• INFORMACIJSKA DRUZBA Zbornik 24. mednarodne multikonference 4.–8. oktober 2021 Ljubljana, Slovenija INFORMATION SOCIETY 4–8 October 2021 Ljubljana, Slovenia I Proceedings of the 24th International Multiconference S Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Kognitivna znanost Cognitive Science Odkrivanje znanja in podatkovna skladišča • SiKDD S Data Mining and Data Warehouses • SiKDD Delavnica projekta Insieme Insieme Project Workshop 14. mednarodna konferenca o prenosu tehnologij 14th International Technology Transfer Conference 0 Ljudje in okolje People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society Delavnica URBANITE 2021 URBANITE Workshop 2021 S 50-letnica poučevanja računalništva v slovenskih srednjih šolah 50th Anniversary of Teaching Computer Science in Slovenian Secondary Schools Delavnica projekta BATMAN BATMAN Project Workshop http://is.ijs.si I Uredniki • Editors:Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Borut Trpin, Maša Rebernik, Olga Markič, Dunja Mladenić, Marko Grobelnik, Primož Kocuvan, Flavio Rizzolio, Špela Stres, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Sergio Campos, Shabnam Farahmand, Nathalie van Loon, Erik Dovgan, Saša Divjak, Alenka Krapež, Sergio Crovella, Anton Gradišek Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 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 Delavnica projekta Insieme Insieme Project Workshop 14. mednarodna konferenca o prenosu tehnologij 14th International Technology Transfer Conference Ljudje in okolje People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society Delavnica URBANITE 2021 URBANITE Workshop 2021 50-letnica poučevanja računalništva v slovenskih srednjih šolah 50th Anniversary of Teaching Computer Science in Slovenian Secondary Schools Delavnica projekta BATMAN BATMAN Project Workshop Uredniki / Editors Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Borut Trpin, Maša Rebernik, Olga Markič, Dunja Mladenić, Marko Grobelnik, Primož Kocuvan, Flavio Rizzolio, Špela Stres, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Sergio Campos, Shabnam Farahmand, Nathalie van Loon, Erik Dovgan, Saša Divjak, Alenka Krapež, Sergio Crovella, Anton Gradišek http://is.ijs.si 4.–8. oktober 2021 / 4–8 October 2021 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 Maša Rebernik, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani Dunja Mladenić, Department for Artificial Intelligence, Jožef Stefan Institute, Ljubljana Marko Grobelnik, Department for Artificial Intelligence, Jožef Stefan Institute, Ljubljana Primož Kocuvan, Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana Flavio Rizzolio, Dipartimento di Scienze Molecolari e Nanosistemi, Cà Foscari University, Italy 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 Tomaž Ogrin, Odsek za anorgansko kemijo in tehnologijo, Institut »Jožef Stefan«, Ljubljana Uroš Rajkovič, Fakulteta za organizacijske vede, Univerza v Mariboru Borut Batagelj, Fakulteta za računalništvo in informatiko, Univerza v Ljubljani Sergio Campos, TECNALIA Research & Innovation, Spain Shabnam Farahmand, Forum Virium Helsinki, Finland Nathalie van Loon, City of Amsterdam, Netherlands Erik Dovgan, Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana Saša Divjak, Univerza v Ljubljani, Ljubljana Alenka Krapež, Gimnazija Vič, Ljubljana Sergio Crovella, IRCCS Burlo Garofolo, Italy Anton Gradišek, Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana 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 2021 Informacijska družba ISSN 2630-371X Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID 86412803 ISBN 978-961-264-225-9 (PDF) PREDGOVOR MULTIKONFERENCI INFORMACIJSKA DRUŽBA 2021 Štiriindvajseta multikonferenca Informacijska družba je preživela probleme zaradi korone v 2020. Odziv se povečuje, v 2021 imamo enajst konferenc, a pravo upanje je za 2022, ko naj bi dovolj velika precepljenost končno omogočila normalno delovanje. Tudi v 2021 gre zahvala za skoraj normalno delovanje konference tistim predsednikom konferenc, ki so kljub prvi pandemiji modernega sveta pogumno obdržali visok strokovni nivo. Stagnacija določenih aktivnosti v 2020 in 2021 pa 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 je pospešil razpad družbenih vrednot, zaupanje v znanost in razvoj. Se pa zavedanje večine ljudi, da je potrebno podpreti stroko, čedalje bolj krepi, kar je bistvena sprememba glede na 2020. Letos smo v multikonferenco povezali enajst odličnih neodvisnih konferenc. Zajema okoli 170 večinoma spletnih 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 – seveda večinoma preko spleta. Izbrani prispevki bodo izšli tudi v posebni številki revije Informatica (http://www.informatica.si/), ki se ponaša s 45-letno tradicijo odlične znanstvene revije. Multikonferenco Informacijska družba 2021 sestavljajo naslednje samostojne konference: • Slovenska konferenca o umetni inteligenci • Odkrivanje znanja in podatkovna skladišča • Kognitivna znanost • Ljudje in okolje • 50-letnica poučevanja računalništva v slovenskih srednjih šolah • Delavnica projekta Batman • Delavnica projekta Insieme Interreg • Delavnica projekta Urbanite • Študentska konferenca o računalniškem raziskovanju 2021 • Mednarodna konferenca o prenosu tehnologij • Vzgoja in izobraževanje v informacijski družbi Soorganizatorji in podporniki multikonference 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. Jernej Kozak. Priznanje za dosežek leta pripada ekipi Odseka za inteligentne sisteme Instituta ''Jožef Stefan'' za osvojeno drugo mesto na tekmovanju XPrize Pandemic Response Challenge za iskanje najboljših ukrepov proti koroni. »Informacijsko limono« za najmanj primerno informacijsko potezo je prejela trditev, da je aplikacija za sledenje stikom problematična za zasebnost, »informacijsko jagodo« kot najboljšo potezo pa COVID-19 Sledilnik, tj. sistem za zbiranje podatkov o koroni. Čestitke nagrajencem! Mojca Ciglarič, predsednik programskega odbora Matjaž Gams, predsednik organizacijskega odbora i FOREWORD - INFORMATION SOCIETY 2021 The 24th Information Society Multiconference survived the COVID-19 problems. In 2021, there are eleven conferences with a growing trend and real hopes that 2022 will be better due to successful vaccination. The multiconference survived due to the conference chairs who bravely decided to continue with their conferences despite the first pandemic in the modern era. The COVID-19 pandemic 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, COVID-19 did increase the downfall of societal norms, trust in science and progress. On the other hand, the awareness of the majority, that science and development are the only perspectives for a prosperous future, substantially grows. The Multiconference is running parallel sessions with 170 presentations of scientific papers at eleven conferences, many round tables, workshops and award ceremonies, and 400 attendees. Selected papers will be published in the Informatica journal with its 45-years tradition of excellent research publishing. The Information Society 2021 Multiconference consists of the following conferences: • Slovenian Conference on Artificial Intelligence • Data Mining and Data Warehouses • Cognitive Science • People and Environment • 50-years of High-school Computer Education in Slovenia • Batman Project Workshop • Insieme Interreg Project Workshop • URBANITE Project Workshop • Student Computer Science Research Conference 2021 • International Conference of Transfer of Technologies • Education in Information Society 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 lifelong outstanding contributions is presented in memory of Donald Michie and Alan Turing. The Michie-Turing award was given to Prof. Dr. Jernej Kozak for his lifelong outstanding contribution to the development and promotion of the information society in our country. In addition, the yearly recognition for current achievements was awarded to the team from the Department of Intelligent systems, Jožef Stefan Institute for the second place at the XPrize Pandemic Response Challenge for proposing best counter-measures against COVID-19. The information lemon goes to the claim that the mobile application for tracking COVID-19 contacts will harm information privacy. The information strawberry as the best information service last year went to COVID-19 Sledilnik, a program to regularly report all data related to COVID-19 in Slovenia. 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 Klara Vulikić 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 Bogdan Filipič Dunja Mladenič Niko Zimic Bojan Orel, Andrej Gams Franc Novak Rok Piltaver Franc Solina, Matjaž Gams Vladislav Rajkovič Toma Strle Viljan Mahnič, Mitja Luštrek Grega Repovš Tine Kolenik Cene Bavec, Marko Grobelnik Ivan Rozman Franci Pivec Tomaž Kalin, Nikola Guid Niko Schlamberger Uroš Rajkovič Jozsef Györkös, Marjan Heričko Stanko Strmčnik Borut Batagelj Tadej Bajd Borka Jerman Blažič Džonova Jurij Šilc Tomaž Ogrin Jaroslav Berce Gorazd Kandus Jurij Tasič Aleš Ude Mojca Bernik Urban Kordeš Denis Trček Bojan Blažica Marko Bohanec Marjan Krisper Andrej Ule Matjaž Kljun Ivan Bratko Andrej Kuščer Boštjan Vilfan Robert Blatnik Andrej Brodnik Jadran Lenarčič Baldomir Zajc Erik Dovgan Dušan Caf Borut Likar Blaž Zupan Špela Stres Saša Divjak Janez Malačič Boris Žemva Anton Gradišek Tomaž Erjavec Olga Markič Leon Žlajpah 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 Estimating Client's Job-search Process Duration / Andonovic Viktor, Boškoski Pavle, Boshkoska Biljana Mileva ............................................................................................................................................................................ 7 Some Experimental Results in Evolutionary Multitasking / Andova Andrejaana, Filipič Bogdan ......................... 11 Intent Recognition and Drinking Detection For Assisting kitchen-based Activities / De Masi Carlo M., Stankoski Simon, Cergolj Vincent, Luštrek Mitja .............................................................................................................. 15 Anomaly Detection in Magnetic Resonance-based Electrical Properties Tomography of in silico Brains / Golob Ožbej, Arduino Alessandro, Bottauscio Oriano, Zilberti Luca, Sadikov Aleksander ........................................ 19 Library for Feature Calculation in the Context-Recognition Domain / Janko Vito, Boštic Matjaž, Lukan Junoš, Slapničar Gašper .............................................................................................................................................. 23 Določanje slikovnega prostora na umetniških slikah / Komarova Nadezhda, Anželj Gregor, Batagelj Borut, Bovcon Narvika, Solina Franc .......................................................................................................................... 27 Automated Hate Speech Target Identification / Pelicon Andraž, Škrlj Blaž, Kralj Novak Petra ........................... 31 SiDeGame: An Online Benchmark Environment for Multi-Agent Reinforcement Learning / Puc Jernej, Sadikov Aleksander ........................................................................................................................................................ 35 Question Ranking for Food Frequency Questionnaires / Reščič Nina, Luštrek Mitja .......................................... 39 Daily Covid-19 Deaths Prediction in Slovenija / Susič David ............................................................................... 43 Iris recognition based on SIFT and SURF feature detection / Trpin Alenka, Ženko Bernard .............................. 47 Analyzing the Diversity of Constrained Multiobjective Optimization Test Suites / Vodopija Aljoša, Tušar Tea, Filipič Bogdan ................................................................................................................................................... 51 Corpus KAS 2.0: Cleaner and with New Datasets / Žagar Aleš, Kavaš Matic, Robnik-Šikonja Marko ............... 55 Kognitivna znanost / Cognitive Science ................................................................................................................ 59 PREDGOVOR / FOREWORD ............................................................................................................................... 61 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................... 62 Nevrofenomenološka študija skupinskih dinamik v spletnem učnem okolju: Preliminarni rezultati / Černe Jaša, Berbić Selma, Kalan Mateja, Mihić Zidar Lucija, Slivšek Uršek, Kordeš Urban............................................... 63 The ONE-ness of change: an explorative neurophenomenological single case study on change in mood / Kolenik Tine, Caporusso Jaya .......................................................................................................................... 68 Sensitivity of expected civilization longevity models / Marinko Anže, Žaucer Maša, Susič David, Gams Matjaž 80 Change ahead! Questioning and changing beliefs in online discussions / Motnikar Lenart, Garcia David, Metzler Hannah ............................................................................................................................................................. 84 Kaj se lahko naučimo od Jacques Mehlerja, klasičnega kognitivnega znanstvenika / Saksida Amanda ............ 89 Vpliv informacije o ceni na subjektivno oceno zvoka violin / Šerbec Anja ........................................................... 93 AI art: Merely a possibility or already a reality? / Todorović Tadej, Bregant Janez ............................................. 99 Compliance with COVID-19 preventive behaviors and proneness to cognitive biases / Toporišič Gašperšič Manca, Grof Nataša ....................................................................................................................................... 103 The ecological rationality of probabilistic learning rules in unreliable circumstances / Trpin Borut, Plementaš Ana Marija ...................................................................................................................................................... 109 Odkrivanje znanja in podatkovna skladišča - SiKDD / Data Mining and Data Warehouses - SiKDD ............. 115 PREDGOVOR / FOREWORD ............................................................................................................................. 117 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 118 Observing odor-related information in academic domain / Novalija Inna, Massri M.Besher, Mladenić Dunja, Grobelnik Marko, Schwabe Daniel, Brank Janez ........................................................................................... 119 Understanding Text Using Agent Based Models / Mladenic Grobelnik Adrian, Grobelnik Marko, Mladenić Dunja ........................................................................................................................................................................ 123 News Stream Clustering using Multilingual Language Models / Novak Erik ...................................................... 127 SloBERTa: Slovene monolingual foundation model / Ulčar Matej, Robnik-Šikonja Marko ................................ 131 Understanding the Impact of Geographical Bias on News Sentiment: A Case Study on London and Rio Olympics / Swati, Mladenić Dunja ................................................................................................................. 135 An evaluation of BERT and Doc2Vec model on the IPTC Subject Codes prediction dataset / Pranjić Marko, Robnik-Šikonja Marko, PI3 ............................................................................................................................. 139 Classification of Cross-cultural News Events / Sittar Abdul, Mladenić Dunja .................................................... 143 v Zotero to Elexifinder: Collection, curation, and migration of bibliographical data / Lindemann David ............... 147 Simple discovery of COVID ISWAR Metaphors Using Word Embeddings / Brglez Mojca, Pollak Senja, Vintar Špela............................................................................................................................................................... 151 Topic modelling and sentiment analysis of COVID-19 related news on Croatian Internet portal / Buhin Pandur Maja, Dobša Jasminka, Beliga Slobodan, Meštrović Ana .............................................................................. 155 Tackling Class Imbalance in Radiomics: the COVID-19 Use Case / Rožanec Jože M., Poštuvan Tim, Fortuna Blaž, Mladenić Dunja ...................................................................................................................................... 159 Observing Water-Related Events for Evidence-Based Decision-Making / Pita Costa Joao, Massri M.Besher, Novalija Inna, Casals del Busto Ignacio, Mocanu Iulian, Rossi Maurizio, Šturm Jan, Eržin Eva, Guček Alenka, Posinković Matej, Grobelnik Marko ................................................................................................... 163 Anomaly Detection on Live Water Pressure Data Stream / Petkovšek Gal, Erznožnik Matic, Kenda Klemen .. 167 Entropy for Time Series Forecasting / Costa Joao, Kenda Klemen, Pita Costa Joao ....................................... 171 Modeling stochastic processes by simultaneous optimization of latent representation and target variable / Jelenčič Jakob, Mladenić Dunja ..................................................................................................................... 175 Causal relationships among global indicators / Neumann Matej ....................................................................... 179 Active Learning for Automated Visual Inspection of Manufactured Products / Trajkova Elena, Rožanec Jože M., Dam Paulien, Fortuna Blaž, Mladenić Dunja ................................................................................................. 183 Learning to Automatically Identify Home Appliances / Lorbek Ivančič Dan, Bertalanič Blaž, Cerar Gregor, Fortuna Carolina ............................................................................................................................................. 187 Delavnica projekta Insieme / Insieme Project Workshop ................................................................................... 191 PREDGOVOR / FOREWORD ............................................................................................................................. 193 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 194 Platform for Multi-Omics Integration (PlatOMICs) applied to skin diseases with alterations in Notch signaling pathway / Brandão Lucas, Tricarico Paola Maura, Gratton Rossella, Moura Ronald, Crovella Sergio ........ 195 Implementing the INSIEME portal according to the patients and caregivers’ point of view / Truccolo Ivana, Gerlero Virginia, Rizzolio Flavio, Canzonieri Vincenzo .................................................................................. 199 An Analytical and Empirical Comparison of Electronic and Mobile Health Platforms / Kocuvan Primož, Dovgan Erik, Gams Matjaž .......................................................................................................................................... 202 Android Application for Distance Monitoring of Elderly Parameters / Kocuvan Primož, Gams Matjaž, Valič Jakob ........................................................................................................................................................................ 206 Development and structural design of the frontend for unifying electronic and mobile health platform / Eržen Samo, Ilijaš Tomi ............................................................................................................................................ 210 Description of Health Service Selection and Structure of ISE-EMH Platform / Bele Klemen, Kocuvan Primož, Dovgan Erik, Gams Matjaž ............................................................................................................................. 213 Usability of smart home and home automation data / Palčič Devid, Ražman Simon, Strnad Marjan .............. 217 Intelligent cognitive assistant technology for (mental) health in the ISE-EMH project / Kolenik Tine, Klun Urša, Kocuvan Primož, Gams Matjaž ...................................................................................................................... 221 Analysis of a recommendation system used for predicting medical services / Noveski Gjorgji, Valič Jakob .... 225 PlatformUptake Methodology for AHA Solution Assessment / Kolar Žiga, Gams Matjaž, Dovgan Erik, Vuk Zdenko ............................................................................................................................................................ 228 What-If Analysis of Countermeasures Against COVID-19 in November 2020 in Slovenia / Janko Vito, Reščič Nina, Tušar Tea, Luštrek Mitja, Gams Matjaž ................................................................................................ 232 Effectiveness of non-pharmaceutical interventions in handling the COVID-19 pandemic: review of related studies / Tomšič Janez, Susič David, Gams Matjaž ..................................................................................... 236 Napovedovanje trendov in optimiziranje ukrepov v boju proti pandemiji COVID-19: Tekmovanje XPRIZE in naslednji koraki / Luštrek Mitja, Reščič Nina, Janko Vito, Susič David, De Masi Carlo M., Vodopija Aljoša, Marinko Matej, Tušar Tea, Dovgan Erik, Gradišek Anton, Cigale Matej, Gams Matjaž ................................ 242 14. mednarodna konferenca o prenosu tehnologij / 14th International Technology Transfer Conference .. 247 PREDGOVOR / FOREWORD ............................................................................................................................. 249 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 250 ZAHVALE / ACKNOWLEDGEMENTS ................................................................................................................ 258 Technology Transfer Fund - Central Eastern European Technology Transfer (CEETT) platform / Leban Marijan, Stres Špela ..................................................................................................................................................... 259 Software Protection and Licensing Challenges in Europe: An Overview / Fric Urška, Stres Špela, Blatnik Robert ........................................................................................................................................................................ 265 European Guiding principles for knowledge valorisation: An assessment of essential topics to be addressed / Stres Špela, Pal Levin, Trobec Marjeta .......................................................................................................... 269 vi Digital Innovation Hubs and Regional Development: Empirical Evidence from the Western Balkan countries / Ćudić Bojan, Stres Špela ............................................................................................................................... 276 Technology Transfer as a Unifying Element in EU Projects of the Center for Technology Transfer and Innovation / Odić Duško, Stres Špela ............................................................................................................................. 277 Proof of Concept cases at the Jožef Stefan Institute in 2020 and 2021 / Trobec Marjeta, Stres Špela ............ 282 European Industrial Strategy - a great opportunity to strengthen the role of technology transfer offices / Pal Levin, Podobnik France, Stres Špela ............................................................................................................. 287 Knowledge generation in citizen science project using on-line tools: CitieS-Health Ljubljana Pilot / Ftičar Jure, Pratneker Miha, Kocman David ...................................................................................................................... 291 Overview of National Sources of Finance and Supports Available to Spin-Out Companies from Public Research Organizations / Žunič Vojka, Klanjšek Gunde Marta ..................................................................................... 295 Application of 3D printing, reverse engineering and metrology / Dedić Remzo, Stojkič Željko, Bošnjak Igor ... 299 Towards the Market: Novel Antimicrobial Material / Lutman Tomaž, Vukomanović Marija ............................... 303 Technology Transfer in Belarus / Uspenskiy Alexander, Uspenski Aliaksei, Prybylski Maxim .......................... 308 DODATEK / APPENDIKS .................................................................................................................................... 311 INTRODUCTION AND AIM OF THE CONFERENCE ................................................................................... 312 ACKNOWLEDGEMENTS ............................................................................................................................... 316 INTRODUCTION TO THE ITTC CONFERENCE AS A WHOLE ................................................................... 317 OVERVIEW OF THE PROGRAMME ............................................................................................................. 319 WELCOME ADDRESSES .............................................................................................................................. 322 ROUND TABLE: THE FUTURE OF KNOWLEDGE TRANSFER IN SLOVENIA AND EU............................ 325 PITCH COMPETITION: BEST INNOVATION WITH COMMERCIAL POTENTIAL ....................................... 338 Course of the competition ......................................................................................................................... 339 Abstracts of the competing teams and their technologies ........................................................................ 343 Award announcement Best innovation with commercial potential ............................................................ 356 Award announcement: WIPO IP Enterprise Trophy.................................................................................. 357 Keynote speech: PoC funding of research spin-offs ................................................................................. 359 Keynote speech: CEETT Platform – Central Eastern European Technology Transfer Platform .............. 361 Paper presentations: scientific papers on technology transfer and intellectual property .......................... 363 Opportunities arising from publicly funded research projects / presentations of successful scientific projects .............................................................................................................................................................. 365 Award announcement: WIPO Medal For Inventors................................................................................... 367 Research2Business meetings (R2B meetings) ......................................................................................... 369 Connecting high-school education system with academia: Presentations of selected research topics from Jožef Stefan Institute and proposals for cooperation ........................................................................... 370 The Conference closing ............................................................................................................................ 372 CONFERENCE CEREMONY ................................................................................................................... 374 Ljudje in okolje / People and Environment .......................................................................................................... 377 PREDGOVOR / FOREWORD ............................................................................................................................. 379 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 381 Demographic processes and their role in fulfilment of the objectives of Agenda 2030 / Behrmani Sami, Bajraktari Fadil ................................................................................................................................................ 383 Za mlajše prebivalstvo v boljšem okolju / Čepar Drago ..................................................................................... 387 Plačna vrzel po starosti in spolu pri inovativni in neinovativni vrsti dela / Farčnik Daša, Istenič Tanja, Sambt Jože, Redek Tjaša .......................................................................................................................................... 390 Vpliv pandemije covid-19 na razlike med spoloma v plačanem in neplačanem delu / Istenič Tanja, Sambt Jože, Farčnik Daša .................................................................................................................................................. 394 Staranje prebivalstva in več vidikov zdravljenja z zdravili / Kasesnik Karin ....................................................... 397 Prebivalstvena politika Kitajske po letu 1950: Od začetnih iskanj in socialistične vere v neomejeno rast prebivalstva do politike enega in zatem treh otrok na družino / Malačič Janez ............................................ 400 Precenjenost presežne umrljivosti za Slovenijo v letu 2020 / Sambt Jože, Istenič Tanja, Farčnik Daša, Viršček Andrej ............................................................................................................................................................. 405 Zaznavanje stresa pri srednješolcih v prvem valu epidemije COVID-19 / Stepišnik Perdih Tjaša, Macur Mirna ........................................................................................................................................................................ 408 »Podivjajmo Slovenijo« kot nov koncept varovanja okolja / Gams Matjaž ......................................................... 412 Involvement of Citizens in Environmental Epidemiology Studies: Some Experience from the CitieS-Health Ljubljana Pilot / Kocman David, Pratneker Miha, Ftičar Jure, Vrabec Tina, Robinson Johanna A., Novak Rok ........................................................................................................................................................................ 416 vii (Eko)golf igrišča in Natura 2000: Golf in varovanje okolja / Lipič Karel .............................................................. 421 Gospodarska in podnebna negotovost v Združenih državah Amerike / Romih Dejan ....................................... 424 Ponovna raba vode v urbanih okoljih kot pristop odgovornega življenja / Vovk Ana ......................................... 429 Uporaba programske opreme v zanki za izdelavo digitalnega dvojčka proizvodnega procesa / Belšak Rok, Gotlih Janez, Karner Timi ............................................................................................................................... 432 Ocena tveganja in ukrepi za varno delo v sodelovalni robotiki / Jovanović Marko, Rečnik Ivan ....................... 435 Detection of Scratches on the Surface of Metal ic Objects / Kalabakov Stefan, Marinko Anže, Ravničan Jože, PI3 .................................................................................................................................................................. 440 Infodemija: etični vidik informiranja o COVID-19 / Pivec Franci, Šercar M. Tvrtko ........................................... 444 Vzgoja in izobraževanje v informacijski družbi / Education in Information Society ........................................ 449 PREDGOVOR / FOREWORD ............................................................................................................................. 451 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 452 Poučevanje elektronike z uporabo spletnega programskega okolja Tinkercad / Albreht Jaka .......................... 455 Izzivi izvedbe praktičnega izobraževanja na višjih strokovnih šolah v pogojih COVID-19 / Balantič Branka, Balantič Zvone ................................................................................................................................................ 460 Skupinske oblike svetovanja na daljavo v času epidemije covid-19 – ugotovitve raziskav in praktične izkušnje / Batagelj Tadeja ............................................................................................................................................... 464 Karierna orientacija na daljavo / Berce Jelka ..................................................................................................... 468 Z orodjem Nearpod do interaktivne obravnave domačega branja / Blatnik Živa ............................................... 472 Liveworksheets - ko učni listi oživijo / Delovec Urška ........................................................................................ 476 Poučevanje loma in odboja svetlobe na daljavo / Hudi Primož .......................................................................... 479 Usvajanje črk v prvem razredu na daljavo / Jerina Tamara ............................................................................... 483 Uporaba spletnega orodja BookWidgets za preverjanje in ocenjevanje znanja pri pouku nemščine / Jerman Urša ................................................................................................................................................................ 486 Vpliv uporabe digitalnih sredstev na motivacijo in uspešnost učenja / Kapun Žan, Perša Tomi, Sajko Klemen, Kožuh Ines ...................................................................................................................................................... 491 Primeri dobre prakse poučevanja tujega jezika na daljavo / Karanjac Blanka ................................................... 497 Poučevanje na daljavo v prvem razredu / Klemen Sonja ................................................................................... 502 Učiteljevi izzivi med šolanjem na daljavo pri pouku geometrije / Knez Jožica ................................................... 506 Učenci v vlogi učiteljev / Kokelj Martina.............................................................................................................. 509 Enotna digitalna identiteta ArnesAAI / Kušar Luka ............................................................................................. 513 Analiza podatkov orodja za pomoč pri izbiri poklica »KamBi« / Leskovar Robert, Baggia Alenka .................... 516 Priprava in uporaba kvizov v različnih programih za preverjanje usvojenega znanja pri predmetu fizika na gimnaziji / Leskovar Kristina .......................................................................................................................... 523 Spletni jezikovni priročniki pri pouku slovenščine / Miljković Mateja .................................................................. 526 Delo na daljavo in preverjanje znanja pri matematiki / Mlinar Biček Polona ...................................................... 530 Matematični učbenik Franca Močnika / Močnik Alenka ...................................................................................... 534 Uporaba aplikacije Genial y v 2. razredu osnovne šole / Nediževec Martina .................................................... 538 Varna raba spleta za učence z učnimi težavami / Ozvatič Jure ........................................................................ 542 Storitve šolske knjižnice v času učenja na daljavo / Pajnik Tina ........................................................................ 546 Preliminarna anketa kot didaktični pripomoček / Planinc Luka .......................................................................... 550 Učenci s posebnimi potrebami in šolanje na daljavo / Posedel Golob Karmen ................................................. 555 Težave pri izobraževanju odraslih na daljavo / Prašnikar Andrej ....................................................................... 559 Digitalizacija doma / Rehberger Roman ............................................................................................................. 562 Primerjava simetričnih algoritmov / Rehberger Roman ...................................................................................... 566 E-učenje in e-poučevanje naravoslovnih vsebin / Simčič Petra ......................................................................... 574 Zaznavanje stresa pri srednješolcih v prvem valu epidemije COVID-19 / Stepišnik Perdih Tjaša, Macur Mirna ........................................................................................................................................................................ 579 Uporaba spletnega socialnega omrežja Facebook pri učenju na daljavo / Strgar Sonja ................................... 583 Discord kot platforma za izvedbo pouka na daljavo / Strniša Gašper, Strniša Iva, Rogelj Aljaž........................ 587 Obogatitev predopismenjevanja v predšolskem obdobju / Šebenik Tina ........................................................... 590 Izdelava laboratorijskih vaj s PWS / Šifrer Robert .............................................................................................. 592 Funkcionalnosti spletnih učilnic pri izobraževanju knjižničarjev med epidemijo / Škrlj Gregor .......................... 597 Primerjava pouka angleščine od 1. do 5. razreda na daljavo / Urankar Patricija ............................................... 601 Virtualna izvedba študije primera na Fakulteti za organizacijske vede Univerze v Mariboru / Urh Marko, Jereb Eva.................................................................................................................................................................. 606 Uporaba sodobnih tehnologij in metod strojnega učenja v mladinskem nogometu / Vrban Rok, Kel y Seamus, Kljajić Borštnar Mirjana ................................................................................................................................... 611 viii Spremljanje napredka in dajanje povratne informacije v času dela na daljavo / Vučko Tadeja......................... 614 Priprava na obštudijsko dejavnost »Organizacija in usposabljanje v potapljanju« / Werber Borut, Rajkovič Uroš ........................................................................................................................................................................ 618 Šolanje na daljavo v digitalnem okolju / Žerjal Samo ......................................................................................... 624 Delavnica URBANITE 2021 / URBANITE Workshop 2021 ................................................................................... 627 PREDGOVOR / FOREWORD ............................................................................................................................. 629 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 630 How Disruptive Technologies can Strengthen Urban Mobility Transformation. The Experience of URBANITE H2020 Project / Ciulla Giuseppe, Di Bernardo Roberto, Matranga Isabel, Martella Francesco, Parrino Giovanni, Farahmand Shabnam .................................................................................................................... 631 An Overview of Transport Modelling Approaches – A Use Case Study of Helsinki / Farahmand Shabnam ..... 635 URBANITE: Messina Use Case in Smart Mobility Scenario / Martella Francesco, Parrino Giovanni, Colosi Mario, Ciulla Giuseppe, Di Bernardo Roberto, Martorana Marco, Callari Roberto, Fazio Maria, Celesti Antonio, Villari Massimo ................................................................................................................................. 638 Data commons in smart mobility – the road ahead? / van Loon Nathalie, Snijders Rosalie.............................. 642 Urbanite Mobility Data Analysis Tools / Olabarrieta Ignacio, Campos Sergio, Laña Ibai, Gil Raquel, Larrañaga Urrotz, Farahmand Shabnam ......................................................................................................................... 646 Applicable European Regulations for Data-driven Policy-making / Bilbao Sonia, López Maria José, Campos Sergio ............................................................................................................................................................. 650 Supporting Decision-Making in the Urban Mobility Policy Making / Dovgan Erik, Smerkol Maj, Sulajkovska Miljana, Gams Matjaž ..................................................................................................................................... 654 URBANITE Data Management Platform / Meiners Fritz, Bilbao Sonia, Ciulla Giuseppe, Lazaro Gonzalo ....... 658 Traffic Simulation for Mobility Policy Analysis / Smerkol Maj, Sulajkovska Miljana, Dovgan Erik, Gams Matjaž ........................................................................................................................................................................ 662 Machine Learning-Based Approach for Estimating the Quality of Mobility Policies / Sulajkovska Miljana, Smerkol Maj, Dovgan Erik, Gams Matjaž....................................................................................................... 666 Visualizations for Mobility Policy Design / Smerkol Maj, Sulajkovska Miljana, Dovgan Erik, Gams Matjaž ...... 670 URBANITE Ecosystem: Integration and DevOps / López Maria José, Etxaniz Iñaki, Ciulla Giuseppe ............. 674 50-letnica poučevanja računalništva v slovenskihsrednjih šolah / 50th Anniversary of Teaching Computer Science in Slovenian Secondary Schools ...................................................................................................... 679 PREDGOVOR / FOREWORD ............................................................................................................................. 681 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 682 Matematiki in računalniško izobraževanje, do 1980 / Batagelj Vladimir ............................................................. 683 Komisija za uvajanje računalništva v srednje šole / Hafner Izidor ..................................................................... 688 50 let od uvedbe predmeta računalništvo v srednje šole: poskusni pouk in učbenik / Bratko Ivan, Lajovic Iztok, Rajkovič Vladislav ........................................................................................................................................... 692 Začetki pouka programiranja na Fakulteti za elektrotehniko UL / Divjak Saša .................................................. 696 Začetki mariborskega računalništva (do ustanovitve univerze 1975) / Pivec Franci ......................................... 699 Slovensko računalništvo skozi pogled dijaka l. 1971 / Gams Matjaž ................................................................. 702 Od prve do enajste šole računalništva / Dolenc Tomi ........................................................................................ 706 50 let računalništva v slovenskih srednjih šolah - pogled dijakinje in učiteljice z Gimnazije Vič / Krapež Alenka ........................................................................................................................................................................ 710 Moje računalniško izobraževanje / Solina Franc ................................................................................................ 712 Delavnica projekta BATMAN / BATMAN Project Workshop ............................................................................... 717 PREDGOVOR / FOREWORD ............................................................................................................................. 719 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 720 Identification Of Novel Genetic Variants In Hidradenitis Suppurativa Patients Through The Investigation Of Familial Cases / Tricarico Paola Maura, Moura Ronald, Gratton Rossella, dos Santos Silva Carlos André, Brandão Lucas, Crovel a Sergio ..................................................................................................................... 721 Generation Of Animal And Human 3D Models Of Acne Inversa / Boufenghour Wacym, Flacher Vincent ........ 725 Development Of New Cellular Models To Identify Molecular Mechanisms In Hidradenitis Suppurativa / Nait- Meddour Cecile, Matar Rola, Boniotto Michele .............................................................................................. 727 Hidradenitis Suppurativa: From Clinic To Bench And Back / Marzano Angelo, Moltrasio Chiara, Genovese Giovanni ......................................................................................................................................................... 730 Disease Burden Of Hidradenitis Suppurativa And Assessment Of A Non-Invasive Treatment Option / von Stebut Esther .................................................................................................................................................. 733 ix An Overview of the BATMAN Platform / Vuk Zdenko, Bizjak Jani, Dovgan Erik, Gams Matjaž, Gradišek Anton ........................................................................................................................................................................ 735 Indeks avtorjev / Author index .............................................................................................................................. 739 x Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek A Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume A Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Uredniki / Editors Mitja Luštrek, Matjaž Gams, Rok Piltaver http://is.ijs.si 8. oktober 2021 / 8 October 2021 Ljubljana, Slovenia 1 2 PREDGOVOR Po zaslugi pandemije COVID-19 še vedno živimo v bolj zanimivih časih, kot bi si želeli, vendar umetne inteligence to ne moti in napreduje s podobnim tempom kot pretekla leta. Računalniški vid in obdelava naravnega jezika sta še vedno vroči področji, pred nedavnim pa nam je OpenAI postregel s parom navdušujočih kombinacij obojega. Prva je DALL-E, globoka nevronska mreža, izpeljana iz OpenAIjeve slavne mreže za generiranje besedila GPT-3, ki je sposobna »razumeti« opis slike in nato takšno sliko generirati. Pri tem je kos slikam, na kakršne prej ni naletela – generirati zna denimo prav čedno sliko redkve daikon v baletnem krilcu, ki sprehaja psa. Druga, CLIP, deluje obratno in generira besedilne opise slik. Še en viden dosežek zadnjega časa prihaja s področje biologije in medicine, ki sta zelo plodni področji za uporabo umetne inteligence. Algoritem AlphaFold 2, ki – podobno kot večina pomembnih dosežkov umetne inteligence zadnjih let – temelji na globokih nevronskih mrežah, je dosegel dramatičen napredek pri določanju strukture beljakovin, kar je težaven problem, pomemben za razvoj zdravil. Posebej odmeven nedaven dosežek umetne inteligence iz domačih logov je metoda za priporočanje optimalnih ukrepov zoper COVID-19, ki jo je razvila ekipa Odseka za inteligentne sisteme na Institutu Jožef Stefan. Pri tej sodbi avtorji predgovora sicer nismo povsem nepristranski, saj sva k dosežku dva prispevala, a drugo mesto ne tekmovanju XPrize Pandemic Response Challenge s polmilijonskim nagradnim skladom našo trditev potrjuje. Za uspeh tokrat ni bila potrebna globoka nevronska mreža – metoda kombinira epidemiološki model SEIR, klasično strojno učenje in večkriterijsko optimizacijo z evolucijskim algoritmom. Na Slovenski konferenci o umetni inteligenci je predstavljen le delček tega dela, več o njem pa je moč izvedeti na Delavnici projekta Insieme Interreg, ki prav tako poteka v okviru Informacijske družbe. Posebej veliko število drugih delavnic in konferenc na Informacijski družbi letos je sicer dobro za multikonferenco kot celoto, našo konferenco pa je bržkone prikrajšalo za kak prispevek. K tej težavi moramo dodati še naveličanost raziskovalne srenje nezmožnosti žive udeležbe na konferencah, tako da smo se morali na koncu zadovoljiti s 13 prispevki. Večino je kot po navadi prispeval Institut Jožef Stefan, dobro je zastopana tudi Fakulteta za računalništvo in informatiko Univerze v Ljubljani, druge ustanove pa žal ne. Kljub temu smo poskrbeli, da so prispevki kakovostni, in smo jih zavrnili več kot pretekla leta. Bomo pa prihodnje leta napeli moči, da privabimo več prispevkov iz širšega nabora ustanov. 3 FOREWORD Thanks to the COVID-19 pandemic we still live in more interesting time than we would like, but artificial intelligence is not much bothered by this and is progressing as rapidly as in the recent years. Computer vision and natural language processing are still hot topics, and OpenAI recently provided a pair of exciting combinations of the two. The first is DALL-E, a deep neural network derived from OpenAI's famous language generation network GPT-3. It can »understand« a description of an image and then generate such an image. It can handle images never encountered before – for instance, it can generate a nice image of a daikon radish in a tutu walking a dog. The second is CLIP, which works in reverse and generates descriptions of images. Another prominent recent achievement comes from biology and medicine, which is fruitful ground for applications of artificial intelligence. The AlphaGo 2 algorithm, which – like most main achievements of artificial intelligence in the recent years – is based on deep neural networks, achieved a breakthrough in protein folding. This is a hard problem important for drug discovery. A prominent recent Slovenian achievement of artificial intelligence is a method for recommending optimal interventions against COVID-19, which was developed by a team from the Department of Intelligence Systems at Jožef Stefan Institute. The authors of this foreword are not entirely unbiased when we say this, because two of us contributed to the achievement, but second placed at the XPrize Pandemic Response Challenge with a prize purse of half a million lends credence to our claim. This success did not require a deep neural network – the method combines a SEIR epidemiological model, classical machine learning and multi-objective optimisation with an evolutionary algorithm. The Slovenian Conference of Artificial Intelligence presents only a small part of this work, while more can be learned in the Insieme Interreg project workshop. A particularly large number of other workshops and conference at Information Society this year are good for the multi-conference as a whole, but probably deprived our conference for a few papers. Another problem is that the research community is getting tired of the inability to attend conferences live, which is why we ended up with only 13 papers. Most of them, as usual, come from Jožef Stefan Institute. The Faculty of Computer and Information Science of the University of Ljubljana is also well represented, while other institutions less so. Despite this we made sure that the papers are high-quality, and we turned away more than usual. But our goal for the following years is of course to secure more papers from a wider range or institutions. 4 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Mitja Luštrek Matjaž Gams Rok Piltaver Cene Bavec Jaro Berce Marko Bohanec Marko Bonač Ivan Bratko Bojan Cestnik Aleš Dobnikar Bogdan Filipič Borka Jerman Blažič Marjan Krisper Marjan Mernik Biljana Mileva Boshkoska Vladislav Rajkovič Niko Schlamberger Tomaž Seljak Miha Smolnikar Peter Stanovnik Damjan Strnad Vasja Vehovar Martin Žnidaršič 5 6 Estimating Client’s Job-search Process Duration Viktor Andonovic1 Pavle Boškoski2 Biljana Mileva Boshkoska2,3 Knowledge Technologies Knowledge Technologies Knowledge Technologies 1Jožef Stefan International 2Institute Jožef Stefan 2Institute Jožef Stefan Postgraduate School Ljubljana, Slovenia 3 Faculty of information studies Ljubljana, Slovenia pavle.boskoski@ijs.si 2Ljubljana, Slovenia viktor.andonovikj@ijs.si 3Novo Mesto, Slovenia biljana.mileva@ijs.si ABSTRACT are built on top of statistical surveys [2]. These data sets comprise a series of snapshots of an individual labour force status observed Modelling the labour market, analysing ways to reduce at discrete time points. Such discrete sampling might be with low unemployment, and creating decision support tools are frequency in order to truly capture the changing dynamics. becoming more popular topics with the rise in digital data and Several methods for approaching similar labour market computational power. The paper aims to analyse a Machine modelling problems have been implemented in other countries. Learning (ML) approach for estimating the time duration until Finland’s Statistical profiling tool, introduced in 2007, consists a job-seeker finds a job, i.e. leaves the Public Employment of a simple logit model [3]. It predicts the probability of long- Service (PES), after the initial entering. The dataset that we use term unemployment and categorises job seekers into two groups, from PES is complex, and there is almost no correlation between risk or high-risk of long-term unemployment. In 2012 Ireland most of the features in it, which makes it challenging for implemented a PEX (probability of exit) model using data modelling. We used statistical analysis and visualisations to collected on job-seekers who entered the PES as unemployed understand the problem better and form a basis for further during 13 weeks [4]. The PEX tool is a probit model for modelling. As a result, we developed several ML models, measuring the job-seeker's probability of exiting unemployment including basic multivariate linear regression used for in one year. performance comparison with other more specifically designed As a result of our work, we have developed an ML model models. that can be used in a PES as a part of their decision toolbox, which can serve as a filtering method that prioritises job-seekers 1 INTRODUCTION and recognises ones who do not necessarily need PES resources and services, as they will get employed soon regardless of the The research field of creating tools for supporting the decision- interventions by the organisation. making process for employment services has attracted significant interest lately. One can track such efforts for more than 20 years [1]. Different variants of tools and systems have been developed 2 DATA and implemented with varying success in different countries. The data used for the paper is provided by a public organisation PES is willing to move away from the traditional role of servicing engaged in the HECAT project [4], which aims at investigation, the job-seekers and take a more systematic approach by demonstration and pilotting a profiling tool to support labour implementing data-driven solutions in their toolbox. Here, the market decision making by unemployed citizens and case goal is to create a model that uses available data that describes workers in PES. the job-seekers that have entered the PES and outputs the approximate time (in days) needed for the individual to leave the 2.1 Data description PES as an employed person. These factors can be assessed either by introducing experts’ The dataset consists of 74086 instances, each representing a knowledge or by extracting the corresponding dynamics directly client enrolled in the PES, described with 16 sociological, from the available data. What was (or is) available determines demographic and time-related characteristics, known as features how the models are built and their effectiveness. or attributes. The data were obtained during one year. The dataset The biggest issue when dealing with any modelling, for that is complex in a way that its attributes come in a different form matter, is the quality of data. Typically models of the labour flow (categorical, numerical, date and time), and most of them need to undergo some transformation for the aim of input suitability for different ML models. The general structure of the client's attributes is described by dividing the attributes into several 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 prominent groups: socioeconomic variables (gender, age, for profit or commercial advantage and that copies bear this notice and the full nationality), information on job readiness (education, health citation on the first page. Copyrights for third-party components of this work must limitations, care responsibilities), and opportunities (regional be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia labour market development), and all available labour market © 2021 Copyright held by the owner/author(s). history information, such as prior work experience. Most of the 7 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia V. Andonovic et al. categorical features are given with numbers, where each number represents a unique category, described in a separate CSV file. The target variable is in numeric form, and it is a counter of days that a person stays in the process before exiting the PES. Some of the features in the dataset contain weird values (such as the negative number for clients age), which are a mistake or a result of noise in the data. This indicates the necessity of performing data cleaning and preprocessing before using the dataset to input various ML models. Figure 1 gives an overview of the attributes of the dataset. Figure 3: Grid of distributions of the dataset features 2.3 Data preprocessing It is estimated that in most data mining and knowledge discovery pipelines, 75 to 85% of the time is dedicated to preprocessing the data [5]. Cleaning and transforming samples are the cornerstone Figure 1: General information on the dataset features of a reliable and robust pattern recognition system. The first step of the data preprocessing part was data cleaning. The dataset 2.2 Data understanding included values for some of the attributes, which were an obvious result of a noise or a mistake. For example, some of the instances The target variable, 'duration', is a numerical count variable. In had negative values for the target variable, which is impossible order to gain a better understanding of the target variable, the because of the nature of that attribute, which is a count-based probability distribution was plotted on a graph. Figure 2 shows variable. the probability distribution of 'duration’. Most of the classical ML algorithms require the input data to be in numerical form. We used one-hot-encoding for the categorical features with at most 20 different categories. High- cardinality features were encoded using the Binary Encoding technique. Frequently used techniques like label-encoding do not work in high-cardinality because of the inclusion of artificial numerical relative distance between the instances or overfitting in the case of one-hot-encoding [6]. The ‘Entry Date’ feature was used to extract the day and month of entry separately. As those are cyclical features, we performed a transformation in order to better represent the cyclical phenomenon, for instance to avoid the artificial large difference between month 1 and month 12. The best way to Figure 2: Probability distribution of the target variable handle this is to calculate the sin() and cos() component so that this cyclical feature is represented as (𝑥, 𝑦) coordinates of a The information for the probability distribution of the target circle. variable directly influences the predictive model selection. By The normalisation of the attributes' values was applied to scale looking at Figure 2, it can be assumed that that the target variable the attributes in a way that their mean value is zero, and their is following the Poisson distribution. We also plotted the variance is retained with the use of their own standard deviation. distributions of the features. Figure 3 illustrates a grid of It allows equality of opportunity for each attribute. By this, no distributions of each feature of the dataset. attribute gives more value to itself regarding the range of values it has. Several normalisation techniques are commonly used, but the most popular one is the standard scaler, defined as: 𝑧 = !"# (2.1) $ where 𝑥 is the actual value, 𝜇 is the mean, and 𝑠 is the standard deviation. 8 Estimating client’s job-search process duration Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia All the calculations and transformations were performed in where 𝑃(𝑘) is the probability of seeing 𝑘 events during time unit Python programming language, by making use of modules like given event rate 𝜆 . Let X, y be our dataset for the Poisson pandas, NumPy and sci-kit learn. regression task. The log-likelihood function that needs to be maximised is: 3 METHODOLOGY ∑0 𝑙𝑜𝑔 %1) 9𝑃 0 <*!"$%&'2,(3&)4(&= (3.4) Since the target variable is numerical, the task should be treated !(𝑦): = ∑ 𝑙𝑜𝑔 %1) 5&! as a regression problem. Regression analysis describes methods whose goal is to estimate the relationship between a dependent After the expression is simplified, the final equation for the (target) variable and one or more independent variables. In Poisson loss has the following form: formal terms, the goal is to specify the following general model 𝐿 0 67%$$78 = ∑ ?𝜆(𝑋 %1) %) − 𝑦%𝑙𝑜𝑔 9𝜆(𝑋%):A (3.5) 𝑌% = 𝑓(𝑋%, 𝛽) + 𝑒% (3.1) CatBoost Regressor is optimised with regard to this objective where 𝑖 denotes the 𝑖&' observed input-output data set, the vector function. 𝑋 represents the input (independent) variables, 𝛽 is the set of model parameters, 𝑓(∙) is the function, and 𝑒% is the modelling error. The goal is to find the proper function 𝑓 and its parameters 4 EVALIUATION 𝛽 so the error term is as close to zero as possible. The model performance on the test set is evaluated with Root In its simplest form, the function 𝑓(∙) can represent a linear Mean Squared Error (RMSE) as a metric. RMSE is frequently model. For example, the univariate linear model of (3.1) would used in regression problems, and it is a measure of the difference be: between the values predicted by a model or an estimator and the 𝑌% = 𝛽( + 𝛽)𝑋% + 𝑒% (3.2) actual values of the instances. RMSE is given with the following expression: Generally, the function 𝑓 can describe much more complex * dynamics. The multivariate linear regression model is used as a 𝑅𝑀𝑆𝐸 = F∑ (5 &+, &"6:&)) (3.6) 0 base model and will be used to help with the assessment of the performance of other more specific and complex models simply where 𝑦% is the original value of the instance, and 𝑝𝑣% is the by comparing them to the base model. The aim is to develop such predicted value by the model. The hyper-parameters of the models that will significantly outperform the base model. In models were tuned using RandomizedSearchCV. This method order to construct a model that generalises well to the data, a optimises the hyper-parameters by cross-validated search over decision tree is used as a base learning algorithm for the given parameter settings. A fixed number of parameter settings ensembles. was sampled from the specified distributions. 3.1 Ensemble learning 65,28 70 60 The idea of ensemble learning is based on the theoretical 51,66 50 44,13 foundations that the generalization ability of an ensemble is usually much stronger than the one of a single learner. Ensemble 40 learning is mainly implemented as two subprocedures: training 30 weak component learners and selectively combine the member 20 learners into a stronger learner [7]. Two ensemble models based 10 on different techniques were developed, Random Forest 0 ean Squared Error (days) Regressor [8] and boosting algorithm - CatBoost Regressor. Linear Random Forest CatBoost Bagging is used to reduce the variance of a decision tree Regression (Poisson oth M classifier. The objective is to create several subsets of data from objective) Ro the training sample chosen randomly with replacement. Each Model collection of subset data is used to train their corresponding decision trees. The result is the average of all the predictions from different trees, which is more robust than a single decision Figure 4: Comparison of the model performance tree classifier. Based on the shape of the probability distribution given in Figure 4 shows the diagram for comparison of the models' Figure 2, we assume that the target variable comes from Poisson performances. The results show that both Random Forest and distribution. Therefore, we design our model to maximise the CatBoost significantly outperform the base linear regression log-likelihood for Poisson distribution [9]. The probability mass model. Also, optimising the mean Poisson deviance as a loss function of the Poisson distribution is given with the following function results in significant improvement in the performance expression: of the boosting model. The final score that the CatBoost Regressor optimised with regards to mean Poisson deviance 𝑃(𝑘) = *!"(,)# (3.3) evaluated on RMSE is 44.13 days. .! 9 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia V. Andonovic et al. 5 CONCLUSION Achieving desirable results using machine learning models requires a significant amount of quality data and a deep understanding of the problem. Feature engineering is one of the key concepts here, which, if it is appropriately done, enables the generation of new features that give helpful, previously unknown insights about the data. The paper proposes an approach that emphasises the engineering of optimisation function concerning the probability distribution of the target variable, which results in developing a specific model for approaching the problem. Including the Poisson objective function in the boosting model resulted in significant improvement in its performance. There is still space for improvement in the results. Using modern end-to- end deep learning architectures have the potential to provide better results than the proposed models, which leaves space for future work on this topic. Having a tool that can roughly estimate the time a new client stays in the job-search process by having the standard data formation about himself is beneficial for the PES. The creation of decision-making tools for organisations dealing with employment services supports the process of reducing unemployment in the countries, which is a massive benefit for the global economy. ACKNOWLEDGMENTS First author acknowledges Ad Futura, Public Scholarship, Development, Disability and Maintenance Fund of the Republic of Slovenia. The second author acknowledges funding from the Slovenian Research Agency via program Complex Networks P1- 0383. The last two authors acknowledge the funding received from the European Union’s Horizon 2020 research and innovation programme project HECAT under grant agreement No. 870702. REFERENCES [1] P. Boshkoski and B. Mileva - Boshkoska, "Report on commonly used algorithms and their performance," Horizon 2020, Deliverable number: D3.1., 2020. [2] J. Grundy, "Statistical profiling of the unemployed," Studies in Political Economy, 2015. [3] T. Riipinen, "Risk profiling of long-term unemployment in finland," Dialogue Con- ference Brussels., 2011. [4] P. J. O'Connel, E. Kelly and J. Walsh, "National profiling of the unemployed in Ireland," ESRI Research Series, vol. 10, 2009. [5] "HECAT - Disruptive Technologies Supporting Labour Market Decision Making," 2020. [Online]. Available: http://hecat.eu. [6] F. Johannes, D. Gamberger and N. Lavrac, "Machine Learning and Data Mining," Cognitive Technologies, 2012. [7] M. Brammer, Principles of Data Mining, 2007. [8] F. Huang, G. Xie and R. Xiao, "Research on Ensemble Learning," International Conference on Artificial Intelligence and Computational Intelligence, 2009. [9] A. Saha, S. Basu and A. Datta, "Random Forest for Dependent Data," arXiv, 2020. [10] A. Zakariya Y, "Diagnostic in Poisson Regression Models," Electronic Journal of Applied Statistical Analysis, 2012. 10 Some Experimental Results in Evolutionary Multitasking Andrejaana Andova Bogdan Filipič Jožef Stefan Institute and Jožef Stefan Institute and Jožef Stefan International Postgraduate School Jožef Stefan International Postgraduate School Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia andrejaana.andova@ijs.si bogdan.filipic@ijs.si ABSTRACT that change with generations and to which techniques resem- Transfer learning and multitask learning have shown that, in bling natural selection and genetic variation are applied. These machine learning, common information in two problems can techniques ensure that the fittest individuals (solutions) from be used to build more effective models. Inspired by this finding, the population are passed to the next generation. The algorithm attempts in evolutionary computation have also been made to begins by initializing a population of solutions. Then, a selection solve multiple optimization problems simultaneously. This new operator is used to select the fittest individuals as parents. After approach is called evolutionary multitasking (EMT). that, a reproduction operator is utilized to create offspring from In this work, we show how EMT extends ordinary evolution- the parents. The next step is to select a subset of individuals from ary algorithms and present the results that we obtained in solving the combined set of parents and children and replace the old pop- multiple optimization problems simultaneously. We also compare ulation with the selected subset. The new population is then used them with the results of algorithms that solve one optimization for the next generation. The cycle of selection, reproduction, and problem at a time. Finally, we provide visualizations and expla- replacement is repeated until a stopping criterion is satisfied. The nations of why and when EMT is beneficial. stopping criterion can be defined in various ways, for example, by the maximum number of generations. KEYWORDS Until recently, most EAs focused on solving only one optimiza- evolutionary algorithms, numerical optimization, multifactorial tion problem at a time. To exploit the parallelism of population- optimization, evolutionary multitasking based search, Gupta et al. introduced a new category of optimiza- tion approach called multifactorial optimization or evolutionary multitasking (EMT) [8]. The goal of EMT is to develop EAs that 1 INTRODUCTION are able to simultaneously solve multiple optimization problems In optimization the task is to find one or more solutions that without sacrificing the quality of the obtained solutions and the best solve a given problem. To determine which of the possible algorithm efficiency. solutions gives the best result, we use the objective function. A practical motivation for the development of EMT algorithms This can be the cost of fabrication, the efficiency of a process, the is the rapidly growing cloud computing. In cloud computing, mul- quality of a product, etc. The mathematical formulation of such tiple users can simultaneously send optimization problems to the problems is given as follows: server. These problems may either have similar characteristics or they may belong to completely different domains. Previously, Minimize/Maximize 𝑓 (𝑥 ) the servers solved these problems sequentially, but with the in- subject to 𝑔 (𝑥 ) ≥ 0, 𝑗 = 1, 2, .., 𝐽 ; troduction of EMT, they can solve the problems in parallel. 𝑗 ℎ (𝑥 ) = 0, 𝑘 = 1, 2, .., 𝐾 ; After the introduction of EMT by Gupta et al., many other 𝑘 (𝐿) (𝑈 ) works followed that also introduced methodologies specialized 𝑥 ≤ 𝑥 ≤ 𝑥 , 𝑖 = 1, 2, .., 𝑛. 𝑖 𝑖 𝑖 (1) in solving multiple optimization problems simultaneously [1, 4, Here, a solution 𝑥 = [𝑥1, 𝑥2, .., 𝑥 ]T is a vector of 𝑛 decision 5, 6, 9, 10]. 𝑛 variables. The objective 𝑓 (𝑥) can be either maximized or mini- In this paper, we present our experimental results in solving mized, but since many optimization algorithms are designed to multiple optimization problems simultaneously and discuss the solve minimization problems, we usually convert maximization results from the point of view of EMT performance. We do this objectives to minimization ones by multiplying the objective by applying the EMT methodology as proposed by Gupta et al. functions by −1. ℎ (𝑥) are equality constraints, 𝑔 (𝑥) inequality to test optimization problems and analyzing the results. 𝑘 𝑗 constraints, and (𝐿) (𝑈 ) The paper is further organized as follows. In Section 2, we in- 𝑥 and 𝑥 are boundary constraints [3]. In 𝑖 𝑖 this paper, we consider problems that include only boundary troduce the basic concepts of EMT. In Section 3, we first present constraints. our results in EMT with visualizations that explain why and When the optimization problem can not be solved using math- when EMT performs well, and then report the results in evolu- ematical methods, the usual alternative is to use randomized tionary many-task optimization. Finally, in Section 4, we give a optimization algorithms such as evolutionary algorithms (EAs). conclusion and present the ideas for future work. These algorithms are characterized by a population of solutions Permission to make digital or hard copies of part or all of this work for personal 2 EVOLUTIONARY MULTITASKING 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 Evolutionary multitasking is characterized by the simultaneous the full citation on the first page. Copyrights for third-party components of this existence of multiple decision spaces corresponding to different work must be honored. For all other uses, contact the owner/author(s). problems, which may or may not be independent, each with a Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). unique decision space landscape. In order for EMT to have cross- domain optimization properties, Gupta et al. proposed to use a 11 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Andrejaana Andova and Bogdan Filipič uniform genetic code in which each decision variable is encoded performance. In particular, it is important to develop a measure with a random number from [0, 1]. Decoding such a represen- of the inter-task complementarity used during the process of tation in continuous problems is done by using the following multitasking. To this end, a synergy metric that captures and equation for each decision variable: quantifies how similar two problems are has been proposed [7]. ( The main idea behind the synergy metric is to use the dot product 𝐿) (𝑈 ) (𝐿) 𝑢 = 𝑢 + (𝑢 − 𝑢 ) · 𝑣 , (2) 𝑖 𝑖 𝑖 𝑖 𝑖 between the gradient of a given solution in one problem, and the where 𝑢 is the decision variable in the original space, and 𝑣 is vector pointing to the global optimum of another problem. If the 𝑖 𝑖 the decision variable in the encoded space. The dimensionality of dot product of a given solution is larger than 0, the solution of the the solution vector is equal to max {𝐷 }, where 𝐷 represents first problem is pushing the candidate solution in the direction of 𝑗 𝑗 𝑗 the dimensionality of a single optimization problem. This type the global optimum of the second problem. If the dot product is of encoding allows problems to share decision variables at the smaller than 0, the solution is pushed in the opposite direction. beginning of the genetic code, which contributes to the transfer of useful genetic material from one problem to another. 3 EXPERIMENTS AND RESULTS Since EMT attempts to solve multiple problems simultaneously EMT is a novel concept in evolutionary optimization, and thus, using a single population, it is necessary to formulate a new a limited number of experiments were carried out so far. We technique for comparing population members. To this end, a set present some experiments performed and results obtained using of additional properties is defined for each individual 𝑥 in the 𝑖 EMT in both multi- and many-task optimization. population as follows. • Skill factor: The skill factor 𝜏 of 𝑥 is the one problem, 3.1 Multitask Optimization 𝑖 𝑖 among all problems in EMT, for which the individual is In the multitask optimization experiments, we took two fre- specialized. This skill factor can be assigned in a complex quently used optimization problems, i.e., 50-dimensional (50D) way by selecting the best individuals for each task or by Sphere and Ackley. We solved them using EMT and a genetic randomly assigning each individual one task for which it algorithm (GA). To be able to compare the results, we used the is specialized. In our case, we will use the later, simpler same population size and the same number of function evalua- method for assigning the skill factor. tions per problem. The 𝑟𝑚𝑝 parameter in EMT was set to 0.3, and • Scalar fitness: The scalar fitness is the fitness of an indi- for GA we used the default parameter values as defined in pymoo vidual for the problem it is specialized. [2]. We monitored the difference between EMT and GA over To compare two solutions, we use the scalar fitness and the skill time. If the difference is positive, EMT performs better than GA, factor. The scalar fitness shows how good a solution is for a while if it is negative, GA performs better than EMT. Because the given problem, and the skill factor shows for which problem the fitness values vary between different problems, we normalized solution performs best. A solution 𝑥 is better than 𝑥 if and the difference between EMT and GA in each problem by dividing 𝑎 𝑏 only if both have the same skill factor and 𝑥 has a higher scalar the values with the highest absolute difference. 𝑎 fitness than 𝑥 . If the solutions have different skill factors, they In the first experiment, the optima of the two problems were 𝑏 are incomparable. placed at the opposite ends of the search space. Because of this, the problems have very little common information, and the syn- 2.1 Assortative Mating ergy function mostly takes negative values. This is visualized for To produce offspring, the authors of EMT [8] used assortative a 2D Sphere function in Figure 1 and for a 2D Ackley function mating as a reproduction mechanism. In assortative mating, two in Figure 2. The normalized difference between EMT and GA randomly selected parents can undergo crossover if they have in optimizing 50D Sphere and Ackley functions is presented in the same skill factor. If, on the other hand, their skill factors differ, Figure 3. From the results, we can see that GA performs better crossover occurs only with a given random mating probability on these problems. 𝑟 𝑚𝑝 , otherwise, mutation takes place. A value of 𝑟𝑚𝑝 close to 0 means that only culturally identical individuals are allowed to perform crossover, while a value close to 1 allows completely random mating. 2.2 Selective Imitation Evaluating each individual for each problem is computationally expensive. For this reason, each child is evaluated only on one problem, which is the skill factor that one of its parents has. In this way, the total number of function evaluations is reduced, while the solution is still evaluated on the problem on which it most likely performs well. The procedure is called selective imitation. Figure 1: Synergy metric on the Sphere function solved to- gether with the Ackley function when the optima are far 2.3 Landscape Analysis away. In multitask machine learning, it is well known that useful infor- mation cannot always be found for two problems. Therefore, to In Figure 4, we present the results from the second experiment enable further success in the field of evolutionary multitasking, where the optima of 50D Sphere and Ackley functions were it is important to develop a meaningful theoretical explanation placed closer together. Here, we can see that the optimization of when and why implicit genetic transfer can lead to improved of the Sphere function does not show significant improvement 12 Some Experimental Results in Evolutionary Multitasking Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 2: Synergy metric on the Ackley function solved together with the Sphere function when the optima are Figure 4: Normalized difference between multitask and far away. single-task optimization on 50D Sphere and Ackley func- tions when the optima are close. Figure 3: Normalized difference between multitask and Figure 5: Synergy metric on the Sphere function solved single-task optimization on 50D Sphere and Ackley func- together with the Ackley function when the optima are tions when the optima are far away. close. when being performed together with the optimization of the Ackley function, but on the Ackley function EMT converges to the optimal solution much faster. An explanation for this is illustrated in 2D in Figures 5 and 6. Here we can see that the synergy in the Sphere space is mostly equal to 0, except for some small parts where it rises to +10 and falls to −10. Because both the positive and the negative parts of the synergy values of the Sphere problem are small, we can notice no difference in convergence on the Sphere problem. In contrast, more than half of the space of the Ackley function has a positive synergy metric, indicating that this part of the space appoints the solutions in the right direction toward the global optimum. On the other hand, most of the decision space Figure 6: Synergy metric on the Ackley function solved of the Ackley function has constant fitness values, which compli- together with the Sphere function when the optima are cates the GA search for the global optimum. For this reason, the close. information transferred from the Sphere problem to the Ackley problem is useful, and thus we can see faster convergence when solving the two problems together using EMT. number of problems we are trying to solve does not cause diffi- culties to EMT. If the problems are similar, we can solve many 3.2 Many-Task Optimization problems simultaneously without losing efficiency. When solving more than three tasks simultaneously, we are deal- Figure 8 shows the results obtained when solving six well- ing with a many-task optimization. In Figure 7, we present the known optimization problems at the same time: Ackley, Sphere, results obtained by randomly shifting (within a small, 10% range Rastrigin, Rosenbrock, Schwefel, and Griewank, all 50D. From the of the total space) the global optimum of both the Ackley and results, we can notice that although the optimization procedure the Sphere function 25 times, resulting in 50 different 50D opti- converges faster for most of the functions, for the Sphere and mization problems. During the optimization process, we used the the Schwefel function the convergence speed of the optimization same algorithm parameter values for EMT and GA as reported process drops. The same pattern can be noticed in Figure 9 where in Section 3.1. In the results, we can notice similar patterns as the optimum of each function is shifted 8 times, resulting in when solving just two problems. This proves that increasing the 6 ∗ 8 = 48 problems altogether. 13 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Andrejaana Andova and Bogdan Filipič However, if the problems are too different, the performance of the optimization drops. To explain why EMT works well on some problem pairs and why on some others it does not, we provided visualizations of the synergy metric. We so far tested EMT on simple benchmark functions that are usually used for single-objective optimization. However, in future work, we plan to test it also on real-world scenarios with more complex functions and constraints. Furthermore, so far we have used the synergy metric to explain why some problems are solved Unfortunately, with this metric we can not strictly determine when solving two problems will be successful. Thus, one possible future direction is to develop machine learning methods that predict when multitasking a set of problems would be successful. Figure 7: Normalized difference between multitask and This may be useful for cloud systems that could form several single-task optimization on 50 problems originating from groups of similar problems and then solve them in a multitask 50D Sphere and Ackley functions whose optima are manner. shifted close to each other. 5 ACKNOWLEDGMENTS We acknowledge financial support from the Slovenian Research Agency (young researcher program and research core funding no. P2-0209). REFERENCES [1] Kavitesh Kumar Bali, Abhishek Gupta, Liang Feng, Yew Soon Ong, and Tan Puay Siew. 2017. Linearized domain adaptation in evolutionary multitasking. In 2017 IEEE Con- gress on Evolutionary Computation (CEC). IEEE, 1295–1302. [2] Julian Blank and Kalyanmoy Deb. 2020. Pymoo: Multi- objective optimization in Python. IEEE Access, 8, 89497– 89509. Figure 8: Normalized difference between multitask and [3] Kalyanmoy Deb. 2001. Multi-Objective Optimization using single-task optimization on six well-known 50D optimiza- Evolutionary Algorithms. John Wiley & Sons, Chichester. tion problems when the optima are shifted close to each [4] Liang Feng, Lei Zhou, Jinghui Zhong, Abhishek Gupta, other. Yew-Soon Ong, Kay-Chen Tan, and Alex Kai Qin. 2018. Evolutionary multitasking via explicit autoencoding. IEEE Transactions on Cybernetics, 49, 9, 3457–3470. [5] Maoguo Gong, Zedong Tang, Hao Li, and Jun Zhang. 2019. Evolutionary multitasking with dynamic resource allocat- ing strategy. IEEE Transactions on Evolutionary Computa- tion, 23, 5, 858–869. [6] Abhishek Gupta, Jacek Mańdziuk, and Yew-Soon Ong. 2015. Evolutionary multitasking in bi-level optimization. Complex & Intelligent Systems, 1, 1-4, 83–95. [7] Abhishek Gupta, Yew-Soon Ong, Bingshui Da, Liang Feng, and Stephanus Daniel Handoko. 2016. Landscape synergy in evolutionary multitasking. In 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 3076–3083. [8] Abhishek Gupta, Yew-Soon Ong, and Liang Feng. 2015. Figure 9: Normalized difference between multitask and Multifactorial evolution: Toward evolutionary multitask- single-task optimization on 48 problems originating from ing. IEEE Transactions on Evolutionary Computation, 20, 3, six well-known 50D optimization problems whose optima 343–357. are shifted close to each other. [9] Abhishek Gupta, Yew-Soon Ong, Liang Feng, and Kay Chen Tan. 2016. Multiobjective multifactorial optimiza- 4 CONCLUSION AND FUTURE WORK tion in evolutionary multitasking. IEEE Transactions on Cybernetics, 47, 7, 1652–1665. We presented our experimental results on solving multiple opti- [10] Yu-Wei Wen and Chuan-Kang Ting. 2017. Parting ways mization problems simultaneously using a novel method called and reallocating resources in evolutionary multitasking. evolutionary multitasking. We were solving just two optimiza- In 2017 IEEE Congress on Evolutionary Computation (CEC). tion problems, but also as many as 50 optimization problems IEEE, 2404–2411. at the same time. From the experimental results, we can con- clude that there are some groups of problems for which EMT can improve the speed of convergence of the optimization process. 14 Intent Recognition and Drinking Detection For Assisting Kitchen-based Activities Carlo M. De Masi Simon Stankoski carlo.maria.demasi@ijs.si simon.stankoski@ijs.si Department of Intelligent Systems Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Vincent Cergolj Mitja Luštrek vc2756@student.uni- lj.si mitja.lustrek@ijs.si Univerza v Ljubljani, Fakulteta za elektrotehniko Department of Intelligent Systems Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT This paper is organized as follows. Section 2 discusses the related work. Section 3 presents the system architectures. Section We combine different computer-vision (pose estimation, object 4 describes the recognition modules of the system. Section 5 detection, image classification) and wearable based activity recog- shows the results of the recognition modules. Finally, Section 6 nition methods to analyze the user’s behaviour, and produce a concludes the paper. series of context-based detections (detect locations, recognize activities) in order to provide real-time assistance to people with mild cognitive impairment (MCI) in the accomplishment of every 2 RELATED WORK day, kitchen-related activities. 2.1 Drinking Detection From Wearables KEYWORDS Recent advances in the accuracy and accessibility of wearable sensing technology (e.g., commercial inertial sensors, fitness computer vision, activity recognition, object detection, pose esti- bands, and smartwatches) has allowed researchers and practi- mation tioners to utilize different types of wearable sensors to assess fluid intake in both laboratory and free-living conditions. 1 INTRODUCTION The necessity for fluid intake monitoring emerges as a result of people’s lack of awareness of their hydration levels. Dehydration Smart home technologies have been extensively adopted for mea- can lead to many severe health problems like organ and cognitive suring and decreasing the impact of Mild Cognitive Impairment impairments. Therefore, a system that can continuously track (MCI) on everyday life [9]. In the scope of the CoachMyLife (CML) the fluid intake and provide feedback to the user if useful. project we have been developing a system employing different In [1], the authors explored the possibility of recognizing drink- machine learning techniques with the aim of assisting persons ing moments from wrist-mounted inertial sensors. They used affected by MCI in performing activities in their apartments, with adaptive segmentation to overcome the problem with variable a particular focus on tasks related to the kitchen. length of the drinking gestures. They used random forest algo- In a previous work, we presented one of the first components rithm, trained with 45 features, and obtained an average precision of this system, i.e. a computer vision pipeline which allows to of 90.3% and an average recall of 91.0%. In [5], the authors em- detect the activity of drinking, by analyzing the video collected ployed a two-step detection procedure, enabling them to detect by an RGB camera through a 3D Convolutional Neural Network drinking moments and estimate the fluid intake. They extracted (3D-CNN) [12]. 28 statistical features, from which only six were selected using In the present paper, we present our work on extending said backward feature selection. Finally, they trained a Conditional pipeline, by discussing (i) a drinking-detection algorithm based Random Field model, resulting in a precision of 81.7% and re- on motion data from a wristband, which can be used to further call of 77.5%. In [4], the authors used a machine-learning based validate the one based on computer vision, and to replace it in model to detect hand-to-mouth gestures. Similarly as the previ- situations where the activity is not performed in front of the ous methods, they extracted 10 time-domain features and trained camera; (ii) a method based on pose detection to identify inter- a random forest classifier. They validated their method in a free- actions of the user with their environment, in order to perform living scenario and obtained precision of 84% and recall of 85%. intent recognition, and (iii) a possible new implementation of our Although remarkable results were achieved, the evaluation of the previous computer-vision pipeline for drinking detection that studies is limited and it is not showing the real-life performance. can be deployed on edge devices. Permission to make digital or hard copies of part or all of this work for personal 2.2 Activity Recognition From Videos or classroom use is granted without fee provided that copies are not made or In recent years, the problem of computer-based Human Activity 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 Recognition (HAR) of daily living has been tackled by different work must be honored. For all other uses, contact the owner /author(s). computer-vision methods. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia HAR can be performed directly on RGB images and videos by © 2021 Copyright held by the owner/author(s). analyzing: (i) the spatial features in each frame, thus obtaining 15 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Trovato and Tobin, et al. predictions for each frame that can then be extended to the whole 4 INTENT RECOGNITION video by pooling or by a recurrent-based neural networks [2], (ii) One of the main goals of the CML project is to provide users with the temporal features related to motions and variations between real-time, context-based notifications to assist them in perform- frames [6], or (iii) some combination of the two [10]. ing activities. The most recent approaches aimed at simultaneous evaluation This is achieved in two steps. First, by combining computer- of both spatial and temporal features involve the usage of 3D- vision and the wearable device, the system detects real-time CNN, i.e., convolutional models characterized by an additional events, such as the position of the user, their interaction with third temporal dimension [12]. the environment, the displacement of a mug the user is expected An alternative approach, not involving the direct analysis of to drink from, the opening/closing of cabinet and fridge door, the whole frames, consists in exploiting the information provided drinking and eating. by human pose estimation, so that body keypoints coordinates, Then, these events are passed to the intent recognition module, reconstructed in a 2D or 3D space, can be fed to deep-learning which uses them to predict which activity the user is performing, models to provide predictions [3]. and provide assistance if needed. We adopted a Single Shot MultiBox Detector (SSD) [8] model, 3 ADOPTED HARDWARE pre-trained on the 80 classes of the COCO dataset [7] for the 3.1 Wristband detection of the user, and fine-tuned on a custom dataset we collected to locate the position of the mug. Pose estimation, which The drinking-detection procedure is implemented on a wrist- is used to track the movement of the user’s hands and detect band which is equipped with a nRF52840 System On Chip (SoC) interactions with domestic appliances, is achieved by a SimpleNet module. The SoC offers a large amount of Flash and RAM, 1MB model with a ResNet backbone [13]. and 256 kB, respectively. Additionally, it has protocol support for Bluetooth Low Energy (BLE). The architecture of nRF52840 is based on 32-bit ARM® Cortex™-M4 CP U with floating point 4.1 Regions of Interest unit running at 64 MHz. The wristbands power supply source During the initial setup, the user is asked to identify some regions is a battery with a capacity of 500 mAh. The measurements of of interest (ROIs) in the camera image, which can be either single accelerations and angular velocities are performed by the system- or double-zoned. in-package LSM6DSL, manufactured by STM. It is equipped with In the first case, the ROI is "activated" when the user’s feet are a 3D digital accelerometer and a 3D digital gyroscope based on within the selected region (Fig. 1a), whereas double-zone ROIs MEMS technology that operates at 0.65 mA in high-performance are used to detect if the user is in the desired area and/or if their mode and allows low power consumption with constant opera- hands are in the selected upper area (Fig. 1b). tion. The most prominent feature of the Inertial Measurement Unit (IMU) is a 4 kB FIFO (First In First Out) buffer, which stores the data of the accelerometer and gyroscope. This allows for very 4.2 Intent Recognition low power operation, as the SoC wakes up only when triggered The events detected by the computer vision pipeline are passed by an "FIFO full" interrupt event. to the intent recognition module, which predicts the activity the user is currently engaged on. 3.2 Local Deployment of The Computer Currently, this prediction is based on a set of pre-determined Vision System rules. A number of possible activities is manually inserted, each The computer vision pipeline for drinking detection we previ- formed by different steps, corresponding to possible events that ously developed for the project worked by retrieving the video can be detected by the computer vision system (Fig. 2a). Different stream collected by an IP camera in the user’s apartment, and activities can share one or more steps, and as the system detects analyzing it on a remote server. This approach, however, pre- the completion of the various steps, the list of possible ongoing sented issues related to the remote access to the camera, which activities gets reduced (Fig. 2b, 2c), until only one activity is can sometimes be blocked by the router’s firewall functionalities, identified and followed until its completion (Fig. 2d). and raised safety and privacy concerns with the users. If too long of a time interval passes between the completion For these reasons, we have been working on deploying the of two steps, the activity is classified as "interrupted", and the CML system on a local device. After some unsuccessful attempts system can show a notification to the user, asking if they require to implement the system on Android devices by using frame- assistance. 1 2 works such as Apache TVM or Deep Java Library (DJL) , we 3 opted for deployment on a Jetson NANO device . 4.3 Drinking Detection From Computer Direct deployment of our system on the device was possible, Vision on the Jetson NANO although not immediate, but the resulting performance was sub- optimal in terms of the FPS reached by the various detection The model we previously adopted to perform activity recognition algorithms (≈2 FPS for the object detection). To overcome this, from videos is particularly computationally expensive and so, we optimized said algorithms by TensorRT, a library built on although it proved to be very effective in the detection of drinking NVIDIA’s CUDA library for parallel programming, thus improv- events, it was not possible to implement it on the Jetson NANO. ing inference performance for deep learning models (≈22 FPS for For this reason, we are currently collecting a dataset of short the object detection). video clips, passing them through a pose estimation model, in order to obtain the 2D position of 18 body parts across a time 1 https://tvm.apache.org/ series of frames, with an associated class label for the frame series. 2 https://djl.ai/ 3 Then, this will be analyzed through an LSTM-based model to https://www.nvidia.com/en-us/autonomous-machines/embedded- systems/jetson-nano/ perform HAR. 16 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia (a) (b) Figure 1: Triggers based on user’s location and their interaction with the environment. Interact: cabinet Interact: cabinet Interact: table Interact: cabinet Interact: cabinet Interact: table Next to: sink Next to: fridge Interact: counter Next to: sink Next to: fridge Interact: counter Interact: stoves Interact: coffee machine Interact: table Interact: stoves Interact: coffee machine Interact: table BOIL MAKE EAT BOIL MAKE EAT WATER COFFEE SOMETHING WATER COFFEE SOMETHING (a) (b) Interact: cabinet Interact: cabinet Interact: table Interact: cabinet Interact: cabinet Interact: table Next to: sink Next to: fridge Interact: counter Next to: sink Next to: fridge Interact: counter Interact: stoves Interact: coffee machine Interact: table Interact: stoves Interact: coffee machine Interact: table BOIL MAKE EAT BOIL MAKE EAT WATER COFFEE SOMETHING WATER COFFEE SOMETHING (c) (d) Figure 2: As the computer vision system detects the completion of various steps, the list of possible ongoing activities gets reduced, until one of them is completed or interrupted. 4.4 Drinking Detection Using a Wearable wait for the next AWT event. Otherwise, if at least one prediction device is positive, the machine-learning procedure continues to work for another three new batches of data. Due to the desired minimum power consumption, the drinking The machine-learning method for detection of drinking ges- detection was implemented directly on the wristband. This is tures is based on time- and frequency-domain features. The raw preferable as it eliminates the need to transfer all the raw sensor data is segmented into 5-second windows and 216 features are data to a smartphone or some sort of central device. Raw sen- extracted in total. We used a relatively simple approach due to sor data transmission is clearly undesirable due to high power the memory limitation of the wristband. The deployed model consumption and it is not possible if the central device is not was trained using the drinking dataset described in Section 4.4.1 nearby. and additional non-drinking data collected in real-life scenario The first step of drinking detection using the wristband is [11]. to enable the IMU in activity/inactivity recognition mode. This allows the IMU to be in a low power state for the most part of 4.4.1 Drinking Dataset. For the aim of this study, we recruited the day. 19 subjects (11 males and 8 females). Each subject was equipped When activity is recognized the IMU enables absolute wrist with the wristband described in Section 3.1. We developed a detection (AWT) which checks if the angle between the horizontal custom application that ran on the wristband and collected three- plane and the Y axis of the IMU is larger than 30 degrees. If the axis accelerometer and three-axis gyroscope data at a sampling condition is met the IMU is enabled in batching mode, storing 4 frequency of 50 Hz. The dataset is publicly available and we accelerometer and gyroscope data in the FIFO buffer. Every time hope that it will serve researchers in future studies. the FIFO buffer is full, data is transferred to the SoC, where we We developed a general procedure for the participants to fol- directly start the machine learning pipeline. This procedure is low during the data collection process. The ground truth was repeated for three batches of IMU readings. If all three predictions registered manually by participants pressing a button on the from the machine learning model are non drinking, we disable wristband before performing the gesture and after finishing the the gyroscope, we stop the machine learning procedure and we 4 https://github.com/simon2706/DrinkingDetectionIJS 17 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Trovato and Tobin, et al. gesture. The data collection procedure included drinking from REFERENCES six different container types—namely, bottle, coffee cup, coffee [1] Keum San Chun, Ashley B Sanders, Rebecca Adaimi, Necole mug, glass, shot glass and wine glass. Streeper, David E Conroy, and Edison Thomaz. 2019. To- For each participant we collected 36 drinking episodes (3 fluid wards a generalizable method for detecting fluid intake level x 6 containers x 2 positions). The idea of the different fluid with wrist-mounted sensors and adaptive segmentation. level was to obtain drinking episodes with a short, medium and In Proceedings of the 24th International Conference on Intel- long duration. We also considered different body positions. The ligent User Interfaces, 80–85. participants first performed the drinking gestures while being [2] Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadar- seated and afterwards they repeated the same gestures while rama, et al. 2015. Long-term recurrent convolutional net- standing. works for visual recognition and description. In Proceed- ings of the IEEE conference on computer vision and pattern 5 RESULTS AND DISCUSSION recognition, 2625–2634. 5.1 Intent Recognition and Local [3] Giovanni Ercolano and Silvia Rossi. 2021. Combining cnn Implementation of Drinking Detection and lstm for activity of daily living recognition with a 3d matrix skeleton representation. Intelligent Service Robotics, A pilot phase will begin shortly, during which the intent recogni- 14, 2, 175–185. tion module will be evaluated. [4] Diana Gomes and Inês Sousa. 2019. Real-time drink trigger Regarding the new model for drinking detection, a prelimi- detection in free-living conditions using inertial sensors. nary test of our new approach, ran on a subset of the Berkeley Sensors, 19, 9, 2145. 5 Multimodal Human Action Database (MHAD) dataset , reached [5] Takashi Hamatani, Moustafa Elhamshary, Akira Uchiyama, an accuracy of over 90%, and we’ll extend the analysis to our case and Teruo Higashino. 2018. Fluidmeter: gauging the hu- once the dataset collection will be over. man daily fluid intake using smartwatches. Proceedings of 5.2 Wearable Sensing Results the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2, 3, 1–25. For evaluation, the leave-one-subject-out (LOSO) cross-validation [6] Ammar Ladjailia, Imed Bouchrika, Hayet Farida Merouani, technique was used. In other words, the models were trained on Nouzha Harrati, and Zohra Mahfouf. 2020. Human activ- the whole dataset except for one subject on which we later tested ity recognition via optical flow. Neural Computing and the performance. Applications, 32, 21, 16387–16400. For the drinking detection model, we considered several clas- [7] Tsung-Yi Lin, Michael Maire, Serge Belongie, et al. 2014. sifiers including logistic regression (LR), linear discriminant anal- Microsoft coco: common objects in context. (2014). arXiv: ysis (LDA), k-nearest neighbors (KNN), naive Bayes (NB) and 1405.0312 [cs.CV]. XGBoost. [8] Wei Liu, Dragomir Anguelov, Dumitru Erhan, et al. 2016. The obtained results are shown in Table 1. It can be clearly Ssd: single shot multibox detector. Lecture Notes in Com- seen that XGBoost outperforms all other classifiers. However, due puter Science, 21–37. issn: 1611-3349. doi: 10.1007/978- to the technical limitations described in Section 3.1 the trained 3- 319- 46448- 0_2. http://dx.doi.org/10.1007/978- 3- 319- model is unable to fit below 100 KB. The size of the LR model 46448- 0_2. is only 2 KB, which is optimal for our device. Furthermore, the [9] Maxime Lussier, Stéphane Adam, Belkacem Chikhaoui, results obtained with LR are only 0.03 lower compared to those Charles Consel, Mathieu Gagnon, Brigitte Gilbert, Sylvain from XGBoost. Therefore, we deployed the model trained with Giroux, Manon Guay, Carol Hudon, Hélène Imbeault, et al. the LR classifier. 2019. Smart home technology: a new approach for per- formance measurements of activities of daily living and 6 CONCLUSIONS prediction of mild cognitive impairment in older adults. We presented our work on drinking detection using wearables Journal of Alzheimer’s Disease, 68, 1, 85–96. and intent recognition/drinking detection using computer vision. [10] Karen Simonyan and Andrew Zisserman. 2014. Two-stream A pilot phase, beginning in October 2021, will provide thor- convolutional networks for action recognition in videos. ough testing of the functionalities described in the paper. Nonethe- In Advances in neural information processing systems, 568– less, the results obtained from the internal testing for each module 576. of the system show promising results for both drinking (with [11] Simon Stankoski, Marko Jordan, Hristijan Gjoreski, and both wearables and computer vision) and intent recognition. Mitja Luštrek. 2021. Smartwatch-based eating detection: data selection for machine learning from imbalanced data 5 http://tele-immersion.citris-uc.org/berkeley_mhad with imperfect labels. Sensors, 21, 5. issn: 1424-8220. doi: 10.3390/s21051902. https://www.mdpi.com/1424- 8220/21/ Table 1: Comparison of different classifiers for detection 5/1902. of drinking activity. [12] Gül Varol, Ivan Laptev, and Cordelia Schmid. 2017. Long- term temporal convolutions for action recognition. IEEE Method Precision Recall F1 score transactions on pattern analysis and machine intelligence, Logistic regression 0.87 0.77 0.81 40, 6, 1510–1517. Linear discriminant analysis 0.54 0.69 0.55 [13] Bin Xiao, Haiping Wu, and Yichen Wei. 2018. Simple base- K-nearest neighbors 0.84 0.69 0.75 lines for human pose estimation and tracking. In Proceed- Naive Bayes 0.68 0.85 0.74 ings of the European conference on computer vision (ECCV), XGBoost 0.89 0.81 0.84 466–481. 18 Anomaly Detection in Magnetic Resonance-based Electrical Properties Tomography of in silico Brains Ožbej Golob Alessandro Arduino Oriano Bottauscio University of Ljubljana Istituto Nazionale di Ricerca Istituto Nazionale di Ricerca Faculty of Computer and Metrologica Metrologica Information Science Torino, Italy Torino, Italy Ljubljana, Slovenia a.arduino@inrim.it o.bottauscio@inrim.it ozbej.golob@gmail.com Luca Zilberti Aleksander Sadikov Istituto Nazionale di Ricerca University of Ljubljana Metrologica Faculty of Computer and Torino, Italy Information Science l.zilberti@inrim.it Ljubljana, Slovenia aleksander.sadikov@fri.uni- lj.si ABSTRACT fields can easily penetrate into most biological tissues, making EPT suitable for imaging of the whole body. The MRI scans for Magnetic resonance-based electrical properties tomography (EPT) EPT are performed using a standard MRI scanner, and its spa- is one of the novel quantitative magnetic resonance imaging cial resolution is determined by MRI images and quality of used techniques being tested for use in clinical practice. This paper 𝐵 -mapping technique [9]. presents preliminary research and results of automated detection 1 The objective of this research was to develop and evaluate of anomalies from EPT images. We used in silico data based on algorithms to automatically detect anomalies of different sizes anatomical human brains in this experiments and developed two in the EPT images. The data consisted of in silico simulated algorithms for anomaly detection. The first algorithm employs a brain scans of phantoms that either contained an anomaly or standard approach with edge detection and segmentation while not. The evaluation was aimed towards answering whether an the second algorithm exploits the quantitative nature of EPT and anomaly can be detected or not, and how large an anomaly can works directly with the measured electrical properties (electrical be (reasonably) reliably detected. This represents an initial step conductivity and permittivity). The two algorithms were com- towards the potential clinical use of EPT. pared on – as of yet – noiseless data. The algorithm using the standard approach was able to quite reliably detect anomalies 2 METHODS roughly the size of a cube with a 14 mm edge while the EPT-based algorithm was able to detect anomalies roughly the size of a cube 2.1 Data Acquisition with a 12 mm long edge. The MRI acquisition of the EPT inputs has been simulated in a noiseless case. Thus, the result of the electromagnetic simulation KEYWORDS at RF has been directly converted in the acquired data, with no electrical properties tomography (EPT), magnetic resonance imag- further post-processing. Precisely, the 𝐵 field generated by a 1 ing (MRI), automatic anomaly detection, artificial intelligence current-driven 16-leg birdcage body-coil (radius 35, height 45) operated both in transmission and in reception with a polarisation 1 INTRODUCTION switch has been computed in presence of anatomical human heads with a homemade FEM–BEM code [2]. The simulations The frequency-dependent electrical properties (EPs), including have been conducted at 64 (i.e. the Larmor frequency of a 1.5 electrical conductivity and permittivity, of biological tissues pro- scanner). vide important diagnostic information, e.g. for tumour charac- The acquisitions of 19 human head models from the XCAT terisation [9]. EPs can potentially be used as biomarkers of the library [6] have been simulated. The considered population is healthiness of various tissues. Previous studies, not based on statistically representative of different genders and ages. For each magnetic resonance imaging (MRI), have shown that various head model, 10 different variants are considered: diseases cause changes of EPs in the tissue [3]. Electrical properties tomography (EPT) is used for quantita- (1) Two physiological variants with the original distribution tive reconstruction of EPs distribution at radiofrequency (RF) of the biological tissues. In one case, the nominal electrical with spatial resolution of a few millimetres. EPT requires no elec- conductivity provided by the IT’IS Foundation database [5] trode mounting and, during MRI scanning, no external energy is assigned to each tissue. In the other case, the electrical is introduced into the body other than the 𝐵 fields. Applied conductivity of white and grey matter is sampled from a 1 𝐵1 uniform distribution that admits a variation up to 10 with Permission to make digital or hard copies of part or all of this work for personal respect to the nominal value. This will be referred to as or classroom use is granted without fee provided that copies are not made or the physiological variability of the electrical conductivity. distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this (2) Eight pathological variants, in which a spherical patho- work must be honored. For all other uses, contact the owner /author(s). logical inclusion is inserted in the white matter tissue. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia The radius of the inclusion ranges from 5 to 45 and its © 2021 Copyright held by the owner/author(s). electrical conductivity is set equal to that of the white 19 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Golob et al. matter increased by a factor uniformly sampled from 10 to 50 of the nominal value, because previous experimental results have shown that pathological tissues have higher EP values than healthy tissue [7, 8]. The location of the inclusion within the head is selected with a random proce- dure and only its intersection with the white matter tissue is kept in the final model (see Fig. 1 panels a and d). All the pathological variants take into account the physiolog- ical variability in the determination of the white and grey matter electrical conductivity. 2.2 Reconstruction Techniques In order to retrieve the distribution of the electrical conductiv- ity, the phase-based implementations of Helmholtz-EPT (H-EPT) Figure 1: Median electrical conductivity distribution by re- and convection-reaction–EPT (CR-EPT) provided by the open- gions. (a) Segmented healthy MRI image. (b) Median elec- source library EPTlib [1] have been used. For each head model, trical conductivity distribution. (c) Detected regions (bor- the distribution of the transceive phase [3] (input of phase-based dered red). (d) Segmented pathological MRI image (anom- EPT) is obtained by linearly combining the phases of the rotat- aly is yellow). (e) Median electrical conductivity distribu- ing components of 𝐵 simulated both in transmission and in 1 tion. (f) Detected regions (bordered red). Please note that reception [1]. not all of the regions are visible as only a 2D slice is shown Since noiseless inputs are considered, the smallest filter has while the data is 3D. been used both in H-EPT and in CR-EPT. Moreover, CR-EPT has been applied for a volume tomography, with an electrical conductivity of 0.1 forced at the boundaries and an artificial −4 diffusion coefficient equal to 10 . biomarker of healthy brain. Mandija et al. [4] presented mean Currently, the proposed anomaly detection algorithms have electrical conductivity and standard deviation of white and grey been tested only on the H-EPT results. matter as a reliable measure of whether the brain contains patho- logical tissue. 2.3 Anomaly Detection In input data for our experiments, electrical conductivity is We developed two anomaly detection algorithms: (i) a more clas- distributed from 90% to 110% of nominal value for white mat- sical approach for anomaly detection in MR images and (ii) an ter, and from 110% to 150% for anomalies. However, it must be EPT-based approach working with direct quantitative properties noted that these are the values used for setting up the phantoms, estimated by the MRI-based EPT. and that these values are then only approximated when EPT re- construction is performed. These reconstructed properties have 2.3.1 Classical Approach. The classical approach uses standard been used as input for anomaly detection. The algorithm detects techniques used for anomaly detection in MR images. This ap- anomalies based on the difference between white matter and proach could be applied (also) on standard MR images as it is anomalies. The algorithm uses noiseless EPT images, produced independent of the MRI technique. The algorithm uses noiseless with H-EPT, as input data. EPT images, produced with Helmholtz reconstruction technique, The algorithm, as the classical one, receives as input previ- as input data. ously segmented white matter from the whole EPT image. It The algorithm receives previously segmented (this segmenta- then detects all voxels that have electrical conductivity between tion was not of interest in this research) white matter from the 110% and 150% of median electrical conductivity of white matter EPT image and detects the edges in it. The edges are detected and marks them as a potential anomaly. These voxels, marked using a simple gradient edge detection technique. The gradient as potentially being an anomaly, are then grouped into regions is calculated for each voxel based on the directional change of based by their location. The algorithm ignores all smaller regions electrical conductivity of neighbouring voxels. The edges are (below a set size threshold) that likely represent noise and recon- represented as borders between white matter and other brain struction errors. All the remaining regions are classified as the tissues as well as borders between white matter and anomalies. anomaly. Edge voxels are ignored in order to avoid H-EPT reconstruction errors, which occur at borders between tissues [4]. 3 RESULTS The algorithm then calculates median electrical conductivity Figure 2 shows the predictions of whether an image contains an of all regions as separated by the detected edges. Figure 1 shows anomaly or not for both algorithms – classical on the left (a) and median electrical conductivity distribution by regions in a sample EPT approach on the right (b). Each EPT image corresponds to image. one bar on the chart and they are arranged with the increasing The k-means algorithm is then employed for the classifica- size of the anomaly; the size of the bar represents the size of tion of regions into healthy and anomaly-containing ones. The the anomaly in voxels. The bars are cut off at 2,000 voxels for algorithm classifies an MR image based on median electrical con- easier viewing. Only images actually containing the anomaly are ductivity of each region. The anomaly location is associated with shown; for the others the false positives (FP) rate describes the the regions detected as containing the anomaly. performance of the two algorithms. The green colour represents 2.3.2 EPT Approach. EPT differs from standard MRI techniques correct predictions and the red colour the incorrect ones. The by representing EPs as quantitative values. EPs are a reliable yellow colour means that the algorithm correctly predicted the 20 Anomaly Detection in MR-based EPT of in silico Brains Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 1: Classification evaluation of the classical ap- Table 3: Classification evaluation of the EPT approach. proach. Measure Training data Test data Measure Training data Test data Precision 0.976 0.971 Precision 0.975 1.000 Recall 0.769 0.708 Recall 0.750 0.708 F1 score 0.860 0.819 F1 score 0.848 0.829 Accuracy 0.800 0.750 Accuracy 0.785 0.767 Table 4: Localisation evaluation of the EPT approach. Table 2: Localisation evaluation of the classical approach. Measure Training data Test data Measure Training data Test data IoU 0.381 ± 0.140 0.435 ± 0.125 IoU 0.197 ± 0.116 0.244 ± 0.110 Precision 0.874 ± 0.208 0.900 ± 0.177 Precision 0.932 ± 0.202 0.988 ± 0.050 Recall 0.396 ± 0.142 0.450 ± 0.126 Recall 0.204 ± 0.123 0.245 ± 0.110 F1 score 0.535 ± 0.166 0.594 ± 0.142 F1 score 0.313 ± 0.163 0.379 ± 0.143 Analogously, Table 3 shows the results of classification eval- uation of the EPT approach and Table 4 shows the results of presence of the anomaly, but for the wrong reasons (hence Inter- localisation evaluation of the EPT approach. Again, IoU and F1 section over Union (IoU) is zero) – these cannot be counted as score values are reduced as the result of ignoring anomaly edge correct performance. Some misclassifications are labeled with the voxels. most likely cause: either that the anomaly is scattered in several An example of anomaly localisation is shown in Figure 3. As smaller regions (each below the detection threshold size) or, in shown in the image, the EPT approach is generally better at case of the EPT approach, that the anomaly is too close to the top anomaly localisation than the classical approach. border and is ”overshadowed” by the cranium. For the unlabelled misclassifications the most likely reason is the small size of the 4 DISCUSSION AND CONCLUSIONS anomaly. Figure 2 captures rather well the minimal anomaly size where The results indicate potential for future use of the EPT technique each algorithm starts performing quite reliably. The classical for the anomaly detection in clinical practice. The results in terms approach detects anomalies larger than 350 voxels and the EPT of the anomaly size are on par with what a trained radiologist is approach detects anomalies larger than 170 voxels. Since each able to detect manually. voxel represents a cube with a 2 mm edge, these volumes trans- EPT, being a quantitative technique, offers the advantage of late roughly to a cube with the edge of 14 mm for the classical comparability of the images (e.g. in longitudinal monitoring of the approach and a cube with the edge of slightly less than 12 mm patient) compared to the standard qualitative MRI. Furthermore, for the EPT approach. the direct EPT approach performed better than the classical one Tables 1-4 further clarify the results. The images were split via edge detection. It is also less complex and this can often be a into a training set, used to optimise several internal parameters bonus in practical applications. and a test set for independent evaluation. Internal parameters of However, this is a pilot study and further research is required the classical approach specify: (i) minimum gradient value for to put these approaches into actual practice. The biggest limita- a voxel to be recognized as an edge; (ii) electrical conductivity tion of the presented study and results is that the images, while difference between anomaly and healthy tissue; (iii) minimum being an actual EPT reconstruction, were deliberately noiseless. region size. Internal parameters of the EPT approach specify: (i) With the introduction of noise the data would very much resem- how many initial slices of white matter are ignored (to avoid ble the actual in vivo cases, however the obtained results will reconstruction errors); (ii) minimum region size. The split, while likely be worse. A lot of further work, mostly on noise reduction random in nature, was made based on individual phantom heads and detection in presence of noise is likely still required. – the same head with different anomalies simulated could not be Moreover, currently only the data captured using H-EPT is both in the test and training set. The training set consisted of 130 used. This technique causes (large) reconstruction errors which images (including 26 not containing an anomaly), and the test set occur at the borders between tissues. The results could poten- consisted of 60 images (including 12 not containing an anomaly). tially be improved by combining H-EPT and CR-EPT [1], as the Table 1 shows the results of classification evaluation of the latter technique does not cause reconstruction errors at borders classical approach and Table 2 shows the results of localisation between tissues. evaluation using the classical approach. The localisation results The anomaly localisation could also be improved by not ignor- are reported as mean ± standard deviation of electrical conduc- ing edges. The edges would still be removed when anomalies are tivity. The values of IoU and F1 score for localisation are lower as detected, however, once an anomaly is detected, the edges around a result of ignoring anomaly edge voxels. Anomaly edge voxels the anomaly could be classified as anomaly, thus improving the are ignored because of H-EPT reconstruction errors. This is not IoU and the F1 score. an issue for anomaly detection as values of precision are still In addition to the mean value of electrical conductivity, the high. Values of IoU and F1 score of localisation will be improved standard deviation of the electrical conductivity could also be by acknowledging edges of anomaly after it is already detected. taken into account when detecting edges and anomalies. 21 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Golob et al. Figure 2: Predictions of anomaly detection algorithms. (a) Classical approach. (b) EPT approach. Kuster. 2018. IT’IS database for thermal and electromag- netic parameters of biological tissues. Version 4.0. (2018). doi: 10.13099/VIP21000- 04- 0. [6] W.P. Segars, B.M.W. Tsui, J. Cai, F.-F. Yin, G.S.K. Fung, and E. Samei. 2018. Application of the 4-D XCAT phantoms in biomedical imaging and beyond. IEEE Transactions on Medical Imaging, 37, 3, 680–692. [7] Andrzej J. Surowiec, Stanislaw S. Stuchly, J. Robin Barr, and Arvind Swarup. 1988. Dielectric properties of breast Figure 3: Anomaly localization. (a) Segmented pathologi- carcinoma and the surrounding tissues. IEEE Transactions cal MRI image. (b) Localization of classical approach (de- on Biomedical Engineering, 35, 4, 257–263. tected anomaly is red). (c) Localization of EPT approach [8] B.A. Wilkinson, Rod Smallwood, A. Keshtar, J. A. Lee, and (detected anomaly is red). F.C. Hamdy. 2002. Electrical impedance spectroscopy and the diagnosis of bladder pathology: a pilot study. The Jour- nal of urology, 168, 4, 1563–1567. Finally, once results achieved on EPT images of phantom brain [9] Xiaotong Zhang, Jiaen Liu, and Bin He. 2014. Magnetic- are satisfactory, implemented approaches could be tested on in resonance-based electrical properties tomography: a review. vivo data. IEEE Reviews in Biomedical Engineering, 7, 87–96. doi: 10. ACKNOWLEDGMENTS 1109/RBME.2013.2297206. The results presented here have been developed in the frame- work of the EMPIR Project 18HLT05 QUIERO. This project has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme. REFERENCES [1] A. Arduino. 2021. EPTlib: an open-source extensible collec- tion of electric properties tomography techniques. Applied Science, 11, 7, 3237. [2] O. Bottauscio, M. Chiampi, and L. Zilberti. 2014. Massively parallelized boundary element simulation of voxel-based human models exposed to MRI fields. IEEE Transactions on Magnetics, 50, 2, 7025504. [3] Jiaen Liu, Yicun Wang, Ulrich Katscher, and Bin He. 2017. Electrical properties tomography based on 𝐵 maps in MRI: 1 principles, applications, and challenges. IEEE Transactions on Biomedical Engineering, 64, 11, 2515–2530. doi: 10.1109/ TBME.2017.2725140. [4] Stefano Mandija, Petar I. Petrov, Jord J. T. Vink, Sebastian F. W. Neggers, and Cornelis A. T. van den Berg. 2021. Brain tissue conductivity measurements with MR-electrical prop- erties tomography: an in vivo study. Brain topography, 34, 1, 56–63. [5] Hasgall P.A., Di Gennaro F., C. Baumgartner, E. Neufeld, B. Lloyd, M.C. Gosselin, D. Payne, A. Klingenböck, and N. 22 Library for Feature Calculation in the Context-Recognition Domain Vito Janko Matjaž Boštic Jožef Stefan Institute Jožef Stefan Institute Department of Intelligent Systems Department of Intelligent Systems Ljubljana, Slovenia Ljubljana, Slovenia vito.janko@ijs.si bosticmatjaz@gmail.com Junoš Lukan Gašper Slapničar Jožef Stefan Institute Jožef Stefan Institute Department of Intelligent Systems Department of Intelligent Systems Ljubljana, Slovenia Ljubljana, Slovenia Jožef Stefan International Postgraduate School Jožef Stefan International Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia junos.lukan@ijs.si gasper.slapnicar@ijs.si ABSTRACT of a new context recognition system can be tedious and time- consuming. It usually consists of collecting relevant sensor data, Context recognition is a mature artificial intelligence domain parsing it to a suitable format, calculating features based on this with established methods for a variety of tasks. A typical machine data and finally training the model. learning pipeline in this domain includes data preprocessing, fea- In this work we present a Python library focused on streamlin- ture extraction and model training. The second of these steps is ing this process. Its main functionality is calculating the features typically the most challenging, as sufficient expert knowledge from sensor data. It can generate over a hundred different fea- is required to design good features for a particular problem. We tures that have proven themselves in various context-recognition present a Python library which offers a simple interface for fea- projects we tackled in the past [4, 3, 5]. Loosely, the features can ture calculation useful in a myriad of different tasks, from activity be divided in two categories: those suitable for motion data (e.g. recognition to physiological signal analysis. It also offers addi- generated by accelerometer or gyroscope) and those specialized tional useful tools for data preprocessing and machine learning, for physiological signals. such as a custom wrapper feature selection method and predic- Furthermore, the library implements some other functionalit- tion smoothing using Hidden Markov Models. The usefulness ies that are often used in context recognition pipelines: reshaping and usage is demonstrated on the 2018 SHL locomotion challenge data into windows, re-sampling the data, selecting the best fea- where a few simple lines of code allow us to achieve solid predict- tures after generating them and a method for smoothing the ive performance with F1 score of up to 93.1, notably surpassing final predictions of the classifier using a Hidden Markov Model the baseline performance and nearing the results of the winning approach. submission. To demonstrate the usefulness of the library we used its func- KEYWORDS tionalities exclusively (with the exception of a generic Random Forest classifier [11]) on the SHL Challenge dataset [16]. We feature calculation, python library, context recognition, machine demonstrate the whole pipeline, from reading in the raw data learning to the finished context-recognition system that is comparable to 1 INTRODUCTION the best-performing submissions in the SHL Challenge. Context recognition is a vague term encompassing a variety of 2 LIBRARY FUNCTIONALITIES tasks where sensors are put on (or around) a person and are then used to determine something about them. For example, The library is implemented in Python as this has been the most sensors in a smartphone can determine if a user is standing, popular data science language in recent years [6]. It is available in walking, running or even falling. A wristband sensor can read a public repository with pip install cr-features command. physiological signals like heart-rate or sweating to determine Its main and most valuable functionality lies in feature gener- stress or blood pressure. These kinds of applications are usually ation. The ‘motion features’ are listed in Section 2.1, while the used for self monitoring in sport activities or for helping the ‘physiological features’ are described in Section 2.2. Remaining users manage various medical conditions. non-feature related functionalities are explained in Section 2.3. The context-recognition field is quite mature and its applic- ations often come pre-installed in many commercial devices 2.1 Motion Sensors Features like wristbands and smartphones. Nonetheless, the development Features listed in the first two subsections are general and can be Permission to make digital or hard copies of part or all of this work for personal applied on any sensor data time-series. The last subsection (2.1.3), or classroom use is granted without fee provided that copies are not made or on the other hand, lists features that have an additional semantic 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 interpretation for acceleration and require data from three (x,y,z) work must be honored. For all other uses, contact the owner /author(s). axes. The library defines similar sensor subsets for some other Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia sensors (e.g. gyroscope). Only a subset of features is listed for © 2021 Copyright held by the owner/author(s). brevity, while the full list can be found in the documentation [1]. 23 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vito Janko, Matjaž Boštic, Junoš Lukan, and Gašper Slapničar 2.1.1 General Statistical Features. between sympathetic and parasympathetic regulation of heart • beat [10] and is thus an especially useful physiological indicator. Basic statistical measures: maximum, minimum, standard Calculation of features related to cardiovascular activity fol- deviation, median, mean difference between samples. • lows recommendations by Malik, Bigger, Camm, Kleiger, Malli- Number of peaks – useful for detecting and counting steps, ani, Moss and Schwartz [8]. To describe heart rate variability, the estimating the energy expenditure and determining the Fourier transform of inter-beat intervals is calculated and then frequency of motion: peak count, number of times data several frequency features are derived from the spectrum [5]. crossed its mean value, longest time data was above or below its mean value. 2.2.2 Skin Conductivity. Electrical conductivity of the skin var- • Different data aggregations that can indicate the intensity ies due to physiological changes in sweat glands, which are con- of the activity: (squared) sum of values, sum of absolute trolled by the autonomic nervous system. In a simple model of values. resistive properties of skin and sweat glands, whenever the level • Autocorrelations (i.e. how similar the data is to a shifted of sweat in the glands is increased, its conductivity also increases version of itself ) which indicate periodicity: autocorrela- [2]. Sweat glands thus act as variable resistors and actual sweat- tion for raw data, for peak positions, for mean crossings. ing, that is sweat secretion from the glands, is not needed for this • Data shape: skewness (a measure of symmetry, or more change to be measurable. precisely, the lack of symmetry), kurtosis (a measure of Changes in skin conductivity are not only triggered by other whether the data is heavy-tailed or light-tailed relative to physiological changes, such as the ones in (skin) temperature, a normal distribution), interquartile range. but also reflect psychological processes. Skin conductivity can indicate cognitive activity or emotional responses and can do so 2.1.2 Frequency Features. They are calculated by first comput- with good sensitivity [see 7, for an exhaustive review]. ing an estimate of the power spectral density of the signal via a Sweat glands continuously adapt to their environment and periodogram. We used the Welch’s method which is an improve- their reactions can be slow or fast. Two main modes of fluctu- ment over the traditional methods in that it reduces noise in the ations are therefore distinguished: skin conductance level changes, estimated power spectra. which are slow variations of the general trend, also called tonic Once the periodogram is obtained, the following features are electrodermal measures, and skin conductance responses, quick computed: the magnitude value of the three highest peaks in reactions, also called phasic electrodermal measures [13]. periodogram, the three highest frequencies corresponding to To calculate skin conductivity features the two components the highest peaks, energy of the signal calculated as the sum are first separated. This is done using the EDA Explorer library of squared FFT component magnitudes, entropy of the signal [14] which enables searching for peaks (SCRs) in the signal by computed as the information entropy of the normalized FFT com- specifying their desired characteristics. ponent magnitudes, and the distribution of the FFT magnitudes The signal is first filtered using a Butterworth low-pass filter into 10 equal sized bins ranging from 0 Hz to 𝐹 /2, where 𝐹 is 𝑠 𝑠 from SciPy [15]. Next, the peaks are detected by considering their the sampling frequency. Finally, we also computed the previously amplitude, onset, and offset time. described skewness and kurtosis for the periodogram. Once the SCRs are found, their characteristics are calculated Most of the described features are useful for finding different which can be used as features. These include their number and periodic patterns, how often they occur and how intense they rate (relative frequency in time) as well as the means and maxima are. of various characteristics, such as their maximum amplitude, their 2.1.3 Accelerometer Features. duration, increase time etc. The tonic component is calculated using peakutils [9]. It • Phone rotation estimation. First, roll and pitch are calcu- is detected as the signal baseline, fitting a 10-th degree polyno- lated, then we calculate their characteristics: mean, stand- mial to the signal. Similarly to the phasic component, statistical ard deviation, peaks, autocorrelations. features are calculated, such as the difference between this com- • Physical interpretations: velocity, kinetic energy. ponent and the raw signal, and the sum of its derivative. • Comparing data axis; useful for determining the sensor orientation relative to the direction of motion: correlation 2.2.3 Skin Temperature. Skin temperature is a fairly simple phy- between axis data, comparing their means, mean direction siological parameter, both from the point of view of measurement of the vector they form. as well as feature calculation. It can still serve as an indicator of affect [7]. Unlike the other physiological parameters which make 2.2 Physiological Features use of expert features only some generic statistical features are Physiological features are useful for obtaining information about calculated for this indicator. a person’s physiological state, typically reflected in their cardi- 2.3 Other Functionalities ovascular response. We computed several features from signals obtainable from many modern wristbands as described in the The following functionalities are not directly related to the fea- sections below. ture generation but are nonetheless often used in conjunction with it – and can thus make the workflow more straightforward. 2.2.1 Heart Rate and Heart Rate Variability. Cardiovascular meas- ures are widely used to predict both medical problems as well as 2.3.1 Resize, Resample. The presented library works with raw psychological processes [7]. They range from simple heart rate data in matrix form: each row representing one window of data, calculations to more complex heart rate variability indicators. i.e. one instance. If the original data is in the form of 1D time- Heart rate variability is a measure of how quickly heart rate it- series, the convertInputInto2d function can reformat it in the self changes and it is usually calculated on a beat-by-beat basis, required format. It can work both with windows of fixed number considering the inter-beat interval (IBI). It reflects the interaction of data samples as well as windows representing a fixed time 24 Feature library Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia interval. Another frequent pre-processing step is down-sampling In the actual challenge, the subset used was the data recor- the data and it can be done with the resample function. ded by one of the three participants, which included 82 days of recording, split into the training set (271 hours) and testing 2.3.2 Wrapper Feature Selection. While many feature selection set (95 hours). Raw data from 7 sensors was provided: acceler- libraries already exist (e.g. scikit-learn [11]), we implemented ometer, gyroscope, magnetometer, linear acceleration, gravity, another one in this library as it was frequently used in our pre- orientation and air pressure. All were sampled at 100 Hz [16]. vious work [4, 3]. It combines the relatively common ‘wrapper’ Data was split into 1-minute segments using a sliding window approach with reducing the feature count using correlations. It without overlap and then randomly shuffled, providing consistent works in three steps: instances. Finally, the training data had 16 310 such instances and (1) Calculate the information gain for every feature and rank test data had 5698, where each instance contained 6000 samples. them based on it. This highlights the sheer size of the data and the challenges in (2) Calculate the correlation between each feature pair. If the processing it in full. correlation exceeds the given threshold, discard the one with lower information gain. 3.2 Methods (3) Create the classifier using only the highest ranking feature and measure the accuracy using a validation set. Then add We used a traditional ML pipeline for this task: first preprocessing the second feature and measure the accuracy again. If it the data, then computing informative features, selecting the best was the same or higher, keep the feature, otherwise discard of them and finally using them to train and evaluate a classifica- it. Repeat for all other remaining features. tion model. We added another not so traditional step: smoothing the predictions using HMM. 2.3.3 Hidden Markov Model Smoothing. The final functionality All steps except training and evaluation were done in few lines is a tool to post-process the predictions of the context-recognition using the presented library; the Python code (with some missing system – taking into account the temporal dependencies between steps in comments) is given below. All classification was done the instances. using scikit-learn implementation of Random Forest with default Take an example in which the classifier predicts the following parameters. minute-by-minute sequence: ‘subway’, ‘subway’, ‘bus’, ‘subway’, ‘subway’. It is far more likely that the ‘bus’ prediction is a mis- from CalculatingFeatures import resample, classification than switching vehicles for just a minute. calculateFeatures, selectFeatures, hmm_smoothing Such a sequence can be corrected using a Hidden Markov Model (HMM). This model assumes that there are hidden states # Data was already windowed # Data was resampled from 100 Hz to 20 Hz corresponding to real activities which emit visible signals – clas- acc_x = pd.read_csv(path, sep=" ") sifications. The parameters of this models can be inferred from acc_x = resample(acc_x, 6000, 1200) the matrix of transitions probabilities and confusion matrix of # Repeat for all data types (and axes) the predictor. features_train = calculateFeatures( Once the parameters are estimated, the Viterbi algorithm is acc_x, used in the background to determine the most likely sequence acc_y, of hidden states (activities) given visible emissions (predictions). acc_z, In many domains [4, 12] this method significantly improves the featureNames=accelerationNames, final prediction accuracy. prefix="acc", While this method is least connected to the feature generation, ) # Repeat for all data types and train/test/valid sets we have not seen it implemented in a different library and have # Merge in one dataframe found it greatly useful. selected = selectFeatures( 3 USAGE EXAMPLE features_train, features_validation ) We illustrate the usage of our library with an example: The Sussex- f1, cf, predictions = evaluate( Huawei Locomotion Challenge 2018 [16]. This was a worldwide features_train[selected], open activity recognition challenge with monetary incentives, features_test[selected], labels_train, organized as part of the HASCA workshop within UbiComp labels_test, conference. 17 teams participated with 19 submissions. The goal ) was to train a recognition pipeline on the provided training data smoothed = hmm_smoothing(labels_train, cf, predictions) and then use it to classify the withheld test data as well as possible # smoothed is an array representing final output in terms of the 𝐹 score metric. 1 3.1 SHL Dataset 3.3 Results The challenge used a subset of the full dataset which was recorded over a period of 7 months by 3 participants engaging in 8 different We compared the results – in terms of 𝐹 score – of different 1 modes of transportation (still, walk, run, bike, car, bus, train and stages in the machine learning pipeline against the top three subway). The phones were worn on 4 body positions, namely the submissions in the competition. hand, torso, hip pocket and in a backpack and recorded 16 sensor In the first stage we used just the mean and standard devi- modalities simultaneously. This totalled to 2812 hours of labelled ation as features (and calculated them for each data modality) to data and this is considered one of the largest such datasets openly provide a baseline solution. Next, we calculated some features us- available [16]. ing the presented library. We then selected only a subset of them 25 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vito Janko, Matjaž Boštic, Junoš Lukan, and Gašper Slapničar Table 1: A comparison of different versions of the pipeline, Mlakar, Mitja Luštrek et al. 2020. Classical and deep learn- against the best submissions in the SHL Challenge. The ing methods for recognizing human activities and modes number of features used in our methods is also listed. of transportation with smartphone sensors. Information Fusion, 62, 47–62. Experiment # features [5] Martin Gjoreski, Mitja Luštrek, Matjaž Gams and Hristijan 𝐹 score 1 Gjoreski. 2017. Monitoring stress with a wrist device using Baseline 38 80.3 context. Journal of Biomedical Informatics, 73, 159–170. All features 298 87.7 doi: 10.1016/j.jbi.2017.08.006. Feature selection 130 87.1 [6] Harshil. 2021. Tools of the trade: a short history. https : HMM 130 93.1 / / www . kaggle . com / haakakak / tools - of - the - trade - a - Third place / 87.5 short- history/. Accessed: 2021-09-20. (2021). Second place / 92.4 [7] Sylvia D. Kreibig. 2010. Autonomic nervous system activ- First place / 93.9 ity in emotion: a review. Biological Psychology, 84, 3, 394– 421. doi: 10.1016/j.biopsycho.2010.03.010. [8] M. Malik, J. T. Bigger, A. J. Camm, R. E. Kleiger, A. Malliani, and again measured the performance. Finally, we used the HMM A. J. Moss and P. J. Schwartz. 1996. Heart rate variability: smoothing; a post-processing step described in Section 2.3.3. standards of measurement, physiological interpretation, Results are shown in Table 1. It shows that the features gener- and clinical use. European Heart Journal, 17, 3, 354–381. ated by the library substantially improve the performance. The doi: 10.1093/oxfordjournals.eurheartj.a014868. feature selection, on the other hand – while significantly reducing [9] Lucas Hermann Negri and Christophe Vestri. 2017. Lucash- the number of features required – did not increase performance. n/peakutils: v1.1.0. (2017). doi: 10.5281/ZENODO.887917. Of note, the performance did increase in the internal validation [10] M Pagani, F Lombardi, S Guzzetti, O Rimoldi, R Furlan, set, but this gain did not translate to the test set. The final jump P Pizzinelli, G Sandrone, G Malfatto, S Dell'Orto and E in performance was achieved using the HMM smoothing and we Piccaluga. 1986. Power spectral analysis of heart rate and highly recommend this method in this and similar domains. arterial pressure variabilities as a marker of sympatho- Using just the methods in the presented library and no para- vagal interaction in man and conscious dog. Circulation meter or method tuning we achieved the results comparable with Research, 59, 2, 178–193. doi: 10.1161/01.res.59.2.178. the first placed submission to the challenge. [11] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, 4 CONCLUSION V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. In this paper we demonstrated the base usage of a Python library Brucher, M. Perrot and E. Duchesnay. 2011. Scikit-learn: capable of calculating features suitable for the context recognition machine learning in Python. Journal of Machine Learning domain. The most important features that can be calculated are Research, 12, 2825–2830. listed in this paper with specialized ones thoroughly described. [12] Clément Picard, Vito Janko, Nina Reščič, Martin Gjoreski We also showed on a topical example (SHL Challenge dataset) and Mitja Luštrek. 2021. Identification of cooking pre- how only a few lines of code can generate a very capable context- paration using motion capture data: a submission to the recognition system that can compete with the best entries submit- cooking activity recognition challenge. In Human Activity ted to this challenge. Such system can be improved with extensive Recognition Challenge. Springer, 103–113. tuning but we provide a solid starting point. [13] Society for Psychophysiological Research Ad Hoc Com- It is our hope that by making this library publicly available mittee on Electrodermal Measures. 2012. Publication re- we can help the workflow of many future context-recognition commendations for electrodermal measurements. Psycho- researchers. physiology, 49, 8, 1017–1034. doi: 10.1111/j.1469- 8986. 2012.01384.x. ACKNOWLEDGMENTS [14] Sara Taylor, Natasha Jaques, Weixuan Chen, Szymon Fedor, We acknowledge the financial support from the Slovenian Re- Akane Sano and Rosalind Picard. 2015. Automatic identi- search Agency (research core funding No. P2-0209). fication of artifacts in electrodermal activity data. In 2015 37th Annual International Conference of the IEEE Engin- REFERENCES eering in Medicine and Biology Society (EMBC). IEEE. doi: 10.1109/embc.2015.7318762. [1] Matjaž Boštic, Vito Janko, Gašper Slapničar, Jakob Valič [15] Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt and Junoš Lukan. 2021. cr-features. A library for feature Haberland, Tyler Reddy, David Cournapeau, ..., Paul van calculation in the context-recognition domain. https : / / Mulbregt and SciPy 1.0 Contributors. 2020. SciPy 1.0: Fun- repo . ijs . si / matjazbostic / calculatingfeatures. Accessed: damental Algorithms for Scientific Computing in Python. 2021-09-20. (2021). Nature Methods, 17, 261–272. doi: 10.1038/s41592- 019- [2] Wolfram Boucsein. 2012. Electrodermal activity. Springer 0686- 2. Science & Business Media. [16] Lin Wang, Hristijan Gjoreski, Kazuya Murao, Tsuyoshi [3] Božidara Cvetković, Robert Szeklicki, Vito Janko, Przemyslaw Okita and Daniel Roggen. 2018. Summary of the sussex- Lutomski and Mitja Luštrek. 2018. Real-time activity mon- huawei locomotion-transportation recognition challenge. itoring with a wristband and a smartphone. Information Fusion In Proceedings of the 2018 ACM International Joint Con- , 43, 77–93. ference and 2018 International Symposium on Pervasive [4] Martin Gjoreski, Vito Janko, Gašper Slapničar, Miha Mlakar, and Ubiquitous Computing and Wearable Computers. ACM, Nina Reščič, Jani Bizjak, Vid Drobnič, Matej Marinko, Nejc 1521–1530. doi: 10.1145/3267305.3267519. 26 Določanje slikovnega prostora na umetniških slikah Reconstruction of image space depicted on artistic paintings Nadezhda Komarova Borut Batagelj Gregor Anželj Narvika Bovcon nadezhdakomarova7@gmail.com Franc Solina gregor.anzelj@gmail.com borut.batagelj@f ri.uni- lj.si Gimnazija Bežigrad narvika.bovcon@f ri.uni- lj.si 1000 Ljubljana, Slovenia franc.solina@f ri.uni- lj.si Fakulteta za računalništvo in informatiko Univerza v Ljubljani POVZETEK dostopne na medmrežju, na primer Google Arts and Culture, Wi- kimedia Commons, Getty Open Content Program, ADA (Archive V članku poročamo o analizi slikovnega prostora na umetniških of Digital Art) in druge [4]. Z analizo in vizualizacijo velikih ume- slikah s pomočjo metod računalniškega vida. Naš cilj je bil, da tniških zbirk se je prvi začel ukvarjati Lev Manovich [8]. Leta ugotovimo, ali je možno zgolj na osnovi zaznave obrazov na sli- 2012 je preučeval vizualizacijske metode za družboslovne vede kah določiti prostorsko organizacijo slike. Analiza je potekala in medijske raziskave. Ukvarjal se je z informativno, uporabno na izbranem vzorcu 3356 slik. Najprej smo določili tridimenzi- in estetsko vrednostjo vizualizacij [9]. onalne koordinate zaznanih obrazov na posamezni sliki. Nato Analiza razlik med predstavitvijo prostora s fotografijo in ume- smo tem točkam priredili ravnino. Slikovni prostor smo tako do- tniško sliko je bila narejena leta 2014 [11]. S statistično analizo ločili z enačbo prirejene ravnine oziroma kotom med to ravnino slik tihožitij, ki so jih ustvarili udeleženci eksperimenta, so ugoto- in slikovno ravnino. Bolj kot je ravnina, ki jo določajo obrazi, vili, da so predmeti, na katere so udeleženci usmerjali pozornost, nagnjena od navpične smeri, globlji je prikazani slikovni prostor. naslikani večji kot so na fotografijah. Zato je vprašanje, ali je KLJUČNE BESEDE dosledna uporaba linearne perspektive najbolj primerna metoda za posnemanje sveta [1]. Umetnostna zgodovina nam nazorno računalniški vid, slikovni prostor, zaznava obrazov, umetnostna prikaže, da so umetniki za posnemanje sveta uporabljali zelo zgodovina različne pristope. ABSTRACT Pri naši analizi slikovnega prostora smo izhajali iz dveh pred- postavk: In the article, we report on the analysis of the image space de- (1) v raziskavi želimo analizirati veliko število umetniških slik picted on artistic paintings utilizing methods of computer vision. v smislu današnjega trenda Big Data, Our aim was to find out whether one can recover the spatial (2) uporabiti želimo take metode računalniškega vida, ki de- organization of a picture based on detection of faces. The anal- lujejo hitro in čimbolj zanesljivo. ysis was conducted on the sample of 3356 paintings. First, 3D coordinates of faces were determined. Then, a plane was fitted to Med hitre in zanesljive metode računalniškega vida zagotovo the faces on every painting. Images were therefore described in sodi zaznava in identifikacija oseb na osnovi njihovih obrazov. terms of the angle between the fitted plane and the picture plane. Zaradi varnostnih razlogov se je teh problemov na področju bio- The bigger the angle between both planes, the deeper the picture metrije lotilo že zelo veliko znanstvenikov. Danes obstajajo hitre space depicted. in zanesljive metode za zaznavo in analizo obrazov na slikah [10]. Za navdih nam je služil članek Irvinga Zupnicka iz leta 1959 KEYWORDS [14], objavljen še veliko pred uporabo računalnikov v likovni computer vision, image space, face detection, art history umetnosti, ki opisuje kako je na slikah iz različnih umetnostnih obdobjih organiziran slikovni prostor. Zato smo si zastavili vpra- 1 UVOD IN MOTIVACIJA šanje, ali je mogoče s pomočjo metod računalniškega vida rekon- struirati slikovni prostor na umetniških slikah? Bolj konkretno, Odločili smo se povezati dve raziskovalni področji, ki sta si na- ali ga je mogoče rekonstruirati na osnovi zaznave obrazov na videz zelo vsaksebi, to je umetnostna zgodovina in umetna in- slikah? Določitve 3D razsežnosti prostora, upodobljenega na sliki, teligenca. Metode računalniškega vida se že redno uporabljajo smo se lotili na osnovi pozicije obrazov na sliki (𝑥 in 𝑦 koordi- tudi za analizo umetniških slik [12]. Večina teh raziskav je osre- nate) in njihove velikosti, kar nam daje grobo informacijo o tretji dotočena na analizo posameznih ali manjšega števila umetniških dimenziji 𝑧 — to je oddaljenosti obraza od opazovalca. Ta pristop slik. Po drugi strani smo danes v dobi velepodatkov (angl. Big Data seveda temelji na predpostavki, da so na slikah ljudje oziroma ), saj je vedno več informacij dostopnih v digitalni obliki. da so upodobljeni njihovi dovolj veliki obrazi. Resda v zgodovini Tudi velike zbirke reprodukcij umetniških slik so danes prosto likovne umetnosti poznamo veliko tihožitij ali pokrajinskih slik, Permission to make digital or hard copies of part or all of this work for personal na katerih ni obrazov. Toda velika večina umetniških slik iz obdo- or classroom use is granted without fee provided that copies are not made or bja pred izumom fotografije dejansko upodablja ljudi oz. njihove 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 obraze. work must be honored. For all other uses, contact the owner /author(s). Iz javno dostopnih baz umetniških slik smo za našo študijo Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia izbrali testno množico 3356 slik iz različnih umetnostnozgodo- © 2021 Copyright held by the owner/author(s). vinskih obdobij in žanrov. 27 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Nadezhda Komarova, Gregor Anželj, Borut Batagelj, Narvika Bovcon, and Franc Solina 2 SLIKOVNI PROSTOR NA UMETNIŠKIH SLIKAH Slika 3: Vijoličasta ravnina, ki se prilega 3D pozicijam obrazov na Renoirjevem Plesu v Le Moulin de la Galette in in rdeča ravnina 𝑧 = 0 – ploskev slikarskega platna, na kateri smo zaznali obraze. upodabljanje prostora: velikosti oseb niso določene s prostorskim oddaljevanjem, temveč npr. z družbenim statusom. Slika 1: Auguste Renoir, Ples v Le Moulin de la Galette; vi- dijo se zaznani obrazi. Velikost obrazov jasno odraža glo- 3 ZAZNAVA OBRAZOV bino slikarskega prostora. Predpostavili smo, da so resnični obrazi pri vseh osebah pribli- žno enako veliki. Zato so bili večji obrazi obravnavani kot bližji površini slike in manjši kot bolj oddaljeni od površine slike oz. od opazovalca. Zaznani so bili z orodjem RetinaFace, ki izvede dvodimenzio- nalno poravnavo in tridimenzionalno rekonstrukcijo obraza [2]. Zasnovan je na osnovi globoke nevronske mreže. Detektor vrne podatke o obrazih v dvodimenzionalnem pro- storu površine slike, torej imajo središča obraznih okvirjev in točke oči, nosu ter ust samo 𝑥 in 𝑦 koordinate. Toda za rekonstruk- cijo tridimenzionalnega prostora slike potrebujemo tudi globine obrazov oz. koordinato 𝑧 . Tridimenzionalni prostor, kot ga prika- zuje umetniška slika, se razlikuje od fotografskega predvsem zato, ker slikarji redko dosledno upoštevajo linearno perspektivo. Na fotografijah je perspektiva po drugi strani bolj konsistentno dolo- čena. Zato je na njih mogoče z enačbo (1) [6] določiti oddaljenost predmeta od kamere: 𝑓 · ℎ · ℎ 𝑟 Slika 2: Poslikava v grobnici Unsu. Vsi obrazi se enake 𝑑 = (1) ℎ · ℎ 𝑖 𝑠 velikosti, ves slikarski prostor je zgoščen kar v ravnini po- Z enačbo (1) izračunamo oddaljenost 𝑑 objekta v milimetrih, če slikave. je 𝑓 goriščna razdalja fotoaparata, ℎ resnična višina objekta v 𝑟 Vsakemu obrazu na slikah smo priredili tridimenzionalne koor- milimetrih, ℎ višina slike v pikslih, ℎ višina objekta na sliki v 𝑖 dinate, ki pa niso bile zanesljive v absolutnih vrednostih, temveč pikslih in ℎ višina senzorja fotoaparata v milimetrih. Z njo so 𝑠 odražajo zgolj relativne razdalje. Nato smo tem obraznim točkam bile določene tudi oddaljenosti obrazov na slikah v vzorcu, pri priredili ravnine s smislu vsote najmanjših kvadratov razdalj med čemer so bile uporabljene vrednosti goriščne razdalje in višine točkami in iskano ravnino. Pri tistih slikah, ki prikazujejo obraze, senzorja, kvocient katerih opiše, kako vidijo človeške oči. Četudi ki so v spodnjem delu slike opazovalcu blizu, in se višje na sliki je bilo po tem postopku nemogoče določiti natančne tridimen- postopno oddaljujejo (Slika 1), so dobljene ravnine bolj nagnjene zionalne koordinate obrazov na sliki, so bile določene relativne v globino kot pri tistih, kjer so vsi obrazi približno na enaki razda- oddaljenosti med obrazi in površino slike. Za namen te raziskave lji od opazovalca (Slika 2). V takih primerih je dobljena ravnina tudi niti ni pomembno, če zaznamo vse obraze na sliki. skorajda vzporedna s površino slike. Rafaelova Atenska šola in staroegipčanska poslikava v grobnici Unsu imata zelo različni 4 GEOMETRIJSKA INTERPRETACIJA prostorski ureditvi. Na prvi sliki se obrazi zmanjšujejo z odda- PROSTORA ljevanjem ljudi. Ravnina, prirejena točkam na tej sliki, je zato Parametre nagnjena v globino (Slika 3). 𝐴, 𝐵 in 𝐶 enačbe ravnine 𝑧 = 𝐴𝑥 + 𝐵𝑦 + 𝐶 smo določili z minimizacijo funkcije Po drugi strani tudi poslikava na Sliki 2 prikazuje množico ljudi, vendar so vsi enake višine in njihovi obrazi so enako veliki. 𝑚 Õ Ravnina, prirejena obrazom na egipčanski sliki, je zato vzporedna 𝐸 (𝐴, 𝐵, 𝐶 ) = (𝐴𝑥 + 𝐵𝑦 + 𝐶 − 𝑧 )2, (2) 𝑖 𝑖 𝑖 ravnini 𝑧 = 0. Za egipčansko slikarstvo je značilno konceptualno 𝑖 =1 28 Določanje slikovnega prostora na umetniških slikah Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia kjer 𝑚 pomeni število točk in 𝑥 , 𝑦 ter 𝑧 koordinate točk. 𝑖 𝑖 𝑖 Funkcija (2) doseže minimum, ko je ∇𝐸 = (0, 0, 0) [3]. Za gradi- 𝜕𝐸 𝜕𝐸 𝜕𝐸 𝜕𝐸 𝜕𝐸 ent te funkcije velja ∇𝐸 = ( 𝜕𝐸 , , ), kjer so , in 𝜕𝐴 𝜕𝐵 𝜕𝐶 𝜕𝐴 𝜕𝐵 𝜕𝐶 naslednji. 𝑚 𝜕𝐸 Õ = 2 𝑥 (𝐴𝑥 + 𝐵𝑦 + 𝐶 − 𝑧 ) (3) 𝑖 𝑖 𝑖 𝑖 𝜕𝐴 𝑖 =1 𝑚 𝜕𝐸 Õ = 2 𝑦 (𝐴𝑥 + 𝐵𝑦 + 𝐶 − 𝑧 ) (4) 𝑖 𝑖 𝑖 𝑖 𝜕𝐵 𝑖 =1 𝑚 𝜕𝐸 Õ = 2 (𝐴𝑥 + 𝐵𝑦 + 𝐶 − 𝑧 ) (5) 𝑖 𝑖 𝑖 𝜕𝐶 𝑖 =1 Slika 4: Razporeditev razredov pri gručenju na osnovi rav- Tako množici 3D točk priredimo ravnino z minimizacijo razdalj nin. Gruče so razpršene in izrazite razmejitve med njimi med temi točkami in njihovimi slikami na ploskvi v smeri 𝑧 . ni. Koeficienti A, B in C so zato rešitve sistema linearnih enačb (6), (7) in (8). 𝑚 𝑚 𝑚 𝑚 Õ Õ Õ Õ 2 𝐴 𝑥 + 𝐵 𝑥 𝑦 + 𝐶 𝑥 = 𝑥 𝑧 (6) 𝑖 𝑖 𝑖 𝑖 𝑖 𝑖 𝑖 =1 𝑖 =1 𝑖 =1 𝑖 =1 𝑚 𝑚 𝑚 𝑚 Õ Õ Õ Õ 2 𝐴 𝑥 𝑦 + 𝐵 𝑦 + 𝐶 𝑦 = 𝑦 𝑧 (7) 𝑖 𝑖 𝑖 𝑖 𝑖 𝑖 𝑖 =1 𝑖 =1 𝑖 =1 𝑖 =1 𝑚 𝑚 𝑚 Õ Õ Õ 𝐴 𝑥 + 𝐵 𝑦 + 𝐶 = 𝑧 (8) 𝑖 𝑖 𝑖 𝑖 =1 𝑖 =1 𝑖 =1 5 REZULTATI Slika 5: Zastopanost posameznih kotov za slike v testni Slike smo izbrali iz prostodostopne zbirke WikiArt (https://www. množici. wikiart.org), kjer so umetnine med drugim razdeljene po žanrih. ustrezajo slikam, kjer se upodobljene osebe enotno oddaljujejo Izbrana so bila slikarska dela (potrebno je bilo izločiti npr. kipar- oz. približujejo. Če je bil kot med ravnino, ki je bila prirejena ska), kjer je bilo upodobljenih več ljudi. Iz zbirke WikiArt so bila obrazom na sliki, in ravnino 𝑧 = 0 izračunan kot natančno 0 zato izbrana dela iz žanrov pastorale (77 slik), allegorical painting stopinj, je to pomenilo, da na sliki ni bilo zaznanega nobenega (1225 slik), history painting (1377 slik) in literary painting (667 obraza, samo en obraz ali pa so imeli vsi obrazi enake globine. Na slik), in sicer skupaj 3356 slik. Poleg žanra smo imeli tudi podatke intervalu od 0 do 5 stopinj (Slika 5) je bil najpogostejši barok, na o umetnostno zgodovinskem obdobju v katero sodi posamezna preostalih intervalih po romantika. Ni pa na nobenem intervalu slika. Zanimalo nas je, kako lahko le na osnovi teh podatkov močno prevladoval le en slog, saj je odstotek slik, ki je pripadal smiselno razdelimo testno množico slik z metodo gručenja in ali najpogostejšemu slogu v posameznem intervalu med 20 in 30%. je ta delitev relevantna z vidika umetnostno zgodovine. Za določitev korelacije med časom nastanka posamezne slike Kot kriterij pri gručenju so bile uporabljene enačbe ravnin ter in kotom med ravninama za to sliko je bil uporabljen Spearma- kot med prirejeno ravnino in slikovno ravnino 𝑧 = 0. Detektor RetinaFace nov koeficient korelacije. Ta predstavlja neparametersko stopnjo opiše slednje s tremi parametri – rotacijami okoli povezanosti med spremenljivkama oz. kako dobro je mogoče osi 𝑥 , 𝑦 in 𝑧 (v pozitivni in negativni smeri). Pri posamezni sliki opisati njun odnos z monotono funkcijo [13]. Koeficient je bil so bile izbrane rotacije v vsaki smeri z največjimi absolutnimi 0.183, kar predstavlja šibko pozitivno korelacijo. p vrednost je vrednostmi. bila v tem primeru blizu 0, kar pomeni, da korelacija med letom Gručenje je bilo opravljeno z algoritmom BIRCH, implemen- nastanka slike in kotom, ki odraža slikarsko globino ni linearna. tiranim s knjižnico scikit-learn. BIRCH (angl. Balanced Iterative Reducing and Clustering using Hierarchies Na prikazu na Sliki 6 je razvidno, da če opazujemo obdobje od ) je algoritem gručenja, približno leta 1700 in vse do danes, povprečen kot med ravninama ki je posebej prilagojen delu z večjimi podatkovnimi vzorci [7]. za posamezna desetletja blago narašča. Na Sliki 4 so ekstremne vrednosti izločene. Prikazana je raz- poreditev slik po gručenju na osnovi ravnin. Bila je izvedena 6 RAZPRAVA primerjava tega, katerim umetnostnim slogom pripadajo slike v posameznih razredih. To je bilo mogoče, saj je bila vsaka slika Glavna hipoteza naše raziskave je bila, ali lahko na nek enostaven v zbirki označena poleg žanra tudi z letom nastanka in ume- način ugotovimo kakšen je slikarski prostor, to je, kako izrazita tnostnim slogom (barok, romantika ipd.). Število razredov smo je globinska dimenzija na dani umetniški sliki. Slikarski prostor omejili na deset. Zaradi izrazite drugačnosti prostorske razpore- pa je povezan tako z umetnostno zgodovinskim obdobjem v ka- ditve na nekaterih slikah so bile slednje izločene v posamezne terega sodi slika, kot tudi z žanrom slike. Na ta način se nam razrede (2, 5, 6, 7 in 8). Ti razredi vsebujejo le po eno sliko in niso odpira možnost avtomatske klasifikacije velikega števila slik, bo- vidni na Sliki 4. disi s statističnimi metodami, še bolj pa bi prišle v poštev metode Histogram na Sliki 5 prikazuje zastopanost različnih intervalov strojnega učenja. kotov v proučevanem vzorcu. Vidi se, da je bil največji delež Odločili smo se, da bomo slikovni prostor določali posredno s slik takih, kjer je bil kot med ravninama med 15 in 20 stopinj, pomočjo zaznave obrazov. Ko je bil posamezen obraz zaznan z kar se zdi relativno malo. Večji koti med ravninama večinoma orodjem RetinaFace, je bil s tem določen obrazni okvir na določeni 29 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Nadezhda Komarova, Gregor Anželj, Borut Batagelj, Narvika Bovcon, and Franc Solina na vprašanja, ki si jih umetnostni zgodovinarji do sedaj sploh še niso upali zastaviti. LITERATURA [1] Katarina Bebar. “Upodabljanje prostora po načelih line- arne perspektive s pomočjo obogatene resničnosti”. V: Likovne besede 114 (2020), str. 14–21. [2] Jiankang Deng in sod. “RetinaFace: Single-Shot Multi- Level Face Localisation in the Wild”. V: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020, str. 5202–5211. doi: 10.1109/CVPR42600.202 0.00525. Slika 6: Koti med ravninama v odvisnosti od časa nastanka [3] David Eberly. “Least Squares Fitting of Data”. V: Magic slike. Rdeče točke predstavljajo povprečen kot za posame- Software, Inc. (sep. 2001). url: http://www.sci.utah.edu/~b zno desetletje. alling/FEtools/doc_f iles/LeastSquaresFitting.pdf . [4] Image resources: Free image resources. Sotheby’s Institute koordinati 𝑥 in 𝑦 na ravnini slike. Velikost obraznega okvirja pa of Art. url: https://sia.libguides.com/images/f reeimagere nam je dal še informacijo o relativni oddaljenosti obraza 𝑧 od sources (pridobljeno 1. 3. 2021). ravnine slike. Zanesljivost zaznave obrazov na umetniških slikah [5] Jure Kovač, Peter Peer in Franc Solina. “Automatic natural je bil verjetno nekoliko slabši, saj je bil RetinaFace naučen na fo- and man-made scene differentiation using perspective tografijah obrazov in ne na umetniških upodobitvah [2]. V kakšni geometrical properties of the scenes”. V: Proceedings 15th prihodnji raziskavi bi lahko uporabili še dodatne informacije, ki International Conference on Systems, Signals and Image jih daje orodje RetinaFace za zaznavo obrazov: orientacija obraza, Processing. Bratislava, 2008, 507–510. lega oči, nosu in ust, spol ter starost osebe, določeno na osnovi [6] Yun Liang. How to measure the real size of an object from obraza. Poleg tega bi lahko v prihodnjih raziskavah pri analizi slik an unknown picture? Jan. 2015. url: https://www.researc upoštevali tudi barvno sestavo in druge slikovne značilke, ki jih hgate.net/post/How- to- measure- the- real- size- of - an- obj lahko robustno določimo z metodami računalniškega vida [12]. ect- f rom- an- unknown- picture. Sami smo se ukvarjali npr. z detekcijo črt perspektivne projekcije [7] Cory Maklin. “BIRCH Clustering Algorithm Example In na fotografijah [5, 1]. Python”. V: towards data science (jul. 2019). url: https://to Četudi smo v našem preizkusu metode likovna dela združevali wardsdatascience.com/machine- learning- birch- clusterin v razrede po podobnosti prostorske ureditve, se niso pokazale g- algorithm- clearly- explained- f b9838cbeed9. stroge meje med umetnostnimi slogi slik. Informativna pa je bila [8] Lev Manovich. “Data Science and Digital Art History”. V: korelacija med časom nastanka dela in kotom med ravninama. International Journal for Digital Art History 1 (jun. 2015). V izbranem vzorcu slik različni umetnostnozgodovinski slogi doi: 10.11588/dah.2015.1.21631. niso bili povsem enakomerno zastopani in je bilo npr. veliko del [9] Lev Manovich. Museum without walls, art history without iz romantike. Za vsako zgodovinsko obdobje so najverjetneje names: visualization methods for Humanities and Media izrazite določene medsebojne povezanosti teh značilnosti. Usta- Studies. Oxford Handbook Online, 2013. doi: 10.1093/oxf ljen umetnostnozgodovinski pristop pri analizi slik je sočasno ordhb/9780199757640.013.005. opazovanje dveh ali več del, pri katerih raziskovalec na osnovi [10] Mohd Nayeem. “Exploring Other Face Detection Approa- svojega predhodnega znanja izloči značilne poteze, razlike ipd. ches(Part 1) — RetinaFace”. V: Analytics Vidhya (jul. 2020). [8]. Strojno učenje bi na tej točki postalo učinkovito, saj po eni url: https://medium.com/analytics- vidhya/exploring- oth strani nudi možnost analize velike količine podatkov, odkrivanje er- f ace- detection- approaches- part- 1- retinaf ace- 9b00f 4 sočasnih povezav med različnimi značilkami, po drugi strani pa 53f d15. zagotavlja objektivnost matematičnih pristopov. Zato bi bilo v [11] Robert Pepperell in Manuela Braunagel. “Do Artists Use nadaljevanju koristno uporabiti poleg obrazov tudi druge infor- Linear Perspective to Depict Visual Space?” V: Perception macije na slikah. Potrebno pa je upoštevati, da delitev umetniških 43 (avg. 2014), 395 – 416. doi: 10.1068/p7692. del ne more biti absolutna, saj umetnostno zgodovino sestavljajo [12] David G. Stork. “Computer Vision and Computer Graphics posamezni umetniki, vsak od njih ustvarja v svojem lastnem Analysis of Paintings and Drawings: An Introduction to slogu, ki lahko do neke mere sledi splošnim trendom obdobja, the Literature”. V: Computer Analysis of Images and Pat- vendar nikoli popolnoma. Tudi posamezni likovni umetniki v terns. Ur. Xiaoyi Jiang in Nicolai Petkov. Berlin, Heidelberg: času svoje kariere lahko spremenijo svoj umetniški slog. Springer Berlin Heidelberg, 2009, str. 9–24. doi: 10.1007/9 78- 3- 642- 03767- 2_2. 7 ZAKLJUČEK [13] Eric W. Weisstein. “Spearman Rank Correlation Coeffici- V članku smo pokazali nov pristop k avtomatski analizi umetni- ent”. V: MathWorld, a Wolfram Web Resource (brez datuma). ških slik z uporabo metod računalniškega vida. Demonstrirali url: https://mathworld.wolf ram.com/SpearmanRankCorr smo, da je z metodo zaznave obrazov na slikah možno nasloviti elationCoef f icient.html. tudi bolj kompleksna vprašanja, kot v našem primeru organiza- [14] Irving L. Zupnick. “Concept of Space and Spatial Organiza- cija prostora na slikah. Čeprav rezultati te raziskave morda niso tion in Art”. V: The Journal of Aesthetics and Art Criticism tako jasno izraženi in niso reproducirali rezultatov umetnostnih (dec. 1959), str. 215–221. doi: 10.2307/427268. zgodovinarjev, se uporaba računalnikov na področju umetnostne zgodovine kot na sploh v humanistiki šele zares začenja. Raču- nalniško zasnovane analitične metode bodo omogočile odgovore 30 Automated Hate Speech Target Identification ∗ ∗ ∗ Andraž Pelicon Blaž Škrlj Petra Kralj Novak andraz.pelicon@ijs.si blaz.skrlj@ijs.si petra.kralj.novak@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 POS tag, keyword-based, knowledge graph-based and relational features) and two types of document embeddings (non-sparse rep- We present a new human-labelled Slovenian Twitter dataset an- resentations). To our knowledge, this is one of the first attempts notated for hate speech targets and attempts to automated hate to solve a Slovene-based text classification task with an autoML speech target classification via different machine learning ap- approach. Finally, we trained a model based on the SloBERTa proaches. This work represents, to our knowledge, one of the pre-trained language model [11], a state-of-the-art transformer- first attempts to solve a Slovene-based text classification task with based language model pre-trained on a Slovenian corpus and a an autoML approach. Our results show that the classification task set of baselines. is a difficult one, both in terms of annotator agreement and in Our results show that the context-aware SloBERTa model terms of classifier performance. The best performing classifier is significantly outperforms all the other models. This result, to- SloBERTa-based, followed by AutoBOT-neurosymbolic-full. gether with the lower inter-annotator scores, confirms our initial KEYWORDS assumption that hate speech target identification is a complex semantic task that requires a complex understanding of the text hate speech targets, autoML, text features spaces that goes beyond simple pattern matching. The SloBERTa model reaches annotator agreement in terms of classification accuracy, 1 INTRODUCTION indicating a fair performance of the model. Hate speech and offensive content has become pervasive in social media and has become a serious concern for government orga- 2 DATA nizations, online communities, and social media platforms [13]. We collected almost three years worth of all Slovenian Twitter Due to the amount of user-generated content steadily increasing, data in the period from December 1, 2017, to October 1, 2020, in the research community has been focusing on developing com- total 11,135,654 tweets. The period includes several government putational methods to moderate hate speech on online platforms changes, elections and the first Covid-19-related lockdown. We [6, 1, 8]. While several of the proposed methods achieve good used the TweetCat tool [5], which is developed for harvesting performance on distinguishing hateful and respectful content, Twitter data of less frequent languages. several important challenges remain, some of them related to the data itself. Several studies report both low amounts of hate 2.1 Annotation Schema speech instances in the labelled datasets, as well as relatively low agreement scores between annotators [9]. The low agreement Our annotation schema is adapted from OLID [13] and FRENK [4]. score between annotators indicates that recognizing hate speech It is a two-step annotation procedure. After reading a tweet, is a hard task even for humans suggesting that this task requires without any context, the annotator first selects the type of speech. a more broad semantic interpretation of the text and its context We differentiate between the following speech types: beyond simple pattern matching of linguistic features. 0 acceptable - non hate speech type: speech that does not To test this assumption, we have gathered a new Slovenian contain uncivil language; 1 dataset containing tweets annotated for hate speech targets . 1 inappropriate - hate speech type: contains terms that are This dataset builds on the dataset used for detecting hate speech obscene, vulgar but the text is not directed at any person communities [3] and topics [2] on Slovenian Twitter. The dataset specifically; is available in the clarin.si dataset repository with the handle: 2 offensive - hate speech type: including offensive gener- https://www.clarin.si/repository/xmlui/handle/11356/1398. alization, contempt, dehumanization, indirect offensive Next, we addressed the hate speech target classification task remarks; by the autoML approach autoBOT [10]. The key idea of autoBOT 3 violent - hate speech type: author threatens, indulges, is that, instead of evolving at the learner level, evolution is con- desires or calls for physical violence against a target; it ducted at the representation level. The proposed approach con- also includes calling for, denying or glorifying war crimes sists of an evolutionary algorithm that jointly optimizes various and crimes against humanity. sparse representations of a given text (including word, subword, If the annotator chooses either the offensive or violent hate ∗ All authors contributed equally to this research. speech type, they also include one of the twelve possible targets 1 Slovenian Twitter dataset 2018-2020 1.0: http://hdl.handle.net/11356/1423 of hate speech: Permission to make digital or hard copies of part or all of this work for personal • Racism (intolerance based on nationality, ethnicity, lan- or classroom use is granted without fee provided that copies are not made or guage, towards foreigners; and based on race, skin color) 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 • Migrants (intolerance of refugees or migrants, offensive work must be honored. For all other uses, contact the owner /author(s). generalization, call for their exclusion, restriction of rights, Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia non-acceptance, denial of assistance . . . ) © 2021 Copyright held by the owner/author(s). • Islamophobia (intolerance towards Muslims) 31 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Pelicon et al. • Antisemitism (intolerance of Jews; also includes conspir- acy theories, Holocaust denial or glorification, offensive stereotypes . . . ) • Religion (other than above) • Homophobia (intolerance based on sexual orientation and/or identity, calls for restrictions on the rights of LGBTQ per- sons • Sexism (offensive gender-based generalization, misogynis- tic insults, unjustified gender discrimination) • Ideology (intolerance based on political affiliation, politi- cal belief, ideology. . . e.g. “communists”, “leftists”, “home defenders”, “socialists”, “activists for. . . ”) • Media (journalists and media, also includes allegations of unprofessional reporting, false news, bias) • Politics (intolerance towards individual politicians, author- Figure 1: Number of annotated examples for hate speech ities, system, political parties) type and target. The class distribution is severely unbal- • Individual (intolerance towards any other individual due anced. to individual characteristics; like commentator, neighbor, acquaintance ) either individuals or groups), 4% as inappropriate (mostly con- • Other (intolerance towards members of other groups due taining swear words), and the remaining 61% as acceptable. In the to belonging to this group; write in the blank column on evaluation set, which is a random selection of 10.000 Slovenian the right which group it is) tweets, only 69 tweets were labelled as violent by at least one 2.2 Sampling for Training and Evaluation annotator, which is about 0.3%. The training dataset for hate speech type includes 34,204 ex- The training set is sampled from data collected before February amples and the evaluation dataset includes 6,430 examples. Many 2020. The sampling was intentionally biased to contain as much of the examples are repeated (by two annotations for the same hate speech as possible in order to obtain enough organic exam- tweet), yet conflicting (due to annotator disagreement). The train- ples to train the model successfully. A simple model was used to ing and evaluation sets for hate speech type and target are sum- flag potential hate speech content, and additionally, filtering by marized in Table 1. users and by tweet length (number of characters) was applied. The overall annotator agreement for hate speech target on the 2 50,000 tweets were selected for annotation. training set is 63.1%, and Nominal Krippendorf Alpha is 0.537. The evaluation set is sampled from data collected between The annotator agreement for hate speech target on the evalua- February 2020 and August 2020. Contrary to the training set, the tion set is 62.8%, and Nominal Krippendorf Alpha is 0.503. These evaluation set is an unbiased random sample. Since the evaluation scores indicate that the dataset is of high quality compared to set is from a later period compared to the training set, the possi- other datasets annotated for hate speech, yet the relatively low bility of data linkage is minimized. Furthermore, the estimates agreement indicates that the annotation task is difficult and am- of model performance made on the evaluation set are realistic, biguous even for humans. or even pessimistic, since the model is tested on a real-world distribution of data where hate speech is less prevalent than in 3 EXPERIMENTS the biased training set. The evaluation set is also characterized We compare different machine learning algorithms on the hate by a new topic, COVID-19; this ensures that our model is robust speech target identification task. They belong to one of the fol- to small contextual shifts that may be present in the test data. For lowing three categories: classical, representation optimization the evaluation set, 10,000 tweets were selected to be annotated. and deep learning. The results are presented in Table 1. 2.3 Annotation Procedure 3.1 autoBOT - an autoML for texts Each tweet was annotated twice: In 90% of the cases by two dif- With the increasing amounts of available computing power, au- ferent annotators (to estimate inter-annotator agreement) and tomation of machine learning has become an active research in 10% of the cases by the same annotator (to assess the self- endeavor. Commonly, this branch of research focuses on auto- agreement). Special attention was devoted to an evening out matic model selection and configuration. However, it has recently the overlap between annotators to get agreement estimates on also been focused on the task of obtaining a suitable representa- equally sized sets. Ten annotators were engaged for our annota- tion when less-structured inputs are considered (e.g. texts). This tion campaign. They were given annotation guidelines, a training work represents, to our knowledge, one of the first attempts to session and a test on a small set to evaluate their understanding solve a Slovene-based text classification task with an existing of the task and their commitment before starting the annota- autoML approach. The in-house developed method, called au- tion procedure. The annotation process lasted four months, and toBOT [10], has already shown promising results on multiple it required about 1,200 person-hours for the ten annotators to shared tasks (and in extensive empirical evaluation). Albeit it complete the task. commonly scores on average worse than large, multi million- In the training set, intentionally biased in favour of hate speech, parameter neural networks, it remains interpretable and does about 1% of tweets were labelled as violent, 34% as offensive (to not need any specialized hardware. Thus, this system serves as an easy-to-obtain baseline which commonly performs better 2 Some annotators skipped some examples. than ad hoc approaches such as, e.g. word-based features coupled 32 Hate speech targets Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia with, e.g. a Support Vector Machine (SVM). The tool has mul- The SloBERTa-based predictor performed the best, however, is tiple configurations which determine the feature space that is also the one which includes the highest number of tunable pa- being evolved during the search for an optimal configuration of rameters (more than 100m). The next series of learners are based both the representation of a given document, but also the most on autoBOT’s evolution and perform reasonably well. Interest- suitable learner. We left all settings to default, varying only the ingly, autoBOT variants which exploit only symbolic features representation type, which was either symbolic, neuro-symbolic- perform better than the second neural network-based baseline lite, neuro-symbolic-full or neural. Detailed descriptions of these which was not pre-trained specifically for Slovene – the mpnet. 3 feature spaces are available online . The main difference between The remaining baselines perform worse, albeit having a similar these variants is that the neuro-symbolic ones simultaneously number of final parameters to the final autoBOT-based models consider both symbolic and sub-symbolic feature spaces (e.g. (tens of thousands at most). The autoBOT-neural, which imple- tokens and embeddings of the documents), whilst symbolic or ments the two main doc2vec variants, performs better than the neural-only consider only one type. The neural variant is based naïve doc2vec implementation, however not notably better. on the two non-contextual doc2vec variants and commonly does To better understand the key properties of the data set which not perform particularly well on its own. carry information relevant for the addressed predictive task, we 3.2 Deep Learning additionally explored autoBOT-symbolic’s ‘report’ functionality, which offers insight into the importance of individual feature We trained a modelbased on the SloBERTa pre-trained language subspaces. Each subspace and each feature in the subspace has a model [11]. SloBERTa is a transformer-based language model weight associated with it: the larger the weights, the more rel- that shares the same architecture and training regime as the evant a given feature type was for the learner. Visualization of Camembert model [7] and is pre-trained on Slovenian corpora. these importances is shown in Table 2. It can be observed that For fine-tuning of the SloBERTa language model, we first split character-based features were the most relevant for this task. the original training set into training and validation folds in the This result is in alignment with many previous results on tweet 90%:10% ratio. We used the suggested hyperparameters for this classification, where e.g. punctuation-level features can be sur- model. We used the Adam optimizer with the learning rate of prisingly effective. Furthermore, relational token features were 2𝑒 − 5 and learning rate warmup over the first 10% of the training also relevant. This feature type can be understood as skip-grams instances. We used a weight decay set to 0.01 for regularization. with dynamic distances between the two tokens. This feature The model was trained for maximum 3 epochs with a batch size of type indicates that short phrases might have been of relevance. 32. The best model was selected based on the validation set score. Interestingly, keyword-based features were not relevant for the We performed the training of the models using the HuggingFace learner. Further, autoBOT, being effectively a fine-tuned linear Transformers library [12]. learner, also offers direct insight into fine-grained performances. We tokenized the textual input for the neural models with the Examples for the top five features per type are shown in Table 2. language model’s tokenizer. For performing matrix operations efficiently, all inputs were adjusted to the same length. After tok- 5 CONCLUSION enizing all inputs, their maximum length was set to 256 tokens. In this work we present a new dataset of Slovenian tweets anno- Longer sequences were truncated, while shorter sequences were tated for hate speech targets. To develop effective computational zero-padded. The fine-tuned model is available at the Hugging- models to solve this task we use two approaches: the autoML 4 Face repository . approach combining symbolic and neural representations and a 3.3 Other Baseline Approaches contextually-aware language model SloBERTa. The two mentioned approaches have demonstrated state-of-the- The results show that the context-aware SloBERTa model art performance; however, to establish their performance on this significantly outperforms all the other trained models. This result, new task, we also implemented the following baselines. First, together with the lower inter-annotator scores, confirm our initial a simple majority classifier to establish the worst-case perfor- assumption that hate speech target identification is a complex mance. Next, a doc2vec-based representation learner was coupled semantic task that requires a more complex understanding of with a linear SVM (doc2vec). The svm-word is a sparse TF-IDF the text that goes beyond simple pattern matching. However, representation of the documents coupled with a linear SVM. Sim- the seemingly simpler models may still offer distinct advantages ilarly, the svm-char, however, the representations are based on over the more complex neural models. First, the auto-ML models characters in this variant. The two alternatives use logistic re- tested in this work are easily interpretable, offering insights into gression (lr-word, lr-char ). As another strong baseline, we used a textual features which contribute to the classification. On the multilingual language model called MPNet to obtain contextual other hand, the neural language models generally work as black- representations, coupled with an SVM classifier. The baseline boxes, and the extent of their interpretability is still an open doc2vec model was trained for 32 epochs with eight threads. The research question. Second, the auto-ML models are significantly min_count parameter was set to 2, window size to 5 and vector more straightforward to deploy as they tend to be much less size to 512. For SVM and logistic regression (LR)-based learners, computationally demanding both in terms of RAM and CP U a grid search including the following regularization values was usage. Neural language models are able to solve harder tasks traversed: {0.1, 0.5, 1, 5, 10, 20, 50, 100, 500}. but their increased number of parameters usually makes them a considerable challenge to deploy in a scalable fashion. 4 RESULTS The classification results for the discussed learning algorithms ACKNOWLEDGEMENTS are given in Table 1. The results are sorted by learner complexity. We would like to thank the Slovenian Research Agency for the 3 autoBOT feature spaces: https://skblaz.github.io/autobot/features.html 4 financing of the second researcher (young researcher grant) and Hate speech target classification model: https://huggingface.co/IMSyPP/hate_ speech_targets_slo the financial support from research core funding no. P2-103. The 33 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Pelicon et al. Table 1: Overview of the classification results. The SloBERTa model significantly outperforms all the other models and reaches inter-annotator agreement. Classification model Accuracy Macro Rec Macro Prec Macro F1 majority 40.79% 8.33% 3.40% 4.83% doc2vec 43.25% 20.65% 20.67% 19.76% AutoBOT-neural (9h) 45.79% 15.37% 20.00% 16.10% svm-word 50.39% 21.40% 25.75% 22.02% lr-word 50.39% 21.40% 25.75% 22.02% lr-char 51.21% 25.14% 28.17% 26.10% svm-char 51.90% 23.47% 27.59% 24.20% AutoBOT-neurosymbolic-lite (4h) 54.26% 27.34% 35.06% 28.90% Paraphrase-multilingual-mpnet-base-v2 + Linear SVM 55.40% 40.24% 44.29% 41.20% AutoBOT-symbolic (9h) 55.99% 29.68% 37.86% 31.32% AutoBOT-neurosymbolic-full (4h) 56.28% 32.29% 37.83% 33.07% SloBERTa 63.81% 53.03% 45.63% 48.28% Table 2: Most relevant features per feature subspace. Feature subspaces are ordered relative to their importance. Individual numeric values next to each feature represent that feature’s importance for the final learner. The features are sorted per-type. Note the word_features and their alignment with what a human would associate with hate speech. char_features ta s : 3.56 ni d : 2.73 lič : 2.69 ola : 2.58 ne m : 2.5 relational_features_token pa–3–je : 2.23 pa–2–se : 2.12 v–2–pa : 1.78 ne–1–pa : 1.75 v–2–se : 1.71 pos_features nnp nn nnp : 1.77 nnp jj nn : 1.75 nnp jj : 1.57 cc : 1.46 nn nn rb : 1.45 word_features idioti : 1.09 riti : 0.95 tole : 0.95 sem : 0.94 fdv : 0.93 relational_features_char e–3–d : 1.74 i–3–s : 1.56 n–3–z : 1.48 h–5–v : 1.43 z–4–t : 1.4 topic_features topic_12 : 0.14 topic_2 : 0.02 topic_0 : 0.0 topic_1 : 0.0 topic_3 : 0.0 keyword_features 007amnesia : 0.0 15sto : 0.0 24kitchen : 0.0 2pira : 0.0 2sto7 : 0.0 work was also supported by European Union’s Horizon 2020 re- [7] L. Martin, B. Muller, P. J. Ortiz Suárez, Y. Dupont, L. Ro- search and innovation programme project EMBEDDIA (grant no. mary, É. de la Clergerie, D. Seddah, and B. Sagot. 2020. 825153) and the European Union’s Rights, Equality and Citizen- CamemBERT: a tasty French language model. In Proceed- 5 ship Programme (2014-2020) project IMSyPP (grant no. 875263). ings of the 58th Annual Meeting of the Association for Com- putational Linguistics. Association for Computational Lin- REFERENCES guistics, Online, (July 2020), 7203–7219. [1] P. Badjatiya, S. Gupta, M. Gupta, and V. Varma. 2017. Deep [8] A. Pelicon, R. Shekhar, B. Škrlj, M. Purver, and S. Pol- learning for hate speech detection in tweets. In Proceedings lak. 2021. Investigating cross-lingual training for offensive of the 26th international conference on World Wide Web language detection. PeerJ Computer Science, 7, e559. companion, 759–760. [9] B. Ross, M. Rist, G. Carbonell, B. Cabrera, N. Kurowsky, [2] B. Evkoski, I. Mozetic, N. Ljubesic, and P. Kralj Novak. and M. Wojatzki. 2017. Measuring the reliability of hate 2021. Community evolution in retweet networks. arXiv speech annotations: the case of the european refugee crisis. preprint arXiv:2105.06214. arXiv preprint arXiv:1701.08118. [3] B. Evkoski, A. Pelicon, I. Mozetic, N. Ljubesic, and P. Kralj [10] B. Škrlj, M. Martinc, N. Lavrač, and S. Pollak. 2021. Autobot: Novak. 2021. Retweet communities reveal the main sources evolving neuro-symbolic representations for explainable of hate speech. (2021). arXiv: 2105.14898 [cs.SI]. low resource text classification. Machine Learning, 110, 5, [4] N. Ljubešić, D. Fišer, and T. Erjavec. 2019. The frenk datasets 989–1028. issn: 1573-0565. doi: 10.1007/s10994- 021- 05968- of socially unacceptable discourse in slovene and english. x. (2019). arXiv: 1906.02045 [cs.CL]. [11] M. Ulčar and M. Robnik-Šikonja. 2021. Slovenian RoBERTa [5] N. Ljubešić, D. Fišer, and T. Erjavec. 2014. TweetCaT: a contextual embeddings model: SloBERTa 2.0. Slovenian tool for building Twitter corpora of smaller languages. language resource repository CLARIN.SI. (2021). http:// In Proceedings of the Ninth International Conference on hdl.handle.net/11356/1397. Language Resources and Evaluation. European Language [12] T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. Resources Association (ELRA), Reykjavik, Iceland, (May Moi, P. Cistac, T. Rault, R. Louf, M. Funtowicz, J. Davison, 2014). S. Shleifer, P. von Platen, C. Ma, Y. Jernite, J. Plu, C. Xu, [6] S. Malmasi and M. Zampieri. 2018. Challenges in discrimi- T. Le Scao, S. Gugger, M. Drame, Q. Lhoest, and A. M. nating profanity from hate speech. Journal of Experimental Rush. 2019. HuggingFace’s Transformers: State-of-the-art & Theoretical Artificial Intelligence, 30, 2, 187–202. Natural Language Processing. ArXiv, abs/1910.03771. [13] M. Zampieri, S. Malmasi, P. Nakov, S. Rosenthal, N. Farra, 5 The content of this publication represents the views of the authors only and is their and R. Kumar. 2019. Predicting the Type and Target of sole responsibility. The European Commission does not accept any responsibility for use that may be made of the information it contains. Offensive Posts in Social Media. In Proceedings of NAACL. 34 SiDeGame: An Online Benchmark Environment for Multi-Agent Reinforcement Learning Jernej Puc Aleksander Sadikov jernej.puc@fs.uni- lj.si aleksander.sadikov@fri.uni- lj.si University of Ljubljana University of Ljubljana Faculty of Mechanical Engineering Faculty of Computer and Information Science Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT “capture the flag” in first-person view, while using similar input and output schemes to those of human players. However, the Modern video games present a challenging benchmark for ar- project is based on an inaccessible implementation of a funda- tificial intelligence research. Various technical limitations can mentally shallow game mode, which makes it untenable as a often lead to playing interfaces that are heavily biased in terms benchmark for reinforcement learning. Nonetheless, it shows a of ease of learning for either humans or computers, and it is dif- type of game that can suit the given requirements. ficult to strike the right balance. In this paper, a new benchmark The first-person shooter (FPS) genre has many interesting environment is presented, which emphasises the role of strategic representatives, some of which have already been repurposed elements by enabling more equivalent interfaces, is suitable for as reinforcement learning environments [4, 5]. Unsuitably, they reinforcement learning experiments on widely distributed sys- tend to revolve around simpler content, such as single-player tems, and supports imitation learning, as is demonstrated. The or deathmatch scenarios, and are not straight-forward for re- environment is realised as a team-based competitive game and searchers to customise. Indeed, accessibility and modifications its source code is openly available at a public repository. generally require developer support and cooperation [6]. KEYWORDS Confronted with this barrier, recent work on Counter-Strike: Global Offensive (CSGO) [6] resigned itself to the limits of imita- simulation environment, multi-agent system, deep neural net- tion learning, which could be facilitated by external recording of works, imitation learning, reinforcement learning public matches. Although CSGO’s standard competitive mode is 1 INTRODUCTION fittingly strategic, it, instead, focused on the mentioned death- match, and withheld information from agents by ignoring sound Reinforcement learning is a powerful concept that can be used and having them use cropped and downscaled image inputs with to take on highly complex challenges. In its advancement, video common information omitted or rendered unrecognisable. games have emerged as suitable benchmarks: they define clear This paper also considers imitation learning, in attempt of goals, allow agents to be compared between themselves and with establishing a baseline and starting point for eventual reinforce- humans, and, in comparison to preceding milestones [7], they ment learning, akin to the approach of AlphaGo [7] and AlphaS- begin to incorporate complexities of the real world. tar [8]. The deep neural network architecture that was used Success has been achieved even in notably difficult tasks, such in these experiments accepts audio inputs similarly to instances as the modern games of StarCraft II [8] and Dota 2 [1]. However, from the literature [3], which convert sounds into their frequency being modern games, the authors were forced to compromise: domain representations using the discrete Fourier transform. the intricate and graphically intensive input spaces had to be sim- plified and transformed, while combinatorically overwhelming 3 THE SDG ENVIRONMENT action spaces were functionally changed until superhuman per- SiDeGame relies on the game rules of CSGO to provide a founda- formances could, as well, be attributed to advantages of different tion of notable depth. Crucially, the observation space is simpli- playing conditions. fied by viewing the environment from a top-down perspective Search for examples that could compare in strategic depth and in low resolution to allow modern deep neural networks to pro- cultivate a competitive player base, while enabling consistent cess it directly. Consequently, not all aspects of the game could interfaces and being open to researchers leaves few options but be reasonably adapted and the action space could not be fully to create one anew. This has led us to create SiDeGame, the preserved, yet the playing experience remains egocentric and is “simplified defusal game” (abbrev. SDG), which incorporates key largely consistent with true first-person control schemes. rules of an established video game title in a computationally and perceptively simpler simulation environment, accessible at: 3.1 Description https://github.com/JernejPuc/sidegame-py By the rules carried over from CSGO, two teams of 5 players each 2 RELATED WORK asymmetrically compete in attack and defence: the goal of one team is to detonate a bomb at one of two preset locations, while Importance of an even playing field has been emphasised by the goal of the other is to prevent them from doing so. After a authors of the For The Win (FTW) agents [4], playing a form of certain number of rounds, the teams switch sides, and the first Permission to make digital or hard copies of part or all of this work for personal to pass a threshold of rounds won is declared the winner. or classroom use is granted without fee provided that copies are not made or In the course of a round, players must navigate a map, an 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 artificial environment with carefully placed tactical elements of work must be honored. For all other uses, contact the owner /author(s). various degrees of passage and cover. Besides weaponry, a player Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia can utilise auxiliary equipment, the availability of both of which © 2021 Copyright held by the owner/author(s). depends on prior survival and economic rewards. 35 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Jernej Puc and Aleksander Sadikov Figure 1: Screenshots of various views encountered in SiDeGame. Additionally interesting for AI research are aspects of the be eventually expressed, causing unintended consequences and game that encourage or demand active coordination, such as leading to practically unplayable conditions. Training regimes shared economy, unassigned roles, and imperfect information on should, for example, reduce the regularity of sampling, bound teammates’ status and surroundings. sampling within acceptable thresholds, or use more sophisticated contextual rules to confirm the agent’s intent. 3.2 Observations 3.4 Execution The majority of information is provided through the image dis- play, several screenshots of which can be seen in Figure 1. Images Multi-agent interaction is built upon separate server and client are generated at a low base resolution of 256×144 pixels, con- processes regularly exchanging state and event information via straining the visual elements to be small and carefully placed, packet communication using the UDP protocol. Simulations are while remaining easily distinguishable. The human interface sim- intended to run in real-time, but can have their tick rate and time ply upscales the display with nearest neighbour interpolation, scale adjusted on both authoritative and local ends. ensuring equivalence of available information. With the exception of pixel-wise iteration for tracing lines of The main view is based on projection of the radar image of a sight and disregarding the dependencies of imported extensions, classic CSGO map, Cache, which has only minor vertically over- the environment is fully implemented in the Python program- lapping components and thus proved easiest to adapt. Alternative ming language. Despite clear inefficiencies, this development views include the inventory wheel, map plan, and communica- choice streamlines integration with machine learning solutions, tion wheels. The latter are used to construct short messages of which predominantly relate to the Python ecosystem, and eases grounded signs that are appended to the chat log in the sidebar code readability and customisation. Server and client processes and allow explicit coordination within the team. are spawned as single Python processes that are restricted to the Since projection is egocentric, the prominent role of sound CP U, enabling mass parallelisation and preserving GP U resources is retained: other agents out of line of sight may still give off for learning processes. some information regarding their relative position, equipment, For AI agents, development targeted 30 updates per second, and preparedness. To support the advantages of awareness of which had been deemed acceptable to human opponents, al- sound, spatial audio is implemented by convolving sound signals though higher tick rates can be achieved at both the original with HRIR filters [2], while amplitude and frequency attenuation (144p) and reasonably upscaled (e. g. 720p) resolutions. This could characteristics were empirically formulated. SiDeGame supports also be used to speed up the simulation, subject to the computa- conversion of sounds into spectral vectors, which were used in tional stability and potential overhead of a specific configuration. the experiments of this work directly, but can also be accumulated and later processed in the form of a spectrogram. 3.5 Online Play If there is a delay between action inference and its effect in the In the context of agent evaluation and comparison, capability of environment, an input analogous to proprioception can also be online play, where actors, both human and artificial, can com- considered. It can be trivially simulated by tracking the effective pete remotely and without having to share their program, is an mouse and keyboard states, i. e. which keys are pressed and how essential component, as outcomes of adversarial games cannot the cursor is moving at a given time. be compared in isolation. Feasible physical distance between actors in a match is expe- 3.3 Actions rientially limited by temporal delays that arise from communi- The game expects 19 binary inputs, corresponding to distinct key cation steps in the client loop. Inclusion of select networking presses, one ternary value for scrolling the chat log, and two real concepts, such as client-side state prediction and reconciliation, values for controlling cursor movement. In general, combinations foreign entity interpolation, and server-side lag compensation, of these can legitimately be executed simultaneously, providing should maintain playable conditions to a large extent even among no benefit to the use of compound actions. international participants. It should be noted that some of the keys, pertaining to al- In extrapolation, online play could also support widely dis- ternative views or otherwise functional when kept held down, tributed multi-agent reinforcement learning experiments in the expect unperturbed presses lasting several seconds. For stochastic form of large-scale population-based training [4, 8]. These are policies, where actions during training are sampled, this dura- subject to training and inference data transfer constraints, which tion could be long enough to cause even minute probabilities to can be alleviated by slowing down the simulation and having the 36 An Online Benchmark Environment for Multi-Agent Reinforcement Learning Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Mouse/kbd. state data pass fewer bottlenecks. In a general configuration, multiple process groups each reserve a subset of agents (unique model Spectra parameters) from the global pool and train them with locally Mouse/kbd. distributed processes, while their instances participate in shared state CNN RNN matches, as depicted in Figure 2. RNN RNN FC Cutout coords. Global Model controller Image Conv params. CNN RNN a) CNN Cutout coords. b) 1 2 N CNN Inf. Opt. Inf. Opt. Inf. Opt. Figure 3: The deep neural network architecture used in our experiments: The visual (red), audio (blue), and c) mouse/keyboard state (yellow) encoding pathways con- Auth. srv. verge in the recurrent core (green). Moreover, visual encod- simulations ing splits off into focused encoding by cropping the input image as specified by the cutout coordinates (orange). Figure 2: Online multiplayer reinforcement learning: a) The global controller process oversees all of the models many of them and is relatively dense, hinting at the inevitability in a population of agents, ensuring they are not simultane- that not all bits of visual information can be equally accounted ously being updated by any two process groups. b) Process for at any given time. Generally, this could be addressed with groups consist of a local controller and locally distributed sufficiently high model capacity and appropriate use of attention- inference, optimisation, and actor processes. c) All actor based layers. In this work, however, the visual pathway was instances may interact through remote environments sim- explicitly split into primary and focused visual encoding, based ulated by authoritative servers. on the intuition of human visual perception, where only a small part of our field of view is perceived in sharp detail. Instead of ingesting full-scale image data, focused visual en- 3.6 Replay System coding processes cutouts of much smaller size, so that singular entities can be unambiguously observed. The cutout coordinates The packets of information that a client exchanges with the are obtained from a spatial probability distribution along with fu- server in the course of a session are made to be sufficient to ture mouse and key states as outputs of the network. If they were, faithfully reproduce the player’s perspective. Byte strings can be instead, determined internally, the cropping operation would gathered, annotated, and saved as binary files, which can then be need to be differentiable, which could prove hard to satisfy. replayed in real-time or manually stepped to inspect and extract the player’s observations and actions, statistics, or other aspects 4.2 Imitation Learning of the underlying game state. Replays are an important resource Imitation learning aims to align the agent’s behaviour to that of for review and analysis of competitive games, but were primarily a number of demonstrators, e. g. experienced humans. Among its included in SiDeGame for the purposes of imitation learning. basic methods is behavioural cloning, which relies on a dataset 4 SUPERVISED LEARNING BASELINE 𝐷 = {{𝑜 } }} of pairs of observations 1, 𝑎1 , . . . , {𝑜 , 𝑎 𝑜 and target 𝑁 𝑁 actions 𝑎. The agent with parameterisation 𝜃 is tasked to predict Within the limits of available computational resources and in for each observation 𝑜 such an action ˆ 𝑎 to satisfy the following 𝑖 𝑖 view of the scale of exemplary projects [1, 8], the estimated level optimisation problem: of parallelisation, required for meaningful results of reinforce- 𝑁 ment learning experiments in an acceptable time frame, could ∗ 1 Õ 𝜃 = arg min 𝐿 (𝑎 , ˆ 𝑎 ), (1) not be reached. Instead, a baseline and a starting point for rein- 𝑖 𝑖 𝑁 𝜃 𝑖 = 1 forcement learning was attempted to be achieved with imitation learning, a form of supervised learning from demonstrations. where the loss function 𝐿, evaluating similarity between predicted and imitated actions, is dependant on the form of the action space. 4.1 Agent Model Architecture In this experiment, all outputs of the model were made discrete and the loss function formulated as an average of cross-entropy The agent’s policy was modelled as a parameterised deep neural terms for 𝑇 sub-actions of 𝐶 categories: network according to the architecture depicted in Figure 3. The model is composed of common elements: residual convolu- 𝑇 𝐶𝑡 Õ Õ 𝑡 ,𝑐 𝑡 ,𝑐 tional blocks, recurrent cells, and fully-connected layers, forming 𝐿 (𝑎 , ˆ 𝑎 ) = − 𝑎 log ˆ 𝑎 (2) 𝑖 𝑖 𝑖 𝑖 recognisable sub-networks, such as the recurrent core, which 𝑡 = 1 𝑐 = 1 provides the agent with memory and delay compensation, input After the gradients are numerically computed with regards to encoding pathways, and distinct output heads. the depth of truncated backpropagation through time, parame- The irregularity of visual encoding stems from the considera- ter updates are applied using one of the standard optimisation tion that, while visual elements are simple, the display includes algorithms. 37 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Jernej Puc and Aleksander Sadikov 4.3 Demonstrations It seemed to respond to the presence and movement of other entities in its vicinity, was able to navigate across the map towards A collection of replays was recorded from a short session between a tactical objective without hindering collisions and seemingly 10 demonstrators of negligible experience with SiDeGame, but hide behind cover, but failed to demonstrate offensive behaviour. with varying degrees of familiarity with related video games. Seven hours or 770,000 samples of total play were obtained at 5 CONCLUSIONS & FUTURE WORK 30 frames per second, which is unideally low, especially since samples and episodes are highly correlated. Attributing the shortcomings of recent works in deep reinforce- Main sub-actions were extracted from mouse and keyboard ment learning to inconsistencies between human and AI inter- states, while focused cutout coordinates would require logistical faces, a new benchmark environment has been created in the and sensory measures that were infeasible to procure. Instead, form of a lightweight multi-agent game with various tools for the coordinates were manually labelled by viewing replays at 75% training and evaluation of agents. In addition to addressing these speed and tracing paths between estimated points of contextual concerns, the simulation environment is based on a renowned tac- interest. These labels, while not ideal, fared noticeably better tical video game, providing interesting challenges for AI research, than synthetically generated pseudo-labels. particularly in domains of sound and explicit communication. Amid data extraction, observation-action pairs had actions In approaching the game with imitation learning, the trained shifted by 6 steps, conditioning the model to predict actions after agent failed to develop practically meaningful behaviours when a temporal delay close to the human response time. trained on arguably few demonstrations and was found lack- ing as a starting point for reinforcement learning experiments. 4.4 Results Nevertheless, the presented agent model architecture is general enough to be applicable to other common tasks with standard The neural network, consisting of approx. 2.9M parameters, and computer peripherals and lends itself to further experimentation. training procedure were implemented using the PyTorch package. Online characteristics of the created environment hint at its po- For training, a machine with 4 Nvidia 1080Ti GP Us was avail- tential for large-scale reinforcement learning experiments, with able. Each GP U corresponded to an optimisation process, which its accessibility and adaptability allowing the AI community to received an approximately equal share of training sequences and explore this and other directions. At the same time, certain com- progressed them chronologically in batches of 12 sequences and ponents of the environment that are not specific to AI research epochs of 30 steps. After every epoch, the gradients with regard to could also prove useful to a wider community, outside of the the loss were computed with truncated backpropagation through scope of its primary intent. time separately on each GP U, synchronously averaged between them, and used to separately update their copy of the model pa- REFERENCES rameters using the AdamW optimisation algorithm with a cosine 1-cycle learning rate schedule. [1] Christopher Berner et al. 2019. Dota 2 with large scale The main training process ran for 300,000 steps over 6 days. deep reinforcement learning. CoRR, abs/1912.06680. arXiv: The large variance in the loss in Figure 4 can be attributed to 1912.06680. http://arxiv.org/abs/1912.06680. differences between game phases and subtler characteristics of [2] Fabian Brinkmann et al. 2017. A high resolution and full- demonstrators, which were found to be distinct from degrees of spherical head-related transfer function database for differ- capability and activity. ent head-above-torso orientations. J. Audio Eng. Soc, 65, 10, 841–848. doi: 10.17743/jaes.2017.0033. http://www.aes.org/ Loss value Cross entropy terms e- lib/browse.cfm?elib=19357. 1.0 7 Focal coords. [3] Shashank Hegde, Anssi Kanervisto, and Aleksei Petrenko. Keys (sum) 0.8 6 Keys (average) 2021. Agents that listen: high-throughput reinforcement 5 Ver. mouse mvmt. 0.6 learning with multiple sensory systems. CoRR, abs/2107.02195. 4 Hor. mouse mvmt. arXiv: 2107.02195. https://arxiv.org/abs/2107.02195. 0.4 3 [4] Max Jaderberg et al. 2018. Human-level performance in 2 0.2 first-person multiplayer games with population-based deep 1 0.0 0 reinforcement learning. CoRR, abs/1807.01281. arXiv: 1807. 0 75000 150000 225000 300000 0 75000 150000 225000 300000 Update step Update step 01281. http://arxiv.org/abs/1807.01281. [5] Michal Kempka et al. 2016. ViZDoom: A Doom-based AI research platform for visual reinforcement learning. CoRR, Figure 4: Loss progression over the course of training. Left: abs/1605.02097. arXiv: 1605 . 02097. http : / / arxiv. org / abs / Average loss value enveloped by minimum and maximum 1605.02097. evaluations. Right: Averages of constituent terms. [6] Tim Pearce and Jun Zhu. 2021. Counter-Strike deathmatch with large-scale behavioural cloning. CoRR, abs/2104.04258. Figure 4 shows that, by the end of the training schedule, only arXiv: 2104.04258. https://arxiv.org/abs/2104.04258. imitation of focal coordinates leaves room for improvement, [7] David Silver et al. 2016. Mastering the game of go with while other terms in the loss function have already overfitted. deep neural networks and tree search. Nature, 529, 7587, Due to the relatively small size of the network, overfitting had 484–489. issn: 1476-4687. doi: 10.1038/nature16961. https: been underestimated, although the outcome could have been //doi.org/10.1038/nature16961. inevitable with the given amount of data. [8] Oriol Vinyals et al. 2019. Grandmaster level in StarCraft II In practice, the trained agent’s behaviour was greatly sensitive using multi-agent reinforcement learning. Nature, 575, 7782, to even imperceptibly slight changes in starting conditions. Its 350–354. issn: 1476-4687. doi: 10.1038/s41586- 019- 1724- z. switching between alternative views was debilitatingly chaotic https://doi.org/10.1038/s41586- 019- 1724- z. and had to be suppressed to allow expression of other behaviours. 38 Question Ranking for Food Frequency Questionnaires Nina Reščič Mitja Luštrek nina.rescic@ijs.si mitja.lustrek@ijs.si Department of Intelligent Systems, Jožef Stefan Institute Department of Intelligent Systems, Jožef Stefan Institute Jožef Stefan International Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT This paper explores the ranking of questions and is the next step from our previous work. With ranking the questions by im- Food Frequency Questionnaires (FFQs) are probably the most portance and asking them in the ranked order, it can be expected commonly used dietary assessment tools. In the WellCo project, that quality of predictions will improve with each additional we developed the Extended Short Form Food Frequency Question- answer and we are not limited with the constraint that certain naire (ESFFFQ), integrated into a mobile application, in order to number of questions should be answered. We addressed the prob- monitor the quality of users’ nutrition. The developed question- lem as a single-target problem for classification and regression. naire returns diet quality scores for eight targets — fruit intake, vegetable intake Additionally, we tested the algorithms on different representa- , fish intake, salt intake, sugar intake, fat intake, fi- bre intake tions of features for both type of problem. The findings of this and protein intake. This paper explores the single-target paper could be used for setting the baseline for our future re- problem of question ranking. We compared the question ranking search. of the machine learning algorithms on three different types of features for classification and regression problems. Our findings 2 METHODOLOGY showed that the addressing problem as a regression problem performs better than treating it as a classification problem and 2.1 Problem outline the best performance was achieved by using a Linear Regression In our previous research [6, 7] we tried to find subsets of questions on features, where answers were transformed to frequencies of that would allow us to ask the users about their dietary habits consumption of certain food groups. with as few questions as possible and still get sufficient informa- tion to evaluate their nutrition. For this we used the Extended KEYWORDS Short Form Food Frequency Questionnaire (ESFFFQ) [5]. The nutrition monitoring, FFQs, question ranking questionnaire returns diet quality scores scores for fruit intake, vegetable intake, fish intake, salt intake, sugar intake,fat intake, fibre intake and protein intake. We calculate the nutrient intake 1 INTRODUCTION amounts and from there we further calculate the diet quality Adopting and maintaining a healthy lifestyle has become ex- scores. tremely important and healthy nutrition habits represent a major The questionnaire was included in a mobile application, where part in achieving this goal. Self-assessment tools are playing a big the system asked the users about their diet with one or two role in nutrition monitoring and many applications are including questions per day. The answers were saved into a database and Food Frequency Questionnaires (FFQs) as a monitoring tool, due every fortnight the quality scores were recalculated. As it could to they in-expensiveness, simplicity and reasonably good assess- happen that the users did not answer all the questions by the ment [8, 3]. An FFQ is a questionnaire that asks the respondents time the recalculation was done, it was of great importance to ask about the frequency of consumption of different food items (e.g., the questions in the right order. In the terminology of machine "How many times a week do you eat fish?"). In the EU-funded learning this would be a feature ranking problem. We explored project WellCo we developed and validated an Extended Short the problem as a set of single-target problems — separately for Form Frequency questionnaire (ESFFFQ) [5] that was included individual outcome scores. As three of the diet quality scores in a health coaching application for seniors. (fruit, vegetable and fish intake) are only dependent on one or two Cade et al. [2] suggest that for assessment of dietary data short questions, the problem of feature ranking is trivial. Therefore we FFQs could be sufficient and that marginal gain in information is explored the problem for the remaining five targets — fat intake, decreasing with extensive FFQs. Block et al. [1] concluded that sugar intake, fibre intake, protein intake and salt intake. longer and reduced return comparable values of micronutrients intake. Taking this idea a step forward, we explored the possi- 2.2 Dataset bilities to get the most information even if one does not answer We got the answers to ESFFFQ from 92 adults as a part of the the whole questionnaire. In our previous work we explored how WellCo project and additionally from 1039 adults included in to find the smallest set of questions that still provides enough SIMenu, the Slovenian EUMenu research project [4]. The ques- information by applying different feature selection techniques tions included in the ESFFFQ were a subset of the questions in the [6, 7]. FFQ in SIMenu. Furthermore, the answers (consumption frequen- cies) were equivalent in both questionnaires, and consequently Permission to make digital or hard copies of part or all of this work for personal extracting the answers from SIMenu and adding them to the or classroom use is granted without fee provided that copies are not made or answers from the ESFFFQ was a very straightforward task. 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). 2.3 Feature ranking Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia To do the experiments, we first randomly split the data into © 2021 Copyright held by the owner/author(s). validation and training sets in ratio 1:3. To train the models and 39 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Reščič et al. rank the features we then used 4-fold cross-validation on the frequencies or amounts, we get better results on the validations training set and used the average feature importance from all 4 set than with RF. folds as the final feature ranking. The ranked features were used to predict quality scores (clas- sification problem) and nutrient amount (regression problem), by adding the question as they were ranked. In this paper we present the results for two commonly used machine learning algorithms — Logistic/Linear Regression and Random Forest Classifier/Regressor. To rank the features we used the absolute value of the coefficients in the Linear/Logistic Regression and the feature_importance attribute as implemented in the Random Forest Classifier/Regressor in the sklearn library. Additionally we compared different feature representations — Figure 1: Results on validation set for fat intake features where answers are represented with nominal discrete equidistant values (once per week is represented as integer 2), Sugar. For sugar intake the story is very similar. RF performed features where answers were transformed into frequencies of fairly well for the first few questions and then the accuracy began consumption (once per week is represented as approx. 0.14 per to fall. The best performing algorithm was the LR on the features day) and features where answers were transformed into amounts (Figure 2, where the answers were transformed into frequencies. of nutrients (once per week is represented as grams/day). In the last represenation, the features differed between the targets sugar, fat, salt, fibre and protein. We ran the experiments for five diet categories (fat intake, sugar intake, fibre intake, protein intake and salt intake) for both classification and regression problem. In both cases we started with the best ranked question, trained the model and compared results on train and validation sets. Then we added the second best ranked question, trained the models and compared the results. We added the questions one by one until the last one. Figure 2: Results on validation set for sugar intake 3 RESULTS 3.1 Classification problem Fibre. For fibre intake the RF algorithms performed better for a very long time (Figure 3) and it reached the best accuracy after For classification we tried to predict the quality scores for each of 6 questions. The LR performed worse, and it did similarly badly the five nutrition categories. There were three scores - 2 (good), on the training set as well. 1 (medium) and 0 (bad). The distribution of the scores for all the categories is shown in Table 1. Table 1: Distribution of target values for classification Score Fat Sugar Fibre Protein Salt 2 51% 74% 26% 79% 32% 1 31% 14% 22% 13% 47% 0 18% 12% 52% 8% 21% Figure 3: Results on validation set for fibre intake We compared Random Forest Classifier and Logistic Regres- sion for three different types of features - discrete equidistant Protein. For protein intake (Figure 4) the results are similar to answers, answers transformed to frequencies and answers trans- those for fibre intake. However, in case of protein intake the formed to amounts. majority class is 79% and most of the algorithms almost never Fat. exceeded this value. For Random Forest (RF) there was not a big difference be- tween the three representations of the features. With all three, the highest accuracy on the validation set (79%) is achieved with 5 questions and afterwards the accuracy starts falling and stays on the interval between 75% and 79%. This clearly indicates over- fitting, which is confirmed by the fact that the accuracy for RF on the training set was 100% from the fifth question. A similar situation happened for all the remaining targets and will not be repeated in the following subsections. On the training set Lo- gistic Regression (LR) had worse results than the RF and it also performed the worst from all algorithms when run on the dis- Figure 4: Results on validation set for protein intake crete features. However, when the features are transformed into 40 Question Ranking for Food Frequency Questionnaires Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Salt. For salt intake the best model is the LR on the answers transformed to amounts. As seen in Figure 5, it exceeded the RF algorithms for almost 20% from eleventh added question on and predicted the quality scores with more than 90% accuracy with only 14 questions, which is half of the questionnaire. Figure 7: Results on validation set for sugar intake Fibre. Classification for fibre intake was very bad, however, when considering it as a regression problem, the LR on ’frequency’ Figure 5: Results on validation set for salt intake features’ predicted the amounts with error smaller than 2 grams when more than eleven questions were used 8. Considering Table 2 this means that predicting how bad/good the fibre intake was 3.2 Regression problem done better then predicting if it is bad or good. While knowing the quality score is a valid first information whether one’s diet is good or not, generally more interesting information is how good (or how bad) it really is. Therefore it is reasonable to look at the same problem as a regression problem , where we try to predict the actual amount (in grams) of con- sumed nutrients. Again we explored the performance of Random Forest Regressor (RF) and Linear Regression (LR) on the three previously described feature sets. Table 2: Nutrient intake in grams/day to quality scores Score Fat[g] Sugar[g] Fibre[g] Protein[g] Salt[g] Figure 8: Results on validation set for fibre intake 2 ≤ 74 ≤ 55 ≥ 30 ≥ 55 ≤ 6 1 else else else else else 0 ≥ 111 ≥ 82 ≤ 25 ≤ 45 ≥ 9 Protein. For protein intake all algorithms had a similar perfor- Fat. mance up to ten included questions, however, the LR on the The best performing algorithm for fat intake was the LR on ’frequency features’ started to perform better and better with the answers transformed to frequencies. The overfitting of the RF each added questions and predicted the amount of protein con- is even more visible than with the classification problem as the sumption with error of 5 grams (Figure 9). errors for these models did not fall under 20 grams even if all the questions were used, while the error of the LR on the feature sets where the answers are transformed to frequencies or amounts was smaller than 5 grams from eleven included questions (Figure 6). Figure 9: Results on validation set for protein intake Figure 6: Results on validation set for fat intake Salt. Similarly to the protein intake all algorithms performed Sugar. Similarly to fat intake, LR with the ’frequency features’ with a comparable error up to nine included questions, and after performed best (Figure 7). However the LR on the ’amounts fea- that LR using the features transformed to frequencies started to tures’ performed well for more than 15 questions, but predicted perform way better and predicted salt intake with error smaller the worst for the first eleven included questions. than 1 gram with eleven included questions (Figure 10). 