1] Mann D., Shakeshaft C., Becker J. and Kottkamp R.,1999 West Virginia’s pisanja v brošuro, pod njimi pa so razvrščeni kemijski elementi Basic Skills/Computer Education Program: An Analysis of Student po vrsti od vodika pa vse do elementa katerega vrstno število je Achievement Milken Family Foundation, Santa Monica CA. enako številu učencev v razredu (Slika 3). Učenci si nato sami [2] Sivin-Kachala J (1998) Report on the Effectiveness of Technology in Schools 1990–1997 Software Publisher’s Association, Washington DC. izberejo kemijski element in ga skozi celotno leto dopolnjujejo, [3] Sutherland R., Lindstro M.B., Lahn, L.C., 2009, Sociocultural perspectives: glede na trenutno obravnavano snov pri pouku. Na ta način technology enhanced learning and knowing. In: de Jong, T., Balacheff, N., Ludvigsen, S., Barnes, S., Lazonder, A. (Eds.), Technology-enhanced učenci pridobijo dodatni učni pripomoček, ki so si ga izdelali Learning: Principles and Products. Springer-Verlag: 39–53. sami in na koncu leta opise za prvih x elementov periodnega [4] Wenglinsky H., 1998, Does it Compute? The Relationship between sistema, ki jim bodo seveda zelo prav prišli v devetem razredu. Educational Technology and Student Achievement in Mathematics Educational Testing Service Policy Information Center, Princeton NJ. [5] Wikipedia 2022, Google Drive, Wikipedia The Free Enciklopedia, Dostopno na: https://en.wikipedia.org/wiki/Google_Drive (10.8.2022) Slika 3 Brošura kemijskih elementov (skupen dokument) 466 Spletni vodnik Plečnik v Kamniku v obliki sobe pobega Online Guide Plečnik in Kamnik in the Form of an Escape Room Andreja Nagode Burger OŠ Komenda Moste Komenda, Slovenija andreja.nburger@oskomenda-moste.si POVZETEK transferred everything to free Google forms. Thus an online guide named Plečnik in Kamnik was created in the form of an Na Osnovni šoli Komenda Moste so v šolskem letu 2021/2022 escape room, where the correct solution opens the next challenge. obeležili Plečnikovo leto z raziskovanjem in spoznavanjem The students used their smartphones and followed the mojstrovih umetnin v Ljubljani, Kamniku in Komendi. Delo na instructions in small groups in the online guide independently. terenu se je šolska knjižničarka odločila učencem približati in jih They researched Plečnik's works in Kamnik and solved the tasks dodatno motivirati s pomočjo informacijsko-komunikacijske at the end of each section. The research was for free, but it didn't tehnologije. Pri organizaciji dejavnosti na terenu je zasledila go without problems. Students read the instructions too quickly spletne vodnike Nexto in jih vključila v raziskovanje učencev. and too superficially. Since they did not observe the appropriate Ker za Kamnik tak spletni vodnik ni obstajal, se ga je odločila way of recording the correct answers, the system did not consider izdelati sama. Po zanesljivih spletnih referenčnih virih in them as correct, so they could not continue their research. The predhodnem ogledu trase je pripravila opise posameznih točk accompanying teachers had to explain the instructions to them ogleda, dodala lastni slikovni material in vprašanja za additionally if necessary, and helped them to enter the answer preverjanje znanja. Pripravljeno je prenesla v brezplačne Google appropriately. obrazce v obliki sobe pobega, kjer pravilna rešitev odpre naslednji izziv. Tako je nastal spletni vodnik Plečnik v Kamniku, KEYWORDS ki je predstavljen v prispevku. Učenci so z lastnimi pametnimi telefoni v manjših skupinah po predhodnih navodilih učiteljice Virtual guide, escape room, local cultural heritage samostojno sledili napotkom v spletnem vodniku, raziskovali Plečnikova dela v Kamniku in reševali naloge na koncu vsakega 1. ORGANIZACIJA DELA IN SPLETNI VIRI sklopa. Razen prevoza so vse dejavnosti na terenu potekale brezplačno, vendar niso minile brez zagat. Učencem so iz njih Aplikacija Nexto je bila na začetku leta 2015 zamišljena, da pomagali spremljajoči učitelji. Učiteljico izbirnega predmeta so uporabniku preko mobilne naprave daje osnovne informacije o po končanih dejavnostih na elektronski pošti že čakali vsi oddani njegovi bližnji okolici. Mobilna naprava informacije sprejema odgovori učencev. Priprava evalvacije opravljene dejavnosti je prek posebnih oddajnikov Bluetooth, ki z njo začnejo bila zato hitra in enostavna. komunicirati, ko se jim uporabnik dovolj približa. Nexto je bila načrtovana za uporabo med obiski muzejev in naravnih KLJUČNE BESEDE znamenitosti ali pa raziskovanjem novih krajev [1]. Danes aplikacijo Nexto lahko brezplačno uporabljamo kot Virtualni vodič, soba pobega, lokalna kulturna dediščina pametni mobilni vodnik po več kot tridesetih destinacijah ABSTRACT slovenske kulturne in naravne dediščine. Aplikacija Nexto Ljubljana uporabniku s pomočjo obogatene Primary School Komenda Moste celebrated Plečnik's year in the resničnosti razkrije štiri velika neuresničena Plečnikova dela za school year 2021/22 by researching and getting to know the Ljubljano: Mesarski most, Novi Magistrat, Magistratni vstop na master's works of art in Ljubljana, Kamnik and Komenda. The grad in Katedralo svobode. Pot ga vodi tudi mimo uresničenih school librarian decided to bring the work in the field closer to Plečnikovih del: čez Tromostovje mimo Prešernovega trga na the students with the help of information and communication Krekov trg, do Čevljarskega mostu in Novega trga, Križank, technology. When organizing activities in the field, she found the Vegove ulice in NUK ter parka Tivoli. Vsaka točka se začne z Nexto online guides and included them in the students' research. uganko oziroma nalogo, ki jo mora uporabnik razvozlati, da Since there is no such virtual guide for Kamnik, she decided to odklene informacije o projektu, o katerem mu pripoveduje make it herself. She prepared descriptions of individual points of Plečnik kot avdiogovorec. Ob koncu vsake točke mora uporabnik view, pictorial material and questions for knowledge testing and rešiti uganko, da razkrije lokacijo naslednje točke, ki mu ni znana Permission to make digital or hard copies of part or all of this work for personal or vnaprej [2]. classroom use is granted without fee provided that copies are not made or distributed Zaradi dobrega odziva na tovrstno spoznavanje Ljubljane je for profit or commercial advantage and that copies bear this notice and the full knjižničarka začela razmišljati o raziskovanju Plečnikovih del v 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). bližnji okolici, v Kamniku. Ker še ni obstajal noben spletni Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia vodnik, ki bi ji bil v pomoč pri organizaciji dela na terenu, se je © 2022 Copyright held by the owner/author(s). odločila, da ga naredi sama. Iskala je brezplačne alternative, ki 467 bodo dostopne preko poslane povezave. Odločila se je za odgovorom so učenci preverili in utrdili pridobljeno znanje, uporabo Googlovih obrazcev, v katere je prenesla predhodno bodisi samo iz besednega opisa in logičnega razmišljanja ali pripravljeno vodenje in naloge, povezane z raziskovanimi dejstev, ki so jih morali povezati z napisanim ali prepoznati v točkami v Kamniku. Po zgledu aplikacije Nexto Ljubljana je videnem na terenu (Slika 2). vodenje in vprašanja uredila v obliko sobe pobega, torej v obliko, kjer je za napredovanje k naslednji točki/nalogi, nujen en in edini pravilni odgovor. Pri sestavi vodenja in nalog je izhajala iz zanesljivih spletnih virov, npr. Kamra, dLib, Kamniško- Komendski bibliografski leksikon … 2. IZDELAVA SPLETNEGA VODNIKA Pri izdelavi dotičnega spletnega vodnika je avtorica izbrala obliko t. i. sobe pobega v Google obrazcih, ki jih je spoznala že v času karantene med iskanjem novih spletnih načinov dela z učenci. Za naloge v obliki sobe pobega je slišala v strokovnih krogih [3]. Poleg splošnih informacij o Google obrazcih so bile zelo uporabne informacije, predstavljene v spletnem predavanju predavateljice Courtney Drysdale, zaposlene na Univerzi Regis [4, 5]. O sobah pobega za potrebe pouka se je v času karanten in kasneje veliko govorilo in pisalo [6], saj so se izkazale za motivacijsko močno in zanimivo orodje za delo z učenci, v obliki spletnih vodnikov pa jih avtorica prispevka še ni zasledila. Kot pri pravi sobi pobega so učenci ujeti v eno nalogo, iz katere lahko napredujejo le s pravilnim odgovorom, ki je ključ za vstop v naslednjo nalogo. Tovrstna oblika je učencem zelo všečna in jih motivira veliko bolj kot druge oblike nalog. Pravilni odgovor je potrebno vpisati v pričakovani obliki, da ga sistem, torej Google obrazci prepoznajo kot pravilnega. Pri vsaki postaji se je avtorica odločila za kratko besedno predstavitev, ki ji je sledila še slikovna ponazoritev (Slika 1). Slika 2: Vprašanje Največjo težavo je učencem predstavljalo natančno branje. V osnovnih navodilih je namreč pisalo, da morajo vse odgovore zapisati z velikimi tiskanimi črkami in pravopisno pravilno, ker drugače ne bodo prepoznani kot ustrezni in zato ne bodo napredovali k naslednji točki/nalogi (Slika 3). Slika 1: Opis in slikovna predstavitev Informacije je povzela po pisnih virih [7], zanesljivih spletnih virih [8] in po predhodnem ogledu načrtovane trase, kjer je s fotografiranjem poskrbela za zadostno in ustrezno lastno slikovno gradivo. Slika 3: Navodila za vpisovanje odgovorov Na koncu sklopa informacij o določeni točki ogleda je vedno zastavljeno vprašanje, povezano s predhodnimi informacijami. Z 468 Učenci so lahko kadarkoli preverili zemljevid načrtovane Spletni vodnik jih sproti pohvali za vsak opravljen izziv. Na poti in svojo trenutno lokacijo (Slika 4). Pri prehajanju na koncu jih napoti k dodatnem raziskovanju o mojstru Jožetu naslednje postaje ogleda se je to izkazalo za uporabno pomoč. Plečniku in njegovih delih na portalu Kamra. Predlaga jim tudi nadaljevanje raziskovanja Plečnikovih sanj z aplikacijo Nexto Ljubljana v slovenski prestolnici. 4. REZULTATI Google obrazci omogočajo hiter in različen pregled poslanih odgovorov in evalvacijo le-teh. Odgovore lahko pogledamo v obliki tabele (Tabela 1) ali grafov (Slika 5). Tabela 1: Oddani odgovori Slika 4: Zemljevid vodene poti 3. VSEBINA SPLETNEGA VODNIKA S klikom na določeno polje v tabeli se odpre celotno besedilo Namen izdelanega spletnega vodnika [9] je spoznati življenje in vprašanja, kar olajša pregled odgovorov in evalvacijo le-teh. delo arhitekta Jožeta Plečnika preko umetnin, ki jih je ustvaril v Kamniku. V 1. slopu so predstavljene informacije o arhitektovem življenju, ki so podprte s slikovnim gradivom, dostopnim na portalu Kamra in dLib. Zaključi ga vprašanje Kaj arhitekt izdela ali izriše, da lahko potem drugi mojstri zgradijo? (Namig: 1 beseda, 5 črk, m. sp., edn.), s katerim učence usmerimo na rezultat arhitektovega dela. V 2. sklopu spletni vodnik preveri pridobljeno znanje po ogledu svečarskega muzeja v Lectarjevi hiši, kjer so se učenci udeležili tudi delavnice poslikave Plečnikovih sveč [10]. Naslednji sklop podatkov je vezan na Glavni trg v Kamniku, kjer učenci pred znamenito fasado na Maistrovi 2 odkrijejo razliko med fasado in fresko. Spoznajo tudi tehniko, ki jo pogosto vključeval v svoje načrte in je sestavni del preučevane fasade. Spletni vodnik nato napoti obiskovalca v Kapelo Božjega groba v frančiškanskem samostanu, kjer spoznajo Plečnikovo vsestranskost, praktičnost in simboliko. Z natančnim opazovanjem in povezovanjem videnega s časom Plečnikovega ustvarjanja učenci izberejo pravi odgovor in dobijo navodila za Slika 5: Rezultati v grafih nov izziv. Po Ljubljanski cesti se sprehodijo do Cerkve Marijinega Učitelji preko poslanih odgovorov doma ali v učilnici hitro brezmadežnega spočetja, poiščejo in raziščejo naslednjo in učinkovito evalvirajo pridobljeno in osvojeno znanje dela na mojstrovo umetnino, čeprav slavna kropilnica žal ni več terenu. dostopna javnosti. Učenci so bili nad novo obliko dela na terenu navdušeni. Na vračanju proti avtobusni postaji se spotoma ustavijo še na Delo na terenu so označili kot najboljšo dejavnost v celem železniški postaji Kamnik mesto, ki je dolgo časa veljala za šolskem letu. Všeč jim je bila samostojnost pri raziskovanju, Plečnikovo. Preverijo svoje pridobljeno znanje s prepoznavo spremljajočih učiteljev zaradi primerne razdalje sploh niso posameznih arhitekturnih detajlov. opazili. Zapletlo se je le pri neustreznem vnašanju pravilnih Raziskovanje zaključijo na mostu čez Nevljico, kjer odgovorov (neustrezne črke, sklon, število …), ker niso mogli razmislijo o vzrokih za uporabo različnih materialov, ki jih je dostopati do naslednjega sklopa informacij za raziskovanje. Šele arhitekt predvidel v svojem načrtu. takrat so potrebovali in poiskali pomoč učitelja. Na avtobusu imajo možnost dokončati svoje reševanje in dokončno oddati svoje odgovore. 469 Po opravljenem terenskem delu in prvi preizkušnji spletnega Ugotovili smo, da so vsi udeleženi učenci spletni vodnik vodnika v praksi je avtorica za sodelujoče učence izbirnega prepoznali kot učinkovito orodje za samostojno raziskovanje predmeta Likovno snovanje II pripravila kratko anketo, da bi Plečnikovega Kamnika (Slika 9). pridobila iskrene in realne povratne informacije. Rezultati opravljene evalvacije so opozorili na najmočnejše in najšibkejše točke spletnega vodnika (Sliki 7,8). Slika 9: Izpolnjen namen spletnega vodnika V zadnjem vprašanju ankete so štirje učenci (28,6 %) Slika 6: Zahtevnost nalog predlagali, da omogoči poljubno izbiranje raziskanih postaj, pet (35,7 %) pa jih je zapisalo, da je potrebno olajšati vpisovanje Četrtina učencev meni, da so naloge v spletnem vodniku odgovorov. prezahtevne, kar je verjetno posledica natančno določenega Na podlagi opravljene evalvacije lahko sklenemo, da je vpisovanja odgovorov. Velik del, tj. 71,4 % oz. 10, sodelujočih spletni vodnik Plečnik v Kamniku učencem za samostojno učencev namreč meni, da je najbolj moteča lastnost vodnika prav raziskovanje všeč, saj so z njim učinkovito in uspešno spoznali predpisana oblika (velike tiskane črke in za vsak odgovor točno Plečnikova dela v Kamniku. Želijo pa si možnost samostojne določena sklonska oblika rešitve) vpisa pravilnega odgovora izbire poti raziskovanja in čim lažji način odgovarjanja, tj. (Slika 7). Za naloge v obliki »sobe pobega« pa je ravno prepoznavo in izbiro ustreznega odgovora med večimi možnimi. upoštevanje tovrstnih navodil ključno za napredovanje. 5. ZAHVALA Hvaležna sem sodelavki, učiteljici likovne umetnosti in izbirnega predmeta likovno snovanje, gospe Tini Kosi, ki je pogumno sprejela izziv predlaganega terenskega dela v povezavi z IKT storitvami in ga z medpredmetnim sodelovanjem obogatila ter preizkusila ustvarjeno aplikacijo. Zaradi njenih konstruktivnih predlogov je le-ta dočakala nadgradnjo in bo uporabljana tudi v naslednjem šolskem letu. Slika 7: Moteče lastnosti spletnega vodnika LITERATURA IN VIRI [1] Matic Tomšič. 2015. Nexto: slovenska aplikacija, ki lahko zamenja Kot najbolj všečno lastnost vodnika so učenci izbrali več turističnega vodnika. Dostopno na naslovu https://siol.net/digisvet/novice/nexto-slovenska-aplikacija-ki-lahko- možnosti. Večini, 57,1 % oz. 8 učencem, so bila všeč jasna in zamenja-turisticnega-vodnika-62593 (1. 8. 2022) kratka navodila, 21 % oz. 3 učencem so bila všeč kratka navodila, [2] Legendarne Plečnikove vizije. Dostopno na naslovu https://www.ljubljana.si/sl/aktualno/legendarne-plecnikove-neuresnicene- 14,3 % oz. 2 učencema kratki opisi posameznih točk, 7,1 % oz. vizije/ (1. 8. 2022) en učenec pa je pod drugo napisal način vodnika, torej način sobe [3] Gregor Škrlj: Knjižnica in spletna soba pobega. 2021. Dostopna na naslovu pobega (Slika 8). https://knjiznicarske-novice.si/novica/1274/pokazi [2. 8. 2022] [4] Courtney Drysdale: Creating Online Escape Games with Google Forms. 2021. Dostopno na naslovu https://enetlearning.adobeconnect.com/p8gxxra41eno/ (3. 8. 2022) [5] Hitro pridobite vpoglede z aplikacijo Google Forms. Dostopno na https://www.google.com/intl/sl_SI/forms/about/ (3. 8. 2022) [6] Tjaša Kampos: sobe pobega in drugi miselni izzivi pri pouku. 2021. Dostopno na naslovu https://www.zrss.si/wp- content/uploads/Konference/2021/NAK2021/1dan/SEKCIJA%206/Sobe%2 0pobega%20in%20drugi%20miselni%20izzivi%20pri%20pouku%20T.Ka mpos.pdf (3. 8. 2022) [7] Maja Avguštin in Saša Lavrinc. 2010. Plečnik na Domžalskem in Kamniškem. Ljubljana : Zavod za varstvo kulturne dediščine Slovenije, 2010 (Ljubljana : Littera picta) [8] Plečnikova dela v Kamniku in okolici. Dostopno na naslovu https://www.kamra.si/digitalne-zbirke/plecnikova-dela-v-kamniku-in- okolici/ (3. 8. 2022) [9] Andreja Nagode Burger: Plečnik v Kamniku. Dostopno na naslovu Slika 8: Pohvaljene lastnosti spletnega vodnika https://forms.gle/yj7MDtSdJ2M5PfUk6 (1. 8. 2022) [10] Lectarjeva hiša. Zibelka 300 letne tradicije oblikovanja in izdelave sveč za vse priložnosti. Dostopno na naslovu https://www.pax.si/lectarjeva-hisa/ (3. 8. 2022) 470 Razvoj digitalnih kompetenc pri delu z učenci z učnimi težavami Development of Digital Competencies Working With Students With Learning Disabilities Jure Ozvatič OŠ Draga Kobala Maribor, Slovenija jure.ozvatic@gmail.com POVZETEK data. Given appropriate education in schools we teach them proper use. Among students with learning dissabilities the Uporaba mobilnih naprav, računalnikov in svetovnega spleta se process is more difficult, slower and partial. With their deficits je v zadnjem obdobju močno povečala, saj je prisotna na vseh they cannot see all the pitfalls and dangers of using the internet ravneh družbenega življenja. S tem je povezana tudi potreba po and mobile devices. In doing so it is necessary to educate and izobraževanju in pravilni uporabi omenjenih naprav, obdelave in empower them to aquire the basic skills within the digital uporabe informacij. Digitalne kompetence zajemajo različne competence and use them properly despite their difficulties. With procese in oblike obdelave in uporabe podatkov v informacijsko- this they will know how to safely and correctly use digital forms komunikacijski tehnologiji. Razvoj digitalnih kompetenc je pri and devices in their everyday and professional life. mladih povezan z njeno uporabo, saj se dnevno soočajo s tem in jo uporabljajo. Slednji pogosto s premalo znanja in veščinami KEYWORDS (ne)kritično uporabljajo spletna orodja, komunikacijo preko družabnih omrežij, izmenjujejo in objavljajo podatke. Z Digital competence, students with learning difficulties, training ustreznimi izobraževanji se jih v šolah uči pravilne uporabe. Pri učencih z učnimi težavami poteka v primerjavi z njihovimi 1 UVOD vrstniki težje, počasneje in parcialno. Svojimi primanjkljaji ne zmorejo uvideti vseh pasti in nevarnosti pri uporabi svetovnega Uporaba računalnikov, pametnih mobilnih telefonov in ostalih spleta in mobilnih naprav. Pri tem jih je potrebno izobraževati in digitalnih pripomočkov se je v zadnjih letnih močno povečala ter opolnomočiti, da bodo lahko kljub svojim težavam osvojili razširila v vse družbene sisteme. Zaradi hitrega razvoja in osnovne veščine znotraj digitalnih kompetenc ter jih pravilno napredka se je način življenja povezal preko svetovnega spleta uporabljali. S tem bodo znali varno in pravilno uporabljati ter družabnih omrežij. IKT je po opredelitvi OECD [1] digitalne oblike in naprave v vsakdanjem in profesionalnem kombinacija proizvodne in storitvene industrije, ki prenaša ter življenju. prikazuje podatke s pomočjo elektronske oblike. Znotraj IKT se pojavljajo različne možnosti računalniških, komunikacijskih in KLJUČNE BESEDE informacijskih naprav, aplikacij in drugih storitev. Vse te možnosti pa se tudi nadgrajujejo, širijo in povezujejo tako na Digitalne kompetence, učenci z učnimi težavami, usposabljanje profesionalnem kot privatnem življenju posameznika [2,3]. ABSTRACT Vsaka naprava, ki se jo porablja znotraj IKT, zahteva določeno stopnjo znanja za njeno varno uporabo. Mnoga podjetja The use of mobile devices, computers and the internet has najdejo tržno nišo ravno med mladimi, ki pogosto spremljajo recently increased significantly increased, because it is present at nove tehnične izdelke in jih nato kupujejo. Množičen porast all levels of social life. Related to this is the need for education pametnih mobilnih naprav je prispeval tudi k množični uporabi and the correct use of the mentioned devices, processing and use spleta, pri tem se porajajo različni vidiki pravilne in varne of information. Digital competence includes different processes uporabe. Mladi običajno dokaj hitro usvajajo nove aplikacije in and forms of data processing and use in information and spletne novosti. Učenci z učnimi težavami so dokaj posebna communication technology. The development of digital skupina, saj imajo nekateri premalo znanja o celovitem competence among young people is related to its use, as they are delovanju in pri uporabi spleta ter pametnih mobilnih naprav. facing and using it on a daily basis. The latter, possessing Vso to znanje o digitalnih informacijah in napravah se je v insufficient knowledge and skills, often (un)critically use online zadnjih letih oblikovalo v t. i. digitalnih kompetencah. tools, communicate via social networks, exchange and publish 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 IKT V VZGOJI IN IZOBRAŽEVANJU for profit or commercial advantage and that copies bear this notice and the full Mladi preživljajo veliko časa s pametnimi telefoni, računalniki 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). in igralnimi konzolami. Vzporedno z zabavo in igranjem Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia videoiger, komuniciranjem preko družabnih omrežij pridobivajo © 2022 Copyright held by the owner/author(s). osnovna znanja za njihovo uporabo. Vse te naprave so se pred 471 nekaj leti začele uporabljati tudi v sistemu vzgoje in 3 DIGITALNE KOMPETENCE V VZGOJI IN izobraževanja, saj so v omenjenem sistemu zelo pomembne z IZOBRAŽEVANJU vidika omogočanja kvalitetne in učinkovite podpore pri pouku. IKT je postala dostopna za njeno vpeljavo v izobraževalne Digitalne kompetence sta OECD (2010) in Digitalna agenda vsebine in učne načrte kot del načrtov v šolah [4]. Z omenjeno Evrope (2013) uvrstili med temeljne kompetence državljana v tehnologijo učenci, pedagoški delavci in ostali strokovnjaki sodobni družbi ter izobraževalnemu sistemu pri pridobivanju in uporabljajo gradivo na spletu, ga urejajo, objavljajo in delijo s razvijanju teh kompetenc. Pri opredelitvi digitalnih kompetenc širšo družbo. Množičnost podatkov je potrebno selekcionirati in so to veščine pri uporabi sodobnih tehnologij, sposobnost se jih naučiti ločevati, ovrednotiti in jim zaupati. Pri tem je uporabe znanja in veščin v konkretnih situacijah. Avtorji različno potrebno pokazati dovolj znanja in veščin, da se posameznik opredeljujejo pojme digitalne kompetence, največkrat so v nauči postati informacijsko opismenjen, saj lahko v nasprotnem uporabi v zvezi z veščinami, povezanimi s IKT, računalniško primeru pride do informacij, ki so nezanesljive, napačne ali težko informatiko in svetovnim spletom, pogosto pa so pod digitalno preverljive [5]. Skozi vseživljenjsko izobraževanje se morajo pri kompetentnost uvrščali tudi medijsko pismenost [11]. V svojem delu pedagoški in drugi strokovni delavci do neke mere povezavi z omenjenimi kompetencami se ta področja dotikajo naučiti uporabljati IKT vsaj na osnovni ravni [6]. S tem bodo profesionalnega, zasebnega, družbenega življenja in preživljanja deležniki v vzgoji in izobraževanju pri poučevanju ter učenju prostega časa dodatno motivirali otroke ter pridobivali digitalno Digitalne kompetence zahtevajo določeno mero funkcionalnost digitalnih kompetenc. Pri pouku je tovrsten način informacijsko-komunikacijske pismenosti in druge oblike še posebej pomemben, saj morajo mladi v procesu pridobivanja komuniciranja. Osnovna raba IKT ter dostopnost do svetovnega znanja pridobiti veščine za pravilno uporabo informacijske spleta potrebujejo pri digitalnih kompetencah ustrezno tehnologije. Z dopolnjevanjem učnih vsebin s pomočjo gradiv z poznavanje IKT, ravnanje z njimi in ustrezen odnos do njih [12]. interaktivnimi viri mladi pridobivajo večjo motivacijo in S pomočjo digitalnih kompetenc usvojimo sposobnost izkušnje pri učenju. Svetovni splet, interaktivni viri in aplikacije ocenjevanja in upravljanja velikih količin informacij ter znanja. z izobraževalnimi gradivi omogočajo učiteljem, da ponudijo Evropski okvir digitalnih kompetenc za državljane [12] možnosti za učinkovito učenje in večje vključevanje samih je na petih področjih poudaril sposobnosti pri razvoju digitalnih učencev v izobraževalni proces v svetu digitalizacije. Učitelji kompetenc: obdelavo podatkov, komunikacijo, ustvarjanje spodbujajo rabo tehnologije pri učencih ter jih tako učijo vsebin, varnost in reševanje problemov. Te spretnosti se nanašajo pravilnih pristopov pri iskanju informacij, analiz, oblikovanju na tehnično uporabo IKT, kompetence IKT pa so mišljene kot rešitev ter učinkoviti komunikaciji. Samo učenje s pomočjo integrirana in funkcionalna uporaba digitalnega znanja, pametnih mobilnih naprav in spleta se nanaša na načine, ko se spretnosti in odnosov [3]. uporablja omenjena tehnologija hkrati s spodbujanjem učenja Digitalne kompetence so med drugim razvrščene v pet [7]. Rezultati raziskav so pokazali, da uporaba informacijsko- sklopov: komunikacijske tehnologije v podporo učnemu okolju pozitivno - obdelava informacij (iskanje informacij, uporaba različnih vpliva na učenje [4]. Med mladimi je prvi vir informacij ter iskalnikov, uporaba filtrov, razvrščanje in preverjanje informacij najpogosteje uporabljena tehnologija v učne namene … ); računalniška in informacijska tehnologija [8]. - ustvarjanje vsebin (ustvariti zahtevnejše digitalne vsebine v Učenci, ki vsakodnevno uporabljajo računalnik v različnih formatih, npr. besedila, preglednice, slike, avdio prostem času, dosegajo nižje učne dosežke, podobno kot imajo vsebine), uporaba orodja in urejevalnikov za ustvarjanje spletnih slabše učne dosežke učenci, ki računalnika nikoli ne uporabljajo strani, urejanje vsebin … ); [3]. Po podatkih iz PISE (2009) so ugotovili, da učenci v - komunikacija (uporaba naprednejših funkcij za spletno domačem okolju uporabljajo računalniško opremo v večji meri komuniciranje, spletna orodja in nalaganje datotek, uporaba za zabavo, igranje iger, manj pa za šolsko delo [9]. spletnih storitev, družbenih omrežij, spletne skupnosti … ); Uporaba elektronskih gradiv je za učenje smiselna, ko z - reševanje problemov (uporaba digitalne tehnologije, njeno uporabo dosežemo časovno racionalizacijo, boljše reševanje nastalih težav, specialnih podatkovnih baz in rezultate pri učenju in preverjanju doseženega znanja. Tovrstni programov …); način se razlikuje od pouka v živo, zato je bilo potrebno - varnost (zaščititi z varnostnimi programi, pravilna uporaba predhodno določiti cilje in načine podajanja učne snovi, gesel, prepoznati neželeno elektronsko pošto, tvegane spletne načrtovati izvedbo, pripraviti ustrezna e-orodja v učnem okolju strani ...). ter samovrednotiti dosežke in pridobljeno znanje [10]. Učenci, ki Učenci so v srednješolskem izobraževanju v Sloveniji imajo nižje sposobnosti, potrebujejo smiselno sestavljene naloge, nad povprečjem EU pri zaupanju v digitalne kompetence: prilagojene težavnostnim stopnjam, da vsebujejo dovolj - varnost SLO (2,94), EU (2,85); podpornega konkretnega slikovnega gradiva ter animacij (še - komunikacija SLO (3,36), EU (3,26); posebej so poučne pri možnostih ponovitve in korigiranju - informacijska pismenost SLO (3,05), EU (3,04); hitrosti). Spletne strani z učno vsebino, ki omogočajo spletne - reševanje problemov SLO (2,86), EU (2,65); povezave z navezovanjem na sorodne vsebine, učencem - ustvarjanje vsebin SLO (2,84), EU (2,74). spodbudijo željo po spoznavanju novih informacij, hkrati pa jih Pri pedagoških delavcih so rezultati pokazali slabše znanje učijo pravilne uporabe osnov digitalnih kompetenc [10]. glede na povprečje EU: - varnost SLO (2,59), EU (3); - komunikacija SLO (2,32), EU (3,05); - informacijska pismenost SLO (2,68), EU (3,17); 472 - reševanje problemov SLO (2,49), EU (2,8); dela delno ohranil kot dodatna možnost. S tem se je pridobila - ustvarjanje vsebin SLO (2,32), EU (2,67). časovna in prostorska neomejenost dostopa do izmenjevanja Starši so izkazali visoko zaupanje v Sloveniji do poučevanja informacij, boljša komunikacija, omogočil se je dostop do otrok za varno in odgovorno uporabo interneta (68 %), kar je informacij, delitve znanja in dela z multimedijskimi orodji. S višje kot v EU (52 %) [11]. pomočjo IKT se je nudila učencu z učnimi težavami možnost prilagoditve, nazornost, postopnost, konkretizacija, utrjevanje in ponavljanje učne snovi. 4 UČENCI Z UČNIMI TEŽAVAMI IN IKT Pri razvoju digitalnih kompetenc so učenci z učnimi V vzgoji in izobraževanju so z dodatnimi veščinami in težavami slabše opremljeni z lastnim znanjem, saj je več težav specialnimi znanji učence, ki imajo učne težave, ustrezno pri sledenju, razvijanju in uporabi IKT pri šolskem delu. opredelili ter strokovno določiti njihove primanjkljaje za lažje Interaktivne vsebine morajo biti dovolj prilagojene, pravilno in premagovanje učnih težav. Ti imajo različne vrste primanjkljajev smiselno sestavljene, prilagojene težavnostnim stopnjam, in so posledično učno manj uspešni glede na svoje vrstnike, saj vsebovati morajo dovolj slikovnega gradiva ter animacij (še počasneje usvajajo znanja ter spretnosti pri učnih predmetih. posebej so poučne pri možnostih ponovitve in korigiranja Učne težave se pri učencih kažejo kot posledica prepleta hitrosti) [10]. dejavnikov, ki vplivajo na učenčevo šolsko delo: podpovprečne Pri delu z učenci z učnimi težavami je bilo s in mejne intelektualne sposobnosti, slabše razvite posameznimi spletnimi orodji, ki so vključevala animacije z samoregulacijske sposobnosti, težave v socialno-emocionalni učno vsebino, videoposnetke, virtualne osebe, zaznati boljše in akomodaciji, primarni socialno-kulturno-jezikovni drugačnosti, hitrejše usvajanje znanja. Gradivo jih je bolj pritegnilo, socialni in kulturni deprivaciji oz. izoliranosti, pomanjkanju informacije so bolje sprejeli preko različnih čutil. Didaktične motiviranosti za delo. Učne težave vplivajo na nekatere ali spletne strani omogočajo poučevanje, utrjevanje in ponavljanje mnoge vidike posameznikovega življenja (izobraževanje, delo, snovi učno šibkejšim učencem, da bodo snov bolje memorirali interakcije v družini, v socialnem okolju) ter se kažejo v različnih ter usvojili. S temi orodji pridobijo znanje na zanimiv in razgiban pogledih. Primanjkljaji se med seboj prepletajo ali so ločeni ter način, ki omogoča pot k samostojnemu pridobivanju iskanja vplivajo na učno delo in na samo življenje [13]. informacij ter nadgraditve obstoječega znanja. Z uporabo Nekateri med njimi z različnimi oblikami pomoči spletnih orodij so bolje motivirani, aktivni, dinamično in zavzeto (dopolnilni pouk, individualna in skupinska pomoč, dodatna rešujejo naloge, abstraktne vsebine bolje konkretizirajo ter si jih strokovna pomoč) pridobijo možnost za premostitev svojih zapomnijo. S tem je proces memoriranja podatkov, ki učencem primanjkljajev. Z uporabo pametnih mobilnih naprav in povzroča težave in nemotiviranost, učinkovitejši ter trajnejši. računalnikov so otroci s posebnimi potrebami bolje motivirani za Nekateri učenci so zaradi slabših tehničnih možnosti imeli učenje, usvajanje ter pomnjenje znanja. Spletne vsebine, orodja omejen ali onemogočen dostop do teh vsebin in se posledično in spletne aplikacije pri učenju digitalnih kompetenc omogočajo niso mogli učiti tako kot njihovi vrstniki. dinamično, nazorno, dostopnejše, multisenzorno podajanje Iz prakse je razvidno, da učenci med brskanjem, informacij, ki so za učence zanimive in privlačne. S tem bolje iskanjem in izbiranjem podatkov pogosto nekritično uporabljajo procesirajo, obdelajo vsebino in njihovo pomnjenje [13]. informacije, saj se ne zavedajo vseh nevarnosti. Njihovo splošno Učitelji učencem z učnimi težavami in premajhno razumevanje in dojemanje je premalo zaznavno. Ne zavedajo se vključenostjo v razred nudijo oporo pri vključevanju v razredno negativnih posledic, saj imajo poenostavljene poglede na okolje, aktivnosti, pouk ter upoštevajo njihove primanjkljaje. tovrstno problematiko, slabše obdelajo ter vrednotijo podatke. S Med šolami prihaja do različnih spodbujanj motiviranosti pridobljenimi informacijami slabše in površno upravljajo, ne učiteljev za poučevanje in motiviranosti otrok za učenje [13]. poznajo varnostnih protokolov ter ukrepov za zaščito svojih vsebin. Pri tem so tudi žrtve izsiljevanj in spletnih prevar, saj nehote pošiljajo podatke nepreverjenim spletnim stranem ali 5 RAZVOJ IN UPORABA DIGITALNIH sogovornikom na družabnih omrežjih. Pri komunikaciji na spletu KOMPETENC PRI UČENCIH Z UČNIMI in družabnih omrežjih je zaznati pomanjkljivo in neprimerno TEŽAVAMI komuniciranje med učenci, kar privede do različnih oblik nasilja med deležniki. Pri pošiljanju, izmenjavi datotek in informacij se Digitalne kompetence se med učenci razvijajo tako v šolskem kot učenci premalokrat zavedajo, da so vse aktivnosti na spletu izvenšolskem okolju pri uporabi IKT. Še posebej so bile v hranljive in jih je ob neprimerni vsebini težje omejiti ter zadnjih dveh letih v času dela na daljavo prisotne velike dileme zaustaviti. Zato jih je potrebno učiti, da se preko učenja digitalnih in težave glede izpeljave učno-vzgojnega procesa. Komunikacija kompetenc ustvarja digitalna identiteta na spletu, ki omogoča je potekala v virtualnem svetu, s tem pa so morali vsi deležniki drugim vpogled v delovanje na spletu. Učence o tem redno hkrati razvijati digitalne kompetence in spretnosti. Vsakodnevno izobražujemo učitelji dodatne strokovne pomoči skupaj z so se morali soočati z novimi izzivi glede zagotavljanja učiteljem računalništva. kvalitetne izvedbe pouka in ostalih učnih vsebin. Po zaprtju šol Pri pouku so učenci z učnimi težavami pri izvajanju so se vzgojno-izobraževalne ustanove različno spoprijele z dodatne strokovne pomoči spoznavali omenjene nevarnosti. izvajanjem pouka na daljavo. Uporabljale so različna spletna Tako so se morali pri pouku na daljavo soočiti z spremembo orodja – ZOOM, Microsoft Teams, Cisco Webex, Jitsi, Skype, okolja, drugačnim bioritmom, organizacijo dela, načinom učenja Vox Arnes, Youtube. Pri svojem delu so uporabljali spletno ter opravljanjem nalog s pomočjo IKT. Med urami dodatne pošto, spletne učilnice ter interaktivne spletne strani. Po odprtju strokovne pomoči so se učenci naučili iskati osnovne informacije vzgojno-izobraževalnih ustanov se je marsikje tovrsten način v spletnih učilnicah, preko elektronske pošte in videokonferenc. 473 Učence smo učitelji DSP seznanili o uporabi spletnih gesel, digitalne identitete je na slabše osveščeno, saj učenci brskalnikov, iskanju ključnih informacij, preverjanju le-teh. Pri neredno menjavajo gesla, še vedno preveč podatkov posredujejo tem smo večkrat ugotovili, da sta njihovo šibko splošno znanje na sumljivih spletnih straneh ali na socialnih omrežjih. Pri tem in primanjkljaji težava za učinkovito in uspešno obdelovanje jih spodbujamo za večjo skrb in ozaveščenost za boljšo varnost. informacij. Zraven tega je tudi prešibko poznavanje strokovnih terminov, slabše dojemanje postopkov iskanja informacij … Učenci z učnimi težavami so pri ustvarjanju predstavitev za 6 ZAKLJUČEK govorne nastope potrebovali pomoč pri urejanju in obdelavi Informacijsko-komunikacijska tehnologija je spremenila način besedil in slikovnega gradiva (powerpoint, word, slikar, …), saj dela v službah in prostem času. Tako je posegla tudi v vzgojno- so bili postopki za dosego želenih rezultatov prezahtevni zanje. izobraževalni sistem, kjer je omogočila drugačen in sodoben Pri nekaterih učencih je bila tudi težava pomanjkanje ustrezne način učenja za učence v učnem procesu. Učenci so pridobivali računalniške in druge opreme zaradi šibkega socialnega statusa nove učne vsebine, ki so jim omogočile nova spoznanja in njihovih družin, nezmožnosti nudenja pomoči ostalih družinskih veščine v svetu digitalnih kompetenc. Slednje bodo kasneje v članov. življenju potrebovali in uporabljali. Učenci z učnimi težavami so Prav tako se je pokazal nov izziv pri strukturiranem učenju v tem oziru pogosto v zaostanku v primerjavi s svojimi vrstniki, postopkov od ustvarjanja, obdelave učnih gradiv do objavljanja saj potrebujejo več časa za usvajanje in uporabo digitalnih končnih izdelkov v spletne učilnice, saj je bilo potrebno kompetenc. Nemalokrat se ne zavedajo pasti in negativnih učencem večkrat pokazati s slikovnim materialom poti do posledic pri uporabi spleta, mobilnih naprav, podajanja in spletnih učilnic, prijave vanje in pravilnega nalaganja datotek. Za sprejemanja informacij. Njihovo znanje je šibko in premalo vedo utrjevanje uporabe in nalaganja gradiv v spletne učilnice je bilo o komuniciranju, varnosti, iskanju, objavljanju informacij na potrebno večkrat ponoviti posamezne korake, tako da so učenci spletu, o varni uporabi teh naprav. Pedagoški delavci skušamo kasneje samostojno uporabljali dane pripomočke ter programe. pomagati z usmerjanjem, izobraževanjem in ustrezno Uporabe kompleksnejših baz podatkov omenjeni učenci komunikacijo pri učenju in uporabi omenjenih resursov. S tem se samostojno niso zmogli uporabljati, saj je kompleksnost bo učencem z učnimi težavami na njim razumljiv način postopkov zanje prezahtevna. predstavilo abstraktne vsebine, prilagodilo spoznavanje novih Varna uporaba spleta, socialnih omrežij in aplikacij je vsebin z omenjenega področja ter jih opolnomočilo pri njihovi pomembna za zdrav psihosocialni razvoj mladih. Pri uporabi uporabi. Tako bodo tudi spoznavali varno rabo naprav in spleta, varnih gesel za elektronsko pošto, pri prijavi v aplikacije, jih je ki je pomembna pri ohranjanju zdravega načina življenja. bilo potrebno naučiti uporabe pametnih in varnih gesel. S tem so imeli učenci z učnimi težavami nekaj težav, kako se tega lotiti, 7 VIRI IN LITERATURA saj je šlo za kombinacijo različnih, na videz nesmiselnih znakov. [1] OECD. (2002). Measuring the information economy. Dostopno na naslovu S pomočjo in nekajkratnimi ponovitvami so to osvojili. http://www.oecd.org/sti/ieconomy/2771153.pdf. (26. 7. 2022). [2] Stare, M. in Bučar. M. (2005). Učinki informacijsko-komunikacijskih Učenje digitalnih kompetenc je zavzemalo tudi tehnologij. Ljubljana: Fakulteta za družbene vede. prepoznavo nezaželene e-pošte, tveganih spletnih strani, saj so [3] Tondeur, J., Aesaert, K., Pynoo, B., van Braak, J., Fraeyman, N. in bili nekateri učenci že žrtve tovrstnih spletnih prevar. Osnovne Erstad, O. (2016). Developing a validated instrument to measure preservice teachers' ICT competencies: Meeting the demands od the 21st elemente prepoznave tveganih spletnih strani so prepoznali, za century. British Journal of Educational Technology, 48(2), 462–472. bolj dovršene sumljive spletne strani pa je bilo potrebno kar Dostopno na naslovu http://onlinelibrary.wiley.com/doi/10.1111/ bjet.12380/abstract (26. 7. 2022). nekaj ponovitev in opozoril nanje. Nekaterim so zaklenili [4] Brečko, B. N.,Vehovar, V. (2008). Informacijsko-komunikacijska uporabniške profile na spletnih igrah, socialnih omrežjih v tehnologija pri poučevanju in učenju v slovenskih šolah. Ljubljana: Pedagoški inštitut. zameno za plačljivo odškodnino. V veliko pomoč pri teh [5] Wechtersbach, R. (2006). Digitalna kompetenca in njeno izgrajevanje. vsebinah je tudi spletna stran safe.si, kjer s primernimi vsebinami Organizacija, 41(1). 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(Elektronski vir) Dostopno na naslovu http://www.zrss.si/pdf/o- naravi-ucenja.pdf (26. 7. 2022). učencev potrebuje pomoč pri osnovnem iskanju pravilnih [9] Eurydice (2012). Pomembni podatki o učenju in inovacijah z IKT po šolah v informacij, shranjevanju le-teh, obdelave in predstavitve. Evropi 2011. Ljubljana: MIZŠ. [10] Rugelj, J., (2007): Nove strategije pri uvajanju IKT v izobraževanje. Polovica učencev z učnimi težavami se je v zadnjem letu veliko Dostopno na naslovu https://skupnost.sio.si/sio_arhiv/sirikt/www.sirikt.si/ naučila in dokaj samostojno obvladala pridobivanje, obdelavo ter fileadmin/sirikt/predstavitve/2007/SIRIKT_2007_JRugelj.pdf (26. 7. 2022). prikaz informacij. Ostali učenci pa potrebujejo še pomoč pri [11] Zakrajšek. S. (2022). Model za oceno scenarijev za povečanjedigitalnih kompetenc dijakov v splošni gimnaziji v republiki Sloveniji. Maribor: naštetih elementih digitalnih kompetenc. Varna raba in zaščita Fakulteta za organizacijske vede. 474 [12] Ferrari, A. (2013). DIGCOMP: A framework for developing and understanding digital competence in Europe. European Commission: Joint Research Centre. Dostopno na naslovu http://publications.jrc.ec.europa.eu/repository/bitstream/JRC83167/lb- na26035-enn.pdf. (26. 7. 2022) [13] Nagode, A. (ur.) (2008). Navodila za prilagojeno izvajanje programa osnovne šole z dodatno strokovno pomočjo. Primanjkljaji na posameznih področjih učenja. Ljubljana: Zavod Republike Slovenije za šolstvo. 475 Digitalna pismenost kot sestavni del razrednih ur v osnovni šoli Digital Literacy as an Integral Part of Classroom Lessons in Primary School Tina Pajnik Sonja Strgar Osnovna šola Vide Pregarc Osnovna šola Antona Martina Slomška Vrhnika Ljubljana, Slovenija Vrhnika, Slovenija tpajnik@gmail.com sonja.strgar@guest.arnes.si POVZETEK Digitalliteracy, class hours, online tools, sustainable development goals V prispevku so predstavljeni primeri razrednih ur, pri katerih so se uporabljale digitalne tehnologije z namenom razvijanja digitalne pismenosti pri učencih osnovne šole. Po pregledu 1 UVOD strokovne literature in priporočil na področju šolstva ostaja digitalna pismenost integrirana v celoten vzgojno-izobraževalni Spremembe v šolskem prostoru so pogojene s stanjem v družbi. sistem, kar omogoča elemente digitalnega opismenjevanja Kljub dolgoletnim prizadevanjem šol, ki so se glede na svoje integrirati v vse šolske predmete. Razredne ure ponujajo širok finančne in intelektualne vire soočale z vzpostavitvijo nabor življenjskih tem, ki prve korake v digitalno pismenost digitalnega opismenjevanja, še vedno ostaja sistematično umeščajo v kontekst. S tega vidika so razredne ure lahko razvijanje digitalnih kompetenc prepuščeno avtonomiji vzgojno- izhodišče za razvijanje digitalne pismenosti, saj se spletna orodja izobraževalnih zavodov. V zadnjih dveh letih je učenje na kažejo kot uporaben element pri razvijanju vseživljenjskih tem. daljavo pokazalo nove izzive in možnosti za izboljšave. Prav s tem namenom smo predstavili nabor sedmih tematskih Pandemija koronavirusa je digitalni prehod in preobrazbo samo sklopov razrednih ur, ki so potekale na dveh osnovnih šolah. še močno pospešila [1]. S šolskim letom 2021/22 vse več šol sistematično pristopa k načrtu digitalne pismenosti ob pomoči KLJUČNE BESEDE smernic in dokumentov, ki so na voljo. Izziv vsake šole je delujoča in uporabna računalniška oprema, digitalno pismen Digitalna pismenost, razredne ure, spletna orodja, cilji strokovni delavec in spletno učno okolje, do katerega ima vsak trajnostnega razvoja učenec dostop. ABSTRACT Digitalno opismenjevanje bi zaradi digitalnega napredka družbe sicer moralo biti kot del obveznega programa osnovne The article presents examples of classroom lessons in which šole sistemsko urejeno, vendar v praksi kljub temu ni tako. Kljub digital technologies were used with the aim of developing digital desetletnim opozarjanjem strokovni delavci na lastno pobudo literacy among primary students. After a review of the iščejo načine, kako integrirati digitalno pismenost v natrpan professional literature and recommendations in the field of redni učni program. Šolska zakonodaja ne predpisuje obveznega education, digital literacy remains integrated into the entire predmeta, ki bi zajela vse učence, da bi lahko vsak šoloobvezni educational system, which enables elements of digital literacy to otrok načrtno razvijal digitalne zmožnosti, zato učitelji iščejo be integrated into all school subjects. Classroom lessons offer a načine, s katerimi bi digitalno pismenost integrirali v redni del wide range of life topics that put the first steps in digital literacy pouka. Ker pa so razredne ure ena od možnosti, v katere se da into context. From this point of view, classroom lessons can be a integrirati elemente digitalnega opismenjevanja in razvijanje starting point for developing digital literacy, as online tools prove digitalnih kompetenc, smo se na Osnovni šoli Vide Pregarc v to be a useful element in developing lifelong topics. It was for Ljubljani in Osnovni šoli Antona Martina Slomška Vrhnika this purpose that we presented a set of seven thematic sets of odločili izvesti razredne ure, ki bi učencem ponudile spoznavanje classroom lessons, which took place at two elementary schools. in uporabo digitalne opreme in spletnih orodij vzporedno z razvijanjem kritičnega mišljenja, socialno-emocionalnih veščin KEYWORDS ter z ozaveščanjem o varni rabi spleta. Permission to make digital or hard copies of part or all of this work for personal or 2 DIGITALNA PISMENOST V OSNOVNI classroom use is granted without fee provided that copies are not made or distributed ŠOLI 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 V dokumentih in strokovni literaturi s področja izobraževanja se be honored. For all other uses, contact the owner/author(s). največkrat pojavi besedna zveza digitalna kompetenca, ki izvira Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). iz angleščine, vendar pa se v slovenskih učnih načrtih vse bolj 476 uveljavlja termin digitalna zmožnost [2]. Je zgolj ena od osmih moti ali pa kakšen problem, o katerem se nato temeljnih zmožnosti, ki zagotavljajo odraslim dovolj orodij za pogovorimo na razredni uri. učinkovito spopadanje z novimi izzivi, omogočajo praktično in  Dobre lastnosti posameznikov v razredu - Anketa je čustveno oporo, so pomembne za posameznika in skupnost [3], anonimna, učenci za vsakega sošolca zapišejo eno vendar digitalna zmožnost vstopa v vse ostale zmožnosti in se z dobro lastnost (slika1). Anketo lahko razrednik uporabi njimi prepleta. za izdelavo srčkov v WordArt-u, ki jih podari učencem Z revidirano konceptualizacijo ključnih kompetenc leta 2018 so (slika 2) ob zaključku šolskega leta ali pa jih natisne in se področja kompetenc preimenovala in preoblikovala, tako da obesi v učilnico na vidno mesto, kar pripomore k smo v strokovni literaturi po letu 2018 prepoznali digitalno vzdrževanju dobrih odnosov in povezanosti v oddelku. kompetenco kot sestavni del digitalne pismenosti [3]. Ta obsega nabor znanj, spretnosti in vedenj, kar omogoča posamezniku, da uporablja in deluje v digitalnem svetu, obenem pa digitalna pismenost omogoča varno in kritično uporabo tehnologij informacijske družbe na različnih področjih [3]. Digitalno pismen učenec naj bi v prvi vrsti poznal digitalne aparate in pripomočke in jih tudi uporabljal, tekom šolanja naj bi spoznal spletna orodja in pridobil znanja in spretnosti, s katerimi bi lahko brez težav opravljal svoje vsakodnevne potrebe. Z uporabo digitalne tehnologije bi tako učenec poiskal in upravljal različne informacije ter razvil strategije za doseganje ciljev. Tem splošnim smernicam pa se priključuje še kritično razmišljanje, zakonitosti digitalno-socialnega okolja ter varna raba interneta. Digitalna pismenost tako zajema zelo raznolik nabor vsebin in veščin, ki bi jih učenec ob zaključku osnovne šole moral poznati oz. obvladati. Pri tem je potrebno poudariti, da je tako kot pri vseh didaktikah posameznih predmetov, tudi pri digitalnem opismenjevanju smiselno izhajati iz razvojne stopnje otrok ter utrjevati in nadgrajevati digitalna znanja in spretnosti. Program Slika 1: Primer spletne ankete osnovne šole sicer ponuja računalništvo kot neobvezni in obvezni izbirni predmet, vendar kot tak omogoča razvoj digitalne pismenosti le skupini učencev, ki si je ta predmet izbrala. Ker je od avtonomije učitelja odvisno, koliko in kaj bo v svoj redni pouk vnašal s področja digitalnega opismenjevanja, so razlike med šolami lahko zelo velike. Razredne ure se v osnovni šoli izvajajo od četrtega do devetega razreda enkrat tedensko, včasih pa tudi po potrebi. Za učence prvega vzgojno-izobraževalnega obdobja so razredne ure sestavni del pouka, saj so vsebine integrirane v več predmetov, najbolj pa sovpadajo s spoznavanjem okolja. Ker se vsebine razrednih ur za učence od četrtega do devetega razreda dotikajo razredne klime, odnosov v razredu in pravil življenja v skupnosti, so s svojim širokim naborom priložnost za povezovanje z digitalnim opismenjevanjem, saj spletna orodja, komunikacijske spretnosti in digitalna tehnologija dobijo vseživljenjski okvir. 3 TEMATSKE RAZREDNE URE IN DIGITALNA PISMENOST V PRAKSI 3.1 Uporabnost spletnih anket Slika 2: Primer srčka v WordArt-u Razrednik velikokrat učence vpraša za mnenje, saj s tem ustvarja boljšo razredno klimo. Eden od načinov za pridobitev mnenja  Ena od tem razrednih ur v tretjem vzgojno- učencev so spletne ankete. V prikazanih primerih je spletne izobraževalnem obdobju je obravnavanje spletnega ankete izdelal razrednik, učenci so ankete le izpolnjevali. Prijave nasilja. Razrednik učencem pripravi spletno anketo, niso bile potrebne, saj so bile ankete anonimne ali pa so vpisali kjer učenci najprej zapišejo ime in priimek, nato pa ime in priimek v anketo. Primeri spletnih anket med razrednimi odgovorijo na vprašanja, ali vedo kaj je spletno nasilje, urami: če so ga že doživeli ali pa izvajali nad drugimi. Na  Spihalnik- Anketa je anonimna in ima eno samo trditev: podlagi ankete se potem v razredu naredi razprava, kjer »Kok je to bedno …«. Učenci zapišejo, kar jih v šoli poiščemo rešitve in nasvete za preprečevanje spletnega 477 nasilja. Pomembno je, da učenci spregovorijo o svojih Učenci se zavedajo, da vse več administrativnih del poteka izkušnjah in poiščejo pomoč. preko spleta. Postopki vpisa in prijav na različnih spletnih  Pri razredni uri smo ankete uporabili tudi pri debati o straneh potekajo na podoben način, zato se na razrednih urah od mobilnih napravah in zasvojenosti z njimi. Anketa je četrtega razreda dalje učenci preizkušajo v ustvarjanju računov bila anonimna, zanimalo nas je, katere pametne naprave in prijavah v razne spletne strani založb ali pa v Discord in Zoom, uporabljajo in za kakšen namen (šola ali za zabavo) ter ki ga uporabljajo za potrebe učenja na daljavo. katere pametne naprave bi lahko prinesli v šolo za potrebe pouka. Na podlagi analize ankete smo nato na 3.3 Svetovni dan otrok razredni uri razvili debato o zasvojenosti z digitalnimi Razrednik lahko svoj oddelek vključi v projekt Svetovni dan napravami in s socialnimi omrežji, ki smo si jih ogledali otrok, ki ga izvaja Unicef. Svetovni dan otroka, 20. novembra, je še v praksi in se pogovorili o nastavitvah profila ter o dan, ko države podpisnice Konvencije o otrokovih pravicah objavah video in slikovnih materialov. obnovijo zavezo za uresničevanje otrokovih pravic. Opisani  Primer spletne ankete, ki se zelo dobro odnese v praksi primer je bil izveden na daljavo, kjer smo preko Microsoft je tudi anonimna anketa z enim nedokončanim stavkom Teams-ov sodelovali v omenjenem projektu. Z učenci osmega »Želim, da bi učiteljica vedela …«. Odgovor na razreda smo se naučili uporabljati omenjeno okolje ter se aktivno vprašanje je lahko poljubno dolg, navadno pa učenci ali vključili v debato. Po dogodku so učenci napisali prispevek za kaj pohvalijo ali pa napišejo težave, ki jih pestijo ali pa šolsko spletno stran. Učenci so zapisali besedilo in priložili slike, teme, ki jih zanimajo. Pri razredni uri se nato naredi ki so jih sami posneli (slikanje zaslona). Nato je razrednik analiza in odgovorimo na vsa vprašanja, ki so bila v prispevek objavil na šolski spletni strani (slika 4). anketi. Analiza anonimnih odgovorov daje razredniku možnost za vpogled v razredno klimo, odnose med učenci ter morebitne stiske in izzive, s katerimi se soočajo. Spletne ankete se navadno rešujejo pri razredni uri. Razrednik rezervira računalniško učilnico, kjer učenci delajo na računalnikih, ali pa se dogovori z učenci, da razrednik učencem posreduje naslov spletne ankete in jo učenci rešijo doma, kar navadno rešujejo na pametnih telefonih ali tablicah. Spletne ankete ponujajo širok nabor vsebin, ki omogočajo anonimnost in so lahko zelo dobro izhodišče za obravnavo tem, ki učence zanimajo. 3.2 Vpogled v rezultate NPZ Digitalno znanje razvijamo tudi pri vpogledih v rezultate nacionalnega preverjanja znanja za učence šestega in devetega Slika 4: Primer objave na šolski spletni strani razreda. Razrednik je prisoten pri predmetu, ki ga poučuje. Z učenci najprej odpre spletno stran https://npz.ric.si/ (slika 3), Sooblikovanje šolske spletne strani je ena od digitalnih nato pomaga pri prijavi učencev, kjer se vpiše šifro in emšo. Sledi zmožnosti, ki zahteva ne samo poznavanje in uporabo spletnih vpogled v rezultate posameznikov, nato pa razlaga točk pri orodij, ampak tudi tvorbo besedila v določenem formatu, posameznih nalogah. V kolikor je potrebno, se zapiše tudi ugovor njegovo oblikovanje in vstavljanje slikovnega materiala v na število točk. besedilo. Obenem avtor prispevka nosi odgovornost za soustvarjanje šolske podobe v spletnem prostoru, kar je tudi ena od vzgojnih komponent, ki jih želimo privzgojiti. 3.4 Otroci po svetu in izzivi mladostništva V osmem razredu smo izvedli tematsko razredno uro z naslovom Otroci po svetu. S pomočjo orodja Zoom smo izvedli videokonferenčno razredno uro, saj so bili učenci OŠ Antona Martina Slomška Vrhnika napoteni v karanteno in so delali od doma. Predavala je učiteljica Tina Pajnik z OŠ Vide Pregarc. Pogovarjali smo se o vrednotah hrane, vode in doma, ter o različni šolski prehrani po svetu. Učiteljica je pokazala tudi, kakšne igre imajo v različnih celinah oz. državah, kako se razlikujejo in npr. v Indiji si otroci iz odpadnih stvari naredijo vozičke in se potem spuščajo ali pa se poganjajo. Pogovarjali smo se tudi, kaj nam pomeni dom in, da to ni samo dom, ampak tudi družina. Učenci so debatirali o tem, kaj je pomembno, ko se Slika 3: Vpogled v NPZ preseliš v drugo državo. Rešili so anketo v Padlet-u na temo, kaj pomeni dom in kaj je pomembno pri vključevanju v novo okolje (slika 5). 478 Slika 7: Pregled poti v šolski okolici Ponovili so znanje o orientaciji in nato na projiciran zemljevid na beli tabli narisali pot, po kateri gredo v šolo. Označili so točke na zemljevidu, ki so se jim zdele nevarne ali nepregledne. Dobljen razredni zemljevid so nato primerjali z načrtom varnih poti in Slika 5: Primer videokonferenčne razredne ure ugotovili, da ima veliko skupnih značilnosti, saj so učenci prepoznali nevarne odseke ali nepregledne prometne poti. Ob Padlet so učenci sedmih in osmih razredov uporabili tudi na koncu razredne ure so pripovedovali o svojih izkušnjah z razredni uri, ki se je izvajala na temo zasvojenosti in drugih zemljevidi oz. z navigacijo. Preizkusili so se v iskanju lokacije izzivih mladostništva. Razredna ura je potekala v računalniški znotraj meja države ter poiskali razdalje med Ljubljano in učilnici, kjer so raziskovali oblike zasvojenosti. Vsak učenec je drugimi mesti. Podobno razredno uro je smiselno ponoviti v izdelal kratek povzetek o poljubni zasvojenosti, nato pa ustvaril petem razredu, ko se učenci pripravljajo na kolesarski izpit. svoj zavihek v Padlet okolju (slika 6). 3.6 Cilji trajnostnega razvoja Učenci šestih razredov so izvedli razredno uro na temo ciljev trajnostnega razvoja v računalniški učilnici. Zaradi velikega števila učencev tujcev v oddelku je bilo potrebno spregovoriti o kulturnih raznolikostih, strpnosti, migracijah in večjezičnih okoljih. Najprej so šestošolci v Padlet-u napisali na lističe, kaj si želijo. Nastal je nabor želja, pri katerem se je lahko avtor oglasil in kaj dodal ali pojasnil, ali pa je ostal anonimen. Nato smo želje na lističih razvrstili v dve skupini, in sicer v materialno in nematerialno. Pod materialno so učenci oblikovali dve skupini: (elektronske) igrače in hišni ljubljenčki. Pri nematerialnem pa so tudi prepoznali dve obliki želja: dosežki in osnovne človekove potrebe. Posebej sta namreč izstopali dve želji, »varnost« in »da ne bi bilo več vojn«, ki sta sprožili čustven odziv sošolcev, da so Slika 6: Izdelava razrednega Padleta začeli spreminjati svoje želje. S pomočjo spletnih strani Projekta MIND (https://www.karitas.si/projekt-mind-migracije- Pri delu so učenci uporabljali računalnik za iskanje podatkov, za povezanost-razvoj/) in Ciljev trajnostnega razvoja Združenih shranjevanje predstavitve v določenem formatu, za izmenjavo narodov (https://unis.unvienna.org/unis/sl/topics/sustainable_ informacij in sporazumevanje ter sodelovanje v skupnem development_goals.htm) so šestošolci spoznavali težave in omrežju. Ob koncu razredne ure so poročali o svojih ugotovitvah, izzive, s katerimi se sooča tako Slovenija kot preostali del sveta. nato pa skupaj z razrednikom naredili povzetek. Ob zaključku ure so se učenci pomerili v spletnem kvizu (slika 8), ki je prosto dostopen na naslovu https://take.quiz- 3.5 Varna pot v šolo maker.com/QU1WXA0X. Kviz s sedemnajstimi vprašanji je Učenci četrtega razreda so na začetku šolskega leta spoznali prosto dostopen, saj je bil del nagradne igre, ki je potekala leta publikacijo s pravili šolskega reda, vzgojnim načrtom in načrt 2021, a je še vedno dobro orodje za preverjanje, saj se pravilni varne poti v šolo. Razredna ura je potekala tako, da so učenci odgovori beležijo in podajajo utemeljitve odgovorov. najprej spoznali tiskano publikacijo, nato pa vse dokumente poiskali na šolski spletni strani. Pri tem so se učili poiskati določene informacije na šolski spletni strani, raziskali so posamezne zavihke in poiskali določene informacije kot npr. jedilnik, seznam šolskih potrebščin, urnik šolske knjižnice. Dalje so v Google Earth poiskali OŠ Vide Pregarc v Ljubljani in si ogledali okolico (slika 7). 479 Slika 10: Primer reševanja spletnega kviza na temo ekologije Slika 8: Primer reševanja kviza 4 ZAKLJUČEK Prikazani primeri iz prakse potrjujejo, da se proces 3.7 Ekološke vsebine digitalnega opismenjevanja lahko načrtno izvaja v celotnem Učenci četrtih razredov so izvedli razredno uro na daljavo in se oddelku pri razrednih urah. Ker so razredne ure zasnovane z povezali s šolsko knjižničarko, saj so se vsebine ure nanašale na življenjskimi tematikami, učitelj razrednik lahko posega po ekologijo. Najprej so po navodilih razredničarke vstopili v različnih spletnih orodjih, ki jih integrira v vsebine. Učenci lažje spletno učilnico Knjižnica ter poiskali nabor prosto dostopnih sodelujejo in spoznavajo uporabnost spletnih orodjih, če se le-ta spletnih besedil z ekološko vsebino. Izbrali so tri besedila in jih uporabljajo v nekem življenjskem kontekstu. prebrali. O prebranem so imeli možnost poročati preko Zooma Da bi pridobili povratne informacije, so udeleženci rešili na dveh terminih, po povratku v šolske klopi pa so četrtošolci kratko spletno anketo (slika 11), v kateri so izrazili svoje mnenje, opravili še dve nalogi v šolski knjižnici. Prva naloga je bila v pripombe in pobude na izpeljane učne ure. spletnem slovarju Franček poiskati določen pojem, ki ga je knjižničarka pripravila na lističu (slika 9). Delo s tiskanimi in spletnimi slovarji je obenem tudi cilj knjižnično-informacijskega znanja, kjer mladi bralci spoznavajo referenčno zbirko. Slika 11: Primer reševanja spletne ankete Slika 9: Primer iskanja pomena besede ekološki Anketa je za učence vsebovala tri preprosta vprašanja. Na vprašanje, kaj bi pohvalili pri izvedenih razrednih urah, smo pri Druga naloga je bila reševanje spletnega kviza Velika četrtošolcih dobili odgovore, ki smo jih razvrstili v dve skupini. Grinijeva pustolovščina (slika 10), ki je dostopen na naslovu 92 % učencev je odgovorilo, da jim je pri razrednih urah bila https://www.grini.si/igralnica/velika-grinijeva-pustolovscina. Z najbolj všeč uporaba računalnikov, aplikacij in spletnih strani. reševanjem kviza so učenci preverili svoje znanje o razvrščanju Med omenjenimi spletnimi aplikacijami je bila v 90 % največkrat odpadkov, načine varčevanja z energijo, uporabi ekoloških omenjena aplikacija Google Earth, ki so jo učenci imeli najraje. otokov ter zbirnih centrov. Ostalih 8 % je pohvalilo izbrane tematske sklope (ekologija in trajnostni razvoj). Odgovori na vprašanje, kaj bi pri izvedenih razrednih urah spremenili, so bili zelo enolični. Kar 98 % pravi, da sicer ne bi ničesar spreminjali, bi si pa želeli več takšnih ur, kjer se uporablja digitalna orodja. 76 % jih je učiteljici sporočilo, da si želijo sodelovanja in uporabo digitalnih orodij tudi v prihodnjem šolskem letu, od tega jih 90 % predlaga, da bi se podobne ure izvajale tudi pri drugih predmetih. 480 Prav vsi učenci od 6. do 9. razreda so ob koncu izpeljanih Za učence je bila že sama uporaba digitalne opreme razrednih ur pohvalili spletne ankete. Zapisali so, da jim je motivacija za delo, poleg tega pa so imeli možnost sodelovanja, velikokrat mnogo lažje stvari zapisati kot povedati, še posebej, (so)ustvarjanja, anonimnosti in varnosti. Ker so v razredne ure če je anketa anonimna. Posebej so pohvalili spletno anketo bili vključeni vsi učenci v oddelku, so res imeli vsi možnost Spihalnik, saj so imeli občutek, da lahko povedo prav vse, kar jih prispevati svoje ideje in uporabljati spletna orodja v skladu s moti, pa si v živo ne upajo povedati na glas. Vsi učenci so bili svojo stopnjo digitalne pismenosti. Razrednik je lahko vsebine in navdušeni nad spletno anketo Dobre lastnosti posameznikov, saj navodila diferenciral ter ponudil boljšim učencem zahtevnejše jim zelo veliko pomeni izdelan srček z njihovimi dobrimi naloge, poleg tega so dejavnosti bile zasnovane tako, da so lastnostmi. Zapisali so, da ga bodo shranili na posebno mesto. vključevale vse otroke – od učencev s posebnimi potrebami do 96 % učencev je pohvalilo delo v Padletu, saj zelo radi ustvarjajo učencev tujcev. Izbrani tematski sklopi so bili življenjski in blizu skupaj z ostalimi učenci enoten plakat. Poudarili so, da so jim učencem, niti ni bilo potrebno imeti predznanja, kar je omogočilo bile všeč izbrane teme. Kot pomanjkljivost so zapisali, da so večji dvig aktivnosti kot pri rednih urah. Povratna informacija nekateri sošolci počasni in jih je potrebno čakati. 100 % učencev učencev ne glede na starost vedno znova sporoča, da si želijo več si želi, da bi več učiteljev večkrat letno imelo anonimno anketo dinamike, aktivnega vključevanja in uporabe digitalnih orodij. Želim, da bi učiteljica vedela … To se učencem zdi dobra Poleg tega izpostavljajo tudi to, da želijo biti slišani, kar je priložnost, da poveš, kar ne moreš v razredu pred ostalimi. pomemben element pri oblikovanju varnega učnega okolja. Vpogled v NPZ jim po večini (53 %) ni bil zanimiv, so se pa vsi strinjali, da je nujen, če želijo videti svoje izdelke NPZ. Pri LITERATURA IN VIRI izvedbi Svetovnega dne otroka so pohvalili predvsem udeležbo [1] Vesna Lešnik Štefotič, 2021. Digitalne kompetence – stanje in prihodnost. predsednika RS Boruta Pahorja. Pri predavanju Otroci po svetu Mednarodno inovativno poslovanje = JournalofInnovative Business and Management, 13(1). 79-88. Dostopno na naslovu pa je vseh 100 % poudarilo, da jim je bilo všeč, ker je bila https://www.dlib.si/stream/URN:NBN:SI:DOC-IR8SEUYR/0d0c7541- izvajalka delavnice oseba, ki je bila izredno energična. Splošno a8c0-4f1c-85df-4bcc188606b9/PDF(1.8.2022) za vse razredne ure, ki so bile izvedene na tak način, pa so učenci [2] e-šolstvo: Pot do e-kompetenstnosti. Dostopno na naslovu https://projekt.sio.si/wp-content/uploads/sites/8/2015/01/E- zapisali, da jim je bilo všeč predvsem delo po skupinah, solstvo_pot_do_e-kompet_BILTEN_2012_final_web_pot_do_ekomp.pdf sodelovanje med vsemi deležniki. Vseh 100 % si želi še več (1.8.2022) [3] Petra Javrh (Ur.). 2018. Digitalna pismenost. Andragoški center Slovenije. razrednih ur izpeljanih na tak način. Dostopno na naslovu https://www.dlib.si/stream/URN:NBN:SI:DOC- NKZPZO9Q/80497777-6718-41ff-99a2-b186288f388f/PDF (1.8.2022) 481 Pandemija COVID-19 in digitalne kompetence študentov COVID-19 Pandemic and Digital Competencies of Students Pia Pičulin Anja Žnidaršič Marjeta Marolt Univerza v Mariboru, Fakulteta Univerza v Mariboru, Fakulteta Univerza v Mariboru, Fakulteta za organizacijske vede za organizacijske vede za organizacijske vede Kranj, Slovenija Kranj, Slovenija Kranj, Slovenija pia.piculin@student.um.si anja.znidarsic@um.si marjeta.marolt@um.si POVZETEK mišljenje še dodatno okrepila [2]. Pandemija COVID-19 ni vplivala le na vsakdanje življenje, ampak tudi na izobraževalne Digitalne kompetence so v 21. stoletju ključne, saj omogočajo sisteme po vsem svetu. Izobraževalne ustanove so bile primorane varno in učinkovito uporabo informacijske tehnologije pri delu čez noč vzpostaviti ali nadgraditi izobraževanje na daljavo, kar in v prostem času. Digitalne kompetence so se v času pandemije je predstavljalo velik izziv za visoko šolstvo [3]. Med drugim so Covid-19 izkazale za pomembne tudi v visokem šolstvu. Zaradi si morali študenti zagotoviti ustrezno delovno okolje, da so se razmer je študij potekal na daljavo, zato so si morali študenti lahko vključili v pedagoški proces na daljavo. Pri tem so bili zagotoviti ustrezno delovno okolje, da so se lahko vključili v zaznani različni nivoji digitalnih kompetenc, saj nekateri študenti pedagoški proces na daljavo. Na podlagi rezultatov raziskave pri vzpostavitvi delovnega okolja za študij na daljavo niso imeli ugotavljamo, da imajo anketirani slovenski študenti dokaj visok težav, drugim pa je to predstavljalo velik izziv. nivo osnovnih digitalnih kompetenc in da so si v času pandemije Digitalne kompetence lahko merimo s pomočjo evropskega COVID-19 le nekoliko izboljšali že obstoječe digitalne okvira digitalnih kompetenc za državljane (DigComp 2.1), ki je kompetence. primeren za uporabo v različnih sektorjih in disciplinah [4]. Okvir DigComp 2.1 sestavlja pet sklopov oz. glavnih področij KLJUČNE BESEDE kompetenc: informacijska pismenost, komuniciranje in Digitalne kompetence, študij na daljavo, študenti, COVID-19 sodelovanje, izdelovanje digitalnih vsebin, varnost in reševanje ABSTRACT problemov. Vsak sklop sestavlja 3 do 6 kompetenc (skupaj 21), za vsako od teh kompetenc je opredeljenih 8 ravni doseganja In the 21st century digital competencies became crucial as they kompetenc. Te ravni so povezan z Bloomovo taksonomijo učnih enable effective use of information technology at work and in dosežkov. Obstajajo tudi drugi okvirji merjenja digitalnih leisure time. During the COVID-19 pandemic digital kompetenc, npr. globalni okvir digitalne pismenosti (Digital competencies have also proved to be essential in higher Literacy Global Framework ali krajše DLGF) in Avstralski education. Due to the circumstances, distance learning was model okvirja temeljnih veščin (Australian Core Skills established and the students had to ensure an appropriate working Fremework ali krajše ACSF). DLGF je nadgradnja okvirja environment in order to be able to participate in the pedagogical kompetenc DigComp 2.0 [5], medtem ko ACSF digitalno process. Based on the results from our survey we can conclude pismenost v svoj model uvršča kot šesto veščino, ki poleg učenja, that Slovenian students who respond to the survey have a fairly branja, pisanja, ustne komunikacije in računanja, igra pomembno high level of basic digital competencies and that they only vlogo za posameznikovo vključevanje v družbo in delo [6]. slightly improved their existing digital competencies during the Mnogi (npr. [7]–[9]) izpostavljajo, da je imela pandemija COVID-19 pandemic. COVID-19 velik vpliv na študij, vendar je malo znanega ali je posledično vplivala tudi na razvoj digitalnih kompetenc, zato nas KEYWORDS je zanimalo: (1) kakšen so trenutne digitalne kompetenc Digital competencies, distance learning, students, COVID-19 študentov v Sloveniji, ter (2) mnenje študentov glede vpliva pandemije COVID-19 na razvoj digitalnih kompetenc. Da bi odgovorili na zgoraj zastavljeni vprašanji, smo med slovenskimi 1 UVOD študenti v zadnji četrtini leta 2021 izvedli raziskavo. Izsledki raziskav zadnjih let poudarjajo pomembnost razvoja digitalnih kompetenc [1]. Pandemija COVID-19 je tako 2 METODOLOŠKI PRISTOP Permission to make digital or hard copies of part or all of this work for personal or Ker smo želeli raziskati digitalne kompetence študentov 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 njihovo mnenje o vplivu pandemije COVID-19 na razvoj citation on the first page. Copyrights for third-party components of this work must digitalnih kompetenc, smo se odločili, da izvedemo kvantitativno be honored. For all other uses, contact the owner/author(s). raziskavo. Pri pripravi vprašalnika smo izhajali iz DigComp 2.1 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). okvira. Za vsak sklop kompetenc smo pripravili pet trditev, ki 482 smo jih nekoliko prilagodili in dopolnili skladno z razvojem Kljub dokaj dobremu nivoju opremljenosti z IKT, pa 21 % informacijske in komunikacijske tehnologije. Uporabili smo 5- študentov ni imelo na voljo ustrezne strojne in programske stopenjsko lestvico Likertovega tipa. Dodali smo vprašanja s opreme za potrebe študija na daljavo. Kar se tiče orodja preko katerimi smo želeli pridobiti mnenja o vplivu pandemije katerih so spremljali predavanja in vaje, so največ uporabljali COVID-19 na študij ter nekaj demografskih vprašanj. Za lažje Zoom (52 %), sledil je MS Teams (42 %), 1 % jih je uporabljajo zbiranje podatkov smo vprašalnik pripravili s pomočjo orodja za Skype, med drugimi orodji (5 %) po omenjajo BigBlueButton in spletno anketiranje 1KA-i [10]. Google Meet. Da bi dosegli čim več slovenskih študentov, ki dobro predstavljajo populacijo, smo anketo delili s pomočjo spletnih 3.2 Digitalne kompetence omrežjih (Facebook in Instagram), s pomočjo elektronske pošte Rezultati bodo predstavljeni ločeno, po posameznih sklopih in z objavo ankete na forumu. Uporabili smo tudi metodo snežne digitalnih kompetenc: informacijska pismenost, komuniciranje kepe [11], kar pomeni, da smo naslovnike prosili, da anketo in sodelovanje, izdelovanje digitalnih vsebin, varnost in delijo naprej med svoje prijatelje in znance. reševanje tehničnih težav. Mnenja smo zbirali dober mesec in prejeli skupaj 81 v celoti Informacijska pismenost razumemo kot zmožnost, da izpolnjenih anket. Slabši odzivnosti anketirancev pripisujem posameznik zna brskati, iskati in filtrirati informacije, ocenjevati kompleksnosti vprašalnika. Za namen tega prispevka smo informacije ter shranjevati in obdelati informacije [4]. Rezultati podatke izvozili in jih analizirali s pomočjo programa Microsoft (Slika ) kažejo, da se anketirani slovenski študenti najbolj Excel. strinjajo s trditvama, da znajo poiskati informacije za študij in jih ustrezno organizirati z namenom kasnejšega lažjega iskanja, medtem ko se najmanj strinjajo s trditvijo, da znajo narediti 3 REZULTATI varnostno kopijo informacij ali datotek, ki jih imajo shranjene na V raziskavi je sodelovalo 63 % žensk in 37 % moških. 19 % je svojih napravah. Manj se strinjajo tudi s trditvama, ki sta vezani mlajših od 20 let, največ (47 %) je starih med 21 in 23 let, 11 % na oceno zanesljivosti informacij na internetu. med 24 in 26 let, le 5 % je starih več kot 26 let. Več kot polovico (51 %) obiskuje Univerzo v Ljubljani, 31 % obiskuje Univerzo v Mariboru, 7 % obiskuje Univerzo na Primorske, sledita Nova Na spletu znam poiskati vire potrebne za univerza in Univerza v Novi Gorici. Med njimi je 67 % 1% 35% 54% moj študij. dodiplomskih in 33 % podiplomskih študentov. Večin jih je vpisana na redni študij (86 %), manjši delež (14 %) na izredni Znam razvrstiti podatke na organiziran način, s pomočjo datoteke in mape, z 4%16% 22% 57% študij. namenom kasnejšega lažjega iskanja. 3.1 Uporaba informacijske in komunikacijske Znam ločiti zanesljive in nezanesljive vire 4% 27% 37% 31% informacij na internetu. tehnologije Študenti dnevno uporabljajo informacijsko in komunikacijsko Znam oceniti zanesljivost/verodostojnost 7% 33% 35% 25% informacij z različnimi merili/kriteriji. tehnologijo (IKT). 94 % uporablja pametni telefon, 91 % namizni oz. prenosni računalnik in 18 % tablični računalnik. Če bolj Znam narediti varnostno kopijo informacij ali datotek, ki jih imam shranjene na svojih 12% 20% 26% 36% natančno pogledamo uporabo pametnega telefona in namiznega napravah. oz. prenosnega računalnika (Slika ), lahko vidimo, da kar 68 % 0% 50% 100% študentov uporablja mobilni telefon več kot tri ure, medtem ko 1-sploh ne drži zame 2 3 4 5-povsem drži zame namizni oz. prenosni računalnik več kot tri ure uporablja le 48 % študentov. 92 % jih ima širokopasovno internetno povezavo. Slika 2: Samoocena kompetenc na področju informacijske pismenosti 40% 31% Komuniciranje in sodelovanje razumemo kot zmožnost, da 30% 24% 23% se posameznik zna sporazumevati in sodelovati z uporabo digitalne tehnologije, pozna spletni bonton in zna upravljati z 20% 17% 17% 14% 14% 13% 13% digitalno identiteto [4]. Rezultati (Slika ) kažejo, da se anketirani 11% 9% slovenski študenti najbolj strinjajo, da znajo uporabljati e-pošto 10% 7%5% in druga orodja za kvalitetno komunikacijo, medem ko so manj 2% vešči pri uporabi spletnih orodij za vodenje projektov in deljenje 0% Manj 1-2 uri 2-3 ure 3-4 ure 4-6 ur 6-8 ur Več kot vsebin, znanja in/ali virov z drugimi ljudmi. kot 1 8 ur ura Namizni/prenosni računalnik Pametni telefon Slika 1: Uporaba računalnika in pametnega telefona po urah 483 uporabljajo funkcijo zasebnosti, ki je na voljo na družbenih medijih, medtem ko v manjši meri uporabljajo dolga in zapletena Uporabljam e-pošto za komunikacijo preko 0% 16% 77% spleta (Gmail, Outlook, …). gesla za dostop do različnih spletnih strani. Imam dovolj digitalnih kompetenc za kvalitetno komunikacijo med študijem na 12% 27% 60% daljavo. Zavedam se tveganja za zdravje, ki lahko Uporabljam spletne aplikacije, ki izhajajo iz neustrezne uporabe tehnologij 5% 20% 31% 44% omogočajo medsebojno komuniciranje 3% 14% 17% 59% (ergonomski vidiki, zasvojenost, ...). uporabnikov (Skype, WhatsApp, Viber, … Moj računalnik je zaščiten z varnostnim Znam uporabljati spletna orodja za vodenje 4% 4% 22% 26% 45% programom. projektov, sodelujem v njih in jih 2% 13% 34% 41% uporabljam za izvedbo, načrtovanje in … Zavedam se vpliva, ki ga imajo IKT in Uporabljam posebna orodja v oblaku za internet v našem vsakdanjem življenju na 2% 5% 21% 33% 40% deljenje vsebin, znanja in/ali virov z drugimi 11% 22% 18% 36% spletni nakup in okolje. ljudmi (predstavitve, fotografije, … Uporabljam funkcijo zasebnosti, ki je na voljo na družbenih medijih, za odobritev in 5%7% 16% 28% 44% 0% 50% 100% zavrnitev vsakega, ki bi želel dostopati do… 1-sploh ne drži zame 2 3 4 5-povsem drži zame Moja gesla so dolga in zapletena in različna 8% 16% 35% 24% 16% za različne spletne strani. 0% 50% 100% Slika 3: Samoocena kompetenc na področju komunikacije in sodelovanja 1-sploh ne drži zame 2 3 4 5-povsem drži zame Izdelovanje digitalnih vsebin razumemo kot zmožnost, da posameznik zna razviti, umeščati in poustvariti digitalne vsebine, Slika 5: Samoocena kompetenc na področju varnosti spoštuje avtorske pravice in licence ter zna programirati [4]. Rezultati (Slika ) kažejo, da se anketirani slovenski študenti Reševanje problemov razumemo kot zmožnost, da najbolj strinjajo s trditvami, da znajo uporabljati Office programa, posameznik zna rešiti tehnične probleme, poiskati najustreznejše se zavedajo posledic nezakonitega nalaganja digitalnih vsebin in rešitve glede na potrebe, uporabiti tehnologijo na inovativen in znajo obdelati slike in video posnetke, medem ko imajo več kreativen način ter identificirati manjkajoča digitalna znanja [4]. težave pri ločevanju konceptov vezanih na avtorske pravice in Rezultati (Slika ) kažejo, da se anketirani slovenski študenti licence. Najmanj pa se strinjajo s trditvijo, za jih zanima in so najbolj strinjajo s trditvama, da so sposobni najti ustrezne seznanjeni z novostmi v zvezi z IKT rešitvami za načrtovanje in alternativne digitalne rešitve, ko je potrebno rešiti težave drugače ustvarjanje izdelkov. in se zavedajo svojih kompetenc in morebitnih pomanjkljivosti na digitalnem področju. Manj pa se strinjajo s trditvama, da znajo delati z bazami podatkov in da v vsakdanje življenje vključujejo vse več digitalnih tehnologij. Znam uporabljati Office programe (Word, 11% 35% 53% Excel, Power Point,...). Zavedam se posledic nezakonitega nalaganja digitalnih vsebin (glasbe, 6%11% 20% 26% 36% Sposoben sem najti ustrezne alternativno programske opreme, filmi...). digitalno rešitve, ko ne morem rešiti težav 0% 2 27% 46% 25% in je potrebno stvari narediti drugače. Znam uporabljati programsko opremo za 10%9% 36% 17% 27% obdelavo slik in video posnetkov. V zvezi z nalogami, ki jih moram opraviti v svojem delovnem, študijskem ali zasebnem 1% 2% 28% 40% 28% življenju, se zavedam svojih kompetenc in… Znam ločiti med koncepti, kot so avtorske pravice, prosta uporaba avtorskega dela in 13% 20% 25% 18% 24% Sposoben/na sem rešiti kakršno koli težavo ustvarjalna skupnost. povezano z nepravilnim delovanjem 1% 11% 36% 29% 22% Zanimam se in seznanjam se z novostmi v digitalne tehnologije. zvezi z IKT rešitvami za načrtovanje in 16% 19% 25% 20% 19% V vsakdanjem življenju vključujem vse več ustvarjanje izdelkov. digitalni tehnologij, za katere ocenjujem, da 5% 18% 26% 33% 19% lahko izboljšajo kakovost mojega življenja. 0% 50% 100% Znam oblikovati in spreminjati baze podatkov z ustreznim računalniškim 30% 24% 24% 14% 8% 1-sploh ne drži zame 2 3 4 5-povsem drži zame orodjem (Access, MySQL, ORACLE, ...) za… 0% 50% 100% Slika 4: Samoocena kompetenc na področju izdelovanja digitalnih vsebin 1-sploh ne drži zame 2 3 4 5-povsem drži zame Varnost razumemo kot zmožnost, da posameznik zna zaščititi svoje naprave in osebne podatke ter se zaveda vpliva Slika 6: Samoocena kompetenc na področju reševanja digitalne tehnologije na zdravje in dobro počutje ter okolje [4]. problemov Rezultati (Slika ) kažejo, da se anketirani slovenski študenti najbolj strinjajo s trditvami, da se zavedajo vpliva digitalne tehnologije na zdravjem vsakdanje življenje in okolje ter imajo računalnik zaščiten z varnostnim programom. Mnogi tudi 484 4 Vpliv pandemije COVID-19 na razvoj reševanja problemov ni bistveno izboljšalo. Vsekakor bi bilo digitalnih kompetenc potrebno nadalje raziskati razloge za take rezultate. Kljub številnim prednostim pa ima študij na daljavo tudi Anketirani študenti so ocenjevali trditve, ki se navezujejo na pet slabosti. Študenti, ki so sodelovali v raziskavi, se strinjajo, da je glavnih sklopov kompetenc. Rezultati (Slika ) kažejo, da se veliko lažje slediti predavanjem v živo, kot pa na daljavo (x̄=3,8) anketirani slovenski študenti najbolj strinjajo s trditvami, da so in da se kvaliteta študija na daljavo ne more primerjati s študijem se jim izboljšale kompetence povezane s komunikacijo in na fakulteti (x̄=3,9). Iz tega lahko zaključimo, da kljub razvoju sodelovanjem, informacijsko pismenostjo in varnostjo. Nekoliko IKT in novim pristopom izobraževanja, študij na daljavo še ne manj se strinjajo s trditvami, da so se jim izboljšale kompetence bo zamenjal študija na fakulteti. Le-ta naj bo zaenkrat le del na področjih izdelovanja digitalnih vsebin in reševanja celotnega proces izobraževanja na fakulteti. Vsekakor pa velja problemov s pomočjo digitalne tehnologije. razmisliti o primernosti takega pristopa za izredne študente, ki jim velikokrat, zaradi službenih obveznosti, primanjkuje časa in bi se lahko v primeru študija na daljavo lažje udeleževali Komunikacija preko interneta mi ne 1%6%11% 21% 61% predavanj in vaj ter posledično sproti opravljali študijske predstavlja težav. obveznosti. Hitreje poiščem in dostopam do želenih Za namen raziskave o digitalnih kompetencah slovenskih 1%8% 28% 32% 31% informacij na spletu. študentov smo razvili dokaj kompleksne vprašalnik, ki nudi priložnosti za nadaljnje analize podatkov, ki pa so izven okvira Znam poskrbeti za svojo varnost in 2%8% 23% 40% 26% zasebnost na internetu. tega prispevka. Nadaljnje analize bodo usmerjene v primerjavo med načini, vrstami, letniki študija, spolom, itd. Zavedamo se Gradivo, ki ga najdem na spletu, znam 2%12% 18% 41% 27% bolje urediti za kasnejšo uporabo. tudi omejitev. Ena je majhen vzorec. Druga, ki jo želimo izpostaviti, je sam vprašalnik. Le-ta temelji na predhodnih Bolje znam ovrednotiti informacije, ki jih 2%9% 32% 33% 24% raziskavah, kar ponuja primerljivost, vendar ugotavljamo, da bi najdem na spletu. morale biti vključene dodatne/novejše digitalne kompetence, kot Pri pripravi digitalnih vsebin znam uporabiti različna digitalna sredstva 4%11% 26% 38% 22% so veliki podatki, robotika in umetna inteligenca [13]. (grafika, diagrami itd.). Bolj sem spreten pri nameščanju in LITERATURA IN VIRI 4% 15% 29% 25% 27% spremembi nastavitev aplikacij. [1] C. Fulton and C. McGuinness, Digital Detectives: Solving Information Dilemmas in an Online World. Elsevier Inc., 2016. Sledim najnovejšim trendom razvoja digitalnih tehnologij in jih vključujem v [2] J. Lai and N. O. Widmar, “Revisiting the Digital Divide in the COVID‐19 6% 14% 31% 29% 20% vsakdanje življenje. Era,” Appl. Econ. Perspect. Policy, vol. 43, no. 1, p. 458, Mar. 2021. [3] J. Crawford et al., “COVID-19: 20 countries’ higher education intra-period Vse težave z informacijsko in digital pedagogy responses,” J. Appl. Learn. Teach., vol. 3, no. 1, pp. 09– komunikacijsko tehnologijo sedaj 6% 16% 32% 28% 18% rešujem sam. 28, Apr. 2020. [4] S. Carretero, R. Vuorikari, and Y. Punie, “The Digital Competence Bolje se zavedam avtorskih pravic in Framework for Citizens With Eight,” Publ. Off. Eur. Union, no. May, p. 9% 19% 34% 24% 14% upoštevam licence. 48, 2017. [5] N. Law, N. Law, D. Woo, and G. Wong, “A Global Framework of 0% 20% 40% 60% 80% 100% Reference on Digital Literacy Skills for Indicator 4.4.2,” 2018. [6] Australian Government, “Digital Literacy Skills Framework - Department 1-sploh ne drži zame 2 3 4 5-povsem drži zame of Education, Skills and Employment, Australian Government,” 2020. [7] C. M. Toquero, “Challenges and Opportunities for Higher Education amid the COVID-19 Pandemic: The Philippine Context,” Pedagog. Res., vol. 2020, no. 4, pp. 2468–4929, 2020. Slika 7: Samoocena študentov glede vpliva pandemije [8] W. Cao et al., “The psychological impact of the COVID-19 epidemic on COVID-19 na dvig njihovih digitalnih kompetenc college students in China,” Psychiatry Res., vol. 287, p. 112934, May 2020. [9] S. Saniuk et al., “Higher Education in and after COVID-19: The Impact of Using Social Network Applications for E-Learning on Student’ Academic Performance,” Sustain. 2022, Vol. 14, Page 5195, vol. 14, no. 9, p. 5195, 5 SKLEP Apr. 2022. [10] “1KA | Spletne ankete.” [Online]. Available: https://www.1ka.si/. Anketirani slovenski študenti svoje digitalne kompetence [Accessed: 06-Jul-2022]. ocenjujejo dokaj visoko, saj je bila povprečna ocena nižja od 3 le [11] L. A. Goodman, “Snowball Sampling,” https://doi.org/10.1214/aoms/1177705148, vol. 32, no. 1, pp. 148–170, pri eni izmed 25 trditev. To je generacija Z oz. net generacija, ki Mar. 1961. naj bi bili iznajdljivi v svetu komunikacije, vešči klikanja, [12] S. Tejedor, L. Cervi, A. Pérez-Escoda, and F. T. Jumbo, “Digital Literacy všečkanja in brskanja po internetu, itd. [12], zato rezultati niso and Higher Education during COVID-19 Lockdown: Spain, Italy, and Ecuador,” Publ. 2020, Vol. 8, Page 48, vol. 8, no. 4, p. 48, Nov. 2020. presenetljivi. Predpostavljamo, da so se njihove digitalne [13] EU Science Hub, “Upskilling for life after the pandemic: Commission kompetence, zaradi dosežene že dokaj visoke stopnje digitalnih launches new digital competence guidelines,” 2020. [Online]. Available: https://joint-research-centre.ec.europa.eu/jrc-news/upskilling-life-after- kompetenc, med pandemijo COVID-19 le nekoliko izboljšale pandemic-commission-launches-new-digital-competence-guidelines- (npr. povprečna ocena trditve »Menim, da sem bolj spreten pri 2020-07-13_en. [Accessed: 08-Jul-2022]. uporabi IKT kot pred pandemijo COVID-19.« je 3,5 na 5- stopenjski lestvici). Ugotavljamo, da so anketirani študenti pridobili predvsem kompetence na področjih komunikacije in sodelovanja ter informacijske pismenosti. Morda je to rezultat študija na daljavo, ki je zahteval visok nivo teh kompetenc. Zanimivo je, da se stanje na področjih ustvarjanja vsebin in 485 Sodobni pristopi poučevanja na daljavo pri poučevanju kardiovaskularnega sistema v srednji šoli Modern Approaches in Distance Learning the Cardiovascular System in High School Miha Povšič Lea Janežič Šolski center Kranj Strokovni izobraževalni center Ljubljana Kranj, Slovenija Ljubljana, Slovenija miha.povsic@sckr.si lea.janezic@siclj.si POVZETEK a way that is modern and interesting to the students. With the use of these two tools, the goal was pursued without major obstacles Poučevanje je dandanes postavljeno pred številne izzive. Na eni despite the implementation of distance learning and did not result strani so dijaki, ki jih je vedno težje motivirati za učenje, na drugi in statistically significant differences in students' knowledge in strani pa nas je zdravstvena situacija prisilila v izvajanje pouka distance learning or in-school classes. With the help of the na daljavo, kar je v nasprotju s tem, kar smo bili vajeni od nekdaj. IPEVO VZ-R camera, distance learning took place smoothly and Pri izvajanju pouka na daljavo se je izkazalo, da je strukturirano with much fewer obstacles than is possible with graphics tablets, načrtovanje učnega procesa ključnega pomena. S pomočjo which have many limitations. Formative monitoring of students uporaba formativnega spremljanja z aplikacijo GoFormative in is one of the keyways in which we can accurately monitor the kamere IPEVO VZ-R je bila učna snov kardiovaskularnega progress of individual students in the learning process, and the sistema predstavljena na način, ki je sodoben in dijakom zanimiv. GoFormative application digitizes the otherwise analog Z uporabo teh dveh orodij je bil cilj kljub izvajanju pouka na monitoring of students and makes the work of both students and daljavo zasledovan brez večjih ovir in ni prinesel statistično teachers easier. The use of these two devices has proven to be pomembnih razlik v znanju dijakov pri pouku na daljavo ali very welcome during distance learning, and their use also makes pouku v šoli. S pomočjo kamere IPEVO VZ-R je pouk na daljavo sense during lessons at school. potekal nemoteno in z veliko manj ovirami, kot to omogočajo grafične tablice, ki imajo številne omejitve. Formativno KEYWORDS spremljanje dijakov je eden izmed ključnih načinov, kako lahko natančno spremljamo napredek posameznih dijakov v učnem Distance learning, digital literacy, biology, cardiovascular procesu, aplikacija GoFormative, pa nam sicer analogno system spremljavo dijakov digitalizira in olajša delo tako dijakov kot tudi učiteljev. Uporaba teh dveh pripomočkov se je v času pouka na daljavo izkazala za zelo dobrodošlo, njuna uporaba pa je tudi 1 UVOD med poukom v šoli smiselna. Poučevanje na daljavo je oblika poučevanja z dvema temeljnima značilnostma: učitelj in učenec sta med poučevanjem prostorsko KLJUČNE BESEDE ločena, komunikacijo med njima in komunikacijo med učenci Pouk na daljavo, digitalna pismenost, biologija, kardiovaskularni samimi pa omogočajo različne vrste tehnologij 3. Unesco sistem opredeljuje izobraževanje na daljavo kot »vzgojno-izobraževalni proces in sistem, v katerem pomemben delež pouka izvaja nekdo ABSTRACT ali nekaj, ki je časovno in prostorsko odmaknjeno od učenca« 2. Teaching today is faced with many challenges. On the one hand, Pri poučevanju na daljavo je tehnološka podpora v celoti in there are students who are increasingly difficult to motivate to načrtno integrirana v celoten vzgojno-izobraževalni proces, tako learn, and on the other hand, the health situation has forced us to v pedagoško kot administrativno podporo ter učno gradivo, kar conduct distance learning, which is contrary to what we have omogoča izvajanje učnega procesa ob fizični ločenosti učitelja in always been used to. When conducting distance learning, it has učenca 1. been proven that structured planning of the learning process is Učinkovito poučevanje na daljavo zahteva strukturirano crucial. With the help of formative monitoring with the načrtovanje, dobro strukturirane učne enote, specialne didaktične GoFormative application and the IPEVO VZ-R camera, the strategije in komunikacijo prek elektronskih ali drugih tehnologij learning material of the cardiovascular system was presented in (prav tam). Unesco poudarja, da poučevanje na daljavo zahteva »visok nivo samouravnavanja in veščin učenja, kar naj bi učitelji Permission to make digital or hard copies of part or all of this work for personal or podprli z novimi poučevalnimi, učnimi in usmerjevalnimi classroom use is granted without fee provided that copies are not made or distributed strategijami«. 10 for profit or commercial advantage and that copies bear this notice and the full Dva načina predstavitve učne teme kardiovaskularnega 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). sistema bosta predstavljena tudi v članku. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 486 2 PREGLED LITERATURE Stanojev in Florjančič 9 ugotavljata, da pri gimnazijcih Pouk je namerno, načrtovano in organizirano izobraževanje, kar med intenzivnostjo uporabe IKT pri pouku in digitalno velja tudi za poučevanje na daljavo. Pri načrtovanju, izvajanju pismenostjo dijakov ni statistično značilne povezanosti, prav in evalvaciji poučevanja na daljavo je potrebno upoštevati t. i. tako tudi višja intenzivnost uporabe IKT pri pouku ni statistično didaktični model, ki ga sestavljajo snovna, pedagoško- značilno povezana z rezultatom digitalne pismenosti dijakov. psihološka, metodična / specialnodidaktična ter tehnična in Z opisi definicij digitalne pismenosti se pojavlja smiselnost uporabe IKT pri poučevanju. Kot nujna za preživetje v sodobnem organizacijska izhodišča 5. času jo spodbujamo tudi v šolskem prostoru s prenovami Snovna izhodišča didaktičnega modela temeljijo na pripravi izobraževalnih programov, žal pa se je v času COVID-19 učnih gradiv in usmerjajo učitelja v širino in globino potrebnih izkazalo, da se dijaki ne dosegajo zadovoljivo te kompetence znanj. Njihov namen je podati bistveno vsebino ter analizirati znanstvenost in sodobnost učne snovi, ki bo posredovana znanja. 8 Eden od načinov spremljanja napredka in obvladovanja učne učencem 5. snovi posameznega dijaka je v aplikaciji “Go Formative”, druga Pedagoško-psihološka izhodišča povezujejo učitelja z učenci, pa za lažje posredovanje zapiskov kot tabelna slika z uporabo saj se nanašajo na predznanje učencev. Pomembno je, da učitelj kamere za posredovanje dokumentov v realnem času (IPEVO – razmisli o obstoječem predznanju učencev, njihovih izkušnjah s VZ-R). samostojnim delom, uporabo informacijske tehnologije idr. Poleg tega pa ima učitelj ves čas v mislih tudi vzgojno vrednost, ki jo bo prek učnih gradiv posredoval učencem 5. 3 REZULTATI Metodična izhodišča izobraževanja na daljavo so temelj za pripravo učnih/študijskih gradiv. Znotraj teh izhodišč imajo 3.1 Go Formative pomembno vlogo operativni vzgojno-izobraževalni cilji, ki jih Ob poplavi spletnih orodij, ki se jih učitelji poslužujemo za želi doseči učitelj. Pomembno je, da tako učenci kot učitelj izboljšanje zanimanja dijakov do pouka in s tem tudi kvalitete natančno poznajo svojo vlogo in zadolžitve pri doseganju pouka, je težko ločiti zrno od plevela. Na spletu je moč najti večje zastavljenih vzgojnoizobraževalnih ciljev. Pri poučevanju na število tako brezplačnih kot tudi plačljivih orodij, ki nam lahko dalajvo mora učno gradivo vključevati vse faze vzgojno pomagajo pri izvedbi določene aktivnosti pri pouku. Številna izobraževalnega sistema: ponovitev stare snovi, osmišljanje spletna orodja so teoretično zelo dobra, vendar zaradi posredovanega znanja, spodbujanje in motiviranje udeležencev; suhoparnosti in manj primernega vmesnika, pri učencih niso podajanje, razlago in pojasnjevanje nove učne snovi, ponavljanje dobro sprejeta in posledično med poukom ne dosežejo željenih in utrjevanje, spodbujanje učencev, da usvojeno znanje prenesejo učinkov. Številni programi in aplikacije pa so za dijake izredno v prakso, preverjanje in ocenjevanje znanja. 5 atraktivne in imajo boljše vmesnike, ki jim omogočajo enostavno Ob vseh načelih poučevanja na daljavo, upoštevanju uporabo, vendar so didaktično veliko slabše. didaktičnih modelov, pa ne smemmo pozabiti na digitalno Uporaba spletnih orodij je v času izobraževanja na daljavo pismenost učencev. »Digitalna pismenost je temeljna zmožnost doživela razcvet, kjer je bila motivacija dijakov in čim bolj posameznika, da se znajde v digitalnem svetu. Digitalno pismen nemoten proces poučevanja glaven namen učiteljev. Tudi tisti posameznik pozna in uporablja digitalne aparature in učitelji, ki so bili navajeni frontalnega poučevanja, so bili pripomočke, razume zakonitosti digitalnega socialnega okolja in prisiljeni poseči po drugih prijemih. se znajde v njem.« 8. Eno izmed orodij, ki se je v času pouka na daljavo izkazalo Pri tem je temeljno računalniško znanje, kot je uporaba kot zelo dobrodošlo je aplikacija GoFormative. S pomočjo računalnika za iskanje, ocenjevanje, shranjevanje, proizvodnjo, aplikacije lahko učitelj preverja in ocenjuje naloge in vprašanja predstavitev in izmenjavo informacij ter za sporazumevanje in različnih kognitivnih ravni. Tiste naloge, kjer z vprašanji sodelovanje v skupnih omrežjih na internetu, zgolj podlaga, ki preverjamo znanje na nižji kognitivni ravni, se pravilnost le teh omogoča spoznavanje drugih, hitro razvijajočih se digitalnih samodejno preverja, naloge višjih kognitivnih ravni, kot so orodij. 6 vprašanja odprtega tipa, pa mora učitelj preverjati in ovrednotiti Mednarodno združenje za tehnologijo v izobraževanju naknadno. Aplikacija nam omogoča, da glede na smernice (ISTE) je merila za določanje veščin digitalne pismenosti formativnega spremljanja, lahko dodelimo določene naloge le razvrstilo v naslednje sklope veščin: eni skupini dijakov, za katere menimo, da jih v določenem - ustvarjalnost in inovativnost, koraku učnega procesa potrebujejo – le to storimo z različnimi - komunikacija in sodelovanje, kodami, ki jih ustvarimo v aplikaciji. V aplikaciji imamo - raziskovanje in informacijska pretočnost, možnost ustvariti nalogo, kjer dijaki na skico vnašajo svoje - kritično mišljenje, rešitve. Prav tako nam aplikacija omogoča dodeljevanje - reševanje problemov in odločanje, različnega števila točk nalogam, kar v praksi pomeni, da naloge, - tehnološke operacije in koncepti. 7, ki so kompleksnejše, prinašajo večje število točk, kot naloge, ki Ferrari 4, digitalno pismenost definira kot nabor znanj, so po Bloom-u na nižji taksonomski stopnji. V aplikaciji ima veščin in navad (zmožnosti, strategije, vrednote in zavedanja), ki učitelj nad rešenimi nalgami neposreden vpogled, tako v času jih ob uporabi IKT potrebujemo za izvajanje nalog, reševanje reševanja, da spremlja napredek dijaka, kot tudi kasnjeje. problemov, komuniciranje, upravljanje informacij, sodelovanje, Aplikacija GoFormative je bila uporabljena pri učnem ustvarjanje in izmenjavo vsebin ter uspešno, učinkovito in procesu obravnave človeškega kardiovaskularnega sistema, pri kritično izgradnjo lastnega znanja. pouku biologije v 1. letniku. Učna ura je bila načrtovana tako, da so dijaki s pomočjo aplikacije GoFormative preverili svoje 487 dosedanje znanje o človeškem kardiovaskularnem sistemu. Kasnejša analiza znanja dijakov pri tej temi ni pokazala Dijaki so s pomočjo mobilnih telefonov obiskali spletno mesto statistično pomembnih razlik med znanjem dijakov, ki so bili GoFormative, kjer so vpisali v naprej posredovano kodo, s katero vključeni v izboraževanje na daljavo in med dijakom, ki so so lahko dostopali do nalog. Nato so imeli 15 minut časa, da so znanje pridobili v šoli. samostojno rešili zahtevane naloge. Med reševanjem nalog so se rezultati oz. pravilnost nalog neposredno prikazovali le učitelju, 3.2 Učenje kardiovaskularnega sistema s kar omogoča takojšno povratno informacijo o znanju dijakov. pomočjo kamere IPEVO VZ-R Dijaki o pravilnosti njihovega reševanja niso bili seznanjeni. Z dijaki smo v času pouka na daljavo poleg uporabe Hitra analiza rezultatov s tem omogoča učitelju prilagoditi GoFormative za lažje posredovanje učne snovi in bolj izvedbo učnega procesa za določeno učno snov. Po uvodnem sistematično razlago uporabljali spletno kamero znamke IPEVO, preverjanju znanja so bili dijaki razporejeni v skupine po štiri. model VZ-R (v nadaljevanju kamera). Skupine so bile formirane tako, da so bili dijaki z najslabšim Z dijaki srednjega strokovnega izobraževanja je bila znanjem dodeljeni k dijakom, ki so na uvodnem preverjanju izvedena učna ura na temo kardivoaskularnega sistema z uporabo dosegali boljše rezultate. S tem je bila omogočena medvrstniška kamere za natančnejšo in bolj sistematizirano razlago, za pomoč. Nato so bili dijaki pozvani k zastavljanju ciljev učnega spremljanje napredka dijakov pa aplikacija GoFormative, s sklopa – kaj želijo izvedeti in kaj je za njih pomembno. Pri pomočjo katere smo preverjali predznanje in usvojeno znanje zastavljanju ciljev so bili upoštevani tudi minimalni standardni glede na strukturirane naloge po Bloom-ovi taksonomiji. znanja in nameni učenja. Vse skupine so nato prejele učno gradivo z vprašanji, ki se nanašajo na minimalne standarde znanja. Vsaka skupina pa je nato prejela individualizirana vprašanja po temah, ki so jih izbrali pri zastavljanju ciljev učnega sklopa in temah, ki so bili na začetnem preverjanju dosegala najnižje število točk. Slika 2: Uporaba kamere VZ-R Sama uporaba kamere je zelo preprosta, odtehta pa nam marsikatero napačno razumevanje ali dilemo. Priklopimo jo preko USB-A vhoda na prenosni ali stacionarni računalnik. Na Sliki 3 vidimo, da lahko dijakom sliko učbenika, shemo, ki smo jo narisali, pokažemo neposredno na njihovem zaslonu. Kamera prepozna branje dokumentov, slik, posnetkov ... skratka vseh analognih in digitalnih vsebin. Slika 1: Primer naloge uporabljen v aplikaciji GoFormative. Po 30 minutah dela v skupinah so dijaki predstavili svoje delo ostalim dijakom, ki so si med predstavitami izvedlovali samostojne zapiske. Po vsaki predstavitvi je sledila še razprava o ugotovitvah, ki so jih skupine predstavile in uporabni vrednosti znanja v vsakdanjem življenju. Nato so bili dijaki znova pozvani, da s pomočjo aplikacije GoFormative ponovno rešijo vse naloge. Z analizo rezultatov so bili dijaki tokrat seznanjeni, kar jim je omogočilo ugotoviti, kaj Slika 3: Prenos slike s tablice na računalnik. so se novega naučili in kakšno znanje o določeni temi zdaj premorejo. Pri pouku smo uporabili kombinacijo kamere, tablice in računalnika, kot kaže slika 3. 488 Na Sliki 4 je predstavljen še en način uporabe in sicer kamero 4 ZAKLJUČEK lahko neposredno povežemo z mikroskopom, tega pa z Primer učne praske z uporabe digitalnih orodij GoFormative in računalnikom. Ta način uporabe nadomesti nameščanje dragih kamere ni samo primer dobre prakse, ki smo jo izvajali v času kamer in lup za posredovanje mikroskopskega preparata na tablo poučevanja na daljavo, temveč se kaže kot dober način ali pametno tablo, kjer enostavneje prikažemo preparat, hkrati pa poučevanja na daljavo v primeru izobraževanja odraslih, v vsi dijaki naenkrat vidijo sliko pod mikroskopom. primeru, ko je dijak bolnišnično odsoten dalj časa, lahko spremlja nekatere vsebine in razlago, na roditeljskih sestankih, pa tudi v času priprav na različna tekmovanja, saj dijaki različnih razredov zaključujejo pouk ob različnih urah, preko poučevanja na daljavo pa vsem omogočimo prisostvovanje na pripravah ali pa kasnejši ogled predavanja na spletni učilnici. LITERATURA IN VIRI [1] Bregar, L., Zagmajster, M. in Radovan, M. (2020). Eizobraževanje za digitalno družbo. Ljubljana: Andragoški center Slovenije. https://www.acs.si/digitalna-bralnica/eizobrazevanje-za-digitalno-druzbo/ (10. 8. 2022) [2] Burns, M. (2011). Distance Education for Teacher Training: Modes, Models, and Methods. Washington, DC: Education Development Center, Inc. [3] Encyclopedia Britannica. @2020 Encyclopedia Britannica, Inc. https://www.britannica.com/topic/Britannica-Online (11. 8. 2022) Slika 4: Posredovanje mikroskopske slike. [4] Ferrari, Anusca. 2012.Digital Competence in Practice: An Analysis of Frameworks. jrc Technical Reports. Luxembourg: Publications Office of the European Union. Dijakom smo z uporabo kamere olajšali delo, zapiske so [5] Gerlič, I. (2002). Didaktična izhodišča izobraževanja na daljavo. V Gerlič, I., delali sproti, hkrati pa smo posnetek učne ure in razlago lahko Debevc, M., Dobnik, N., Šmitek, B. in Korže, D. (ur.),. Načrtovanje in priprava študijskih gradiv za izobraževanje na daljavo (str. 83–92). Maribor: tudi snemali in kasneje naložili na spletno učilnico v Moodle ali Fakulteta za elekrotehniko, računalništvo in informatiko. na MS Teams. [6] Gilster, Paul. 1997. Digital Literacy. New York: Wiley. [7] ISTE. Areas of focus. https://www.iste.org/ (12. 8. 2022) [8] Javrh, P., Možina, E., Bider, K., Kragelj K., Volčjak, D., Sepaher, G., Gjerek, L., Matavž, H., Rejec, P., Babič Ivaniš, N., Brecelj, V. (2018). Digitalna pismenost. Ljubljana: Andragoški center Slovenije. https://pismenost.acs.si/wp-content/uploads/2018/09/Digitalna-pismenost-e- verzija.pdf (12. 8. 2022) [9] Stanojev, S, Florjančič, V. (2018). Digitalna pismenost srednješolcev. Koper: Založba Univerze na Primorskem. [10] UNESCO COVID-19 Education Response. (2020). [11] https://en.unesco.org/covid19/educationresponse/ (12. 8. 2022) 489 Fizikalni poskusi z in brez informacijsko-komunikacijske tehnologije Physics Experiments With or Without ICT Katja Presetnik Osnovna šola Vide Pregarc Ljubljana Slovenija katja.presetnik@osvp.si POVZETEK smiselna uporaba ene in druge metode, ter s pomočjo evalvacije, ki sem jo naredila z učenci presodila še njihovo izkustvo. V zadnjih dveh desetletjih številni predavatelji in pedagoški delavci iščemo nove metode podajanja učne snovi s pomočjo KLJUČNE BESEDE informacijsko-komunikacijske tehnologije (v nadaljevanju IKT). V času epidemije pa je delo na daljavo postalo edini način, ki je Izkustveno učenje, fizikalni poskusi, e-gradiva, spletne sploh omogočil izobraževalni proces. Po vrnitvi v šolske klopi aplikacije, simulacija fizikalnih eksperimentov smo učitelji lahko izbirali med klasičnim poučevanjem ter ABSTRACT uporabo digitalnih oblik poučevanja. Čeprav smo v času dela na daljavo vsi pogrešali klasičen pouk, je jasno, da si pouka brez Teachers have been looking for new ways to incorporate ICT into IKT ne predstavljamo več. Učitelj mora tako smiselno presoditi, their teaching methods in the last two decades. It became clear katere metode dela izbrati za določene vsebine, da bo učencem during distance learning that ICT is crucial to achieve snov čimbolj nazorno predstavljena in da znajo povezati educational goals. After returning to schools the teachers were teoretično znanje s prakso. Ko učenje temelji na konkretni able to choose between the established teaching methods and the izkušnji, govorimo o izkustvenem učenju. Če želimo, da učenci use of methods supported by ICT. Although traditional pridobijo iz izkušenj nova znanja, morajo biti prisotni tako classroom education was sorely missed during distance learning fizično, kot čustveno. To pomeni, da morajo o izkušnji it became clear that education without the use of ICT is no longer razmišljati, jo razumeti in povezati z dosedanjim znanjem in possible, however the teacher should be the one to determine the pridobljenimi izkušnjami. best teaching methods for their students. When learning is based on a concrete experience we talk about experience based learning M. Garvas (2010) je zapisala, da je izkustveno učenje način, kako or empirical learning. If we want the students to acquire new se povežeta teorija in praksa, bistveno vlogo pa ima seveda knowledge based on experiences they need to be present osebna izkušnja, saj je za izkustveno učenje značilno, da se physically as well as emotionally. They need to think about the najbolje učimo, če nekaj naredimo sami. Govorimo o experience, understand it and connect it to their previous transformaciji spoznanj na podlagi novih izkušenj. S takšnim knowledge and experiences. pristopom dosegamo trajnejše znanje ter drugačen način razmišljanja in delovanja. Pomembno je, da znamo praktične M. Garvas (2010) wrote that experience based learning provides izkušnje povezati s teoretičnim znanjem, kar omogoča prenos a way to connect theory and practice, a major part of it being a teorije v prakso in spodbuja učenje avtonomnega delovanja. personal experience. It is well known that students learn better Tako znanje učencev postaja še kakovostnejše, širše, bogatejše when they experience something themselves. In that case we can in uporabnejše. talk about a transformation of lessons learnt through new experiences. By including experience based learning the V prispevku bom predstavila izvedbo dneva dejavnosti na temo students' knowledge acquires a more lasting value. It is important elektrike, kjer so učenci izvajali poskuse po klasični metodi s to be able to relate practical experiences to theoretical knowledge pomočjo didaktičnih pripomočkov in s pomočjo brezplačnega which in turn enables the transfer of theory into practice and it internetnega programa, ki nam omogoča simulacije poskusov. also encourages autonomous learning. In this way the knowledge Predstavila bom tudi učinkovitost dela pri posamezni metodi, that the students get is the widest posible knowledge as well kdaj lahko govorimo o izkustvenem učenju in katera metoda je richer and more useful. bila učencem bolj všeč. Pri vsaki metodi bom opredelila prednosti in slabosti le-te, podala praktične primere, kjer je This paper presents an activity day where the students carried out electricity experiments using didactical aids and a free online program. The paper presents the efficiency of each method and 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 the experience based learning. Furthermore, it evaluates which for profit or commercial advantage and that copies bear this notice and the full of the methods described were better recieved by the students. citation on the first page. Copyrights for third-party components of this work must The pros and cons of each method as well as practical examples be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia of usage are also presented. Students' evaluations are also © 2022 Copyright held by the owner/author(s). included in the paper to present their experiences. 490 KEYWORDS eksperimentiranje z didaktičnimi pripomočki. Gre za princip Experience based learning, Physics experiments, E-learning izkustvenega učenja, kjer prihaja do povezovanja med materials, Online applications, simulation of physical teoretičnim in praktičnim delom in omogoča učinkovitejše experiments dojemanje pojmov in novih spoznanj. Čeprav imajo učenci v času poskusov že predznanje o vezavah, so vsakič presenečeni o svetilnosti žarnic ter toku in napetosti, ki ga izmerijo na njih. S 1 UVOD svojim znanjem lahko predvidijo, kakšne bodo meritve, te pa največkrat malo odstopajo od pričakovanih. Za natančne Učitelji pri podajanju učne snovi želimo pomoč računalnika v meritve, dokazovanje zakonov in risanje grafov se bolj nagibam vzgojno-izobraževalnem procesu vključiti tam, kjer je mogoče in k uporabi animacij in računalniških programov. Te učencem smiselno. Pri pouku fizike je zelo pomembno, da se učenci pomagajo pri predstavitvi abstraktnih vsebin, vendar pa jih ne seznanijo tako s teoretičnimi, kot tudi s praktičnimi vsebinami. začutijo tako kot klasične poskuse. Pri uporabi animacij Pri vsebinah, ki so za učence preveč abstraktne, so nam za spodbujam učence, da preizkusijo stvari, ki so sicer tvegana učinkovitejše podajanje snovi v pomoč animacije, računalniški (kratek stik, napačna vezava baterij ...). programi, simulacije. Za optimalno učinkovitost pri pouku je V naslednjem delu bom še bolj podrobno predstavila delo pri potrebna »prava mera« različnih metod dela. Da učenci vsaki od delavnic ter prednosti in slabosti posameznih metod dela. ponotranjijo snov, se morajo srečati s konkretnimi primeri. Že star kitajski pregovor pravi: Povej mi in bom pozabil, pokaži mi in se bom spomnil, vključi me in bom razumel. To najbolje opiše pomen izkustvenega učenja, ki ga pri učencih želimo doseči. Izkustveno učenje se je povečalo v zadnjih nekaj desetletjih kot odgovor na učenje, ki je zasnovano na knjigah, torej abstraktno učenje. Izkustveno učenje je način, kako se povežeta teorija in praksa, bistveno vlogo pa ima seveda osebna izkušnja, saj je za izkustveno učenje značilno, da se najbolje učimo, če nekaj naredimo sami (Garvas, 2010). [3]. Predstavila bom potek dneva dejavnosti (naravoslovni dan), kjer smo uporabili različne metode eksperimentiranja, prednosti in slabosti obeh ter evalvacijo dela pri učencih. Raziskovalna tema je bila elektrika. Učenci so teoretičen del predhodno obravnavali pri pouku fizike, na dnevu dejavnosti pa so svoje znanje uporabili za dokazovanje lastnosti elektrike z eksperimenti in meritvami. Razdeljeni so bili v skupine (po štiri Slika 1. Primer navodil za učence (učni list) oz. po trije učenci) in so krožno izvajali naslednje delavnice: 1. delavnica: Vezave električnih krogov s pomočjo vezavnih 2.1 Klasično eksperimentiranje s pomočjo plošč. Učenci so na šolski malonapetostni vir vezali različne vezave s porabniki in merili električni tok in napetost. didaktičnih pripomočkov 2. delavnica: Vezave električnih krogov s pomočjo Učenci so se prvič rokovali s sestavljanjem električnih vezij, zato računalniškega on-line programa. Učenci so s pomočjo sem jih v začetku vodila frontalno, kasneje pa so poskušali programa sestavili električni krog z uporom in merili izvajati eksperimente samostojno. Učenci so s pomočjo električni tok in napetost. Dobljene rezultate so predstavili sestavljenih vezij ugotavljali lastnosti vzporednih in zaporednih z grafom. vezav porabnikov. Pri sestavljanju so bili zelo motivirani, saj so 3. delavnica: Zaporedna in vzporedna vezava virov in vsi v skupini prišli do izraza z delitvijo vlog. Dobro so se izkazali porabnikov ter lastnosti magnetizma. učenci, ki jim računanje ne gre najbolje od rok oz. kot sami Na sliki 1 je del učnega lista z navodili za eksperimentiranje, pravijo, jim fizika »ne leži«. Izjemno zanimanje za praktični del ki ga učenci dobijo ob začetku dneva dejavnosti. Tu so zbrane elektrike pokažejo fantje. Največkrat se radi preizkusijo še pri naloge po sklopih z navodili za eksperimentiranje s klasičnimi sestavljanju kompleksnejših vezij in imajo pri tem tudi veliko eksperimenti ter računalniškimi simulacijami. praktičnih vprašanj. Tukaj se izrazito opazijo učinki izkustvenega učenja, kjer se učenčeva neposredna izkušnja pretvarja v pomembno in zanesljivo znanje ter pri tem povezuje 2 POTEK DNEVA DEJAVNOSTI IN spoznavni, čustveni in akcijski vidik. PRIMERJAVA UČINKOVITOSTI Na podlagi teoretičnega predznanja so učenci po beleženju POUČEVANJA S KLASIČNIM meritev kmalu prišli do ugotovitve, da dejanske meritve EKSPERIMENTIRANJEM IN Z UPORABO odstopajo od pričakovanih in da pri realnih poskusih prihaja do ANIMACIJ izgub. Tako se tok pri zaporedno vezanih žarnicah ne razpolovi oz. pri vzporedni vezavi podvoji, kot vedo iz teorije, ampak Ker je ura fizike prekratka za učinkovito eksperimentiranje po dobijo približek temu. Presenečeni so bili tudi, da gonilna skupinah, že nekaj let organiziram naravoslovni dan za učence 9. napetost ni bila enaka napetosti na izviru in v nadaljevanju imeli razreda, kjer svoje teoretično znanje uporabijo pri praktičnih razpravo, zakaj je do razlik sploh prišlo. nalogah. Tako za iskanje lastnosti vzporednih in zaporednih vezav porabnikov je zagotovo bolj priporočljivo in nazorno 491 Pri meritvah uporabljamo analogne merilnike, kjer morajo Prednosti fizikalnih poskusov s pomočjo računalniških učenci določati merilna območja in s pomočjo izbranih skal programov: pravilno odčitati meritev. Pomembno je, da kljub možnosti - skupine so lahko številčnejše, uporabe digitalne opreme spodbujamo rokovanje z analognimi - natančne meritve, merilniki, saj le-ti spodbujajo boljše razumevanje rezultatov. - učenci lahko program uporabljajo tudi kot pripomoček Ker so kakovostni kompleti za fizikalne poskuse zelo dragi, pri preverjanju računskih nalog, jih imamo na šoli manj, posledica tega pa so številčne skupine. - enostavna ponazoritev abstraktnih stvari (potovanje Zato pri pouku izvajamo le krajše frontalne poskuse in uporabo elektronov in smer električnega toka), računalniških animacij, za eksperimentiranje po skupinah pa - možnost preizkušanja (česar v realnosti raje ne izkoristim naravoslovni dan, ki traja pet šolskih, kjer so učenci počnemo), razdeljeni v manjše skupine. Na sliki 2 je prikazano, kako učenci - uporabnost programa tudi doma. izvajajo poskuse s škatlami za eksperimentiranje, na sliki 3 pa zajem zaslona računalniške simulacije, kjer so učenci raziskovali lastnosti vzporednih in zaporednih vezav virov ter prevodnost materialov. Slika 3. Primer vzporedne in zaporedne vezave virov ter prevodniki in neprevodniki Slabosti fizikalnih poskusov s pomočjo računalniških Slika 2. Klasično eksperimentiranje po skupinah programov: - učenci ne dobijo realnega občutka uporabe elektrike, Prednosti klasičnega eksperimentiranja: - za sestavljanje vezij niso bili tako motivirani kot pri - učenci so zelo motivirani za delo, klasični metodi. - primerno za raziskovanje lastnosti vzporednih in zaporednih vezav porabnikov in virov, 3 ZAKLJUČEK - nazorna uporaba ampermetra in voltmetra, - elektrika ni več tako abstraktna, V prispevku sem želela orisati pozitivne in negativne lastnosti - izkustveno učenje. aplikacije na eni strani in klasično eksperimentiranje na drugi strani. Ker na naravoslovnem dnevu izvajam obe metodi dela, ju Slabosti klasičnega eksperimentiranja zlahka lahko primerjamo. Tako se pokaže, kdaj je smiselno za - Pri rednih urah so prevelike skupine eksperimentiranje uporabiti klasično metodo in kdaj podporo - Meritve niso natančne računalničkih animacij. Mnenje učencev ob koncu dneva je bilo, da jim je bilo bolj zanimivo eksperimentiranje po klasični 2.2 Sestavljanje vezij s pomočjo spletnega metodi, ker je bilo to za njih nekaj novega in so bili zato bolj programa in animacij motivirani. Celovite učenčeve vpletenosti v izkušnjo ne more Za sestavljanje vezij na računalniku smo uporabili brezplačen nadomestiti nobeno še tako doživeto pripovedovanje ali branje o internetni program PhET (https://phet.colorado.edu/) [1]. izkušnjah nekoga drugega. Seveda pa ni samoumevno, da je Učenci so s pomočjo programa sestavili vezja (vzporedna in vsako izkustveno učenje kakovostno. Treba je znati ustvariti zaporedna vezava žarnic, uporov ter baterij), opravili meritve ter ustrezna učna okolja in omogočiti učni proces, v katerem pride tako natančno ugotovili lastnosti posameznih vezij, dokazali do integracije zaznavanja, čustvovanja, delovanja in razmišljanja Ohmov zakon in s pomočjo meritev narisali graf. Preizkusili so pri ustvarjanju znanja in osebnostnem oz. profesionalnem tudi veljavnost formule za vzporedne in zaporedno vezane razvoju [2]. porabnike, opazovali smer potovanja elektronov in smer Iz pedagoškega vidika menim, da sta obe metodi dela z električnega toka, nazorno opravili meritve za vzporedno in učenci dobri, naloga učitelja pa je, da dobro razmisli, katere cilje zaporedno vezavo dveh virov, naredili kratek stik, opazovali in bomo bolj nazorno približali učencem s klasično metodo oz. z spreminjali fizikalne parametre na žarnicah in opazovali uporabo računalniških programov oz. animacij. svetilnost le teh. 492 LITERATURA [1] Spletna aplikacija PhET. Pridobljeno 7. 8. 2021 https://phet.colorado.edu/ [2] Barica Marentič Požarnik, Marjeta Šarić, Barbara Šteh, 2021. Izkustveno učenje. Oddelek za pedagogiko in andragogiko [3] Garvas, M. (2010). Izkustveno učenje kot praksa in teorija izobraževanja in usposabljanja strokovnih delavcev v vrtcu Trnovo. Andragoška Spoznanja, 16 (1), 35–46. https://doi.org/10.4312/as.16.1.35–46 493 Recept, navodilo, algoritem Recipe, Instruction, Algorithm Peter Purg Osnovna šola Antona Martina Slomška Vrhnika Vrhnika, Slovenija peter.purg@guest.arnes.si POVZETEK organization of the activity day and various gamification tools that can help with digital competences. As a result, the students Prispevek bo prikazal, kako smo se z učenci 8. razreda lotili dela not only enjoyed the day – they have also become empowered to na tehniškem dnevu, posvečenem programiranju. Vsebinsko smo face new challenges in a new way. Some have also reported that dodali tudi ponavljanje in usposabljanje učencev za oblačno now that they know how to break down a large task into smaller računalništvo. V primeru, da bi pouk ponovno potekal na daljavo, parts, they find problem solving less difficult. smo poglobili pomembno znanje uporabnega računalništva. Vsebinsko pa smo obogatili in razbili monotonost z različnimi KEYWORDS dejavnostmi. Za proces učenja smo za najobsežnejši del tehniškega dneva zbrali igrifikacijo. Gre za način dela, kjer Gamification, technical day, computational thinking, posameznik s pomočjo igre razvija računalniško razmišljanje in programming, algorithm pridobiva znanje. Ta dan smo obogatili še na način, da smo dodali dejavnost, ki je povezovala digitalno in fizično delo ter 1 UVOD obdelali računalniške koncepte s pomočjo igre v fizični obliki. V prispevku bo predstavljena igrifikacija, motivacija, organizacija Naloga učitelja je konstantno razmišljanje o tem, kako učence dneva dejavnosti in različna orodja za igrifikacijo, ki lahko navduševati, spodbuditi, motivirati in angažirati za delo ter pomagajo pri digitalnih kompetencah. Rezultat tovrstnega učenje. To nikakor ni preprosta in samoumevna naloga, vendar pristopa je, da so učenci ta dan ne samo uživali, ampak smo jih je vredna vloženega truda. Uspešna izpeljava te naloge je odvisna tudi opolnomočili za soočenje z novimi izzivi na nov način. od izobraževanja in iskanja novih načinov dela. Eden izmed Nekateri so poročali tudi o tem, da jim sedaj, ko vedo, kako takšnih načinov dela, ki vključuje diferenciacijo in razdeliti veliko nalogo na manjše dele, reševanje problemov dela individualizacijo, je igrifikacija. Igrifikacijo za osnovno šolo manj težav. lahko razumemo kot igro, največkrat digitalno, ki omogoča, da se učenci med igranjem nekaj naučijo. Vsi tega pojma ne KLJUČNE BESEDE razumejo na tak način. Igrifikacijo različno opredeljujejo tudi strokovnjaki, saj gre za razmeroma nov način dela. Igrifikacija, tehniški dan, računalniško razmišljanje, Izziv, s katerim smo se soočili, je dan dejavnosti izpeljati za programiranje, algoritem učence na način, da bi utrdili znanje za možne prihajajoče šolanje ABSTRACT na domu. Obenem pa smo želeli predstaviti računalniško razmišljanje in programiranje s pomočjo igrifikacije. Tako smo The paper presents the work done on the technical day. The topic povezali navezavo recept – navodilo – algoritem: recept za peko of the technical day was programming, to which we added palačink, navodilo za peko in algoritem, ki bi ga razumel repetition and training of students for cloud computing as well. računalnik. In the event that the lessons were to be taught remotely again, we deepened the important knowledge of applicable computing. We enriched the content and took the monotony away with various 2 IGRIFIKACIJA activities. For the learning process, we have chosen gamification for the major part. This is a way of working where an individual 2.1 Opredelitev pojma develops computational thinking and acquires knowledge with Igrifikacijo, ki je precej sodobna besedna skovanka, lahko the help of a game. We enriched this day in the way that we added razumemo različno. Razlogov za to je več. Eden izmed njih so an activity that connected digital work as well as physical work lahko jezikovne razlike. Pojem je bil povzet iz angleščine and processed computer concepts with the help of a game in ( gamification), kjer so za različne tipe iger različni izrazi, kar physical form. The paper will present gamification, motivation, vpliva na različno razumevanje pojma. Poznamo veliko različnih Permission to make digital or hard copies of part or all of this work for personal or tipov iger: lahko so športne, glasbene, video igre, uganke, igre v classroom use is granted without fee provided that copies are not made or distributed obliki stav … [1]. V opredelitvi igrifikacije se razlikujejo tudi for profit or commercial advantage and that copies bear this notice and the full mnenja strokovnjakov, četudi se pri vseh pojavljajo enotni 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). ključni elementi. Enotni elementi so napredovanje v naslednje Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia nivoje, točkovanje, nagrajevanje ipd. Burke igrifikacijo opredeli © 2022 Copyright held by the owner/author(s). kot »uporabo igralne mehanike in oblikovanje izkušenj za 494 digitalno angažiranje in motiviranje ljudi za dosego svojih 2.3 Motivacija pri igrifikaciji ciljev« [2]. Pojem igrifikacija je skoval britanski raziskovalec Huang in Soman trdita, da igrifikacija pomaga pri ljudeh, ki Nick Pelling leta 2002. Pelling je programer, ki je ustvarjal igre, izgubijo motivacijo ali je sploh nimajo. Zakaj pride do tega? in je bil zadolžen za razvoj igri podobnega vmesnika za Motivacija in zavzetost sta običajno predpogoja za bankomate in prodajne avtomate. Besedo bi naj namensko dokončanje naloge ali spodbujanje določenega vedenja. Pri ustvaril kot »grdo besedo« - tako jo je opisal Nick Pelling. izobraževanju, učenju ipd. so razlogi za nižjo uspešnost po Uporabil jo je za opis pospešenega uporabniškega vmesnika navadi dolgočasje ali pomanjkanje angažiranosti, večkratna podobnega igri [3]. Tako beseda kot način dela sta se hitro odsotnost (ki se stopnjuje: večkrat je otrok odsoten, bolj je težko prijela. To dokazuje tudi Google Trends (Slika 1), ki kaže, da sta vzpostaviti motivacijo in zavzetost), zaradi česar posameznik ni prvi večji preboj beseda in iskanje le-te doživela šele leta 2010, pripravljen, da se posveti temi. Največkrat otroke moti dve leti kasneje pa dosegla največjo rast v zgodovini besede. tehnologija, kot so na primer pametni telefoni, internet … Iskanje se je drastično dvignilo kot tudi priljubljenost dela na tak Podobno kot učenci v šoli, se s takimi izzivi soočajo tudi način. zaposleni, oziroma izvajalci programov za usposabljanje zaposlenih. Učenci ali zaposleni lahko kažejo nezanimanje ali minimalno zanimanje in s tem tudi majhno pozornost pri prejemanju znanja. To po navadi vodi v stres in vpliva na slabše razumevanje celotnega razreda oziroma skupine. Dodatno lahko vodi tudi v skupinsko nezadovoljstvo in slabe rezultate. Igrifikacija kot oblika spodbujanja motivacije je današnjim generacijam v digitalni dobi zelo blizu. Gre za priljubljeno taktiko za spodbujanje določenega vedenja in povečanje motivacije ter angažiranosti. Najpogosteje jo najdemo v tržnih strategijah, obenem pa jo vključujemo že v številne Slika 1: Google Trends 2004 – izobraževalne programih v šolah, saj učiteljem pomaga najti ravnovesje med doseganjem ciljev in zadovoljstvom pri učencih Opaziti je tudi, da se je zanimanje za igrifikacijo povečalo v [5]. zadnjih letih. Temu je gotovo botrovalo to, da so ljudje preživeli Ljudje se velikokrat lažje poistovetijo z glavnim likom v igri več časa doma tudi zaradi obsežnejšega dela na daljavo in in se na ta način hitro ubranijo oviram, kot so depresija, ciničnost pandemije Covid-19. To je razvidno z naslednjega grafa (Slika ali razočaranost. Pri igrah se namreč lahko vključijo sami in se 2) [4]. lažje s tem motivirajo ter tudi brez posledic igro večkrat poskusijo igrati. Z igro se dolgočasne ali vsakdanje naloge spremenijo v zanimive in jih lažje osmislijo. Motivirajo pa se lahko preko predstavitve praktičnih izzivov, spodbujanja, napredovanja po ravneh (stopnjah), vodenih izzivov in si tako sami prizadevajo dosegati najboljše rezultate. Igrifikacija omogoča vse te načine zraven doseganja zastavljenih ciljev preko vključevanja na čustveni ravni (poistovetenje z glavnim likom) to še dodatno motivira. Dodatno razbija večje naloge na Slika 2: Google Trends 2015 - manjše praktične izzive in igralce spodbuja, da napredujejo po ravneh do cilja: naučiti se nekaj novega. [5] 2.2 Motivacija Na tak način se notranja in zunanja motivacija povežeta. Zunanja motivacija so ravni, točke, nagrade, misije … S tem Motivacija je duševni proces, ki s pomočjo različnih motivov ali spodbujajo naravno notranjo motivacijo, saj se posameznik teženj, to so lahko potrebe, vrednote, želje, ideali ali nagoni, vodi odloči ali bo ukrepal ali ne. [7] vedenje ljudi in jih usmerja k določenim ciljem.[11] Delimo jo na notranjo in zunanjo motivacijo. »O zunanji motivaciji govorimo, kadar se učimo zaradi zunanjih posledic, kadar cilj ni 3 DAN DEJAVNOSTI v dejavnosti sami, ampak zunaj nje. Zunanja motivacija po Ministrstvo za izobraževanje, znanost in šport (v navadi ni trajna, pogosto je povezana s pritiski, zaskrbljenostjo, nadaljevanju MIZŠ) je dneve dejavnosti dodelilo in opredelilo posebej kadar ciljem, ki si jih zastavimo, nismo kos. Pri notranji leta 1998. Opredelili so jih kot del obveznega programa osnovne motivaciji je cilj delovanja v dejavnosti sami in vir podkrepitve šole in vsebujejo določene atribute kot so medpredmetno v nas. Prednost notranje motivacije je v vztrajnosti v povezovanje, usvajanje in nadgrajevanje pridobljenega znanja z zadovoljstvu, ko dosežemo cilj. Notranjo motivacijo povezujemo različnih področij, nadgrajevanje znanja s praktičnim učenjem, s spontanostjo, ustvarjalnostjo in širjenjem interesov. V ljudeh se odzivanje na aktualne dogodke idr. Vsakemu dnevu dejavnosti je prepletata želja po uspehu in strah pred neuspehom. Otrok se dodeljeno 5 pedagoških ur. Osmi razredi imajo 4 tehniške dni (v začne zavedati posebnosti storilnostne situacije po tretjem letu, nadaljevanju TD). Izhodišča za dneve dejavnosti so srečni in zadovoljni otroci so običajno zdravi, sreča pa je vir vzpodbujanje vedoželjnosti, ustvarjalnost in samoiniciativnost motivacije za dejavnost.« [6] učenk in učencev, usposabljanje za samostojno opazovanje in pridobivanje izkušenj ter znanja, za razvijanje spretnosti ter za 495 samostojno reševanje problemov. Pri TD učenci in učenke računalniku, poskusimo razložiti koncepte delovanja opazijo tehniški problem, ga raziščejo in zanj poiščejo rešitev ter računalnika. Minecraft (Slika 3), Scratch (Slika 4), Pišek (Slika jo preverijo. TD se povezujejo s cilji tehnike in tehnologije ter 5), Poliglot (Slika 6) in druga orodja so po navadi igre za učenje gospodinjstva. [8] Tehnika in tehnologija sta se od leta 1998 programiranja ali pa igri dodajo izobraževalni del za še dodatno spremenili, kakor so se zamenjale določene vsebine. V tehniki je motivacijo udeležencev z že znanim izgledom in načinom novost robotika, kjer se fizično računalništvo sreča s tehniko. Na upravljanja. Za konec smo si pustili še Robotize – program, podlagi tega smo se na osnovni šoli Antona Martina Slomška zapisan v Scratchu in je narejen tako, da vsebuje še fizični Vrhnika odločili, da naredimo na robotiki osnovane TD z poligon ter nagrado. vsebino, ki smo jo poimenovali programiranje. Vsebino smo predstavili osmim razredom. 3.1 Organizacija in opredelitev TD programiranje TD smo organizirali za učence osmih razredov, ki smo ga strukturirali na udeležencem čim bolj jasen način. Najprej smo predstavili, kako bo potekal celoten dan dejavnosti. Navedli smo, da se bodo spoznali z že znanimi temami, ki jih obnovimo, ponovimo ali morda za nekatere predstavimo na novo. Teme so obsegale oblačno računalništvo, spletne učilnice, varnost, deljenje dokumentov … Po predstavitvi tem smo prešli na programiranje s pomočjo igrifikacije. Slika 3: Minecraft education edition Tako kot večini ljudem, ki prvič slišijo besedo programiranje, je tudi veliko učencem to nekaj eksotičnega, morda celo nekaj, kar lahko malenkost odvrača. Še posebej tiste, ki so nevešči uporabe računalnika. Naslov članka razkriva, kako smo programiranje na čim lažji način predstavili učencem. Naš postopek je bil: recept, navodilo, algoritem. Za začetek smo učence pripravili na to, da zagotovo vedo, kaj skuhati ali speči. Nato smo jih prosili, da nam predstavijo recept za jed, ki so si jo morali sami izbrati (izbrali so si palačinke). Za tem smo primerjali, kako bi lahko to spisali kot navodilo, ki bi ga lahko razumel robot na višji taksonomski stopnji. Za razliko od recepta je to navodilo moralo biti veliko bolj natančno, sicer se bi lahko zgodilo, da bi ponev pri peki palačink ostala na štedilniku, brez Slika 4: Scratch in Robotize da bi vklopili grelno telo. Takoj za tem pa smo dali učencem nalogo, da poskusijo to zapisati tako, da bi razumel računalnik. Takrat še pojma algoritem niso poznali. SSKJ pravi, da je »algorítem -tma m (í) mat. navodilo, ki določa vrsto in zaporedje operacij v računskem postopku: določiti algoritem; algoritem za deljenje večmestnih števil …« [9]. S tem smo jih želeli opolnomočiti, da računalniški jezik ni tako težek. Pomagali smo jim tudi z diferenciacijo po predznanju in jim dali različno težke naloge. Na voljo je veliko orodij, mi smo izbrali naslednje: Minecraft education edition, Pišek ACM, Poliglot, Vidra.si in nekaj, kar smo s pomočjo fizične aktivnosti in računalnika Robotize izumili sami. Slednje bo v nadaljevanju članka podrobneje opisano. Orodja smo jim postopoma prikazali in dali možnost izbire, da so lahko delovali po najboljših močeh. Seveda element učiteljske ali mentorske spodbude in vodenja ni manjkal. Bili smo prisotni, pozorni, jih bodrili, ko je to bilo potrebno in dajali ustrezne nasvete za nadaljevanje ter reševanje nalog. Slika 5: Pišek ACM 4 ORODJA ZA UČENJE PROGRAMIRANJA Večina orodij je zgrajenih tako, da s pomočjo igrifikacije uporabnika vodijo do znanja. Velikokrat koncentracija vseeno opeša, zato smo si zamislili, da morebitno monotonost prekinemo s posebnimi aktivnostmi. Zelo dobre so bile vsebine s strani Vidra.si, kjer preko nalog, ki se ne izvajajo na 496 Slika 6: Poliglot 5 POVEZOVANJE DIGITALNE IN FIZIČNE Slika 8: Del TD IGRE Za čim bolj kakovostno in razgibano izpeljavo omenjenega TD (Slika 8) smo v zaključek umestili igro, ki smo jo s svojimi bloki naredili v Scratchu in je oblika zgoraj opisane igrifikacije. Tako smo povezali še digitalno igro z fizičnim doživetjem (Slika 9) in dodali dva elementa presenečenja. Prvi element presenečenja je aktivnost na poti do cilja. Sam cilj pa zraven pohvali in uspeh podkrepi s sladkim presenečenjem. Ideja za Robotize je narejena na način kot iskanje skritaga zaklada. Za izvedbo je potrebno delo učencev v dvojicah in porazdelitev vlog, ki se nato lahko zamenjajo. Udeleženca se v paru dogovorita, kdo bo prevzel vlogo reševalca naloge in kdo programerja. Programer robotizira svojega partnerja tako, da mu pokaže kodo (Slika 7), s katero pride do cilja. Ta si jo fotografira bodisi s telefonom bodisi s tablico. Tako postane »robot«, ki izvaja nalogo po ideji programerja. V primeru, da je pravilno sledil algoritmu, na koncu dobi sladko nagrado. [10] Tako smo še dodatno razmigali učence in na kreativen ter igriv način zagotovili utrjevanje znanja, ki so ga pridobivali tekom TD. Slika 9: Fizična aktivnosti pri Robotize 6 REZULTATI Učitelji smo z uporabo igrifikacije in še posebej pripomočka Robotize izjemno zadovoljni. Nivo zadovoljstva smo preverili tudi pri udeležencih. Povratne informacije učencev so bile zelo dobre. Eden od pokazateljev njihovega zadovoljstva je tudi to, da se jih je na izbirne predmete računalništva vpisalo več kot prejšnja leta. Učenci so z vpeljavo igrifikacije usvajali znanja in pridobivali kompetence, ki jih pri drugih predmetih v šoli ne pridobivajo. Urili so se v računalniškem mišljenju, kar pomeni, da so se spoznali z novimi metodami. Te metode udeležencem pomagajo pri spopadanju s čustvi, ko je učno okolje frustrirajoče. To pomaga pri vztrajanju ob neuspehu, kar so učenci prav tako potrdili. Velika večina je poročala o tem, da so nadaljevali z nalogami tudi, ko jim je padla koncentracija. Najbolj so jim bile všeč naloge, kjer so lahko iskali in popravljali napake programa. Tudi to je način učenja, ki ga drugače ne morejo izkusiti in jim je bil zelo všeč. TD in učenje računalniškega mišljenja jim je Slika 7: Robotize algoritem omogočil, da so spoznali samoregulacijsko učenje, reševanje velikega problema z razdelitvijo na manjše delčke, kako vztrajati 497 kljub neuspehom ter na tak način bolj kakovostno učenje in igrifikacija ima. Priporočili bi vpeljavo tudi pri drugih predmetih višanje psihološke odpornosti. za usvajanje nove ali ponavljanje stare snovi. Za učitelja priprava takšnega TD predstavlja velik izziv. Tri Izzivi za naprej so gotovo usposabljanje večjega števila različne razrede je potrebno razporediti na tri različne dni, saj je učiteljev in navduševanje za tako obliko dela. Morda bo ravno omejitev velikost učilnice. Dodatna omejitev je znanje ostalih igrifikacija pripeljala do izboljšanja rezultatov učencev na učiteljev. Tema je zelo specifična in mora eden od učiteljev TD prijazen način. prevzeti kot glavni organizator in izvajalec. Njegova naloga je, da dobro premisli, kako bodo podane vsebine, da bodo postopne. Izbrati mora tudi prava orodja, da učencem ne bo pretežko ali ZAHVALA prelahko in hkrati nekaj kar že poznajo, da jih pritegne. Odziv je Zahvalil bi se sodelavcem in sodelavkam osnovne šole Antona bil zelo pozitiven in dobili smo dodatno motivacijo, da bi tak TD Martina Slomška, saj nas vedno podpirajo pri idejah in izvedbi še naredili in morda vključil ostale učitelje. Tako bi lahko tak različnih vsebin. Posebej bi se zahvalil Branku Pongracu, ki je način dela vpeljali tudi pri drugih predmetih. Velika prednost pri izvedbi tega dneva še posebej pomagal in bil nepogrešljiv na igrifikacije je, da lahko z igrami motiviramo več starostnih vsakem koraku. skupin učencev. Kot slabost bi izpostavili predvsem tehnični vidik, saj morajo računalniki ali tablice delati brezhibno. V LITERATURA IN VIRI primeru, da ne delujejo brezhibno, hitro izgine motivacija, ki jo [1] Csabaa R., Damsab A. Kristófc G. A., Gamification on the edge of predstavlja igranje igre in hkrati učenje. Kot druga slabost, ki jo educational sciences and pedagogical methodologies. Dostopno na naslovu vidimo, je obvezno dodatno izobraževanje kadra, da bi lahko http://real.mtak.hu/74171/1/12.pdf (30.7.2022) [2] Burke B., 2014. Gamify: how gamification motivates people to do izpeljali TD za več razredov. extraordinary things. Bibliomotion, Inc., 109(1), 5–10. Dostopno na naslovu Kljub vsemu, je bila izkušnja tako dobra, da jo priporočamo https://doi.org/10.1017/CBO9781107415324.004 [3] Pelling N., 2017. The (Short) Prehistory of “Gamification. Dostopno na vsem, ki so se pripravljeni lotiti nekaj novega ali nekaj https://nanodome.wordpress.com/2011/08/09/the-short-prehistory- drugačnega. ofgamification/ (2. 8. 2022) [4] Google.com, Google Trends. Dostopno na naslovu https://trends.google.com/trends/explore?date=all&q=%2Fm%2F0cm8xv9 (29. 7. 2022) 7 ZAKLJUČEK [5] Huang W. H. and Soman D., 2013. A Practitioner’s Guide To Gamification Of Education. Dostopno na naslovu https://mybrainware.com/wp- Za učitelja je največja motivacija videti, da naš pristop zagotovi content/uploads/2017/11/Gamification-in-Education-Huang.pdf (5. 8. 2022) želene rezultate pri pridobivanju znanja za učence in načinu dela [6] Podplatnik V., Motivacija. Dostopno na naslovu http://www.solazaravnatelje.si/ISBN/978-961-6637-29-9/61-62.pdf (1. 8. ter v tem, da pri učencih opazimo zadovoljstvo. Pri pripravi TD 2022) smo dejavnosti načrtovali tako, da bi učenci bili ves čas aktivni [7] Muntaen C. I., Raising engagement in e-learning through gamification. 