41 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Reščič et al. several nutrition quality scores but still would want to avoid answering too many questions. Next, probably more important and interesting research problem, is how to use the answers already provided to our advantage — so instead of statically ranking the questions we would rather explore how we could improve the prediction performance by dynamically ranking and asking the questions. ACKNOWLEDGMENTS Figure 10: Results on validation set for salt intake WellCo Project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769765. 3.3 Discussion The authors acknowledge the financial support from the Slove- nian Research Agency (research core funding No. P2-0209). We compared performance of feature ranking for two different The WideHealth project has received funding from the Euro- machine learning algorithms on three different types of features pean Union’s Horizon 2020 research and innovation programme for both classification and regression problems. While the classi- under grant agreement No 95227. fication problem might give the general idea about one’s dietary habits, it is inclined towards overfitting even for very simple mod- REFERENCES els, such as Logistic Regression, while more complex algorithms, [1] Block G, Hartman AM, and Naughton D. 1990. A reduced Random Forest Classifier in our case, are even more subject to dietary questionnaire: development and validation. Epi- this deficiency. By predicting amounts instead of quality scores, demiology, 1, 58–64. doi: 10 . 1097 / 00001648 - 199001000 - one gets information about how good/bad the dietary habits are 00013. instead of just if they are good or bad. [2] Cade J., Thompson R., Burley V., and Warm D. 2002. Devel- Transforming features from discrete equidistant values to fre- opment, validation and utilisation of food-frequency ques- quencies or amounts of nutrients proved to be a very good ap- tionnaires – a review. Public Health Nutrition, 5, 4, 567–587. proach. The transformation gave better results for both classifi- doi: 10.1079/PHN2001318. cation and regression problem for both Random Forest Regres- [3] Shim JS, Oh K, and Kim HC. 2014. Dietary assessment meth- sor/Classifier and Logistic/Linear Regression. While the perfor- ods in epidemiologic studies. Epidemiol Health, 36. doi: mance of both algorithms on features transformed to frequencies 10.4178/epih/e2014009. and features transformed to amounts for the classification prob- [4] Gregorič M, Blaznik U., Delfar N., Zaletel M., Lavtar D., lem was comparable, and Linear Regression on features trans- Koroušić-Seljak B., Golja P., Zdešar Kotnik K., Pravst I., formed to amounts gave markedly better results for salt intake, Fidler Mis N., Kostanjevec S., Pajnkihar M., Poklar Vatovec the Linear Regression on features transformed to frequencies T., and Hočevar-Grom A. 2019. Slovenian national food outperformed all other combinations of features and algorithms consumption survey in adolescents, adults and elderly : for the regression problem for all of the targets. The reason for external scientific report. EFSA Supporting Publications, 16, this is that linear regression on amounts is a very good match in 11, 1729E. doi: 10.2903/sp.efsa.2019.EN- 1729. the sense that the target variable (total amount) is the sum of all [5] Reščič N., Valenčič E., Mlinarič E., Seljak Koroušić B., and features (partial amounts). Luštrek M. 2019. Mobile nutrition monitoring for well- Transforming the features to frequencies instead to amounts being. In (UbiComp/ISWC ’19 Adjunct). Association for has another advantage — frequencies transformed to amounts are Computing Machinery, London, United Kingdom, 1194–1197. specific to each target, while features transformed to frequencies doi: 10.1145/3341162.3347076. are equal for all targets. This is an important finding for possible [6] Reščič N., Eftimov T., Koroušić Seljak B., and Luštrek M. future research where one would address ranking of questions as 2020. Optimising an ffq using a machine learning pipeline a multi-target problem. Additionally, regression problem using to teach an efficient nutrient intake predictive model. Nu- Linear Regression on features transformed to frequencies could trients, 12, 12. doi: 10.3390/nu12123789. solve as a baseline for future experiments. [7] Reščič N., Eftimov T., and Seljak Koroušić B. 2020. Com- 4 CONCLUSION AND FUTURE WORK parison of feature selection algorithms for minimization of target specific ffqs. In 2020 IEEE International Conference on Ranking the questions of FFQs when it could be expected that not Big Data (Big Data), 3592–3595. doi: 10.1109/BigData50022. all of the questions will be answered is an important step when 2020.9378246. building models for predicting quality of one’s diet. In this paper [8] Thompson T. and Byers T. 1994. Dietary assessment re- we compared two feature ranking algorithms on three different source manual. The Journal of nutrition, 124, (December types of features for classification and regression problem for 1994), 2245S–2317S. doi: 10.1093/jn/124.suppl_11.2245s. five targets. The findings of this paper show that considering the problem as a regression problem on features transformed to frequencies and using a simple machine learning algorithms (Linear Regression) gives the best results for all five targets and provides baseline for future experiments. There are several possibilities for future work. As hinted in the previous section, the question of multi-target question ranking is one of the first that appears — one might want to monitor 42 Daily Covid-19 Deaths Prediction For Slovenia David Susič "Jožef Stefan" Institute Ljubljana, Slovenia david.susic@ijs.si ABSTRACT related government interventions (school closing, workplace clos- ing, cancel public events, restrictions on gatherings, close pub- In this paper, models for predicting daily Covid-19 deaths for lic transport, stay at home requirements, restrictions on inter- Slovenia are analysed. Two different approaches are considered. nal movement, international travel controls, public information In the first approach, the models were trained on the fist wave campaigns, testing policy, contact tracing, and facial coverings), dataset of state intervention plans, cases and country-specific Covid-19 related cases and deaths, and some static data, in par- static data for 11 other European countries. The models with the ticular the country’s population, population density, median age, best performance in this case were the k-Nearest Neighbors re- percentage of people over 65, percentage of people over 70, gdp gressor and the Random Forest regressor. In the second approach, per capita, cardiovascular death rate, diabetes prevalence, per- a time-series analysis was performed. The models used in this centage of female and male smokers, hospital beds per thousand case were Seasonal Autoregressive Integrated Moving Average people, and life expectancy. To suppress anomalies in registered Exogenous and Feed forward Neural Network. For comparison, cases on Sundays and holidays, a 7-day moving average was all 4 models were tested on the second wave for Slovenia and used for both cases and deaths. The dataset covers the European the model with the best performance was Feed forward Neural countries of Slovenia, Italy, Hungary, Austria, Croatia, France, Network, with a mean absolute error of 1.34 deaths. Germany, Poland, Slovak Republic, Bosnia and Herzegovina, and KEYWORDS the Netherlands from January 22, 2020 to December 11, 2020. All of the countries chosen for this study are geographically next to Covid-19, deaths, predictions, machine learning one another and are thus expected to have similar course of epi- demic. The data on government interventions, cases and deaths are derived from the "COVID-19 Government response tracker" 1 INTRODUCTION database, collected by Blavatnik School of Government at Oxford The aim of this analysis is to find out whether we can predict University [4]. The intervention values range between 0-4 and Covid-19 deaths for Slovenia based on the characteristics of the represent their strictness, for example, if only some or all schools epidemic in other European countries, and whether we can pre- are closed. The static data are collected from a variety of sources dict deaths based on a time series analysis of historical data (e.g. (United Nations, World Bank, Global Burden of Disease, Blavat- predicting for the second wave based on the first wave infor- nik School of Government, etc.) [3]. The original data are publicly mation). The main advantage of the first approach is that we available online. The processed data used for the purpose of this do not need historical case and death data for the country for study can be found online at https://repo.ijs.si/davidsusic/covid- which we are making a prediction (in this case Slovenia), while seminar-data. the second approach is generally more accurate but relies on historical death data. The aim is also to find out which of the two 3 METHODS AND MODELS approaches provides more accurate predictions. It is important Two different approaches were considered for the analysis. For to note that although this is a study for Slovenia, the results can the first part of the analysis, referred to as the country-specific be interpreted as a general assessment of the effectiveness of the approach, the models were trained on the data of government methods described for predicting Covid-19 deaths and can be intervention plans, cases, deaths and country-specific static data applied to any country for which the data are available. for the 10 other European countries, with the aim of predicting The data used in this analysis are described in Section 2. Sec- deaths for Slovenia. In this case, the predictions were made for tion 3 provides a description of the approaches and the models. each day, disregarding the time order. For the second part of the Section 4 contains a discussion of the determination of the opti- analysis, a time series prediction was performed, using only the mal parameters of the selected models. The results are given in daily deaths for Slovenia as data. Section 5. The conclusion, along with ideas for possible improve- ments, is given in Section 6. 3.1 Country-Specific Approach 2 DATA DESCRIPTION AND PREPARATION In the country-specific approach, the selection of the base model was very important, as models that perform worse than the base The data used in this paper consist of daily Covid-19 related model are not worthy of interpretation. The baseline was defined features at the country level. It contains 12 different Covid-19 as 𝑁 (𝑡 ) = 𝑁 (𝑡 − 14) · 𝑀, (1) deaths cases 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 where 𝑀 = 0.023 is the mortality rate factor of those infected, 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 calculated as a weighted average of the mortality rates of the work must be honored. For all other uses, contact the owner /author(s). countries included in this study [2], and 𝑡 denotes a specific Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia day. This simple model implies, that the number of deaths on © 2021 Copyright held by the owner/author(s). a given day 𝑡 is equal to the number of new infections on the 43 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia David Susič day 𝑡 − 14, multiplied by the mortality rate factor. The regres- sor model that were tested are: Random Forest (RF), k-Nearest 0.10 Neighbors (KNN), Stochastic Gradient Descent, Ridge, Lasso, and Epsilon-Support Vector. Description of all of the models can be Base found in the Python scikit-learn documentation [5]. The two that MAE 0.05 KNN performed significantly better than the baseline were the KNN regressor and RF regressor. Other regression models performed RF the same or worse than the baseline model and were thus not used in the further analysis. All models were tested in the 10-fold −28 −24 −20 −16 −12 −8 −4 0 cross-validation with the performance measures mean absolute Lookback [days] 2 error (MAE), mean squared error (MSE) and 𝑅 score on the data subset that does not include Slovenia. The measures are defined as: 𝑛−1 1 Õ 0.04 MAE (𝑦, ˆ 𝑦 ) = |𝑦 − ˆ 𝑦 |, (2a) Base 𝑖 𝑖 𝑛 𝑖 =0 KNN 𝑛−1 MSE 0.02 1 Õ RF MSE (𝑦, ˆ 𝑦 ) = (𝑦 − ˆ 𝑦 )2 , (2b) 𝑖 𝑖 𝑛 𝑖 =0 0.00 Í𝑛 (𝑦 − ˆ 𝑦 )2 𝑖 𝑖 2 𝑖 =1 𝑅 (𝑦, ˆ 𝑦 ) = 1 − , (2c) −28 −24 −20 −16 −12 −8 −4 0 Í𝑛 (𝑦 − ¯ 𝑦 )2 𝑖 𝑖 𝑖 =1 Lookback [days] where ˆ 𝑦 is the predicted value of the 𝑖 -th sample, 𝑦 is the 𝑖 corresponding true value, n is the sample size and ¯ 𝑦 is the average Í𝑛 true value ¯ 𝑦 = 1 𝑦 . 1 𝑛 𝑖 =1 For each sample, additional features of the government inter- 1.0 ventions and cases were added for the previous days. The number Base of previous days was defined using the lookback parameter. Mod- re KNN els were tested for lookback values between −28 and 0 days. The 0.8 sco RF comparison is shown in Figure 1. It can be seen that the perfor- 2 R mance decreases in the range where the lookback is shorter than 0.6 14 days, but does not increase in the range where the lookback exceeds this value. The main reason for this is probably the fact −28 −24 −20 −16 −12 −8 −4 0 that most deaths occur within the first 14 days of infection. A Lookback [days] lookback of 14 days was used for further analysis as it was found to be the most appropriate. 3.2 Time-Series Approach Figure 1: 10-fold cross validation performance measure In the second approach, a time series analysis was performed. In of the models for different lookback parameter. The mea- this case, only daily deaths for Slovenia were used as data. The sures and its units are are: MAE [deaths/100k] (top), MSE models used in this case were Seasonal Autoregressive Integrated [deaths2/100k2] (middle) and 2 𝑅 score (bottom) Moving Average Exogenous (SARIMAX(p,d,q)(P,D,Q,m) [6] and Feed forward Neural Network (FFNN) [1]. The former is a combination of several different algorithms. Table 1: 10-fold cross-validation performance measures of The first is the autoregressive AR (p) model, which is a linear the predictions for 21 days for SARIMAX and FFNN algo- model that relies only on past p values to predict current values. rithms. The next is the moving average MA (q) model, which uses the residuals of the past q values to fit the model accordingly. The I(d) 2 MAE MSE score represents the order of integration. It represents the number of 𝑅 2 [deaths] [deaths ] times we need to integrate the time series to ensure stationarity. The X stands for exogenous variable, i.e., it suggests adding a SARIMAX 1.13 4.81 0.71s separate other external variable to measure the target variable. FFNN 0.53 1.15 0.88 Finally, the S stands for seasonal, meaning that we expect our data to have a seasonal aspect. The parameters P, D, and Q are the seasonal versions of the parameters p, d, and q, and the parameter m represents the length of the cycle. n-fold cross validation. This means, that there is no random The FFNN structure included 10 input perceptrons - one for shuffling of the data. The test set must always be the final portion each death value in the last 10 days, a hidden layer of 64 percep- of the data - the final part of the date range. The concept of trons, and 1 output perceptron. forward chaining is shown in Figure 2. The results of the 10-fold Since the future data of the time series contain the information cross-validation of the predictions for 21 days are shown in Table about the past, a forward chaining approach was performed for 1. 44 Daily Covid-19 Deaths Prediction For Slovenia Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia each splitting decision, the results and hence the performance measures are also somewhat random. However, they do follow a certain trend that becomes apparent when a polyfit is applied. To reduce the randomness of the results, the average of 3 separate predictions was calculated for each number of trees. To determine the best parameters of the SARIMAX model, the auto_arima algorithm from the Python pmdarima library was used [7]. The algorithm analyzes the given data and determines the best model and its parameters for that data. In this case, the selected model was SARIMAX(2, 1, 4)(4, 1, 1, 12). Figure 2: Forward chaining approach to time-series n-fold In the case of FFNN, the parameter selection was omitted - the cross-validation. same model structure was always used. 5 RESULTS 4 MODELS’ PARAMETERS SELECTION With the optimal parameters selected, the graphs of the pre- The next step was to determine the optimal parameters of the dictions can be plotted. The predictions of the country-specific selected models. For this purpose, the regressor models were approach are shown in Figure 5. trained on the same dataset used in the 10-fold cross-validation and tested on the data for Slovenia. For this particular case, differ- ent model parameters were tested to see which performed best. The MAE [deaths/100k] as a function of parameters K for the 50 Random Forrest Regressor KNN and as a function of the number of trees for RF are shown K Nearest Neighbours Regressor in the Figures 3 and 4, respectively. 40 Baseline Truth 30 Deaths 20 0.15 10 MAE 0 K = 55 0.10 r-22 r-21 y-21 0 50 100 150 eb-21 Jan-22 F Ma Ap Ma Jun-20 Jul-20 Aug-19 Sep-18 Oct-18 Nov-17 K Figure 5: Deaths for Slovenia from 22.1.2020 to 11.12.2020. Figure 3: MAE of the KNN regressor as function of K. Models’ predictions, compared to true values. All models predicted the number of deaths for the first epi- demic wave fairly accurately. As a result of the unrepresentative reporting of Covid-19 cases for the second wave, the base model polyfit predicts a much lower number of daily deaths. We can also see 0.15 that the KNN regressor predicts the same value from a certain day forward. The reason for this is most probably that the algorithm MAE always finds the same k=55 neighbors, thus always predicts the 0.10 same value. To avoid this, a larger dataset would be required. MAE for RF, KNN and baseline are shown in Table 2. 50 100 150 200 Table 2: MAE comparison of the country-specific models Number of trees for the interval from 22.1.2020 to 11.12.2020. Figure 4: MAE of the RF regressor as a function of the num- RF KNN baseline ber of trees. MAE [deaths] 5.41 5.39 5.48 For the KNN regressor, MAE has a minimum at 𝐾 = 55, while The predictions for the time interval between 21.11.2020 and for RF the fitting function shows that the appropriate number of 11.12.2020 for the time-series approach are shown in Figure 6. trees is 100, since the model does not improve with additional MAE for FFNN and SARIMAX, shown in Table 3, are substantion- trees at this point. It is important to note that since RF is ran- ally lower than MAE of the country-specific models. However, dom in the sense that it randomly selects a subset of features at the accuracy decreases as the prediction time interval increases. 45 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia David Susič Table 3: MAE comparison of the time-series models for the Table 4: MAE comparison of the models for the interval interval from 21.11.2020 to 11.12.2020. from 1.11.2020 to 11.12.2020. FFNN SARIMAX FFNN SARIMAX RF Reg. KNN Reg. MAE [deaths] 1.24 2.27 MAE [deaths] 1.34 1.67 6.46 8.85 It can be seen that in this case the time-series approach is more accurate than the country-specific one. However, for longer time intervals, the country-specific approach is better because it does not rely on past data. It is important to note that the country-specific models’ error are actually lower when making predictions from the start of the epidemic. The reason for this is that for the first 6 months, the numbers of deaths were very low 50 as can be seen in the Figure 5. The best performing model overall is the FFNN with the MAE of 1.34 deaths. The reason for the best performance of this model 45 is probably that it had a relatively high number of input pa- Deaths rameters. The input layer consisted of 10 perceptrons, i.e. each FFNN prediction was based on the values of the last 10 days. 40 SARIMAX 6 CONCLUSION Truth In this paper, two different approaches to predicting Covid-19 deaths for Slovenia were tested. Both approaches turned out to be reliable. The main implications of the presented study are that Nov-17 Nov-21 Nov-25 Nov-29 Dec-03 Dec-07 Dec-11 for short time intervals the time series approach is much more accurate than the country-specific approach. The advantage of the country-specific approach is that it can predict the number of Figure 6: Slovenia deaths from 21.11.2020 to 11.12.2020. deaths for a given day, based on the number of cases, countermea- Time-series models’ predictions, compared to true values. sures and country-specific static data, without necessarily having information about the past. On the other hand, for the prediction of the second wave, where we already know the course of the epidemic in the first wave, the time series approach is better To determine the overall best model for such predictions, all 4 - at least for the prediction for Slovenia. In the future studies, models were tested on the second epidemic wave. The predictions predictions for the third and fourth waves will be analysed. are visualized in the Figure and the MAEs [deaths] are listed in the Table 4. REFERENCES [1] Francois Chollet et al. 2015. Keras. https : / / github . com / fchollet/keras. [2] Ensheng Dong et al. 2020. An interactive web-based dash- board to track covid-19 in real time. The Lancet Infectious 50 Diseases, 20, 5. doi: 10.1016/S1473-3099(20)30120-1. http: //doi.acm.org/10.1016/S1473- 3099(20)30120- 1. [3] Thomas Hale et al. 2020. A cross-country database of covid- 40 19 testing. Scientific Data, 7, 345. doi: 10.1038/s41597-020- 00688- 8. http://doi.acm.org/10.1038/s41597- 020- 00688- 8. [4] Thomas Hale et al. 2021. A global panel database of pan- Deaths FFNN 30 demic policies (oxford covid-19 government response tracker). SARIMAX Nature Human Behaviour, 5, 3529–538. doi: 10.1038/s41562- RF Reg. 021- 01079- 8. http://doi.acm.org/10.1038/s41562- 021- 01079- 20 KNN Reg. 8. Truth [5] Fabian Pedregosa et al. 2012. Scikit-learn: machine learn- ing in python. Journal of Machine Learning Research, 12, ( January 2012). [6] Skipper Seabold and Josef Perktold. 2010. Statsmodels: econo- metric and statistical modeling with python. Proceedings of Nov-01 Nov-07 Nov-13 Nov-19 Nov-25 Dec-01 Dec-07 the 9th Python in Science Conference, 2010, (January 2010). [7] Taylor G. Smith et al. 2017. pmdarima: arima estimators for Python. [Online; accessed 9.1.2021]. (2017). http : / / www. Figure 7: Slovenia deaths from 1.11.2020 to 11.12.2020. alkaline- ml.com/pmdarima. Models’ predictions, compared to true values. 46 Iris Recognition Based on SIFT and SURF Feature Detection Alenka Trpin Bernard Ženko Faculty of Information Studies Department of Knowledge Technologies Ljubljanska cesta 31A Jožef Stefan Institute 8000 Novo mesto, Slovenia 1000 Ljubljana, Slovenia alenka.trpin@fis.unm.si bernard.zenko@ijs.si ABSTRACT (3) Feature extraction, where a feature vector is generated using different filters, and (4) comparison, based on different distances Human iris recognition is generally considered to be one of the (Hamming distance in specific cases) between pairs of most effective approaches for biometric identification. transformed iris images and the corresponding masks [10]. The Identification is required in numerous areas such as security (e.g., comparison step nowadays frequently implemented with a airports and other buildings, airports), identity verification (e.g., machine learned classification model. banking, electoral registration), criminal justice system. This This work firs uses Scale Invariant Feature Transform paper presents an approach for iris image classification that is (SUFT) and Speed Up Robust Features (SURF) algorithms to based on two popular algorithms for image feature construction extract image keypoints or descriptors and then the bag of visual Scale Invariant Feature Transform (SIFT) and Speed Up Robust words to generate image features that can be used by standard Features (SURF). Both algorithms were used in combination supervised machine learning methods. We evaluate our method with the bag of visual words approach to create descriptive image on a publicly available iris image dataset. features that can be used by supervised machine learning methods and a set of standard machine learning methods (k- Nearest Neighbor, random forest, support vector machines and 2 RELATED WORK neural networks) were evaluated on publicly available iris data Iris recognition is frequently used for gender recognition and set. personal biometric authentication [6, 8, 9]. Ali et. al. applied KEYWORDS contrast-limited adaptive histogram equalization to the normalized image. They used SURF and investigated the Iris recognition, image classification, SIFT features, SURF necessity of iris image enhancement based on the CASIA-Iris- features Interval dataset [1]. Păvăloi and Ignat present experiments carried out with a new approach for iris image classification based on matching SIFT on iris occlusion images. They used the 1 INTRODUCTION UPOL iris dataset to test their methods [6]. Bansal and Sharma Biometrics is the science of determining a person's identity and use a statistical feature extraction technique based on the is an important approach for forensic and security identity correlation between adjacent pixels, which was combined with a management. Face, fingerprints, voice and iris are the most 2-D Wavelet Tree feature extraction technique to extract commonly used biometrics identifiers for personal identification. significant features from iris images. support vector machines They provide characteristics in terms of personal appearance. (SVM) were used to classify iris images into male or female The biometric system first scans the biometric characteristic, and classes [2]. Salve et. al. used an artificial neural network and then, typically based on a library of scans or classification model SVM as a classifier for iris patterns. Before applying the identifies the person [5]. classifier, the region of interest, i.e., the iris region, is segmented Typical iris recognition system consists of four key modules: using a Canny edge detector and a Hough transform. The eyelid (1) image pre-processing, where the system detects the boundary and eyelash effect are kept to a minimum. A Daugman rubber- of the pupil and the outer iris, (2) normalization, where the inner plate model is used to normalise the iris to improve and outer circle parameters obtained from iris localization are computational efficiency and appropriate dimensionality. given as input. Then, a transformation from polar to Cartesian Furthermore, the discriminative feature sequence is obtained by coordinates is applied which maps the circle (iris) into a rectangle. feature extraction from the segmented iris image using 1D Log Gabor wavelet [14]. Adamović et. al. applied an approach that classifies biometric templates as numerical features in the 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 CASIA iris image collection. These templates are generated by for profit or commercial advantage and that copies bear this notice and the full converting a normalised iris image into a one-dimensional fixed- 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). length code set, which is then subjected to stylometric feature Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia extraction. The extracted features are further used in combination © 2021 Copyright held by the owner/author(s). with SVM and random forest (RF) classifiers [15]. 47 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Trpin and Ženko 3 METHODOLOGY vocabulary (generate a vector of visual word frequencies) [15]. It is worth mentioning that a specific BoVW model is based on a Our iris recognition approach combines image feature generation given training dataset and it only includes visual words that algorithms SIFT, SURF, bags of visual words model and appear in the training images. standard supervised machine learning classification methods. In the following subsections we briefly describe each of these 3.4 Classification Methods components, and then explain how these components are combined together. The image classification phase of image analysis can be in principle performed with any machine learning method for 3.1 SIFT classification. We have decided to evaluate a diverse set of standard methods, which we briefly describe in the following The SIFT algorithm detects a set of local features in an image. paragraphs. These features represent local areas of the image, and the The kNN is a supervised method that can be used for algorithm also computes their description in a form of a vector. classification and regression. It is a simple algorithm where the The algorithm proceeds in several stages. The first stage of classification of new instances is based on the majority class of computation is scale-space extrema detection which searches the k closest training examples. The closeness is measured with over all scales and image locations. It employs the so-called a distance measure, which is usually Euclidean, Minkowski or difference of Gaussian function to identify potential interest Manhattan distance [9]. points that are invariant to scale and orientation. The second RF is a supervised learning algorithm based on the ensemble stage localizes each candidate at a location. Keypoints are principle of using decision trees as the basic classifier and extracted by detecting scale space extrema. The main idea behind creating a learning model by combining multiple decision trees. the scale space extrema detection is to identify stable features The main idea of the RF classifier is to create multiple decision which are invariant to changes in scale and viewpoint. At this trees using a bootstrapped sampling method and introduce point the keypoint descriptors are extracted [4, 6]. In essence, randomness in the individual tree building process. The class SIFT describes each image with a set of keypoints, and each label of a new example is determined by majority voting of all keypoint is described with a vector of dimension 128. It is worth trees in the ensemble [11]. mentioning that SIFT can detect different numbers of keypoints The neural networks (NN) consist of several layers of simple in different images. units (neurons), which are simple functions with weight and bias parameters. Each neuron in one layer is connected to all neurons 3.2 SURF in the next layer by a process called back-propagation, and uses The SURF algorithm is based on similar ideas as SIFT, but their gradient descent to measure the rate of change of the loss implementation is different. It can be used for similar tasks as function (e.g. Cross-Entropy loss). NN can have different SIFT, but it is faster, and produces highly accurate results when structures, but typically have an input layer, one or more hidden provided appropriate reference images. Instead of difference of layers and an output layer. Each of these layers contain one or Gaussian function, SURF uses approximate Laplacian of more neurons [9, 12, 13]. In this work, we used the adam solver Gaussian images and a box filter. Determinants of the Hessian function because it is fast and gives good results. It is an matrix are then used to detect the keypoints. A neighbourhood optimisation algorithm that uses running averages of the two around the key point is selected and divided into sub-regions and gradients and other moments of the gradients [13]. then for each sub-region the wavelet responses are taken and For the activation function, we use the logistic or sigmoid represented to get SURF feature descriptor [1, 4]. In the end, each activation function. This determines how nodes in the network image is again represented with a set of keypoints, which are layer convert a weighted sum of input data into output data. The described with vectors. logistic or sigmoid activation function accepts any real value as input and the output values are from 0 to 1 [12]. 3.3 Bag of Visual Words Support vector machines (SVM) is a discriminant technique The bag of visual words (BoVW) approach can be used for which means that the classification function takes a data point transforming or tokenizing keypoint-based image features, such and assigns it to one of the different classes of the classification as SIFT or SURF, into a fixed number of features, which is task. SVM transform the original data with a kernel function in a typically required by supervised machine learning methods. At hyperspace, and then tries to find a hyperplane that distinguishes first generates a visual word vocabulary from a (training) set of the two classes optimally. This hyperplane is defined with images, and then describes each image with these visual words. support vectors and distances between support vectors are The visual word vector of an image contains the presence or maximised. SVM is very effective method for high dimensional absence information of each visual word in the image. In case of problems [2, 14]. SIFT or SURF keypoints, for example, the visual word vector contains numbers of keypoints in an image that are similar to a 3.5 Our Method given visual word. The process for extracting BoVW features Our approach for iris image classification is a based on the bag from images involves the following steps: automatically detect of visual words model, and we use either SIFT or SURF regions or points of interest, compute local descriptors over those algorithm for image keypoint detection. In the training phase we points (in our case, this means employing SIFT or SURF perform the following steps. algorithm), quantize the descriptors into words to form the visual vocabulary, for example with a clustering algorithm, and find the occurrences in the image of each specific visual word in the 48 Iris recognition based on SIFT and SURF feature detection Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia 1. For each image 𝑖, the SIFT or SURF algorithm is run, In our experiments we have used available Python which detects 𝐾𝑖 keypoints (each keypoint has 𝐷 = implementations of included algorithms (scikit-learn for machine 128 dimensions). learning) with their default parameters, except the following: 2. We collect keypoints from all training images, that is,  k-means: k=500, ∑𝑛 𝐾 𝑖=1 𝑖 keypoints.  kNN: k=15, Euclidean metric, 3. We cluster the above set of keypoints with the k-means  RF: number of estimators = 100, clustering algorithm. Based on preliminary experimets  we decided to use k = 500. The clusters, or their SVM: linear kernel function,  centroids, represent the visual words for our problem NN: "adam" solver function, 8 hidden layers and 8 of iris recognition. neurons, "logistic" activation function. The classification accuracy was evaluated with 5-fold 4. Now, we use the clustering model to assign each stratified cross validation. The results are presented separately keypoint in an image to its nearest centroid (visual for the small and big Ubiris.v1 datasets in Table 1 and 2, word) and sum up the occurrences of these visual respectively. words for each image. We end up with image descriptions, where each image is described with a vector of length k. Table 1: Classification accuracy on the small dataset with 5. The dataset derived in the previous step can now be standard deviation used to train a classification model with an arbitrary machine learning method. In our experiments, we have classifier/keypoint method SIFT SURF used four methods: k-Nearest Neighbor, Random Forest, Support Vector Machines and Neural kNN 0,37 ± 0,0 0,46 ± 0,0 Networks. RF 0,43 ± 0,06 0,63 ± 0,0 In the classification phase, when we need to classify a new image, we need to perform three steps. SVM 0,67 ± 0,0 0,86 ± 0,0 NN 1. Run the SIFT or SURF algorithm on the new image to 0,63 ± 0,0 0,77 ± 0,0 detect keypoints (analogous to step 1 in training). 2. Use the clustering model to assign each keypoint to its The baseline accuracy for the small data set is 0.14 (i.e., nearest centroid and sum up their occurrences to derive 1/number of classes=1/7), and in Table 1 we can see that all visual words vector (analogous to step 4 in training). instantiations of our method give better results than chance. The 3. Classify the image with the trained classification NN and SVM classifiers perform much better than RF and model. especially kNN. Comparing the keypoint detectors, we can see We have performed experiments with two keypoint detection that SURF gives consistently better results than SIFT, although algorithms (SIFT and SURF) and four classification algorithms the difference is not very large. The results on the big dataset are, (kNN, RF, SVM and NN), and the results are presented in the as expected, worse. The default accuracy in this case is 0.0079 next section. (i.e., 1/127), and again all instantiations of our method give better results than chance. Again, SVM and NN perform best, but for some reason, NN performs very poorly in combination with 4 RESULTS SURF keypoints. RF in this case performs only slightly worse For evaluating our approach, we have used the Ubiris.v1 dataset than SVM, while kNN is much worse. Also, on this data we can (http://iris.di.ubi.pt/ubiris1.html). It contains 1865 images of 200 see that SURF keypoints give somewhat better results than SIFT, x 150 resolution in 24-bit colours. They are grouped in two the only exception is NN, where SURF fails. subsets: the first contains 1205 images in 241 classes and the In summary we can conclude that for iris recognition the more second one contains 660 images in 132 classes. Images in the complex learning algorithms (SVM, NN) outperform simpler first subset have minimal noise factors, especially those related ones (kNN and even RF), and that the SURF algorithm slightly to reflections, luminosity, and contrast, because they were outperforms SIFT. However, we can also conclude that iris captured inside a dark room. The second subset of images was recognition is a hard problem, which would probably benefit collected in a less controlled setting to introduce natural from application of state-of-the-art deep learning approaches. luminosity variation. This resulted in more heterogeneous images with included reflections, contrast, luminosity and focus Table 2: Classification accuracy on the big dataset with problems. Images collected at this stage simulate the ones standard deviation captured by a vision system without or with minimal active participation from the subjects [7]. These two subsets of images do not have the same classes. classifier/keypoint method SIFT SURF For our experiments we used the examples belonging to a subset kNN 0,02 ± 0,025 0,06 ± 0,039 of all classes: for the small subset we have selected 7 (the first seven classes) and for the big subset we have selected 127 classes RF 0,1 ± 0,018 0,11 ± 0,014 (the first 127 classes). In the resulting datasets the examples were SVM 0,08 ± 0,039 0,13 ± 0,014 evenly distributed among the selected classes. NN 0,17 ± 0,01 0,25 ± 0,005 49 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Trpin and Ženko To investigate whether any of the observed differences is additional feature extractors, like Oriented FAST and Rotated statistically significant, we applied Friedman and Nemenyi tests BRIEF (ORB) or Local Binary Pattern (LBP), and, given their as recommended in [8]. The results in the form of an average success in image recognition in general, also convolutional rank diagram with the estimated critical distance is presented in neural networks approaches. With the latter, we will be Figure 1 for big dataset and Figure 2 for small dataset. especially interested in evaluating and comparing the performance vs. computational cost trade off. REFERENCES [1] Ali, H.S., Ismail, A.I., Farag, F.A. 2016. Speeded up robust features for efficient iris recognition. SIViP 10, 1385–1391 (2016). [2] Atul Bansal, Ravinder Agarwal and R. K. Sharma, "SVM Based Gender Classification Using Iris Images," 2012 Fourth International Conference on Computational Intelligence and Communication Networks, 2012, pp. 425-429. Figure 1: Average rank diagram with the estimated critical [3] David G. Lowe. 2004. Distinctive Image Features from Scale-Invariant distance for the evaluated methods (small dataset) keypoints. International Journal of Computer Vision, 60, 2, pp. 91-110. [4] Ebrahim Karami, Siva Prasad, Mohamed Shehata. 2017. Image Matching Using SIFT, SURF, BRIEF and ORB: Performance Comparison for Distorted Images. Newfoundland Electrical and Computer Engineering Conference. [5] Hájek J., Drahanský M. 2019. Recognition-Based on Eye Biometrics: Iris and Retina. In: Obaidat M., Traore I., Woungang I. (eds) Biometric-Based Physical and Cybersecurity Systems. Springer, Cham. [6] Ioan Păvăloi and Anca Ignat. 2019. Iris Image Classification Using SIFT Features. 23rd International Conference on Knowledge-Based Systems and Intelligent Information & Engineering Systems, Elsevier. 159 (2019) Figure 2: Average rank diagram with the estimated critical 241–250. distance for the evaluated methods (big dataset) [7] Hugo Pedro Proença and Luís A. Alexandre. 2005. UBIRIS: A noisy iris image database. 13th International Conference on Image Analysis and Processing - ICIAP 2005, Springer, (Sept, 2005) 970-977. The critical value for the eight classifiers and a confidence [8] Janez Demšar. 2006. Statistical Comparisons of Classifiers over Multiple level of 0.05 is 3.031, the critical distance is CD = 4.695605. Data Sets. J. Mach. Learn. Res., 7, 1-30. Based on the size of CD we can only claim that the top of [9] Jiawei Han, Micheline Kamber and Jian Pei. 2012. Data Mining: Concepts and Techniques. (3rd ed.). The Morgan Kaufmann. ranked methods and significantly better than the low ranked ones. [10] John Daugman. 2004. How iris recognition works. IEEE Trans Cir-cuits For example, NN-SURF, NN-SIFT and SVM-SURF are better Syst Video Technol 14(1): 21–30. [11] Leo Breiman. 2001. Random forests. Machine Learning, 45(1), 5-32. than KNN-SIFT. On the other hand, the differences among [12] Saša Adamović, Vladislav Miškovic, Nemanja Maček, Milan neighboring methods on the diagram are not significant. Milosavljević, Marko Šarac, Muzafer Saračević, Milan Gnjatović. 2020. An efficient novel approach for iris recognition based on stylometric features and machine learning techniques, Future Generation Computer Systems, 107 (2020), 144-157. 5 CONCLUSION [13] Shervin Minaee and Abdolrashidi Amirali. 2019. DeepIris: Iris Recognition Using a Deep Learning Approach. The paper presents an evaluation of a typical bag of visual words [14] Sushilkumar S. Salve and S. P. Narote. 2016. Iris recognition using SVM approach on a specific dataset for human iris recognition. The and ANN. 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 474-478. results show that iris recognition is a relatively hard task and in [15] Wadhah Ayadi, Wajdi Elhamzi, Imen Charfi, Mohamed Atri. 2019. A order to improve the accuracy we would need a dataset with more hybrid feature extraction approach for brain MRI classification based on Bag-of-words. Biomedical Signal Processing and Control, 48, 144-152. examples of each class. In the future work we plan to evaluate 50 Analyzing the Diversity of Constrained Multiobjective Optimization Test Suites Aljoša Vodopija Tea Tušar Bogdan Filipič aljosa.vodopija@ijs.si tea.tusar@ijs.si bogdan.filipic@ijs.si Jožef Stefan Institute and Jožef Stefan Institute and Jožef Stefan Institute and Jožef Stefan International Jožef Stefan International Jožef Stefan International Postgraduate School Postgraduate School Postgraduate School Jamova cesta 39 Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT In this study, we employ the landscape features proposed in [13] to express and discuss the diversity of frequently used test A well-designed test suite for benchmarking novel optimizers suites of CMOPs. This is achieved by firstly computing the land- for constrained multiobjective optimization problems (CMOPs) scape features and then employing the t-distributed Stochastic should be diverse enough to detect both the optimizers’ strengths Neighbor Embedding (t-SNE), a dimensionality reduction tech- and shortcomings. However, until recently there was a lack of nique, to embed the 29-D CMOP feature space into the 2-D space. methods for characterizing CMOPs, and measuring the diversity Note that due to space limitations, only selected results are shown of a suite of problems was virtually impossible. This study utilizes 1 in this paper. The complete results can be found online . the landscape features proposed in our previous work to charac- The rest of this paper is organized as follows. Section 2 pro- terize frequently used test suites for benchmarking optimizers in vides the theoretical background. In Section 3, we present the solving CMOPs. In addition, we apply the t-distributed Stochastic landscape features and the t-SNE algorithm. Section 4 is dedi- Neighbor Embedding (t-SNE) dimensionality reduction approach cated to the experimental setup, while the results are discussed in to reveal the diversity of these test suites. The experimental re- Section 5. Finally, Section 6 summarizes the study and provides sults indicate which ones express sufficient diversity. an idea for future work. KEYWORDS 2 THEORETICAL BACKGROUND constrained multiobjective optimization, benchmarking, land- A CMOP can be formulated as: scape feature, t-SNE minimize 𝑓 (𝑥 ), 𝑚 = 1, . . . , 𝑀 𝑚 (1) 1 INTRODUCTION subject to 𝑔 (𝑥 ) ≤ 0, 𝑖 = 1, . . . , 𝐼 𝑖 Real-world optimization problems frequently involve multiple where 𝑥 = (𝑥 ) is a search vector, : 1, . . . , 𝑥 𝑓 𝑆 → 𝐷 𝑚 R are objective 𝐷 objectives and constraints. These problems are called constrained functions, 𝑔 : 𝑆 → is a search 𝑖 R constraint functions, 𝑆 ⊆ R multiobjective optimization problems (CMOPs) and have been space of dimension 𝐷, and 𝑀 and 𝐼 are the numbers of objectives gaining a lot of attention in the last years [13]. As with other and constraints, respectively. theoretically-oriented optimization studies, a crucial step in test- If a solution 𝑥 satisfies all the constraints, 𝑔 (𝑥 ) ≤ 0 for 𝑖 = 𝑖 ing novel algorithms in constrained multiobjective optimization 1, . . . , 𝐼 , then it is a feasible solution. For each of the constraints is the preparation of a benchmark test. 𝑔 we can define the constraint violation as 𝑣 (𝑥 ) = max(0, 𝑔 (𝑥 )). 𝑖 𝑖 𝑖 One of the key elements of a benchmark test is the selection of In addition, an overall constraint violation is defined as suitable test CMOPs [1]. A well-designed benchmark suite should 𝐼 Õ include “a wide variety of problems with different characteris- 𝑣 (𝑥 ) = 𝑣 (𝑥 ) . (2) 𝑖 tics” [1]. This way the benchmark problems are diverse enough 𝑖 to “highlight the strengths as well as weaknesses of different A solution 𝑥 is feasible iff 𝑣 (𝑥 ) = 0. algorithms” [1]. However, until recently there existed only few A feasible solution 𝑥 ∈ 𝑆 is said to dominate a solution 𝑦 ∈ 𝑆 if and limited techniques proposed to explore CMOPs [13]. For this 𝑓 (𝑥 ) ≤ 𝑓 (𝑦) for all 1 ≤ 𝑚 ≤ 𝑀, and 𝑓 (𝑥 ) < 𝑓 (𝑦) for at least 𝑚 𝑚 𝑚 𝑚 reason, the test suites of CMOPs were insufficiently understood ∗ one 1 ≤ 𝑚 ≤ 𝑀 . In addition, 𝑥 ∈ 𝑆 is a Pareto-optimal solution and measuring their diversity was virtually impossible. ∗ if there exists no 𝑥 ∈ 𝑆 that dominates 𝑥 . All feasible solutions To overcome this situation, in our previous work [13], we represent a feasible region, 𝐹 = {𝑥 ∈ 𝑆 | 𝑣 (𝑥 ) = 0}. Besides, experimented with various exploratory landscape analysis (ELA) all nondominated feasible solutions form a Pareto-optimal set, techniques and proposed 29 landscape features to characterize 𝑆 . The image of the Pareto-optimal set is the Pareto front, = o 𝑃o CMOPs, including their violation landscapes—a similar concept {𝑓 (𝑥 ) | 𝑥 ∈ 𝑆 }. A connected component (a maximal connected o as the fitness landscape where fitness is replaced by the overall subset with respect to the inclusion order) of the feasible region constraint violation. is called a feasible component, F ⊆ 𝐹 . In [13], we introduced analogous terms from the perspective Permission to make digital or hard copies of part or all of this work for personal of the overall constraint violation. A local minimum-violation 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 solution is thus a solution 𝑥 for which exists a 𝛿 > 0 such the full citation on the first page. Copyrights for third-party components of this ∗ ∗ that 𝑣 (𝑥 ) ≤ 𝑣 (𝑥 ) for all 𝑥 ∈ {𝑥 | 𝑑 (𝑥 , 𝑥 ) ≤ 𝛿 }. If there is work must be honored. For all other uses, contact the owner /author(s). ∗ ∗ Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia no other solution 𝑥 ∈ 𝑆 for which 𝑣 (𝑥 ) > 𝑣 (𝑥 ), then 𝑥 is a © 2021 Copyright held by the owner/author(s). 1 https://vodopijaaljosa.github.io/cmop-web/ 51 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vodopija, et al. (global) minimum-violation solution Table 1: The ELA features used to characterize CMOPs cat- . We denoted the set of all egorized into four groups: space-filling design, informa- local minimum-violation solutions by 𝐹 and called a connected l tion content, random walk, and adaptive walk [13]. component M ⊆ 𝐹 a local minimum-violation component. l In order to express the modality of a violation landscape, we defined a local search procedure to be a mapping from the search Space-filling design features space to the set of local minimum-violation solutions, 𝜇 : 𝑆 → 𝐹 , 𝑁 l F Number of feasible components such that 𝜇 (𝑥 ) = 𝑥 for all 𝑥 ∈ 𝐹 . A basin of attraction of a local F Smallest feasible component l min minimum-violation component M and local search 𝜇 is then a F Median feasible component med subset of 𝑆 in which 𝜇 converges towards a solution from M , F Largest feasible component max i.e., B (M ) = {𝑥 ∈ 𝑆 | 𝜇 (𝑥 ) ∈ M }. The violation landscape is O (F ) Proportion of Pareto-optimal solutions in F max max unimodal if there is only one basin in 𝑆 and multimodal otherwise. F Size of the “optimal” feasible component opt 𝜌 Feasibility ratio F 3 METHODOLOGY 𝜌 Minimum correlation min 3.1 ELA Features 𝜌 Maximum correlation max 𝜌 Proportion of boundary Pareto-optimal solutions 𝜕𝑆𝑜 The landscape features used in this study were introduced in our Information content features previous work [13] and can be categorized into four groups: space- 𝐻 Maximum information content max filling design, information content, random walk and adaptive 𝜀 Settling sensitivity 𝑠 walk features. They are summarized in Table 1. 𝑀 Initial partial information 0 The space-filling design features are used to quantify the fea- Random walk features sible components, the relationship between the objectives and (𝜌 ) Minimal ratio of feasible boundary crossings 𝜕𝐹 min constraints, and measure the feasibility ratio and proportion of (𝜌 ) Median ratio of feasible boundary crossings 𝜕𝐹 med boundary Pareto-optimal solutions. Next, the information con- (𝜌 ) Maximal ratio of feasible boundary crossings 𝜕𝐹 max tent features are mainly used to express the smoothness and Adaptive walk features ruggedness of violation landscapes. They are derived by ana- 𝑁 B Number of basins lyzing the entropy of sequences of overall violation values as B Smallest basin min obtained from a random sampling of the search space. Then, the B Median basin med random walk features considered in this study are used to quan- B Largest basin max tify the number of boundary crossings from feasible to infeasible (B ) Smallest feasible basin F min regions. They are used to categorize the degree of segmentation (B ) Median feasible basin F med of the feasible region. Finally, features from the last group are (B ) Largest feasible basin F max derived from adaptive walks through the search space. They are ∪B Proportion of feasible basins F used to describe various aspects of basins of attraction in the 𝑣 (B) Median constraint violation over all basins med violation landscapes. 𝑣 (B) Maximum constraint violation of all basins max 3.2 Dimensionality Reduction with t-SNE 𝑣 (B ) Constraint violation of B max max O (B ) Proportion of Pareto-optimal solutions in B max max The t-SNE algorithm is a popular nonlinear dimensionality re- B Size of the “optimal” basin opt duction technique designed to represent high-dimensional data in a low-dimensional space, typically the 2-D plane [12]. First, it converts similarities between data points to distributions. Then, MW [9]. In addition, we included also a novel suite named RCM [6]. it tries to find a low-dimensional embedding of the points that In contrast to other suites which consist of artificial test prob- minimizes the divergence between the two distributions that lems, RCM contains 50 instances of real-world CMOPs based measure neighbor similarity—one in the original space and the on physical models. Note that we actually used only 11 RCM other in the projected space. This means that t-SNE tries to pre- problems, since only continuous and low-dimensional problems serve the local relationships between neighboring points, while were suitable for our analysis. We considered three dimensions of the global structure is generally lost. the search space: 2, 3, 5. It is to be noted that large-scale CMOPs Finding the best embedding is an optimization problem with were not taken into account since the methodology described a non-convex fitness function. To solve it, t-SNE uses a gradient in Section 3 is not sufficiently scalable. This limits our results to descent method with a random starting point, which means that low-dimensional CMOPs. Table 2 shows the basic characteristics different runs can yield different results. The output of t-SNE of the studied test suites. depends also on other parameters, such as the perplexity (similar For dimensionality reduction, we used the t-SNE implemen- to the number of nearest neighbors in other graph-based dimen- tation from the scikit-learn Python package [10] with default sionality reduction techniques), early exaggeration (separation of parameter values. That is, we used the Euclidean distance metric, clusters in the embedded space) and learning rate (also called 𝜀). random initialization of the embedding, perplexity of 30, early The gradients can be computed exactly or estimated using the exaggeration of 12, learning rate of 200, the maximum number of Barnes-Hut approximation, which substantially accelerates the iterations of 1000, and the maximum number of iterations with- method without degrading its performance [11]. out progress before aborting of 300. The gradient was computed by the Barnes-Hut approximation with the angular size of 0.5. 4 EXPERIMENTAL SETUP 5 RESULTS AND DISCUSSION We studied eight suites of CMOPs which are most frequently used in the literature. These are CTP [2], CF [14], C-DTLZ [5], The results obtained by t-SNE are shown in Figures 1 and 2. NCTP [7], DC-DTLZ [8], LIR-CMOP [3], DAS-CMOP [4], and Specifically, the figures show the 2-D embedding of the 29-D 52 Analyzing the Diversity of Constrained Multiobjective Optimization Test Suites Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 2: Characteristics of test suites: number of problems, represent severe multimodality since it contains no problems dimension of the search space 𝐷, number of objectives from the green region (Figure 2d). On the other hand, DC-DTLZ, 𝑀 , and number of constraints 𝐼 . The characteristics of se- LIR-CMOP, and MW are biased towards highly multimodal viola- lected RCM problems are shown in parentheses. tion landscapes or those with small basins of attraction (Figure 2e, Figure 2g, and Figure 2h). Nevertheless, MW is one of the most Test suite #problems 𝐷 𝑀 𝐼 diverse suites considering other characteristics (Figure 2h). CTP [2] 8 * 2 2, 3 The C-DTLZ and DAS-CMOP suites are mainly located in the CF [14] 10 * 2, 3 1, 2 green and orange regions and fail to sufficiently represent the C-DTLZ [5] 6 * * 1, * characteristics of the red and blue regions. NCTP [7] 18 * 2 1, 2 Finally, the results show that CF and RCM are well spread DC-DTLZ [8] 6 * * 1, * through the whole embedded feature space (Figure 2b and Fig- DAS-CMOP [4] 9 * 2, 3 7, 11 ure 2i). As we can see, they have at least one representative CMOP LIR-CMOP [3] 14 * 2, 3 2, 3 instance in each region. Therefore, CF and RCM are the most MW [9] 14 * 2, * 1–4 diverse test suites according to the employed landscape features. RCM [6] 50 (11) 2–34 (2–5) 2–5 1–29 (1–8) *Scalable parameter. 6 CONCLUSIONS In this paper, we analyzed the diversity of the frequently used test suites for benchmarking optimizers in solving CMOPs. For this purpose, we considered 29 landscape features for CMOPs that were proposed in our previous work. In addition, the t-SNE algorithm was used to reduce the dimensionality of the feature space and reveal the diversity of the considered test suites. The experimental results show that the most diverse test suites of CMOPs according to the applied landscape features are CF and RCM. Indeed, they include the widest variety of CMOPs with different characteristics. In addition, MW also proved to be a di- verse suite except for unimodal CMOPs. Nevertheless, we suggest to consider CMOPs from various test suites for benchmarking optimizers in constrained multiobjective optimization. One of the main limitations of our study is that only low- dimensional CMOPs were used in the analysis. Therefore, we Figure 1: Embedding of the feature space as obtained by t- were unable to adequately address the issue of scalability. For this SNE. The four regions are depicted in green, red, blue, and reason, a crucial task that needs to be addressed in the feature is orange. The points that are not contained in any region the extension of this work to large-scale CMOPs. are considered to be outliers. ACKNOWLEDGMENTS We acknowledge financial support from the Slovenian Research feature space consisting of the landscape features presented in Agency (young researcher program and research core funding Table 1. Each subfigure in Figure 2 corresponds to one of the no. P2-0209). This work is also part of a project that has received test suites. For example, Figure 2a exposes the embedding of the funding from the European Union’s Horizon 2020 research and CTP suite in blue, while the gray points correspond to the rest innovation program under Grant Agreement no. 692286. of the test suites. Points with a shape of a plus (+) correspond to CMOPs with two variables, points with a shape of a triangle REFERENCES (▲) to CMOPs with three variables, and points with a shape of a [1] T. Bartz-Beielstein, C. Doerr, J. Bossek, S. Chandrasekaran, pentagon ( ) to CMOPs with five variables. T. Eftimov, A. Fischbach, P. Kerschke, M. López-Ibáñez, K. An additional analysis shows that the embedding of the fea- M. Malan, J. H. Moore, B. Naujoks, P. Orzechowski, V. Volz, ture space can be, based on the corresponding characteristics, M. Wagner, and T. Weise. Benchmarking in optimization: split into four regions: green, red, blue and yellow (Figure 1). Best practice and open issues. arXiv:2007.03488v2, (2020). The green region corresponds to CMOPs with severe violation [2] K. Deb, A. Pratap, and T. Meyarivan. 2001. Constrained test multimodality, small basins of attraction, and rugged violation problems for multi-objective evolutionary optimization. landscapes. The red region corresponds to CMOPs with mod- In Evolutionary Multi-Criterion Optimization (EMO 2001), erate violation multimodality, rugged violation landscapes, and 284–298. small feasibility ratios. The blue region corresponds to relatively [3] Z. Fan, W. Li, X. Cai, H. Huang, Y. Fang, Y. You, J. Mo, C. low violation multimodality, rugged violation landscapes, small Wei, and E. Goodman. 2019. An improved epsilon constraint- feasibility ratios, and positive correlations between objectives handling method in MOEA/D for CMOPs with large in- and constraints. Finally, the yellow region corresponds to uni- feasible regions. Soft Comput., 23, 23, 12491–12510. doi: modal CMOPs with large feasible components, smooth violation 10.1007/s00500- 019- 03794- x. landscapes, and large feasible regions. [4] Z. Fan, W. Li, X. Cai, H. Li, C. Wei, Q. Zhang, K. Deb, and As we can see from Figure 2a, almost all CTP problems are E. Goodman. 2019. Difficulty adjustable and scalable con- located in the orange region. Therefore, many relevant character- strained multiobjective test problem toolkit. Evol. Comput., istics are poorly represented by CTP, e.g., violation multimodality, 28, 3, 339–378. doi: 10.1162/evco- a- 00259. small feasibility ratios, etc. Similarly, NCTP fails to sufficiently 53 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vodopija, et al. (a) CTP (b) CF (c) C-DTLZ (d) NCTP (e) DC-DTLZ (f) DAS-CMOP (g) LIR-CMOP (h) MW (i) RCM Figure 2: Embedding of the feature space as obtained by t-SNE. Each subfigure exposes the embedding of a selected suite. [5] H. Jain and K. Deb. 2014. An evolutionary many-objective [9] Z. Ma and Y. Wang. 2019. Evolutionary constrained mul- optimization algorithm using reference-point based non- tiobjective optimization: Test suite construction and per- dominated sorting approach, Part II: Handling constraints formance comparisons. IEEE Trans. Evol. Comput., 23, 6, and extending to an adaptive approach. IEEE Trans. Evol. 972–986. doi: 10.1109/TEVC.2019.2896967. Comput., 18, 4, 602–622. doi: 10.1109/TEVC.2013.2281534. [10] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. [6] A. Kumar, G. Wu, M. Z. Ali, Q. Luo, R. Mallipeddi, P. N. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, Suganthan, and S. Das. 2020. A Benchmark-Suite of Real- V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. World Constrained Multi-Objective Optimization Prob- Brucher, M. Perrot, and E. Duchesnay. 2011. Scikit-learn: lems and some Baseline Results. Technical report. Indian machine learning in Python. J. Mach. Learn. Res., 12, 2825– Institute of Technology, Banaras Hindu University Cam- 2830. pus, India. [11] L. van der Maaten. 2014. Accelerating t-SNE using tree- [7] J. P. Li, Y. Wang, S. Yang, and Z. Cai. 2016. A comparative based algorithms. J. Mach. Learn. Res., 15, 1, 3221–3245. study of constraint-handling techniques in evolutionary [12] L. van der Maaten and G. Hinton. 2008. Visualizing data constrained multiobjective optimization. In IEEE Congress using t-SNE. J. Mach. Learn. Res., 9, 2579–2605. on Evolutionary Computation (CEC 2016), 4175–4182. doi: [13] A. Vodopija, T. Tušar, and B. Filipič. Characterization 10.1109/CEC.2016.7744320. of constrained continuous multiobjective optimization [8] K. Li, R. Chen, G. Fu, and X. Yao. 2019. Two-archive evo- problems: A feature space perspective. arXiv:2109.04564, lutionary algorithm for constrained multiobjective opti- (2021). mization. IEEE Trans. Evol. Comput., 23, 2, 303–315. doi: [14] Q. Zhang, A. Zhou, S. Zhao, P. N. Suganthan, W. Liu, and 10.1109/TEVC.2018.2855411. S. Tiwari. 2008. Multiobjective optimization test instances for the CEC 2009 special session and competition. Techni- cal report CES-487. The School of Computer Science and Electronic Engieering, University of Essex, UK. 54 Corpus KAS 2.0: Cleaner and with New Datasets Aleš Žagar, Matic Kavaš, Marko Robnik-Šikonja University of Ljubljana, Faculty of Computer and Information Science Ljubljana, Slovenia {ales.zagar,matic.kavas,marko.robnik}@fri.uni-lj.si ABSTRACT wrongly marked to contain both abstracts or switched Slovene Corpus of Academic Slovene (KAS) contains Slovene BSc/BA, and English abstracts. Several entries did not contain the abstract; MSc/MA, and PhD theses from 2000 - 2018. We present a cleaner instead, there was front or back matter like copyright statement, version of the corpus with added text segmentation and updated table of contents, list of abbreviations etc. POS-tagging. The updated corpus of abstracts contains fewer Our analysis has shown that the corpora can be improved in artefacts. Using machine learning classifiers, we filled in miss- many aspects. Besides addressing the above-mentioned weak- ing research field information in the metadata. We used the full nesses, the main improvements in the updated KAS 2.0 and KAS- texts and corresponding abstracts to create several new datasets: Abs 2.0 corpora are chapter segmentation and improved meta- monolingual and cross-lingual datasets for long text summariza- data with machine learning methods (described in Sections 2 and tion of academic texts and a dataset of aligned sentences from 3). A further motivation for our work is the opportunity to ex- abstracts in English and Slovene, suitable for machine transla- tract valuable new datasets for text summarization (monolingual tion. We release the corpora, datasets, and developed source code and cross-lingual) and a sentence-aligned machine translation under a permissible licence. dataset created from matching Slovene and English abstracts (see Section 4). We present conclusions and ideas for further KEYWORDS improvements in Section 5. KAS corpus, academic writing, machine translation, text summa- rization, CERIF classification 2 UPDATES: KAS 2.0 AND KAS-ABS 2.0 1 INTRODUCTION We first describe methods for extracting text and abstracts from The Corpus of Academic Slovene (KAS 1.0)1 is a corpus of Slove- PDF, followed by the differences between the versions 1.0 and nian academic writing gathered from the digital libraries of Slove- 2.0 of corpora. nian higher education institutions via the Slovenian Open Science portal2 [3]. It consists of diploma, master, and doctoral theses from Slovenian institutions of higher learning (mostly from the 2.1 Extraction of Text Body University of Ljubljana and the University of Maribor). It contains 82,308 texts with almost 1.7 billion tokens. As many texts in corpora version 1.0 contained several hard to The KAS texts were extracted from the PDF formatted files, fix faults (like gibberish due to extracted tables and figures), we which are not well-suited for the acquisition of high-quality raw decided to extract texts once again from the PDFs. We used the texts. For that reason, the KAS corpus is noisy. Our analysis pdftotext tool, which is a part of the poppler-utils. The software showed that most original texts contain tables, images, and other proved to be accurate and reliable. Its important feature is keeping kinds of figures which are transformed into gibberish when con- the original text layout and excluding the areas where we detected verted from the PDF format. The extracted figure captions also figures, tables, and other graphical elements. do not give any helpful information. Some texts contain front or In the first step, we converted PDF files to images, one page back matter (for example, a table of contents at the beginning at a time and used the OpenCV computer vision library to detect or references at the end), which shall not be present in the main text and non-text areas. We marked the text areas on each page. text body. For each document, we also calibrated the size of the header and The Corpus of KAS abstracts (KAS-Abs 1.0)3 contains 47,273 footer areas and removed them from the text areas together with only Slovene, 49,261 only English, and 11,720 abstracts in both the page numbers. In this process, we removed 2,467 out of the languages. We observed several shortcomings of this corpus. A original 91,019 documents due to the documents containing less vast majority of abstracts contain keywords or the word "Ab- than 15 pages or some unchecked exceptions in the code. stract" somewhere in the abstract text. Many texts contain other Next, we searched for the beginning and the end of the main kinds of meta-information, e.g., the name of the author or super- text body. We observed that practically all bodies start with some visor and the title of the thesis. Several corpus entries contain variation of the Slovene word "Uvod" (i.e. introduction). If we English and Slovene abstracts in the same unit, only one of them found the beginning, we searched for the ending in the same way but with different keywords (viri, literatura, povzetek, etc). For 1https://www.clarin.si/repository/xmlui/handle/11356/1244 texts with found beginning and end, the areas were clipped and 2https://www.openscience.si/ 3https://www.clarin.si/repository/xmlui/handle/11356/1420 the extracted texts were normalized. The normalization included handling Slovene characters with the caret (č, š, ž), ligattures Permission to make digital or hard copies of part or all of this work for personal (tt, ff, etc.), removal of remaining figure and table captions, and 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 empty lines. The obtained text was segmented into the structure the full citation on the first page. Copyrights for third-party components of this extracted from the table of contents. We matched headings in the work must be honored. For all other uses, contact the owner/author(s). text with the entries in the table of contents and used page num- Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). bers as guidelines. We ended with 83,884 successfully extracted documents. 55 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Žagar, Kavaš and Robnik-Šikonja 2.2 Extraction of Abstracts are not mutually exclusive. Thus, we tackle a multi-label classifi- We tried to improve the KAS-abstracts corpus by cleaning the cation problem. In the corpus, there are 13,738 documents with existing documents and extracting the abstracts directly from high confidence levels of CERIF codes which we use in machine the PDFs. An initial analysis of existing texts showed different learning. Our dataset contains 64 labels out of 363 possible. We formattings (71 different organizations publish the works in the used 10% or 1374 samples as the test set and the remaining 90% KAS corpus). We identified five major patterns of problems and as the training set. created scripts for resolving them. This produced approximately As several studies have shown that recent neural embedding 40,000 cleaned texts while 20,000 were still problematic. The approaches are not yet competitive with standard text repre- direct extraction from the PDFs followed the same procedure as sentations in document level tasks, we decided to use standard for the main text body (described above). We considered figures, Bag-of-Words representation with TF-IDF weighting. In the pre- headers, footers, page numbers, keywords, meta-information, processing step, we lemmatized texts using CLASSLA lemma- abstract placement at the beginning and end of the documents, tizer5 and removed stop-words6 and punctuation. multiple abstracts of different lengths, etc. This resulted in 71,567 We compared four classifiers. For logistic regression (LR), k- collected Slovene abstracts. A similar procedure was applied to nearest neighbours (KNN), and support vector machines (SVM), English abstracts and yielded 53,635 abstracts. we used Scikit-learn [6], and for the multi-layer perceptron (MLP), we tried Keras implementation. For the first three, we prelimi- 2.3 Differences from Version 1.0 to 2.0 nary tried several different parameter values but found that they Besides cleaner texts, excluded gibberish from figures and ta- perform the best with the default ones. The MLP neural network bles, and excluded front- and back-matter, the most important consists of one hidden layer with 256 units, sigmoid activation difference between KAS versions 1.0 and 2.0 is that the texts are function on hidden and output layers, Adam optimizer [5] with segmented by structure, i.e. by headings. Unfortunately, some an initial learning rate of 0.01, and binary cross-entropy as a loss documents present in the original KAS were lost due to the dif- function. We used the early stopping (5 consecutive epochs with ferent extraction, and for some documents appearing only in no improvement) and reduced the learning rate on the plateau version 2.0, there is no metadata. (halving learning rate for every 2 epochs with no improvement) KAS-abstracts is greatly improved and no longer contains large as callbacks during the learning process. quantities of unusable text and different artefacts (e.g., metadata, In Table 2, we report pattern accuracy and binary accuracy keywords, or front- and back-matter). Again, for some abstracts of the trained classifiers. A model predicts a correct pattern if present only in version 2.0, there is no metadata. Still, they are it assigned all true sub-CERIF codes to a document. For binary usable for several tasks, including machine translation studies. accuracy, a model predicts a sub-CERIF code correctly if it assigns Table 1 gives the quantitative overview of the obtained body texts a true single sub-CERIF code to the document. For example, let and abstracts. us assume that we have four sub-CERIF codes and an example with a label sequence ’1010’. If a model predicts ’1010’, it receives 100% for both pattern and binary accuracy. If a model predicts Table 1: Statistics of the obtained body texts and abstracts ’0010’, it gets 0% pattern accuracy and 75% binary accuracy since in version 2.0 of the KAS corpora. it misclassified only the first label. Sum Same as Missing With in 1.0 from 1.0 metadata Table 2: Results on the sub-CERIF multi-label classifica- Slo abstracts 71,567 56,610 2,383 67,533 tion task. The best result for each metric is in bold. Eng abstract 53,635 44,685 16,296 50,674 Body text 83,884 79,320 2,988 79,320 Algorithm Binary accuracy Pattern accuracy LR 98.48 38.36 KNN 98.52 43.75 SVM 98.68 47.82 3 SUB-CERIF CLASSIFICATION MLP 98.66 46.58 CERIF (Common European Research Information Format) is the standard that the EU recommends to member states for recording information about the research activity4. The top level has only Using the pattern accuracy metric, SVM and MLP are signifi- five categories (humanities, social sciences, physical sciences, cantly better than KNN and LR. LR is the worst performing model, biomedical sciences, and technological sciences). In comparison, and KNN is in the middle. SVM is the best, and MLP is behind for the lower level distinguishes 363 categories. As Slovene libraries 1.24 points. We assume that we do not have enough data for MLP use the UDC classification, in the KAS corpus 1.0, only 17% of the to beat SVM. It is difficult to assess the models regarding binary documents also contain the CERIF and sub-CERIF codes in their accuracy. In the test set, we have 761 examples with 1 label, 466 metadata. These are mapped from UDC codes by the heuristics with 2 labels, 107 with 3 labels, 26 with 4 labels, 10 with 5, and 4 produced by the Slovene Open Science Portal. Below, we describe with 6. A dummy model that predicts all zeros achieves binary how we automatically annotated documents with missing sub- accuracy of 97.51. All our models are better than this baseline, CERIF codes using a machine learning approach. and their ranks correspond with the pattern accuracy. We build a dataset for automatic annotation of sub-CERIF We conclude that given 64 labels and 10k training instances, codes from the body texts of the documents. A document may our best model (SVM) correctly predicts almost half of them, have more than one sub-CERIF code, which means that classes which is a useful result. 4https://www.dcc.ac.uk/resources/metadata-standards/cerif-common-european- 5https://github.com/clarinsi/classla research-information-format 6We used the list from https://github.com/stopwords-iso/stopwords-sl 56 Corpus KAS 2.0 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 4 NEW DATASETS other sentence alignments in existing translation datatsets). How- We created two types of new datasets, described below: summa- ever, if one would prefer even more certain alignment, the value rization datasets and machine translation datasets. of the threshold can be further increased at the expense of less sentences in the datatset. We released three such datasets that 4.1 Summarization Datasets reflect a trade-off between quality and quantity of the data. The We created two new datasets appropriate for sizes of the obtained datasets are available in Table 3. long-text summariza- tion in the monolingual and cross-lingual settings. The monolin- Table 3: Size of the machine translation datasets based on gual slo2slo dataset contains 69,730 Slovene abstracts and Slovene the margin-based quality threshold. body texts and is suitable for training Slovene summarization models for long texts. The cross-lingual slo2eng dataset contains 52,351 Slovene body texts and English abstracts. It is suitable for Dataset Threshold Size Normal alignment 1.1 496,102 the cross-lingual summarization task. Strict alignment 1.2 474,852 Very strict alignment 1.3 425,534 4.2 Machine Translation Datasets For the creation of a sentence-aligned machine translation dataset, we used the neural approach proposed by Artetxe & Schwenk [1]. The main difference to other text alignment approaches is in 5 CONCLUSIONS using margin-based scoring of candidates in contrast to a hard In this work, we created version 2.0 of Corpus KAS and Corpus threshold with cosine similarity. We improved the approach by KAS-Abstracts. We cleaned the texts and abstracts, introduced the replacing the underlying neural model. Instead of BiLSTM-based text segmentation based on its structure, and improved the meta- LASER [2] representation, we used the transformer-based LaBSE data. We created two new long text summarization datasets and a [4] sentence representation, which has significantly improved dataset of aligned sentences for machine translations. The latest average bitext retrieval accuracy. We used the implementation versions of corpora and datasets are available on the CLARIN.SI. from UKPLab7. This approach requires a threshold that omits The corpora are annotated with the CLASSLA tool and released candidate pairs below a certain value. This value represents a in txt, JSON and TEI formats. The source code for producing trade-off between the quantity and quality of aligned pairs. The the new versions of the corpora8 and the created datasets are higher the threshold, the better the quality of alignments, but publicly available9 . more samples are discarded. In future work, the extraction of metadata for entries where In text alignment, sentences do not always exhibit one-to-one they are missing would be beneficial. There could be further im- mapping: a source sentence can be split into two or more target provements in cleaning the texts, and this would increase the sentences and vice versa. To address the problem, we iteratively number of available documents. When the corpora are extended ran the alignment process until all sentences above the chosen with data post-2018, the software might need further modifica- threshold were assigned to each other. In cases of more than one tions due to new formats and templates used in the academic sentence assigned to a single sentence, we merged them and thus works. Further experiments on the created MT datasets would created a translation pair. clarify the setting of parameters and show if current MT systems We manually inspected the alignments consisting of more than benefit more from better quality or larger quantity of data. one sentence in either source or target text on a small subset of abstracts. We observed that a merging process produces better ACKNOWLEDGMENTS results than imposing a restriction allowing only the one-to-one The research was supported by CLARIN.SI (2021 call), Slove- mapping. In Table 4, we present an example of the alignment. nian Research Agency (research core funding program P6-0411), The first column represents a margin-based score. If an aligned Ministry of Culture of Republic of Slovenia through project Devel- pair contains more than one sentence in the source or target, opment of Slovene in Digital Environment (RSDO), and European the score consists of the average margin-based score between Union’s Horizon 2020 research and innovation programme under a single sentence and multiple sentences. The last column is an grant agreement No 825153, project EMBEDDIA (Cross-Lingual indicator of whether merging was applied. Embeddings for Less-Represented Languages in European News We used the ratio variant of margin-based scoring and set the Media). We thank Tomaž Erjavec (JSI, Department of Knowledge default threshold to 1.1. We manually tested the alignment on our Technologies) for providing data access and his assistance in internal dataset. From 2015 examples, we successfully aligned building TEI format of the corpus. 2002 of them (99.3%), misaligned 1 (0.1%), and omitted 12 of them (0.6%). The analysis of 12 omitted cases showed that some pairs REFERENCES do not match each other or are not accurate translations of each [1] Mikel Artetxe and Holger Schwenk. 2019. Margin-based par- other, e.g., a large part of the original sentence is omitted, phrases allel corpus mining with multilingual sentence embeddings. are only distantly related, etc. However, approximately half of In Proceedings of the 57th Annual Meeting of the Association the 12 cases shall be aligned, which means that our model works for Computational Linguistics, 3197–3203. very well, but conservatively and may fail for free translation 8 pairs. https://github.com/korpus-kas 9KAS 2.0: https://www.clarin.si/repository/xmlui/handle/11356/1448 With the default value of the threshold (1.1), we produced KAS-Abs 2.0: https://www.clarin.si/repository/xmlui/handle/11356/1449 496.102 sentence pairs. We believe the threshold is strict enough Summarization datasets: https://www.clarin.si/repository/xmlui/handle/11356/1446 to produce good-quality dataset (especially if compared to many MT datasets: https://www.clarin.si/repository/xmlui/handle/11356/1447 7https://github.com/UKPLab/sentence-transformers/blob/master/examples/ applications/parallel-sentence-mining/bitext_mining.py 57 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Žagar, Kavaš and Robnik-Šikonja Table 4: Examples from sentence-aligned Slovene-English abstracts. Score Slovene source sentence English target sentence Mrg 1.670 Moški pa pogosteje opravljajo opravila, ki se tičejo mehanizacije na Men, however, often perform tasks related to machinery on the farm. No kmetiji. 1.612 Zanimala nas je tudi prisotnost tradicionalnih vzorcev pri delu. Additionally, I have also focused on the presence of traditional work No patterns. 1.520 Želeli smo izvedeti, ali se kmečke ženske počutijo preobremenjene, cenjene I wanted to know whether rural women feel overwhelmed or valued, and No in kako preživljajo prosti čas (če ga imajo). how they spend their free time (if they have it). 1.441 Dotaknili smo se tudi problemov, s katerimi se srečujejo kmečke ženske Moreover, I have tackled the problems that rural women face when it No med javnim in zasebnim življenjem. comes to their public and private life. 1.437 Na koncu teoretičnega dela smo opisali še predloge za izboljšanje položaja At the end of the theoretical part, I have denoted further proposals for No kmečkih žensk v družbi. improving the situation of rural women in today’s society. 1.388 V diplomskem delu obravnavamo položaj žensk v kmečkih gospodinjstvih The thesis deals with the situation of women in rural households of No v Sloveniji. Slovenia. 1.354 V empiričnem delu pa smo s pomočjo anketnega vprašalnika, na katerega In the empirical part, I have conducted a survey on peasant women to No so kot respondentke odgovarjale kmečke ženske, ugotavljali, kako je delo determine the gender division of farm labour. na kmetiji porazdeljeno med spoloma. 1.271 V teoretičnem delu predstavljamo pojme, kot so gospodinja, kmečko In the theoretical part, I have presented the following concepts: Yes gospodinjstvo ter kmečka družina, kjer smo opisali tudi tipologijo kmečkih ˝housewife˝, ˝rural household˝ and ˝rural family˝. In addition, I have družin. described the typology of rural families. 1.249 V nadaljevanju smo predstavili tradicionalno dojemanje kmečkih žensk, I have explained the processes that have influenced the change in the Yes njihovo obravnavo skozi čas v slovenski literaturi, pojasnili smo procese, situation of rural women through history and focused on their work ki so vplivali na spremembo položaja kmečkih žensk skozi zgodovino ter se (working day, divison of labour, work evaluation). Furthermore, I have osredotočili na delo kmečkih žensk (delovni dan, delitev dela, vrednotenje shed light on the traditional perception of peasant women and their dela). treatment over time in Slovene literature. 1.217 Ugotovili smo, da so tradicionalni vzorci delitve dela na kmetiji še vedno Hence, the majority of work related to home and family (housework Yes prisotni, saj smo iz analize anket in literature ugotovili, da ženske opravl- and child-rearing) is performed by women. By analyzing the conducted jajo večino del vezanih na dom in družino, to pa so gospodinjska dela in survey and examining the literature, I have come to the conclusion that vzgoja otrok. the division of farm labour more or less still follows traditional patterns. [2] Mikel Artetxe and Holger Schwenk. 2019. Massively mul- [5] Diederik P Kingma and Jimmy Ba. 2014. Adam: a method tilingual sentence embeddings for zero-shot cross-lingual for stochastic optimization. In Internationmal Conference transfer and beyond. Transactions of the Association for on Representation Learning. Computational Linguistics, 7, 597–610. [6] Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, [3] Tomaž Erjavec, Darja Fišer, and Nikola Ljubešić. 2021. The Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu KAS corpus of Slovenian academic writing. Language Re- Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, sources and Evaluation, 55, 2, 551–583. et al. 2011. Scikit-learn: Machine learning in Python. Journal [4] Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Naveen Ari- of machine learning research, 12, 2825–2830. vazhagan, and Wei Wang. 2020. Language-agnostic BERT sentence embedding. arXiv preprint arXiv:2007.01852. 58 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek B Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume B Kognitivna znanost Cognitive Science Uredniki / Editors Toma Strle, Borut Trpin, Maša Rebernik, Olga Markič http://is.ijs.si 7. oktober 2021 / 7 October 2021 Ljubljana, Slovenia 59 60 PREDGOVOR Na letošnji konferenci Kognitivna znanost sodelujejo avtorice in avtorji z različnih disciplinarnih področij in predstavljajo tako empirične rezultate svojih raziskav kot tudi teoretska raziskovanja z najrazličnejših področij – od psihologije in jezikoslovja do nevrofenomenologije, filozofije in umetne inteligence. Upamo, da bo letošnja disciplinarno in metodološko bogata konferenca odprla prostor za izmenjavo zanimivih raziskovalnih idej ter povezala znanstvenice in znanstvenike z različnih disciplinarnih področij, ki se ukvarjajo z vprašanji kognicije. Toma Strle Borut Trpin Maša Rebernik Olga Markič FOREWORD At this year’s Cognitive Science conference, the authors present their empirical studies as well as theoretical research from a diverse range of disciplinary backgrounds – from psychology and linguistics to neurophenomenology, philosophy, and artificial intelligence. We hope that this year's cognitive science conference – rich in disciplinary approaches and methodologies – will open space for exchanging intriguing research ideas and will bring together scientists from a diverse range of areas related to the exploration of the human mind. Toma Strle Borut Trpin Maša Rebernik Olga Markič 61 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Toma Strle, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Borut Trpin, Filozofska fakulteta, Univerza v Ljubljani Maša Rebernik, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani Urban Kordeš, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Matjaž Gams, Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana ORGANIZACIJSKI ODBOR / ORGANIZING COMMITTEE Toma Strle, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Borut Trpin, Filozofska fakulteta, Univerza v Ljubljani Maša Rebernik, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani 62 Nevrofenomenološka študija skupinskih dinamik v spletnem učnem okolju: Preliminarni rezultati Neurophenomenological Study of Group Dynamics in the Online Learning Environment: Preliminary results Jaša Černe Selma Berbić Mateja Kalan Center za kognitivno znanost MEi:CogSci MEi:CogSci Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija jasa.cerne@pef.uni-lj.si selmaberbic2@gmail.com mateja.kalan07@gmail.com Lucija Mihić Zidar Uršek Slivšek Urban Kordeš MEi:CogSci MEi:CogSci Center za kognitivno znanost Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija lucijamihiczidar@gmail.com slivsek@protonmail.com urban.kordes@pef.uni-lj.si POVZETEK existence of various group dynamics at the level of experience and psychophysiology, which represents the basis for further Učno okolje je prostor, v katerem se med udeleženimi v učnem neurophenomenological analysis. We hope that the findings will procesu ustvarjajo kompleksne skupinske dinamike. V prispevku offer fresh insight into the increasingly common online teaching predstavimo preliminarne rezultate eksploratorne and help shape better learning approaches. nevrofenomenološke študije, v kateri smo preučevali takšne dinamike v spletnem učnem okolju. Udeleženci so na štirih KEYWORDS srečanjih merili elektrodermalno aktivnost in ob naključnih trenutkih vzorčili doživljanje. Po vsakem srečanju so izvajali Group dynamics, neurophenomenology, experience sampling, fenomenološke intervjuje in se spoznavali s podatki. Rezultati so electrodermal activity, physiological synchrony, online learning pokazali obstoj različnih skupinskih dinamik na ravni doživljanja environment in psihofiziologije, kar predstavlja osnovo za nadaljnjo nevrofenomenološko analizo. Nadejamo se, da bodo ugotovitve 1 UVOD ponudile svež uvid v vedno pogostejše spletno poučevanje in pomagale oblikovati boljše učne pristope. Učno okolje sestavljajo učitelji in učenci, ki sodelujejo v izmenjavi znanja. Čeprav gre v osnovi za delovanje avtonomnih KLJUČNE BESEDE posameznikov, postane to delovanje včasih zelo usklajeno, tj. tvorijo se skupinske dinamike [1]. V zadnjem času se je zvrstilo Skupinska dinamika, nevrofenomenologija, vzorčenje doživljanja, elektrodermalna aktivnost, fiziološka sinhronizacija več študij, ki skušajo raziskati naravo tovrstnih dinamik z , družnim raziskovanjem doživljanja (prvoosebni vidik) in spletno učno okolje nevrološke aktivnosti (tretjeosebni vidik) [2, 3, 4, 5, 6]. Pokazale ABSTRACT so, da obstaja korelacija med kolektivnim doživljajskim stanjem A learning environment is a space wherein complex group učencev v razredu (npr. čustveno atmosfero) in pripadajočo dynamics form between those who participate in the learning nevrološko oziroma psihofiziološko sinhronizacijo [2, 3, 4]. process. In this paper, we present the preliminary results of an Kljub temu, da se poučevanje vztrajno širi na splet [7], kar lahko exploratory neurophenomenological study in which we predrugači običajne skupinske dinamike [8], se nobena takšna examined such dynamics in an online learning environment. študija še ni ukvarjala s spletnim učnim okoljem. Z raziskavo, ki Throughout four sessions, participants measured electrodermal jo opišemo v tem prispevku, smo želeli zapolniti to vrzel. activity and sampled their experience at random moments. After Sodobni kognitivni znanosti povezovanje doživljajskega in each session, they conducted phenomenological interviews and nevrološkega nivoja ni tuje [9, 10]. Tretjeosebne opise, ki jih familiarized themselves with the data. The results showed the podaja npr. nevroznanost, je potrebno osmisliti skozi prizmo pripadajočih prvoosebnih opisov [11]. Toda slednji so pogosto pridobljeni s tehnikami, ki dajejo prednost posploševanju in Permission to make digital or hard copies of part or all of this work for personal or formalizaciji, zapostavljajo pa veljavnost in ločljivost [11, 12]. 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 Zaradi tega lahko ostane ogromno nevroloških variabilnosti, kot citation on the first page. Copyrights for third-party components of this work must tudi morebitnih korelacij med prvoosebnim in tretjeosebnim be honored. For all other uses, contact the owner/author(s). nivojem, spregledanih [13, 14]. Potencialno rešitev je v svojem Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). nevrofenomenološkem programu predlagal Francisco Varela 63 Nevrofenomenologija skupinskih dinamik Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia [11]. Poudaril je pomembnost poglobljenega, a sistematičnega rening v or en a do ivl an a in i va an a pridobivanja prvoosebnih podatkov in združevanja fenomenolo ih interv u ev prvoosebnega in tretjeosebnega nivoja po principu vzajemnega Pilotno sre an e in tri ra is ovalna sre an a omejevanja. Več študij je pokazalo, da takšno nevrofenomenološko raziskovanje ni samo izvedljivo, pač pa Prvoose ni nivo ret eose ni nivo lahko ponudi svež uvid v pereče probleme kognitivnih znanosti (za nedavni pregled glej [12]). Tehnika za pridobivanje or en e er en e ED prvoosebnih podatkov, ki je bila že večkrat uspešno uporabljena do ivl an a v nevrofenomenološkem kontekstu [15, 17], je opisno vzorčenje Sprotna do ivl a s a Sprotna anali a izkustva (OVI) [18, 19]. Sestavni del tehnike OVI sta naključno anali a ED vzorčenje doživljanja in kasnejši fenomenološki intervjuji, pri enomenolo i čemer sta tako spraševanje kot tudi poročanje o doživljanju interv u i smatrana za spretnosti, v katerih se je potrebno uriti [19]. Za razumevanje nevrološke podstati doživljajskih stanj se Do ivl a s a anali a nali a ED pogosto uporabljajo mere delovanja avtonomnega živčnega sistema (AŽS), kot je npr. elektrodermalna aktivnost (EDA) [20], Nevrofenomenolo a anali a [21, 22]. EDA je produkt interakcije lokalnih procesov v koži in delovanja simpatičnega dela AŽS ter se navadno uporablja kot Slika 1: Shema poteka raziskave indikator vzburjenosti, čustev in stresa [24, 25]. Različne mere sinhronizacije EDA med več udeleženci so se nedavno uveljavile 2.2 Udeleženci kot učinkovit pokazatelj skupinskih dinamik, povezanih npr. z empatijo [26], s povezanostjo med govorniki in občinstvom [27] V raziskavi je sodelovalo petnajst udeležencev (enajst žensk; ter s povečano slušno osredotočenostjo [28]; pa tudi skupinskih povprečna starost = 27,0 let; SD = 7,4) od tega štirinajst dinamik, ki se oblikujejo v učnem okolju, npr. nižja vključenost študentov in en izvajalec. Izvajalec je imel večletne izkušnje z v učni proces [29], mentalni napori skupine [30] in čustvena raziskovanjem doživljanja, študenti pa so pred raziskavo opravili atmosfera [27]. Kljub obetavnim rezultatom pa doslej še ni bilo trening vzorčenja doživljanja in izvajanja fenomenoloških opravljene študije, ki bi mero EDA na nevrofenomenološki način intervjujev. Po vzoru tehnike OVI [19] je vsak študent vzorčil združila s sodobno metodo za pridobivanje prvoosebnih doživljanje vsaj 9 dni, pridobil vsaj 39 vzorcev, bil intervjuvan o podatkov, kot je npr. tehnika OVI. vsaj 15 svojih vzorcih in opravil intervju o vsaj 15 vzorcih V nadaljevanju predstavimo preliminarne rezultate nekoga drugega. Pred prvim srečanjem so bili udeleženci eksploratorne nevrofenomenološke raziskave, v kateri smo na seznanjeni z raziskavo, pridobljeno pa je bilo tudi njihovo ekološko veljaven način preučevali doživljanje in EDA soglasje za sodelovanje. Udeleženci so lahko s sodelovanjem v udeležencev v spletnem učnem okolju. Odgovoriti smo želeli na raziskavi opravili del obveznosti pri študiju. štiri raziskovalna vprašanja: (RV1) Kaj doživljajo študenti in izvajalci tekom spletnih predavanj? (RV2) Ali lahko ob istih 2.3 Pripomočki in tehnike časovnih trenutkih prepoznamo skupinske dinamike na Za merjenje EDA je bil uporabljen brezžični nadlahtni merilnik doživljajskem nivoju? (RV3) Ali se med udeleženimi v učnem BodyMedia SenseWear. Merilnik je beležil EDA štirikrat na procesu tekom spletnih predavanj pojavljajo skupinske dinamike minuto in shranjeval podatke v interni spomin. oziroma sinhronizacije na nivoju EDA? (RV4) Ali obstajajo Prvoosebni podatki so bili pridobljeni s tehniko vzorčenja povezave med doživljanjem in EDA udeleženih v učnem doživljanja, osnovano na tehniki OVI [19]. Signal za vzorčenje procesu? je sprožila aplikacija, naključno v intervalu od 5 do 15 minut. Za vzorčenje je bil uporabljen vprašalnik, ki se je delno razlikoval med pilotnim in ostalimi srečanji. Na pilotnem so udeleženci 2 METODA poročali o kontekstu in doživljanju v zadnjem trenutku pred signalom za vzorčenje, podali pa so lahko tudi komentar in 2.1 Oris raziskave opazke o doživljanju pred tem. Na vseh ostalih srečanjih so Raziskava je vključevala štiri spletna srečanja (pilotno in tri udeleženci poročali o istih postavkah kot na pilotnem srečanju in raziskovalna) v okviru predavanj na skupnem dodatno o doživljanju, ki je bilo v zadnjem trenutku pred Interdisciplinarnem srednjeevropskem magistrskem študijskem signalom za vzorčenje v ospredju, podali pa so tudi odgovor na programu Kognitivna znanost (MEi:CogSci). Sodelovanje v dve vprašanji z vnaprej predvidenimi odgovori. Pri prvem so raziskavi je bilo izrazito aktivno oziroma participatorno. Med označili stopnjo, do katere so bili v trenutku vzorčenja vpeti v srečanjem so udeleženci vzorčili doživljanje in merili EDA, po vsebino predavanja (označili so lahko: aktivna vpetost, vpetost, srečanju pa so opravili fenomenološke intervjuje o izbranih delna vpetost, delna odsotnost, odsotnost ali drugo), pri drugem vzorcih in krajšo sprotno analizo. Fazi zbiranja podatkov je pa vrsto socialnega doživljanja, ki je bila takrat prisotna (označili sledila obširnejša analiza, v načrtu pa imamo opraviti še so lahko: brez socialnega doživljanja, preverjanje doživljanja nevrofenomenološko analizo, v kateri bo izveden poskus drugih, občutek kolektivnega doživljanja, socialno uravnavanje integracije prvoosebnih in tretjeosebnih podatkov. Splošno ali drugo). shemo poteka raziskave prikazuje Slika 1. Doživljajski vzorci so bili razširjeni in preverjeni s tehniko fenomenološkega intervjuja, osnovano delno na ekspozicijskem [26] in delno na mikrofenomenološkem [31] intervjuju. 64 Nevrofenomenologija skupinskih dinamik Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 2.4 Postopek (dvominutni odsek) po eno meritev naprej, dokler nismo obdelali vseh dvajsetih meritev (petminutni odsek). Vsa srečanja so potekala na spletni platformi Zoom. Pilotno srečanje je bilo namenjeno spoznavanju protokola raziskave in raziskovanega pojava, testiranju uporabljene tehnologije ter 3 REZULTATI natančni specifikaciji raziskovalnih vprašanj. Na podlagi podatkov, pridobljenih na pilotnem srečanju, je bil oblikovan Cilj raziskave je bil opisati doživljajsko pokrajino udeležencev vprašalnik za vzorčenje doživljanja. med spletnimi predavanji (RV1) in preveriti, ali se na Na začetku vsakega srečanja so si udeleženci namestili doživljajskem (RV2) in psihofiziološkem (RV3) nivoju, ter na merilnik za merjenje EDA, sledili sta dve minuti mirovanja, nato obeh nivojih skupaj (RV4), porajajo skupinske dinamike. V se je začelo predavanje. Tekom predavanja se je od pet do nadaljevanju predstavimo preliminarne rezultate, ki se šestkrat predvajal zvočni signal, po katerem so imeli udeleženci navezujejo na RV1, RV2 in RV3. na voljo eno do dve minuti za vzorčenje doživljanja. Po srečanju so udeleženci zbrane podatke naložili na spletni repozitorij. 3.1 Doživljanje udeležencev (RV1) Študenti so v času do tri dni po vsakem srečanju izvedli Kot je razvidno iz Slike 2, je doživljajska analiza pokazala, da sprotno analizo prvoosebnih in tretjeosebnih podatkov, med lahko doživljanje udeležencev (izvajalca in študentov) tekom tremi do šestimi dnevi po srečanju pa še fenomenološke spletnih predavanj opišemo s štirimi krovnimi kategorijami, intervjuje o izbranih doživljajskih vzorcih. O vsakem intervjuju vezanimi na osredotočenost in socialno doživljanje. so zapisali kratko poročilo. topnja vpetosti v ranzi ija med topnja smerjenost vse ino predavanja stopnjami vpetosti večopravilnosti pozornosti 2.5 Analiza tivna vpetost Pos us o usirana smer enost fo usiran a po ornost nav ven Analizo podatkov smo izvajali med in po koncu zbiranja a pr ena smer enost podatkov. Glavni cilj analize je bil prepoznavanje vzorcev, ki Pasivna vpetost o usiran e po ornost nav noter namigujejo na obstoj skupinskih dinamik. Odsotnost pad fo usa Sprotna analiza. Sprotna analiza podatkov EDA je vključevala vizualno identifikacijo sinhronizacij v signalih, sprotna analiza doživljajskih podatkov pa primerjavo vzorcev in Slika 2: Hierarhija izbranih doživljajskih kategorij preliminarno kategorizacijo. Izsledki sprotnih analiz so Stopnja vpetosti v vsebino predavanja. Nekateri študenti so informirali nadaljnje faze raziskovanja in analize. se v trenutku vzorčenja aktivno ukvarjali z relevantno vsebino ali Doživljajska analiza. Primarne podatke za doživljajsko pa so kako drugače izkazovali zanimanje zanjo; poročali so npr. analizo so predstavljali odgovori na odprto vprašanje o o vizualizaciji in interpretaciji relevantnih konceptov, doživljanju v zadnjem trenutku pred signalom za vzorčenje, povezovanju z obstoječim znanjem, pa tudi o pričakovanju odgovori na ostale postavke vprašalnika in poročila o intervjujih sledeče vsebine. Tako je zapisala Mara 3 : “Slušno zaznavam pa so služili dodatnemu preverjanju. Analiza je potekala po vzoru besede [izvajalca], subtilno si predstavljam nadaljnji potek smernic za doživljajsko [32] in kvalitativno analizo [33, 34]. predavanja, kot ga opisuje, na način, da interpretiram pomen Najprej smo označili »satelitske« [31] dimenzije doživljanja, besed v nesimbolnih mislih.” Izvajalec je sicer zmeraj aktivno nato pa z induktivnim pristopom odprtega kodiranja [33] posredoval vsebino, a je včasih vseeno poročal o večjem vsakemu vzorcu pripisali kategorije prvega reda. S primerjalno zanimanju. Takšne primere smo imenovali aktivna vpetost ( n = analizo smo prvotne kategorije po potrebi prilagodili, oblikovali 88). Včasih so študenti vsebino predavanja sicer zaznavali, a ne višjenivojske kategorije in dobljene kategorije definirali. Na tako pozorno in z njo niso ničesar aktivno počeli. Tudi izvajalec koncu smo izbrali tiste kategorije, ki so bile najpogostejše in/ali je včasih poročal o manjši zbranosti ali naveličanosti. Takšne najbolj relevantne z vidika zastavljenih raziskovalnih vprašanj. primere smo uvrstili v podkategorijo pasivna vpetost ( n = 50). Analiza EDA. Analiza EDA je vključevala izračun Nazadnje smo prepoznali tudi več primerov odsotnosti ( n = 30), sinhronizacij med pari udeležencev (od tu naprej parnih ko v doživljajskih pokrajinah študentov ni bilo mogoče zaznati sinhronizacij) in izračun povprečnih parnih sinhronizacij (PPS) vsebine predavanja, izvajalec pa je poročal npr. o zmedenosti. različnih skupin: (1) skupin vsaj treh med seboj sinhroniziranih Tranzicija med stopnjami vpetosti. Doživljanje udeležencev udeležencev ( r ≥ 0,40)1 ; (2) vnaprej definiranih skupin (vsi se je včasih nanašalo na prehodne faze med stopnjami vpetosti v udeleženci; samo študenti; izvajalec z vsakim študentom). vsebino predavanja. Nekateri udeleženci so v trenutku vzorčenja Petminutne odseke signalov EDA2, ki so bili posneti v času poročali o poskusu fokusiranja ( n = 19) oziroma prizadevanju za pred vzorčenjem doživljanja, smo ročno pregledali in odstranili aktivnejšo vpetost v vsebino predavanja. Mara je na primer takšne, ki so vsebovali artefakte [24]. Pred nadaljnjo analizo smo zapisala: “Doživljam težnjo po poglobitvi pozornosti na dobljene signale standardizirali. Za izračun parnih sinhronizacij predavanje.” Drugi so težnjo po fokusiranju že začeli udejanjati smo uporabili prilagojen algoritem Marci in Orra [26]. – signal za vzorčenje jih je ujel v procesu fokusiranja ( n = 15), Sinhronizacijo EDA enega para pri enem vzorčenju smo ko so pozornost že preusmerjali na vsebino predavanja. Spet izračunali kot povprečje dvanajstih Pearsonovih korelacij, drugi so poročali o pravkaršnjemu upadu fokusa ( n =19), bodisi pridobljenih s pomikanjem tekočega okna dolžine osmih meritev zaradi utrujenosti, zaspanosti, lakote ali naveličanosti. 1 Kriterij r ≥ 0,40 razumemo kot spodnjo mejo srednje močne korelacije [23]. 3 Izseki, ki jih podajamo ob opisih kategorij, so urejeni tako, da ne razkrivajo 2 Doživljajski podatki so bili omejeni izključno na zadnji trenutek pred signalom za identitet udeležencev in so po potrebi osnovno lektorirani. vzorčenje, zato v analizi EDA nismo upoštevali celih signalov, ampak zgolj petminutne odseke, ki so bili posneti pred vzorčenjem doživljanja. 65 Nevrofenomenologija skupinskih dinamik Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Stopnja večopravilnosti. Doživljanje udeležencev je bilo drugem (šest vzorčenj) deset in na tretjem (pet vzorčenj) devet. mogoče razdeliti tudi glede na številčnost aktivnosti, na katere so Sinhronizirane skupine se niso ohranjale prek več vzorčenj enega bili pozorni. Včasih so bili osredotočeni le na vsebino predavanja srečanja. Najvišja PPS je znašala 0,78 (tretje vzorčenje tretjega – takšne primere smo imenovali fokusirana pozornost ( n = 15). srečanja), povprečje PPS vseh skupin pa je bilo 0,62 ( SD = 0,08). Med njimi najdemo zapis Mare: “Sem v stanju pričakovanja, Pri vnaprej definiranih skupinah smo največjo skupinsko občutim radovednost kot željo po razjasnitvi pojma dinamiko opazili na prvem srečanju, kjer je bila PPS vseh izomorfizem.” Občasno so bili udeleženci, npr. Zoja, poleg udeležencev 0,20 ( SD = 0,54), vseh študentov 0,14 ( SD = 0,53), predavanja osredotočeni še na kaj drugega: “Poslušam in zdi se izvajalca s študenti pa 0,40 ( SD = 0,58). Pri drugem vzorčenju je mi (čutim), da vem, o čem predavatelj govori [...]. Moja bila PPS vseh udeležencev 0,19 ( SD = 0,29), vseh študentov 0,17 pozornost je sicer rahlo razpršena – misli mi tavajo na več ( SD = 0,30), izvajalca s študenti pa 0,29 ( SD = 0,22). Pri zadnjih koncev, predvsem preverjam, kaj vse moram še danes narediti.” treh vzorčenjih se je PPS gibala okrog 0. Na drugem srečanju Takšne primere smo označili z razpršeno pozornostjo ( n = 16). smo prepoznali manj očitne skupinske dinamike. Pri prvem Usmerjenost pozornosti. Doživljanja udeležencev so včasih vzorčenju je PPS izvajalca s študenti znašala 0,17 ( SD = 0,55), zaznamovali občutki, vezani na druge (virtualno) prisotne na pri drugem 0,15 ( SD = 0,38) in pri šestem prav tako 0,15 ( SD = srečanju; udeleženci so se zavedali drugih, skušali so ugotoviti, 0,29). Pri četrtem vzorčenju je znašala PPS vseh udeležencev kaj drugi doživljajo, ali pa so jih opazovali na Zoomu. Te primere 0,12 ( SD = 0,37), vseh študentov pa 0,16 ( SD = 0, 38). Sicer se smo združili v podkategorijo usmerjenost navzven ( n = 44). Toda je PPS gibala okrog 0. Na tretjem srečanju nismo prepoznali PPS socialnega doživljanja ni bilo zmeraj zaznati; včasih so večjih od 0. Za vsa tri srečanja je povprečje PPS vseh udeleženci opazovali svoje doživljanje, izvajali samorefleksijo, udeležencev znašalo 0,04 ( SD = 0,07), vseh študentov 0,03 ( SD ali pa se samoopazovali na Zoomu . Takšne zapise smo označili = 0,10) in izvajalca s študenti 0,05 ( SD = 0,15). z usmerjenostjo navznoter ( n = 27). 3.2 Doživljajske skupinske dinamike (RV2) 4 DISKUSIJA Skupinsko dinamiko na doživljajskem nivoju smo definirali kot V prispevku smo pokazali, da se tudi v spletnem učnem okolju, skupino treh ali več udeležencev, katerih istočasno podane kjer udeleženci niso fizično prisotni, tvorijo doživljajski in vzorce doživljanja smo uvrstili v isto podkategorijo (glej Sliko psihofiziološki vzorci koordiniranega delovanja tako med 2). Skupno smo prepoznali 56 primerov skupinskih dinamik, od študenti kot med študenti in izvajalcem. Da bi videli, ali se tega 19 za prvo, 19 za drugo in 18 za tretje srečanje. 40-krat so prepoznane skupinske dinamike porajajo na obeh nivojih hkrati, skupinske dinamike tvorili študenti, 16-krat pa študenti in bomo v naslednjem koraku izvedli nevrofenomenološko analizo, izvajalec. Najpogosteje so bile skupinske dinamike vezane na v kateri bomo izsledke neodvisne doživljajske analize preverili z podkategorijo aktivna vpetost ( n = 18). Najbolj opazno dodatno analizo EDA in izsledke neodvisne analize EDA z usklajenost smo prepoznali pri petem vzorčenju tretjega srečanja, dodatno doživljajsko analizo. Upamo, da bodo končni rezultati ko so tako izvajalec kot sedem študentov sočasno poročali o poglobili razumevanje skupinskih dinamik, ki se tvorijo v aktivni vpetosti. Izvajalec je takrat zapisal: “Stanje zaganjanja v spletnem učnem okolju. Ker so določene skupinske dinamike predavateljski tok – ne še čisto tam. Tokrat je nemir v ozadju povezane z akademsko uspešnostjo [1, 35, 36], upamo, da bodo močnejši, je pa tudi višja energija – bolj aktivno 'sodelujem' pri naši rezultati pripomogli tudi k izboljšanju učnih pristopov. oblikovanju predavanja.” Ena izmed študentk, Ajša, pa je Določene pomanjkljivosti raziskave najdemo v načinu poročala: “Zanimanje za to, kar [izvajalec] govori, kar sem čutila izvedbe, uporabljeni tehnologiji in izbrani metodi. Prvič, dejstvo, kot željo, da si o tem kaj napišem ter da slišim vse, kar izreče, da da je bila raziskava izvedena v naravnem okolju je po eni strani ne izgubim toka govora.” povečalo njeno ekološko veljavnost, po drugi strani pa otežilo Skupinske dinamike so se tekom vzorčenj posameznega posploševanje zaradi nezmožnosti zagotavljanja univerzalnosti srečanja sistematično spreminjale. Denimo na prvem srečanju eksperimentalnega okolja. Drugič, merilnik, s katerim smo smo pri četrtem vzorčenju zaznali splošen upad osredotočenosti pridobivali podatke EDA, je namenjen za uporabo na nadlahti, ki tako pri izvajalcu kot pri študentih. Do tretjega vzorčenja so je optimalna lokacija z vidika nizke invazivnosti, ne pa tudi z izvajalec in večina študentov ( M = 9,3; SD = 2,3) poročali o vidika pridobivanja podrobnih podatkov o psihofiziološkem aktivni vpetosti, manj študentov pa je poročalo o pasivni vpetosti stanju uporabnika [24, 37]. Tretjič, podatke o psihofiziologiji ( M = 2,7; SD = 2,4) in odsotnosti ( n = 1). Zatem izvajalec ni več smo pridobivali zgolj s pomočjo mere EDA, medtem ko bi lahko poročal o aktivni vpetosti, prav tako je o njej poročalo bistveno kombinirana uporaba več senzorjev psihofiziologije omogočila manj študentov ( M = 5,0; SD = 0,0), število tistih, ki so bili podrobnejši uvid v delovanje AŽS [38]. Četrtič, doživljajski pasivno vpeti ( M = 5,0; SD = 2,0) v vsebino predavanja, ali so vzorci so bili mestoma premalo natančni, fenomenološki bili odsotni ( M = 3,0; SD = 0,0), pa se je dvignila. Izvajalec je intervjuji, s katerimi smo reševali ta problem, pa so bili takrat zapisal: “Čutim se odsotnega, avtomatično govorjenje – opravljeni le o izbranih vzorcih in včasih šele tretji dan po tema mi je dolgočasna, rad bi, da jo čim prej zrecitiram, da grem srečanju, kar je otežilo priklic informacij iz spomina. Izvajanje naprej na bolj zanimivo vsebino.” intervjujev o vseh vzorcih v krajšem času od vzorčenja bi po drugi strani bistveno povečalo že tako visoke zahteve, ki jih je 3.3 Psihofiziološke skupinske dinamike (RV3) raziskava polagala na pleča udeležencev. Analiza podatkov EDA je pokazala skupno 25 skupin s tremi ali Metodološki izziv za prihodnje raziskave je torej najti način, več medsebojno parno sinhroniziranimi člani. Na prvem srečanju kako sočasno zagotoviti visoko ekološko veljavnost in (pet vzorčenj) smo prepoznali šest sinhroniziranih skupin, na univerzalnost okoljskih dejavnikov, kako sočasno zadovoljiti potrebo po nizki invazivnosti in visoki odzivnosti merilnikov 66 Nevrofenomenologija skupinskih dinamik Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia psihofiziologije, ter kako uskladiti potrebe po pridobivanju resting-state experience in the scanner. Frontiers in psychology 6, 1535, podrobnih in veljavnih prvoosebnih podatkov na način, ki ne bo (Oktober, 2015). https://doi.org/10.3389/fpsyg.2015.01535 [17] Russell T. Hurlburt, Ben Alderson-Day, Simone Kühn in Charles pretirano zahteven za udeležence. Fernyhough. 2016. Exploring the ecological validity of thinking on demand: Neural correlates of elicited vs. spontaneously occurring inner speech. PLoS ONE 11, 2, (Februar, 2016), e0147932. https://doi.org/10.1371/journal.pone.0147932 ZAHVALA [18] Russell T. Hurlburt in Sarah A. Akhter. 2006. The Descriptive Experience Sampling method. Phenomenology and the Cognitive Sciences 5, Hvala Gregorju Geršaku za merilnike in uvod v svet (November, 2006), 271–301. https://doi.org/10.1007/s11097-006-9024-0 psihofiziologije, Tini Giber za praktične nasvete pri rokovanju z [19] Russell T. Hurlburt, Sharon Jones-Forrester (Sod.), Michael J. Kane merilniki in vsem študentom za potrpežljivo ter vse prej kot (Sod.), Ricardo Cobo (Sod.), Sarah A. Akhter (Sod.), Chris Heavey (Sod.) in Arva Bensaheb (Sod.). 2011. Investigating pristine inner experience: pasivno sodelovanje v raziskavi. Moments of truth. Cambridge University Press. Cambridge, UK. https://doi.org/10.1017/CBO9780511842627 [20] Antoine Bechara, Hanna Damasio, Daniel Tranel in Antonio R. Damasio. LITERATURA 1997. Deciding advantageously before knowing the advantageous [1] Maria R. Reyes, Marc A. Brackett, Susan E. Rivers, Mark White in Peter strategy. Science 275, 5304, (Februar, 1997), 1293–1295. Salovey. 2012. Classroom emotional climate, student engagement, and https://doi.org/10.1126/science.275.5304.1293 [21] Lea K. Hildebrandt, Cade McCall, Haakon G. Engen in Tania Singer. academic achievement. Journal of Educational Psychology 104, 3, 2016. Cognitive flexibility, heart rate variability, and resilience predict (Avgust, 2012), 700–712. https://doi.org/10.1037/a0027268 fine-grained regulation of arousal during prolonged threat. [2] Lauri Ahonen, Benjamin U. Cowley, Arto Hellas in Kai Puolamäki. 2018. Psychophysiology 53, 6, (Junij, 2016), 880–890. Biosignals reflect pair-dynamics in collaborative work: EDA and ECG study of pair-programming in a classroom environment. Scientific reports https://doi.org/10.1111/psyp.12632 8, 1, (Februar, 2018), 3138. https://doi.org/10.1038/s41598-018-21518-3 [22] Cade McCall, Lea K. Hildebrandt, Boris Bornemann in Tania Singer. [3] Dana Bevilacqua, Ido Davidesco, Lu Wan, Kim Chaloner, Jess Rowland, 2015. Physiophenomenology in retrospect: Memory reliably reflects Mingzhou Ding, David Poeppel in Suzanne Dikker. 2019. Brain-to-Brain physiological arousal during a prior threatening experience. Synchrony and Learning Outcomes Vary by Student-Teacher Dynamics: Consciousness and Cognition 38, (December, 2015), 60–70. Evidence from a Real-world Classroom Electroencephalography Study. https://doi.org/10.1016/j.concog.2015.09.011 Journal of cognitive neuroscience 31, 3, (Marec, 2019), 401–411. [23] Haldun Akoglu. 2018. User’s guide to correlation coefficients. Turkish https://doi.org/10.1162/jocn_a_01274 Journal of Emergency Medicine 18, 3, (September, 2018), 91–93. [4] Anne-Marie Brouwer, Ivo V. Stuldreher in Nattapong Thammasan. 2019. https://doi.org/10.1016/j.tjem.2018.08.001. Shared attention reflected in eeg, electrodermal activity and heart rate. [24] Wolfram Boucsein. 2012. Electrodermal Activity (2. izdaja). Springer, New York. NY. CEUR Workshop Proceedings, 2019 Socio-Affective Technologies: An [25] Gregor Geršak. 2020. Electrodermal activity - a beginner’ s guide. Interdisciplinary Approach, (Oktober, 2019), 27-3. Elektrotehniški Vestnik 87, 4, (Januar, 2020), 175–182. http://resolver.tudelft.nl/uuid:d9afe398-c8e5-42ff-ab93-7b9313cf6d2e [5] Suzanne Dikker, Lu Wan, Ido Davidesco, Lisa Kaggen, Matthias Oostrik, [26] Carl D. Marci in Scott P. Orr. 2006. The effect of emotional distance on James McClintock, Jess Rowland, Georgios Michalareas, Jay J. Van psychophysiologic concordance and perceived empathy between patient Bavel, Mingzhou Ding in David Poeppel. 2017. Brain-to-Brain Synchrony and interviewer. Applied Psychophysiology and Biofeedback 31, 2 (Junij, Tracks Real-World Dynamic Group Interactions in the Classroom. 2006), 115–128. https://doi.org/10.1007/s10484-006-9008-4 Current biology: CB 27, 9, (Maj, 2017), 1375–1380. [27] Shkurta Gashi, Elena Di Lascio in Silvia Santini. 2019. Using Unobtrusive https://doi.org/10.1016/j.cub.2017.04.002 Wearable Sensors to Measure the Physiological Synchrony Between [6] Yu Zhang, Fei Qin, Bo Liu, Xuan Qi, Yingying Zhao in Dan Zhang. 2020. Presenters and Audience Members. Proceedings of the ACM on Wearable Neurophysiological Recordings in Middle-School Classroom Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 1, (Marec, Correlate with Students’ Academic Performance. Frontiers in human 2019), 1–19. https://doi.org/10.1145/3314400 neuroscience 12, 457, (November, 2018). [28] Ivo V. Stuldreher, Nattapong Thammasan, Jan B. F. van Erp in Anne- Marie Brouwer. 2020. Physiological Synchrony in EEG, Electrodermal https://doi.org/10.3389/fnhum.2018.00457 Activity and Heart Rate Detects Attentionally Relevant Events in Time. [7] Shivangi Dhawan. 2020. Online Learning: A Panacea in the Time of Frintiers in Neuroscience 14, 575521, (December, 2020), COVID-19 Crisis. Journal of Educational Technology Systems 49, 1, (Junij, 2020), 5–2. https://doi.org/10.1177/0047239520934018 https://doi.org/10.3389/fnins.2020.575521 [8] Lynn Clouder, Jayne Dalley, Julian Hargreaves, Sally Parkes, Julie Sellars [29] Elena Di Lascio, Shkurta Gashi in Silvia Santini. 2018. Unobtrusive Assessment of Students’ Emotional Engagement during Lectures Using in Jane Toms. 2006. Electronic [re]constitution of groups: Group dynamics from face-to-face to an online setting. Computer Supported Electrodermal Activity Sensors. Proceedings of the ACM on Interactive, Learning 1, (December, 2006), 467–480. https://doi.org/10.1007/s11412- Mobile, Wearable and Ubiquitous Technologies 2, 3, (September, 2018), 006-9002-0 1–21. https://doi.org/10.1145/3264913 [9] John T. Cacioppo, Louis G. Tassinary in Gary Berntson (ur.). 2007. [30] Muhterem Dindar, Sanna Järvelä in Eetu Haataja. 2020. What does Handbook of psychophysiology (3. Izdaja). Cambridge University press. physiological synchrony reveal about metacognitive experiences and New York, NY. group performance? British Journal of Educational Technology 51, (Junij, [10] Michael Gazzaniga, Richard B. Ivry in George R. Mangun. 2019. 2020), 1577–1597. https://doi.org/10.1111/bjet.12981 [31] Claire Petitmengin. 2006. Describing one’s subjective experience in the Cognitive neuroscience: The biology of the mind (5. izdaja). Norton, New second person: An interview method for the science of consciousness. York, NY. Phenomenology and the Cognitive Sciences 5, 3–4, (November, 2006), [11] Francisco J. Varela. 1996. Neurophenomenology: A methodological remedy for the hard problem. Journal of Consciousness Studies, 3, 4, 229–269. https://doi.org/10.1007/s11097-006-9022-2 (April, 1996), 330-49. [32] Claire Petitmengin, Anne Remillieux in Camila Valenzuela- [12] Aviva Berkovich-Ohana, Yair Dor-Ziderman, Fynn-Mathis Trautwein, Moguillansky. 2019. Discovering the structures of lived experience: Yoav Schweitzer, Ohad Nave, Stephen Fulder in Yochai Ataria. 2020. The Towards a micro-phenomenological analysis method. Phenomenology Hitchhiker's Guide to Neurophenomenology - The Case of Studying Self and the Cognitive Sciences 18, 4, (September, 2019), 691–730. Boundaries with Meditators. Frontiers in psychology 11, 1680, (Julij, https://doi.org/10.1007/s11097-018-9597-4 2020). https://doi.org/10.3389/fpsyg.2020.01680 [33] Kathy C. Charmaz. 2006. Constructing Grounded Theory: A Practical [13] Antoine Lutz, Jean-Philippe Lachaux, Jacques Martinerie, Francisco Guide through Qualitative Analysis. Sage Publications. London. Varela, 2002. Guiding the study of brain dynamics by using first-person [34] Uwe Flick. 2018. An Introduction to Qualitative Research (6. izdaja). data: Synchrony patterns correlate with ongoing conscious states during a SAGE. Los Angeles, LA. [35] Katsumi Watanabe. 2013. Teaching as a Dynamic Phenomenon with simple visual task. PNAS, 99, 3, 1586–1591. https://doi.org/10.1073 Interpersonal Interactions. Mind, Brain, and Education 7, 2, (Junij, 2013), [14] Claire Petitmengin, Vincent Navarro in Michel Le Van Quyen, 2007. 91-100. https://doi.org/10.1111/mbe.12011 Anticipating seizure: Pre-reflective experience at the center of neuro- phenomenology. Consciousness and Cognition, 16, 3, 746–764. [36] Kazuo Yano. 2013. The Science of Human Interaction and Teaching. https://doi.org/10.1016/j.concog.2007.05.006 Mind, Brain, and Education 7, 1, (Marec, 2013), 19–29. [15] Simone Kühn, Charles Fernyhough, Benjamin Alderson-Day in Russell T. https://doi.org/10.1111/mbe.12003 Hurlburt. 2014. Inner experience in the scanner: Can high fidelity [37] Gregor Geršak in Janko Drnovšek. 2016. Sensewear body monitor in apprehensions of inner experience be integrated with fMRI? Frontiers in psychophysiological measurements. IFMBE Proceedings 57, (Januar, 2016), 437–441. https://doi.org/10.1007/978-3-319-32703-7_85 Psychology 5, 1393, (December, 2014). https://doi.org/10.3389/fpsyg.2014.01393 [38] Jennifer A. Healey in Rosalind W. Picard. 2005. Detecting stress during [16] Russell T. Hurlburt, Ben Alderson-Day, Charles Fernyhough in Simone real-world driving tasks using physiological sensors. IEEE Transactions Kühn. 2015. What goes on in the resting-state? A qualitative glimpse into on Intelligent Transportation Systems 6, 2, (Junij, 2005), 156–166. https://doi.org/10.1109/TITS.2005.848368 67 The ONE-ness of change: An exploratory neurophenomenological single case study on change in mood Tine Kolenik†,* Jaya Caporusso* Department of Intelligent Systems MEi:CogSci Jožef Stefan Institute University of Vienna Ljubljana, Slovenia Vienna, Austria tine.kolenik@ijs.si jaya.caporusso96@gmail.com ABSTRACT The process of change is universally referred to when explaining 1 INTRODUCTION the human psyche in the domain of attitude and behavior change. Established research on the mind related to human change However, change is either presumed to simply exist without processes, also referred to as attitude and behavior change, further elaboration, or it is reduced to neurobiological processes. presumes change simply exists, without any further elaboration. While there is a substantial effort to detect, forecast and induce Implicitly, researchers treat change as dark matter: there is state change, especially in the mental health-related fields, the results of interest SA at a time t, state of interest SB at time t+1, and what have been mixed so far. Understanding what change is is happens in between is magic [1-4].1 When change is defined, therefore crucial. Data on first-person experience has been thus albeit rarely, it falls into reductionist pits, being reduced to far absent from studying change, which may turn out to be a neurobiological processes [5], or it is defined functionally, where deciding oversight. This exploratory study employs the change equals SB less SA, especially in quantitative research. framework of neurophenomenology to explore the process of Thus, research is mostly concerned with how to drive SA to SB, change from multiple perspectives. In this circularly informing tackling questions such as “What motivates change?”, “How is research process, we used ecological momentary assessment to change implemented?”, “How is change sustained?”, “When to gather daily questionnaire and diary data on mood. Afterward, induce change?”, and similar [1-4]. What surprisingly lacks from we selected a single case, and determined the moment of change this list is a bit more intimate and primary: What is change? in mood through an inter-methodological agreement using The question is neither trivial nor unimportant. Various qualitative and computational methods. Lastly, we conducted domains interested in change - from mental health [4] to green phenomenological interviews to study change on the experiential behavior [6] - are facing a considerable obstacle when trying to level. We found that while there may be inter-methodological detect, forecast and induce (desired) change [7]. Physiological agreement on the moment of change, different levels of analysis (e.g., sensors) and psychological (e.g., questionnaires) tools have (operational, narrative, experiential - ONE) establish different been used to this end, but have produced mixed results, definitional aspects, whereas the existence of change on the especially on longer scales [8]. What is more, it seems that experiential level is unclear. It was ambiguous whether the same cognitive science is still in its infancy when studying change. phenomenon was studied even after inter-methodological Analogies can be found in both extreme levels of analysis. In agreement. Further intersubjective research is needed to explore physics, classical thermodynamics ignored the process of change, the phenomenon further. and it was only non-equilibrium thermodynamics that started to consider change as a fundamental process as opposed to only KEYWORDS studying substances [9]. In philosophy, process philosophy faced ecological momentary assessment, empirical phenomenology, Plato’s claim on change as illusionary, and stood against the human change processes, idiographic computational dynamics, classical philosophical view of ontology [10]. Post-cognitivist mental health, natural language processing, paradigms in cognitive science provided a similar opposure, neurophenomenology especially dynamical systems theory (e.g., psychotherapy [7]). In behavioral sciences, the study of persuasion is starting to brush against the notion of what change might be [11]. Permission to make digital or hard copies of part or all of this work for personal or Another consequence of the prolificacy of post-cognitivist 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 paradigms was the introduction of first-person experience [12] as citation on the first page. Copyrights for third-party components of this work must an essential aspect of studying the mind. Expectedly, empirical be honored. For all other uses, contact the owner/author(s). phenomenology [13, 14] has so far eluded inclusion into the Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia science of change, an oversight which might have hurt its efforts. © 2021 Copyright held by the own er/author(s). * The authors contributed equally to this work. 1 Please note that throughout the text we use “state A” and “state B” to delineate, respectively, the state before change and the state after change. However, the different instances of “state A” and “state B” do not necessarily correspond. 68 First-person experience reports might uncover experiential RQ2: What are the properties of change that are discerned (or patterns that may thus prove to be an invaluable tool for constructed) by various methods and where do they diverge? answering the questions on change. Phenomenological Are they addressing and describing the same phenomenon? interviews in particular are often focused on the “transitions between different phases [in time of an experience]” [15, p. 6], RQ1 is concerned with the level of methodological agreement and could therefore elucidate the nature of the magic happening that change occurred in a selected moment in time. RQ2 is between two states. However, to our knowledge, no empirical concerned with how change can be described when using specific phenomenological study investigated the experience of change, methods, how the latter influence the definition, and whether the that is, no empirical phenomenological study aimed at an phenomenon they ultimately research is the same. accurate phenomenological description of how it is to experience The research questions specific to the phenomenological change per se (for a study on the experiential nature of the investigation were informed by time series data. transition between two sequential moments, see [16]). This exploratory study therefore aimed to spur non- pRQ1: Was change experienced at any point of the reductionist research on the fundamental nature of what change investigated episode? is (see section Outline of the research framework for details). The general domain of mental health offers an appropriate context to pRQ2: What is the experiential difference between the state study change, because it makes it salient. We focus on change in before and the state after the change? mood, which is not only ubiquitous, but also one of the primary concerns in mental health. We followed neurophenomenology These RQs cannot be addressed through the results only due [17] on combining first-person and third-person methodologies to the exploratory nature of the work. We thus partially address with mutual constraints, and used ecological momentary them in the Discussion section as well. assessment (EMA) to collect daily quantitative and qualitative data on mood as well as conducted phenomenological interviews on selected data. 3 METHODOLOGY To pursue the research questions, we employed a mixed-methods methodology, using quantitative data collected from daily 2 OUTLINE OF THE RESEARCH questionnaires, text data collected from daily diary entries, and FRAMEWORK first-person experiential data collected with phenomenological The highly exploratory nature of this research is two-fold: 1) its interviews. Due to the circular informing that occurred between object of inquiry is on the one hand ubiquitous and on the other these data that guided the research, we have adopted the hand definitionally very vacuous; and 2) the mutual-informing of framework of neurophenomenology, where “‘neuro’ refers [...] the methods used has been untested so far. Since our to the entire array of scientific correlates which are relevant to presupposition is that change is fundamentally a dynamical cognitive science” [17, p. 330]. process, we rely on collecting time series and diachronic data. To be able to study change ecologically, occurring in the wild Due to the human idiography [18], this touches the framework of as much as possible, we followed the EMA framework, which small or personalized data [19], where inter-human variance and involves "repeated sampling of subjects’ current behaviors and noise are reinterpreted and feature as important data. Following experiences in real time, in subjects’ natural environments", this, our framework investigates a moment in time with which aims to "minimize recall bias, maximize ecological dynamics-sensitive methods on various levels of analysis. What validity, and allow study of microprocesses that influence is sought is inter-methodological agreement, and descriptions of behavior in real-world contexts" [20, p. 1]. the phenomenon on various levels of analysis. Once the latter are gathered, the unified definitional outlines can occur. 3.1 Materials For this study, we are focusing on a single case, and within We used the 10-item international Positive and Negative Affect this single case, on a single identified unity of data. We believe Schedule Short Form (I-PANAS-SF) in English [21] to collect methodological pluralism is necessary to explore this daily mood data. I-PANAS-SF evaluates the following moods in phenomenon. Note that this research is not executed sequentially, a desired time span (in our case, daily) on a 5-point Likert scale: as various types of data inform one another and the direction of Afraid (AF), Alert (AL), Determined (DE), Distressed (DI), the research [17]. The decision on the context of mood was made Enthusiastic (EN), Excited (EX), Inspired (IN), Nervous (NE), due to the ubiquity of it, and the importance of change processes Scared (SC), Upset (UP). in mental health. We note that change may not be invariant in To collect the diary entry data, guidelines suggested to the co- every context. researchers (see [22] for the use of the term co-researcher) to focus on the descriptions of mood, the effects of mood on the 2.1 Research Questions experiences of themselves and the world, the change of the latter This work pursues the following research questions: from the previous day to the present day, and on any salient factual information about the day (for more, see Supplementary RQ1: What is the inter-level agreement between various materials, section Diary entry guidelines). methods with which change can be detected? 69 3.2 Sample and Case SD/ MAD bounds represent the baseline, which means that The sample included seven people, largely acquaintances of the between a data point falling outside of these bounds while the authors, from which a single person was arbitrarily selected, preceding data point was inside the bounds change occurred, and codenamed as Quentin. Our co-researcher was 30 years old at the vice versa. If inside the baseline, change can still occur, but it has end of the data collection phase, biologically assigned at birth as to be bigger than one SD/ MAD. male and identifying as a man and as non-binary, with a master’s To apply this calculation to the data, it has to be preprocessed, degree. He was of somewhat good mental health, had never been extracting the described values. diagnosed with a mental disorder, did not have mental health- This computational definition of change is independent of the related therapy in the recent past, and was not taking any mental context (in our case, mood). health-related medications. He slept seven hours on average per night and had bad sleep quality. He was generally a positive 3.5 Empirical Phenomenology person who felt neutral about his emotional arousal or did not identify with having positive or negative emotional arousal. His We included empirical phenomenology as a method to obtain experience with phenomenological reporting amounted to data on experience. Empirical phenomenology, based on the around 70 hours. concept of epoché [26], allows to get descriptions of how the investigated episodes and phenomena are actually lived. It 3.3 Data Collection excludes the possible narratives, conceptualizations, and judgements that might be constructed after the experience per se. We used the Synergetic Navigation System (SNS), a web- and In particular, we opted for an interviewing approach based on the mobile-based technology for EMA [23], to collect questionnaire micro-phenomenological interview method [24]. The and diary data, and conducted in-depth phenomenological interviewer non-suggestively accompanies the interviewee in interviews based on micro-phenomenology [24] to collect providing accurate phenomenological descriptions of the experiential data. The data was collected from June 24th to July diachronic (temporal unfolding) and synchronic (non-temporal 14th 2021. The SNS data on a given day was collected from dimension, associated with a specific moment or phase) structure 18:00 onwards on the same day or in the morning of the of the experience. For these reasons, empirical phenomenology following day. Quentin was notified at the starting hour of data allowed us to investigate how it is to experience change. The collection through email and mobile push notifications. The interviewing was informed by our research questions, and the interviews were recorded with a Samsung Galaxy A41. interviews were conducted after change had already been 3.4 Computational Definition of Change partially identified (see Results, Subsection Identifying the moment of change). To detect change in quantitative data, change had to first be defined methodologically. Since quantitative data are generally 3.6 Collected Data analyzed computationally, we present a computational definition Quentin completed 16 questionnaires and provided 16 diary of change which was applied to the data. We computationally entries between June 24th and July 14th 2021. The mean of defined (inspired from sudden gains literature [11] and anomaly Quentin’s diary entries was 195 words. Furthermore, three in- detection [25]) that change C between data point or state A ( SA) depth phenomenological interviews were conducted on the at time t and data point or state B ( SB) at time t+1 occurs if selected moment within the time series data (see Results, subsection Identifying the moment of change), clocking (((SB > (M + SD/MAD)) || (SB < (M − SD/MAD))) & ((M − 00:43:33, 01:00:51, 1:09:41 in length, respectively. The SD/MAD) < SA < (M + SD/MAD))) (1) interviews are being transcribed verbatim. || 4 RESULTS (((SA > (M + SD/MAD)) | (SA < (M − SD/MAD))) & ((M − This section presents the analysis of the collected data. For SD/MAD) < SB < (M + SD/MAD))) (2) computational analysis of the time series data, features were extracted in order to calculate whether and when change had || occurred. Change was already defined computationally for the time series in the previous section. Phenomenological results (ΔC > SD/MAD) (3) present the effort to identify change experientially, without a definition pre-given by the authors. where M equals the mean value of the entire time series and standard deviation ( SD) is used if the data is normally distributed, 4.1 Feature Extraction and median and mean average deviation ( MAD) is used if the data is not normally distributed. It denotes that change occurs: Features extracted from the quantitative questionnaire scores included: the mean and SD of a given mood category if the a) if SB falls outside of bounds of SD/ MAD while SA falls inside (Equation (1)); or distribution was normal; and the median and MAD if the b) if S distribution was non-normal. We performed a normalcy test to A falls outside of bounds of SD/ MAD while SB falls inside (Equation (2)); or discern that. Instances with missing questionnaire data were c) if both are inside the SD/ MAD bounds, S filled with last collected data scores. B is more than one SD/ MAD away from SA (Equation (3)). 70 Features extracted from the diaries included sentiment graphs for mood graphs with detected change. Figure 1 presents analysis features and statistical features of sentiment features. one such graph, signifying the change in EN. We used VADER, “a lexicon and rule-based sentiment analysis tool,” [27, para. 1] to get negative and positive sentiment scores for each daily diary entry. Afterward, we extracted statistical features following the same process as for the quantitative questionnaire scores. Instances with missing diary data and therefore missing sentiment scores were linearly interpolated. 4.2 Identifying the Moment of Change To identify the moment of change and address RQ1, several steps were taken. Authors studied the data, particularly reading the diary entries, and asked Quentin to propose a data instance where he felt an instance of change had occurred. Quentin suggested the data Figure 1: Detected change in the Enthusiastic mood instance from July 1st, 2021. This is the selected data instance: category from 30. 06. 2021 to 01. 07. 2021. Table 1: Quentin’s mood scores on July 1st 2021 (see full Furthermore, change was detected in both the positive and names in this subsection, para. 5). negative sentiment scores from the diary entries. See DI AF UP NE SC IN AL EX EN DE Supplementary material, section Sentiment graphs for sentiment 1 1 1 1 1 5 5 5 5 5 graphs. The results show maximum inter-methodological agreement. For the selected diary entry (DiaryE0) and the data from the Every part of the two data streams that could have possibly previous day, see Supplementary material, section Diary entries validated the initial identification of change had validated it. The and quantitative questionnaire mood scores. The text part next step was to see whether change occurred in the selected (pDiaryE0) containing the description of change can be read moment on the experiential level. below: 4.3 Phenomenological Results I saw myself as important, I was very self-confident. This To identify the moment of change to be investigated in the brought about a certain feeling, a certain change in the air interviews, we analyzed the fragment of the co-researcher’s diary around me. [...] people listening to me [...] had this entry in which the selected episode is described (pDiaryE0 below directionality towards me which gave me some sort of power. Table 1). We identified two possible instances of change: one in Compared to yesterday, when I also felt inspired and the third sentence, and the other in the last sentence. We decided enthusiastic, today I had this huge undertone of confidence, to focus on the first one, as it seemed to have had occurred at a and this caused a difference especially in how I perceived specific point in time, and it was therefore possible to investigate others. it with phenomenological interviews. We present the provisional results of the phenomenological Quentin confirmed this is a good example of change investigation. On the 1st July 2021, our co-researcher, Quentin, occurring during the data collection. The authors had beforehand was giving a lecture at a seminar. He was sitting at a desk in a identified the same data instance as a potentially good candidate. lecture hall, and he was talking to the people in front of him. He The change specifically referred to the particular confidence initially felt a self-confined confidence that later changed into a (“Compared to yesterday, […] today I had this huge undertone new confidence. We summarize the experiential categories that of confidence” ). The state of the mood before the change (or State were different from before (state A) to after the change (state B) A) was therefore either no confidence or a different kind of in Figure 2 (pRQ2). confidence, coupled with inspiration and enthusiasm, and the In between state A and state B, Quentin noticed a ray of state of the mood after the change was the newly found sunshine filtering through the air. He felt like his arms had the confidence (or State B). potentiality to move more freely in that direction, experienced as For inter-methodological agreement on the moment of a sense of brightness on their upper left part. This aspect was part change, the computational method for detecting change (see of the new confidence, which was not fully present yet. Quentin Methodology, subsection Computational definition of change) realized that this brightness was something new ((1) in Figure 2). was applied to two data streams, the quantitative questionnaire Quentin felt a ball-like entity in his chest, which expanded until scores (all the 10 mood categories) and the diary entries. it reached the audience. It is at this point that the experience For the quantitative questionnaire scores, change was reached state B, where Quentin felt the full new confidence. detected in 7 out of 10 mood categories (AL, DE, DI, EN, EX, Quentin had the knowledge that the way he was perceiving and IN, UP). The three categories where change was not detected could interact with people had changed ((2) in Figure 2). (AF, NE, SC) were stationary, which means that there were no changing curves. See Supplementary material, section Mood 71 Table 2: Models of experiential change. 1) Change is not present at all at the level of experience. 2) Change is the experiential nature of the experiential flow in which state A and state B succeed each other. Figure 2: Experiential structure (diachronic and synchronic) of the target episode. 3) Between state A and state B there is a state C where change 5 DISCUSSION is experienced. 5.1 The ONE-ness of Change 4) a) Change is an experiential While discussing the data from the different methods, we element present in both state A specified incongruencies between the data and how it and state B. b) Change is an characterizes change (addressing RQ2). In quantitative analysis, experiential element present change was necessarily defined by the authors - the either in state A or c) in state B. computationally defined bounds were arbitrary wrt the phenomenon itself. We labeled this kind of (definition of) change Some representational aspects of the models above are due to OPERATIONAL (definition of) change (oC). In diary data, functional reasons. We envisioned further models but for the change was defined by the co-researcher in two instances, one of sake of brevity we only included some. which includes the exact word “change” (see pDiaryE0). It is Following, we discuss how we tried to address pRQ1. During argued that we “organize [our] experiences and actions according the first interview, Quentin said: “Not that I felt the change, the to narrative structures thereby situating them in the context of a change happened and I felt the consequences of the change”. unifying story,” [28, p. 179] which we attest also happens while This seems to suggest either model 1) or 4c). Later, we found two writing a diary entry. Change was therefore narratively different instances of experience that could represent experiential constructed. Arguably, this construction occurred in the moment change. The first refers to (1) in Figure 2. Quentin made it clear of the writing of the diary, at a point in time successive to the that the knowledge was about the brightness being something original experience that the narrative was about. We labeled this new, not something different from before, since “There was no kind of change NARRATIVE change (nC). In the trace of what was before or how this came to be”. This does not phenomenological data, change was looked for in a collaboration mean that this experience does not entail experiential change: as between the co-researcher and the researcher conducting the far as we know, experiential change might be precisely interviews. Differently from the other levels of analysis, the experienced as the knowledge, or perception, of the newness of understanding of something as change was here not already something. This would correspond to model 3). The other given, but to be explored and discussed. In fact, our instance that might delineate experiential change refers to (2) in phenomenological inquiry was aimed precisely at investigating Figure 2. This change would correspond to model 4c). However, how change might present itself in experience, if it does at all. we were specifically interested in the experience of change in We labeled this kind of change EXPERIENTIAL change (eC). mood, and we cannot claim that the change referred to in (2) in There are two big problems that arise from this: a) the Figure 2 complies with this. When asked towards the end of the granularity problem, and b) the level problem. It is not clear how third interview whether at any point of the investigated episode the various time spans correspond to each other (a)), and whether he realized that his confidence had changed, Quentin answered the various levels of change (oC, nC, eC) refer to and describe no (which hints at model 1)). the same phenomenon, using different levels of analysis. It might in fact be that oC, nC and eC refer to multiple phenomena. We do sense there is a certain correspondence between the three 6 CONCLUSIONS AND FUTURE WORK levels (and there was an agreement on the moment between the This work represents an exploratory neurophenomenological co-researcher’s suggestion and the authors’ suggestion), but inquiry into the nature of change in the context of mood. We used unraveling the complexity of that is out of scope of this paper. ecological momentary assessment to collect daily questionnaire 5.2 Models of Experiential Change and diary data, and after selecting a proper data instance, we conducted phenomenological interviews on it. We discerned that We hypothesize different models of how change might be there was an inter-methodological agreement on the moment of experienced in a simplified “state A to state B transition”. change; however, it is not clear how it manifested, if at all, on the experiential level. We observed various definitional aspects of change, culminating in ONE-ness of change, describing operational, narrative, and experiential change. Finally, we presented some possible models of experiential change and 72 analyzed how our phenomenological data fit into them. We [7] Günter K. Schiepek, Kathrin Viol, Wolfgang Aichhorn, Marc-Thorsten Hütt, Katharina Sungler, David Pincus and Helmut J. Schöller, 2017. found two major problems to address in the future: the Psychotherapy is chaotic — (not only) in a computational world. Frontiers granularity and the levels problem. in Psychology, 8 (May 2017), 379. The study had many limitations, mostly due to its exploratory [8] Tine Kolenik, 2021. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression. In nature. It was ultimately single case, where it analyzed only one Integrating Artificial Intelligence and IoT for Advanced Health episode. It had a limited number of interviews, which may have Informatics. Springer, Berlin. In print. [9] Howard Reiss, 1996. Methods of thermodynamics. Courier Corporation, not gone in depth enough to really identify and specify the Chelmsford, MA. phenomenon of interest. Furthermore, interviews on the moment [10] Nicholas Rescher, 1996. Process metaphysics: An introduction to process of writing might be necessary as well. When collecting philosophy. Suny Press, Albany, NY. [11] Tony Z. Tang and Robert J. DeRubeis, 1999. Sudden gains and critical quantitative data, not every day was sampled, and the amount of sessions in cognitive- behavioral therapy for depression. Journal of data may have produced biased baseline calculations, resulting Consulting and Clinical Psychology, 67, 6 (Dec 1999), 894–904. DOI: https://doi.org/10.1037/0022-006X.67.6.894 in faulty change detections. Using a single method to detect [12] Joana Rigato, Scott M. Rennie, and Zachary F. Mainen, 2019. The change may also not be enough, and a discussion is needed on overlooked ubiquity of first-person experience in the cognitive sciences. Synthese, (Feb 2019), 1-37. how to proceed when two methods from the same or different [13] Patrik Aspers, 2009. Empirical phenomenology: A qualitative research levels of analysis disagree on the change moment. We will not approach (The Cologne Seminars). Indo-pacific journal of delve into the potential problems of ecological momentary phenomenology, 9, 2 (Oct 2009), 1-12. [14] Urban Kordeš, 2016. Going beyond theory. Constructivist Foundations, assessment and quantitative and qualitative self-reports. 11, 2 (Mar 2016), 375-385. In future work, apart from addressing the limitations, we plan [15] Jaya Caporusso and Ema Demšar, 2020. Phenomenology of dissolution experiences: An exploratory study. In Proceedings of 23rd International to continue with the general effort of this study. Future Multiconference INFORMATION SOCIETY (Vol. B). T. Strle, J. Černe, & possibilities include: applying the same methodology O. Markič (Eds.), Institut "Jožef Stefan”, Ljubljana, Slovenia, 5-9. transdiagnostically and for induced, volitional and spontaneous https://www.academia.edu/44494880/Phenomenology_of_Dissolution_E xperiences_An_Exploratory_Study_conference_contribution_ change; conducting interviews on episodes reported as including [16] Julian Bass-Krueger, 2021. Consciousness and Time [Unpublished experiential change, and with expert meditators observing master’s thesis]. University of Vienna. [17] Francisco J. Varela, 1996. Neurophenomenology: A methodological change; analyzing the inter-methodological and experiential remedy for the hard problem. Journal of consciousness studies, 3, 4 (Apr structure of change, where it seems to follow some aspects of the 1996), 330-349. [18] Peter CM. Molenaar, 2004. A manifesto on psychology as idiographic matryoshka principle [29]; applying post-cognitivist science: Bringing the person back into scientific psychology, this time frameworks, e.g., the dynamical systems theory framework; forever. Measurement, 2, 4 (Oct 2004), 201–218. DOI: addressing the granularity problem by expanding the https://doi.org/10.1207/s15366359mea0204_1 [19] Rutvik V. Shah, Gillian Grennan, Mariam Zafar-Khan, Fahad Alim, Sujit methodology by changing the EMA contingency (e.g., when Dey, Dhakshin Ramanathan, and Jyoti Mishr, 2021. Personalized machine experiential change occurs, when a physiological signal occurs) learning of depressed mood using wearables. Translational Psychiatry, 11, 1 (Jun 2021). DOI: https://doi.org/10.1038/s41398-021-01445-0 and including descriptive experience sampling [30]; seeing [20] Saul Shiffman, Arthur A. Stone, and Michael R. Hufford, 2008. Ecological whether change can be forecasted with machine learning and momentary assessment. Annu. Rev. Clin. Psychol., 4 (Apr 2008), 1-32. what implications it brings; exploring what the possibilities in [21] Edmund R. Thompson, 2007. Development and validation of an Internationally Reliable short-form of the positive and negative Affect how oC, nC and eC relate to one another are; testing models of Schedule (PANAS). Journal of Cross-Cultural Psychology, 38, 2 (Mar experiential change with computational simulations; making the 2007), 227–242. DOI: https://doi.org/10.1177/0022022106297301 [22] Urban Kordeš and Florian Klauser, 2016. Second-person in-depth dataset and codebook publicly available; interpreting our phenomenological inquiry as an approach for studying enaction of beliefs. findings in the contexts of different theories of change and time. Interdisciplinary Description of Complex Systems: INDECS, 14, 4 (Oct 2016), 369-377. [23] Günter Schiepek, Heiko Eckert, Benjamin Aas, Sebastian Wallot, and ACKNOWLEDGMENTS Anna Wallot, 2015. Integrative psychotherapy: A feedback-driven dynamic systems approach. Hogrefe Publishing, Göttingen. DOI: The authors acknowledge the financial support from the https://doi.org/10.1027/00472-000 Slovenian Research Agency (research core funding No. P2-0209; [24] Claire Petitmengin, 2006. Describing one’s subjective experience in the second person: An interview method for the science of consciousness. the Young researchers’ grant), and thank their wonderful co- Phenomenology and the Cognitive sciences, 5, 3 (Dec 2006), 229-269. researchers. DOI: https://doi.org/10.1007/s11097-006-9022-2 [25] Mark Woodard, Michael Wisely, and S. Sedigh Sarvestani, 2016. A survey of data cleansing techniques for cyber-physical critical REFERENCES infrastructure systems. Advances in Computers, 102, 63–110. DOI: [1] Charles Abraham and Susan Michie, 2008. A taxonomy of behavior https://doi.org/10.1016/bs.adcom.2016.05.002 change techniques used in interventions. Health Psychology, 27, 3 (May, [26] Edmund Husserl, 1983. Ideas pertaining to a pure phenomenology and to 2008), 379–387. DOI: https://doi.org/10.1037/0278-6133.27.3.379 a phenomenological philosophy (F. Kersten Trans.). Martinus Nijhoff [2] Robert Cialdini, 2017. Pre-suasion. Random House Business, New York, Publishers, Leiden. (Original work published 1952) NY. [27] Clayton Hutto and Eric Gilbert, 2014. VADER: A Parsimonious Rule- [3] Brian J. Fogg. (2003). Persuasive technology: Using computers to change based Model for Sentiment Analysis of Social Media Text. In Eighth what we think and do. Morgan Kaufmann, Burlington, MA. International Conference on Weblogs and Social Media (ICWSM-14). [4] Richard H. Thaler and Cass R. Sunstein, 2021. Nudge: Improving Ann Arbor, MI. decisions about health, wealth and happiness. Yale University Press, New [28] Dan Zahavi, 2007. Self and other: The limits of narrative understanding. Haven, Connecticut. Royal Institute of Philosophy Supplements, 60 (May 2007), 179-202. [5] John T. Cacioppo, Stephanie Cacioppo, and Richard E. Petty, 2018. The [29] Wikipedia contributors, 2021. Matryoshka doll. In Wikipedia, The Free neuroscience of persuasion: A review with an emphasis on issues and Encyclopedia. Retrieved 16:44, September 15, 2021, from opportunities. Social neuroscience, 13, 2 (Mar 2018), 129-172. https://en.wikipedia.org/w/index.php?title=Matryoshka_doll&oldid=103 [6] Fredrik Carlsson, Christina Gravert, Olof Johansson-Stenman, and Verena 0022988 Kurz, 2021. The Use of Green Nudges as an Environmental Policy [30] Russel T. Hurlburt and Sarah A. Akhter, 2006. The Descriptive Instrument. Review of Environmental Economics and Policy, 15, 2 (Jun Experience Sampling method. Phenom Cogn Sci, 5 (Nov 2006), 271–301. 2021), 216-237. DOI: https://doi.org/10.1007/s11097-006-9024-0 73 Supplementary material 1 Diary entry guidelines Please, answer the following questions in the form of a diary entry. Be mindful that your entry is approximately 150 words at minimum. There is no upper word limit. Questions: 1) Describe your mood. 2) Describe how your mood affected your experience: a) of yourself; b) towards the world and its elements. 3) Describe how these experiences have changed from yesterday to today. a) Change of experience towards yourself from yesterday to today. b) Change of experience towards the world and its elements from yesterday to today. 4) Factual information from the last day that you would like to highlight. 2 Diary entries and quantitative questionnaire mood scores a) July 1st 2021 DiaryE0: Today I mostly felt quite inspired, determined and enthusiastic. I saw myself as important, I was very self-confident. This brought about a certain feeling, a certain change in the air around me. The air was pointing up, and I could move throughout differently. Also, for example, people listening to me at a seminar about using a tool for daily assessment had this directionality towards me which gave me some sort of power. Compared to yesterday, when I also felt inspired and enthusiastic, today I had this huge undertone of confidence, and this caused a difference especially in how I perceived others. Otherwise it was a full day, I had a meeting about the future of my software, I worked on my study, I sorted out the details of my stay in another country which I was invited to visit, to see the psychiatric processes and to share knowledge at their clinic, I had the before mentioned seminar, my girlfriend Jaya and I went together to a wonderful classical concert with my parents, and finally, we ate homemade apple pie and drank champagne that was a gift from my mom's best friend. It was a great day. Mood scores: DI AF UP NE SC IN AL EX EN DE 1 1 1 1 1 5 5 5 5 5 b) June 30th 2021: DiaryE1: The day was signified by three moods - uninterested, determined, and inspired. I saw myself too scattered, without a center to hold me or to hold onto, and this made me uninterested in the world around me and it was hard to do anything I wanted to, which I disliked. The narrative of where I am was quite dispersed, and it was hard to look at the things that hold me together. At first I was frustrated, so I spend some time just embracing that feeling, with knowledge that afterwards I will pull myself together. When this phase came, I became determined to set myself straight, and I made a sort of a plan or a diagram of what I want to do and is important to me, what makes me happy. This was quite successful and afterwards I was inspired to do the tasks I wanted to do. The world was consequently also different, it is like after being inspired I am seeing it, it has this brighter quality, but not visually, but the feeling of its atmosphere. Otherwise I was quite happy to have my weekly meet with two of my friends online. Mood scores: DI AF UP NE SC IN AL EX EN DE 2 1 3 1 1 3 2 2 2 2 74 3 Graph of the mood over the entire time series 4 4 Mood graphs 75 76 77 78 5 Sentiment graphs 79 Sensitivity of expected civilization longevity models Anže Marinko Maša Žaucer anze.marinko@ijs.si masa.zaucer@student.fmf.uni-lj.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia David Susič Matjaž Gams David.Susic@ijs.si Matjaz.Gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT hypothesis [12]. For both models we analysed the difference In this paper, we analyse the parameter sensitivities of the Sand- between using log-uniform and log-normal distributions of the berg and Rare Earth civilization longevity models. The Sandberg parameters. In addition, we analysed which parameters most model relies on the Drake equation, while the Rare Earth model affect the results in each model. All in all, we dove into the assumes that the Earth is a very unique planet because of rare structure of the models and tried to improve the accuracy of the sequence of events causing its evolution. In addition to the sensi- results. tivity of the parameters, we also analyse the importance of those parameters. 2 RELATED WORK Some publications suggest there are 600 to 40 000 technological KEYWORDS civilizations in our galaxy [10], while others think there should Human extinction, Drake equation, Civilization collapse, Rare be about 36 of them, assuming an average lifespan of 100 years Earth hypothesis, distributions [13]. However, given our ability to detect intelligent life [3] and their radio signals [2], and the fact that we have not detected 1 INTRODUCTION anything yet, a large number of civilizations is unlikely. After years of dealing with Fermi’s question: "Where is every- In our previous paper [4], we analyzed 4 different models of body?", we still do not seem to have a good answer. After scan- the modified Drake equation to determine longevity of human ning more than 10 million stars [11], we have not found a single civilization. From the accessible data, we concluded that the hu- extraterrestrial life. man technological civilization will most likely survive at most 10 We know that it is inevitable that human civilization will one 000 years. Note that the analysis is not able to conclude anything day die out, but what is the expected longevity and how is it about biological aspects of humans. Another research induces related to the absence of observed civilizations? One way is to that the yearly probability for extinction is most likely less than design human longevity models that use a variety of parameters 1 in 87 000 using four different models [9]. In [5] they explain to answer this question. However, it is not clear which models that humanity will eventually have to move to avoid the death heavily rely on the values of parameters. In this paper we study of our Sun. the sensitivity of the models to the parameters and we also try In this paper we focused on how the parameters of the Drake to determine which parameters have the greatest impact. equation and the choice of the various attributes in two mod- In our previous papers [6, 14] we approached the topic of els affect the probability of longevity of human technological the extinction of human civilization and introduced the Drake civilization. equation [1]. In the first paper [6] we presented Sandberg’s [8] interpretation of the Drake equation and analysed it. In the second 3 ESTIMATING THE LONGEVITY OF paper [14], we presented possible causes of human extinction and HUMAN CIVILIZATION WITH used the Drake equation to estimate the longevity of human civi- SANDBERG AND RARE EARTH MODEL lization. In the last paper [4], we presented four different models 3.1 SANDBERG MODEL with some modifications of the Drake equation and considered their prospects for the time we have left. We concluded that we The Sandberg model [8] is based on Drake equation: are most likely to survive at most 10 000 years. 𝑁 = 𝑅 𝑛 𝑓 𝑓 𝑓 𝐿 (1) In this paper, we focused mainly on two of the models from ∗ 𝑓𝑝 𝑒 𝑙 𝑖 𝑐 the previous paper [4]. The first model we analysed is based • 𝑅∗ being the rate of star formation per year, on Sandberg [8] and the second one represents the "rare Earth" • 𝑓 the fraction of stars with planets, 𝑝 • 𝑛 the number of Earth-like (or otherwise habitable) plan- 𝑒 Permission to make digital or hard copies of part or all of this work for personal ets per a star that has planets, 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 • 𝑓 the fraction of habitable planets with actual life, 𝑙 the full citation on the first page. Copyrights for third-party components of this • 𝑓 the fraction of life-bearing planets that develop intelli- 𝑖 work must be honored. For all other uses, contact the owner/author(s). gence, Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). • 𝑓 the fraction of intelligent civilizations that are detectable, 𝑐 • 𝐿 the average longevity of such civilizations. 80 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Anže Marinko, Maša Žaucer, David Susič and Matjaž Gams Table 1: Probability densities for the parameters in equa- Table 2: Probability densities for the parameters in equa- tion (1) tion (4) Parameter Distribution Parameter Distribution ∗ 𝑅∗ log-uniform from from 1 to 100 𝑁 log-uniform from 10.7 to 12.7 𝑓 log-uniform from 0.1 to 1 𝑛 log-uniform from -1.3 to -0.8 𝑝 𝑔 𝑛 log-uniform from 0.1 to 1 𝑓 log-uniform from -3 to -0.7 𝑒 𝑝𝑚 𝑓 log-normal rate, described in paper [9] 𝑓 log-uniform from -2.5 to -1.5 𝑙 𝑚 𝑓 log-uniform from 0.001 to 1 𝑓 log-uniform from -1 to 0 𝑖 𝑗 𝑓 log-uniform from 0.01 to 1 𝑓 log-uniform from -2.5 to -1.5 𝑐 𝑚𝑒 𝑁 point values: 1 to 10 000 From the equation we can compute they appear to have the same weight on the logarithmic scale. 𝑁 , which is the number of detectable civilizations, or longevity The high values near zero therefore make it very sensitive to 𝐿: changes in parameter ranges and can even cause numerical er- 𝑁 rors when multiplications occur or at least strongly influence the 𝐿 = (2) final result. 𝑅∗ 𝑓 𝑛 𝑓 𝑓 𝑓 𝑝 𝑒 𝑙 𝑖 𝑐 with parameters, i.e. probability densities and limits from Table 1. For this reason, distributions whose values are close to zero As Sandberg suggests, all distributions used in this model were at the boundaries of the parameter range are more stable with log-uniform. respect to changes in the parameters. We compared the stability of the log-uniform distribution with the log-normal distribution 3.2 RARE EARTH MODEL by slightly changing the lower bound of some parameters and The Rare Earth model is based on the "rare Earth" theory that observing the corresponding change in the distribution. The assumes that Earth is a very unique planet evolved under rare results in Figures 1 and 2, and later 3 and 4 indicate that the circumstances. This theory introduces equation: change of log-uniform distribution is much larger than that of log-normal distribution. Therefore, the log-normal distribution ∗ 𝑁 = 𝑁 𝑛 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 (3) 𝑔 𝑝 𝑝𝑚 𝑖 𝑐 is much less dependent on the choice of the parameter range. 𝑙 𝑚 𝑗 𝑚𝑒 We combined equation (3) with Drake’s equation and used prob- ability distributions from Tables 1 and 2. This instantly rules out the need of the 𝑓 (the fraction of stars with planets) parameter. 𝑝 Furthermore, product 𝑓 ∗ 𝑓 ∗ 𝑓 from Drake is equal to 𝑓 ∗ 𝑓 ∗ 𝑓 𝑙 𝑖 𝑐 𝑖 𝑐 𝑙 from Rare Earth, which gives us the final equation: ∗ 𝑁 𝑛 𝑓 𝑓 𝑓 𝑓 𝑔 𝑝𝑚 𝑚 𝑗 𝑚𝑒 𝐿 = (4) 𝑅∗𝑛𝑒 and some new parameters: • ∗ 𝑁 is the number of stars in the Milky Way galaxy (be- tween 250 and 500 billion), • 𝑛𝑔 • 𝑓 is the fraction of planets that are metal-rich (between 𝑝𝑚 1 and 10 percent), Figure 1: Change of probability distribution with respect • 𝑓 is the fraction of planets with a large moon (between 𝑚 to change of lower range limit of parameter 𝑓 . 𝑖 0.3 and 3 percent), • 𝑓 is the fraction of solar systems with Jupiter-size planets 𝑗 (between 5 and 10 percent), • 𝑓 is the fraction of planets with a critically low number 𝑚𝑒 of extinction events (between 1 and 10 percent). In the Rare Earth model we also used log-uniform distribution, in order to compare it to the Sandberg model results. 4 EXPERIMENTS 4.1 Issues with log-uniform distribution In analysing the two models, we focused primarily on how dif- ferent distributions affect the results. Due to the shape of log- uniform distribution (see Figure 2), the part of the graph that is very close to zero has a significant impact on the final result. Since we have a logarithmic scale, the part from zero to one on Figure 2: Change of probability distribution with respect the logarithmic scale corresponds to the range from zero to one to change of lower range limit of parameters 𝑅∗, 𝑛 and 𝑓 . 𝑒 𝑖 percent, while the part from one to two percents corresponds to the range between one and one hundred percent, even though 81 Sensitivity of models Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 3: Difference between log-uniform and log-normal Figure 5: Importance of parameters in Rare Earth model distribution in the Sandberg model. for estimating probability of surviving 1000 years. Figure 4: Difference between log-uniform and log-normal Figure 6: Importance of parameters in Sandberg model for distribution in the Rare Earth model. estimating probability of surviving 1000 years. 4.2 Parameter importance In order to analyse the stability/sensitivity of the two models, we studied which parameters have the greatest impact on the final result. For this purpose, a dataset with different values and distributions for the parameters was created for the two models. Then, three subsets were taken, each containing only the subset with rows for which the probability that we survive at least L years is above 90%. The L options chosen were: 1000, 10 000, 100 000. The importance of the features in each of the subsets was then calculated using the Gini importance method implemented in the Python’s scikit-learn decision tree regressor algorithm [7]. Figure 7: Importance of parameters in Rare Earth model The feature importance scores are shown in Figures 5 to 10. for estimating probability of surviving 10 000 years. We found that in the Sandberg model, parameters 2 and 9 play the most important role, as you can see in Figures 6, 8 and 10, which show the importance of the parameters in calculating the probability that we survive 1000, 10 000 and 100 000 years. In the model Rare Earth, on the other hand, parameters 5 and 7 are crucial for the prediction. This can be seen from Figures 5, 7 and 9, which show the importance scores of the parameters when calculating the same probabilities with the model Rare Earth. 5 DISCUSSION AND CONCLUSION This research took two promising models from our earlier study [4] and analysed stability and sensitivity of the models and param- eters. We analysed the stability of the log-uniform distribution compared to the log-normal distribution. To determine the differ- Figure 8: Importance of parameters in Sandberg model for ence between the two, Figures 1 and 2 are visually informative: estimating probability of surviving 10 000 years. changing the parameter range significantly affects the log-normal distribution, while the log-normal distribution is insensitive to cause some numerical curiosities. It seems reasonable to use dis- these changes. Therefore, the log-normal distribution provides tributions that rely mainly on the central values rather than the more reliable results, while the log-uniform distribution may marginal values. 82 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Anže Marinko, Maša Žaucer, David Susič and Matjaž Gams REFERENCES [1] Frank Drake. 2015. The Drake Equation: Estimating the Prevalence of Extraterrestrial Life Through the Ages. Cam- bridge University Press. [2] Marko Horvat. 2007. Calculating the probability of detect- ing radio signals from alien civilizations. arXiv:0707.0011 [physics.pop-ph]. [3] Mansavi Lingam and Abraham Loeb. 2018. Relative likeli- hood of success in the searches for primitive versus intelli- gent extraterrestrial life. arXiv:1807.08879 [physics.pop-ph]. [4] Anže Marinko, Klara Golob, Ema Jemec, Urša Klun, and Figure 9: Importance of parameters in Rare Earth model Matjaž Gams. 2020. A new study of expected human longevity. for estimating probability of surviving 100 000 years. Informacijska družba, volume B. [5] Jason G. Matheny. 2007. Reducing the risk of human ex- tinction. Risk Analysis, 27, 5, 1337. [6] Jurij Nastran, Beno Šircelj, Drago Bokal, and Matjaž Gams. 2019. Sensitivity analysis of computational models that dissolve the fermi paradox. Informacijska družba, volume A. [7] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011. Scikit-learn: machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. [8] Anders Sandberg, Eric Drexler, and Toby Ord. 2018. Dis- Figure 10: Importance of parameters in Sandberg model solving the Fermi paradox. arXiv preprint arXiv:1806.02404. for estimating probability of surviving 100 000 years. [9] Andrew E. Snyder-Beattie, Toby Ord, and Michael B. Bon- sall. 2018. An upper bound for the background rate of human extinction. From Figures 3 and 4 we can observe that the Rare Earth Scientific Reports 9:11054. doi: 10.1038/ model is considerably more optimistic than the Sandberg model. s41598-019-47540-7. [10] Robert Strom G. 2015. We are not alone: extraterrestrial If we assume that Earth is very unique in our galaxy, we have technological life in our galaxy. the highest probability of living around 1 000 000 years. On Astrobiol Outreach 3: 144. the other hand, universe observations do not support well the doi: 10.4172/2332-2519.1000144. [11] Chenoa Tremblay and Steven Tingay. 2020. A seti sur- uniqueness of our planet in terms of the large amount of suns vey of the vela region using the murchison widefield ar- with their planets. Further galaxy observations should provide ray: orders of magnitude expansion in search space. more information which model fits the reality better. doi: From Figures 5 to 10, we can interpret that parameters 2, 5, 7, 10.1017/pasa.2020.27. [12] Peter Douglas Ward and Donald Eugene Brownlee. 2000. and 9 play the most important role in predicting the extinction of humanity. This seems novel compared to previous studies, and Rare Earth: Why Complex Life Is Uncommon in the Universe. Copernicus. enables further discussion and studies regarding the causes and [13] Tom Westby and Christopher J Conselice. 2020. The as- consequences of it. Whatever the case, while parameters seem trobiological copernican weak and strong limits for in- to have numerically equal role and weight, studies of numerical telligent life. relevance of the parameters of the equations (2) or (4) indicate The Astrophysical Journal 896(1):58. doi: 10. significant differences. 3847/1538-4357/ab8225. [14] Beno Šircelj, Laura Guzelj Blatnik, Ajda Zavrtanik Drglin, Parameter 9 represents the choice of the distribution of the and Matjaž Gams. 2019. Expected human longevity. parameters. This is consistent with the distribution studies in Infor- this paper indicating that the probability curve for the longevity macijska družba, volume B. of human civilization strongly influences the obtained results. Finally, while models do perform differently given different values of parameters, some patterns seem to emerge quite con- sistently if the parameters are set reasonably. ACKNOWLEDGMENTS The authors acknowledge the financial support from the Slove- nian Research Agency (research core funding No. P2-0209). 83 Change ahead! Questioning and changing beliefs in online discussions Lenart Motnikar† David Garcia Hannah Metzler Complexity Science Hub Complexity Science Hub Vienna Complexity Science Hub Vienna Vienna & & lenart.motnikar@ait.ac.at Graz University of Technology Graz University of Technology dgarcia@tugraz.at metzler@csh.ac.at ABSTRACT inspected the latter mainly focused on features of the argument itself, measuring factors like linguistic, stylistic, Recent studies of persuasion and persuasibility in online and topical composition, as well as user interaction [3, 4, 5]. discussions have predominantly focused on argument- These studies, however, all focused on features pertaining specific features but not addressed extraneous factors that directly to the arguments, neglecting a domain of potential make someone question their beliefs in the first place. In this explanatory significance – how users behave outside the exploratory study, we sought to uncover factors underlying argument. users’ decisions to challenge their views in an online Research in computational social science has indeed shown discussion forum and subsequently change them. We that the behavioral and linguistic traces of online activity can discovered that the examined psycholinguistic factors play a carry important information about the psychology of greater role in the questioning than the changing of opinions humans and the interactions between them [6]. and further discuss the findings. Observing those would enable not only a deeper understanding of susceptibilities to being persuaded once a KEYWORDS view has been questioned but also delving into the factors persuasion, ChangeMyView, reddit, belief change that influence the questioning of one’s view in the first place. Reddit provides a unique opportunity for such investigation, as each user’s history of activity is publicly available and, 1 INTRODUCTION because of the variety of discussion communities, less Social media are becoming an increasingly dominant means dependent on topic of discussion. of exerting persuasive influence on people. However, if not That being said, despite CMV’s credo stating that the forum is done appropriately and targeted at individuals who are not susceptible in the first place, attempts at persuasion can “A place to post an opinion you accept may be flawed, in an effort result in backfiring, pushing people further apart [1]. As to understand other perspectives on the issue.” these phenomena propagate through the population, affecting and changing society at large, persuasion in online only a small minority (13%) of the community’s members social spaces has become an important topic of scientific ever post submissions on their own opinions, while the inquiry. majority only participate in the discussions of others’ views. Providing an open-access, natural discursive environment While posting on CMV does not guarantee that a person is, in with user-labeled data, the Change My View (CMV) Reddit fact, open to view-change and the environment is not the only forum has become a popular research subject, being one where the process takes place, the relatively small share investigated in at least 20 studies [2] from fields like of submitting users implies that deliberately and openly computational linguistics, behavioral design, and discourse challenging one’s view is a relatively unique phenomenon, studies. even within a purposed community like CMV. On the forum, users write about their views on various topics To fill the identified gap in current research on persuasion, with the purpose of having their views challenged. Users can we set out to explore the factors associated with users’ then award the arguments of others with a “delta” if they decisions to, first, challenge their opinions on CMV, and succeed in changing their initial stance. second, to end up changing them. Studies of persuasion on the forum have mostly focused on To answer these questions, we inspected the users’ activities what makes an argument persuasive and, to a lesser extent, on Reddit before they joined the CMV community. As this is what makes the users persuadable. The studies that an exploratory endeavor without much theoretical foundation, we focused on surface-level parameters, observing the user’s posting patterns, stylistic and linguistic Permission to make digital or hard copies of part or all of this work for personal features, indicators of personality, and their community 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 affiliation. 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). 84 Information Society 2021, 4–8 October 2021, Ljubljana, L. Motnikar et al. Slovenia 2 METHOD We then set to explore the data in two problems, comparing two sets of users in each task. We collected submissions and comments that were posted to CMV between January 1st and December 31st, 2020, excluding 2.2 Task 1: Questioning one’s view those that were removed by moderators, or made by bots and deleted accounts. This left us with 31,419 submissions In Task 1, we explored the characteristics of CMV users who and 1,563,865 comments, authored by 158,724 unique users, posted submissions questioning their views by comparing 21,168 of whom posted submissions. them to those who only commented on others’ posts but We studied users who made their first contribution to CMV never submitted posts on their own views. in the studied period and were active on the forum over a After filtering by the previously mentioned criteria, the span of at least seven days. While this threshold is somewhat experimental group consisted of 4,639 users who posted at arbitrary, it allowed us to exclude users who were mere least one submission on CMV. passersby of the community (who may be unfamiliar, We compared those users to a control group of the same size, unserious, or even purposefully disruptive), while retaining randomly selected from the users that passed the criteria but a representative sample accounting for a majority (69%) of never posted their submission (although they may have done newcomer-created content. so after the studied period). From here on, we refer to these We then downloaded the users’ post histories one year groups as questioning (Q) and non-questioning (Non-Q). before their first post (submission or comment) on CMV and imposed additional filters, keeping the users who: 2.3 Task 2: Changing one’s view a) made less than 10,000 submissions and comments, to In the second part, we were interested in finding the exclude potential bots and spammers, and characteristics underpinning one’s susceptibility to view- b) made at least 10 posts containing 100 analyzable tokens change. For this, we divided questioning users into two before joining CMV, to ensure enough data. subgroups: those susceptible (S) and non-susceptible (Non- For each user, we created two separate corpora, one of pre- S) to view-change. CMV submissions and one of pre-CMV comments. We then We deemed a submission as ending in view-change if its analyzed their posts across various domains, excluding author has awarded a “delta” that has been confirmed by the deleted and non-English (estimated automatically, using [7]) forum’s Delta-Bot, which checks for rule compliance. posts from text analysis. We selected CMV submissions that garnered at least 10 comments (indicating that some discussion took place) and 2.1 Investigated features compare authors who changed their views in either 100% Posting behavior. First, we collected data on the users’ (n=1,435) or 0% (n=1,204) of the submissions they posted. posting behavior, including days of activity pre-CMV activity, We opted for this distinction following [3], presupposing that the number of communities they were involved with, the the differences would be more notable between extremes. average length of submissions and comments, and their daily rates of posting. 3 Psycholinguistic characteristics. Second, we scored the RESULTS post histories on selected categories of the LIWC2015 In both tasks, we conducted a series of Bonferroni-Holm- dictionary [8], a popular tool for psycholinguistic research, corrected significance tests, comparing the features of the containing common words and word stems categorized by users’ pre-CMV submission and comment corpora grammatical and semantic categories. separately. We present results in Table 1 for Task 1 and Table We selected features relating to grammar, as well as selected 2 for Task 2, showing only features that yielded significant psychological categories. The latter included affective, differences, due to spatial limitations. cognitive, social, perceptual, and biological processes, drives, In Task 1, we observed that questioning users, on average, relativity, and time orientations. posted submissions more often while having a shorter Formatting and structure. Third, we looked at the outward duration of pre-CMV activity. appearance and structure of users’ posts by extracting Regarding LIWC, users differed in most of the studied Markdown formatting features, namely the use of bold, categories. In most cases, the trend pointed in the same italics, quotations, links, and un/ordered lists. direction in both submissions and comments. In some cases, Personality. Fourth, we built a predictor of BIG5 personality the difference was significant only in one set, and in a few, the traits by matching the top and bottom 100 n-grams that were trends in submissions and comments opposed one another. shown to be associated with each personality dimension in Regarding formatting, questioning users used more ordered [9] and summing their correlation-weighted scores. lists in both sets of corpora, while they used fewer quotes in Reddit communities. In addition, we also explored the comments. differences in the communities where the users were active, The users’ posts exhibited quite inconsistent manifestations to see if particular communities are more or less popular of personality, expressing lower neuroticism in submissions, within a certain population. We looked at the subreddits while in the comments, they showed higher agreeableness, where the users posted and calculated the percentages of extraversion and conscientiousness, and lower openness. affiliated users in the studied groups. 85 Change ahead! Information Society 2021, 4–8 October 2021, Ljubljana, Questioning and changing views in online discussions Slovenia Table 1. Significance testing results in Task 1. The numbers Table 2. Significance testing results in Task 2. Arrow represent effect sizes (Cohen’s d). Arrow direction represent how directions represent feature expression in S users relative to Non-S. the feature expresses in Q users relative to Non-Q. The number of arrows denotes significance at p<.05, p<.01, p<.001, or p<.0001. Feature Characteristic of susceptibility? Posting features Feature Characteristic of questioning? Submissions per day -.17 ↓↓ Posting features Submissions per day .32 ↑↑↑↑ Submissions Comments Days of activity -.39 ↓↓↓↓ Formatting Ordered list .08 .14 ↑ Submissions Comments LIWC Personality Function words .14 ↑↑↑↑ .07 ↑ Agreeableness .01 .15 ↑ Pronouns .16 ↑↑↑↑ .21 ↑↑↑↑ Neuroticism .11 .20 ↑↑↑↑ Personal pronouns .10 ↑↑↑ .22 ↑↑↑↑ 1st person singular -.03 .31 ↑↑↑↑ In Task 1, for example, questioning users had a 2.37 times 1st person plural -.10 ↓↓ .00 higher likelihood to post on r/askphilosophy (a forum for 2nd person .14 ↑↑↑↑ .04 discussion of philosophical ideas) and a relative likelihood of 3rd person plural .02 -.11 ↓↓↓↓ 0.3 to post on r/bestof (a forum where users share their Impersonal .15 ↑↑↑↑ .06 ↑ favorite comments across all Reddit). Similarly, in Task 2, Articles -.06 -.21 ↓↓↓↓ susceptible users were 2.7 times more likely to post on Prepositions -.07 -.16 ↓↓↓↓ r/getdisciplined (a support community for self- Common adverbs .11 ↑↑↑↑ .08 ↑↑ improvement) but had a likelihood of 0.58 to post on Conjunctions .13 ↑↑↑↑ .11 ↑↑↑↑ r/socialism. Common adjectives .10 ↑↑↑ -.08 ↓↓ Comparisons .12 ↑↑↑↑ -.04 Table 3: Quotients of subreddit association rates Interrogatives .26 ↑↑↑↑ .12 ↑↑↑↑ between Q and Non-Q users in Task 1 and S and Non-S Numbers -.15 ↓↓↓↓ -.08 ↓↓ users in Task 2. Quantifiers -.03 -.08 ↓↓ Positive emotion -.01 .11 ↑↑↑↑ Task 1 Task 2 Negative emotion .16 ↑↑↑↑ -.03 subreddit ratio subreddit ratio Social processes .24 ↑↑↑↑ .04 askphilosophy 2.37 getdisciplined 2.70 Cognitive processes .16 ↑↑↑↑ .12 ↑↑↑↑ SuicideWatch 2.08 woooosh 2.33 Perceptual processes -.04 .09 ↑↑↑ FreeKarma4U 1.96 confidentlyincorrect 2.31 Drives .03 -.08 ↓↓ ask 1.95 ShitAmericansSay 2.31 Present focus .08 ↑ .08 ↑↑ findareddit 1.90 antimeme 2.28 Relativity -.20 ↓↓↓↓ -.17 ↓↓↓↓ … … Formatting The_Mueller 0.36 AbruptChaos 0.62 Quote .02 -.08 ↓↓ LeopardsAteMyFace 0.35 sports 0.62 Ordered list .07 ↑ .08 ↑↑ MaliciousCompliance 0.33 PoliticalDiscussion 0.61 Personality LivestreamFail 0.33 PS4 0.59 Openness -.06 -.16 ↓↓↓↓ bestof 0.30 socialism 0.58 Conscientiousness -.04 .08 ↑↑ Extraversion .04 .16 ↑↑↑↑ Agreeableness -.06 .09 ↑↑↑ 4 DISCUSSION Neuroticism -.15 ↓↓↓↓ .03 In this study, we sought to uncover parameters that might In Task 2, there were fewer differences compared to Task 1. carry explanatory information about a user’s tendency to Regarding posting features, susceptible users exhibited a openly question and then change their views. First, we lower rate of posting submissions. There were no observable compared users who posted submissions on CMV to those differences in LIWC categories, while in formatting, that only commented. Second, we compared the submitters susceptible users exhibited a slightly higher use of ordered who always ended up changing their views to those that lists in the comments. Regarding personality, susceptible never did. users expressed higher agreeableness and neuroticism in the We first observed that the users who posted submissions to comments. CMV also had a higher rate of posting submissions elsewhere, We also inspected if the user groups in both tasks differ in the before they joined the forum, indicating that the users who communities they contribute to. Table 3 presents ratios submit to CMV are in general more inclined to post between the percentages of users who were affiliated with submissions, which could be due to many factors. We the community in each group, with a bottom threshold of 2%. observe a similar albeit weaker discrepancy in Task 2, where 86 Information Society 2021, 4–8 October 2021, Ljubljana, L. Motnikar et al. Slovenia a higher rate of posting submissions was characteristic of questioning users tend to be more personal in their non-susceptible users. expression. We then noticed that the time of the questioning users’ This considered, it is important to note that the effect sizes of activity or Reddit before their first contribution to CMV was observed differences are minimal, and without a deeper shorter on average. One explanation could be that the examination of context, nuanced interpretation is difficult. submissions were posted from secondary accounts, perhaps An interesting observation is that across all features, the to anonymize one’s expression of a view they would not feel groups differed a lot more in Task 1 than in Task 2. This comfortable sharing otherwise. Despite our intentions to shows that the psycholinguistic characteristics underpinning limit such “throwaway” accounts by imposing a limit of one’s tendency to challenge their view on CMV play greater minimum activity, enough might have remained to have importance compared to the ones behind their susceptibility affected the data. to award “deltas”. At the same time, they show that the users We further observed that questioning users have a who decide to submit to CMV might gravitate towards a significantly different linguistic profile, as significant certain type of user, begging the question of generalizability differences appeared in several measured LIWC categories. of studies of the forum. Of those, function words and pronouns in particular have The personality measures showed several differences in both been studied the most and are known to bear psychological tasks but were inconsistent when comparing expressions in relevance, as they reveal the focus of the author’s attention submissions and comments. Given that differences for each and the relations between the entities discussed [10]. Higher dimension were shown only in one set of corpora, this might (personal) pronoun use, which was characteristic of high indicate contextual dependency. Research has indeed questioning users, generally points towards more personal shown that word correlation-based measures of personality and people-oriented language. However, when it comes to depend on communication contexts [11], which could also interpretation, it is important to also consider the different apply to those of submitting and commenting. The second contexts of submissions and comments, which differ in who contextual consideration is that the tokens used for they’re directed to. In submissions, where users address a personality estimation were taken from a study of posts on general audience, we observed that questioning users used Facebook and might therefore not translate well to the social more second person (“you”) and less first-person plural environment on Reddit. (“we”) pronouns. The role of second person has been We also observed that certain subreddits were more or less predominantly studied in close relationships, where it is likely to be visited by the studied groups, indicating some likely to entail confrontation [10]. However, in the context of kind of community preferences, although it is not obvious submissions, this is not likely to be the case. As they are what underlies them. Going forward, it would be interesting directed towards an unspecified reader, it is probably more to examine if these differences are driven by topic or by likely that the use of “you” is meant in a manner that is specific social characteristics. inquisitive or directing (e.g., “What do you guys think?”, “You The main takeaway from this study is that the explored should try this!”), showing initiative and an interest in others. factors, particularly those regarding language, have a greater This interpretation is also in line with the observation that role in underlying questioning one’s views on CMV, than questioning users used more interrogatives. changing them. However, as noted in the beginning, Next, the lesser use of first-person plural (“we”) in questioning users posted more submissions overall. It is submissions could indicate a lower degree of community important to note that although we interpreted our findings affiliation and belonging. It has previously been suggested through the lens of questioning beliefs, this might not be the that binding one’s view to a group disperses the feeling of main explaining factor behind the observations. It could be responsibility for it [5]. If questioning users hold beliefs as that the differences we observed are driven more by this their own rather than representing a group they identify general propensity to post submissions than a wish to with, they may be more likely to question their views. challenge one’s views. In the comments, we observed two further pronoun-related In the future, it would therefore be necessary to explore this trends. In particular, questioning users used more first- question further. For example, one could investigate if person singular (“I”), which entails greater self-focus, similar differences exist between submitters and non- perhaps as a means of explaining oneself, and less third- submitters in other communities or if these effects scale with person plural (“they”), indicating a lesser focus on an the users’ rates of posting submissions. To better understand outgroup or people in general. the mechanisms behind challenging beliefs, we would have Furthermore, we observed differences in several other to control for such factors, as well as discern how grammatic and semantic categories in both submissions and motivations for submitting in general interact with those comments. These point towards thematic and topical specifically relating to questioning views. discrepancy between the users’ use of language. As a general observation, questioning users used fewer numbers, articles, ACKNOWLEGMENT prepositions, and relativity, which indicates a lesser D. G. and H. M. acknowledge funding from the Vienna Science propensity for complex, analytic, and concrete language. This and Technology Fund through the project “Emotional Well- is contrasted by a higher use of words in the psychological Being in the Digital Society” (Grant No. VRG16-005). process categories, supporting the previous explanation that 87 Change ahead! Information Society 2021, 4–8 October 2021, Ljubljana, Questioning and changing views in online discussions Slovenia REFERENCES [1] Simon Schweighofer, Frank Schweitzer, and David Garcia. 2020. A Weighted Balance Model of Opinion Hyperpolarization. Journal of Artificial Societies and Social Simulation 23, 3 (2020), 5. DOI: https://doi.org/10.18564/jasss.4306. [2] Nicolas Proferes, Naiyan Jones, Sarah Gilbert, Casey Fiersler and Michael Zimmer. 2021. Studying Reddit: A Systematic Overview of Disciplines, Approaches, Methods, and Ethics. Social Media + Society 7, 2 (Jun, 2021), 1-14. DOI: https://doi.org/10.1177/20563051211019004. [3] Humphrey Mensah, Lu Xiao, and Sucheta Soundarajan. 2019. Characterizing Susceptible Users on Reddit’s ChangeMyView. In Proceedings of the 10th International Conference on Social Media and Society (SMSociety ’19). Toronto, ON, Canada, 102-107. DOI: https://doi.org/10.1145/3328529.3328550. [4] John Hunter Priniski and Zachary Horne. 2018. Attitude Change on Reddit’s Change My View. In Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Madison, WI. 2279- 2284. [5] Chenhao Tan, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, and Lilian Lee. 2016. Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions. In Proceedings of the 25th international conference on world wide web. Montreal, QC, Canada, 613-624. DOI: https://doi.org/10.1145/2872427.2883081. [6] Michele Settanni, Danny Azucar, and Davide Marengo. 2018. Predicting Individual Characteristics from Digital Traces on Social Media: A Meta-Analysis. Cyberpsychology, Behavior, and Social Networking 21, 4 (April, 2018), 217-228. DOI: https://doi.org/10.1089/cyber.2017.0384. [7] Michal Mimino Danilak. 2021. langdetect 1.0.9. Python Package Index (PyPI), https://pypi.org/project/langdetect/1.0.9/. [8] James W. Pennebaker, Ryan L. Boyd, Kayla Jordan, and Kate Blackburn. 2015. The development and psychometric properties of LIWC2015. University of Texas at Austin, Austin, TX. [9] H. Andrew Schwartz et al. 2013. Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach . PloS one 8, 9 (2013), e73791. DOI: https://doi.org/10.1371/journal.pone.0073791. [10] Yla E. Tausczik, and James W. Pennebaker. 2010. The psychological meaning of words: LIWC and computerized text analysis methods. Journal of language and social psychology, 29, 1 (March, 2010), 24-54. [11] Matthias R. Mehl, Megan L. Robbins, and Shannon E. Holleran. 2012. How Taking a Word for a Word Can Be Problematic: Context- Dependent Linguistic Markers of Extraversion and Neuroticism. Journal of Methods and Measurement in the Social Sciences 3, 22 (2012). 30-50. DOI: https://doi.org/10.2458/v3i2.16477. 88 Kaj se lahko naučimo od Jacques Mehlerja, klasičnega kognitivnega znanstvenika What can we Learn from Jacques Mehler, a Classical Cognitive Scientist Amanda Saksida Institute for Maternal and child health Burlo Garofolo – Trieste Italija amanda.saksida@icloud.com POVZETEK classical cognitive science, modularity of mind, language acquisition, Jacques Mehler Prispevek prikazuje življenjsko delo Jacquesa Mehlerja, ki je bil eden uspešnejših evropskih raziskovalcev razvoja človeške kognicije, še posebej zgodnjega razvoja govora. Ob tem 1 Klasična kognitivna znanost in Mehlerjev doprinos predstavi glavne predpostavke klasične kognitivne znanosti – modularnost uma ter vlogo narave in vzgoje pri razvoju in V letu 2020 je v Parizu v starosti 83 let po dolgi delovanju miselnih procesov – in opiše, katere vpoglede je nevrodegenerativni bolezni umrl Jacques Mehler, eden izmed omogočilo empirično raziskovanje teh predpostavk v preteklih pomembnih mladih akterjev tako imenovane kognitivne desetletjih. Na kratko tudi oriše nova spoznanja, ki so revolucije, ki se je zgodila v 60-ih letih prejšnjega stoletja in je pomenila odmik od takrat prevladujočega behaviorizma k kognitivno znanost v zadnjih dveh desetletjih dodobra proučevanju vrojenih lastnosti kognicije. Od leta 1975 do spremenila in ki so deloma vplivala tudi na njegovo delo. Način, kako je Mehler ta nova spoznanja vedno znova 2001 je vodil psiholingvistični laboratorij v Parizu integriral v svoje delo, lahko predstavlja enega od modelov (Laboratoire de Sciences Cognitives et Psycholinguistique, sinteze empiričnega in teoretskega raziskovanja. EHESS-ENS). Zaradi po njegovem mnenju prezgodnje upokojitve v francoskem CNRS se je leta 2001 lotil še vzpostavitve laboratorija Language, Cognition and KLJUČNE BESEDE Development Lab na SISSA-ISAS v Trstu, ki ga je vodil do klasična kognitivna znanost, modularnost uma, razvoj govora, končne upokojitve leta 2016. Jacques Mehler Mehler je kot direktor pariškega laboratorija veljal za ABSTRACT klasičnega kognitivnega znanstvenika, ki je človeško kognicijo raziskoval v skladu z osnovnima predpostavkama, The article shows the life work of Jacques Mehler, who was da je um modularen ter da je večina miselnih procesov one of the most successful European researchers in the field of vrojenih. Ideja o modularnosti uma se je deloma napajala iz the development of the human mind, especially early language raziskav zgodnje nevrologije, vendar pa jo je v drugi polovici acquisition. The article presents the main assumptions of 20. stoletja najbolje izpeljal Jerry Fodor⁠. Fodorjeva različica classical cognitive science – the modularity of the mind and teorije o modularnosti uma, ki jo je povzel tudi Mehler, ne the role of nature and nurture in the development and nudi neposredne navezave na fiziološke procese, functioning of the mind – and describes which insights have predpostavlja pa, da na vsakem področju (modulu) been enabled by Mehler’s empirical research of these uma/kognicije veljajo drugačni načini učenja in zaznavanja assumptions over the past decades. New findings are also (angl. domain specificity), ki niso neposredno vezani na drug briefly presented that have changed cognitive science over the modul (angl. information encapsulation) in ki niso nujno last two decades and that have partly influenced his work. The vezani na eno samo čutilo [1]. Ideja o vrojenosti miselnih way in which Mehler has repeatedly integrated these new procesov je, podobno, izhajala iz spoznanja o visoki insights into his work can represent one of the models of the specializaciji nekaterih delov kognicije že zelo zgodaj v synthesis of empirical and theoretical research. razvoju, še najbolj izrazito v razvoju govora [2]. Skladno s to idejo je učenje pravzaprav zgolj sprožanje nastavitev KEYWORDS parametrov, ki so sami po sebi vrojeni [3] Kognitivna znanost, ki je predpostavljala modularnost uma in vrojenost miselnih Permission to make digital or hard copies of part or all of this work for personal or procesov je pomenila neposredno kritiko behaviorizma, ki je classroom use is granted without fee provided that copies are not made or predpostavljal splošne mehanizme učenja za vse miselne 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 procese in po katerem je učenje vedno neposredni odziv na work must be honored. For all other uses, contact the owner/author(s). zunanje dražljaje [4]. Razprava o vlogi narave in vzgoje je sicer stara tisočletja, in mnenja o tem, da so nekateri miselni © 2021 Copyright held by the owner/author. procesi vrojeni, saj jih lahko opazujemo takoj po rojstvu ali še 89 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Saksida, A. pred njim, se še danes silovito krešejo z mnenji, da so ti izvršilne funkcije že kmalu po rojstvu: dojenčki iz dvojezičnih procesi posledica učinkovitih splošnih učnih mehanizmov. družin že pri 7 mesecih izkazujejo boljšo kontrolo in inhibicijo kot njihovi enojezični vrstniki [23], [24]. V teh teoretskih okvirih je Mehler izpeljal vrsto empiričnih raziskav o tem, kako je človeško zaznavanje selektivno in Mehlerjeva izhodiščna pozicija je bila torej jasna in večina pogojeno z vrojenim znanjem tudi na področju prepoznavanja objavljenih del se je ukvarjala z omejitvami splošnih učnih in učenja maternega jezika. Ugotovil je, da je zlog osnovna mehanizmov ter visoko specializiranimi mehanizmi, ki so po zaznavna enota v govoru in da je prepoznava zloga kot njegovem prepričanju najverjetneje vrojeni (specializirani osnovne zaznavne enote pomembna pri učenju in segmentaciji mehanizmi zaznavanja, stavčni ritem in prozodija, soglasniki- besed [5], [6], in to že od rojstva naprej [7]. Vendar pa so že samoglasniki). Vendar pa je pri svojem delu ostajal trdno novorojenčki pozorni tudi na druge pomembne elemente zavezan empiričnemu preverjanju glavnih teoretskih vprašanj govora, kot so premori in spremembe v intonaciji [8], [9]. s pomočjo čim bolj objektivnega in nepristranskega Skupaj s študenti je raziskoval zmožnost razločevanja opazovanja človeških odzivov od rojstva naprej, pravzaprav različnih jezikov ob rojstvu in ugotovil, da novorojenčki podobno kot Piaget, čeprav so ju ločevala nesoglasja. Ker mu prepoznajo materin glas ter ritem jezika, ki so ga poslušali že je empirično raziskovanje omogočalo vsaj delno distanco od pred rojstvom, ter ga ločijo od jezika z drugačnim ritmom, teoretskega dela, ostaja odprto vprašanje, kako bi na razvoj vendar pa ne ločijo dveh ritmično podobnih jezikov [10], [11]. kognitivne znanosti gledal danes. Kljub določeni meri skepse glede neposredne povezave med (vrojenimi) miselnimi procesi in njihovo fiziološko 3 Kognitivna znanost danes v odnosu do Mehlerjevega (nevrološko) podlago je bil zavezan eksperimentalnemu delu dela ter sodelovanju pri metodoloških inovacijah, potrebnih za raziskave zgodnjega razvoja. To je kasneje omogočilo tudi Predstavljena teoretska vprašanja kognitivne znanosti so bila v nekatera dognanja s področja nevrologije kognitivnih zadnjih letih soočena z novimi podatki, ki so kazali na to, da procesov, ki jih je preučeval. Med drugim je prvi uporabil lahko splošni kognitivni primanjkljaji zaradi spremenjenega NIRS (angl. near-infrared spectroscopy) tehniko optične vnosa podatkov pripeljejo do specifičnih razvojnih motenj. Na topografije pri novorojenčkih ter tako prvi pokazal, da človek primer, specifična jezikovna motnja bi bila lahko posledica že ob rojstvu procesira govor v levi možganski polovici [12]. centralnega primanjkljaja v procesiranju hitrih zvočnih dražljajev [25]. Podobno sosledje morda velja tudi za 2 Mehlerjeva integracija novih idej v klasično kognitivno disleksijo [26], [27]. Vendar pa mnenja o izvoru učnih znanost razvojnih motenj ostajajo deljena in zato še vedno prevladujejo kognitivni modeli, ki predvidevajo modularnost Kognitivna znanost se je na prelomu tisočletja zopet začela posameznih področij kognicije [28], [29]. korenito spreminjati. Bolj množično so se začele zbujati kritike teorije o modularnosti uma ter selektivnih zaznavnih in Ker so kognitivni procesi nujno posledica dejavnosti učnih mehanizmov. Naraslo je tudi zanimanje za vlogo možganov, ideja modularnosti uma tudi v svojih novejših splošnih statističnih učnih mehanizmov pri učenju govora, na različicah vselej predpostavlja, da so specializirani procesi primer zaznavanja pogostosti pojavitve osnovnih gradnikov tisti, ki zasedajo nek točno določen predel možganskega tkiva jezika, fonemov, zlogov, besed, ter pogojnih verjetnosti [30]. To idejo so nedavna spoznanja v nevroznanosti dodobra sopojavljanja teh gradnikov v jeziku [13], [14]. To je po načela z dokazi, da so posamezni možganski moduli, ki so bili naključju sovpadlo tudi z Mehlerjevim premikom iz Pariza v tradicionalno razumljeni kot osnovni kognitivni moduli, v Trst leta 2001. Novi laboratorij v Trstu se je začel ukvarjati z resnici deli nevronskih mrež, ki pa so v možganih pogosto odnosom med statističnim učenjem in osnovnimi uporabljene večkrat in za različne namene (angl. neural reuse, predpostavkami klasične kognitivne znanosti. S skupino neural redeployment) [31], [32]. Še več, bistvo specializacije mladih sodelavcev je Mehler preučeval lastnosti in omejitve nevronskih mrež verjetno ni v njenih osnovnih gradnikih, statističnega učenja pri segmentaciji in učenju besed. možganskih modulih, temveč v načinu, kako so ti gradniki Statistično učenje recimo deluje drugače na samoglasnikih kot povezani. Zato je mogoče za iste kognitivne funkcije na soglasnikih [15], [16], kadar pa so si statistične in opazovati dejavnost različnih nevronskih mrež, ali pa obratno, prozodične informacije v nasprotju, se človeški um bolj dejavnost istih (ali vsaj navidezno istih) nevronskih mrež za zanaša na prozodične [17]–[19]. različne kognitivne funkcije [33]. Primer za slednje so ekspertne veščine, ki jih eksperti lahko navidezno opravljajo Opažanje, da je zaznavanje selektivno, je pripeljalo tudi do avtomatizirano, vendar pa obenem ohranjajo centralni nadzor študij bolj ali manj specializiranih mehanizmov zaznavanja, nad dinamiko dogajanja, kar bi lahko nakazovalo, da je za dva npr. zaznavanje identitete (ponavljanja, npr. ponavljanja procesa odgovorno eno (ali vsaj na videz eno) nevronsko zlogov) in zaznavanje robov (npr. boljše pomnjenje zlogov na omrežje [34]. robovih besed), ki v veliki meri olajšajo zgodnje učenje jezika [20]–[22]. Obenem pa so v laboratoriju potekale tudi Čeprav so se kognitivni modeli delovanja kognicije v raziskave o tem, kako razvoj govora, kot specializiranega preteklosti lahko ogradili od modelov nevrološkega delovanja, znanja, vpliva na druge dele človeške kognicije, na primer na ker ti niso bili v neposrednem nasprotju s prvimi, ima centralne nadzorne in izvršilne funkcije. Na primer, ponujeni model organizacije nevronskih mrež neposredne vsakodnevno poslušanje dveh ali več jezikov vpliva na posledice tudi za kognitivne modele, saj predpostavlja, da so vsa specializirana znanja modularna samo v zelo abstraktnem 90 Kaj se lahko naučimo od Jacques Mehlerja, klasičnega Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia kognitivnega znanstvenika smislu, ter da so nujno posledica učenja in ne vrojena. Vendar REFERENCES pa obenem ponudi svežo rešitev uganke, s katero se že dolgo [1] J. A. Fodor, The modularity of mind. MIT Press, 1983. soočajo raziskovalci specifičnih razvojnih motenj, ki se jim [2] N. Chomsky, „A Review of B . F . Skinner ’ s Verbal Behavior“, izmika enoznačna razlaga izvora teh motenj⁠. Možno je Language (Baltim). , let. 1, str. 26–58, 1959. namreč, da kognitivni profili in razvojne motnje niso [3] E. Gibson in K. Wexler, „Triggers“, Linguist. Inq. , let. 25, št. 3, str. 407–454, 1994. posledica lastnosti in pomanjkljivosti v posameznih [4] B. F. Skinner, „Behaviorism at Fifty“, Science, let. 140, št. 3570, str. možganskih modulih, temveč predvsem načina, kako so 951–958, 1963. organizirane nevronske mreže [35], [36]. Organizacija [5] A. Cutler in J. Mehler, „The periodicity bias“, J. Phon. , let. 21, št. nevronskih mrež pa je v veliki meri odvisna od dogodkov v 1/2, str. 103–108, 1993. času nastajanja človeškega bitja⁠. [6] J. Mehler, J. Y. Dommergues, U. Frauenfelder, in J. Segui, „The Syllable’s Role in Speech Segmentation“, J. verbal Learn. evrbal Behav. , let. 20, str. 298–305, 1981. To pa je pravzaprav pot, ki ji je sledil tudi Mehler, ko je [7] J. Bertoncini in J. Mehler, „Syllables as Units in InfantSpeech zametke razvoja govora iskal in razpoznaval v obdobju Perception“, Infant Behav. Dev. , let. 4, str. 247–260, 1981. globoko pred prvo besedo, že takoj po rojstvu. Na novorojena [8] J. Bertoncini, C. Floccia, T. Nazzi, in J. Mehler, „Morae and človeška bitja je vedno gledal kot na aktivne, zavedajoče se syllables: rhythmical basis of speech representations in neonates.“, soudeležence pri lastnem razvoju, in logična posledica tega Lang. Speech, let. 38, št. 4, str. 311–329, 1995. [9] A. Christophe, J. Mehler, in N. Sebastián-Gallés, „Perception of pogleda je bila, da so se nekateri njegovi študentje in sodelavci lahko spustili na področje raziskovanja izkušenj in Prosodic Boundary Correlates by Newborn Infants“, Infancy, let. 2, št. 3, str. 385–394, jul. 2001. znanj, ki jih zarodki pridobijo že pred rojstvom⁠. Nove [10] F. Ramus, M. D. Hauser, C. Miller, D. Morris, in J. Mehler, raziskave tako med drugim ugotavljajo, kako lahko pri „Language Discrimination by Human Newborns and by Cotton-Top zarodkih merimo in spodbujamo njihovo zmožnost slušne Tamarin Monkeys“, Science, let. 288, št. 5464, str. 349–351, apr. (glasba, govor, glas) ali vidne prepoznave (obrazne poteze) ter 2000. pomnjenja in kako lahko to učinkuje na organizacijo [11] T. Nazzi, J. Bertoncini, in J. Mehler, „Language discrimination by newborns: toward an understanding of the role of rhythm.“, J. Exp. nevronskih mrež že pred rojstvom [37], [38]. In tako se Psychol. Hum. Percept. Perform. , let. 24, št. 3, str. 756–66, jun. nadaljuje naloga, ki si jo je zadal Mehler: ugotoviti, koliko 1998. lahko prispeva dejavnost in stimulacija na zmožnost [12] M. Peña idr. , „Sounds and silence: An optical topography study of zaznavanja in razločevanja ter na učenje, vendar pa ne več pri language recognition at birth“, Proc. Natl. Acad. Sci. , let. 100, št. 20, novorojenčkih, kot je to počel on, temveč že pred rojstvom. ⁠ str. 11702–11705, 2003. [13] J. R. Saffran, R. N. Aslin, in E. L. Newport, „Statistical Learning by 8-Month-Old Infants“, Science, let. 274, št. 5294, str. 1926–1928, 4 Sklep 1996. [14] D. Swingley, „Statistical clustering and the contents of the infant Jacques Mehler je svoje področje zapustil v času, ko je vocabulary“, Cogn. Psychol. , let. 50, št. 1, str. 86–132, feb. 2005. gotovosti v zvezi z razumevanjem kognicije na videz manj, saj [15] L. L. Bonatti, M. Peña, M. Nespor, in J. Mehler, „On consonants, so se zrahljali klasični kognitivni modeli. Vendar pa se zdi, da vowels, chickens, and eggs.“, Psychol. Sci. , let. 18, št. 10, str. 924–5, so nedavna spoznanja o povezljivosti možganov odprla nove okt. 2007. [16] J. M. Toro, M. Nespor, J. Mehler, in L. L. Bonatti, „Finding words možnosti za razumevanje razvoja in delovanja uma. In prav mogoče je, da bi se tudi Jacquesovo delo, če bi bil še vedno and rules in a speech stream: functional differences between vowels and consonants.“, Psychol. Sci. , let. 19, št. 2, str. 137–44, feb. 2008. dejaven, usmerilo v raziskovanje nevronskih omrežij, ki [17] A. L. Ferry idr. , „On the edge of language acquisition: Inherent sodelujejo pri procesiranju jezika od rojstva naprej ali pa še constraints on encoding multisyllabic sequences in the neonate pred rojstvom⁠. Gotovo pa je, da bi ga radovednost in brain“, Dev. Sci. , let. 19, št. 3, str. 488–503, 2016. natančnost, ki ju je gojil pri sv [18] A. Saksida, A. Langus, in M. Nespor, „Co-occurrence statistics as a ojem delu, še naprej vodila v language-dependent cue for speech segmentation“, Dev. Sci. , let. 20, tehtno pretresanje mej ter omejitev modelov razvoja in št. 3, str. e12390-n/a, 2016. delovanja človeškega uma. [19] M. Shukla, M. Nespor, in J. Mehler, „An interaction between prosody and statistics in the segmentation of fluent speech.“, Cogn. In prav to je vodilo, ki je lahko koristno za vsakogar, ki ga Psychol. , let. 54, št. 1, str. 1–32, feb. 2007. zanima razvoj človeškega uma. Z natančnim pretresanjem [20] S. Benavides-varela in J. Mehler, „Verbal Positional Memory in 7- možnosti, ki jih odpira vsak model delovanja človeškega uma, Month-Olds“, Child Dev. , let. 86, št. 1, str. 209–223, 2015. in možnih odgovorov, ki jih nudijo človeški odzivi na [21] A. D. Endress, M. Nespor, in J. Mehler, „Perceptual and memory constraints on language acquisition.“, Trends Cogn. Sci. , let. 13, št. dražljaje, lahko vsakdo od nas prispeva delež novega vedenja 8, str. 348–53, avg. 2009. o pomenu in funkciji modulov – vrojenih ali priučenih, [22] A. D. Endress, B. J. Scholl, in J. Mehler, „The role of salience in the anatomskih ali kognitivnih – ki omogočajo specializirana extraction of algebraic rules.“, J. Exp. Psychol. Gen. , let. 134, št. 3, znanja, lastna človeku. str. 406–19, avg. 2005. [23] A. M. Kovács in J. Mehler, „Cognitive gains in 7-month-old bilingual infants.“, Proc. Natl. Acad. Sci. U. S. A. , let. 106, št. 16, str. 6556–60, apr. 2009. ZAHVALA [24] A. M. Kovács in J. Mehler, „Flexible learning of multiple speech Za pomoč pri zbiranju informacij za prispevek se zahvaljujem structures in bilingual infants“, Science, let. 325, št. 5940, str. 611–2, kolegom, ki so v istem času pisali retrospektivne članke o jul. 2009. življenju in delu Jacquesa Mehlerja: Jean Remy Hochmann, [25] A. Karmiloff-smith, „Development itself is the key to understanding developmental disorders“, Trends Cogn. Sci. , let. 2, št. 10, str. 389– Judit Gervain, Agnes Kovacs, Stanislas Dehaene. 398, 1998. 91 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Saksida, A. [26] U. Goswami, „Sensory theories of developmental dyslexia: three challenges for research“, Nat Rev Neurosci, let. 16, št. 1, str. 43–54, jan. 2015. [27] R. Hari in H. Renvall, „Impaired processing of rapid stimulus sequences in dyslexia.“, Trends Cogn. Sci. , let. 5, št. 12, str. 525– 532, dec. 2001. [28] A. D. Baddeley, „Modularity, working memory and language acquisition“, Second Lang. Res. , let. 33, št. 3, str. 299–311, 2017. [29] I. Peretz in M. Coltheart, „Modularity of music processing“, Nat. Neurosci. , let. 6, št. 7, str. 688–691, 2015. [30] J. Zerilli, „Neural redundancy and its relation to neural reuse“, Philos. Sci. , let. 86, št. 5, str. 1191–1201, 2019. [31] M. L. Anderson, „Neural reuse : A fundamental organizational principle of the brain“, Behav. Brain Sci. , let. 33, str. 245–313, 2010. [32] M. L. Anderson in B. L. Finlay, „Allocating structure to function: the strong links between neuroplasticity and natural selection“, Front. Hum. Neurosci. , let. 7, št. January, str. 1–16, 2014. [33] J. Zerilli, „Neural Reuse and the Modularity of Mind : Where to Next for Modularity ?“, Biol. Theory, 2018. [34] A. Guida, G. Campitelli, in F. Gobet, „Becoming an expert: Ontogeny of expertise as an example of neural reuse“, Behav. Brain Sci. , let. 39, 2016. [35] D. S. Grayson idr. , „Structural and Functional Rich Club Organization of the Brain in Children and Adults“, PLoS One, let. 9, št. 2, str. 1–13, 2014. [36] R. Siugzdaite, J. Bathelt, J. Holmes, in D. E. Astle, „Transdiagnostic Brain Mapping in Developmental Disorders“, Curr. Biol. , str. 1–13, 2020. [37] T. Donovan, K. Dunn, V. M. Reid, A. Penman, in R. J. Young, „Fetal eye movements in response to a visual stimulus“, Brain Behav. , let. 10, št. e01676, str. 1–6, 2020. [38] V. M. Reid idr., „The Human Fetus Preferentially Engages with Face- like Visual Stimuli Report The Human Fetus Preferentially Engages with Face-like Visual Stimuli“, Curr. Biol., let. 27, št. 12, str. 1825-1828.e3, 2017. 92 Vpliv informacije o ceni na subjektivno oceno zvoka violin Influence of Price Information on the Subjective Evaluation of Violin Sound Anja Šerbec Gimnazija Bežigrad Peričeva ulica 4 Ljubljana, Slovenija aanjaserbec@gmail.com POVZETEK more expensive was rated significantly better the second time. The cheapest violin was rated significantly worse in the V raziskavi sem analizirala, v kolikšni meri informacija o ceni experiment in which the price information was given. inštrumenta vpliva na posameznikovo subjektivno oceno zvoka. Zanimalo me je tudi, ali so subjektivne ocene zvoka pri glasbenikih bolj povezane s ceno violin v primerjavi z ocenami KEYWORDS poslušalcev, ki se z glasbo ne ukvarjajo. S poskusom sem preverjala, če bo lažna informacija o ceni vplivala na subjektivno placebo effect, marketing, effects on sound perception, oceno zvoka. Pri poskusu, ko cena ni bila podana, sem zaznala assessment of violins, price information šibko do zmerno povezanost med ceno violine in subjektivno oceno zvoka. Pri poskusu, ko je cena bila podana, sem zaznali visoko povezanost med ceno in subjektivno oceno zvoka. 1 UVOD Posameznikovo vrednotenje zvoka je tako pri glasbenikih kot Drage stvari so nam pogosto všeč. Mogoče višjo ceno tudi pri udeležencih, ki se z glasbo ne ukvarjajo močno povezano povezujemo z boljšo kakovostjo izdelka, za nekatere pa je z informacijo o ceni. Violina, ki sem jo enkrat predstavila z njeno posedovanje dragega izdelka statusni simbol. Zdi se, da že sama realno prodajno ceno, drugič pa kot bistveno dražjo, je bila cena vpliva na naše vrednotenje izdelkov. V raziskavi sem drugič ocenjena zaznavno boljše. Najcenejša violina je bila v opazovala, kako informacija o ceni vpliva na mnenje poslušalca poskusu, v katerem je bila cena podana, ocenjena zaznavno o zvoku violine. Zanimalo me je, če in v kolikšni meri je slabše. poznavanje cene povezano s subjektivno oceno zvoka šestih violin popolnoma različnih cenovnih razredov. KLJUČNE BESEDE Osnovna predpostavka v ekonomiji je, da je stopnja ugodja placebo efekt, marketing, vplivi na zaznavanje, ocenjevanje pri uživanju nekega produkta odvisna le od lastnosti tega violin, informacija o ceni produkta in stanja posameznika. Tako naj bi na primer užitek, ki izhaja iz uživanja pijače bil odvisen le od molekulske sestave ABSTRACT pijače in stopnje žeje posameznika [6]. Pretekle raziskave pa so In this study, I investigated the extent to which an instrument's pokazale, da informacije iz okolja vplivajo na naše pričakovanje price information affects a person's attitude toward its sound. I in zaznavanje na senzoričnih področjih: bolečina, vid, vonj in was also interested in whether musicians' ratings of sound tudi sluh. Kljub temu ni popolnoma znano, kako možgani aesthetics were more strongly related to violin prices than were spremembe pričakovane vrednosti pretvorijo v spremembe the ratings of participants who were not involved with music. I izkušene vrednosti [10]. experimented with whether misinformation about price would V raziskavi na Stanfordski Univerzi leta 2007 so testirancem influence ratings of sound. In the experiment in which price was povedali, da bodo degustirali pet različnih vin in, da je namen not mentioned, I found a low to moderate correlation between poskusa preučiti vpliv časovnega trajanja degustacije na zaznan violin price and sound ratings. In the experiment where price was mentioned, I found a high correlation between price and sound okus. Eno izmed vin je bilo degustirano dvakrat: enkrat z realno ratings. informacijo o ceni in drugič z (lažno) nizko ceno. Testiranci so bili pozvani, naj poročajo o všečnosti in intenzivnosti okusa vin. Sound ratings correlated strongly with price information for Rezultati so pokazali bistvene razlike v oceni všečnosti okusa both musicians and non-musicians. The violin we presented once dveh degustacij istega vina predstavljenega z dvema različnima with its actual retail price and a second time as being significantly cenama. Sklepamo, da informacija o ceni znatno vpliva na Permission to make digital or hard copies of part or all of this work for personal or všečnost okusa. Poskus so izvedli še enkrat, le da so tokrat classroom use is granted without fee provided that copies are not made or distributed opazovali delovanje različnih možganskih centrov ob poskušanju 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 vina. Izkazalo se je, da je delovanje možganskih centrov be honored. For all other uses, contact the owner/author(s). povezanih z sprejemanjem senzoričnih signalov in njihovo Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia predelavo različno pri dveh degustacijah istega vina, ko je informacija o cenah podana [6]. Tudi raziskava z energijskimi © 2021 Copyright held by the owner/author(s). pijačami na Stanfordski univerzi iz leta 2005 je predhodno 93 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia A. Šerbec pokazala, da imajo določene marketinške poteze, kot je Kljub temu, da se zaznavanje zvoka razlikuje od posameznika določanje in spreminjanje cen vpliv na naše zaznavanje, presojo do posameznika raziskava na UWE Bristol iz leta 2005 kaže na in vedenje [9]. Pojav je bil poimenovan »marketinški placebo določeno stopnjo strinjanja pri kvalitativnih opisih lastnosti efekt«, saj je zelo podoben znanemu fenomenu placebo efekta v zvoka inštrumentov pri skupini glasbenikov [4]. Glasbeniki za farmaciji [6], [9]. opis »barve« zvoka (tembre) določene violine pogosto uporabijo »diferencialne pridevnike«. Primeri teh so: svetlost, trdost, jasnost, tankost, polnost, nazalnost, odprtost, ostrina, celo 2 TEORETIČNE OSNOVE »kovinskost« in »lesenost« zvoka. Glasbenik bi zvok izbrane V prispevku nas, podobno kot v prej opisanih poskusih, zanima violine ocenil na dimenzijah: svetel – temen, trd – mehek, jasen fenomen »placebo efekta«, le da se osredotočamo na zaznavanje – nejasen (»umazan«), tanek – širok, poln – prazen (»na prijetnosti zvoka. površju«), nazalen – usten, zaprt – odprt. Umestitev zvoka Placebo efekt je definiran kot »sprememba bolnikovega violine na prej-naštetih dimenzijah omogoča glasbenikom bolj stanja, ki jo je mogoče pripisati simboličnem vnosu zdravljenja poenoteno oceno zvoka izbrane violine v primerjavi z laiki. in ne farmakološkim ali fiziološkim lastnostim zdravljenja« [3, Uporaba naštetih lasnosti pri ocenjevanju s strani glasbenikov je pp.1]. Kljub temu, da je pojem placebo efekt ponavadi v raziskavi nakazana pri odgovorih na vprašanje kombiniranega uporabljen v povezavi z zdravili, je povezan z našim problemom, tipa »Kaj je vplivalo na vašo odločitev?«. Na to vprašanje so saj opisuje vpliv informacijskega nabora iz okolja na čutne glasbeniki večkrat odgovorili s pridevniki »čistost«, »mehkoba«, izkušnje. Opisala bom tudi katere lastnosti zvoka zaznavamo. »jasnost«, »odprtost«. Pri posameznikovi oceni pomembno vlogo igrajo osebne preference, a v splošnem velja, da ima dobra 2.1 Teorija pričakovanja violina svetel, mehek, jasen, širok, poln, usten in odprt zvok [1]. Teorija pričakovanja pravi, da testirančeva pričakovanja in prepričanost v dober rezultat sprožijo placebo efekt. V skladu s 3 OPIS RAZISKAVE to teorijo bi na primer testiranec iz skupine, ki pozna ceno pričakoval boljši zvok violin, ki so bile predstavljene kot dražje. Kot merski instrument sem uporabila spletni anketni vprašalnik, S prepričanostjo v dober rezultat in pristranskostjo bi jih zato ki je vseboval poseben tip vprašanja, ki je omogočilo testirancu razvrščanje violin glede na ocenil kot boljše [3]. njihovo subjektivno oceno zvoka. Vprašalnik je vseboval tudi zvočni zapis narejen z visoko 2.2 Klasično pogojevanje kakovostnim snemalnikom zvoka Zoom h1. Zvočni zapis je predstavljal posnetke lestvice in melodij, zaigranih na 6 različnih Teorija predvideva, da je placebo efekt pogojni refleks zaradi ponavljajočih se povezav med pogojnim dražljajem (nevtralna violin (Tabela 1). Vse violine so bile posnete v istem prostoru (predavalnica 212, UL PeF), na njih pa sem igrala z istim lokom. komponenta) in brezpogojnim dražljajem (aktivni element) [3]. Vprašalnik je bil sestavljen iz dveh delov: v prvem delu V našem primeru je pogojni dražljaj informacija o ceni in (Poskus 1) so bili podani zgolj posnetki melodij: izseki iz skladb brezpogojni dražljaj zvok, oziroma kakovost zvoka. Testiranci Bacha, Paganinija, Glazunova ter Mozarta. Bach je skladatelj bi lahko nezavedno prevzeli, da imajo dražje violine boljši zvok baroka, Glazunov romantike, Mozart klasicizma, Paganini pa in jih je posledično bolj prijetno poslušati (brezpogojni odziv). sicer spada v romantiko, vendar igranje njegovih Cappricciov Tako bi že sama informacija o višji ceni (pogojni dražljaj) sprožila večjo všečnost do poslušane violine. Seveda velja tudi ponazarja zmožnost inštrumenta, da se odzove na tehnično obratno: če bo imel testiranec negativne izkušnje z cenejšimi zahtevnih delih. Želela sem namreč predstaviti zvok vsake violine v različnih glasbenih slogih. Med glasbeniki namreč velja violinami, bo nižjo ceno podzavestno povezal z slabšim zvokom. prepričanje, da nekatere violine bolje »ustrezajo« določenim 2.3 Socialni vplivi na zaznavanje in vedenje slogom kot drugim. Poslušalci so s funkcijo »povleci in spusti« razvrstili šest Pomembno lahko vplivajo na zaznavanje tudi članstvo in procesi različnih violin glede na njihovo subjektivno oceno zvoka v skupini [6]. Kljub temu, da poskus ni bil izveden v skupinah, posamezne violine. Udeleženci so violine med sabo primerjali in ampak ga je vsak testiranec reševal sam, menim, da so socialni jih razvrstili od najboljše do najslabše glede na njihovo oceno dejavniki imeli močan vpliv na rezultate. Veliko ljudi je namreč estetike zvoka (Slika 1). Povprečne ocene so bile izračunane po prepričanih, da visoka cena violine kaže, da večina visoko naslednjih formulah: vrednoti to violino. Predvidevam, da bodo namesto, da bi se odločili avtonomno prilagodili mnenje skupini, oziroma temu, 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑛𝑛𝑜𝑜𝑛𝑛𝑛𝑛𝑛𝑛(𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛 kar menijo da je mnenje večine. 𝑖𝑖) ∑𝑁𝑁𝑗𝑗= ( 1 𝑀𝑀𝑀𝑀𝑀𝑀 = 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 − 𝑛𝑛𝑜𝑜𝑛𝑛𝑛𝑛𝑛𝑛𝑗𝑗(𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛𝑖𝑖) 𝑁𝑁 2.4 Lastnosti zvoka violin N – Število razvrstitev za 𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛𝑖𝑖 Kljub temu, da se v raziskavi ukvarjam z vplivom informacije o 𝑀𝑀𝑀𝑀𝑀𝑀𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 – pri Poskus 1 je enaka 6, pri Poskus 2 je enaka 7 ceni na všečnost zvoka violin in ne sámo kakovost zvoka, ne 𝑛𝑛𝑜𝑜𝑛𝑛𝑛𝑛𝑛𝑛𝑗𝑗(𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛𝑖𝑖) – razvrstitev violine i na določeno mesto moremo zanemariti precejšnje verjetnosti, da imajo dražje violine dejansko bolj kvaliteten zvok. Violine se ocenjuje po treh Ker pa sta bili 𝑀𝑀𝑀𝑀𝑀𝑀𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 pri Poskus 1 in Poskus 2 drugačni (pri dimenzijah: odzivnost, enakomernost in »glas«. Slednji je Poskus 1 je bila 𝑀𝑀𝑀𝑀𝑀𝑀𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 6, ker so testiranci razvrščali 6 izrazito subjektiven, zato vrednosti violin in kakovost zvoka ni posnetkov 6 različnih violin, pri Poskus 2 pa 7, saj so se posnetki mogoče objektivno oceniti [1]. 94 Vpliv informacije o ceni na oceno zvoka Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia Violine 3 ponovili), je bilo ocene potrebno normirati. Povprečne ceno violin v primerjavi z ocenami estetike zvoka v skupini ne- ocene so bile normirane od 1 do 100 po naslednji formuli: glasbenikov? Vprašanje 3: Ali bo napačna informacija o ceni violine (lažna 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑛𝑛𝑜𝑜𝑛𝑛𝑛𝑛𝑛𝑛(𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛 informacija, da je cenejša violina draga) vplivala na subjektivno 𝑖𝑖) = 𝑀𝑀𝑀𝑀𝑀𝑀 oceno zvoka pri tako glasbenikih kot tudi ne-glasbenikih? = 𝑅𝑅𝑅𝑅𝑅𝑅𝑁𝑁𝑅𝑅( 𝑜𝑜𝑜𝑜𝑛𝑛 − 𝑀𝑀𝑀𝑀𝑁𝑁𝑜𝑜𝑜𝑜𝑛𝑛 𝑀𝑀𝑀𝑀𝑀𝑀 Da bi odgovorila na Vprašanje 1 sem primerjala rezultate 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 − 𝑀𝑀𝑀𝑀𝑁𝑁𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 Poskusa 1 in Poskusa 2. Odgovor na Vprašanje 2 sem iskala v ∗ (𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑛𝑛𝑜𝑜𝑛𝑛𝑛𝑛𝑛𝑛(𝑣𝑣𝑛𝑛𝑛𝑛𝑣𝑣𝑛𝑛𝑛𝑛𝑛𝑛𝑖𝑖) rezultatih Poskusa 1. Pri odgovarjanju na Vprašanje 3 sem − 𝑀𝑀𝑀𝑀𝑀𝑀𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜) + 𝑀𝑀𝑀𝑀𝑀𝑀𝑜𝑜𝑜𝑜𝑛𝑛) uporabila rezultate Poskusa 2. 𝑅𝑅𝑅𝑅𝑅𝑅𝑁𝑁𝑅𝑅 – zaokroženo 𝑀𝑀𝑀𝑀𝑁𝑁𝑜𝑜𝑜𝑜𝑛𝑛 = 1 𝑀𝑀𝑀𝑀𝑀𝑀 Tabela 1: Maloprodajne cene violin 𝑜𝑜𝑜𝑜𝑛𝑛 = 100 𝑀𝑀𝑀𝑀𝑁𝑁𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 = 1 Cena (EUR) V drugem delu (Poskus 2) so bili poleg posnetkov melodij VIOLINA 1 16 500 podani tudi posnetki lestvice a-mol in informacija o ceni. Pri tem VIOLINA 2 7 200 so bili enaki posnetki iste violine (VIOLINA 3) podani dvakrat: VIOLINA 3 3 000 enkrat z resnično informacijo oceni (3000 evrov) in enkrat z VIOLINA 4 13 500 lažno informacijo o ceni (30.000 evrov). Posnetki lestvice so bili VIOLINA 5 15 200 dodani zato, da preusmerijo testirančevo pozornost od dejstva, da VIOLINA 6 20 000 je v Poskusu 2 navidezno bila predstavljena ena violina več. VIOLINA 7 (VIOLINA 3) 30 000 (3 000) Na koncu obeh poskusov so bili testiranci vprašani o tem, kaj je vplivalo na njihovo odločitev. Vprašanje je bilo 3.1 Opis vzorca kombiniranega tipa, nanj pa so lahko odgovorili z več odgovori: Poskus je v večini potekal preko spleta, delno pa tudi v živo na Gimnaziji Bežigrad in Akademiji za glasbo. Vprašalnik je do • »jakost zvoka« konca izpolnilo 100 ljudi, od tega 40 glasbenikov in 60 ne- • »barva zvoka (tembre)« glasbenikov. Reševan je bil v Sloveniji, Makedoniji, Rusiji, • »dinamične razlike« Nemčiji in Avstriji. Anketni vprašalnik je v celoti rešilo 4o žensk • »cena« in 31 moških. Anketni vprašalnik je bil objavljen na neuradni • »drugo« (odprtega tipa) Facebook strani dijakov in bivših dijakov Gimnazije Bežigrad, rešili pa so ga tudi dijaki Konzervatorija za glasbo in balet Ljubljana, študenti in profesorji Akademije za glasbo Ljubljana Testirance sem razdelila v dve osnovni skupini: glasbeniki in in Univerze za umetnost Gradec ter člani simfoničnega orchestra neglasbeniki. Kot glasbeniki so bili označeni vsi, ki so na RTV Slovenija. vprašanje »Kateri stavek vas opisuje?« odgovorili z enim izmed stavkov: • »Sem profesionalen–i/-a glasben–ik/-ica in igram inštrument – godalo.« • »Sem profesionalen–i/-a glasben–ik/-ica in ne igram inštrumenta, ki je godalo.« • »Obiskujem akademijo za glasbo in igram inštrument – godalo.« • »Obiskujem akademijo za glasbo in igram inštrument, ki ni godalo.« • »Obiskujem glasbeno šolo in igram inštrument – godalo.« • »Obiskujem glasbeno šolo in igram inštrument, ki ni godalo.« • »Končal-a sem osnovno [in srednjo] glasbeno šolo.« Kot ne-glasbeniki so bili označeni vsi, ki so na vprašanje »Kateri stavek vas opisuje?« odgovorili z enim izmed stavkov: • »Obiskoval-a sem nekaj let osnovne glasbene šole.« • »Ljubiteljsko se ukvarjam z glasbo.« • »Z glasbo se ne ukvarjam.« Zanimala so me naslednja raziskovalna vprašanja: Vprašanje 1: Ali se zaznavanje estetike zvoka glede na Slika 1: Razvrščanje violin po okusu od 1 do 6 (7). Zgornja informiranost o ceni pri obeh skupinah (glasbeniki, ne- slika kaže frekvence, oz. kako so udeleženci razvrščali glasbeniki) razlikuje? violine brez informacije o ceni. Spodnja slika kaže Vprašanje 2: Ali so subjektivne ocene zvoka pri skupini frekvence, oz. kako so udeleženci razvrščali violine z glasbenikov v poskusu brez informacije o ceni bolj povezane s informacijo o ceni. 95 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia A. Šerbec 4 REZULTATI IN UGOTOVITVE Uporabila sem Spearmanov koeficient korelacije za oceno povezanosti med ceno violin in oceno zvoka violin v celotnem Vpršanje 1: Ali se subjektivne ocene zvoka violin glede na vzorcu. V Poskusu 1 ni bilo statistično značilne korelacije med informiranost o ceni pri obeh skupinah (glasbeniki, ne- glasbeniki) razlikujeje? spremenljivkama cena violin in ocena zvoka violin, rs = 0,564; p Graf, ki ga prikazuje Slika 1 prikazuje povprečne normirane = 0,188; N = 6. Korelacija med spremenljivkama je bila v ocene violin na lestvici od 1 do 100, ki so izračunane na podlagi Poskusu 1 zmerna. V Poskusu 2 sem zaznala statistično značilno ocen violin v celotnem vzorcu (torej glasbeniki in ne-glasbeniki). korelacijo med spremenljivkama cena in subjektivna ocena zvoka, rs = 0,964; p = 0,0004; N = 6. Korelacija med spremenljivkama je bila v Poskusu 2 zelo močna. Primerjava normiranih ocen violin za To indicira, da je bila ocena zvoka v celotnem vzorcu pri oba poskusa Poskusu 2 povezana z informacijo o ceni violin. 70 60 60 63 Spearmanov koeficient korelacije za oceno povezanosti med 57 60 55 55 53 ceno violin in oceno zvoka violin sem izračunala za vsako 52 skupino posebaj. Pri skupini glasbenikov pri Poskusu 1 ni bilo 50 42 44 statistično pomembne korelacije med spremenljivkama cena in 37 38 39 40 subjektivna ocena zvoka, rs = 0,771; p = 0,072; N = 6. Korelacija med spremenljivkama je bila v Poskusu 1 močna. V Poskusu 2 30 sem pri skupini glasbenikov zaznala statistično pomembno 20 korelacijo med spremenljivkama cena in subjektivna ocena zvoka, rs = 0,886; p = 0,019; N = 6. Korelacija med 10 spremenljivkama je bila v Poskusu 2 zelo močna. 0 Pri skupini neglasbenikov pri Poskusu 1 ni bilo statistično VIOLINA VIOLINA VIOLINA VIOLINA VIOLINA VIOLINA VIOLINA pomembne korelacije med spremenljivkama cena in subjektivna 1 2 3 4 5 6 7 ocena zvoka rs = 0,314; p = 0,544; N = 6. Korelacija med Poskus 1 Poskus 2 spremenljivkama je bila v Poskusu 1 šibka. V Poskusu 2 sem pri skupini glasbenikov zaznala statistično pomembno korelacijo Slika 2: Povprečne ocene violin vseh testirancev za oba med spremenljivkama cena in subjektivna ocena zvoka, rs = poskusa (z in brez informacije o ceni 0,943; p = 0,005; N = 6. Korelacija med spremenljivkama je bila v Poskusu 2 zelo močna. Da bi ugotovila, če se ocene violin, ki so jih dali testiranci To indicira, da je bila ocena zvoka v vsaki od skupin pri pred in po informiranju o ceni (torej rezultati Poskusa 1 in Poskusu 2 povezana z informacijo o ceni violin. Poskusa 2) statistično značilno razlikujejo, sem uporabila Wilcoxonov test predznačenih rangov. Ta je pokazal statistično Tabela 3: Spearmanov koeficient korelacije za oceno značilno razliko med rezultati Poskusa 1 in Poskusa 2 pri povezanosti med ceno violin in oceno zvoka violin pri violinah 1, 3, 4, 5 (p < 0,05). Test ni pokazal statistično značilne skupinah glasbenikov in neglasbenikov. Statistično razlike med rezultati Poskusa 1 in Poskusa 2 pri Violini 2 in pomembne korelacije so označene krepko. Violini 6 (p > 0,05). Teh izjem ne morem pojasniti. Spearmanov Brez Informacije Z informacijo Rezultati Wilcoxonovega testa predznačenih rangov koeficient o ceni o ceni nakazujejo, da se ocene večine violin glede na informiranost o za 6 violin ceni v celotnem vzorcu razlikujejo. Glasbeniki rs = 0,771, rs = 0,886, p = 0,072 p = 0,019 Tabela 2: Wilcoxonov test predznačenih rangov za pare Neglasbeniki rs = 0,314 , rs = 0,943, ocen violin, ki so jih dali testiranci pred in po informiranju p = 0,544 p = 0,005 o ceni. Stat. pomembne vrednosti so označene krepko. Brez informacije o Na vprašanje »Kaj je vplivalo na vašo odločitev?« pri ceni/ Poskusu 2 so testiranci lahko odgovorili z več odgovori. Prikazan Wilcoxonov test Z informacijo o ceni delež testirancev je izbral naslednje odgovore: VIOLINA 1 z = 2,119 • »jakost zvoka« - 26,15% p = 0, 034 • »barva zvoka (tembre) – lestvica« - 44,25% VIOLINA 2 z = 1,678 • »barva zvoka (tembre) – melodije« - 49,28% p = 0,092 • »dinamične razlike« - 24,14% VIOLINA 3 z = 3,910 • »cena« 15,8% p = 0,0001 • »drugo« (odprtega tipa) -17,10% VIOLINA 4 z = 2,208 Dejavnik, ki je po mnenju testirancev najbolj vplival na p = 0,027 njihovo razvrstitev je bila barva zvoka (tembre) pri posnetkih VIOLINA 5 z = 2,951 melodij (43 odgovorov). Veliko vlogo naj bi igrala tudi barva p = 0,003 zvoka (tembre) pri lestvicah (38 odgovorov). Pod »drugo« so bili VIOLINA 6 z = 0,528 pogosti odgovori: »alikvoti«, »izenačenost registrov«, p = 0,597 »odzivnost« ter »intonacija«. Zanimivo je, da je cena med 96 Vpliv informacije o ceni na oceno zvoka Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia dejavniki, ki po mnenju testirancev vplivajo na njihovo razvrstitev, po pogostosti na zadnjem mestu z le 14 odgovori.. Tabela 3: Wilcoxonov test za VIOLINO 3/7 celoten vzorec. Stat. pomembne vrednosti so označene krepko. Vprašanje 2 : Ali so subjektivne ocene zvoka violin pri skupini Brez informacije o Brez informacije o glasbenikov v poskusu brez informacije o ceni bolj povezane s ceni/ ceni/ ceno violin v primerjavi z ocenami estetike zvoka v skupini ne- Wilcoxonov Z informacijo o Z lažno glasbenikov? ceni: 3000 informacijo o Izračunan Spearmanov koeficient korelacije med ceno violin test ceni: 30.000 in oceno zvoka violin pri skupini glasbenikov je pri Poskusu 1 VIOLINA z = 3,886 z = 0,247 kazal močno korelacijo (Tabela 3). 3/7 p = 0,0001 p = 0,802 Spearmanov koeficient korelacije med ceno violin in oceno zvoka violin je pri skupini neglasbenikov pri Poskusu 1 kazal Wilcoxonov test predznačenih rangov za pare ocen violin, ki zgolj zmerno korelacijo med spremenljivkama (Tabela 3). so jih dali testiranci pred in po informiranju o ceni sem izračunala Ker pa noben od omenjenih koeficientov ni statistično tudi za vsako skupino posebej. značilen, ne morem poročati o povezanosti med Wilcoxonov test predznačenih rangov ni indiciral statistično spremenljivkama pri obeh skupinah. značilne razlike v ocenah zvoka pri skupini glasbenikov pred in po informiranju o ceni, ko je bila podana resnična informacija o Poskus 1 ceni. Ocena zvoka po informiranju o resnični ceni ni bila zaznavno nižja, z = 0,809; p = 0,381. 80 Zanimivo je, da je Wilcoxonov test 64 predznačenih rangov 57 59 57 60 54 indici 60 52 ral statistično značilno razliko v ocenah zvoka pri skupini 47 42 glasbenikov pred in po informiranju o ceni, ko je bila podana 41 3538 40 lažna informacija o ceni. Ocena zvoka po informiranju o resnični ceni je bila zaznavno višja, z = 2,505; p = 0,012. 20 Wilcoxonov test predznačenih rangov je indiciral statistično značilno razliko v ocenah zvoka pri skupini neglasbenikov pred in po informiranju o ceni, ko je bila podana resnična informacija VIOLINA 1VIOLINA 2VIOLINA 3VIOLINA 4VIOLINA 5 VIOLINA 6 o ceni. Ocena zvoka po informiranju o resnični ceni je bila GLASBENIK NEGLASBENIK zaznavno nižja, z = 4,139; p = 0,000003. Presenetljivo je tudi, da Wilcoxonov test predznačenih Slika 3: Primerjava povprečnih normiranih ocen violin rangov ni indiciral statistično značilne razlike v ocenah zvoka pri skupin glasbeniki in ne-glasbeniki pri Poskusu 1 skupini neglasbenikov pred in po informiranju o ceni, ko je bila podana resnična informacija o ceni. Ocena zvoka po Vprašanje 3: Ali bo napačna informacija o ceni violine (lažna informiranju o resnični ceni ni bila zaznavno nižja, z = 1,267; p informacija, da je cenejša violina draga) vplivala na oceno zvoka = 0,205. pri tako glasbenikih kot tudi ne-glasbenikih? Rezultati nakazujejo, da je lažna informacija o ceni bolj vplivala na glasbenike v primerjavi z neglasbeniki. Da bi ugotovila, če je razlika v ocenah zvoka pri celotnem vzorcu pred in po informiranju o ceni (enkrat z resnično informacijo oceni in enkrat z lažno) statistično značilna sem Tabela 4: Wilcoxonov test za VIOLINO 3/7 za glasbenike in uporabila Wilcoxonov test test predznačenih rangov. neglasbenike. Stat. pomembne vrednosti so označene Wilcoxonov test predznač krepko. enih rangov je nakazoval na statistično značilno Wilcoxonov test Brez informacije Brez informacije razliko v ocenah zvoka pri celotnem vzorcu za o ceni / o ceni / pred in po informiranju o ceni, ko je bila podana resnična informacija o ceni. Ocena zvoka po informiranju o resnični ceni 3/7 violino Z informacijo o Z lažno informacijo o ceni 3.000 EUR ceni 30.000 EUR je bila zaznavno nižja, z = 3,886; p = 0,0001. Presenetljivo pa je, da Wilcoxonov test predznačenih rangov Glasbeniki z = 0,809 z = 2,505 ni indiciral statistično značine razlike v ocenah zvoka pri p = 0,381 p = 0,012 celotnem vzorcu pred in po informiranju o ceni, ko je bila podana Neglasbeniki z = 4,139 z = 1,267 lažna informacija o ceni (zlagano visoka). Ocena zvoka po p = 0,000003 p = 0,205 informiranju o lažni ceni ni bila zaznavno višja, z = 0,247; p = 0,802. 5 MOŽNE IZBOLJŠAVE Dejstvo, da je bil anketni vprašalnik večinoma reševan preko spleta in ne v živo pa ima nekaj pomanjkljivosti. Testiranci so pri poslušanju zvočnih posnetkov violin imeli različno kakovostno opremo (zvočniki). Testiranci z boljšo opremo so tako lahko bolj natančno slišali razlike v lastnostih zvoka med violinami. Nekaj 97 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia A. Šerbec pomanjkljivosti pa je bilo tudi v pripravi samega vprašalnika: razlike, idr. Veliko vlogo igrajo tudi osebne preference, zato je izpolnjevanje vprašalnika je zaradi dolžine posnetkov vzelo vsaj določanje vrednosti violine nekakšna »siva cona«. V poskusu 12 minut. Posledično del testirancev ni rešil vprašalnika v celoti, sem opazovala vpliv faktorja, ki ni neposredno povezan z kar je močno zmanjšalo obseg vzorca. Možna posledica je tudi lastnostmi zvoka: informacija o ceni. Raziskava zato omogoča to, da je udeleženim proti koncu poskusa zmanjkovalo nekoliko provokativen pogled v svet prodaje in kupovanja violin, pozornosti (in potrpljenja) in so zato violine ocenjevali naključno ter je uporabna tako za izdelovalce in prodajalce kot za kupce ali po informaciji o ceni. Razlog za daljše posnetke je bila želja, violin. da pri vsaki violini predstavim njen zven v različnih stilih preko Uporabna je tudi na področju psihologije v marketingu, saj melodij iz različnih obdobji glasbene umetnosti. nakazuje, da informacije iz okolja vplivajo na naša pričakovanja Kot moteča spremenljivka, bi lahko deloval tudi vpliv povezana z vrednostjo in na to kako poročamo o izkušnjah na izvajalca: ker sem bila sama izvajalka, nisem bila enako senzoričnih področjih, natančneje na področju sluha. »navajena« na vse igrane violine. Nekatere violine so bile redno Predvidevam, da bi spoznanja raziskave lahko prenesli še na servisirane, strune na njih so bile nove in bile so »igrane«, druge druga senzorična področja, kot so okus, vid, vonj. pa ne. Vsi našteti faktorji zaznavno vplivajo na kakovost zvoka violine. REFERENCE Da bi poskus izboljšala, bi ga izvedla še enkrat, z nekaj [1] Bissinger, G. (2008). Structural acoustics of good and bad violins. The spremembami: vse violine bi servisirala in »uigrala«. Da izničim Journal of the Acoustical Society of America, 124(3), 1764-1773. vpliv lastne afinitete do določenih vi [2] Brody, H. (1981). The Lie That Heals: The Ethics of Giving Palcebos. Soc. olin, bi tokrat posnela Resp.: Journalism L. Med. , 7, 27. igranje violinista, ki na vse violine igra prvič. Uporabila bi bolj [3] Cho, H. J., Hotopf, M., & Wessely, S. (2005). The placebo response in the treatment of chronic fatigue syndrome: a systematic review and meta- kakovosten snemalnik zvoka. Poskus bi najraje izvedla v živo in analysis. Psychosomatic Medicine, 67(2), 301–313. tako zagotovila, da vsi udeleženci poslušajo posnetke pod [4] Darke, G. (2005, March). Assessment of timbre using verbal attributes. enakimi pogoji (enako kakovostne slušalke/zvočnik). Zanimivo In Conference on Interdisciplinary Musicology. Montreal, Quebec. sn. bi bilo tudi razširiti poskus na področje nevro [5] Karmarkar, U. R., & Plassmann, H. (2019). Consumer neuroscience: Past, -ergonomije in z present, and future. Organizational Research Methods, 22(1), 174. slikanjem možganov z metodo funkcijske magnetne resonance [6] Kompare, A., Stražišar, M., Dogša, I., Vec, T., & Curk, J. (2019). Psihologija: spoznanja in dileme: učbenik za psihologijo v 4. (fMRI) opazovati razlike v delovanju možganov testirancev pri letniku gimnazijskega izobraževanja. DZS. poslušanju violin in odločanju. [7] Plassmann, H., O'Doherty, J., Shiv, B., & Rangel, A. (2008). Marketing actions can modulate neural representations of experienced Ob ponovnem izvajanju poskusa bi v anketni vprašalnik pleasantness. Proceedings of the National Academy of Sciences, 105(3), vključili več vprašanj o lastnostih testirancev. Tako bi vzorec 1050–1054. razdelili na več smiselnih podskupin, ki bi jih primerjali med [8] Schacter, D., Gilbert, D., Wegner, D., & Hood, B. M. (2011). Psychology: European Edition. Macmillan International Higher Education. seboj. (Npr. “Na testirance, mlajše od 25 let, je informacija o ceni [9] Shiv, B., Carmon, Z., & Ariely, D. (2005). Placebo effects of marketing vplivala bolj/manj, kot na testirance starejše od 25 let.”) actions: Consumers may get what they pay for. Journal of marketing Research, 42(4), 383–393 Znano je, da je ocena kakovosti zvoka inštrumenta zelo [10] Smith, P. L., & Ratcliff, R. (2004). Psychology and neurobiology of kompleksna tema: pri njej igrajo vlogo barva, jakost, dinamične simple decisions. Trends in neurosciences, 27(3), 161–168 98 AI Art: Merely a Possibility or Already a Reality? Tadej Todorović Janez Bregant Faculty of Arts Faculty of Arts University of Maribor University of Maribor Maribor, Slovenia Maribor, Slovenia tadej.todorovic@gmail.com janez.bregant@um.com ABSTRACT [1]. Nevertheless, the AI art debate is a debate about whether AI can produce art, so it has to presuppose that there are in fact The paper discusses the compatibility of AI art with various works of art and that there is an intelligible way or definition that definitions of art within the analytic tradition, namely functional, can capture this phenomenon. Not presupposing this would historical, and institutional ones. For every definition, we first render the entire debate meaningless. offer a general overview, discuss whether AI art could be However, to remain as metaphysically non-committing as compatible with it, detect possible problems, and finally offer possible, we decided to analyse the compatibility of AI art with real-life examples that could arguably serve as an example of AI various most popular definitions. We excluded some more basic that fits the given definition. In the final section, we address the definitions, namely single property definitions, such as issue of intentionality for AI art, which seems to be in one way representational, expressive, and formal definitions; these seem or another part of all discussed definitions and which seems to be to have fallen out of fashion, undoubtedly because they are “not the biggest challenge for AI art. difficult to find fault with” [1]. Thus, we first analyse the compatibility of AI art with KEYWORDS functional definitions, followed by historical and institutional Artificial intelligence, art, functionalism, historicism, definitions of art, and offering existing AI art examples along the institutionalism, intentionalism. way. Afterwards, we also offer a response to probably the biggest obstacle to AI art, i.e. intentionality. 1 Introduction Today, there are hardly any doubts that artificial intelligence (AI) 2 AI and functional definitions of art can perform many tasks much better than us, all the way from Functional definitions of art define art in terms of some function playing chess, backgammon, or checkers to intelligent or intended function. Usually, the function is connected with scheduling and pricing systems in airline reservations, proving some aesthetic properties, such as the aesthetic experience we theorems, or solving equations. And as the AIs are getting better undergo when admiring a work of art, e.g., catharsis or simply and better at these domain-specific tasks, we, with more and some aesthetic judgments or experiences. In this sense, more uncertainty, diligently move the goalposts, stating that AI functional definitions are more traditional, and have issues will surely not be able to beat us at the next mark. No wonder accommodating, e.g., modern art, like Duchamp’s ready-mades then that one of the last bastions of human uniqueness, i.e. (although some have argued that ready-mades have aesthetic creativity, best shown through art and its creations, is fiercely properties [2]). Despite their flaws, such definitions seem to be defended against the possibility of AI art. What should perfect for accommodating AI art. Beardsley’s definition can philosophy say about that? Are there any definitional obstacles serve as a good example of a functional aesthetic definition. It to admitting AI art? Are there already existing examples of AI states that an artwork is “either an arrangement of conditions art that might fit various definitions of art? intended to be capable of affording an experience with marked Definitions of art remain a controversial subject in analytic aesthetic character or (incidentally) an arrangement belonging to philosophy. There has been much discussion about the value of a class or type of arrangements that is typically intended to have the definition of art and many sceptical concerns about its this capacity” [3]. existence in the first place, starting all the way back in the 1950s But which conditions evoke such feelings and experiences? To our knowledge, a satisfactorily account of them has not been given. Nevertheless, in the context of AI art, there seem to be no 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 formal obstacles against AI creating (art) works that meet such distributed for profit or commercial advantage and that copies bear this notice conditions. In fact, this is not only conceivable, but has arguably and the ful citation on the first page. Copyrights for third-party components of already been done. A prime example is the “Creative Adversarial this work must be honored. For al other uses, contact the owner/author(s). Network” (CAN) [4], the design of which was motivated by Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Berlyne’s theory [5] inspired by his most significant arousal- © 2020 Copyright held by the owner/author(s). 99 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia T. Todorović and J. Bregant raising properties for aesthetics: “novelty, surprisingness, AI art in the final section. The question that we have to answer complexity, ambiguity, and puzzlingness”. is thus whether AI artworks could stand in an appropriate The CAN project proved very successful. The authors ran a relationship to established artworks and, more importantly, series of experiments (Turing style tests with human subjects) whether they already do. Similar to the problem in functional with the created artworks to test how the AI measures up to definitions, this should not present an insurmountable problem human artists. The experiment III is the most relevant for for AI art. It is not only conceivable that AIs could use a family- functional definitions. In it, they asked human subjects to rate the resemblance process to create artworks, AIs already utilize a artworks by CAN and artworks by human artists (set of paintings process that looks extremely similar. Alexander Mordvintsev, from a display at Art Basel 2016). The paintings were rated on a the software engineer behind DeepDream, Google’s neural scale of 1-5 (5 being the best) on intentionality, visual structure, network, writes as follows, “We train an artificial neural network communication, and inspiration. Not only did the human subjects by showing it millions of training examples and gradually fail to notice that CAN paintings were not made by human artists, adjusting the network parameters until it gives the classifications they outperformed human artists in all metrics. Of course, the we want” [10]. size of the experiment was rather small (21 participants), so the The already mentioned CAN is an even better example: it results are not statistically powerful; however, as the authors uses a slightly different approach because its purpose is to create state, “the fact that subjects found the images generated by the artworks that would be indistinguishable from human artworks. machine intentional, visually structured, communicative, and The CAN is comprised of two adversary networks, a inspiring, with similar levels to actual human art, indicates that discriminator and a generator. A discriminator is “trained” on subjects see these images as art!” [4] human art samples, so it has a reference of art images, Functional definitions do not require anything but the accompanied with styles and labels. The generator then creates realization of certain functional, i.e. aesthetic, properties, which new works of art, trying to accomplish two things: the first is to makes them tailor-made for AI art. We believe it is safe to claim generate works that the discriminator would recognize as works that if one subscribes to such a definition, they would be hard- of art, i.e., it tries to create art that fits into the already-existing pressed to find an argument against including the already- styles. However, if it did only that, it would just emulate existing AI artworks. artworks, similar to an art forger. So, the second task of the CAN generator is to confuse the discriminator regarding the style of the work created. So, “on one hand it tries to fool the 3 AI and historical definitions of art discriminator to think it is ‘art’, and on the other hand it tries to Historical definitions are another popular way of understanding confuse the discriminator about the style of the work generated” art. The core message of historical definitions is that an artwork [4]. In other words, the neural network has to navigate between “is standing in some specified art-historical relation to some the Scylla, which is getting recognized as art, and Charybdis, specified earlier artworks” [1], which is similar to family- which is generating works that are “style-ambiguous”, trying to resemblance theories in certain aspects [6]. Moreover, and this is find the sweet spot where the painting still resembles other works what distinguishes historical definitions from functional or of art but it is still original. And considering the experimental institutional definitions: proponents of historical definitions do results introduced in the previous section, CAN is apparently not commit to a trans-historical concept of art, i.e. the concept doing an extremely good job at it. that would capture commonalities across various classes of The idea of AI art being compatible with the historical artworks in distinct historical periods, e.g. some stable core of definitions is thus not only conceivable or possible; just like with aesthetic properties that are present in all art movements functional definitions of art, we could reasonably state that there throughout the history. Thus, historical definitions present “an are already examples of AI art that fit the criteria of historical alternative to the definitional approach” [7]. One of the most definitions. recognised historical definition of art is offered by Levinson, who defines a work of art as “something that has been intended by someone for regard or treatment in some overall way that 4 AI and institutional definitions of art some earlier or pre-existing artwork or artworks are or were The institutional definition of art is probably one of the most correctly regarded or treated” [8]. influential and simultaneously one of the most criticized There seem to be two common elements in historical definitions of art of the 20th century. Many have argued that “the definitions (even though proponents of historical definitions definition’s obvious circularity is vicious” [1]; nevertheless, it understand their reasoning as an alternative to the definitional has remained fairly popular. The groundwork for institutionalism approach, we will refer to historical “definitions” as definitions was laid by Danto [11]; however, Dickie’s institutional definition for the sake of simplicity and because our argument does not is probably the most influential. The spirit of institutionalism can hinge on this): let us call the first one the family-resemblance be summed up by the following quote: “a work of art is an artifact element, and the second one the intentional element, despite the which has had conferred upon it the status of candidate for fact that some historical definitions do not require the intentional appreciation by the artworld” [12]. In other words, something is element [9]. a work of art if people within the artworld grant it such a status. In this section, we will focus on the family-resemblance The definition is more elaborate, and has been expanded by element; however, we will address intentionality as a problem for Dickie in his more recent work, so it now consists of five 100 AI Art: Merely a Possibility or Already a Reality? Information Society 2021, 7–8 October 2021, Ljubljana, Slovenia interlocking conditions: “(1) An artist is a person who almost as difficult as arguing that the path that was created participates with understanding in the making of a work of art. unintentionally somehow differs as an artifact from the (2) A work of art is an artifact of a kind created to be presented intentionally created path. In short, if humans recognize to an artworld public. (3) A public is a set of persons the members something as an artifact and behave as if it is an artifact, then of which are prepared in some degree to understand an object why should we not count it as one? The idea that something is an which is presented to them. (4) The artworld is the totality of all artifact if recognized as an artifact is also compatible with artworld systems. (5) An artworld system is a framework for the Dickie’s institutionalism since, according to him, “anything presentation of a work of art by an artist to an artworld public” brought into an art space as a candidate for appreciation becomes [12]. thereby ‘artefactualized’” [17]. For brevity’s sake, we will only focus on the premises that The only question that remains to answer is whether there are seem problematic for AI art, i.e., premises (1) and (2). Premise examples of AI art that pass fit the institutional definition. And, (1) seems problematic, as AI is obviously not a person. However, in fact, there are. Jeff Clune decided to test the level of artworks the context has to be considered here; the authors of the 20th produced by Evolving Artificial Intelligence Lab’s deep neural century assumed that “the artist is always human, without networks (DNN), submitting the artworks to the University of exploring much whether non-humans can create art” [13]. This Wyoming’s 40th Annual Juried Student Exhibition, “which seems fairly anthropocentric in this day and age, and we are accepted 35.5% of its submissions” [18]. Its artworks were not confident that most theorists would agree that a being with the only accepted, but also among the “21.3% of submissions to same or greater understanding in the making of a work of art receive an award” [18], and, what is perhaps most important for (e.g., aliens) would still be considered artists. Therefore, the an institutional definition of art, were displayed at the problem does not seem to be not being human, but rather not university’s art museum. So not only can we say that there does possessing the capacity to understand and partake in the making not seem to be a good reason against AI art in the framework of of a work of art. This is closely (if not completely) related to the institutional definition of art, we could arguably claim that AI intentionality, which we address in the next section, so we will art is already here. put it aside for now. The second premise might also pose some problems. There seem to be two separate questions here: what counts as an artifact 5 AI and intentionality and is an AI made object an artifact. So what is an artifact? Some sort of intentionality component was present in almost all Hilpien’s definition should serve our goals: “artifacts are analysed definitions. The idea that something can only count as physical objects which have been manufactured for a certain art if it was produced intentionally could thus be compatible with purpose or intentionally modified for a certain purpose” [14]. all analysed definitions. Intentionality is aboutness, it is “power Notice that such a definition “does not rule out the possibility that of minds and mental states to be about, to represent, or to stand at least some things made by non-human animals are artifacts” for, things, properties and states of affairs” [19]. It is hard to [15]. E.g. “[b]eavers /…/ might be thought to intentionally imagine that an organism or a system would possess such powers construct dams in order to create ponds” [15]. On the other hand, without consciousness. Even consciousness is not sufficient for some more rigid behaviours of other animals, like webs woven intentionality: we agree that animals (most animals) are by spiders, might not count as artifacts. Paths can serve as an conscious, but they (or babies) do not possess intentionality, as even more ambiguous example. They are often created intentionality belongs to higher order cognition. So, we cannot unintentionally, when people take the same short-cut across the possibly ascribe intentionality to AI, as we have no reason to university lawn over and over again: but, as Preston argues, “/…/ think it is even conscious. what is the point of saying that such a path is not an artifact, Nevertheless, we believe intentionality is problematic as a whereas an identical one that was created intentionally by exactly condition for artworks. Here’s why. Definitions of art usually the same process is? Moreover, what would it take to make the include intentionality to exclude natural phenomena being art. erstwhile non-artifactual path into an artifact? Would it be However, intentionality can be understood in two ways. We can enough to notice and approve it? Or would I have to intentionally understand it in the narrower sense of producing and expressing maintain it, by sweeping it clean of leaves, for instance?” [15] a particular idea that the artist has, or we can understand it in a The line has to be drawn somewhere, and it is hard to imagine much broader, abstract sense of simply creating a work of art. If that the line will not be, in some sense, arbitrary. one stick to the former, this already excludes many art So, are AI made objects artifacts? If we dismiss the artifacts movements. Surrealism greatly emphasized automatism, which debate because it seems arbitrary, then it does not matter. If one is “perhaps the most famous of their [surrealists’s] techniques for insists on the artifact/non-artifact distinction, a proponent of such evading conscious control of the artistic process” [20]. Breton distinction has to first offer a good reason in favour of it. Even if defines Surrealism as “Psychic automatism in its pure state, by such a reason could be provided, they have to answer the which one proposes to express /…/ the actual functioning of following question: how to classify AI object that are thought /…/ in the absence of any control exercised by reason, indistinguishable from human artifacts? If someone not familiar exempt from any aesthetic or moral concern” [21]. So not only with The Painting Fool [16] discovered a painting made by it, did the surrealists want to create artworks in the absence of they would, without a doubt, classify it as a (human) artifact. So reason and intention, they saw “reason as a guard barring entry why should we revoke that status once we discover that there was to this storehouse” [20]. no intention involved in the production of the image? It would be 101 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia T. Todorović and J. Bregant Defenders of intentionality can quickly offer the following REFERENCES retort: even if one admits that surrealists’ process for creating art [1] Adajian, Thomas. 2018. “The Definition of Art”. In Edward N. Zalta (Ed.), was not intentional in the narrow sense, they nevertheless had The Stanford Encyclopedia of Philosophy, Fall 2018. https://plato.stanford.edu/archives/fall2018/entries/art-definition/. intention to produce art in the broader sense; they had the more [2] Lind, Richard. 1992. “The Aesthetic Essence of Art”. Journal of abstract “impulse” or “urge” to create a work of art, which AI Aesthetics and Art Criticism, 50, pp. 117–29. DOI: lacks. However, not all artists throughout the history demanded https://doi.org/10.1017/CBO9780511625251.023. [3] Beardsley, Monroe. 1982. The Aesthetic Point of View. Ithaca, New York: or valued such broad intentionalism; in fact, some have been Cornell University Press. explicitly against it. Advocates of Primitivism, a widespread [4] Elgammal, Ahmed, Liu, Bingchen, Elhoseiny, Mohamed, Mazzone, Marian. 2017. “CAN: Creative Adversarial Networks, Generating ‘Art’ by trend in the modern art, celebrated “primitive works”, which Learning About Styles and Deviating from Style Norms”. International “came from an unconscious source of creativity rather than from Conference on Computational Creativity (ICCC). [5] Berlyne, Daniel Ellis. 1971. Aesthetics and psychobiology. Appleton- artistic traditions, an idea which suited many modern artists /…/ Century-Crofts. DOI: 10.1093/oxfordhb/9780195304787.001.0001. modern artists also praised the ‘primitivism’ of art produced by [6] Wittgenstein, Ludwig. 1953. Philosophical Investigation s. G.E.M. children, the insane and untrained, ‘naïve’ adults.” [20]. Even Anscombe and R. Rhees (Eds.), G.E.M. Anscombe (trans.), Oxford: Blackwell. though one could argue that “primitive” art had a source of [7] Carroll, Noel. 1993. “Historical Narratives and the Philosophy of Art”. inspiration, a sort of intentionality, it would be hard to argue that The Journal of Aesthetics and Art Criticism, 51(3), pp. 313–26. [8] Levinson. 2007. “Artworks as Artifacts.”. In E. Margolis and S. Laurence what they had in mind was this broader concept of creating art. (Eds.), Creations of the Mind: Theories of Artifacts and Their Such a broader claim would be even harder to defend in case of Representation, Oxford: Oxford University Press, pp. 74–82. children or the “insane”. [9] Stock, Kathleen and Thomson-Jones, Katherine. 2008. New Waves in Aesthetics. London: Palgrave Macmillan. Two conclusions can be drawn from all this: if one demands [10] Mordvintsev, Alexander. 2015. “Inceptionism: Going Deeper into Neural intention in the narrow sense then this would exclude movements Networks”. Google AI Blog. Available at: https://ai.googleblog.com/2015/06/inceptionism-going-deeper-into- like Surrealism, and therefore should not be a necessary neural.html. condition for artworks; and if one demands intentionality in the [11] Danto, Arthur. 1981. The Transfiguration of the Commonplace. broader sense then such a concept will differ massively over Cambridge: Harvard University Press. [12] Dickie, George. 1974. Art and the Aesthetic: An Institutional Analysis. cultures and individuals, especially if we find value in Ithaca, NY: Cornell University Press. “primitive” art. If modern artists cherished and valued art [13] Hertzmann, Aaron. 2018. “Can Computers Create Art?”. Arts 7 (2): 18. DOI: https://doi.org/10.3390/arts7020018. produced by children and the “insane”, which lack intentionality [14] Hilpinen, Risto. 1992. “Artifacts and Works of Art”. Theoria, 58(1), pp. in the broader sense altogether, then this should also not be a 58–82. DOI: 10.1111/j.1755-2567.1992.tb01155.x. [15] Preston, Beth. 2020. “Artifact”. In Edward N. Zalta (Ed.), The Stanford necessary condition for artworks. Encyclopedia of Philosophy, Fall 2020. URL = Throughout this paper, we have shown examples of AI . artworks that were not only appreciated as art, but which also [16] Colton Simon. 2012. “The Painting Fool: Stories from Building an Automated Painter”. In John McCormack and Mark d’Inverno (Eds.) won prizes, and arguably outperformed human artists. Spectators Computers and Creativity. Berlin: Springer. DOI: recognized such works as intentional, inspiring, and https://doi.org/10.1007/978-3-642-31727-9_1 [17] Slater, Barry Hartley. “Aesthetics”. In James Fieser and Bradley Dowden communicative. Similar to “primitive” art, AI was able to (Eds.), Internet Encyclopedia of Philosophy. Available at: achieve this without intentionality in the narrow or broader sense. https://iep.utm.edu/aestheti/. Understanding intentionality in the narrow sense excludes too [18] Shein, Esther. 2017. “Computing the Arts”. Communications of the ACM, 60(4), pp. 17–19. DOI: 10.1145/3048381. much from the world of art, and understanding it in the broader [19] Jacob, Pierre. 2019. “Intentionality”. In Edward N. Zalta (Ed.), The sense does not allow an objective definition of art: the concept of Stanford Encyclopedia of Philosophy, Winter 2019. URL = . this artistic impulse, as seen with Primitivism, just varies too [20] Little, Stephen. 2004. Isms: Understanding art. New York: Universe. much across cultures and individuals to enable an unbiased [21] Breton, André. 1969. Manifestoes of Surrealism. Ann Arbor: The University of Michigan Press description of art. As such, it would seem more appropriate to judge works of art on their external properties, not the intentions of the artists. We can confidently say that AI (art) works can already pass some kind of the so-called Turing test in the world of art, something that perhaps many post-modern or contemporary human works of art would not. And whereas some people see AI art as blasphemous, we see it as potentially offering us new insight into our understanding of art. Nevertheless, it seems that whatever objection AI defeats, the goal-post always moves further away. Simon Colton wrote (about his creation, the Painting Fool) that “it is our hope that one-day people will have to admit that the Painting Fool is creative because they can no longer think of a good reason why it is not” [16]. Similarly, hopefully one-day people will have to admit that AI can produce art, because they can no longer think of a good reason why it could not. 102 Compliance with COVID-19 preventive behaviors and proneness to cognitive biases Manca Toporišič Gašperšič† Nataša Grof Undergraduate Psychology Poljane grammar school Program Strossmayerjeva 1 Faculty of Arts, University of Ljubljana, Slovenia Ljubljana (Slovenia) natasa.grof@gimnazija- manca.verano@gmail.com poljane.com ABSTRACT Research so far has extensively focused on linking certain personal traits to compliance with behavioral recommendations. Due to common non-compliance with behavioral hygiene Extraversion has therefore been negatively correlated to recommendations to contain the SARS-CoV-2 virus, the younger compliance with COVID-19 social distancing measures, whereas generation has often been regarded as a catalyst of the current conscientiousness is believed to be positively correlated to pandemic. Therefore, the aim of the present study is to determine compliance [2]. At the same time, low levels of empathy and the connection between proneness to specific cognitive biases antisocial traits are linked to noncompliance with containment and compliance with COVID-19 preventive recommendations in measures [3, 4]. On the other hand, current literature has offered high school students. Our results indicate that decision myopia is inadequate understanding of the cognitive factors of behavioral positively correlated to non-compliance with COVID-19 non-compliance. In this study, we try to theoretically and containment measures. Surprisingly, no link has been found empirically bridge this research gap. We therefore undertake to between risk aversion and compliance to self-protective examine certain cognitive biases we believe might be related to recommendations, whilst individuals who are more prone to engaging in self-protective behavior. belief bias report greater compliance with COVID-19 preventive behaviors. The results clearly indicate that proneness to cognitive Cognitive biases and their possible correlation with biases is somewhat important but not a decisive factor of preventive behavior adherence to preventive measures. Framing is defined in the framework of prospect theory, which predicts that people are inconsistent when evaluating losses and KEYWORDS gains. In particular, when faced with losses, people typically tend to engage in more risk-seeking behavior than when faced with COVID-19, preventive behavioral measures, compliance, cognitive biases, high school students gains [5, 6]. In consequence, more negative, loss-emphasizing information may result in greater risk-taking decision making. Adherence to even the most basic hygienic measures which aim 1 INTRODUCTION to limit the spread of the coronavirus SARS-CoV-2, is to a certain extent a decision based on one’s risk attitude. In the 1.1 Theoretical background current pandemic, the most recurrent example of framing losses is enumerating the number of lives lost due to COVID-19. Known psychological correlates to compliance with Emphasizing saved lives, is on the other hand, an example of behavioral interventions framing gains. With the rise of novel coronavirus SARS-CoV-2 variants and However, in addition to this typical framing context, some related vaccine hesitancy trends, basic behavioral hygienic authors have already pointed out other framing types. There have measures (such as wearing masks, frequent hand washing, as been indications that different countries framed the outbreak well as physical distancing) have remained the fundamental tools differently at the beginning of the coronavirus outbreak in 2020. to contain the spread of the virus. However, evidently certain Whilst Western countries focused more on framing COVID-19 individuals do not comply to these behavioral recommendations as a respiratory disease, similar to the seasonal flu, Asian [1], thus probably contributing to the spread of the coronavirus. countries compared the novel coronavirus to the SARS virus – a Identifying factors that are linked to compliance with behavioral difference in framing that supposedly contributed to the great recommendations and restrictions is thus extremely important. success of Asian countries in flattening the initial curves of new infections [7]. Risk aversion is another important notion, defined in the Permission to make digital or hard copies of part or all of this work for personal or framework of prospect theory. It is a cognitive bias, best classroom use is granted without fee provided that copies are not made or described as a constant inclination to select the most certain and distributed for profit or commercial advantage and that copies bear this notice and the ful citation on the first page. Copyrights for third-party components of reliable option, even when there are more profitable (but at the this work must be honored. For al other uses, contact the owner/author(s). same time riskier) options available [8]. Current theory stipulates that people more prone to this bias, tend to be more compliant Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). with COVID-19 measures [9]. 103 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Toporišič Gašperšič & Grof On the other hand, not engaging in self-protective behavior H2: Participants, prone to belief bias, report lower may not only be connected to one’s risk attitudes, but also to their compliance with COVID-19 containment behavioral lack of reasoning and unwillingness to incorporate new evidence recommendations. into their thought processes. In syllogistic reasoning, belief bias H3: There is a positive correlation between compliance with is described as the tendency “to rely on prior beliefs rather than behavioral guidelines and loss aversion. to fully obey logical principles [10].” In other words, it means H4: Decision myopia is negatively correlated with being constrained by your own opinions and predispositions. In compliance with behavioral recommendations to contain the response, acquiring new, accurate, and unbiased information can spread of COVID-19. be extremely difficult for individuals who are especially prone to this cognitive bias [11]. And since the COVID-19 pandemic has often been referred to as a pandemic of misinformation [12], 2 METHODOLOGY possessing factual evidence that may be connected with our health-related decisions is surely of utmost importance. 2.1 Participants and procedure In contrast, decision myopia or the present bias “is the To determine the cognitive factors of non-compliance with nonlinear and inconstant tendency of many individuals to prefer behavioral guidelines in the younger generation, the generation a smaller sooner pay-off over a larger future pay-off [13].” often proclaimed to be reluctant towards the epidemiological Favoring smaller and sooner rewards over long-term ones has restrictions [1], our study exclusively focused on this age group. been a recurrent phenomenon of the pandemic. During the The study thus included 83 participants – all students at Poljane pandemic, we have witnessed how many people have Grammar School, aged from 15 to 19 years old. However, as disproportionately ignored social distancing guidelines in order three participants failed to complete the study, their results were to socially interact with others. However, since social gatherings excluded from the final analysis. The majority (75%) of are known to lead to a spike in coronavirus cases, this a very participants identified themselves as female, 24% defined short-sighted move on various levels since it is believed to themselves as male, whilst the remaining 1% did not wish to additionally contribute to lives lost. In addition, long-lasting disclose their gender. Although this gender structure is not draconian lockdowns to contain the spread of the virus limiting typical of the general population, it is typical of Poljane Grammar in-person contacts are often imposed to restrict such gatherings. School. The empirical study was conducted on 18th and 19th February 1.2 Overall aim and hypotheses 2021 via the Slovenian survey tool 1ka. Since the study took The key objective of the study is to shed light on the relationship place during the national COVID-19 lockdown and in-person between framing, belief bias, risk aversion, and decision myopia learning restrictions, the subjects completed the study in the to non-compliance with behavioral recommendations1 to contain course of their class meetings that were held online, and were a the spread of the coronavirus. According to the presented theory, part of their distance-learning schedule. All participants were we introduce several hypotheses. On account of framing effects informed about and consented to the general purpose of the and their role in risky decision making, we hypothesize: study, and were acquainted with the fact that their participation H1a: Participants who are exposed to the framing of losses, in the research was entirely voluntary and anonymous. will make riskier choices than participants who are exposed to While completing the empirical questionnaire, they were the framing of gains in the neutral condition. supervised by the researcher via Zoom, the online video H1b: Participants who are exposed to the framing of losses conferencing platform used by their high school. Whilst the when seasonal flu is mentioned, will make riskier choices than research was being carried out, all participants were required to participants who are exposed to the framing of gains when virus turn on their camera. Moreover, all the participants were notified SARS is mentioned. that any communication among them was prohibited since it H1c: Participants who are exposed to the framing of gains in could adversely affect the results. To prevent interpersonal the neutral condition, are less likely to opt for the riskier option communication among the participants, we carefully set the than participants who are exposed to the framing of gains when Zoom chat settings so that they prevented participants from the SARS virus is mentioned. communicating with each other. At the same time, a direct online H1d: Participants who are exposed to the framing of losses chat communication channel between each participant and the in the neutral condition, are less likely to opt for the riskier option researcher was established. Thus, students participating in the than participants who are exposed to the framing of losses when study were able to point out certain technical issues or other the SARS virus is mentioned. concerns directly to the researcher without disrupting others. Moreover, our other hypotheses are as follows: Furthermore, students were not externally motivated in any way 1 In this paper, we distinguish between basic behavioral recommendations to behavioral recommendations can be epidemiologically as successful as restrictive contain the spread of the coronavirus (for instance, hand washing, mask wearing, containment measures, provided that individuals adhere to these recommendations, and maintaining physical distance from others) and restrictive measures (such as we add. On the other hand, our decision to focus on behavioral interventions rather lockdown, curfews, and regional restrictions). In our study, we overall address non- than on restrictive measures was also largely based on the fact that an international compliance to basic behavioral recommendations, but not non-compliance to extension of the current study will probably be carried out. As epidemiological restrictive measures. Partially our decision is based on the fact that restrictive (restrictive) measures vary from country to country, a goal of the present study was measures are of limited use when individuals are non-compliant with the basic also to lay out the measurements for our later studies. behavioral recommendations. A study [27] has, for instance, indicated that basic 104 COVID-19 preventive behaviors and cognitive biases Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia to participate in the study: they were not given a fee nor were Belief Bias their results classified or publicly disclosed in any way. We To measure a participant’s proneness to belief bias and its therefore believe that the current results are the best possible connection to compliance with behavioral recommendations, we representation of the participants’ proneness to cognitive biases. used adapted tasks of Markovits and Nantel [15]. Although the original toolkit to measure this cognitive bias was comprised of 2.2 Tasks and measures eight tasks, we used only seven of them as we believed that Compliance with COVID-19 behavioral recommendations participants would generally not be acquainted with the individual mentioned in one task3, and hence unable to respond To measure reported compliance with the COVID-19 behavioral to the question. All seven questions used were in fact syllogisms containment recommendations, we used an adapted form of the – combinations of three statements. The participants were Compliance with COVID-19 prevention guidelines scale [14]. instructed to assume that the first two statements (premises) are The adapted 4-point Likert scale includes 13 items, which true; their task was to estimate whether or not the third statement predominantly focus on determining the extent of compliance is the right conclusion derived from the first two statements. with basic hygiene guidelines (such as mask wearing or hand In four tasks, the conclusion that is correctly derived from the washing) rather than on compliance with more restrictive two premises is contradictory to general knowledge. As such, measures (for instance curfews or lockdown). proneness to belief bias is in these tasks determined as the Framing willingness to estimate conclusions as inaccurate due to their In the framing section of the questionnaire, participants were dissimilarity to generalized facts. This can be illustrated by the randomly assigned into two groups. We measured the impact of following task used in the study: framing with two similar tasks. The first task was the original Premise 1: All things that are smoked are good for your task used by Kahneman and Tversky [6]. In this paper, we often health. refer to this task of framing as framing in the neutral condition. Premise 2: Cigarettes are smoked. The instructions of the task were identical in both experimental Conclusion: Cigarettes are good for the health. groups and are, as follows: If we were to ignore the premises and read only the Imagine that Slovenia 2 is preparing for the outbreak of an conclusion, we would correctly proclaim it to be false. However, unusual Asian disease, which is expected to kill 600 people. Two the conclusion is in accordance with the premises, hence it is alternative programs to combat the disease have been proposed. correct in the context of the given task. A person, susceptible to Participants of both tasks were then asked to peruse scientific belief bias will, consequently, likely struggle to reflect on the estimates of how many people would die / live if a certain intuitively-suggested responses and in the particular case program is accepted and make a decision on which program incorrectly answer that the conclusion is false. should be imposed. In both experimental groups, programs On the other hand, the other three tasks we used had actually predict the same number of lives lost / lives saved. seemingly reasonable conclusions. However, these conclusions However, as indicated below, gains (lives saved) were framed in could not have been made on the basis of the given premises and the 1st experimental group, whilst losses (lives lost) were framed were, as a result, incorrect. Here, proneness to belief bias is in the 2nd experimental group. That is: regarded as the decision that the conclusion is right. This can be Group 1: If Program A is adopted, 200 people will be saved. exemplified by the following task: If Program B is adopted, there is a one-third probability that Premise 1: All flowers have petals. 600 people will be saved and a two-thirds probability that no Premise 2: Roses have petals. people will be saved. Conclusion: Roses are flowers. Group 2: If Program A is adopted, 400 people will die. Risk aversion If Program B is adopted, there is a one-third probability that We used a truncated Holt-Laury Task [16] 4 to measure risk nobody will die and a two-thirds probability that 600 people will aversion. The task is formulated as a set of paired lottery choices die. and was initially designed to measure financial risk aversion. In addition to the task in the neutral condition, another task However, it is applicable to non-financial fields as well, and as was added to measure how specifying the disease impacts risk- such useful for the purpose of our study, as people are consistent seeking behavior. The text of the second task was slightly in their preferences regarding risk-taking in all areas of life [17]. modified in comparison with the first task. Participants in the The original task contains ten rounds of paired choices, whilst experimental group 1 (the group with framing of gains) were ours included only nine due to the complexity and length of the given the information that the disease of the outbreak is similar study. In every round, participants are required to opt for either to diseases, caused by the SARS virus. In contrast, participants option A or option B; both options are profitable. Nevertheless, in the group with framing of losses were provided with the their profitability and risk level differ. The potential profits of comparison of the disease with the seasonal flu. both options remain constant throughout all nine rounds (thus, 2 The original text of the task predicted that the U.S., and not Slovenia was 4 In comparison with the original task, the currency was also changed to familiarize preparing for an outbreak. For the purpose of this study, this detail was changed. the participants with the task. 3 This individual was John D. Rockefel er. 105 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Toporišič Gašperšič & Grof option A can potentially bring either €2.00 or €1.60, whereas the If you choose option A, you will lose €1000 this year. If you predicted payoff of option B is €3.85 or €0.10; [16]). Generally, choose option B, you will lose €2000 next year. option A is regarded as the “safe” option, meanwhile option B is The 11th round was in fact not a lottery choice task – it was a regarded as the “riskier” option as the potential profits in option question, also used in the original intertemporal choice B vary more than potential profits in option A [8]. The course of measurement [18], which asked the participants to indicate the task can be demonstrated by its first three rounds: whether they would be prepared to pay more for overnight shipping of a chosen product. Table 1: First three rounds of Holt-Laury Task Round Option A Option B 3 RESULTS 1 10% 90% 10% 90% All acquired data were statistically analyzed in Microsoft Excel chance of chance of chance of chance of 2016. receiving receiving receiving receiving €2.00 €1.60 €3.85 €0.10 3.1 Framing 2 20% 80% 20% 80% chance of chance of chance of chance of To measure the impact of framing gains/losses, we used a chi- receiving receiving receiving receiving squared test. Our data indicate that there is no statistical €2.00 €1.60 €3.85 €0.10 difference in risk taking behavior when losses are framed as 3 30% 70% 30% 70% opposed to gains in the neutral condition, X2 (1, N = 80) = 0.03, chance of chance of chance of chance of p = 0.87. Moreover, no significant difference in risk attitude has receiving receiving receiving receiving been found when comparing the framing of gains when SARS is €2.00 €1.60 €3.85 €0.10 mentioned and the framing of losses when seasonal flu is The average behavior of the majority of participants in initial mentioned, X2 (1, N = 80) = 0.00, p = 0.99. rounds is to opt for the safer option, option A. This trend is, Nevertheless, the results demonstrate that participants who however, expected to alter when the likelihood of receiving were exposed to framing of gains in the neutral condition were larger payments as a result of choosing option B substantially more risk averse than participants who were exposed to framing increases [16]. One’s willingness to engage in risk-taking of gains when the SARS virus was mentioned, X2 (1, N = 80) = behavior is measured by the number of “risky” decisions – the 26.53, p = 0.00. On the other hand, the difference in risk attitudes selections of option B. is statistically significant when comparing framing of losses in Decision myopia the neutral condition to framing of losses when the seasonal flu An adapted 5 measurement of intertemporal choice by was mentioned; when the flu is mentioned, participants tend to Frederick [18] was used in this study in order to link decision acquire select the risk-taking option more commonly, X2 (1, N myopia to non-compliance with behavioral recommendations to =80) = 4.82, p = 0.03. contain the spread of SARS-CoV-2. In total the measurement included eleven items. As with the risk aversion task, the 3.2 Cognitive biases and compliance intertemporal choice measurement was structured as a Correlations between belief bias, loss aversion, decision myopia, combination of paired lottery choices. and compliance with COVID-19 preventive recommendations In the first eight rounds, participants had to choose between are measured with the Pearson correlation coefficient. Data two profitable options, option A and option B. Option B was analysis showed that proneness to belief bias and compliance always more lucrative than option A. However, the payoff of with behavioral recommendations are positively correlated (r = option A was always immediate or at least chronologically 0.35, p < 0,01). However, there is no statistically significant sooner in comparison with the payoff of option B. For instance: correlation between proneness to risk aversion and compliance (r If you choose option A, you will receive €3000 this month. If = 0.09, p = 0.42). Furthermore, a negative correlation has been you choose option B, you will receive €3400 next month. found between decision myopia and compliance to COVID-19 In such tasks, short-sighted individuals are therefore expected preventive behavioral recommendations (r =-0.53, p < 0.01). to select instant gratification by persistently choosing option A [18]. In the 9th and 10th round, participants were asked to choose between the two given options once again. This time both options 4 DISCUSSION were loss-making: option A predicted a more immediate, but Our study has offered a more profound understanding of financially lower loss, whilst option B involved a greater, but behavior during the ongoing pandemic. To provide an accurate deferred loss. Decision myopic individuals are believed to prefer insight, we exclusively focused on the correlation between deferred losses even when it is not financially profitable for them proneness to certain cognitive factors and compliance with [18], as indicated in the following example: preventive measures. However, we acknowledge the fact that our 5 In addition to the fact that the task was shortened (original task to measure intertemporal choice included 17 items), we also changed the currency – as with the risk aversion task. 106 COVID-19 preventive behaviors and cognitive biases Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia results might have been affected by other equally important remain unaccounted for: it is not clear whether they can be factors correlated to compliance, such as demographic directly linked to the use of heuristics, mental shortcuts, as characteristics, socioeconomic status, personality, individual simply complying rather than questioning the measures often differences in the perception of and emotional responses to the requires less cognitive effort, or there is an indirect correlation pandemic, resilience, political ideology, conspiracy mentality between cognitive reflection and proneness to biases, etc. Furthermore, our study has also shed light on some results compliance, and other noteworthy psychological factors, such as that differ from those in the current literature. social norms [24]. Our results, for instance, did not confirm that in the neutral Similarly unexpected was the finding that students prone to condition, participants exposed to framing of losses were, in risk aversion bias were not more inclined to comply with consequence, more in favor of engaging in risk-taking behavior behavioral recommendations. The current literature on than their peers exposed to framing of gains. This is contrary to preventive behaviors suggests that the perceived threat that the pre-existing theory [5, 6]. Similarly, no significant results COVID-19 presents to an individual is a significant factor of were found when comparing framing of losses and framing of compliance to preventive measures [25]. In other words, when gains with regard to seasonal flu and the SARS virus. We were feeling threatened, people typically engage in more risk-averse thus not able to confirm our first two hypotheses. In our opinion, behavior than when they feel there is no danger. According to the there are several possible reasons for such results. Firstly, national tracking data of the spread of coronavirus SARS-CoV- participants in our study were high school students, who are not 2 in Slovenia, COVID-19 presents a relatively low threat to the often represented in gain-loss framing research. It is therefore population of high school students [26]. This may, in turn, impact possible that the impact such framing has on high school students their risk attitudes and compliance with preventive measures. At is limited. At the same time, we must acknowledge that the the same time, it is important to stress that the measuring tool students, representatives of the younger generation, were perhaps used to estimate the extent of participants’ risk aversion was not so familiar with the SARS virus, which might impact their designed to measure financial risk attitudes. Although inclination uptake of risky / safe options. Secondly, the experiment took towards risk-taking behavior has been found to be consistent in place during the ongoing COVID-19 pandemic. It is possible that every behavioral aspect [17], there is a possibility that we would participants were either very disturbed by reading the outbreak have obtained significant results, if we had introduced a scenario (which might have been, to a certain extent, reminiscent measuring tool for health-related risk attitudes. This is certainly of the current pandemic) or indifferent towards it, as people may an important fact we need to consider before planning our future become when unable to help others in need [19]. research in the field. In contrast, it is very interesting that participants’ risk Our finding that impulsive satisfaction of needs is linked to attitudes noticeably change when a specific disease is mentioned. non-compliance with COVID-19 preventive measures is in line Analyzed data indicate that specifying the disease as very similar with the current literature. It has been suggested that the to either the SARS virus or the seasonal flu contributes to proneness to this cognitive bias should be used to promote stay- subjects engaging in risk-taking decision making, no matter at-home restrictions and recommendations by providing free whether losses or gains are framed. Since our study included only internet access or benefit packages for vulnerable groups [13]. high school students, we cannot transpose these findings to the Overall, our study offers an intriguing and thought-provoking general population. However, it seems that in the risk-loss insight into cognitive correlates of COVID-19 preventive framework our subjects understood every specification of the behaviors and is a valuable starting point for future research in disease as a loss, which caused them to engage in more risk- the field. taking behavior. Our results are unanticipated in terms of other hypotheses as REFERENCES well. Contrary to our initial expectations, individuals who are [1] Syon Bhanot. 2020. Why are people ignoring expert warnings? - more prone to belief bias express greater level of compliance Psychological Reactance. Behavioral Scientist. https://behavioralscientist.org/why-are-people-ignoring-expert-warnings with COVID-19 behavioral recommendations. This might be [2] Lucas de F. Carvalho, Giselle Pianowski, and André P. Gonçalves. 2020. linked to the fact that, during the pandemic, compliance with Personality differences and COVID-19: are extroversion and conscientiousness personality traits associated with engagement with COVID-19 behavioral recommendations and regulations has, in containment measures?. Trends Psychiatry Psychother, Vol. 42(2), 179- many cases, become a political matter [20]. Previous research has 184. DOI: https://doi.org/10.1590/2237-6089-2020-0029 shown that people who overall tend to reflect less on their [3] Fabiano K. et al. 2021. Compliance with containment measures to the COVID-19 pandemic over time: Do antisocial traits matter? Personality decisions (a characteristic of belief bias) often support populistic and individual differences, Vol. 168, 110346. DOI: leaders [21]. In that regard, the decision to comply with https://doi.org/10.1016/j.paid.2020.110346 [4] Marcin Zajenkowski et al. 2020. Who complies with the restrictions to behavioral recommendations and containment measures might reduce the spread of COVID-19?: Personality and perceptions of the be more politically motivated than health-related. This is COVID-19 situation. Personality and individual differences, Vol. 166, 110199. DOI: https://doi.org/10.1016/j.paid.2020.110199 additionally confirmed by the pre-existing literature in social [5] Daneil Kahneman. 2011. Thinking, Fast and Slow. Farrar, Straus and psychology: individuals who support the group imposing the Giroux. New York: NY. conformity, are more likely to conform to their social norms as [6] Daniel Kahneman and Amos Tversky. 1979. Prospect Theory: An Analysis of Decision under Risk. Econometrica, Volume 47(2), 263-291. well [22]. Furthermore, a handful of studies in the field report [7] Olivier Sibony. 2020. HEC Paris Insights - Cognitive Biases and similar results - participants who are less reflective in their Decision-Making in the COVID-19 Crisis. [Video]. https://www.youtube.com/watch?v=RhAKzmpwpzw decision making (that is, they rely more on their intuition than on [8] Urška Ferjančič. 2019. The influence of hormones and personal traits on analytical deliberation when making decisions) are reportedly the propensity for risk-taking (Masters thesis, University of Ljubljana, more compliant with preventive measures [23, 24]. Such results 107 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Toporišič Gašperšič & Grof School of Economics and Business). http://www.cek.ef.uni- lj.si/magister/ferjancic3490-B.pdf [9] Mahmoud A. H. Shahin, and Rasha M. Hussien. 2020. Risk perception regarding the COVID-19 outbreak among the general population: a comparative Middle East survey. Middle East Curr Psychiatry, Vol. 27(71). DOI: https://doi.org/10.1186/s43045-020-00080-7 [10] Ding Daoqun et al. 2020. Belief Bias Effect in Older Adults: Roles of Working Memory and Need for Cognition. Front. Psychol. 10:2940. DOI: https://doi.org/10.3389/fpsyg.2019.02940 [11] Laura Macchi et al. 2019. How to Get Rid of the Belief Bias: Boosting Analytical Thinking via Pragmatics. Europe's Journal of Psychology, Vol. 15(3), 595–613. DOI: https://doi.org/10.5964/ejop.v15i3.1794 [12] Fabio Tagliabue, Luca Galassi, and Pierpaolo Mariani. 2020. The "Pandemic" of Disinformation in COVID-19 . SN comprehensive clinical medicine, 1–3. Advance online publication. DOI: https://doi.org/10.1007/s42399-020-00439-1 [13] Moslem Soofi, Farid Najafi, and Behzad Karami-Matin. 2020. Using Insights from Behavioral Economics to Mitigate the Spread of COVID- 19. Applied health economics and health policy, Vol. 18(3), 345-350. DOI: https://doi.org/10.1007/s40258-020-00595-4. [14] Nejc Plohl and Bojan Musil. 2020. Modeling compliance with COVID-19 prevention guidelines: The critical role of trust in science. Psychology, Health & Medicine, 1-12. DOI: https://doi.org/10.1080/13548506.2020.1772988. [15] Henry Markovits and Guilaine Nantel. (1989). The belief-bias effect in the production and evaluation of logical conclusions. Memory & Cognition, Vol. 17(1), 11–17. DOI: https://doi.org/10.3758/BF03199552 [16] Charles A. Holt and Susan K. Laury. 2002. Risk Aversion and Incentive Effects. American Economic Review, Vol. 92(5), 1644–1655. [17] Eyal Ert and Ernan Haruvy. 2017. Revisiting risk aversion: Can risk preferences change with experience? Economics Letters, Vol. 151, 91–95. [18] Shane Frederick. 2005. Cognitive Reflection and Decision Making. Journal of Economic Perspectives, Vol. 19 (4), 25-42. DOI: https://doi.org/10.1257/089533005775196732 [19] Daniel Västfjäll et al. 2014. Compassion fade: affect and charity are greatest for a single child in need. PloS one, Vol. 9(6), e100115. DOI: https://doi.org/10.1371/journal.pone.0100115 [20] Jordan Steffen and Jiuqing Cheng 2021. The influence of gain-loss framing and its interaction with political ideology on social distancing and mask wearing compliance during the COVID-19 pandemic. Current psychology (New Brunswick, N.J.), 1–11. Advance online publication. DOI: https://doi.org/10.1007/s12144-021-02148-x [21] Gordon Pennycook and David G. Rand. 2019. Cognitive Reflection and the 2016 US Presidential Election. Personality and Social Psychology Bulletin, Vol. 45(2) 224–239. DOI: https://doi.org/10.1177/0146167218783192 [22] Deborah J. Terry and Michael A. Hogg. 1996. Group Norms and the Attitude-Behavior Relationship: A Role for Group Identification. Personality and Social Psychology Bulletin, 22(8), 776–793. https://doi.org/10.1177/0146167296228002 [23] Predrag Teovanović et al. 2020. Irrational beliefs differentially predict adherence to guidelines and pseudoscientific practices during the COVID- 19 pandemic. Applied Cognitive Psychology, 35(2), 486-496. https://doi.org/10.1002/acp.3770. [24] Volker Thoma, et al. 2021. Cognitive Predictors of Precautionary Behavior During the COVID-19 Pandemic. Front. Psychol. 12:589800. DOI: https://doi.org/10.3389/fpsyg.2021.589800 [25] Eric Bonetto et al. 2021. Basic human values during the COVID-19 outbreak, perceived threat and their relationships with compliance with movement restrictions and social distancing. PloS one, 16(6), e0253430. https://doi.org/10.1371/journal.pone.0253430. [26] COVID-19 sledilnik [COVID-19 Tracker Slovenia]. 2021. https://covid- 19.sledilnik.org/en/stats. [27] Nils Haug et al. 2020. Ranking the effectiveness of worldwide COVID-19 government interventions. Nat Hum Behav, Vol. 4, 1303–1312. DOI: https://doi.org/10.1038/s41562-020-01009-0 108 The ecological rationality of probabilistic learning rules in unreliable circumstances Borut Trpin† Ana Marija Plementaš Munich Center for Mathematical Philosophy MEi:CogSci Ludwig Maximilian University of Munich University of Ljubljana Munich Germany Ljubljana Slovenia borut.trpin@guest.arnes.si ap0231@student.uni-lj.si ABSTRACT (represented by different learning rules as described above), are some types of reasoning under uncertainty better than In today’s �lood of information in many �ields we do not know others and how may we even tell whether one type is better which sources are reliable and which are not. On what basis than another? That is, how can we compare the performance can we draw conclusions? Whom to trust? We could say each of various learning rules that guide our reasoning? of us has a belief system that updates based on the arrival of It is quite clear that in answering this question we need to new relevant evidence. In our research we used a computer consider what the goals of reasoning are. To name a few model where we were investigating which learning rule is possibilities: perhaps the goal of reasoning is to increase the more reliable when we do not have a trustworthy source. The understanding of the phenomenon that is the subject of main goal is to discover the truth and to do so quickly. Our reasoning, or the goal may be to uncover whether some results show that different probabilistic learning rules may statement holds. In fact, it seems that there are countless be preferable in different situations and environments. aspects that could be considered as valuable outcomes of KEYWORDS reasoning and that could as such be used in comparing which rule that guides reasoning is better (or better in some ecological rationality, belief updating, reasoning, learning context). rules, uncertainty In our investigation we focused on two valuable outcomes: (i) uncovering the truth, and (ii) the speed of 1 reasoning. The former, (i), considers how certain one is of INTRODUCTION true propositions due to reasoning according to a speci�ic We cannot fully rely on our senses nor on other external (learning) rule. If (i) is our guide, then we take a rule to be sources of information (e.g., testimony provided by others). better if it makes one more certain of true propositions. The In addition, it seems that there are multiple types of latter, (ii), considers how quickly one can reach conclusions reasoning under uncertainty in the sense that we use while reasoning. Similarly, if a rule is quicker in making an different learning (or reasoning) rules that guide the process agent more certain (it quickly lessens uncertainty), then it of reasoning. For instance, in trying to reach a conclusion performs better on this count. about some question (e.g., a doctor is trying to diagnose a Ideally, both (i) and (ii) would go hand in hand: a reasoner patient) on the basis of some evidence/information (e.g., would reach true conclusions and would also reach them diagnostic tests) an agent might follow a principle of quickly. However, it seems that they do not usually go hand inferring to the best explanation (e.g., of the tests and their in hand: rules that are especially conducive of (i) seem to sensitivity and speci�icity). Another agent might consider typically not be so conducive of (ii), and vice-versa (see, e.g., other aspects of the situation and hence follow different [1], [2]): more conservative learning rules (i.e., not jumping learning rules like, e.g., how con�irmatory the evidence is of to conclusions too quickly) are usually such that lead to more some hypothesis that is being reasoned about (e.g., if a accurate conclusions. patient had a disease X, how likely it would be that the tests For instance, one could excel on count (i) but fail on count would be such and such given the objectively known (ii): e.g., a learning rule could lead to mostly true conclusions information about the reliability of the test). A question that but only after a vast amount of evidence is considered. An may be raised could then be put as follows: Given that there example of this would be a medical doctor that identi�ies the are multiple ways of reasoning under uncertainty correct disease in her patient but needs to conduct a large number of diagnostic tests before she is able to do so. Similarly, one could underperform on (i) but excel on (ii): 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 such a case would be a doctor that makes a diagnosis on the distributed for profit or commercial advantage and that copies bear this notice basis of a single or few tests but her diagnosis is wrong. What and the ful citation on the first page. Copyrights for third-party components of we aimed to answer in our research project was which this work must be honored. For al other uses, contact the owner/author(s). learning (or reasoning) rules are the most conducive of (i) Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia and (ii), and how the two valuable goals (truth and speed) © 2021 Copyright held by the owner/author(s). could be balanced when we compare different learning rules. 109 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia B. Trpin and A. M. Plementaš Additionally, we wanted to keep in mind that the sources of As we can see from this brief explanation of the information need not be fully reliable -- they could even be background, they already considered both valuable completely misleading. outcomes of reasoning that we were also interested in: (i) epistemic aspects: how close to truth we get due to learning/reasoning under uncertainty, and (ii) pragmatic 2 BACKGROUND aspects: how quickly we manage to form strong beliefs on the Our research project actually starts from an investigation of basis of learning. Moreover, they considered unreliable learning on the basis of partial lying, i.e., learning in cases sources similarly as we did. where one asserts information that she believes to be likely Another related research project was conducted by but not necessarily false. Another agent then learns based on Douven (see [4]). In that research, the focus was not so much both (a) such statements and (b) observations of whether the on unreliable sources of information but rather on how statements are true or false. This provides the basis for different probabilistic learning rules compare. In the �irst estimating the reliability of the source: if statements are part of his research, which was based on computer (mostly) true, the source is more reliable and vice versa, if simulations of learning, he found that the rules diverged on statements are mostly false, the source is taken to be more both aspects. In the second part, he devised an interesting unreliable. We were interested in reliability/trustworthiness method for balancing the two aspects (accuracy and speed) of the source under uncertainty more generally (e.g., and to estimate natural selection of the best rules for a given diagnostic tests in a medical setting might be unreliable too, environment (viz. ecological rationality of different not just our interlocutors who may want to mislead us probabilistic learning rules). Speci�ically, he considered that intentionally), but a previous research project of partial lying we can simulate an intensive care unit (hereafter: ICU) in (see [3]) turned out to be a good starting point because it which doctors are trying to help a patient. There are three provided a useful formal description of the mechanisms on options: the doctor either intervenes correctly, wrongly, or - how to estimate reliability/trustworthiness of a source and in case she remains uncertain - does not intervene at all. The how to incorporate this estimate in a learning rule (there: probability of the patient's survival changes through time Bayesian learning, although our research project also and depends on the decision: as time passes, the survival includes other learning rules). Before we can explain why becomes less likely. Similarly, at any point, the correct partial lying is very similar to the topic we were intervention increases the probability of survival, the wrong investigating, let us brie�ly explain the issue of what partial intervention decreases it and not intervening at all puts the lying even is. probability of survival in between the two other options. Philosophers de�ine lying with four conditions: (1) a Douven demonstrated that using a method of natural statement, (2) the belief that the statement is false, (3) the optimization can provide another argument in favor of addressee, and (4) the purpose of misleading the addressee probabilistic inference to the best explanation: although it is (see [3] and the references therein). a bolder learning rule -- it leads to quicker conclusions and If someone is constantly lying to us, this individual can be may therefore suffer from inaccuracy -- it is still quick and simply deemed unreliable and ignored or even taken as if reliable enough, so that it will typically provide the best they are telling us the opposite of truth (saying "A" could be trade-off between the two valuable outcomes of reasoning: taken as evidence for "not A"). If, however, truth and lies are speed and accuracy. Speci�ically, in this case he was mingled in varying proportions, choosing whether to trust simulating 200 doctors, 50 learning from diagnostic tests this individual, and if so to what degree, becomes according to each of the 4 learning rules. Then each of them increasingly dif�icult. This fact has been emphasized by Trpin would get 100 simulated patients and would be able to and colleagues [1], which pointed out that the de�inition for conduct a number of tests on them (100 tests) to diagnose lying misses out on many similar cases because the second their disease. At the end of a run we can see what the condition is too strict. They broadened the second condition probability of survival was for each of the 200 simulated – we usually also consider someone a liar when they believe doctors and the top 100 doctors were duplicated and the their statement to be more likely false than true. However, as bottom 100 erased from the population. This then went on they discovered through several computer simulations, for 100 generations when mostly explanationist doctors estimating the trustworthiness of the source then becomes remained. more dif�icult, hence such medium-strong lies (that is, those Although his research project included reasoning under where the liar is only somewhat certain that they are uncertainty and an insightful way of balancing the valuable asserting falsehoods) do us more epistemic harm. Following speed and accuracy of reasoning, it did not consider the Bayes’ learning rule to model lying, the research conducted trustworthiness of information sources and it also did not by Trpin and colleagues [1] sparked debates as to whether it consider that information (here: diagnostic tests) might be is sensible to consider partial lies at all, if one aims to reduce false. Hence, a combination of the research on partial lying epistemic harm. What they found is that this approach is only (as described above and in [3]) and that of natural useful when the goal is to quickly avoid believing false optimization for comparing different probabilistic learning propositions. 110 The ecological rationality of probabilistic learning rules in unreliable circumstances Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia rules (as just described, see also [4]) appeared to be an The idea is that we can look at mean squared error of the interesting topic that needed to be tackled. probability distribution: effectively, if a forecast is perfect, the score is 0, and the more off it is, the higher the score, which is also the reason why the score is sometimes called 3 METHOD: PART 1 Brier's penalty. A computer model was created on the basis of other projects In our simulations, we used it to compare the accuracy of described in the previous section. The model included a trust ascribed coin biases. If the simulated coin has a .7 bias to land system in which updating was simulated. heads, then ideally our reasoner would assign probability 1 Speci�ically, in the �irst part we simulated a game of coin to the hypothesis that the coin is .7 biased. As this is unlikely bias detection. Agent A is observing the coin and reasoning to happen, we then measure mean squared error of the about its bias, i.e., A is trying to learn how biased the coin is. discrete probability distribution from this ideal outcome. In The simulations consisted of 500 throws of 11 different coins turn, we can use this to compare the performance of different - hypotheses. Each of the 11 coins had its own bias, with learning rules. probability from 0 to 1 in .1 increments for it to land on heads. Similarly, for measuring speed we can simply compare The experiment was repeated a thousand times. In how long it took each reasoner to assign a probability above addition to coin throws we also simulated another Agent B, some threshold value (e.g., above .9) to the true hypothesis who may be taken as an information source. Agent B was about the coin's bias. Note that both the speed of there to provide unreliable and potentially misleading convergence and the accuracy (Brier's score) also depend on information to A, viz. B is telling A which side the coin is the coin that is used in simulations. This is because it is easier supposedly going to land on, although B does not necessarily to determine the bias of a fully biased coin than of a fair coin: provide true information ("B lies to A"). There were also if it always lands on the same side, it is easier to conclude it three lists of lies according to the following principles: simple is fully biased than when it is landing on various sides (note lying (the player states the least probable outcome of the coin, that a fair coin may also land on the same side many times in i.e., if the coin is biased to land on heads, agent B will state a row, although such a pattern is more expected from a fully that it will land on tails), gambler's lying (the player turns the biased coin). coin secretly and states the opposite of the outcome) and clairvoyant lying (the clairvoyant knows the exact outcome and states the opposite). Bayes’s learning rule, Good’s 4 RESULTS: PART 1 learning rule, Popper’s learning rule and Explanatory Results mainly show differences in probabilistic learning learning rule were used to learn from these data rules in simple lying when the probability of lying is 1.0 - (observations of coins and statements + dynamic trust) to constant lying, which is also the only part that we are see which belief system update is causing the least epistemic including in this extended abstract. It was found that the best damage. Learning rules offer a way to update the beliefs in probabilistic learning rule, in this case, is Explanatory the light of the arrival of new relevant evidence. Speci�ically: learning rule with the lowest Brier penalties (i.e., the lowest Bayes’ learning rule requires that the new probability inaccuracy). This result has interesting implications: it shows distribution (after learning) corresponds to the prior that if the data is misleading, then it may make more sense to conditional probability distribution (conditional on the use non-Bayesian alternative probabilistic rules. learned piece of evidence and the level of trust in the source). Note, however, that the accuracy is even greater when we The other three rules are all based on Bayes’ but deviate in look at control runs, that is, the cases where the information various ways: the explanatory learning rule adds extra source was ignored, so that the learning agent was merely weight to the hypothesis that provides the best explanation. observing which side the coin landed on without considering That is, if a coin lands heads 5 times in a row, the best what the liar was asserting. This seems to suggest that when explanation is that it is fully biased towards heads, so this we are dealing with unreliable sources of information, it hypothesis gets a probabilistic "push" compared to what might be best to immediately ignore such sources, e.g., a Bayes’ rule would require. Good's and Popper's rule are doctor who notices that her diagnostic tests are unreliable similar, except that instead of looking at the best explanation, could stop conducting these tests. However, when we look at they award those hypotheses that provide the most the speed of convergence, we observe that it makes sense not con�irmatory theories according to measures of con�irmation to ignore such sources if we are also interested in quickly developed by Good and Popper, respectively (see [4] for recognizing true hypotheses: control runs were slower than formal details about the updating rules). others at least for some of the simulated coins. After the simulations are conducted, we then look at the Moreover, inference to the best explanation was, contrary collected data. Speci�ically, we were interested in the to previous research, the fastest but also the most accurate, epistemic performance of the rules (how close to the truth i.e., it was able to combine both accuracy and speed of they bring an agent) and the speed of convergence towards reasoning, the two values that previously appeared to be true hypotheses. To measure how accurate the rules were, mutually exclusive. we used a measure called Brier's score (or Brier's penalty). 111 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia B. Trpin and A. M. Plementaš 5 METHOD: PART 2 The second part of our research followed the approach used by Douven (see [4] and the section on background above). Particularly, we were interested in simulating an ICU with doctors trying to diagnose their patients when the tests are potentially unreliable/misleading. The situation is very similar to part 1: instead of coin biases we deal with diseases that may show some symptom with 0, .1, .2, ..., 1 probability and tests that correspond to partial lying in various lying styles: they are not fully reliable and our doctors estimate the reliability of the tests. We can then look at what the survival rates were for each of the doctor's patients and replicate the top performing half doctors and repeat this for 100 generations. Hence, we combine the research from the �irst part and the research described in the background section. Figure 2: Average percentage of agents ("simple" lying) 6 RESULTS: PART 2 The results are interesting: if we look at tests that are constantly misleading (i.e., all of them are unreliable to some degree that needs to be estimated) and if they correspond to what would be akin to simple lying (if it is more likely that a patient has a symptom X than not at the time of the testing, the test will not show the presence of X), then the doctors that infer to the best explanation prevail through generations (see Figure 1 for an example of a simulation and Figure 2 for average percentage of different doctors in our simulations). However, if the tests correspond to being unreliable in what is akin to gambler's or clairvoyant lying we get different results: tests that are unreliable in the gambler's lying style favor both Good's and explanationist reasoning (Figure 3), while those that are like clairvoyant's (always the wrong result) favor Bayes's rule: see Figure 4. Figure 3: Average percentage of agents ("gambler's" lying) Figure 1: Example of different agents in a single simulation Figure 4: Average percentage ("clairvoyant" lying) 112 The ecological rationality of probabilistic learning rules in unreliable circumstances Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 7 CONCLUSIONS The results, especially those of Part 2, are very interesting because they suggest that different probabilistic learning rules that have been addressed in literature may be preferable in different situations and preferable in various environments. Ecological rationality then suggests that if we happen to be in an environment with speci�ic features, which we plan to identify in our future research work, then Bayes' rule might be the best way to proceed. Similarly, explanationist learning or Good's or Popper's learning might be preferable in other situations. It remains an open question what features of the information environment determine the choice of a learning rule, but our results suggest that a pluralist approach to learning rules under uncertainty is needed. Our results also provide one possible explanation why we seem to have different reasoning patterns under uncertainty in a descriptive sense, that is, because different environments call for different reasoning strategies. Further research could also provide some insights into pluralist reasoning strategies, i.e., strategy-switching. REFERENCES [1] Igor Douven, 2013. Inference to the Best Explanation, Dutch Books, and Inaccuracy Minimisation. Philosophical Quarterly, 63. 428–444. DOI: https://doi.org/10.1111/1467-9213.12032 [2] Borut Trpin and Max Pellert. 2019. Inference to the Best Explanation in Uncertain Evidential Situations. The British Journal for the Philosophy of Science, 70, 4. 977-1001. DOI: https://doi.org/10.1093/bjps/axy027 [3] Borut Trpin, Anna Dobrosovestnova, and Sebastian Jakob Götzendorfer. 2020. Lying, more or less: a computer simulation study of graded lies and trust dynamics. Synthese, 1-28. DOI: https://doi.org/10.1007/s11229-020-02746-5 [4] Igor Douven. 2020. The ecological rationality of explanatory reasoning. Studies in History and Philosophy of Science Part A. 1-14. DOI: https://doi.org/10.1007/s11229-020-02 113 114 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek C Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume C Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Urednika / Editors Dunja Mladenić, Marko Grobelnik http://is.ijs.si 4. oktober 2021 / 4 October 2021 Ljubljana, Slovenia 115 116 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. 117 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Jane Brank, Jožef Stefan Institute, Ljubljana Marko Grobelnik, Jožef Stefan Institute, Ljubljana Jakob Jelenčič, Jožef Stefan Institute, Ljubljana Branko Kavšek, University of Primorska, Koper Aljaž Košmerlj, Qlector, Ljubljana Dunja Mladenić, Jožef Stefan Institute, Ljubljana Inna Novalija, Jožef Stefan Institute, Ljubljana Jože Rožanec, Qlector, Ljubljana Luka Stopar, Sportradar, Ljubljana 118 OBSERVING ODOR-RELATED INFORMATION IN ACADEMIC DOMAIN Inna Novalija M. Besher Massri Jožef Stefan Institute Jožef Stefan Institute and Jožef Stefan Jamova cesta 39, Ljubljana, Slovenia International Postgraduate School inna.koval@ijs.si Jamova cesta 39, Ljubljana, Slovenia Dunja Mladenić besher.massri@ijs.si Jožef Stefan Institute and Jožef Stefan Marko Grobelnik International Postgraduate School Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia Jamova cesta 39, Ljubljana, Slovenia dunja.mladenic@ijs.si marko.grobelnik@ijs.si Daniel Schwabe Janez Brank Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia Jamova cesta 39, Ljubljana, Slovenia daniel.schwabe@ijs.si janez.brank@ijs.si ABSTRACT In this paper we present an approach for mining olfactory information from scientific research collections, such as the In this paper, we demonstrate an approach for observing olfactory Microsoft Academic Graph (MAG) [3]. related information in an academic publications environment (such as Microsoft Academic Graph) based on semantic technologies. The olfactory mining approach combines data processing, We present an Odor Observatory tool that enables several usage modelling and visualization methods in order to develop applicable scenarios, such as observing odor-related papers and topics, tools for data analysis. viewing institutions conducting olfactory research, defining top We present an Odor Observatory tool [4] targeted at several journals and key countries in the olfactory domain. visualization scenarios. In particular, the Odor Observatory allows Validation of the proposed approach on a collection of academic exploring olfactory related papers from the MAG over time, and publications from 1800 until 1925 confirms applicability of the along with current data, provides historical information starting proposed approach on large data collections with a wide span of with the early XIX century. time. In usage scenarios we observed the odor-related publications The data-driven functionalities of Odor Observatory are: in Microsoft Academic Graph by topic, discovered the journals ▪ with historical olfactory publications and found that the most Possibility of exploring top ranked topics in the olfactory popular terms in odor-related research content are: method, academic domain; ▪ olfactory, odor, device, invention, smell, preparation, utility model. Possibility of exploring top ranked institutions conducting olfactory research; ▪ Possibility of exploring key countries and defining top KEYWORDS ranking journals in the olfactory academic domain; ▪ Odor-related search functionalities; Odor, Olfactory information, Microsoft Academic Graph (MAG), ▪ Word cloud visualization for odor-related terms. Data mining. 2. RELATED WORK 1. INTRODUCTION Olfactory science covers different aspects of research related to Olfaction, or the sense of smell, is the sense through which smells odors, therefore exploring odor related information and data can be (or odors) are perceived [1]. Olfactory science involves studying viewed as complex multidisciplinary area. olfaction and odor-related topics, the sensory system, physiology, Lötsch et al. [5] considered machine learning approaches for human and pheromone signals. olfactory research. The authors state that the complexity of the The Odeuropa project [2] gathers and integrates expertise in human sense of smell is reflected in complex and high-dimensional sensory mining and olfactory heritage. The project partners are data, which supports the applicability of machine learning and data developing novel methods to collect information about smell from mining techniques. The use of machine learning in human olfactory (digital) text and image collections. research includes the following aims: The Odeuropa project partners apply state-of-the-art AI techniques to text and image datasets in order to identify and trace how ‘smell’ 1. The study of the physiology of pattern-based odor was expressed in different languages, with what places it was detection and recognition processes; associated, what kinds of events and practices it characterized, and 2. Pattern recognition in olfactory phenotypes; to what emotions it was linked. 3. The development of complex disease biomarkers including olfactory features; 119 4. Odor prediction from physico-chemical properties of Figure 2 illustrates an entry in MAG for a historical publication volatile molecules, and tagged with several odor-relevant topics. 5. Knowledge discovery in publicly available large databases. The authors provide review of key concepts of machine learning and summarizes current applications on human olfactory data. At the same time, linguistic and semantic communities focused on studying the language of smell [6]. Iatropoulos et al. developed a computational method to characterize the olfaction-related semantic content of words in a large text corpus of internet sites in English. They also introduced novel metrics, such as olfactory association index (OAI) and olfactory specificity index (OSI). Tonelli [7] describes olfactory information extraction and semantic processing from a multilingual perspective. The author states that in several studies it was found that languages seem to have a smaller vocabulary to describe smells as compared to other senses. In our work we apply data mining and machine learning, as well as semantic approaches for enriching textual data. We use data from Microsoft Academic Graph and our methodologies can be regarded as being in the context of semantic and text processing research. Our approaches can cover cross-lingual and multilingual data and Figure 2: Publication in MAG allow for tracking olfactory trends in time. 3. PROBLEM DEFINITION 3.1 DATA SOURCES The Microsoft Academic Graph (MAG) [3] is a heterogeneous graph containing scientific publication records, citation relationships between those publications, as well as authors, institutions, journals, conferences, and fields of study. Since this research is conducted in line with the Odeuropa project (targeted at olfactory heritage), the time frame used for MAG data is set to range from the early publications in the 19th century to the present time. The Odeuropa project is interested in particular in the data available up to 1925. Though the project is focused on the historical datasets, the developed Odor Observatory tool allows users to explore recent olfactory publications as well. The dataset is updated on a monthly basis and new available data is uploaded into the observatory. Figure 3: Odor in the MAG Taxonomy Figure 1: The Conceptual Schema for MAG Figure 3 shows a representation of Odor in the MAG taxonomy, The Microsoft Academic Graph data schema is based on the list of with parent topics (Organic chemistry and Neuroscience) and child following entity types: publication, author, author affiliation topics (Olfactory learning, Geosmin etc.) (institution), publication venue (journals and conferences), field of study (topic). It contains information about publication dates, as An important functionality while exploring the literature is the well as citation pairs and co-authorship data (see Figure 1). ability to expand searches by looking at related topics to a topic of interest. Figure 4 displays topics about/related to Figure 2 illustrates an entry in MAG for a historical publication Olfaction/Odor/Smell in MAG taxonomy. tagged with several odor-relevant topics. 120 Figure 5 shows the number of odor-related historical publications in MAG over time. This scenario assumes observing trends in different olfactory topics throughout a time interval. It is possible to observe that the highest number of publications are in the domains of biology and psychology. Figure 4: Odor-related Topics in MAG Figure 5: Odor-related Publications in MAG (from year 1800 until year 1925, cumulative) by topic 3.2 METHODOLOGY 2. What are the most popular terms used in odor-related The methodology for observing olfactory related information from publications? academic publication resources includes a number of steps: ▪ This use case helps the user to visualize term usage by displaying a Using the MAG taxonomy, obtain the list of research word cloud with the most popular olfactory terms used in the papers that corresponds to odor-related topics. Papers publications in the period of interest (see Figure 6). were filtered to those containing the topics: Olfaction, Odor, Fragrance, Fragrance ingredient, as well as the “smell” keyword; ▪ Ingest the extracted corpus into the Elastic Search tool1; ▪ Provide visualization functionalities, such as MAG time series per term. The key challenges of the development techniques include: ▪ Interpretability and explainability of the results – the aim is for the visualizations to be able easily interpretable by humans; ▪ Given the large scale of the incoming data streams, it is essential that building visualizations are scalable. The MAG contains more than 265 million records (August 2021), including several types of publication, such as Figure 6: Odor Terms Word Cloud in MAG journal articles, conference papers, books, book chapters, and papers from other repositories. In addition, MAG also indexes a large corpus of patents. 3. Which venues were mostly used when publishing odor- related research articles? 3.3 USAGE SCENARIOS This use case shows a number of journals that had historical We present a couple of usage scenarios for the Odor Observatory publications about smells (see Figure 7). tool, cast as questions asked by scholars studying the field. The figure shows that JAMA and Nature journals are the most 1. What are the historical trends in odor-related popular journals regarding historical olfactory publications. publications? 1 https://www.elastic.co 121 The figure shows a ranked list of relevant publications on the topic of “smells”, in the period from 1900 to 1925. The list is modified by changing the context on the right side - the focus is changed by placing the cursor over a cluster, and publications associated with this cluster are displayed. 4. CONCLUSION In this paper we demonstrated an approach towards observing olfactory related information in scientific publications, as recorded in the MAG. In addition, we present an Odor Observatory tool that enables several usage scenarios for exploring historical and present olfactory research. Figure 7: Journals with Olfactory Publications in MAG The future work will include the exploration of other textual (from year 1800 until year 1925, cumulative) datasets applicable for olfactory research, with an accent on olfactory heritage information. In line with the Odeuropa project, the relevant information 4. Which are the publications about smell (from a extracted from textual sources will be, following semantic web contextual point of view)? standards, aligned with the ‘European Olfactory Knowledge The Research Explorer tool is a search engine that enables Graph’ (EOKG). exploring the individual articles in the corpus of odor-related publications. 5. ACKNOWLEDGMENTS This research is supported by the Slovenian research agency and by the European Union’s Horizon 2020 program project Odeuropa under grant agreement number 101004469. REFERENCES [1] Wolfe, J. M., Kluender, K. R., Levi, D. M., Bartoshuk, L. M., Herz, R. S., Klatzky, R., Lederman, S. J., & Merfeld, D. M. (2012). Sensation & perception (3rd ed.). Sinauer Associates. [2] Odeuropa project, https://odeuropa.eu (accessed in August, 2021). [3] Wang K. et al. A Review of Microsoft Academic Services for Science of Science Studies, Frontiers in Big Data, 2019, doi: 10.3389/FDATA.2019.00045. [4] JSI Odor Observatory, public service, https://odeuropa.ijs.si/dashboards/Main/Index?visualization= visualizations-MAG--top-topics# (accessed in August, 2021). [5] Lötsch, J., Kringel, D., Hummel, T. Machine Learning in Human Olfactory Research, Chemical Senses, Volume 44, Issue 1, January 2019, Pages 11–22, https://doi.org/10.1093/chemse/bjy067. [6] Iatropoulos, G., Herman, P., Lansner, A., Karlgren, J., Figure 8: List of Olfactory Publications in MAG (from year Larsson, M., Olofsson, JK. The language of smell: Connecting 1800 until year 1925) that contains the keyword "smell" linguistic and psychophysical properties of odor descriptors. Cognition. 2018 Sep;178:37-49. doi: The tool is built on Elastic Search and provides search by keyword 10.1016/j.cognition.2018.05.007. Epub 2018 May 12. PMID: and by date. It also supports smart navigation through the results by 2976379. clustering the results and re-ranking the results by moving the focus [7] Tonelli, S. A Smell is Worth a Thousand Words: Olfactory of search through the cluster space (see Figure 8). The goal of the Information Extraction and Semantic Processing in a tool is to enhance a search engine by providing the users multiple Multilingual Perspective. doi: rankings of the results for each query. It is achieved by https://doi.org/10.4230/OASIcs.LDK.2021.2 generating topics for the given query and its result set, and https://drops.dagstuhl.de/opus/volltexte/2021/14538/pdf/OA visualizing these topics on the “Ranking Space” panel. When SIcs-LDK-2021-2.pdf (accessed in August, 2021). the focus is set near a given topic, results that are on or closer to that topic are ranked higher. 122 Understanding Text Using Agent Based Models Adrian Mladenic Grobelnik Marko Grobelnik Dunja Mladenic Jozef Stefan Institute Jozef Stefan Institute Jozef Stefan Institute Ljubljana Slovenia Ljubljana Slovenia Ljubljana Slovenia adrian.m.grobelnik@ijs.si marko.grobelnik@ijs.si dunja.mladenic@ijs.si ABSTRACT The main contributions of this paper are (1) a novel approach to explainable story understanding, (2) a system generating stories The paper proposes a novel approach to text understanding and given a set of agents with attributes and goals, and (3) text generation focusing on short stories. The proposed approach implementation of the proposed approach, with publicly attempts to understand and generate stories by creating an available source code [7] allowing users to create and analyze explainable, agent-based world model of the story. The world their own stories. model is defined through agents, their goals, actions, attributes The rest of this paper is organized as follows: Section 2 provides and relationships between them. We demonstrate our approach a problem description. Section 3 describes the approach used to on the story of ‘Little Red Riding Hood’, simulating it as a tackle the problem. Section 4 demonstrates the functioning of our sequence of 48 actions, involving 7 main agents and 14 goals. approach. The paper concludes with discussion and directions for KEYWORDS future work in Section 5. Text understanding, agent-based approach, world model, agent- based model 2 Problem Description The problem we are solving is, given the text of a short story, convert it into a machine understandable and actionable 1 Introduction description representing the dynamics of the story being told. With recent advancements in deep learning and overall increases Such an actionable description should encode the implicit in computing power, artificial intelligence systems are now able knowledge assumed by the text in the form of an agent-based to make commonsense inferences from simple events, as world model. proposed in research such as COMET [1] and MultiCOMET [2]. The world model should include enough representational power While the aforementioned commonsense inferences can be made to fully represent the story. This includes agents, their with a high degree of precision, they lack an explainable and environment and the relationships between them. The world comprehensive structure capable of storing and predicting future model should be actionable enough to simulate the dynamics of events with such inferences. Agent-based models (ABMs), while an input story with all the key elements, and relevant details capable of simulating complex interactions between agents, mentioned in the input text. rarely focus on understanding stories in greater depth. Moreover, As the world model can represent a story given its text, it should they cannot perform commonsense reasoning on agent’s goals, also be able to represent and simulate other stories within the actions or attributes. In our research, we draw from existing world model’s constraints. work on ABMs to create a system capable of understanding short Some of the key operations the resulting system should support: text-based stories, with the potential to incorporate 1. representation of the story commonsense inferences in the future. 2. simulation of the story’s dynamics Related work such as ‘Automated Storytelling via Causal, 3. question answering about explicit and implicit Commonsense Plot Ordering’ [3] and ‘Modeling Protagonist elements written or assumed within the story Emotions for Emotion-Aware Storytelling’ [4] makes use of 4. creating alternative stories, given their context COMET to tackle automated story plot generation. As the stories are generated using COMET’s commonsense causal inferences, they lack explainability. In our work, we focus on generating 3 Approach Description explainable stories. The general aim of our approach is to provide deep text Other related work [5] focuses on story understanding using understanding of the input story. Not all the steps are automatable manually supplied commonsense rules, concept patterns and at this stage. In particular, the biggest challenge is to story text. Our system aims to understand and simulate a story, automatically translate the story text into the knowledge based given the story text, goals and initial attributes of its agents. representation aligned with the world model. We are looking forward to eventually automate all of the steps in the approach. 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 2021, 4-8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 123 Figure 1: A partial representation of the Wolf agent’s goals, actions and attributes. As a running example of the input story, we selected the popular preconditions and effects. We show two example action children’s story ‘Little Red Riding Hood’ [6]. In the first stage, representations in Figure 3 and Figure 4. The duration of each we restructured the original story into 73 simplified sentences action corresponds to the passing of one time unit. where we identified 23 key events involving 7 main agents: 1. Mother 2. Riding Hood 3. Flower Field 4. Butterfly 5. Wolf 6. Grandma 7. Woodsman Each agent is represented by its goals, actions and attributes (see Figure 1 for an example involving the Wolf). All goals cause actions and all actions change at least one agent’s attributes. As depicted on Figure 2, an agent’s goal is defined by a goal state (a set of agents with specific attribute values) and ‘pre-goals’ (goals that must be completed and act as preconditions for an Figure 3: An example representation of an action agent to start working towards the goal). Figure 4: An example pseudocode representation of a concrete action, taken from [9] Figure 2: An example representation of a goal An attribute is simply defined as any information relating to the To define actions, we use an action schema proposed as part of agent. For instance, the agent’s location, inventory of items and ‘UCPOP: A Sound, Complete, Partial Order Planner for ADL’ awareness of other agents. [8] where each action consists of a set of parameters, 124 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia A.M. Grobelnik et al. Figure 5: Hierarchy of agents for the Little Red Riding Hood story The agents are defined through a hierarchy, ensuring consistency We first initialize the world model to an initial setting similar to across agent goals, actions, attributes and providing a clear that of ‘Little Red Riding Hood’, illustrated in Figure 7. For overview of the agent types as observed in Figure 5. instance, agents ‘forest4’ and ‘woodsman’ are in the same Throughout the story simulation of ‘Little Red Riding Hood’ 3 location, 1 unit above agent ‘forest3’. The model is initialized key agents jointly had 14 goals, causing them to perform a total with the agents, their initial attributes with values and their goals of 48 actions composed of 12 unique action types. in the story. Once initialized, we can run the model and see the We propose a simple textual description of each performed agents interact with each other within their environment. For an action, stating why the agent executed the action and which other example, see Figure 9. agents were involved. See Figure 8 for an example. One could divide the story into the following 5 main segments: At the highest conceptual level, we randomly select an agent and 1. Riding Hood discusses visiting Grandma with Mother simulate all of its possible next actions. We then select the action (6 actions) that brings the agent closest to all it’s currently active goals, and 2. Riding Hood meets Wolf and goes to Grandma (23 execute this action. We repeat this until there are no more agents actions) with active goals in our world model, as depicted in Figure 6. 3. Wolf eats Grandma and tries to impersonate her; Riding Hood arrives at GrandmaHouse and cries for help (6 actions) 4. Woodsman saves Grandma and takes Wolf away, Riding Hood gifts Grandma (13 actions) As an example, in the third story segment the actions occur in the following order: 1. Wolf eats Grandma to satisfy hunger. Figure 6: High level pseudocode of the simulation within the 2. Wolf took perfume from GrandmaHouse’s inventory world model to try impersonating Grandma. 3. Wolf took nightgown from GrandmaHouse’s inventory to try impersonating Grandma. 4 Approach Demonstration 4. Wolf took sleeping cap from GrandmaHouse’s inventory to try impersonating Grandma. 5. Riding Hood moved 1 unit up to visit Grandma. 6. Riding Hood cried for help to get help. The system is able to automatically generate the textual description of the story simulation over time, as depicted in Figure 8. Figure 7: Initial state of the agents’ locations within the world model; each X, Y slot includes a list of agents at that location 125 Understanding Text Using Agent Based Models Information Society 2021, 4 October 2021, Ljubljana, Slovenia Adapting the system to another story using our source code is relatively easy, provided the action and attribute types of the agents in the story are similar to those in the ‘Little Red Riding Hood’. If the story requires the implementation of new actions or attributes, this can be done by extending the class structure in C++ using already implemented actions and attributes as examples. Figure 8: A part of an example story, generated by the In our future work we intend to integrate commonsense system inferences, such as those from MultiCOMET into our model to further the system’s degree of textual understanding. Our system could also benefit from the addition of dynamic and simultaneous goals that change based on the agent’s environment. Another possible future line of work is to use our approach in other domains to describe more complex phenomena, such as real- world events or geopolitics. Lastly, a user evaluation of our system’s performance on a variety of stories and scenarios could provide further insight into the efficacy of our approach. ACKNOWLEDGMENTS The research described in this paper was supported by the Slovenian research agency under the project J2-1736 Causalify Figure 9: Screenshot of two subsequent agent location and co-financed by the Republic of Slovenia and the European configurations on the map: (1) after Riding Hood gives Union under the European Regional Development Fund. The Grandma flowers and (2) after Woodsman carries away operation is carried out under the Operational Programme for the Wolf Implementation of the EU Cohesion Policy 2014–2020. One of the more conceptually complex parts of the story was Riding Hood asking Mother for permission to visit Grandma. REFERENCES This required the creation of a new attribute for human agents to [1] Bosselut, A.; Rashkin, H.; Sap, M.; Malaviya, C.; Celikyilmaz, A.; and Choi, Y. 2019. COMET: Commonsense transformers for automatic describe their opinions of other agents’ goals. knowledge graph construction. In ACL, 4762–4779. The most complex action implemented was “cry for help”. This [2] Adrian Mladenic Grobelnik, Marko Grobelnik, Dunja Mladenic. 2020. involved the creation of a new goal “respond to cry for help” for MultiCOMET – Multilingual Commonsense Description. In Proceedings of the 23rd international multiconference information society, pages 37- all human agents within a certain radius of the agent crying for 40 help, provided they were conscious and able to respond. [3] Prithviraj Ammanabrolu, Wesley Cheung, William Broniec, and Mark O Riedl. 2021. Automated storytelling via causal, commonsense plot The story ends when Riding Hood gives Grandma the flowers ordering. In Proceedings of the 35th AAAI Conference on Artificial she picked and the basket Mother gave her, and Woodsman Intelligence (AAAI). [4] Faeze Brahman and Snigdha Chaturvedi. 2020. Modeling protagonist carries the Wolf “deep into the forest where he wouldn't bother emotions for emotion-aware storytelling. In Proceedings of EMNLP, people any longer” [6]. pages 5277– 5294. The system was implemented in about 3,000 lines of C++ code, [5] Patrick Henry Winston. The genesis story understanding and story telling system: A 21st century step toward artificial intelligence. 2014. Technical available on GitHub [7]. report, Center for Brains, Minds and Machines (CBMM). [6] Little Red Riding Hood by Leanne Guenther. https://www.dltk- teach.com/RHYMES/littlered/story.htm. Accessed 16.09.2021. [7] Understanding Text Using Agent Based Models GitHub. 5 Discussion https://github.com/AMGrobelnik/Understanding-Text-Using-Agent- Based-Models . Accessed 16.09.2021. In our research we expanded on and adapted existing work on [8] Penberthy, J., & Weld, D. 1992. UCPOP: a sound, complete, partial-order agent-based models, providing an alternate approach to text planner for ADL. In Proceedings of KR’92, pp. 103–114, Los Altos, CA. understanding and generation involving short stories. As a proof Kaufmann. [9] An Introduction to AI Story Generation. https://thegradient.pub/an- of concept, we applied our approach on the children’s story of introduction-to-ai-story-generation/. Accessed 16.09.2021. ‘Little Red Riding Hood’, describing it through a series of 48 highly explainable actions involving 7 main agents. 126 News Stream Clustering using Multilingual Language Models Erik Novak erik.novak@ijs.si Jožef Stefan Institute Jožef Stefan International Postgraduate School Jamova cesta 39 Ljubljana, Slovenia ABSTRACT in Section 5. Finally, we conclude the paper and provide ideas for In this paper, we propose a news stream clustering algorithm future work in Section 6. which directly outputs cross-lingual event clusters. It uses multi- lingual language models to generate cross-lingual article repre- 2 RELATED WORK sentations which enable a direct comparison of articles in differ- ent languages. The algorithm is evaluated using a cross-lingual News Stream Clustering. The objective of news stream cluster- news article data set and compared against a strong baseline ing is to group news articles that report about the same event algorithm. The experiment results show the algorithm has great that happened in the world. Grouping can be a difficult task, promise, but requires additional modifications for improving its especially if the articles are written in multiple languages. To performance. this end, various approaches were developed for cross-lingual event clustering. A statistical approach called Generalization of KEYWORDS Canonical Correlation Analysis is used to compare news articles in different languages [9]. Information extraction techniques, online news, event detection, news events, multilingual language such as named entity recognition and part-of-speech tagging, are model also used for event detection [6]. With the increasing popularity of neural networks, more advanced approaches are used to link 1 INTRODUCTION event clusters. The work in [3] uses word embeddings to com- pare and link monolingual event clusters into cross-lingual ones. Online news is producing hundreds of thousands of articles per Transformer-based language models are used for event sentence day reporting about any significant event that happened in the coreference identification [4], a task that links parts of articles to world. The articles cover various domains (such as politics, sports, multiple events. However, the algorithm is performed only on a and culture) and are written in different languages. In order to monolingual data set. automatically identify these events, news stream clustering algo- To the best of our knowledge, our work is the first that uses rithms are used. These usually have the following steps: (1) they multilingual language models for grouping articles directly into group articles written in the same language into monolingual cross-lingual events. clusters, and (2) form cross-lingual clusters by linking monolin- gual clusters that report on the same event. Both steps usually employ monolingual text features such as TF-IDF vectors; these Multilingual Language Models. Since the introduction of the do not allow cross-lingual comparison without using advanced transformers [11], language model development has gained trac- statistical or machine learning methods. tion in the research community. One of the most well known In this paper, we propose a news stream clustering algorithm language models, BERT [2], has improved the performance of that directly generates cross-lingual event clusters. The algorithm various NLP tasks. By training it using multilingual documents, uses multilingual language models for generating cross-lingual the multilingual BERT [5] enabled solving tasks that require content embeddings and extracting named entities found in the cross-lingual text representations. While these models improved articles. These are used to measure if an article should be assigned the performance of various NLP tasks, they do not provide good to an event. The algorithm is evaluated using a cross-lingual data document embeddings for tasks like clustering. This changed set consisting of articles in English, Spanish, and German, and is with the introduction of Sentence-BERT [8], which generates compared against a strong baseline. While the experiment results monolingual sentence embeddings appropriate for measuring look promising, there is still room for improving the algorithms sentence similarity. A year later, an approach for making mono- performance. lingual document representations cross-lingual [7] opened a way The paper is structured as follows: Section 2 contains an for using sentence embeddings for cross-lingual clustering. overview of the related work on cross-lingual news stream clus- In this work, we employ the multilingual Sentence-BERT tering and multilingual language models. Next, we present the model to generate cross-lingual embeddings used to group arti- proposed clustering algorithm in Section 3, and describe the ex- cles into events. periment setting in Section 4. The experiment results are found 3 THE CLUSTERING ALGORITHM Permission to make digital or hard copies of part or all of this work for personal We propose a news stream clustering algorithm that directly 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 outputs cross-lingual events. It uses cross-lingual embeddings, the full citation on the first page. Copyrights for third-party components of this named entities, and temporal features to measure if an article work must be honored. For all other uses, contact the owner/author(s). should be assigned to an event cluster. If none of the events are Information Society 2021, 4 - 8 October 2021, Ljubljana, Slovenia appropriate, a new cluster is created and the article is assigned © 2021 Copyright held by the owner/author(s). to it. Figure 1 shows the algorithm’s workflow diagram. 127 Information Society 2021, 4 - 8 October 2021, Ljubljana, Slovenia Erik Novak event clusters content embedding: a 6 c 1 c 2 a ® (0) 𝑐 = ® 0, 1 𝑒 a a 2 4 a a (𝑘−1) 5 3 (𝑘 − 1) · ® 𝑐 + 𝑐 ® 𝑒 𝑎 ® (𝑘) 𝑘 𝑐 = , 𝑒 𝑘 (𝑘) COND? YES where ® 𝑐 is the centroid calculated using the first 𝑘 articles 𝑒 assigned to the event 𝑒, and 𝑐 ® is the content embedding of the c 𝑎𝑘 3 𝑘 -th article 𝑎 . 𝑘 NO Event Named Entities. Each event stores all of the unique named entities that are found in any of its articles. The named entities are used to identify if the incoming article mentions the Figure 1: The algorithm’s workflow diagram. The algo- event’s entities. The event’s named entities set is updated when rithm maintains a set of event clusters which are used a new article is assigned to the event: when asessing if a new article (𝑎6) should be assigned to (0) 𝑟 = ∅, an existing event. If the conditions are met, the article is 𝑒 assigned to the most appropriate cluster ( (𝑘) (𝑘−1) 𝑐 2). Otherwise, an 𝑟 = 𝑟 ∪ 𝑟 , 𝑒 𝑒 𝑎𝑘 empty event cluster is created (𝑐3), the article is assigned to (𝑘) it, and the newly created event is added to the cluster set. where 𝑟 is the set of named entities generated using the first 𝑒 𝑘 articles assigned to the event 𝑒 , and 𝑟 is the set of named 𝑎𝑘 entities of the 𝑘-th article 𝑎 . 𝑘 In this section we describe how the algorithm represents the Time Statistics. The time statistics provide insights into the articles and events, and how it decides when to assign an article articles’ temporal distribution. These are calculated using the to the event cluster. articles’ time attribute. In this experiment we measured the fol- lowing statistics: the minimum, average, and maximum article 3.1 Article Representation timestamps. These are used to validate if an article was published In this section we describe the different article representations at a time when it could still report about an existing event. used in the algorithm. Each article is assumed to have a title, body, and time attributes, which are used to (1) generate the content 3.3 Assignment Condition embedding and (2) extract its named entities. The most crucial part of the proposed algorithm is how to mea- sure to which event should an article be assigned to, if any. We Content Embedding. Each article is assigned an embedding propose a condition that combines (1) the cosine similarity be- that represents the article’s content. Using multilingual Sentence- tween the article’s content embedding and the event’s centroid, BERT1, a language model designed for generating vectors used in (2) the overlap between the article’s and event’s named entities, cross-lingual clustering tasks, we get the content embedding by and (3) the time difference between the article’s time and one of concatenating the article’s title and body and inputing it into the the event’s time statistics. language model. The output is a single 768 dimensional vector Let 𝐸 = {𝑒 } be the set of existing event clusters, that captures the semantic meaning of the article. 1, 𝑒2, . . . , 𝑒 𝑗 where each event is represented with its centroid, named entities, Article Named Entities. For each article we extract the named and one of its time statistics 𝑒 = ® 𝑐 , 𝑟 , 𝑡 . Let the article 𝑖 𝑒 𝑒 𝑒 𝑖 𝑖 𝑖 entities that are mentioned in the article’s body. To extract them, be represented by its content embedding, named entities, and we developed a multilingual NER model using XLM-RoBERTa time attribute 𝑎 = ( ® 𝑐 , 𝑟 , 𝑡 ). We then check if the following 𝑎 𝑎 𝑎 [1] and fine-tuned it using the CoNLL-2003 [10] data set.2 Af-conditions are met for each event: terwards, we filter out the duplicates and store the remaining ⟨ ® 𝑐 , ® 𝑐 ⟩ 𝑒 𝑎 𝑖 unique entities for later use. 𝛿 = ≥ 𝛼, 𝑐 ∥ ® 𝑐 ∥ ∥ 𝑒 2 ∥ ® 𝑐𝑎 2 𝑖 (1) 𝛿 = |𝑟 ∩ 𝑟 | ≥ 𝛽, 3.2 Event Representations 𝑟 𝑒 𝑎 𝑖 𝛿 = |𝑡 − 𝑡 | ≤ 𝜏, 𝑡 𝑒 𝑎 An event is represented as an aggregate of its articles. This in- 𝑖 cludes (1) the event centroid, (2) the named entities, and (3) the where 𝛼, 𝛽 and 𝜏 are the thresholds corresponding to how similar time statistics. In this section we describe how the aggregates the article’s content must be to the event, the required amount are calculated and updated. of overlapping entities, and the time window in which an article has to be to be assigned to the event, respectively. Thus, 𝛿 , 𝛿 , 𝛿 𝑐 𝑟 𝑡 Event Centroid. The centroid represents the average content correspond to the content similarity, entity overlap, and time embedding of the articles assigned to the event. It is used to assess window conditions, respectively. if an incoming article’s content is similar enough to the event. If an event meets the conditions described in Equation 1, the Since the algorithm is intended to work on a news streams, we article is assigned to it. If multiple events are appropriate, the iteratively update the centroid with the newly assigned article’s article is assigned to the event that has the greatest 𝛿 value. 𝑐 If none are appropriate, a new empty event cluster is created, 1The model is available at https://huggingface.co/sentence-transformers/ the article is assigned to it, and the event representations are paraphrase-xlm-r-multilingual-v1. updated. 2The code of the model is available at https://github.com/ErikNovak/named-entity- To compare the impact of the conditions, we implement mul- recognition. tiple versions of the algorithm that use a different combination 128 News Stream Clustering using Multilingual Language Models Information Society 2021, 4 - 8 October 2021, Ljubljana, Slovenia of 𝛿 , 𝛿 , and 𝛿 conditions. Table 1 shows all of the algorithm 4.3 Baseline Algorithm 𝑐 𝑟 𝑡 versions compared in the experiment. The baseline algorithm used in the experiment is presented in [3]. It performs cross-lingual news stream clustering by first gen- Table 1: The list of algorithm versions. Each algorithm uses erating monolingual event clusters using TF-IDF subvectors of a different combination of conditions. words, word lemmas and named entities of the articles. After- wards, it merges monolingual into cross-lingual clusters using Algorithm condition combination cross-lingual word embeddings to represent the articles. The algo- CONTENT rithm compares two approaches when performing cross-lingual 𝛿𝑐 CONTENT + NE clustering: 𝛿 and 𝛿 𝑐 𝑟 CONTENT + TS 𝛿 and 𝛿 • Global parameter. Using a global parameter for measuring 𝑐 𝑡 CONTENT + NE + TS 𝛿 and 𝛿 and 𝛿 distances between all language articles for cross-lingual 𝑐 𝑟 𝑡 clustering decisions. • Pivot parameter. Using a pivot parameter, where the dis- 4 EXPERIMENTS tances between every other language are only compared to English, and cross-lingual clustering decisions are made We now present the experiment setting. We introduce the data set only based on this distance. and how it is prepared for the experiment. Next, we present the evaluation metrics. Finally, the baseline algorithm is described. Since the baseline algorithm was already evaluated using the cross-lingual data set we are using the the experiment, we only 4.1 Data Set report their performances from the paper. To compare the algorithm performances we use the news article 5 RESULTS data sets acquired via Event Registry and prepared by [3] for the purposes of news stream clustering. These data sets are in three In this section we present the experiment results. For all exper- different languages (English, German, and Spanish), and consist iments we fix the values 𝛽 = 1 and 𝜏 = 3 days, and evaluate of articles containing the following attributes: the algorithms using different values of 𝛼. In addition, all experi- ments use the event’s minimum time statistic when validating • Title. The title of the article. the time condition . • Text. The body of the article. 𝛿𝑡 • Lang. The language of the article. Baseline Comparison. Table 3 shows the experiment results • Date. The datetime when the article was published. of the best performing algorithm on the evaluation data set. We • Event ID. The ID of the event the article is associated with. report the best performing CONTENT + NE + TS algorithm It is used to measure the performance of the algorithms. which uses the content similarity threshold 𝛼 = 0.3. For the experiment, we merge the three data sets together to create a single cross-lingual news article data set. We extract Table 3: The algorithm performances. The best reported their content embeddings and named entities, and sort them in algorithm uses all three asssignment conditions. chronological order, i.e. from oldest to newest. Table 2 shows the data set statistics. Algorithm 𝐹1 𝑃 𝑅 Table 2: Data set statistics. For each language data set we Baseline (global) 72.7 89.8 61.0 denote the number of documents in the data set (# docs), the Baseline (pivot) 84.0 83.0 85.0 average length of the documents (avg. length), the number CONTENT + NE + TS 72.2 79.7 66.0 of event clusters (# clusters) and the average number of documents in the clusters (avg. size). While the proposed algorithm does not perform better than any of the baselines with respect to the 𝐹1 score, our algorithm Language # docs avg. length # clusters avg. size still shows promising results. Its performance is comparable to English 8,726 537 238 37 the baseline using the global parameter and also outperforms the German 2,101 450 122 17 baseline (global) recall by 5%, showing it is better at grouping Spanish 2,177 401 149 15 articles. Together 13,004 500 427 30 Condition Analysis. We have analyzed the impact the con- ditions have on the algorithm’s performance. For each algo- rithm version we run the experiments using different values 4.2 Evaluation Metrics of 𝛼 ∈ {0.3, 0.4, 0.5, 0.6, 0.7}, and measure the balanced F-score, precision, and recall, as well as the number of clusters it gener- For the evaluation we use the same metrics as [3]. Let tp be the ated. Table 4 shows the condition analysis results. By analysing number of correctly clustered-together article pairs, let fp be the the results we come to two conclusions: number of incorrectly clustered-together article pairs, and let fn Increasing 𝛼 increases precision, decreases recall, and be the number of incorrectly not-clustered-together article pairs. tp tp generates a larger number of clusters. When 𝛼 is bigger, the Then we report precision as 𝑃 = , recall as 𝑅 = , and tp+fp tp+fn content condition 𝛿 requires the articles to be more similar to 𝑐 the balanced F-score as 𝐹1 = 2 · 𝑃 ·𝑅 . While precision describes the event. This condition is met when the article’s content em- 𝑃 +𝑅 how homogenous are clusters the, recall tells us the amount of bedding is close to the event’s centroid. Since this has to hold for articles that should be together but are actually found in different all articles in the event, then the articles that have high similar- clusters. ity are clustered together, increasing the algorithm’s precision. 129 Information Society 2021, 4 - 8 October 2021, Ljubljana, Slovenia Erik Novak Table 4: The condition analysis results. The bold values REFERENCES represent the best performances on the data set. [1] Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vish- rav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Algorithm 𝛼 # clusters 𝐹1 𝑃 𝑅 Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin CONTENT 0.3 46 29.6 19.7 59.8 Stoyanov. 2020. Unsupervised cross-lingual representa- 0.4 234 51.6 46.2 58.4 tion learning at scale. In Proceedings of the 58th Annual 0.5 849 57.7 67.7 50.3 Meeting of the Association for Computational Linguistics, 0.6 1762 45.3 73.1 32.8 8440–8451. 0.7 3185 26.0 81.9 15.5 [2] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: pre-training of deep bidirectional CONTENT 0.3 279 43.7 33.3 63.8 transformers for language understanding. In Proceedings + NE 0.4 648 52.9 55.8 50.3 of the 2019 Conference of the North American Chapter of 0.5 1168 56.5 67.4 48.6 the Association for Computational Linguistics: Human Lan- 0.6 1939 45.1 73.6 32.5 guage Technologies, Volume 1 (Long and Short Papers). As- 0.7 3254 25.9 82.3 15.4 sociation for Computational Linguistics, 4171–4186. CONTENT 0.3 344 58.8 63.2 55.0 [3] Sebastião Miranda, Art¯urs Znotin,š, Shay B Cohen, and + TS 0.4 806 64.1 76.5 55.2 Guntis Barzdins. 2018. Multilingual clustering of stream- 0.5 1346 58.8 83.4 45.4 ing news. In Proceedings of the 2018 Conference on Empirical 0.6 2068 47.1 81.7 33.1 Methods in Natural Language Processing. Association for 0.7 3356 25.2 84.8 14.7 Computational Linguistics, Brussels, Belgium. [4] Faik Kerem Örs, Süveyda Yeniterzi, and Reyyan Yeniterzi. CONTENT 0.3 925 72.2 79.7 66.0 2020. Event clustering within news articles. In Proceedings + NE 0.4 1221 72.2 80.5 65.5 of the Workshop on Automated Extraction of Socio-political + TS 0.5 1554 54.0 81.9 40.2 Events from News 2020, 63–68. 0.6 2174 46.7 80.7 32.9 [5] Telmo Pires, Eva Schlinger, and Dan Garrette. 2019. How 0.7 3403 25.0 84.8 14.7 multilingual is multilingual BERT? In Proceedings of the 57th Annual Meeting of the Association for Computational However, if the Linguistics. Association for Computational Linguistics, 𝛼 is to large then the condition is too strong, thus similar articles can be split into multiple clusters, conse- 4996–5001. quently decreasing recall and increasing the number of clusters [6] Xiaoting Qu, Juan Yang, Bin Wu, and Haiming Xin. 2016. the algorithm generates. A news event detection algorithm based on key elements Algorithms with more conditions can achieve better per- recognition. In 2016 IEEE First International Conference on formance. The algorithm’s performance is increasing with added Data Science in Cyberspace (DSC). (June 2016), 394–399. conditions. While the worst performance is achieved when only [7] Nils Reimers and Iryna Gurevych. 2020. Making monolin- the content condition gual sentence embeddings multilingual using knowledge 𝛿 is used (CONTENT algorithm), the best 𝑐 is reached when all three conditions are used (CONTENT + NE + distillation. In Proceedings of the 2020 Conference on Em- TS algorithm). The most significant contribution is provided by pirical Methods in Natural Language Processing (EMNLP). the time condition Association for Computational Linguistics, 4512–4525. 𝛿 which drastically improves the 𝐹 𝑡 1 score. [8] Nils Reimers and Iryna Gurevych. 2019. Sentence-BERT: 6 CONCLUSION sentence embeddings using Siamese BERT-Networks. In Proceedings of the 2019 Conference on Empirical Methods We propose a news stream clustering algorithm that directly in Natural Language Processing and the 9th International generates cross-lingual event clusters. It uses multilingual lan- Joint Conference on Natural Language Processing (EMNLP- guage models to generate cross-lingual article representations IJCNLP). Association for Computational Linguistics, 3982– which are used to compare with and generate cross-lingual event 3992. clusters. The algorithm was evaluated on a news article data set [9] Jan Rupnik, Andrej Muhic, Gregor Leban, Primoz Skraba, and compared to a strong baseline. The experiment results look Blaz Fortuna, and Marko Grobelnik. 2016. News across promising, but there is still room for improvement. languages - Cross-Lingual document similarity and event In the future, we intend to modify the assignment condition tracking. en. J. Artif. Intell. Res., 55, (January 2016), 283– and learn the condition parameters instead of manually setting 316. them. Modifying the language models to accept longer inputs [10] Erik F. Tjong Kim Sang and Fien De Meulder. 2003. In- could better capture the articles semantic meaning. In addition, troduction to the CoNLL-2003 shared task: language-in- events from different domains are reported with different rates. dependent named entity recognition. In Proceedings of Learning these rates and including them in the algorithm could the Seventh Conference on Natural Language Learning at improve its performance. HLT-NAACL 2003, 142–147. ACKNOWLEDGMENTS [11] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszko- reit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia This work was supported by the Slovenian Research Agency and Polosukhin. 2017. Attention is all you need. In Proceedings the Humane AI Net European Unions Horizon 2020 project under of the 31st International Conference on Neural Information grant agreement No 952026. Processing Systems. Curran Associates Inc., Red Hook, NY, USA, 6000–6010. 130 SloBERTa: Slovene monolingual large pretrained masked language model Matej Ulčar and Marko Robnik-Šikonja University of Ljubljana, Faculty of Computer and Information Science Ljubljana, Slovenia {matej.ulcar, marko.robnik}@fri.uni- lj.si ABSTRACT Successful transformer models typically contain more than 100 million parameters. To train, they require considerable com- Large pretrained language models, based on the transformer putational resources and large training corpora. Luckily, many of architecture, show excellent results in solving many natural lan- these models are publicly released. Their fine-tuning is much less guage processing tasks. The research is mostly focused on Eng- computationally demanding and is accessible to users with mod- lish language; however, many monolingual models for other lan- est computational resources. In this work, we present the training guages have recently been trained. We trained first such mono- of a Slovene transformer-based masked language model, named lingual model for Slovene, based on the RoBERTa model. We SloBERTa, based on a variant of BERT architecture. SloBERTa is evaluated the newly trained SloBERTa model on several classi- the first such publicly released model, trained exclusively on the fication tasks. The results show an improvement over existing Slovene language corpora. multilingual and monolingual models and present current state- of-the-art for Slovene. 2 RELATED WORK KEYWORDS Following the success of the BERT model [5], many transformer- natural language processing, BERT, RoBERTa, transformers, lan- based language models have been released, e.g., RoBERTa [14], guage model GPT-3 [3], and T5 [28]. The complexity of these models has been constantly increasing. The size of newer generations of the models has made training computationally prohibitive for all 1 INTRODUCTION research organizations and is only available to large corporations. Solving natural language processing (NLP) tasks with neural Training also requires huge amounts of training data, which do networks requires presentation of text in a numerical vector not exist for most languages. Thus, most of these large models format, called word embeddings. Embeddings assign each word have been trained only for a few very well-resourced languages, its own vector in a vector space so that similar words have similar chiefly English, or in a massively multilingual fashion. vectors, and certain relationships between word meanings are The BERT model was pre-trained on two tasks simultaneously, expressed in the vector space as distances and directions. Typical a masked token prediction and next sentence prediction. For the static word embedding models are word2vec [19], GloVe [24], and masked token prediction, 15% of tokens in the training corpus fastText [1]. ELMo [25] embeddings are an example of dynamic, were randomly masked before training. The training dataset was contextual word embeddings. Unlike static word embeddings, augmented by duplicating the training corpus a few times, with where a word gets a fixed vector, contextual embeddings ascribe each copy having different randomly selected tokens masked. The a different word vector for each occurrence of a word, based on next sentence prediction task attempts to predict if two given its context. sentences appear in a natural order. State of-the-art text representations are currently based on the The RoBERTa [14] model uses the same architecture as BERT, transformer architecture [35]. GPT-2 [27] and BERT [5] models but drops the next sentence prediction task, as it was shown that it are among the first and most influential transformer models. Due does not contribute to the model performance. The masked token to their ability to be successfully adapted to a wide range of prediction task was changed so that the tokens are randomly tasks, such models are, somewhat impetuously, called foundation masked on the fly, i.e. a different subset of tokens is masked in models [2, 17]. While GPT-2 uses the transformer’s decoder stack each training epoch. to model the next word based on previous words, BERT uses Both BERT and RoBERTa were released in different sizes. Base the encoder stack to encode word representations of a masked models use 12 hidden transformer layers of size 768. Large models word, based on the surrounding context before and after the use 24 hidden transformer layers of size 1024. Smaller-sized BERT word. Previous embedding models (e.g., ELMo and fastText) were models exist using knowledge distillation from pre-trained larger used to extract word representations which were then used to models [11]. train a model on a specific task. In contrast to that, transformer A few massively multilingual models were trained on 100 models are typically fine-tuned for each individual downstream or more languages simultaneously. Notable released variants task, without extracting word vectors. are multilingual BERT (mBERT) [5] and XLM-RoBERTa (XLM- R) [4]. While multilingual BERT models perform well for the trained languages, they lag behind the monolingual models [36, Permission to make digital or hard copies of part or all of this work for personal 33]. Examples of recently released monolingual BERT models for or classroom use is granted without fee provided that copies are not made or various languages are Finnish [36], Swedish [16], Estonian [30], 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 Latvian [37], etc. work must be honored. For all other uses, contact the owner /author(s). The Slovene language is supported by the aforementioned Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia massively multilingual models and by the trilingual CroSloEngual © 2021 Copyright held by the owner/author(s). BERT model [33], which has been trained on three languages, 131 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ulčar and Robnik-Šikonja Croatian, Slovene, and English. No monolingual transformer 98 epochs) on the Slovene corpora, described in Section 3.1. The model for Slovene has been previously released. model supports the maximum input sequence length of 512 sub- word tokens. 3 SLOBERTA SloBERTa was trained as a masked language model, using The presented SloBERTa model is closely related to the French fairseq toolkit [22]. 15% of the input tokens were randomly Camembert model [18], which uses the same architecture and masked, and the task was to predict the masked tokens. We training approach as the RoBERTa base model [14], but uses a used the whole-word masking, meaning that if a word was split different tokenization model. In this section, we describe the into more subtokens and one of them was masked, all the other training datasets, the architecture, and the training procedure of subtokens pertaining to that word were masked as well. Tokens SloBERTa. were masked dynamically, i.e. in each epoch, a different subset of tokens were randomly selected to be masked. 3.1 Datasets Training a successful transformer language model requires a large 4 EVALUATION dataset. We combined five large Slovene corpora in our training We evaluated SloBERTa on five tasks: named-entity recognition dataset. Gigafida 2.0 [13] is a general language corpus, composed (NER), part-of-speech tagging (POS), dependency parsing (DP), of fiction and non-fiction books, newspapers, school textbooks, sentiment analysis (SA), and word analogy (WA). We used the texts from the internet, etc. The Janes corpus [9] is composed of labeled ssj500k corpus [12, 6] for fine-tuning SloBERTa on each several subcorpora. Each subcorpus contains texts from a certain of the NER, POS and DP tasks. For NER, we limited the scope to social medium or a group of similar media, including Twitter, three types of named entities (person, location, and organization). blog posts, forum conversations, comments under articles on We report the results as a macro-average 𝐹 score of these three 1 news sites, etc. We used all Janes subcorpora, except Janes-tweet, classes. For POS-tagging, we used UPOS tags, the results are since the contents of that subcorpus are encoded and need to be reported as a micro-average 𝐹 score. For DP, we report the 1 individually downloaded from Twitter, which is a lengthy process, results as a labeled attachement score (LAS). The SA classifier as Twitter limits the access speed. KAS (Corpus of Academic was fine-tuned on a dataset composed of Slovenian tweets [20, Slovene) [8] consists of PhD, MSc, MA, Bsc, and BA theses written 21], labeled as either "positive", "negative", or "neutral". We report in Slovene between 2000 and 2018. SiParl [23] contains minutes the results as a macro-average 𝐹 score. 1 of Slovene national assembly between 1990 and 2018. SlWaC [15] Traditional WA task measures the distance between word vec- is a web corpus collected from the .si top-level web domain. All tors in a given analogy (e.g., man : king ≈ woman : queen). For corpora used are listed in Table 1 along with their sizes. contextual embeddings such as BERT, the task has to be modified Table 1: Corpora used in training of SloBERTa with their to make sense. First, word embeddings from transformers are sizes in billion of tokens and words. Janes* corpus does generally not used on their own, rather the model is fine-tuned. not include Janes-tweet subcorpus. Four words from an analogy also do not provide enough con- text for use with transformers. In our modification, we input the four words of an analogy in a boilerplate sentence "If the word Corpus Genre Tokens Words [word1] corresponds to the word [word2], then the word [word3] Gigafida 2.0 general language 1.33 1.11 corresponds to the word [word4]." We then masked [word2] and Janes* social media 0.10 0.08 attempted to predict it using masked token prediction. We used KAS academic 1.70 1.33 Slovene part of the multilingual culture-independent word anal- siParl 2.0 parliamentary 0.24 0.20 ogy dataset [32]. We report the results as an average precision@5 slWaC 2.1 web crawl 0.90 0.75 (the proportion of the correct [word2] analogy words among the Total 4.27 3.47 5 most probable predictions). Total after deduplication 4.20 3.41 We compared the performance of SloBERTa with three other transformer models supporting Slovene, CroSloEngual BERT (CSE-BERT) [33], multilingual BERT (mBERT) [5], and XLM- 3.2 Data preprocessing RoBERTa (XLM-R) [4]. Where sensible, we also included the results achieved with training a classifier model using Slovene We deduplicated the corpora, using the Onion tool [26]. We split ELMo [31] and fastText embeddings. the deduplicated corpora into three sets, training (99%), validation We fine-tuned the transformer models on each task by adding (0.5%), and test (0.5%). Independently of the three splits, we pre- a classification head on top of the model. The exception is the DP pared a smaller dataset, one 15th of the size of the whole dataset, task, where we used the modified dep2label-bert tool [29, 10]. For by randomly sampling the sentences. We used this smaller dataset ELMo and fastText, we extracted embeddings from the training 1 to train a sentencepiece model , which is used to tokenize and datasets and used them to train token-level and sentence-level encode the text into subword byte-pair-encodings (BPE). The classifiers for each task, except for the DP. The classifiers are sentencepiece model trained for SloBERTa has a vocabulary con- composed of a few LSTM layer neural networks. For the DP taining 32,000 subword tokens. task, we used the modified SuPar tool, based on the deep biaffine 3.3 Architecture and training attention [7]. The details of the evaluation process are presented in [34]. SloBERTa has 12 transformer layers, which is equivalent in size The results are shown in Table 2. The results of ELMo and to BERT-base and RoBERTa-base models. The size of each trans- fastText, while comparable between each other, are not fully com- former layer is 768. We trained the model for 200,000 steps (about parable with the results of transformer models as the classifier 1 https://github.com/google/sentencepiece training approach is different. 132 SloBERTa Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 2: Results of Slovene transformer models. 2020 research and innovation programme under grant agreement No 825153, project EMBEDDIA (Cross-Lingual Embeddings for Model NER POS DP SA WA Less-Represented Languages in European News Media). fastText 0.478 0.527 / 0.435 / REFERENCES ELMo 0.849 0.966 0.914 0.510 / [1] Piotr Bojanowski, Edouard Grave, Armand Joulin, and mBERT 0.885 0.984 0.681 0.576 0.061 Tomas Mikolov. 2017. Enriching word vectors with sub- XLM-R 0.912 0.988 0.793 0.604 0.146 word information. Transactions of the Association for Com- CSE-BERT 0.928 0.990 0.854 0.610 0.195 putational Linguistics, 5, 135–146. SloBERTa 0.933 0.991 0.844 0.623 0.405 [2] Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Alt- man, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. On the NER, POS, SA, and WA tasks, SloBERTa outperforms all 2021. On the opportunities and risks of foundation models. other models/embeddings. For the POS-tagging, the differences ArXiv preprint 2108.07258. (2021). between the models are small, except for fastText, which performs [3] Tom Brown et al. 2020. Language models are few-shot much worse. ELMo, surprisingly, outperforms all transformer learners. In Advances in Neural Information Processing Sys- models on the DP task. However, it performs worse on the other tems. Volume 33, 1877–1901. tasks. SloBERTa performs worse than CSE-BERT on the DP task, [4] Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav but beats other multilingual models. Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard The success of ELMo on the DP task can be partially explained Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. by the different tools used for training the classifiers. Further 2019. Unsupervised cross-lingual representation learning work needs to be done to fully evaluate the difference and success at scale. arXiv preprint arXiv:1911.02116. of ELMo embeddings on this task. [5] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina The performance on the SA task is limited by the low inter- Toutanova. 2019. BERT: pre-training of deep bidirectional annotator agreement [20]. The reported average of 𝐹 scores for 1 transformers for language understanding. In Proceedings positive and negative class is 0.542 for inter-annotator agreement of the 2019 Conference of the North American Chapter of and 0.726 for self-agreement. Using the same measure (average of the Association for Computational Linguistics: Human Lan- 𝐹 for positive and for negative class), SloBERTa scores 0 1 𝐹1 .667, guage Technologies, Volume 1 (Long and Short Papers), 4171– and mBERT scores 0.593. 4186. doi: 10.18653/v1/N19- 1423. On the WA task, most models perform poorly. This is expected [6] Kaja Dobrovoljc, Tomaž Erjavec, and Simon Krek. 2017. because very little context was provided on the input, and the The universal dependencies treebank for Slovenian. In transformer models need a context to perform well. SloBERTa Proceeding of the 6th Workshop on Balto-Slavic Natural significantly outperforms other models, not only because it was Language Processing (BSNLP 2017). trained only on Slovene data, but largely because its tokenizer [7] Timothy Dozat and Christopher D. Manning. 2017. Deep is adapted to only Slovene language and does not need to cover biaffine attention for neural dependency parsing. In Pro- other languages. ceedings of 5th International Conference on Learning Repre- 5 CONCLUSIONS sentations, ICLR. [8] Tomaž Erjavec, Darja Fišer, and Nikola Ljubešić. 2021. We present SloBERTa, the first monolingual transformer-based The KAS corpus of Slovenian academic writing. Language masked language model trained on Slovene texts. We show that Resources and Evaluation, 55, 2, 551–583. SloBERTa large pretrained masked language model outperforms [9] Darja Fišer, Tomaž Erjavec, and Nikola Ljubešić. 2016. existing comparable multilingual models supporting Slovene on Janes v0. 4: korpus slovenskih spletnih uporabniških vse- four tasks, NER, POS-tagging, sentiment analysis, and word anal- bin. Slovenščina 2.0: empirical, applied and interdisciplinary ogy. The performance on the DP task is competitive, but lags research, 4, 2, 67–99. behind some of the existing models. [10] Carlos Gómez-Rodríguez, Michalina Strzyz, and David In further work we intend to compare improvement of BERT- Vilares. 2020. A unifying theory of transition-based and like monolingual models over multilingual models for other lan- sequence labeling parsing. In Proceedings of the 28th Inter- guages. national Conference on Computational Linguistics, 3776– The pre-trained SloBERTa model is publicly available via CLA- 3793. doi: 10.18653/v1/2020.coling- main.336. 2 3 RIN.SI and Huggingface repositories. We make the code, used [11] Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao for preprocessing the corpora and training the SloBERTa, publicly Chen, Linlin Li, Fang Wang, and Qun Liu. 2020. Tiny- 4 available . BERT: Distilling BERT for natural language understanding. ACKNOWLEDGMENTS (2020). arXiv: 1909.10351 [cs.CL]. [12] Simon Krek, Kaja Dobrovoljc, Tomaž Erjavec, Sara Može, The work was partially supported by the Slovenian Research Nina Ledinek, Nanika Holz, Katja Zupan, Polona Gantar, Agency (ARRS) core research programmes P6-0411 and project Taja Kuzman, Jaka Čibej, Špela Arhar Holdt, Teja Kavčič, J6-2581, as well as the Ministry of Culture of Republic of Slovenia Iza Škrjanec, Dafne Marko, Lucija Jezeršek, and Anja Zajc. through project Development of Slovene in Digital Environment 2019. Training corpus ssj500k 2.2. Slovenian language re- (RSDO). This paper is supported by European Union’s Horizon source repository CLARIN.SI. (2019). 2 http://hdl.handle.net/11356/1397 3 https://huggingface.co/EMBEDDIA/sloberta 4 https://github.com/clarinsi/Slovene-BERT-Tool 133 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ulčar and Robnik-Šikonja [13] Simon Krek, Tomaž Erjavec, Andraž Repar, Jaka Čibej, [28] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Spela Arhar, Polona Gantar, Iztok Kosem, Marko Rob- Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and nik, Nikola Ljubešić, Kaja Dobrovoljc, Cyprian Laskowski, Peter J Liu. 2020. Exploring the limits of transfer learning Miha Grčar, Peter Holozan, Simon Šuster, Vojko Gorjanc, with a unified text-to-text transformer. Journal of Machine Marko Stabej, and Nataša Logar. 2019. Gigafida 2.0: Korpus Learning Research, 21, 1–67. pisne standardne slovenščine. viri.cjvt.si/gigafida. (2019). [29] Michalina Strzyz, David Vilares, and Carlos Gómez-Rodrí- [14] Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar guez. 2019. Viable dependency parsing as sequence la- Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettle- beling. In Proceedings of the 2019 Conference of the North moyer, and Veselin Stoyanov. 2019. RoBERTa: A robustly American Chapter of the Association for Computational Lin- optimized BERT pretraining approach. ArXiv preprint guistics: Human Language Technologies, Volume 1 (Long 1907.11692. (2019). and Short Papers), 717–723. doi: 10.18653/v1/N19-1077. [15] Nikola Ljubešić and Tomaž Erjavec. 2011. hrWaC and [30] Hasan Tanvir, Claudia Kittask, and Kairit Sirts. 2020. Est- slWaC: Compiling web corpora for Croatian and Slovene. BERT: A pretrained language-specific BERT for Estonian. In International Conference on Text, Speech and Dialogue. arXiv preprint 2011.04784. (2020). Springer, 395–402. [31] Matej Ulčar and Marko Robnik-Šikonja. 2020. High quality [16] Martin Malmsten, Love Börjeson, and Chris Haffenden. ELMo embeddings for seven less-resourced languages. In 2020. Playing with Words at the National Library of Swe- Proceedings of the 12th Language Resources and Evaluation den – Making a Swedish BERT. ArXiv preprint 2007.01658. Conference, LREC 2020, 4733–4740. (2020). [32] Matej Ulčar, Kristiina Vaik, Jessica Lindström, Milda Daili- [17] Gary Marcus and Ernest Davis. 2021. Has AI found a new d ˙ enait ˙ e, and Marko Robnik-Šikonja. 2020. Multilingual foundation? The Gradient. 11 September 2021. culture-independent word analogy datasets. In Proceedings [18] Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, of the 12th Language Resources and Evaluation Conference, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé 4067–4073. Seddah, and Benoît Sagot. 2020. CamemBERT: A tasty [33] Matej Ulčar and Marko Robnik-Šikonja. 2020. FinEst BERT French language model. In Proceedings of the 58th Annual and CroSloEngual BERT: less is more in multilingual mod- Meeting of the Association for Computational Linguistics, els. In Proceedings of Text, Speech, and Dialogue, TSD 2020, 7203–7219. 104–111. [19] Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. [34] Matej Ulčar, Aleš Žagar, Carlos S. Armendariz, Andraž 2013. Efficient estimation of word representations in vector Repar, Senja Pollak, Matthew Purver, and Marko Robnik- space. arXiv preprint 1301.3781. Šikonja. 2021. Evaluation of contextual embeddings on [20] Igor Mozetič, Miha Grčar, and Jasmina Smailović. 2016. less-resourced languages. ArXiv preprint 2107.10614. (2021). Multilingual Twitter sentiment classification: the role of [35] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszko- human annotators. PLOS ONE, 11, 5. reit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia [21] Igor Mozetič, Miha Grčar, and Jasmina Smailović. 2016. Polosukhin. 2017. Attention is all you need. In Advances Twitter sentiment for 15 european languages. Slovenian in neural information processing systems, 5998–6008. language resource repository CLARIN.SI. (2016). http:// [36] Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, hdl.handle.net/11356/1054. Juhani Luotolahti, Tapio Salakoski, Filip Ginter, and Sampo [22] Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Pyysalo. 2019. Multilingual is not enough: BERT for Finnish. Gross, Nathan Ng, David Grangier, and Michael Auli. 2019. arXiv preprint arXiv:1912.07076. (2019). Fairseq: a fast, extensible toolkit for sequence modeling. [37] Art ¯ urs Znotinš and Guntis Barzdinš. 2020. LVBERT: Trans- , , In Proceedings of NAACL-HLT 2019: Demonstrations. former-based model for Latvian language understanding. [23] Andrej Pančur and Tomaž Erjavec. 2020. The siParl corpus In Human Language Technologies–The Baltic Perspective: of Slovene parliamentary proceedings. In Proceedings of Proceedings of the Ninth International Conference Baltic the Second ParlaCLARIN Workshop, 28–34. HLT 2020. Volume 328, 111. [24] Jeffrey Pennington, Richard Socher, and Christopher Man- ning. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing EMNLP, 1532–1543. [25] Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gard- ner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018. Deep contextualized word representations. In Pro- ceedings of the 2018 Conference of the North American Chap- ter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2227–2237. doi: 10.18653/v1/N18- 1202. [26] Jan Pomikálek. 2011. Removing boilerplate and duplicate content from web corpora. PhD thesis. Masaryk university, Brno, Czech Republic. [27] Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019. Language models are unsupervised multitask learners. OpenAI blog. 2019 Feb 24. (2019). 134 Understanding the Impact of Geographical Bias on News Sentiment: A Case Study on London and Rio Olympics Swati Dunja Mladenić swati@ijs.si dunja.mladenic@ijs.si Jožef Stefan Institute, Jožef Stefan Institute, Jožef Stefan International Postgraduate School Jožef Stefan International Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia News article on London Olympic Legacy News articles on Rio Olympic Legacy Headline: Five Years On, Headline: Rio 2016's London's Olympic Real Estate venues abandoned and Headline: Rio 2016: An Legacy Is A Clear Winner vandalised in worrying legacy Olympics legacy of despair Category: Business Category: Business Headline: Rio de Janeiro and wreckage suffering painful post-Olympic Category: Business Summary: The Olympics have Summary: Rio de Janeiro hangover become famously bad for real pulled off last year's Olympics, Category: Sports Summary: When any country estate… keeping crime… hosts a major sporting event, Summary: The Brazilian the organisers and those... Sentiment: 0.067 Sentiment: -0.372 metropolis of Rio de Janeiro was the epicenter of the… Sentiment: -0.435 Article Similarity: 0.509, Sentiment Dissimilarity: 0.439 Sentiment: -0.388 Article Similarity: 0.632, Sentiment Dissimilarity: 0.502 Article Similarity: 0.503, Sentiment Dissimilarity: 0.455 Figure 1: An example to illustrate the impact of geographical location on the sentiment of similar news articles. ABSTRACT to induce a variety of political and social implications, both direct There are various types of news bias, most of which play an and indirect. For instance, any political controversy presented important role in manipulating public perceptions of any event. from a specific perspective may alter the voting pattern [4, 1, 6]. Researchers frequently question the role of geographical location There are different forms of news bias, and geographical bias in attributing such biases. To that end, we intend to investigate the is one of them. It exists if the sentiment polarity of similar arti- impact of geographical bias on news sentiments in related articles. cles published in different geographical location is contradictory As our case study, we use news articles collected from the Event or varies significantly. Sentiment analysis methods, which are Registry over two years about the Olympic legacy in London commonly used to determine news bias [3, 14], can be used to and Rio. Our experimental analysis reveals that geographical examine the shift in sentiment polarity in similar news articles. boundaries do have an impact on news sentiment. Now, an intriguing question arises: Is geographical bias a factor affecting news sentiment? This study seeks to answer the above KEYWORDS question by identifying and comparing sentiments of similar news articles. In doing so, we demonstrate how geographical Bias, News Bias, Geographical Bias, Olympics, Semantic Similar- location impacts the sentiments of similar articles. We also inves- ity, Sentiment Analysis, Dataset tigate this impact in relation to several news categories such as politics, business, sports, and so on. 1 INTRODUCTION The Olympic Games are a symbol of the greatest sports events Claims of bias in news coverage raise questions about the role of in the world. Every edition leaves a number of legacies for the geography in shaping public perceptions of similar events. Based Olympic Movement, as well as unforgettable memories for each on the geographical location, multiple factors, such as political host city, whether positive or negative. In this regard, we select affiliation, editorial independence, etc., can influence the way news articles about the Olympic legacy in London and Rio as a news articles are generated. Although it is well known that biased case study for our analysis. news can have more influence on people’s thinking and decision- We use Event Registry1 [10] to collect English news articles, making processes [7, 9], it is nearly impossible to produce an along with their sentiment and categories, published between article without any bias. Biased news articles have the potential January 2017 and December 2020. We use the popular Sentence- BERT (SBERT) [12] embedding to represent the articles and then 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 compute the cosine similarity between them to identify similar distributed for profit or commercial advantage and that copies bear this notice and article pairs. the full citation on the first page. Copyrights for third-party components of this Our data and code can be found in the GitHub repository at work must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4 October 2021, Ljubljana, Slovenia https:// github.com/ Swati17293/ geographical-bias. © 2021 Copyright held by the owner/author(s). 1https://eventregistry.org 135 Information Society 2021, 4 October 2021, Ljubljana, Slovenia Swati and Dunja Mladenić 1.1 Contributions in London/Rio if the headline and/or summary of the article The paper’s contributions are as follows: contains the keywords ‘London’/‘Rio’, ‘Olympic’, and ‘Legacy’. For each article, we then extract the summary, category, and • We propose a task of analyzing the impact of geographical sentiment. The article summaries vary in length from 290 to 6,553 bias on the sentiment of news articles with data on the words. Sentiment scores ranges from −1 to 1. We select seven Olympic legacies of Rio and London as a case study. major news categories, namely business, politics, technology, • We present a dataset of English news articles customized environment, health, sports, and arts-and-entertainment, and to the above-mentioned task. remove the rest of the categories. After excluding the duplicate • We present experimental results to demonstrate the afore- articles we end up with 8,690 and 5,120 articles about the Olympic mentioned impact of geographical bias. legacy in London and Rio respectively. 2 RELATED WORK 4 MATERIALS AND METHODS The Majority of the sentiment analysis methods for news bias analysis depend on the sentiment words that are explicitly stated. 4.1 Methodology SentiWordNet2, which is a publicly available lexical resource used The primary task is to compute the average difference in senti- by the researchers for opinion mining to identify the sentiment ment scores between similar news articles about the Olympic inducing words that classify them as positive, negative, or neutral. legacies in Rio and London. The stated task can be subdivided Melo et al. [5] collected and analyzed articles from Brazil’s and mathematically formulated as follows: news media and social media to understand the country’s re- (1) Generate two distinct sets of news articles 𝐴1 and 𝐴2, one sponse to the COVID-19 pandemic. They proposed using an about the London Olympic legacy and the other about the enhanced topic model and sentiment analysis method to tackle Rio Olympic legacy. For each ′ 𝑎 ∈ 𝐴 ∈ 𝐴 𝑖 1 find a list of 𝑎 2, 𝑗 this task. They identified and applied the main themes under con- where 𝑡 ℎ 𝑎 is the 𝑖 article in set 𝐴 , 𝑠 )} 𝑖 1 = {(𝑎1, 𝑠1), (𝑎2, 𝑠2)...(𝑎𝑛 𝑛 sideration in order to comprehend how their sentiments changed and ′ 𝑡 ℎ ′ ′ ′ ′ ′ ′ 𝑎 is the 𝑗 article in set 𝐴2 = {(𝑎 , 𝑠 ), (𝑎 , 𝑠 )...(𝑎 , 𝑠 )} over time. They discovered that certain elements in both media 𝑗 1 1 2 2 𝑚 𝑚 which is the closest match (c.f. Section 4.1.1) to 𝑎 . Here, reflected negative attitudes toward political issues. 𝑖 𝑛 = |𝐴 Quijote et al. [11] used SentiWordNet along with the Inverse 1 | and 𝑚 = |𝐴2 |. (2) For each list, calculate 𝐷 to represents the difference Reinforcement Model to analyze the bias present in the news ar- 𝑖 𝑗 between the sentiment scores ′ 𝑠 and 𝑠 of the articles 𝑎 ticle and to determine whether the outlets are biased or not. The 𝑖 𝑖 𝑗 ′ lexicons were first scored for the experiments using SentiWord- and 𝑎 . 𝑗 Net and then fed to the Inverse Reinforcement model as input. (3) Calculate the average difference 𝐷 of sentiment scores. To determine the news bias, the model measured the deviation (4) Calculate the percentage of similar article pairs with re- and controversy scores of the articles. The findings lead to the versed polarity and those with unchanged polarity. inference that articles from major news outlets in the Philippines The secondary task is to assess the primary task with respect are not biased, excluding those from the Manila Times. to news categories, i.e. to calculate the average difference 𝐷 of Bharathi and Geetha [3] classified the articles published by sentiment scores for similar articles in each category. the UK, US, and India median as positive, negative, or neutral In the following subsections, we discuss the tasks mentioned using the content sentiment algorithm [2]. The sentiment scores above in greater detail. of the opinion words and their polarities were used as input to 4.1.1 Article Similarity. We embed the articles in sets 𝐴1 and 𝐴2 the algorithm. to construct sets ′ ′ ′ 𝐹1 = {𝑓1, 𝑓2...𝑓 } and 𝐹 , 𝑓 ... 𝑓 }. While 𝑚 2 = {𝑓 Existing research investigates news bias using sentiment anal- 1 2 𝑛 alternative embedding approaches can be utilized, in this study ysis methods, but, unlike our work, it does not provide a suitable we select the popular Sentence-BERT (SBERT) [12] embedding automated method for analyzing the impact of geographical bias to extract 768-dimensional feature vectors to represent the indi- on news sentiment. vidual articles in 𝐹1 and 𝐹2. For each article in 3 DATA DESCRIPTION 𝑎 𝐴 𝑖 1, we compute the similarity score3 between 𝑎 and every article 𝑎 in 𝐴 𝑖 𝑗 2 using the cosine similarity 3.1 Raw Data Source metric 𝑐𝑜𝑠 ′ ′ 𝑆𝑖𝑚 (𝑎 , 𝑎 ) (Eq 1). We consider articles 𝑎 and 𝑎 to be 𝑖 𝑖 𝑗 𝑗 We use Event Registry [10] as our raw data source which mon- similar only if their similarity score is greater than 0.5. itors, gathers, and delivers news articles from all around the ′ 𝑓 · 𝑓 world. It also annotates articles with numerous metadata such as 𝑖 𝑗 𝑐𝑜𝑠 ′ 𝑆𝑖𝑚 (𝑎 , 𝑎 ) = (1) 𝑖 a unique identifier for article identification, categories to which 𝑗 || ′ 𝑓 | | | | 𝑓 || 𝑖 𝑗 it may belong, geographical location, sentiment, and so on. Its where ′ 𝑓 and 𝑓 represents the embedded feature vectors of article 𝑖 𝑗 large-scale coverage can therefore be used effectively to assess ′ 𝑎 and 𝑎 . 𝑖 the impact of geographical bias on news sentiment. 𝑗 The similarity score ranges from −1 to 1, where −1 indicates 3.2 Dataset that the articles are completely unrelated and 1 indicates that they are identical, and in-between scores indicate partial similarity or To generate our dataset, we use a similar data collection process dissimilarity. as described in [13]. Using the Event Registry API, we collect all English-language news articles about the Olympic legacy in 4.1.2 Average Sentiment Dissimilarity. For every pair of similar ′ London and Rio published between January 2017 and December articles 𝑎 and 𝑎 , we calculate the difference 𝐷 between their 𝑖 𝑖 𝑗 𝑗 ′ 2020. We consider an article to be about the Olympic Legacy sentiment scores 𝑠 and 𝑠 . To calculate the average sentiment 𝑖 𝑗 2http://sentiwordnet.isti.cnr.it/ 3https://en.wikipedia.org/wiki/Cosine_similarity 136 Understanding the Impact of Geographical Bias on News Sentiment Information Society 2021, 4 October 2021, Ljubljana, Slovenia Table 1: Category-wise confusion matrix to show the percentage of similar article pairs with respect to their sentiment polarity. Sports Business Politics Environment Health Technology Arts & Entertainment Pos Neg Pos Neg Pos Neg Pos Neg Pos Neg Pos Neg Pos Neg Pos 77 10 62 28 42 18 55 18 29 12 87 4 59 16 Neg 11 2 7 4 23 16 14 12 12 46 1 0 7 18 Table 2: Confusion matrix to show the percentage of sim- ilar article pairs with respect to their sentiment polarity. Positive Negative Positive 69 15 Negative 11 4 Table 3: Distribution of average sentiment difference across news categories for similar article pairs with iden- tical category. Figure 2: Distribution of average sentiment differences News category Average Sentiment Difference across categories for similar articles in the same category. Sports 0.19 Business 0.20 Politics 0.18 Health 0.16 Environment 0.22 Technology 0.14 Arts and Entertainment 0.19 dissimilarity score 𝐷, we add all 𝐷 and divide it by the total 𝑖 𝑗 number of similar article pairs. 5 RESULTS AND ANALYSIS Figure 3: An illustration of the effect of category on senti- In our experiments, we compare 44,492,800 possible article pairs ment polarity. for similarity and discover 375,008 similar pairs. The comparison in terms of sentiment similarity reveals that if two articles from different geographical regions are similar, in our case Rio and The categorical distribution of the percentage of similar article London, the average difference in their sentiment scores is 0.171. pairs in terms of sentiment polarity is shown in Table 1. ‘Politics’ In addition, as defined in Table 2, we calculate the percentage of has the highest percentage of articles with reversed polarity, similar article pairs based on their sentiment polarity. It’s worth while ‘technology’ has the lowest. Categories such as ‘business’ noting that the polarity of the article is completely reversed and ‘entertainment’, though not as clearly as ‘politics’, exhibit the 27% of the time, indicating the impact of geographic region on same bias. sentiments. This disparity arises from the fact that, in contrast to other cat- It is because the success of mega-events such as the Olympics egories, politics is most influenced by geographical boundaries, in a particular host city is heavily influenced by its residents’ trust whereas science and technology are typically location indepen- and support for the government [8]. It can be viewed positively as dent. Since politics has such a large influence on shaping beliefs a national event with social and economic benefits, or negatively and public perceptions, it is frequently twisted to fit a particu- as a source of money waste. While the Olympics have left an lar narrative of a story. It is inherently linked to geographical economic and social legacy in London, a series of structural borders, and it can be extremely polarizing depending on the investment demands in Rio raise the question of whether or not geographical region. the Olympics was worthwhile for the entire country. 6 CONCLUSIONS AND FUTURE WORK 5.1 Impact of news categories In this work, we use news articles about the Olympic Legacy in The impact of news categories on the sentiments of similar arti- London and Rio as a case study to understand how geographical cles with identical categories from different geographical regions boundaries interplay with news sentiments. is shown in Table 3. It demonstrates that certain news categories We begin by presenting a dataset of news articles collected have a greater impact than others. Figure 2 depicts this distinction over two years using the Event Registry API. We compute the more clearly. cosine similarity scores of all possible embedded article pairs, one 137 Information Society 2021, 4 October 2021, Ljubljana, Slovenia Swati and Dunja Mladenić from each set of Olympic legacy articles (London and Rio). We algorithm. Indonesian Journal of Electrical Engineering and use the popular Sentence-BERT for article embedding and then Computer Science, 16, 2, 882–889. compute the sentiment difference between similar article pairs. [4] Chun-Fang Chiang and Brian Knight. 2011. Media bias From 44,492,800 possible article pairs we end up with 375,008 and influence: evidence from newspaper endorsements. similar pairs. The Review of economic studies, 78, 3, 795–820. In our analysis, we discovered that the sentiment reflected [5] Tiago de Melo and Carlos MS Figueiredo. 2021. Comparing in similar articles from different geographical regions differed news articles and tweets about covid-19 in brazil: senti- significantly. We also investigate this difference in relation to ment analysis and topic modeling approach. JMIR Public different news categories such as politics, business, sports, and Health and Surveillance, 7, 2, e24585. so on. We find a significant difference in news sentiment across [6] Claes H De Vreese. 2005. News framing: theory and typol- geographical boundaries when it comes to political news, while ogy. Information Design Journal & Document Design, 13, in the case of news in technology, the difference is much smaller. 1. We find that articles in categories such as politics and business [7] John Duggan and Cesar Martinelli. 2011. A spatial theory can be heavily influenced by geographical location, articles in of media slant and voter choice. The Review of Economic categories such as science and technology are typically location Studies, 78, 2, 640–666. independent. [8] Dogan Gursoy and KW Kendall. 2006. Hosting mega events: In the future, we plan to identify the most frequently men- modeling locals’ support. Annals of tourism research, 33, 3, tioned topics in the Olympic legacy corpus to see how they affect 603–623. the news sentiment of articles about different geographical lo- [9] Daniel Kahneman and Amos Tversky. 2013. Choices, val- cations. Since our study is limited to English news articles, we ues, and frames. In Handbook of the fundamentals of finan- intend to learn more about the role of cultures and languages in cial decision making: Part I. World Scientific, 269–278. this bias analysis. We also intend to broaden our investigation to [10] Gregor Leban, Blaz Fortuna, Janez Brank, and Marko Gro- discover the adjectives used to describe the negative and positive belnik. 2014. Event registry: learning about world events legacies of Rio and London. Such an analysis would aid in un- from news. In Proceedings of the 23rd International Confer- derstanding the expectations from cities such as Rio (the first in ence on World Wide Web, 107–110. South America to host the Olympics) in comparison to London. [11] TA Quijote, AD Zamoras, and A Ceniza. 2019. Bias detec- tion in philippine political news articles using sentiword- 7 ACKNOWLEDGMENTS net and inverse reinforcement model. In IOP Conference This work was supported by the Slovenian Research Agency and Series: Materials Science and Engineering number 1. Vol- the European Union’s Horizon 2020 research and innovation ume 482. IOP Publishing, 012036. program under the Marie Skłodowska-Curie grant agreement No [12] Nils Reimers and Iryna Gurevych. 2019. Sentence-bert: 812997. sentence embeddings using siamese bert-networks. In Pro- ceedings of the 2019 Conference on Empirical Methods in REFERENCES Natural Language Processing. Association for Computa- [1] Dan Bernhardt, Stefan Krasa, and Mattias Polborn. 2008. tional Linguistics, (November 2019). http://arxiv.org/abs/ Political polarization and the electoral effects of media 1908.10084. bias. Journal of Public Economics, 92, 5-6, 1092–1104. [13] Swati, Tomaž Erjavec, and Dunja Mladenić. 2020. Eveout: [2] Shri Bharathi and Angelina Geetha. 2017. Sentiment anal- reproducible event dataset for studying and analyzing the ysis for effective stock market prediction. International complex event-outlet relationship. Journal of Intelligent Engineering and Systems, 10, 3, 146– [14] Taylor Thomsen. 2018. Do media companies drive bias? 153. using sentiment analysis to measure media bias in news- [3] SV Shri Bharathi and Angelina Geetha. 2019. Determina- paper tweets. tion of news biasedness using content sentiment analysis 138 An evaluation of BERT and Doc2Vec model on the IPTC Subject Codes prediction dataset Marko Pranjić Marko Robnik-Šikonja Senja Pollak marko.pranjic@styria.ai marko.robnik@fri.uni- lj.si senja.pollak@ijs.si Jožef Stefan International University of Ljubljana, Faculty of Jožef Stefan Institute Postgraduate School Computer and Information Science Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia Trikoder d.o.o. Zagreb, Croatia ABSTRACT standardized set of topics would enable faster news production and higher quality of the metadata for news content. Large pretrained language models like BERT have shown excel- In this paper, we use recently published ST T News[10] dataset lent generalization properties and have advanced the state of the in Finnish to evaluate the performance of the monolingual Fin- art on various NLP tasks. In this paper we evaluate Finnish BERT BERT model [13] on the IPTC Subject Codes prediction task, (FinBERT) model on the IPTC Subject Codes prediction task. We together with the Doc2Vec[3] model as a baseline. We attempt compare it to a simpler Doc2Vec model used as a baseline. Due to to encode the hierarchical nature of the prediction task in the hierarchical nature of IPTC Subject Codes, we also evaluate the prediction network topology by mimicking the structure of the effect of encoding the hierarchy in the network layer topology. labels. Finally, impact of using a different tokenizers with the Contrary to our expectations, a simpler baseline Doc2Vec model same model is evaluated. clearly outperforms the more complex FinBERT model and our The paper is structured as follows. In Section 2, we describe attempts to encode hierarchy in a prediction network do not the dataset and the labels relevant for the prediction task. Section yield systematic improvement. 3 describes the methods used to model the prediction task and KEYWORDS all variations of experiments. In Section 4, we provide results of our experiments and, finally, in Section 5 we conclude this paper news categorization, text representation, BERT, Doc2Vec, IPTC and suggest ideas for further work. Subject Codes 2 DATASET 1 INTRODUCTION The ST T corpus [10] contains 2.8 million news articles from the The field of Natural Language Processing (NLP) has greatly ben- Finnish News Agency (ST T) published between 1992 and 2018. efited from the advances in deep learning. New techniques and The articles come with a rich metadata information including the architectures are developed at a fast pace. The Transformer ar- 1 news article topics encoded as IPTC Subject Codes . The IPTC chitecture [12] is the foundation for most new NLP models and Subject Codes are a deprecated version of IPTC taxonomy of it is especially successful with models for text representation, news topics focused on text. The IPTC Subject Codes standard such as BERT model [1] which dominates the text classification. describes around 1400 topics structured in three hierarchical The gains in performance promised by the large BERT models levels. The first level consists of the most general topics. Topics comes at the price of significant data resources and computa- on the second level are subtopics of the ones at the first level and, tional capabilities required in the model pretraining phase. The likewise, topics on the third level are subtopics of the ones on practitioners take one of the models pretrained in the language second level. All topics on the third level are leaf topics - there of the data and finetune it for the specific classification prob- are no more subdivisions, but there are also some topics on the lem. Multilingual BERT-like models have also shown remarkable second level that are leaf topics and do not extend to the third potential for cross-lingual transfer ([7], [8], [6]). A majority of level. A set of IPTC topics at ST T is an extended version of IPTC the research with BERT-like models is focused on English, while Subject Codes as some codes used at ST T are not part of the IPTC less-resourced languages tend to be neglected. standard. The IPTC Subject Codes originate in the journalistic setting. Not all articles in the ST T corpus contain the IPTC Subject The news articles are tagged with the IPTC topics to enable search Codes, as can be seen in Figure 1, showing the ratio of articles and classification of the news content, as well as to facilitate containing this information through time. IPTC Subject Codes content storage and digital asset management of news content were introduced in ST T in May 2011 and around 10-15% of articles at media houses. It provides a consistent and language agnostic do not contain this information. coding of topics across different news providers and across time. If an article contains a specific sub-topic, it also contains its Solving the automatic classification of the news content to the upper-level topics. For example, if an article contains the third level topic "poetry", it also contains the second level topic "litera- Permission to make digital or hard copies of part or all of this work for personal ture" that generalizes the "poetry", as well as the first level topic 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 "arts, culture and entertainment". In this way, article metadata the full citation on the first page. Copyrights for third-party components of this contains full path through the topic hierarchy. work must be honored. For all other uses, contact the owner /author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1 https://iptc.org/standards/subject-codes/ 139 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Pranjić, et al. experiments use the PV-DM variant of the algorithm available 2 in the Gensim library with most of the hyperparameters set to their default values. We set the context window width to 5 and train the network for 10 epochs on the news content from the training data. The model produces a 256 dimensional output vector. Once the model is trained, we do not finetune it further during training of the prediction task. Tokenization of the data was done using the SentencePiece[2] tokenizer. It was trained to produce a vocabulary of 40,000 tokens by using randomly selected 1 million sentences sampled from the articles in the training set. Additionally, we ran experiments using the same WordPiece[14] tokenizer that is used with the FinBERT model. 3.2 BERT Figure 1: The Ratio of news articles in STT corpus contain- ing IPTC Subject Codes. BERT is an deep neural-network architecture of bidirectional text encoders introduced in [1]. The base model consists of 12 Transformer [12] layers. It is trained using the masked language Most articles are assigned only a small number of leaf-level modeling (MLM) and next sentence prediction (NSP) objectives topics (and its higher-level topics), but they can contain up to 7, 19 on a large text corpora. Maximum length of the input sequence and 30 topics from the first, second and third level, respectively. for the model is 512 tokens and each token is represented with 768 We split the dataset to train, validation and test set such that dimensions. Model inference produces a context dependent repre- all articles published after 31-12-2017 belong to the test set and sentations of the input tokens. The whole input sequence can be discard articles without IPTC Subject Codes from it. The rest of represented with a single vector by using the context dependent the articles were randomly split such that 5% of articles contain- representation of the [CLS] token. In [1], this representation is ing IPTC Subject Codes represent the validation set and all other used as an aggregate sequence representation for classification articles belong to the train set. tasks. Another way to represent the whole sequence, as used After this step, there are around 30 thousand articles in the in [9], is to take the average representation of all output tokens validation set, around 100 thousand in test set and 2.7 million in (AVG). In this paper, we use FinBERT, a BERT model introduced 3 training set - of which some 560 thousand contain IPTC Subject in [13] that was pretrained on Finnish corpora. We should note Codes annotation. that this model contains the ST T corpus as part of its training The train set contains 17 different topics on the first level, 400 data. 4 on the second level, and 972 on the third (the most specific) level. Input to the model is restricted to 512 tokens and longer news In our experiments, we evaluate models only on topics found in articles are trimmed such that only the first 512 tokens are used. the training set. In the dataset, there are less than 5% and 7% of documents in the training and test data that are longer than 512 tokens. We 3 METHODOLOGY experiment with the CLS and the AVG representations and in both cases the article representation is a 768 dimensional vector. For our experiments, we used a network design consisting of two The FinBERT model is finetuned during training of the IPTC stacked neural networks (extractor and predictor). The extractor Subject Codes prediction task. processes the text and produces the text representation in the format of a numeric vector. The predictor (the second part) is 3.3 Prediction network a multi-label prediction network that maps the extracted text representation vector to IPTC Subject Codes. For the extractor For the predictor part, we experiment with two different archi- part, we evaluate the Doc2Vec and BERT model and for the tectures. The first is a single layer of the neural network that predictor our models use one or three layer neural network. maps the input vector to the predictions and can be seen in the Figure 2. The IPTC Subject Codes on all levels are concatenated 3.1 Doc2Vec together, thus producing a 1389 outputs in the final layer. The second architecture utilizes the tree hierarchy of the IPTC Before the contextual token embeddings became popular, this Subject Codes. We assumed that a flat output (the previous ap- model was regularly used to represent a text paragraph with proach) requires the network to predict each label independently, a fixed vector. It was introduced in [3] with two variants of irrespective of the level of the target label. By introducing sepa- the algorithm - PV-DM (Paragraph Vector-Distributed Memory) rate layers for each target level, we expect that the model will and PV-CBOW (Paragraph Vector-Continuous Bag-of-Words). implicitly learn the hierarchy among labels. We designed this In the PV-DM variant of the algorithm, a training context is network in three layers and the architecture is shown in Figure 3. defined as a sliding window over the text. The model is a shallow The first layer of the network predicts labels from the third IPTC neural network trained to predict the central word of this context hierarchical level (the most fine-grained topics), the second layer window given the embeddings of the rest of the context words together with the embedding of the whole document. During 2 training, the network learns both the word embeddings and the https://radimrehurek.com/gensim/ 3 We also test the FinEst BERT[11] but since the better performance was achieved embedding for the document. The simpler PV-CBOW variant with the FinBERT[13], we do not include FinEst BERT it in the results. does not employ a context window, the neural network is trained 4 The tokenizer used with the model is a predefined WordPiece tokenizer that came to predict a randomly sampled word from the document. Our with the FinBERT model. 140 STT IPTC Subject Codes evaluation Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia using a WordPiece (WP) tokenizer and either the CLS token or the average (AVG) of all output tokens as a text representation. The Doc2Vec model is using either the WordPiece (WP) tokenizer or the SentencePiece (SP) tokenizer. 4.1 Evaluation metrics We approach the article categorization problem through the in- formation retrieval paradigm. Namely, we try to return the set of the most probable IPTC Subject Codes assigned to each ar- ticle in the ST T corpus. We use two performance metrics, the mean average precision (mAP) and recall at 10 (R@10). The mean average precision returns the expectation of the area under the precision-recall curve for a random query. The recall at 10 com- putes the ratio of correct topics found in the 10 tags with the highest predicted probability. To measure the generalization of our prediction models, we compute these metrics separately for each level of the IPTC Subject Codes. Figure 2: Predictor network architecture, flat variant. The 4.2 Results and discussion image does not show a normalization layer before the out- put layer. In all experiments, the Doc2Vec model performed significantly better than the FinBERT model, regardless of the specific extrac- tor or predictor setup. This is surprising in the light of other successful applications of BERT models. Nevertheless, as there are less than 5% of articles in the training set and less than 7% of articles in the test set that have more than 512 tokens (the limitation of BERT but not Doc2Vec) we cannot assign the poor performance of BERT to this limitation. Some other relevant findings are as follows. While for some tasks[9] the BERT average token representation performs better than the representation based on the CLS token, in our experi- ments the CLS and the AVG representations perform comparably. The three-layer network mimicking the shape of the tree-like IPTC Subject Codes hierarchy did not yield any systematic im- provement over the single, flat layer of the neural network. Dif- ference in tokenizers for Doc2Vec experiments shows small, but consistent improvement when using the SentencePiece tokenizer. 5 CONCLUSIONS AND FURTHER WORK Figure 3: Predictor network architecture, tree variant. The In this work, we have compared a monolingual FinBERT and image does not show a normalization layer before each Doc2Vec model on the IPTC Subject Codes prediction task in output layer. Finnish language. We evaluated several variations of experiments and achieved consistently better results with a Doc2Vec model. In contrast to the Doc2Vec, the BERT model has a limitation in predicts topics from the second level and the third layer predicts the form of maximum number of input tokens. We believe the only the toplevel IPTC Subject Codes. results cannot be explained by this as the data used does not 3.4 Training contain a significant amount of documents exceeding this limit. We plan to explore this topic further in hope of understanding Each model was trained using the batch size of 128 articles and and addressing this problem. Recent work in BERT finetuning AdamW[4] optimizer with the learning rate of 1e-3. We compute strategies[5] identifies a problem of vanishing gradients due to the metrics on the validation set every 100 iterations. Once the excessive learning rates and implementation details of the opti- loss on the validation data starts increasing, we stop the training mizer. and evaluate the best performing checkpoint on the test data. Our attempt at encoding the hierarchical nature of the predic- The loss function used in all experiments is the sum of binary tion task did not yield systematic improvement and we believe cross-entropy losses calculated at each topic level. The news it is worthwhile to explore other strategies and improve on this articles that do not have an annotation for certain topic level do area, like encoding the hierarchy of the predictions in the loss not contribute to the loss of that level. function itself. For Doc2Vec experiments, consistently better results were 4 EXPERIMENTS AND RESULTS achieved using the SentencePiece[2] tokenizer over the Word- All experiments were repeated three times and we report the Piece[14] tokenizer used in FinBERT model. Both of those tok- median of those three runs in Table 1. The extraction network enizers retain the whole information of the input as there are no was evaluated with four configurations. The FinBERT model is destructive operations on the text. We plan further experiments 141 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Pranjić, et al. Table 1: Results for different experimental configurations. Extractor Predictor mAP (lvl 1) mAP (lvl 2) mAP (lvl 3) R@10 (lvl 1) R@10 (lvl 2) R@10 (lvl 3) FinBERT (CLS) Flat 0.5432 0.2047 0.1031 0.9058 0.3687 0.2242 FinBERT (CLS) Tree 0.5434 0.1949 0.1043 0.9058 0.3602 0.2417 FinBERT (AVG) Flat 0.5401 0.2026 0.1006 0.9045 0.3692 0.2391 FinBERT (AVG) Tree 0.5410 0.2088 0.1089 0.9078 0.3724 0.2367 Doc2Vec (WP) Flat 0.8091 0.5204 0.2990 0.9721 0.7008 0.4750 Doc2Vec (WP) Tree 0.8127 0.5202 0.2972 0.9743 0.7099 0.4714 Doc2Vec (SP) Flat 0.8298 0.5550 0.3149 0.9803 0.7277 0.4951 Doc2Vec (SP) Tree 0.8315 0.5643 0.3282 0.9832 0.7358 0.4896 to confirm and quantify these findings and understand what en- [7] Telmo Pires, Eva Schlinger, and Dan Garrette. 2019. How ables such improvement of downstream prediction task at the multilingual is multilingual BERT? In Proceedings of the tokenizer level. 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Flo- ACKNOWLEDGMENTS rence, Italy, (July 2019), 4996–5001. doi: 10.18653/v1/P19- The work was partially supported by the Slovenian Research 1493. https://aclanthology.org/P19- 1493. Agency (ARRS) core research programmes P6-0411 and P2-0103, [8] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, as well as the research project J6-2581 (Computer-assisted mul- Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and tilingual news discourse analysis with contextual embeddings). Peter J. Liu. 2020. Exploring the limits of transfer learning This paper is supported by European Union’s Horizon 2020 re- with a unified text-to-text transformer. Journal of Machine search and innovation programme under grant agreement No Learning Research, 21, 140, 1–67. http://jmlr.org/papers/ 825153, project EMBEDDIA (Cross-Lingual Embeddings for Less- v21/20- 074.html. Represented Languages in European News Media). [9] Nils Reimers and Iryna Gurevych. 2019. Sentence-BERT: sentence embeddings using Siamese BERT-networks. In REFERENCES Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International [1] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Joint Conference on Natural Language Processing (EMNLP- Toutanova. 2019. BERT: pre-training of deep bidirectional IJCNLP). Association for Computational Linguistics, Hong transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of Kong, China, (November 2019), 3982–3992. doi: 10.18653/ the Association for Computational Linguistics: Human Lan- v1/D19- 1410. https://aclanthology.org/D19- 1410. guage Technologies, Volume 1 (Long and Short Papers) [10] ST T. 2019. Finnish news agency archive 1992-2018, source . (June (http://urn.fi/urn:nbn:fi:lb-2019041501). (2019). 2019), 4171–4186. doi: 10.18653/v1/N19- 1423. [11] Matej Ulčar and Marko Robnik-Šikonja. 2020. Finest bert [2] Taku Kudo and John Richardson. 2018. Sentencepiece: a and crosloengual bert. In Text, Speech, and Dialogue. Petr simple and language independent subword tokenizer and Sojka, Ivan Kopeček, Karel Pala, and Aleš Horák, editors. detokenizer for neural text processing. In (January 2018), Springer International Publishing, Cham, 104–111. 66–71. doi: 10.18653/v1/D18- 2012. [12] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszko- [3] Quoc Le and Tomas Mikolov. 2014. Distributed represen- reit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia tations of sentences and documents. In Proceedings of the 31st International Conference on Machine Learning Polosukhin. 2017. Attention is all you need. In Proceedings (Pro- of the 31st International Conference on Neural Information ceedings of Machine Learning Research) number 2. Eric P. Processing Systems (NIPS’17). Curran Associates Inc., Red Xing and Tony Jebara, editors. Volume 32. PMLR, Bejing, Hook, NY, USA, 6000–6010. isbn: 9781510860964. China, (June 2014), 1188–1196. https://proceedings.mlr. [13] Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, press/v32/le14.html. Juhani Luotolahti, Tapio Salakoski, Filip Ginter, and Sampo [4] Ilya Loshchilov and Frank Hutter. 2019. Decoupled weight Pyysalo. 2019. Multilingual is not enough: bert for finnish. decay regularization. In International Conference on Learn- ing Representations (2019). arXiv: 1912.07076 [cs.CL]. . https : / / openreview. net / forum ? id = [14] Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Bkg6RiCqY7. Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, [5] Marius Mosbach, Maksym Andriushchenko, and Dietrich Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Klakow. 2021. On the stability of fine-tuning {bert}: mis- Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan conceptions, explanations, and strong baselines. In Inter- national Conference on Learning Representations Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith . https : Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff //openreview.net/forum?id=nzpLWnVAyah. Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, [6] Andraž Pelicon, Marko Pranjić, Dragana Miljković, Blaž Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016. Škrlj, and Senja Pollak. 2020. Zero-shot learning for cross- Google’s neural machine translation system: bridging the lingual news sentiment classification. Applied Sciences, gap between human and machine translation. (2016). arXiv: 10, 17. issn: 2076-3417. doi: 10.3390/app10175993. https: 1609.08144 [cs.CL]. //www.mdpi.com/2076- 3417/10/17/5993. 142 Classification of Cross-cultural News Events Abdul Sittar∗ Dunja Mladenić abdul.sittar@ijs.si dunja.mladenic@ijs.si Jožef Stefan Institute and Jožef Stefan International Jožef Stefan Institute and Jožef Stefan International Postgraduate School Postgraduate School Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT meta data of an event is shown in the Table 1. The main scientific We present a methodology to support the analysis of culture contributions of this paper are the following: from text such as news events and demonstrate its usefulness (1) A novel perspective of aligning news events across dif- on categorising news events from different categories (society, ferent cultures through categorising countries and news business, health, recreation, science, shopping, sports, arts, com- events. puters, games and home) across different geographical locations (2) A cross-cultural automatically annotated dataset in several (different places in 117 countries). We group countries based on different domains (Business, Science, Sports, Health etc.). the culture that they follow and then filter the news events based (3) Experimental comparison of several classification mod- on their content category. The news events are automatically els adopting different set of features (character ngrams, labelled with the help of Hofstede’s cultural dimensions. We GLOVE embeddings and word ngrams). present combinations of events across different categories and check the performances of different classification methods. We Table 1: The description of the meta data of an event. also presents experimental comparison of different number of Attributes Description features in order to find a suitable set to represent the culture. title title of the event summary summary of the event source event reported by a news source KEYWORDS categories list of DMOZ categories cultural barrier, news events, text classification location location of the event 1 INTRODUCTION Culture is defined as a collective programming of the mind which 2 RELATED WORK distinguishes the members of one group or category of people In this section, we review the related literature about the influ- from another [9]. It has a huge impact on the lives of people and ence of culture, its representation and classification in different in result it influences events that involve cross-cultural stake- fields. holders. News spreading is one of the most effective mechanisms Countries that share a common culture are expected to have for spreading information across the borders. The news to be heavier news flows between them when reporting on similar spread wider cross multiple barriers such as linguistic, economic, events [10]. There are many quantitative studies that found de- geographical, political, time zone, and cultural barriers. Due to mographic, psychological, socio-cultural, source, system, and rapidly growing number of events with significant international content-related aspects [2]. impact, cross-cultural analytics gain increased importance for Cross-cultural research and understanding the cultural influences professionals and researchers in many disciplines, including digi- in different fields have competitive advantages. The goal of re- tal humanities, media studies, and journalism. The most recent searching the impact of culture might be to draw conclusions examples of such events include COVID-19 and Brexit [1]. There in which way the cultural factors influence a specific corporate are few determinants that have significant influence on the pro- action. There are many type of cultures such as societal, organi- cess of information selection, analysis and propagation. These zational, and business culture etc [8]. include cultural values and differences, economic conditions and The hidden nature of cultural behavior causes some difficulties association between countries. For instance, if two countries are in measurement and defining these. To cope with difficulties, culturally more similar, there are more chances that there will researchers have developed measurements that measure culture be a heavier news flow between them [10], [3]. In this paper, on a general scale to compare differences among cultures and we focus on classification of news events across different cul- management styles. These results can be used to find similarities tures. We select some of the most read daily newspapers and within a region and differences to other regions. There are many collect information using Event Registry about the news they models that have tried to explain cultural differences between have published. Event Registry is a system which analyzes news societies. Hofstede’s national culture dimensions (HNCD) have articles, identifies groups of articles that describe the same event been widely used and cited in different disciplines [6, 5]. Hofst- and represent them as a single event [7]. The description of the ede’s dimensions are the result of a factor analysis at the level of country means of comprehensive survey instrument, aimed Permission to make digital or hard copies of part or all of this work for personal at identifying systematic differences in national cultural. 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 purpose is to measure culture in countries, societies, sub-groups, the full citation on the first page. Copyrights for third-party components of this and organizations; they are not meant to be regarded as psycho- work must be honored. For all other uses, contact the owner/author(s). logical traits. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). There is a plethora of research studies that were conducted to un- derstand the cultural influences such as cross-culture privacy and 143 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Abdul and Dunja, et al. attitude prediction, and cultural influences on today’s business. provided by the Event Registry. This task can be formulated as: [4] explores how culture affects the technological, organizational, 𝐶 = 𝑓 (𝑆, 𝐺 ) and environmental determinants of machine learning adoption by conducting a comparative case study between Germany and C donates the culture of the news event, f is the learning function, US. Rather than looking at the influence of cultural differences S donates summary of a news event and G donates category of a within one domain, we intend to understand association between news event (see Table 1). news events belonging to different domains (society, business, health, recreation, science, shopping, sports, arts, computers, 4.2 Methodology games and home) and different cultures (117 countries from all the continents). We conduct this research to find an appropriate representation and classification of culture across different do- mains. Clusters of Countries Char Ngrams 3 DATA DESCRIPTION News Events Dataset Annotation Glove Embeddings Classification 3.1 Dataset Statistics We choose the top 10 daily read newspapers in the world in 2020 1 and collect the events reported by these newspapers using Event Category of Events Word Ngrams Registry [7] over the time period of 2016-2020. Approximately 8000 events belongs to each newspaper with exception of “Za- man” that has only 900 events. Figure 1 shows the number of events reported by the selected newspapers on a yearly basis. Figure 2: Classification of cross-cultural news events. This dataset can be found on the Zenodo repository (version 1.0.0) 2 4.2.1 Data labeling. Each news event has information about the type of categories to which it belongs and the location where it happened (see Table 1). Each event has many categories and each category has a weight reflecting its relevance for the event. We only keep the most relevant categories and group the news events based on their categories. For each group of events, we estimate the cultural characteristic of each event through the country of the place where the event occurred. We cluster the countries based on their culture. We utilize the Hofstede’s national culture dimensions (HNCD) to represent the culture of a country. We take average of cultural dimensions and call it average cultural score. Based on this score, we find optimal number of clusters using Figure 1: Each color in a bar represents the total number popular clustering algorithm k-means (see Figure 4). Finally, we of events per year by a daily newspaper and a complete label each news event with one of the six cultural clusters. bar shows the total number of events per year by all the newspapers. The attributes of an event with description are displayed in Table 1. Few attributes are self-explanatory such as title, summary, date, and source. DMOZ-categories are used to represent topics of the content. The DMOZ project is a hierarchical collection of web page links organized by subject matters 3. Event Registry use top 3 levels of DMoz taxonomy which amount to about 50,000 categories 4. 4 MATERIAL AND METHODS 4.1 Problem Definition Figure 3: The pie chart depicts the percentage of the news events that occurred in six different clusters (each cluster There are two main parts of the problem that we are addressing. consists of a list of countries with similar culture). The first part is to label the examples by assigning a culture C to a news event E using its location L. The second part is a multi-class classification task where we predict the culture C of a news event 4.2.2 Data representation. Each news event in Event Registry E using its summary description S and its content category G as has associated categories with it along with a weight (see Table 1), we take the top categories based on their weight. In case of 1https://www.trendrr.net/ 2 multiple categories with equal weight, we sort them alphabeti- https://zenodo.org/record/5225053 3https://dmoz-odp.org/ cally and keep the first one. We represent each news event by a 4https://eventregistry.org/documentation?tab=terminology short summary S and a set of content categories G. 144 Classification of Cross-cultural News Events Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 4: In word cloud, the color of each word shows cluster to whom it belongs (see Figure 3). Radial dendrograms illustrate the shared categories of news events between the pair of six clusters. 4.2.3 Data Modeling. For multi-class classification task, we use word ngrams using 1 to 3 word ngrams (see Figure 5). Looking at simple classification models (SVM, Decision Tree, KNN, Naive the character ngrams, the highest F1-score is achieved when we Bayes, Logistic Regression) as well as neural network. For sim- select the top 15K characters for all the tested algorithms except ple classification models, we input character and word ngrams Naive Bayes which declines in performance with the growing varying the number of ngrams and compare the results. We also set of features. Based on these settings, we achieve the highest use pre-trained Glove embeddings. accuracy (0.85) using Logistic Regression. Using Glove embed- dings, we experiment with and without using the category of 5 EXPERIMENTAL EVALUATION event. The highest F1-score with and without the category is 0.80 5.1 Evaluation Metric and 0.79 respectively. For multi-class classification task, we use following most com- monly used evaluation measures: accuracy, precision, recall, and F1 score. 7 CONCLUSIONS AND FUTURE WORK 6 RESULTS AND ANALYSIS For researchers and professionals, it is very important to anal- 6.1 Annotation Results yse the cross-cultural differences in different disciplines. As the The results of annotation are six clusters where almost 50% news international impact is increasing and international events are events belong to the two clusters (shown with red and blue colors) becoming popular, the need to develop some automatic methods and remaining 50% belong to the other four clusters 3. Looking is significantly increasing and leaving a blank space. We con- in each group, we find that clusters do not lies in a specific ducted experiments on news events related to different fields geographic area or a continent. Rather all the countries in a to have a broader look on data and machine learning methods. cluster belong to the different continents. Similarly, these clusters Further research would be helpful in examining the impact of do not have all the countries that are economically rich or poor. specific socio-cultural factors on news events. In this research There are more categories in green and red colors in the word work, we estimate the culture of a specific place by its country, cloud (see Figure 4) which represent to the cluster with that colors. use basic features and simple classification models. To continue Radial dendrograms in Figure 4 present the shared categories this work further, we would like to improve feature set such as between the clusters. In the figure, root of the tree is data and by including part of speech tagging (POS) as well as other state then there are ten pair of clusters that share the same categories. of the art embeddings. The objective of this whole process was to keep news events according to the category to whom they belongs. Moreover, we can only observe the cultural differences when we have same type of news events from different places. ACKNOWLEDGMENTS 6.2 Classification Results The research described in this paper was supported by the Slove- Fro the experimental results we can see that the best performance nian research agency under the project J2-1736 Causalify and is achieved by Logistic Regression, kNN and Decision Tree. The by the European Union’s Horizon 2020 research and innovation performance of SVM varies depending on the number of selected programme under the Marie Skłodowska-Curie grant agreement features: the highest F1-score is achieved with the top 10K or 20K No 812997. 145 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Abdul and Dunja, et al. [3] Tsan-Kuo Chang and Jae-Won Lee. 1992. Factors affecting gatekeepers’ selection of foreign news: a national survey of newspaper editors. Journalism Quarterly, 69, 3, 554–561. [4] Verena Eitle and Peter Buxmann. 2020. Cultural differences in machine learning adoption: an international compari- son between germany and the united states. [5] Meihan He and Jongsu Lee. 2020. Social culture and in- novation diffusion: a theoretically founded agent-based model. Journal of Evolutionary Economics, 1–41. [6] Mahmood Khosrowjerdi, Anneli Sundqvist, and Katriina Byström. 2020. Cultural patterns of information source use: a global study of 47 countries. Journal of the Association for Information Science and Technology, 71, 6, 711–724. [7] Gregor Leban, Blaz Fortuna, Janez Brank, and Marko Gro- belnik. 2014. Event registry: learning about world events from news. In Proceedings of the 23rd International Confer- ence on World Wide Web, 107–110. [8] Björn Preuss. 2017. Text mining and machine learning to capture cultural data. Technical report. working paper, 2. doi: 10.13140/RG. 2.2. 30937.42080. [9] Giselle Rampersad and Turki Althiyabi. 2020. Fake news: acceptance by demographics and culture on social media. Journal of Information Technology & Politics, 17, 1, 1–11. [10] H Denis Wu. 2007. A brave new world for international news? exploring the determinants of the coverage of for- eign news on us websites. International Communication Gazette, 69, 6, 539–551. Figure 5: First two line charts illustrate the variations in F1 score by simple classification models after varying the number of features. The first line chart depicts the results of word ngrams whereas the second one shows the results for character ngrams. The last line graph presents com- parison between Glove embeddings (with and without cat- egory feature). REFERENCES [1] Sara Abdollahi, Simon Gottschalk, and Elena Demidova. 2020. Eventkg+ click: a dataset of language-specific event- centric user interaction traces. arXiv preprint arXiv:2010.12370. [2] Hosam Al-Samarraie, Atef Eldenfria, and Husameddin Dawoud. 2017. The impact of personality traits on users’ information-seeking behavior. Information Processing & Management, 53, 1, 237–247. 