2011. – miselno kot tudi fizično. Še posebej smo si obetali uspehe, saj Dostopno na naslovu http://icvl.eu/2011/disc/icvl/documente/pdf/met/ICVL_ModelsAndMethod novejši način poučevanja z metodo igrifikacije zunanje motivira ologies_paper42.pdf (29. 7. 2022) udeležence tako, da spodbudi tudi notranjo motivacijo. [8] Nacionalni kurikularni svet in Strokovni svet Republike Slovenije za splošno izobraževanje, Dnevi delavnosti, 1998. Dostopno na naslovu Igrifikacija lahko na prvi pogled deluje zelo enoznačno. Vendar https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- se v kratki zgodovini pojma, od leta 2002, spreminja in razume sola/Ucni-nacrti/Drugi-konceptualni-dokumenti/Dnevi_dejavnosti.pdf (30. različno tako s strani strokovnjakov kot tudi zaradi jezikovnih 7. 2022) [9] Inštitut za slovenski jezik Frana Ramovša ZRC SAZU in avtorji, Slovar razlik. Mi smo jo tolmačili kot digitalno ali fizično igro, ki je slovenskega knjižnega jezika, 1970–1991, 1994, 1997, 1998, 2000, 2008, namenjena pridobivanju znanja. Gre torej za hvaležno obliko 2010, 2014. Dostopno na naslovu https://fran.si/iskanje?FilteredDictionaryIds=130&View=1&Query=algorite igre, ki se jo uporabi v izobraževalne namene. Učencem smo m (7. 8. 2022) ponudili individualni pristop in prilagajanje vsebin glede na [10] ZRSŠ, Zbornik povzetkov SIRIKT, 11. mednarodna konferenca – Skupaj v izzive, 82-83, 2018. Dostopno na naslovu predhodno znanje. Monotonost, ki bi se lahko pojavila, smo https://www.zrss.si/pdf/Sirikt2018.pdf (1. 8. 2022) razbili s fizično aktivnostjo, oziroma igro, ki je povezala [11] Nanut P. A. in Škorjanc B. D., Umetnost učenja, 2013. Dostopno na naslovu digitalno in fizično sfero delovanja. http://www2.arnes.si/~lukoper9/umetnost_ucenja/kaj_je_motivacija.html (7.8.2022) Metoda igrifikacije se je v našem primeru izkazala za [12] Mikrosoftove izobraževalne vsebine https://education.minecraft.net/en-us izjemno koristno. Izpostavili bi, da je izid TD bil izjemno [13] Spletni pripomoček Vidra.si http://vidra.si/ [14] Spletni pripomoček Scratch https://scratch.mit.edu/ uspešen in je odtehtal možne pomanjkljivosti, ki jih lahko [15] Spletni pripomoček Poliglot https://poliglot.um.si/ [16] Spletni pripomoček Pišek https://pisek.acm.si/contents/4903/ 498 Protokoli za preverjanje pristnosti uporabnikov User Authentication Protocols Roman Rehberger Šolski center Kranj, Višja strokovna šola Kranj, Slovenija rehberger@siol.net POVZETEK password storage for password-based authentication. The paper provides an overview of the use of hash functions, explains their Pri razvoju programske opreme nenehno uporabljamo properties and use in different domains, possible attacks and preverjanje pristnosti uporabnikov na podlagi gesel. weaknesses, as well as ways to strengthen and improve hash Uporabniška gesla moramo varno shraniti tako, da se uporabniki functions. A comparative analysis of compaction algorithms lahko prijavijo, preverijo pristnost in spremenijo svoje geslo, enables users to choose the safest algorithms for their needs. hkrati pa napadalci ne morejo dešifrirati shranjenih gesel nazaj v čisto besedilo, tudi če jim uspe pridobiti dostop do baze podatkov, KEYWORDS ki vsebuje uporabniške račune. Če uporabljamo ali razvijamo spletna mesta ali spletne aplikacije, imamo dostop po prijavi na Protocols, authentication, hash functions podlagi uporabniškega imena in gesla. Enako lahko dostopamo z mobilnimi aplikacijami, spletnimi storitvami in drugimi sistemi 1 UVOD zaščitenimi z gesli, saj vsi potrebujejo varno shranjevanje gesel. Razvijalci pogosto shranjujejo uporabniška gesla na svoja Sodobna kriptografija je namenjena izdelavi in analizi spletna mesta, aplikacije ali druge sisteme v zbirki podatkov, protokolov, ki premagajo grožnje informacijski varnosti. tako kot vse druge uporabniške podatke, vendar večina sistemov Zgoščevalna funkcija je ključna komponenta številnih aplikacij, uporablja shemo zgoščevanja, šifriranja ali avtentikacije gesla. od prevajalnikov, baz podatkov ali internetnih brskalnikov do Članek med drugim ponuja pregled uporabe zgoščevalnih videoiger ali omrežnih naprav. Nize različnih dolžin pretvori v funkcij, razloži njihove lastnosti in uporabo v različnih domenah, nize s fiksno dolžino, znane kot zgoščene vrednosti ali povzetki. možne napade in slabosti, kot tudi načine za okrepitev in Ne glede na vhod je izhod pri zgoščevalni funkciji enake izboljšanje zgoščevalnih funkcij. Predstavljena je pimerjalna velikosti; če zgostimo eno besedo ali celo knjigo, bo izhod enake analiza algoritmov zgoščevanja z namenom olajšati uporabniku velikosti. izbiro najvarnejših algoritmov za svoje potrebe. Zgoščevanje je algoritem, ki izračuna vrednost bitnega niza fiksne velikosti iz datoteke. Datoteka vsebuje bloke podatkov, ki KLJUČNE BESEDE jih zgoščevanje pretvori v veliko krajšo vrednost ali ključ s fiksno dolžino, ki predstavlja izvirni niz. Ena glavnih nalog Protokoli, preverjanje pristnosti, zgoščevalne funkcije zgoščevanja je primerjava dveh datotek med seboj. Ne da bi ju ABSTRACT morali odpreti in primerjali besedo za besedo, bo izračunana zgoščena vrednost teh datotek takoj pokazala, ali sta različni. Password-based user authentication is used continuously in Zgoščevalno vrednost je mogoče obravnavati kot povzetek v software development. User passwords must be stored securely datoteki [1]. so that users can log in, authenticate and change their passwords, V nadaljevanju bomo razložili uporabo zgoščevalnih funkcij, while attackers cannot decrypt stored passwords back to plain njihove lastnosti in uporabo v različnih domenah, možne napade text, even if they manage to gain access to the database in slabosti ter načine za okrepitev in izboljšanje zgoščevalnih containing the user accounts. If we use or develop websites or funkcij. Osredotočili se bomo na primerjavo nekaterih web applications, we have access by logging in with a username algoritmov zgoščevalnih funkcij, s pomočjo katere lahko and password, the same as with mobile apps, web services and uporabnik izbere najvarnejše algoritme za svoje potrebe. other password-protected systems, as they all need secure password storage. Developers often store user passwords on their websites, applications or other systems in a database like any 2 POSTOPKI ZGOŠČEVANJA other user data, but most systems use hash functions, encryption or authentication scheme. There are many ways to implement Zgoščevalne funkcije so kriptografski protokoli, ki temeljijo na bločnih šifrah in imajo pomembno vlogo pri varovanju sodobnih Permission to make digital or hard copies of part or all of this work for personal or komunikacijskih sistemov, saj zagotavljajo preverjanje pristnosti classroom use is granted without fee provided that copies are not made or distributed podatkov. Uporablja se jih za varno kreiranje in shranjevanje 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 gesel, iskanje podvojenih zapisov, anonimne kriptografske be honored. For all other uses, contact the owner/author(s). transakcije, hitro shranjevanje in pridobivanje podatkov ter v Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia varnostnih aplikacijah, kot so digitalni podpisi, kode za © 2022 Copyright held by the owner/author(s). 499 preverjanje pristnosti sporočil (MAC) in druge oblike anliz so številne varnostne organizavije ocenile, MD5 ni več avtentikacije. Močne zgoščevalne funkcije zagotavljajo varen za uporabo [5]. celovitost podatkov, zaščitijo pred nepooblaščenimi SHA je algoritem varnega zgoščevanja in je spremenjena spremembami, zaščitijo shranjena gesla in delujejo pri različnih različica MD5, ki se uporablja za zgoščevanje podatkov in hitrostih, da ustrezajo različnim namenom [1]. potrdil. SHA je bil razvit in objavljen s sodelovanjem NIST in Zgoščevanje in šifriranje zagotavljata zaščito občutljivih NSA leta 1993 kot zvezni standard za obdelavo informacij (FIPS podatkov, vendar je treba v skoraj vseh okoliščinah gesla zgostiti, PUB 180). ne le šifrirati. Zgoščevanje je enosmerna funkcija (nemogoče je Zgoščevalne funkcije z oznako SHA (angl. Secure Hash "dešifrirati" zgoščevanje in pridobiti izvirno vrednost v Algorithm) so funkcije, ki se najpogosteje uporabljajo v navadnem besedilu) in je primerna za preverjanje gesla. Tudi če kriptografiji. Hkrati z razvojem računalnikov kot tudi z razvojem napadalec pridobi zgoščeno geslo, ga ne more vnesti v polje za različnih algoritmov kriptoanalize, so bile kriptografske funkcije geslo aplikacije in se prijaviti kot žrtev. Šifriranje je dvosmerna vedno močnejše. Tako je NIST izdal standarde SH-0, SH-1, SH- funkcija, kar pomeni, da je mogoče pridobiti izvirno odprto 2 in SH-3. Trenutno je še vedno najbolj aktualna uporaba funkcij besedilo. Primerno je za shranjevanje podatkov, kot je naslov iz družine SHA-2, v kateri so štiri zgoščevalne funkcije SHA- uporabnika, saj so ti podatki prikazani v navadnem besedilu v 224, SHA-256, SHA-384 in SHA-512, ki so imenovane po profilu uporabnika. Zgoščevanje njihovega naslova bi povzročilo dolžini prstnega odtisa, ki ga dobimo kot rezultat zgoščanja. popačeno zmešnjavo. Šifriranje se uporablja samo v primerih, ko SHA-2 je v osnovi sestavljen iz dveh zgoščevalnih algoritmov je potrebno pridobiti izvirno geslo v navadnem besedilu. SHA-256 in SHA-512. SHA-224 je različica SHA-256 z Kot del postopka zgoščevanja je geslu lahko dodano soljenje različnimi začetnimi vrednostmi in okrnjenim izhodom. SHA- (Salting), to je edinstven, naključno ustvarjen niz bitov. Ker je 384 in manj znani SHA-512/224 in SHA-512/256 so vse različice sol edinstvena za vsakega uporabnika, mora napadalec razbiti SHA-512. SHA-512 je varnejši od SHA-256 in je običajno zgoščene vrednosti eno za drugo z uporabo ustrezne soli, hitrejši od SHA-256 na 64-bitnih napravah, kot je AMD64. namesto da enkrat izračuna zgoščeno vrednost in jo primerja z Zaenkrat SHA-2 še vedno velja za varnega in se pogosto vsako shranjeno zgoščeno vrednostjo. Zaradi tega je razbijanje uporablja. Bitcoin in nekatere kriptovalute uporabljajo SHA-256 velikega števila zgoščenih vrednosti bistveno težje. Sol prav tako v procesu rudarjenja. ščiti pred napadalcem, ki vnaprej izračuna zgoščene vrednosti z SHA se uporablja pri vseh digitalnih podpisih in certifikatih, uporabo mavričnih tabel ali iskanj v bazi podatkov. Zaradi ki se nanašajo na povezave SSL/TLS. SHA uporabljajo soljenja je nemogoče ugotoviti, ali imata dva uporabnika isto aplikacije SSH, S-MIME (varne/večnamenske razširitve geslo, ne da bi razbili zgoščene vrednosti, saj bodo različne soli internetne pošte) in IPSec. SHA-ji se uporabljajo tudi za povzročile različne zgoščene vrednosti, tudi če sta gesli enaki. razpršitev gesel, tako da si mora strežnik zapomniti zgolj hashe Sodobni algoritmi zgoščevanja, kot so Argon2id, Bcrypt in in ne gesel PBKDF2, samodejno solijo gesla. RIPEMD (RACE Integrity Primitive Evaluation Message Za dodatno zaščito lahko poleg soljenja uporabimo poper Digest) je družina kriptografskih zgoščevalnih funkcij, z (Peppers). Namen popra je preprečiti napadalcu, da bi vdrl v dolžinami 128, 160, 256 in 320 bitov. Temelji na principih katero koli zgoščeno vrednost, če pridobi dostop do baze oblikovanja, uporabljenem v MD4, in je po zmogljivosti podatkov, na primer, če je izkoristil ranljivost vbrizgavanja SQL podoben bolj priljubljenemu SHA-1. ali pridobil varnostno kopijo baze podatkov. Whirlpool je kriptografska zgoščevalna funkcija, ki temelji Ena od strategij zgoščevanja je zgoščevanje gesel z uporabo na bistveno spremenjeni različici naprednega standarda šifriranja algoritma za zgoščevanje gesel, ki se mu doda HMAC ali (AES). To je funkcija razprševanja blok šifre, ki je zasnovana po šifriranje zgoščenih vrednosti s simetričnim šifrirnim ključem, kvadratni blok šifri. Vnese manj kot 2256 bitne dolžine in jo preden se zgoščena vrednost gesla shrani v bazo podatkov, pri pretvori v 512-bitno razpršitev (64 bajtov). čemer ključ deluje kot poper. Strategije popranja ne vplivajo na Bcrypt je algoritem, zasnovan za shranjevanje gesel z funkcijo zgoščevanja gesel. Za razliko od soli, pri popranju geslo enosmerno funkcijo zgoščevanja, ki se je izkazal za zanesljivega ne sme biti shranjeno v bazi podatkov, temveč ga je potrebno in varnega. Ta funkcija zgoščevanja gesel je bila zgrajena za hraniti v "skrivnih trezorjih" ali HSM-jih (Hardware Security upočasnitev napadov s surovo silo. Sol je vključena v postopek Modules). zgoščevanja, ki ščiti shranjene zgoščene vrednosti pred napadi z mavričnimi tabelami. Pogost primer uporabe je pretvorba gesla v n-bitni kriptografski ključ, ki se nato lahko uporabi za varno 3 ALGORITMI ZGOŠČEVANJA preverjanje pristnosti. Bcrypt zagotavlja zelo omejeno varnost in Pomembna naloga algoritmov zgoščevanja je preverjanje njegove slabosti so v veliki meri odpravljene z algoritmom za celovitosti sporočila. S primerjavo povzetkov sporočil shranjevanje Scrypt [6][11]. izračunanih pred in po prenosu lahko ugotovimo, ali so bile v Scrypt je počasna funkcija, zasnovana za ustvarjanje močnih sporočilu narejene kakršne koli spremembe. Glavna razlika med kriptografskih ključev, npr. zasebnega ključa iz gesla, kjer je algoritmi zgoščevanja je zgoščena vrednost, ki jo ustvari vsak novi zasebni ključ daljši in varnejši. Zanaša se na visoke zahteve algoritem. Varnostne lastnosti nekaterih najbolj pogosto glede pomnilnika in ne na visoke zahteve glede procesorske moči. rabljenih algoritmov so opisane v nadaljevanju. Scrypt je boljši od Bcrypt in ima široko uporabo z MD5 je peta različica algoritma preusmeritve sporočil za implementacijo tehnologij GPU, ASIC in FGPA. Od pojava izdelavo 128-bitnega povzetka sporočila. Je precej hitrejši kot algoritma Scrypt uporabljajo številne kriptovalute za druge različice povzetka sporočil MD. Na podlagi varnostnih implementacijo znotraj svojih protokolov. Scrypt nedvomno izboljša slabosti Bcrypta, vendar zaščita, ki jo zagotavlja, še 500 zdaleč ni popolna. Vrzeli Bcrypt in Scrypt so privedle do razvoja Glavne varnostne funkcije, ki so zdaj nepogrešljive za algoritmov za shranjevanje Argon2 [7]. najsodobnejši način zgoščevanja gesla, vključujejo odpornost Argon2 je sodoben kriptografski algoritem, ki je namenjen proti trkom, odpornost na podaljšanje dolžine in naključni izhod. šifriranju gesel in omogoča varno shranjevanje vnosov. Velja za MD5 in SHA sta izjemno hitra, ko gre za izračun podatkov, enega najbolj varnih in ga priporoča Open Web Application vendar to ni nujno dobro za shranjevanje gesel. Hitrejše Security Project (OWASP). Zagotavlja visoko raven obrambe računalništvo olajša prevlado napadov s surovo silo. MD5 in pred napadi, ki temeljijo na GPU, napade stranskega kanala ali SHA ne omogočata obvezne soli kot dodatne zaščite za celo oboje. Šteje se za izboljšavo algoritmov Bcrypt in Scrypt. shranjevanje zgoščenih gesel. Argon2 je optimiziran za arhitekturo x86 ter izkorišča Bcrypt za razliko od MD5 in SHA vključuje dodatno zaščito, predpomnilnik in pomnilniško organizacijo novejših procesorjev ki onemogoča prevlado napadov s surovo silo. Bcrypt se pogosto Intel in AMD. imenuje CPU algoritem, kar pomeni, da izračun ene zgoščene Za ustvarjanje gesel Argon2 uporablja tri parametre: čas, vrednosti v sistemu Bcrypt zahteva več ciklov procesorja. Za pomnilnik in niti. Vsakega od njih je mogoče prilagoditi glede na razliko od MD5 in SHA, Bcrypt poveča težavnost in potrebe in strojne vire, vendar se morajo vrednosti prilagoditi neprepustnost vstopa v sistem s surovo silo. Bcrypt omogoča tudi glede na zmogljivosti strežnika [8]. načrtovanje številnih iteracij z uporabo posebnih dejavnikov dela, Argon2i je učinkovit pri zaščiti pred napadi stranskih ki upočasnjujejo hitrost računanja. Je tudi zahteven za hekerje, kanalov, Argon2d uporablja dostop do pomnilnika, ki je odvisen saj morajo uporabiti zelo drago opremo in porabiti ogromno časa od podatkov, zaradi česar je primeren za kriptovalute in za vdor v sisteme Bcrypt. aplikacije varne pred grožnjami. Argon2i uporablja izoliran RIPEMD-160 je trenutno najbolj varen in temelji na dostop do pomnilnika, ki je najboljši za shranjevanje gesel. konstrukciji Merkle–Damgård. Je okrepljena različica algoritma Hibridna različica združuje prednosti 2i in 2d, da zagotovi RIPEMD, ki proizvede 128-bitni razpršeni rezultat, medtem ko popolno varnost. Argon2id deluje kot 2i vsaj 50 odstotkov prve algoritem RIPEMD-160 ustvari 160-bitni izhod (20 bajtov). Do iteracije v pomnilniku in kot 2d za preostale operacije [8]. sedaj še niso zabeležili vdora v RIPEMD-160. BLAKE2 se tako kot BLAKE opira na algoritem ChaCha in SCrypt je boljša izbira kot BCrypt, saj je bolje zasnovan je določen v RFC 7693. BLAKE2 je na voljo v sledečih zlasti v smislu pomnilnika. različicah: BLAKE2b, BLAKE2 in BLAKE2x [3]. Strinjamo se z mnenjem avtorjev [5], da je velika prednost BLAKE3 je kriptografska zgoščevalna funkcija, ki temelji na Argona2 možnost izbire med načini zaščite. Drugi algoritmi Bao in BLAKE2. BLAKE3 je algoritem z veliko zaželenimi nimajo te prilagodljivosti. lastnostmi (vzporednost, XOF, KDF, PRF in MAC). Število Bcrypt uporablja sol in je dražji kot Argon2 ter za ustvarjanje krogov zmanjša z 10 na 7. Poleg tega lahko BLAKE3 učinkovito zgoščene vrednosti porabi več časa. Edina pomanjkljivost izkorišča večjedrne arhitekture in večnitnost, kar mu zagotavlja uporabe Bcrypt je, da je občutljiv za napade stranskih kanalov odlično razširljivost [4]. [11]. KangarooTwelve omogoča vzporedno zgoščevanje velikih Bcrypt pa ne priporočamo za nove modele, kjer je vhodna datotek. Ima vgrajen vzporedni način, ki učinkovito izkorišča vrednost žeton, ki ga ustvari človek (npr. geslo) in je v modelu vzporednost ukazov pri več jedrih ali SIMD za dolga sporočila, groženj brez povezave, ker ima pomanjkanje pomnilniške ne da bi to vplivalo na zmogljivost kratkih sporočil. Zahteva trdnosti. manj računskega napora, medtem ko še vedno nudi udobno Scrypt je podoben Argonu 2 na način, da za računanje varnostno rezervo. Splošna varnost KangarooTwelve je potrebuje čas, pomnilnik in niti. Prav tako zahteva veliko več zagotovljena z uporabo kodiranja Sakura za zgoščevanje drevesa pomnilnika v primerjavi z Bcrypt. Izhodni hash, ki ga uporablja [2]. scrypt, je vedno edinstven. Razbiti ga z uporabo surove sile bi PBKDF2 (Password-Based Key Derivation Function 2) je bilo veliko težje kot razbiti geslo Bcrypt [11]. preprosta funkcija izpeljave kriptografskih ključev, ki je odporna Priporočamo Scrypt, kjer je to najpreprostejša možnost za na slovarske napade in napade mavrične tabele. Temelji na shranjevanje gesel v jeziku ali ogrodju, ki ga uporabljamo, na večkratni ponovitvi izpeljave HMAC. PBKDF2 preprečuje, da bi primer, če je že vgrajena možnost za zaščito uporabniških gesel. orodja za razbijanje gesel optimalno uporabljala grafične Bilo je kar nekaj dokumentov, ki so preučevali varnostne procesne enote (GPU), s čimer zmanjša hitrost ugibanj s sto tisoč dokaze Argona2, veliko več pa je preučevalo možne načine za ugibanj na sekundo na manj kot nekaj deset tisoč ugibanj na pospešitev algoritma na namenski strojni opremi. Doslej je zelo sekundo [9]. dobro prestal nadzor. Argon2i ni ranljiv za napade stranskega kanala, v nasprotnem primeru pa Argon2d je ranljiv za časovne napade. 4 PRIMERJALNA ANALIZA Lahko uporabimo hibridni pristop Argon2id, da dobimo Predpostavljamo, da bo potreben kateri koli način zgoščevanja najboljše iz obeh algoritmov. Priporočamo, da v prihodnje ne gesla v prihodnosti nadgraditi. Zagotoviti je potrebno, da bo uporabljate PBKDF2 ali BCrypt in zato Argon2 priporočamo (po nadgradnja algoritma zgoščevanja čim enostavnejša. Za možnosti Argon2id) za novejše sisteme. Scrypt je lahko druga prehodno obdobje je potrebno omogočiti kombinacijo starih in izbira v sistemih, kjer ima Argon2 določene pomankljivosti [8]. novih algoritmov zgoščevanja. Uporaba mešanice algoritmov Argon2 je zgrajen okoli šifre AES, večina sodobnih zgoščevanja je lažja, če sta algoritem za zgoščevanje gesel in procesorjev x86_64 in ARMv8 pa izvaja razširitev niza navodil delovni faktor shranjena z geslom v standardni obliki, na primer AES. To pomaga zapolniti vrzel v zmogljivosti med predvidenim modularni format niza PHC. sistemom in namenskim sistemom za razbijanje. Novejše 501 različice Argona2 morda niso združljive z implementacijo AES BLAKE3 in Argon2 primerni, medtem ko MD5, SHA1, v razširitvah strojne opreme. PBKDF2 in SHA256 niso preveč primerni za shranjevanje gesel. Argon2 je še posebej odporen na napade kompromisov, ki presegajo pomnilniški delež ene tretjine, zaradi česar je veliko težje pospešiti na FPGA. To je zato, ker so rešitve za razbijanje, Tabela 2: Primerjava zgoščevalnih algoritmov ki temeljijo na FPGA, večinoma omejene s pasovno širino pomnilnika, z zasnovo Argon2 pa mora napadalec porabiti veliko Število Število Število Število računskega časa, da zmanjša zahteve glede pasovne širine Algoritem Leto besed blokov izhodov krogov pomnilnika, zaradi česar je kompromis neučinkovit. Parametre ARGON2 2015 512 8192 1024 12 trdote pomnilnika in trdote procesorja je mogoče konfigurirati bcrypt 1999 184 96 128 16 ločeno, skupaj s faktorjem vzporednosti. To vam omogoča, da 224/256/38 BLAKE2 2012 32/64 1024 10/12 4/512 bolje prilagodite varnost, vezano na primer uporabe, kot je BLAKE3 2020 32 512 neomejeno 7 strežnik z zmerno močjo procesorja in veliko količino RAM-a. Kangaroo PBKDF2 obstaja že dolgo časa in ni varen za uporabo: 2016 512 neomejeno 12 Twelve 8192 enostavno vzporeden na večjedrnih sistemih (GPE) in trivialen MD4 1990 32 512 128 48 za prilagojene sisteme (FPGA/ASIC) [8]. MD5 1992 32 512 128 64 V primerjavi s PBKDF2 in Bcrypt je Scrypt najbolj odporen RIPEMD 1992 32 512 128 48 na ranljivosti, povezane s pomnilnikom [8] RIPEMD-160 1996 32 512 160 80 RIPEMD-320 1996 32 512 320 80 Scrypt obstaja že dlje, kar mu daje večjo izpostavljenost in SHA0 1993 32 512 160 80 več časa za odpravo morebitnih hroščev ali zapletov. Poleg tega SHA1 1995 40 512 160 80 teoretični rezultati o trdoti pomnilnika kažejo, da je Scrypt dobro 234/256/38 SHA2 2002 32/64 512/1024 64/80 zasnovan in zmanjšuje možnost katastrofalne okvare. Po drugi 4/512 strani pa ima Scrypt dve veliki slabosti. Algoritem je odvisen od 1152/1088/ 224/256/38 SHA3 2015 64 24 podatkov, kar pomeni, da obstaja možnost napada na stranskem 832/576 4/512 kanalu. Whirlpool 2004 8 512 512 10 V tem trenutku je SHA-2 standard za algoritme za razpršitev, čeprav bi bil lahko SHA-3. SHA-3 je na programski strani 5 ZAKLJUČEK počasnejši, vendar je na strani strojne opreme vedno hitrejši od SHA-1 in SHA-2. Iz teh razlogov bodo organizacije prešle na Članek ponuja obsežen pregled kriptografskih zgoščevalnih SHA-3, ko bo SHA-2 postal nevaren ali zastarel. protokolov. Zgoščevanje je bistveno orodje za računalniško BLAKE2 je kriptografska zgoščevalna funkcija, hitrejša kot varnost. Pomaga varovati podatke in ponuja pregled pri MD5, SHA-1, SHA-2 in SHA-3, vendar je vsaj tako varna kot spreminjanju datotek in podatkov. Poleg tega njegove edinstvene standardni SHA-3. Zaradi visoke hitrosti, varnosti in preprostosti lastnosti preprečujejo napadalcem, da bi izkoristili obratno so BLAKE2 sprejeli številni uporabniki. inženirstvo za ogledovanje navadnega besedila ali izvirnih BLAKE3 je zasnovan tako, da je veliko hitrejši kot MD5, vhodnih podatkov. V kombinaciji z drugimi kriptografskimi SHA-1, SHA-2, SHA-3 in BLAKE2 ter varnejši od MD5 in orodji, kot je šifriranje, funkcija zgoščevanja podpira SHA-1; avtorji trdijo, da je 128-bitno varen za vse varnostne cilje. avtentikacijo, nezavrnitev podpisnika in celovitost podatkov pri To pomeni, da je BLAKE3 enako varen kot SHA3-256 in druge uporabi digitalnih podpisov [10]. zgoščene vrednosti, ki ciljajo tudi na 128-bitno varnost. Eden od Zgoščevanje je zelo koristno kriptografsko orodje za avtorjev BLAKE3 Jean-Philippe Aumasson trdi, da veliko preverjanje digitalnih podpisov, celovitosti datotek ali podatkov, simetričnih kriptografskih algoritmov uporablja preveč krogov in gesel v informacijski tehnologiji. Kriptografske zgoščevalne bi jih bilo mogoče narediti hitrejše z manj krogi, ne da bi to funkcije se razlikujejo glede na funkcionalnosti in aplikacije za vplivalo na njihovo varnost. posebne namene. Velik del uporabe zgoščevanja vključuje Upoštevati je potrebno, da čeprav BLAKE3 močno prekaša razumevanje, katere algoritme zgoščevanja uporabiti (ali se jim druge zgoščene vrednosti, kot sta BLAKE2 in SHA-2/3, to ni izogniti) v določenih kontekstih [7]. edina kriptografska funkcija, ki zagotavlja takšno raven Čeprav niso popolne, kriptografske zgoščevalne funkcije zmogljivosti. KangarooTwelve doseže približno enako služijo kot odlične kontrolne vsote in mehanizmi za preverjanje prepustnost kot BLAKE3. KangarooTwelve je hitra in varna pristnosti. Kot metodo za varno shranjevanje gesel (če je zgoščevalna funkcija, izpeljana iz Keccaka in je namenjena uporabljena tehnika soljenja) na način, ki je preveč nepraktičen, višjim hitrostim kot funkcije SHA-3, hkrati pa ohranja svojo da bi jih kibernetski kriminalci poskušali spremeniti v nekaj prilagodljivost in osnovo za varnost. Ima 12 krogov namesto 24 uporabnega [6][7]. in zmogljivost 256 bitov. Tabela 1 ponuja primerjavo tu Namen članka je bil olajšati uporabniku izbiro najvarnejših analiziranih algoritmov glede na število besed, število blokov, algoritmov za svoje potrebe. Zato smo na tem mestu opisali, izhodov in število krogov. primerjali in povzeli najnovejše kriptografske algoritme. Bistvenega pomena pri shranjevanju gesel je način, ki Ugotovili smo, da so KangarooTwelve, Scrypt, Bcrypt, preprečuje, da bi gesla napadalec pridobil, tudi če je aplikacija BLAKE3 in Argon2 primerni, medtem ko MD5, SHA1, ali zbirka podatkov ogrožena. Poskušali smo analizirati in PBKDF2 in SHA256 niso preveč primerni za shranjevanje gesel. povzeti najnovejše kriptografske algoritme in se strinjamo z Upamo, da bodo te ugotovitve bralcem v pomoč. nekaterimi avtorji [5], da so KangarooTwelve, Scrypt, Bcrypt, 502 LITERATURA IN VIRI [7] Houston K.: Password hashing methods: PBKDF2, Scrypt, Bcrypt and ARGON2, 2021, Dostopno na naslovu: https://www-mo4tech- [1] Azad U:, Cryptographic Hash Functions, 2021, Dostopno na naslovu: com.translate.goog/password-hashing-methods-pbkdf2-scrypt-bcrypt-and- https://linuxhint.com/cryptographic-hash-functions/ (22. 7. 2022) argon2.html?_x_tr_sl=en&_x_tr_tl=sl&_x_tr_hl=sl&_x_tr_pto=op,sc (8. 7. [2] Bertoni G., Daemen J.: KangarooTwelve: fast hashing based on Keccak-p, 2022) 2022, Dostopno na naslovu: [8] Mehta, P.: What Is a Hash Function Within Cryptography, 2022, Dostopno https://repository.ubn.ru.nl/bitstream/handle/2066/195384/3/195384.pdf na naslovu: https://securityboulevard.com/2022/06/what-is-a-hash-function- (11. 7. 2022) within-cryptography-quick-guide/ (15. 7. 2022) [3] BLAKE2, Fast secure hashing, 2017, Dostopno na naslovu: [9] Owasp: PBKDF2, 2021, Dostopno na naslovu: https://www.blake2.net/#co (11. 7. 2022) https://cheatsheetseries.owasp.org/cheatsheets/Password_Storage_Cheat_Sh [4] De Simone S.: BLAKE3 Is an Extremely Fast, Parallel Cryptographic Hash, eet.html#pbkdf2 (8. 7. 2022) 2020, Dostopno na naslovu: https://www.infoq.com/news/2020/01/blake3- [10] Szostak, M.; How to improve user password security with Argon2? 2022, fast-crypto-hash/ (11. 7. 2022) Dostopno na naslovu: https://www.boldare.com/blog/how-to-improve-user- [5] Fromaget P: What’s The Best Algorithm For User Credential Storage In password-security-with-argon2/ (8. 7. 2022) 2022? 2022, Dostopno na naslovu: https://infosecscout.com/best-algorithm- [11] Wagner, L: Bcrypt Step by Step, 2020, Dostopno na naslovu: password-storage/ (20. 7. 2022) https://blog.boot.dev/cryptography/bcrypt-step-by-step/ (8. 7. 2022) [6] Preziuso M.: Password Hashing: Scrypt, Bcrypt and ARGON2, 2019, Dostopno na naslovu: https://medium.com/analytics-vidhya/password- hashing-pbkdf2-scrypt-bcrypt-and-argon2-e25aaf41598e (8. 7. 2022) 503 Finančno opismenjevanje v osnovni šoli Financial Literacy in Primary School Sonja Strgar OŠ Antona Martina Slomška Vrhnika Vrhnika, Slovenija sonja.strgar@guest.arnes.si POVZETEK KEYWORDS V prispevku je predstavljen primer dobre prakse finančnega Financial literacy, primary school, money quiz, European Money opismenjevanja na Osnovni šoli Antona Martina Slomška Week Vrhnika, ki poteka od 6. do 9. razreda pri pouku matematike in interesni dejavnosti Finančno opismenjevanje mladih. V okviru pouka matematike potekajo predstavitve, kjer učenci 1 UVOD predstavljajo teme s področja financ. Izbirajo lahko med temami, Evropska komisija si je za eno izmed pomembnih prioritet ki jih ponudi učitelj ali pa si izberejo svojo. Pri interesni postavila finančno opismenjevanje državljanov članic Evropske dejavnosti Finančno opismenjevanje mladih se celo šolsko leto unije [1]. Finančna pismenost je v državah Evropske unije in pripravljamo na Nacionalni in evropski denarni kviz, ki se vsako ostalih državah sveta priznana kot pomemben element leto izvede v mesecu marcu. Za potrebe kviza obravnavamo gospodarske in finančne stabilnosti ter razvoja. finančne pojme, tveganja, Evropsko unijo, denar, matematiko v V svetu in pri nas se v današnjih časih veča potreba po financah in digitalno varnost. Zagotovo je za mlade zelo izobraževanju potrošnikov. Ti se v spremenjenih razmerah vse pomembno, da se izobražujejo tudi na področju financ, saj se teže premišljeno odločajo. Še posebej to velja za področje bodo tako kot potrošniki bolj premišljeno odločali. Finančna finančnih storitev, ki je zaradi hitrega razvoja in pojavljanja pismenost v osnovni šoli je na zelo nizki ravni, zato bi morali v vedno novih proizvodov izredno zapleteno. Potrošniki tako učne načrte vključiti več vsebin s področja financ. potrebujejo nekatere veščine, znanja in strategije, ki jim olajšajo vsakdanje odločanje [2]. KLJUČNE BESEDE Finančna pismenost, osnovna šola, denarni kviz, Evropski teden denarja 2 FINANČNO OPISMENJEVANJE MLADIH Finančna pismenost je zmožnost posameznika, da na osnovi ABSTRACT finančnega znanja uporablja finančne pojme in postopke v The article presents an example of good financial literacy različnih življenjskih situacijah; analizira, utemeljuje, vrednoti in practice at the Elementary School, Antona Martina Slomška učinkovito sporoča svoje zamisli in rezultate pri oblikovanju, Vrhnika which takes place from the 6th to the 9th grade during reševanju in interpretaciji finančnih problemov v različnih mathematics lessons and Financial Literacy of Youth Club. življenjskih situacijah; sprejema odgovorne/utemeljene Presentations are held as part of mathematics lessons, where odločitve s prepoznavanjem razlik med željami, zmožnostmi in students present topics from the field of finance. They can choose dejanskimi potrebami; pridobi zavedanje o vlogi finančnih from the topics offered by the teacher or they can choose their veščin in pomenu ustreznega izobraževanja na tem področju za own. In the Financial Literacy of Youth Club we prepare for the kakovostno vsakdanje in poklicno življenje [2]. whole school year for the National and European financial quiz, Skoraj vsaka naša odločitev ima finančne posledice. Zelo which is held every year in the month of March. For the purposes pomembno je, da znamo racionalizirati naše finance, saj ima of the quiz, we cover financial concepts, risks, the European večina ljudi večje potrebe kot denarja na razpolago. Union, money, mathematics in finance and digital security. It is Finančno pismen posameznik ima pozitiven vpliv na družbo certainly very important for young people to be educated in the in če znamo upravljati s svojim premoženjem imamo field of finance as well, as they, like consumers, will make more zagotovljeno zadovoljno življenje. informed decisions. Financial literacy in primary school is at a Slabosti finančne nepismenosti so kupovanje neprimernih very low level, so more financial content should be included in finančnih produktov, slabo razpršen denar, vlagatelji slabo the curriculum. poznajo zakonitosti varčevanja v delnicah, ljudje ne opravijo skrbnega pregleda naložbe pred vlaganjem, posamezniki imajo Permission to make digital or hard copies of part or all of this work for personal or hudo nerealna pričakovanja, možnost finančnih piramid in prevar, 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 poveča se stopnja zadolževanja in poslabša kvaliteta življenja. citation on the first page. Copyrights for third-party components of this work must Finančno znanje in razumevanje, veščine in sposobnosti ter be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia odgovornost so brez pomena, če jih posameznik ne zna © 2022 Copyright held by the owner/author(s). uporabljati v praksi, zato imajo vzgojno-izobraževalne ustanove 504 pomembno vlogo in nalogo na področju finančnega izobraževanja in finančne pismenosti [2]. 3 OPIS DELA IN REZULTATI 3.1 Gradiva za učitelje V nadaljevanju je prikazanih nekaj gradiv, kjer se učitelj lahko izobražuje na temo finančne pismenosti. ZBS – Združenje bank Slovenije ima odlično spletno stran, ki je dostopna na https://www.zbs-giz.si/financno- opismenjevanje/. Spletna stran ima 3 zavihke (slika 1): Programi Slika 3: Spletna stran projekta FINLIT za OŠ, SŠ in odrasle, Nacionalni in evropski denarni kviz in Evropski teden denarja. Njihova gradiva uporabljamo pri ZRSŠ in projekt NA-MA – Del projekta NA-MA je tudi interesni dejavnosti Finančno opismenjevanje mladih za pripravo finančna pismenost. ZRSŠ je naredil gradivo, v katerem finančno na Nacionalni in evropski denarni kviz. pismenost opredeli in našteje gradnike. Publikacija je dostopna https://www.zrss.si/pdf/Financna_pismenost_gradniki.pdf. Prav tako se vsako leto pridružijo projektu Global Money Week (GMW), kjer lahko sodelujejo tudi šole, ki se prijavijo. Več o projektu dostopno na https://www.zrss.si/novice/o-financni- pismenosti-ki-jo-mladi-potrebujejo-za-uspesno-zivljenje/. Projekt GMW ima tudi spletno učilnico, do katere dostopamo na https://skupnost.sio.si/course/view.php?id=10988. Za vstop v spletno učilnico sta potrebni AAI prijava in geslo. (slika 4). Slika 1: Spletna stran ZBS Tukaj najdemo odlična gradiva, ki jih lahko uporabimo v Svetovnem tednu izobraževanja o financah. Moje finance – ponujajo izobraževanje za učitelje, na katerega se prijavimo kar preko KATIS-a (slika 2). Seminar se imenuje Finančno izobraževanje učiteljev za mentorje finančnega opismenjevanja mladih. Seminar je plačljiv in v obsegu 20 ur. Na seminarju učitelj dobi dva priročnika za poučevanje, ki sta polna dobrih primerov in napisana kot priprava na učne ure. Stara spletna stran, kjer si lahko ogledate priročnika, je dostopna na naslovu https://mojefinance.finance.si/mf-narocam, nova spletna stran pa na naslovu https://www.financna-sola.si/. Oblikovali so Finančno šolo, kjer tudi najdemo koristne informacije za učitelje. Ponujajo tudi možnost sodelovanja šole v Tekmovanju iz finančne pismenosti. Slika 4: Spletna učilnica GMW Slika 2: Izobraževanje za učitelje BANKARIUM – muzej bančništva na Slovenskem. Učence lahko peljemo na ogled muzeja, kjer se skupaj sprehodimo skozi FINLIT – Finančno izobraževanje v splošnih knjižnicah. Cilj zgodovino bančništva in denarja. Poleg ogleda muzeja ponujajo projekta je zvišati stopnjo finančne pismenosti odraslih z novim tudi različne finančne igrice in finančni labirint. Več o muzeju pristopom preko številnih možnosti, ki jih nudijo splošne preberite na https://bankarium.si/. knjižnice kot neformalni izobraževalci, in preko ustanov za BANKA SLOVENIJE – Banka Slovenije ponuja vseživljenjsko izobraževanje. Za uporabo spletne strani se Izobraževalni dan, na katerem lahko izbiramo med več moduli in moramo prijaviti, nato pa lahko izbiramo med več moduli. Več o različnimi vsebinami. Več informacij na https://www.bsi.si/o- projektu dostopno na https://finlit.eu/edu/?lang=sl (slika 3). nas/izobrazevalni-dan. Mi smo Banko Slovenije že večkrat obiskali in bili zelo navdušeni nad delavnicami. 505 3.2 Predstavitve pri matematiki Učenec 9. razreda je predstavil Banko Slovenije. Najprej je banko opisal, nato je povedal njeno zgodovino, predstavil Muzej V začetku šolskega leta smo učencem 6. – 9. razreda pri Banke Slovenije in predstavil izobraževalne dneve, ki jih matematiki ponudili možnost, da izdelajo predstavitev na temo ponujajo (slika 7). finančne pismenosti. Skupaj smo določili kriterije za izdelavo predstavitve. Učiteljica je ponudila nekaj tem, učenci pa so lahko izbrali tudi svojo temo. Izdelava ni bila obvezna za vse učence. Prva predstavitev je bila raziskava o nakupu pametnega telefona. Učenki sta se spraševali pri katerem ponudniku telefonskih storitev najceneje kupiš nov telefon (Samsung Galaxy A22 5G) brez naročnine, kakšen je skupni strošek telefona in naročnine in v kateri spletni trgovini najceneje dobiš ta telefon brez vezave. Raziskali sta tudi prednosti in slabosti spletnega nakupovanja ter kaj pomeni zanesljiv ponudnik (slika 5). Učenki sta vse postavljene hipoteze zavrnili, saj sta v Slika 7: Predstavitev Banke Slovenije raziskavi prišli do ugotovitev, da je najcenejši ponudnik A1, skupaj z vezavo pa Telemach. Presenečeni sta bili tudi nad Poslušali smo tudi predstavitve o davkih. Učenci so raziskali izrazom »navidezni nakup«, saj sta prvič slišali zanj in ga ob kaj je davek, zgodovino davkov, katere vrste davkov poznamo in predstavitvi razložili. opisali posamezno vrsto davka. Razložili so, zakaj je pomembno, da plačujemo davke ter kaj se zgodi, če davkov ne plačamo. Pokazali so plačilno listo in jo razložili. Učenci so naredili tudi primerjavo plačevanja davkov po državah EU (slika 8). Učenci so izvedli anketo med sošolci in ugotovili, da velika večina sošolcev pravilno ve, da plačujemo davke, da je bruto plača višja od neto plače in da večina sošolcev napačno misli, da če davka ne plačaš, ga kasneje plačaš dvojno. Slika 5: Primer raziskave o nakupu pametnega telefona Učenci so raziskovali tudi, kako izbrati svoj sanjski poklic. To temo je izbralo več učencev. Zanimalo jih je, s čim si lahko pomagamo pri izbiri poklica, kateri so najbolj priljubljeni poklici, kakšna je razlika med bruto in neto plačo, kaj je poklic, kateri poklici izumirajo, katere poklice delodajalci najpogosteje iščejo, Slika 8: Predstavitev o davkih predstavili so kvize, ki pomagajo pri izbiri poklica ter predstavili nekaj poklicev. Naredili so tudi raziskavo med sošolci ter celo Raziskovali smo tudi poklice prihodnosti. Zanimalo nas je, odigrali predstavitev različnih poklicev (slika 6). kateri poklici so že izumrli, ali bo v prihodnosti več naravoslovnih ali družboslovnih poklicev, ali se bo v dvajsetih letih zmanjšalo število obrtniških del ter kateri zanimivo poklici bodo v prihodnosti pogostejši kot danes. Ugotovili smo, da se bodo pojavili nekateri poklici, ki jih danes sploh še ni na trgu (slika 9). Slika 6: Odigran prizor predstavitve poklica natakarja Slika 9: Predstavitev o prihodnosti poklicev 506 Učenki 6. razreda sta raziskali, kako s spletnim nakupom do V okviru interesne dejavnosti smo obiskali tudi Banko najcenejše Milka čokolade (slika 10). Zanimalo ju je, katera vrsta Slovenije, kjer smo poslušali zelo kvalitetna predavanja (slika Milka čokolade je najcenejša v spletnih trgovinah in kje 12). Izobraževanje poteka v prostorih Banke Slovenije na najceneje kupimo Milka čokolado skupaj s poštnino. Ob koncu Slovenski 35 v Ljubljani. Mi smo izbrali teme: Kaj je Banka predstavitve sta nas postregli s koščkom čokolade in tako Slovenije?, Kaj so plačila in kako potekajo? (celostna ponazoritev prenosa denarnih sredstev med dvema subjektoma) predstavitev še popestrili. Učenci so raziskovali še spletne in Gotovina (predstavitev aktivnosti pri izdajanju bankovcev in nakupe nekaterih drugih izdelkov, kot so športni copati in kovancev, količine denarja v obtoku, nadzora nad ponaredki ...). računalniška miška. Predavanja so bila zanimiva in poučna, denar v rokah pa mamljiv. Izvedeli smo veliko novega. V času korone pa smo Finančno uro v 8. razredu izvedli kar na daljavo preko okolja Zoom. Slika 10: Predstavitev spletnih nakupov 3.3 Interesna dejavnost Finančno opismenjevanje mladih Vsako šolsko leto razpišemo interesno dejavnost Finančno Slika 12: Obisk Banke Slovenije opismenjevanje mladih. Prijavijo se lahko učenci 8. in 9. razreda. V sklopu interesne dejavnosti se pripravljamo na Nacionalni in 4 ZAKLJUČEK evropski denarni kviz, ki ga organizira ZBS. Na interesni dejavnosti se dobimo vsak teden eno šolsko uro, pred kvizom pa Rezultati dodatnih preverjanj finančne pismenosti in večkrat po potrebi. Navadno se družimo v šoli, občasno tudi na reševanja problemsko zasnovanih situacij, ki so jih v Sloveniji Zoom urah. Na začetku šolskega leta naredimo uvod v finančno izvedli v okviru raziskave PISA 2012, kažejo šibkejše rezultate opismenjevanje, nato pa učenci na vsako uro prinesejo svoj slovenskih 15-letnikov od matematičnih in naravoslovnih pametni telefon, ki ga potrebujejo za pripravo na kviz. Učiteljica dosežkov, ki so jih predstavili decembra 2013 [3]. vsako šolsko uro projicira na tablo 2 – 3 kvize, ki jih učenci V raziskavi PISA je Slovenija sodelovala leta 2012, kasneje rešujejo preko telefona. Nato se o posameznih vprašanjih ne več. Vendar iz prakse ugotavljamo, da je finančno znanje pogovorimo. Vprašanja, ki jih rešujemo, so v sklopih: finančni učencev šibko. Po večini se mladi ne zavedajo, da bodo za svoje pojmi, tveganja, denar, digitalna varnost, Evropska unija in finance odgovorni sami. V naših šolah moramo večji poudarek matematika. Vprašanja so prosto dostopna na https://www.zbs- nameniti mladim, saj se samoiniciativno le redki izobražujejo o giz.si/financno-opismenjevanje/. Učenci na interesni dejavnosti financah. Poslanstvo izobraževalnega sistema pa mora biti tudi vsako leto zelo uživajo in se veliko novega naučijo. Marca se zagotavljanje kakovostne finančne izobrazbe posamezniku. Na potem šola prijavi na tekmovanje, kjer tekmuje vsak učenec sam. naši šoli bomo s finančnim izobraževanjem nadaljevali tudi v (slika 11). prihodnje in področje izobraževanja še razširili z obiskom različnih ustanov in predavatelji zunanjih inštitucij. LITERATURA IN VIRI [1] EPALE: Finančna pismenost. Dostopno na naslovu https://epale.ec.europa.eu/sl/taggar/financial-literacy (11.8.2022) [2] ZRSS: Spodbujanje razvoja pismenosti v vrtcu in šoli. Dostopno na naslovu https://www.zrss.si/pdf/Spodbujanje_razvoja_pismenosti.pdf (11.8.2022) [3] Pedagoški inštitut:Izhodišča merjenja finančne pismenosti v raziskavi PISA 2012 s primeri nalog. Dostopno na naslovu https://www.dlib.si/stream/URN:NBN:SI:DOC-XPSUSNHL/9e71ca13- b86e-4252-bce6-45d5b57e00df/PDF (11.8.2022) Slika 11: Nacionalni denarni kviz 507 Oglaševanje in izdelava oglasov na STŠ ŠC Kranj Advertising and Creating Advertisements at STŠ ŠC Kranj Gašper Strniša Iva Strniša ŠC Kranj GFP Kranj, Slovenija Kranj, Slovenija gasper.strnisa@sckr.si iva.strnisa@gfp.si POVZETEK samih, učiteljih, učencih, starših in institucijah, ki s šolami neposredno sodelujejo [1]. Izbira prave srednje šole in izobraževalnega programa je za Udeleženci izobraževalnega procesa so bili dokaj hitro posameznika zelo pomembna, vpis čim večjega števila dijakov primorani poglobiti nivo digitalne pismenosti ter usvojiti načine pa je zaradi financiranje srednjih šol iz javnega proračuna po izvedbe pouka na daljavo, ki se je preselil iz učilnic v virtualni sistemu MOFAS zelo pomemben tudi za šolo samo. Prav zaradi prostor. V virtualni prostor pa so se preselile tudi vse s poukom tega se srednje šole borijo za vpis vsakega dijaka. Šola potrebuje povezane aktivnosti, kot npr. roditeljski sestanki, govorilne ure, splošno prepoznavnost s pozitivno konotacijo, ki pa jo je v času izvedba informativnih dni, ipd. korona virusa težko izpostavila zaradi pomanjkanja različnih Srednješolsko izobraževanje je ena ključnih faz za razvoj dogodkov, ki bi jih bilo možno oglaševati in organizirati. Članek posameznika tako v privatnem kot tudi v njegovem poklicnem opisuje načine oglaševanja, ki ga je izvedla Srednja tehniška šola življenju, zato je prava izbira srednje šole in izobraževalnega iz Kranja in so se izkazali kot razlog za 9,56 % povečanje prejetih programa še kako pomembna. prijav v prvem vpisnem roku glede na preteklo leto in posledično skorajšnjo zapolnitev vseh razpisanih mest. 2 PREDSTAVITEV PROBLEMA KLJUČNE BESEDE Financiranje srednjih šol iz javnega proračuna po sistemu Oglaševanje, marketing, šola, vpis, plakat MOFAS, ki naj bi šolam omogočil predvsem učinkovitejšo ABSTRACT organizacijo pouka zaradi večje avtonomije pri porabi denarja, s tem pa tudi njihovo odgovornost za porabo denarja in uspešnost, Choosing the right secondary school and educational program is je pripeljalo do tega, da se srednje šole borijo za vpis vsakega very important for the individual, and the enrollment of as many dijaka. students as possible is also very important for the school itself Znano je dejstvo, da je najboljše priporočilo »od ust do ust«, due to the financing of secondary schools from the public budget zato je v prvi meri potrebno poskrbeti za kvalitetno izvedbo according to the MOFAS system. This is precisely why pouka, šolskih in obšolskih dejavnosti, dobre in korektne odnose, secondary schools strive to enroll every interested student. The oz. na splošno ugodno šolsko klimo. Vendar pa vse prej zapisano school needs general recognition with a positive connotation, but še ni dovolj. Potrebna je tudi splošna prepoznavnost, ki je during the corona virus it was difficult to highlight it due to the povezana s pozitivno konotacijo. lack of various events. The article describes the methods of Predvsem v času korona virusa oz. z njim povezanega zaprtja advertising carried out by the Secondary Technical School from javnega življenja, ko ni bilo organiziranih ekskurzij, športnih dni, Kranj, which proved to be the reason for the 9.56% increase in kulturnih dni, prireditev, tekmovanj, ipd., je bilo potrebno najti applications received in the first registration period compared to inovativne načine za predstavitev šole v raznih medijih, ki bi med the previous year. splošno javnostjo krepili pozitivno podobo šole, zainteresirano javnost pa nagovorili za obisk informativnega dne, ki po lastnih KEYWORDS raziskavah v veliki meri vpliva na končno odločitev za vpis na Advertising, marketing, school, enrollment, poster srednjo šolo. Kljub podobnosti pri načinih oglaševanja med različnimi šolami v npr. tiskanih medijih, radijskih objavah, televizijskih 1 UVOD objavah, plakatih, objavah na družbenih omrežjih ipd., pa je Na odpoved pouka, ki se je v preteklem letu zgodil zaradi vendar potrebno biti nekoliko drugačen. Ne želimo namreč biti pandemije korona virusa, marsikdo ni bil pripravljen. Tukaj eden izmed mnogih, pač pa pritegniti čim več pozornosti bodočih govorimo tako o krovnih šolskih organizacijah kot tudi o šolah 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 for profit or commercial advantage and that copies bear this notice and the full 3 MARKETING IN OGLAŠEVANJE citation on the first page. Copyrights for third-party components of this work must Marketing in oglaševanje sta tesno povezani dejavnosti, vendar be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia med njima obstajajo pomembne razlike. Oglaševanje je namreč © 2022 Copyright held by the owner/author(s). le del marketinške celote, ki se neposredno nanaša na 508 predstavitev organizacije. Razumevanje razlik med pojmoma pa naknadno uporabi tudi kot digitalne oglase v spletnih medijih in lahko v veliki meri pomaga pri oblikovanju in izvedbi strategije na družabnih omrežjih. za dosego zadanih ciljev. Pri predstavitvenem filmu smo kot inovativnost oz. O marketinškem ravnanju šol lahko govorimo, ko v šoli in drugačnost od ostalih ravnatelja pretvorili v hologram. Na takšen zunaj nje potekajo dejavnosti, ki ji prinašajo konkurenčno način je predstavil šolo ter šolske in obšolske dejavnosti. Slika 2 prednost na trgu izobraževalnih storitev in so »raziskovalni prikazuje ravnatelja kot hologram v predstavitvenem videu. element« do konkurenčnih šol. Marketing in marketinške dejavnosti v šoli se kažejo pretežno v [2]: • pridobivanju učencev oziroma dijakov, • približevanju dnevnih dejavnosti šole potrebam zunanjih odjemalcev in drugih sekundarnih uporabnikov, • komercializmu v šolah. Pojem oglaševanje bi lahko pojasnili tako, da bi rekli, da gre za plačano obliko komuniciranja znanega naročnika, ki uporabi različne medije, preko katerih želi vplivati na javnost. Ker gre za masovno komuniciranje, je oglaševanje neosebne narave [3]. Oglaševanje je zelo kompleksno, saj morajo oglaševalci doseči različne tipe ljudi. Nastanek enega oglasa zahteva ljudi z znanjem s področja ekonomije, oblikovanja, fotografije, filma, psihologije, jezikoslovja, umetnosti, kulture, računalništva... [4]. Slika 2: Ravnatelj kot hologram Plakate, ki smo jih izobesili po osnovnih šolah, krasijo 4 IZDELAVA OGLASOV fotografije najbolj tipičnih elementov posameznih smeri. Na vsaki sliki smo izkoristili učinke zunanjih dejavnikov pozornosti, Če smo se v preteklem letu lahko izgovarjali da nas je situacija z npr. rdečo barvo, ki še posebej pritegne pozornost. Okvirji slik in zaprtjem šol presenetila, pa tega ne moremo reči tudi za letošnje povezave med njimi predstavljajo elektronsko vezje, vse skupaj šolsko leto, saj smo lahko pričakovali dokaj podoben scenarij. pa predstavlja tudi črko »E«, ki neposredno predstavlja sodobno Devetošolcem, ki se vpisujejo v srednjo šolo, in njihovim tehnologijo. Slika 3 prikazuje izdelan plakat manjšega formata. staršem, ki v veliki meri vplivajo na njihovo odločitev o izbiri nadaljnjega šolanja, je torej potrebno kvalitetno predstaviti šolo in izobraževalne programe, za kar so dandanes potrebni inovativni pristopi. Na Srednji tehniški šoli (v nadaljevanju STŠ) Šolskega centra Kranj smo se resno lotili oglaševalske kompanije, ki bi bila prilagojena tudi izvedbi informativnih dni na daljavo. Začelo se je s sestavo ekipe, ki je najprej izvedla viharjenje idej v povezavi z našo šolo. Tukaj smo želeli ugotoviti najbolj značilne elemente, ki bi jih vključili v oglaševane izdelke. Začetno viharjenje idej v obliki razvejanega miselnega vzorca omogoča iskanje in odkrivanje novih poti v prvih fazah oblikovalskega procesa [5]. Slika 1 prikazuje miselni vzorec viharjenja idej, ki smo ga narisali. Slika 1: Miselni vzorec viharjenja idej Sledila je opredelitev oglasnih medijev. Odločili smo se za izdelavo predstavitvenega filma, plakatov manjšega formata in Slika 3: Plakat manjšega formata plakata velikega formata. Vse izmed naštetih oglasov se lahko 509 Za plakat večjega formata, ki je prikazan na sliki 4, smo 6 ZAKLJUČEK izdelali novo grafiko, saj zanj veljajo posebna pravila, tako kar Prav zaradi vse večje ponudbe in konkurence na trgu se tiče velikosti kot tudi dejavnikov pozornosti. izobraževanja se izobraževalne organizacije poslužujejo marketinga. Zavedajo se, da mora marketinški pristop temeljiti na potencialnih uporabnikih in njihovi odprti komunikaciji z morebitnim bodočim uporabnikom. Bistvenega pomena je, da ta komunikacija poteka tudi kasneje, ko so uporabniki že del te izobraževalne organizacije. Če želi šola pritegniti pozornost potencialnih uporabnikov, dobro predstaviti prednosti in koristi, ki jih bodo imeli uporabniki, če se vpišejo v določeno šolo, je pomembna učinkovita in uspešna promocija šole [2]. Izbira izobraževanja ni lahka, saj na trgu izobraževanja obstaja ogromno inštitucij in organizacij s takšnimi in drugačnimi izobraževalnimi programi, vse pa zagotavljajo, da je njihova institucija najboljša in da bomo z njihovo pomočjo dobili najboljše znanje za vse življenje. Na izbiro izobraževanja lahko vplivata starost otroka in omejitev vpisa. Vsekakor velja, da nižja kot je starost otrok, pomembnejši so starši. Oni so tisti, ki izberejo vrtec in osnovno šolo. Izbira srednje šole in fakultete pa Slika 4: Plakat večjega formata je v večji meri odločitev učencev/dijakov, ima pa v tem primeru omejitev vpisa večji vpliv na izbiro institucije oz. Podjetja imajo na razpolago ogromno kanalov preko katerih izobraževalnega programa [2]. lahko oglašujejo: bodisi tradicionalni mediji ali pa kakšne Na Srednji tehniški šoli Šolskega centra Kranj smo v šolskem novejše oblike oglaševanja, ki so v zadnjih letih močno porasle letu 2022/23 na kar štirih od šestih programov (razvidno iz tabele [4]. Z namenom, da bi oglasno sporočilo doseglo čim več 2) presegli omejitev vpisa. To na kratki rok pomeni, da bomo potencialnih dijakov, smo ga objavili tudi v digitalni obliki na verjetno dobili dijake z boljšim učnim uspehom, na dolgi rok pa, spletni strani in na družabnih omrežjih. da bomo v prihodnjem letu morali še dodatno iskati inovativne načine oglaševanja naših izobraževalnih programov. 5 PREDSTAVITEV REZULTATOV Tabela 2: Razpisana mesta in število vpisanih dijakov v Merjenje rezultatov oglaševanja pri ne-spletnem oglaševanju je šolskem letu 2022/23 izredno zahtevno, zato si je pred začetkom oglaševanja najprej potrebno določiti specifične in merljive cilje. V našem primeru smo si zastavili cilj, da presežemo število pridobljenih prijav na našo šolo v primerjavi s preteklim šolskim letom v prvem vpisnem roku. Tabela 1 prikazuje podatke pridobljenih prijav v vse programe na katerih smo imeli razpisana mesta, na dan 4. april v letih 2021 in 2022. Tabela 1: Pridobljene prijave v letih 2021 in 2022 LITERATURA IN VIRI [1] G. Strniša in drugi, “Discord kot platforma za izvedbo pouka na daljavo”, Vzgoja in izobraževanje v informacijski družbi – Zbornik 24. mednarodne multikonference. Uredila: U. Rajkovič in B. Batagelj, Ljubljana, 8. oktober 2021. Institut “Jožef Stefan”, Ljubljana. [2] K. Pavec, “Vpliv informativnih dni na odločitev dijakov za nadaljevanje študija”, diplomsko delo, Univerza v Mariboru, Fakulteta za organizacijske vede, Kranj, 2011. [3] W. Wells, “Advertising, principles and practices. Engelwoods Cliffs: Prentice Hall, 1996. [4] M. Krmelj, “Prikrito oglaševanje”, magistrsko delo, Univerza v Mariboru, Ekonomsko-poslovna fakulteta, Maribor, 2015. Iz tabele 1 je razvidno, da smo v letu 2022 prejeli kar 28 prijav [5] D. Dabner in drugi, “Grafično oblikovanje: Priročnik za grafične oblikovalce tiskanih, digitalnih in večpredstavnih medijev”, Tehniška založba Slovenije, oz. 9,56 % več kot v preteklem šolskem letu. Glede na podatke Ljubljana, 2011. Statističnega urada republike Slovenije, da se je v prve letnike srednjih šol vpisalo zgolj 6,42 % več dijakov kot v preteklem šolskem letu (ponavljalci so iz tega odstotka izvzeti), zato lahko zaključimo, da je bil naš cilj v veliki meri dosežen. 510 Učenje risanja in spoznavanje novega IKT orodja Learning To Draw and Getting To Know a New IKT Tool Tina Šebenik Župnijski vrtec Vrhnika Vrhnika, Slovenija malatiny@gmail.com POVZETEK ABSTRACT V prispevku je predstavljeno projektno delo učenje risanja in The paper presents project work on learning to draw and getting spoznavanje z novim računalniškim orodjem v vrtčevski skupini to know a new computer tool in a kindergarten group of five- petletnikov. Z otroki smo se pogovarjali o živalih (njihovem year-olds. We talked with the children about animals (their izgledu), si jih ogledali na spletu in se odločili, da lahko drugače, appearance), looked at them online and decided that we could na bolj zanimiv način s pomočjo računalnika te živali tudi draw these animals in a different, more interesting way with the narišemo. Navaden papir smo zamenjali z računalniškim help of the computer. We replaced ordinary paper with a programom. Na mizo smo postavili računalnik, se seznanili z computer program. We put the computer on the table, miško in odprli program za risanje (3D-slikar). familiarized ourselves with the mouse and opened the drawing Omenjeni didaktični pristop je otroke motiviral, bili so bolj program (3D painter). zbrani. Predstavljal jim je nov način učenja in je bil močno The mentioned didactic approach motivated the children, they motivacijsko sredstvo, ki ni potreboval dodatnih stimulacij za were more collected. It presented them with a new way of delo. Pokazali so izjemno vztrajnost. Zavzeto so vlekli različne learning and was a powerful motivational tool that did not need črte, krivulje in se trudili, da je njihova žival izgledala tako, kot additional stimulation to work. They showed remarkable tenacity. jo vidimo v vsakdanjem življenju. Spoznali so slikarska orodja They busily drew different lines, curves and tried to make their in se soočali z nagajivo miško. Rokovanje z njo ni bilo za vse animal look like we see it in everyday life. They learned about najbolj enostavno. Predstavljala jim je izziv. Imeli so nekaj težav painting tools and faced a mischievous mouse. Handling her was z vodenjem in s kliki. Dobro je bilo, ker so svoje umetnine lahko not the easiest for everyone. She presented them with a challenge. shranili in nadaljevali kasneje ali v naslednjih dneh. Pri They had some management and click issues. It was good dejavnosti so bili v ospredju otroci, ki so že imeli nekaj izkušenj because they could save their artwork and continue later or in the z informacijsko-komunikacijsko tehnologijo od doma, zato smo following days. In the activity, the focus was on children who jih spremljali in omogočili več ustvarjanja tudi ostalim, ki dela z already had some experience with information and računalnikom še niso bili vajeni. Delo je potekalo individualno communication technology from home, so we accompanied them in skupinsko. Spremljali so drug drugega in se izpopolnjevali. and enabled more creativity for others who were not yet used to Med njimi je uspešno potekala komunikacija. Otroci so tako working with computers. The work was carried out individually krepili fino motoriko in dobili nove izkušnje in znanje. Tako je and in groups. They followed each other and improved. There bil naš cilj dosežen. Med dejavnostjo so aktivno sodelovali in si was good communication between them. The children thus pomagali. Računalnik jim je bil zanimiv in zabaven vir strengthened their fine motor skills and gained new experiences informacij. Drug drugega so dopolnjevali. Njihova vztrajnost je and knowledge. So that our goal was achieved. During the bila nagrajena z uspehom. Nastale so zanimive umetnine, ki smo activity, they actively participated and helped each other. The jih ob koncu aktivnosti tudi natisnili. Česa podobnega se bomo computer was an interesting and fun source of information for nedvomno še kdaj lotili, saj se je učenje risanja s pomočjo them. They complemented each other. Their persistence was informacijsko-komunikacijske tehnologije izkazalo kot uspešen rewarded with success. Interesting works of art were created, primer prakse, kjer je bilo prisotnega veliko smeha, sproščenosti, which we also printed at the end of the activity. We will poglobljenega sodelovanja, vztrajnosti in uspešne komunikacije. undoubtedly do something similar again, because learning to draw with the help of information and communication KLJUČNE BESEDE technology proved to be a successful example of practice, where Risanje, IKT, sodelovanje, sprostitev, predšolsko obdobje, there was a lot of laughter, relaxation, indepth cooperation, učenje skozi igro perseverance and successful communication. Permission to make digital or hard copies of part or all of this work for personal or KEYWORDS classroom use is granted without fee provided that copies are not made or distributed Drawing, ICT, cooperation, relaxation, pre-school period, 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 learning through play be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 511 1 UVOD gre naprej, nazaj, levo, desno. Morali so pridobiti občutek za drsenje. Miška se je pomikala iz ene strani proti drugi. Vse čas Pojem digitalna tehnologija povezujemo z različnimi predmeti, s so urili koordinacijo ekran - miška. Drsenje po ekranu je bilo katerimi se srečujemo v vsakdanjem življenju, od mobilnih videti enostavno, a za posameznike ni bilo. Nekaj otrok se je telefonov, do tablic in računalnikov. Tako se že v zgodnjem prvič srečalo z njo in vztrajali so, dokler jim je bil računalnik na obdobju življenja srečujejo z novodobno tehnologijo tudi otroci. voljo. Za razvijanje svojih potencialov pa potrebujejo spodbudno S spretnostjo in vztrajnostjo so jo osvojili. Opazovali so drug vzgojno-učno okolje (ugodna klima, miselni izzivi, sredstva) in drugega in se zabavali. Zanimanja ni manjkalo. Vsak kompetentne strokovne delavce [3]. posameznik si je nato ogledal 3D-slikarja in se poigraval z Tehnologija je v zadnjih letih tako napredovala, da je ikonami. Skupaj smo si ogledali 3D-oblike, čopiče, učinke, smiselno, da se otrok z njo seznani že v zgodnjih letih. nalepke, kako izbrisati, če smo se zmotili, kako shranimo sliko, Informacijsko komunikacijska tehnologija ponuja veliko ki nam je všeč. Vse smo skupaj pregledali, preizkusili in se možnosti za razvoj otroka na različnih področjih. Na področju osredotočili na risanje izbranih živali. Vsak se je odločil, katera umetnosti lahko razvija umetniško predstavljivost, spoznava žival mu je najbolj všeč, in jo naslikal. Uporabili smo celo paleto različne načine komuniciranja. Vse te cilje lahko dosežemo ob barv. Sprva so bile živali bolj abstraktne in pisane. Z vajo pa so pravilni pripravi dejavnosti ter premišljeni izbiri aktivnosti s postale podobne tistim pravim iz živalskega vrta. Vsak pripomočki digitalne tehnologije. Otroci so vse bolj spretni pri posameznik je glasno razmišljal, kako jo bo pobarval in kakšen rokovanju s pametnimi napravami. Za uporabo moderne način barvanja uporabil. Otroci so izbirali med akvarelom, tehnologije so zelo motivirani, saj jih privlačijo številni oljnim čopičem, pastelom, peresom, razpršilcem in multisenzorični dražljaji. označevalcem. Preizkusili so vse, kar smo si skupaj ogledali. Le Kot pri vsakem vzgojnem izzivu tudi tehnologija ne pride kar miška ni vedno ubogala in črte so bile večkrat preveč ukrivljene naenkrat. Otroka moramo postopno navajati na vsebine, ki jih in neenakomerne, tako da so žival večkrat pobrisali. Zabavno je nudi IKT. Razumeti moramo vsako fazo otrokovega razvoja in bilo tudi radiranje. Tega ni manjkalo. Motivacije in zbranosti pa ugotoviti, katero komponento tehnologije je treba v določenem tudi ne. Med dejavnostjo so drug drugemu svetovali, kako naj trenutku obravnavati – na kaj je otrok pripravljen in, morda riše in kakšno barvo uporabi. Vlekli so dolge sklenjene in najpomembnejše, kako digitalni mediji prispevajo k zdravemu nesklenjene črte. Poleg nasvetov, pa se je pojavila tudi kritika. razvoju [1]. Kako pa ti rišeš? Glej, tole ni podobno žirafi. Zakaj si naredil Kot vzgojiteljica predšolske vzgoje sem si zadala cilj, da tako dolg rep? Toliko kot je bilo vprašanj, je bilo tudi odgovorov. izkoristim pozitivne lastnosti moderne tehnologije (večja Dejavnost je potekala 14 dni in še bi lahko nadaljevali. Vsak je motivacija otrok za izvajanje dejavnosti, dejavnosti so bolj narisal svojo najljubšo žival po svojem občutku in željah. Nastalo razgibane, delovno okolje v igralnici je bolj dinamično, otroci so je veliko abstraktnih, unikatnih umetnij. bolj motivirani in umirjeni). Otrok v umetnosti ustvarja, izumlja, odkriva in oblikuje sliko. Tako lahko govorimo o otroški dejavnosti na področju umetnosti 3 REZULTATI kot o umetniški dejavnosti otroka in o otroških umetnostnih delih. Taka dela nastanejo, ko ima otrok svobodo in se od njega Otroci, stari pet let, so bili pri ustvarjanju svoje lastne umetnine pričakuje drugačnost, izvirnost. Prav to so odlike otroške dobro razpoloženi, vztrajni in osredotočeni na svoj cilj – kako umetnosti, ki jih gojimo in cenimo in po katerih jo tudi narisati žival, ki so si jo izbrali. Koordinacija oko in miška sta vrednotimo. Otrokova umetnost in okus sta izrazito osebne bila v nenehni povezavi. Spremljali so vsak svoj klik in se učili. narave in se ju vedno opazuje, razume in presoja v okviru Iz dneva v dan jim je šlo lažje in rezultati so bili vidni. njegovega razvoja in življenjskega okolja [2]. Raziskovali in uporabljali so vedno več ikon, kar je spodbudilo njihovo intelektualno rast. Krepili so ustvarjalnost in spomin. Kar pa je najpomembnejše, med dejavnostjo so zelo uživali. 2 POTEK DELA V SKUPINI Primerjali so svoje umetnine, se smejali in se pogovarjali o izboljšavah. Izrazili so svoje težave in nazorno pokazali, kaj jim 2.1 Uvodna motivacija je bilo najtežje. Bili so zmožni samorefleksije. Nekateri rezultati Z otroki smo se zbrali v jutranjem krogu. Pogovarjali smo se o so prikazani na slikah 1 do 4. živalih, ki jih imajo doma. Vsak izmed njih je povedal, katera Na koncu smo vse izdelke shranili, natisnili in jih razstavili žival ga spremlja, kako zanjo skrbi, kako izgleda in kaj si še želi. po igralnici. Nekaj le-teh je dodano spodaj v tej projektni nalogi. Drugi so ostalim zaupali, katero žival bi si želeli imeti ali katera žival se jim je najbolj vtisnila v spomin ob obisku živalskega 4 ZAKLJUČEK vrta. Živali smo si ogledali v knjigah in kasneje tudi na spletu. Odprli smo program Google Chrome, vpisali v iskalnik ime Vključevanje IKT-orodja je zelo pomembo za vzgojno delo v živali in jo opazovali. Otroci so ugotovili, da nam računalnik današnjem času. Ko se otrok sooči z izzivom, se z vso nudi vse, kar nas zanima, in nam lahko poda kup informacij. pozornostjo in zavzetostjo usmeri k svojemu početju. Pri tem iz okolja vsrkava informacije, ki jih potrebuje za svoje ustvarjanje. 2.2 Glavni del (Uporaba 3D-slikarja) Računalnik je močno motivacijsko sredstvo, ki ne potrebuje Po ogledu vseh izbranih živali smo odprli računalniški program posebnih dodatnih stimulacij za delo. Skozi igro so otroci ves čas – 3D-slikarja in se seznanili z miško in vsemi ikonami, ki nam miselno aktivni in med seboj sodelujejo. jih je program ponudil. Otroci so najprej preizkusili miško, kako 512 Likovno ustvarjanje s pomočjo računalnika v predšolskem obdobju predstavlja otrokom posebno doživetje. Spoznali so, da se ob računalniku lahko veliko naučimo. Projektno delo učenje risanja s pomočjo IKT-tehnologije se je izkazalo, kot nadvse uspešen primer prakse. Vsekakor je omenjeni didaktični pristop popestril vzgojno delo. Otrokom je bilo všeč procesno učenje ob učnem pripomočku, ki je multisenzoričen. Ob tem so spoznali, da se na računalniku lahko veliko naučimo, da nam ponuja mnogo možnosti. Postavili smo temelje in sedaj bomo gradili naprej. Zadovoljna pa sem bila tudi sama, saj so otroci pokazali veliko volje, vztrajnosti, kritičnega mišljenja, kreativnosti ter sposobnosti povezovanja in sodelovanja v skupini, kar je v današnjem času še kako pomembno. Tako so bili doseženi vsi predvideni vzgojni in učni cilji projektne dejavnosti. Slika 3: Žirafa Slika 1: Gepard Slika 4: Pes VIRI IN LITERATURA [1] Gold J. 2015. Vzgoja v digitalni dobi. Ljubljana: Založba Didakta. [2] Kurikulum za vrtce. 2009. Ljubljana: Ministrstvo za šolstvo in šport, Urad Republike Slovenije za Šolstvo. [3] Usar K., Jerše L. 2016. Smernice za vključevanje IKT v vrtcu. Ljubljana: ZRSŠ. Slika 2: Lev 513 Razvijanje digitalne pismenosti na razredni stopnji s pomočjo aplikacije BookCreator Developing Digital Literacy at the Class Level Using the BookCreator Application Nastja Škrabl Osnovna šola Hruševec Šentjur Šentjur, Slovenija nastja.skrabl@hrusevec.si POVZETEK As a classroom teacher, I know how important it is to start digital literacy at the right time and offer them quality and proven Digitalna tehnologija je nujno zlo vsakega posameznika. Otroci applications, games, and online environments that ensure se z njo rokujejo že zelo zgodaj, pri čemer je pomembno, da jim comprehensive brain development and encourage development jo starši in kasneje strokovni delavci predstavijo na pravilen in all other areas. There are many tools and applications available, način ter da je njena uporaba nadzorovana. IKT otrokom z nižjo so it is good for the teacher to analyse them with the help of starostno stopnjo predstavlja predvsem igro, ki je v otroštvu spreadsheets before using them to check their effectiveness and najpomembnejša dejavnost, ki jo moramo spodbujati in podpirati. use. S pomočjo IKT lahko pri otrocih spodbujamo ustvarjalnost, logično razmišljanje, jezikovni razvoj, povečajo pa se tudi In this article, we will present an example of using the njihova samozavest, splošna razgledanost in socialne spretnosti. BookCreator application, in the subject social science, in the Kot učiteljica razrednega pouka se zavedam, da je treba otroke fourth grade of elementary school. By introducing the pravi čas digitalno opismeniti, jim ponuditi kakovostne in BookCreator application, we introduced digital literacy through preverjene aplikacije, igre, spletna okolja, ki zagotavljajo celovit the lessons of the home landscape, thereby providing a new way razvoj njihovih možganov in spodbujajo njihov razvoj tudi na of learning the subject, contributing to higher quality and more vseh ostalih področjih. Na razpolago je ogromno orodij in diverse daily activities in the classroom and increasing the level aplikacij, zato je prav, da jih učitelj pred uporabo s pomočjo of technological literacy as well as that of the teacher himself. preglednic analizira, preveri njihovo učinkovitost in uporabo. KEYWORDS V prispevku bomo predstavili primer uporabe aplikacije BookCreator pri predmetu družba v četrtem razredu osnovne šole. Digital literacy, BookCreator, grade level S pomočjo aplikacije BookCreator smo skozi pouk o domači pokrajini vpeljali digitalno opismenjevanje, s tem pa zagotovili 1 UVOD nov način spoznavanja snovi, pripomogli h kakovostnejši in raznovrstnejši vsakodnevni dejavnosti v razredu in zvišanju Potreba po tehnološkem opismenjevanju se vzpenja iz dneva v nivoja tehnološke pismenosti kot tudi samega učitelja. dan. Tehnološka rast, industrializacija in vse svetovne spremembe silijo tudi vzgojno izobraževalne ustanove, da KLJUČNE BESEDE omogočijo učenje in razvoj vseh tistih, ki bodo postali znanstveniki, inženirji, tehniki in delavci (Avsec in Sajdera, Digitalna pismenost, BookCreator, razredna stopnja 2019; Herschbach, 1997). ABSTRACT Kadar govorimo o vključevanju digitalne pismenosti, je izredno pomembno, da se strokovni delavci zavedamo, da smo z Digital technology is everyone's necessary evil. Children use it njo v prvi vrsti suvereni ter da s tem omogočamo dodano from a very early age, and it is crucial that parents and later vrednost in dobro motivacijo pri svojem delu. professionals present it to them correctly and control its use. ICT Tehnološka pismenost obsega tri dimenzije: znanje, način for children with a lower age level is primarily a game, but it is razmišljanja o delovanju in zmožnosti. Obsega tudi sposobnost the most important activity in childhood that we must encourage uporabe, razumevanja, vrednotenja in uporabe tehnologij and support. With the help of ICT, creativity, logical thinking, (Garmire in Pearson, 2006). and language development can be encouraged in children, and Če želimo uvesti smiselne dejavnosti, je treba dobro poznati self-confidence, general awareness and social skills also increase. otrokov razvoj, otroke v svojem razredu in njihove želje, predvsem pa njihovo individualno sposobnost in zahtevnost. Na Permission to make digital or hard copies of part or all of this work for personal or področju kognitivne psihologije je bilo ugotovljeno, da IKT classroom use is granted without fee provided that copies are not made or distributed otrokom omogoča optimalen razvoj njihove raziskovalne 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 aktivnosti. Stopnja razvoja je odvisna od spodbud okolja in be honored. For all other uses, contact the owner/author(s). količine izkušenj otrok (Novak s sod., 2013). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 514 Veliko aplikacij je izdelanih v tujem jeziku, kar predstavlja  poznajo različne dejavnike, ki vplivajo na ravnanje dokaj velik problem uporabe na razredni stopnji, saj morajo biti udeležencev v prometu, na primerih analizirajo in aplikacije otrokom prijazne, sicer jih lahko njihova uporaba presojajo strategije ravnanja pešcev in kolesarjev, odvrne že na samem začetku. Učitelj mora izbirati aplikacije,  razumejo vlogo posameznika v skupnosti pri skrbi za primerne starostni stopnji, poskrbeti pa mora tudi, da jih pred urejenost domačega kraja, uporabo učencem predstavi in jih seznani z njihovo uporabo.  vrednotijo urejenost domačega kraja z vidika različnih potreb ljudi, varovanja okolja ter naravne in kulturne dediščine. 2 PREDSTAVITEV APLIKACIJE Naš projekt se je začel s pojmovno mapo o kraju Šentjur. BOOKCREATOR Učenci so nizali ideje in dejstva o njihovem kraju. Pripovedovali BookCreator je preprosto orodje za oblikovanje digitalnih knjig. so o svojem domu in počutju v kraju, kjer živijo, o stvareh, ki jih Orodje je uporabno tako za učitelja kot za učence. Učitelj lahko pogrešajo, so jim všeč itd. S pomočjo Google zemljevida so na pripravlja različna gradiva, ki jih pri pouku uporabi za interaktivni tabli pokazali svoj dom. Hitro smo ugotovili, da demonstracijo ali pa za nadaljnje delo učencev. Možno je tudi, kljub temu da vsi živijo v isti občini, ne poznajo vseh vasi, ulic da učenci samostojno ustvarjajo lastne izdelke. Izdelujejo lahko in zaselkov. Ker je bilo njihovih idej in zgodb o njihovem kraju interaktivne zgodbe, digitalne portfolije, raziskovalna besedila, preveč, smo se odločili, da bo vsak o svojem kraju, o svojem pesmi, znanstvena poročila, navodila za uporabo, predstavitve zaselku napisal zgodbo, ki jo bo potem predstavil svojim itd. sošolcem. Idejo zasnove zgodbe smo medpredmetno povezali še Orodje je za delo z računalnikom dostopno na spletni strani z ostalimi predmeti. Učenci so si lahko izmislili kakšno pesem, https://BookCreator.com/, lahko se uporablja tudi na tabličnem rimo na temo njihovega kraja in jo kot zvočni posnetek vstavili računalniku. Za iPad je dostopno na: https://itunes.apple.com/ v njihovo predstavitev. Lahko so posneli okoliš in video vpeli v us/app/book-creator-for-ipad/id442378070?mt=8. stran v knjigi, pri likovni umetnosti pa so lahko kaj poustvarili na temo njihovega kraja in v knjigo dodali ilustracijo ipd. Ideje 2.1 Primer dobre rabe pri pouku družba so bile skupne, končni izdelek pa je bil izviren in na podlagi Pri prvi učni uri smo se z učenci pogovarjali o naravni dediščini zamisli vsakega posameznika. Projekt je potekal tri tedne, pri in si v domači pokrajini ogledali njene primere. V naslednji vseh urah družbe in tudi doma, saj so si učenci šolske tablice šolski uri so učenci samostojno prebrali krajše besedilo o pojavu izposodili tudi za domov. iz naravne ali kulturne dediščine iz domače pokrajine. Na Na koncu so svojo knjigo predstavili najprej svojim razpolago so imeli naslednje pojave: soteska Zelenjak, ribnik sošolcem, nato so svoje različice še natisnili in jih odnesli v Trebče, Žurajev hrast, skalno okno, razvaline gradu Kunšperk, knjižnico na razstavo, najprej šolsko, nato pa še v mestno Kravaričeva domačija itd. V zvezek so si zapisali pomembne knjižnico. Izvedli smo natečaj za najboljšo napisano knjigo in jo podatke. ob občinskem prazniku poslali županu občine Šentjur. Sledila je predstavitev orodja BookCreator in samostojno ustvarjanje strani v knjigi. Učenci so izdelali naslovno stran z 3 PREDNOSTI IN SLABOSTI APLIKACIJE risbo in zemljevidom, napovedali naravne in kulturne pojave ter en pojav tudi predstavili. Nekaj ur kasneje, po obravnavi Poleg tega da je aplikacija preprosta za uporabo, učitelju poglavja dejavnosti, smo v knjigo dodali novo stran na temo omogoča povratno informacijo o samem učenčevem izdelku. dejavnosti v domači pokrajini. Učenci so morali narisati in Izdelek si lahko ogledamo v samem orodju, izvozimo v PDF napisati gospodarske in negospodarske dejavnosti v svojem obliki in natisnemo. Izdelke lahko tudi posredujemo v e-obliki, okolju. Načrtujemo, da bodo učenci knjige dopolnjevali in e- jih objavimo, za kar pa je potrebna prijava z e-pošto. Oblikovanje knjižica bo do konca šolskega leta dobila svojo celostno podobo. je zelo enostavno in ponuja veliko funkcij, izbiramo lahko tudi Delo z aplikacijo je potekalo individualno. Preden smo se med različnimi vrstami oblik podlage. Aplikacija tako omogoča lotili konkretnega dela, smo skupaj pregledali aplikacijo, učenčevo ustvarjalnost in domišljijo, navsezadnje pa tudi prevedli določene ikone, izdelali vzorčni primer. Orodje je v socialno povezanost, ko se izdelek zaključi, saj ga lahko deli s angleščini, vendar vsebuje preproste besede in besedne zveze, širšo množico. poleg tega pa vsebuje nazorne ikone (slika, fotoaparat, besedilo, Vse izdelke si lahko ogledamo v samem orodju ali pa jih iz mikrofon, oblike, spletne povezave). Uporaba orodja je sicer zelo orodja izvozimo v PDF obliki ali v obliki videoposnetka. PDF preprosta in učenci so jo hitro usvojili. Svojo knjigo so izdelovali oblika omogoča, da izdelke natisnemo ali posredujemo v e-obliki. s tabličnim računalnikom. Prav tako lahko učitelj izdelke objavi (potrebna prijava z e-pošto). Pri pouku družbe so učenci z uvajanjem aplikacije Orodje ponuja veliko funkcij (fotoaparat, risanje, snemanje BookCreator dosegli naslednje cilje: zvoka, videoposnetek) in kombinacijo vsega. Lahko se izbira  poznajo naravne osnove za nastanek in razvoj tudi med različnimi vrstami oblik podlag. domačega kraja za življenje, Orodje ima več prednosti kot slabosti. Kot učiteljica, ki  spoznajo gospodarske in druge dejavnosti, različne spodbuja sodelovalno delo, pri aplikaciji pogrešam, da bi lahko poklice, skupno knjigo oblikovalo več učencev hkrati, da bi svoje zapise  prepoznajo in analizirajo varne in manj varne poti za delili in ustvarili sodelovalno delo. Še ena pomanjkljivost, ki smo pešce in kolesarje, jo zaznali, je ta, da lahko z brezplačno različico izdelamo le eno knjigo z več stranmi. Možno je tudi, da vsak učenec izdela po 515 eno stran, učitelj fotografira izdelke in sestavi eno knjigo z več motivacijo, idejo za razvoj in uporabo aplikacije tudi pri drugih stranmi različnih avtorjev. predmetih, učinkovita pa je bila za razvoj pomnjenja, pridobivanja osnovnih in specifičnih znanj ter razvoj socialnih veščin. 4 ZAKLJUČEK Popestritev vsakodnevnih dejavnosti v razredu je zelo dobrodošla, tako za učitelja kot učence. Vsekakor lahko to LITERATURA IN VIRI drugačnost v veliko primerih dosežemo z digitalno pismenostjo. [1] Avsec, S. in Sajdera, J. (2019). Factors influencing pre-services preschool Vsako vsebino, ki jo učencem ponudimo, moramo dobro teachers' engineering thinking: model development and test. International journal of technology and design education, doi: 10.1007/s10798-018-9486- preučiti, kritično analizirati in spoznati pravilen pristop do tega. 8. Na koncu lahko pridobimo veliko več, kot smo na začetku upali [2] BookCreator (b. d.). Pridobljeno dne 8. 8. 2022 s https://itunes.apple.com/us/app/book-creator-for-ipad/id442378070?mt=8. in želeli. Eden ključnih razlogov, zakaj razvijati digitalno [3] Garmire, E. in Pearson, G. (2006). Tech Tally: Approaches to Assessing pismenost in drugačnost pouka, je zagotovo ta, da so učenci Technological Literacy. Washington. V The National Academy Press. Dostopna na: htps://www.nap.edu/read/11691/chapter/4. veliko bolj motivirani in kreativni pri pouku. Poleg tega se učijo [4] Novak, L., Velianje, E. in Kranjc, R. (2013). Ali vemo, kaj zmorejo učenci spretnosti uporabe IKT za celo življenje. Učna ura, ki smo jo 1. ViO na področju računalništva? V Kreuh, N., Trestenjak, B., Blagus, K., izpeljali s pomočjo aplikacije BookCreator, je pokazala pozitiven Kosta, M. in Lenarčič, A. (ur). V Mednarodna konferenca Splet izobraževanja in raziskovanja z IKT – SIRikt 2013. (Str. 149–153). Kranjska vpliv vključevanja IKT v pouk. Pri učencih je spodbudila Gora: Miška d. o. o. 516 Spodbujanje in razvijanje bralnega razumevanja pri pouku angleščine s tehnologijo Encouraging and Developing Reading Comprehension in English Classes With Technology Rok Škrlec Šolski center Kranj Kranj, Slovenija rok.skrlec@sckr.si POVZETEK that will enhance the reading comprenshion for students. That is why we focused our tasks on Google Forms, Microsoft software Branje pri dijakih pogosto povzroči slabo voljo, saj sami ne želijo OneNote and a website called Liveworksheets. A new method of brati daljših besedil in odgovarjati na vprašanja v fizični obliki. teaching and working at home has enhanced the classes and Odločili smo se jim približati in obogatiti njihovo bralno increased the students’ motivation and at the same time, the new razumevanje. Pouk smo popestrili z uporabo telefonov, tablic ali way of tackling reading comprehension has enabled all students, računalnikov. Poleg tega so dijaki za domačo nalogo na especially those who want or need to, to do reading računalniku izdelali bralni zvezek, iz katerega so bili kasneje comprehension tasks at their own leasure. ocenjeni. Cilj drugačnih pristopov k bralnemu razumevanju je bil predvsem popestriti razvijanje bralne kompetence z vključitvijo KEYWORDS tehnologije in večjega števila nalog za bralno razumevanje med in po branju, kot tudi za uvodno motivacijo pred branjem. Pri English, secondary school, reading, reading comprehension, izbiri orodja za popestritev bralnega razumevanja je potrebno OneNote, motivation upoštevati tudi dostopnost brezplačnih orodij, zaradi česar smo se pri tem osredotočili na Google Forms, Microsoftov program 1 UVOD OneNote in spletno stran Liveworksheets. Nov način dela v šoli in doma je popestril pouk in dobro vplival na delovno motivacijo Tehnologija je postala tako dostopna, da jo učitelj zelo enostavno dijakov, hkrati pa je nov način preverjanja bralnega razumevanja vključi v didaktični proces in z različnimi metodami poučevanja omogočal dodatno individualno delo tistim, ki so to želeli ali vpliva na motivacijo in učinek učenja v šoli ali doma. Bralno potrebovali. razumevanje v izobraževanju tujih jezikov ostaja ena izmed štirih glavnih jezikovnih spretnosti, poleg slušnega razumevanja, KLJUČNE BESEDE govornega in pisnega sporočanja. Od vseh štirih spretnosti je branje pri mlajših generacijah izgubilo svojo priljubljenost, saj v Angleščina, srednja šola, branje, bralno razumevanje, OneNote, prostem času ni več tako popularno, kot je bilo v preteklosti. motivacija Vseeno pa je branje pri tujem jeziku še vedno izjemnega pomena, ABSTRACT saj širi bralni zaklad, hkrati pa se dijak utrjuje v poznavanju slovničnih struktur [1]. Reading in class often puts students to a bad mood since they do Poleg tega bralno razumevanje ostaja pomemben element not enjoy reading long passages of texts and answer numerous zaključnih izpitov v srednješolskih programih, kot sta poklicna questions on paper. Due to the constant and annoying presence in splošna matura, in se ga povezuje ne le z razumevanjem of phones in class, we have decided to use them for the purpose sporočila besedila, vendar tudi z razumevanjem uporabe of education. Phones have made the reading experience more slovničnih struktur in besednih kolokacij. Pri poklicni maturi gre diverse and easier and whenever we had a chance, we resorted to za tipe nalog, kot so dopolnjevanje besedila z besedami ali deli the computers and tablets as well. In addition, the students had to stavkov, odgovarjanje na vprašanja, povezovanje tem z deli compile a reading notebook on the computer and were graded besedila, izbira pravilnega odgovora. Podobno bralno from it. The goal of such different teaching and learning razumevanje se preverja tudi na splošni maturi, vendar na višji approaches was mainly to diversify reading comprehension by ravni B2, poleg tega pa morajo dijaki poznati tudi vse osnove including technology and a bigger scope of tasks during and after slovnice, besedotvorja in glagolskih oblik. Učitelji morajo v času reading, as well as tasks for before reading. While the number of srednješolskega izobraževanja dijake s tovrstnim bralnim tools is big, one needs to consider the accessibility of free tools razumevanjem ne le seznaniti, ampak jih na to tudi pripraviti in jim delo olajšati s posameznimi aktivnostmi. 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 2 MOTIVACIJA ZA BRANJE be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Motivacija v učilnici je širok pojem, ker jo lahko razdelimo na © 2022 Copyright held by the owner/author(s). notranjo ali zunanjo motivacijo. Hkrati lahko dijake motiviramo 517 na kratek rok, kasneje pa tudi na daljšega. Pri tem je najbolj Bralni zvezek je način, ki dijakom daje dovolj svobode za učinkovit način, da učitelj motivira dijake postopoma – sprva na izbiro člankov, zato lahko vključijo tematike, ki jih zanimajo in krajši način s pomočjo ugank, primerno hitrostjo, primerno o katerih želijo govoriti oz. brati. Z namenom, da bi popestrili tematiko, ki spodbuja komunikacijo dijakov in pritegne njihovo vsebino bralnega zvezka, pa se morajo dijaki vseeno dotakniti pozornost. Eden izmed pomembnih elementov pri vzpostavljanju vsaj pet poljubnih tematik. Izdelave bralnega zvezka do pozitivne motivacije je ustvarjanje prijetnega vzdušja v razredu. končnega datuma ne preverjamo, kar tudi povečuje motivacijo k [2]. Ker so dijaki močno navajeni uporabe mobilnih telefonov, delu in spodbudi dijake k samostojnemu delu ter razmišljanju. lahko raba le-teh vzpostavi prijetnejše vzdušje pri pouku, pa tudi Slika 1 prikazuje primer dobro urejenega članka. če le za kratek čas. Drugi elementi, ki močno vplivajo na motivacijo dijakov pri branju so: izbira besedila oz. teme, namen branja, količina besedila, branje na glas ali po tiho, čas branja, razumevanje jezika in besedišča [3]. Besedila beremo z različnim namenom in od tega je odvisno tudi, kako jih preberemo. Dijaki se branja hitro naveličajo, ker je besedilo predolgo ali pa se učiteljev način pristopa k branju ponavlja. Potrebno je načelo pestrosti, ki poskrbi, da način obravnave besedila in namen branja ne ostaja enak. Pomembna spretnost, ki jo dijaki morajo razviti, je hiter pregled besedila (ang. skimming) [3]. Pri tem dijaki ne preberejo celega besedila, vendar najdejo določene informacije. Dijaki nimajo celotnega besedila pred seboj, vendar ga lahko odprejo na tablici ali telefonu. S tem se osmisli uporaba mobilne naprave pri pouku in učna ura se popestri. Poleg pestrih in spreminjajočih učnih pripomočkov in tipov nalog je potrebno poskrbeti, da so besedila, ki jih dijaki analizirajo na poglobljen način, krajša, oz. jih ne obdelujejo prepogosto. Slika 1: Primer članka iz bralnega zvezka. 3 BRANJE S TEHNOLOGIJO 3.2 Potopni bralnik Branje smo poskušali vključiti v učni proces na več načinov. Pri natančnejši obravnavi besedila se pogosto pokažejo razlike Bralnega razumevanja ni mogoče razviti v krajšem času, zato med dijaki. Dijaki različno hitro berejo in rešujejo naloge smo poskrbeli, da so dijaki v štiriletnem izobraževanju redno bralnega razumevanja. Pojavili so se tudi primeri dijakov, ki izpostavljeni branju. Tehnologija nam je omogočila, da smo zaradi disleksije ali ostalih težav niso tako dobro sledili pouku bralno razumevanje popestrili in da so bili dijaki dodatno oz. so morali snov nadoknaditi doma. Besedilo na belem listu motivirani. papirja je nespremenljivo in njegova velikost, pisava ali barva otežijo branje in bralno razumevanje določenim dijakom s 3.1 Bralni zvezek posebnimi potrebami. Na učnih urah nižjih letnikov srednje Za redno spodbujanje branja so dijaki dobili domačo nalogo, kjer poklicne in tehniške šole so se pokazale tudi razlike v so v štirih mesecih izdelovali bralni zvezek. Bralni zvezek razumevanje besed in nezmožnosti izgovorjave. vsebuje več besedil, ki jih dijaki berejo postopoma. Za vsako Orodje potopni bralnik (ang. Immersive reader) v orodjih besedilo, ki ga najdejo na internetu ali v revijah, napišejo vir, Microsoft Word in OneNote omogoča ogled besedila z ustreznim označijo nekaj neznanih besed in ga v petih povedih obnovijo. razmikom črk in besed, ki olajša branje marsikaterim dijakom s Vsak teden v prvi polovici šolskega leta preberejo besedilo, v posebnimi potrebami. Besedilo je dostopno v orodju OneNote, drugi polovici šolskega leta pa učitelj bralni zvezek oceni. Tako kar pomeni, da ga dijak lahko ponovno prebere doma in si je dijak hkrati ocenjen iz razumevanja besedil in poznavanja spremeni velikost ali pisavo besedila. Vsi dijaki, ki imajo besedišča. primanjkljaj v poznavanju besedišča, lahko s tem orodjem Metoda se je izkazala kot odlična pri spodbujanju branja, s kliknejo na besedo, ki jo program prevede v slovenščino, za katero ima dijak svobodo izbire besedila, v določenih primerih določene besede pa se pojavi tudi slika pomena. pa lahko izbira tudi tematiko. Ker se je bralni zvezek izkazal za Poznavanje besednih vrst v besedilu je ključnega pomena za uspešnega v papirnati obliki, smo se odločili, da dijak bralni učenje besedotvorja. Zgradba povedi in prepoznavanje glagola, zvezek pripravi tudi v elektronski obliki – najprej v obliki samostalnika, pridevnika in prislova v povedi bo dijakom datoteke Microsoft Word, ko pa so dijaki usvojili rabo programa omogočila boljše razumevanje slovnične zgradbe stavka. Microsoft OneNote, pa so bralne zvezke oddali v tej obliki. Potopni bralnik je orodje, ki v vsakem besedilu samodejno Bralni zvezek se je izkazal kot dober način priprave na označi besedne vrste, tako da lahko dijak sam utrjuje maturo, saj dijaki na poklicni maturi dobijo zelo podobno nalogo, prepoznavanje besednih vrst s pomočjo tega orodja. kjer govorijo o članku iz strokovne tematike, podoben učinek pa Ob obravnavi besedila v razredu pa smo potopni bralnik ima ta način dela tudi na dijake gimnazijskih smeri, ki so tako uporabili tudi za glasno branje besedila, iz katerega smo razvili bolj pripravljeni na branje krajših odsekov literarnih del, ki jih več vrst aktivnosti. Na primer, dijakom smo predvajali narek obravnavajo na splošni maturi. besedila ob počasnejši ali hitrejši hitrosti, pri tem pa so imeli 518 različne naloge – zapis besed in prislovov, dokončanje stavka itd. Na sliki 2 so v besedilu besede različnih besednih vrst označene z različnimi barvami, možna pa je tudi podrobna razlaga besede s klikom nanjo. Slika 3: Odsek učnega lista z izbiro odgovorov s spletne strani Liveworksheets. 4 ZAKLJUČEK Branju se pri pouku tujega jezika v srednji šoli ne moremo izogniti. Orodij na spletu je dovolj, da si vsak učitelj najde način, ki mu olajša delo, dijakom pa popestri učne ure in domače delo. Zaradi uporabe telefona in računalnika pri bralnem razumevanju so dijaki lahko prebrali več besedil, si tako bolj razširili besedišče Slika 2: Primer besedila z označenimi besednimi vrstami. stroke. Vseeno pa moramo biti pozorni, da z uporabo tehnologije pri pouku učitelj ne pretirava. Kratka anketa je pokazala, da je 3.3 Preverjanje bralnega razumevanja nov način ocenjevanja bralnega zvezka ustreznejši 60 % Pri bralnem razumevanju je pogosto potrebno veliko vaje. dijakom, hkrati pa je 70 % dijakov odgovorilo, da jim Namesto ogromno učnih listov v fizični obliki lahko učitelj preverjanje bralnega razumevanja v obliki spletnih učnih listov dijakom pripravi izročke v obliki spletnega kviza. Učitelji lahko bolje ustreza kot na papirju. Kljub temu verjamemo, da je pri besedila s spleta uvozijo v Google Obrazec, kjer označijo uporabi različnih metod poučevanja pomembna pestrost – tako pravilne odgovore. Tako imajo lahko dijaki dostop do več nalog kot je potrebno v pouk občasno vključiti tehnologijo, je za dijake bralnega razumevanja. Mnogi učitelji radi uporabljajo tudi in učitelja pomembna tudi vrnitev k tradicionalnemu načinu Microsoft Forms, podobno aplikacijo, vendar Google Obrazce branja, ki ima druge pozitivne lastnosti. uporabljamo predvsem zaradi večjih možnosti pri sestavljanju vprašanj in bolj primernega izgleda vprašanj. LITERATURA IN VIRI Na podoben način deluje tudi spletna stran Liveworksheets. [1] Jermeny Harmer. 2007. The Practice of English Language Teaching (4th. ed.). Pearson Longman, Harlow, Essex. Po ustvarjenem profilu si lahko učitelj ustvari učni list, ki ga [2] Henry D. Brown. 2007. Teaching by Principles: An Interactive Approach to spletna stran prikaže v obliki PDF. V dokumentu je v za to Language Pedagogy (3rd. ed.). Allyn & Bacon, Boston, Massachusetts. označene prostore možno vpisati kratke odgovore ali številke, [3] David Cross, 1992. A practical handbook of Language Teaching. Cassell, London. učitelj pa rešitve vnese že prej. Na enak način lahko dijak označi pravilne odgovore ali izbira med več možnostmi, tako da obkljuka pravilni odgovor. Ko dijak učni list pregleda in napiše svoje odgovore, jih orodje pregleda ter točkuje, učitelj pa takoj dobi povratno informacijo o številu točk. Slika 3 prikazuje primer treh vprašanj, kjer lahko dijaki preverijo pravilnost svojih odgovorov takoj po reševanju učnega lista na spletni strani. 519 Izobraževanje šolskih knjižničarjev na daljavo v Narodni in univerzitetni knjižnici Distance Learning for School Librarians at National and University Library Gregor Škrlj Narodna in univerzitetna knjižnica Ljubljana, Slovenija gregor.skrlj@nuk.uni-lj.si POVZETEK z zakonodajo izvaja knjižnično dejavnost kot javno službo [2] in skrbi za dediščino ter sodeluje v nacionalnem vzajemnem Narodna in univerzitetna knjižnica ima med svojimi nalogami bibliografskem sistemu, opravlja pa tudi druge dejavnosti in tudi izobraževalno dejavnost. Velik del programa je namenjen naloge. Med drugim je za knjižničarsko stroko izjemno izobraževanju strokovnih knjižničarskih delavcev. Epidemija pa pomembna izobraževalna dejavnost, za katero v NUK skrbi je posegla v sam proces izobraževanj, zato je bilo potrebno vsa Oddelek za izobraževanje, razvoj in svetovanje. Potencialni izobraževanja preseliti v spletno okolje. V luči spremenjenih udeleženci izobraževanj so slovenski strokovni knjižničarski razmer dela in izobraževanja na daljavo so bile vse vsebine delavci, založniki ter uporabniki knjižnic. Izobraževalne vsebine tečajnikom podane s pomočjo spletne platforme ZOOM. so razdeljene po sklopih, ki so namenjeni knjižničarjem Narodna in univerzitetna knjižnica je torej v letu 2021 uspešno začetnikom, knjižničarjem, ki želijo izpopolniti svoje znanje in izpeljala izobraževanja na daljavo za šolske knjižničarje. tistim, ki se želijo usposobiti za delo v sistemu vzajemne katalogizacije ter uporabnikom knjižnic (študentje, raziskovalci, KLJUČNE BESEDE občani …) [3]. Stalno izobraževanje je za vsakega posameznika Narodna in univerzitetna knjižnica, izobraževanje, ZOOM, nepogrešljivo ter pomembno, česar se NUK zaveda in temu epidemija, šolske knjižnice vsako leto posveča veliko pozornosti. ABSTRACT National and University Library also has educational activities 2 IZOBRAŽEVANJE ŠOLSKIH among its tasks. However, the epidemic has interfered with the KNJIŽNIČARJEV IN NUK training process itself, and it has been necessary to move all Kot že omenjeno med drugimi nalogami NUK zagotavlja tudi training to an online environment. In the light of the changed izobraževalne vsebine. Vsako koledarsko leto objavi program working and distance education situation, all content was izobraževanja (dostopen na spletni strani NUK) ter izvede delivered to the participants using the ZOOM online platform. strokovna spopolnjevanja in permanentno izobraževanje za National and University Library has therefore successfully zaposlene v knjižnični dejavnosti [4], saj je strokovno delivered distance learning courses for school librarians in 2021. izobraževanje izjemnega pomena za vsakega strokovnega knjižničarskega delavca. Kot je zapisano tudi v Etičnem kodeksu KEYWORDS slovenskih knjižničarjev, mora vsak knjižničar znova in znova National and University Library, education, ZOOM, epidemic, izpopolnjevati svoje strokovno znanje ter ustvarjalno prispevati school libraries k razvoju knjižničarske stroke in njene dejavnosti [5]. NUK zato organizira ter izvaja različne oblike izobraževanj za knjižničarje, založnike in usposabljanja za uporabnike knjižnic [6]. Svoj 1 UVOD izobraževalni progam NUK izvaja na dveh lokacijah: v Narodna in univerzitetna knjižnica (dalje NUK) je nacionalna računalniški učilnici NUK na Turjaški ulici 1 ter v učilnici na knjižnica Republike Slovenije, katere temeljno poslanstvo je Leskoškovi cesti 12. Od leta 2020, ko se je zaradi epidemije zbiranje in varovanje ter zagotavljanje uporabe nacionalne zbirke COVID-19 vse spremenilo, pa izobraževanja izvaja tudi na knjižničnega gradiva, strokovna podpora knjižnicam pri spletu. izvajanju javne službe in nacionalnemu bibliografskemu sistemu Ob nastopu epidemije je bilo treba izvajanje izobraževanj ter vključevanje v mednarodne knjižnične povezave [1]. Skladno prilagoditi razmeram, kar je pomenilo vzpostavitev različnih možnosti izobraževanja prek spleta oziroma na daljavo [7]. Kot eno izmed optimalnih izobraževalnih izkušenj smo v NUK 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 izbrali ZOOM (ZOOM je spletna platforma za avdio in video for profit or commercial advantage and that copies bear this notice and the full komunikacijo, ki se uporablja za organiziranje sestankov, citation on the first page. Copyrights for third-party components of this work must izobraževanj, delavnic in drugih oblik sodelovanja) [8]. Za be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia dostopnost vsebin ter gradiv pa je bilo potrebno pripraviti tudi © 2022 Copyright held by the owner/author(s). 520 spletno učilnico, ki je osnovna aplikacija za uporabo pri 3.1 Krepitev kompetenc šolskega knjižničarja izobraževalnem procesu na daljavo [9]. Izobraževanje je potekalo od 11. do 14. oktobra 2021, vsak dan Tudi izobraževalne vsebine za šolske knjižnice so se preselile na od 9.00 do 11.00 ure, z uporabo aplikacije ZOOM. splet. Načrtovana so bila naslednja izobraževanja: Vsebina: - Krepitev kompetenc šolskega knjižničarja, - Izločanje, odpis in inventura v šolski knjižnici, - zakonodajni okvirji delovanja šolske knjižnice, - Spletna orodja in aplikacije za šolske knjižnice. - šolske knjižnice in njihovi deležniki, Potencialni udeleženci izobraževanj, ki so zaposleni v - načini komuniciranja z deležniki, šolskih knjižnicah, so prejeli e-pošto z vsemi podatki ter - komuniciranje na daljavo, informacijami, na voljo je bila tudi prijava na izobraževanja prek - domače in tuje dobre prakse šolskih knjižnic. spletnega obrazca. Obveščeni so bili, da bodo za udeležbo Cilj izobraževanja je bil optimizacija dela šolskih potrebovali ustrezno tehnično opremo (računalnik s kamero, knjižničarjev ter seznanitev z zakonskimi obveznostmi delovanja zvočnikom in mikrofonom ter čim boljšo internetno povezavo). knjižnice. V okviru izobraževanja so udeleženci spoznali Na Sliki 1 je prvo vabilo na izobraževanje za šolske knjižnice. različne oblike komuniciranja, ki mora biti prilagojeno posameznim deležnikom. 3.2 Izločanje, odpis in inventura v šolski knjižnici Izobraževanje je potekalo od 8. do 11. novembra 2021, vsak dan od 9.00 do 11.00 ure, z uporabo aplikacije ZOOM. Vsebina: - zakonodajni okvirji za izločanje, odpis in inventuro, - izločanje in odpis knjižničnega gradiva, - inventura v šolski knjižnici, - primeri iz prakse in čas za vprašanja. Cilj izobraževanja je bil razrešitev dilem, s katerimi se šolski knjižničarji soočajo pri izločanju, odpisu in inventuri knjižničnega gradiva. 3.3 Spletna orodja in aplikacije za šolske knjižnice Izobraževanje je potekalo od 30. novembra do 3. decembra 2021, vsak dan od 9.00 do 11.00 ure, z uporabo aplikacije ZOOM. Vsebina: - digitalna pismenost, - digitalne kompetence, - uporaba brezplačnih aplikacij ter spletnih orodij v Slika 1: Prvo vabilo ter povezave do spletne prijave na šolski knjižnici, izobraževanja za šolske knjižnice. - izobraževanje s pomočjo aplikacij in spletnih orodij, - prikaz praktičnih primerov. Cilj izobraževanja je bil usposobiti šolske knjižničarje za 3 IZPELJAVA IZOBRAŽEVANJ ZA ŠOLSKE izobraževalce na področju informacijske pismenosti in digitalnih KNJIŽNIČARJE NA DALJAVO kompetenc. Udeleženci so se seznanili s koristmi aplikacijami in V spletno okolje je bilo potrebno preseliti vsa tri (v nadaljevanju spletnimi orodij za delo v šolski knjižnici. omenjena) izobraževanja, ki so bila posebej namenjena šolskim knjižničarjem. Večjih težav pri predpripravi ni bilo, saj smo v Po spletni prijavi je vsak udeleženec prejel povratne NUK že izvajali izobraževanja v spletnem okolju. Vsa tri informacije, gradiva in napotke za delo ter vedenje v času trajanja izobraževanja smo razdelili na štiri zaporedne dni po dve uri. izobraževanja (navodila glede poimenovanja, kamere, načina Naklonjenost takemu načinu izvedbe so izrazili sami šolski sodelovanja ter druge informacije). Za vsako izobraževanje so knjižničarji, ki so predhodno izpolnili anketni vprašalnik. Na udeleženci prejeli natančen opis, urnik ter časovnico. Povezavo anketno vprašanje 'V kolikšni meri vam ustrezajo spodaj za vstop v spletno okolje so dobili nekaj dni pred začetkom navedene oblike izobraževanja?', kjer so bile na voljo tri izobraževanja. možnosti: spletna izobraževanja, kombinirana izobraževanja in Vsebine izobraževanj so bile pripravljene posebej za potrebe klasična izobraževanja v živo, je odgovorilo 207 anketirancev. in naravo dela v šolskih knjižnicah. Šolske knjižnice namreč Prvo možnost (spletna izobraževanja) je izbralo kar 157 izvajajo knjižnično dejavnost, potrebno za izvajanje javne službe anketirancev, kar je 76 % vseh anketirancev. Za drugo možnost na področju vzgoje in izobraževanja [10]. (kombinirana izobraževanja) se je odločilo 34 anketirancev, kar Vsak dan vsake izvedbe izobraževanja je bil časovno ravno je 16 % in za zadnjo možnost (v živo) se je odločilo le 16 dovolj obširen, da so udeleženci pred zasloni obdržali motivacijo anketirancev (8 %). za sodelovanje ter zbrano sledili vsem vsebinam. Izkazalo se je 521 tudi, da je bilo dovolj časa za vprašanja ter reševanje zastavljenih Na Sliki 4 prikazujemo vsebino oziroma poglavje spletne vaj in nalog. Poleg vseh uporabnih virov, dejavnosti in funkcij je učilnice za izobraževanje Krepitev kompetenc šolskega bil uporaben tudi klepet v ZOOM-u, kjer je potekala knjižničarja. Na enem mestu so zbrani vsi za šolske knjižnice komunikacija med udeleženci in izvajalci izobraževanj (vsi pomembni dokumenti, povezave ter gradiva. namreč niso imeli možnosti video in avdio vklopa). Tako so postavljali vprašanja ter komunicirali preko klepeta. Slika 2 prikazuje NUK učilnico za šolske knjižnice ter vsebine. Slika 2: Vpogled v NUK učilnico za šolske knjižnice. Vsebine v učilnici so vezane na delovanje šolskih knjižnic. Posebej za določeno izvedbo je bilo pripravljano poglavje z Slika 4: Zaslonska slika določenega poglavja v spletni vsebinami ter vajami (zelo uporabno pri tečaju o aplikacijah). učilnici. Na Sliki 3 je viden pogled v spletno učilnico, kjer so za udeležence (skladno z zastavljenimi cilji) pripravljeni posamezni 4 ZAKLJUČEK sklopi, vsebine in gradiva posameznega izobraževanja. V besedilu smo na kratko predstavili in opisali izobraževalno dejavnost NUK za šolske knjižnice v letu 2021, ko je bilo potrebno izobraževanje zaradi epidemije prenesti v spletno okolje. V poučevanje na daljavo smo se v letu 2020 podali čez noč, saj so z razglasitvijo epidemije ustavili tako rekoč celotno državo. V tako imenovani novi realnosti je bilo potrebno prilagoditi tudi izobraževanje, ki ga za knjižničarje, založnike in uporabnike izvaja NUK. Izobraževanja na daljavo se je izvedlo s pomočjo spletne aplikacije ZOOM in spletnih učilnic, kar so z odobravanjem sprejeli tudi udeleženci. Čas in trajanje posamezne izvedbe izobraževanj ter sama komunikacija so bili prilagojeni udeležencem. Udeleženci so pridobili in nadgradili sposobnosti sodelovanja, komuniciranja, reševanja in uporabe spletnih orodji (tudi spletne učilnice) ter krepili posamezne stopnje digitalnih kompetenc (digitalne kompetence segajo na področja informacijske pismenosti, komuniciranja in sodelovanja, izdelovanja digitalnih vsebin in drugo) [11]. Še posebno pa so znanja na področju informacijske tehnologije nadgradili udeleženci izobraževanja Spletna orodja in aplikacije za šolske knjižnice. Vse tri izvedbe izobraževanj so nekako zaokrožile delo v šolski knjižnici. Zagotovo lahko trdimo, da je nov način izvajanja izobraževanj na daljavo s svojo prilagodljivostjo, funkcionalnostjo prispeval k novim izobraževalnim potem. S tem, da je NUK izvajal izobraževanja na daljavo, so se v strokovni prostor vpeljale nove strategije, novi načini dela in podajanja Slika 3: Vpogled v spletno učilnico Spletna orodja in vsebin ter so se ob tem razvijale nekatere strokovne kompetence. aplikacije za šolske knjižnice, v kateri so bile pripravljene Kar pa je še bolj pomembno, vsebine ter izobraževanja so bila interaktivne naloge (udeleženci so jih reševali tekom dostopna širšemu krogu potencialnih udeležencev, kar so v izobraževanja), napotki za delo z aplikacijami ter primeri že anketnem vprašalniku potrdili ter zapisali njihovi udeleženci. pripravljenih dejavnosti. V kolikor kdo ni uspel rešiti ter Lažje in rajši so se udeležili izobraževanja na daljavo kot v živo pregledati pripravljenih vaj med samim izobraževanjem, je (različni razlogi – od stroškov, prevoza, časovne zamude …). imel nato še 14 dni časa, da je vaje lahko rešil sam. 522 Nekateri pa so celo zapisali, da se izobraževanja v živo sploh ne [5] Etični kodeks slovenskih knjižničarjev. 1995. Dostopno na: bi udeležili. https://www.zbds-zveza.si/daljsa-6/ (3. 8. 2022) [6] Uredba o osnovnih storitvah knjižnic. Dostopno na naslovu: http://www.pisrs.si/Pis.web/pregledPredpisa?id=URED2851 (3. 8. 2022) [7] Izobraževanje na daljavo NUK. Dostopno na naslovu: https://www.nuk.uni- LITERATURA IN VIRI lj.si/izpostavljamo/izobrazevanje-na-daljavo (3. 8. 2022) [8] Uporaba aplikacije ZOOM. Dostopno na naslovu: https://www.nuk.uni- [1] Naloge, vizija, poslanstvo in vrednote NUK. Dostopno na naslovu: lj.si/sites/default/files/dokumenti/2020/ZOOM.pdf (3. 8. 2022) https://www.nuk.uni-lj.si/nuk/poslanstvo# (3. 8. 2022) [9] Spletna učilnica. Dostopno na naslovu: [2] Zakon o knjižničarstvu. 2015. Dostopno na naslovu: https://www.knjiznice.si/knjiznicarji/izobrazevanje/spletna-ucilnica/ (4. 8. http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO2442 (3. 8. 2022) 2022) [3] Marinšek, P. 2020. Mnenje knjižničarjev o e-izobraževanju. V Knjižničarske [10] Zakon o knjižničarstvu. 2015. Dostopno na naslovu: novice. Dostopno na naslovu: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO2442 (4. 8. 2022) http://www.dlib.si/stream/URN:NBN:SI:DOC-7FVZ2H9N/15cb3bc3- [11] Posodobitve pouka v osnovnošolski praksi. Knjižnično informacijsko znanje. 43bd-4711-94d9-d548fc595b94/PDF (9. 8. 2022) 2014. Zavod RS za šolstvo, Ljubljana, Dostopno na naslovu: [4] Škrlj, G. 2006. Management kadrovskih virov v knjižnici: izobraževanje in http://www.dlib.si/details/URN:NBN:SI:DOC-ABAUB0ON (10. 8. 2022) usposabljanje kadrov v visokošolskih knjižnicah Univerze v Ljubljani. G. Škrlj, Ljubljana 523 Airnominal Airnominal Filip Štamcar Jakob Kralj Alenka Mozer Gimnazija Vič Gimnazija Vič Gimnazija Vič Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija filip.stamcar@hotmail.com jakob.kralj04@gmail.com alenka.mozer@gimvic.org POVZETEK researchers need to be able to obtain many higher quality data in a standardized format. To address this problem, we decided to Problem onesnaženosti zraka je eden izmed najbolj akutno build an open platform of air quality measuring stations, which nevarnih ekoloških problemov, s katerimi se danes soočamo. enables people to connect and exchange air quality Glede na študije Svetovne zdravstvene organizacije skoraj vsi measurements. We also wanted to provide a design of an open prebivalci sveta dihajo zrak, ki presega priporočene vrednosti measuring station that anyone could build and connect to the WHO in vsebuje visoke ravni onesnaževal. Čeprav so senzorji in platform. In this way, citizens would be contributing valuable druga merilna oprema že dolgo na voljo, podatki, ki jih information for local air research, revealing the main uporabljajo raziskovalci, običajno prihajajo z dveh do treh postaj sources/causes of high air pollutants concentrations; when na nekem območju, velike zbirke podatkov z visoko prostorsko working on our project, only PM sensors were easy to get to ločljivostjo pa niso na voljo. Da bi raziskovalci lahko preverili, (Covid-19 crisis interfered with the shipments all over the world). ali je katera koli rešitev, ki obravnava kakovost zraka, dejansko In future, nitrous oxides and ozone sensors will be added, when učinkovita, morajo imeti možnost pridobiti veliko podatkov višje reasonable price sensors of acceptable quality will be available kakovosti v standardizirani obliki. Da bi rešili to težavo, smo se on the market again. odločili, da zgradimo odprto platformo merilnih postaj za kakovost zraka, ki ljudem omogoča povezovanje in izmenjavo KEYWORDS meritev kakovosti zraka. Prav tako smo želeli zagotoviti zasnovo odprte merilne postaje, ki jo lahko vsakdo zgradi in poveže s Air pollution, air monitoring, PM (particulate matter), public platformo. Na ta način bi državljani prispevali dragocene health, climate change, ecology informacije za lokalne raziskave zraka in razkrili glavne vire/vzroke visokih koncentracij onesnaževal v zraku; med delom na našem projektu je bilo enostavno priti le do senzorjev 1 UVOD PM (kriza Covid-19 je ovirala pošiljke po vsem svetu). V Med vsemi ekološkimi problemi, s katerimi se danes soočamo, prihodnosti bodo dodani senzorji dušikovih oksidov in ozona, ko je le malo takšnih, ki so bolj nevarni kot problem onesnaženosti bodo na trgu spet na voljo cenovno sprejemljivi senzorji zraka. Glede na študije Svetovne zdravstvene organizacije skoraj sprejemljive kakovosti. vsi prebivalci sveta dihajo zrak, ki presega priporočene vrednosti WHO in vsebuje visoke ravni onesnaževal. Onesnaženost zraka KLJUČNE BESEDE je priznana kot dejavnik tveganja za številne bolezni, vključno z Onesnaženost zraka, spremljanje zraka, PM (trdi delci), javno ishemično boleznijo srca, možgansko kapjo, kronično zdravje, podnebne spremembe, ekologija obstruktivno pljučno boleznijo, astmo in rakom. Ocenjuje se, da so bolezni, ki jih pripisujejo onesnaženosti zraka, zdaj ABSTRACT enakovredne drugim zdravstvenim tveganjem, kot sta nezdrava The problem of air pollution is one of the most acutely dangerous prehrana in kajenje tobaka, ter da je samo ta težava vzrok za več ecological problems we face today. According to studies made kot 7 milijonov smrti na leto (to je več ljudi, kot je prebivalcev by World Health Organization, almost all of the global 12 držav članic EU). [1, p. 7] [2] population breathe air that exceeds WHO guideline limits Problem je znan že vrsto let, senzorji in druga merilna containing high levels of pollutants. Even though sensors and oprema pa so poceni in lahko dostopni. Za veliko mladih, tudi za other measurement equipment is already available, data that naju, je bilo zbiranje podatkov o meritvah zraka morda prvi researchers use usually comes from two to three stations in an projekt z Arduinom. Kljub temu podatki, ki jih uporabljajo area, and large datasets of high spatial resolution are not available. raziskovalci, še vedno običajno prihajajo z dveh ali treh postaj na To test if any solution addressing air quality is in fact effective, nekem območju, velike zbirke podatkov z visoko prostorsko ločljivostjo pa niso na voljo. Da bi lahko preizkusili, ali je katera Permission to make digital or hard copies of part or all of this work for personal or koli rešitev, ki obravnava kakovost zraka, dejansko učinkovita, classroom use is granted without fee provided that copies are not made or distributed morajo imeti raziskovalci možnost pridobiti veliko podatkov for profit or commercial advantage and that copies bear this notice and the full višje kakovosti v standardizirani obliki. 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). Glede na to težavo smo se odločili, da bomo vzpostavili Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia odprto platformo za zbiranje podatkov z merilnih postaj za © 2022 Copyright held by the owner/author(s). merjenje kakovosti zraka; ta platforma bi ljudem omogočila 524 povezovanje in izmenjavo meritev kakovosti zraka, vključno z Knjižnica prek omrežja Wi-Fi ali drugih komunikacijskih vlago, temperaturo, koncentracijo delcev PM, dušikovimi oksidi protokolov podatke pošlje na centralen strežnik, kjer se shranijo. (NOx ) in koncentracijo ozona. Delimo tudi našo zasnovo odprte Vsi podatki so brezplačni in javno dostopni prek http merilne postaje, ki jo lahko vsakdo zgradi in poveže s platformo programskega vmesnika ter posebne spletne strani za ter tako zagotovi dragocene informacije za raziskave ter razkrije prikazovanje podatkov. glavne vire/vzroke visokih koncentracij delcev PM. Podatke si je mogoče ogledati tudi prek spletne strani, kjer Poleg tega ta projekt mladim omogoča, da se naučijo so na voljo tudi navodila za nastavitev lastnih merilnih naprav in programiranja, spajkanja in konstrukcijskih spretnosti ter njihovo registracijo na strežnik. Po registraciji naprave izboljšajo svoje znanje o meritvah onesnaženosti in kakovosti uporabniki dobijo posebno konfiguracijo, ki jo morajo nato zraka. nastaviti na njivi merilni napravi. V prihodnosti nameravamo na spletno stran dodati še več funkcionalnosti, povezanih z upravljanjem podatkov in merilnih naprav. 2 PREGLED LITERATURE Uporabniki si lahko ogledajo zemljevid vseh trenutno Onesnaženost zraka je eden izmed najbolj nevarnih okoljskih aktivnih postaj ali izberejo določeno postajo in si ogledajo vse problemov. Večina svetovnega prebivalstva diha zrak, ki presega pretekle podatke. Na strani za posamezno postajo so prikazane mejne vrednosti, ki jih priporoča Svetovna zdravstvena tudi trenutne meritve, pretekli podatki s pomočjo razumljivih organizacija, pri čemer so najbolj prizadete države z nizkimi in grafov ter trenutne in vse pretekle lokacije na zemljevidu. srednjimi dohodki. Znano je, da je onesnaženje zraka pomemben Izberete lahko tudi več postaj in primerjate njihove podatke. vir obolevnosti in umrljivosti ter prispeva kot dejavnik tveganja Raziskovalci, ki morajo analizirati veliko količino podatkov, za številne bolezni, vključno z boleznimi srca, kroničnimi lahko prek vmesnika API neposredno prenesejo pretekle podatke. obstruktivnimi pljučnimi boleznimi in akutnimi okužbami dihal. Strežnik omogoča tudi omejitev podatkov na določeno datumsko Ocenjuje se, da onesnaženost zraka v zaprtih prostorih in okolice območje, postajo ali vrsto meritev, tako da jim ni treba skrbeti za skupaj povzroči približno 8 milijonov prezgodnjih smrti na svetu filtriranje podatkov in se lahko osredotočijo na svoje raziskave. letno. [3] [4] Ta funkcionalnost je lahko zelo uporabna za raziskovalce ali Onesnaževanje zraka povzročajo vsi kemični, fizikalni ali druge posameznike ali organizacije, ki morajo lokalno izvajati biološki dejavniki, ki spreminjajo lastnosti zraka. Glavni viri naprednejše analize. onesnaževanja zraka so domače kurilne naprave, industrijski Projekt je odprtokoden in na voljo na spletnem mestu obrati in motorna vozila. Glavna onesnaževala so trdni delci GitHub: https://github.com/ChristofferNorgaard/Airnominal (PM), ogljikov monoksid (CO), dušikov dioksid (NO2), žveplov Uradna instanca je trenutno nameščena na strežnikih šole: dioksid (SO2) in ozon (O3). https://zrak.gimvic.org/ Trdni delci (PM) so pogost kazalnik onesnaženosti zraka in prizadenejo več ljudi kot katero koli drugo onesnaževalo. 3.2 Analiza podatkov Sestavljajo ga predvsem sulfati, nitrati, amonijak, natrijev klorid, Želeli smo vključiti in analizirati podatke, pridobljene na črni ogljik, mineralni prah in voda, kompleksna mešanica trdnih nekaj lokacijah v Sloveniji (slika 1). Žal zaradi nepredvidljivih in tekočih delcev, suspendiranih v zraku. Običajno se razvršča v razmer pri pošiljanju senzorjev s Kitajske nismo mogli izvesti različne kategorije PMx , kjer "x" določa največji premer delcev vseh želenih vrst meritev, vendar nam je uspelo pridobiti vsaj v μm. Najpogostejši kategoriji sta PM10 in PM2.5 . Delci PM10 meritve temperature, vlage in PM z nekaj postaj. najpogosteje vplivajo na oči in grlo, delci PM2.5 pa so še Naša šola se nahaja tik ob Tržaški cesti, eni glavnih nevarnejši, saj lahko skozi pljuča potujejo v krvni sistem. Ko so ljubljanskih prometnic. Da bi analizirali, kako promet vpliva na na voljo občutljivejša merilna orodja, se delci običajno razdelijo kakovost zraka v kraju, smo se odločili, da na naši šoli postavimo v dodatne kategorije, kar omogoča boljšo analizo delcev. Manjši dve postaji, eno obrnjeno proti ulici in eno proti dvorišču. kot so, globlje v dihala in krvni sistem lahko prodrejo, kar povzroča vedno večje tveganje. Kronična izpostavljenost delcem prispeva k boleznim srca in ožilja ter dihal in pljučnemu raku. [4] [5] 3 REZULTATI 3.1 Delovanje platforme Naše merilne postaje so trenutno sestavljene iz mikrokrmilnikov Slika 1: Meritve s šolske postaje, obrnjene na šolsko Arduino in ESP, na katere je mogoče priključiti senzorje dvorišče (od 2022-04-13 do 2022-04-14) temperature, vlage, PM in druge senzorje ter modul GPS za določanje lokacije postaje. Postaja zbira meritve iz senzorjev in Opažamo, da se koncentracija delcev PM10 in PM2.5 prvič modula GPS ter jih s pomočjo naše knjižnice pošilja v naš poveča okoli 21.00, kar je zelo verjetno posledica zaprtja strežnik. Uporabniki lahko merilne postaje izdelajo tudi iz drugih bližnjega nakupovalnega središča, ponoči se pojavi nekaj skokov, krmilnikov, kompatibilnih z Arduino sistemom, ter nanje zjutraj pa tudi velik skok, ki ga povzročijo ljudje, ki se vozijo na priključijo poljubne senzorje in jih povežejo na platformo s delo. Čez dan je bila koncentracija večinoma nizka. Žal nam pomočjo programske knjižnice. zaradi nedostopnih senzorjev še ni uspelo postaviti postaje, 525 obrnjene proti ulici, vendar jo nameravamo postaviti, ko jih ter izboljšujejo svoje spretnosti programiranja, spajkanja, bomo pridobili. konstruiranja in fine motorike. Naš projekt omogoča šolam in Vzpostavili smo tudi uvoz urnih meritev, ki jih zagotavlja drugim izobraževalnim ustanovam, da si aktivno prizadevajo za Agencija Republike Slovenije za okolje (ARSO), tako da je izboljšanje teh spretnosti, hkrati pa pripomorejo k zbiranju mogoče naše postaje primerjati z uradnimi in strokovnimi znanstvenih podatkov. meritvami (slika 2). Postaje ARSO se nahajajo na različnih Na začetku bo naš izdelek namenjen posameznikom in lokacijah v Sloveniji, zato je mogoče njihove meritve izobraževalnim ter drugim javnim ustanovam. Z razvojem neposredno primerjati z našimi. platforme bo raziskovalcem na voljo vedno več podatkov, kar bo povečalo znanstveno in tržno vrednost projekta. Pridobivanje povratnih informacij od posameznikov in raziskovalnih organizacij nam bo omogočilo nenehno izboljševanje naše platforme, da bo boljša in še bolj uporabna za različne uporabnike. Povezali se bomo z lokalnimi skupnostmi in klubi, ki nam bodo pomagali pri promociji projekta, ter na oddaljenih lokacijah namestili merilne naprave in tako povečali pokritost s podatki Slika 2: Primerjava med šolsko postajo in postajo ARSO na ZAHVALA istem območju (od 2022-04-13 do 2022-04-14) Zahvaljujemo mentorici Alenki Mozer za pomoč in podporo pri Naše meritve večinoma kažejo višje koncentracije, vendar še projektu ter prof. dr. Griši Močniku za seznanitev s problemom vedno sledijo enakim trendom kot uradna postaja. Razlog za to onesnaženosti zraka. je, da je postaja ARSO precej bolj oddaljena od ulice (približno 1 km), medtem ko je naša postaja oddaljena le eno stavbo. Iz LITERATURA IN VIRI naših grafov je tudi razvidno, da na delce PM2.5 veliko bolj vpliva oddaljenost od vira (ulice) kot na delce PM10 . [1] World Health Organization, "WHO global air quality guidelines," 2021. [Online]. Available: Vse meritve z vseh postaj so na voljo tudi na naši spletni https://apps.who.int/iris/rest/bitstreams/1371692/retrieve. strani (https://zrak.gimvic.org/). [2] World Health Organization, "Air pollution," [Online]. Available: https://www.who.int/health-topics/air-pollution. [3] World Health Organization, "Household air pollution and health," 22 09 2021. [Online]. Available: https://www.who.int/news-room/fact- 4 ZAKLJUČEK sheets/detail/household-air-pollution-and-health. [4] World Health Organization, "Ambient (outdoor) air pollution," 22 09 2021. Glavni edinstveni vidik našega projekta je, da uporabnikov ne [Online]. Available: https://www.who.int/news-room/fact- omejuje na nobeno določeno merilno postajo in jim omogoča, da sheets/detail/ambient-(outdoor)-air-quality-and-health. [5] L. Lattanzio, "Particulate Matter Sensing for Air Quality Measurements," 27 opremo popolnoma prilagodijo svojim potrebam. Poleg tega 12 2018. [Online]. Available: odprtost naše platforme s podporo za postaje po meri spodbuja https://www.fierceelectronics.com/components/particulate-matter-sensing- for-air-quality-measurements. ljudi, da oblikujejo svoje izdelke, se učijo o pomembnih temah 526 Vpliv osebnostnih lastnosti starejših ljudi na zadovoljstvo uporabe ADC sistema za mobilno upravljanje senčil The Influence of Personality Characteristics of Elderly People on the Satisfaction of Using the ADC System for Mobile Blind Control Tanja Todorović Aleksandar Dojčinović Univerza PIM, Filozofska fakulteta ADC sistemi d.o.o. Banja Luka, Bosna in Hercegovina Kranj, Slovenija tanjatodorovic446@gmail.com adojci@gmail.com POVZETEK lastnosti ne vplivajo na sprejemanje in uporabljanje novih tehnologij. V prispevku bomo obravnavali problem starejših ljudi na 50 let in njihovo zadovoljstvo uporabe ADC sistema za mobilno KLJUČNE BESEDE upravljanje senčil. Podjetje ADC sistemi d.o.o. je slovensko podjetje, specializirano za mobilno upravljanje električnih senčil. Osebnostne lastnosti, velikih 5 faktorjev osebnosti, krmilnik, Podjetje razvija inovativne rešitve na področju senčil, pergol, uporabniška izkušnja garažnih vrat, ramp, kontrole pristopa itd... Razvoj programske ABSTRACT in strojne opreme so v celoti ustvarili slovenski inženirji, proizvedena pa je s pomočjo partnerskih podjetij v Sloveniji. In this article, we will discuss the problems and satisfaction of Rezultat so tehnološko dovršeni in zanesljivi produkti, razviti v using the ADC system for mobile control of blinds in persons skladu s predpisi Evropske unije. Vizija podjetja je razvoj over the age of 50. The company ADC sistemi d.o.o. is a opreme za upravljanje vseh vrst senčil (rolete, žaluzije, screen Slovenian company specializing in mobile control of electric senčila, tende, komarniki, pergole) in upravljanje različnih vrat blinds. The company is developing innovative solutions in the (garažna vrata, vhodna vrata, rampe,…). V prispevku smo fields of window blinds, pergolas, garage doors, ramps, access predstavili rezultate zadovoljstva uporabe ADC sistema, ki je control, etc... The software and hardware are completely zanesljiv, varen in enostaven in je prilagojen starejšim ljudem. developed by Slovenian engineers and produced with the help of Slovenian partner companies. The result is technologically Namen prispevka je raziskati, enostavno opisati ter predstaviti complete and reliable products, developed in accordance with the osebnostne lastnosti starejših uporabnikov po modelu »velikih regulations of the European Union. The company's vision is the pet faktorjev osebnosti« in njihovo zadovoljstvu ob uporabi development of products for managing all types of blinds (roller ADC sistema. V današnjem času večina ljudi misli, da se starejši shutters, venetian blinds, textile screens, awnings, insect screens, ljudje ne morejo navaditi na novo tehnologijo in jo ne bodo pergolas) and doors (garage doors, entrance doors, ramps, ...). In sprejeli. Cilj prispevka je analizirati ter teoretično in praktično the article, we present results about the satisfaction of using the utemeljiti, da vsi starejši ljudje zelo dobro sprejmejo ADC sistem ADC system, which is reliable, safe, easy to use, and adapted for za mobilno upravljanje senčil. use by older persons. Pri pisanju smo se osredotočili na analizo primarnih in The purpose of this article is to research, describe simply, and sekundarnih virov, s primerjalno analizo in študijo primera smo present the personality traits of older users with the use of the na podlagi kritične analize zbranih podatkov podali končno "big five personality traits" model as well as their satisfaction oceno. with using the ADC system. Nowadays most people think that older people cannot get used to new technology and will not V prispevku smo predstavili 5 ključnih osebnosti človeka (nad adopt it. The goal of this article is to analyze and theoretically 50 let) in korelacijo teh osebnosti na sprejemanje nove and practically show that the ADC system for mobile control of tehnologije ADC sistema za mobilno upravljanje senčil. Starejši blinds is very well received by older persons. ljudje so tehnologijo sprejeli zelo dobro in jo bodo v nadaljevanju uporabljali, tako da lahko trdimo, da starost in osebnostne During the writing of this article, we focused on the analysis of primary and secondary sources, and with comparative analysis Permission to make digital or hard copies of part or all of this work for personal or and example study we gave based on critical analysis of collected classroom use is granted without fee provided that copies are not made or distributed data a final score. 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 In the article, we present the 5 key human traits (of persons over be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia the age of 50) and the correlation between personality and how © 2022 Copyright held by the owner/author(s). the new technology of the ADC system for mobile control of 527 blinds is received. The technology was received by older persons pet faktorjev osebnosti« ter seznaniti bralce z psihološkimi very well and they will continue to use it in the future, as such, elementi, ki bi jim pomagali pri razumevanju tega prispevka. we can conclude that age and personality traits do not affect the Drugi cilj našega prispevka je predstaviti vpliv osebnostnih reception and usage of new technologies. lastnosti starejše populacije nad starostjo 50 let glede na model » velikih pet faktorjev osebnosti« o uporabi ADC sistema za KEYWORDS mobilno upravljanje senčil, ki bo olajšala krmiljenje senčil Personality traits, big 5 personality factors, controller, user starejšim ljudem. Tretji cilj našega prispevka je starejšim ljudem experience predstaviti in jim dati na uporabo ADC sistem za mobilno upravljanje senčil, ter odkriti prednosti in slabosti ADC sistema ter odkriti napake in grožnje, s katerimi se soočajo starejši ljudje 1 UVOD pri uporabi le teh. Tehnologija se danes hitro menja. To je razlog, da so podjetja 1.3 Predpostavke in omejitve inovativna, podajajo ideje, stremijo k izobraževanju, izboljšujejo svoje produkte ter stremijo k medsebojnemu sodelovanju in V prispevku kot predpostavko navajamo zlorabo varstva osebnih zaupanju med uporabniki. Tehnologija z omenjenimi lastnostmi podatkov. Predpostavimo lahko, da na podlagi prejšnjih je bolj produktivna in zanesljiva, kar vodi v vse večjo uspešnost ugotovitev psiholoških osebnostnih lastnosti ter njihov vpliv na organizacije. Za uporabnike in podjetja so pomemben osebne uporabo ADC sistemov postavimo model, da bo čim bolj značilnosti, saj z značilnostmi, ki jih imamo in ki jih od nas enostaven za starejšo populacijo in primeren za proizvajalce zahteva tehnologija, bomo lahko preživeli in ostali v koraku z senčil. časom. Glavna omejitev našega prispevka bo najti starejše ljudi nad Od osebnih značilnosti uporabnika je odvisno, ali stremimo starostjo 50 let, ki bo želelo sodelovati in odgovarjati na k izobraževanju, ali sodelujemo s podjetjem, kako se odzovemo vprašanja, ki jih večina ljudi ne želi razkriti. Kot omejitev pa v stresnih situacijah in kako bomo sprejeli novo tehnologijo. lahko izpostavimo obseg ter zapletenost preučevanja psiholoških Nekatere osebne značilnosti so prirojene, druge pa pridobljene osebnostnih lastnosti in njihov vpliv na uporabo ADC sistemov. skozi različna življenjska obdobja. Na osebnost močno vpliva družina, družba okolje, vzgoja, saj je osebnost posameznika 1.4 Metodologija sestavljena iz celote telesnih, vedenjskih in duševnih značilnosti, Pregledali bomo literaturo po različnih svetovnih bazah, kot so zato lahko rečemo, da je celota trajna, kompleksna in Web of Science, Scopus, Google Scholar in Research Gate. individualna. Osebne lastnosti izvirajo od vsakega posameznika Literaturo bomo iskali z ključnimi besedami: personality traits, v dani situaciji ter iz interakcije med posameznikom in situacijo big five, IoT, blinds. [1]. Anketa je bila zaprtega tipa, kar pomeni, da anketiranci ne vpisujejo lastnih mnenj ampak za vsako trditev obkrožijo 1.1 Predstavitev problema odgovor, ki opisuje njegovo strinjanje oz. nestrinjanje (1 – Vsak človek ima značilne osebnostne lastnosti. Te lastnosti popolnoma se ne strinja, 2 – delno se ne strinjam, 3 – nisem pogojujejo vedenje v vsakdanjem življenju in v različnih prepričan, 4 - delno se strinjam, 5 – popolnoma se strinjam). situacijah. Obstaja veliko dejavnikov, ki vplivajo na vedenje Vzorec v tej raziskavi vključuje 58 ljudi, starih od 50 do 70 let, posameznika, kombinacije teh dejavnikov in osebnostnih ki uporabljajo ADC sistem za mobilno upravljanje električnih lastnosti pa ustvarjajo razlike med ljudmi. Prav zato ob senčil. Anketni vprašalnik je bil izveden s pomočjo spletne upoštevanju dejstva, da se tehnološki dosežki razvijajo z veliko ankete preko Google Forms. Povezavo smo poslali po hitrostjo, pojavila se je ideja, da bi bilo treba tehnologijo elektronski pošti vsem uporabnikom ADC sistemov, ki so uporabiti za izboljšanje kakovosti življenja starejših ljudi. starejši od 50 let. Vsi anketiranci so se strinjali, da bo Vendar, kot je bilo že omenjeno, ljudje na različne načine prostovoljno sodelujejo v tej raziskavi, pri čemer so se strinjali, pristopajo in sprejemajo nove stvari in situacije, še posebej ko da je njihova zasebnost varovana in da bodo njihovi podatki gre za starejšo populacijo. Zaradi tega razloga, pomembno je uporabljeni izključno v znanstveno-raziskovalne namene. preučiti vpliv osebnostnih lastnosti na uporabo pametnih Raziskava je potekala v obdobju od junija do avgusta 2022. sistemov oz. v nadaljevanju ADC sistema za mobilno upravljanje Ob zaključku ankete smo samodejno beležili podatke o senčil. Na podlagi pregledane literature nismo zasledili študije, rešenih anketah, ki smo jih izvozili v program za statistično ki bi se ukvarjale s tem vprašanjem. analizo IBM SPSS in pa v Microsoft Excel. Primerjava spola oziroma med moškim in žensko kaže vpliv V prispevku bomo analizirali in predstavili podatke, ki smo na osebnostne značilnosti in sicer pri ženskah je veliko bolj jih dobili z pomočjo ankete, ki bo sestavljena iz dveh delov. V izražena ekstravertnost in sprejemljivost [2]. Kot ugotavlja prvem delu ankete je bila za ocenjevanje uporabljena skrajšana MacDonald da so razlike med moško in žensko populacijo v verzija različice vprašalnika » Big Five Plus Two« [5]. V drugem splošnem minimalne oziroma zanemarljive [3]. Avtorja Phares delu ankete so vprašanja, ki so vezana na zadovoljstvo uporabe in Chaplin pa sta mnenja, da se moški in ženske razlikujejo v ADC sistema. vseh osebnostnih dimenzijah razen pri dimenziji odprtosti [4]. Delovna hipoteza je: Starejša populacija sprejema uporabo ADC sistema za mobilno upravljanje senčil. 1.2 Cilj Z nastankom našega prispevka želimo doseči tri cilje. Prvi cilj prispevka je preučiti psihologijo osebnosti po modelu » velikih 528 2 PREGLED LITERATURE Vestnost kot osebnostna lastnost ima tudi svoje negativne strani. Pretiravanje včasih vodi v obsedenost. Pretirana predanost delu 2.1 Velikih pet faktorjev osebnosti in deloholičnost vodita v zanemarjanje drugih vidikov življenja, Costa in McCraejev model velikih pet faktorjev osebnosti je eden dolžnosti, oseb in potrebe. Ljudje z nizko oceno na tej dimenziji od najbolj znanih modelov osebnosti in velja za najbolj ponavadi hitro obupajo in imajo manjša pričakovanja do sebe in sprejemljivo teorijo osebnosti v znanstveni skupnosti. Njihova do drugih[5]. raziskava temelji na predhodnih empiričnih in teoretičnih Odprtost se nanaša na sprejemanje novih idej, pristopov in raziskavah, kjer jim je z raziskavo uspelo v svojem modelu izkušenj ter je povezana z ustvarjalnostjo. To so ljudje, ki imajo predstaviti veliko število osebnostnih lastnosti [6,7]. sposobnost videti realnost iz širše perspektive. Visoka ocena je Model velikih pet faktorjev osebnostnih lastnosti se je pokazatelj ustvarjalnosti, radovednosti, širokih interesov, izkazal za doslednega in stabilnega. Posameznike so namreč izvirnosti in domišljije. Takšni ljudje so navdušeni nad spremljali skozi leto, da bi pokazali in dokazali stabilnost inovativnostjo. Po drugi strani pa ljudje z nizkimi rezultati na tej osebnostnih lastnosti oziroma kako se lastnosti osebnosti ne dimenzije imajo ozke interese, so bolj konzervativni in se spreminjajo, niti nanje ne vplivajo zunanji dejavniki [7]. Nadalje, počutijo bolj udobno z znanimi stvari [5]. Jensen pravi, da lahko vsako osebnostno lastnost obravnavamo Nevroticizem: čustvena stabilnost je dimenzija, ki jo imajo kot kontinuum, tj. posamezniki so lahko visoko ali nizko na vsaki uravnoteženi ljudje, katerih čustva ne vplivajo na vedenje. ravni od petih faktorjev. Vsaka oseba se nahaja v določenem delu Takšni ljudje se znajo upreti lastnim nagonom in prenagljenim kontinuuma za vsak faktor in tako tvori kompleksno sestavo odločitvam, saj jih pri odločanju in na splošno v življenju vodi kombinacij, ki so značilne za osebnost določenega posameznika. razum. Posledica odsotnost čustvene stabilnosti je nevroticizem. Posameznik ima lahko prevladujočo osebnostno lastnost in lahko Nevroticizem je značilen za ljudi, ki so nagnjeni k močnemu imam osebnostno lastnost, ki je v središču kontinuuma in v tem čustvenemu doživljanju ter težkemu prenašanje in prilagajanje primeru ta osebnostna lastnost nima posebej izrazitega vpliva na na življenjske spremembe. Pomembno je poudariti, da ta posameznika. Ta model je sestavljen iz naslednjih faktorjev: dimenzija ni patocentrična in da ljudje z visokimi fasetami v tej 1. Sprejemljivost, dimenziji ne rabijo imeti kakršno koli psihiatrično motnjo [5]. 