146 Zotero to Elexifinder: Collection, curation, and migration of bibliographical data David Lindemann david.lindemann@ijs.si Jožef Stefan Institute Jamova cesta 39 Ljubljana, Slovenia Figure 1: Zotero to Elexifinder workflow model ABSTRACT workshop connected to the 2019 eLex conference in Sintra (Por- tugal), it was decided to combine the efforts, and the workflow In this paper, we present ongoing work concerning a workflow explained in this paper was designed, in order to merge existing and software tool pipeline for collecting and curating bibliograph- datasets, decide criteria for data curation, and make the results ical data of the domain of Lexicography and Dictionary Research, available to the lexicographic community. Two years later, at the and data export in a custom JSON format as required by the 2021 Euralex conference, Elexifinder version 2 was introduced Elexifinder application, a discovery portal for lexicographic lit- [3]. Main shortcomings of Elexifinder version 1 have been sorted erature. We present the employed software tools, which are all out, namely the missing author disambiguation, and the coverage freely available and open source. A Wikibase instance has been of the domain’s literature has been significantly increased, also chosen as central data repository. We also present requirements regarding publication languages other than English. Moreover, a for bibliographical data to be suitable for import into Elexifinder; vocabulary of lexicographic terms has been developed, which is these include disambiguation of entities like natural persons and now used for content-describing indexation of article full texts. natural languages, and a processing of article full texts. Beyond Lexicography and Dictionary Research is a relatively small the domain of Lexicography, the described workflow is applicable discipline, having thematic intersections with Corpus Linguis- in general to single-domain small scale digital bibliographies. tics, Terminology, Natural Language Processing, and Philology. KEYWORDS In metalexicographic literature, all aspects of the lexicographic process, dictionary structure and functions, dictionary use, and bibliographical data, author disambiguation, e-science corpora other relevant issues are discussed. The lexicographic commu- 1 INTRODUCTION nity communication is mainly taking place through a reduced number of conference series and journals, being complemented 1 In 2019, version 1 of Elexifinder, a discovery portal for lexico- by handbooks and other edited volumes. The need for a dedicated graphic literature, was launched in the framework of the ELEXIS digital bibliography arises from the following observations: 2 project [2]. At the same time, at University of Hildesheim, a domain ontology and bibliographical data collection for Lexicog- • The vast majority of publications do not have Digital Ob- raphy and Dictionary Research was planned [6, 5]. Both endeav- ject Identifiers (DOI), and thus are not indexed in cross- ours already had compiled significant datasets. At a dedicated domain digital collections of publication metadata. This applies to nearly all older publications, but also to many 1 Accessible at https://finder.elex.is. 2 newer contributions published in the last two decades. See https://elex.is. • When searching for metalexicographical publications in Permission to make digital or hard copies of part or all of this work for personal cross-domain digital collections, search results are mixed or classroom use is granted without fee provided that copies are not made or up with publications from other domains, which may dis- 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 turb a straightforward information retrieval. work must be honored. For all other uses, contact the owner /author(s). • Author disambiguation in domain-independent digital col- Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia lections that can be considered the big players in the field © 2020 Copyright held by the owner/author(s). (such as Google Scholar) is not at all accurate, so that very 147 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia D. Lindemann 12 often name variants are not resolved to a single person added. Duplicate management has been done in batches (whole entity, and different persons with the same name are not journal issues or conference iterations), or one by one using disambiguated. Zotero’s built-in duplicate detection functionality. Main criterion • If articles are indexed with content-describing terms in for the inclusion of metadata records has been the availability of cross-domain digital collections, the vast majority of those the corresponding full texts. This means a clear preference for terms will be out of the scope of the domain we are looking Open Access publications; but also other publications have been at. included, wherever a suitable license agreement allowed access • 13 Publication metadata found at big (i.e. automatically com- to the text. 14 piled) repositories is often incomplete or noisy, so that Zotero data can be accessed by API, or exported locally using using those, e.g. for citations, requires manual interven- pre-set or custom export scripts. We use an adapted version of tion in order to achieve a publishable quality. the Zotero JSON-CSL exporter, which produces a list of JSON objects containing all metadata fields and their values as literal Therefore, it seems useful to provide the lexicographic commu- strings, as well as the location of all local file attachment copies. nity with a platform that makes publications and their metadata For statements that cannot be expressed using standard Zotero accessible in a way that the described shortcomings will be over- 15 fields , we have used Zotero tags as workaround, following a come. Single-domain endeavours of this kind, which all involve simple syntax of predicate and object. For example, for asserting manual curation, are DBLP 3 for Computer Science, IxTheo4 for that an article is a review article, the tag ":type Review", and so Theology, or EconBiz5 for Economics. Inspired by features found on. Tags in Zotero can be easily copied from one item to others in these, we propose a workflow that involves the use of free by manual drag-and-drop operations, set via API, and also be software accessible to anybody, which makes it reproducible and included in display styles, so that in the Zotero item listings, cost-reducing. for example, review article titles can be preceded by a coloured symbol. With this workaround we can assert semantic triples 2 LEXBIB ZOTERO GROUP inside Zotero. That is, for instance, that for representing the 6 Zotero, developed and maintained by the Corporation for Digital statement that a certain item is contained in another item (e.g. a 7 Scholarship , a non-profit organisation, is the most widely used book chapter item in an item of type book), we use a tag beginning open source citation management software application. Zotero with ":container", followed by an identifier for the containing offers functionality for web-scraping publication metadata, im- item; for a conference paper presented at a certain event, we use porting metadata from different structured formats, and an online a tag beginning with ":event", followed by an identifier for that platform for collaborative curation of metadata, along with the event. For both of these, corresponding Zotero fields do exist possibility to attach full text PDF (and TXT versions) to metadata ("contained in", "presented at"), but these are filled by the web records. The Zotero scraper functionality allows to download scraping and importer translators with literal string values as publication metadata and attached PDF files from all those sites needed for citations, and not with unambiguous identifiers. 8 the Zotero community has provided a "translator" for, includ- For Elexifinder, a special metadatum is included in all publica- ing the web platforms of major publishing houses, Open Journal tion metadata sets: The location of the first author. This allows Systems, etc. From the Zotero platform, users are able to obtain the generation of location maps and search filters according to metadata records as single items or as batches for import into locations in the Elexifinder portal. For these locations, we insert their own citation managers, or as export records in a range of 16 English Wikipedia page titles in the Zotero "extra" field. citation styles or in structured formats such as bibtex. Members of a Zotero group can view and download full text attachments. 3 LEXBIB WIKIBASE Moreover, Zotero items can be annotated with custom tags, and 3.1 Wikibase as LOD infrastructure solution additional information (such as excerpts or comments) can be attached to them. Around Zotero, an active community is devel- The decisive shift from a metadata set as in Zotero, which con- 9 oping plug-ins that add new functionalities to Zotero. sists of certain fields and their literal values, towards unambigu- In the first planning period of the LexBib project, funded by the ous Linked Data lies in the reconciliation of those literal values University of Hildesheim, conference publications of the Euralex against existing or new unambiguous identifiers. For example, and the eLex conference series, and publications from a range of and this already refers to the hardest nut to crack in this context, journals and edited volumes have been added to LexBib Zotero an author may have several name variants appearing across the 10 group. Items collected for Elexifinder version 1, available as publication metadata collection, and there may be other persons tabular data, have then been merged to the Zotero group. For this sharing the same name, or any of the name variants. But one 11 purpose, tabular csv data has been transformed to RIS format author or editor (i.e., a "creator") should only have one identifier and imported to Zotero. Additionally, metadata records from (such as ORCID). Since we do not know Wikidata and/or ORCID OBELEX-meta and EURALEX-Dykstra bibliographies have been identifiers of all creators in our database, we need to create our own (and map them later). Other Zotero fields that should be 3 Accessible at https://dblp.org/. 12 See references in [3]. 4 Accessible at https://ixtheo.de/. 13 Article full text are stored and exclusively used for project-related text mining 5 Accessible at https://www.econbiz.de/. tasks; they cannot be downloaded from Zotero. We instead provide download links 6 See https://zotero.org. which lead to the download offered by the corresponding publisher, subject to 7 See https://digitalscholar.org/. applicable restrictions. 8 14 See https://www.zotero.org/support/translators. See https://www.zotero.org/support/dev/web_api/v3/start. 9 15 For example, very recently the Cita plug-in has been developed, which allows to See https://www.zotero.org/support/kb/item_types_and_fields. add citation metadata to Zotero records, see https://meta.m.wikimedia.org/wiki/ 16 Wikipedia page titles are unambiguous (see e.g. https://en.wikipedia.org/wiki/ Wikicite/grant/WikiCite_addon_for_Zotero_with_citation_graph_support. Cambridge vs. https://en.wikipedia.org/wiki/Cambridge, _Massachusetts), and map 10 Last version accessible at https://www.zotero.org/groups/lexbib/library. to only one Wikidata entity. This strategy has turned out effective, since manual 11 See https://en.wikipedia.org/wiki/RIS_(file_format). annotators are able to find the adequate Wikipedia page without hassle. 148 Zotero to Elexifinder Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia reconciled against unambiguous identifiers are those describing wikibase properties, in this case with datatype "item", that the containing item, the conference where the contribution was is, to object properties. presented, the journal, the publisher, the publication place, and • Creator name and publisher name literals are mapped to the publication language. For some of these, persistent identifiers the properties corresponding to the creator role (author are available in many cases (e.g. journals), or in all cases (lan- or editor), or to the publisher. This is done in a way that guages). In general, we create our own identifiers, and map them the name literals appear as qualifiers to a wikibase "no- to Wikidata; in some cases, immediately (languages, places, and, value" statement, which is a placeholder for the creator or by ISSN, also journals), and in other cases, we leave that mapping publisher item, that will be defined in the disambiguation to the (near) future, as it is the case for creators and publishers. process explained below. Other Zotero fields contain identifiers (ISSN, ISBN, DOI), which • Zotero fields that contain external identifiers (ISSN, ISBN after normalisation can be taken directly as external identifiers and DOI), are mapped to the corresponding properties of in a Linked Database. datatype "external identifier". Wikibase properties of that After experimenting with different RDF database solutions, datatype allow to define a URL pattern, in order to make which allow to represent data in the described way, we have the identifier a valid hyperlink, which can be clicked on 17 decided for Wikibase, which is the software infrastructure un- in Wikibase entity data pages. 18 derlying main Wikidata. Since 2019, "Wikibase as a Service" • As mentioned, we use the Zotero "extra" field ("note" in 19 is offered to the community. Wikibase entities are items (each bibtex) for annotation of the item with a Wikipedia page of which has its own identifier preceded by the letter Q), and that corresponds to the first author’s location. Wikidata properties (preceded by letter P), just as in Wikidata, but in a API is queried for the corresponding Wikidata entity, an different namespace. Properties may point to other items, other equivalent of which is created in LexBib Wikibase, in order properties, external identifiers, or values of a certain datatype, to function as object to the property "first author location". 20 such as "monolingual text", "point in time", "string", "url", etc. • The Zotero "language" field, in LexBib may contain a two- Wikibase as central data repository solution has several ad- letter ISO-639-1, or a three-letter ISO-639-3 code. This vantages compared to other infrastructure solutions for Linked is mapped to a property pointing to the language item Open Data (LOD): corresponding to that code. • • The Zotero item URI is taken as external identifier in Entity data is displayed on entity pages, where it can be LexBib wikibase, with the Zotero storage location of PDF viewed and edited. These pages always reflect the last and TXT attachments as qualifiers to that statement. In update. • addition, we annotate this statement with a qualifier as- A complete edit history is available, and changes can be serting the presence of an abstract, and, if any, in what undone. 23 • language. Every entity page is linked to a dedicated discussion page. • • The content of the remaining fields is mapped to Wikibase User and user rights management allow a community- properties of the corresponding datatype ("URL", "string", driven editing process. • or "point in time"). In addition to query interface and SPARQL endpoint known from other RDF database solutions, Wikibase data can be The resulting dataset is then imported into LexBib Wikibase. It uploaded and downloaded using an API, and as entity data is worth mentioning that uploading data to a Wikibase triple 24 dump in several formats. by triple using the mediawiki API of the Wikibase instance takes about 0.5 seconds per triple, which is due to the need of The backbone of LexBib Wikibase is an ontology of classes and updating Wikibase search indices and edit histories for every 21 properties, which can be aligned to Wikidata or other external single uploaded triple. ontologies. We have started to define these alignments. This en- sures interoperability with other resources, such as Wikidata, so 3.3 Entity disambiguation using Open Refine that data can be transferred from LexBib to Wikidata or vice versa, The around 5,000 creator names appearing in LexBib Zotero by or accessed in both at the same time, using federated SPARQL spring 2021 have been mapped to around 4,000 unique person queries. items. This has been done testing different clustering algorithms 25 3.2 Zotero to Wikibase migration available in the Open Refine application, by Christiane Klaes from the University of Hildesheim, in the framework of her MA As mentioned before, Zotero item data is exported from a local thesis [1]. These are the creator items present in LexBib Wikibase Zotero instance, using an adapted version of the Zotero JSON-CSL 26 experimental version 2. 22 exporter. The resulting list of JSON objects is then processed From that moment on, any new Zotero item that is exported in the following way: to Wikibase, which will contain, as explained above, one or more • Zotero tags that contain semantic triple shortcodes (ex- creator statements of type "novalue", is reconciled against existing plained above) are mapped to the corresponding LexBib LexBib Wikibase creator items, using the given and last name literal qualifiers. For this purpose, a reconciliation service for 27 LexBib Wikibase is set up , and then accessed by Open Refine, 17 See http://wikiba.se; our instance is accessible at http://lexbib.elex.is. 18 in order to match creator name literals to creator items. Accessible at http://www.wikidata.org. 19 See https://www.wbstack.com. The service has been co-enabled by Adam Shore-23 land (https://addshore.com/), Rhizome (https://rhizome.org/), and WMDE (https: The abstract language is assumed to be the same as the publicaton language, if //www.wikimedia.de/). not stated different as tag shortcode ":abstractLang". 20 24 See https://www.wikidata.org/wiki/Help:Data_type. For LexBib Wikibase, see https://lexbib.elex.is/w/api.php. 21 25 For more information, see LexBib Wikibase main page at https://lexbib.elex.is. Available at https://openrefine.org/. 22 26 Available at https://github.com/elexis- eu/elexifinder/blob/master/Zotero/LexBib_ Accessible at https://data.lexbib.org. 27 JSON.js. This is done using https://github.com/wetneb/openrefine- wikibase. 149 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia D. Lindemann If a literal can not be matched to any existing item, a new The full text body itself is also exported to Elexifinder, where person item is created. The reconciliation also works with fuzzy it is used for displaying the first bits of it in search result displays, matches, and all name variants attached to existing items are and for wikification, from which Elexifinder "concepts" are ob- considered. Matches can also be manually chosen. Any additional tained, as long as the system is able to associate named entities name variant appearing in Zotero data is linked to the LexBib occurring in the text with Wikipedia pages that describe them. Wikibase person item as "alias" label, while the most frequent name variant is chosen as "preferred" label. This allows for the 5 CONCLUSIONS AND OUTLOOK new name variants being available for subsequent reconciliation The described workflow enables us to disambiguate entities found iterations. in bibliographical datasets. For the time being, we are applying LexBib persons have up to six name variants found in Zotero this for feeding the Elexifinder app. Having chosen Wikibase data. In some cases, we have chosen the preferred name variant as central data repository also allows for aligning LexBib data manually, according to the author’s own choice, or to conventions with Wikidata in a straightforward way. In some cases, we have in the community regarding the naming of commonly known imported statements from Wikidata, in order to enrich LexBib 28 authors. entities with additional information, but that can be done the other way round as well. In other words: Wherever we find (or 3.4 Full text processing create) a Wikidata entity to align with our own, we can export the LexBib full text PDFs are stored in the local Zotero storage folder, statements asserted on LexBib Wikibase to the main Wikidata. which is automatically synchronised with Zotero cloud. When We have done this using LexBib events (conferences) as test case, processing Zotero JSON output, PDF files are sent to an installa- and plan to align other entity types with Wikidata in the near 29 tion of the GROBID application , which will propose a TEI rep- future, namely articles, persons, and organisations. resentation of the PDF content. This allows for isolating the full text body from the other text components, such as title, running ACKNOWLEDGMENTS titles, abstract, author list, and references section. The extracted The research received funding from the European Union’s Hori- full text body is manually validated, and, in case of any mistake, zon 2020 research and innovation programme under grant agree- it is corrected, using a plain TXT version of the PDF, which is by ment No. 731015. default produced by Zotero. GROBID turns out to structure PDF content as TEI very ef- REFERENCES ficiently if the article resembles a typical structure as found in [1] Christiane Klaes. 2021. Linked Open Data-Strategien zum journals and proceedings. Book chapters and review articles, Identity Management in einer Fachontologie. Master’s thesis. which normally do not feature an abstract, in turn, are usually Universität Hildesheim, Hildesheim, (June 2021). http : / / not parsed adequately. In those cases, we now use directly the lexbib.elex.is/entity/Q15468. plain TXT version for producing a cleaned version manually. [2] Iztok Kosem and Simon Krek. 2019. ELEXIFINDER: A Tool 30 The article text is then lemmatised, and lexicalisations of for Searching Lexicographic Scientific Output. In Electronic 31 LexVoc lexicographic terms are looked up in the text. LexVoc Lexicography in the 21st Century: Proceedings of the eLex 32 vocabulary is a resource still under development; for the term 2019 Conference. Lexical Computing CZ s.r.o., Brno, 506– discovery process, terms and lexicalisations (labels) are obtained 518. http://lexbib.elex.is/entity/Q9484. from LexBib Wikibase by a SPARQL query, the result of which [3] Iztok Kosem and David Lindemann. 2021. New develop- will reflect the state of LexVoc in that particular moment. The ments in Elexifinder, a discovery portal for lexicographic keyword processor returns counts of every term, so that relative literature. In Lexicography for Inclusion: Proceedings of the frequencies can be calculated for every term, according to the 19th EURALEX International Congress, 7-11 September 2021, occurrences of its labels and the amount of tokens in the article Alexandroupolis, Vol. 2. Democritus University of Thrace, text body; this information can be uploaded to LexBib Wikibase Alexandroupolis, 759–766. http : / / lexbib . elex . is / entity / bibliographical items, so that term indexation becomes part of Q15467. their entity data. [4] Gregor Leban, Blaz Fortuna, Janez Brank, and Marko Gro- belnik. 2014. Event registry: learning about world events 4 WIKIBASE TO ELEXIFINDER from news. In Proceedings of the 23rd International World The described workflow is necessary for being able to export Wide Web Conference, WWW14, Seoul, Korea, April 7-11, bibliographical data in a custom JSON format, as needed for Elex- 2014, 107–110. doi: 10.1145/2567948.2577024. ifinder, which is an application based on some of the elements of [5] David Lindemann, Christiane Klaes, and Philipp Zumstein. the Event Registry system architecture [4]. In particular, authors 2019. Metalexicography as Knowledge Graph. OASICS, 70. and content-describing terms (Elexifinder "categories") have to http://lexbib.elex.is/entity/Q13955. be represented as objects containing an unambiguous URI and a [6] David Lindemann, Fritz Kliche, and Ulrich Heid. 2018. LexBib: textual label; the containing item, the LexBib Zotero item URI, A Corpus and Bibliography of Metalexicographical Publi- and the link for accessing full text download are represented as cations. In Lexicography in Global Contexts: Proceedings of URL, publication date in ISO 8601 format, publication language the 18th EURALEX International Congress, 17-21 July 2018, in ISO 639-3 format, and the item title as simple string. Ljubljana. Ljubljana University Press, Ljubljana, 699–712. http://lexbib.elex.is/entity/Q6059. 28 See an example at http://lexbib.elex.is/entity/Q1583. 29 See https://grobid.readthedocs.io. 30 For the time being, we are only processing English text. For lemmatisation, we use spaCy (see https://spacy.io/). 31 This is done using https://pypi.org/project/flashtext/. 32 Described at http://lexbib.elex.is/wiki/LexVoc. 150 Simple Discovery of COVID IS WAR Metaphors Using Word Embeddings Mojca Brglez Senja Pollak Špela Vintar University of Ljubljana Jožef Stefan Institute University of Ljubljana Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia mojca.brglez@ff.uni- lj.si senja.pollak@ijs.si spela.vintar@ff.uni- lj.si ABSTRACT an innovative methodological approach. We propose a top-down method to search for expected conceptual metaphors through In the past year, the discourse on the COVID-19 pandemic has semi-automatic means employing word embeddings. While most produced a great number of metaphors stemming from the more previous corpus-based approaches to identify metaphors either basic conceptual metaphor ILLNESS IS WAR. In this paper, we use a small set of candidate words or require manual inspec- present a semi-automatic method to detect linguistic manifes- tions of large data samples, our approach reduces manual work tations of the latter in Slovene media. The method consists of on assembling linguistic data by combining existing annotated assembling a seed vocabulary of war-related words from an ex- resources and text mining methods. isting Slovene metaphor corpus, extending the vocabulary using word embeddings, and refining the extended vocabulary using 2 PROPOSED APPROACH intersection filtering. Our method offers a quick compilation of corpus data for further analysis, however, we also address is- Our method aims to discover linguistic expressions of the con- sues related to the method’s precision and the need for manual ceptual metaphor COVID IS WAR in the corpus by targeting filtering. a broader potentially metaphoric vocabulary. Previous related works have relied on either a limited vocabulary set (e.g. [7]) or a KEYWORDS list of words laboriously compiled from various sources such as dictionaries, thesauri and other studies on metaphor [19], or have metaphors, covid, word embeddings, media discourse used sophisticated but complex NLP methods and specialized 1 INTRODUCTION resources (e.g. [6]). In our experiment, we use a simple unsuper- vised approach using existing resources and language processing The COVID pandemic has been a ubiquitous topic in the dis- technologies. course of the past year, featuring in medical, political, public The main novelty of our approach is using pre-trained word and personal discourse. The emergence of a new virus of yet embeddings to extend the vocabulary, used also by e.g. [16] and unknown origin, behaviour and effects has presented itself like a [18] to extend terminology. As past research has shown [14], word complex and obscure topic. To make sense of it, we have once embeddings used for training language models retain linguistic more resorted to metaphorical language, much like we do when regularities, including syntactic and semantic relationships be- faced with other abstract, obscure concepts. According to Con- tween words. This means that similar words have similar vectors, ceptual Metaphor Theory (CMT, [11, 12]), metaphors “are among and the closer vector representations (word embeddings) are, our principal vehicles for understanding” and “play a central role the higher the chance they share a certain semantic space. We in the construction of social and political reality” ([12, p. 151]). make use of this feature by trying to capture a semantic space that In CMT, linguistic metaphors such as "food for thought" and would resemble the conceptual domain of WAR, which represents "half-baked idea" are considered manifestations of an established the source domain of the metaphor. conceptual mapping between a more concrete domain and a more abstract domain, here for example IDEAS ARE FOOD. The do- 2.1 Method main of DISEASES, on the other hand, is often mapped to the First, we start by collecting war-related lexical units from the domain of WAR, a more common frame of reference which has KOMET corpus [1], the only corpus of metaphors in Slovene taken hold as a fairly conventional way to talk about illnesses which was recently compiled and annotated similarly to the and their treatments, as well as several other domains ([8]). English corpus of metaphors, VUAMC [17]. KOMET contains ap- As was already observed in various studies ([19, 2, 5, 7]), the dis- proximately 200,000 words obtained from journalistic, fiction and course on the current COVID pandemic has also repeatedly used online texts and was hand-annotated for metaphoricity on the ba- the WAR domain in its metaphors. At the time of our experiment, sis of the MIPVU procedure ([17]). Additionally, the metaphoric however, no study has yet addressed the use of such metaphors expressions are tagged for one of 69 semantic frames, i.e. the in Slovene, where they were also adopted for communicating source concepts that semantically motivate them. One of these se- various implications, preventive measures, recommendations and mantic frames is #met.battle, which subsumes 105 metaphoric laws to abide by. To investigate the use and pervasiveness of this instances with 67 different lemmas, such as predati, ostrostrelec, metaphorical domain in Slovene media, we have conducted a orožje, napasti [surrender, sniper, weapon, attack]. These also quick analysis of a corpus of COVID-related news articles using form multi-word idioms such as železna pest [iron fist] and boriti Permission to make digital or hard copies of part or all of this work for personal se z mlini na veter [to tilt at windmills] which we exclude from or classroom use is granted without fee provided that copies are not made or our candidates list because the word embeddings we use only rep- 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 resent tokens, not whole phrases. Moreover, the lemmas within work must be honored. For all other uses, contact the owner /author(s). do not themselves necessarily represent the desired domain. We Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia also filter out some words erroneously annotated with the frame © 2021 Copyright held by the owner/author(s). such as številen [numerous]. This gives a starting vocabulary of 151 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Brglez et al. 51 unique seed words. Then, to extend the vocabulary further, (2) true metaphorical expressions referring to disease as target we employ Slovene word token embeddings ([13] pre-trained domain with fastText ([4]) on various large corpora of Slovene (GigaFida, For example, in the following sentence, the word brigade Janes, KAS, slWaC etc.). For each seed word in the list of words [brigades] only refers to a name of a street, which we mark extracted from the KOMET corpus, we use the Gensim library as literal usage. ([20]) to find the word’s N nearest neighbours in the fastText embeddings’ space (using the most_similar function). • /. . . / odvzem brisov pri pacientih s sumom na Covid-19: ob To increase the robustness of the extended vocabulary, we try Cesti proletarskih brigad 21 /. . . / to automatically filter out lexis not related to war. To this end, /. . . / taking swabs from patients with suspected Covid-19: at we use the word embeddings intersection method ([18]). The 21, Proletarian Brigades Road /. . . / method retains only the candidates that intersect between the In the following example, the word napad [attack] is used to refer sets, meaning they occur in the neighbourhood of at least k input to another domain – INTERNET, COMP UTING, which we mark seed words. For our main experiment, presented in this paper, we as metaphor for another target domain. select the parameters N =50 and k=3. We thus obtain a maximum • Covid-19 je okrepil trend rasti kibernetskih napadov [Covid- of 2550 (50 x 51) potential candidates. In the output, there are 19 reinforced the growing trend of cyber attacks] 2078 unique words, and, after lemmatization, 1539 unique lemmas. After the intersection filtering, the vocabulary extended by word The following three example sentences contain expression that embeddings consists of 184 word lemmas: 44 of them are already we mark as metaphor for the target domain of DISEASE. included in our initial seed set and 140 are new lemmas. We join • Čeprav v boju z virusom to nikakor ni hitro. the new, extended set with the initial seed set, which yields a [Although this is by no means fast in the fight against the total of 191 lemmas to search for. virus.] 3 CORPUS • Kako bo jeseni, ko bodo »udarili« še drugi virusi? The experiment is carried out on a corpus of Slovene COVID- [What will happen in autumn, when other viruses also 19-related news articles, automatically crawled from the web by “strike”?] searching for the keyword “covid-19” in article titles (a subset of the Slovene corpus used in the Slav-NER 2021 shared task ([15]). • Prvi organski sistem v organizmu, ki ga virus napade, The corpus consists of 233 texts spanning from February 2nd povzroči pljučnico, . . . to December 11th, 2020 . To prepare it for analysis, we remove [The first system in the organism that the virus attacks the header of each text (comprised of the article number, locale, causes pneumonia . . . ] date and URL), then parse the text into sentences and tokens Results of this analysis are presented in Table 1, whereby using the NLTK library ([3]). We also lemmatize the corpus using we report only lemmas that were metaphorically used for the the LemmaGen lemmatization module ([9]). The pre-processed DISEASE target domain at least once. corpus contains 7,273 sentences and 151,947 tokens. As can be derived from Table 1, our proposed method correctly 3.1 Corpus search identified 25 different lemmas with a total of 123 occurrences that are used metaphorically to frame the topic of the pandemic. In the next step, we extract all sentences from the corpus con- Out of our 233 articles, 68 or 29,18% contained at least one mili- taining any of the war-related terms from our expanded vocab- taristic metaphorical expression. The ostensibly most frequent ulary of 191 lemmas. The results yield 335 instances of poten- expression used was boj [fight] with 46 metaphorical occurrences, tially metaphorical expressions. Out of the 191 lemmas on the followed by boriti [to fight] with 13 metaphorical occurrences metaphorical candidate list, the COVID corpus contains 49, ap- and soočati [to confront] with 7 metaphorical occurrences. They pearing in 268 sentences. Due to the unsupervised approach these account for 37.4%, 10.6% and 5.7% of all metaphorical expressions are still only candidate words from the semantic domain of war. found by our method, respectively, and together, they represent A manual analysis shows that in addition to war metaphors, our more than 50% of them. This points to the interpretation that the extracted sentences include the following four cases: news corpus contains mostly highly conventional and recurrent (1) Some of the seed words found in the corpus are used metaphors. A lot of the war-related vocabulary (potential can- literally; didates in our extended war-related lexis) is not used, meaning (2) Some of the seed words found in the corpus are a result the corpus does not, at this moment, exhibit very original, novel of lemmatization errors metaphorical expressions. Using a larger and a more recently (3) Some of the seed words found in the corpus are used compiled corpus would perhaps reveal a more innovative use of metaphorically, but refer to other target domains, such COVID IS WAR metaphors. The vocabulary extension method as POLITICS or NATURE (e. g. boriti se proti podnebnim using word embeddings has proven fruitful as it revealed some spremembam [’fight against climate change’]) metaphorical expressions that were not in the initial 51-word (4) Some of the seed words in our initial 191-candidate list list extracted from the KOMET corpus. The 9 newly discovered are not actually related to the topic of WAR but are more lemmas are: soočiti, izbojevati, zmagati, obraniti, uiti, soočanje, closely related to another topic (e.g. gol [‘goal’]) spopadati, zoperstaviti, podleči [to confront, to fight, to win, to On this account we perform a manual analysis of the extracted defend, to escape, confrontation, to combat, to oppose, to suc- sentences and categorize them as follows: cumb]. (1) falsely extracted instances due to a lemmatization error The analysis also revealed some additional lemmas that relate or literal use, or true metaphorical expressions but with the epidemic to the war frame. In the sentences containing the other source or target domain, and lemmas we searched for, there were other words from the WAR 152 Simple Discovery of COVID IS WAR Metaphors Using Word Embeddings Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 1: Analysis of metaphoric lemmas from the ex- (75, 100, 150 and 200). Our initial experiments were carried out tended vocabulary on a N of 50 and intersection k of 3. However, by changing the parameters, the results of initial new lemmas could differ. In Lemma Corpus Literal DISEASE Figure 1, we analyse how the seed list changes with different oc- uses, as target parameters: N of 50 and 75 neighbours, each combined with the curences lemma- domain intersection count k of 2, 3 and 4. Note that these refer only to tization the list of potentially metaphoric lemmas, and not to the analy- errors sis of their use, which can only be analysed in context. We see or other that the initially selected parameters (50 neighbours and 3 recur- source/target rences) are an acceptable middle-ground between precision and domain size while still maintaining an unsupervised approach, however, had we wanted more examples, we could increase the parameter Boj [fight] 57 11 46 N or decrease the parameter k. Boriti [to fight] 16 3 13 For the recall, we are not able to carry out a systematic eval- Soočati [to confront] 17 10 7 uation. Nevertheless, based on metaphor clusters analysis men- Spopad [to combat] 6 6 tioned above, we identified the set of additional words that belong Spopadanje [combat- 6 6 to the military vocabulary: fronta, strategija, preboj, akcijski, vo- ting] jen, sovražnik [front, strategy, breakthrough, action [ADJ], war Zoperstaviti [to 5 5 [ADJ], enemy]. The words vojen [war[ADJ]] and sovražnik [en- oppose] emy] would have been included if we lowered the intersection Bitka [battle] 5 1 4 parameter to k = 2 at N = 50 neighbours or extended the vo- Napad [attack] 41 37 4 cabulary by N = 75 neighbours while keeping the intersection Podleči [succumb] 5 1 4 parameter k = 3. Other metaphorical expressions occurring in Spopadati [to combat] 5 1 4 the corpus (fronta, preboj, strategija, akcijski) [front, strategy, Bojen [combat [ADJ]] 17 15 2 breakthrough, action [ADJ]] are not found anywhere in the first Borba [battle] 3 1 2 200 neighbours of any of the words, indicating perhaps that the Braniti [to defend] 4 2 2 number of neighbours might be further increased. However, we Napasti [to attack] 6 4 2 observe that increasing the number of neighbours leads to fuzzier Obramben [defense 9 7 2 results. The added vocabulary using 75, 100, 150, and 200 near- [ADJ]] est neighbours of our initial seed words includes increasingly Soočanje [confronting] 2 2 more words unrelated to the topic of war and some very common Soočiti [to confront] 6 4 2 words, which would need additional filtering. We assume that Žrtev [victim] 49 47 2 the reason for this is that words commonly used metaphorically Borec [fighter] 3 2 1 (conventional or dead metaphors) are “displaced” in the vector Izbojevati [to fight] 1 1 space of embeddings, moving away from the words in their orig- Obraniti [to defend] 1 1 inal semantic domains and closer to words in other semantic Štab [base, headquar- 3 2 1 domains – target domains. For example, we observed a lot of ters] sports expressions in our extended vocabulary (e.g. “ball”, “goal”, Udariti [to hit] 2 2 “goalpost”). This shows how entrenched metaphors are in our Uiti [to escape] 2 1 1 language: in the vector space of word embeddings, the seman- Zmagati [to win] 5 4 1 tic domains are already “muddled”. In the present example, this TOTAL 270 147 123 could be a due to the frequent linguistic manifestations of the conceptual metaphor COMPETITION IS WAR. domain forming so called metaphor clusters ([10]). Thus, we man- aged to capture some metaphorical expressions that appeared in close vicinity (in the same sentence) of the found metaphor- ical expressions: fronta, strategija, preboj, akcijski načrt, vojna mentaliteta, sovražnik [front, strategy, breakthrough, action plan, war mentality, enemy]. For instance, our method found the sen- tence below which, in addition to the word bitka [battle] in our candidate list, contains a metaphorical use of the word fronta [front]. • Bitka proti virusu na več frontah [Battle against the virus on multiple fronts] 4 ANALYSING DIFFERENT PARAMETER SETTINGS Figure 1: Analysis of vocabulary extension parameters N Some of the expressions mentioned above would have been cap- and k tured had we modified the parameters of vocabulary extension. Namely, we experimented with using more nearest neighbours 153 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Brglez et al. 5 CONCLUSION [9] Matjaž Juršič, Igor Mozetič, Tomaž Erjavec, and Nada Lavrač. 2010. Lemmagen: multilingual lemmatisation with We present an innovative approach using word embeddings as induced ripple-down rules. Journal of Universal Computer a tool for extending the vocabulary of potentially metaphoric Science, 16, 9, 1190–1214. http://www.jucs.org/jucs_16_9/ expressions and identify them in corpora. Our approach shows lemma_gen_multilingual_lemmatisation|. promise in that it correctly identifies numerous such expressions [10] Veronika Koller. 2003. Metaphor clusters, metaphor chains: and confirms that intersections of semantic spaces of metaphor- analyzing the multifunctionality of metaphor in text. In ical seed words can be used to refine the quest for words per- volume 5, 115–134. taining to the military domain. Nevertheless, some metaphoric [11] George Lakoff and Mark Johnson. 1980. Metaphors we live expressions are missed by our method and the experiment still by. University of Chicago press. needs manual analysis. Further research and experiments would [12] George Lakoff and Mark Johnson. 2003. Metaphors we live be needed for a larger expansion of vocabulary and a finer filter- by. University of Chicago press. ing approach as well as comparing different word embeddings, [13] Nikola Ljubešić and Tomaž Erjavec. 2018. Word embed- possibly those trained on more literal language. dings CLARIN.SI-embed.sl 1.0. Slovenian language resource ACKNOWLEDGMENTS repository CLARIN.SI. (2018). http://hdl.handle.net/11356/ 1204. This work is supported by the Slovenian Research Agency by [14] Tomas Mikolov, Wen-tau Yih, and Geoffrey Zweig. 2013. the research core funding P6-0215 and P2-0103, as well as by Linguistic regularities in continuous space word represen- the research project CANDAS ( J6-2581). The work has also been tations. In Proceedings of the 2013 Conference of the North supported by the European Union’s Horizon 2020 research and in- American Chapter of the Association for Computational Lin- novation programme under grant agreement No. 825153, project guistics: Human Language Technologies. Association for EMBEDDIA (Cross-Lingual Embeddings for Less-Represented Computational Linguistics, Atlanta, Georgia, (June 2013), Languages in European News Media). The results of this paper 746–751. https://aclanthology.org/N13- 1090. reflect only the authors’ view and the Commission is not re- [15] Jakub Piskorski, Bogdan Babych, Zara Kancheva, Olga sponsible for any use that may be made of the information it Kanishcheva, Maria Lebedeva, Michał Marcińczuk, Preslav contains. Nakov, Petya Osenova, Lidia Pivovarova, Senja Pollak, REFERENCES Pavel Přibáň, Ivaylo Radev, Marko Robnik-Sikonja, Vasyl Starko, Josef Steinberger, and Roman Yangarber. 2021. [1] Špela Antloga. 2020. Metaphor corpus KOMET 1.0. Slove- Slav-NER: the 3rd cross-lingual challenge on recognition, nian language resource repository CLARIN.SI. (2020). http: normalization, classification, and linking of named entities //hdl.handle.net/11356/1293. across Slavic languages. In Proceedings of the 8th Workshop [2] Benjamin R. Bates. 2020. The (in)appropriateness of the on Balto-Slavic Natural Language Processing. Association war metaphor in response to SARS-CoV-2: a rapid analysis for Computational Linguistics, Kiyv, Ukraine, 122–133. of Donald J. Trump’s rhetoric. Frontiers in Communication, https://aclanthology.org/2021.bsnlp- 1.15. 5, 50, (June 2020). doi: 10.3389/fcomm.2020.000505. [16] Senja Pollak, Andraž Repar, Matej Martinc, and Vid Pod- [3] Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural pečan. 2019. Karst exploration: extracting terms and defi- Language Processing with Python. (1st edition). O’Reilly nitions from karst domain corpus. In Proceedings of eLex Media, Inc. 2019, 934–956. [4] Piotr Bojanowski, Edouard Grave, Armand Joulin, and [17] G. Steen. 2010. A Method for Linguistic Metaphor Identifica- Tomas Mikolov. 2017. Enriching word vectors with sub- tion: From MIP to MIPVU. Converging evidence in language word information. Transactions of the Association for Com- and communication research. John Benjamins Publishing putational Linguistics, 5, (June 2017), 135–146. doi: doi. Company. doi: 10.1075/celcr.14. org10.1162/tacl_a_00051. [18] Špela Vintar, Larisa Grcic, Matej Martinc, Senja Pollak, [5] Eunice Castro Seixas. 2021. War metaphors in political and Uroš Stepišnik. 2020. Mining semantic relations from communication on Covid-19. Frontiers in Sociology, 5, 112. comparable corpora through intersections of word embed- doi: 10.3389/fsoc.2020.583680. dings. In (May 2020). https://aclanthology.org/2020.bucc- [6] Jane Demmen, Elena Semino, Zsófia Demjén, Veronika 1.5.pdf . Koller, Andrew Hardie, Paul Rayson, and Sheila Payne. [19] Philipp Wicke and Marianna M. Bolognesi. 2020. Framing 2015. A computer-assisted study of the use of violence COVID-19: how we conceptualize and discuss the pan- metaphors for cancer and end of life by patients, family demic on Twitter. PLOS ONE, 15, 9, (September 2020), 1– carers and health professionals. International Journal of 24. doi: 10.1371/journal.pone.0240010. Corpus Linguistics, 20, 2, 205–231. doi: 10.1075/ijcl.20.2. [20] Radim Řehůřek and Petr Sojka. 2010. Software framework 03dem. for topic modelling with large corpora. In (May 2010), 45– [7] Damián Fernández-Pedemonte, Felicitas Casillo, and Ana 50. doi: 10.13140/2.1.2393.1847. Jorge-Artigau. 2021. Communicating COVID-19: metaphors we “survive” by. Tripodos, 2, (February 2021), 145–160. doi: 10.51698/tripodos.2020.47p145- 160. [8] Stephen J. Flusberg, Teenie Matlock, and Paul H. Thi- bodeau. 2018. War metaphors in public discourse. Metaphor and Symbol, 33, 1, 1–18. doi: 10 . 1080 / 10926488 . 2018 . 1407992. 154 Topic modelling and sentiment analysis of COVID-19 related news on Croatian Internet portal Maja Buhin Pandur Jasminka Dobša Faculty of Organization and Informatics, Faculty of Organization and Informatics, University of Zagreb University of Zagreb Varaždin, Croatia Varaždin, Croatia mbuhin@foi.hr jasminka.dobsa@foi.hr Slobodan Beliga Ana Meštrović University of Rijeka, Department of Informatics & University of Rijeka, Department of Informatics & University of Rijeka, Center for Artificial University of Rijeka, Center for Artificial Intelligence and Cybersecurity Intelligence and Cybersecurity Rijeka, Croatia Rijeka, Croatia sbeliga@uniri.hr amestorovic@uniri.hr ABSTRACT approach by using NRC word-emotion lexicon [13] for detection of sentiments (positive or negative) and basic emotions, The research aims to identify topics and sentiments related to the according to Pluchik’s model of emotions [15], in extracted COVID-19 pandemic in Croatian online news media. For topics. analysis, we used news related to the COVID-19 pandemic from The main goal of this paper is to analyse sentiments and the Croatian portal Tportal.hr published from 1st January 2020 to emotions in crises communication in the news related to the 19th February 2021. Topic modelling was conducted by using the COVID-19 pandemic published on the Croatian online portal. LDA method, while dominant emotions and sentiments related Our goal was aggravated in this research because articles belong to extracted topics were identified by National Research Council rather to objective than to subjective type of reporting. Another Canada (NRC) word-emotion lexicon created originally for problem is the lack of lexical resources for sentiment and English and translated into Croatian, among other languages. We emotions in the Croatian language. Glavaš and co-workers [10] believe that the results of this research will enable a better developed a Croatian sentiment lexicon called CroSentiLex, understanding of the crisis communication in the Croatian media which consists of positive and negative lists of words ranked with related to the COVID-19 pandemic. PageRank scores. Nevertheless, there is no available lexicon for the analysis of emotions for the Croatian language. Our analysis uses the NRC word-emotion lexicon, initially developed for KEYWORDS English and translated into 104 languages, including Croatian. News media, sentiment, emotions, pandemic, lexicon approach, Such an approach has disadvantages due to cultural differences, Latent Dirichlet Allocation but developing emotion lexicons for low-resource languages as Croatian is very demanding. Sentiment analysis of COVID-19 related texts is conducted mainly for texts written in English, 1 INTRODUCTION such as research by Shofiya and Abidi [17], where the There are three major approaches to sentiment and emotions SentiStrength tool was used to detect the polarity of tweets, and analysis in text: lexicon based, machine learning based approach support vector machine (SVM) algorithm was employed for [12] and the most recent deep-learning approach. In this research, sentiment classification. In [14], tweets about COVID-19 in we used a hybrid approach by applying the method of Latent Brazil written in Brazilian Portuguese due to lack of language Dirichlet Allocation (LDA) for topic modelling [6] and lexicon resources are analysed by translating original text from Portuguese to English and using available resources for English. Regarding Croatian social media space, Twitter social network communication was analysed through sentiment 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 analysis [2] and COVID-19 information spreading [3]. Crisis for profit or commercial advantage and that copies bear this notice and the full communication of Croatian online portals was already explored 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). by topic modelling of COVID-19 related articles [7]. However, Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia in that research, it is not included further sentiment and emotional © 2020 Copyright held by the owner/author(s). analysis of topics. In [4], information monitoring and name entity 155 Information Society 2020, 5–9 October 2020, Ljubljana, M. Buhin Pandur et al. Slovenia recognition were conducted on news portal texts related to a COVID-19 article only if it contains at least one keyword pandemics. related to coronavirus thematic. We use COVID-19 thesaurus for article filtering, which contains about thirty of the most important words describing the SARS-CoV-2 virus epidemic together with 2 METHODS their corresponding morphological variations. From the total of 31,177 articles, according to defined filtering, the dataset used in 2.1 Latent Dirichlet Allocation the experiment consists of 12,080 COVID-19 related articles. LDA is a generative, probabilistic hierarchical Bayesian model Articles on the portal are categorised into one of nine main that induces topics from a document collection [5,6]. The categories: Biznis ( Business), Sport ( Sport), Kultura ( Culture), intuition behind topic modelling using LDA is that documents Tehno ( Techno), Showtime, Lifestyle, Autozona ( Autozone), exhibit multiple topics. The topic is formally defined as a Funbox, and Vijesti ( News) (see Table 1). distribution over fixed vocabulary. Induction of topics is done in Documents of a collection are created using text from the three steps: article’s subcategory, introduction, main text, and tags. The  Each document in the collection is distributed over topics collection is preprocessed by ejection of English and Croatian that are sampled using Dirichlet distribution. stop words and numbers and performing a lemmatisation. It is  Each word in the document is connected with one single created a term-document matrix using tf-idf weighting scheme. topic based on Dirichlet distribution. The collection is indexed by terms contained in at least four  Each topic is defined as a multinomial distribution over documents of the collection, and the final list of index terms words that are assigned to the sampled topics. contained 31,121 terms. Topic modelling by LDA is conducted using stm package in R [16]. Table 1: Number of articles from dataset categorised into one of nine main categories 2.2 Number of topics estimation Before performing the LDA topic modelling, it has to be Category Number COVID-19 articles estimated the number of topics. In this research we used four Business 2,767 metrics from the R package ldatuning: Arun2010 [1], Sport 2,008 CaoJuan2009 [8], Deveaud2014 [9], and Griffiths2004 [11]. Culture 894 Measures Arun2010 and CaoJuan2009 have to be minimised, Techno 101 while measures Deveaud2014 and Griffiths2004 have to be Showtime 1,352 maximised. However, as measures, Arun2010 and CaoJuan2009 Lifestyle 1,442 Autozone 124 generally decrease with the number of topics, and measures Funbox 58 Deveaud2014 and Griffiths2004 increase with the number of News 3,334 topics, we will choose the number of topics as the value when observed measures start to stagnate. 3.2 Results 2.3 Detection of sentiments and emotions As a first step, the number of topics had to be estimated. Since For the association of sentiments and emotions to extracted articles on the portal are categorised into nine main categories, topics it was used NRC word-emotion lexicon [13], which we examined a number of topics from 5 to 15. We chose nine consists of 14,182 words with scores of 0 or 1, according to the topics since the metrics started to stagnate for a higher number association to positive or negative sentiment or one of eight of topics (see Figure 1). emotions of Pluchick’s model ( anger, anticipation, disgust, fear, joy, sadness, surprise, and trust) [15]. The lexicon was created manually by crowdsourcing on Mechanical Turk. For every sentiment and emotion, we created a vector with a distribution of zeros and ones over the words of a controlled dictionary created from the collection. Association of topics to sentiments and emotions is calculated as the cosine similarity between vectors of topics and corresponding vector of sentiment or emotion. 3 EXPERIMENT 3.1 Data set and preprocessing The data set used for research consists of articles from the Internet portal Tportal.hr related to the topics of COVID-19 Figure 1: Metrics for estimation of the best fitting number pandemic crises and collected from 1st January 2020 to 19th of topics for 5 to 15 topics February 2021. Each article included in the dataset is defined as 156 Topic modelling and sentiment analysis of COVID-19 Information Society 2020, 5–9 October 2020, Ljubljana, related news on Croatian Internet portal Slovenia Table 2: Top 10 words with the largest probabilities over mali (small), trošak (expenditure), posljedica topics and top 10 words with a negative sentiment with the (consequence), epidemija (epidemic) largest probabilities over topics, both sorted in descending words by theme: order of their probabilities. Topics are sorted by their osoba (person), koronavirus (coronavirus), covid, representation in documents in descending order. slučaj (case), mjera (measure), broj (number), županija (county), nov (new), sat (hour), bolnica Topic 7 – Topic’s (hospital) Top 10 words Daily words by negative sentiment: theme reports bolest (disease), virus (virus), zaraziti (to infect), words by theme: zaraza (infection), epidemija (epidemic), umrijeti (to koronavirus (coronavirus), liga (league), klub (club), die), velik (big), infekcija (infection), zarazan nogometni (football), igrač (player), godina (year), (contagious), simptom (symptom) utakmica (match), sezona (season), hrvatski words by theme: Topic 1 – (Croatian), nogomet (football) godina (year), film (film), nov (new), festival Sport words by negative sentiment: (festival), program (program), hrvatski (Croatian), igrač (player), velik (big), problem (problem), Zagreb, kultura (culture), kazalište (theater), knjiga epidemija (epidemic), odgoditi (to delay), prekinuti Topic 8 – (book) (to interrupt), čekati (to wait), borba (fight), napraviti Culture words by negative sentiment: (to make), posljedica (consequence) velik (big), mali (small), predstavljati (to present), words by theme: nastup (appearance), otkazati (to cancel), odgoditi (to cijepljenje (vaccination), cjepivo (vaccine), zemlja delay), smrt (death), rat (war), strana (side), kritika Topic 2 – (country), europski (European), koronavirus (critique) Vaccination (coronavirus), doza (dose), predsjednik (president), words by theme: vlada (government), mjera (measure), čovjek (man) and nov (new), proizvod (product), automobil (car), velik words by negative sentiment: epidemic (big), godina (year), hrvatska (Croatia), proizvodnja vlada (government), velik (big), epidemija (production), tvrtka (company), trgovina (market), measures (epidemic), red (order), borba (fight), sud (court), Topic 9 – kupac (buyer) granica (border), problem (problem), potreban Business 2 words by negative sentiment: (required), upozoriti (to warn) velik (big), nafta (oil), epidemija (epidemic), lanac words by theme: (chain), smanjiti (decrease), kriza (crisis), mali mjera (measure), hrvatska (Croatia), vlada (small), zaraza (infection), problem (problem), utjecaj Topic 3 – (government), rad (labor), pomoć (help), potpora (influence) Earthquake (support), odluka (decision), potres (earthquake), zaštita (protection), Zagreb and Topics were labelled based on words with the largest words by negative sentiment: government probabilities in topics vectors (keywords) shown in Table 2. potres (earthquake), velik (major), pogoditi (to hit), measures potreban (required), posao (job), šteta (demage), Some of the topics are directly connected to main categories on prijava (report), republika (republic), poziv (call), the portal: the first topic is labelled as Sport, the fourth topic as posljedica (consequence) Lifestyle, and the eighth topic as Culture, while the sixth and the words by theme: ninth topics are connected to the business world and are labelled modni (fashion), godina (year), pandemija as Business 1 and Business 2. Business 1 is associated with the (pandemic), nov (new), koronavirus (coronavirus), capital market, while Business 2 is associated with production. poznat (famous), moda (fashion), obitelj (family), Topic 4 – Topic 2 is associated with Vaccination and epidemic measures, brend (brand), model (model) Lifestyle while Topic 3 is associated with Earthquake and government words by negative sentiment: velik (big), nositi (to wear), izolacija (isolation), veza measures. Topic 5 seems rather General on stories in a pandemic (relationship), majka (mother), dug (debt), djevojka world, while Topics 7 contains daily reports on the pandemic (wench), znak (sign), mali (small), pun (full) state. words by theme: We found that all topics are mainly associated with negative čovjek (man), vrijeme (time), znati (know), virus sentiments. In Table 2 are listed words associated with negative (virus), velik (big), život (life), dan (day), dijete sentiment with the largest probabilities across topics, while Topic 5 – (child), koronavirus (coronavirus), dobro (good) words associated with positive sentiment have coincided with the words by negative sentiment: Generally words from topics theme. This list gives some insight into what velik (big), virus (virus), problem (problem), posao stories “bears” negative sentiment in the topics. (job), napraviti (to make), bolest (disease), mali (small), potreban (required), teško (hard), nositi (to Figure 2 shows the association of topics to sentiments and wear) emotions. The ratio of positive and negative sentiments is the best for categories of Sport and Culture. These categories and words by theme: Lifestyle are only categories associated with joy as one of the posto (percentage), godina (year), pad (drop), velik dominant emotions. Surprise and anticipation are dominant (big), pandemija (pandemic), tržište (market), rast emotions across all topics. Categories Vaccination and epidemic (growth), kuna, gospodarstvo (economy), banka Topic 6 – measures, Earthquake and government support, Generally (bank) Business 1 stories and Business 1 are associated with the emotion of sadness, words by negative sentiment: pad (drop), velik (big), kriza (crisis), vlada while categories Vaccination and epidemic measures and Daily (government), prihod (income), smanjiti (decrease), reports are associated with fear. 157 Information Society 2020, 5–9 October 2020, Ljubljana, M. Buhin Pandur et al. Slovenia ACKNOWLEDGEMENTS This work has been supported in part by the Croatian Science Foundation under the project IP-CORONA-04-2061, “Multilayer Framework for the Information Spreading Characterization in Social Media during the COVID-19 Crisis” (InfoCoV) and by the University of Rijeka project number uniri- drustv-sp-20-58. REFERENCES [1] R. Arun, V. Suresh, C.E. Madhavan and M. Narasima Murty. 2010. On finding the natural number of topics with Latent Dirichlet Allocation: Some observations, In Proceedings of Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference (PAKDD 2010), Hyderabad, India. doi: 10.1007/978-3-642-1357-3_43. [2] K. Babić, M. Petrović, S. Beliga, S. Martinčić-Ipšić, A. Jarynowski and A. Meštrović. 2022. COVID-19-Related Communication on Twitter: Analysis of the Croatian and Polish Attitudes. In: Yang XS., Sherratt S., Dey N., Joshi A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 216. Springer, Singapore. Available at https://link.springer.com/chapter/10.1007%2F978-981-16-1781-2_35. [3] K. Babić, M. Petrović, S. Beliga, S. Martinšić-Ipšić, M. Pranjić and A. Meštrović. 2021. Prediction of COVID-19 related information spreading on Twitter. In Proceedings of the IEEE International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2021), accepted for publication. [4] S. Beliga, S. Martinčić-Ipšić, M. Matešić and A. Meštrović. 2021. Natural Language Processing and Statistic: The First Six Months of the COVID- 19 Infodemic in Croatia, In The Covid-19 Pandemic as a Challenge for Media and Communication Studies. K. Kopecka-Piech and B. Łódzki, Eds., Routledge, Taylor & Francis Group, accepted for publication. Figure 2: Association of topics to sentiments and emotions [5] D. M. Blei. 2012. Probabilistic topic models. Communications of the ACM, 55(4), 77-84. doi:10.1145/2133806.2133826. [6] D. M. Blei, A. Y. Ng and M.I. Jordan. 2003. Latent Dirichlet Allocation. 4 CONCLUSIONS AND FURTHER WORK Journal of Machine Learning Research 3, 993-1022. [7] P. K. Bogović, S. Beliga , A. Meštrović and S. Martinčić-Ipšić. 2021. The main goal of this paper was to analyse sentiments and Topic modelling of Croatian news during COVID-19 pandemic. In emotions in crises communication in the news related to the Proceedings of the IEEE International Convention on Information and COVID-19 pandemic. For that purpose, we have created our Communication Technology, Electronics and Microelectronics (MIPRO 2021), accepted for publication. collection of documents from articles on the Internet news portal [8] J. Chao, L. Tian, Z. Jintao, T. Yongdong and S. Tang. 2009. A density- connected to pandemic crises and analysed it utilising the LDA based method for adaptive LDA model selection, Neurocomputing, 72(7- method for extraction of prevalent topics in the collection and 9), 1775-1781. doi: 10.1016/j.neucom.2008.06.0011. [9] R. Deveaud, E. Sanjuan, P. Bellot. 2014. Accurate and effective latent NRC word-emotion lexicon for detection of sentiments and concept modeling for ad hoc information retrieval, Document emotions associated with extracted topics. Numérique, 17(1). doi: 10.3166/dn.17.1.61-84. Application of LDA resulted in relatively intuitive topics. [10] G. Glavaš, J. Šnajder and B. Dalbelo Bašić. 2012. Semi-supervised Some of them can be associated with the main categories of the acqusition of Croatian sentiment lexicon. In Proceedings of 15th International Conference on Text, Speech and Dialogue, TSD 2112, Brno, observed portal, and the other are related to the actual situation 166-173. in a pandemic world in Croatia: vaccination, earthquake (there [11] T.L. Griffiths, M. Steyvers. 2004. Finding scientific topics. In Proceedings were two great earthquakes in Croatia in 2020), stories, daily of the National Academy of Sciences 101 Suppl 1(1), 5228-35, doi: 10.1073/pnas.0307752101. reports. It is shown that all extracted topics are associated [12] H. Lane, C. Howard and H. Hapke. 2019. Natural Language Processing dominantly with negative sentiment, while prevalent emotions in Action. Manning Publications, New York, NY. are anticipation, surprise, sadness and fear. [13] S. M. Mohammad and P.D. Turney. 2013. Crowdsourcing a word-emotion By this research, we have gained insight into how COVID-19 association lexicon. Computational Intelligence, 29(3), 436-465. [14] T. Melo and C. M. S. Figueiredo. 2021. Comparing news articles and pandemic crises was communicated to the public. To gain insight tweets about COVID-19 in Brasil: Sentiment analysis and topic modeling into how the public experienced the crises, we could use the same approach. JMIR Public Health and Surveillance, 7(2), doi: methodology applied to comments of articles or on social 10.2196/24585. [15] R. Plutchik. 1962. The Emotions. Random House, New York, NY. networks. This could be a direction for a further work. Also, it [16] M. Roberts, B.M. Stewart and D. Tingley. 2019. stm: An R package for would be interesting to investigate how topics and structural topic models, Journal of Statistical Software, 91(2), 1-40. doi: sentiments/emotions are changing and evaluating over time. 10.18637/jss.v091.i02. [17] C . Shofiya and S. Abidi. 2021. Sentiment analysis on COVID-19-related social distancing in Canada using Twitter data. International Journal of Environmental Research and Public Health, 18(11), 1-10. 158 Tackling Class Imbalance in Radiomics: the COVID-19 Use Case Jože M. Rožanec∗ Tim Poštuvan∗ Jožef Stefan International Postgraduate School École Polytechnique Fédérale de Lausanne (EPFL) Ljubljana, Slovenia Lausanne, Switzerland joze.rozanec@ijs.si tim.postuvan@epfl.ch Blaž Fortuna Dunja Mladenić Qlector d.o.o. Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia blaz.fortuna@qlector.com dunja.mladenic@ijs.si ABSTRACT dyspnea[5]. In addition, older people, or people with previous med- Since the start of the COVID-19 pandemic, much research has been ical problems (e.g., diabetes, obesity, or hypertension), are more published highlighting how artificial intelligence models can be likely to develop a severe form of the disease[12, 42], which can used to diagnose a COVID-19 infection based on medical images. derive into multiple organ failure, acute respiratory distress syn- Given the scarcity of published images, heterogeneous sources, for- drome, fulminant pneumonia, heart failure, arrhythmias, or renal mats, and labels, generative models can be a promising solution failure, among others[37, 40]. for data augmentation. We propose performing data augmentation Expert radiologists have observed that the impact of the COVID- on the embeddings space, saving computation power and stor- 19 infection on the respiratory system can be discriminated from age. Moreover, we compare different class imbalance mitigation other viral pneumonia in computed tomography (CT) scans[7, 39]. strategies and machine learning models. We find CTGAN data aug- Most frequent radiological signs include irregular ground-glass mentation shows promising results. The best overall performance opacities and consolidations, observed mostly in the peripheral and was obtained with a GBM model trained with focal loss. basal sites[31]. While such opacities were observed up to a maxi- mum of seven days before the symptoms onset[25], they progress CCS CONCEPTS rapidly and remain a long time after the symptoms onset[35, 38]. • While such opacities can be observed on chest radiography, they Information systems → Data mining; • Computing method- have low sensitivity, which can lead to misleading diagnoses in ologies → Computer vision problems; • Applied computing; early COVID-19 stages, and thus a CT scan is preferred[38]. Scientific studies have shown Artificial Intelligence (AI) is a KEYWORDS promising technology transforming healthcare and medical prac- COVID-19, CT Scans, Imbalanced Dataset, Data Augmentation, tice helping on some clinicians’ tasks (e.g., decision support, or Computer-Aided Diagnosis, Radiomics, Artificial Intelligence, Ma- providing disease diagnosis)[45]. In particular, the field of radiomics chine Learning studies how to mine medical imaging data to create models that ACM Reference Format: support or execute such tasks. Given that distinct patterns can Jože M. Rožanec, Tim Poštuvan, Blaž Fortuna, and Dunja Mladenić. 2021. be observed on chest radiographies and CT scans, clinicians and Tackling Class Imbalance in Radiomics: the COVID-19 Use Case. In Ljubljana researchers sought to use AI for COVID-19 diagnostics[31]. ’21: Slovenian KDD Conference on Data Mining and Data Warehouses, October, There are multiple challenges associated with radiomics, and 2021, Ljubljana, Slovenia. ACM, New York, NY, USA, 4 pages. in particular, with the COVID-19 diagnosis use case. Despite the limitations that can exist regarding privacy concerns[26, 44], many 1 INTRODUCTION datasets have been made publicly available. From those datasets, In December 2019, an outbreak of the coronavirus SARS-CoV-2 many are limited to a few cases[35]; were collected from different infection (a.k.a COVID-19) began in Wuhan, China. The disease sources and image protocols, and thus cannot be merged (e.g., the rapidly spread across the world, and on January 30th 2020, the gray-levels across images can have different meanings[7]); or were World Health Organization (WHO) declared a global health emer- labeled at different granularity levels (e.g., patient-level, or slice- gency. The most common COVID-19 symptoms are dry cough, level)[2]. Therefore, models developed from these datasets cannot sore throat, fever, loss of taste or smell, diarrhea, myalgia, and always be ported to a specific environment. Finally, limitations can exist regarding data collection, further limiting available data to ∗Both authors contributed equally to this research. develop working models to diagnose the disease. The main contributions of this research are (i) a comparative Permission to make digital or hard copies of part or all of this work for personal or study between four data-augmentation strategies used to deal with classroom use is granted without fee provided that copies are not made or distributed class imbalance, (ii) across eight frequently cited machine learn- 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. ing algorithms, based on a real-world dataset of chest CT scans For all other uses, contact the owner/author(s). annotated with their COVID-19 diagnosis. We developed the ma- SiKDD ’21, October, 2021, Ljubljana, Slovenia chine learning models with images provided by the Medical Physics © 2021 Copyright held by the owner/author(s). 159 SiKDD ’21, October, 2021, Ljubljana, Slovenia Rožanec and Poštuvan Research Group at the University of Ljubljana and made them avail- data[8]. Due to these reasons, care must be taken to select met- able as part of the RIS competition1. rics not sensitive to such imbalance. Among common strategies We report the models’ discrimination power in terms of the area to deal with class imbalance, we find oversampling data methods, under the receiver operating characteristic curve (AUC ROC). The which aim to increase the number of data instances of the minority AUC ROC is a widely adopted classification metric that quantifies class to balance the dataset. Oversampling methods can add data the sensitivity and specificity of the model while is invariant to a instances from existing ones by replicating them (e.g., using a näive priori class probabilities. random sampler that draws new samples by randomly sampling This paper is organized as follows. Section 2 outlines related with replacement from the available train samples), or by creating scientific works, Section 3 provides an overview of the use case, synthetic data instances (e.g., through SMOTE[9], ADASYN[19], and Section 4 details the methodology. Finally, section 5 presents or GANs). In addition to data oversampling, the Focal Loss[29] and discusses the results obtained, while Section 6 concludes and can be used on specific algorithms. The Focal Loss reshapes the describes future work. cross-entropy loss to down-weight well-classified examples while focusing on the misclassified ones, achieving better discrimination. 2 RELATED WORK Finally, while the techniques mentioned above are useful for clas- The field of radiomics is concerned with extracting high-dimensional sification, we can reframe the problem as an anomaly detection data from medical images, which can be mined to provide diagnoses problem, attempting to detect which data instances correspond to and prognoses, assuming the image features reflect an underly- the minority class (anomaly). ing pathophysiology[16, 27, 28]. While the research on the field is Through the research we reviewed, we found a paper describing experiencing exponential growth, multiple authors have warned the use of SMOTE[14], and two papers using GANs[1, 34] for data about common issues affecting the quality and reproducibility of augmentation at the image level. We found no paper performing radiomics research and proposed several criteria that should be met a more extensive assessment of the class imbalance influence nor to mitigate them (e.g., RQS, CLAIM, or TRIPOD)[10, 27, 32]. It has compared class imbalance strategies towards the COVID-19 detec-also been observed that the translation into clinical use has been tion models’ outcomes. We propose utilizing data augmentation slow[13]. techniques, generating new embeddings instead of full images. Such Since the start of the COVID-19 pandemic, much research has an approach provides similar information in the embedding space been published highlighting how AI models could be used to is- as would be obtained from synthetic images while enabling widely sue COVID-19 diagnoses based on medical images. While much used techniques for tabular data oversampling. Furthermore, in research was invested into transfer learning leveraging pre-trained GANs, new data instances are cheaper to compute and store than deep learning models, or the use of deep learning models as feature would be if creating new images. extractors[24], some authors also experimented with handcrafted features[7]. Most common machine learning approaches involved 3 USE CASE the use of deep learning (end-to-end models, or pre-trained models The research reported in this paper is done with images provided by for feature extraction)[14, 23, 34, 36, 43], Support Vector Machine the Medical Physics Research Group at the University of Ljubljana (SVM)[4, 7, 14, 22, 23, 34, 36, 38, 43], k-Nearest Neighbors (kNN)[14, and made available as part of the RIS competition. The dataset 22, 23, 38, 43], Random Forest (RF)[22, 23, 36], CART[22, 23, 36], was built from computed tomography (CT) scans obtained from Näive Bayes[22, 23], and Gradient Boosted Machines (GBM)[6, 22]. three datasets reported in[18, 25, 33], that correspond to 289 healthy Two commonly faced challenges regarding COVID-19 diagnoses persons and 66 COVID-19 patients. Healthy persons are determined based on medical images are images scarcity and class imbalance. with a CT score between zero and five, while COVID-19 patients are Given the heterogeneity of the datasets, it is not always possi- considered those with a CT score equal to or higher than ten[15]. ble to merge them[2, 7, 35]. Thus, some researchers successfully Each CT scan was segmented into twenty slices, resulting in 7.100 experimented using generative adversarial networks (GANs) to images with an axial view of the lungs, and annotated into two generate new images that comply with the existing patterns in classes: COVID-19 and non-COVID-19. The visual inspection of the dataset[1, 34]. GANs provide means to learn deep representa- CT scans aims to determine if the person was infected with the tions from labeled data and generate new data samples based on a COVID-19 disease. Automating this task reduces manual work and competition involving two models: a generator, learns to generate speeds up the diagnosis. new images only from its interaction with the discriminator; and the discriminator, who has access to the real and synthetic data 4 METHODOLOGY instances, and tries to tell the difference between them[3, 11]. While this method was first applied on images[17], new approaches were We propose using artificial intelligence for an automated COVID-19 developed to adapt it for tabular data[41]. diagnosis based on images obtained from CT scan segmentation, The fact that the classification categories are not approximately posing it as a binary classification problem. The discrimination equally represented in a dataset can affect how the machine learn- capability of the models is measured with the AUC ROC metric ing algorithms learn and their performance on unseen data, where with a cut threshold of 0.5. the distribution can be different from the one observed in training We use the ResNet-18 model[20] for feature extraction, retrieving the vector produced by the Average Pooling layer. Since the vector consists of 512 features, we perform feature selection computing 1http://tiziano.fmf.uni-lj.si/ the features’ mutual information and selecting the top K to avoid 160 Tackling Class Imbalance in Radiomics: the COVID-19 Use Case SiKDD ’21, October, 2021, Ljubljana, Slovenia √ overfitting. To obtain K, we follow the equation 𝐾 = 𝑁 suggested this approach leads to the best forecast outcomes with a GBM by[21], where N is the number of data instances in the train set. model trained with a Focal Loss on a dataset enriched with new To evaluate the models’ performance across different data aug- CTGAN generated instances. Moreover, we compare this approach mentation strategies, we apply a stratified ten-fold cross-validation. to other imbalanced data strategies, finding that Näive random Data augmentation is performed by introducing additional minority oversampling, SMOTE, and ADASYN degrade the resulting models’ class data samples on the train folds. We consider five imbalance mit- performance compared to the original dataset. Future work will igation strategies: NONE (without data augmentation), RANDOM focus on further understanding the cases where the CTGAN data (näive random sampler), SMOTE, ADASYN, and CTGAN (GAN that augmentation leads to poor results and provide an integral explain- enables the conditional generation of data instances based on a ability model for machine learning classifiers that consume image class label)[41]. No augmentation is performed on the test fold to embeddings. ensure measurements are comparable. The performance of the data augmentation strategies is measured across eight machine learning ACKNOWLEDGMENTS algorithms: SVM, kNN, RF, CART, Gaussian Näive Bayes, Multi- This work was supported by the Slovenian Research Agency. The layer Perceptron (MLP), GBM, and Isolation Forest (IF)[30]. Finally, authors acknowledge the Medical Physics Research Group at the we compare the performance of the data augmentation scenarios University of Ljubljana2 for providing the image segmentation data computing the average AUC ROC across the test folds and assess as part of the RIS competition3. if the difference is statistically significant by using the Wilcoxon signed-rank test, using a p-value of 0.05. REFERENCES [1] Erdi Acar, Engin Şahin, and İhsan Yılmaz. 2021. Improving effectiveness of 5 RESULTS AND ANALYSIS different deep learning-based models for detecting COVID-19 from computed tomography (CT) images. Neural Computing and Applications (2021), 1–21. When comparing the results across different imbalance mitigation [2] Parnian Afshar, Shahin Heidarian, Nastaran Enshaei, Farnoosh Naderkhani, strategies (see Table 1), we observed that data augmentation leads Moezedin Javad Rafiee, Anastasia Oikonomou, Faranak Babaki Fard, Kaveh to inferior results in most cases. While this outcome was expected Samimi, Konstantinos N Plataniotis, and Arash Mohammadi. 2021. COVID- CT-MD, COVID-19 computed tomography scan dataset applicable in machine for IF (the minority class is no longer an outlier after data augmen- learning and deep learning. Scientific Data 8, 1 (2021), 1–8. tation), we found that only the CART, MLP, and GBM algorithms [3] Alankrita Aggarwal, Mamta Mittal, and Gopi Battineni. 2021. Generative adver- sarial network: An overview of theory and applications. achieved better performance with CTGAN data augmentation com- International Journal of Information Management Data Insights (2021), 100004. pared to the original dataset. Moreover, six algorithms achieved [4] Dhurgham Al-Karawi, Shakir Al-Zaidi, Nisreen Polus, and Sabah Jassim. 2020. the best results when augmented with CTGAN compared to other Machine learning analysis of chest CT scan images as a complementary digital test of coronavirus (COVID-19) patients. MedRxiv (2020). data imbalance strategies (except NONE). We confirmed the AUC [5] William E Allen, Han Altae-Tran, James Briggs, Xin Jin, Glen McGee, Andy Shi, ROC differences between imbalanced datasets strategies were sta- Rumya Raghavan, Mireille Kamariza, Nicole Nova, Albert Pereta, et al. 2020. tistically significant, with a few exceptions: Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and SMOTE vs. ADASYN testing. Nature human behaviour 4, 9 (2020), 972–982. for CART, MLP, and GBM; NONE vs. RANDOM for CART; NONE [6] Eduardo J Mortani Barbosa, Bogdan Georgescu, Shikha Chaganti, Gorka Bastar- vs. SMOTE for Näive Bayes; RANDOM vs. SMOTE for SVM and RF; rika Aleman, Jordi Broncano Cabrero, Guillaume Chabin, Thomas Flohr, Philippe Grenier, Sasa Grbic, Nakul Gupta, et al. 2021. Machine learning automatically de- and RANDOM and SMOTE vs. CTGAN for SVM and IF. From the tects COVID-19 using chest CTs in a large multicenter cohort. European radiology results obtained, we consider the CTGAN success can be attributed (2021), 1–11. to the fact the generative model can learn over time to generate [7] Mucahid Barstugan, Umut Ozkaya, and Saban Ozturk. 2020. Coronavirus (covid- 19) classification using ct images by machine learning methods. arXiv preprint high-quality data instances based on the discriminator’s feedback arXiv:2003.09424 (2020). loop, while Näive random sampling reuses existing instances (pro- [8] Nitesh V Chawla. 2009. Data mining for imbalanced datasets: An overview. Data viding little new information to the dataset), and the SMOTE and mining and knowledge discovery handbook (2009), 875–886. [9] Nitesh V Chawla, Kevin W Bowyer, Lawrence O Hall, and W Philip Kegelmeyer. ADASYN algorithms generate new samples based on heuristics 2002. SMOTE: synthetic minority over-sampling technique. Journal of artificial without learning capabilities. intelligence research 16 (2002), 321–357. [10] Gary S Collins, Johannes B Reitsma, Douglas G Altman, and Karel GM Moons. We observed that GBM models trained with a Focal Loss achieved 2015. Transparent reporting of a multivariable prediction model for individual the best results in all datasets. Even when no data augmentation is prognosis or diagnosis (TRIPOD): the TRIPOD statement. Journal of British performed and the RF achieves the best result, the difference is not Surgery 102, 3 (2015), 148–158. [11] Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sen- statistically significant compared to the GBM model. The overall gupta, and Anil A Bharath. 2018. Generative adversarial networks: An overview. best performance was obtained with a GBM model trained over a IEEE Signal Processing Magazine 35, 1 (2018), 53–65. dataset with CTGAN data augmentation. While the reasons behind [12] Thays Maria Costa de Lucena, Ariane Fernandes da Silva Santos, Brenda Regina de Lima, Maria Eduarda de Albuquerque Borborema, and Jaqueline de Azevêdo Silva. the performance drop for the kNN, Näive Bayes, RF, and SVM 2020. Mechanism of inflammatory response in associated comorbidities in models remain unclear, further investigation is required to clarify COVID-19. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 14, 4 (2020), 597–600. them. Nevertheless, we consider the CTGAN data augmentation [13] Daniel Pinto Dos Santos, Matthias Dietzel, and Bettina Baessler. 2021. A decade on the embeddings space approach is promising. of radiomics research: are images really data or just patterns in the noise? [14] El-Sayed M El-Kenawy, Abdelhameed Ibrahim, Seyedali Mirjalili, Marwa Met- wally Eid, and Sherif E Hussein. 2020. Novel feature selection and voting classi- 6 CONCLUSION fier algorithms for COVID-19 classification in CT images. IEEE Access 8 (2020), 179317–179335. This research presents a novel approach towards data augmentation in radiomics by generating new data instances in the embedding 2https://medfiz.si/en space rather than generating new images. We demonstrate that 3http://tiziano.fmf.uni-lj.si/ 161 SiKDD ’21, October, 2021, Ljubljana, Slovenia Rožanec and Poštuvan Class Imbalance Mitigation CART IF kNN MLP Naive Bayes RF SVM GBM Strategies NONE 0,6429 0,6802 0,8504 0,7879 0,6653 0,8601 0,8066 0,8555 RANDOM 0,6402 0,5215 0,7846 0,7993 0,6464 0,6691 0,6888 0,8150 SMOTE 0,6147 0,5607 0,6813 0,7663 0,6590 0,6660 0,6817 0,7826 ADASYN 0,6020 0,5863 0,6660 0,7655 0,6282 0,6435 0,6652 0,7787 CTGAN 0,7401 0,5340 0,8118 0,8419 0,6395 0,7090 0,6896 0,8871 Table 1: Average AUC ROC values obtained across the ten cross-validation folds. Best results are bolded, second-best results are highlighted in italics. [15] Marco Francone, Franco Iafrate, Giorgio Maria Masci, Simona Coco, Francesco [30] Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. 2008. Isolation forest. In 2008 Cilia, Lucia Manganaro, Valeria Panebianco, Chiara Andreoli, Maria Chiara eighth ieee international conference on data mining. IEEE, 413–422. Colaiacomo, Maria Antonella Zingaropoli, et al. 2020. Chest CT score in COVID- [31] Hossein Mohammad-Rahimi, Mohadeseh Nadimi, Azadeh Ghalyanchi- 19 patients: correlation with disease severity and short-term prognosis. European Langeroudi, Mohammad Taheri, and Soudeh Ghafouri-Fard. 2021. Application of radiology 30, 12 (2020), 6808–6817. machine learning in diagnosis of COVID-19 through X-ray and CT images: a [16] Robert J Gillies, Paul E Kinahan, and Hedvig Hricak. 2016. Radiomics: images scoping review. Frontiers in cardiovascular medicine 8 (2021), 185. are more than pictures, they are data. Radiology 278, 2 (2016), 563–577. [32] John Mongan, Linda Moy, and Charles E Kahn Jr. 2020. Checklist for artificial [17] Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, intelligence in medical imaging (CLAIM): a guide for authors and reviewers. Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial [33] Sergey P Morozov, Anna E Andreychenko, Ivan A Blokhin, Pavel B Gelezhe, nets. Advances in neural information processing systems 27 (2014). Anna P Gonchar, Alexander E Nikolaev, Nikolay A Pavlov, Valeria Yu Chernina, [18] Stephanie A Harmon, Thomas H Sanford, Sheng Xu, Evrim B Turkbey, Hol- and Victor A Gombolevskiy. 2020. Mosmeddata: data set of 1110 chest ct scans ger Roth, Ziyue Xu, Dong Yang, Andriy Myronenko, Victoria Anderson, Amel performed during the covid-19 epidemic. Digital Diagnostics 1, 1 (2020), 49–59. Amalou, et al. 2020. Artificial intelligence for the detection of COVID-19 pneu- [34] Jawad Rasheed, Alaa Ali Hameed, Chawki Djeddi, Akhtar Jamil, and Fadi Al- monia on chest CT using multinational datasets. Nature communications 11, 1 Turjman. 2021. A machine learning-based framework for diagnosis of COVID-19 (2020), 1–7. from chest X-ray images. Interdisciplinary Sciences: Computational Life Sciences [19] Haibo He, Yang Bai, Edwardo A Garcia, and Shutao Li. 2008. ADASYN: Adaptive 13, 1 (2021), 103–117. synthetic sampling approach for imbalanced learning. In 2008 IEEE international [35] Michael Roberts, Derek Driggs, Matthew Thorpe, Julian Gilbey, Michael Yeung, joint conference on neural networks (IEEE world congress on computational intelli- Stephan Ursprung, Angelica I Aviles-Rivero, Christian Etmann, Cathal McCague, gence). IEEE, 1322–1328. Lucian Beer, et al. 2021. Common pitfalls and recommendations for using machine [20] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning to detect and prognosticate for COVID-19 using chest radiographs and learning for image recognition. In Proceedings of the IEEE conference on computer CT scans. Nature Machine Intelligence 3, 3 (2021), 199–217. vision and pattern recognition. 770–778. [36] Prottoy Saha, Muhammad Sheikh Sadi, and Md Milon Islam. 2021. EMCNet: [21] Jianping Hua, Zixiang Xiong, James Lowey, Edward Suh, and Edward R Automated COVID-19 diagnosis from X-ray images using convolutional neural Dougherty. 2005. Optimal number of features as a function of sample size network and ensemble of machine learning classifiers. Informatics in medicine for various classification rules. Bioinformatics 21, 8 (2005), 1509–1515. unlocked 22 (2021), 100505. [22] Lal Hussain, Tony Nguyen, Haifang Li, Adeel A Abbasi, Kashif J Lone, Zirun [37] Adekunle Sanyaolu, Chuku Okorie, Aleksandra Marinkovic, Risha Patidar, Kokab Zhao, Mahnoor Zaib, Anne Chen, and Tim Q Duong. 2020. Machine-learning Younis, Priyank Desai, Zaheeda Hosein, Inderbir Padda, Jasmine Mangat, and classification of texture features of portable chest X-ray accurately classifies Mohsin Altaf. 2020. Comorbidity and its impact on patients with COVID-19. SN COVID-19 lung infection. BioMedical Engineering OnLine 19, 1 (2020), 1–18. comprehensive clinical medicine (2020), 1–8. [23] Seifedine Kadry, Venkatesan Rajinikanth, Seungmin Rho, Nadaradjane Sri Mad- [38] Ahmet Saygılı. 2021. A new approach for computer-aided detection of coronavirus hava Raja, Vaddi Seshagiri Rao, and Krishnan Palani Thanaraj. 2020. Development (COVID-19) from CT and X-ray images using machine learning methods. Applied of a machine-learning system to classify lung ct scan images into normal/covid-19 Soft Computing 105 (2021), 107323. class. arXiv preprint arXiv:2004.13122 (2020). [39] H Swapnarekha, Himansu Sekhar Behera, Janmenjoy Nayak, and Bighnaraj Naik. [24] Sara Hosseinzadeh Kassania, Peyman Hosseinzadeh Kassanib, Michal J Wesolows- 2020. Role of intelligent computing in COVID-19 prognosis: A state-of-the-art kic, Kevin A Schneidera, and Ralph Detersa. 2021. Automatic detection of coron- review. Chaos, Solitons & Fractals 138 (2020), 109947. avirus disease (COVID-19) in X-ray and CT images: a machine learning based [40] Tianbing Wang, Zhe Du, Fengxue Zhu, Zhaolong Cao, Youzhong An, Yan Gao, approach. Biocybernetics and Biomedical Engineering 41, 3 (2021), 867–879. and Baoguo Jiang. 2020. Comorbidities and multi-organ injuries in the treatment [25] Michael T Kassin, Nicole Varble, Maxime Blain, Sheng Xu, Evrim B Turkbey, of COVID-19. The Lancet 395, 10228 (2020), e52. Stephanie Harmon, Dong Yang, Ziyue Xu, Holger Roth, Daguang Xu, et al. 2021. [41] Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni. Generalized chest CT and lab curves throughout the course of COVID-19. Scien- 2019. Modeling tabular data using conditional gan. arXiv preprint arXiv:1907.00503 tific reports 11, 1 (2021), 1–13. (2019). [26] Virendra Kumar, Yuhua Gu, Satrajit Basu, Anders Berglund, Steven A Eschrich, [42] Jing Yang, Ya Zheng, Xi Gou, Ke Pu, Zhaofeng Chen, Qinghong Guo, Rui Ji, Haojia Matthew B Schabath, Kenneth Forster, Hugo JWL Aerts, Andre Dekker, David Wang, Yuping Wang, and Yongning Zhou. 2020. Prevalence of comorbidities in Fenstermacher, et al. 2012. Radiomics: the process and the challenges. Magnetic the novel Wuhan coronavirus (COVID-19) infection: a systematic review and resonance imaging 30, 9 (2012), 1234–1248. meta-analysis. Int J Infect Dis 10, 10.1016 (2020). [27] Philippe Lambin, Ralph TH Leijenaar, Timo M Deist, Jurgen Peerlings, Eve- [43] Huseyin Yasar and Murat Ceylan. 2021. A novel comparative study for detection lyn EC De Jong, Janita Van Timmeren, Sebastian Sanduleanu, Ruben THM Larue, of Covid-19 on CT lung images using texture analysis, machine learning, and deep Aniek JG Even, Arthur Jochems, et al. 2017. Radiomics: the bridge between learning methods. Multimedia Tools and Applications 80, 4 (2021), 5423–5447. medical imaging and personalized medicine. Nature reviews Clinical oncology 14, [44] Stephen SF Yip and Hugo JWL Aerts. 2016. Applications and limitations of 12 (2017), 749–762. radiomics. Physics in Medicine & Biology 61, 13 (2016), R150. [28] Philippe Lambin, Emmanuel Rios-Velazquez, Ralph Leijenaar, Sara Carvalho, [45] Kun-Hsing Yu, Andrew L Beam, and Isaac S Kohane. 2018. Artificial intelligence Ruud GPM Van Stiphout, Patrick Granton, Catharina ML Zegers, Robert Gillies, in healthcare. Nature biomedical engineering 2, 10 (2018), 719–731. Ronald Boellard, André Dekker, et al. 2012. Radiomics: extracting more informa- tion from medical images using advanced feature analysis. European journal of cancer 48, 4 (2012), 441–446. [29] Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. 2017. Focal loss for dense object detection. In Proceedings of the IEEE international conference on computer vision. 2980–2988. 162 Observing Water-Related Events for Evidence-Based Decision-Making Joao Pita Costa * *****, M. Besher Massri *, Inna Novalija *, Ignacio Casals del Busto **, Iulian Mocanu ***, Maurizio Rossi ****, Jan Šturm *, Eva Erzin *, Alenka Guček *, Matej Posinković *, Marko Grobelnik * ***** * Institute Jozef Stefan, Slovenia, ** Aguas del Alicante, Spain, *** Apa Braila, Romania, **** Ville de Carouge, Switzerland, ***** Quintelligence, Slovenia ABSTRACT propose a slightly different approach that integrates heterogeneous data sources to try and solve common With the awareness of a changing climate impacting our research questions, as well as to support water management sustainability, and in line with the European Green Deal companies in their current problems. This solution is named initiative or the Sustainable Development Goal 6 addressing NAIADES Water Observatory (NWO), available at water, the industry, society and local governments are naiades.ijs.si, putting together: (i) real-time information from requiring reliable and comprehensive technology that can multilingual world news on water topics; (ii) data provide them an overview to water events to anticipate visualisation of water-related indicators through time, problems and the tools to analyse best practices appropriate sourced from the datasets associated with the Sustainable to solve them. This paper presents the NAIADES Water Development Goal 6 (water) and other UN data (see Figure Observatory (NOW), a digital solution offering a series of 1); and (iii) scientific knowledge from published biomedical analysis and visualisations of water-related topics, helping research on water-related topics (e.g., water contamination). users to extract important insights in relation to the water Due to the rapidly growing awareness of the sustainability sector. Taking advantage of heterogeneous data sources, from challenges that we are facing in Europe and worldwide in the the media and social media landscape, to published research context of water resource management, there has been much and global/local indicators. Through collaboration with local work done to develop systems that are able to collect water resource management institutions, the NWO was information about the available water and even simulate and configured to local priorities and ingests local datasets to forecast that in the near future. But these are usually better fit the needs of decision-makers. geolocation-based systems ingesting water-related data to enable real-time monitoring of resources and usage [x] [y] [z], CCS CONCEPTS and thus much different than the water observatory that we • Real-time systems • Data management systems • Life and are proposing in this paper. The typical example is GoAigua medical science system [4], a digital twin technology allowing, e.g., the city of Valencia to optimize its water management at the network KEYWORDS level, improving efficiency in daily operations, plan real-time Water Resource Management, Smart Water, Observatory, scenarios, and make some prediction on its future behaviour Water Digital Twin, Elasticsearch, Streamstory [5]. 1 Introduction The water sector is facing rapid development towards the smart digitalisation of resources, much motivated and supported by the UN’s global initiative for the Sustainable Development Goal 6. In that context, the efforts to address the specific challenges related to water management data and priorities multiply globally. There are several “digital twin” systems dedicated to water, each of which focuses on the Figure 1: Visualisation of water-related indicators within different aspects of the digitalisation of signals to support Spain to complement the global indicators view ingesting water management companies, as well as water data from, e.g., U.N. and the World Bank. “observatories”. These are usually meant as Geographical Information Systems that showcase the different aspects of water resources through time. 2 A data-driven solution for water events Within the scope of the European Commission-funded project The proposed Water Observatory enables extraction of NAIADES [1] focusing on the automation of the water insightful water-related information, configured to use case resource management and environmental monitoring, we priorities and needs from the data integration of 163 SIKDD’21, October 2021, Ljubljana, Slovenia J. Pita Costa et al. heterogeneous sources. This includes information from social ● Media: each location has its own news and social media media when the weather is favourable for floods and the streams configured to priorities and aspects of the news historical information from news and published research on that stakeholders define as topics of interest (e.g. floods) these weather-related events and how to make better ● Research: similarly to the media sources, the research decisions to solve them. topics allow for some customisation to fit the needs of This is complemented by data ingested from global and local the local user better indicators (i.e., datasets at regional level), showcasing the ● Resources: the natural resources information provided observation of water-related datasets linked to SDG 6 at for exploration is geolocated to the regions of interest to global and country levels that can help us observe changes the user of the platform and trends. The NAIADES Water Observatory enables the It is relatively easy to include new use cases and user to explore the information provided by published corresponding workspaces after the discussions on user science and the success stories that can be used in decision- priorities that will allow us to configure the information making and water education at the local level (i.e., showcasing presented and making it meaningful. the resources and problematics of the region). In this approach, the water data sensing is done over dynamic open data sources that serve as digital sensors (news, social 3 Addressing the challenges of tomorrow media, indicators, publications, weather forecasts). This data With the range of views provided at the observatory, the is then integrated and visualised, each in its tab, addressing problems addressed can be of complex nature and cover a specific topics of interest. The observatory is thus composed range of concerns and workflows. The different ICT of all that heterogeneous data coming in at different capabilities available across the water sector require intuitive frequencies. The interactions between those data sources to and meaningful technologies to ensure the usefulness of the solve common problems make it a Water Digital Twin. The contribution to the Community. The target users of the NWO envisioned examples include the analysis of best practices in seem to belong to three main scenarios with different water events in, e.g. Braila, identified in the news and workflows that can be supported by the developed explored over the published research, or the alerts triggered technology: by weather conditions and observed over social media on a 1. Water resource management: using the provided water event. The questions we are trying to solve with this information in the resolution of problems related to innovative technology are, e.g., if we can predict water weather events to understand how their actions are shortages in a certain region given the historical data; or if we perceived by the consumers and to explore successful can identify early signals of water-related problems from scenarios in similar cases social media (see Figure 2). 2. Local governments: to help evidence-based decision- making using open data, better synchronise to SDG6 and other guidelines and evaluate commitments in time 3. General public: for water education with a local context, in aspects that matter to the local population, based on parts of the Water Observatory that can be open to public The priorities in the European Union are rapidly changing towards sustainability and environmental efficiency, transversally to most domains of action. The European Commission’s Green Deal [3] aiming for a climate-neutral Europe by 2050 and boosting the economy through green Figure 2: Analysis of the sentiment in water-related posts in Twitter and the relation to consumer satisfaction and technology provides a new framework to understand and water-related events position water resource management in the context of the challenges of tomorrow. The NAIADES Water Observatory All of the views of this observatory, each of which represents will not only contribute to the improvement of European digital solutions on their own, are configured to the local sustainability in water-related matters but will also assign the priorities of the NAIADES users as a Proof of Concept, local actors on the water resource management an active role showing that each can address specific conditions. in that. The NAIADES Water Observatory provides the user of ● Indicators: adding to the global UN indicators, we are the NAIADES platform, as earlier extensively discussed, with ingesting curated open datasets that have regional the global and local insight that can be transformed into information about water topics of interest to the business intelligence, and help companies to steer their stakeholder strategies towards customer satisfaction. We will be 164 Observing Water-Related Events for Evidence-based Decision- SIKDD’21, October 2019, Ljubljana, Slovenia Making describing selected views of this observatory through the enabled sites across the world. From the data management verticals (or views) News – Indicators – Biomedical, first at module the real-time news data is accessed by the news the level of the specific dashboards that constitute the tabs in dashboard that can be configured by the NAIADES user to the online instance, and then by the extended exploratory tune the topics of interest in the configuration web app. To instances, including public instances and APIs, for each of the further explore a water-related topic, the NWO provides a three verticals. dashboard for the analysis of social media posts in Twitter (see Figure 2), collected in a real-time frequency, where sentiment is analysed, related concepts are extracted and it is possible to access the raw tweets or apply several filters. Finally, the biomedical module allows for the exhaustive exploration of water contamination information from scientific research articles published worldwide and available through the MEDLINE biomedical open dataset [9] and the Microsoft Academic Graph [8]. The MEDLINE dataset is collected from the official FTP source made available by the North American National Library of Medicine (NLM) over an Figure 3: The global view of the pilot 1 over usage and data XML dump and uploaded to the elasticSearch data sources. management system through a python script, the Microsoft Academic Graph dataset is collected from an Azure container These dashboards come together to provide the user with a with the data biweekly updated by the Microsoft Research global perspective in real-time, where five different tiers of team. The data management is based on the elasticsearch usability are made available (see Figure 3). The tiers allow for technology [2, useful for both the interactive data the extended usability of the Water Observatory, visualisations and the Indicators Explorer view. The latter Transversally to the data sources available. allows the NAIADES user to explore the raw data through template visualisations, use a Lucene-based query that can 4 System description and architecture leverage the loaded metadata, and easily build visualisation The NWO offers user exploratory dashboards for the further modules that can define a new dashboard of data investigation over news, to get deeper into the indicators visualisation modules. The dataset is then called over and ingested, and to explore the biomedical research on water HTTP API by the SearchPoint technology [6] to load the contamination in detail. Moreover, each of the three dataset and respective metadata. thus allowing for powerful dashboards have versions built to be exposed by, e.g., iframe Lucene-based queries and further interaction over a movable through a publicly available channel that can be used for pointer. This will lead to the refinement of the search of integration in high management KPI-monitoring dashboards. information that can then be extended over the Biomedical Furthermore, we also offer a part of the information in these Explorer, which feeds over the same dataset through Kibana, through APIs easily integrable with our own systems. but also allows for the analysis of raw data, or the easy The Indicators view provides the user with interactive data construction of data visualisation modules from templates, exploration tools that allow for the KPI-monitoring over and for an interactive data visualisation dashboard. All the several water-related topics that include the SDG 6, the World mentioned dashboards can be made publicly available Bank Open Data, the UN data, etc. In this module we also through, e.g., iframe to be integrated in high-management KPI ingest regional data sources that include local indicators, monitors. addressing the user’s priorities. Considering their well- established data types, the data integration is possible and, whenever limitations appear due to lack or poor quality of the data, the dataset is pre-processed to allow for data completion (whenever possible), or at least the improvement of data quality. The Media view provides the user with the real-time news monitoring over water-related topics (such as Water Scarcity and Water Contamination), and the analysis of water-related tweets based on data visualisation modules. Based on the news engine Eventregistry [7] this view provides the system Figure 4: System architecture of the NAIADES Water Observatory showcasing the relation between used with a continuous stream of news articles, sourced from RSS- technologies and NOW views 165 SIKDD’21, October 2021, Ljubljana, Slovenia J. Pita Costa et al. 5. Conclusions and further work In this paper we discussed the technological development and research opportunities motivated by the emerging need to support decision-makers with evidence from open data that can retract best practices and answer questions from the collected data, bringing the digitalisation of the water sector to a new level. The potential to ingest complementary local data and configure global sources to parameters addressing local priorities provides a local dimension that is being explored Figure 6: The multi time-series analysis of the weather close to the priorities of the NAIADES data providers within parameters, using Markov chains in complex data water resource management institutions. It will also be visualisation through the Streamstory technology [9]. exploring the insights driven by the appropriate aspects of chosen datasets, e.g., between news data and focused ACKNOWLEDGMENTS interactions through Twitter for weather-related events when the weather is likely to be favourable to their cause (see We thank the support of the European Commission on the Figure 5). There are many systems that can collect business H2020 NAIADES project (GA nr. 820985). intelligence data, but we believe that the “digital twin”-type of insight is in the interaction between these data streams. REFERENCES [1] CORDIS, "NAIADES Project". [Online]. Available: https://cordis.europa.eu/project/id/820985 [Accessed 1 9 2020]. [2] Elasticsearch, "Elasticsearch," 2020. [Online]. Available: https://www.elastic.co/elasticsearch/. [Accessed 1 9 2020]. [3] European Commission, "European Green Deal," 2019. [Online]. Available: https://ec.europa.eu/info/strategy/priorities-2019-2024/european- green-deal_en. [Accessed 1 9 2020]. [4] Idrica, "GoAigua: Smart Water for a Better World," 2020. [Online]. Available: https://www.idrica.com/goaigua/. [Accessed 1 9 2020]. [5] Idrica, "Digital Twin: implementation and benefits for the water sector," 19 2 2020. [Online]. Available: https://www.idrica.com/blog/digital- Figure 5: Preliminary data analysis of the relation twin-implementation-benefits-water-sector/. [Accessed 1 9 2020]. between news and tweets on water-related events and [6] Institute Jozef Stefan, "Streamstory". [Online]. Available: their relations with other topics (e.g., weather). http://streamstory.ijs.si/. [Accessed 26 8 2021] [7] G. Leban, B. Fortuna, J. Brank and M. Grobelnik, "Event registry: learning about world events from news," Proceedings of the 23rd International Further development to the NAIADES Water Observatory, Conference on World Wide Web, pp. 107-110, 2014. will be providing the users with tools to explore the impact of [8] Microsoft, "Microsoft Academic Graph". [Online]. Available: https://www.microsoft.com/en-us/research/project/microsoft- natural resources as, e.g., the weather, as well as predictions academic-graph/. [Accessed 26 8 2021] on the levels of the available bodies of water, based on [9] National Library of Medicine, "MEDLINE". [Online]. Available: https://www.nlm.nih.gov/medline/medline_overview.html. [Accessed 26 ingested weather data from the ECMWF (on humidity, 8 2021] temperature and rainfall) and other open data sources. This [10] L. Stopar, P. Škraba, M. Grobelnik, and D. Mladenić (2018). StreamStory: Exploring Multivariate Time Series on Multiple Scales. IEEE transactions will help the users to have some insight on the impact of the on visualization and computer graphics 25.4: 1788-1802. climate crisis in regions that directly relate to their water resources. We will use a sophisticated engine - Streamstory [6][10] - to explore the states of that weather-related data and short/medium term predictions on aspects of that data (see Figure 6). 166 Anomaly Detection on Live Water Pressure Data Stream Gal Petkovšek Matic Erznožnik Klemen Kenda Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova 39, 1000 Ljubljana, Jamova 39, 1000 Ljubljana, Jožef Stefan International Slovenia Slovenia Postgraduate School gal.petkovsek@ijs.si matic.erznoznik@ijs.si Jamova 39, 1000 Ljubljana, Slovenia klemen.kenda@ijs.si ABSTRACT The algorithms in this paper were already considered in the We present the application of several anomaly detection related work in different settings and for different time series. algorithms to water pressure data streams. We evaluate their quality on unlabelled data sets using agreement rates. Anomaly detection can be used by estimating the expected The applied algorithms are the Generative Adversarial Net- regular interval in the upcoming measurement. This can be work (GAN), DBSCAN, Welford’s algorithm and Facebook achieved in an incremental fashion with a simple short-term Prophet. We found that GAN performed best. prediction model, for example with Kalman filter [7], or with a more advanced approach, based on time-series modeling Keywords [11]. The latter can be used in several settings, for example water management, machine learning, anomaly detection in detecting air temperature anomalies in the sewer systems [12]. 1. INTRODUCTION DBSCAN [10] is a data clustering algorithm that can be ap- In last decades, Internet of Things (IoT) has penetrated plied in frequently changing data sets. Its incremental ver- and shaped several fields such as energy management, traf- sion [5] can be used in a streaming setting. The potential of fic, health care and others. The water sector is, however, the algorithm for anomaly detection has been demonstrated still implementing IoT solutions that will improve the water in several use cases, for example in detecting air temperature management with features such as real-time consumption anomalies [3]. prediction, leakage detection, water quality estimation and others. The paper that demonstrated the use of Generative Ad- versarial Networks for anomaly detection on data stream is In the presented work, we focus on the anomaly detection on fairly recent [6]. The authors have shown that this approach the live water pressure data stream from the town of Braila can outperform several other baselines on data sets obtained (Romania). The overall goal of the research is to detect leak- from NASA, Yahoo, Amazon etc. They introduced different age points in the city’s water distribution network. To detect measures of evaluating the reconstruction accuracy, which the presence of a leakage in the system we apply an anomaly we tried to improve upon in our paper. detection algorithm to the water pressure data stream. We considered several such algorithms, which were applied and In this work, we use the already established anomaly detec- evaluated on four data streams obtained from four pressure tion approaches and compare their performance on an unla- sensors. Our goal was to find the algorithm which returns beled water pressure data stream from a water distribution the best results. Since the data is not labeled (regular or network. A more detailed description of the algorithms is anomalous), the estimation of accuracy was done with a given in the Methodology section. We argue that the rela- method considering relative agreement among selected al- tive agreement approach [1] improves the anomaly detection gorithms [1]. The anomaly detection algorithms that were performance, which we demonstrate by manual evaluation tested were GAN (generative adversarial networks) [6], DB- of the results. SCAN [10], Welford’s algorithm [9] and anomaly detection with Facebook Prophet [11]. It is important to note that first three algorithms consider the data stream as an actual 2. DATA AND DATA PREPROCESSING live stream. This means that they consume one sample at We demonstrate our anomaly detection methodology on four a time (or a feature vector containing multiple past values, data sets. Each of the data sets represents the pressure val- enrichment values and contextual data) and declare it reg- ues of one of the sensors, which are located at different points ular or anomalous as the algorithms were intended to do in in Braila’s water distribution network. The sensors are la- production. In contrast, the Facebook Prophet consumes beled as ‘5770’, ‘5771’, ‘5772’ and ‘5773’. The data sets the whole data stream as a batch and labels all the samples contain between 10 and 11 thousand instances, which are together. This makes it unusable in production (in this set- spaced in 15 minute intervals, so about 100 days-worth of ting), however it is included in the experiment since it can data. The data was first pre-processed to remove any du- help to estimate the accuracy of other algorithms. plicated points and ‘holes’ in the data which were formed as a consequence of sensor down-time. When working with Anomaly detection on time series is a well researched field. data streams, this process should be done automatically to 167 avoid any incorrect analysis when feeding the data into the errors (4 standard deviations from the mean of the window). anomaly detection algorithms. Each of the four data sets We used a slightly different approach using the moving aver- was split into a training and evaluation part. The training age multiplied by a constant as the threshold. This proved sets consisted of the first 2000 data points and the evalu- to be easier to implement on our live data stream use-case. ation sets contained all the rest. This is done so that the algorithms which require training can be trained on one part of the data and evaluated on the other (GAN, DBSCAN). 3.3 DBSCAN DBSCAN [4] is a well-known data clustering algorithm. It 3. METHODOLOGY groups together points, which are close together based on 3.1 Evaluation of algorithms Euclidean distance. The group with the largest number of points in our case are considered ‘normal’, and the lower- Evaluation of the performance of algorithms on unlabelled density groups are outliers which are then labeled as an data always represents a challenge. Since we are work- anomaly. The parameter which measures how close the ing with such data an actual calculation of accuracy scores points should be for them to still be considered of the same would require manual labelling of the data instances. To group, can be adjusted based on the data set, and the de- avoid this time-consuming process, we use a method for es- sired sensitivity of the algorithm. For DBSCAN we also use timating error rates (ratio of wrong classifications to the an input vector composed of consecutive pressure values. In total number of instances) from the agreement rates of mul- this case, we discovered that a vector of 5-6 values works tiple algorithms. Agreement rate of two classifiers fi and fj best. is defined in the following way: S 1 X a 3.4 Welford’s algorithm {i,j} = I{fi(Xs) = fj (Xs)} S s=1 Welford’s algorithm gets its name from the Welford’s method for online estimation of mean and variance. A very simple where X1, ..., XS are unlabeled samples. The calculated anomaly detection approach [9] can then be constructed by agreement rates are then inserted into the following equa- defining the upper and lower limits (UL and LL) of ”normal” tions: data as a function of mean and variance: a{i, j} = 1 − e{i} − e{j} + 2e{i,j} U L = mean + X ∗ variance Here we assume that the functions make independent errors we can substitute e{i, j} with e{i}e{j}. With such a system of equations we can then calculate error rates using some LL = mean − X ∗ variance root-finding algorithm. Such an approach has been previ- X is fixed and determines the threshold band. Any instance ously used for the evaluation of classifiers on an unlabelled which falls out of that band is labeled as an anomaly. In- dataset [1]. Therefore we consider the anomaly detection stances can then be input into the algorithm one by one to algorithm as a binary classifier and use the aforementioned be labeled and after each the mean and the variance (con- method for the comparison of different algorithms. Addi- sequently UL and LL also) are updated. tionally, two important assumptions were made. Firstly, we For this experiment the actual Welford’s method was not assumed that the anomaly detection algorithms were inde- used since the mean and variance were computed from the pendent and secondly, that each of those algorithms per- last 1500 samples so that they would better adapt to the forms better than a random classifier. new samples. Note that the first 1500 samples therefore Since the estimated performance of one algorithm depends could not be labeled; however, this was not a problem since on the output of the others it was important that the al- most of the other approaches required 2000 samples for fit- gorithms yield a similar percentage of anomalies. In other ting the models and the evaluation was therefore done on words, the algorithms are tuned to have similar predicted the remaining stream. However, the upper and lower limits positive condition rate (P P CR = F P +T P ). For F P +T P +F N +T N of the interval were still computed as shown above with the most data streams this means that 1%-3% of the samples value of X = 2.2. are labelled as anomalous. 3.2 GAN 3.5 Facebook Prophet The Generative Adversarial Network (GAN)[6] is an unsu- Facebook Prophet is an algorithm for time series forecast- pervised machine learning approach to anomaly detection. ing that works especially well on data streams with multiple An encoder-decoder structure of the neural network is used seasonalities [8]. Prophet also works well with missing data to first encode the input data point and then decode the which makes it a good candidate for the problem at hand. encoded one. The model learns to reconstruct the input After fitting the model it can make predictions for a cho- data point as closely as possible. The idea is that the re- sen set of timestamps presented to it. Furthermore besides construction should be better if the input data is ‘normal’ the prediction it also outputs upper and lower limits of the and worse if it is abnormal/anomalous. We use an input confidence interval for every sample. Ashrapov [2] demon- vector, which is composed of 10 consecutive values of the strates the implementation of an anomaly detection algo- uni-variate data stream. We then compare the input vec- rithm which uses this property to classify the samples inside tor to the reconstructed one using the mean squared error the confidence interval as regular and the rest as anoma- (MSE) metric. We classify the data point as ‘normal’ if the lies. The model is fitted on the entire data set and then value of the MSE is below the defined threshold. [6] calcu- makes predictions on the same data set, providing both the lated the thresholds using sliding windows on reconstruction anomaly detection and the confidence interval. 168 4. RESULTS The results of the algorithms for data stream from sensor 5770 are presented in Figures 1, 2, 3 and 4. The charts show the raw values obtained from the pressure sensors, indicating the points which are labeled as anomalies with red points. Since the data sets are unlabelled it is hard to assess the accuracy of each algorithm based on anomaly visualizations alone, but we do notice some similarities and some differ- ences. All of the algorithms are good at identifying obvious outliers (points which fall far out of the ‘normal’ range). The difference between the algorithms can be noticed when Figure 4: Anomalies found using Facebook Prophet on datas- classifying points closer to the normal range. For example tream from sensor 5770. Welford’s algorithm tends to label points as anomalies at the peaks of daily pressure fluctuation, which might not be ideal since we know that this behaviour can be considered sets are unlabeled, it is hard to determine the optimal pa- normal. More sophisticated algorithms such as GAN and rameters. We decided to tune the algorithms to have similar Prophet were also able to identify more ”subtle” anomalies. recall of 1 - 3%, as we deemed that this would make the com- parison of the algorithms the most fair. In Table 1 the shares of anomalies are presented for each separate data stream. 5770 5771 5772 5773 Algorithm anomaly anomaly anomaly anomaly share share share share GAN 1.42% 0.99% 0.77% 1.13% DBSCAN 2.63% 2.82% 2.73% 2.85% Welford’s 3.39% 3.41% 1.66% 3.16% algorithm Facebook 1.66% 1.13% 0.46% 1.40% Prophet Figure 1: Anomalies found using GAN on data stream from sensor 5770. Table 1: Shares of anomalies for all four data streams. The error rates calculated from agreement rates are shown in Table 1 for each of the data streams. Since we assumed most of the samples in the data stream were normal these error rates are not very informative out of context. We can however, observe that Prophet performed best followed by GAN, DBSCAN and Welford, respectively. The results are consistent in all four scenarios. If we take into consideration that Prophet worked on the whole data set at once when the other three were limited to one sample at a time (as it is in production) we can declare that GAN performed best out of Figure 2: Anomalies found using DBSCAN on datastream the algorithms that can detect anomalies on a live stream. from sensor 5770 5770 5771 5772 5773 Algorithm Error Error Error Error rate rate rate rate GAN 1.34% 1.38% 0.66% 1.09% DBSCAN 1.59% 1.70% 1.78% 1.81% Welford’s 2.44% 2.41% 1.10% 2.31% algorithm Facebook 1.14% 0.62% 0.39% 0.81% Prophet Table 2: Error rates estimated from agreement rates for all Figure 3: Anomalies found using Welford’s algorithm on four data streams. datastream from sensor 5770. We also considered a state-of-the-art method Isolation For- est, however it was too sensitive and therefore not usable in The recall of each algorithm can be increased or decreased the error rate calculation. by modifying parameters and thresholds. Since the data 169 5. CONCLUSIONS [10] Schubert, E., Sander, J., Ester, M., Kriegel, We have tested five anomaly detection algorithms (Gener- H. P., and Xu, X. Dbscan revisited, revisited: why ative Adversarial Network, DBSCAN, Facebook Prophet, and how you should (still) use dbscan. ACM Welford’s algorithm and Isolation Forest) on four separate Transactions on Database Systems (TODS) 42, 3 data streams of water pressure data. Out of those five the (2017), 1–21. Isolation Forest performed poorly since the share of anoma- [11] Taylor, S. J., and Letham, B. Forecasting at scale. lies found with this method was unreasonably high and was The American Statistician 72, 1 (2018), 37–45. therefore not included in the final error estimates calcula- [12] Thiyagarajan, K., Kodagoda, S., Ulapane, N., tion. and Prasad, M. A temporal forecasting driven Other approaches had similar shares of anomalies and were approach using facebook’s prophet method for therefore used to calculate agreement rates and finally the anomaly detection in sewer air temperature sensor estimated error rates of each anomaly detection algorithm. system. In 2020 15th IEEE Conference on Industrial The results were consistent for all four data streams. Prophet Electronics and Applications (ICIEA) (2020), performed best in every setting, however it looked at a data pp. 25–30. stream as a batch and it therefore could not be used for online anomaly detection. GAN performed second best fol- lowed by DBSCAN and Welford’s algorithm which all work on a live data stream. Therefore we can conclude that the most fitting algorithm to be used for anomaly detection on the live water pressure data from water distribution network is GAN. In future work, Facebook prophet could be adopted in such a way that it would also work on a live data stream since it has shown promising results in this experiment. 6. ACKNOWLEDGMENTS This paper is supported by European Union’s Horizon 2020 research and innovation programme under grant agreement No. 820985, project NAIADES (A holistic water ecosystem for digitisation of urban water sector). 7. REFERENCES [1] Antonios Platanios, E. Estimating accuracy from unlabeled data. [2] Ashrapov, I. Anomaly detection in time series with prophet library, Jun 2020. [3] Celik, M., Dadaser-Celik, F., and Dokuz, A. S. Anomaly detection in temperature data using dbscan algorithm. 2011 International Symposium on INnovations in Intelligent SysTems and Applications (2011). [4] do Prado, K. S. How dbscan works and why should we use it?, Apr 2017. [5] Ester, M., and Wittmann, R. Incremental generalization for mining in a data warehousing environment. In International Conference on Extending Database Technology (1998), Springer, pp. 135–149. [6] Geiger, A., Cuesta-Infante, A., and Veeramachaneni, K. Adversarially learned anomaly detection for time series data, 2020. [7] Kenda, K., and Mladenić, D. Autonomous sensor data cleaning in stream mining setting. Business Systems Research: International journal of the Society for Advancing Innovation and Research in Economy 9, 2 (2018), 69–79. [8] Krieger, M. Time series analysis with facebook prophet: How it works and how to use it, Mar 2021. [9] Lobo, J. L. Detecting real-time and unsupervised anomalies in streaming data: a starting point, Feb 2020. 170 Entropy for Time Series Forecasting João Costa António Costa Fakulteta za matematiko in fiziko ESN Paris joaocostamat@gmail.com antoniocbscosta@gmail.com Klemen Kenda João Pita Costa Jožef Stefan Institut IRCAI klemen.kenda@ijs.si joao.pitacosta@quintelligence.com Figure 1: Sample of the time series and projections of the embedding - This plot gives us a geometrical representation of the theory involved in section 3 and shows the reconstructed state space of the given time series. This can be obtained by using Takens’ embedding to reconstruct the time series 𝑦, given in figure a), as the markovian system 𝑌 with 𝐾 time delays and 𝐾 then use Principal Component Analysis in order to perform the change of basis of the data. The obtained projections b), c) and d) attain the dynamics of the system, which gives us the possibility to predict the time series with higher efficiency. ABSTRACT for the H2020 NAIADES Project [2] with data collected from the Municipality of Alicante (Spain). We will present this study for In this paper, we present the exploitation of a method to extract the Autobus Dataset, related to the Bus Station Areas in Alicante. information from microscopic samples of time series data in order to provide a representation of optimized stability to a chaotic sys- tem [1]. The main goal of this approach is to predict the dynamics 2 STATIONARY AND CHAOTIC NATURE of a time series and therefore develop optimized forecasting al- gorithms. First, we study how to increase the predictability of 2.1 Dickey-Fuller Test for Stationarity a system and second, we develop a Deep Learning Algorithm, In order to proceed with the theory involved in the method, namely an LSTM, that can recognize patterns in sequential data it is necessary to understand the behaviour of the time series and accurately predict the future behaviour of a time series. and its sensitivity to initial conditions. For studying time series’ stationarity, one can use the Augmented Dickey-Fuller test, which KEYWORDS is a type of statistical test called a unit root test, where generally Recurrent Neural Networks, LSTM, Entropy, Markov Chain, Clus- the null hypothesis is that the time series can be represented by tering, Time Series a unit root, which means that for 𝑦 = {𝑦 }𝑇 , the information 𝑡 𝑡 =1 at point 𝑦 does not provide us the ability to predict 𝑦 . In 𝑡 −1 𝑡 1 INTRODUCTION our case, we obtained that the p-value of the test was 0, so the null hypothesis was rejected and the time series has no unit Given its intrinsic nature, mathematics concerns with the con- root. Therefore, it is stationary and the time delays will provide struction of formal statements and proofs relating the different important information for predicting the dynamics of the time concepts within it. Its methods are used in countless ways and series. effectively model the shape of our world. But how is it possible to shape the unknown? Motivated by this question and the upmost need for finding ways of optimizing water resources for future 2.2 Lyapunov exponents for understanding generations, there has been a great development on the study of chaotic nature dynamical systems based on, for example, (Shannon) entropy [9] and phase space reconstruction [4]. In this paper, we provide an The Lyapunov Exponent is a quantifier for the sensitivity of the approach to water resource management using Deep Learning time series on initial conditions and therefore for its chaotic na- and Chaos Theory, by studying the dynamics of a time series ture. The main idea is to select an array of nearest neighbors, i.e, using the 2 main ideas cited before. This study was developed points at minimum distance, and calculate its trajectories in time. By doing so, we can then obtain an average of this divergence Permission to make digital or hard copies of part or all of this work for personal exponent which gives us the Lyapunov Exponent. Since the sys- or classroom use is granted without fee provided that copies are not made or tem is bounded, the divergence is also bounded and will reach 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 a plateau after a certain number of timesteps. In our case, the work must be honored. For all other uses, contact the owner /author(s). Lyapunov Exponent, given as the initial slope, is ≈ 518 and the Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia initial growth is exponential, as can be seen in figure 5. Therefore, © 2020 Copyright held by the owner/author(s). the time series is of a chaotic nature. 171 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia João Costa, et al. 3 MAXIMUM PREDICTABILITY Given the high variability of any chaotic system, it is hard to capture the whole set of variables that model the state space. This is characteristic of a non-Markovian system which is highly unpredictable. How do we surpass this issue? Takens’ Embedding Theorem [8] tells us that, under certain con- ditions, it is possible to use past data to reconstruct a Markovian system, thus giving us the possibility to model the initial time series with higher efficiency. We start by considering a set of ODEs 𝑥 = ( ¤ 𝑥 ) and the 1, ¤ 𝑥 2, . . . , ¤ 𝑥 𝑑 -dimensional time series 𝐷 𝑦 (𝑡 ) of duration 𝑇 which is a set of incomplete measurements of 𝑥 given by a measure 𝑀 , i.e., 𝑦 = 𝑀 (𝑥 ). Then, in order to Figure 2: An LSTM performs the following ordered compu- calculate the number of 𝐾 time delays to feed the LSTM with, tations: The first step is to forget their irrelevant history. the 𝑑 -dimensional measurements are lifted into the state space Then, LSTMs perform computation to decide on relevant 𝑑 ×𝐾 𝑌 ∈ consisting of the previously referred 𝐾 time delays parts of new information and based on the previous two 𝐾 R [3]. It is possible to quantify the chaotic measure of the system steps, they selectively update the internal state. Finally, an 𝑌 by calculating the entropy resulting from clustering. This output is generated. 𝐾 can be done by partitioning the 𝑑 × 𝐾 -dimensional space into 𝑁 Voronoi cells using 𝐾 -Means clustering. Having partitioned shown in this figure can be mathematically represented as the state space 𝑌 , the reconstructed dynamics are encoded as a 𝐾 row-stochastic transition probability matrix 𝑃 = [𝑃 ] which 𝑇 𝑖 𝑗 𝑖, 𝑗 𝑓 (𝑥 , ℎ ) = 𝜎 (𝑤 𝑥 + 𝑤 ℎ + 𝑏 ) 𝑡 𝑡 𝑡 −1 𝑡 𝑡 −1 𝑓 ,𝑥 𝑓 ,ℎ 𝑓 relates increments on the state-space density 𝑝 in the following ( ) = 𝑇 + + ) (4) way 𝑖 𝑥 , ℎ 𝜎 (𝑤 𝑥 𝑤 ℎ 𝑏 𝑡 𝑡 𝑡 −1 𝑖,𝑥 𝑡 𝑖,ℎ 𝑡 −1 𝑖 𝑇 ∑︁ 𝑜 (𝑥 , ℎ ) = 𝜎 (𝑤 𝑥 + 𝑤 ℎ + 𝑏 ), 𝑡 𝑡 𝑡 −1 𝑜 ,𝑥 𝑡 𝑜 ,ℎ 𝑡 −1 𝑜 𝑝 (𝑡 + 𝛿𝑡 ) = 𝑃 𝑝 (𝑡 ). (1) 𝑖 𝑗 𝑖 𝑗 𝑑 𝑗 where 𝑤 , 𝑤 , 𝑤 ∈ are weight parameters and 𝜎 is an 𝑓 ,𝑥 𝑖,𝑥 𝑜 ,𝑥 R activation function. The entropy rate of the initial time series 𝑦 (𝑡 ) is then approxi- mated by estimating the entropy rate (Figure 3) of the associated 4.2 Our approach Markov chain on the different time delays 𝐾 using Kolmogorov’s The core idea is to take a list of 𝑘 training sets 𝑄 0, 𝑄1, . . . , 𝑄𝑘−1 definition and testing sets 𝑃 in order to generalize the model 0, 𝑃1, . . . , 𝑃𝑘 −1 ∑︁ and do the best estimation for the time series. This is based ℎ (𝐾 ) = − 𝜋 𝑃 log 𝑃 , (2) 𝑝 𝑖 𝑖 𝑗 𝑖 𝑗 𝑁 on translating the testing sets’ partitions along the time series, 𝑖, 𝑗 0 𝑛 where the first partition 𝑃 = { } is taken from the 0 𝑝 , . . . , 𝑝 0 0 where 𝜋 is the estimated stationary distribution of the Markov zeroth point of the time series data and the last partition 𝑃 = 𝑘 −1 0 𝑛 chain 𝑃 . This approximation gives an estimate for the conditional {𝑝 , . . . , 𝑝 } until the last point of the time series data and 𝑘 −1 𝑘 −1 entropies (Figure 6), i.e., for a discrete state with delay vectors |𝑦 | ®𝐾 𝑦 = { ® 𝑦 , . . . , ® 𝑦 }, the entropy of the Markov chain provides | | = 𝑖 𝑖 +𝐾 −1 𝑃 , ∀𝑖 ∈ {0, . . . , 𝑘 − 1} (5) 𝑖 𝑘 an estimate for the conditional entropy, where |𝑦 | stands for the cardinality of the time series 𝑦. This procedure yields 𝑘 models which will use each of the training ℎ (𝐾 ) ≈ ⟨− log[𝑝 (𝑦 |𝑦 , . . . , 𝑦 )]⟩ 𝑝 𝑖 𝑁 𝑁 𝑖 +𝐾 𝑖 +𝐾 −1 sets to make predictions on the respective test sets. Given the = 𝐻 (𝑁 ) − 𝐻 (𝑁 ) 𝐾 +1 𝐾 (3) erratic nature of the data, which was taken in 15 and 30 minutes = ℎ (𝑁 ), 𝐾 samples, a resampling to 30 minute delays had to be done on the 15 minutes delay data points and a masking was added to the time where 𝐻 is the Shannon Entropy of the sequence obtained by 𝐾 series in order to neglect NaN values that could be created from partitioning the ® 𝑦 space into 𝑁 partitions. resampling. Therefore, a masking layer was added and the model is composed by 3 other layers L , L and L , where 𝑛 = 𝑛 𝑛 𝑛 1 1 2 3 4 MODEL ARCHITECTURE 𝑛 = 1 (we have a univariate timeseries) and = 64, since it gave 3 𝑛2 the best results in cross validation. A dropout regularization of 4.1 LSTM 0.1 was added for better approximation of training and validation Long Short Term Memory (LSTM) Networks are a special type errors and the batch size was set to 128. The mean squared error of Recurrent Neural Networks (RNN) which rely on gated cells for the predictions on the training set is ≈ 0.00115 and for the that control the flow of information by choosing what elements testing set is ≈ 0.00236. One can address the capacity of the model of the sequence are passed on to the next module. This idea was whose predictive results are shown in figure 4. introduced in order to surpass the vanishing gradient problem in conventional RNNs [7]. At each time 𝑡 , consider 𝑓 as the 𝑡 5 FORECASTING forget gate, 𝑖 as the input gate and 𝑜 as the output gate, which 𝑡 𝑡 5.1 Forecasting Methods are functions that depend on the output of the previous LSTM Consider a time series 𝑇 = {𝑡 }. The forecasting process module, given by ℎ and on the input of the current timestep, 1, . . . , 𝑡 𝑁 𝑡 −1 can be done in 3 ways: given by 𝑥 . Then, the next figure shows a representation of how 𝑡 a single LSTM cell performs its computations. The computations (1) iterated forecasting 172 Entropy for Time Series Forecasting Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia (2) direct forecasting 6.3 Data and Code Git Repository (3) multi-neural network forecasting The complete work can be found in: Process number (1) is based on "many-to-one" forecast for which https://github.com/johncoost/JoaoModelsForAlicante. 𝑡 ≈ F (𝑡 , . . . , 𝑡 ), 𝑖 ∈ {1, . . . , 𝑁 − 𝑛}. (6) 𝑛+1 𝑖 𝑖 +𝑛−1 7 PLOT OF RESULTS Then, a 𝐾 -step forecast can be iteratively obtained by ˆ 𝑡 := F ( ˆ 𝑡 , . . . , ˆ 𝑡 , ˆ 𝑡 ), 𝑗 ∈ 1, . . . , 𝐾 . (7) 𝑁 + 𝑗 𝑁 + 𝑗 −𝑛+1 𝑁 + 𝑗 −2 𝑁 + 𝑗 −1 Process number (2) can be characterized by training a "many-to- many" function F for which (𝑡 , . . . , 𝑡 ) ≈ F (𝑡 , . . . , 𝑡 ), (8) 𝑖 +𝑛 𝑖 +𝑛+𝐾 −1 𝑖 𝑖 +𝑛−1 where 𝑖 ∈ {1, . . . , 𝑁 − 𝑛 − 𝐾 + 1}. We can obtain a 𝐾 -step forecast by ( ˆ 𝑡 , . . . , ˆ 𝑡 ) := F (𝑡 , . . . , 𝑡 ). (9) 𝑁 +1 𝑁 +𝐾 𝑁 −𝑛+1 𝑁 Finally, process (3) is defined by 𝑘 "many-to-one" functions F which hold the following relationship 1, . . . , F𝑘 𝑡 ≈ F (𝑡 , . . . , 𝑡 ) 𝑖 +𝑛 1 𝑖 𝑖 +𝑛−1 Figure 3: Entropy Rate ℎ - The entropy rate ℎ is given as .. the function of the number of partitions 𝑁 for increasing (10) . number of delays 𝐾 (given by the different colors in a de- 𝑡 ≈ F (𝑡 , . . . , 𝑡 ), 𝑖 +𝑛+𝐾 −1 𝑘 𝑖 𝑖 +𝑛−1 scendent mode). It is possible to observe that the entropy rate is a non-decreasing function on the number of par- where 𝑖 ranges from 1 to 𝑁 − 𝑛 − 𝐾 + 1. Process (1) does not titions 𝑁 . The idea is to choose the value of 𝑁 for which require 𝑘 a propri while both process (2) and (3) are dependent the entropy is maximum so that we have the maximum on the choice of 𝑘 . possible information about the system’s dynamics. 5.2 Our Approach We chose to do a Direct Forecasting for the next 7 days by taking the last test set partition 𝑃 and did a prediction on this test 𝑘 −1 set. Although forecasting seems pretty motivating, by choosing a partition that attains more characteristics of the time series, one can achieve even better results. The achieved forecast can be seen on Figure 8 and compared with a 7 days sample on Figure 7. 6 RESEARCH METHODS 6.1 Time Series Reconstruction Consider the time series 𝑦 with duration 𝑇 as given in section 2. The idea is to add 𝐾 time delays to 𝑦 in order to obtain a ( 𝑑 ×𝐾 𝑡 − 𝐾 ) × 𝐾𝑑 space 𝑌 ∈ and further partition 𝑌 using Figure 4: Prediction on the last test set - This shows a sam- 𝐾 R 𝐾 𝑘 -means Clustering into 𝑁 Voronoi Cells. ple of the last test set and its prediction. We can observe the effectiveness of the LSTM in modelling the given time 6.2 Entropy Calculation series by having a deep understanding of its inherent dy- namics. Consider the 𝑁 Voronoi Cells given as the number of partitions of 𝑌 and consider the joint probability 𝑝 (𝑐 , . . . , 𝑐 ), {𝑖 } ∈ 𝐾 𝑖 𝑖 1, . . . , 𝑖 1 𝑙 𝑙 {0, . . . , 𝑁 − 1}. Then, the Shannon Entropy [6] is given by ∑︁ 𝐻 = − 𝑝 (𝑐 , . . . , 𝑐 ) log 𝑝 (𝑐 , . . . , 𝑐 ) (11) 𝑙 𝑖 𝑖 𝑖 𝑖 1 𝑙 1 𝑙 and the conditional probabilites are given by 𝑝 (𝑐 |𝑐 , . . . , 𝑐 ), (12) 𝑖 𝑖 𝑖 𝑙 +1 1 𝑙 where 𝑐𝑖 is the next Voronoi Cell after 𝑐 . We can calculate the 𝑙 +1 𝑖𝑙 entropy rate growth by considering the conditional probabilities of the system given the previous 𝑙 cells, when visiting the (𝑙 +1)-th cell, via ℎ = ⟨− log[𝑝 (𝑐 |𝑐 , . . . , 𝑐 )]⟩ = 𝐻 − 𝐻 (13) 𝑙 𝑖 𝑖 𝑖 𝑙 +1 1 𝑙 𝑙 +1 𝑙 Figure 5: In this figure, we can understand the initial expo- Taking the supremum limit over all possible partitions 𝑃 of 𝑌 , 𝐾 nential growth on distance between points (given in blue), we obtain the Kolmogorov-Sinai invariant of the system, relative to a curve of slope 1 (given in orange). ℎ = sup lim ℎ (𝑃 ). (14) 𝐾 𝑆 𝑙 𝑙 →∞ 𝑃 173 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia João Costa, et al. building other algorithms, such as Transformer neural network, that would provide even better results. Another idea is to use weather data and build a multivariate LSTM that optimally gives better results than the univariate one. 9 ACKNOWLEDGMENTS I greatly thank to António Carlos Costa for working in coopera- tion and giving me the possibility to use the powerful machinery he built in order to obtain the desired 𝐾 time delays and under- stand the complex dynamics of the system. Also, to the NAIADES team at Jožef Stefan Institute for all the knowledge exchange and, in particular, to Klemen Kenda for giving me the possibility of writing this paper and João Pita Costa for giving me insights on Figure 6: Conditional Entropies - In this plot we can see how to write and structure the paper. the entropy rate for number of partitions This paper is supported by European Union’s Horizon 2020 𝑁 = 200 which maximizes this entropy. This function reaches a plateau research and innovation programme under grant agreement No. at 820985, project NAIADES (A holistic water ecosystem for digiti- ≈ 24 timesteps, which gives us an idea about which is the optimal sation of urban water sector). 𝐾 to choose. Given that we have 30 minutes timesteps, this plot shows that the optimized time delay is REFERENCES of 12h which corresponds to the day and night cycles [1] Tosif Ahamed, Antonio Carlos Costa, and Greg J. Stephens. 2019. Capturing the continuous complexity of behavior in c. elegans. (2019). arXiv: 1911.10559 [q-bio.NC]. [2] 2019-2022. Cordis, "naiades project". In CORDIS. \url{https: //cordis.europa.eu/project/id/820985}. [3] Antonio Carlos Costa, Tosif Ahamed, David Jordan, and Greg Stephens. 2021. Maximally predictive ensemble dy- namics from data. (2021). arXiv: 2105.12811 [physics.bio-ph]. [4] Vicente de P. Rodrigues da Silva, Adelgicio F. Belo Filho, Vijay P. Singh, Rafaela S. Rodrigues Almeida, Bernardo B. da Silva, Inajá F. de Sousa, and Romildo Morant de Holanda. 2017. Entropy theory for analysing water resources in north- eastern region of brazil. Hydrological Sciences Journal, 62, Figure 7: 7 Days Sample 7, 1029–1038. doi: 10.1080/02626667.2015.1099789. eprint: https : / / doi . org / 10 . 1080 / 02626667 . 2015 . 1099789. https : //doi.org/10.1080/02626667.2015.1099789. [5] David A. Dickey and Wayne A. Fuller. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 366a, 427–431. doi: 10 . 1080 / 01621459 . 1979 . 10482531. eprint: https : / / doi . org / 10 . 1080 / 01621459 . 1979 . 10482531. https : //doi.org/10.1080/01621459.1979.10482531. [6] Robert M. Gray. 2011. Entropy and Information Theory. (2nd edition). Springer Publishing Company, Incorporated. isbn: 9781441979698. [7] Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short- term memory. Neural Computation, 9, 8, 1735–1780. doi: Figure 8: Prediction for 7 days ahead - Actual forecast using 10.1162/neco.1997.9.8.1735. 336 timesteps that gives a 7 day future forecast sample using [8] Floris Takens. 1981. Detecting strange attractors in tur- the LSTM model and direct forecasting. It is possible to bulence. In Lecture Notes in Mathematics. Springer Berlin observe that, as in figure 6, the values vary between ≈ 2000 Heidelberg, 366–381. doi: 10.1007/bfb0091924. to ≈ 14000 flow units and the essential dynamics of the [9] Peyman Yousefi, Gregory Courtice, Gholamreza Naser, and time series were understood by the LSTM. Hadi Mohammadi. 2020. Nonlinear dynamic modeling of urban water consumption using chaotic approach (case 8 CONCLUSION study: city of kelowna). Water, 12, 3. issn: 2073-4441. doi: 10.3390/w12030753. https://www.mdpi.com/2073- 4441/12/ Having developed all the necessary machinery for constructing 3/753. a coherent forecasting engine, we come to the conclusion that although the cardinality of the time series data was relatively small, the obtained results are promising and the model will certainly show satisfying results when applied in real time. For the future, we want to continue developing the project by 174 Modeling stochastic processes by simultaneous optimization of latent representation and target variable Jakob Jelenčič Dunja Mladenić Jozef Stefan International Jozef Stefan International Postgraduate School Postgraduate School Jozef Stefan Institute Jozef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia jakob.jelencic@ijs.si dunja.mladenic@ijs.si ABSTRACT We have evaluated the proposed method on an equities This paper proposes a novel method for modeling stochastic dataset and a cryptocurrency dataset, in both cases achieving processes, which are known to be notoriously hard to predict extraordinary results on the test dataset. We have also shown accurately. State of the art methods quickly overfit and the importance of noise distribution and how the de-noising create big differences between train and test datasets. We fails if the distributions of the data and noise do not align. present a method based on simultaneous optimization of la- tent representation and the target variable that is capable of The rest of the paper is organised as follows. Section 2 dealing with stochastic processes and to some extent reduces describes the data we were using. In section 3 we introduce the overfitting. We evaluate the method on equities and the proposed method. In section 4 we present empirical cryptocurrency datasets, specifically chosen for their chaotic results. In section 5 we conclude by pointing out the main and unpredictable nature. We show that with our method results and defining guidance for the future work. we significantly reduce overfitting and increase performance, compared to several commonly used machine learning algo- 2. DATA rithms: Random forest, General linear model and LSTM The proposed method works well for stochastic processes. deep learning model. Equities are supposed to follow some form of stochastic pro- cess [9], either the Black-Scholes one or some more complex 1. INTRODUCTION process with unknown formulation. In order to evaluate our Time series prediction has always been an interesting chal- method, we have collected daily data of more than 5000 lenge. Deep learning structures that are designed for time equities listed on NASDAQ from 2007 on. The data is freely series are prone to overfitting. Especially if the underlying available on the Yahoo Finance website [2]. We transformed time series is stochastic by nature. Every young researcher’s the data using technical analysis [10] and for test set took first attempt when dealing with time series, was trying to every instance that happened after 2019. We calculated mov- learn a time series model that will predict future prices; ing average using 10 days closing price then tried to predict whether in equities, commodities, forex or cryptocurrencies. the direction of the change of this trendline. Unfortunately it is not that simple. One can easily build a near perfect model on the train dataset just to find it is The equity data turned out to be a little bit timid, not completely useless on the test dataset. chaotic enough to demonstrate the full ability of the pro- posed method. This is why we also collected minute data of We propose a novel method that is capable of effectively cryptocurrencies Ethereum and Bitcoin and used the method combatting the overfitting, especially this proves to be a on them as well. Data is available on the crypto exchange difficult task when one is dealing with a problem directly Kraken [1]. We used the same transformation as for the applicable in practical situations. The main idea is to add equities, but with a bit quicker trend. This time the target noise from the same distribution as the training data and variable was change in the trendline in the next 6 hours. For then at the same time optimize the target variable and the the test set we took every instance that has time stamp after latent representation with the help of the autoencoder. The December 2020. longer the training goes, the lower is the amplitude of noise and the less focus is on the optimization of the representation. The reader should note that the end goal is not to accurately predict future equity price, since that is next to impossible. As soon there is a pattern, someone will profit from it and then the pattern will change. By predicting the future trend line, one can obtain a significant confidence interval and estimates of where the price could be, and then design for example a derivative strategy that searches for favourable risk versus rewards trades. 3. PROPOSED METHOD 175 We propose the method designed for prediction of stochastic Algorithm 1 Noise definition processes. The method achieves significant results improving 1: Inputs: X, α, β, epoch the metrics and loss functions on unseen data, where standard 2: Y = [ts, ts, np] . Array for holding Cholesky deep learning is prone to over-fit. The main advantage is decompositions of time correlation matrices. reducing the gap between training data and testing data, 3: for t ∈ {1, . . . , np} do sometimes to a degree where one sacrifices a little bit on the 4: Σt = cov(X[, , t]) train side to actually have the model outperforming it on 5: Y [, , t] = chol(Σt) . In practice the test data. This is very important in time series, where a closest positive definite matrix of Σt is computed before prediction model is usually just one part of a bigger strategy the Cholesky decomposition. and where the train over-fit is the biggest issue. For example, 6: end for designing a trading strategy on over-fitted predictions, that 7: Z = [bs, ts, np] . Array for holding noise samples. kind of mistake can lead to huge capital losses. 8: for i ∈ {1, . . . , ts} do 9: Σi = cov(X[, i, ]) The proposed method can be broken down into 3 important 10: Z[, i, ] = mvn(bs, Σi) parts: normalization, noise addition and additional opti- 11: end for mization of latent representation. Each part can be easily 12: for j ∈ {1, . . . , np} do integrated into an already existing pipeline. 13: Z[, , j] = matmul(Z[, , j], Y [, , j]) . Correcting initially independent noise samples with respect to time. 14: end for 3.1 Empirical normalization 15: for w ∈ {1, . . . , ts} do Normalization plays an important role in deep learning mod- 16: Z[, w, ] = Z[, w, ] ∗ ((βts−w · αepoch) · sd) . Decrease els. It was shown that normalization significantly speeds up the noise during the training procedure. the gradient descent, almost independently of where normal- 17: end for ization takes place. It can be weight normalization [11] during 18: R = X + Z the actual optimization, or it can be the batch normalization 19: Return R. [8], or just normalization of the whole input data [7]. In the proposed method it is important that the 3 dimensional input data comes from the same distribution as the gener- 3.3 Optimization of latent representation ated noise. Since it is fairly straightforward to sample data The most common issue with deep learning optimization is from a 3 dimensional normal distribution, we normalize input falling into a local optimum and being unable to move past data using an empirical cumulative distribution function [12] it [13]. We introduce autoencoder part into the optimization and empirical copula [4] [5]. We align all central moments procedure in order to force the model to shift from going of the unknown distribution to the ones from centered and directly to local optimum to learning the latent representation standardised normal distribution. The normalization takes first. We expect that this combined with the addition of place before the data is reshaped to 3 dimensional tensor. noise, will force the model first to learn how to ignore the noise that we added and the noise that is already in the data 3.2 Noise addition by nature of the stochastic process [15]. We optimized the Introduction of the noise is not new in unsupervised learning model using the Adam optimizer [6]. The loss function used and it was shown that it has a positive effect [14]. Adding in optimization is defined like: noise to input data and then forcing the model to learn how to ignore it has a lot of success in generative adversar- ial networks [3], where convergence can be very tricky to L = LY + Wae · decayepoch · Lae, achieve. We transformed that idea and embedded it into su- pervised learning procedure. The noise addition is described in Algorithm 1. where LY stands for the supervised loss function which will depend on the problem while Lae stands for the loss between In Algorithm 1 we will use the following abbreviations. encoded output and input data. Decay weight is decreasing the longer the training goes on. • X = [bs, ts, np] stands for the input tensor with 3 di- 4. RESULTS mensions; batch size, time steps and number of features We have divided the results section into 2 parts: unsupervised used for predictions. and supervised. In the first we demonstrate why the noise distribution is important. For the unsupervised part, due to • α, β are parameters that control how fast noise will hardware constraints, we have only used the cryptocurrency decrease during the training procedure. They should dataset since we deemed it more demanding than the equity be between 0 and 1, where lower value correspond to a one. In the second, we demonstrate how the our method faster decrease in the amplitude of the added noise. increases test metric on both datasets. • mvn stands for function sampling from a two dimen- sional correlated Gaussian distribution, where Σ is the covariance. matmul stands for matrix multiplication. 176 4.1 Unsupervised learning results one. This result is definitely worth further investigation and In order to test the efficiency of distributed noise versus just experimentation. random noise, we created 3 models. The baseline model was a deep learning model with 3 stacked LSTM layers, encoded 4.2 Supervised learning results layer, then again 3 stacked LSTM for decoded output. We In the previous section we have shown that the distribution have used Adam as optimizer. As loss function we used of the noise matters. In this section we will show that mean-squared error. We have stopped the learning after noise combined with optimization of latent representation there was no improvement for 25 epochs on the validation set. significantly improves metrics on unseen data. Similarly as The validation set was randomly taken out of the train set. before, α and β were both set to 0.99 and sd was initially set Parameters α and β were both set to 0.99 and sd was initially to 1.25. From our experience this setting achieves the best set to 1.25. The noise decreases with learning procedure. results, but further exploration needs to be done. Wae was Interestingly keeping noise constant did not achieve any initially set to 5 and decay to 0.95. results. Since we now operate in a supervised environment, we can compare our models to the majority class. But to really demonstrate the effectiveness of the method, we chose to compare the following models: • Majority class, which serves as a sanity check. • Random Forest with 500 trees. • Generalized linear model. • Deep learning model with 3 stacked LSTM layers. Figure 1: Test loss of autoencoder model with random noise (green) versus no noise (blue). • Deep learning model with 3 stacked LSTM layers and optimization of latent representation. Initially we have tested baseline model versus de-noising • Deep learning model with 3 stacked LSTM layers and model but with uncorrelated noise. In the Figure 1 is plotted correlated noise addition. the de-noising test loss function in green colour and the baseline test loss function in blue. Training was stopped • Finally, deep learning model with 3 stacked LSTM relatively early compared to Figure 2 and it is also obvious layers and correlated noise addition and optimization that de-noising test loss is even worse than that of the classic of latent representation. autoencoder. In the second example we switched from uncorrelated noise All 4 of the deep learning models are identical, all are opti- to the noise with same distribution as input data. As is mized with Adam and categorical cross entropy was used as a apparent on Figure 2, where again we have de-noising test loss function for the supervised part and mean squared error loss plotted with green and classic test loss with blue, the de- for the autoencoder part. Initially we have only tested the noising autoencoder achieved lower test loss than the classic models on equities data, but it turned out that the equities one. were not chaotic enough. By that we mean that especially with deep learning models the difference between train and test loss was not so big that it would be problematic. From previous work experience we know that overfit is a big issue in cryptocurrency dataset, so then we decided to test that dataset in a supervised setting as well. All models were trained three times on each dataset and the results in Table 1 and Table 2 are the averages of the 3 runs. In Table 1 we show the results from the equity dataset. Our method managed to improve test accuracy (from 0.673 to 0.682) without decreasing train accuracy (0.681). Maintain- ing test accuracy and keeping it comparable to test one is important if one needs to build additional strategy upon Figure 2: Test loss of autoencoder model with correlated noise predictions. Just noise addition slightly improved the results (green) versus no noise (blue). (from 0.673 to 0.675), while just the optimization of the latent distribution does not improve anything. What we expected is that then the train and validation losses will be worse than with the classic autoencoder. Surprisingly, that was not the case. With the de-noising autoencoder using noise with the same distribution as the input data, both train and validation losses were better than with classic 177 6. ACKNOWLEDGMENTS Table 1: Supervised results on equity dataset. This work was supported by the Slovenian Research Agency. Method Train Accuracy Test Accuracy We also wish to thank prof. dr. Ljupčo Todorovski for his Majority 0.513 0.537 help, especially with unsupervised results. Random Forest 0.649 0.655 GLM 0.664 0.655 7. REFERENCES LSTM 0.681 0.673 latent LSTM 0.633 0.673 [1] Kraken exchange. https://www.kraken.com/. noise LSTM 0.681 0.675 [2] Yahoo Finance. https://finance.yahoo.com/. latent noise LSTM 0.681 0.682 [3] A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, and A. A. Bharath. Generative adversarial networks: An overview. IEEE Signal In Table 2 we show results from the cryptocurrency dataset. Processing Magazine, 35(1):53–65, 2018. Similar as on the equity dataset, our method behaves as [4] P. Jaworski, F. Durante, W. K. Hardle, and T. Rychlik. intended on the cryptocurrency dataset as well. We can see Copula theory and its applications, volume 198. reduced overfitting that is apparent in the normal LSTM Springer, 2010. model. With those results we can conclude that the proof of [5] H. Joe. Dependence Modeling with Copulas. CRC Press, concept works, but for additional claims we will need more 2014. testing and deeper parameter analysis. [6] D. Kingma and J. Ba. Adam: A Method for Stochastic Optimization. 2014. https://arxiv.org/abs/1412.6980. Table 2: Supervised results on cryptocurrency dataset. [7] K. Y. Levy. The power of normalization: Faster evasion Method Train Accuracy Test Accuracy of saddle points. arXiv preprint arXiv:1611.04831, Majority 0.512 0.556 2016. Random Forest 0.689 0.692 [8] M. Liu, W. Wu, Z. Gu, Z. Yu, F. Qi, and Y. Li. Deep GLM 0.682 0.695 learning based on batch normalization for p300 signal LSTM 0.754 0.696 detection. Neurocomputing, 275:288–297, 2018. latent LSTM 0.736 0.683 [9] R. C. Merton. Option pricing when underlying stock noise LSTM 0.697 0.695 returns are discontinuous. Journal of financial latent noise LSTM 0.706 0.714 economics, 3(1-2):125–144, 1976. [10] J. J. Murphy. Technical Analysis of the Financial It is interesting to point out that with the proposed method Markets: A Comprehensive Guide to Trading Methods the test loss on cryptocurrency dataset was 0.552, while and Applications. New York Institute of Finance Series. train loss was 0.592. While 0.552 was the best loss any deep New York Institute of Finance, 1999. learning model achieved, that wide difference indicates that [11] T. Salimans and D. P. Kingma. Weight normalization: we could improve our model even further by fine tuning the A simple reparameterization to accelerate training of parameters. deep neural networks. Advances in neural information processing systems, 29:901–909, 2016. 5. CONCLUSIONS AND FUTURE WORK [12] B. W. Turnbull. The empirical distribution function In this work we have introduced and demonstrated how the with arbitrarily grouped, censored and truncated data. addition of noise and simultaneous optimization of latent Journal of the Royal Statistical Society: Series B representation and target variable reduce overfitting on time (Methodological), 38(3):290–295, 1976. series data. In the unsupervised case we have shown that the [13] R. Vidal, J. Bruna, R. Giryes, and S. Soatto. distribution of the noise matters and the input data must Mathematics of deep learning. arXiv preprint align to achieve maximum effect from the noise addition. arXiv:1712.04741, 2017. [14] P. Vincent, H. Larochelle, Y. Bengio, and P.-A. In the future work we have to estimate the effect of the Manzagol. Extracting and composing robust features newly introduced parameters on method’s convergence. At with denoising autoencoders. In Proceedings of the 25th the same time we need to explore how the method behaves international conference on Machine learning, pages when embedded into larger models, transformers for example. 1096–1103, 2008. We also need to evaluate the method in datasets that are by nature stochastic but do not come from the financial domain. [15] N. Wax. Selected papers on noise and stochastic Finally, we need to evaluate our method on a dataset that is processes. Courier Dover Publications, 1954. not stochastic. 178 Causal relationships among global indicators Matej Neumann Marko Grobelnik Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia Jamova cesta 39, Ljubljana, Slovenia matej.neumann@student.fmf.uni- marko.grobelnik@ijs.si lj.si ABSTRACT This is the official source published by the United Nations it It is important to know how changing one thing will affect provides information on the development and implementation of another. This becomes even more important when the thing we an indicator framework for the follow up and review of the 2030 are changing will affect a lot of people. Therefore, we need a way Agenda for Sustainable Development [4]. to visualize how all the things are connected. In this paper, we will demonstrate an approach that uses Granger causality to find 2.2 The World Bank (WB) causal relationships between global indicators. Our results show As the data set provided by the UN itself often has missing that global indicators are indeed highly interconnected however, values, which results in unhealthy timeseries and unreliable they still need to be looked at within each country individually. results, we decided to add the dataset “World Development We also comment how this approach can be used to help with Indicators” from The World Bank [5]. Although the data set policy making decisions. might not be as official as the one provided by the UN, it does contain 1440 unique indicators for 266 different countries and KEYWORDS groups, where each indicator contains a timeseries ranging from Causality, Global indicators, Granger, Timeseries, SDGs the year 1960 to the present time. This addition does not only make the dataset healthier, it also introduces new indicators that are not listed in the UN SDGs. Even so our new dataset still has 1 INTRODUCTION some limitations. From Figure 1 we can see that on average a The Sustainable Development Goals (SDGs) launched on country or groups has no values for around 33% of its indicators. January 1, 2016 include 17 goals, 169 targets and 232 unique Therefore, from now on when talking about the indicators, we indicators with the intent to help frame the policies of the United will restrict ourselves to just those ones that have at least 20 Nations’ (UN) member states through 2030 [8]. Because the nonmissing values in their timeseries. This restriction will insure goals are highly interconnected, as the indicators are not that we are always dealing with a healthy timeseries and it is independent, it is important to understand synergies, conflicts justified as on average those indicators make up about 50% of all and causal relationships between them to support decisions. of the ones available as seen in Figure 2. Without such understanding a policy to help one goal could hurt another. For example, a policy aiming to improve hunger could conflict with climate-mitigation. This paper will focus on finding such relationship with Granger causality. Granger causality is a statistical concept of causality that is based on prediction and was traditionally only used in the financial domain however, over recent years there has been growing interest in the use of Granger causality to identify causal interactions in neural data [6]. Similar works such as [7] and [2] have already looked for causal relationships between specific SDGs. This paper confirms the previously done work and expands it by adding additional indicators and looking for causal relationship between all the indicators, not just the ones focused on SDGs. In paper [2] the authors say that the analysis of all of the indicators country by country is without doubt impractical. Figure 1: Percentage of indicators having x nonmissing Nevertheless, Table 2 shows that however impractical it may be, values in its timeseries. it is still required, as even neighboring countries have vastly different causal relationships. 2 DESCRIPTION OF DATA 2.1 United Nations Statistics Division (UNSD) 179 future values of Y with both the past values of X and Y and not just the past values of Y. More formally, let x and y be stationary timeseries and let x(t) and y(t) be the univariate autoregression of x and y respectfully: 𝑝 𝑥(𝑡) = 𝑏 0 + ∑ 𝑏𝑖𝑥(𝑡 − 𝑖) + 𝐸2(𝑡) 𝑖=1 𝑝 𝑦(𝑡) = 𝑎0 + ∑ 𝑎𝑖𝑦(𝑡 − 𝑖) + 𝐸1(𝑡) 𝑖=1 where p is the number of chosen lagged values included in the model, 𝑎𝑖 and 𝑏𝑖 are contributions of each lagged observation to the predicted values of 𝑥(𝑡) and 𝑦(𝑡) and 𝐸 𝑖(𝑡) the difference between the predicted value and the actual value. To test the null hypothesis that x does not Granger-cause y, we augment 𝑦(𝑡) by including the lagged values of 𝑥 to get: Figure 2: percentage of indicators having at least x 𝑝 nonmissing values in its timeseries. 𝑦(𝑡) = 𝑐0 + ∑ 𝑎𝑖𝑦(𝑡 − 𝑖) + 𝑏𝑖𝑥(𝑡) + 𝐸3(𝑡). 𝑖=1 To better imagine what kind of indicators we are dealing with, We then say that x Granger-causes y if the coefficients 𝑏𝑖 are we can check Table 1 which shows the top 10 most common ones. jointly significantly different from zero. This can be tested by performing an F-test of the null hypothesis that 𝑏𝑖 = 0 for all i. Indicator name Frequency Renewable electricity output 265 3.2 Statistical significance and the p-value (% of total electricity output) In testing, a result has statistical significance if it is unlikely to Population, total 265 occur assuming the null hypothesis. More precisely, a Population growth (annual %) 265 significance level α, is the probability of the test rejecting the null Nitrous oxide emissions in 265 hypothesis, given that the null hypothesis was assumed to be true energy sector (thousand metric and the p-value is the probability of getting result at least as tons of CO2 equivalent) extreme, given that the null hypothesis is true. Then we say that Methane emissions in energy 265 the result is statistically significant when 𝑝 ≤ 𝛼. sector (thousand metric tons of CO2 equivalent) 3.3 Limitations of the Granger causality test Agricultural nitrous oxide 265 As its name implies, Granger causality is not necessarily true emissions (thousand metric tons causality. Having said this, it has been argued that given a of CO2 equivalent) probabilistic view of causation, Granger causality can be Agricultural methane 265 considered true causality in that sense, especially when emissions (thousand metric tons Reichenbach's "screening off" notion of probabilistic causation of CO2 equivalent) is considered [1]. Urban population growth 263 A problem may occur if both timeseries x and y are connected (annual %) via a third timeseries z. In that case our test can reject the null Urban population (% of total 263 hypothesis even if manipulation of one of the timeseries would population) not change the other. Other possible sources of problems can Urban population 263 happen due to: (1) not frequent enough or too frequent sampling, Table 1: Most common indicators and their frequency of 20 (2) time series nonstationarity, (3) nonlinear causal relationship. nonmissing values 4 EXPERIMENTS 3 METHODOLOGY 4.1 Setup Due to time constraints and the limitations of my home system, 3.1 Granger causality we decided to limit ourselves to taking just a few countries and The causal relationships between indicators were determined by groups and calculating the causality relationships for them. The the Granger causality test. The Granger causality test is a ones we decided on are: (1) United States, (2) China, (3) statistical hypothesis test for determining whether one timeseries Uruguay, (4) Slovenia, (5) Austria, (6) Croatia, (7) Italy, (8) is useful in forecasting another. Informally we say that timeseries European Union and (9) OECD. Our plan was to choose X Granger-causes timeseries Y if predictions of the value of Y based on its own past values and on the past values of X are better than predictions of Y based only on Y's own past values. Or in other words X Granger-causes Y if we can better explain the 180 AUS CH CRO EU ITA OECD SLO UY USA AUS 100% 4.8% 5.1% 6.9% 6.7% 6.0% 5.9% 4.4% 7.1% CH 100% 5.6 3.5% 4.3% 3.9% 4.2% 4.7% 4.3% CRO 100% 4.6% 5% 3.3% 6.6% 3.8% 5.6% EU 100% 11% 20% 5.7% 3.6% 10% ITA 100% 6.7% 7.5% 3.8% 6.7% OECD 100% 5% 3% 17% SLO 100% 3.5% 5.6% UY 100% 4.2% USA 100% Table 2: Percentage of same causal relationships. That being said one can easily imagine why each population age Granger-causes a few of the major world powers and compare the differences and similarities between the causal relationships. the next one. For example, if we know the percentage of people 4.2 Modeling the dataset aged 4, we can pretty accurately predict what the percentage of Once the data was collected from the UNSD and WB website it people aged 5 is going to be in the next year. first had to be put into a suitable form. We decided on a 3D matrix where the first component represented the country or SDG Buzzwords group, the second component represented the time series and last Zero Hunger nourishment, food, stun, anemia, one representing the indicator. agriculture 4.3 Parameters Clean Water and water, sanitation, drinking, drink, Sanitation hygiene, freshwater As mentioned before, when searching for causal relationships in a certain country or group we limit ourselves only to those Affordable and energy, electricity, fuel indicators who have at least 20 nonmissing values. Furthermore, Clean Energy we chose a significance level of 0.05 or 5% and tested for lagged Climate Action disaster, disasters, climate, natural, values from 1 to 4. risk, Sendai, environment, environmental, green, developed, pollution 4.4 Determining causality Good Health and mortality, birth, infection, Once the modeling was done and the parameters were set we first Well-Being tuberculosis, malaria, hepatitis, needed to make sure that the timeseries were stationary. To do disease, cancer, diabetes, that we ran the ADF-test and differenced the times series treatment, Alcohol, death, birth, accordingly to make them stationary. Then we ran the Granger- health, pollution, medicine causality test 4 times, once for each lagged value, for each of the Table 3: Some of the most common buzzwords found in 9 countries and groups listed in 4.1. The results for each lagged SDGs value were then saved in a 1440x1440 weighted adjacency matrix, where the (i,j) element was nonzero if and only if the i-th indicator Granger-caused the j-th indicator for all lagged values between 1 and 4 and had the weight of the average of the 4 p- values. Once we had the weighed adjacency matrix we matched the available indicators with the 17 SDGs by comparing the most common buzzwords found in the description of the SDGs and the name of the indicators. An example of some of the buzzwords can be seen in Table 3. 5 RESULTS With the weighted adjacency matrix in hand, it is sensible to ask ourselves whether there exist any causal relationships that hold true for each of the tested countries or groups. The answer is positive as seen in Figure 3. We can however see that the only causal relationships that survived were the ones that connected Figure 3 Only causal relationships that are true for each of different population ages to each other. This result seems the 9 countries and groups (continuous down). sensible as in general no two countries are exactly the same and are therefore going to have a unique set of causal relationships. On the other hand, one may assume that if we compare countries which are close to each other or are historically connected then the causal relationships should not differ by a lot. 181 Figure 4: Interconnectedness of SDGs. That however is not the case as can be seen in Table 2. This This work has been supported by the Slovenian research agency. suggests, that when talking about causal relationships, one must look at each country or group individually. Therefore, let’s focus just on Slovenia. Due to Slovenia 8 REFERENCES having 10083 positive causal relationships we will limit ourselves to just those that interact with SDGs. Figure 4 shows that indeed SDGs are not independent and in fact are highly [1] M. Michael in S. L. Bressler, „Foundational interconnected. The presence of self-loops also suggests that perspectives on causality in large-scale brain networks,“ there exist causal relationships between indicators of an SDG Physics of Life Reviews, pp. 107-123, 2015. itself. This result has two consequences: [2] G. Dörgő, V. Sebestyén in J. Abonyi, „Evaluating the • When thinking about policies aiming to improve Interconnectedness of the Sustainable Development one goal we need to be careful to not harm another Goals Based on the Causality Analysis of Sustainability • Indicators,“ Instead of outright improving one goal, we can Sustainability, 2018. instead focus the ones that are in causal relationship [3] C. Stefano in S. Sangwon, „Cause-effect analysis for with the one we wish to improve sustainable development policy,“ NRC Research Press, Let’s give an example. Suppose we would want to 2017. implement a policy to help to help lower the suicide mortality [4] https://unstats.un.org/sdgs/indicators/database/. rate, but we are not how to do that directly. We can therefore [5] https://datacatalog.worldbank.org/search/dataset/00377 instead check which indicators Granger-cause the one we are 12/World-Development-Indicators. trying to improve. In our case the indicator “Unemployment, youth total (% of total labor force ages 15-24)” Granger-causes [6] B. Corrado in K. Peter, „On the directionality of cortical the suicide mortality rate. Therefore, if we improved the % of interactions studied,“ Biological Cybernetics, 1999. unemployed young people we would be able to also reduce the [7] K. Irfan, H. Fujun in P. L. Hoang, „The impact of suicide mortality rate which was our initial goal. natural resources, energy consumption, and population growth on environmental quality: Fresh evidence from the United States of America,“ Science of The Total 6 CONCLUSION AND FUTURE WORK Environment, 2020. In this paper we demonstrated an approach for calculating [8] H. Tomáš, J. Svatava and M. Bedřich, “Sustainable causality between depending global indicators and mentioned Development Goals: A need for relevant indicators,” how this can help with implementing policies. We also showed Ecological Indicators, pp. 565-573, 2016. that neighboring and similar countries in general don’t have the same causal relationships, which makes it hard to group them together. However, finding such a grouping, if it exists, could be done in the future. The approach shown in this paper could also be implemented to find causal relationship between certain google searches and natural events. For example, we could check if there is any correlation between the increase of users searching the words “water”, “rain”, or “cloud” and the likelihood of a flood happening. 7 ACKNOWLEDGMENTS 182 Active Learning for Automated Visual Inspection of Manufactured Products Elena Trajkova∗ Jože M. Rožanec∗ Paulien Dam University of Ljubljana, Faculty of Jožef Stefan International Philips Consumer Lifestyle BV Electrical Engineering Postgraduate School Drachten, The Netherlands Ljubljana, Slovenia Ljubljana, Slovenia paulien.dam@philips.com trajkova.elena.00@gmail.com joze.rozanec@ijs.si Blaž Fortuna Dunja Mladenić Qlector d.o.o. Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia blaz.fortuna@qlector.com dunja.mladenic@ijs.si ABSTRACT regarding defective products, it provides insights into when and Quality control is a key activity performed by manufacturing enter- where such defects occur, which can be used to further dig into the prises to ensure products meet quality standards and avoid potential root causes of such defects and mitigation actions to improve the damage to the brand’s reputation. The decreased cost of sensors and quality of manufacturing products and processes. connectivity enabled an increasing digitalization of manufacturing. The decreased cost of sensors and connectivity enabled an in- In addition, artificial intelligence enables higher degrees of automa- creasing digitalization of manufacturing [3], which along with the tion, reducing overall costs and time required for defect inspection. adoption of Artificial Intelligence (AI) [12], represents an opportu- In this research, we compare three active learning approaches and nity towards enhancing the defect detection in industrial settings five machine learning algorithms applied to visual defect inspection [5]. While the quality of the manual inspection has low scalability with real-world data provided by Philips Consumer Lifestyle BV. Our (requires time to train an inspector, the employees can work a lim- results show that active learning reduces the data labeling effort ited amount of time and are subject to fatigue, and the inspection without detriment to the models’ performance. itself is slow), its quality can be affected by the operator-to-operator inconsistency, and it depends on the complexity of the task, the CCS CONCEPTS employees (e.g., their intelligence, experience, well-being), the en- • vironment (e.g., noise and temperature), the management support Information systems → Data mining; • Computing method- and communication [23]; none of these factors affect the outcome ologies → Computer vision problems; • Applied computing; of automated quality inspection. Machine learning has been suc- KEYWORDS cessfully applied to defect detection in a wide range of scenarios [1, 9, 11, 15, 21]. Smart Manufacturing, Machine Learning, Automated Visual Inspec- An annotated dataset must be acquired to implement machine tion, Defect Detection learning models for defect detection successfully. The increasing ACM Reference Format: number of sensors provides large amounts of data. As the manufac- Elena Trajkova, Jože M. Rožanec, Paulien Dam, Blaž Fortuna, and Dunja turing process quality increases, the data obtained from the sensors Mladenić. 2021. Active Learning for Automated Visual Inspection of Man- is expected to be highly imbalanced: most of the data instances ufactured Products. In Ljubljana ’21: Slovenian KDD Conference on Data will correspond to non-defective products, and a small proportion Mining and Data Warehouses, October, 2021, Ljubljana, Slovenia. ACM, New York, NY, USA, 4 pages. of them will correspond to different kinds of defects. Annotating all the data is prone to similar limitations as manual inspection 1 INTRODUCTION described in the paragraph above. It is thus imperative to provide strategies to select a limited subset of them that are most informa- Quality control is one of the critical activities that must be per- tive to the defect detection models. formed by manufacturing enterprises [27, 28]. The main purpose of We frame the defect detection problem as a supervised learning such activity is to detect product defects meeting quality standards, problem. Given a large amount of unlabeled data, and based on avoid rework, supply chain disruptions, and avoid potential dam- the premise that only a tiny fraction of the data provides new age to the brand’s reputation [3, 27]. Along with the information information to the model and thus has the potential to enhance its ∗Both authors contributed equally to this research. performance, we adopt an active learning approach. Active learning is a subfield of machine learning that attempts to identify the most 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 informative unlabeled data instances, for which labels are requested for profit or commercial advantage and that copies bear this notice and the full citation some oracle (e.g., a human expert) [24]. This research compares on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). three active learning strategies: pool-based sampling, stream-based SiKDD ’21, October, 2021, Ljubljana, Slovenia sampling, and query by committee. © 2021 Copyright held by the owner/author(s). 183 SiKDD ’21, October, 2021, Ljubljana, Slovenia Trajkova and Rožanec The main contributions of this research are (i) a comparative instances are drawn one at a time, and a decision is made whether study between the five most frequently cited machine learning a label is requested, or the sample is discarded), and (iii) pool-based algorithms for automated defect detection and (ii) three active selective sampling (queries samples from a pool of unlabeled data). learning approaches (iii) for a real-world multiclass classification Among the frequently used querying strategies, we find (i) un- problem. We develop the machine learning models with images certainty sampling (select an unlabeled sample with the highest provided by the Philips Consumer Lifestyle BV corporation. The uncertainty, given a certain metric or machine-learning model[17]), dataset comprises shaver images divided into three classes, based or (ii) query-by-committee (retrieve the unlabeled sample with the on the defects related to the printing of the logo of the Philips highest disagreement between a set of forecasting models (com- Consumer Lifestyle BV corporation: good shavers, shavers with mittee)) [6, 24]. More recently, new scenarios have been proposed double printing, and shavers with interrupted printing. leveraging reinforcement learning, where an agent learns to select We evaluate the models using the area under the receiver oper- images based on the similarity relationship between the instances ating characteristic curve (AUC ROC, see [4]). AUC ROC is widely and rewards obtained based on the oracle’s feedback [22]. In addi- adopted as a classification metric, having many desirable properties tion, it has been demonstrated that ensemble-based active learning such as being threshold independent and invariant to a priori class can effectively counteract class imbalance through new labeled probabilities. We measure AUC ROC considering prediction scores images acquisition [2]. cut at a threshold of 0.5. Active learning was successfully applied in the manufacturing This paper is organized as follows. Section 2 outlines the current domain, but scientific literature remains scarce on this domain [19]. state of the art and related works, Section 3 describes the use case, Some use cases include the automatic optical inspection of printed and Section 4 provides a detailed description of the methodology circuit boards[8] and the identification of the local displacement and experiments. Finally, section 5 outlines the results obtained, between two layers on a chip in the semi-conductor industry[25]. while Section 6 concludes and describes future work. The use of machine learning automates the defect detection, and active learning enables an inspection by exception [5], only querying for labels of the images that the model is most uncertain about. 2 RELATED WORK While this considerably reduces the volume of required inspections, Among the many techniques used for automated defect inspection, it is also essential to consider that it can produce an incomplete we find the automated visual inspection, which refers to image ground truth by missing the annotations of defective parts classified processing techniques for quality control, usually applied in the as false negatives and not queried by the active learning strategy production line of manufacturing industries [1]. Visual inspection [7]. requires extracting features from the images, which are used to train the machine learning model. This procedure is simplified when using deep learning models, enabling end-to-end learning, where a 3 USE CASE single architecture can perform feature extraction and classification The use case provided for this research corresponds to visual in- [10, 18], and have shown state-of-the-art performance for image spection of shavers produced by Philips Consumer Lifestyle BV. The classification [20]. visual quality inspection aims to detect defective printing of a logo The use of automated visual inspection for defect detection has on the shavers. This use case focuses on four pad printing machines been applied to multiple manufacturing use cases. [21] manually ex- setup for a range of different products, and different logos. A lot tracted features (e.g., histograms) from machine component images of products are produced every day on these machines, which are and compared the performance of the Näive Bayes and C4.5 models. manually handled and inspected on their visual quality and re- [9] extracted statistical features from the images and compared moved from further processing if the prints on the products are the performance of Support Vector Machines (SVM), Multilayer not classified as good. Operators spend several seconds handling, Perceptron (MLP), and k-nearest neighbors (kNN) models for visual inspecting, and labeling the products. Given an automated visual inspection of microdrill bits in printed circuit board production. quality inspection system would strongly reduce the need to manu- [11] used 3D convolutional filters applied on computed tomog- ally inspect and label the images, it could speed up the process for raphy images and an SVM classifier for defect detection during more than 40%. Currently there are two types of defects classified metallic powder bed fusion in additive manufacturing. [15] used related to the printing quality of the logo on the shaver: double some heuristics to detect regions of interest on slate slab images, printing, and interrupted printing. Therefore, images are classified on which they performed feature engineering to later train an SVM into three classes: good printing (class zero), double printing (class model on them. Finally, [1] reported using a custom neural network one), and interrupted printing (class two). A labeled dataset with a for feature extraction and an SVM model for classification when total of 3.518 images was provided to train and test the models. inspecting aerospace components. While the authors cited above worked with fully labeled datasets, a production line continually generates new data, exceeding the 4 METHODOLOGY labeling capacity. A possible solution to this issue is the use of active We pose automated defect detection as a multiclass classification learning, where the active learner identifies informative unlabeled problem. We measure the model’s performance with the AUC ROC instances and requests labels to some oracle. Typical scenarios in- metric, using the "one-vs-rest" heuristic method, which involves volve (i) membership query synthesis (a synthetic data instance splitting the multiclass dataset into multiple binary classification is generated), (ii) stream-based selective sampling (the unlabeled problems. Furthermore, we calculate the metrics for each class and 184 Active Learning for Automated Visual Inspection of Manufactured Products SiKDD ’21, October, 2021, Ljubljana, Slovenia compute their average, weighted by the number of true instances When analyzing the results, we were interested in how the mod- for each class. els’ performance evolved through time and significant variations To extract features from the images, we make use of the ResNet- between the first and last results observed. To that end, we as- 18 model [13], extracting embeddings from the Average Pooling sessed the statistical significance between the means of the first layer. Since the embedding results in 512 features, which could and last quartiles of the test fold for each active learning scenario. cause overfitting, we use the mutual information to evaluate the We assessed the statistical significance using the Wilcoxon signed- √ most relevant ones and select the top K features, with 𝐾 = 𝑁 , rank test, with a p-value of 0.05. While such variations existed and where N is the number of data instances in the train set, as suggested were positive in most test folds (the models learned through time), in [14]. the improvements were not statistically significant in none of the To evaluate the models’ performance across different active learn- scenarios. ing strategies, we apply a stratified k-fold cross validation [29], using one fold for testing, one fold as a pool of unlabeled data for 6 CONCLUSION active learning, and the rest from training the model. We adopt In this paper, we compared three active learning scenarios (pool- k=10 based on recommendations by [16], and query all available based, stream-based with classifier uncertainty sampling, and query- unlabeled instances to evaluate the active learning approaches. We by-committee) across five machine learning algorithms (Gaussian compare three active learning scenarios: drawing queries through Näive Bayes, CART, Linear SVM, MLP, and kNN). We found that (i) stream-based classifier uncertainty sampling accepting instances the best performance was achieved by the MLP model regardless with an uncertainty threshold above the 75th percentile of observed of the active learning strategy. The second-best performance was instances, (ii) pool-based sampling selecting the instances a given obtained through the query-by-committee strategy, while the fre- model is most uncertain about, and pool-based sampling consider- quently used SVM models ranked third. We found no significant ing a query-by-committee strategy, where the committee is created difference between using pool-based or stream-based active learn- with models trained with the five algorithms we consider in this re- ing approaches. Results from the query-by-committee approach search: Gaussian Näive Bayes, CART (Classification and Regression were statistically significant in all cases and better than all the Trees, similar to C4.5, but it does not compute rule sets), Linear SVM, models, except for the MLPs. Finally, we found no case where the MLP, and kNN. Comparing deep learning models remains a subject improvement between the first and last quartile of the test fold in of future work. Finally, we compare the performance of the active each active learning scenario would be significant. We believe that learning scenarios computing the average AUC ROC of each fold further investigation is required to determine if a larger pool of un- and assess if the results differences obtained from each model are labeled images would help us achieve such a significant difference. statistically significant by using the Wilcoxon signed-rank test[26], Future work will focus on data augmentation techniques that could using a p-value of 0.05. help achieve a statistically significant improvement over time when applying active learning techniques. 5 RESULTS AND ANALYSIS ACKNOWLEDGMENTS The results obtained from the experiments we ran, and described This work was supported by the Slovenian Research Agency and in Section 4, are presented in Table 1, and Table 2. Table 1 describes the European Union’s Horizon 2020 program project STAR under the average AUC ROC per each active learning scenario and model grant agreement number H2020-956573. The authors acknowledge for each cross-validation test fold. We observe that the best model the valuable input and help of Jelle Keizer and Yvo van Vegten from across strategies is the MLP, which achieved the best or second-best Philips Consumer Lifestyle BV. performance across almost every fold in pool-based and stream- based active learning. Among those two scenarios, the best results REFERENCES were obtained for stream-based active learning. We observed the [1] Carlos Beltrán-González, Matteo Bustreo, and Alessio Del Bue. 2020. External same across the rest of the models, though the differences were and internal quality inspection of aerospace components. In 2020 IEEE 7th Inter- national Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE, 351–355. not significant for all but the Näive Bayes models (see Table 2). [2] William H Beluch, Tim Genewein, Andreas Nürnberger, and Jan M Köhler. 2018. Query-by-committee displayed a strong performance, showing best The power of ensembles for active learning in image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 9368–9377. results immediately after the MLP. When assessing the statistical [3] Tajeddine Benbarrad, Marouane Salhaoui, Soukaina Bakhat Kenitar, and Mounir significance between the query-by-committee scenario and results Arioua. 2021. Intelligent machine vision model for defective product inspection obtained from different models with stream-based and pool-based based on machine learning. Journal of Sensor and Actuator Networks 10, 1 (2021), 7. strategies, we observed that differences were significant in all cases, [4] Andrew P. Bradley. 1997. The use of the area under the ROC curve in the except for the SVM models. SVM models, most widely used in ac- evaluation of machine learning algorithms. Pattern Recognition 30, 7 (1997), 1145 tive learning literature related to automated defect inspection, were – 1159. https://doi.org/10.1016/S0031-3203(96)00142-2 [5] Amal Chouchene, Adriana Carvalho, Tânia M Lima, Fernando Charrua-Santos, the third-best models among the tested ones, immediately after Gerardo J Osório, and Walid Barhoumi. 2020. Artificial intelligence for prod- the MLPs in stream-based and pool-based active learning and the uct quality inspection toward smart industries: quality control of vehicle non- conformities. In 2020 9th international conference on industrial technology and query-by-committee approach. SVM models did not display signif- management (ICITM). IEEE, 127–131. icant differences when compared across different active learning [6] David Cohn, Les Atlas, and Richard Ladner. 1994. Improving generalization with scenarios. The worst results were consistently observed for the active learning. Machine learning 15, 2 (1994), 201–221. [7] Antoine Cordier, Deepan Das, and Pierre Gutierrez. 2021. Active learning using CART models. weakly supervised signals for quality inspection. arXiv preprint arXiv:2104.02973 185 SiKDD ’21, October, 2021, Ljubljana, Slovenia Trajkova and Rožanec Active Learning scenario Model Fold 1 Fold 2 Fold 3 Fold 4 Fold 5 Fold 6 Fold 7 Fold 8 Fold 9 Fold 10 CART 0,8168 0,7828 0,7810 0,7694 0,8196 0,7805 0,7843 0,7970 0,8409 0,7940 kNN 0,9289 0,9121 0,9174 0,8686 0,9024 0,9000 0,9051 0,8960 0,9282 0,9082 stream-based MLP 0,9900 0,9928 0,9846 0,9563 0,9804 0,9807 0,9710 0,9729 0,9793 0,9845 Näive Bayes 0,8818 0,8668 0,8819 0,8686 0,8829 0,8899 0,8650 0,8877 0,8864 0,9098 SVM 0,9752 0,9828 0,9725 0,9530 0,9816 0,9720 0,9570 0,9412 0,9824 0,9712 CART 0,7584 0,7904 0,7543 0,7468 0,8441 0,7730 0,8044 0,7701 0,7850 0,7412 kNN 0,9189 0,9149 0,9161 0,8581 0,9055 0,9036 0,8961 0,8910 0,9224 0,9056 pool-based MLP 0,9892 0,9921 0,9845 0,9563 0,9790 0,9803 0,9702 0,9723 0,9806 0,9840 Näive Bayes 0,8800 0,8654 0,8809 0,8677 0,8813 0,8895 0,8637 0,8873 0,8850 0,9090 SVM 0,9752 0,9819 0,9726 0,9518 0,9806 0,9712 0,9562 0,9412 0,9823 0,9722 query-by-committee 0,9774 0,9824 0,9714 0,9500 0,9723 0,9726 0,9597 0,9571 0,9830 0,9734 Table 1: AUC ROC values were obtained across the ten cross-validation folds. Best results are bolded, second-best results are highlighted in italics. Active Learning scenarios Model stream-based vs. pool-based stream-based vs. query-by-committee pool-based vs. query-by-committee CART 0,0840 0,0020 0,0020 kNN 0,1309 0,0020 0,0020 MLP 0,0856 0,0039 0,0039 Näive Bayes 0,0020 0,0020 0,0020 SVM 0,1824 0,4316 0,6250 Table 2: p-values obtained for the Wilcoxon signed-rank test when comparing the average of AUC ROC results across ten cross-validation folds. (2021). [22] Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang [8] Wenting Dai, Abdul Mujeeb, Marius Erdt, and Alexei Sourin. 2018. Towards Chen, and Xin Wang. 2020. A survey of deep active learning. arXiv preprint automatic optical inspection of soldering defects. In 2018 International Conference arXiv:2009.00236 (2020). on Cyberworlds (CW). IEEE, 375–382. [23] Judi E See. 2012. Visual inspection: a review of the literature. Sandia Report [9] Guifang Duan, Hongcui Wang, Zhenyu Liu, and Yen-Wei Chen. 2012. A machine SAND2012-8590, Sandia National Laboratories, Albuquerque, New Mexico (2012). learning-based framework for automatic visual inspection of microdrill bits in [24] Burr Settles. 2009. Active learning literature survey. (2009). PCB production. IEEE Transactions on Systems, Man, and Cybernetics, Part C [25] Karin van Garderen. 2018. Active Learning for Overlay Prediction in Semi- (Applications and Reviews) 42, 6 (2012), 1679–1689. conductor Manufacturing. (2018). [10] Tobias Glasmachers. 2017. Limits of end-to-end learning. In Asian Conference on [26] Frank Wilcoxon. 1992. Individual comparisons by ranking methods. In Break- Machine Learning. PMLR, 17–32. throughs in statistics. Springer, 196–202. [11] Christian Gobert, Edward W Reutzel, Jan Petrich, Abdalla R Nassar, and Shashi [27] Thorsten Wuest, Christopher Irgens, and Klaus-Dieter Thoben. 2014. An ap- Phoha. 2018. Application of supervised machine learning for defect detection proach to monitoring quality in manufacturing using supervised machine learn- during metallic powder bed fusion additive manufacturing using high resolution ing on product state data. Journal of Intelligent Manufacturing 25, 5 (2014), imaging. Additive Manufacturing 21 (2018), 517–528. 1167–1180. [12] Irlán Grangel-González. 2019. A knowledge graph based integration approach for [28] Jing Yang, Shaobo Li, Zheng Wang, Hao Dong, Jun Wang, and Shihao Tang. 2020. industry 4.0. Ph.D. Dissertation. Universitäts-und Landesbibliothek Bonn. Using deep learning to detect defects in manufacturing: a comprehensive survey [13] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual and current challenges. Materials 13, 24 (2020), 5755. learning for image recognition. In Proceedings of the IEEE conference on computer [29] Xinchuan Zeng and Tony R Martinez. 2000. Distribution-balanced stratified vision and pattern recognition. 770–778. cross-validation for accuracy estimation. Journal of Experimental & Theoretical [14] Jianping Hua, Zixiang Xiong, James Lowey, Edward Suh, and Edward R Artificial Intelligence 12, 1 (2000), 1–12. Dougherty. 2005. Optimal number of features as a function of sample size for various classification rules. Bioinformatics 21, 8 (2005), 1509–1515. [15] Carla Iglesias, Javier Martínez, and Javier Taboada. 2018. Automated vision system for quality inspection of slate slabs. Computers in Industry 99 (2018), 119–129. [16] Max Kuhn, Kjell Johnson, et al. 2013. Applied predictive modeling. Vol. 26. Springer. [17] David D Lewis and Jason Catlett. 1994. Heterogeneous uncertainty sampling for supervised learning. In Machine learning proceedings 1994. Elsevier, 148–156. [18] Jonathan Long, Evan Shelhamer, and Trevor Darrell. 2015. Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition. 3431–3440. [19] Lingbin Meng, Brandon McWilliams, William Jarosinski, Hye-Yeong Park, Yeon- Gil Jung, Jehyun Lee, and Jing Zhang. 2020. Machine learning in additive manu- facturing: A review. Jom 72, 6 (2020), 2363–2377. [20] Samira Pouyanfar, Saad Sadiq, Yilin Yan, Haiman Tian, Yudong Tao, Maria Presa Reyes, Mei-Ling Shyu, Shu-Ching Chen, and Sundaraja S Iyengar. 2018. A survey on deep learning: Algorithms, techniques, and applications. ACM Computing Surveys (CSUR) 51, 5 (2018), 1–36. [21] S Ravikumar, KI Ramachandran, and V Sugumaran. 2011. Machine learning approach for automated visual inspection of machine components. Expert systems with applications 38, 4 (2011), 3260–3266. 186 Learning to Automatically Identify Home Appliances Dan Lorbek Ivančič1, Blaž Bertalanič1,2, Gregor Cerar1, Carolina Fortuna1 1Jozef Stefan Institute, Ljubljana, Slovenia 2Faculty of Electrical Engineering, University of Ljubljana, Slovenia E-mail: dl0586@student.uni-lj.si Abstract. Appliance load monitoring (ALM) is a The obtained data is then disaggregated and each individ- technique that enables increasing the efficiency of domes- ual appliance and its energy consumption are detected. tic energy usage by obtaining appliance specific power One promising approach to ILM for automatic iden- consumption profiles. While machine learning have been tification of home appliances is the use of machine learn- shown to be suitable for ALM, the work on analyzing ing (ML). For instance, in [4] they used ML to find pat- design trade-offs during the feature and model selection terns in the data and extract useful information such as steps of the ML model development is limited. In this type of load, electricity consumption detail and the run- paper we show that 1) statistical features capturing the ning conditions of appliances [4]. More recently, [5] fo- shape of the time series, yield superior performance by cused on the study of design trade-offs during the fea- up to 20 percentage points and 2) our best deep neural ture and model selection steps of the development of the network-based model slightly outperforms our best gradi- ML-based classifier for ILM. In their study they consid- ent descent boosted decision trees by 2 percentage points ered various statistical summaries for feature engineering at the expense of increased training time. and classical machine learning techniques for model se- lection. We complement the work in [5] by extending 1 Introduction the feature set with additional shape capturing values and considering deep learning (DNN) and gradient boosted Household energy consumption accounts for a large pro- trees (XGBoost) as promising modelling techniques. The portion of the world’s total energy consumption. The first contributions of this paper are as follows: studies, conducted as early as the 1970s, showed that as much as 25% of national energy was consumed by our • We explore a variety of different statistical features and domestic appliances alone. This figure rose to 30% in show the ones capturing the shape of the time series, 2001 [1] and continues to increase with an exponential such as longest strike above mean, longest strike be- rate. Some researchers even predict that these numbers low mean, absolute energy and kurtosis yield superior will double by 2030 [2]. performance by up to 20 percentage points. In support of rationalizing consumption, appliance load monitoring (ALM) has been introduced. It aims to help • We show that our best DNN based model slightly out- solve domestic energy usage related issues by obtaining performs our best XGBoost by 2 percentage points at appliance specific power consumption profiles. Such data the expense of increased training time. We also show can help devise load scheduling strategies for optimal en- that our models outperform the results from [5] by 5 ergy utilization [2]. Additionally, data about appliance percentage points. usage can provide useful insight into daily activities of The paper is organized as follows. Section 2 summa- residents which can be useful for long-distance monitor- rizes related work, Section 3 formulates the problem and ing of elderly people who prefer to stay at home rather provides methodological details, Section 4 focuses on the than going to retirement homes [2]. Other applications study of feature selection trade-offs, while Section 5 dis- include theft detection, building safety monitoring, etc. cusses model selection. Concluding remarks are drawn The two different ways of realizing ALM are intru- in Section 6. sive load monitoring (ILM) and non-intrusive load mon- itoring (NILM). While ILM is known to be more accu- 2 Related Work rate, it requires multiple sensors throughout the entire building to be installed which incurs extra hardware cost Existing work that uses machine learning for ALM, such and installation complexity. NILM, however, is a cost- as in [6] investigates the performance of deep learning effective, easy to maintain process for analyzing changes neural networks on NILM classification tasks and builds in the voltage [3] and current going into a building with- a model that is able to accurately detect activations of out having to install any additional sensors on different common electrical appliances using data from the smart household devices, since it operates using only data ob- meter. More complex DNNs for NILM classification tasks tained from the single main smart meter in a building. are presented by the authors in [3], where they introduce 187 a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) based model and show that it outperforms the considered baselines. In [7] they approach a simi- lar problem by proposing a convolutional neural network based model that allows simultaneous detection and clas- sification of events without having to perform double pro- cessing. In [8] authors train a temporal convolutional neural network to automatically extract high-level load signatures for individual appliances while in [9] a fea- ture extraction method is presented using multiple par- allel convolutional layers as well as an LSTM recurrent neural network based model is proposed. 3 Problem formulation Our goal was to design a classifier that when given an input time series T, it is able to accurately map this data to the appropriate class C, as shown in equation 1. C = Φ(T ) (1) where Φ represents the mapping function from time series to target classes and C is a set of these classes, where each class corresponds to one of the following house- hold appliances: computer monitor, laptop computer, tele- vision, washer dryer, microwave, boiler, toaster, kettle Figure 1: Selected appliances, showing power in relation to time and fridge. The appliances and measured data illustrated over a 1 hour interval. in Figure 1 available in the public UK-Dale dataset are used. The UK DALE (Domestic Appliance-level Elec- tricity) contains the power demand from 5 different houses are provided by dedicated time series feature engineering in the United Kingdom. The dataset was build at a sample- tools such as tsfresh 1. rate of 16 Hz for the whole-house and 0.1667 Hz for each Following an extensive evaluation of combinations of individual appliance. Data is spread into 1 hour long seg- time-series, we report the results for a representative se- ments, each dataset sample contains a time series with lection of three feature sets as follows: 600 datapoints as depicted in Figure 1. FeatureSet1 - This feature set consists of the raw For realizing Φ, we perform first a feature selection time series, containing 2517 time series samples, each task followed by a model selection one. For selecting the with 600 datapoints. It is used as a baseline to see the best feature set, we perform feature selection in Section performance achieves with the available data. 4. For model selection, we go beyond the work in [5] and FeatureSet2 - This feature set consists of: mean consider deep learning architectures enabled by Tensor- value, maximum, minimum, standard deviation, flow and advanced decision trees that use on optimized variance, peak − to − peak, count above mean, count distributed gradient boosting technique available in the below mean, mean change, absolute mean change, XGBoost open source library as detailed in Section 5. absolute energy. The count above and below mean counts the numbers of values in each sample that are higher or 4 Feature selection lower than the mean value of that same sample and helps quantifying the width of a pulse such as the ones for the As can be seen in Figure 1, the time-series corresponding toaster and microwave from Figure 1. The mean absolute to each device has unique shape and patterns, therefore an change gives the mean over the absolute differences be- intuitive approach to feature selection is to extract statis- tween subsequent time series values. The absolute energy tical properties of the time series that would capture the represents the sum of squared values, calculated using unique properties of the signals. For instance, a summary formula shown in equation 2 and provides the informa- such as the peak-to-peak value is able to capture the dif- tion on whether a specific appliance has large consump- ference between the maximum and minimum value in a tion profile or not. time series signal while one such as skewness is able to describe the asymmetry in the distribution of datapoints n−1 X in a particular sample. A good combination of such fea- E = x2i (2) ture would be able to inform the model with relevant in- i=0 formation about the power consumption of each appli- FeatureSet3 - After taking a deeper look into the fea- ance, making it easier to find patterns in the data and per- tures from FeatureSet2, we noticed that minimum is re- form classification task more accurately. Recently, stan- 1 dard tools for computing a large range of such summaries https : //tsf resh.readthedocs.io/en/latest/text/list of f eatures.html 188 dundant as it is usually zero in every sample and peak-to- them. Nevertheless, the CNN classifies all three the best peak is in most cases equal to maximum value due to the due to its superior pattern recognition ability. lowest value mostly being zero. This feature set consists of: maximum, standard deviation, mean absolute Table 2: Per class performance, FeatureSet3 vs best [5] change, mean change, longest strike above mean, Class Inst. CNN f1 XGB f1 [5] f1 longest strike below mean, absolute energy, kurtosis, number of peaks in each signal. The longest strike monitor 300 0.827 0.833 0.780 above and below mean returns the length of the the longest laptop 276 0.983 0.932 0.838 consecutive subsequence that is higher or lower than the television 300 0.992 0.976 0.941 mean value of that specific sample. The kurtosis is an- washer/dryer 226 0.941 0.912 0.804 other metric of describing the probability distribution and microwave 300 0.688 0.620 0.687 measures how heavily the tails of a distribution differ boiler 300 1.000 0.968 0.940 from the tails of a normal distribution. toaster 215 0.949 0.940 0.806 kettle 300 0.756 0.722 0.739 fridge 300 1.000 0.983 0.970 Table 1: Feature comparison using the best models. Model Feature set Precision Recall f1 DNN3 FeatureSet1 0.638 0.595 0.573 5 Model selection XGB3 FeatureSet1 0.799 0.769 0.779 DNN3 FeatureSet2 0.918 0.885 0.889 For analyzing the performance of DNN and XGBoost for XGB3 FeatureSet2 0.869 0.864 0.867 our problem we conducted extensive performance eval- DNN3 FeatureSet3 0.931 0.898 0.902 uations. We started by developing a deep learning se- XGB3 FeatureSet3 0.888 0.889 0.889 quential model, which at first consisted of three dense layers, each with an arbitrarily chosen number of neu- DNN3 best[5] 0.893 0.887 0.888 rons. By trying different combinations of hyperparame- XGB3 best[5] 0.861 0.860 0.861 ters such as number of neurons, loss functions, optimiz- SVM[5] best[5] 0.851 0.835 0.834 ers, batch size, number of epochs, number of layers and learning rate, we came closer to finding the best suited model for our problem. For optimizing certain hyperpa- rameters we took advantage of the automatic hyperpa- 4.1 Results rameter optimization framework Optuna 2. We then ap- The results of the feature selection process are listed in plied similar optimization techniques on the XGB model, Table 1 for the two techniques considered in this paper. although it’s default parameter configuration already gave As can be seen from the second column of the table en- good results. All the experiments were ran on Google titles instances, the dataset is balanced. From columns Colab using an instance with Nvidia Tesla K80 GPU and 3-5 it can be seen that for the baseline FeatureSet1, the 12.69 GB of RAM. f1 score is 0.57 for the CNN and 0.77 for XGB. By using In this section we present and analyze three represen- features that better capture the shape of the time series tative models from each class, DNN and XGboost respec- such as in the case of FeatureSet2, an improvement of tively. up to 20% can be seen as follows: the f1 of the CNN model increasing to 0.89, the precision 0.92 and recall to 5.1 Deep neural network 0.88. The XGBoost model also performed better with an DNN1 - This model consisted of three fully con- f1 of 0.87, precision of 0.87 and recall of 0.86. Finally, it nected dense layers. The first two had 32 neurons each can be seen from the table that FeatureSet3 performs the as well as ReLU (rectified linear unit) activation function, best with the f1 of 0.90, precision of 0.93 and recall of while the output layer had nine neurons, each correspond- 0.90 for the CNN model and f1 of 0.89, precision of 0.89 ing to one of the nine possible appliances and Softmax and recall of 0.89 for the XGB model. FeatureSet3 per- activation function. formed better than FeatureSet2 because its features had DNN2 - For this model we took the DNN1 model and much less correlation between each other as well as all of added an additional dense layer with 64 neurons as well the redundant features from FeatureSet2 were removed. as changed the activation function to linear in the penulti- For FeatureSet3, a variety of different feature orderings mate layer. With this additional complexity we expected were also tested but the results remained more within 1% to see better results. accuracy variance. DNN3 - For this model we introduced two 1D con- To gain insights into the per class performance of Fea- volution layers, first with 128 filters and second with 64. tureSet3 with the two techniques, we present per device Then we used a flatten layer to reduce the dimensionality f1 score breakdown in Table 2. It can be seen that com- of the output space, and make the data compatible with puter monitor, microwave and kettle are classified worst the following dense layer, followed by another (output) by all three models, as their similar consumption profiles dense layer. make it difficult for the models to distinguish between 2https : //optuna.org 189 5.2 XGBoost 6 Conclusions XGB1 - This is the model with standard configura- In this paper we investigated the design trade-offs during tion, i.e. maximum depth of 3, 100 estimators and learn- the feature and model selection steps of the development ing rate of 0.1. of the ML-based classifier for ILM. After formulating our XGB2 - In this model we increased the maximum problem, we first show that by extracting various statis- depth to 4 as well as first reduced learning rate by 50% tical features from raw time series data and then training (to 0.05) and then increased the number of estimators by our models with these features, we were able to improve 50% (to 200). Doing this gave slightly better results. f1 score by up to 20 percentage points. XGB3 - For this model we decreased the maximum Second, we propose two different ML techniques and depth to 2, increased number of estimators to 500 and our process of developing the proposed models using these. learning rate to 0.25. We show that optimizing hyperparameters to better suit our specific problem can improve their respective perfor- Table 3: Model performance on FeatureSet3. mance by around 4 percentage points. However, choos- ing the right features that better capture the shape of the Model Precision Recall f1 Comp. time data has a much greater impact on the end results than op- DNN1 0.866 0.851 0.846 10.972s timizing the models. We also show that classical machine DNN2 0.900 0.887 0.889 21.026s learning model does not perform significantly worse than DNN3 0.931 0.898 0.902 21.124s the deep neural network based one, while at the same time being less computationally expensive. XGB1 0.876 0.863 0.864 1.126s XGB2 0.884 0.881 0.882 2.518s References XGB3 0.888 0.889 0.889 3.225s [1] L. Shorrock, J. Utley et al., Domestic energy fact file 2003. SVM [5] 0.878 0.852 0.852 0.301s Citeseer, 2003. [2] A. Zoha, A. Gluhak, M. A. Imran, and S. Rajasegarar, “Non-intrusive load monitoring approaches for disaggre- 5.3 Results gated energy sensing: A survey,” Sensors, vol. 12, no. 12, pp. 16 838–16 866, 2012. 5.3.1 Classification performance [3] J. Kim, T.-T.-H. Le, and H. Kim, “Nonintrusive The classification performance of the models is provided Load Monitoring Based on Advanced Deep Learn- in Table 3. It can be seen that the best performing models ing and Novel Signature,” Computational Intelli- are DNN3 with an f1 score of 0.90 and XGB3 with an f1 gence and Neuroscience, vol. 2017, p. e4216281, of 0.88. However, the computation time of XGB3 is only Oct. 2017, publisher: Hindawi. [Online]. Available: 3.23s while for DNN3 it is 21.12s. The XGB classifier https://www.hindawi.com/journals/cin/2017/4216281/ using classical machine learning performed only about [4] E. Aladesanmi and K. Folly, “Overview of non- 1 percentage point worse than the CNN model, while at intrusive load monitoring and identification tech- the same time being much less complex and able to com- niques,” IFAC-PapersOnLine, vol. 48, no. 30, pp. plete the entire training process about 18 seconds faster 415–420, 2015, 9th IFAC Symposium on Control than the CNN. In addition, the XGB model is much eas- of Power and Energy Systems CPES 2015. [Online]. ier to optimize since it has no hidden layers and a pre- Available: https://www.sciencedirect.com/science/article/ arranged hyperparameter configuration that usually re- pii/S2405896315030566 quires no further optimization at all. From the last line of [5] L. Ogrizek, B. Bertalanic, G. Cerar, M. Meza, and C. For- the table it can be seen that the SVM-based model from tuna, “Designing a machine learning based non-intrusive [5] performs 5 percentage points less than DNN3 on Fea- load monitoring classifier,” in 2021 IEEE ERK, 2021, pp. 1–4. tureSet3. [6] M. Devlin and B. P. Hayes, “Non-intrusive load monitor- 5.3.2 Computation time ing using electricity smart meter data: A deep learning approach,” in 2019 IEEE Power Energy Society General The superior performance of the DNN model comes at a Meeting (PESGM), 2019, pp. 1–5. cost of increased algorithm complexity and hence longer computation time. As depicted in Table 3 the first DNN [7] F. Ciancetta, G. Bucci, E. Fiorucci, S. Mari, and A. Fiora- vanti, “A new convolutional neural network-based system model took 10.97 seconds to complete the training pro- for nilm applications,” IEEE Transactions on Instrumenta- cess and the best (most complex one) took 21.12 seconds. tion and Measurement, vol. 70, pp. 1–12, 2021. XGBoost, on the other hand, was much faster with XGB1 [8] Y. Yang, J. Zhong, W. Li, T. A. Gulliver, and S. Li, taking only 1.12 seconds. The added depth for the XGB2 “Semisupervised multilabel deep learning based nonintru- caused a slight increase in computation time to 2.52 sec- sive load monitoring in smart grids,” IEEE Transactions onds, which further increased to 3.23 seconds due to the on Industrial Informatics, vol. 16, no. 11, pp. 6892–6902, high number of estimators used in XGB3. Finally, the 2020. state of the art was the fastest to complete the training [9] W. He and Y. Chai, “An empirical study on energy disaggre- process taking only 0.3 seconds but scored the worst in gation via deep learning,” Advances in Intelligent Systems terms of performance. Research, vol. 133, pp. 338–342, 2016. 190 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek D Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume D Delavnica projekta Insieme Insieme Project Workshop Uredniki / Editors Matjaž Gams, Primož Kocuvan, Flavio Rizzolio http://is.ijs.si 5. oktober 2021 / 5 October 2021 Ljubljana, Slovenia 191 192 FOREWORD The year 2021 is the first Insieme (ISE-EMH) Workshop since we have reached some achievement to present in the second year of the Insieme Italian-Slovenian Interreg project. Unfortunately, 2021 is also the second year of the Covid-19 pandemics, causing several problems. For one thing, we received less papers for the workshop than expected, although still quite a reasonable number. The second undesired Covid-19 problem is that the participants will not be able to meet in person and discuss the presentations and also the Insieme project progress. There is a certain difference when people meet alive and discuss issues also in the free time after the conference compared to the virtual official-time only events. However, that is the reality that we face these months. Nevertheless, the Insieme Worksop was proclaimed open to the broader area of Electronic and Mobile health (EMH). As a result, a couple of quite interesting papers were submitted, while on general the quality was extraordinarily high for a workshop. Some of the Insieme and EMH papers seem to bear a huge potential to progress towards decent SCI papers since they indeed tackle important issues and present novel research ideas and methods. Some of the additional papers deal with the research that yielded 2nd place in one of the top worldwide Xprize competitions for non-pharmaceutical measures against Covid-19. This research also resulted in some other awards, e.g. at the ETAI conference. There are 13 accepted papers for this year's workshop. Nine of them are related to JSI and the other four to the Insieme project partners. Each Insieme partner submitted at least one paper, which demonstrates the successful cooperation on this project. The workshop consists of two subsections. One is directly related to the Insieme project and the other is for general EMH topics, mainly to the Covid-19, and Comparison between health platforms – another European project Platform Uptake. Flavio Rizzolio, Primož Kocuvan Program Chairs 193 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Flavio Rizzolio (Chair) Rossella Gratton Diego Santaliana Matjaž Gams Primož Kocuvan Simon Ražman Samo Eržen 194 Platform for Multi-Omics Integration (PlatOMICs) applied to skin diseases with alterations in Notch signaling pathway. Lucas Brandão Paola Maura Tricarico Rossella Gratton Department of Medical Genetics, Department of Medical Genetics, Department of Medical Genetics, IRCCS Burlo Garofolo, IRCCS Burlo Garofolo, IRCCS Burlo Garofolo, Trieste, Italy Trieste, Italy Trieste, Italy lucabrand@gmail.com paolamaura.tricarico@burlo.trieste.it rossella.gratton@burlo.trieste.it Ronald Moura Sergio Crovella Department of Medical Genetics, Department of Biological and IRCCS Burlo Garofolo, Environmental Sciences, College of Trieste, Italy Arts and Sciences, University of ronald.rodriguesdemoura@burlo.trieste Qatar, Doha, Qatar sgrovella@qu.edu.qa ABSTRACT 1 INTRODUCTION Over the last years, a huge amount of information concerning Omics data have been produced and are of crucial Permission to make digital or hard copies of part or all of this work for significance for the understanding of the molecular personal or classroom use is granted without fee provided that copies are not mechanisms and for the identification of potential molecular 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 targets associated to many diseases. Indeed, Omics components of this work must be honored. For all other uses, contact the approaches allowed to initially decipher several biological owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, processes found to be critically involved in the context of Slovenia © 2020 Copyright held by the owner/author(s). various pathologies. Despite these remarkable scientific advances, the majority of obtained results are disconnected We developed a Platform for Multi-Omics Integration and divergent, making their use limited. Thus, our team (PlatOMICs) that assembles a set of tools and bioinformatics started the deployment of PlatOMICs, a new Platform for applications that can allow the retrieval of scientific literature multi-omics integration, carrying an user-friendly interface. data (genomics, epigenomics, transcriptomics, proteomics Currently, PlatOMICs is under deployment in an and microbiomics) together with the analysis, deciphering, international cooperation including Brazil, Qatar and Italy interpretation and integration of all these set of information and has been divided into three phases. In the present work automatically, therefore building networks of molecular we report phase I in which multiple interactions and Omics meta-analysis. database/resource/repositories were interrogated to access Our goal is to refine the data available in scientific literature data from skin diseases presenting alterations in Notch and in Omics databases/resource/repositories relative to skin signaling pathway, as they constitute a cluster of disorders diseases that are characterized by defects in Notch signaling that were extensively studied during the Omics era, in order route, seeking to describe networks of molecular interactions to perform biological syntactical analysis to be implemented in the epithelial tissue potentially involved in the loss of in the next PlatOMICs phases. homeostasis in this district, event that may lead to the onset of different skin pathologies. 1.1 Multi-omics integration applied to skin diseases with KEYWORDS Notch signaling alterations Omics, genomics, transcriptomics, proteomics, network interaction, skin diseases. An aberrant progression of Notch signaling, either due to altered regulation or direct mutations, can induce skin diseases [1,2]. To date, molecular alterations in Notch signaling pathway have been reported for five human skin diseases including: Hidradenitis Suppurativa (HS), Dowling Degos Disease (DDD), Adams–Oliver Syndrome (AOS), Psoriasis (PS) and Atopic Dermatitis (AD) [1,3]. Therefore, a deep characterization of this cellular route seems to be of 195 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Brandão, et al. pivotal importance in order to clarify potential new performed, hence securing a more reliable and homogeneous pathogenic scenarios involved in these skin diseases. Indeed, investigation. Therefore, PlatOMICs will contain the results considering this critical aspect, in order to further restrict the obtained from literature and their integration, databases and search, we decided to consider in this study only skin new Omics studies. diseases possessing alterations in Notch pathway excluding malignancies. 2 RESULTS These skin disorders have been thoroughly studied in the last five years; indeed, 1555 articles regarding these five diseases As a validation model, phase I of PlatOMICs was executed and OMICs (genomics, transcriptomics, proteomics and on skin diseases presenting alterations in Notch signaling microbiomics) studies are available in PubMed [4]. pathway by examining the literature, thus providing Specifically, considering these five skin disorders possessing molecular insights to multi-omics integration approaches. alterations in Notch signaling, 821 articles about genome, 2.1 Results deriving from literature analysis: molecular 225 about transcriptome, 143 about proteome and 602 about insights to multi-omics integration microbiome, were published. The literature scan was accomplished by assessing the 1.2 Perspectives on multi-omics integration for skin following term "(Hidradenitis Suppurativa OR Dowling diseases with alterations in Notch signaling pathway Degos Disease OR Adams Oliver Syndrome OR Psoriasis OR Atopic Dermatitis) AND (Genome OR transcriptome OR Currently, PlatOMICs is under deployment in an proteome OR epigenome OR microbiome OR metagenome international cooperation including Brazil, Qatar and Italy. OR metabolome OR omic OR multi-omic) AND 'Homo PlatOMICs will be an online platform offering services to sapiens'[orgn:__txid9606]" using the DaVinci tool. access and analyze scientific literature and Omics data A DaVinci literature database (DaVinci Lit) was created automatically with great accuracy. The deployment was with 1252 articles retrieved from PubMed, and amongst all divided into three phases and in the present work, we report recovered papers 82 were excluded due to the absence of phase 1. Briefly, the various phases that constitute abstract/summary. Next, the remaining 1170 articles were PlatOMICs multi-omics analysis are given by: phase I, step analyzed, classified and categorized. The most cited words based on the interrogation and analysis of the whole available were 'skin' and 'patient'. The words ‘immune’, literature and Omics databases; phase II, stage regarding the ‘inflammatory’ and ‘inflammation’ were common. 742 analysis and questioning of previous and new Omics (or (63.4%) of articles cited, at least once, one of the indicated multi-omics) studies; phase III, part relative to the merge of words. Next, we seeked the context of each of these terms, findings deriving from phases I and II in order to finally revealing that they were mainly used to explain the immune compose the ultimate multi-omics integration in a meta- and inflammatory conditions of each disorder. 