2. Ekstravertnost, 2.2 VPRAŠALNIK VELIKIH 5 PLUS 2 3. Vestnost, 4. Odprtost, Vprašalnik Velikih pet plus dva (ang. Big Five Plus Two) je bil 5. Nevroticizem. zgrajen na podlagi leksikalnih opisov osebnosti v srbskem Vsak faktor modela velikih pet faktorjev osebnosti velja za jeziku. Druga psiholeksikalna študija v srbskem jeziku, iz katere večplasten konstrukt, torej vključuje dve oz. več faset nižjega je izpeljan vprašalnik temelji na primeru po Telegenovi in reda [8,9]. Fasete predstavljajo skupino značilnosti (pridevniki), Wallerjevi neomejevalni metodologiji za izbiro opisa osebnosti ki opisujejo človekovo osebnost in so združene v širši, [10]. Vprašalnik je namenjen za ocenjevanje sedem dimenzij večdimenzionalni dejavnik, ki jih logično povezuje in pojasnjuje osebnosti na najvišjem hierarhičnem nivodju, od tega vsaka ter kaže na širšo sliko določene dimenzije osebnosti. vključuje dve ali tri ožje dimenzije. V skladu s tem ima vsaka od Sprejemljivost je dimenzija, ki jo imajo izjemno skromni sedmih lestvic vprašalnika ma dve ali tri podlestvice. Lestvica ljudje, katerih življenjska gonila in glavna motivacija je nevroticizem vključuje podlestvico anksioznost, depresija in nesebičnost in usmerjenost k drugim ljudem. Ljudje, ki imajo negativni efekt, lestvica ekstravertnost vsebuje podlestvico izraženo to osebnostno lastnost so kooperativni in prijazni. toplina, družabnost in pozitiven učinek, odprtost vsebuje intelekt Empatija omogoča, da vidijo situacijo iz perspektive nekoga in iskanje novih stvari, vestnost ima podlestvico vztrajnost, drugega, kar spodbuja k razumevanje in prosocialnemu način premišljenost in samodisciplina, agresivnost ima podlestvico postopanja. Ti ljudje so pošteni in prilagodljivi . Ljudje, ki imajo jeza, nepopustljivost in trdoživost, pozitivna valenca ima nizko oceno na tej dimenziji, so pogosto obrnjeni proti sebi, speriornost in pozitivna samopodoba in negativna valenca ima skeptični do namer drugih ljudi, neprilagodljivi, egocentrični, manipulativnost in negativna samopodoba. Vprašalnik vsebuje trmasti in pogosto so nesramni in sovražno nastrojeni. S svojim 184 postavk s petstopenjsko Likertovo lestvico [5]. pristopom odbijajo druge od sebe [5]. Ekstravertnost je opredeljena kot dimenzija, po kateri se 2.3 ADC SISTEMI ljudje razlikujejo glede na število medosebnih odnosev, ob Podjetje ADC sistemi d.o.o. je prvo in edino slovensko podjetje, katerih se dobro počutijo [5]. Za osebe z visoko oceno specializirano za mobilno upravljanje električnih senčil. ADC je ekstravertnosti je značilno veliko število medosebnih odnosov in eden od vodilnih svetovnih proizvajalcev visokokakovostnih večja verjetnost preživljanja časa z drugimi, pri nizki oceni pa je izdelkov za avtomatizacijo poslovnih in zasebnih objektov. ravno obratno. Take osebe poimenujejo intraverti. Ekstraverti so Podjetje ADC sistem je ustanovljeno leta 2020 in se je v 2 odprti, energični, družabni ljudje z izraženimi komunikacijskimi letih razvilo v mednarodno podjetje, ki ponuja inovativne rešitve sposobnostmi in so radi v središču pozornosti. Poleg teh v vseh državah Evropske unije. Razvoj temelji na pozitivnih strani obstajajo tudi negativne, to je, da so ti ljudje interdisciplinarnem pristopu in skupinskih metodah dela, in sicer precej čustveni in impulzivni, in pogosto jim je zanemarjena tudi v skladu s sodobnimi spoznanji različnih strok. Razvoj vzročno-posledična zveza določenih postopkov. programske in strojne opreme smo v celoti ustvarili slovenski Vestnost se nanaša na število ciljev, na katere smo inženirji, proizvedena pa je s pomočjo partnerskih podjetij v osredotočeni. Ti ljudje upoštevajo pravila in roki, in so zelo Sloveniji. Rezultat so tehnološko dovršeni in zanesljivi produkti, odgovorni. Odlikujeta jih izjemna disciplina in perfekcionizem. razviti v skladu s predpisi Evropske unije. Varnost in zanesljivost 529 ADC produktov postavljamo na prvo mesto, zato so vsi produkti testirani v naših raziskovalnih laboratorijih. Podpiramo upravljanje vseh vrst senčil (rolete, žaluzije, screen senčila, tende, komarniki, pergole ...) s telefonom, tabličnim računalnikom, spletnim portalom glasovnim upravljanjem ali s stikalom/tipalom. ADC omogoča širok nabor funkcionalnosti, zato je primeren za vsakega posameznika od povprečnih uporabnikov pa vse do naprednih. S pomočjo glasovnega upravljanja (Google Assistant, Alexa, Siri) lahko senčila upravljamo z govornimi ukazi. Poleg osnovnih funkcionalnosti lahko izbiramo med velikim naborom senzorjev, ki se uporabljajo za nadzor senčil. ADC aplikacija (sliki 1 in 2) omogoča priročen uporabniški vmesnik, kar pomeni da je preprosta in enostavna za uporabo. Na voljo je v Google Play, App Store, AppGallery in je brezplačna. Aplikacija je visoko zmogljiva, tako da se vsi procesi na aplikaciji hitro naložijo. Varnost je naše vodilo, zato so uporabniški podatki dobro zaščiteni in šifrirani. Naši strokovnjaki redno posodabljajo aplikacijo in jo nadgrajujejo z novimi funkcionalnostmi. Aplikacija je prilagojena vsem uporabnikom in jo lahko povežemo tudi z drugimi sistemi. ADC aplikacija je zaradi svojega dizajna, odzivnosti, preprostosti, zanesljivosti, varnosti, učinkovitosti najbolj priljubljena aplikacija za mobilno upravljanje električnih senčil. Aplikacija je na voljo v slovenskem jeziku, prav tako pa tudi v angleškem, nemškem italijanskem, hrvaškem, bosanskem in srbskem jeziku. Slika 2: Prikaz upravljanja žaluzij ADC krmilnik (slika 3) je naprava, zasnovana za brezžično upravljanje električnih senčil z uporabo mobilnega telefona, tabličnega računalnika, spletnega portala, glasovnega upravljanja ali pa stikala/tipala. Krmilnik je sodobna in edinstvena rešitev, saj za svoje delovanje potrebuje le elektriko in domače Wi-Fi omrežje. Namestitev krmilnika je enostavna. Slika 3: ADC krmilnik Slika 1: ADC aplikacija seznam naprav 530 3 REZULTATI Sprejemljivost 3.1 Značilnosti anketirancev Med 58 anketiranci je bilo 35 moških, kar predstavlja 60 % vseh Pogosto se prepiram z… 1.9 anketirancev in 23 žensk, kar predstavlja 40 % celotne populacije Sem vzkipljiv/a. 2.4 (Tabela 1). Pogosto nasprotujem… 2.3 Zlahka se razjezim. 2.6 Pogosto se jezim. 2.5 Tabela 1: Struktura anketirancev po spolu Pogosto nasprotujem… 2.2 Sem blage narave. 2.9 Rad/a ukazujem. 2.5 Delež Sem "težka" oseba. 2.2 Spol N v % Lahko rečem, da sem… 2.1 Moški 35 60% 1 2 3 4 5 Ženski 23 40% Slika 4: Sprejemljivost s povprečno oceno Skupaj 58 100% Starostna struktura anketirancev je prikazana v tabeli 2. Največ anketirancev, ki uporabljajo ADC sistem je bilo od 50 do Ekstraverzija 59 let, kar predstavlja 48 % vseh anketirancev. V naslednji starostni skupini od 60 do 69 let je bilo 20 anketirancev, kar znaša 34 % celotne populacije. Med 70 in 79 leti je bilo samo 8 Sem poln/a energije. 4 anketirancev oziroma 14 % od celotne populacije. Na koncu smo Z lahkoto se zbližam z… 4 imeli srečo, da smo imeli predstavnike nad 80 let in sicer 2 osebi Sem zelo družabna oseba. 4.1 Sem vesela oseba. oziroma 3 % celotne populacije. 4.4 Zelo sem prijazen/na. 4.3 Na splošno sem dobre… 4.2 Sem zgovorna oseba. 4.1 Tabela 2: Struktura anketirancev po starosti Sem prijetna oseba. 4.2 Rad/a imam ljudi. 4.3 Družim se z veliko ljudmi. 3.8 Delež Starost N v % 1 2 3 4 5 od 50 do 59 28 48% Slika 5: Ekstraverzija s povprečno oceno od 60 do 69 20 34% od 70 do 79 8 14% nad 80 2 3% Na sliki 5 je prikazana dimenzija ekstraverzija, ki smo jo merili z 10 trditvami in sicer: Skupaj 58 100% 1. Družim se z veliko ljudmi – 3,8. 2. Rad/a imam ljudi – 4,3. 3.2 Osebnostne značilnosti anketirancev 3. Sem prijetna oseba – 4,2. Sprejemljivost smo merili z 10 trditvami. Na sliki 4 so 4. Sem zgovorna oseba – 4,1. prikazani rezultati povprečja dimenzije sprejemljivosti. Merili 5. Na splošno sem dobre volje – 4,2. smo naslednje trditve: 6. Zelo sem prijazen/na – 4,3. 1. Pogosto se prepiram z drugimi ljudmi – 1,9. 7. Sem vesela oseba – 4,4. 2. Sem vzkipljiv/a - 2,4. 8. Sem zelo družabna oseba – 4,1. 3. Pogosto nasprotujem mnenju drugih – 2,3. 9. Z lahko se zbližam z ljudmi – 4. 4. Zlahka se razjezim – 2,6. 10. Sem poln/a energije – 4. 5. Pogosto se jezim – 2,5. 6. Pogosto nasprotujem drugim ljudem – 2,2. Podobno smo z 10 trditvami merili dimenzijo neuroticizma 7. Sem blage narave – 2,9. (slika 6). Trditve so urejene po padajočih rezultatih: 8. Rad/a ukazujem – 2,5. 1. Pogosto sem zaskrbljen/a – 2,7. 9. Sem "težka" oseba – 2,2. 2. Nimam veliko sreče – 2,8. 10. Lahko rečem, da sem čemerna oseba – 2,1. 3. Zlahka postanem maloduešn – 2,6. 4. Pogosto se počutim ogorčeno – 2,3. 5. Čutim, da je življenje krivično do mene – 2,3. 6. Pogosto se počutim krivega – 2,2. 531 7. Pogosto imam morje žalostnih misli – 2,1.  Nekatere umetnine v meni zbudijo močna čustva 3,1. 8. Pogosto čutim tesnobo - 1,9.  Nenehno se izpopolnjujem in napredujem 4. 9. Sem nesrečna oseba – 1,7.  Pogosto iščem informacije o stvareh, ki me zanimajo 10. Pogosto mislim, da življenje nima smisla – 1,6. 4,2.  Hrepenim po razburljivosti in novostih 3,5.  Jaz sem kreativna oseba 4,2. Neuroticizem 1.9 Odprtost Pogosto mislim, da… 1.6 2.2 Pogosto sem zaskrbljen/a. 2.7 Jaz sem kreativna oseba. 4.2 2.1 Hrepenim po… 3.5 Sem nesrečna oseba. 1.7 2.3 Pogosto iščem informacije… 4.2 Pogosto se počutim… 2.3 Nenehno se… 4 2.8 Zlahka postanem… Nekatere umetnine v… 2.6 3.1 Čutim, da mi novo znanje… 4.4 1 2 3 4 5 V življenju bi rad/a… 4.2 V prostem času počnem… 3.4 Imam različne interese. Slika 6: Neuroticizem s povprečno oceno 3.8 Spremljam novosti v… 3.1 0 1 2 3 4 5 Negativna valenca Slika 8: Odprtost s povprečno oceno Pogosto ogovarjam druge. 2.1 Včasih mislim, da sem… 1.6 Malo spletkarim. 1.7 Pozitivna valenca Rad vtikam nos povsod. 1.7 Pogosto lažem. 1.6 Pogosto izkoriščam druge. 1.3 O sebi imam zelo visoko… 3.3 Ni mi problem nekoga… 1.3 Sem vplivna oseba. 2.5 Uživam, ko se me drugi… Sem močna oseba. 1.8 4.1 Pogosto se norčujem iz… Sem pomembna oseba. 1.5 2.5 Mislim, da imam nekaj… Pogosto provociram druge. 3.8 2 Ustvarjen sem bil za velika… 3.5 1 2 3 4 5 Mislim, da sem zelo… 3.6 Jaz sem modra oseba. 3.7 Sem očarljiva oseba. 3.5 Slika 7: Negativna valenca s povprečno oceno Jaz sem rojeni zmagovalec. 3.7 1 2 3 4 5 Slika 7 prikazuje 10 trditev za negativno valenco in sicer: 1. Pogosto provociram druge – 2. Slika 9: Pozitivna valenca s povprečno oceno 2. Pogosto se norčujem iz drugih – 1,5. 3. Uživam, ko se me drugi bojijo – 1,8. Trditve, namenjene za pozitivno valenco so prikazane na sliki 9. 4. Ni mi problem nekoga prevarati – 1,3. Te trditve so: 5. Pogosto izkoriščam druge – 1,3.  Jaz sem rojeni zmagovalec - 3,7. 6. Pogosto lažem – 1,6.  Sem očarljiva oseba – 3,5. 7. Rad vtikam nos povsod – 1,7.  Jaz sem modra oseba – 3,7. 8. Malo spletkarim – 1,7.  Mislim, da sem zelo nadarjen - 3,6. 9. Včasih mislim, da sem grozljiva oseba – 1,6.  Ustvarjen sem bil za velika dela – 3,5. 10. Pogosto ogovarjam druge – 2,1.  Mislim, da imam nekaj posebnih lastnosti – 3,8.  Sem pomembna oseba - 2,5. Na sliki 8 vidimo trditve za dimenzicjo odprtosti in sicer te so:  Sem močna oseba – 4,1.  Spremljam novosti v umetnosti (glasba, film,  Sem vplivna oseba – 2,5. literatura...) – 3,1.  O sebi imam zelo visoko mnenje – 3,3.  Imam različne interese 3,8.  V prostem času počnem veliko zanimivih stvari 3,4. Dimenzija vestnosti (slika 10) se je obravnavala z naslednjimi  V življenju bi rad/a poizkusil/a čim več stvari 4,2. trditvami:  Čutim, da mi novo znanje bogati življenje 4,4.  Zelo sem vztrajen – 3,7. 532  Zame velja: kaj lahko narediš danes, ne pusti za jutri – 17. Grafični vmesnik aplikacije je pregleden in 2,2. prilagodljiv – 5.  Sem zelo pridna in delovna oseba – 1,7. 18. Za upravljanje senčil bi rajši izbral/a ADC aplikacijo  Vedno izpolnim vse svoje obveznosti – 2,3. kot pa daljinec – 5.  Vse kar začnem, to končam - 4. 19. ADC sistem mi je olajšal/a življenje.  V tem kar počnem, sem zelo temeljit/a – 3,9. 20. ADC sistem bi priporočil/a vsakemu.  Nagnjen/a sem k odlašanju - 4.  Pri obveznostih sem malomaren – 4,2.  Sem lena oseba – 3,7. Zadovoljstvo uporabe ADC  Pogosto najdem delo – 4,3. sistema Vestnost Zelo pogosto uporabljam… 5 Za premikanje senčil… 4.2 Aplikacija je enostavna za… 5 Pogosto najdem delo. 3.7 ADC aplikacijo uporabljam… 2.8 Sem lena oseba. 2.2 Stroški implementacije… 4.6 Pri obveznostih sem… 1.7 Všeč mi je, da ne… 5 Nagnjen/a sem k odlašanju. 2.3 Namestitev celotnega… 5 V tem kar počnem, sem… 4 Odzivnost aplikacije je… 5 Vse kar začnem, to končam. 3.9 Vse moje zahteve in… 4.3 Vedno izpolnim vse svoje… 4 Počutim se varnega z ADC… 4.8 Sem zelo pridna in… 4.2 Uporabljam pametne… 4.5 Zame velja: kaj lahko… 3.7 Pametni vremenski… 4.8 Zelo sem vztrajen. 4.3 Všeč mi je, da se krmilniki… 5 0 1 2 3 4 5 Verjamem, da se ADC… 4.3 Stroški gretja in hlajenja… 4.4 Povezava med ADC… 5 Slika 10: Vestnost s povprečno oceno Grafični vmesnik ADC… 5 Za upravljanje senčil bi… 5 3.3 Zadovoljstvo uporabe ADC sistema ADC sistem mi je olajšal/a… 4.6 Vsi anketiranci so uporabljali ADC sistem za mobilno ADC sistem bi priporočil/a… 4.9 upravljanje senčil in so podali mnenja na naslednje trditve (slika 1 2 3 4 5 11). 1. Zelo pogosto uporabljam telefon - 5. 2. Za premikanje senčil uporabljam stikala/tipkala – 4,2. Slika 11: Zadovoljstvo uporabe ADC sistema s povprečno 3. Aplikacija je enostavna za uporabo - 5. oceno 4. ADC aplikacijo uporabljam tudi na tabličnem računalniku – 2,8. 4 DISKUSIJA 5. Stroški implementacije ADC sistema so nizki – 4,6. 6. Všeč mi je, da ne potrebujem dodatne centralne enote V prispevku smo postavili hipotezo » Starejša populacija - 5. sprejema uporabo ADC sistema za mobilno upravljanje senčil«, 7. Namestitev celotnega ADC sistema je enostavna in ki smo jo preverjali v empiričnem delu naloge. Na podlagi nezahtevna - 5. rezultatov hipotezo potrdimo, saj so starejši ljudje pozitivno 8. Odzivnost aplikacije je zelo visoka - 5. sprejeli novo tehnologijo ADC sistemi in jo tudi zelo hitro 9. Vse moje zahteve in potrebe so vključene v ADC sprejeli kot del vsakdanja. sistem – 4,3. Pravijo da med starostjo in sposobnostjo sprejemanja novih 10. Počutim se varnega z ADC sistemom – 4,8. tehnologij ni korelacije oziroma starejša populacija težko 11. Uporabljam pametne vremenske scenarije brez sprejema nove stvari. Na podlagi raziskave lahko rečemo, da so dodatnih senzorjev – 4,5. bili starejši ljudje zadovoljni z ADC sistemom in so ga zelo hitro 12. Pametni vremenski scenariji so enostavni za uporabo – sprejeli. V primerjavi z starejšo tehnologijo daljincev, so se 4,8. starejši ljudje odločili, da bi rajši uporabljali ADC sistem kot pa 13. Všeč mi je, da se krmilniki povezujejo na domače Wi- daljinec. Fi omrežje (router) - 5. Med moškim in ženskim spolom ni razlik v osebnostnih 14. Verjamem, da se ADC sistemi nenehno izpopolnjujejo lastnostih po modelu velikih pet faktorjev osebnosti. Moški in in skrbijo za sistem – 4,3. ženske so si po želenih osebnostnih lastnostih zelo podobni, torej 15. Stroški gretja in hlajenja so manjši z ADC sistemom – spol nima nobenega vpliva na osebnost posameznika. 4,4. Rezultati so pokazali, da v povprečju osebnostne lastnosti 16. Povezava med ADC sistemi in domačim omrežjem je pozitivno vplivajo na sprejemanje uporabe ADC sistema. zanesljiva in varna – 5. Nekatere dimenzije se malo težje prilagodijo, nekatere pa zelo 533 hitro. Da bi dobili še bolj natančne rezultate, moramo vsako pretvori v Wi-Fi signal. Vsi sistemi se med seboj razlikujejo po dimenzijo še razdeliti v pod dimenzije, nato določiti osebnost ceni, velikosti, zmogljivosti, varnosti, prilagodljivosti, posameznika in mu dati na uporabo ADC sistem. Šele po uporabnosti itd… določenem številu istih vzorcev bi videli, katera dimenzija se ADC sistem je postavljen sodobno in poleg interneta za lažje prilagodi na novo tehnologijo, katera se pa težje. S tem bi delovanje ne potrebuje ničesar. ADC sistemi so v Sloveniji lahko še podrobneje preverili, katere dimenzije imajo velik vpliv najbolj priljubljeni sistemi za mobilno upravljanje senčil. Veliko in katere dimenzije imajo majhen vpliv na sprejemanje uporabe je bilo govora o tem, kako bo starejša populacija sprejela novo ADC sistema. tehnologijo ADC sistem, kjer so predpostavljali lastniki podjetij, V nadaljnje raziskave bi lahko vključili tudi vprašalnik BFQ, da se bodo starejši ljudje zelo težko oz. se ne bodo navadili na ki prav tako meri osebnostne značilnosti. BFQ vprašalnik novo tehnologijo. V prispevku lahko potrdimo da je starejša vsebuje 132 trditev. Tako bi lahko med seboj primerjali populacija sprejela uporabo ADC sistema za mobilno upravljanje pridobljene rezultate obeh vprašalnikov in jih med seboj električnih senčil. primerjali. Vprašalnik BFQ omogoča bolj poglobljene rezultate, saj poleg pet dimenzij modela velikih pet vključuje tudi deset podrejenih dimenzij. ZAHVALA Raziskave o osebnih značilnostih starejših ljudi in njihovo Zahvaljujeva se izr. prof. dr. Urošu Rajkoviču za pomoč in sprejemanje ADC sistema med pisanjem prispevka nismo podporo pri nastajanju projekta in prispevka. zasledili ne v slovenski ne v tuji literaturi. LITERATURA IN VIRI [1] Musek, J., 2002. Dimenzije in meje osebnosti. Dialogi, 38(9/10), 23-35. 5 ZAKLJUČEK [2] Cecić Erpić, S., Boben, D., Zabukovec, V., Škof, B., 2002. Dejanske in želene osebnostne lastnosti športnih pedagogov. Psihološka obzorja, 11(4), Temeljni cilj prispevka je preveriti povezanost osebnostnih 81-102. značilnosti v povezavi z zadovoljstvom uporabe ADC sistema za [3] MacDonald, K., 1995. Evolution, the five-factor model, and levels of mobilno upravljanje senčil. Da smo cilj dosegli smo najprej personality. Journal of Personality, 63(3), 525-567. [4] Phares, E. J., Chaplin, W. F., 1997. Introduction to personality. New York: preučili opredelitev osebnosti po modelu velikih pet faktorjev Longman. osebnosti. Model velikih pet sestavlja pet dimenzij mi smo pa [5] Smederevac, S., Mitrović, D., 2006. Ličnost-metode i modeli. Beograd: Centar za primenjenu psihologiju. uporabili zadnjo verzijo anketnega vprašalnika velikih pet plus [6] Costa, P. T., McCrae, R. R. (1992). Four ways five factors are basic. dve, kjer smo ugotavljali naslednje dimenzije: ekstravertnost, Personality and Individual Differences, 13, 653-665. [7] Jensen, M., 2015. Personality Traits, Learning and Academic Achievements. nevroticizem, vestnost, sprejemljivost, odprtost, pozitivna Journal of Education and Learning, 4(4), 91-118. valenca in negativna valenca, s katerimi smo ugotavljali [8] Digma, J M., 1990. Personality structure: Emergence of the five-factor osebnostne značilnosti, razlike med posameznimi dimenzijami in model. Annual Rewiev of Psychology, 41(1), 417-440. [9] Varvodić, I., 2016. Kupovno ponašanje i model »velikih pet« faktora ličnosti. razlike me spolom. Diplomsko delo. Dostopno na naslovu Tehnologija hitro napreduje in danes imamo kar nekaj https://repozitorij.efst.unist.hr/islandora/object/efst:896 (1.8.2022). [10] Waller, N. G., 1999. Evaluating the structure of personality. In C. R. sistemov za mobilno upravljanje senčil, ki delujejo preko Wi-Fi Cloninger (Ed.), Personality and psychopathology. Washington, DC; signala ali pa radijskega signala, ki se preko centralne enote American Psychiatric Press, 155-197. 534 Igrifikacija v visokošolskem izobraževanju: primer visokošolskih učiteljev in sodelavcev Gamification in Higher Education: The Case of Higher Education Teachers and Colleagues Marko Urh Eva Jereb Univerza v Mariboru Univerza v Mariboru Fakulteta za organizacijske vede Fakulteta za organizacijske vede Kranj, Slovenija Kranj, Slovenija marko.urh@um.si eva.jereb@um.si POVZETEK find that the gamification elements in higher education teachers and colleagues are both formal and informal in nature. The most Igrifiakcijo lahko opredelimo kot uporabo elementov igrifikacije important of them are presented in detail below. The v neigranih kontekstih. Najbolj poznani elementi igrifikacije so gamification elements have a great influence in higher education. točke, lestvice, nagrade in drugo. Izobraževanje je področje, kjer Some elements have an impact on the employee's personal se je igrifikacija zelo uveljavila. Igrifikacija v izobraževanju se income, promotion, employee status and more. najpogosteje omenja in uporablja pri študentih z namenom doseganja večje motiviranosti, angažiranosti in učinkovitosti. KEYWORDS Manj poznana in analizirana pa je igrifikacija, ki se uporablja pri visokošolskih učiteljih in sodelavcih. Članek obravnava Higher education, higher education teachers, higher education igrifikacjio na področju visokega šolstva, natančneje njene colleagues, gamification, gamification elements aplikacije pri visokošolskih učiteljih in sodelavcih. Slednji so v primerjavi z ostalimi javnimi uslužbenci najbolj izpostavljeni elementom igrifikacije. Ugotavljamo, da so elementi igrifikacije 1 UVOD pri visokošolskih učiteljih in sodelavcih, tako formalne kot Ljudje so se in se srečujemo z igrami skozi vso svojo zgodovino. neformalne narave. Najpomembnejši in najbolj znani izmed njih Igre najpogosteje povezujemo z zabavo, sprostitvijo, so predstavljeni v nadaljevanju. Elementi igrifikacije imajo v prostovoljno udeležbo in otroštvom. Igre so pomembne za otroke visokem šolstvu velik vpliv. Nekateri elementi vplivajo na kot tudi za odrasle, saj vplivajo na razvoj in počutje posameznika osebni dohodek zaposlenega, napredovanje, status zaposlenega in skupnosti ter predstavljajo pomembno psihološko in in drugo. fiziološko potrebo [1]. Igro lahko opredelimo kot "oblika igranja neke igre s cilji in strukturo" [2]. Najbolj poznane in prisotne KLJUČNE BESEDE sledeče igre [3]: športne igre, namizne igre, igranje vlog, Visokošolsko izobraževanje, visokošolski učitelji, visokošolski simulacije, poslovne igre in video igre (offline in online). Z sodelavci, igrifikacija, elementi igrifikacije razvojem informacijsko-komunikacijske tehnologije (IKT) so se spreminjale tudi igre. Prav zaradi IKT so se najbolj razvile video ABSTRACT igre. Na njihovo splošno razširjenost pa so vplivale številne nove Gamification can be defined as the use of gamification elements tehnologij, kot so igralne konzole, igralne platforme, mobilna in non-game contexts. The most familiar gamification elements telefonija, tablice in tehnologije za igranje [4]. IKT v igrah je are points, leaderboards, prizes, rankings and more. Education is omogočila zbiranje velike količine podatkov. V industriji iger se an area where gamification has become very popular. tako zbrani podatki analizirajo z namenom prilagajanja igre oz. Gamification in education is usualy used for students in order to njenega izboljšanja. Glavni namen video iger je zadržati igralca achieve greater motivation, engagement and efficiency. Less čim dlje časa v igri. Zato mora biti igra zanimiva in zabavna. V known and analyzed is gamification, which is used for higher industriji iger v ta namen uporabljajo tako imenovane elemente education teachers and colleagues. The article deals with igrifikacije. Najbolj poznani elementi igrifikacije so razni sistemi gamification in the field of higher education, more precisely its točk, značke, trofeje, lestvice, ravni, ugled, skupine naloge, applications for higher education teachers and colleagues. časovni pritisk, naloge, avatarji, virtualni svetovi in virtualna Compared to other civil servants, the higher education teachers trgovanja [5]. Uporabo teh elementov lahko označimo kot and colleagues are most exposed to gamification elements. We igrifikacijo (angl. gamification). Z igrifikacijo želimo vplivati na posameznikovo obnašanje in vedenje. Zaradi pozitivnih vplivov omenjenih elementov so se začela spoznanja ter elementi 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 igrifikacije iz industrije igre prenašati tudi na druga področja in for profit or commercial advantage and that copies bear this notice and the full industrije. Danes lahko najdemo elemente igrifikacije skoraj v citation on the first page. Copyrights for third-party components of this work must vseh industrijah in panogah. be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Eno izmed bolj zanimivih področij za uporabo igrifikacije je © 2022 Copyright held by the owner/author(s). zagotovo izobraževanje in visokošolsko izobraževanje pri tem ni 535 izjema. Najbolj znana je uporaba igrifikacije pri študentih, kjer skrbi za njihov razvoj. Umetniška akademija opravlja pretežno je njen glavni namen povečati motivacijo, angažiranost in umetniško in izobraževalno dejavnost s področij ene ali več učinkovitosti študentov pri študiju. Manj poznana ter znanstveno sorodnih oziroma med seboj povezanih umetniških disciplin in in strokovno analizirana pa je uporaba igrifikacije pri zaposlenih skrbi za njihov razvoj. Visoka strokovna šola opravlja v visokošolskem izobraževanju, ki sodelujejo v pedagoškem izobraževalno dejavnost s področja ene ali več sorodnih oziroma procesu. Zaposleni v visokošolske izobraževanju so na tak ali med seboj povezanih strok in skrbi za njihov razvoj.« drugačen način izpostavljeni elementom igrifikacije. V članku je Pri delu s študenti oz. pedagoškem delu v visokem šolstvu v nadaljevanju predstavljeno področij visokega šolstva, zasledimo različne akterje. Najbolj poznani nazivi so redni igrafikacije in elementi igrifikacije. Sledi pregled profesor, izredni profesor, docent, višji predavatelj, predavatelj najpomembnejših elementov igrifikacije s katerim se srečujejo in lektor. Omenjene uvrščamo med tako imenovane visokošolske visokošolski učitelj in sodelavci. Ti elementi imajo lahko velik učitelje. Osebe oz. nazive kot so asistent, bibliotekar, strokovni vpliv na posameznikovo aktivnost, kariero, dohodek kot tudi na svetnik, višji strokovni sodelavec, strokovni sodelavec in učitelj počutje in posameznikova občutja. Na visokošolske učitelje in veščin pa uvrščamo med tako imenovane visokošolske sodelavce imajo takšni elementi lahko pozitivne kot tudi sodelavce. Visokošolski učitelji in sodelavci so glavni nosilci negativne vplive. pedagoškega in raziskovalnega dela na univerzah oz. fakultetah. Kot bo prikazano v nadaljevanju so prav ti zaposleni podvrženi velikemu številu ocenjevanj, rangiranju, tekmovanju, 2 VISOKOŠOLSKO IZOBRAŽEVANJE razvrščanju ter drugimi elementi, ki jih lahko opredelimo kot Izobraževanje ima pomembno vlogo v življenju vsakega elemente igrifikacije v visokošolskem izobraževanju. posameznika. Temeljne cilje izobraževalnega sistema lahko hierarhično delimo na [6]: izobraževalne cilje, ki jih izobraževalnemu sistemu postavlja družba; izobraževalne cilje 3 IGRIFIKACIJA posameznih izobraževalnih programov, ki jih navadno Igrifikacija se začne resneje uvajati in proučevati šele od druge opredeljujejo posamezne stroke, seveda ob upoštevanju polovice leta 2010 [9]. Opredelitev igrifikacije lahko označimo prejšnjih; izobraževalne cilje v učnih načrtih predmetov, ki kot aktivnost z značilnostim iger, ki so vključene v dejavnosti, ki tvorijo posamezen izobraževalni program, s pomočjo katerih same niso igre [10]. Igrifikacija ima lastnosti značilne iger, ki so skušamo uresničiti izobraževalne cilje, postavljene na prejšnjih zabavne in privlačne ter so uporabljene za izboljšanje dveh nivojih. uporabniške izkušnje igralca v okolju brez iger (na delovnem Na spletnem portalu gov.si [7] lahko zasledimo, da je cilji mestu, šoli, aplikacijah ali spletnih straneh) [11]. Igre so visokošolskega izobraževanja v Sloveniji sledeč: »Osnovni cilji najpogosteje zasnovane tako (predvsem video igre), da skušajo slovenskega visokošolskega prostora so kakovost in odličnost, igralca čim hitreje vpelje v igro in ga obdržati v navidezni raznovrstnost ter dostopnost. Kakovost bo vsem omogočala povratni zanki sestavljeni iz akcije, povratne informacije in mednarodno primerljivo in priznano visokošolsko izobrazbo, s refleksije [12]. Namen igrifikacije je povečati določene aktivnost tem pa večje zaposlitvene možnosti ter mobilnost v evropskem ljudi in spodbujati določena vedenja [13]. Igrifikacijo lahko prostoru in svetu. Pri tem je pomembna socialna razsežnost, ki razumemo tudi kot zbirko orodij, ki se lahko uporablja za omogoča širok dostop do visokega šolstva in zagotavlja pogoje doseganje želenega vedenja [14]. za uspešno dokončanje študija.«. Na omenjenem spletnem Z igrifikacijo nekega področja ali procesa lahko dosežemo portalu [7] lahko zasledimo tudi opredelitev visokošolskega drugačno obnašanje udeležencev v tem procesu. Številne sistema v Sloveniji, ki se glasi: »Visokošolski zavodi v raziskave na različnih področjih, ki so podprta z elementi slovenskem visokošolskem prostoru so univerze, fakultete, igrifikacije, poročajo o višji stopnji motiviranosti, angažiranosti umetniške akademije in visoke strokovne šole. Zagotavljajo in učinkovitosti udeležencev. Čas preživet v takšni aktivnosti je razvoj znanosti, strokovnosti in umetnosti ter v izobraževalnem daljši in uporabnik je bolj zadovoljen. Če je neka naloga (ali igra) procesu posredujejo spoznanja z znanstvenih, strokovnih, zasnovana na način, da sta zahtevnost naloge in veščina raziskovalnih in umetniških področij. Fakultete, umetniške udeleženca usklajeni lahko govorimo o tako imenovanem stanju akademije in visoke strokovne šole so lahko ustanovljene tudi toka (angl. flow). Stanj toka se definira kot optimalna izkušnja, kot samostojni visokošolski zavodi zunaj univerz.«. Spletna stran za katero sta značilna popolna osredotočenost in angažiranost na spot.gov [8] navaja, da so za izvajanje visokošolskega neko aktivnost v kateri je nek udeleženec [15]. Na Sliki 1 je izobraževanja v Sloveniji zadolžene univerze, fakultete, prikazan model oz. stanje udeleženca glede na nivo umetniške akademije in visoke strokovne šole. Na omenjeni sposobnosti/znanja in izziva oz. naloge. Glede na nivo spletni strani spot.gov [8] lahko najdemo tudi opredelitev sposobnosti/znanja in nivo izziva se pri udeležencu pojavljajo univerze, fakultete, umetniške akademije in visoke strokovne določeni občutki in stanja prikazana na Sliki 1. šole, ki se glasi: »Univerza zagotavlja razvoj znanosti, Obstaja devet značilnosti med stanjem toka in izkušnjo strokovnosti in umetnosti in prek fakultet, umetniških akademij uporabnika in sicer kot: uravnoteženost med zahtevnostjo naloge ali visokih strokovnih šol v izobraževalnem procesu posreduje in sposobnostjo posameznika, samodejno opravljanje neke spoznanja z več znanstvenih oziroma umetniških področij ali aktivnosti, jasno postavljeni cilji, jasne povratne informacije, disciplin. Univerza lahko neposredno organizira izvajanje osredotočenost na nalogo, občutek nadzora aktivnosti, znanstveno-raziskovalnih in študijskih interdisciplinarnih izguba samozavedanja, občutek za čas postane izkrivljen in programov. Fakulteta opravlja pretežno znanstveno- avtentična izkušnja (dejavnost je sama po sebi razlog raziskovalno in izobraževalno dejavnost s področij ene ali več opravljanja) [15]. V tem stanju se pogosto zgodi, da izgubimo sorodnih oziroma med seboj povezanih znanstvenih disciplin in občutek za čas in dogajanje v oklici. Udeleženec, ki je v stanju 536 toka je popolnoma osredotočen na nalogo. Izvajanje takšne V nadaljevanju so predstavljeni elementi igrifikacije v naloge je pogosto najučinkovitejše in najuspešnejše. visokem šolstvu s poudarkom na visokošolskih učiteljih in sodelavcih. Anksioznost Vzburjenost Stanje toka 5 ELEMENTI IGRIFIKACIJE V sokiV (anxiety) (arousal) (flow) VISOKOŠOLSKEM IZOBRAŽEVANJU Uporaba elementov igrifikacije v izobraževanju ima številne prednosti, njihova uporaba v izobraževalnih okoljih pa se je geloa el) izkazala za uspešno [17]. Pri tem moramo poudariti, da je velika n ev l Nadzor Skrb večina raziskav s področja igrifikacije v izobraževanju narejena oz. eg (control) (worry) iva len na učencih, dijakih in študentih. Elementi igrificikaje, ki jih izz hal lahko najpogosteje zasledimo v izobraževanju in so uporabljeni ivo (c N na študentih so (po abecednem vrstnem redu) [3]: časovna omejitev (naloga, izpit), delo z virtualnimi karakterji in problemi, dobra ocena, dodatne točke, doseči čim več točk na izpitu, vajah, Apatija Dolgočasje Relaksacija finančne nagrade, hitre povratne informacije, individualno delo, zek (apathy) (boredom) (relaxation) iN javna podelitev priznanj, javna pohvala profesorja, kazen za neaktivnost, materialne nagrade, naloge, ki imajo velik družben Nivo sposobnosti Nizek Visok (skill level) pomen, negativne točke za napačen odgovor, objava med najboljšimi študenti, pisno priznanje, predčasno dokončanje Slika 1: Prikaz mentalnega stanja igralca glede na nivo nalog in skupinsko delo, strah pred neuspehom, sposobnosti in izziva [16]. tekmovanje/primerjanje s sošolci, ustna pohvala profesorja, vizualni prikaz in statusa napredka. Zelo malo pa je bilo izvedenih raziskav o igrifikaciji, elementih igrifikacije ter 4 ELEMENTI IGRIFIKACIJE njihovem vplivu na visokošolske učitelje in sodelavce. V Glavni cilj igrifikacije v izobraževanju je narediti izobraževanje primerjavi z drugimi javnimi uslužbenci, kamor štejmo tudi prijetno, kot je to značilno za video igre [13]. Ko je govora o visokošolske učitelje in sodelavce, lahko trdimo, da so prav igrifikaciji nikakor ne moremo mimo njenih glavnih gradnikov, omenjeni najbolj izpostavljeni elementom igrifikacije. ki so elementi igrifikacije. Seznam elementov igrifikacije s Visokošolski učitelji in sodelavci v Sloveniji najpogosteje kratkim pojasnilom (po abecednem vrstnem redu) [10]: delujejo oz. so zaposleni na univerzah (fakultetah). Omenjene  avatar: vizualna predstavitev igralčevega značaja, ustanove so podvržene številnim medsebojnim primerjavam, ki  boj z močnejšim: značilno težka naloga v okviru so javno dostopne. Na spletni strani Univerze v Ljubljani pod določene stopnje, poglavjem kakovost lahko najdemo nekatere mednarodne  boj: ničelni seštevek vsote točk ali financ med igralci, lestvice po katerih lahko medsebojno primerjamo posamezne ki se borijo za isti cilj, univerze [18]: (1) Academic Ranking of World Universities  dosežki: specifično definirana naloga v igri, (Shanghai Ranking); (2) QS World University Ranking; (3)  lestvice: primerjanje z drugimi igralci, ki temelji na Times Higher Education (THE) World Universities Ranking; (4) sposobnostih, Times Higher Education Emerging Economies University  naloge: predhodno določeni izzivi, Rankings in (5) Center for World University Rankings (CWUR).  nivoji: težavnostno merilo, ki temelji na igralčevih Omenjene lestvice omogočajo medsebojno primerjanje kompetencah, univerz. V Sloveniji sta vodilni in najbolj poznani Univerza v  obdarovanje: zagotavljanje pomoči drugim igralcem, Ljubljani in Univerza v Mariboru, ki sta tudi največji tekmeci za  odklepanje vsebin: zagotavljanje novih vsebin, ki so študente in ugled. Številni kriteriji, ki so zajeti v rangiranju posledica osvojitve delnega cilja, univerz upoštevajo znanstvene objave visokošolskih učiteljev in  sodelavce. Zato je pomembno, da so visokošolski učitelji in skupine: skupina igralcev, ki sodeluje z namenom sodelavci aktivni v svojem znanstveno-raziskovalnem in dosege nekega cilja,  strokovnem delu oz. da imajo kvalitetne objave v priznanih točke: numerični zapisi o igralčevi aktivnosti, revijah. Visokošolske učitelje in sodelavce se najpogosteje  virtualne dobrine: sredstva z določeno vrednostjo v ocenjuje in vrednoti po sledečih elementih: (1) znanstveno- okviru igre. raziskovalna dejavnost; (2) strokovna dejavnost; (3) umetniška  zbirke: zbirka določenih značk in dejavnost in (4) pedagoška dejavnost. Visokošolski učitelji in  značke: vizualna predstavitev dosežka. sodelavci morajo za svoj obstoj oz. zaposlitev izpolnjevati Elementi igrifiakcije imajo svoje značilnosti. Namenjeni so določene pogoje. Eden izmed teh pogojev je aktivno znanstveno- specifičnim uporabnikom v specifičnih situacijah. Zgolj uvedba raziskovalno in strokovno delo, ki se odraža v znanstvenih in elementov igrifikacije v nek proces še ne zagotavlja, da bo proces drugih objavah. Med omenjenimi zaposleni je ta proces znan pod oz. njegovi uporabniki zadovoljni. Pri uporabnikih obstajajo imenom habilitacija. Habilitacija se mora opraviti vsakih nekaj številne posebnosti kot so kultura, rasa, veroizpoved, starost, let (najpogosteje za dobo petih let). Za številne zaposlene spol, osebnostne lastnosti in drugo, ki vplivajo na dojemanje in predstavlja habilitacija velik napor in stres. Za razliko od večine sprejemanje elementov igrifikacije. javnih uslužbencev pa so rezultati dela visokošolskih učiteljev in 537 sodelavcev, ki so v obliki znanstvenih objav, javno dostopni na najugodnejših revijah in njihove avtorje (Slika 2). Omenjen raznih spletnih straneh. Ena izmed pomembnejših spletnih strani, objave lahko kot element igrifikacije opredelimo kot status, ki kjer so objavljena dela visokošolskih učiteljev in sodelavcev je avtorjem objav v najuglednejših revijah veliko pomeni. Objava SICRIS. Na področju visokega šolstva ima spletna stran SICRIS na tako pomembni spletni strani kot je COBISS pri javno zelo pomembno vlogo, kjer lahko najdemo različne podatke o objavljenih avtorjih vzbuja pozitivne občutke, kot so ponos, raziskovalcih, raziskovalnih skupinah, projektih in drugo. Na pomembnost, motiviranost za nadaljnje delo in drugo. spletni strani Wikipdija [19] lahko zasledimo opredelitev SICRIS-a, ki se glasi: »Informacijski sistem o raziskovalni dejavnosti v Sloveniji (kratica SICRIS - Slovenian Current Research Information System) je namenjen javnemu spletnemu prikazu podatkov iz zbirke oziroma evidence izvajalcev raziskovalne in razvojne dejavnosti, ki jo vodi Javna agencija za raziskovalno dejavnost Republike Slovenije (ARRS), ter podatkov o raziskovalnih projektih in raziskovalnih programih, Slika 2: Objavljeni naslovi in avtorji člankov, ki so ki jih financira ARRS iz sredstev državnega proračuna. Evidenca objavljeni v najuglednejših publikacijah [23]. izvajalcev raziskovalne in razvojne dejavnosti vsebuje podatke o raziskovalnih organizacijah, o raziskovalnih skupinah in o Na spletni strani COBISS lahko najdemo tudi številna dela, raziskovalcih oziroma o raziskovalnem kadru. Informacijski mentorstva, somentorstva in druga dela pri katerih so sodelovali sistem vzdržujeta Institut informacijskih znanosti in Javna visokošolski učitelji in sodelavci. Spletni strani COBISS in agencija za raziskovalno dejavnost Republike Slovenije.« Na SICRIS ponujata javni vpogled na rezultate dela posameznega SICRIS-u lahko vidimo kakšne rezultate dosega nek visokošolskega učitelja in sodelavca. V Sloveniji je zelo malo visokošolski učitelja ali sodelavec. Pregled informacijskega spletnih strani, kjer bi lahko na tako raznolik, kritičen in javen sistema o raziskovalni dejavnosti v Sloveniji (SICRIS) pokaže, način medsebojno primerjali rezultate dela posameznih javnih da lahko visokošolske učitelje in sodelavce rangiramo in uslužbencev (npr. upravne delavce, zdravnike, policiste, …). primerjamo po številnih kriterijih kot so na primer [20]: A'' - Poleg elementov igrifikacije, ki prikazujejo znanstveno- Izjemni dosežki; A' Zelo kvalitetni dosežki; A 1/2 - pomembni raziskovalno delo visokošolskih učiteljev in sodelavcev moramo dosežki; Ocena A1 - objave; Ocena A3 - sredstva izven ARRS; na tem mestu omeniti še druga področja, ki so izpostavljena CI10 - število čistih citatov znanstvenih del v zadnjih desetih igrifikaciji. Eno izmed teh je pedagoško delo visokošolskih letih; CImax - najodmevnejše delo; h-indeks; Scopus - povezani učiteljev in sodelavcev. Omenjeni zaposleni so glavni nosilci zapisi; Scopus - citati (TC); Scopus - čisti citati (CI); Scopus - pedagoškega dela oz. dela s študenti, ki se najpogosteje odraža v povprečje čisti citatov (CIAu); WoS - povezani zapisi; WoS - obliki predavanj in vaj. Študenti imajo možnost preko anket citati (TC); WoS - čisti citati (CI) in WoS - povprečje čistih oceniti delo visokošolskih učiteljev in sodelavcev. Ocena je citatov (CIAu). najpogosteje v obliki ocenjevalne lestvice (točk). Slaba ocena, ki Na spletni strani SICRIS najpogosteje zasledimo elemente jo dobi nek učitelj ali sodelavec ima lahko resne posledice. Kot igrifikacije kot so točke in lestvice. Na omenjeni spletni strani primer takšne ankete lahko omenimo anketo (Slika 3), ki se lahko zasledimo številne izvedbe pojava, ki ga imenujemo izvaja na Univerzi v Mariboru že od študijskega leta 2009/2010 igrifikacija in se kaže v obliki [20]: vrednotenja skupin izbranih do danes (opomba: imena in priimki so zaradi diskretnosti raziskovalcev; prikaza najuspešnejših raziskovalcev; prikaza zamegljeni). Na spletni strani Univerze v Mariboru [24] lahko najuspešnejših skupin; objav v najuglednejših publikacijah in najdemo opredelitev študentske ankete, ki se glasi: "Študentska biografskih kazalcev uspešnosti za izvolitve v naziv. anketa je mnenjska anketa, s katero študenti izražajo svoje Na področju izobraževanja je v Sloveniji zelo poznana tudi mnenje o pedagoškem delu na vseh članicah Univerze v spletna stran COBISS. »COBISS (Co-operative Online Mariboru. O anketiranju, njegovem namenu in vprašalniku, Bibliographic System & Services, slovensko Kooperativni dekan obvesti vse študente in visokošolske učitelje in sodelavce online bibliografski sistem in servisi) je slovenski knjižnični na začetku študijskega leta." informacijski sistem, ki ga je razvil mariborski Institut informacijskih znanosti (IZUM). COBISS je organizacijski model povezovanja knjižnic v nacionalni knjižnični informacijski sistem z vzajemno katalogizacijo, vzajemno bibliografsko-kataložno bazo podatkov COBIB in lokalnimi bazami podatkov sodelujočih knjižnic, bazo podatkov o knjižnicah COLIB, normativno bazo podatkov CONOR ter s številnimi drugimi viri in funkcijami.« [21]. Po podatkih spletne strani Similarweb [22], spletno stran COBISS-a mesečno obišče 106.600 obiskovalcev, ki si v povprečju ogledajo 1,68 strani in ostanejo na spletni strani minuto in 45 sekund. Spletna stran Slika 3: Ocene visokošolskih učiteljev in sodelavcev kot COBISS-a se v primerjavi z ostalimi spletnimi stranmi v rezultati ankete o pedagoškem delu in obremenitvi študenta Sloveniji po obisku nahaja na 783 mestu. Navedeni podatki 2020/2021 [25]. pričajo, da je spletna stran COBISS-a zelo priljubljena v Sloveniji in pomembna za področje izobraževanja. Na omenjeni Omeniti moramo tudi dejstvo, da je dostop do rezultatov spletni strani lahko med drugim zasledimo tudi objave v ankete javen in da si rezultate lahko ogleda pravzaprav vsak, ki 538 le ima dostop do svetovnega spleta. Študentska anketa je v veliki AD Scientific Index (https://www.adscientificindex.com/) lahko meri pokazatelj oz. posledica odnosa visokošolskega učitelja ali najdemo številne primerjave med državami, univerzami, sodelavca do študentov. Če je nek študent zadovoljen bo ocena najboljše uvrščenimi znanstveniki, največkrat citirane višja in obratno. Zato je cilj vsakega zaposlenega imeti kar posameznike in drugo. najboljši pristop do študentov. Na tem mestu moramo opomniti Našteti in opisani so bili samo najpomembnejši in najbolj na dejstvo, da se visokošolski učitelji in sodelavci uvrščajo med znani elementi igrifikacije, ki jih lahko zasledimo na področju javne uslužbence v Sloveniji. Zelo malo je področij in visokošolskega izobraževanja in so uporabljeni na visokošolskih zaposlenih, ki so tako javno izpostavljeni elementov igrifikacije učiteljih in sodelavcih. Iz prikazanega lahko zaključimo, da so kot ravno visokošolski učitelji in sodelavci. Nikjer na spletu ne visokošolski učitelji in sodelavci izpostavljeni številnim moremo na primer najdi ocene nekega zdravnika splošne elementov igrifikacije s katerimi naj bi zaposlene ocenjevali, medicine, ki so jo podali pacienti glede zadovoljstva ali motivirali in angažirali za delo. obravnave. Prav tako nikjer ni mogoče najti javno prikazanih ocen (v točkah) zaposlenih na upravnih enotah glede prijaznosti. Iz omenjenega lahko sklepamo, da so visokošolski učitelji in 6 ZAKLJUČEK sodelavci najbolj izpostavljeni igrifikaciji med vsemi javni Kljub temu, da se je igrifikacija začela relativno pozno uslužbenci glede odnosa do svojih strank (v tem primeru so to znanstveno in strokovno proučevati lahko zasledimo njeno hitro študenti). Poleg anket o pedagoškem delu s študenti na ravni uvajanje na različna druga področja. Eno takšnih je zagotovo univerz obstajajo tudi ankete na ravni fakultet, ki prav tako izobraževanje, kjer igrifikacije pridobiva vse večjo veljavo. Kot ocenjujejo pedagoško delo visokošolskih učiteljev in sodelavcev. je bilo že omenjeno je namen igrifikacije vlivati na vedenje Mnenja študentov o delu visokošolskih učiteljev in uporabnikov v neki dejavnosti ali aktivnosti. Večina igifikacije v sodelavcev imajo tudi druge učinke in posledice (pozitivne in izobraževanju se uvaja za namen povečevanja motiviranosti, negativne). Na nekaterih slovenskih fakultetah obstajajo t.i. angažiranosti in učinkovitosti učencev ali študentov. Bistveno dekanove nagrade oz. dekanove liste. Omenjene liste so manj pa je znanstvenih in strokovnih raziskav na področju predvsem namenjene podelitvi nagrad ali priznanj najboljšim igrifikacije v izobraževanju glede administrativnih delavcev, študentov. V sklopu takšnih prireditev pa se pogosto podeli tudi učiteljev in profesorjev oz. visokošolskih učiteljev in sodelavcev. nagrada za najboljšega profesorja in asistenta. Nagrade in Slednji so največkrat zaposleni na fakultetah oz. univerzah. priznanja namenjena visokošolskim učiteljem in sodelavcem se Njihova glavna dejavnost se lahko razdeli in se vrednosti kot podeljujejo tudi na nivoju univerz. Kot primer navajamo seznam znanstveno-raziskovalna dejavnost, strokovna dejavnost, nagrad in priznanj, ki jih podeljuje Univerza v Mariboru [26]: (1) umetniška dejavnost in pedagoška dejavnost. Kot je bilo Nagrada Univerze v Mariboru za znanstvenoraziskovalno, predstavljeno so visokošolski učitelji in sodelavci podvrženi umetniško in izobraževalno delo; (2) Nagrada Univerze v številnim elementom igrifikacije, katerih namen je vplivati na Mariboru za sodelovanje z gospodarstvom in prenos znanja; (3) aktivnost in obnašanje zaposlenih. Priznanje Univerze v Mariboru za znanstvenoraziskovalno, Visokošolski učitelji in sodelavci so eni izmed najbolj umetniško in izobraževalno delo; (4) Nagrada Univerze v točkovalnih, rangiranih, ocenjevanih in javno izpostavljenih oseb Mariboru za strokovno delo; (5) Priznanje Univerze v Mariboru med vsemi javnimi uslužbenci. Spletne strani kot so SICRIS in za strokovno delo in (6) Svečana listina Univerze v Mariboru. COBISS nudijo vpogled v rezultate znanstveno-raziskovalnega Podeljena nagrada ali priznanje je posledica dela, ki ga zaposleni in strokovnega dela visokošolskih učiteljev in sodelavcev. V opravlja. Nagrada ali priznanje pomeni za posameznika Sloveniji praktično ni spletni strani, ki bi na tako natančen, pozitivno povratno informacijo za nadaljnje delo. V kontekstu sistematičen in javen način spremljala delo ostalih javnih igrifikacije se nagrade uporabljajo kot motivacija za krepitev uslužbencev (recimo zdravnikov, zaposlenih na upravnih enotah, zaželenega obnašanja posameznika v neki aktivnosti. Nasprotno sodnikov in drugih) kot je to v primeru visokošolskih učiteljev in nagradi se v igrifikaciji uporablja element kazni ali sankcije. sodelavcev. Poleg formalnih oblik igrifikacije v visokem šolstvu Pedagoška dejavnost visokošolskih učiteljev in sodelavcev je obstajajo tudi neformalne oblike igrifikacije dela in rezultatov tako kot znanstveno-raziskovalna in strokovna dejavnost visokošolskih učiteljev in sodelavcev. V svetu raziskovalcev podvržena elementom igrifikacije. Osnova za vrednotenje obstajajo spletne strani, ki omogočajo objavo člankov, pedagoškega dela so številne ankete, ki se redno izvajajo na medsebojno povezovanje, komuniciranje in medsebojno nivoju univerz in fakultet. Nekatere univerze javno objavljajo primerjanje. Ena izmed bolj znanih spletnih strani je rezultate anket. Ocena nekega zaposlenega je izražena v točkah ResearchGate (https://www.researchgate.net/). Registracija na zato lahko na enostaven način medsebojno primerjamo sebi omenjeni spletni strani je brezplačna in prostovoljna. podobne zaposlene na univerzi ali fakulteti. Ovrednoteni Vrednotenje aktivnosti in objav je izvedena s posameznimi rezultati (največkrat v točah) znanstveno-raziskovalne, elementi igrifikacije, kjer prevladujejo točke. Na omenjeni strokovne in pedagoške dejavnosti vplivajo na številne spletni strani lahko pri vsakem raziskovalcu najdemo naslednje karakteristike. Ena izmed teh je delovna uspešnost zaposlenega. elemente igrifikacije, ki kažejo na posameznikovo aktivnost in Delovna uspešnost se vrednosti po različnih kriterijih. Na objave [27]: (1) Research Interest Score, (2) Citations in (3) h- številnih fakultetah se v končni oceni delovne uspešnosti index. Na osnovi vrednotenja del, ki so prikazane v obliki točk je upoštevajo vpisane objave v sistem SICRIS, pedagoška ocena omogočeno medsebojno primerjanje raziskovalcev z vsega študentke ankete in drugo. Ocena delovne uspešnosti pa se sveta. Podobne spletne strani kot ResearchGate so še Inkpath, posledično odraža tudi v osebnem dohodku oz. plači. MyScienceWork, Academia.edu, Mendeley, AD Scientific V članku so prikazani samo nekateri najbolj poznani in Index in druge. Kot zanimivost naj omenimo, da na spletni strani pomembni elementi igrifikacije uporabljeni na visokošolskih 539 učiteljih in sodelavcih. Obstajajo tudi drugi, vendar manj [7] Gov.si. 2022. Visokošolsko izobraževanje. Dostopno na naslovu pomembni elementi, ki pa vseeno vplivajo na delo, obnašanje in https://www.gov.si/podrocja/izobrazevanje-znanost-in-sport/visokosolsko- izobrazevanje/ (10. 8. 2022) počutje visokošolskih učiteljev in sodelavcev. V znanstveni in [8] Spot.gov. 2021. Visokošolsko izobraževanje. Dostopno na naslovu strokovni literaturi pa je zelo malo dokazov, da so uporabljeni https://spot.gov.si/sl/dejavnosti-in-poklici/dejavnosti/visokosolsko- izobrazevanje/ (8. 8. 2022) elementi igrifikacije optimalno uporabljeni oz. najboljši za [9] Deterding, S. 2011. Situated motivational affordances of game elements: A doseganje motiviranosti, angažiranosti in učinkovitosti conceptual model, in: Presented at Gamification: Using Game Design Elements in Non-Gaming Contexts, a workshop at CHI 2011. Dostopno na visokošolskih učiteljev in sodelavcev. Omenjeni zaposleni imajo naslovu http://gamification-research.org/wp-content/uploads/2011/04/09- svoje značilnosti in specifičnosti. Raziskava, ki so jo opravili Deterding.pdf Urh, Jereb, Šprajc, Jerebic in Rakovec (2022) ugotavlja, da imajo [10] Werbach, K., in Hunter, D. 2012. For the Win: How Game Thinking Can Revolutionize Your Business. Wharton Digital Press, Philadelphia, PA. različni elementi igrifikacije različen vpliv na posameznike (v [11] Pedreira O., García F., Brisaboa N. in Piattini M. (2015). Gamification in tem primeru na študente) glede na njihove osebnostne lastnosti - software engineering – A systematic mapping, Information and Software Technology 57, 157–168. velikih pet faktorjev osebnosti (angl. Big Five personality traits). [12] Hickey, D. T., Ingram-Goble, A., in Jameson, E. M. 2009. Designing Tudi visokošolski učitelji in sodelavci imajo različne osebnostne assessments and assessing designs in virtual educational environments. lastnosti. Vsesplošna uporaba elementov igrifikacije v Journal of Science Education and Technology, 18(2), 187–208. [13] Simões, J., Redondo, R. D., in Vilas, A. F. 2013. A social gamification visokošolskem izobraževanju zato zagotovo ni optimalna. framework for a K-6 learning platform, Computers in Human Behavior 29, Takšna uporaba elementov igrifikacije ne prinaša najboljših 345–353. [14] Buckley, P., in Doyle, E. 2017. Individualising gamification: An rezultatov. Še več, nekateri zaposleni se zaradi takšne uporabe investigation of the impact of learning styles and personality traits on the igfirikacije lahko (in se) počutijo neprijetno, prestrašeno, efficacy of gamification using a prediction market, Computers & Education osramočeno in drugo. V prihodnosti bi bilo smiselno podrobno 106, 43−55. [15] Csíkszentmihályi, M. 1990. Flow: The psychology of optimal experience. in natančno proučiti uporabljene elemente igrifikacije in njihov New York: Harper and Row. vpliv na visokošolske učitelje in sodelavce. Spoznanja bi lahko [16] Csikszentmihalyi, M. 1997. Finding flow: The psychology of engagement with everyday life. Basic Books. prispevala k boljši sprejetosti omenjenih in predstavljenih [17] de-Marcos, L., Domínguez, A., Saenz-de-Navarrete, J., in Pages, C. 2014. elementov in večji motiviranosti zaposlenih. Zanimivo bi bilo An empirical study comparing gamification and social networking on e- learning. Computers & Education 75:82-91. 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(2022). cobiss.si. Dostopno na naslovu http://www.playwales.org.uk/login/uploaded/documents/Playwork%20Prin https://www.similarweb.com/website/cobiss.si/#overview (15. 8. 2022) ciples/playwork%20principles.pdf (16. 3. 2015). [23] COBISS. 2022. Objave v najuglednejših publikacijah. Dostopno na naslovu [2] Maroney, K. 2001. My entire waking life. Dostopno na naslovu https://www.cobiss.si/raziskovalci.htm (11. 8. 2022) http://www.thegamesjournal.com/articles/ MyEntireWakingLife.shtml (11. [24] Univerza v Mariboru. 2022a. Študentska anketa. Dostopno na naslovu 2. 2013). https://www.um.si/kakovost/studentska-anketa-2/ (8. 8. 2022) [3] Urh, M. in Jereb, E. 2017 Igrifikacija v izobraževanju. BERNIK, Mojca (ur.), [25] Univerza v Mariboru. 2022b Anketa o pedagoškem delu in obremenitvi 2017, Kadrovski management v sodobni organizaciji [na spletu]. študenta 2020/2021. Dostopno na naslovu https://www.um.si/wp- Univerzitetna založba Univerze v Mariboru. ISBN 978-961-286-102-5. content/uploads/2021/12/Rezultati-studentske-ankete-za-studijsko-leto- Dostopno na naslovu https://dk.um.si/IzpisGradiva.php?lang=slv&id=68990 2020-2021.pdf (10. 8. 2022). [4] Connolly, T. M., Boyle E. A., MacArthur E., Hainey T., in Boyle J. M. 2012. [26] Univerza v Mariboru. 2022c. Nagrade in priznanja. Dostopno na naslovu A systematic literature review of empirical evidence on computer games and https://www.um.si/o-univerzi/predstavitev/nagrade-in-priznanja/nagrade-in- serious games, Computers & Education 59, 661–686. priznanja/ (10. 8. 2022). [5] Blohm, I., in Leimeister, J. M. 2013. Gamification: Design of IT-based [27] Researchgate. 2022. Researchgate. Dostopno na naslovu (20. 8. 2022) enhancing services for motivational support and behavioral change. Bus. Inf. https://www.researchgate.net/Tabela 1: Table caption (Slovene) Syst. Eng. 5, 275–278. http://dx.doi.org/10.1007/s12599-013-0273-5. [6] Jereb, J. 1998. Teoretične osnove izobraževanja. Založba Moderna organizacija, Kranj. 540 Pozitiven impulz IKT otroku s čustveno vedenjskimi težavami? A Positive Impulse ICT for a Child With Emotional and Behavioural Problems? Alenka Zabukovec Tadej Lorenčič MD Malči Beličeve MD Malči Beličeve Ljubljana, Slovenija Ljubljana, Slovenija alenka.zabukovec@guest.arnes.si tadej.lorencic@gmail.com POVZETEK Izzivi današnjega časa narekujejo vzgojiteljem, učiteljem in 1 UVOD staršem prilagajanje vzgojnih in učnih prijemov nastalim Mladinski dom Malči Beličeve je zavod, ki nudi situacijam. Znano je, da je za učence/dijake IKT močno otrokom/mladostnikom s čustveno vedenjskimi težavami motivacijsko sredstvo v šolah, manj raziskana pa je smiselna celodnevno oskrbo po načelih družinske vzgoje. uporaba IKT pri vzgoji in izobraževanju v zavodih, kjer so Otroci/mladostniki hodijo v eksterne šole, v Domu pa se izvaja nastanjeni otroci s čustveno vedenjskimi težavami. V prispevku vzgojni program, ki vključuje dejavnosti (preventivne socialno- so predstavljeni primeri dobre prakse uporabe IKT za dvig varstvene, učno-vzgojne, kompenzacijske, osebnostno in motivacije pri učenju in preusmerjanju vedenja, ki slonijo na socialno integrativne idr.) za dosego cilja, ki je vključitev otroka teoretični podlagi s področij čustveno vedenjskih težav, (učne) v običajno življenje. motivacije in uporabne vrednosti IKT v šolskem prostoru, ter V prispevku je predstavljen izkustveni primer uporabe IKT praktični podlagi dolgoletnih izkušenj pri delu z kot motivacijske metode pri učenju in prevzgoji oz. usmerjanju otroki/mladostniki. vedenja. Opira se na poznavanje čustveno vedenjskih težav, (učne) motivacije, uporabne vrednosti IKT v šolskem prostoru in KLJUČNE BESEDE na dolgoletne izkušnje učno-vzgojne pri delu z Čustveno vedednjske težave, učenje z IKT, motivacija z IKT, otroki/mladostniki. uravnavanje vedenja z IKT Vzgojitelji moramo otroku ustvariti ljubeče in vzpodbudno ABSTRACT okolje, pozorno moramo spremljati otrokove majhne dosežke, ki se dogajajo dan za dnem. Pohvaliti je potrebno vsako pozitivno Today's challenges require educators, teachers and parents to dejanje in napredek. Pogoj za uspešno vzgojno delo so motivirani adapt their educational and learning approaches to the situations. otroci, za uspešnost motivacije pa je odgovoren vzgojitelj, ki It is known that ICT is a powerful motivational tool for izbira najbolj učinkovito vzgojno sredstvo pri različnih oblikah pupils/students in schools, but the meaningful use of ICT in in metodah dela [11]. education in institutions housing children with emotional behavioural problems is less researched. The paper presents examples of good practice in the use of ICT for increasing 2 MLADINSKI DOM MALČI BELIČEVE motivation in learning and for behaviour regulation, which are Mladinski dom Malči Beličeve (v nadaljevanju MDMB) je od based on a theoretical basis from the areas of emotional- leta 2021 strokovni center, ki skrbi za otroke in mladostnike s behavioral problems, (learning) motivation and the useful value čustvenimi in vedenjskimi težavami ter motnjami (v of ICT in the school environment, as well as on the practical basis nadaljevanju ČVT/M). Je del ene od štirih skupin, v katero so of many years of experience in working with children/youths. vključeni trije zavodi (Mladinski dom Jarše in Vzgojno izobraževalni zavod Višnja Gora), ki pokrivajo oskrbo in KEYWORDS obravnavo otrok in mladostnikov osrednjeslovenske, Emotional-behavioral problems, learning with ICT, motivation jugovzhodne, zasavske in spodnjeposavske regije. with ICT, behavior regulation with ICT Zavod MDMB je bil ustanovljen za opravljanje javne službe na področju vzgoje in izobraževanja otrok in mladostnikov s posebnimi potrebami (vzgoje in izobraževanja otrok in mladostnikov s čustvenimi in vedenjskimi motnjami) po javnoveljavnih vzgojno-izobraževalnih programih, ki jih v Permission to make digital or hard copies of part or all of this work for personal or izvajanje določi pristojni šolski minister [8]. 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 MDMB izvaja dejavnost socialnega varstva z nastanitvijo, ki citation on the first page. Copyrights for third-party components of this work must obsega vse oblike pomoči v zavodu ali druge organizirane oblike, be honored. For all other uses, contact the owner/author(s). s katerimi se upravičencem nadomeščajo ali dopolnjujejo Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 541 funkcije doma ali lastne družine, zlasti pa bivanje, organizirana komuniciranja, (2) odnos do pravil in družbenih norm, (3) prehrana in varstvo [8]. zdravstveno stanje, (4) interesne dejavnosti, (5) delovne navade, Otroka oz. mladostnika se v strokovni center namesti (1) po (6) šolsko področje idr. izvedenem nujnem odvzemu s strani centra za socialno delo v Vzgojno delo zajema vse dejavnosti, ki stremijo k skladu z zakonom, ki ureja družinska razmerja, ali (2) z odločbo uresničevanju individualiziranih programov posameznih o namestitvi v skladu z zakonom, ki ureja nepravdni postopek, in otrok/mladostnikov in hkrati sledijo osrednjemu cilju: vključitvi zakonom, ki ureja družinska razmerja, ali (3) z odločbo o izreku otroka/mladostnika s ČVT/M v običajno življenjsko okolje. V vzgojnega ukrepa oddaje v vzgojni zavod v skladu z zakonom, MDMB poteka vzgojno delo po okvirnem dnevnem urniku, ki ki ureja obravnavanje mladoletnih storilcev kaznivih dejanj [16]. vključuje tudi t. i. učne ure, med katerimi se uresničujejo predvsem učno-vzgojni cilji, in sicer [7]: ugodna psihosocialna 2.1 Vzgojni program klima, ki omogoča zadovoljitev potreb po varnosti in sprejetosti; Osrednji cilj izvajanja veljavnega vzgojnega programa je dobri medosebni odnosi, zadovoljevanje naravne potrebe po ponovna uspešna vključitev otroka ali mladostnika s ČVT/M v uspešnosti in napredovanju, dvig otrokove samopodobe, običajno življenjsko sredino. Zato se v zavodu sledi naslednjim približevanje učno-vzgojnih vsebin otrokovim psihofizičnim ciljem: (1) preventivnim socialno-varstvenim in zdravstvenim zmožnostim (pozitivno učenje). ciljem, (2) učno-vzgojnim ciljem (zagotavljanje šolske uspešnosti in celovite vzgoje), (3) kompenzacijski cilji - 3 OTROCI/MLADOSTNIKI S ČVT/M nadomestitev zamujenega, manjkajočega v razvoju otroka/mladostnika, (4) osebnostno in socialno integrativnim Čustveno vedenjske težave oz. motnje različni avtorji ciljem (spreminjanje/odpravljanje socialno nesprejemljivih opredeljujejo različno. V strokovni literaturi so navedeni številni navad, odnosov, vedenj, razbremenjevanje občutkov pomembni avtorji s tega področja in njihova pojmovanja manjvrednosti, razvijanje zdravega samozaupanja, postopno čustvenih, vedenjskih in socialnih težav: ČVT se kaže kot vključevanje v običajno življenjsko okolje, usposobitev za neprimerno, moteče, pasivno ali agresivno vedenje, družbeno sprejemljiv način življenja in delovanja ipd.), (5) nasprotovanje, iskanje pozornosti, ustrahovanje, vzgojno-izobraževalne dejavnosti, povezane s prehrano, in samopoškodovalna tendenca, socialni umik, izolacija, jokavost, dejavnosti, s katerimi se vzpodbuja zdravo prehranjevanje in nepričakovan nemir, odsotnost, raztresenost, brezdelje, otročjost, kulturo prehranjevanja [7]. defenzivnost, trma, težave s pomnjenjem in pozornostjo; MDMB je ustanova, ki razvojno, vzgojno in socialno delinkventnost ter nevodljivost oz. težja vodljivost [9]. Večina ogroženim otrokom in mladostnikom z vedenjskimi in avtorjev poudarja tudi, da morajo biti omenjena vedenja čustvenimi težavami nudi in zagotavlja celovito celodnevno kontinuirana in se pojavljati na več področjih oskrbo skozi vse leto. Poleg tega nudi še varstvo, zdravstveno otrokovega/mladostnikovega življenja, da lahko govorimo o nego, vzgojo in prevzgojo ter celotno pomoč pri izobraževanju kategoriji težav ali celo motnji. osnovnošolski/srednješolski populaciji [8]. Naj izpostavimo obširno klasifikacijo oz. shemo simptomov MDMB deluje po načelu družinske vzgoje. Otroci in po Schraderju iz leta 1991 [6], ki deli vedenjske težave na: (1) mladostniki (izraz "mladostnik" po ZOOMTVI pomeni funkcijske motnje: enureza, enkopreza, zaprtje, motnje mladostnika, starega od 15 do 26 let) iz vzgojnih skupin se prehranjevanja, splošen motorični nemir, tiki, govorne motnje, izobražujejo v eksternih šolah v rednih programih šol, lahko pa slabosti čutil ipd.; (2) motnje navad: sesanje palca, grizenje bi obiskovali interne izobraževalne programe, ki jih izvajata nohtov, puljenje las, škripanje z zobmi, ekscesivna masturbacija; ostala dva strokovna centra v tej regiji. (3) motnje občutkov jaza in temeljnega razpoloženja: obča Za izvajanje programa vzgojno izobraževalne in socialno bojazljivost, bojazen v določenih situacijah, bolehanje, varstvene dejavnosti so v zavodu MDMB organizirane skupine, samopomilovanje, tečnarjenje, depresija, jok, poskus samomora, in sicer: 6 vzgojnih skupin, 2 stanovanjski skupini, intenzivna evforičnost; (4) socialne motnje: trma, kljubovalnost, pretirano skupina in mladinsko stanovanje. V zavodu je v času pisanja tega ljubosumje, čustveno šibka navezanost na ljudi, govorne motnje, prispevka približno 70 osnovnošolcev in srednješolcev, za njih samotarstvo, izostajanje iz šole, pobegi, potepanje, pretirana skrbi 37 strokovnih delavcev. podrejenost, neznosno vedenje, brutalnost, mučenje živali in ljudi, zlobnost, zahrbtnost, škodoželjnost, nagnjenost k 2.2 Individualizirani program uničevanju, klovnovstvo, bahanje, nastopaštvo, goljufanje, Za vsakega otroka/mladostnika strokovna skupina, ki jo vodi in tatvine; (5) motnje na področju dela in storilnosti: motnje pri igri usklajuje delavec strokovnega centra (v skupino je vključen tudi ali pomanjkanje interesa, šolsko nazadovanje, neuspešnost, predstavnik pristojnega centra za socialno delo in predstavnik motnje zaznavanja, raztresenost, pozabljivost, motnje šole, v katero je otrok/mladostnik vključen, po potrebi tudi koncentracije, igrivost, sanjarjenje, počasnost, pomanjkanje predstavnik pristojnega centra za duševno zdravje otrok in pobud, lenoba, odpor do dela, prevelika pridnost, umazanost, mladostnikov), pripravi individualiziran program, ki se ga s netočnost, neurejenost, pretirana pedantnost, prevelika skrb za timskim pristopom izvaja in spremlja celotno šolsko leto. V čistočo, pretirana skrbnost. individualiziranemu programu so določeni kratkoročni in ČVT ima dve dimenziji: čustveno in vedenjsko, ki ju celoletni cilji, oblike in metode dela z otrokom/mladostnikom, povezujemo z dvema kontekstoma, in sicer (1) notranji svet oz. oblike sodelovanja s starši in nosilci posameznih dejavnosti. njegov referenčni okvir in (2) socialni kontekst, na katerega se Vsak individualiziran program zajema več področij, med posameznik odziva na podlagi svojih izkušenj, pričakovanj, drugimi tudi naslednja: (1) socialni odnosi in veščine trenutne situacije in socialnega položaja, v katerem se znajde [9]. Pri nastajanju čustvenih in vedenjskih težav, ki se lahko 542 pojavljajo ločeno ali skupaj in so lahko pretežno internalizirane predstavljanju realnosti - potreba začne delovati šele, ko jo (čustvene težave), eksternalizirane (vedenjske težave) ali človek zazna [4]. kombinirane (čustvene in vedenjske težave), gre za izrazito V literaturi zasledimo tudi delitev na notranjo in zunanjo heterogenost pojavnih oblik in dejavnikov, ki vplivajo na njihovo motivacijo. Intrinzična motivacija je povezana z željo po učenju nastajanje oz. utrjevanje. Gre za preplet bioloških, psiholoških in zaradi želje same in s prirojeno radovednostjo v zvezi z socialnih dejavnikov, ki delujejo interaktivno v procesu razvoja neznanim; spodbuja pojmovno učenje in vodi k ustvarjalnemu otroka/mladostnika [5]. učenju. Ekstrinzična motivacija pa je povezana s potrebo po Za razumevanje pojava je tako pomemben splet, kombinacija učenju, učenec se uči zaradi zunanjega vzroka, npr. ocene, dogajanj, ki je pri vsakem otroku drugačna. Dejavniki lahko nagrade ipd. [13]. izhajajo iz družine, iz otroka samega, iz širšega okolja ali iz šole [10]. (1) Neugodne družinske razmere so pogosteje prisotne pri 4.1 Učna motivacija otrocih/mladostnikih s čustvenimi in vedenjskimi težavami kot Učna motivacija psihološki proces, ki učenca spodbudi k učenju, pri tistih, ki teh težav nimajo. Družinski neugodni vplivi so ga pri učenju usmerja, določa intenzivnost učenja in učencu predvsem dolgotrajna nesoglasja in prepiri med starši, čustveno omogoči, da pri njem vztraja [12]. prazni odnosi med otroki in starši, ravnodušnost staršev za Skozi zgodovino so se spreminjala mnenja o tem, kateri so otrokovo vzgojo, odsotnost nadzora otroka, alkoholizem, dejavniki, ki vplivajo na učno motivacijo otrok in mladostnikov. delinkventnost ali druge psihosocialne motnje pri starših, S časoma so kot pomembne dejavnike označili tudi učiteljeve odsotnost ustreznega vzora za učenje moralnih norm in osebnostne lastnosti, stil in strategijo vodenja ter šolsko klimo socialnega vedenja. (2) K pojavu težav lahko prispevajo nekatere [3]. Če želimo torej povečati motivacijo pri otrocih, je ključno, odzivne in značajske lastnosti posameznika: nekatere lastnosti da ustvarimo za to spodbudno okolje. Pomembno je, da so temperamenta, kot so: slabša sposobnost samoobvladovanja, zadovoljene otrokove osnovne potrebe (fiziološke potrebe, manjša sposobnost premagovanja neuspehov in konfliktov, večja potreba po varnosti, potreba po ljubezni in pripadnosti, potreba sprejemljivost za slabe vplive, večja občutljivost oz. ranljivost za po spoštovanju, samospoštovanju, potreba po vrednotenju drugih, neugodna doživetja, otrok ima lahko težave pri učenju potreba po samouresničitvi). Vse to pa lahko dosežemo s vedenjskih norm zaradi nezrelosti. Med nemirnimi otroki je več pomočjo različnih strategij in predvsem odnosom, ki ga otrok s težavami v vedenju kot med otroki, ki teh motenj nimajo. oblikujemo z otrokom/mladostnikom [14]. (3) Znano je, da se družbeni pritiski in krizne situacije lahko Učitelj mora razumeti, da se motivacija vedno dogaja v odražajo tudi s povečanjem števila vedenjskih težav med otroki učencu in da je učenec sam osrednji vir lastnega motivacijskega in mladostniki. (4) Med dejavnike šole spadajo kakovost šole kot delovanja. Učencu ne more dati motivacije, saj je že v njem. Z socialne organizacije in učinkovitost tehnik učiteljevega različnimi motivacijskimi spodbudami, ki jih učitelj nameni delovanja v razredu. učencu, to "njegovo" motivacijo lahko samo spodbudi, neguje, ČVT nastajajo dlje časa, ni pa nujno, da so trajne [14]. dodatno krepi ali celo zavre. Motivacijske spodbude se lahko razdeli na dve skupini: (1) didaktične motivacijske spodbude: npr. 4 MOTIVACIJA organizacija učnega okolja in učenja, učne metode, didaktični material in (2) psihološke motivacijske spodbude: vodenje Motivacija je pojem, ki spremlja človeka na vseh ravneh učenca med učenjem, povratne informacije o dosežkih, učna njegovega življenja. Pojem motivacija izhaja iz latinske besede podpora, osredotočanje na območja učenčevega bližnjega "movere", ki v prevodu pomeni premikati se oz. gibati se. razvoja [2]. Motivacija je proces, ki vodi vedenje ljudi in jih usmerja k določenim ciljem, s pomočjo različnih motivov, npr. potreb, 4.2 Motivacija pri otrocih/mladostnikih s vrednot, želja, idealov idr. [1]. ČVT/M Motivacija je proces, ki uravnava obnašanje in ga poenoti v Otroci/mladostniki, ki so vključeni v zavodsko okolje, se v prizadevanju za dosego zadanih ciljev. Je kompleksen pojav, saj življenju na različne načine spoprijemajo z novimi negotovostmi so dejanja usmerjena k določenemu cilju iz različnih razlogov. tveganji. Pogosto se v novih situacijah počutijo nemočni, Obnašanje je vedno motivirano in se ne pojavlja kar samo od socialno izolirani, njihovo samospoštovanje je nizko. Iz tega sebe, ker so vedno prisotni določeni cilji. Motivacija predstavlja razloga se zatekajo v različne nesprejemljive oblike vedenja kopičenje psihične energije pri človeku (pod vplivom notranjih (pasivnost, agresija idr.). Zaradi nezaupanja pogosto težko in zunanjih dražljajev), ki jo človek izkoristi za svojo aktivnost - vzpostavljajo stike, saj ljudi okrog sebe doživljajo kot sovražne posledica je sproščena napetost, zaradi katere človek čuti in negativne. Še težje vzpostavljajo globlje stike z vrstniki, vsi spodbudo za to, da nekaj stori. Delovanje različnih motivov v njihovi odnosi so površinski in posledično v teh odnosih ni človeku sproži motivacijo, na osnovi katere se človek nagiba ali prostora za empatijo. Zanje značilni so tudi občutki dolgočasja in odvrača od določenih predmetov, ki predstavljajo vsebino brezciljnosti v življenju. Primanjkuje jim motivacije za motivov. Motivacija je psihična funkcija, ki daje vsakemu kakršnokoli delo [15]. človeku značilen pečat posebnosti in enkratnosti [11]. Pri otrocih/mladostnikih s čustvenimi in vedenjskimi Proces motivacije vključuje čustveni in kognitivni vidik. težavami se pogostoma opazi visoko raven demotiviranosti, ki se Čustva imajo sama po sebi motivacijsko funkcijo, saj spodbujajo pojavlja na različnih področjih, od preprostih vsakodnevnih in usmerjajo obnašanje/vedenje - če motivi ne bi bili podprti z dejavnosti (pospravljanje, druženje) do učne motivacije. emocionalnim doživljanjem, sploh ne bi mogli delovati. Pogosto opažamo tudi motivacijske in učne primanjkljaje, ki Pomembnost kognitivnega vidika je v sodelovanju pri so hkrati značilnosti naučene nemoči - motivacija danes je 543 odvisna od izkušenj v preteklosti. Neuspeh v preteklosti je torej Otrokom/mladostnikom, ki so nameščeni v zavod in ki ključen razlog za demotivirano vedenje danes in v prihodnosti. prihajajo iz socialno šibkih družin (ali pa jih sploh nimajo) Otrok/mladostnik je prepričan, da je kakršenkoli odziv na prestavlja uporaba IKT potrebo, ki je v preteklosti zaradi trenutno stanje neučinkovit in da ni sposoben obvladovati različnih razlogov niso mogli zadovoljiti. Zato smo prišli do ideje, trenutne situacije. Zaradi tovrstnega prepričanja ni pripravljen da bi z dostopnostjo/smiselno uporabo IKT lahko razvijali in niti poskusiti [4]. usmerjali motivacijske procese, tako za učenje kot splošno Precej pogosteje se lahko v šolah/zavodih doseže, da so obnašanje, pri naših otrocih/mladostnikih. otroci zunanje motivirani, kar pomeni, da počnejo stvari zaradi Primer 1: Otrok težje računa in ne mara matematike. Ve, da zunanjih posledic. Zunanja motivacija ponavadi ni trajna, vztraja se mora učiti, a je ves čas nemiren, moti druge, glasno daje samo do trenutka, ko to zahteva okolje in je pa povezana s pritiski neprimerne pripombe o drugih, vstaja od svoje mize in hodi okoli, oz. zaskrbljenostjo, predvsem, kadar so cilji zastavljeni ne pripravi zvezka oz. učnih pripomočkov. Vzgojiteljeva naloga previsoko. Pri notranji motivaciji, ki se pri otrocih v zavodu v takem primeru je večplastna, saj je potrebno pripraviti in običajno težko zazna, je cilj delovanja v želji/dejavnosti sami, vir vzdrževati spodbudno učno okolje tako za skupino (vsi podkrepitve pa je v posamezniku. Notranja motivacija običajno otroci/mladostniki se učijo v istem prostoru) kot tudi za vztraja dlje, saj je povezana z notranjim zadovoljstvom, ki se ga posameznika. Za to, da otroka umirimo in pripravimo za učenje, čuti ob doseženem cilju. Notranjo motivacijo se povezuje s je potrebno uporabiti vzgojno motivacijsko metodo, ki je spontanostjo, ustvarjalnostjo in širjenjem interesov [11]. prilagojena posamezniku in hkrati deluje tudi na skupino. V našem primeru je bila to vzgojiteljeva vzpodbuda otroku v obliki kratkega nasveta: "Jaz vem, da ti to zmoreš. Vsak se lahko nauči 5 IKT računati, samo potruditi se je potrebno." in v obliki obljube, da Uporabna vrednost IKT kot motivacijskega sredstva v šolskem bo dobil tablico za naloge računanja, če bo opravil vse "šolske prostoru je znana, vse več učiteljev ugotavlja, da je vse bolj domače" naloge. Vzpodbuda in obljuba sta delovali pozitivno v pomembna. Vsak učitelj se je že znašel v situaciji, ko je ugotovil, večino primerih, saj se je otrok umiril in začel učiti samostojno, da so učenci veliko bolj motivirani za delo, če imajo možnost tako da je bilo potrebno le preverjanje opravljenega, pohvala in aktivnega vključevanja z IKT. večkratna vzpodbuda. Na koncu je sledila uporaba tablice, a pod IKT je "in". Danes se je raba IKT razmahnila do take mere, določenimi pogoji – samo didaktične spletne naloge, ki so bile da vsak od nas uporablja dnevno vsaj eno digitalno napravo, od skrbno, premišljeno izbrane (primerne letom in težavnosti učne telefona, računalnika do tablice in drugih naprav. Nameni so zelo snovi) za ponavljanje/utrjevanje učne snovi. Ob tem se je otrok različni. Pri otrocih/mladostnikih je opaziti uporabo predvsem mimogrede naučil po principu učenja iz napak tudi "tehnične" zaradi zabave oz. v družabne namene, po pandemiji Covid-19 pa uporabe IKT za učenje (prižgati/ugasniti tablico; "klik" oz. pri njih narašča osveščenost, da je uporaba digitalnih naprav kratkotrajen dotik s prstom ali pisalom na zaslonu tablice (ali mogoča tudi za učenje. pametnega telefona); "dvoklik", uporaba gumbov (1) za glasnost, (2) na zaslonu/v aplikaciji; uporaba menijev v aplikacijah idr.). Epilog: uspešno usmerjena motivacija, zadovoljen otrok z novim 6 IZKUSTVENI PRIMERI UPORABE IKT znanjem in ustreznim obnašanjem, pozitivna učna klima, KOT MOTIVACIJSKE METODE V MDMB pozitivna izkušnja je povečala motivacijo za nadaljnje učenje. Avtorja sva vzgojitelja v eni od vzgojnih skupin v MDMB. Naj pripomnimo še pomembno dejstvo, da na začetku, ko ni bilo Vzgojna skupina vključuje otroke/mladostnike različnih starosti, vzpostavljenega osebnega odnosa otrok-vzgojitelj, tak način najmlajši ima 10, najstarejša 16 let. Skupina (v času pisanja usmerjanja motivacije ni bil uspešen – predvidevamo da zato, ker prispevka je 8 otrok in mladostnikov) je heterogena tako po otrok še ni imel zaupanja v vzgojitelja oz. se še ni vzpostavil starosti kot tudi po čustveno vedenjskih težavah. konkretni pozitivni medosebni odnos otrok-vzgojitelj. Pri svojem delu se vzgojitelji vsakodnevno soočamo z Primer 2: Mladostnik ne mara angleščine in ne zna velikimi izzivi spodbudnega okolja, vsakodnevno izbiramo nepravilnih glagolov. Uči se jih iz knjige, tako da jih bere. Po najbolj učinkovita vzgojna sredstva, uporabljamo različne oblike nasvetu vzgojitelja, jih prične izpisovati v zvezek – samo tiste, ki in metode dela, hkrati pa preverjamo različne strategije jih ne zna. Ko ne zmore več koncentracije, postane nemiren in (učno)vzgojnega dela za dosego različnih ciljev tako pri skupini nepozoren. Predlog vzgojitelja, da naj pri ponavljanju naučenega v celoti, kot tudi pri posameznikih. uporabi svoj telefon in vanj tipka nepravilne glagole, z Vsak otrok/mladostnik dnevno v skupino prinese svojo začudenjem sprejme (predvidevamo da zato, ker so mladostniki energijo, razpoloženje, hotenja, želje. Pomembna naloga navajeni uporabljati telefon in aplikacija po večini za družabne vzgojitelja je, da empatično poveže vse energije v celoto, a namene) – ko se uči na tak način, se vidi, da se je koncentracija ohrani individualnost posameznika. Pri ustvarjanju za učenje in sama motivacija ponovno dvignila, saj je mirno vzpodbudnega okolja oz. ugodne psihosocialne klime je nujna osredotočen na delo. Po določenem času je opaziti ponoven tudi vzgojiteljeva korektivna vloga - da prepozna padec učne moči (odsotnost, sanjarjenje, brezdelje), zato otrokovo/mladostnikovo sprejemljivo/nesprejemljivo vedenje in vzgojitelj vpraša (da se izogne nasprotovanju oz. odporu do dela), ga poskuša usmerjati k pravim ciljem. Načini so zelo različni, če bi morda delal naloge za nepravilne glagole prek prenosnika skupno vsem pa je, da otrok/mladostnik ozavesti svoja dejanja in in ko mladostnik privoli, si sam prinese prenosnik, vzgojitelj pa za njih prevzame odgovornost. Uspešnost vzgojitelj pohvali in ga samo usmerja, da najde primerno spletno didaktično orodje za nagradi, za neuspešnost se dodeli postopen in sorazmeren učenje nepravilnih glagolov (naloge so bile večstopenjske, vzgojni ukrep. težavnost si je mladostnik izbiral sam, po nasvetu vzgojitelja od lažjih nalog do težjih: "Ko dobiš občutek, da znaš, in ti spletno 544 orodje pokaže, da imaš vse prav, nadaljuj z naslednjo stopnjo ali LITERATURA IN VIRI pa jo preskoči, izbira je tvoja."). Računalnik/prenosnik/telefon je [1] Barbara Benčina. 2016. Motiviranje zaposlenih. Vodenje v vzgoji in bil tako priložnost za kratek odmor med učenjem in odlično izobraževanju, 14(1), 27–47. motivacijsko sredstvo za nadaljevanje učenja, hkrati pa je v [2] Mojca Juriševič. 2012. Motiviranje učencev v šoli. Ljubljana: Pedagoška fakulteta. mladostniku povečal samostojnost in občutek uspešnosti ter [3] Mojca Juriševič. 2006. Učna motivacija in razlike med učenci. Ljubljana: napredovanja, s tem pa se je za mali drobec dvignila tudi njegova Pedagoška fakulteta. [4] Darja Kobal Grum, D. and Janez Musek. 2009. Perspektive motivacije. samopodoba, saj je ugotovil, da se je zmogel učno snov naučiti Ljubljana: Znanstvena založba Filozofske fakultete. sam. [5] Alenka Kobolt. 2011. Razumevanje in odzivanje na čustvene in vedenjske težave. Socialna pedagogika, 15(2), 153–175. Primer 3: Mladostnici iz neznanih razlogov "gresta na beg" [6] Mitja Krajnčan. 2006. Na pragu novega doma: oddaja otrok v vzgojni zavod. iz Doma ponoči v pižamah. Zjutraj, po vrnitvi sledi temeljit Ljubljana: Pedagoška fakulteta. pogovor z vzgojiteljem o dejanjih in posledicah. Resno, brez [7] MDMB. (2021a). Letni delovni načrt SC MDMB za š. l. 2021-22. [8] MDMB. (2021b). Pravila strokovnega centra Mladinskega doma Malči posmehovanja, prevzameta krivdo za dejanje. Določen je bil Beličeve Ljubljana. vzgojni ukrep za kršitev Domskih pravil – do konca šolskega leta [9] Uroš Metljak, Alenka Kobolt in Špela Potočnik. 2010. Narava čustvenih, vedenjskih in socialnih težav se izmika definicijam. V A. Kobolt (ur.), brez telefona. Vzgojni ukrep je pozitivno vplival na kasnejše Izstopajoče vedenje in pedagoški odzivi (str. 87–113). Ljubljana: Pedagoška vedenje obeh mladostnic, saj tega dejanja nista ponovili. fakulteta. [10] Anica Mikuš Kos. 1991. Šola in duševno zdravje. Murska Sobota: Pomurska založba. [11] Vesna Podplatnik. 2011. Motivacija. V J. Erčulj in P. Peček (ur.), 7 ZAKLJUČEK Sofinanciranje profesionalnega usposabljanja strokovnih delavcev v vzgoji in izobraževanju v letih 2008–2011 (str. 61–62). Brdo pri Kranju: Šola za Uporaba IKT se je v zadnjih letih zelo razmahnila na vseh ravnatelje. področjih našega življenja. Namenov uporabe je več, najbolj [12] Melita Puklek Levpušček, M. and Maja Zupančič. 2009. Osebnostni, motivacijski in socialni dejavniki učne uspešnosti. Ljubljana: Znanstvena zaželena pa je smiselna raba. Tudi v MDMB uporabljamo IKT v založba Filozofske fakultete. smiselne namene in preskušamo možnosti uporabe v učno- [13] Phil Race. 1998. Teaching: Creating a Thirst for Learning? V S. Brown (ur.) Motivating Students (str. 47–58). London: Kogan Page. motivacijske in vzgojne namene. Prikazani primeri dobre rabe so [14] Edita Rihar Škoflek. 2018.. Otroci s čustveno vedenjskimi motnjami – ČVM. lahko eden od možnih načinov pri iskanju vzgojnih in učnih Dostopno na naslovu http://scvsi.splet.arnes.si/files/2019/04/Motnje- prijemov za otroke/mladostnike s čustveno vedenjskimi vedenja-in-%C4%8Dustvovanja.pdf (11. 8. 2022) [15] Mirjana Ule. 2000. Temelji socialne psihologije. Ljubljana: Znanstveno in motnjami. Morda bi veljalo v prihodnosti razmišljati tudi o, do publicistično središče. sedaj pri nas neraziskani, drugačni rabi IKT: (1) usmerjenem in [16] Zakon o obravnavi otrok in mladostnikov s čustvenimi in vedenjskimi težavami in motnjami v vzgoji in izobraževanju (ZOOMTVI). 2020. Uradni nadziranem skupinskem preskusu uporabe aplikacij za list RS, št. 200/20. Dostopno na naslovu sproščanje/osredotočanje in (2) testiranju individualne uporabe http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO8083 (12. 8. 2022) aplikacij za krepitev izvršilnih funkcij/"trening možganov". Metode približevanja posamezniku, ob upoštevanju heterogene skupine, z različnimi motivacijskimi strategijami in oblikami dela, lahko lažje prinesejo pričakovane rezultate otrokom/mladostnikom in ne nazadnje tudi vzgojiteljem. Nekaj rezultatov pa že čutimo vsi, tako merljivih kot nemerljivih. In zato bomo zagotovo obdržali preskušene in razvijali nove učinkovite motivacijske prevzgojne in učne metode, tudi z IKT. 545 Programski vzorci v rešitvah nalog iz uvodnega programiranja Programming Patterns in Solutions to Introductory Programming Tasks Matej Zapušek Irena Nančovska Šerbec Univerza v Ljubljani, Pedagoška fakulteta Univerza v Ljubljani, Pedagoška fakulteta Ljubljana, Slovenija Ljubljana, Slovenija matej.zapusek@pef.uni-lj.si irena.nancovska@pef.uni-lj.si POVZETEK ABSTRACT Znanje računalniškega programiranja omogoča razvijanje veščin Programming skills allow you to develop problem solving, za reševanje problemov, algoritmično, analitično in abstraktno algorithmic, analytical, abstract reasoning, and logical thinking razmišljanje ter logično sklepanje. Izkušnje kažejo, da imajo skills. Experience shows that beginners often have difficulty začetniki pri usvajanju tega znanja pogosto težave, ki so acquiring these skills because they lack strategic knowledge. posledica pomanjkljivega strateškega znanja. Programski vzorci Programming patterns are structured cognitive building blocks, so od programskega jezika neodvisni strukturirani kognitivni independent of the programming language, that represent delčki, ki predstavljajo konceptualne rešitve ponavljajočih conceptual solutions to recurring algorithmic problems and can algoritemskih problemov in jih je mogoče med seboj povezovati be assembled into complex solutions. They provide novice v kompleksne rešitve. Začetniku dajejo uvid v proces reševanja programmers with insight into the problem-solving process and problemov in s tem v strategije reševanja, ki so značilne za thus into the solution strategies that are typical of experienced izkušene programerje. V predstavljeni študiji smo analizirali programmers. In the present study, we analysed novice rešitve nalog študentov uvodnega programiranja v sistemu programmers' solutions to problems in Project Tomo to identify Projekt Tomo, da bi ugotovili, kateri programski vzorci se programming patterns that occur in 1) correct solutions, 2) pojavljajo v: 1) pravilnih, 2) pravilnih, ki vključujejo odvečno correct solutions with redundant code, and 3) incorrect solutions. kodo in 3) nepravilnih rešitvah. Raziskovali smo, ali določene We investigated whether certain combinations of programming kombinacije programskih vzorcev uspešno napovedujejo patterns successfully predict the correctness of a solution. We pravilnost rešitve. Prav tako nas je zanimal proces gradnje rešitve were also interested in the process of creating a solution by s kombiniranjem programskih vzorcev, kar smo spremljali z combining programming patterns, which was monitored by analizo zaporednih oddaj. Rezultati študije so pokazali, da analysing sequential submissions. The results of the study prisotnost pričakovanih programskih vzorcev v rešitvi dobro showed that the presence of expected programming patterns in napove njeno pravilnost in je bolj natančna od avtomatskega the solution predicts its correctness well and is more accurate vrednotenja v sistemu Projekt Tomo. Ugotovili smo, da analiza than automatic evaluation in the Project Tomo system. We found zaporednih oddaj daje vpogled v proces reševanja na that the analysis of sequential submissions provides insight into konceptualnem nivoju, saj uporabljene kombinacije programskih the solution process at the conceptual level, as the combinations vzorcev razkrijejo načine razmišljanja študenta. Menimo, da so of programming patterns used reveal the students' thinking. We rezultati raziskave uporabni na področju didaktike uvodnega believe that the results of the study are useful for the didactics of programiranja, saj dokazujejo smotrnost uporabe programskih introductory programming as they reveal the rationality of using vzorcev. S programskimi vzorci si začetnik izgradi pomembno programming patterns. By using programming patterns, the množico gradnikov, ki jih lahko uporabi v procesu snovanja novice builds an important set of building blocks to use in rešitve in na ta način izboljša veščine pristopanja k reševanju designing solutions, and in this way improves his ability to solve problemov. problems. KLJUČNE BESEDE KEYWORDS Uvodno programiranje, programski vzorci, avtomatsko Introductory programming, programming patterns, automatic ocenjevanje rešitev programerskih nalog, didaktika evaluation of solutions to programming tasks, programming programiranja, analiza programske kode didactics, code analysis Permission to make digital or hard copies of part or all of this work for personal or 1 UVOD 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 Programiranje predstavlja eno od temeljnih veščin v sodobnem citation on the first page. Copyrights for third-party components of this work must svetu, saj omogoča ustrezen razvoj veščin reševanja problemov, be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia logičnega in kritičnega mišljenja [1]. Računalniški programi in © 2022 Copyright held by the owner/author(s). algoritmi so vpeti v vsakdan, zato je pomembno, da imajo 546 posamezniki vsaj osnovno razumevanje temeljnih konceptov, na Soloway [9], ki je ugotovil, da je ključna razlika med začetniki katerih so osnovani. Z učenjem programiranja učenci pridobijo in izkušenimi programerji ravno v uporabi/neuporabi znanja in veščine za ustvarjalno pristopanje k reševanju programskih vzorcev. Razvil je metodo »goal/plan analysis«, ki problemov. Programiranje je lahko zanimiva in izpolnjujoča temelji na deljenju prvotnega problema na manjše podprobleme izbira za njihov bodoči poklic [2]. oz. »cilje«, za katerega pa ima programer v okviru svojega Številne raziskave [3], Error! Reference source not found. , strateškega znanja programski vzorec, ki ga reši. Te pa nato [4], [5], [6] so pokazale, da je za začetnike programiranje težko združuje v rešitev problema. Slika prikazuje uporabo metode na in kompleksno ter da imajo posledično težave pri pridobivanju primeru iskanja povprečne vrednosti vpisanih števil. tega znanja. Podrobnejši vpogled v njihove težave razkrije, da te ne temeljijo na razumevanju lastnosti, pravil in značilnosti določenega programskega jezika (sintaksa), prav tako nimajo težav z razumevanjem kako deluje posamezen programski konstrukt (semantika). Najbolj problematičen vidik predstavlja znanje o tem kako smiselno združiti posamezne programske konstrukte v pravilno rešitev in kako ustrezno uporabiti veščine reševanja problemov v procesu snovanja rešitve (strateško znanje) [6]. Začetniki programerji se srečujejo s številnimi omejitvami. Pogosto imajo neustrezne miselne modele, težave pri smiselnem deljenju kompleksnega problema na manjše, obvladljive podprobleme, njihovo predznanje pa je običajno neorganizirano in površno. Zaradi teh pomanjkljivosti pristopajo k razumevanju Slika1: Dekompozicija problema iskanja povprečne programske kode in snovanju rešitev na nivoju posamezne vrednosti vpisanih števil (povzeto po [9]) vrstice v kodi [7]. Izkušeni programerji se od njih pomembno razlikujejo, saj pri razumevanju oz. snovanju rešitve uporabljajo Trdil je, da z eksplicitnim poučevanjem programskih specializirane kognitivne sheme, urejene po funkcijah. To jim vzorcev pozitivno vplivamo na razvoj strateškega znanja pri omogoča, da pristopajo k programiranju na višjem, začetnikih, ki je zanje najtežje dosegljivo. Pomembno konceptualnem nivoju, posledično pa so pri tem bolj učinkoviti raziskovalna smer na področju programskih vzorcev predstavlja in uspešni Error! Reference source not found. . To znanje je njihovo identificiranje, opisovanje in klasificiranje [11], [12] zajeto v programskih vzorcih. [13] [14]. Cilj prizadevanj je znanje, ki je zajeto v programskih Programski vzorci so od programskega jezika neodvisne vzorcih, narediti eksplicitno. V tabeli 1 predstavljamo izbor rešitve algoritemskih problemov na konceptualnem nivoju, ki se programskih vzorcev iz literature [15], ki smo jih našli pri analizi pogosto pojavljajo pri reševanju problemov z računalnikom. predstavljenih nalog. Predstavljajo gradnike, ki ponazarjajo načine razmišljanja in Programske vzorce so avtorji uspešno uporabili na različnih sklepanja ter omogočajo pristopanje k snovanju programskih področjih poučevanja programiranja: kot modul v programskem rešitev na abstraktnem nivoju. Uporaba programskih vzorcev okolju za učenje uvodnega programiranja [16], za izboljšanje programerju omogoča, da se najprej osredinja na višje nivojske rezultatov pri predmetu uvodnega programiranja [17], na oz. meta koncepte ter relacije med njimi, šele nato pa se ukvarja področju učenja s pomočjo iger [18], za analizo napačnih s tem kako bo rešitev zakodiral v izbranem programskem jeziku. razumevanj [5] in ugotavljanje kompleksnosti rešitev v V članku bomo predstavili analizo programskih kod rešitev programskem okolju Scratch [19]. za dve nalogi iz uvodnega programiranja 50 visokošolskih Ključne prednosti uporabe programskih vzorcev pri učenju študentov 1. letnika študijskega programa Praktična matematika, uvodnega programiranja so: zmožnost posredovanja splošnega na Fakulteti za matematiko in fiziko, Univerze v Ljubljani v programerskega znanja, ki je neodvisno od konkretnega študijskem letu 2020/21, ki so jih oddali v sistem Projekt Tomo programskega jezika [19]; učinkovitejše učenje splošnih visoko [10]. Projekt Tomo omogoča učiteljem sestavljanje nalog, nivojskih strategij in konceptov za snovanje rešitev in študentom pa nalaganje rešitev, za katere pridobijo avtomatično strukturiranje programov [11] [19]; prepoznavanje situacij, v povratno informacijo o pravilnosti. Cilj raziskave je ugotoviti ali katerih je smiselno uporabiti vzorec [16]; neposredno začetniki programerji uporabljajo programske vzorce, ali je prepoznavanje usvojenega konceptualnega znanja, ki se kaže v prisotnost/odsotnost pričakovanih programskih vzorcev vzorcih v kodi začetnikov ter naslavljanje težav, ki jih imajo pokazatelj njihove pravilnosti, kakšne so razlike v uporabi zaradi pomanjkanja strateškega znanja [13]. programskih vzorcev v nepravilnih rešitvah ter kako je iz V raziskavi analiziramo programsko kodo študentov - zaporednih oddaj možno slediti razvoju rešitve iz vidika uporabe začetnikov programerjev, ki so kodo oddali kot rešitev v sistem oz. kombiniranja programskih vzorcev. za avtomatično vrednotenje pravilnosti kode – Projekt Tomo. Sistem so razvili na Fakulteti za matematiko in fiziko, Univerze v Ljubljani leta 2010 in ga uporablja več kot 30 izobraževalnih 2 PREGLED LITERATURE inštitucij v Sloveniji. Podpira tri različne programske jezike: Programski vzorci že desetletja predstavljajo aktivno in Python, Octave in R. Učiteljem omogoča ustvarjanje lastnih pomembno raziskovalno področje. Avtorji so preučevali različne nalog, uporabo nalog, ki so jih ustvarili drugi in spremljanje vidike njihove uporabe v okviru uvodnega programiranja. Prvi, napredka učencev. Njim nudi takojšno povratno informacijo o ki je vzorce preučeval v okviru uvodnega programiranja je bil pravilnosti naloge in predstavlja okolje za samostojno učenje. 547 Pomembna lastnost sistema je, da hrani vse zaporedne oddaje Rešitev naloge je oddalo 49/50 študentov, ena od njih je bila posameznega učenca, tako da lahko spremljamo razvoj rešitve od napačna. Študenti so implementirali rešitev z uporabo while (35) začetne do končne oddaje [10]. in for zanke (14). Tabela 1: Opis izbranih programskih vzorcev (povzeto po [15]) Programski vzorec Opis Procesiraj vse Z zanko dostopimo do vseh elemente vrednosti v zbirki in jih procesiramo Posredno sklicevanje Posredno sklicevanje v vseh oblikah (klici funkcij, vrednost v seznamu…) Štetje Štetje objektov, vrednosti, dogodkov, ki ustrezajo kriteriju Nepovezana izbira Zaporedno preverjanje več neodvisnih pogojev Zanka in pol Izstopni pogoj je v telesu zanke Slika 2: Programski vzorci vključeni v rešitve naloge »Pica« Ekstremne vrednosti Iskanje ekstremne vrednosti v zbirki z zanko glede na izbran kriterij Slika prikazuje, kateri programski vzorci so vključeni v Ali pogoj velja ali ne Pogojni stavek, ki ne določa kaj se pravilne (zelena pika), pravilne z odvečno kodo (zelena in zgodi, če pogoj ni resničen vijolična pika) in nepravilne (rdeča pika) rešitve. V rešitvah so Alternativna akcija Pogojni stavek, ki določa kaj se se pojavljali trije programski vzorci: procesiraj vse elemente, zgodi, ko je oz. ni izpolnjen pogoj posredno sklicevanje in štetje. Vse pravilne rešitve so Računanje vsote Seštevanje vrednosti v zbirki z vključevale programski vzorec procesiraj vse elemente (48/48 = zanko 100%) , sledil je vzorec posredno sklicevanje (36/48 = 75%) in Filtriranje zbirke Procesiramo elemente, ki ustrezajo štetje (3/48 = 6%). Iz rezultatov lahko sklepamo, da pravilna pogoju rešitev naloge zahteva uporabo vzorca procesiraj vse elemente. Prirejanje Podatkovnemu objektu priredimo Vzorec posredno sklicevanje pa so morali uporabiti tisti študenti, vrednost ki so se odločili za uporabo while zanke, saj je to edini način za sklicevanje na elemente v seznamu. V programskem jeziku Stalna povratna informacija je v procesu učenja Python lahko uporabimo zanko for kot iterator, takrat pa programiranja izjemno pomembna za pridobivanje sklicevanja ne potrebujemo. Trije študenti (16, 21 in 32) so konceptualnih znanj in razvoju programerskih veščin. Običajno uporabili programski vzorec štetje, ki je odvečen, saj ne vpliva imajo učitelji v razredu veliko učencev, zato se težko posvetijo na pravilnost naloge. vsakemu učencu pri odkrivanju napak. Ročno iskanje napak je namreč težavno in zamudno. Avtomatizirani sistemi za Študent 1 - pravilna Študent 21 - pravilna ocenjevanje pomagajo učiteljem, da se hitreje odzovejo, Vzorec: procesiraj vse elemente Vzorci: procesiraj vse elemente, štetje in posredno sklicevanje učencem pa omogočijo, da se lahko učijo v lastnem tempu. sestavine = ['testo', 'pelati', 'sir', 'olive', 'jajce'] sestavine = ['testo', 'pelati', Tovrstni sistemi pomagajo učiteljem pri ustvarjanju učnih gradiv, for i in sestavine: 'sir', 'olive', 'jajce'] print(i) stevec = 0 sledenju učnemu procesu in analizi rešitev, ki jih učenci nalagajo element = 0 v sistem [10]. while stevec != len(sestavine): print(sestavine[element]) stevec += 1 element += 1 3 REZULTATI V raziskavi smo analizirali 10 različnih nalog. V tekoči prispevek Slika 3: Programska koda z označenimi vzorci za rešitvi bomo analizirali rešitve dveh nalog, ki najbolj nazorno opiše študentov 1 in 21 za nalogo »Pica« pomen prisotnosti programskih vzorcev kodi študentov: »Pica« in »Iskanje lastnosti« . Raziskava je temeljila na neslučajnostnem Slika prikazuje kako sta študenta z oznako 1 in 21 priložnostnem vzorcu 50 študentov prvega letnika Fakultete za implementirala programske vzorce. Študent 1 je uporabil zanko matematiko in fiziko, smeri Praktična matematika, v študijskem for v programskem jeziku Python kot iterator in je na ta način letu 2020/2021. Rešitve, ki so jih oddali v sistem Projekt Tomo implementiral programski vzorec procesiraj vse elemente. smo ročno pregledali in v njih iskali vzorce. Študent 21 pa je uporabil drugačen pristop in je ta vzorec implementiral z uporabo zanke while, pri čemer je uporabil 3.1 Analiza končnih rešitev naloge – Pica spremenljivko element za sklicevanje na posamezne elemente ter Definicija naloge: Napišite program, ki bo po vrsti izpisal funkcijo len v kombinaciji s spremenljivko stevec, da je ugotovil sestavine za pico, naštete v seznamu sestavine = ['testo', 'pelati', ali je dostopil do vseh elementov v seznamu. Za določanje konca 'sir', 'olive', 'jajce'], vsako v svojo vrstico. bi lahko uporabil kar spremenljivko element, zato je uporaba 548 posebne spremenljivke, s katero je štel elemente v seznamu 3.3 Analiza končnih rešitev naloge – Iskanje (programski vzorec štetje), odvečna. lastnosti 3.2 Analiza zaporednih oddaj naloge – Pica Definicija naloge: Izpiši število znakov najkrajšega niza v poljubnem seznamu. Z analizo zaporednih oddaj smo spremljali proces gradnje rešitve Rešitev naloge je oddalo 46/50 študentov. Med oddanimi za nalogo »Pica« iz vidika uporabe programskih vzorcev pri rešitvami bilo 37 pravilnih in 9 napačnih. Radi bi izpostavili, da študentih z identifikacijsko številko: 3, 7, 9, 21 in 29 (Slika ). smo med analizo ugotovili, da je 8 rešitev, ki so bile nepravilne, Projekt Tomo ovrednotil kot pravilne. Po našem mnenju gre za primere, ko so študenti vedeli za princip delovanja preverjanja pravilnosti in so ga namerno ukanili. Med pravilnimi rešitvami smo odkrili naslednje kombinacije programskih vzorcev, ki odražajo tipe reševanja: Tip-1 (24/37), Tip-2 (6/37), Tip-3 (2/37) in Tip-4 (3/37). Te so prikazane v tabeli 2. Tabela 2: Kombinacije programskih vzorcev v različnih tipih pravilnih rešitev za nalogo “Iskanje lastnosti” Programski vzorec Tip-1 Tip-2 Tip-3 Tip-4 Procesiraj vse + + + + elemente Slika 4: Programski vzorci v zaporednih oddajah študentov Ali pogoj velja ali ne + - - - 3, 7, 9, 21 in 29 za nalogo »Pica« Alternativna akcija - + - - Prirejanje + + + - Študent 3 je rešitev oddal dvakrat. V prvi oddaji ni uporabil Posredno + + + + nobenega programskega vzorca, rešitev pa je bila nepravilna. Pri sklicevanje drugi oddaji je uporabil oba pričakovana vzorca, rešitev pa je bila Ekstremne vrednosti - - + + pravilna. Filtriranje zbirke - - - + Študent 7 je prav tako dvakrat oddal rešitev. V prvi je uporabil zanko while za dostopanje do vrednosti v seznamu, Slika grafično ponazarja, katere kombinacije programskih vendar se je zmotil v določanju pogoja za izstop iz zanke. Na ta vzorcev so se pojavljale v posameznih rešitvah. Zelena pika nad način ni dosegel zadnjega elementa v seznamu in posledično ni stolpcem pomeni, da je rešitev pravilna, rdeča označuje pravilno implementiral vzorca procesiraj vse elemente. V drugi nepravilno rešitev. Iz slike lahko vidimo, da se kombinacije oddaji je napako popravil, na ta način implementiral oba programskih vzorcev ponavljajo (tipi reševanja), prav tako pa, da pričakovana vzorca in njegova rešitev je postala pravilna. napačne rešitve ne vsebujejo ustrezne kombinacije vzorcev Študent 9 je trikrat oddal rešitev. V prvi oddaji je uporabil enega od tipov reševanja. programski vzorec nepovezana izbira, ki v kontekstu reševanje te naloge ni smiseln. Rešitev je bila nepravilna. V drugi oddaji je preverjal kako deluje while zanka v kombinaciji s funkcijo len, 5 pri čemer ni implementiral nobenega vzorca, rešitev pa je bila i 4 nepravilna. V zadnji oddaji je vključil oba pričakovana vzorca, orc vz 3 njegova rešitev pa je bila pravilna. mskira 2 Študent 21 je petkrat oddal rešitev. V prvi in tretji oddaji je rog uporabil programski vzorec štetje, ki v kontekstu reševanja P 1 naloge ni smiseln, rešitev pa je bila v obeh primerih nepravilna. 0 1 3 5 7 9 V drugi oddaji ni uporabil nobenega vzorca, rešitev pa je bila 11! 13! 15! 17 19 21 23 25 27 29 31 33! 35 37 39 41! 43 45 47 49! Študenti nepravilna. Zanimivi sta naslednji dve oddaji. V četrti je uporabil procesiraj vse elemente štetje posredno sklicevanje vzorce procesiraj vse elemente, štetje in posredno sklicevanje, zanka in pol ekstremne vrdnosti ali pogoj velja ali ne rešitev je bila pravilna, vendar je vključevala odvečno kodo (tisto, alternativna akcija računanje vsote filtriranje zbirke ki je implementirala vzorec štetje). V zadnji oddaji je odstranil prirejanje funkcionalnost programskega vzorca štetje in na ta način napisal pravilno rešitev brez odvečne kode. Radi bi omenili še primer študenta 29, ki je oddal svojo Slika 5: Programski vzorci v oddanih rešitvah za nalogo rešitev v obliki funkcije. Sistem Projekt Tomo je njegovo rešitev “Iskanje lastnosti” ovrednotil kot nepravilno, čeprav je bila njegova rešitev konceptualno pravilna. Analiza s programskimi vzorci je Analiza je potrdila, da vse pravilne rešitve vsebujejo pokazala, da je uporabil oba pričakovana vzorca in je bolje programska vzorca: procesiraj vse elemente in posredno napovedala pravilnost rešitve. sklicevanje. Nalogo je nemogoče v splošnem pravilno rešiti, če ne dostopimo vsakega niza v seznamu, zato je uporaba procesiraj vse elemente nujna. Vzorec posredno sklicevanje sicer ni nujen, 549 saj lahko do elementov v programskem jeziku Python dostopamo ev 4 tudi preko iteratorja z uporabo zanke for. Študenti so v rešitvah večinoma uporabljali while zanko, ki pa zahteva uporabo tega vzorc 3 vzorca. To lahko pripišemo temu, da je bil to učni sklop učenja 2 ramskih uporabe zanke while. Najbolj pogosta rešitev je bila Tip-1. Pri tej ogpr 1 rešitvi so študenti uporabili programski vzorec ali pogoj velja ali ne, da so z njim iskali lokalni minimum. Tega so uporabili v evilo 0 Št 2 11 11 11 15 33 33 33 49 49 49 kombinaciji z vzorcem prirejanje, da so ga shranili. Podobna Zaporedne oddaje študentov rešitev je Tip-2, pri kateri pa je funkcionalnost ali pogoj velja ali procesiraj vse elemente štetje posredno sklicevanje ne zamenjal vzorec alternativna akcija. V rešitvah Tip-3 je zanka in pol ekstremne vrednosti ali pogoj velja ali ne lokalni minimum realiziran preko vzorca ekstremne vrednosti. alternativna akcija prirejanje Študenti so v tem primeru minimalni element iskali s pomočjo funkcije min, ki pa dejansko implementira enega od prejšnjih Slika 7: Programski vzorci v zaporednih oddajah študentov tipov reševanja. Vseeno smo se odločili, da ga štejemo kot 2, 11, 15, 33 in 49 za nalogo »Iskanje lastnosti« poseben tip, saj izkazuje, da študent pozna in zna uporabiti vgrajeno funkcijo min. Rešitve Tip-4 pa ponazarjajo manj Študent 2 je v svojo rešitev vključil vse pričakovane vzorce pričakovan pristop k reševanju problema in sicer so študenti rešitve Tip-1. Napaka, zaradi katere je sistem za avtomatsko ustvarili nov seznam, v katerega so shranili dolžine nizov iz preverjanje pravilnosti Projekt Tomo rešitev označil kot vhodnega seznama in nato uporabili funkcijo min. nepravilno, je bila odsotnost izpisa končne vrednosti. Gre zgolj Analiza s programskimi vzorci nam omogoči vpogled v za površnost, saj je očitno, da študent nalogo zna rešiti. rešitve na konceptualnem nivoju, ki je od programskega jezika Študent 11 je trikrat oddal rešitev. Iz slike je razvidno kako neodvisen. Tako lahko hitro ugotovimo, da sta rešitvi je v vsako oddajo vključil drugo kombinacijo programskih konceptualno ekvivalentni, čeprav sta implementirani drugače. vzorcev, nobena pa ni enaka kombinaciji enega od tipov Slika prikazuje dve različni implementaciji konceptualno reševanja. Trik, ki ga je uporabil, da je »ukanil« sistem ekvivalentne rešitve (Tip-1). preverjanja pravilnosti, je bilo preverjanje dolžine nizov s konkretnim številom 3. To je bila dolžina najkrajšega niza v Študent 2 - pravilna Študent 9 - pravilna Vzorci: procesiraj vse elemente, ali Vzorci: procesiraj vse elemente, ali podanem primeru. Takrat je to izpisal kot rezultat. pogoj velja ali ne, prirejanje in posredno pogoj velja ali ne, prirejanje in posredno sklicevanje. sklicevanje. Študent 15 je sistem »ukanil« tako, da je z zanko dostopil do seznam = ['testo', 'pelati', seznam = ['testo', 'pelati', vseh vrednosti v seznamu, nato pa izpisal dolžino zadnjega. Ker 'sir', 'olive', 'jajce'] 'sir', 'olive', 'jajca'] najmanjsa = len(seznam[0]) najkrajsa = len(seznam[0]) je bil to najkrajši niz v podanem primeru je to sistem ovrednotil i = 1 for i in seznam: kot pravilno. Iz analize vključenosti programskih vzorcev pa je while i < len(seznam): if(len(i) <= najkrajsa): dolzina = len(seznam[i]) najkrajsa = len(i) razvidno, da nobena od rešitev ni ustrezala pričakovanim if dolzina < najmanjsa: print(najkrajsa) najmanjsa = dolzina kombinacijam. i += 1 print(najmanjsa) Študent 33 je oddal rešitev trikrat. Nobena od rešitev ni vsebovala pričakovanih kombinacij vzorcev, vse od njih pa so bile nepravilne. Študent je sistem vrednotenja »ukanil« tako, da je med zaporednih dostopanjem do nizov v seznamu iz podanega Slika 6: Programska koda z označenimi vzorci za rešitvi primera hkrati gradil nov seznam z dolžinami teh nizov. Nato je študentov 2 in 9 za nalogo »Iskanje lastnosti« le izpisal vrednost zadnjega elementa iz novega seznama. Študent 49 je oddal tri rešitve. Vse so bile nepravilne, čeprav 3.4 Analiza zaporednih oddaj naloge – Iskanje jih je sistem označil kot pravilne. Sistem vrednotenja je ukanil lastnosti tako, da je ustvaril nov seznam in vanj sam ročno vpisal dolžine Z analizo zaporednih oddaj smo spremljali proces gradnje rešitve nizov iz podanega primera. Nato je na njem uporabil funkcijo za nalogo »Iskanje lastnosti« iz vidika uporabe programskih min, ki je vrnila najmanjšega. Naša analiza je pokazala, da vzorcev pri študentih z identifikacijsko številko: 2, 11, 15, 33 in nobena od rešitev ni imela ustrezne kombinacije pričakovanih 49 (Slika ). Te primere smo izbrali, ker želimo pokazati kako programskih vzorcev. analiza programskih vzorcev v kodi bolj zanesljivo napove pravilnost rešitve, kot avtomatično preverjanje pravilnosti v Projekt Tomo. Ta je namreč rešitve študentov 11, 15, 33 in 49 4 ZAKLJUČEK označil kot pravilne, čeprav niso bile, rešitev študenta 2 pa kot V raziskavi smo se ukvarjali s prisotnostjo programskih vzorcev nepravilno, čeprav je bila pravilna. Slednji deluje na osnovi v rešitvah študentov uvodnega programiranja. Zanimalo nas je klicev testnih funkcij, kar nekateri študenti uporabijo pri tem, da ali so vzorci prisotni oz. katere programske vzorce je možno avtomatično preverjanje ukanijo v svoj prid. Programski vzorci najti. Skušali smo ugotoviti ali prisotnost pričakovanih pa ponazorijo idejo rešitve, saj lahko z njimi dobimo vpogled v programskih vzorcev dobro napoveduje pravilnost rešitve in kaj rešitev na višjem nivoju abstrakcije. Rezultati nakazujejo, da ta nam razkrije spremljanje procesa reševanja programerskega način bolj zanesljivo napove pravilnost rešitve. problema z opazovanjem uporabljenih kombinacij programskih vzorcev pri zaporednih oddajah. Analiza rešitev programskih kod je pokazala, da študenti uporabljajo programske vzorce pri reševanju nalog iz 550 programiranja. 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Adams, Sue Fitzgerald, William Fone, John Hamer, Morten Lindholm, Robert McCartney, Jan Erik Moström, Kate Sanders, Otto Seppälä, Beth Simon, and Lynda Thomas. 2004. A multi– national study of reading and tracing skills in novice programmers. ACM SIGCSE Bulletin 36, 4 (February 2004), 119–150. 551 Animacija, ustvarjena z orodjem Stop Motion Animation Made With the Tool Stop Motion Sonja Žmavc OŠ Toma Brejca Kamnik, Slovenija zmavcsonja@gmail.com POVZETEK interesting. Animation is a form of film where moving images are created by rapidly exchanging drawings. We create the Pouk v času epidemije je uvedel nove pristope upodabljanja illusion of movement in this case with the help of photos. During šolskih prireditev. Kulturna šolska prireditev zajema govorni the lesson, the teacher is forced to use a tool that is easy to use nastop, igro, ples in scenografijo. V času epidemije je bila and that would make it easier for the students to learn all the prireditev prenesena v digitalno obliko in tako so si jo vsi učenci intended learning goals and develop creativity. lahko ob istem času pogledali preko spletne povezave. The article presents the process of sketches, creation of Poleg igre in nastopov učencev, ki so bili posneti, je bila videu illustrations and photography in the Stop Motion tool, which dodana še animacija za popestritev. Animacija je oblika filma, v gives us the illusion of movement. katerem se s hitrim izmenjevanjem risb ustvarijo gibljive podobe. Ustvarjamo iluzijo gibanja, v tem primeru s pomočjo fotografij. The final result of the product is presented in the form of a clip. Pri pouku je učitelj primoran uporabiti orodje, ki je nezahtevno We decided to choose this tool because it is not complicated to za uporabo, in z uporabo tega učenci najlažje usvojijo vse use, it is accessible on all school tablets, with which we used the predvidene učne cilje ter razvijajo ustvarjalnost. created photo directly in the tool. V prispevku je predstavljen proces načrtovanja, ustvarjanja Students were highly motivated to use the Stop Motion tool, they ilustracij in fotografiranja z orodjem Stop Motion, ki nam had more work to do with making storyboard and drawing omogoči iluzijo gibanja. illustrations. Končni rezultat izdelka je predstavljen v obliki posnetka. Za KEYWORDS izbiro tega orodja smo se odločili, ker uporaba ni zapletena in je dostopno na vseh šolskih tabličnih računalnikih, s katerimi smo Stop Motion, storyboard, sketch, illustration, distance school ustvarjeno fotografijo direktno uporabili v orodju. event Za uporabo orodja Stop Motion so bili učenci visoko motivirani, več dela so imeli z načrtovanjem snemalne knjige in risanjem 1 UVOD ilustracij. Po učnem načrtu za likovno umetnost iz leta 2011 učenec v tretjem vzgojno-izobraževalnem obdobju razvija uporabo KLJUČNE BESEDE digitalnih orodij pri pouku likovne umetnosti. Ti naj bi Stop Motion, snemalna knjiga, skica, ilustracija, prireditev na uporabljali digitalno tehnologijo pri razvijanju spretnih daljavo zmožnosti, in sicer: ABSTRACT - razvijanje izrazne zmožnosti pri risanju na ploskvi in s tem negovanje individualnega likovnega izraza; Lessons during the epidemic brought new approaches to - kot podporo kritičnemu mišljenju, ustvarjalnosti in depicting school events. The cultural school event includes a inovativnosti; speech performance, a play, a dance and scenography. During the - uporaba digitalne tehnologije, s pomočjo katere se izdela epidemic, the event was transferred to a digital format, where all animirani film; students could watch the event at the same time via an online - uporaba osnovnih postopkov digitalnih tehnologij, s connection. katerimi se izdela fotografijo in pozornost je usmerjena In addition to the play and performances of the students, which na kadriranje [1]. were recorded, animation was added to the video to make it more Kot učitelji likovne umetnosti se veliko srečujemo z digitalnim oblikovanjem, zato so nam IKT-orodja blizu. Uporaba Permission to make digital or hard copies of part or all of this work for personal or in izpeljava učne ure v računalniški učilnici učencem omogoča classroom use is granted without fee provided that copies are not made or distributed občutek za tridimenzionalnost. Likovna umetnost ima poleg 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 teoretičnega dela največji delež praktičnega dela, pri katerem se be honored. For all other uses, contact the owner/author(s). učencem zagotavlja sproščeno ustvarjanje in preizkus novo Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia naučenih tehnik. Današnje generacije otrok si ne predstavljajo © 2022 Copyright held by the owner/author(s). 552 življenja brez računalnikov in interneta. Zaradi uporabe socialnih - fotografirati, omrežij hitro izgubijo interes do vsakdanjih opravil in obveznosti. - narediti majhno spremembo prizora, Otroška domišljija, branje, inovativnost so v pomanjkanju pri - posneti še eno fotografijo, generacijah, ki so vsakodnevno izpostavljeni socialnim - narediti majhno spremembo prizora, omrežjem, ki ponujajo neomejen dostop do sveta vplivnežev, - posneti še eno fotografijo, umetnikov in iger. Vse predstavljene podobe, ki jih otrok vidi, - ponavljajti tako dolgo, kot je potrebno, spremlja na internetu, pustijo vtis. Učitelji si prizadevamo in - z aplikacijo ali programsko opremo za urejanje združiti poskušamo izčrpati pozitivne in poučne izseke tega. Usmeritev fotografije v film [2]. otroka in njegove ustvarjalnosti v pravo smer je delo, ki ga Preden se lotimo dela, je smiselno, da se učencem predstavi opravljamo učitelji. Tako pri likovni umetnosti poskušamo nekaj primerov že ustvarjenih animacij stop-motion. Te je lahko vstopiti v njihov digitalni svet in uporabiti njihove spretnosti v najti na samem orodju Stop Motion ali pa na številnih spletnih umetniškem izražanju. Za izdelavo animacije je bilo potrebno straneh, posnetkih na YouTubu in seveda tudi socialnih omrežjih, poleg ideje, zasnove in izvedbe na koncu tudi vse skupaj ki so bistveni za današnji čas glede marketinga. Vsak umetnik se digitalno urediti in povezati zvok. V razvoj animacije so bili tako vključeni učenci 8. razreda. lahko predstavi brezplačno in dobi popularnost s pomočjo objave V nadaljevanju prispevka bo natančneje predstavljeno orodje na svojih socialnih omrežjih, kot sta Instagram in TikTok. Stop Motion, ki smo ga skupaj z učenci 8. razreda uporabljali. Primera ilustriranih in izrezanih animacij sta Animacija [3] in Paper Cut [4]. Primera animacij s predmeti sta Reklama za Mac and Cheese [5] in Leteči kolač [6]. 2 PRIMER UPORABE ORODJA STOP MOTION 2.2 Uvodna motivacija Po predstavitvi orodja za animacijo in ogledu posnetkov so 2.1 Kaj je Stop Motion? učenci dobili predstavo, kakšen bo končen izdelek. Stop Motion je aplikacija, ki se uporablja na tabličnih Medpredmetno povezovanje nam ponuja ozadje in potek zgodbe, s katerima se ustvarijo skice prizorov, ki so uprizorjeni v računalnikih in pametnih telefonih. Preko App Stora, Google animaciji. Učenci so se razdelili v skupine, znotraj katerih so si Play trgovine ali drugih platform, ki jih zagotavljajo različni med seboj razdelili naloge in zastavili načrt. Samostojno so s operacijski sistemi, se brezplačno naloži aplikacija Stop Motion pomočjo tabličnih računalnikov preverili zgodovinsko ozadje. Studio (Slika 1). Aplikacija je brezplačna za prenos in uporabo v Preučili so čas in prizorišče dogajanja in si na papir zarisali najosnovnejši obliki. To je zadostno za ustvarjanje filmov stop- snemalno knjigo. Izdelek, ki je najbolj izstopal od drugih, je bil motion z zvokom v visoki ločljivosti. vključen v video kulturne prireditve. To je bila učencem dodatna motivacija za trud in inovativnost. 2.3 Kako ustvariti snemalno knjigo? Ko dokončamo filmski scenarij in ugotovimo osnove svoje zgodbe, lahko začnemo risati svojo snemalno knjigo. Vse, kar potrebujemo, je kos papirja, razdeljen na okvirje. Šest sličic na stran je dober začetek, lahko jih je več. V vsak okvir narišemo osnovno sceno (Slika 2). Koristno je napisati opombe pod vsako risbo, za razumevanje prizorov. Uporabimo lahko tudi puščice za prikaz premikov kamere ali barv za razlikovanje predmetov scene od ozadja. Pomembno je, da prikažemo različne kote kamere in dejanja, ki jih želimo zajeti, in zabeležimo, kaj počnejo Slika 1: Prenos aplikacije v App Store naši liki in kako jih nameravamo posneti. Čeprav je mogoče kar začeti fotografirati in to ugotoviti pozneje. Veliko lažje je imeti Stop-motion je tehnika snemanja filmov, ki se uporablja za vizualizacijo filma pred animiranjem. oživitev neživih predmetov z uporabo niza fotografij. Med Nasveti za snemalno knjigo: vsakim posnetkom se predmeti v okvirju rahlo premaknejo, da se - Pri načrtovanju kotov kamere se prepričajte, da ustvari videz gibanja, ko se slike sestavijo. Količina časa, ki je občinstvo ve, kje so vaši liki. Najbolje je, da pred potrebna za izdelavo videa stop-motion, je v celoti odvisna od snemanjem od blizu prikažete pregled prizora. dolžine in obsega projekta. Eksperimentiranje s kratkimi 15- do - Uporabite kot kamere, ki prenaša vašo zgodbo. 30-sekundnimi videoposnetki naj traja manj kot eno uro. Seveda, Uporabite bližnje posnetke, ko želite sporočiti čustva, in če se želi ustvariti dovršene prizore ali uporabiti umetniške široke posnetke, ko želite poudariti okolje. stvaritve, kot je glina, lahko projekt stop-motion traja več dni. - Prepričajte se, da ima vsak prizor v vaši snemalni knjigi Ne glede na to, katero metodo se uporablja za ustvarjanje svoj namen. Ne želite dolgočasiti svojega občinstva. videa v stop-motionu, se uporabijo osnovni koraki: - Poskusite ne premikati kamere, razen če je to nujno. - ustvariti sceno, Tako bo snemanje veliko lažje, saj imate neprekinjeno - postaviti telefon na stojalo in pripraviti prizor, svetlobo in vam ni treba prilagajati ozadja [7]. - nastaviti telefon ali tablico, 553 Slika 4: Izrezovanje Slika 2: Skica snemalne knjige 2.4 Ilustracija Ilustracija je likovna zvrst, ki smo se jo pri pouku likovne umetnosti odločili uporabiti pri izdelavi animacije. Učenci so dobili navodilo, da se podrobno spoznajo z zgodbo in ozadjem zgodovinskega dogajanja Rudolfa Maistra. Za inspiracijo jim je bila knjiga Naš Maister (v stripu). Zaradi zgodbe v stripu so si učenci lažje ustvarili začetno snemalno knjigo. Osredotočili so se na bistvene podatke in dogajanja. Pri risanju ilustracije je pomembno, da imajo pomembni liki v zgodbi vedno enako podobo, da se lažje prepoznajo. Pri ilustraciji za animacijo se lahko učenci več poigravajo z mimiko obraza in premikanjem ustnic in oči, ki sinhrono z zvokom dobijo življenje. Za vsak premik ustnic, oči, rok ali predmetov so si učenci narisali dodatne dele. Vsak del so si pazljivo označili in shranili, da so imeli Slika 5: Postavitev elementov za primerjavo pripravljene vse elemente za snemanje prizorov. Učenci so za celostno podobo animacije uporabili svinčnik, 2.5 Fotografiranje in urejanje v aplikaciji suhe barvice in alkoholni flomaster (Slika 3). Za animacijo so učenci uporabili narisane ilustracije, narejene po Za lažjo uprizoritev množice ljudi si je učenka s pomočjo načrtih snemalne knjige. Ko so bile vse ilustracije in ozadja enobarvnih papirjev zarisala silhuete ljudi (Slika 4). Razdelila jih pripravljeni, smo uporabili orodje Stop Motion. Kot že je v več skupin, s čimer je potem v izdelavi animacije prikazala omenjeno, smo si za izpeljavo metode dela za ustvarjanje videa premikanje množice. S pomočjo dveh različnih odtenkov silhuet najprej postavili IKT-pripomoček na stabilno postavitev. Sledilo je pridobila globino prostora. Da je lahko njena ilustracija silhuet je fotografiranje ilustracij (oz. prizorov) in premikanje teh. Po izstopala, je za ozadje uporabila le prelivanje barv, ki predstavlja končanih fotografiranih prizorih smo si ogledali narejeni čas poznega popoldneva (Slika 5). posnetek (Slika 6). Med predvajanjem se je posnetek ustavil in uredil, kjer je bilo to potrebno (Slika 7). Za vsako posneto fotografijo orodje namreč ponuja možnost urejanja, spreminjanja in dodajanja (Slika 8, 9 in 10). Slika 3: Učenečeva ilustracija 554 Slika 6: Predvajanje animacije Slika 9: Urejanje barve fotografij Slika 7: Urejanje fotografij Slika 10: Dodajanje elementov v animaciji 3 REZULTATI Interaktivne dejavnosti so bile izbrane premišljeno in so učence postopoma vodile od usvajanja minimalnih do temeljnih standardov znanja. Končni projekt z vsem digitalnim oblikovanjem fotografij in montiranjem, dodajanjem zvoka znotraj orodja Stop Motion je bil združen v montaži s preostalimi igranimi posnetki, ki so ustvarili celoten video posnetek kulturne prireditve. Celotna skupina učencev je dosegla zastavljene učne cilje in pokazala zanimanje za nov projekt, po zasnovi njihovih zgodb. Povezava do končne kulturne prireditve, z vložkom animacije na 12 minuti in 32 sekund ter trajanje do 14 minute in Slika 8: Urejanje hitrosti predvajanja fotografij 57 sekund: Misel pesnika in odločnost generala. 4 ZAKLJUČEK Z digitalnim oblikovanjem in ustvarjanjem animacije se učenci soočajo s spretnostmi, ki jih silijo ven iz svojih okvirjev. Uporaba likovnih tehnik, ki se združijo z digitalnimi tehnikami, uporabljenimi v spletnem orodju, je trajnostna. Današnji umetniški svet vse več in več posega po internetnem prostoru, v katerem se predstavljajo, prodajajo umetniška dela. Umetnost je 555 v digitalni dobi širok pojem, saj se učenci lahko sedaj sprehodijo [3] Ungaro Goncalves, C., 2020. Dear Sunset. Dostopno na naslovu po spletnih galerijah, učilnicah ali svetu domišljije. https://www.instagram.com/p/CBI3M5SHxMO/ (8. 8. 2022). [4] Bips, 2014. Stop Motion Video- paper stop motion. Dostopno na naslovu https://www.youtube.com/watch?v=Xo2ioUYugMA (8. 8. 2022). LITERATURA IN VIRI [5] Peri, C., 2022. Mac and Cheese. Dostopno na naslovu https://www.instagram.com/p/CdZzxn0rDxV/ (8. 8. 2022). [1] Učni načrt. 2011. Program osnovna šola, Likovna vzgoja. Ljubljana, [6] Dagnino, A., 2021. Floating brownie turns into an Energy Ball. Dostopno na Ministrstvo za šolstvo in šport, Zavod RS za šolstvo. naslovu [2] How to make a stop-motion video on iPhone: Apps, ideas, and tips. Dostopno https://www.instagram.com/p/CMmnKREKWfd/?utm_source=ig_embed&i na naslovu https://backlightblog.com/stop-motion-video-on-iphone (8. 8. g_rid=c18bc6d3-3dbc-4615-a841-1d0b6e21b354 (8. 8. 2022). 2022). [7] Članek iz aplikacije Stop Motion Studio. Dostopno v aplikaciji Stop Motion Studio App (8. 8. 2022). 556 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek H Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume H Vseprisotne zdravstvene storitve in pametni senzorji Pervasive Health and Smart Sensing Uredniki / Editors Nina Reščič, Oscar Mayora, Daniel Denkovski http://is.ijs.si 13. oktober 2022 / 13 October 2022 Ljubljana, Slovenija 557 558 PREDGOVOR Pomen digitalnih zdravstvenih storitev v zadnjih desetletjih nenehno narašča. Staranje prebivalstva je neposredno povezano s povečevanjem števila kroničnih bolnikov, ki jim razvoj medicine sicer omogoča zdravstveno oskrbo in posledično tudi podaljševanje življenjske dobe, hkrati pa je zdravstveni sistem zaradi tega dodatno obremenjen. Razvoj digitalne tehnologije je prinesel vse več dostopnih orodij za stroškovno učinkovito vzdrževanje in izboljševanje zdravja in kakovosti življenja ter obenem pripomogel k razbremenitvi zdravstva. Nedavna pandemija COVID-19 je dodatno poudarila potrebo po zagotavljanju zdravstvenih storitev na daljavo. Tehnološki napredek je sicer nekoliko upočasnjen zaradi zakonodaje, saj digitalne tehnologije ne morejo nositi odgovornosti zaradi napačnih zdravstvenih odločitev, prav tako je zelo pomembno tudi varstvo podatkov in spoštovanje zasebnosti pacientov. Sodelovanje vseh pomembnih družbenih, zdravstvenih in pravnih akterjev tako pomaga postaviti stabilnejše in zanesljivejše temelje za razvoj, uvajanje in uporabo digitalnih zdravstvenih tehnologij in storitev. Vseprisotne zdravstvene storitve in uporaba pametnih senzorjev so tako ključni deli digitalnega zdravja. Pametni senzorji in razne nosljive naprave omogočijo spremljanje na daljavo in in tako dodatno podprejo spremljanje zdravstvenega stanja bolnikov v klinikah in izven njih. Dodatno lahko pametni in vseprisotni sistemi za spremljanje zdravja zmanjšajo določena tveganja in odkrijejo težave v zgodnejših fazah bolezni. Konferenco »Vseprisotni zdravstveni sistemi in pametni senzorji« organizira EU projekt WideHealth, t.i. »widening« projekt, katerega glavni namen je vzpostavljanje trajnostne mreže raziskav med vključenimi partnerji. Konzorcij projekta sestavlja pet partnerjev (trije »widening« in dva »non-widening«), ki preko izmenjav in drugih raziskovalnih sodelovanj poglabljajo znanje na treh glavnih področjih: »data-driven healthcare«, »human factors in pervasive health« in »federated learning«. Namen konference »Vseprisotne zdravstvene storitve in pametni senzorji« je izmenjava strokovnega znanja in napredka raziskav na omenjenih področjih. Na konferenci bo predstavljenih 12 prispevkov, ki se osredotočajo na različne vidike pametnega zaznavanja in vsesplošnega zdravja. V prvem delu konference so vključeni prispevki, ki se osredotočajo na prepoznavanje človeških aktivnosti z uporabo nosljivih naprav (vključno z novejšimi tehnologijami, npr. pametnimi očali). Prispevki drugega dela konference se osredotočajo na objektivno in subjektivno spremljanje duševnega zdravja. V zadnjem, tretjem, delu so zbrani prispevki, ki predlagajo nove aplikacije, metodologije in IKT rešitve za vseprisotne zdravstvene sisteme ter izboljšanje varnosti in zasebnosti v takih sistemih. 559 FOREWORD The importance of digital health is constantly growing in recent decades. The reasons are well known: on the one hand, the aging of the population is producing an increasing number of chronic patients, and the progress of medicine is keeping them alive and in need of care; on the other hand, the progress of digital technology is creating an increasing number of available tools to maintain and/or increase health and quality of life cost-effectively. The recent COVID-19 pandemic has further emphasized the need to provide remote medical services to patients, which has boosted the emergence and adoption of digital technologies, especially in telehealth and telemedicine. Technological advances have been slowed mainly due to legislation since bad medical decisions cannot be blamed on digital technologies, and security and privacy issues also cannot be neglected. However, the involvement of all the important social, medical, and legal actors helps set up a more stable and reliable foundation for developing, deploying, and using digital health technologies and services. Pervasive health and smart sensing are crucial parts of digital health. Smart sensors and wearables can augment the healthcare system, enabling remote monitoring and supporting the patient's medical condition in and out of the clinics. Furthermore, smart and pervasive health monitoring systems can reduce death risks, identifying the issues at earlier stages of the diseases. They are the main focus of our "Pervasive Health and Smart Sensing" conference, as the name suggests. The conference is organized by the EU WideHealth project, a widening project that aims to conduct research on pervasive eHealth and establish a sustainable network of research and dissemination across Europe. It connects five partners (3 widening and two non-widening) to share and develop their research on three main topics: data-driven healthcare, human factors in pervasive health, and federated machine learning. The Pervasive Health and Smart Sensing conference aims to share expertise and research advancements in these areas. The 12 papers we have accepted at the conference focus on different aspects of smart sensing and pervasive health. Several works utilize wearable devices (including new types, i.e., smart glasses) and machine learning for human activity recognition. Several others focus on objective and subjective monitoring of mental health. Finally, there are papers proposing new applications, methodologies, and ICT solutions for pervasive health and improving the security and privacy in such systems. 560 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Oscar Mayora Daniel Denkovski Nina Reščič Orhan Konak Hristijan Gjoreski Valentin Rakovic Diogo Branco Monika Simjanoska Martin Gjoreski Tiago Guerreiro Tome Eftimov Vito Janko Venet Osmani Junoš Lukan Eftim Zdravevski 561 562 Optimized Method for Walking Detection by Wristband with Accelerometer Sensor Aleksander Hrastič Matej Kranjec Primož Kocuvan alekshrastic@gmail.com matejkranjec04@gmail.com primoz.kocuvan@ijs.si University of Ljubljana, Faculty of University of Ljubljana, Faculty of Department of Intelligent Systems Electrical Engineering Electrical Engineering Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT detect whether the person is walking or not. However, many stud- ies have focused on using machine learning algorithms, which This paper presents the part of the gait impairment measurement provide high accuracy but are computationally expensive to im- algorithm, which consists exclusively of the walking detection plement in embedded systems (wristbands). algorithm. The purpose of the optimized algorithm is to improve We present to you a computationally inexpensive algorithm the detection of walking. Today’s embedded devices (like wrist- for detecting whether a person is walking or not. Furthermore, bands) have low-level interrupts that detect steps and, conse- the algorithm can detect walking and other daily activities similar quently, walking. The problem is that these could be inaccurate to the walking pattern and can be used on a low-power wristband in some cases. For example, a person can swing with a hand system. In our case, the most crucial aspect of our gait detection while sitting, and the device will detect steps. The importance of algorithm should be to detect as minimal cases as possible where walking detection is crucial for gait impairment measurements, the algorithm predicts that the person is walking naturally. Still, as gait data should only be collected when a person is walking in the actual case, the person is performing other activities. in a "normal" manner and not performing any other walking- An algorithm to measure gait deterioration (our next step) like activities. An algorithm to measure gait impairment will be will help the elderly prevent falls. The algorithm will monitor developed in the later stages of this study. We focused on improv- a person’s gait daily, and when a person’s gait deteriorates dra- ing the walking detection algorithm with statistical methods in matically, it will notify caregivers of increased chances of falling. both time and frequency domains in contrast to computation- Accordingly, caregivers can take the person to rehabilitative walk- ally expensive algorithms that use machine learning. The walk ing therapy or give them more care. detection algorithm has been optimized based on data collected by a wristband with a 3-axis accelerometer sensor. With our optimized algorithm, we got an average accuracy of 89.4%. We 2 RELATED WORK can conclude that our proposed method works well for detecting Advances in the accuracy and accessibility of wearable sensing when a person is walking normally. The algorithm successfully technology (e.g., fitness bands and smartwatches) has allowed detects "not natural walking" scenarios when the person is sit- researchers and practitioners to utilize different types of wearable ting and swinging their hand or walking with extreme hand sensors to detect walking. movements. In [2] the authors explored the possibility of detecting activity KEYWORDS from a smartphone-based accelerometer sensor. They used smart- phones placed in different positions(backpack, pocket, in hand) wristband, walking detection, FFT, periodogram, activity recog- to collect data when doing an activity (walking, fast walking, nition, hamming window slow walking, running). To reduce complexity, they computed the magnitude of the 3-axis accelerometer. The magnitude vector 1 INTRODUCTION is then processed using time and frequency domain statistical Every year number of older adults fall and injure themselves. For techniques. Finally, the statistical methods on the time-domain example, in Western Europe, in 2017 alone, 13840 per 100,000 measures are applied for state recognition, while the statistical older adults over the age of 70 are known to have fallen and techniques on the frequency-domain features are implemented injured themselves to the extent of medical assistance [1]. To for walking movement distinction. prevent such phenomena, measurement and monitoring of gait In [3], they use a smartphone with a gyroscope to collect deterioration in the elderly must be developed. One part of the data. They propose a new algorithm based on Fast Fourier Trans- such algorithm must consist of a walking detection algorithm form (FFT) [4] to identify the walking activity of a user who that detects whether a person is walking or not in a non-invasive can perform different activities and hold the smartphone differ- way. ently. The proposed algorithm (FFT) was able to achieve superior Wristbands with various sensors (e.g., accelerometer, gyro- overall performance compared to the other two best-performing scope) have proven to be an excellent technology for automatic algorithms (Short Time Fourier Transform (STFT) and Standard and non-invasive detection of daily activities. In this case, we can Deviation Threshold (STD TH)). use the acceleration vector data from the accelerometer sensor to The authors in [5] propose an algorithm that classifies human activity in real time based on data from an accelerometer attached Permission to make digital or hard copies of part or all of this work for personal to the subject. The algorithm uses dynamic linear discriminant or classroom use is granted without fee provided that copies are not made or analysis (LDA), which can dynamically update classifier matrices 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 without storing all training samples in memory. LDA is used to work must be honored. For all other uses, contact the owner /author(s). find a transformation of extracted features that separate data dis- Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia tribution into different classes while minimizing the distribution © 2022 Copyright held by the owner/author(s). of data of the same class in the newly transformed space. 563 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Aleksander Hrastič, Matej Kranjec, and Primož Kocuvan Compared to the state-of-the-art algorithm, our paper aims to combine the FFT and threshold algorithm from [2] and axis selec- tion algorithm from [3] while adding an upper bound threshold to detect exaggerated hand movements and excluding them from false positives. 3 METHODOLOGY The main goal of the research was to improve, or rather optimize, the gait detection algorithm based on statistical methods and frequency coefficients obtained from the measurements of the Empatica E4 bracelet accelerometer. To achieve this, we had to record data with the wristband while performing various activi- ties and test the performance of our algorithm on the collected data. The data was collected using the Empatica E4 wristband Figure 1: Example of raw signal from accelerometer sensor [6]. The sampling frequency for the 3-axis accelerometer is 32 Hz. It has an 8-bit resolution and a default range of ± 2 g with sensitive motion detection along three axes: x, y and z. threshold to prevent false walk detection when a subject is swing- 3.1 Data collection ing a hand uncontrollably, shown in the main algorithm 2 on line (18). This is more thoroughly described below. An Empatica E4 bracelet was used for data collection and placed First, we use the time windowing algorithm (Algorithm 1) to on the subject’s left wrist. The wristband was connected to a process the data in a shorter time frame. Then, we need to divide smartphone via Bluetooth and streamed real-time data that was the data into time windows (W). We found empirically that it is uploaded to the Empatica server. We have designed various routes best if the data window length (𝑤 ) is 5 seconds with a 2.5-second 𝑡 and defined actions on these routes, which the subjects should overlap (𝑜 ). 