'Expression' multi-omics analysis (Figure 1). was cited along 333 (28.4%) articles to demonstrate molecular expression on experimental works of transcriptome (48 articles), epigenome or methylome (36 articles) and proteome (12 articles). The last word worth commenting is 'gut'. Gut was present in 158 articles and refers to the existing relationship between gut dysbiosis and the onset of allergic, the latter also represents a term included in the top cited words, disbalance. The overview of word atomization enabled us to understand what was the main focus of Omics literature for skin diseases with alterations in Notch signaling pathway. Next, we categorized the whole DaVinci Lit into five classes of Omics. Most of the articles were included as a genome or microbiome (metagenome) study, followed by transcriptome and multi-omics approaches (Table 1). Moreover, in the Figure 1. Workflow of OMICs Platform (PlatOMICs) for Omics multi-omics category, the most commonly employed integration. (1) The user informs the descriptors, categorical approaches included the combination between genome and terms and keywords in PlatOMICs. (2-3) Through DaVinci tool, transcriptome and genome and microbiome. the literature and the OMICs databases will be evaluated. (4) Selected omics studies and new ones are (re)analyzed and integrated by standard pipelines. (5) PlatOMICs produces the final meta-analysis multi-omics integration results in a friendly Category Number of article interface. Genome 245 The first analysis (phase I) outputted by PlatOMICs is Microbiome 241 performed by the new tool called DaVinci Literature and Transcriptome 97 Database Analysis (under submission and not publicly available) . Briefly, DaVinci is able to scan several databases, Proteome 32 such as PubMed, SRA, GEODatabase and GWAS Catalog, Metabolome 2 extracting multiple information from summary, abstracts and other meta-data information to report a syntax analysis and Multi-Omics 95 molecular panels (genes, variants, tissues, cells and drugs). Next, following the study and sample selection from the Table 1. Omic categorization of literature from Omics studies previous researches, raw data might be downloaded. The concerning skin diseases with alterations in Notch signaling analysis, including the new Omics (or multi-omics) studies, pathway. will be carried out by the same standard pipeline when 196 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Brandão, et al. The next step in PlatOMICs is to extract genes and variants networks, underlining both health and diseases states, using from the literature. The goal is to unravel genes/variants existing data. The presented platform for multi-omics previously established as involved with skin disorders integration constitutes a time-saving and cost-efficient characterised by alterations in Notch signaling route. In this approach that might surely guide researches in the circumstance, the gene atomization process retrieved 546 advancement of more elaborate and articulated hypothesis. genes. From obtained genes, we extracted each time the Indeed, PlatOMICs is able to refine, assemble and integrate context in which the gene was cited. In total, 465 articles and thousands of information spread around multiple 1308 gene contexts were analysed. Subsequently, four database/resource/repositories. In the future, PlatOMICs will researchers classified, independently, the gene relations as present an intuitive and automated friendly web-end interface associated or not associated with the disease. Of these, 80 with accessible tables, graphs and images. genes were excluded, and 426 genes were associated. The accumulation of scientific texts and Omics data settled in Next, PlatOMICs outputted the top 10 pathways and gene various databases may have never been correlated and ontology (GO) predicted by these genes (Table 2). analysed in conjunction. In this perspective, it is presumable Enrichment pathway and a GO analysis were conducted by that significant scientific responses may have been generated reactomePA, limma and topGO Bioconductor package. The but are still uncovered. In this critical context, PlatOMICs pathway reveals the role of interleukin (IL) signaling, mainly was developed in order to promote the analysis and driven by IL-4, IL-13 and IL-10. GO adds the defense integration of the available Omics data, and in the present response and interspecies interactions between organisms. study we applied PlatOMICs for the analysis of skin diseases Collectively, both descriptions point out that inflammation as a validation model. Our approach allowed us to further and skin microbial host defense are to be considered as key emphasize that our integrated strategy seeks to identify a outcomes from the global literature findings, suggesting that common link between skin diseases and deregulations in these pathways and GO should be included in future Omics homeostatic processes in epithelial tissues. studies. PlatOMICs also performed a gene atomization on DaVinci ACKNOWLEDGMENTS Omics. This analysis was assessed on 158 genes, most of which were found to be similar to the DaVinci Lit output. Equals enriched pathways and GO from Table 2 were found, This work was supported by a grant from the Institute for thereby ratifying the importance of these pathways and GO Maternal and Child Health IRCCS “Burlo Garofolo/Italian on multi-Omics integration. Ministry of Health” (BioHub 03/20), by the grant Interreg Italia-Slovenia, ISE-EMH 07/2019 and by CNPq 3 CONCLUSION (311415/2020-2). The scientific goal of PlatOMICs is to promote the understanding of biological mechanisms and molecular Reactome ID Pathway Description GO ID GO Description R-HSA-449147 Signaling by Interleukins GO:0034097 Response to cytokine R-HSA-6785807 Interleukin-4 and Interleukin-13 signaling GO:0019221 Cytokine-mediated signaling pathway R-HSA-6783783 Interleukin-10 signaling GO:0071345 Cellular response to cytokine stimulus R-HSA-877300 Interferon gamma signaling GO:0002376 Immune system process R-HSA-447115 Interleukin-12 family signaling GO:0006952 Defense response R-HSA-8854691 Interleukin-20 family signaling GO:0009605 Response to external stimulus R-HSA-913531 Interferon Signaling GO:0044419 Interspecies interaction between organisms R-HSA-380108 Chemokine receptors bind chemokines GO:0070887 Cellular response to chemical stimulus R-HSA-451927 Interleukin-2 family signaling GO:0010033 Response to organic substance R-HSA-1059683 Interleukin-6 signaling GO:0051707 Response to other organism Table 2: Top 10 Enriched pathway and a gene ontology of 426 genes associated with skin diseases with alterations in the Notch signaling pathway. 197 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Brandão, et al. REFERENCES [1] Gratton R., Tricarico P.M., Moltrasio C., Lima Estevão de Oliveira A.S., Brandão L., Marzano A.V., Zupin L., Crovella S. Pleiotropic Role of Notch Signaling in Human Skin Diseases. Int. J. Mol. Sci. (2020), 21(12):4214. doi: 10.3390/ijms21124214. [2] Siebel C. and Lendahl U. Notch Signaling in Development, Tissue Homeostaasis, and Disease. Physiol Rev. (2017), 97(4):1235-1294. doi: 10.1152/physrev.00005.2017. [3] Massi D. and Panelos J. Notch Signaling and the Developing Skin Epidermis. Adv Exp Med Biol. (2012), 727:131-41. doi: 10.1007/978-1-4614-0899-4_10. [4]https://pubmed.ncbi.nlm.nih.gov/?term=%28Hidradenitis+ Suppurativa+OR+Dowling+Degos+Disease+OR+Adams- Oliver+Syndrome+OR+Psoriasis+OR+Atopic+Dermatitis%2 9+AND+%28genome+OR+transcriptome+OR+proteome+O R+microbiome%29&filter=pubt.classicalarticle&filter=pubt. clinicalstudy&filter=pubt.clinicaltrial&filter=pubt.comment &filter=pubt.dataset&filter=pubt.journalarticle&filter=pubt.le tter&filter=pubt.observationalstudy&filter=pubt.technicalrep ort&filter=years.2016-2020, last accessed on November 18, 2020). 198 Implementing the INSIEME portal according to the patients and caregivers’ point of view Ivana Truccolo† Virginia Gerlero Flavio Rizzolio ANGOLO OdV, Italian Venetian Cluster Department of Molecular Sciences Association of Long-term Cancer virginia.gerlero@venetiancl and Nanosystems, Ca’ Foscari Survivors, President University of Venice uster.eu ivanatruccolo@gmail.com flavio.rizzolio@unive.it Vincenzo Canzonieri Anatomia Patologica, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Department of Medical, Surgical and Health Sciences, University of Trieste vcanzonieri@cro.it Figure 1: Official logotype from the project In the health sector as well, technology can help people tracking ABSTRACT / POVZETEK and controlling their own health information and make informed decisions about their health but only at two conditions2: The 2030 Agenda for Sustainable Development highlights that the spread of information and communications technology and global interconnectedness has great potential to accelerate human progress, to bridge the digital divide and to develop - Technology must be really accessible knowledge societies1. - Health information must be really understandable, scientifically correct and aligned with the reality The project Interreg Italia Slovenia ISE-EMH aims to create a †Corresponding name health portal integrating useful information about health topics Permission to make digital or hard copies of part or all of this work for personal or and health facilities related to a specific interregional area both classroom use is granted without fee provided that copies are not made or distributed in Slovenian and Italian languages. INSIEME is the name of the for profit or commercial advantage and that copies bear this notice and the full portal. 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 C opyright held by the owner/author(s). 1 WHO, Draft Global strategy on Digital Health 2020-2025. Available at http://bit.do/fLkpp 2 Australia’s health 2018, available at http://bit.do/fLkoA 199 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ivana Truccolo et al. KEYWORDS - Social services: the individual municipalities of the province of Oncology, health topics, health facilities, patients, caregivers, Venice and the Region of Friuli Venezia Giulia offer social cancer survivors, digital health services to citizenship - Physiotherapy and rehabilitation services: as far as the province of Venice is concerned, the two main departments of Physical 1 Introduction Medicine and Rehabilitation of the San Giovanni e Paolo The contribution of the Ca' Foscari University, partner of the Hospital of Venice and the Angelo Hospital of Mestre have been project, was to integrate into this portal INSIEME some described. In addition, the local rehabilitation and physical categories of useful resources related to the cancer topic. The therapy services in the different health and social authorities have selection of these categories was made with the contribution of a been listed. About the Friuli Venezia Giulia Region, the two cancer survivors and caregivers association. It is a fact that very University & health agencies of Udine and Trieste have been often a patient relies on the search engines algorithms to find out described, in addition to health services of home rehabilitation the information he/she needs. But it happens that resources - Psychological services: the family counselors are available in ranked as not important by the search engines are actually very the metropolitan area of Venice and in the Friuli Venezia Giulia useful to him/her. So, the point of view of some individuals, both Region. In addition, the ANT Foundation 1978 Onlus has been cancer patients and caregivers, was the main guide to identify the described that offers psychological support at home to all resources to be listed in the portal. Not only the management of patients. the cancer disease is important to a patient but also his/her mental - Accommodation services: accommodation facilities near the condition, his/her wellness and practical things such as main hospitals have been described with the information of their accommodation and work related issues websites. Some of them are free, others offer low price 3 . There are good examples of this integration accommodation. In addition, the channels of Airbnb and 4 Booking.com have been reported; 2 Results - Information and advocacy services for the protection of patients' rights: for both areas were listed the main services A preliminary search was made to find out informational - Administrative services resources about cancer to widen the spectrum of categories and - Local health and social services - Screening: the cancer services. Then we tried to categorize the cancer services related prevention opportunities of the Friuli Region has been listed both to the area of the metropolitan city of Venice and the Region - Local social and health services - Palliative care: the Health Friuli Venezia Giulia. District of Mirano and Dolo has been reported with regard to palliative care services; In addition to basic services, the search has highlighted the - Specialized voluntary associations through the useful webtool following complementary categories: of Oncoguida 5 , the large number of voluntary associations operating in the area of Venice and Friuli can easily be identified. - Hospital services - websites with dealing with current information about cancer - Social services topics and tools to easily discover fake news were also described - Physiotherapy services - websites with patients stories or personal narrations were also - Physical activities opportunities and related opportunities indicated as they are very helpful to patients wellness. - Psychological services Last but not least the websites related to all the hospitals and - Accommodation services for patients and/or family members Health Comprehensive Centers of the Friuli Venezia Giulia - Information and counselling services about health topics and Region and Venice area were listed and described. patients' rights - Administrative services - Local social and health services – screening - Local social and health services - palliative care - Voluntary associations - Independent information on cancer - Information on fake news For each category, a minimum of 5 websites was listed if available. Below a brief summary of the research carried out through the consultation of a large number of websites. - Hospital health services: no 15 facilities were found in the province of Venice and no 24 in Friuli Venezia Giulia. 3 Truccolo I, Cipolat Mis, C, De Paoli P (eds), Insieme ai pazienti. Costruire la Stakeholder Co-Design. J Med Internet Res. 2019 Feb 11;21(2):e11371. doi: Patient Education nelle strutture sanitarie. Il Pensiero scientifico, 2016 10.2196/11371 4 Kildea J, Battista J, Cabral B, Hendren L, Herrera D, Hijal T, Joseph A. Design 5 Oncoguida, available at 5 http://www.oncoguida.it/html/home.asp and Development of a Person-Centered Patient Portal Using Participatory 200 Insert Your Title Here Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 3 Conclusions The different categories of resources integrated into the INSIEME portal are not exhaustive of course. They just give a hint of the importance of taking into account both informational and practical resources and involving patients and caregivers in the building of digital health portals ACKNOWLEDGMENTS The paper was supported by the ISE-EMH project funded by the program: Interreg V-A Italy-Slovenia 2014-2020. We thank the patients and caregivers that help to identify the resources listed in the portal. REFERENCES [ 1 ] WHO, Draft Global strategy on Digital Health 2020-2025. Available at http://bit.do/fLkpp [2] Australia’s health 2018, available at http://bit.do/fLkoA [3] Truccolo I, Cipolat Mis, C, De Paoli P (eds), Insieme ai pazienti. Costruire la Patient Education nelle strutture sanitarie. Il Pensiero scientifico, 2016 [4] Kildea J, Battista J, Cabral B, Hendren L, Herrera D, Hijal T, Joseph A. Design and Development of a Person-Centered Patient Portal Using Participatory Stakeholder Co-Design. J Med Internet Res. 2019 Feb 11;21(2):e11371. doi: 10.2196/11371 [5] Oncoguida, available at http://www.oncoguida.it/html/home.asp Figure 2: View of the Oncology section in the INSIEME portal 201 An Analytical and Empirical Comparison of Electronic and Mobile Health Platforms Primož Kocuvan Erik Dovgan Matjaž Gams primoz.kocuvan@ijs.si erik.dovgan@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 The rest of the paper is organized as follows: In Section 2, Electronic and mobile health (EMH) is a new way of deliver- we describe existing platforms. Section 3 presents the ISE-EMH ing health services to patients with the use of small portable platform, The results of analytical and empirical comparison devices like mobile phones or tablets. The term electronic indi- of the platforms are given in Sections 4–5. Finally, Section 6 cates that doctors and medical personnel use electronic health summarizes the paper with ideas for future work. records or electronic prescribing of medicine for patients. Some countries like Slovenia, use electronic prescriptions of medicine 2 AN OVERVIEW OF EXISTING EMH for many years now. According to World Health Organization PLATFORMS (WHO), mHealth has the ability to transform the delivery of health services all over the world and bring about a paradigm 2.1 Genoa shift in healthcare delivery processes [6]. By using technologi- Genoa is a platform that offers telepsychiatry services [5]. It is, cal innovations we can overall improve healthcare not only in for now, available only in the United States. It connects people developed countries but also in countries that are still in the (patient-doctor) through a system of video-conference technol- developing phase. In these countries, there is a lack of doctors, so ogy. Telepsychiatry is a branch of telemedicine where they only optimizing the process of delivering medicine and information provide help for psychiatric and mental disorders. to the patients is very desirable. In this paper, we describe some of the EMH online available platforms and compare them with 2.2 DigiGone the one which we developed within the ISE-EMH project. DigiGone is a packet of services, including a medical one called DigiMed [2]. Their philosophy is like that of Genoa. However, KEYWORDS they offer general medical services, not only for psychiatric prob- mHealth, eHealth, electronic and mobile health, EMH, compari- lems. For example, when applying as a patient, you get a technical son of EMH platforms, ISE-EMH kit. When you have an appointment with a doctor, your nurse or caregiver comes to your home and examines you, and via video 1 INTRODUCTION conference tells the information to a doctor. In this kit, you have From the early beginning of the web when there was only limited also an ultrasound device, so it can stream the data to the doctor information about key institutions, e.g., universities, libraries, in real-time. and organizations, available on the web and till this day where we can find practically anything including illegal organizations 2.3 Doxy.me and activities, the public need platforms or portals which will Doxy.me is a free telemedicine service, implemented as a web aggregate all useful information on one central place. While application, thus no installation is needed. It is also accessible anything can be found on the web, it is often difficult to find from various devices. All you need is a microphone and a web proper and useful information [9]. camera. All the data is encrypted and also no account is needed, To overcome the issues of disinformation especially in the in contrast to many other platforms [3]. field of medicine and products for the elderly, as part of the ISE- EMH project we implemented a unified EMH platform together 2.4 eVisit with an application for smart hardware devices. We described the application for smart devices in [9]. The EMH platform is eVisit is a telehealth service that is not free of charge. For the a central entity where the user can find key information about doctors and patients it offers virtual flexible scheduling [4]. For health and elderly, and where he can converse with other patients doctors it provides a list of medications for prescription to pa- and doctors via text- or video-based call centers, or exchange tients, which is a very convenient and helpful feature that saves information, e.g., x-ray images or photographs of the patient time. Other platform services are similar to the already described skin. We analytically and empirically compare the existing EMH ones in other telemedicine platforms. platforms with each other to learn more about the pros and cons, and to improve the ISE-EMH platform in the future. 2.5 iPath iPath is the oldest telemedicine platform from the early begin- Permission to make digital or hard copies of part or all of this work for personal ning of the development of protocols for the internet. iPath is a 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 case-based collaboration platform that is used in telemedicine the full citation on the first page. Copyrights for third-party components of this applications to share information within a distributed group of work must be honored. For all other uses, contact the owner/author(s). people. It is being used in the domains of consultation, teach- Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). ing and research [8]. It is also multilingual like the ISE-EMH platform. 202 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Primož Kocuvan et al. 2.6 MedSymphony the patients can converse with each other in the public chan- The MedSymphony platform is build for telemedicine electronic nels, where they can exchange thoughts / opinions about their and mobile health, MedSymphony is directed to accelerate the diagnosis, disease or condition. Also, the platform includes a use of telemedicine as a key platform for providing health care. virtual assistant (bot) and connects it with the Rocketchat sys- The key feature is to provide better health care for millions of tem. The purpose of bot is to answer questions about medicine, patients anywhere and anytime. MedSymphony was created to partners, waiting queues, and similar. This is helpful when no qualify doctors, medical personnel, caretakers and health institu- doctor is available. There is also an advanced search mechanism, tions as well as patients with a complete electronic and mobile implemented with the versatile, fast, and efficient Elasticsearch. health technology platform. The platform includes everything The ISE-EMH platform development will result in an EMH you need to establish a video-based doctor’s office. – a completely ecosystem that will include/provide [7]: cloud-based compliant solution with integrated video conferenc- • A platform that connects products and services, i.e., the ing, online prescription ordering joined with SMS, MMS, and backbone of the ecosystem; email integration to facilitate the doctor-patient relationship, and • Integration and connection of existing products, services, automated billing for recurring and one-time fees [10]. and systems through the platform in a complete ecosys- tem. 2.7 Bodi Zdrav 4 ANALYTICAL COMPARISON Bodi Zdrav (in English "Be Healthy") is a Slovenian health-related platform [1] and it is only meant for patients in Slovenia. Its pur- The described platforms were compared with respect to a set of pose is to give information about the services and to connect selected features (see Section 4.1). The comparison was performed the patients and doctors. It only offers services that are not offi- analytically and empirically, where the results of the former cially recognized in medicine, e.g., homeopathy, bio-resonance, evaluation are presented in Section 4.2 and the results of the hypnotherapy, etc. Its main content is a search function through latter one are given in Section 5. regions in Slovenia and filtering of services from specific medical branch. 4.1 Choosing the Features for Comparison The set of features for the platform comparison consists of care- fully selected features, selected based on the state-of-the-art re- 2.8 EcoSmart search in the EMH domain. Demographic and social character- The EcoSmart project was a three-year project that included the istics were also carefully taken into account, e.g., if it is free of participation of 26 partners. It included smart cities as well as charge for using it and if it is available in more than one lan- eHealth and mHealth domains. Within the project, an electronic guage. We also included some of the other key features which and mobile health system was developed. The purpose of the are important for user experience, e.g., if it has a GUI and if it is system was to provide key information about the project partners responsive or not. The selected features are the following: and municipalities in Slovenia, as well as health domains and prototypes. It also included a smart bot for which the main task • Free: Is the EMH platform free of charge to use it? was to answer questions to users. • Graphical user interface: Does it have a GUI or is it just text-based? • Dynamic data: Can we insert new data and update the 3 THE ISE-EMH PLATFORM fields via a form? 3.1 Basic Information • Responsive: Is the web platform responsive, which means, The ISE-EMH platform is being developed within an Interreg does it automatically resize the website when viewing on Italy-Slovenia project, where the final goal is to develop a unified the different devices? telemedicine (EMH) platform for both Slovenian and Italian pub- • Virtual assistant: Does the platform offer the chance to lic and private institutions, with the aim of accelerating the coop- talk with a bot, e.g., about medicine, diagnosis, partners, eration between Italian and Slovenian stakeholders and transfer etc.? knowledge from academic field into practice. The platform in- • Use without registration: Can we use the EMH platform cludes new diagnostic approaches, advanced sensors, including without registration? devices that monitor vital signs, and also methods of Artificial • Multilingual: Is the EMH platform available in more than Intelligence (AI) that will help patients overcome anxiety, depres- one language? sion and sedate stress. By connecting various stakeholders, the • Official medicine: Does the EMH platform offer services platform also aims at overcoming the main problem of EMH that to the people from only official (recognized) medicine? is the lack of transfer of innovative services from laboratories • Call center: Does the EMH platform offer call centers (text- into practice, due to the lack of support services in terms of both based or video-based) for getting help? ICT systems and human partners, and their integration [9]. • General medicine: Does it offer services from different medicine practices or only one? 3.2 Detailed Description of the ISE-EMH 4.2 Results of the Analytical Comparison Platform The results of the analytical comparison of platforms are shown The purpose of the ISE-EMH is to connect different partners, in Table 1. Based on these results we constructed a histogram medical personnel, doctors, patients, and end-users. This is done of features, where each bar presents the percentage of included through different logic and programmatic mechanisms. The plat- features in a specific EMH platform (see Figure 1). This histogram form uses the Rocketchat text-based communication system to shows that the worst platforms with respect to the chosen fea- enable users, e.g., patients to send questions to doctors. Also, tures are Genoa and BodiZdrav. 203 An Analytical and Empirical Comparison of Electronic and Mobile Health Platforms Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 5.2 EcoSmart User Experience The EcoSmart platform has a simple and sleek graphical user interface design. When the user first visits the page it has ten categories on the landing page. It does not provide a search tool, but it has a link to the EcoSmart bot and other bots on the page (see Figure 3). Figure 1: A histogram of platform feature percentages, where each bar represents the percentage of checkmarks from Table 1. For Genoa the cons are that it is not free, it does not have a virtual assistant, e.g., a bot that can answer your question at any Figure 3: EcoSmart Homepage. time of the day, you cannot use it without registration, it is not multilingual, and also the usage is limited to only psychiatric conditions, since they are specialized only in telepsychiatry. 5.3 ISE-EMH User Experience For BodiZdrav the cons are that it does not have a virtual as- The ISE-EMH platform has an original graphical user interface sistant, it is only available in the Slovenian language, the services design. A user visiting the page for the first time has all the com- which they offer are not from officially recognized medicine, it ponents on the landing page (see Figure 4). These components does not have call centers, and also they do not have services are a virtual assistant, services, search tool, and button for chang- from general medicine but only alternative medicine. ing the language. This is very crucial when users need to find The most versatile and useful system based on the selected specific information fast. The user interface is constructed and features is the ISE-EMH platform. designed in such a way that every person no matter the age can use the platform. 5 EMPIRICAL COMPARISON OF SIMPLY ACCESSIBLE PLATFORMS Among the evaluated platforms, the ones that are simply acces- sible, i.e., they do not require to create an account to use them, were further analysed. This analysis was empirical, from the user perspective usage, and it also included side features such as user story. Based on the simply accessible criterion, three systems were empirically analysed: Bodi Zdrav, EcoSmart and ISE-EMH. 5.1 Bodi Zdrav User Experience The Bodi Zdrav platform has a good graphical user interface design. When the user visits the page, it has only one component Figure 4: ISE-EMH Homepage. on the landing page, i.e., a search. The user can select a category and a region, which act as filters for search. As already mentioned, it does not have a virtual assistant nor call centers (see Figure 2). 6 CONCLUSION In this paper, we described and compared a set of most important EMH platforms that are available on the web. Also, we presented the developed ISE-EMH platform. We also analytically compared these platforms based on a selected set of key features. In addition, a subset of platforms was empirically compared by focusing on a user’s point of view. This analysis shows that the best-rated platform is the ISE-EMH platform. In our future work, we will test our hypothesis stating that a user can find specific information about health-related topics on the ISE-EMH platform in under 30 seconds, instead of search- ing for more than 30 minutes on other platforms or through the search engine like Google or Bing. We will conduct the experi- Figure 2: Bodi Zdrav Homepage. ment with the help of volunteers, where they will try to find 10 randomly selected services on the ISE-EMH platform and also using a general search engine. 204 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Primož Kocuvan et al. Genoa DigiGone Doxy.me eVisit iPath MedSymphony BodiZdrav EcoSmart Insieme Free ✗ ✗ ✓ ✗ ✓ ✗ ✓ ✓ ✓ User-friendly ✓ ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✓ Graphical user interface ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Dynamic data ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✗ ✓ Responsive ✓ ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✓ Virtual assistant ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✓ Use without registration ✗ ✗ ✗ ✗ ✓ ✗ ✓ ✓ ✓ Multilingual ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✓ Official medicine ✓ ✓ ✓ ✓ ✓ ✓ ✗ ✓ ✓ Call center ✓ ✓ ✓ ✓ ✗ ✓ ✗ ✗ ✓ General medicine ✗ ✓ ✓ ✓ ✓ ✓ ✗ ✓ ✓ Table 1: Comparison between the analysed EMH platforms. ACKNOWLEDGMENTS [5] Genoa Telepsychiatry. 2021. https://genoatelepsychiatry. The paper was supported by the ISE-EMH project funded by com. the program Interreg V-A Italy-Slovenia 2014-2020. We thank [6] Varadraj P. Gurupur and Thomas T. H. Wan. 2017. Chal- students Urša Klun, Lan Sovinc and Jan Urankar for helping at lenges in implementing mhealth interventions: a technical the implementation of the ISE-EMH platform. perspective. mHealth, 3, 8. [7] Insieme: Full General Electronic and Mobile Health Plat- REFERENCES form. 2021. https://www.ita-slo.eu/en/ise-emh. [1] BodiZdrav: Free eHealth Solution and Search Engine for [8] iPath.me: Free EMH Solution. 2021. https://www.ipath- Ehealth. 2021. https://bodizdrav.net/. network.com/ipath. [2] DigiGone: Telemedicine and Other Services. 2021. https: [9] Primož Kocuvan, Matjaž Gams, and Jakob Valič. 2021. An- //www.digigone.com/home-health-care. droid application for distance monitoring of elderly pa- [3] Doxy.me: Free Telemedicine Solution. 2021. https://doxy. rameters. In Proceedings of the Information Society 2021. me/. Submitted for publication. [4] eVisit: Telemedicine Solution and Other Services. 2021. [10] MedSymphony: Advanced Mobile Health Platform. 2021. https://evisit.com/platform/overview. https://www.medsymphony.com/. 205 Android Application for Remote Monitoring of the Elderly’s Parameters Primož Kocuvan Jakob Valič Matjaž Gams primoz.kocuvan@ijs.si jakob.valic@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 for smart devices. The platform includes new diagnostic ap- proaches, advanced sensors, including wearable devices that According to the latest predictions, the average age in Europe monitor vital signs, and sophisticated computer algorithms and in 2050 will be 49, whereas today it is only 39 years [3]. Europe, artificial intelligence methods that gain new knowledge from therefore, faces quite a significant population problem. With data. The main problem regarding the introduction of EMH re- insufficient numbers of young workers, we need technical, eco- mains the transfer of innovative services from laboratories into nomic, and political solutions to help the elderly maintain vitality practice, as there is a lack of support services in terms of both and independence. The aim of technical solutions is to delay the ICT systems and human partners and their integration. As a rule, departure of the elderly to a retirement home and to help main- researchers can not find commercial partners for even the most taining the economic stability of the country. In this paper, we excellent academic prototypes, while the prototypes are rejected describe an application that helps the elderly and relieves the due to inertia, despite the indisputable advantages of both ICT society and economy. We present the technical specifications and and knowledge. It is difficult to implement novel ICT solutions features of the Android application, which was developed as part to the elderly. The key purpose of this project is to accelerate of the project ISE-EMH (Insieme) with the collaboration of IPM the cooperation of Italian and Slovenian stakeholders in the field Digital within the project HoCare 2.0. The Android application of EMH and the transfer of knowledge, systems, and services is created and intended for usage for the pairs: one elder and one of EMH from the academic sphere to actual use. The other pur- caretaker (e.g relatives, nurses, paramedics). pose is to enable better connections between users and providers. KEYWORDS While anything can be found on web, it is often difficult to find proper information. Bearing these specifications in mind, sev- Android application, care for the elderly, elder, caretaker, fall eral applications are being included in the platform, one of them detection, easy to use, ISE-EMH, Insieme, HoCare 2.0 being the Android application presented here. 1 INTRODUCTION 1.2 Chosen Android OS and programming Due to the development and introduction of so-called MEMS language (Microelectromechanical systems) technologies in mobile devices, According to the global market share in Table 1, obtained in these became smarter in terms of tracking and perceiving the May 2021, the most used OS for smartphones is Android OS environment [1]. This is achieved by using accelerometer, GPS, with about 72% market share [2]. Therefore, Android OS was gyroscope, proximity sensor, and many other sensors. These chosen as the operating system for our application. Regarding sensors allow us to monitor the movement of a person, location the programming language, we were deciding between Kotlin and brightness of the room in which a person is located. This and Java. As Kotlin is a fairly new language, we had chosen Java. comes in handy in the research field of ambient intelligence. In Java is still a versatile and general programming language that our case, we developed an application for the elderly and their 1 runs inside Java Virtual Machine environment . caretakers which allows us to use these technologies. In this paper, we will describe the application and its technical features. The Table 1: Global market share for mobile phone’s OS paper is thus divided into two central sections. The first describes the functions that an elderly person can use and the second Operating system Market share in procent describes the functions caretaker can use. Finally, we describe the advantages and disadvantages of the developed application, Android OS 72.18% which were highlighted by the elderly in the performed focus iOS 26.96% group. Samsung 0.43% KaiOS 0.19% 1.1 Basic information about the project Unknown 0.14% Nokia Unknown 0.03% As part of the Insieme project, we implemented a unified EMH (Electronic and Mobile Health) platform together with software Permission to make digital or hard copies of part or all of this work for personal 1.3 Overview of the functions 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 Here is a list of all functions implemented. the full citation on the first page. Copyrights for third-party components of this The elder has access to these functions: work must be honored. For all other uses, contact the owner /author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia • reminders, © 2021 Copyright held by the owner/author(s). 1 The Kotlin also uses virtual environment 206 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Primož Kocuvan et al. • contacts, • SOS function, • settings, • fall detection, • pedometer, • alarm when searching for mobile phone, • alarm as a reminder to charge the battery. The caretaker has access to these functions: • overview of elder’s parameters, • history, • exact location of the elder, • sandbox settings, • enable/disable the settings for the elder. All functions for both the elder and the caretaker will be de- scribed in more details in the following sections. The application runs on two advanced mobile phones with Android OS. The general idea is that the elder needs help, support and monitor- ing of the caretaker, and the mobile phones enable the needed functionality. 2 THE INITIAL SCREEN First, user has to confirm and enable access to the services of the phone. The user has to grant application permissions of: • accessing the contacts, • accessing the location of the device, • accessing the multimedia and files, • recording and taking photography, • sending SMS messages, • making telephone calls, • audio recordings. Figure 1 presents the initial screen of the Android application. The elder and the caretaker enter their role. The selected role is set once for the application, and to change it, the application has to be installed again. On the initial screen, the user can select the language. The application is available in Italian, English, and Slovene. There is also a button on the bottom of the initial screen. By pressing it, a user can start or stop a function of searching the mobile phone by vocal call. 3 THE ELDER’S HOME VIEW AND FUNCTIONS 3.1 Sandbox Sandbox is a term that denotes the area of elder’s home, residence or a safe place defined by the elder during the initialization of Figure 1: The initial screen, shown during the first use of their profile. When the elder leaves the sandbox area, the care- the application. taker is notified via SMS message. The elder or caretaker can arbitrarily set the radius of a sandbox area from minimum of 0 meters and a maximum of 500 meters. Changing the distance by has no internet connection or GPS service turned on, the last elder is only possible when the caretaker allows it in the settings. location on the server is displayed to the caretaker. The elder can also enable the search for mobile phone function. 3.2 Battery If enabled, the mobile phone is constantly listening to its environ- The elder is alerted when the battery charge drops to 20%. In ment. In case the elder forgets the location of the mobile phone case the elder does not connect their phone to the charger, the and wants to find it, they should say the keyword "TSUNAMI" application warns them about it every 5 minutes. loudly and clearly. The mobile phone will start to vibrate and ring in order to reveal its location. 3.3 Mobile phone location and vocal search 3.4 Alarms and reminders The application is periodically sending the location of the mo- bile phone to the central server. From there, the information is The elder has an option of adding one-time or periodic alarms. transferred to caretaker’s mobile phone. In case the elder’s phone One-time alarms are designed for non-daily tasks such as visiting 207 Android Application for Remote Monitoring of the Elderly’s Parameters Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia response to the call of the first contact, it calls the second, and so on. The elder can add a maximum of three contacts to the SOS call list. The application has an implemented algorithm that detects the falls of the elder using the phone’s accelerometers. In order to do that, the elder must have a phone that has a built-in accelerometer. In case of false detection, the elder can press the "Cancel Fall" button. A SMS message is sent to the caretaker that either a fall or a false fall has occurred. 3.6 Phone book and pedometer The elder has the option of storing existing or new contacts in the app’s phone book. By arranging the contacts in the directory, priorities are assigned to the individual contacts for the SOS function. The app measures the number of steps that the elder has taken. Depending on the refresh interval, the application sends the data to the central server, from which the values can be read by the caretaker. 4 THE CARETAKER VIEW AND FUNCTIONS The motivation for the caretaker’s application is that it enables the caretaker to monitor and communicate with the elder. The elder’s application, on the other hand, has two modes of work: in case of elder’s inability to set technical functions, the elder has access to limited set of functions, such as calls, SOS button and similar. If the elder is still able to control the settings of the application, then all options are enabled. The caretaker has full control of all functions. 4.1 Sandbox In case of the caretaker, the sandbox area is denoting the home, residence, or safe place of each specific elder separately. The caretaker can arbitrarily change the radius of sandbox area from the minimum of 0 meters and the maximum of 500 meters. They do this by entering the more options extension of settings and using the slider to select the desired distance. In the menu, they can also enable access to the settings of a particular elder. 4.2 Battery At 15% charge of the elder’s battery, the application automatically sends a SMS message to the caretaker. The message contains a warning that the battery status of the elder’s mobile phone is Figure 2: The elder’s home view, after they enter their per- low. This gives the caretaker the chance to contact the elder and sonal data remind them about charging the phone. 4.3 Mobile phone location and vocal search a doctor. Periodic alarms are designed for daily tasks such as taking medications at a specific time. When the alarm goes off, The caretaker can see the last known location of the elder by the elder must confirm it. This sends a confirmation to the central pressing the "Show exact location" button. A Google map opens, server, from which the caretaker can check the status of alarms. where a blue dot indicates the last known location of the elder. If The elder’s access to the alarms can be seen on elder’s home page, the elder has internet connection and GPS location turned on, the depicted on Figure 2. last known location is also the current location of elder’s phone. The caretaker does not have the option to perform vocal search 3.5 SOS function and fall detection for their mobile phone. In the event of problems such as nausea or feeling unwell, the 4.4 Alarms and reminders elder can press the "SOS" button, which triggers a call for help by successively calling the contacts on the list. The application The caretaker sees the confirmation of specific elderly person’s calls contacts by the list order, i.e. priority. In case there is no alarms. 208 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Primož Kocuvan et al. 5 CONCLUSION We developed the Android application for the elderly and their caretakers. This article describes the features of the application. Sensors integrated into today’s smartphones and special soft- ware enable us to create applications which help the elderly live more independently. The drawbacks of the software which is now available on Google play market are: complicated usage, high price, lack of features. We designed the application bearing in mind ease of use for the elder and features that allow the care- takers to monitor the elderly anywhere anytime. Also, after the application is fully tested, it will be available for free. ACKNOWLEDGMENTS The paper was supported by the ISE-EMH project funded by the program: Interreg V-A Italy-Slovenia 2014-2020. We thank IPM Digital, which organized the focus group as part of the HoCare 2.0 project. We also thank students: Lukas Kranjc, Urša Klun and Jan Hrastnik for helping with implementation part of the project. REFERENCES [1] Abdullah Algamili, Mohd Haris, Md Khir, John Dennis, Abdelaziz Ahmed, Sami Omar, Saeed Ba Hashwan, and Muhammad Junaid. 2021. A review of actuation and sens- ing mechanisms in mems-based sensor devices. Nanoscale Research Letters, 16, (January 2021). doi: 10.1186/s11671- 021- 03481- 7. [2] 2021. Market share android vs ios and others. https : / / gs . statcounter . com / os - market - share / mobile / worldwide. (2021). [3] 2021. The european demographic deficit. https : / / www . europarl . europa . eu / sides / getDoc . do ? pubRef= - / / EP / /TEXT+ IM - PRESS + 20080414FCS26499 + 0 + DOC + XML + V0//EN. (2021). Figure 3: The caretaker’s home view 4.5 SOS function and fall detection The caretaker or elder’s relative or anyone on the elder’s SOS list receives a call for help. In case of a fall, the caretaker receives an SMS that there was a fall of the elderly. 4.6 Phone book and pedometer The caretaker does not have a phone book, but a list of the elderly they take care for. The caretaker has the option to call a specific elder by pressing their contact. For the caretaker, the application does not measure the number of steps made. However, the care- taker has the ability to review the number of steps for each elder they take care for. The caretaker can see all the key information of each elder they take care of, e.g. Figure 3. 209 Development and structural design of the frontend for unifying electronic and mobile health platform Samo Eržen Tomi Ilijaš Arctur d.o.o. Arctur d.o.o. Industrijska cesta 1a Industrijska cesta 1a Nova Gorica, Slovenia Nova Gorica, Slovenia samo.erzen@arctur.si tomi.ilijas@arctur.si ABSTRACT Eurostat on 27/03/2020 reported the survey on the use of ICT in 2 FRONTEND DESIGN households and by individuals, one in two EU citizens (53%) Anonymous visitors come to the site in order to find information aged 16-74 reported that they sought online health information about their disease or guidance on where to turn for advice. They related to injury, disease, nutrition, improving health or similar have different knowledge not only of disease causes, symptoms, [1]. On the other hand, an estimated 7 percent of Google's daily and health domain language, but also of various computer skills. searches are health-related, according to Google Health Vice Using user story mapping we isolate six stories: President David Feinberg, MD and Google's total daily health- related searches amount to 70,000 each minute, according to The 1. Browse – Visitor is knowledgeable and can navigate Telegraph report [2]. through the structured content to find information. 2. Search – Visitor can describe the main symptoms to search Nobody really enjoys going to a doctor, but there are many for possible results. reasons why you should avoid simply searching the internet for 3. Bot – Visitor can chat with the bot to narrow down the medical advice. Essentially this can go in two bad ways: either results and get the best information available. you overestimate your symptoms and end up taking the wrong 4. Chat – Visitor is having difficulties finding useful results medication or engaging in the wrong self-treatment, or you via navigation and he would like to chat with real person to underestimate your symptoms and let a condition worsen. get proper help. 5. HelpDesk – Call-center operator or doctor wants to In this paper, we describe a platform that helps an anonymous supervise many chat channels and answer messages from visitor to find verified health information or even chat with the the visitors. call-centre operator or health expert when available. We present 6. Administration – Administrator of platform wants to the technical specifications and features of the Insieme platform, manage the content and users (administrators, call-center which was developed as part of the project ISE-EMH. operators, and doctors). KEYWORDS The frontend is developed as a fully responsive webpage and is Frontend design, the structure of the frontend, health, EMH, also usable on mobile devices. medical advice, health-related searches At this point the platform supports content in three languages (Slovene, Italian, English) as this was the objective of the ISE- EMH project. 1 INTRODUCTION While Google certainly has a vast quantity of information, it 3 FRONTEND FEATURES lacks selectivity. Although it’s easy to find lists that sound like our symptoms, we don’t have the medical training to understand Application features implement the user stories described in the the other factors that go into making a medical diagnosis, like previous section. personal and family history. And neither does Google. 3.1 Browse Insieme platform content is organized by professionals and To assure to a site visitor effortless navigation through the managed by medical experts. The aim of the platform is not only platform content this was divided into two level services to publish verified content but also to promote other proven hierarchy. Visitor can select a hierarchy item on left vertical bar platforms and online content. And if the site visitor doesn’t find to get a list of all the services of the selected group each in few appropriate content, he can choose to speak with the available lines. By selecting a service from the list visitor gets detail page trained operator or medical expert. of that service. 210 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Samo Eržen et al. Figure 1: Platform content navigation 3.2 Search On the middle of the home page a visitor can find a search box to insert the search string. This is sent to the backend to execute the search on the main entities (services hierarchy, companies, user groups, experts) for presence of the search string in name or description. The result is presented as a list of entities grouped by type, each in few lines of description. By selecting a result item from the list, the visitor gets the detailed page of that entity. Using the Advanced search option, a visitor can filter the results using various parameters. Figure 3: Chat with an operator or expert 3.5 HelpDesk Figure 2: Search panel on the home page After logging in the user with the role of expert can select the HelpDesk button to open the chat dashboard with the list of 3.3 Bot active chat channels. When another visitor starts a new chat, a Visitor can at any moment decide to invoke bot and start a chat. channel is added to the list and the dashboard user is notified. He Bot backend tries to understand the intent of the visitor and offer can select the channel and chat with a visitor. There is also a the platform content, or some implemented functionality (e.g., possibility to use a shortcut to add a link pointing to the selected Waiting times and booking). platform content to the message he is writing. Adding more content and functionality to the bot backend, we don’t need to change the frontend to enable visitor to use them. 3.4 Chat On the home page an anonymous visitor sees active operators or experts. By selecting one chat, a pop-up window opens and he can write a message and chat with the selected person as we all do using many chat applications (e.g., WhatsApp, Skype, …). Figure 4: Operator chat dashboard 211 Development and structural design of the frontend for unifying Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia electronic and mobile health platform 3.6 Administration harmful information, people are searching the internet for health advice. Administrators have to login to gain the possibility to manage users and their properties as roles (call-center operator, expert, In this first phase of the project, we’ve learned how to organize …). Further he can define services, experts, companies, user health information and make it accessible to everyone to find groups and configure various parameters necessary for the answers to their questions or advise them on the best way to correct functioning of the platform. The content can be described proceed. The information can also be accessed by asking the bot in one or more languages to be visible to the visitors of platform or go into detailed chatting with a qualified operator or a doctor in a selected language. if available. During the next phases we will offer the visitors the possibility to register, so the operator can see his/her name and conversation history. We will improve the bot’s conversation recognition capabilities. By saving navigation and search history we can use Machine Learning to understand the visitor’s behaviour. With this understanding and adding seasonal (e.g., winter) or exceptional (e.g., Covid) health problems we can enrich search results and bot behaviour. ACKNOWLEDGMENTS The paper was supported by the ISE-EMH project funded by the program: Interreg V-A Italy-Slovenia 2014-2020. REFERENCES Figure 5: Platform content management [1] »53% of EU citizens sought health information online«, https://ec.europa.eu/eurostat/web/products-eurostat-news/-/ddn- 20200327-1: Accessed 31. August 2021. 4 CONCLUSION AND FUTURE WORK [2] »Dr Google will see you now: Search giant wants to crash in on your medical queries«, The quality and reliability of websites providing health https://www.telegraph.co.uk/technology/2019/03/10/google-sifting-one- knowledge can vary greatly. Yet despite the chances of billion-health-questions-day/: Accessed 31. August 2021. unnecessary stress and finding incorrect, or even potentially 212 primoz.kocuvan@ijs.si ABSTRACT Human population is getting older and more prone to diseases. In the information society, it is possible to find lots of helpful information on the web; however, the overload of information makes it hard to find information about a particular health issue. The ISE-EMH platform aims at providing the needed medical information faster and more context-specific than general search engines. The goal is to enable finding relevant services in few minutes instead of seeking for information with general search engine in web browser spending on average half an hour for one of common actions. To achieve such goal, the platform has to be direct and transparent and well structured, and these issues were studied as part of the project. The platform also includes an Future work is described at the end of the text, where future stakeholders are mentioned service providers and medical doctors. Their role will be significant for successful use of the platform, which can hopefully improve access to relevant information about healthcare services. 2 ISE-EMH PLATFORM Health service, patient, disease, improving healthcare system, 2.1 Concept Description ICD, ISE-EMH platform, workflow diagram, medical doctor 1 INTRODUCTION 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 2021, 4 8 October 2021, Ljubljana, Slovenia 21 Copyright held by the owner/author(s). 213 Information Society 2021, 4 8 October 2021, Ljubljana, Slovenia Klemen Bele et al. 20 minutes search 2 minutes search Figure 1: Comparison between searching on ISE-EMH platform and web browser. 2.2 Concept Demonstration 3 THE ISE-EMH PLATFORM To demonstrate how the platform works and to emphasize its advantages, a simple demonstration is presented in Figure 1. We 3.1 Side Menu Layout compared time spent for a user to find an application for skin cancer detection. Firstly, the user visited ISE-EMH platform and tried to find a link to the application. That took him around 2 minutes and can be seen on the left side of Figure 1. After that we used Google search engine to find the same result. The first search engine could not find the preferred application within first cancer checking) in the search engine and preferred application was found as 38th result. That can be seen on the right side of the Figure 1. This demonstration shows the real added value of the platform. 2.3 Other Health Platforms 214 Description of Health Service Selection and Structure of ISE-EMH Information Society 2021, 4 8 October 2021, Ljubljana, Slovenia Platform 3.2 Disease Webpage Layout 4 WORKFLOW DIAGRAM 3.3 Figure 4: Workflow Diagram. International Statistical Classification of Diseases and Related Health Problems (ICD). Inside the team we agreed to first include around 75 most common diseases and add more of them later. That number 215 Information Society 2021, 4 8 October 2021, Ljubljana, Slovenia Klemen Bele et al. comes from fact that they are 15 sets of diseases included at the ISE-EMH platform and we agreed to include 5 diseases in each The paper was supported by the ISE-EMH project funded by the set [9]. program Interreg V-A Italy-Slovenia 2014-2020. We thank our When all the diseases were selected the team started to write project partners for great collaboration: ARCTUR., Institut definitions of diseases. They were formulated in few sentences , Robotina, Burlo Hospital Trieste, Polo, and include information about the cause of the disease, common University of Venezia [11].We thank for help at the symptoms, diagnostics and any special warnings about the discussions and his contribution to project. disease (whether it is contagious or needs immediate treatment). Next step was searching for any kind of relevant services on Web. For that purpose, we were mainly using Google as search engine and spend around one hour to go through each relevant service for patients. We arranged services in eight categories: clinic services, mobile phone applications, world leading experts, symptoms, diets and special products that helps diagnosing or monitoring the disease. The relevant and checked services were added to platform. Main criteria in evaluating such services were very good reviews different clinics. For example, University Clinical Centers in Ljubljana and Maribor are part of tertiary healthcare system in [4] zVEM. 2021. https://zvem.ezdrav.si/domov Slovenia and as such have the best available equipment and also [5] Mediately. 2021. https://mediately.co/si medical staff in the state [11]. [6 , Mediately. 2021. http://www.healthday.si/novice-news/2020/3/18/intervju-z- 5 CONCLUSION blaem-triglavom-mediately [7] NHS App. 2021. https://digital.nhs.uk/services/nhs-app [8] Insieme: Full General Electronic and Mobile Health Plat- form. 2021. https://www.ita-slo.eu/en/ise-emh 216 Usability of smart home and home automation data Devid Palčič Simon Ražman Marjan Strnad Director Ma rketing specia list Product ma na ger for Sma rt Robotina d.o.o. Robotina d.o.o. Spa ces OIC - Hrpelje 38, 8333 Kozina , OIC - Hrpelje 38, 8333 Kozina, Robotina d.o.o. Slovenija Slovenija OIC - Hrpelje 38, 8333 Kozina, devid.pa lcic@robotina .com simon.ra zma n@robotina.com Slovenija ma rja n.strnad@robotina .com ABSTRACT enabling a variety of services and strategies for assisted living and detection of behavior change. In this case HEMS and 4G Technology and electrical energy are as a matter of fact closely platform act as an enabler for third party assisted living services. interconnected. The electric revolution and adopted technologies that assure a better standard of living enabled a longer life span. The demographic prediction is that by 2050, one in four persons KEYWORDS living in Europe and Northern America could be aged 65 or over. HEMS (Home Energy Management System), Smart Home, care In 2018, for the first time in history, persons aged 65 or above for elderly, elderly, change behavior detection. ISE-EMH, outnumbered children under five years of age globally. The Insieme number of persons aged 80 years or over is projected to triple, from 143 million in 2019 to 426 million in 2050. Growing at a slower pace, world population is expected to reach 9.7 billion in 2050 and could peak at nearly 11 billion around 2100 | UN DESA | United Nations Department of Economic and Social Affairs ) 1 INTRODUCTION With the more user friendly and affordable technology, the In harmony with sustainable energy use, interconnected standard of living and the quality of life for the past 60 years was devices and solutions for energy management in homes (HEMS), rising, and it enabled to adopt many technologies from the the possibilities of using the captured data for a variety of simplest as lighting, heating to more complex as home secondary use open up. Technology of connectable devices, automation technologies and solutions. The use of this sensors, cloud data technologies and energy monitoring and technology, however, has become part of everyday life, which is energy management technologies, such as Robotina's HEMS reflected in the routine management or use of them. solution, enable real-time monitoring of energy consumption and The future demographic structure and longer life expectancy based on this, generation of events and patterns of user behavior. also bring challenges for society. With the increase in life expectancy and the lack of young people who opt for nursing professions, it will be necessary to find appropriate technological solutions that will help maintain the quality of life and assistance of the elderly. To provide an adequate general care for the elderly, remotely assist them, predict health issues and to alert the caregivers appropriate technological solutions must be in place. In this paper, we describe the way how through energy management we enable to create events based on the behavior or use of devices in homes, apartments, or spatialized caregiving rooms. These (1) events are the foundation for triggering actions for assistance or prevention and safety in the relevant behavior change. In this paper we describe the role of HEMS (Home Energy Management System) solution and 4G cloud platform in Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Figure 2: HEMS system operation and for profit or commercial advantage and that copies bear this notice and the full functionalities scheme. citation on the first page. Copyrights for third -party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1.1 Basic information about the project 217 Robotina 2021, August 2021, Kozina, Slovenia D. Palčič et al. Data sets As a part of Insieme project we developed the features for data Time of the event acquisition, safe data transfer, models of event generation and event logging. For the purpose of third-party data use we Duration of the event developed a standardized Data API on 4S platform based on Type of the device or system SMIP cloud platform API service. For a better understanding of the topic the paper describes the Additional parameters to trigger actions are: possibilities and the technology behind it. Age of the person 1.2 Home energy management system as a source Current health status of data 2 DATA AND CONNECTIVITY The HEMS system monitors all energy production systems and all energy consumers in an individual home and, in the case of a Data collecting and data transfer to the cloud are crucial for the hospital or nursing home, energy consumption at the level of an interoperability and inter-usability of data by third-party individual floor or individual room. The feature of the Energy providers of ambient assisted living application information Management System (HEMS) works locally, and at the same solutions and home care assistance solutions. At the level of the time the connection to the cloud allows it to take advantage of all HEMS (Home Energy Management System) solution, the benefits that cloud technologies allow. To comprehensively connectivity is ensured through the edge technology of the cover all business models and services of energy management Robotinas IoT Linker product, which ensures that data is solutions, Robotina has built the 4S cloud platform, which securely transmitted to the cloud xEMS platform. enables data capture and analytical data services. Event detection, event generation and consequently as the main functionality 3 EVENT GENERATION activity triggering. In case of assisted living as an example triggering a warning to caregivers. Events once generated may Events are generated out of available data sets and are time be used for other purposes. stamped. Event can be generated through result of a simple equation. Let’s take temperature as an example. Equation, which would generate variable high_temperature as (TRUE): if (t1)>38 then high_temperature. More complex events may be result of an algorithm, like counting number of bathroom light_ON events between 22 and 6’ o clock. Finally, events may be result of a complex combination of algorithms, machine learning and artificial intelligence. Events are defined/described by healthcare specialists and translated into formulas or algorithms. Artificial Intelligence is used, when patterns are not clearly known upfront or when relations are too complex. 3.1 Lighting scenarios Figure 3: Sankey diagram from HEMS energy management Lighting and its use in rooms is the simplest, but on the other application. hand the most used device or set of devices in daily life of every person. The data of lighting usage provides us a variety of information. Use at a certain time of the day, the frequency of its 1.3 Overview of available data sets use, use in an individual, specific space provides us with valuable data in generating events and patterns of behavior. the logical consequence is that it also allows the detection of anomalies and Energy monitoring and energy management provides us with changes in behavior. A clear example is the non-extinguishing of data on the use of various devices and systems. The collected lights, which can serve as scenarios of causes such as insomnia, data give us information on the use of an individual device or dementia or even death. The frequency of lighting in a particular system and the time frames for the use of the devices. Depending room, such as the frequent use of lights in toilets at night, can on the time period, the duration of an individual event and the provide us with information about the disruption of water type of device or system that was used at a given time, we can drainage, ie the detection of the onset of incontinence or prostate specifically build events and content interpretations of events problems in the case of the male population. However, early that trigger event-specific activities. detection and early diagnosis of the disease can have a radical 218 Usability of smart home and home automation data Robotina, August 2020, Kouina, Slovenia impact on further prevention of disease development. In the case reach key data that enable to build additional services in assisted of homes for the elderly, however, caregivers have the option of living and other remote care services. Data API configurations comprehensive insight and prompt action. enable devices to be accessible to third-party clients by calling SMIP Data API Web Services. Content developers may define 3.2 Heating scenarios which things and which variables may be accessible to which third-party. Write access to variables is also defined in Data API Heating and cooling are also the most common solutions in any configurations. home or building. In this case, energy management and HEMS also provide us with information on a person's health through 5. REAL LIFE SOLUTION APPLICATION monitoring the operation of heating and cooling systems. There are, of course, many scenarios. An example of excessive cooling Through energy consumption and the use of various devices, or heating may indicate a physiological change in a person or a HEMS can define various events, which, of course, depend on change in health. the type of building or living environment and the age or health condition of the person. 3.3 Energy consumption scenarios 5.1 Individual home Comprehensive energy management and monitoring through HEMS provides us with rich data to interpret the behavior of the For an individual home as we have already mentioned in the individual through monitoring energy consumption. An obvious paper, the key goal is to monitor the routine through HEMS example of such a scenario is the example of "morning coffee". energy management. Through an appropriate, long enough Hems can clearly identify patterns of behavior and deviations, period to define individual events, the system obtains data to changes, or anomalies in an individual’s routine actions or tasks detect changes in routine tasks, define current health status, through monitoring peak energy consumption. In this case, detect deterioration in health status, or early detection of “morning coffee,” which is routine for most people, can be an potential new disease at an early stage. Notifications to relatives indicator of a person’s condition. Perceived changes in the or caregivers are generated when routines change. This way they performance of routine tasks are systematically interpreted as an have the ability to check the situation and the ability to act event that triggers activities to inform relatives or caregivers. quickly. The benefits of this type of solution are for the elderly and their therapists or doctors, caregivers and, of course, relatives. 4 DATA AVAILABILITY With the growth of the elderly population, solutions such as HEMS and the Ambient Assisted Living service can indirectly help extend the autonomy of the elderly and the independence of The power of big data is in its usability. To assure 3rd party data use it is necessary to assure the data availability in a standardized the elderly, as everything takes place automatically and remotely. This is especially important for seniors living in remote locations. way through standard protocols. This ensures to other provider All involved stakeholders who directly or indirectly care for a to use the collected data and make them a part of an applicable person thus have the opportunity to be informed and to act in a solution, which provides stand-alone services based on this timely manner for the benefit of the quality of life of the elderly information or data. person ore their beloved ones. 6 CONCLUSION We have described the possibilities offered by the energy management solution (HEMS) and the 4S cloud platform in the direction of “Ambient Assisted Living” solutions. We have prepared an environment for the capture, transfer and storage of data and the creation of events that serve to implement other applications of application solutions. We examined the possibilities of using the obtained data to generate events and trigger actions. We have identified scenarios that can provide solutions to the well-being of older people and the early detection of potentially pathological changes and diseases. These solutions can be applied fast and with the least investment in the current infrastructure. Figure 4: HEMS prosumers and consumers configurator. ACKNOWLEDGMENTS 4.1 Data API The paper was supported by the ISE-EMH project funded by the program: Interreg V-A Italy-Slovenia 2014-2020. As mentioned above, Robotinas HEMS (Home Energy Management System) enables to spatialized IT companies to 219 Robotina 2021, August 2021, Kozina, Slovenia D. Palčič et al. REFERENCES DESA | United Nations Department of Economic and Social Affairs (2021) [1] 2021. Growing at a slower pace, world population is expected to reach [2] 2021. Robotina-WikiPage en:hems:hems [] (hiq-universe.com) (2021). 9.7 billion in 2050 and could peak at nearly 11 billion around 2100 | UN 220 Intelligent cognitive assistant technology for (mental) health in the ISE-EMH project Tine Kolenik† Urša Klun Primož Kocuvan Department of Intelligent Department of Intelligent Department of Intelligent Systems Systems Systems Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Jamova cesta 39, 1000 Ljubljana, Jamova cesta 39, 1000 Ljubljana, Slovenia Slovenia Slovenia tine.kolenik@ijs.si ursaklun10@gmail.com primoz.kocuvan@ijs.si Matjaž Gams Department of Intelligent Systems Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia matjaz.gams@ijs.si ABSTRACT Intelligent cognitive assistant technology (ICAs) has been defined as a technology powered by complex information The paper presents the inclusion of intelligent cognitive assistant processing agents. These can acquire information, put it into technology in an electronic and mobile health system under action and transmit knowledge, bringing together perception, development for the ISE-EMH project. After introducing the intelligence, thinking, calculation, reasoning, imagining and, in project and the intelligent cognitive assistant technology, the the end, conscience [1]. ICAs aspire to: understand context; be paper describes the included assistants in the developing adaptive and flexible; learn and develop; be autonomous; be electronic health system. The main focus of the paper is its communicative, collaborative and social; be interactive and emphasis on the current state of the design of an advanced personalized; be anticipatory and predictive; perceive; act; have adaptive and personalized assistant for mental health. The most internal goals and motivation; interpret; and reason. Such agents in-depth description focuses on the utilization of a generative are usually deployed either as conversational agents – computer pre-trained transformer (based on OpenAI’s GPT-3) to respond systems that converse with humans in (usually written) natural to users’ self-reports about their mood and mental health issues. language – or robots. All these characteristics make them very suitable for various functionalities inside an emHealth platform, KEYWORDS some of which will be presented in this paper, as they also play Attitude and behavior change, digital mental health, electronic a role in the ISE-EMH project. and mobile health system, intelligent cognitive assistant The ISE-EMH project encompasses a platform of emHealth technology and is co-financed by the European Regional Development Fund. As a result of a collaboration of multiple Slovenian and Italian partners, it connects cross-border healthcare systems. The project 1 INTRODUCTION consists of three main components: a mobile application, a web Electronic and mobile health system (emHealth) describes page and a chat system. The mobile application, available for OS healthcare services that are largely enriched by the use of Android, is developed specifically for elderly persons and their information and communication technology (ICT) for its caretakers. The goal is to simplify and improve quality of functionalities. This mostly includes computers and mobile seniors’ lives. This is achieved through a design that provides phones, which make healthcare more flexible and available at all simple usage and implementation of multiple integrations, such times, but can also extend to newer technologies, such as robots. as alarms for taking medicines, fall detection and an SOS call ICT is made useful in a wide range of services, from data keeping option. The web page consists of several relevant information to predictive modeling. One of the existing and still evolving about health concerns, diseases, and fields of medicine, along technologies that benefit emHealth the most is the intelligent with useful links for booking certain services, for waiting queues cognitive assistant technology. for procedures, and of presentations of other helpful platforms. Because all data are gathered in one place and easily available, it allows better access to the healthcare itself, as searching for information is intuitively designed. The chat system is 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 implemented in the web page, and is intended for all users that for profit or commercial advantage and that copies bear this notice and the full have questions concerning health problems or are simply looking citation on the first page. Copyrights for third-party components of this work must for more information about certain services. Its main goal is to be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia provide answers, give advice to users, and present information © 2020 Copyright held by the owner/author(s). about waiting queues for certain procedures and services. This is possible through the use of ICAs. 221 Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia T. Kolenik et al. This paper presents the use of the ICA technology in the ISE- analyzing large amounts of data [4]) on trigram words, it EMH emHealth platform, and focuses on an adaptive and allows fast and precise searching. personalized ICA for attitude and behavior change in mental health, which is planned to be implemented into the platform. 2 INTELLIGENT COGNITIVE ASSISTANT TECHNOLOGY IN THE ISE-EMH PROJECT The ICA technology in the ISE-EMH project, similarly as other chat possibilities, is integrated in Rocket.Chat [2], a widely used open source communicating platform. The ICA technology is mostly deployed when a professional is not available to chat with the users. At that moment, the answers are provided by various ICAs. Three assistants are implemented directly in the platform, all of them with different domains they cover in terms of their semantic understanding: the JSI assistant, an assistant for waiting queues, and an assistant for service searching. They all provide their answers, but users can alternatively select only one of them. Others assistants (e.g., an assistant for information on hepatitis) are also included, but are not integrated, and they can be accessed through a link, suggested in the chat window. The three major integrated assistants are described below: Figure 1. Left: An assistant for waiting queues giving information 1. The JSI assistant [3]: An assistant developed in Bottle on oncological procedures. Right: Various possibilities from (Python). Jožef Stefan Institute (JSI) is a partner of the different ICAs when more answers are possible. project, and this ICA’s purpose is to give answers to any question related to the JSI institute and its employees. It can Another planned ICA integration is an intelligent cognitive also provide answers to more general questions. It works by assistant for attitude and behavior change in mental health. This enacting the following pipeline: 1) all stop-words are is going to be an advanced adaptive and personalized ICA, removed in given text to obtain relevant keywords; and 2) planned to be state of the art (SOTA) in the field of ICAs for lemmatization, a procedure that returns the root of a word, is mental health. Its design is described in the next section. used on these keywords to provide more efficient searching through the database. 3 DESIGN FOR AN INTELLIGENT 2. An assistant for waiting queues: An assistant developed COGNITIVE ASSISTANT FOR ATTITUDE in Django (Python), which provides information on waiting AND BEHAVIOR CHANGE IN MENTAL queues in the Slovenian healthcare system of a given health HEALTH service. The data of all the possible procedures are obtained To be able to understand how to design such an ICA, the mental from the website https://cakalnedobe.ezdrav.si/, which makes health issues in the society have to be overviewed. Stress, anxiety them non-obsolete. Based on the selected health service, and depression (SAD) are on the rise in the entire world, with urgency and the region of procedure, information on the figures in certain groups reaching 71% for stress, 12% for medical institutions that provide the service along with first anxiety disorder and 48% for depression [5]. This opens the available time slots are given. For avoiding any doors for technological and scientific interventions to help misunderstandings about what procedures the user wants, mitigate the occurring mental health pandemic. One such stop words are removed and a lemmatizator is used. The user technology is persuasive technology (PT), which tries to change then chooses among all the suggested services. If a procedure attitudes or behaviors without coercion or deception. ICAs can is not available, other solutions are suggested, such as be effective vessels for such goals., as they can communicate in searching in all the available regions. This makes searching natural language. By employing ICAs in mental health, the faster and more precise as well as easier to use, which is benefits can be numerous: they can be free of charge, available enabled through the button-based chat implementation. 24/7, and available in remote locations [6]. Furthermore, people tend to be more comfortable talking to an ICA than to a person 3. An assistant for service searching: The assistant is [7]. implemented as a service search; the services are available on To discover what SOTA in this field was, three major ICAs the ISE-EMH platform website as well. The ICA uses entered for SAD were reviewed, also because only rare review articles keywords to provide descriptions of services, including many on this topic exist [8]. An ICA by Yorita, Egerton, Oakman, Chan useful links. With the stop-words removal and the use of and Kubota [9] is based on the Belief-Desire-Intention Elasticsearch (a search engine that allows faster searching and architecture with three models: “a conversation model for acquiring state information about the individual, measuring their 222 Intelligent cognitive assistant technology in the ISE-EMH Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia project stress level, a Sense of Coherence (SOC) model for evaluating The module architecture represents the following pipeline: the individuals state of stress, and Peer Support model, which uses the SOC to select a suitable peer support type and action it” 1. Information input. Users answer quantitative [Ibid., p. 3762]. The ICA teaches users how to improve their questionnaires on their mental health, and provide a textual mental resilience to stress, which it succeeds in in the reported input on their mood, their experiences while in that mood, and experiment. Another effective ICA is called Woebot [10]. It is similar. If the user has already provided quantitative scores based on a “decision tree with suggested responses that accepts for enough time, only text is necessary. natural language inputs” [Ibid., p. 3]. It intervenes by outputting educational content, personalized messages, and scripted advice 2. The scores and text are automatically preprocessed to by collecting data on users’ emotions and identifying their errors extract the features. in thinking. In one experiment, Woebot was more successful in helping with SAD symptoms than the government-prescribed 3. A pre-trained model is used first to recognize moods, material. The last reviewed ICA is called Tess, which “reduce[s] emotions, sentiment, and other mental health markers in the self-identified symptoms of depression and anxiety” [11]. It uses text, and it uses this on conjunction with the quantitative an extensive emotion ontology to identify the emotions of its scores to forecast mental health trends of the user. This part users from the text. It uses prepared scripts to help the users, and determines various metrics: the severity of mental health collects journal data and user feedback to improve its outputs. In problems, the specificity of mental health problems, and the one experiment, Tess significantly reduced depression and short-term trend of mental health problems. anxiety symptoms as opposed to the government-approved eBook for self-help. 4. The three metrics are sent to the next part of the module. Reviewed ICAs seem to already be at least partly successful, but they do not fully exploit the possibilities PT offers (e.g., 5. A pre-written text is selected according to the metrics, attitude and behavior change theories, user modeling, adaptation, determined in the previous part. The text serves to mitigate personalization). The ICA we are designing takes that into the user’s mental health problems, and, if the forecasted trend account. In this paper, we focus on describing a module in the is negative, to try to break that trend. ICA that utilizes a generative pre-trained transformer (based on GPT-3 [12]) to formulate outputs. 6. The text is sent to be augmented with the next part of the Our ICA surpasses the SOTA by possessing a ‘theory of module. mind’. This is achieved by the ICA a user model with the data on users’ emotions, mental states, and personality, which relies on 7. The text from the previous part is enriched by a generative behavioral and cognitive sciences advances; a reinforcement pre-trained transformer based on GPT-3 with additional text. learning algorithm to learn from historical interactions between This makes responses more varied and alive for the user. the ICA and the user, thus capturing which strategies work and which do not; and ontologies on attitude and behavior change, 8. The enriched text is passed to the GPT humanizer. stress, anxiety, and depression. The focus is however on the following module and its architecture: 9. GPT humanizer return the original text for enrichment if deemed risky for the user. Module architecture: 10. GPT humanizer decides whether the added text by Generative pre-trained transformer based on GPT-3 is acceptable in terms of risk for the user. It consists of a rule- based model that rejects text with certain words, sentiment analyzer that rejects text that fails to reach a certain positive sentiment threshold, and a pre-trained model based on a dataset of risky sentences that rejects text if it is detected as risky. 11. The final text goes through some additional modifications to check that everything is in order. 12. Output of the final text. Example: 1. The user inserts text “Today I have felt very bad. I feel a Figure 2. A module for detecting and forecasting mental health lot of stress because I have a deadline at work coming, and I issues, and responding to the detected and forecasted issues by utilizing fought with my partner yesterday. I am anxious to talk to them a generative pre-trained transformer, based on GPT-3. tonight. The deadline is a bit scary because I did not do a good 223 Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia T. Kolenik et al. job last time, and if it happens again, it might trigger my friends. They probably have some experience with them and depression.” can offer advice as well as another perspective on the situation. Don't ignore or repress the problem if you need 2. Features are extracted. This includes performing sentiment to seek help. You are not a burden and you do have analysis, creating n-grams, vectorizing, calculating basic worth. ” statistical features, and applying psychological and cognitive lexicons on the text. 4 CONCLUSION 3. The features from the second step are used for detecting the The paper presented an emHealth platform being developed in user’s specific mental health problems, their severity and, if the ISE-EMH project. First, the paper focused on the ICA there is historical data of the user, the short-term trend. The technology used in the project, and later it focused on one model returns abnormal levels of stress and depression, and it particular ICA, an advanced adaptive and personalized ICA for forecasts a negative trend. attitude and behavior change in mental health. The field of emHealth is still developing as advancing 4. The information on the mental health of the user is sent to technologies are being integrated into various domains of our the sentence selector. society. The project ISE-EMH represents one such use case of integrating the domain of healthcare with the ICA technology. 5. Due to the abnormal levels of stress and depression as well as a negative trend forecasting, the text, which also takes the ACKNOWLEDGMENTS / ZAHVALA user’s personality, which is more easily persuaded when The authors acknowledge the financial support from the addressing their social circle, into account, selects the text Slovenian Research Agency (research core funding No. P2-0209 “Tackling stress and depression is hard, especially since and the Young researchers’ grant) and the ISE-EMH project many people have problems with them, but it is not funded by the program Interreg V-A Italy-Slovenia impossible. Try to think outside of the current situations and 2014-2020. discuss them with your friends. They probably have some experience with them and can offer advice as well as another REFERENCES perspective on the situation. ”. [1] Oakley, J. 2018. Intelligent Cognitive Assistants (ICA). Workshop Summary. IBM Almaden Research Center. 6. The module takes the selected text and sends it for [2] Rocket.Chat – The Ultimate Communication Platform. https://rocket.chat/ [3] Asistent. http://www.projekt-asistent.si/ijs-en enrichment. [4] Elasticsearch: The Official Distributed Search & Analytics Engine. https://www.elastic.co/elasticsearch/ [5] Twenge, J. M. 2014. Time Period and Birth Cohort Differences in 7. The text is enriched with the following two sentences: Depressive Symptoms in the U.S., 1982–2013. Soc. Indic. Res. 121, 2 “Don't ignore or repress the problem if you need to seek (2014), 437-454. [6] Kolenik, T. and Gams, M. 2021. Persuasive Technology for Mental help. You are not a burden and you do have worth. ” (This Health: One Step Closer to (Mental Health Care) Equality? IEEE was an actual output of GPT-J [13]). Technology and Society Magazine. 40, 1 (2021), 80-86. [7] Lucas, G. M., Gratch, J., King, A., and Morency, L. P. 2014. It’s only a computer: virtual humans increase willingness to disclose. Comp. Human. 8. The enriched text is passed to the GPT humanizer. Behav. 37 (2014), 94-100. [8] Kolenik, T. and Gams, M. 2021. Intelligent Cognitive Assistants for Attitude and Behavior Change Support in Mental Health: State-of-the-Art 9. Does not occur. Technical Review. Electronics. 10, 11 (2021), 1250. [9] Yorita, A., Egerton, S., Oakman, J., Chan, C., and Kubota, N. 2018. A Robot Assisted Stress Management Framework. 2018 IEEE International 10. GPT humanizer extracts features from the added text. It Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, does not find any risky indicators. 2018. [10] Fitzpatrick, K. K., Darcy, A., and Vierhile, M. 2017. Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and 11. The final text is passed to the final stage without Anxiety Using a Fully Automated Conversational Agent (Woebot): A modifications. Randomized Controlled Trial. JMIR Ment. Health. 4, 2 (2017), e19. [11] Fulmer, R., Joerin, A., Gentile, B., Lakerink, L., and Rauws, M. 2018. Using Psychological Artificial Intelligence (Tess) to Relieve Symptoms of 12. The user receives the full text output: “Tackling stress and Depression and Anxiety. JMIR Ment. Health. 5, 4 (2018), e64. [12] Brown, Tom B. et al. Language Models are Few-Shot Learners. arXiv. depression is hard, especially since many people have 2005.14165 (2020). problems with them, but it is not impossible. Try to think [13] Wang, B. and Komatsuzaki, A. GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model. https://github.com/kingoflolz/mesh- outside of the current situations and discuss them with your transformer-jax 224 Analysis of a recommendation system used for predicting medical services Gjorgji Noveski Jakob Valič gjorgi.noveski@ijs.si jakob.valic@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT Collaborative filtering Recommendation systems are widely used in prediction of user Collaborative filtering is based on the idea that users who have preferences given a set of data. More often these preferences similar interest in the past, will be more likely to rate future items are part of the domains of the entertainment or general goods the same way. The recommendation is gathered from data from industry, striving to improve recommendations for items such as various users, but it is tailored just for the specific user that is songs, movies, electronics, etc. In this work, we give an overview doing the query. of using a recommendation system in a electronic and mobile health platform, showcasing the applicability of such a system Item-item collaborative filtering for recommending healthcare services and keywords relating to Another form of collaborative filtering is the item-item collab- user’s initial search query. orative filtering. Instead of looking at users which are similar based on their previous ratings, it looks at the items that are KEYWORDS rated by one user and it suggest a new item which has the high- Electronic and mobile health, recommendation systems, Insieme est similarity between the previously rated ones. This form of filtering performs well when the number of users is higher than 1 INTRODUCTION the numbers of items, which is a good fit for our problem. Recommendations systems have been proven to provide solid recommendations in various tasks, such as movie recommenda- Insieme tions, song recommendations, general goods recommendations The environment where the recommendation system will be ana- on online shopping platforms, etc. With their help, using online lyzed is called ISE-EMH (Insieme). It represents an EMH platform platforms and services has become more enjoyable since they which connects various medical institutions and patients. The tailor suggestions in respect to each individual user. Focusing on platform provides information about services which are obtained the healthcare domain, we can see that recommender systems from medical institutions. An example use case is a patient that are able to offer help in many aspect of a patient’s health [3]. Sim- requires information about certain illnesses, queries information ilarly, they are also used by the healthcare professionals, aiding through keywords on the platform and the platform returns the them in decision making scenarios in order to decrease the risk relevant information. of errors. An interesting approach is proposed by [2], where the The users who are using Insieme are not required to have an entirety of the recommendation system is build as a whole plat- account to use its services. Because of that, a session based recom- form. Their platform takes into consideration the user’s health mendation system is used, meaning the user’s queries (searched status and finds healthcare services which it considers would keywords) are only relevant in only one session. The user may be be of value to the user. Our work is interested in analyzing a able to search for different illnesses in different sessions, but we recommender system in conjunction with an electronic and mo- can not assume their previous searches are related to the current bile health (EMH) platform. We want to recommend relevant one. healthcare services to the users based on their search queries. Having good recommendations allows the user to find relevant 2 EXPERIMENT services in a faster and easier way. In order to carry out the analysis of the recommendation model Problems with recommendation systems for project Insieme, we decided to simulate a small set of input data due to lack of real data. First, we chose a subset of services A recommendation system has the most difficult time achieving and then we simulated some users’ choices. The simulation was good results at the beginning of its work period. This is widely done by generating use cases which simulate a typical user using known as the "cold start" problem. This problem is due to the fact the EMH platform and choosing appropriate services. This was that a system can not infer any significant information about its done because real user interaction data was unobtainable. users or items because previous information is scarce. There are several approaches one can take while designing a recommenda- tion system, such as: Input data Insieme services are organized into medical categories. For the Permission to make digital or hard copies of part or all of this work for personal purpose of the experiment, we chose the following medical cate- 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 gories: dermatology, oncology and infections. From each of those the full citation on the first page. Copyrights for third-party components of this we chose 3 to 4 services, thus obtaining 10 various medical ser- work must be honored. For all other uses, contact the owner/author(s). vices. Each service has keywords describing it. Since the services Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). refer to the diseases, the keywords refer to the affected part of the body and describe some additional properties of the disease. 225 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Gjorgji Noveski and Jakob Valič Table 1: A subset of services with corresponding keywords Table 2: Users’ choices of services When choosing the subset of services, we carefully selected those filtering model. In addition, an implicit feedback model is used with various keyword intersections. The services and keywords that regards the absence of information in the interaction matrix are shown in Table 1. The ’+’ sign denotes which keywords are as negative feedback. The motive for this is that a user already associated with a service. made a conscious choice about what kind of services he needs Next, we have simulated the interactions between users and information for, so the keywords that the user didn’t search can services. The ’+’ sign denotes that the user has chosen the service. be regarded as negative interactions in the interaction matrix. The users’ choices are in Table 2. When preparing the data, we We built the recommendation model using the LightFM library bore in mind the possible reasons to some users’ choices. E. g., [1]. We compared the outcome of two various models. The first users 1, 7 and 10 might be concerned about some skin problems, model is trained on the users’ choices of the services only. The while user 11 might be concerned about the lung problems and second model is additionally trained on keywords describing the user 2 might be investigating all information about cancer avail- service. Using these two models, we obtained the suggestions for able. However, in order to make data more realistic, the majority each user. of users’ choices don’t have agenda. Results Recommendation model The top recommendations for all users are mostly the same. The Our choice for a recommendation system is LightFM [1]. The differences between the recommended services are minimal, e. g. reason for using this implementation is the ability to create tag for user 2: embeddings by supplying user and item features. In our use case, our item features represent tags that further explain the keywords • pneumonia: 0.13 (items), for e.g. : "Acne" item has the corresponding "Dermatol- • acne: 0.18 ogy" and "Skin" items associated with it. The benefit of using • psoriasis: 0.13 embeddings is that they capture semantic similarities between • dermatitis: 0.15 the keywords, which in turn will result in better inference of • skin cancer: 0.18 the model and provide an option to choose top N most similar • lung cancer: 0.18 keywords. • brain tumor: 0.13 With the help of the learned latent vectors improvement is • Lyme disease: 0.17 achieved on "cold start" scenarios. If the item features were not • tick-borne meningoencephalitis: 0.17 supplied, the model would default back to a pure collaborative • COVID-19: 0.16 226 Recommendation system analysis - project Insieme Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia This data is produced by the model with only interactions. The Digital, which organized the focus group as part of the HoCare model with item features has the same recommendations, with 2.0 project. slightly lower probability. For each user, the top 3 suggested services are acne, skin cancer and lung cancer. These predictions REFERENCES are not satisfactory, since we would like to obtain the suggestions [1] Maciej Kula. 2015. Metadata embeddings for user and item tailored to every user separately. We assume more data would be cold-start recommendations. In Proceedings of the 2nd Work- needed for training of recommendation models. shop on New Trends on Content-Based Recommender Systems co-located with 9th ACM Conference on Recommender Sys- 3 CONCLUSION tems (RecSys 2015), Vienna, Austria, September 16-20, 2015. In this work we analyzed a recommendation system that is used (CEUR Workshop Proceedings). Toine Bogers and Marijn with an EMH platform. The goal was to see if such a system is Koolen, editors. Volume 1448. CEUR-WS.org, 14–21. http: applicable on an EMH platform and offer medical service recom- //ceur-ws.org/Vol-1448/paper4.pdf. mendations to users. Because of limited amount of interaction [2] Choon-oh Lee, Minkyu Lee, Dongsoo Han, Suntae Jung, and data, the recommendation system faces difficulties in learning Jaegeol Cho. 2008. A framework for personalized healthcare meaningful representations. The system requires data which service recommendation. In HealthCom 2008-10th Interna- would be gathered during a longer period of time, in order to tional Conference on e-health Networking, Applications and give more accurate and meaningful suggestions. Services. IEEE, 90–95. [3] Thi Ngoc Trang Tran, Alexander Felfernig, Christoph Trat- ACKNOWLEDGMENTS tner, and Andreas Holzinger. 2021. Recommender systems The paper was supported by the ISE-EMH project funded by the in the healthcare domain: state-of-the-art and research is- program: Interreg V-A Italy-Sovenia 2014-2020. We thank IPM sues. Journal of Intelligent Information Systems, 57, 1, 171– 201. 227 PlatformUptake Methodology for AHA Solution Assessment Žiga Kolar Zdenko Vuk Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ziga.kolar@ijs.si zdenko.vuk@ijs.si Erik Dovgan Matjaž Gams Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia erik.dovgan@ijs.si matjaz.gams@ijs.si ABSTRACT Course for synergies, knowledge exchange and a common un- The EU PlatformUptake project aims for AHA solution assess- derstanding among all stakeholders in the Active and Healthy ment. It assesses the societal impact of the existing platforms, Ageing market [3]. creates monitoring and evaluation toolkits, collects successful The rest of the paper is organized as follows. Section 2 presents user stories and best practices, promotes interoperability, and the main objectives of the project, project methodology and plat- defines guidelines for a common evolution of such platforms forms for elderly. Clustering and taxonomies are described in within existing policy frameworks and initiatives. In this paper section 3. Finally, section 4 concludes the paper with summary we present (i) PlatformUptake methodology for AHA solution and ideas for future work. assessment and its main objectives, (ii) the results of two ways of clustering, and (iii) the results of taxonomies generation of the 2 METHODOLOGY FOR AHA SOLUTION text descriptions of the EU PlatformUptake platforms for elderly. ASSESSMENT After the data was prepared, we ran the K-means algorithm and hierarchical clustering to get the number of clusters. We also 2.1 Main objectives created a decision tree of platforms for elderly. The main objectives of the EU PlatformUptake methodology for AHA solution assessment are: KEYWORDS • To identify the critical success factors of the development, uptake, clustering, artificial intelligence, health, elder people deployment and spread of open platforms in the Active And Healthy Ageing Domain, through a sophisticated 1 INTRODUCTION tailor-made monitoring methodology. Ageing presents one of the greatest socio-economic challenges of • To develop monitoring and self-evaluation tools to sup- the twenty-first century. According to estimates more than 20% port platform providers and users self-assess their success, of Europeans will be 65 or older by 2025 [5]. Reacting to related uptake, capability gaps and evolution potentials through puzzlements of demographic shifts and ageing in general, and smart assessment and visualization tools. guaranteeing the availability of the required structure to help Eu- • To analyse existing platforms based on the created method- rope utilize the active and healthy ageing sector’s opportunities, ology, by assessing the projects and initiatives hosted by the EU has devoted a high level of resources to ICT projects in the them, their further evolution, uptake, sustainability and field of active and healthy ageing. As such a considerable num- socioeconomic benefits. ber of open source platforms for the development of innovative • To involve end-user communities and related stakehold- solutions in the AHA domain have been created [3]. ers to initiate a knowledge exchange cycle for collecting The EU PlatformUptake methodology for AHA solution as- insights on best practices and challenges of platforms’ sessment assesses the societal impact of these existing platforms, uptake, evolution and costs, etc. create monitoring and evaluation toolkits, collect successful user • To leverage the platform uptake by their user communities stories and best practices, promote interoperability and define as well as their continuous improvement and expansion, guidelines for a common evolution of such platforms within ex- by elaborating and showcasing best-practice models and isting policy frameworks and initiatives. Seeking to support the evaluation guidelines. large-scale uptake of the platforms, the project proposes the cre- • To disseminate the acquired knowledge to end-users for ating of an online information hub which provides descriptive increasing their uptake of existing platforms, and promote and support materials on all existing platforms, the organisation best practice models and identified benefits to foster future of several stakeholder events, as well as Massive Open Online developments. Permission to make digital or hard copies of part or all of this work for personal 2.2 Methodology 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 EU PlatformUptake methodology for AHA solution assess- the full citation on the first page. Copyrights for third-party components of this ment seeks to deliver an inventory of the state of the art and anal- work must be honored. For all other uses, contact the owner/author(s). yse the use of open service platforms in the Active and Healthy Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). domain, covering both open platforms – such as UnversAAL, FIWARE and partly-open/proprietary platforms developed by 228 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Žiga Kolar, et al. industry, and address the interactions between these platforms The FIWARE Foundation is the legal independent body pro- [3]. viding shared resources to help achieve the FIWARE mission by To measure the impacts of such platform and enhance their up- promoting, augmenting, protecting, and validating the FIWARE take, the project proposal presents a methodology for monitoring technologies as well as the activities of the FIWARE community, open platform development, adoption and spread across Europe, empowering its members including end users, developers and by listing key factors that determine success or hinderance in rest of stakeholders in the entire ecosystem. their uptake by the end-user groups, and also the evolution of REACH represents a solution that seeks to prevent elderly their ecosystems and stakeholder networks. citizens from loss of function and a decline of being able to per- The proposed methodology shall be employed in the project form Activities of Daily Living (ADLs) independently leading to evaluate the use of open platforms by collecting and process- ultimately to entering Long Term Care (LTC). ing data from past and currently running European projects VAALID (Accessibility and Usability Validation Framework and other initiatives that are built upon such platforms. Follow- for AAL Interaction Design Process) is a STREP project of the ing the knowledge acquisition, the methodology will elaborate 7th Marco Program for Investigation and Development of the evaluation guidelines and best practice models of integrating European Commission, included within the Strategic Objective multiple platforms, taking account of technical, organizational, ‘Accessible and Inclusive ICT’; Thematic Priority ICT-2007.7.2. financial/business and legal aspects. GIRAFF+ is a complex system which can monitor activities Following the assessment of the ecosystem and output of an in the home using a network of sensors, both in and around the extended evidence on the ecosystem, the methodology will create home as well as on the body. support materials for all involved stakeholders to promote the The purpose of the EkoSmart program is to develop a smart large-scale uptake of existing platforms and also their contin- city ecosystem with all the support mechanisms necessary for uous improvement. In concrete terms this action includes the efficient, optimized and gradual integration of individual areas creation of toolkits for Monitoring and Self-Assessment for both into a unified and coherent system of value chains. platform providers and platform users, the creation of an Online PERSONA aims at advancing the paradigm of Ambient Intel- Information Hub which showcases all information through visu- ligence through the harmonisation of Ambient Assisted Living ally appealing smart tools, and the creation and implementation (AAL) technologies and concepts for the development of sus- of a Massive Open Online Course and final project activities to tainable and affordable solutions for the social inclusion and promote synergies and knowledge exchange between the com- independent living of Senior Citizen, integrated in a common munity members [3]. semantic framework. OASIS introduces an innovative, Ontology-driven, Open Refer- 2.3 Platforms ence Architecture and Platform, which will enable and facilitate interoperability, seamless connectivity and sharing of content be- Within the development of the methodology 18 platforms for tween different services and ontologies in all application domains elderly were analysed. These platforms are: relevant to applications for the elderly and beyond. (1) ACTIVAGE The general objective of the AmIVITAL project is the devel- (2) universAAL opment of a new generation of ICT technologies and tools for (3) FIWARE the modelling, design, operation and implementation of Ambient (4) ReAAL Intelligence (AmI) devices and systems to be used for providing (5) VAALID services and personal support for independent living, wellbeing (6) GIRAFF+ and health. (7) EkoSmart REACH2020 represents a solution that seeks to prevent elderly (8) PERSONA citizens from loss of function and a decline of being able to per- (9) OASIS form Activities of Daily Living (ADLs) independently leading (10) AmIVITAL ultimately to entering Long Term Care (LTC). (11) REACH2020 The Amigo project develops open, standardized, interoperable (12) AMIGO middleware and attractive user services for the networked home (13) MPOWER environment. (14) SOPRANO/OPENAAL MPOWER defines and implements an open platform to sim- (15) INTER-IOT plify and speed up the task of developing and deploying services (16) UNCAP for persons with cognitive disabilities and elderly. (17) BeyondSilos SOPRANO designs and develops highly innovative, context- (18) INLIFE aware, smart services with natural and comfortable interfaces for older people at affordable cost, meeting requirements of users, ACTIVAGE consists of a set of Techniques, Tools and Method- family and care providers and significantly extending the time ologies for interoperability between heterogeneous IoT Platforms we can live independently in our homes when older. and an Open Framework for providing Semantic Interoperabil- In the absence of global IoT standards, the INTER-IoT results ity of IoT Platforms for AHA while addressing trustworthiness, will allow any company to design and develop new IoT devices privacy, data protection and security. or services, leveraging on the existing ecosystem, and bring get universAAL enables seamless interoperability of devices, ser- them to market quickly. vices and applications for IoT enabled smart environments. The UNCAP (“Ubiquitous iNteroperable Care for Ageing People “) platform provides the framework for communication, connec- makes use of solutions and technologies developed in previous tivity and compatibility between otherwise disparate products, research projects to develop an open, scalable and privacy-savvy services and devices. 229 PlatformUptake Methodology for AHA Solution Assessment Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia ICT infrastructure designed to help aging people live indepen- dently while maintaining and improving their lifestyle. BeyondSilos aims at further spreading ICT-enabled, joined-up health and social care for older people by developing, piloting and evaluating integrated services based on two generic pathways in a multicentric approach, making extensive use of knowledge and experience gained among early adopters of integrated eCare in Europe. INLIFE aims to prolong and support independent living for elderly with cognitive impairments, through interoperable, open, personalised and seamless ICT services that support home activ- ities, communication, health maintenance, travel, mobility and socialization, with novel, scalable and viable business models, based on feedback from large-scale, multi-country pilots. 3 CLUSTERING AND TAXONOMIES Here we present the results of two ways of clustering and the results of taxonomies generation of the text descriptions of the Figure 1: Result of k-means with four clusters. EU PlatformUptake platforms for elderly. There are 18 platforms, each of which is described by 66 features. First, the text description of the platforms was converted into numeric values, e.g. “yes” gets converted to 10, “no” to 0, “par- tial” to 5. A part of features couldn’t be directly converted into numbers – mainly features with string-type unordered values, e.g. “Any (web)”, “Windows, mobile, Symbian”, “Java”. 3.1 K-means clustering K-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. k-means clustering minimizes within- cluster variances (squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances. For instance, Figure 2: Result of k-means with four clusters with labels. better Euclidean solutions can be found using k-medians and k-medoids [2]. The goal of clustering is to determine how many and which cluster groups represent the platforms best, based on the descrip- tions of EU platforms for elderly, created by the EU PlatformUp- take project in Spring 2021. In Figure 1 we can see the results of k-means with four clusters. In Figure 2 we can see the results of k-means with four clusters with labels. The platforms are divided into: • cluster 1: VAALID. • cluster 2: AmIVITAL, EKOSMART, INLIFE, OASIS, sensi- Nact, UNCAP, UNIVERSAL. • cluster 3: ActivAgeR, FIWARE, Giraff+, InterIoTL, REACH, Figure 3: Result of hierarchical clustering. SOFIA2. • cluster 4: AMIGO, BeyondSilos, PERSONA, SOPRANO. It should be noted that there are only 15 dots visible in Figure is distinct from each other cluster, and the objects within each 1 although there are 18 platforms. The reason is that 4 dots are cluster are broadly similar to each other [1]. overlapped one over another, and therefore are not seen in Figure Hierarchical clustering starts by treating each observation as 1 separately. a separate cluster. Then, it repeatedly executes the following two steps: first, identify the two clusters that are closest together, 3.2 Hierarchical clustering and second, merge the two most similar clusters. This iterative Hierarchical clustering also known as hierarchical cluster analy- process continues until all the clusters are merged together. The sis, is an algorithm that groups similar objects into groups called main output of hierarchical clustering is a dendrogram, which clusters. The endpoint is a set of clusters, where each cluster shows the hierarchical relationship between the clusters [1]. 230 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Žiga Kolar, et al. We got the best result using complete linkage (linkage deter- • All the related web servers ensure... <= 1.875 mines which distance to use between sets of observation). • Implemented data analytics analyze environmental . . . <= Figure 3 shows the dendrogram for the hierarchical clustering. 0.5 In general, closer and shorter lines present greater similarity. • Operating systems supported (including . . . <= 0.5 There are three clusters. One is green colored, one is orange In a similar way, all descriptions of the platforms can be ob- colored and the combined one is blue colored. tained from the generated tree, best differentiating between them. The only exception is the second node from the left where it is 3.3 Taxonomies not possible to distinguish between the three platforms. While the previous features lead to all three of them, the algorithm is not able to create further questions to differentiate between them, i.e. using additional features. 4 CONCLUSION AND DISCUSSION We presented the EU PlatformUptake project for AHA solution assessment, its main objectives and its 18 platforms for elderly chosen because they allow elderly to live more healthy and more independently. We studied similarities and differences between the 18 platforms, and presented the results by two ways of clus- Figure 4: A decision tree of platforms for elderly. tering, and the taxonomies generated from the text descriptions of the EU PlatformUptake platforms. We conclude that the plat- forms can be clustered into similar categories and that an effective According to Wikipedia [4], taxonomy is “the practice and decision tree taxonomy can be created for the platforms. Cluster- science of categorization or classification based on discrete sets.” ing and structuring taxonomies for elderly in the proposed way It is a hierarchical classification, in which things are organized enables an integrated understanding of the field of EU platforms into groups or types. Many taxonomies are hierarchies in the for elderly. form of a tree structure, but not all are. Creating taxonomies In future work, deeper analysis of the clustering is required. often corresponds to machine learning (ML) of a decision tree With k-means it is possible to get better and more clear results from input, where each leaf in a decision tree corresponds to a with 6 or more clusters. It is feasible that hierarchical clustering specific object, e.g. a specific plant species, or in our case – a could also yield more clusters which would be better for deeper taxonomy description. The input for the taxonomies generation analysis. in this section is the same as for the all other approaches in this text, e.g. clustering. There are Initially 61 features. Most of these ACKNOWLEDGMENTS features have values that can be easily converted into numeric values, e.g. “yes” gets converted to 10, “no” to 0, “partial” to 5. This study received funding from the European Union’s Hori- A part of features couldn’t be directly converted into numbers zon 2020 research and innovation programme under the grant – mainly features with string-type unordered values, e.g. “Any agreement number 875452. The authors acknowledge the finan- (web)”, “Windows, mobile, Symbian”, “Java”. These features have cial support from the Slovenian Research Agency (research core been broken (hot encoding) into a bigger number of new features, funding No. P2-0209). e.g. “is web”, “is Windows”, “is mobile”, “is Symbian”, “is Java”. After the transformations, there are 66 features. REFERENCES Figure 4 represents the generated taxonomy on the platforms [1] 2021. Hierarchical clustering. https://www.displayr.com/ analyzed in the EU PlatformUptake project. It is a decision tree what-is-hierarchical-clustering/. (2021). where most of the leafs correspond to only one platform. Starting [2] 2021. K-means clustering. https://en.wikipedia.org/wiki/K- from the root (the top of the decision tree), it contains all the means_clustering. (2021). platforms, hence all 1s in the “value” field. The set of all platform [3] 2021. Platform uptake. https://project.platformuptake.eu/ descriptions gets split into the left and the right node based on the about/. (2021). feature/question “All the related web servers ensure maintenance [4] 2021. Taxonomy. https://en.wikipedia.org/wiki/Taxonomy. and corrections against the main known weaknesses <= 1.875?”. (2021). According to the question that was found the most relevant for [5] 2021. The european demographic deficit. https://www. this decision tree / taxonomy, the set of all taxonomies splits into europarl . europa . eu / sides / getDoc . do ? pubRef= - / / EP / two: (1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0) in the left /TEXT+IM-PRESS+20080414FCS26499+0+DOC+XML+ subtree and (0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1) in the V0//EN. (2021). right subtree. The procedure repeats until ideally there is just one platform left, i.e. all the other platforms do not correspond to the set of questions except the one. For example, the yellow leaf corresponds/represents to the “AmIVITAL” platform. It’s parent node splits platforms looking at the feature named “Operating systems supported (including mobile) – Java OSGi”. If the value is <= 5, it continues the graph over its left arrow; if the value is > 5, it continues the graph over its right arrow, in this case for a leaf “AmIVITAL”. Therefore, the features (questions) leading to the yellow node, i.e. the AmIVITAL platform, are: 231 What-If Analysis of Countermeasures Against COVID-19 in November 2020 in Slovenia Vito Janko Nina Reščič Tea Tušar Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Department of Intelligent Systems Department of Intelligent Systems Department of Intelligent Systems Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia vito.janko@ijs.si nina.rescic@ijs.si tea.tusar@ijs.si Mitja Luštrek Matjaž Gams Jožef Stefan Institute Jožef Stefan Institute Department of Intelligent Systems Department of Intelligent Systems Ljubljana, Slovenia Ljubljana, Slovenia mitja.lustrek@ijs.com matjaz.gams@ijs.com ABSTRACT In the study reported here we used the improved version, specialized for Slovenia, to objectively answer a few what-if Choosing best sets of countermeasures against COVID-19 is a questions, such as whether school closure and mask usage were difficult task, and it is often not clear whether the the counter- justified at a particular point in time, or were they an unnecessary measures that were actually chosen were justified. In this paper burden. we studied if the introduction of masks and school opening in These questions were posed to us by the Slovenian Ministry of the times of exponential growth in November 2020 in Slovenia Health. Namely, in August 2021 we sent the our XPRIZE system to were justified or not. all EU Ministries of Health with the motivation to help decision- KEYWORDS makers better select NPIs. No ministry was able or eager to use the system itself so far, but we got some replies and requests for COVID-19, epidemiological models, multi-objective optimization, particular studies, such as the one tackled in this paper. non-pharmaceutical interventions 1 INTRODUCTION 2 DATASET Our system was trained on the data from 235 world regions Coronavirus disease 2019 (COVID-19) is an infectious disease between the dates of March 1, 2020 and April 14, 2021. While that has rapidly spread across the world. Due to its high mor- taking data from Slovenia only might result in a more localized tality rate [4], most countries deemed it too disruptive to let it model, this data does not provide the necessary range of imple- run unchecked and have thus implemented countermeasures mented NPIs and their combinations. against it. The main type of countermeasures, in particular in The main source of data was the "COVID-19 Government re- the times when the vaccines were not yet available, were the sponse tracker" database, collected by the Blavatnik School of non-pharmaceutical interventions (NPI) that include lockdowns, Government at Oxford University [2], that defines which (and closure of schools and workplaces, and required mask usage. in what time interval) NPIs were implemented in each country. Due to the lack of precedent in the recent history, and several The NPIs in this database are listed in Table 1. The database also variables that influence the effect in a particular country, e.g. provides the strictness of the implementations in the form of weather and cultural circumstances, it was and still is hard for numbers, e.g., "Workplace closing – 1" represents that govern- decision-makers and domain experts to determine which NPIs to ment only suggests closure, while "Workplace closing – 3" strictly implement in a given epidemiological situation and what effect demands it. The detailed description for each level of strictness would a particular combination of NPIs have. is provided by the database authors [2]. As we are now in the second year of the pandemic, large Other key data needed for training the system are the numbers databases of data regarding the spread of the virus and imple- of infections and deaths, obtained from the same database. In mented NPIs aimed at stopping it, became available. This in turn addition we used data on weather, mobility, hospitalizations, allows for the use of artificial intelligence (AI) methods to analyze vaccination and 93 features based on country characteristics (e.g., the data, create predictive models, and consequently help the culture, development) from our previous work [3]. decision-makers in their task. It also enables reevaluation of the influence of particular NPIs at a particular time. 3 METHODS In our previous work [5] we built such an AI system, as part of The results in this work were made using an upgraded version the XPRIZE: Pandemic Response Challenge. At that competition, of our XPRIZE system that can predict the number of infections our system achieved second best results, and was significantly given the active NPIs, and propose best NPIs to counter them. upgraded since that time. The whole system is thoroughly described in our previous Permission to make digital or hard copies of part or all of this work for personal work [5]. Here, a quick overview is provided. The system first or classroom use is granted without fee provided that copies are not made or uses historical data of all regions to create a model that predicts 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 COVID-19 infections given a set of NPIs. A SEIR epidemiological work must be honored. For all other uses, contact the owner /author(s). model is used for this purpose, combined with a machine-learning Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia model that predicts the SEIR models’s parameters as a function © 2021 Copyright held by the owner/author(s). of NPIs. This model is used to predict the infections resulting 232 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vito Janko, Nina Reščič, Tea Tušar, Mitja Luštrek, and Matjaž Gams Table 1: The NPIs used in our study, and the range of val- ues representing their strictness. NPI Value range C1: School closing [0-3] C2: Workplace closing [0-3] C3: Cancel public events [0-2] C4: Restrictions on gatherings [0-4] C5: Close public transport [0-2] C6: Stay at home requirements [0-3] C7: Restrictions on internal movement [0-2] C8: International travel controls [0-4] H1: Public information campaigns [0-2] H2: Testing policy [0-3] H3: Contact tracing [0-2] H6: Facial Coverings outside the home [0-4] Figure 1: A comparison of actual number of daily infec- from a sequence of NPIs (referred to as "intervention plan") – its tions, with predicted number of infections for the hypo- benefit. thetical case where masks were not used. The system also estimates the cost of each intervention plan. Calculating costs of NPIs is a complex issue that will be dis- cussed in a forthcoming paper. In brief, they consist of economic costs (due to disruption of business and similar), for which some sources are available in the literature [6, 1], and social costs (due to isolation, restriction of freedom and similar). The cost of each plan is traded off against its benefit, as stricter plans results in fewer infections, but are costlier. Finally, the system uses multi-objective optimization to find intervention plans with good trade-off between benefits and costs. The two major improvements of the system for the purpose of this paper are: 1) the added possibility to set a constraint on the maximal number of infections allowed – no plan exceeding this constraint is generated and 2) the added possibility to limit the strictness of any individual NPI. This two changes allowed us to analyze the what-if scenarios of what would happen if a certain NPI were not implemented, and what plans can we implement to have a similar number of infections, but not the undesired NPI. The plans presented in this paper were evaluated using only Figure 2: A comparison of actual number of daily infec- their economic component (estimated GDP loss [in %] for that tions, with predicted number of infections for the hypo- month), but not with the social one. While we repeated all the thetical case where schools were re-opened. experiments using social costs, the results were similar, and the social costs we used are less objective than the economic ones. greatly changes the reproduction rate and consequently leads to 4 RESULTS the exponential growth. All the predictions were made for the time interval 30. 10. 2020 – Such fast growth as was predicted in these to experiments is 30. 11. 2020, for Slovenia. That time interval was chosen because probably too pessimistic, as in reality in the case that the number of the high number of infections observed and strict counter- of infections were starting to grow so alarmingly, the population’s measures imposed. behavior would likely become more cautious – counterbalancing In the first experiment, we tested what would have happened the growth. Nonetheless, the model indicates that the school if masks were not worn in closed spaces, and all other NPIs would closure is a major contributor to regulating COVID-19, even remain the same as the actually implemented. The results are more important than the masks. Please note that scale of the 𝑦 shown in Figure 1. They indicate an increase of infections, which axis differs between Figures 1 and 2. was expected considering that we are simulating lowering the The two described experiments show that removing an NPI countermeasures during the epidemic peak, and no other NPI from the implemented intervention plan will likely result in sub- was simulated instead of masks. stantial growth, which decision-makers would not allow. There- A similar experiment was made for the hypothetical case fore, we attempted to compensate for the missing NPIs with other where schools fully re-opened for a month. The results (Figure NPIs to prevent the exponential growth. 2) show that the number of infections would grow even faster. We used multi-objective optimization to show the best plans This happens due to the exponential nature of the epidemiolo- one can make given the restriction that a certain NPI cannot be gical model, encapsulating the actual nature of the virus infection used, at least not with a strictness exceeding a given threshold. in favorable conditions. Obviously, this reduction in strictness These plans were compared based on the predicted infections 233 Feature library Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 2: The weekly strictness of selected intervention plans. The letters identify the plan on the Pareto front approximations in Figures 3 and 4. Strictness 0044 would indicate that the lowest strictness is used for the first two weeks, and highest for the last two ones. NPI a b c d e f g h i C1: School closing 3333 3333 3333 2222 2222 1111 1111 3333 3333 C2: Workplace closing 2222 0000 2000 1000 3000 3002 3301 0000 3000 C3: Cancel public events 2222 2222 2222 2222 2222 2222 2222 2222 2222 C4: Restrictions on gatherings 4444 4444 4442 4444 4444 4444 4444 4444 4444 C5: Close public transport 0022 2222 2222 2222 2222 2222 2222 2222 2222 C6: Stay at home requirements 2222 0010 1100 1111 1110 1111 1111 1100 3110 C7: Restrictions on internal movement 2222 0000 1000 1000 2000 2011 2210 0000 2200 C8: International travel controls 2222 4343 4443 4444 4444 4444 4444 4444 4444 H1: Public information campaigns 2222 2222 2222 2222 2222 2222 2222 2222 2222 H2: Testing policy 2222 3333 3333 3333 3333 3333 3333 3333 3333 H3: Contact tracing 1111 2222 2222 2222 2222 2222 2222 2222 2222 H6: Facial coverings outside the home 4444 4444 4444 4444 4444 4444 4444 0000 0000 Figure 3: Proposed intervention plans using different re- Figure 4: Proposed intervention plans generated using dif- strictions on the value of "School closing". They were eval- ferent restrictions on the value of "Facial covering". They uated based on the predicted number of infections and were evaluated based on the predicted number of infec- estimated GDP loss. The marked plans are explained in tions and estimated GDP loss. The marked plans are ex- Table 2. plained in Table 2. "School closing" NPI, so it is easier to replace by increasing other NPIs. and predicted GDP loss for that month. The resulting Pareto- front approximations for school closure with different levels of 5 DISCUSSION AND CONCLUSIONS strictness are shown in Figure 3. In this study we analyzed what-if scenarios in regards to reduced The blue line in Figure 3 represents the case with no limit- wearing of masks and school re-openings for Slovenia at peak ations when constructing an intervention plan, and obviously infection time in November 2020. The study showed that both of these solutions are substantially better than the intervention plan these changes would worsen the epidemiological situation in the actually implemented, and the plans with limitations. The orange country if no other NPI was introduced instead. Furthermore, for and green lines represent plans that have schools partially or fully school closure the AI model could not find proper replacement in open. These plans are visibly worse in terms of the two desired that situation, suggesting that school closure was justified. The objectives: this happens because the system is compensating for closest viable solution was "Solution e" that proposes only partial the lack of "School closing" NPI with "Workplace closing" NPI, school closing, but compensates it with increased testing and which is more expensive. A sample of the generated plans is international travel control. On the other hand, the model indic- given in Table 2. ated that mask usage could be almost completely compensated This experiment was repeated, this time restricting the strict- with an increase of other NPIs. It cannot judge whether this is ness of the "Facial Coverings" NPI. The results are shown in desirable – that may depend on social costs. Figure 4 and sample plans are given in Table 2. The study has a number of limitations: For the mask analysis, the system found comparable solutions that compensate for the reduced "Facial Coverings" NPI. While (1) The study was done using historic data for Slovenia, while this NPI has a good ratio between benefit and economic cost, the AI system was trained on data from all regions and its benefit in absolute terms is nevertheless smaller than of the was only somewhat tuned to Slovenia. 234 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vito Janko, Nina Reščič, Tea Tušar, Mitja Luštrek, and Matjaž Gams (2) The data and the resulting model do not contain the in- Acknowledgement formation on vaccination, as it was not available in the First, we would like to acknowledge all other authors who con- tested period. tributed to the development of the presented AI system: Erik (3) The data and the resulting model do not contain the in- Dovgan, David Susič, Carlo De Masi, Tea Tušar, Matej Cigale, formation on the Delta or newer variants, as it was not Matej Marinko, Aljoša Vodopija, Anton Gradišek. available in the tested period. Second, we want to acknowledge XPRIZE, the organizer of (4) The model does not predict what would happen with a the $500K Pandemic Response Challenge competition and their different implementation of the NPI (e.g., stricter testing sponsor Cognizant, who made the development of the system of students/teachers). possible. (5) The study uses costs available from the literature and Finally, we acknowledge the financial support from the Slove- might not fit best Slovenian specifics. nian Research Agency (research core funding No. P2-0209). (6) The study does not use social costs, which are certainly important but difficult to set in a justifiable manner. REFERENCES Because of these limitations, it is not recommended that this [1] 2021. Business closures and partial reopenings due to covid- study be used as a basis for future policies. For such purpose, we 19 could cost the u.s. trillions. https://news.usc.edu/178979/ strongly recommend performing new experiments tailored to business- closures- covid- 19- pandemic- united- states- gdp- the problem we try to address. losses/. Comparing best AI-proposed measures with the actual ones by [2] Thomas Hale, Sam Webster, Anna Petherick, Toby Phil- humans reveals a well-known phenomenon that humans cannot lips and Beatriz Kira. 2020. Oxford covid-19 government on their own consider all possibilities and propose best actions. response tracker, blavatnik school of government. (April Although demonstrated only on a couple of cases here, in our 2020). https : / / www . bsg . ox . ac . uk / research / research - opinion that is a fairly general conclusion valid not only for projects/covid- 19- government- response- tracker. COVID-19 NPIs. In most cases it should still be the human’s role [3] Vito Janko, Gašper Slapničar, Erik Dovgan, Nina Reščič, to make final decisions, but humans should take advantage of AI Tine Kolenik, Martin Gjoreski, Maj Smerkol, Matjaž Gams assistance when possible. and Mitja Luštrek. 2021. Machine learning for analyzing In summary, school closing and masks in general represent non-countermeasure factors affecting early spread of covid- important NPIs, and the decision to use them in peak infection 19. International Journal of Environmental Research and Pub- cases when vaccinations are not available or sufficient, seems lic Health, 18, 13. issn: 1660-4601. doi: 10.3390/ijerph18136750. reasonable. However, unlike the school closing, the masks can be https://www.mdpi.com/1660- 4601/18/13/6750. replaced with other NPIs. Furthermore, vaccinations in particular [4] Gideon Meyerowitz-Katz and Lea Merone. 2020. A system- render NPIs less important – if no new variant of COVID-19 atic review and meta-analysis of published research data appears. on covid-19 infection-fatality rates. International Journal of Infectious Disease, 101, (December 2020), 138–148. An optional note. [5] Reščič Nina, Janko Vito, Susič David, De Masi Carlo, Vodop- ija Aljoša, Marinko Matej, Tušar Tea, Dovgan Erik, Gradišek Anton, Cigale Matej, Gams Matjaž and Luštrek Mitja. 2021. Finding efficient intervention plans against covid-19. In ETAI 2021 (exact name will be given for the camera ready version). (September 2021). [6] Md Z Sadique, Elisabeth J Adams and William J Edmunds. 2008. Estimating the costs of school closure for mitigating an influenza pandemic. BMC public health, 8, 1, 1–7. 235 Effectiveness of non-pharmaceutical interventions in handling the COVID-19 pandemic: review of related studies Janez Tomšič David Susič Matjaž Gams janez2001@gmail.com David.Susic@ijs.si Matjaz.Gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT restrictions on gatherings, public transport closure, stay at home In this paper, we analyse 30 articles on studies that focus on requirements, restrictions on internal movement, international assessing the effectiveness of different non-pharmaceutical in- travel controls, public information campaigns, testing policy, terventions (NPIs) to flatten the pandemic curve. The articles contact tracing and facial coverings. The 12 NPIs listed were reviewed use different methods, data sources, and metrics for chosen because they are independent of each other and cover all NPI effectiveness. They also analyse different regions in different radical government interventions used worldwide. For example, time periods. Here, we rank the interventions from each article curfew is included in the stay at home requirements. using a consistent scoring system. This allows us to rank and The articles included in this review, the corresponding NPI compare the effectiveness of each NPI. data sources, the countries included, and the time frame in which We conclude that school closure, workplace closure and restric- the effectiveness of the interventions was assessed can be seen tions on gatherings are the most effective interventions. Public in Table 1. events cancellation and public information campaigns also ap- pear to have a significant impact. Stay at home requirements, 2.2 Articles not based on OxCGRT data facial coverings, restrictions on internal movement and interna- In articles on studies that obtained NPI data from other sources, tional travel controls have a moderate effect. The least effective intervention policies were checked for compatibility with Ox- NPIs across all studies were found to be public transport closure, CGRT descriptions wherever possible, using documentation from testing policy and contact tracing. the individual NPI databases or descriptions provided by the au- thors (in studies where data collection was conducted by the KEYWORDS authors themselves). Non-pharmaceutical interventions, COVID-19, SARS-CoV-2 In this review, some interventions from the article by Haug et al. [15] were merged into those specified by OxCGRT, with 1 INTRODUCTION the effectiveness of the merged NPI defined as the maximum The COVID-19 pandemic has forced governments around the effectiveness of the nonmerged ones. In this way, both small globe to implement several non-pharmaceutical interventions and mass gathering cancellations were merged into restrictions (NPIs). Researchers have studied the effectiveness of such inter- on gatherings. Border restriction, travel alert and warning were ventions to help governments make more informed decisions in merged into international travel controls. dealing with the crisis. Some interventions have been reassigned to the appropriate The aim of this review is to summarize and compare the find- OxCGRT definitions. Educate and actively communicate with ings and methods of several articles on the impact of NPIs on the public was transformed into public information campaigns, COVID -19 and to determine which interventions are best suited enhance detection system into testing policy, and national lock- to improve the epidemiological situation. down into stay at home requirements. The study by Bo et al. [3] analysed the impacts of four inter- 2 METHODOLOGY vention categories, namely traffic restriction, social distancing, mandatory wearing of a face mask in public, and isolation or 2.1 Selection of articles quarantine. Most of these interventions are a combination of For this review, we searched for articles that focused on assessing several OxCGRT interventions, so their effectiveness score was the effectiveness of NPIs in dealing with the ongoing COVID -19 assigned to all the NPIs that comprise them. The score of traffic pandemic. To be included here, articles had to include compar- restriction was assigned to restrictions on internal movement and isons of at least two interventions so that each could be ranked international travel controls, and the social distancing to school from most to least effective. Important works on the spread of closing, public events cancellation, and restriction on gatherings. COVID -19 that do not include a comparison of different NPIs Mandatory face masks in public was assigned to facial coverings (e.g., Chang, S. et al. [5]) are therefore not included in this review. and isolation or quarantine to stay at home orders. Effectiveness of the following NPIs from the Oxford COVID- Banholzer et al. [2] estimated the effectiveness of seven NPIs. 19 Government Response Tracker (OxCGRT) [14] was assessed: They treated bans on small and large gatherings as two seper- school closure, workplace closure, public events cancellation, ate interventions, so they were merged here into restrictions on gatherings. Venue closure and work-from-home order were Permission to make digital or hard copies of part or all of this work for personal merged into workplace closure based on the fact that the authors 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 described venue closure as "closure of some or all non-essential the full citation on the first page. Copyrights for third-party components of this businesses". Their border closure intervention was treated as work must be honored. For all other uses, contact the owner/author(s). international travel controls in this review. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). In other articles that included the non-essential business clos- ing intervention it was treated as OxCGRT’s workplace closure. 236 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Janez Tomšič, David Susič, and Matjaž Gams Table 1: Articles included in this review Authors Published in NPI data source Countries included Askitas et al. [1] Nature OxCGRT 175 countries Banholzer et al. [2] Plos One Collected by the authors USA, Canada, Australia and 17 EU countries Bo et al. [3] ScienceDirect Collected by the authors 190 countries Brauner et al. [4] Science Collected by the authors 41 countries (of which 34 are European) Chaudhry et al. [6] The Lancet Collected by the authors 50 countries Chernozhukov et al. [7] ScienceDirect Covid Tracking Project USA Courtemanche et al. [8] Health Affairs John Hopkins University 3138 US counties Deb et al. [9] SSRN OxCGRT 129 countries Dreher et al. [10] ScienceDirect unclear USA Ebrahim et al. [11] JMIR Hikma Health 1320 US counties Esra et al. [12] medRxiv WHO-PHSM 26 countries and 34 US states Haug et al. [15] Nature CCCSL 56 countries, 79 territories Hunter et al. [16] medRxiv IHME 30 European countries Islam et al. [17] BMJ OxCGRT 149 countries Jalali et al. [18] medRxiv Collected by the authors 30 most populous US counties Jüni et al. [19] CMAJ Collected by the authors 144 worldwide geopolitical re- gions Koh et al. [20] ScienceDirect OxCGRT 170 countries Leffler et al. [21] AJTMH OxCGRT 200 countries Li et al. (a) [22] The Lancet OxCGRT 131 countries Li et al. (b) [23] MDPI NSF spatiotemporal center USA Liu et al. [24] BMC Medicine OxCGRT 130 countries and territories Olney et al. [26] American Journal of Epidemi- Collected by the authors USA ology Papadopoulos et al. [27] medRxiv OxCGRT 151 countries Piovani et al. [28] ScienceDirect OxCGRT 37 members of OECF Pozo-Martin et al. [29] Springer Link OxCGRT and WHO-PHSM 37 members of OECD Sharma et al. [30] medRxiv Collected by the authors 114 subnational areas in 7 Eu- ropean countries Stokes et al. [32] medRxiv OxCGRT 130 countries Wibbens et al. [33] Plos One OxCGRT 40 countries and US states Wong et al. [34] Journal of Infection OxCGRT 139 countries Zhang et al. [35] MDPI NY Times and CNN USA National lockdown was mapped to stay at home requirements. graded its effectiveness as 2. International travel controls NPI Some studies measured the effectiveness of bans on small and was less effective. Restrictions on internal movement and public mass gatherings separately. Their results were combined into a transport closures had a negligible impact. single intervention - restrictions on gatherings. In the study by Liu et al. [24], the effectiveness of NPIs was measured in two scenarios: maximum effort (i.e., the NPIs are at 2.3 Ranking effectiveness of NPIs their maximum intensity) and any effort (i.e., the NPIs are active at any intensity). They described interventions as either strong, Different studies estimated the individual impacts of implement- moderate, or weak in each of the scenarios. Their results were ing interventions in different ways. We used a simplified ranking adapted to the simplified ranking system by assigning a value of system by assigning values between 1 and 4 to the NPIs, with 1 1 to NPIs strong in either both scenarios or in any effort scenario. representing the most effective and 4 the least effective interven- NPIs that are strong only at maximum effort were graded 2, tions. Several interventions from individual studies could have moderate NPIs were ranked as 3 regardless of the scenario and been assigned the same value. weak NPIs were ranked as 4. In the articles where the authors have already quantitatively In the article written by Li et al. (a) [22], the impact of NPIs was estimated the impacts of individual NPIs, their results have simply estimated 7 days, 14 days and 28 days after its implementation as been converted to new values, as described above. the ratio between the reproduction number (R) at a given time Askitas et al. [1] graded interventions only descriptively. They point (after 7, 14 or 28 days) and the initial R. We simplified this found that the most effective interventions in reducing the spread by calculating the average between all three ratios for each NPI of COVID-19 were restrictions on gatherings, public events can- and ranking them with values between 1 to 4. cellation, school closure and workplace closure, so they were Wibbens et al. [33] estimated the effectiveness of 11 NPIs at assigned a value of 1. Stay at home requirements were estimated different levels of intensity. They were first ranked at their highest to have a smaller effect after a longer period of time and we 237 NPI effectiveness review Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia intensity and then at an intermediate intensity. Our metric with by COVID-19 and 5 articles [7][9][18][23][27] analysed the im- values between 1 and 4 was then applied based on the average of pact on both cases and deaths. high and intermediate intensity rankings. 3.3 NPI effectiveness estimations 2.4 Comparison with a similar article Some intervention policies were included in more studies than While looking for studies to include in this review we found a others. The ones that were included in most of the studies re- similar article by Mendez-Brito et al. [25]. Their review included viewed are school closure (conclusively assessed in 22 studies), 34 articles on the subject of NPI effectiveness. Here, some of these workplace closure (in 22 studies), restrictions on gatherings (in articles were excluded, most of them because they only found 18 studies), and stay at home requirements (in 20 studies). The conclusive evidence for the effectiveness of a single intervention distribution of estimated effectiveness of these NPIs across in- policy. Furthermore, the study conducted by Flaxman et al. [13] is cluded articles is shown in Figure 1. Contact tracing was only also not included in this review because Soltesz et al. [31] proved analysed in two articles [33][24] and testing policy in four articles that the model used was too sensitive to subtle and realistic [15][24][29][33]. alterations in parameter values. Two additional articles were included in this review [1][30]. However, all other studies included in our paper were already reviewed in the review by Mendez-Brito et al. [25]. Despite that, there are a few differences between our findings and theirs. Slight differences occur in grading effectiveness of NPIs from different studies, most likely because many studies did not present a rank- ing system and so our interpretation of their results might be different than that of Mendez-Brito et al. There are some articles that do not compare impacts of dif- ferent intervention policies, but rather only qualitatively mark them as effective in reducing the COVID-19 incidence. The NPIs assessed in those studies were all graded with the same grade by Mendez-Brito et al. They treated those interventions as the Figure 1: Distribution of effectiveness values for the most least effective according to their scale. Since such NPIs were only frequently represented NPIs (lower values stands for bet- found to be effective but it was not determined how effective ter effectiveness they were, we could not confidently grade them as the most effec- tive interventions, but their impact likewise could not be treated The impacts of NPIs in the included studies are shown in Fig- as negligible. That is why they are marked here as moderately ure 3. Blank cells indicate that the intervention was either not effective, i.e., they are graded with a 2. included in the corresponding study or that the estimates of its effectiveness were inconclusive. Cells are also color coded ac- 3 RESULTS cording to the strength of the interventions in the corresponding articles. A darker shade indicates that the NPI is more effective. 3.1 Assessed regions and time frames The average effectiveness, median effectiveness and the most The reviewed studies assessed the impact of COVID-19 inter- frequent value were calculated for each NPI across all articles vention policies in different time frames. Most studies only anal- and are presented in Figure 2 along with inormation on how ysed the first epidemiological wave. Only Sharma et al. [30] many articles conclusively assessed each NPI and the standard focused on estimating effectiveness of NPIs during the second deviation for each NPI. wave. Wibbens et al. [33] analysed a longer time frame - from March to November 2020. Pozo-Martin et al. [29] analysed both 4 CONCLUSION waves independently, but the estimates of NPI effectiveness dur- Studies estimating the effectiveness of COVID-19 interventions ing the second wave were not as statistically significant. Zhang used different approaches. They analysed data from different et al. [35] also analysed a longer period including both waves. regions and in different time frames. They did not use the same The majority of studies (19 out of 30) analysed only country- models to analyse the data or the same metrics to determine the level data. Two studies [29][28] used data only on countries that effects different interventions had on the pandemic. Nonetheless, are members of the Organisation for Economic Co-operation and their findings were often agreed with each other. Development (OECD). The works [11][26][8][23][18][35][7][10] The most effective interventions across the reviewed studies analysed impacts of NPIs in the United States, either state-level were school closure, workplace closure and restrictions on gather- or county-level. The only more detailed analysis for Europe was ings. School closure was estimated to be among the most effective done by Sharma et al. [30], who analysed 114 subnational areas intervention policies in 9 studies (41% of studies in which it was in 7 European countries. assessed), workplace closure in 5 (23%) studies, and restrictions on gatherings in 8 (44%) studies. Public events cancellation was 3.2 Metrics used in studies also found to be one of the most effective measures in 3 (33%) out The studies in this review used different metrics to evaluate the of 9 studies. Interestingly, public information campaigns appear impacts of the interventions. 10 studies analysed how individual to be as effective as cancellation of public events. NPIs affect the reproduction number [3][4][10][12][15][20][22] Stay at home requirements was also estimated to have a con- [24][26][30]. 8 studies estimated the effectiveness of NPIs based siderable impact, but the interventions mentioned above were on case incidence or case growth rates [1][2][8][11][19][29][33] found to be even more effective. This could be because the stay [35]. 4 articles [6][21][28][32] focused only on mortality caused at home requirements NPI was often implemented as a last resort 238 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Janez Tomšič, David Susič, and Matjaž Gams Figure 2: Averaged effectiveness, median effectiveness and most frequent value (Mode) of each NPI across studies (lower value stands for better effectiveness) along with the number of studies that assessed each NPI (Counts) and standard deviations (Std dev). in addition to many other interventions and its isolated effect analysis measuring the impact of government actions, might only be what it adds on top of those. country preparedness and socioeconomic factors on covid- Facial coverings, restrictions on internal movement and inter- 19 mortality and related health outcomes. EClinicalMedicine, national travel controls were generally associated with having a 25, 100464. moderate effect on flattening the epidemic curve. The least effec- [7] Victor Chernozhukov, Hiroyuki Kasahara, and Paul Schrimpf. tive NPIs were consistently found to be public transport closure, 2021. Causal impact of masks, policies, behavior on early testing policy and contact tracing. covid-19 pandemic in the us. Journal of econometrics, 220, 1, 23–62. REFERENCES [8] Charles Courtemanche, Joseph Garuccio, Anh Le, Joshua [1] Nikolaos Askitas, Konstantinos Tatsiramos, and Bertrand Pinkston, and Aaron Yelowitz. 2020. Strong social distanc- Verheyden. 2021. Estimating worldwide effects of non- ing measures in the united states reduced the covid-19 pharmaceutical interventions on covid-19 incidence and growth rate: study evaluates the impact of social distanc- population mobility patterns using a multiple-event study. ing measures on the growth rate of confirmed covid-19 Scientific reports, 11, 1, 1–13. cases across the united states. Health Affairs, 39, 7, 1237– [2] Nicolas Banholzer, Eva Van Weenen, Adrian Lison, Alberto 1246. Cenedese, Arne Seeliger, Bernhard Kratzwald, Daniel Tsch- [9] Pragyan Deb, Davide Furceri, Jonathan D Ostry, and Nour ernutter, Joan Puig Salles, Pierluigi Bottrighi, Sonja Lehti- Tawk. 2020. The effect of containment measures on the nen, et al. 2021. Estimating the effects of non-pharmaceutical covid-19 pandemic. interventions on the number of new infections with covid- [10] Nickolas Dreher, Zachary Spiera, Fiona M McAuley, Lind- 19 during the first epidemic wave. PLoS one, 16, 6, e0252827. sey Kuohn, John R Durbin, Naoum Fares Marayati, Muham- [3] Yacong Bo, Cui Guo, Changqing Lin, Yiqian Zeng, Hao Bi mad Ali, Adam Y Li, Theodore C Hannah, Alex Gometz, Li, Yumiao Zhang, Md Shakhaoat Hossain, Jimmy WM et al. 2021. Policy interventions, social distancing, and sars- Chan, David W Yeung, Kin On Kwok, et al. 2021. Effec- cov-2 transmission in the united states: a retrospective tiveness of non-pharmaceutical interventions on covid-19 state-level analysis. The American journal of the medical transmission in 190 countries from 23 january to 13 april sciences, 361, 5, 575–584. 2020. International Journal of Infectious Diseases, 102, 247– [11] Senan Ebrahim, Henry Ashworth, Cray Noah, Adesh Kadambi, 253. Asmae Toumi, and Jagpreet Chhatwal. 2020. Reduction of [4] Jan M Brauner, Sören Mindermann, Mrinank Sharma, covid-19 incidence and nonpharmacologic interventions: David Johnston, John Salvatier, Tomáš Gavenčiak, Anna B analysis using a us county–level policy data set. Journal Stephenson, Gavin Leech, George Altman, Vladimir Miku- of medical Internet research, 22, 12, e24614. lik, et al. 2021. Inferring the effectiveness of government [12] Rachel T Esra, Lise Jamesion, Matthew P Fox, Daniel interventions against covid-19. Science, 371, 6531. Letswalo, Nkosinathi Ngcobo, Sithabile Mngadi, Janne [5] Serina Chang, Emma Pierson, Pang Wei Koh, Jaline Ger- Global Estill, Gesine Meyer-Rath, and Olivia Keiser. 2020. ardin, Beth Redbird, David Grusky, and Jure Leskovec. Evaluating the impact of non-pharmaceutical interven- 2021. Mobility network models of covid-19 explain in- tions for sars-cov-2 on a global scale. MedRxiv. equities and inform reopening. Nature, 589, 1, 82–85. [13] Seth Flaxman, Swapnil Mishra, Axel Gandy, H Juliette [6] Rabail Chaudhry, George Dranitsaris, Talha Mubashir, T Unwin, Thomas A Mellan, Helen Coupland, Charles Justyna Bartoszko, and Sheila Riazi. 2020. A country level Whittaker, Harrison Zhu, Tresnia Berah, Jeffrey W Eaton, 239 NPI effectiveness review Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 3: Estimated effectiveness of each NPI in different studies (lower value stands for better effectiveness) 240 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Janez Tomšič, David Susič, and Matjaž Gams et al. 2020. Estimating the effects of non-pharmaceutical [25] Alba Mendez-Brito, Charbel El Bcheraoui, and Francisco interventions on covid-19 in europe. Nature, 584, 7820, Pozo-Martin. 2021. Systematic review of empirical stud- 257–261. ies comparing the effectiveness of non-pharmaceutical [14] Thomas Hale, Noam Angrist, Rafael Goldszmidt, Beat- interventions against covid-19. Journal of Infection. riz Kira, Anna Petherick, Toby Phillips, Samuel Webster, [26] Andrew M Olney, Jesse Smith, Saunak Sen, Fridtjof Thomas, Emily Cameron-Blake, Laura Hallas, Saptarshi Majumdar, and H Juliette T Unwin. 2021. Estimating the effect of so- et al. 2021. A global panel database of pandemic policies cial distancing interventions on covid-19 in the united (oxford covid-19 government response tracker). Nature states. American Journal of Epidemiology, 190, 8, 1504– Human Behaviour, 5, 4, 529–538. 1509. [15] Nils Haug, Lukas Geyrhofer, Alessandro Londei, Elma Der- [27] Dimitris I Papadopoulos, Ivo Donkov, Konstantinos Char- vic, Amélie Desvars-Larrive, Vittorio Loreto, Beate Pinior, itopoulos, and Samuel Bishara. 2020. The impact of lock- Stefan Thurner, and Peter Klimek. 2020. Ranking the effec- down measures on covid-19: a worldwide comparison. tiveness of worldwide covid-19 government interventions. MedRxiv. Nature human behaviour, 4, 12, 1303–1312. [28] Daniele Piovani, Maria Nefeli Christodoulou, Andreas [16] Paul Raymond Hunter, Felipe Colon-Gonzalez, Julii Suzanne Hadjidemetriou, Katerina Pantavou, Paraskevi Zaza, Pan- Brainard, and Steve Rushton. 2020. Impact of non-pharmaceutical telis G Bagos, Stefanos Bonovas, and Georgios K Nikolopou- interventions against covid-19 in europe: a quasi-experimental los. 2021. Effect of early application of social distancing in- study. MedRxiv. terventions on covid-19 mortality over the first pandemic [17] Nazrul Islam, Stephen J Sharp, Gerardo Chowell, Sharmin wave: an analysis of longitudinal data from 37 countries. Shabnam, Ichiro Kawachi, Ben Lacey, Joseph M Massaro, Journal of Infection, 82, 1, 133–142. Ralph B D’Agostino, and Martin White. 2020. Physical dis- [29] Francisco Pozo-Martin, Heide Weishaar, Florin Cristea, tancing interventions and incidence of coronavirus disease Johanna Hanefeld, Thurid Bahr, Lars Schaade, and Charbel 2019: natural experiment in 149 countries. bmj, 370. El Bcheraoui. 2021. The impact of non-pharmaceutical [18] Aliea M Jalali, Sumaia G Khoury, JongWon See, Alexis M interventions on covid-19 epidemic growth in the 37 oecd Gulsvig, Brent M Peterson, Richard S Gunasekera, Gen- member states. European journal of epidemiology, 1–12. tian Buzi, Jason Wilson, and Thushara Galbadage. 2020. [30] Mrinank Sharma, Sören Mindermann, Charlie Rogers- Delayed interventions, low compliance, and health dispar- Smith, Gavin Leech, Benedict Snodin, Janvi Ahuja, Jonas B ities amplified the early spread of covid-19. MedRxiv. Sandbrink, Joshua Teperowski Monrad, George Altman, [19] Peter Jüni, Martina Rothenbühler, Pavlos Bobos, Kevin Gurpreet Dhaliwal, et al. 2021. Understanding the effec- E Thorpe, Bruno R Da Costa, David N Fisman, Arthur S tiveness of government interventions in europe’s second Slutsky, and Dionne Gesink. 2020. Impact of climate and wave of covid-19. medRxiv. public health interventions on the covid-19 pandemic: a [31] Kristian Soltesz, Fredrik Gustafsson, Toomas Timpka, Joakim prospective cohort study. Cmaj, 192, 21, E566–E573. Jaldén, Carl Jidling, Albin Heimerson, Thomas B Schön, [20] Wee Chian Koh, Lin Naing, and Justin Wong. 2020. Es- Armin Spreco, Joakim Ekberg, Örjan Dahlström, et al. 2020. timating the impact of physical distancing measures in The effect of interventions on covid-19. Nature, 588, 7839, containing covid-19: an empirical analysis. International E26–E28. Journal of Infectious Diseases, 100, 42–49. [32] Jonathan Stokes, Alex James Turner, Laura Anselmi, Mar- [21] Christopher T Leffler, Edsel Ing, Joseph D Lykins, Matthew cello Morciano, and Thomas Hone. 2020. The relative ef- C Hogan, Craig A McKeown, and Andrzej Grzybowski. fects of non-pharmaceutical interventions on early covid- 2020. Association of country-wide coronavirus mortality 19 mortality: natural experiment in 130 countries. medRxiv. with demographics, testing, lockdowns, and public wear- [33] Phebo D Wibbens, Wesley Wu-Yi Koo, and Anita M Mc- ing of masks. The American journal of tropical medicine Gahan. 2020. Which covid policies are most effective? a and hygiene, 103, 6, 2400. bayesian analysis of covid-19 by jurisdiction. PloS one, 15, [22] You Li, Harry Campbell, Durga Kulkarni, Alice Harpur, 12, e0244177. Madhurima Nundy, Xin Wang, Harish Nair, Usher Net- [34] Martin CS Wong, Junjie Huang, Jeremy Teoh, and Sunny H work for COVID, et al. 2021. The temporal association of Wong. 2020. Evaluation on different non-pharmaceutical introducing and lifting non-pharmaceutical interventions interventions during covid-19 pandemic: an analysis of with the time-varying reproduction number (r) of sars- 139 countries. The Journal of Infection, 81, 3, e70. cov-2: a modelling study across 131 countries. The Lancet [35] Xue Zhang and Mildred E Warner. 2020. Covid-19 policy Infectious Diseases, 21, 2, 193–202. differences across us states: shutdowns, reopening, and [23] Yun Li, Moming Li, Megan Rice, Haoyuan Zhang, Dexuan mask mandates. International Journal of Environmental Sha, Mei Li, Yanfang Su, and Chaowei Yang. 2021. The Research and Public Health, 17, 24, 9520. impact of policy measures on human mobility, covid-19 cases, and mortality in the us: a spatiotemporal perspec- tive. International Journal of Environmental Research and Public Health, 18, 3, 996. [24] Yang Liu, Christian Morgenstern, James Kelly, Rachel Lowe, and Mark Jit. 2021. The impact of non-pharmaceutical interventions on sars-cov-2 transmission across 130 coun- tries and territories. BMC medicine, 19, 1, 1–12. 241 Napovedovanje trendov in optimiziranje ukrepov v boju proti pandemiji COVID-19: Tekmovanje XPRIZE in naslednji koraki Forecasting trends and optimizing the intervention plans against the COVID-19 pandemic: The XPRIZE competition and beyond Mitja Luštrek, Nina Reščič, Matej Cigale, Anton Odsek za inteligentne sisteme Vito Janko, David Susič, Gradišek, Matjaž Gams Institut “Jožef Stefan” Carlo De Masi, Aljoša Ljubljana, Slovenija mitja.lustrek@ijs.si Vodopija, Matej Marinko, nina.rescic@ijs.si, Tea Tušar, Erik Dovgan, vito.janko@ijs.si POVZETEK KEYWORDS V tem preglednem prispevku predstavimo delo, ki smo ga COVID-19, epidemiological models, nonpharmaceutical sodelavci Odseka za inteligentne sisteme opravili v zadnjem letu interventions, multi-objective optimization v povezavi s pandemijo COVID-19. Raziskave modelov, ki predvidevajo prenos okužb v lokalnem okolju in na podlagi tega predlagajo ukrepe za boj proti epidemiji, so najprej potekale v 1 UVOD okviru mednarodnega tekmovanja $500k Pandemic Response Ko se danes ozremo na prve mesece leta 2020, je jasno, da je Challenge, v organizaciji fundacije XPRIZE in podjetja pandemija COVID-19 zahodni svet ujela nepripravljen. Ker je Cognizant. Na tekmovanju se je ekipa JSI vs COVID uvrstila na šlo za nov virus, se najprej ni vedelo, kako kužen je, kako hitro drugo mesto. V nadaljevanju so potekale raziskave v povezavi z se širi, predvsem pa kako se pred njim zaščititi in kako preprečiti Ministrstvom za zdravje RS, da bi ugotovitve in modele lahko v obremenitev bolnišnic in visoka števila težko bolnih in mrtvih. boju proti pandemiji uporabili tudi v praksi. Zelo hitro se je namreč pokazalo, da v primerjavi z nekaterimi drugimi respiratornimi obolenji več obolelih potrebuje KLJUČNE BESEDE bolnišnično oskrbo, nekateri tudi obravnavo na intenzivni negi in COVID-19, epidemiološki modeli, nefarmacevtski ukrepi, pomoč medicinskega ventilatorja. Zdravniki so poleg tega večkriterijska optimizacija potrebovali več mesecev, da so ugotovili, kako najučinkoviteje zdraviti paciente s COVID-19. Pomembno je bilo tudi ABSTRACT podcenjevanje nevarnosti, ker se je pričakovalo, da bo možno s We present an overview of the work that was carried out by the sledenjem okuženih, ki so npr. prileteli z avionom, zajeziti vdor members of the Department of Intelligent Systems in the last year, virusa v državo. Ker je virus sposoben prenašanja tudi preko na related to the COVID-19 pandemic. We were studying the videz zdravih ljudi, ta ukrep ni bil sposoben zajeziti vdora oz. models that forecast the spread of infection in local environment blokirati pri majhnem številu okuženih. and tried to suggest the countermeasures based on the trends. The Med različnimi pristopi v boju proti širjenju okužb se je zelo research first took place within the $500k Pandemic Response hitro uveljavil pristop »lockdowna«, praktično popolnega zaprtja Challenge, organized by the XPRIZE fundation and the company družbe. Ta pristop so najprej uporabili na Kitajskem, v mestu Cognizant. The JSI vs COVID team won the second place in the Wuhan, kjer so najprej zasledili virus, v Evropi so prvi začeli z competition. In the following months, the research focused on zapiranjem v Italiji, februarja, najprej v posameznih občinah na the applicability of the results in practive, in collaboration with severu države, kasneje po celotni državi. V Sloveniji so bili prvi the Ministry of Health. primeri virusa zaznani v začetku marca, sredi marca pa je prišlo do zaprtja države. Časovni potek prvih mesecev pandemije je opisan v [1]. Kmalu se je pokazalo, da popolno zaprtje družbe sicer precej učinkovito omeji širjenje okužb, ni pa učinkovito na dolgi rok, 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 saj je izredno drago za državo in prebivalce tako z ekonomskega for profit or commercial advantage and that copies bear this notice and the full kot tudi z družbenega vidika. Raziskovalci so zato začeli citation on the first page. Copyrights for third-party components of this work must preučevati kombinacije ukrepov, ki bi po eni strani učinkovito be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia omejili širjenje okužb, po drugi strani pa bi čim manj prizadeli © 2021 Copyright held by the owner/author(s). 242 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia M. Luštrek et al. gospodarstvo in državljane. Takih sistemskih rešitev, npr. milijona dolarjev. Še osem ekip je prejelo posebna priznanja in programov, ob pojavu virusa COVID-19 še ni bilo. simbolične nagrade. Iskanje učinkovitih kombinacij ukrepov, ki hkrati ne bi prizadeli družbe, je bilo tudi vodilo tekmovanja $500k Pandemic Response Challenge, v organizaciji fundacije XPRIZE in 3 NEFARMACEVTSKI UKREPI podjetja Cognizant, ki je bilo organizirano konec leta 2020. Na V okviru tekmovanja so ekipe dobile predpisan seznam NPI, tekmovanje se je prijavila tudi ekipa JSI vs COVID, ki prihaja iz ki so ga uporabile za gradnjo preskriptorja, hkrati pa so za vsak Odseka za inteligentne sisteme IJS, in na koncu osvojila drugo ukrep dobile tudi »ceno« uveljavljanja tega ukrepa. Seznam je mesto. V pričujočem prispevku najprej predstavimo tekmovanje, vseboval sledeče NPI: nato skiciramo rešitev, ki jo je razvila ekipa JSI vs COVID, na 1. Zapiranje šol koncu pa orišemo nadaljnje raziskave, ki so potekale v povezavi 2. Omejitev prihoda na delo z Ministrstvom za zdravje Republike Slovenije. Opisana je tudi 3. Preklic javnih dogodkov ponudba evropskim ministrstvom za zdravje za brezplačno 4. Omejitve zbiranja uporabo sistema JSI vs COVID. 5. Omejitev javnega prometa 6. Omejitev izhodov od doma 7. Omejitve gibanja po državi 2 TEKMOVANJE PANDEMIC RESPONSE 8. Omejitve gibanja med državami CHALLENGE 9. Kampanja osveščanja javnosti Tekmovanje $500k Pandemic Response Challenge [2] je 10. Strategija testiranja potekalo med oktobrom 2020 (registracija udeležencev) in 11. Sledenje stikov februarjem 2021 (razglasitev zmagovalcev). Naloga, ki so jo 12. Uporaba zaščitnih mask dobili udeleženci, je bila razviti modele, ki bodo po eni strani čim Ukrepi so se lahko izvajali v strožji ali v milejši obliki. Ukrep natančneje predvideli lokalne izbruhe okužb (»prediktor«), po »Omejitve gibanje po državi« v strožji različici tako prepove drugi strani pa predlagati čim učinkovitejši načrt ukrepov, tako gibanje izven določenega območja, v milejši pa ga samo da se hkrati minimizira število okužb ter ekonomsko škodo odsvetuje, »Omejitve zbiranja« pa z naraščanjem strogosti (»preskriptor«). Beseda ukrepi se v tem primeru nanaša na zmanjšuje število ljudi, ki se lahko zbira. Seveda se je pri ukrepih nefarmacevtske ukrepe (angleško non-pharmaceutical potrebno zavedati, da se jih ljudje lahko držijo ali ne, in od interventions, NPI), ki jih nekoliko podrobneje opišemo v posamezne države je odvisno, kako strogo bo preverjala nadaljevanju. Število sodelujočih ekip je bilo omejeno na 200. spoštovanje ukrepov – pa tudi od tega, kako so ukrepi V prvi fazi tekmovanja so se ekipe osredotočile na analizo predstavljeni javnosti in kako jih ljudje sprejmejo. obstoječih podatkov in strategij boja proti pandemiji v različnih državah. Cilj je bil razviti in ovrednotiti napovedne modele za razvoj pandemije. Pri tem so imele ekipe na razpolago zbirko 4 MODELI podatkov o pandemiji za vrsto držav z Univerze v Oxfordu Modeli prediktorjev in preskriptorjev so oz. bodo podrobneje (Oxford COVID-19 Government Response Tracker (OxCGRT) opisani v konferenčnem prispevku [6] in v prihajajočih [3]), vključno z ukrepi, ki so bili v državah veljavni v različnih publikacijah, zato tu le skiciramo rešitve. obdobjih, ter vzorce temeljnih prediktorjev in preskriptorjev podjetja Cognizant, Evolutionary AI™. 4.1 Prediktor Prediktorji, ki so jih ekipe razvile, so se nato uporabljali za Cilj prediktorja je napovedati število okužb na določenem napovedovanje, napovedi pa so se primerjale z razvojem območju (v državi ali v regiji) za vsak dan, za obdobje več pandemije v realnem svetu. Ta primerjava je bila osnova za mesecev v prihodnost. Pri tem upoštevamo seznam NPI, ki so v uvrstitev v prvi fazi. Pomembno je poudariti, da so vse ekipe državi v danem trenutku v veljavi. dobile na voljo natanko iste podatke in bile ocenjevane po enakih Prediktor uporablja standardni epidemiološki model SEIR, kriterijih. kjer upoštevamo dinamiko med skupinami posameznikov, ki so Prva faza tekmovanja se je zaključila januarja 2021 z Susceptible (dovzetni), Exposed (izpostavljeni), Infected merjenjem dejanskih infekcij. V drugo fazo se je uvrstilo 48 (okuženi) in Removed (ozdraveli ali umrli, se pravi niso več najbolje uvrščenih ekip, ki so prihajale iz 17 držav. V drugi fazi dovzetni za okužbo). Model SEIR [7] je sestavljen iz sklopljenih tekmovanja je bil cilj razvoj preskriptorjev. V tem delu seveda ni diferencialnih enačb (1), kjer uporabljamo parametre, ki določajo bilo mogoče testirati v praksi, zato je testiranje potekalo na verjetnosti za prehode iz ene skupine v drugo: 𝑆 → 𝛽 → 𝐸 → sledeči način: za predikcije se je uporabljal »standardni 𝜎 → 𝐼 → 𝛾 → 𝑅. prediktor«, ki so ga razvili organizatorji [4]. Vsaka ekipa je predlagala do deset strategij intervencije za vsako državo. Pri 𝑑𝑆 𝛽𝑆𝐼 ocenjevanju se je upoštevalo, da je ena strategija od druge boljša, = − 𝑑𝑇 𝑁 če je boljša po enem kriteriju, ne pa hkrati tudi slabša po drugem (kriterija sta tu omejevanje širjenja okužb in cena ukrepov). 𝑑𝐸 𝛽𝑆𝐼 = − 𝜎𝐸 (1) Druga faza se je končala marca 2021, ko so bili razglašeni 𝑑𝑡 𝑁 zmagovalci [5]. Prvo mesto je osvojila španska ekipa 𝑑𝐼 VALENCIA IA4COVID19 iz Valencie, drugo mesto pa = 𝜎𝐸 − 𝛾𝐼 𝑑𝑡 slovenska ekipa JSI vs COVID z zelo podobnim numeričnim rezultatom. Ekipi sta si enakovredno razdelili nagradni sklad pol 243 Napovedovanje trendov in optimiziranje ukrepov v boju proti Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia pandemiji COVID-19: Tekmovanje XPRIZE in naslednji koraki 𝑑𝑅 posamezno oceno potreboval približno 2 s. Z uporabo slednjega = 𝛾𝐼 𝑑𝑡 bi tako lahko ocenili le približno 45 planov, kar ne zadostuje za Pri tem velja zveza 𝑆 + 𝐸 + 𝐼 + 𝑅 = 𝑁 (vsi posamezniki). algoritem tipa NSGA-II. Natančneje, uporabili smo dva Parametre smo določili na sledeč način: 𝛽 (merilo za prenos) je nadomestna modela, enega na osnovi SEIR prediktorja (Sekcija bil določen s prilagajanjem modela na realne podatke o okužbah. 4.1) in enega na osnovi prekalkuliranih planov za različne poteke Z metodami strojnega učenja smo zgradili modele, ki se naučijo pandemije. Slednji deluje tako, da za dano regijo in čas najprej napovedovati ta parameter glede na nabor ukrepov. Pri tem smo ocenimo potek pandemije in nato predpišemo plane, ki se za dani upoštevali dejstvo, da posamezne države/regije uporabljajo potek najbolje odnesejo. Med vsemi kompromisnimi rešitvami, različen nabor NPI in da v posameznih obdobjih število okužb ki jih dobimo tako s prvim kot drugim nadomestnim modelom, narašča ali pada. 𝛽 je bil zato prilagojen za posamezno situacijo. izberemo 10 takih, ki najbolje pokrijejo množico vseh Parametra »optimalnih« kompromisov. Tipičen primer kompromisnih 𝜎 (inkubacijska doba) in 𝛾 (merilo za okrevanje) smo določili na podlagi podatkov iz literature. rešitev v obliki fronte najdemo na Sliki 2. Prediktor, ki smo ga zgradili z naborom različnih vrednosti 𝛽, se tako lahko prilagaja ukrepom, ki jih posamezne države uvajajo v različnih trenutkih. Prediktor deluje s časovno ločljivostjo enega dneva. Slika 1 prikazuje primer napovedi prediktorja v primerjavi z realnimi podatki. Slika 2: Primer desetih kompromisnih rešitev v obliki fronte, dobljenih z metodo iz tekmovanja. 5 SODELOVANJE Z MINISTRSTVOM ZA ZDRAVJE RS Slika 1: Primer dnevnega števila novih okužb za Italijo V okviru delovanja zadnjega avtorja kot državnega svetnika za jeseni 2020. Modra črta predstavlja napoved, črtkana rdeča črta pa število potrjenih primerov. S sivo je označen raziskovalno dejavnost je bil dne 28. 6. 2021 izveden posvet v Državnem svetu na temo uporabe programskih metod za krotenje interval za vhodne podatke. epidemije z naslovom: »Problemi COVID-19 in iskanje optimalnih rešitev za naprej«. Na komisijah DS in na 4.2 Preskriptor plenarnem zasedanju je bila pogosta debata na temo COVID-19, Cilj preskriptorja je izdelati plane intervencij (NPI) za kjer je avtor prispeval s strokovnimi analizami in napovedmi, dal posamezno obdobje za posamezno državo ali regijo. Pri tem je tudi nekaj pobud vladi v smeri najboljšega delovanja. Nekatere želimo predpisati plane, ki predstavljajo dobre kompromise med izmed teh zamisli so bile uresničene, druge ne. omejevanjem širjenja okužb in ekonomsko in družbeno ceno teh Ministrstvo za zdravje RS je poleg tega naročilo nekaj študij. ukrepov. Dodatna zahteva pri tekmovanju je bila časovna Del teh študij je prikazan v Vito Janko itd. »What-If Analysis of omejitev za izdelavo načrta, namreč, v šestih urah je bilo treba Countermeasures Against COVID-19 in November 2020 in izdelati načrte za 235 regij, kar predstavlja v povprečju 90 s na Slovenia« v zborniku konference Informacijska družba 2021. regijo. Tam je pokazano, da je v fazi velike rasti smotrno vpeljati ukrepa Preskripcijo planov lahko naravno predstavimo kot tako zapiranja šol kot nošenja mask. Za november 2020 so večkriterijski optimizacijski problem, kjer želimo minimizirati analize celo pokazale, da se zapiranju šol ne da povsem izogniti, dva konfliktna si kriterija: (1) povprečno število infekcij in (2) pa četudi uporabimo vrsto drugih ukrepov, če želimo ustaviti ekonomska in družbena cena ukrepov. Za potrebe optimizacije rast. Ukrep nošenja mask se glede na naš model izkaže enako smo uporabili dobro poznan genetski algoritem z nedominiranim učinkovit kot kombinacija bolj restriktivnih ukrepov, vendar je sortiranjem II (ang. nondominated sorting genetic algorithm II – predvidoma do posameznikov bolj prijazen. Družbenih cen NSGA-II) [11]. posameznih ukrepov v boju proti pandemiji v tej fazi nismo Zaradi stroge časovne omejitve (90 s na regijo), smo za oceno upoštevali, spada pa to med področja, ki jih bomo obravnavali v kakovosti planov standardni prediktor nadomestili z prihodnje. nadomestnimi modeli. Standardni prediktor je namreč za 244 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia M. Luštrek et al. 6 SODELOVANJE Z EVROPSKIMI programov, kot na primer razvitih na tekmovanju XPRIZE, MINISTRSTVI omogočila bistveno boljše rezultate. Rezultate smo delili s slovenskim in z evropskimi ministrstvi za zdravje. Julija 2021 smo vsem ministrstvom EU poslali pismo, kjer jim dajemo možnost neposredne uporabe programa XPRIZE JSI, ZAHVALA specializiranega za njihovo državo. Vsaka država torej lahko uporablja z geslom zaščiteno verzijo programa. Poslali smo jim Raziskave so bile financirane s strani ARRS, v sklopu tudi navodila, kako uporabljati programe in na kakšen način jim programske skupine P2-0209. nudimo podporo. Razvite rešitve so bile evropski in svetovni javnosti ponujene brezplačno. VIRI Nimamo podatkov, koliko EU ministrstev je aktivno [1] Derrick Bryson Taylor, A Timeline of the Coronavirus Pandemic, New uporabilo ali uporablja programe, a glede na odzive in glede na York Times, 17. marec 2021, dostopano 10. septembra 2021, https://www.nytimes.com/article/coronavirus-timeline.html to, da imamo kontakte le z nekaj ministrstvi, se zdi, da ne prav [2] Pandemic Response Challenge, dostopano 10. septembra 2021, veliko. https://www.xprize.org/challenge/pandemicresponse [3] T. Hale, N. Angrist, R. Goldszmidt, B. Kira, A. Petherick, T. Phillips, S. Webster, E. Cameron-Blake, L. Hallas, S. Majumdar and H. Tatlow, “A global panel database of pandemic policies (Oxford COVID-19 7 ZAKLJUČEK Government Response Tracker),” Nature Human Behaviour, p. 529–538, 2021. [4] R. Miikkulainen, O. Francon, E. Meyerson, X. Qiu, D. Sargent, E. Canzani V prispevku so pregledno opisane programske rešitve, ki jih je and B. Hodjat, “From Prediction to Prescription: Evolutionary Optimization of Nonpharmaceutical Interventions in the COVID-19 skupina Odseka za inteligentne sisteme razvila v okviru Pandemic,” IEEE Transactions on Evolutionary Computation, vol. 25, no. tekmovanja XPRIZE. Nekatere med njimi so bile v celoti izvirne 2, pp. 386-401, 2021. in so prispevale k drugem mestu na svetovnem prvenstvu na to [5] Announcing the Grand Prize Winners, XPRIZE, 10. marec 2021, temo. dostopano 10. septembra 2021, https://www.xprize.org/challenge/pandemicresponse/articles/pandemic- Po tekmovanju smo razvili vrsto dodatnih rešitev. Eno smo response-challenge-winners uporabili za iskanje ukrepov retroaktivno – ali in v kolikšni meri [6] Nina Reščič et al. Finding efficient intervention plans against Covid-19, je bil kak ukrep upravičen. Ena taka študija je zajemala obdobje presented at ETAI 2021. [7] Model SEIR, dostopano 10. septembra 2021, novembra 2020 v Sloveniji. V večini študij se je pokazalo, da so https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology# bili človeški ukrepi daleč od optimalnega in bi uporaba The_SEIR_model 245 246 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek E Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume E 14. mednarodna konferenca o prenosu tehnologij 14th International Technology Transfer Conference Urednika / Editors Špela Stres, Robert Blatnik http://ittc.ijs.si 7. oktober 2021 / 7 October 2021 Ljubljana, Slovenia 247 248 PREDGOVOR / FOREWORD Spoštovani državni sekretar prof. dr. Mitja Slavinec, spoštovani državni sekretar gospod Simon Zajc, spoštovani najvišji predstavniki javnih raziskovanih organizacij, spoštovani udeleženci, lepo pozdravljeni in dobrodošli na 14. 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, innovators and representatives from governmental institutions and policy-making organizations. Najlepše se zahvaljujemo soorganizatorjem, spin-out partnerjem, programskim partnerjem, promocijskim partnerjem, ter partnerjem, ki so podprli dvostranske sestanke med podjetji in raziskovalci. Za podporo se zahvaljujemo tudi Ministrstvu za izobraževanje, znanost in šport in Slovenskemu podjetniškemu skladu. Začetni del konference, pozdravni nagovori in okrogla miza bodo potekali v slovenščini, nadaljevali pa bomo v angleščini. The event, except the pitching section, is being recorded and will be made public in the next days. The welcome addresses and the round table will be held in Slovenian, later sections will be in English. Po pozdravnih nagovorih bomo začeli z okroglo mizo o prihodnosti prenosa tehnologij v Sloveniji in Evropi s častnimi gosti. Spremljali bomo tekmovanje raziskovalno-podjetniških ekip, ki se potegujejo za naziv najboljše inovacijo iz javnih raziskovanih organizacij, nato razglasitev nagrade Svetovne organizacije za intelektualno lastnino WIPO IP Enterprise Trophy. Vzporedno se bodo odvijali vnaprej dogovorjeni posamični sestanki med raziskovalci in podjetji. Osrednjo temo konference, premagovanje izzivov financiranja v t.i. dolini smrti, nam bosta predstavila spoštovana gosta: Matthias Keckl, managing partner sklada Fraunhofer Technologie-Transfer in Natalija Stošicki, direktorica Oddelka za naložbe in evropske programme, SID banka. Nato bodo uveljavljeni strokovnjaki iz Slovenije in tujine predstavili znanstvene prispevke o prenosu tehnologij in intelektualni lastnini ter izbrane raziskovalne projekte. Vzporedno bo izvedena še sekcija za šole, pred zaključkom konference pa bomo razglasili tudi prejemnika nagrade WIPO Medal for Inventors. Program je, kot vidite, res bogat, saj se dotika množice aktivnosti, pri katerih smo v pisarnah za prenos tehnologij osrednjega pomena. Organizacijski odbor 14.ITTC / Organizing Committee of the 14.ITTC 249 ORGANIZACIJSKI ODBOR, PARTNERJI IN SPONZORJI / ORGANIZING COMMITTE, PARTNERS AND FINANCERS The main organizer of the 14th 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 The scientiffic 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 The 14th ITTC Conference is organized in collaboration with the International multiconference Information Society (IS2021). 250 The 14th ITTC Co-organizers are: Slovenian Intellectual Property Office (SIPO) World Intellectual Property Organization (WIPO) Faculty of Information Studies Novo mesto The 14th ITTC Programme partners are: Fraunhofer Technologie-Transfer Fonds Slovenian association of technology transfer professionals (SI-TT) The 14th ITTC Spin-out partners are: Slovene Enterprise Fund 251 SID Bank (SID – Slovenska izvozna in razvojna banka) The 14th ITTC Research-to-Business meetings partners are: SRIP - Smart Cities and Communities partnership The Research-to-business meetings at the 14th ITTC Conference were co-organized in collaboration with the Enterprise Europe Network partners: Innovation Center of the Faculty of Mechanical Engineering in Belgrade Fundació Universitat-Empresa de les Illes Balears (FUEIB) MIR Foundation Development agency of the Republic of Srpska 252 Area Science Park Business Incubator Novi Sad The Netherlands Chamber of Commerce KVK KOSGEB Ankara Ostim (Small and Medium Enterprises Development Organization EU and Foreign Relations Department) The 14th ITTC Associated partners are: University of Ljubljana National Institute of Biology National Institute of Chemistry 253 University of Maribor Agricultural Institute of Slovenia University of Primorska The 14th ITTC Promotion partners: University of Belgrade GIS – Transfer Center Foundation Scientific Research Centre Bistra Ptuj Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins (CIPKeBiP) 254 Development Centre Novo mesto SAŠA inkubator SIS EGIZ SRIP Health – Medicine SRIP hrana Podjetniški inkubator Vrelec RDA Koroška - Regional Development Agency for Koroška University Industry Collaboration Centers Platforms of Turkey 255 Razvojno informacijski center Bela krajina 256 The Conference is co-financed by: Consortium for Technology Transfer Enterprise Europe Network R2B meetings are organized and co-financed in the frame of the Enterprise Europe Network (contract number 880148). Slovene Enterprise Fund The event is co-financed by the Slovenian Enterprise Fund and the European Union, namely from the European Regional Development Fund. It is implemented on the basis of the program "Substantive support of recipients of funds (SMEs) in the period from 2018 to 2023", within the Operational Program for the Implementation of European Cohesion Policy in the period 2014-2020. 257 ACKNOWLEDGEMENTS The editors and organizing committee of the Conference would like to express cordial thanks to all who helped make the 14th 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: Dr. Jon Wulff Petersen from Plougmann Vingtoft Matthias Keckl from Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič from Slovene Enterprise Fund Gregor Klemenčič from Deep Innovations for their evaluation of written technology commercialization proposals and selection of winning teams, authors of inventive technologies with the best potential for commercialization of the technologies, developed at Public Research Organizations. We are particularly grateful to the members of the EVALUATION COMMISSION: Alojz Barlič from Slovenian Intellectual Property Office (SIPO) Matthias Keckl from Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič from Slovene Enterprise Fund, for their evaluation and selection of the awardees of the WIPO IP ENTERPRISE TROPHY and WIPO MEDAL FOR INVENTORS 258 Technology Transfer Fund - Central Eastern European Technology Transfer (CEETT) platform Marijan Leban Špela Stres Center for Technology Transfer and Innovation Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana Jamova cesta 39, Ljubljana Marijan.Leban@ijs.si Spela.Stres@ijs.si ABSTRACT Venture Capital (VC) is usually available to start-ups or other This article describes the importance of technology transfer young companies that show potential for long-term growth. funds in financing the transition of discoveries from the laboratory to the market, which is called bridging the commercialization gap or the “valley of death”. Presented is the newly established Central Eastern European Technology Transfer (CEETT) platform, the first multinational technology transfer investment platform ever introduced in the European Union, as well as its importance and expectations in the protection of intellectual property and technology transfer from public research organizations (PROs) to industry in Slovenia and Croatia. KEYWORDS Technology transfer, venture capital, proof of concept, technology transfer fund, commercialization gap, valley of death, Central Eastern European Technology Transfer platform, CEETT Figure 1: Commercialization gap [4]. 1 INTRODUCTION On the other hand, there is a lack of funding to develop laboratory Much of what is used today was born in a laboratory — but how discoveries to prototypes suitable for the market because this step did it develop from research to a product that can be bought? is risky for investors. Between the laboratory and the market is a Technology Transfer (TT) funds commercialise promising commercialization gap (Figure 1) that has to be bridged to research, allowing it make that crucial step from the prototype successfully put the discovery on the market as a product or world into the commercial space. Technology transfer (TT) can service. be broadly defined as the process of converting scientific findings from research organisations into useful products by the commercial sector [1]. TT is also known as “knowledge transfer or knowledge sharing” [1], the process whereby an enterprise converts scientific findings from research laboratories and universities into products and services in the marketplace [1]. This understanding is adopted for the purposes of the present article. The transformation of scientific findings into products can take place through a number of means, in particular through the collaboration between research organisations and industry, the licensing of intellectual property rights, the creation of start- up businesses or university spin-out companies. Although Technology Transfer seed investments in Europe are in the radar of some investors, academic research is often considered to be 'too new' or 'too high-risk' to be transferred out Figure 2: Technology readiness levels and the “valley of of the research laboratory and financed by the traditional death” [5]. investors [2]. New discoveries and technologies may not realize their potential unless they become attractive to industry or The journey of new technology from research to downstream investors, so the aim of the European Investment commercialization goes through a number of technology Fund (EIF) [3] is to play an important role. readiness levels (TRLs). The latest version of the scale from 259 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Leban et al. NASA includes nine TRLs and has gained widespread Investment Fund (EIF) [3] remains a crucial player, often taking acceptance across governments, academia, and industry. The the role as lead investor. The EIF is a specialist provider of risk European Commission adopted this scale in its Horizon 2020 finance to benefit small and medium-sized enterprises (SME) program. across Europe. It is part of the EIB Group. EIF’s shareholders are the European Investment Bank (EIB), the European Union, Academia tends to focus on TRLs 1–4, whereas industry prefers represented by the European Commission, and a wide range to work with TRLs 7–9, rarely 6. Therefore, TRLs 4–6 represent of public and private banks and financial institutions. EIF carries a gap between academic research and industrial out its activities using either its own resources or those provided commercialization. This gap, show in Figure 1 as the commercialization gap, is colloquially referred to as the by the European Investment Bank, the European Commission, technological “valley of death” (Figure 2) to emphasize that by EU Member States or other third parties. By developing and many new technologies reach TRLs 4–6 and die there. offering targeted financial products to EIF’s intermediaries, such as banks, guarantee and leasing companies, micro-credit 2 TECHNOLOGY TRANSFER FUNDS providers and private equity funds, EIF enhances SMEs access Venture capital (VC) funds are pooled investment funds that to finance. manage the money of investors who seek private equity stakes in EIF also seeks to support financially sustainable Technology startups and small- to medium-sized enterprises with strong growth potential. These investments are generally characterized Transfer structures or funds. These intermediaries typically as very high-risk/high-return opportunities. Although invest into projects or start-up companies, at proof of concept investments of VC funds in start-ups are risky, investments in (PoC), pre-seed, seed, post-seed to A & B rounds, where the development of technology between TRL4 and TRL 6 are even companies can be financed further by the normal Venture capital more risky. As a result, VC funds with private equity / Private equity investor. The EIF have become one of the main participation do not typically invest in bridging the “valley of European investors providing guidance and cornerstone funding death”. So, special technology transfer funds are needed to to players in this emerging market segment. Between 2006 and financially support the development of discoveries from TRL 4 2018 the EIF alone invested an amount of about EUR 1.7 billion to TRL6. in 38 TT funds throughout Europe [6]. While the market is more advanced in the Nordic countries and Western Europe, two TT Technology transfer still remains a rather political investment funds have recently been established in Germany in cooperation field, but one that offers economic opportunities with a growing with the Fraunhofer Society and the Max Planck Foundation, potential for commercialization. Even though private investors respectively. The number of TT funds funded by the EIF [3] become more and more interested in this field, the European between 2006 and 2020 is shown in Table 1. There are very few other TT funds in Europe not funded by the EIF (if any). Table 1: Technology Transfer (TT) Funds funded by the EIF by country and year of start of funding. 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 sum France 1 1 3 3 1 2 1 12 United Kingdom 1 1 1 2 1 7 Italy 1 2 1 2 6 Belgium 1 1 1 1 1 5 Netherlands 1 1 1 3 Turkey 2 3 Germany 2 3 Sweden 1 1 2 Norway 1 1 2 Portugal 1 1 Spain 1 1 Ireland 1 1 Finland 1 1 Switzerland 1 1 In terms of best practices, the most relevant somehow are IP team/first time funds, and both good examples of how a fund Venture [7] in UK and CD3 [8] in Belgium. Another very should collaborate with the research institutes). interesting is Innovation Industries [9] in Netherlands. Of the Italian ones that the EIF funded through ITAtech [10], each is 3 CENTRAL EASTERN EUROPEAN quite interesting, especially because they have been funded through a similar initiative (and the only one such initiative at the TECHNOLOGY TRANSFER (CEETT) moment). Particularly interesting would be Sofinnova Telethon PLATFORM [11] (Sofinnova is one of the most important VC firm in Europe, In July 2021, the European Investment Fund (EIF), part of the and the strategy is focused on rare and genetic diseases), or European Investment Bank Group, the Slovenia’s national Progress Tech Transfer [12] and Eureka [13] (both first time promoter bank, SID Banka, and the Croatian Bank for Reconstruction and Development (HBOR) signed an agreement 260 Technology Transfer Fund - Central Eastern European Information Society 2021, 7 October 2021, Ljubljana, Slovenia Technology Transfer (CEETT) platform Coloured columns show countries’ performance in 2019, usin g the most recent data for 27 indicators, relative to that of the EU in 2012. The horizontal hyphens show performance in 2018, u sing the next most recent data, relative to that of the EU in 2012. Grey columns show countries’ performance relative to that of the EU 2012. For al years, the same measurement methodology has been used. The dashed lines show the threshold values between the performance groups. Figure 3: Slovenia's innovation performance fell in 2012/18 (source EIS [17]). on establishing a regional technology transfer platform, Central technology transfer office (TTO) in Slovenia at public research Eastern European Technology Transfer - CEETT platform [14], organizations (PRO or JRO in Slovene). In January 2015, Dr from research institutions to the economy, amounting to at least Špela Stres, the head of the CTT, was invited to an “ad-hoc 40 million euros. The scope of the EIF’s SEGIP (Slovene Equity meeting on the design of the EC's pilot Technology Transfer Growth Investment Programme) and CROGIP (Croatian Growth Financial Facility (TTFF)". As the only representative from the Investment Programme) mandates has been expanded to include EU13 countries, together with 14 colleagues from more the support for business applications of Slovene and Croatian innovative and open environments in Western Europe, she academic research via a commitment to a technology transfer participated in the final stages of creating the Technology fund operating in the two countries. The resulting joint initiative Transfer Financial Facility pilot, from which Invest EU later is the first investment programme under the Central and Eastern grew and the participation of the European Investment Fund with European Technology Transfer (CEETT) initiative, to which SID various actors in Europe in the creation of the Proof of concept Banka contributed an additional EUR 10 million to SEGIP, (PoC) funds. They all shared the opinion that the European HBOR contributed additional EUR 10m to CROGIP and the EIF Commission's initiative to finance the technology transfer of made further EUR 20 million available for investment. Thus, the research results from universities and other public research total available funding amount indicatively represents EUR 40 organizations to the economy and society is crucial for the million. development of processes linking excellent and prioritized science and knowledge transfer to the economy and society. The CEETT will invest in venture capital funds and finance innovative technological research projects and the protection of 3.1.1 Why is such a Proof of Concept (PoC) Fund measure the intellectual property of universities and research institutes in urgently needed? Slovenia and Croatia. It will also fund the commercialisation of The strong European, Slovenian and Croatian research success is scientific achievements and research projects. currently not translated into innovation due to the lack of breakthrough innovations that create new markets. Two financial This is the first multinational investment platform for technology gaps (2 “valleys of death”) prevent innovations: transfer ever launched in the European Union. The EIF estimates 1) The transition from laboratory to enterprise and that the universities and research institutes in Slovenia and 2) Scale-up (growth) for high-risk innovative start-ups. Croatia targeted by the platform will generate more than 350 patent applications and 100 spin-off companies in the next five In addition, many national and local ecosystems have been years [15]. established, but they are fragmented and unconnected. In addition, not all PROs (JROs in Slovene) and all talents Investment in innovation and technology transfer will be key to (especially not women and young people) are systematically the long-term sustainable green economy, job creation and global involved in innovation processes. It is at least partly due to such competitiveness of the European Union. a situation that e.g. Slovenia's innovation performance decreased in the period 2012–2018 (Figure 3). Slovenia fell 6 places (for an 3.1 Benefits of the platform from the point of extra place in 2019) and went from strong innovators to moderate view of the research organization followers. The trend shows an even more worrying picture, as Slovenia is only slightly below average in terms of results, but The Center for Technology Transfer and Innovation (CTT) at the with the most negative trend of all EU28 countries (Figure 4). Jožef Stefan [16] is the largest and the most experienced 261 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Leban et al. Figure 4: Performance and trend of EU members in the field of innovation – Slovenia is slightly below average with the most negative trend (source EIS [17]). Meanwhile, Croatia is positioned slightly worse than Slovenia, growing companies, European, Slovenian, Croatian gazelles, is but its development innovation trend is average compared to the absolutely necessary. EU28. 3.1.2 What are the benefits of the Proof of concept (PoC) fund In the case of Slovenia, therefore, it is not so much a matter of for a research organization? deteriorating the absolute situation as of not improving it. The The easiest way to answer is the Jožef Stefan Institute’s (JSI) main issue of Slovenia lies in its diminishing innovation capacity example. Today, there are over forty companies operating from 2021-2019, where Slovenia’s position has dropped from directly based on JSI technology and knowledge. As early as Strong innovators to Moderate innovators (source: European 2010, the JSI adopted detailed procedures that prevent conflicts Innovation Scoreboard [17]). Even though the public R&D of interest and encourage researchers on their entrepreneurial expenditure remains at the EU average, the Slovenian scientists path. JSI has had an internal PoC fund for more than 20 years, overproduce with 155 % in number and 105% in highly cited the and the fund is not financed from the budget, but exclusively EU average. On the other hand, the product/process innovation from royalties. However, there are certainly many more and the number of SMEs innovating in house is at 80% of the EU examples that could / should be supported on their way to the average, IPR, in particular patenting issues place Slovenia at 93 market than can be financially supported by public research % of the EU average, which all results in the sales of new market organizations themselves. At JSI alone, around 30 technology and firm products at 84% of the EU average. The main solution offers have been identified that are currently waiting for a clear for this issue is to push for scientific knowledge, created and interest from the economy, or to be internally developed with the collected at the Public Research Organizations (PROs), to be help of the PoC fund to the extent that they can be marketed used in the national economy and increase its competitiveness. It independently. There are even more such offers of research is expected that the CEETT platform will play a very important results at all four universities and public faculties, as well as 17 role in reversing the negative innovation trend into a positive one. public research institutes in Slovenia and all public research institutions in Croatia. Therefore, following the example of 48 However, the funding gap for scaling up highly innovative similar European funds established in previous years, intended startups and SMEs in significant, as US venture capital specifically for cases from public research organizations, a multi- investments in the period from 2016-2020 were 4-5 times higher million PoC fund, which will be established by SID Bank than in the EU (source: Invest EU, Pitchbook) and the number together with HBOR and the European Investment Fund (EIF), and market value of “unicorn” companies (those valued at over is urgently needed. 1 EUR billion) in Europe (according to CB Insights [18] in It is crucial that a significant share of funding will also go to the January 2021) is 3-4 times smaller than in North America and pre-incorporated phase, ie projects that are still within the PROs Asia. And Slovenia lags behind Europe. There are not as many and are preparing to spin off into new start-ups. And it is this risk, spin-outs in Europe and in Slovenia as there are in the USA or the investment in the pre-incorporated phase of bridging the Asia, neither per capita nor per researcher, because there is no valley of death, that is key to the successful transfer of career path that would enable a return to the PRO, because there knowledge from public research organizations into practice and is no PoC fund and because in Slovenia failure is punished with separates it from other instruments available. ridicule and do not reward with a smile [19]. Therefore, the establishment of interconnected, integrated instruments that enable the growth of technology and researchers with it, in fast- 262 Technology Transfer Fund - Central Eastern European Information Society 2021, 7 October 2021, Ljubljana, Slovenia Technology Transfer (CEETT) platform 3.1.3 What are the direct benefits of the new fund for research time, development will raise the quality of life in the conditions organizations? of a rapidly aging society based on digitalisation and in the face The new platform will also offer funding in the early stages of of intensified climate change. TRL development, which will enable a smooth transition of projects from the research environment to the market. Funding 4 CONCLUSIONS will be open to all innovators in any priority area. The platform will act as a path finder for advanced research into new Establishment of a regional technology transfer platform, technologies and enable the growth of TRL, which is essential Central Eastern European Technology Transfer - CEETT for the transition from the laboratory to the commercial platform, the first multinational investment platform for environment. The platform will also provide access to business technology transfer ever launched in the European Union, promotion services (coaches, mentors, companies, investors and intended for Slovenia and Croatia, is a great opportunity for knowledge partners). It will further enable the development of a technology transfer from public research organization to vision for breakthrough, portfolio management and integration industry in both countries. The established technology transfer with ecosystems, and crowd-sourcing of other investors. The fund will enable the public research organizations to bridge the PoC fund will give teams from public research organizations commercialization gap or the “valley of death” and to improve enough time to come up with technology according to market the successful rate of technology transfer from the academia to needs, to decide on their further research and business path, to industry. regulate intellectual property relationships, to establish The successful operation of CEETT will require an appropriate relationships that will reward both those who will remain manager with experience in the field of venture capital researchers at the parent organization and those who will also investments and cooperation between research organizations operate within new start-ups. and companies. In addition, he will have to be aware of the specifics of Central Europe region, especially Slovenia and 3.1.4 Could public research organizations cope without the Croatia, as well as the specifics of public research Proof of Concept (PoC) fund? organizations in both countries. In 2015 it was and still is the opinion that there is enough money. That there is certainly no shortage of money to move from ACKNOWLEDGMENTS research to the economy. This is partly true. It really isn’t just money that is lacking and really the most proactive and skillful Special thanks for the establishment of the CEETT platform go can find money in any country, in any situation, despite all to the entire team of SID Bank for perseverance and, above all, obstacles, as long as they are persistent enough. This is called tireless proactivity in establishing the fund. Thanks also go to entrepreneurship. As Professor Howard Stevenson, the godfather colleagues Dr Tony Raven of the University of Cambridge, Paul of the study of entrepreneurship at Harward Business School, put Van Dunn from the Catholic University of Leuven, colleagues it, entrepreneurship is the pursuit of opportunity beyond from the Technical University of Copenhagen, colleagues from resources controlled. Entrepreneurs need to show significant the Fraunhofer Institute in Frankfurt and many others, without progress in raising funds, and time alone is consuming available whom Slovenian investment in the establishment of the system funding. would not be possible. But the goal of society that funds research and development through gross domestic product is not just to fund excellent REFERENCES inventions and then place them at the start of a mountain trail that [1] J. Darcy, H. Kraemer-Eis, O. Debande, D. Guellec, Financing gets lost between rocks and impassable overhangs leading to the technology transfer, Working Paper 2009/002, EIF Research & Market market. The aim of society is by no means to place as high an Analysis, Available from: https://www.eif.org/news_centre/publications/eif_wp_2009_002_financi obstacle as possible to the transfer to the economy and ng-tt_fv.pdf (visited August 27, 2021). entrepreneurship, obstacles that can only be overcome by the [2] Technology Transfer : Converting Research into Products for the Market, Available from: naturally most talented and most stupidly persistent. The goal of https://www.eif.org/what_we_do/equity/technology_transfer/index.htm the society is sensible and proactive management of innovations (visited August 27, 2021). [3] EIF – European Investment Fund, Available from: arising from the research system in such a way that as many https://www.eif.org/index.htm (visited August 25, 2021). useful inventions find their way to the market (instead of just in [4] PRIs in Technology Transfer, Available from: the drawers of public research organizations). The goal is for as https://www.vennfoundation.org/tech-transfer (visited August 26, 2021). [5] Alessandro Rossini, Bridging the technological “valley of death”, many innovations as possible to find their niche in the market, Available from: https://blogg.pwc.no/digital-transformasjon/bridging- the goal is to establish a clear, transparent path, a motorway that the-technological-valley-of-death (visited August 25, 2021). [6] Technology Transfer Funds – Bridging the Gap between Science and is easily followed by those who want it, and others who would Business, Available from: https://www.pe-magazin.com/technology- like to remain in the safe haven of publicly funded research can transfer-funds-bridging-the-gap-between-science-and-business/ (visited stay there. continue to contribute constructively. Smooth paths to August 25, 2021). [7] IP Venture Fund, Available from: https://www.ipgroupplc.com/about- the market are necessary for the renewal and progress of society us/business-model/ip-capital/ip-venture-fund (visited August 25, 2021). in a double transition and as a basis for a decisive breakthrough [8] Centre for Drug Design for Design and Discovery (CD3), Available from: https://www.cd3.be/ (visited August 26, 2021). of Slovenia and Croatia between competitive and research-based [9] Innovation Industries, Available from: society with sustainable development, which will catch up with https://www.innovationindustries.com/ (visited August 26, 2021). [10] the most productive and competitive countries in the world. life The ITAtech Platform, Available from: https://www.cdp.it/sitointernet/page/en/the_itatech_platform?contentId= in the conditions of a rapidly aging society based on digitalisation PRD4974 (visited August 26, 2021). and in the conditions of aggravated climate change. At the same [11] Telethon, Available from: https://www.telethon.it/en/ (visited August 26, 2021). 263 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Leban et al. [12] Progress Tech Transfer, Available from: https://www.progressttfund.it/ hbor-launch-new-40-million-euros-investment-support-innovation- (visited August 25, 2021). scientific-research-protection-of-intellectual-property-slovenia- [13] Eureka! Fund I – Technology Transfer, Available from: croatia.htm (visited August 26, 2021). https://www.eurekaventure.it/funds/eureka-fund-i (visited August 25, [16] Center for Technology Transfer and Innovation at the Jožef Stefan, 2021). Available from: http://tehnologije.ijs.si/en/ (visited August 26, 2021). [14] Central Eastern European Technology Transfer – CEETT platform, [17] EIS - European innovation scoreboard, Available from: https://ec.europa.eu/growth/industry/policy/innovation/scoreboards_en. https://www.eif.org/what_we_do/resources/ceett/index.htm (visited [18] CB Insights, https://www.cbinsights.com/. August 26, 2021). [19] Špela Stres, Presentation of the benefits of the platform from the point of [15] EIF, SID Banka and HBOR launch a new €40 million investment view of the research institution, speech at the signing of the joint platform to support innovation, scientific research and the protection of agreement between EIF, SID Bank and HBOR on the establishment of intellectual property in Slovenia and Croatia, Available from: Central Eastern European Technology Transfer (CEETT) platform, https://www.eif.org/what_we_do/guarantees/news/2021/eif-sid-banka- Ljubljana 26 July 2021. 264 Software Protection and Licensing Challenges in Europe: An Overview Izzivi na področju zaščite in licenciranja programske opreme v Evropi: pregled stanja Urška Fric Špela Stres Robert Blatnik Knowledge and Technology Center for Technology Transfer Center for Technology Transfer Transfer Office and Innovation and Innovation Faculty of Information Studies in Jožef Stefan Institute Jožef Stefan Institute Novo mesto Jamova cesta 39 Jamova cesta 39 Ljubljanska cesta 31 A 1000 Ljubljana, Slovenia 1000 Ljubljana, Slovenia 8000 Novo mesto, Slovenia spela.stres@ijs.si robert.blatnik@ijs.si urska.fric@fis.unm.si ABSTRACT KLJUČNE BESEDE With the transition of innovation to the digital sphere, software Programska oprema, patenti, zaščita in izkoriščanje pravic intelektualne lastnine, izzivi, Evropa. has become an important part of contemporary inventions and creations and it is also an extremely important part of intellectual property – in Slovenia and in Europe. The software protection in 1 INTRODUCTION the European Union – that is, in Europe – not considered fully arranged. Computer scientists face a number of challenges when Computers are part of almost every area of contemporary life it comes to exploiting intellectual property rights in software. and they are becoming more advanced every day, with The field therefore offers many opportunities for further work. In increasingly small gadgets performing increasingly complicated this paper, we discuss software and focus mainly on the tasks. Consequently, the number of new inventions seeking challenges computer scientists face in protecting and licensing patent status in the field has been rising steadily. In fact, patent software in the European innovation arena. applications for computer-based inventions display one the highest growth rates across all patent categories arriving at the KEYWORDS European Patent Office (EPO). A thorough examination process Software, patents, protection and exploitation of intellectual awaits all new applications in this field. The crucial aim is to property rights, challenges, Europe. distinguish between legitimate technological innovations which contribute to the overall technological progress and straightforwardness and inventiveness of computer-implemented POVZETEK inventions. [1] S prehodom inovacij na digitalno področje je programska Over the last decade there has been an intense debate over oprema postala pomemben del sodobnih izumov in stvaritev, the extent to which software should be the subject to patent hkrati pa predstavlja izjemno pomemben del intelektualne protection as opposed to copyright protection for a program. lastnine – tako v slovenskem kot evropskem prostoru. Stanja na Different understanding applies to the US, Europe and the rest of področju zaščite programske opreme v Evropski uniji oz. v the world. Many companies in the software industry are Evropi s pravnega vidika še vedno ne moremo obravnavati kot apprehensive of the perceived difficulty of defining the scope for povsem dorečenega, prav tako pa se znanstveniki na področju software patent. Inappropriate scope definitions can result in računalništva soočajo s številnimi izzivi, ko gre za izkoriščanje legal proceedings involving large fees where plaintiffs have the pravic intelektualne lastine iz programske opreme. Področje zato advantage of patent ambiguity. Others feel equally strongly that narekuje številne priložnosti za nadaljnje delo. V prispevku the software industry needs strong software patents. [2] obravnavamo programsko opremo, pretežno pa se posvečamo Currently, software that does not demonstrate a technical izzivom, s katerimi se znanstveniki na področju računalništva contribution can only be protected by copyright, which does not soočajo pri zaščiti in licenciranju programske opreme v protect ideas. The appearance of a command line or graphical evropskem inovacijskem prostoru. interface can be protected as a registered design, whereas a patent for computer or mobile application can be granted if a technical ∗Article Title Footnote needs to be captured as Title Note contribution is demonstrated. Under EPO rules, if this criterium †Author Footnote to be captured as Author Note is fulfilled software must be connected to the hardware. [3] Part Permission to make digital or hard copies of part or all of this work for personal or of the reason for the lack of appropriate legal instrument is that classroom use is granted without fee provided that copies are not made or distributed such inventions are very specific and proving their technical 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 contribution and industrial applicability can be challenging. [3] be honored. For all other uses, contact the owner/author(s). In order for computer scientists to successfully market software, Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). the Public Research Organization (PRO) system needs to provide 265 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia U. Fric et al. the motivation and reward computer scientists for it. The present ownership of a newly developed technical solution or creation state of European innovation arena contains nothing to motivate that is autonomously created, enabled or co-created by a computer scientists in this respect. program. Methods of resolving the question without stifling The current situation calls for a study to identify the most critical innovation potential are subjects of intense debate and points in order to update some of the legal bases, to address this accelerated activity at the EPO [7]. area more clearly and to resolve the issue of rewarding computer scientists (described in this document with the focus on software), also in terms of Technology Transfer Office (TTOs) 3 SOFTWARE AND EXPLOITATION OF role. INTELLECTUAL PROPERTY RIGHTS 3.1 Software Licensing Process 2 SOFTWARE IN THEORY AND PRACTICE Intellectual property is an essential tool for protecting the The European Patent Convention stipulates in Article 52(2) value created by software. As a general rule, almost all software (c) that programs for computers are not regarded as inventions is protected, including the smallest libraries and subroutines. [4]. European Patent Convention in this Article excludes Intellectual property rights are divided into economic and moral computer programs from patentability. It is important to rights. [8] emphasize the distinction between "software patents", which are Economic rights give the holder the right to exploit the work excluded according to the aforementioned Article, and and prevent others from using it without consent, and are aimed "computer-implemented inventions", which are accepted by EPO at economic gain. The right to use can be granted by license. [5]. Exclusive license allows the holder to exclude others from using Software that does not demonstrate a technical contribution the intellectual property in question and, if it is transferable, it can only be protected by copyright which does not protect ideas. allows the holder to grant third parties the rights to use it. A The appearance of a command line or a graphical interface can license is a permission granted by the licensor to the licensee to be protected as a registered design, whereas a patent for computer use an identified asset under certain conditions. In doing so, the or mobile application can be granted if a technical contribution licensor may determine at their discretion the extent of the is demonstrated. Under EPO rules, if technical contribution is exclusive intellectual property rights granted in respect to the successfully demonstrated the software must be connected to the asset (and, conversely, the rights it reserves for itself). Moral hardware. [3] rights include the right to authorship, the right to publish the Although the European Patent Convention excludes work anonymously or under a pseudonym, and the right to "computer programs" from patentability to the extent that a integrity of the work. In most countries (including all EU patent application relates to a computer program "as such", this countries), copyright protection lasts throughout the author's is interpreted to mean that any invention that makes a non- lifetime and extends 70 years after their death. [6] obvious "technical contribution" or "solves" a "technical As we have seen above, software is very specific as far as problem" in a non-obvious way is patentable, even if the intellectual property is concerned – it can be protected by several technical problem can be solved by running a computer program. types of intellectual property rights ranging from pure creations [6] of the mind to technical inventions. But a whole new level of The problem of strictly classifying software similar to a complexity arises from intangible nature of software, variety of literary work arises when one considers that computer programs uses and different means of creating value from software. As a have other elements that are usually not protected by copyright. consequence, the means of creating value from software can vary Software is not just a literary expression – lines of code have a considerably depending on the exploitation scheme chosen and function that does not depend on their grammatical construction. associated ecosystem to which the use of software in question is Issues related to protection of additional elements of computer directed. Nevertheless, licensing plays an essential role in programs have created a perceived need for software creating value through management of intellectual property patentability. Today, the three largest patent offices in the world associated with software development. Business models are – in the EU, US and Japan – allow patenting of certain software, formalized in a contract, usually in the form of licensing although there are differences in the criteria they use when agreements which impose specific rules of use on third parties accepting applications. In the US, all new and non-obvious who intend to exploit the software. Figure 1 shows some typical software that produces a useful material and tangible result is software licensing models. [6] eligible for patent protection, whereas in Europe the technical contribution of the invention must be defined as described above (also applies to Slovenia). These discussions led to the widely accepted principle that computer programs should be protected by copyright, while apparatus using computer software or software-related inventions should be protected by patent. [6] Protecting and obtaining intellectual property rights in fast- growing areas such as artificial intelligence is a particular challenge. Artificial intelligence provides entirely new Figure 1: Classification of typical software licenses approaches to creation of intellectual property. Questions arise as to the eligibility of patent protection, authorship and rights 266 Software Protection and Licensing Challenges in Europe: An Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Overview Free and open-source software rights include use, inspection 2. Node licensing, where the license can be used by multiple and modification, and distribution of modified and unmodified users, but on the same device rather than at the same time. copies. They typically allow it to be used for any purpose without 3. Site licensing (licensing for use on a dedicated website), restriction. When the code is reviewed and modified, it requires where the software may be used by multiple users on that the modified code is made available again under the same multiple devices in a specific area or company, but the conditions. The rights also allow distributing modified and number of users may be limited. 4. Network licensing (floating licensing), where the same unmodified copies of the software. When free and open-source software may be used by multiple users at the same time, software is modified, derivative works are created, and when but a central server authorizes access to the application. [6, various components of the software are assembled, composite 9, 10, 11] parts of the underlying components are created. When Component A and Component B are assembled and Component 3.2 Management of Intellectual Property Rights A is also modified, Component C is created, which is both a for Software derivative work of Component A and a composite work of Managing intellectual property in software requires the Component B. Different economic rights may arise from the use strategic and complementary use of different types of intellectual of open-source and free software. Free software derives from property. Exploitation and licensing strategies need to be licenses granted by the Free Software Foundation, while open- carefully considered, taking into account all associated costs and source software is defined by the Open Source Initiative, which market opportunities. Two basic issues should be addressed in has a more business-oriented approach. We consider the the assessment and planning process [6, 12, 13]: following types of such licenses [6, 9, 10, 11]: 1. Why was the software created: was it intended to generate 1. Academic licenses are extremely open, permissive licenses income through licensing to end users or was it developed which allow licensees to perform, modify, and distribute as part of a scientific project without an exploitation derivative works without restrictions, although licenses for strategy in mind? Even if we focus only on the technical derivative works may lead to new licensing terms, including proprietary ones. Such licenses are generally accepted in challenges of R&D, we should not neglect the long-term academia. benefits of protecting intellectual property not only from a 2. Contextual licenses allow licensees to use, modify, and revenue perspective but also in light of reusing the distribute derivative works, provided that the derivative or developed software in future applications. composite works are distributed under the same license. 