𝑡 carry out. Data was then collected from different individuals The time windows are then filtered (x, y, and z axes are filtered who wore the bracelet and followed the planned route. Various separately) with a high-pass Butterworth filter to capture the sig- walking styles were performed on the designed paths, such as nal proportionally (symmetrically) with respect to the time axis. normal walking, slow walking, fast walking, and walking with The general shape of the frequency response of a Butterworth random hand movements. Some actions involved sitting in a filter is defined as equation (1). Where 𝑓 is the cutoff frequency, 𝑐 chair and performing arm swings that are similar in motion to 𝜖 is the passband gain, and 𝑛 is the order of the filter. We chose arm swings if the subject were walking. the order of 𝑛 to be 5. We chose it heuristically. For our example, In [2], data was gathered from 7 individuals doing different the cutoff frequency was set to 1 Hz. walking styles (slow walking, fast walking, normal walking). They collected 27 samples. In our case, the data was collected 1 from 4 individuals shown in Table 1. We also collected a total of 𝐻 ( 𝑓 ) = (1) √︂ 2𝑛 𝑓 27 samples. 2 1 + 𝜖 𝑓𝑐 In the next step, we detect which of the three axes is the most Table 1: Table of participants sensitive for each time window. This step is accomplished by cal- culating each filtered axis’s standard deviation (STD) separately Participant Gender Age Disability and selecting the one axis with the highest STD value. A Male 22 None Afterward, we compute modified periodogram coefficients B Male 24 None from the most sensitive axis for each window. To calculate the C Male 83 Difficulty walking modified periodogram in the algorithm 2 we multiplied signal D Female 79 None windows with Hamming window, which is defined as (2). The Hamming window is an extension of the Hamming window and is a semi-cosine bell-shaped curve. Figure 1 shows all three axes of raw accelerometer data col- lected from the Empatica wristband. During an interval between 2𝜋 𝑛 20 seconds and 70 seconds, the subject wearing the Empatica 𝑤 (𝑛) = 0.54 − 0.46𝑐𝑜𝑠 , 0 ≤ 𝑛 ≤ 𝑀 − 1 (2) walked in a straight line. 𝑁 − 1 Where N represents total length of the window. 3.2 Algorithm Our optimized algorithm combines aspects from two papers For each time window, two main conditions had to be met for [2][3]. From the first paper, we used the modified periodogram it to be classified as "walking." thresholding algorithm to detect walking only when the mini- Modified periodogram coefficients are computed using equa- mum required hand activity is reached in frequency ranges that tion (3). Time windows that met the first condition (4), need to correspond to human walking activity. From the other paper, we have computed modified periodogram coefficients that are on implemented this on the 3-axial accelerometer. For each time the interval 0.6 to 2 Hz (𝑆 ( 𝑓 ) where 𝑓 represents all the fre- 𝑥 𝑥 𝑖 𝑖 window, we select and process only the data on an axis with the quencies inside the interval) and had higher mean than the mean most variance. Our contribution to the algorithm for walking of coefficients in the interval outside 0.6 to 2 Hz (𝑆 ( 𝑓 ) where 𝑥 𝑥 𝑜 detection is a combination of the two, with added upper bound 𝑓 represents all the frequencies outside the interval). 𝑜 564 Optimized Method for Walking Detection by Wristband with Accelerometer Sensor Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Algorithm 2 for detection of walking function Stationary(𝑑) 𝑛 ← 2 𝑛𝑜𝑟 𝑚 (𝑑 ) 𝑆 ( 𝑓 ) = |𝐹 ( 𝑓 ) |2 (3) 𝑥 𝑥 𝑚 ← 𝑛 [:] − ) 2 𝑚𝑒𝑎𝑛 (𝑛2 𝑠𝑑 ← 𝑠𝑡𝑑 (𝑚) Where F(f ) is output from FFT at desired frequency f. end function Require: 𝑊 Ensure: 𝑏𝑜𝑜𝑙𝑒𝑎𝑛 [] for all (𝑊 ) do ⊲ i represents index of current window in a 𝑖 𝑆 ( 𝑓 ) > 𝑆 ( 𝑓 ) (4) 𝑥 𝑥 𝑖 𝑥 𝑥 𝑜 loop if 𝑙𝑒𝑛𝑔𝑡ℎ(𝑆𝑡𝑎𝑡𝑖𝑜𝑛𝑎𝑟𝑦 (𝑊 )) ≥ 0 then 𝑖 𝑊 ← 𝐵𝑢𝑡𝑡𝑒𝑟𝑤𝑜𝑟𝑡ℎ𝐹𝑖𝑙𝑡𝑒𝑟 (𝑊 (𝑥 )) 𝑥 𝑖 The second condition (5) that had to be met for the time win- 𝑊 ← 𝐵𝑢𝑡𝑡𝑒𝑟𝑤𝑜𝑟𝑡ℎ𝐹𝑖𝑙𝑡𝑒𝑟 (𝑊 (𝑦)) 𝑦 𝑖 dow is that the STD of the vector norm of the unfiltered signal 𝑊 ← 𝐵𝑢𝑡𝑡𝑒𝑟𝑤𝑜𝑟𝑡ℎ𝐹𝑖𝑙𝑡𝑒𝑟 (𝑊 (𝑧)) 𝑧 𝑖 must be between 0.3 g and 0.7 g. The lower limit (0.3 g) ensures 𝑛 ← 𝑎𝑣𝑔(𝑛𝑜𝑟𝑚(𝑊 )) 𝑚𝑒𝑎𝑛𝑥 2 𝑥 that walking is not falsely detected when the subject is not mov- 𝑛 ← 𝑎𝑣𝑔(2𝑛𝑜𝑟𝑚(𝑊 )) 𝑚𝑒𝑎𝑛 𝑦 2 𝑦 ing. The higher limit (0.7 g) prevents walking detection when 𝑛 ← 𝑎𝑣𝑔(2𝑛𝑜𝑟𝑚(𝑊 )) 𝑚𝑒𝑎𝑛𝑧 2 𝑧 subjects move their arms uncontrollably. Both limits were de- 𝑎𝑚 ← 𝑎𝑟 𝑔𝑚𝑎𝑥 {𝑛 } 𝑚𝑒𝑎𝑛𝑥 2, 𝑛𝑚𝑒𝑎𝑛 𝑦 2, 𝑛𝑚𝑒𝑎𝑛𝑧 2 termined empirically based on our collected data set. The norm 𝑝𝑔 ← 𝑝𝑒𝑟 𝑖𝑜𝑑𝑜𝑔𝑟 𝑎𝑚 (𝑎𝑚, ℎ𝑎𝑚𝑚𝑖𝑛𝑔) ⊲ hamming is the is calculated using equation (6) where x, y, and z are the time- windowing function windowed accelerometer signal vectors, each representing an if (𝑚𝑎𝑥 (𝑎𝑚) − 𝑚𝑖𝑛(𝑎𝑚) > 0.3) and 𝑝𝑔 ( 𝑓 > axis. "i" means the same index on all three axes, ranging from 0.6 and 𝑓 < 2) then 1 to the length of the time window (this is calculated from the 𝑏𝑜𝑜𝑙 𝑒𝑎𝑛 ← 𝑏𝑜𝑜𝑙𝑒𝑎𝑛 + [1] raw signal using the (7) where N is a number of samples in a else time window). Time windows that satisfy both conditions are 𝑏𝑜𝑜𝑙 𝑒𝑎𝑛 ← 𝑏𝑜𝑜𝑙𝑒𝑎𝑛 + [0] classified as "walking"; all other window cases are classified as end if "not walking." end if end for 0.3 < 𝜎 > 0.7 (5) 𝑛𝑜𝑟 𝑚 4 RESULTS √︃ We ran the algorithm on different recordings taken with the Em- 2 2 2 𝑛𝑜𝑟 𝑚 = 𝑥 + 𝑦 + 𝑧 (6) 𝑖 𝑖 𝑖 𝑖 patica wristband. Slow and fast straight walking, stair climbing, and sitting involving arm swing. Figure 2 shows a dot plot where zero (on the y-axis) represents "no walking," and one represents "walking." The x-axis represents time (in seconds). Dots on the x-axis are linearly spaced by 2.5 √︄ Í𝑁 (𝑛𝑜𝑟𝑚 − 𝑛𝑜𝑟𝑚)2 seconds. During the first 8 seconds, the subject was standing, so 𝑖 𝑖 =1 𝜎 = (7) 𝑛𝑜𝑟 𝑚 for this part of the signal, the algorithm correctly classified it as 𝑁 "not walking." After 8 seconds, the subject started to walk in a straight line, and the algorithm correctly detected this activity as "walking." For our example, we can confirm that the algorithm works correctly under normal walking conditions. Algorithm 1 for windowing Require: (𝑎𝑐𝑐 , 𝑎𝑐𝑐 , 𝑎𝑐𝑐 ), 𝑤 , 𝑜 ⊲ 𝑜 is the overlap 𝑤 = 𝑥 𝑦 𝑧 𝑡 𝑡 𝑡 𝑡 length of the window Ensure: (𝑊 ,𝑊 ,𝑊 ) 𝑥 𝑦 𝑧 𝑊 ← [] 𝑠 ← 0 ⊲ 𝑠 = start index of windowl 𝑡 𝑡 𝑒 ← 𝑠 + 𝑤 ⊲ 𝑒 = end index of window 𝑡 𝑡 𝑡 𝑡 for all (𝑎𝑐𝑐 , 𝑎𝑐𝑐 , 𝑎𝑐𝑐 ) do 𝑥 𝑦 𝑧 while 𝑠 ≤ 𝑁 do ⊲ N is the number of samples in a 𝑡 window, i represents index of current sample in a loop ′ 𝑎𝑐𝑐 ← 𝑎𝑐𝑐 [𝑠 : 𝑒 ] 𝑖 𝑡 𝑡 𝑖 ′ 𝑊 ← 𝑊 + [𝑎𝑐𝑐 ] 𝑖 𝑠 ← 𝑠 + 𝑜 𝑡 𝑡 𝑡 𝑒 ← 𝑒 + 𝑜 𝑡 𝑡 𝑡 end while Figure 2: Proposed algorithm used on straight walking end for activity, recorded Empatica E4 wristband 565 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Aleksander Hrastič, Matej Kranjec, and Primož Kocuvan Table 2: Table of activities and their accuracy Activity Detected as "Walking" Detected as "Not walking" Accuracy Walking and swinging hand 47.5s 7.5s 86.4% Slow walking 52.5s 2.5s 95.5% alking Stair climbing 17.5s 37.5s 68% W Fast walking 5s 52s 91.2% Standing 7.5s 47.5s 86.4% alking Sitting 0s 55s 100% W Sitting and swinging hand 2.5s 52.5s 95.5% Not Walking and uncontrollably moving hand 0s 55s 100% Figure 3 shows an example of a recording where several human the elderly to walk fast. In the stairs climbing case, the algorithm did not perform very well, but that is not relevant in our case. activities are present, such as standing, sitting on a chair and More importantly, in the last 6 cases algorithm performs well in performing random hand movements, walking and performing detecting true negatives. hand movements, and walking and performing exaggerated hand movements. It can be seen that the algorithm had difficulty in gait classification when high-amplitude arm movements were present during the subject’s gait. This is because gait characteristics are lost in the noise of high-amplitude hand movements. For our purposes, the issue is not critical because the future end goal is to measure the subjects’ gait impairment, so there is no problem in discarding the parts of the signal where the person does not walk in a "natural" way. However, we can also observe that there was deviation when the subject sat down and started swinging his arm (One instance at the 42nd second where the algorithm should predict "not walking" but instead, it predicted "walking"). On Figure 4: Proposed algorithm used when sitting and swing- Figure 4 at about 78th second, we can observe that the algorithm ing hand, recorded on Empatica E4 wristband detected sitting as if it were walking. 5 CONCLUSION In the related work, we described the state-of-the-art algorithms used in today’s many applications. For this research, we selected two algorithms from many of them and expanded (optimized) the work for our purposes. The results of our algorithm were able to detect when a person was walking normally, slowly, and quickly. In addition, the algorithm correctly detected cases when a person does not walk while sitting but swings his arm. To measure gait impairment, we only want to use time win- dows of the signal where we are certain that the person is walking and that there are no additional "unnecessary" hand movements. In the future, we will further improve the algorithm so that the deterioration of walking, our final goal, can be measured cor- rectly. Figure 3: Proposed algorithm used on multiple activities, recorded on Empatica E4 wristband REFERENCES [1] Juanita A Haagsma et al. 2020. Falls in older aged adults in 22 european countries: incidence, mortality and burden of disease from 1990 to 2017. We require that we have the least amount of false positives in Injury Prevention, 26, (Feb. 2020), i67–i74. doi: 10.1136/injuryprev-2019-0433 our data set because we want to detect only the scenarios where 47. a person is walking the most naturally. This is a typical binary [2] Chalne T ornqvist. 2017. Walking movement detection using stationary sto- chastic methods on accelerometer data. MA thesis. Lund University. classification problem, where the final results are shown in Table [3] Guodong Qi and Baoqi Huang. 2018. Walking detection using the gyroscope 2. The first three activities (walking and swinging hand, slow of an unconstrained smartphone. In (Jan. 2018), 539–548. isbn: 978-3-319- 66627-3. doi: 10.1007/978- 3- 319- 66628- 0_51. walking...) are considered natural walking and should be detected [4] E. O. Brigham and R. E. Morrow. 1967. The fast fourier transform. IEEE as walking. The next 6 (Fast walking, standing, sitting, sitting Spectrum, 4, 12, 63–70. doi: 10.1109/MSPEC.1967.5217220. and swinging hand, walking and uncontrollably moving hand) [5] Yen-Ping Chen, Jhun-Ying Yang, Shun-Nan Liou, Gwo-Yun Lee, and Jeen- Shing Wang. 2008. Online classifier construction algorithm for human activity activities should be considered as "not walking" because they are detection using a tri-axial accelerometer. Applied Mathematics and Compu- less optimal for feature collection for the algorithm that will be tation, 205, 2, 849–860. Special Issue on Advanced Intelligent Computing implemented in the next stages of this study. The study we are Theory and Methodology in Applied Mathematics and Computation. doi: https://doi.org/10.1016/j.amc.2008.05.099. conducting is primarily meant for the elderly, so we categorized [6] [n. d.] Medical devices, ai and algorithms for remote patient monitoring. the "fast walking" scenario as not walking, as it is not common for empatica. https://www.empatica.com/. 566 Android Integration of a Machine Learning Pipeline for Human Activity Recognition Viktor Srbinoski, Daniel Denkovski, Emilija Kizhevska, Hristijan Gjoreski Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, N. Macedonia, Jozef Stefan Institute, Slovenia viktor_srbinoski@hotmail.com, danield@feit.ukim.edu.mk, emilija.kizhevska@ijs.si, hristijang@feit.ukim.edu.mk ABSTRACT more convenient to use smartphone sensors for the common user, as smartphones have become ubiquitous. In the last decade, smartphones have seen a serious growth Human activity recognition is a popular topic, which has in the processing power. Coupled with greater affordability been worked on extensively in the recent years [2]. Practical this has led to a worldwide smartphone ubiquity. Alongside applications for HAR are mainly in improvement of the the advances in processing and battery technology, there are quality of life and medicine. A great example of HAR models great advances in sensor technology as well, and every being used in medicine can be found in paper [3], which smartphone today comes equipped with multiple sensors: focuses on fall detection mainly for the elderly population. accelerometer, gyroscope, magnetometer etc. The sensory Using dedicated wearable sensors to recognize activities data is already being used in a variety of applications, among is the most common approach. Smartwatch is usually which several focus on the human activity recognition. In this equipped with the same sensors as the smartphones and has paper, we propose a smartphone Android integration of a a much more fixed position on the body (tightly around the machine learning pipeline for recognizing human activities. wrist). The drawback is that the arms are more prone to The proposed approach uses the 3-axis accelerometer in the random movement which introduces noise into the system smartphone, processes the data in real time, and then a and makes HAR more difficult. A detailed analysis on these machine learning model recognizes the user's activities in issues can be found in paper [4]. real time: walking, running, jumping, cycling and standing Using data from smartphone sensors to train models for still. The proposed Recurrent Neural Network model and its HAR has also been explored recently in [5], where a deep machine learning pipeline are developed on a publicly open neural network is trained on the data from multiple sensors activity dataset, which are then implemented into the on the smartphone. In our study we go a step further and Android application and once again validated on a dataset analyze and compare a simplified subset of the sensor data recorded with a smartphone itself. (only accelerometer magnitude) - which allows us to have a model that will work regardless of the smartphone KEYWORDS orientation and to have a simple yet effective method of Human activity recognition, machine learning, Android integrating a model into an Android application. integration, Tensorflow Light, recurrent neural network, We propose an Android integration of a Machine Learning accelerometer, magnitude. (ML) pipeline for recognizing human activities in real time on a smartphone. In particular, the proposed approach uses the 3-axis accelerometer in the smartphone, processes its data in 1 INTRODUCTION real time, and then the ML model recognizes the user's Human Activity Recognition (HAR) is the process of activities: walking, running, jumping, cycling and standing examining data from one or multiple sensors and still. The proposed Recurrent Neural Network (RNN) model determining which (if any) activity is being performed. The and its machine learning pipeline are developed on a publicly sensors are traditionally placed on key points on the human open activity dataset, then implemented into an Android body and contain composite data (accelerometer, gyroscope, application, which finally, is once again evaluated on a magnetometer data, etc.). Advances in sensor technology dataset recorded with a smartphone itself. Additionally, as have made sensors more compact and precise over the years, part of this study we release an Android application [6], but most importantly more affordable. Today these sensors which can be used by other researchers to easily gather data can be found in the standard package of any smartphone. with a smartphone and as a practical demonstration of how The purpose of this paper is to leverage these smartphone to integrate an ML model with an Android application and sensors to perform HAR in real time, by utilizing an Android use the built-in accelerometer data. application which continuously reads its own sensor data, instead of using the traditional dedicated wearable sensors. The premise is that the smartphone sensors have reached the 2 DATASET required quality to be comparable to the wearable sensors in The models were trained on a publicly available dataset accuracy [1]. The benefit of this approach is that it is much which was originally used to evaluate the impact of sensor placement in activity recognition [7]. The dataset consists of 567 wearable sensor readings from 17 healthy subjects which are the mean and the standard deviation of the 150 values perform any of 33 different activities. There are a total of 9 in the window. The three additional statistical features are: wearables placed on the body: two on each arm and leg, and  Mean first-order difference: average difference one on the back. Each wearable sensor reads 13 values with between consecutive values in the window. Computed a frequency of 50Hz: three for acceleration, three for by first creating a list of first-order differences between rotation, three for magnet flux vector and four for orientation consecutive values in the window and then calculating in quaternion format. This brings the total amount of the mean of this list. readings to 117 per frame (9 wearable sensors with 13  Mean second-order difference: average difference values each). Out of all these measurements only six are used: between consecutive elements in the list of first-order the 3 accelerometer values from each of the two upper leg differences. sensors (left and right). These sensors are chosen as they are  Min-max difference: difference between the minimum approximately at the location where a smartphone would be and maximum value in the window. (in a side pocket). Additionally, the magnitude of each sensor The feature extraction is performed on every sensor (x, y, is added as an additional feature, calculated as: z axis and magnitude on both accelerometers, left and right), which gives a total of 40 features. The features are then 𝑚𝑎𝑔𝑛𝑖𝑡𝑢𝑑𝑒 = √𝑎𝑐𝑐 2 2 2 ( 1 ) 𝑥 + 𝑎𝑐𝑐𝑦 + 𝑎𝑐𝑐𝑧 separated into three datasets: left accelerometer, right Due to the position of the sensors, recognizing motion accelerometer with 20 features each, and combined mainly expressed with the upper torso and arms is accelerometers which contains the data from both the left impossible, so the dataset is truncated to only activities that accelerometer and right accelerometer datasets, by matching are dependent on the legs: walking, running, jumping, cycling the respective features (e.g., x-axis on the left accelerometer and standing still. and x-axis on the right accelerometer are treated as the same feature: x-axis), thus the combined accelerometers dataset also contains 20 features, but it is twice as long. 3 METHODOLOGY To compare the effectiveness of a simplified version of the In order to adapt the dataset to fit the needs of this model that is orientation independent, a second version of application, certain preprocessing and feature extraction is the dataset is created. This dataset uses only the features performed, described in detail in the following subsections. extracted from the magnitudes of both accelerometers (5 features each). It is further split into three parts: magnitude- 3.1 Preprocessing and segmentation only left, magnitude-only right and magnitude-only combined, The dataset contains a disproportionate number of readings each containing five features. for standing still in comparison to all other activities. To correct this a random under-sampling is performed (only 5% 3.3 ML Models of the standing still data is used). Additionally, similar Multiple ML models were evaluated, such as K-NN, Linear activities are grouped together, namely jogging and running SVM, Random Forest, Naï ve Bayes and Neural Networks are grouped together as running, and jumping upwards, (DNN and RNN). jumping front and back, jumping side to side, and jump rope Ultimately the RNN model had the best performance. A are grouped as jumping. The resulting distribution of data is simple RNN was chosen as the ML model for this application. illustrated on Figure 1, with running having the most amount The model is created using Keras and contains two RNN of data (1760s), and cycling having the least (860s). layers with 512 nodes each and tanh activation function. The final decision layer is a Dense layer with 5 nodes and a softmax activation function. It is trained for 100 epochs with a sparse categorical cross entropy activation function. 4 EXPERIMENTS With the dataset prepared, the following experiments were conducted:  Accuracy comparison between magnitude-only and full- featured versions of the dataset. Figure 1 Activity distribution after selection  Evaluation of models trained on data from the left accelerometer and evaluated on data from the right, and Once selection has been performed, the data is grouped vice-versa. into 3-second windows. Since the data is collected at a frequency of 50Hz, each window contains 150 records. 4.1 Evaluation and metrics The models were evaluated using K-fold Cross- 3.2 Feature extraction Validation, where K is equal to the number of subjects, and After the data has been split into 3-second windows, five in each iteration a different subject’s data is used as the statistical features are calculated per window. The first two validation set. Splitting the data this way ensures that the test 568 data and train data do not both contain windows from the simplified and right simplified sets) which could be due to same subject (as consecutive windows from the same subject random noise. are very similar). Instead, when using the data from a In order to evaluate if the model takes in a bias from the separate subject as a validation set, a good estimate can be side on which it is trained or if the sides carry an intrinsic made of how the model will behave when a never seen before difference, the model was trained on one side and evaluated person’s data needs to be evaluated. on the other. This was done twice, trained on left and In every iteration of the K-fold Cross-Validation a evaluated on right, and trained on right and evaluated on left. confusion matrix is generated from the predicted values. The results are displayed on Figure 4, along with a control set From there the precision and recall are calculated for every which was trained and evaluated on the same side. activity as well as the overall accuracy. These metrics are compiled for every iteration and the average values across all iterations form the overall evaluation of the model. 4.2 Results Initially nine models were considered and evaluated on both the full-featured dataset and the magnitude-only dataset (for combined accelerometers). The results are illustrated on Figure 2, sorted by accuracy. Figure 4 Comparison between same and opposite side evaluation The accuracy differences are within 2% which is negligible, and in the case of the right accelerometer dataset, evaluating on the left actually increased the overall accuracy. This is due to the slight difference in quality between the left and right sides, and not due to switching sides when evaluating. These results suggest that there is no significant side bias Figure 2 Accuracy comparison of all inspected ML models in the models and thus the activity recognition will work regardless of on which side the smartphone is located. This The accuracy of the models with full features was in addition to the simplified model’s independence from expectedly higher than the magnitude-only version, with the orientation make it the ideal choice for integrating with a drop in accuracy being on average 7% (K-NN being the smartphone. exception with an increase in accuracy of 2%). The RNN had the highest accuracy in both cases, with 98.8% on the full- featured dataset and 95.8% on the magnitude-only dataset. 5 ANDROID INTEGRATION Therefore, the following results focus on the RNN model. In order to integrate with an Android smartphone device, The comparison in accuracy between the full-featured the magnitude-only model with combined accelerometers and magnitude-only versions was made on all three datasets was converted into a tflite format using the Tensorflow Lite (left, right and combined). The results for the RNN are library, which is the most commonly used library for artificial displayed on Figure 3. intelligence in Android. The converted models are then added in the file structure of an Android application which reads them into memory when it starts up and uses them in real time to recognize activities. All Android devices come equipped with accelerometers (along with many other sensors) and they can be accessed with the built-in class SensorManager, which is part of the default library: android.hardware. The data read by the SensorManager is on a by-axis basis and in the standard unit of m/s2. The orientation of the x, y and z axis is illustrated in Figure 5. Figure 3 Comparing full-featured and magnitude-only datasets The frequency with which the sensor records data is adjustable, with the tradeoff being higher quality data vs The average drop in accuracy for the RNN was 3% which is lower battery consumption. In our implementation, the well within acceptable boundaries. As a side note, the right sensor delay is set to 20ms between reads (50Hz frequency). side in general seems to show slightly weaker results, Since there is no way to predict which way the however at most this is 1.5% (when comparing the left smartphone will be oriented in the pocket, the magnitude of 569 the accelerometer is the only thing that is used in the feature The overall accuracy of the model was 90.2%, which is a calculation. The magnitude readings are kept in memory noticeable drop from the 95.8% evaluated from the original until 150 samples are accumulated (exactly 3s), which is the training dataset. This is expected, as there is a certain amount size of the window used in the training of the models. Then of noise introduced to the system from the fact that the the same statistical features are calculated on the collected smartphone is not fixed in place as rigidly as the wearables. window: mean, std. deviation, mean first-order and second- order differences, min-max difference. These values are then placed in a tensor and it is sent as the input into the model, 6 CONCLUSION which is also kept in memory (in the form of an object). The This paper presented a practical way of training and output of the model is also a tensor (the output layer which implementing a HAR model in an Android application, along has a softmax activation function), which is then converted with solving the practical issues of reading smartphone into a single result (the node with the highest value) and is accelerometer data such as unpredictable orientation and displayed on screen. whether it is kept on the left or right side. To determine whether there is an intrinsic difference between the left and right side or whether the models develop a side bias, an experiment was conducted where models were evaluated on the opposite side of where they were trained, and it was determined that no such bias existed. To gain independence from orientation, a simplified dataset was created which used only the magnitude readings. Training on this dataset resulted in an expected drop in accuracy, but within an acceptable margin. An RNN was trained on the magnitude-only dataset and integrated into an Android application which reads the accelerometer data and calculates the features in real time. The calculated features are used as an input for the model, which then outputs the predicted activity, and is subsequently shown on screen. The sensors in the used smartphone did prove to be of a Figure 5 Accelerometer axis orientation in smartphones comparable quality to the wearable sensors as the model Since 150 samples need to be accumulated before the successfully recognized activities recorded with smartphone features are calculated and the model is called to make the sensors with a solid accuracy of 90.2%, even though it was prediction, there is the side effect that the displayed value on trained on a dataset from wearable sensors. screen is 3s behind (in other words the current activity the user is doing will be displayed in 3s). All the data read by the ACKNOWLEDGEMENT accelerometer along with the prediction and a timestamp and is kept in memory (a single entry will contain all the This research was partially supported by the WideHealth calculated features from the 3-second window, the model project - EU Horizon 2020, under grant agreement No prediction and a timestamp). The user can choose to export 952279. this data to csv and use it as a dataset. The model was evaluated on a practically collected REFERENCES dataset with a Samsung Galaxy s20 smartphone (5 minutes of each activity). The predicted value was compared to the [1] Patima Silsupadol, Kunlanan Teja, Vipul Lugade, “Reliability and validity of a smartphone-based assessment of gait parameters across actual activity by cross-referencing the timestamps (the walking speed and smartphone locations: Body, bag, belt, hand, and activities were performed at specific times), and a confusion pocket”, Gait & Posture, Volume 58, 2017, [2] matrix was created, from which the precision, recall and f1 O. D. Lara and M. A. Labrador, "A Survey on Human Activity Recognition using Wearable Sensors," in IEEE Communications score, as well as overall accuracy, was calculated. The results Surveys & Tutorials, vol. 15, no. 3, pp. 1192-1209, Third Quarter 2013 are displayed on Figure 6. [3] Kozina, S., Gjoreski, H., Gams, M., & Luštrek, M. (2013, September). Efficient activity recognition and fall detection using accelerometers. In International competition on evaluating AAL systems through competitive benchmarking (pp. 13-23). Springer, Berlin, Heidelberg. [4] Gjoreski, M.; Gjoreski, H.; Luštrek, M.; Gams, M. How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls? Sensors 2016, 16, 800. https://doi.org/10.3390/s16060800 [5] Charissa Ann Ronao, Sung-Bae Cho, Human activity recognition with smartphone sensors using deep learning neural networks, Expert Systems with Applications, Volume 59, 2016, ISSN 0957-4174 [6] https://github.com/ViktorSrbinoski/SmartphoneActivityRecognition [7] Oresti Banos, Miguel Damas, Hctor Pomares, Ignacio Rojas, Mt Attila Toth, and Oliver Amft. A benchmark dataset to evaluate sensor Figure 6 Precision, recall and f1 score results on the practically displacement in activity recognition. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp ’12, pages 1026–1035, collected dataset on a Galaxy s20 smartphone New York, NY, USA, 2012. ACM. 570 Speaking Recognition with Facial EMG Sensors Antonio Nikoloski1, Petar Poposki1, Ivana Kiprijanovska2, *, Simon Stankoski2, Martin Gjoreski3, Charles Nduka1, Hristijan Gjoreski1, 2 1 Ss. Cyril and Methodius University in Skopje, N. Macedonia 2 Emteq Ltd, Sussex Innovation Centre, Science Park Square, Brighton, UK 3Università della Svizzera Italiana, Switzerland ivana.kiprijanovska@emteqlabs.com* ABSTRACT part due to its ability to be applied non-invasively, facial sEMG has been used to detect the activation of facial muscles that are With the advent of interactive virtual reality (VR) applications, activated during speaking. However, most sEMG sensors used in the interest in tools that allow users to engage with VR conventional speaking recognition systems have been attached environments unobtrusively and intuitively is growing. One such around the user's lips and neck. This poses a number of practical interfacing tool for VR applications is speech recognition, which issues, including the need for extra wearable devices in addition can contribute to enhanced human-computer interaction. In this to the VR headset, limited facial muscle movement, and user study, we explore the usage of a novel VR facial mask equipped discomfort. with seven surface electromyography (sEMG) sensors to To overcome these issues, in this study we explore the usage recognize if the user is speaking or not using machine learning. of a novel facial mask equipped with sEMG sensors. The mask We collected speaking and non-speaking data from 30 is incorporated into a VR headset to recognize if the user is participants. The machine learning pipeline that was developed speaking or not. Our approach is based on signal processing and included data preprocessing, de-noising, filtering, segmentation, machine learning (ML), which are used to develop a binary feature engineering, and training of a binary classification model. classification model. The experimental results indicate that the mask can be used to recognize the speaking activity. On the test data of five unseen participants, the best-performing model achieved an accuracy of 2 RELATED WORK 89% and an F1-macro score of 91. Additionally, by removing The first studies with sEMG sensors were performed by each sensor from the dataset, we analyzed the individual Piper[1]. Since then, researchers have been widely using sEMG influence each sensor has on the models' outcomes. We did not sensors to measure the electrical signal that emanates from observe a significant drop in the accuracy of the models, contracting muscles. The usefulness of the sEMG signal for indicating that using the mask speaking can be detected even if measuring human performance was demonstrated by Inman [2] some of the sensors are not used. who investigated the technical aspects of human locomotion. By KEYWORDS the early 1960s, the improvements in signal quality and convenience made the sEMG sensors a common tool in clinical speaking recognition, machine learning, classification, wearable and research laboratories. Despite their popularity, current sensors, surface EMG, facial muscles. recording methods can be problematic in maintaining signal fidelity when vigorous or long-duration activities are monitored [4] [3] . 1 INTRODUCTION Speech recognition by using sEMG was first used in the 80s Virtual reality (VR) is an emerging technology that has [4] [6] . The results in these studies were preliminary but introduced immersive user experience in virtual environments important for the further progress of the field. Jorgensen and and is expected to revolutionize the way we interact with the Binsted [6] showed that it is possible to recognize speaking even digital world. VR applications have already been widely used in if the words are spoken silently and/or without any actual sounds. many different disciplines, ranging from research and training Jou et al. [7] showed that it is possible to recognize not just the facilities to entertainment and healthcare. With the emergence of words but also the phonemes to a certain degree. Additional interactive VR applications, there is an increasing interest in new works include direct synthesis of speech via sEMG – which aids immersive tools that enable users to interact with VR people who have problems with their vocal cords or airways [8] surroundings in an unobtrusive and intuitive manner. One such [9] . interfacing tool for VR applications is speech recognition. Its Compared to the previous studies, we differ in the sense that incorporation with VR provides users with increased flexibility we are using a novel facial mask – emteqPROtm, which is for interfacing with VR environments and can contribute to equipped with seven sEMG sensors. The sEMG sensors may be improved human-computer interaction. more error-prone compared to the intramuscular EMG sensors, In recent years, surface electromyography (sEMG)-based and thus here we study their utility. Additionally, the location of interfaces have been utilized for unobtrusive interaction in a VR our sEMG sensors makes the task of speaking recognition more environment. sEMG is used to measure muscle contractions challenging because the facial mask is placed on the upper part using sensors applied directly on the skin by detecting changes of the face (as part of the VR headset) and not the mouth and the in surface voltages on the skin when muscle activation occurs. In lips – which would be more convenient for speech recognition. 571 3 DATASET features, and statistical features. The feature extraction procedure resulted in a total of 238 features. The data collection protocol included healthy participants that The extracted features were used as input to four classification were asked to read a pre-defined text (news article). Additionally, algorithms: (i) K- Nearest Neighbors [13] - a simple statistical we recorded a segment where the participants were sitting still, algorithm where a datapoint is assigned a class according to the i.e., we recorded a baseline session with a neutral face. This data most numerous class of its k nearest neighbors; (ii) Support was recorded while the participants were watching a neutral Vector Machine Classifier (SVM) [14] – an algorithm that works video, without moving their facial muscles or speaking. A total along the principle of finding a hyperplane in N-dimensional of 30 participants were recorded, of which 18 were male and 12 space to separate two classes of data points; (iii) Random Forest were female, with a mean age between 19 and 25 years. The [15] - an ensemble learning method that trains N decision trees native language of all the participants was Macedonian. using random subsets of data and features and determines the During the data collection protocol, we were using the instance’s class by majority voting among the trained decision emteqPROtm mask [10] [11] to record sEMG sensor data. The trees; and (iv) Extreme Gradient Boosting [16] - a gradient mask has seven EMG sensors (Figure 1): two frontalis sensors (6 boosting algorithm which trains decision tree models and 0 in Figure 1) used to monitor eyebrow movement; two sequentially, and each subsequent model strives to correct the orbicularis sensors (4 and 2 in Figure 1) used to monitor eye errors of its predecessors. movements; two zygomaticus sensors (5 and 1 in Figure 1) used to monitor mouth and cheek movements; and one corrugator sensor (3 in Figure 1) used to monitor forehead movements. 5 EXPERIMENTS 5.1 Evaluation Setup The recorded data was split into training (20 of the participants), validation (5 of the participants) and test datasets (5 of the participants). The train dataset was used to train the models, the validation was used to optimize hyperparameters, and the test dataset was used to report the accuracy. The evaluation metrics we used to test the performance of our models were accuracy and F1 score. Additionally, the experiments were performed so that the training validation and test subsets do not have overlapping participants - i.e., each participant's data is found only in one of the three subsets. This is done so that we replicate a scenario where the model is used in practice on participants that are not in the training dataset. 5.2 Default Hyperparameters Results Figure 2 presents the results (accuracy and F1-score) achieved by each of the algorithms with their default hyperparameters. We additionally included the Dummy Figure 1: emteqPRO face mask with all 7 EMG sensors classifier as a reference (which predicts the majority class). The results show significant improvement by all the algorithms 4 DATA PREPROCESSING AND compared to the Dummy classifier. The Random Forest and the MODELING SVM achieved similar results, while the XGBoost classifier achieved the best results overall (87% accuracy and 89% F1- The sEMG data were continuously recorded at a fixed rate of score). Apart from this, this classifier also scaled efficiently with 1000 Hz. These data underwent a data preparation process, which the size of the datasets, as it was able to quickly and efficiently included data filtering, segmentation, and feature engineering. create and train models. This was also beneficial for the To improve the quality of the sensor data, we performed signal hyperparameter optimization – explained in the next subsection. de-noising and filtering. The EMG signals were initially filtered with a Hampel filter to eliminate sudden peaks in the signals that emerge as a result of quick movements. Additionally, we also applied a frequency-based filtering method based on spectrum interpolation [12] to reduce the noise caused by electromagnetic interference. [12] A sliding window technique was utilized for data segmentation. Specifically, the data were segmented into windows of size of 0.5 seconds with 0.4 seconds overlap (0.1 seconds slide). Finally, for each sEMG channel, we extracted 34 features, including various amplitude-based features, amplitude derivatives, auto-regressive coefficients, frequency-based 572 1 portion of the baseline sessions, the model is falsely predicting 0.87 0.9 0.85 0.86 0.89 speaking activity. We speculate that the reason might be that 0.82 0.83 0.79 0.8 0.73 0.75 these two subjects were moving their head during the baseline 0.7 session, which may have caused the sensors to shift from their 0.58 0.6 original position and deteriorate their contact with the skin. 0.5 0.4 0.3 0.2 0.1 0 Dummy KNN SVM Random Forest XGBoost Accuracy F1 Score Figure 4: Continuous recognition results for the XGBoost Figure 2: Algorithm comparison (accuracy and F1-score) algorithm. The blue line represents true classes (1 – speaking, using default hyperparameters 0 – not speaking), and the orange line represents the predictions (1 – speaking) 5.3 Optimized Hyperparameters Results In the next step, we performed hyperparameter optimization. 5.5 Sensor Analysis Results This process involves iterative changes of certain parameters of We additionally analyzed the results achieved by the models a classifier. During this process, an interval for every if a certain sensor is missing. This way, we were able to check hyperparameter is defined, and afterward, each parameter is the importance of each sensor for the given task. Knowing the iteratively updated, and the performance of the models is positions of the sensors on the face, we wanted to learn how the monitored. During this step, all 238 features of the datasets were data would change if we were to drop data from a certain sensor used, and a large number of numerical and other parameters while keeping the rest. (such as kernel for SVM, booster for XGB, etc.) were tuned. The results are shown in Figure 5, which in general, show that Figure 3 presents the results (accuracy and F1-score) the drop in accuracy and F1 score is not significant for all the achieved by each of the algorithms after the hyperparameter sensors. The accuracy drops from 87% to 85% at most. A more optimization. The results show slight improvement for the KNN, detailed analysis shows that the sensors placed on left and right SVM, and XGBoost algorithms, the latest one achieving 89% orbicularis, corrugator, and left frontalis have the most impact on accuracy and 91% F1-score – which was the best score that we accuracy, i.e., the accuracy drops the most when one of these achieved on this dataset. sensors is missing. One of the reasons for this is that while the participants were speaking, they were actually reading – which 1 0.91 means they activated their eyes which is recorded by the 0.89 0.86 0.86 0.9 0.82 0.83 0.83 orbicularis muscles. This analysis shows us that certain muscles 0.78 0.8 activate more while speaking compared to others, so that is why 0.7 the model itself gains or loses accuracy more, depending on 0.6 which sensor is dropped. 0.5 0.4 0.3 90 88.8 89.0 89.3 0.2 87.6 87.9 87.8 88 87.5 87.3 87.3 0.1 86.5 0 86 85.2 KNN SVM Random Forest XGBoost 84.7 84.9 84.5 Accuracy F1 Score 84 82 Figure 3: Algorithm comparison (accuracy and F1-score) 80 using optimized hyperparameters Left Left Left Corrugator Right Right Right Frontalis Zygomaticus Orbicularis Orbicularis Zygomaticus Frontalis 5.4 Continuous Recognition Results Accuracy F1-score Figure 4 illustrates the continuous recognition results for the five subjects from the test set achieved by the best-performing Figure 5: Sensor analysis showing the performance when a XGBoost classifier. A comparison was made between the true particular sensor is missing. and the predicted class on a time scale, i.e., with a blue line, the true classes are presented (1 represents speaking, 0 represents not 6 CONCLUSION speaking). Additionally, the orange color presents the speaking predictions by the model. Each subject’s data is separated with In this work, we presented a ML approach for speaking black dashed lines in the figure. The results show that a large recognition using facial sEMG sensors integrated into a VR portion of the error is down to the baseline sessions of the last headset. The dataset was collected with 30 healthy participants two subjects in the test dataset, marked with red circles. In a large while reading a news article and watching videos. The results 573 show that the best performing model is XGBoost, which Proceedings of the 2021 ACM International Joint achieved 89% accuracy. Additionally, the error analysis per Conference on Pervasive and Ubiquitous Computing and participant showed that most of the misclassifications were Proceedings of the 2021 ACM International Symposium incorrect speaking predictions in the baseline (non-speaking) on Wearable Computers (pp. 23-25). sessions of two participants. We speculate that this is caused by [11] Gnacek, Michal & Broulidakis, John & Mavridou, Ifigeneia & Fatoorechi, Mohsen & Seiss, Ellen & the head movement of the participants and we plan to tackle this Kostoulas, Theodoros & Balaguer-Ballester, Emili & using the IMU sensor on the emteqPROtm mask. Kiprijanovska, Ivana & Rosten, Claire & Nduka, Charles. An additional problem was that while the participants were 2022. emteqPro-Fully Integrated Biometric Sensing Array reading, they were making small breaks, which were for Non-Invasive Biomedical Research in Virtual Reality. automatically labeled as speaking – but in fact were not speaking. Frontiers in Virtual Reality. 3. (Mar. 2022) This labeling problem will be tackled in future by using audio to [12] Mewett, D. T., Reynolds, K. J., & Nazeran, H. Reducing exactly label the speaking segments. power line interference in digitised electromyogram Finally, we plan to implement person-specific normalization recordings by spectrum interpolation. Medical and on the EMG data. This is an important step given that different Biological Engineering and Computing, 42(4), 524-531, participants have different facial muscles, and even more, those (2004). [13] D. Aha, D. Kibler (1991). Instance-based learning muscles are activated differently while doing the same facial algorithms. Machine Learning. 6:37-66. expressions or speaking. [14] Zhang, Yongli. (2012). Support Vector Machine Classification Algorithm and Its Application. 179-186. ACKWNOLEDGEMENT [15] Breiman, “Random Forests”, Machine Learning, 45(1), 5- Part of this study was supported by the Innovate UK Project no. 32, 2001. 81376: Virtual Reality rehabilitation tailored to older brain injury [16] Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A patients (Healthy Ageing), and part by the WideHealth project Scalable Tree Boosting System. In Proceedings of the 22nd no. 952279 - European Union’s Horizon 2020 research and ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16). Association for innovation programme. Computing Machinery, New York, NY, USA, 785–794. REFERENCES [1] Piper H (1912) Elektrophysiologie menschlicher Muskeln. Springer, Berlin, pp 1–163. [2] Inman, V. T., Saunders, J. B., & Abbot, L. C. (1944). Observations on the function of the shoulder joint. Journal of Bone and Joint Surgery, 26, 1-30. [3] M. Wand, M. Janke, and T. Schultz, “Investigations on Speaking Mode Discrepancies in EMG-based Speech Recognition,” in Proc. Interspeech, 2011, pp. 601–604. [4] N. Sugie and K. Tsunoda, “A speech prosthesis employing a speech synthesizer—Vowel discrimination from perioral muscle activities and vowel production,” IEEE Trans. Biomed. Eng., vol. BME-32, no. 7, pp. 485–490, Jul. 1985. [5] M. S. Morse and E. M. O’Brien, “Research summary of a scheme to ascertain the availability of speech information in the myoelectric signals of neck and head muscles using surface electrodes,” Comput. Biol. Med., vol. 16, no. 6, pp. 399–410, 1986. [6] C. Jorgensen and K. Binsted, “Web browser control using EMG based sub vocal speech recognition,” in Proc. 38th Annu. Hawaii Int. Conf. Syst. Sci., 2005, p. 294c. [7] S.-C. Jou, T. Schultz, M. Walliczek, F. Kraft, and A. Waibel, “Towards continuous speech recognition using surface electromyography,” in Proc. Interspeech, 2006, pp. 573–576. [8] J. Freitas, A. Teixeira, and M. S. Dias, “Towards a silent speech interface for portuguese,” in Proc. Biosignals, 2012, pp. 91–100. [23] A. Toth, M. Wand, and T. Schultz, “Synthesizing speech from electromyography using voice transformation techniques,” in Proc. Interspeech, 2009, pp. 652–655. [9] K.-S. Lee, “Prediction of acoustic feature parameters using myoelectric signals,” IEEE Trans. Biomed. Eng., vol. 57, no. 7, pp. 1587–1595, Jul. 2010. [10] Gjoreski, H., I. Mavridou, I., Fatoorechi, M., Kiprijanovska, I., Gjoreski, M., Cox, G., & Nduka, C. EmteqPRO: Face-mounted Mask for Emotion Recognition and Affective Computing. In Adjunct 574 Machine-learning models for MDS-UPDRS III Prediction: A comparative study of features, models, and data sources Vitor Lobo1, Diogo Branco1, Tiago Guerreiro1, Raquel Bouça-Machado2,3, Joaquim Ferreira2,3,4 and CNS Physiotherapy Study Group2 1LASIGE, Faculdade de Ciências, Universidade de Lisboa 2CNS—Campus Neurológico, 3Instituto de Medicina Molecular João Lobo Antunes, 4Faculdade de Medicina, Universidade de Lisboa vitormarqueslobo@gmail.com;djbranco@fc.ul.pt;tjvg@di.fc.ul.pt;raquelbouca@gmail.com;jferreira@medicina.ulisboa.pt ABSTRACT require a visit to a clinic or hospital. Clinicians use validated as- Parkinson’s disease is the second most common neurodegenera- sessments for PD to characterize a patient’s current disease stage tive disease worldwide. Symptoms tend to fluctuate during the [9]. These assessments occur spaced in time and can be hard to day and through disease progression. Clinical evaluations tend capture all the fluctuations that may have happened between to occur spaced in time. Further, the assessments used are mostly appointments. Further, instruments used in clinical practice fo- subjective. The gold standard for evaluating disease severity is cus on subjective evaluations. Namely, visual assessments during MDS-UPDRS. The increase in sensor usage enabled objective clinical visits that are supported by clinical scales. evaluation and continuous monitoring of the disease fluctuations. The gold standard for evaluating disease severity in PD is the One of the symptoms that most affect mobility are gait disor- Movement Disorder Society-Sponsored Revision of the Unified ders. The use of gait characteristics started to become popular to Parkinson’s Disease Rating Scale (MDS-UPDRS). This is a com- monitor the disease. However, the approaches used lack in-depth prehensive rating scale that assesses both motor and non-motor knowledge of machine learning models for disease staging. In symptoms associated with Parkinson’s [7]. To optimize disease our work, we try to estimate the MDS-UPDRS part III score from management, close monitoring of symptom fluctuations is crucial. accelerometer data. We collected data from 74 patients using the However, today this monitoring is usually performed through Axitvity AX3 device both on the wrist and lower back. We did medical appointments, every six months, with a mean duration experiments with different models, features, and windows size. of 30 minutes. Additionally, what published evidence suggests is We achieved a 4.26 Mean Absolute Error on the on left out 10% that patients perform differently during these moments, provid- data using both devices with a 2.5-second sliding window and a ing only information about their best capacity, rather than their random forest model for prediction. We contribute with a com- usual performance in their daily lives. parison of the performed experiments and provide, according to The democratization of sensors’ usage, namely the body-worn our experiments, the optimal models for MDS-UPDRS part III devices, that measure acceleration, and angular velocity allowed estimation using only accelerometer data. the increase of objective evaluations [10]. These devices passively monitor patients during clinical evaluation and in free-living KEYWORDS environments. Furthermore, allow movement metrics and feature gait, accelerometer, mds-updrs, Parkinson’s disease, features, ma- extraction that can be related to motor symptoms or clinical chine learning, models scales used for disease assessments [6]. Gait disorders are one of the symptoms that most affect mobility. Inertial measuring units can help to identify fluctuations. There have been studies 1 INTRODUCTION that leverage the identification of walking bouts to extract gait Parkinson’s Disease (PD) is a neurodegenerative disease that metrics like step length or step variability [1, 4]. affects around 1% of the world’s population. This disease is char- Research using these gait characteristics as a marker for PD acterized by motor and non-motor symptoms [15]. Motor symp- has demonstrated the potential for monitoring the disease in toms include bradykinesia, tremor, rigidity, and gait impairment. several ways [2]. While the use of these gait characteristics has These are present in the early stages of the disease and worsen become a popular approach for monitoring PD, novel research as the disease progresses. has started to analyze signal processing metrics that could also Although there is no cure, the available pharmacological and be of use for this purpose. In a 2019 study, the contributions of non-pharmacological therapeutic interventions effectively con- signal-based features and gait characteristics for the classification trol symptoms. However, as the disease progresses their efficacy of PD were analyzed [13]. Another emerging method to stage tends to reduce and motor complications, such as motor fluc- PD is the use of total scores of the entire MDS-UPDRS or sub- tuations and dyskinesia, appear [11]. These have been labeled parts of the scale. Specifically, MDS-UPDRS III scores have been as ’ON’ and ’OFF’ stages [4]. To minimize the impact of these empirically demonstrated as a good metric for monitoring the fluctuations and inform better the clinicians there is the need to progression of PD [12]. As such, several studies have focused periodically assess the symptoms. Generally, these evaluations on the prediction of this score to monitor disease progression. A recent example of this approach for the monitoring of PD Permission to make digital or hard copies of part or all of this work for personal progression is the 2021 study that leveraged a convolutional 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 neural network (CNN) model trained using inertial data collected the full citation on the first page. Copyrights for third-party components of this from the lower back during gait to estimate MDS-UPDRS III work must be honored. For all other uses, contact the owner/author(s). scores [14]. While these results are promising, the authors suggest Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia that a comparison with traditional feature-engineered machine © 2021 Copyright held by the owner/author(s). learning models could be an avenue for future work, towards 575 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Lobo et al. the deployment of such technologies for continuous monitoring 10-meter walk test. Visualization of each of the segmented gait in- of PD. Other studies have revealed that it is possible to estimate stances was then created in order to exclude session data that con- PD progression using gait data collected with accelerometers [8]. tained sensor failures and misalignment, or mismatched times- However, the relative efficacy and effect of different approaches tamps. During this step, the vector magnitude of the accelerome- to data collection and processing, and machine learning pipeline try signal was computed and appended to each segment using design still lack consensus and clear comparisons that could help the traditional euclidean vector norm formula √︁ 2 2 2 𝑥 + 𝑦 + 𝑧 . To inform future research in this field. avoid the possible temporal drift associated with the process, In our work, we try to estimate the MDS-UPDRS part III from a resampling step was performed after segmentation to ensure accelerometer data. We collected the data using the Axitvity even sampling, as required for the extraction of some of the used AX3 device both on the wrist and lower back [3]. Our dataset Time and Frequency domain features. Finally, all segments were contains data collected from 74 patients (HY between 2 and 4) filtered using a fourth-order, digital low pass Butterworth filter at Campus Neurológico (CNS), a tertiary specialized movement with a cut-off frequency of 20 Hz in order to remove possible disorders center in Portugal. The final subset of data contained ”machine noise” [5]. 267 instances of gait from 104 evaluation sessions. We did differ- ent experiments with 4 models (Random Forest, XGBoost, SVM, Linear Regression), and 59 features from the statistical, spectral, 2.3 Evaluated Models and Features and temporal domains. Furthermore, we used non-overlapping We used 16 statistical, 26 temporal, and 17 spectral domain fea- window sizes of 2.5 and 5 seconds. To validate the trained models tures, with a total of 59. They were computed from all accelerom- we used Leave One Subject Out (LOSO) cross-validation. etry axes and vector magnitude. A sliding window technique Our results showed that the best configuration, with the lowest was used to segment the signal into non-overlapping windows prediction error on the left out of 10% data, achieved a 4.26 MAE, from which the features were extracted. Different feature data with the Random Forest model, and a 2.5-second sliding window frames were then created using 2.5 and 5-second windows, both using combined data from the wrist and lower back. For all of of which were previously used in the literature [14], in order the selected models, the configurations that achieved the best to assess the effect of window size on the estimation task. Dur- results using either of the validation schemes used data collected ing this feature extraction process, MDS-UPDRS III scores were from the lower back or both sensors. Most models performed also computed and appended to the corresponding windows for better using a 5-second window length, with the exception of both data frames. The first step toward feature selection was the xgboost model. The best-performing linear regression and to use a variance filter to exclude features with low (<0.025%) SVM-based models used the SURF and relieF feature selection or zero variance which lowered the feature space from 2081 to methods. 266 in the 2.5-second window and 3081 to 452 in the 5-second Therefore, we contribute with the comparison of different window. While this reduction may seem drastic, it is to be ex- models, features, sensor placement, and window sizes. We pro- pected because of the way Time Series Feature Extraction Library vide, according to our experiments, the optimal models for MDS- works, computing the same feature several times for different fre- UPDRS part III estimation using only accelerometer data. quencies for example which results in a large number of feature columns with hardly any variability, and thus, descriptive power. 2 METHODS A further feature selection step was performed using four differ- The MDS-UPDRS III estimation was performed using different ent feature selection methods that implement different strategies approaches to data collection, signal processing, and using dif- for feature ranking. Each of these feature selection algorithms ferent machine learning pipelines. In this section, we describe was used to rank and select the top 10/25/50 features to be used the steps taken together with the variables for each step, in order for the regression task using the linear regression algorithm, to enable a comparison between different design decisions and and with the support vector-based model. The complete feature their effect on the estimation of the disease stage. subset was also used for these models, in order to establish a baseline comparison with the remaining tree-based models that 2.1 Data Collection are less affected by the number of features due to their capability to perform intrinsic feature selection. We collected data from 74 patients with PD at CNS from peri- For each model, a set of parameters were selected and used in odic evaluations conducted by trained physiotherapists. Each a grid search procedure to test all possible combinations. This participant wore an Axivity AX3 on the wrist and lower back procedure was then carried out for each sensor placement and the during a set of clinical assessments. Accelerometer data was set combined sensors, and for the different sliding window lengths to record at 100 Hz. Our dataset includes 267 instances of gait used during feature extraction, in order to compare the effect of from 104 evaluation sessions of the 10-meter walk. MDS-UPDRS these variables for the estimation task. Leave One Subject Out were also applied for each patient in each session. Among these (LOSO) cross-validation was used during the grid search proce- patients, 49 were male and 23 were female, while the gender of dures in order to avoid overfitting and optimize the models for the remaining 2 patients was not reported. The average patient generalizability. Finally, the optimal models for each combination age was 70.4 years (SD=13.12). The average weight was 71.76 of these variables were saved and used for the ensuing valida- kg (SD=13.89) and the average height was 166.49 cm (SD=9.26). tion tasks. To validate the trained models, the original dataset Finally, the average MDS-UPDRS III score was 40.92 (SD=14.31) was split into training and testing subsets. The training subset and 2.57 (SD=0.97) for the H&Y scale. comprised 90% of the data and was used during the grid-search procedure for training the models using LOSO cross-validation. 2.2 Data Pre-Processing The remaining 10% of the data was then used as a validation set In order to isolate gait instances, the selected data files were to test the model’s performance on unseen data from patients segmented using the annotated timestamps for the 3 trials of the whose data the model had already seen, providing information on 576 Machine-learning models for MDS-UPDRS III Prediction Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia val_m model device_placement win_length ft_sel num_fts loso_mae val_mae 1 rf combined 250 - 266 11.50 4.26 1 xgboost trunk 500 - 229 11.67 4.39 1 svm combined 500 SURF 25 9.99 7.95 1 lin_reg combined 500 reliefF 25 10.21 8.98 2 rf combined 500 - 452 11.39 11.39 2 xgboost trunk 250 - 133 11.49 5.74 2 svm combined 500 SURF 25 9.99 7.95 2 lin_reg combined 500 reliefF 25 10.21 8.98 Table 1: Optimal configurations used by each model to achieve optimal MAE on the left out 10% of data (val_m => 1) and LOSO (val_m => 2). validation schemes using data from both sensors, with the excep- tion of the SVM-based model using a 2.5-second window, which compared to the other options using the same window length achieved lower, albeit negligible, validation MAE using data from the wrist. As for the tree-based models, optimal validation MAE Figure 1: Overall optimal predictions on the 10% of left was attained by models using both sensors with the 2.5-second out data using a Random Forest model on data collected sliding windows, and data from the lower back for the same from both sensors and a 2.5s sliding window. Each point models using the 5-second window. Figures 2a and 2b illustrate represents a window. the intra and inter-model comparison for both of the validation schemes, using different window lengths. While the fluctuations the model’s ability to estimate MDS-UPDRS III scores for patients were relatively low using LOSO CV, most models performed bet- that were already known to these models. These steps yield two ter using a 5-second window length, with the exception of the different scores for each of the optimal models using the same xgboost model. MAE using the left out 10% of validation data Mean Absolute Error (MAE) evaluation metric: the average MAE fluctuated more considerably but was also lowest using 5-second for all LOSO splits during training and the MAE for the held-out windows for all models except RF. validation set. For the purpose of this study, this metric is defined as the mean absolute difference between real (x) and estimated 3.3 Optimal parameters (y) MDS-UPDRS III scores over the number of samples used for As for model parameters, excluding linear regression, the remain- estimation. ing models had different parameters to achieve the best perfor- mance during LOSO CV. For Random Forest (criterion: mae ; 3 RESULTS AND DISCUSSION max_features: 0.333 ; n_estimators: 250), for xgboost (colsam- This section lays out the results from all of the steps taken to- ple_bynode: 1; eta: 0.1 ; importance_type: total_gain; max_depth: ward UPDRS III estimation, including data processing, feature 3 ; num_parallel_tree: 100 ; tree_method: gpu_hist), and for svm extraction and selection, and finally model training and validation (C: 10 ; epsilon: 0.3 ; gamma: auto ; kernel: rbf). The xgboost was results. the one that used only the trunk sensor. The others models used both devices. We used a Grid Search procedure that exhaustively 3.1 Optimal configurations tested all parameter combinations for each model, independently The configuration with the lowest prediction error on the left of the used device placements and sliding window lengths. The out 10% of data used data from both devices processed using exhaustive nature of the grid search procedure makes this method a 2.5-second sliding window and a Random Forest model for of parameter optimization computationally expensive. For this prediction, achieving 4.26 MAE and strong correlation (𝜌 = 0.93) reason, and considering that the procedure was used for several as illustrated in Figure 1. The best performing configuration models, the used parameter space for each model was not as when performing LOSO CV was a Support Vector-based model, comprehensive as those used in some other works with a smaller using data from both sensors but a 5-second feature extraction scope and narrower focus. However, the present results should window, achieving a MAE of 9.99. While predictions using this still serve as a good starting point for model tuning in future model on the validation set were less accurate than some of the research. other options at 7.94 MAE, it achieved the best balance when considering both of the validation schemes. Table 1 summarizes the optimal results achieved by each model along with the used data sources and sliding window length for the 10% left out and LOSO validation tasks. 3.2 Sensor placement and windows size Both device placement and window length used during feature extraction significantly impacted the performance of all models. (a) LOSO CV MAE values (Y-axis) (b) LOSO CV MAE values (Y-axis) For all of the selected models, the configurations that achieved for different device placements for different device placements the best results using either of the validation schemes used data using 5-second windows. using 2.5-second windows. collected from the lower back or both sensors combined. Specifi- cally, all of the non-tree-based models performed better in both Figure 2 577 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Lobo et al. 3.4 Feature importance opportunities for longitudinal studies in free-living environments For the models that benefited from it, several feature selection with larger datasets. methods were tested, along with different numbers of features to select. The best performing linear regression and SVM-based ACKNOWLEDGEMENTS models used the SURF and relieF feature selection methods re- We would like to thank all the participants that kindly partici- spectively, both selecting 25 as the optimal number of features. pated in the studies. This project was partially supported by FCT We then selected the top 20 for each model. Among the 8 top per- through LASIGE Research Unit funding refs. UIDB/00408/2020 forming models across the two tested window lengths, no model and UIDP/00408/2020 and SFRH/BD/144242/2019 to Diogo Branco., used data exclusively from the wrist, and only 3 models used and the WideHealth project which has received funding from data exclusively from the trunk. As for the remaining models, the European Union’s Horizon 2020 research and innovation the majority of top-ranking features were extracted from devices programme under grant agreement No. 952279. mounted on the lower back. In some cases, no wrist features were ranked among the top 20, which suggests that although these REFERENCES were used for the estimation task, their contribution is minimal, [1] Raquel Bouça-Machado, Diogo Branco, Gustavo Fonseca, Raquel Fernan- which is in line with the minimal performance gain in these mod- des, Daisy Abreu, Tiago Guerreiro, Joaquim J Ferreira, and CNS Physiother- apy Study group. 2021. 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However, in future work, there are 578 Elements of a System for Automatic Monitoring of Specific Mental Health Characteristics at Home Kristina Kirsten, Bert Arnrich Hasso Plattner Institute University of Potsdam Potsdam, Germany {kristina.kirsten,bert.anrich}@hpi.de ABSTRACT assessment, has many advantage as it can minimize retrospective Addressing one’s mental health has never been more important. bias. On the one hand, it enables long-term monitoring which The incidences of mental diseases, such as depression or anxiety makes it easier to detect small changes. On the other hand, data disorders, have drastically increased in recent years. The longer can be collected at the time of occurrence and do not have to an adequate treatment is delayed, the greater the impact on the be remembered and described retrospectively when the actual severity of the illness which often results in long absences from condition has already passed [17]. work. With the development of smart devices and wearables, it This paper presents a collection of elements that can be in- is already possible to measure many physiological parameters cluded in a system for automatic monitoring of mental health in everyday life. In addition, monitoring people in their natural characteristics in the home environment. These approaches go environment offers many advantages, e.g. it is not based on retro- beyond conventional questionnaires and refer to technical pos- spective feelings and memories but can measure and reflect the sibilities for measuring individual characteristics. For this, we momentary state. This conceptual paper presents an overview look at various characteristics of individual mental disorders of possible elements of a system for automated monitoring of and present ways in which these can be measured in an auto- mental health characteristics in the home. We describe examples matic way. However, questionnaires, for example in the form of typical parameters for various mental disorders and present of ecological momentary assessments (EMAs), can always be different systems and methods to measure them. Furthermore, considered as an additional tool for comparison with the auto- we show how the individual components of a system can be matic measurements. Finally, we also review different solutions connected to get a holistic view of specific mental health charac- for measurability and propose a potential system overview. teristics. Finally, we also discuss challenges and limitations. 2 BACKGROUND KEYWORDS Mental illnesses are disorders that are very diverse and individual mental health, wearables, ubiquitous sensing, monitoring concept and can affect thinking, mood, and behavior. In 2019, 280 million people were living with depression, 301 million people had an 1 INTRODUCTION anxiety disorder, 40 million people had a bipolar disorder and Being mindful of mental health is more important than ever. 14 million people suffered from an eating disorder [20]. But also In 2019, according to the World Health Organization (WHO), lesser-known disorders, such as OCD, which affects about 2.3% of one in eight people worldwide suffered from a mental disorder people at least once in their lifetime [11], should not be ignored. [20]. That is associated with significant impairments in thinking, There are characteristics or behavioral patterns that can be emotion regulation, or behavior. The WHO also states that in observed in various mental illnesses and also generally indicate a 2020, the number of people with depression and anxiety disorders bad mental health state. These include, but are not limited to, sad- increased significantly, due to the COVID-19 pandemic. ness and dejection, excessive anxiety or worry, decreased ability The most common mental illnesses include depression, anxiety to concentrate, significant fatigue, low energy, sleep problems, disorders, bipolar disorder, and obsessive-compulsive disorder and inability to cope with everyday problems or stress [2]. (OCD), among others. Often, initial symptoms are not recognized Nevertheless, each mental disorder also has very specific char- and, consequently, diagnoses are made late, which in many cases acteristics. Depressed patients, for example, often describe feeling leads to a worsening of the symptoms [6]. Nevertheless, mental empty and worthless inside and experiencing hopelessness, sad- illnesses have, partly overlapping, typical characteristics. For ness, and restlessness. Sleep is also affected in most patients, but example, fatigue, and lack of energy are among the most common it can go both ways, with insomnia or excessive need for sleep symptoms of depression, or checking things over repeatedly are as symptoms. Furthermore, a loss of interest in hobbies and so- signs of OCD. Some of these characteristics are measurable and cial activities may also indicate depression. Sometimes patients interpretable with modern sensors, devices, and machine learning even report unexplained physical problems such as back pain or models especially when it comes to behavioral or determining headaches [1]. People with bipolar disorder also experience the physiological parameters. In addition, studying people in their above symptoms during the depressive phase. But in addition natural environment respectively at home, so-called ambulatory to this, patients also go through manic episodes. In this phase, many characteristics of the depressive episode reverse. Patients Permission to make digital or hard copies of part or all of this work for personal often experience an energetic and euphoric phase where their 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 motivation is increased, concentration is improved, less sleep is the full citation on the first page. Copyrights for third-party components of this required, and they feel the drive to be active [3]. work must be honored. For all other uses, contact the owner/author(s). There are several types of anxiety disorders, including gen- Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). eralized anxiety disorder (GAD), panic disorder, social anxiety disorder, and phobia-related disorders [4]. They have in common 579 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Kirsten et al. that people suffer from anxiety over a long period of time, which sensors, heart rate sensors but also Global Positioning System also often increases and interferes with daily activities ranging (GPS) and inertial measurement units (IMUs). The latter is a com- from the job to personal relationships. In anxiety disorders, indi- bination of several inertial sensors such as a 3D accelerometer viduals often experience physical symptoms. GAD often comes and a 3D gyroscope. However, the term IoT covers many more with headaches, muscle and stomach pain, or other unexplained areas and intelligent devices, such as connected personal scales, aches. During a panic attack, affected people may feel a racing smart ovens, and stoves, or smart lighting systems which can be heart, sweat intensely, tremble, experience loss of control, or feel grouped together under the term smart home. chest pain. In addition, people with social anxiety disorder tend to blush, adopt a rigid posture, or speak with an overly soft voice. For OCD, patients suffer from recurrent obsessive thoughts 3.2 Human Activity Recognition or compulsive acts. Obsessive thoughts are ideas, images, or impulses that repeatedly appear in the mind of the affected person. The topic of HAR has been widely researched as it offers enor- The patient cannot successfully suppress these thoughts. Further, mous potential and numerous use cases [8, 9, 12]. It comprises the more obvious symptoms of OCD are compulsive acts or rituals. research field of automatic detection and differentiation of vari- They are closely related to the obsessions and serve to alleviate ous everyday activities and can be divided into video-based and them and the anxiety that is constantly present. The patient is sensor-based HAR. With the development of new and increas- aware of the unusualness of these actions. Most compulsive acts ingly powerful smart devices and wearables, HAR is becoming involve cleaning (especially hand washing), repetitive checking less expensive, easily accessible, and unobtrusive. Research shows to ensure that a potentially dangerous situation does not occur, that when combining data from different devices, such as smart- or order and cleanliness [5]. phone and smartwatch, the results become even more accurate For any mental illness, not every patient needs to experience [13]. These days, HAR goes far beyond simple classifications, all of the characteristic symptoms. Because symptoms can overlap such as the distinction between sitting, standing, and walking. between disorders, it can be difficult to clearly assign them to Among others, HAR also finds great application in the healthcare a single mental illness. By having a system that automatically sector, e.g. through gait analyses that indicate diseases such as monitors a range of characteristics, a more holistic picture of Alzheimer’s [18] or in systems that focus on elderly care to detect mental status can be created, and changes can be detected early. falls [10], for example. Diagnoses for mental illness can only be made by professionals. Experts often use various forms of questionnaires and scales to determine the severity of an illness (e.g. Beck Depression 3.3 Indoor Positioning Systems Inventory for depression or Yale-Brown Obsessive Compulsive The ability to determine a person’s exact location in a home can Scale for OCD). However, collecting and analyzing sensor data help better identify activities that are connected to specific loca- to monitor mental health in general, is a topic that has been tions, for example, compulsive or eating behavior. Although GPS studied a lot in recent years but is still very relevant and has offers high coverage, it is not suitable for indoor localization be- great potential. The majority of studies are related to the analysis cause the receiver and satellite have to be in the line of sight, and of smartphone data, but wearables are also increasingly used for walls, roofs, and other objects prevent this. That is why in recent mental health studies. When it comes to the specific monitoring years approaches for IPS have been designed which use vari- of certain mental illnesses, the vast majority of these studies ous available technologies such as radio-frequency identification relate to anxiety disorders, depression, bipolar disorder or stress (RFID), Wireless Local Area Networks (WLAN), Bluetooth Low in general [14]. This paper focuses on technical possibilities to Energy (BLE) beacons, and more recently Ultra Wideband (UWB) unobtrusively measure certain mental health characteristics in [15, 21, 22]. Localization techniques can be divided into triangu- the home environment by using the latest technologies. lation algorithms (e.g. Time of Arrival (ToA), Time Differences of Arrival (TDoA), Received Signal Strength Indicators (RSSI)-based, 3 MONITORING SYSTEM ELEMENTS Angle of Arrival (AoA)), scene analysis (e.g. Fingerprinting-based To monitor certain mental health characteristics in the home techniques) and proximity detection algorithms [21]. The latter environment, it is possible to use various new wearable devices, is the process of determining whether a user is close to a cer- human activity recognition (HAR), indoor positioning systems tain range. This concept is often found in combination with BLE (IPSs) and already derived parameters from consumer devices. beacons, which are installed stationary at points of interest and send Bluetooth packets that are picked up and processed by the user’s smartphone, calculating the distance. In a scene analysis 3.1 Smart Devices and Wearables with using Fingerprints, measurements as e.g. RSSI-values, are The smartphone is an integral part of everyday life and almost collected in an offline phase for different positions and stored all of us carry it with us all the time. Although it is the most com- in a map. For position determination in real-time, the current mon everyday smart device, the use of so-called wearables has measurements are then compared with offline measurements to also been rising rapidly in recent years [19]. The term Internet determine the user’s location [22]. of Things (IoT) is shaping the technological development of the Different localization techniques have advantages and dis- last decade. It includes devices such as activity trackers, smart- advantages and it depends on the use case which methods are watches, and smart rings. Since these are worn on the body and suitable. Most triangulation techniques (e.g. AoA) provide high therefore often called wearables, they can measure physiological accuracy but require complex hardware and extensive synchro- parameters such as heart rate variability (HRV), blood oxygen nization. Whereas RSSI- and Fingerprinting-based methods are level, or skin conductivity. The modern smart devices contain fairly easy to use but with lower accuracy or, in the case of Finger- a variety of sensors, such as oximetry sensors, skin tempera- printing, with a dependence on a predefined map that is sensitive ture, and ambient temperature sensors, electrodermal activity to any change in the home environment [22]. 580 Elements of a System for Automatic Monitoring of Specific Mental Health Characteristics at Home Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 3.4 Derived Parameters Table 1: Listing of exemplary mental health characteristics In addition to using raw sensor data for use cases like HAR or IPS, and possibilities of monitoring them. HAR corresponds to consumer devices often provide pre-calculated values and derived the detection of human movements with motion sensors, parameters, such as about sleep. Many device manufacturers PP stands for measuring physiological parameters and IPS try to draw conclusions about sleep duration, sleep quality, and implies the positioning of a person in the room or home. sleep phases. Additionally, information such as screen time, the frequency with which the phone is picked up, or the number of Characteristic HAR PP IPS Others calls and messages is also documented. Even though many of derived smartphone these values are pre-calculated and in some cases do not provide Sleeping and smartwatch much information on their own, they can give insights when Behaviour x x (x) parameters (sleep combined with each other and with data from additional devices. hours, sleep phases, sleep quality) 4 EXEMPLARY SYSTEM OVERVIEW Compulsive Handwashing x (x) This section describes example characteristics and their monitor- Compulsive ing possibilities, and proposes a connected system architecture. Checking x x Stress 4.1 Characteristics Monitoring Level (x) x The possible elements of a monitoring system presented in the interaction with previous section, offer particular value when combining them. Eating IoT devices, e.g. Different systems and methods are needed to measure specific Behavior x x x personal scale, psychological characteristics. To illustrate this, we looked at some microwave symptoms and characteristics of mental illnesses and considered derived smartphone how these can be measured. The following Table 1 shows a short and smartwatch list of mental health characteristics and possible ways of mea- Social parameters (screen suring them. This table represents an exemplary overview and Interaction (x) (x) time, pick up times, therefore does not claim to be complete. With this table, we show phone call and that different characteristics can be measured and documented messages frequencies) with the same sensors, wearables, and systems but also that one characteristic can be determined with more than one measure- ment. We focused on the three main elements for monitoring, namely a HAR system, measuring and evaluating physiological individual expressions. For this purpose, it can be helpful to train parameters (abbreviated with PP in the table), and using an IPS. a personalized machine learning model for a potential patient Additionally, we list other parameters or devices which can sup- in order to observe variations from normal behavior. In general, port the measurement of the respective characteristic. For some personalized models are well suited to represent the individual characteristics, additional information might increase the accu- aspects of everyday activities. racy and lead to a greater knowledge gain (indicated by (x) in the table). In general, it can be said that oftentimes the combination of different input signals and parameters leads to a better system 4.2 Connected System quality [7]. We do not present the exact algorithms and devices, In Figure 1 we demonstrate how the individual components of a as these depend heavily on other external factors (availability of system for monitoring characteristics of mental disorders can be devices, overall use case, acceptance of the user, privacy aspects). connected. Depending on the concrete use case, data from mul- It has long been known that sleep, e.g. in form of insomnia, tiple devices will be constantly collected. For energy efficiency, is an essential feature of mental disorders such as depression or it makes sense to store the collected data on the respective de- anxiety [16]. Sleeping behavior can be observed across a variety vice first, and only send it to a data hub from time to time. For of systems and devices. By means of a HAR system, for example, this, smartphone applications like SensorHub [7] are very useful. it is possible to document how often a person wakes up at night, Multiple (wearable) sensors can be connected via Bluetooth, col- how restful the sleep is, and when and whether one gets out lecting and storing the data in a central place and a unified format of bed in the morning. Monitoring this behavior can help in to provide complete control over the data. Additionally, systems observing depressive phases, where patients sometimes find it like SensorHub provide the possibility to get point-in-time feed- difficult to get out of bed at all. But beyond that, it can also make back from the user by repeatedly querying certain conditions (be- sense to include other information, such as the position in the havior, feelings, experiences), so-called EMAs. This is extremely apartment in order to get more contextual information. valuable and these subjective sensations could be supported and The measurement of physiological parameters can help for the enriched by objective, quantifiable sensor measurements. majority of the characteristics. By measuring skin conductance, A system designed to give a holistic view of a current state is for example stress, which plays a major role in many mental not intended to make assessments or provide results at any time. illnesses, could be detected. Furthermore, it is also known that That means these kinds of systems have a long-term character social behavior changes in some mental disorders. For example, rather than being a snapshot. Moreover, when working with raw social interaction decreases in depressive or anxiety patients but sensor data, this often means that it needs a lot of pre-processing increases in people in a manic phase. and cleaning. This includes e.g. filtering and de-noising. When it For some characteristics, it is particularly interesting to look comes to machine learning, domain-specific knowledge is also at changes over time because mental illnesses often have very helpful in order to come up with meaningful features. 581 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Kirsten et al. Figure 1: System Overview to Monitor Mental Health Characteristics at Home 5 CHALLENGES AND LIMITATIONS REFERENCES Each component of an overall system has its advantages and [1] 2018. Depression (major depressive disorder). https://www.mayoclinic.org/ disadvantages. It always has to be determined which features diseases-conditions/depression/symptoms-causes/syc-20356007 [2] 2019. Mental illness. https://www.mayoclinic.org/diseases-conditions/ predominate for the specific use case. It should also be noted that mental-illness/symptoms-causes/syc-20374968 issues like data security, especially with such sensitive topics as [3] 2020. 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IEEE Communications Surveys limitations and possibilities are encountered. & Tutorials 21, 3 (2019), 2568–2599. 582 Towards Multi-Modal Recordings in Daily Life: A Baseline Assessment of an Experimental Framework ∗ Christoph Anders ∗ Sidratul Moontaha Bert Anrich firstname.lastname@hpi.de Hasso Plattner Institute Potsdam, Germany ABSTRACT that the onset of MF depends on contextual factors such as level Background: of sleep during previous nights, overall health, emotional state, Wearable devices can record physiological signals and more. MF can increase the amount of mistakes an individual from humans to enable an objective assessment of their Mental does, and hinder work-performance amongst others. The impact State. In the future, such devices will enable researchers to work of MF on economies can be estimated from the finding that a on paradigms outside, rather than only inside, of controlled labo- fatigued work-force costs the US economy an approximation ratory environments. This transition requires a paradigm shift on of 18 billion USD per year [2]. Methods that quantify the level how experiments are conducted, and introduces new challenges. Method: of MW an individual experiences in and outside of laboratory Here, an experimental framework for multi-modal base- environments are of interest to a broad community. line assessments is presented. The developed test battery covers MF can be circumvented in various ways, e.g. by taking more stimuli and questionnaire presenters, and multi-modal data can Micro-Breaks [2]. To quantify the impact of interventions, mea- be recorded in parallel, such as Photoplethysmography, Elec- surement frameworks have to be developed in controlled envi- troencephalography, Acceleration, and Electrodermal Activity ronments and evaluated for use in uncontrolled environments. data. The multi-modal data is extracted using a single platform, Subjective measurements of MW can be performed using ques- and synchronized using a shake detection tool. A baseline was tionnaires or discussions with individuals. However, these ap- recorded from eight participants in a controlled environment. proaches take time, require active truthful participation, and are Using Leave-One-Out Cross-Validation, the resampling of data, therefore not suited for every context. To overcome this hurdle, the ideal window size, and the applicability of Deep Learning objective measurement methods are researched, amongst which for Mental Workload Classification were evaluated. In addition, EEG seems promising [3]. participants were polled on the acceptance of using the wearable To-be-developed measurement frameworks for experiments devices. Results: The binary classification performance declined mainly conducted in controlled environments, such as MW quan- by an average of 7.81% when using eye-blink removal, under- tification, need to be combined with research on the quality and lining the importance of data synchronization, correct artefact amount of sensor data needed, accurate synchronization between identification, evaluating and developing artefact removal tech- different modalities, and precise data labeling. Merging research niques, and investigating on the robustness of the multi-modal on all these aspects into one skeleton would increase the overall setup. Experiments showed that the optimal window size for usability of the resulting framework. This paper presents an ex- the acquired data is 30 seconds for Mental Workload classifica- perimental framework for baseline assessment on the use-case of tion, with which a Random Forest classifier and an optimized objective measurements of MW conducted across university stu- Deep Convolutional Neural Network achieved the best-balanced dents. As data storage, compression, and transmission consume classification accuracy of 70.27% and 74.16%, respectively. Con- clusions: a lot of battery power [4], the length of time windows required This baseline assessment gives valuable insights on for accurate classifications, the sampling-rate required, and the how to prototype stimulus presentation with different wearable time-series classification performance were evaluated. Finally, devices and suggests future work packages, paving the way for participants of this study were surveyed about their experiences researchers to investigate new paradigm outside of controlled with the two well-established wearable devices used, since this environments. framework can be customized in terms of stimulus presentation 1 INTRODUCTION and multi-modality used for the Affective Computing research community in general. The measurement framework is presented The concept of Mental Workload (MW) originates from the field in detail, and necessary steps towards an experimental frame- of psychology, refers to the amount of working memory used work for multi-modal recordings in uncontrolled environments in the brain, and is historically researched on in the context of are outlined. laboratories [1]. High levels of MW experienced over an extended period of time lead to Mental Fatigue (MF). It can be assumed 2 EXPERIMENTAL FRAMEWORK ∗ Both authors contributed equally to this research. The experimental framework for this study was built using Psy- choPy ( v2022.2.0) [5] running under Python 3.10.4 in a controlled Permission to make digital or hard copies of part or all of this work for personal environment, as a preliminary step for recordings in daily life. 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 Among the most frequently used software packages for visual the full citation on the first page. Copyrights for third-party components of this 1 stimulus presentation , Psychopy was preferred due to the us- work must be honored. For all other uses, contact the owner /author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia ability, automated calibration feature, and the real-time stimulus © 2022 Copyright held by the owner/author(s). 1 http://hans-strasburger.userweb.mwn.de/psy_soft.html#imagen 583 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Anders and Moontaha, et al. presentation [6]. The setup was implemented to induce MW in PsychoPy. How data labeling will be performed for recordings in line with common practice from state-of-the-art studies (e.g. [7]). uncontrolled environments remains an open question. As a first step, participants were asked the put all the devices Once the data was labeled, data cleaning needed to be per- into a box and shake them, to synchronize the devices. Then, formed. As time-series data is not uniform over time (e.g. due high magnitude tapping onto the space bar was performed to to a temporary loss of connection), missing values needed to synchronize with Psychopy. After instructing participants to min- be interpolated. Linear interpolation was performed by filling 2 imize movement, a five minute relaxation video was presented missing data with the mean value of two neighboring data points. for baseline recording. An eye-closing session of one-minute du- Additionally, head-movements and eye-blinks predominantly ration followed, before the MW was induced. Participants had compromised the EEG recordings, while movements of the hand to work on the N-Back task (n=3) for five minutes. Afterwards, predominantly compromised readings from the Empatica E4. participants had to work for five minutes on the Stroop task, Removal of artefacts in the data from the Empatica E4 was per- where four colors (yellow, green, blue, and red) were shown for formed in three steps: First, both the raw values for accelera- a duration of 3 seconds. For every wrong answer, a buzz sound tion and BVP were normalized to the range of [-1, 1]. Second, a was played to intensify the workload and provide feedback to fourth-order Butterworth band-pass filter with 0.5 Hz and 3.5 Hz the participants. Both tasks were followed by the pairwise NASA cutoff-frequencies was applied. Third, a Savitzky-Golay filter was Task Load Index (NASA-TLX) questionnaire [8]. By using physio- applied, using a 101-sample window and a 5th-degree polynomial. logical data recorded during the relaxation video and eye-closing These steps removed the baseline-drift in the recorded BVP sig- session as ’Low-to-No-Workload’-class, and using the data from nal. Additionally, adaptive noise cancellation was performed to both MW tasks as ’High-Workload’-class, a binary classification remove movement-artefacts from the BVP signal, by using linear task was formed. Physiological data recorded during answering recursive least-squares filtering. Removal of artefacts from the of the questionnaires, or reading instructions for the MW tasks, EEG signal was performed using spectral filtering with an infinite was excluded. With a ratio of 4:10 for ’Low-to-No-Workload’ to impulse response filter. Following parameter recommendations ’High-Workload’, the recorded data was imbalanced. from the literature [11], a Chebyshev type 2 band-pass filter with Two wearable devices were used: The Empatica E4 which 0.5 Hz and 48.5 Hz cutoff-frequencies and 40 dB attenuation in records skin temperature (4 Hz), PPG (64 Hz), and GSR (4 Hz), the pass-band was applied. Thereby, the power-line interference alongside acceleration-readings (32 Hz) that can be used for the and other artefacts such as jaw-clenching were removed. Strong identification and removal of artefacts. The Muse S device was artefacts for EEG recordings, especially in the frontal channels, used, which records EEG (256 Hz) and accelerometer data (50 are eye-blinks [12]. Here, eye-blink were removed using the in- Hz). Following the 10/20-system for electrode placement [9], the dependent component analysis (ICA) [13]. 3 EEG electrodes of the Muse S device are located at TP9, AF7, Spatial filtering of the EEG data was investigated using the AF8, TP10, with a reference electrode at FPz. common spatial pattern (CSP) algorithm [14] implemented in the meet7 repository [15]. CSP performs a generalized eigenvalue Instructions Video Instructions Eye-Closing Instructions decomposition of two distinct mutlivariate sets of data, for which an additive underlying mixture of sources is assumed. CSP basi- Synchronization 5 min 1 min cally maximizes power differences between the two conditions ’Low-to-No-Workload’ and ’High-Workload’. After derivation of Stroop Instructions N-back NASA TLX NASA TLX filter values for each channel, the filter with the highest Eigen- value is chosen and applied to both the ’Low-to-No-Workload’-, Synchronization 5 min and the ’High-Workload’-, classes. The result is the sum of all 5 min the multiplications of the respective scalar-filters with the cor- responding electrode-channels, resulting in one single channel Figure 1: Study design of the experimental paradigm uti- which best describes the underlying phenomenon optimized for. lized for the multi-modal framework Temporal filtering describes the process of either rejecting recordings from the process of building trials all-together (e.g. physiological data recorded during answering of questionnaires), 3 METHODS or of building trials from the recorded data. Two important pa- 4 rameters have to be taken into account: window-size, and window- The Muse S data was recorded using MindMonitor and loaded overlap. Here, multiple parameters for the window-size were eval- by devicely 5, whereas the Empatica E4 data was recorded us- uated: 5 sec, 10 sec, 30 sec. The window-overlap was constantly ing the SesnsorHub Application [10]. Synchronization was per- chosen to be 0.5 sec smaller than the respective window-size: 4.5 formed at simultaneous peaks in the accelerometer data, using jointly6 sec, 9.5 sec, 29.5 sec. on readings from both wearable devices. Acceleration To extract different features, the cleaned BVP signal was used was caused once in the beginning and once at the end of the to extract the heart rate variability using NeuroKit2 8 package experimental protocol: The devices were placed in the same box, [16], which locates the peaks in the peak to peak (RR) inter- and the box was shook. This procedure was repeated after the ex- val of the hear rate variability and calculates different time-and periment. Potential offsets and time-shifts in the recordings were frequency-domain features, partially mentioned below. Addition- automatically corrected by Jointly. Labeling of the sensor data ally, the mean and standard deviations (SD) from GSR and skin was performed using the information contained in the logs from temperature were extracted. The different feature-sets utilized 2 https://www.youtube.com/watch?v=S6jCd2hSVKA 3 https://choosemuse.com/de/muse-s/ 4 https://mind-monitor.com/ 5 7 https://github.com/hpi-dhc/devicely https://github.com/neurophysics/meet 6 8 https://github.com/hpi-dhc/jointly https://neuropsychology.github.io/NeuroKit/ 584 Experimental Framework for Multi-Modal Recordings: Baseline Assessment Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia were extracted from the training data only, and can be summa- Hidden (2D convolution, 5x5, ReLu), 3rd Hidden (2D Max Pooling, rized as follows: CSP features: Gamma, Beta, Alpha, Theta and 2x2), 4th Hidden (Flatten), 5th Hidden (Fully-Connected, ReLu), Delta band powers, mean over the band powers, mean and SD of 6th Hidden (Dropout), 7th Hidden (Fully-Connected, ReLu), 8th the absolute band powers; BVP features: Mean and SD of the RR Hidden (Dropout), Output (Fully-Connected, Single-Output, Sig- intervals (peak to peak of Hear Rate Variability), SD of the suc- moid). cessive differences between RR intervals, ratio of SD and mean For the RF, the default hyperparameters of the RandomForest- RR intervals, low frequency band power (0.04 - 0.15 Hz), high Classifier from scikit-learn were chosen. For the SVM, a radial frequency band power (0.15 - 0.4 Hz), very high frequency band basis function kernel was utilized, and the gamma value was power (0.4 - 0.5 Hz), ratio of low-high band power; GSR: Mean calculated for each evaluation. The best hyperparameters of and SD of absolute values, mean amplitude of Skin Conductivity DCNN were identified using the sequential model based optimiza- Response (SCR) peaks; Local Skin Temperature: Mean and SD tion (SMBO) algorithm with the tree-structured parzen estimator of absolute values; and PSD features: Power spectral density of (TPE), which has been shown to outperform both grid search and raw EEG of TP9, TP10, AF7, AF8. random search [18]. The derived hyperparameters are listed in Table 1. The inputs to all classifiers were min-max normalized. Hyperparameter Value Range Baseline Optimized Dropout 0 - 0.5 (0.1) 0.5 0.3 Epochs 1 -200 (5) 200 25 Batch Size 1 - 1000 (50) 500 350 Conv. Layer 1 10 - 100 (10) 20 70 Conv. Layer 2 25 - 250 (25) 50 125 Hidden Layer 1 100 - 1000 (50) 500 200 Hidden Layer 2 100 - 1000 (50) 250 750 Window Size 5 - 30 5 30 Input Height 20 - 130 (10) 28 110 Input Width 20 - 130 (10) 28 110 Table 1: Hyperparameters for the DCNN. Values in paren- thesis indicate incremental steps. Window size in seconds. 4 RESULTS The first experimental evaluation used two different sets of fea- tures, each resampled to 10 Hz. Averaged results of all of the Leave-One-Out Cross-Validation for the classification tasks are shown in Table 2. Set # Window Size Blink Removal Balanced Acc. Set 1 1200 sec no 74.06 Set 1 1200 sec yes 65.52 Set 1 6000 sec no 82.21 Set 1 6000 sec yes 73.49 Set 2 1200 sec no 77.31 Set 2 1200 sec yes 72.43 Figure 2: The flowchart of the employed study protocol Set 2 6000 sec no 80.94 with the necessary intermediate steps. Set 2 6000 sec yes 71.84 Table 2: TSC Performance for RF. Set 1: Raw TP9, TP10, In total, three different evaluations were performed on the AF8, AF7, Skin Temperature, BVP features. Set 2: Set 1 + data recorded in a controlled environment. First, two different GSR. The row of the best performance is printed in bolt feature sets were investigated for data resampled to 10 Hz, using face. a Random Forest (RF) classifier. This evaluation was performed to investigate on the possibility of reducing the sampling rate required per modality. Second, the optimal time window for time The second experiment evaluated on the optimal window-size. series classification (TSC) of MW was investigated on by com- Results are visualized in Figure 3, where the PSD feature set refers paring the performance of different feature sets utilized by RF to all the extracted features mentioned in 3, and the FE feature- and a Support Vector Machine (SVM). Therefore, the modalities set refers to all but the PSD features. With the FE feature-set, were utilized at the respective sampling rates recorded with and while RF performed best across all time-windows, the average simply combined. Third, the application of Deep Learning to this time series classification performance increased only marginally task was investigated using a Deep Convolutional Neural Net- across all TSC models when varying the window-size. The best work (DCNN) [17]. The DCNN was built of ten layers: Input (2D performance of 70.27% balanced accuracy was achieved for RF convolution, 5x5, ReLu), 1st Hidden (2D Max Pooling, 2x2), 2nd with FE for a window-size of 30 sec. 585 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Anders and Moontaha, et al. SVM FE SVM PSD RF FE RF PSD AVG features such as power-ratios; to recruit more participants; and 72.5 to investigate on feature-importance. Also, resampling the sen- sor data to frequencies other than 10 Hz and investigating the 70.0 effect of interventions to remove MF in controlled environments, should be performed. The presented framework needs to be ex- 67.5 tended to allow automatic randomization of the tasks, recovery from crashes, more robust data extraction, to be evaluated for 65.0 applicability to uncontrolled environments, and published. Ex- perimental paradigms for measuring MW need to be taken from ccuracy in % 62.5 controlled environments, and frameworks that are under devel- opment need to be tested and evaluated in uncontrolled settings. 60.0 Balanced A 6 ACKNOWLEDGMENTS 57.5 We appreciate the contribution of Ahmed Azzouz, Alina Krichev- 55.0 sky, Leonhard Hennicke, Nastassia Heumann, Nikita Shishelyakin and Tanja Manlik as a part of their master project. This research 52.5 was (partially) funded by the HPI Research School on Data Sci- 5 sec 10 sec 30 sec mean ence and Engineering. 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(e.g. [19, 20]); on longer window-sizes, different DL models, more 586 Assessing Sources of Variability of Hierarchical Data in a Repeated-Measures Diary Study of Stress Junoš Lukan Larissa Bolliger Els Clays Jožef Stefan Institute Department of Public Health and Department of Public Health and Department of Intelligent Systems Primary Care Primary Care Jožef Stefan International Ghent University Ghent University Postgraduate School Ghent, Belgium Ghent, Belgium Ljubljana, Slovenia larissa.bolliger@ugent.be els.clays@ugent.be junos.lukan@ijs.si Primož Šiško Mitja Luštrek Jožef Stefan Institute Jožef Stefan Institute Department of Intelligent Systems Department of Intelligent Systems Ljubljana, Slovenia Jožef Stefan International sisko.primoz@gmail.com Postgraduate School Ljubljana, Slovenia mitja.lustrek@ijs.si ABSTRACT In machine learning literature, this problem falls under the topic of affective computing [19]. Typical studies settle for one There are different methodological approaches to stress recog- definition of stress and either measure it by simply asking about nition in different disciplines. In machine learning literature, a it or using one of the established psychological questionnaires typical approach is to select a target variable and try to predict it [2]. Next, stress detection is relayed to machine learning models as generally as feasible, but possibly with person-specific feature as a supervised problem in which objectively measured data are normalization or personalization of models. In medical, psycho- used as predictors of self-reports, serving as labels. logical, and social sciences, the nested nature of data is often The aim of this paper is to employ statistical techniques from taken into account by using multilevel models, especially with medical and social sciences to inform machine learning mod- repeated measures data. In our diary study, we asked partici- elling. Specifically, we analyse daily aggregated data collected pants to assess different aspects of stress every 90 min for 15 in our study and consider possibilities for analysis on a lower, working days. They accessed their questionnaires through an within-day level. We do this by describing the data in terms of Android application which also served to passively record phone multilevel models and then assess how each level of measure- usage and sensor data. At the same time they wore Empatica ments contributes to the overall stress variability. E4 wristbands which collected physiological data. This study de- sign lends itself well to hierarchical consideration. In this paper, 2 METHODS we use variance partitioning, a technique which is also a part of multilevel modelling, to inform a machine learning pipeline. 2.1 Data Collection We show how consideration of different sources of variability Three main data types were collected using different measuring can help us decide how to personalize normalization of data or devices. Physiological parameters were measured by Empatica machine learning models. E4 wristbands, while participants filled in questionnaires on their smartphones for 15 working days. These ecological momentary KEYWORDS assessments (EMAs) were presented at random intervals through- stress detection, ecological momentary assessment, variance par- out the working day, roughly 90 minutes apart, while an addi- titioning, hierarchical data tional, longer questionnaire was offered in the evening, asking about the day as a whole. The questions in each EMA session (a 1 INTRODUCTION set of questions) were selected from questionnaires that measure different aspects of stress and related constructs, such as stress ap- Chronic stress is a well researched medical, psychological, and praisal, negative affect, job demand and job control. Smartphone sociological phenomenon which has been shown to have detri- sensor data and phone usage data were continuously collected by mental health consequences [8]. It is less clear, however, how a self-developed Android application based on the AWARE frame- daily experiences of stress translate into a long-term experience work [9]. The contents of the questionnaires and the data types of chronic stress [13]. In the STRAW project, we have tackled collected have already been described in an extensive protocol this question by carrying out a longitudinal diary study [6]. paper [6]. We collected the data of 56 participants, recruited from aca- Permission to make digital or hard copies of part or all of this work for personal demic institutions in Belgium (29 participants) and Slovenia (26 or classroom use is granted without fee provided that copies are not made or participants). Only the data pertaining to 𝑁 = 55 participants 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 were complete, which included 26 women and 29 men. Their work must be honored. For all other uses, contact the owner /author(s). mean age was 34.9 years with the range from 24 years to 63 years Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia and they held various positions in their institutions, such as PhD © 2022 Copyright held by the owner/author(s). students, employees in administration, and tenured professors. 587 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Junoš Lukan, Larissa Bolliger, Els Clays, Primož Šiško, and Mitja Luštrek The participants adhered to the study protocol well. In their 2.3.2 A Two-Level Model. To model the differences between participation period, each participant responded to more than 96 participants using a linear regression model, we can include EMA sessions on average. The median time difference between a personalized intercept term. The regression equation can be 1 two subsequent workday EMA sessions was 93 minutes, just a described in two parts, where the first level is given by : bit over what was designed [12]. 𝑦 = 𝛽 + 𝜖 (3) 𝑖 𝑗 𝑖 0 𝑖 𝑗 2.2 Classical Machine Learning Data Analysis Here, we are trying to predict the stress score for each day 𝑗 = 1, . . . , 𝑛 within each participant 𝑖 = 1, . . . , 𝑁 . As the first step of the analysis, we followed a classical machine 𝑑 We model the intercepts as the sum of the overall intercept, learning approach for detecting stress (see Figure 3 in [2]). After 𝛾 and person-specific intercepts, , also called the random 00 𝑢𝑖0 preprocessing, we calculated hand-crafted features. For phone error component. The second level regression equation is given sensor data, we used a modified Reproducible Analysis Pipeline for 2 by : Data Streams (RAPIDS, [20]) library, which calculates behavioural 𝛽 = 𝛾 + 𝑢 (4) features using R, Python, and Snakemake [16] following a well- 𝑖 0 00 𝑖 0 defined set of rules (steps). For physiological data, we used our 2.3.3 A Three-Level Model. Since participants in our study an- in-house developed Python library, cr-features [11]. swered the EMA prompts repeatedly throughout the day, we The data were aggregated on a daily basis, by averaging target can add a third level of analysis, that is we consider within-day variables and calculating statistical physiological features that variability. In this case, we are trying to predict the score for were first calculated on short segments. Next, we standardized each EMA session 𝑘 = 1, . . . , 𝑛 within each day 𝑗 within each 𝑠 the data within participants, i.e., by subtracting the daily mean participant 𝑖 . This is a more fine-grained level of analysis and and dividing by daily standard deviation. Finally, we used a leave- includes many more instances, namely 𝑛 = 𝑁 × 𝑛 × 𝑛 𝑑 𝑠 one-subject-out validation technique and tested various linear Joining the expressions for all three levels of intercept, the (e.g., linear regression), non-linear (e.g., support vector regres- equation can be written as: sion) and ensemble machine learning techniques (e.g., ADA boost 𝑦 = 𝛽 + 𝜖 regressor) from scikit-learn [17]. 𝑖 𝑗 𝑘 𝑖 𝑗 0 𝑖 𝑗 𝑘 = 𝛾 + 𝑣 + 𝜖 𝑖 00 𝑖 𝑗 0 𝑖 𝑗 𝑘 2.3 Variance Partitioning = ( 𝛿 + ) + + (5) 000 𝑢 𝑣 𝜖 𝑖 00 𝑖 𝑗 0 𝑖 𝑗 𝑘 Multilevel models (also known as mixed-effect, random-effect Now, the top level intercept, 𝛽 is composed of three different 𝑖 𝑗 0 or mixed models) are methods commonly used in medical, bio- components. The first one, 𝛿 , is fixed for all participants and 000 logical, and social sciences to analyse hierarchical (nested) data days, and it represents the overall intercept corresponding to the [10]. Labels in our dataset are nested in at least three levels: mean of scores aggregated per EMA session. The other two are each participant collected data on multiple days and each day random effects, where 𝑢 is the person-specific intercept, while 𝑖 00 included several measurements. We analysed self-perceived data 𝑣 is the intercept specific to each day within each person. 𝑖 𝑗 0 from questionnaires using mixed models in other publications [4, 5], while in this paper we use the related technique of variance 3 RESULTS partitioning for exploring variability of the data at different levels. Variance partitioning (or partitioning of sums of squared devia- 3.1 Machine Learning on Daily Aggregated tions) can be used to ascribe the overall variability in a dataset to Data different sources of variability. In multilevel models, this sources As described in Section 2.2, we followed a typical machine learn- can be different levels of analysis. ing approach to detect daily stress. We chose negative affect as 2.3.1 Simple Linear Regression. To model daily stress, we can an indicator for stress, which was measured with the Positive use linear regression in the following form: and Negative Affect Schedule (PANAS, [22]). This is the most commonly used questionnaire in similar diary studies looking at daily measures of stress [13]. It is composed of a list of adjectives 𝑦 = 𝛽 + 𝛽 + · · · + 𝛽 𝑥 + 𝜖 (1) 𝑗 0 1𝑥 𝑗 1 𝑝 𝑗 𝑝 𝑗 describing emotional states, which are self-assessed on a scale Here, 𝑦 represents the mean of the chosen indicator of stress 𝑗 from 1 to 5. 𝑛 on a day 𝑗 , 𝛽 is the intercept term, represent 0 𝑥 𝑗 1, . . . , 𝑥 𝑗 𝑝 This approach did not yield good predictions as shown in Fig. 1. 𝑗 =1 𝑛 daily values of 𝑝 features (or predictors), 𝛽 their In fact, most of the models performed no better than the dummy 1, . . . , 𝛽𝑝 𝑗 =1 2 model, as evaluated by the median of the 𝑅 metric across all corresponding regression coefficients, while 𝜖 is the error term 𝑗 participants. Even when considering the individual rounds of the which captures all other factors related to variable 𝑦 , which are leave-one-subject-out validation scheme, the best model (in this not described by the available features (predictors included in case an instance of an XGBoost regressor) achieved a maximum the model). The index 𝑗 runs from 1 to 𝑛, where 𝑛 = 𝑁 × 𝑛 is 𝑑 2 of 𝑅 = 0.52. This corresponds to 52 % of explained variance for the product of the number of participants (𝑁 ) and the number of that particular participant. days each one participated in the study (𝑛 ). 𝑑 We considered modelling within-day stress as the natural next As we are interested in variance partitioning only, we can focus step. However, this gives the possibility of processing the data on the intercept and omit all the predictor terms. Equation (1) on the level of days, rather than only subjects. For example, stan- thus becomes: dardization, feature selection, and model cross validation could 𝑦 = 𝛽 + 𝜖 (2) 𝑗 0 𝑗 1 In general, this equation would include predictor terms, such as 𝛽 𝑥 , but they In the context of machine learning, this is known as a baseline 𝑖 1 𝑖 𝑗 1 are omitted for clarity as mentioned above. or a dummy model, which predicts the same value for all days 2 Similarly, we could write the equation for person specific regression coefficients and participants: the mean. as 𝛽 = 𝛾 + 𝑢 and also model person-specific predictors as 𝛾 𝑊 . 1𝑖 10 1𝑖 01 𝑖 588 Assessing Sources of Variability of Hierarchical Data Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia proportion of variance already explained at the subject-level, so Linear regr. Ridge regr. the total proportion of explained variance increased to 68 %. Lasso regr. This is also illustrated in Figure 3 which shows that individual Bayesian Ridge regr. statistic days differ from the overall mean by maximum of 1.5 points. On RANSAC regr. Support vector regr. max the ordinal axis, the random effects are ordered by participant, Kernel Ridge regr. similarly to Fig. 2. Within participants, however, the data are or- median Gaussian Process regr. dered consecutively by date. This is manifested in the noisy struc- Random Forest regr. XGBoost regr. ture of the confidence intervals as opposed to the monotonously ADA Boost regr. increasing random effects shown in red points. -1.0 -0.5 0.0 0.5 1.0 value Figure 1: Median and maximum 2 𝑅 value as achieved by different regression methods in a leave-one-subject-out validation scheme. day : all be done on the lowest, daily level. To get an idea of whether a participant more fine-grained analysis of the data might be warranted, we turned to variance partitioning. 3.2 Sources of Variability -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 As mentioned in Section 2.2, the data for machine learning exper- random effects with confidence intervals iments were standardized within participants, i.e., the normal- ization was personalized. In multilevel modelling terms, this is Figure 3: The offset of random effects of interaction terms equivalent of introducing a participant random effect. By defining of person and day (roughly corresponding to person-day- an intercept-only linear mixed model using the lme4 library [3], specific means of stress in one EMA session) main intercept it turned out that the variance explained by these person-specific effect (roughly corresponding to the overall mean). 2 intercepts was 𝜎 = 0.20, which amounted to 57 % of the total 𝑢 variance. By including day-specific intercepts, this model performs sig- The random effect of participants is illustrated in Figure 2. It 2 nificantly better ( 𝜒 = 509, 𝑝 < 0.001). We next consider what shows that the participants differ in how they evaluated their that means in the context of machine learning. negative affect. Their mean assessments are mostly distributed within 1 point away from the overall mean, but some differed 4 DISCUSSION from it by almost 2 points When considering two sources of variability, the person and the day level, we showed that much of the total variance can be ascribed to within-person differences. This can be interpreted to confirm the merit of personalized normalization of the data, but other interpretations are also possible. It should be noted that we only dealt with the target variable in this work. Thus, variance partitioning does not help with deciding whether to normalize independent variables. In general, it is advised to normalize physiological data since there exists participant inherent variability of physiological functioning in the general population [18]. Similarly, explorative analysis indicated that phone sensors vary across devices and it is also feasible to assume that people’s phone usage varies significantly (independent of their stress level). -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 For the target variable itself, the proportion of variance ex- random effects with confidence intervals plained with within-person differences can be interpreted in at least two ways. Either the participants were on average exposed Figure 2: The offset of person random effects (roughly cor- to different levels of stress and this is why their assessments differ responding to person-specific means of daily stress) from in a systematic way. Alternatively, participants can have differing the main intercept effect (roughly corresponding to the thresholds of evaluating something as stressful. Since the self- overall mean). reports are completely subjective, it is not possible to differentiate between these two interpretations with the self-assessments as Next, we considered a three-level model with data aggregated labels. It would be possible to explore this further by taking phys- on an EMA session basis. We modelled a random effect by varying iological measures as ground truth for stress and use them to the intercept among subjects and among days within subjects. explain subjective measures. Treating the physiological measures The variance that was explained by adding the day level was as universal is problematic, however, and they might not even 2 𝜎 = 0.08 or 11 % of the total variance. This is in addition to the be related to stress deterministically. Physiological responses 𝑣 589 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Junoš Lukan, Larissa Bolliger, Els Clays, Primož Šiško, and Mitja Luštrek are not specific to different stress states, but rather a more com- measurements. A review. Journal of Biomedical Informatics, 59, (Feb. 2016), 49–75. doi: 10.1016/j.jbi.2015.11.007. plex relationship exists between the stimuli, physiology, and the [3] Douglas Bates, Martin Mächler, Ben Bolker, and Steve Walker. 2015. Fitting parameters that control dynamics between them [7]. linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1. Finally, normalization is not at all the only option of removing doi: 10.18637/jss.v067.i01. [4] Larissa Bolliger, Ellen Baele, Elena Colman, Gillian Debra, Junoš Lukan, the person-specific variation. Methods such as linear discriminant Mitja Luštrek, Dirk De Bacquer, and Els Clays. 2022. The association between analysis offer ways that have been shown to perform better [1]. day-to-day stress experiences, recovery, and work engagement among office Including person-day random effects in the three-level model, workers in academia. An ecological momentary assessment study. PLOS ONE. Submitted. the intercept model performs better than the one with only per- [5] Larissa Bolliger, Gillian Debra, Junoš Lukan, Rani Peeters, Mitja Luštrek, son random effects included. Following the same reasoning as for Dirk DeBacquer, and Els Clays. 2022. The association between day-to- day stress experiences and work–life interference among office workers the two level model, this could be interpreted that day-specific in academia. An ecological momentary assessment study. International normalization would be beneficial. There are several arguments Archives of Occupational and Environmental Health. doi: 10.1007/s00420-02 against this interpretation, however. 2- 01915- y. In press. [6] Larissa Bolliger, Junoš Lukan, Mitja Luštrek, Dirk De Bacquer, and Els Clays. First, as indicated in Section 2.2, participants responded to 2020. Protocol of the stress at work (STRAW) project: how to disentangle questionnaires 5 or 6 times a day. Standardizing with this lit- day-to-day occupational stress among academics based on EMA, physio- tle data is dubious, while using such small samples for feature logical data, and smartphone sensor and usage data. International Journal of Environmental Research and Public Health, 17, 23, (Nov. 2020), 8835. doi: selection or model validation is unacceptable. Second, the ques- 10.3390/ijerph17238835. tionnaire data are not truly continuos, but in fact interval data [7] Justin Brooks, Joshua C. Crone, and Derek P. Spangler. 2021. A physiological and dynamical systems model of stress. International Journal of Psychophys- (at best) that can take 5 possible values. Since each EMA session iology, 166, (Aug. 2021), 83–91. doi: 10.1016/j.ijpsycho.2021.05.005. included only two items from each questionnaire, aggregating at [8] Daniel J. Brotman, Sherita H. Golden, and Ilan S. Wittstein. 2007. The car- this level brings the number of possible values to only 9. Aggre- diovascular toll of stress. The Lancet, 370, 9592, 1089–1100. doi: 10.1016/s01 40- 6736(07)61305- 1. gating on a daily level, however, summarises about 10 different [9] Denzil Ferreira, Vassilis Kostakos, and Anind K. Dey. 2015. AWARE: Mobile measurements, increasing the resolution to 0.1 point. This makes context instrumentation framework. Frontiers in ICT, 2, 6, 1–9. doi: 10.3389 daily means much closer to a continuous variable which can be /f ict.2015.00006. [10] Andrew Gelman and Jennifer Hill. 2006. Data Analysis Using Regression modelled by regression methods. and Multilevel/Hierarchical Models. Cambridge University Press, 648. isbn: We can therefore argue that normalizing data by considering 9780521686891. [11] Vito Janko, Matjaž Boštic, Junoš Lukan, and Gašper Slapničar. 2021. Library each day as a separate unit is not appropriate. We can conclude, for feature calculation in the context-recognition domain. In Proceedings of however, that treating each EMA session as its own instance is the 24nd International Multiconference INFORMATION SOCIETY – IS 2021. beneficial. As stated in Section 3.2, analysis on the EMA session Slovenian Conference on Artificial Intelligence (Ljubljana, Slovenia, Oct. 4– 8, 2021). Mitja Luštrek, Rok Piltaver, and Matjaž Gams, editors. Vol. A, 23–26. level can explain at least 11 % of variance that is not captured https://library.ijs.si/Stacks/Proceedings/Inf ormationSociety/2021/IS2021 by the variability between participants. This conclusion is also _Volume_A.pdf . illustrated in Figs. 2 and 3: while the general pattern of random [12] Junoš Lukan, Larissa Bolliger, Els Clays, Oscar Mayora, Venet Osmani, and Mitja Luštrek. 2021. Participants’ experience and adherence in repeated effects shown by red points in Fig. 3 can already be sensed in measurement studies among office-based workers. In Adjunct Proceedings Fig. 2, the noisy structure of confidence intervals is noticeable of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on and worth exploring further. Wearable Computers (Virtual, Sept. 21–24, 2021). ACM. doi: 10.1145/346041 8.3479367. 5 CONCLUSIONS [13] Junoš Lukan, Larissa Bolliger, Nele S. Pauwels, Mitja Luštrek, Deirk De Bacquer, and Els Clays. 2022. Work environment risk factors causing day-to- Multilevel models are a well established method in medical, bio- day stress in occupational settings. 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Journal of Personality and Social Psychology, 54, 6, 1063–1070. doi: early stress recognition system for office environments based on multimodal 10.1037/0022- 3514.54.6.1063. 590 Academic Performance Relation with Behavioral Trends and Personal Characteristics: Wearable Device Perspective Berrenur Saylam, Ekrem Yusuf Ekmekci, Eren Altunoğlu, Ozlem Durmaz Incel Computer Engineering Department, Boğaziçi University İstanbul, Turkey {berrenur.saylam,ozlem.durmaz}@boun.edu.tr ABSTRACT surveys corresponding to the subject’s origin, sex, education level, Understanding the relevant factors related to students’ academic bad habits, as well as state-of-the-art sleep, big five, mental health performance can help to construct a more precise methodology inventories (the details are given in Table 1). We aim explore the for conducting successful academic life. Several studies examine factors affecting students’ academic performances. the relationship between students’ lives and academic perfor- We utilize the NetHealth open source data [5] which contains mances using statistical techniques with subjective responses students’ sleep routines, daily physical activities, communication collected via questionnaires in the literature. In the last decade, behaviors collected with mobile phones, and a detailed survey wearable devices, such as smartwatches and smartphones, have about family history, living conditions, and personality. Data gained popularity in the research community since they can pro- related to sleep and activity is collected from wearable devices vide objective measurements of the users’ activity, sleep, and and documented. We aim to find the relation between some of mood states with integrated sensors. It is possible to extract the abovementioned aspects and academic performance. markers related to individuals’ physiological and psychological We have a large dataset from different academic periods (waves) states. This study explores the most important factors from wear- and various survey data. However, the surveys were not filled ables and questionnaires about students’ academic grades using in every period, hence, we focused on one period with the least the NetHealth dataset. We utilize machine learning techniques, amount of missing information. Before applying our models, we specifically Random Forest, rather than classical statistical ana- performed a preprocessing procedure by imputing the data with lyzes in literature. We believe that we contribute to interpreting proper techniques to handle missing values and preparing them the underlying factors related to grade by examining objectively- for the final analysis. We utilized machine learning techniques, measured multi-modal datasets. We also focus on classifying the specifically Random Forest (RF) algorithm, both for factor selec- grades with Random Forest and achieve overall 76% accuracy. tion and classification. In addition, we provide essential parame- The most important factors affecting academic performance are ters for the student’s academic performance. These are related observed to be sleep, big five personalities, health, and mental to sleep, big five personalities, health, mental health, personal health. information, and origin data in order. We believe that these in- formation can be helpful in understanding affecting factors for KEYWORDS further improvement of student life to get better performance Wearable computing, machine learning, multi-modality, well- during their academic life. being, pervasive computing, student grades, behavioral patterns, One of the essential contribution of our work is bringing dif- personality traits ferent factors together and trying to produce a combination of them. In that way, we aim to find the most important predictors 1 INTRODUCTION for students’ academic performance by combining other focus areas, such as sleep, mental health, and activities, in the scope of Understanding the underlying factors of academic performance one study. may help students to perform better throughout their academic Considering the studies utilizing NetHealth data, some are life. Many studies have investigated these factors affecting aca- analyzing the data on different topics such as biometric-based demic performance, including family history, psychological well- authentication [6], physical activity and sleep pattern [7]. There being, and physical activity [1, 2, 3, 4]. Some approached the are studies doing network analysis [8, 9], physical activity predic- situation from family history [1], and some focused on the ex- tion [10]. To the best of our knowledge, no similar study exists istence of physical activity in the curriculum [2]. Also, some among the listed papers. studies considered sleep based on self-reported measures [3]. The rest of the paper is organized as follows: In Section 2, However, they are based on one modality, focusing on one factor we explain state of the art on student grades studies and from and trying to understand its effect on the target (i.e., students’ point of wearable domain. In Section 3, we explain dataset details academic performance). This approach does not provide a meta- and the preprocessing steps for further analyses. In Section 4, understanding between different modalities. Thus, a multi-modal we present academic grade’s classification results with different approach is necessary to obtain a more expanded view. balancing strategies. We give factors for best case. Finally, in This study focuses on multi-modal data analysis collected Section 5, we discuss our findings with other future study ideas. from objectively measured wearable devices’ sensors and several Permission to make digital or hard copies of part or all of this work for personal 2 RELATED WORKS 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 Many related works exist about student’s academical perfor- the full citation on the first page. Copyrights for third-party components of this mance from the point of different domains such as educational, work must be honored. For all other uses, contact the owner/author(s). psychological and smartphone sensing [11, 12, 13, 14]. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). Objectively measured signals sensed from wearables applied into the research field related to student’s mental health and 591 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Saylam, et al. academic performance, to the best of our knowledge, starts with • Network survey data: Interactions’ network data with the StudentLife [11] project. related information such as relationship type, duration, In [12], authors collect the day-to-day and week-by-week frequency of interaction, similarity, etc. impact of workload on stress, sleep, activity, mood, sociability, mental well-being and academic performance via smartphone 3.2 Preprocessing sensors. They examined strong correlations between smartphone As stated in Section 3.1, there are 8 waves. Each wave has different sensors and student’s mental health along with their academical survey questions and thus responses. For instance, in waves scores by not counting behavioral differences. 1, 2, 3, 7, there are no questions related to stress, while in 4, 5, 6, 8, In [13], authors extracted related factors to the students aca- there are. Similarly, sleep ground truth is not collected during demical grades from academic related behaviors, personality, the study waves 5, 7. Thus, we chose to work on wave 1 as it affect, stress, lifestyle and sensed behaviors with wearables. They contains relatively higher responses than other waves. modelled behavior change points to capture individual’s behav- Firstly, we constructed a sub-dataset from NetHealth concen- iors while having the same final grade. One of the findings is trating on our purpose. The details are explained in Section 3.2.1. study duration has positive correlation with the final grade. Then, we prepossessed our data by deleting highly correlated In [14], researchers examined the relation between wearable ones (in Section 3.2.3). Finally, we applied the Random Forest device sensors and survey with student’s grade in a similar man- algorithm for the rest of the study. ner. They used SVM with different kernel setups. They found social features such as negative email contacts and negative inter- 3.2.1 Dataset Preparation. As the dataset includes many differ- actions are lower on students with high GPA. Also, accelerometer ent data types, each of them has various parameters, we decided sensor in wearables have an impact on discriminating the higher which parameters to use before starting our study. We consid- and lower performants. This study is similar to our experiment, ered all parameters from wearable devices and course-grades where there is multi-modal data from wearable sensors and sur- datasets. However, we selected some of the collected data from veys. We also examine the related factors on different datasets, the survey dataset. Surveys constitute, mainly, bad habits, big-five but our study also explores class balancing scenarios. personality inventory, education, exercise, health, mental health, origin, personal information, sex, and sleep related answers. We 3 METHODOLOGY used only the summarizing parameters provided by the survey for mental health, personal information, and sleep. We select 3.1 Dataset some parameters from the origin category manually. We used We utilized the NetHealth dataset1. It is collected from under- the parameters of parents’ status, economic condition, number graduate students from Notre Dame (ND) University between of siblings, and religion. Table 1 gives the final list of utilized Fall 2015 and Spring 2019. Thus, there are 8 waves corresponding parameters. At the end of the naming, some parameters have _1 to each semester. There are approximately 700 students’ data indications, which relate to the measuring from wave1. from the 2015 − 2017 period and 300 from the 2017 − 2019 period caused by the drops in participation. Data collection consists of 3.2.2 Handling Missing Values. Once the dataset was prepared the social network, physical activity, sleep data from Fitbit wear- for analysis, we noticed missing values over columns. We pre- able device, and ground truth data from questionnaires about ferred to keep these columns and impute them since they are physical and mental health, social-psychological states, tastes, partially missed. We applied the most frequent imputation tech- and various self-reported behaviors, demographics, and back- nique to the categorical ones and the mean imputation technique ground traits. The collection procedure is approved through IRB to the numerical ones. However, there is enough correlation for protocols, and each participant has consented. Nevertheless, not activity-related wearable data to use the KNN imputation tech- all data collection is publicly shared due to privacy concerns. nique. Thus, we used this technique. Finally, sleep data from The details of the collected dataset per modality are as follows. wearables did not contain any missing values. We performed our study with boldly-marked sub-datasets. 3.2.3 Correlation. We checked the correlation between parame- • Communication data: Collection of smartphone-based com- ters to reduce dimensionality. We deleted the ones which exhibit munication logs data. higher than %80 correlations. These are cardiomins, fatburnmins, • Wearable data: Collected measurements regarding activ- lowrangemins, minsasleep, minsawake, peakmins parameters. We ity and sleep such as the number of steps, active minutes, can deduct the information related to them from other parame- heart rate, sleep duration, sleep time, and awaken time ters, for instance, cardiocals for cardiomins and fatburnmins. We using Fitbit. decided on the threshold value after many experiments. When • Courses and grades data: Administrative records from we increase it, we keep the highly correlated ones, and when we ND Registrar’s Office containing course and grade infor- decrease the threshold, more parameters will be deleted, which mation. causes unnecessary parameter loss. Eliminating them prevents • Calendar: Weekly calendar showing the days about the misleading results due to highly correlated features in detecting beginning of classes, break weeks, holidays, etc. interactions between different features. We had 93 parameters. • Survey data: Self-reported questionnaires related to phys- After removal of the 6 highly correlated ones, we have 87 features. ical and mental health, social-psychological states, tastes, and various self-reported behaviors, and demographics 3.2.4 Target value’s distribution. In this study, we are working towards the identification of important parameters and the appli- and background traits. cation of machine learning methods regarding students’ grades. Thus, before starting the analysis, we examined target values, i.e., student grades distribution, to observe whether there is class 1http://sites.nd.edu/nethealth/ imbalance. The distribution is in Figure 1. Here, it is seen that we 592 Academic Performance via Wearable Devices Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Table 1: Details of the features Dataset Measured Values complypercent (percent minutes using Fitbit), meanrate (mean heart rate), sdrate (st. dev. heart rate), steps, floors, sedentaryminutes, Wearable data lightlyactiveminutes, fairlyactiveminutes, veryactiveminutes, (Activity) lowrangemins (low range minutes), fatburnmins, cardiomins, peakmins, lowrangecal, fatburncal, cardiocal, peakcal timetobed (time went to bed), timeoutofbed (time out of bed), bedtimedur (minutues in bed in minutes), minstofallasleep (minutes to fall asleep), Wearable data minsafterwakeup (minutes in bed after waking), minsasleep (minutes asleep), (Sleep) minsawake (minutes awake during sleep period), Efficiency (minsasleep/(minsasleep + minsawake) Courses and grades AcademicPeriod, CourseReferenceNumber, FinalGrade usetobacco_1 (used tobacco), usebeer_1 (drank beer), usewine_1 (drank wine or liquor), Survey data usedrugs_1 (used rec drugs like marij. or cocaine), (Bad habits) usedrugs_prescr_1 (used presc. drugs not prescribed), usecaffine_1 (drank caffenated drinks) Survey data Extraversion_1, Agreeableness_1, Conscientiousness_1, (BigFive/Personal inventory) Neuroticism_1, Openness_1 hs_1 (high school type), hssex_1 (high school sex composition), Survey data hsgrade_1 (high school average grade), apexams_1 (# of hs ap exams), (Education) degreeintent_1 (highest intended degree), hrswork_1 (paid hours senior year), ndfirst_1 (Notre Dame first choice of applied colleges?) hsclubrc_1 (club activities), exercise_1 (excersise), Survey data clubsports_1 (play club, intramural or rec sports) , (Exercise) varsitysports_1 (play varsity sports), swimming_1 (swim), Dieting_1 (special type of diet), PhysicalDisability_1 (physical disability) SelfEsteem_1 (on the whole, I am satisfied with myself), Trust_1 (most people can be trusted), SRQE_Ext_1 (external self-regulation (exercise)), SRQE_Introj_1 (introjective self-regulation (exercise)), Survey data SRQE_Ident_1(identified self-regulation (exercise), (Health) SelfEff_exercise_scale_1 (when i am feeling tired), SelfEff_diet_scale_1 (self_efficacy score (diet items)), selfreg_scale_1 (i have trouble making plans to help me reach my goals) STAITraitTotal_1 (state_trait anxiety score), CESDOverall_1 (CES depression score), Survey data BAIsum_1 (beck anxiety score), STAITraitGroup_1 (state_trait anxiety 2 category), (Mental health) CESDGroup_1 (CES depression - 2 categories), BAIgroup_1 (beck anxiety (3 category)), majorevent_1 (life changes) momdec_1 (is your mother deceased?), momusa_1 (was mother born outside usa?), daddec_1 (is your dad deceased?), dadusa_1 (was your dad born outside usa?), parentstatus_1 (parents living together or divorced/living apart), Survey data dadage_1 (father’s age), momage_1 (mom’s age), numsib_1 (number of siblings), (Origin) birthorder_1 (which # in birth order are you?), parentincome_1 (parent’s total income last year), parenteduc_1 (combined parent education), momrace_1 (mother’s race), dadrace_1 (father’s race), momrelig_1 (mother’s religious preference), dadrelig_1 (father’s religious preference), yourelig_1 (your religious prefence) selsa_rom_1 (romantic loneliness), Survey data selsa_fam_1 (family loneliness), (Personal info) selsa_soc_1 (social loneliness) Survey data (Sex) gender_1 (gender) PSQI_duration_1 (computed time in bed), PSQIGlobal_1 (PSQI total score), Survey data PSQIGroup_1 (PSQI two categories), (Sleep) MEQTotal_1 (MEQ (chronotype) score - high score morning person), MEQGroup_1 (MEQ (chronotype) groups - 5 categories)) have A grade on the majority, and we have very few instances the same class distribution [15]. After SMOTE, we got 41856 from the B-, C+, C, C- classes. More specifically, we have 41856, instances from each class. 19321, 10048, 7265, 2526, 1617, 1258, 354, 4346 from classes A, A-, B+, B, B-, C+, C, C-, S (satisfactory), respectively. To well clas- sify minority classes, we applied the SMOTE (synthetic minority over-sampling) technique to produce synthetic data by keeping 593 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Saylam, et al. Table 2: Classification performance details precision recall f1-score support A 0.53 0.56 0.55 10434 A- 0.52 0.44 0.47 10410 B 0.66 0.71 0.68 10449 B+ 0.67 0.60 0.63 10507 B- 0.85 0.87 0.86 10507 C 0.89 0.92 0.91 10494 C+ 0.88 0.89 0.88 10418 Figure 1: Target value distribution: Grade C- 0.98 0.98 0.98 10502 S 0.78 0.83 0.80 10455 accuracy 0.76 94176 3.3 Model details and performance metrics macro avg 0.75 0.75 0.75 94176 weighted avg 0.75 0.76 0.75 94176 As a classification method, we used RF algorithm because it is an ensemble method and performs better than the other used methods in literature in this domain [16]. The used parameters for RF are n estimators 1000, criterion Gini, and max features sqrt from scikit-learn toolkit2. %75 and %25 train and test sizes are chosen, respectively. 4 CLASSIFICATION PERFORMANCE EVALUATION Since our target variable is already categorical, we used the dataset after preprocessing without any other change in the classification task. In Table 2, we present f1-score details of each class performance and the global average of the f1-scores with the accuracy metric. We obtained %76 average accuracy. We see that the best performances are achieved for the classes B-, C+, C-, Figure 2: Confusion Matrix S. Before SMOTE application, it was %65 average accuracy; fur- thermore, we had lower f1 scores for these indicated classes, but we did not present the details due to the page limit. The confused instances may be observed in Figure 2. For instance, A class is confused mostly with A+ with an important ratio. It is expected since these are very close classes. The class S is mostly confused with others. It can be interpreted as expected since a satisfac- tory result corresponds to passing the course. SMOTE generates instances based on a similarity measurement rather than replicat- ing existing ones. Thus, the bias is relatively lower compared to simple replications of instances since these are newly generated ones. Nevertheless, we also applied the under-sampling strategy and down-sampled higher class instances to be equal to the class Figure 3: Feature Importance for Classification with fewer instances. Thus, we obtained 354 instances for each class. When we applied RF to that data, we obtained even worse performance, which is 47% average accuracy. It is expected since 5 DISCUSSION AND CONCLUSION we deleted most data points, so learning with few instances led In this study, we applied a machine learning technique, RF, to to lower results. see how accurately we can classify and predict students’ grades In addition, in Figure 3, we provide the most critical factors using surveys and wearable data. In addition, we extract the most to obtain this classification performance by calculating the most important factors affecting the model’s performance. Results important 20 parameters via RF feature selection. The order is indicate sleep, big five, health, mental health, personal information, following: MEQTotal (sleep), Trust (health), Extraversion (big five), and origin survey parameters have higher effects on performance. selsa_soc (personal info), selsa_rom (personal info), Openness (big We differ from state-of-the-art [12, 13, 14] by applying SMOTE. five), Neuroticism (big five), SRQE_Ext (health), dadage (origin), For further research, one may examine other waves since there PSQI_duration (sleep), PSQIGlobal (sleep), BAISum (mental health), are 8 to obtain more instances from each class. Also, since the hsgrade (education), SRQE_Introj (health), CESDOverall (mental dataset is collected from one of the top University students, it health), SelfEff_exercise_scale (health), Agreeableness (big five), is expected to have higher grades, i.e., A, A+. Thus, applying a momage (origin), MEQGroup (sleep). The explanation of these similar experimental data collection setup to students with lower parameters is presented in Table 1. We can interpret this result performances in the courses may be helpful. as the most important factors arrive from survey datasets. The important sub-surveys are sleep, big five, health, mental health, ACKNOWLEDGEMENTS personal information, and origin. Tübitak Bideb 2211-A academic reward is gratefully acknowl- edged. This work is supported by The Turkish Ministry of Devel- 2https://scikit-learn.org/stable/ opment under the TAM Project number DPT2007K120610. 594 Academic Performance via Wearable Devices Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia REFERENCES [9] Liu, Shikang, et al. “Network analysis of the NetHealth data: exploring co- [1] Misty, Lacour, and D. Tissington Laura. “The effects of poverty on academic evolution of individuals’ social network positions and physical activities." Applied achievement." 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(2019): 103139. 595 Detection of postpartum anemia using machine learning David Susič Lea Bombač Tavčar Hana Hrobat david.susic@ijs.si bombac.lea@gmail.com hana.hrobat@icloud.com Jožef Stefan Institute University Medical Centre Ljubljana, University of Ljubljana, Faculty of Jamova cesta 39 Division of Gynaecology and Medicine Ljubljana, Slovenia Obstetrics Vrazov trg 2 Šlajmerjeva 3 Ljubljana, Slovenia Ljubljana, Slovenia Lea Gornik Miha Lučovnik Anton Gradišek lea.gornik@gmail.com miha.lucovnik@kclj.si anton.gradisek@ijs.si University of Ljubljana, Faculty of University Medical Centre Ljubljana, Jožef Stefan Institute Medicine Division of Gynaecology and Jamova cesta 39 Vrazov trg 2 Obstetrics Ljubljana, Slovenia Ljubljana, Slovenia Šlajmerjeva 3 Ljubljana, Slovenia ABSTRACT unacceptably high prevalence of anaemia in women after child- birth in both, up to 50% in developed and up to 80% in developing Postpartum anemia is seen as a health problem and should be countries [4], it appears to be of great importance to treat iron treated. We evaluate performance of nine machine learning re- deficiency effectively. In addition to the increased transfusion gression models in predicting the postpartum anemia six weeks risk, peripartum iron deficiency anaemia can affect the wellbeing after childbirth. We focus on tree key parameters: ferritin, haemoglobin, of both the mother and child. It causes cardiovascular symp- and transferrin saturation. Our models are compared with the toms like palpitations and dizziness, breathlessness. It increases baseline model, which always predicts the mean value of the a risk of infections as well as excessive postpartum bleeding. Fur- training data. We found that the models for ferritin and trans- thermore, postpartum anemia adversely affects maternal mood, ferrin saturation have good predictive performances, whereas cognition, and behavior resulting in increased fatigue, reduced this was not the case for haemoglobin prediction, as all of the physical and mental performance [6]. This is associated with implemented models were outperformed by the baseline model. several negative consequences, such as impaired health-related KEYWORDS quality of life [3]. Impaired health-related quality of life linked to postpartum anemia include depression, fatigue, and reduced postpartum anemia, haemoglobin level, machine learning cognitive abilities. All of these symptoms significantly interferes with mother-child interactions and impact a woman’s ability to 1 INTRODUCTION breastfeed [1]. Postpartum anemia is a common maternal health problem glob- Postpartum anemia should be treated by restoring iron stores. ally and constitutes a significant health problem in women after Although there is a number of treatment options for women with birth, even in the developed world. Women may develop it either postpartum anaemia, the debate about iron supplementation and because of antepartum depletion of iron stores or peripartum the ideal form of administration is ongoing and is not universal excessive blood loss [1]. It is associated with several negative con- in all countries. Currently, common treatment includes iron sup- sequences, such as maternal fatigue [2, 3]. With the unacceptably plementation administered orally or intravenouslly (IV). The tra- high prevalence of anaemia in women after childbirth in both, ditional treatment for mild to moderate iron deficiency anaemia up to 50% in developed and up to 80% in developing countries [4], is oral supplementation of iron with iron sulfate perorally be- it appears to be of great importance to treat iron deficiency effec- cause of its low cost and simple use. There are advantages and tively. Ferrum sulphate perorally is the most commonly used iron disadvantages of either of the two approaches, which we will not for pospartum anemia because of its low cost and simple use. Def- go into detail here. Since the postpartum anaemia contributes inition of postpartum anaemia rely on haemoglobin values alone, to a major healthcare problem even in developed countries, it defined as Hb level <100 g/L. Postpartum haemorrhage defined as is important to treat it efficiently [7]. However, IV iron may be a blood loss of 500 ml or more within 24 hours after birth is one of preferred because the non-compliance and absorption challenges the most frequent complications of delivery. This makes women of oral iron, but it includes increased drug costs and the need for vulnerable and frequently results in postpartum anemia. Conse- supervised treatment in healtcare institutions. Recent robust stud- quently, this increases the risk for a peripartum blood transfusion, ies have compared different iron preparations and there has been a treatment with potential severe adverse outcomes [5]. With the a network meta-analysis of different iron medications. However, no randomized clinical trial has directly compared intravenous derisomaltosie, intravenous carboxymaltose and peroral ferrous 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 sulphate for treatment of postpartum anemia, including fatigue distributed for profit or commercial advantage and that copies bear this notice and measurements. the full citation on the first page. Copyrights for third-party components of this In this paper, we address the question on predicting the post- work must be honored. For all other uses, contact the owner /author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia partum anemia six weeks after childbirth. We look at three key © 2022 Copyright held by the owner/author(s). parameters from blood tests that are related to anemia, namely 596 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Susič et al. Table 1: Dataset features. also be cause as a consequence of an injury during childbirth or Cesarean section. Typically, CRP levels are increased after Personal Blood test childbirth. If the high level of CRP (>8 mg/L) still persists after six weeks after the childbirth, this indicates inflammation. Age [years] Haemoglobin [g/L] Gestational age [weeks] Serum iron [𝜇 mol/L] 3 METHODOLOGY Number of children born TIBC [𝜇 gmol/L] The aim of this initial study was to evaluate the performance of Number of total pregnancies Transferrin saturation [%] several machine learning (ML) models in predicting the values of Number of total childbirths Ferritin [𝜇 g/L] haemoglobin, ferritin, and transferrin saturation levels in blood Number of total abortions Phosphate [mg/dL] of the anemia patients six weeks after childbirth, as these parame- Type of childbirth CRP [mg/L] ters are related to anemia. The input of the models were personal Transfusion features and the features of the blood test immediately after the Marital status childbirth. In each experiment, only one of the three quantities Education was the output. Thus, we ran three experiments with the same BMI before childbirth input and different outputs. Additionally, we ran additional sep- BMI after childbirth arate experiments for each of the three medication groups. We Medication compared our results with the baseline, which always predicted the mean output value of the training data. the ferritin, haemoglobin, and transferrin saturation. Using a 4 RESULTS database containing 296 patients that were diagnosed with ane- Our dataset included 224 patients with 20 predictor features. We mia, we investigate the possibilities to predict these relevant used mean absolute error (MAE), root mean squared error (RMSE), blood test values using machine-learning models. We present the and mean absolute percentage error (MAPE) as the evaluation results of our initial studies. metrics, with MAE as the main metric of performance evaluation. 2 DATA Formulas for calculation of MAE, RMSE , and MAPE are given in equations (1), (2), and (3). Parameter 𝑦 denotes predicted values, 𝑖 The initial dataset included 296 patients that were diagnosed 𝑥 denotes true values, and 𝑛 denotes the total number of data 𝑖 with anemia and 27 features that had some missing values. As points. this was our initial study, we did not perform any missing data inputation, but rather dropped the patients that had missing Í𝑛 |𝑦 − 𝑥 | 𝑖 𝑖 𝑖 =1 values in any of the columns. We were left with 224 patients that 𝑀 𝐴𝐸 = (1) 𝑛 had data for all 27 features. Based on the medications that the patients were given during their treatment, they can be separated √︄ Í𝑛 (𝑦 − 𝑥 )2 𝑖 𝑖 in three groups: 80 of the patients were treated with Iroprem, 75 𝑖 =1 𝑅𝑀 𝑆 𝐸 = (2) 𝑛 were treated with Monofer, and 69 were treated with Tardyfer. Both Monofer and Iroprem are IV medications with iron, while 𝑛 1 ∑︁ − 𝑥 𝑦 𝑖 𝑖 Tardyfer is administered orally as tablets. 𝑀 𝐴𝑃 𝐸 = (3) 𝑛 𝑥𝑖 The data included personal data and blood test results. Blood 𝑖 =1 tests were performed both right after the childbirth as well as six We implemented nine ML regression models. Regression mod- weeks after. The list of personal and blood test features is given els predict a continuous variable(s). Linear regression (LR), Kernel in Table 1. Ridge (KR), and elastic net regression (EN) find linear correla- In the dataset, there are 13 personal features and 2 · 7 blood test tions between the predictor features and the output. Bayesian features. Among personal features, gestational age corresponds ridge regression (BR) formulates linear regression using proba- the number of weeks since the last period. The type of child- bility distributions rather than point estimates. Support vector birth is a categorical variable and can either be vaginal delivery, regression (SVR) finds a hyper-plane in the feature space that has planned Cesarean section, or elective Cesarean section. Trans- maximum number of data points. Gradient boosting regressor fusion is a binary variable indicating whether a patient needed (GB), Light gradient boosting machine (LGBM), extreme grad- a blood transfusion after the childbirth or not. Marital status ing boosting regressor (XGB), and CatBoost regressor (CB) are is a categorical variable and can either be lives alone, married, ensemble methods that combine the predictions of multiple deci- or non-marital partnership. Education is ordinal variable of 10 sion tree regressors. A decision tree regressor uses a tree diagram different values with the lowest representing elementary school for decision making, where each branch is partitioned based on education and the highest representing a doctoral degree. Lastly, a threshold for a predictor feature. BMI stands for body mass index. The models trained on the whole dataset were compared in a In the blood test features, serum iron describes the amount 10-fold cross validation with the folds stratified with respect to of iron in the blood. TIBC stands for total iron binding capacity, the medication. The models trained for separate medication only which is a good indicator of the amount of iron in blood. If the iron were compared in a 5-fold cross validation due to the smaller level in blood is low, the TIBC is higher as the free capacity for dataset size. For each of the output variables, we also show a his- binding of the iron is higher. Transferrin saturation is the value togram of values distribution along with the mean and standard of serum iron divided by the TIBC of the available transferrin. deviation (SD). The higher the transferrin saturation, the bigger the iron stores The models’ training and performance evaluation was done in the body. Lastly, CRP stands for C-reactive protein, which using Python 3.7 and libraries Numpy 1.18.5 [8], Scikit 0.24.2 [9], is high is there is inflammation in the body. Inflammation can LightGBM 3.2.1 [10], XGBoost 1.4.2 [11], and CatBoost 0.26 [12]. 597 Detection of postpartum anemia Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 4.1 Ferritin Table 3: Results for the prediction of ferritin for each med- ication separately. Distribution of ferritin blood levels six weeks after childbirth is given in Figure 1. We see that the patients that were given medication Tardyfer had significantly lower levels than those Model Iroprem MAE Monofer MAE Tardyfer MAE that were given medications Iroprem or Monofer. The mean and LR 93.65 70.85 41.33 SD values of the distribution are 185.88 𝜇 g/L and 141.31 𝜇 g/L, LGBM 86.19 57.03 21.74 respectively. Results of the regression models are given in Table XGB 95.48 62.44 19.43 2. CB 81.26 58.78 20.48 KR 98.90 69.93 33.11 EN 92.76 63.77 31.81 BR 96.24 61.47 21.99 GB 88.37 70.00 25.69 SVR 97.41 58.20 19.27 Baseline 94.61 55.87 23.42 Figure 1: Distribution of ferritin blood levels in patients six weeks after childbirth. Table 2: Results for the prediction of ferritin. −2 Model MAE RMSE MAPE [10 ] Figure 2: Distribution of haemoglobin blood levels in pa- tients six weeks after childbirth. CB 61.96 87.44 80.11 XGB 62.76 93.97 61.23 LGBM 63.07 88.31 65.88 Table 4: Results for the prediction of haemoglobin. GB 64.14 91.32 83.86 LR 68.42 89.45 86.26 −2 Model MAE RMSE MAPE [10 ] KR 69.3 90.62 80.2 Baseline 6.11 8 4.62 EN 79.64 99.56 158.81 BR 6.31 8 4.77 BR 80.43 101.93 135.88 SVR 6.33 8.01 4.80 Baseline 111.81 138.88 272.51 EN 6.56 8.22 4.96 SVR 112.91 140.25 260.76 LR 6.67 8.41 5.03 CB 6.74 8.34 5.10 We see that the best performing model according to both LGBM 7.16 8.93 5.41 metrics was the CB. Except for the SVR, other models have had XGB 7.2 9.19 5.44 similar performances to that of CB. Additionally, we see that GB 7.28 9.03 5.52 most of the models significantly outperform the baseline. KR 7.43 9.45 5.59 The results of the models performance of predictions for sepa- rate medications only are shown in Table 3. The models within each medication have similar performances. In the case of Monofer, We see that the models do not perform well in predicting all of the models’ performances are worse than that of the base- haemoglobin, as they perform worse than the baseline for both line. the general case and the separate medication cases. 4.2 Haemoglobin 4.3 Transferrin saturation Distribution of haemoglobin blood levels six weeks after child- Distribution of transferrin saturation in blood six weeks after birth is given in Figure 2. We see that the distributions are very childbirth is given in Figure 3. We see that the distributions are similar between all three medication groups. The mean and SD very similar between all three medication groups. The mean and values of the distribution are 133.87 g/L and 8.10 g/L, respectively. SD values of the distribution are 33.56 % and 11.53 %, respectively. Results are given in Tables 4 and 5. Results of the regression models are given in Table 6. 598 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Susič et al. Table 5: Results for the prediction of haemoglobin for each Table 7: Results for the prediction of transferrin saturation medication separately. for each medication separately. Model Iroprem MAE Monofer MAE Tardyfer MAE Model Iroprem MAE Monofer MAE Tardyfer MAE LR 6.99 7.04 8.17 LR 7.68 9.4 11.84 LGBM 5.46 6.41 8.21 LGBM 7.16 7.59 11.39 XGB 6.38 6.58 9.20 XGB 8.36 9.12 12.86 CB 5.75 6.58 8.03 CB 7.2 7.87 11.44 KR 7.65 7.13 8.63 KR 7.73 8.94 12.01 EN 5.69 6.43 7.36 EN 7.16 8.54 11.24 BR 5.31 6.45 7.33 BR 6.8 7.83 12.02 GB 5.79 7.23 9.41 GB 7.88 8.78 11.61 SVR 5.42 6.62 7.28 SVR 6.94 7.62 11.62 Baseline 5.17 5.85 7.22 Baseline 6.49 7.75 11.82 haemoglobin, and transferrin saturation. We compared the results with the baseline model, which always predicted the output mean of the training data. We found that the models for ferritin and transferrin saturation had good predictive performance, whereas this was not the case for haemoglobin prediction, as all models were outperformed by the baseline model. ACKNOWLEDGMENTS The authors acknowledge the funding from the Slovenian Re- search Agency (ARRS), Grant (PR-10495) and Basic core funding P2-0209. The dataset was collected as a part of the study Clini- caltrials.gov registration number NCT03957057. REFERENCES [1] Nils Milman. 2011. Postpartum anemia i: definition, prevalence, causes, and consequences. Annals of hematology, 90, 11, 1247–1253. [2] Kathryn A. Lee and Mary Ellen Zaffke. 1999. Longitudinal changes in fa- Figure 3: Distribution of transferrin saturation in blood of tigue and energy during pregnancy and the postpartum period. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 28, 2, 183–191. patients six weeks after childbirth. [3] Kiyoshi Ando et al. 2006. Health-related quality of life among japanese women with iron-deficiency anemia. Quality of life research, 15, 10, 1559– 1563. Table 6: Results for the prediction of transferrin saturation. [4] Nils Milman. 2012. Postpartum anemia ii: prevention and treatment. Annals of hematology, 91, 2, 143–154. [5] Andreas Greinacher, Konstanze Fendrich, Ralf Brzenska, Volker Kiefel, and −2 Model MAE RMSE MAPE [10 ] Wolfgang Hoffmann. 2011. Implications of demographics on future blood supply: a population-based cross-sectional study. Transfusion, 51, 4, 702– KR 8.74 10.93 36.74 709. [6] Christian Breymann. 2005. Iron deficiency and anaemia in pregnancy: mod- LR 8.78 10.97 36.80 ern aspects of diagnosis and therapy. European Journal of Obstetrics & Gy- EN 8.82 11.14 38.45 necology and Reproductive Biology, 123, S3–S13. Baseline 8.88 11.12 39.16 [7] Lisa M. Bodnar, Anna Maria Siega-Riz, William C Miller, Mary E Cogswell, and Thad McDonald. 2002. Who should be screened for postpartum anemia? SVR 9.11 11.38 39.51 an evaluation of current recommendations. American journal of epidemiology, CB 9.11 11.31 38.81 156, 10, 903–912. BR 9.22 11.41 40.49 [8] Charles R. Harris, Jarrod K. Millman, Stefan J. van der Walt, Ralf Gommers, Pauli Virtanen, and David Caurnapeau. 2020. Array programming with GB 9.51 11.89 40.20 numpy. Nature, 585, 357–362. doi: https://doi.org/10.1038/s41586- 020- 2649- LGBM 9.55 12.10 39.58 2. [9] F. Pedregosa et al. 2011. Scikit-learn: machine learning in Python. Journal XGB 9.62 12.11 39.64 of Machine Learning Research, 12, 2825–2830. http://www.jmlr.org/papers/v olume12/pedregosa11a/pedregosa11a.pdf . [10] Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017. Lightgbm: a highly efficient gradient We see that the top three performing models outperform the boosting decision tree. In Proceedings of the 31st International Conference baseline, with the best model being the KR. The results of the on Neural Information Processing Systems (NIPS’17). Curran Associates Inc., models performance of predictions for separate medications only Long Beach, California, USA, 3149–3157. isbn: 9781510860964. [11] Tianqi Chen and Carlos Guestrin. 2016. XGBoost: a scalable tree boosting are shown in Table 7. Unlike Monofer and Tardyfer, the models system. In Proceedings of the 22nd ACM SIGKDD International Conference do not perform well in the case of Iroprem. on Knowledge Discovery and Data Mining (KDD ’16). ACM, San Francisco, California, USA, 785–794. isbn: 978-1-4503-4232-2. doi: 10.1145/2939672.29 5 DISCUSSION AND CONCLUSION 39785. [12] Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika We evaluated nine classic machine learning regression models for Dorogush, and Andrey Gulin. 2018. Catboost: unbiased boosting with cate- gorical features. In Proceedings of the 32nd International Conference on Neural the prediction of three key parameters associated with anaemia Information Processing Systems (NIPS’18). Curran Associates Inc., Montréal, collected from blood tests six weeks after childbirth: ferritin, Canada, 6639–6649. 599 Covid symptoms home questionnaire classification and outcome verification by patients Goran Jakimovski Dragana Nikolova Faculty of Electrical Engineering and Information Technology Faculty of Electrical Engineering and Information Technology University of “Ss. Cyril and Methodus” University of “Ss. Cyril and Methodus” Skopje, Macedonia Skopje, Macedonia goranj@feit.ukim.edu.mk nikolova.dragana98@gmail.com with Covid-19 data. They are using different approaches to get the best ABSTRACT results when combining ML and Covid. Furthermore, [4] is again using Testing for Covid, in a time of pandemic, can put a lot of overhead on CT scans and ML to classify patients as infectious or not, which would be useful to decrease infection spread amongst the population. the medical and testing facilities. Moreso, in a pandemic crisis, people become more hypochondriacs and get tested even if a slightest Much like in [1], authors in [5] are helping other authors with an symptom of Covid is detected. This leads to many people, infected and overview of the ML techniques. Additionally, they are offering data sets not infected, to gather at the medical facilities, thus increasing the to help with the further investigation. The research done in [1] and [5], coupled with the research in [6], gives authors the means, the possibility for not infected people to get Covid infection. Our knowledge, the data set and the information on how to proceed with the application registers patients and, by using a medical survey, research for covid and ML. The research in [6] evaluates all the data determines if the patient is supposed to get tested for Covid or even and the publishing process of papers regarding Covid and ML and how more severe measure are to be taken. Additionally, our application uses the publication process changes the initial paper submission. medical tests results from patients to determine the success rate of the Further analysis is done in [7] about covid detection and CT images prediction. The case study has shown that the application has 89% using a pre-trained data set that can help classify the new data set before success rate of classification. Using this application, only people with training and testing using deep learning and multi-layered convolution the right symptoms will be advised to get tested, thus lowering the algorithms. This way, the data set can be increased and overcome the overload placed on the medical facilities and minimizing the virus persisting problem of ML with not having enough data to perform the spread. training and testing. The overall analysis of all the research in ML and data set is concluded by the authors in [8], where they give a detailed analysis of the functions and usage of ML and Covid. KEYWORDS There is a lot of research of Machine Learning/Deep Learning analysis, classification, Covid, survey, symptoms, test cases techniques to detect Covid using medical images. Our approach is simpler and uses medical questionnaires and human input to improve the detection of Covid 19 in patients. The architecture of our Covid 1 Introduction Medical App system is described in Section 2, whereas the behavior and case scenarios are described in Section 3. Section 4 concludes the Although world-wide pandemics are not that often, yet Covid paper and gives information about further development. pandemic hit the world fast, with many patients dying and doctors not being able to understand the cause in time. The aftereffect of the pandemic has left many people with health issues with more and more 2 Architecture of the system people becoming hypochondriacs. Technology was and is still used to alleviate the hit from the virus and help prevent the spread of the corona The Covid Medial Application is designed to help patients and the virus and maintain the current lifestyle as much as possible. On the other health system by classifying patients into six categories. These side, technology was used to help fight against the virus and return life categories range from the patient not having Covid (or the least suspect to its original form. of a Covid infection), to an almost certain Covid infection (requires isolation and medical treatment). The users of the applications are A lot of research has been done on the Covid virus and Corona taking a short survey (questionnaire) about their wellbeing and outbreak, including image processing, machine learning and so on. In symptoms, and the result of the questionnaire is the classification of the [1], they give a summary of the different machine learning techniques user into one of categories [9]. The application accesses the survey from to predict and classify covid-19 cases. They are using mathematical an API that is standardized and provided by the InferMedica Medical models and machine learning to predict Covid-19 cases. The authors in Platform, implemented and approved by World Health Organization [2], have further used machine learning and image processing to (WHO). The API contains all sorts of Covid data that can be retrieved determine the cause of pneumonia in covid-19 infected patients. They and many surveys the users can take, our application utilizes only the are using X-rays and CT images to create a software to determine how API for classification of Covid, which is done based on symptoms and to classify patients based on pneumonia and Covid-19 images. patient’s wellbeing. The machine learning approach is also used in most papers but in Besides all the Covid recommendations and information that is [3], authors are trying to investigate the best possible options and weight displayed in the application, the users can take the survey and find out, distribution in the ML techniques to get the best results when working 600 based on their symptoms, in which category they belong. The categories with the diagnosis and recommendations. This information can also be are: easily translated and wrapped. • No risk – the patient is the least likely to have Covid Patients that might have higher risk of Covid infection (placed in • Self-monitoring – the patient should continue to monitor that category by the API) can isolate themselves in time to prevent the symptoms but is not likely to have Covid others to be infected. Furthermore, the entire pandemic made many • Call a doctor – there is an infection, but it is not Covid- patients hypochondriacs and suspect Covid symptoms even for a small related cough. Thus, by using this application, if they get classified in no • Quarantine – the patient is advised to quarantine himself Covid infection categories, uninfected patients can avoid going to the from the environment and perform Covid tests hospitals for unnecessary Covid tests, and reducing the possibility to get infected in the testing areas. • Isolation call – the person should isolate themselves from the environment with high probability for Covid infection On the figure below (Figure 2), we can see a part of the survey • Isolation ambulance – the person has high probability for interface and the questions that the users have to answer to be classified Covid infection and should call for ambulance since the in the categories. symptoms are severe. The architecture and the organization of the application is presented on Figure 1. Figure 2 Questions from the survey (multipart) The series of questions can vary from input fields for body temperature measured or blood pressure, to multiple choice questions and Yes/No questions. The requirements from the questionnaire are simple and easily understandable that every patient can answer even if with severe health issues. The interface is adjusted and simplified as to not impose any incorrect information that could lead to a faulty classification. On Figure 3 we can see a list of results that the patient received, as Figure 1 Organization of the application a result of the survey. From Figure 3, we can see that the information is presented in different color based on the severity of the classification, followed by a short information summary intended for the classification. The patient can take the questionnaire multiple On Figure 1 we can see that our application is a wrapper around times, and each result is marked and presented to the user with the date the API provided from InferMedica, which first and foremost, provides and time of the questionnaire taken and the result. a human readable survey that patients can take and classify their symptoms into a category. The questionnaire helps patients with symptoms of Covid to determine the best possible action to take, in case they are suspecting Covid infection. Users of the application access it via web link, where users can get Covid-related information, access their profile and take the questionnaire. The questionnaire taken from a patient is packed, formatted and sent to the API, the API returns the result, which is displayed back to the patient. As presented on Figure 1, we can see that the application uses two APIs from InferMedica. The first API is diagnosis endpoint, that we Figure 3 Result of the classification use to obtain the questions to form the questionnaire. These questions are predetermined, can easily be translated into any language, and be On the other hand, medical personnel also have access to these adapted if the questionnaire changes from the endpoint. The second classifications, but only to patients that they have been assigned to. API is the triage endpoint that is used to perform the diagnosis and Based on the outcome of the classification, the medical personnel can classification of the patient. Also, the result returns a short info status schedule an appointment for testing or send an ambulance to the that is presented to the patient with information about how to proceed appointed address. The panel of the medical personnel is similar to the 601 one of the patient’s, except it additionally displays the information of Our medical application allows users to take a Covid survey based the patient that took the survey and contact information. on their symptoms and be classified into categories of high to low Covid infection. Alongside with the classification, a short information is presented on how to proceed with their result and how to minimize 3 Evaluation of the system further infection on other patients. The survey, as stated before, is intended to keep patients with low risk of infection to visit Covid testing places in order to avoid getting infected. Also, by advising patients with Each medical classification system cannot guarantee a faultless low possibility of Covid infection to not get tested, reduces crowding classification method, so there is always a chance that the classification the medical facilities and Covid test centers, thus reducing overhead of might not be correct. If there are numerous of medical tests and the medical system. However, patients can still ignore the results from findings, a different doctor might give a different diagnosis and our application and get tested to make sure if they have Covid or not. classification of a patient’s condition. Even more so in our case, where we are using a questionnaire to classify a patient in a six different Covid The case study of the API and our application was conducted with categories, it gives a rough classification as a basic step of the diagnosis. 20 patients who already have been tested with Polymerase Chain The questionnaire, as stated before, is taken from Infermedica, which Reaction (PCR) test for Covid in the past. More than half of the patients was previously issued by the WHO, but it is not something that can be (15 of them) have been tested twice for Covid, thus the total number of used with absolute certainty and fully depended upon. That is why, in test cases is 35. The patients already had the diagnosis for Covid from this section of the paper, we are also making an evaluation of the results their PCR test before the survey was taken on our application. After of the questionnaire. which, we have compared the results from the survey with the results from the PCR tests of the patients. The results from the case study are presented on Figure 4. Figure 4 Results from the case study of our application with 35 tests On Figure 4 we can see the results from our application (shown with prediction and classification. If we consider the binary classification, blue bars) and the results from the PCR tests (shown with orange bars). the success rate of the API is increased to 89%. As we can see from the results, the PCR and the application bars are mostly the same. The deviation in the PCR and the application results 4 Conclusion are mostly in categories one, two and three. The most common error is when the API suggests category one, but the PCR shows category Our application tends to use a simplified system for online diagnosis three. This error is minimal since the first three categories are linked of Covid patients that uses questionnaire designed to give initial with low to no infection. The next frequent error is in the last two diagnosis of the patient. This initial diagnosis is used to give patients categories, when the API suggests category five, but the PCR suggests information as to whether they have Covid or not and to suggest testing category six and vice versa. If we put the results of the questionnaire and medical care, only if necessary, thus reducing the overhead on the in binary form (the patient has Covid or the patient doesn’t have testing places and the medical facilities from patients that are with low Covid), the first three categories will form the result that the patient risk or no infection at all. The case study in section III shows that the doesn’t have Covid, whereas the last three categories will form the questionnaire is accurate enough to give initial diagnosis and sufficient result that the patient has Covid. If the categories are binary, the error enough to determine if the patient has Covid or not with 89% accuracy. between the API and the PCR is close to zero. The minimal diversion is detected in the subcategories presented by the questionnaire. Also, For future work we propose testing the system with patients before the PCR gives information as to whether the patient has or hasn’t got they go to the hospital or testing facilities for Covid. The user can Covid, the subcategorizing is done based on hospitalization of the update the results of the API with the results from the medical/test patient and the recommendations received from their doctor. facilities. This can be done by result category, and the system can If we consider the six categories offered by the API, the overall success present the accuracy of the API result next to the result. Thus, users rate of the API, compared with the PCR tests is at 85% of accurate can get classified into the categories, but also receive accuracy information provided by users of the application that have been classified and afterwards tested. 602 [5] Chadaga, K., Prabhu, S., Vivekananda, B., Battling COVID-19 using machine learning: A review, Cogent Engineering, 8:1, 1958666, DOI: References 10.1080/23311916.2021.1958666 [6] Jemioło, P.; Storman, D.; Orzechowski, P. Artificial Intelligence for [1] Swapnarekha, H, Behera, S., Nayak, J., Naik, B., Role of intelligent COVID-19 Detection in Medical Imaging—Diagnostic Measures and computing in COVID-19 prognosis: A state-of-the-art review, Chaos, Wasting—A Systematic Umbrella Review. J. Clin. Med. 2022, 11, 2054. Solitons & Fractals, Volume 138, 2020, ISSN 0960-0779 https://doi.org/10.3390/ jcm11072054 [2] Bharati, S., Podder, P., Mondal, R. H, Prasath, S., Medical Imaging with [7] Mehboob, F., Rauf, A., Jiang, R. et al. Towards robust diagnosis of Deep Learning for COVID- 19 Diagnosis: A Comprehensive Review, COVID-19 using vision self-attention transformer. Sci Rep 12, 8922 arXiv:2107.09602 (2022). https://doi.org/10.1038/s41598-022-13039-x [3] Mohammed, M., Abdulkareem, K., Al-Waisy, A., Benchmarking [8] Swapnarekha, H., Behera,H., Nayak, J., Naik, B., Role of intelligent Methodology for Selection of Optimal COVID-19 Diagnostic Model computing in CнOVID-19 prognosis: A state-of-the-art review, Chaos, Based on Entropy and TOPSIS Methods, IEEE Access, May 2020, Solitons & Fractals,Volume 138,2020,ISSN 0960- 10.1109/ACCESS.2020.2995597 0779,https://doi.org/10.1016/j.chaos.2020.109947. [4] Subhalakshmi, R.T., Appavu, S, Sasikala, S., Deep learning based fusion [9] Infermedica Medical Platform, Covid-19 survey API, model for COVID-19 diagnosis and classification using computed https://developer.infermedica.com/docs/api tomography images, oncurrent Engineering: Research and Applications 2022, Vol. 30(1) 116–127 603 Piloting ICT Solutions for Integrated Care Mitja Luštrek Samo Drobne Sokratis G Papageorgiou Department of Intelligent Systems Faculty of Civil and Geodetic Neurology Department Jožef Stefan Institute Engineering Aiginition Hospital, National and Jožef Stefan International University of Ljubljana Kapodistrian Univ. of Athens Postgraduate School Ljubljana, Slovenia Athens, Greece Ljubljana, Slovenia samo.drobne@fgg.uni-lj.si sokpapa@med.uoa.gr mitja.lustrek@ijs.si Roberta Matković Bojan Blažica Efthalia Angelopoulou Teaching Institute Computer Systems Department Neurology Department for Public Health Jožef Stefan Institute Aiginition Hospital, National and of Split and Dalmatian County Ljubljana, Slovenia Kapodistrian Univ. of Athens Split, Croatia bojan.blazica@ijs.si Athens, Greece roberta.matkovic@nzjz-split.hr angelthal@med.uoa.gr Miodrag Miljkovic Pietro Hiram Guzzi Marketing Department Municipality of Miglierina Special hospital Merkur Miglierina, Italy Vrnjacka banja, Serbia sindaco@comunemiglierina.it miljkovicdzoni@gmail.com ABSTRACT retirement age, and social and technological innovations that can improve the care for the seniors and their quality of life. The SI4CARE project is aiming to develop a strategy and action The SI4CARE project [2] aims to create a transnational plans to improve health and social care in the Adriatic-Ionian ecosystem for social innovation in integrated care with a focus region. It started with surveying the state of affairs in the region, on ICT technology. It started with surveying the status quo of identifying needs and challenges, as well as best practices that health and social care in the Adriatic-Ionian region, identifying can answer them. Based on these, wishes for improvement were needs and challenges, as well as best practices that can answer formulated. The paper describes the methodology of this process them. It then formulated wishes and actions for improved health and the key findings. Some of the best practices are being piloted and social care, which will eventually result in a transnational to support the development and monitoring of the policy actions. strategy and national/regional action plans. In the paper, we describe nine pilots that involve pervasive health To gain a deeper insight into the benefits of the identified best technology and otherwise strongly leverage ICT to benefit senior practices and ways of implementing them, the project started 13 users. Most employ wearables and other sensing devices to pilots in seven countries. We describe the nine that involve monitor the users and provide health and care services, or provide pervasive health technology and otherwise strongly leverage ICT telehealth and care through web and mobile technology. to benefit senior users. Most employ wearables and other devices to monitor the users and provide health and care services, or KEYWORDS provide telehealth and care through web and mobile technology. Social innovation, integrated care, telehealth, telecare, transnational strategy, action plan 2 SI4CARE PROJECT: FROM STATUS QUO TO ACTION 1 INTRODUCTION The SI4CARE project used a systematic and evidence-based The population of Europe and the rest of the developed world is approach for devising a strategy and actions to improve rapidly aging. In the last 20 years, the old-age dependency ratio integrated care via social and technological innovation, with the of working-age population vs. seniors in Europe decreased from aim of presenting solid arguments to decision makers. 4 : 1 to 3 : 1, and it is projected to further decrease to 1.75 : 1 by 2050 [1]. This will result in a range of problems, including a lack 2.1 Status Quo of Health and Social Care of people who can support the seniors once they can no longer The first step was to survey the status quo (the state of affairs) in live independently. These problems will have to be tackled from health and social care in the Adriatic-Ionian region, comprising multiple angles: with demographic policies, increases in Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Montenegro, Permission to make digital or hard copies of part or all of this work for personal or Greece and Italy. Four key activities were done: classroom use is granted without fee provided that copies are not made or distributed  We surveyed the literature, such as statistical reports, 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 national and regional policy documents and legislation. be honored. For all other uses, contact the owner/author(s).  We conducted semi-structured interviews with high-level Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia stakeholders such as highly placed employees at relevant © 2022 Copyright held by the owner/author(s). 604 ministries, non-governmental organizations and educational include providing information and training to seniors about institutions. The interviews included 26 questions on the health(care), particularly dementia, and digital technology; healthcare system, financial and physical accessibility of promotion of social inclusion; and organizing provision of healthcare services, future challenges and other topics. 31 (health)care (e.g., via mobile medical units). stakeholders were interviewed in total. Qualitative analysis of the answers was performed, focusing on the main points 2.3 Wishes to Improve Care and Quality of Life raised among the participants. Based on the analysis of status quo (Section 2.1) and inspired by  We administered a questionnaire to various people employed the best practices (Section 2.2), the SI4CARE project formulated in health and social care services. The questionnaire included a number of wishes that – if fulfilled – would leverage social and 29 items on the use of healthcare services by seniors, their technological innovation to improve the care and quality of life accessibility, the ability to obtain information on healthcare, of seniors. These were developed for each of the involved and the status of seniors in the society and their social care. countries, and validated in a focus group involving stakeholders. A subset of these questions was asked specifically about Since the analysis of the status quo found a strong need for people with memory impairment or dementia. We received the introduction of new technologies, and many technology- responses from 222 health and social care staff. based best practices were identified, it is not surprising that  We administered the same questionnaire to seniors. We various initiatives aimed at increasing the use of telehealth and received responses from 619 people. telecare comprise the largest group of wishes. They had different Our finding was that in general, the provision of healthcare focus: rehabilitation (where the current availability is particularly services is moderately good, with a lack of human resources cited poor), cost-effectiveness (which is a prerequisite for institutional as a key problem. Rehabilitation was noted to be less available funding), non-pharmacological interventions (that tend to be than other services, and people with dementia face more neglected), applications that do not require institutional support problems than the general elderly population. A significant (which are typically inexpensive and non-pharmacological) … problem is that seniors are poorly informed about healthcare. Activities to improve digital skills of seniors were also wished Even though healthcare is mostly covered by insurance, many for, as well as better digital infrastructure. seniors face significant financial problems, mainly due to low Unlike best practices, most wishes were not technological. pensions. In part, this appears to be because, despite the This is perhaps because wishes are about goals, whereas insurance, they sometimes still need to resort to private services. technology in health and social care is often a means of achieving Waiting times are a common issue, which may explain the use of these goals. The non-technological wishes include increases in private services. Physical accessibility is also a major issue – the human resources (which were found to be a key reason for the seniors have significant difficulties using public transport. inadequacies of healthcare provision), improved overview of the Secondary healthcare for people living in rural areas was also state of care and solutions for improvement (essentially activities found to be difficult to access. similar to SI4CARE’s but put on a more sustainable basis), Seniors have a low digital literacy and find anything improvements in home care, training and better policies. involving the internet (e.g., booking an appointment) a major problem. High-level stakeholders feel that new technologies 2.4 Transnational Strategy and Action Plans have not been successfully integrated in the healthcare system, The preparation of the transnational strategy and and this is even more true for the questionnaire respondents. national/regional action plans – one for each country involved – Most stakeholders believe such technologies are important, is still in progress. The strategy is organized in five pillars: though, validating the objectives of the SI4CARE project.  Digital transitions are concerned with pervasive health technologies and other ICT-based innovations exemplified 2.2 Best Practices by the pilots presented in this paper. The SI4CARE project identified and documented 115 best  Digitalization process will support digital transitions by practices in social and technological innovation to improve the providing the required infrastructure and knowledge. care and quality of life of seniors, selected based on their  Economic and financial implications deal with appropriate effectiveness as demonstrated by experience. funding for healthcare and other aspects of long-term care. Since SI4CARE emphasizes the use of ICT technologies in  Governance and policies address sustainable and integrated care, most of the identified best practices are geographically appropriately distributed provision of care, technology-based. The largest group involve pervasive health ensuring its quality and properly trained staff. technology, such as wearables to monitor users, either to help  The SI4CARE community will ensure the sustainability of them manage their health or to provide functions such as fall the project via organizations that will exist after the end of detection. Some also use sensing integrated in fitness devices or the funding period. 3D cameras to support rehabilitation. There are also web and The national/regional action plans aim at implementing this mobile platforms that support various activities interesting to strategy in individual countries. Their main components are seniors (e.g., gardening, cognitive training), facilitate specific actions, which essentially fulfill the wishes discussed in communication and social inclusion. A few best practices are Section 2.3. These wishes are being validated by stakeholders in intended for hospitals and other care organizations (e.g., for events organized in each country, one of which is also taking management of health records). place at the Information Society 2022 multiconference. Some of the best practices – less relevant to this paper but Afterwards, the action plans will be presented to high-level otherwise just as important – are non-technological. Examples decision makers. 605 3 PILOTS OF ICT SOLUTIONS FOR south to north. In 2018, healthcare mobility in Calabria amounted INTEGRATED CARE to approx. € 310 million. This is particularly relevant for small towns and villages where people suffer from a lack of general 3.1 Mobile Application for Self-management of medicine and efficient public transportation to regional hubs. Heart Failure Due to some recent programs, many rural areas in Calabria have good internet connections. In this pilot, with the help of Heart failure is a common and debilitating disease among UCCP del Reventino (a team of physicians), we are evaluating seniors, and a leading cause of hospitalizations. It requires the use of tele-assistance and remote monitoring of chronic complex management difficult for many seniors. Healthcare patients (elderly people and people affected by dementia). institutions provide only periodic checkups and cardiac The developed services are particularly useful for patients rehabilitation, the latter not to all who would benefit. Resources who require a re-evaluation of an already known clinical picture, to provide more support are hard to come by, so a mobile people suffering from rare diseases, and frail people who require application to assist self-management is an attractive solution. constant contact with health facilities. Teleadvice also proved of The HeartMan application [3] provides a personalized great utility in the context of COVID-19. exercise program and nutrition advice, support for measurement of vital parameters, medication reminders, mindfulness exercises 3.4 Specialized Outpatient Clinic for Memory, intended to improve the patients’ mental health and wellbeing, Dementia and Parkinson's Disease and cognitive behavioral techniques to improve the adherence to the application’s advice. The first step of the pilot was to make Approximately 20% of the population above the age of 65 are the application easier to deploy and to remove physiological affected by mild cognitive impairment or dementia. As the status monitoring as input for its decisions, as this is a barrier from the quo analysis indicated, these people have limited access to usability and regulatory perspective. The user experience was specialized healthcare. This is more pronounced in remote areas. also improved. The ongoing second step is a feasibility study Greece has many small and isolated islands with a high with 20 patients using the application and 10 controls. percentage of elderly inhabitants and understaffed health centers. The lesson learned so far is that designing an application for The Aeginition Hospital of the National and Kapodistrian heart-failure patients is difficult due to the complex topic and University of Athens developed an outpatient clinic pilot through poor digital and health literacy of this group. Our solution was to the National Telemedicine Network, in collaboration with the guide less advanced users by simple automatic prompts, and not 2nd Regional Healthcare Administration of Piraeus and the require them to do much on their own initiative. Aegean Islands. Through this clinic, patients with cognitive or movement disorders living in remote Aegean islands are 3.2 ICT Solution for Monitoring the Health of examined by a specialized healthcare team (neurologist, Patients after Returning Home psychiatrist and neuropsychologist) through video-conferencing. Based on the questionnaires from 58 telemedicine visits, all Special Hospital Merkur is a secondary health institution in stakeholders are highly satisfied with this telemedicine service, Serbia specializing in diabetes. Upon discharge, patients often mentioning improved care, better health, and convenience, return to bad habits, and diabetes complications occur. In reduced transportation and cost. The low number of cases addition, they face problems when they need to see a doctor. compared to the available capacity points to the need to better The main aim of the pilot was to investigate the integration of disseminate the information about the availability of modern communication technology in diabetes treatment to telemedicine in the area by involving local health professionals facilitate better coordination between stakeholders. The patients and other telemedicine services in Greece. were trained to use the SmartCare mobile application, and to input the necessary data (insulin, sugar, mass, blood pressure, 3.5 Tele-exercise for the Elderly and Patients temperature, etc.). Merkur's medical team had insight into the with Cognitive Disorders/Dementia patient's condition and intervened as needed. In addition, patients were trained to contact doctors for consultations from home. Physical activity is a well-established non-pharmaceutical The combined effect of the involvement of patients in their intervention for health improvement in the elderly. It improves health condition, and the remote intervention of doctors, proved mobility, fitness, and cognitive function, prevents falls, improves to reduce the risk of diabetes complications. The pilot functionality and quality of life as well as increases socialization. demonstrated the feasibility of remote treatment in Serbia, which The Aeginition Hospital of the National and Kapodistrian can also lead to significant financial savings. It should be University of Athens in collaboration with the Medical School of repeated on a larger sample on a national level to provide a basis Athens developed a tele-exercise pilot to provide specialized for the introduction of telemedicine in the health system. online physical activity programs for the elderly. Small groups of about 10 individuals receive aerobic and resistance training 3.3 ICT to Enable Accessibility to Health with a frequency of 2–5 times/week and duration of 40 min per Systems by the Elderly intervention, guided in real-time via video-conference by specialized healthcare professionals. The elderly involved were In the Italian healthcare system, regional governments are trained to use the tablets though which they are participating. responsible for ensuring the delivery of a health benefits package All participants report high satisfaction rates and improved through a network of health management organizations. There is functionality in everyday life. Key lessons learned are that tele- a remarkable difference among regions, with northern regions exercise is feasible and effective non-pharmacological treatment providing better services, resulting in migration of patients from that enhances social interaction, and that effective collaboration 606 between healthcare providers is necessary. The elderly face assessment service interprets movement and activity data from difficulties in the use of new technologies and training is needed. devices in the user’s home. The aim is to automatically detect abnormal behaviors that may indicate an emerging disease. 3.6 Individualized Training Based on The lesson learned so far is that there is a need for a more Biomechanical Measurements systematic coordination of the call center with public health care The importance of physical activity was already discussed in the units, doctors, social care workers and emergency units. previous pilot description. The status quo analysis in Slovenia showed that the availability of physical exercising and 3.9 Accessibility to Integrated Long-term Care rehabilitation services is not adequate. Resorting to the private In the pilot project we analyzed both spatial accessibility and sector may result in lower quality of services as they might be accessibility of information. Slovenia is rural country. Older provided by people without the necessary knowledge and skills. people in rural Slovenia face poor access to public services and We prepared a pilot in which training was based on initial especially to health facilities. In terms of spatial accessibility, we screening of the participants by an orthopedist and experienced identified the locations of buildings where seniors live alone. In coaches, followed by biomechanical measurements of lower 2021, there were 42,344 seniors living alone in houses (27,136 extremities. Isometric measurement of peak torque and aged 65–79 and 15,208 aged 80 and older) in Slovenia. tensiomyography were used along with a body composition There are a number of elderly care services advertised online, measurement. 24 participants performed training 2 times per but the offer is scattered and searching for such information is week for 3 months under two conditions: half of the participants time-consuming. To avoid these obstacles, we set up a web exercised in a gym, while the other half online. In the in-person platform where different providers (formal and informal) are scenario, participants were divided in small groups. The focus presented in one place. We included all formal providers in was proper posture and exercise execution. Only after absorbing Slovenia in the database. We enabled self-registration of service proper technique, the training increased intensity. providers and spatial representation of providers via the web. Both conditions were warmly accepted by participants, with We highlighted areas with poor accessibility to health and the in-person one slightly preferred. Working in small groups not social care services, and will present them to local decision- only enabled individual training, but also group cohesion, makers and caregivers to improve integrated long-term care and resulting in socialization after exercising in the nearby café. transport for them. We will also present them our web app. 3.7 Nursing by Monitoring 4 CONCLUSION The pilot carried out in Split, Croatia, was motivated by the well- established issue of inadequate resources to provide quality care The paper presented the SI4Care project and its methodology to to seniors who cannot live independently. bring social innovation to integrated care. The focus was on the The pilot used monitoring technology that requires minimal presentation of the pilots that address the identified needs and interactions with senior users, since they are not familiar with wishes in the region. The fact that most, nine out of thirteen, of digital technology. 10 medically non-certified wristbands, the piloting activities within the SI4Care project involve some equipped with LoRaWAN radio, ensure data delivery to large sort of pervasive health technology testifies to the importance of distances without using mobile phones as a gateway. The such technologies also for integrated care. Preliminary results wristbands enable 10-minute acquisition of heart rate, GPS from most pilots show benefits for stakeholders and good location, steps, calories, and wrist temperature, as well as having acceptance. However, digital literacy is a significant barrier, and alarms for low heart rate and falls, and a help button. The data is in some cases also infrastructure, organizational readiness and received by a system called IoT Wallet, which allows future legislation. Pervasive technology clearly cannot be introduced in expansion since it supports adding add more wristbands. isolation, which is why our strategy consists of five pillars, only LoRaWAN technology turned out to provide broad coverage one of which is concerned with pervasive technology. with a relatively low power consumption. ACKNOWLEDGMENTS 3.8 Access to Public Social Services by This paper has been produced with the financial assistance of the Telemedical Monitoring (Click for Life) European Union. The content of the paper is the sole Seniors represent a high percentage of the population of Region responsibility of project partners and can under no circumstances of Central Macedonia (RCM) in Greece (22% are over 65), with be regarded as reflecting the position of the European Union a significant proportion of them living alone (approx. 100,000). and/or ADRION programme authorities. The SI4CARE project They face difficulties in access to public social services, is supported by the Interreg ADRION Programme funded under especially in high-density urban places and remote rural areas. the European Regional Development Fund and IPA II fund. The RCM regional authority launched the pilot project 'Click for Life', offering telemedicine/homecare assistance to seniors REFERENCES with a low income living alone. Approx. 3000 users participate [1] Eurostat, 2021. Eurostat Regional Yearbook (2021 edition). DOI: 10.2785/894358 so far. They are provided: (1) 24-hour monitoring via devices [2] SI4CARE – Social Innovation for integrated health CARE of ageing with fall detection and a panic button. The panic button enables population in ADRION Regions. https://si4care.adrioninterreg.eu/ communication with a call center 24 hours/day. (2) Medical [3] M. Luštrek, M. Bohanec, C. Cavero Barca, M. C. Ciancarelli, E. Clays et al., 2021. A personal health system for self-management of congestive history is accessible to relatives and health professionals, and the heart failure (HeartMan): Development, technical evaluation, and proof- users can receive notifications from the relatives. (3) Behavioral of-concept randomized controlled trial. JMIR Med. Inform. 9, 3, e24501. DOI: 10.2196/24501 607 Network Anomaly Detection using Federated Learning for the Internet of Things Ana Cholakoska Bojan Jakimovski Bjarne Pfitzner Ss. Cyril and Methodius University Ss. Cyril and Methodius University Hasso Plattner Institute in Skopje in Skopje Digital Health — Connected Faculty of Electrical Engineering Faculty of Electrical Engineering Healthcare and Information Technologies and Information Technologies Potsdam, Germany Skopje, North Macedonia Skopje, North Macedonia bjarne.pfitzner@hpi.de acholak@feit.ukim.edu.mk kti1562018@feit.ukim.edu.mk Hristijan Gjoreski Bert Arnrich Marija Kalendar Ss. Cyril and Methodius University Hasso Plattner Institute Ss. Cyril and Methodius University in Skopje Digital Health — Connected in Skopje Faculty of Electrical Engineering Healthcare Faculty of Electrical Engineering and Information Technologies Potsdam, Germany and Information Technologies Skopje, North Macedonia bert.arnrich@hpi.de Skopje, North Macedonia hristijang@feit.ukim.edu.mk marijaka@feit.ukim.edu.mk Danijela Efnusheva Ss. Cyril and Methodius University in Skopje Faculty of Electrical Engineering and Information Technologies Skopje, North Macedonia danijela@feit.ukim.edu.mk ABSTRACT 1 INTRODUCTION The widespread use of IoT devices has contributed greatly to In the last decade, a significant increase in the usage of Inter- the continuous digitisation and modernisation of areas such as net of Things (IoT) devices has been observed. The ability to healthcare, facility management, transportation, and household. connect various kinds of devices from different manufacturers These devices allow for real-time mobile sensing, use input and to a network wirelessly and share data has proven beneficial then simplify and automate everyday tasks. However, like all to nearly every domain where this technology is involved, in- other devices connected to a network, IoT devices are also subject cluding household, industry, infrastructure, transportation, and to anomalous behaviour primarily due to security vulnerabilities healthcare[3]. Additionally, the actions that end users can take or malfunction. Apart from this, they have limited resources are increasing everyday and vary from changing ambient param- and can hardly cope with such anomalies and attacks. Therefore, eters of a home or car setting easily and on-the-go to remotely early detection of anomalies is of great importance for the proper and securely controlling a manufacturing process inside a smart functioning of the network and the protection of users’ personal factory setting. Implementing these devices into an ambient as- data above all. In this paper, deep learning and federated learning sisted living (AAL) setting has proven to be beneficial both for the algorithms are applied in order to detect anomalies in IoT network patients and for the medical staff, as it can improve monitoring traffic. The results obtained show that all the models achieve and medical assistance (if needed), as well as medication dose high accuracy, with the FL models providing slight worse results adjustment[7]. compared to the DL models. However, with the increase in the However, the diversity of IoT devices, accompanied by wire- amount of user data, the model based on federated learning is less networking and a slow standardisation process, have led to expected to have better results over time. many issues regarding the privacy and security of data and also the processes based on that data. The occurrence of various cyber KEYWORDS attacks on networks composed of IoT devices, but also on indi- federated learning; deep learning; malware; internet of things; vidual IoT devices performing specific tasks, is becoming more anomaly detection common [8]. By disabling, reconfiguring or reprogramming such devices, attackers can manipulate the network, obtain private data illegally and maybe even induce a life-threatening situation, especially in the e-health domain. Therefore, it is significantly 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 important to detect potential attacks and anomalies that occur distributed for profit or commercial advantage and that copies bear this notice and in an IoT setting. the full citation on the first page. Copyrights for third-party components of this This paper examines the detection of anomalies in IoT network work must be honored. For all other uses, contact the owner/author(s). traffic by using deep learning and federated learning algorithms. Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). The remainder of this paper is structured as follows. Section 608 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Cholakoska et al. 2 gives an overview of the approaches tackling IoT network for tackling anomaly detection in smart buildings. The results anomaly detection using deep and federated learning algorithms. showed twice as fast convergence during training, compared to Section 3 describes the used dataset and gives an insight into the centralised LSTM. the importance of the features. The experiments done in this research and the discussion of the results obtained are presented 3 DATASET AND EXPLORATORY DATA in Section 4, while Section 5 gives a brief summary and provides ANALYSIS further research directions. For the purpose of this research we used the publicly available dataset N-BaIoT [11]. It is a dataset created by a group of re- 2 RELATED WORK searchers from the University of California, Irvine, School of Information and Computer Sciences in the USA. The dataset ad- One of the most popular approaches when tackling network dresses the lack of public botnet datasets, especially for the IoT anomaly detection is the usage of network intrusion detection domain. It is composed of real-time network traffic data gathered systems (NIDS). By examining network data flow patterns (signa- from nine commercial IoT devices, including a baby monitor, secu- tures), the NIDS can track inconsistencies (also called anomalies) rity cameras, a webcam, doorbells, and a thermostat, which have and resolve them in a timely manner. However, directly analysing been infected by the most common families of botnet attacks: the behaviour of the IoT devices has proven to be more beneficial Mirai and Bashlite [1]. in detecting newer and unknown types of attacks, in spite of the overall lower detection accuracy and higher computational cost [6]. Usingmachinelearning(ML)techniqueshashadabigimpact on the development of NIDS and malware anomaly detection sys- tems in general. Lin et al. [9] propose a combination of Support Vector Machines (SVMs) and Artificial Fish Swarm algorithms for IoT botnet detection. A combination [5] using different ML algorithms, also including an SVM has been done to evaluate the accuracy in detecting Mirai DDoS attacks. The authors in [16] used Convolutional Neural Networks (CNN) with binary visu- alisation to provide fast zero-day malware detection. However, some of the datasets used in these research papers provide only network traffic flow from conventional networks and have little to do with the attacks which target IoT networks. A further issue is that using traditional ML techniques increases the security risk, as data has to be moved away from the network and the Figure 1: N-BaIoT dataset distribution by class data source to a powerful system performing the ML training. Federated learning (FL) has emerged as a new decentralised The N-BaIoT dataset consists of 7,062,606 entries with 115 way of training models on privately held datasets that can or different features, which are further divided into 10 attack cat- should not be shared for security and privacy reasons. The train- egories: gafgyt_combo, gafgyt_junk, gafgyt_scan, gafgyt_tcp, ing process consists of a central server and several clients, where gafgyt_udp, mirai_ack, mirai_scan, mirai_syn, mirai_udp, mi- the former facilitates the training and the latter possess the pri- rai_udpplain and one benign category, which contains the nor- vate data. In each round of federated training, the server randomly mal traffic flow of the observed devices. As it can be seen from selects a subset of clients who receive the current model param- Figure 1, which shows the distribution of the dataset used in eters. Then, local training is performed by each of the clients, the upcoming experiments, only a portion (509,149 entries) is keeping the local data on-site. The updated model parameters considered for the model training in both DL and FL experiments. are then sent back to the server, where the global server model For the DL experiments, the dataset is further divided into a is updated. Opposed to centralised ML or classical decentralised train and test partition including 80% and 20% of the data, while techniques, FL can work with both independent and identically maintaining the distribution intact. As for the FL experiments, distributed (IID) and non-IID datasets. [10] the data is divided into 50 IID datasets which include a train and Several approaches have been using this decentralised tech- test subsets. They represent the 50 clients which will take part in nique in order to detect anomalies in IoT networks. The DIoT the FL process. approach [2] uses federated learning to aggregate profiles of IoT network behaviour. It was evaluated in real-world conditions and Table 1: Most important dataset features reported no false alarms. Saharkhizan et al. [14] used a recurrent neural network with ensemble learning to detect cyberattacks Number Feature on IoT devices. The evaluation of the model was performed on a Modbus dataset of network traffic. Some of the approaches even 1 H L0.01_mean used a combination of FL and a distributed ledger (blockchain) 2 Ml_dir_L0.01_mean [12, 17] in order to detect anomalies in networks. In [13], the fed- 3 Ml_dir_L0.01_variance erated deep learning model created for zero-day botnet attacks on 4 H_L0.01_variance IoT devices outperformed traditional decentralised approaches, 5 H_L0.1_mean as well as both localised deep learning (DL) and distributed DL methods. In [15], a novel privacy-by-design FL model using a After preprocessing the data, an exploratory analysis was stacked long short-time memory (LSTM) model is introduced done in order to obtain the features which have the greatest 609 Network Anomaly Detection using Federated Learning for the Internet of Things Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Figure 2: DL model using the five layer NN - accuracy Figure 4: FL model using the five layer NN - accuracy Figure 5: FL model using the three layer NN - accuracy Figure 3: DL model using the three layer NN - accuracy server. In the FL experiments 35 rounds were performed, which corresponds to approximately 35 epochs in the DL experiments. influence. The mutual dependence between the features and As previously mentioned, two DL models, the first one using the class was determined with the help of Mutual Information a NN with multiple layers and the second one using a simple NN Gain. From Table 1, it can be noticed that the five features with were trained and tested. From Figures 2 and 3 we can notice that the greatest importance are H L0.01_mean, Ml_dir_L0.01_mean, the accuracy between the two models is very similar - the first Ml_dir_L0.01_variance, H_L0.01_variance and H_L0.1_mean. model obtained an accuracy of 90.75% on the test data, while the second model obtained an accuracy of 90.18%. Furthermore, if 4 EXPERIMENTS AND DISCUSSION the confusion matrices of both DL models are analysed, it can be This paper compares two DL and two FL models for network noted that both models make the same mistake - predicting class anomaly detection, which are able to distinguish anomalous be- 4 (gafgyt_scan) as class 5 (gafgyt_tcp). haviour or a deviation from the normal traffic flow of IoT devices. When it comes to the results obtained from the FL process after After performing the training, all models were evaluated in order 35 rounds it can be seen that the first model obtained an accuracy to see their accuracy in detecting anomalies. In the first exper- of 88% (Figure 4). As for the second simplified model, the accuracy iment, a feed-forward neural network with 5 layers, an input is 86% (Figure 5). This means that even though a simpler NN was layer, 3 hidden layers and an output layer was used. In the sec- used, the second model actually performed similarly in terms of ond experiment, a simple feed-forward neural network with one FL. We can also observe the minor differences in accuracy ( 1- hidden layer was used. In both cases, the output layer has 11 5%) between the DL and FL models, which means that although neurons, which represent all the classes in the dataset. the DL models performed slightly better, the FL models can also Both models have the same hyperparameters. We used the accurately predict anomalies. Adam optimiser with a learning rate of 0.001, which works well From Figures 6 and 7 we can analyse the SHAP (SHapley Ad- for many use cases and models. Since the model performs a multi- ditive exPlanations) force plot, which shows the contribution class prediction task, we minimised the categorical cross entropy of each feature in making a prediction. We can see that the fea- loss during training. The DL experiments were performed us- tures 69, 25, 75, 87, 56 and 101 (HH_jit_L3_mean, H_L0.1_mean, ing the TensorFlow framework and the FL experiments were HH_jit_L0.1_mean, HpHp_L3_weight, HH_L0._covariance and performed using the Flower [4] framework and TensorFlow Fed- HpHp_L0.1_weight) have the greatest influence in making the erated, applying the FedAvg aggregation strategy [10] on the prediction. The features 69, 25 and 75 have a positive impact on 610 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Cholakoska et al. Figure 6: SHAP force plot for DL model using the five layer NN. Figure 7: SHAP force plot for DL model using the three layer NN. decision-making, i.e. prediction, while the features 87, 56 and 101 [6] Satish Kumar, Sunanda Gupta, and Sakshi Arora. 2021. Research Trends in affect negatively on the performance. When we compare Figures Network-Based Intrusion Detection Systems: A Review. IEEE Access 9 (2021), 6 & 7 and Table 1, we can see that the most important features 157761–157779. https://doi.org/10.1109/ACCESS.2021.3129775 [7] Isabel Laranjo, Joaquim Macedo, and Alexandre Santos. 2012. Internet of are different. This is because the SHAP method deals with the Things for Medication Control: Service Implementation and Testing. Elsevier model and its output, while Mutual Information Gain deals with Procedia Technology 5 (10 2012), 777–786. https://doi.org/10.1016/j.protcy. 2012.09.086 the preprocessed data. [8] In Lee. 2020. Internet of Things (IoT) Cybersecurity: Literature Review and IoT Cyber Risk Management. Future Internet 12 (09 2020), 157. https://doi. org/10.3390/fi12090157 5 CONCLUSION AND FUTURE WORK [9] Kuan-Cheng Lin, Sih-Yang Chen, and Jason Hung. 2014. Botnet Detection This paper compares two models of DL and FL for accurate anom- Using Support Vector Machines with Artificial Fish Swarm Algorithm. Journal of Applied Mathematics 2014 (04 2014), 1–9. https://doi.org/10.1155/2014/ aly detection purposes in IoT networks. The FL model distributes 986428 the learning process to several clients, thus preserving data pri- [10] H. Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang. 2017. Learning Differentially Private Language Models Without Losing Accuracy. vacy and security. Both models achieve high accuracy, with the CoRR abs/1710.06963 (2017). arXiv:1710.06963 http://arxiv.org/abs/1710.06963 FL models providing similar results to the DL models. [11] Yair Meidan, Michael Bohadana, Yael Mathov, Yisroel Mirsky, Asaf Shabtai, Future work will include implementing some security mech- Dominik Breitenbacher, and Yuval Elovici. 2018. N-BaIoT—Network-Based Detection of IoT Botnet Attacks Using Deep Autoencoders. IEEE Pervasive anisms to the FL models and evaluating the trade-off between Computing 17, 3 (2018), 12–22. https://doi.org/10.1109/MPRV.2018.03367731 privacy and accuracy. Also, these models can be further tested [12] Yisroel Mirsky, Tomer Golomb, and Yuval Elovici. 2020. Lightweight collabo- and improved by being provided with new substantial datasets rative anomaly detection for the IoT using blockchain. J. Parallel and Distrib. Comput. 145 (06 2020). https://doi.org/10.1016/j.jpdc.2020.06.008 which may combine similar categories of attacks and/or include [13] Segun I. Popoola, Ruth Ande, Bamidele Adebisi, Guan Gui, Mohammad Ham- novel attacks on IoT networks. New federated learning algo- moudeh, and Olamide Jogunola. 2022. Federated Deep Learning for Zero-Day Botnet Attack Detection in IoT-Edge Devices. IEEE Internet of Things Journal rithms can also be tested and evaluated on the same and new 9, 5 (2022), 3930–3944. https://doi.org/10.1109/JIOT.2021.3100755 datasets, which can lead to a novel federated learning algorithm [14] Mahdis Saharkhizan, Amin Azmoodeh, Ali Dehghantanha, Kim-Kwang Ray- for anomaly detection purposes. mond Choo, and Reza M. Parizi. 2020. An Ensemble of Deep Recurrent Neural Networks for Detecting IoT Cyber Attacks Using Network Traffic. IEEE In- ternet of Things Journal 7, 9 (2020), 8852–8859. https://doi.org/10.1109/JIOT. 2020.2996425 ACKNOWLEDGMENTS [15] Raed Abdel Sater and A. Ben Hamza. 2021. A Federated Learning Approach The authors would like to thank Daniel Denkovski and Valentin to Anomaly Detection in Smart Buildings. ACM Trans. Internet Things 2, 4, Article 28 (aug 2021), 23 pages. https://doi.org/10.1145/3467981 Rakovic for the useful discussions on the research topic. 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Ob tem smo spoznali možnosti uporabe domačih pisarne in sodelovanja na spletnih izvedbah konferenc. Vsemu navkljub smo prepričani, da ostaja konferenca, na kateri pride do osebnega stika in pogovora, nenadomestljiva. Zato smo pričeli s pripravo naslednje konference MATCOS, 4. po vrsti. Pri organizaciji in izvedbi smo imeli srečo, da so člani tako organizacijskega kot programskega odbora večinoma sprejeli tudi letošnje povabilo ter izdatno prispevali k organizaciji in izvedbi konference. Vabljeno predavanje je običajno eden osrednjih dogodkov konference. Letos bo to predavanje Györgyja Turána z University of Illinois at Chicago (USA) z naslovom »Interpretability of deep-learned error-correcting codes«. Predavanje nam bo posredovalo uvid v vpliv sodobne UI na načrtovanje klasičnih kod za popravljanje napak. Poleg vabljenega predavanja bo na konferenci predstavljen še izbor člankov iz širokega področja računalništva in informatike vključno s primeri uporabe. Tradicionalno prihaja na konferenco večina prispevkov in avtorjev iz Madžarske in Slovenije. Vendar je naš napor letos obrodil sad, saj so se jim na naše veliko zadovoljstvo pridružili avtorji še iz sedmih drugih držav in predstavili svoje delo. Člani tako organizacijskega kot programskega odbora so v zadnjih nekaj mesecih opravili odlično delo. Zato vsem, ki so pomagali pri organizaciji in izvedbi konference MATCOS-22, iskrena zahvala. Zaključujemo z željo, da boste te dni uživali v Kopru in da vzpostavite nove profesionalne stike na konferenci MATCOS-22. V imenu organizatorjev Andrej Brodnik in Gábor Galambos sopredsedujoča 615 FOREWORD In 2019 – when we organized the 3rd MATCOS conference – we strongly believed that we established a new tradition here in Koper. Then, the next few years we had to concentrate to win over the covid. We got acquainted with the possibilities of home offices and the organization of online conferences became current. But we are sure that a conference with personal interviews and discussions are irreplaceable. So, this year we started to organize the next MATCOS conference, the 4th one. Fortunately, the former members of the Organizing Committee and the Program Committee accepted our invitation and took part actively in organization. The invited talk is a central point while you organize a conference. This year György Turán from the University of Illinois at Chicago (USA) will present a talk on “Interpretability of deep-learned error-correcting codes”, and so, we can take a look the influence of modern AI research to the design of classical error-correcting processes. Selecting among the submitted papers we sorted out those ones that came from a wide range of the computer science and its applications. Following the “traditions” most of the participants come from Hungary and Slovenia, but it is really a great pleasure to see that our efforts have been successful: the authors represent new research results from 7 countries. The members of PC and OC did an excellent job during the last few months. Thanks to everybody who helped to organise the MATCOS-22. We hope you will enjoy these days in Koper and you can establish new professional contacts during the MATCOS-22 conference. On behalf of the organisers Andrej Brodnik and Gábor Galambos co-chairs 616 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Andrej Brodnik, co-chair Gábor Galambos, co-chair Neil Hurley Gabriel Istrate Ivana Kolingerova Miklós Krész Ujjwal Maulik Silvano Martello Benedek Nagy Rolf Niedermeier Ion Petre Ulrich Pferschy Gerhard Reinelt Giovanni Rinaldi Borut Žalik 617 618 A Neural Network Based Classification Algorithm for Asthma Using Capnography [Extended Abstract] József Békési Gábor Galambos András Kelemen Institute of Informatics Juhász Gyula Faculty of Juhász Gyula Faculty of University of Szeged Education, Department of Education, Department of Árpád tér 2. Applied Informatics Applied Informatics H-6720 Szeged, Hungary University of Szeged University of Szeged bekesi@inf.u-szeged.hu Boldogasszony sgt. 6. Boldogasszony sgt. 6. H-6725 Szeged, Hungary H-6725 Szeged, Hungary GalambosGabor@szte.hu kelemen.andras.felix@szte.hu Imre Papp József Tolnai Juhász Gyula Faculty of Albert Szent-Györgyi Medical Education, Department of School, Department of Applied Informatics Medical Physics and University of Szeged Informatics Boldogasszony sgt. 6. University of Szeged H-6725 Szeged, Hungary Korányi fasor 9. pap.imre@szte.hu H-6720 Szeged, Hungary tolnai.jozsef@med.u- szeged.hu ABSTRACT ENCES—Capnography This article presents a neural network-based method to help physicians diagnose and monitor asthma and other chronic General Terms respiratory diseases. The method is based on capnography, Applications using measurement data from a specially developed hand- held device. Keywords After proper preparation, various parameters are calculated Decision support, Neural networks, Capnography on the capnographic curve from which healthcare profession- als can conclude the condition of the patient’s respiratory system. 1. INTRODUCTION Capnography is a non-invasive method for the numerical Another purpose of using the calculated parameters is to and graphical analysis of exhaled CO2 concentration. Time- serve as a learning base for an artificial intelligence applica- based capnography is part of routine daily patient monitor- tion that can be used in the decision support of physicians. ing during mechanical ventilation and anesthesia. For spon- The shape of the capnogram obtained from the gas sample taneously breathing patients, the method has the advantage exhaled by the patient and thus the parameters calculated that it does not require the patient to carry out any special from it are different for healthy people and those with res- breathing maneuvers, the measurement is easy to perform, piratory diseases. and therefore requires minimal cooperation. It also holds the potential for the diagnosis of obstructive airway disease, Categories and Subject Descriptors as bronchospasm severity can be quantitatively assessed [4, 6]. The feasibility of non-invasive examinations is essential H.4 [Information Systems Applications]: Decision Support; in pediatrics, so it also opens up new areas of application for J.3 [Computer Applications]: LIFE AND MEDICAL SCI- capnography [7, 9, 10]. Although the analysis of capnogram shape parameters is not yet a standard part of patient mon- itoring, it appears promising in the monitoring of chronic respiratory diseases, as it provides useful information on the pathophysiological processes of pulmonary ventilation, such as airway patency and lung recoil tendency. In capnographic studies, the carbon dioxide content of ex- haled air can be considered as a function of time or plotted against the exhaled gas volume. In the former case, we are 619 talking about time-based, while in the latter case we are creates the opportunity to apply learning algorithms and au- talking about volumetric capnography. tomatically determine the condition of the patients studied. As a first step, faulty respiratory cycles were filtered out In the first part of the article, we examine the formal prop- based on physiological rules that were supported by mea- erties of time-based capnograms. Possible parameters de- surement techniques.The parameter calculator smoothed the scribing the shape of the curve are presented. In the second points of the raw curve using the moving average method. In part we introduce a neural network based method that uses this case, each point was replaced by an average calculated these parameters to help physicians in diagnosing patients. from a specified number of adjacent points. For the 100Hz sampling frequency used for recording, we found the 9-point 2. THE CAPNOGRAMS AND THEIR PARAM- moving average to be the most suitable. Then, for each point of the smoothed curve, we calculated the first-order ETERS derivatives using the standard differential quotient. Since The capnogram curve plots the partial pressure of the CO2 the curve containing the first derivatives can also be slightly content of the exhaled gas against time or volume. The par- noisy, we performed the previous smoothing algorithm for tial pressure of a given gas in a gas mixture is the pressure this as well. Then, following the same method, we calculated that a gas in question would create alone if it filled the avail- the curve containing the second derivative and its smoothed able space alone. The partial pressure of CO2 is denoted by version. Finally, using the smoothed derivative 2 curve, the P CO2. starting point of Phase 2 (local maximum) and the end point of Phase 3, i.e. the end of exhalation (local minimum) can The capnogram consists of an exhalation segment and an be determined. It should be noted that the starting point of inhalation segment. In this study we focused only on the the exhalation cannot be precisely determined only from the shape indices of the exhalation section. The three phases of time capnogram curve. However, before the start of Phase the exhalation segment (Phases 1-3) contain different slopes, 2, we can find the point where the curve still takes approxi- angles and other parameters which are described in many mately a value of 0, and then this point can be considered as articles and textbooks (e.g. [2, 3, 8]). the starting point of the fitting algorithm described below. We then fit a function to the exhalation sections obtained as previously described using the method introduced by Tus- man et al. in [11]. The beginning of Phase 2 and the end of Phase 3 have already been determined as described above, and its post-fitting correction is not necessary. However, af- ter fitting, the first, second, and third derivatives must be re-determined (now on the fitted curve). The end point of Phase 2 (the starting point of Phase 3) is obtained from the local maximum of the calculated third derivative. 2.1.1 The slopes of Phases 2 and 3 (S2, S3) Figure 1: General form of time-based capnograms To determine the inflection point of Phase 2, we use the first- order derivative values, which mathematically represent the slope of the line drawn at a given point on the curve. The slope at the inflection point will be the largest. The slope of Phase 2 (S2) is the maximum slope that can be read at this inflection point [11]. The slope of Phase 3 (S3) is the slope of the line fitted to the middle third of Phase 3, which is a simplified but not significantly different modification of the method used by Tusman et al [11]. Figure 2: Phases of a capnogram with End-tidal CO2(ET CO2) 2.1 The calculated parameters The various morphological parameters are calculated using mathematical methods, which are presented in this subsec- tion. The resulting capnographic indices - in the knowledge of the patients’ condition - provide an opportunity to assess the characteristics of healthy and chronic respiratory pa- Figure 3: The slopes of time-based capnograms tients (see [12] for more details). We aim to calculate these parameters as accurately and objectively as possible. This 2.1.2 End-tidal CO2 (ET CO2) 620 The carbon dioxide concentration increases throughout Phase • Class of the patient’s age at the time of examina- 3, so it normally peaks at the end of the phase. This is the tion. (The patient’s age was divided into 10-year-long final exhalation CO2 concentration (ET CO2, P ET CO2), classes. For example: 13 years old, 17 years old -> which is equal to the carbon dioxide partial pressure read at class: 1, 33 years old -> class: 3, 60 years old, 62 the end of Phase 3. years old -> class: 6, etc. This was necessary because without classification only a few measurements would 2.1.3 The normalized slopes of Phases 2 and 3 (Sn2, belong to some ages, which would impair the effective- ness of learning.) Sn3) The normalized slopes of Phase 2 (Sn2) and Phase 3 (Sn3) • Class of the patient’s body weight at the time of exam- are obtained by dividing the slopes of the second and third ination. (The patient’s body weight was divided into phases (S2, S3) by the value of ET CO classes of 10 kilograms, in the same way as for age.) 2. 2.1.4 Sn3/Sn2 We used one label for teaching, which was a manual medical The quotient of the Sn3 and Sn2 values. diagnosis of the patient for the test. (One test could include several measurements. One measurement could only belong 2.1.5 D2min and D2max to one test. One test could only have one diagnosis.) We The maximum and minimum of the second derivative, the only used measurements with a ”healthy” or ”asthmatic” di- rate of change of the start and end points of Phase 2 (the agnosis. We omitted from teaching the load measurements lower and upper curves). and the measurements marked as incorrect. The method was implemented in Java and relied on the 2.1.6 The α angle (Q) Deeplearning4j library [1]. The training of the neural net- The angle enclosed by the slopes of Phases 2 and 3. work and the diagnosis prediction with the trained neural network ran on the following configuration: Intel Core i7 2.1.7 The area ratio (AR) 10700K CPU, 32GB DDR4 RAM, 256GB SSD, 2TB HDD, The area ratio in the section between the inflection point Nvidia GeForce 8500 GT video card. and the beginning of Phase 3 is the quotient of the area under the curve and the area of the entire rectangle. It is The neural network had 3 hidden layers, each with 50 neu- practically the shape of the transition from Phase 2 to Phase rons. For each hidden layer, the activation function was the 3. TANH function. The activation function of the output layer was the SIGMOID function. We gave 6000 epochs for teach- ing, but according to the log files, no significant learning took 2.1.8 Squared difference (R2SUM) place after the 652nd epoch. The training was performed on The sum of the squares of the differences between the points a record of 3141 healthy and 16670 asthmatic breathing cy- of the raw, original curve and the fitted one. As previously cles, which lasted 2169 seconds on the configuration given described, the original capnogram curve contains higher fre- above. quency noises, which may have physiological reasons. There- fore, these sums of squares are used to examine the differ- 4. RESULTS ences in the curves of the patients in each group. Since the training was done per respiratory cycle (the pa- rameters are also calculated separately for each cycle), the 2.1.9 Respiratory rates (RR) diagnosis prediction with the trained neural network is also In the absence of flow data, the exact length of respiratory done per respiratory cycle. For each measurement, we cal- cycles cannot be determined from the time capnogram alone. culated how many cycles of the measurement were ”healthy” Thus, the length of the given respiratory cycle can be esti- and how many cycles were ”asthmatic”. (The prediction is mated from the combined length of Phases 2 and 3. Exam- not performed for cycles marked as incorrect.) If the num- ining the measurements in parallel with the flow measure- ber of healthy predictions is lower than the number of asth- ment, we found that the combined length of Phases 2 and 3 matic predictions, then the entire measurement is considered is about 65 percent of the respiratory cycle. Currently, we asthmatic. Otherwise, the entire measurement is considered use this ratio to estimate respiratory length, from which we healthy. The number of measurements used in the predic- calculate the actual respiratory rate. tion was 648. Considering the ”asthmatic” diagnosis as pos- itive and the ”healthy” diagnosis as negative we found the 3. THE INPUT DATA AND THE STRUCTURE followings: OF THE NETWORK • True positive (TP): 517 (79.78%) The data used for teaching the network were as follows: • True negative (TN): 107 (16.51%) • False positive (FP): 23 (3.55%) • All time-based parameters calculated from mainstream measurements: S2T, S3T, ET CO • False negative (FN): 1 (0.15%) 2, Sn2, Sn3, Sn3/Sn2, D2min, D2max, Q, AR, R2SUM, RR (Sep- arate records for each breathing cycle). TP: The number of measurements for which the manual diagnosis of the test is ”asthmatic” and the diagnosis ob- • Gender of the patient. tained with the neural network is also ”asthmatic”. TN: 621 The number of measurements for which the manual diagno- conditions), COVID, etc. Distinguishing these diseases sis of the test is ”healthy” and the diagnosis obtained with with the help of a trained neural network. the neural network is also ”healthy”. FP: The number of measurements for which the manual diagnosis of the test is 6. ACKNOWLEDGMENTS ”healthy”, but the diagnosis obtained with the neural net- This study was carried out in cooperation with PROFIT- work is ”asthmatic”. FN: The number of measurements for EXPERT Ltd., University of Szeged, Bay Zoltán Nonprofit which the manual diagnosis of the test is ”asthmatic”, but Ltd. for Applied Research, Optin Ltd. in the framework the diagnosis obtained with the neural network is ”healthy”. of the EU-funded Hungarian project ”CAPNO - research on the application possibilities of capnography and develop- The metrics calculated from these are: ment of an instrument for the diagnosis of asthma and other respiratory diseases (GINOP-2.2.1-15-2017-00046).” • Accuracy: 0.96, • Precision: 0.96, 7. REFERENCES [1] Deeplearning4j Suite Overview. • Recall: 1.00, https://deeplearning4j.konduit.ai/. [Accessed • F1 Score: 0.98. 16-Jul-2022]. [2] K. Bhavani-Shankar, A. Y. Kumar, H. S. L. Moseley, Here we used the usual metrics of classifiers, based on the and R. Ahyee-Hallsworth. Terminology and the following formulas [5]: Accuracy: (TP + TN) / (TP + FP current limitations of time capnography: A brief + TN + FN) Precision: TP / (TP + FP) Recall: TP / (TP review. Journal of Clinical Monitoring, 11(3):175–182, + FN) F1 score: 2* precision * recall / (precision + recall) May 1995. [3] K. Bhavani-Shankar and J. H. Philip. Defining All of the above metrics must fall within the interval [0.0, segments and phases of a time capnogram. Anesthesia 1.0]. The closer the value is to 1.0, the better the result. & Analgesia, 91(4):973–977, Oct. 2000. The total running time of the diagnosis prediction was 240 [4] J. B. Chambers, P. J. Kiff, W. N. Gardner, seconds for 1361 measurements, so the prediction takes an G. Jackson, and C. Bass. Value of measuring end tidal average of 0.1763 seconds per measurement. Comments: partial pressure of carbon dioxide as an adjunct to treadmill exercise testing. BMJ, 296(6632):1281–1285, 1. The evaluation is somewhat distorted by the fact that we may 1988. have fewer healthy subjects than asthmatics. [5] D. Chicco and G. Jurman. The advantages of the matthews correlation coefficient (MCC) over f1 score 2. It is similarly distorted by the fact that we used all the and accuracy in binary classification evaluation. BMC measurements of all asthmatic and healthy tests from the Genomics, 21(1), jan 2020. database for teaching. This is due to the limited number [6] C. Chopin, P. Fesard, J. Mangalaboyi, P. Lestavel, of measurements. In the case of several measurements, we M. C. Chambrin, F. Fourrier, and A. Rime. Use of could use only a small part of the measurements during capnography in diagnosis of pulmonary embolism teaching, and test the neural network on the larger part. during acute respiratory failure of chronic obstructive That way we would get more objective test results. pulmonary disease. Critical Care Medicine, 18(4):353–357, apr 1990. 5. CONCLUSIONS [7] N. Eipe and D. R. Doherty. A review of pediatric In this research we developed a neural network based ap- capnography. Journal of Clinical Monitoring and plication that uses capnography measurements to help the Computing, 24(4):261–268, jul 2010. diagnosis of asthma. Possible future works are the follow- [8] J. S. Gravenstein, M. B. Jaffe, N. Gravenstein, and ings: D. A. Paulus, editors. Capnography. Cambridge University Press, Mar. 2011. 1. Training the neural network with the raw measure- [9] B. D. Guthrie, M. D. Adler, and E. C. Powell. ment data as well, not only with the calculated pa- End-tidal carbon dioxide measurements in children rameters. This is expected to require more hardware with acute asthma. Academic Emergency Medicine, resources and time. An advantage may be that the 14(12):1135–1140, dec 2007. neural network can also learn useful information that [10] S. Kunkov, V. Pinedo, E. J. Silver, and E. F. Crain. is lost during the parameter calculation. Predicting the need for hospitalization in acute 2. Training the neural network with the volumetric pa- childhood asthma using end-tidal capnography. rameters or together with volumetric and time-based Pediatric Emergency Care, 21(9):574–577, sep 2005. parameters. The disadvantage here may be that there [11] G. Tusman, A. Scandurra, S. H. Böhm, are no volumetric parameters for purely time-based F. Suarez-Sipmann, and F. Clara. Model fitting of measurements without flow data. volumetric capnograms improves calculations of airway dead space and slope of phase III. Journal of Clinical 3. Teaching the neural network for the different severities Monitoring and Computing, 23(4):197–206, June 2009. of asthma, and using the trained neural network to [12] B. You, R. Peslin, C. Duvivier, V. D. Vu, and distinguish between them. J. Grilliat. Expiratory capnography in asthma:. 4. Teaching the neural network for other diseases, e.g. European Respiratory Journal, 7(2):318–323, Feb. COPD (and its sub-conditions), ACOS (and its sub- 1994. 622 Online Bin Covering with Exact Advice∗ Andrej Brodnik Bengt J. Nilsson Gordana Vujovic University of Ljubljana Malmö University University of Ljubljana Slovenia Sweden Slovenia andrej.brodnik@upr.si bengt.nilsson.TS@mau.se gogili.vujovic@gmail.com ABSTRACT the computational model. Boyar et al. [4] look at bin cov- We show a 2/3-competitive strategy for the bin covering ering using extra advice provided by an oracle through an problem using O(b + log n) advice, where b is the number of advice tape that the strategy can read. If the input sequence bits used to encode a rational value and n is the length of consists of n items, they show that with o(log log n) bits of the input sequence. advice, no strategy can have better competitive ratio than 1/2. They also provide a strategy with O(log log n) bits of Categories and Subject Descriptors advice having competitive ratio 8/15 and then show that a 500 [Theory of computation]: Online algorithms linear number of bits of advice is necessary to achieve com- 1. INTRODUCTION petitive ratio greater than 15/16. In the bin covering problem, we are given a set of items of We show a 2/3-competitive strategy for the one-dimensional different sizes in the range ]0, 1] and the goal is to find a bin covering problem using O(b + log n) advice, where b is maximum number of covered bins where a bin is covered if the number of bits used to encode a rational value in the the sizes of items placed in it is at least 1. It has been shown input sequence and n is the length of the input sequence. that is NP-hard [1]. The covering problem has applications 2. PRELIMINARIES in various situations in business and in industry, from pack- The online bin covering problem we consider is, given an ing snack pieces into boxes so that each box contains at least input sequence σ = (v its defined net weight, to such complex problems as redistri- 1, v2, . . .), of rational values vi ∈ [0, 1], find the maximum number of unit sized bins that can be bution tasks/items to a maximum number of factories/bins, covered online with items from the input sequence σ. The all working at or beyond the minimal feasible level. The bin covering problem is a dual version of the bin packing problem is, as mentioned, maximizing the number of cov- problem. ered bins, and is NP-hard [9]. The bin covering problem was studied in-depth in Assmann’s Ph.D. thesis [2]. In the We define the load of a bin B to be online version, items are delivered successively (one-by-one) X and each item has to be packed, either in an existing bin or a ld(B) def = v. (1) new bin, before the next item arrives. The quality of online v∈B strategies is measured by their competitive ratio, the mini- We can similarly define the load of a sequence σ to be mum ratio between the quality of the strategy’s solution and ld(σ) def = P v. that of an optimal one. The first known online strategy that v∈σ has been proposed for the problem is Dual Next Fit (DNF), A covering is a partitioning of the items into bins B1, B2, . . . analogous to Next Fit for the bin packing problem. A com- such that for each bin Bj petitive ratio of DNF is 1/2 proved by Assmann et al. [1]. ld(B A few years later, Csirik and Totik [8] prove that no online j ) ≥ 1 (2) algorithm can achieve a competitive ratio better than 1/2. and our objective is to find the maximum number of bins Further lower bounds ar given by Balogh et al. [3]. Thus, the that satisfy Inequality (2). In contrast to the bin packing only way to improve on the competitive ratio is to change problem, a strategy can open any number of bins at any ∗ time. However, only those that are filled to a load of at This work is sponsored in part by the Slovenian Research least 1 are counted in the solution. Agency (research program P2-0359 and research projects J1- 2481, J2-2504, and N2-0171). We measure the quality of an online maximization strategy by its competitive ratio, the maximum bound R such that A(σ) ≥ R · OPT(σ) − C, (3) for every possible input sequence σ, where A(σ) is the solu- tion produced by the strategy A on σ, OPT(σ) is a solution on σ for which |OPT(σ)| is minimal, and C is some constant. Of particular interest is the Dual Next Fit strategy (DNF), where DNF maintains one active bin B, and packs the items into B until it is covered. It then opens a new empty bin as 623 the active bin and continues the process. Assmann et al. [1] If the rational value lies in the interval [0, 1], then me ≤ md prove that DNF has a competitive ratio of 1/2 and Csirik and the encoding can be made using O(log md) bits. and Totik [8] prove that no online algorithm can achieve a We will base our strategy on DH competitive ratio better than 1/2. k with added advice to improve on the competitive ratio, as do Boyar et al. [4]. If we know some further structure of the input sequence, we 3. AN EXACT ADVICE STRATEGY FOR BIN can do slightly better as is shown in the next lemma that we will make extensive use of in the sequel. COVERING Each item v corresponds to a rational value 0 < v < 1, since Lemma 1. The online strategy DNF for the bin cover- any v above or equal to 1 will cover a bin and the optimum ing problem on an input sequence σα where the items have solution can be assumed to place v alone in a bin to cover weights bounded by α < 1 has cost it. Also, values of size 0 could be placed in the first covered 1 1 bin without loss of generality. DNF(σα) > . 1 + α OPT(σα) − 1 + α Fix an integer k ≥ 2. We will subdivide the set of items into k subsets, such that 1/t ≤ v < 1/(t − 1) for each integer Proof. Assume that DNF opens m + 1 bins when access- 2 ≤ t ≤ k, the t-items, and items v < 1/k, the small items. ing the sequence σα, m of which are covered. Since every Consider a fixed optimal covering OPT(σ) for the input item has weight at most α, it means that each of the m cov- sequence σ. We can partition the solution OPT(σ) into ered bins are filled at most to a total weight of 1 + α. A groups, Gt , where the index t1t2 · · · tj, with 2 ≤ t1 ≤ bin not obeying this limit would have been covered already 1 t2 ···tj t2 ≤ · · · ≤ tj ≤ k, denotes that each bin in group Gt before 1 t2 ···tj DNF places the last item in it, a contradiction. Thus contains one t1-item, one t2-item, etc, multiplicity denoting the total load of the sequence σ is the number of times each item type occurs in the bin in ad- (1 + α)m + 1 > ld(σ dition to the small items needed to fill it. We say that a bin α) ≥ ld(σα) ≥ OPT(σα) , in group Gt is easy, if P 1/t ≥ 1 and we 1 t2 ···tj t∈{t1,t2,...,tj } whereby |DNF(σα)| = m > |OPT(σα)|/(1 + α) − 1/(1 + α) can assume without loss of generality that easy bins contain as claimed. no small items. Furthermore, we assume that if the bins in Gt are easy, then any bin group Gt is empty, Another strategy of interest is Dual Harmonic ( 1 t2 ···tj 1 t2 ···tj tj+1 DHk), where if t1t2 · · · tj is a subsequence of t1t2 · · · tj+1, as the tj+1-item the strategy subdivides the items by sizes into k groups, in a bin in Gt can be moved to other bins while we 1 t2 ···tj tj+1 ]0, 1/k[, [1/k, 1/(k − 1)[, . . . , [1/3, 1/2[, [1/2, 1[, still maintain coverage in the bin. We also say that a bin in Gt is a gap bin, if P 1/(t − 1) < 1, as 1 t2 ···tj t∈{t1,t2,...,tj } and packs items in each group, maintaining k groups, ac- each of these bins must contain small items to the amount of cording to DNF. Evidently, DHk is at best 1/2-competitive more than 1−P 1/(t−1) to be covered. Lastly, t∈{t1,t2,...,tj } using the same argument as in Csirik and Totik [8]. we denote the group of bins that are only covered by small In certain situations, the complete lack of information about items by GS. future input is too restrictive. In a sense, the online strat- As an example, G22 are those bins that each contain two 2- egy plays a game against an all-powerful adversary who can items (bins in G22 are easy), G2 are those bins that each con- construct the input sequence in the worst possible manner. tain one 2-item and some small items, and G3 are those bins To alleviate the adversary’s advantage, we consider the fol- that each contain one 3-item and some small items (bins in lowing advice-on-tape model [6]. An oracle has knowledge G3 are gap bins since they require small items to the amount about both the strategy and the full input sequence from of more than 1/2 to be covered). the adversary, it writes information on an advice tape of un- bounded length. The strategy can read bits from the advice The size of the optimal solution is given by tape at any time, before or while the requests are released by X the adversary. The advice complexity is the number of bits |OPT(σ)| = |Gt | + |G 1 t2 ···tj S |, (4) read from the advice tape by the strategy. Since the length ∀t1t2···tj of the advice bit string is not explicitly given, the oracle is for all valid index combinations t unable to encode information into the length of the string, 1t2 · · · tj . thereby requiring some mechanism to infer how many bits We modify the Dual Harmonic strategy to operate on advice of advice the strategy should read at each step. This can be and describe this strategy, denoted DHak, dependent on the done with a self-delimiting encoding that extends the length parameter k, the number of item types used to partition the of the bit string only by an additive lower order term [5]. items into. The superscript a indicates that the strategy admits advice. Let x A bit string s is encoded as e(s) = u(s) ◦ b(s) ◦ s (◦ denotes 1, . . . , xn, n = |σ|, be an ordering of the items in σ, such that x concatenation), where b(s) is a binary encoding of the length i ≥ xi+1, for 1 ≤ i ≤ |σ|. The oracle provides the strategy with an integer m and the value of the string s and u(s) consists of b(s) ones followed by a x single zero, thus indicating how many bits the strategy needs m through a self-delimiting encoding. to read in order to obtain the length of the string s. The The strategy DHak initially reads the parameters m and xm encoding has length at most e(s) = |s| + 2⌈log(|s| + 1)⌉ + 1. and opens m bins that we call critical bins and that will We henceforth assume that all advice information is encoded each be covered with one of the m largest items of the input in this way. An integer m can thus be encoded exactly using sequence σ together with small items. Initially, each criti- O(log m) bits and a rational value me/md, where me and md cal bin is assumed to have a virtual load of xm. When an are integers can be encoded using O(log me + log md) bits. item of size ≥ xm is placed in a critical bin, its virtual load 624 is increased to the actual value of the item. The strategy these groups is guaranteed to have small items to the amount further opens a t-bin for every item type t ∈ {2, . . . , k}, and of at least 1/2, 2/3, 1/6, and 1/3, respectively. Thus, for a small bin for the small items. As the next item v of the each of those groups we have S3 ≥ |G3|/2, S4 ≥ 2|G4|/3, input sequence arrives, it is handled as follows: S34 ≥ |G34|/6, and S44 ≥ |G44|/3. 1. if xm ≤ v, place v in the next critical bin that does not For each group of non-easy bins G2, . . . , G444, let It (m) ⊆ 1 ···t4 yet contain a large item and update the virtual load of {1, . . . , m} be the set of indices i such that the last small el- the critical bin, ement (of weight zi) that was placed in critical bin Ci was 2. if 1/k ≤ v < x placed by the optimal solution in a bin from bin group Gt . m is a t-item, place v in the correspond- 1 ···t4 ing t-bin using DNF. If the bin becomes covered, close Easy bins are assumed, without loss of generality, to not it and open a new t-bin, contain any small items. Also, let IS(m) = 1, . . . , m \ S I (m) be the set of remaining indices. t t1···t4 3. if v < 1/k is small, place v in the next critical bin that 1 ···t4 6∈Easy The possible values of m range between 0 ≤ m ≤ m+ = does not contain small items up to a virtual load of at (|G least 1 and update the virtual load of this critical bin. 2| − |I2(m+)|)/2, where m+ is the largest integer such that 2m+ + |I If all critical bins are filled up to a virtual load of 1, 2(m+)| ≤ |G2|, since the strategy needs to guarantee that it can cover all the critical bins. place v in the small bin using DNF. If the small bin becomes covered, close it and open a new small bin. The oracle reveals m = m+ = (|G2| − |I2(m+)|)/2 and Lemma 2. Assume that the strategy DHa xm = x 4 has access to m+ , the mth largest item in the input sequence σ, so the exact values of m and x our strategy constructs m critical bins, (T2 − m)/2 2-bins, m, then it has competitive ratio T 2 173 3/3 3-bins, T4/4 4-bins, and some bins corresponding to the amount of unused small items, giving us DHa 4 (σ) ≥ 3 OPT(σ) − 60 for serving any sequence σ of size n. T2 − m T3 T4 4 Proof. Note that the number of t-items, for t = 2, 3, DHa 4 (σ) > m + + + + SS 2 3 4 5 and 4, in the instance is m !! X 4 T + S y − 2 = |G2| + 2|G22| + |G23 | + |G24| + |G233 | + |G234 | + 2 + S3 + S4 + S34 + S44 − i + zi 5 i=1 + |G244|, (5)     T m T2 T3 T4 4 X 4 X 3 = |G3| + |G23| + 2|G33 | + |G34| + 2|G233 | + |G234 | + ≥ + + + + SS − zi + S3 − zi 2 2 3 4 5 5 + 3|G333| + 2|G334| + |G344| + 2|G3344|, +|G3444|, (6) i∈IS (m) i∈I3(m)       T4 = |G4| + |G24| + |G34| + 2|G44| + |G234| + 2|G244| + 4 X 4 X 4 X + S z  + S z  + S z  + |G 4 − i 34 − i 44 − i 334| + 2|G344 | + 3|G444 | + 2|G3344 | + 3|G3444 | + 5 5 5 i∈I4(m) i∈I34(m) i∈I44(m) + 4|G4444|. (7)   4 m X X 163 For each non-easy bin group G + S (1 − w z  − 2, . . . , G444 (there are eleven of 2 − m) − i 5 60 them), let S i=1 i∈I t denote the weight of the small items that 2 (m) 1 ···t4 the optimum solution packs in the bins of group G | {z } t . In 1 ···t4 ≥0 addition, we denote by SS = P ld(B) the total load of   B∈GS the small items covering the bins in G m T T T 2 X S . ≥ + 2 + 3 + 4 + SS − zi 2 2 3 4 3 i∈IS (m) We consider first some arbitrary set of covered bins G, where     each bin only contains small items. Assume that these bins 2 X 5 X + S z  + S z  have a total load of S = P ld(B) ≥ |G| and that the 3 − i 4 − i 3 8 B∈G i∈I i∈I input sequence restricted to these small items is σ 3 (m) 4 (m) S . From     Lemma 1 we have that 1 X 1 X 163 + S z  + S z  − 4 4 4 4 34 − i 44 − i 2 2 60 i∈I i∈I DNF(σS ) > S − ≥ (8) 34 (m) 44 (m) 5 5 5 G − 5 m T2 T3 T4 2SS |IS(m)| 2S3 |I3(m)| We can analyze the competitive ratio of the critical bins by ≥ + + + + − + − 2 2 3 4 3 6 3 6 first considering a decreasing ordering of the bins B1, . . . , B|G2| 5S4 5|I4(m)| S34 |I34(m)| S44 |I44(m)| 163 in G2 by the weight of their 2-item, w + − + − + − − i. We let ui = ld(Bi) − 8 32 2 8 2 8 60 wi be the weight of the small items in Bi, whereby S2 ≥ m T2 T3 T4 2S m |I2(m)| |I3(m)| |G S 2| − m · 1 − wm for arbitrary choice of m ≤ |G2| since ≥ + + + + − + + 2 2 3 4 3 6 6 6 Bm+1, . . . , B|G2|, each contains at least 1 − wm amount of |I |I |I 2S |I small items; see Figure 1. The critical bins, C 4(m)| 34(m)| 44(m)| 3 3(m)| i, 1 ≤ i ≤ m, + + + + − 6 6 6 3 6 each contains one 2-item of weight ai, a small item of weight 5S 5|I S |I S |I 163 z 4 4(m)| 34 34(m)| 44 44(m)| i that was the last small item placed in Ci by our strategy, + − + − + − − and small items to the weight of y 8 32 2 8 2 8 60 i = ld(Ci) − ai − zi. Again, by construction, y m T2 T3 T4 |I2(m)| 2|GS | |G3| 5|G4| i ≤ 1 − wm for each 1 ≤ i ≤ m. > + + + + + + + 3 2 3 4 6 3 3 12 Consider next the gap bins in the optimal solution. These |G34| |G44| 163 are the bins in groups G + + − 3, G4, G34, and G44. Each bin in 12 6 60 625 z2 z u1 u2 z m 1 um um+1 u y y |G2| y 2 m 1 . . . . . . . . . w1 w2 wm wm+1 w a |G 1 a2 am 2| B1 B2 Bm Bm+1 B C |G 1 C2 Cm 2| Figure 1: The critical bins and their relationship to the G2-bins in the optimal covering. In the G2-bins, blue are 2-items and light green are the small items. In the critical bins, red represents the last small items in the bin, dark green are the remaining small items, grey items are the 2-items, and dark grey represents the overlap between the virtual and actual load of the 2-item. 2|G 2|G 2|G 2|G 2|G 2|G 2|G = 2| + 3| + 4| + 33| + 34| + 44| + S | consists of only 2-items and small items. Any critical bin- 3 3 3 3 3 3 3 based strategy must solve this instance and does so, even if 3|G 3|G 5|G 5|G 11|G + 24| + 444 | + 23 | + 344 | + 334 | + |G the adversary provides all the small items first and the 2- 22| 4 4 6 6 12 items last, by choosing m = ⌊|G2|/3⌋, since the index set is 13|G 13|G 7|G + |G 234 | 3444 | 233 | I 244| + |G333 | + |G4444 | + + + 2(m) = {1, . . . , m}, for all m, to guarantee that all critical 12 12 6 bins are covered, thus opening m critical bins, and packing 7|G 173 2 173 + 3344 | − ≥ |OPT(σ)| − the remaining 2-items in pairs to cover ⌊(|G2| − m)/2⌋ bins. 6 60 3 60 The strategy covers bins, by applying Equalities (5)–(7) in the second to last |G 2| − m |G2| |G2| − ⌊|G2|/3⌋ step, while using that each z m + = + i < 1/4, that SS ≥ P z i∈I i S (m) 2 3 2 and St ≥ P z , 1 ···t4 i∈I i, for each bin group Gt t (m) 1 ···t4 1 ···t4 |G2| |G2| 1 2 1 that critical bin C ≤ + + ≤ (9) i can be covered by a large item of size OPT(σ) + 3 3 3 3 3 at least wm plus the small items from a bin among the last bins B bins, proving that our analysis in Lemma 2 is asymptotically m+1, . . . , B|G2| in G2 and one extra small item from a non-easy bin in the optimal solution; see Figure 1, and that tight. m = |IS(m)| + P |I (m)|, for any m. The com- t t 1 ···t4 1 ···t4 4. REFERENCES petitive ratio is the smallest coefficient of any of the terms corresponding to bin groups, since an adversary can ensure [1] Susan Fera Assmann, David S. Johnson, that the groups with larger coefficient contain no bins. This Daniel J. Kleitman, and Joseph Y-T. Leung. On a dual gives a competitive ratio of 2/3 ≈ 0.6666 . . .. version of the one-dimensional bin packing problem. Journal of Algorithms, 5(4):502–525, 1984. [2] Susan Fera Assmann. Problems in discrete applied For completeness sake we mention that using the same proof mathematics. PhD thesis, Massachusetts Institute of technique it is possible to show that |DHa Technology, 1983. 2 (σ)| ≥ 3|OPT(σ)|/5− 19/15, where 3/5 = 0.6 and |DHa3(σ)| ≥ 9|OPT(σ)|/14 − [3] János Balogh, Leah Epstein, and Asaf Levin. Lower 173/84, where 9/14 ≈ 0.64285 . . ., if these strategies are bounds for online bin covering-type problems. Journal given the exact values for m and xm. of Scheduling, 22(4):487–497, 2019. [4] Joan Boyar, Lene M. Favrholdt, Shahin Kamali, and The two advice values m ≤ n and xm can be represented by Kim S. Larsen. Online bin covering with advice. O(log n) bits and O(b) bits respectively, where b is the num- Algorithmica, 83(3):795–821, 2021. ber of bits required to represent the integer denominator of [5] Joan Boyar, Shahin Kamali, Kim S. Larsen, Alejandro the rational value xm, since xm < 1. We have the following López-Ortiz. Online bin packing with advice. immediate theorem. Algorithmica, 74(1):507–527, 2016. [6] Hans-Joachim Böckenhauer, Dennis Komm, Rastislav Theorem 1. The strategy DHa Královič, Richard Královič, Tobias Mömke. On the 4 receives O(b + log n) bits of advice and has competitive ratio advice complexity of online problems Proc. 20th ISAAC, LNCS 5878, pages 331–340, 2009. 2 173 [7] Edward G. Coffman Jr., Joseph Y-T. Leung, and DHa 4 (σ) ≥ 3 OPT(σ) − 60 D.W. Ting. Bin packing: Maximizing the number of for serving any sequence σ of size n, where b is the number pieces packed. Acta Informatica, 9(3):263–271, 1978. of bits required to represent any rational value in σ. [8] János Csirik and Vilmos Totik. Online algorithms for a dual version of bin packing. Discrete Applied Mathematics, 21(2):163–167, 1988. One could venture to think that strategy DHak, for k > 4, would give improved competitive ratio, or even that extend- [9] Michael R. Garey and David S. Johnson. Computers ing the strategy with more sets of critical bins could improve and intractability, volume 174. Freeman San it further. However, this is not possible, since an adversary Francisco, 1979. can simply provide an instance where all bin groups except G2 in an optimal solution are empty. Thus, the instance 626 Subsets without arithmetic subsequences: computational experiments and unsatisfiable cores Uroš Čibej Ervin Gy ˝ori University of Ljubljana Alfréd Rényi Institute of Mathematics Faculty of Computer and Information Science Hungarian Academy of Sciences 1000 Ljubljana, Slovenia H-1053 Budapest, Reáltanoda u. 13-15. uros.cibej@fri.uni-lj.si gyori@renyi.hu ABSTRACT particular problem, but from our experience, we established A reduction to satisfiability of a combinatorial problem of that it takes a huge effort to construct a competitive solver minimal saturated subset without arithmetic subsequences which could outperform a state-of-the-art SAT solver. So is given in this paper. We conduct an empirical evaluation instead of putting the effort into a custom-made solver, we and present previously unknown optimal solutions for cer- construct a reduction to SAT and explore where are the tain instances of the problem. The results also show where limits of this approach. the limits for computing the optimal solutions are. Finally, we present a new possibility for solving such combinatorial The paper is structured as follows. The next section gives problems, namely the unsatisfiable cores of the SAT expres- a short definition of the combinatorial problem and the re- sions, which could give new insights to mathematicians and duction of this problem to SAT. Furthermore, we show what possibly new methods for solving the problem computation- the reduced expressions look like for the instances that we ally. are interested in. Section 3. describes the computational re- sults, namely what are the optimal solutions for our problem Categories and Subject Descriptors and what are the times required to obtain them. This will give us some insight into what are the feasible sizes that can G.2.2 [Mathematics of Computing]: Discrete Mathematics— be solved with any kind of solver. Section 4. describes an combinatorics interesting concept that can be obtained with SAT solvers and could be a new approach to solving this problem, either Keywords theoretically or empirically. satisfiability, solvers, modelling 2. PROBLEM DEFINITION AND REDUC- 1. INTRODUCTION TION TO SAT The problem of satisfiability has been at the center of com- 2.1 Problem definition puter science for more than half a century. It has been Definition 1 (Arithmetic triple). A set {a, b, c} (assuming widely used to show some of the most important results in a < b < c) is an arithmetic triple if b − a = c − b. computational complexity and it is used as a showcase prob- lem of a hard computational problem. But on the other hand, there has been a huge interest in developing better The set of all arithmetic triples of a set A will be denoted and better algorithms that can solve impressively large in- as stances. The main driving force of this development is the annual SAT competition [5], spawning a huge research field arith(A) = {{a, b, c} ⊆ A|{a, b, c} is an arithmetic triple} and resulting in an enormous improvement in the speed and . efficiency of these solvers in the past decade. Definition 2 (Non-arithmetic set). A set A is said to be non- In this paper, we are exploring the possibilities of solving arithmetic if arith(A) = ∅. a set of instances of a hard combinatorial problem with the final goal of getting some new insights into the problem with such an empirical exploration. One way to implement this With these two definitions in place, we can define our opti- search could be to hand-tailor an efficient solver for this mization problems. Definition 3 (MinNArith). Given a set A = {1 . . . n}, what is the smallest non-arithmetic subset A′ ⊆ A, which is also maximal (or saturated), i.e. it is not possible to enlarge this set without creating an arithmetic triple, formally: ∀i ∈ A \ A′ : arith(A′ ∪ {i}) ̸= ∅ In our case, we are mostly interested in the size of such a set, given a particular value of n. 627 Example:. Let us say the set A = {1, . . . , 16}, one sat- The N ARIT H constraints have already been described (if urated set that does not contain any arithmetic triple is we apply DeMorgan’s rule it is already in CNF form), now A′ = {6, 7, 10, 11}. It can be easily checked that by adding we need to define more precisely how CARD and SAT U R any other number from A, we create an arithmetic triple. constraints are written as logical expressions. We will see that this is also the smallest such subset of A. What is known about this problem? [7, 6] Cardinality constraints. The problem of encoding cardi- 1. it seems to be a hard mathematical problem nality constraints in SATs is a research topic on its own, 2. for n = 4k there exists a construction of such a set of size √ and many different approaches are known. The main issue n,i.e., 2k we are addressing in this problem is how to enforce that 3. it is conjectured that this is the smallest possible such set at most a certain number of variables are set to true. The 4. It has been proven that this is indeed the case for n = most researched version of this problem is known as at-most- 4, 16, and 64. one (AMO) constraint [9]. Generalizations (at-most-k con- straints) have been explored and are now part of most stan- dardized SAT modeling toolboxes. It is also well-known [12] The goal of this work is to push this boundary further, as that different encodings can have varying effects on the ex- much as possible, with the final goal to explore the feasibility ecution times of different solvers. of computing the size of the minimal set for n = 256. Since we already know such a set of size 16, the goal is to prove In order to explore this impact, we tested 4 different stan- that there is no such set of size 15. dard encodings: Sequential counting [10], Sorting network [2], Cardinality network [1], and k-modulo totalizer [8]. 2.2 Reduction to SAT In principle, this is a minimization problem, but we will use a decision version of this problem to reduce to SAT. Saturation constraints. For each element i ∈ A, we have to express that either it is in the set A′, or that there exists Definition 4 (MinNArithDEC). Given a set A = {1, . . . , n} an arithmetic triple {i, j, k} ∈ arithA such that j, k ∈ A′. and a number k, does a saturated non-arithmetic subset A′ ⊆ A exist, such that |A′| ≤ k. This is straightforwardly transformed into a logical expres- sion: In what follows, we give a reduction M inN ArithDEC → _ x (x SAT . The input to this problem are two numbers n and k, i ∨ ( j ∧ xk )) the reductions construct a logical expression (in CNF form) (i,j,k)∈arith(A) that is satisfiable if there exists a saturated non-arithmetic subset of A = {1 . . . n} with the size ≤ k. However, there is a technical difficulty with this expression. Namely, it is not in CNF, which is a typical requirement Each element in i ∈ A has a corresponding logical vari- of SAT solvers. A straightforward transformation to CN F able xi, which is true if i ∈ A′. To describe the problem would result in exponentially large expressions, which would M inN ArithDEC, we introduce three types of constraints quickly make them practically unusable. Luckily, there ex- on this set of logical variables. ists a transformation, called the Tseitin transform [11], that transforms any logical expression into CNF, and the final expression is linear in the size of the original expression. 1. Cardinality constraint, i.e., at most k of the variables The downside of this transformation is that also introduces xi can be true. We will denote this constraint as a linear number of new variables. CARD. 2. In order for the set of true variables to describe a non- arithmetic subset, we have to check every arithmetic 2.3 Sizes of instances triplet {a, b, c} ∈ arith(A) and assure that not all three To give an impression of the sizes of the reduced problem, the elements are in A′: number of clauses and the number of variables for different n and k are given in Table 1. xa ∧ xb ∧ xc . We will denote this type of constraint as N ARIT H. Two different parameters describe the size of the expression, those are the number of variables and the number of clauses 3. And the third type of constraints assure the satura- in the expression. tion of the set A′. For every element, a ∈ A, either a is already in the chosen subset, or there exists an arith- The table gives these two sizes for three different expressions, metic triplet where both of the other two elements are E(16, 3), E(64, 7), E(256, 15). These are the expressions at in the set. We will denote this type of constraint as n = 4k since we are testing the hypothesis that the solution SAT U R. at this n is 2k and these expressions should all be unsatisfi- able based on this hypothesis. We also show the difference in sizes if different cardinality encodings are used. We can The final expression is the conjunction of these three con- see that the encoding does not greatly influence the entire straints: size of the expression, since the largest difference is only a E(n, k) = CARD ∧ N ARIT H ∧ SAT U R few percent. 628 Table 1: Sizes of reduced problems √ 12 y = n y = min n, k CC # of vars # of clauses 10 seqcount 391 1168 8 cardnet 440 1213 (16,3) 6 sortnet 416 1265 kmtotalizer 397 1182 4 seqcount 6415 19760 2 (64,7) cardnet 6600 19789 sortnet 7102 20542 20 40 60 80 100 kmtotalizer 6251 19598 seqcount 101407 316576 Figure 2: The plot of the minimal saturated set sizes. The (256,15) cardnet 101248 314305 black plot shows the lower bound which was reached only at sortnet 105470 320638 the points n = 4k. kmtotalizer 98712 312147 An even more important aspect of our empirical test is the running times to prove the optimality for a certain n. Fig- But that does not describe the entire picture of the struc- ure 3 shows the measurements for 4 different cardinality con- ture of these expressions. A more detailed view is given straint encodings. The first chart gives the running times (y in Figure 1 which shows the percentage of clauses and new axis is log scale) and it can be seen that all four encodings variables introduced by each type of constraint. The first follow the same trend. Nonetheless, some differences cannot graph shows how the ratio of the three types of clauses. It be seen on this log-plot, so we show the results for E(75, 10) can be seen that the SAT U R constraint contributed to the and E(81, 11) which shows that that k modulo totalizer has vast majority of clauses. As n grows, the dominance of the a significant advantage over the other three encodings. SAT U R clauses gets even bigger. A similar situation can be seen on the right graph that shows the ratio of the newly in- troduced variables. First, notice that N ARIT H constraints 4. UNSATISFIABLE CORES do not introduce any new variables and are thus omitted Based on the results described above, it seems unlikely that from this graph. Again, the vast majority of newly intro- we could solve the expression E(256, 15) in a reasonable duced variables originate from the SAT U R constraints. amount of time. This also gives little hope for solving the problem using some other reductions or even hand-crafted solvers for this particular problem. Clauses Additional vars 100 100 100 100 100 100 100 100 100 100 100 95 95 95 95 95 However, there could be a different path, using the byprod- 80 uct of SAT solvers. Namely, these solvers produce proof that ses 60 their claim (satisfiable or unsatisfiable) is true. For satisfi- uacl able expressions, the proof is simply the variable assignment 40 % that yields a true value of the expression. But for unsatis- 20 12 8 6 7 3 fiable expressions, the proof is the trace of the execution of 2 1 4 2 1 0 the solver. 1 5 1 5 16-3 32-4 64-7 16-3 32-4 64-7 128-1 256-1 128-1 256-1 The trace of the execution is very large, but a more compact card satur narith proof can be extracted from it, and that is the unsatisfiable Figure 1: The structure of the SAT expression. core [4] of the expression. Unsatisfiable cores are subexpres- sions that are unsatisfiable, but if we remove any clause, the expression becomes satisfiable. This can thus be viewed as 3. COMPUTATIONAL RESULTS the core ”reason” why this expression is unsatisfiable. These generated SAT expressions have been given to the As an example, let us examine the unsatisfiable core of the state-of-the-art solver. We used currently the fastest solver expression E(16, 3). The entire expression has 397 variables kissat [3], which won the 2020 and 2021 SAT competitions. and 1182 clauses (k modulo totalizer), but the unsatisfiable core has only 399 clauses. We can brake down the structure The minimal size of the set is obtained by finding a number of the unsatisfiable core even further: k, such that E(n, k) is satisfiable and E(n, k − 1) is unsat- isfiable. In the evaluation description, we will be mostly describing the unsatisfiable expressions, since these expres- • original size of the CARD expression is 102 and the sions are usually much harder for the SAT solvers. core contains only 73, Figure 2 shows the sizes of minimal saturated subsets. The • N ARIT H has 56 clauses, but the core only contains √ black plot is n, i.e., the hypothesized lower bound. The 19 of these, results give further empirical evidence for this hypothesis to √ • and SAT U R has 1024 clauses, but the core only 307. be true since the n lower-bound is reached only at points n = 4k, which makes it more plausible that the proposed construction of such sets is also optimal. These results show that there is a more compact reason for 629 kmtot a pessimistic result that it seems unlikely to obtain optimal seq results for a much larger n without a significant new insight 104 sortnet cardnet into this problem. 102 c But the reduction to SAT also has another potentially useful se side-effect, namely the unsatisfiable cores. These subexpres- 100 sions that can be obtained by SAT solvers carry some new insight into the problem and the study of their structure and reverse-engineering the rules for their creation might 10−2 lead to discoveries in this and maybe other similar problems 20 30 40 50 60 70 80 as well. n ·105 kmtot 1.5 6. REFERENCES seq sortnet [1] R. As´ın, R. Nieuwenhuis, A. Oliveras, and cardnet E. Rodr´ıguez-Carbonell. Cardinality networks and 1 their applications. In O. Kullmann, editor, Theory and c Applications of Satisfiability Testing - SAT 2009, se pages 167–180, Berlin, Heidelberg, 2009. Springer 0.5 Berlin Heidelberg. [2] K. E. Batcher. Sorting networks and their applications. In Proceedings of the April 30–May 2, 0 1968, Spring Joint Computer Conference, AFIPS ’68 75-10 81-11 (Spring), page 307–314, New York, NY, USA, 1968. Association for Computing Machinery. Figure 3: Run times for solving the problem E(n, k), by [3] A. Biere, K. Fazekas, M. Fleury, and M. Heisinger. varying n and k being the largest value where the expres- CaDiCaL, Kissat, Paracooba, Plingeling and sion is unsatisfiable. The left plot shows the log plot of Treengeling entering the SAT Competition 2020. In the time for four different encodings of the cardinality con- T. Balyo, N. Froleyks, M. Heule, M. Iser, M. Järvisalo, straint. The right plot shows only the times for E(75, 10) and M. Suda, editors, Proc. of SAT Competition 2020 and E(81, 11) to show a more significant difference between – Solver and Benchmark Descriptions, volume different encodings. B-2020-1 of Department of Computer Science Report Series B, pages 51–53. University of Helsinki, 2020. [4] A. Cimatti, A. Griggio, and R. Sebastiani. A simple the impossibility of the existence of a saturated set of size 3. and flexible way of computing small unsatisfiable cores There are two possible usages of these unsatisfiable cores: in sat modulo theories. In J. Marques-Silva and K. A. Sakallah, editors, Theory and Applications of • reverse engineering the unsatisfiable core to obtain the Satisfiability Testing – SAT 2007, pages 334–339, rules and find a general pattern and thus the proof for Berlin, Heidelberg, 2007. Springer Berlin Heidelberg. the lower bound as it is currently hypothesized. [5] N. Froleyks, M. Heule, M. Iser, M. Järvisalo, and M. Suda. Sat competition 2020. Artificial Intelligence, • knowing the shape of the unsatisfiable cores, we could 301:103572, 2021. solve the problem by explicitly finding such a sub- [6] E. Gy˝ ori. personal communication, 2022. structure in the entire expression, e.g. E(256, 15). This would require a search for a known substructure, [7] S. J. Miller. Combinatorial and additive number which is a computationally simpler problem than prov- theory problem sessions: ’09–’19, 2014. ing that a certain structure does not exist. [8] A. Morgado, A. Ignatiev, and J. Marques-Silva. Mscg: Robust core-guided maxsat solving. J. Satisf. Boolean 5. CONCLUSIONS Model. Comput., 9:129–134, 2014. [9] V.-H. Nguyen, V.-Q. Nguyen, K. Kim, and In this paper, we described a reduction of the problem of P. Barahona. Empirical study on sat-encodings of the finding a minimal saturated non-arithmetic subset. This is a at-most-one constraint. In The 9th International hard mathematical problem and empirical results could shed Conference on Smart Media and Applications, pages some new light on this problem, giving potential insights for 470–475, 2020. future exploration of the problem. [10] C. Sinz. Towards an optimal cnf encoding of boolean The current hypothesis is, that the lower bound for the size cardinality constraints. In P. van Beek, editor, √ of such a set is n and it can be reached for values n = 4k. Principles and Practice of Constraint Programming - Our initial hope was to be able to reach n = 256, where a CP 2005, pages 827–831, Berlin, Heidelberg, 2005. known set is of size 16 and we need to prove or disprove that Springer Berlin Heidelberg. this is the smallest possible one. [11] G. S. Tseitin. On the complexity of derivation in propositional calculus. In Automation of reasoning, Using state-of-the-art solvers, we attacked this problem and pages 466–483. Springer, 1983. obtained optimal solutions for values up to 100. All the [12] N.-F. Zhou. Yet another comparison of sat encodings results are in favor of the current hypothesis, but there is also for the at-most-k constraint, 2020. 630 Exact time measuring challenges Tomaž Dobravec University of Ljubljana Faculty of Computer and Information Science tomaz.dobravec@fri.uni-lj.si ABSTRACT complexity. The model that is used in theoretical study In this paper, we focus on implementations of the Bubble- does usually not take into account all the peculiarities of Sort algorithm in three different programming languages: the real execution environment (like memory caching, pag- Java, C, and x86 assembler. Using the ALGator system we ing, branch prediction, etc.), which are revealed only during execute these implementations with different inputs and per- the execution of the algorithm on a real computer. There- form an empirical evaluation of the results. We discuss the fore, for practical comparison of actual algorithms’ capacity importance of test repetition for achieving accurate timing theoretical analysis has to be replaced with empirical mea- results. We show that the Java and the C implementations surements of resource usage during the algorithms’ execu- achieve similar efficiency and that the quality order depends tions on various types of input data [5]. In order to provide on the type of input data. quality results, these measurements have to be performed carefully since many factors impact the measured data. In Categories and Subject Descriptors this paper we focus on some of them and present results of F.2 [Analysis of algorithms and problem complexity]: Relia- our measurements that highlight the importance of each of bility and Testing; D.2.8 [Software Engineering]: Metrics— them. Namely, we use three programming languages and complexity measures, performance measures present the impact of language selection on the speed of execution. Furthermore, we present the importance of rep- etition of tests, especially when the size of the input (and General Terms therefore the execution time) is small. In addition, we dis- Algorithm Engineering cuss how the type of input data can affect the algorithms’ quality rankings. Keywords empirical algorithm analysis, time measuring, accuracy, re- liability, comparing Java and C 2. TESTING ENVIRONMENT SETUP For all our tests in this research we will use the Bubble- This work is sponsored in part by the Slovenian Research Sort [1] algorithm for sorting arrays of integers. Since this Agency (research project N2-0171). is a very well known and a simple algorithm we are able to perform a precise theoretical analysis and provide very ac- 1. INTRODUCTION curate (theoretical) forecast for the time complexity of its The theoretical complexity analysis of algorithms is a very implementations. The algorithm is so simple that we can important part of the algorithm design process. This anal- count the number of operations performed during the exe- ysis usually estimates the amount of resources (e.g. time or cution for different inputs. Thus we will be able to compare memory storage) that is going to be utilized during the al- theoretical predictions with the empirical results. One of the goals of this research was to analyse the impact gorithm execution [4]. The result of the analysis depends on of the selected programming language on the efficiency of the selected computation model [3] which implies the execu- algorithm execution. Therefore we used three programming tion environment and its limitations. Roughly, the results of languages (namely the Java, the C and the x86 assembler) such theoretical analysis are used to distinguish between fast to implement BubbleSort. Due to the simplicity of the al- (i.e. polynomial) and slow (exponential) algorithms. But in gorithm we managed to write the three implementations in practice these results are of limited value especially if the such a way that they provide semantically identical code. two algorithms compared have the same (theoretical) time For further reference, we named implementations BubbleJ, BubbleC and BubbleA, where the last letter denotes the pro- gramming language used (J for Java, C for C and A for x86 assembler). When executing these implementations on the same inputs they will perform the same number of each programming-language-dependant atomic operations. Any differences in the execution speed will thus reflect the differ- ences in the execution speed of these operations in the se- lected programming language. The C implementation was compiled with the gcc compiler in two ways: without op- 631 timization (the -O0 flag) and with full optimization (the - way is much more reliable and accurate quality indicator. O3 flag). In this way we got two distinct implementations (namely BubbleC0 and BubbleC3). In the following we will 3. THE MEANING OF TEST REPETITION analyze the impact of this optimization to the speed of exe- In our first experiment we would like to find out the meaning cution. of several repetitions of a given test case execution. For this we used a test set consisting of three groups of test cases: To facilitate the empirical evaluation in our research we used in each group there are 50 identical tests of sizes 500, 5000 the ALGator system [2]. We used its tools to configure and 20000. All the input arrays in these test cases were the Sorting project, to provide the test sets of input data ordered in inverse order (to ensure the identical number of and implementations and to execute the algorithms’ imple- operations during the sort process). We executed each test mentations in a controlled environment. For the execution case 50 times. By analysing the results we noticed that the machine we used the Intel(R) Core(TM) i7-6700 CPU @ (absolute) difference between Tfirst and Tmin is approxi- 3.40GHz computer with 32GB RAM and with the Linux mately the same for all three groups of test cases. The rela- Ubuntu operating system installed. tive difference is therefore smaller for bigger measured times. We can conclude that the measurement of both Tfirst and The inputs for our algorithms consist of arrays of integers Tmin is important for small inputs and that the importance prearranged in three different orders: random order (RND), of distinguishing between Tfirst and Tmin decreases with sorted order (SOR) and inversely sorted order (INV). These increasing input size. Measurements have shown that some- three distributions of input data are well manageable from thing similar to the Java’s ”Tfirst phenomenon” also happens a theoretical point of view, since we know for all three the with C, except that in this case ”warming up the machine” number of operations that will be performed during the sort- adds significantly less to the overall time complexity, so the ing process. In all three case BubbleSort will perform exactly differences in speed between Tfirst and Tmin are noticeable n(n − 1)/2 comparisons, and n2/4, 0, n(n − 1)/2 swaps for only in experiments that take very little time. From Table 1, RND, SOR, INV respectively. Note that all the numbers which shows the relationship between the average first and of operations are exact, except for the number of swaps in T first RND case - here we only have the expected (instead of ex- the minimum execution time of a test case, f = it Tmin act) number of swaps, since the sequence is randomly mixed. can be seen that for small n the ratio is similar in both im- Since BubbleSort performs only comparisons and swaps (and plementations, but for larger n the difference between Tfirst some auxiliary increments of indices to maintain the loops) and Tmin is almost negligible for the BubbleC3, while for we could expect that, for example, sorting RND array will the BubbleJ the value decreases significantly more slowly. be faster than sorting INV array of the same size. But as At n = 20000 the difference is still more than 5%. we will see in the following this in not the case. The difference in measured times of multiple executions of In the ALGator project inputs (i.e. test cases) are grouped the BubbleJ and BubbleC3 implementations is depicted in into test sets. Each test case has its own identifier (Test Fig. 1. Here we used 50 inversely ordered arrays of size ID), so the results can also be compared on the test-basis. 5000, each test case was repeated 50 times. On the graph, To provide accurate results each test case is executed sev- the time of the first execution of the test case is shown in eral times (each execution of the test case has its identifier, gray (Tfirst, Repetition ID=0), the first 20 repetitions are Repetition ID). Besides a list of all execution times of a shown in orange, and the next 30 in red. With BubbleJ, we test case ALGator provides two information, the time of the see that the first times (Tfirst) deviate considerably from first execution (Tfirst) and the time of the fastest execution the other measured times; the Tfirst times are somewhere (Tmin) of this test case. The first execution is usually much between 18k and 22k, and the other times are much smaller slower than other executions since (this is true especially for (between 12k and 14k), which corresponds to the factor of the java environment) the execution machine needs to warm 1.4 from Table 1. Other measured times on this graph does up. As we will see in the following the Tfirst time can even not show much fluctuation, as the scale of the display is be twice as big as the Tmin time. reduced due to the large Tfirst times; we see that some Tfirst times are almost 100% larger than the smallest measured To measure the time in Java we can only use the wall-clock times. With BubbleC3, all times are quite similar to each (Java does not provide any processor usage information). other; the graph shows some variations, but everything is To minimize the unreliability of the measured time (which between 14.6k and 15.6k; the differences between measured is due to the fact that the process may spend time waiting times are relatively small (approx. 6%). for I/O or for other processes that are also using the CPU) we use a ”clean” computer which is dedicated only for exe- For the conclusion: is it important to repeat the algorithm cution of the algorithms. Besides that, we usually take the execution for several times to find the minimum time? As Tmin time as a reference data, since this is a time in which the computer is capable of solving the problem (the number of disturbing factors is minimal). For he algorithms imple- mented in the C programming language we use the CPU time obtained by the clock() function (which returns the number of clock ticks used by the process). By calling this function before and after the algorithm execution and sub- tracting the returned values we get the total amount of time T Table 1: The ratio f = f irst between the average of the a process has actively used a CPU. The time measured this Tmin first and the minimal measured times 632 Figure 1: Times of execution of 50 identical test cases (50 repetitions of each test case) with BubbleJ and BubbleC3 the measurements show, the answer depends on the size of tations, Java turned out to be the slowest, although the dif- the input - the smaller the input, the more measurements ferences in speed are not so great. Fitting all measurements are unreliable, so we need to take more measurements to get with a quadratic functions results in the following: a good result. BubbleC0: Tmin(n) = 2.438n2 µs Bar charts in Fig. 2 depict the proportion of measurements BubbleJ: Tmin(n) = 1.372n2 µs that differ from the smallest measurement by the given per- BubbleA: Tmin(n) = 1.311n2 µs centage range. The measurements on small inputs for the BubbleC3: Tmin(n) = 1.246n2 µs BubbleJ vary a lot. More than 36% of all measurements differ from the minimal time more than 10%. For the Bub- The ratio between the best (BubbleC3) and the worst (Bub- bleC3 on the other hand only 17% of the measurements are bleC0) implementation is 1 : 1.956, which we also noticed that bad. When increasing the size of the input the results from the graph. More interesting is the ratio between the for both algorithms improve. For n=20000, for example, optimized C3 and Java implementation: BubbleC3 : Bub- more than 73% (98%) of measurements differ from the min- bleJ = 1 : 1,101. This means that for sorting random se- imal measurements for less than 1% for BubbleJ (BubbleC3) quences Java is 10% slower than C. To find out, how good implementation. this conclusion is, lets calculate and depict the relative error The relative standard deviations of all measured times for BubbleJ are 21%, 7% and 1% for n=500, 5000 and 20.000 |BubbleC3.Tmin − 1.1 ∗ BubbleJ.Tmin| respectively. This confirms the claim that as the size of the Error = ∗ 100% BubbleJ.T input increases, the importance of multiple tests decreases. min Since the relative standard deviations are even smaller for BubbleC3 (namely 15%, 1%, 0.24%), the importance of a Fig. 4 shows that for small inputs (n < 5000) the error is large number of measurements is even smaller here. very big (as big as 1200%), but for larger inputs (n > 10000) the error is always less than 5% and it seems that it decreases when n increases. 4. THE IMPACT OF THE PROGRAMMING LANGUAGE As the last experiment we compared the times of execu- We compared the times of execution of four implementations tion of four implementations on inversely ordered sequences (BubbleJ, BubbleA, BubbleC0 and BubbleC3) on randomly (INV) of length 500 to 50,000 (step 500). The results that ordered sequences (RND) of length 500 to 50000 (step 500). are presented in Fig. 5 are somehow surprising. Each test was executed 30 times. Fig. 3 shows the minimum The quality ranking of algorithms when sorting INV data measured times Tmin of all four algorithms. changes comparing to the ranking on RND data. While We expected the BubbleC3 to be the best, which was also BubbleC0 remains the worst implementation, on the first proven with the measurements. The difference between Bub- place there is a swap - BubbleC3 gives way to BubbleA and bleC0 and BubbleC3 is somewhat surprising. Since Bub- BubbleJ. Something similar happens with the sorted (SOR) bleSort is a simple algorithm, one would expect that the data. This change in ranking is hard to explain, but ac- speedup resulting from the optimization would not be that cording to our other research results which shown that the great. But this is not the case, the difference is almost 2 processor’s branch predictor has a great impact to the exe- times for large n. The relationship between BubbleJ and cution time, we could speculate that the code generated by BubbleA is interesting. In a battle between fast implemen- JVM is less suitable for branch prediction. With INV (and 633 Figure 2: The proportion of measurements that differ from the smallest measurement by the given percentage range. Figure 3: Tmin, RND data, n = 500, ..., 50000 Figure 5: Tmin, INV data, n = 500, ..., 50000 small inputs. We also compared the differences between the programming languages. We showed that the difference be- tween Java and C is not very big and that it depends on the type of input data - for randomly sorted arrays, the C implementation was faster, while for inversely ordered and already sorted data, Java took the first place in the ranking. In the future we could provide similar results for some other problems (to see if the results can be generalized), we could Figure 4: Relative error of estimating BubbleJ.Tmin with use another popular programming language (like Python) 1.1*BubbleC3.Tmin and we could investigate the real impact of the branch pre- dictor the final results. SOR) data the code predictor is always correct, which could 6. REFERENCES reflect in better performance. Anyway, the results unequiv- [1] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and ocally shows that the type of the input has a great impact C. Stein. Introduction to Algorithms. The MIT Press, on the quality of implementation. While with random data 2nd edition, 2001. BubbleC3 implementation was faster than BubbleJ, for in- [2] T. Dobravec. Algator — an automatic algorithm versely ordered data (and sorted, as we also found out) the evaluation system. Advances in Computers, Java implementation is the fastest. 116(1):65–131, 2019. [3] M. Fernández. Models of Computation, An Introduction 5. CONCLUSIONS to Computability Theory. Springer, 2009. The results presented in this paper show that there are many [4] B. Swathi. A comparative study and analysis on the factors that have impact to the execution time of the algo- performance of the algorithms. International Journal of rithms. We have shown that despite a carefully controlled Computer Science and Mobile Computing, 5(1):91–95, environment, deviations occur in measurements. The devi- Januar 2016. ations are particularly pronounced in Java, since the way [5] M. Tedre and N. Moisseinen. Experiments in of measuring time here is significantly more sensitive to the computing: A survey. The Scientific World Journal, influence of the environment than in C. We have seen that 2014(1):1–11, 2014. repeated execution of algorithms is especially important for 634 Systematic generation of precedence based MILP models with P-graphs for multipurpose scheduling problems Máté Hegyháti Institute of Informatics and Mathematics Bajcsy-Zs. u. 4. Sopron, Hungary hegyhati.mate@uni-sopron.hu ABSTRACT equipment units are used to produce a certain set of goods. Scheduling of various processes is a widely researched topic More specifically, makespan minimization for multipurpose in the literature. Different fields have their own specific batch processes is investigated, which has been addressed constraints and parameters, thus, specialized approaches of- with various techniques over the last few decade, such as ten emerge to tackle these needs efficiently. Solution meth- Mixed-Integer Linear Programming (MILP), S-graph frame- ods have many flavors from general mathematical models work, Linearly-Priced Timed Automata, and others[1, 7]. such as mathematical programming, constraint program- Even among MILP models, several different branches have ming; through general purpose heuristics, e.g., genetic al- emerged, the two main categories are precedence based and gorithms, ant colony optimization; to problem specific tools time discretization based formulations[2]. like the S-graph framework. A lot of effort has been invested into the testing various mod- A general aim of any newly developed method is to perform els on case studies, benchmark examples, or a large number efficiently, and provide the optimal solution quickly, prefer- of randomly generated examples. When such a study is car- ably faster than existing approaches. However, each tool ried out, the examiner has to make a decision about the has its strengths and weaknesses, and even for a well de- models to be included. This is not a straight forward de- fined problem class, it is often not trivial to select the best cision even for only MILP models, as there is a huge num- approach for a problem instance in advance. This work fo- ber of them, often developed for a slightly different problem cuses on a prerequisite of this dilemma: having the set of classes, and usually have several variants. Moreover, even approaches to consider. with expert knowledge on the field, one can only include models that have already been published. The aim of the paper is to present a modeling approach which enables the systematic generation of sound MILP The aim of this work is to introduce a modeling approach, models for a problem class. To illustrate this approach, a that results in a mathematical model enabling systematic well known scheduling problem class from the batch pro- generation of possible general precedence based models, in- cess industry is considered, and the investigation is limited cluding the ones published in the literature. Such a method to only a specific type of MILP formulations, namely the would ensure for a comparative study, that it is not limited general precedence models. on manually hand-picked models, but consider all options within a given set of limitations. For the sake of simplicity Keywords and the illustration if this approach, this work focuses only on precedence based MILP models with general precedence scheduling, model generation, precedence, P-graph, MILP variables for the most basic multipurpose batch scheduling problems without any common real life requirements such as 1. INTRODUCTION AND LITERATURE changing- and setup times, storage limitations, etc. It would In general, the goal of scheduling is to time processes and have been too ambitious for this study to include a a wider often to allocate resources wisely in order to achieve a plan range of model types or a more complex scheduling problem that meets all requirements or to find the best one among class. This is left to future research. It is not the aim of them. Due to its general nature, scheduling has been in- this paper to provide any comparative results between the vestigated in many different fields of science. In this work, various MILP models, neither is to present the list of the nu- the focus is on the production industry, where machines or merous MILP formulations generated. The key messages of this study are the concepts and techniques used for building this model. For the aforementioned purposes, the P-graph framework was utilized. P-graphs have been originally introduced as combinatorial models of process networks[3], that allows the developed algorithms to find feasible or optimal solution structures to synthesis problems[5, 4]. Since then, the mod- els and the algorithms of the framework have been widely 635 applied in different areas of science from renewable supply inequality, where M is a sufficiently large number: chain optimization through polygeneration plant modeling to mobile workforce optimization[8, 6, 9]. Si0 ≥ Si + ptij − M · (1 − Xiji0 ) ∀j ∈ J, i, i0 ∈ Ij This formulation, however, requires an unnecessarily large The paper is structured as follows: Section 2 provides the number of binary variables, thus models often employ an- definition of the scheduling problem class selected for illus- other variable, Xii0 that takes the value of 1 if tasks i and tration. Different modeling techniques among precedence i0 are assigned to the same unit, and the decision has been based MILP formulations are briefly discussed in Section made that i is performed before i0. With such variables, the 3. Due to space limitations, completeness is not the aim of constraint above can be replaced with another: this section, only the showcasing of variations. To facilitate understanding, the utilized parts of the P-graph framework Si0 ≥ Si +ptij −M ·(3−Xii0 −Yij −Yi0j) ∀j ∈ J, i, i0 ∈ Ij are briefly introduced in Section 4. The P-graph formulation of precedence based MILP models is illustrated in 5, again Note, that the value of Xii0 is irrelevant if i and i0 are as- without the aim of completeness. Concluding remarks are signed to different units. If that feature is ensured by an- shared in 6 along with possible directions of further research. other constraint, and a separate completion variable is de- fined, sequencing can be enforced via the following simple constraint: 2. PROBLEM DEFINITION The goal of the considered problem class is to minimize Si0 ≥ Ci − M · (1 − Xii0 ) ∀i, i0 ∈ I, Ji ∩ Ji0 6= ∅ makespan of producing a set of products P with the set of Again, this constraint does not require Xii0 to be 0 if the equipment units: J . The production recipe of each product tasks are assigned to different units, it only needs them to p ∈ P is linear, and n + p ∈ Z denotes the number of steps. A be allowed to be 0. derived set, I = (p, n) | p ∈ P, n ∈ {1, 2, . . . , np} denotes the set of all tasks to be carried out. For simpler notation, Following similar thinking, other variants of the X variables a task is denoted by i instead of (p, n) when that level of and their corresponding constraints can be derived. Such detail is unnecessary. Ij ⊆ I refers to the tasks that can be further discussion is omitted here, however, there other ways carried out by unit j ∈ J , and for all i ∈ Ij , the execution how different model variants can be generated. For example, time is denoted by ptij in that unit. Ji is used to refer to Xii0 variables could either be defined for all i, i0 pairs in both units that can perform i ∈ I, i.e., Ji = {j ∈ J | i ∈ Ij }. directions or only for i < i0 if a total ordering is defined. Or, when Ci is introduced, it may be required to be the exact Each task is uninterruptible, must be assigned to exactly one time when i finishes, or just any time point after that, as unit, and a unit may not work on two tasks at the same time. discussed in a bit more detail in Section 5. Also, if the same Other common timing parameters for setups, changeovers, requirement of the problem class can be expressed in vari- etc., are neglected, and intermediate materials can be stored ous ways, only one can be selected or even several of them at any amounts for any duration of time, i.e., Unlimited redundantly. The latter may seem unreasonable, however, Intermediate Storage (UIS) Policy is considered. 1 testing experience often shows, that redundant constraints may affect the search space in such a way, that MILP solvers 3. VARIATIONS FOR GENERAL PRECE- and their heuristics can find better solutions or bounds. DENCE BASED MILP MODELS Precedence based models for the described problem class 4. BRIEF INTRODUCTION TO P-GRAPHS usually rely on decision variables about the assignment, se- The P-graph framework was introduced to provide a rigor- quencing, and starting time of tasks. ous and efficient framework to generate feasible process net- works [3], or find the optimal one among them[5, 4]. This Assignment is generally modeled by a binary variable, Y work relies only on the original P-graph model (without any ij denoting whether unit j ∈ J is assigned to task i ∈ I. Sim- extensions or additional parameters) and the SSG (Solution ilarly, the exact starting time of task i ∈ I is modeled by a Structure Generator) algorithm, that generates all combina- continuous variable S 0+ torially feasible solution structures. i ∈ R . The models also always define the makespan, M S as a target variable to be minimized. A P-graph is an (M, O) pair, where M denotes the set of This is the point, where models start to diverge. Some dedi- materials, and O the set of operating units. Each operating cate a continuous variable C unit o ∈ O is a pair of material sets: its (mandatory) inputs i for the completion time of each task, similar to S and outputs. A Process Network Synthesis (PNS) problem i. The largest difference, however, appears in the sequencing variables, usually denoted by X. In some is defined by a triple (P, R, O) where models, Xiji0 takes the value of 1 if and only if both tasks i and i0 are assigned to unit j and the decision has been made P is the set of product materials that must be produced by to perform i before i0. With such a variable, the constraint at least one operating unit. to properly sequence tasks can be expressed by the following 1 R is the set of raw materials that can be consumed without In this simplified form, the problem class is reduced to Flex- ible Job Shop Scheduling. However, as the research was mo- being produced by an operating unit. tivated by the batch production industry, its terminology is kept along with its standard notation, that has less conflicts O is the set of possible operating unit to be included in the with that of the P-graph framework. network. 636 The SSG algorithms takes (P, R, O) as its input, and gener- The inputs of this O-node are less obvious and worth a short ates all of the feasible subsets of O that satisfy the 5 axioms discussion. Seemingly there should be two of them, the R- for feasible solution structures. nodes representing the Si and Ci variables. However, that is not correct, as the R-nodes only represent the availability 5. SYSTEMATIC MODEL GENERATION of those variables, but don’t ensure additional semantic fea- tures. Namely, the R-node for C In many industrial applications of the P-graph framework, i only ensures that there is a variable named C but nothing about its timing. For the the original meaning of operating units and materials is ex- O-node above to produce P2, such a C variable is needed, tended to broader concepts. Materials often represent logical whose value is ensured to be greater or equal than the com- states, and operating units may model transportation, etc. pletion time of the task. This semantically correct C variable This application of P-graphs follows the same idea. There is different from the R-node above, and can be represented are, however, terms like intermediates, product, unit, etc., by an I-node. In turn, this I-node can be produced by the that both appear in the underlying process to be scheduled following O-node: and in the P-graph model, that is used to generate MILP models. To avoid confusion, the elements of the P-graph X Ci ≥ Si + Yij · ptij ∀i ∈ I model will be referred to as M-, P-, I-,R- and O-nodes. j∈Ji 5.1 or by another O-node: P- and R-nodes The R-nodes of the proposed model are the variable decla- Ci ≥ Si + Yij · ptij ∀i ∈ I, j ∈ Ji rations with their domain, such as: Both O-nodes require the R-nodes for C and S variables as inputs. Again, the R-node representing the Y variables is • S 0+ not an input, as it does not hold the semantic meaning, that i ∈ R ∀i ∈ I one unit is assigned to a task. This is represented by P1. • C 0+ i ∈ R ∀i ∈ I An observant reader may point out that the first suggested • Yij ∈ {0, 1} ∀j ∈ J, i ∈ I O-node above should have had equality: • X X ii0 ∈ {0, 1} ∀i, i0 ∈ I, i < i0, Ji ∩ Ji0 6= ∅ Ci = Si + Yij · ptij ∀i ∈ I • X j∈Ji ii0 ∈ {0, 1} ∀i, i0 ∈ I, i > i0, Ji ∩ Ji0 6= ∅ This constraint, of course is a valid, and a different O-node • Xiji0 ∈ {0, 1} ∀j ∈ J, i, i0 ∈ Ij, i < i0 in the proposed model. However, the output of this node is not the same, as in this case, it is ensured that C • X i is iji0 ∈ {0, 1} ∀j ∈ J, i, i0 ∈ Ij, i > i0 exactly the finishing time of a task, not a time point at least that much. Some O-nodes may require this more specific The P-nodes are the feasibility constraints of the scheduling version of C, others the previous one. On the other hand, problem: if this new I-node for the C variables with exact timing is available, the other I-node is also implied. This implication is also represented by an O-node, that has no constraint P1 Each task must be carried out. assigned to it. P2 Production steps of a product must be in order. Thus, I-nodes in the proposed model are concepts similar P3 Tasks assigned to the same unit can not overlap. to the P-nodes, albeit more specific to the variables of the model. O-nodes represent either constraints or logical im- P4 The shutdown of the facility must happen after all of the plications. products are produced. 5.3 Illustration Figure 1 illustrates the part of the model that in the previous These are the results that has to be produced (ensured) from section. the R-nodes. To do so, O-nodes are available. It is easy to see, that there are 7 feasible solution structures 5.2 O- and I-nodes (3 of them without redundancy) to just this small part of One type of O-nodes are the possible constraints in a prece- the P-graph model. Generating the model from a solution dence based MILP model. structure is straight forward, the constraints and variable declarations corresponding to included O-nodes and R-nodes As an example, the following constraint is an O-node, that compose the MILP model together with the objective func- consumes the R-node representing Y and generates P1: tion to minimize the makespan. X Yij = 1 ∀i ∈ I Note, however, that there could be other O-nodes producing j∈J P2, further increasing the number of possible models. For As another example, the following constraint is another O- example: node that generates P2: X S(p,n+1) ≥ S(p,n) + Y(p,n)j · pt(p,n)j ∀(p, n) ∈ I S(p,n+1) ≥ C(p,n) ∀p ∈ P, n ∈ {1, 2, . . . , np − 1} j∈J(p,n) 637 declarations and operating units are linear constraints on them. An MILP model can easily be derived for the orig- inal illustrative problem class for every solution structure generated by SSG for this PNS problem. The model is backwards-compatible with addition, i.e., the introduction of new variables and constraints does not render previous solution structures (MILP formulations) infeasible (invalid). This research is in an early stage. There are numerous ad- ditions and extensions of the proposed approach that could be considered for future research. After the inclusion of intermediate precedence variables, parts of time discretiza- tion models may be added, which may help uncover previ- ously unknown hybrid models. Extensive performance test- ing of generated models, and observing the reduction be- Figure 1: Part of the proposed P-graph model tween model variants by the preprocessor of various MILP solvers could be of interest. 5.4 Remarks on extendability 7. ACKNOWLEDGEMENT The rest of the model could be formulated in a similar fash- ion. Naturally, the presented model only considers con- The author thanks Nikolett Sós, whose diploma project con- straints that are included as O-nodes. It will not discover sultations sparked the idea behind this work. new type of constraints, only find the sound combinations of proposed ones. 8. REFERENCES [1] State-of-the-art review of optimization methods for The modeling procedure, however, allows extension by addi- short-term scheduling of batch processes. Computers & tion. 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State Thus, this is a model that can continuously grow, and fea- of the Art in Global Optimization, chapter sible solution structures of a previous version would still re- Combinatorially Accelerated Branch-and-Bound main feasible. Method for Solving the MIP Model of Process Network Synthesis, pages 609–626. Kluwer Academic Publishers, There are still options, that were not discussed here due to Dordrecht, 1996. space limitations, and to the early stage of this research. For [5] F. Friedler, J. B. Varga, and L. T. Fan. example, in an extended model, some I-nodes could require Decision-mapping: A tool for consistent and complete a mutually exclusive relation. This is a feature, that is not decisions in process synthesis. Chemical Engineering supported by the P-graph tools introduced here. P-graphs Science, 50:1755–1768, 1995. with material balances and an underlying MILP model can, [6] F. Friedler, Ákos Orosz, and J. P. Losada. P-graphs for however, easily model this. Process Systems Engineering. Springer, Cham, 1 edition, 2022. Also, the presented model only allows redundancy among [7] M. Hegyhati and F. Friedler. Overview of industrial constraints, but not among variables. Simplest example to batch process scheduling. Chemical Engineering this would be, if two sets of Ci variables were introduced, and Transactions, 21:895–900, 2010. some would be used by one subset of O-nodes, and the other one by others. This feature, again, could be modeled by [8] J. Klemes and P. Varbanov. Spreading the message: introducing material balances and quantities into the model. P-graph enhancements: Implementations and applications. Chemical Engineering Transactions, 45:1333–1338, 10 2015. 6. CONCLUSIONS & FUTURE RESEARCH [9] A. Éles, I. Heckl, and H. Cabezas. New general In this paper, an approach is presented to develop a model, mixed-integer linear programming model for mobile that can generate MILP models for a specific problem class. workforce management. Optimization and Engineering, This modeling technique - based on P-graphs - is illustrated Feb. 2021. IF: 2.760. on the simple class of multipurpose batch process scheduling problems and with the scope on general precedence based MILP models by P-graphs. Following this technique results in a large PNS problem, where raw materials are variable 638 On relations of Watson-Crick finite automata to other computational paradigms [Extended Abstract] Benedek Nagy Department of Mathematics, Eastern Mediterranean University Famagusta, North Cyprus, via Mersin 10, Turkey Institute of Mathematics and Informatics, Eszterházy Károly Catholic University, Eger, Hungary nbenedek.inf@gmail.com ABSTRACT to the Chomsky hierarchy. However, they are not indepen- We study language classes that are accepted by some vari- dent of each other, as in the former model, the class of selec- ants of Watson-Crick finite automata, i.e., with a 2-head tion languages is frequently chosen as one of the classes of the model of finite automata working on Watson-Crick tape Chomsky hierarchy. There are two main types of contextual modeling DNA molecules. We show a relation between sti- grammars, the internal and the external types, in the former cker systems and stateless traditional Watson-Crick automa- the words of a context are inserted inside the actual word, ta where the two heads scan the input in the same direction. while in the latter the words of the context are attached to We also establish a new connection between external contex- the two ends of the actual word. In this paper, we are inter- tual grammars with choice to the sensing 50 → 30 Watson- ested mostly in the external contextual grammars, thus we Crick automata, i.e., to the 2-head model of finite automata will only recall those in Section 2. On the other hand, DNA where the two heads starting from the two extremes of the computing belongs to new computing paradigms emerged in input and they move in opposite direction till they meet. the end of the last century. Two of the ‘traditional’ mod- els of DNA computing, the filtering and the sticker systems Categories and Subject Descriptors are in close relation to the ground breaking experiments of F.4.3 [Formal Languages] Adleman and Lipton solving (some instants) of the Hamil- tonian path and SAT problems by coding graphs in sets of DNA molecules, filtering out and detecting the result [1, 8]. General Terms DNA computing and its models can also be used to gen- Theory, Automata, Languages, Computing paradigms erate/accept formal languages, and not only to solve some (combinatorially hard) problems. The sticker systems can Keywords also be used for language generation based on the sticking Watson-Crick automata, sticker systems, formal languages, operation: DNA molecules having single stranded, so-called finite state machines, stateless automata, external contex- ‘sticky’ ends, can stick together to form a larger molecule. tual grammars, linear languages For a good analogy, one may think about how a (long) line can be built by dominos. (A more formal description is given 1. INTRODUCTION in Section 2.) On the one hand, contextual grammars are one of the formal methods developed to generate languages [2, 9, 21] initiated Another early formal DNA computing model, named by the by Solomon Marcus in the end of 1960s. The generation of Nobel price winners Watson and Crick, who discovered the the words, i.e., the derivation process is going by inserting structure of the DNA molecules, is a generalisation of finite or attaching two subwords at the same time to the actual state automata working on two-stranded DNA molecules word. The inserted/attached subwords are called context (also called Watson-Crick tape) instead of the traditional and the condition how the process is done, the “choice”, is tape [3]. These models of computation, namely Watson- handled by selection languages. The main motivation comes Crick automata, are entirely defined to describe some for- from linguistics, as there are various non-context-free struc- mal languages, in a similar manner as models of traditional tures that occur in natural languages, in general. Contextual automata theory do. Already it is mentioned in [20, 22] grammars give a somewhat orthogonal classes of languages that Watson-Crick finite automata are developed as a kind of accepting counterpart of the language generating sticker systems. In this paper, our aim is twofold, first we investigate a formal connection between some sticker systems and some variants of Watson-Crick finite automata, and then, we also concen- trate on connections of reverse Watson-Crick automata and external contextual grammars. Some variants of the reverse Watson-Crick automata are also called 50 → 30 Watson- 639 Crick automata as the heads of these automata are scan- nucleotides on one of the ends, than this is called a sticky ning the input DNA in opposite physical directions, i.e., end, as the molecule can be expanded by sticking there an both strands from their 50 to 30 direction. We note here appropriate other molecule... that there is an expansive literature on the sensing 50 → 30 Watson-Crick automata [10, 11, 12, 13, 14, 16, 17, 18, 19] Instead of the original nucleotides, in formal models we may in which the process on the input finishes when the heads use letters of any alphabet. Moreover, as [6] has proven, meet if the automaton does not get stuck earlier. The struc- we may use the identity relation in the role of the comple- ture of this paper is as follows. In the next section we re- mentarity relation without loss of generality, both at sticker call some formal definitions from the literature mentioned systems and at traditional Watson-Crick automata. Thus, earlier. In Section 3, the first part of the main results are for simplicity, from now on we use always the identity rela- presented, by establishing a connection between sticker sys- tion. tems and Watson-Crick automata. Then, in Section 4, we present connections between external contextual grammars Now, we are ready to see Watson-Crick automata (WK and sensing 50 → 30 Watson-Crick automata. automata shortly). These automata work on (full double stranded) DNA molecules; they have two reading heads one 2. NOTATIONS AND DEFINITIONS for each of the two DNA strands. Formally, a Watson-Crick Here, we recall some important definitions and fix our nota- automaton is a 6-tuple M = (V, ρ, Q, q0, F, δ), where V is tions. We assume that the reader already knows the basic the (input) alphabet, ρ ⊆ V × V denotes a complementarity concepts of finite automata, formal languages, generative relation, (in this paper, we use the identity), Q represents a grammars and computing. We denote the empty word by λ. finite set of states, q0 ∈ Q is the initial state, F ⊆ Q is the set of final (accepting) states and δ is called transition map- Let us start with external contextual grammars with choice V ∗ ping and it is of the form δ : Q × → 2Q, such that (also called selection). Formally, an external contextual V ∗ grammar EC is a triplet (V, A, P ) where V is a finite al- it is non empty only for finitely many triplets of q, u and v, phabet, A is a finite set of words over V , the set of axioms i.e., (q, u ), where q ∈ Q, u, v ∈ V ∗. In case Q = F = {q v 0}, and P is a finite set of pairs. The elements of P are of the we say that the automaton is stateless. form (C, S) where C ⊂ V ∗ × V ∗ contains the contexts and S is a language over V , the selection language for context The description so far has not distinguished the traditional C. The direct derivation relation is defined as follows: for and the sensing 50 → 30 models. Thus, the configuration and any word x ∈ V ∗, x ⇒ uxv if there is a context C = (u, v) the computation steps, i.e., the transitions between config- such that x ∈ S, for a pair (C, S) ∈ P . As usual, the direct urations play crucial role to specify the type of the model. derivations (or also called derivation steps) can be extended In a traditional WK automaton, both heads of the automa- to the derivation relation, denoted by ⇒∗ by taking their ton starts from the same place, from one of the ends of reflexive and transitive closure. The generated language is the input DNA molecule, and both of them read the entire then defined as strand in an accepting computation. The input molecule is accepted, if the automaton could reach an accepting state L(EC) = {w ∈ V ∗| there exists x ∈ A such that x ⇒∗ w}. when both strands are fully scanned. Formally, a configu- We say that an external contextual grammar is without ration of a traditional WK automaton is a triplet u , q v choice if S = V ∗ for every element of P . If all choice lan- in which u, v ∈ V ∗ are the upper and lower strand parts guages are regular/linear etc., then we say that this is an ex- of the input that have not processed yet, and q ∈ Q is ternal contextual grammar with regular/linear, etc. choice. the actual state. The initial configuration is w , q with w 0 the input word w in both strands, as at that stage of the Now we describe some basic facts about DNA. DNA mole- computation the whole input DNA w is to be processed. w cules are built up by 4 types of nucleotides which are usu- From the configuration bu , q the configuration u , p cv v ally abbreviated as A,C,G,T by their name. A DNA strand directly computed (or computed in one step), denoted by bu can be seen as a sequence of nucleotides. The sequence has , q ⇒ u , p), if p ∈ δ q, b . The reflexive and cv v c two ends, one of them is denoted by 50 and the other by transitive closure of ⇒ is denoted by ⇒∗ and called compu- 30. These ends can easily be distinguished chemically. The tation. A DNA molecule w or, let us say, the word w, is w nucleotides have a so-called Watson-Crick complementarity accepted if w , q ⇒∗ λ , p for some p ∈ F . The set w 0 λ relation meaning that A and T are pairs of each other as of accepted words is the accepted language. well as C and G are pairs of each other. Two DNA strands could form a DNA molecule that is double stranded, if they However, as we have already mentioned, the two strands of are complement of each other as follows. At each position of the DNA molecule have opposite 50 → 30 orientations, thus it a strand the nucleotide is the Watson-Crick pair of the nu- is worth to take into account such variants of Watson-Crick cleotide of the other strand at that position. Moreover, the automata that parse the two strands of the Watson-Crick direction of the two strands are opposite, i.e., the nucleotide tape in opposite directions. These automata are also called of the 50 end of a strand is paired to the nucleotide of the reverse WK automata. Obviously, if each head starts to read 30 end of the other. A full double stranded DNA molecule its strand from its 50 end, as usually enzymes also do, then is denoted by u with u on the upper and v on the lower they start to scan the input DNA from physically different v strand. With the notation u we may denote a DNA which ends [7, 22]. On the other hand, as the two strands of a v has u on the upper and v on the lower strand, but it may not DNA molecule are determined by each other via the Watson- be a full double stranded molecule, e.g., their lengths may Crick complementarity relation, we may also think about the not be identical. When one of the strands has some extra sensing 50 → 30 WK automata, in which the two heads sense 640 if they arrived into the same position. Since, actually, by this T be a finite alphabet and u : Du → T , ` : Dl → T be two point of the computation, exactly one of the letters of each mappings to T . For a finished computation, let us assign position has been already read, this model finishes the work the string wu ∈ T ∗, by using u, to the sequence of dominos on the input at this point and decides on the acceptance. used in the upper strand. Similarly, let us assign wl ∈ T ∗, It is easy to see, that the complementarity relation can also by using `, for the sequence of dominos used in the lower be substituted by the identity in case of these automata strand. without changing their computational power, (i.e., the class of languages that can be formed by the words on the upper Further, a computation is coherent, if wu = wl. Based on strands of the accepted molecules). that, the language generated by a simple regular sticker sys- tem R in coherent way is Formally, a configuration of a sensing 50 → 30 WK automa- n h w i o ton is a pair (q, w) where q is the current state of the au- w | can be generated in coherent way in R . w tomaton and w is the (double stranded) part of the input word which has not been processed (read) yet by any of the 3. STICKER SYSTEMS AND heads. For w0, x, y ∈ V ∗, q, q0 ∈ Q, we write a transition, a WATSON-CRICK AUTOMATA step of a computation, between two configurations as: In this section we present relations between two paradigms (q, xw0y) ⇒ (q0, w0) if and only if q0 ∈ δ(q, x). We denote y dealing with formal languages in DNA computing. the reflexive and transitive closure of the relation ⇒ by ⇒∗ also in this case. Therefore, for a given w ∈ V ∗, an accepting It is known that if a language L can be obtained by a simple computation is a sequence of transitions (q0, w) ⇒∗ (p, λ), regular sticker system in a coherent way, then there is a WK starting from the initial state and ending in a final state automaton that accepts L [22]. p ∈ F . The language accepted by a sensing 50 → 30 WK automaton M is: Now, we give a kind of extension of this result. L(M ) = {w ∈ V ∗ | (q0, w) ⇒∗ (p, λ), p ∈ F }. Theorem 1. If the language L can be obtained by a sim- ple regular sticker system without axiom in a coherent way, Finally, let us recall the sticker systems. We note here that then L is also accepted by a stateless WK automaton. sticker systems, as computing model, can be used to pro- vide efficient solutions to computationally hard, e.g., NP- complete problems (at least theoretically) [1, 4, 8, 15, 23]. Proof. Let (V, %, Du, Dl, A) be a simple regular sticker However, in this paper we are concentrating in their lan- system that generates L in coherent way with the mappings guage generating feature, thus we present them in the sequel u : Du → T and ` : Dl → T with some alphabet T . Let us from this point of view [5]. construct a stateless WK automaton M that accepts L as follows. Let M = (V, %, {q}, q, {q}, δ), where δ is defined in Single stranded DNA molecules of the form u are called the following way: q ∈ δ q, x , for all pairs x ∈ D λ y λ u, upper dominos, while ones of the form λ are called lower v λ ∈ D dominos. The set of double stranded DNA molecules with y l, if u(x) = `(y). sticky end on the right side are denoted by R(V ): they are either of the form w u or w λ. By the construction, the application of the sticking opera- w λ w v tion in a coherent way is matched with the computing steps A simple regular sticker system is a pentuple of M , and thus, exactly those molecules can be generated (V, %, D by the given sticker system as the ones accepted by M . u, Dl, A), where • V is an alphabet, • % is the complementarity relation (we use identity in this 4. 50 → 30 WK AUTOMATA AND EXTER- paper), NAL CONTEXTUAL GRAMMARS • Du and Dl are sets of dominos that are associated to the In this section we present two new links between Watson- upper and lower strand, respectively, Crick automata and external contextual grammars. On the • A ⊂ R(V ) is a finite set of axioms. first hand, sensing 50 → 30 WK automata accept exactly the class of linear languages of the Chomsky hierarchy [10, The generation starts with an axiom and goes step by step. 11, 13, 14, 17, 18]. It is also known (see, e.g., [2]) that ex- Depending on the position of the sticky end of the actual ternal contextual grammars without choice generate exactly molecule, only dominos of the other strand may stick to it those languages which can be generated by linear grammar by filling that strand without gaps and maybe further ex- with exactly one nonterminal symbol. First, we complement panding it. The generation has finished when a full double these results as follows. stranded DNA is produced. The generated language is de- fined consequently [5, 15]. Theorem 2. If the language L is generated by external Those special cases are called sticker systems without ax- contextual grammars without choice such that the only axiom ioms, when A = λ to infer the fact that the molecules is the empty word λ, then L is accepted by a stateless sensing λ are built up only by dominos and the generation could start 50 → 30 WK automaton. from any dominos in this case. Proof. We prove by construction. Let EC = (V, {λ}, P ) Let (V, %, Du, Dl, A) be a simple regular sticker system. Let be an external contextual grammars without choice, where 641 P contains pairs (Ci, V ∗) with Ci = (ui, vi). Let M = [7] P. Leupold and B. Nagy. 50 → 30 Watson-Crick (V, ρ, {q}, q, {q}, δ) be a stateless 50 → 30 WK automaton automata with several runs. Fundamenta Informaticae with the identity relation on V as ρ and let δ be defined 104, pp. 71-–91, 2010. as follows based on P : q ∈ δ(q, ui) for each C [8] R. J. Lipton. DNA solution of hard computational v i. It is i easy to see that derivations, i.e., generations of words in EC problems. Science, 268(5210), pp. 542–545, 1995. correspond step by step in an opposite order to accepting [9] S. Marcus. Contextual grammars. Revue Roum. Math. computations in M and vice versa. Pures Appl., 14, pp. 1525—1534, 1969. [10] B. Nagy. On 50 → 30 sensing Watson-Crick finite automata. 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Typotex, Budapest, Hungary, 2014. [16] B. Nagy and S. Parchami. On deterministic sensing 5. CONCLUSIONS 50 → 30 Watson–Crick finite automata: a full hierarchy in 2detLIN. Acta Informatica 58 pp. 153–175, 2021. Languages that can be obtained by a simple regular sticker [17] B. Nagy and S. Parchami. 50 → 30 Watson-Crick system without axiom in a coherent way, are shown to be automata languages – without the sensing parameter. accepted by WK automaton with a sole state. On the other Natural Computing, online first, 2022. doi: hand, languages generated by external contextual grammar 10.1007/s11047-021-09869-9 without choice and with linear choice are related to lan- [18] B. Nagy, S. Parchami and H. M. M. Sadeghi. A new guages of sensing 50 → 30 WK automata. sensing 50 → 30 Watson-Crick automata concept. In: Proc. 15th Int. Conf. Automata and Formal 6. REFERENCES Languages, AFL 2017, EPTCS 252, pp. 195–204, 2017. [1] L. M. Adleman. Molecular computation of solutions to [19] S. 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Theory, DLT 2004, LNCS 3340, Springer, Berlin, Heidelberg, pp. 272—283, 2004. 642 Surrogate Component Approach for a Synchronization Problem Alejandro Olivas Alain Quilliot Hélène Toussaint González Labex IMOBS3 LIMOS UCA/CNRS Labex IMOBS3 LIMOS Lab, UCA/CNRS Clermont-Ferrand, France LIMOS Lab, UCA/CNRS Clermont-Ferrand, France Clermont-Ferrand, France alain.quilliot@uca.fr ABSTRACT cles, initially located at a depot Depot = 0, and required to We deal here with electric vehicles, provided in energy by perform VRP: Vehicle Routing Problem tours, that means to a local photovoltaic micro-plant, with limited storage and visit a set of stations J = {1, . . . , M } within a time horizon time-dependent production capacities. Our goal is to syn- [0, TMax ]. Moving from station j to station k requires ∆j,k chronize energy production and consumption. Because of time units and an amount Ej,k of energy. Recharge trans- the complexity of resulting bi-level model, we handle it by actions take place at the depot. An Elementary Trip is any short-cutting the production level through surrogate esti- VRP sub-tour that a vehicle may perform without recharg- mators, whose values are computed with the help of flexible ing at the depot. The fleet relies on a set B of identical pricing and machine learning devices. batteries, with capacity C and charge speed CS , initially lo- cated at Depot, and vehicles switch their battery every time Keywords they come back to Depot. This plug out/in operation is Operational Research, Combinatorial Optimization, Machine instantaneous and avoids that the vehicle waits for recharg- Learning ing. It comes that while the vehicles are running with active batteries, idle batteries are recharged at Depot before be- 1. INTRODUCTION ing used again by the vehicles. For any battery b in B, Vb denotes the energy load of b at time 0. Multi-level decisional [1] models usually involve several pla- yers, tied together by some hierarchical or collaborative links. In order to implement a self-consumption policy, Depot is They aim at providing scenario which would be the best provided with a PV-Plant, that means a photovoltaic faci- in case all the players accept a common rule (centralized lity which assigns the batteries to the vehicles and produces paradigm), or at searching for a compromise (collabora- energy that it distributes between the currently idle bat- tive paradigm). Standard approaches involve decomposition teries or that it sells to the market. In case this energy schemes, hierarchical (Benders, Stackelberg,...) or transver- is not enough, the PV-Plant can also buy energy to the sal (Lagrangean). Main difficulties are related to the re- market. The time space [0, TMax ] is divided into small pe- trieval of information from the different levels in order to riods i = 1, ..., N , all with same length p. We denote by make them interact, and to the collaborative issue, which CR, the recharge per period capacity, that means the quan- may impose the players to deal with incomplete informa- tity p · CS of energy which may be loaded into a battery tion. A trend, boosted by the rise of machine learning tech- during a period. We also denote by R nology [5], is to bypass some levels and replace them by i the expected pro- duction of the PV-Plant at period i, by A surrogate constraints or estimators. We follow this trend i the energy unit purchase price at period i, and by B here while dealing with the joint management of local pho- i the energy unit sale price. For technical reasons, a battery switch takes place tovoltaic energy [3] production and its consumption by a only at the junction between 2 periods, that means at a time fleet of electric vehicles [2, 4]. This problem arose in the con- t = p · i, i = 0, . . . , N . So resulting PV Prod VRP decision text of the activities of IMOBS3 (Innovative Mobility ) Labex problem, represented in the Figure 1, comes as follows: in Clermont-Ferrand, which conducts research on both au- tonomous electric vehicles and solar energy, and of the na- PV Prod VRP: Simultaneously schedule the vehicles and tional PGMO program promoted by power company EDF. the PV-Plant, in such a way that: So we consider here a fleet of K small identical electric vehi- • Every station is visited at least once by the fleet; • Every time a vehicle k comes back to Depot, it is as- signed a battery charged in such a way that it will make possible its next elementary trip; • The global energy load of the batteries does not to de- crease between the beginning and the end of the pro- cess. • Some global cost is minimized, which combines stan- dard VRP cost with the PV-Plant cost of energy self- 643 consumption. Any VRP decision means a collection Σ0 of scheduled trips σ = (π, I(π)) such that: - For any period i, Card({σ ∈ Σ0 s.t. i ∈ I(σ)}) ≤ K; (S1) - For any station j, Card({σ ∈ Σ0 s.t j ∈ S(σ)}) ≥ 1; (S2) If we consider as standard VRP cost of Σ0 the global riding time P T (σ) (Driver Cost ) then, a time versus money coef- σ ficient α being given, a bi-level setting of our PV Prod VRP problem comes as follows: PV Prod VRP Problem: Compute a collection Σ0 of sche- duled trips, such that (S1, S2) hold and which minimizes the sum α P T (σ) + V al P V P rod(Σ σ 0) where V al P V P rod is the optimal P V P rod(Σ0) value. Figure 1: The PV-Plant, the batteries and the vehicle fleet. 2. HANDLING PV_PROD_VRP WITH SURROGATE COMPONENTS In order to formalize, let us suppose that a collection Π0 of MILP formulation of PV PROD VRP is hardly practicable elementary trips π has been computed and that every such a and does not fit uncertain or collaborative contexts. So we trip π has been scheduled inside a set of consecutive periods try: I(π). We denote by Σ0 = {(π, I(π)), π ∈ Π0} the resulting set of scheduled trips σ = (π, I(π). For any trip π we denote • First approach: It aims at benchmarking. We solve by E(π) the energy that its requires, by T (π) its duration, PV Prod VRP through the MILP model restricted to and by S(π) the set of stations that it visits. We extend a set Σ0 of scheduled trips, pre-computed through suc- those notations to scheduled trips σ and set EMean(σ) = cessive applications of a randomized simple greedy pro- E(σ)/Card(I(σ)). Then, PV Prod resulting sub-problem is cedure. about the way the PV-Plant loads the batteries and assign • Second Approach: We short-cut the PV Prod level them to scheduled trips σ. through the introduction of surrogate constraints and estimators. PV Prod(Σ0) MILP (Mixed Integer Linear Program) Model: Compute: 2.1 Solving the PV_Prod_VRP bi-level model, • XA = (XA while partially short-cutting the slave i , i = 1, ..., N ), X B = (XB i , i = 1, ..., N ) and XD = (XD b,i, b ∈ B, i = 1, ..., N ): respectively PV_Prod level. the energy amount bought on the market, sold to the Our purpose here is to compute the scheduled trip set Σ0 market, and distributed to battery b by PV-Plant; without involving the PV-Plant. But, while the schedule • W = (Wb,i, b ∈ B, i = 0, ..., N ): the amount of energy σ → I(σ) must take into account prices Ai, Bi and produc- inside the battery b at the period i ; tion rates Ri, we can only say that a well-fitted collection Σ0 • U = Uσ,b, σ ∈ Σ0, b ∈ B : Uσ,b = 1 if the battery b is requires small amounts of both time and energy. This sug- assigned to the process σ; gests that we should distinguish between the design of the • δ = δb,i, b ∈ B, i = 1, ..., N : δb,i = 1 if the battery b is trip collection Π0 and the way we turn it into a collection Σ0 idle at period i. of scheduled trips. This leads us to the following parametric VRP Surrogate process: Objective function: P (A − B i i · X A i i · X B i ). Constraints: VRP Surrogate Parametric Algorithm: • For any b, i : Wb,i ≤ C and XD ≤ Initialize flexible scaling parameter γ; Not Stop; current best b,i CR · δb,i ; (R1) • For any b : Wb,0 = Vb; (R2) solution Best Sol is undefined; • P W V While Not Stop do b b,N ≥ Pb b; (R3) • For any i : R 1st step: Compute an ad hoc elementary trip collection i + X A i = XB i + P XD b b,i ; (R4) • For any b, i : (1 − δ Π0 which minimizes α · P T (π) + γ · P E(π); b,i) = P U π∈Π π∈Π σ s.t. i∈I(σ) σ,b ≤ 1 ; (P1) 0 0 2nd step: Turn Π • For any σ ∈ Σ 0 into a scheduled trip collection Σ0, 0 : P U b σ,b = 1. (P2) that means compute the period sets I(π), π ∈ Π • 0 in such For any b, i : Wb,i = Wb,i−1 + XD b,i a way that some surrogate constraints (SURR1) be sat- − P Emean(σ) · U σ s.t. i∈I(σ) σ,b; (P3) isfied and that some surrogate cost Φ(π → I(π) be min- imized; Explanation: (R1): We charge a battery b only if it is idle. 3rd step: Update γ and Stop; Solve P V P rod(Σ0) and (R3): The batteries must be globally loaded with at least update Best Sol. as much energy at the end of the whole process as at the beginning. (R4) tells the way energy is distributed between 2.2 Dealing with Step 1: A Branch and Cut sale, purchase and battery loading. (P1): b is active at Algorithm based upon Strong No Subtour period i only if has been assigned to a unique scheduled trip σ active at period i. (P2): any scheduled trip σ is assigned a constraints unique battery b. (P3) describes the evolution of a battery For any subset A of the station set J = {1, . . . , M }, we b from a period i − 1 to next period i. set: δ+(A) = {arcs (j, k) such that j / ∈ A and k ∈ A} and 644 Cl(A) = { arcs e = (j, k) s. t. at least j or k is in A}. Then 2.3 Dealing with Step 2: Surrogate the auxiliary Elementary Trip ILP model comes as follows: Components In order to enhance P V P rod(Σ0) feasibility, we impose Elementary Trip ILP model: the following surrogate necessary (but not sufficient) cons- Compute a (0, 1)-valued vector Z = (Zj,k, j, k = 0, ..., M ) traints: in such a way that : • For any period i : Card({σ ∈ Σ0 such that i ∈ I(σ)}) ≤ K; (S1) • For any j in {1, ...M } : P Z Z k j,k = Pj j,k = 1 ; (S2) • For any subset i0 = 1, ..., N : CR · P n(Σ0, i) + • For any subset A of {1, ...M } : i≤i0−1 Σ E(σ), where n(Σ C · P Z E bVb ≥ Pσ s.t. Start(σ)≤i 0, i) is the 0 (j,k)∈δ+(A) j,k ≥ P(j,k)∈Cl(A) j,k · Zj,k ; (SNS) number of scheduled trips σ idle at period i, and Start(σ) • Minimize α · (P Z Z j,k j,k · Tj,k ) + γ · (Pj,k j,k · Ej,k ). is the starting period of σ. (SURR1) Explanation: Above SNS: Strong No Sub-Tour constraints The constraint (SURR1) means that we must be able to not only forbid sub-tours in the usual sense, but also en- feed the batteries in such a way that trips becomes possible. sure us that vector Z represents a collection of elementary Then, in order to make possible the use of any surrogate esti- trips, that means of routes π from Depot to Depot such that mator Φ(π → I(π)), we implement Step 2 while relying on a E(π) ≤ C. non deterministic local search heuristic Scheduled T rip(Π0, Φ). So, what remains to be done is to discuss estimator Φ. Theorem 1: {0, 1} vector Z satisfies (S2, SNS) if and only if arcs (j, k) such that Z Defining Φ(Σ j,k = 1 define a collection Π0 of 0) according to a Pricing Mechanism. The idea sub-tours π here is that the cost of a schedule (π → I(π)) is determined 1, ..., πS with S = P Z k 0,k such that: by the distribution of above defined values n(Σ0, i). Let • For every s = 1, ..., S, π E = P E(π) be the global charge loaded into the bat- s starts from Depot = 0 and π∈Π0 ends into Depot, and spends less than C energy; teries and I = P ⌈T (π)/p⌉ be the number of periods π∈Π0 • Every station is visited exactly once by collection Π required by the trips of Σ0. If all batteries receive a same 0. charge EMean = E/I at every period when they are idle, then the cost of the production process is I ·QStand , where Constraints SNS may be separated in polynomial time through i,n(Σ0,i) application of a max flow (min cut) procedure. QStand i,n = Ai·(n·EMean−Ri) if n·EMean ≥ Ri and QStand i,n = Bi ·(n·EMean −Ri) else. This suggests us to express the sur- Sketch of the Proof: (S2, SNS) imply that Z gives rise to rogate cost Φ(π → I(π)) involved into the VRP Surrogate a collection τ of sub-tours τ algorithm as a sum P Q 0, ..., τS , and that if some tour i i,n(Σ0,i), where Qi,n is the estima- τ tion of the cost induced by n batteries in recharge (idle) at S spends more energy than capacity C, then a subset A of {0, . . . , M + 1} exists which makes Z violate (SNS). We period i. We notice that if n(Σ0, i) · EMean ≥ Ri, then Qi,n get our first statement. As for the second, we see that, Z should increase with Ai and that if n(Σ0, i) · EMean < Ri, (integral or rational) being given, separating (SNS) means then Qi,n should decrease as Bi increases. This suggests to searching for A ⊆ {1, ..., M } and B = {1, ..., M } − A, such set: that (*): • AMean = mean value Ai, i = 1, ..., N ; BMean = mean P Z Z ·E j,k∈B j.k · Ej,k + C · P(j,k)∈δ+(B) j,k < ∆ = Pj,k j,k value Bi, i = 1, ..., N ; So we construct a network GAux, whose node set is {0, 1, ..., • Qi,n = QStand · i,n (1 + ρ1(Ai − AMean)) if n(Σ0, i) · M + 1} and whose arc set may be written as U Aux = U ∪ EMean ≥ Ri, and Qi,n = QStand · i,n (1+ρ2(Bi −BMean)) Copy(U ) with: else, where ρ1 and ρ2 are 2 non negative flexible pa- rameters. • U = {all pairs (j, k), j, k = 0, ..., M } s.t Zj,k ̸= 0: such Computing Φ(Σ0) through a Neural Network N Energy. an arc u = (j, k) is provided with a capacity wu = Instead of relying on energy price coefficients Qi,n, we use Zj,k · (C − Ej,k); a neural network N Energy in order to provide us with the • With any arc e = (j, k) in U, we associate an arc u = quality of a scheduled trip collection Σ0. N Energy is im- Copy(e) = (j, M + 1): such an arc u = Copy(e) = plemented with the help of the TensorFlow open software (j, M + 1) is provided with a capacity wu = Zj,k · Ej,k. and trained with a large number (4000) of P V P rod(Σ0) Then arc set Copy(U) is the set of all arcs Copy(e), instances. It is designed as a convolutional neural network. e ∈ U . Such a network, whose main purpose is to be adaptable to inputs with flexible sizes, usually works in 2 (or more) steps: We conclude, by checking that searching for B such that In the first step, a same standard perceptron called convolu- (*) holds is equivalent to solving a Max Flow problem in tional mask is applied to fixed size neighbours of the compo- GAux. nents of the input vector IN = (INm, m ∈ M ), and yields an output vector OU T = (OU Tm, m ∈ M ). In the next Theorem 1 and related proof provide us with an efficient step, a pooling mechanism is applied to OUT, in order to separation procedure which opens the way to the implemen- compact it into the fixed size input of another perceptron tation of a Branch and Cut process. Still, because such a which computes the final output. In the present case this Branch and Cut approach remains difficult to use in case of final output is a number Θ between 0 and 1, such that the large size instances and in case of uncertainty, we also im- optimal value V AL P V P rod(Σ0) of P V P rod(Σ0) may be plement a heuristic Insertion/Removal (Build/Destroy) al- written V AL P V P rod(Σ0) = V al M in + Θ · (V al M ax − gorithm. V al M in), where Val Max and Val Min are respectively 645 lower and upper easy to compute bounds of V AL P V P rod(Σ0). the cost value of PV Prod VRP may be negative, due to More precisely we homogenize any input Σ0, A, B, R, V of the fact that the cost may become a profit. Also, we try P V P rod as a vector IN, with IN [i] = (A∗i, B∗i, R∗i, µ∗i, Qi, C∗, CR∗) as follows: Table 2: Behavior of the Price and Machine Learning based • A∗ VRP Surrogate Algorithms i = Ai/AM ean; B∗ i = Bi/Amean; • RMean = Mean values of coefficients R Inst. UB G W ML W Price i; • µ 1 -235.91 -193.38 -116.28 i = P EMean(σ); µ∗ σ s.t. i∈I(σ) i = µi/RM ean; 2 -1311.60 -835.27 -1165.42 • R∗I = Ri/RMean; Qi = n(Σ0, i)/Card(B); 3 248.43 409.91 631.02 • C∗ = C/RMean; CR∗ = CR/RMean. 4 1760.33 1861.24 2138.38 The convolutional mask CM works on any sub-vector IN ∗ i = 5 3742.12 1602.39 1900.69 (IN [i], . . . , IN [i + 4]), which means an input with 35 input arcs. It contains 3 inner layers, respectively with sizes 8, the Branch and Cut algorithm and the Insertion / Removal 4 and 2, and ends into an output layer, with 1 input value heuristic algorithm of Section 2.2 on the Elementary Trip OU T model, and retrieve in less that 1 CPU h: i. This network is complete in the sense that all 322 synaptic arcs are allowed, together with standard biased sig- • The lower and upper bounds LB BC and UB BC com- moid activation functions whose derivative value in 0 is equal puted by the algorithm; to 1/2. The pooling mechanism works by merging consecu- • The value Relax induced by the relaxation of the inte- tive values OU T grality constraint; i into a single value, in such a way it yields an intermediate vector AUX, with 13 entries, all with values • The number CUT of SNS cuts generated during the between 0 and 1, which we handle with a perceptron N Pool, Branch and Cut process; with intermediate layers with size 6 and 3, and a final layer • The value W Heur computed by the heuristic algo- with size 1. At the very end, we must learn 421 synaptic rithm. coefficients. • Related CPU time Time of the heuristic algorithm. The Branch and Cut algorithm was executed during 1 3. NUMERICAL EXPERIMENTS hour. Technical Context: We use libraries CPLEX12 (for ILP mo- Related results are contained into the Table 3. dels) and TensorFlow/Keras (for Machine Learning). Table 3: Behavior of the Branch and Cut Algorithm Instances: The main characteristics of an instance are: N = Inst. LB BC UB BC Relax CUT W Heur Time Number of periods, M = Number of stations, S = Expected 1 366.258 424.268 362.979 2917 428.08 1.19 number of elementary trips involved into a VRP solution, Q 2 362.481 470.942 359.901 904 470.50 5.41 = number of macro-periods, which are associated with gene- 3 421.34 528.725 420.884 712 534.73 10.38 ral trends in the production rate and in the market prices, L 4 1514.61 1809.3 1514.6 583 1776.16 28.30 = expected length of an elementary trip, µ = Battery Stress 5 2425.26 3372.26 2425.26 367 3025.93 41.79 coefficient, β = Recharge Stress coefficient, H = Production Stress coefficient and α = time versus money coefficient. Comments: Taken as a whole, solving PV Prod VRP while Stress is related to the difficulty that one may have in com- relying on surrogate component happens to be rather ef- puting the solution of the instance, in such a way that de- ficient. We also see that, even with Strong No Sub-Tour creasing the Stress parameters increases the difficulty. The constraints, the Elementary Trip model is difficult for large Table 1 shows the characteristics of the instances used dur- instances. The heuristic algorithm allows us to get close ing the experimentation. upper bounds to the Branch and Cut in reasonable time. Table 1: Characteristics of the instances 4. REFERENCES Instance N M S Q L µ β H α [1] S. Dempe, V. Kalashnikov, Pérez-Valdés, and 1 40 50 20 4 5 2 1.5 1 1.2 N. Kalashnykova. Bilevel Programming Problems 2 40 75 25 5 5 1.5 2 1.5 0.8 Theory. Springer, 2015. 3 40 100 32 4 3 2.5 1.5 0.8 1.2 [2] T. Erdelić and T. Carić. A survey on the electric vehicle 4 60 150 42 3 8 3 3 0.5 1.5 routing problem: variants and solution approaches. 5 60 200 55 5 10 2 1.5 0.75 1.2 Journal of Advanced Transportation, 2019, 2019. [3] S. Irani and K. R. Pruhs. Algorithmic problems in power management. ACM Sigact News, 36(2):63–76, Outputs: For every instance, we apply the VRP Surrogate 2005. resolution scheme while relying on both the pricing mecha- nism and the machine learning mechanism, performing the [4] G. Macrina, L. D. P. Pugliese, and F. Guerriero. The first VRP Surrogate step through the Insertion / Removal green-vehicle routing problem: a survey. In Modeling algorithm. We denote by W Price the value obtained with and Optimization in Green Logistics, pages 1–26. the pricing device and we denote by W ML the value ob- Springer, 2020. tained while involving Machine Learning. UB G denote an [5] J. Wojtusiak, T. Warden, and O. Herzog. Machine upper bound obtained through the first approach described learning in agent-based stochastic simulation: in Section 2. The Table 2 shows these results. When the Inferential theory and evaluation in transportation size of the instances increases, it tends to outperform the logistics. Computers & Mathematics with Applications, results produced by the global MILP model. Notice that 64(12):3658–3665, 2012. 646 Local reflection symmetry detection in Earth observation data David Podgorelec Luka Lukač Borut Žalik University of Maribor University of Maribor University of Maribor Faculty of Electrical Faculty of Electrical Faculty of Electrical Engineering and Computer Engineering and Computer Engineering and Computer Science Science Science Maribor, Slovenia Maribor, Slovenia Maribor, Slovenia david.podgorelec@um.si luka.lukac@student.um.si borut.zalik@um.si ABSTRACT of visual systems where individual regularities have been se- We propose a new algorithm which detects patterns with re- lected on the basis of their relevance [9]. This explains why flection symmetry in Earth observation data. It must con- symmetry has always inspired people in different fields, in- sider approximate symmetries, as the acquisition of input cluding arts, architecture, biology, medicine, mathematics, datasets is not able to provide exact pairs of symmetric el- and various engineering disciplines [1]. However, in con- ements. Therefore, we look for symmetries between voxels, trast to natural, almost self-evident symmetry perception not between the input points. Furthermore, the nature of processes in living beings, computer-aided symmetry detec- such data implies that the symmetric patterns in the top tion is anything but simple [1]. Machine learning approaches view are the most interesting and, thus, it suffices to detect are increasingly popular as everywhere else [8], but they rely symmetries with vertical symmetry planes. The symmetry heavily on training datasets, which are usually incomplete. detection may thus be split into horizontal voxel slices and Traditional constructive approaches for individual types of the results with the same symmetry plane are then merged. symmetries, particularly the reflection and rotational one, At the end, the resulting symmetries are ranked with respect still prevail. Symmetry can be global when it concerns the to the number of voxels involved. Early results obtained for whole object, or local when only parts of the scene are in- some voxelisations of two LiDAR datasets of different sizes corporated. A local symmetry containing a single connected are promising both in terms of the detection speed and qual- component is called partial symmetry. Furthermore, sym- ity of solutions. metry can be perfect (strong) or approximate (weak) [5]. Approaches of Žalik et al. [1] and Hruda et al. [4] are Categories and Subject Descriptors representatives of global reflection symmetry detection al- gorithms. Local (partial) symmetry is sometimes handled I.3.5 [Computing Methodologies]: Computer Graphics— by decomposing the scene into individual parts and then Computational Geometry and Object Modeling detecting global symmetry separately on each of them [7]. Cailliere et al. [2] presented a true local reflection symmetry General Terms detection operating on triangular meshes. In 2006 already, Algorithms, Performance, Theory Mitra et al. [5] presented a powerful general algorithm that detects different types of global and local symmetry. Keywords Approximate symmetry, voxelization, line segment, merging In this paper, a new algorithm is presented, predominantly designed to detect local reflection symmetries in Earth ob- 1. INTRODUCTION servation (EO) data. Section 2 illustrates the overall idea of the proposed approach, while section 3 experimentally An object is symmetric if there is a transformation (such as confirms its usability. Section 4 briefly summarizes the pre- translation, scaling, rotation, reflection, etc.) that maps it sented work and discusses future research challenges. onto itself [6]. The symmetry perception has been studied and demonstrated in humans, but also in birds, dolphins, apes and even honey bees [3]. It is assumed that symme- 2. METHODOLOGY try perception has become an integral part of the individ- The presented algorithm is predominantly designed to de- ual’s perceptual organization process during the evolution tect local reflection symmetries in EO and complementary geographic information systems (GIS) data. Current imple- mentation reads LiDAR (light detection and ranging) point clouds stored in LAS files only, but these data are immedi- ately voxelized and, thus, 3D or 2D raster grids may also be considered valid inputs. The algorithm is fully scalable, as the resolution of the voxelisation can vary from a few centimetres or even lower up to tens or hundreds of me- tres, depending on the data acquisition technology and the intended use. Furthermore, grayscale and colour raster im- 647 the ratios between the three sides of the bounding box are tried to be kept and, furthermore, the number of voxels in each coordinate direction must be above some user-defined threshold. Consequently, the actual number of voxels may be significantly lower than the value entered by the user. The material voxels are then identified in the grid. Each material voxel contains at least one point from the input point cloud. Theoretically, the symmetries should be identi- fied among these voxels, but this would result in numerous trivial solutions (e.g. “infinitely” many symmetries could be Figure 1: Concept of the new algorithm. found on a flat surface), so we further reduce the set of candi- dates for the symmetry detection by extracting the so-called interesting voxels. ages may be processed if colours are interpreted as altitudes. Whether these input datasets are 2D or 3D, they are mostly A voxel is considered interesting for further processing if its acquired downwards from satellites, airplanes, drones, etc. surroundings is not flat. We therefore test each material This means that much more data are collected from the vis- voxel against the patterns of 26 adjacent voxels and filter ible top surfaces than from the side and bottom surfaces. out the interesting ones which are not in the middle of a Furthermore, width and length of a considered geographic vertical, horizontal or diagonally slanted local surface. Such area are usually much greater than the range of altitudes, i.e. interesting voxels represent the input for the next step. bigger geographic areas are relatively flat. All these findings have the following implications on symmetry detection: 2.2 Clustering Our algorithm is designed to determine the basic symmetries • Due to sampling, points of an original“ part and mir- between pairs of LSs. Such a pair may be symmetric only if ” rored part rarely match exactly. both LSs have the same length. Furthermore, only the LSs which mainly pass through the interesting voxels are consid- • Due to higher density of acquired data on visible top ered in this step. It is worthless to compare two LSs of the sides, it is more likely to detect symmetric parts there. same length where one lies on the objects’ surfaces and the • Due to flatness“ of acquired areas, it is more likely to other penetrates the air. The default threshold for amount ” explore symmetries from above than from side. of material voxels in a regular LS is set to 80. Therefore, the “regular” LSs are extracted in this step and arranged into clusters due to their lengths. For these reasons, the algorithm is designed to detect locally symmetric patterns with approximate (and not the ideal) re- 2.3 Basic Symmetry Detection flection symmetries with regard to vertical symmetry planes As this step runs separately for each horizontal voxel slice, only. The latter implies that it is sufficient to detect symme- it appears quite straightforward. However, the distance tries in horizontal slices and then combine them on the basis between two voxels differs from the distance between two of the common detected symmetry planes. This constraint points inside these voxels, and the angle between two LSs crucially contributes to the affordable time complexity of the defined by four points differs from the angle between two algorithm in the EO data domain, although the majority of LSs defined by the centres of four voxels. Some user defined the algorithm’s steps can be easily generalized when we can tolerances must be considered in this step. Smaller voxels afford a slower execution. decrease relevance of these tolerances, but they significantly increase the time complexity. Note that this is computation- Bottom-up approach is another crucial feature of the pro- ally most demanding task with the theoretical time complex- posed algorithm. The idea is to find basic symmetries first ity O(n4), where n is the number of voxels. The previous and then construct larger ones by merging. In the context steps of extracting interesting voxels and grouping them into of the reflection symmetry, the basic symmetry is the sym- clusters not only prevent the calculation of trivial (meaning- metry of two geometric primitives, while the construction less) symmetries, but above all reduce the number of pairs means merging the symmetric pairs which share the same of LSs that need to be compared here. symmetry plane. Primitives may be points (voxels), line seg- ments, or more complex structures, and our choice are line segments. Core idea is that each line segment which appears 2.4 Merging in some symmetry should have a symmetric pair (copy) or The previous step determines all symmetry planes between more of them with the same length somewhere (in the slice). pairs of “regular” LSs. Next, we join all pairs that share a common plane of symmetry. This step simultaneously A rough outline of the algorithm is presented in Figure 1, considers both the clusters in a single slice and the results and a more detailed explanation of the individual steps is in different slices, as seen in the concept from Fig. 1. given in the subsections that follow. 2.5 Postprocessing 2.1 Voxelization After determining all symmetry planes and arranging all in- A user enters the total number of voxels, and the program teresting voxels into individual symmetries, the method con- computes subdivisions in each coordinate direction, where cludes its work by coupling the rest of the material (non- 648 Table 1: Results for two voxelizations of the Maribor Cathedral and two of the Slomšek Square Measure Cathedral Cathedral Square Square Points 11779 11779 35985 35985 Input voxels 500 1500 1000 2000 Voxels 384 1089 960 1680 Material 78 193 64 428 Interesting 37 64 129 132 Symmetries 45 152 1490 2340 Time [s] 0.38 1.86 48.73 55.93 interesting) voxels with respect to each symmetry plane. Furthermore, input points within the voxels participating in an individual symmetry may be checked, whether they have a mirrored sibling close enough on the other side of the symmetry plane. The same effect can be reached by increasing the number of voxels, which requires less effort for implementation but importantly slows down the perfor- mance. The classification of points on the two sides of the symmetry plane is based on a simple vector product test. Figure 2: The Maribor Cathedral – the strongest 3. RESULTS symmetry in the 384 voxels grid: a) side view, b) top view. Two point clouds read from LiDAR LAS files were used to demonstrate the performance of the algorithm. The first one represents Slomšek Square with the Cathedral of Saint John the Baptist to the east, the Rectorate of the University of Maribor to the west, the Slovene National Theatre to the north, and the building of the main Maribor Post office to the south. The second file contains the Cathedral extracted from the first one. Experiments were carried out on a PC computer with Intel Core i7-5820K and 32GB DDR4 RAM. The algorithm was programmed in C++ in QtCreator 7.0.1. Two different voxelizations of the Maribor Cathedral and two voxelizations of the Slomšek Square point cloud were used in the measurements. Fig. 2 shows the results for the strongest symmetry detected on the Maribor Cathedral point cloud, voxelized with 384 voxels (the input was set to 500). Red and blue points are those inside the detected symmetric pairs of voxels on both Figure 3: The Maribor Cathedral – the bottommost side of the symmetry plane (in black), while gray points are slice of 8 in the strongest symmetry in the grid of in material voxels not participating in this strongest sym- 384 voxels. metry. Fig. 3 shows only the points in the bottommost horizontal slice of voxels. By merging this slice and other 7 slices above it, the results from Fig. 2b are obtained. In an- other voxelization with 1089 voxels (the input se to 1500), the symmetry from Fig. 4 was detected as the strongest. Nearly the same symmetry was at the sixth place (out of 45) in the previous voxelization, while the strongest sym- metry from Fig. 2 and Fig. 3 is the 11th strongest (out of 152) in this different voxelization. In the top part of Table 1, a process of decreasing the number of entities from the LiDAR points to interesting voxels is demonstrated. Instead of 11779 points, only 37 or 64 interesting voxels were used in the basic symmetry detection step in both voxelizations of the Cathedral. Fig. 5 shows two different local reflection symmetries de- tected in the point cloud representing the Slomšek Square Figure 4: The Maribor Cathedral – the side view in in Maribor. The first one (Fig. 5a) is the strongest one ob- the strongest symmetry in the grid of 1089 voxels. tained from the voxelization with 960 voxels (the input set 649 Table 2: Number of points and voxels in individ- ual symmetries and the proportion of the latter (%) among the material voxels The Cathedral Slomšek Square Points Voxels % Points Voxels % Best 2493 26 33.33 7489 133 31.07 2nd 2129 18 23.08 5715 116 27.10 3rd 779 10 12.82 7428 106 24.77 Last 174 4 5.13 131 4 0.93 first voxelizes the point cloud, extracts the so-called inter- esting voxels, and then finds basic symmetries between pairs of line segments of the same length, separately in each hor- izontal voxel slice. Basic symmetries sharing the symmetry plane are then merged into larger ones. The first results are promising, but there is a plenty of work left in order to ulti- mately affirm the method. The code and particularly some data structures must be optimized for faster performance. Individual voxel slices could be easily processed in parallel. Besides this, the inputs and the results must be filtered to eliminate connected parts with the number of voxels below some threshold. Finally, the algorithm must be evaluated in comparison to state-of-the-art methods. 5. ACKNOWLEDGMENTS This research was funded by Slovene Research Agency un- Figure 5: Slomšek Square in Maribor: a) the der Research Project N2-0181 and Research Programme P2- strongest symmetry out of 1490 in the grid of 960 0041. voxels and b) the 68th strongest symmetry out of 2340 in the grid of 1680 voxels. 6. REFERENCES [1] B. Žalik, D. Strnad, S. Kohek, I. Kolingerová, A. Nerat, N. Lukač, and D. Podgorelec. A hierarchical universal to 1000), and the bottom one (Fig. 5b) was obtained from algorithm for geometric objects’s reflection symmetry the voxelization with 1680 voxels (the input set to 2000). detection. Symmetry, 14(5), 2022. Relatively low number of red in blue points indicates that this symmetry (Fig. 5b) is not among the strongest – it is [2] D. Cailliere, F. Denis, D. Pele, and A. Baskurt. 3d indeed at the 68th place out 2340. Note that this example mirror symmetry detection using hough transform. In was not chosen at random. Namely, the symmetry plane 2008 15th IEEE International Conference on Image here coincides with that of the Cathedral in Fig. 2. Processing, pages 1772–1775. IEEE, 2008. [3] M. Giurfa, B. Eichmann, and R. Menzel. Symmetry In each voxelization, the algorithm detects as many symme- perception in an insect. Nature, 382(6590):458–461, tries as possible. They are ranked with respect to the num- 1996. ber of voxels in a symmetry. Table 2 shows indicators of the [4] L. Hruda, I. Kolingerová, and L. Váša. Robust, fast three strongest and the weakest symmetries for the Cathe- and flexible symmetry plane detection based on dral with 384 voxels and Slomšek Square with 1680 voxels. differentiable symmetry measure. The Visual The former is described wit 11,779 LiDAR points and with Computer, 38(2):555–571, 2022. 78 material voxels, while the latter has 35,985 points and [5] N. J. Mitra, L. J. Guibas, and M. Pauly. Partial and 428 material voxels. approximate symmetry detection for 3d geometry. ACM Transactions on Graphics (TOG), 25(3):560–568, 2006. We have also carried out experiments with bigger point [6] M. Petitjean. A definition of symmetry. Symmetry: clouds. Of course, the execution time and the quality of Culture and Science, 18(2-3):99–119, 2007. detected symmetries depend on voxelization. For an urban [7] I. Sipiran, R. Gregor, and T. Schreck. Approximate area about 20 times the size of Slomšek Square, described symmetry detection in partial 3d meshes. In Computer by half a million points and voxelised with 5000 voxels, the Graphics Forum, volume 33, pages 131–140. Wiley algorithm took just over 1 hour. Online Library, 2014. [8] S. Tsogkas and I. Kokkinos. Learning-based symmetry 4. CONCLUSIONS detection in natural images. In European Conference on In this paper, we introduce a new algorithm for local reflec- Computer Vision, pages 41–54. Springer, 2012. tion symmetry detection. It was predominantly designed [9] C. W. Tyler. Human symmetry perception. Human for EO data processing, where it typically suffices to detect symmetry perception and its computational analysis, symmetries with vertical symmetry planes. The algorithm pages 3–22, 1996. 650 Approximate Keys and Functional Dependencies in Incomplete Databases With Limited Domains–Algorithmic Perspective [Extended Abstract] ∗ Attila Sali Munqath Alattar Alfréd Rényi Institute of Mathematics ITRDC, University of Kufa, Iraq and Department of Computer Science, munqith.alattar@uokufa.edu.iq Budapest University of Technology and Economics Budapest, Hungary sali.attila@renyi.hu ABSTRACT the sense that for any rational number 0 ≤ p < 1 there are q A possible world of an incomplete database table is obtained tables of an arbitrarily large number of rows and a constant by imputing values from the attributes (infinite) domain number of columns that satisfy g3 − g5 = p . A possible q to the place of NULL s. A table satisfies a possible key or world is obtained usually by adding many new values not possible functional dependency constraint if there exists a occurring in the table before. The measure g5 measures the possible world of the table that satisfies the given key or smallest possible distortion of the active domains. We study functional dependency constraint. A certain key or func- complexity of determining these approximate measures. tional dependency is satisfied by a table if all of its possible worlds satisfy the constraint. Recently, an intermediate con- Categories and Subject Descriptors cept was introduced. A strongly possible key or functional H.2 [Database Management]: Miscellaneous; F.2 [Analysis of dependency is satisfied by a table if there exists a strongly Algorithms and Problem Complexity]: Miscellaneous possible world that satisfies the key or functional depen- dency. A strongly possible world is obtained by imputing values from the active domain of the attributes, that is from General Terms the values appearing in the table. In the present paper, we Theory study approximation measures of strongly possible keys and FDs. Measure g3 is the ratio of the minimum number of tu- Keywords ples to be removed in order that the remaining table satisfies Strongly possible functional dependencies, Strongly possible the constraint. We introduce a new measure g5, the ratio of keys, incomplete databases, approximate functional depen- the minimum number of tuples to be added to the table so dencies, approximate keys. the result satisfies the constraint. g5 is meaningful because the addition of tuples may extend the active domains. We prove that if g 1. INTRODUCTION 5 can be defined for a table and a constraint, then the g3 value is always an upper bound of the g5 value. The information in many industrial and research databases However, the two measures are independent of each other in may usually be incomplete due to many reasons. For ex- ample, databases related to instrument maintenance, med- ∗Research of the second author was partially supported by ical applications, and surveys [8]. This makes it necessary the National Research, Development and Innovation Office to handle the cases when some information missing from a (NKFIH) grants K–116769 and SNN-135643. This work was database and are required by the user. Imputation (filling also supported by the BME- Artificial Intelligence FIKP in) is one of the common ways to handle the missing values grant of EMMI (BME FIKP-MI/SC) and by the Ministry [13]. of Innovation and Technology and the National Research, Development and Innovation Office within the Artificial In- telligence National Laboratory of Hungary. In the present paper the classical relational model is consid- ered that is the underlying concept of practical SQL database systems. The database is considered as a table, where rows (tuples) represent individual records, while columns corre- spond to properties or attributes. Important properties of these tables are the integrity constraints they (must) sat- isfy. In particular, keys and functional dependencies are the most common ones of those. An attribute set is a key if it determines all other attribute values in individual records, while functional dependency X → Y means that the values in attributes of X determine the values in attributes of Y . 651 A new approach for imputing values in place of the missing that SQL allows multiple occurrences of tuples. Of course, information was introduced in [3], to achieve complete data the order of the tuples in an instance is irrelevant, so math- tables, using only information already contained in the SQL ematically speaking we consider a multiset of tuples as an table attributes (which are called the active domain of an instance. For a tuple tr ∈ T and X ⊂ R, let tr[X] be the attribute). Any total table obtained in this way is called a restriction of tr to X. strongly possible world. We use only the data shown on the table to replace the missing information because in many It is assumed that ⊥ is an element of each attribute’s domain cases there is no proper reason to consider any other at- that denotes missing information. tr is called V -total for a tribute values than the ones that already exist in the table. set V of attributes if ∀A ∈ V , tr[A] ̸= ⊥. Also, tr is a total Using this concept, new key and functional dependency con- tuple if it is R-total. t1 and t2 are weakly similar on X ⊆ R straints called strongly possible keys (spKeys) and strongly denoted as t1[X] ∼w t2[X] defined by Köhler et.al. [12] if possible functional dependencies (spFDs) were defined in [5, 4] that are satisfied after replacing any missing value (NULL) with a value that is already shown in the corresponding at- ∀A ∈ X (t tribute. In Section 2, we provide the formal definitions of 1[A] = t2[A] or t1[A] = ⊥ or t2[A] = ⊥). spKeys and spFDs. Furthermore, t1 and t2 are strongly similar on X ⊆ R de- The present paper continues the work started in [5], where noted by t1[X] ∼s t2[X] if an approximation notion was introduced to calculate how close any given set of attributes can be considered as a key. A classical measure is the ration of tuples needed to be re- ∀ moved. Tuple removal may be necessary because the active A ∈ X (t1[A] = t2[A] ̸= ⊥). domains do not contain enough values to be able to replace For the sake of convenience we write t1 ∼w t2 if t1 and t2 are the NULL values so that the tuples are pairwise distinct on weakly similar on R and use the same convenience for strong a candidate key set of attributes K. In the present paper, similarity. Let T = (t1, t2, . . . ts) be a table instance over R. we introduce approximation measures of spKeys and spFDs Then, T ′ = (t′1, t′2, . . . t′s) is a possible world of T , if ti ∼w t′i by adding tuples. Adding a tuple with new unique values for all i = 1, 2, . . . s and T ′ is completely NULL -free. That will add more values to the attributes’ active domains, thus is, we replace the occurrences of ⊥ with a value from the some unsatisfied constraints may get satisfied. Adding tu- domain Di different from ⊥ for all tuples and all attributes. ples is only meaningful for strongly possible worlds. Earlier A active domain of an attribute is the set of all the distinct concept of possible worlds when any value of the attribute values shown under the attribute except the NULL. Note that domain could be added is not appropriate, as adding tuples this was called the visible domain of the attribute in papers does not change the range of values usable for imputation. [3, 4, 5, 2]. However, for strongly possible constraints the minimum ra- tio of tuples added to satisfy the constraint shows a smallest possible extension such that the constraint holds. Definition 1. The active domain of an attribute Ai (V DT i ) is the set of all distinct values except ⊥ that are already used We denote by g3 the minimum ratio of necessary tuple dele- by tuples in T : tions and g5 is the minimum ratio of necessary tuple ad- V DT ditions. These two measures were shown to be basically i = {t[Ai] : t ∈ T } \ {⊥} for Ai ∈ R. independent of each other in [1]. In the present paper we review these results then turn our attention to interesting To simplify notation, we omit the upper index T if it is clear algorithmic and complexity problems involving the two ap- from the context what instance is considered. proximation measures. The structure of the paper is as fol- lows. Section 2 contains the necessary definitions, Section 3 While a possible world is obtained by using the domain val- discusses some related work. Section 4 reviews the defi- ues instead of the occurrence of NULL, a strongly possible nitions and main theorems about approximation measures. world is obtained by using the active domain values. Subsection 4.2 contains the new results about complexity questions. Finally, Section5 includes some summary and concluding remarks. Definition 2. A possible world T ′ of T is called a strongly possible world (spWorld) if t′[Ai] ∈ V DT i for all t′ ∈ T ′ and 2. DEFINITIONS Ai ∈ R. Let R = {A1, A2, . . . An} be a relation schema. The set of all the possible values for each attribute Ai ∈ R is called the The concept of strongly possible world was introduced in [3]. domain of Ai and denoted as Di = dom(Ai) for i = 1,2,. . . n. A strongly possible worlds allow us to define strongly possible Then, for X ⊆ R, then DX = Q Di. keys (spKeys) and strongly possible functional dependencies ∀Ai∈K (spFDs). An instance T = (t1,t2, . . . ts) over R is a list of tuples such that each tuple is a function t : R → S dom(A A i) and Definition 3. A strongly possible functional dependency, i ∈R t[Ai] ∈ dom(Ai) for all Ai in R. By taking a list of tuples in notation X →sp Y , holds in table T over schema R if we use the bag semantics that allows several occurrences of there exists a strongly possible world T ′ of T such that T ′ |= the same tuple. Usage of the bag semantics is justified by X → Y . That is, for any t′1, t′2 ∈ T ′ t′1[X] = t′2[X] implies 652 t′1[Y ] = t′2[Y ]. The set of attributes X is a strongly possible if there exists a subset S of the tuples T such that T \ S key, if there exists a strongly possible world T ′ of T such satisfies sp ⟨K⟩, and |S|/|T | ≤ a. The minimum a such that that X is a key in T ′, in notation sp⟨X⟩. That is, for any asp− a ⟨K ⟩ holds is denoted by g3(K ). t′1, t′2 ∈ T ′ t′1[X] = t′2[X] implies t′1 = t′2. The g3 approximation measure for spKeys was introduced If T = {t1, t2, . . . , tp} and T ′ = {t′1, t′2, . . . , t′p} is an spWorld in [5]. In this section, we introduce a new approximation of it with ti ∼w t′i, then t′i is called an sp-extension or in measure for spKeys. short an extension of ti. Let X ⊆ R be a set of attributes and let ti ∼w t′i such that for each A ∈ R : t′i[A] ∈ V D(A), Definition 5. Attribute set K is an add-approximate strongly then t′i[X] is an strongly possible extension of ti on X (sp- possible key of ratio b in table T , in notation asp+ ⟨K⟩, if extension) b there exists a set of tuples S such that the table T S satisfies 3. RELATED WORK sp ⟨K⟩, and |S|/|T | ≤ b. The minimum b such that asp+ ⟨K⟩ b holds is denoted by g5(K). Giannella et al. [9] measure the approximate degree of func- tional dependencies. They developed the IFD approxima- tion measure and compared it with the other two measures: Definition 6. For the attribute sets X and Y , σ : X →sp g3 (minimum number of tuples need to be removed so that Y is a remove-approximate strongly possible functional de- the dependency holds) and τ (the probability of a correct pendency of ratio a in a table T , in notation guess of an FD satisfaction) introduced in [11] and [10] re- T |=≈− a X →sp Y , if there exists a set of tuples S such that spectively. They developed analytical bounds on the mea- the table T \ S |= X →sp Y , and |S|/|T | ≤ a. Then, g3(σ) sure differences and compared these measures analysis on is the smallest a such that T |=≈− a σ holds. five datasets. The authors show that when measures are meant to define the knowledge degree of X determines Y (prediction or classification), then IF D and τ measures are Definition 7. For the attribute sets X and Y , σ : X →sp more appropriate than g Y is an add-approximate strongly possible functional depen- 3. On the other hand, when mea- sures are meant to define the number of ”violating” tuples in dency of ratio b in a table T , in notation T |=≈+ X → b sp Y , an FD, then, g if there exists a set of tuples S such that the table T ∪ S |= 3 measure is more appropriate than I F D and τ . This paper extends the earlier work of [5] that utilized X →sp Y , and |S|/|T | ≤ b. Then, g5(σ) is the smallest b the g such that T |=≈+ σ holds. 3 measure for spKeys by calculating the minimum num- b ber of tuples to be removed from a table so that an spKey holds if it is not. The same paper proposed the g 4.1 Relation between 4 measure g3 and g5 measures that is derived from g3 by emphasizing the effect of each The following Proposition is used to prove Proposition 2. connected component in the table’s corresponding bipartite graph (where vertices of the first class of the graph represent Proposition 1. [1] Let T be an instance over schema R the table’s tuples and the second class represent all the pos- and let K ⊆ R. If the K-total part of the table T satisfies sible combinations of the attributes’ active domains). In this the key sp ⟨K⟩, then there exists a minimum set of tuples U paper, we propose a new measure g5 to approximate FDs by to be removed that are all non-K-total so that T \ U satisfies adding new tuples with unique values rather than deleting sp ⟨K⟩ . tuples as in g3. In [14], Jef Wijsen summarizes and discusses some theoretical developments and concepts in Consistent query answering CQA (when a user queries a database that Proposition 2. [1] For any K ⊆ R with |K| ≥ 2, we is inconsistent with respect to a set of constraints). Database have g3(K) ≥ g5(K). repairing was modeled by an acyclic binary relation ≤db on the set of consistent database instances, where r1 ≤db r2 means that r Apart form the previous inequality, the two measures are 1 is at least as close to db as r2. One pos- sible distance is the number of tuples to be added and/or totally independent for spKeys. removed. In addition to that, Bertossi studied the main con- cepts of database repairs and CQA in [6], and emphasis on Theorem 1. [1] Let 0 ≤ p < 1 be a rational number. tracing back the origin, motivation, and early developments. q Then there exist tables over schema {A1, A2} with arbitrarily J. Biskup and L. Wiese present and analyze an algorithm large number of rows, such that g3({A1, A2})−g5({A1, A2}) = called preCQE that is able to correctly compute a solution p . instance, for a given original database instance, that obeys q the formal properties of inference-proofness and distortion minimality of a set of appropriately formed constraints in Unfortunately, the analogue of Proposition 1 is not true for [7]. spFDs, so the proof of the following theorem is quiet in- volved. 4. APPROXIMATION OF STRONGLY POS- SIBLE INTEGRITY CONSTRAINTS Theorem 2. [1] Let T be a table over schema R, σ : For examples of the following definitions see [1]. X →sp Y for some X, Y ⊆ R. Then g3(σ) ≥ g5(σ). Definition 4. Attribute set K is an approximate strongly Theorem 3 is proven by a construction [1] similar to the possible key of ratio a in table T , in notation asp− a ⟨K ⟩, proof of Theorem 1. 653 Theorem 3. [1] For any rational number 0 ≤ p < 1 can be created by extending a maximum matching of G⋆ q there exists tables with an arbitrarily large number of rows greedily to the vertices (tuples) in T \ Tj . and bounded number of columns that satisfy g3(σ) − g5(σ) = p for σ : X → SpKey-g5: To check whether g q sp Y . 5(K ) ≤ q it is enough to add ⌊q|T |⌋ pairwise distinct tuples with pairwise distinct new 4.2 Complexity problems values and then check the satisfaction of sp⟨K⟩ in polyno- mial time in the extended table. Definition 8. The SPKey problem is the following. Input Table T over schema R and K ⊆ R. Question Is it true that T |= sp⟨K⟩? The SPKeySystem problem is the following. Input Table T over schema R and K ⊆ 2R. Example. Let R = {A1, A2, A3}, K1 = {A1, A2}, K2 = Question Is it true that T |= sp⟨K⟩? {A2, A3}. The SPFD problem is the following. A1 A2 A3 Input Table T over schema R and X, Y ⊆ R. t1 1 ⊥ 1 Question Is it true that T |= X →sp Y ? T = t2 1 2 2 t3 2 1 1 t4 2 1 1 The following was shown in [4]. T \ {t4} |= sp⟨K1⟩ and T \ {t4} |= sp⟨K2⟩, but the spWorlds are different. In particular, this implies that for K we have Theorem 4. SPKey∈P, SPkeySystem and SPFD are NP- g3(K) > max{g3(K) : K ∈ K} On the other hand, trivially complete g3(K) ≥ max{g3(K) : K ∈ K} holds. This motivates the following theorem. However, the approximation measures raise new, interesting algorithmic questions. Theorem 6. Let Table T over schema R and K ⊆ 2R. The problem Max-g3 defined as Is g Definition 9. The SpKey-g3 problem is the following. 3(K) = max{g3(K ) : K ∈ K}? is NP-complete. Input Table T over schema R, K ⊆ R and 0 ≤ q < 1. Question Is it true that g3(K) ≤ q in table T ? The SpKey-g5 problem is the following. Proof. The problem is in NP, a witness consists of a set Input Table T over schema R, K ⊆ R and 0 ≤ q < 1. of tuples U to be removed, an index j : |U| = g |T | 3(Kj ), also Question Is it true that g5(K) ≤ q in table T ? an spWorld T ′ of T \ U such that each Ki is a key in T ′. Verifying the witness can be done in three steps. Theorem 5. Both, SpKey-g3 and SpKey-g5 are in P. 1. g3(Kj ) ̸≤ |U|−1 is checked in polynomial time using |T | Theorem 5. Proof. SpKey-g3: Let bipartite graph G = (T, T ⋆; E) 2. For all i ̸= j check that g using again be defined as in [4]. T ⋆ is the set of sp-extensions of tu- 3(Ki) ≤ |U | |T | ples in T on K, {t, t⋆} ∈ E ⇐⇒ t⋆ is an extension of Theorem 5. t. Then T \ X |= sp⟨K⟩ iff there exists a matching cov- 3. Using standard database algorithms check that ∀i : Ki ering T \ X in G. Thus, X is a minimum set of tuples is a key in T ′. to be removed iff |T \ X| = ν(G), the matching number of G. This gives us g3(K) = |T |−ν(G) , so determination |T | of g On the other hand, the SPKeySystem problem can be Karp- 3(K ) is equivalent with finding ν (G). The only prob- lem is that |T ⋆| is usually of exponential size. In order to reduced to the present question as follows. First check for avoid exponential sized bipartite graph we only generate as each Ki ∈ K separately whether sp⟨Ki⟩ holds, this can be many extensions as needed.For the sake of simplicity as- done in polynomial time. If ∀i : T |= sp⟨Ki⟩ then give K sume that K = {A and T as input for Max-g3. It will answer Yes iff T |= 1, A2, . . . , Ab}. Let T = {t1, t2 . . . tm} and ℓ(t sp⟨K⟩. However, if ∃i : T ̸|= sp⟨K i) = |{t⋆ ∈ V D1 × V D2 × . . . × V Db : t⋆ ∼w ti[K ]}|. i⟩, then give the example Note that ℓ(t above as input for Max-g3. Clearly both problems have No i) = Q |V D j : t j |, hence these values i [Aj ]=⊥ answer. can be calculated by scanning T once and using appropriate search tree data structures to hold values of visible domains of each attribute. Sort tuples of T in non-decreasing ℓ(t 5. CONCLUSIONS i) order, i.e. assume that ℓ(t1) ≤ ℓ(t2) ≤ . . . ≤ ℓ(tp). Let In the present paper we treat approximation measures of j = max{i : ℓ(ti) < i} and Tj = {t1, t2, . . . tj }, furthermore keys and functional dependencies in SQL database tables T ⋆ j = {t⋆ : ∃t ∈ Tj : t⋆ ∼w t[K ]} ⊆ V D1 × V D2 × . . . × V Db. with null values. The strongly possible world semantics Note that |T ⋆| ≤ 1 j j(j − 1). If ∀i = 1, 2, . . . , m : ℓ(t is used, that is only values from the active domains of at- 2 i) ≥ i, then define j = 0 and T ⋆ j = ∅. Let G⋆ = (Tj , T ⋆ j ; E⋆) be the tributes are allowed to be imputed in place of the null values. induced subgraph of G. Clearly ν(G) ≤ ν(G⋆) + |T \ Tj |. This semantics avoids unnecessary distortions of domains, On the other hand, a matching of G of size ν(G⋆) + |T \ Tj | since the active domain of an attribute is the set of values 654 that actually occur in the table. A classical approximation functional dependencies from relations. Theoretical measure of an integrity constraint is that what percentage Computer Science, 149(1):129–149, 1995. of the tuples must be deleted in order to that the remain- [12] H. Köhler, U. Leck, S. Link, and X. Zhou. Possible ing table satisfies the constraint. This is usually denoted by and certain keys for sql. The VLDB Journal, g3. The strongly possible world semantics allows to intro- 25(4):571–596, 2016. duce a new approximation measure, namely by adding new [13] W. Lipski Jr. On databases with incomplete tuples the active domains can be extended and so the in- information. Journal of the ACM (JACM), tegrity constraints may be made valid in that way, as well. 28(1):41–70, 1981. The minimum set of tuples to be added is a minimum exten- [14] J. Wijsen. Foundations of query answering on sion of the current strongly possible world(s) to one, which inconsistent databases. ACM SIGMOD Record, satisfies the given constraint. The percentage of the neces- 48(3):6–16, 2019. sary new tuples is denoted by g5. It was shown earlier that for keys and functional dependencies g3 ≥ g5, but otherwise they are independent. The approximation measures give rise to new algorithmic problems and complexity questions. The new results of the present note are about the complexity to determine g3(K) and g5(K) for a key constraint K. Also a natural decision problem about system of keys is investi- gated and it is shown to be NP-complete. 6. REFERENCES [1] M. Al-Atar and A. Sali. Approximate keys and functional dependencies in incomplete databases with limited domains. 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Approximate inference of 655 Building energy demand regression Tamás Storcz István Kistelegdi Zsolt Ercsey Department of Systems University of Pécs, János Department of Systems and Software Szentágothai Research and Software Technologies, University of Centre, Energy Design Technologies, University of Pécs, Boszorkány u. 2, Research Group, Ifjúság u. Pécs, Boszorkány u. 2, 7624 Pécs, Hungary, 20, 7624 Pécs, Hungary, 7624 Pécs, Hungary, storcz.tamas@mik.pte.hu kistelegdisoma@mik.pte.hu ercsey.zsolt@mik.pte.hu ABSTRACT thermal insulation is, but artificial heating type and organization is not taken into consideration. In the paper the applicability of regression models Based on priorities specified by architect experts, for building heating energy estimation is from the collection of optimization aims, annual examined. During the experiment, regression heating energy demand minimization comes first. models were created to estimate annual heating energy demand of generic family houses. Non- Complex and computation-intensive simulations linearity of regression models was enhanced by could be replaced by multivariate linear creating non-linearly correlated new input regression. First test resulted bad regression variables. Then performance of generated models accuracy, because as expected, the estimated was measured and compared. As a result, energy demand function is not linear. But when multilayer dense neural net model with original increasing non-linearity of the model by enhance input parameters was proposed. Its performance it with max. 3rd power of multiplicative was almost equal to linear regression with combination of input variables, the accuracy of extended input variables, but its structural and multivariate linear regression model grew above functional flexibility makes the neural network 0.95 of R2 points, which is high enough to be applicable in wider range of tasks. accepted by architect experts. But increasing the number of input variables in a Keywords non-linear extent, makes the model much more Heating energy, Regression, Neural network, complex meanwhile the new input features are Regression tree not interpretable by experts. The proposed dense neutral network-based INTRODUCTION regression model is generated in 346 seconds. The created model calculates 3500 (train) Heating energy demand determination by estimations in 0.12 second and 1500 (test) simulation for a family house by a special estimations in 0.05 seconds. Its performance in energetic simulation software requires time accuracy, 0.96 R2 is also acceptable by architect consuming setup and calculation per each experts. The model operates on the initial input building configuration. For energy optimization, a variables, no need for non-linearity addition by lot of simulations must be done, therefore increasing number and complexity of input. speeding up the process would be very helpful. Required non-linear features were extracted by the network in the training process. Besides, its Investigated simulations apply the same, generic structural flexibility opens possibilities of engineering setup, since finding optimal building extended applications. configurations and construction parameters are in the focus of the experiment series. Therefore, 656 ENERGY REGRESSION special properties (convex edges and vertices, side walls, floors, roofs, etc.) were used as The main aim of regression models is to independent input variables. approximate unknow or known but complex correlation of descriptor and response variables. Regression is a widely used statistical method [4], Such procedures are applied in all fields of in which the aim is to model the relation between science; thus, their application is not new in the descriptors and the dependent variable. architectural energetics. Linear regression Peña-Guzmán and Rey [1] applied several types Linear regression [5] is a special case of generic of linear regression models to estimate future regression, in which dependent variable is development of residential electric power generated as linear combination of descriptor consumption with higher than 0.93 R2 accuracy. variables, as first-order Taylor series. For parameter determination in model generation, Mehedintu et al. [2] also used R2 score for most commonly the least squares method is used. efficiency measurement of polynomial and auto Heating energy demand of family houses is a regression methods. They applied these non-linear function. Definition of linear regression methods estimate the rate of total regression method enables dependency between energy consumption and its part from renewable its input variables, therefore multiplicative sources with higher than 0.91 score. combination of inputs can be added to increase input complexity. Difficulty of this is the Mohammed et al. [3] estimated energy demand of determination of maximum power of these school facilities. For the creation of linear combinations. As stated in the results, application regression model, 350 samples were used for of maximum 3rd power provides more than 0.95 training and 35 for testing. The accuracy of of R2 score. generated model was higher than 90%. Decision tree Regression trees are special decision trees [6] for REGRESSION MODELS regression tasks. A decision tree is generated by a recursive binary partitioning process, which Descriptive data results internal nodes of the tree as decision nodes. Building configurations can be used as input These contain a test of the value of a specific variables only if an appropriate representation is input variable. The terminal nodes are the found for the blueprints. To help creation of this predicted output variable values. representation, the building is created from equal Keys of regression tree generation are first the size boxes joined on sides conforming predefined selection of the input variable for the decision – architectural rules. what to test. Next the selection of the separator Figure 1. shows a valid building configuration. value to test for. The idea behind the selection is the minimalization of variance of subspaces resulted by the split of decision. For measuring the variances, the following methods are used: • Mean Absolute Error based on L1 distance • Mean Squared Error based on L2 distance Figure 1: Building configuration example • Poisson method Multivariate regression models cannot handle close relation of input variables (like coordinate Finally for the terminal nodes the predicted response value must be selected. This is done by triplets) therefore instead of using 3D coordinates averaging the group of samples covered by the of building components, count of details with terminal node. 657 Benefits of regression trees: designed 167 configuration of valid family • greedy algorithm houses of the same size. Then had to equip those • results good approximation with architectural (wall window ratio and • short execution time – low resource needs orientation) and engineering (thermal insulation, • well understandable decisions heating system) components Then using weather data from local statistics of many years annual Drawbacks of regression trees: energy demand simulation must be done. • not robust – sensitive to training data Simulation outputs are generated by changes summarization of daily demands. • creation of optimal tree is NP-complete Using 70% of these samples (3507) 5 different • type of models were created: high chance for overfitting - linear regression - decision tree with L1 metric Dense neural net - decision tree with L2 metric Neural net regression model [7] is inspired by - decision tree with Poisson metric nerve system and based on universal - dense neural net with 1 hidden layer approximation theorem. 