2. How was the software developed: which are our own Specific form of such license is called a "Copyleft license" components, what have we obtained from elsewhere, and, if which is the practice of granting the right to freely distribute obtained from elsewhere, under which licenses? and modify intellectual property with the requirement to Developing from third-party components can result in legal preserve the same rights in derivative works created from challenges as the individual licenses of different third-party that property. The main advantage of such license is to ensure joint investment, as no derivative or major works can software may not be compatible. be licensed under another license. They allow the original Derivative works based on academic license software licensor to be granted the same rights in the derivatives as components may be re-licensed under the same type of license or those originally acquired by the original code licensees. upgraded to contextual or reciprocal licenses which are 3. Reciprocal licenses are very complex as licenses of major compatible. If necessary, contextual licensing code can be re- works using an unmodified version of the original licensed by reusing the same license, upgrading the license to a component under a contextual license are not limited by the newer version that remains in the same contextual field, or original license and derivative product containing a switching to reciprocal licenses. It is not allowed to embed free modified component must be released under the same and open-source software in proprietary software. However, it is license. Many different types of contractual relationships or possible to combine copyleft-licensed software without contractual sets of rules can be derived from proprietary licenses, copyright and some contextual rights (e.g., LGPL). [6] all of which typically require a financial contribution from the However, if the software is protected exclusively by end user. Exceptions are: copyright it is possible to easily circumvent all prior rights as long as we have access to the source code: the same idea can 1. Freeware, where the software is available free of charge but simply be implemented in another source code. As previously any modification of the code is prohibited. 2. Shareware, where the user is free to use the software for a explained: copyright does not protect the idea, only its expression. limited period of time or with limited functionality, but in A new implementation of the code is the only legal way to order to gain access to the full unrestricted version an convert academic or reciprocal software code into proprietary additional license must be obtained. code and sell and license it under the rights granted by copyright All proprietary licenses prohibit modification of the law. software, impose strict conditions of use and usually do not allow access to the source code. Typical models for proprietary licenses are: 4 CONCLUSION 1. End-user licensing where the license can be used by a The situation of software in the European innovation arena specific user while sharing with other users is not allowed. can still be considered as neither resolved nor uncertain in legal However, the license can be used by the same user on different devices. terms, thus raising a number of open questions and opportunities for further work. 267 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia U. Fric et al. TTOs are deeply involved in the work of organizations where [2] Stephen Jonson. 2015. Guide to Intellectual Property. What it is, how to inventions and creations take place. Their expertise primarily protect it, how to exploit it. The Economist in Association with Profile Books Ltd. And PublicAffairs, New York. helps computer scientists who create software evaluate which [3] Urška Fric and Nina Tomić Starc. 2021. Computer-Implemented problem they are solving and based on that make an informed Inventions and Computer Programs – Status Quo in Slovenia and EU. Informatica, 45, 5 (Aug, 2021), 667–673, DOI: decision on how to protect intellectual property using copyright https://doi.org/10.31449/inf.v45i5.3468 or patent. In view of the above, TTOs can contribute to a [4] European Patent Office. 2007. European Patent Convention (EPC 1973). constructive decision-making process regarding the future of https://www.epo.org/law-practice/legal-texts/html/epc/1973/e/ar52.html [5] European IP Helpdesk. 2020. Copyright or Patent – how to protect my software protection and rewards for computer scientists by Software? https://www.iprhelpdesk.eu/news/copyright-or-patent-how- participating in (open) public debates and presenting real-life protect-my-software [6] Urška Fric, Nina Tomić Starc, Špela Stres and Robert Blatnik. 2021. examples of scientists developing software in PRO. Programska oprema in vprašanje nagrajevanja raziskovalcev. In Modrosti In order to ensure successful marketing of software, the PRO iz inovacijskega podpornega okolja v JRO za upravljalce inovacijskega system needs to provide the motivation and a rewarding sistema, Špela Stres, Eds. Ljubljana: Institut 'Jožef Stefan' (IJS), Novo mesto: Fakulteta za informacijske študije v Novem mestu (FIŠ) Ljubljana: mechanism for scientists for their enterprise. Kemijski inštitut (KI), Ljubljana: Kmetijski inštitut Slovenije (KIS), It is good to remember that any invention that implements a Ljubljana: Nacionalni inštitut za biologijo (NIB), Koper: Univerza na Primorskem (UP). non-obvious "technical contribution" or "solves a technical [7] European Patent Office. 2020. Digital Conference. 17–18 December 2020. problem" in a non-obvious way may be patentable, even if the https://www.epo.org/news-events/events/conferences/ai2020.html [8] European IPR Helpdesk. 2014. Fact Sheet IPR Management in Software same technical problem can be solved by running a computer Development. program. Consequently, program code in which technical effect https://iprhelpdesk.eu/sites/default/files/newsdocuments/Fact-Sheet-IPR- (even if in a non-obvious way) constitutes a technical Management-in-Software-Development.pdf [9] Andrew Morin, Jennifer Urban and Piotr Sliz. 2012. A Quick Guide to improvement is patentable by its very nature. The trade secret Software Licensing for the Scientist-Programmer. PLos Computational segment is also important, since disclosure of program code Biology, 8, 7 (Jul, 2012), 1–7, DOI: https://doi.org/10.1371/journal.pcbi.1002598 without a suitable proprietary license or any license at all may [10] Daniel Gull and Alexander Wehrmann. 2009. Optimized Software result in commercial damage. By combining the technical effect Licensing – Combining License Types in a License Portofolio. Business of the software code with the trade secret effect, it is possible to & Information Systems Engineering, 4, 2009 (Jan, 2009), 277–289, DOI: 10.1007/s12599-009-0063-2 register the software code example as an invention and, [11] Carlos Denner dos Santos Jr. 2017. Changes in Free and Open Source consequently, ensure a reward for computer scientists. Software Licenses: Managerial Interventions and Variations on Project Attractiveness. Journal of Internet Services and Applications, 8, 11, (Dec, We therefore propose that regular reflection among computer 2017), DOI: 10.1186/s13174-017-0062-3 scientists within PRO is facilitated on new, marketable software [12] Goh Seow Hiong. 2005. Open Source and Commercial Software. An In- depth Analysis of the Issues. code, that verification is introduced to any technical contribution, https://www.wipo.int/edocs/mdocs/copyright/en/wipo_ip_cm_07/wipo_i and that invention based on software code is registered p_cm_07_www_82575.pdf accordingly. TTOs play a key role in this respect, as their specific [13] Carlo Daffara. 2011. Open Source License Selection in Relation to Business Models. Open Source Business Resource (Dec, 2011), expertise contributes to the proper assessment and registration of https://timreview.ca/article/416 service inventions as well as to the wider popularization of software commercialization (also protected and registered in this way). At the same time, the proposed method allows computer scientists working in the field of software code development to be rewarded for their work. ACKNOWLEDGMENTS / ZAHVALA The operation is partially co-financed by the European Union from the European Regional Development Fund and the Ministry of Education, Science and Sport of the Republic of Slovenia. The operation is implemented under the Operational Program for the Implementation of European Cohesion Policy for the period 2014–2020, priority axis 1 Strengthening research, technological development and innovation. Operacijo delno sofinancirata Evropska unija iz Evropskega sklada za regionalni razvoj in Ministrstvo za izobraževanje, znanost in šport Republike Slovenije. Operacija se izvaja v okviru Operativnega programa za izvajanje evropske kohezijske politike v obdobju 2014–2020, prednostne osi 1 Krepitev raziskav, tehnološkega razvoja in inovacij. REFERENCES [1] Daniel Closa, Alex Gardiner, Falk Giemsa and Jörg Machek. 2011. Patent Law for Computer Scientists. Steps to Protect Computer Scientists. Springer-Verlag, Berlin, Heilderberg, Dordrecht, London, New York. 268 European Guiding principles for knowledge valorisation: An assessment of essential topics to be addressed Špela Stres Levin Pal Marjeta Trobec Center for technology transfer Center for technology transfer Center for technology transfer and and innovation and innovation innovation Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana, Jamova cesta 39, Ljubljana, Jamova cesta 39, Ljubljana, Slovenia Slovenia Slovenia spela.stres@ijs.si levin.pal@ijs.si marjeta.trobec@ijs.si ABSTRACT form. However, some new aspects have arisen and are further Knowledge transfer is a complex mechanism of providing the addressed in this paper - for example, state-aid issues connected society with benefits arising from all segments of publicly to the intellectual property right (IPR) issues. financed research. Knowledge transfer is also an important To conclude, the idea of further networking between innovation mechanism to advance and improve technology transfer as its support stakeholders needs to be put forward, particularly part (as technology is only one of several research outputs [1], regarding Enterprise Europe Network (EEN). In the coming [8]), and a reason to analyse the current situation in the field. years, EEN plans to pay more attention to the field of KT, as KT This paper has three different parts. In the first part, models of is essential for raising the competitiveness of the European knowledge and technology transfer will be discussed, including economy. In this context, the presented proposal of topics that the Defense Advanced Research Projects Agency (DARPA) need to be addressed within new European Commission model of operation, as it was the basis for the development of the recommendations will be mutually beneficial in developing new European Innovation Council (EIC) of Horizon Europe internal strategies of EEN and KTOs as well. It would be of utmost management operation in which the author of this paper was importance to establish a fruitful collaboration between KTOs involved. The model is essential also for the future development and national EEN offices to assure full in-depth support to of EU Knowledge Transfer Offices (KTOs). Given its high researchers and SMEs alike in this TRL challenging exercise in budget and added operational and substantive value related to between the worlds of academia and industry, in particular given Program Managers, the EIC in a way represents the largest - a the EEN's core values (Fig.6). kind of umbrella - KTO in Europe, which should integrate many small, different and unique European KTOs into one whole. KEYWORDS Therefore, it is recommended in this paper that each European Knowledge valorization, knowledge and technology transfer, KTO reviews and understand the previous DARPA / ARPA-E knowledge transfer office, innovation, public research models and/or the European EIC model. They should use it as a organization, industry, key performance indicator, licensing, framework for adaptation of operations based on its legislation collaborative research, funding, spin-out, spin-off, intellectual and the specificities of the industrial and public sector so that property, models, technology readiness level, networking. each KTO becomes a comparable element of the whole at the European landscape. 1 MODELS OF KT: DARPA AND THE EU In the second part, a brief review of the knowledge transfer KTO WAY (KT) literature of the past 15 years will be done, given the KT profession's prevailing state of mind. A lot has been done during The formal organizational models of KTOs in the EU are ranging this time in KT development and attempts to evaluate the from internal KTOs, through institutionally owned enterprises to operation of KTOs. It turns out that there are different national national, either network-based or private regional entities. This environments, so the way KTOs operate may differ slightly from contribution will focus on an internal model of operation of a KTO to KTO. Nevertheless, there are common points in the KTO. pipeline of all KTOs, namely the KPIs represented in this paper The goal of any innovation intermediary should be to increase (Table 1), which are not limited to KTO results only (e.g. patents the deal flow, increase the number of deals, and increase the filed, license and R&D agreements), but rather act as indicators impact of those deals. The Defense Advanced Research Projects of the quality of the KTO activities. The represented Agency (DARPA) and the Advanced Research Projects Agency- nomenclature of KPIs should help set up a uniform path that Energy (ARPA-E) in the US became hands-on innovation European KTOs are supposed to follow to achieve the results. agencies to achieve such a goal. This required innovative internal In the third part, specific segments of the Commission procedures, a new risk-taking mindset and tailor-made Recommendation on intellectual property management in management. Its operating concept is to be hands-on, thus knowledge transfer activities and Code of Practice for involving the activities of a group of people in many segments, universities and other public research organisations [1] will be very similar to a proactive KTO. This concept is embedded in a touched upon. These documents are still relevant in their present set of questions known as the "Heilmeier Catechism", attributed 1 269 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Š. Stres et al. to George H. Heilmeier, a former DARPA director (1975-1977), them to the market. To support breakthrough innovations, the EU who crafted them to help Agency officials think through [2], KTOs must themselves be an organizational breakthrough in evaluate and manage proposed research programs for maximum Europe. The main components for achieving this endeavour are impact. By being proactive in managing the innovation side of centred on the creation of challenge- and thematic-driven the financed projects, DARPA and ARPA-E could successfully pipelines in each of the KTOs, high rejection rate in the operate their model for breakthrough innovation. acceptance of the cases to the portfolio, active portfolio The DARPA proactive model of operation is also present in the management of cases, transition activities that bring new work processes of the European Innovation Council (EIC), with solutions to the market and KTO personnel who binds all of this its important new feature, the Programme Managers. As Europe's together into complementary practices (see Fig.2). It is crucial to flagship innovation programme to identify, develop and scale up understand that DARPAs results show that this is the right way, breakthrough technologies and game-changing innovations, EIC and it should be investigated how such a proactive system could has a budget of €10.1 bil ion to support game-changing be set up in an environment like ours. innovations throughout the lifecycle from early-stage research to Proof of concept, technology transfer, and the financing and scale-up of start-ups and small to medium-sized enterprises (SMEs). With its Programme managers and support staff, it can be considered the largest KTO in Europe. The synergies and similarities of KTOs with EIC should be looked into. The EIC builds (and so should the EU KTOs) on active pipeline management (see Fig.1), combined with Proof of concept funding related to a well-defined pipeline of case management. The management is done by highly skilled professionals, combining technical and commercial acumen through a well- defined interface, expanding far beyond the current average Figure 2: The need for highly skilled personnel in the KTO public relations activities of the European KTOs [3]. to active pipeline management, combined with Proof of concept funding related to the pipeline [4] 2 STATE OF THE ART IN KT IN THE EU 2.1 A literature review For almost 15 years now, the Knowledge transfer flow has been discussed: on the operational and top policy levels. In this section, a discussion about the essential works in this field is given: »Communication (2007)« [5], »Recommendations (2008)« [1], »A composite indicator (2011)« [6], »Knowledge economy (2020)« [6], »Performance indicator system (2021)« [8]. The KT topic was brought into the open by the »Communication« [5], co-signed by the Slovenian commissioner for research Janez Potočnik) in 2007, just before when Kevin Cullen from Glasgow University designed his KT flow in 2008 Figure 1: From Horizon 2020 to Horizon Europe: Active (Fig.3). Moreover, Kevin's KT flow has been used ever since: in Portfolio Management of funded projects [3] A comparison the »Recommendations« in 2008, later shown in the 2011 EC between Future Emerging Technologies (FET) calls in Report »A Composite Indicator« and also in the new 2020 Horizon 2020 as a predecessor of European Innovation »Knowledge« report. Council (EIC) calls in Horizon Europe The view on the KTO role in connecting research to the economy The goal of any KTO in Europe should not be to copy the (and its vehicles) has not changed since 2007. To observe this, a DARPA/ARPA-E or the EIC model. However, it should instead comparison between Fig.3 [6] and Fig.4 [7]) can be made. The be to translate a known useful model into their context flow is divided into Research Outputs, KT Channels/Activities, considering the Horizon Europe rules, the national legislation Users/Economic Activity and Impact. The segments are not and the current national/regional/local research, development surprising because the division represents the flow-through of and innovation culture. Only in this way can the innovation knowledge in the KT system, as described already in 2008. intermediaries, the KTOs, create their own unique identity in the However, the perception of the KT community has changed for European landscape for supporting breakthrough innovations – the better in the meantime. It has at least changed in terms of the create the EU KTO way. involvement of a KTO in different KT vehicles. In 2013 the Board members and Vice Presidents of the European Association Developing the unique EU KTO way is challenging and of Technology Transfer Professionals (ASTP) even at this necessary. It will comprise novel practices supporting the premier knowledge transfer organization's top-level, we could development of breakthrough technologies and actively bringing barely discuss the inclusion of Key Performance Indicators 270 European Guiding principles for knowledge valorization: What has changed since 2008? Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia (KPIs) on software and contract or collaborative research and recognized profession. Scientific research, critically endeavours to the KT pipeline in the yearly Metrics report of analyzing the processes within KTOs, their success and fail European KTOs. Most of the time, negative comments regarding factors, and a rigorous scientific approach to monitoring trial and the importance of indicators other than licensing deals came from error knowledge transfer practices within the KTOs is needed to people working in biotech or medical technologies focused improve the EU KTOs. public research organization (PRO) environments connected to university hospitals in Western Europe. As these had a prevailing licensing deal flow at the time, primarily with the pharmaceutical industry, their interest in widening the scope of the KT vehicles was limited. Figure 4: Knowledge Transfer: from research to impact [7] 2.2 The role of the missing KT KPIs The goal of any innovation intermediary is to increase the deal flow, increase the number of deals, and increase the impact of those deals. To achieve such a goal, DARPA and ARPA-E in the US became proactive, hands-on innovation agencies. In Europe, given the Knowledge Transfer Metrics [7], in 2020, the authors Figure 3: Model of knowledge transfer within the focus on defining the KT indicators in four quadrants, including innovation ecosystem [8] Internal Context, Environment, Activity, Impact – trying to assess the inputs and the outputs of the KT system (Fig.5). In However, gradually through the years, an understanding has effect, apart from the Activity indicators, the proposed metrics arisen that as there are many different national environments, observes the enabling factors - the success factors of the KTO's there are many different economic situations, with diverse pipeline from the outside of the KTOs (which they have little technological absorption capacity from the industry, requesting influence over). On the other hand, it observes the final impacts and even demanding different vehicles to achieve actual KT. of KTO's operations on society (which are very distant from Thus, we recognized that there are indeed many different today's perspective). However, it does not focus into great detail vehicles, and as KTOs are the primary activity-focused linkage on the internal procedures and pipelines directly under the KTO's between the Public Research Organizations (PROs) and the influence. Thus, such enabling indicators have a role in industry, they should be appropriately put into the KTO practice. evaluating the level of the KTOs possible maximum results, not Many KTOs, in particular in the Eastern and Southern parts of the quality of its operations. Europe, but also such prominent ones as Cambridge Enterprise, started to empower any one of the KT vehicles (including The KT profession is clearly labelled as inefficient throughout contract and collaborative research and services), which bring Europe, which is also confirmed by the fact that the results for the global/national/regional/local economy, society Recommendations of 2008 are now being urgently reviewed by and the PRO itself. In this way, the perception of the role of a the European Commission, but seeking remedies outside the KTO in the innovation flow system remained the same community, not taking responsibility for its actions. In order to throughout the last 15 years (if we compare the figures presented improve the operation's quality, it is not enough to assess what is in 2011 [6] and in 2020 [7], they are essentially the same), but outside of the KTO's reach (internal PRO's context, the understanding and the focus of KTOs rightly shifted from environment). Moreover, it is not enough to claim that [7] the patenting and licensing to other vehicles of KT as well. However, KTO impact is long term, we cannot measure it right now, we even though progress has been made, the KT community is still shall see what happens long-term—neglecting evaluations of the struggling to define the KPIs of the KT operations completely internal KTO procedures and their efficiency results in the fact [8]. This shortcoming is an echo of the under-developed research that the profession is not advancing as fast as it should. activity in the field of KT. The results are indeed dependent on the enabling factors, but are The level of research activity in and on KT is still relatively low essentially determined by the actions taken by the KTOs [9]. in the EU. Primary sources as Joint Research Centre (JRC), TTO Thus, to improve the quality of the KTO operation in Europe, it Circle and ASTP mainly focus on producing success stories and is necessary to set up process KPIs to monitor KTO processes incomparable status reports, which lack the in-depth definition of and evaluate their quality. The focus should be paid to measuring KPIs to allow for fair and holistic assessment of the KT system the efficiency of the KT process, using Detailed Activity or in the EU. As important as success stories, networking and Process KPIs, organized as a funnel, and, on this basis, address workshops in the field of the KT profession are, these are not the shortcomings in the effectiveness of KTOs. The focus should enough to professionalize the activities and create a full-pledged be given to KTO's internal operation, evaluating the KTO 271 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Š. Stres et al. activity in detail: analyzing the deal pipelines, making them to researchers, Active marketing: number of offers prepared for professional, flow-through, and improving KTOs' performance selected companies, Number of received expressions of interest- by understanding the interdependence of the processes KTOs based on active marketing, Spinout Business Plans prepared, carry out. Internal Proof of Concept projects approved, financed and managed and others ... Table 1: The proposed nomenclature of KT Key Performance Indicators Description of KPI/Result (al counted in Number of, unless where specified) Cases accepted for processing in KT Number of patent applications filed Office with full examination First meetings with researchers - Opinions on continuation of IP inventors protection Assessments of the state of the art Passive Marketing: Preparation and publication of Technology Offers Market assessments/analysis Submitted expressions of interest First meetings with companies Active marketing: number of offers Figure 5: Input and Output KT Indicators: the four (company visits) prepared for selected companies quadrants [7] Participations of licensing team Active marketing: number of offers sent To monitor the activity within a KTO's pipeline is the only way member in 1st meetings with to selected companies companies to observe the points where the activity goes awry. In the »Knowledge economy« report, the valuable parts of the Second meetings with companies Active marketing: no. of received expressions of interest indicators are shown under the Activity part in the quadrant, focusing on the final KTO results only. However, it is not Participations of licensing team Signing of Non-disclosure agreements member at 2nd meetings with analyzed how the results were obtained. The KTOs are stuck with companies the KT indicators – they indicate the temperature in the KT Third meetings with companies Negotiations conducted system. However, they do not analyze what is going on and how the impactful factors are connected. The problem is similar to the Participations of licensing team Cooperation agreements (R&D member at 3rd meetings with contracts) signed difference between measuring water temperature in a glass and companies understanding the physical processes behind heating the water. Identified topics at meetings with Licensing agreements (licensing From the measured water temperature, it might be concluded that companies for potential col aboration Contracts) signed the fact that we are based in tropical climate influences its heating with PRO research teams on the stove, but not how. Likewise, from observing the lower Collaboration topics from meetings with Amount covered by R&D Contracts than desired KT results, it might be concluded that the only companies identified by licensing team (EUR) members reason for the unsatisfactory performance of the KT in Europe is the too low percentage of the GDP spent for the KTO or the Meeting minutes from the 1st, 2nd Amount covered by licensing Contracts and/or 3rd meeting with the company (EUR) R&D. To support breakthrough innovations, the EU KTOs must themselves be an organizational breakthrough in Europe. Supplementations by licensing team New Companies in col aboration with member, of minutes from the 1st, 2nd the PRO (via R&D and licensing Moreover, to achieve that, we should focus on the KT process and / or 3rd meeting with the company agreements) and understand it. We must focus on internal KTO operation, Collaboration topics disseminated to Consultings on Access to financial internal technology transfer sources (Tenders, VCs, Commercial evaluate the KTO activity in detail and set up KPIs to monitor it. coordinators and published in the Loans) We must analyze the deal pipelines, make them professional, suitable PR publications (counting by flow-through, and improve our performance by understanding company visit) our processes. Col aboration topics disseminated by Spinout First meetings on spinout licensing team member to PRO creation How can we establish process focused KPIs to evaluate the Researchers (counting by company visit) efficiency of KTO operation? The efficiency of the innovation Individual Advisory Supports delivered Spinout Business Plans prepared management system in a country can be evaluated through the to companies share of successful commercialization of patents and secret Individual Advisory Supports delivered Spinout documentations for the know-how originating from PROs. The commercialization to researchers establishment of the spinout prepared for consideration by PRO involving KTOs occurs through new company creation, IPR licensing and sales, and direct R&D collaboration. These are the Invention disclosures at PRO / decision Signed contracts for the establishment to acquire the invention by PRO of spinout companies results of the KT process (but not the impact). Nevertheless, there are many other processes KPIs, which enable us to monitor the Author: Š. Stres in collaboration with selected members of efficiency of the KTO process: for example, the number of Center of Technology Transfer and Innovation, 2020 (M. Market assessments/analyses, Identified topics at meetings with Trobec, F. Podobnik, L. Pal) companies for potential collaboration with PRO research teams, Setting up and active monitoring of the entire funnel of KTO Number of Individual Advisory Supports delivered to KPIs may turn out especially advantageous for young KTOs that companies, Number of Individual Advisory Supports delivered have been just established. The "case-by-case" process from 272 European Guiding principles for knowledge valorization: What has changed since 2008? Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia preparation to protection and marketing and hopefully should continuously be published before setting a contract with conclusion of license and R&D agreement can take a very long a specific entity to distort the market's competition. Need to time (on average at least 12 - 30 months), and much work has to publish the TOs to assure state aid and fairness in terms of be done before the final results are earned. During this time, well- competition laws. established and internationally recognized KPIs might become extremely useful - justifying the existence of such young KTOs Synergies: Look into possible synergies with European to the management authorities and tracking/evaluating their Innovation Council (EIC), Enterprise Europe Network .. from operations. Verified and standardized international KPIs, operational, not political or networking point of view. KTOs therefore, illustrate whether the KTOs are on the right path to should capitalize on the existing financing available and the their goals or not. existing support networks available. With the process KPIs of KTO operations, we can set complete Broader view on IPR: Registration of models, trademarks, metrics for the Key KT Activities of KTOs. Such metrics are printed circuits, new plant sorts, software should be encouraged. presented in Table 1, The nomenclature of KT. These metrics Copyright implications should be addressed, as software is part allow for the intertwining of contract and collaborative research of the Copyright legislation. Recommendations should be given in countries where this is necessary, with actual licensing and on how to award researchers for software commercialization and sales of industrial property (nationally or internationally) and define incentives in different countries (as the legislation in some spinout creation. Every country has a specific distribution of countries excludes copyright from the rules on awarding particular KT Activities and results (final contribution measured researchers in case of commercialization of copyright). much later on by Economic Impact). The efficiency of these Diversification of KT Activities: Wherever only licensing is efforts measured by KPIs may differ throughout the countries, mentioned as a vehicle; this should be remedied with other but the KPIs themselves, the nomenclature, and the results available KT vehicles. The difference between spinouts and remain the same everywhere: Number of disclosures, Number of spinoffs should be introduced. The specific knowledge and licensing, contract, collaborative and service deals, Spinouts capacity on capital share management by the KTOs should be established. addressed. The positive impact of spinoffs vs spinouts and vice versa? The need to develop internal PoCs which increase the efficiency of the KTO, the InvestEU with EIF policy 3 AN ASSESSMENT OF TOPICS THAT introduction. Publishing the technology offers (TOs) and sending NEED TO BE ADDRESSED WITHIN THE them around - active and passive marketing, requiring different NEW RECOMMENDATIONS knowledge and yielding different success rates, depending on the In light of the above analysis of the field and the existing "name" of the institution. Recommendations, we suggest topics of concern to be The use of EEN and its Thematic/Sector Groups for addressed in the amending of the text of the 2008 technology marketing is also essential. There is a mutual need to Recommendations – because these are topics of concern in increase KTOs' awareness about EEN and its Sector Groups the current KT endeavors in Europe and they are not (mainly "technology-based") and Thematic Groups as a channel covered within the existing Recommendations. The for technology marketing, access to SMEs and obtaining the suggestions areas are listed below. latest expert information in the field of work, respectively. EEN Operational Issues: Every KTO should have a set of operational should continue its efforts to emphasize actively seeking principles, an honour code and a code of conduct as a basis of its Technology Requests at SMEs and linking them to Technology operation. It could be based on the Code of Conduct of the Offers of PROs. Moreover, KTOs should actively harvest Enterprise Europe Network (EEN) or built anew. commercial databases for technology requests. Several services offered by EEN serve as a prelude to the required (but not always Accounting issues: Emphasize the importance of registering the available) expert services of the KTO consultants. Providing a intangible assets – in principle, one cannot sell something that vibrant innovation ecosystem, in which the EEN and KTOs has not been registered according to the European accounting would work in view of signposting and the hub and spoke model, principles for intangible assets (including its initial accounting EEN serving as a liaison (account manager), but KTO as a final value). expert service provider, could work effectively. State Aid and Evaluation methods with competition law: A wider approach to science disciplines: Collaboration with Evaluation of IPR is also essential in state aid in collaborative social sciences and humanities (for example, the connection with projects (IPR transfer in the context of state aid). Even though heritage science and alike should be investigated) should be not in Horizon Europe, operating under the State-Aid encouraged. In this regard, the »Outputs« as defined in the Exemptions, but in all cohesion related funding and national Research Excellence Framework (REF) of the UK research funding for higher TRLs (which are not part of the State-Aid evaluation system should be studied and possibly all 22 Exemptions). To assess the value, different valuation methods categories, which also include patents) should be analyzed for (not valutation) should be understood to set the first value in the further usage. Citizen science and science with and for society accounting books. For this purpose, intangible asset evaluation issues should become more prominent within the work of KTOs. methods should be analyzed and valuation principles accepted for the KTO usage. Competition law – Technology Offers A systematic research approach to KT content and increasing the quality: Policymaking and lobbying for research 273 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Š. Stres et al. projects in the KT – political impact of the EC and JRC is Network aims to help businesses innovate and grow required for this. The explicit notion of the need to upgrade the internationally. KTO services from PR activities, and the importance of KT activities to actual execution of such activities, measured by unique KPIs, results should be normalized to research FTE headcount. KPIs are the same in all KTOs regardless of the enabling factors (these only define the maximum KTO output and maximum impact in the economy). Build on the impact factors from the pathway to impact of the EC (commercial, research, societal). Systemization on the Horizon Europe level: In the same way as »Gender equality plans« need to be published as a prerequisite to a Horizon Europe project approval, also »IP and commercialization policy, including Open Science« should Figure 6: Enterprise Europe Network Code of Conduct, become such a required action for HE projects. The DARPA Annex 2 to the Grant Agreement, 2014 model and EIC model (with PMs and the support team) are development directions. In the coming years, EEN plans to pay more attention to the field Beneficiaries of the KT Activities: It should be emphasized in of KT, as KT is essential for raising the competitiveness of the the Recommendations that students as private persons are not the European economy. In this context, we believe that the presented target of the Recommendations nor the focus of KT activities of proposal of topics that need to be addressed within new the KTO, at least not under the legislation for IP ownership; recommendations will be mutually beneficial in developing new remedies to assist student-based inventions should be devised strategies of EEN and KTOs and strengthening their relations. under different measures than KTOs (e.g. university, incubators). Organizational issues in different specific 4 CONCLUSIONS situations: Recommendations on how to organize the system for • European KTOs should review and fully understand smaller institutions that do not have the capacity nor the need to the current European EIC model connected to the retain a full-pledged KTO are needed. Such recommendations successful DARPA / ARPA-E models. They should are required due to the diversity of personnel needed. Several consider the model as the main framework while employees are needed to have a successfully operating KTO. adapting its operations to national legislation and the Several models have been tried out: SATT (centralized), specificities of the industrial and public sector – all Knowledge Transfer Ireland & Slovenia (consortium with the aim that each KTO becomes a comparable element of the whole community of KTOs at the distributed), Cambridge (University-owned), Leuven R&D European landscape. (independent internal office) .. It is true that everyone needs to find their way, but there are specifics and criteria which can help • There are some common critical points in the pipelines find the suitable model. The emphasis on trust-building with the of all KTOs irrespective of different national research and economic community is of the utmost importance. environments and specifics, namely the KPIs represented in Table 1. Such KPIs are indicators of the Pooling and open science: Requirements for pooling among KTO activities rather than only general and final KTO institutions on IPR offer should be upgraded in pooling of Open results (e.g. patents filed, license and R&D science access. The possible tension between IP protection and agreements) or remote indicators of KTOs' maximum Open science, particularly secret know-how, should be addressed possible results (limited by the environment). The in straightforward operational funnels. represented nomenclature of KPIs should help set up a uniform path that European KTOs are supposed to Career progression in KT: The career progression of KTO follow to achieve the results. professionals should be addressed, agencies and ministries • should be invited to discuss this issue. It would be of utmost importance to establish a fruitful collaboration between KTOs and national EEN offices Managing the financial return: Recommendation on how the to assure full in-depth support to researchers and SMEs PRO uses the income from commercial activities - should it be alike in this TRL challenging exercise in between the used for a PoC fund managed by the KTO for TRL increase of worlds of academia and industry, in particular given commercialization cases? Or for further IPR cost financing? the EEN's core values (Fig.6), focusing on the signposting and the hub and spoke model of operation. Why? Last but not least, an idea of further networking between innovation support stakeholders needs to be put forward, particularly in regards to Enterprise Europe Network (EEN) REFERENCES being active in more than 60 countries worldwide providing [1] European Commission. 2008. Commission Recommendation on the support to SMEs with international ambitions. Co-funded by the management of intellectual property in knowledge transfer activities and Code of Practice for universities and other public research organisations. European Union's COSME and Horizon 2020 programmes, the Luxembourg: Office for Official Publications of the European 274 European Guiding principles for knowledge valorization: What has changed since 2008? Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Communities. Retrieved August 3, 2021 from https://ec.europa.eu/invest- in-research/pdf/download_en/ip_recommendation.pdf. [6] Finne H., Day A., Piccaluga A., Spithoven A., Walter P., Wellen D. 2011. [2] Heilheimer H. George. The Heilheimer Catechism. Retrieved August 3, A Composite Indicator for Knowledge Transfer Report, European 2021 from https://www.darpa.mil/work-with-us/heilmeier-catechism. Commission’s Expert Group on Knowledge Transfer Indicators (page 10). [3] European Commission. 2020. Implementing the pro-active management Retrieved August 3, 2021 from of the EIC pathfinder for breakthrough technologies & innovations. https://www.belspo.be/belspo/stat/docs/papers/ERAC%20Report_2011_ Retrieved August 3, 2021 from A%20Composite%20Indicator%20for%20Knowledge%20Transfer.pdf. https://ec.europa.eu/info/publications/implementing-pro-active- [7] Campbell A. et al. 2020. Knowledge economy and its impact. Retrieved management-eic-pathfinder-breakthrough-technologies-innovations_en. August 3, 2021 from [4] Working Report on Technology 2 Market Support, WG on pro/active https://knowledge4policy.ec.europa.eu/event/knowledge-economy-its- management, EIC, January 2021. impact-0_en. [5] European Commission. 2007. Communication from the Commission: [8] Holi et al., 2008 p. 2; attributed to Kevin Cullen of Glasgow University Improving knowledge transfer between research institutions and industry [9] Alejandro M. Aragon, A measure for the impact of research, 2013. across Europe. Annex: Voluntary guidelines for universities and other Retrieved August 4, 2021 from research institutions to improve their links with industry across Europe. https://www.nature.com/articles/srep01649 275 Digital Innovation Hubs and Regional Development: Empirical Evidence from the Western Balkan countries Bojan Ćudić Špela Stres University of Maribor Center for Technology Transfer Koroška cesta 160, Maribor, Slovenia and Innovation bojan.cudic@um.si Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia spela.stres@ijs.si ABSTRACT The Digital Innovation Hubs (DIHs) in Europe are created to support the digital transformation of small and medium enterprises (SMEs). The network of DIHs is in the process of establishing throughout Europe. However, the work of DIHs is not sufficiently investigated neither in developed nor developing countries. In the Western Balkan region (the WB-5), there are 24 registered DIHs, but only five of them are fully operational. Throughout the survey, the authors investigated the WB-5 DIHs and compared their performance with their EU-28 counterparts. The survey results and interviews with the WB-5 DIHs indicate a lower level of their specialization and suggest that they failed to support the digital transformations of local businesses. They also have a great potential to improve cooperation among industry, academia, and governments in the WB-5 countries and between the countries. KEYWORDS Digital Innovation Hubs, Business Support Organizations, Small and Medium Enterprises, Quadruple Helix Model of cooperation, developing countries. 1 276 Technology Transfer as a Unifying Element in EU Projects of the Center for Technology Transfer and Innovation Prenos tehnologij kot povezujoči element EU projektov na Centru za prenos tehnologij in inovacij Duško Odić Špela Stres Center for Technology Transfer and Innovation Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia dusko.odic@ijs.si spela.stres@ijs.si ABSTRACT how our projects align to a technology transfer pipeline on an SME’s path to innovation, and how different projects Technology transfer supports the transfer of knowledge from complement each other in creating a comprehensive innovation research institutions to industry through various mechanisms, support system for SMEs. Finally, we identify the type of project including those enabled by international project schemes. We most suited for bringing into practice collaborative research that analysed how projects, carried out within our unit, the Center for drives technology transfer’s ultimate goal, innovation. technology transfer and innovation (CTT), based on the outputs and processes developed, align to a technology transfer pipeline on an SME’s path to innovation. We also investigated how 2 METHODOLOGY different projects complement each other in creating a comprehensive innovation support system for SMEs. Projects Ten EU projects analyzed in this work (out of a total of 24) have involving voucher-based financial support of innovative been selected with the criterion of being geared towards collaboration and highest involvement of researchers emerge as supporting SMEs in gaining new knowledge and/or finding most engaging for future funding applications, with other types research and/or industrial business partners with the goal of of project nevertheless being recognized as important in focusing innovation. CTT projects not included were those related to on individual stages of innovation. Regardless of project, popularizing science and introducing scientific courses into high dedicated efforts are important for establishing strong research- school programs. National projects were not surveyed due to industry connections and enabling their continuous collaboration their different selection process. Projects that ended before after the project’s end. December 2014, and more recent projects that didn’t entail KEYWORDS sufficient involvement and therefore familiarity by one of the authors (D.O.) to enable analysis, were not included. The Technology transfer, innovation, EU projects, H2020, Interreg surveyed projects are listed in Table 1. To identify projects’ alignment to individual stages of innovation and evaluate the extent to which they incorporate 1 INTRODUCTION elements of technology transfer, we reviewed project Technology transfer supports the transfer of knowledge from deliverables, outputs, and processes developed most relevant to research institutions to industry, enabling laboratory research to innovation. progress to an industrial level, and in turn, enabling small-to- To illustrate the range of support types that the projects have medium-sized enterprises (SMEs) to innovate through offered, and to identify the type of projects most in line with collaboration with researchers. An SME can use various forms technology transfer goals, we created a simplified project of support offered by a technology transfer office, and the forms landscape wherein we distributed the projects along two of support are frequently part of a national or an international dimensions: (1) level of involvement of research institutions, and project scheme, such as European Commission’s Horizon 2020 (2) innovation stage reached by the project’s outcome, from basic and EU’s Interreg programs. CTT at the Jožef Stefan Institute has raising of awareness to concrete advanced innovative been a partner in several such projects. In this work, we analyzed collaboration. The analysis aims to identify type(s) of project towards which most efforts should be directed in future funding applications. 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 RESULTS 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). Selected project deliverables, outputs, and processes relevant to Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). innovation, are listed in Table 2. All projects lead to raised 277 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Odić, Š. Stres Table 1: EU projects surveyed. Acronym Brief description Duration Program KET4CP Supporting manufacturing SMEs with key enabling technologies 2018-2021 H2020 provided by research institutions, with the emphasis on environmentally–friendly manufacturing Central Supporting life-science-oriented SMEs and research institutions in 2012-2014 Central Europe Community finding business partners through a platform Co-Create Supporting SMEs in involving creative sectors to define new products 2016-2020 Interreg and services according to social trends Mediterranean EU-GIVE Connecting SMEs to collaborative, circular and sharing economy 2017-2019 COSME actors for increased efficiency of innovation finMED Supporting financing of innovation in green growth sectors through 2018-2022 Interreg improved delivery of policies and strategies Mediterranean IP4SMEs Supporting SMEs in defining the role of intellectual property (IP) in 2012-2014 Slovenia – Italy creating regional value through interregional IP exchange Cross Border KETGATE Supporting SMEs with access to key enabling technologies through 2017-2020 Interreg Central research equipment and services provided by research institutions Europe Open I SME Supporting SMEs in solving technical issues with the aid of researchers 2014-2016 CIP via an online tool matching technology requests with research competencies Scale (up) Supporting SMEs by setting up a hub enabling a single entry point to 2016-2019 Interreg Alpine Alps assistance in access to finance, access to talent, and access to market Space opportunities in the EU SYNERGY Supporting SMEs in finding potential innovation partners through 2017-2020 Interreg Central platforms for submitting technology challenges and enabling Europe crowdfunding schemes awareness and new knowledge gained by SMEs, as well as new include mechanisms to sustain active collaboration, such as Open processes developed at CTT to effectively support SMEs. I SME and Central Community, are those that enable However, individual projects lead to innovative collaboration to matchmaking through platforms but in absence of further varying degrees. innovation support actions they do so with lower impact. In Based on data from Table 2, we aligned the projects with a effect, they start the process by introducing potential partners but hypothetical innovation process in an SME. The relevance of leave them to carry out setting up the collaboration by selected projects at different stages of innovation (from problem themselves. to innovative solution) is shown in Figure 1. While individual Projects having the most impact in raising awareness rather projects are relevant to different stages and support technology than in producing actual collaborative development, such as transfer to different extents, most have the goal of connecting IP4SMEs, EU-GIVE, Co-Create, and Scale(up) Alps, enter the SMEs to relevant stakeholders and lead to innovative pipeline at the middle of the process (scouting and innovation collaboration. potential discovery) and are least relevant, as their impact on Since technology transfer from research to industry ideally technology transfer is most indirect. They make the potential entails participation of researchers, we analyzed the projects not partners aware of the fact that there is an opportunity for only according to the stage of innovation but also according to collaboration to be seized, but do least about creating an actual researcher involvement. Distribution of projects in relation to collaboration among potential partners. involvement of researchers – from none to full - and to role in Lastly, projects that only deal with a singular aspect of the innovation based on project results and outputs – from indirect to process can be influential in terms of that particular aspect (for direct – is shown in Figure 2. Both dimensions are descriptive example, finMED for financial support setup, IP4SMEs in IP rather than quantitative, and the landscape has been created for issues), but act out of context in terms of the innovation pipeline. illustrative purposes. From the analyses conducted, the KET4CP and KETGATE The results show that projects such as KET4CP and projects emerge as a type of project most closely in line with the KETGATE, which include operational support steps from the complete collaborative innovation pipeline, involving strong beginning till the end of the innovation pipeline (Table 2), and research participation, creating concrete connections and have important roles in innovation as well as a high level of following them through to realization of the opportunity, thus researcher involvement, emerge as having the highest potential most effective in increasing SME-research collaboration and for technology transfer. most attractive in subsequent funding opportunities. Projects with lower relevance that enter the innovation pipeline in the beginning of the innovation process but do not 278 Technology Transfer in EU Projects IInformation Society 2020, 5–9 October 2020, Ljubljana, Slovenia Table 2: Project deliverables, outputs, and developed processes most relevant to innovation, distributed based on the benefit to SMEs participating in the project. Project knowledge gained Instruments / processes developed registration on successful joint by SME platforms, submission research and of challenges, development matchmaking projects KET4CP map of European Cascade funding with evaluation and KET4SME platform yes (voucher- technology centers support process supported) Central list of Life Science Process of scouting, matching, and LifeScience Room Community companies encouraging SMEs towards open innovation Co-Create design thinking, Design thinking process for inclusion of Co-Create platform co-creation different stakeholders in traditional SME innovation process EU-GIVE map of collaborative Process of engaging researchers in economy initiatives creating innovative collaborative economy approaches finMED list of financial Process of including intangibles into instruments and financial intermediaries’ (as banks) loan mechanisms capability criteria evaluation IP4SMEs importance of IP Process of auditing SMEs towards discovery of innovation potential KETGATE available research Process of scouting, matching and KETGATE platform yes (voucher- equipment at JSI financially supporting research and SME supported) partners with cascade funding Open I SME Process of scouting, motivating research OpeniSME platform yes experts to become available to SMEs for industrial counseling Scale (up) list of Slovenian Process of scouting for expertise, Scale(up) Alps Alps startup ecosystem supporting creation of SME (spinout), support ecosystem actors matching its needs to the support system and allocating relevant support – it being a part of a group of companies with similar needs SYNERGY list of crowd Process of determining entities suitable SYNERGY platform innovation for crowd sourcing, based on relevant initiatives criteria, and of matching them with suitable crowd innovation initiatives innovation process. Consider a hypothetical Company that agrees to participate in all listed projects. The Company benefits 4 DISCUSSION from all aspects of innovation (Table 2), and ends up having a In this work, we analyzed selected projects in terms of their complete set of services that are in fact part of technology contribution to technology transfer. It should be noted that there transfer. It starts by attaining basic knowledge about intellectual is a distinction in terms of relevance to individual stages (Figures property and innovation management (IP4SMEs), its position 1, 2), however, the KET4CP and KETGATE projects emerge as among other SMEs in a given sector (for example, life sciences; a type of project most closely in line with the complete Central Community) and familiarizes itself with the landscape of collaborative innovation pipeline. On the other hand it should be collaborative economy (EU-GIVE), available technology centers emphasized that each project has its place in the overall (KET4CP) and research equipment (KETGATE), startup support 279 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Odić, Š. Stres (Scale(up) Alps) and crowd innovation initiatives (SYNERGY). just a single innovation stage, can represent an added value for The Company then proceeds to learn about the design thinking an SME, through providing knowledge about a specific subject, approach in innovation and the possibilities to connections with thereby allowing other projects to offer support with the benefit the creative sector (Co-Create), and gets an opportunity to of that gained knowledge. explore a host of national and international research and/or Low-level- and mid-level-impact projects are thus important business partners via various online platforms (KET4CP, Central since they provide information and knowledge for companies Community, Co-Create, KETGATE, Open I SME, SYNERGY) that makes them suitable as target beneficiaries for further forms or through attending matchmaking events (KETGATE). The of support down the pipeline. For example, a highly relevant Company receives a comprehensive informative guideline on the project, such as KETGATE, may not itself include in-depth possibilities of financing (finMED), and may enter into research analysis of mechanisms for defining intellectual property and development collaborations (Open I SME), with the (otherwise provided by IP4SMEs) or in-depth analysis for setting possibility of additional financial support by vouchers up familiarity with available financial instruments (otherwise (KETGATE, KET4CP). Thus, any given project, even if filling provided by finMED). However, as both are useful traits in signing cooperation agreements and looking for continued financing of pilot projects established within KETGATE, their execution provided grounds for setting up a fully-fledged innovation pipeline support. An SME thus more efficiently benefits from KETGATE services, having previously received services from IP4SMEs and finMED. Ranking of the projects (Figure 2) is therefore not a reflection of their quality or relevance but of their position within the complete support to technology transfer. The processes developed within individual projects, from discovering innovation potential (e.g. IP4SMEs) to cascade funding of research and development projects (e.g. KET4CP), culminated in the development of a comprehensive SME innovation support system at the CTT that is flexible and adaptable to a company’s level of innovation and particular Figure 1: Relevance of selected projects at different stages needs. The projects proved important in strengthening of the of innovation (from problem to innovative solution) in an technology transfer pipeline by developing ways of engaging SME. various stakeholders, their auditing, developing of matchmaking platforms, and protocols for facilitating collaborative research, including voucher-supported cascade financing schemes. It is the long-term goal of EU projects to not only develop processes for comprehensive SME support but also act as stepping stones for achieving continuing innovation activities between research / industry partners and building strong and inspirational success stories after the projects’ closure. This is particularly important in the light of the fact that mechanisms established during a project, such as platforms, are often inactivated once the project is finalized. Efforts are in principle invested towards sustainability of platforms after the project’s end, but platform maintenance is rarely guaranteed and/or requires dedicated funding from other sources. It is therefore important to enter into a project with a clear vision of its benefits Figure 2: Distribution of projects in relation to involvement and strong dedication to reaching relevant goals. Understanding of researchers, and to role in innovation based on project the role of a specific project in the innovation pipeline is crucial results and outputs. Note that the numbers indicate a relative to achieve this. Previous experience has shown that prudent position of the project based on project design rather than any attitude towards engagement with project target audience (from quantitative measure, and are provided for illustration purposes identifying relevant companies, identifying the right only. Numbers on the y axis indicate no involvement (1), correspondent individuals, to right type of motivation) can lead potential involvement (2), or full involvement (3). Numbers on not only to fruitful project collaboration but also to continued the x axis indicate stages in innovation pipeline as follows: 1 – research-industry collaboration outside of the project. gaining knowledge about IP and innovation management, 2 – Finally, we estimate that the culmination of the efforts gaining knowledge about design thinking, collaborative described in this article will be seen on one hand within the economy, or financial instruments 3 – registration on platforms, European Innovation Council of the Pillar 3 in Horizon Europe, 4 – matchmaking, 5 – access to equipment or services, 6 – joint in particular in the creation of new high-tech-based companies research and development projects. In this type of display, the stemming from Public Research Organizations. But the projects located in the upper right part are most suited for contribution of this myriad of projects should also be seen as supporting technology transfer between research and industry. important within further financing of the European Commission 280 Technology Transfer in EU Projects Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia in the form of cascade funding, available to connect in massive websites, wherever still active as of 30.9.2021, to individual numbers SMEs and the academia. Such numerous collaboration projects analyzed: is required to build trust, to execute the contract / collaborative research and to improve the technological absorption capacity KET4CP - https://www.ket4sme.eu/ ever so needed to be improved in some parts of Europe, ours Co-Create - https://co-create.interreg-med.eu/ EU-GIVE - https://www.eugiveproject.eu/ included. finMED - https://finmed.interreg-med.eu/ IP4SMEs - http://www.ip4smes.eu/ KETGATE - https://www.interreg-central.eu/Content.Node/KETGATE.html 5 REFERENCES Open I SME - https://www.openisme.eu/ Scale (up) Alps - https://www.alpine-space.eu/projects/scale-up-alps/en/home This work is a result of experience- and output-based analysis SYNERGY - https://www.interreg-central.eu/Content.Node/SYNERGY.html and does not include references as such. Below are given links to 281 Proof of Concept cases at the Jožef Stefan Institute in 2020 and 2021 Marjeta Trobec Špela Stres Center for Technlogy Transfer and Innovation Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana, Slovenia Jamova cesta 39, Ljubljana, Slovenia marjeta.trobec@ijs.si spela.stres@ijs.si ABSTRACT improving reputation at all levels in its own tech-transfer process [10]. Auerswald and Branscomb write that the most vital The development of economy and society is inextricably linked technology commercialization phase occurs between invention to inventions and innovations from public research organisations. and product development when commercial concepts are created Technology transfer offices identify potentially suitable and verified and the best appropriate markets are defined. The technologies for commercialization and support researchers in PoC phase has a funding gap, caused by information and the field of intellectual property (IP), commercialization etc. motivation asymmetries and institutional gaps between the However, financial resources are necessary for the further science, technology and enterprises [4]. development of the identified technologies in order to reach Such a gap is primarily due to the “embryonic” nature of the higher levels of technological maturity. In EU, UK, USA and research organization-generated inventions, which tend to elsewhere the so-called Proof of Concept (PoC) funds are operate at the frontier of scientific advancements, thus involving available on institutional, regional, national and international considerable risks associated with their subsequent validation, level. In Slovenia till 2021 we only had four PoC funds, all of them were institutional / internal, one of them the Jožef Stefan industrialization and commercialization [5]. The time required to transform discoveries into products and the vast amount of Institute PoC, created as the first one already in 1996. This paper focuses on the eleven Proof of Concept cases from the Jožef resources needed to pursue the required development constitute a mix of high uncertainty and negative cash flows that decrease Stefan Institute that were financially supported in 2020 and 2021. investment incentives and limit opportunities to secure funding. We have shown their individual characteristics and the expected This pattern is especially pronounced in science-based sectors benefits for the projects due to the received PoC funding based like life sciences, biotechnology etc. [5]. The gap and PoC on the project applications. The projects are dispersed across positioning in regards to the stage of development and funding Technology Readiness Levels (TRL) of the so-called Valley of sources is also shown in Figure 1. death (TRL 3-7). Further developments based on the received funding are in line with their current and expected TRLs – the most common are validation in the laboratory and / or in the relevant environment, prototype demonstration and testing. We have also made an overview of possible future scenarios for them on the basis of the expected CEETT Proof of Concept fund. KEYWORDS Proof of Concept, Entrepreneurship, Innovative financing, Technology Transfer 1 INTRODUCTION A Proof of Concept phase (PoC) is a research practice and Figure 1: Representation of PoC in regards to Stage of serves as an instrument of knowledge construction in an development [5] individual study and helps to build further understanding of certain objects, data, metrics, apparatus, processes, materials. A The lack of dedicated funding and support to help PoC research is composed from a set of activities (i.e. actions, inventions from public research institutions to mature to the stage movements, analyses, simulations, techniques, tests, etc) for the at which they are market and investor ready represents a major assessment, understanding, validation and exploitation of, and obstacle to effective knowledge transfer. Different support the learning about particular research object [1]. A PoC is used mechanisms address these gaps, at general policies level as well “to prove a concept through a practical model” [2]. The PoC as on the level of specific, local initiatives, including research phase is in research institutions in terms of technology transfer organizations funds [6, 7]. considered as critical for the success of both licensing and the PoC funding programs are mechanisms that combine creation of spin-off companies [3]. The POC therefore increases money, expertise and training to help new inventions and technology transfer office (TTO) chances of a larger percentage discoveries emerge and to demonstrate their technical and of the income stream from the commercialization of innovations commercial feasibility. Such funds can appear under different so that it can fulfil some main tech-transfer goals, that is, return names like PoC funds, proof-of-principle funds, translational on investment, job creation, start-up creation, IP licensing and funding, pre-seed funding, verification funding, maturation 1 282 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Trobec et al. programs, innovation grants, ignition grants [5]. No matter the 2.2 Jožef Stefan Institute PoC calls in 2020 and name they all have common objectives and characteristic, shown 2021 [8] also in Table 1: to evaluate the technical feasibility and Calls for funding of projects are intended to help move commercial potential of early-stage research ideas and projects starting from at least the TRL 3 towards higher TRLs. technologies and to demonstrate their value to potential industrial The call is open for JSI researchers with a status of at least 50 % partners and investors. Under the programs, the employment at JSI. researcher/research team gets capital and assistance across a broad spectrum of areas, such as intellectual property rights, business plan development, market studies, networking etc. The Table 2: Approved Jožef Stefan Institute projects in 2020 ultimate goal is to advance the technology to a point at which it and in 2021 [9] can be licensed to an external industrial partner or a start-up to Y. Title JSI research be created to attract the interest of investors in later stages of department, development [5]. project leader 2021 Upgrading the Open Computer Systems Clinical Nutrition (E7), Koroušič Table 1: Main characteristics of PoC funds [5] Platform with a mobile Seljak application PoC Programs 2021 Data gap analysis for Advanced Objective biocide regulatory Materials (K9), Evaluate and support the technical feasibility protocol of Vukomanović and commercial potential of early stage apatite/gold/arginine as technologies generated by public research novel antimicrobial agent organizations Focus of Primarily projects by individual researchers or 2021 Connecting with industry Nanostructured investment research teams partners to build an Materials (K7), Investments Typically grants, but other forms are possible automated laboratory Suhadolnik typology (i.e., loan, repayment schemes) Investment Pre-seed stage (typically before company 2021 Libra wireless pocket-size Computer Systems stage formation) kitchen scale (E7), Blažica As mentioned in the paragraph above, PoC funding schemes 2021 Multifunctional coatings Physical and for the protection of metal Organic can be created internationally and nationally. In Slovenia, we do surfaces Chemistry (K3), not have a national PoC funding jet. Some public research Rodič organizations have therefore developed their internal schemes. These schemes are available at the National Institute of 2020 Apparatus for ultra-fast Experimental Chemistry, University of Ljubljana, University of Maribor, and fluorescence lifetime Particle Physics at the Jožef Stefan Institute. measurement (F9), Seljak 2020 Ceramic capacitive Electronic 2 PROOF OF CONCEPT FUND AT THE pressure sensor with Ceramics (K5), JOŽEF STEFAN INSTITUTE doubled pressure Malič sensitivity 2.1 Legal framework 2020 Scaling of the synthetic Gaseous method of electrochemical Electronics (F6), The Jožef Stefan Institute (JSI) has in 1998 implemented electrodes Filipič the Internal Employment-Relate Inventions Act. At the same time, the innovation fund of the institute has been created. 2020 Predicting exacerbation of Intelligent The goal of the innovation fund is to enable the projects to chronic heart failure based Systems, (E9), increase their technology readiness level (TRL), increase their on telemedicine date Gradišek maturity and attraction towards potential customers, increase their suitability for external calls for proof of concept funds, and 2020 Preparation of synthetic Electronic establish partnerships with the industry. blood substitute for testing Ceramics (K5), The innovation fund of the Center for Technology Transfer medical equipment Kuščer and Innovation (CTT) at the institute is filled only from the part of the incomings from the commercialized intellectual property 2020 CAUSALIFY – Artificial Exemplary in the Intelligence (E3), of the JSI. Funds are being distributed through internal JSI calls dynamics of world events Grobelnik prepared and managed by CTT based on a detailed internal act. In this work, we will focus on the 2020 and 2021 cases. 283 Proof of Concept cases at the Jožef Stefan Institute in 2020 and Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 2021 The purpose of the call is to: - define the technology to the extent that it is suitable for the official acceptance of the invention / technical improvement / registration of the intangible asset at the JSI; - help with application for a larger concept verification and validation call; - help projects to a higher TRL in order to increase the attractiveness of technology for potential customers or to use technology in a JSI spin-off; - establish long-term partnerships with the industry. Expected results for the approved / selected projects: - upgrading their TRL and therefore increasing the value and attractiveness of the technology; - higher possibility of selling or licensing the innovation; - creating links with industry partners; Figure 2: Starting and expected TRL of the JSI PoC cases - getting ready to apply to a bigger tender for testing and validating the concept and Based on the info from the applications, all the projects will - participation in the selection of the best invention / innovation be targeting world-wide market. Five of them will develop from public research organization at the International solutions for niche markets, other six are targeting wider Technology Transfer Conference. audience – numerous users. It is important that six of the projects are trendsetters, the rest are developing solutions for current “hot” In 2020 six projects were approved and in 2021 five projects. topics like environmental legislative requirements, health issues of the population, ageing population, solutions for non-animal Each PoC project has its TT guardian in the Center for tests in pharmacy, energy consumption. Six projects have little Technology Transfer and Innovation. The allocated TT experts competitors and their competitive advantages are high. It is are guiding the research teams in terms of IP, further financial extremely interesting to observe where the science has its possibilities, connecting with industrial partners, project expected effect. This is shown in Figure 3. The Technological preparations, technology assessments etc. areas are the ones of the four broader activities of the Institute (Physics, Chemistry and Biochemistry, Electronics and Information Technologies, Reactor Engineering and Energy). A 3 ANALYSIS OF PROOF OF CONCEPT particular Technological area has been defined based on the PROJECTS FROM THE JOŽEF STEFAN research department of the applying team. The expected impacts INSTITUTE / the targeted markets are listed as they were identified by the We have looked at the approved projects from different teams. points, as a source taking project applications: - Current and expected TRL; - Time needed to reach the expected TRL; - Technological background of the projects and the markets they are targeting; - The intellectual property protection of the projects; - The type of the market the researches are targeting, trends on the market and the competition; - Spin-out vs licensing plans; - The benefits of the PoC financing for the project development. Figure 3: The Jožef Stefan Institute PoC projects and their As it can be seen from the Table 2, the projects are from three expected effect on different markets different areas of the Jožef Stefan Institute: - Physics (2 projects) - Chemistry and Biochemistry (5 projects) Three out of eleven teams are seriously considering the - Electronics and Information Technology (4 projects). option of establishing a spin-out company. The rest wish to license the technology. The majority of projects has been at TRL 3 (6 projects) when The main expected benefits for the projects due to the applying for funds, 3 were at TRL 4, one at TRL 5 and one at received financial resources are described below. To assure TRL 7. In the next 12 months the TRL of all project will with the anonymity, the order of the projects below is not the same as in received financial help rise for at least one TRL. In two projects Table 2: the rise would be event from TRL 3 to TRL 7 as shown in the P1: start test cooperation with industrial partners, Figure 2. The expected TRL is not known yet in four cases. construction of a prototype, testing a prototype, preparation of 284 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Trobec et al. detailed plans for the manufacturing of critical components of the - The key market will be defined. All activities (research, device, applications to EU projects. development, financing, promotion) will follow the P2: analysis for regulatory protocol. defined key market needs. P3: designing a mobile application, user interface design, - The research towards the markets that are not promising user testing of the application. will be abandoned. P4: running a trial with early adopters, improving the user - Further financing will be acquired also from external experience of the demo, preparation of promo material, lowering sources (relevant for all the projects). the production costs. P5: experimental / test cooperation with an industrial partner, pilot transfer of the solution to the industry, IP protection. 4 CONCLUSIONS P6: developing industrial prototype and user interface, Through the calls in 2020 and 2021 the main lessons learned testing the prototype. for the the Center for Technology Transfer and Innovation team P7: developing a prototype, testing the prototype with the were: potential users. - It is necessary to have PoC funds available at P8: scaling-up the existing prototype, testing it for one of the institutional / JSI level as well as on national level. possible applications, developing a method for simplifying the operating procedure. - The funds are welcomed by JSI researchers since the P9: pilot testing, improvements needed for clinical testing, application is simple, the results are available soon and promotion. the support regarding the project funding and reporting P10: component validation in a laboratory environment, IP is in-house. protection, preparation for suitable project calls. P11: developing protocols for scale-up in the laboratory - CTT gets through the application additional insights environment, validation in the relevant environment. into the research activities of research departments and can offer its assistance to new research teams. We have grouped the main expected benefits into four most common areas: 1. Developing a prototype, 2. Testing a prototype - Besides the funds that the teams get, it is necessary that in a lab, 3. Testing a prototype with industry / potential users, 4. CTT supports the projects also with the guidance on IP, Preparing a support documentation i.e. documentation to fulfil further financial possibilities, connecting with industrial the legislative requirements, IP protection documentation (patent partners, project preparations, technology assessments applications and similar), project applications, communication / etc. commercialization promo material etc). As it is shown in Figure 4 in seven projects researchers are developing a prototype, in four - Market assessments and defining the target market are cases prototype will be tested in a lab, in nine projects prototype crucial for further development. In this step feedbacks will be tested with industry or other potential users, seven sets of from business sphere are priceless. needed support documentation will be prepared as well. - The teams are in most cases composed from natural sciences and engineering experts. It is necessary to connect them with experts from human- and economics sphere as soon as possible in order to focus further development based on market needs. In July 2021 the Central Eastern European Technology Transfer (CEETT) platform has been launched by the European Figure 4: The Jožef Stefan Institute PoC projects and Investment Fund (EIF) together with Slovenian SID bank and the expected outcomes of project Croatian bank for reconstruction and development (HBOR). The €40 million will be invested in venture capital funds and finance With the rise of TRLs it is expected that the projects will gain innovative technological research projects and the protection of also on the following areas: the intellectual property of research organizations in Slovenia - The teams will get additional team members with the and Croatia (other Central Eastern European countries are not expertise in business plan development, marketing, included). technology transfer, certification, etc (relevant for all The eleven JSI PoC projects have gained with JSIs’ internal the projects) or they will licence the technology to a PoC funding in the past two years an excellent basis and will be company that will take over the future product / service ready for CEETT funding as soon as it is available. and launch it on the market. - Intellectual property (IP) will be better defined, IP REFERENCES management plan will be developed, relationships [1] between researchers themselves and with host Antonio J. Rodrigez Neto, Maria M. Borges, Licinio Roque, 2018, A Preliminary Study of Proof of Concept Practices and their Connection with organizations will be arranged. Information Systems and Information Science. ACM DL: https://dl.acm.org/doi/abs/10.1145/3284179.3284226. [2] Iúri Batista Teles. 2017. Arcano: Um Sistema de Resposta Pessoal Mobile para Ambientes sem Conexão com a Internet. UFS, 74. 285 Proof of Concept cases at the Jožef Stefan Institute in 2020 and Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 2021 [3] Catarina Maia, Joao Claro, 2012, The role of a proof of Concept Center in a university ecosystem: an exploratory study. The Journal of Technology [7] Rasmussen E. and Soreheim R. (2012). How governments seek to bridge Transfer 38(5), DOI:10.1007/s10961-012-9246-y the financing gap for university spin-offs: Proof-of-concept, pre-seed, and [4] Philip E. Auerswald & Lewis M. Branscomb, 2003, Valleys of Death and seed funding. Technology Analysis and Strategic Management, 24(7), pp. Darwinian Seas: Financing the Invention to Innovation Transition in the 663–678 United States, [8] Jožef Stefan Institute internal acts and calls https://link.springer.com/article/10.1023/A:1024980525678 [9] Info about the recipients of PoC calls: [5] Munari F, Sobrero M, and Toschi L. (2014b). Financing Technology http://tehnologije.ijs.si/?page_id=124 Transfer: An assessment of university-managed “proof-of-concept [10] Alunni Andrea (2019): Innovation Finance and Technology Transfer, programmes” in Europe. Paper presented at the Annual Conference of the https://www.routledge.com/Innovation-Finance-and-Technology- EPIP Association (European Policy for Intellectual Property), Bruxelles, Transfer-Funding-Proof-of-Concept/Alunni/p/book/9780367671839 September 2014. [6] Miörner, J., Kalpaka, A., Sörvik, J., & Wernberg, J. 2019. Exploring heterogeneous Digital Innovation Hubs in their context. Seville: Joint Research Center. 286 European Industrial Strategy - a great opportunity to strengthen the role of technology transfer offices Levin Pal France Podobnik Špela Stres Center for technology transfer and Center for technology transfer and Center for technology transfer and innovation innovation innovation Jozef Stefan Institute Jozef Stefan Institute Jozef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia levin.pal@ijs.si france.podobnik@ijs.si spela.stres@ijs.si ABSTRACT KEYWORDS The latest European (EU) industrial strategy of the EU European Industrial Strategy, Enterprise Europe Network, Commission (EC) envisage increasing the innovation of small to Technology Transfer, Industrial ecosystems, Sector groups, medium-sized enterprises (SMEs) with the emphasis on the BioChemTech, biotechnology, chemistry double transition to a green and digital economy. The Enterprise Europe Network (EEN), which operates within the EC and its 17 sector groups will be involved in achieving these goals. 1 INTRODUCTION Optimized functioning of SMEs and PROs in the innovation The EU Industrial Strategy of EC from March 2020 focuses ecosystem is extremely important and technology transfer (TT) mainly on the dual transition to a green and digital economy [1] will play a key role here. aiming to increase the competitiveness of EU industry and This paper presents the interactions between sector groups and enhancing the Europe’s open strategic autonomy. industrial ecosystems on the example of the BioChemTech sector The EU industrial strategy defines 14 industrial ecosystems group as it is important to understand them in order to act in line (Figure 1). The primary aim of the new industrial strategy is to with the new EU strategy. A database of EEN profiles, namely increase the innovativeness of SMEs within these industrial all profiles marked for dissemination in the BioChemTech group ecosystems. According to the Single Market Programme (SMP were analysed and the technology, market and client outreach COSME) the research and TT are considered as a core expertise based on real business and technological offers and requests is to ensure efficient support for SMEs by providing support to thus presented in this paper. The BioChemTech sector group has industry-academia cooperation including the provision of the most direct applications in Health (30%), Digital Industries technology expertise and technology infrastructure services to (10%), Agri-Food (9%), and Renewables (4%) and many indirect facilitate lab testing, validation and demonstration [2]. synergies with the same industrial systems in the areas of Industrial Products, Genetic Engineering/Molecular Biology and Consumer-Related Products. The sector group has already established contacts with clients in the field of Digital industries (5%) and Renewables (5%), which will need to be maintained, reinforced and upgraded in cooperation with other sector groups to ensure effective digitalization and sustainability of companies. The results reveal a unique opportunity for TT offices (TTOs), as the future demand for digital and environmental solutions should increase in companies. TTOs should catch this wave and thus overcome the usuall bottleneck of disproportionately large share of technology supply compared to technology demand as presented in this paper. Figure 1: Industrial ecosystems according to European 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 Industrial Strategy [1]. 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 EEN, which is operating under the EC has established 17 be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Sector Groups - the groups of network partners, who commit to © 2021 Copyright held by the owner/author(s). work together in order to meet the specific needs of their clients operating in a particular sector [3]. The following sectors are 287 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia L. Pal et al. covered by the groups: Aeronautics, Space and Defence, 3 RESULTS AND DISCUSSION Agrofood, BioChemTech, Creative Industries, Environment, Healthcare, ICT Industries and Services, Intelligent Energy, 3.1 Technology outreach Maritime Industry and Services, Materials, Mobility, Nano and BioChemTech sector mainly covers the technological field of micro technologies, Retail, Sustainable Construction, Textile and biological sciences (39%) and industrial technologies (26%) Fashion, Tourism and Cultural Heritage and Woman mainly in the fields of biotechnology, chemistry and materials, Entrepreneurship [3]. which is not surprising (Figure 2). Within biotechnology and It is difficult to directly link the mentioned sectors to chemistry, there are some cross-cutting areas with other sectors. industrial ecosystems shown at Figure 1. For example, The largest overlaps are in the areas of healthcare (19% of biotechnology and chemistry and many others are not listed as profiles), agri-food (10% of profiles), environmental protection relevant industrial ecosystems. The reasons for the thematic (8% of profiles) and ICT (8% of profiles). Smaller overlaps are mismatches between industrial ecosystems and sector groups also in the field of micro and nanotechnologies (2% of profiles) vary. Some sector groups are based on the political agenda or are and advanced materials (7%) including textile materials (Figure covering different services. However, the majority of sector 2). groups is based on technology areas as defined by ATI - Advanced Technologies for Industry (former KET - Key Enabling Technologies) [3] meaning that the sector groups were established to transfer the advanced technologies from relatively narrow scientific fields to a relatively wide spectrum of industrial ecosystems. Determination of how the technological sectors are related to industrial ecosystems is important to ensure the optimal functioning of SMEs and PROs in the innovation ecosystem according to the EU industrial strategy [1]. The information should benefit to Jozef Stefan Institute (JSI) as a PRO and ATI Technology Centre [3] as well as the partners of Slovenian EEN consortium [2] and Consortium for Technology Transfer from PROs to economy (KTT) [4] coordinated by JSI. The EEN and KTT community is indeed acting on various relations: SME- SME, PRO-PRO, PRO-SME and SME-PRO In this paper, we describe an example of solving the above issue from the perspective of technology, market and client coverage in case of BioChemTech sector. We further discuss the opportunities for TTOs brought by the new EU industrial strategy and how TTOs can use the given situation to consolidate their role and importance in the innovation ecosystem. 2 METHODOLOGY The profiles published on the EEN website (https://een.ec.europa.eu/partners) were exported using the following filters: profile date: “from 1 June 2020 to 20 May 2021”; partners: relevant sector groups: “BioChemTech”. The obtained 199 results were exported into the Microsoft Excel worksheet (registration and login to EEN intranet is required to Figure 2: The incidence of EEN technology code easily export the profiles). The technology, market and NACE descriptions and the representation of other cross-cutting codes with corresponding descriptions were further analysed sectors covering the same technology areas. (each profile has a maximum of five technology, market and NACE codes). The incidences of different individual codes were The field of Biotechnology is therefore interdisciplinary, calculated. The most relevant sector groups or industrial which partly answers the question of why biotechnology and ecosystems were attributed to the sets of most frequent codes chemistry are classified as individual industrial ecosystems in occurring within 199 profiles and graphically displayed at Figure new EU Industrial Strategy. Sectors such as biotechnology, 2, Figure 3, and Figure 4. The “Others” group within individual nanomaterials, advanced materials etc. were established on the sub-areas of Figures 1 – 4 represents the sum of various different basis of ATIs, which are interdisciplinary by their nature and codes that each individually covered less than 1% of the overall applicable in multiple industrial ecosystems simultaneously. BioChemTech area. The number of business and technology profiles presented at Figure 5 is based on the same set of exported data. Analyses were performed in May 2021. 3.2 Market outreach This interdisciplinarity can also be observed in Figure 3 representing the main markets of BioChemTech sector. Medical 288 European Industrial Strategy - a great opportunity to strengthen Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia the role of technology transfer offices and Healthcare and Industrial products account for more than one Renewables (5% of clients from profiles), which only need to be half of the market, while other applications belong to various strengthened. other industrial ecosystems, from Agri-food to Renewables and Digital Industries. Interestingly, there are a number of products 3.3 Client outreach in the ICT field intended for biotechnological applications and Manufacturers of pharmaceutics, food and chemical products their development takes place hand in hand together with the ICT represent the largest share, 35% of clients of the BioChemTech and BioChemTech experts as the knowledge has to be exchanged sector group, while the representatives of Professional, scientific between these distinct groups of experts in order to build and technical activities represent only a slightly smaller share, properly functioning medical/health/chemistry related computer 27% of clients (Figure 4). Almost equal representation of applications. The said expert knowledge is intertwined in the industrial partners and PROs should be considered as an unique fields of bioinformatics, assisted living facilities, electronic opportunity for TT linking the technology demand of companies laboratory books, software for clinical study analyses, dietary with technological supply of PROs, which is in line with the needs, automation of laboratories, equipment management expectations of the latest Single Market Programme [2]. software etc. Figure 4: The incidence of NACE code descriptions and the representation of corresponding industrial ecosystems. 3.4 Opportunities for Technology Transfer Figure 5 shows that there is a disproportionately large number of technology and business offers as compared to the number of requests. It is precisely this disparity that represents a bottleneck disabling the establishment of business and technological cooperation through matchmaking of supply and demand in commercial databases. Figure 3: The incidence of EEN market code descriptions and the representation of corresponding industrial ecosystems. It makes sense to maintain the established synergies with various industrial ecosystems, especially Healthcare and Agri- food in the upcoming years. However, from a strategic point of view, it is necessary to strengthen the integration with the Renewables and Digital industries in line with the new EU Industrial Strategy, which focuses most on digitalisation and sustainability of all industrial ecosystems [1]. For the mentioned integration, the BioChemTech sector group already seems to Figure 5: Number of profiles based on the profile type, have established connections with the clients of the industrial organization type and number of employees in industry. ecosystems Digital industries (5% of clients from profiles) and 289 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia L. Pal et al. The technology offer of companies is higher as compared to line with EU Industrial Strategy [1] and the latest EU Single the PROs at least in the BioChemTech sector. However, 58% of Market Programme [2]. industrial clients in the segment are Micro Companies having less than 10 employees (Figure 5) and they are mostly start-ups Low technological demand (Figure 5) represents a bottleneck for and spin-offs (data not shown). Therefore, the knowledge successful TT and this paper suggests two ways of approaching included within the high number of technology profiles is coming this problem for the TTOs in the upcoming years: predominantly from PROs. Analogously, the high number of (i) active seeking of the technological demand from companies business offers is coming from companies due to their desire to at both national and international level and matchmaking the promote their products. The authors of this paper cannot find a demand of companies with the offer of PROs; good explanation for the low proportion of technology requests, (ii) introducing the digitalisation and sustainability to every except that they see it as a great window of opportunity for TTOs. company, which should in itself increase the technological TTOs should play a key role in solving this problem by demand of companies lacking of appropriate skills in the field of increasing the amount of technological requests gained from the digitization and environmental protection. companies. Direct marketing activities that lead to well identified topics of research with the companies by TTOs should be The current situation is therefore a unique opportunity for TTOs considered as a tool to bridge the above described lack of that should be more adequately trained for: technological demand. For example, the direct marketing (i) active searching and identifying the topics and research activities of Center of Technology Transfer and Innovation problems for further development and optimization of (CTT) at JSI include direct contacting of companies, promotion production processes and services in companies; of technologies at brokerage events and other events, and (ii) establishing research and development collaborations physical visiting of companies: In the years 2017-2020 CTT between the companies and PROs based on the interest of visited 112 companies and identified 418 topics for cooperation companies; with JSI. As a result of direct marketing CTT contributed to 35 (iii) seeking for finance in the framework of national and EU license and 67 research and development agreements in years projects for digitalization and sustainability. 2017-2020. A relatively small proportion of the identified themes that lead to concrete agreements is best explained by well-known 5 ACKNOWLEDGEMENTS model of technology transfer funnel [6]. However, the TT funnel Colleagues from BioChemTech sector group of the EEN and the should not be taken as an excuse for not having successful European Innovation Council and SMEs Executive Agency are commercialization cases at TTOs, but rather as an incentive to greatly acknowledged for a constructive discussion on the increase the quantity as well as the quality of company visits and industrial ecosystems and their relations to various sectors. The identified topics [6]. colleagues from CTT are acknowledged for taking actions and On the other hand, in the future, the need for digitalization improving the overall CTT results. and sustainability is likely to arise in companies, which should have a positive impact on technology demand for digital and REFERENCES environmental solutions and thus positively influence the [1] European industrial strategy. 2020. European Commission. [internet]. imbalance of technology supply and demand. TTOs, as experts [cited on September 24th] in industrial ecosystems and technology sectors, should be able https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital- age/european-industrial-strategy_en to help companies and PROs to establish collaboration and help [2] Single Market programme. 2021. Enterprise Europe network. [internet]. especially SMEs to obtain national and EU funding. [cited on September 24th] https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- 2027/smp/wp-call/2021/call-fiche_smp-cosme-2021-een_en.pdf (24.9.2021) 4 CONCLUSIONS [3] Enterprise Europe Network. 2021. European Commission. [internet]. [cited on September 24th] Advanced Technologies for Industry (ATIs) areas are strongly https://een.ec.europa.eu/ intertwined (Figure 2) and have applications in several different [4] Advanced Technologies for Industry. 2021. European Commission. [internet]. [cited on September 24th] markets (Figure 3) and consequently appear in several industrial https://ati.ec.europa.eu/ ecosystems simultaneously (Figure 4) as shown on the case of [5] KTT - Consortium for technology transfer from public research organizations to economy in years 2017-2022. Republic of Slovenia, BioChemTech sector. Ministry of Education, Science and Sports, European Regional Development Fund [internet]. [cited on September 24th] http://jro-ktt.si/ The emphasis on digitalization, sustainability and environmental [6] Tan. S., 2021. The alternative view of scaling up regional knowledge protection can only be established through active cross-sectoral transfer output. ASTP – Association of Knowledge Transfer Professionals. integration, with the transfer of technologies from Digital [internet]. [cited on September 24th] https://www.astp4kt.eu/about-us/kt-news/an-alternative-view-of-scaling- Industries and Renewables related areas to other industrial up-regional-knowledge-transfer-output.html ecosystems and the TTOs should play a crucial role, which is in 290 Knowledge generation in citizen science project using on- line tools: CitieS-Health Ljubljana Pilot Jure Ftičar Miha Pratneker David Kocman† Department of Environmental Department of Environmental Department of Environmental Sciences Sciences Sciences Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia jure.fticar@ijs.si miha.pratneker@ijs.si david.kocman@ijs.si ABSTRACT where citizens are invited to take part in all the phases of research activities [4]. In this contribution, we describe the development of a tool for Many potentials of environmental citizen science are data visualization and treatment designed for the participants recognised by scientific community, among others generation of involved in the citizen science (CS) activities in Ljubljana, new knowledge and facilitation of (in-depth) learning at the Slovenia, as part of the CitieS-Health H2020 project dealing with individual level [5]. However, it is necessary to take into account environmental epidemiology. The tool, a web application that that volunteers in CS projects have a very different prior enables volunteers to autonomously collect, edit and analyse the knowledge, as well as socio-economic background and education, data, was designed to encourage their involvement in discovering and are usually inexperienced in analysing and processing the and generating new knowledge, together with professional data gathered by themselves. Their motivation to participate can researchers and according to the principles of co-creation. Some also vary [6]. Thus, appropriate specific tools tailored to the preliminary lessons about the tool applicability and usability, capability of the individual user are needed to empower and including potential intellectual property aspects, are discussed. facilitate their integration into the process of knowledge generation. In this paper, we present some preliminary results KEYWORDS and describe an example of creating a web application designed Citizen science, co-creation, knowledge generation for the volunteers to independently process their own data gathered in Ljubljana, Slovenia, under the CitieS-Health H2020 project on noise exposure and health. 1 INTRODUCTION In recent years, CS is on the rise and there is a growing body of literature on various aspects of CS, its role and increasing 2 METHODS importance in scientific research [1]. There is no single definition of CS as taxonomy depends on the type and level of involvement 2.1 CitieS-Health Project and Ljubljana Pilot of participants, but in general citizen science defines the practice Activities where non-professionals take part in the scientific research Activities reported in this contribution were conducted within the process. Such an approach brings many new opportunities, such frame of the Cities-Health, EU Horizon 2020 programme funded as generation of new knowledge and understanding, but it also project on CS in environmental epidemiology brings several challenges. Therefore, the European Citizen (https://citieshealth.eu/). In Ljubljana pilot, citizens took part in Science Association (ECSA) prepared a common set of ten core co-designing citizen science study that addressed noise pollution principles to consider in the CS projects, one of them and health. Altogether, 49 volunteers aged 10-67 participated in emphasising the need to take into consideration legal and ethical the study from November 2020 to June 2021. They were issues surrounding copyright, intellectual property, data-sharing recruited during meetings and various engagement and agreements, confidentiality, attribution and the environmental empowerment activities organised with local NGOs, schools, impact of any activities [2]. private companies and based on contacts established in previous Intellectually property (IP) rights of participants in CS similar projects. Following the CitieS-Health methodological projects depend on the type of their involvement and contribution. framework [7] that is based on co-creation with citizens in four To this end, Scassa and Chung [3] outlined typology of CS phases of the project – initial identification of concerns and projects based upon IP issues and classified participant's interests of citizens, followed by co-design of data collection contribution into following four broad categories: (i) protocols, data collection and analysing, and action - the classification or transcription of data; (ii) data gathering; (iii) following overarching research question was formulated: How participation as a research subject; and/or (iv) the solving of do the quality of the living environment (with an emphasis on problems, sharing of ideas, or manipulation of data. The fourth noise) and living habits affect the (mental) health and well-being category is of special interest from the IP point of view, as it of individuals? To this end, volunteers performed measurements demands bigger intellectual engagement from participants [3]. and gathered information on various aspects of their living This is usually the case in the so-called co-created CS projects environment (noise levels, characteristics and perception of their surroundings, sleep quality and cognitive performance) using 291 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia J. Ftičar et al. smartphone applications and physical activity trackers (Figure participants, and thus their proactive involvement in discovering 1). Apart from the sleep questionnaire, they were prompted to do and generating of new knowledge. all the activities twice per day (morning and afternoon), and each individual collected the data for a minimum of seven days. 2.3 Development of Web-based Application Overall, 75 aggregated variables were collected, and over 1000 2.3.1 Technical details. The application was developed using observations made, which resulted in over 50000 the R programming language, a free software environment for records/observations all-together. statistical computing and graphics, specifically the Shiny package. This environment allowed development of the application with relatively low effort and without using other languages (as the package translates the R code into HTML, CSS and JavaScript). Even though R applications are server side and are typically slow, this was not an obstacle, as the user count was sufficiently low. For reasons of data protection and privacy, the application along with the underlying databases was installed on internal institute’s server. The application cleans, prepares and loads the data, and users only have access to their own data through password authentication. In this way, no data pre- treatment is needed from the participants’ side, and they can proceed to immediate data processing. 2.3.2 Structure of the application. The application comprises the following four general sections: (i) the intro page, containing the overall instructions and overview of the application; (ii) data overview page, containing the overall activity summary, data tables, descriptions and graphs of individual variables, and their sleep quality assessment; (iii) data with spatial context, containing georeferenced information regarding movement patterns of the individual and noise measurements, overlaid with general maps of air and noise pollution; (iv) analysis tools, containing interactive plots allowing visualization and analyses of combinations of chosen variables. The latter comprises a Figure 1: Schematic outline of the Ljubljana pilot boxplot/violin plot section, a scatterplot section, a radar chart section and a 3D plot section. 2.2 Challenges of Information Processing Following the principles of user-centred design, application As participants were collecting the data about themselves and was tested by three participants with varying degrees of their living environment, it was expected that they each get a knowledge. Their feedback and suggested improvements along personalized report on the data collected. On the other hand, with a smaller test group trial (15) helped us improve the participant’s proactive contribution in all phases of the project, usability of the application. including data analysis and processing, is one of the key aspects of co-created CS projects such as CitieS-Health. However, the scale and variability of the data collected can present a challenge 3 RESULTS (60-75 variables depending on the user). Moreover, in discussion with participants in the planning and execution phase, it became 3.1 Functionality of the Web-application clear that participants have very different interests and unalike In general, application enables three types of functionalities: perception on data processing. Therefore, a uniform report Access to the raw data along with basic descriptive statistics, comprising all the topics and all the parameters might come general data on the patterns of movement in space and sleeping across as too excessive and incomprehensible, at the risk of habits, pre-processed by researchers, and specific tools for losing the desired information and consequently reducing the independent data processing (Figure 2). In this way, step-by-step interest of volunteers in active participation. Moreover, as known approach is used, adding increased level of analytical complexity form previous similar efforts [8], it has to be assumed that the and dimensionality. reader is a layperson, and therefore information provided must The main idea was to make the app straightforward and be brief enough and concise, as too much information can create effortless for the users with no prior statistical knowledge. That’s distraction. An alternative would be to send raw data to the why it was designed with as few elements as possible to prevent participants, who would have to learn to use different data cluttering and burdening the participants with too complex processing tools on their own, or the latter would have to be taken functions. Hence, some functionalities only became visible when care of by researchers, which can be time consuming and not relevant (example: the button to switch the confidence intervals necessarily effective. on and off only becomes visible when the regression line is To overcome the aforementioned challenges, a web-based turned on). Moreover, the app was designed in a way that initial application was created for volunteers in Ljubljana pilot, which help sections are elementary and easily accessible (usually by enables independent editing, visualization and analysis of data by hovering over a question mark or a mini tab besides the plots), 292 Knowledge generation in citizen science project using on-line tools: CitieS-Health Ljubljana Pilot with the option of deeper explanations on external links. Similar, skills and interests. Initial descriptive statistics, general as there were many variables to choose from, the feature of behavioural patterns and explanations are included to nudge the choosing between the main pre-selected variables (5 variables users in some directions, however the decision on which topics per argument) or all of them (between 60 and 75) was added. or variables they would focus is up to them. This approach offers more user-friendly experience than traditional paper reports, as it simplifies the experience and makes it more understandable for laypeople while it is not losing the professional and educational aspect. 3.2 User-experience Feedback The results presented in this paper are preliminary in nature, as a more detailed analysis of the user experience will be evaluated in detail in the final phase of the project. However, based on the interactions with the volunteers involved so far, two general observations can be made. Lay volunteers show interest primarily in their own data and the level of their own exposure to environmental stressors, and are mostly interested in exposure to noise in the light of living habits, data on physical activity, and especially the quality of sleep. On the other hand, volunteers who have more experience with research, either within their profession or in general, recognize the added value of such tools. Among other things, it was proposed to expand the use of such an application for the continuous collection of a wider set of data in the living environment for the purposes of assessing the state of the environment, also as an aid to the work of inspection services and decision-makers. 4 CONCLUSION The tool developed for the specific needs of the specific citizen science project described in this paper proves to be a very promising solution with the possibility of expanding its applications. Namely, it enables the interactive inclusion of lay people in data analysis, which gives them a personalized experience, maintains their engagement, and at the same time, in addition to creating new knowledge for the common good, users gain insight into their own living habits and quality of life. Its full potential however still needs to be explored. For this purpose, an evaluation will take place in the final phase of the project, where among others aspects of intellectual property, specifically if and to what extent participants perceive these aspects, as well as the possibilities of using newly acquired knowledge as a result of cooperation between researchers and volunteers acquired in the respective activities, will be analysed. ACKNOWLEDGMENTS This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824484, and the P1-0143 program “Cycling of substances in the environment, mass balances, modelling of Figure 2: Examples of three types of functionalities: a) basic environmental processes and risk assessment”, funded by the descriptive statistics b) general data pre-processed by Slovenian Research Agency. researchers on general patterns of sleeping habits, c) tools for independent data processing The primary advantage of this approach is that the users have the freedom to explore their own data, tailored according to their 293 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia J. Ftičar et al. REFERENCES [1] Susanne Hecker, Muki Haklay, Anne Bowser, Zen Makuch, Johannes [6] Johanna Amalia Robinson, David Kocman, Orestis Speyer and Evangelos Vogel and Aletta Bonn (Eds.), 2018. Citizen Science: Innovation in Open Gerasopoulos, 2021. Meeting volunteer expectations — a review of Science, Society and Policy. UCL Press, London, UK. volunteer motivations in citizen science and best practices for their [2] Lucy Danielle Robinson, Jade Lauren Cawthray, Sarah Elizabeth West, retention through implementation of functional features in CS tools. In Aletta Bonn and Janice Ansine, 2018. Ten principles of citizen science. In Journal of Environmental Planning and Management, 64, 12 (2021), Citizen Science – Innovation in Open Science, Society and Policy. UCL 2089-2113. DOI: 10.1080/09640568.2020.1853507 Press, London, 27–40. [7] Raul Toran, Rodney Ortiz, Florence Gignac, Carolyn Daher, Mark [3] Teresa Scassa and Haewon Chung, 2015. Typology of Citizen Science Nieuwenhuijsen, Gabrielle Donzelli, Giulia Malavasi, Antonella Ficorilli, Projects from an Intellectual Property Perspective. Wilson Center – Bruna De Marchi, Giulia Bastiani, Fabrizio Rufo, Annibale Biggeri, Commons Lab, Washington, DC. Sandra Andrušaitytė, Regina Gražulevičienė, Fleur Froeling, Gerard [4] Frederique Froeling, Florence Gignac, Gerard Hoek, Roel Vermeulen, Hoek, David Kocman, Lucia Errandonea, et al., 2019. Documentation on Mark Nieuwenhuijsen, Antonella Ficorilli, Bruna De Marchi, Annibale activities and outcomes in CS actions (first report). Retrieved Biggeri, David Kocman, Johanna Amalia Robinson, Regina from: http://citieshealth.eu/download/435/?v=440 Grazuleviciene, Sandra Andrusaityte, Valetia Righi and Xavier Basagaña, [8] David Kocman, Tjaša Kadunč, Rok Novak, Johanna A. Robinson et al., 2021. Narrative review of citizen science in environmental epidemiology: 2020. Multi-sensor data collection for personal exposure monitoring : Setting the stage for co-created research projects in environmental ICARUS experience. In 20th International Symposium on Environmental epidemiology. In Environment International. 152, (Jul, 2021). DOI: Pollution and its Impact on Life in the Mediterranean Region, October 26- 10.1016/j.envint.2021.106470. 27, 2020: virtual event : book of abstracts. 71 (October 2020). ISBN 978- [5] Tabea Turrini, Daniel Dörler, Anett Richter, Florian Heigl and Aletta 1-00520-280-4. Bonn, 2018. The threefold potential of environmental citizen science - Generating knowledge, creating learning opportunities and enabling civic participation. In Biological Conservation, 225. DOI: https://doi.org/10.1016/j.biocon.2018.03.024 294 Overview of National Sources of Finance and Supports Available to Spin-Out Companies from Public Research Organizations * Vojka Žunič† Marta Klanjšek Gunde Knowledge Transfer Office Department of Materials Chemistry Mysteria Colorum – MyCol d.o.o. National Institute of Chemistry National Institute of Chemistry Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia marta@mycol.si vojka.zunic@ki.si marta.k.gunde@ki.si ABSTRACT po posebni opremi, dragih materialih in visokokvalificiranih človeških virih, zato ne zadovoljujejo finančnih potreb At Slovenian public research organizations numerous advanced odcepljenih podjetij s področja globoke tehnologije. technologies and know-how are generated, a lot of which have great commercial potential. One of the possible ways to bring V tem prispevku je podan pregled obstoječih finančnih virov, these innovations to the market is by selling or licensing them to uporabnih za podporo spin-out podjetjem. Predlagane so spin-out* companies established by the researchers, employed nekatere izboljšave, ki bi mladim spin-out podjetjem olajšale within the parent public research organization. However, the path zagon in tako omogočile učinkovitejši prenos izumov in znanja s to commercialization for the spin-outs can take a long time, področja globoke tehnologije v gospodarstvo. mainly due to a lack of financial resources and the legal impossibility for the public research organization to participate KLJUČNE BESEDE in spin-off companies. Especially spin-out companies from the Prenos IP, odcepljeno podjetje, komercializacija, finančna deep-tech fields require not only specific technical and business orodja. expertise, but also high capital investment. On the national level, there are available public sources of funding that can help companies in the initial phase. In general, these means are 1 INTRODUCTION adequate for start-ups with no needs for special equipment, Knowledge and technology established at public research expensive materials, and highly qualified human resources, and organizations in Slovenia are commonly transferred to the so don’t meet the financial needs of a deep-tech company. economy through the sale of the intellectual property rights, by In this paper, an overview of the existing financial initiatives, licensing the technology to an existing company, or by setting up helps and sources of funds, which can be used to support spin- a new spin-out company. A spin-out is a new company outs are given and some improvements are proposed that would established specifically to further develop and commercialize make it easier for young spin-out to get off the ground and thus technology arising from the public research organization. The enable more effective transfer of deep-tech inventions and relationship between a spin-out company and its parent public knowledge to the economy. research organization is in most cases based on a licensing relationship. The spin-out company is 100% owned by investors, KEYWORDS of which at least one is a researcher in a working relationship with the parent public research organization.[1] Such an IP transfer, spin-out company, commercialization, financial organization ensures the best possible and successful transfer of initiatives, help, funds. knowledge and close cooperation in the future. POVZETEK Like all of the young companies, i.e. start-ups, the initial founding of a spin-out comes from the equity funding from Na slovenskih javnih raziskovalnih organizacijah nastajajo founders also known as the 3F model (family, friends, and številne napredne tehnologije in znanje, ki imajo velik tržni founders). A key difference between spin-outs and start-ups is potencial. Eden od možnih načinov komercializacije the path to commercialization, which is much longer for potencialnih inovacij je prodaja ali licenciranje spin- spin-outs. A deep-tech spin-out usually aims to commercialize a out**podjetjem, ki jih ustanovijo raziskovalci, zaposleni v complex product that acquires a long development and scale-up matični javni raziskovalni organizaciji. Pot do komercializacije to manufacturing. The more complex the product, the more spin-out podjetja je dolga, predvsem zaradi pomanjkanja resources and time are required to bring it to the market. Before finančnih sredstev ter zakonsko onemogočenega sodelovanje a young spin-out can generate sufficient revenues on the market javnih raziskovalnih organizacij pri ustanavljanju odcepljenih and become attractive to outside investors, it has to live on podjetij. Zlasti spin-out podjetja s področij globoke tehnologije various sources of funding, mainly public funding, which is zahtevajo poleg posebnega tehničnega in poslovnega znanja tudi commonly aligned with the needs of start-up companies and visoke kapitalske naložbe. Na nacionalni ravni so na voljo javni already established companies, but less suitable for deep-tech viri financiranja, ki lahko pomagajo podjetjem v začetni fazi. Na spin-outs. Commercialization of deep-tech technologies requires splošno so ta sredstva primerna za zagonska podjetja brez potreb * A company linked to the parent organization based on licensing relationships (the company is wholly owned by investors, at least one of whom is a researcher in an employment relationship at the parental organization).[1]Napaka! Vira sklicevanja ni bilo mogoče najti. ** Podjetje, povezano z matično organizacijo na podlagi licenčnih razmerij (podjetje je v celoti v lasti vlagateljev, od katerih je vsaj eden raziskovalec v delovnem razmerju v matični organizaciji).[1] 295 National Financial Instruments for Spin-Out Companies V. Žunič and M. Klanjšek Gunde besides highly skilled personnel, the resources for expensive biggest gap in raising the technology level of their innovative materials and specialized equipment. An excellent example of product, especially above TRL5 where the technology needs to financial support to commercialize deep-tech technologies are be demonstrated and developed into the real product. Most deep the calls supported by the European Innovation Council (EIC), tech inventions require a long and costly development to raise e.g. programmes Pathfinder, Transition, and Accelerator.[2] the TRL and make all the necessary adjustments and scaling. These calls allow the applicant, e.g. a spin-out company, to Very few options are available to finance these needs and the develop according to the innovative idea, to develop the grants described are not very suitable although they are welcome. appropriate marketing model, to elaborate and scale the new product up to pilot production and to find first customers. 2.2 Subsidies, loans, guarantees, and equity Coaching and specific meetings are organized to connect directly These funds are derived from EU financial assistance to support with the companies that are the potential end-users of the product EU policies and programmes in form of all types of loans to or service to be developed. In this way, the pilot product can be companies to invest in research and innovation. It also provides transferred to a suitable industrial environment at an early stage guarantees to help recipients get loans from banks and other of development, and based on the received feedback adapted and lenders and on better terms. In Slovenia, these funds are mainly optimized. It should be noted that EIC calls are overcrowded with managed by Slovenian Enterprise Fund (SEF) and SID Banka.[3] applicants and the success rate is very low, so very few spin-outs get this chance. It is clear that most action should be taken at 2.2.1. SEF Programme »YOUNG ENTERPRISES« national level first. A good national funding mechanism would In the scope of a newly formed spin-out company, the Slovenian be welcome to create a supportive environment also for spin-out Enterprise Fund (SEF) offers the product Programme »YOUNG companies in the deep-tech fields that bring particular innovation ENTERPRISES« for companies younger than 5 years. The and specialized knowledge. purpose of the programme is to provide the initial financial support for entrepreneurial ideas and/or for already established young companies that have a guaranteed market and demonstrate 2 PUBLIC SOURCES OF FUNDING the potential increase in added value per employee. The For newly establishes Slovenian companies there are few means programme is primarily aimed at companies with a high share of of funding especially through the Slovenian Enterprise Fund, their own knowledge, innovation, and the potential of creating which, together with SID Bank and with the support of the products or services with high added value. It enables a Ministry of Economic Development and Technology, offers a comprehensive financial support adapted to development phases wide range of financial incentives and assistance. In the for young companies with initial support solely through public following subchapters, we summarized and reviewed the funds and subsequent public-private financing. There are few available public funding’s in the terms of support for a spin-out supports available in regard to the company's stage of company. Only the support important for spin-out companies is development among which the most adequate for new spin-out discussed, although there is additional support available for is the start-up Incentives for innovative start-ups "SEF TWIN". established businesses.[3] It purposes the support of start-up companies with a potential for rapid growth and that develop innovative products, processes, 2.1 Grants and services with high added value for a broader market.[9] The "YOUNG ENTERPRISES" programme is highly welcomed The aim of support of grants is primarily for research and and appreciated by start-ups with innovative ideas that do not development activities that are in line with the national and/or require much effort to reach the required TRL. Such examples EU programme and policy priorities. The grants enable some include various IT -based services and interesting products that coverage of costs for human resources and certain investment are high risk but can be developed to the development stage with activities. Support in form of grants can also be called by larger relatively little funding. In contrast, cutting-edge technology EU initiatives and independent bodies, such as EIT Climate KIC areas typically require much larger investments in equipment, [4], EIT Digital [5], EIT Food [6], EIT Raw Materials [7] other materials, and various human resources with specialized EITs, Bio-based Industries (BBI) [8], etc.[3] The aim of the technical knowledge and skills. The time required for growth is European Institute for Innovation and Technology (EIT) is to usually much longer. It is very likely that most of these increase Europe's innovation capacity by nurturing companies would not be able to sustain the financial incentives entrepreneurial talent and supporting new ideas. To make this of the programme because of the time and resources required to possible, the EIT sets up various Knowledge and Innovation grow rapidly to the stage where venture capital could be Community, (KICs) specialized in different challenges, such as available. climate, digitalization, food, raw materials, energy, etc. One of In many cases, eligible costs serve almost exclusively IT -based their activities is also grants for start-ups. They offer business- start-ups and allow for the purchase of computers and related oriented acceleration programmes and aim to prepare a company equipment, but not materials, such as chemicals, or special for greater growth in the region and make it investment-ready. equipment needed to develop the new products. Nor can they Usually, numerous entrepreneurial training courses are offered to fund the rental of laboratory space, which is urgently needed for boost the business. These services are highly appreciated and the development of cutting-edge technology inventions. For this help the new business to secure the best possible path. However, reason, the programme mainly includes SMEs with interesting a lean spin-out, especially from the cutting-edge technology but technologically relatively simple products, but not many sector, usually does not have free human resources that can be spin-outs from research institutes and university operating in the used only for these tasks. Most deep-tech spin-outs see the deep-tech field of innovation. [10] 296 National Financial Instruments for Spin-Out Companies V. Žunič and M. Klanjšek Gunde Another instrument implemented by the SEF are the substantive possible to claim corporate income tax (CIT) tax deductions for support programmes in form of vouchers such as Small Value 100% investment in research and development, investment in in- Incentives, Content support for young innovative companies, and house R&D activities and for the purchase of R&D services, Abroad training for high-tech companies.[9] The support enables investment in equipment and intangible assets at 40 % of the the financing of e.g. intellectual property protection, certificates amount invested.[16] It should be noted that these benefits do not of quality, internationalization costs, networking and include the investments made with the help of the projects, not information, fast-growth accelerator programmes. For example, even the part in which the company has to participate. This part the Patent, design, trademark vouchers are meant to cover the ranges from 30% to 50% or even higher, depending on the costs of preparing the application dossier and/or maintaining financing arrangements of the instrument. This can be a large and/or extending legal protection for the intellectual property at amount, especially for large investments in specialized national, European and international patent offices, including the equipment likely required by the deep-tech. costs of the patent attorney, official fees and translation costs. The available means are between 500,00 and 5.000,00 € for 2.5 Non-financial forms of public aid applications without substantive examination and between Non-financial forms of state aid are available through support 500,00 and 9.999,99 € for applications with substantive environments and networks across Slovenia. They offer examination. Based on practical experience this amount is assistance mainly as services for potential entrepreneurs, and enough to cover the cost from application till grand at individual SMEs, such as technical assistance, advice, mentoring, guidance, national offices, such as the SIPO, UK IPO or at the European workshops and training, competence building, opening up new Patent Office (EPO).[10] business opportunities and exchanges of good practice.[3] 2.2.2. SID Bank Fund of Funds The SID Bank Fund of Funds was set up in 2017 by the Ministry 3 WHAT IS MISSING of Economic Development and Technology and SID Bank and is intended for the use of European cohesion funds. These funds are 3.1 Venture capital fund along the lines of the aimed at the financing of sustainable economic growth and, EIC development, investments in innovation and current operations through debt financing in four areas: research, development and Support should be developed along the lines of the European innovation, small and medium-sized enterprises, energy Innovation Council (EIC), which is an example of good practice efficiency, and urban development. The Fund of Funds includes that should be transferred to Slovenia. many repayable forms of financing, which are extremely The steps needed to set up such a support would first and welcome at later stages of development, i.e. at higher TRLs, foremost require an appropriate legal basis, which is currently especially after reaching TRL9. At this stage, a deep-tech SME lacking - this could change with the new Research and is fully confident in its successful technology and knows exactly Innovation Act, we are expecting soon. Furthermore, it is what investment is required to develop pilot production into real necessary to ensure coordinated action and support from funders production and grow the business beyond early adopters and - Slovenian Research Agency (ARRS), Public Agency for byers. The instruments managed by the SID Bank which can be Entrepreneurship, Internationalization, Foreign Investments and of interest to spin-out companies are the (i) Loans to finance Technology (SPIRIT), Slovenian Enterprise Fund (SEF), and research, development, and innovation (RDI) (enable to cover other existing or future funders of such projects. In this way, the cost of development, improvement or launch of a new or coordinated and continuous funding of successful projects on the improved product, process, or service, etc.) and (ii) Micro loans area of higher TRLs could be ensured, without interruptions in for SMEs (SME micro) (applicable to cover the costs of business the (co-)financing of the development of a specific technology. process, investments in property, plant, and equipment). These instruments draw funding from the European Cohesion Policy 3.2 Innovation projects at national research funds and funds from financial intermediaries. However, for agency – the new financial instrument to earlier TRL stages, the Fund of Funds is most likely too risky, balance the basic science funds especially for deep tech.[11] To develop innovation at the scale required, especially for deep- edge technology, we need a new funding instrument. This 2.3 Awards instrument is best located at ARRS, which currently with the new Lower financial support is possible to be obtained through law needs to upgrade its funding of science with innovation innovation prizes such as the Rector's Award for the Best funding. Innovation at the University of Ljubljana [12], EIT Jumpstarter Beneficiary projects should be funded at a realistic cost of [13], EIT Awards [14], BASF Innovation Hub [15], etc. Such 100,000.00 € per year upwards (similar to the ERC Proof of awards are important to raise awareness of the novelty and Concept grants, which offer a lump sum of 150,000.00 € for a publicize the spin-out company, but too early notes could also period of 18 months) [17], comparable to the projects and mean too much of a push in a particular direction that could funding levels of typical basic research projects at ARRS. The become a side track. Agency also finances the so-called larger research projects with higher funding. The allocation of funds for innovation projects 2.4 Benefits should consider the real costs of the project and not a fixed The national Corporate Income Tax Act (ZDDPO-2) enables amount which is current praxis for research projects. In view of spin-out companies benefits in form of tax deductions which are the final added value that could be generated by the company 297 National Financial Instruments for Spin-Out Companies V. Žunič and M. Klanjšek Gunde with such support, the proposed sum is actually low. The number REFERENCES of innovation projects selected should be in line with the number [1] Špela Stres (Ed.). 2021. Modrosti iz inovacijskega podpornega okolja v of projects awarded for basic science at national level. javno raziskovalnih organizacijah za upravljalce inovacijskega sistema. The envisaged financial support should finance promising Inštitut “Jožef Stefan” (IJS), Ljubljana. [2] European Innovation Council accessed on 10/08/2021 research that has already been funded as a basic research project https://eic.ec.europa.eu/index_en by the ARRS and as such should have priority for funding. This [3] Start:up Slovenija accessed on 10/08/2021 [4] https://www.startup.si/sl-si/za-startupe/javni-viri-financiranjaEIT would achieve greater funding coherence and justify the Climate-KIC accessed on 10/08/2021 rationality of funding basic research and ensure higher added https://www.climate-kic.org/countries/slovenia/ value of funding that if serving just excellent science. [5] EIT Digital accessed on 10/08/2021 https://www.eitdigital.eu/ Additionally, it would create systematic and continuous financial [6] EIT Food accessed on 10/08/2021 support in Slovenia from idea to market entry, especially in the https://www.eitfood.eu/in-your-country/country/slovenia [7] EIT Raw Materials accessed on 10/08/2021 field of deep-tech. This is a basic requirement for entering the https://eitrawmaterials.eu/ innovation-based community and could bridge the gap between [8] Bio-based Industries accessed on 10/08/2021 https://www.bbi.europa.eu/ basic science and the start-up opportunities already available in [9] Slovenian Enterprise Fund accessed on 10/08/2021 Slovenia. https://podjetniskisklad.si/en/sef-s-products/programme-young- enterprises [10] Slovenian Enterprise Fund accessed on 10/08/2021 3.3 Other possibilities https://podjetniskisklad.si/sl/produkti-sklada/sps-dvojcekdpora-pri- produktih In order to improve all opportunities to make our original deep- [11] Skladi skladov SID Banke accessed on 11/08/2021 tech knowledge available to the economy, especially that https://www.skladskladov.si/en generated by spin-out companies as a result of the pre-funding of [12] UL Pisarna za prenos znanja accessed on 11/08/2021 https://ppz.uni-lj.si/novice/rektorjeva-nagrada-2021/ basic research, we recommend that the other financial initiatives [13] EIT JumpStarter accessed on 11/08/2021 adopt some changes. To this end, the SEF programme "YOUNG https://eitrawmaterials.eu/eit-jumpstarter/ [14] EIT Awards accessed on 11/08/2021 ENTERPRISES" could make appropriate changes to support https://eit.europa.eu/our-activities/eit-awards SMEs with more complex needs. It should also be thoroughly [15] BASF Innovation Hub accessed on 11/08/2021 discussed whether the corporate tax deductions for investments https://join-innovationhub.com/ [16] Pravno informacijski sistem accessed on 11/08/2021 in in-house R&D activities and for the purchase of R&D services http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4687 and equipment during an R&D project are also possible for the [17] ERC Proof of Concept Grant accessed on 23/09/2021 https://erc.europa.eu/funding/proof-concept part that the company has to co-invest through its own participation. Note: Researcher who wish to establish a spin-out company can acquire more information at the Technology Transfer Office of the parental research organization. 298 Application of 3D printing, reverse engineering and metrology Remzo Dedić† Željko Stojkić Igor Bošnjak Faculty of Mechanical Faculty of Mechanical Faculty of Mechanical Engineering, Computing and Engineering, Computing and Engineering, Computing and Electrical Engineering Electrical Engineering Electrical Engineering University of Mostar University of Mostar University of Mostar Mostar Bosnia and Herzegovina Mostar Bosnia and Herzegovina Mostar Bosnia and Herzegovina remzo.dedic@fsre.sum.ba zeljko.stojkic@fsre.sum.ba igor.bosnjak@fsre.sum.ba ABSTRACT metrology. Students, assistants, and engineers from local companies are introduced to 3D printing, 3D scanners and 3D Examples of transfer of knowledge in the field of 3D printing, scanning through practical examples. Also, they can actively reverse engineering, and metrology will be presented in this participate in the development and adjustment of materials for paper. The first chapter contains the description of the concept of the implementation of training and laboratory exercises, as well the Learning Factory, within which knowledge is created and as in the organization of training, laboratory exercises and transferred to the economic entities in the environment. exercises on real examples. The practical work of printing and Technologies of 3D printing, reverse engineering, and metrology scanning objects is done in the premises of the Learning Factory. are subsequently described and various examples of development projects for the local industry are presented. A conclusion regarding the realized activities is given at the end. 2 3D PRINT, REVERSE ENGINEERING AND METROLOGY KEYWORDS 3D print, reverse engineering, metrology, Learning Factory, 2.1 Rapid prototyping - 3D print transfer of knowledge Several 3D printers were procured at FSRE through the project. • Stratatys F 270 is an industrial type of F123 series printer with FDM technology. It uses materials for model/support: PLA, 1 INTRODUCTION ABS-M30, ASA, TPU, 92A/QSR. The Learning Factory at the Faculty of Mechanical Engineering, • MakerBot Method X Carbon Fiber Edition uses carbon fiber Computing and Electrical engineering (FSRE) has the basic goal reinforced material, ABS, ASA, SR30, PLA, PVA. of enabling students to experience many problems that will be • Zortrax M200 Plus uses LPD/FFF printing technology. It uses present in the production facilities where they will soon be dedicated M series material. operating. At the same time, the Factory also provides engineers • Ultimaker 2+ is a small 3D printer that is programmed within from local companies with the opportunity to get acquainted with the Cura software package. The software is easy to use and new technologies that were not present at the time they were allows you to move objects, load multiple objects for printing, studying. and change resolutions and other settings. The set goals are achieved through several projects: “Reconnecting universities and enterprises to unleash regional 2.2 Reverse engineering in general innovation and entrepreneurial activity” (Kno wHUB) and Modern manufacturing companies that want to maintain and “Increasing competitiveness of micro, small and medium-sized improve competitiveness in the global market are forced to enterprises through digitalization” (IC SMED ). The main goal systematically update existing and find new ways to reduce of the KnowHUB project is to build HUBs as a link between operating costs in all aspects of their operations. higher education institutions, the business environment and the The process of transforming an idea into a functional product wider community. The main goal of the IC SMED project is to consists of a series of steps that in some cases can be iterated increase the competitiveness of micro, small and medium several times. Such a setting implies a significant expenditure of enterprises with the help of digitalization. Through these projects, time and financial resources during the product development conditions have been established to help and support local process, without a guarantee of a positive outcome of the entire businesses in the areas of 3D printing, reverse engineering, and process. These reasons were sufficient to try to find ways and ∗Article Title Footnote needs to be captured as Title Note methods of shortening the time of product development and †Author Footnote to be captured as Author Note spending financial resources related to the product development process in everyday engineering practice. One of the ways of reducing the time and cost of the new product development Permission to make digital or hard copies of part or all of this work for personal or process is reverse engineering. classroom use is granted without fee provided that copies are not made or In a narrower sense, reverse engineering can be defined as the 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 process of duplicating an existing component, assembly, or this work must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 299 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Dedic, Stojkic, Bosnjak product, without the aid of a drawing, technical documentation, or computer model (Figure 1). In the context of the aforementioned, the technique of reverse engineering can be applied to analyze and study the internal working parts of the machine, for example, to compare the current device with the performed analyzes in order to obtain suggestions for improvement. Figure 2. 3D scanner within the FSRE Learning Factory 2.2.1.2 GOM Inspect Suite. GOM Inspect Suite is a comprehensive software package for simple or complex measured tasks during the entire quality control process - from 3D product scanning, polygon network editing, CAD model import, GD&T analysis, statistical trend analysis, digital editing, etc. (Figure 3) Figure 1. Reverse engineering process [1] Unlike "classical" engineering design that starts from the abstract - the idea implies its elaboration through conceptual and then detailed CAD design, design based on the principles of reverse engineering begins with a physical object which is then translated into a CAD model, possibly adapted or refined and in the end manufactured by one of the CNC, that is, RP technologies [2]. Figure 3. The appearance of the workspace inside the GOM 2.2.1 Reverse Engineering and Metrology at FSRE In the scanning module "Learning Factory" at the Faculty of Mechanical Engineering, Computing and Electrical Engineering, within the KnowHUB project, several tasks related to the topic of reverse engineering 2.2.1.3 Geomagic for SolidWorks. Represents a set of were performed. 3D digitization, for example, scanning of software tools for reverse engineering that provides advanced workpieces is performed using the scanner GOM ATOS capabilities for point clouds and polygon networks to become Compact Scan 8M. Processing is done within the GOM Inspect usable in the product construction and redesign process. Data can Suite 2020 software package, and CAD model generation is done be imported or scanned directly into SolidWorks. Supports all using the reverse engineering tool Geomagic for SolidWorks. major scanners and portable CMMs as well as importing standard point cloud and network formats. 2.2.1.1 GOM ATOS Compact Scan. A new class of compact 2.3 Metrology in general 3D scanners for 3D metrology and control (Figure 2). Light, compact construction of the trigger probe opens new areas of Metrology is a scientific discipline that deals with measurement application and provides adaptability for three-dimensional in all its theoretical and practical forms. Basic metrology deals measurement of components such as cast and injection molded with the scientific assumptions of measurement, technical parts, cores and models, interiors, prototypes, and similar. metrology covers the procedures and methods of measurement, Adopts blue light technology, combines scanning and and legal metrology covers the applications prescribed by law. measurement, adjustable measuring range, complete and Metrology includes all theoretical and practical aspects of portable measuring system, compact trigger probe with measurement, deals with methods of measuring physical integrated control unit, etc. quantities, realization, and maintenance of standards of physical quantities, development and production of measuring instruments, and analysis of measurement results. Metrology has been developed to the level of applied science. 300 Application of 3D printing, reverse engineering and metrology Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia within the Learning factory at the University of Mostar 2.4 Integration of rapid prototyping and reverse engineering processes With the help of the characteristics of the process of rapid prototyping and reverse engineering, the possibilities provided by their combination and adequate application provide numerous advantages that are primarily reflected in the ability to reduce time and reduce costs of product development/redesign, and in Figure 5. Reverse engineering on G-1S connector certain conditions in the production of tools and ready-to-use (polygonized mesh - scanned piece and CAD model - CAD products. The integration of these approaches ensures the model - deviation display) transition of the problem of transformation, that is, the translation of a virtual product from a digital form stored in the appropriate CAD software into a real tangible form-object and vice versa (Figure 4). Namely, reverse engineering ensures the generation of 3D CAD models based on a real object, and the model is transformed into a suitable real prototype/product relatively quickly and without significant human involvement by applying the process of rapid prototyping. Figure 6. Scanned elements made with 3D printing technology 3.2 Reverse engineering on the example of a pulley for the local company “ZEC” This task aimed to use reverse engineering to obtain the geometry of the pulley profile using a CAD model to make an equal part since the original part is frayed (Figure 7). Figure 4. Integration process [3] 3 APPLICATION OF 3D PRINT, REVERSE ENGINEERING AND METROLOGY Various examples of the application of 3D printing, reverse engineering, and metrology will be presented in this chapter. Figure 7. Scanned pulley, 3D model of the pulley and deviation display 3.1 Reverse engineering applied on metal joints for FSRE 3.3 Reverse engineering on the example of a The task aims to generate a CAD model (original geometry or part of a plastic injection tool for a local redesign) of metal couplings with the intention of small series company “Weltplast” production (3D printing technology) for the needs of the "Learning Factory" if the prototype satisfies during testing The task aims to generate a 3D model of a part of a plastic (Figure 5). injection tool since the original part is frayed (Figure 8). All aforementioned elements were made with 3D printing technology after scanning and processing (Figure 6). Figure 8. Reverse engineering on a part of a plastic injection tool 301 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Dedic, Stojkic, Bosnjak 3.4 Reverse engineering on the example of dental spoons for the local company “MA- COM” This task aims to create a CAD model (and technical documentation) of dental spoons for taking dental impressions (Figure 9). Figure 11. Drawing of the shutter on the pool and a prototype of the shutter made by 3D printing 3.7 Metrology applied on a milling cutter for the company “Škutor” In the FSRE Learning Factory, several tasks related to the topic of metrology were performed. The objects that have to be measured were first subjected to a Figure 9. Scanned spoons U1 and U4 and redesign of the scanning process performed using a GOM ATOS Compact Scan spoon 8M scanner. The measurement process itself is performed within the GOM Inspect Suite 2020 software package within the 3.5 Reverse engineering applied on a lever for measurement module [4]. the company “SIK” The task aims to determine the dimensions of cutters with a The task aims to create a new lever with 3D printing technology diameter of Ø20 and Ø12 and to prepare accompanying using the process of reverse engineering (Figure 10). documentation ((Figure 12). Figure 10. Reverse engineering on a lever 3.6 Reverse engineering applied to the pool shutter Figure 12. Display of the measurement report page The task aims to create documentation based on a damaged shutter and then create a new part by reverse engineering and 3D 4 CONCLUSION printing. The technology of rapid prototyping with 3D printing in In this specific case: combination with a 3D scanner and appropriate software using - No spare parts on the market reverse engineering can significantly speed up the path to the - No shutter drawing finished product, which is extremely important for relevant - No tools for making shutters companies. Shutter requirements: - Must be made with 3D printing - The material must be elastic due to the installation REFERENCES requirements [1] https://www.indiamart.com/proddetail/reverse-engineering- - The material must be resistant to sunlight 4480021012.html, 28.09.2021. A drawing of the shutter in SolidWorks and a prototype of the [2] I. Budak: Prezentacije s predavanja iz kolegija Reverzibilno inženjerstvo i brza izrada prototipa u biomedicinskom inženjerstvu, Univerzitet u shutter obtained by 3D printing are shown in Figure 11. Novom Sadu - Fakultet tehničkih nauka [3] A. Topčić, Dž. Tufekčić, E. Cerjaković, A. Fajić, S. Lovrić: Brza izrada prototipa i reverzibilno inženjerstvo kao alati za reinžejering proizvodnih procesa, Mašinski fakultet u Tuzli, Tuzla, 2015. [4] Topomatika,https://topomatika.hr/gom-inspect-suite-najnovija-verzija- gom-2020inspekcijskog-softvera/, 15.05.2021 302 Towards the Market: Novel Antimicrobial Material Tomaž Lutman Marija Vukomanović Center for Technology Transfer and Innovation Advanced Materials Department Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia tomaz.lutman@ijs.si marija.vukomanovic@ijs.si ABSTRACT KLJUČNE BESEDE The Jožef Stefan Institute has developed novel antimicrobial prenos tehnologije, antimikrobni material, zlato, študija nanogold composite and patented it (EP2863751 B1). In preverjanja koncepta, stopnja tehnološke zrelosti comparison with widely used silver, the material is less toxic to human and environment and has better antibacterial properties. Good antiviral effect has also been shown. In the period 10/2020- 1 INTRODUCTION 04/2021 the technology for applying this material on textile has In year 2012 DDr. Marija Vukomanović published her second been developed within KET4CleanProduction project. This was an important step towards higher TRLs. Before entering the PhD thesis with title ‘Sonochemical synthesis and market, the novel material must be tested according to Biocidal characterization of hydroxyapatite/metal-based composite Product Regulation (EU No 528/2012). This includes toxicity materials for biomedical applications’ which represented the and efficacy testing and submission of the dossier to European work performed at the Advanced Materials Department, Jožef Chemical Agency. In order to successfully enter the market, Stefan Institute [1]. Furthermore, the research group identified an suitable industrial partner which will scale up the production of invention that was made within this work – a novel antimicrobial the material and commercialize it is needed. Horizon Europe material and its production method. Together with the Institute’s calls represent interesting financial tool to support this endeavour Center for Technology Transfer and Innovation technology and to reach higher TRLs. market potential was evaluated. In the same year, a Slovenian patent application was filed. Due to high potential of the KEYWORDS technology a PCT application was filed next year and in the technology transfer, antimicrobial material, gold, proof of beginning of 2015 an entry in European phase was made. In the concept study, technology readiness level period 2015-2018 European patent office examined the patent POVZETEK application and expressed their opinion about patentability. Necessary modifications of the claims were made and the Institut "Jožef Stefan" je razvil nov protimikrobni kompozit na European patent EP2863751B1 was granted in 2018 and no osnovi zlata in ga patentiral (EP2863751 B1). V primerjavi s opposition has been filed afterwards [2]. široko uporabljenim srebrom je material manj strupen za ljudi in okolje ter ima boljše protibakterijske lastnosti. Dokazan je bil tudi dober protivirusni učinek. V obdobju 10/2020-04/2021 je 2 ANTIMICROBIAL MATERIALS bila v okviru projekta KET4CleanProduction razvita tehnologija Novel trends in developing antimicrobial technology are za nanašanje tega materiala na tekstil. To je bil pomemben korak associated with the use of multifunctional nanosystems. The k višjim stopnjam TRL. Pred vstopom na trg je treba novi material preskusiti v skladu z Uredbo o biocidnih proizvodih (EU challenges for the use of nanotechnology are focused into: (i) št. 528/2012). To vključuje testiranje toksičnosti in učinkovitosti nanoparticles loaded with antimicrobial substance(s) able to ter predložitev dokumentacije Evropski agenciji za kemikalije. control their release and (ii) “nanoantibiotics” – nanoparticles Za uspešen vstop na trg je potreben ustrezen industrijski partner, with antimicrobial nature. The main drawback of the first ki bo povečal proizvodnjo materiala in z njem vstopil na trg. strategy is dependence of the released substance on the properties Razpisi programa Horizon Europe predstavljajo zanimivo of the carrier that provides conditions potentially favourable for finančno orodje, ki podpirajo tako prizadevanje za doseganje bacterial resistance. The second strategy is based on the višjih stopenj TRL. development of novel antibacterial nanoparticles and it has been applied for many different materials including silver, copper-, titanium-, zinc-, cerium- oxides, doped hydroxyapatite, carbon nanotubes, NO-releasing nanoparticles, fullerenes and clay nanoparticles. Among all of the listed materials, silver is the most Permission to make digital or hard copies of part or all of this work for personal or economic and most effective in action against various bacterial classroom use is granted without fee provided that copies are not made or distributed stains. However, as for the silver, the majority of listed materials for profit or commercial advantage and that copies bear this notice and the full are leaching and they release active component (particularly 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). reactive oxygen species) which provides action against bacteria. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia The mechanism is highly non-selective and has the very similar © 2020 Copyright held by the owner/author(s). contribution to the death of bacterial cells as to the death of mammalian cells. Even composites with bioactive component 303 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Lutman et al. (like apatite) do not mitigate toxic effect of silver and selectivity have been enhanced by the Center for Technology Transfer and indexes remain quite low [3]. Innovation (CTT) after the European patent was granted. Contact- based antimicrobials, designed to perform CTT has used several channels and media to promote antimicrobial action without leaching any active substance, are the invention and find suitable partners to reach higher TRLs. exceptional solution for above described problem. Mainly The initial step was to publish technology offer in Enterprise designed as functionalized polymers, contact-based Europe Network, which is the largest brokerage network for antimicrobials usually contain high density of charged companies (SMEs and others), research institutes and functional groups (i.e. quaternary ammonium compounds, alkyl universities. It brings together 3,000 experts from more than 600 pyridiniums, or quaternary phosphonium). They use multiple member organizations from Europe and beyond [5]. The charges to attach and interact with bacterial membranes technology offer is published for maximum two years and has to providing their disassembly. As observed in antimicrobial include information about the technology, owner organization, peptides and polymers, the main limitation of these systems is advantages and innovation, information about partner sought, low chemical stability, pronounced susceptibility to enzymatic cooperation type and keywords. Enterprise Europe Network degradation and conformational changes induced by includes also topic specific groups, called Sector Groups. The environmental stimuli. These are very good targets for potential invention was presented and promoted in SG Materials in which inactivation mechanism that will lead to losing their we also have a member. antimicrobial potential. In 2018 the innovation was presented at the Innovative contact-based antimicrobials, based on International Exhibition of Inventions ARCA, Zagreb Croatia functionalized gold, invented by our group at the Advanced with the help of partners from the Slovenian Consortium of Materials Department, Jozef Stefan Institute, is a step ahead in Technology Transfer (Figure 2). A silver medal was awarded for comparison to the common contact-based antimicrobials and this innovation [6]. This contributed to general promotion of the very promising alternative (Figure 1) [4]. They use surface- invention. associated guanidinium groups to physically disintegrate bacterial cells. Bactericidal effect is enabled in a range of gram + and - bacterial strains and is associated to the surface potential of bacterial membranes. Due to bioinert gold and natural- sourced functionalizing agents, concentrations toxic to human and animal cells are up to 20 times higher than biocidal, confirming high selectivity. In addition, since they are functionalized using direct bonding of charged, small molecules to the surface on nanoparticles (rather than formation of long polymeric chains) they keep their stability under different environmental stimuli, including presence of enzymes. With better stability and safety, the novel kind of contact-based antimicrobials is overcoming general difficulties with common contact-based antimicrobials and significantly decreases possibility for inactivation. Figure 2: Presentation of inventions at the International Exhibition of Inventions ARCA, Zagreb, Croatia. As antimicrobial materials can be applied in many different fields (cosmetics, medical devices, plasters, filters, paints, dentistry, textile etc.) it was hard to decide and look for a partner from specific industry so we decided to make a broad search of partners for different applications. We contacted producers of implants and other medical devices, filters, toothpastes, medical plasters, plastics, seats, which represented the entities nearer to end user in the value chain of antimicrobial materials. This resulted in scarce response. Additionally, we Figure 1: Current state of the invention: gold powder its contacted also companies that produce active antimicrobial efficacy and cytotoxicity in direct comparison to nano- component and companies that produce antimicrobial mixtures silver. – masterbatches. Sometimes these two activities are performed by the same company. We received an important feedback from UK masterbatch producer about the relevance of Regulation 3 TOWARDS HIGHER TRLS (EU) No 528/2012 also named Biocidal Products Regulation – BPR [7]. They told us that if we want to enter European market 3.1 Initial steps in finding R&D partners with novel antimicrobial component, we have to perform the After filing the priority Slovenian patent application for the novel necessary toxicity and efficacy tests. They estimated costs for a antimicrobial material first attempts to establish connections new BPR product registration to > 1 million €. with relevant industry partners have been made. These efforts 304 Towards the Market: Novel Antimicrobial Material Information Society 2020, 4–8 October 2021, Ljubljana, Slovenia 3.2 EU Biocidal Product Regulation 120.000 €, whereas there are additional fees for registration of biocidal products, which is additional procedure performed at Although the regulations often limit the entry of new ECHA and national agencies of countries, where the biocidal technologies on the market due to its high costs it is important to product is to be placed on market. Management, registration confirm the safety and efficiency of the technologies in order to procedure and communication with ECHA, which is done by provide long term benefit for the society. consultant companies costs 150.000-480.000 €. Due to high Regulation (EU) No 528/2012 concerning the making costs, companies that want to place novel biocidal products also available on the market and use of biocidal products was form a consortium and jointly finance this procedure. Only the accepted by the European Parliament and Council on 22 May applicant that submitted results of tests can make reference to 2012 and is successor of Directive 98/8/EC. BPR concerns this data. If another company wishes to place such product on biocidal products, which are used for protection of people, the market and hasn’t performed any procedure at ECHA or animals, materials or products against pathogen organisms like national offices, they have to purchase a license to make bacteria, viruses or fungi and comprise active component. The reference to already submitted data. This creates a specific aim of this regulation is to improve the market of biocidal situation on the market, similar to patent system. products in EU and provide high level of safety for humans and environment. 3.3 Proof of Concept study on textile For each biocidal product or its active component, it is In the frame of Interreg project KETGATE CTT and partners necessary to acquire permission, before it can be placed on organized brokerage event for SMEs and research organizations market. The active components can be available on the market from Central Europe [8]. Due to COVID-19 pandemic it took in some occasions also during the procedure of their registration. place online in May 2020. 124 participants attended short 1:1 The regulation aims to simplify and unify the procedure for EU meetings. We had a meeting with Hungarian textile producer, member states. It also aims to maximize the sharing of available which uses silver to prepare antimicrobial clothes. We data and minimize the amount of tests on animals. introduced them our invention and they were interested to Novel biocidal active components and biocidal investigate the possibility to apply our material on their textile products are submitted to European Chemical Agency – ECHA products. Due to relatively low TRL (at that time TRL4) and high and national authorities (i.e. Chemicals Office in Slovenia). The risk associated with the material, we had to find a financing data is managed and available on the Register for Biocidal program for this kind of cooperation. The call Products (R4BP 3). Another IT tool, IUCLID, is used for KET4CleanProduction offered Proof of Concept study for SMEs preparing the applications. which wanted to use Key Enabling Technologies, developed at According to Annex II of BPR the tests performed for the research organizations. The KET4CleanProduction was a registration of any new active substance should comply with the Horizon Europe project with its own fund of 2 million € for the relevant requirements of protection of laboratory animals, set call, that was open in period 2018-2020 and granted projects out in Directive 2010/63/EU of the European Parliament and the received 50.000 € of lump sum. In the KET4CleanProduction Council of 22 September 2010 on the protection of animals used network we also identified suitable partner for this Proof of for scientific purposes and in the case of ecotoxicological and Concept – a Portuguese textile institute – and the project was toxicological tests, good laboratory practice, set out in Directive granted [9]. 2004/10/EC of the European Parliament and of the Council of 11 February 2004 on the harmonization of laws, regulations and In the period 10/2020-04/2021 the project to apply the administrative provisions relating to the application of the Au/apatite nanoparticles on textile took place. The nanoparticles principles of good laboratory practice and the verification of were synthesized and sent for further application – deposition on their application for tests on chemical substances or other textile. For the functionalization of the cotton textile, one of the international standards recognized as being equivalent by the EU suitable method was found the most efficient one in terms of Commission or the ECHA. Tests on physic-chemical properties yield of the functionalization, leading to higher amounts of and safety-relevant substance data should be performed at least nanoparticles bonded to the textile substrate. Textiles (cotton) according to international standards. obtained after single washing were confirmed to have bacteriostatic effect in P. aeruginosa, as Gram negative strain, Due to high standards needed for the tests, these are and strong bactericidal effect in Gram negative E. coli and Gram very expensive. The tests are performed stepwise and in dialog positive S. epidermidis and B. subtillis (Figure 3). Antimicrobial with ECHA. Some tests are then performed only if the results of effect was detected on contact with textiles; it followed contact- first set of tests are not satisfactory or ECHA decided they are based mechanism of Au/apatite nanoparticles and confirmed necessary. The amount of tests also rises for nanomaterials, their very stable bonding to the cotton textile. The gold-based which might involve additional risk. nanoparticles also showed high antiviral activity, even at low concentrations. As the procedure to prepare and submit the data, needed for registration of novel active component is very demanding and extensive, companies often employ consultants to manage this procedure. For this reason, we also contacted such consultant companies to see, how we can use their support. They informed us is that the first step is to perform Data Gap Analysis, where existing data is reviewed and a list of necessary further tests to be performed is made. Preparation of this document costs 10.000-30.000 €. We received different information for the costs of toxicity and efficacy tests according to suitable standards, which varied between 0,5 and 3 million €. The ECHA fee for application of novel active substance is 305 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Lutman et al. The project is expected to have an important impact on prevention of spreading of already known and novel pathogens (bacteria, viruses, fungi, etc.) by limiting their transmission through different surfaces. In the first place, the project will provide demonstrators on face masks, hospital linen, protective clothes, textile handles for public transport, pull handles for doors or textile sheath for pull handles, paper for everyday use, banknotes, passport, plastic covers for door handles, working surfaces in healthcare sector (i.e. hospitals) and areas where food is prepared. Furthermore, it will explore the opportunity to include it in the antimicrobial masterbatches, which can be used for wide variety of end products. The demonstrators will pave the way to other possible usage of novel antibacterial material based on gold as the demonstrators of the Figure 3. Antibacterial test on Au/apatite nanoparticles project will include various materials like cotton; different bound to textile. polymers such as polyester, polypropylene, polyamide; cellulose; mineral composite; metals etc. This will enable the opportunity to relatively easily apply it also on other products in the hospitals, long-term care facilities, public transport, public 3.4 Horizon Europe project offices, restaurants and bars, sport facilities, shopping centres, The KET4CleanProduction project represented strong support to cinemas and theatres as well as other places frequently visited reach higher TRLs. It proved that the novel antimicrobial can be by general public. The efficiency of the novel material among applied on end product and still keeps its excellent antimicrobial wide range of pathogens including bacteria, fungi, viruses and function. This project paved further way towards entry of the yeast will be evaluated. Special emphasis will be given to virus novel material on the market. We identified next three tasks that SARS-CoV-2 including its latest variants. needed to be performed in the following steps: The longterm vision is that a French manufacturer of • Testing the toxicity and efficacy (antibacterial, composite materials will sign license agreement with JSI, start antiviral, etc.) of the composite nanogold material and to produce the novel gold composite on industrial level, register preparation of the documentation according to the it at the ECHA and enter the market with it. Producers of Biocidal Product Regulation (EU 528/2012) different antimicrobial products, members of the consortium shall be first clients and further promotion will be made to • Development and optimization the technology for successfully increase the sales share. textile application and for other relevant applications • ACKNOWLEDGMENTS / ZAHVALA Scaling up the nanogold composite production process In order to reach planed goals, we had to (i) find We acknowledge the funding from KET4CleanProduction, suitable partners and (ii) get a funding on the scale of few million Horizon 2020 Action No 777441. €. When the end of previous period for EU financing was approaching, new set of large R&D funding package for 2021- REFERENCES 2027 - Horizon Europe - was announced. We identified suitable call for our plan: HORIZON-CL4-2021-RESILIENCE-01-20: [1] M. Vukomanovic. Sonochemical synthesis and characterization of Antimicrobial, Antiviral, and Antifungal Nanocoatings (RIA) hydroxyapatite/metal-based composite materials for biomedical [10]. Activities within the project are expected to start at TRL 3 applications : doctoral dissertation = Sonokemijska sinteza in karakterizacija materialov na osnovi hidroksiapatit/kovine za and achieve TRL 6 by the end of the project. The budget of the biomedicinsko uporabo : doktorska disertacija. [Ljubljana: M. call is 23 million € and it is expected to fund 4-5 projects. The Vukomanović, 2012]. XIV, 179 str., ilustr., tabele. deadline is in the end of September 2021. This call is directly [2] M. Vukomanovic, S. D. Skapin, D. Suvorov. Functionalized related to the well-being of citizens in the context of COVID-19 hydroxyapatite/gold composites as "green" materials with antibacterial virus pandemic. It aims to minimise the risk of spread of activity and the process for preparing and use thereof : European patent infections from harmful pathogens arising from everyday human specification EP 2863751 (B1), 2018-07-25. München: European Patent Office, 2018. activities; and create a healthier living and working environment https://register.epo.org/application?number=EP13735469&tab=main and offer holistic solutions to people with health issues. The [3] M. Vukomanovic, U. Repnik, T. Zavasnik-Bergant, R. Kostanjsek, S. research should focus on sustainable synthesis of Skapin, D. Suvorov, Is nano-silver safe within bioactive hydroxyapatite nanocoatings/nanocomposites with effectiveness against a range composites?. ACS Biomater. Sci. Eng., 1 (2015) 935-946. of pathogens. [4] M. Vukomanovic, M. Logar, S. D. Skapin, D. Suvorov, Hydroxyapatite/gold/arginine : designing the structure to create We decided to keep the consortium created in antibacterial activity. Journal of Materials Chemistry. B, Materials for KET4CleanProduction and add new required partners. We biology and medicine, 2014 (2014) 1557-1564. contacted different antimicrobial active component producers [5] Enterprise Europe Network [cited 23th of August 2021]. Available from: https://een.ec.europa.eu/ and received higher interest, presumably due to demonstrator on [6] International Exhibition of Inventions ARCA [cited 23th of August 2021]. textile and a plan regarding the Biocidal Product Regulation. We Available from: also contacted different companies – producers of high traffic http://www.arcahr.com/index.php?task=group&gid=1&aid=118 objects, where antimicrobial materials need to be applied. [7] Regulation (EU) No 528/2012 of the European Parliament and of the Currently 10 partners are forming consortium which is about to Council of 22 May 2012 concerning the making available on the market be finalized and project plan submitted. and use of biocidal products [cited 24th of August 2021]. Available from: https://eur-lex.europa.eu/legal- content/EN/TXT/?uri=celex%3A32012R0528 306 Towards the Market: Novel Antimicrobial Material Information Society 2020, 4–8 October 2021, Ljubljana, Slovenia [8] Interreg Central Europe project KETGATE [cited 24th of August 2021]. xt=true;typeCodes=1;statusCodes=31094501,31094502;programmePeriod Available from:https://www.interreg- =2021%20- central.eu/Content.Node/KETGATE.html %202027;programCcm2Id=43108390;programDivisionCode=null;focusA [9] KET4CleanProduction, Horizon 2020 Action No 777441 [cited 25th of reaCode=null;destination=null;mission=null;geographicalZonesCode=nul August 2021]. Available from: https://www.ket4sme.eu/ l;programmeDivisionProspect=null;startDateLte=null;startDateGte=null;c [10] Call for projects HORIZON-CL4-2021-RESILIENCE-01-20: rossCuttingPriorityCode=null;cpvCode=null;performanceOfDelivery=null Antimicrobial, Antiviral, and Antifungal Nanocoatings [cited 25th of ;sortQuery=sortStatus;orderBy=asc;onlyTenders=false;topicListKey=topi August 2021]. Available from:https://ec.europa.eu/info/funding- cSearchTablePageState tenders/opportunities/portal/screen/opportunities/topic-details/horizon- cl4-2021-resilience-01- 20;callCode=null;freeTextSearchKeyword=antimicrobial;matchWholeTe 307 Technology Transfer in 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 in 2018. Belarus has demonstrated progress in a number of indicators reflecting the practical results of innovations in the The paper informs on current state and future prospects of production sector. Belarus highest rankings were in Human technology transfer in Belarus. It outlines legislation in the field Capital and Research (37th place), Infrastructure (46th place), of technology transfer; key features of the research and and Knowledge and Technological Output (58th place). The development system; system and instruments of technology achieved results are due to the constant improvement of transfer; structure and mission of the Republican Centre for legislation in the field of technology transfer (TT). Technology Transfer, the Business Cooperation Centre “Enterprise Europe Network Belarus” and its services provided 2 THE LEGISLATIVE CONTEXT to innovation activity agents. Finally, the recommendations are The purpose of the legislation and policies of the Republic of given to improve legislation in the field of technology transfer Belarus in the field of TT is to facilitate the transfer of in Belarus. technologies developed with government funding in order to KEYWORDS ensure sustainable growth of national economy and to increase competitiveness of local products [4]. Technology transfer (TT), legislation, public research organizations, intellectual property rights (IPR), spin-off, R&D Currently, Belarus has more than 50 regulatory legal acts contracts related to TT. 1 INTRODUCTION The analysis of Belarusian legislation shows that it regulates the Belarus is a country with 9,5 million inhabitants, 451 public following relationships in the field of TT: R&D organizations (PROs) and 25600 research personnel. The structure of research personnel remains practically unchanged: 1. Public funding of fundamental and applied research researchers – 65,2%, technicians – 6,5%, support personnel – 2. Transfer of developed technologies to state enterprises and 28,3% [1, 2]. organizations 3. Transfer of developed technologies to enterprises and Belarus is a small, open, upper-middle income economy. The organizations with a mixed form of ownership, small country is not well endowed with natural resources. It largely business, and foreign firms relies on imported energy and raw materials and has a historical 4. Dissemination of information in the field of TT specialization in processing. The main activities of Belarusian 5. Establishment of organizations related to TT (technology industrial sector are engineering (agricultural technology and transfer centers, science and technology parks, venture specialized heavy vehicles), potash fertilizers, and refining capital organizations) (which relies on oil supplies from Russia). These sectors 6. Ownership of inventions and remuneration for using the depend heavily on external demand. Trade openness is among inventions. highest in the region, with a ratio of merchandise exports to GDP of 48% in 2020 (52% in 2019) [2]. In recent years the government expenditure on R&D in Belarus was at 0,45% of GDP [2]. In the next five years Belarusian Belarus is ranked 64th in the Global Innovation Index 2020 [3], economy and science are faced with the task of reaching R&D that is eight places up from the 2019 and 22 places higher than financing of 1% of GDP. Permission to make digital or hard copies of part or all of this work for personal or While allocating public funds for applied research to contactor classroom use is granted without fee provided that copies are not made or the state enterprise is simultaneously assigned to commercialize distributed for profit or commercial advantage and that copies bear this notice and anticipated research results. If, for some reason, the state 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). enterprise is not using the developed technology or product, the Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia contractor is obliged to pay back the allocated funds to the state © 2020 Copyright held by the owner/author(s). budget. 308 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia A. Uspenskiy et al. Every year Belarusian PROs create over 400 new products and technologies for commercialization at state enterprises [1, 2]. The dissemination of information in the field of TT is regulated The plan for this year is to introduce about 470 new by the Law of the Republic of Belarus No. 250-Z “On scientific technologies and products. and technical information” dated 05.05.1999, and the Law of the Republic of Belarus No. 170-Z “On state secrets” dated After Belarus gained independence in 1991, the first normative 19.06.2010 [7, 8]. act regulating the acquisition of property rights on the results of scientific and technical activities and the disposal of those The establishment of organizations related to TT regulates the rights was the Presidential Decree No. 432. According to it, Presidential Decree No. 1 “On approval of the Regulations on property rights resulted from research subsidized (in whole or the procedure for creating subjects of innovation infrastructure in part) by public funds were obtained by the state. The IP right and amendments and additions to the Decree of the President of holders could be a government customer and (or) a research the Republic of Belarus dated September 30, 2002, No. 495” contractor – PRO. Legal practice showed that de facto, the state dated 03.01.2007 [9]. According to it, the center for technology retained ownership of IP rights and consequently research transfer (CTT) is an organization with an average number of contractors were not interested to commercialize them. employees up to 100 persons, tasked to ensure the transfer of innovations from the sphere of their creation to the sphere of In 2013, the Presidential Decree No. 59 approved new practical use. A scientific organization with a separate TT Regulation on the commercialization of the results of scientific subdivision with at least 7 employees can also be recognized as and technical activities created at the expense of state funds, CTT, and use all privileges and advantages granted to CTT by which expanded opportunities for research contractors to obtain law. In Belarus CTTs are not funded from the state budget. rights on results of R&D activities. Still, in spite of the amendments made to Decree No. 59 in 2018, the legal 3 THE REPUBLICAN CENTRE FOR procedures to obtain IP rights remain overly complex and TECHNOLOGY TRANSFER unwieldy. Research contractors do not have “the right to risk”, The Republican Centre for Technology Transfer (RCTT) was due to the requirement to pay back funds in case of failure to established in 2003, under the aegis of the State Committee on commercialize the developed technology of product. Since the Science and Technology of the Republic of Belarus, the state retains the IP rights the transfer of technologies developed National Academy of Sciences of Belarus, the United Nations with government funding to private enterprises and foreign Development Programme and the United Nations Industrial companies is carried out not through the sale or licensing of Development Organization [10]. IPR, but under commercial agreements with technical assistance, research and technical cooperation agreements, and RCTT’s primary goal is to facilitate transfer of technologies joint venture agreements. For the same reason the Belarusian developed in Belarus and abroad for sustained growth of the PROs don’t create spin-offs. country’s economy and increase the competitiveness of Belarusian industry and agriculture, provide advice to CTTs in The Belarusian law on patents for inventions, utility models and the country. industrial designs was amended several times [5]. This law regulates the property and associated personal moral relations Tasks set for RCTT: arising in connection with the creation, legal protection and use - create and maintain information databases meant for serving of inventions, utility models, and industrial designs. The clients in the technology transfer sector; legislation is in harmony with international treaties and, in - provide RCTT clients with access to foreign technology principle, it enables the protection of intellectual property transfer networks; objects of domestic and foreign entities. In addition, some - assist innovation activity agents in development and government decrees have set the legal framework for the promotion of their innovation and investment projects; sharing of royalties and other IPR incomes between inventors - train specialists in research- and innovation-related and employers [1]. According to legislation, remuneration is entrepreneurship; paid in the amount and on terms specified in agreements - establish RCTT offices across the country, to create a unified between the employee and the employer – the minimum level national network of technology transfer centers; of remuneration shall be determined by the Council of - promote international technical and scientific cooperation and Ministers of the Republic of Belarus [6]. exchange of experts. Legislation doesn’t limit maximum remuneration to authors RCTT is a consortium with the headquarters in Minsk. It’s (co-authors) for the created objects of industrial property rights. made up of: If the employer decides to keep an invention as a secret know- - 5 regional offices and 30 branch offices at research how, then the reward for the creation of objects of industrial organizations, institutes, universities, enterprises in Brest, property rights to authors, co-authors and individuals should be Vitsebsk, Homel, Hrodna, Lida, Minsk, Mahileu, Novapolatsk paid as a lump sum within three months of employer’s decision. and other cities and towns across Belarus; Businesses may combine both options: keep some inventions - 91 foreign partners in 23 countries: Armenia (3), Azerbaijan secret and patent the other abroad (e.g. innovative export (2), China (25), Denmark (1), Great Britain (2), Germany (4), products). The inventor should be compensated equally Georgia (1), India (1), Iran (1), Italy (1), Lithuania (1), regardless of the option. 309 Technology Transfer in Belarus Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Moldova (1), the Republic of Korea (4), Poland (3), Kazakhstan 3. legislative acts requiring inclusion into job description of (6), Russia (19), the USA (2), Sweden (1), the Republic of employees of all state organizations engaged in R&D the South Africa (1), Uzbekistan (2), the Czech Republic (2), obligation to engage in TT, and the administration of Ukraine (7), Vietnam (2). organizations to take into account TT activities when - 2 overseas field offices. assessing the work of employees; 4. legislative acts stimulating the transfer of technologies RCTT staff is a certified member of 12 technology transfer developed with government funding to small businesses networks, in particular, Russian Technology Transfer Network (“gratuitous” transfer); (since 2004), yet2.com (since 2005), AUTM (since 2012), 5. legislative acts stimulating the creation and funding of TT Enterprise Europe Network (since 2015) and others. organizations (departments); and 6. introduce the technology transfer course into the curricula of higher educational institutions. RCTT offers its services to innovation activity agents in Belarus as well as foreign companies and investors. 5 CONCLUSIONS RCTT has a web-portal (https://ictt.by), with several subject This paper provides an overview of the current state of sections and databases such as: “Virtual exhibition of the NAS technology transfer in Belarus. It highlights several legal issues of Belarus”; “Catalogue of innovation offers by organizations that need to be addressed in the future to make technology of the NAS of Belarus”; “New partnership opportunities”, to transfer more efficient. present in real-time offers and requests from RCTT, EEN, and AUTM networks; “Catalogs”; “Manuals”; “Investment and ACKNOWLEDGMENTS venture funds”; “Crowdfunding”; “IP auctions”; “IP insurance”; We would like to thank the National Academy of Sciences of “Legislation” covering the laws and regulations applicable to Belarus and the State Committee on Science and Technology of innovation activity in Belarus and foreign countries; the Republic of Belarus for their constant support of RCTT “Technoparks of Belarus”, and others. activities and express gratitude to all our colleagues who work in technology transfer for their help and advice. RCTT provide services to more than 250 Belarusian state organizations, private enterprises and individuals. The National REFERENCES Academy of Sciences, Belarusian State University, Belarusian [1] Innovation for Sustainable Development Review of Belarus. United National Technical University are among the centre’s clients. Nations Economic Commission for Europe. 2017: With the support from RCTT in 2003–2020 more than 6200 https://unece.org/DAM/ceci/publications/IPR_Belarus/_Eng_Innovation 4SD_Belarus_-_FINAL_LB_REV.pdf Belarusian specialists have been trained and instructed in [2] National Statistic Committee of the Republic of Belarus: various fields of technology transfer at 510 local and https://www.belstat.gov.by/ [3] Global Innovation Index 2020: international workshops, seminars and exhibitions. https://www.wipo.int/edocs/pubdocs/en/wipo_pub_gii_2020.pdf [4] Политика и законодательство в сфере трансфера технологий: RCTT was involved in implementation of more than 30 зарубежный и национальный опыт/ Д.М. Вильтовский, Е.П. Машонская, А.А. Успенский; под общ. ред. А.А. Успенского. – international projects related to improving the competencies of Минск : Ковчег, 2010. – 60 с.: researchers and representatives of small and medium-sized http://ictt.basnet.by/Docs/Policies_Legislation_in_the_Technology_Tran sfer_20100915.pdf businesses funded by UNDP, UNIDO, FP7, Baltic Sea Region [5] Law of the Republic of Belarus No. 160-Z of December 16, 2002, on Programme, CEI, Latvia, Lithuania and Belarus Cross Border Patents for Inventions, Utility Models, and Industrial Designs (with Cooperation Programme, The Swedish Institute, Chinese amendments on 18.12.2019). [6] Decree of the Council of Ministers from 28.02.2002 No. 288 on Government and others. regulations of conditions for stimulation of creation and use of objects of industrial property from 28.02.2002 No. 288 (with amendments on 19.06.2019 No. 402). Since 2015 RCTT is a coordinator of the project “Creation of [7] Law of the Republic of Belarus of 05.05.1999 No. 250-З "On scientific the Business Cooperation Centre “Enterprise Europe Network and technical information". [8] Law of the Republic of Belarus of June 19, 2010 No. 170-З "On State Belarus” (BCC “EEN Belarus”)”. The aim of the project is to Secrets" (as amended on December 10, 2020). encourage the provision of services to support cross-border [9] Decree of the President of the Republic of Belarus dated January 3, 2007 business cooperation, technology transfer, and research No. 1 “On approval of the Regulations on the procedure for creating subjects of innovation infrastructure and amendments and additions to collaboration on the basis of mutual benefit via the Enterprise the Decree of the President of the Republic of Belarus dated September Europe Network. 30, 2002 No. 495”. [10] Республиканский центр трансфера технологий: 15 лет в национальной инновационной системе (история развития, 4 FURTHER DEVELOPMENT структура, методология, деятельность, перспективы) / А.Ал. Успенский, В.В. Кузьмин, Ал.А. Успенский, М.С. Прибыльский, The 18 years of RCTT work experience show that to improve В.В. Земцов, А.И. Долгополова – Мн.: Центр системного анализа и commercialization of technologies developed with government стратегических исследований НАН Беларуси, 2018. – 78 с.: https://ictt.by/Docs/news/2018/06/2018-06- funding in Belarus, it is necessary to develop and adopt: 15_01/RCTT__15th_Anniversary__2003-2018__RU.pdf 1. a law similar to Bayh-Dole Act; 2. legislative acts that will allow the contractor to restrict access to research results and inventions if public disclosure could damage commercial interests; 310 DODATEK / APPENDIX 311 INTRODUCTION AND AIM OF THE CONFERENCE Conference topic: how to survive the valley of death? How to enable investors in early stage deep tech ventures: buying a lottery ticket vs building the jackpot? How to integrate the PoC funding in the national and regional innovation ecosystem? What is the role of TTOs, PROs, governments and industry in the setting up a successful PoC funding scheme? Illustration: Dusko Odić. 2021. Objectives of the Conference The main aim of the Conference is to promote knowledge exchange between academia and industry, in order to strengthen the cooperation and transfer of innovations from research labs into industrial exploitation. The Conference goal is also further strengthening the knowledge base and experiences of technology transfer professionals at public research organisations. In the past events, we hosted more than 2600 participants, including investors, inventors, researchers, students, technology commercialization and intellectual property experts, start-up funders, industrial development experts etc. We have successfully organized twelve competitions to award the teams with their technology and business proposition with the biggest commercial potential, which led to successful start-ups and licensing contracts. Biannually we organise Research2Business (R2B) pre-scheduled meetings in order to give the participants additional opportunity to meet and discuss possible cooperation. Researchers presenting their work being financed by Slovenian Research Agency (ARRS) is another channel for enterprises to get familiar with recent discoveries and development opportunities. Conference prize for the best innovations in 2021 The main objective of the special prize for innovation is to encourage commercialization of inventive/innovative technologies developed at public research organizations and to promote cooperation between research organizations and industry. One of the main objectives is also 312 promoting the entrepreneurship possibilities and good practices in the public research organizations. Researchers are preparing business models for their technologies and present them to an international panel of experts in a pitch competition. They need support in many aspects of their path from research to industrial application. The researchers and their team need assistance, knowledge and tools to develop business models, find appropriate partners, form a team, and secure financial resources to bridge the gap from publicly funded research to the market, either in their own start-up (spin-out) company or by licensing out their technology. How shall they do it and how can we help them? The Conference pitch competitions in the last eleven years resulted in spin-out company creation or licensing case development in at least one case per competition each year. In many cases, young researchers that participated in pitch competition in the past years, have been involved for the first time in an organized and structured process of development business model around their technology and preparation of the targeted (pitch) presentation about their planned venture to investors and technology commercialization experts. WIPO IP Enterprise Trophy The aim of the WIPO IP Enterprise Trophy is to stimulate Slovenian enterprises to intensify their cooperation with public research organisations. We wish to expose as a good practice those enterprises that are constantly and methodologically using the IP system in their business activities. WIPO Medal for Inventors The goal of the WIPO Medal for Inventors is to award inventive and innovative activity of Slovenian public researchers and to recognize their contribution to national wealth and development. Research2Business meetings In the course of the conference, pre-scheduled Research2Business (R2B) meetings will take place, allowing the representatives of companies and research institutions to discuss possible development solutions, inventions and commercially interesting technologies. Such meetings present an excellent basis for possible future research cooperation and business synergies. Opportunities arising from publicly funded research projects / presentations of successful scientific projects Researchers will be presenting their work that is being financed by Slovenian Research Agency. Scientific papers on TT and 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); Key inventions and their protection for the greater good; Market perspective through different TRL phases; Financing different TRL phases; Setting-up internal Proof-of-Concept funds at public research organisations; Lowering the Proof-of-Concept risks; Shortening the time-to-market for different technological fields; Spin-out vs spin-off; Key trends in IP protection and TT for mid TRL phases; Examples of IP protection in Artificial Intelligence; The role of patents in Artificial Intelligence; Activating the IP protection and TT players in the SEE region; National IP protection: a profit or a hindrance; Governmental support vs institutional support of IP protection and TT; IP and internal secret know-how: who prefers what and why; Other, chosen by the contributor 313 School section 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. Target audience and benefits Target audience of the conference are researchers, students and post-graduate students with entrepreneurial ambitions, representatives of industry, established and future entrepreneurs, innovators and also representatives from governmental institutions and policy-making organizations. Introduction to the International Technology Transfer Conference The International Technology Transfer Conference (ITTC) is organized by the Jožef Stefan Institute (Center for Technology Transfer and Innovation) for the 14th 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 (IS2021), organized by the Jožef Stefan Institute. The Center for Technology Transfer and Innovation at the Jožef Stefan Institute is the coordinator of the project KTT (2017-2022), coordinator of Enterprise Europe Network Slovenia, and is a financially independent unit. The CTT is presently involved in 4 projects, having recently been involved in three additional ones. The Conference has been organized with the support of partners from the KTT project (2017-2022). The previous project KTT, from 2013 through 2014, was the first project within which technology transfer in Slovenia was systematically funded from national funds. There were 6 partners involved, but the project only lasted for 17 months. The current KTT project, 2017-2022, comprises 8 partners, all public research organizations (PROs), represented by their respective technology transfer offices (TTOs), namely, 4 leading institutes and 4 renowned universities. The project's mission is twofold: the strengthening of links and increasing the cooperation of PROs and industry and the strengthening the competences of TTOs, researchers and enterprises. Most (80%+) of the finances go to human resource financing. Support of Slovenian Industry The goal of the KTT project is to support the industry in Slovenia, rather than an outflow of knowledge abroad or great profit for PROs. Collaboration between PROs and SMEs in Slovenia should be strengthened. However, Slovenian companies prefer contract and collaborative cooperation to buying licenses and patent rights. Also, a relatively low added value per employee and a low profit margin are not stimulating the research-industry collaboration. 314 Investing into Intellectual Property Rights Despite the above stated it is important to invest in patents and other forms of intellectual property (IP). Investments in intellectual property increase licensing opportunities and the IP position of the Slovenian knowledge worldwide. Research2Business meetings One-to-one research-to-business pre-scheduled (virtual) meetings allow the representatives of companies and research institutions to discuss possible development solutions, inventions and commercially interesting technologies. Such meetings present an excellent basis for possible future research cooperation and business synergies. The meetings focus on applications, solutions and expertise in natural sciences like electronics, IT, robotics, new materials, environment, physics, chemistry and biochemistry. Companies and researchers book meetings also with technology transfer experts from the Center of technology transfer and innovation. The meetings are held virtually through b2match platform. The Research-to-business meetings at the Conference were co-organized in collaboration with the Enterprise Europe Network partners. Strengthening the Competences of TTOs The goal of the KTT project is to establish technology transfer centers in Slovenia as integral parts of PROs, which shall, first and foremost, strive to serve the interests of the researcher and the PRO. The TTOs shall assist the researcher throughout the entire procedure of the industry- research cooperation, by raising competences and educating, taking care of legal and administrative issues, and promote research achievements among the industry. Lastly, TTOs shall support the cooperation already established by research groups. 315 ACKNOWLEDGEMENTS The editors and organizing committee of the Conference would like to express cordial thanks to all who helped make the 14th 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: Dr. Jon Wulff Petersen from Plougmann Vingtoft Matthias Keckl from Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič from Slovene Enterprise Fund Gregor Klemenčič from Deep Innovations for their evaluation of written technology commercialization proposals and selection of winning teams, authors of inventive technologies with the best potential for commercialization of the technologies, developed at Public Research Organizations. We are particularly grateful to the members of the EVALUATION COMMISSION: Alojz Barlič from Slovenian Intellectual Property Office (SIPO) Matthias Keckl from Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič from Slovene Enterprise Fund, for their evaluation and selection of the awardees of the WIPO IP ENTERPRISE TROPHY and WIPO MEDAL FOR INVENTORS. 316 INTRODUCTION TO THE ITTC CONFERENCE AS A WHOLE Value creation should be at the heart of valorization activities and denotes a process where stakeholders' benefits are articulated, created, and captured throughout the valorization process. Value in this sense is, however, not static or absolute. Value is relative and usually changes with the stakeholders addressed. Hence, value creation implies, wherever it is meaningful and possible, that the benefits for a stakeholder must be higher than the efforts, risks and resources needed to obtain the promised benefits. Turning any publicly financed knowledge, i.e. intellectual property in its broadest sense to socio-economic benefits calls for a much wider scope of activities than just industrial rights management. The Center for Technology Transfer and Innovation at Jožef Stefan, if anyone, has always been very much aware of this. Thus, we have set in motion in the past ten years of our existence, based on the dowry of additional 15 years of a Technology transfer office of Jožef Stefan Institute, many different changes. These changes have influenced the Institute and the society around us. We have created processes that any Slovenian public research organization would be able to use. We have created an internal ecosystem of activities and interactions with essential innovation actors, allowing us to research, assess, understand, co- create, offer, and fine-tune the academia-industry-society helix on the most bottom-up, most influential level. We are proud of that. Now we must go on. We created a proof of concept of activities – of what the ecosystem in our environment could look like in a scalable way. Others should take the essential elements (codes of practices we have so prudently developed through the past 10 years of our existence) and use them to their liking and the capacities of their institutions. There are differences among actors in the ecosystem. But once these differences have been understood, there are just similarities that can be harvested in the quest for better valorization results. We are all unique. And we are all very similar. Acknowledging this means not fighting better from us but building on their experience. “Yeah, everybody wants change. Don’t nobody wanna change though. (NF)” We need to creatively and constructively take part in knowledge valorization for a better future, even if it means it is our turn to change. 317 Day 1 318 OVERVIEW OF THE PROGRAMME 7 October 2021 (hybrid teleconference, virtual and live) MAIN SESSION 08.30 – 09.00 Registration Welcome address (in Slovene language) Prof. Dr. Mitja Slavinec, State Secretary, Ministry of Education, Science and Sport 09.00 – 09.15 Simon Zajc, State Secretary, Ministry of Economic Development and Technology Prof. Dr. Boštjan Zalar, director, Jožef Stefan Institute Round table: Future of Knowledge Transfer in Slovenia and EU (in Slovene language) Prof. Dr. Gregor Majdič, University of Ljubljana Prof. Dr. Boštjan Zalar, Jožef Stefan Institute Prof. Dr. Maja Ravnikar, National Institute of Biology 09.15 – 10.30 Prof. Dr. Klavdija Kutnar, University of Primorska Prof. Dr. Matej Makarovič, Faculty of information studies in Novo mesto Prof. Dr. Urban Bren, University of Maribor Prof. Dr. Robert Repnik, Slovenian Research Agency Gregor Klemenčič, Deep Innovations Gregor Umek, mag., Ministry of Economic Development and Technology mag. Damjana Karlo, Ministry of Education, Science and Sport 10.30 – 12.00 Pitch competition: Best innovation with commercial potential 12.00 – 13.00 Lunch break Award announcement: Best innovation with commercial potential 13.00 – 13.20 Award announcement: WIPO IP Enterprise Trophy Keynote speech: PoC funding of research spin-offs Matthias Keckl, Managing Partner, Fraunhofer Technologie-Transfer Fonds (FTTF) GmbH Keynote speech: CEETT Platform – Central Eastern European 13.20 – 15.30 Technology Transfer Platform Natalija Stošicki, Director, Investments and EU Programmes Department, SID Bank / SID – Slovenska izvozna in razvojna banka Paper presentations: scientific papers on technology transfer and intellectual property 319 Opportunities arising from publicly funded research projects / 15:30 – 16.50 presentations of successful scientific projects Award announcement: WIPO Medal for Inventors 16.50-17:00 Closing PARALLEL SESSION I 10:00 – 13:20 Research2Business meetings (R2B meetings) PARALLEL SESSION II Connecting high-school education system with academia: Presentations of selected research topics from Jožef Stefan Institute and proposals for cooperation Povezovanje šolskega sistema z akademsko sfero: Predstavitve izbranih raziskovalnih tem Instituta “Jožef Stefan” in predlogi za sodelovanje Agenda (in Slovene language) 13:20-13:25 Uvodni pozdrav 13:25-13:40 Predstavitev možnosti sodelovanja Instituta »Jožef Stefan« z šolstvom, CTT - Obiski instituta »Jožef Stefan« med šolskim letom - Dan odprtih vrat in Teden odprtih vrat na IJS - Izobraževanja, usposabljanja in predavanja za učitelje in profesorje - Mentorstva pri raziskovalnih nalogah dijakov 13:20 – 15:20 - Aktivnosti promocije znanosti in raziskovalnega dela - različne evropske - projekte in iniciative ter druge aktivnosti (Znanost z in za družbo / Science - with and for society) 13:40-14:20 Predstavitev odsekov s področja kemije, biokemije, materialov in okolja - Odsek za znanosti o okolju, O2 - Odsek za biokemijo, molekularno in strukturno biologijo, B1 - Odsek za fizikalno in organsko kemijo, K3 - Odsek za Sintezo materialov, K8 14:20-14:30 Predstavitev odsekov s področja fizike - Odsek za tehnologijo površin, F4 14:30-15:00 Predstavitev odsekov s področja elektronike in informacijske tehnologije 320 - Odsek za umetno inteligenco, E3 - Laboratorij za odprte sisteme in mreže, E5 15:00-15:20 Morebitna dodatna vprašanja za raziskovalce 15:20 Zaključek 321 WELCOME ADDRESSES From 9:00 to 09:15 Honourable Speakers: Prof. Dr. Mitja Slavinec, State Secretary Ministry of Education, Science and Sport Povzetek uvodnega pozdrava / Abstract of the Welcome address Govorca veseli in se zahvaljuje organizatorju konference, Centru za prenos tehnologij in inovacij na Institutu »Jožef Stefan«, da ima uvodni nagovor na zelo pomembnem srečanju. Na izvedbeni ravni, kjer znanje nastaja, sodelovanje dobro poteka. Sodelovanje je odlično na univerzah in institutih, prav tako je okrepljeno sodelovanje med izobraževanjem in raziskovanjem na institucionalni osnovi, kar dokazuje tudi udeležba na današnjem dogodku, saj so prisotni predstavniki univerz in raziskovalnih institutov. Na drugi strani se zna gospodarstvo tudi relativno hitro povezati, ker jim to narekuje njihova gospodarska pobuda. Največ lahko naredimo na tem, kako ta znanja in raziskave čimprej prenesti v gospodarstvo. Pri raziskovanju je možno zaznati najmanj dve ravni. Pri bazičnih raziskavah je Slovenija na nekaterih področjih v svetovnem vrhu. Manj uspešni smo pri prenosu in implementaciji aplikativnih raziskav v celotni družbi in gospodarstvu. Država je od leta 2017 dalje s 6 mio EUR podprla pravo pot za prenos tehnologij, ki se odvija s pomočjo pisarn za prenos tehnologij. MIZŠ namerava to podporo še okrepiti in okrepiti sodelovanje z MGRT. Nujno je sodelovanje z MGRT, ker MIZŠ podpira nizke TRL-je in MGRT višje. Vendar srednji TRL-ji še vedno »ostajajo v zraku«. K sodelovanju je potrebno poleg MGRT povabiti še Gospodarsko zbornico Slovenije, ki ima povezovalno vlogo in dostop do gospodarstva. S sodelovanjem vseh deležnikov bo Slovenija postajala družba, kjer se bo več delalo z glavo in manj z rokami. Simon Zajc, State Secretary, Ministry of Economic Development and Technology Povzetek uvodnega pozdrava / Abstract of the Welcome address Živimo v nenavadnih časih, ko je COVID-19 razkril pomanjkljivosti in šibke točke slovenskega gospodarstva in nabavnih verig. Slovenski gospodarski model mora biti z uvedbo inovacij v gospodarstvo odpornejši za prehod v zeleno družbo. 322 V Evropski skupnosti se vsi usmerjamo v zeleni, digitalni prehod. Prehod je mogoče narediti samo na krilih inovacij, ki so ključni dejavnik uspeha podjetij, konkurenčnosti nacionalnih držav in Evropske skupnosti kot celote ter družbe, ki je usmerjena k okolju prijaznem načinu življenja. Načrt za okrevanje in odpornost (NOO), ki bo podlaga za koriščenje razpoložljivih sredstev iz Sklada za okrevanje in odpornost (RRF), nam ponuja veliko priložnosti za okrevanje. V Slovenski industrijski strategiji 2021-2030, ki jo je pripravilo Ministrstvo za gospodarski razvoj in tehnologijo, so začrtali zelen, digitalen in ustvarjalen razvoj industrije in gospodarstva do leta 2030. Na drugi strani je na evropski lestvici upadla slovenska inovacijska uspešnost v primerjavami z drugimi državami EU. Slovenija ne sodi več med močne, ampak zmerne inovatorje, ker je imela padec uspešnosti v obdobju 2018 – 2020. Velik izziv predstavlja zagotovitev stabilnih vzpodbud države za znanost. Na drugi strani moramo v naslednjih desetih letih zagotoviti tako podjetniške naložbe v raziskave in inovacije kot naložbe na raziskovalnem nivoju. Pri tem ne moremo računati samo na evropska sredstva, ampak tudi na našo premišljenost pri dodeljevanju nacionalnih sredstev za ključne finančne instrumente, ki bi jih morali izvajati vsako leto brez vmesnih premorov. Ministrstvo za gospodarski razvoj in tehnologijo bo okrepilo vlogo SPIRIT-a na področju inovacij in tehnologij ter pri podpori povezovanju med industrijo in javnimi raziskovalnimi organizacijami. Ministrstvo bo še naprej spodbujalo prenos znanj in tehnologij na trg z vzpostavljenimi strateškimi, razvojnimi in inovacijskimi partnerstvi, ki po začetnih težavah delujejo vedno bolje prav zaradi vzpostavljenih povezav s številnimi podjetji, društvi in raziskovalnimi organizacijami. Pomembno je, da se bodo vsi deležniki v Sloveniji prizadevali za prenos inovacij na trg – iz bazičnega razvoja v tržne aplikacije. Prof. Dr. Boštjan Zalar, director, Jožef Stefan Institute Povzetek uvodnega pozdrava / Abstract of the Welcome address Govorec je v uvodnem in pozdravnem nagovoru izpostavil Center za prenos tehnologij in inovacij (CTT), vodjo centra dr. Špelo Stres, njene sodelavke in sodelavce, ki so organizirali že 14. Mednarodno konferenco o prenosu tehnologij. Na teh konferencah sodelavke in sodelavci CTT z učinkovitim prenosom tehnologij v prakso še posebej krepijo sodelovanje med znanstveno sceno in gospodarstvom. Pisarne za prenos tehnologij naj bodo ključne v procesu prenosa tehnologi ter pri sodelovanju z deležniki, ki so dobro vpeti v inovacijskem sistemu. Najpomembnejša vprašanja, ki bi jih bilo potrebno nasloviti, so: 323 • Vzpostavljanje sklada za preverbo koncepta na nacionalni in na institucionalnih ravneh • Problematika ustanavljanja odcepljenih podjetij • Odnosi med raziskovalno in tehnološko infrastrukturo ter centri odličnosti • Večji družbeni vpliv javnih raziskovalnih organizacij in univerz ter njihovo boljše povezovanje z družbo • Vloga odprte znanosti v povezavi z intelektualno lastnino • Vpliv razdrobljenosti raziskovalnega sistema v Republiki Sloveniji ter ocenjevanja učinkovitosti sistema in vpliva na kakovost delovanja pisarn za prenos tehnologij • Sodelovanje med SRIP-i in pisarnami za prenos tehnologij Na današnji konferenci so prisotni skupaj s pisarnami za prenos tehnologij vsi, ki soustvarjajo inovacijski sitem v Sloveniji. Na zaključku pozdravnega nagovora se je govorec zahvalil sodelavkam in sodelavcem Centra za prenos tehnologij in inovacij za organizacijo današnje okrogle mize in za že 14. dogodek po vrsti. 324 ROUND TABLE: THE FUTURE OF KNOWLEDGE TRANSFER IN SLOVENIA AND EU From 09:15 to 10:30 (in Slovene language) Moderators: Dr. Špela Stres, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Dr. Vojka Žunič, National Institute of Chemistry, KnowledgeTransfer Office Round table speakers: Prof. Dr. Gregor Majdič, University of Ljubljana Prof. Dr. Boštjan Zalar, Jožef Stefan Institute Prof. Dr. Maja Ravnikar, National Institute of Biology Prof. Dr. Klavdija Kutnar, University of Primorska Prof. Dr. Matej Makarovič, Faculty of information studies in Novo mesto Prof. Dr. Urban Bren, University of Maribor Prof. Dr. Robert Repnik, Slovenian Research Agency Gregor Klemenčič, Deep Innovations Gregor Umek, mag., Ministry of Economic Development and Technology Mag. Damjana Karlo, Ministry of Education, Science and Sport Povzetek okrogle mize / Abstract of the Round table Okroglo miza sta odprli moderatorki dr. Špela Stres, MBA, LLM, Vodja Centra za prenos tehnologij in inovacij na Institutu ‘’Jožef Stefan’’, in dr. Vojka Žunič, Vodja pisarne za prenos znanja na Kemijskem inštitutu. Uvodni nagovor moderatorke dr. Špele Stres: Podatki o inovacijah in internacionalizaciji kažejo, da je potrebno omogočiti skladno in na mejnikih temelječe financiranje inovacij ter podpreti internacionalizacijo. Naš cilj je, da izboljšamo politike za celostno nemoteno preoblikovanje rezultatov raziskav v ekonomsko in družbeno vrednost. Moderatorka dr. Vojka Žunič je predstavila udeležence okrogle mize: • prof. dr. Gregor Majdič, rektor Univerze v Ljubljani • prof. dr. Boštjan Zalar, direktor Instituta ‘’Jožef Stefan’’ • prof. dr. Maja Ravnikar, direktorica Nacionalnega inštituta za biologijo • prof. dr. Klavdija Kutnar, rektorica Univerze na Primorskem • prof. dr. Matej Makarovič, dekan Fakultete za informacijske študije v Novem mestu • prof. dr. Urban Bren, prorektor za prenos znanja Univerze v Mariboru 325 • prof. dr. Robert Repnik, direktor Javne agencije za raziskovalno dejavnost Republike Slovenije • mag. Gregor Umek, vodja Sektorja za industrijo, spodbujanje inovativnosti in tehnologije v Direktoratu za internacionalizacijo, podjetništvo in tehnologije (Ministrstvo za gospodarski razvoj in tehnologijo) • mag. Damjana Karlo, vodja Sektorja za strukturne sklade na področju raziskovalno- razvojne dejavnosti (Ministrstvo za izobraževanje, znanost in šport) • Gregor Klemenčič, Deepinovations (Nizozemska) 1. Gregor Klemenčič, sr. principal innovation researcher for e-health data driven solutions za Philips Research (Medical systems) na Nizozemskem in soustanovitelj ter solastnik mednarodnega podjetja Deep Innovations B.V Gospod Klemenčič je predstavil svoj pogled na inovacijski sistem v naslednjih točkah: • Innovation to market – I2M • Research to application – R2A • Value proposition creation – VPC • The game of rules – IPR • Earning models Curiosity is a personal characteristic of a researcher or entrepreneur. A researcher is looking for an inspiration, learning from white papers and colleagues. Researcher combines different sources of information. It looks like a child play for clever people. Creation is also creation of products and services and how to apply. This is a game for elderly researchers. Researchers have to understand the buyer and not try to sell unique selling points and not even unique buying reasons. Researchers have to find out why buyers become hungry for new innovation applications. We have fundamental, applied and complementary research. Researchers have to try as fast as they can to combine information from different sources domains. It’s a lot of hard work and play as well. If you play, you may do a mistake. Researchers have to learn fast and make NOT TO DO list to ignore or mitigate the risk. Provocative design is another applied approach in the innovation system. Researchers design new solution or concept and they test them with people without asking them what they want. Mixed research teams with different skills from different research areas with non-standard combination of knowledge will bring applications out of the box. New school doesn’t believe much in IP as the old one. Also, how to make money with innovations is different from the old school. New school prefers to organize focused micro meetings, attract micro investors and apply IP stacking or block chain to trace effort input as output values. 326 Iztočnica okrogle mize – dr. Špela Stres: Winston Churchill je rekel, Personally I'm always ready to learn, although I do not always like being taught. Del napredka v človeški zgodovini je povezan s posebno sposobnostjo ljudi, da smo se sposobni učiti. Zato bomo danes uporabili svoje znanje in naslovili nekaj ključnih tematik, ki bodo opredeljevale vsebino področja prenosa znanja in njegove valorizacije v prihodnosti. 2. Prof. dr. Gregor Majdič, rektor Univerze v Ljubljani Vprašanje: Problematika ovir z ustanavljanjem odcepljenih podjetij. Glede na vaše izkušnje tudi iz podjetniškega sveta, če bomo z novim Zakonom o znanstveni razvojni in inovacijski dejavnosti lahko JROji postajali solastniki odcepljenih podjetij, je to pametno, ker bodo institucije v bolj zgodnjih fazah lahko upravljale z inovacijami v podjetniških vodah ali dodaten zaplet, v katerem bodo JRO upočasnjevali razvoj mladih podjetij proti trgu? Ali se vam zdi, da smo zreli za ta korak? Prof. dr. Gregor Majdič: Tak sistem je vzpostavljen v številnih zahodnih državah, dobro deluje ter prinaša velike koristi za akademsko sfero in gospodarstvo, če ta proces pravilno izvajamo. Če se bodo javne raziskovalne organizacije, ki so običajno velike in nekoliko bolj okorne kot so majhna podjetja na trgu, preveč vmešavale v samo delovanje podjetij na trgu, ko bodo le-ta naskakovala nove trge in se internacionalizirala, to zna biti ovira. Če pa bodo raziskovalne organizacije preko pisarn za prenos tehnologij to upoštevale in pustile malim podjetjem samostojnost, hkrati pa sodelovale pri potrebni pomoči, pa je to zagotovo lahko velika prednost in nova dodana vrednost, ki bo omogočila takšnim podjetjem, da bodo lažje prišla na trg in lažje izhajala iz akademskih institucij ter prenašala znanje v gospodarstvo v Sloveniji in v mednarodnem prostoru. 3. Prof. dr. Maja Ravnikar, direktorica Nacionalnega inštituta za biologijo Vprašanje: Vzpostavljanje sklada Proof-of-Concept. Na NIB ste prav v letošnjem letu uspešno ustanovili novo visokotehnološko podjetje. V letu 2021 so SID banka, HBOR in EIF podpisali pogodbo za prvi PoC sklad v regiji. Na posamičnih institucijah, IJS (od leta 1998), UL (od leta 2020) in UM (od leta 2020) - PoC skladi delujejo že nekaj časa in podpirajo raziskovalce na njihovi poti proti trgu. Kako se do tega opredeljuje NIB? Je 40 mio EUR v skladu PoC za dve državi preveč za regijo, ki je šele na začetku svoje poti povezovanja z gospodarstvom ali pa celo premajhen vložek za regijo, ki mora nujno ustvariti množico gazel, da se bo vrnila med inovacijsko uspešne države? Prof. dr. Maja Ravnikar: Na NIB smo pred desetimi leti ustanovili prvi spin-out Biosistemika. Pri tem je podjetju zelo pomagal mehanizem projektov VALOR. PoC skladi bodo omogočali javnim raziskovalnim organizacijam, da pridejo v svojih raziskavah na srednje TRL-je, ker takšnega financiranja v tem trenutku v Sloveniji ni. V letošnjem letu smo na NIB za novoustanovljeno podjetje pridobili močne investitorje, ki so lahko takoj investirali samo v opremo več kot milijon evrov in odkupili intelektualno lastnino, vendar to ni običajno stanje pri ustanavljanju spin-out podjetij. 327 Če bodo sredstva PoC sklada primerno odrejena, bo to velik korak naprej, ker akademska sfera in javne raziskovalne organizacije nimajo dovolj potrebnih sredstev za premagovanje »doline smrti«. ARRS financira tako bazične kot aplikativne projekte, ki pa se ocenjujejo več ali manj kot bazični. Projekti izkazujejo svojo aplikativnost z zainteresiranostjo podjetij za takšno vrsto raziskav. Takih financiranih projektov je v Sloveniji bistveno premalo. 4. Mag. Damjana Karlo, vodja Sektorja za strukturne sklade na področju raziskovalno- razvojne dejavnosti (Ministrstvo za izobraževanje, znanost in šport) Vprašanje: Kako vidite problematiko ustanavljanja odcepljenih podjetij na MIZŠ? Kako vidite možnosti pomoči zasebnim podjetjem v solastništvu JRO, v luči državnih pomoči? Vemo, da bi na nekaterih področjih (biotehnologija, medicina, nanomateriali, itd) morali biti začetni vložki v bodoče gazele precej veliki, tudi milijonski. Mag. Damjana Karlo: Z novim Zakonom o znanstvenoraziskovalni in inovacijski dejavnosti (ZZRID) je predvidena možnost za ustanovitev odcepljenih podjetij. To in celotno področje inoviranja je tipično medresorsko vprašanje predvsem med MIZŠ in MGRT. Najprej so potrebne reforme institucij in obeh ministrstev ter kadrovske in vsebinske krepitve tako ministrstev kot njihovih izvajalskih agencij – ARRS in SPIRIT, ki smo se jih lotili v okviru Načrta za okrevanje in odpornost. Prenizko javno financiranje je vplivalo tudi na padec uspešnosti Slovenije v kazalnikih Evropskega inovacijskega indeksa. Slovenija mora priti do 1% javnega financiranja za raziskovalno-razvojne dejavnosti iz različnih virov, ki so sedaj na razpolago v Načrtu za okrevanje in odpornost ter v okviru evropskih kohezijskih sredstev za naslednjih 10 let, ki jim morajo slediti tudi sredstva iz nacionalnega proračuna. MIZŠ iz evropskih kohezijskih sredstev financira povezovanje gospodarstva z raziskovalno sfero ter s tem razvojno-raziskovalne projekte na TRL lestvici od 3 do 6, ki se jim s financiranjem priključi tudi MGRT na višjih ravneh tehnološke pripravljenosti. Zagotovljeni so formalni pogoji za ustanovitev odcepljenih podjetij, za katera so potrebni tudi veliki finančni vložki. MIZŠ teh vložkov v odcepljena podjetja ne more financirati iz opravljanja javne službe. Prav tako je potrebno poleg vzpostavitve finančnih instrumentov pritegniti tudi partnerje, ki imajo veliko raziskovalne opreme in znanja. 5. Prof. dr. Robert Repnik, direktor Javne agencije za raziskovalno dejavnost Republike Slovenije Vprašanje: ARRS določa v Pravilnikih (Pravila za oblikovanje cen za uporabo raziskovalne opreme, obveščanje in poročanje o uporabi raziskovalne opreme) način določanja cen in upravljanja z raziskovalno in tehnološko infrastrukturo v Sloveniji. Kakšne priložnosti še vidimo med podjetji in JRO ter centri odličnosti, ki imajo infrastrukturo, ki bo jo lahko potrebovala podjetja? Kako podjetjem dovolj na glas povedati, da imamo opremo, ki jo potrebujejo, a je pri nas še niso našli? 328 Prof. dr. Robert Repnik: Srednji del TRL-jev je v Sloveniji resen problem. Nižji TRL-ji (predvsem TRL 1-2, pogojno TRL 3) spadajo v področje znanosti, ki jih pokrivata MIZŠ in ARRS v skladu s smernicami resornega ministrstva. Na drugi strani podporo pri premostitvi srednjih TRL-jev nudijo MGRT, SPIRIT, Slovenski podjetniški sklad in tudi Gospodarska zbornica Slovenije. Za rešitev problematike srednjih TRL-jev je ključno zavedanje deležnikov in njihovo soglasje, da je problem srednjih TRL-jev v Sloveniji resen in je zato potrebno premostiti dolino smrti. Za uspešno premostitev je potrebno sprejeti skupno odločitev, da je to nujno ter zagotoviti institucionalno podprtost in pokritost premostitvenega procesa. Prav tako morajo skupno nastopiti vsi, ki pokrivajo posamezne skupine TRL-jev. Nižje TRL- je pokrivajo znanstveniki, višje pa gospodarstvo, medtem ko je »srednja množica« prazna. Ljudje, ki delujejo na teh področjih in stojijo za temi skupinami TRL-jev, morajo začutiti svojo osebno motivacijo, da uspešno izkazujejo svoje talente skozi rezultate. Govorec je prepričan, da obstajajo še nekateri talenti, ki jih je potrebno aktivirati za vstop na področje srednjih TRL-jev. Pri tem sta možna dva pristopa, in sicer, da ustvarimo skupino ljudi, ki bi delala na področju srednjih TRL-jev, ali pa motiviramo obe skupini raziskovalcev, da aktivirajo svoje lastne talente in začnejo delovati tudi na področju srednjih TRL-jev. Raziskovalna oprema je drugi segment, ki odgovarja in naslavlja težavo srednjih TRL-jev. En del je že vzpostavljen, ker se skozi ARRS plačujejo investicije v nakup raziskovalne opreme na javnih raziskovalnih organizacijah. Taka oprema na javnih raziskovalnih organizacijah že obstaja, vendar podjetja premalo poznajo možnosti, kako do nje dostopati. V Evropi obstajajo primeri dobre prakse, ki pa jih ni mogoče enostavno preslikati v naše okolje, da bi delovali. V Sloveniji bi morali najprej dobro pregledati seznam opreme, preveriti, če je ustrezno vpisana in ažurirana. Potem bi lahko seznam opreme promovirali pri gospodarskih družbah, da podjetja spoznajo, kakšne možnosti obstajajo. 6. Prof. dr. Urban Bren, prorektor za prenos znanja Univerze v Mariboru Vprašanje: Kaj sploh je povezovanje z družbo? S stališča univerze, katere raziskovalno delo obsega velik delež naravoslovno tehničnih vsebin? Gre bolj za članke in sodelovanje na konferencah, za neformalne razgovore in občasno naključno pomoč tistim podjetjem, ki so bolje informirana in se bolje znajdejo pri dostopanju do JRO, ali pa bi se morali potruditi vzpostaviti enoten sistem, v katerem bi vsako, še tako majhno, če le dovolj aktivno in radovedno podjetje prišlo v stik s pravim raziskovalcem, pa tudi dobilo dostop do ustrezne infrastrukture za izvedbo meritev za potrebe podjetja? Prof. dr. Urban Bren: Univerza v Mariboru izhaja iz gospodarske pobude. Na dolgi tradiciji sodelovanja z gospodarstvom gradimo naprej. Včasih je bilo tako sodelovanje naključno in stihijsko na podlagi osebnih poznanstev. Danes pa projekta KTT1 in KTT2 vzpostavljata institucionalno in 329 formalizirano raven sodelovanja. Na ta način lahko univerze in javne raziskovalne organizacije delujejo kot enotna vstopna točka (one-stop-shop) za sodelovanje z industrijo. V vzhodni kohezijski regiji smo zelo razpršeni. Tako ima Univerza v Mariboru svoje institucije še v Krškem, Brežicah, Velenju, Celju, Hočah in pri Murski Soboti. Na ta način se znanje bliža uporabnikom v regije, kar je pomembno za enakomeren razvoj države. Prav tak »one-stop- shop« pristop preko kohezijskih regionalnih središč lahko opolnomoči Slovenijo in jo naredi mnogo odpornejšo. Pomembno pa se je zavedati, da prenos znanja ne vključuje zgolj tehnologij za gospodarstvo, ampak tudi prenos v negospodarstvo, v javne institucije in občine. 7. Prof. dr. Klavdija Kutnar, rektorica Univerze na Primorskem in prof. dr. Boštjan Zalar, direktor Instituta ‘’Jožef Stefan’’ Vprašanje: Vloga Centrov odličnosti. Leta 2009 je bilo s strani MIZŠ ustanovljenih 7 Centrov odličnosti, ki so spremenili slovensko raziskovalno pokrajino in jo razgibali, predvsem tudi glede ponujanja dostopa do raziskovalne infrastrukture. IJS ima veliko izkušenj s centri odličnosti, saj je že ob ustanovitvi deloval kot ustanovitelj v treh različnih, na različnih področjih, pomemben del sodelovanja z industrijo poteka tudi danes z njihovo pomočjo. Univerza na Primorskem, kot soustanovitelji zasebnega raziskovalnega zavoda Innorenew, katerega soustanovitelj je tudi nemški Fraunhofer WKI, se dobro zaveda pomembnosti povezave med temeljnim in uporabnim raziskovanjem, kot pravne oblike, ki omogoča tudi sodelovanje slovenskih in mednarodnih deležnikov. Kako vidite razvoj področja centrov odličnosti v Sloveniji v prihodnje? Si želimo nove CO in zakaj ali zakaj ne? Kaj to pomeni za nadaljnje drobljenje raziskovalnega prostora v Sloveniji? Kako skozi Centre odličnosti s pomočjo javnih raziskovalnih organizacij urediti odnos glede raziskovalne in tehnološke infrastrukture ter ponujanje le-te podjetjem, saj vemo, da je vsaj del opreme nepopolno izkoriščen, podjetja imajo potrebo po rabi, vendar do realizacije zaradi zapletenosti sistema ne pride? Kako vidite centre odličnosti na lestvici nivoja tehnološke pripravljenosti TRL? In kako so s centri odličnosti ter raziskovalno infrastrukturo, ki prehaja v tehnološko infrastrukturo, povezane pisarne za prenos tehnologij kot most med njimi? Prof. dr. Klavdija Kutnar: Univerza na Primorskem (UP) je nastala na drugačen način kot Univerza v Mariboru. UP je imela predvsem družboslovno in humanistično usmeritev, hkrati pa izjemno željo za sodelovanje z gospodarstvom v lokalnem okolju. Sodelovanje je bilo oteženo, ker ni bilo razvoja na naravoslovno-tehničnem področju. V naslednjih osemnajstih letih so vzpostavili odlična in tudi nekatera vrhunska nišna naravoslovna področja. Pri tehnologiji pa je bilo težje, ker so v ozadju zelo veliki finančni stroški. Zato so iskali rešitve za okrepitev področja tehnike in tehnologij. V tem konceptu so s pomočjo evropskih sredstev s še osmimi drugimi institucijami ustanovili Center odličnosti. Center odličnosti Innorenew ne drobi raziskovalnega prostora, ampak krepi znanstveno odličnost in povezovanje različnih institucij. Preko Centra odličnosti so združili različne 330 kompetence in znanja, da so naredili preboj v znanstveni odličnosti. Vsi partnerji so vstopili s strateško odločitvijo. Zato Center odličnosti ni konkurenca, ampak partner, ki so mu podelili polno avtonomijo. V UP želijo, da bi prišli do tako močnih pisarn za prenos tehnologij kot jih ima njihov odlični partner Fraunhofer. Le-ta deluje na način, da zaposleni strokovni sodelavci najprej presodijo vsak znanstveni članek, če ima potencial za preboj in prenos v industrijo. Potem se odločijo, ali gredo v patentiranje in zaščito intelektualne lastnine, ali v odprto znanost. V Sloveniji se razlikujejo cilji javnih raziskovalnih institucij, ki stremijo k odprti znanosti in podjetij, ki zasledujejo druge cilje. Zato imajo pisarne za prenos tehnologij pomembno vlogo, da povežejo gospodarstvo z raziskovalno sfero. Raziskovalci UP, ki so najaktivnejši v povezovanju z gospodarstvom, imajo največ težav z ohranitvijo svoje raziskovalne pozicije na univerzi, ker takšnega sodelovanja ne morejo uveljavljati v habilitacijskih merilih. Zato si na UP prizadevajo, da bi dali več točk v habilitacijskih postopkih dodani vrednosti prenosa znanja v gospodarstvo. Komentar moderatorke dr. Špele Stres: Profesionalizacija dela v pisarnah za prenos tehnologij bi bila pravi korak v smeri, da bi se tovrstno podporo lahko nudilo. Prof. dr. Boštjan Zalar: Govorec meni, da Centri odličnosti sodijo na tisti del lestvice nivoja tehnološke pripravljenosti TRL, kjer govorimo o dolini smrti. Centri odličnosti bi lahko bili zelo učinkoviti na tem področju. Raziskovalci imajo dokaj deljena mnenja o uspešnosti Centrov odličnosti, ki so bili ustanovljeni v drugem valu v letih 2008 in 2009 in so žal sovpadali s svetovno gospodarsko in finančno krizo. Centri so bili mišljeni kot injekcija v raziskovalno opremo, ki bi bila na uporabo podjetjem. Vendar se je prav v tem obdobju dogajalo podfinanciranje osnovne znanosti. Namesto, da bi država za takšne iniciative našla dodaten denar, je del denarja prenesla iz enega sektorja v drugega. Centri odličnosti so potrebni, saj se lahko preko njih podpre in mednarodno uveljavi prioritizirano področje znanosti, npr. digitalno transformacijo, kvantne tehnologije in umetno inteligenco, kjer Slovenija kot majhna država naredi preboj v svetovnem merilu. Pomembno vlogo pri tem ima na IJS pisarna za prenos tehnologij, ki je vez med akademijo in gospodarstvom, predvsem s pravno in sistemsko podporo, z ovrednotenjem učinka in doprinosa raziskovalčevega izuma k dodani vrednosti. V Sloveniji bo potrebno na pisarne za prenos tehnologij gledati kot na nekaj nujnega, saj sploh niso umeščene v današnjim sistem financiranja. Delo v pisarnah za prenos tehnologij je specifično, ker potrebuje visoko izobražen kader. Od odločevalcev se pričakuje, da bodo na boljši način uredili delo in financiranje pisarn za prenos tehnologij kot del javno raziskovalnih organizacij. 331 8. Prof. dr. Matej Makarovič, dekan Fakultete za informacijske študije v Novem mestu Vprašanje: IKT. Glede na to, da je ena od temeljnih usmeritev dela Fakultete za informacijske študije prav informatika kot področje raziskav in da je velik del na delo raziskovalcev vezanih inovacij po svoji naravi software. Stanja na področju zaščite programske opreme v Evropski Uniji oz. v Evropi še vedno ne moremo obravnavati kot povsem pravno urejenega, niti kot pravno neurejenega. Področje zato narekuje številne priložnosti za nadaljnje delo. Kako vidite smernice za obravnavo programske opreme, da bi izboljšali stanje s katerim se znanstveniki na področju računalništva soočajo predvsem pa nagrajevanju iz izumov, povezanih s programsko opremo v slovenskem inovacijskem prostoru? Prof. dr. Matej Makarovič: V času digitalne transformacije je paradoksalno, da je področje patentov in nagrajevanja inovacij na področju programske opreme do neke mere nedorečeno. Kadar je inovacija samo na področju programske opreme in ne vključuje strojne razsežnosti, ne omogoča klasičnega polnega preskusa patenta oziroma njegovega tehničnega doprinosa. S tem so raziskovalci, ki inovirajo samo na področju programske opreme, v neenakopravnem položaju, saj se postavlja neka arbitrarna meja pri patentiranju. To vprašanje bi morali reševati na nivoju Evropske unije. V Sloveniji bi lahko na nacionalnem nivoju uredili npr. nagrajevanje, ki ni samo denarno. Raziskovalce - informatike pritegnejo tudi dobri odnosi, priznanja in možnosti napredovanja. Z razmislekom glede kriterijev habilitacije in točk, ki se izračunavajo na osnovi SICRIS baze, je možno urediti nagrajevanje inovacij na programski opremi, ki nima strojne dimenzije. Tehnični preskusi patentov namreč prinesejo veliko več točk. To bi lahko bilo priporočilo za ARRS in NAKIS, da se ta dimenzija pri kriterijih za projekte in habilitacije bolj upošteva. 9. Prof. dr. Gregor Majdič, rektor Univerze v Ljubljani Vprašanje: Eden od prijaviteljev European Digital Innovation Hub (e-DIH) je tudi Fakulteta za elektrotehniko UL. S prehodom inovacij na digitalno področje je programska oprema postala pomemben del sodobnih izumov in stvaritev, hkrati pa predstavlja izjemno pomemben del intelektualne lastnine – tako v slovenskem kot evropskem prostoru. Obenem je prav to področje v praksi najmanj urejeno tudi glede ustanavljanja odcepljenih podjetij, poleg tega pa podjetja v Sloveniji ne dobijo dovolj podpore pri procesih digitalizacije. Kako vidite možnosti, da se to v praksi izboljša in kako so v te napore vpeti vzporedno ali v sodelovanju tako TTO kot DIHi in kje vidite sinergije med njimi? Prof. dr. Gregor Majdič: Vsekakor bi tu morale biti povezave in vzporednice. Nenazadnje gre za veliko vzporednic. Pri digitalni transformaciji govorimo od dveh stvareh. En del so podjetja, ki izvajajo in tržijo digitalne inovacije, na drugi strani pa so pomemben del podjetja, ki proizvajajo druge produkte in pri svojem delovanju uporabljajo digitalna orodja. Pri ustanavljanju novih podjetij, ki delajo na področju digitalizacije, imajo pisarne za prenos tehnologij klasično vlogo. Pri pomoči pri digitalizaciji drugih podjetij bi pisarne za prenos znanja prav tako lahko imele podobno podporno vlogo kot jo imajo pri drugih vidikih ustanavljanja nekega podjetja, npr. s pomočjo pri birokratskih in finančnih vprašanjih. Tudi pisarne za prenos znanja bi se lahko posvetile digitalizaciji tako, da bi v svoje delovanje 332 vključile digitalizacijo, pomoč podjetjem, našle načine, kako tudi z digitalizacijo pomagati podjetjem, ko se ustanavljajo, prihajajo na trg ter iščejo nove poti za internacionalizacijo in scale-up ter kako pri tem čimbolj izkoristiti digitalizacijo. Govorec lahko na podlagi lastnega primera, kot znanstvenik na področju znanosti o življenju, ki se ne spozna na digitalizacijo, vidi veliko pomoč pisarn za prenos znanja pri tem. 10. Prof. dr. Urban Bren, prorektor za prenos znanja Univerze v Mariboru Vprašanje: Ob tem ne smemo pozabiti, da je eden od prijaviteljeDIH tudi UM. Naslednje vprašanje pa je povezano z Open Science. Univerza v Mariboru se v okviru vzpostavljanja odprte znanosti kot pomemben akter na slovenskem parketu glede naslavljanja vsebin Open Science, še posebej v kontekstu Ustanovitve Slovenske skupnosti odprte znanosti. Kakšna je vloga TTOjev v upravljanju z IL in hkratnemu spodbujanju raziskovalcev h konceptu odprte znanosti. European Open Science Community že od leta 2013 vzpostavlja sistem za hranjenje in ponovno uporabo podatkov iz raziskav, ki jih financira država. Če vemo, da je skozi celoten H2020 OpenScience postajal pojem za dostopanje do podatkov, ali smo v večini raziskovalnih skupin danes vsebinsko pripravljeni na dele projektov, kjer je potrebno opisati pretekle data-sete, njihovo validacijo ter prakse open science? Open science sicer ni v nasprotju z zaščito IL, vendar pa oboje sledi nekim pravilom, ki jih je potrebno upoštevati, da se doseže maksimalen vpliv raziskav, kako so z zagotavljanjem vpliva povezani TTOji in če v Sloveniji niso, zakaj ne? Kako vidimo razvoj vseh teh področij v Sloveniji in ali jih vidimo povezano? Prof. dr. Urban Bren: Univerza v Mariboru ima resnično številne repozitorije odprte znanosti, ki jih uporabljajo tudi druge institucije. Vsekakor se odprta znanost sliši odlično na papirju. Odprta znanost je financirana iz javnih sredstev, zato so tudi izsledki javno dostopni. V tem mozaiku pa smo pozabili na založbe, ki večinoma niso javne, zasledujejo tržni princip in zahtevajo plačilo za objavo prispevkov znanstvenikov. Znanstveniki tako sami plačujemo za odprte članke. Na drugi strani pa mnogo založb zahteva članarino ali direktno plačilo na spletni strani za prebiranje člankov. Posledično se lahko zgodi, da znanstvenik ne bo mogel objavljati, ali pa bo zelo težko objavljal, če ne bo imel raziskovalnega projekta, s katerim si bo kupil odprtost svojih člankov. ARRS sicer najboljše članke v posamezni kategoriji naslavlja preko njenega razpisa. Še večji strah in problem pa je v primerih, ko je s tem povezano podjetje, ki ga skrbi, da ne bi izgubilo svoje intelektualne lastnine. Javnost podatkov, ki jih moramo zasledovati v skladu s strategijo odprte znanosti, predstavlja večji izziv od javnosti objav. Lahko se zgodi, da bo kdo drug na znanstvenikovih odprtih podatkih napisal članek. Še večji izziv pa bi nastal za podjetje, ki sodeluje z javnim zavodom in bi na ta način delilo svoje podatke s konkurenco. 333 11. Mag. Gregor Umek, vodja Sektorja za industrijo, spodbujanje inovativnosti in tehnologije v Direktoratu za internacionalizacijo, podjetništvo in tehnologije (Ministrstvo za gospodarski razvoj in tehnologijo) Vprašanje: Reforma inovacijskega sistema. V okviru Načrta za okrevanje in odpornost je predvidena tudi reforma na področju RRI. Deležniki inovacijskega okolja v Sloveniji pogosto med seboj niso dovolj povezani. Kako na MGRT razmišljate o možnostih izboljšanja povezav in koherentnosti delovanja inovacijskega okolja? Kako bi po vašem mnenju lahko dosegli boljše sodelovanje JROjev in gospodarstva ter politike v Sloveniji, tudi z namenom izboljšanja procesov prenosa tehnologij iz JRO v gospodarstvo? Mag. Gregor Umek: Reforma RRI znotraj Načrta za okrevanje in odpornost je ključna in predvideva sprejem novega Zakona o znanstvenoraziskovalni in inovacijski dejavnosti (ZZRID). Prav tako je ključna vpeljava novega modela upravljanja in povezovanja deležnikov inovacijskega sistema predvsem preko razvojnega sveta. MGRT je s strani ministrstva, ki naslavlja gospodarstvo, predvidel vključitev direktorjev SPIRIT-a in Slovenskega podjetniškega sklada ter predstavnike SRIP-ov v razvojni svet, ki naj bi na strateški ravni usklajeval politiko. V programskem svetu sodelujejo MGRT, MIZŠ, Ministrstvo za kmetijstvo in SVRK s svojimi izvajalskimi agencijami, ki implementirajo ukrepe. Trenutno je v pripravi postopek za evalviranje in standardizacijo ukrepov. Zato sta ključni okrepitvi ARRS-ja in SPIRIT-a, v katerem je predvidena zaposlitev 15 novih ljudi. Področje inovacij bi se upravljalo v okviru Agencije SPIRIT na trodelnem sloju na način, da bi se vse finančne spodbude izvajale preko Agencije, kar je boljše z vidika upravljanja, prav tako podjetja vse dobijo na enem mestu. Tudi vsa mednarodna dejavnost bi se izvajala v sklopu Agencije SPIRIT, kar bi dalo slovenskim inovacijam prepoznavnost na mednarodni ravni. Prav tako bi se v Agenciji upravljali in koordinirali vsi deležniki. Pri reformi RRI je zelo pomembno, da MGRT v okviru obstoječih razpisov za spodbujanje raziskav in razvoja ter demo pilotov, uvaja v skladu z Načrtom za okrevanje in odpornost načelo, da vsi ukrepi, ki bodo znotraj teh razpisov, ne smejo škodovati okolju. Kar 40% meril mora biti vezano na trajnost in zeleni prehod, kar je ključno tudi v naši industrijski strategiji, v kateri moramo doseči zeleni prehod. Prav inovacije lahko pripomorejo k zelenemu prehodu, kar je govorec ilustriral na primeru Steklarne Hrastnik, ki je s pomočjo pilotov naredila inovacijo na steklarski peči s ciljem ničelne ogljičnosti. Pri reformi RRI je ključno stabilno financiranje. Ker imamo pomanjkanje integralnih sredstev, nastanejo vrzeli med več finančnimi kohezijskimi perspektivami, v katerih podjetja ne morejo dve leti dostopati do sredstev. Ključno je, da se tudi z novim Zakonom o znanstvenoraziskovalni in inovacijski dejavnosti MGRT zavezuje k 1,25% javnemu financiranju, ker morajo imeti podjetja stalen dostop do teh sredstev. Prav tako je ključno povezovanje vseh ukrepov MGTR-ja in MIZŠ-a za podporo/ financiranje lestvice nivojev tehnološke pripravljenosti, da lahko tudi podjetja na eni točki dostopajo do vseh ukrepov. 334 MGRT konkretno sodeluje z Gospodarsko zbornice Slovenije pri Načrtu za okrevanje in odpornost, ki lahko da odziv s terena, kaj dejansko podjetja potrebujejo in kje so izzivi, ki jih mora nasloviti MGRT. Če bomo v Sloveniji želeli financirati vse, kar je vključeno v Načrtu za okrevanje in odpornost, so ključne sheme državnih pomoči. Brez ustreznih shem ni možno financirati investicij pri demo pilotih in zelenega prehoda. Evropski komisiji je potrebno predlagati, da je nujna večja prilagodljivost države članice, ki je omejena s shemami državnih pomoči. Podvprašanje: Vloga strateško razvojno inovacijskih partnerstev (SRIP). Vzporedno z vzpostavitvijo Konzorcija za prenos tehnologij s strani MIZŠ se je na MGRT vzpostavil sistem S4 in SRIPi. Danes vidimo, da SRIPi in TTO opravljajo komplementarne storitve (SRIPi informiranje in mreženje podjetij tudi za namen vzpostavljanja tematik za razpisne sheme), TTO pa pri vzpostavljanju odnosov JRO-podjetja igrajo bolj operativno vlogo podpore posamičnim primerom sodelovanja pri vzpostavljanju vsakodnevnih, mukotrpnih gradenj odnosov med posamičnimi podjetji in JRO. SRIPi in TTO se torej prekrivajo v manjšem deležu svojih aktivnosti. Kako naj se vzpostavi aktivna povezava in sinergije med obojimi? Mag. Gregor Umek: SRIP-i in pisarne za prenos tehnologij so deležniki inovacijskega sistema, ki z različnim delovanjem povezujejo javne raziskovalne organizacije in gospodarstvo. Pisarne za prenos tehnologij želijo prenesti znanje iz JRO-jev v gospodarstvo. SRIP-i delujejo širše in krepijo razvojno-raziskovalno in inovacijsko dejavnost med gospodarstvom, JRO-ji in tudi drugimi deležniki na področju razvoja. Predvsem pa je vloga SRIP-ov, da povezujejo vse te deležnike v mednarodne verige vrednosti na področju internacionalizacije. MGRT z MIZŠ in drugimi deležniki sodeluje pri projektu Evropske komisije z naslovom »Strengthening the innovation eco-system in Slovenia«. Ključno sporočilo projekta je, da morajo bolje povezati vse deležnike inovacijskega eko sistema, za kar bodo v Načrtu za okrevanje in odpornost predvidena konkretna finančna sredstva (3 mio EUR) za mreženja, organizacijo delavnic in opolnomočenje med vsemi deležniki. Na ta način lahko povežemo SRIP-e, pisarne za prenos tehnologij in vse deležnike. 12. Mag. Damjana Karlo, vodja Sektorja za strukturne sklade na področju raziskovalno- razvojne dejavnosti (Ministrstvo za izobraževanje, znanost in šport) Vprašanje: Konzorciji za prenos tehnologij. Če pogledamo skozi zadnjih 15 let, Leta 2008 je le redkokdo poznal določbe v Zakonu o izumih iz delovnega razmerja, ki opredeljujejo obvezo države, da financira TTOje za delo z raziskovalci, posebej. Leta 2013 je konzorcij za prenos tehnologij financiral MGRT za slabi dve leti. Rezultati niso bili navdušujoči, čeprav so bili zahtevani rezultati minimalni. Leta 2015 so najprej MGRT, nato pa še skupno SVRK in MIZŠ zavrnili možnost financiranja novega konzorcija za prenos tehnologij, od leta 2017 pa pod okriljem MIZŠ konzorcij uspešno deluje. Kako vidite razvoj področja v zadnjem desetletju na MIZŠ in kako vnaprej, ne toliko glede financiranja, ki je sicer pomembno za trajnostni razvoj področja. Temveč: kako vidite strateški razvoj področja prenosa znanja, njegovega pomena za Slovenijo, možnost in načine profesionalizacije aktivnosti in predvsem povezave z drugimi strateškimi instrumenti? 335 Mag. Damjana Karlo: MIZŠ je ta izziv že naslovil iz preteklih izkušenj pri pripravi nove raziskovalne in inovacijske strategije Slovenije do leta 2030. V strategiji namenjajo še večjo težo sistemskemu urejanju področja prenosa znanja, da se okrepi sistemska podpora z integralnimi sredstvi, ki jih 20 JRO- jev pridobi za delovanje. Znotraj teh sredstev bo vsak JRO v skladu s svojo avtonomijo opredelil, koliko sredstev bo namenil področju prenosa tehnologij. MIZŠ želi, da se na vseh 20 JRO ustanovijo pisarne za prenos znanja. MIZŠ namerava iz evropskih kohezijskih sredstev 2021-2027 nadgraditi obstoječi konzorcij KTT v približno enakem obsegu, ker so praktično že letos doseženi ali preseženi vsi kazalniki projekta, ki se zaključuje 30. junija naslednje leto. MIZŠ si bo prizadeval, da ne bo prišlo do vrzeli v financiranju in načrtuje objavo javnega razpisa za nadgradnjo konzorcija KTT iz evropske kohezijske politike 2021-2027 takoj, ko bodo izpolnjeni vsi formalni pogoji na ravni države, kar bi lahko bilo od druge polovice leta 2022 dalje. Komentar moderatorke dr. Špele Stres: Obe ministrstvi (MGRT in MZIŠ) sta usklajeni v svojem delovanju, da preprečita vrzel v financiranju. Še posebej želi MIZŠ preprečiti vrzel pri financiranju konzorcija KTT. Vendar se projekt KTT zaključuje 30.6. naslednje leto, kar pa pomeni operativno težavo in nastanek vsaj minimalne vrzeli, če bodo razpisi objavljeni v drugi polovici leta 2022. Kadri za prenos tehnologij, ki so se razvili in profesionalizirali v okviru konzorcija, so izjemnega pomena in bi jih pisarne za prenos tehnologij želele obdržati. Zato bi bilo potrebno vrzel v financiranju čimbolj skrajšati. 13. Prof. dr. Boštjan Zalar, direktor Instituta ‘’Jožef Stefan’’ Vprašanje: Razdrobljenost. Kako razdrobljenost raziskovalne sfere (slišali smo, da govorimo o 20 JRO in nekaj desetih nejavnih, ki prav tako izvajajo raziskovalno dejavnost, predvsem iz evropskih sredtsev) v Sloveniji vpliva na kvaliteto storitev TTOjev na posamičnih organizacijah? Je smiselno in upravičeno pričakovati visokokvalitetne storitve za raziskovalce, od vzpostavljanja raziskovalne strategije in pridobivanja financiranja za vse faze TRL (kot npr. pri Fraunhoferju, kjer pregledujejo vse znanstvene članke raziskovalcev in se odločajo, ali gredo v odprto znanost ali patentiranje), do kapitalizacije na trgu? So take storitve celostno sploh zaželene, saj deloma posegajo v raziskovalno svobodo? Prof. dr. Boštjan Zalar: V dvomilijonski naciji ne moremo preslikati učinkovitih rešitev iz velikih nacij, ki so svoje sisteme že zgradile. Zato bomo vedno doživljali rahlo razdrobljenost raziskovalne sfere. Pri reševanju določenega tehnološkega problema se je potrebno ozreti tudi v tujino, ker ni nujno, da bomo v svojem ožjem okolju našli tehnološko rešitev. Na drugi strani se dnevno postavlja vprašanje, od katere stopnje tehnološke pripravljenosti dalje potrebujemo podporo pisarn za prenos tehnologij. Postavlja se tudi dilema, ali je vse, kar delamo v znanosti (npr. merjenje mase črne snovi v vesolju), možno uvrstiti na lestvico TRL. V znanosti je še vedno en del, kjer bi morala biti lestvica znanja – na kateri stopnji znanja smo in ne na kateri stopnji tehnološke pripravljenosti. 336 V Sloveniji naj se zgledujemo po dobrih zgledih iz tujine. Evropa je ustanovila Evropski raziskovalni svet. V programu Obzorje Evropa imamo sedaj tudi novo institucijo - Evropski inovacijski svet, ki se ukvarja z vprašanjem, koliko daleč naj posega na lestvici TRL – ali že v osnovni znanosti, ali sploh ne. ZAKLJUČKI Gregor Klemenčič, Deepinovations (Nizozemska) Kot zunanji opazovalec in nekdo z ogromno izkušnjami iz obeh strani, JRO in gospodarstva v inovacijskem sistemu, še posebej glede na to, da ste vanj umeščeni v bolj razvitem tujem okolju, ki se mu želi Slovenija s svojo inovacijsko dejavnostjo približati. Kako v luči današnjega pogovora gledate na vlogo in pomen različnih deležnikov v inovacijskem okolju? Kako močno lahko politika, JRO in TTOji vplivajo na zagotavljanje inovativnega mišljenja, internacionalizacije, prenosa znanja in izkoriščanja rezultatov? Prosim za zaključno misel. Zaključna misel: V njegovem raziskovalnem okolju razdrobljenost obstaja in ni problem, ker gre za razdrobljenost po temah (npr. informacijsko-komunikacijske tehnologije, biotehnologija). Tudi pisarne za prenos tehnologij so praviloma uspešne, še posebej, če se povezane z gospodarskimi zbornicami, drugimi raziskovalnimi organizacijami in komercialnimi firmami. V pogledu od spodaj navzgor imajo znanstveniki s svojim zagonom, znanjem in interesi možnost, da se srečujejo z drugimi znanstveniki in start-upi. Na zelo uspešnih mikro srečanjih na določeno temo se znanstveniki povežejo in izmenjujejo znanje z drugimi raziskovalci, se povezujejo z malimi, srednjimi podjetji ter pridobijo tudi mikro financiranje. Komentar moderatorke dr. Špele Stres: Mikro srečanja so v tej luči vzpostavila B2R sestanke, ki se dogajajo on-line vzporedno s konferenco in iz katerih se lahko razvije dolgoročnejše sodelovanje. Zaključne misli drugih udeležencev okrogle mize: Mag. Damjana Karlo: Znanje je potrebno ne samo ustvariti, ampak ga tudi prenesti v družbo - tako v gospodarstvo kot v širši sistem, zaščititi in pripeljati do inovacij ter na ta način izboljšati našo mednarodno konkurenčnost in izboljšati kakovost življenja. Prof. dr. Robert Repnik: Pristop, o katerem smo danes govorili, je pravilen. Vendar ga je potrebno kombinirati s pristopom od spodaj navzgor. Pri tem je potrebno upoštevati, kateri motivacijski elementi bi ljudi prepričali v to, da bi se začeli ukvarjati s srednjimi stopnjami tehnološke pripravljenosti. Prav tako se je potrebno osrediniti na področja, kjer je največ možnosti, potencialov in priložnosti in kjer ima Gospodarska zbornica pomembno vlogo. Mag. Gregor Umek: Najpomembnejše je povezovanje med vsemi deležniki, ki je tudi del reforme v Načrtu za okrevanje in odpornost. Povezovanje od spodaj navzgor je zelo pomembno in MGRT že 337 sodeluje z Gospodarsko zbornico in drugimi deležniki. MGRT mora pridobiti informacije s terena, se primerno odzvati in temu primerno voditi politiko. Prof. dr. Matej Makarovič: Ko govorimo o javnem financiranju in javnem raziskovanju, je predvsem pomembno, da služi tudi popravljanju »tržnih napak«, torej zagotavljanju tega, česar trg sam ne zagotavlja. Tipičen primer tega je področje trajnostnega razvoja. Prof. dr. Maja Ravnikar: Biti moramo aktivni na promociji znanosti, saj s tem osveščamo družbo in gospodarstvo, kaj je na voljo v Sloveniji. Poleg tega so zelo pomembne mehke veščine in izobraževanje raziskovalcev, kako pravilno pristopiti in se pogovarjati z gospodarstvom ter kako jim ponuditi tehnološke rešitve. Zato so nujno potrebne okrepitve pisarn za prenos tehnologij in znanja. Prof. dr. Urban Bren: V Sloveniji imamo dobro izdelan sistem financiranja temeljne znanosti. Aplikativna znanost šepa - kot da potrebujemo samo katalizatorje, potem pa bo prenos znanja stekel sam od sebe. Dejansko pa ta proces stalno potrebuje potisk energije in finančnih sredstev. Potem učinki prelivanja naredijo tak prenos znanja vzdržen in v dobrobit celotne skupnosti. Nekatera odlična orodja kot so mladi raziskovalci v gospodarstvu, mladi raziskovalci na začetku kariere in projekti TRL 3-6 so že razvita in jih je potrebno zgolj kontinuirano uporabljati. Prof. dr. Gregor Majdič: V Sloveniji imamo ogromno odlične znanosti, tako bazične kot aplikativne, čeprav sam nikakor nisem zagovornik takšne delitve na bazično in aplikativno znanost saj menim, da je znanost ena. Šepa pa nam pa prenos znanja, premalo znamo izkoristiti to znanje in ga prenesti na trg, da bi imelo tudi ekonomske učinke. Zato potrebujemo pisarne za prenos znanja, ki opravljajo zelo dobro vlogo in je njihov pomen potrebno še okrepiti. So pa v Sloveniji problem tudi kapitalske spodbude in pretakanje kapitala, saj nimamo pravih inštrumentov in vlagateljev v mlada zagonska podjetja. To je posebno velik problem na področju naravoslovja in deloma tehnike, saj so na teh področjih potrebni višji finančni vložki, ki se povrnejo v daljšem časovnem obdobju in zaradi tega je pogosto težko pridobiti zagonski kapital za podjetja s takšnih področij. Prof. dr. Klavdija Kutnar: Sporočilo današnje okrogle mize je, da je zelo pomembno povezovanje slovenskih raziskovalnih institucij. Prav partnerji iz drugih institucij so pomagali Univerzi na Primorskem, da so svojo dejavnost dvignili na višji nivo. Prof. dr. Boštjan Zalar: Prenehajmo se pogovarjati o temeljnosti in aplikativnosti, raznih lestvicah, saj linearne linije vse med sabo prepletejo. Zaključna beseda: dr. Špela Stres Če smo začeli s citatom Winstona Churchila o tem, da se moramo učiti celo življenje, naj tudi končamo na tak način. Vedno se bomo soočali z izzivi, in izzivi bodo vedno večji od nas. G. Churchil je glede našega odziva na izzive rekel Fear is a reaction courage is a decision. Z iskrenim upanjem, da bomo pri soočanju s prihodnostjo pogumni, se vam najlepše zahvaljujemo za vaše sodelovanje na tej izredno zanimivi okrogli mizi. 338 PITCH COMPETITION: BEST INNOVATION WITH COMMERCIAL POTENTIAL From 10:30 to 12:00 Moderator: Robert Blatnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission: Dr. Jon Wulff Petersen, Plougmann Vingtoft Matthias Keckl, Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič, Slovene Enterprise Fund Gregor Klemenčič, Deep Innovations Presentation of six (6) selected business model proposals from public research organizations to the technology transfer experts. 339 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 2021 at public research organizations (PROs) aims at stimulating the researchers from public research organizations to develop business models for commercialization of their inventions. The competition was initiated with a public call, which was open to authors of inventive technologies. Eligible authors are individuals, employed at PROs, which are developing innovative technologies and their teams into a viable business model. Possible business models are either licensing the technology to industrial partners or commercialization in a spin-out company. The teams have prepared description of their technology and the key discoveries that underpin the commercial activity (licensing or spin-out creation). 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 the researchers learned the main guidelines on how to prepare their pitch presentation. 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: Matthias Keckl, Managing Partner, Fraunhofer Technologie-Transfer Fonds (FTTF) GmbH, Gregor Klemenčič, Founder and co- owner, Deep Innovations B.V., Nina Urbanič, Adviser for equity investment monitoring, Slovene Enterprise Fund, and Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft. 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 the experts exchanged their views and opinions and selected the winner(s). The Criteria is presented in the Table 1. 340 The traditional pitch competition, which this year had its 13th 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 KTT project, financed by Slovenian Ministry of education, science and sport. Members of the teams are entirely or partly employed or study at the PROs, Jožef Stefan Institute, Jožef Stefan International Postgraduate School, University of Belgrade. Members of the teams are also the founders or employed at industrial partners, which are already involved in the technology and business model development. 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. What do the end users use today? Any other technology underway? Which is the expected competition level when you will hit the market Competition How good is the present solution (not yours) in solving the problem? 1 How good will any expected future solutions (not yours) be in solving the problem? 341 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) 342 Abstracts of the competing teams and their technologies 343 Real-time fluorescence lifetime acquisition system – RfLAS Authors/inventors: Andrej Seljak, Rok Dolenec, Rok Pestotnik, Matija Milanič, Peter Križan, Samo Korpar PRO: Jožef Stefan Institute Abstract: The present pandemic has shown us how vulnerable we are, and challenged the human knowledge-based capacity to adapt very quickly. Biomedical engineering has produced one of the most outstanding up to date solution to avoid severe consequences due to Covid complications. One of the key tools used in biomedical engineering is measuring of the fluorescence response. This method is non-invasive, sample non-destructive, provides functional and structural information, biochemical parameters, oxygen concentration, pH, and other vital parameters, that enable the study of the interaction of proteins, and is sensitive enough to monitor cellular environment and metabolic states. Moreover, fluorescence is used in material sciences to characterize novel materials or screening drug production as examples. This key tool is made using complex electronic and optical elements, which makes market accessible devices very expensive. We constructed a novel device, which compared to the current state of the art is about 10 times faster, provides extended capabilities, can be made the size to fit into a portable suitcase, and allows for very competitively pricing on the market, even considering initial small productions. This lands it perfect for start-ups and tech giants in the field, to access tools for future discovery. The technology is also scalable into a variety of different systems for different purposes. Our primary target are therefore biomedical and bioengineering companies, research institutes, universities, and companies requiring specific know how or OEM products. We expect this technology to enter the biotech market, which alone is expected to hit 2.44T USD in 2028 [*]. This estimate is 3 times higher compared to pre Covid times (about 2 years ago). We present the newly developed device and its envisaged future. *https://www.grandviewresearch.com/press-release/global-biotechnology-market 344 Figure 1: Fluorescence samples. Rok Dolenec. 2020. Figure 2: Cross view into sample space. Rok Dolenec. 2020. 345 Figure 3: Device in operation. Rok Dolenec. 2020. 346 Tomappo OptiGarden – healthy, sustainable and nutritious vegetable garden planned in a few clicks Authors/inventors: Bojan Blažica, Andrejaana Andova, Barbara Koroušić Seljak, Bogdan Filipič. PRO: Jožef Stefan Institute Industrial partner: Proventus, d.o.o. Abstract: Vegetable gardening is gaining popularity among the younger generation as growing your own local food and taking care of a healthy nutrition is increasingly trendy. Gardening is a rewarding and relaxing hobby, but can also be daunting as there is much knowledge to be considered when planning a healthy, nutritious garden. Considering gardening best practices such as crop- rotation and companion planning, data about vegetables and climate, yield estimation, nutritional contents and the needs and tastes of the gardener can be treated as an optimization problem and thus solved automatically with an algorithm with little effort by the user. Automatic garden planning can be used to develop solutions in the home and garden market. From powering a mobile application for gardeners (B2C, approx. 5 million potential users in main EU markets, 44 million in the US) to advanced lead generation and e-marketing solutions addressing the need of garden centers and gardening brands to connect to a younger generation of gardeners and digitalize their operations both online and in-store. A team of researchers with backgrounds in AI, optimisation, meteorology and human-computer interaction, who are keen gardeners themselves, is devoted to bring the benefits of gardening just a click away to all expert and aspiring gardeners. Teaming up with Proventus, the start-up developing the gardening platform Tomappo, ensures market uptake in both B2B and B2C segments and much needed business development experience. 347 Figure 1: A segment of a vegetable garden illustrating the concepts to be considered in garden planning. Andrejaana Andova and Bogdan Filipič. 2021. Figure 2: Testing the interactive kiosk in garden centre Kalia, Ljubljana. Bojan Blažica. 2021. 348 Figure 3: Automatic garden planning on interactive kiosk: input of basic parameters, selection of vegetables, display of different optimal layouts, info about vegetables. Bojan Blažica. 2021. 349 Novel surface finishing procedures for medical devices, especially vascular stents Authors/inventors: Ita Junkar, Metka Benčina, Rok Zaplotnik, Matic Resnik PRO: Jožef Stefan Institute Abstract: Cardiovascular diseases cause millions of deaths all over the world and present a serious health care burden. The minimally invasive way to treat diseased blood vessels is by insertion of expandable tubular stent. Currently three types of stents are available on the market; the bare metal stents (BMS), drug eluting stents (DES), and the bioabsorbable stents (BAS). According to Market Data Forecast the European Coronary stents market is estimated to grow to reach 3.64 billion by 2026. Vascular stents have already saved countless lives, but unfortunately their surface properties, which significantly affect biocompatibility, are still far from optimal and there is a huge demand to develop vascular stents with superior properties. The main issues are the stent induced thrombosis (blot clotting) and restenosis (narrowing of blood vessel wall), which are linked with health complications, high health care costs, high demand for medication, and revision surgeries, which can be even fatal for the patient. Numerous approaches have been proposed to improve coronary stent surface mainly by developing various types of coatings, however so far improvements have been only incremental. Our interdisciplinary team (chemical and mechanical engineers, plasma scientists, microbiologist) developed plasma-based approaches for surface modification of biomaterials, especially vascular stents. The novel approach is based on one step plasma treatment, which enables fabrication of multifunctional surface that; prevents platelet adhesion and smooth muscle cell proliferation, promotes proliferation of endothelial cells and reduces bacterial adhesion. By relatively fast and environmentally friendly treatment at optimized plasma conditions it is possible to fabricate nanostructured stent surface with specific surface chemistry, that are mechanically stable, anti- corrosive and can prevent undesired release of toxic ions like Ni in case of NiTi implants. 350 Figure 1: On the left-hand side bare metal vascular stent from NiTi alloy (Kindly donated by Rontis AG) is shown, while stent surface after incubation with whole blood is presented on the right-hand side. Interaction of platelets with the surface of commercial and plasma-treated vascular stent (images obtained from scanning electron microscopy) is shown. Ita Junkar. 2021. 351 Superhydrophobic coatings with dual action: corrosion and antibacterial/antiviral protection Authors/inventors: Peter Rodič, Ana Kraš, Barbara Kapun, Chris Černe, Ingrid Milošev, Veronika Bračič PROs: Jožef Stefan Institute Abstract: The innovation is the synthesis and preparation of superhydrophobic coating, which can be deposited on various metal surfaces. The superhydrophobic surface has two principal roles: (i) it repels the solution droplets from the surface and thus acts as corrosion protection since it prevents a corrosive solution to reach the underlying metal substrate and initiate the corrosion process, and (ii) it prevents, or diminishes, the attachment of pathogens (bacteria and viruses) or biofilm (microorganisms) to the surface and thus acts as antimicrobial/antiviral protection. The development of superhydrophobic coating as corrosion protection responds to the need to extend the lifetime of devices/constructions made of metals. Superhydrophobic coating as antimicrobial protection is required in various critical applications such as hospitals and health care facilities, where microorganisms can be easily spread. Contaminated surfaces such as doorknobs, tables, and utensils used in hospitals/restaurants/hotels/apartment blocks can facilitate the viral transfer. Although surfaces can be sanitised with a variety of household cleaners, sterilising all the surfaces after each use is challenging to maintain. Further, by using disinfectants, the corrosion protection of the metals can be reduced because disinfectants solutions are usually chlorine- or alcohol-based and highly alkaline or acidic. Consequently, they are harsh for many metals such as copper, zinc, steel and aluminium. Therefore, the metal surfaces must be additionally protected against corrosion. Our innovation can be applied in all the applications where the needs exist to preserve metal surfaces from corrosion and to protect them from the action of microorganisms. Compared to the competition, the main advantage of this coating synthesis is an easy and innovative preparation with desirable superhydrophobic properties. 352 Figure 1: Water droplet on the superhydrophobic surface with contact angle above 150° 353 Cutting Tool Life Estimator Authors/inventors: Anže Marinko, Jože Ravničan, Matjaž Gams PRO: Jožef Stefan Institute, Jožef Stefan International Postgraduate School Industrial partner: Unior, d.d. Abstract: In mechanical engineering, a lot of work is performed on lathes, where the cutting tools wear out over time. Replacing cutting tools is expensive and time consuming so it should be delayed if possible. On the other hand, costs and customer dissatisfaction may be caused by products not performing well if cutting tools are worn out. To avoid non-quality products, replacement of the cutting tool should be performed at optimal time. Currently, most of cutting-tool replacement if performed by human operators using either human or specialized sensors for inputs. With our Cutting Tool Life Estimator (CTLE), the human operator relies on CTLE sensors detecting 3D accelerations, and the CTLE artificial intelligence (AI) proposing replacement when needed. The role of the human operator changes from the one getting input information and making subjective decision into a second-opinion generator and supervisor since the CTLE system objectively proposes a decision on its own. Compared to human-only decision making, the new approach enables use of more sensors and combining human with artificial intelligence, which in recent years progressed substantially in performing real-life problems based on complex input signals. The use of CTLE therefore enables better timing of the replacement of the cutting tools. As a consequence, the production is cheaper and of better quality, thus providing an important advantage over competitors in the mature automotive, tool and other mechanical industries. In the future, the CTLE could become more independent, as the program would eventually learn more to predict the time of excessive tool wear and would propose changing the cutting tool at the closer-to-optimal time. Machine learning models in general improve over time when more data are provided. Figure 1: Amplitudes of vibrations in time of one machining cycle. Anže Marinko. 2021. 354 Figure 2: Estimated cutting tool wear during cycles until the cutting tool replacement. Anže Marinko. 2021. Figure 3: User interface of the program. Anže Marinko. 2021. Figure 4: The CTLE systems runs on a PC connected to sensors on a lathe. Application in the UNIOR company. Anže Marinko. 2021. 355 Award announcement Best innovation with commercial potential 13:00 to 13:10 Moderator: Robert Blatnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission members: Dr. Jon Wulff Petersen, Plougmann Vingtoft Matthias Keckl, Fraunhofer Technologie-Transfer Fonds (FTTF) Nina Urbanič, Slovene Enterprise Fund Gregor Klemenčič, Deep Innovations 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 1250 Euro goes to the team members: Andrej Seljak, Rok Dolenec, Rok Pestotnik, Matija Milanič, Peter Križan and Samo Korpar, Jožef Stefan Institute for Real-time fluorescence lifetime acquisition system – RfLAS. The award of 1250 Euro goes to the team members: Ita Junkar, Metka Benčina, Rok Zaplotnik and Matic Resnik, Jožef Stefan Institute for Novel surface finishing procedures for medical devices, especially vascular stents. Congratulations! 356 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) Evaluation commission members: Alojz Barlič, Slovenian Intellectual Property Office (SIPO) Matthias Keckl, Fraunhofer Technologie-Transfer Fonds (FTTF) GmbH Nina Urbanič, Slovene Enterprise Fund ANNOUNCEMENT OF THE WINNER WIPO IP ENTERPRISE TROPHY Dear Ladies and Gentlemen, It’s a big honour for us to have the World Intellectual Property Organisation and Slovenian Intellectual Property Office among the co-organisers of this conference. 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. Last year at the 13th International Technology Transfer Conference the WIPO awards were given in Slovenia for the first time. Today we will announce the recipients of two WIPO awards. The awards will be given tomorrow at the conference ceremony between noon and one o’clock and will be accessible via live streaming on the institutes’ TV channel. The selection committee consisting of Mrs. Nina Urbanič, Slovene Enterprise Fund and Mr. Matthias Keckl, Fraunhofer Technologie-Transfer Fonds who you already know, were joined by Mr. Alojz Barlič from the Slovenian Intellectual Property Office. The WIPO Medal for Inventors will be announced just before the end of the conference. 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: - 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. 357 May I use the words from a member of the selection committee: I am very impressed with the applications, and I think there are a lot of passionate and great people behind the technologies and companies. Among the applications, the jury has decided to give the IP Enterprise Trophy to GEM Motors. Short justification: GEM Motors is actively cooperating with several public-research organisations. They have a clear IP strategy with patents in EU, India, USA, Russia, Japan, China and S. Korea and that is essential for B2B business. Their in-wheel patented technology has been presented at several fairs and conferences. Through the social responsibility programs by promoting the urban e-mobility different project partners, other companies and schools are included. And finally, they constantly and methodologically encourage the creativity and innovativeness among their staff and encourage PhD employments. Congratulations! 358 Keynote speech: PoC funding of research spin-offs From 13:20 to 13:40 Matthias Keckl, Managing Partner, Fraunhofer Technologie-Transfer Fonds (FTTF) GmbH ABSTRACT OF THE KEYNOTE SPEECH Matthias Keckl is a Managing Partner of the FTTF - Fraunhofer Technologie Transfer Fonds GmbH, an independent Venture Capital unit and financing partner for Deep Tech Start-Ups using Fraunhofer technologies with an investing volume of € 60 million. FTTF invests exclusively in starts-up using Fraunhofer technologies. As a strong entrepreneurial partner with 30+ years of experiences in supporting Fraunhofer start-ups, FTTF offers financing in their pre-seed phase with up to 250.000 euros, and in further funding rounds with additional investments of up to five million euros. FTTF provides fast investments process and on-site support. Moreover, the fund supports entrepreneurs with comprehensive founding experience and a broad network of investors in order to realize the full potential of their companies. FTTF is backed by Fraunhofer- Gesellschaft and the European Investment Fund (EIF). FTTF focuses on bridging the gap – from tech to market - in close collaboration with internal Fraunhofer tech-transfer and incubation programs, like AHEAD and CoLab. FTTF has access to German innovation hubs whilst bridging the gap between scientists as founders and investors. FTTF ensures optimal and efficient setup/ structure of the start-up right from the beginning and provides runway 12 to 18 months. FTTF begins investing in the very early PoC stage of the start-up (pre-seed) giving researchers the opportunity to start the business. FTTF invests in the VC start-ups with growth and exit potential as well as funding requirement. FTTF doesn’t invest only in founded companies that are also in pre-revenue phase – start-ups have already started pilot projects but usually do not yet have revenues. FTTF requirements for a PoC (pre-seed) investment: • Start-up has to have access to technology: ▪ Freedom to operate ▪ Acceptable license fees ▪ Call option to take over IP, or at least option to start negotiations • Founding team is the core of any FTTF investment. Investor has to know and understand the people behind the start-up, drivers of the team and their long-term entrepreneurship. FTTF strictly insists that tech competence is part of start-up and the founders are 100% committed to the start-up. 359 • Business Model characteristics are: ▪ Market entry in attractive niche ▪ Scalable products ▪ Deep understanding of the market environment and problem/ solution fit FTTF standard investment approach focuses on investing 250k EUR as a convertible loan for the 7,5% shares in the start-up equity. FTTF is usually the first investors whilst other investors may also join PoC investments – excluding strategic investors or non-profit organizations. 360 Keynote speech: CEETT Platform – Central Eastern European Technology Transfer Platform From 13:40 to 14:00 Natalija Stošicki, Director, Investments and EU Programmes Department, SID Bank / SID – Slovenska izvozna in razvojna banka ABSTRACT OF THE KEYNOTE SPEECH In 2017 and 2018 Slovene Equity Growth Investment Program (SEGIP) with EUR 100m and Croatian Growth Investment Program (CROGIP) with EUR 80m were launched in cooperation between European Investment Fund (EIF) and SID Banka and Croatian Bank for Reconstruction and Development (HBOR), respectively, with the aim to support the growth segment of the private equity market in the two countries. All available funds were transferred to the private equity funds for further equity and quasi equity funding of Slovene and Croatian companies in growth stage. SEGIP and CROGIP deployment exceeded initial expectations, prompting the parties to enhance the collaboration by expanding the scope of the respective program to the next level - Central Eastern European Technology Transfer (CEETT platform) that is based on the ITA Tech best practices. The resulting joint initiative is the first investment program under the Central and Eastern European Technology Transfer (CEETT) initiative, to which SID Banka contributed an additional EUR 10 million to SEGIP, HBOR contributed additional EUR 10m to CROGIP and the EIF made further EUR 20 million available for investment. Thus, the total available funding amount indicatively represents EUR 40 million. CEETT platform will support the most promising technology transfer projects originated at public research organizations in Slovenia and Croatia that would otherwise be considered not mature enough for traditional Venture Capital funds and thus trapped in so called “Valley of Death”. CEETT platform shall actually close two financial gaps (two Valleys of Death) in the TRL ranges 4-9 that are: transition from laboratory to company and scale-up for high-risk innovative start-ups. Existing grants that are dedicated to fund the TRL phases 1-7 are not big enough and not regularly available. Therefore, Tech Transfer Fund (VC TT Fund) that will address financing to the projects at lower TRL, would be established. The fund will be focused on technology transfer activities across various fields providing financing primarily to university and research center spin-offs and to projects at the proof-of- concept stage, also providing follow-on financing to these projects at a later stage. It is expected that projects in the proof-of-concept phase (pre-seed), in terms of the number of investments, will represent a majority focus of the Fund’s investments. Beneficiaries, the enterprises, must be in the seed, start-up or later stage venture investment phase and must originate from a university or research institute. Fund Manager will be looking for investments in collaboration with public research organizations, academia and industry partners on a contract and NDA basis. Fund manager will 361 be looking for private co-investors in projects and spin-outs, but also for private investors on the level of the Fund. Investment program size is for both countries EUR 40m. SID Banka, Croatian Bank for Reconstruction and Development and EIF can invest additional funds in the platform it has promising pipe-line of projects and start-ups. We hope that Republic of Slovenia will complement the CEETT support of technology transfer also with grants for the TRL phases 1- 7 taking part of the risk of closing two valleys of death gap, which will additionally incentivise transfer of research achievements and innovations into economy. 362 Paper presentations: scientific papers on technology transfer and intellectual property From 14:00 to 15:30 Moderator: Tomaž Lutman, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Title Authors Technology Transfer Fund - Central Eastern European Technology Marijan Leban Transfer (CEETT) platform Špela Stres Software Protection and Licensing Challenges in Europe: An Urška Fric Overview Špela Stres Robert Blatnik European Guiding principles for knowledge valorisation: An Špela Stres assessment of essential topics to be addressed Levin Pal Marjeta Trobec Digital Innovation Hubs and Regional Development: Empirical Bojan Ćudić Evidence from the Western Balkan countries Špela Stres Technology Transfer as a Unifying Element in EU Projects of the Duško Odić Center for Technology Transfer and Innovation Špela Stres Proof of Concept cases at the Jožef Stefan Institute in 2020 and 2021 Marjeta Trobec Špela Stres European Industrial Strategy - a great opportunity to strengthen the Levin Pal role of technology transfer offices France Podobnik Špela Stres Knowledge generation in citizen science project using on-line tools: Jure Ftičar CitieS-Health Ljubljana Pilot Miha Pratneker David Kocman Overview of National Sources of Finance and Supports Available to Vojka Žunič Spin-Out Companies from Public Research Organizations Marta Klanjšek Gunde Application of 3D printing, reverse engineering and metrology Remzo Dedić 363 Željko Stojkič Igor Bošnjak Towards the Market: Novel Antimicrobial Material Tomaž Lutman Marija Vukomanović Technology Transfer in Belarus Alexander Uspenskiy Aliaksei Uspenski Maxim Prybylski 364 Opportunities arising from publicly funded research projects / presentations of successful scientific projects From 15:30 to 16:40 (in Slovene and English languages) Moderators: dr. Vojka Žunič, National Institute of Chemistry, Knowledge Transfer Office, mag. Jure Vindišar, National Institute of Biology, Technology Transfer Office, Tomaž Lutman, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Title Presenter(s) Organization Vloga glukagonu podobnega peptida-1 Prof. Dr. Mojca University medical center v reprodukciji / The role of GLP-1 in Jensterle Sever Ljubljana Reproduction Does relatedness matter for bacterial Prof. Dr. Ines Biotechnical faculty, University interactions? Mandić-Mulec of Ljubljana Prof. Dr. Nataša Faculty of Medicine, University Kanabinoidni receptorji in zdravljenje Debeljak, Dr. of Ljubljana, Institute of hormonsko odvisnega raka dojke Luka Dobovišek Oncology Ljubljana Slovenian Academy of Sciences and Arts 6600 years of human and climate Research done in cooperation Doc. Dr. Maja impacts on the environment, recorded in Andrič with Prof. Andrej Šmuc, the lacustrine sediments of Lake Bohinj University of Ljubljana and Prof. Nives Ogrinc, Jožef Stefan Institute. COVID-19: Razvoj postopka za Dr. Polona testiranje zaščitnih mask National Institute of Biology Kogovšek Doc. Dr. Aleš How we developed a living coating Jožef Stefan Institute Lapanje 365 DNA technologies and seafood / DNA Doc. Dr. Andreja National Institute of Biology tehnologije in hrana iz morja Ramšak 366 Award announcement: WIPO Medal For Inventors From 16:40 to 16:50 Moderator: Marjeta Trobec, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission members: Alojz Barlič, Slovenian Intellectual Property Office (SIPO) Matthias Keckl, Fraunhofer Technologie-Transfer Fonds (FTTF) GmbH Nina Urbanič, Slovene Enterprise Fund ANNOUNCEMENT OF THE WINNER WIPO IP MEDAL FOR INVENTORS Dear Ladies and Gentlemen, With the World Intellectual Property Organisation and the Slovenian Intellectual Property Office on-board as co-organisers we wish to announce the second WIPO award recipient today. The WIPO IP Enterprise Trophy is awarding Slovenian enterprises for their good practice in constant and methodological usage of the IP system in their business activities. That award went to GEM Motors. GEM Motors is actively cooperating with several public- research organisations. They have a clear IP strategy with patents in EU, India, USA, Russia, Japan, China and S. Korea and that is essential for B2B business. Their in-wheel patented technology has been presented at several fairs and conferences. Through the social responsibility programs by promoting the urban e-mobility different project partners, other companies and schools are included. And finally, they constantly and methodologically encourage the creativity and innovativeness among their staff and encourage PhD employments. On the other hand, the WIPO Medal for Inventors is awarding a Slovenian public researcher for her contribution to the national wealth and development. The awards will be given tomorrow at the conference ceremony between noon and one o’clock and will be accessible via live streaming on the institutes’ TV channel. The selection committee members were Mrs. Nina Urbanič, Slovene Enterprise Fund, Mr Matthias Keckl, Fraunhofer Technologie-Transfer Fonds and Mr. Alojz Barlič from the Slovenian Intellectual Property Office. 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. May I use the words from a member of the selection committee: I am very impressed with the applications, and I think there are a lot of passionate and great people behind the technologies and companies. 367 They carefully ranked at all applications and decided that the "WIPO Medal for Inventors" goes to assoc. prof. Marta Klanjšek Gunde, researcher at the National Institute of Chemistry, innovator and a co-founder of a start-up. Short justification: based on a patented invention, prof. Gunde has established a start-up company MyCol. In the company the licensed technology is a base for developing smart labels with temperature-sensitive ink, which permanently color when heated above a predetermined temperature. The invention resulted also in 5 new jobs created in the company. Congratulations! 368 Research2Business meetings (R2B meetings) Parallel session from 10:00 – 13:20 France Podobnik, Robert Premk, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) One of parallel sessions of 14. International Technology Transfer Conference were bilateral meetings between researchers and companies (Research-2-Business, R2B). They took place once again in a virtual form due to COVID-19 restrictions, but also because of good experience from 2020 and how well accepted they were last year. Registration period started already in May 2021 and lasted until the event. In this time 63 participants from 9 countries registered to the event – Slovenia, Belarus, India, Italy, Netherlands, Romania, Serbia, Spain and Turkey. International component of the meetings was also achieved with active support of Enterprise Europe Network members from Italy, Spain, Serbia, North Macedonia, Serbia, Netherlands and Turkey. Main aim of the meetings was to promote knowledge exchange between academia and companies, especially in terms of cooperation between researchers and company representatives to overcome technology challenges, to discuss available commercially interesting technologies, to find options of cooperation in forthcoming European and other international projects, to get acquainted with experts on specific fields of interest and with the current trends, while also to get familiar with the topics, that might be relevant for companies/researchers in the near future … Participants were in advance informed about the format of the meetings and how the concept of virtual meetings works in practice to avoid any technical issues at the time of the event. During the meetings main organizer was also available for support to the participants via phone and mail. At the meetings participated 27 researchers, company representatives and other stakeholders. Their fields of expertise were diverse and covered robotics, artificial intelligence, new materials, (bio)chemistry, biotechnologies, environment, physics, etc. In total 31 meetings took place between 10:00 and 13:00 (CEST). Virtual concept of meetings allowed participants to attend the meetings from any place at the pre-scheduled time. While the expected time for each conversation was set at 20 minutes, the average length of 31 meeting was around 15 minutes. The shortest meeting lasted 7 minutes, while the longest almost 26 minutes. As results and feedback from the previous years show, we can expect in the following months that established contacts between participants from the industry and research community will lead to cooperation between them. 369 Connecting high-school education system with academia: Presentations of selected research topics from Jožef Stefan Institute and proposals for cooperation Parallel session from 13:20 – 15:20 Moderator: Urška Mrgole, Jožef Stefan Institute, Center for Technology Transfer and Innovation 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 14th International Technology Transfer Conference 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. At the beginning, 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 collaboration 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. Preparation and implementation of lectures for teachers and principals: for closed groups of professors the Center for Technology Transfer and Innovation can organize trainings and lectures from the Jožef Stefan Institute’s field of work with the aim of implementing new in-depth knowledge in classrooms. Mentorships for research assignments of high school students: The researchers from the Jožef Stefan Institute offer mentorships for research assignments for high school students. Participation in various European projects and initiatives such as “Science with and for Society”: the Center for transfer technology 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 and SciChallenge. Within the STEM4Youth project nine modules in the field of chemistry were prepared and 370 implemented in 19 Slovenian primary and secondary schools, with 20 mentors and over 500 elementary and high school students participating. In the second part researchers from various research departments presented their work. Dr. Janja Vidmar, 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 recent research projects was related to the investigation of drug abuse in educational institutions using wastewater analysis. Matej Kolarič, mag. biochem., Department of Biochemistry, Molecular and Structural Biology, B1: The mission of the department is related to enzyme analysis, molecular mechanisms of programmed cell death, and the immune response. Areas of research focus on proteolytic enzymes with the aim of treating and detecting diseases and improving the quality of life of patients. At the department the identification and quantification of different proteins, for example in human blood, is done via mass spectrometry. Assist. prof. dr. Peter Rodič, Department of Physical and Organic Chemistry, K3: The department is focused on the investigation of physicochemical processes on the surfaces of solids, such as corrosion and heterogeneous catalysis, as well as the synthesis of new compounds. The goal is to gain new insights and understanding of mechanisms of protection and degradation of materials in different environments. The activities of the department are also related to a phenomenon we all encounter every winter: what is the impact of road salting on corrosion. Sebastjan Nemec, mag. pharm., Department for Materials Synthesis, 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. Mark Zver, M. Sc., Department of Surface Engineering and Optoelectronics, 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. Erik Novak, mag. prof. mat., Artificial Intelligence Laboratory, E3: The Department for Artificial Intelligence is concerned mainly with research and development in information technologies with an emphasis on artificial intelligence. Their main focus is development of practical solutions useful in the public and private sector. The department cooperates with videolectures.net which is an online repository of lectures from prestigious conferences and events. Dr. Živa Stepančič, Laboratory for Open Systems and Networks, E5: The focus of the laboratory is on research and development of next generation networks, telecommunication technologies, components and integrated systems, information society services and applications etc. The laboratory participated in the SI-PASS project, where hub (network) was established and the national e- services are integrated. Center for Technology Transfer and Innovation at Jožef Stefan Institute wishes 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. 371 The Conference closing From 16:50 to 17:00 Moderator: Robert Blatnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) It is time to close this year's conference. The topic of the conference was how to bridge the valley of death – and we received some answers to that question today. While listening to the presentations I will quote dr. Spela Stres from the last year Conference closing: Water dripping day by day wears the hardest rock away (»Tiha voda bregove dere«). Tech transfer is always going to be the silent water almost going unnoticed. But that is how you maximise the impact of tech transfer: by being persistent and persistently professional. But I would like to add also this, that many small springs of water coming together could bring strong river which is irrigating the deserts. From the perspective of the Conference organizing committee we can say that this year's conference has been professional in every aspect. We are happy, though, that the conference is behind us, because there is a lot of work put into it every year, and we would like to thank all our colleagues here at the Center for Technology Transfer and Innovation at the Jožef Stefan Institute who worked tirelessly for the conference to take place in such a diverse format and with such perfect execution. But what actually mattered today was that everyone who followed this conference was able to feel how far we can go with the collective spirit of the researchers from all public research organisations in Slovenia, and we have high hopes that all tech transfer offices are going to join in to that spirit as well. This has been a lovely event, despite the covid-19 situation. We now feel this has been again the best conference we have ever had. Thank you all and see you soon! 372 Day 2 373 CONFERENCE CEREMONY 374 Overview of the Conference Ceremony 8 October 2021 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 Mark Boris Andrijanič Minister za digitalno preobrazbo Republike Slovenije Minister for Digital Transformation 11:20 – 12:25 Greetings Prof. Dr. Mojca Ciglarič Chair of the Programme Committee of IS2020 Dean of Faculty of Computer and Information Science 12:25 – 12:55 Awards of IS2021 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 14. ITTC: Awards ceremony – competition for the best innovation with commercial potential in the year 2021, WIPO Medal for Inventors and WIPO IP Enterprise Trophy 14. ITTC Organising Committee World Intellectual Property Organisation representative / Slovenian Intellectual Property Office representative Awards “Pioneers of computer education in high-schools” 12:55 – 13:00 Musical performance 375 376 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek F Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume F Ljudje in okolje People and Environment Uredniki / Editors Janez Malačič, Tomaž Ogrin, Matjaž Gams http://is.ijs.si 6. oktober 2021 / 6 October 2021 Ljubljana, Slovenia 377 378 PREDGOVOR Konferenca je sestavljena iz dveh: - demografske, predsednik prof. dr. Janez Malačič, letos štirinajstič - okoljske, predsednik mag. Tomaž Ogrin, letos tretjič. Število umrlih za kovidom se približuje petim milijonom, število registriranih obolelih gre proti 250 milijonov. V primerjavi s 130 milijoni rojenimi in 60 milijoni umrlimi letno se pet milijonov ne zdi več zanemarljivih kljub uspešnim cepivom. Hkrati je razlika med rojenimi in umrlimi vsako leto manjša, a se bo zaradi strukturnih vplivov rast svetovnega prebivalstva nadaljevala še dolgo v prihodnost. Za Slovenijo sta med najbolj perečimi tematikami staranje prebivalstva 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. Ekstrapolacija sedanje rodnosti pokaže uničujoče posledice že v nekaj prihodnjih stoletjih celo za tako velika prebivalstva, kot je japonsko. Še veliko težje posledice pa bi bile v Sloveniji in drugih majhnih evropskih prebivalstvih. Zato je za Slovenijo ključno, da v prihodnjih desetletjih vodi politiko, ki bo dvignila rodnost na ravnovesno raven. Podobno travmatične so napovedi glede okolja. Medtem ko zavedanje o pomenu okolja narašča, mirno gradimo nova in nova veletrgovska središča na najboljši kmetijski zemlji, smo prvi v Evropi po m2 veletrgovin na prebivalca v Evropi, po tem kriteriju in kilometrih avtocest na prebivalca pa smo med prvimi na svetu. To je posledica kratkovidnosti, saj recimo narašča spletno nakupovanje in vse veletrgovine enostavno ne bodo mogle obstati. V letih od osamosvojitve smo izgubili 70.000 ha, tako da je ostalo še cca 180.000 ha obdelovalnih (njivskih) zemljišč, v občinskih prostorskih načrtih je predvidenih za pozidavo še 57.000 ha. Ni čudno, da imamo manj kot 50% samopreskrbo s hrano in podobno energetsko odvisnost. Od leta 2000 smo izgubili 10 odstotkov obdelovalnih površin. Slovenija je majhna država z malim vplivom na svet, a narava je naša prednost v Evropi in mora biti prioriteta. Ima tudi gospodarski turistični pomen z delovnimi mesti za veliko prebivalcev in generacij. Ena od prioritet so prosto tekoče reke in potoki, za nas in za zanamce. Modrost je v izreku: ''Ne uničujmo narave, da bi reševali okolje. '' Poznan v tujini kot ''Do Not Destroy the Nature to Save the Environment.'' Želimo podati usmeritev Slovenije v varno, prijazno, zdravo in kakovostno okolje za vse državljane in državljanke Slovenije. Opozarjamo na prehitro uničevanje okolja, kmetijskih površin, nepotrebno gradnjo novih in novih trgovskih centrov, avtocest in energijskih objektov na najboljših zemljiških površinah, še posebej pa moti zaostalost v odnosu do okolja in demografije, kar se vidi npr. v čedalje več reklamah ob avtocestah. Večinoma so nezakonito postavljene na kmetijskih površinah, a ker je to v pristojnosti posameznih občin, se reklame množijo še naprej. Za primerjavo – na Češkem so jih prepovedali pred kar nekaj leti. Je mogoče hkrati spodbujati tehnološki razvoj, uporabo obnovljivih virov in preprečevati negativne vplive na okolje? Smo sposobni preusmeriti antropocentrični razvoj v ekocentričnega, v trajnostnega? Potrebujemo strožji nadzor varstva na ožjih, širših in vplivnih vodnih območjih za zaščito podtalnice in pitne vode, vključno z ekonomskimi in lastniškimi načeli? Imajo mesta dovolj zelenih površin v mestih, ali bodo imela podjetja in 379 inštitucije vse pozidano, v asfaltu in betonu? Kdaj bomo sanirali degradirana območja, na primer Celjsko kotlino? V letu 2020 smo pripravili Belo knjigo strokovnega varovanja okolja http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20znanost%20o%20okolju%202020.pdf in s tem postavili pomemben mejnik pri izboljševanju slovenskega okolja. Politično vodstvo je sprejelo okoli 10 predlogov izmed zbranih 50, kar bi optimist ocenil kot dobro, pesimist pa kot slabo. A najbrž je pot do trajnostnega razvoja še dolga, dolga! Janez Malačič, Tomaž Ogrin in Matjaž Gams 380 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Konferenca Ljudje / Conference People Janez Malačič, predsednik Matjaž Gams, organizator Drago Čepar Christian Gostečnik Majda Černič Istenič Boštjan Kerbler Karin Kasesnik Dušan Kidrič Marko Krevs Tomaž Merše Mari Osredkar Janja Pečar Janja Povhe Jože Ramovš Jože Sambt Milivoja Šircelj Petronela Vertot Božidar Voljč Konferenca Okolje / Conference Environment Tomaž Ogrin, predsednik 381 382 DEMOGRAPHIC PROCESSES AND THEIR ROLE IN FULFILMENT OF THE OBJECTIVES OF AGENDA 2030 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: Demographic processes throughout the whole history of the and comprehensive definition is the definition of the World development of human society were an important factor of Commission on Environment and Development which development and survival whereas for many fields are also defines the sustainable development as: "..... development crucial. Demographic phenomena are one of the main that meets the requirements of the current generation and at challenges for sustainable development as they have an the same time does not endanger the opportunities of future impact on a wide range of issues including sustainable generations to meet their own requirements” where special development. importance is given to the third generation. One of the most important elements of sustainable development which is also expressed in the most important document of the contemporary concept of sustainable development which is Agenda 2030 and Agenda 21., are demographic trends and factors, therefore, as such, they should be incorporated in the general analyses by exploring the interaction between demographic trends and sustainable development. Demographic components are the basis for progress, survival and development for all societies/humanity and ignoring this basic truth sooner or later brings negative results in other areas of life. However, regardless of which socio-economic or environmental sector is in question, the path to sustainable development is the people so it is imperative that the problems and demographic potential be taken into account if we are to find answers to the demand for sustainability in Figure 1 . Sustainable development scheme economic, social, ecological, etc. development. Thus for the sustainable development of countries, regions, Sustainable development means qualitative growth and municipalities, etc., it is necessary in the first place to ensure socio-economic and cultural development which is in demographic sustainability. relation to the capacities of the living environment which must be developed so that future generations are not Keywords: demographic processes, demographic hampered (endangered) by the possibilities of existence. sustainability, sustainable development, etc. However, sustainable development can not be conceived only as activity which is oriented towards environmental protection and environmental problems (the first concepts 1 INTRODUCTION for sustainable development) but is a multidimensional process of global character which includes social, In the perspective of the development and progress of economic, demographic, political issues, etc. human society, the concept of sustainable development is Agenda 2030 and Agenda 21 which have been transformed given the main attention, transforming sustainability as the into: "global partnership for sustainable development" and most important part of development policies of all spheres "work program for the 21st century", underline the weight of of life whether those of global, regional or local levels. demographic developments for sustainable development, In the contemporary literature there are various definitions therefore it is necessary: the incorporation of demographic of sustainable development, however, the most widespread 383 factors and trends in the analysis of sustainable However, the sustainable demographic development is also development. often conceived in a very reduced way, only in population Having regard to the role and importance of demographic growth and the gender and age structure of the population. processes for sustainable development and the fact that the Based on this approach, different authors define sustainable population is the biological structure of society and the demographic development with the state of the population economy of all geographical areas, it is necessary that for which ensures at least simple reproduction of the population the sustainable development of contries, regions or or "optimal population growth" which corresponds to the municipalities in the first place to ensure demographic fertility level of 2.1 children per woman (reproduction with sustainability thus transforming demographic sustainability the same contingency as the previous generation). Other as a subsystem into the sustainability system. authors conceive of sustainable demographic development Also the specialized research institutions of the United as a ratio between active (productive) and inactive (non- Nations (United Nations Institute for Social Development - productive) population or even as a numerical balance in UNRISD and the United Nations Development Program - gender representation. UNDP), demographic developments and their forecast rank The most comprehensive and complete definition is the (second) among the six main areas for completion of the definition of the authors who emphasize that the definition objectives of Agenda 2030. The most important of sustainable demographic development should include the demographic components for completing the Agenda 2030 socio-economic characteristics of the population (2). are: population growth trends, population trends by age, Based on this definition the SUSTENDEMO model consists migration trends, urbanization trends and demographic of two dimensions of equal importance which are the projections(1). quantitative and the qualitative dimensions. The quantitative dimension consists of components of natural growth and migration, overall population growth, 2 SUSTAINABLE DEMOGRAPHIC and population structure by age and gender. DEVELOPMENT - SUSTENDEMO The qualitative dimension consists of the socio-economic characteristics of the population, including in the first place At the center of sustainable development is undoubtedly the the educational structure of the population, professional human-the population expressed also in the most important training and economic activity. document of the contemporary concept of sustainable development which is the Rio Declaration 1992, respectively Agenda 21. An important part (Chapter V) of Agenda 21 is devoted to the role and importance of demographic dynamics and its sustainability for sustainable development. For sustainable development in the future it is necessary that: demographic factors and trends be incorporated into the global analysis of environment and development; Having regard to the role and importance of demographic movements for sustainable development and the fact that population is the biological structure of society and the economy of all geographical areas, demographic Figure 3. Demographic sustainability subsystems (3) sustainability should be considered as a subsystem in the system of sustainability (2) - SUSTENDEMO. For sustainable demographic development of a certain area is required minimal demographic development (corresponding to at least simple reproduction - stationary type of population S.B) in quantitative and qualitative terms, in order to endure economic and social sustainability. From the quantitative dimension a territory is considered demographically stable when there is an optimal correlation between: growth, size, migration and population structure by age and gender, while in qualitative terms a territory is considered demographically stable when there is a balance in socio-economic structures of the population (3). Consequently, the United Nations forecasts of the end of the last century for the trends of the global population at the beginning of the 21st century have also been revised and corrected in all scenarios, as Bricker and Ibbitson point out. Figure 2 . Sustainable demographic development scheme - "We are not facing the challenge of a population bomb, but Sustendemo of reducing the human population." (4) 384 3 DEMOGRAPHIC PROCESSES AND SUSTAINABLE DEVELOPMENT 3.1 Are demographic changes the key to sustainable development People are the main concern of sustainable development (Rio Declaration, 1992, Principle 1). In an effort to promote sustainable development, demographic movements must also be taken into account) - number, location, age structure, other structures, especially education, living conditions, ambitions and opportunities, etc. (IIASA and UNFPA, 2011). The most comprehensive and complete definition is the definition: sustainable demographic development should also include the socio-economic characteristics of the population. The World Bank defines sustainable development as: development which involves the transfer of an equal reserve Figure 4. Pyramid model of the population of stationary or according to the greatest possibilities of human, population type (6). economic and social capital, to future generations(5). Based on the above definitions, it can be concluded that for A territory is considered demographically stable (in terms sustainable development of countries or regions, sustainable of population structure by age), when there is an optimal demographic development is necessary, which at least correlation in population structure by age and gender requires that each country should achieve a stationary (graph 5). population model, which means that the next generation will be the same as the existing one. 3.4 Demographic ageing In order to achieve the necessary minimum and achieve demographic development which will not be limiting Agenda 2030 presents a universal action plan towards factors for sustainable development and fulfillment of the sustainable development in the protection and realization of objectives of Agenda 2030, it is necessary to meet several the rights of all people without ignoring anyone and any objectives in demographic developments which are: group of society, including all segments of society, all ages, with a special focus on more vulnerable groups such as the 3.2 Total number of population elderly people. The fact that the 21st century will be a century of ageing, the Total number of population - in order to achieve the key to dealing with this process is the fact that the stationary type of population where the next generation is opportunities offered by these age groups will be used the same as the existing one or the level of simple (incomparable experience and skills, active participation of population regeneration or the replacement of generations older generations in the economy, labor market and society means that at the individual level a woman in the period of in general, etc.), to face the challenges posed by the process, her fertility should be replaced by a female child - the net to respond to the ageing of the population and to promote a reproduction rate is equal to one, or the overall fertility rate sustainable development of ageing. is 2.1 children per woman (reproduction with the same With the increase of the participation of the elderly in the contingency as the previous generation). general population of a country, the society should increase the knowledge about the importance, needs, rights of the 3.3 Population structure by age elderly, with the purpose of eliminating prejudices and discrimination against the elderly. It shows not only the past but also the present and the future In this way the main goal of the Agenda 2030 will be of demographic development and is the most important fulfilled through comprehensiveness and not bypassing demographic indicator which in addition to population anyone. development also affects all other socio-economic spheres, therefore the analysis of population structure by age is basic. 3.5 Population migrations not only in demographic research but also for all other socio-economic spheres turning the process into an In the Agenda 2030 for Sustainable Development, important factor for sustainable socio-economic and spatial migrations attract special attention in fulfilling this agenda development in general. and require interdisciplinary approach and multidimensional and comprehensive commitment in addressing the role and importance of migrations in order to fulfil the objectives of Agenda 2030. 385 Population migrations present significant potential to lift LITERATURE millions of people out of poverty by providing greater employment and access to decent jobs thus affecting [1] GLOBAL TRENDS, Challenges and Opportunities in sustainable development. the Implementation of the Sustainable Development The close correlation that exists between development Goals, © United Nations Development Programme and migration (both in the country of origin and the country of United Nations Research Institute for Social destination) and the weight of migration to achieve the Development, 2017. SDOs make migrations an integral part of Agenda 2030 (7). [2] Lutz W.et al (2002), Population and environment, In reality, migration is important for 8 of the 17 SDOs that Population Council, New York, fq 6. show the role and importance of migration in fulfilment of [3] Roca Z, Roca M.N.O. Roca Z, Roca M.N.O. the objectives of Agenda 2030. The agenda, specifically in Demographic sustainability and spatial development in Objective 10.7, requires: facilitation of migration, safe, Portugal. Acta geographica Bosniae et Herzegovinae, orderly and accountable migration" implementation and 2014,2, p.25.fq.25. good management of "migration policies"- sustainable [4] Jadranka Polović: Demographic Challenges and the migration model. Future of Humanity ”., taken from: https://www.geopolitika.news/analize/dr-sc- jadranka- 3.6 Urbanization polovic-demografski-izazovi-i-buducnost- covjecanstva /. From the demographic point of view urbanism is [5] World Bank, Albania: The road to sustainable understood as the process of concentration of population in development., taken from; cities (urban areas); from the urban point of view the issue www.bankofalbania.org/web/pub/sybi_hida_280_1.pd is about the concentration of functions in a settlement; f. economists with urbanism imply the concentration of [6] Behrami S. Bajraktari F, (2021) Demographic productive power in industry and post-industrial activities, Dimension of Agenda 2030, the case of Kosovo- whereas from the sociological point of view urbanism is a Perspectives and challenges. Institute for Development process of the level of social development which is Policy. Prishtin. accompanied by changes in the way of life. [7] Schraven, D. B., Keijzer, N., & Knoll, A. (2013). Post The specialized organizations of the United Nations specify 2015: Making Migration Work for Sustainable that the Agenda 2030 for Sustainable Development and its Development .( Proucavanje Migracije Stanovnistva u 17 objectives can only be successfully implemented and Skladu sa Ciljevima Odrzivog Razvoja Ujedinjenih achieved if countries begin a transition towards sustainable Nacija) urbanization. The necessity for sustainable urbanism [8] Sustainable urbanization strategy UNDP ’s support to derives from a demographic fact that until the end of the first sustainable, inclusive and resilient cities in the half of the 21st century , over 65% of the world population developing world, UNDP, New York, 2016, fq 6.. will live in cities and towns. file:///C:/Users/sami/Downloads/UNDP_Urban- Sustainable urban development is exclusively related to Strategy.pdf Objective 11 of the Agenda 2030. [9] Development, Co-operation Raport 2012. Lessons in In fact, sustainable urban development is essential for 11 of Linking Sustainability and Development. http:// the 17 objectives of Agenda 2030. (8) www.oecd ilibrary.org/docserver/download/4312011ec011.pdf?e 3.7 Population projections xpires=1475241543&id=id&accname=guest&checksu m=164431C2E94103DDF8FE25565CD9E189. In the scope of the ways to promote sustainable development [10] Population Dynamics in the Post-2015 Development and fulfill the Agenda 2030, among the most important Agenda: Report of the Global Thematic Consultation elements, according to UNFPA experts, is the integration of on Population Dynamics, UNFPA, UNDESA, UN- population projections in development strategies and HABITAT, IOM 2013, Marr nga: policies (9), emphasizing once again the role, importance https://www.iom.int/files/live/sites/iom/files/What- and necessity of demographic developments for sustainable We-Do/docs/Outcome-Report-Pop-dynamic-and-post- development. 2015-dev-agenda-14-March-2013.pdf Trends and perspectives on population growth, demographic ageing - population ageing, migration and urbanization represent the main opportunities and challenges of countries towards the Objectives for Sustainable Development and fulfillment of the Agenda 2030, with direct and indirect implications (10). 386 Za mlajše prebivalstvo v boljšem okolju For younger population in better environment Drago Čepar Ljubljana, Slovenija Tel.: 00 386 41 677 850 drago.cepar@gmail.com ABSTRACT / POVZETEK 1.Neprijetna dejstva Avtor s pomočjo statističnih podatkov o primanjkljaju rojstev in starostni sestavi prebivalstva v Sloveniji prikaže grozljive Število rojstev v Sloveniji je že dolgo bistveno premajhno za razsežnosti primanjkljaja ljudi v delovni starosti v naslednjih enostavno dolgoročno obnavljanje prebivalstva. Skupni desetletjih. Državni razvojni dokumenti razsežnosti tega primanjkljaj rojstev do števila, ki bi zagotavljalo dolgoročno primanjkljaja podcenjujejo; ne uvrščajo ga med razvojno obnavljanje, je od leta 1980 dalje že presegel 350 tisoč oseb in pomembne makroekonomske spremenljivke in ne predlagajo je vsako leto večji. Rastoči primanjkljaj ljudi v delovni starosti, ukrepov družinske politike za povečanje rojstev, ki bi ga kadrovska vrzel, ki izvira iz primanjkljaja rojstev in odseljevanja dolgoročno zmanjšali. državljanov RS, gospodarstvu že nekaj let povzroča velike Vlada naj razkrije njegove razsežnosti za težave. naslednja desetletja, oceni gospodarske in družbene posledice, predlaga ukrepe in oceni njihovo trajanje, stroške in doprinos. Ob Grozljivo padanje števila ljudi v delovni starosti do leta 2045 prizadevanju za izboljšanje okolja je treba poskrbeti, da bo v tem lahko prikažemo s pomočjo podatkov SURS za prebivalstvo 1.7. boljšem okolju imel kdo živeti. 2020. Ker je povprečna starost iskalcev prve zaposlitve pri nas višja od 25 let, in delamo okrog 40 let, smo za delovno starost vzeli 40 let širok starostni interval od 25 do 64 let, čeprav Using statistical data on birth deficit and population age structure nekateri postavljajo spodnjo mejo na 20 ali celo na 15 let. Leta in Slovenia, the author shows frightening dimensions of deficit 2020 jih je v starostni skupini 25 do 64 let bilo 1 156 498. Čez of people in their working age in the following decades. The 25 let bodo v tej skupini tisti, ki so bili leta 2020 stari od 0 do 39 public development documents underestimate this deficit; they let; bilo jih je 912 986. Od njih jih bo v teh 25 letih umrlo 28 272, če bodo po starosti umirali do not include it among important macroeconomic variables and tako kot so po podatkih SURS leta 2019. Tako jih bo ob ničelnem priseljevanju in odseljevanju, dne they do not try to diminish it on the long term by proposing 1. 7. 2045 v skupini 25 do 64 let 884 717, torej za 271 784 manj family policy measures to increase the number of births. kot 1. 7. 2020. Enako število ljudi v delovni starosti bi izgubili, Government should unveil its dimensions for the next decades, če bi pandemija COVID trajala do leta 2045 in bi zaradi nje estimate its economic and social consequences, propose dodatno umrlo vsak dan 30 ljudi iz te starostne skupine. measures and estimate their duration, cost and benefit. While Selitveni prirast je bil v 2020 najvišji po letu 2008: priselilo se je striving for better climate, we have to make sure that somebody 18.365 prebivalcev več, kot se jih je odselilo.1 remains to live in the better climate. 2.Državni razvojni dokumenti ne predlagajo zdravil KEYWORDS / KLJUČNE BESEDE Razvojni dokumenti - Strategija dolgožive družbe2 , Strategija Demografija, rodnost, obnavljanje prebivalstva, primanjkljaj razvoja Slovenije 20303, Poročilo o razvoju 20194- temu ne rojstev, selitveni prirast, delovna starost, vladni ukrepi, okolje, posvečajo dovolj pozornosti. Prebivalstveni primanjkljaj kadrovska vrzel. omenjajo olepševalno, kot oviro za hitrejši razvoj, ne pa kot hudo grožnjo sedanji ravni blaginje. V Poročilu o razvoju 2019 Demography, fertility, population regeneration , births deficit, , ki predstavlja spremljanje uresničevanja Strategije razvoja migration surplus, working age, governmental measures, Slovenije 2030, UMAR leta 2019 predstavi 70 kazalnikov environment, human, resources gap. uspešnosti, vendar se niti eden ne nanaša na število ljudi v delovni starosti, ali na rodnost. Zapiše, da »tudi ob pozitivnih ∗Article Title Footnote needs to be captured as Title Note † neto migracijah… okoli štiri tisoč oseb na leto bo po Author Footnote to be captured as Author Note 1 Barica Razpotnik, Selitveni prirast pozitiven, 3 Vlada RS, december 2017, https://www.gov.si/assets/vladne- https://www.stat.si/StatWeb/News/Index/9650, 19.9. 2021 sluzbe/SVRK/Strategija-razvoja-Slovenije- 2 Vlada RS, julij 2017, 2030/Strategija_razvoja_Slovenije_2030.pdf https://www.umar.gov.si/fileadmin/user_upload/publikacije/kratke_analize/Strate 4 UMAR, april 2019, gija_dolgozive_druzbe/Strategija_dolgozive_druzbe.pdf https://www.umar.gov.si/fileadmin/user_upload/razvoj_slovenije/2019/Porocilo_o _razvoju_2019.pdf 387 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia F. Surname et al. projekcijah do leta 2030 prišlo do zmanjševanja aktivnega usposobljenosti in učinkovitosti upravljanja in njunih skupno 22 prebivalstva v povprečju za 10 tisoč oseb na leto.«, vendar ob kazalnikih ne omenja kadrovske vrzeli. Med vsemi 70 kazalniki tem ne vključi sirene. Odsoten je pogled za več kot 10 let nobeden ne naslavlja primanjkljaja ljudi. naprej. Bralec ne dobi občutka za ogromnost prebivalstvenega primanjkljaja niti zavesti o nujnosti ukrepanja. V Pomladanski napovedi gospodarskih gibanj 2021 7, UMAR zapiše, da bo predvidena gospodarska rast tudi posledica »nadaljnje ugodne dinamike pritoka tuje delovne sile, ki je tudi v Poročilo o razvoju 20205 pogosteje in z večjim poudarkom preteklem zaostrenem letu ostal na visoki ravni, in nadaljnjega omenja demografske spremembe in pomanjkanje ustrezne zviševanja stopnje aktivnosti. To bo tudi vidno blažilo postopno delovne sile. Na strani 9 UMAR zapiše: » Vse to zahteva zelo upadanje števila prebivalcev v starosti 20– hitro in še precej korenitejše ukrepanje za 64 let, ki zadnjih deset zagotavljanje ustrezno usposobljenih človeških virov oziroma znanj in spretnosti. let negativno vpliva na obseg razpoložljive delovne sile.« » in opredeli nekaj prednostnih nalog za zmanjševanje tega pomanjkanja. Med njimi ni ukrepov za povečanje rodnosti. Slika Načrt za okrevanje in odpornost (NOO) je Vlada sprejela 28. 28 na strani 53 pozornemu bralcu pove, da samo petina odstotka aprila 20218 . Sloveniji prinaša 1,8 milijarde evrov nepovratnih prebivalcev EU živi v državah, ki imajo neugodnejše Projekcije sredstev. Države morajo vsaj 37 odstotkov sredstev nameniti javnih izdatkov, povezanih s staranjem, 2016–2070. S Sliko 31 stebru Zeleni prehod, vsaj 20 odstotkov pa stebru Digitalne na strani 56 pove o zmanjševanju števila ljudi v delovni starosti, spremembe. Slovenija je prvemu namenila 42, drugemu pa 21 kar je povedal že leto dni prej, namreč, da jih bo do leta 2030 odstotkov vseh sredstev. V poglavju Politike za naslednjo vsako leto za 14 do 15 tisoč manj; graf zelo nazorno prikaže generacijo(str.17) , kjer bi pričakovali ukrepe za povečanje večanje primanjkljaja. Škoda, da slike ne podaljša preko leta števila rojstev in s tem števila mladih, je za mlade od vrtca do 2030. univerze predvidenih mnogo koristnih ukrepov, vendar ni ukrepa, ki bi zagotavljal ali prispeval k temu da mladi bodo in da Poročilo o razvoju 2021 6 v glavnih ugotovitvah sicer omenja jih bo več kot sedaj. V poglavju o Stanovanjski politiki (str. 454), »povečanje javnih izdatkov, povezanih s staranjem pri izzivih sicer zapiše, da »se mladi zaradi oteženega dostopa do prebivalstva«, ne omenja pa vpliva epidemije na družine z otroki stanovanj kasneje osamosvajajo in odločajo za oblikovanje in na odločanje mladih za otroke. Med Priporočili razvojni družine, kar se odraža na demografskih trendih«(str.455). Med politiki navede pospešitev rasti produktivnost, vključujoči ciljnimi skupinami stanovanjske politike, ki gotovo lahko družbeni razvoj in medgeneracijsko solidarnost (med drugim z bistveno prispeva k odločanju mladih za otroke, navaja tudi zagotavljanjem zadostnega obsega delovne sile tudi z aktivnim družine z več otroki (str. 462); vendar med cilji ukrepov ne vključevanjem priseljencev v socialno in družbeno življenje), navede večjega odločanja za otroke(str.457). Povišanje rodnosti pospešeni prehod v nizkoogljično krožno gospodarstvo ter ni omenjeno. Treba bi bilo omeniti vpliv pandemije na krepitev razvojne vloge države in njenih institucij, ne omeni pa zniževanje rojstev in na položaj družin v rodni dobi ter določiti premajhnega števila rojstev, oziroma potrebe po povečanju. V razumen del sredstev EU za odpravo posledic in za zvišanje poglavju Visoko produktivno gospodarstvo, ki ustvarja dodano rodnosti. Pohvaliti je treba poskus projekcije vpliva NOO na vrednost za vse ugotovi, da »se obseg ponudbe delovno ključne makroekonomske spremenljivke do leta 2040 na strani sposobnega prebivalstva zmanjšuje«, in to pomeni težavo pri 502 in 505, žal pa med njimi ni tistih, ki odražajo primanjkljaj »zapiranju razvojne vrzeli«, vendar zdravilo išče samo v ljudi. povečanju produktivnosti, potrebe po povečanju rodnosti pa ne omeni. Med 19 kazalniki nobeden ne prikazuje primanjkljaja 3. Zakaj ne ukrepamo? rojstev ali kadrov. V poglavju Vključujoča, zdrava, varna in odgovorna družba omenja ranljive skupine, vendar med njimi na Pred Slovenijo sta dve nujni nalogi. Prva je, zagotoviti dovolj nademo družin z otroki. Omeni in oceni povečanje izdatkov ljudi v delovni starosti za gospodarsko in narodno preživetje v povezanih s staranjem z 20,7 % BDP v letu 2019 na 29,8 % v naslednjih 25 letih. Iz razvojnih dokumentov je videti, da se te letu 2070, oceni povečanje izdatkov za pokojnine in zapiše, da se naloge vedno bolj zavedamo, in tudi razmišljamo, kako jo bo leta 2050 število upokojencev izenačilo s številom zaposlenih, reševati, ne najdemo pa ničesar o drugi dolgoročno ključni vendar ne omeni možnosti, da bi vplivali na demografske nalogi, to je predlogov za povečanje rodnosti. spremembe. Od 21 kazalnikov, nobeden ni povezan s pomanjkanjem ljudi. Če je kaj vsakomur jasno, je jasno to, da če imamo danes premalo V poglavju Učenje za in skozi vse življenje prikaže Sliko 26, ki ljudi v delovni starosti, je to zato, ker se nam jih je pred desetletji kaže, da je že konec leta 2018 kadrov primanjkovalo polovici premalo rodilo. Zakaj ne zgrabimo bika za roge in odpravimo vseh podjetij, med njimi 70 odstotkom velikih podjetij. Med 8 problema pri korenini? Kako, da v razvojnih dokumentih ne kazalniki nobeden ne obravnava pomanjkanja ljudi.V poglavjih najdemo prizadevanj za povečanje rojstev? Ohranjeno zdravo naravno okolje in Visoka stopnja sodelovanja, 5 UMAR, junij 2020, https://www.umar.gov.si/fileadmin/user_upload/razvoj_slovenij 7 UMAR, Ljubljana, marec 2021 e/2020/slovenski/POR2020.pdf https://www.umar.gov.si/fileadmin/user_upload/napovedi/poml 6( UMAR, junij 2021, ad/pomladanska_2021/Pomladanska_napoved_2021- https://www.umar.gov.si/publikacije/single/publikacija/news/po splet_01.pdf rocilo-o-razvoju- 2021/?tx_news_pi1%5Bcontroller%5D=News&tx_news_pi1% 8 (https://www.eu-skladi.si/sl/dokumenti/rrf/01_si-rrp_23-7- 5Baction%5D=detail&cHash=c64dcbcdb53bdad9c7a048e131d 2021_lekt.pdf) 72d09 388 Insert Your Title Here Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Poročilo o spletnem dogodku Ekonomija pod žarometi9 navaja delovni starosti ogroža ne le gospodarski razvoj in gospodarsko ekonomista in bivšega finančnega ministra dr. Dušana rast, ampak tudi sedanjo raven blaginje. Nemudoma je treba Mramorja: » Vse meni znane napovedi ekonomskih gibanj za prepoznati demografski primanjkljaj kot hudo grožnjo in v prihodnjih približno 30 let vodijo do naslednjega sklepa. povezavi s tem potrebo po takojšnjem ukrepanju s pogledom 30 Materialna blaginja srednjega in visoko razvitega sveta, tudi in več let naprej. Titanic ni šel pod vodo, ker bi spregledali Slovenije, je izjemno ogrožena. Pričakujemo lahko nižji ledeno goro, ampak ker so jo ugledali prepozno in prepozno življenjski standard, torej zmanjšanje dobrin, ki bodo na zasukali krmilo. razpolago posameznemu prebivalcu. Ključni problem, zaradi katerega so napovedi tako črnoglede, so na eni strani vedno bolj Pristojne ustanove naj priskrbijo podatke; vsi imamo pravico do katastrofalne spremembe v okolju in na drugi strani staranje njih. Tako kot pri osvetljevanju okoljske problematike, naj tudi prebivalstva.« na področju starostne zgradbe ovrednotijo in prikažejo posledice nesprejemanja ukrepov za povečevanje števila mladih. Če je Naslov letošnje konference Ljudje in okolje torej zadene žebljico Nemčija lahko ocenila svoj primanjkljaj delavcev, ga lahko zase na glavico. Nočemo prezreti pomena COVIDA, vendar je ta, kar tudi Slovenija. Če lahko predvidimo in ocenimo zaloge lesa in se tiče preventivnih ukrepov na boljšem. Ko posledice virusa pitne vode, samooskrbo z mlekom, mesom, elektriko, vidim danes in tukaj na svojih najbližjih, meni pa grozijo že jutri, premogom …, naj vlada s strokovnimi uradi in službami oceni in se mi ni težko odločiti za najbolj zdravilen ukrep, čeprav ni objavi zaloge in samooskrbo z delovnimi rokami in bistrimi najbolj prijeten. Posledice današnje nizke rodnosti pa bomo čutili glavami za nekaj desetletij naprej. Ukrepati je treba ne le v šele čez 25 let. In kakšne bodo? Znanost že desetletja ponazarja, Sloveniji, ampak tudi na mednarodni ravni: z dejavnim slika in preračunava dolgoročne posledice podnebnih sodelovanjem pri oblikovanju ukrepov EU, ki bodo pripomogli, sprememb. Po desetletjih risanja in ponavljanja teh posledic v da ne bomo del področij EU, kjer »nikogar več ni«; v drugih medijih, šoli, politiki in drugod je vladam mogoče sprejeti mednarodnih organizacijah in v dvostranskih odnosih s ukrepe, ki za okolje namenjajo ogromne vsote. Pri nizki rodnosti posameznimi državami. Pandemija dodatno ogroža življenja in je drugače. Kratkoročno je blagodejna, težave in slabe posledice povečuje potrebo po prizadevanju za razvoj in obstoj. Zato je nastopijo čez desetletja. Nihče pa nam nazorno ne prikaže teh poglobljena vsebinska javna razprava na osnovi dejstev in posledic za pokojnine in proračun, za zdravstvo, šolstvo, znanost, podatkov – tudi tistih, ki jih prinaša virus – v času virusa še kulturo, kakovost življenja. nujnejša kot prej. Na osnovi razprave pa so potrebni odločni ukrepi. Pri virusu in pri podnebju vsi vemo, da bomo skupaj zmagali ali skupaj poraženi, kajti ne virus ne podnebje ne spoštujeta Z ukrepi družinske politike in drugimi spodbudami je treba pri državnih meja. Ker pa vsaka država skrbi za svoje upokojence, mladih spodbuditi odločanje za življenje in povečati število za bolnike …, medtem ko mladi in zdravi lahko vanje vložena rojstev, da ne bomo čez 25 let spet v istem položaju kot danes, državna sredstva podarijo komurkoli, so finančne in druge to je z ogromnim primanjkljajem ljudi, sposobnih in voljnih posledice nizke rodnosti zaprte v meje posameznih držav. Vsaka delati, za naslednjih 25 let. Evropske države z načrtno sama sprejema odločitve in nosi odgovornost zanje. družinsko politiko imajo zdaj skoraj dovolj rojstev za dolgoročno obnavljanje prebivalstva. Desetletja so se zavedale, Matjaž Gams je leta 2018 kot enega od vzrokov za neukrepanje zdaj pa se je jasno pokazalo in potrdilo, da družinska politika na ravni EU zapisal tudi dejstvo, da so voditelji 8 ključnih spodbujanja odločanja za življenje ni le socialna politika evropskih inštitucij takrat imeli skupno 2 otroka, leta 1951 pa so pomoči potrebnim, ampak najbolj donosno vlaganje v imeli ti voditelji 32 otrok.10 Ni pričakovati, da nas bo EU ljubeče gospodarsko uspešnost in vsakršni razvoj. Prizadevanje za opominjala, naj zvišamo rodnost, vendar je prav, da si kot njena večjo rodnost je povezano in utemeljeno tudi z dejstvom, da enakopravna članica z vplivom na oblikovanje njenih odločitev smo si Slovenci v zadnjih stoletjih prizadevali za lastno državo in razporejanje sredstev, za primerne politike prizadevamo tudi tudi zato, da bi si z njo zagotovili dolgoročni razvoj in obstoj. v okviru povezave. Vzporedimo strah pred taljenjem arktičnega ledu s strahom pred revščino in izumrtjem in v skladu s tem določimo razmerje med Evropska ljudska stranka je na kongresu leta 2019 na predlog sredstvi za okolje in sredstvi za nova življenja. Poskrbeti HDZ sprejela resolucijo Demografski izziv na podeželskih moramo. da bo v boljšem okolju imel kdo živeti. območjih EU: nikogar več ni! (leaving nobody behind). V njej opozarja na področja, ki se soočajo s krčenjem prebivalstva, Preveč je pričakovati, da bo sedanja vlada ob boju z virusi in izgubo mladih, slabšanjem življenjskih pogojev, in zapiše: opozicijo ter predsedovanju EU v tem mandatu zmogla dosti » Zaradi alarmantnih posledic demografskega razvoja popraviti za nazaj in narediti velik korak naprej na tem področju. zahtevamo nujno ukrepanje.« D ržave z boljšo starostno sestavo Na naslednjih volitvah je treba dati možnost vladanja tistim od Slovenije se zavedajo, da je skrajni čas za znak za preplah, in strankam, ki bodo v svojih programih pokazale dolgoročen zahtevajo ukrepe EU. pogled, voljo do dejavne vloge v prebivalstvenem razvoju in odločanju o lastni usodi ter zavedanje, da pri tako velikem 4. Sklep. primanjkljaju ne gre le za razvoj, temveč za obstoj. Velik primanjkljaj rojstev v preteklih štirih desetletjih že sam po sebi ogroža obstoj Slovenije in slovenstva. Primanjkljaj ljudi v Dr. Drago Čepar 9 Okoljski izzivi in staranje so ključni problem, Gospodarska multikonference–IS 2018, Uredili Thomas Bartz-Beielstein in redakcija, Delo 23. 4. 2021 drugi, IJS, Ljubljana, 2018, str.291, 10 Matjaž Gams, Demografski trendi v svetu in Sloveniji, http://library.ijs.si/Stacks/Proceedings/InformationSociety/2018 Kako preprečiti izumiranje slovenskega naroda?, /IS2018_Zbornik_Komplet.pdf, 3.3.2019. INFORMACIJSKA DRUŽBA, Zbornik 21. mednarodne 389 Plačna vrzel po starosti in spolu pri inovativni in neinovativni vrsti dela The age and gender wage gap in innovative and non-innovative type of work Daša Farčnik Tanja Istenič Jože Sambt Tjaša Redek Ekonomska fakulteta Ekonomska fakulteta Ekonomska fakulteta Ekonomska fakulteta Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija dasa.farcnik@ef.uni-lj.si tanja.istenic@ef.uni-lj.si joze.sambt@ef.uni-lj.si tjasa.redek@ef.uni-lj.si POVZETEK Zmanjšana produktivnost zaposlenih pa je v nasprotju s po večini empirično ugotovljenimi višjimi plačami v starosti [2]. V prispevku ugotavljamo velikost plačne vrzeli po starosti in po Ena najbolj znanih teorij, ki pojasnjuje razlike v starostni spolu pri inovativni in neinovativni vrsti dela, pri čemer porazdelitvi plač in produktivnosti je Lazear-jeva »alternativna inovativno delo opredelimo s tremi vrstami neotipljivega teorija«, ki zagovarja, da so mlajši posamezniki plačani pod kapitala. Na podlagi Statističnega registra delovno aktivnega svojo mejno produktivnostjo, medtem ko so starejši posamezniki prebivalstva in dohodki iz dela za obdobje od leta 2009 do leta plačani nad svojo mejno produktivnostjo [4]. Razlog za to so med 2017, ugotavljamo, da je plačna vrzel po starosti in spolu odvisna drugim tudi plače, vezane na senioriteto [5]. Potrebno pa se je od vrste dela in od vrste neotipljivega kapitala. zavedati, da se bo produktivnost starejših delavcev v prihodnosti KLJUČNE BESEDE verjetno zviševala, saj se bodo izboljševale njihove kognitivne sposobnosti in njihovo zdravje. Prav tako razvoj zmanjšuje Neotipljivi kapital, plačna vrzel med starostnimi skupinami, potrebo po fizični moči delavcev [1]. plačna vrzel med spoloma Na drugi strani, v skladu z modeli človeškega kapitala, ABSTRACT ženske zaradi svoje tradicionalne vloge v družini manj kontinuirano sodelujejo na trgu dela, kar povzroča njihovo nižjo In this paper, we identify the size of the wage gap by age and by produktivnost in s tem tudi nižje plače v primerjavi z moškimi gender for innovative and non-innovative types of work, where [6] [7] [8]. Poleg tega ženske običajno izbirajo manj tvegane in s innovative work is defined in terms of three types of intangible capital. Based on the Statistical Register of the Working tem slabše plačane poklice [7] [9], na trgu dela pa se soočajo tudi z diskriminacijo [10]. Vendar pa se razlika v plačah med spoloma Population and Labour Income for the period 2009 to 2017, we skozi čas zmanjšuje [7], predvsem zaradi manj pogoste find that the age and gender wage gap depends mainly on the diskriminacije na delovnem mestu [11]. Poleg tega si moški in types of intangible capital. ženske skozi čas izbirajo vedno bolj podobna področja študija in KEYWORDS podobne poklice [12], kar dodatno znižuje plačno vrzel med spoloma. Intangible capital, age wage gap, gender wage gap V tem članku analiziramo razlike v plačah po starosti in med spoloma, in sicer ločeno za inovativne in neinovativne oz. tradicionalne oblike dela. Konkretno nas zanima, kakšna je 1 UVOD povprečna plača posameznega tipa delavca in na drugi strani, pri Produktivnost posameznika se skozi življenje spreminja iz več katerih starostnih skupinah ter oblikah dela obstaja statistično razlogov, npr. zaradi pridobljenih delovnih izkušenj, njegovih značilna razlika med plačami moških in žensk. kognitivnih in fizičnih sposobnosti, motivacije, usklajenosti med delavcem in delavno nalogo [1]. Številne empirične študije kažejo upad delovne uspešnosti posameznikov v starejših letih. 2 METODOLOGIJA IN PODATKI Upad je še posebej očiten pri posameznikih, starejših od 50 let V raziskavi se osredotočamo na razlike v plači med različnimi [2] ter pri delovnih nalogah, ki zahtevajo reševanje problemov, skupinami zaposlenih. Zaposleni so razdeljeni v skupine na dodatno učenje in hitrost. Nasprotno je upad produktivnosti pri podlagi treh različnih spremenljivk: starosti (do 30 let, med 30 in višji starosti manjši, ali pa ga sploh ni zaznati, pri tistih delovnih 49 let, od 50 let dalje), spola (moški, ženske) in vrste nalogah, ki so povezane z izkušnjami in verbalnimi neotipljivega kapitala. sposobnostmi [1]. Ob tem pa je potrebno dodati, da lahko Pri določanju vrste neotipljivega kapitala izhajamo iz pridobljene izkušnje iz preteklosti tudi zmanjšujejo definicije, ki se uporablja v projektu Globalinto [13] in določa tri produktivnost starejših, še posebej v današnji informacijski dobi, vrste neotipljivega kapitala: (i) organizacijski, (ii) raziskovalno- kjer znanje in izkušnje delavcev postanejo zastarele [3]. razvojni in (iii) informacijski neotipljivi kapital. Vrsta neotipljivega kapitala se določi glede na poklic zaposlenega ter 390 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Farčnik, Istenič, Sambt, Redek njegovo stopnjo in vrsto izobrazbe. Zaposleni, ki imajo terciarno (neotipljivega kapitala). V povprečju velja, da so starejši delavci, izobrazbo družbenih ved, novinarstva in informacijskih znanosti ne glede na vrsto neotipljivega kapitala in spol, prejeli višje plače. ali poslovnih in upravnih ved ter prava in opravljajo poklice kot Največje relativne razlike med starostnimi razredi so med na primer generalni direktorji/generalne direktorice, zaposlenimi starimi do 30 let in tistimi, ki so stari med 30 in 49 člani/članice uprav, menedžerji/menedžerke, let. Na primer, moški v skupini organizacijskega kot tudi strokovnjaki/strokovnjakinje za finančno poslovanje, upravljanje raziskovalno-razvojnega neotipljivega kapitala, ki so stari do 30 procesov dela in ljudi, prodajo, trženje in odnose z javnostmi, let, so v povprečju prejeli 49 odstotkov nižjo plačo kot tisti, stari pravni strokovnjaki/pravne strokovnjakinje so tisti zaposleni, ki med 30 in 49 let. Podobno visoke so tudi relativne razlike za obe sodijo v skupino zaposlenih z organizacijskim neotipljivim omenjeni skupini neotipljivega kapitala med ženskami v prvi in kapitalom [13] [14] [15]. V skupino zaposlenih z raziskovalno- drugi starostni skupini. Tako so ženske v skupini razvojnim neotipljivim kapitalom sodijo posamezniki s terciarno organizacijskega neotipljivega kapitala, ki so stare do 30 let, v izobrazbo naravoslovja, matematike in statistike in opravljajo povprečju prejele 45 odstotkov nižjo plačo od žensk v starostni poklice kot na primer strokovnjaki/strokovnjakinje fizikalnih in skupini med 30 in 49 let, v skupini raziskovalno-razvojnega zemeljskih ved, tehnično-tehnoloških strok ali elektrotehnike, neotipljivega kapitala pa 42 odstotkov nižjo plačo. zdravstveni strokovnjaki/strokovnjakinje, tehniki/tehnice Razlike med drugim in tretjim starostnim razredom, torej tehnično-tehnoloških strok. V skupino zaposlenih z med posamezniki, starimi od 30 do 49 let, in posamezniki, informacijskim neotipljivim kapitalom pa so uvrščeni zaposleni starimi 50 let in več, so razlike še vedno statistično značilne, s terciarno izobrazbo informacijske in komunikacijske vendar manjše, kar velja predvsem za moške. Tako so moški, tehnologije in upravljajo poklice kot na primer razvijalci in stari med 30 in 49 let v povprečju prejeli med 10 in 19 odstotkov analitiki/razvijalke in analitičarke programske opreme in nižje plače, odvisno od vrste neotipljivega kapitala, kot moški, aplikacij, strokovnjaki/strokovnjakinje za podatkovne zbirke in stari 50 let in več. Večje razlike so pri ženskah, predvsem v računalniška omrežja, tehniki/tehnice za telekomunikacije in skupini raziskovalno-razvojnega neotipljivega kapitala, kjer so oddajanje. Posamezniki, ki niso razvrščeni v nobeno izmed treh ženske v starostni skupini od 30 do 49 let v povprečju prejele 34 skupin neotipljivega kapitala, so zaposlenih, ki jih v nadaljevanju odstotkov nižjo plačo od žensk starih 50 let in več, ter v skupini označujemo z »brez neotipljivega kapitala« in predstavljajo informacijskega neotipljivega kapitala, kjer so ženske stare od 30 neinovativno vrsto dela. do 49 let prejele 33,6 odstotkov nižjo plačo od žensk starih 50 let Na podlagi starostnih skupin (3 skupine), spola (2 skupini) in in več. vrste neotipljivega kapitala (4 skupine), so zaposleni razvrščeni v eno izmed 24 skupin. Za vsako izmed skupin je najprej Tabela 1: Razlike v letni bruto plači med starostnimi izračunana povprečna plača, nato pa so razlike v povprečni plači razredi primerjane s t-testom. Skupine, njihove povprečne plače in razlike v plači po starostnih razredih so prikazane v Tabeli 1, Moški, Moški, Abs. Rel. razlika skupine, njihove povprečne plače in razlike v plači med spoloma Skupina <30 let 30-49 let razlika (%) pa so prikazane v Tabeli 2. Brez n.k. Za izračun povprečnih plač posamezne skupine smo 11.823 17.939 6.116 34,1*** uporabili podatke Statističnega registra delovno aktivnega Org. k. 17.643 34.973 17.329 49,6*** prebivalstva (SRDAP) za obdobje od leta 2009 do leta 2017 ter R&R k. 15.643 31.109 15.466 49,7*** podatke o dohodkih iz dela (dohodninski podatki) za enako Inf. k. 16.519 25.377 8.858, 34,9*** obdobje [16]. Dohodki iz dela so navedeni kot bruto vrednosti, Moški, Moški, Abs. Rel. razlika popravljene za rast cen življenjskih potrebščin v času, in jih v 30-49 let 50+ let razlika (%) nadaljevanju imenujemo povprečna plača. Celotno število Skupina opazovanj znaša 7.085.588 zaposlenih. Približno tretjina Brez n.k. 17.939 20.047 2.107 10,5*** (32,25 %) vseh opazovanj so moški stari od 30 do 49 let, sledijo Org. k. 34.973 38.733 3.759 9,7*** ženske iste starostne skupine (28,91 %). Moški, stari 50 let in več, R&R k. 31.109 38.362 7.252 18,9*** predstavljajo 13,47 odstotka celotnega vzorca, ženske v isti Inf. k. starostni skupini pa 10,63 odstotka. Najmlajša starostna skupina 25.377 30.496 5.119 16,8*** predstavlja najmanjši delež v celotnem vzorcu, kjer moški, stari Ženske, Ženske, Abs. Rel. razlika do 30 let, predstavljajo 8,83 odstotka celotnega vzorca, ženske Skupina <30 let 30-49 let razlika (%) pa 5,91 odstotka. Brez n.k. 10.002 15.844 5.842 36,9*** Večina opazovanih posameznikov je takšnih, ki niso Org. k. 14.573 26.616 12.043 45,2*** uvrščeni v nobeno izmed skupin neotipljivega kapitala, saj je le R&R k. 3,3 odstotka celotnega vzorca opredeljenih kot takih. 2,8 15.083 25.888 10.805 41,7*** odstotka zaposlenih je uvrščenih v skupino organizacijskega Inf. k. 14.841 21.703 6.862 31,6*** kapitala, sledi skupina raziskovalno-razvojnega kapitala (0,3 % Ženske, Ženske, Abs. Rel. razlika vzorca) in informacijskega kapitala (0,2 %). Skupina 30-49 let 50+ let razlika (%) Brez n.k. 15.844 18.891 3.046 16,1*** Org. k. 3 REZULTATI 26.616 35.896 9.280 25,9*** R&R k. 25.888 39.691 13.802 34,8*** V Tabeli 1 so najprej predstavljene razlike v plači med starostnimi razredi in po spolu ter vrstah inovativnega dela Inf. k. 21.703 32.697 10.993 33,6*** 391 Plačna vrzel po starosti in spolu pri inovativni in neinovativni Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia vrsti dela Opombe: Brez n.k. – skupina zaposlenih, ki ni uvrščena v nobeno 4 ZAKLJUČEK izmed skupin neotipljivega kapitala; Org. k. – organizacijski V prispevku ugotavljamo velikost plačne vrzeli med spoloma in neotipljivi kapital; R&R k. – raziskovalno-razvojni neotipljivi po starosti pri inovativni in neinovativni obliki dela, pri čemer kapital; Inf. k. – informacijski neotipljivi kapital. * značilno pri inovativno delo opredelimo s tremi vrstami neotipljivega 10 %, ** značilno pri 5 %, *** značilno pri 1 %. kapitala. Na podlagi Statističnega registra delovno aktivnega prebivalstva in dohodki iz dela za obdobje od leta 2009 do leta V Tabeli 2 so predstavljene razlike v letni bruto plači med 2017, ugotavljamo, da je plačna vrzel predvsem odvisna od vrst spoloma, in sicer za 24 skupin zaposlenih, ki so v tabeli prikazane neotipljivega kapitala. v treh delih glede na starostne skupine in ločeno po spolu. V Ugotavljamo, da v povprečju starejši delavci, ne glede na najmlajši starostni skupni, torej med zaposlenimi, starimi manj vrsto neotipljivega kapitala in spol, prejemajo višje plače. kot 30 let, so v povprečju moški prejeli višje dohodke iz dela. V Največje relativne razlike se kažejo med starostnima skupinama skupini zaposlenih, ki opravljajo ne inovativno delo, so moški, pod 30 let in 30-49 let. Na primer, moški, stari pod 30 let, ki stari manj kot 30 let v povprečju prejeli 15 odstotkov višjo plačo opravljajo delo v skupini organizacijskega ali pa raziskovalno- kot ženske; v skupini organizacijskega neotipljivega kapitala pa razvojnega neotipljivega kapitala so v povprečju prejeli 49 je relativna razlika v povprečnem dohodku iz dela najvišja in odstotkov nižjo plačo kot tisti, stari med 30 in 49 let. Podobno znaša 17 odstotkov. V skupini informacijskega neotipljivega velja tudi za ženske. kapitala je bila razlika 10 odstotna. Razlika v plači med moškimi V prispevku ugotavljamo tudi, da moški v povprečju in ženskami, starimi manj kot 30 let v skupini raziskovalno- zaslužijo več kot ženske, vendar je razlika odvisna od starosti in razvojnega neotipljivega kapitala, ni statistično značilna. vrste dela, ki jo posamezniki opravljajo. Rezultati kažejo, da je Največja relativna razlika v plači med moškimi in ženskami je v največja relativna razlika v plači med moškimi in ženskami v skupni organizacijskega neotipljivega kapitala, za stare med 30 skupni organizacijskega neotipljivega kapitala, in sicer za stare in 49 let, in znaša 24 odstotkov. Na drugi strani pa so ženske, med 30 in 49 let, ki znaša 24 odstotkov. Na drugi strani pa so stare 50 let in več, v skupini razvojno-raziskovalnega ženske, stare 50 let in več v skupini razvojno-raziskovalnega neotipljivega kapitala v povprečju prejele 3 odstotka višjo plačo neotipljivega kapitala v povprečju prejele 3 odstotka višjo plačo od moških. To je tudi edina statistično značilna razlika v plači kot moški. To je tudi edina statistično značilna razlika v plači med moškimi in ženskami, ki je v prid žensk. med moškimi in ženskami, ki je v prid žensk. V prihodnjih raziskavah bi bilo med drugim zanimivo Tabela 2: Razlike v letni bruto plači med spoloma pogledati še razlike v panogah, predvsem za razlike med javnim in zasebnim sektorjem ter proizvodnjo in storitvami. Moški, Ženske, Rel. Abs. Skupina razlika <30 let <30 let razlika (%) ZAHVALA Brez n.k. 11.823 10.002 1.820 15*** Org. k. 17.643 14.573 3.070 17*** R&R k. Raziskava je del GLOBALINTO projekta. 15.643 15.083 559 4 GLOBALINTO projekt je financiran s strani programa Evropske Inf. k. 16.519 14.841 1.677 10** unije Horizon 2020, Mehanizem za promocijo pametne, Moški, Ženske, Rel. Abs. trajnostne in vključujoče rasti, št. projekta 822259. Skupina razlika 30-49 let 30-49 let razlika (%) REFERENCES- niso še dodane Brez n.k. 17.939 15.844 2.094 12*** [1] Skirbekk, V. (2008). Age and productivity capacity: descriptions, causes Org. k. 34.973 26.616 8.356 24*** and policy options. Ageing horizons, 8, 4-12. [2] Skirbekk, V. (2004). Age and individual productivity: A literature survey. R&R k. 31.109 25.888 5.221 17*** Vienna yearbook of population research, 133-153. [3] Hu, Y. (2016). Implications of population ageing for the Chinese Inf. k. 25.377 21.703 3.673 14*** productivity. Economic and Political Studies, 4(4), 454-467. Moški, Ženske, [4] Lazear, E. P. (1979). Why is there mandatory retirement? Journal of Abs. Rel. razlika Skupina political economy, 87(6), 1261-1284. 50+ let 50+ let razlika (%) [5] Ilmakunnas, P., & Maliranta, M. (2005). Technology, labour characteristics and wage‐productivity gaps. Oxford Bulletin of Economics Brez n.k. 20.047 18.891 1.155 6*** and Statistics, 67(5), 623-645. Org. k. [6] Becker, G. S. (1985). Human capital, effort, and the sexual division of 38.733 35.896 2.836 7*** labor. Journal of Labor Economics, 3(1), 33-58. R&R k. 38.362 39.691 -1.328 -3*** [7] Blau, F. D., & Kahn, L. M. (2007). The Gender Pay Gap: Have Women Gone as Far as They Can? The Academy of Management Perspectives, Inf. k. 30.496 32.697 -2.200 -7 21(1), 7-23. Opombe: Brez n.k. – skupina zaposlenih, ki ni uvrščena v nobeno [8] Mincer, J., & Polachek, S. (1974). Family investments in human capital: Earnings of women. Journal of political Economy, 82(2), 76-108. izmed skupin neotipljivega kapitala; Org. k. – organizacijski [9] OECD. (2012). Closing the Gender Gap: Act Now, OECD Publishing. neotipljivi kapital; R&R k. – raziskovalno-razvojni neotipljivi [10] Castilla, E. J. (2008). Gender, Race, and Meritocracy in Organizational Careers. American Journal of Sociology, 113(6), 1479-1526. kapital; Inf. k. – informacijski neotipljivi kapital. * značilno pri [11] Mandel, H., & Semyonov, M. (2014). Gender Pay Gap and Employment 10 %, ** značilno pri 5 %, *** značilno pri 1 %. Sector: Sources of Earnings Disparities in the United States, 1970-2010. Demography, 51(5), 1597-1618. [12] England, P. (2010). The gender revolution uneven and stalled. Gender & Society, 24(2), 149-166. 392 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Farčnik, Istenič, Sambt, Redek [13] Globalinto (2021). https://globalinto.eu/ [15] Farčnik, D., Gorišek, A., & Redek, T. (2021). Micro-level intangibles [14] Piekkola, H., Redek, T., & Farčnik, D. (2020). Intangible assets in the measure: the case of public sector & application to Slovenia. public sector: an extended definition and methodological guide. https://globalinto.eu/papers/deliverables/ https://globalinto.eu/papers/deliverables/ [16] Statistični urad Republike Slovenije (2020): Zaščiteni mikro podatki SRDAP, dohodninski podatki. 393 Vpliv pandemije covid-19 na razlike med spoloma v plačanem in neplačanem delu The impact of the COVID-19 pandemic on gender differences in paid and unpaid work Tanja Istenič† Jože Sambt Daša Farčnik Ekonomska fakulteta Ekonomska fakulteta Ekonomska fakulteta Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija tanja.istenic@ef.uni-lj.si joze.sambt@ef.uni-lj.si dasa.farcnik@ef.uni-lj.si POVZETEK 1 UVOD Članek analizira razlike med spoloma v času, porabljenem za Od konca leta 2019 se ljudje po vsem svetu soočajo z obsežno plačano in neplačano delo pred in med pandemijo covid-19 v katastrofo, ki jo povzroča akutna okužba dihal covid-19 [3]. Sloveniji. Na podlagi primarnih podatkov ugotavljamo, da so se Ukrepi za preprečevanje hitrega širjenja virusa iz človeka na med pandemijo razlike med spoloma v času, porabljenem za človeka [1] so med drugim vključevali zaustavitev gospodarstva, plačano delo povečale, pri čemer moški delajo več kot ženske. zaprtje vrtcev, šol, delo od doma in družbeno distanciranje. Na drugi strani so se zmanjšale razlike med spoloma v času, Ukrepi so med drugim vplivali tudi na način preživljanja našega namenjenemu varstvu otrok, kuhanju in čiščenju, ki predstavljajo časa. V tem prispevku tako preučujemo, kako se je porabljen čas aktivnosti, ki so v večji meri izvajane s strani žensk, ter v za 14 aktivnosti na povprečni delovni dan spremenil v času vzdrževanju doma, kjer so aktivnosti v večji meri izvajane s prvega vala epidemije covid-19 v Sloveniji. Pri tem se strani moških. osredotočamo predvsem na razlike v porabljenem času za posamezno aktivnost med spoloma, in sicer pred epidemijo ter KLJUČNE BESEDE na morebitne spremembe v času epidemije. Prispevek najprej Neplačano delo, covid-19, razlike med spoloma, Slovenija, opisuje zbrane podatke s pomočjo ankete o porabi časa in poraba časa uporabljeno metodologijo, sledita predstavitev rezultatov ter zaključek. ABSTRACT This paper analyses gender differences in time spent on paid and unpaid work in Slovenia before and during the pandemic 2 PODATKI IN METODOLOGIJA COVID-19. Based on primary data collection, we find that Raziskava temelji na podatkih, zbranih v začetku maja 2020, in during the pandemic, gender gaps in time spent on paid work sicer med razglašenim prvim valom epidemije covid-19, ko so actually widened, with men working more than women. On the veljali strogi ukrepi glede omejevanja širjenja virusa. other hand, gender gaps narrowed in time spent on childcare, Posamezniki so bili naprošeni, da izpolnijo anketo o porabi časa, cooking and cleaning, which are activities that are predominantly ki se je nanašala na dve obdobji: pred epidemijo in med done by women, and household maintenance, which is epidemijo. Čas pred epidemijo je bil opredeljen kot čas pred predominantly done by men. razglasitvijo Odloka o začasni splošni prepovedi gibanja in zbiranja ljudi na javnih mestih in površinah v Republiki Sloveniji KEYWORDS (UR št. 30/20), čas med epidemijo pa kot čas veljave omenjenega Unpaid work, COVID-19, gender gap, Slovenia, time use odloka. Vprašanja so se nanašala na običajen delovni dan, pri čemer so posamezniki 24 ur razdelili med 14 različnih aktivnosti: (i) spanje, (ii) priprava obrokov, prehranjevanje, (iii) umivanje, oblačenje, (iv) delo (plačano), (v) pospravljanje, pranje, likanje, (vi) vrtnarjenje, skrb za hišne ljubljenčke, (vii) vzdrževanje, gradnja (npr. stanovanja, hiše, opreme), (viii) nakupovanje, Permission to make digital or hard copies of part or all of this work for personal or urejanje dokumentacije, (ix) študij, (x) skrb za otroke 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 (varstvo/igra/ustvarjanje), (xi) skrb za ostale posameznike (npr. citation on the first page. Copyrights for third-party components of this work must ostale družinske člane, ki niso otroci), (xii) druženje (npr. be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia pogovor s prijatelji, praznovanja, telefoniranje, videoklici), (xiii) © 2020 Copyright held by the owner/author(s). rekreacija, sprehod, vadba, (xiv) prosti čas (npr. poslušanje radia, 394 Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia Istenič, Sambt in Farčnik gledanje televizije, počitek). Aktivnosti so bile usklajene z so ga posamezniki (ne glede na spol) namenili plačanemu delu. vprašalnikom o porabi časa [1]. Moški so prav tako porabili veliko več časa za vzdrževanje doma V raziskavo je bilo vključenih 467 delovno sposobnih (v povprečju 23 minut več kot ženske), pri čemer je razlika med posameznikov, starih med 25 in 65 let. V vzorcu je bilo 50,5 % spoloma predstavljala 75 % celotnega povprečnega časa, moških in 49,5 % žensk. 47,8 % anketirancev je živelo v porabljenega za vzdrževanje. Na drugi strani so ženske porabile mestnem okolju. Ker v raziskavi preučujemo razlike med bistveno več časa za pripravo obrokov (približno pol ure oz. spoloma v porabi časa za različne aktivnosti, med drugim tudi za 38,5 % več kot moški) in za čiščenje (kjer je absolutna razlika plačano in neplačano delo, smo med anketirance vključili znašala 0,5 ure, relativna pa 44,8 %). Pred pandemijo je obstajala predvsem tiste, ki so živeli v partnerski zvezi (95,3 % tudi znatna razlika med spoloma v času, porabljenem za varstvo posameznikov v vzorcu). 67,2 % posameznikov je živelo v oz. nego otrok, čemur so ženske namenile več časa kot moški. gospodinjstvu z vsaj enim otrokom mlajšim od 18 let, od tega jih Razlika med spoloma je predstavlja 30 % celotnega časa, je imelo 42,4 % vsaj enega otroka v vrtcu ali osnovni šoli. Večina porabljenega za varstvo otrok. Pred pandemijo ni zaznati anketirancev je bila sekundarne (48,2 %) ali terciarne izobrazbe statistično značilnih razlik med spoloma v času, porabljenem za (54,4 %). 80,7 % posameznikov je bilo zaposlenih, spanje, rekreacijo, prosti čas, vrtnarjenje in nego hišnih samozaposlenih, ali so opravljali delo preko drugih oblik dela ljubljenčkov. (npr. preko avtorske pogodbe ali pa so opravljali priložnostno delo); 6,6 % je bilo brezposelnih; 5,6 % je bilo upokojenih. Od Tabla 1. Razlike med spoloma v porabljenem času pred tistih, ki so delali, jih je v času anketiranja 37,0 % delalo na pandemijo svojem delovnem mestu, 22,7 % jih je delalo od doma, 16,3 % je Porabljen čas (v urah) čakalo na delo, preostali pa niso delali iz drugih razlogov, npr. Relativna razlika zaradi varstva otrok. Absolutna (kot % porabljenega V nadaljevanju prispevka je na podlagi vzorca najprej razlika časa vseh predstavljen povprečen čas, porabljen za različne aktivnosti pred Moški Ženske (M-Ž) posameznikov) in med epidemijo covid-19 v Sloveniji, in sicer za oba spola skupaj. Nato analiziramo povprečni čas, ki so ga moški in ženske Spanje 6.81 6.86 -0.05 -0.79 porabili za različne dejavnosti v obeh obdobjih. Razlike med Priprava 1.27 1.87 -0.60 -38.45*** spoloma v obdobju pred in med epidemijo so tudi testirane s t- obrokov, testom za neodvisne vzorce. hranjenje Umivanje, 0.81 0.90 -0.10 -11.21* 3 REZULTATI oblačenje Pred pandemijo so posamezniki v povprečju na delovni dan 6,8 Plačano delo 7.44 5.98 1.45 21.59*** ur spali, 6,7 ur delali, 1,6 ure pripravljali obroke in jedli. Povprečno so porabili 1,4 ure za prosti čas in približno eno uro Čiščenje, 0.81 1.27 -0.46 -44.81*** za: čiščenje, pranje perila, likanje (1,0 ure), varstvo otrok (1,0 pranje, likanje ure), rekreacijo (0,9 ure), nego drugih posameznikov (0,9 ure), Vrtnarjenje, 0.83 0.87 -0.04 -4.35 umivanje in oblačenje (0,9 ure), vrtnarjenje, skrb za hišne nega hišnih ljubljenčke (0,9 ure). Pred pandemijo so ljudje v povprečju manj ljubljenčkov kot eno uro dnevno porabili za nakupovanje in pripravo dokumentacije (0,7 ure), druženje (0,6 ure), vzdrževanje in Vzdrževanje, 0.69 0.31 0.38 75.48*** gradnjo doma (0,5 ure) ter študij (0,3 ure). Pred pandemijo je gradnja doma povprečni čas, porabljen za neplačano delo, tako znašal 6,5 ur. Nakupovanje, 0.66 0.78 -0.12 -16.75* Med pandemijo se je povečal predvsem porabljen čas za študij urejanje (za 48,0 %), vzdrževanje doma (za 22,8 %) in druženje (za 23,8 dokumentacije %). V času pred in med epidemijo se je porabljen čas zvišal tudi v primeru skrbi za druge (za 18,2%), vrtnarjenje in nego hišnih Študij 0.20 0.33 -0.13 -45.76 ljubljenčkov (za 14,7%), prosti čas (za 14,2%) in spanje (za Nega otrok 0.81 1.11 -0.29 -29.96† 2,3%). Ta dodatni čas je bil nadomeščen z veliko manj plačanega dela - v času pandemije so ljudje delali v povprečju 19,5 % oz. Nega ostalih 0.83 0.85 -0.02 -2.88 1,3 ure manj kot pred pandemijo. Za prehranjevanje in pripravo posameznikov obrokov je bilo porabljenih 1,7 ure, za druga gospodinjska Druženje opravila pa v povprečju 5,5 ur. Čas, namenjen neplačanemu delu, 0.52 0.66 -0.15 -24.33** se je tako zvišal za skoraj 45 minut na dan. Rekreacija 0.93 0.94 -0.01 -0.75 Za ponazoritev razlik med spoloma v obdobju pred pandemijo je v tabeli 1 prikazan povprečni čas moških in žensk Prosti čas 1.43 1.29 0.14 10.16 ter absolutna in relativna razlika pred pandemijo za vsako Opomba: ***p < 0.001; **p < 0.01; *p < 0.05; †p ≤ .10 aktivnost posebej, medtem ko tabela 2 prikazuje enake kazalnike Absolutna razlika je opredeljena kot razlika med povprečnim časom, ki za obdobje med pandemijo. Pred pandemijo so moški na trgu so ga moški in ženske porabili za posamezno aktivnost pred pandemijo. dela delali v povprečju 1,5 ure več kot ženske, pri čemer je Relativna razlika pa kot absolutna razlika, relativno glede na povprečni čas, porabljen s strani celotnega (po spolu nerazčlenjenega) vzorca razlika med spoloma predstavljala 21,6 % povprečnega časa, ki pred pandemijo. 395 Vpliv pandemije covid-19 na razlike med spoloma v plačanem in neplačanem delu Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Med pandemijo (glej tabelo 2) so moški zopet porabili Druženje 0.65 0.84 -0.18 -24.49*** statistično značilno več časa za plačano delo, v povprečju eno uro in 24 minut oz. 25,9 % več kot ženske. Moški so porabili tudi več Rekreacija 1.05 1.07 -0.02 -1.82 časa za vzdrževanje doma in gradbena dela (približno 25 minut Prosti čas 1.69 1.44 0.25 15.96 več kot ženske). Po drugi strani so ženske porabile več časa za pripravo obrokov (približno 38 minut oz. 39,9 % več kot moški) Opomba: ***p < 0.001; **p < 0.01; *p < 0.05; †p ≤ .10 in za čiščenje, pranje in likanje (približno 27 minut oz. 39,5 % Absolutna razlika je opredeljena kot razlika med povprečnim časom, ki so ga moški in ženske porabili za posamezno aktivnost med pandemijo. več kot moški). Kot je razvidno tudi iz tabele 1 za obdobje pred Relativna razlika pa kot absolutna razlika, relativno glede na povprečni pandemijo, so ženske tudi v času pandemije v povprečju porabile čas, porabljen s strani celotnega (po spolu nerazčlenjenega) vzorca več časa za študij, druženje in nakupovanje kot moški. Iz tabele med pandemijo. 2 je razvidno tudi, da so se v času pandemije zmanjšale razlike med spoloma v času, porabljenem za nego otrok – ta razlika je 4 ZAKLJUČEK postala tudi statistično neznačilna. V času med pandemijo ostajajo statistično neznačilne razlike med spoloma v količini Spomladi 2020, ko je bila razglašena pandemija covid-19 tudi v časa, ki ga posamezniki porabijo za nego drugih (običajno ostalih Sloveniji in so vlade izvajale vrsto ukrepov za preprečevanje družinskih članov), pa tudi v količini spanja in času, porabljenem širjenja virusa, so bili posamezniki prisiljeni spremeniti način za rekreacijo in prosti čas. preživljanja časa. Spremembe v porabljenem času za različne aktivnosti so bile med moškimi in ženskami neenakomerno Tabla 2. Razlike med spoloma v porabljenem času med porazdeljene. V članku tako preučujemo vpliv pandemije covid- pandemijo 19 na čas, ki ga posamezniki v povprečnem delovnem dnevu porabijo za različne dejavnosti. Naši rezultati kažejo, da se je Porabljen čas (v urah) med pandemijo znatno povečala količina porabljenega časa za Relativna razlika spanje, kuhanje, čiščenje, vzdrževanje doma in skrb za druge. Absolutna (kot % porabljenega Poleg tega so posamezniki porabili več časa za študij in povečali razlika časa vseh Moški količino prostega časa. Ta dodatno porabljen čas je bil Ženske (M-Ž) posameznikov) nadomeščen z veliko manj dela - v povprečju so posamezniki Spanje 6.98 7.00 -0.03 -0.36 med pandemijo delali 20 % manj kot pred pandemijo. Ob osredotočenju na razlike med spoloma ugotavljamo, da so Priprava 1.34 1.97 -0.63 -37.91*** moški na trgu dela pred pandemijo običajno delali 1,5 ure več kot obrokov, ženske. Moški so porabili tudi znatno več časa za vzdrževanje hranjenje doma kot ženske. Na drugi strani so ženske porabile bistveno več Umivanje, 0.80 0.90 -0.10 -11.42** časa za kuhanje, čiščenje in druge gospodinjske dejavnosti. Med oblačenje pandemijo se je razlika med spoloma v plačanem delu relativno še povečala. Moški so začeli tudi več kuhati in še posebej čistiti, Plačano delo 6.11 4.71 1.40 25.86*** medtem ko so ženske začele porabljati več časa za vzdrževanje Čiščenje, 0.92 1.36 -0.45 -39.53*** doma. Moški so tudi v času pandemije več počivali, a so namenili pranje, likanje tudi znatno več časa skrbi za otroke kot pred pandemijo, kjer je razlika med spoloma med pandemijo postala statistično Vrtnarjenje, 0.96 0.99 -0.03 -3.26 neznačilna. nega hišnih ljubljenčkov Vzdrževanje, 0.82 0.41 0.41 65.78*** ZAHVALA gradnja doma Raziskava je bila sofinancirana s strani ARRS programa P5- 0128: Izzivi vključujočega in trajnostnega razvoja v prevladujoči Nakupovanje, 0.62 0.76 -0.14 -20.88** paradigmi ekonomskih in poslovnih znanosti. urejanje dokumentacije REFERENCE Študij 0.31 0.51 -0.20 -49.42** [1] Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D. Y., Chen, L., Wang, M. (2020): Presumed asymptomatic carrier transmission of COVID- Nega otrok 1.03 1.14 -0.11 -10.35 19. Jama, 323(14): 1406-1407. [2] Statistični urad Republike Slovenije (2019). Poraba časa, 2019. Nega ostalih 0.98 1.03 -0.05 -5.11 https://www.stat.si/StatWeb/File/DocSysFile/10306 [3] Wankmüller, C. (2020): European disaster management in response to the posameznikov COVID-19 pandemic. Mind & Society: 1-6. 396 Staranje prebivalstva in več vidikov zdravljenja z zdravili Population ageing and several aspects of pharmacological treatment Karin Kasesnik SPC NIJZ Ljubljana, Slovenija karin.kasesnik@nijz.si POVZETEK Staranje prebivalstva je proces, razviden v Sloveniji, pa tudi globalno. D. N. Weil [1] je že pred več kot dvema desetletjema V okviru naraščajoče porabe zdravil na recept je razvidna tudi analiziral trend staranja prebivalstva na svetovni ravni. Ta trend rast predpisovanja zdravil starejšim osebam. Obstajajo tveganja je zelo izrazit v razvitih državah, s pomembnim povečanjem pri polifarmakoterapiji, sočasnem predpisovanju več zdravil. deleža prebivalcev nad 65 let in sočasnim zmanjšanjem deleža Premagovanje ovir pri jemanju zdravil prispeva k izboljšanem prebivalcev, mlajših od 20 let. Čeprav je staranje prebivalstva sprejemanju zdravljenja in boljšim terapevtskim rezultatom. razmeroma počasen proces, se predvidevajo ekonomske Razpoznan je pomen ustreznega razumevanja pisnih virov o posledice staranja prebivalstva. zdravilih, ki vpliva na jemanje zdravil ter njihovo učinkovitost in varnost. Starejšim osebam je treba pomagati pri navodilih za jemanje zdravil in razumevanju informacij o zdravilih, posebej 2 RACIONALNO PREDPISOVANJE v pogojih pandemije. ZDRAVIL STAREJŠIM OSEBAM IN RAZLIKE V UČINKOVANJU ZDRAVIL KLJUČNE BESEDE V zahodnih državah se stroški za zdravstveno varstvo Zdravila na recept, zdravila brez recepta, starejše osebe, povečujejo. S staranjem prebivalstva povezujejo zmerno racionalno predpisovanje zdravil, razumevanje pisnih virov povečanje stroškov akutnega zdravljenja in znatno povečanje ABSTRACT stroškov zdravljenja kroničnih bolezni [2]. Pomemben dejavnik rasti stroškov za zdravstveno varstvo je medicinska tehnologija, Related to an increasing prescription medicine usage also an ki je močno povezana s starostjo in zdravjem. Razvoj increased usage of the medicines, prescribed to the elderly medicinske tehnologije omogoča, da tudi osebe s kroničnimi patients, has been observed. Risks at a polypharmacy, a boleznimi prebivajo doma, kar vodi v znatne prihranke v concomitant prescribing of medicines, have existed. dolgotrajni oskrbi. Osebe z boljšim zdravstvenim stanjem lahko Overcoming the barriers at taking medicines has contributed to tudi v starejših letih več prispevajo v delovnem okolju. Večji an improved treatment adherence and to better therapeutic obseg stroškov za varovanje zdravja starejših oseb lahko tudi results. The meaning of an appropriate written medicine bremeni medgeneracijsko solidarnost. sources’ comprehension has been recognized, with an effect on Iz poročila slovenske zdravstvene zavarovalnice ZZZS [3] je the medicine taking and their efficacy and safety. Elderly razvidno, da so v letu 2020 odhodki za zdravila in živila znašali persons should be assisted at the instructions for taking of 11,6 % vseh odhodkov ZZZS v tem letu. Glede na predhodne medicines and at a comprehension of the medicines’ leto so se odhodki ZZZS za zdravila povečali za 15,3 %. Število information, especially within the pandemic requirements. predpisanih receptov na prebivalca je bilo 8,35 v letu 2020. KEYWORDS Čeprav se je število receptov glede na leto 2019 zmanjšalo (za 1,4 %), se je poraba zdravil na posamezno osebo, ki je prejela Prescription medicines, over-the-counter medicines, elderly zdravilo, povečala za 7,9 %, oziroma za 2,9 % letno v zadnjih persons, rational prescribing of medicines, comprehension of petih letih. written sources V poročilu [3] omenjeni trend upočasnitve naraščanja predpisanih receptov na prebivalca ima ekonomski smisel. Bolj racionalno predpisovanje zdravil pa je obenem tudi terapevtsko 1 UVOD smiselno, če pacient pri tem prejme ustrezno terapijo. V Prispevek pregledno obravnava več vidikov varovanja zdravja, poročilu je navedena tudi zahtevana pozornost pri sočasnem s poudarkom na določenih ovirah pri zdravljenju z zdravili, v predpisovanju več zdravil hkrati (polifarmakoterapija). Posebej povezavi s staranjem prebivalstva. Že več let se na demografski pri starejših osebah se lahko, zaradi možnega medsebojnega konferenci, v okviru multikonference Informacijska družba, delovanja zdravil, pojavijo neželeni učinki. predstavljajo raziskovalni prispevki, ki poudarjajo pomemben Ugotovitve raziskovalcev so namenjene tudi podpori ukrepov vpliv demografskih sprememb ne le na področju zdravljenja, odločevalcev. Ti ukrepi bi morali voditi v izboljšano kakovost temveč tudi na sociološkem, antropološkem, ekonomskem in življenja starejših oseb, posebej tistih, ki prebivajo sami. drugih področjih. Pomembna je učinkovita odzivnost na demografske 397 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Karin Kasesnik spremembe, saj nekateri ukrepi učinkujejo šele po določenem Vodenje zdravljenja starejših oseb je večinoma zahtevno, zato času, na primer gradnja domov za starejše osebe, investicije v potrebujejo pomoč strokovnjakov s področja zdravja in svojcev, zdravstvu, spremembe na ekonomskem področju in drugi da zdravila dosežejo pričakovan učinek in so varna. ukrepi. 3.1 Medikamentozno zdravljenje starejših oseb v pogojih pandemije 3 JEMANJE ZDRAVIL PRI STAREJŠIH Zelo zahtevne razmere, tudi glede zdravljenja z zdravili, so v OSEBAH letu 2020 nastale med pandemijo, še posebej za starejše osebe. Že podatki iz leta 2008 kažejo povečanje povprečne vrednosti Dejavnosti v zdravstvenih ustanovah so bile osredotočene na receptov zdravil (brez dragih zdravil), ko se pomikamo od obvladovanje bolezni covid-19, zato je potrebna še večja skrb starostne skupine otrok do skupine starejših oseb. Posebej pri kroničnem zdravljenju starejših oseb z zdravili [9]. Še izrazito je to povečanje v starostnih skupinah nad 65 oziroma posebej veliko pozornost bi bilo treba posvetiti nad 85 let [4]. V Sloveniji se je v letu 2015 preko 178 tisoč medikamentoznemu lajšanju bolečine, zdravljenju duševnih oseb zdravilo z zdravili, ki vsebujejo pet do devet zdravilnih motenj, uravnavanju visokega krvnega pritiska in sladkorne učinkovin oziroma več kot 23 tisoč oseb z zdravili z vsebnostjo bolezni. Pomemben je nadzor pacientov, ki jemljejo štiri ali več deset ali več zdravilnih učinkovin. zdravil, zaradi možnih posledic kot so na primer padci. S Zdravila imajo številne pozitivne učinke pri zdravljenju in povečanjem števila zdravil se poveča tveganje neželenih zmanjševanju simptomov bolezni [5]. Koristi zdravljenja pa je učinkov. treba ovrednotiti glede na možna tveganja. Po ocenah delež Avtorica [9] predlaga več ukrepov za boljše organiziranje in bolnišničnih obravnav zaradi jemanja zdravil znaša med 2,4 % nadzorovanje zdravljenja starejših oseb z zdravili. Svetuje in 6,2 %. Veliko izmed teh neželenih učinkov bi bilo mogoče pripravo navodil zdravnika za pacientovo jemanje zdravil, ki ji preprečiti. Tveganje za neželene učinke je podvojeno, če je sledi priprava odmerkov zdravil na domu. Priporoča se, da se v pacient star 65 let, ali več, posebej če pacient sočasno jemlje lekarnah pripravijo posamezni odmerki zdravil za določenega več zdravil. Poročajo, da je celo 30 % bolnišničnih sprejemov pacienta; na ta način se poveča verjetnost ustreznega dnevnega pacientov starih 65 let ali več zaradi neželenih učinkov zdravil. odmerjanja predpisanih zdravil, ob sočasnem preverjanju s Starejše osebe pogosto sočasno jemljejo dve ali več zdravil [6]. strani družinskih članov. Klinični farmacevt pripomore pri Staranje je povezano z anatomskimi in fiziološkimi ugotavljanju morebitnih neskladnosti predpisanih zdravil in spremembami, ki vplivajo na delovanje zdravil. Te spremembe svetuje pacientom. Tudi v primeru sočasnega jemanja vključujejo razlike v absorbciji, metabolizmu in izločanju vitaminov oziroma prehranskih dopolnil se svetuje posvet s zdravilnih učinkovin. Pri starejših osebah so učinki zdravil farmacevtom, da se prepreči morebitna medsebojna lahko povečani ali zmanjšani zaradi sprememb v receptorjih za učinkovanja oziroma neželene učinke. zdravilne učinkovine. Spremembe v farmakokinetiki in farmakodinamiki se lahko odražajo v podaljšanem razpolovnem času, povečanem potencialu za toksičnost zdravil in v večji 4 PISNI VIRI INFORMACIJ O ZDRAVILIH verjetnosti za pojav neželenih učinkov. Zaradi tega je treba Kljub objavam strokovnih in znanstvenih člankov je področje razumeti anatomske in fiziološke spremembe v starejših letih, informacij o zdravju in zdravilih še premalo raziskano in se v preden se zdravila predpisujejo. praksi dobre prakse premalo udejanjajo. Zdravilom na recept in Ovire pri učinkovitem zdravljenju starejših predstavljajo tudi zdravilom brez recepta so priložena navodila za uporabo, v kognitivne motnje, slab vid, slabši finančni položaj [7]. katera so vključena bistvena navodila za odmerjanje in način Razpoznali so s starostjo povezana tveganja zaradi slabšega jemanja zdravil ter tudi informacije o možnih tveganjih, komuniciranja, polifarmakoterapije, medsebojnega delovanja povezanih z jemanjem zdravil. V zadnjih letih se v znatnem med zdravilnimi učinkovinami in sprememb v farmakokinetiki, obsegu uporabljajo prehranska dopolnila. Čeprav prehranska ki prispevajo k težavam pri zdravljenju in neustreznem dopolnila sodijo k živilom, je treba njihovo uživanje sprejemanju zdravil in lahko vplivajo na bolnišnične sprejeme. nadzorovati in paziti na morebitno medsebojno delovanje z K izboljšanem vodenju zdravljenja prispeva pregled in zdravilnimi učinkovinami, predvsem ko gre za ranljive skupine poenostavitev shem jemanja zdravil. V pomoč so strokovni oseb. timi, v katere so vključeni tudi farmacevti. Pomembno je Pomembno je razumevanje pisnih navodil, ki je bistven pogoj usklajevanje načinov medikamentoznega zdravljenja med za ustrezno jemanje in ravnanje z zdravili. Razumevanje različnimi specialisti. Pacienti, ki sočasno jemljejo pet ali več navodil za uporabo in promocijskih pisnih virov o zdravilih je zdravil, potrebujejo usmeritve glede jemanja in ravnanja z bolj zahtevno v primeru polifarmakoterapije. Izkušnje kažejo, zdravili. Varnost zdravljenja se poveča, če je zdravil manj in so da je razumevanje informacij o zdravilih izboljšano, če poleg obenem bolj učinkovita. razpoložljivih pisnih virov o zdravilih pacient za nasvet vpraša Kljub razpoznanim tveganjem polifarmakoterapije pri zdravnika, farmacevta oziroma drugega strokovnjaka, ki pozna starejših osebah, številni pacienti prejemajo zdravljenje, ki je farmakoterapijo. zanje lahko tvegano [8]. Določili so izrecna merila za določitev Z oziroma na velik delež starejših oseb, ki se zdravijo z enim zdravil, ki so primerna za kronično zdravljenje starejših oseb. ali več zdravili, bi morali izbrati primerne oblike njihovega Na osnovi znanstvenih spoznanj so določili zdravila, ki za izobraževanja in informiranja. Poleg objav člankov bi koristil zdravljenje starejših oseb niso primerna. način komuniciranja, ki je pristopen starejšim osebam. Kljub povečanemu trendu digitalnega iskanja informacij je treba 398 Staranje prebivalstva in več vidikov zdravljenja z zdravili Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia upoštevati, da veliko starejših oseb nima hitrega dostopa do predstavitev režima zdravljenja poveča razumljivost navodil in računalnika. Prijazen, hiter in preprostejši dostop do informacij olajša jemanje zdravil. Nasvet strokovnjaka podpira ustrezno je bolj učinkovit. jemanje zdravil, ob sočasnih, starejšim osebam prijaznih Medtem ko je v uradno odobrenih pisnih virih vsebina oblikah pridobivanja informacij o zdravilih in načinih strukturirana in nadzorovana, pa so promocijska gradiva komuniciranja z njimi. običajno bolj komercialno usmerjena. Na osnovi rezultatov Čeprav se v zdravstvenih sistemih velik pomen pripisuje raziskave [10] smo v slovenskih besedilih ugotovili, da apeli o nadzoru proračuna za zdravljenje, bi morala biti v ospredju prednostih zdravil brez recepta niso bili uravnoteženi z apeli o predvsem dobrobit ljudi. Posebna skrb bi morala biti namenjena tveganjih. Zaradi vpliva zaznavanja in razumevanja apelov je starejšim osebam, ki so ranljiva skupina prebivalcev. Starejše bistveno uravnoteženje apelov o prednostih in možnih osebe pogosto živijo same, ali pa njihovi svojci zaradi tveganjih, povezanih z uporabo zdravil brez recepta. Ker so zaposlenosti ne morejo v zadostni meri skrbeti zanje. Starejši pisni viri običajno glavni vir informacij o zdravilih brez recepta, ljudje so skrbeli za nas in nas učili v mladosti, poskušajmo je pomembna njihova vsebina, vključno z uravnoteženjem sedaj mi poskrbeti zanje, da bo starost kolikor je mogoče apelov. Ne le zdravila na recept, temveč tudi zdravila brez prijetna in dostojanstvena. Zaradi obremenitev zdravstvenih recepta se mora natančno odmerjati in pozornost nameniti tudi delavcev med pandemijo starejše osebe potrebujejo še več možnim medsebojnim delovanjem med zdravilnimi pozornosti in skrbi za zdravje. učinkovinami. Določanje berljivosti je prav tako pomemben dejavnik pri LITERATURA IN VIRI razumevanju besedil. Medtem ko se v določenih, razvitih [1] David N Weil, 1997. The Economics of Population Aging. V Mark. R. državah uporabljajo formule za določanje berljivosti, pa se v Rosenzweig in Oded Stark (Ur.), Handbook of Population and Family Economics., Ch. 17. Elsevier Science B.V. DOI: Sloveniji to področje še razvija. Ustrezne stopnje berljivosti https://www.researchgate. net/profile/David-Weil/publication/4912786_ vodijo v primerno razumljivost besedil o zdravju in zdravilih. The_economics_of_population_aging/links/5e1dc7a3a6fdcc28e9c4d746/ Raziskovalca sva ugotovila [11], da stopnje berljivosti izbranih The-economics-of-population-aging.pdf . [2] Claudine de Meijer, Bram Wouterse, Johan Polder in Marc besedil o zdravju in zdravilih ne dosegajo priporočene stopnje. Koopmanschap, 2013. The effect of population aging on health Pri zdravilih se pojavlja tudi vprašanje sprejemanja expenditure growth: a critical review. Eur J Ageing, 10 (maj, 2013), 353- 361. DOI: 10.1007/s10433-013-0280-x. zdravljenja s strani pacientov. Med navedbami o učinkovitosti [3] Letno poročilo ZZZS 2020, 2021. Zavod za zdravstveno zavarovanje in tveganjih zdravil je tudi z vidika sprejemanja zdravljenja Slovenije. DOI: http://api.zzzs.si/ZZZS/info/egradiva.nsf/ pomembno, katere navedbe v večji meri vplivajo na paciente, 0/a998991f0f548b4bc125868c0040ba61/$FILE/Letno%20poro%C4%8D ilo%20ZZZS%202020.pdf da se odločijo za izbor zdravila brez recepta, oziroma za [4] Jurij Fürst, 2017. Poraba zdravil z vidika racionalnega predpisovanja. jemanje zdravila na recept. V raziskavi [12] smo ugotovili, da Modul za specializante družinske medicine. DOI: https://www.mf.uni- lj.si/application/files/7315/3842/4712/MTP_fuerst.pdf. neželenim učinkom zdravil brez recepta osebe pripisujejo večjo [5] Katrin M. Cresswell, Bernard Fernando, Brian McKinstry in Aziz pomembnost kot učinkovitosti oziroma določenim drugim Sheikh, 2007. Adverse drug events in the elderly. British Medical lastnostnim, ki se povezujejo s koristmi zdravila. Osebe so kot Bulletin, 83 (junij 2007), 259-274. DOI: 10.1093/bmb/Idm016. [6] Darryl S. Chutka, Jonathan M. Evans, Kevin C. Fleming in Keith G. posebej tvegane opredelile resne neželene učinke. Zaključili Mikkelson, 1995. Drug Prescribing for Elderly Patients. Symposium on smo, da bi bilo v pisnih gradivih za paciente koristno opisati Geriatrics – Part I, vol. 70, 7 (julij 1995), 685-693. DOI: https://doi.org/10.4065/70.7.685. neželene učinke zdravil ter prikazati njihovo dejansko tveganje. [7] Eric G. Tangalos in Barbara J. Zarowitz, 2006. Medication management in the elderly. Annals of Long-Term Care, 14, 8 (avg 2006), 27-31. DOI: https://mayoclinic.pure.elsevier.com/en/publications/medication- 4.1 Pomoč starejšim osebam pri ustreznem management-in-the-elderly. razumevanju pisnih virov o zdravilih [8] Darryl S. Chutka, Paul Y. Takahashi in Robert W. Hoel, 2004. Inappropriate medications for elderly patients. Mayo Clin Proc, 79, 1 S posredovanjem informacij o zdravilih medicinske sestre (jan 2004), 122-139. DOI: 10.4065/79.1.122. pripomorejo k informiranju starejših pacientov o uporabi na [9] Cathy Lea, 2020. 5 tips for managing medications for aging patients during a pandemic. DOI: https://www.mayoclinichealthsystem.org/ recept predpisanih zdravil [13]. Prejem pisnih navodil za hometown-health/featured-topic/5-tips-for-managing-medications-for- jemanje zdravil je pomemben za starejše osebe s pogosto aging-parents-during-a-pandemic. [10] Karin Kasesnik, Mihael Kline, Todd Gammie in Zaheer Ud-din Babar, oslabljenim fizičnim stanjem. Težave pri jemanju zdravil lahko 2016. Analyzing medicines information of over-the-counter medicines nastanejo pri starejših osebah z nižjo stopnjo razumevanja leaflets in Slovenia. Akademija MM, vol. XIII, 26, 9-22. DOI: besedil o zdravju in zdravilih oziroma izobrazbe ter pri http://www.dlib.si/?URN=URN:NBN:SI:DOC-RL2UYP6Y. [11] Karin Kasesnik in Mihael Kline, 2011. Analyzing readability of zapletenih režimih odmerjanj zdravil za zdravljenje kroničnih medicines information material in Slovenia. Southern Med Review, bolezni. Svetuje se uporaba modelov za tvorbo ustreznih pisnih 4, 2 (dec 2011), 33-40. DOI: 10.5655/smr.v4i2.1005. [12] Karin Kasesnik, Mihael Kline in Jani Toroš, 2020. Analysis of informacij o zdravilih za starejše osebe. Medicines Attributes within Patient Infrormation Leaflets. V: Lidija Boljše razumevanje besedil pomeni večjo možnost za Weis (ur.), Viktor Koval (ur.), Katarina Askerc Veniger (ur.). Eastern European Conference of Management and Economics: ustrezno učinkovitost in varnost zdravljenja z zdravili. Environmental management and sustainable economic development: EECME 2020: proceedings of the 2nd international scientific conference: May 29, 2020, Ljubljana, Slovenia. Ljubljana: Ljubljana School of Business, 2020, 9-15. DOI: 5 ZAKLJUČEK https://www.vspv.si/uploads/visoka_sola/datoteke/zbornik_eecme_2020_- Staranje populacije in naraščajoč delež starejših oseb se __proceeding_of_conference.pdf [13] Karen Hayes, 2021. Designing Written Medication Instructions: povezuje tudi s spremembami v uporabi zdravil. Predpisovanje Effective Ways to Help Older Adults Self-Medicate. Home Journal of zdravil starejšim osebam pogosto zajema polifarmakoterapijo. Gerontological Nursing, 31, 5 (jan 2021). DOI: https://doi.org/10.3928 /0098-9134-20050501-04. Jemanje več zdravil hkrati lahko povzroči medsebojno učinkovanje med zdravili in možne neželene učinke. Pregledna 399 Prebivalstvena politika Kitajske po letu 1950: Od začetnih iskanj in socialistične vere v neomejeno rast prebivalstva do politike enega in zatem treh otrok na družino Population Policy of China Since 1950: From Early Socialist Ideas and Oscillations to the One-child Policy and Recent Two and Three Children Policy per Family Janez Malačič Ekonomska fakulteta Univerze v Ljubljani Ljubljana, Slovenija janez.malacic@ef.uni-lj.si POVZETEK 1 UVOD Avtor analizira razvoj prebivalstvene politike Kitajske v Prebivalstvo Kitajske je v obdobju po letu 1950 največje zadnjih nekaj več kot sedemdesetih letih. V tem obdobju je prebivalstvo sveta. Leta 1950 je štelo po kitajskih uradnih kitajska prebivalstvena politika doživela velike spremembe, podatkih 546,8 milijona ter imelo stopnjo natalitete 37,0 ‰, ki so bile povezane z gospodarskimi in družbenimi stopnjo smrtnosti 18,0 ‰ in stopnjo celotne rodnosti 5,81 spremembami in razvojem, različnimi fazami otroka na žensko (Calot, 1984). Na ta način je bilo v zgodnji demografskega prehoda in veliko modernizacijo družbe fazi demografskega prehoda, v kateri se je smrtnost že nasploh. Od začetne negotovosti in nihanj je politika prišla v zniževala, medtem ko se rodnost še ni začela zniževati. V osrednjo fazo, ki jo je zaznamovala politika enega otroka na zahodni demografski literaturi so avtorji kritično ocenjevali družino. (Pre)dolgo trajanje te faze bo gotovo otežilo uradne kitajske demografske podatke. Za obdobje 1953-1980 doseganje ciljev prebivalstvene politike Kitajske v te ocene ne kažejo večjih razlik pri celotnem prebivalstvu, naslednjih fazah, namreč politike dveh in zatem treh otrok na pri stopnji natalitete in še posebej pri stopnji smrtnosti pa so družino. Kako uspešna bo kitajska politika pri spodbujanju razlike precej večje. Stopnji natalitete in smrtnosti sta v tem rodnosti, bo pokazal šele čas. obdobju v kitajskih uradnih podatkih podcenjeni (Banister, 1984). Razlike so še posebej velike v obdobju politike KLJUČNE BESEDE velikega skoka naprej, ki je povzročila lakoto in veliko prebivalstvena politika, Kitajska, pospešeni demografski povečanje smrtnosti. prehod. Ne glede na razlike v omenjenih dveh virih podatkov pa nam ti podatki omogočajo okvirno slediti ABSTRACT poteku demografskega prehoda od visokih ravni rodnosti in smrtnosti na nizke ravni teh dveh demografskih procesov v China's population policy has changed tremendously since Kitajski. Pri tem je še posebej zanimivo pogledati, kdaj se je 1950. The changes have been caused by political, economic začela zniževati rodnost oziroma stopnja natalitete. Po obeh and social developments, demographic transition and virih podatkov lahko ugotovimo, da se je to zgodilo okrog modernization of the society. From early socialist ideas and leta 1970, ko je prebivalstvo Kitajske štelo že 820 milijonov. oscillations the population policy evolved in one-child per Do leta 1982, ko je število z 1,008 prvič preseglo milijardo, family policy. This central phase ended in 2015, probably too je stopnja natalitete padla na 21,1 ‰ in stopnja smrtnosti na late. Therefore, the goals of the last three children per family 7,9 ‰ (kitajski podatek je 6,6 ‰). Ob upoštevanju ocene, da policy will be harder to achieve. Generally, it remains to be je bilo na Kitajskem leta 1950 550 milijonov ljudi, je bila seen how effective will be pronatalist policy in China. povprečna letna stopnja rasti prebivalstva v obdobju 1950- 1982 1,89 %. Po tej stopnji rasti bi se modelsko prebivalstvo KEY WORDS podvojilo v 37 letih. Na osnovi ocen OZN o gibanju osnovnih kazalcev rodnosti in smrtnosti lahko sklenemo, da population policy, China, induced demographic transition. se je demografski prehod na Kitajskem končal v 1990-ih 400 letih. Stopnja natalitete se je znižala na 18,2 ‰ leta 1990 in S prvim petletnim planom (1953-57) se je odnos na 13,6 ‰ leta 2000. V teh dveh letih je bila stopnja celotne vlade začel spreminjati. Podatki popisa prebivalstva leta rodnosti zaporedoma 1,92 in 1,70 otroka na žensko. Število 1953 in potrebe planskega usklajevanja teh podatkov z prebivalstva pa je bilo leta 2000 1,270 milijarde (UN, 2007). ekonomskimi viri so vodili do sproščanja omejitev pri splavu Dodajmo še, da je leta 2021 objavljeni podatek popisa v letu in večje podpore načrtovanju družine. Leta 1956 so prvič 2020 1,410 milijarde, stopnja celotne rodnosti pa le 1,33. Po začeli kampanjo načrtovanja rojstev. Vodilni politiki so v teh podatkih je bila povprečna letna stopnja rasti prebivalstva letih 1954-57 večkrat javno podprli načrtovanje rojstev. Leta Kitajske v obdobju 1950-2020 1,35 %. 1957 je tudi Mao odredil, da je treba načrtovanje družine spodbujati, sprejeti desetletni program načrtovanja družine in Kitajski demografski prehod je bil izjemno hiter, saj je trajal izpolniti njegove cilje (Zheng, Jian idr., 1981). le okrog 40-50 let. Po trajanju se zelo razlikuje od demografskih prehodov v razvitem delu sveta, kjer so ti Vendar je bilo vse to kratkega daha. Že leta 1958 trajali 150 do 200 let. Vendar se razlikuje tudi od prehodov je Mao vpeljal novi ekonomski program znan kot Veliki skok v ostalih nerazvitih državah sveta, kjer je praviloma smrtnost naprej. Načrtovanje družine je bilo izenačeno z prav tako hitro padla, rodnost pa se je prilagajala znižani maltuzijanizmom. Prevladal je slogan »več ljudi je boljše«. smrtnosti največkrat veliko počasneje. Tako hiter Prebivalstvena vprašanja in teorije so postala tabu. Ironično demografski prehod, še posebej pri rodnosti, je Kitajska pa je, da je ravno v teh letih rodnost padla, rast prebivalstva dosegla s pomočjo prebivalstvene politike in doslednega pa se je zmanjšala. V letih 1959-62 se je prebivalstvo celo izvajanja te politike s strani vladajoče politike, države in zmanjšalo. Razlog je bil v hudi lakoti in v drugih ekonomskih celotne družbe. težavah, ki jih je povzročila politika Velikega skoka. Že leta 1962 pa je sledila druga kampanja načrtovanja rojstev. Vlada V tem besedilu bomo analizirali razvoj kitajske je ustanovila urad za načrtovanje rojstev, uvedla cilje rasti prebivalstvene politike v obdobju 1950 – 2021. To obdobje prebivalstva, sprejela milejše zakone o splavu in sterilizaciji, bomo razdelili na tri dele v skladu z osnovnimi značilnostmi spodbujala uporabo kontracepcije in poznejše poročanje. kitajske prebivalstvene politike. Prvo obdobje je 1950-1980, Politični voditelji so ponovno razglašali, da je načrtovanje ko oblast niha med začetnimi iskanji in potrebo po družine napredno in po svoji naravi komunistično. Kljub intervenciji na eni strani in socialistično vero v neomejeno vsemu pa je tudi ta preobrat podrla kulturna revolucija v letu rast prebivalstva na drugi strani. Drugo je obdobje politike 1966. Načrtovanje družine je bilo ponovno ukinjeno, enega otroka na družino 1980-2015. Tretje obdobje od leta proizvodnja in prodaja kontracepcijskih sredstev sta bili 2016 naprej pa je obdobje politike dveh in zatem treh otrok opuščeni, pa tudi administrativne kontrole pri starosti na družino. poročanja ni bilo več. Sledila je hitra rast prebivalstva, pomanjkanje stanovanj in zaposlitev, nazadovanje izobraževalnih in kulturnih standardov ter celo pojav novih nepismenih. 2 ZGODNJE FAZE DEMOGRAFSKEGA PREHODA TER NIHANJE MED POTREBO Kulturni revoluciji je sledila vzpostavitev reda v letu 1971 in z njim tretja kampanja načrtovanja rojstev. PO INTERVENCIJI IN STIHIJNIM Slednje je končno dobilo polno veljavo, njegovi cilji pa so RAZVOJEM: 1950 – 1980 bili razglašeni kot »pozno, redko in malo«. Leta 1973 so prvič vgradili prebivalstvene cilje v petletni gospodarski Prvo obdobje prebivalstvene politike socialistične Kitajske, plan, naslednje leto pa je predsednik Mao ponovno poudaril, ki je nastala s prevzemom oblasti s strani komunistične da je potrebno rast prebivalstva kontrolirati. Po smrti partije v letu 1949, so zaznamovala velika nihanja v teoriji in predsednika leta 1976 in obračunu z levičarji (»tolpa štirih«) praksi med različnimi skrajnostmi ( Zheng, Jian idr., 1981). so novi voditelji razglasili politiko štirih modernizacij Letom podpore in kampanj načrtovanja družine so sledila (kmetijstvo, industrija, obramba in znanost) in javno leta popolnega zavračanja. Predsednik Mao je že leta 1949 poudarili, da je njihov uspeh odvisen od dosega ničelne rasti zanikal obstoj kakršnihkoli resnih prebivalstvenih prebivalstva v bližnji prihodnosti. problemov na Kitajskem in zavrnil »absurdno« Malthusovo teorijo, ki so jo zavrgli marksisti in socialistična praksa v To prvo zelo razburkano obdobje v razvoju Sovjetski zvezi in na Kitajskem (Population Reports, 1982). Kitajske in njene prebivalstvene politike je sklenila Vlada je v prvih letih deloma podpirala rojstva, prepovedala sprememba ustave leta 1978. V ustavo so zapisali, da država sterilizacijo in splav, dajala podporo vladnim uslužbencem zagovarja in spodbuja načrtovanje družine. Tudi v pravno za rojstvo otroka ter v propagandi povezovala veliko otrok z formalni obliki je načrtovanje družine postalo osnovna novim družbenim sistemom. dolžnost državljanov. 401 3 POLITIKA ENEGA OTROKA NA Z uvedbo politike enega otroka na družino se je DRUŽINO: 1980 – 2015 neposredni administrativni pritisk na posamezno kitajsko družino s strani kadrov načrtovanja družine in drugih Zelo radikalno in za marsikoga problematično politiko enega uradnikov, ki je bil prisoten že v 1970ih letih, še znatno otroka na družino so na Kitajskem uvedli leta 1980 s četrto okrepil. Tudi sami kadri so namreč pod močnim pritiskom kampanjo načrtovanja rojstev. uresničevanja konkretnih ciljev, ki so podrobno razčlenjeni Tega leta je državni svet objavil poziv ljudem naj imajo samo enega otroka na na regionalnih, mestnih in drugih lokalnih ravneh. Pritisk se družino, septembra istega leta pa je CK KP naslovil odprto širi od pogostega obiskovanja uradnikov, strogega pismo vsem članom partije z zahtevo, da prevzamejo vodilno izobraževanja in prepričevanja pa vse do odkritega nasilja. vlogo pri uresničevanju tega cilja. Preveč vneti lokalni politiki in aktiv Hkrati je voditelj partije in isti so posegali tudi po države Hua Guofeng razglasil cilj, da bo Kitajska omejila prisili pri sterilizaciji in vstavljanju materničnih vložkov, pa število prebivalstva na maksimalno 1,2 milijarde do leta tudi po umetnem prekinjanju nedovoljenih nosečnosti, 2000. Država je uvedla politiko ideološkega izobraževanja, pogosto tudi v poznih fazah le teh. O tej plati prebivalstvene politike na Kitajskem večinoma molčijo. Ne glede na to pa ki jo je kombinirala z ekonomskimi in administrativnimi je možno skleniti, da veliko ljudi ukrepi. Leta 1980 je država sprejela zakon o porokah, ki je na Kitajskem prostovoljno dvignil minimalno starost za ženske na 20 in za moške na 22 izvaja predpisano politiko, hkrati pa je tudi veliko dokazov, da tako velikega in hitrega znižanja rodnosti ne bi bilo brez let. Za uspešnost prebivalstvene politike pa je bilo še bolj pomembno delno sproščanje kolektivizacije v kmetijstvu, ki odločne administrativne podpore in moči vladajoče partije in države. je spremenila sistem spodbud in s tem povečala ekonomske razlike med ljudmi ter hkrati okrepila ekonomsko vrednost otrok. S tem pa je pomenila novo težavo za prebivalstveno Do začetka 21. stoletja je politika enega otroka na družino temeljila bolj na političnih kot pravnih osnovah in politiko. sredstvih ter bolj na predpisih in uredbah lokalnih oblasti, ki Nova politika je bila sprejeta na vrhuncu so bile najbolj odgovorne za izvajanje te politike. Sama politika se v tem obdobju ni bistveno spreminjala, čeprav demografskega prehoda, ko je prebivalstvo zelo hitro so naraščalo in se oblasti trudile odpravljati večje zlorabe in korupcijo. s tem grozilo, da bo onemogočilo razvoj države in štiri modernizacije. Popis prebivalstva leta 1982 je Razvoj je bil v tem času v skladu s širšimi spremembami v kitajski družbi in je šel v smeri od političnih improvizacij pokazal, da je imela Kitajska takrat le 19,5 % urbanega Maove dobe proti večjemu pomenu prava in zakonov. Vse to prebivalstva, visoko gostoto v najbolj naseljenih predelih ter izrazito neenakomerno regionalno porazdelitev. Navedimo je vodilo do tega, da sta CK KP in Državni svet Kitajske leta še, da je tega leta 6,67% prebivalstva pripadalo narodnostnim 2000 sprejela odločitev o okrepitvi politike prebivalstva, manjšinam, za katere striktna politika enega otroka na načrtovanja družine in ustalitve nizke rodnosti. KP je jasno družino ni veljala, vendar je bilo tudi za njih obvezno zapisala, da podpira vse osnovne značilnosti dotedanje načrtovanje rojstev in v praksi omejitev na dva otroka na politike. S tem je izrazila podporo stabilnosti politike, hkrati pa je predvidela spremembe v prihodnje, ki bi se naj nanašale družino. predvsem na izboljšanje kvalitete prebivalstva in na večji V zelo strnjeni obliki lahko za politiko enega pomen ekonomskih in drugih spodbud. Kvaliteto so otroka na družino zapišemo, da se je do neke mere pojmovali izrazito zdravstveno, predvsem bi se naj izboljšalo razlikovala med mestnimi in vaškimi območji. V mestih je zdravje otrok in žena. Na osnovi te odločitve je bil konec leta bilo manj izjem, politika pa je bila bolj stroga. S prevzemom 2001 končno sprejet Zakon o prebivalstvu in načrtovanju obveze, da bodo imeli le enega otroka, so si pari zagotovili rojstev, s katerim se je tako dolgo odlašalo (PCR Law on materialno nagrado, podaljšan porodniški dopust, prednost Population, 2002). Ta zakon je po eni strani konkretiziral pri zaposlitvi, dodelitvi stanovanja, zdravstveni oskrbi, politično odločitev partije in države, po drugi strani pa je sprejemu otroka v jasli, vrtec in šolo, pa tudi pravico do postavil pravne temelje v obliki splošnih načel, vloge dodatka k pokojnini. V vaseh so takšni pari dobili enkratno planskih aktov, mikro regulacije reprodukcije, ukrepov in denarno nagrado, gradbeno parcelo, zagotovilo vaške aktivnosti na področju spodbud in zdravstvenih storitev, pa skupnosti, da bo ta poskrbela zanje v starosti ipd. Zlasti na vse do legalne odgovornosti (Winkler, 2002). Zakon se je vasi se je že v 1980ih letih pokazalo, da je uvajanje tržnih začel izvajati 1. 9. 2002. Zakon je v osnovi zakoličil politiko elementov gospodarjenja ponovno začelo spodbujati višjo enega otroka na družino za naslednjih 15 let, hkrati pa je rodnost. Zaradi tega so povečali število primerov, ko so namenoma izpustil nekatere probleme, npr. velikega števila ljudem dovolili rojstvo drugega otroka. Rojstvo treh in več nelegalnih rojstev in s tem Kitajcev, ki nimajo pravnega otrok na družino pa je bilo strogo prepovedano (Malačič, statusa in pretiranega porušenja spolnega ravnovesja v času 2006). trajanja politike, pri drugih pa je pustil precej nejasnosti, ki 402 na lokalni ravni omogočajo še naprej trdo uveljavljanje družino vse do leta 2016 (Xiaoyu, 2021). Od tega leta naprej planskih ciljev. so se lahko vsi pari, ki so to želeli, odločili za rojstvo dveh otrok. Sprememba politike je bila sprejeta, ko je stopnja Tukaj ne moremo podrobneje obravnavati izjem in celotne rodnosti v državi bila 1,5 otroka na žensko, moderno vseh fines politike enega otroka, ki so postajale številčnejše kontracepcijo je uporabljalo okrog 85 % parov v rodni dobi, v kasnejših letih njene veljave, ko je bilo vse več ljudem 51 % ljudi je živelo v mestih, rodilo se je 116 dečkov na 100 dovoljeno, da so imeli še drugega otroka. Povejmo pa, da je deklic, povprečna letna stopnja rasti prebivalstva je bila 0,43 bilo z leti tudi vse več konkretnih predlogov, kako preiti %, deleža 0-14 let in 65+ let starosti sta bila zaporedoma 18 najprej na dva otroka na družino in kasneje na popolno in 10 %, življenjsko pričakovanje ob rojstvu za moške in sprostitev (Yi, 2007). Ob dejstvu, da je Kitajska dosegla ženske je bilo zaporedoma 75 in 78 let, prebivalstvo pa je leta raven rodnosti, ki ni več zagotavljala enostavnega 2015 znašalo 1396,7 milijonov (Asian Data Sheet, 2018). obnavljanja prebivalstva že v 1990ih letih, je težko razumeti, Dodajmo še, da je bruto nacionalni dohodek na prebivalca po zakaj je kitajsko vodstvo (pre)dolgo vztrajalo pri tej politiki. kupni moči znašal leta 2014 13.130 ameriških dolarjev Vmes se je Kitajska hitro razvijala in modernizirala, (Pison, 2015). demografski prehod se je že zdavnaj končal, prebivalstvo se je začelo (pre)hitro starati, politike enega otroka na družino Podobno kot so projekcije v poznih 1970ih letih pa niso opustili vse do leta 2015. Odgovor verjetno leži v napovedovale zelo hitro rast prebivalstva, novejše projekcije želji po stabilnosti in strahu pred prehitrim sproščanjem in prebivalstva Kitajske vsaj v zadnjih tridesetih letih vrnitvijo starega. napovedujejo zelo hitro staranje prebivalstva. Ker je osnovni vzrok staranja prebivalstva prenizka rodnost, je razumljivo, Na koncu te točke povejmo, da je z današnjega da je politika enega otroka na družino staranje prebivalstva vidika težko razumeti, zakaj se je kitajsko politično in še posebej pospešila. To pa pomeni, da se bo Kitajska soočala državno vodstvo na prehodu iz 1970ih v 1980ta leta odločilo z veliko starega in postopnim zmanjševanjem aktivnega za tako skrajno obliko prebivalstvene politike. Podrobnejša prebivalstva. Prvo skrbi politike zaradi tega, ker nimajo analiza pa pokaže, da so osnovne predpostavke in vzdržnega modernega pokojninskega sistema, drugo pa konstrukcijo »prebivalstvene krize« na Kitajskem povzeli po zaradi morebitnega pomanjkanja delovne sile in znižanja zahodni znanosti in delovanju povezav, kot je npr. Rimski konkurenčnosti gospodarstva. klub, ki so v tistem času glasno opozarjale na to, da bo prehitra rast prebivalstva ogrozila gospodarski razvoj Kar smo navedli v prejšnjem odstavku je skupaj z (Greenhalgh, 2003). Kitajsko prebivalstvo je sredi geopolitičnimi in obrambnimi razmisleki vodilo do tega, da demografskega prehoda izredno hitro naraščalo. Projekcije je KP Kitajske 31. maja 2021 sprejela odločitev, da bo na osnovi take hitre rasti pa so kazale skrb zbujajoče visoke kratkoživo politiko dveh otrok na družino zamenjala s številke. V začetku 1980ih se je prebivalstvo podvojilo v 33 politiko treh otrok na družino (Xiaoyu, 2021). Osnovna letih, ko je leta 1982 po popisu preseglo milijardo. Ob taki logika te politike je enaka kot pri ostalih dveh politikah. Ta rasti bi okrog leta 2010 štelo že dve milijardi in to bi po je, da imajo pari lahko sedaj do tri otroke, ne pa tudi več. mnenju kitajskih voditeljev ne le ogrozilo štiri modernizacije Očitno se predlogi nekaterih strokovnjakov, da bi sprostili ampak razvoj gospodarstva in družbe nasploh. Po drugi omejitve in uvedli svobodno odločanje o rojstvih vsaj do tega strani pa kitajske politike enega otroka na družino ni mogoče leta še niso uresničili. povsem reducirati na politiko načrtovanja rojstev oziroma družine. Politika enega otroka in širša prebivalstvena politika Tako o politiki dveh kot o politiki treh otrok je še se vključujeta v petletne gospodarske plane in sta del težko obširneje pisati, ker sta še čisto sveži. Strokovnjaki in državnega vodenja in masovnega izvajanja, ki je bolj ali manj verjetno tudi politiki se zavedajo, da bodo morali ljudi (ne)prostovoljno. Hkrati pa se Kitajska tudi trudi, da bi bila spodbujati, da se bodo odločali za dva ali tri otroke, morali vse bolj del širše politike države blaginje ob tem, da je že bodo poskrbeti za jasli in vrtce, za otroške dodatke in druge sicer del državne socialne in ekonomske politike. ukrepe, ki bodo znižali stroške družin z otroki. Zelo pomembno pa bo, kako se bo Kitajska spopadla s povsem 4 POLITIKA DVEH IN ZATEM TREH nasprotnim ciljem, kot je bil pri politiki enega otroka, ko je OTROK NA DRUŽINO: 2016+ šlo za zniževanje rodnosti, ki že po naravi pojava poteka hkrati z gospodarskim razvojem. Pri povečevanju rodnosti pa Kitajsko politiko in strokovnjake je že dolgo časa skrbelo, bo treba omenjeni naravni potek preobrniti navzgor. Današnje razvite države pri tem niso bile posebej uspešne, pa kako izpeljati »rahel pristanek« zelo stroge in (pre)dolgo trajajoče politike enega otroka na družino. Postopno tudi ljudje so ukrepe za spodbujanje rodnosti preveč hitro sproščanje omejitev je bilo prisotno dalj časa, vendar so vzeli za samoumevne in jih niso več povezovali s politiki odlašali s prehodom na politiko dveh otrok na pronatalitetnimi cilji. Kitajska lahko doda že znanim politikam in ukrepom v razvitih državah partijsko disciplino 403 in državni pritisk, ki pa verjetno ne bosta bistveno dvignila LITERATURA IN VIRI stopenj rodnosti. 1. Asian Demographic and Human Capital Data Sheet 2018 (2018) 5 SKLEP ADRI, and IIASA, Shanghai, China and Laxenburg, Austria. 2. Banister, J. (1984) An Analysis of Recent Data on the Population of China, Population and Development Review, No. 2, The Kitajska politika prebivalstva je prehodila v preteklih malo Population Council, New York. več kot 70 letih vladavine komunistične partije dolgo pot. V 3. Calot, G. (1984) Donnees nouvelles sur evolution demographique prvih 30 letih je nihala med skrajnostmi popolne stihije in chinoise. Population, 4-5/1984, INED, Paris. 4. Greenhalgh, S. (2003) Science, Modernity, and the Making of socialistične vere v svetlo prihodnost na eni in zavedanjem, China's One-Child Policy. Population and Development Review, da je družbi potrebna modernizacija in načrtovanje družine No. 2, The Population Council, New York. na drugi strani. Na vrhuncu demografskega prehoda, ko so 5. Malačič, J. (2006) Demografija. Teorija, analiza, metode in matematični modeli projekcij prebivalstva kazali možnost modeli. 6. Izdaja, Ekonomska fakulteta, Ljubljana. 6. Pison, G. (2015) The Population of the World (2015). Population povečanja prebivalstva na 2 milijardi v dobrih 30 letih, so se and Societies, No. 525, INED, Paris. politični voditelji odločili za strogo politiko enega otroka na 7. Population and Birth Planning in the PR China (1982) Population družino. V naslednjih 35 letih je bila politika zelo skopa pri Reports, Ser. J, No. 25, The Johns Hopkins University, Baltimore. dovoljevanju izjem, predvsem pa je politika enega otroka na 8. PRC Law on Population and Birth Planning (2002) Population družino trajala precej dalj, kot bi bilo potrebno. To je and Development Review, No. 3, The Population Council, New privedlo do tega, da sta si sledili politiki dveh in od leta 2021 York. 9. United Nations (2007) World Population Prospects, New York. naprej treh otrok zelo hitro, hkrati pa bo pri slednjih dveh in 10. Zheng, L., Jian, S. idr. (1981) China,s Population:Problems and še posebej zadnji veliko težje uresničevati cilje, kot če bi Prospects. New World Press, Beijing. politiko enega otroka opustili vsaj 10 let prej. 11. Winkler, E. A. (2002) Chinese Reproductive Policy at the Turn of the Millennium: Dynamic Stability. Population and Development Review, No. 3, The Population Council, New York. Kitajska je s prikazano politiko uspela pospešiti 12. Xiaou, W. (2021) Nation,s new 3-child policy seen as timely. zniževanje rodnosti in skrajšati demografski prehod, kar China Daily, June 4-10. nekaterim drugim nerazvitim državam, npr. Indiji, ni uspelo. 13. Yi, Z. (2007) Options for Fertility Policy Transition in China. Uspela je tudi omejiti najvišje število prebivalstva, ki ne bo Population and Development Review, No. 2, The Population bistveno preseglo 1,4 milijarde. Za vse to so država in še bolj Council, New York. posamezniki in njihove družine plačali precej visoko ceno. Mnenja o tem, ali je bilo to treba, se bodo verjetno zmeraj razlikovala. Šele prihodnja leta pa bodo pokazala, ali bo Kitajski uspelo tudi dvigniti rodnost in zagotoviti nemoteno obnavljanje prebivalstva z rodnostjo okoli 2,1 otroka na žensko. Razvite države pri tem še niso bile uspešne. 404 Precenjenost presežne umrljivosti za Slovenijo v letu 2020 Overestimated excess mortality for Slovenia in 2020 Jože Sambt† Tanja Istenič Daša Farčnik Andrej Viršček Ekonomska fakulteta, Ekonomska fakulteta, Ekonomska fakulteta, Statistični urad RS, Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija andrej.virscek@gov.si joze.sambt@ef.uni-lj.si tanja.istenic@ef.uni-lj.si dasa.farcnik@ef.uni-lj.si POVZETEK 1 UVOD Eurostat ter zgledujoč po njem Statistični urad RS in V letu 2020 je virus covid-19 močno spremenil številni drugi izračunavajo presežno umrljivost kot življenje po vsem svetu. Drastični ukrepi v zvezi z razliko med dejanskim številom umrlih in povprečnim omejevanjem širjenja okužb so izhajali iz visoke številom umrlih v obdobju 2015-2019. Pri tem ne umrljivosti, ki jo je povzročal ta virus. Eurostat, upoštevajo 1) spreminjanja števila in starostne strukture Statistični urad Republike Slovenije (v nadaljevanju prebivalstva ter 2) trenda zniževanja umrljivosti v času. »SURS«) in številni drugi so začeli izračunavati V članku upoštevamo ta dva dejavnika in ocenimo, da »presežno umrljivost« kot število umrlih v je v Sloveniji v letu 2020 presežna umrljivost znašala posameznem letu oziroma mesecu minus povprečno 14,9 %, medtem ko pristop od Eurostata oz. število umrlih v preteklem 5-letnem obdobju Statističnega urada RS daje oceno 18,8 %. (2015-2019). Eurostat sicer namesto 5-letnega obdobja v praksi uporablja 4-letno obdobje (2016-2019), saj za KLJUČNE BESEDE 2015 podatki niso na voljo za vse države, želeli pa so zagotoviti enotnost in s tem primerljivost med Presežna umrljivost, umrljivost, covid-19, staranje državami. Prednost tako opredeljenega kazalnika je, da prebivalstva, Slovenija je zelo preprost in nezahteven glede podatkov, potrebnih za njegov izračun. Potrebujemo zgolj ABSTRACT podatek o številu umrlih, ki ga tako nacionalni statistični uradi kot Eurostat redno objavljajo. Presežna Eurostat, and following their example also Statistical umrljivost je nov kazalnik, ki se je uvedel iz potrebe Office of the Republic of Slovenia and many others spremljanja umrljivosti in učinkov ukrepov v izrednih calculate excess mortality as the difference between the razmerah virusa covid-19. Za večjo ažurnost se ta actual number of deaths and the average number of kazalnik sedaj izračunava tudi na mesečni ravni. deaths between 2015 and 2019. This way they ignore 1) changing number and the age structure of the population Metodološko gledano pa tak poenostavljen pristop and 2) trend of declining mortality over time. In the ne upošteva dveh procesov, ki vplivata na število article we consider these two factors, and we estimate umrlih. Prvič, število umrlih je odvisno tudi od števila the excess mortality for Slovenia for 2020 to be 14,9 %. in starostne strukture prebivalstva, ki se v času In contrast, the approach used by Eurostat and Statistical spreminjata. Število prebivalstva Slovenije se zaradi Office of the Republic of Slovenia estimates the excess visokega neto priseljevanja v zadnjih letih povečuje, mortality to 18,8 %. hkrati pa se hitro stara. Posledično bi se število umrlih povečevalo tudi, če ne bi bilo virusa covid-19. Drugič, umrljivost po posameznih starostnih razredih se v času KEYWORDS znižuje, saj živimo vedno dlje in zato bi se ob Excess mortality, mortality, covid-19, population nespremenjeni zakonitostih umiranja ter ageing, Slovenia. nespremenjenem številu in starostni strukturi prebivalstva število umrlih v času zniževalo. 405 V tem članku bomo ocenili, koliko sta ta dva starostno specifične stopnje umrljivosti po spolu in dejavnika neto vplivala na število umrlih v Sloveniji v starosti za posamezna leta od 2015 do 2019 na sledeči letu 2020. Če bi se ta dejavnika, ki vplivata na število način: umrlih v nasprotni smeri, medsebojno ravno izničila glede na povprečno število umrlih v obdobju 𝑀𝑥 2015-2019, bi dobili povsem enake rezultate o presežni 𝑚𝑥 = (1) 𝑉𝑥 umrljivosti kot s pristopom Eurostata oz. SURS. Če temu ne bo tako, pa bodo naše ocene o presežni pri čemer x označuje starost, M število umrlih, V pa umrljivosti ustrezno višje oziroma nižje. število prebivalcev (včasih se uporablja tudi oznaka P, vendar je črka P v demografiji praviloma uporabljena za 2 METODOLOGIJA IN PODATKI označevanje celotnega števila prebivalstva, medtem ko Preden predstavimo svoje izračune, prikazujemo v se pri razčlenjevanju prebivalstva po posameznih Sliki 1 gibanje števila umrlih v zadnjih treh desetletjih, dimenzijah uporablja črka V). to je od leta 1990 do 2019, torej pred virusom covid-19. Za tako dobljene starostno specifične stopnje V tem obdobju je bil do leta 2006 trend gibanja števila umrljivosti mx nato izračunamo trendne vrednosti za leto smrti negativen, saj se nam je v Sloveniji pričakovano 2020. Pri tem izhajamo iz obdobja 2015-2019 in trajanje življenja hitro podaljševalo in je več kot uporabimo linearni trend z metodo najmanjših kompenziralo naraščanje števila prebivalcev v višji kvadratov. Dejanskih starostno specifičnih stopenj starosti, kjer je umrljivost visoka. Nato pa je naraščanje umrljivosti za leto 2020 namreč ne moremo uporabiti, števila starejših prebivalcev prevladalo in kot kažejo saj so visoke zaradi virusa covid-19, medtem ko mi projekcije prebivalstva, se bo ta trend še posebej želimo ugotoviti, kolikšno bi bilo število umrlih v letu intenzivno nadaljeval v prihodnjem desetletju [1]. V 2020, če virusa covid-19 ne bi bilo. Sliki 1 torej lahko vidimo, da smo že več kot desetletje Hkrati želimo upoštevati število in starostno priča očitnemu trendu naraščanja števila umrlih. porazdelitev prebivalcev v letu 2020. Tu se lahko odločamo med (Eurostatovimi) projekcijami števila prebivalcev za leto 2020 in dejanskim številom 21000 prebivalcev Slovenije sredi leta 2020. Odločili smo se 20500 za drugo možnost, saj so podatki o številu prebivalcev 20000 sredi leta 2020 medtem že na voljo [2], hkrati pa je bila rlihm v prvi polovici leta 2020 umrljivost zaradi virusa u 19500 covid-19 nizka in je zato vpliv na število prebivalcev vilo 19000 Šte sredi leta 2020 zanemarljiv – do 30. 6. 2020 je za virusom covid-19 umrlo skupaj 111 oseb [4]. Tako za 18500 število umrlih kot za število prebivalcev uporabljamo 18000 podatke po enoletnih starostnih razredih od starosti 0 let 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 pa do starosti 100+. Leto V naslednjem koraku apliciramo trendne vrednosti Slika 1: Gibanje števila umrlih v Sloveniji v obdobju starostno specifičnih stopenj umrljivosti (po starosti in 1990-2019 (vir: Statistični urad RS [1]) spolu) na dejansko število prebivalcev po starosti in V letih 2015 do 2019 je v Sloveniji zaporedoma spolu sredi leta 2020: umrlo 19.834, 19.689, 20.509, 20.485 in 20.588 oseb. Povprečje za obdobje 2015-2019 tako znaša 20.221 𝑀 100+ 𝑙𝑡2020 1.7.2020 2020′ = ∑ 𝑚 𝑥=0 𝑥 ∗ 𝑉𝑥 (2) umrlih in na osnovi te vrednosti Eurostat, SURS in številni drugi izračunavajo presežno umrljivost. Vendar pa bo ob naraščajočem trendu števila umrlih izračunana kjer 𝑀2020′ označuje ocenjeno število umrlih v letu presežna umrljivost precenjena, če jo bomo definirali 2020, če ne bi bilo virusa covid-19, x označuje enoletne 𝑙𝑡2020 kot razliko med dejanskim številom umrlih in starostne razrede od 0 do 100+ let, 𝑚𝑥 označuje povprečnim številom umrlih v preteklih petih letih. trendne starostno specifične stopnje umljivosti za 2020 z uporabo linearnega trenda (upoštevaje metodo Pri svojih izračunih uporabljamo podatke o številu najmanjših kvadratov), 𝑉1.7.2020 pa označuje število umrlih [2] in številu prebivalcev na dan 1. 7. (torej sredi 𝑥 prebivalcev sredi leta 2020 po enoletnih starostnih leta) [3] v letih 2015 do 2020. Najprej izračunamo 406 razredih. Ta izračun naredimo ločeno za moške in precejšnjim zamikom. S 5-letnim povprečjem se tudi ženske in nato rezultata seštejemo v skupno število ublaži vpliv slučajnega nihanja števila umrlih, ki je še umrlih v letu 2020. posebej aktualno v majhnih prebivalstvih. Rezultat torej pokaže, koliko prebivalcev Slovenije V tem članku opozarjamo, da ta pristop na eni strani ne bi umrlo v letu 2020, če bi se nadaljeval trend upadanja upošteva spreminjanja števila in starostne strukture umrljivosti v posameznih starostnih razredih iz obdobja prebivalstva (kar v proučevanem obdobju v Sloveniji 2015-2019, kar pomeni brez učinka virusa covid-19 na prispeva k naraščanju števila umrlih), na drugi strani pa umrljivost v posamezni starosti, hkrati pa upoštevaje ne upošteva trenda zniževanja umrljivosti v času, dejansko število in starostno porazdelitev prebivalstva v zaradi česar število umrlih v času upada. Na število letu 2020. umrlih delujeta torej v nasprotni smeri in empirično vprašanje je, kateri bo prevladal. Gibanje števila umrlih v Slovenji v zadnjem desetletju pokaže, da prevlada 3 REZULTATI prvi izmed teh dveh dejavnikov. V zadnjem desetletju Z uporabo opisanega pristopa smo izračunali, da bi v je namreč očiten trend naraščanja števila umrlih. Tudi letu 2020 v Sloveniji umrlo 20.896 oseb, če ne bi bilo iz Eurostatovih projekcij prebivalstva [1] izhaja, da bi virusa covid-19. Ta vrednost je za 675 oseb višja kot se brez virusa covid-19 število umrlih v prihodnje hitro znaša povprečje števila umrlih za obdobje 2015-2019 povečevalo. To pomeni, da z navedenim (to je, kot smo že omenili, 20.221 oseb). Ocenjujemo poenostavljenim pristopom Eurostat oziroma po njem torej, da za toliko oseb rezultati o presežni umrljivosti, zgledujoč se SURS precenjujeta presežno umrljivost, ki jih objavljata Eurostat in SURS, precenjujejo saj bi bilo tudi brez virusa covid-19 v letu 2020 število presežno umrljivost. Vendar pa tudi naš rezultat ni umrlih višje od povprečnega števila umrlih v obdobju enoličen, saj smo ga dobili ob predpostavljanju 2015-2019. Njihov pristop poda za 21,6 % višjo 5-letnega trenda (2015-2019) gibanja starostno vrednost presežne umrljivosti kot pa smo jo izračunali specifičnih stopenj umrljivosti v posamezni starosti mi z našim pristopom. Po metodi Eurostata oz. SURS (ločeno za oba spola). Za 5-letni trend 2015-2019 smo je namreč presežna umrljivost v Sloveniji v letu 2020 se odločili, ker tudi metoda Eurostata oz. SURS znašala 18,8 % (24.016 dejansko umrlih napram uporablja to obdobje kot referenčno. 20.221, kolikor znaša povprečno število umrlih za Po opisani metodi Eurostata oziroma SURS bi obdobje 2015-2019), mi pa jo ocenjujemo na 14,9 % presežno umrljivost za leto 2020 izračunali kot (24.016 dejansko umrlih napram 20.896). dejansko število umrlih v letu 2020 (24.016 oseb) minus povprečno število umrlih v obdobju 2015-2019 LITERATURA IN VIRI (20.221). Po metodi, ki jo uporabljata Eurostat oz. SURS, je torej presežna umrljivost v Sloveniji v letu [1] Eurostat (2020), “Population projections 2020 znašala 3.795 oseb. Z našo metodo pa znaša EUROPOP2019”. Najdeno 11. septembra 2021 na ocenjena presežna umrljivost 3.120 oseb. To pomeni, https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset da je ocena Eurostata oz. SURS o presežni umrljivosti =proj_19np&lang=en za 21,6 odstotka višja od vrednosti, ki smo jo izračunali [2] Statistični urad RS (2021) »Umrli po starosti in spolu, mi. Slovenija, letno«. Najdeno 11. septembra 2021 na Podatkovnem portalu SI-STAT: https://pxweb.stat.si/SiStatData/pxweb/ 4 ZAKLJUČEK sl/Data/-/05L1008S.px Natančne vrednosti presežne umrljivosti v letu 2020 iz [3] Statistični urad RS (2021a) »Prebivalstvo po starosti in naslova virusa covid-19 ne bomo nikoli izvedeli, saj ne spolu, kohezijski regiji, Slovenija, polletno«. Najdeno 11. bomo nikoli vedeli, koliko oseb bi umrlo, če virusa septembra 2021 na Podatkovnem portalu SI-STAT: covid-19 ne bi bilo. Eurostat, SURS in številni drugi https://pxweb.stat.si/SiStatData/pxweb/sl/Data/- presežno umrljivost izračunavajo /05C1002S.px kot razliko med dejanskim številom umrlih [4] COVID-19 sledilnik (2021). »Umrli«. Najdeno 11. v posameznem letu oz. septembra 2021 na https://covid-19.sledilnik.org/sl/stats mesecu in povprečnim številom umrlih v 5-letnem predhodnem obdobju (2015-2019). Ta pristop zahteva samo podatke o številu umrlih, tako da lahko izračune naredimo takoj, ko izvemo (letno ali mesečno) število umrlih, brez da bi čakali na podatke o številu prebivalcev v tem obdobju, ki praviloma sledijo s 407 Zaznavanje stresa pri srednješolcih v prvem valu epidemije COVID-19 Stress perception in high school students in the first wave of the COVID-19 epidemic dr. Tjaša Stepišnik Perdih dr. Mirna Macur Fakulteta za uporabne družbene študije Fakulteta za zdravstvo Angele Boškin Nova Gorica, Slovenija Jesenice, Slovenija tjasa.stepisnik.perdih@fuds.si mmacur@fzab.si POVZETEK of students experienced it significantly more than before the epidemic. The research also showed that the level of perceived Prvi val epidemije COVID-19 je prinesel veliko negotovosti, stress is significantly related to gender, school program, saj smo se s tako strogimi ukrepi za omejevanje prenosa okužbe, (non)staying in the dormitory, and chronic diseases. kot je zaprtje šol, omejitve druženja, nezmožnost opravljanja dela ipd., srečali prvič. Za marsikoga je to predstavljalo velik KEYWORDS stres, zato nas je zanimalo, kako so v prvem valu epidemije zaznavali stres slovenski srednješolci? V ta namen smo Stress perception, high school students, the first wave of the oblikovali spletno anketo in jo po metodi snežne kepe razširili epidemic, COVID-19, coronavirus. po srednjih šolah in dijaških domovih. Podatki na vzorcu 1492 srednješolcev kažejo, da je večina dijaške populacije (69,9%) v prvem valu epidemije zaznavala srednje močan stres (kategorije 1 UVOD nizek-srednji-visok), dobra šestina dijakov (17,8%) pa visok Soočanje z epidemijo in strogimi ukrepi za omejevanje prenosa stres. Več težav s spanjem, razdražljivosti, več močnih in/ali okužbe je za marsikoga predstavljalo velik stres. Raziskave [1, 2, neprijetnih čustev, občutkov nemoči in pomanjkanja energije kot 3] kažejo, da so nekateri razvili celo simptome, ki so značilni za v času pred epidemijo je doživljalo 34 - 44% srednješolcev, posttravmatsko stresno motnjo. To so bili predvsem tisti, ki so tistih, ki so to doživljali občutno bolj kot pred epidemijo, je bilo sami trpeli za resno obliko COVID-19 in jim je grozila smrt; ki 8-10%. Raziskava je tudi pokazala, da je stopnja zaznanega stresa statistično pomembno povezana s spolom, programom so bili kot družinski člani ali kot zdravstveni delavci priča šolanja, (ne)bivanjem v dijaškem domu in kroničnimi težavami trpljenju in smrti drugih; ki so izvedeli za smrt ali tveganje smrti oz. bolezenskimi stanji. družinskega člana ali prijatelja; in posamezniki, ki so bili zelo izpostavljeni grozljivim podrobnostim epidemije (npr. novinarji, KLJUČNE BESEDE zdravniki in bolnišnično osebje) [4]. Zaznavanje stresa, srednješolci, prvi val epidemije, COVID- Mladostniki spadajo v manj rizično skupino za okužbo s 19, koronavirus. COVID-19 in jih virus večinoma neposredno ne prizadene. Raziskave tako ugotavljajo, da je epidemija prizadela predvsem ABSTRACT starejše generacije, posledice ukrepov za njeno zajezitev pa The first wave of the COVID-19 epidemic brought a lot of predvsem mlajše [5]. Na Inštitutu RS za socialno varstvo [6] uncertainty, as it was the first time, we encountered such ugotavljajo, da je epidemija na otroke vplivala predvsem 1.) s stringent measures to limit the transmission of the infection, such psihološko obremenitvijo zaradi neznane situacije in strahu pred as school closures, social-distancing, inability to work, etc. and tem, da bi zboleli njihovi bližnji; 2.) povečano negotovostjo in for many, that posed great stress. The aim of this study was večjo možnostjo, da bodo njihovi bližnji izgubili zaposlitev; 3.) to investigate the perceived stress of Slovenian high school z ukrepi, ki so prekinili ustaljeni tok življenja družin in omejili students in the first wave of the epidemic. For this purpose, we nekatere svoboščine . conducted an online survey sent to secondary schools and student Prvi val je s seboj prinesel posebej veliko negotovosti, saj smo dormitories. Data on a sample of 1492 students show that the se s tako strogimi ukrepi za omejevanje prenosa okužbe, kot je majority of the student population (69.9%) perceived moderate zaprtje šol, omejitve druženja, nezmožnost opravljanja dela ipd., stress (low-medium-high categories) in the first wave of the srečali prvič. V raziskavi kitajskih mladostnikov, ki so ostali epidemic and a good sixth of students (17.8%) high stress. 34- doma v karanteni v prvem mesecu izbruha COVID-19, jih je kar 44% of students had more sleep problems, were more irritable, 12,8% doživljalo stresne simptome, ki so dosegali raven had stronger and/or unpleasant emotions, more feelings of posttravmatske stresne motnje [7]. Kako so v prvem valu helplessness and lack of energy than before the epidemic. 8-10% epidemije zaznavali stres slovenski srednješolci, pa bomo poskušali odgovoriti s pričujočo raziskavo. 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Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 408 2 METODOLOGIJA Tabela 2: Zaznavanje stresa po spolu in vrsti šolanja 2.1 Vzorec STRES V raziskavi je sodelovalo 1492 srednješolcev, od tega je bilo SPOL nizki srednji visoki SKUPAJ 58,1% (867) dijakinj. 0,9% srednješolcev je obiskovalo nižji N 101 465 59 625 poklicni program, 11.3% srednji poklicni program (triletni), moški 53,8% srednji strokovni program (štiriletni) in 34,0% srednji % 16,2% 74,4% 9,4% 100% splošni program (gimnazije). 24,3% (365) srednješolcev je bilo iz dijaških domov, 10,3% srednješolcev pa se je soočalo s N 83 578 206 867 kroničnimi težavami oz. bolezenskimi stanji. Geografska ženski % 9,6% 66,7% 23,8% 100% zastopanost je predstavljena v Napaka! Vira sklicevanja ni bilo mogoče najti. . VRSTA ŠOLANJA Tabela 1: Razporeditev dijakov po pokrajinah nižji N 0 12 1 13 poklicni % 0,0% 92,3% 7,7% 100% Pokrajina Frekvenca Procent program Gorenjska 151 10,0 srednji N 22 139 8 169 poklicni Osrednjeslovenska 187 12,4 program % 13,0% 82,2% 4,7% 100% Štajerska 533 35,4 (triletni) Prekmurje 28 1,9 srednji N 99 555 149 803 strokovni Koroška 28 1,9 program % 12,3% 69,1% 18,6% 100% Notranjska 50 3,3 (štiriletni) srednji N 63 337 107 507 Dolenjska 330 21,9 splošni Primorska 197 13,1 program % 12,4% 66,5% 21,1% 100% (gimnazija) N 184 1043 265 1492 SKUPAJ % 12,3% 69,9% 17,8% 100% 2.2 Instrumenti in postopek Za namene raziskave smo pripravili spletni vprašalnik z orodjem Statistično pomembna razlika pri zaznavanju stresa se kaže 1ka. Vključeval je sociodemografska vprašanja, primerjavo tudi glede na program šolanja (χ2(6)=27.582, p<0.01). Če življenjskega sloga (preživljanje časa na socialnih omrežjih, izvzamemo nižje poklicno izobraževanje, kjer je bil numerus prehranjevanje, spanje/nespečnost ipd.) s stanjem pred epidemijo izrazito majhen (0,9% vseh srednješolcev), je delež in Lestvico zaznanega stresa (The Perceived Stress Scale – srednješolcev, ki zaznavajo nizek stres približno enak, in sicer Cohen, Kamarck in Mermelstein, 1983), ki meri, kako pogosto 12,3-13%. Procent visoko zaznanega stresa narašča po anketiranci zaznavajo svoje življenje kot stresno, nepredvidljivo, zahtevnosti programa (z izjemo nižjega poklicnega programa). preobremenjujoče in nenadzorljivo. Rezultat PSS-ja se razvrsti v Pri tem je potrebno omeniti, da v srednjem strokovnem in eno od treh kategorij, in sicer nizko, srednje in visoko zaznani splošnem programu prevladujejo ženske (Slika 1). stres. Z višjim rezultatom se povečuje verjetnost, da stres v posameznikovem življenju presega njegove sposobnosti soočanja z njim. 100,0% Zbiranje podatkov je trajalo od 20.-26.4.2020 preko socialnih 90,0% 21,4% 19,9% mrež svetovalnih delavcev v srednjih šolah in vzgojiteljev 80,0% dijaških domov (t.i. metoda snežne kepe). Analiza podatkov je 53,0% 70,0% bila narejena s programom SPSS, uporabili smo deskriptivno 60,0% 79,1% statistiko ter hi-kvadrat test in Pearsonov korelacijski koeficient. 50,0% 40,0% 78,6% 80,1% 3 REZULTATI 30,0% 47,0% Kot prikazuje Tabela 2 je velika večina srednješolcev (69,9%) v 20,0% prvem valu epidemije zaznavala srednje močan stres. Visok stres 10,0% 20,9% je zaznavalo 23,8% vseh dijakinj in 9,4% dijakov. Dijaki in 0,0% dijakinje se statistično pomembno razlikujejo v stopnji nižji poklicni srednji srednji srednji program poklicni strokovni splošni zaznavanja stresa (χ2(2)=57.816, p<0.01). program program program M Ž Slika 1: Zastopanost spola po vrsti šolanja 409 Statistično pomembna razlika v zaznavanju stresa obstaja tudi - težave s spominom in/ali koncentracijo so že poleg glede na to, ali se srednješolci soočajo s kroničnimi težavami oz. omenjenega pozitivno povezane s stiskanjem v prsih, bolezenskimi stanji (χ2(2)=41.877, p<0.01), pri čemer večina le- razbijanjem srca, tesnobo (r=0.474, p<0.01) in doživljanjem teh zaznava srednje močan stres (55,6%). močnih in/ali neprijetnih čustev (r = 0.488, p<0.01); Stopnja stresa je odvisna tudi od tega, ali srednješolci živijo v Vidimo, da se štirje vidiki odzivanja med epidemijo 1.) dijaškem domu ali ne (χ2(2)=12.772, p<0.01). Najvišja razlika se nemoč, pomanjkanje energije, brezvoljnost, 2.) težave s kaže pri visoko zaznanem stresu, ki ga zaznava 23,1% srednješolcev spominom in/ali koncentracijo, 3.) stiskanje v prsih, razbijanje iz dijaških domov in 16,1% tistih, ki ne živijo v dijaškem domu. srca, tesnoba in 4.) doživljanje močnih in/ali neprijetnih čustev Slika 2 prikazuje procent srednješolcev, ki naštete vidike pomembno zmerno povezujejo med seboj. izkuša oz. opravlja “več” in “občutno več” kot pred epidemijo. Prav tako se medsebojno zmerno povezujejo razdražljivost oz. Svetleješi stolpci prikazujejo pozitivno spremembo, in sicer več napetost, stiskanje v prsih, razbijanje srca, tesnoba ter težave s kreativnega udejstvovanja (ustvarjanje, risanje ipd.), spanjem (srednješolci težko zaspijo, se zbujajo ponoči in/ali neformalnega izobraževanja, več časa zase oz. več umirjenosti težko vstanejo). ter več telesne aktivnosti kot pred epidemijo. 4 RAZPRAVA delo za šolo 58,7% Raziskava med 1492 srednješolci v času prvega vala epidemije v prehranjevanje 37,6% močna/neprijetna čustva 35,3% Sloveniji kaže, da je večina srednješolcev zaznavala srednje tesnoba, stiskanje v prsih 22,2% intenziven stres. Pri tem želimo opozoriti na dobro šestino težave s koncentracijo 29,9% srednješolcev, ki je zaznavala visok stres, v 78% so bile to kreativno udejstvovanje 38,1% ženske. Zaskrbljujoče povečanje psihične obremenjenosti med socialna omrežja, TV 61,5% dekleti ugotavlja tudi poročilo Inštituta RS za socialno varstvo sanjarjenje 41,6% [6]. neformalno izobraževanje 25,4% Študije mladih iz evropskih, azijskih in ameriških držav več časa zase, umirjenost 48,9% ugotavljajo povečanje težav z duševnim zdravjem, kot so brez energije, nemoč 44,0% razdražljivost, tesnoba, depresivni simptomi, simptomi telesna aktivnost 54,1% razdražljivost, napetost 39,6% posttravmatske stresne motnje ipd. [5, 6, 7]. Nemška študija je na težave s spanjem 34,2% reprezentativnem vzorcu pokazala, da je dve tretjini otrok in mladostnikov zaradi pandemije COVID-19 močno obremenjena. Slika 2: Vidiki doživljanja in aktivnosti, ki jih Poročali so o bistveno nižji kakovosti življenja, povezani z srednješolci opravljajo oz. izkušajo več kot pred epidemijo zdravjem (40% proti 15%), več težavah z duševnim zdravjem (18% proti 10%) in višjo stopnjo tesnobe (24% proti 15%) kot Po drugi strani je najvišji delež tistih srednješolcev, ki pred pandemijo [11]. V naši raziskavi doživlja težave s spanjem, preživljajo več časa na socialnih omrežjih, gledajo TV, serije ipd. močna in/ali neprijetna čustva, razdražljivost, občutke nemoči, Od tega jih je 20,2%, ki to počno občutno več kot pred brezvoljnost in pomanjkanje energije “več” in “občutno več” kot epidemijo. Preživljanje časa na socialnih omrežjih, z gledanjem pred epidemijo med 34 in 44% srednješolcev. Tistih, ki so to serij oz. pred TV se pomembno šibko povezuje s sanjarjenjem doživljali občutno bolj kot pred epidemijo in jih v tem pogledu oz. zatekanjem v domišljijo (r=0.202, p<0.01). 37,6% srednješolcev pojé več kot pred epidemijo. lahko štejemo kot rizične, je bilo 8-10% (že v prvem valu). Na Prehranjevanje se statistično pomembno, a neznatno pozitivno porast duševnih stisk med otroki in mladimi v času prvega vala povezuje z napetostjo (r=0.133, p<0.01), tesnobo (r=0.078, epidemije kažejo tudi podatki TOM telefona. Čeprav je bilo v p<0.01), pomanjkanjem energije (r=0.141, p<0.01), zatekanjem letu 2020 skupno število klicev manjše kot v preteklih letih, pa v domišljijo (r=0.074, p<0.01), gledanjem serij, TVja, je bilo klicev, ki so poročali o psihičnih težavah, 33% več kot v preživljanjem časa na socialnih omrežjih (r=0.154, p<0.01), povprečju zadnjih petih let [12]. težavami s koncentracijo (r=0.111, p<0.01) in doživljanjem Naša raziskava kaže, da je 62% srednješolcev preživljalo čas močnih in/ali neprijetnih čustev (r=0.126, p<0.01), negativno pa na socialnih omrežjih, z gledanjem videev, serij ipd. “več” in s telesno aktivnostjo (r=0.072, p<0.01). “občutno več” kot pred epidemijo. Čeprav je bil porast ob ukrepu V nadaljevanju izpostavljamo tiste vidike, kjer obstaja omejevanju druženja pričakovan, ne gre prezreti ugotovitve pomembna zmerna povezanost: - razdražljivost, napetost je pozitivno povezana s Inštituta RS za socialno varstvo, da se je precej povečala težavami s spanjem (r=0.497, p<0.01), nemočjo, pomanjkanjem ranljivost otrok na ravni aktivnosti, ki vodijo v odvisnost in energije, brezvoljnostjo (r=0.501, p<0.01), težavami s spominom odtujitev, kot npr. igranje računalniških igric, gledanje in/ali koncentracijo (r=0.406, p<0.01), s stiskanjem v prsih, videoposnetkov na youtube in televizije [6]. razbijanjem srca, tesnobo (r=0.497, p<0.01) in doživljanjem Izpostavili bi še en potencialen način soočanja s stresom oz. močnih in/ali neprijetnih čustev (r=0.572, p<0.01), negativno pa prilagoditveni odziv na epidemijo, in sicer v naši raziskavi je 9% je razdražljivost povezana s časom zase in občutkom umirjenosti srednješolcev označilo, da se prehranjuje “občutno več” kot prej. (r=0.413, p<0.01); Raziskave opozarjajo na naraščanje teže pri mladostnikih v času - nemoč, pomanjkanje energije in brezvoljnost je karantene [13], še posebej pri tistih, ki so se že prej soočali s pozitivno povezana s težavami s spominom in/ali koncentracijo povišano telesno težo [11, 12, 13]. Ta pojav je dobil celo svoje (r=0.453, p<0.01), s stiskanjem v prsih, razbijanjem srca, tesnobo ime – ang. covibesity [17]. (r=0.418, p<0.01) in doživljanjem močnih in/ali neprijetnih V razpravi smo izpostavili predvsem tiste vidike, ki so že ob čustev (r = 0.488, p<0.01); začetku epidemije nakazovali morebitne kasnejše težave. 410 Rezultate je namreč potrebno gledati retrospektivno, saj se “Immediate Psychological Effects of the COVID-19 Quarantine in nanašajo na april 2020, tj. čas prvega zapiranja šol, in jih tako Youth From Italy and Spain,” Front. Psychol. , vol. 11, pp. 1–10, 2020. [10] G. Pietrabissa et al. , “The impact of social isolation during the covid-19 lahko jemljemo kot prikaz, kakšen je bil prvi odziv srednješolcev pandemic on physical and mental health: The lived experience of na ukrepe za omejitev širjenja virusa COVID-19. adolescents with obesity and their caregivers,” Int. J. Environ. Res. Public Health, vol. 18, no. 6, pp. 1–20, Mar. 2021. [11] U. Ravens-Sieberer, A. Kaman, M. Erhart, J. Devine, R. Schlack, and LITERATURA IN VIRI C. Otto, “Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany,” Eur. Child [1] V. M. E. Bridgland et al. , “Why the COVID-19 pandemic is a traumatic Adolesc. Psychiatry, 2021. stressor,” PLoS One, vol. 16, no. 1, p. e0240146, Jan. 2021. [12] ZPMS, “TOM telefon: VPLIV EPIDEMIJE COVID-19 NA OTROKE [2] Y. Tu et al. , “Post-traumatic stress symptoms in COVID-19 survivors: IN MLADOSTNIKE,” 2021. a self-report and brain imaging follow-up study,” Mol. Psychiatry 2021, [13] C. A. Nogueira-de-Almeida, L. A Del Ciampo, I. S. Ferraz, I. L. R. Del pp. 1–6, Jul. 2021. Ciampo, A. A. Contini, and F. da V Ued, “COVID-19 and obesity in [3] D. Janiri et al. , “Posttraumatic Stress Disorder in Patients After Severe childhood and adolescence: a clinical review,” J. Pediatr. (Rio. J). , vol. COVID-19 Infection,” JAMA Psychiatry, vol. 78, no. 5, pp. 567–569, 96, no. 5, pp. 546–558, Sep. 2020. May 2021. [14] R. An, “Projecting the impact of the coronavirus disease-2019 pandemic [4] “Post-COVID Stress Disorder: Another Emerging Consequence of the on childhood obesity in the United States: A microsimulation model,” Global Pandemic.” [Online]. Available: J. Sport Heal. Sci. , vol. 9, no. 4, pp. 302–312, Jul. 2020. https://www.psychiatrictimes.com/view/post-covid-stress-disorder- [15] A. Pietrobelli et al. , “Effects of COVID-19 Lockdown on Lifestyle emerging-consequence-global-pandemic. [Accessed: 04-Aug-2021]. Behaviors in Children with Obesity Living in Verona, Italy: A [5] A. Grom Hočevar et al. , “Pandemija covid-19 v Sloveniji. Izsledki Longitudinal Study,” Obesity, vol. 28, no. 8, pp. 1382–1385, Aug. 2020. panelne spletne raziskave o vplivu pandemije na življenje (SI-PANDA), [16] V. Bayram Deger, “Eating Behavior Changes of People with Obesity 6. val,” Ljubljana, 2021. During the COVID-19 Pandemic,” Diabetes. Metab. Syndr. Obes. , vol. [6] U. Boljka, T. Narat, J. Rosič, M. Škafar, and M. Nagode, “Vsakdanje 14, pp. 1987–1997, 2021. življenje otrok v času epidemije covid 19,” Ljubljana, 2020. [17] M. A. Khan and J. E. Moverley Smith, “‘Covibesity,’ a new pandemic,” [7] L. Liang et al. , “Post-traumatic stress disorder and psychological Obes. Med. , vol. 19, Sep. 2020. distress in Chinese youths following the COVID-19 emergency:,” J. Health Psychol. , vol. 25, no. 9, pp. 1164–1175, Jul. 2020. [8] L. Ezpeleta, J. B. Navarro, N. De La Osa, E. Trepat, and E. Penelo, “Life Conditions during COVID-19 Lockdown and Mental Health in Spanish Adolescents,” Int. J. Environ. Res. Public Health, vol. 17, 2020. [9] M. Orgilés, A. Morales, E. Delvecchio, C. Mazzeschi, and J. P. Espada, 411 »Podivjajmo Slovenijo« kot nov koncept varovanja okolja “Rewild Slovenia” - new concept of conservationism Matjaž Gams† Jozef Stefan Institute Jamova 39 Ljubljana matjaz.gams@ijs.si POVZETEK Predstavljen je koncept »podivjanja Slovenije«, ki ga nekateri razumejo kot ponovno uvajanje že izumrlih živali v Sloveniji, recimo evropskega bizona. A omenjeni koncept je precej širši in temelji na spremembi odnosa do živali in okolja: vsi državljani naj bi se prilagodili življenju z živalmi, jim omogočili sobivanje, spodbujali naravno okolje, avtohtone rastline in živali in hkrati tudi živali priučili sobivanja s človekom. KEYWORDS / KLJUČNE BESEDE Varovanje okolja, podivjajmo, novi pristopi ABSTRACT In this paper we introduce “rewilding” as a new concept for conservationism. It is the version that propagates introducing wild species back to Slovenia, e.g. European bison. However, it is much more than that, it builds on the proposition that we humans must learn, adapt and encourage wildlife, whereas wild animals must adapt to human coexistence. KEYWORDS Slika 1: Knjiga Rewilding (slovensko »podivjanje«) je ena Conservation, environment, rewilding izmed ključnih objav za novo ekološko usmeritev s tem imenom. Vir: https://m.media- amazon.com/images/I/618YTln54bL.jpg 1 UVOD Medtem ko človeštvo po eni strani še naprej masovno uničuje A najprej poglejmo osnovno problematiko varovanja okolja in okolje in živali [1][2] in celo ogroža razvoj civilizacije [3], se živali. Denimo, da bi v divjini pobili 4% vseh sesalcev na med ljudmi širi drugačna, bolj privlačna miselnost. Gre za to, da planetu. Koliko divjih sesalcev bi ostalo? Odgovor je – nič! Vseh naredimo sobivanje z divjimi živalmi ne samo znosno, ampak divjih sesalcev na Zemlji je le 4% skupne teže, ljudje prispevamo zaželeno in obojestransko uspešno 36%, domače živali pa 60%. Poglejte tule: (https://www.zurnal24.si/slovenija/komentarji-in- (https://africacheck.org/fact-checks/fbchecks/study-found-60- kolumne/podivjajmo-slovenijo-evropo-svet-371239). Gre za all-mammal-carbon-mass-livestock-36-people-only-4-wildlife). varovanje in ponovno uvajanje živali, ki smo jih iztrebili v Slovenija je prva po m2 veletrgovin na glavo v Evropi in med Sloveniji. Gre za novo usmeritev v varovanju okolja, ki je prvimi na svetu. Prav tako je med prvimi na svetu po km predstavljena v [4], naslovnica pa je na Sliki 1. zgrajenih avtocest. Avtocesto in fakulteto v vsako slovensko vas! Naši politiki pa bi kar naprej gradili, sekali gozd, uničevali najboljšo zemljo, postavljali reklame ob cestah sredi polj, zapirali reke v betonska korita in potočke v podzemne cevi. Pisali Permission to make digital or hard copies of part or all of this work for personal or smo že, kako bodo z novo potezo kmetijskega ministrstva 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 zmanjšali število divjih živali. Nekateri mediji pri tem žal citation on the first page. Copyrights for third-party components of this work must premalo pomagajo okolju. Pred leti so vsakodnevno pisali, kako be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia okoljsko škodljive da so sveče. A izračun pokaže, da en zelo © 2020 Copyright held by the owner/author(s). velik tovornjak na avtocesti naredi približno toliko škode okolju kot vse sveče v Sloveniji [5], podobno kot vse kremacije. Zakaj 412 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Gams torej ne opozarjamo na posledice kremiranja in še bolj – prometa volkove in nezadostno povračamo škodo, ali zahtevamo, da zlasti po avtocestah? živinorejci sami nosijo stroške postavitve varnostnih ograj, slej ko prej jezni domačini tako ali drugače škodijo volkovom. Podobno je z napadalnimi vranami, ki napadajo otroke, ki se 2 PONOVNA NASELITEV ŽIVALI približajo gnezdom. Pričakovati, da bodo starši ranjenih otrok imeli posebej dober odnos do okolja in živali, ni posebej realno. Če jim damo možnost, se živali vrnejo [6]. Primer je Černobil, Na takih dogodkih se dobiva ali izgublja odnos do okolja in živali. kjer je kljub visoki radioaktivnosti odsotnost ljudi povzročila Vran ne primanjkuje in premik gnezda oz. »pouk« napadalnih pravi razcvet živali (https://www.unep.org/news-and- vran je malenkost v primerjavi z javnim mnenjem. stories/story/how-chernobyl-has-become-unexpected-haven- Naslednja napaka je nekontrolirano širjenje določenih wildlife). Drug primer so evropska mesta, kamor se vračajo lisice, živalskih vrst. Divje svinje, avtohtone v Evropi in Aziji, so se kune, jazbeci, šakali (https://www.amazon.com/Feral-Cities- razširile po vsem svetu in ustvarijo toliko izpustov kot milijon Adventures-Animals-Jungle/dp/1569760675) in se tako dobro avtomobilov, piše prispevek v reviji Global Change Biology skrivajo pred ljudmi, da jih le redko vidimo, pa tudi ljudje jih ne (https://onlinelibrary.wiley.com/doi/10.1111/gcb.15769). preganjajo več intenzivno. V Evropi marsikatera mesta Podobno je z medvedi pri nas, ki jih je približno dvakrat preveč namenoma uvajajo spremembe, ki koristijo živalim. Posledično glede na površino in zato ustvarjajo ekološki in živalski problem. je gostota nekaterih živali večja kot v naravnem okolju, pa tudi Preštevilčne vrste je potrebno tako ali drugače uravnati na znosno živijo dalj. Mesta vsaj malo vračajo naravi bogastvo življenja, ki mejo. A prispevek o divjih svinjah je zanimiv tudi po medijski so ga odvzela. plati: če vse divje svinje po svetu ustvarijo toliko CO2 kot cca Ta trend je v visoko civilizirani Evropi čedalje bolj izrazit milijon avtomobilov, potem obstoječa milijarda avtomobilov (https://rewildingeurope.com/rewilding-in-action/wildlife- ustvari tisočkrat več izpustov CO2 kot divje svinje, tako v comeback/large-carnivores/) in se bo slej ko prej razživel tudi v Sloveniji kot na svetu, da o drugih škodljivih učinkih ne Sloveniji. Ključno je vračanje velikih živali, zlasti plenilcev: govorimo: drugi plini, segrevanje okolja zaradi vrtanja do nafte medveda, volka, risa, pa tudi divje mačke, kot to poskušajo na itd. Torej je v primerjavi s škodljivostjo transporta zanemarljivo! Nizozemskem. Evropski bizon je v naravi izumrl, ostalo je le 54 Tretji velik problem so invazivne vrste, ki izrivajo domače. živali v živalskih vrtovih (https://www.dw.com/en/global-ideas- Primer so vodne želve, ki izrivajo domače sklednice. Če bi imeli biodiversity-rewilding-conservation-europe/a-18586774), sedaj primeren zakon o invazivnih živalih, ki bi ne samo dovoljeval jih je okoli 3000, manj kot črnih nosorogov. A njihovo število vsem, ampak celo s kaznijo nalagal lastnikom, da jih raste in uvajajo jih v čedalje več državah, npr. v Veliki Britaniji. odstranjujejo, ne bi imeli polne obale rdečevratk nekaterih jezer Zakaj ne tudi v Sloveniji? Se še kdo med nami spomni, ko smo v celo v Ljubljani. A logika je kruto preprosta: če ne bomo ljubljanskem živalskem vrtu občudovali ogromnega zobra? odstranili invazivnih rdečevratk, bodo rdečevratke odstranile Podobno uspešno je naseljevanje divjih goved in konj na kar sklednice iz Slovenije. Vrsto lahko iztrebiš z neposrednim nekaj lokacijah v Evropi. Primer je okoli 200 divjih konjih blizu izlovom, lahko pa enostavno tako, da ne kontroliraš invazivne Livnega na Hrvaškem. vrste. In da ne bo pomote: to ni naravno, ker so rdečevratke vnesli Leta 1908 je iz Slovenije izginil zadnji ris kot največja ljudje! Pa tudi druga logika je preprosta: dokler ne bo mogoče evropska mačka v velikosti mladega leoparda nobenemu ministrstvu dopovedati zgornjega, se bo težko kaj (https://www.metropolitan.si/aktualno/zgodovina-risa-v- spremenilo. sloveniji-in-usoda-te-cudovite-male-zveri-v-evropi/). V Sloveniji smo ponovno uvedli risa leta 1973, žal je bila prva runda preveč v sorodstvu, tako da je bilo potrebno dodati novo. 4 »Podivjajmo« vrt in tako pomagajmo S Hrvaške se je pred 20 leti sam vrnil bober in sedaj živi ob Savi, okolju in živalim Krki, Dravi, Sotli, Muri, Kolpi, Lahinji, Dobličici in nekaterih manjših rečicah. Kozoroga smo ponovno naselili leta Marsikatera okolica hiše je življenju negostoljubna : beton in 1902. Iztrebili smo tudi svizca, a je ponovno naseljen in živi na morda nekaj malega kratko pokošene trave. Idealna okolica hiše območju Grintovca, Ojstrice ter še ponekod. vsebuje grme, drevesa, tolmun, »rezervat« - težko dostopen konček za ljudi in del nepostrižene trate, kjer kraljujejo pašne cvetlice in letajo metulji ali kačji pastirji. Vrt postane poln 3 UPRAVLJANJE Z ŽIVALMI biodiverzitete tako rastlin kot živali. A začnimo s podivjanjem vrta: en del vrta nehajte redno kositi. Volkovi se kljub napakam lepo širijo, a hkrati se pojavljajo Lahko kupite semena travnih cvetlic, lahko pa le kosite npr. problemi. Recimo moderna napaka je, da ne odstraniš ali enkrat letno in cvetlice pridejo same od sebe. To je ena izmed kaznuješ divje živali, recimo napadalnega volka, ampak je modernih eko smernic, ki delajo naše življenje lepše, hkrati pa »nagrajen« z mesom domačih živali. Podobno, ko pride v bližino preprečujejo izumiranje naravnega sveta. ljudi. Živali se učijo in prilagajajo in zato jih moramo Pred desetletji se je bilo v poletnih mesecih na poti na morje sistematično vzgajati, da bodo lahko živele hkrati z nami. Če iz Ljubljane potrebno ustaviti, ker se je na avtomobilskem steklu bodo tiste nevzgojene jezile ljudi, tudi onih sobivajočih ne bo več. nabralo toliko žuželk. Danes se lahko peljete najmanj desetkrat Zato je ključnega pomena vzgoja živali, da se prilagodijo ljudem. brez čiščenja stekel, ker je letečih insektov 75% manj kot pred Seveda naj se tudi ljudje prilagodijo živalim, a za sobivanje je 50 leti. Morda bo kdo rekel: »odlično«, a brez insektov se začne potrebno sodelovanje obeh. Če samo z dekretom uvedemo podirati ekološka piramida – manj je ptic, manj je drugih živali 413 “Podivjajmo” Slovenijo Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia in na koncu smo pri nekaj odstotkov divjih živali, izumiranje pa v. Obdavčiti vse in posebej nove veletrgovine je 100-1000x hitrejše kot naravno, tako so pokazale študije, w. Uvesti hitre vlake recimo [1], ali x. Dodatno kaznovati in nadzirati prehitro vožnjo (https://www.nationalgeographic.com/adventure/article/140529 y. Dodatno obdavčiti tranzitne tovornjake -conservation-science-animals-species-endangered-extinction). z. Omejiti promet izven kategoriziranih cestišč Nič hudega? Tudi semenčic imajo mladi moški 50% manj kot aa. Prepovedati genetsko spremenjene rastline pred 50 leti. Brez stroke počnemo nove in nove neumnosti. bb. Propagirati samo-skrb za okolje Junijska številka 2021 revije »National geographic« vsebuje cc. Uvesti bele ali poraščene fasade in strehe prispevek o spreminjanju džungle v kmetijske površine na dd. Uvesti ribje steze, kjer je smotrno mehiškem polotoku Jukatan, gojenju genetsko spremenjenih ee. Podivjati Slovenijo rastlin in škropljenju z insekticidi. Posledično ne samo izumirajo leteče in druge žuželke, nekoč cvetoče čebelarstvo je skoraj Ti predlogi, zbrani s strani okoli 100 strokovnjakov v propadlo. Ko je vlada prepovedala genetske spremenjene rastline, večletnih razpravah predvsem v Državnem svetu [8], pa tudi v so se za nekaj časa razmere izboljšale, a ker ni bilo nadzora, se je strokovnih združenjih kot Inženirski akademiji Slovenije, nadaljevalo ilegalno izsekavanje džungle in sajenje genetsko predstavljajo osnovno strokovno utemeljeno smer skrbi za okolje spremenjenih poljščin. Za tono medu je bilo pred 20 leti v Sloveniji. Utemeljitve za posamezne predloge so v [5]. Recimo potrebnih 12 panjev, danes 45. Morda se boste vprašali, kaj ima omejitve prehitre vožnje so utemeljene s tem, da vsakih dodatnih to z nami? Poleg ZDA je glavni uvoznik EU, torej smo mi 10km/h nad 100 km/h prinese 10% dodatnega onesnaževanja. Evropejci oz. naši politiki soodgovorni za to. Pa tudi mi lahko Ali pa prepoved genetsko spremenjene hrane, ki ne temelji na skoraj prenehamo kupovati hrano, ki je prišla od daleč. Bližja je potencialnem strahu pred škodo ljudem, ampak na škodi, ki jo z bolj sveža in bolj ekološka! genetsko vcepljenimi varovali pred žuželkami povzroča preko žuželk celotnemu ekosistemu. Tako ali tako moderno monokulturno kmetijstvo uničuje biodiverziteto, a vseeno manj kot genetsko spremenjena hrana. 5 Napotki iz Bele knjige strokovnega varovanja okolja 6 ZAKLJUČEK Naštejmo nekaj posodobljenih napotkov iz Bele knjige strokovnega varovanja okolja [5]: Pri varovanju okolja sta dve ključni smeri: ena pravi, da je treba ljudi odstraniti od narave, naj se ne vtikajo v okolico, naj ne krmijo ptic pozimi in naj ne pomagajo npr. prezeblemu ježku, a. ki ste ga razkrili v kompostu. Druga smer temelji na sožitju, da Prepoved reklamnih panojev v vidnem polju avtocest b. sobivamo, da pomagamo naravi, rastlinam in živalim, kolikor Prepoved oglaševanja v odprtem prostoru krajine c. moremo. Ljudje so spremenili pol vse planetove površine, živali Prenehati prekomerno osvetljevanje in ohranjanje vidnosti zvezdnega neba uničujemo in izrivamo, da prihaja do 6. svetovnega izumiranja d. (https://www.amazon.com/Sixth-Extinction-Unnatural- Omejitev obsega cestne razsvetljave e. History/dp/0805092994; [2]; Ne povečevati števila prebivalcev Slovenije [7] f. http://www.allcreation.org/home/understand). To počnemo ali v Povečati sredstva za znanost, zlasti okoljsko g. hlastanju za bogastvom, kapitalom, ali pa zaradi neumnosti. Povečati okoljsko osveščenost/izobraženost občin in občanov Stroka in ljubitelji lahko pomagajo narediti naše okolje in odnos h. do rastlin in živali tak, da bomo lahko sobivali in uživali drug ob Sprejeti nov zakon in spremeniti odnos do invazivnih rastlinskih in živalskih vrst drugem. i. »Podivjanje« uvaja nov, dober odnos do narave, okolja, Odstraniti alergene rastline iz javnega sektorja j. rastlin in živali. Propagira sobivanje in souživanje darov in Sprejeti nov zakon za odstranjevanje agresivnih živali k. pestrosti naravnega sveta. Strokovno je marsikaj opredeljenega v Uvajati klimatske naprave-inverterje kot najbolj učinkovito napravo prosto dostopni »Beli knjigo o strokovnem varovanju okolja« l. (http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20znanos Izvajati financiranje obnovljivih virov m. t%20o%20okolju%202020.pdf) [5], kjer so zbrani moderni Ukiniti termoelektrarne na premog n. strokovni nasveti, kako varovati okolje. Čeprav so naši politiki Zgraditi nov blok jedrske elektrarne kot najbolj čiste 24/7 energije realizirali le manjši del napotkov stroke, jih lahko izvajamo o. državljani sami – npr. odstranjujemo invazivne rastline in živali Bolje izkoriščati vodne vire – hidroelektrarne, kjer je primerno in podivjamo vrt. p. Uporabljati solarne panele, kjer je primerno q. Izboljšati varčevanje z energijo REFERENCES r. Spodbujanje naseljevanja prebivalstva v urbanih okoljih in ne po krajini [1] De Vos, J. M., Joppa, L.N., Gittleman, J.L., Stephens, P.R., Stuart L., S. L. Pimm, S.L., 2014. Estimating the Normal Background Rate of Species s. Otežiti uvoz hrane iz oddaljenih krajev Extinction, Article first published online: 26 AUG 2014 t. Otežiti prodajo oddaljenih izdelkov DOI: 10.1111/cobi.12380. [2] Kolbert. E. 2014, The Sixth Extinction: An Unnatural History, u. Otežiti prodajo kmetijskih površin Bloomsbury, February 11. 414 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M. Gams [3] Meadows, Donella H; Meadows, Dennis L; Randers, Jørgen; Behrens III, William W (1972). The Limits to Growth; A Report for the Club of Rome's Project on the Predicament of Mankind (PDF). New York: Universe Books. ISBN 0876631650. [4] Cain Blythe, Paul Jepson, 2020. Rewilding: The Radical New Science of Ecological Recover, W. F. Howes Ltd (Publisher). [5] Matjaž Gams, Nina Črnivec, Lidija Globevnik, Stanislav Pejovnik, Žiga Zaplotnik, Aleksander Zidanšek, 2020. Bela knjiga o strokovnem varovanja okolja, http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20znanost%20o%2 0okolju%202020.pdf [6] George Monbiot, 2013. Feral, Searching for enchantment on the frontiers of rewilding, Penguin Press [7] Gams, M., Malačič, J. 2019. Bela knjiga slovenske demografije. Evropska demografska zima. Institut ”Jozef Stefan” Ljubljana. http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20demografije%20 DS%202018.pdf [8] M. Gams, posvet Znanost o okolju; http://www.ds-rs.si/node/4922. 415 Involvement of Citizens in Environmental Epidemiology Studies: Some Experience From the CitieS-Health Ljubljana Pilot David Kocman† Miha Pratneker Jure Ftičar Department of Environmental Department of Environmental Department of Environmental Sciences Sciences Sciences Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia david.kocman@ijs.si miha.pratneker@ijs.si jure.fticar@ijs.si Tina Vrabec Johanna A. Robinson Rok Novak Department of Environmental Department of Environmental Department of Environmental Sciences Sciences Sciences Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia tina.vrabec@ijs.si johanna.robinson@ijs.si rok.novak@ijs.si ABSTRACT of approaches on how to connect the public with scientific research, to what extent and in what type of research, but the In this contribution, a general overview and experience gained in main objective of CS is that the approach is beneficial for both conducting citizen science (CS) activities in the field of citizens and researchers. environmental epidemiology is presented. The described Even though CS has gained recognition within various activities were carried out in Ljubljana, Slovenia, in the frame of scientific and civic communities [1], environmental sciences the CitieS-Health H2020 project, dealing with the topic of noise, may especially utilize the collection of large amounts of well-being and health in the context of urban environment. observations and data classifications public involvement brings Following the project’s methodological framework, citizens to expert research (e.g. [2,3]). In return, citizens get answers on were actively involved in all phases of the project – problem issues concerning them. Froeling et al. [4] argue that the true identification, co-designing of experimental works, as well as added benefit of CS in environmental epidemiology is in its data gathering and interpretation. Some preliminary results and ability to democratize epidemiological research, which addresses lessons learned are summarized for both the main study the content of research, investigates local problems and provides involving volunteers participating in respective data collection, findings that are crucial for changes in citizens' immediate as well as specific activities carried out with elementary school environment. pupils. The ultimate outcomes and effects of these activities are In this contribution, we present some preliminary results and still to be properly evaluated. The overall preliminary conclusion observation obtained within the EU Horizon 2020 project CitieS- however is that, while the concept was well received among the Health (https://citieshealth.eu) which is based on the so-called engaged citizens and valuable new insights in the topics co-created CS approach, allowing citizens and their concerns to addressed can be achieved in this way, managing volunteer be at the heart of research agenda on environmental motivation and expectations which in turn affect their retention epidemiology. Together with the help of researchers, new and sustainability of the project, can be challenging, especially if technologies and customized tools, citizens in five European conducted in the time of pandemic. cities, including Ljubljana, Slovenia, are involved in all stages of research in order to find out how pollution in their living environment is affecting their health. KEYWORDS In the Ljubljana pilot, the public was engaged in co-creating Citizen Science, Environmental epidemiology, Urban stressors, a CS research study on how the quality of living environment Well-being, Health (with emphasis on noise) and living habits affect the (mental) health and well-being of individuals. A great deal of studies have discovered the connection between noise pollution and health, resulting in hearing damages, sleep disorders, cardiovascular diseases, lower work productivity etc. [5], but the data on the 1 INTRODUCTION correlation between noise and health, especially in the multi- stressors context in urban environments, is still scarce. Citizen Science is a term that generally describes lay people involvement in scientific research projects. There are a great deal 416 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Kocman et al. 2 METHODS short and detailed user guides for the participants were prepared, providing information on the use and installation of the tools. Following the CitieS-Health methodological framework [6], citizens were involved in four phases of the project, from identification of their concerns and interests, to co-designing of data protocols, data collection and analysis to action (Figure 1). Figure 2: The tools used and the levels of involvement Figure 1: CitieS-Health methodological framework (adopted from Toran et al. [6]) 2.3 Deployment phase During the deployment phase, two general types of activities 2.1 Identification phase took place. Altogether, 49 volunteers participated in the main In the identification phase, numerous meetings with interested study, collecting data on characteristics of their living stakeholders were organized in Ljubljana, Slovenia, to map their environment and mental health using the tools described above. perception, interests and concerns related to noise pollution and Depending on their interest, each of the participants participated health issues. In addition to some very specific noise and health- 7–14 days. The main study lasted for 6 months, from October related questions identified during these discussions, the 2020 to April 2021. Following the data collection, a report for recurring topic was their belief these issues should be addressed the participants was prepared. In the spirit of co-creation and co- in the multi-stressor context of the living environment and habits design, the report was prepared as an interactive web-application of an individual. This resulted in a consolidation of the following enabling individuals to access the raw data, along with basic final overarching research question: How do the quality of the descriptive statistics, general data on the patterns of movement living environment (with an emphasis on noise) and living habits in space and sleeping habits, pre-processed by researchers, and affect the (mental) health and well-being of individuals? specific tools for their independent data processing. Besides the main study, part of the project activities took place in cooperation with various schools in Ljubljana, involving 2.2 Design phase both teachers and students. Activities comprised involvement of students in school research assignments and organization of As a result of the design phase, we selected and tested sensors various tailored events (see section 3.2 for details). and other tools (smartphone apps, noise level meters and similar low-cost devices) to be used by participants. This included the 2.4 Action definition of experimental variables, the types of data to be collected and the methods and tools for collecting them. A The action phase will follow in the final stage of the project. In general Ljubljana Pilot protocol was formulated and submitted to that phase, workshops for participants will be organized to reflect the Republic of Slovenia National Medical Ethics Committee. In on their own findings, as well as with other stakeholders the protocol, different levels of involvement were foreseen, interested in this topic, including public institutions and civil depending on the specific interests and willingness of the society. individual. Each new level adds to the complexity of the involvement and the tools used (Figure 2). The EthicaData platform (ethicadata.com) was chosen as the main tool for 3 RESULTS managing the study, and through which both volunteers and basic data collection tools are administered: questionnaires on well- In this section, some preliminary results are shown, to indicate being, sleep, living environment characteristics and cognitive the type of data and outcomes of the activities described above, tests, as well as time-activity diaries. In addition, NoiseCapture including observations regarding motivation and general and Fitbit smartphone app were used to measure noise and collect involvement of participants, as well as potential involvement of physical activity parameters, respectively. Because of the citizens in such specific research. Overall, data gathered can be COVID situation that prevented face-to-face meetings, various processed in two ways. The first approach is evaluation of the results by processing all of the data together at the community 417 Involvement of Citizens in Environmental Epidemiology Studies: Some Experience From the CitieS-Health Ljubljana Pilot level in order to identify general patterns. The second approach Understanding volunteer motivation and expectations helps in comprises an evaluation of data on individual level, preferably as retaining their interest in the long-term [7]. Regarding independently as possible by volunteers themselves and with the expectations and motivation to participate in this study, most of help of researchers. In the following, a few general examples of the volunteers indicated contribution to science and solving the the former are given, as well as more details on activities carried problems as the main drive, followed by an interest in this out with schools are provided. specific topic, results in general and personal interests (Figure 4). 