3 versions were generated from all 5 model types, In terms of its structure, consists of independent using different inputs: analogue processing units which are organized - default inputs into connected layers. The first layer of the - inputs extended with max. 2nd power of network is called input, the last is the output, and multiplicative combination layer between them (if any) is called hidden layer. - inputs extended with max. 3rd power of Figure 2. shows the schematic model of a multiplicative combination network with one hidden layer and l, m, n processors in input, hidden and output layers. That result 15 different model classes. To get rid of performance differences caused by randomization, 25 instances were generated from all 15 model classes. All 375 model instances were evaluated, then individual evaluations were averaged on classes. MODEL EVALUATION For better evaluation of model instance Figure 2: Neural net with 3 layers performances, a calculation of a single value is required for all instances. This single value must Processors of consecutive layers are fully represent the approximation errors of each connected, but there are no connections between individual tests. R2 metric is widely used in processors of same or non-consecutive layers. statistics and regression analyses was applied. As The individual elements first calculate weighted stated in equation 1, it conforms aforementioned sum of their inputs, then generate their output requirement to represent individual using an activation function. For providing the approximation errors. non-linearity and to support the learning procedure, special activations could be chosen. ∑(𝑦 − 𝑦̃)2 𝑅2 = 1 − Equation 1 ∑(𝑦 − 𝑦̅)2 MODEL GENERATION where y is the value to approximate, 𝑦̅ is its average and 𝑦̃ is the approximation. For the model generation, 5010 samples were created by IDA ICE energy demand simulation In addition to R2 score absolute and relative software. Through simulations, architect experts 658 (relative to the value to approximate) error [3] Mohammed, A., Alshibani, A., Alshamrani, average and their standard deviation also were O., Hassanain, M., A regression-based model measured. for estimating the energy consumption of school facilities in Saudi Arabia. Energy & RESULTS Buildings. 2021 vol. 237, 110809 [4] Sarstedt, M., Mooi, E. Regression Analysis. A After analysing averages and accuracy metrics of Concise Guide to Market Research. pp 193- data groups, it can be stated that linear regression 233. Springer Texts in Business and with 3rd and 2nd power of input variables and Economics 2014 ISBN: 978-3-642-53964-0 dense neural network with 1st (default) input had [5] Heiberger R., M., Holland B. Linear almost same performance, around 0.96 R2 score. Regression by Least Squares in book Score of all other model classes were below 0.75, Statistical Analysis and Data Display 2015 therefore they were rejected. pp. 235-262, Springer Averages of absolute errors of estimations for all [6] Loh, W.Y. Classification and regression trees models are negligible compared to the annual 2011. Wiley interdisciplinary reviews: Data demands, but only for the previously selected 3 Mining and KnowledgeDiscovery, 1(1), 14- model classes did the standard deviance of 23. estimation error stayed below 500kWh/year. [7] Malte, J. Artificial neural network regression models: Predicting GDP growth. 2018. CONCLUSION HWWI Research Paper, No. 185, Hamburgisches WeltWirtschaftsInstitut As a final conclusion, it is stated that linear (HWWI), Hamburg regression with higher power of input and dense neural net with default input perform the same. But for model selection, structural flexibility is also taken into consideration. And linear regression model cannot be enhanced in the future. In the other hand, neural network structure can be extended or with more processors of the same type or different type of processor layers (convolutional, recurrent). Therefore, the proposed model is the dense neural network with 1 hidden layer. REFERENCES [1] Peña-Guzmán C., Rey J. Forecasting residential electric power consumption for Bogotá Colombia using regression models, Energy Reports, (2020) vol. 6 sup. 1., pp. 561-566 [2] Mehedintu, A., Sterpu, M., Soava, G Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union. Sustainability 2018, 10(5), 1515 659 Clique relaxations of zero-one linear programs Sándor Szabó Institute of Mathematics and Bogdán Zaválnij Alfréd Rényi Institute of Informatics University of Pécs Mathematics sszabo7@hotmail.com bogdan@renyi.hu ABSTRACT We distinguish two types of conflict graphs such as totally In an earlier work a so-called conflict graph was associated computed conflict graphs and partially computed conflict to a given zero-one linear program basically to accumulate graphs. In other words a partially computed conflict graph information to construct cuts to speed up the solution of the can be viewed as a relaxed version of the totally computed program. Later it was noticed that the conflict graph can conflict graph. Typically one works with partially computed be used in fixing values of variables and fathoming partial conflict graphs. The reason of this is the following. Deciding solutions in enumerative type solvers. In this paper we will whether the pair {ui, uj } is an edge of the conflict graph H show that the conflict graph helps in dividing dividing a amounts to deciding the linear program P has a feasible zero-one linear program into independent smaller instances solution with the extra constraints ui = uj = 1. and so it opens a way for a parallel solution. Further the conflict graph suggests certain possibilities for preprocessing If the zero-one linear program P with the extra constraints and simplifying the given zero-one linear program. ui = uj = 1 does not have any feasible solution then, the unordered pair {ui, uj } is an edge of the conflict graph H. Keywords Carrying out these computations for each 1 ≤ i < j ≤ discrete optimization, clique, independent set, weighted clique, 2n can be computationally prohibitive. So one accepts this zero-one program, parallel computing, preprocessing limitation and introduces edges into H whose existence can be verified easily. In this way we end up with a partially 1. INTRODUCTION constructed conflict graph. Given a zero-one linear program P . We assume that ob- In [1] a number of properties of the conflict graph were es- jective function of P is to be maximized, that is, we are tablished and were used to construct cuts. The next three of dealing with a maximization problem. A zero-one variable the above results were used to aid an enumerative solutions sometimes called a binary or Boolean variable. The fact in [9]. that a zero-one variables takes on the value zero sometimes expressed saying that variable is on level zero. Similarly, we can say that the variable is on level one. Lemma 1. (Extension rule) If {xi, uj } and {yi, uk} are edges of H, then {uj , uk} is an edge of H. Following [1] using the linear program P we construct a so- called conflict graph H and we assign this graph H to the program P . Here is the construction of H. Let x1, . . . , xn Lemma 2. (Fixing rule) If {ui, ui} is an edge (loop) of be the variables of the given zero-one linear program P and H, then ui = 0 must hold. let y1 = 1 − x1, . . . , yn = 1 − xn. Finally, for the sake of a uniform notation let Lemma 3. (Fathoming rule) A partial solution in which u1 = x1, . . . , un = xn, un+1 = y1, . . . , u2n = yn. xi is fixed on level 0 and yi is fixed on level 0 cannot be a The nodes of the conflict graph H are the variables feasible solution. u1, . . . , un, un+1, . . . , u2n. We apply the extension rule repeatedly as long as the ex- The nodes ui, uj , 1 ≤ i < j ≤ 2n are connected by an edge tension rule is applicable. This leads to the so-called closure in H if the inequality ui + uj ≤ 1 holds. of the conflict graph. If we are lucky we may fix the value of some variable in the linear program or we may fathom a partial solution. The set of neighbors of a node v of the graph G consists of all the nodes of G that are adjacent to v. The set of neighbors of v is denoted by N (v). In practice we apply the extension rule to the nodes xi and yi for each i, 1 ≤ i ≤ n. Namely, the edges {x, y}, x ∈ [N (xi) \ {yi}], y ∈ [N (yi) \ {xi}] are added to the conflict graph. Of course some of these edges 660 Table 1: The adjacency matrix of a conflict graph. x x x x x y y y y y 1 2 3 4 5 1 2 3 4 5 x 1 • • • • • x1 u u y x 2 • • 1 x 3 • • @ A x 4 • • x2 u A@ u y @ 2 A x 5 • A y 1 • • • A y 2 • • x3 u y Au 3 y 3 • • y 4 • x4 u y u 4 y 5 • • x1 u u y1 x5 u u y5 @ A x2 u @ A y @u 2 A A x3 u A y u A 3 Figure 2: Extending the conflict graph. The newly added edges are bold. x4 u y u 4 x5 u u y5 Figure 1: A graphical representation of the conflict graph may already be an edge of the conflict graph in which case we do not add any new edge to the conflict graph. Note that yi ∈ N (xi), xi ∈ N (yi) and so if |N (xi)| = 1 or |N (yi)| = 1, then we do not add any new edge to the conflict graph. If Table 2: The adjacency matrix of the extended conflict graph. [N (xi) \ {yi}] ∩ [N (yi) \ {xi}] 6= ∅, then there are variables The new edges are indicated by “◦” signs. whose values can be fixed. Namely, the variables appearing in the intersection can be fixed. x x x x x y y y y y To see why let us assume that uj is an element of the in- 1 2 3 4 5 1 2 3 4 5 tersection. In this situation by the extension rule the un- x 1 • • • • • ordered pairs {xi, uj } and {yi, uj } are edges of the conflict x 2 • • ◦ graph. Again, by the fixing rule {uj , uj } is an edge of the x 3 • ◦ • conflict graph. x 4 • ◦ ◦ • x 5 • As an illustration we included a small example. In Table 1 y 1 • • • the reader can see the adjacency matrix of a conflict graph. y 2 • ◦ ◦ • Figure 1 depicts a possible geometric representation of this conflict graph. Figure 2 shows the new edges we get applying y 3 ◦ • ◦ • the extension rule. y 4 • y 5 • • Of course the computations are happening on the adjacency matrices. During a computations only Tables 1 and 2 ap- pear. 661 2. THE WEIGHTED AGREEMENT GRAPH Lemma 6 suggests to remove full degree nodes from the In this section we define a new agreement graph G. This weighted conflict graph, then after locating a maximum weight G can be used to preprocessing or precondition the original clique in the reduced graph we can construct a maximum linear program and to divide it into smaller independent weight clique in the original weighted agreement graph. instances. We say that node v dominates node u of the weighted agree- Let G be the complement of the subgraph of H induced by ment graph G if u, v are distinct, N (u) ⊆ N (v) and the the set of nodes {x1, . . . , xn}. To the node xi of G we assign weight of u is not larger than the weight of v. (Remember the coefficient of xi in the objective function as a weight. that N (v) is the set of neighbors of the node v in G.) A subset C of the vertices {x1, . . . , xn} of the weighted We say that the edge e = {u, v} dominates edge f = {v, w} agreement graph G is called a clique if each two distinct in the weighted agreement graph G if the unordered pair vertices in C are adjacent in G. The sum of the weights {u, w} is not an edge of G, [N (v) ∩ N (w)] ⊆ [N (u) ∩ N (v)] assigned to the elements of C is called the weight of the and the weight of w is not larger than the weight of u. clique. The vector [α1, . . . , αn] is referred to as the charac- teristic vector of the set C if αi = 1 whenever xi ∈ C and More generally, we say that the edge e = {u, v} dominates αi = 0 whenever xi 6∈ C. edge f = {x, y} in the weighted agreement graph G if at least one of the unordered pairs The observation we will use is stated formally as a lemma. {u, x}, {u, y}, {v, x}, {v, y} is not an edge of G, [N (x) ∩ N (y)] ⊆ [N (u) ∩ N (v)] and Lemma 4. The set of characteristic vectors of the cliques the sum of weights of x and y is not larger than the sum of of G contains each feasible solution of the zero-one linear weights of u and v. program P . The following result is proved in [8]. We spell out explicitly Lemma 5 as a corollary to Lemma 4. Lemma 7. If node v dominates node u, then node u can safely deleted from G when we are looking for a maximum Lemma 5. The value of each optimal solution of the zero- weight clique in G. one linear program P is at most the weight of a maximum weight clique in the graph G. Lemma 8. If edge e dominates edge f , then edge f can safely deleted from G when we are looking for a maximum Any of the maximum weight clique solvers in [2], [4], [5], [6], weight clique in G. (We do not delete any of the endpoints [7] can be deployed to locate a maximum weight clique in the of the edge f .) agreement graph G. This clique does not necessarily provide a feasible solution of the original zero-one linear program P . What is certain that we can establish upper bound for the Deleting a node from G means that we may fix the value of optimal solution of the zero-one linear program P . the corresponding variable of P on level zero. Deleting an edge from the weighted agreement graph G means that we The Carraghan-Pardalos algorithm [3] is capable of listing may enter a new edge into the original unweighted conflict all maximum weight cliques in the weighted agreement graph graph H. Applying the extension rule in H may result fixing G. The algorithm maintains a partially constructed clique variables or fathoming. C and a list consisting of nodes that can be added to C to get a larger clique. With a slight modification of the 3.1 Coloring the vertices procedure we may also check if C can be part of a feasible In this section we will show how coloring of the nodes of the solution of the given zero-one program P . Thus, the mod- weighted agreement graph G can be used for preprocessing ified Carraghan-Pardalos algorithm could locate a clique in the zero-one linear program P . G, which has maximum weight among the feasible solutions of P . In short, a clique problem solver can solve moderate We say that a coloring of the vertices of the graph G is a size zero-one linear programs. proper coloring if each node is colored exactly one color and the two end points of each edge of G receive distinct colors. 3. KERNELIZATION Usually we use the numbers 1, . . . , k as colors. The nodes of A node of the graph G is referred to as a full degree node if G receiving colors i give the elements of the color i-th color it is adjacent to each other node of G. Let v be a full degree class Ci. A coloring of the nodes of G can be given by the node of G and let G0 be the subgraph of G induced by the color classes C1, . . . , Ck. From the color class Ci we pick a nodes distinct from v. In plain English we get G0 from G by node with a maximum weight. Summing up these weights deleting the node v. for each i, 1 ≤ i ≤ k we get a number which we call the weight of G with respect to the given coloring of the nodes of G. Lemma 6. (Full degree rule) If C0 is a maximum weight clique in G0, then C = C0 ∪ {v} is a maximum weight clique Let v be a vertex of G. We consider the subgraph L of in G. G induced by the set N (v). Using a greedy algorithm we 662 properly color the vertices of L. To the vertex v we assign 6. REFERENCES the weight of the coloring of L and call this number the color [1] A. Atamtürk and M. W. P. Savelsbergh, Conflict index of v. graphs in solving integer programming problems, European Journal of Operation Research 121 (1994), Let e = {u, v} be an edge of G. We consider the subgraph 40–45. M of G induced by the set N (u) ∩ N (v). Using a greedy [2] E. Balas, J. Xue, Weighted and unweighted maximum algorithm we properly color the vertices of M . To the edge clique algorithms with upper bounds from fractional e we assign the weight of the coloring of M and call this coloring, Algorithmica 15 (1996), 397–412. number the color index of e. [3] R. Carraghan, P. M. Pardalos, An exact algorithm for the maximum clique problem, Operation Research Using a greedy procedure we locate a clique C in G. The Letters 9 (1990), 375–382. larger of the weight T of C is the better. Clearly, T is a [4] S. W. Cai and J. K. Lin, Fast solving maximum lower bound of the weight of any maximum weight clique in weight clique problem in massive graphs. In G. Proceedings of 25th International Joint Conference on Artificial Intelligence, IJCAI, (2016) 568???574. The basic observation we use for preprocessing is stated as [5] D. Kumlander, A new exact algorithm for the a lemma. maximum weight clique problem based on a heuristic vertex-coloring and a backtrack search. In Proceedings of Modeling, Computation and Optimization in Lemma 9. Let v be a vertex of G. If weight(v)+index(v) < T , then v can be deleted safely from G when we are looking Information Systems and Management Sciences, for a maximum weight clique in G. MCO, 202???208. Hermes Science Publishing 2004. [6] P. R. J. Österg˚ ard, A new algorithm for the Let e = {u, v} be an edge of G. If weight(u) + weight(v) + maximum-weight clique problem, Nordic Journal of index(e) < T , then e can be deleted safely from G when we Computing 8 (2001), 424–436. are looking for a maximum weight clique in G. (We do not [7] P. Prosser, Exact algorithms for maximum clique: A delete any of the endpoints of the edge e.) computational study, Algorithms 5 (2012), 545–587. [8] S. Szabó, Parallel algorithms for finding cliques in a 4. PARALLELIZATION graph, Journal of Physics: Conference Series 268 Let us turn to the parallelization result. Let W (2011) 1, W2, W3 be subsets of the nodes of the finite simple graph G and assume [9] S. Szabó, Conflict graphs in implicit enumeration, that V is the set of nodes of G. Suppose W Pollack Periodica 7 (2012), 145–156. 1, W2, W3 are pair-wise disjoint and V = W1 ∪ W2 ∪ W3. If in addition [10] S. Szabó, Metric space method for constructing there is no edge of G is going from W1 to W3, then we say spiltting partitions of graphs, Acta Univ. Sapientiae, that the triple (W1, W2, W3) is a splitting partition of G. Informatica 11 (2019), 131–141. [11] S. Szabó and B. Zavalnij, Splitting partitions and Let G1 be the subgraph of G induced by the set of nodes clique search algorithms, Middle-European Conference W1 ∪ W2 and let G3 be the subgraph of G induced by the on Applied Theoretical Computer Science 2019, 75–78. set of nodes W2 ∪ W3. The next result is proved in [8]. Lemma 10. If C is a maximum weight clique in the graph G, then C is a maximum weight clique in either G1 or in G3. In the particular case when both of the sets W1, W3 has more than one elements Lemma 10 offers a way to replace the original zero-one linear program P by two smaller programs P1 and P3. The program P1 is constructed from program P by deleting variables corresponding the elements of the set W3. Similarly, the program P3 is constructed from program P by deleting variables corresponding the elements of the set W1. Sytematic ways to construct splitting partitions are pre- sented and tested in [10] and [11]. 5. ACKNOWLEDGMENTS The project has been supported by National Research, De- velopment and Innovation Office – NKFIH Fund No. SNN- 135643. 663 664 Zbornik 25. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2022 Zvezek J Proceedings of the 25th International Multiconference INFORMATION SOCIETY – IS 2022 Volume J Legende računalništva in informatike Legends of Computing and Informatics Urednika / Editors Borut Žalik, Matjaž Gams http://is.ijs.si 10. oktober 2022 / 10 October 2022 Ljubljana, Slovenija 665 666 PREDGOVOR V 2022 smo poskusili z novim konceptom promovirati slovensko računalništvo in informatiko. Imenuje se »Legende računalništva in informatike« (Krajše »Legende RI« ali kar »legende«) s podnaslovom »Galerija slavnih slovenskega računalništva in informatike«, angleško »Hall of fame of Slovenian computer science and informatics«. Motiv je, da stroka sama da priznanja pomembnim raziskovalcem, razvojnikom in inženirjem na področju RI, hkrati pa zberemo pomembne avtobiografske prispevke v obliki zapisa slovenske zgodovine RI, torej sledimo dvema ciljema hkrati. Strokovnost brez politike in ideologije, demokratičnost in transparentnost so dominantne komponente postopka Legend RI. Škoda bi bila tudi, da ne bi nekateri pomembni posamezniki nikjer zbrano predstavili svojega dela. Po drugi strani pa poglejmo samo Alana Turinga, ki je eden najpomembnejših računalničarjev vseh časov, a je bil namesto nagrade obsojen in kaznovan zaradi svoje usmerjenosti, ne da bi komurkoli storil kaj žalega. Pričakujemo, da bo programski odbor nagradil vse pomembne računalnikarje s priznanjem "Legenda" glede na njihov dejanski prispevek. Vsak začetek je težak, zato je bilo tudi nekaj začetniških spodrsljajev, a sedaj imamo programski odbor, ki odloča z glasovanjem o vseh pomembnih točkah. Tako je bilo izglasovano ime dogodka, da so dobitniki nagrade Michie-Turing brez glasovanja sprejeti po poslanem referatu na konferenco, ki hkrati služi kot avtobiografska zgodovina. Podobno naj bi veljalo za zelo pomembne mednarodne nagrade (o zadostni pomembnosti glasuje programski odbor) ne pa tudi za nacionalne nagrade. Nagrad naj bi bilo prvo leto med 10 in 20. Absolutna zgornja meja naj bi bila nekaj nad 50, zagotovo manj kot 100 legend. Ker naj bi preprečili, da kdorkoli glasuje zase, bo volilna komisija multikonference Informacijska družba (IS) preverila vsako volilnico posebej. Pošiljanje predlogov je odprto, pričakovano pa predvsem s strani društev ACM Slovenija in SLAIS. Volilna komisija legend je kar standardna IS komisija. Rezultati so predani naprej samo v zbirni obliki, to je v številu glasov. Predlog je potrjen, ko je zanj več oddanih glasovnic ZA kot NE in ne presega dogovorjene letne ali absolutne meje – v tem primeru odloča vrstni red. Predlog za legendo mora biti v obliki 2-4 stranskega prispevka za konferenco IS v pravem formatu, podkrepljen z literaturo. Predlog lahko poda vsak zase, kandidira pa lahko tudi koga drugega. Vsak lahko hkrati napiše več predlogov. Pri posthumni kandidaturi je potrebno pridobiti soglasje najbližjih svojcev. Prispevek velja urediti podobno kot življenjepis oz. CVI, s tem da izpostavljamo dosežke in ne osebne lastnosti. Dosežke velja strukturirati, recimo znanstveno, prenosi v prakso, pedagoško, organizacijsko, a zaenkrat je tu precej svobode. V bodoče bi bilo morda smiselno strukturo tudi poenotiti, S tem novim mehanizmom skušamo dodatno razviti slovensko računalništvo in informatiko ter informacijsko družbo. Prosiva za sodelovanje, podporo, ali vsaj za strpnost in razumevanje. In seveda, iskrena hvala vsem sodelujočim in čestitke sedanjim in bodočim nagrajencem! Borut Žalik in Matjaž Gams 667 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Žalik Borut, predsednik programskega odbora Adamič Milan Bric Rudi Brodnik Andrej Divjak Saša Gerlič Ivan Horvat Bogomir Gams Matjaž Grad Janez Grobelnik Marko Hafner Izidor Jurič Simon Kalin Tomaž Kljajić Borštnar Mirjana Kozak Jernej Lesjak Janez Leskovar Robert Luštrek Mitja Martinec Mark Mernik Marjan Mladenič Dunja Mongus Domen Pisanski Tomaž Rajkovič Vladislav Reinhardt Robert Schlamberger Niko Solina Franc Škedelj Franc Špegel Marjan Trampuž Cveto Trček Denis Turk Žiga Vilfan Boštjan Vidmar Rok Volk Mira Zimic Niko Zupan Blaž Železnikar Anton Žerko Miha 668 Dosežki kandidata Rudija Brica . Rudi Bric rudi.bric@pe-tra.com POVZETEK Iz dolgoletnega sodelovanja ISKRE in CDC-ja se je v tem času zgodil nakup licence za proizvodnji mini računalnika za V prispevku so opisani dosežki avtorja. poslovno uporabo Cyber C-18. Čisto slučajno sem leta 1978 postal član skupine 21-tih mladih, v glavnem diplomiranih inženirjev elektrotehnike in matematike, ki jih je ISKRA poslala 1 UVOD na šolanje v ZDA. Naša naloga je bila, da spoznamo HW in SW Zaprošen sem bil, naj opišem svoj prispevek na IT področju v komponente sistema. Imeli smo dostop do vse izvorne kode, vseh Sloveniji. Zapisano je pravzaprav samo spomin na dogodke, kot informacij in odličnih poznavalcev sistema. se je pač ohranil v moji glavi in ni povsem verodostojen Cyber-18 je imel izredno napreden 16-bitni procesor. deloval je dokument. Na tem delam in še ni končan. v dveh načinih - batch in interaktivno. V batch načinu je izvajal programe zaporedno, podobno kot IBM-360 z operacijskim sistemom MSOS 5.0. Interaktivno delo z do 16 terminali je bilo 2 ŽIVLJENJEPIS podprto z operacijskim sistemom ITOS 1.2 (Interactive Terminal Rojen sem 1. julija 1951 v Ljubljani očetu šoferju in materi Oriented System). Hkratno delo ni bilo mogoče. Sistem je imel gospodinji. Že v osnovni šoli sem tekmoval na tekmovanjih iz maksimalno 256 KB spomina. Na pamet mi je prišel način, kako matematike in po osnovni šoli nadaljeval izobraževanje na brez velikih sprememb programja doseči sočasno delovanje obeh Bežigrajski gimnaziji v matematičnem razredu. Vseskozi sem bil operacijskih sistemov. Moj predlog je bil sprejet in v manjši »politično aktiven«, bil predsednik razreda, pionirske in skupini še dveh sodelavcev Lada Peternela in Janeza Kožuha, ki mladinske organizacije v osnovni šoli in gimnaziji, vedno kot je našel način, kako razširiti spomin na 512KB in podpreti 32 neka alternativa prevladujoči politiki. V četrtem letniku terminalov, smo idejo izpeljali. Hkrati smo izvedli spremembe gimnazije sem skupaj s še tremi sošolci, gotovo kot prvi, za podporo šumnikov in odstranili vrsto napak v File Manager protestno izstopil iz ZSMS. Zdela se nam je premalo napredna. podsistemu, ki so povzročale občasne ustavitve sistema. Nov Študij sem nadaljeval na Fakulteti za naravoslovje in tehnologijo, sistem smo poimenovali ITOS 2.0 in v CDC-ju so nam celo na smeri tehnična matematika in leta 1976 diplomiral. formalno priznali avtorstvo sistema. Razvoj je ob zelo Računalniško programiranje je predaval dr. Egon Zakrajšek. intenzivnem delu trajal manj kot leto dni. V ISKRI so Praktično delo, programiranje v FORTRAN-u, smo študenti računalnike imenovali ISKRADATA C-18 in C-19 in jih opravljali na sistemih IBM 1130 in CDC Cyber 72. Skupaj s uspešno prodajali po vsej Jugoslaviji. Med mnogimi sošolcem in prijateljem Igorjem Fakinom sva kot seminarsko pomembnimi aplikacijami je bila tudi glavna knjiga v vseh nalogo izdelala program, ki je uspešno poiskal maksimalni temeljnih bankah NLB. Lasten razvoj smo nadaljevali in pretok usmerjenega grafa. Ta moja prva izkušnja me je na implementirali zanesljiv prenos datotek po protokolu IBM 3780 zanimiv način spremljala skozi vse življenje. preko telefonskih linij. Zadnji razvoj, pri katerem sem kreativno Po odsluženju vojnega roka sem se leta 1977 zaposlil v ISKRI sodeloval, je bila implementacija najpogosteje uporabljene kode Commerce, kjer sem imel štipendijo. Moj prvi računalnik, do (memory scheduler) z »native mode« instrukcijami. Prav kmalu katerega sem imel neomejen pristop, je bil Philips P320. Sistem smo namreč ugotovili, da je celoten sistem deloval v emulaciji je bil namenjen računovodstvom. Glavna podatkovna asemblerja, v katerem je bil napisan sistem MSOS. Tudi pri vhodno/izhodna enota pa je bila magnetna kartica formata A4 za največji obremenitvi je bil sam procesor sano polovično magnetnim trakom ob strani. Uspelo mi je izdelati program za izkoriščen. Po spremembi je procesor deloval z okoli četrtino optimizacijo cene krmnih mešanic za podjetje Emona. zmogljivosti. Na naše presenečenje pa sistem ni deloval prav nič Nenavadno za strogo namensko napravo. hitreje. Problem j bila organizacija diska. Moj predlog za reorganizacija dika ni bil sprejet, ker je v tem času celoten projekt Permission to make digital or hard copies of part or all of this work for personal or ISKRADATA v ISKRI počasi ugašal in bil nadomeščen s classroom use is granted without fee provided that copies are not made or distributed projektom DELTA. 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 Zame je bil ta čas pomemben tudi zaradi dogodkov, povezanih s be honored. For all other uses, contact the owner/author(s). prvo možnostjo, da bi ISKRA izvozila svoje znanje v Mehiko, Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). veliki državni firmi DICONSA SA, ki je takrat imela preko 80 računalnikov C-18, s katerimi so upravljali oskrbovanje z 669 osnovnimi živili po celi Mehiki. Ker sem dobro poznal File distribuciji in šolanju strank pa je sodeloval Savo Tatalović. To Manager, sem tudi natančno vedel, zakaj se CDC C-18 sistemi je bil eden prvih primerov res uspešnega in koristnega na videz slučajno ustavijo brez kakršnega koli obvestila. To se je programskega paketa, ki je prinesel okoli 750.000 DEM v DICONSI redno dogajalo in CDC je to s pridom izkoriščal. Ob prihodka. To Mikro Adi, tudi pri njeni širši vlogi, ni škodilo. vsaki napaki so v Mehiko poslali tehnika, jih v glavnem obtožili, Ko se je v letu 1990 pokazala možnost ustanovitve zasebnih da ne znajo uporabljati programja, in jim »odpravo napake« družb, se je uspešno podjetje HERMES razdelilo v 13 družb. zasoljeno zaračunali. Kljub moji intervenciji pri odgovornih v Sodelavci v prodaji in servisu zastopstva HP-ja so ustanovili CDC se je tako početje nadaljevalo. V naši verziji operacijskega podjetje HERMES Plus. Andrej Kuščer, Tomaž Schara in Zoran sistema smo te napake odpravili. Zagorc smo ustanovili podjetje HERMES SoftLab. Nanj smo Slučajno sem spoznal nekega managerja iz DICONS-e in mu prenesli že v HERMES-u sklenjeno pogodbo s HP-jem in dobili povedal, kaj se dogaja. Predlagal sem demonstracijo na njihovem 6.000 USD popotnice v obliki kredita z zmanjšano obrestno sistemu v Tijuani, okoli 120 km iz San Diega. Demonstracija bila mero. Ne gre pozabiti, da je bil takrat čas hiperinflacije. Prav več kot uspešna in dogovorili smo se za posodobitev vseh 85 anekdotično je, da smo kasneje morali zaradi te zmanjšane sistemov na ITOS 2.0 z možnostjo softverske podpore in razvoja obrestne mere plačati kazen za »oškodovanje družbenega aplikacijskega programja za podjetje. Ko smo s to možnostjo premoženja«. seznanili vodstvo v Kranju in Ljubljani, so v San Diego poslali Razvojno delo za HP se je hitro povečevalo in zaslužek je bil managerja, ki je na hitro uspel izničiti vse naše uspehe in odličen. Dobiček smo vlagali v nove ljudi, njihovo vsestransko napovedal prekinitev sodelovanja s CDC-jem. izobraževanje in nakup opreme. Nekatere posle smo prevzeli z Takrat sem se zarekel, da bom nekoč ustanovil podjetje, ki bo z veliko rizika, saj naše znanje ni bilo preverjeno dovolj dobro. dobičkom prodajalo softver v ZDA. Trajalo je celih 12 let, da so Zelo pomemben dosežek je bila izdelava sistema za zaščito se moje želje uresničile. podatkov OmniBack, ki je postal svetovna uspešnica s V začetku 80-tih let sem, med prvimi v Sloveniji, pokazal, da se kompletnim razvojem v Ljubljani. Uporabljale so ga številne da s programiranjem tudi dobro zaslužiti. Z dovoljenjem največje družbe na svetu (npr. DHL, Boeing). Razvoj je vodil direktorja in delavskega sveta sem skupaj z Zoranom Zagorcem, Andrej Kuščer. S HP-jem smo sklenili dogovor s katerim nam je ki je pozneje postal soustanovitelj HERMES SoftLab-a, izpeljal HP zagotovil razvojno HW in SW okolje mi pa smo financirali optimizacijo delovanja programov na računalnikih razvojno delo. To bi bilo plačano samo v primeru, da razvoj ISKRADATA v NLB (10-kratno pohitritev obdelav zaključka uspešno zaključimo. Uspelo nam je in zaslužili smo prvi milijon glavne knjige NLB) in zaslužili smo 40.000 DEM – veliko mark. denarja za tisti čas. Kot solastnik in prvi investitor v HERMES SoftLab sem nam je Ker je program ISKRADATA ugasnil, sem se leta 1984 pridružil pridružil tudi Karlheinz Weiland, projektni vodja v HP, podjetju HERMES, ki je zastopalo podjetje Hewlett-Packard v Boeblingen. Jugoslaviji z dogovorom, da bom pomagal ustanoviti softversko Prevzeli smo sodoben način vodenja in v podjetje prenesli dobre podporno službo, ki do takrat ni obstajala. Kmalu so se pridružili prakse softverskega inženirstva v HP-ju. Leta 1993 smo prejeli še Andrej Kuščer, Zoran Zagorc in Tomaž Schara. Sam sem bil naziv Podjetniki leta. V letu 1998 smo, kot prvi, prejeli slovensko odgovoren za programsko podporo za poslovni sistem HP3000, priznanje za poslovno odličnost. Prav tako smo leta 1998 v sodelavci pa za LINUX oziroma kasneje HPUX – UNIX sistem Parizu prejeli priznanje za uvrstitev med štiri najboljša podjetja na računalnikih HP9000 RISC. Kmalu smo se ob šolanju v HP- po sistemu upravljanja kakovosti EFQM Business Excellency ju spoznali s tehnologijo in z več zanimivimi rešitvami težjih Award. tehničnih problemov tudi pridobili toliko zaupanja odgovornih v Od samega začetka smo izrazito podpirali ZOTK-o, ki je bila HP-ju, da smo leta 1988 pridobili prvi razvojni projekt. Delo smo organizator slovenskega državnega tekmovanja v računalništvu. opravili v glavnem izven rednega delovnega časa in zaslužili Zmagovalce smo pošiljali v razvojne laboratorije v HP. Ker so 250.000 DEM. Ker je denar prišel ravno pred novim letom, se je bili res dobri, je to pripomoglo k našemu dobremu imenu. delavski svet prav na hitro odločil, da je neprimerneje ta denar Kmalu smo ustanovili podjetje v ZDA v mestu Mountain View porabiti za dodatno »božičnico« za vseh 300 takrat zaposlenih v v Santa Clari, v bližini Palo Alta, kjer je sedež Heweltt-Packarda. HERMES-u. Prav nič ni ostalo za kak nov računalnik za razvoj. V Sloveniji smo imeli prostore in sodelavce v Novi Gorici in V praksi sem občutil, da je nadzor nad dobičkom in njegovo Mariboru, v Bosni in Hercegovini pa smo takoj po Daytonskem smotrno vlaganje izjemno pomemben. Tega sem se, morda še sporazumu ustanovili podjetji v Sarajevu in Banja Luki. V Srbiji preveč, držal celo svojo kasnejšo poslovno kariero. smo imeli svoje podjetje v Kragujevcu. Bil sem tudi aktivno udeležen pri ustanovitvi prvega slovenskega Kmalu po osamosvojitvi leta 1992 smo za potrebe bivše SDK, ki softverskega podjetja v mešani lasti Mikro Ade, katerega jo je takrat vodil Igor Omerza, razvili program za optimalen direktor je bil Igor Omerza. Družbeni kapital je zastopala večstranski pobot. S pomočjo matematičnega bistreca Tomaža takratna ZSMS. Ker se nisem želel izpostavljati, je bila med Schare in z vrhunsko implementacijo smo dosegli bistveno višji zasebnimi ustanovitelji moja žena Sonja in sestra Janeza Janše. pobot za desetino prejšnje cene pobota, ki ga je SDK izvajala na JJ je bil uslužbenec podjetja. Preko Mikro Ade smo od začetka Hrvaškem v centru SRCE, kjer je bil takrat najhitrejši IBM-ov 1988 do osamosvojitve prodajali programski sklop RIP računalnik. Nekaj časa je to bil to pomemben del prihodka (Rentabilnost Investicijski Projektov) po celi Jugoslaviji. Ta je podjetja. Z njim smo prebrodili začetne težave in napake. izjemno pohitril tedaj obvezen izračun investicij in ga je V letu 1993 smo s lotili prenove plačilnega pometa v Sloveniji. sestavljalo skoraj 500 med seboj povezanih LOTUS Med prvimi v svetu smo za transakcijsko poslovno aplikacijo razpredelnic, ki sem jih lastnoročno napisal. Vsebinsko je uporabili operacijski sistem UNIX, relacijsko bazo podatkov in metodologijo obvladal moj sošolec, ekonomist Boris Šefman, pri client/server arhitekturo. Na našo pobudo so v SDK kot prvi 670 državnih organizacijah uvedli masovno uporabo elektronske in leta 2002 presegli 42M EUR prihodkov in preko 700 pošte. Sistem je bil zelo uspešno uveden leta 1997. Celoten zaposlenih. razvoj je za HSL pomenil 3,5 m DEM prihodka, ki pa ni pokril Podjetje sem vodil kot direktor do leta 2002, ko sem odstopil, ker vseh stroškov. Prav gotovo najcenejši razvoj nacionalnega nisem sprejel ultimata finančnih investitorjev, da takoj plačilnega sistema do takrat. Na žalost je bil v uporabi samo odpustimo 50% zaposlenih in maksimiramo dobiček. Domače nekaj let in je s prehodom na medbančni plačilni promet zamrl. banke niso sprejele mojih predlogov, da financirajo 14M EUR, s Njegovo različico še danes uporabljajo na UJP. katerimi bi izplačali neizprosne finančne vlagatelje in ohranili Zelo uspešno je HSL sodeloval z Mobitelom. Zelo zgodaj smo podjetje v slovenski lasti. prepoznali pomembnost podatkovnega prenosa na mobilnem V podjetju sem nadaljeval delo kot svetovalec v prodaji in bil omrežju čeprav je bila hitrost prenosa v začetku majhna. vpet v (neuspešen) projekt za DURS leta 2008 kjer smo na Izdelali smo SMS komunikacijski portal M-vrata s javnem razpisu kljub daleč najboljši ponubi izgubili proti navezi podsistemoma SMS-poštar in Ključna beseda s katerima je takrat SAP/IBM. Velika zamujena prilika, da bi v Sloveniji razvili Mobitel bil praktično vodilni v svetu na področju negovornih izdelek vreden vsaj 20M EUR in ga tržili po svetu drugim mobilnih storitev. Danes nas mnogo uporablja sistem pri akcijah državam. Zadnji večji (tudi neuspešen) poskus je bil javni razpis zbiranja pomoči, glasovanjih, reklamah in prenosu raznoraznih za informacijski sistem nove pediatrične klinike leta 2009. Na informacij preko SMS-ov. njem je zmagal Marand. Poskus poeenotenja informacijskih Mobitel je tudi financiral razvoj sistema MojAlbum s katerim sistemov v slovenskih bolnišnicah je bil tako uspešno preprečen smo, takoj po pojavu prvih kamer na NOKIA mobilnih telefonih, in še dandanašnji ostal nerešen. omogočili prenos in shranjevanje slik na Mobitelovi V podjetju, ki ga je leta 2008 kupil srbski podjetnik Veselin infrastrukturi. Ideja ni bila prav dobro sprejeta, ker so se pojavili Jevrosimović za 35M EUR pretežno financiranim s kreditom dvomi o zaščiti zasebnosti. Poskus, da bi Mobitel omogočil italijanske banke. Podjetje je izgubilo svojo indentiteto s popolno individualiziran pristop do shranjenih slik in podprl še druge e- integracijo v Comtrade oktobra leta 2012. Organizacijsko in storitve za svoj stranke je bil preveč vizionarski za tedanje upravljalsko je ostalo praktično nespremenjeno s povdarkom na razmere. širitvi dejavnosti izdelave in prodaje lastnih izdelkov. V HSL smo se leta 1998-1999 reorganizirali v privatno delniško Ocenjujem, da je podjetje v prvih 20 letih izvozilo vsaj za 500M družbo z namenom, da se pripravimo na vstop na NASDAQ leta EUR programske opreme. 2004. V ta namen smo organizirali ugleden nadzorni svet z Sedaj posvečam svoje delo poskusom, da bi v svetu uveljavili mednarodno priznanimi, uglednimi posamezniki kot je bil na večstranski pobot kot pomoč pri reševanju vse večje notranje primer Joel Birnbaum, oče RISC procesorja, vodilni znanstvenik zadolženosti v mnogih državah sveta. To bi bil pravi, globalno v HP in direktor HPLabs, in dr. Zvonko Fazarinc. Podjetje smo potreben in pozitiven prispevek matematike in računalniške leta 2000 dokapitalizirali z 10M EUR za 18% solastniškega tehnologije k reševanju dolžniške krize na globalni ravni. deleža uglednih novih solastnikov HP, EBRD, Charlemagne Capital, NLB in Triglav. Namen je bil dvigniti verodostojnost podjetja za nastop na največji tehnološki borzi na svetu in pridobiti nove stranke kjer so imeli novi lastniki vpliv. Vse to LITERATURA smo počeli kot pionirji, saj v Sloveniji takega poslovnega dejanja [1] Podjetnik: Rudi Bric - izvoznik domače pameti (podjetnik.si) še ni bilo. Prav pomanjkanje prakse in izkušenj pi sklepanju delniških pogodb nas je, takratne lastnike, ob prodaji podjetja drago stalo. Poleg podjetja HP smo našli še druge velike kupce naših storitv. Za podjetje Softlab iz Muenchna smo na primer opravili preverjanje celotne izvorne kode za Y2K problem njihovega ogromnega AMADEUS rezervacijskega sistema za potniški letalski promet. Zaradi velikosti sistema smo za nalizo izdelali specializirano programsko opremo z našimi najboljšimi strokovnjaki. Nova stranka je postalo tudi rent-a-car podjetje SIXT. Zanj smo razvili veliko aplikacij vključno z eno prvih prodaj rabljenih avtomobilov na internetu. Slovensko podjetje RESULT še dandanašnji opravlja razvojno in vzdrževalno delo za njihove IT potrebe. V letu 2000 je HSL kupil podjetje ZASLON, ki je izdelalo takrat najbolj napredno aplikacijo za mobilno bančništvo. Iz te zasnove so nastale danes poznane aplikacije kot sta NLB Klik in Proklik ter SKB Net in še vrsta drugih. Potem je prišla kriza celotne informacijske in telekomunikacijske industrije konec leta 2000. NASDAQ indeks je dramatično padel. IPO trg je povsem zamrl. Leta 2004 nismo dosegli predvidene vrednosti na borznem trgu, čeprav smo rasli 671 Dosežki kandidata M. Gamsa Achievements of the candidate M. Gams Matjaž Gams Odsek za inteligentne sisteme Institut “Jožef Stefan” Ljubljana, Slovenija matjaz.gams@ijs.si POVZETEK zagonu je motiv jasen: pomembni slovenski računalniški ali informacijski strokovnjaki naj svoje dosežke za zgodovino V prispevku so opisani dosežki avtorja v smislu zgodovine in v opišejo v obliki referatov, priznanje stroke pa naj se manifestira smislu kandidature za “Dvorano slavnih slovenskega na omenjeni način. Zakaj ne bi računalništvo imelo mehanizmov računalništva in informatike”. drugih pomembnih ustaljenih področjih? Se pa še spotoma učimo in denimo - razmišlja se o konkretni izvedbi KLJUČNE BESEDE konference/mehanizma naprej v bodočnost. Doživljenjski dosežki, znanost, gospodarstvo, slovarji, družbeno delo 2 Pedagoški dosežki ABSTRACT Life achievements of the author are presented in several areas Povprečna pedagoška obremenitev od doktorata dalje je 3-4 ure from science to industry, dictionaries and public work as part of predavanj tedensko, zadnja leta po nekaj dni na semester. Je historical autobiographical achievements and also as candidacy dolgoletni zunanji sodelavec FRI - Fakultete za računalništvo in for the “Hall of the fame of Slovenian computer science and informatiko, kjer je bil asistent pri okoli 10 predmetih. Po informatics”. docenturi je poučeval na dodiplomski stopnji na Pedagoški fakulteti in Fakulteti za družbene vede ter na podiplomski stopnji KEYWORDS na Ekonomski fakulteti. Sodeloval je tudi pri izvajanju Life achievements, science, industry, dictionaries, relevancy tretjestopenjskega študija v Vojvodini, na Hrvaškem in v writing in Slovene, add English keywords below the Slovene Nemčiji leta 2002. Izvedel je tudi več vabljenih predavanj na ones, keyword, keyword, keyword tujih inštitucijah. Sodeluje pri mentoriranju in ocenjevanju doktorskih, magistrskih in diplomskih del na ljubljanski, mariborski univerzi in MPŠ. Kot mentor ali komentor je 1 UVOD sodeloval pri 12 magisterijih, kot mentor 10 doktorandom in bil komentor pri 7 doktoratih. V letu 2021 smo izvedli konferenco oz. dogodek »Pionirji Bil je tudi zunanji izvajalec za Novomeško visoko šolo, kjer je računalništva in informatike« v okviru multikonferenca tudi poučeval več predmetov. V Kopru je sodeloval z dvema Informacijska družba [1]. Takrat se je porodila tudi zamisel o pedagoškima inštitucijama - za management in pomorstvo. Galeriji ali Dvorani slavnih, tj. »Hall of fame«. V svetu obstajajo Skupno je aktivno poučeval na 14 pedagoških inštitucijah, na podobni mehanizmi tako za športnike kot za druga področja. nekaj računalniških tečajih itd. [1]: Osnovna zamisel je, da strokovnjaki s področja mimo ideologije in politike, ki vse preradi sodelujeta pri priznavanju dosežkov 1. Fakulteta za računalništvo in informatiko, Ljubljana, všečnih posameznikov, sami povemo, kateri posamezniki so v 2. Ekonomska fakulteta, Ljubljana, resnici dosegli zelo pomembne dosežke. Poglejmo samo Alana 3. Evropsko središče, Maribor, Turinga [1], ki danes velja za računalniškega Einsteina, in 4. Filozofska fakulteta, Ljubljana, njegovo ime nosi poglavitna računalniška nagrada [1], pa je bil 5. Fakulteta za družbene vede, Ljubljana, obsojen za neko malenkost in je namesto priznanj ali nagrade v 6. Pedagoška fakulteta, Ljubljana, procesu prevzgoje leta 1954 ugasnil svečko. Kljub težavam pri 7. Fakulteta za management, Koper, 8. Fakulteta za pomorstvo in promet, Ljubljana / Portorož, 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 9. University of applied sciences, Zweibrücken, Nemčija, for profit or commercial advantage and that copies bear this notice and the full 10. Mednarodna podiplomska šola Jožefa Štefana, citation on the first page. Copyrights for third-party components of this work must Ljubljana, be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia 11. Visoka šola za upravljanje in poslovanje, Novo mesto, © 2022 Copyright held by the owner/author(s). 12. Evropsko središče, predhodnik AME, Maribor, 13. Alma Mater Europea, Maribor, 672 14. Gimnazija Bežigrad, Ljubljana. Zadnja leta se aktivno ukvarja s študijem človeške civilizacije – katere nevarnosti grozijo in kaj je potrebno narediti, da se Pedagoškega dela je precej manj kot pri rednih profesorjih, npr. nevarnostim izognemo. Poglavitne nevarnosti so: jedrska vojna pri prof. F. Solini, prof. D. Trčku ali prof. Bratku, je pa kar (ni analize), umetna inteligenca, demografija, družbeni propad, obsežna za raziskovalca po osnovni usmeritvi, medtem ko je biološki agenti, torej je kar precej nevarnosti našlo pot v analize število pedagoških inštitucij, kjer je kandidat predaval, precej in objave kandidata. Demografija je, podobno kot misli Elon nadpovprečno. Musk, med najnevarnejšimi in najbolj urgentnimi. Po desetletjih, ko je grozila prevelika rast, sedaj grozi prevelik upad in posledično v nekaj sto letih izumrtje malih evropskih narodov. 3 Raziskovalno-razvojno delo Slovenski avtohtoni narodi kot Slovenci ali Hrvati naj bi po projekcijah izumrli v 200 letih, če ne bo prišlo do pomembnih sprememb. Analize tudi pokažejo, kaj je potrebno narediti: Kandidat je vodja Odseka za inteligentne sisteme na IJS s preko ojačati mehanizem družine in še marsikaj drugega. Pri študiju 30 zaposlenimi, je vrsto let vodil raziskovalno skupino na IJS COVID-19 je bilo doseženo drugo mesto (vodja ekipe Mitja znotraj programske skupine, ki se izvaja na IJS in FRI. V Luštrek, kandidat predlagal nekaj novih algoritmov) in nagrada ocenjevanju leta 2015 je bila skupina ocenjena kot najboljša na 250.000$ v XPRIZE tekmovanju. Analize pokažejo, da umetna svojem področju. Kandidat se ukvarja z raziskavami in razvojem inteligenca dosega 20% boljše rezultate pri krotenju pandemij, a na področju inteligentnih sistemov, inteligentnih agentov, hkrati se je izkazalo, da je ljudje (politiki, zdravniki) nočejo poslovne inteligence, kognitivnih sistemov, informacijske uporabljali, čeprav smo sistem zastonj ponudili EU družbe ter računalništva in informatike. Skupni imenovalec je ministrstvom. Pri družbenem propadu se je izkazalo, da ob uvedba inteligentnih metod v računalniške sisteme in s tem novih stagnaciji oz. propadu civilizacij istočasno prihaja do napetosti v sposobnosti, recimo izboljšano klasifikacijo ali boljšo družbi, medsebojnemu sovraštvu, idej, ki nimajo stika z sposobnost komunikacije. Z uvajanjem tovrstnih sistemov, realnostjo oz. produktivnimi odnosi. To se v precejšnji meri kaže predvsem inteligentnih agentov, se pospešuje prehod družbe, še v sodobni družbi, recept za umiritev razmer pa je jasen. Obsežne posebej slovenske, v informacijsko družbo. S stališča povsem analize na osnovi Drakove enačbe kažejo, da bomo ljudje slej ko bazičnih znanosti kandidat ocenjuje kot najbolj zanimive prej izumrli, če ne bomo osvojili presenetljivo veliko drugih raziskave inteligentnosti in zavesti v relaciji človek-stroj. planetov. Po svoje je to logično, vendar je zanimivo, da formalne Poglavitna kandidatova teza, začenši z doktoratom, je, da je analize matematičnih modelov, temelječe na opazovanjih naše potrebno sedanje računalniške sisteme bistveno dograditi v galaksije, kažejo tako. Torej preprosto povedano: človeštvo mora smislu t.i. mnogoterega znanja [1] – prepletanja več procesov, ki stremeti k temu, da gre na Mars in izven našega osončja, hkrati aktivno interaktirajo med seboj. S tem pridobimo načeloma večjo mora umiriti medsebojne konflikte, izrojene ideje in z računsko sposobnost kot s Turingovimi stroji. Nenavadna uravnavanjem rojstev preko sistema družine in sorodnih ukrepov podobnost te informacijske teorije je s fizikalno teorijo doseči trajnostjo rast oz. skrb za okolje. Znanstvene analize mnogoterih svetov. Prve odmevne raziskave, povezane z umetne inteligence in zdrava pamet kažeta enako. doktoratom, pa so bile na področju patologije – kdaj se pri globljem preiskovanju pojavijo slabši rezultati [1]. Poleg raziskav je pomemben prenos znanj v slovenski prostor, kjer je 4 Objave avtor med bolj aktivnimi pisci strokovnih besedil in drugih aktivnosti, ki dvigujejo nivo Slovenije. Primer bi bila strokovna knjiga o kvalitetnem programiranju [1]9]. S tovrstnimi objavami Bibliografija dr. Gamsa [1]10] zajema čez 1600 postavk v se je spodbujalo računalniška znanja v Sloveniji. COBISSU, od tega 157 objav v 1.01, skupaj s v zbornikih konferenc in knjigami preko 900 objav. Nekatere objave so v Princip mnogoterega znanja pravi, da je optimalno znanje najkvalitetnejših tujih revijah s področja računalništva in mnogotero (beseda redundantno ni prava, čeprav je mnogotero informatike [1]11]. Vseh citatov je po Google scholarju čez znanje običajno precej redundantno), da torej ansambelske 4500, medtem ko je tam h-indeks 32, na internetu najdemo preko metode v strojnem učenju dosegajo boljše rezultate (empirično 40.000 omemb. Je soavtor 8 patentov oz. vlog. V rubriki 1.04 potrjeno), da skupina ljudi bolje deluje kot posameznik, itd. Ta Professional article in 1.05 Popular article je 290 vnosov. princip je v navideznem nasprotju z Ockhamovim principom, ki pravi, da je optimalno porezati vse redundantno. Za dobre Pri objavah je kar nekaj raziskovalcev z višjim h-indeksom v rezultate pa je potrebno smotrno sestaviti skupno znanje več računalništvu, recimo Sašo Džeroski ali Ivan Bratko. Po številu modelov znanja, ki so čim bolj kvalitetni in čim bolj različni. vseh objav in po številu vseh vnosov v Cobiss pa kandidat dosega Nekaj zaključkov je precej nenavadnih: skoraj vedno obstaja več enega najboljših rezultatov v računalništvu in informatiki v enot, recimo več planetov ali več galaksij / vesolij. Ali ta, da ni Sloveniji, prav tako po številu omenjanj na spletu. Podobno po mogoče doseči prave inteligence z obstoječo računalniško številu poljudnih objav, kjer izstopajo redni komentatorji kot arhitekturo, ker je premalo mnogotera. Morda omogoča Žiga Turk, pa tudi Denis Trček ima precej zanimivih objav. Pri simulacije mnogoterosti, vendar najbrž preveč težko. Paradoks pedagoških knjigah po številu izjav verjetno izstopata Ivan pa pravi, da lahko mnogotere modele združimo v enega, a to je v Bratko in Vladislav Rajkovič, po največjem številu izvodov v dinamičnem svetu zahtevna naloga; lažje je v stacionarnem. tujini Ivan Bratko. Po branjih poljudnih člankov je kandidat verjetno med odličnimi, saj je v povprečju prispevek bran/klikan okoli 10.000-krat, rekord pa je okoli 200.000 klikov prispevka. 673 5 Uredniško vrhu, če upoštevamo rezultate na zaposlenega (ali glede na GDP), ne pa absolutno. Podobno smo ob kritikah visokega znanja z nekaj analizami in objavami pokazali, da je visoko Je vodja in sodelavec večjega števila domačih in mednarodnih znanje (visoko šolstvo, znanost, patenti, delež v izvozu) med raziskovalnih projektov, skupno nekaj sto. Je član več društev najpomembnejšimi relacijami z GDP države. (ACM, ECCAI, IEEE) in uredniških odborov mednarodnih revij, skupno se jih je nabralo okoli 15. Največ energije nameni Po položaju izstopajo Peter Tancig kot minister ali Cene Bavec slovenski mednarodni reviji Informatica [1]12] kot izvršni kot državni sekretar, kljub temu je kandidat med najbolj kontaktni urednik revije od leta 2017 dalje, prej pa vrsto leto vplivnimi pri sprejemanju zakonov in promociji informacijske pridruženi izvršni urednik, kjer je po uredniškem stažu drugi za družbe ter zagovarjanju znanosti in visokega šolstva, hkrati je prof. Železnikarjem. Vsako leto je v povprečju član okoli deset ustanovil največ ključnih računalniških in informacijskih društev organizacijskih odborov konferenc, med drugimi tudi svetovno ter drugo nacionalno akademijo IAS. Po številu mandatov v najbolj slovečih kot IJCAI ali AAAI. Je desetletja glavni društvih morda izstopa Niko Schlamberger, po društveni organizator tradicionalne konference Informacijska družba, ene aktivnosti po širini najbrž kandidat. največjih te vrste v Evropi z nekaj sto letnimi prispevki in podelitvami nagrad Michie-Turing. 7 Gospodarstvo 6 Organizacijsko Izpeljal cca 10 aplikacij na svetovnem nivoju, kjer so po nekih Soustanovil je društvo za umetno inteligenco, društvo za rezultatih presegali konkurenčne. Zaposlovalni agent na kognitivne znanosti, društvo ACM Slovenija, društvo za internetu, ki je govoril slovensko in angleško, je dosegel peto tehniško-naravoslovne vede SATENO in inženirsko akademijo najbolj brano mesto med slovenskimi na spletu, je prvi na svetu IAS. V letih 1996–2004 je bil pomočnik vodje Odseka za v katerikoli državi nudil prek 90% vseh nacionalnih prostih računalniške sisteme na Institutu “Jožef Stefan” (IJS); 2004− delovnih mest preko spleta. Z ekipo razvil cca 300 inteligentnih vodja Odseka za inteligentne sisteme na IJS; 2009–2011, član asistentov za razne naročnike. Prvi razvili sistem TTS za nacionalnega Programskega sveta CRP; član UO IJS, večkrat slovenski jezik »Govorec«, kjer je sodeloval tudi Jure Leskovec. predsednik Elektronike na IJS in član Znanstvenega sveta IJS. V letu 2000 dan v prosto uporabo vsem slepim in slabovidnim 2008-2012 (pod)predsednik društva ACM Slovenija; Slovenije. Sistem pri železarni Jesenice je prek kvalitete oljne soustanovitelj in 11 let tajnik društva SATENA in tedanje IAS; emulzije skoraj desetletje nadziral kvaliteto površine pri 2010 in 2x po 4 leta predsednik konference SVIZ za fakultete in produkciji 100.000 t jekla letno, tj. praktično vso proizvodnjo v inštitute; podpredsednik SVIZ s 40 000 člani; soustanovitelj in Sloveniji. Vpeljava inteligentnega sistema VIDA za DURS, za predsednik več društev, med drugim Društva za kognitivne svetovanje v slovenščini pri izpolnjevanju davčnih napovedi. Za znanosti, Društva za umetno inteligenco in ACM Slovenija. Član Lotrič razvit nadzor hladilnih naprav, v celoti cca 100 prototipov, več nacionalnih svetov, med drugim Nacionalnega sveta za od katerih so se nekateri uporabljali leta oz. največ kakšno znanost in tehnologije. Bil predstavnik v evropski zvezi za desetletje. umetno inteligenco EurAI, sedaj predstavnik v IFIP Technical Committee 12. Trenutno poskušamo ustanoviti svetovno združenje za umetno inteligenco. Od leta 2018 dalje Državni 8 Slovenski jezik svetnik za raziskovalno dejavnost, kjer je dosegel za znanost in visoko šolstvo zelo pomembne rezultate, recimo preprečil sprejem slabih verzij raziskovalnega zakona in podprl sprejem Skupaj z nekaj deset sodelavci s cele Slovenije, zlasti pa z dvema sedanje dobre verzije. Moto je bil in je : Več znanosti v politiko sodelavcema FRI, dr. Kodekom in dr. Vilfanom, je sodeloval pri in manj politike v znanosti. izdaji Računalniškega slovarčka, prvega leta 1985 [1]13], Leksikona "Računalništvo" in Velikega leksikona Cankarjeve V letih 2000 in 2001 je dr. Gams postal član Programskega sveta založbe. S ponatisi in razširjenimi izdajami so v skupni nakladi za informatizacijo šolstva in član Strateškega sveta za okoli 50.000 izvodov postavili temelje slovenskega informacijsko družbo, ki ga je ustanovil dr. Drnovšek. V tem računalniškega izrazoslovja. Sedaj je računalniški slovarček z obdobju so bili postavljeni temelji slovenske informacijske 12.000 izrazi največja zbirka angleško-slovenskih izrazov v družbe. Bil je tudi član več nacionalnih svetov, med drugim član obliki Wiki slovarčka http://dis-slovarcek.ijs.si/. Pri slovarjih in strateškega Sveta za znanost in tehnologijo Slovenije. Med leksikonih je v tej kategoriji verjetno na prvem mestu, še danes bojem za osamosvojitev Slovenije med drugim organiziral dopis je ključni urednik spletnega Računalniškega slovarčka, v Sobotni prilogi Dela za vse inštitute, ki se je pojavil hkrati z največjega nabora slovensko-angleških terminov iz dopisom Univerze in cerkvenih predstavnikov. V sindikatu računalništva in informatike. SVIZ si je kot predsednik konference visokega šolstva in znanosti aktivno prizadeval za izenačitev pedagoških in raziskovalnih poklicev z zdravniškimi, ter s tem doseči primeren status in dohodke v obeh sferah. V času pritiskov na fakultete in inštitute smo z analizo objav po Šanghajski študiji pokazali, da so slovenske inštitucije od univerz do inštitutov v svetovnem 674 9 Tekmovanja REFERENCES [1] Multikonferenca Informacijska družba, https://is.ijs.si/ [2] Hodges, A. 2014. Alan Turing: The Enigma. Princeton University Press. Prvo mesto na svetovnem tekmovanju EvAAL v 2013; 2014, [3] Gams, M. 2021. ACM Turing Award for 2020 Honors Alfred Vaino Aho uvrstitev med prvih 10 na tekmovanju Tricorder z nagradnim and Jeffrey David Ullman, Informatica, vol. 45, no. 5, Editorial. https://www.informatica.si/index.php/informatica/issue/view/226/showT skladom 10 milijonov $; nekaj prvih nagrad; 2009, 1. nagrada oc na Forumu inovacij, 1. in 2. mesto na tekmovanju Sussex- [4] Domača stran M. Gamsa: https://dis.ijs.si/mezi/ [5] Gams, M. 2001. Weak intelligence: through the principle and paradox of Huawei, 2. mesto na tekmovanju XPRIZE za kovid ukrepe in multiple knowledge, (Advances in computation, vol. 6). Huntington: Nova nagrado 250.000 $. 6 zmag od 10 udeležb na svetovnih Science. [6] Gams, M. 1988. Principi poenostavljanja v sistemih za avtomatsko učenje tekmovanjih, nikoli slabše kot četrto mesto. Po uspehih na : disertacija. Ljubljana. tekmovanjih v zadnjih letih se le nekaj laboratorijev na svetu [7] Luštrek, M., Gams, M., Bratko,I. 2006. Is real-valued minimax lahko kosa oz. je boljše kot kandidatov. pathological?. Artificial intelligence, ISSN 0004-3702, vol. 170, str. 620- 642. [8] Bratko, I., Gams, M. 1982. Error analysis of the minimax principle. V: CLARKE, M.R.B. (ur.). Advances in computer chess. 3, (Pregamon chess 10 Zaključek series). Oxford [etc.]: Pergamon Press, vol. 3, str. 1-15. [9] Matjaž Gams, M., Kos, B., (illustrator) 1985. Osnove dobrega programiranja : metode, tehnike, principi. Ljubljana: Cankarjeva založba. [10] Literatura M. Gamsa v COBISSU: Na vsakem področju posamezno so marsikje odlični http://izumbib.izum.si/bibliografije/Y20220905175100-08501.html posamezniki, ki so tam dosegli več kot kandidat, ponekod celo [11] Gjoreski, Martin, Janko, Vito, Slapničar, Gašper, Mlakar, Miha, Reščič, Nina, Bizjak, Jani, Drobnič, Vid, Marinko, Matej, Mlakar, Nejc, Luštrek, precej več, zato je nekaj posameznikov navedenih. Najbrž so Mitja, Gams, Matjaž. Classical and deep learning methods for recognizing doseženi rezultati kandidata zanimivi predvsem kot integralna human activities and modes of transportation with smartphone aktivnost v vseh omenjenih področjih. Po tem kriteriju je najbrž sensors. Information fusion, ISSN 1566-2535, 2020, vol. 62, str. 47-62, doi: 10.1016/j.inffus.2020.04.004. malo posameznikov v Sloveniji s podobnimi dosežki. Značilna [12] Revija Informatica, https://www.informatica.si/index.php/informatica je tudi izvirnost novih tez, ki marsikje naleti na odpor, kar pa je [13] GAMS, Matjaž (Author, Editor), JAKOPIN, Primož, KANIČ, Ivan, KODEK, Dušan, MOHAR, Bojan, VILFAN, Boštjan, DIVJAK, Saša, bil najpogostejši odnos do marsikaterega misleca v zgodovini. RAPOŠA, Kazimir (Editor). Računalniški slovarček : angleško-slovenski, Vprašanje seveda je, kako se bodo omenjenih dosežkov slovensko-angleški. Ljubljana: Cankarjeva založba, 1985. 226 str. spominjale naslednje generacije in ali bodo omenjeni dosežki [COBISS.SI-ID 15631617] dejansko vplivali na razvoj človeške civilizacije. Trenutne analize kažejo, da je najbolj verjetna življenjska doba človeške civilizacije med 1.000 do 10.000 leti, ker kljub starosti naše galaksije 4.6 milijarde let ni nobenega sledu o obstoječi civilizaciji ali civilizaciji, ki bi za seboj pustila kakšno sled. Verjetnost, da smo prva civilizacija v galaksiji, je minorna, verjetnost povprečnega preživetja civilizacije kot ocenjeno. Zato je za dolgoročno preživetje ključnega pomena, da gremo na Mars in nato na druga osončja. Temu bi moralo človeštvo posvetiti osrednjo pozornost in se izogniti stranpotem. Najpomembnejše odkritje je verjetno princip mnogoterega znanja, ki preprosto povedano pravi, da je več virov/modelov znanja, pametno kombiniranih skupaj, bolje kot najboljši posamezni vir/model. Princip je v navideznem konfliktu z Ockhamovim rezilom (britvijo) in tudi paradoksom mnogoterega znanja, omogoča pa razumevanje, zakaj so ljudje bolj inteligentni kot računalniki in zakaj tega konflikta v resnici ni. Inherentno ta princip uporabljajo tako nevronske mreže kot ansambelski učni algoritmi. ZAHVALA V prvi vrsti bi se zahvalil mentorju prof. dr. Ivanu Bratku, pa tudi nekaj 10 profesorjem in raziskovalcem iz njegove generacije. Vsi so pomembno vplivali na moj razvoj. Nato bi se zahvalil vsem sodelavcem, predvsem na Institutu »Jožef Stefan« ter vsem sodelavcem z drugih inštitucij, tako akademskih kot iz gospodarstva. 675 Opis dosežkov Tomaža Gornika Tomaž Gornik Better d.o.o tomaz.gornik@better.care VoiceXML in nato rešitev preko podjetja HP prodali operaterjem Megafon (Rusija) ter Etisalat in DU (Dubaj). 1 UVOD V nadaljevanju so opisani moji dosežki kot podlaga kandidature 2000-2010 za “Dvorano slavnih slovenskega računalništva in informatike”. V začetku novega tisočletja smo s pomočjo ljubljanske FRI Zadnjih štiridesetih letih se večinoma ukvarjam s tem področjem, razvili in uvedli metodologijo razvoja aplikacij Marand najprej kot srednješolski zanesenjak in tekmovalec na Application Framework (MAF) in Marand Agile Process (MAP). republiških tekmovanjih, nato študent zatem pa vodja razvoja, S tem smo poenotili in predvsem pospešili razvoj kompleksnih podjetnik in lastnik podjetij, ki razvijajo programsko opremo. V aplikacij. nadaljevanju sledi kratek povzetek ključnih mejnikov te zgodovine. Prav tako smo razširili sodelovanje s Telekomom Slovenije. Postavili smo sodobno centralno informacijsko infrastrukturo, ki je temeljila na modularnosti, aplikacijskih strežnikih, orodjih za upravljanje poslovnih procesov (BPM) in podatkovnih 2 PODJETJE MARAND skladiščih. Razvili smo ključne modularne komponente, kjer so bili podatki in programska koda združeni okoli ključne entitete 1990-1999 (Poslovni Partner, Zahtevki, Pogodbe, Storitve, Stiki), Proti koncu študija računalništva in informatike na ljubljanski Komponente smo nato povezali z BPM platformo s katero smo FRI sem leta 1989 soustanovil podjetje Marand. V začetnem integrirali tudi več kot deset drugih ključnih sistemov (regletna obdobju sem skrbel za prodajo programske opreme, kjer smo kot knjiga, finanančni sistem SAP, obračunski sistem, ipd). Sistem prvi v takratni Jugoslaviji tržili cenovno dostopno programsko je vseboval 700 različnih procesov s katerimi je 1,500 opremo predvsem podjetja Borland. Kot zanimivost naj povem, uporabnikov zagotavljalo podporo 1,2M strank. Takšno da smo ob predstavitvi novih različic Quattro Pro in Paradox leta storitveno usmerjeno (SOA) arhitekturo Telekom uporablja še 1991 napolnili Galusovo dvorano. Uspeli smo legalizirati veliko danes. kopirane programske opreme in uvesti Quattro Pro v slovensko šolstvo. Vedno smo strmeli k inovativnim pristopom, ki poskušajo neko področje standardizirati ter zagotoviti ponovno uporabo že Zatem sem v podjetju prevzel vodenje razvoja programske razvitih komponent. Zato smo se velikokrat pridružili opreme. Začeli smo z razvojem zdravstvenih informacijskih organizacijam kot je naprimer Telemanagement Forum. Vsled sistemov za potrebe bolnišnic, takrat predvsem onkološnega sodelovanja s TMF je le ta za obračun storitev kot standard inštituta v Ljubljani. Med prvimi smo v zdravstvu uporabili nove sprejel podatkovni model, ki smo ga razvili v podjetju Marand. ahitekturne pristope in tehnologije kot so odjemalec-strežnik (1993), relacijske baze podatkov (1993), javanski programski Po zagotovitvi ključnih komponent smo se na podlagi jezik (1997), tro-slojno arhitekturo (1998), popolnoma spletne omenjenega podatkovnega modela lotili še obračuna storitev. uporabniške vmesnike (2000). Slednja aplikacija, Webdoctor, je Kot zamenjavo za staro, tujo rešitev smo razvili popolnoma nov na onkološkem inštitutu v uporabi še danes. obračunski sistem, ki je temeljil na porazdeljeni arhitekturi, orodjih za poslovna pravila (BRMS) in procesiranju v pomilniku. S širitvijo interneta sredi 90 let smo začeli sodelovati s ponudniki Sistem se je pokazal kot izjemno zmogljiv, saj je več kot 1M tovrstnih storitev v Sloveniji (SiOL) in na Hrvaškem (HiNET) za faktur iz 100M zapisov o klicih za posamezen mesec pripravil v katere smo razvili sistem za upravljanje s strankami (CRM) in manj kot štirih urah. Tudi ta sistem je v uporabi še danes, po več obračun storitev. V nadaljevanju smo razvili ter integrirali vrsto kot 15 letih. storitev za ponudnike vsebin (Mobitel: glasovno pošto, orodja za konfiguracijo glasovnih storitev - IVR, mVstopnica, video Hkrati z aplikacijami za podporo ponudnikom portali, mobilno plačevanje na Petrolu, STA in Siol: uredniški telekomunikacijskih storitev smo naprej razvijali tudi sistem za portale). Pri tem smo uporabili nove pristope kot je bil informacijske sisteme na področju zdravstva. Pri tem naj omenim nacionalne projekte kot so register raka ter preventivne 676 programe za rak materničnega vratu (ZORA) in rak dojk Malte in kmalu Cipra, mesta Moskva in London, ter (DORA), ter zaledni sistem za preverjanje zavarovanja pacientov vrsta uglednih bolnišnic kot so Heidelberg, Charite, ZZZS OnLine. Oxford in Christie. • aplikacijo za upravljanje z zdravili uporablja deset Tretje področje je bilo zavarovalništvo. Za Zavarovalnico bolnišnic v Veliki Britaniji, regija v Novi Zelandiji, v Triglav smo zagotovili sistem za obračun premij in depozitov Sloveniji pa Onkološki Inštutut in UKC Ljubljana. naložbeno življenskega zavarovanja. Tudi to sodelovanje še vedno traja, že skoraj 20 let. Bolj pomembno pa je to, da prinašamo nov koncept ločevanja podatkov od aplikacij, ki povečuje innovativnost, razbija Omeniti velja še, da sem leta 2014 prevzel tudi vodenje podjetja monopole in omogoča zdravstvu postopen prehod na nove Marand. tehnologije. Pri tem smo vodilni v svetovnem merilu, kar kažejo tudi zgoraj omenjene reference. 2010-2019 Z uspehom na razpisu za nov informacijski sistem pediatrične Prav tako smo vodilni ponudnik nizko-kodnih (low-code) rešitev klinike UKC Ljubljana se je začelo novo obdobje, kjer smo se specializiranih za področje zdravstva. To je prepoznal tudi ponovno osredotočili na zdravstveno informatiko. Zagrabili smo Gartner Group in nas uvrstil med inovativna podjetja s tega priložnost in razvili popolnoma nov sistem, ki je temeljil na področja. platformi za upravljanje podatkov v odprtem formatu openEHR. Več o podjetju na www.better.care Sistem smo dograjevali in razmišljali o prodoru v tujino. Konkurenca na področju EHR (electronic health record) sistemov je izredna, uvedba zahteva tudi veliko storitev 4 ZAKLJUČEK prilagoditve in integracije. Kot majhno podjetje na tujih trgih ne bi uspeli zagotavljati tovrstnih storitev, zato smo se odločili, da se osredotočimo na dve ključni komponenti EHR sistemov - Vseskozi skušam uvesti novosti v razvoj aplikativne programske platformo za upravljanje s kliničnimi podatki ter aplikacijo za opreme, v zadnjem času predvsem na področju zdravstvene upravljanje z zdravili. informatike. Nekaj novosti, kjer smo bili pri uvedbi med prvimi (če ne čisto prvi) na svetu: Hitro smo dosegli prve uspehe,. Največji je bil odločitev mesta Moskve, da vse klinične podatke 10M prebivalcev za 1,000 • popolnoma spletni odjemalec aplikacije za bolnišnice zdravstvenih inštitucij hrani v naši platformi. (Webdoctor) leta 2000 • standardni podatkovni model sistema za Platformo smo uporabili tudi v Sloveniji, pri projektu zaračunavanje telekomunikacisjkih storitev (TMF) Integracijske Hrbtenice, ki je jedrna infrastruktura eZdravja. V • pristop Postmodern EHR - uvedba inovacijske njej se hranijo vsi podatki (odpustna pisma, napotnice, recepti, platforme ob obstoječih (legacy) sistemih povzetki zdravljenja, cepljenja, ipd), kar je omogočilo, da smo • arhitektura, ki ločuje klinične podatke od aplikacij ob nastopu pandemije na nivoju države lahko pravočasno • nizkokodna platforma specializirana za zdravstvene zagotovili SMS obveščanje o rezultatih cepljenja in digitalno aplikacije zeleno potrdilo za COVID19. • Design sistem za zdravstvene aplikacije Večina teh inovativnih rešitev je opisana v prispevkih, ki so 3 PODJETJE BETTER D.O.O. dostopni tukaj. Ko pogledam nazaj ugotavljam, da so praktično vsi razviti 2019 - sistemi še vedno v uporabi pri naročnikih, kar je presentljivo, saj Za podporo ambicijam prodora na tujih trgih smo se morali jih je veliko starih skoraj 20 let! Prav vsi temeljijo na (takrat) osredotočiti na zdravstvo. Zato smo leta 2019 razdružili podjetje novih pristopih in konceptih, ki so se skozi obdobje uporabe Marand. Nastalo podjetje Better, ki je v moji lasti, je tako izkazali za pravilne. prevzelo razvoj aplikacij za področje zdravstva in se usmerilo predvsem na tuje trge. V letu 2021 smo od 10.6M EUR Potrebno je poudariti, da nobenega od teh produktov nisem prihodkov 90% realizirali v tujini, večinoma na razvitih trgih ustvaril sam. Za največji dosežek štejem dejstvo, da mi je v teh severne Evrope. Tam imamo lastna podjetja (Velika Britanija, letih uspelo pridobiti okrog 150 sodelavcev, ki jih lahko brez Nemčija in Irska) in 20 partnerjev, med njimi ugledna podjetja zadržka postavim ob bok najboljšim s tega področja. kot so Accenture, Atos, CGI, EY, NTT Data in T-Systems. Z obema poduktoma smo v teh letih dosegli lep uspeh: • platformo uporablja več kot 150 strank v 18 državah, med drugim nacionalni sistemi Slovenije, Walesa, 677 LITERATURA Press Release: Shared care planning solution is deployed across London Press Release: Better awarded £3.1m for London-wide shared care solution Mednarodne organizacije/Konference/predavanja Press Release: Suffolk and North East Essex ICS work with Better on Skozi celotno 30 letno kariero sem redno nastopal na številnih care planning platform konferencah s področja informatike, telekomunikacij in zdravstva. Med njimi so: Presentations/Videos: • INFOS - programski odbor • Tomaz Gornik: Better Intro; video, slides • Skladišča Podatkov - organizator (s • Ian McNicol, Tomaz Gornik - openEHR intro profesorjem Krisperjem) in programski odbor • • Oliver Heinze, Deputy CIO Heidelberg University Telemanagement Forum - predavanja Hospital – The HighMed Project • Dnevi Slovenske Informatike - programski svet, predavatelj • HiGHmed Symposium: openEHR and FHIR- Friends or • HealthDay - ustanovitelj, progranski odbor, predavatelj Foes? • openEHR - organizator, programski odbor, predavatelj • John Meredith, Architect NWIS Wales – openEHR Case • HIMSS (Health Information Management Systems) - Study predavatelj • Somerset NHS Trust: Building and deploying COVID-19 • Veterans Affairs ViSTA Conference – predavatelj forms using Better Platform • World of Health IT – predavatelj • HLTH – predavatelj Articles/Whitepapers: • ViVE health – predavatelj • ReWired Health – predavatelj • DigitalHealthnet: Rethinking the architecture of health IT to • Health 2.0 - predavatelj unlock potential • eHealth Week – predavatelj • Gartner: Hype Cycle for Healthcare Providers 2020 • NHS Digital Academy - predavatelj • EY: How will you design information architecture to unlock • European Connected Health Alliance - predavatelj the power of data? • EY: Three essential shifts to build and elevate a smarter health experience Kot vabljeni predavatelj vsako leto pripravim predavanje na • podiplomskem študiju Univerity of Toronto, letos tudi na EY: Connected Health Cloud Placemat University of • Pittsburg. Enako na nekaj slovenskih fakultetah - Medicinski, Open Data Institute: Standards for data and interoperability Ekonomski, FRI. • Apperta Foundation: Defining an open Platform • Apperta Foundation: A Blueprint for a Co-Produced Še posebej sem ponosen na to, da sem bil pred leti izvoljen za Personal Health Record (CoPHR) Ecosystem sopredsedujočega upravnemu odboru neprofitne organizacije openEHR • WHO, ITU: Digital Health Platform Handbook: Building a International, ki ima sedež na UCL v Londonu. openEHR si že 25 let Digital Information Infrastructure (Infostructure) for Health prizadeva za standardizacijo kliničnih podatkov s ciljem povečanja • NHS Wales Informatics Service (NWIS): What is openEHR izmenljivosti in uporabnosti podatkov. and why is it important? • Matt Hancock: Speech at Rewired on separating data from Nagrade applications Nekaj nagrad, prejetih za informacijske rešitve: Blogs: • Best Innovation at HP Communications WorldBest To better understand our thinking, please have a look at blog posts on Innovation at HP Communications World Issued by 2008 HP Communications World, Vienna, Austria · Nov 2008 • • Več nagrad za informacijske projekte na Dnevih Slovenske Microsoft blog: Supporting openEHR with Azure Health Data Services Informatike • • Introducing FHIR Connect 2014 Best eHealth Solution by EU SME2014 Best eHealth • Solution by EU SME Issued by HIMSS/World of Health IT FHIR + openEHR 2014, Nice, France · Apr 2014 • Building a design system for digital solutions in healthcare • EU SME Instrument Horizon 2020- Maj 2014 • Why openEHR is eating healthcare • Nominacija DIGITALEUROPE’s Future Unicorn Award • Accelerating innovation in healthcare using low-code 2021 development • Turning healthcare IT architectures inside out Druge vsebine • A transformation architecture for regional health and care Better Intro slides systems Better Design System: video • Re-thinking the IT architecture of health and care Anatomy Mapper Demo video • Building better applications faster SNOMED concept linking: video • Momentum building for a new approach to EHRs, In-app communication - video • the Postmodern EHR, the enablers, the data layer, Better Digital Health Platform Whitepaper • Press Release: The Christie goes live with ePROMs patient portal the feral systems dilema and Press Release: The Christie, the largest cancer trust in Europe adopts • application centric vs. data centric interoperability. Better Platform. 678 Opis dosežkov Tomaža Kalina Tomaž Kalin tomaz@kalin.si kurzu iz Računalniških komunikacij in mrež, v Sloveniji sploh, so se kasneje pridružili analogni predmeti na dodiplomski 1 UVOD stopnji. Pri tem je bil član doktorskih komisij, mentor pri Tomaž Kalin [1,2], rojen 22.11.1936, je končal diplomski in diplomah, magisterijih in doktoratih študentov, ki so pozneje podiplomski študij na Fakulteti za naravoslovje in tehnologijo. pomembno krojili informacijsko področje v Sloveniji in posebej Izpopolnjeval se je na Rensellaer Polytechnic Instiute, Troy, za razvoj nacionalne akademske mreže, ARNES, zaslužna mgr. New York kot Fullbrightov štipendist, in nato doktoriral v M. Bonač in mgr. A.Jauk. Ljubljani. V letu 1992 je postal Generalni sekretar Evropskega združenja Po diplomi se je zaposlil na Inštitutu “Jožef Stefan” v Ljubljani, akademskih in univerzitetnih računalniških mrež, s sedežem v kjer je vpeljal računalniško zbiranje eksperimentalnih podatkov. Amsterdamu s štiriletnim mandatom. Skozi to delo je prešel na področje računalništva in nato k Po vrnitvi v domovino, leta 1996, je najprej pol leta delal kot računalniškim komunikacijam in mrežam in je delal na RRC neodvisen konzultant, nato pa je sprejel vabilo, da se vrne na IJS, (Republiški računalniški center), ki je deloval v okviru Inštituta kot pomočnik direktorja. To funkcijo je opravljal do konca leta Jožef Štefan, kot sistemski menažer. Tu je posebej treba omeniti, 2000. V tem času je v okviru KORISA sodeloval pri definiciji tudi v širšem okolju, prvo strokovno utemeljeno dogradnjo koncepta novega zakona o raziskovalni dejavnosti in dodelavi (takrat velikega) računalnika CYBER tvrdke CDC, ki je potekalo tega dokumenta. z najeto programsko opremo za simulacijo računalnika. Podatke o bremenu je zbiral eden od perifernih processorjev. Iz teh je bilo Decembra 2000 ga je Vlada republike Slovenije imenovala za zgrajeno sintetično breme, kot vhodni podatek za simulacijo državnega sekretarja na Ministrstvu za informacijsko družbo, dogradnje. Rezultat je bil presenetljiv: namesto povečanja kjer je bil odgovoren za komunikacijsko infrastrukturo. Tam je s pomnilnika in perifernih enot je bil predlagan nakup še enega skupino v nekaj mesecih pripravil ZTEL-1, zakon, ki je uskladil dodatnega računalnika. Upravni odbor RRC je to slovensko zakonodajo na področju telekomunikacij z evropsko, nekonvencionalno in tvegano rešitev sprejel in se je izkazala kot ki je šla, ob hudem nasprotovanju monopolnega Telekoma uspešna. Slovenije, radikalno daleč, recimo obveznosti, da nudi operater s pomembno tržno močjo, na razpolago konkurenci, tudi kanale in V letih 1977 / 1978 je bil zaposlen kot pomočnik direktorja drogove (kar je imela tedaj le Kanada). Pozneje pa je s sodelavci projekta COST 11 (European Informatics Network), na National prenesel v Slovenijo tudi nov zakon o poštnih storitvah, ki je dal Physical Laboratory, Teddington, Velika Britanija. To je bila podlago za sedanjo konkurenco na tem področju tudi pri nas, v prva mednarodna eksperimentalna računalniška mreža sploh. Sloveniji. Bazirala je na datagramski infrastrukturi, na višjih nivojih pa na ISO modelu. Koncem leta 2002 je sprejel, vabilo, da za omejen čas (dve leti) vodi neprofitno organizacijo DANTE, s sedežem v Cambridgeu, Od 1981 do 1984 pa je bil vodja nadaljevalnega projekta COST ki skrbi za GEANT, evropsko akademsko računalniško 11bis, s pisarno v Joint Research Centru (Evropskem skupnem infrastrukturo, na katere se vežejo vse nacionalne akademske raziskovalnem centru) v Italiji. mreže. Po povratku v Slovenijo, leta 1984, ga je Znanstveni svet inštituta Od septembra 2004 je neodvisen konzultant. Med projekti je “J.Stefan” imenoval za direktorja inštituta. To funkcijo je vredno omeniti: opravljal dva mandata, do leta 1992. - TEIN 2, projekt povezave GEANT s kitajsko raziskovalno informacijsko infrastrukturo, ki ga EU Že pred odhodom v Italijo, in vsa leta, ko je bil direktor IJS, je so-financira z okrog 10 MEUR. predaval na Fakulteti za elektrotehniko in računalništvo - Drugi projekt je svetovanje nemškemu ministrstvu predmete iz področja računalniških komunikacij in mrež, na BMBF okrog tehničnih elementu in politike pri dodiplomski in podiplomski stopnji. Prvemu podiplomskemu 679 razvoju akademske komunikacijske infrastrukture v Nemčiji. V času delovanja na področju elektronskih komunikacij je bil član različnih mednarodnih teles in delovnih skupin, kot: - Information Society Technology Committee (nadzor IST v 5. Okvirrnem programu), - ONP Committee (Svetovalni organ EC za področje komunikacij), in drugih. - Je ustanovni član Internet Society (ISOC, Reston Virginia) in je bil dva mandata član njenega Upravnega odbora. In dva mandata podpredsednik. - Od leta 2009 do 2013 je bil član in podpredsednik Nadzornega sveta Telekoma Slovenije. - Posebno je ponosen, da je bil član delovne skupine, ki jo je ustanovila Komisija EU, za pripravo pomembnega dokumenta, ki je dokazal nujnost financiranja akademske komunikacijske infrastrukture s strani Komisije EU. Rezultat je organizacija GEANT, ki jo z nekaj dest milijoni letno sofinancira EU. Brez posebnega olepševanja je mogoče, iz navedenega sklepati, da je Tomaž Kalin pomembno prispeval k razvoju informatike in elektronskih komunikacij v Sloveniji in tudi v širšem okolju. LITERATURA [1] Wikipedija https://sl.wikipedia.org/wiki/Toma%C5%BE_Kalin [2] Splet elektronskih komunikacij https://www.386tele.com/content/view/5102/105/ 680 Evolucija predmeta Računalništvo in informatika v obdobju dveh desetletij Evolution of course Computer Science and Informatics in two decades Robert Leskovar Univerza Maribor, Fakulteta za Laboratorij za kakovost in organizacijske vede testiranje programske opreme Kranj, Slovenija robert.leskovar@um.si POVZETEK Prispevek obravnava evolucijo predmeta Računalništvo in 1 UVOD informatika, ki sem ga predaval v obdobju 1998-2021 na Predmet z nazivom Rac unalnis tvo in informatika na Fakulteti Fakulteti za organizacijske vede Univerze v Mariboru tako na za organizacijske vede Univerze Maribor ima zac etke v letu visokošolskem kot tudi na univerzitetnem programu. 1975, ko so na takratni Visoki s oli za organizacijo dela v Predmet pa so moji predhodniki razvijali že od leta 1975 Kranju dobili dovoljenje za izvajanje s tudijske smeri, ki se je dalje, ko je bila formalno potrjena Računalniška usmeritev. imenovala Rac unalnis ka usmeritev. Leta 1979, ko sem postal Moje obdobje lahko razdelim v štiri faze: a) diskete in CD, b) s tudent, je bil moj profesor Sas a Dekleva. Starejs a s tudenta lokalizacija in enostavne interakcije s sistemom za podporo Igor Korelic in Bojan Pec ek sta sodelovala pri izvedbi vaj, ki učenja Moodle, c) integracija Moodle in videokonferenčnega so potekale na Deltinem (PDP-11) rac unalniku z sistema BigBlueButton ter d) oddaljeno namizje in vsebniki. vec uporabnis kim operacijskim sistemom RSX-11M. Podane so značilnosti posameznih faz in usmeritve za Zaganjali smo programski jezik Basic, pa Datatrieve-11. S prihodnost. slednjim smo lahko definirali zapise in poizvedovali po podatkih. Po odhodu profesorja Dekleve v ZDA je predmet KLJUČNE BESEDE prevzel profesor Miro Gradis ar. Pri vajah sta mu pomagala Računalništvo in informatika, predmet, Fakulteta za Polde Podlogar in Joz ef Langerholz. Profesor Gradis ar je organizacijske vede napisal imeniten uc benik za predmet Rac unalnis tvo in ABSTRACT informatika, ki so ga uporabljali med drugim tudi na Ekonomski fakulteti Univerze v Ljubljani. Tja se je okoli leta The paper presents the evolution of the course Computer 1998 tudi prezaposlil. Ko mi je bil ponujen predmet Science and Informatics, which I taught in the period 1998- Rac unalnis tvo in informatika, sem ga z velikim veseljem tudi 2021 at the Faculty of Organizational Sciences, University of prevzel. Bilo je 45 ur predavanj in 45 ur vaj, tako na Maribor, both in the higher professional education and vis jes olskem kot tudi na univerzitetnem s tudiju. Vsebino bi university programs. The course was developed by my najprimerneje opisal kot uvod v rac unalnis tvo in predecessors from 1975 onwards, when the major study in informatiko. Ker je bil to skupni predmet 1. letnika za vse Computer Science was formally approved. Personally, I see dodiplomske programe (kadrovska, proizvodna in my teaching in four phases: a) floppy disks and CDs, b) rac unalnis ka usmeritev), je seveda obsegal mehkejs i nabor z localization and simple interactions with the Moodle druz boslovimi aspekti, nekaj zgodovine in principov v learning management system, c) integration of Moodle and rac unalnis tvu, pa seveda praktic ne vaje s pisarnis kimi orodji. the BigBlueButton videoconferencing system, and d) remote Ker sem imel nekaj izkus enj s programskimi jeziki in bazami desktop and virtualization. The characteristics of these podatkov, sem to z elel vpeljati. Takrat smo uporabljali phases and directions for the future are presented. rac unalnik VAX 750 in operacijski sistem VAX/VMS, katerega znac ilnost je bila, da je lahko disk postal dodaten pomnilnik. KEYWORDS V rac unalnis kih uc ilnicah so bili osebni rac unalniki z Computer Science and Informatics, course, Faculty of operacijskim sistemom Windows 95 in Windows NT. Selitev Organizational Sciences fakultete v nove prostore leta 1999 je omogoc ila bistveno boljs e s tudijske pogoje in odpirala nove moz nosti. ∗Article Title Footnote needs to be captured as Title Note †Author Footnote to be captured as Author Note Permission to make digital or hard copies of part or all of this work for personal 2 DISKETE IN CD (1998-2004) 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 C eprav je bila to z e doba interneta (na voljo so bili tudi 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). strez niki FTP in HTTP), so se s tudijski materiali vec inoma Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia izmenjevali prek disket in CD. S tudentom sem na teh medijih © 2022 Copyright held by the owner/author(s). 681 dal zapiske predavanj v MS Powerpoint in MS Word, videoposnetke in razne programe kot sta prevajalnik GNU C++ in simulator mikroprocesorja SMS32. Slednjega je avtor Neil Bauers leta 2003 sprva kot preskusni program (shareware) naloz il na spletno stran https://softwareforeducation.com (od leta 2022 ni vec dostopna). Simulator je oponas al delovanje 8-bitnega mikroprocesorja z 256 bajti pomnilka in 6 vhodnimi/izhodnimi napravami. Napisan je bil v Borlandovem Turbo Pascalu (32-bitna verzija), zadnja leta pa je bil licenciran kot GNU GPL. Zato je bila dostopna tudi izvorna koda Omogoc al je pisanje v zbirniku podobnem jeziku, izvajanje posameznih ukazov, prikazoval je stanje s tirih splos nih in s tirih specialnih registrov (v dvojis kem, Slika 1: Uporaba foruma v letu 2004 desetis kem in s estnajstis kem sistemu) kot tudi pomnilnika (ASCII, izvorna koda, s estnajstis ka predstavitev ukazov in Poleti istega leta sem Moodle prevedel v slovenski jezik in ga operandov). Zelo zabavna moz nost je bila direktno dal v splos no uporabo. Po zac etnih tez avah s kodno tabelo se naslavljanje pomnilnika in spreminjanje vsebine – v je sistem za uc no podporo Moodle zac el s iriti v osnovnih in , izvornem programu je bil npr. ukaz za dodajanje (ADD), nato srednjih s olah. Tudi Univerza v Mariboru ga je okoli leta 2007 je ukaz MOV v pomnilniku zamenjal vsebino z s estnajstis ko prepoznala kot primernega. Moodle smo s skupino kodo drugea ukaza (npr. SUB). Program je namesto podiplomskih s tudentov okoli leta 2007 s e enkrat prevedli ses tevanja izvajal ods tevanje. Spreminjanje stanja naprav in dopolnili (verjetno je bila to verzija 1.7), nato pa so (npr. 64 znakovnega prikazovalnika, dveh semaforjev, prevajanje prevzeli drugi. V tem obdobju je bil izveden korac nega motorja) je bilo prikazano v posebnih oknih. Ta prehod na Linux-ov strez nik (Ubuntu), uvedli smo protokol simulator mikroprocesorja je bil na nek nac in napoved https, iz fizic nega strez nika pres li na virtualnega. To obdobje Interneta stvari in kiberfizic nih sistemov, ki sta se pojavila karakterizira enostavna interakcija profesor-s tudent in tudi vec kot deset let kasneje. Pomembno mi je bilo, da so s tudent-s tudent. Vsak s tudent je dobil uporabnis ko ime in s tudenti lahko “videli” delovanje procesorja in so lahko geslo, s katerim je dostopal do uc nih gradiv, sodeloval v napisali preprost program v jeziku, ki je podoben zbirniku klepetalnici in forumu ter oddal res itev nalog. C eprav je x86. V tej fazi evolucije predmeta smo poskus ali tudi z Moodle zelo hitro vkljuc eval dodatne funkcije, je bila jezikom C++, vendar so le redki s tudenti imeli svoj osebni primarna naloga strez nika olajs ati dostop do s tudijskih rac unalnik, s e redkejs i pa so uspeli namestiti prevajalnik. V gradiv ter komuniciranje. Nekaj prvih let je bila silno generacijah, ki so prihajale, so bile velike razlike v zanimiva klepetalnica, ki je omogoc ala celi skupini s tudentov teoretic nem in uporabnem znanju informatike [1]. V (nekaj deset) istoc asno odzivanje, deljenje izkus enj, naslednjih letih smo s soavtorji s e vec krat prouc evali ta res evanje razlic nih tez av pri dostopu do interneta, uc nega fenomen. Za boljs o interakcijo s s tudenti in med s tudenti sem strez nika in res evanja nalog. Dosez en je bil tudi vsebinski iskal orodje za celovito pomoc pri izvedbi s tudijskega premik pri predmetu Rac unalnis tvo in informatika. Poleg procesa. prej omenjenega zbirnika in osnov jezika C++ sem vkljuc il s e PHP, Tega sem ga ob prevajanju Moodla dobro spoznal (skupaj z bazo podatkov). Res itve “domac ih” nalog so 3 LOKALIZACIJA IN ENOSTAVNE s tudenti z e oddajali na Moodle. Pregledovanje oddanih INTERAKCIJE S SISTEMOM ZA PODPORO res itev je bilo zame zaradi velikih skupin (samo vis jes olcev je UČENJA MOODLE (2004-2013) bilo preko sto) vse prej kot zanimivo. Predmet pa je bil v letu 2005 akreditiran v bolonjskem visokos olskem (6 ECTS) in Moodle 1.3 sem 16.5.2004 namestil na strez nik z univerzitetnem programu (7 ECTS) Organizacija in operacijskim sistemom Windows in ga testiral s management informacijskih sistemov. V prvem letniku je bil podiplomskimi s tudenti. Na sliki 1 je prikazan del forumske obvezni predmet za bruce vseh dodiplomskih programov, diskusije, ki je bila namenjena predstavitvi sos olcev (vsak je fond kontaktnih ur pa se je zmanjs al zaradi varc evanja. po kratkem intervjuju predstavil drugega sos olca). Zaradi velikih razlik v predznanju s tudentov smo to analizirali in objavili v [2], [3], [4] in [5]. V [6] smo poroc ali tudi o preverjanju znanja s programom Perception in o izkus njah z Moodlom v [7]. Ob koncu tega obdobja se je Slovenija s e vedno ukvarjala s posledicami svetovne gospodarske krize, ki se je pri s tudentih manifestirala kot poglabljanje razlik med tistimi, ki so imeli na voljo IKT in tistimi, ki so zgolj slis ali, da obstaja internet. Po nakljuc ju sem leta 2013 dobil v uporabo delovno postajo Supermicro (16 CPU, 24 GB pomnilnika in 1 TB diska ) ter jo med poc itnicami spremenil v videokonferenc ni strez nik. V zadnjih letih tega 682 obdobja sem vse bolj uporabljal distribucijo Kubuntu tudi na 5 ODDALJENO NAMIZJE IN VSEBNIKI (2018- osebnem rac unalniku, ob seveda prevladujoc ih oknih. 2021) Moz nosti odprtokodnih alternativ so me vedno bolj navdus evale. Virtualni stroj, ki so si ga s tudenti names c ali na lastne osebne rac unalnike, je zasedel le okoli 10GB, vendar je bila vc asih strojna oprema s tudentov s e vedno preskromna. Leta 2018 4 INTEGRACIJA Moodle – BigBlueButton IN smo skupaj s sodelavci Centra za informacijske tehnologije VIRTUALIZACIJA (2013-2018) sestavili strez nik s 128 GB pomnilnika, 16 CPU /32 niti in 1 TB diska s tehnologijo NVMRAM. Kot hipervozor smo BigBlueButton (kratica BBB) v. 0.8 je tekel na operacijskem uporabili Proxmox, nanj pa sem namestil virtualni stroj sistemu Ubuntu 10. Ker sem imel na voljo dovolj c asa in (operacijski sistem Kubuntu 18). Na tem je imel vsak s tudent ustrezno strojno opremo (prej navedeno delovno postajo), svoj uporabnis ki rac un, omogoc en oddaljen dostop in mi je uspelo videokonferenc ni sistem poleti 2013 prenesti na grafic ni uporabnis ki vmesnik KDE. Za potrebe s tudijskega operacijski sistem Ubuntu 12. Verjetno je bila to ena redkih procesa pri predmetu Rac unalnis tvo in informatika sem implementacij na tem operacijskem sistemu v svetovnem namestil C++, Javo, PHP, NetBeans, RStudio, Scilab, KDEnlive, merilu. Sprva sem BBB zaganjal na fizic nem strez niku, nato SMS32, wine, GPG, GPA, Apache server, phpmyadmin, pa sem ga virtualiziral v VirtualBox-u. V Moodle (tudi z e LibreOffice in s tevilne druge. Portfelj nalog je bilo moz no virtualiziran) sem vstavil vtic nik za videokonferenc ni sistem res iti z navedenimi orodji zgolj z uporabo varne povezave BBB in z e je bila odprta moz nost za delo na daljavo. Seveda preko VPN in odjemalca za oddaljeno namizje. Na smo pri predmetu Rac unalnis tvo in informatika to takoj oddaljenem strez niku je bil names c en docker OpenProject s zac eli uporabljati. Ob zac etnem navdus enju, da zadeva povezavo na strez nik LDAP (implementiran kot Linuxov deluje, pa so se pokazale nove moz nosti. Transfer znanja vsebnik na hipervizorju). OpenProject je odprtokodni sistem med vrstniki se je izboljs al pri res evanju nalog v C++, Javi in za vodenje projektov, ki smo ga s skupino dodiplomskih SQL. Kot predavatelj sem lahko na daljavo demonstriral s tudentov tudi lokalizirali v slovenski jezik. Za s tudente vis jih razvoj preprostih programov, delovanje razlic nih letnikov sem za njihove razvojne projekte namestil tudi odprtokodnih res itev na Linux-u. BBB je sprva kot strez nik GitLab. Eden od rezultatov podiplomskega s tudenta uporabnis ki vmesnik uporabljal Adobe Flash Player. Ta je Luka Berganta je simulator mikroprocesorja SMS32, povzroc al s tudentom kar nekaj zac etnih tez av, ko pa so implementiran v razvojnem okolju Lazarus za operacijski uredili varnostne izjeme, slus alke in mikrofone, je bila sistem Linux. Repozitorij projekta je na strez niku GitLab. S omogoc ena zelo dobra komunikacija profesor-s tudent in tem je prenesena koda iz leta 2003 v polni meri zasijala na s tudent-s tudent. BBB od verzije 2.0 uporablja odjemalca distribuciji Kubuntu brez emulatorja wine. HTML5, kar omogoc a tudi enostavno uporabo na vseh Predmet trenutno obsega 39 ur predavanj in 24 ur vaj – oboje mobilnih napravah. V tem obdobju se je del kontaktnih ur z aktivnim sodelovanjem preko videokonferenc in delom na (30-49%) pri predmetu Rac unalnis tvo in informatika z e oddaljenem namizju ter v rac unalnis ki uc ilnici. Od leta 2018 izvajal preko videokonference. To je bila zame zelo dobra je na voljo tudi ena uc ilnica s tankimi odjemalci na platformi priprava na spremembe pri predavanjih, ki jih je prinesel Raspberry PI. Vsebinsko predmet ponuja pregled Covid-19. Analizirali smo uspes nost pri izpitih iz predmeta informacijske druz be in digitalnega sveta, zgodovine in Rac unalnis tvo informatika s posebnim povdarkom na definicij v rac unalnis tvu in informatiki, pregled strojne, udelez bi s tudentov na klasic nih in videokonferenc nih mrez ne in programske opreme, seznanitev in delo z predavanjih in vajah [8] in [9]. V tem obdobju sem za operacijskima sistemoma Windows in Linux, osnove s tudente poleg gradiv na uc nem strez niku pripravil tudi programskih jezikov C++ Java in PHP, uvod v objektno virtualiziran stroj z operacijskim sistemom Kubuntu (16.04 programiranje z orodjem Greenfoot. Na vajah s tudenti delajo in 18.04). S tudenti so si na svoje osebne rac unalnike naloz ili tudi s pisarnis kimi orodji MS (Word. Powerpoint, Access). Virtualbox in nato uvozili pripravljen virtualni stroj. Ta je Portfeljske naloge zahtevajo uporabo spletnega brskalnika, vseboval: prevajalnik C++, interpreter PHP, Javansko video urejevalnika, Scilab, R, C++, Jave, PHP, baze mysql in razvojno in izvajalno okolje (JDK in JRE), integrirano orodja za malokodni razvoj spletnih aplikacij Oracle APEX razvojno orodje NetBeans (C++, PHP, Java), lokalni spletni [10]. Z izjemo slednjega so vsa orodja dostopna na strez nik Apache, orodje phpmyadmin in simulator oddaljenem namizju. mikroprocesorja SMS32, ki je sicer aplikacija za operacijski sistem Windows. Zato je bil v virtualnem stroju names c en emulator wine, ki je brez tez av pognal datoteko EXE. Za 6 USMERITVE ZA PRIHODNOST s tudente sem pripravil tudi portfelj nalog, ki jih je moz no res iti s prej navedenimi orodji (odprtokodna). Glavne tez ave Zadnje obdobje prav gotovo zaznamuje koncept pri s tudentov so bile s e vedno preskromna strojna oprema malokodnega programiranja, ki je z e vkljuc eno v s tudijske njihovih osebnih rac unalnikov ter tovarnis ko onemogoc ena vsebine tudi pri predmetu Rac unalnis tvo in informatika. virtualizacija (BIOS ali Windows). To je bil tudi glavni razlog Odpirajo se moz nosti uporabe oblac ne infrastrukture kot za pripravo strez nika, ki bi omogoc al s tudentom oddaljeno storitve. Primer za to je Oracle Cloud Infrastructure. Ta namizje. omogoc a vsakemu s tudentu vzpostavitev in zagon arhitekturnih virov: virtualnega omrez ja, procesor, 683 pomnilnik, disk, bazo podatkov, podatkovno analitiko, razvoj za šolstvo, 2004. 6 str., tabele. ISBN 961-6101-21-8. [COBISS.SI-ID in uporabo metod strojnega uc enja in umetne intelligence. 4180243] [6] ZUPAN, Neja, MAYER, Janez, LESKOVAR, Robert. Elektronsko Izkustveno in problemsko zasnovano uc enje sta kljuc na za to, preverjanje znanja s programom Perception = Electronic testing of da s tudenti ne ostanejo zgolj kupci, temvec kreatorji novega students using the Perception software. V: RAJKOVIČ, Vladislav (ur.). znanja. Upam, da sem v zadnjih dveh desetletjih c imvec Management sprememb : zbornik 25. mednarodne konference o s tudentom odpiral to moz nost tudi z vsebinami predmeta razvoju organizacijskih znanosti, Slovenija, Portorož, 15.-17. marec 2006 = Change management : proceedings of the 25th International Rac unalnis tvo in informatika. Conference on Organizational Science Development, Slovenia, Portorož, March, 15th-17th 2006. Kranj: Moderna organizacija, 2006. Str. 350-362. ISBN 961-232-186-8. [COBISS.SI-ID 4829971] REFERENCES [7] LESKOVAR, Robert. Podpora izvajanja študija s paketom "Moodle" - [1] ZUPAN, Neja, LESKOVAR, Robert. Teoretično in uporabno znanje izkušnje in perspektive = Studies implementation support using the informatike ob vstopu na fakulteto. V: HERIČKO, Marjan (ur.), et al. "moodle" package - experience and perspectives. V: KALUŽA, Jindřich Informacijska družba IS'2002 = Information society IS'2002 : zbornik (ur.). Sinergija metodologij : zbornik 24. mednarodne konference o D 5. mednarodne multi-konference, 14. do 18. oktober 2002, razvoju organizacijskih znanosti, Slovenija, Portorož, 16.-18. marec Ljubljana, Slovenia. Ljubljana: Institut Jožef Stefan, 2002. Str. 156. 2005 = Synergy of methodologies : proceedings of the 24th International ISBN 961-6303-43-0. [COBISS.SI-ID 7506198] Conference on Organizational Science Development, Slovenia, Portorož, March 16-18, 2005. Kranj: Moderna organizacija, 2005. Str. 550-557. [2] ZUPAN, Neja, LESKOVAR, Robert, MAYER, Janez. Influence of prior ISBN 961-232-175-2. [COBISS.SI-ID 4526867] knowledge in information science on results at university. V: JAŠKOVÁ, Mária (ur.). ECON '04 : [selected research papers]. Ostrava: [8] LESKOVAR, Robert, BAGGIA, Alenka. Udeležba na predavanjih ter Technical University of Ostrava, Faculty of Economics, 2004. Str. 426- uspeh pri opravljanju izpita = Lecture attendance and exam 442. Research works proceedings, Vol. 11, 2004. ISBN 80-248-0674- performance. V: DOUCEK, Petr (ur.), NOVAK, Aleš (ur.), PAAPE, Björn 6. ISSN 0862-7908. [COBISS.SI-ID 4389139] (ur.). Trajnostna organizacija : zbornik 35. mednarodne konference o razvoju organizacijskih znanosti = Sustainable organization : [3] ZUPAN, Neja, LESKOVAR, Robert, BERNIK, Igor, MAYER, Janez. Znanje proceedings of the 35th International Conference on Organizational informatike visokošolskih študentov ob vstopu na fakulteto. V: Science Development. 35. Mednarodna konferenca o razvoju RAJKOVIČ, Vladislav (ur.), URBANČIČ, Tanja (ur.), BERNIK, Mojca organizacijskih znanosti, Portorož, 16.-18. marec 2016. Kranj: (ur.). Vzgoja in izobraževanje v informacijski družbi. Kranj: Moderna Moderna organizacija, 2016. Str. 490-498. ISBN 978-961-232-285-4. organizacija, 2004. Str. 500-506, tabele. Organizacija, Letn. 37, 2004, [COBISS.SI-ID 7530003] št. 8. ISSN 1318-5454. [COBISS.SI-ID 4179219] [4] [9] LESKOVAR, Robert, BAGGIA, Alenka. Zločin in kazen : udeležba na ZUPAN, Neja, LESKOVAR, Robert, BAGGIA, Alenka, MAYER, Janez, BERNIK, Igor. Spremljanje znanja iz informatike ob vstopu na avditornih in videokonferenčnih predavanjih ter uspešnost reševanja fakulteto. V: Management, knowledge and EU : proceedings of the 23rd nalog = Crime and punishment : participation in auditoria and videoconference lectures and problem solving performance. V: International Conference on Organizational Science Development = BERNIK, Mojca (ur.), RAJKOVIČ, Uroš (ur.). Vzgoja in izobraževanje v Management, znanje in EU : zbornik 23. mednarodne znanstvene informacijski družbi - VIVID 2015 : zbornik referatov = Education in konference o razvoju organizacijskih ved, Slovenija, Portorož, 24.-26. information society : conference proceedings. 18. mednarodna marec 2004. Proceedings of the 23rd International Scientific multikonferenca Informacijska družba IS 2015, 28. in 29. september Conference on organizational Science Development, Slovenia, 2015 = 18th International Multiconference Information Society IS Portorož, March, 24th-26th 2004. Kranj: Moderna organizacija: = 2015, 28th & 29th September 2015, Ljubljana, Slovenia. Kranj: Modern Organization, 2004. Str. 279-287. ISBN 961-232-167-1. Fakulteta za organizacijske vede, 2015. Str. 287-296. ISBN 978-961- [COBISS.SI-ID 4124947] 232-284-7. http://vivid.fov.uni-mb.si/sites/vivid.fov.uni- mb.si/files/VIVID2015-web.pdf. [COBISS.SI-ID 7510035] [5] ZUPAN, Neja, LESKOVAR, Robert, BERNIK, Igor, MAYER, Janez. Znanje informatike visokošolskih študentov ob vstopu na fakulteto. V: [10] BAGGIA, Alenka, MALI, Aljaž, GRLICA, Andrej, LESKOVAR, Robert. RAJKOVIČ, Vladislav (ur.), URBANČIČ, Tanja (ur.), BERNIK, Mojca Oracle APEX v visokošolskem izobraževanju = Oracle APEX in higher (ur.). Vzgoja in izobraževanje v informacijski družbi : zbornik education. V: ARSENIJEVIĆ, Olja (ur.), et al. Organizacija in referatov = Education in information society : conference negotovosti v digitalni dobi : konferenčni zbornik = Organization and proceedings. 7. mednarodna multi-konferenca Informacijska družba uncertainty in the digital age : conference proceedings. 37th IS 2004, 15. oktober 2004, Ljubljana, Slovenija = 7th International International Conference on Organizational Science Development, Multi-Conference Information Society IS 2004, 15th October, 2004. 21st - 23rd March 2018, Portorož, Slovenia. 1. izd. Maribor: Ljubljana: Ministrstvo za šolstvo, znanost in šport: Fakulteta za Univerzitetna založba Univerze, 2018. Str. 27-38, ilustr. ISBN 978- organizacijske vede: Institut Jožef Stefan: Zavod Republike Slovenije 961-286-146-9. http://press.um.si/index.php/ump/catalog/book/326. [COBISS.SI- ID 8000019] 684 Dosežki kandidata Domna Mongusa Achievements of the candidate Domen Mongus† GeMMA Lab University of Maribor Maribor, Slovenia domen.mongus@um.si POVZETEK • 2014 – Nagrada za izjemen dosežek slovenske znanosti, Agencija za raziskovanje Republike V tem prispevku so predstavljeni dosedanji dosežki kandidata Slovenije Domna Mongusa na pedagoškem, znanstveno-raziskovalnem in • 2015 – Ime tedna, RTV Slovenija, Val 202 projektnem področju ter področju mednarodne vpetosti. Iz • 2015 – Mladi znanstvenik Podonavske regije, Inštitut vsebinskega vidika predstavljeni dosežki obsegajo razvoj novih za Podonavsko regijo in centralno Evropo (ang. metodologij obdelave podatkov daljinskega zaznavanja, Institute for the Danube Region and Central), Europe, arhitektur podatkovnega zlivanja in metod lokacijske inteligence Ministrstvo republike Avstrije za znanost, za razvoja naprednih geografskih informacijskih sistemov. raziskovanje in ekonomijo (ang. Austrian Federal Ministry for Science, Research and Economy) KLJUČNE BESEDE • 2015 – Nagrada za tekoče dosežke na področju informacijske družbe, Informacijska Družba 2015 Dosežki, znanstveno delo, raziskovalni prispevek, pedagoška • 2018 – Najvišja nagrada Univerze v Mariboru za aktivnost, izvedeni projekti Izjemne prispevke k znanstvenemu in pedagoškemu ugledu in odličnosti Univerze v Mariboru ABSTRACT • 2019 – Nagrada za izjemne raziskovalne dosežke na This paper presents the achievements of Domen Mongus from Fakulteti za Elektrotehniko Računalništvo in pedagogical, scientific, research and project perspectives, and in Informatiku, Univerze v Mariboru. the light of his international involvement. The presented achievements include author’s contributions to the development V nadaljevanju tega prispevka so predstavljeni nekateri of novel remote sensing data processing methodologies, data pomembnejši prispevki kandidata po vsebinskih sklopih. fusion architectures and location intelligence methods for the development of advanced geographic information systems. 2 PEDAGOŠKO DELO KEYWORDS Domen Mongus deluje v okviru Laboratorija za geoprostorsko modeliranje, multimedijo in umetno Achievements, scientific work, research contributions, inteligenco (GeMMA) na Fakulteti za elektrotehniko, pedagogic activities, completed projects računalništvo in informatiko, Univerze v Mariboru, kjer je pričel s pedagoškim delom kot asistent, v času raziskovalnega usposabljanja za mladega raziskovalca. Po 1 UVOD uspešnem zaključenem doktorskem študiju je okoli pol leta Domen Mongus je kandidat za »galerijo slavnih na področju deloval kot asistent z doktoratom s polno pedagoško računalništva in informatike«. Njegovo delo obsega obremenitvijo, po izvolitvi v naziv docenta pa je prevzel pedagoške, znanstveno-raziskovalne in projektne aktivnosti. izvajanje treh predmetov na univerzitetnih študijskih V nadaljevanju je v kronološkem vrstnem redu podan programih Računalništvo in informatika (UM-FERI), povzetek najodmevnejših nagrad in priznanj, ki jih je za Medijske komunikacije (UM-FERI) in Bioinformatika svoje delo kandidat prej v zadnjih desetih letih: (UM-FZV) in nadaljeval z vodenjem vaj. Ob izvolitvi v • naziv izrednega profesorja je v celoti prevzel delo 2012 – Nagrada za izjemne znanstvene dosežke, UM- FERI predavatelja in opravljal 6-10 ur predavanj tedensko pri prej • omenjenih študijskih programih ter predmetih iz programov 2013 – Nagrada za pedagoško odličnost, UM-FERI ERASMUS. Poleg uspešno zaključenega mentorstva mlademu raziskovalcu je bil do danes mentor pri 13 magistrskih delih in 38 diplomskih delih. ∗Article Title Footnote needs to be captured as Title Note †Author Footnote to be captured as Author Note V svojem pedagoškem delovanju je vodil več študentov, ki Permission to make digital or hard copies of part or all of this work for personal or so dosegli opazne mednarodne dosežke. Med slednje lahko classroom use is granted without fee provided that copies are not made or distributed štejemo objave v najprestižnejših mednarodnih revijah (na for profit or commercial advantage and that copies bear this notice and the full primer IEEE transactions on neural networks and learning citation on the first page. Copyrights for third-party components of this work must systems [6] in ISPRS Journal of Photogrammetry and be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Remote Sensing [4]) in nagrade za članke, objavljene na © 2022 Copyright held by the owner/author(s). mednarodnih znanstvenih konferencah. Primer slednjega je 685 dr. Marko Bizjak, ki je s člankom »Segmentacija oblaka tudi pošta Republike Irske. Uporabljen koncept učinkovite točk z lokalnim prileganjem ploskev« zmagal na predstavitve podatkov LiDAR pa ima mednarodno zaščito s tekmovanju študentskih člankov na konferenci ERK 2015 podeljenim patentom v ZDA [5]. Za programski paket in bil uvrščen med 5 najboljših člankov študentskega gLiDAR je Domen Mongus leta 2015 prejel tudi nagrado IS tekmovanja IEEE, Regije 8 – Evropa, Bližnji vzhod in za tekoče delo. Afrika. 3.2 Arhitekture zlivanja podatkov za luščenje Leta 2013 je Domen Mongus prejel tudi nagrado za značilk pedagoško delo na Fakulteti za elektrotehniko, računalništvo in informatiko, Univerze v Mariboru. Svoje delo na področju obdelave podatkov LiDAR je kandidat kasneje nadgradil z razvojem novih arhitektur podatkovnega zlivanja in luščenja značilk iz 3 RAZISKOVALNO DELO komplementarnih podatkovnih virov. Nizkonivojski pristopi k časovno-prostorski podatkovni poravnavi in V svojem dosedanjem raziskovalnem delu se je kandidat osredotočil na razvoj novih arhitektur zlivanja podatkov, pri strukturiranju podatkovnih slojev, ki jih je v tem kontekstu čemer njegovi najpomembnejši raziskovalni dosežki razvil kandidat, danes predstavljajo ogrodje zaledne obsegajo nove metodologije obdelave podatkov daljinskega informacijske infrastrukture več nacionalnih distribucijskih zaznavanja, senzorskih podatkov ter implementacij sistemov prostorskih podatkov. Kandidat je tako med naprednih geografskih informacijskih sistemov za namene drugim načrtoval nacionalni distribucijski sistem podatkovno podprtega odločanja. V nadaljevanju so v prostorskih podatkov Geodetske Uprave Republike kronološkem zaporedju predstavljeni ključni kandidatovi Slovenije (GURS), Sistem medopravilne infrastrukture dosežki po tematskih sklopih. Ministrstva za okolje in prostor (MOP) in Sistem za obvladovanje naravnih nesreč (angl. disaster risk 3.1 Obdelava podatkov LiDAR management system) Republike Srbije. V času svojega doktorskega študija se je kandidat posvetil Na mednarodnem nivoju je kandidat razvite arhitekturne razvoju novih metod obdelave podatkov, zajetih s koncepte zlivanja podatkov za področja obdelave tehnologijo LiDAR (angl. Light Detection and Ranging), ki velepodatkov (angl. BigData), interneta stvari (angl. je takrat predstavljala enega večjih tehnoloških prebojev na Internet of Things) in odprtih podatkov (angl. Open Data) področju zemeljskih opazovanj. Kandidat je pomembno predstavil tudi v obliki usmerjevalnih člankov, ki jih je prispeval k utemeljitvi uporabe tako imenovanih izdala Krovna evropska organizacija za geografske diferencialnih atributnih profilov, ki izhajajo iz teorije informacije EUROGI (angl. European Umbrella matematične morfologije in danes predstavljajo enega izmed ključnih orodij za luščenje značilk iz topološko Organisation for Geographic Information) [7]. nestrukturiranih oblakov točk. Njegovo delo na področju generiranja digitalnih modelov reliefa iz podatkov LiDAR, Iz teoretičnega vidika pa je nedavno razvil novo objavljeno v članku [1], danes velja za drugo najbolj metodologijo učenja razložljivih značilk [7] in jo objavil v citirano delo na področju glede na bazo Google Scholar. reviji IEEE transactions on neural networks and learning Nadaljevanje tega dela, objavljeno v članku [2], pa je systems s faktorjem vpliva IF = 14,255. prejelo nagrado Odlični v znanosti 2013 s strani Agencije za Raziskovanje Republike Slovenije. Za svoje delo na področju razpoznave dreves, objavljeno v članku [ 3.3 Lokacijska inteligenca 3], mu je Inštitut za Podonavsko regijo in centralno Evropo (ang. Razvite koncepte podatkovnega zlivanja kandidat pri Institute for the Danube Region and Central Europe) v svojem trenutnem delu nadgrajuje v celostne sisteme okviru Podonavske konference Združenega raziskovalnega lokacijske inteligence. Rezultati tega dela pa so že vidni v centra Evropske komisije (angl. Joint Research Centre, večih večjih operativnih sistemih, ki temeljijo na konceptih European Commission) podelil naziv Mlad znanstvenik tako imenovanih digitalnih dvojčkov. Podonavske Regije 2015 (angl. Danubius Young Scientist Award 2015). Predstavljena metodologija pa, predvsem zaradi specifik učnih podatkov, tudi v dobi globokega Kandidat je tako osnoval in skupaj s sodelavci uspešno učenja razvil in vpeljal v operativno okolje podjetja ELES d.o.o. , še vedno spada med najučinkovitejše pristope k obdelavi podatkov LiDAR. prvi digitalni dvojček naravnega ekosistema v svetovnem merilu. Slednji omogoča samodejno izgradnjo digitalnih Razvito metodologijo je kandidat izdal v obliki modelov daljnovodnih koridorjev iz podatkov daljinskega programskega paketa gLiDAR [4], s katerim je bil izveden zaznavanja in, podprt z simulacijami rasti vegetacije, prvi in do sedaj edini nacionalni projekt zajema podatkov predvidevanje groženj za varnost daljnovodov ter LiDAR celotne Slovenije. Ključen rezultat slednjega optimizacijo delovnih nalogov z minimizacijo stroškov predstavlja uraden digitalni model reliefa Slovenije v visoki posegov. Rezultate rabe sistema pa je v soavtorstvu z ločljivosti, ki predstavlja temeljno izhodišče številnih uporabniki objavil v članku [8]. Podoben koncept splošno uporabljenih podatkovnih slojev, vključno z natančnimi mapami rečnih strug, cestišč, objektov in ostalih samodejnega (skoraj) realno-časovnega zlivanja podatkov geografskih entitet. Predstavljen programski paket pa je bil za luščenje komplementarnih značilnic je danes v razvoju kasneje uporabljen v številnih mednarodnih projektih, med tudi za optimizacijo vzdrževanja avtocest podjetja DARS drugim ga je za svoj projekt obogatitve podatkovne baze d.d., pri čemer je v tem primeru arhitekturna zasnova naslovov z okoljskimi podatki o geometriji stavb uporabila 686 digitalnega dvojčka izrabljena za predvidevanje stanja kandidat razume predvsem kot dobre temelje za nadaljnje prometa. delo in prispevek k uveljavitvi naprednih metodologij obdelave podatkov za namene podatkovno podprtega Zadnji večji uspešno zaključen projekt, ki ga je vodil odločanja. kandidat, je sistem celostnega nadzora teritorija Slovenije Medtem, ko so v tem prispevku predstavljeni zgolj in bojišč Slovenske Vojske za odkrivanje potencialnih dosedanji dosežki, je kandidatove nadaljnje prispevke k nevarnosti. Enote Slovenske Vojske trenutno vpeljujejo utrditvi položaja slovenske računalniške in informacijske razvit sistem na taktičnem nivoju izvidniških operacij. stroke v Slovenskem in mednarodnem merilu moč Slednje pa jim omogoča realno-časovno obdelavo pričakovati tudi na osnovi njegovih tekočih projektnih in podatkov, zajetih z izvidniškimi brezpilotnimi letalniki, ter raziskovalnih aktivnosti, rezultati katerih še niso javno neposredno kartiranje civilnih in vojaških enot, vozil in objavljeni. Kandidat trenutno nastopa kot vodilni tehnološki objektov. V bližnji prihodnosti je predvidena raba sistema partner v dveh projektih, financiranih iz programa Horizont tudi v civilnih operacijah, kot na primer odkrivanje Evropa, vodi štiri industrijske projekte večjega obsega in ponesrečencev, zaznavanje požarov ter iskanje oseb in aplikativni raziskovalni projekt ARRS. predmetov v kritičnih situacij. ZAHVALA 4 MEDNARODNE IN OSTALE Za svoje dosežke se v prvi vrsti želim zahvaliti svojemu AKTIVNOSTI mentorju prof. dr. Borutu Žaliku, ki je soustvarjal tako mojo profesionalno, kakor tudi osebnostno rast. Posebna zahvala Raziskovalni rezultati kandidata se odražajo tudi v njegovi močn gre tudi vse sodelavcem v laboratoriju GeMMA ter strateškim i vpetosti v mednarodne strokovne in znanstvene mreže. Od leta 2013 do 2019 industrijskim partnerjem, brez katerih ne bi bilo mogoče je tako kandidat deloval dva mandata kot član izvršnega odbora krovne Evropske osnovati in uspešno izvesti navedenih raziskovalnih in projektnih idej. organizacije za geografske informacije EUROGI, kjer so ga za svojega zastopnika izbrale naslednje krovne nacionalne REFERENCES organizacije: AGORIA (Belgija), AM/FM-GIS Belux aisbl [1] Domen Mongus and Borut Žalik, 2012. Parameter-free ground (Luksemburg), Geo-SEE Inštitut (Makedonija), HI-Norden filtering of LiDAR data for automatic DTM generation. ISPRS journal (Norveška), IGIS (Hrvaška) in ISPik (Polska). Od 2020 pa of photogrammetry and remote sensing, vol. 67, str. 1-12. je član izvršnega odbora mednarodne organizacije [2] Mongus, Domen, Lukač, Niko, Žalik, Borut, 2014. Ground and building extraction from LiDAR data based on differential »Geographical Information Systems International Group morphological profiles and locally fitted surfaces. ISPRS journal of (GISIG)«. photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing, vol. 93, str. 145-156. Kandidat je tudi reden udeleženec in vabljen predavatelj na [3] Domen Mongus and Borut Žalik, 2015 . An efficient approach to 3D mednarodnih dogodkih, predavanjih TEDx ter član single tree-crown delineation in LiDAR data. ISPRS journal of photogrammetry and remote sensing : official publication of the uredniškega odbora dveh mednarodnih znanstvenih revij, ki International Society for Photogrammetry and Remote Sensing, vol. glede na faktor vpliva spadajo v kategorijo A1 ali A2. 108, str. 219-233. [4] Domen Mongus in Denis Horvat, 2015. gLiDAR. COBISS.SI-ID: 19366166. Za svoje delo v nacionalnem in mednarodnem okolju je leta [5] Žalik, Borut and Mongus, Domen, 2016. Light detection and ranging (Lidar)data compression and decompression methods and apparatus . 2018 prejel tudi najvišjo nagrado Univerze v Mariboru za United States Patent and trademark office, Appl. no.: 13/289.839 . Izjemne prispevke k znanstvenemu in pedagoškemu ugledu [6] Vlahek, Dino and Mongus, Domen, 2021. An efficient iterative in odličnosti Univerze v Mariboru. approach to explainable feature learning. IEEE transactions on neural networks and learning systems, 13. [7] Barbieri, Maurice and Mongus, Domen, 2015. EUROGI policy papers : internet of things, big/linked data & open data. Geospatial World 5 ZAKLJUČEK forum, Lisbon, Portugal. 2015. [8] Mongus, Domen, Brumen, Matej, Žlaus, Danijel, Kohek, Štefan, Predstavljeni rezultati nedvomno uvrščajo kandidata med Tomažič, Roman, Kerin, Uroš, Kolmanič, Simon. A complete environmental intelligence system for LiDAR-based vegetation uglednejše raziskovalce na področjih lokacijske inteligence management in power-line corridors. Remote sensing. 2021, vol. 13, in geografskih informacijskih sistemov v Evropskem merilu iss. 24, 15 str. ter računalništva in informatike v splošnem. Slednje pa 687 Prispevek za zgodovino slovenske informatike Osebni pogled Niko Schlamberger Slovensko društvo INFORMATIKA niko.schlamberger@gmail.com Povzetek računalniških sistemov IBM in usposabljanje računalniških kadrov (tedaj organizatorjev, programerjev in operaterjev) v izobraževalnem Prispevek obravnava razmeroma spregledan del centru, ki ga je ustanovilo v Radovljici, kamor so razvoja informatike v Sloveniji. Medtem ko so prihajali tečajniki iz teoretična informatika, informatika v šolstvu in vse Jugoslavije. Poenostavljeno, vendar točno bi se lahko reklo, da proizvodnja računalniških naprav z zgodovinskega so bili to začetki organiziranega razvoja poslovne vidika razmeroma dobro opisani, je poslovna informatike. Šele več desetletij zatem je bil na informatika praktično spregledana. Pričujoči članek poskuša to Ekonomski fakulteti Univerze v Ljubljani pomanjkljivost popraviti vsaj v delu, ki ustanovljen Inštitut za poslovno informatiko, za kar zadeva finančno dejavnost, posebej bančništvo in gre skoraj izključna zasluga in pohvala tedanjemu plačilni promet, avtor pa upa, da bo spodbudil profesorju (in kasnejšemu prorektorju ljubljanske katerega od razvijalcev poslovnih aplikacij, ki so univerze) dr. Andreju Kovačiču, dokazuje pa bili aktivni v času uvajanja računalnikov v njegovo daljnovidnost in razumevanje pomena poslovanje, saj so pomembno prispevali k učinkovitejšemu poslovanju tedaj in so s tem informatike za – najširše rečeno – razvoj moderne družbe. zaslužni za to, da današnja slovenska poslovna informatika ne zaostaja za tisto v razvitih državah. Ko obravnavamo uvajanje prvih računalnikov v tedanja podjetja, današnje gospodarske družbe, ne Ključne besede poslovna informatika, plačilni promet smemo spregledati nekaterih, ki so navedene v nadaljevanju. To so bili Elan, Begunje; Emona, Ljubljana; Gorenje, Velenje; Lisca, Sevnica; Grosist, Nova Gorica; Salonit, Anhovo; 1. Uvodna pojasnila Kovinotehna, Celje; Zlatorog, Maribor; Merkur, Kranj; Astra, Ljubljana; Ljubljanska banka, O uvajanju računalnikov v znanstvenoraziskovalno Ljubljana; Služba družbenega knjigovodstva, delo v Sloveniji v sedemdesetih letih prejšnjega Ljubljana. Te navedbe so je daleč od popolnega stoletja je že kar nekaj napisanega [3] in tega na tem pregleda in obsegajo le računalniške sisteme IBM, mestu ne bi ponavljali. Manj ali skoraj nič pa ni res pa je, da je bila večina računalnikov v napisanega o uvajanju računalnikov v istem gospodarstvu te znamke. Nekaj je bilo tudi obdobju. To je tako rekoč bela lisa v zgodovini računalniških sistemov proizvajalcev NCR, slovenske informatike, ki jo skuša ta članek vsaj Honeywell, kasneje še Burroughs, Fujitsu, Unisys nekoliko zmanjšati. Pri tem naj pojasnimo, da in VAX. Za njihovo uvedbo je treba priznati zasluge pisanih virov, ki bi pokrivali obravnavano tematiko, tedanjim odločevalcem, ki so verjeli, da je skorajda ni. Redka izjema je opis razvoja slovenske računalnik lahko pomembno, če že ne bistveno računalniške industrije [1], ki pa se poslovne orodje za učinkovitejše vodenje in izvajanje informatike le bežno dotika. Avtor se zato naslanja poslovnih in proizvodnih procesov. na svoje delovanje in izkušnje iz tistega obdobja, zato je tudi podnaslov članka Osebni pogled. Poslovne aplikacije na teh sistemih so v tistem času obsegale pretežno obdelave podatkov, kjer je bilo V sedemdesetih letih prejšnjega stoletja je imelo ročno delo zamudno, delovno intenzivno in kjer je podjetje Intertrade zastopstvo računalniškega bila zahtevana ročnost in točnost rezultatov. Tipične velikana IBM. Poleg prodaje računalniških naprav take obdelave so bile knjigovodstvo, obračun plač, IBM je razvilo še dve pomembni dejavnosti: fakturiranje, vodenje stanja skladišč in podobne. tehnično podporo uvajanja in vzdrževanja Manj je bilo takih, ki bi izboljševale proizvodne ali 688 poslovne procese. Posebno področje, kjer je bila finančna transakcija v notranjem plačilnem prometu računalniška obdelava spoznana kot nepogrešljiva je bila tako zabeležena v SDK, po zakonu pa je za ažurno obdelavo velikega števila podatkov, so morala biti obdelava podatkov plačilnega prometa bile finančne dejavnosti, katerih izvajalci so bili do zaključena vsak delovni dan. Država je torej leta 1991 izključno banke, pošta in Služba naslednji dan zjutraj razpolagala z natančnim družbenega knjigovodstva. Slednji je posvečena stanjem dinarskih vplačil, izplačil in stanja. večina tega zapisa, ker obstaja v primerjavi z drugimi poslovnimi aplikacijami razmeroma precej Podobne institucije so poznane v Evropi že od druge dokumentacije ([1], [7]), deloma zato, ker je bil polovice 18. stoletja (clearing house, clearing bank, avtor na tem področju dlje časa aktiven, ne nazadnje Girocentrale), vendar je bilo njihovo poslanstvo pa tudi zato, ker so bili za njeno delovanje razvite drugačno, reklo bi se poslovno orientirano, ker je bil aplikacije in programi, ki še danes veljajo za glavni namen pobotanje plačil in terjatev ([6]). vrhunske strokovne dosežke tedanje informatike. Poleg plačilnega prometa je opravljal SDK tudi druge naloge – statistiko, analize, inšpekcijo in 2. Plačilni promet poročanje, večina tega pa je bila omogočena prav zaradi razpoložljivih podatkov o plačilnem Plačilni promet bi lahko kratko in poljudno prometu. opredelili kot izvajanje finančnih transakcij preko poslovnih subjektov, ki so za to pooblaščeni. Vsako nakazilo denarja, plačilo računa, dviga ali polog 3. Obdelava podatkov plačilnega denarja s kakršnim koli plačilnim instrumentom prometa (plačilni nalog, kreditna kartica, ček in drugi, [2]) je finančna transakcija ([4]), ki se odraža v V primerjavi z današnjim številom poslovnih knjigovodskih sistemih udeležencev v tej subjektov, obsegom poslovanja in finančnih transakciji, torej pri izvajalcu transakcije, transakcij bi najprej pomislili, da je bilo v 70. letih prejemniku sredstev in plačniku. Izvajalec prejšnjega stoletja tega malo. Mogoče; vendar je transakcije si svoje delo, ki ga ima z njo, poplača s bilo dnevno število plačilnih nalogov samo v provizijo v breme enega ali drugega udeleženca v podružnici SDK Ljubljana okoli 300.000, včasih tej transakciji. Spet poenostavljeno in poljudno bi tudi do pol milijona, v vseh 14 podružnicah SDK v lahko rekli, da je finančna transakcija informacijska Sloveniji pa reda velikosti en milijon dnevno, kar je preslikava poslovnega dogodka. Ta kratki opis je bilo za tedanje možnosti tehnologije zelo zahtevno potreben za razumevanje nadaljevanja tega zapisa. za obdelavo, bilo pa je tudi izjemno delovno intenzivno. V SDK Jugoslavije je bil sicer razvit Pred letom 1991 je bila udeleženka vsake finančne program AROPS1, ki je imel tri funkcionalne transakcije v notranjem plačilnem prometu še sklope: zajem podatkov, kontrola podatkov in Služba družbenega knjigovodstva, ki je po tedanjih priprava podatkov za obdelavo na računalniškem ustavi in zakonu izvajala plačilni promet, to je tisti, sistemu. Prejšnje ročne postopke, to je tiste, ki so se kjer je nastopala domača valuta. Razlog za izvajali s pomočjo elektromehanskih naprav, je ustanovitev take institucije je bilo spoznanje bistveno izboljšal, vendar je imel mnogo politike, verjetno intuitivno, da je denar v bistvu pomanjkljivosti. Glavne so bile počasna informacija. Eden od vodilnih teoretikov James računalniška obdelava (reda velikosti 1.000 Martin je namreč šele v osemdesetih letih prejšnjega transakcij na uro), zahtevni postopki za odpravljanje stoletja v svojem delu opisal in dokazal, da je denar napak in zamudna priprava podatkov za nadaljnjo informacija. Kdor vidi denarne tokove, ta vidi vse, obdelavo. Precej razmišljanja je bilo torej, kako kar tudi pojasnjuje, zakaj kriminal posluje z postopke pospešiti s pomočjo računalnika, gotovino – le-ta se pretaka mimo uradnih denarnih konkreten predlog pa so izdelali Mladen Trobec2, tokov. Do tega spoznanja pa se je politika dokopala Matjaž Čadež3 in Wolfgang Jung4. že prej in ga institucionalizirala tako, da je bila ustanovljena organizacija, ki je imela nadzor nad Njihova rešitev je temeljila na tedaj izjemno vsemi denarnimi transakcijami – Služba družbenega naprednega načina z uporabo metode direktnega knjigovodstva, še danes ne pozabljeni SDK. Vsaka 1 Automatizacija rednih operativnih poslova službe 3 Tedaj Intertrade IBM 2 Tedaj SDK podružnica Ljubljana 4 Tedaj IBM Regional Office Europe Central and East 689 pristopa do podatkov na diskovnih pomnilnikih5. sta razvila program ELKA8, ki je omogočal Pogledano z današnjimi očmi bi bilo seveda analitikom, da so pregledovali podatke in izdelovali učinkoviteje uporabiti relacijske ali objektne poročila brez posredovanja programerjev. Razvila podatkovne baze, kar pa je bilo v tistem času zaradi sta tudi podoben program za spremljanje investicij. ne dovolj zmogljivih računalniških naprav Skupina razvijalcev je proti koncu 80. let neizvedljivo. Indikativno je tudi ime rešitve – sprogramirala in demonstrirala prvo elektronsko Tezaurus6[10], ki dokazuje, da so bili njeni avtorji plačilo v notranjem plačilnem prometu. Vse tri vrhunski informatiki, razumeli pa so tudi pomen inovacije so bile priznane kot take in razvijalci zanje podatkov7[11]. tudi nagrajeni. Čeprav so bili tedaj na razpolago že programski jeziki tretje generacije, pri IBM tipično PL/1, so bili 4. Namesto zaključka programi napisani v asemblerju, ki je bil nezahteven glede porabe virov, hkrati pa dovolj hiter pri Pričujoči prispevek se omejuje na zelo posebno izvajanju. Računalniški sistem podružnice SDK področje obdelave podatkov plačilnega prometa. Ljubljana je bil IBM serije 370 model 138 z Poleg oseb, ki so imenoma navedene v članku, so operacijskim sistemom DOS/VS, s 64KB pri razvoju in izboljšavah sodelovali številni pomnilnika in enotami magnetnih diskov IBM 2314 informatiki in strokovnjaki z drugih področij, ki so zmogljivosti 27MB. Upoštevaje zgolj ti dve ostali vse do danes neopaženi in, če se lahko značilnosti in dejstvo, da je bili treba obdelati izrazimo nekoliko bolj slikovito, neopevani junaki dnevno ažurno ca 1.000.000 plačilnih nalogov ob poslovne informatike. Poudariti pa je treba, da je vseh drugih obdelavah za potrebe SDK (statistika, obravnavano področje zgolj eno in da so dosežki analize in druge), je očitno, da so morali biti avtorji poslovne informatike nezasluženo spregledani in rešitve izjemno kreativni. Razvijalci so se torej zamolčani. Seveda obstaja razlaga tudi za to. srečevali z omejitvami, na katere današnji niti ne Medtem ko se od raziskovalcev zahteva, da svoja pomislijo, saj so viri naprav praktično neomejeni. dognanja in dosežke objavljajo, se od informatikov Diskovni pomnilnik zmogljivosti 1 TB je bil tedaj v zahteva zgolj to, da njihove rešitve delujejo, za kaj domeni znanstvene fantastike, danes pa je na več pa pretežno zmanjka časa in energije. Njihovi notesniku že običajen. Vseh podrobnosti rešitve prispevki na nacionalnih konferencah prikazujejo Tezaurusa na tem mestu ne moremo navajati, saj so skoraj izključno tekoče dosežke. Avtor upa, da bo s podrobno opisane v razpoložljivi literaturi [9]. svojim prispevkom spodbudil še koga, ki bi lahko Navedemo pa naj vendar nekaj podrobnosti, ki bodo prispeval svoj kamenček za mozaik, iz katerega bi ilustrirale zgornjo oceno. se nekoč izoblikovala zgodovina slovenske informatike. Za kar najhitrejše izvajanje programov so bili uporabljeni makroukazi. Ker je bil pomnilnik centralne procesne enote daleč premalo zmogljiv, so 5. Zahvala bili programi napisani v tehniki prekrivanja (overlay). Krmilni del programa je osnovni in je ves čas v pomnilniku, glede na potrebe pa prikliče z Avtor se najprijazneje zahvaljuje - Mladenu Trobcu za pomoč pri odkrivanju in zunanjega pomnilnikom ustrezni del programa pridobivanju virov, posebej pa še za vzpostavitev (podprogram), ki izvede zahtevano funkcijo. domačih strani (vira [8] in [10]), ki sta dragocen Posebna tehnika je bila razvita za zapis podatkov na zunanji disk, ki je dala zapis natančno take dolžine, prispevek za dokumentiranje razvoja poslovne informatike, za kritični pregled in izboljšave, in da je bil disk izkoriščen natančno do poslednjega - prof. dr. Matjažu Gamsu za spodbudo za pisanje bajta. tega prispevka. Poleg te najbolj obsežne aplikacije naj omenimo še Brez njiju bi bila zgodovina slovenske informatike nekaj drugih dosežkov. Franc Potočnik in Ivan Turk revnejša vsaj za ta članek. Hvala obema. 5 Direct Access Method, DAM 7 "treasury, storehouse," from Latin thesaurus "treasury, 6 V informacijski tehnologiji so tezavri baze podatkov, a hoard, a treasure, something laid up," from na področju umetne inteligence pa se jim reče tudi Greek thēsauros "a treasure, treasury, storehouse, ontologije. chest," … 8 ELementi in KAzalci 690 6. Viri [1] Marijan Frković, Franci Pivec, Niko [5] Osebni zapiski avtorja Schlamberger, Janez Grad: A contribution to the [6] Dušan Drofenik: Clearing houses, clearing bank, history of computing and informatics in West girozentrale, Obvestila SDK, maj 1991 Balkan countries, Uporabna informatika 2016/4, [7] http://sdk- URN:NBN:SI:DOC-UAGSD7MU tezaurus.blogspot.com/2011/07/kontrolni-program- [2] Aleš Zelenik, Zdenko Mezgec: Zaščita tezaurus.html, obisk 13.9.2022 negotovinskih oblik plačevanja, Uporabna [8] http://sdk- informatika 2009/4, URN:NBN:SI:DOC- tezaurus.blogspot.com/2011/07/zakaj- ZSUPALYC tezaurus.html, obisk 13.9.2021 [3] Janez Grad: Razvoj računalništva in [9] Kontrolni program Tezaurus, SDK Ljubljana, informatike na Univerzi v Ljubljani, s poudarkom 1980 na pomenu RRC in RCU, Uporabna informatika [10] https://sl.wikipedia.org/wiki/Tezaver (obisk 2018/3, URN:NBN:SI:DOC-SWR9IXMO 14.9.2022) [4] https://www.bsi.si/placila-in- [11] infrastruktura/placilne-storitve-in-elektronski- https://www.etymonline.com/search?q=thesaurus denar/placilni-instrumenti-in-placilni-nalogi (obisk (obisk 24.9.2022) 15.9.2022) 691 Pregled mojega raziskovalnega dela Overview of my research work Franc Solina franc.solina@fri.uni- lj.si Fakulteta za računalništvo in informatiko Univerza v Ljubljani 1000 Ljubljana, Slovenia POVZETEK raziskovalna skupina je bila interdisciplinarno sestaljena. V is- tem laboratoriju sem nato naredil tudi svojo magistrsko nalogo, V članku podajam pregled mojega raziskovalnega dela od konca kjer sem se posvetil analizi srčnih aritmij [2]. Objavili smo nekaj 70-tih let 20. stol. do leta 2022. Moji začetki so bili na področju člankov na mednarodnih konferencah [3], naša skupina pa je analize biomedicinskih signalov, med študijem v ZDA sem se leta 1982 tudi dobila Nagrado Sklada Borisa Kidriča za razvoj mi- začel ukvarjati z računalniškim vidom. Moje glavno raziskovalno kroprocesorskega analizatorja EKG [4]. Več o tem obdobju sem področje je 3D interpretacija slikovnih informacij in uporaba raču- napisal v [5]. nalniškega vida pri uporabniških vmesnikih. Glavni aplikacijski področji katerim sem se posvetil pa sta dediščinska znanost, kjer 2 REKONSTRUKCIJA SUPERKVADRIKOV IZ metode računalniškega vida postajajo neobhodne za dokumenta- cijo najdišč in raznoraznih artefaktov, in sodobna novomedijska GLOBINSKIH SLIK umetnost, kjer posebej pri interaktivnih instalacijah računalniški Po obveznem služenju vojaškega roka, ki sem ga opravil v Hi- vid omogoča interakcijo z okoljem in obiskovalci. drografskem inštitutu Jugoslovanske vojne mornarice v Splitu v letu 1982/83, sem s pomočjo Fulgrightove in IREXove štipen- KLJUČNE BESEDE dije odpravil na Pensilvansko univerzo v Filadelfijo, ZDA. V svoj Analiza EKG, računalniški vid, rekonstrukcija volumetričnih mo- laboratorij GRASP (General Robotics, Automation, Sensing & Per- delov, superkvadriki, uporabniški vmesniki, dediščinske znanosti, ception Lab) me je sprejela prof. dr. Ruzena Bajcsy. Prof. Bajcsy podvodna arheologija, analiza podatkov v letalstvu, novomedij- [6], po rodu iz Slovaške, je svoj drugi doktorat znanosti dobila ska umetnost na Univerzi Stanford pod mentorstvom prof. Johna McCarthya [7], enega od pionirjev umetne inteligence. Zato se lahko pohva- ABSTRACT lim, da je moj akademski “dedek” eden od začetnikov umetne inteligence [8]. In this article I give an overview of my research work from the V svoji doktorski disertaciji sem se ukvarjal z rekonstrukcijo late 1970s to 2022. My beginnings were in the field of biomedical volumetričnih modelov iz globinskih slik, ki navdih išče v teo- signal analysis, and I started working on computer vision while riji človeškega zaznavanja slik. Rekonstrukcija vidne scene iz studying in the USA. My main research area is 3D interpretation vizualnih podatkov je temeljno področje raziskav na področju of image information and the application of computer vision to računalniškega vida. Njegov glavni cilj je čim bolj natančno re- user interfaces. The main application areas I have focused on konstruirati opazovano okolje z opisom različnih predmetov v are heritage science, where computer vision methods are becom- prizoru. Eden od prevladujočih pristopov k rekonstrukciji temelji ing indispensable for the documentation of sites and various na predstavitvi kompleksnih prizorov s pomočjo množice prepro- artefacts, and contemporary new media art, where, especially stih geometrijskih oblik, znanih tudi kot volumetrične primitivne in interactive installations, computer vision enables interaction oblike. Tako predstavljena okolja lahko nato avtonomni agenti with the environment and visitors. uporabljajo za različne naloge, kot sta navigacija po okolici ali KEYWORDS prijemanje predmetov, kar je praktično uporabno npr. v skladi- ščih in v proizvodnji. Opisani pristop rekonstrukcije, ki temelji na ECG analysis, computer vision, reconstruction of volumetric volumetričnih primitivih, je znan kot rekonstrukcija od spodaj models, superquadrics, user interfaces, heritology, underwater navzgor. Superkvadriki so volumetrični 3D modeli, ki za obli- archaeology, data analysis in air traffic, new media arts kovanje različnih oblik potrebujejo le nekaj parametrov oblike, drugi parametri pa opisujejo njihovo velikost ter položaj in ori- 1 ANALIZA SIGNALOV EKG entacijo v prostoru. V računalniško grafiko jih je vpeljal Alan Barr, v računalniški vid pa Sandy Pentland. Na osnovi njunih idej Moja prva raziskovalna izkušnja sega v leto 1979, ko sem izdelal sem v svojem doktorskem delu razvil metodo rekonstrukcije su- svojo diplomsko nalogo v Laboratoriju za avtomatiko in kiber- perkvadrikov iz globinskih slik na osnovi minimizacije funkcije netiko pod mentorstvom akad. prof. dr. Ludvika Gyergyeka [1]. prileganja. Minimizacija je zahtevala iterativen postopek reše- Delal sem na računalniški analizi elektrokardiogramov in naša vanja, saj je šlo za izrazit nelinearen problem. Kljub relativno kompleksni rešitvi, se je moja metoda uveljavila na zelo različnih Permission to make digital or hard copies of part or all of this work for personal aplikacijskih področjih, od robotike, medicine, pa celo antropolo- or classroom use is granted without fee provided that copies are not made or gije za modeliranje človeških lobanj, kar priča okoli 2000 citatov 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 na Google učenjaku. work must be honored. For all other uses, contact the owner /author(s). Članek na osnovi mojega doktorata so sprejeli na prvi medna- Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia rodni konferenci iz računalniškega vida (ICCV), ki je bila 1987 v © 2022 Copyright held by the owner/author(s). Londonu [9], kasneje sem članek objavil tudi reviji IEEE PAMI 692 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Franc Solina [10]. Konec leta 1987 sem zagovarjal svojo disertacijo [11]. Do med uporabniki videokonferenčnih sistemov [26] in vizualizacijo avgusta 1988 sem nato imel na UPenn še status podoktoranta, glasbe [27]. nato sem se vrnil v Ljubljano na FE in začel s predavanji na študijskem programu računalništva in informatike. V Ljubljani 4 UPORABA RAČUNALNIŠKEGA VIDA V sem nadaljeval z delom na rekonstrukciji superkvadrikov. Leta DEDIŠČINSKI ZNANOSTI 1991, ravno v času osamosvajanja Slovenije, sem na fakulteti Kot sem že omenil, so metode računalniškega vida postale skoraj ustanovil tudi lasten Laboratorij za računalniški vid. S svojima neobhodne v arheologiji in dediščinski znanosti, tako pri zajemu doktorskima študentoma Alešem Leonardisem in Alešem Jakli- 3D podatkov (npr. večslikovna fotogrametrija, Lidar) kot pri mo- čem sem izpopolnil metodo rekonstrukcije superkvadrikov tako, deliranju in analizi teh podatkov. Z našo metodo rekonstrukcije da je vključevala še segmentacijo kompleksnih predmetov na več superkvadrikov smo modelirali kamnite sarkofage, ki jih je pre- superkvadrikov [12]. O tem našem delu smo napisali monografijo, važala rimska ladja, ki se je potopila na severni strani otoka Brača ki je izšla pri založbi Kluwer, oziroma kasnejšem Springerju [13]. [15]. Superkvadriki so zaradi rotacijske simetrije tudi zelo pri- Tematika superkvadrikov pa s tem ni čisto zamrla, saj sem s svo- pravni modeli za modeliranje amfor [16]. Sodelovali smo tudi pri jim doktorskim študentom Jako Krivicem razvil zanimivo metodo dokumentiranju in analizi rimske ladje s pomočjo fotogrametrije prepoznavanja objektov na osnovi superkvadrične rekonstruk- v reki Ljubljanici pri Sinji Gorici [28, 29]. V kontekstu podvodne cije [14]. Superkvadrike smo uporabili tudi pri dokumentiranju arheologije se vedno znova pojavi problem ohranjanja mokrega arheoloških artefaktov v kontekstu dediščinske znanosti [15, 16]. lesa. Na primeru 40.000 let stare paleolitske lesene osti, ki jo je Po dolgem premoru smo se superkvadrične obnove pred pa- našel v reki Ljubljanici naš sodelavec arheolog Miran Erič, smo rimi leti ponovno lotili, pri čemer nas je navdihnil izjemni napre- preučevali spremembe, ki nastanejo med konzerviranjem takih dek na področju globokega učenja. Ti najsodobnejši pristopi zaob- predmetov [30]. idejo računsko intenzivnost zgodnjih iterativnih rešitev. Obravna- vajo tudi rekonstrukcijo iz različnih vrst podatkov, kot so oblaki 5 ANALIZA PODATKOV V LETALSTVU točk, globinske slike in celo kombinacija intenzitetnih in barvnih Marko Hrastovec, moj doktorski študent, me je potisnil na podro- slik. Da bi dosegli uspešne rekonstrukcije, vsi pristopi sprejmejo čje analize letalskih podatkov. Hrastovec je zaposlen na Slovenski učne cilje, ki vključujejo določeno raven geometrijskih infor- kontroli poletov in ima tako dostop do podatkov, ki se zbirajo v macij. Pokazali smo, da je z uporabo globokega učenja mogoče centrih za kontrolo poletov. Za svojo magistrsko nalogo je po- rekonstruirati superkvadrike iz ene same globinske slike [17], pri stavil informacijski sistem, ki meteorološke podatke, ki jih letala čemer smo se pri ocenjevanju velikosti, oblike, položaja in rota- preko radarskih povezav pošiljajo v kontrolne centre, posreduje cije upodobljene superkvadrike oprli na napovedovalnik CNN. naprej meteorološkim središčem, ki z obogatenimi podatki o tem- Razvili smo tudi metodo rekonstrukcije superkvadričnih modelov peraturah ozračja, hitrosti vetrov in vlažnosti lahko povečajo iz intenzitetnih in barvnih slik [18]. Da bi to dosegli, smo sledili natančnost meteoroloških napovedi [31]. Z bolj natančnimi me- splošni zamisli metode, ki temelji na globinskih slikah, vendar teorološkimi podatki in drugimi podatki o posameznih letih, pa smo naredili korak naprej in raziskali uporabo modelov globo- s pomočjo strojnega učenja lahko izboljša napovedi o trajanju kega učenja za rekonstrukcijo superkvadrikov iz ene same slike posameznih poletov [32]. RGB. Z globokimi nevronskimi mrežami smo se lotili tudi pro- blema sočasne segmentacije in rekonstrukcije superkvadričnih 6 NOVOMEDIJSKA UMETNOST modelov [19]. Prednost metod z uporabo CNN je predvsem veliko hitrejša rešitev, kar omogoča uporabo teh metod tudi takrat, ko Kmalu po mojem povratku na Univerzo v Ljubljani sem se po- je potrebno poiskati rešitev v realnem času, kot na primer pri vezal s Srečom Draganom, pionirjem video umetnosti v tedanji avtonomni vožnji. Jugoslaviji in profesorjem na Akademiji za likovno umetnost in oblikovanje. Povod za najino sodelovanje je bil spletni portal Slovenska virtualna galerija [33], ki je na nov način predstavil 3 UPORABA RAČUNALNIŠKEGA VIDA V slovensko likovno umetnost. S Srečom Draganom sva začela dol- UPORABNIŠKIH VMESNIKIH goletno plodno sodelovanje na področju umetnosti novih medijev Če je še v 80-tih letih zajem slik z računalnikom zahteval do- [34]. V sodelovanje sva pritegnila tudi najine študente na FRI datno strojno opremo, pa je v 90-tih letih vse več računalnikov in ALUO. V interdisciplinarnem duhu in z uporabo tehnologij, imela že vgrajeno kamero. Zajem slik in s tem njihova uporaba je ki smo jih razvijali v našem laboratoriju, smo eksperimentirali postala enostavna. Zato me je začela zanimati uporaba slik v kon- z novimi tehnologijami in jih preizkušali v kontekstu novome- tekstu uporabniških vmesnikov. Razvili smo poseben uporabniški dijske umetnosti. Z našimi projekti smo se redno udeleževali vmesnik za kontrolo zajema video slike na daljavo. Z enostavno Mednarodnega festivala računalniških umetnosti v Mariboru, fe- robotsko roko je bilo možno premikati kamero levo-desno in gor- stivalov Speculum Artium v Trbovljah, se pojavljali na drugih dol. Na ta način smo lahko zajeli panoramsko sliko [20] in tudi razstavah ali organizirali lastne letne preglede naše novomedij- globinsko panoramsko sliko [21]. Ker nas je zanimala detekcija ske dejavnosti in študentskih umetniških projektov. Opažen je obrazov, smo razvili tudi enostavno metodo detekcije na osnovi bil tudi naš prispevek v okviru evropskega meseca kulture leta barve kože, ki se je prilagajala različnim vrstam osvetlitve [22]. 1997 v Ljubljani [35]. Novomedijska umetnost, ki je življensko Prav zaradi preprostosti je ta naša metoda postala zelo popularna, odvisna od računalniške tehnologije, se je izkazala kot zelo pri- saj ima na Google učenjaku skoraj 1000 citatov. merno eksperimentalno polje tudi za preizkušanje novih metod Preučevali smo tudi uporabo metod računalniškega vida za računalniškega vida [36]. analizo gledanosti digitalnih oglasov [23] in novo vrsto dina- Sčasoma sem začel razvijati tudi lastne novomedijske projekte. mične anamorfoze, ki se prilagaja poziciji opazovalca v prostoru Moj prvi odmeven projekt je bil 15 sekund slave, ki so jo nav- [24]. Preučevali smo tudi uporabniške vmesnike za ljudi s kogni- dihnili portreti znanih ljudi Andyja Warhola [37]. Prvič je bila tivnim deficitom [25] in problem manjkajočega kontakta z očmi razstavljena leta 2002 na Mednarodnem festivalu računalniških 693 Pregled mojega raziskovalnega dela Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia umetnosti v Mariboru, kasneje pa še velikokrat, tudi na samostojni društva. (Dubrovnik). Ur. Krunoslav Turkulin. Udruženje razstavah [38]. Instalacija s samodejnim zaznavanjem obrazov Kardiologa Jugoslavije, 1980, str. 25–33. iz naključno izbranih obrazov obiskovalcev galerije, ki stojijo [4] Damjan Zazula, Marjan Vezjak, Ludvik Gyergyék, Franc pred instalacijo, ustvari pop art portrete. Ti portreti se nato za Solina in France Mihelič. “A microcomputer for on-line 15 sekund prikažejo na računalniškem monitorju, ki je oukvirjen analysis of exercise electrocardiographic signals”. V: Mini kot umetniška slika. Instalacija je bila ustvarjena, še preden se je and microcomputers and their applications: proceedings of začela doba selfijev, vendar je že odlično naslovila potrebo ljudi the ISMM international symposium. (Sant Felâiu de Guixols, po samospoznavanju in samopotrditvi. Na primeru te instalacije Spain). Ur. E. Luque. Universidad Autonoma de Barcelona, smo tudi preučevali vzdrževanje novomedijske umetnosti [39]. 1985, str. 307–310. Pred desetimi leti, leta 2012, sem začel bolj po naključju ki- [5] Franc Solina. “Moje računalniško izobraževanje = My com- pariti v kamnu in lesu morda iz želje, da bi z rokami počel kaj puter science education”. V: 50-letnica poučevanja računal- več kot le tipkal in sedel za računalniškim zaslonom. Po nekaj ništva v slovenskih srednjih šolah: 6. oktober 2021, Ljubljana, kiparskih delavnicah pod vodstvom akademskih kipark Alenke Slovenia. Ur. Saša Divjak in Alenka Krapež. Institut “Jožef Vidrgar in Dragice Čadež Lapajne sem začel delati samostojno. Stefan”, 2021, 34–37. url: http : / / library . ijs . si / Stacks / Moje dosedanje kiparsko delo je bilo nedavno predstavljeno na sa- Proceedings/InformationSociety/2021/IS2021_Volume_I. mostojni razstavi, ki je bila jeseni 2020 v Galeriji DLUL v Ljubljani pdf . [40]. Svoje znanje računalništva poskušam združiti s kiparstvom. [6] Ruzena Bajcsy — Wikipedija, prosta enciklopedija. url: Raziskujem, kako lahko kip obogatimo z virtualno vsebino. V https : / / sl . wikipedia . org / wiki / Ruzena _ Bajcsy (prido-preteklosti so umetniki kamnite skulpture pogosto postavljali bljeno 12. 9. 2021). v vodno okolje - bodisi v stoječo vodo, v kateri se je skulptura [7] John McCarthy — Wikipedia, The Free Encyclopedia. url: zrcalila, bodisi kombinirali s tekočo vodo v obliki različnih fontan, https : / / en . wikipedia . org / w / index . php ? title = John _ ki so vnašale dinamičen element. Za serijo skulptur Svetlobna McCarthy_(computer_scientist)&oldid=1041515367 (pri-fontana — doslej sem v tej seriji izdelal dve skulpturi, Sonce in dobljeno 12. 9. 2021). Galaksijo [41] — sem za zajem 3D-oblike skulpture uporabil Ki- [8] Mathematics Genealogy Project — Ruzena Kucera Bajcsy. nectov globinski senzor. Te informacije o 3D-obliki se lahko nato url: https://genealogy.math.ndsu.nodak.edu/id.php?id= uporabijo za izračun gibanja vodnih kapljic, ki navidezno padajo 39957 (pridobljeno 12. 9. 2021). na skulpturo. Ker gre le za virtualne vodne kaplje, jih predsta- [9] Ruzena Bajcsy in Franc Solina. “Three dimensional object vljajo svetlobne točke, ki se prek videoprojekcije projicirajo na representation revisited”. V: First International Conference skulpturo. Te svetlobne točke se dejansko gibajo kot vodne ka- on Computer Vision, ICCV’87. (London, UK). IEEE Compu- pljice, saj drsijo po površini skulpture v smeri največjega nagiba ter Society, 1987, str. 231–240. [42]. O kreativnosti v znanosti in umetnosti in kako se povezujeta [10] Franc Solina in Ruzena Bajcsy. “Recovery of parametric ti dve področji pa sem pisal v [43]. Po bolonjski reformi sem začel models from range images: the case for superquadrics redno predavati tudi na ALUO, smer Video in novi mediji. with global deformations”. V: IEEE Transactions on Pattern Analysis and Machine Intelligence 12.2 (1990), str. 131–147. 7 SKLEP doi: 10.1109/34.44401. Moje strokovno in organizacijsko delo po ustanovitvi samostojne [11] Franc Solina. “Shape recovery and segmentation with de- Fakultete za računalništvo in informatiko leta 1996 je bolj po- formable part models”. Doktorska disertacija. Philadel- drobno opisano v zborniku, ki je izšel ob 20-letnici fakultete [44]. phia, PA: University of Pennsylvania, 1987. url: https : Naj na kratko omenim le, da sem se kot dekan fakultete med leti //repository.upenn.edu/dissertations/AAI8804963. 2006 in 2010 posvetil predvsem bolonjski reformi in arhitektur- [12] Aleš Leonardis, Aleš Jaklič in Franc Solina. “Superquadrics nim načrtom nove stavbe. Pri bolonjski reformi sem si prizadeval, for segmenting and modeling range data”. V: IEEE Tran- da bi tudi umetna inteligenca dobila svoj zaslužen del študijskega sactions on Pattern Analysis and Machine Intelligence 19.11 programa na FRI, ki ga do tedaj ni imela, čeprav je prav ume- (1997), str. 1289–1295. doi: 10.1109/34.632988. tna inteligenca prispevala največ raziskovalnih rezultatov. Pri [13] Aleš Jaklič, Aleš Leonardis in Franc Solina. Segmentation novi stavbi pa smo od arhitektov predvsem želeli prostore, ki and Recovery of Superquadrics. Computational Imaging bodo omogočali lažje srečevanje ljudi in tako spodbujali večje and Vision. Springer Dordrecht, 2000. doi: 10.1007/978- sodelovanje. 94- 015- 9456- 1. [14] Jaka Krivic in Franc Solina. “Part-level object recognition LITERATURA using superquadrics”. V: Computer Vision and Image Un- derstanding 95.1 (2004), str. 105–126. doi: https://doi.org/ [1] Franc Solina. “Računalniška analiza ravninskih in prostor- 10.1016/j.cviu.2003.11.002. skih zank VKG signalov”. Diplomska naloga. Fakulteta za [15] Aleš Jaklič, Miran Erič, Igor Mihajlović, Žiga Stopinšek in elektrotehniko, Univerza v Ljubljani, 1979. Franc Solina. “Volumetric models from 3D point clouds: [2] Franc Solina. “Računalniška prepoznava motenj srčnega The case study of sarcophagi cargo from a 2nd/3rd cen- ritma”. Magistrska naloga. Fakulteta za elektrotehniko, tury AD Roman shipwreck near Sutivan on island Brač, Univerza v Ljubljani, 1982. Croatia”. V: Journal of Archaeological Science 62 (2015), [3] Krunoslav Turkulin, Ludvik Gyergyék, Marjan Vezjak, str. 143–152. doi: 10.1016/j.jas.2015.08.007. Franc Solina, Vojko Valenčič, Janez Trontelj in Slobodan [16] Žiga Stopinšek in Franc Solina. “3D modeliranje podvo- Ribarić. “Automatska analiza elektrokardiograma u opte- dnih posnetkov”. V: SI robotika. Ur. Marko Munih. Sloven- rečenju”. V: Neinvazivne metode u kardiologiji: međunaro- dni simpozij pod pokroviteljstvom Evropskog kardiološkog ska matica, 2017, 103–114. [17] Tim Oblak, Jaka Šircelj, Vitomir Štruc, Peter Peer, Franc Solina in Aleš Jaklič. “Learning to Predict Superquadric 694 Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Franc Solina Parameters From Depth Images With Explicit and Implicit [30] Enej Guček Puhar, Lidija Korat, Miran Erič, Aleš Jaklič in Supervision”. V: IEEE Access 9 (2021), str. 1087–1102. doi: Franc Solina. “Microtomographic Analysis of a Palaeoli- 10.1109/ACCESS.2020.3041584. thic Wooden Point from the Ljubljanica River”. V: Sensors [18] Darian Tomašević, Peter Peer, Franc Solina, Aleš Jaklič 22.6 (2022). doi: 10.3390/s22062369. in Vitomir Štruc. “Reconstructing Superquadrics from In- [31] Marko Hrastovec in Franc Solina. “Obtaining meteoro- tensity and Color Images”. V: Sensors 22.14 (2022). issn: logical data from aircraft with Mode-S radars”. V: IEEE 1424-8220. doi: 10 . 3390 / s22145332. url: https : / / www. Aerospace and Electronic Systems Magazine 28.12 (2013), mdpi.com/1424- 8220/22/14/5332. str. 12–24. doi: 10.1109/MAES.2013.6693664. [19] Jaka Šircelj, Tim Oblak, Klemen Grm, Uroš Petković, Aleš [32] Marko Hrastovec in Franc Solina. “Prediction of aircraft Jaklič, Peter Peer, Vitomir Štruc in Franc Solina. “Segmen- performances based on data collected by air traffic control tation and recovery of superquadric models using convo- centers”. V: Transportation Research Part C: Emerging Te- lutional neural networks”. V: Proceedings of the 25th Com- chnologies 73 (2016), str. 167–182. doi: https://doi.org/10. puter Vision Winter Workshop Conference, Rogaška Slatina, 1016/j.trc.2016.10.018. February 3-5, 2020. Ur. Alan Lukežič, Domen Tabernik in [33] Andrej Lapajne, Bor Prihavec, Aleksander Ruben, Žiga Klemen Grm. Slovensko društvo za razpoznavanje vzorcev, Kranjec in Franc Solina. “Slovenian Virtual Gallery”. V: 2020, 74–81. url: http://data.vicos.si/cvww20/CVWW20- Proceedings 4th Electrotechnical and Computer Science Con- proceedings.pdf . ference ERK. Zv. A. 1995, str. 3–6. [20] Bor Prihavec in Franc Solina. “User interface for video [34] Franc Solina in Srečo Dragan. “Novomedijski umetniški observation over the internet”. V: Journal of Network and projekti kot most med realnim in virtualnim svetom”. V: Computer Applications 21.4 (1998), str. 219–237. doi: https: Robotika in umetna inteligenca. Ur. Tadej Bajd in Ivan //doi.org/10.1006/jnca.1999.0074. Bratko. Slovenska matica, 2014, str. 187–230. url: http : [21] Peter Peer in Franc Solina. “Panoramic Depth Imaging: / / eprints . fri . uni - lj . si / 2861 / 1 / Poglavje _ SM _ Solina - Single Standard Camera Approach”. V: International Jo- Dragan.pdf . urnal of Computer Vision 47.1/2/3 (2002), 149–160. doi: [35] Srečo Dragan, Franc Solina, Bor Prihavec, Slavko Korenč 10.1023/A:1014541807682. in Bojan Nemec. “Netropolis — the Cyborg’s eye: project”. [22] Jure Kovač, Peter Peer in Franc Solina. “Human skin color V: Programme of the European cultural month: May 15 to clustering for face detection”. V: The IEEE Region 8 EURO- July 5, 1997. Municipality of Ljubljana, 1997, str. 36. CON 2003. Computer as a Tool. Zv. 2. 2003, str. 144–148. [36] Franc Solina. “New media art projects, panoramic ima- doi: 10.1109/EURCON.2003.1248169. ges and live video as interface between real and virtual [23] Robert Ravnik in Franc Solina. “Audience Measurement worlds”. V: DESIDOC Journal of Library & Information of Digital Signage: Quantitative Study in Real-World En- Technology 34.2 (2014), str. 110–124. vironment Using Computer Vision”. V: Interacting with [37] Franc Solina. “15 seconds of fame”. V: Leonardo 37.2 (apr. Computers 25.3 (feb. 2013), str. 218–228. doi: 10.1093/iwc/ 2004), str. 105–110. doi: 10.1162/0024094041139274. iws023. [38] Franc Solina. 15 sekund slave = 15 seconds of fame. Ur. Aleš [24] Robert Ravnik, Borut Batagelj, Bojan Kverh in Franc So- Vaupotič in Narvika Bovcon. Galerija spomeniškovarstve- lina. “Dynamic Anamorphosis as a Special, Computer- nega centra, Trg francoske revolucije 3, Ljubljana, 1.-12. Generated User Interface”. V: Interacting with Computers 2. 2005. ArtNetLab - društvo za povezovanje umetnosti in 26.1 (apr. 2013), str. 46–62. doi: 10.1093/iwc/iwt027. znanosti, 2005, str. 20. url: http://eprints.fri.uni- lj.si/194/. [25] Erika Pavlin, Žiga Elsner, Tadej Jagodnik, Borut Batagelj [39] Borut Batagelj in Franc Solina. “Preservation of an inte- in Franc Solina. “From illustrations to an interactive art ractive computer-based art installation - a case study”. V: installation”. V: Journal of Information, Communication International Journal of Arts and Technology 10.3 (2017), and Ethics in Society 13.2 (2015), str. 130–145. doi: 10.1108/ str. 206–230. doi: 10.1504/IJART.2017.086669. jices- 02- 2014- 0007. [40] Franc Solina. Skulpture / Sculptures 2012–2020, 2. izdaja / [26] Aleš Jaklič, Franc Solina in Luka Šajn. “User interface for 2nd Edition. Ljubljana: Društvo likovnih umetnikov Lju- a better eye contact in videoconferencing”. V: Displays 46 bljana, Fakulteta za računalništvo in informatiko, 2021. (2017), str. 25–36. doi: https : / / doi . org / 10 . 1016 / j . displa . doi: 10.51939/0001. 2016.12.002. [41] Franc Solina. Light Fountain II – Galaxy. 2022. url: https: [27] Peter Ciuha, Bojan Klemenc in Franc Solina. “Visualization //youtu.be/y6NAiXlNm20 (pridobljeno 1. 9. 2022). of concurrent tones in music with colours”. V: Proceedings [42] Franc Solina in Blaž Meden. “Light fountain – a virtually of the 18th ACM international conference on Multimedia. enhanced stone sculpture”. V: Digital Creativity 28.2 (2017), ACM. Firenze, 2010, str. 1677–1680. str. 89–102. doi: 10.1080/14626268.2016.1258422. [28] Miran Erič, Andrej Gaspari, Katarina Čufar, Franc Solina in [43] Franc Solina. “Creativity in Science and Art”. V: Creativity. Tomaž Verbič. “Zgodnjerimska ladja iz Ljubljanice pri Sinji Ur. Sílvio Manuel Da Rocha Brito in João Thomaz. Ri- Gorici = Early Roman barge from the Ljubljanica River jeka: IntechOpen, 2022. Pogl. 29. doi: 10.5772/intechopen. at Sinja Gorica”. V: Arheološki vestnik 65 (2014), 187–254. 101955. url: http://av.zrc- sazu.si/Si/65/Eric_AV_65.html. [44] Miha Bejek, Vesna Gračner, Vida Groznik, Viljan Mah- [29] Miran Erič, Enej Guček Puhar, Žiga Stopinšek, Aleš Jaklič nič in Franc Solina, ur. FRI 20: 1996-2016: 20 let Fakultete in Franc Solina. “The significance of detailed analysis of za računalništvo in informatiko Univerze v Ljubljani. Lju- 3D cloud points which include data that the human eye bljana: Fakulteta za računalništvo in informatiko, 2016. can overlook: the case of a flat-bottomed ship from the url: http://eprints.fri.uni- lj.si/3655/1/Zbornik_FRI20_ Ljubljanica river”. V: Skyllis 19.1/2 (2019), 29–40. web_100.pdf . 695 INFORMATIKA NARODU Computer science to the nation Tone Stanovnik Direktor Špica International Ljubljana, Slovenija tone.stanovnik@spica.com POVZETEK Pa ne toliko zaradi tehnike kot zaradi svobodomiselnosti, ki sem se je nalezel od sodelavcev na radiu. Zdelo se mi je, da se je pred Takoj po drugi svetovni vojni je začel izhajati časopis “Tehnika menoj odprl popolnoma nov svet. To je bilo ravno v času, ko je narodu”. Naši očetje so v želji po obnovi domovine zagnali na zahodu stopilo na pohod “mikroračunalništvo”. S starejšimi vsesplošno gibanje, da bi spodbudili prenovo ne samo na podlagi kolegi na fakulteti in nekaj entuziasti iz Iskre Delte smo delovnih brigad (na mišice) temveč tudi na krilih tehnoloških ustanovili mikroračunalniški klub in poskušali kar sami sestavit inovacij. Ob mojem vstopu v gimnazijo me je preveval občutek, svoj prvi mikroračunalnik. Na Radiu Študent pa smo zagnali da moram odkriti “perpetum mobile”. Kasneje ob študiju na posebno računalniško sekcijo in po končanem programu vsak fakulteti pa sem bil prepričan, da sem našel kar, sem iskal, to je dan predvajali zvočni zapis programske opreme, ki smo jo takrat bila informacijska tehnologija. Obilica projektov, ki sem jih na začetkih lahko posneli iz radia kar na kasete. speljal v preteklosti, mi je danes dokaz, da se nisem motil, saj je informatika danes glavna sila, ki poganja svet in tudi moj osebni inovacijski motor. Prepričan sem, da bi domovini Sloveniji sila 3 ŠKUC koristilo, da vzpostavi logiko in informatiko kot predmet že v osnovno šolo. To je tudi rdeča nit skozi vse moje javne nastope. To je bilo obdobje, ko si morali imeti svoj Punk bend ali pa vsaj mikroračunalniško delavnico v garaži. Ker še ni bilo KLJUČNE BESEDE možnosti, da bi kar odprl podjetje, sem pa imel nekaj inovativnih idej, sem se znašel tako, da sem v ŠKUCu takrat na Kersnikovi Radio Študent, Moj Mikro, Računalniški klub, Mikrohit, Špica, 4 dobil kartico svobodnega umetnika, kot so jo dobili vsi takratni ZITex, Informatika narodu, Zlata Nit Punk bendi. Tako smo lahko kupovali potrebno opremo in material brez davka. Seveda smo tudi takrat potrebovali inicialno investicijo in ker ni bilo investitorjev za vsakim vogalom kot so 1 RAČUNALNIŠKI KROŽEK danes, sem se znašel tako, da sem noč in dan na ulicah prodajal Moje prvo srečanje z informatiko je bilo v Šentviški takrat zelo popularno Tribuno in Mladino ter posebej v gimnaziji, kjer sem se skupaj z nekaj sošolci vključil v decembrskem času, ko so ljudje bolj radodarni, prišel do nujnega računalniški krožek. Naučili smo se osnove računalniškega zagonskega kapitala. jezika Fortran in nato dobili kratek termin v kleti Vegove srednje šole v mestu. Program, ki smo ga zasnovali na papirju, smo pretipkali v luknjač in rezultat je bil šop “luknjanih” kartic (za vsako vrstico programa je bila ena kartica). Nato smo svoj šop kartic pustili, da so jih v prostem času spustili skozi obdelavo in čez nekaj dni smo zopet z mestnim avtobusom prišli po izpis. Pogosto se je izkazalo, da je bilo še polno napak in tako smo ponavljali, dokler nismo prišli do končnega rezultata. Moj prvi program, se spominjam, je izračunal število prehojenih stopnic iz danega šolskega urnika v Šentviški gimnaziji, ki je bila takrat v dveh stavbah. Večkratno potovanje z avtobusom v center in nazaj me takrat ni posebej fasciniralo, a ker smo to počeli v družbi s sošolci, se mi je zdelo zelo zabavno. Saj smo drug drugemu pomagali pri odpravi napak in debatirli ter delili izkušnje. 2 RADIO ŠTUDENT V času študija je moja prijava za tonskega tehnika na Radiu Slika 1: Članek objavljen 1985 v takrat sveži reviji Moj Mikro Študent ključnega pomena za mojo usmeritev v informatiko. 696 4 ŠPICA • WFM Work Force management / Evidenca Delovnega Časa Ob zaključku študija je postal posebej v regiji zelo popularen Kot eno prvih manjših slovenskih IKT podjetij smo dali pod mikroračunalnik Spectrum, ker je bil tako majhen kot knjiga, streho tudi ISO9001 in tako že na samem začetku nakazali smer smo jih Slovenci pridno kupovali v Munchnu in jih tihotapili delovanja, ki ni zasnovana samo na količinah in hitri rasti, preko meje pod sedeži ter se tako izognili plačilu carine. Glavna temveč tudi na kakovosti, ki je ključna za dolgoročni uspeh. slabost tega za tiste čase zelo uporabnega računalnika je bila gumi tipkovnica, ki je onemogočala hitro dvoprstno tipkanje. 7 EXPORT Prišel sem na idejo, da bi izdelal profesionalno tipkovnico, ki se jo priključi na ta mali računalnik in to je bil poslovni začetek Majhna podjetja so bila v tistih časih izvozno najbolj uspešna v ŠPICE. Leta 1984 sem ŠPICA tipkovnico že prvič razstavil na radiju 500 km. In tudi Špici smo geografsko najprej postavili sejmu SODOOBNA ELEKRONIKA, o čemer je pisala tudi Mija svoje bazne tabore – svoja podjetja v glavnih mestih regije LJ, Repovž v Delu. Ker pa se mi je bližal čas, ko sem moral v vojsko, ZG, BG, SA, SK ter vzpostavili partnersko sodelovanje s podjetji sem se znašel tako, da sem v reviji Moj Mikro objavil moj načrt v Romuniji, Bolgariji in Madžarski. Z biometrično identifikacijo za samoizdelavo tipkovnice in je med mojo odsotnostjo vse pa smo se uspešno prebili tudi na trge Bližnjega Vzhoda, kjer so sestavne dele pošiljala po povzetju moja šošolka iz gimnazije. še danes naše največje implementacije Evidence delovnega časa Tako je vse funcioniralo tudi v času moje vojaščine. in kontrole dostopa v podjetjih preko 10.000 zaposlenih. Že leta 2002 smo postavili tudi zelo napredno web storitev www.myhours.com ki je izredno uspešna predvsem v Ameriki in 5 MIKROHIT je neke vrste podlaga za našo današnjo uspešno metamorfozo v Tudi v vojski nisem miroval, saj mi je oče poslal Spectrum in SaaS podjetje. Leta 2017 smo prejeli laskavo nagrado mini televizijo Shiljaris, s katerim sem vodil Računalniške IZVOZNIK LETA, ki jo podeljuje organizacija SPIRIT urice in si izboril nekaj dodatnih dni dopusta in vojsko lahko prej zaključil. Po povratku z vojske sem se zopet prijavil kot razstavljalec na sejem Sodobna Elektronika in na razstavni prostor povabil tudi MIKROHIT takrat prvo slovenko mikroračunalniko podjetje v nastajanju. Vzameno sem po sejmu dobil mesto vodje razvoja v tem mladem dinamičnem podjetju. Že takoj na začetku smo začeli razvijati HW in SW izdelke za izvoz in nastopati na največjem računalniškem sejmu CeBIT. Na sejmu smo izborili odlično pozicijo takoj pri vhodu North1 in mnogi Slovenski obiskovalci sejma so imeli tu miting-point. Ker pa je bil Mikrohit ustanovljen še kot družbena lastnina, smo Slika 3: Podelitev nagrade za izvoznika leta 2017 (agencija jo po nekaj letih štirje sodelavci mahnili na svoje in ustanovili SPIRIT Slovenija) svoje podjetje Špica International. 8 ZITex V želji, da izvozno ambicijo prenesem na širši krog slovenskih računalniških podjetij sem v okviru gospodarske zbornice GZS zagnal slovensko prebojno izvozno IKT sekcijo – ZITex, katere prvi predsednik sem postal in popeljal v tujino nekaj uspešnih izvoznih delegacij. Za dosežke na omenjenem področju sem leta Slika 2: Šport je bil vedno rdeča nit Špice, in nas tesno povezuje 2010 dobil tudi nagrado gospodarske zbornice za posebne še danes. Saj smo tudi ponosni sponzorji Benija Savška od dosežke v gospodarsvu. mladih nog. 6 ŠPICA INTERNATIONAL Nov začetek po relativnem obilju, ki nam je bil na voljo v Mikrohitu, je bil seveda težak, a kot pravi angleško reklo: Scarcity breeds clarity - Pomanjkanje zbistri pogled na ključne prioritete. Tako že samo ime ŠPICA ponazarja, da smo zastavili svojo ponudbo ozko nišno in podaljšek imena INTERNATIONAL, da želimo prodreti geografsko široko v svet. Odločili smo se, da svoje rešitve razvijemo takrat nastajajoči IDentifikacijski tehnologiji črtne kode in kasneje RFID. Na tej tehnologiji pa sta se uspešno razvili dve prepoznavni diviziji: • SCM Suplay Chain management / Logistika 697 Slika 4: Podelitev nagrade za izjemne gospodarske dosežke (GZS Gospodarska Zbornica Slovenije) 9 GaaS Government as a Service - Slovenski državni aparat kot gonilo digitalnega razvoja. Nastop na IJU 2016 - Informatika v Javni Upravi sem usmeril v pobudo, da se do 2025 na DESI lestvici iz trenutnega 20 mesta prebijemo med TOP10 EU držav s pobudo da: Slika 6: Logiko in informatiko približati mladini • Da država postane generator sprememb na področju digitalne preobrazbe, kar se je z e-Računi tudi zgodilo, a kasneje žal zastalo 11 PRODUKTIVNOST • Da vsako od TOP1000 SLO podjetji investira v 3 startup-e Kot pionir uvajanja črtne kode v Sloveniji sem seveda in tako pridemo do 3.000 startup-ov kot nekoč do 3.000 tehnologijo vedno želel vpeti v celovite rešitve, ki jih kupci mladih raziskovalcev potrebujejo za izbolšanje svojega rezultata. Pogosto še danes • Vzpostavimo predmet Logika in informatika že v osnovni naletim na trditev kakšnega direktorja, ki ga srečam v dvigalu “ šoli Stanovnik mene ne zanima čas, mene zanimajo samo rezultati”. Slovenija se je v teh zadnjih letih tudi uspešno približala prvi Jaz seveda poskušam prepričat, da je rezultat potrebno delit s deseterici. časom in tako pridemo do produktivnosti in učinkovitosti. Zato http://iju2016.iju-konferenca.si/Upload/Predstavitve/T.Stanovnik.pdf menim, da je spremljanje časa na projektih ključno za dvig učinkovitosti in posledično dodane vrednosti, ki vpliva tudi na debelino kuverte, ki jo delavci konec meseca odnesejo domov. Informatika je ključno orodje in vodstvo je zadolženo za digitalno transformacijo, ki posledično pripelje do dviga učinkovitosti v podjetju. 12 METAMORFOZA ŠPICE Špica trenutno prehaja skozi največjo metamorfozo v svojem življenju. Pripravljamo podjetje za prehod v naslednjo generacijo in krepko smo zajahali tehnologijo CLOUD računalništva, ki bo garant za prihodnje uspehe. Podobno kot v avtomobilski industriji proizvajalci prehajajo iz nafte na elektriko, v informatiki prehajamo iz prodaje sw licenc na prodajo oblačnih Slika 5: DESI lestvica 2016 z ponazoritvijo planiranega preboja storitev. Svoje preoblikovanje smo zasnovali na petih stebrih in naprej v naslednjih 10 letih. jo poimenovali K5: Kadri. Ključni Procesi, Kupci, KPI, Kultura. Že pri prvem področju Kadri smo dosegli nesluten uspeh, saj smo v zadnjih dveh zaporednih letih dosegli prvo mesto na 10 INFORMATIKA NARODU tekmovanju za najboljšega zaposlovalca Slovenije med srednjimi Počaščen sem bil s povabilom takratne ministrice za šolstvo k podjetji ZLATA NIT. sodelovanju v delovni skupini RINOS, ki se s svojimi https://www.youtube.com/watch?v=3cm_ZX0v2R8&t=93s aktivnostmi trudi za povečanje prisotnosti logike in informatike v osnovni šoli, saj je to ključnega pomena za dolgoročno uspešnost Slovenije v bodočem svetu. Ker se zavedam, da je šolski kurikulum precej težko spremenit, sem spodbujal, da poskusimo priti v šolo skozi tehnični pouk. Ocenjujem, da je to ključno področje mojega delovanja na področju računalništva, saj ima najbolj dalnosežen vpliv na bodoči uspeh Slovenije. Svojo pobudo sem kronal z nastopom na SAZUju http://videolectures.net/posvetRIN2017_stanovnik_informatika/ Slika 7: Dvakrat na vrhu ZLATA NIT 2020 in 2021. Zaposlovalec leta med srednje velikimi podjetji 698 REFERENCES: [1] Previharimo Viharje https://www.linkedin.com/pulse/previharimo-viharje-tone- stanovnik-/ [2] BIM Building Information Modeling Cankarjev Dom svetovni gradbeni kongres (2019) https://www.youtube.com/watch?v=tVpz4k6jRpc [3] SBC Tone Stanovnik Špica ustanovni član Slovenskega Kluba Podjetnikov: Čas je zlato ! (2021) https://www.linkedin.com/feed/update/urn:li:activity:689464358792 2165760 [4] GZS Gravitacija podcast: Tone Stanovnik Špica Disruptivno Innoviranje (2021) https://gravitacija.gzs.si/gravitacija-36/ [5] MJU: Digital nomads welcome to Slovenija (2020) https://www.youtube.com/watch?v=HlNcDVBjqEE [6] Finance Izvozni Fokus: Change Management (2020) https://youtu.be/Cr54Jpmj76E [7] ADECCO: CEO pogled (2020) https://www.youtube.com/watch?v=r1xtSrge-Jk [8] GZS Metamorfoza Špice long (2020) https://www.youtube.com/watch?v=aAWnvq86UVw&t=7s [9] Corpo EXPORT https://www.youtube.com/watch?v=KdtPjY9i5YA [10] Corpo Video SLO: https://www.youtube.com/watch?v=l5v6WkGKWYw [11] Corpo Video ENG: https://www.youtube.com/watch?v=fphZurgcBL0 [12] Točka Preloma 2020: Produktivnost https://4d.rtvslo.si/arhiv/tocka- preloma/174717227 [13] Špica Microsoft Partner leta: Produktivnost 2019 Kristalka: https://www.youtube.com/watch?v=56nfB- 8H9cE&feature=youtu.be [14] FINANCE: Tovarna leta: ht t ps : / / yout u. be/ 9 lP lv 1LYW 78 [15] INFOSEC Špica Time & Space Varnostni produkt leta 2019: https://www.youtube.com/watch?v=xVjBu8mnAiQ [16] Informatika Narodu: http://videolectures.net/posvetRIN2017_stanovnik_informatika/ [17] Slovenski Forum Inovacij NG: https://www.youtube.com/watch?v=gQ- eQ5xdX_o&list=PLQswk7TgcYpPf1EPldgcZdq4ca6751scS&index =3 [18] RTV Prava ideja: http://4d.rtvslo.si/arhiv/prava-ideja/30529184 [19] SPIRIT Izvoznik leta2017: https://youtu.be/VSwF5F_f2wU?t=167 [20] Radio VAL202: http://4d.rtvslo.si/arhiv/poletje-za- podjetje/174288684 [21] Val202 Poslovne krvulje: Delo od doma https://val202.rtvslo.si/2019/02/poslovne-krivulje-132/ [22] Videolectures zbirka Tone Stanovnik http://videolectures.net/tone_stanovnik/ [23] GZS ZITex https://www.youtube.com/watch?v=vgEmPcaMHPQ [24] GZS Vrh Gospodarstva GZS https://www.youtube.com/watch?v=t38s39JiiGg [25] Slovenija 5.0 1,50 min https://www.youtube.com/watch?v=kP5D2VFXeUE [26] GS1 Dec2016 https://www.youtube.com/watch?list=PLQswk7TgcYpPVd0kb QM7YwQ-kSq3pqK_R&v=P_WgCLiXY3w [27] Adria Summit BG 2016 https://www.youtube.com/watch?v=bFDjCpEQbZU&list=PLQ swk7TgcYpPVd0kbQM7YwQ-kSq3pqK_R&index=2 [28] Odmevi 11 Vrh Gospodarstva na bledu 2016 19:34 http://4d.rtvslo.si/arhiv/odmevi/174439505 699 Omrežne varnostne storitve, zasebnost in računalniško obvladovanja zaupanja – strnjena kronologija (Slovenija od učenke do mednarodne partnerice)* Cyber-security Services, Privacy and Computational Trust Management – A Timelapse (Slovenia from a student to an international partner) Denis Trček† Laboratorij za e-medije FRI, Univerza v Ljubljani denis.trcek@fri.uni-lj.si POVZETEK protocols, which have already anticipated the emergence of the Internet of Things and computing devices with restrained Pričujoč prispevek podaja kratko kronologijo pomembnejših resources. Further, computational trust management area is dogodkov pri razvoju z Internetom povezanih tehnologij in presented. Besides, there are two interesting projects from the raziskav v Sloveniji, kjer je bil avtor tvorno (so)udeležen. Za 1990s, the first one is the nation-wide introduction of the Health začetek je podan minimalen pregled vzpostavitve Interneta, ker Insurance Card of ZZZS, and the other is the establishment of the je to pač logično izhodišče. Potem pa so prikazana podrobneje National Gallery information system, which was already based ostala raziskovalna področja, o katerih se ve manj, a smo na njih on the Internet. The »establishment« of the Internet was not an dosegli pomembne dosežke. Ta področja so povezana z, npr. important achievement as far as science is concerned, but a mere lahkimi kripto-protokoli, ki so že anticipirali pojav interneta transfer of technology. Nevertheless, it gave us an important stvari (to je z računskimi viri omejenih naprav), potem je tu starting point to catch the leading developments in this and računalniško obvladovanje zaupanja, itd. Aplikacijsko pa related areas and came shoulder to shoulder with the leaders - omenimo dva zanimivejša projekta iz devetdesetih let prejšnjega sometimes we were even the first. stoletja, eden je kartica zdravstvenega zavarovanja ZZZS, drugi pa vzpostavitev informacijskega sistema Narodne galerije v KEYWORDS Ljubljani, ki je že baziral na Internetu. Če pri samem vzpostavljanju Interneta res nismo naredili kakega posebnega cyber (information) security, crypto-protocols, privacy, znanstvenega preboja pa se je to pri ostalih omenjenih področjih computational trust management gotovo zgodilo. A brez tega, da smo »splovili« Internet tudi ostalih področij verjetno ne bi bilo – to nam je dalo pomembno 1 Mreža vseh mrež kot začetek izhodišče in možnost, da smo ujeli vlak na tem področju ter se postavili z ramo ob rami z vodilnimi, včasih pa smo bili tudi prvi. O tem, kako je Internet prišel v Slovenijo je bilo že dovolj napisanega, npr. v [1]. Bi pa bilo na mestu za dodati še določene KLJUČNE BESEDE podrobnosti glede posameznikov, ki niso bili izpostavljeni do sedaj, pa je njihov prispevek gotovo potrebno omeniti. kibernetska (informacijska) varnost, zasebnost, kripto-protokoli, Torej na IJS na Odseku za digitalne komunikacije E6, ki ga računalniško obvladovanje zaupanja je v začetku devetdesetih let prejšnjega stoletja vodil dr. Janez ABSTRACT Korenini, se je znanje s področja računalniških komunikacij nabiralo predvsem v teamu, v katerem so bili dr. Borka Jerman This paper gives a short chronology of some major events in the Blažič, mag. Marko Bonač, mag. Avgust Jauk, dr. Marjeta development of Internet related technologies and research in Pučko, dr. Monika Kapus Kolar, mag. Iztok Tvrdy, mag. Jože Slovenia, where the author was actively involved. A brief Rugelj in avtor tega prispevka. »Tihi« in pomembni »zunanji« overview of the establishment of the Internet is given because it član je bil tudi takratni direktor dr. Tomaž Kalin. Znotraj IJS pa is a logical starting point. Other research areas are presented next, je potrebno omeniti še mag. Marka Martinca iz Računalniškega where we also have achieved important results, which may be centra, ki je velikokrat pomagal s svojim sistemskim znanjem, ne less known. These areas are, among others, lightweight crypto ∗ samo v povezavi z Digitalovim omrežjem Decnet in Article Title Footnote needs to be captured as Title Note †Author Footnote to be captured as Author Note operacijskim sistemom VMS, ampak tudi v povezavi s svetom operacijskega sistema Unix. 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 Omenjena skupina na IJS je bila verjetno najmočnejše jedro for profit or commercial advantage and that copies bear this notice and the full na tem področju v Sloveniji, posamezni pomembni igralci, ki so citation on the first page. Copyrights for third-party components of this work must bili z njo v povezavi pa so še mag. Davor Šoštarič z IZUM-a v be honored. For all other uses, contact the owner/author(s). Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia Mariboru in Darko Bulat iz zagrebškega SRCE-a, ki se je kasneje © 2022 Copyright held by the owner/author(s). tudi preselil v Slovenijo. 700 Začetek Interneta pri nas sega v leto 1991, ko je dr. Jerman standardih. Najprej so bili tu bolj operativni problemi, ko smo še Blažičeva vzpostavila ustrezne stike, avtor pa je kot sistemski (in v letu 1994 reševali zaplete pri »enostavnem« navzkrižnem delno programerski) akter to povezavo realiziral in nato precej certificiranju našega AC z nemškim oz. angleškim. Potem pa so časa upravljal za akademski svet. V tem času celo v ZDA ni bilo bili tu še bolj vsebinski problemi, ki so vplivali ne le na dobro znano, kaj je Internet in kako se priklopiti nanj. Zato je funkcionalnost, ampak na operabilnost strukture nasploh. Npr. založba Prentice Hall izdala knjigo, kjer so navedeni tudi administrativne pravice določene AC so bile podrejene »pionirji« vzpostavljanja interneta, med njimi mi [2]. administrativnim pravicam entitete, ki je upravljala pripadajoč Ne glede na vse povedano pa sama vzpostavitev te povezave del imenskega prostora v X.500 – in ta lahko sploh ni bila AC. ne pomeni kaj vidnejšega v znanstvenem pogledu – gre le za Takih problemov je bilo precej, tudi na uporabniški strani, npr. prenos tehnologije. A izkazala se je kot pomembna, saj je naši kako naj v globalnem imeniku X.500 uporabnik najde vse raziskovalni sferi tudi na tem in povezanih področjih omogočila certifikate, ki tvorijo verigo certifikatov, ki bi omogočila pospešeno pridruževanje najboljšim. Sreča je bila še ta, da je preverjanje nekega certifikata v poljubni mreži AC-jev. Avtor je omenjeno področje (digitalnih in računalniških komunikacij) po identifikaciji in analizi slednjega problema zasnoval rešitev, imelo tudi jasno podporo s strani vodstva IJS, predvsem dr. za realizacijo prototipa pa gre zasluga novemu članu laboratorija Tomaža Kalina in dr. Vita Turka. dr. Tomažu Klobučarju. Rešitev je vzbudila zanimanje vodilne srenje na tem področju in rezultati so bili predstavljeni na simpoziju NDSS 94 (Network and Distributed Systems Security 2 Začetek eksperimentov 94) v San Diegu [3], kjer so se zbrali mnogi poznani igralci na Z današnjega gledišča so bila gornja udejstvovanja precej tem področju, npr. dr. Steve Kent (med drugim oče standardov trivialna, a kot rečeno, tovrstnega znanja je bilo tudi po svetu za protokol IPSec). Na tem simpoziju so bili prvič tudi širše takrat malo. V kolikor so avtorju pri sami vzpostavitvi Interneta predstavljeni požarni zidovi (ang. firewalls), ki so danes lahko pomagali predvsem kolegi iz nizozemskega inštituta standardni arzenal pri zaščiti računalniških omrežij. NIKHEF (M. Teerpstra in P. Berteema), pa pri eksperimentiranju Nadaljnja analiza certificiranja in dela z direktorijem X.500 z varnostnimi storitvami ni bilo več tako. Po zaslugi vodje je pokazala, da bi bilo potrebno »bolj trdo«, to je formalno Laboratorija za odprte sisteme in mreže E5 dr. Borke Jerman- spoprijemanje s problematiko. Avtor je tovrstni model napravil Blažič (ki je zapustila odsek E6 in kamor je avtor šel z njo kot v formalnem jeziku Z (ta temelji na teoriji množic in predikatnem svojo delovno mentorico na IJS) smo pridobili potrebno strojno računu prvega reda). Ideja z jezikom Z se ni prijela, je pa imel in programsko opremo, npr. ISODE paket z imenikom po zato večji odmev iz razvitega modela izhajajoč nabor procedur. standardu X.500, a ob pičli dokumentaciji. In tako je kmalu sledil naslednji »veliki met« [4]. Administracija Vedeti je treba še, da je bilo to obdobje, ko smo vso ameriškega predsednika Clintona je septembra leta 1995 prek računalniško opremo, knjige itd. dobivali z dolgim zamikom svojih vladnih in zveznih služb (US Dept. of Commerce, samo preko podjetij, ki si imela potrjeno izvozno-uvozno National Institute of Standards and Technology, Federal Security dejavnost. Poleg tega je bil avtor »lokalni samotar«, kajti v Infrastructure Program Management Office) organizirala v Laboratoriju E5 je bil poleg vodje dolgo časa edini raziskovalni mestu McLean, Virginia, delavnico zaprtega tipa, ki je služila kot član. Nadalje, zgoraj omenjeni softver je bil pisan za drug tip orientacija vladi pri njenih odločitvah in usmeritvah na tem operacijskega sistema Unix, kot smo ga imeli mi (SunOS). Pa še področju. Nanjo je bil povabljen tudi avtor tega prispevka, kjer dobili smo ga na magnetnem traku, ki ga na IJS ni bilo moč je predstavil z naše strani raziskano problematiko ter možne prebrati. Tu so pomagali kolegi na Fakulteti za elektrotehniko in rešitve. Med udeleženci so bili tudi dr. S. Micali z MIT (nosilec računalništvo UL v laboratoriju dr. Trontlja. Potem pa smo ga Goeddelove nagrade in Turingove nagrade), pa dr. W. Ford iz prek omrežja Decnet prenesli na Digitalov računalnik Cathy na Bell Northern Research (Kanadčan, ena osrednjih oseb v tistem IJS, kjer je tekel protokol FTP, ki pa je nativni protokol za prenos času, ko je bila Kanada tudi prva država, ki je v digitalno datotek v okolju Unix. Tako je omenjeni softver končno prišel na podpisala enega od mednarodnih sporazumov). postajo Sun, prek katere je avtor že upravljal Internetno Poudariti velja, da je bil takrat OSI pristop še vedno v središču povezavo in sistem DNS. (kar je pomenilo tesno sklopljenost z imenikom X.500), kmalu Vendar je bilo pred eksperimenti s strukturami za upravljanje za tem pa je zmagoviti pristop »vsilila« ameriška komercialna ključev zaradi imenika X.500 potrebnih kar nekaj dolgih tednov sfera, spodbujena z ustreznimi vladnimi ukrepi – to je sistemskega dela ter programerskega prilagajanja aplikacije, pri nekompleksna struktura overiteljev in odmrtje globalnega čemer je izvorna koda (če spomin ne vara) obsegala še za imenika X.500 (ob odmrtju mnogih standardov OSI). Ta prehod današnji čas obsežnih cca. 40MB. S sistematičnim analiziranjem je avtor prispevka zaznal dovolj zgodaj in se je že v letu 1996 in modificiranem kode (pa tudi s poskušanjem in nekaj sreče) se usmeril na novo porajajoča se varnostna področja. je nabralo dovolj znanja, da je nekako sredi leta 1993 direktorij X.500 stekel. Manj težav je bilo s softverom, ki je omogočal certificiranje javnih ključev, a vseeno. 1 3 Kriptoprotokli z anticipacijo interneta stvari S tem se je lahko začelo vsebinsko raziskovalno delo na tem Nov fokus so postali kriptografskimi protokoli, predvsem taki, ki področju. Po nekajmesečnem delu se je izkazalo, da programski temeljijo izključno na močnih enosmernih zgoščevalnih gigant X.500 in pa struktura agencij za overjanje javnih ključev funkcijah (katerih eksistenca, teoretično gledano in skladno z (AC) ne moreta funkcionirati na način, kot je bil predviden v njihovo formalno definicijo še vedno ni dokazana) – vse to s 1 Prvo našo AC je avtor v letih 1993/94 integriral prek X.500 s prvo mednarodno infrastrukturo javnih ključev v projektu Password - https://cutt.ly/VXIr5wc. 701 poudarkom na čim manjši porabi. Verjetno je temu botrovalo Zanimivo je, da smo ob tem delu nehote delno pristali na predhodno ukvarjanje z mikrokontrolerji in delo z zbirnikom. področju umetne inteligence, čeprav tja nismo bili niti usmerjeni, Čim manjša poraba pa je permanenten inženirski izziv in to je niti se ne štejemo med tovrstne eksperte. Da se je to zgodilo je ena rdečih niti na omenjenem področju. razlog ta, da je Kvalitativna dinamika primerna za simulacije z Kmalu so sledile objave s tega področja, fokusirane na umetnimi agenti. In na tej točki je doktorand dr. David Jelenc družine lahkih kriptoprotokolov, ki temeljijo na enosmernih dobil preblisk in napravil pomemben korak naprej [11]. zgoščevalnih funkcijah. Prva najpomembnejša je prišla leta 2013 Do leta 2010 je že obstajala množica metod za računalniško v reviji IEEE Wireless Communications (kot zanimivost - revija obvladovanje zaupanja, ki so se raztezale od Dempster- je bila prva na treh področjih ISI WoS, kjer je indeksirana). Shafferjeve Teorije evidence pa do metod na osnovi teorije iger. Članek je bil s področja lahkih protokolov za zasebnost in Kako sedaj vedeti, kaj je objektivno boljše od drugega? In dr. varnost pri uporabi interneta stvari v medicini [5]. Podobna je Jelenc je dobil pravi preblisk - zasnoval je simulacijsko agentno tudi družina protokolov HFBA [6], idr. okolje, kjer smo lahko obstoječe metode »prevedli na skupni Dodaten mejnik je tudi objava znanstvene monografije s imenovalec« ter jih v kontroliranem okolju in pod kontroliranimi področja informacijske varnosti pri ugledni založbi Springer [7] pogoji evalvirali. Delo je bilo objavljeno v reviji Knowledge- – pred tem je monografijo pri tej založbi od Slovencev leta 1956 based systems (mimogrede, revija je bila prva v svoji – edini - objavil le dr. Milan Vidmar (a tu bi bilo potrebno opraviti še kategoriji revij indeksiranih po ISI WoS). dodatna preverjanja). Na tem mestu velja omeniti tudi dosežke drugih mlajših V ozadju pa je ves čas na tihem čakala problematika zaupanja, sodelavcev na področju obvladovanja zaupanja, na katere je ki zaradi težke formalne opredelitve in tretmaja sprva ni bila avtor tudi ponosen, to je doktorandov dr. Damjana Kovača in dr. primerna za inženirski oz. večdisciplinarni pristop, saj tega Eve Zupančič (s področja varnosti pa doktorandov dr. Jerneja znanja takrat nismo imeli dovolj. Kosa, dr. Aleksa Huča in dr. Andreja Dorovoljca). In končno, tudi s področja računalniškega obvladovanja zaupanja je leta 2018 sledila še ena znanstvena monografija pri 4 Računalniško obvladovanje zaupanja ugledni založbi Springer [12]. Že od prvih poskusov zagotavljanja varnosti v Internetu se je le- ta prepletala s pojmom zaupanja, npr. da v povezavi s certifikatom, kjer imamo podpis s strani agencije za preverjanje 5 Praktični rezultati za družbo pristnosti (overjanja) javnih ključev, da je to npr. sinonim za Do sedaj omenjeno delo je vodilo tudi do praktičnih zaupanje. Tudi to, da če je kaka storitev »varna«, se je kar enačilo implementacij v slovenskem okolju. Seveda pa gre večji del tega s tem, da je inherentno prisotno zaupanje vanjo. Za podkrepitev na račun npr. preostalih sodelavcev IJS. trditve – eden prvih pomembnih standardov s področja varnosti Če začnemo s akademsko mrežo ARNES – pri njenem računalniških sistemov se je imenoval Trusted Computer zagonu je potrebno izpostaviti vlogo mag. Marka Bonača in mag. Systems Evaluation Criteria! Avgusta Jauka, znotraj ARNES-a pa je bil zagnan center za A zaupanje je izmuzljiv fenomen. Zaradi ukvarjanja z intervencije ob incidentih SI-CERT, ki ga je prevzel mag. varnostjo in zasebnostjo ter konceptualnimi nejasnostmi v zvezi Gorazd. Nadalje omenimo še dr. Aleša Dobnikarja, ki je vodil s tem je področje zaupanja pritegnilo zanimanje in prve projekt SIgovCA in SIgenCA na Centru vlade za informatiko. izpostavljene dileme ter kontroverznosti v zvezi s tem so bile Neposredno je bil, med drugim, avtor udeležen tudi pri podane na vabljenem predavanju avtorja na elitni nemški uvajanju kartice zdravstvenega zavarovanja ZZZS. Celoten univerzi Ludwig Maximillian Universiataet v Muenchnu projekt je vodil mag. Marjan Sušelj z ZZZS, gonilna sila februarja 2002, kjer je bil gostujoči raziskovalec [8]. projekta. V povezavi z IJS in Odsekom E6, ki ga je vodil dr. G. Kmalu so sledile temeljne raziskave za računalniško Kandus je prišlo do sodelovanja pri varnostnih vidikih same obvladovanje zaupanja, ki so vključevala tudi več-disciplinarna kartice (to je bila domena dr. R. Novaka) in pri varnostni znanja. Najprej je bil razvit formalizem, ki je bil po svoji naravi arhitekturi pripadajočega omrežja na opremi, ki jo je dobavil polgrupa. Kar je delovalo spodbudno, saj bi lahko uporabili Siemens (to pa je bilo v domeni avtorja prispevka). Omenjeni obsežno obstoječe znanje s področja abstraktne algebre. A je projekt je šel v produkcijo leta 1998 in je bil, po dostopnih nadaljnje delo pokazalo, da ta struktura ni ustrezno reflektirala podatkih, prvi tovrstni uspešni projekt na nacionalni ravni v svetu fenomena zaupanja. In sledila je nova struktura, ki je iz [13]. Ta projekt »imamo« v uporabi še sedaj, posodobljen in zgodovinskih razlogov imela kratek čas ime Kvalitativna pripravljen za migracijo na novo osebno izkaznico. algebra, potem pa je prišlo ustreznejše poimenovanje - Od praktičnih rezultatov, o katerih se do sedaj skoraj ni Kvalitativna dinamika (KD, angl. Qualitative Assessment govorilo, omenimo še razvoj z Internetom integriranega Dynamics, QAD). KD predstavlja antropocentrični model informacijskega sistema Narodne galerije v Ljubljani v sredini zaupanja. V tem modelu so operandi kvalitativne vrednosti vzete devetdesetih let prejšnjega stoletja. Takrat je galerijo vodil dr. z ordinalne lestvice ocen, ki se najpogosteje uporabljajo v Andrej Smrekar, doktorand ugledne univerze Harvard, kjer je bil medsebojni komunikaciji pri opredeljevanju zaupanja, operatorji v stiku z Internetom ter imel na tem področju ustrezno vizijo. pa reflektirajo »možgansko procesiranje« pri nastajanju ocen Tako so se stvari pokrile v pravem času in – Narodna galerija v zaupanja posameznih entitet v odnosu do drugih entitet. Prvi, Ljubljani je bila tehnološko na področju IT kmalu pred uglednimi čeprav še precej elementarni članek na to temo, je bil objavljen tovrstnimi institucijami v svetu. leta 2003 v SCI reviji Mathematical and Computer Modelling Lahko bi nadaljevali še z vzpostavitvijo infrastrukture za [9], prva bolj poglobljena formalna obravnava pa v [10]. komercialno ponudbo interneta podjetja Quantum d.o.o. (drugi ponudnik interneta pri nas, prvo je bilo podjetje NIL), ko 702 Telekom še ni imel sestrskega podjetja Siol, pa kakim projektom to precej omogočilo prosperiteto, vključno z ugledno v bančnem sektorju… So pa tu še sodelovanja z nekaterimi Fulbrightovo štipendijo – in to možnosti bi rad zagotovil še pomembnimi mednarodnimi organizacijami, ki jih zaradi mlajšim kolegom. osebnih razlogov ne bi navajal. Zunanje vrednotenje, ki se začne z objavami v uglednih mednarodnih revijah, je pomembno izhodišče. Ker se porajajo v zadnjem času pri nas precej drugačne pobude bi veljalo razmisliti, 6 Še nekaj glasbenih paberkov da SICRIS obdržimo kot ogrodje, ki npr. do 80% ovrednoti Študij glasbe je bila ena od resnejših opcij, ki se tudi po spletu relevantnost in kakovost raziskav, ostalo pa bi bil »fine tuning«, naključij pač ni realizirala. Je pa glasba bila ves čas prisotna ki lahko ostane lokalne narave. In ena ključnih oseb pri tekom osnovne kariere na področju računalništva in informatike, uveljavljanju kvantitativnega (pretežno eksternega) vrednotenja saj je avtor tega prispevka občasno produciral in komponiral je bil dr. Franci Demšar s sodelavci, ki so tudi izšli z IJS. glasbo za npr. oddaje, ki jih je potem realizirala RTV Slovenija (primer je serija filmov o Pajkcu Ajkcu, ki je služila izobraževanju najmlajših na področju restavratorstva). DODATEK Nadalje, inspiriran s psevdo-znanstvenim pristopom pesnika Prav je, da navedem še profesorje, ki so mi predavali tekom J.W. Goetheja in njegovo Teorijo barv je želel z osnovnim študija in katerim gre posebna zahvala: dr. G. Tomšič, dr. S. naborom semantično smiselnih preslikav povezati vizualno Hodžar, dr. J. Furlan, dr. S. Poberaj, dr. L. Pipan, dr. F. Bratkovič, domeno z avdio domeno – gre torej proces za sonifikacije, ki je dr. A. Sinigoj (takrat asistent), dr. I. Bratko, dr. Z. Bohte, dr. T. za razliko od obratne preslikave (vizualizacije glasbe), skorajda Kalin in dr. N. Pavešić. nepokrit. In razvil je ustrezen nabor »semantično ekvivalentnih« preslikav na fizikalnem nivoju, fiziološkem nivoju ter čisto kreativnem nivoju. Na osnovi tega je demonstriral, kako se REFERENCE skladno s temi principi sonificira določeno sliko in rezultat je še [1] Udovč Lea, 2021. Gverilska akcija, romantika in zaupanje – tako je kar zanimiv – sodi nekako na področje minimalistične internet prišel v Slovenijo, 27. Nov 2021, https://n1info.si/poglobljeno/30- elektronske ambientalne glasbe. Celotno delo je objavljeno v obletnica-tako-je-internet-prisel-v-slovenijo/. [2] April Marine, 1993. International Sri, Internet--Getting Started (Sri reviji Digital creativity, ki visoko kotira v umetniški srenji [14]. Internet Information Series), ISBN-10: 0133279332, Prentice Hall. [3] Denis Trček, Tomaž Klobučar, Borka Jerman Blažič, Franc Bračun, 1994. CA-browsing system: a supporting application for global security services. Proceedings: Symposium on Network and Distributed System 7 Namesto zaključka Security, San Diego, str. 123-128. [4] Denis Trček, Borka Jerman-Blažič, 1995. Certification infrastructure Na koncu bi dodal nekaj generalnih misli, ki se nanašajo na reference procedures. V: BURR, William E. (ur.). Public Key našo znanstveno srenjo in so prisotne v ozadju gornje kronologije. Infrastructure Invitational Workshop, Septermer 28, 1995 MITRE Corporation McLean, NIST. Ekonomska moč države in njen mednarodni rating sta še kako [5] Denis Trček, Andrej Brodnik, 2013. Hard and soft security provisioning pomembna tudi za plasma in možnost prodora znanstvenih for computationally weak pervasive computing systems in e-health. IEEE odkritij. Iz lastne izkušnje izhaja, da je nekaj povsem drugega, če wireless communications, IEEE, ISSN 1536-1284, vol. 20, no. 4, pp. 8. [6] Trček Denis, 2005. MAC based lightweight protocols for strong npr. kak dopis pride z elektronskega naslova authentication and key exchange. Journal of information science and denis.trcek@stanford.edu (avtor je bil leta 2015 gostujoči engineering, ISSN 1016-2364, 2005, vol. 21, str. 1-13. [7] Trček Denis, 2006. Managing information systems security and privacy. profesor na Stanfordu) kot pa z elektronskega naslova Berlin; Heidelberg, Springer, cop. 2006. XIII, 235 str., ISBN 3-540- denis.trcek@poddomena.si. To je javno potrdil tudi kak drug 28103-7. ISBN 978-3-540-28103-0. raziskovalec, ki se je vrnil po doktoratu na elitni tuji univerzi - [8] Trček Denis, 2002. Computer networks security - a holistic perspective, invited talk. München: Ludwig Maximilians Universität, Institut für na tihem pa je to splošno poznana »skrivnost«. Posledično je Informatik, 8 Jan. 2002. opaznost naše znanosti manjša, tudi ko imamo dobre rezultate. [9] Trček Denis, 2009. A formal apparatus for modeling trust in computing environments. Mathematical and computer modelling, Elsevier, ISSN Slovenska znanost je del blagovne znamke Slovenija, od 0895-7177. [Print ed.], Jan. 2009, vol. 49, no. 1/2, str. 226-233, ilustr., doi: katere v tem pogledu v glavnem še prejema (po zaslugi npr. naših 10.1016/j.mcm.2008.05.005. [10] Trček Denis, 2014. Computational trust management, QAD, and its športnikov), četudi vedno več prispeva. In mora imeti možnost applications. Informatica, ISSN 0868-4952, vol. 25, no. 1, str. 139-154, vedno več prispevati tako, da je opažena (ob tem pa služi tudi https://doi.org/10.15388/Informatica.2014.08. skupnosti). Da pa bi prispevek slovenske znanosti rastel, je [11] Jelenc David, Hermoso Ramón, Sabater-Mir Jordi, Trček Denis, 2013. Decision making matters: a better way to evaluate trust models. verjetno največja nevarnost ta, da se naša znanost kakorkoli Knowledge-based systems, Elsevier, ISSN 0950-7051. vol. 52, str. 147- zapre. Npr., da manjša skupina odloča, kaj je znanost in v 164. http://dx.doi.org/10.1016/j.knosys.2013.07.016. [12] Trček Denis, 2018. Trust and reputation management systems: an e- kolikem obsegu kaj financirati – četudi so to kredibilni business perspective, SpringerBriefs in information systems, Springer, posamezniki in to počno z dobrimi nameni je dejstvo, da je moč cop. 2018. Ilustr. ISBN 978-3-319-62374-0. ISBN 3-319-62374-5. lokalnosti »neobvladljivo kvarna«. https://link.springer.com/book/10.1007/978-3-319-62374-0. [13] Trček Denis, Novak Roman, Kandus Gorazd, Sušelj Marjan, 2001. SICRIS ni čudežen, vendar omogoča vrednotenje Slovene smart card and IP based health-care information system znanstvenega dela prek spektra faktorjev. Naredil je precej reda infrastructure. International journal of medical informatics, ISSN 1386- 5056, vol. 61, str. 33-44. in transparentnosti – in slovensko znanost potisnil iz dokajšnje [14] Trček Denis 2021. Cruxes for visual domain sonification in digital arts. anonimnosti, kjer je bila. Avtor sam je mnenja, da je tudi njemu Digital creativity, vol. 32, no. 4, str. 293-30, Taylor & Francis. 703 Dosežki kandidata Žiga Turka Achievements of the candidate Ž. Turk Žiga Turk UL-FGG Jamova 2 1000 Ljubljana ziga.turk@fgg.uni-lj.si POVZETEK 1986 napiše in pri Zvezi organizacij za tehnično kulturo izda knjigo Programski jezi C. V prispevku so opisani dosežki avtorja. 1986 pod mentorstvom J. Duhovnika diplomira na FAGG z diplomskim delom »Geometrijsko modeliranje – mejni model«. 1 ŽIVLJENJEPIS 1986 se zaposli kot mladi raziskovalec na FAGG. 1989 pod mentorstvom S. Divjaka magistrira na FERI z nalogo Žiga Turk (1962) je redni profesor na Fakulteti za gradbeništvo »Razredi objektov za modeliranje v gradbeništvu«. in geodezijo Univerze v Ljubljani, prodekan za področje kakovosti in razvoja ter vodja programske skupine 1991 napiše in pri Zvezi organizacij za tehnično kulturo izda eGradbeništvo. Je univerzitetni diplomirani inženir gradbeništva, knjigo Uvod v objektno orientirano programiranje in programski magister računalništva in informatike ter doktor tehniških jezik C++. znanosti. Vse naslove je dobil na Univerzi v Ljubljani. Poleg 1992 pod mentorstvom J. Duhovnika doktorira z nalogo »Okolje akademskih ima nekaj političnih izkušenj. Dvakrat je bil minister za računalniško projektiranje gradbenih konstrukcij”. v Vladi Republike Slovenije. Več. 1993 postavi enega prvih spletnih strežnikov v Sloveniji. Starejše generacije se ga spominjajo kot enega izmed pionirjev osebnega računalništva pri nas. 1994 izdela internetni iskalnik po prosti programski opremi “Virtual Shareware Library”, ki v svetu takrat postane glavno 1983 napiše prve programe za ZX Spectrum, ki zakrožijo po orodje za ta namen. tedanji Jugoslaviji. Med temi je progam, ki je urejevalnik 1996 je med ustanovnimi uredniki mednarodne znanstvene revije besedila Tasword razširil z jugoslovanskimi črkami čćšđž in “Electronic Journal of Information Technology in Construction” Loader-Saver-Dekder za izdelavo varnostnih kopij programov. (ITCON), ki od začetka izhaja na internetu in je ena prvih v 1984 se pridruži računalniški redakciji Radia Študent. prostem dostopu. 1984 za računalniško kaseto s programi napiše naslovno igro 1997 izdela orodje WODA za izdelovanje spletnih storitev, ki Kontrabant (skupaj z Matevžem Kmetom) in še nekaj drugih imajo osnovo v zbirki podatkov. Orodje je osnova za številne programov. storitve na spletu tistega časa. Orodje da kasneje v javno rabo in 1984 skupaj s Cirilom Kraševcem predlagata ustanovitev revije se še vedno uporablja. za mikroračunalništvo. Časopisna hiša Delo ustanovi revijo Moj 2001 postane ustanovni predstojnik Katedre za gradbeno mikro. Prav številka je izšla septembra 1984. Vsebinsko sta informatiko na FGG. revijo prva štiri leta urejala Turk in Kraševec. V tem času je Turk 2004 je na FGG izvoljen za rednega profesorja. za Moj mikro napisal okrog 120 poljudnih člankov. Njegova znanstvena pot je povezana z gradbeno informatiko, 1984 razširi urejevalnik pustolovskih iger Quill z grafiko. kjer je okrog njega nastala v svetu uveljavljena raziskovalna Urejevalnik je uporabljen za igro Kontrabant 2, ki izide pri skupina. Rezultati so razvidni iz biografij in bibliografij v založbi Xenon. Napišeta jo skupaj z Matevžem Kmetom. sistemu COBISS. 1985 z Matevžem Kmetom napiše igro Eurorun. 1986 z Barbaro in Igorjem Bizjakom napišejo igro Bajke in povesti o Gorjancih. Permission to make digital or hard copies of part or all of this work for personal or LITERATURA 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 [1] Wikipedija https://sl.wikipedia.org/wiki/%C5%BDiga_Turk citation on the first page. Copyrights for third-party components of this work must [2] Domača stran https://www.zturk.com/p/ziga-turk.html be honored. For all other uses, contact the owner/author(s). [3] Vsi članki naSiol.net https://siol.net/avtorji/ziga-turk-512/ Information Society 2022, 10–14 October 2022, Ljubljana, Slovenia © 2022 Copyright held by the owner/author(s). 704 Indeks avtorjev / Author index Alatar Munqath .......................................................................................................................................................................... 651 Albreht Jaka ............................................................................................................................................................................... 359 Altunoğlu Eren ........................................................................................................................................................................... 591 Alukić Erna .................................................................................................................................................................................. 35 Anastasiou Theodora .................................................................................................................................................................. 136 Anders Christoph........................................................................................................................................................................ 583 Andova Andrejaana ........................................................................................................................................................................ 7 Angelopoulou Efthalia ............................................................................................................................................................... 604 Arnrich Bert ............................................................................................................................................................... 579, 583, 608 Avelino Roberto ......................................................................................................................................................................... 238 Babič Davorin ............................................................................................................................................................................ 363 Baeva Motušić Andreana ........................................................................................................................................................... 370 Baggia Alenka ............................................................................................................................................................................ 370 Bahovec Igor .............................................................................................................................................................................. 293 Bajraktari Fadil ........................................................................................................................................................................... 297 Baldouski Daniil ......................................................................................................................................................................... 124 Balić Nikola ............................................................................................................................................................................... 197 Bass-Krueger Julian ..................................................................................................................................................................... 55 Behrami Sami ............................................................................................................................................................................. 297 Békési József .............................................................................................................................................................................. 619 Belusky Michal .......................................................................................................................................................................... 221 Berič Martin ................................................................................................................................................................................. 87 Blatnik Robert ............................................................................................................................................................................ 226 Blatnik Živa ................................................................................................................................................................................ 375 Blažica Bojan ............................................................................................................................................................................. 604 Blaznik Dunja ............................................................................................................................................................................. 379 Bolliger Larissa .......................................................................................................................................................................... 587 Bombač Tavčar Lea ................................................................................................................................................................... 596 Bouça Raquel ............................................................................................................................................................................. 575 Branco Diogo ............................................................................................................................................................................. 575 Bratuša Maša ................................................................................................................................................................................ 60 Brecelj Bor ................................................................................................................................................................................. 132 Brence Jure ................................................................................................................................................................................... 11 Bric Rudi .................................................................................................................................................................................... 669 Brodnik Andrej ........................................................................................................................................................................... 623 Buza Krisztian ............................................................................................................................................................................ 148 Calcina Erik ................................................................................................................................................................................ 103 Carmona Natalija........................................................................................................................................................................ 383 Casals del Busto Ignacio ............................................................................................................................................................ 140 Čebulj Zajc Petra ........................................................................................................................................................................ 387 Čelan Nika .............................................................................................................................................................................. 19, 39 Čepar Drago ............................................................................................................................................................................... 303 Cerar Gregor ............................................................................................................................................................................... 144 Chaushevska Marija ..................................................................................................................................................................... 11 Cholakoska Ana ......................................................................................................................................................................... 608 Čibej Uroš .................................................................................................................................................................................. 627 Clays Els..................................................................................................................................................................................... 587 Costilla Emmanuel ..................................................................................................................................................................... 238 Delovec Urška ............................................................................................................................................................................ 390 Demšar Ema ................................................................................................................................................................................. 55 Denkovski Daniel ....................................................................................................................................................................... 567 Dobravec Tomaž ........................................................................................................................................................................ 631 Dojčinović Aleksandar ............................................................................................................................................................... 527 Drobne Samo .............................................................................................................................................................................. 604 Držanič Petra ...................................................................................................................................................................... 394, 397 705 Durmaz İncel Özlem .................................................................................................................................................................. 591 Džeroski Sašo ............................................................................................................................................................................... 11 Efnusheva Danijela .................................................................................................................................................................... 608 Ekmekci Ekrem Yusuf ............................................................................................................................................................... 591 Ercsey Zsolt ................................................................................................................................................................................ 656 Eriksonas Linas .......................................................................................................................................................................... 200 Erzar Blaž ............................................................................................................................................................................... 19, 39 Evkoski Bojan ............................................................................................................................................................................ 120 Ferreira Joaquim ......................................................................................................................................................................... 575 Filipič Bogdan .......................................................................................................................................................................... 7, 43 Florjančič Urška ......................................................................................................................................................................... 241 Fomichov Vladimir ............................................................................................................................................................ 161, 175 Fomichova Olga ................................................................................................................................................................. 161, 175 Fortuna Blaž ....................................................................................................................................................................... 132, 136 Fortuna Carolina ......................................................................................................................................................................... 144 Fric Urška ................................................................................................................................................................................... 233 Galambos Gábor ......................................................................................................................................................................... 619 Gams Matjaž .................................................................................................................................................... 19, 31, 39, 306, 672 Gjoreski Hristijan ................................................................................................................................................. 15, 567, 571, 608 Gjoreski Martin .......................................................................................................................................................................... 571 Gornik Lea ................................................................................................................................................................................. 596 Gornik Tomaž ............................................................................................................................................................................ 676 Gradišek Anton .......................................................................................................................................................................... 596 Grobelnik Marko .................................................................................................................................................................... 95, 99 Gruden Reya Kristina ................................................................................................................................................................. 401 Gsenger Rita ................................................................................................................................................................................. 64 Gucek Alenka ............................................................................................................................................................................. 140 Guerreiro Tiago .......................................................................................................................................................................... 575 Guzzi Pietro Hiram..................................................................................................................................................................... 604 Győri Ervin ................................................................................................................................................................................. 627 Havasi Andras ............................................................................................................................................................................ 197 Hegyháti Máté ............................................................................................................................................................................ 635 Heintz Christophe ......................................................................................................................................................................... 83 Horvat Laura .............................................................................................................................................................................. 412 Hrastič Aleksander ............................................................................................................................................................... 19, 563 Hrobat Hana ............................................................................................................................................................................... 596 Hudi Primož ............................................................................................................................................................................... 405 Iatchevici Vadim ........................................................................................................................................................................ 217 Istenič Tanja ............................................................................................................................................................................... 339 Jagič Katarina ............................................................................................................................................................................. 409 Jakimovski Bojan ....................................................................................................................................................................... 608 Jakimovski Goran ....................................................................................................................................................................... 600 Jakomini Žiga ............................................................................................................................................................................. 412 Jakopič Veronika ........................................................................................................................................................................ 412 Janežič Lea ................................................................................................................................................................................. 486 Jelenec Ines ................................................................................................................................................................................ 418 Jereb Eva .................................................................................................................................................................................... 535 Jerebic Drago ............................................................................................................................................................................. 311 Jerebic Sara ................................................................................................................................................................................ 311 Jevšnik Barbara .......................................................................................................................................................................... 425 Jurač Vesna ................................................................................................................................................................................ 428 Justin Martin ................................................................................................................................................................................. 68 Kalendar Marija.......................................................................................................................................................................... 608 Kalin Tomaž ............................................................................................................................................................................... 679 Kasesnik Karin ........................................................................................................................................................................... 315 Kasz Jacek .................................................................................................................................................................................. 205 Keizer Jelle ................................................................................................................................................................................. 136 Kelemen András ......................................................................................................................................................................... 619 Keser Ranka ............................................................................................................................................................................... 432 Kim Joonho ................................................................................................................................................................................ 185 706 Kiprijanovska Ivana ................................................................................................................................................................... 571 Kirsten Kristina .......................................................................................................................................................................... 579 Kistelegdy István ........................................................................................................................................................................ 656 Kizhevska Emilija ................................................................................................................................................................ 15, 567 Kobal Grum Darja ........................................................................................................................................................................ 87 Kocuvan Primož ......................................................................................................................................................................... 563 Kokec Barbara ............................................................................................................................................................................ 437 Kokelj Martina ........................................................................................................................................................................... 440 Kołakowski Paweł ...................................................................................................................................................................... 209 Kolar Žiga .............................................................................................................................................................................. 19, 39 Komarova Nadezhda .................................................................................................................................................................... 95 Konečnik Martin .................................................................................................................................................................... 19, 39 Koprivec Filip ............................................................................................................................................................................ 128 Korenič Tratnik Sebastian .......................................................................................................................................................... 116 Kosi Tina .................................................................................................................................................................................... 443 Kožuh Ines ................................................................................................................................................................................. 412 Kralj Jakob ................................................................................................................................................................................. 524 Kralj Novak Petra ....................................................................................................................................................................... 120 Kranjec Matej ............................................................................................................................................................................. 563 Krivec Jana ................................................................................................................................................................................. 181 Krömer Pavel ................................................................................................................................................................................. 7 Kržmanc Gregor ......................................................................................................................................................................... 128 Kukowska-Kaszuba Magdalena ................................................................................................................................................. 209 Kurbegović Hidajet .................................................................................................................................................................... 241 Kuzman Taja .............................................................................................................................................................................. 107 Leskovar Robert ................................................................................................................................................................. 370, 681 Leskovec Gašper .................................................................................................................................................................... 19, 39 Ljubešić Nikola .................................................................................................................................................................. 107, 120 Lobo Vítor .................................................................................................................................................................................. 575 Logar Katja ................................................................................................................................................................................... 23 Lorenčič Tadej ........................................................................................................................................................................... 541 Lozar Andrej .............................................................................................................................................................................. 447 Lučovnik Miha ........................................................................................................................................................................... 596 Lukač Luka ................................................................................................................................................................................. 647 Lukan Junoš ............................................................................................................................................................................... 587 Luštrek Mitja ................................................................................................................................................................ 15, 587, 604 Lutman Tomaž ........................................................................................................................................................................... 228 Malačič Janez ............................................................................................................................................................................. 319 Maldonado Pedro ....................................................................................................................................................................... 238 Malnarič Vili .............................................................................................................................................................................. 241 Marolt Marjeta ........................................................................................................................................................................... 482 Marušič Jar Žiga ........................................................................................................................................................................... 72 Massri M.Besher ........................................................................................................................................................................ 140 Matkovic Roberta ....................................................................................................................................................................... 604 Meden Katja ............................................................................................................................................................................... 151 Mekiš Nejc ................................................................................................................................................................................... 35 Micarelli Rita ............................................................................................................................................................................. 167 Mifsud Marie .............................................................................................................................................................................. 197 Miljković Mateja ........................................................................................................................................................................ 452 Miljkovic Miodrag ..................................................................................................................................................................... 604 Minić Miroslava ......................................................................................................................................................................... 456 Mladenić Dunja .................................................................................................................................................... 99, 111, 132, 136 Mladenić Grobelnik Adrian.......................................................................................................................................................... 99 Mlakar Miha ................................................................................................................................................................................. 35 Mlakar Tina ................................................................................................................................................................................ 460 Mocanu Iulian ............................................................................................................................................................................ 140 Močilar Mitja ............................................................................................................................................................................. 464 Mongus Domen .......................................................................................................................................................................... 685 Moontaha Sidratul ...................................................................................................................................................................... 583 Mozer Alenka ............................................................................................................................................................................. 524 707 Mozetič Igor ............................................................................................................................................................................... 120 Mušić Din ................................................................................................................................................................................... 144 Nagode Burger Andreja ............................................................................................................................................................. 467 Nagy Benedek ............................................................................................................................................................................ 639 Nančovska Šerbec Irena ..................................................................................................................................................... 418, 546 Nduka Charles ............................................................................................................................................................................ 571 Nikoloski Antonio ...................................................................................................................................................................... 571 Nikolova Dragana ...................................................................................................................................................................... 600 Nikonov Anatolij ........................................................................................................................................................................ 241 Nilsson Bengt J. ......................................................................................................................................................................... 623 Novak Erik ................................................................................................................................................................... 99, 103, 116 Novalija Inna ................................................................................................................................................................................ 95 Olivas González Alejandro ........................................................................................................................................................ 643 Osojnik Aljaž ............................................................................................................................................................................... 27 Osredkar Mari Jože .................................................................................................................................................................... 322 Ozvatič Jure ................................................................................................................................................................................ 471 Pajnik Tina ................................................................................................................................................................................. 476 Pal Levin .................................................................................................................................................................................... 226 Panev Ida .................................................................................................................................................................................... 171 Papageorgiou Sokratis G ............................................................................................................................................................ 604 Papamartzivanos Dimitrios ........................................................................................................................................................ 136 Papp Imre ................................................................................................................................................................................... 619 Pestotnik Rok ............................................................................................................................................................................. 447 Pfitzner Bjarne ........................................................................................................................................................................... 608 Pičulin Pia .................................................................................................................................................................................. 482 Piotrowska-Kirschling Agnieszka .............................................................................................................................................. 209 Pita Costa Joao ........................................................................................................................................................................... 140 Pizziolo Giorgio ......................................................................................................................................................................... 167 Podgorelec David ....................................................................................................................................................................... 647 Podgorelec Vili ........................................................................................................................................................................... 412 Podpečan Vid ............................................................................................................................................................................... 47 Poljak Lukek Saša ...................................................................................................................................................................... 326 Pollak Senja .................................................................................................................................................................................. 47 Poposki Petar .............................................................................................................................................................................. 571 Povšič Miha ................................................................................................................................................................................ 486 Presetnik Katja ........................................................................................................................................................................... 490 Prestor Domen ........................................................................................................................................................................ 19, 39 Prybylski Maxim ........................................................................................................................................................................ 213 Purg Peter ................................................................................................................................................................................... 494 Quilliot Alain ............................................................................................................................................................................. 643 Rajkovič Uroš ............................................................................................................................................................................. 370 Rehberger Roman ....................................................................................................................................................................... 499 Repič Slavič Tanja ..................................................................................................................................................................... 331 Robnik-Šikonja Marko ................................................................................................................................................................. 23 Rossi Maurizio ........................................................................................................................................................................... 140 Rožanec Jože Martin .......................................................................................................................................................... 132, 136 Rutkowski Grzegorz ................................................................................................................................................................... 209 Sali Attila ................................................................................................................................................................................... 651 Sambt Jože ......................................................................................................................................................................... 335, 339 Santos Costa João ....................................................................................................................................................................... 140 Sarabia Silvestre ......................................................................................................................................................................... 238 Saylam Berrenur ......................................................................................................................................................................... 591 Schlamberger Niko ..................................................................................................................................................................... 688 Šebenik Tina ............................................................................................................................................................................... 511 Sever Nace ................................................................................................................................................................................... 43 Sevšek Tomaž ............................................................................................................................................................................ 241 Shulajkovska Miljana ................................................................................................................................................................... 31 Simonič Barbara ......................................................................................................................................................................... 342 Šircelj Beno ................................................................................................................................................................................ 132 Šiško Primož .............................................................................................................................................................................. 587 708 Sittar Abdul ................................................................................................................................................................................ 111 Skobir Matjaž ......................................................................................................................................................................... 19, 39 Škrabl Nastja .............................................................................................................................................................................. 514 Škrjanc Maja .............................................................................................................................................................................. 128 Škrlec Rok .................................................................................................................................................................................. 517 Škrlj Gregor ................................................................................................................................................................................ 520 Slapničar Gašper .......................................................................................................................................................................... 35 Smerkol Maj ................................................................................................................................................................................. 31 Solina Franc ............................................................................................................................................................................... 692 Srbinoski Viktor ......................................................................................................................................................................... 567 Štamcar Filip .............................................................................................................................................................................. 524 Stankoski Simon ......................................................................................................................................................................... 571 Stanovnik Tone .......................................................................................................................................................................... 696 Storcz Tamás .............................................................................................................................................................................. 656 Stres Špela .......................................................................................................................................................................... 226, 228 Strgar Sonja ........................................................................................................................................................................ 476, 504 Strniša Gašper ............................................................................................................................................................................ 508 Strniša Iva................................................................................................................................................................................... 508 Susič David .................................................................................................................................................................... 19, 39, 596 Szabo Sandor .............................................................................................................................................................................. 660 Todorović Tanja ......................................................................................................................................................................... 527 Todorovski Ljupčo ....................................................................................................................................................................... 11 Tolnai József .............................................................................................................................................................................. 619 Tomat Nastja ................................................................................................................................................................................ 77 Tomšič Nika ............................................................................................................................................................................... 412 Tošić Aleksandar ........................................................................................................................................................................ 124 Toussaint Hélène ........................................................................................................................................................................ 643 Trček Denis ................................................................................................................................................................................ 700 Turk Žiga .................................................................................................................................................................................... 704 Tušar Tea .................................................................................................................................................................................. 7, 43 Uher Vojtěch .................................................................................................................................................................................. 7 Urbančič Jurij ............................................................................................................................................................................. 233 Urh Marko .................................................................................................................................................................................. 535 Us Peter ........................................................................................................................................................................................ 35 Uspenski Aliaksei ....................................................................................................................................................................... 213 Uspenskiy Alexander ................................................................................................................................................................. 213 Valenta Tanja ............................................................................................................................................................................. 347 Veliou Entso ............................................................................................................................................................................... 136 Vodopija Aljoša ....................................................................................................................................................................... 7, 43 Voronina Liubov .......................................................................................................................................................................... 83 Vujovic Gordana ........................................................................................................................................................................ 623 Vuka Ivana ................................................................................................................................................................................. 197 Webber Jason ............................................................................................................................................................................. 111 Wiedemann Elisa.......................................................................................................................................................................... 55 Zabukovec Alenka...................................................................................................................................................................... 541 Žalik Borut ................................................................................................................................................................................. 647 Zapušek Matej ............................................................................................................................................................................ 546 Zavalnij Bogdan ......................................................................................................................................................................... 660 Zelič Žan ...................................................................................................................................................................................... 87 Ženko Bernard .............................................................................................................................................................................. 27 Zevnik Filip ................................................................................................................................................................................ 144 Žganec Gros Jerneja ................................................................................................................................................................... 241 Žganec Mario ............................................................................................................................................................................. 241 Žibert Janez .................................................................................................................................................................................. 35 Žmavc Sonja ............................................................................................................................................................................... 552 Žnidaršič Anja ............................................................................................................................................................................ 482 Žnidaršič Martin ..................................................................................................................................................................... 27, 47 709 710 Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Mitja Lustrek, Matjaz Gams, Rok Piltaver Kognitivna znanost Cognitive Science Toma Strle, Borut Trpin, Olga Markic Odkrivanje znanja in podatkovna skladisca - SiKDD Data Mining and Data Warehouses - SiKDD Dunja Mladenic, Marko Grobelnik Kognitonika Cognitonics Vladimir A. Fomichov, Olga S. Fomichova 15. mednarodna konferenca o prenosu tehnologij 15th International Technology Transfer Conference Spela Stres, Robert Blatnik Demografske in druzinske analize Demographic and Family Analyzes Janez Malacic, Mari Joze Osredkar, Matjaz Gams Vzgoja in izobrazevanje v informacijski druzbi Education in Information Society Uros Rajkovic, Borut Batagelj Vseprisotne zdravstvene storitve in pametni senzorji Pervasive Health and Smart Sensing Nina Rescic, Oscar Mayora, Daniel Denkovski Srednjeevropska konferenca o uporabnem teoreticnem racunalnistvu Middle-European Conference on Applied Theoretical Computer Science Andrej Brodnik, Gabor Galambos, Branko Kavsek Legende racunalnistva in informatike Legends of Computing and Informatics Borut Zalik, Matjaz Gams Document Outline IS2022_Volume-ALL 02 - Naslovnica - notranja - A - TEMP 03 - Kolofon - A - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - A Blank Page 08 - Naslovnica - notranja - A - TEMP Blank Page 09 - Predgovor podkonference - A 10 - Programski odbor podkonference - A Blank Page 01 Andova Abstract 1 Introduction 2 Theoretical Background 3 Exploratory Landscape Analysis 4 Test problems 5 Experimental setup 6 Results 7 Conclusion and future work Acknowledgments 02 Chaushevska Abstract 1 Introduction 2 Grammars for Equation Discovery 2.1 Context-Free Grammar (CFG) 2.2 Probabilistic Context-Free Grammar (PCFG) 3 Learning probabilities in PCFGs for arithmetical expressions 3.1 The Approach 3.2 The Corpora 3.3 The Learned Probabilities 4 Conclusions and Further work 03 Kizhevska Abstract 1 Introduction 2 Metodology 2.1 Preprocessing 2.2 Feature Engineering 3 Experiments and results 3.1 Dataset Description 3.2 Experimental Setup 3.3 Results 4 Conclusions 04 Kolar Abstract 1 Introduction 2 Related work 3 Methodology 3.1 Peak Detection with Derivatives 3.2 Peak Detection with Encoder/Decoder 3.3 Peak Detection with Artificial Neural Network 3.4 Peak Detection with Convolution Neural Network 3.5 Peak Detection with Predefined Method Find_peaks 3.6 Peak Detection with Library Tsfresh 4 Conclusion and discussion Acknowledgments 05 Logar Abstract 1 Introduction 2 Related work 3 Methodology 4 Experiments and results 4.1 Evaluation Metrics 4.2 English UnifiedQA Results Using T5small 4.3 Slovene Monolingual Results Using SloT5 4.4 Cross-Lingual Transfer Using mT5 4.5 Qualitative Analysis 5 Conclusion and future work 06 Osojnik Abstract 1 Introduction 2 Related Work 3 Data 4 Methods 4.1 Sentiment Analysis 4.2 Frequent Tokens 4.3 Topic Modeling 4.4 Aggregates and trends 5 Web application 6 Conclusion Acknowledgments 07 Shulajkovska Abstract 1 Introduction 2 System 3 Data collection 3.1 Simulation 3.2 Scenarios 3.3 KPIs Calculation 4 Machine-learning for policy proposal 4.1 Methods and Results 5 conclusion 6 future work Acknowledgments 08 Slapnicar Abstract 1 Introduction 2 Related Work 3 Data Description and Preprocessing 4 Methodology and Results 5 Discussion and Conclusion Acknowledgments 09 Susic Abstract 1 Introduction 2 Dataset 3 Methodology 3.1 Signal Decomposition 3.2 Convolutional Autoencoder 4 Results 5 Conclusion Acknowledgments 10 Tusar Povzetek 1 Uvod 2 Problem razporejanja terenskega dela 2.1 Scenarij razporejanja 2.2 Spremenljivke 2.3 Omejitve 2.4 Optimizacijski kriterij 3 Trinivojski optimizacijski algoritem 3.1 Prvi nivo: razporejanje nalog po delavcih 3.2 Drugi nivo: razporejanje nalog delavca po dnevih 3.3 Tretji nivo: določitev časa začetka nalog za en dan enega delavca 4 Preizkus učinkovitosti 5 Poenostavitev problema 6 Zaključki Zahvala 11 Znidarsic Abstract 1 Uvod 2 Ozadje in sorodno delo 2.1 Platforme za vizualno programiranje in deljenje rešitev 2.2 Besedne vložitve 3 ClowdFlows 4 Uporaba Vektorskih Vložitev 4.1 Učenje modela vložitev v ClowdFlows 4.2 Izkušnje uporabnikov 5 Zaključek Zahvala 12 - Index - A Blank Page Blank Page 08 - Naslovnica - notranja - A.pdf Blank Page Blank Page IS2022_Volume-B - MIN 02 - Naslovnica - notranja - B - TEMP 03 - Kolofon - B - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - B Blank Page 08 - Naslovnica - notranja - B - TEMP Blank Page 09 - Predgovor podkonference - B 10 - Programski odbor podkonference - B 01 - Bass-Krueger-et-al_finalfinal 02 - bratusa_final 03 - Gorjup - PRAZNO 03 - Gorjup - PRAZNO 03 - Gorjup - PRAZNO 03 - Gorjup - PRAZNO 03 - Gorjup - PRAZNO 04 - Gsenger_final 05 - Justin_final Abstract 1 Introduction 2 Black box problem 3 Explanation and understanding 4 Two dimensions of opacity 5 Prediction versus understanding 6 Conclusion Acknowledgments 06 - Marusic_final 07 - Tomat_final 08 - Voronina_final 09 - Zelic_et_al-final 12 - Index - B Blank Page 07 - Kazalo - B.pdf Blank Page 12 - Index - B.pdf Blank Page 08 - Naslovnica - notranja - B.pdf Blank Page Blank Page IS2022_Volume-C - MIN 02 - Naslovnica - notranja - C - TEMP 03 - Kolofon - C - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - C 08 - Naslovnica - notranja - C - TEMP - Copy 09 - Predgovor podkonference - C 10 - Programski odbor podkonference - C 01 - SiKDD2022_paper_5613 Abstract 1 Introduction 2 Proposed Method 2.1 Constructing the Graph of n-grams 2.2 Constructing the Emotion Category Graphs 2.3 Assigning an Emotion to a Given Text 3 Related Work 4 Results 4.1 Experimental Setup 4.2 Analysis 5 Discussion 6 Conclusion 7 Acknowledgements 02 - SiKDD2022_paper_5674 03 - SiKDD2022_paper_5269 Abstract 1 Introduction 2 Related Work 3 Methodology 3.1 Topic Modeling 3.2 Artists' Similarity using Topic Clusters 4 Experiment 4.1 Dataset 4.2 Implementation details 5 Results 6 Discussion 6.1 Topic Cluster Discussion 7 Conclusion Acknowledgments 04 - SiKDD2022_paper_5343 Abstract 1 Introduction 2 Dataset 3 Feature Engineering 4 Machine Learning Experiments 4.1 Experimental Setup 4.2 Results of Learning on Various Linguistic Features 5 Conclusions Acknowledgments 05 - SiKDD2022_paper_7454 Abstract 1 Introduction 2 Related Work 2.1 Topic Modelling 2.2 Stylistic Features 2.3 Bag-of-words 3 Data collection 4 Methodology 5 Experimental Evaluation 6 Results and Analysis 7 Conclusions 06 - SiKDD2022_paper_4772 07 - SiKDD2022_paper_817 Abstract 1 Introduction 2 Results 3 Conclusion 08 - SiKDD2022_paper_3754 Abstract 1 Introduction 2 THE ROLE OF VISUALIZATIONS IN DEBUGGING COMPLEX DISTRIBUTED SYSTEMS 3 Research Objectives 4 GRAFANA PLUGINS FOR VISUALISING VOTE BASED CONSENSUS MECHANISMS AND P2P OVERLAY NETWORKS 4.1 Network Plugin 4.2 Consensus Plugin 4.3 Generality 5 Conclusion 6 Acknowledgments 09 - SiKDD2022_paper_1139 Abstract 1 Introduction 2 Related work 3 Data 4 Data representation as a heterogeneous graph 4.1 Network statistics 4.2 Feature generation 5 Anomaly detection problem definition 6 Results 6.1 Experiment details 6.2 Link prediction 6.3 Anomaly detection 7 Discussion and future work Acknowledgments A Detailed results A.1 Link prediction (AUC) A.2 Anomaly detection (F1 score) 10 - SiKDD2022_paper_2558 Abstract 1 Introduction 2 Related Work 3 Use Case 4 Methodology 4.1 Data analysis 4.2 Model training 5 Results and Analysis 6 Conclusion Acknowledgments References 11 - SiKDD2022_paper_2909 Abstract 1 Introduction 2 Related Work 3 Use Case 4 Methodology 5 Results and Analysis 6 Conclusion Acknowledgments References 12 - SiKDD2022_paper_6501 13 - SiKDD2022_paper_1337 14 - SiKDD2022_paper_4886 Abstract 1 Introduction 2 Background: Hubness-aware Weighting 3 Cython-based Implementation of Hubness Calculations 4 Discussion References 15 - SiKDD2022_paper_4306 12 - Index - C Blank Page Blank Page Blank Page 08 - Naslovnica - notranja - C.pdf Blank Page 07 - Kazalo - C.pdf Blank Page 12 - Index - C.pdf Blank Page Blank Page IS2022_Volume-D - MIN 02 - Naslovnica - notranja - D - TEMP 03 - Kolofon - D - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - D Blank Page 08 - Naslovnica - notranja - D - TEMP Blank Page 09 - Predgovor podkonference - D 10 - Programski odbor podkonference - D Blank Page 1 - FomichovsVladimirOlgaCognit2022fin1 2 - MicarelliPizzioloCognit2022fin1 3 - PanevCognit2022fin1 4 - OlgaVladimirFomichovsCognit2022fin1 5 - KrivecCognit2022fin1 6 - KimCognit2022fin1 12 - Index - D Blank Page 08 - Naslovnica - notranja - D.pdf Blank Page Blank Page IS2022_Volume-E - MIN 02 - Naslovnica - notranja - E - TEMP 03 - Kolofon - E - TEMP 04 - IS2022 - Predgovor - Koncna verzija 05 - IS2022 - Konferencni odbori 07 - Kazalo (komplet) - E 08 - Naslovnica - notranja - E - TEMP 09 - Predgovor podkonference - E 10 - Programski odbor podkonference - E 01 - JSI_paper_final_Vuka 02 - Linas Eriksonas_final 03 - Jacek Kasz- 15 ITTC final 04 - Kukowska-Kaszuba et al. manuscript after_final 05 - Uspenskiy_RCTT22_10_07_2 06 - Iatchevici Vadim - final 07 - belusky_state_aid_rdi_final 08 - 22.10.24_Article_LP_RB_SS_ITTC_IP management in collaborative projects-final 09 - Project support ITTC_Lutman_final 10 - Urska_Fric_Jurij_Urbancic_final 11 - Proyecto GSM_Slovenia_Ingles - urejeno 12 - ICTT 15 Florjancic_final Zbornik_ITTC_2022_DODATEK - ML 12 - Index (komplet) - E Blank Page Blank Page Blank Page Blank Page Blank Page IS2022_Volume-F - MIN 02 - Naslovnica - notranja - F - TEMP 03 - Kolofon - F - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - F Blank Page 08 - Naslovnica - notranja - F - TEMP Blank Page 09 - Predgovor podkonference - F 10 - Programski odbor podkonference - F 1 - Bahovec - final 2 - Behrami 3 - Cepar 4- Gams 5 - Jerebic - NOVO 6 - Kasesnik 7 - MalacicIS-final 8 - Osredkar 9 - PoljakLukek 10 - RepicSlavic - final 11 - Sambt - final 12 - SambtIstenic-final 13 - Simonic 14 - Valenta - final 12 - Index - F Blank Page 07 - Kazalo - F.pdf Blank Page 07 - Kazalo - F.pdf Blank Page 12 - Index - F.pdf Blank Page Blank Page 12 - Index - F.pdf Blank Page 07 - Kazalo - F.pdf Blank Page 12 - Index - F.pdf Blank Page 08 - Naslovnica - notranja - F.pdf Blank Page Blank Page IS2022_Volume-G - MIN 02 - Naslovnica - notranja - G - TEMP 03 - Kolofon - G - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - G 08 - Naslovnica - notranja - G - TEMP - Copy Blank Page 09 - Predgovor podkonference - G 10 - Programski odbor podkonference - G VIVID 2022 - vsi prispevki 12 - Index - G 08 - Naslovnica - notranja - G.pdf Blank Page Blank Page IS2022_Volume-H - MIN 02 - Naslovnica - notranja - H - TEMP 03 - Kolofon - H - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - H Blank Page 09 - Predgovor podkonference - H 10 - Programski odbor podkonference - H 1 - Hrastič Abstract 1 Introduction 2 Related work 3 Methodology 3.1 Data collection 3.2 Algorithm 4 Results 5 Conclusion 2- Srbinoski 3 - Nikoloski 4 - Lobo Abstract 1 Introduction 2 Methods 2.1 Data Collection 2.2 Data Pre-Processing 2.3 Evaluated Models and Features 3 Results and Discussion 3.1 Optimal configurations 3.2 Sensor placement and windows size 3.3 Optimal parameters 3.4 Feature importance 3.5 Limitations 4 Conclusions References 5 - Kirsten Abstract 1 Introduction 2 Background 3 Monitoring System Elements 3.1 Smart Devices and Wearables 3.2 Human Activity Recognition 3.3 Indoor Positioning Systems 3.4 Derived Parameters 4 Exemplary System Overview 4.1 Characteristics Monitoring 4.2 Connected System 5 Challenges and Limitations 6 Conclusion References 6 - Anders Abstract 1 Introduction 2 Experimental Framework 3 Methods 4 Results 5 Conclusion 6 Acknowledgments 7 - Lukan Abstract 1 Introduction 2 Methods 2.1 Data Collection 2.2 Classical Machine Learning Data Analysis 2.3 Variance Partitioning 3 Results 3.1 Machine Learning on Daily Aggregated Data 3.2 Sources of Variability 4 Discussion 5 Conclusions 8 - Saylam Abstract 1 Introduction 2 Related Works 3 Methodology 3.1 Dataset 3.2 Preprocessing 3.3 Model details and performance metrics 4 Classification Performance Evaluation 5 Discussion and Conclusion 9 - Susič Abstract 1 Introduction 2 Data 3 Methodology 4 Results 4.1 Ferritin 4.2 Haemoglobin 4.3 Transferrin saturation 5 Discussion and conclusion Acknowledgments 10 - Jakimovski 11 - Luštrek 12 - Cholakoska Abstract 1 Introduction 2 Related work 3 Dataset and exploratory data analysis 4 Experiments and discussion 5 Conclusion and future work Acknowledgments References 12 - Index - H Blank Page 08 - Naslovnica - notranja - H - TEMP.pdf Blank Page 07 - Kazalo - H.pdf Blank Page 12 - Index - H.pdf Blank Page Blank Page Blank Page IS2022_Volume-I - MIN 02 - Naslovnica - notranja - I - TEMP 03 - Kolofon - I - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - I Blank Page 08 - Naslovnica - notranja - I - TEMP Blank Page 09 - Predgovor podkonference - I 10 - Programski odbor podkonference - I Blank Page MATCOS-2022_paper-01_1132 MATCOS-2022_paper-02_1441 MATCOS-2022_paper-03_7512 MATCOS-2022_paper-04_8329 MATCOS-2022_paper-05_4523 MATCOS-2022_paper-06_9505 MATCOS-2022_paper-07_5263 MATCOS-2022_paper-08_3938 MATCOS-2022_paper-09_3644 MATCOS-2022_paper-10_9189 MATCOS-2022_paper-11_8913 12 - Index - I Blank Page Blank Page 08 - Naslovnica - notranja - I.pdf Blank Page Blank Page IS2022_Volume-J - MIN 02 - Naslovnica - notranja - J - TEMP 03 - Kolofon - J - TEMP 04 - IS2022 - Predgovor - TEMP 05 - IS2022 - Konferencni odbori - TEMP 07 - Kazalo - J Blank Page 08 - Naslovnica - notranja - J - TEMP Blank Page 09 - Predgovor podkonference - J 10 - Programski odbor podkonference - J 1 - Bric 2 - Gams 3 - Gornik 5 - Kalin 6 - Leskovar 7 - Mongus 8 - Schlamberger 9 - Solina Abstract 1 Analiza signalov EKG 2 Rekonstrukcija superkvadrikov iz globinskih slik 3 Uporaba računalniškega vida v uporabniških vmesnikih 4 Uporaba računalniškega vida v dediščinski znanosti 5 Analiza podatkov v letalstvu 6 Novomedijska umetnost 7 Sklep 10 - Stanovnik 11 - Trcek 12 - Turk 12 - Index - J Blank Page 08 - Naslovnica - notranja - J.pdf Blank Page Blank Page Blank Page Blank Page