3.1 Ljubljana Pilot – main study Volunteers included in the main study were collecting approximately 75 different variables at each measurement session (through questionnaires, measurements by smartphones and physical activity trackers and meta-data). This resulted in over 50.000 data points, excluding the geo-spatial data. In Figure 3, a heatmap of the density distribution of GPS, and number of measurements of noise levels (in seconds) aggregated in 500 meter cells, collected from all participants combined at the level of the Municipality of Ljubljana. The distribution on both maps shows a relatively even spatial distribution with an emphasis on the densely populated city centre. Figure 4: Drivers of motivation to participate In the main study, participants were, in the morning and afternoon, automatically prompted at random times, to record their own observations, measure noise level and test their cognitive abilities with a Stroop test [8]. A comparison of the average response over time showed that it usually decreased significantly with increasing length of participation, which is typical of studies involving volunteers. Similarly, within a single day, the response rate significantly dropped between 13th and 15th hour of the day as shown in Figure 5, but interestingly the cognitive (Stroop) performance during this time of the day when people are usually busy at work or in school, improved in general. For the later, daily z-score was employed in order to mitigate the learning effect of the participants. Lower values of the score indicate better cognitive performance. Figure 5: Frequency of data gathering by hour of day and cognitive performance Other general initial findings show a curve of positive moods Figure 3: Heatmap of the density distribution (above) and leaning towards the weekend, as well as the opposite, with number of measurements of noise levels (below) negative moods, both assessed by three different indicators 418 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Kocman et al. (Figure 6). Regarding noise, results revealed a considerable research in general and their interest in participating in other adaptability of the perception of sound in humans. While no project activities. considerable difference was observed in terms of cognitive performance at a community-level in noisy or silent C. Organization of tailored events: Two tailored School Tech- environments, results indicate that there are differences in Day Events (STDE) as part of the school’s curriculum were cognitive performance driven by specific activities individuals prepared and aligned with the project’s methodological are involved in (Figure 6). framework together with teachers. The pupils were initially involved in identifying noise-related issues and translation of selected topics into research questions. Next, together with mentors, they participated in the process of hypothesis formulation and the design of data collection protocols. Finally, they participated in data gathering, as well as data analysis and presentation [9]. Figure 6: Variation of average community-level mood over a week (above) and relationship between cognitive performance and activity (below) 3.2 School activities Activities at schools covered different levels of student involvement: A. School research assignments on the topic of noise and health: Several school research assignments addressing different aspects of noise and health were performed by students, e.g. sound levels in different school environments, spatial distribution of noise at Figure 7: Elementary school students performing selected locations in their living environment and surrounding measurements of noise levels (above) and interpreting the school, using smartphone application for quantitative results with the help of researchers (below) assessment, as well as by recording their subjective perception. Slightly older students showed interest in the technical aspects of noise level monitoring and developed a sensor unit with a 4 CONCLUSION supporting data infrastructure. The outcome of this work was Results and observations presented in this contribution are presented at the national level event meetings of young preliminary ones. While an important phase of the project – researchers of Slovenia, organized by Association for Technical evaluation and impact assessment still needs to be performed, Culture of Slovenia. some initial conclusions and lessons learned so far can be summarized as follows: B. Organization of nature day events: Treasure hunts were The concept – CitieS-Health methodological framework – organized in a protected area of Tivoli, Rožnik and Šišenski Hill was well received among the engaged citizens and valuable new landscape park. Locations where pupils had to look for hidden insights in the topics addressed can be achieved following this questions on the topic of sound and noise were marked on the approach. Most citizens expressed interest in the multi-exposure map. At each point, we measured the noise level with the help of aspect of living environment, not only noise, which proved to be an application on a smartphone, wrote the data on a census sheet very useful in the light of potential confounding factors and and discussed the results obtained. The aim of the event was to interpretation of the results. Citizens sometimes, however, have involve pupils in research activities and trigger their curiosity, a hard time with the concept of co-design. It was observed that 419 Involvement of Citizens in Environmental Epidemiology Studies: Some Experience From the CitieS-Health Ljubljana Pilot most volunteers prefer to follow a pre-defined schedule of tasks Reduced cognitive function during a heat wave among residents of non- and rarely opt for tasks that are optional. Adjustments had to be air-conditioned buildings: An observational study of young adults in the summer of 2016. PLoS Med 15(7): e1002605. DOI: made to adjust the number of the former in our study protocol. It https://doi.org/10.1371/journal.pmed.1002605 turned out that most volunteers needed additional, more detailed [9] Kocman D, Števanec T, Novak R, Kranjec N. Citizen Science as Part of the Primary School Curriculum: A Case Study of a Technical Day on the instructions, e.g., for using certain application features and Topic of Noise and Health. Sustainability. 2020; 12(23):10213. DOI: storing data on servers. This was especially the case due to the https://doi.org/10.3390/su122310213 COVID situation, as respective mitigation measures had to be prepared that comprise interaction with volunteers in the on-line mode only, and accordingly tools used were adjusted. To this end, detailed and tailored user guides and info-graphics were prepared to help the volunteers. Time-constrain was the main preventing factor for participation and continuous efforts had to be made to keep volunteers engaged. The activities organized at the school stimulated the interest of the school staff and attracted them to participate in the main study of the project. Overall, once again, schools proved to be a great environment for the conduct of CS activities, and pupils seemed to enjoy and learn from practical hand-on experience in conducting research. Concept of CS activities has great potential for further ongoing inclusion in the school curriculum, adjusted according to the specifics of the topics addressed [9]. ACKNOWLEDGMENTS This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824484, and the P1-0143 program “Cycling of substances in the environment, mass balances, modelling of environmental processes and risk assessment”, funded by the Slovenian Research Agency. REFERENCES [1] Susanne Hecker, Muki Haklay, Anne Bowser, Zen Makuch, Johannes Vogel and Aletta Bonn (Eds.), 2018. Citizen Science: Innovation in Open Science, Society and Policy. UCL Press, London, UK. [2] Kullenberg C., Kasperowski D. (2016) What Is Citizen Science? – A Scientometric Meta-Analysis. PLoS ONE 11(1): e0147152. DOI: https://doi.org/10.1371/journal.pone.0147152 [3] Pykett, J., Chrisinger, B., Kyriakou, K. et al. Developing a Citizen Social Science approach to understand urban stress and promote wellbeing in urban communities. Palgrave Commun 6, 85 (2020). DOI: https://doi.org/10.1057/s41599-020-0460-1 [4] Frederique Froeling, Florence Gignac, Gerard Hoek, Roel Vermeulen, Mark Nieuwenhuijsen, Antonella Ficorilli, Bruna De Marchi, Annibale Biggeri, David Kocman, Johanna Amalia Robinson, Regina Grazuleviciene, Sandra Andrusaityte, Valeria Righi, Xavier Basagaña, Narrative review of citizen science in environmental epidemiology: Setting the stage for co-created research projects in environmental epidemiology, Environment International, Volume 152, 2021, 106470, DOI: https://doi.org/10.1016/j.envint.2021.106470 [5] Jake Hays, Michael McCawley, Seth B.C. Shonkoff, Public health implications of environmental noise associated with unconventional oil and gas development, Science of The Total Environment, Volume 580, 2017. DOI: https://doi.org/10.1016/j.scitotenv.2016.11.118 [6] Toran, R., Ortiz, R., Gignac, F., Daher, C., Nieuwenhuijsen, M., Ortiz, R., Donzelli, G., Makavasi, G., Fivorilli, A., De Marchi, B., Bastiani, G., Kocman, D., Errandonea, L., et al., 2019. Documentation on activities and outcomes in CS actions (first report). Retrieved from: http://citieshealth.eu/download/435/?v=440 (accessed 11 September 2021). [7] Robinson, J. A., Kocman, D., Speyer, O., & Gerasopoulos, E. (2021). Meeting volunteer expectations—A review of volunteer motivations in citizen science and best practices for their retention through implementation of functional features in CS tools. Journal of Environmental Planning and Management, 64(12), 2089–2113. https://doi.org/10.1080/09640568.2020.1853507 [8] Jose Guillermo Cedeño Laurent, Augusta Williams, Youssef Oulhote, Antonella Zanobetti, Joseph G. Allen and John D. Spengler. 2018. 420 (Eko)golf igrišča in Natura 2000: Golf in varovanje okolja (Eco) Golf courses and Natura 2000: Golf and Environmental Protection Karel Lipič Zveza ekoloških gibanj Slovenije Krško,Slovenija zegslo20@gmail.com POVZETEK V članstvo Sveta za okolje pri Golf zvezi Slovenije (GZS) nas je (Zvezo ekoloških gibanj Slovenije – ZEG) Golf zveza Golf po vsem svetu igra približno 70 milijonov ljudi, v več kot povabila k sodelovanju že davnega leta 1999. 200 državah Igralci golfa čutijo in izkoriščajo prednost, ki jih zdravju prinaša ta šport in prisotnost v naravnem okolju. Skupaj smo načrtovali oglede igrišč in ocenjevanje z vidika Načrtovanje, gradnja, adaptacija do okolja prijaznih golf igrišč okoljsko odgovornega ravnanja slovenskih golf igrišč, ter nujna pridobitev mednarodnih in domačih eko certifikatov promocijo takratne okoljskega Evropskega certifikata (standardov) v Sloveniji bi Slovenijo uvrstila med privlačne Committed to Green, razmišljali in pripravljali smo celo za destinacije mehkega turizma. »Slovenski znak okoljske kakovosti«, kot standard, ki bi naj veljal na vseh golf igriščih v Sloveniji. Posebno delovno KLJUČNE BESEDE skupino (dr. Vladimir Meglič, Bogdan Macarol, Gorazd (eko)golf igrišča, okoljski standardi,okolje,prostor,Natura 2000 Nastran in Karel Lipič) v Svetu za okolje sestavljajo tudi številni drugi strokovnjaki, ki se na svojih področjih trudijo za ABSTRACT boljše stanje okolja v Sloveniji in njim ni vseeno, kaj se dogaja Golf is played by around 70 million people worldwide, in more na področju golf igrišč. than two hundred countries. Golfers feel and take advantage of the health benefits of the mentioned sport and its presence in the natural environment. Planning, construction, adaptation to 2 GOLF IGRIŠČA V SLOVENIJI environmentally friendly golf courses and the necessary Golf kot igra se je začela v Sloveniji na Bledu že leta 1937, ko acquisition of international and domestic eco certificates and so zaključili prvih devet lukenj, kar je sicer polovica običajnega standards in Slovenia would also mean placing Slovenia among igrišča. Leta 1972 smo dobili tam prvo zaključeno golf igrišče z the most attractive destinations of tourism. osemnajstimi luknjami, ki ga je projektiral Donald Harradine, priznani golf arhitekt, ki je imel velik občutek za poudarjanje KEYWORDS naravnih danosti. (eco)golf courses, environmental standards, environment, Natura 2000 Drugo golf igrišče v Sloveniji smo dobili leta 1989 v Lipici, sicer spet le polovično – z devetimi luknjami. Tudi tu se je pod projekt podpisal isti arhitekt. 1 UVOD Načrtovanje in gradnja golf igrišča v Sloveniji , tudi na V naslednjih letih se je kar aktivno nadaljeval razvoj golf igrišč. slovenski obali (npr. občina Piran), ta čas še vedno povzroča Gradnja golf igrišč v Sloveniji pa je nekako obstala po letu javno negodovanje nekaterih posameznikov in skupin. 2006, ko sta bila izgrajena še prvo »Pitch putt« - krajše vadbeno Slovenska javnost in prav tako številni odgovorni na igrišče s šestimi luknjami v Šempetru pri Novi Gorici in igrišče ministrstvih, katerih aktivnosti so neposredno povezane tudi z z devetimi luknjami – Trnovo na saniranem odlagališču smeti delovanjem golf igrišč, ter s tem možnostjo igranja golfa, so na Ljubljanskem Barju. zelo slabo seznanjeni z vplivi načrtovanja, gradnje in vzdrževanja golf igrišč na okolje. Ob pomanjkanju V Sloveniji imamo danes šestnajst golf igrišč z 18. ali več verodostojnih informacij, tako prihajajo do veljave luknjami (Bled, Lipica,Moravske Toplice..) in sedem manjših, s neobjektivni, neresnični in zelo pogosto nestrokovni,predvsem 6. ali 9. luknjami, ki skupno z še 6-imi vadbišči za vadbo pa neverodostojno argumentirani članki ter izjave kritikov golf udarcev leži na skupni površini , cca 800 ha. igrišč. Potrebno je redno in načrtno pridobivati podatke o okoljskih vplivih, ki jih dejavnosti v zvezi z golf igrišči imajo Golf zveza Slovenije je aktivna v prizadevanjih za varstvo na okolje, jih kritično ovrednotiti in o izsledkih seznanjati okolja že od leta 1996, ko se je njen predstavnik udeležil prvega slovensko javnost. sestanka tehnične komisije mednarodne neodvisne Fundacije Committed to Green, ki je postavljala temelje okoljsko 421 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Karel Lipič odgovornih principov načrtovanja, gradnje in vzdrževanja golf Sredi leta 2005 je bila ob podpori Evropske Komisije igrišč v Evropi. V začetku leta 2001 je bil ustanovljen prvi Svet ustanovljena Golf Environment Europe – neodvisna fundacija, za okolje pri Golf zvezi, ki je že s koncem istega leta, skupaj z ki je ob kvalitetnem okoljskem programu ob sprejemu in Združenjem vzdrževalcev golf igrišč Slovenije, organiziral podpori vseh, ne zgolj le Evropsko v golf vpetih strani, ob posvet Golf in okolje. Podlaga za posvet so bili podatki zbrani velikem interesu v letu 2008 prerasla v Golf Environment na vseh – takrat osmih igriščih v Sloveniji. Posveta so se Organization. Njena vizija je: Golf je lahko vodilni v aktivno udeležili tako predstavniki golf igrišč, vzdrževalci, zagotavljanju trajnostnega razvoja v športu in poslovanju, v nekatere okoljske NVO (ZEG idr.) kot tudi Ministrstvo za najširšem javnem pogledu, pa cenjen po okoljskem in okolje in prostor. socialnem prispevku! Zaključki takratnega posveta so bili tudi: Spomladi leta 2007 je bil s strani Golf zveze Slovenije pripravljen še en posvet na temo Golf – Okolje - Prostor, kateri - upravljanje in vzdrževanje igrišč v Sloveniji je pa je bil žal odpovedan zaradi premajhne prijave pričakovanih odgovorno do okolja, vendar je potrebno zagotoviti udeležencev; malo iz golfskih sredin, še manj pa iz strani sistem rednega letnega preverjanja, svetovanja in institucij države; ministrstev, uprav, agencij. pomoči pri izvajanju programa; - potrebno je vpeljati sistem rednega monitoring-a vseh V maju 2014 je bila organizirana prva predstavitev golfa v talnih vodnih virov in podtalnice na golf igriščih; Evropskem parlamentu. Na kratko naj povzamemo nekaj MOP, igrišča; navedenih vidikov tega športa v Evropi: - v pet letnem obdobju se pregleda vsa slovenska golf igrišča ter se popiše redke ptice, sesalce ter druge redke živali poleg tega pa še avtohtone rastlinske - ekonomski: prispevek v ekonomiji presega 15 vrste, zaščitene rastline in območja, ter se izda milijard evrov; navodilo za zagotavljanje njihovega normalnega - socialni: golf igra v Evropi preko 7,9 milijona ljudi; življenja; MOP, Agencija RS za varstvo narave; - okoljski: obstaja preko 6.000 golf igrišč v Evropi, na - potrebno je pripraviti nosilno slovensko okoljsko področju katerih je vsaj 70% zemljišč mogoče strategijo za izbiro lokacij, gradnje in vzdrževanje uporabiti in varovati kot posebne in pomembne golf igrišč; priprava MOP, Urad za prostorsko habitate. planiranje in Agencijo RS za varstvo narave, Ministrstvo za kmetijstvo, gozdarstvo in prehrano, ob pomoči Golf zveze Slovenije in Združenja 3 V SLOVENIJI NIMAMO GOLF IGRIŠČ V vzdrževalcev golf igrišč Slovenije, ter drugih; Zveza NATURI 2000 ekoloških gibanj Slovenije - ZEG.; V tujini poznamo mnogo primerov, ko golf igrišča izkazujejo - javnost je potrebno redno in dovolj kakovostno obveščati o okoljskih dejavnostih najvišje standarde. Eno takih je v Kristianstadu na Švedskem, ki in stanju na slovenskih golfiščih; je celo pod zaščito UNESCA, ali pa Hilversumsche golf na - svet za okolje naj v naslednjih letih z dopolnjenimi in Nizozemskem z izredno bogato floro in favno, ki tudi redno popravljenimi vprašalniki nadaljuje delo z gosti European Tour – tekmovanje v golfu na najvišji, ocenjevanjem igrišč in svetovanjem izboljšav; profesionalni ravni. - potrebna je jasna, nedvoumna zakonska kategorizacija golf igrišč kot celote in njenih Golfska igrišča lahko ob pravilni zasnovi, načrtovanju, dobrem sestavnih delov. Določitev je pomembna tudi zaradi upravljanju pomembno prispevajo k biotski raznovrstnosti in razvrstitve in umeščanja v prostor pogostih ohranjanju te pestrosti s široko paleto vsega življenja, ki ga samostojnih vadbišč, ali manjših vadbenih golf igrišč; gostijo – od rastlin do ptic, od nevretenčarjev do dvoživk. MOP, Urad za prostorsko planiranje, Ministrstvo za Pomembno pa je to tudi preverjati in tudi objaviti izsledke! kmetijstvo, gozdarstvo in prehrano; - pri pripravi in spremembah zakonodaje s področja Namen je, da se promovira dobre prakse, da se umakne golfa, morajo Ministrstva k razpravi povabiti Golf negativno konotacijo z golfa, obenem pa usmerja upravljalce zvezo Slovenije in Združenje vzdrževalcev golf igrišč igrišč in tudi igralce same, k okoljsko odgovornemu Slovenije. vzdrževanju in rabi prostora.So objem narave, hrepenenja po aktivnosti in vpliva zdravega življenja. V Zvezi ekoloških gibanj Slovenije - ZEG, nevladni okoljski organizaciji (ima status društva v javnem interesu po ZVO) Golf zveza Slovenije kot krovna organizacija golfa v Sloveniji lahko ugotavljamo, da se v vsem tem obdobju (po letu 2001) na je v svojih aktivnostih vedno skrbela za odgovoren odnos do nivoju države ni zgodilo nič, kar bi bilo potrebno za izboljšanje okolja. Čas bi bil, da bi se v te aktivnosti vključile tudi državne pregleda, nadzora in verodostojnega poročanja o stanju in inštitucije, ki so neposredno vezane na to področje in to ne le z odnosu do okolja Slovenskih golf igrišč. Nič ni bilo narejeno za restriktivnim – omejevalnim pristopom (nadzorom), temveč pripravo podlag za načrtovanje golf igrišč v prostoru, njihovo konstruktivno s svetovalnimi in usmerjevalnimi aktivnostmi. gradnjo in upravljanje! Edino kar se je zgodilo so bili Pred kratkim je bil nov Svet za okolje. Pripravljene so restriktivni ukrepi v smislu nadzora nad rabo fitofarmacevtskih aktivnosti, katerih izvedba je ponovno odvisna od aktivne sredstev. soudeležbe s strani države. Upam, da bo tokrat več posluha, predvsem pa želje po izboljšanju stanja.Imamo že preko 10.000 golfistov. 422 (Eko)golf igrišča in Natura 2000: Golf in varovanje okolja Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Slovenska javnost zahteva dokaze (če so?), da slovenska golf Vemo, da je golf kot šport in kot gospodarska aktivnost dobra. igrišča res ne onesnažujejo okolja in da so lahko pomemben Vemo, da je pomemben za okolje na področju igrišč in tudi člen Nature 2000, varovanja okolja ter rekreacije ljudi v naravi. mnogo širše do koder sežejo vplivi. Vemo pa tudi, da je lahko še boljši, da lahko okolje, njegovo zdravje in pestrost še izboljšamo! Zato pa moramo vsi pridati svoj prispevek in ne le 4 ZAKLJUČEK čakati na naslednji vlak! V Zvezi ekoloških gibanj Slovenije - ZEG, nevladni okoljski organizaciji po dvajsetih letih stalnih prizadevanj pričakujemo V Zvezi ekoloških gibanj Slovenije v času še trajajoče javne večje strokovno vključevanje Golf zveze Slovenije v razprave in iskanja dolgoročnih okoljskih rešitev v Republiki načrtovanje eko golf igrišč. Sloveniji na področju izvajanja podnebne politike (NPVO, NEPN…) prosimo vlado RS in njena resorna ministrstva oz. Od pristojnih državnih institucij in ministrstev pa korenite strokovne službe , da nas seznanijo ali načrtujejo , kakršne koli okoljske spremembe v praksi, da vključijo te igralne površine v aktivnosti na tem področju, oz. ali se vam ne zdi, da bi bilo zavarovana območja. Ob dobrem okoljskem upravljanju nujno, da bi se slovenska golf igrišča priključila Evropskemu lastnikov igrišč, le-te lahko pomembno prispevajo k biotski programu certificiranja (GEO) primernosti okoljskega ravnanja raznovrstnosti države. kot ga pozna cela Evropa? Golf zveza Slovenije in lastniki vseh golf igrišč bi morali 5 VIRI pogosteje dokazovati svojo okoljsko neoporečno ravnanje, saj se v javnosti sliši mnogo opazk na neustrezno in neodgovorno - lastni viri, arhiv in dokumentacija ZEG ravnanje na področju kemizacije tal. - medijski strokovni članki o golf igriščih - zapisi skupnih sestankov na GZS in Združenju V ZEG-u predlagamo, da se v te aktivnosti morajo nujno vzdrževalcev golf igrišč Slovenije (med leti 2000-2015) vključiti resorna ministrstva (MOP, MKGP, Ministrstvo za - Matjaž Gams infrastrukturo, MGT…) in vlada. Mnenja smo, da bi morala slovenska golf igrišča izdelovati naslednja letna poročila: - skupne površine golf igrišča, gnojene površine, količine in vrste porabljenega gnojila; - uporabljena vsa fito farmacevtska sredstva in na koliko površin (katerih) so bila uporabljena; - količine in viri vode uporabljeni za vzdrževanje, - količine porabljenih maziv in olj ter potrdila o varnem odstranjevanju; - količine komunalnih in biološko razgradljivih odpadkov. Golf zvezi Slovenije in Svetu za okolje pri GZS predlagamo, da: - ponovno pripravi in dodela vprašalnik o okoljskih vplivih slovenskih golf igrišč; - pridobitev vseh potrebnih podatkov na golf igriščih do meseca junija 2022; - skupaj z Združenjem vzdrževalcev golf igrišč Slovenije pripravi letni zbir vseh potrebnih,variabilnih podatkov o vzdrževanju golf igrišč; - pripravi več sestankov v širši slovenski politiki in javnosti s ciljem seznanjanja in izboljšanja medsebojnega odnosa in sodelovanja; - nudi pomoč pri nastajanju novih golf igrišč z nasveti oz. pomoč pri implementaciji okoljskega programa Zavezani okolju (Committed to Green) zainteresiranim golf igriščem v Sloveniji in tujini; - pripravi predlog za sklic slovenskega posveta na temo »GOLF IN OKOLJE« v letu 2022 ter izdela zgibanko oz. TV oglas za seznanjanje javnosti o odnosu golf igrišč do okolja. 423 Gospodarska in podnebna negotovost v Združenih državah Amerike Economic and climate uncertainty in the United States Dejan Romih Ekonomsko-poslovna fakulteta Univerza v Mariboru Maribor, Slovenija dejan.romih@um.si POVZETEK krize na drugi strani. Izkazalo se je, da ZDA niso odporne proti gospodarskim, družbenim in zdravstvenim šokom na eni in Gospodarske in podnebne razmere se spreminjajo, kar med podnebnim šokom na drugi strani, kar ameriškim oblikovalcem gospodarskimi enotami povzroča potrebo po prilagajanju. V tem politike povzroča težave. prispevku analiziram gospodarsko in podnebno negotovost v Dejstvo je, da je negotovost zanimiva tema, ki med drugim ZDA. Ugotovil sem, da se je zaradi gospodarske in podnebne zanima tudi ekonomiste. Raziskave kažejo, da negotovost krize povečala gospodarska oz. podnebna negotovost v ZDA. negativno vpliva na gospodarstvo in družbo. KLJUČNE BESEDE gospodarstvo, podnebje, politika, negotovost, ZDA 2 GOSPODARSKA NEGOTOVOST ABSTRACT Pandemija covida-19 je v ZDA povzročila gospodarsko recesijo, ki je trajala od marca do aprila 2020 [1]. Zaradi gospodarske Economic and climate conditions are changing, leading to the krize (recesijskega pritiska v gospodarstvu) se je v ZDA povečala need among economic units for adaptation. In this paper, I gospodarska negotovost [2, 3, 4, 5, 6], ki jo obravnavam v prvem analyse the economic and climate uncertainty in the US. I found delu tega prispevka. Slika 1 kaže odnos med »gospodarstvom« that economic and climate uncertainty in the US have increased na eni in »negotovostjo« na drugi strani, pri čemer je presek obeh due to the economic and climate crisis, respectively. krogov »gospodarska negotovost«, ki jo lahko na kratko definiramo kot negotovost glede gospodarskih razmer. KEYWORDS economy, climate, policy, uncertainty, US 1 UVOD Gospodarske in podnebne razmere se spreminjajo, kar med gospodarskimi enotami povzroča potrebo po prilagajanju. Od njihove sposobnosti prilagajanja je odvisno, kakšen bo njihov jutri. Zadnje leto in pol se v medijih veliko govori in piše o negotovosti, ki jo zaradi gospodarske, družbene in zdravstvene krize na eni in podnebne krize na drugi strani čutimo na vsakem koraku. To med gospodarskimi enotami povzroča potrebo po ukrepanju. Znano je, da pandemija covida-19 spreminja naš način življenja: vprašanje je, ali na boljše ali na slabše. V tem prispevku analiziram gospodarsko negotovost, ki jo na kratko definiram v poglavju 2, in podnebno negotovost, ki jo na Slika 1: Odnos med »gospodarstvom« in »negotovostjo« kratko definiram v poglavju 4, pri čemer se omejujem na ZDA, ki se zadnje leto in pol soočajo s hudimi posledicami Raziskave kažejo, da je pandemija covida-19 prispevala k gospodarske, družbene in zdravstvene krize na eni in podnebne povečanju negotovosti v ZDA [2, 3, 4, 5, 6]. Slika 2 kaže gibanje indeksa negotovosti za ZDA v obdobju od prvega četrtletja 2000 do drugega četrtletja 2021, slika 3 pa gibanje indeksa Permission to make digital or hard copies of part or all of this work for personal or pandemične negotovosti za ZDA v obdobju od zadnjega 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 četrtletja 2019 do drugega četrtletja 2021. Iz slik je razvidno, da citation on the first page. Copyrights for third-party components of this work must sta indeksa svoj vrh dosegla v prvem četrtletju 2020, tj. v prvem be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia valu okužb s koronavirusom SARS-CoV-2. © 2021 Copyright held by the owner/author(s). 424 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Romih 0,90 0,80 0,70 s 0,60 k 0,50 ed 0,40 In 0,30 0,20 0,10 0,00 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q -Q 0 1 2 3 5 6 7 8 0 1 2 3 5 6 7 8 0 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Četrtletje Slika 2: Negotovost v ZDA v obdobju od prvega četrtletja 2000 do drugega četrtletja 2021 [7, https://worlduncertaintyindex.com/] 50,00 40,00 Slika 4: Odnos med »gospodarstvom«, »politiko« in sk 30,00 e »negotovostjo« d 20,00 In 10,00 Dejstvo je, da obstaja potreba po opazovanju in spremljanju gospodarskopolitične negotovosti v ZDA. V ta namen so Baker 0,00 4 1 2 3 4 1 2 idr. [8] razvili indeks gospodarskopolitične negotovosti za ZDA, -Q -Q -Q -Q -Q -Q -Q 9 0 0 0 0 1 1 ki med drugim temelji na številu člankov, objavljenih v desetih 1 2 2 2 2 2 2 0 0 0 0 0 0 0 2 2 2 2 2 2 2 ameriških časopisih. Da se članek upošteva, mora vsebovati Četrtletje besedo »ECONOMIC« ali »ECONOMY«, besedo »CONGRESS« ali » DEFICIT« ali »FEDERAL RESERVE« ali »LEGISLATION« ali »REGULATION« ali »WHITE HOUSE« in besedo »UNCERTAIN« ali Slika 3: Pandemična negotovost v ZDA v obdobju od »UNCERTAINTY«. zadnjega četrtletja 2019 do drugega četrtletja 2021 [7, Slika 5 kaže gibanje indeksa gospodarskopolitične https://worlduncertaintyindex.com/] negotovosti za ZDA v obdobju od januarja 2000 do avgusta 2021. Iz slike je razvidno, da je bila gospodarskopolitična negotovost v Dejstvo je, da so bile na začetku krize (šoka) gospodarske ZDA največja maja 2020, prim. [5]. enote v negotovosti (negotovem položaju) glede gospodarskih razmer doma in po svetu, zaradi česar so odlašale z odločitvami glede novih investicij in zaposlitev. 600 500 s 400 k 3 GOSPODARSKOPOLITIČNA e 300 dIn NEGOTOVOST 200 100 Raziskave kažejo, da je pandemija covida-19 prispevala tudi k 0 povečanju gospodarskopolitične negotovosti v ZDA [2, 5]. Na 1 6 1 4 9 2 7 2 5 0 3 8 1 6 1 4 začetku gospodarske krize še ni bilo znano, katere ukrepe za -0 -0 -1 -0 -0 -0 -0 -1 -0 -1 -0 -0 -0 -0 -1 -0 0 1 2 4 5 7 8 9 1 2 4 5 7 8 9 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 2 oživitev gospodarske dejavnosti v ZDA bo na primer sprejela 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 ameriška vlada pod vodstvom Donalda J. Trumpa ml., kar je v Mesec ZDA povzročilo gospodarskopolitično negotovost, ki jo obravnavam v nadaljevanju tega poglavja. Slika 4 kaže odnos med »gospodarstvom« na eni, »politiko« Slika 5: Gospodarskopolitična negotovost v ZDA v obdobju na drugi in »negotovostjo« na tretji strani, pri čemer je presek od januarja 2000 do avgusta 2021 [8, vseh treh krogov »gospodarskopolitična negotovost«, ki jo lahko https://www.policyuncertainty.com/] na kratko definiramo kot negotovost glede gospodarske politike, prim. [8]. Slika 6 kaže zanimanje za gospodarskopolitično negotovost v ZDA od 5. januarja 2000 do 29. avgusta 2021. Iz slike je razvidno, da je bilo zanimanje za gospodarskopolitično negotovost v ZDA največje maja 2020, ko je bila tudi gospodarskopolitična negotovost v ZDA največja. 425 Gospodarska in podnebna negotovost v ZDA Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 120 70 100 60 s 80 50 k s e k 60 40 d ed 30 In 40 In 20 20 10 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Datum Datum Slika 8: Zanimanje za podnebne spremembe v ZDA od Slika 6: Zanimanje za gospodarskopolitično negotovost v januarja 2004 do avgusta 2021 (Google Trendi) ZDA od 5. januarja 2000 do 29. avgusta 2021 (Google [https://trends.google.com/trends/] Trendi) [https://trends.google.com/trends/] Dejstvo je, da se ZDA zaradi podnebnih sprememb ne piše Raziskave kažejo, da gospodarskopolitična negotovost dobro, kar je razvidno iz slike 9, ki kaže odstopanje povprečne negativno vpliva na gospodarstvo [2]. Zato je naloga mesečne temperature v ZDA glede na referenčno obdobje 1986– oblikovalcev politike in politikov, da preprečujejo nastajanje 2005 (scenarij: visoke emisije). gospodarskopolitične negotovosti. -2-0 0-2 2-4 4-6 6-8 4 PODNEBNA NEGOTOVOST Dec. Podnebne spremembe povzročajo podnebno krizo, o kateri se v Nov. ameriških medijih premalo govori in piše. Znano je, da je odnos Okt. ameriških gospodarskih enot do vprašanja podnebnih sprememb Sept. odvisen od strankarske pripadnosti [9, 10]. Donald J. Trump ml. Avg. (ki je pripadnik politične desnice) na primer v nasprotju z c Jul. e Josephom R. Bidnom ml. (ki je pripadnik politične levice) ne se Jun. verjame v podnebne spremembe. M Zaradi podnebne krize se je v ZDA povečala podnebna Maj negotovost., ki jo obravnavam v nadaljevanju tega poglavja. Apr. Slika 7 kaže odnos med »podnebjem« na eni in Mar. »negotovostjo« na drugi strani, pri čemer je presek obeh krogov Feb. »podnebna negotovost«, ki jo lahko na kratko definiramo kot Jan. negotovost glede podnebnih razmer. –1960 –1970 –1980 –1990 –2000 –2010 –2020 –2030 –2040 –2050 –2060 –2070 –2080 –2090 –2100 1951 1961 1971 1981 1991 2001 2011 2021 2031 2041 2051 2061 2071 2081 2091 Obdobje Slika 9: Odstopanje povprečne mesečne temperature glede na referenčno obdobje 1986–2005 v ZDA po mesecih in obdobjih [https://climateknowledgeportal.worldbank.org/download- data] Raziskava, ki so jo marca 2021 opravili Leiserowitz, Maibach, Rosenthal, Kotcher, Carman, Wang, Marlon idr. [11] na vzorcu 1037 odraslih Američanov, med drugim kaže: − da jih 70 odstotkov meni, da prihaja do globalnega Slika 7: Odnos med »podnebjem« in »negotovostjo« segrevanja; − da jih 57 odstotkov meni, da prihaja do globalnega Slika 8 kaže zanimanje za podnebne spremembe v ZDA od segrevanja zaradi človekovega delovanja; januarja 2004 do avgusta 2021. Iz slike je razvidno, da se − da jih je 64 odstotkov zaskrbljenih zaradi zanimanje za podnebne spremembe v ZDA povečuje. globalnega segrevanja; − da jih 57 odstotkov meni, da globalno segrevanje negativno vpliva nanje; 426 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia D. Romih − da jih 45 odstotkov meni, da globalno segrevanje »UNCERTAINTY«. Podatki za obdobje od januarja 2000 do marca negativno vpliva na druge, 2021 kažejo, da je indeks podnebnopolitične negotovosti za ZDA − da jih 64 odstotkov čuti (so)odgovornost za svoj vrh dosegel septembra 2019, ko je v New Yorku potekala globalno segrevanje; Konferenca o podnebnih spremembah (Climate Action Summit − da jih 61 odstotkov meni, da globalno segrevanje 2019) (gl. sliko 11). negativno vpliva na vreme v ZDA. 5 PODNEBNOPOLITIČNA NEGOTOVOST 700 600 Logično je, da lahko k zmanjšanju politične negotovosti največ s 500 400 prispevajo politiki sami. Lep primer za to je Joseph R. Biden ml., ek 300 ki se po načinu vodenja precej razlikuje od svojega predhodnika. Ind 200 Ta je na primer z izjavo, da bodo ZDA odstopile od Pariškega 100 sporazuma o podnebnih spremembah (Paris Agreement on 0 1 8 3 0 5 2 7 2 9 4 1 6 1 8 Climate Change), ki jo je dal 1. junija 2017, prispeval k -0 -0 -0 -1 -0 -1 -0 -0 -0 -0 -1 -0 -0 -0 povečanju 0 1 3 4 6 7 9 1 2 4 5 7 9 0 politične negotovosti v ZDA. 0 0 0 0 0 0 0 1 1 1 1 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 V tem poglavju obravnavam podnebnopolitično negotovost, 2 2 2 2 2 2 2 2 2 2 2 2 2 2 ki je tako kot gospodarskopolitična negotovost zanimiva tema. Mesec Slika 10 kaže odnos med »podnebjem« na eni, »politiko« na drugi in »negotovostjo« na tretji strani, pri čemer je presek vseh treh krogov »podnebnopolitična negotovost«, ki jo lahko na Slika 11: Podnebnopolitična negotovost v ZDA v obdobju kratko definiramo kot negotovost glede podnebne politike. od januarja 2000 do marca 2021 [12, https://www.policyuncertainty.com/] 6 SKLEP Dejstvo je, da se ZDA (tako kot druge svetovne države) zaradi gospodarske, družbene in zdravstvene krize na eni in podnebne krize na drugi strani soočajo z novimi težavami, ki so izziv za ameriške oblikovalce politike. Za gospodarske enote velja, da se morajo prilagajati razmeram doma in v svetu. Zaradi pandemije covida-19 se je v ZDA povečala negotovost, ki jo analiziram v tem prispevku. Ugotovil sem, da se je le-ta povečala na začetku pandemije, ko še na primer ni bilo cepiva proti koronavirusu SARS-CoV-2. Negotovost pa se v ZDA ni povečala samo zaradi gospodarske, družbene in zdravstvene krize, ampak tudi zaradi podnebne, katere posledice čutimo na lastni koži. REFERENCES [1] National Bureau of Economic Research (2021). US Business cycle expansions and contractions. https://www.nber.org/research/data/us-business-cycle- Slika 10: Odnos med »podnebjem«, »politiko« in expansions-and-contractions »negotovostjo« [2] Al-Thaqeb, S. A., Algharabali, B. G., Alabdulghafour, K. T. (2020). The pandemic and economic policy uncertainty. Tako kot obstaja potreba po opazovanju in spremljanju International Journal of Finance & Economics, 1–11. gospodarskopolitične negotovosti v ZDA, obstaja tudi potreba po https://doi.org/10.1002/ijfe.2298 opazovanju in spremljanju podnebnopolitične negotovosti v [3] Altig, D., Baker, S., Barrero, J. M., Bloom, N., Bunn, P., ZDA. V ta namen je Gavriilidis [12] razvil indeks Chen, S., Davis, S. J., Leather, J., Meyer. B., Mihaylov, E., podnebnopolitične negotovosti za ZDA, ki temelji na številu Mizen, P., Parker, N., Renault, T., Smietanka, P., & Thwaites, člankov, objavljenih v osmih ameriških časopisih. Da se članek G. (2020). Economic uncertainty before and during the upošteva, mora vsebovati besedo »CARBON DIOXIDE« ali COVID-19 pandemic. Journal of Public Economics, 191, »CLIMATE« ali »CLIMATE CHANGE« ali »CLIMATE RISK« ali »CO2« 104274. https://doi.org/10.1016/j.jpubeco.2020.104274 ali »EMISSIONS« ali »ENVIRONMENTAL« ali »GLOBAL WARMING« [4] Baker, S. R., Bloom, N., Davis, S. J., & Terry, S. J. ali »GREEN ENERGY« ali »GREENHOUSE« ali »GREENHOUSE GAS (2020). Covid-induced economic uncertainty (Working Paper EMISSIONS« ali »RENEWABLE ENERGY«, besedo »CONGRESS« ali No. 26983). National Bureau of Economic Research. »EPA« ali »LAW« ali »LEGISLATION« ali »POLICY« ali https://doi.org/10.3386/w26983 »REGULATION« ali »WHITE HOUSE« in besedo »UNCERTAIN« ali [5] Romih, D. (2021). Gospodarskopolitična negotovost v 427 Gospodarska in podnebna negotovost v ZDA Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Združenih državah Amerike med koronakrizo. Glasilo Društva ekonomistov Maribor, 1(2), 9–14. [6] Romih, D. (2021). Poslovna negotovost v Nemčiji in Združenih državah Amerike med koronakrizo. Glasilo Društva ekonomistov Maribor, 1(3), 11–15. [7] Ahir, H., Bloom, N., & Furceri, D. (2018). The World Uncertainty Index. http://dx.doi.org/10.2139/ssrn.3275033 [8] Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593– 1636. https://doi.org/10.1093/qje/qjw024 [9] Leiserowitz, A., Maibach, E., Rosenthal, S., Kotcher, J., Carman, J., Wang, X, Goldberg, M., Lacroix, K., & Marlon, J. (2021a). Politics & global warming, March 2021. Yale University in George Mason University. New Haven: Yale Program on Climate Change Communication. https://climatecommunication.yale.edu/publications/politics- global-warming-march-2021/ [10] Leiserowitz, A., Maibach, E., Rosenthal, S., Kotcher, J., Carman, J., Wang, X, Goldberg, M., Lacroix, K., & Marlon, J. (2021b). Public support for international climate action, March 2021. Yale University in George Mason University. New Haven: Yale Program on Climate Change Communication. https://climatecommunication.yale.edu/publications/public- support-for-international-climate-action-march-2021/ [11] Leiserowitz, A., Maibach, E., Rosenthal, S., Kotcher, J., Carman, J., Wang, X., Marlon, J., Lacroix, K., & Goldberg, M. (2021). Climate change in the American mind, March 2021. Yale University in George Mason University. New Haven: Yale Program on Climate Change Communication. https://climatecommunication.yale.edu/publications/climate- change-in-the-american-mind-march-2021/ [12] Gavriilidis, K. (2021). Measuring climate policy uncertainty. http://dx.doi.org/10.2139/ssrn.3847388 428 Ponovna raba vode v urbanih okoljih kot pristop odgovornega življenja Water Reuse in Urban Environments as an Approach to a Responsible Life Ana Vovk Oddelek za geografijo Filozofska fakulteta/Univerza v Mariboru Maribor, Slovenija ana.vovk@um.si POVZETEK površin, ki postajajo v mestih vse bolj pomembne tudi zaradi drugačnih potovalnih navad in omejitev gibanja, ki jih poznamo Naravni viri so vsebolj omejeni in zlasti mesta že občutijo na eni izpred nekaj časa zaradi korone [2]. strani pomanjkanje vode zlasti v sušnih delih leta in na drugi strani viške vode v času močnih nalivov. Pozidva in neprepustne površine onemogočajo ponikanje vode in ponovno izhlapevanje, 2 ZBIRANJE IN ZADRŽEVANJE VODE zato se uvajajo sistemi za zadrževanje in ponovno rabo vode. V Pametno vodno gospodarstvo in družba bi morala upravljati z prispevku so predstavljeni izzivi urbanih območij v smeri vsemi razpoložljivimi vodnimi viri (vključno s površinskimi, prilagajanja na podnebne spremembe s poudarkom na krožni rabi vode ter uporabi zelenih sistemov, s pomočjo katerih zadržujemo podzemnimi, odpadnimi in prečiščenimi vodami). S tem bi se deževnico in povečujemo ponikovalno in zadrževalno izognili pomanjkanju vode in onesnaževanju, povečali bi sposobnost tal in stavb ter neprepustnih površin, ki jih oprememo odpornost na podnebne spremembe, ustrezno obvladali tveganja, z zelenimi sistemi in tehnologijami povezana z vodo, in zagotovili, da se pridobijo vse koristne snovi, ki jih je mogoče pridobivati iz postopkov čiščenja odpadne KLJUČNE BESEDE vode ali so integrirane v vodne tokove. Preizkušeni ukrepi za Urbana območja, deževnica, krožno gospodarjenje, zeleni zadrževanje vode v urbanih območjih so zbiranje deževnice sistemi. (zbiranje deževnice iz streh, parkirišč), ki prinaša številne prednosti, kot so zmanjšanje močnih deževnih vplivov in ABSTRACT prispevanje k ohranjanju vode. V krožnem gospodarstvu ima tudi ponovna uporaba vode ključno vlogo, ki prinaša pomembne Natural resources are increasingly limited and cities in particular are already experiencing water shortages on the one hand, okoljske, socialne in gospodarske koristi. Poleg tega se lahko especially in dry parts of the year, and on the other hand, excess siva voda (odpadna voda iz kopalnic, pranja perila in kuhinj) ki so 50 do 80 % stanovanjskih odpadnih voda, široko upor water during heavy rains. Sealing and impermeable surfaces ablja za namakanje v mestnem okolju in za domače namene (kot je prevent water from sinking and re-evaporating, so water toaletna voda), kot tudi deževnica. retention and reuse systems are being introduced. The paper Tudi v Vodni direktivi so presents the challenges of urban areas in adapting to climate predvideni ukrepi za ponovno rabo vode [3], zlasti za urbana območja. change with an emphasis on circulating water use and the use of green systems to contain rainwater and increase the sinking and retention capacity of floors and buildings and impermeable surfaces equipped with green systems and technologies. KEYWORDS Urban areas, rainwater, circular management, green systems. 1 UVOD Z rastjo prebivalstva, urbanizacijo in gospodarskim razvojem, se povečujejo potrebe po sladki vodi v mestih po vsej Evropi. Hkrati podnebne spremembe in onesnaževanje prav tako vplivajo na Slika 1: Zeleni sistemi zbiranja vode v urbanih območjih [1] razpoložljivost vode za prebivalstvo v mestih. Voda v mestih postaja vse večji izziv, tako količina, kvaliteta, razpoložljivost, dosegljivost, preobremenjenost oskrbe kot tudi poškodbe 3 KROŽNO UPRAVLJANJE Z VODO kanalizacijskih sistemov. Zato so potrebni inovativni predlogi V mestih se vse večja pozornost daje krožnemu upravljanju z kako bodo lahko mesta še naprej zagotavljala sladko vodo svojim vodami. Poznamo šest ciljev upravljanja z vodami, to so: prebivalcem ter dolgoročno skrbeli za ohranjanje zelenih 429 Information Society 2021, 5–9 October 2021, Ljubljana, Slovenia Ana Vovk 1. reciklirati in ponovno uporabiti odpadno vodo; zbiralnikov. Za manjše uporabnike se uporablja večinoma vkop 2. povečati učinkovitost uporabe in distribucije plastičnih ali betonskih podzemnih zbiralnikov. vode; 3. zagotoviti dobro kakovost vodnih teles; Uporaba deževnice je vse bolj prioriteta za hlajenje z 4. zbiranje vode; izhlapevanjem v gosto naseljenih urbanih območjih. Zlasti 5. spodbujati večkratno uporabo vode in trajnost vlagoljubno rastlinstvo zadržuje veliko vode in količina tako voda; izhlapele vode v enem poletnem mesecu je podobna, kot je 6. ohraniti pretok v vodnih telesih. izhlapi iz drevesa, zato je umeščanje vlagoljubnih rastlin vse bolj pomemben blažilni ukrep [4]. V urbanih okoljih je pogosta težava preobremenitev kanalizacije, saj vse več padavin pade v zelo kratkem času. Prelivi kanalizacije Koristi zbiranja deževnice so večdimenzionalne: povzročajo negativne vplive na rastlinstvo in živalstvo, pa tudi - deževnica je razmeroma čista in njena kakovost je umrljivost rib. običajno dovolj za številno uporabo z malo ali celo brez čiščenja Če voda steče v kanalizacijo brez zadrževanja, se iz prometnih ; površin izperejo mikroplastika in težke kovine. Tak odtok tudi - deževnica ima nizko slanost in jo je mogoče ponovno uporabiti kjerkoli, kjer ej potrebna mehka voda, kot je vzpostavlja nenaravno vodno bilanco, saj se zmanjšuje proces za pranje perila, hlajenje in v industriji; lokalnega izhlapevanja in lokalnega polnjenja podzemne vode. - z deževnico lahko prihranimo do 50 % potrebe po vodi Zato so pomembni centralizirani izpusti deževnice z v gospodinjstvu; zadrževalnimi filtri v zemlji, ki blažijo izhlapevanje in odtok v - uporaba deževnice zmanjša stroške energije za hlajenje, saj 1 m3 deževnice, ki izhlapi, sprosti 680 kanalizacijo. kWh energije; - zbiranje deževnice pomembno zmanjša obremenitev odtokov na kanalizacijo in poplave v mestnih območjih; - zbiranje deževnice je prilagodljiva tehnologija, ki jo je mogoče zasnovati tako, da izpolnjuje skoraj vse zahteve; - prispeva k samooskrbi z vodo. S ciljem, da bi se urbana območja odločala za tovrstne projekte, smo pripravili v letu 2020 zbornik projektov za Mestno občino Maribor.1 V letu 2021 pripravljamo digitalno monografijo s z naslovom Slika 2: Trajnostni pristopi v urbanih okoljih za blaženje Inovativni predlogi za ponovno rabo vode v urbanih območjih, podnebnih sprememb [1] kjer nadgrajujemo ideje o možnostih odgovornega življenja v mestih. 4 VEČSTRANSKE KORISTI DEŽEVNICE Urbana območja so razvila prioritete pri upravljanju deževnice in 5 ZAKLJUČEK to so: Za implementacijo navedenih idej bi bilo potrebno narediti več 1. izogibanje novim pozidavam inširjenju mestnih sprememb tako v načrtovalnih kot v izvedbenih postopkih. površin; Seznami projektov, ki jih financirajo mestne občine v Sloveniji 2. zbiranje in uporaba deževnice na kraju samem; večinoma niso usklajeni z zahtevami po krožnem gospodarstvu 3. zadrževanje deževnice; in po trajnostno naravanih ukrepih z večfunkcijskimi učinki, ne 4. infiltracija (polnjenje podzemne vode); samo na infrastrukturo in ekonomijo, ampak na kvaliteto bivanja. 5. puščanje deževnice v vodno telo. Že prisotne podnebne spremembe bodo vse bolj zahtevale opisane spremembe, zato bi se morala znanost bolj vključiti v Za čiščenje deževnice se uporabljajo razni filtri, od mehanskih načtovanje strategij razvoja, kjer se načrtujejo tovrstni projekti. sesalnih filtrov, do navpičnih cevi za hitro preusmeritev v rezervoar. Plavajoči fini sesalni filtri zagotavljajo, da se deževnica črpa iz najbolj čistega nivoja rezervoarja in ne vsebuje 6 ZAHVALA mehanskih delcev. Mestni občini Maribor se zahvaljujemo za izvajanje projekta Voda in podnebne spremembe ter Ponovna raba vode v urbanih Sicer je na razpolago veliko različnih sistemov za zbiranje območjih v letih 2020 in 2021. deževnice, od različno velikih posod, do betonskih podzemnih 1 Dostopno na povezavi: http://okolje.maribor.si/data/user_upload/okolje/NVO/E_zbornik_voda_in_podne bne_spremembe_041120.pdf 430 Insert Your Title Here Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia 7 VIRI [1] Vovk, Ana. 2020. Voda in podnebna kriza. IPVO, Maribor. , 14. 9. 2021 [2] Vovk, Ana, Buheji, Mohamed, Davidović, Danijel. Re- interpretation of "sustainability" concept, in post- covid-19 period. International journal of management. 2021, vol. 12, iss. 2, str. 156-165, ilustr. ISSN 0976-6510. http://www.iaeme.com/MasterAdmin/Journal_uploads/IJM/VO LUME_12_ISSUE_2/IJM_12_02_016.pdf, DOI: 10.34218/IJM.12.2.2021.016. [COBISS.SI-ID 52048387] [3] Vovk, Ana, Motaln, Anja. Implementation of the Water directive in Slovenia : (selected cases). Acta geographica Bosniae et Herzegovinae. 2019, vol. 6, no. 12, str. 27-38. ISSN 2303-7288. https://drive.google.com/file/d/1OuVG4IuC6Utl7VdCI4V- wH4JQgVaejNE/view. [COBISS.SI-ID 25064456] [4] Vovk, Ana. Ekoremediacije in podnebne spremembe. Nazarje: GEAart, 2015. 130 str., ilustr., zvd. ISBN 978-961- 93683-5-0. [COBISS.SI-ID 277607424] 431 Uporaba programske opreme v zanki za izdelavo digitalnega dvojčka proizvodnega procesa Using Hardware in the Loop for Making a Digital Twin of Production Process Rok Belšak† Janez Gotlih Timi Karner Laboratorij za robotizacijo Laboratorij za robotizacijo Laboratorij za robotizacijo Fakulteta za strojništvo/Univerza Fakulteta za strojništvo/Univerza Fakulteta za strojništvo/Univerza v Mariboru v Mariboru v Mariboru Maribor Slovenija Maribor Slovenija Maribor Slovenija rok.belsak@student.um.si janez.gotlih@um.si timi.karner@um.si POVZETEK Eno močnejših podjetij za namene načrtovanj in vodenj digitalnih proizvodnih procesov je nemški SIEMENS, ki glede Programska oprema v zanki oz. ‘hardware in the loop’ se v na zahteve in obsežnost sistemov omogoča več programskih zadnjem času vse pogosteje uporablja v simulacijske namene, rešitev. Uporaba robotskih sistemov v avtomatizaciji kjer samo z enim programskim orodjem ne moremo simulirati proizvodnih procesov v industriji 4.0 se v splošnem zdi realno-fizikalnega modela proizvodnega procesa. Gre za nepogrešljiva, kar zahteva predvsem potrebo po kolaboraciji med integracijo programske opreme, istih, kot tudi različnih programskimi okolji različnih proizvajalcev. V omenjenem proizvajalcev, v eno simulacijo. Programski paketi tako proizvodnem procesu kontrole kakovosti pečice s pomočjo komunicirajo med seboj in si izmenjujejo podatke. V robota in industrijskega krmilnika se uporabljajo programska nadaljevanju bo predstavljena programska oprema v zanki za okolja podjejta SIEMENS in UNIVERSAL ROBOTS. namene načrtovanja in vodenja industrijskega procesa kontrole kakovosti pečice s pomočjo kolaborativnega robota in 1.1 UPORABA PROGRAMSKE OPREME industrijskega krmilnika. Programska oprema v zanki tako predstavlja digitalni dvojček proizvodnega procesa. Trenutno bistvo programske opreme v zanki je uporaba več specializiranih programov, kjer vsak program opravlja svojo KLJUČNE BESEDE dotično nalogo in si ob tem izmenjuje podatke z ostalimi okolji za celovito delovanje digitalnega sistema, saj trenutno še ne Programska oprema v zanki, proizvodni proces, SIMIT, TIA, poznamo programskega okolja, oziroma še ni toliko razširjen, ki PLCSim, NX MCD, URSim, WinCC bi omogočal gnezdene funkcije vse do sedaj potrebne ABSTRACT programske opreme. Using hardware in the loop is gaining on popularity for simulation purposes where only one hardware is not enough to simulate the real-world physics of the automation process. Hardware in the loop is used to integrate software or program packages of the same or different producers into one simulation. Program packages are integrated into the hardware in the loop for the purpose of planning and control of the automation process for quality control of the oven production line with the collaborative robot and industrial controller. Hardware in the loop represents the digital twin of the production process. KEYWORDS Slika 1: Primer uporabe programskih okolij digitalnega dvojčka [1] Hardware in the loop, production process, SIMIT, TIA, PLCSim, Slika 1 prikazuje primer uporabljene programske opreme v zanki NX MCD, URSim, WinCC za medsebojno komunikacijsko izmenjavo podatkov. Komunikacija poteka v realnem času med okolji za načrtovanje in avtomatizacijsko vodenje sistema (NX – MCD, SIMIT, 1 UVOD PLCSIM, TIA Portal in WinCC) ter simulacijskim okoljem za Napredek človeškega razvoja temelji na razvoju metod, ki programiranje industrijskega robota podjetja UR (URsim). olajšujejo potrebno delo za opravljanje nalog. Digitalni dvojček, z uporabo programske opreme v zanki, je ena izmed 1.1.1 NX – MCD. Je ena izmed razširitev programskega pomembnejših metod digitalnega razvoja, ki omogoča bistven okolja NX, ki se uporablja za simuliranje kompleksnih napredek v razvoju procesov in končnih produktov, lažjimi elektromehanskih sistemov in omogoča mehatronski pristop implementacijami idej ter manjšimi stroški testiranj razvitih razvoja sistemov. sistemov v dobi tako imenovane industrije 4.0. 432 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia R. Belšak et al. V enem orodju razvijamo sistem s podporo mehanskih, elektro parametre, ki so potrebni ob izvajanju. Vse izvršbe funkcij se in avtomatizacijskih sklopov. Vključuje fizikalni vmesnik, izvajajo v realnem času. podobno kot pri računalniških igrah, ki omogoča simulacijo fizikalnih pojavov, ki so primerljivi realnemu svetu. 1.1.2 SIMIT. Je platforma, na kateri lahko izvajamo simulacije, ki omogočajo celovite teste avtomatizacije projektov, kot tudi virtualno zaganjanje sistemov, strojev in procesov. Simulacijsko platformo uporabljamo tudi za usposabljanje operativnega osebja v realističnih okoljih. [1] 1.1.3 S7 – PLCSIM. Programsko okolje PLCSIM Advanced je platforma za simulacijo programirljivega logičnega krmilnika (PLK) S7-1500 in ET 200SP. Omogoča virtualno testiranje in upravljanje vseh funkcij realnega programirljivega logičnega krmilnika. 1.1.4 TIA Portal. Oziroma angl. »Totally Integrated Slika 2: Digitalni dvojček v času simulacije. Automation Portal« (prevedeno kot popolnoma integriran avtomatizacijski portal) nam združuje celotno avtomatizacijo Celoten proizvodni proces digitalnega dvojčka se izvaja po stroja, od digitalnega načrtovanja elementov do konfiguracije diagramu poteka, kot je prikazano na sliki 3. vseh naprav, v enotni sistem. 1.1.5 URsim. Je simulacijsko okolje za programiranje START industrijskih robotov podjetja UNIVERSAL ROBOTS (UR). Omogoča kreiranje programov gibanja, simuliranje in testiranje Vklop napajanja hitrostnih osi (MC_POWER) sistemov z industrijskim robotom v 3D okolju. Ukleščenje pečice Vklop vhodnega transporter Položajni osi 2 PROGRAMSKA OPREMA V ZANKI ja NE na mestu DA Za izvajanje simulacij režima digitalnega dvojčka lahko Izklop vhodnega Izdelek na DA izpostavimo eno izmed možnih konfiguracij uporabe programske Izhodni transporter vhodu celice signal start ja opreme v zanki. NE UR cikla Grafični prikaz virtualnega okolja kot tudi približek realnemu Vhodni signal okolju se definira v programu NX MCD, kjer se uvoženi CAD Začetni položaj celice konec UR modeli definirajo kot telesa. Tukaj se jim priredijo fizikalne cikla lastnosti (kinematika in dinamika) in se jih sintetizira v celico z Celica na izhodišču vsemi transportnimi in manipulacijskimi elementi. Aktivnim UR konec cikla NE & NE Izdelek na vhodu elementom se priredijo krmilni signali za komunikacijo z celice eksternimi okolji. DA Izpust pečice Platforma SIMIT se opredeli kot komunikacijski most med grafičnim prikazom MCD okolj HMI ukaz a, virtualnim krmilnikom Start Premik PLCSIM Advance z algoritmom vodenja in okoljem za izdelka iz celice programiranje robotskih rok UR – URsim. SIMIT deluje tudi kot Start cikla simulacijska platforma naprav (primer: motorni pogoni). KONEC CIKLA S7-PLCSIM deluje kot virtualni krmilnik na katerega se naloži Premik programski algoritem razviti v programskem okolju TIA Portal. izdelka v celico Za programiranje robotske roke se v dotičnem problemu uporabi okolje URsim, kjer se izdela algoritem izvajanja gibanja. Za Slika 4: Diagram poteka izvajanja kontrole pečice. doseganje vključitve človeka v času izvajanja virtualnega avtomatiziranega procesa se izdela vmesnik HMI. 4 DISKUSIJA Digitalni dvojčki, z uporabo programskih paketov v zanki, omogočajo naslednji korak v digitalizaciji postopkov razvojev 3 IZVAJANJE SIMULACIJ IN REZULTATI novodobnih industrijskih rešitev, ki zahtevajo fleksibilnost, strateško okretnost ob iskanju rešitev in pogojem nizkih tržnih Opisano konfiguracijo virtualno poženemo v programskem cen. Tako lahko podjetje že v fazi digitalnega načrtovanja okolju SIMIT, kar sproži simultan zagon vseh programov popolnoma pripravi projekt na lastno zmožnost in ob tem digitalnega dvojčka. Na Slika 2 so razvidna delovna okna predvidi in odpravi tako imenovane porodne krče, ki se pojavijo programskih okolij. Pri tem je smisel okolja MCD grafični prikaz ob razvoju in realizaciji novih produktov oziroma sistemov. virtualnega delovnega okolja (čim bolj primerljivo realnemu), Vendar je potrebno izpostaviti, da so rezultati digitalnih UR sim okolje predstavlja grafični prikaz izvajanja gibov dvojčkov pogojeni z optimizacijo in dovršenostjo modelov robotske roke in prikazan HMI vmesnik prikazuje definirane 433 Uporaba programske opreme v zanki za izdelavo digitalnega dvojčka proizvodnega proce Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia sa predstavljenega sistema, saj je odzivnost in kooperativnost programskih paketov odvisna od najmanjših podrobnosti, ki lahko v fizičnem svetu doprinesejo velik preobrat v odzivanju sistema. Večja dovršenost sistema ob tem zahteva tudi svoj davek v potrebni procesorski moči računalnika, kar pa se z razvojem naprednih in zmogljivih računalniških sistemov omili. Razviti koncept digitalnega dvojčka robotizirane demonstracijske celice v sklopu projekta ROBKONCEL je omogočil vpogled v zmožnosti in prednosti uporabe tehnologij virtualnih simulacij industrijskih sistemov. S tem se je modelirana robotizirana celica virtualno razvila v delujoč sistem, ki potrjuje ustreznost razvitih elementov in ustreznost izbrane robotske roke glede na zahteve projekta. Brez pomisleka lahko trdimo, da so sistemi digitalnih dvojčkov tehnologija prihodnosti, ki ne bo ostala le na zaslonih računalnikov. ZAHVALA Avtorji bi se radi zahvalili Ministrstvu za izobraževanje, znanost in šport ter Evropskemu skladu za regionalni razvoj, Naložba v vašo prihodnost, za finančno podporo. Ta raziskava je bila opravljena kot del projekta ROBKONCEL OP20.03530. VIRI [1] SIEMENS AG."Virtual commissioning and operator training with SIMIT." (2021) Dostopno na: https://new.siemens.com/global/en/products/automation/industry- software/simit.html [29. 6. 2021]. [2] Bernard Marr."What Is Digital Twin Technology - And Why Is It So Important?". (2017) Dostopno na: https://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital- twin-technology-and-why-is-it-so-important/?sh=741d55972e2a [29. 6. 2021]. [3] Cadcam LAB ."Digitalni dvojček." (2021) Dostopno na: https://www.cadcam-group.eu/sl/resitve/po-procesu/digitalna- preobrazba/digitalni-dvojcek-digital-twin/ [10. 9. 2021]. [4] SIEMENS AG - Andrej Lazović."S7-1500/S7-1500T - Motion webinar." (2021) Dostopno na: andrej.lazovic@siemens.com [9.3. 2021]. 434 Ocena tveganja in ukrepi za varno delo v sodelovalni robotiki Risk Assessment and Safe Working Measures in Collaborative Robotics Marko Jovanović† Ivan Rečnik SMM proizvodni sistemi d.o.o. SMM proizvodni sistemi d.o.o. Maribor, Slovenija Maribor, Slovenija marko.jovanovic@smm.si ivan.recnik@smm.si POVZETEK Sodelujoči roboti, ki lahko “čutijo” svojo okolico, ustvarjajo revolucijo ne le v svetu industrijske proizvodnje, temveč tudi v Postopek ocene tveganja je namenjen zaščiti delavcev v varnostnih zahtevah, povezanih z uporabo robotov. Čeprav so industrijskem okolju. V prispevku sta predstavljena postopka tovrstni roboti vse bolj priljubljeni in se tržijo kot varni, to še ne ocene tveganja v sodelovalnih robotskih celicah v primeru zmanjšuje varnostnih pomislekov, ki so povezani z uvedbo teh uporabe običajnega (industrijskega) robota in robota z omejeno robotov v industrijsko okolje. močjo in silo (sodelujočega robota). Celovito opravljen postopek ocene tveganja in ustrezna uporaba zunanjih varnostnih naprav omogočata uvajanje tako sodelujočih, kot tudi industrijskih 2 SPLOŠNA VARNOST ROBOTSKIH robotov v sodelovalne robotske aplikacije. PROIZVODNIH SISTEMOV KLJUČNE BESEDE Škoda, ki jo povzroči nesreča v delovnem okolju, ni omejena le na poškodbe delavca, ampak ima tudi finančne posledice v obliki Ocena tveganja, varnostni standardi, sodelujoči roboti stroškov zavarovanja, izgub v proizvodnji, poškodovanega ABSTRACT stroja, izgubljenih kupcev in celo izgube ugleda podjetja. Kadar je robot v istem okolju kot delavec vedno obstaja The risk assessment procedure is designed to protect workers in določena stopnja tveganja, ki se šteje za sprejemljivo. To raven an industrial environment. This paper presents the risk določajo različni parametri, povezani s stopnjo in verjetnostjo assessment in collaborative robotic cells in the case of a nastanka poškodbe delavca. Način, da ugotovimo, če je conventional (industrial) robot and a power and force limited potencialna nevarnost presegla sprejemljive varnostne standarde, robot (collaborative robot). A comprehensive risk assessment je izvedba ocene tveganja. Postopek ocene tveganja je sestavljen procedure and the appropriate use of external safety devices iz definiranja obsega sistema, ugotavljanja virov tveganja, allow the deployment of both collaborative and industrial robots ocenjevanja in vrednotenja tveganja ter izvedbe postopka in collaborative robotic applications. zmanjševanja tveganja. KEYWORDS 2.1 Varnostni standardi v robotiki Risk Assessment, Safety Standards, Collaborative Robots Varnostne standarde lahko opredelimo kot “standarde, ki so zasnovani tako, da zagotavljajo ukrepe, ki so potrebni ali primerni za preprečevanje nesreč in poškodb, pa tudi za zaščito 1 UVOD pred izpostavljenostjo nezdravim okoljskim in poklicnim Sodelovanje med človekom in robotom je odgovor na vse večjo dejavnikom” [1]. potrebo po prilagodljivi proizvodnji. Namen sodelovanja je Ena od organizacij, ki določa varnostne standarde, je združitev najboljših lastnosti ljudi in robotov v cilju Mednarodna organizacija za standardizacijo (ang. International zmanjševanja stroškov in časa proizvodnje. Z uporabo Organization for Standardization - ISO). Varnostni ISO standardi sodelovalnih aplikacij je mogoče izkoristiti prednosti človeka in so sestavljeni tako, da je standard najvišje ravni prva referenca robota za izboljšanje učinkovitosti, kakovosti, zmogljivosti, (raven A varnostnih standardov). Z nižanjem ravni standarda okolja zaposlenih, stroškov in časa proizvodnega cikla. Eno (varnostni standardi ravni B in C) pridemo do najbolj ključnih vprašanj na tem področju je varnost. specifičnega varnostnega standarda, ki v tem primeru velja za robote ali robotske naprave. †Corresponding author at SMM production systems Ltd., Jaskova 18, 2000 Maribor, Standard ISO 12100 (raven A) opredeljuje splošna načela, kot Slovenia sta ocena tveganja in zmanjšanje tveganja za vse vrste strojev. Permission to make digital or hard copies of part or all of this work for personal or Standard ISO 13849 (raven B) opredeljuje z varnostno povezane classroom use is granted without fee provided that copies are not made or distributed dele krmilnih sistemov. Standard ISO 10218 (raven C) pa je for profit or commercial advantage and that copies bear this notice and the full napisan za varnost na področju industrijske robotike. Ker je bil 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). prvotni standard ISO 10218 prilagojen za industrijske robote, ta Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia standard ni upošteval posebnosti sodelujočih robotov. Leta 2016 © 2020 Copyright held by the owner/author(s). 435 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Jovanović et al. je odbor Mednarodne organizacije za standardizacijo poleg certificiranja zagotavljajo ustrezno raven varnosti svojih naprav, revidiranih delov standarda ISO 10218 izdal tudi tehnično vendar to še vedno ne pomeni, da je ta varen glede na okolje, v specifikacijo ISO/TS 15066. Ta tehnična specifikacija se katerem obratuje. Zlasti pri industrijskih aplikacijah je uporaba osredotoča na aplikacije sodelujočih robotov in predstavlja tako raznolika, da je nemogoče, da bi proizvajalec robotov smernice za različne meritve hitrosti, sile in pritiska, ki so odobril vsak posamezen postopek. Tu pride na vrsto ocena dovoljene med neposrednim sodelovanjem človeka z robotom. tveganja, s pomočjo katere ocenjujemo varnost industrijske Dejstvo, da je sodelujoči robot certificiran kot varno orodje aplikacije kot celote in ne vsake naprave posebej. Postopek ocene ne pomeni, da je celotna celica samodejno varna. To pomeni, da tveganja je prikazan na sliki 2. mora ocena tveganja zajemati tudi celotno industrijsko delovno mesto, v katerega poleg robota sodijo tudi robotska prijemalka, predmeti manipulacije in ostale potrebne naprave in stroji. Osnova za takšno oceno tveganja so poleg tehnične specifikacije ISO/TS 150066 tudi standardi ISO 10218 (del 1 in 2), standard ISO 12100 in Direktiva o strojih 2006/42/EC. 3 OCENA TVEGANJA V SODELOVALNIH ROBOTSKIH CELICAH Ko večina ljudi govori o “sodelujočih robotih” (ang. Collaborative Robots) ali kobotih (ang. Cobots), imajo v mislih to, kar ISO/TS 15066 imenuje “roboti z omejeno močjo in silo” (ang. Power and Force Limited Robots) [2]. Roboti z omejeno močjo in silo so posebej zasnovani za skupno delo z ljudmi. Sila in navor se spremljata in v primeru stika se robot ustavi. Sodelujoči roboti so zasnovani tako, da delajo skupaj s človekom, vendar to niso nujno roboti z omejeno močjo in silo. Pri tem se upoštevajo tudi aplikacije, pri katerih z uporabo zunanjih varnostnih naprav ali tehnologij, standardni industrijski robot postane sodelujoči. Slika 2: Postopek ocene tveganja, vir [5] Oceno tveganja lahko opredelimo kot proces ugotavljanja, vrednotenja in ocenjevanja ravni tveganja v določeni situaciji, Določitev mej stroja oz. področja uporabe robotskega sistema njihove primerjave z merili in standardi ter določanja je opis konteksta uporabe stroja, ki zajema informacije o tipu sprejemljive ravni tveganja [3]. Osnova za oceno tveganja so robotske roke, orodij in ostalih naprav celice. Vse postopke, ki poleg tehnične specifikacije ISO/TS 150066 tudi standardi ISO vključujejo kakršno koli nevarnost definiramo v koraku 10218 (del 1 in 2), standard ISO 12100 in Direktiva o strojih prepoznavanja tveganja. Tako bodo v postopku ocene tveganja 2006/42/EC. analizirani različni gibi robota in ostalih naprav v sistemu pri Tehnična specifikacija ISO/TS 15066 določa sodelovalno opravljanju nalog glede na potencialna tveganja. Na podlagi varnost s podrobnejšimi informacijami o oblikovanju opravljene analize prepoznavanja tveganj je potrebno za vsako sodelujočega robotskega sistema. Na Univerzi v Mainzu v prepoznano tveganje določiti stopnjo izpostavljenosti tveganju Nemčiji so testirali tudi biomehanske omejitve človeka, rezultati oz. zahtevani nivo zanesljivosti delovanja varnostnih krmilnih pa zajemajo omejitve največje sile in pritiska za 29 delov telesa elementov (PLr – ang. performance level rating). Na podlagi (Slika 1). standarda ISO 13849-1, ta analiza uporablja tri različne parametre oz. elemente tveganja: resnost poškodb (S – ang. severity), pogostost izpostavljenosti nevarnosti (F – ang. frequency) in možnost izogibanja nevarnosti (P – ang. possibility). Slika 3 prikazuje omenjene elemente tveganja. Slika 1: Model telesa, vir [4] 3.1 Postopek ocene tveganja Slika 3: Elementi tveganja, vir [5] Da zagotovimo varnost delavcev, moramo pri načrtovanju in Postopek določanja stopnje izpostavljenosti tveganju vsebuje integraciji robotske celice upoštevati predpisane ISO standarde s ocenjevanje vsakega od treh parametrov s pomočjo diagrama, ki področja robotike. Proizvajalci robotov skozi postopek je prikazan na sliki 4 levo. 436 Ocena tveganja in ukrepi za varno delo v sodelovalni robotiki Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Predstavljena robotska celica se uporablja v procesu kontrole mehansko obdelanih odkovkov. Zaradi enostavnosti in preglednosti so v nadaljevanju prikazane le osnovne informacije posameznih korakov postopka ocene tveganja. 4.1 Sodelovalna robotska celica z industrijskim robotom – Splošne informacije Tloris postavitve sodelovalne robotske celice za kontrolo Slika 4: Diagram za določanje stopnje izpostavljenosti mehansko obdelanih odkovkov je prikazan na sliki 5. tveganju in nivoja zanesljivosti, vir [5] Nivo zanesljivosti delovanja varnostnih krmilnih elementov (PL – ang. performance level) je vrednost, ki se uporablja za opredelitev zanesljivosti z varnostjo povezanih delov krmilnega sistema, da izvajajo varnostno funkcijo v predvidljivih pogojih. Med zahtevanim nivojem zanesljivosti delovanja varnostnih krmilnih elementov (PLr) in nivojem zanesljivosti (PL – ang. performance level) obstaja povezava, ki je prikazana na sliki 4 desno. To pomeni, da če je ocenjena stopnja izpostavljenosti tveganju v celici visoka (PLr = high), moramo zagotoviti, da je nivo zanesljivosti delovanja varnostnih krmilnih elementov enak ali višji od d (v tem primeru d ali e). V naslednjem koraku postopka ocene tveganja je pomembno, da se zastavi vprašanje: Ali je tveganje sprejemljivo? V večini primerov je zaželeno biti v kategoriji nizkih (ang. low) ali zanemarljivih (ang. negligible) vrednostih tveganja, da se zagotovi varnost delavcev. Če je ocenjena vrednost tveganja v zaželenih kategorijah, potem je postopek ocene tveganja končan. Slika 5: Tloris postavitve sodelovalne robotske celice za Če ocenjena vrednost tveganja ni v zaželenih kategorijah, so kontrolo mehansko obdelanih odkovkov potrebni nadaljnji koraki. Če je tveganje visoko (ang. high) se je Osnovni gradniki sodelovalne robotske celice za kontrolo potrebno osredotočiti na tveganja in jih zmanjšati ali odpraviti. mehansko obdelanih odkovkov so: To pomeni, da je potrebno v robotsko celico vključiti varnostne ukrepe ali opraviti neko konstrukcijsko spremembo, da ta • industrijski robot, postane varna oz. manj tvegana. Ko se tveganja zmanjšajo, se je • robotsko prijemalo z namensko oblikovanimi prsti, potrebno vrniti v postopek ocene tveganj in ponovno dokončati • vhodni zalogovnik izdelkov, ki je postavljen na celoten postopek, da se zagotovi, da pravkar zmanjšano tveganje natančno določeno pozicijo na vhodni mizi, ne bo povzročilo novega tveganja. Ta postopek je ponavljajoč in • izhodni zalogovnik za izdelke brez napak, ki je ga je treba izvesti zelo previdno, pri čemer je treba preučiti in postavljen na natančno določeno pozicijo na izhodni ponovno pretehtati vsako morebitno tveganje. mizi, • izhodni zalogovnik za izdelke z napako, ki je postavljen na natančno določeno pozicijo na izhodni 3.2 Varnostne metode sodelovalnih operacij mizi, V tehnični specifikaciji ISO/TS 15066 so navedene 4 različne • kontrolni modul (3D sistem strojnega vida), metode za zagotavljanje varnosti med sodelovanjem: varnostno • zaščitna ograja, nadzorovano ustavljanje (ang. safety-rated monitored stop), • varnostna skenerja. ročno vodenje (ang. hand-guiding), nadzor hitrosti in ločevanja (ang. speed and separation monitoring) ter omejevanje moči in Zaporedje robotskih operacij v celici poteka po naslednjih sile (ang. power and force limiting). Metode se lahko uporabljajo korakih: ločeno ali pa je rešitev sestavljena iz kombinacije teh metod. Če • robot pobere izdelek iz vhodnega zalogovnika, je robot sodelovalen, to še ne pomeni, da je sodelovalna tudi • robot nato izdelek premakne do kontrolnega modula, v celotna celica in obratno. Dejansko se lahko za številne katerem se opravi kontrola izdelka, robot pri tem sodelovalne aplikacije uporabljajo običajni (industrijski) roboti. opravlja ustrezno pozicioniranje izdelka, • če se v kontrolnem modulu zazna napaka na izdelku, robot odloži izdelek v zalogovnik za izdelke z napako, 4 OCENA TVEGANJA IN UKREPI ZA v nasprotnem primeru robot odloži izdelek v VARNO DELO V SODELOVALNI zalogovnik za izdelke brez napake. ROBOTSKI CELICI Z INDUSTRIJSKIM ROBOTOM Naloga delavca v sodelovalni robotski celici je ročna zamenjava zalogovnikov v sodelovalnih območjih. V robotski V prvem primeru izvajanja postopka ocene tveganja je prikazana celici obstajata dve sodelovalni področji (obkroženo z zeleno sodelovalna robotska celica z industrijskim robotom. 437 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Jovanović et al. barvo na sliki 5): področje vhodnega zalogovnika in področje sistema in vrednost varnostne razdalje opozorilnih območij izhodnih zalogovnikov. Omenjeni področji sta opredeljeni tudi varnostnih skenerjev. kot nevarni območji, če se v njiju istočasno nahajata delavec in V obravnavanem primeru čas ustavitve sistema znaša 0,66 s, robot. Zaradi tega se za preprečevanje dostopa do nevarnih kar vpliva na vrednost varnostne razdalje, ki znaša 2551mm. območij uporabljajo zaščitna ograja (nepomično varovalo) in Na podlagi opravljene analize sklepamo, da lahko varnostni varnostna laserska skenerja (varovalne naprave). laserski skener MISC3 proizvajalca SICK (PL d) [6] uporabimo za preprečevanje hitrega približevanja nevarnemu območju 4.2 Opredelitev virov tveganja celice, saj najdaljša razdalja zaznavanja zaščitnega polja znaša 9 V sodelovalni robotski celici za kontrolo mehansko obdelanih m. odkovkov lahko kot vir tveganja opredelimo možnost, da se delavec hitro približa nevarnemu območju in stopi na pot premikajočemu se robotu, kot je prikazano na sliki 6. 5 OCENA TVEGANJA IN UKREPI ZA VARNO DELO V SODELOVALNI ROBOTSKI CELICI S SODELUJOČIM ROBOTOM V drugem primeru izvajanja postopka ocene tveganja je prikazana sodelovalna robotska celica s sodelujočim robotom. Namen uporabe te robotske celice je enak kot v prvem primeru. 5.1 Sodelovalna robotska celica s sodelujočim robotom – Splošne informacije Tloris postavitve sodelovalne robotske celice za kontrolo mehansko obdelanih odkovkov je prikazan na sliki 8. Slika 6: Opredelitev vira tveganja 4.3 Ocena tveganja in merila za vrednotenje Kot merilo za vrednotenje pri oceni tveganja se lahko uporabi diagram za določanje stopnje izpostavljenosti tveganju iz standarda ISO 13849-1 (Slika 4 levo). Postopek določanja stopnje izpostavljenosti tveganju z uporabo diagrama za določanje stopnje izpostavljenosti tveganju iz standarda ISO 13849-1 je prikazan na sliki 7. Slika 8: Tloris postavitve sodelovalne robotske celice za kontrolo mehansko obdelanih odkovkov Osnovni gradniki sodelovalne robotske celice za kontrolo mehansko obdelanih odkovkov so: • sodelujoči robot, • robotsko prijemalo z namensko oblikovanimi prsti, Slika 7: Postopek določanja stopnje izpostavljenosti • vhodni zalogovnik izdelkov, ki je postavljen na tveganju natančno določeno pozicijo na vhodni mizi, • izhodni zalogovnik za izdelke brez napak, ki je Po opravljenem postopku določanja stopnje izpostavljenosti postavljen na natančno določeno pozicijo na izhodni tveganju je ugotovljena visoka vrednost tveganja. Nivo mizi, zahtevane zanesljivosti za opisani primer je d. To pomeni, da se • izhodni zalogovnik za izdelke z napako, ki je mora v danem primeru opraviti še postopek zmanjševanja postavljen na natančno določeno pozicijo na izhodni tveganja. mizi, • kontrolni modul (3D sistem strojnega vida). 4.4 Postopek zmanjševanja tveganja Zaporedje robotskih operacij je podobno kot v prvem primeru. Za zmanjševanje tveganja se lahko uporabi ukrep b iz poglavja Naloga delavca ostaja enaka kot v prvem primeru. Za razliko od 4.3.4 standarda ISO/TS 15066, ki se glasi: »Zaščitni ukrepi, ki prvega primera je sedaj celotno delovno območje robotske celice preprečujejo dostop osebja do nevarnih območij ali nadzorujejo opredeljeno kod sodelovalno območje. To je doseženo zaradi nevarnosti tako, da jih omejijo do nivoja sprejemljivega tveganja integracije robota z omejeno silo in močjo v robotsko celico. V (npr. zaustavitev, omejitev sil, omejitev hitrosti ipd.) preden je danem primeru ni več posebno opredeljenih nevarnih območij, delavec izpostavljen nevarnosti«. Da lahko dosežemo zahtevani za katera bi bilo treba implementirati dodatne ukrepe za nivo sprejemljivega tveganja je treba izračunati čas ustavitve 438 Ocena tveganja in ukrepi za varno delo v sodelovalni robotiki Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia preprečevanje dostopa delavca. To še vedno ne pomeni, da je zmanjšamo na 140 N, kar bo znižalo stopnje izpostavljenosti robotska celica varna. Tudi v tem primeru je potrebno opraviti tveganju (Slika 11). postopek ocene tveganja. Zaradi enostavnosti in preglednosti so v nadaljevanju prikazane le osnovne informacije posameznih korakov postopka ocene tveganja. 5.2 Opredelitev virov tveganja V sodelovalni robotski celici za kontrolo mehansko obdelanih odkovkov lahko kot vir tveganja opredelimo možnost, da delavec nehote postavi roko na pot premikajočemu se robotu v operaciji odlaganja vilic na podstavek, kot je prikazano na sliki 9. Takšno tveganje lahko povzroči kvazistatični udarec ali zdrobitev. Slika 11: Postopek določanja stopnje izpostavljenosti tveganju 6 ZAKLJUČEK Postopek ocene tveganja je namenjen zaščiti delavcev, ki uporabljajo industrijske stroje. V primeru sodelovalne robotike se ocena tveganja izvaja za zagotovitev varnosti delavcev med izvajanjem sodelovalnih operacij v celotni robotski celici, v katero poleg robota sodijo tudi robotska prijemalka, predmeti manipulacije in ostale potrebne naprave in stroji. Ne glede na Slika 9: Opredelitev vira tveganja dejstvo, da proizvajalci sodelujočih robotov zagotavljajo varnostne zahteve za svoje naprave (PL=d), je še vedno potrebno 5.3 Ocena tveganja in merila za vrednotenje opraviti postopek ocene tveganja z upoštevanjem specifičnih Za izvedbo naloge preprijemanja izdelka mora robot najprej pogojev uporabe robota v delovnem okolju celice. odložiti izdelek na podstavek na mizi. Pri tej operaciji robot deluje s hitrostjo 2000 mm/s in ima največjo omejeno silo 250 N. ZAHVALA Spodnja površina izdelka znaša 2,15 cm2, kar lahko ustvari Ta raziskava je bila delno financirana s strani projekta pritisk 116 N/cm2. Za razliko od sile, pritisk pri tej nalogi ni ROBKONCEL (št. razvojno-raziskovalnega projekta 330-18- omejujoči dejavnik. Ker je sila od 250 N za 80 % višja od mejne 1123). vrednosti (140 N), določene v tehnični specifikaciji ISO/TS 15066, domnevamo, da lahko v tem primeru pride do poškodb LITERATURA zaradi prevelike sile. [1] Treasury Board of Canada Secretariat, 1993. Directives and Standards - Kot merilo za vrednotenje pri oceni tveganja se lahko uporabi General - Occupational Health and Safety. Available at: https://www.tbs- diagram za določanje stopnje izpostavljenosti tveganju iz sct.gc.ca/pol/doc-eng.aspx?id=13662 standarda ISO 13849-1 (Slika 4 levo). Postopek določanja [2] Belanger-Barette, M., 2016. Are Collaborative Robots Safe?. Available at: https://www.isa.org/intech-home/2016/july-august/features/iso-ts-15066- stopnje izpostavljenosti tveganju z uporabo diagrama za and-collaborative-robot-safety določanje stopnje izpostavljenosti tveganju iz standarda ISO [3] Association of International Wealth Management of India, December 2013. 13849-1 je prikazan na sliki 10. Certified Credit Research analyst (Level 2). Mumbai: Taxmann Publications Ltd.. [4] International Organization for Standardization (ISO), 2016. ISO/TS 15066: Robots and robotic devices - Collaborative robots. Geneve: ISO copyright office. [5] SMM d.o.o., 2010. QN7-05.7 Izdelava ocene tveganja, Maribor: SMM d.o.o.. [6] SICK AG, 2021. Safety Laser Scanners - microScan3, Waldkirch, Germany: SICK AG. Slika 10: Postopek določanja stopnje izpostavljenosti tveganju Po opravljenem postopku določanja stopnje izpostavljenosti tveganju je ugotovljena visoka vrednost tveganja. To pomeni, da se mora v danem primeru opraviti še postopek zmanjševanja tveganja. 5.4 Postopek zmanjševanja tveganja Da lahko dosežemo zahtevani nivo sprejemljivega tveganja je treba zmanjšati največjo silo, ki jo uporablja robot. To silo lahko 439 Detection of Scratches on the Surface of Metallic Objects Stefan Kalabakov Anže Marinko stefan.kalabakov@ijs.si anze.marinko@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Jože Ravničan Matjaž Gams joze.ravnican@unior.com matjaz.gams@ijs.si UNIOR Kovaška industrija d.d. Jožef Stefan Institute Zreče, Slovenia Jamova cesta 39 Ljubljana, Slovenia ABSTRACT industrial adoption of artificial intelligence (AI) is becoming more and more feasible [5], mainly thanks to the significant progress With today’s manufacturing throughput in mind, a fast and accu- in hardware computational resources. However, despite this, AI rate quality control stage is of extreme importance. This is why hasn’t been fully adopted in the quality control processes in many manufacturers are increasingly interested in using machines and industries. This paper aims to develop such a solution, which artificial intelligence to streamline their quality control processes. would utilize AI for quality control in the automotive industry, In this paper, we explore the possibility of building a pipeline more specifically, the detection of scratches on the surface of based on the use of line scanners, which produce 3D point clouds metallic objects. of objects with great detail, to detect scratches on their metal- lic surfaces. More specifically, we leverage a small sample base to establish the basic features of scratches and then use these 2 PROBLEM DEFINITION principles to build a larger artificial set of examples. Finally, we One of the goals of the ROBKONCEL project is to produce quality train a classifier using the artificial examples and evaluate its control pipelines for specific components produced by the com- performance on the few real-life objects which we were able to pany Unior. These pipelines have the goal of detecting several obtain. different imperfections, either on the surface of objects or in their dimensions. The components in question are manufactured for KEYWORDS the needs of several different automobile makers and as such quality control, scratch detection, point clouds are subject to extensive quality control measures. An example of one such object can be seen in Figure 1. The goal of the quality 1 INTRODUCTION control pipeline which will be presented in this paper is to de- tect scratches on one of the highly polished parts of the objects. Consumers rarely observe the manufacturing process of the items The system does not have to locate the detected scratches, but they use, but they are usually able to notice when there is a defect rather just sort the objects based on whether or not they pos- in the product. These defects can be limited to cosmetic damage, sess a scratch. In the past, we have explored the implementation however, they can also result in very significant malfunctions. of such a quality control system based on computer vision and In contemporary manufacturing processes, unanticipated errors vibrations, but those pipelines have not been able to produce occur more frequently than most people realize, which can be a adequate results [2]. In this study, we explore the possibility of significant cost for the company if the error is not spotted early using a line scanner to create a point cloud of the objects and enough. This is the reason why quality control (real-time defect run our analysis on that data. This also plays nicely with the fact detection) is an important part of modern manufacturing. Cur- that point clouds can also be used to measure the dimensions of rently, quality assessment is executed by human operators [3]. the objects with a high degree of accuracy. Even though people can generally perform these tasks better than machines, they are much slower. In addition, human opera- 3 DATA COLLECTION tors require capabilities and skills that usually take a long time to acquire, which is why they are hard to find and maintain in To solve the problem of detecting very thin scratches on a pol- the industry. In some applications, the quality assessment can be ished surface with additional artefacts, we decided to explore critical and dangerous. This is especially true in the automotive the option of creating high definition 3D scans of the objects industry which is at the heart of this study and for which we using a line scanner. The scanner in question is the LMI Gocator develop a quality control pipeline. All of the reasons mentioned 2330 which has a resolution of 0.044mm in the X direction and above are why automatic methods for quality control in the indus- 0.006mm in the Z direction. An image of the scanner and the axes try have received great interest in recent years [4][1]. Moreover, can be seen in Figure 2. To create the point clouds, the scanner was attached to a rail above the object being scanned and was Permission to make digital or hard copies of part or all of this work for personal moved along an axis which is perpendicular to the X and Z-axis or classroom use is granted without fee provided that copies are not made or shown in Figure 2. 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 Because this type of error does not occur very often, at the work must be honored. For all other uses, contact the owner /author(s). time of development we had access to only four objects which Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia contained a scratch on their polished cylindrical area and thus we © 2021 Copyright held by the owner/author(s). were able to produce only four point clouds on which a scratch 440 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Kalabakov et al. Figure 1: The object whose cylindrical polished surface we must examine for scratches Figure 3: A visualization of several point clouds which show real-life objects with a visible scratch on their metal- lic surface. 3.1 Data generation To perform any meaningful evaluation of our methods, we need to be able to have a set of point clouds on which we would tune the parameters of our algorithms and a separate set of point clouds on which we would test their accuracy. However, splitting the eight point clouds into two subsets would not yield satisfactory results. To this end, we opted to create tens of artificial examples that we would use to substantiate and evaluate our methods. The Figure 2: A diagram of the line scanner used to gather the first step in generating each artificial point cloud is to select one point clouds. of the previously mentioned point clouds without a scratch, to which we will later add a randomly generated imperfection. The next step is to add random noise to the point cloud. This is done was visible. In addition to this, we also scanned the surfaces of by moving each of the points by a maximum of 0.001mm in any four other objects which did not contain a scratch. The point direction. Adding random noise allows us to always end up with clouds for the four objects which contained a scratch can be seen a base that has not been previously used. At this stage, we have in Figure 3. In the images, the color of each point represents generated a surface that has not been previously seen and can be the reflectance value that the sensor measured at that place and used as an artificially generated (part of an) object which does ranges from blue, which represents a low reflectance value, to not contain a scratch. Finally, if we want to generate a surface red, which represents high reflectance values. with a scratch the following algorithm is used: As we can see from the point clouds on Figure 3, the scratches are irregular and sometimes very complex in shape. Scratches, (1) Choose two points on the generated surface. The line however, are always characterized by missing points as well as a between those points will be the one which passes through change in the value of the reflectance. The number of missing the center of the scratch. points seems to increase as we approach the scratch centre line. (2) Choose a point on that line which will represent the place Another important feature of a scratch that we noticed is that the where the scratch will be widest. width of the scratch is not constant along the entire length, that (3) Mark all points inside the circle defined with the center is, the scratch can be wider in one place compared to another. line as its diameter as potentially affected points. Finally, the reflectance values seem to be decreasing as we move (4) Iterate through the potentially affected points and remove from the area surrounding the scratch and towards the centre those points using some probability. The probability of line. As was pointed out to us by Unior, in the real world, the removing a point is based on the distance between the width of the scratches ranges between 0.15mm and 2mm. point and the line from step (1) as well if the point is 441 Detection of scratches on the surface of metallic objects Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia part of a circle defined around the point chosen in step (2). Points which are closer to the center line and which belong in the circle have a higher probability of being removed, while that probability decreases as they move away from the center line and towards the edges of the circle. The radius of the circle is chosen randomly for each scratch and ranges between 0.15mm and 2mm. (5) Iterate through all potentially affected points which were not removed in the previous step and lower their reflectance value using the same rule as the one for the probability of removal in step (4). Figure 5: A 2D representation of a point cloud, with the Z-axis information coded as pixel brightness. The area of Figure 4 shows a few examples of artificially generated sur- interest is the one in the green rectangle. faces with scratches. In total, 226 examples without a scratch and 214 examples with a scratch were generated. actually on the object but are only the result of the scanning process. Next, we make a binary image using a threshold at a value of 60. To decide on whether the selected area contains a scratch or not, we compare the image to an image of an error-free surface using a metric called the “structural similarity index”, which returns a value between 0 and 1. Finally, using the structural similarity index as the only fea- ture, we use a random forest classifier to differentiate between objects with and without a scratch. The training of this classifier is explained in the next section. 5 RESULTS The training of the above-mentioned classifier, which uses the structural similarity index as the only feature is done primarily using artificially generated surfaces with and without an error. In our first experiment, which deals with scratches whose width ranges between 0.5 and 2mm (higher end of the range), the classifier is trained and evaluated using 94 artificially generated surfaces without a scratch and 76 surfaces with a scratch. Half of Figure 4: A visualization of several point clouds which the examples in each category are taken as a training set and the show artificially generated surfaces with a visible scratch other half is used to evaluate the performance of the classifier. on their metallic surface. The confusion matrix for this experiment is shown in Table 1. As we can see, the classifier achieves a perfect score. 4 METHOD Table 1: A confusion matrix for the system when testing on artificial errors whose width ranges between 0.5 and Our method rests upon one of the features of scratches men- 2mm. tioned in Section 3, specifically the fact that scratches are always represented by an area with missing points. The first step of our method, is to reduce the dimensionality of the problem by remov- Predicted No error With error ing the Z-axis information of the point clouds. This creates a 2D True representation that can be viewed and processed as an image. In No error 47 0 fact, the Z-axis information is not completely lost and is used as With error 0 38 the brightness of the pixels in the images. This allows us to work with previously used and extensively tested tools compared to the ones used for 3D data analysis. In our second experiment we expand the range of scratch The second step, after reducing the dimensionality, is to select widths and they can now range between 0.15mm and 2mm. This the area in which we will perform our analysis. The 2D repre- experiment includes all of the artificial surfaces used in the pre- sentation of a surface, along with the area which is selected for vious experiment as well as 132 new surfaces without an error analysis, can be seen on Figure 5. We avoid the edges of each and 138 surfaces with an error. The scratch width of these new scan, because of the sparseness of points in those areas, which surfaces ranges between 0.15mm and 0.5mm. This new set of do not point to a scratch but rather to an intrinsic property of artificially generated surfaces brings the grand total to 440 (226 the scanning process. without a scratch and 214 with a scratch). As in the previous The third step is to use a median filter on this image with a experiment, half of the examples from each category were used 3x3 kernel which smoothes the image and removes the parabolic for training and half for evaluation. The confusion matrix of the lines visible on the surface, which are not scratches and are not classifier on the extended set can be seen in Table 2. 442 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Kalabakov et al. Table 2: A confusion matrix for the system when testing learning in smart manufacturing. Journal of manufacturing on artificial errors whose width ranges between 0.15 and systems, 48, 170–179. 2mm Predicted No error With error True No error 113 0 With error 1 106 In our final evaluation, the classifier was trained using all artificial surfaces and its performance was tested on the eight point clouds which were created by scanning real-life objects. The classifier achieved a perfect score. 6 CONCLUSIONS In this paper, we presented a methodology for detecting scratches on the surface of metallic objects by analysing their point clouds created using a line scanner. Based on our results, it seems that generating random artificial examples of the surfaces in question and using them to train a classifier is beneficial and produces adequate results. Based on the accuracy of the classifier alone it also seems that our pipeline is more than adequate for use as a tool in quality control processes. However, the method has one significant drawback in the time it takes to properly scan objects. It is our opinion that this time might be significant (especially if objects are large or need to be scanned from several angles) and cannot be overlooked, especially when the production through- put is high. ACKNOWLEDGMENTS Part of this research was done under and for the ROBKONCEL project. Additionally, this research was partly funded by the Slovene Human Resources Development and Scholarship Fund (Ad futura). Finally, the authors acknowledge the financial sup- port from the Slovenian Research Agency (research core funding No. P2-0209). REFERENCES [1] Fernando Gayubo, José Luis Gonzalez, Eusebio de la Fuente, Félix Miguel, and José R Perán. 2006. On-line machine vi- sion system for detect split defects in sheet-metal forming processes. In 18th International Conference on Pattern Recog- nition (ICPR’06). Volume 1. IEEE, 723–726. [2] David Golob, Janko Petrovčič, Stefan Kalabakov, Primož Kocuvan, Jani Bizjak, Gregor Dolanc, Jože Ravničan, Matjaž Gams, and Marko Bohanec. 2020. Detekcija napak na in- dustrijskih izdelkih. In Proceedings of the 23rd International Multiconference INFORMATION SOCIETY. Volume A, 27–31. [3] Anil Mital, M. Govindaraju, and B. Subramani. 1998. A comparison between manual and hybrid methods in parts inspection. Integrated Manufacturing Systems, 9, 344–349, 6. doi: 10.1108/09576069810238709. [4] Iker Pastor-López, Igor Santos, Aitor Santamaría-Ibirika, Mikel Salazar, Jorge de-la Peña-Sordo, and Pablo G. Bringas. 2012. Machine-learning-based surface defect detection and categorisation in high-precision foundry. In 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), 1359–1364. doi: 10.1109/ICIEA.2012.6360934. [5] Michael Sharp, Ronay Ak, and Thomas Hedberg Jr. 2018. A survey of the advancing use and development of machine 443 Infodemija: Etični vidik informiranja o COVID-19 Infodemia: Ethical Aspect of Informing About COVID-19 Franci Pivec Tvrtko M. Šercar IZUM IZUM Maribor, Slovenija Maribor, Slovenija franci.pivec@ext.izum.si tvrtko.sercar@ext.izum.si POVZETEK Infodemija je spremljajoč pojav pandemije COVID-19, ko se 1 INFORMIRANJE KOT NALEZLJIVA prvič v zgdovini pretežni del informacij pretaka po digitalnih BOLEZEN omrežjih. Še bolj kot v dobi tiska se kažejo podobnosti med COVID-19 je prva pandemija v zgodovini, pri kateri ima veliko širjenjem infekcij in informacij, kar lahko pomaga pri njegovem vlogo informacijska tehnologija. Njene zmogljivosti naj bi razumevanju in upravljanju. Soočeni smo z neobvladljivim prispevale k utrjevanju občutka varnosti, obveščenosti in obsegom in hitrostjo širjenja lažnih novic, zmotnih, zavajajočih povezanosti, toda soočili smo se z njenim nasprotnim in zlonamernih informacij, ki zaznamujejo dobo post-resničnosti delovanjem, ko spodkopava in ogroža ukrepanje za obvladovanje in post-žurnalizma. Pri iskanju poti do zaupanja vrednih pandemije. Že 20. februarja 2020 je generalni director WHO informacij je treba upoštevati čustvene, epistemološke, pravne in Ghebreyesus na Minhenski varnostni konferenci opozoril: “Ne etične kontekste in obnoviti sisteme ter orodja za evalvacijo borimo se zgolj z epidemijo, borimo se z infodemijo!” [1] kakovosti informacij. EU je za ta namen razvila izpopolnjene Sledeč Williamu Goffmanu [2], smo že pred desetletjem strategije upravljanja z zdravstvenimi informcijami ter izostrila pisali o pojavu, da se posebej v spletnem okolju informacije širijo etični kodeks boja z dezinformacijami. kot nalezljive bolezni. [3] Posamezniki, izpostavljeni epidemiji, so bodisi imuni na nalezljivo bolezen bodisi se lahko okužijo ob KLJUČNE BESEDE stiku z gostiteljem bolezni ali vektorjem. Enako je s širjenjem infodemija, infekcijski-informacijski processi, lažne novice, religijskih idej ali znanstvenih konceptov itd... [4] zmotne informacije, zavajajoče informacije, zlonamerne Odkritje podobnosti med infekcijskim in informacijskim informacije, informacijski konteksti, EU kodeks ravnanja z procesom je pripomoglo k lažjemu razumevanju narave dezinformacijami informacij, danes pa lahko informacijska znanost vrne uslugo in z informacijskimi modeli omogoči “jasnejšo predstavo o ABSTRACT socialnih vidikih prenosa infekcijskih bolezni.” [5] Končno so The infodemic is an accompanying occurrence to the COVID-19 infekcijske bolezni označene kot komunikabilne bolezni in pandemic, as for the first time in history, the majority of prepoznan process inficiranja je identičen krožnemu prenosu information is travelling through digital networks. Even more so informiranja: inficiran agent → dovzeten gostitelj → vstop → than in the times of print, there are similarities between spreading modus prenosa → izstop → zbiralnik. [6] Slabo je, če ljudje infection and information, which can help us understand and epidemijo dojemajo kot vreme in s strahom čakajo poročila, ali manage it. We are faced with an unmanageable amount and bo jutri dež ali sonce, namesto da bi zavzeli aktivno pozicijo kot speed of spreading fake news, misinformation, misleading je običajna v družbeni komunikaciji in jo danes IKT omogoča in information and mal-information, which are shaping the era of podpira v neprimerljivo večji meri kot kdajkoli doslej. Problem post-reality and post-journalism. When searching for a way pa nastane, če je družbeno informiranje moteno in je IKT towards trustworthy information, emotional, epistemological, zlorabljena kot v znanem škandalu Cambridge Analytica ob legal, and ethical contexts must be considered and the systems ameriških volitvah 2016. and tools for evaluating information quality must be renewed. Širjenje informacij kot nalezljive bolezni je splošni zakon, ki For this purpose, the European Union developed improved ga uporabljajo tudi v politični in ideološki sferi, in sicer za strategies for managing medical information and tightened the propagiranje svojih partikularnih interesov pod pretvezo skrbi za code of ethics for the fight against misinformation. splošno dobro. Epidemijo bolezni je treba brezpogojno preprečiti, pri epidemiji političnih informacij pa se ravna KEYWORDS drugače: krepi se zgolj imunost do alternativnih političnih idej, infodemic, infection-information processes, fake news, da bi se obdržala vladajoča struja in njena družbeno-gospodarska misinformations, disinformation, mal-information, formacija. Nosilci alternativnih ideologij v sodobni globalni informational contexts, EU Code of Practice on Disinformation neoliberalni partitokratski družbi so prvenstveno marginalizirane družbene skupine ter kritična inteligenca in enako kot z virusom, Permission to make digital or hard copies of part or all of this work for personal or je treba obračunati tudi z njimi. V času epidemije je najbolje to classroom use is granted without fee provided that copies are not made or distributed storiti kar obenem in v infodemijah se obe tendenci razvidno 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 prepletata. 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). 444 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Franci Pivec, Tvrtko M. Šercar Informacijska obolelost se navzven prikazuje kot Vprašanje je, kako te goljufive vsebine pridobijo legitimnost pri informacijsko onesnaženje t. j. hiperprodukcija in preobilica masah, kako postanejo njeno prepričanje, zakaj se resnica ne informacij. Informacij naj bi bilo preveč, kar je absurd, saj znanja veže več na objektivna dejstva? Očitno standardi in kriteriji v nikoli ni dovolj. V resnici gre za etični vidik in za zlorabo sodobnih kominkacijskih procesih, ki naj bi odločali o informacijske tehnoloije. Informacijsko onesnaževanje ja lahko kredibilnosti, niso več isti kot prej. Reference tradicionalnih zavestno delovanje, podobno hekerstvu in širjenju računalniških medijev so v času post-resničnosti izhlapele in javnost brez razmišljanja sprejema post-žurnalizem in post-faktičnost. virusov z namenom povzročanja škode. To je dejansko ozadje Porazdelila se je v algoritemsko tvorjene mnenjske mehurčke, od lažnih novic, napačnih informacij, zavajajočih informacij, katerih ima vsak svojo resničnost, podprto s filtriranimi dejstvi. zlonamernih informacij, sovražnega govora ipd. Kar je za enega resnica, je za drugega laž. Mehanizem te transformacije je začel razkrivati Jűrgen Habermas že v šestdesetih, ko je pojasnil razmerje med javnim mnenjem in 2 ZNAČILNOSTI INFODEMIJE družbenim prostorom, v katerem je možna kritika, obramba Infodemologija kot veda o determinantah in distribuciji lastnih idej, reflektiranje lastnega položaja v svetu ter avtonomno zdravstvenih informacij je znana že nekaj časa in je prisotna v odločanje. Nenadomestljivo vlogo pri oblikovanju javnega študijskih programih nekaterih medicinskih fakultet, infodemija mnenja imajo mediji. [11] Če jim je sprva ustrezala ohlapnejša uredniška odgovornost in so se radi prelevili v “rumeni tisk”, ob pa pomeni ekscesno količino nepresejanih informacij, ki zaradi tem pa še izkoristili mnogo lagodnejše digitalne informacijske neobvladljivega obsega in hitrosti njihovega širjenja ogroža tehnologije, so kmalu ugotovili, da so jih te “izboljšave” požrle. družbo. Chris Zielinski [7] ugotavlja naslednje značilnosti Namesto, da bi formirali javno mnenje, so se začeli ozirati po infodemije: glede obsega informacij je nemogoče izslediti dominantnih mnenjskih mehurčkih, pripravljeni vstopiti v lokacijo izvora, ni jih mogoče v celoti zbrati in hraniti, težko je njihovo službo. S to naravnanostjo, ne morejo odigrati pametne identificirati njihovo kakovost, njihov vpliv je nepregleden, vloge v spoprijemu z infodemijo. težko je razkrinkati lažne novice; zaradi hitrosti objavljanja jih ni mogoče sproti analizirati, ni časa za njihovo izpodbijanje, nemogoče je vse korigirati, težko je slediti njihovemu toku in 3 POT DO ZAUPANJA VREDNIH skratka ni mogoče zaustaviti snežne kepe. Tri milijarde INFORMACIJ uporabnikov spleta hlepi po informacijah in pripravljeni so Lavinia Marin ugotavlja, da pri infodemiji COVID-19 ne klikniti prav vse, kar jim ponuja zaslon, za operaterje pa je to pomaga še tako skrbno (in takointako neizvedljivo) popravljanje denar – infosfera je padla na najnižje veje etičnosti svojega podatkov, saj jih večina ne razume, pač pa iščejo pojasnila o poslanstva in je ključni generator infodemije. [8] smiselnosti ukrepov proti pandemiji, ki jih potem iščejo pri Upravljanje z informacijami o COVID-19 je praktično povsem nekompetentnih virih. In še: “Eden od najbolj zatajilo in jih nikjer ne uspevajo sortirati, klasificirati, pregledati problematičnih vidikov infodemije je, da ustvarja preobilje in pretehtati, niti prilagoditi različnim avditorijem in informacij, ki povzroča informacijsko zasičenost in utrujenost odločevalcem. Čeprav so se glede tega s skupnim pozivom uporabnikov: njihova kapaciteta pozornosti je omejena in se hitro oglasile vse poklicane multilateralne organizacije (WHO, ZN, izčrpa.” [12] UNICEF, UNDP, UNESCO, UNAIDS, ITU, IFRC itd.), to ni Zavedati se moramo informacijskega konteksta, v katerem se pomagalo. V mesecu maju 2021 so bile sprejete obširne spoprijemamo z infodemijo in zanj je značilno, da je Smernice Evropske komisije za podkrepitev Kodeksa ravnanja z emocionalno inteziven, da teži k normativizmu, da pa je dezinformacijami iz leta 2018, ki ga je bilo treba po izbruhu epistemološko krhek. Ponudniki informacij to dobro vedo in COVID-19 konkretizirati in spodbuditi podpisnike (med njmi so večino sporočil rekontekstualizirajo na način, prilagojen Facebook, Google, Twitter, Mozila in TikTok) k doslednejšemu omenjenim značilnostim, zato informacije razvlečejo, skrivijo ali ukrepanju. [9] predelajo, neredko povsem na novo sfabricirajo. Formighieri Giordani s sodelavci [10] opredeljuje naslednje Manipuliranje čustev ima že ustaljeno strokovno ime značilne pojave infodemije: “empatična optimizacija”, razpolaga s celim spektrom - lažne novice (fake news), ki so običajno neavtorizirane preizkušenih orodij in Facebook je v primeru COVID-19 dodal in imajo namen prevare, pojavljajo pa se kot satire, le še nekaj emotikonov. Normativistična preokupacija je parodije, fabrikacije, manipulacije, propaganda, povezana z dokazovanjem, da je “naša” država naredila več kot reklama, lahko tudi kot irelevantne vesti; “druge” in potem se opisi razglašajo za predpise in raziskovalne - zmotne informacije (misinformation), ki so nenamerne, hipoteze o aerosolih za osnovo kaznovanja tekačev po parkih, napačno razumljene ali tolmačene informacije, v katere jasno pa je tudi, da je nacionalni pravni okvir nezadosten in so njihov razširjevalec bolj ali manj trdno verjame; potrebni mednarodni dogovori. Epistemološke težave izhajajo že - zavajajoče informacije (disinformation), namerno iz tega, da družbena omrežja niso narejena za razširjanje znanja, napačne, da bi nekomu povzročile škodo in ga prizadele ampak za klepet in zabavo, pri COVID-19 pa so postala za ali povzročile splošno zmedo, pogosto podložene še s večino glavni vir zdravstvenih informacij, ki jih večinoma ne teorijami zarote; razumejo, jih pa na veliko delijo z drugimi. Vsak si najde svojega - zlonamerne informacije (mal-information), namerno “eksperta” ali pa kar pri samem sebi nenadoma odkrije tako potvorjene in neposredno kot orožje naperjene na zmožnost. posameznike ali manjšine, tipična pa sta sovražni govor S kakovostjo informiranja o COVID-19 nima problemov le in rasizem. laično, ampak tudi strokovno obveščanje. Recenzijski postopki in drugi načini evalviranja kakovosti zdravstvenih informacij beležijo resne zdrse. HONcode (Health on the Net Foundation 445 Infodemija: Etični vidik informiranja o COVID-19 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Code of Conduct), certificira spletne strani na podlagi 8 točk sporočila, omogočajo uporabnikom dostop do kvalitetnih virov etičnega kodeksa: ugleda, celovitosti, zaupanja, pravičnosti, itd.. Kodeks EU ne priporoča arbitrarnega umikanja potencialno prispevanja, transparentnosti, finančne neodvisnosti in politike zavajajočih informacij, če ne vsebujejo sovražnega govora, ne reklamiranja. Od vzorca 110 spletnih strani, ki so 2/2 2020. kršijo zakonskih predpisov in nimajo značaja prevare. Vendar obravnavale “koronavirus”, bi le dve dobili etični certifikat. tudi EU nudi “popuste” za ponudnike e-storitev, ki imajo manj JAMA Benchmarks vrednoti avtorstvo, vsebinski prispevek, kot milijon dostopov mesečno v zadnjih dveh letih, ali manj kot finančno neodvisnost in pravočasnost. Le 10 % istih spletnih 25 milijonov evrov letnih prihodkov – noben problem za strani o koronavirusu je ustrezalo vsem štirim kriterijem, 40 % prilagoditev konfiguracije firm s slabimi nameni. pa ni izpolnjevalo niti enega. Google rank, ki algoritemsko Infodemija kot sinonim poplave zmotnih informacij in lažnih izračunava hierarhično pozicijo spletne strani, je le dvema vsebin postane veliko tveganje, ko zajame nazore o zdravju, o priznal mesto med prvimi desetimi. Webside Categorization je preventivnem ravnanju in o javnem zdravstvu. Posledice so med 110 spletnimi stranmi, ki so obravnavale koronavirus le 2 smrtne in družbo nepreklicno potiskajo v vseobsegajočo krizo. prepoznal kot “medicinski”. [13] Protislovno čvekanje po družbenih mrežah ruši vsakršno Pri HONcode se je po poročanju Zielinskega (isti vir) zgodilo zdravstveno doktrino in z razvrednotenjem znanja in znanosti še nekaj hujšega, da se je vanj vtihotapilo ok. 200 proticepilskih napoveduje distopijo tragičnih razsežnosti. spletni strani, kar je ogrozilo celotno shemo in razvrednotilo njen Ob nedorečenosti slovenske strategije spopada z infodemijo, etični kodeks – temu se reče onesnaženje lastnega gnezda. preostane trdnejša naslonitev na EU in njeno strategijo boja z Kontaminiranih je 8.000 spletnih strani, ki so po letu 1995 prejele dezinformacijami. [14] “Kriza zaradi COVID-19 je pokazala certifikat HONcode. WHO je znova pred problemom, kako ključno vlogo svobodnih in neodvisnih medijev kot bistvene zagotoviti domeno najvišje ravni (TLD – top level domain), ki bi storitve, saj državljanom zagotavljajo zanesljive in preverjene zagotavljala verodostojne zdravstvene informacije in bi bila informacije, ki prispevajo k reševanju življenj” (str.11). vredna zaupanja. Zdravstveni in farmacevtski kapital bo naredil Vzpostavljena je EDMO – Evropska opazovalnica digitalnih vse, da do take nepodkupljive domene ne pride. medijev (https://edmo.eu/), ki naj bi dobila tudi slovensko V informacijski zmedi glede COVID-19 sta se izoblikovala izpostavo, a ima že sedaj o razmerah pri nas bistveno natančnejšo dva pola: znanstveni in oporečniški. Znanstvena stran se trudi sliko kot si kdo predstavlja, zanimajo pa jo pobude za vzpostaviti konsenz znotraj znanstvene skupnosti in zagotoviti spodbujanje verodostojnosti vsebin in za izboljšanje neoporečnost informacijskih virov na podlagi načel ozaveščenosti uporabnikov, aktivno razkrivanje transparentnosti, reproduktibilnosti in kontrolibilnosti dognanj. manipulativnega vedenja družbenih medijev in podatki o tokovih Opredeljen je klinični sprekter bolezni, vključno s prevencijo. oglaševanja s pomočjo dezinformacij o COVID-19. Sprotno Oporečniška stran pa se navezuje na neresnične informacije in na spremlja tudi raziskave o dezinformacijah v povezavi s COVID- teorije zarote. Zanika vse, kar odkriva znanost, COVID-19 je 19 v članicah EU, pri čemer 2 raziskavi (od 76) zajemata tudi zanjo običajna gripa, kar ne opravičuje ukrepov kot so maske, Slovenijo, vendar med 115 raziskovalci ni nikogar iz naše omejitev gibanja, zapiranje fitnesov, prazne nogometne stadione države. [15] itd.. Zagovarja pa vse mogoče pripravke za “zgodnjo zaščito”, tudi gospodinjska čistilna sredstva in kot povzema Zielinski, je REFERENCE bilo zabeleženih 5.800 hospitalizacij na tej osnovi ter najmanj [1] World Health Organization. 1st WHO Infodemiology Conference. 2020. 800 smrti. Oporečniška fronta je široka, saj vključuje številna https://www.who.int/news-room/events/detail/2020/06/30/default- calendar/1st-who-infodemiology-conference. retrogradna gibanja, ki zagovarjajo ploščatost zemlje, splošni [2] William Goffman, 1965. An epidemic process in an open population. antiintelektualizem, so aktivni anti-semiti in zanikajo holokavst, Nature, 205, 4973, 831-832. se identificirajo za neofašiste, svarijo pred večkulturnostjo in so [3] Tvrtko-Matija Šercar, 2012. Informacijska ekologija (2. del članka Plaidoyer za prenovljeno teorijo informacij). Organizacija znanja, 17 (3) zagrizeni proticepilci. Kriza legitimnosti oblasti, poglabljanje 105-123 . nezaupanja, zavračanje meritokracije, razkroj javnih sistemov in [4] Tvrtko-Matija Šercar, 1988. Komunikacijska filozofija znanstvenih časopisa. Globus institucij že dlje časa odpirajo prostore za takšne retrogradne [5] Caroline Buckee, Abdisalan Noor & Lisa Sattenspiel, 2021. Thinking procese, zato ni mogoče govoriti o kakšnem presenečenju. clearly about social aspects of infectious disease transmission. Nature, Za predinternetne medije je samoumevno, da morajo prevzeti 595, 8 july 2021, 205-213. [6] Communicable Diseases Module: 1. Basic Concepts in the Transmission pravno in moralno odgovornost za vsebine, ki jih objavljajo. Pri of Communicable Diseases. internetu take odgovornosti ni več, ker pravo raje gleda stran ali https://www.open.edu/openlearncreate/mod/oucontent/view.php?id=848 &printable=1 pa odgovornost opredeljuje zelo približno. Ameriški [7] Chris Zielinski, 2021. Infodemic and infodemiology: a short history, a Communication Decency Act (1966) izrecno navaja (razdelek long future. Rev Panam Salud Publica 45, 2021 https://doi.org/10.26633/RPSP.2021.40 230), da niti ponudnik niti uporabnik internetne storitve nista ne [8] Debanjan Benrjee in K. S. Meena, 2021. COVID-19 as an “Infodemic” in izdajatelj, ne prednašalec informacije, tudi ko gre za zlonamerno Public Health: Critical Role of the Social Media. Front. Public Health, 18. laganje. V Nemčiji kličejo na odgovornost posredovalce marec 2021. https://doi.org/10.3389/fpubh.2021.610623 [9] European Commission, 2021. Communication from the Commission to sovražnega govora, ki ga je treba v 24 urah odstraniti, toda le v the European Parliament, the Council, the European Economic and Social primerih digitalnih platform z več kot 2 milijona uprabnikov. Committee and Committee of the Regions, 26. 5. 2021. COM (2021) 262 final. Leta 2018 je EU sprejela Kodeks ravnanja z dezinformacijami, [10] Rubia Carla Formighieri Giordani, Joao Pedro Giordano Donasolo, ki obvezuje naslovnike, da nadzirajo pojavljanje lažnih novic Valesca Daiana Both Ames in Rosselane Liz Giordani, 2021. The science online. Med drugim je prepovedano financiranje spletnih strani, between the infodemic and other post-truth narratives: Challenges during the pandemic. Ciencia & Saude Coletiva, 26 (7), 2863-2872. ki zavestno delijo lažne, senzacionalistične ali zarotniške [11] Jűrgen Habermas, 1989. Strukturne spremembe javnosti. Studia informacije na način, da nadzorujejo lažne račune, jamčijo Humanitatis – FF/ŠKUC [12] Lavinia Marin, 2020. Three contextual dimensions of information on uporabnikom transparetnost, označujejo politična propagandna social media: lesson learned for the COVID-19 infodemic. Ethics and 446 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Franci Pivec, Tvrtko M. Šercar Information Technology, 26. avgust 2020. https://doi.org/10.1007/s10676- [14] Evropska komisija, 2020. Boj proti dezinformacijam v zvezi s COVID-19 020-09550-2 – Kaj je res in kaj ne. 10/6 2020. JOIN (2020) 8 final [13] J. Cuan-Baltazar, J. Munoz-Perez, C. Robledo-Vega, M. Perez-Zepeda, E. [15] P. Bak, M. Sørensen., J. Walter in R. Bechmann, 2021. IV. D. A.: Soto-Vega, 2020. Misinformation of COVID-19 on the internet: Academic research on disinformation at scale in the EU. Aarchus: EDMO Infodemiology Study. JMIR Public Health Surveill 2020; 6 (2) el 18444. report IV. D. A. 447 448 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek G Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume G Vzgoja in izobraževanje v informacijski družbi Education in Information Society Urednika / Editors Uroš Rajkovič, Borut Batagelj http://is.ijs.si 8. oktober 2021 / 8 October 2021 Ljubljana, Slovenia 449 450 PREDGOVOR Soočamo se z velikimi spremembami v procesih vzgoje in izobraževanja, ki jih je povzročila epidemija COVID-19 ob širokem razmahu uporabe informacijsko-komunikacijske tehnologije. Upamo, da bo v prihodnjih letih prevladovala šola v živo, kar pa ne pomeni, da se bomo povsem vrnili na stare tirnice. Rešitve pouka na daljavo so pokazale tudi pozitivne plati. Upravičeno govorimo o smiselnosti hibridnih modelov poučevanja in spremembah v vsebini in metodiki dela. Podobno kot lanska bo tudi letošnja konferenca Vzgoja in izobraževanje v informacijski družbi 2021 potekala na daljavo. Pogovarjali se bomo o različnih rešitvah in spoznanjih, kako si lahko v bodoče pomagamo s sodobno tehnologijo pri prenosu znanja. Izkušnje minulih let nas ne bodo vodile v stanje pred epidemijo ampak nas bogatijo in vodijo v renesanso vzgoje in izobraževanja v novi realnosti. Vabimo vas, da se aktivno udeležite konference Vzgoja in izobraževanje v informacijski družbi 2021, da predstavite svoje poglede in izkušnje ter da skupaj snujemo našo prihodnost. Uredniški odbor FOREWORD We are facing grand changes in the educational processes caused by the COVID-19 epidemic and the widespread use of information and communication technology. We hope that direct face-to-face education will prevail in the coming years, but that does not mean that things will be completely as they were. Distance learning solutions have also shown positive sides. It is reasonable to talk about the significance of hybrid teaching models and changes in the content and methodology of work. Similar to last year, this year's conference Education in Information Society 2021 will be held online. We will discuss various solutions and insights into how we can help ourselves in the future with contemporary technology in the processes of knowledge transfer. The experiences of the past years will not lead us to the state before the epidemic, but enrich us and lead us to a renaissance of education in a new reality. We invite you to actively participate in the conference Education in Information Society 2021, to present your views and experiences, and to plan our future together. Editorial board 451 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 452 Branislav Šmitek, Univerza v Mariboru, Fakulteta za organizacijske vede Srečo Zakrajšek, Fakulteta za medije RECENZENTI / REVIEWERS Alenka Baggia, Univerza v Mariboru, Fakulteta za organizacijske vede Jelka Bajželj, Šolski center Kranj, Višja strokovna šola Branka Balantič, Šolski center Kranj, Višja strokovna šola Zvone Balantič, Univerza v Mariboru, Fakulteta za organizacijske vede 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 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 Iztok Škof, Osnovna šola Toma Brejca Kamnik Alenka Tratnik, Univerza v Mariboru, Fakulteta za organizacijske vede 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 Anja Žnidaršič, Univerza v Mariboru, Fakulteta za organizacijske vede Jasmina Žnidaršič, Univerza v Mariboru, Fakulteta za organizacijske vede 453 454 Poučevanje elektronike z uporabo spletnega programskega okolja Tinkercad Teaching electronics using online software Tinkercad Jaka Albreht Šolski center Kranj, Srednja tehniška šola Kidričeva 55, 4000 Kranj, Slovenija jaka.albreht@sckr.si POVZETEK Tinkercad, which allows us to create and simulate electronic circuits. The paper presents the implementation of practical Učitelji smo se med epidemijo morali prilagoditi na poučevanje exercises in the Tinkercad environment and their comparison na daljavo. Poseben izziv nam je predstavljalo poučevanje with the actual implementation in the laboratory. The advantages praktičnega pouka strokovnih modulov. Pri praktičnem delu and disadvantages of the Tinkercad environment and our modula Digitalna tehnika poučevanje poteka v laboratoriju, kjer experience with it are also given. We were also interested in the imajo dijaki dostop do elektronskih elementov in vse feedback of students or their opinion on such a way of working potrebne opreme. Ker so bile šole zaprte in pouk, ki smo ga remotely. To this end, we conducted a survey. The results show običajno izvajali, ni bil mogoč, je bilo potrebno poiskati that most students find the Tinkercad online environment very alternativo, ki bi bila primerna za poučevanje na daljavo. Odločili useful, but the vast majority still prefer to work in a laboratory or smo se za spletno okolje Tinkercad, ki nam omogoča izdelovanje workshop. Our findings show that Tinkercad is an excellent tool in simuliranje elektronskih vezij. V prispevku je prikazana that has successfully enabled the teaching of practical electronics izvedba praktičnih vaj v okolju Tinkercad in njihova primerjava lessons. Nevertheless, it cannot fully replace practical work in z realno izvedbo v laboratoriju. Podane so prednosti in school and can only serve as a welcome addition. pomanjkljivosti okolja Tinkercad ter naše izkušnje z le-tem. Zanimala nas je tudi povratna informacija dijakov oz. njihovo KEYWORDS mnenje o takšnem načinu dela na daljavo. S tem namenom smo izvedli anketo. Rezultati kažejo, da se večini dijakov zdi spletno Electronics, distance learning, practical lessons, Tinkercad okolje Tinkercad zelo uporabno, vendar ima kljub temu velika večina še vedno raje delo v laboratoriju oz. delavnici. Naše 1 UVOD ugotovitve kažejo, da je Tinkercad odlično orodje, ki je uspešno omogočalo poučevanje praktičnega pouka elektronike. Kljub Zaradi pojava epidemije in posledično dela na daljavo je bilo temu pa ne more v polnosti nadomestiti praktičnega dela v šoli potrebno spremeniti način poučevanja. Poseben izziv je in lahko služi zgolj kot dobrodošla dopolnitev. predstavljalo poučevanje praktičnega pouka elektronike. Pri praktičnem delu strokovnega modula Digitalna tehnika dijaki KLJUČNE BESEDE spoznavajo integrirana vezja. Na testni plošči povezujejo Elektronika, poučevanje na daljavo, praktični pouk, Tinkercad elektronske elemente in testirajo delovanje vezij. Delo običajno poteka v namenskih učilnicah oz. laboratorijih, kjer je na voljo ABSTRACT vsa potrebna oprema kot so npr. merilni instrumenti, testne We teachers had to adapt to distance learning during the plošče, elektronski elementi in računalniki z ustrezno epidemic. A special challenge for us was teaching practical programsko opremo. lessons of professional modules. In the practical part of the Zaradi nezmožnosti dela v šoli je bilo potrebno poiskati Digital Electronics module, teaching takes place in a laboratory, primerno aplikacijo, ki bi nam omogočala učinkovito poučevanje where students have access to electronic elements and all the na daljavo. Obstajajo različna programska okolja s katerimi necessary equipment. Since the schools were closed and the lahko simuliramo elektronska vezja kot so npr. SimulIDE, lessons we normally conducted were not possible, it was Simulator.io, Circuito.io, Fritzing, EveryCircuit, Wokwi, necessary to find an alternative that would be suitable for Tinkercad. Vsako okolje ima svoje prednosti in slabosti. Iskali distance teaching. We opted for the online environment smo aplikacijo, ki vsebuje vse elemente, ki jih potrebujemo za izvedbo vaj. Aplikacija mora biti enostavna za uporabo in mora čim bolj realistično prikazovati uporabljane elemente. Permission to make digital or hard copies of part or all of this work for personal or Pomembno nam je bilo tudi to, da se simulacija izvaja kar na 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 spletu in aplikacija ni plačljiva. 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). Pri nekaterih okoljih kot npr. Wokwi [1] lahko zgolj Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia spreminjamo obstoječe primere, tako da popravljamo © 2021 Copyright held by the owner/author(s). programsko kodo. Pomanjkljivost je tudi to, da ni mogoča uporaba »drag and drop« elementov, ampak je potrebno 455 spreminjati kodo v Java Script. Veliko naštetih okolij se osredotoča predvsem na uporabo mikrokrmilniških razvojnih plošč, ne pa tudi na simulacijo različnih integriranih vezij, ki jih pri pouku uporabljamo. Po hitrem pregledu in primerjavi vseh možnosti nas je najbolj prepričalo okolje Tinkercad. V nadaljevanju je opisan potek poučevanja z uporabo spletnega okolja Tinkercad in izkušnje, ki smo jih pri tem pridobili. 2 POUČEVANJE V OKOLJU TINKERCAD Tinkercad je spletno okolje, ki nam omogoča izdelavo 3D modelov, testiranje programske kode in simuliranje elektronskih vezij. Istoimensko podjetje Tinkercad (Slika 1) je bilo ustanovljeno leta 2010 z namenom izdelave preprostega programa, ki bi omogočal 3D modeliranje, dostopno širši populaciji. Leta 2011 je bila postavljena tudi spletna stran Tinkercad [2]. Le-ta omogoča, da v spletnem okolju izdelujemo Slika 3: Prikaz nekaterih elektronskih elementov 3D modele, testiramo programsko kodo ali sestavljamo in 2.2 simuliramo elektronska vezja. Za naše potrebe smo se omejili na Izvedba praktičnega dela strokovnega izdelovanje in simuliranje elektronskih vezij. modula Digitalna tehnika Praktični del modula Digitalna tehnika je razdeljen na tri sklope. V prvem sklopu dijaki spoznajo integrirana vezja, ki vsebujejo logična vrata. Na testni plošči (breadboard) testirajo delovanje. Slika 4 prikazuje izvedbo vaje v spletnem okolju Tinkercad, Slika 5 pa izvedbo v realnosti. Pri tej vaji smo testirali delovanje integriranega vezja 7408, ki vsebuje logična vrata IN (AND). Slika 1: Tinkercad logotip 2.1 Kako začeti? Na spletni strani se prijavimo z elektronskim naslovom ali Google računom. Izberemo novo delovno površino kjer bomo sestavljali vezje (Slika 2). Vsi elektronski elementi (Slika 3) in oprema je na voljo na desni strani delovne površine. Slika 4: Testiranje integriranega vezja v okolju Tinkercad Slika 2: Začetna stran okolja Tinkercad Slika 5: Testiranje integriranega vezja v realnosti Element s klikom in potegom preprosto prenesemo na delovno V drugem delu dijaki sestavijo kompleksnejše vezje in sicer površino. Elemente povežemo med seboj in poženemo dekadni števec s prikazovalnikom. V tem primeru je potrebno simulacijo. Če želimo spreminjati vezje, je potrebno ustaviti povezati več elementov. Na Sliki 6 vidimo simulacijo v okolju simulacijo. Povezavam, ki predstavljajo žice je mogoče Tinkercad, na Sliki 7 pa prikaz izvedbe vaje v šoli. spreminjati tudi barvo, zaradi česar je vezje bolj pregledno. 456 Slika 6: Simulacija dekadnega števca s prikazovalnikom v okolju Tinkercad Slika 7: Prikaz dekadnega števca s prikazovalnikom v realnosti Tretji sklop vaj je namenjen spoznavanju programirljivih vezij. Dijaki uporabljajo razvojno ploščo Arduino UNO [3] na kateri je mikrokrmilnik Atmega328. Poleg povezovanja vhodno-izhodnih Slika 9: Programska koda v okolju Tinkercad elementov je potrebno napisati tudi programsko kodo. Spletno okolje Tinkercad nam omogoča tudi pisanje programske kode, ki Oglejmo si še izvedbo vaje v šoli (Slika 10). V tem primeru je se nato v okviru simulacije izvaja na razvojni plošči Arduino bila programska koda napisana v programskem okolju Arduino, UNO. Možno je tudi izbrati grafični način programiranja, ki ki je bilo predhodno nameščeno na računalniku. Program s Slike vključuje različne funkcijske bloke, ki jih povezujemo med seboj. 11 smo, po uspešnem prevajanju, preko povezave USB naložili na mikrokrmilnik in opazovali delovanje. Slika 8: Arduino UNO v okolju Tinkercad Na Sliki 8 je prikazana simulacija delovanja razvojne plošče Arduino UNO. Na njo so priključene svetleče diode (LED) s Slika 10: Arduino UNO v realnem okolju predupori. Programska koda na Sliki 9 povzroči postopno prižiganje in ugašanje svetlečih diod. 457 3 REFLEKSIJA Zanimalo nas je kakšne so bile izkušnje dijakov s spletnim okoljem Tinkercad, zato smo jih prosili, da izpolnijo kratko anketo. Glede na to, da so anketo reševali med počitnicami lahko razpolagamo le z manjšim vzorcem (N=10). Najprej smo jih prosili naj ocenijo uporabnost okolja Tinkercad pri delu na daljavo (Slika 12). Večini se zdi okolje uporabno, kar se je videlo tudi med samim poučevanjem saj je ta način dela večina lepo sprejela. Slika 12: Rezultati ankete (uporabnost okolja Tinkercad) Zanimalo nas je tudi ali je uporaba spletnega okolja Tinkercad pripomogla k večjemu navdušenju nad elektroniko (Slika 13). Mnenja glede tega so deljena. Zanimanje za elektroniko je težko v večji meri pripisati le vplivu ene aplikacije. Slika 13: Rezultati ankete (vpliv okolja Tinkercad na zanimanje za elektroniko) Slika 11: Programska koda v okolju Arduino Podali so nam tudi svoje videnje prednosti in slabosti 2.3 Delo na daljavo omenjenega okolja, kar prikazuje Tabela 1. Dijaki so prepoznali V času epidemije smo se na šoli odločili, da poenotimo orodje za veliko prednosti spletnega okolja, prav tako pa se zavedajo tudi poučevanje in komuniciranje z dijaki. Izbrali smo aplikacijo nekaterih pomanjkljivosti. Microsoft Teams [4], ki nam je omogočala uspešno delo na daljavo. Pouk smo v največji meri izvajali preko videokonferenc. Dijaki so pri praktičnem pouku modula Digitalna tehnika med Tabela 1: Prednosti in slabosti okolja Tinkercad po mnenju videokonferenco ob učiteljevi razlagi sestavljali in preizkušali dijakov elektronska vezja v spletnem okolju Tinkercad. V primeru nejasnosti oz. težav so lahko delili svoj zaslon, kar se je izkazalo Prednosti Slabosti za zelo uporabno. Učitelj je nato opozoril na morebitne napake v Možno je delo od doma Ni dela na realnih komponentah vezju. Na ta način so se tudi ostali dijaki naučili, na kaj je treba Lažje se odpravi težave Ni na voljo vseh elementov biti pozoren in kje se lahko pojavijo napake. Nekateri dijaki so Ne moremo ničesar uničiti Potreben je zmogljiv računalnik tudi sami sodelovali pri odkrivanju napak v vezjih svojih Lažje razumevanje vezij sošolcev. Brezplačna aplikacija Dostopno povsod kjer je internet Vse komponente delujejo 458 Na koncu pa so podali svoje mnenje glede tega, kateri način Do aplikacije dostopamo kar preko spleta, prav tako nam ni učenja jim je bliže (Slika 14). Velika večina ima kljub vsem potrebno nameščati namizne aplikacije. Vse naše delo se shrani prednostim, ki jih ponuja okolje Tinkercad, še vedno raje v računu s katerim smo se prijavili. Z elektronskimi praktični pouk v šoli. komponentami lahko poljubno eksperimentiramo, brez skrbi, da bi kaj uničili ali se sami poškodovali. Zaradi izkušenj z delom v virtualnem okolju lažje preidemo na realno izdelovanje vezij na testni plošči. Kot pomanjkljivost bi izpostavili to, da je potrebno imeti internetno povezavo, saj zgolj namizna aplikacija še ni na voljo. Poleg tega nimamo fizičnega stika z elektronskimi elementi, kar posledično pomeni, da ni realnih problemov kot npr. slab stik, nedelujoče komponente, motnje ipd. Pri virtualnem delu se ne razvija fine motorike, ne uri se ročnih spretnosti pri sestavljanju elektronskih vezij. Prav tako ne rešujemo realnih Slika 14: Rezultati ankete (primerjava realnega dela in problemov, saj je simulacija vedno zgolj približek realnosti. simulacije Tinkercad) Menimo, da najboljše rezultate pri poučevanju dosežemo s kombinacijo spletnega okolja in praktičnega dela, 4 ZAKLJUČEK zato lahko okolje Tinkercad služi kot dobrodošla dopolnitev pri Spletno okolje Tinkercad se je med poučevanjem na daljavo poučevanju praktičnega pouka elektronike. Nikakor pa ne more izkazalo za odlično izbiro. Predvsem dobro se je obneslo v v polnosti nadomestiti dela v laboratoriju oz. delavnici. kombinaciji z videokonferencami znotraj aplikacije Microsoft Teams. VIRI Kljub temu, da so že dijaki podali svoje videnje [1] Wokwi. Dostopno na naslovu https://wokwi.com (9. 9. 2021) prednosti in slabosti spletnega okolja pa si vseeno oglejmo še [2] Spletno okolje Tinkercad. Dostopno na naslovu https://www.tinkercad.com (27. 7. 2021) naše izkušnje. Med prednosti lahko uvrstimo naslednje. V [3] Razvojna plošča Arduino. Dostopno na naslovu https://www.arduino.cc primerjavi s profesionalnimi programi za simulacijo in 3D (27. 7. 2021) [4] Microsoft Teams. Dostopno na naslovu modeliranje je Tinkercad relativno enostaven za uporabo. https://www.microsoft.com/microsoft-365/microsoft-teams (27. 7. 2021) Uporabljamo ga lahko zastonj in ne potrebujemo nobenih licenc. 459 Izzivi izvedbe praktičnega izobraževanja na višjih strokovnih šolah v pogojih COVID-19 Challenges of the implementation of practical education at higher vocational schools in the conditions of COVID-19 Branka Balantič Zvone Balantič Šolski center Kranj Univerza v Mariboru Višja strokovna šola Kranj Fakulteta za organizacijske vede Kidričeva 55, 4000 Kranj Kidričeva 55a, 4000 Kranj branka.balantic@sckr.si zvone.balantic@um.si POVZETEK ABSTRACT Pandemične razmere COVID-19 so ustvarile povsem nova The COVID-19 pandemic situation has created completely new izhodišča pri delovanju družbe in v vseh njenih spremljajočih starting points in the functioning of the society and in all its vitalnih mehanizmih. Poleg osnovnih življenjskih vrednot je v accompanying vital mechanisms. takih pogojih potrebno poskrbeti tudi za delovanje vseh ostalih sistemov, med katere spada tudi izobraževanje s celovitim in In addition to the basic values of life, in such conditions it is korektnim funkcioniranjem vseh predpisanih in ustaljenih necessary to take care of the operation of all other systems, protokolov. Pri tem lahko izpostavimo tudi konkretne težave pri including education with the comprehensive and correct vzpostavitvi in tekoči izvedbi obveznega praktičnega functioning of all prescribed and established protocols. We can izobraževanja (PRI) na višjih strokovnih šolah (VSŠ). VSŠ also point out the concrete problems in the establishment and programi se v Slovenskem ogrodju kvalifikacij (SOK) nahajajo ongoing implementation of compulsory practical education / on na ravni 6/1. Programi so ovrednoteni s 120 kreditnimi točkami the job training (PE/OJT - PRI) at higher vocational schools (KT) in trajajo 2 leti. Za doseganje ustreznih strokovno- (HVS - VSŠ). VSŠ programs in the Slovenian Qualifications teoretičnih kompetenc je zelo pomemben del študijskega Framework (SQF - SOK) are located at level 6/1. The programs procesa, ki vključuje PRI v podjetju in zajema 800 ur oziroma are evaluated with 120 credit points (ECTS - KT) and last for 2 traja 20 tednov. years. To achieve the appropriate professional-theoretical competencies, it is a very important part of the study process, V tem delu so v izobraževalni proces vključeni tudi mentorji iz which includes PRI in the company and covers 800 hours or lasts posameznih podjetij, s katerimi je potrebno vzpostaviti 20 weeks. interaktiven in delujoč komunikacijski kanal, ki smo ga v preteklosti realizirali s pomočjo obiska organizatorja PRI v In this part, mentors from individual companies are also included podjetju. V pogojih pandemije zaradi COVID-19 je prav na in the educational process, with whom it is necessary to establish področju tekočega spremljanja dejavnosti v okviru PRI prihajalo an interactive and functioning communication channel, which we do občasnih motenj v utečenem sistemu sodelovanja. Tako, kot realized in the past with the help of the PRI organizer's visit to večina komunikacije v tem obdobju je tudi tu potekala preko IKT the company. In the conditions of the pandemic due to COVID- in telefonskih pogovorov. 19, it was in the field of ongoing monitoring of activities within the PRI that there were occasional disturbances in the established Razvili smo nov model komunikacije z vključevanjem virtualnih system of cooperation. Like most communication in this period, obiskov organizacij, z izvedbo pogovorov z mentorji v podjetjih it also took place here through ICT and telephone conversations. in s študenti na dejanskih delovnih mestih. Povratne informacije povsem ekvivalentno sledijo rezultatom raziskav iz preteklih let. We have developed a new model of communication by including virtual visits to organizations, by conducting interviews with mentors in companies and with students in actual jobs. The KLJUČNE BESEDE feedback follows the results of previous years' research in exactly Praktično izobraževanje, COVID-19, mentor, študent, višja the equivalent way. strokovna šola KEYWORDS 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 Practical education, COVID-19, mentor, student, higher for profit or commercial advantage and that copies bear this notice and the full vocational school 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). 460 1. UVOD V sistemu izvajanja PRI gre za tripartitni odnos, v katerem Višje strokovno izobraževanje je osredotočeno na usposabljanje sodelujejo študenti s specifičnimi znanji, izkušnjami in visoko usposobljenih, aplikativno usmerjenih strokovnjakov, ki osebnostnimi lastnostmi, podjetja oz. različne organizacije z se zaposlujejo na vodilnih mestih proizvodnih ali storitvenih realnimi delovnimi okolji in ustrezno usposobljenimi mentorji ter oddelkov v podjetjih. Osnovno vodilo v VSŠ je stalno šola (org. PRI, predavatelji, vodstvo šole). [6]. izboljševanje kakovostnega izobraževanja s praktičnim V okviru PRI imajo študenti priložnost razvijati in utrjevati usposabljanjem in inovativnimi izobraževalnimi metodami. številne kompetence, kot so sposobnost organiziranja delovnega Sinteza vsega naštetega spodbuja razvoj individualnih praktičnih časa, reševanje realnih problemov, uporaba znanja v praksi … sposobnosti in zagotavlja njihov individualni razvoj. Pridobijo si sposobnosti ustne in pisne komunikacije (kjer je to V našem primeru skrbimo za razvoj teoretičnega znanja na pomembno, tudi v tujem jeziku). PRI mora biti usmerjeno tudi v področju informatike, skupaj s praktičnimi veščinami na tem razvijanje kompetence, kot so kritičnost, samokritičnost, delo v področju. Smisel PRI je v poglabljanju študentovega skupini, etičnost, samoiniciativnost, kreativnost, avtonomnosti razumevanja njihovega osnovnega strokovnega znanja, hkrati pa pri delu, podjetništvo, sposobnost prilagajanja novostim, skrb za jim daje dodatne možnosti spoznavanja realnega delovnega kakovost, sposobnost priprave in vodenja ali koordiniranja okolja v katerem bodo morda našli ali iskali svojo zaposlitev. projektov [1]. Vključevanje v sistem PRI običajno razkriva tudi posebnosti V izobraževalni proces so vključeni tudi mentorji iz posameznih osebnostnih značilnosti študentov in pokaže posameznih podjetij, s katerimi je potrebno vzpostaviti možnosti integracije v realna delovna okolja. Proučevanje interaktiven in delujoč komunikacijski kanal, ki smo ga v naštetih relacij je koristno tako za študenta, kot delodajalca, preteklosti realizirali s pomočjo obiska organizatorja PRI v mentorja v podjetju, VSŠ in seveda za razvijalca kurikuluma. podjetju. V pogojih pandemije zaradi COVID-19 je prav na Študenti se seznanijo s kompleksnimi nalogami, ki se izvajajo področju tekočega spremljanja dejavnosti v okviru PRI prihajalo v podjetjih in pri tem spoznajo praktične modele reševanja do občasnih motenj v utečenem sistemu sodelovanja. Tako, kot realnih izzivov. Temeljni namen višješolskega izobraževanja je večina komunikacije v tem obdobju je tudi tu potekala preko IKT torej prizadevanje za ustrezne odločitve in doseganje večje in telefonskih pogovorov. uspešnosti bodočih zaposlenih v realnih delovnih okoljih [1]. V EU se v okviru mreže višjih strokovnih šol izobražuje več kot 1,7 milijona ljudi. Ti programi so nastali na osnovi poklicnih 2. METODE standardov, ki so jih narekovale potrebe gospodarstva. Podoben Zaradi znanih pogojev dela v okviru pandemičnih omejitev, je sistem najdemo tudi v Sloveniji. Izobraževanje za pridobitev in bilo potrebno slediti novim idejam komuniciranja tudi na izpopolnjevanje javnoveljavne višje strokovne izobrazbe in omenjenem področju. Del študijskega leta 2019/20 in pretežni del študijskega leta 2020/21 sta potekali v posebnih okoliščinah, organizacijo višjih strokovnih šol (VSŠ) v Sloveniji ureja Zakon kjer je bil neposredni stik sodelujočih deležnikov praktično o višjem strokovnem izobraževanju (ZVSI) [2]. onemogočen. Tako, kot v večini primerov je bila vsa možna Višješolski programi (VSŠ) se v Slovenskem ogrodju dejavnost prenešena v virtualno okolje. V določenem začetnem kvalifikacij (SOK) nahajajo na ravni 6/1 [3, 4]. Programi trajajo obdobju pandemije so bile smernice še zelo nejasne, vendar so se 2 leti in so ovrednoteni s 120 kreditnimi točkami (KT). Za z razvojem dogodkov in spoznavanjem nevarnosti COVID-19, doseganje teh ciljev je zelo pomemben tisti del študijskega počasi spreminjale. Celotni šolski sistem je sproti dobival procesa, ki vključuje praktično izobraževanje (PRI) v podjetju in navodilo za delo is strani NIJZ [7], Ministrstva za izobraževanje, zajema 800 ur oziroma traja 20 tednov. znanost in šport MIZŠ [8], glede integracije PRI pa smo delo Normativne podlage za izvajanje PRI študentov v podjetjih koordinirali tudi v skladu s priporočili Ministrstva za opredeljuje Zakon o višjem strokovnem izobraževanju v 50. gospodarski razvoj in tehnologijo [9]. V navodilih za delo so bili opredeljeni grobi okviri, natančne smernice pa smo oblikovali v členu [2]. Zakon določa, da morajo šole sodelovati z delodajalci skladu z našimi idejami in širšimi priporočili. in da pogodbo o izvajanju PRI lahko sklenejo s tistimi delodajalci, ki imajo ustrezne prostore in opremo, katerih PRI je kljub zaostrenim delovnim pogojem potrebno izvesti poslovanje obsega dejavnost poklica, za katerega se študent na najvišjem možnem nivoju. Če želimo zagotoviti kakovost tega izobražuje, in imajo zaposlenega, ki je lahko mentor študentu. dela izobraževanja, je potrebno sprotno samoevalviranje vseh Podrobne pogoje, povezane s prostorom, opremo in mentorji, je izvedbenih elementov. Ključni členi pri samoevalvaciji PRI so določila Gospodarska zbornica Slovenije, ki tudi vodi register študenti, organizacije in mentorji v šolah in organizacijah. delodajalcev. Pridobljene informacije v okviru PRI so zelo pomembne, saj Izvajanje PRI spremlja in vodi mentor v podjetju v skladu z plemenitijo celotni formalni del izbranega programa, v katerem okvirnim programom za izvedbo PRI. Ob zaključku PRI mentor sodeluje posamezni študent. izdela ustrezno poročilo o opravljenem PRI študenta, v katerem Regulacijska sposobnost informacijskega sistema na poda oceno o PRI ter izpolni anketni vprašalnik o PRI, kar področju PRI za spodbujanje sinergije med pedagoškim in študent skupaj s svojim poročilom odda organizatorju PRI. poslovnim okoljem, je kompleksna. V letu 2020 je bil razvit VSŠ imajo izkušnje z načrtnim organiziranjem mreže model sporočilnih poti v sistemu sooblikovanja t.i. reflektivne podjetij, pri tem pa imajo posebej pomembno vlogo zaposleni v prakse v okviru PRI [1]. Zaradi jasno postavljenega sistema PRI podjetju, ki so mentorji študentom. Tak način partnerskega je bilo v danih pogojih moč dokaj nemoteno pristopiti k sodelovanja med šolo in podjetji je primerljiv z evropsko uspešno oblikovanju virtualnih obiskov organizacij, z izvedbo prakso in posebej primeren za področje strokovnega pogovorov z mentorji v podjetjih in s študenti na dejanskih izobraževanja, ki naj usposablja za potrebe konkretnih delovnih delovnih mestih. okolij [5] 461 Virtualni obisk podjetja je pomembna točka v razvoju medsebojnih tripartitnih odnosov v sistemu višješolskega izobraževanja, saj s tem vzpostavimo temelje nadaljnjemu sodelovanju, vzpostavimo sistem regulacijskega kroga med višjo šolo in podjetjem ter spodbujamo aktivno interaktivno sodelovanje med vsemi sodelujočimi. S pomočjo proučevanja kazalnikov smo želeli opredeliti dejansko stanje na področju izvedbe PRI in odkriti morebitne usmeritve za delo v prihodnjem obdobju. Ideja virtualnega obiska zahteva temeljite priprave pred izvedbo, zato smo ob vseh obiskih želeli pridobiti temeljne informacije v zvezi z izvedbo, ki bi jih lahko koristno uporabili ob morebitnem nadaljevanju ogroženosti s COVID-19 v naslednjem študijskem letu. Osredotočili smo se na vlogo mentorja v podjetjih in v ta namen pripravili anketni vprašalnik s Slika 1: Mnenje mentorja o pripravi in izvedbi PRI temeljnimi demografskimi vprašanji, s sklopom vprašanj v zvezi z opredelitvijo podjetja, z vprašanji o vlogi mentorja v podjetju in vprašanja v zvezi s povratno informacijo pri izvedbi PRI s Priprava in izvedba PRI je ključnega pomena za vse sodelujoče poudarkom na virtualnem obisku organizatorja PRI iz VSŠ. (slika 1) Praktično vsi kazalniki dosegajo zelo visoko povprečno oceno (4,64). Najnižjo oceno (4,3) beležimo pri oceni Študenti v tej raziskavi niso bili posebej vključeni. razpoložljivosti ostalih zaposlenih v podjetju za morebitna vprašanja študenta in pomoči pri vključevanju v delovni proces, 3. REZULTATI kar je razumljivo, saj študenti iz vidika vodenja podjetja in količnika cost/benefit predstavljajo določen izziv. Prispevek se ukvarja z evalvacijo virtualnega obiska organizatorja PRI v podjetju v okviru programa Informatika na V danih pogojih je bil virtualni obisk podjetja zanimiv izziv, VSŠ ŠC Kranj. V študijskem letu 2020/2021 je bilo na ki se je po naših optimističnih napovedih pokazal tudi kot opravljanje PRI v 2. letniku napotenih 38 študentov, ki so izjemno dobro sprejet pri mentorjih v podjetjih. opravljali PRI v 32 različnih podjetjih. V raziskavo smo uspeli Ocena virtualnega obiska organizatorja PRI v podjetju (slika vključiti 17 mentorjev iz nabora vseh sodelujočih podjetij. 2) praktično soglasno podpira idejo o virtualnem obisku podjetja V okolju Microsoft Teams smo oblikovali skupino v kateri so s strani organizatorja PRI iz šole (4,9). Mentorji v podjetjih tudi bili istočasno prisotni študent, mentor iz podjetja in organizator zelo visoko ocenjujejo pogovor med študentom, mentorjem in PRI. V okviru omenjene skupine smo izvedli klasični 15 – 20 organizatorjem PRI (4,7) in so prav tako zelo zadovoljni z min. pogovor, ki ga sicer opravimo tudi v normalnih usklajevanjem termina srečanja (4,7). Organizator PRI je tudi nepandemijskih časih. Pogovor poteka po običajnem dnevnem povsem izpolnil pričakovanja glede vsebine pogovora med redu, ki vključuje naslednje elemente: udeleženci (4,5). • izmenjava informacij o poteku PRI z usvajanjem kompetenc, • spremljanje in vrednotenje PRI študenta, • problematika v zvezi z dokumentacijo PRI (študent, mentor), • informiranje v zvezi z razpisom za sofinanciranje spodbud delodajalcev, ki izvajajo PRI študentov, • pogovor o morebitni izbiri teme diplomske naloge, • verifikacija učnih mest za študente na GZS, • pedagoško-andragoško usposabljanje mentorjev, • drugo (posebnosti, pripombe, pohvale . .), V raziskavi so sodelovali mentorji, ki prihajajo iz podjetij z do 10 zaposlenimi (55%), iz podjetij z 11-50 zaposlenimi (18%) in iz podjetij z 51-150 zaposlenimi (18%). Mentorji v podjetju svojo vlogo razumejo različno. Raziskava ugotavlja, da 64% mentorjev svojo vlogo razume kot sodelavca v študijskem procesu za praktični del pri ustvarjanju bodočega kadra, 27% mentorjev svojo vlogo vidi v organizatorju dela za novo delovno moč v delovnih procesih, 9% mentorjev pa svojo Slika 2: Ocena virtualnega obiska organizatorja PRI v vlogo vidi v "podaljšani roki" kadrovske službe pri iskanju podjetju potencialnega sodelavca. Mentorji so tudi zelo zadovoljni s časovnim obsegom obiska (15 do 20 minut). 91% mentorjev je bilo mnenja, da bi podoben način izvedbe obiska organizatorja PRI v podjetjih v prihodnje še nadaljevali. 462 4. RAZPRAVA Pri razpravi o nadgradnji modela, bi morali razmisliti še o Pandemija COVID-19 je vplivala na vse pore našega življenja, celovitem in zanesljivem sistemu izmenjave dokumentacije z posredno pa tudi na vse sisteme vezane v naš vsakdan. Naša uporabo verificiranih potrdil. Pričakujemo, da bo ta del logična tematika se je lotevala racionalnih rešitev, ki so bile potrebne za nadgradnja vseh zastavljenih sistemov v Digitalni Sloveniji [10]. rešitev problematike celovite izvedbe PRI v okviru VSŠ izobraževanja. Razumljivo je, da so nastale razmere zahtevale kompromisno delovanje v določenih okvirih, npr. zamiki 5. ZAKLJUČEK datumov odhoda študentov na prakso v posamezna podjetja. Pandemične razmere ob pojavu COVID-19 so nas prisilile, da Povsem nekaj drugega pa je premik / zamik / odlog 400 urnega smo praktično povsod začeli razmišljati "izven škatle" in bili bloka obveznih dejavnosti (PRI) v okviru izobraževanja na VSŠ prisiljeni uporabiti vse mogoče pripomočke za izhod iz nastale za posamezni letnik. Izobraževalni program Informatika ima že družbene slepe poti. Tudi v okviru izobraževanja so se pojavili po svoji strukturi velik potencial organiziranja dela na daljavo, nešteti izzivi, ki smo jih bili prisiljeni reševati. Razvili smo model kar so delodajalci in mentorji iz podjetij s pridom izkoristili. virtualnega obiska podjetij med izvedbo PRI na VSŠ in na ta Kljub dejstvu, da je veliko študentov delo v okviru PRI opravilo način uspeli vzpostaviti povsem ekvivalentno strukturo dela, ki tudi na daljavo, pa je za funkcionalno in delujočo strukturo PRI je bila običajna v nepandemijskem obdobju. Določene izkušnje nujno potrebno aktivno in soodvisno sodelovanje med študenti, bi veljalo obdržati in jih skladno z razvojem digitalizacije tudi mentorji v podjetjih in organizatorjem PRI v VSŠ. nadgrajevati. Na način, ki ga ponuja opisan model nismo izgubljali na kakovosti izvedbe, še več – v danih razmerah smo s pomočjo virtualnega obiska v podjetjih preizkusili drugačen model, ki ga 6. LITERATURA morda v običajnih razmerah ne bi uspeli realizirati v realnih [1] B. Balantič, „Evalvacija vsebinskih zahtevkov v regulacijskem krogu pogojih. PRI na VSŠ,“ v EKIF: izzivi prihodnosti, 1. mednarodna strokovna konferenca EKIF, Murska Sobota, 2020. Model virtualnega obiska smo izvedli preko orodja MST in [2] Ur. l. RS št. 86/04, „Uradni list Republike Slovenije,“ 2004. na ta način na daljavo obiskali mentorja in se istočasno povezali [Elektronski]. Available: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4093. s študentom na svojem delovnem mestu. V realnem svetu je [3] Ur. l.RS št. 104/15, „Uradni list Republike Slovenije,“ 2015. organizatorju PRI marsikdaj onemogočen dostop do dejanskega [Elektronski]. Available: delovnega okolja, kjer določeni študent opravlja PRI. Vzroki za http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO6958. [4] SOK, „Slovensko ogrodje kvalifikacij,“ marec 2020. [Elektronski]. prepoved vstopa v zaščiteno področje so različni (varnost in Available: https://www.nok.si/. zdravje pri delu, vnos nečistoč, segrevanje prostorov, [5] Jarc Kovačič, B., Balantič, B., „Učenje skozi delo - pridobivanje praktičnih znanj med študijem mehatronike,“ v Zbornik referatov 2. letne občutljivost delujočih sistemov, poslovne skrivnosti. .). Virtualni konference Kakovost v višjih šolah, Murska Sobota, 2010. obisk organizatorja PRI v podjetjih pa marsikdaj omogoči video [6] Balantič, B., Jarc Kovačič, B., Balantič, Z., „Model sporočilnih poti v in audio vstop v zaščitena področja, video vpogled v študentovo sistemu reflektivne prakse za spodbujanje sinergije med pedagoškim in poslovnim okoljem,“ Uporabna informatika, pp. 173-181, 2014. delo na njegovem dejanskem delovnem mestu itd. [7] NIJZ, „Dnevno spremljanje okužb s SARS-CoV-2 (COVID-19),“ 01 08 Raziskava potrjuje naše domneve o pozitivni afiniteti 2021. [Elektronski]. Available: www.nijz.si. [8] MIZŠ, „Koronavirus (SARS-CoV-2),“ 01 08 2021. [Elektronski]. mentorjev v podjetjih do obiska organizatorja PRI. Na virtualni Available: https://www.gov.si/drzavni-organi/ministrstva/ministrstvo-za- način je organizacija obiska bolj natančno določena in izobrazevanje-znanost-in-sport/. [9] MGRT, „Ministrstvo za gospodarski razvoj in tehnologijo,“ 01 08 2021. načrtovana. Delodajalci so zadovoljni, saj njihovi predstavniki – [Elektronski]. Available: https://www.gov.si/drzavni- mentorji v podjetjih za to dejavnost lahko namenijo manj organi/ministrstva/ministrstvo-za-gospodarski-razvoj-in-tehnologijo/. njihovega dragocenega časa. [10] Vlada RS, „Digitalizacija družbe,“ 01 08 2021. [Elektronski]. Available: https://www.gov.si/teme/digitalizacija-druzbe/. Vsekakor ne smemo zanemariti velike prednosti klasične izvedbe obiska organizatorja PRI v podjetju, saj je osebna izmenjava mnenj in iskanje idej ter rešitev vsekakor boljša in zelo dobrodošla, toda tudi virtualni obisk je svojevrsten izziv, posebno če je izveden v okoljih, ki jih vključeni deležniki že dobro poznajo. 463 Skupinske oblike svetovanja na daljavo v času epidemije covid-19 – ugotovitve raziskav in praktične izkušnje Group telecounseling during the covid-19 epidemic – research findings and practical experience Tadeja Batagelj Svetovalni center za otroke, mladostnike in starše Maribor Maribor, Slovenija tadeja.batagelj@guest.arnes.si POVZETEK counseling to the Internet. Increased service user distress created an increased need for such treatment and professionals Izbruh epidemije covid-19 je v šolski prostor prinesel številne faced the change without clear guidelines and evidence of the nenadne spremembe, ki so zahtevale spremembe vzgojno effectiveness of the new ways of working. The purpose of this izobraževalnega procesa in prilagoditve vseh udeležencev le article is to highlight the theoretical findings of research into tega. Svetovalna služba kot pomemben povezovalni in group forms of counseling and therapeutic work at a distance svetovalni člen in podporne zunanje strokovne institucije, med and to present practical experiences and opinions of users of katerimi imajo pomembno vlogo svetovalni centri, so morali v such forms of work at Counseling Center Maribor. All the kratkem času spremeniti način delovanja in se iz svetovanja v findings presented lead to the conclusion that despite some živo preseliti na splet. Pri tem so se zaradi povečanih stisk pri limitations and the lack of theoretical evidence of effectiveness, uporabnikih storitev pokazale povečane potrebe po tovrstnih group counseling and therapeutic work by videoconferencing is obravnavah, strokovnjaki pa so se s spremembami soočali brez effective in practice and well received by users, which would jasnih smernic in dokazov o učinkovitosti novih oblik dela. make further introduction into counseling services in schools Namen prispevka je osvetliti teoretične ugotovitve raziskav and in supportive external settings useful. glede skupinskih oblik svetovalnega in terapevtskega dela na daljavo ter predstaviti praktične izkušnje in mnenja KEYWORDS uporabnikov tovrstnih oblik dela na Svetovalnem centru Maribor. Vsi predstavljeni rezultati vodijo do ugotovite, da je School counselors, group counseling, epidemic covid-19, skupinsko svetovalno in terapevtsko delo preko videokonferenc telecounseling kljub nekaterim omejitvam in ob pomanjkanju teoretičnih dokazov o učinkovitosti, v praksi učinkovit in pri uporabnikih 1 UVOD dobro sprejet način dela, za katerega bi bilo smiselno, da se v prihodnosti večji meri uvaja v svetovalne službe na šolah in v Epidemija covid-19 je v šolski prostor prinesla veliko podpornih zunanjih institucijah. negotovosti in sprememb. Na spremembe se ni bilo mogoče pripraviti vnaprej, zaradi česar je bilo prilagajanje še KLJUČNE BESEDE zahtevnejše. Pouk na daljavo, okrnjenost in spremenjenost Šolski svetovalni delavci, skupinsko svetovanje, epidemija vzgojno-izobraževalnega procesa so zahtevali hitre prilagoditve covid-19, svetovanje na daljavo tako učiteljev, kot učencev in staršev. V teh okoliščinah je bila vloga svetovalne službe izjemnega pomena. Njena temeljna ABSTRACT naloga je namreč, “da se na podlagi svojega posebnega The outbreak of the covid 19 epidemic brought about many strokovnega znanja preko svetovalnega odnosa in na strokovno sudden changes in the school environment, requiring changes in avtonomni način vključuje v kompleksno reševanje pedagoških, the educational process and adjustments by all involved. The psiholoških in socialnih vprašanj vzgojno-izobraževalnega dela school counselors, as a key link and counseling member, and v vrtcu oziroma šoli s tem, da pomaga in sodeluje z vsemi the supporting external professional institutions, among which udeleženci v vrtcu oziroma šoli in po potrebi tudi z ustreznimi counseling centers play an important role, had to change their zunanjimi ustanovami.” [10] mode of operation in a short period of time, moving from live Svetovalni center Maribor z namenom celostne in strokovne podpore uporabnikom intenzivno sodeluje tudi s svetovalnimi službami na šolah. Na Svetovalnem centru smo v času Permission to make digital or hard copies of part or all of this work for personal or epidemije covid-19 zaznali povečane potrebe po psihološki, 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 specialno-pedagoški in podobni podpori. Z namenom nudenja the full citation on the first page. Copyrights for third-party components of this podpore čim večjemu številu uporabnikov, smo želeli v kar work must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia največji meri ohraniti skupinske oblike dela. Zaradi ukrepov za © 2021 Copyright held by the owner/author(s). omejevanje gibanja in združevanja pa smo morali tako v 464 svetovalnih službah kot v Svetovalnih centrih začeti iskati nove nadomesti [4], kar velja tako za individualne kot za skupinske in izvirne pristope pri svojem delu. oblike dela. Raziskave na področju spletnih skupin so maloštevilne in potrebnih je več raziskav, da bi se raziskalo učinkovitost 2 SKUPINSKE OBLIKE DELA – IZZIVI IN tovrstnega načina dela za različne posameznike in vsebine. MOŽNOSTI V ČASU EPIDEMIJE COVID- Odprta ostajajo številna vprašanja kot so etična vprašanja, 19 vprašanja zaupnosti informacij in nevarnosti spleta, možnosti za Skupinsko svetovanje preko spleta je relativno nova modaliteta izgradnjo dobrega odnosa, vpliv odsotnosti očesnega stika in za vodenje skupin. Raziskave, ki bi evalvirale učinkovitost fizične bližine in podobno. Vse to so vprašanja, ki doprinašajo k skupinskih oblik dela preko spleta (kot so svetovanje, terapija, učinkovitosti skupinskih oblik dela in jih je potrebno ob delu na vodenje in podobno) ali postavljale jasne smernice za izvajanje daljavo še posebej nasloviti. tovrstnih oblik pomoči, so redke. Med številnimi strokovnjaki [6] je v preteklosti veljalo prepričanje, da je zaradi vseh 3 DELO SVETOVALNIH SLUŽB IN omejitev, ki jih tovrstna oblika dela prinaša, učinkovitost skupinskih oblik dela na daljavo okrnjena do te mere, da je pod ZUNANJIH STROKOVNIH INSTITUCIJ V vprašanjem upravičenost izvajanja tovrstnih oblik svetovanja in ČASU EPIDEMIJE COVID-19 terapije. Z izbruhom epidemije covid-19 pa je delo na daljavo Mrvar, Jeznik, Šarić in Šteh [4] navajajo: »Ob izbruhu postalo nuja in številne skupine so bile primorane svoja epidemije covida-19 se je življenje in delo v vzgojno- srečanja nadaljevati na način videokonferenc, hkrati pa so se izobraževalnih ustanovah v trenutku izjemno spremenilo. povečale potrebe po strokovni pomoči [7], zaradi česar so se Skupnost otrok, učencev oz. dijakov in strokovnih delavcev se oblikovale številne nove skupine. Tako je postalo nujno, da se je preselila v virtualni prostor.« Z namenom podpore so bila strokovnjakom, strokovnim delavcem v šoli in v zunanjih izdana priporočila za delo z uporabniki, izvedene pa so bile tudi strokovnih institucijah čim prej ponudi pregled raziskav in jasne raziskave o tem, kako se je način dela v času epidemije smernice za delo skupin preko spleta. Randomiziranih raziskav spremenil. na tem področju je sicer še vedno malo, dostopne ugotovitve pa so sledeče[14]: 3.1 Predlogi in priporočila za delo šolske - Udeleženci, ki so bili del spletnih skupin za svetovalne službe v času izolacije zaradi samopomoč, so poročali o večji opolnomočenosti. epidemije - Video-konferenčne skupine so izvedljive, učinki pa so primerljivi kot v skupinah, ki se srečujejo v živo. Kmalu po izbruhu epidemije covid-19 in selitvi vzgojno - Skupine, ki temeljijo na vedenjsko – kognitivnih izobraževalnega in svetovalnega dela na daljavo, sta se Zavod principih dosegajo podobne učinke, kot intervencije, RS za šolstvo in Oddelek za pedagogiko in andragogiko ki potekajo v živo, a je doseganje primerljivih Filozofske fakultete UL odzvala na novo nastale razmere in rezultatov običajno dolgotrajnejše. podal nekaj predlogov za delo šolske svetovalne službe v času - Učinkovitost spletnih skupin se poveča z uvedbo izolacije zaradi epidemije [12]. Predlogi so se nanašali na: gradiva za samopomoč. - ohranjanje stika z udeleženci vzgojno- - Tako videokonferenčne skupine kot skupine, ki izobraževalnega procesa, temeljijo na izmenjavi pisnih mnenj ( chat group) - dejavnosti v oddelčni skupnosti, kažejo pomembna izboljšanja v primerjavi s - pripravo napotkov za samostojno učenje doma, kontrolno skupino, vendar kažejo videokonferenčne - vprašanja motivacije učencev za šolsko delo, skupine primerjalno pomembnejše izboljšanje - seznanjenost o bolezni covid-19 in ukrepih v zvezi z mentalnega zdravja. epidemijo in - Učinkovitost spletnih oblik skupinskega dela se - na skrb zase. razlikuje glede na modaliteto vodenja, vključene Posebej so bili izpostavljeni predlogi za individualni posameznike in glede na naravo težav in teme, ki se pogovor z učenci/dijaki na daljavo. Predlogov in navodil za na skupini odpirajo. Pri mlajših, bolj izobraženih, je skupinsko izvajanje podpore in pomoči je bilo manj. Svetovalke možnost uporabe IKT v svetovalni dejavnosti večja, ZRSŠ [9] so svetovale, da se svetovalna služba vključi v hkrati so večji tudi učinki tovrstnega svetovanja. izvajanje videokonferenčnih razrednih ur, kamor se lahko Večje učinke kažejo skupine, ki delajo po vedenjsko- vključi delavnice iz socialnega in čustvenega učenja. Omenile kognitivnih principih, a upoštevati je potrebno, da je so tudi možnost organiziranja posebne skupine učencev ali tudi raziskav na teh skupinah več (verjetno zaradi lažjega merjenja učinkov). dijakov, ki potrebujejo še dodatno spremljanje, razbremenilne - Omejitve dela na daljavo se najbolj intenzivno kažejo pogovore, konkretnejšo spodbudo in pomoč. na področju oblikovanja skupinske klime in V aprilu 2020 je bila na Oddelku za pedagogiko in zaupnosti. andragogiko Filozofske fakultete Univerze v Ljubljani izvedena raziskava, namen katere je bil proučiti, kako se je svetovalna Tudi nekatere slovenske raziskave potrjujejo ugotovitve, da služba soočala z vprašanji, izzivi in težavami, ki so se pojavili kakovost komunikacije in dela na daljavo ni enaka kot prej, saj med izvajanjem izobraževalnega in svetovalnega dela na manjka predvsem osebni stik s sogovorniki, ta stik pa lahko daljavo [4]. Dve vprašanji v raziskavi sta se nanašali na interakcija ob pomoči sodobnih tehnologij samo delno sodelovanje svetovalnih delavcev v času dela od doma z 465 drugimi udeleženci, to je s sodelavci, učenci oziroma dijaki, Medsebojna podpora je pomembna prednost skupinskega kolegi svetovalnimi delavci in na oceno tega sodelovanja. Iz svetovanja, vendar to ni edina prednost skupine. Vsako skupino rezultatov je razvidno, da so bili v stalnem stiku z učitelji oz. vodita en ali dva usposobljena voditelja, ki člane skupine učita vzgojitelji, da so si nudili medsebojno podporo, se posvetovali z dokazi podprtih strategij za reševanje problemov. Zanemariti in reševali aktualne težave. Glede sodelovanja z učenci oz. ne gre niti časovne in finančne ekonomičnosti takih oblik dela, dijaki raziskava ugotavlja precejšnje razlike glede odzivnosti in saj lahko en ali dva strokovna delavca v določenem časovnem sodelovanja, globalna ugotovitev pa je, da »tisti učenci in terminu nudita podporo večjemu številu uporabnikov, kar je še dijaki, ki že v času rednega pouka niso dobro sodelovali, se tudi posebej dobrodošlo v časih povečanih stisk in negotovosti, kot sedaj slabo ali pa sploh ne odzivajo«. Tudi glede sodelovanja s je tudi obdobje epidemije covid-19. Zaradi vsega navedenega je starši so rezultati raziskave podobni – pomemben delež staršev lahko intenzivnejše uvajanje skupinskih oblik dela v času dela v ostaja neodziven. Tudi tisti svetovalni delavci, ki so živo ali na daljavo, pomembna dopolnitev za svetovalne sodelovanje ocenili kot dobro, pa opozarjajo, da manjka osebni delavce, s katero lahko delujejo na vseh osnovnih vrstah stik. dejavnosti, predvsem pa na področju razvojnih in preventivnih Hkrati so navajali, da je (bilo) v času izobraževanja na dejavnosti [10]. daljavo več dela, da je to bolj naporno (za vse udeležene), mnogim se je delavnik raztegnil čez ves dan. Večina dela je potekala individualno, z učenci in dijaki ter učitelji preko e- 4 PRAKTIČNE IZKUŠNJE PRI IZVAJANJU pošte in videokonferenc, s starši pa je prevladovala SKUPINSKIH OBLIK DELA NA DALJAVO komunikacija po spletni pošti. Ugotovitev o prevladujočih V SVETOVALNEM CENTRU MARIBOR načinih komunikacije in o povečanem obsegu dela na področju Ob intenzivnem sodelovanju s svetovalnimi službami smo v svetovalne službe, mora nujno voditi v razmišljanje o možnih Svetovalnem centru Maribor zaznali povečane potrebe po rešitvah za nastalo situacijo. Ena od možnih rešitev je lahko v strokovni pomoči tako staršem, otrokom in mladostnikom, kot skupinskih oblikah dela. strokovnim delavcem šol. Kljub zavedanju omejitev spletnega 3.2 Primernost skupinskih oblik dela za delo skupinskega dela smo se zaradi možnosti podpore večjemu številu uporabnikov in ob prednostih, ki jih skupinske oblike šolske svetovalne službe dela prinašajo, odločili za izvedbo več skupinskih programov, Skupinske oblike dela, kot so svetovanje in terapija, so v ki so vsi potekali preko videokonference ZOOM: vzgojno-izobraževalnem prostoru (ob ustrezni usposobljenosti - Neverjetna leta – trening starševstva, namenjen strokovnega delavca) primerne za vse skupine uporabnikov – staršem vzgojno zahtevnejših predšolskih otrok. tako učence, kot starše in učitelje. V skladu s standardi - Učimo se učiti – delavnice namenjene učencem ameriške psihološke agencije APA [11] skupinsko svetovanje druge in tretje triade z namenom spoznavanja sebe kot učenca, praviloma poteka v skupini od 5 do 15 udeležencev z dvema učenje organiziranja časa, preizkušanje različnih strategij učenja voditeljema, ki sta za tovrstno delo ustrezno usposobljena. in razvijanje veselja do učenja. Običajno se skupine srečujejo enkrat tedensko in posamezno - HOPS – delavnice namenjene učencem tretje triade srečanje traja eno ali dve uri. Številne skupine so oblikovane z za spodbujanje izvršilnih funkcij, kot so organizacija, namenom psihoterapevtske podpore na točno določenem pozornost, spomin, začenjanje z aktivnostjo in podobno. področju (na primer depresija, anksioznost, motnje hranjenja in - Trening branja – za učence 4. in 5. razredov, ki se podobno), druge pa se usmerjajo na bolj splošna vprašanja spopadajo s šibkostmi na področju branja ali jim za branje izboljšanja socialnih spretnosti, pomoč pri spoprijemanju z primanjkuje motivacije. jezo, izgubo, sramežljivostjo, osamljenostjo ali nizko - Supervizija za učitelje – namenjena učiteljem in samopodobo ali na aktualne izzive vsakdanjika. V šolskem svetovalnim delavcem kot strokovna in medsebojna podpora v okolju so skupinske oblike dela učinkovite tudi pri spodbujanju času sprememb, povečanega obsega dela in negotovosti. izvršilnih funkcij, pridobivanju učnih in organizacijskih veščin, Po zaključku posameznih skupinskih programov, je bila obravnavi tem s področja poklicne orientacije, izgradnji izvedena tudi evalvacija s strani udeležencev in izvajalcev. rezilientnosti, podpori staršem pri vprašanjih glede šolanja Evalvacija je praviloma potekala v obliki nestrukturiranega njihovega otroka ali kot oblika intervizije učiteljev ali drugih intervjuja ali krajše ankete. Povzamemo lahko, da so bile vse strokovnih delavcev in podobno. oblike skupinskega dela na daljavo kljub določenim omejitvam Čeprav je vključitev v skupino tujcev lahko sprva izvedbe dobro sprejete. Iz odgovorov udeležencev in izvajalcev zastrašujoča misel, ima skupinsko delo številne prednosti, ki jih lahko povzamemo nekatere prednosti in ovire ter izpeljemo individualno svetovanje in pomoč ne moreta nuditi. Prednost priporočila za nadaljnje izvajanje skupinskih oblik dela na skupinskega svetovanja in drugih oblik skupinskega dela z daljavo. uporabniki je, da omogoča deljenje izkušenj, takojšnje povratne Med prednostmi takega načina dela so udeleženci navajali: informacije s strani udeležencev skupine in medsebojno učenje. Pomembna prednost skupine je tudi podpora, ki jo skupina nudi - možnost delitve mnenj, izkušenj, posamezniku in normalizacija težav, ki jo lahko posameznik - pridobivanje praktičnih napotkov za reševanje težav, doživi v skupini. Pogosto je namreč prepričanje, da je - učinkovitost naučenih strategij, posameznik v stiski sam, da določeno težavo doživljamo le on, - časovno ekonomičnost, v skupini pa lahko člani spoznajo, da gredo tudi drugi člani - večjo sproščenost, kot pri srečanjih v živo in skupine skozi podobne težave in da niso sami. Hkrati pridobijo - zmanjšanje občutka osamljenosti. dobrodošle ideje, kako se lahko z neko težavo in stisko soočijo. 466 Omejitve skupinskega dela na daljavo, ki so jih udeleženci LITERATURA IN VIRI zaznavali so bile podobne tistim, o katerih beremo v raziskavah. [1] Batagelj, T. (2020). Podpora učencem s šibkimi izvršilnimi funkcijami v Poleg pomislekov glede zasebnosti in pasti, ki jih prinaša času šolanja od doma. V Cigur, A. in Vuk, N. (ur.), VIII. Mednarodna deljenje zasebnosti preko spleta, so čutili manjšo povezanost strokovno-znanstvena konferenca Izzivi in težave sodobne družbe (str. 57-65). RIS Dvorec. https://www.ris- skupine zaradi pomanjkanja osebnega stika in neverbalne dr.si/data/attachment/a5d907c1122676441ed98f3c6b33c94e6fb0bb97/16 komunikacije. Nekateri učenci so izrazili pomisleke zaradi 11840977Bilten_Izzivi_in_te_ave_sodobne_dru_be_2020.pdf [2] Batagelj, T. (2021). Trening starševstva »Neverjetna leta« v času manjše zasebnosti – v kolikor do spleta dostopajo iz skupnega epidemije COVID-19. V Dajčar, M. in Novak, M. (ur.), IX. mednarodna prostora v stanovanju, kamor imajo kadarkoli dostop tudi drugi konferenca Izzivi in težave sodobne družbe (str. 11-19). RIS Dvorec. družinski člani. Pomembna ovira so lahko tudi tehnične težave, https://www.ris- dr.si/data/attachment/1337657643fd0d52ac5e7876743a129134fb40a7/16 vendar udeleženci na Svetovalnem centru tega niso posebej 29126744BILTEN_IZZIVI_IN_TE_AVE_SODOBNE_DRU_BE_2021. izpostavljali. pdf [3] Batagelj, T. in Mičić, S. (2021). Pomoč in podpora učencem s Skupinsko delo je glede na izkušnje uporabnikov primanjkljaji na področju izvršilnih funkcij v času šolanja na daljavo. Svetovalnega centra Maribor dobrodošla dopolnitev k podpori, Sodobna pedagogika, 72(138), 218-233. pomoči in svetovanju v času izrednih razmer zaradi epidemije [4] Gregorčič Mrvar, P., Jeznik, K., Šarić, M in Šteh, B. (2021). Soočanje svetovalnih delavk in delavcev v vzgojno-izobraževalnih ustanovah z [1, 2, 3]. Vsekakor je pri načrtovanju tovrstnih aktivnosti epidemijo covida-19. Sodobna pedagogika, 72(138), 150-167. potrebno upoštevati omejitve in posebnosti, ki jih prinaša [5] Kastelic, N., Kmetič, E., Lazić, T., Okretič, L. (2021). Kako motivirati učence pri poučevanju na daljavo. Priročnik za učitelje. Univerza v videokonferenčni način srečevanja. Med možnimi rešitvami in Ljubljani, Filozofska fakulteta: Oddelek za psihologijo. prilagoditvami so delo v manjših skupinah, ki omogoča bolj [6] Markowitz, J. C., Milrod, B., Heckman, T. G., Bergman, M., Amsalem, D., Zalman, H. Ballas, T., Neria, Y. (25. 9. 2020). Psychotherapy at a poglobljeno diskusijo, dodatne spodbude voditeljev, dodatna Distance. ajp.psychiatryonline.org. gradiva za samopomoč, digitalne oblike nagrajevanja in https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.2020.20050557 spodbujanja, spodbujanje k prosti diskusiji med odmori z [7] Mikuž, A., Kodrič, J., Musil, B., Svetina, M., Juriševič, M. (30. 10. 2020). Psihosocialne posledice epidemije covid-19 in spremljajočih namenom večjega povezovanja članov skupine in podobno [1, ukrepov za otroke, mladostnike in družine. Klinična-psihologija.si. 2, 3, 5 in 13]. http://klinicna-psihologija.si/wp-content/uploads/2020/11/psihosocialne- posledice-epidemije-covid19-psiholo%C5%A1ka-stroka.pdf [8] Parks, C. D. (2020). Group dynamics when battling a pandemic. Group Dynamics: Theory, Research, and Practice, 24(3), 115-121. 5 ZAKLJUČKI [9] Priporočila za delo svetovalnih delavcev z učenci na daljavo. (27. 10. 2020). skupnost.sio.si. Na področju skupinskega dela na daljavo so potrebne dodatne https://skupnost.sio.si/mod/folder/view.php?id=337341 raziskave. Posebej ostajajo odprta vprašanja vzpostavljanja [10] Programske smernice svetovalne službe v osnovni šoli. (13. 5. 1999). Kurikularna komisija za svetovalno delo in oddelčno skupnost. skupinske povezanosti in dinamike, vpliv pomanjkanja [11] Psychotherapy: Understanding group therapy. (31. 10. 2019). apa.org. neposredne interakcije, predvsem očesnega stika in vprašljiva https://www.apa.org/topics/psychotherapy/group-therapy [12] Šarić, M. in Gregorič Mrvar, P. (20. 4. 2020). Nekaj predlogov za delo kvaliteta vzpostavljenih odnosov. Prehod na spletne oblike šolske svetovalne službe v času izolacije zaradi epidemije. Zdpds.si. skupinskega svetovanja zahteva znanje in trening. Kljub https://zdpds.si/obvestila/nekaj-predlogov-za-delo-solske-svetovalne- sluzbe-v-casu-izolacije-zaradi-epidemije/ odprtim vprašanjem, pomanjkanju teoretičnih izhodišč in [13] Webster-Sratton, C. (2020). Hot Tips for IQ Group Leaders Delivering smernic, pa so se skupinske oblike svetovanja v času epidemije the Incredible Years Video Parent Programs via On-Line Tele-Sessions. izkazale kot učinkovita in dobrodošla oblika dela za vse incredibleyears.com. https://incredibleyearsblog.wordpress.com/2020/08/12/hot-tips-for-iy- vključene skupine uporabnikov. Uporabniki so kot posebej group-leaders-delivering-parent-programs-online/ dobrodošlo izpostavljali možnost deljenja izkušenj, [14] Weinberg, H. (2020). Online Group Psychotherapy: Challenges and Possibilities During COVID-19 – A Practice Review. Group Dynamics: medsebojnega učenja in medsebojno podporo. Ob strogem Theory, Research, and Practice, 24(3), 201-211. omejevanju gibanja in združevanja, so jim tedenska srečanja omogočala stik z drugimi ljudmi in lajšala občutek osamljenosti. Skupinsko svetovanje tako ostaja pomembna oblika dela z uporabniki v času omejitev in sprememb in je lahko dobrodošlo strokovno in ekonomično dopolnilo k delu svetovalne službe in strokovnih delavcev v zunanjih strokovnih institucijah. 467 Karierna orientacija na daljavo Career orientation online Jelka Berce Osnovna šola Cvetka Golarja Škofja Loka, Slovenija jelka.berce@gmail.com POVZETEK ABSTRACT Šolsko leto 2020/21 se je pričelo s »cmokom v grlu«, saj smo The 2020/21 school year began with a "lump in the throat", se na podlagi pomladne izkušnje zaprtja šol zaradi spopadanja s as we wondered how direct work with pupils would take place in koronavirusom (COVID-19) spraševali, kako bo potekalo the new school year, based on the experience from spring of neposredno delo z učenci v novem šolskem letu. Pripravljali smo closing schools due to the Coronavirus (COVID-19). We were se na delo »v živo«, a se vzporedno ves čas izobraževali za delo preparing for "live" work, but at the same time, we were na daljavo. constantly training for online “distance” education. Ena od pomembnih nalog svetovalne službe je področje One of the important functions of the school counselling kariernega svetovanja – to je dejavnost, ki se načrtno izvaja v service is the field of career counselling - this is an activity that zadnji triadi osnovnošolskega izobraževanja in kjer se učenci ob is systematically carried out in the last triad of primary education pomoči in vodenju svetovalnega delavca učijo postavljati and where pupils learn to set career goals and make career karierne cilje in sprejemati karierne odločitve. Da bodo učenci decisions with the help and guidance of a counsellor. In order for sprejeli prave, morajo dobro poznati svoje interese, možnosti in the pupils to determine the right ones, they need to know their zmožnosti. Šolska podpora in pomoč pri samospoznavanju sta interests, opportunities, and abilities well. School support and the usmerjeni tako v skupinsko delo z učenci kot individualno help with self-knowledge are focused on both; group work with informiranje. pupils as well as individual advising. V prispevku je predstavljen proces karierne orientacije v 8. in The article presents the process of career orientation in the 8th 9. razredu osnovne šole v šolskem letu 2020/21, ki je, z izjemo and 9th grade of primary school in the school year 2020/21, izpolnjevanja prijavnic za vpis v srednjo šolo, potekal na daljavo. which, with the exception of filling out application forms for Največji izziv je bila soorganizacija tehniškega dne za učence enrolment to secondary school, took place online. The greatest treh osnovnih šol občine Škofja Loka z naslovom »Karierni dan« challenge was the co-organization of a technical day for pupils prek spletnega orodja ZOOM. Tudi individualna svetovanja of three primary schools in the municipality of Škofja Loka učencem so do marca potekala prek orodja ZOOM in Arnesovih entitled "Career Day" through the online application ZOOM. spletnih učilnic, za starše pa je bila pripravljena posneta Until March, individual counselling for pupils had been Powerpoint predstavitev o dejavnikih kariernega odločanja ter v conducted using the ZOOM application and Arnes online februarju izveden tudi ZOOM roditeljski sestanek. classrooms, and a recorded PowerPoint presentation on career decision-making factors was prepared for parents, including a S pripravljenostjo na novo učenje, prilagajanje, sodelovanje ZOOM parents meeting in February. in iskanje novih rešitev, se je izkazalo, da »ZOOM karierna orientacija iz domačega naslonjača« prinaša tudi nekatere The readiness for new learning, adaptation, cooperation and prednosti pred klasičnim načinom dela, ki jih velja razvijati tudi finding new solutions have proved that "ZOOM career v prihodnje. orientation from the comfort of your home" has indeed some advantages over the traditional way of working, which should be KLJUČNE BESEDE further developed in the future. Karierna orientacija, vpis v srednjo šolo, karierni dan, spletno orodje ZOOM, spletna učilnica KEYWORDS Career orientation, high school enrolment, career day, online application ZOOM, online classroom 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 Svet in ljudje smo v četrti industrijski revoluciji, ki je s seboj be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia prinesla digitalizacijo, avtomatizacijo in robotizacijo, ki © 2021 Copyright held by the owner/author(s). posledično močno vplivajo na delovna mesta, dinamiko trga dela in narekujejo prilagajanje vseh vpletenih v ta ekosistem, med 468 drugim tudi izobraževalnih inštitucij, kjer se posameznik prvič • svetovalno delo z učenci: zajema vse od informiranja do sreča s karierno orientacijo [1]. organizacije obiskov učencev v podjetjih in pri Karierna orientacije je orodje, s katerim posameznikom delodajalcih, organizacijo predavanj in pogovorov z pomagamo pri načrtovanju in vodenju kariere. Zajema tako delo zunanjimi strokovnjaki, izvedbo predavanj in delavnic s posamezniki v procesu izobraževanja (tu gre za začetek), kot za učence, zbiranje podatkov o učencih za potrebe tudi s tistimi, ki se odločajo za zaposlovanje, so že zaposleni in poklicnega svetovanja ter individualno in skupinsko iščejo novo delo. Ukvarja se tudi z razvojem kadrov in svetovanje; načrtovanjem aktivnosti po upokojevanju. • svetovalno in posvetovalno delo z učitelji in drugimi Prav zaradi sprememb v okviru četrte industrijske revolucije, sodelavci na šoli, skrb za bazo informativnih poklicnih kot so npr. razvoj na področju genetike, umetne inteligence, gradiv na šoli; nanotehnologije, 3-D tiskanja, biotehnoliogije, … potreba po • svetovalno in posvetovalno delo s starši: organizacija učinkoviti karierni orientaciji postaja vse večja, saj morajo predavanj in delavnic o vlogi staršev pri poklicnem državljani obvladovati vedno pogostejše prehode znotraj razvoju in odločanju; izobraževanja, dodatnega usposabljanja in trga delovne sile [2]. • sodelovanje z vodstvom in Zaradi bliskovitih tehnoloških sprememb je zelo težko • sodelovanje in koordinacijo dela z zunanjimi napovedati spremembe v spretnostih, znanjih in veščinah, ki jih ustanovami (npr. Zavod za zaposlovanje, srednje šole, bodo posamezniki potrebovali pri opravljanju svojih poklicev. podjetja, …). Do leta 2030 naj bi se povečevalo povpraševanje po tehnoloških, Karierna orientacija zajema štiri ključne elemente [5]: socialno-čustvenih in višjih kognitivnih sposobnostih (npr. 1. učenje odločitev: učenci razvijajo veščine odločanja; kritično mišljenje, odločanje, kompleksna obdelava informacij, 2. zavedanje o priložnostih: učenci ob strokovni podpori …). Za mlade, ki prihajajo na trg dela, je tako najbolj pomembno, izkusijo in spoznajo svet dela, potencialne priložnosti, zahteve in da spremljajo prihajajoče trende, razvijajo kompetence ter odgovornosti, ki jih bodo morali izpolniti; osebno prožnost in fleksibilnost pri odločitvah o poklicni poti [1]. 3. učenje prehoda: razvijajo samozavedanje in spretnosti, Mladi potrebujejo pomoč pri učenju postavljanja kariernih upravljajo prehode v odraslost, razvijajo mehke veščine, ki jim ciljev in sprejemanju kariernih odločitev. Šolska podpora in bodo pomagale pri vstopu na trg dela; pomoč pri samospoznavanju sta usmerjeni tako v skupinsko delo 4. samozavedanje: razvijajo zavedanje podobnosti in razlik v z razredom kot tudi v individualno informiranje in spremljanje primerjavi z drugimi, spoznavajo svoje kompetence in omejitve, posameznega učenca. raziskujejo interese in vrednote. Vloga pedagoških delavcev na področju karierne orientacije Vloga kariernega svetovalca v osnovni šoli je podpora se je spremenila skladno s spremembami na trgu dela. Ključen učencem pri spodbujanju spoznavanja samega sebe, raziskovanja premik je v smeri od »tistega, ki ve« v smer vodnika in mentorja, področij, interesov, močnih kompetenc, in omogočanje učenja o ki učencu »stoji ob strani«. Poleg dobrega poznavanja področja tem, kako in kje še lahko iščejo informacije, oblikujejo podporno karierne orientacije mora svetovalni delavec biti opremljen tudi mrežo in tudi načrtujejo cilje in aktivnosti. z veščinami empatičnega poslušanja, postavljanja vprašanj, Izbira poklica ni več statična, ampak dinamična in vodenja procesa, usmerjanja in svetovanja [1]. spremenljiva, kot je okolje, v katerem odraščajo nove generacije Karierna orientacija je pomembno področje, ki se v okviru [1]. razrednih ur in dodatnih dejavnosti vključuje v zadnjo triado izobraževanja v osnovni šoli. Kljub spremenjenim pogojem dela zaradi koronavirusa v šolskem letu 2020/21 je svetovalna 3 KARIERNA ORIENTACIJA V OSNOVNI delavka zavzela stališče, da učenci ne smejo biti prikrajšani za ŠOLI CVETKA GOLARJA suport in vodenje pri sprejemanju pomembnih življenjskih odločitev, kot je izbira srednješolskega programa oziroma 3. 1 OSMI RAZRED začetek načrtovanja poklicne poti. Proces karierne orientacije v OŠ Cvetka Golarja poteka na dveh ravneh: na prvi ravni se učenci s poklici seznanjajo na različne 2 KARIERNA ORIENTACIJA V OSNOVNI načine v okviru pouka vse od 1. razreda dalje, svetovalna služba ŠOLI pa se intenzivneje neposredno v to področje vključi v 8. razredu, ko psihologinja pripravi po dve razredni uri za vse učence. S tema Karierna orientacija (sprva se je področje dela imenovalo razrednima urama želi učence informirati s srednješolskimi poklicno usmerjanje) je bila tista naloga, zaradi katerih so se pred možnostmi v slovenskem izobraževalnem sistemu, hkrati pa dobrimi 50-imi leti svetovalni delavci prvič pojavili v slovenskih preveri predznanje učencev s tega področja. Namen prvih šolah [3]. razrednih ur je učence tudi spodbuditi, da začno aktivno Še vedno aktualne programske smernice svetovalne službe v raziskovati svoje interese, želje, možnosti in zmožnosti. V drugi osnovni šoli iz leta 1999 [4] opredeljujejo poklicno orientacijo polovici šolskega leta se učenci udeležijo tudi tehniškega dne na kot delo z učenci, učitelji, starši in vodstvom šole z namenom temo karierne orientacije: pred koronavirusom so obiskovali pomagati učencem pri izbiri in uresničevanju izobraževalne in Vrtiljak poklicev – poklicni sejem gorenjskih srednjih strokovnih poklicne poti. in poklicnih šol; v šolskem letu 2020/21 pa so na šoli v Ta med drugim zajema: sodelovanju s Kariernim placom za mlade organizirali tehniški • sodelovanje pri poklicni vzgoji v okviru rednega pouka dan, v okviru katerega so učenci spoznali pojem kompetence ter učiteljev, skladno s cilji, zajetimi v učnem načrtu, in v se udeležili različnih delavnic s področja projektnega vodenja, okviru ur oddelčne skupnosti; 469 kreativnih poklicev in izdelave Lego animacije. V okviru Srednjim šolam so svetovalne delavke poslale dopis s razrednih ur se učenci učijo tudi postavljanja ciljev, iščejo povabilom k sodelovanju. Ker tudi same niso bile enotne v področja, na katerih so do sedaj že pridobili formalna in uporabi spletnih orodij za videokonference (na eni šoli so neformalna znanja ter raziskujejo lastne interese in izkušnje. uporabljali le MS Teamse, na eni šoli pa tako Teamse kot Izkušnje iz prakse kažejo, da večina učencev v 8. razredu ZOOM), so se odločile, da bodo zaradi bolj enostavne uporabe intenzivneje še ne razmišlja o prehodu na naslednjo srednje šole prosile, da pripravijo predstavitve svojih programov izobraževalno raven. Menijo, da imajo za to odločitev še dovolj v živo prek spletnega orodja ZOOM ali jim posredujejo vnaprej časa. Zato svetovalna delavka več aktivnosti s področja karierne pripravljeno e-gradivo v obliki promocijskih filmov, povezav do orientacije izvede, ko učenci vstopijo v deveti razred in so že bolj spletnih strani in koristnih informacij glede vpisa. Večina notranje motivirani za proces samospoznavanja in postavljanja srednjih šol ni imela težav s prilagajanjem na nov način dela, zato osebno pomembnih ciljev. so OŠ Cvetka Golarja, OŠ Škofja Loka-Mesto in OŠ Ivana Groharja 11. 11. 2020 v popoldanskem času izvedle dogodek v 3. 2 DEVETI RAZRED živo prek spleta, na katerem se je predstavilo več kot 20 Delo v 9. razredu se najprej začne z roditeljskim sestankom za srednješolskih programov v posameznih ZOOM predstavitvah. starše. Tu so v šoli v letošnjem šolskem letu naleteli že na prvo K sodelovanju so povabile srednješolske programe, za katere so težavo, saj skupnega dela roditeljskega sestanka za vse starše učenci izrazili največ interesa v predhodno izvedeni anketi. Vsak devetošolcev (trije oddelki učencev) zaradi ukrepov pred učenec si je v posameznem terminu izbral po eno ZOOM širjenjem koronavirusa v živo ni bilo mogoče izvesti. Ker so predstavitev izmed ponujenih, v prvem delu tehniškega dne pa so razredniki srečanje s starši izpeljali v »mehurčkih« v svojih vsi učenci prisluhnili kratki predstavitvi Kompetenc, ki so jo učilnicah, se svetovalna delavka ni odločila za dodatno ZOOM pripravili v Kariernem placu za mlade v Kranju. Vse povezave srečanje za starše, saj ni želela podvajati dogodkov. Za starše je so bile dan pred dogodkom objavljene v spletni učilnici šolske pripravila Powerpoint predstavitev o dejavnikih kariernega svetovalne delavke. Vsaka svetovalna delavka je koordinirala odločanja in o poteku dela z učenci v 9. razredu ter informacije, delo svojih učencev, v prvem delu predstavitve pa so sodelovali ki jih je želela predstaviti staršem, posnela na PPT predstavitev. tudi razredniki, ki so preverili prisotnost učencev na tehniškem Predstavitev je v obliki videoposnetka objavila na Youtube dnevu. kanalu šole. Dobila je kar nekaj povratnih informacij staršev, da Prednosti e-tehniškega dneva: je bila predstavitev koristna za pridobivanje informacij s • vse tri šole so ga lahko izvedle istočasno (v preteklosti je področja karierne orientacije. Osebno pa ni bila čisto zadovoljna bilo treba tehniški dan zaradi velikega števila učencev z izvedbo prvega predavanja, saj ji je manjkal neposredni stik s izvesti na dveh lokacijah); starši, zato se je odločila, da bo drugi roditeljski sestanek, če bo • če učenec v terminu ZOOM predstavitev ni našel le mogoče, izveden v živo ali prek videokonference. predstavitve, ki bi ga zanimale, si je v tem času ogledal Z devetošolci so konec oktobra začeli z izpolnjevanjem pripravljena promocijska gradiva v obliki filma ali je Elektronskega vprašalnika o poklicni poti, ki so ga pripravili na pregledoval spletne strani; Zavodu za zaposlovanje in že pred leti prevedli v e-obliko, zato • tudi po zaključku tehniškega dneva so bile učencem na ga vsako leto učenci rešujejo v računalniški učilnici. Pred voljo vse zbrane povezave do koristnih informacij zaprtjem šol je bila dejavnost izpeljana le v enem oddelku, zato posameznih srednješolskih programov; je svetovalna delavka vsem ostalim učencem razdelila • ni bilo prehajanja med učilnicami in dela s pripravo uporabniška imena in gesla ter pripravila pisna navodila za prostorov v šoli; posledično je sodelovalo tudi manj samostojno delo doma. Večina učencev je elektronski vprašalnik strokovnih delavcev šole. uspešno izpolnila, nekateri učenci pa so imeli težave z Pomanjkljivosti oziroma predlogi za naslednje šolsko leto: izgubljenimi gesli, nedokončanjem vprašalnika, manjšina Vsaka šola, ki je pripravila ZOOM dogodek, bi morala imeti učencev pa k reševanju sploh ni pristopila. Delo »v živo« ima tu poleg predavatelja v skupini tudi »co-hosta«, ki skrbi za nemoten prednost, saj strokovni delavec lahko neposredno pomaga potek komunikacije – poskrbi za komunikacijo v »chatu« in bdi učencu pri izpolnjevanju vprašalnika, kadar pride do težav in tudi nad tem, da učenci z vmesnimi komentarji ne motijo predstavitve. motivira učence za reševanje. Učenci pri izpolnjevanju Ob zaključku tehniškega dneva so učenci v spletnem orodju vprašalnika pogosto potrebujejo vodenje odrasle osebe, saj ob Forms izpolnili evalvacijo dneva dejavnosti, iz katere je bilo podpori odrasle osebe lahko ocenijo svoja močna področja, razvidno, da se je večini učencev tehniški dan zdel koristen in razmišljajo o svojih interesih, zaznanih ovirah ter motivacijskih zanimiv in so na njem dobili koristne informacije v zvezi z elementih in svojih prihodnjih izobraževalnih namerah. Ker o nadaljnjim izobraževanjem. sebi na ta način šele začenjajo razmišljati, potrebujejo V Formsih je bila narejena statistična analiza zadovoljstva s mentorstvo in pomoč. Psihologinji ta vprašalnik služi kot tehniškim dnevom vseh udeleženih (slika 1), v Excellovi tabeli priprava na individualne razgovore z učenci v svetovalni službi. pa so bili zbrani posamezni odgovori učencev, tako da so V novembru je šola ponovno sodelovala v soorganizaciji svetovalne delavke dobile povratne informacije o vsakem Kariernega dneva – tehniškega dneva za devetošolce. S posameznem učencu šole, ki je izpolnil evalvacijo. Izpolnjena kolegicama iz sosednjih osnovnih šol so se že konec avgusta evalvacija je bila pogoj za uspešno opravljen tehniški dan dogovorile, da v vsakem primeru karierni dan izvedejo na učencev. daljavo – prek spletnega orodja ZOOM, saj je bilo udeleženih okoli 300 devetošolcev in več kot 20 srednjih šol ter njihovih predstavnikov, ki bi se srečevali in se menjavali v skupinah. 470 programe, za katere izobražujejo, in okolje, v katerem poteka izobraževanje. V mesecu marcu je ostalo le še izpolnjevanje prijavnic za vpis v srednjo šolo, ki pa je, kljub naprednemu razvoju in pridobljenemu znanju na področju e-tehnologij, zaradi zastarelosti in preobremenjenosti portala ministrstva potekal po starem – s pisno prijavnico po navadni pošti. Svetovalna delavka je v okviru razrednih ur učencem pomagala pri izpolnjevanju prijavnic in jih nato tudi poslala na naslove srednjih šol. Na ta način pridobi podatke o vpisu učencev v posamezne izobraževalne programe in poskrbi, da prav vsi učenci do izteka roka oddajo prijavnico za vpis. Slika 1: Prikaz zadovoljstva učencev s Kariernim Po končanem postopku vpisa je bila svetovalna delavka dnevom (evalvacija v Formsih) učencem na voljo še za vprašanja o prenosu prijavnic, informacije o vpisnem postopku ter načinih in rokih za oddajanje Od novembra 2020 so potekali individualni pogovori z vlog za pridobivanje različnih štipendij. Karierna orientacija se devetošolci, za katere so starši podpisali soglasje za pomoč na za večino devetošolcev konča z zaključkom šolskega leta in področju karierne orientacije (71 od 73 učencev). Svetovalna uspešnim vpisom, nekateri učenci pa se po pomoč v šolo vračajo delavka je na ZOOM razredni uri učencem objavila razpored tudi v času drugega in tretjega vpisnega roka. prostih terminov, na katere so se učenci vpisali. Seznam s povezavo do srečanj je bil nato objavljen v spletni učilnici. Za razliko od dela v šoli, ko so učenci prihajali na razgovore v času 4 ZAKLJUČEK pouka, so bili tokrat razgovori zaradi majhnega števila ur ZOOM Dolgotrajno šolanje na daljavo je prineslo številne izzive, saj je pouka, izvedeni izven pouka. Vsak učenec je imel na voljo 20 pouk od doma od učencev zahteval veliko samostojnosti in minut za prvi pogovor. V razgovoru je svetovalna delavka samoiniciativnosti. Na področju karierne orientacije so učenci 8. izhajala iz odgovorov, podanih v elektronskem vprašalniku o in 9. razreda OŠ Cvetka Golarja v šolskem letu 2020/21 pokazali poklicni poti in z vtisov tehniškega dne. Pregledali so tudi veliko mero odgovornosti, samostojnosti in pripravljenosti za rokovnik za vpis. Večina devetošolcev je že imela oblikovane delo v spremenjenih pogojih. To dokazuje, da je karierna karierne cilje, neodločeni pa so se večkrat udeležili orientacija področje dela, ki je za učence zelo pomembno, zato individualnega pogovora prek ZOOMA, izpolnili pa so tudi so se tudi udeležili vseh ponujenih aktivnosti. Redno so interesni vprašalnik Kam in kako. Psihologinja jih je spodbudila pregledovali spletno učilnico svetovalne delavke, se odzivali na tudi k raziskovanju možnosti prek spletnih strani, na primer elektronsko pošto, ob dogovorjenem času so se udeleževali ogledu spletnih strani srednjih šol in predmetnikov, uporabi ZOOM razrednih ur, individualnih srečanj in opravili vse aplikacij spletne strani mojaizbira.si, filmov To bo moj poklic na zadolžitve v okviru kariernega dne. Youtubu. Nezanemarljiv je tudi pogovor s starši, sorojenci in Čeprav nam je vsem bolj blizu klasičen način dela v učilnicah, prijatelji. je na področju karierne orientacije smiselno obdržati nekatere Namesto šolske oglasne deske je psihologinja oblikovala oblike dela. Karierni dan je tako tudi v šolskem letu 2021/22 svojo spletno učilnico. V njej so učenci našli vse aktualne načrtovan prek spletnega orodja ZOOM, prav tako bo svetovalna informacije v zvezi z vpisom v srednje šole, objavila je tudi delavka ohranila oglasno desko v spletni učilnici, ki učencem rokovnik o vpisu z vsemi pomembnimi datumi za vpis. omogoča, da le s klikom na miško pridejo do želenih informacij Oblikovala je tudi forum za morebitna vprašanja učencev. na svetovnem spletu. Učencem je bila na voljo tudi za klepet v klepetalnici spletne Nenazadnje pa so tudi strokovni delavci okrepili svoje učilnice ali prek elektronske pošte. Svetovalno delo tako ni imelo digitalne kompetence in pridobili ogromno novega znanja, ki več osemurnega delovnika od ponedeljka do petka, ampak je bilo omogoča inovativen pristop k poučevanju sodobnih generacij. razporejeno čez ves dan in tudi ob koncih tedna, saj je bilo potrebno uskladiti delovne in domače oz. družinske obveznosti. LITERATURA IN VIRI V februarju se je psihologinja s starši devetošolcev srečala še na ZOOM roditeljskem sestanku, kjer so starši dobili informacije o [1] Gergorić, I. in Založnik. P. (2020). Novi pristopi pri delu z mladimi na področju karierne orientacije. Priročnik za strokovne delavce osnovnih rokovniku za vpis v srednje šole, dosedanjem delu na področju šol. Ljubljana, Javni zavod Cene Štupar – Center za izobraževanje karierne orientacije z njihovimi otroki ter informacije o Ljubljana [2] Rupar, B. (2012). Vseživljenjska karierna orientacija – povezava med štipendijah. Tokrat so zaradi dogodka v živo lažje tudi šolo, poklicem in življenjem . Vzgoja in izobraževanje.revija za teoretična vzpostavili dvosmerno komunikacijo in tako so starši takoj dobili in praktična vprašanja vzgojno izobraževalnega dela, 43(2), 19-23. Ljubljana, Zavod republike Slovenije za Šolstvo. odgovore na vsa vprašanja. Največ vprašanj je bilo glede [3] Povše, L. (2016). Vloga in položaj socialnega pedagoga kot svetovalnega spremenjenih pogojev za pridobitev Zoisove štipendije zaradi delavca v osnovni šoli [Diplomsko delo]. Univerza v Ljubljani, Pedagoška posledic koronavirusa. fakulteta [4] Nacionalni kurikularni svet (2008). Programske smernice: Svetovalna Tudi informativni dnevi so potekali na daljavo in učenci so služba v osnovni šoli. Ljubljana, Zavod republike za šolstvo ponujene termine v večini dobro izkoristili. Srednje šole so se [5] Law, B. in Watts, A. G., (2003). The DOTS Analysis: original version. Dostopno prek http://hihohiho.com/memory/cafdots.pff, (9. 8. 2021) potrudile, da bi učencem čim bolj približale izobraževalne 471 Z orodjem Nearpod do interaktivne obravnave domačega branja With the online tool Nearpod to interactive home reading discussion Živa Blatnik OŠ Toma Brejca Kamnik, Slovenija ziva.blatnik@gmail.com POVZETEK distance learning, as the teacher is obliged to find and master a tool that is not demanding to use or interactive activities in which Domače branje je obvezna dejavnost v okviru pouka slovenščine, pupils would find it easiest to master all the intended learning s katero učenci razvijajo sposobnost branja, razumevanja in objectives. vrednotenja književnih besedil. Izbrano književno besedilo učenci doma preberejo in zapišejo bralni dnevnik, pri pouku pa The article presents the process discussion about a literary sledijo pestre dejavnosti, ki preverjajo in nadgrajujejo učenčevo text during distance learning, made in the paid online tool razumevanje prebranega ter razvijajo kritično mišljenje in Nearpod, which includes the inclusion of the teacher's latest ustvarjalnost. Izpeljava omenjenih dejavnosti po samostojnem constructions, links to videos in various interactive activities that branju se je izkazala kot poseben izziv v času pouka na daljavo, require pupils to actively participate. Solutions of the tasks are saj je bil učitelj dolžan poiskati in osvojiti orodje, ki je presented in the form of a report that serves as a proof to the nezahtevno za uporabo, oz. interaktivne dejavnosti, ob katerih bi teacher of the activities in the progress of an individual pupil and učenci najlažje usvojili vse predvidene učne cilje. influences the methods and forms of work in future lessons. We chose this tool also because the use is not complicated, pupils do V prispevku je predstavljena procesna obravnava književnega not need passwords and usernames to participate. Some tasks besedila na daljavo, izdelana v plačljivem spletnem orodju were solved by the students independently when the time suited Nearpod, ki omogoča vključevanje učiteljevih lastnih gradiv, them (Student-Paced), while they solved the quiz at the same povezav na videe in številnih interaktivnih aktivnosti, ki od time, live, when we met at the videoconference (Live učencev zahtevajo aktivno udeležbo. Rešitve nalog so Participation). To solve the interactive challenges in the Nearpod predstavljene v obliki poročil, ki učitelju služijo kot dokaz o tool, the pupils were highly motivated, the tasks were solved in a aktivnosti in napredku posameznega učenca in vplivajo na high proportion. Some of them also solved the tasks several times metode in oblike dela v prihodnjih učnih urah. Za izbiro tega and showed a desire for knowledge. In particular, they were orodja smo se odločili tudi zato, ker uporaba ni zapletena, učenci willing to participate in quizzes that were conducted at the same za sodelovanje ne potrebujejo gesel in uporabniških imen. time, as they were thus connected to classmates, and the element Nekatere naloge so učenci reševali samostojno, ko jim je časovno of competition also helped to strive for progress. ustrezalo, medtem ko so kviz reševali istočasno, v živo, ko smo se srečali na videokonferenci. Za reševanje interaktivnih izzivov KEYWORDS v orodju Nearpod so bili učenci visoko motivirani, naloge so bile rešene v z visokim deležem. Nekateri so se reševanja lotili tudi Nearpod, home reading, distance learning, interactive večkrat in izkazali željo po znanju. Še posebej so bili pripravljeni assignments sodelovati v kvizih, ki so bili izvedeni istočasno, saj so bili tako povezani s sošolci, pa tudi element tekmovalnosti je pripomogel 1 UVOD k strmenju po napredku. Posodobljeni učni načrt za slovenščino iz leta 2018 na ravni KLJUČNE BESEDE vključevanja medpredmetnih vsebin posebno pozornost namenja Nearpod, domače branje, pouk na daljavo, interaktivne naloge razvijanju digitalne pismenosti učencev. Ti naj bi uporabljali digitalno tehnologijo pri razvijanju sporazumevalne zmožnosti in ABSTRACT pri komunikaciji (dejavnem stiku) z besedili, in sicer: Home reading is a compulsory activity within the Slovene - pri sprejemanju, razčlenjevanju in tvorjenju language lessons, with which pupils develop the ability to read, neumetnostnih in umetnostnih besedil; understand and evaluate literary texts. Pupils read the selected - kot podporo kritičnemu mišljenju, ustvarjalnosti in literary text at home and write a reading diary, followed by a inovativnosti; variety of activities that check and upgrade the pupil's - za iskanje, zbiranje, izmenjavo in obdelavo podatkov ter understanding of what is read and develop critical thinking and njihovo sistematično rabo pri tvorjenju informacij, pri creativity. Carrying out the mentioned activities after čemer naj bi se posluževali primerne strojne in independent reading proves to be a special challenge during programske opreme in samostojno uporabljali primerne 472 didaktične računalniške programe in splet kot vir znajo, nam orodje ponuja številne interaktivne didaktične igre podatkov in komunikacijsko orodje [1]. npr. kviz, kratka vprašanja, likovni izziv, iskanje parov, Učitelji slovenščine, ki nam je IKT blizu, smo pri dopolnjevanje besedila …) (Slika 2). Rezultati reševanja nalog neposrednem delu v učilnici že pred prenovo učnega načrta so prikazani v obliki natančnih statistično oblikovanih poročil. nemalokrat uporabljali spletna orodja in e-vsebine (e-gradiva, Kdaj in kako bodo učenci naloge reševali je mogoče nastaviti – e-učbenike, spletne slovarje in druge jezikovne priročnike) ali ali ko bodo imeli čas (način Student-Paced) ali v živo, istočasno, izpeljali učno uro v računalniški učilnici, kjer so učenci v našem primeru na videokonferenčni uri (način Live oblikovali besedila in se seznanili tudi s kritično uporabo Participation). urejevalnikov, pregledovalnikov in črkovalnikov besedil. Pri pouku z vključevanjem IKT je učitelj mentor, ki glede na učenčevo zmožnost uporabe strojne in programske opreme diferencira metode in oblike dela. Nekateri učenci niso suvereni pri uporabi računalnika in programske opreme – te učitelj vodi, da se seznanijo s programom oz. spletnim orodjem, v nadaljevanju pa so usmerjeni k doseganju učnih ciljev predmeta. Domačih zadolžitev ali projektnih nalog, ki bi vključevale uporabo IKT, večinoma nismo vključevali, saj vsem učencem ne bi mogli zagotoviti enakih možnosti (neenakovredna preskrbljenost gospodinjstev s strojno opremo). Slika 1: Nabor gradiv, ki jih lahko naložimo na nadzorno V času pouka na daljavo so bile tako za učitelje kot učence ploščo edina mogoča izbira učne ure v spletnem okolju. Poleg uporabe spletne učilnice in videokonferenčnega orodja Zoom, na uporabo katerih smo učence sistematično pripravljali od prvega tedna v šolskem letu 2020/21 dalje, smo učitelji želeli učencem ponuditi privlačnejše interaktivne vsebine, zato smo poiskali in raziskali številna spletna orodja. Z vidika učitelja nas je zanimalo, ali e-gradivo sledi učnim ciljem, ali bo učencem zanimivo, ali vsebuje kakovostne multimedijske elemente, kakšne vrste nalog vsebuje … Z vidika uporabnika učenca pa smo morali upoštevati učenčevo znanje o uporabi informacijskih tehnologij, preglednost e-gradiva, preprostost uporabe, vsebnost Slika 2: Nabor interaktivnih aktivnosti multimedijskih elementov, presoditi koliko naše pomoči učenec potrebuje oz. v kolikšni meri je ob naših navodilih lahko samostojen (razumljivost razlage, nalog …), koliko je učenec 2.2 Uvodna motivacija lahko dejaven (interaktivnost e-gradiva), na kakšen način bomo Med ali po branju so učenci samostojno zapisali bralni dnevnik lahko mi in učenci dobili povratno informacijo o njihovem (podatki o avtorju in književnem besedilu, kratka obnova, znanju, ali je e-gradivo res vsem dostopno ipd. [2]. Poleg razločevanje glavnih in stranskih književnih oseb, izražanje omenjenega je bilo bistvenega pomena, da učitelj zna izdelati, mnenja o ravnanju književnih oseb in utemeljitev o všečnosti oblikovati ali posodobiti e-gradiva in dejavnosti, s katerimi je prebranega besedila) in fotografijo dela zapisa posredovali v sodelujočim v procesu izobraževanja pri pouku omogočeno spletno učilnico. Bralni dnevniki so bili prvi dokazi o tem, kako sodelovalno delo, reševanje problemov, raziskovanje ali natančno je bilo branje in kako so besedilo razumeli. V skladu s ustvarjanje [3]. temi dokazi smo pripravili nadaljnje aktivnosti v orodju V nadaljevanju prispevka bo natančneje predstavljeno Nearpod. plačljivo orodje Nearpod, ki smo ga izbrali za obravnavo Prvo uro so učenci razmišljali, ali so bili pri samostojnem branju književnega besedila, ki so ga učenci prebrali kot domače branje uspešni. Učni sklop smo tako začeli s prosojnico o kriterijih v 6. razredu. Orodje omogoča vključevanje učiteljevih uspešnosti (Slika 3) in se o njih pogovorili na videokonferenčni elektronskih prosojnic, povezav na videe in številnih učni uri. interaktivnih aktivnosti, ki predvidevajo učenčevo aktivno udeležbo. 2 PRIMER UPORABE SPLETNEGA ORODJA NEARPOD 2.1 Kaj je Nearpod? S spletnim orodjem Nearpod lahko pripravimo vsako učno uro interaktivno. Oblikovano je v obliki nadzorne plošče, kamor lahko naložimo PPT-projekcije, Google prosojnice (Google Slides), PDF-je ipd. in vključimo svoje videe ali dodamo video direktno z YouTuba (Slika 1). Da lahko učenci pokažejo, kaj Slika 3: Vstavljena Google prosojnica 473 Učni sklop so dopolnjevale interaktivne naloge, ki naj bi jih učenci približno dve šolski uri reševali samostojno v t. i. Student-Paced načinu, zato je v nadaljevanju učne ure sledila predstavitev spletnega orodja in konkretna ponazoritev njegove uporabe. Učencem smo pokazali, da bodo v spletno učilnico dobili povezavo do učnega sklopa. Ko bodo kliknili na povezavo, se bo odprlo okno, kamor bodo zapisali svoje ime in priimek in kliknili gumb »Join Lesson« (Slika 4). Pokazali smo jim, katere aktivnosti jih čakajo v tem spletnem okolju, kako se jih rešuje in na kakšen način oddajo svoje rešitve (s klikom na »Post« ali Slika 6: Primer odprtega vprašanja, vključenega v posnetek »Submit«). Preden smo se poslovili, so vsi poskusili, ali na njihovi napravi povezava deluje. Sledila je aktivnost, ki je preverjala razumevanje zaznamovanih besed oz. besednih zvez in besed v prenesenem pomenu ter zaznavanje humorne perspektive v besedilu. Gre za igro spomina – na eni kartici je v beseda oz. besedna zveza, na drugi pa njena razlaga. Učenci so morali ustrezno povezati pare (Slika 7). Slika 4: Vstop v interaktivno učno uro 2.3 Interaktivne aktivnosti (Student-Paced) Interaktivne dejavnosti so bile izbrane premišljeno in so učence postopoma vodile od osvajanja minimalnih do temeljnih Slika 7: Igra spomin standardov znanja. Zadnja aktivnost je bila pripravljena v obliki kviza (Slika 8) Prva naloga je narekovala, da zapišejo vprašanje o vsebini in je preverjala, ali učenec sledi književnemu dogajanju in ga prebranega, ki bi ga zastavili sošolcem (Slika 5). S postavljenem razume ter prepozna glavne motive za ravnanje književnih oseb. vprašanja sošolcu je učenec dokazal, da je tudi sam prebral besedilo. Na vprašanja, ki so se pojavila na tabli, so učenci odgovarjali na eni od naslednjih videokonferenčnih ur. Slika 8: Primer vprašanja v kvizu 2.4 Poročila Slika 5: Tabla, na katero so učenci dodajali vprašanja Interaktivna učna vsebina je bila časovno omejena za reševanje na 48 ur, po tem času sodelovanje bi bilo več mogoče. Nato smo Druga aktivnost je bila sestavljena iz posnetka, v katerem pregledali poročila, ki jih orodje statistično natančno izdela pisatelj Slavko Pregl pojasnjuje okoliščine nastanka mladinskega (Slika 9). romana in značajske posebnosti književnih oseb. V posnetek smo Iz poročil smo izvedeli: vstavili odprta vprašanja, ki so preverjala tako razumevanje - kateri deli besedila so bili učencem težje razumljivi; književnega dogajanja kot vrednotenje besedila oz. posameznih - kako dobro so uspeli razvozlati besedne igre, besede v prvin besedila (Slika 6). prenesenem pomenu ipd.; - ali so v besedilu zaznali humorno perspektivo in kje; - ali razumejo časovno in vzročno-posledično zaporedje dogodkov, vzvode za ravnanje književnih oseb itd. V skladu z ugotovitvami smo pripravili še 2 učni uri, pri katerih so učenci sodelovali v razgovoru in v zvezek zapisali nekaj bistvenih ugotovitev. 474 3. REZULTATI Kljub temu da so bile vse ure pouka, v okviru katerih smo obravnavali domače branje, izpeljane na daljavo – ali v obliki videokonferenčnega pouka ali samostojnega dela učencev v spletnem orodju Nearpod – so vsi učenci dosegli večino zastavljenih učnih ciljev. O doseganju standardov znanja pričajo poročilo zaključnega kviza in preverjanje ter ocenjevanje znanja ob vrnitvi v šolske klopi. Lahko trdimo, da so bili nekateri učenci v spletnem okolju celo aktivnejši, kot so pri običajnem pouku. Kot narekujejo Smernice za uporabo IKT pri predmetu slovenščina, se je izkazalo, da lahko raba informacijskih tehnologij bistveno pripomore h kvalitetnejšemu pouku, ko je Slika 9: Primer poročila tesno povezana z novimi načini in oblikami dela, predvsem pa s cilji in z vsebinami pouka slovenščine, tj. z razvijanjem 2. 5 Istočasna interaktivna dejavnost (Live sporazumevalne zmožnosti [4]. Participation) 4. ZAKLJUČEK Zadnjo uro obravnave domačega branja smo preverili, kako V obdobju, ki je za učence predmetne stopnje trajalo skoraj štiri dobro so učenci usvojili predvidene učne cilje. Pripravili smo mesece, je bilo smiselno in zaželeno, da smo učitelji posegali po kviz »Time to climb«, ki je preverjal tako doživljanje, spletnih orodjih, ki učne vsebine popestrijo, učence spodbudijo k razumevanje in vrednotenje književnega besedila kot tudi aktivnemu učenju in pripomorejo k razvijanju učenčeve literarnovedno znanje. Učitelju je omogočena izbira med odgovornosti za lastno učenje. različnimi izgledi kviza, ki prispevajo k privlačnejši podobi in Uporaba spletnega orodja Nearpod pri obravnavi domačega posledično bolj doživeti uporabniški izkušnji. Na branja v času pouka na daljavo se je izkazala kot uspešen primer videokonferenci so se učenci s kodo pridružili kvizu v živo, prakse, saj je omogočila hitrejše in kakovostnejše doseganje izbrali so si svoj vzdevek in karakter (Slika 10). Ko so bili v kviz ciljev pouka književnosti. Učenci so bili namreč nasičeni s vpisani vsi učenci, smo delili zaslon, kjer so lahko opazovali, frontalnim delom v obliki videokonferenc in jim je bilo reševanje kako napredujejo v primerjavi s sošolci. Vsako rešitev smo sproti oz. igranje interaktivnih nalog in iger v veselje. Izkazalo se je pokomentirali, da so tudi učenci z napačnimi rešitvami lahko tudi, da so bile omenjene naloge rešene z visokim deležem (21 zapolnili vrzeli v svojem znanju. Motivacija za tak način dela je učencev od 22), nekatere celo večkrat. Vsekakor pa so bili bila v času pouka na daljavo še posebej visoka, saj je sodelovanje najbolj motivirani za igranje kvizov istočasno, v živo, ki so s sošolci vzbujalo občutek pripadnosti in povezanosti. Učenci so omogočili tekmovanje s sošolci in izražanje pripadnosti oddelku. želeli kviz reševati kar dvakrat in tako so vsi še dodatno utrdili Nestabilna internetna povezava v domovih nekaterih učencev se svoje znanje. je pokazala kot edina pomanjkljivost pri istočasnem sodelovanju v kvizu, saj jim je kviz prekinjal ali pa jim je bilo sodelovanje celo onemogočeno. Na katero izmed vrsto aktivnosti, ki jo omogoča orodje Nearpod, bi se bilo smiselno opreti tudi med poukom v učilnici (tako pri slovenščini kot drugih predmetih) kot element uvodne motivacije ali hitrega preverjanja znanja na inovativen in igriv način. 5. LITERATURA IN VIRI [1] Učni načrt (posodobljena izdaja). 2018. Program osnovna šola, Slovenščina. Ljubljana, Ministrstvo za šolstvo in šport, Zavod RS za šolstvo. [2] J. Oražem. 2020. E-gradiva za slovenščino kot prvi jezik. Magistrsko delo. Slika 10: Kviz omogoča izbiro karakterja Ljubljana, Filozofska fakulteta. [3] Šest temeljnih e-kompetenc. Pridobljeno 8. 9. 2021 iz SIO Slovensko izobraževalno omrežje: https://projekt.sio.si/e-solstvo/opis-e- kompetenc/sest-temeljnih-e-kompetenc/ [4] Čuk, A., Hedžet Krkač, M. (2016). Smernice za uporabo IKT pri predmetu slovenščina. Zavod Republike Slovenije za šolstvo. Pridobljeno 8. 9. 2021 iz https://www.zrss.si/digitalnaknjiznica/smernice- iktslo/files/assets/common/downloads/publication.pdf 475 Liveworksheets - ko učni listi oživijo Liveworksheets - when worksheets come alive Urška Delovec Osnovna šola Matije Valjavca Preddvor Šolska ulica 9, 4205 Preddvor urska.delovec@os-preddvor.si POVZETEK povratno informacijo, pregled nad njihovimi odgovori pa ima tudi učitelj. [1] Namen prispevka je predstaviti spletno orodje za izdelavo Orodje nam uporabnikom ponuja dve možnosti. Prva interaktivnih učnih listov Liveworksheets ter nekaj primerov možnost je, da na spletni strani nalog. S tem orodjem lahko različne dokumente (pdf, jpg, png) https://www.liveworksheets.com/ z brskalnikom ‘Search spremenimo v spletne vaje, ki omogočajo samodejno interactive worksheets’ pregledamo bazo že obstoječih nalog in popravljanje nalog. Učitelju orodje nudi tudi vpogled v to, kako uporabimo le-te. Zbirka že pripravljenih nalog zajema veliko so učenci reševali naloge. Na podlagi tega lahko učitelj nato različnih jezikov in predmetov. Za lažje iskanje imamo možnost učencem poda povratno informacijo o njihovem delu in uporabe naprednega iskanja ('advanced search'), kjer poleg napredku. ključnih besed lahko vnesemo še nekaj ostalih filtrov: jezik, predmet, razred oz. stopnjo ter starost (slika 1). KLJUČNE BESEDE Liveworksheets, spletno učno orodje, učni listi, interaktivne naloge, formativno spremljanje ABSTRACT The aim of the article is to present an online learning tool called Liveworksheets and a few examples of exercises designed with it. This learning tool allows us to transform different documents (pdf, jpg, png) into interactive online exercises with self- correction. By using Liveworksheets, teachers get a chance to Slika 1. Določanje kriterijev za napredno iskanje (VIR: check the students’ answers and give them feedback on their lasten, zajem zaslonske slike) work and progress. Za iskanje ustreznih nalog lahko namesto zgornjega brskalnika ali naprednega iskanja uporabimo tudi zavihek 'Interactive KEYWORDS worksheets'. Na seznamu na levi strani izberemo področje, ki nas zanima, in pregledamo ponujene naloge. Liveworksheets, online learning tool, worksheets, interactive exercises, formative assessment Če med že obstoječimi nalogami ne najdemo ustrezne, lahko ustvarimo tudi lastne naloge (za to je potrebna registracija). Z izbiro zavihka 'Make interactive worksheets' se nam prikažejo tri možnosti. Ko se prvič spopademo z 1. UVOD ustvarjanjem lastnih nalog, nam prvi dve možnosti ('tutorial' in Zadnji dve šolski leti sta bili popolnoma drugačni od prejšnjih 'video tutorial') ponujata navodila za delo v pisni in video let. Šole so se za nekaj mesecev zaprle, učitelji pa smo izgubili obliki. Z možnostjo 'Get started' nato pričnemo z delom. V neposreden stik z učenci. Spoprijeti smo se morali s orodje naložimo datoteko, ki jo želimo pretvoriti v interaktivno poučevanjem učencev na daljavo. Učencem smo pošiljali nalogo. Sistem datoteko pretvori v sliko. Na tistih mestih, kjer navodila za delo preko različnih kanalov, pošiljali smo jim učne od otrok želimo odgovore, narišemo okvirčke in vanje vnesemo liste in posnetke z razlago učne snovi, obenem pa iskali nova pravilne odgovore (slika 2), da lahko računalnik potem nalogo spletna orodja, ki bi nam vsem delo olajšala. Eno izmed pregleda. [2] spletnih orodij, ki sem ga preizkusila pri pouku angleščine, je Zaželeno je, da ustvarjene interaktivne naloge delimo spletna stran za izdelavo interaktivnih učnih listov z drugimi uporabniki, določeno število nalog pa lahko Liveworksheets. Meni osebno se je izkazala za zelo uporabno nastavimo kot zasebne in jih obdržimo zase oz. delimo le s sredstvo poučevanja in učenja pri angleščini. svojimi učenci. 2. UČNO ORODJE LIVEWORKSHEETS Liveworksheets je spletno orodje, ki običajne učne liste spremeni v interaktivne spletne naloge, ki omogočajo samodejno popravljanje nalog. Učenci dobijo takojšnjo 476 Slika 2. Vnašanje okvirčkov in pravilnih odgovorov (VIR: lasten, zajem zaslonske slike) Slika 4. Priprava naloge 'izbirnega tipa' in končana naloga 3. TIPI NALOG (VIR: lasten, zajem zaslonske slike) 3.1 Dopiši ustrezen odgovor ('gap fill') 3.4 Povezovanje parov ('join with arrows') Orodje omogoča oblikovanje različnih tipov nalog. Najbolj Zelo priljubljen tip naloge, ki jo je možno narediti, je osnoven tip naloge (in za oblikovanje tudi najenostavnejši) je, povezovanje parov. Čez odgovore na učnem listu narišemo da na mestih, kjer želimo odgovore, narišemo okvirčke in okvirčke, vanje vnesemo besedo 'join', dodamo dvopičje, nato vnesemo odgovore, za katere želimo, da se štejejo kot pravilni. pa odgovora, ki ju je potrebno povezati, označimo z isto Priporočljivo je, da vnesemo vse odgovore, ki so sprejemljivi številko (slika 5). (npr. an apricot, apricot). [3] 3.2 Izbirni tip s spustnim menijem ('drop down select box') Pripravimo lahko tudi nalogo izbirnega tipa, pri kateri učenci med vsaj dvema odgovoroma v spustnem meniju izberejo pravilnega. To storimo tako, da v okvirček najprej napišemo besedo 'choose', dodamo dvopičje, nato pa vnesemo možne odgovore. Pravilni odgovor označimo z zvezdico (slika 3). Slika 5. Priprava naloge 'povezovanja parov' in rešena naloga (VIR: lasten, zajem zaslonske slike) 3.5 Povleci na ustrezno mesto ('drag and drop') Oblikujemo lahko tudi nalogo, kjer je potrebno odgovore prenesti na ustrezna mesta. Okvirčke narišemo tja, kamor želimo, da učenci premaknejo posamezne odgovore. Vanje napišemo 'drop', dodamo dvopičje, nato pa številke. Odgovori, za katere želimo, da jih učenci potegnejo na ustrezna mesta, Slika 3. Priprava naloge 'izbirnega tipa s spustnim menijem morajo biti napisani že na učnem listu. Čez njih narišemo in končana naloga (VIR: lasten, zajem zaslonske slike) okvirčke ter vanje natipkamo 'drag', dvopičje in številko mesta, na katerega je potrebno polje prenesti (slika 6). 3.3 Izbirni tip ('multiple choice exercise') Ustvariti je možno tudi drugačno nalogo izbirnega tipa. Učencem lahko ponudimo več odgovorov, med katerimi enega izberejo. Možni odgovori se v tem primeru ne nahajajo v spustnem meniju, ampak morajo biti napisani že na učnem listu, ki smo ga naložili na internet. Čez vsak možen odgovor narišemo okvirček, vanj pa natipkamo besedo ‘seleči’, dodamo dvopičje, nato pa pri pravilnem odgovoru napišemo ‘yes’, pri napačnem pa ‘no’ (slika 4). Slika 6. Priprava naloge tipa 'povleci na ustrezno mesto' in končana naloga (VIR: lasten, zajem zaslonske slike) 477 3.6 Ostale možnosti zvezke, kadarkoli lahko pregleda naloge, ki so jih rešili in zraven nalog oz. posameznih primerov doda svoje komentarje V učne liste lahko dodamo še zvočne posnetke, video posnetke, (slika 8). datoteke Powerpoint, pripravimo lahko govorne naloge (te učenci rešijo s pomočjo mikrofona). Naredimo lahko tudi Brezplačni paket učiteljem dovoljuje do 10 naloge odprtega tipa. Pri teh vnesemo le okvirček za odgovor in interaktivnih delovnih zvezkov in do 100 prijavljenih učencev. pustimo praznega. Teh nalog učenci seveda ne morejo sami [3] pregledati. [3] 5. ZAKLJUČEK 4. REŠEVANJE NALOG IN POVRATNA Spletno učno orodje Liveworksheets je dokaj preprosto za INFORMACIJA uporabo. Klasične učne liste hitro spremeni v interaktivne Učenci do nalog dostopajo na dva načina. Prva možnost je, da naloge, ki so zaradi vseh možnosti, ki jih orodje ponuja, od učitelja prejmejo povezavo do naloge in jo rešijo. Na koncu učencem bolj privlačne. Ker orodje učencem omogoča, da naloge pritisnejo gumb 'Finish' in 'Check my answers', da naloge sami pregledajo, učitelju prihrani veliko časa. Učenci pregledajo odgovore. Pravilni odgovori so obarvani z zeleno, lahko naloge rešijo večkrat, če seveda učitelj izbere to možnost napačni pa z rdečo. V zgornjem levem kotu se jim prikaže tudi med nastavitvami. skupna ocena. Če želijo svoje odgovore pregledati in jih hkrati Orodje se lahko uporablja pri pouku različnih poslati učitelju, izberejo gumb 'Send my answers to the teacher'. predmetov, saj lahko v interaktivno obliko pretvorimo V tem primeru morajo vnesti elektronski naslov svojega katerikoli učni list. [4] učitelja. Učitelj obvestilo o rešeni nalogi dobi v elektronski Kot učiteljica angleščine vidim dodano vrednost tega nabiralnik, učenčeve odgovore pa ima shranjene tudi v svojem orodja tudi v tem, da lahko učencem z njim pripravim naloge, ki računu na Liveworksheets v zavihku 'Notifications'. preverjajo slušno oz. bralno razumevanje, slovnične naloge, raznolike naloge za utrjevanje besedišča ter naloge, ki preverjajo pisno sporočanje. V gradivo lahko vstavim tudi zvočni posnetek z navodili za reševanje. V času šolanja na daljavo sem svojim učencem najprej poslala povezave do posameznih nalog na tej spletni strani in jih prosila, da na koncu izberejo možnost pošiljanja odgovorov učitelju. Ker se je ta način dokaj dobro obnesel, smo kmalu prešli na interaktivne delovne zvezke, ki jih to orodje ponuja. Učenci so poročali, da jim to orodje odgovarja, saj ni bilo potrebno rešenih nalog fotografirati in naložiti v spletno učilnico, naloge pa so bile razgibane in zanimive. Odgovore sem jim sproti pregledovala in jim preko tega orodja dajala tudi povratno informacijo. Ker sem registrirala vse svoje učence in zanje pripravila interaktivne delovne zvezke, je zame največja prednost tega orodja, da imam vpogled v vse njihove naloge Slika 7. Primer interaktivnega delovnega zvezka (VIR: hkrati. Če vidim, da jim določena snov povzroča težave, jim ob lasten, zajem zaslonske slike) nalogi lahko napišem komentar in poskusim snov ponovno razložiti. Predstavljeno orodje je meni in mojim učencem bistveno olajšalo obdobje šolanja na daljavo. 6. VIRI [1] K. Bučar. 2020. Uporaba digitalnih tehnologij pri angleščini v osnovni šoli. Zbornik Mednarodne strokovne konference Kreativna učna okolja (2020), 86-95 [2] M. Sukič Kuzma. Spletna učna orodja za poučevanje in preverjanje znanja: Quizlet, Kahoot! In Liveworksheets. Webinar Rokusove centrifuge https://s3-eu-west-1.amazonaws.com/rokus-video- transcode/player/index.html?video=rokus/dn200559_webinar_kuzma_mp Slika 8. Primer komentarja ob nalogi (VIR: lasten, zajem 4/stream (pridobljeno 10. 9. 2021) [3] Spletno orodje Liveworksheets zaslonske slike) https://www.liveworksheets.com/aboutthis_en.asp (pridobljeno 16. 8. 2021) Če učitelj želi boljši pregled nad delom učencev, pa se lahko [4] Interaktivni učni listi Liveworksheets https://racunikt.splet.arnes.si/2020/05/14/interaktivni-ucni-listi-liveworksheets odloči za drugo, nekoliko bolj zapleteno varianto. Za učence (pridobljeno 10. 9. 2021) ustvari interaktivne delovne zvezke (slika 7), v katere doda [5] Program interaktivnih delovnih listov lastne naloge oz. naloge drugih uporabnikov. Učenci si morajo https://podpora.sio.si/liveworksheets/ za dostop do delovnih zvezkov ustvariti svoj račun, lahko jim (pridobljeno 16. 8. 2021) ga ustvari tudi učitelj. Z uporabniškim imenom in geslom se prijavijo v orodje (izberejo zavihek 'Student access') in dostopajo do delovnih zvezkov oz. nalog, ki jim jih učitelj dodeli. Učitelj ima v tem primeru vpogled v njihove delovne 478 Poučevanje loma in odboja svetlobe na daljavo Online teaching light refraction and reflection Primož Hudi II. OŠ Celje Celje, Slovenija primozhudi@gmail.com POVZETEK KEYWORDS Poučevanje na daljavo predstavlja izziv za veliko večino učiteljev, saj so bili čez noč prisiljeni spremeniti oz. prilagoditi Refraction and reflection of light, optical collection, simulation, klasičen način poučevanja. Učenci so sprva kazali navdušenje online learning nad takšnim načinom dela, nato pa je motivacija hitro padla. Poučevanje na daljavo pri vsakem predmetu poteka drugače, kot 1 UVOD sicer. Predmet fizike je še posebna specifika, saj proučevanje naravnih zakonov, s pomočjo različnih eksperimentov, zahteva Epidemija je dodobra premešala karte v izobraževalnem sistemu precej prilagajanja pri sami izvedbi pouka. V prispevku je na vseh stopnjah. Učitelji vseh predmetov so morali »čez noč« predstavljen IKT pristop k poučevanju loma, odboja svetlobe ter prilagoditi klasični pouk in se lotiti izvajanja pouka prek totalnega odboja v osnovni šoli. Pri delu je poleg klasičnih videokonferenc. Potek dela se je najbolj spremenil pri predmetih, pripomočkov nujno potrebna optična zbirka in stojalo, kamor pri katerih učenci pridobivajo ročne spretnosti in izvajajo, del vpnemo kvalitetno spletno kamero. Razlago, podkrepljeno s ali večino ur, praktičnega pouka. Fizika je nekje vmes. poskusi, je smiselno povezati s spletnimi orodji (simulacijami, Kakovostno razlaganje snovi ne vključuje zgolj teorije, ampak je video posnetki, slikami življenjskih situacij). Poskusi in IKT treba teorijo in prakso, v ravno pravi mešanici, prepletati. poučevanje je eden izmed redkih pristopov, ki tudi v teh časih Poučevanje fizike na daljavo je za vsakega učitelja dvigujejo motivacijo med učenjem prek videokonferenc. svojevrsten izziv, ker ustaljena praksa, ki predvideva demonstracije eksperimentov, pogosto pade v vodo oz. je KLJUČNE BESEDE potrebno kar nekaj truda in volje, če želimo isto snov učencem podati na podoben in zanimiv način kot v šoli. Nazornost Lom in odboj svetlobe, optična zbirka, simulacija, poučevanje prikazanega je ključna. Tu se mora učitelj potruditi, da zagotovi na daljavo ustrezno opremo (prenosni računalnik, optično zbirko, močnejši ABSTRACT laser, kakovostno spletno kamero na premičnem stojalu in druge pripomočke za demonstracijo eksperimentov) in prostorske Online teaching is initially a challenge for the vast pogoje (v tem primeru pri lomu svetlobe dovolj zatemnjeno majority of teachers, as they were forced to change classical way učilnico), da so eksperimenti nazorni in dobro vidni. V prispevku of teaching, overnight. Pupils were bosta predstavljeni lom in odboj svetlobe ter totalni oz. popolni showing enthusiasm above such manner of work at odboj z eksperimentalnega in IKT vidika pri delu na daljavo. first, then motivation fell quickly. Tema bo predstavljena zaradi pohval s strani učečih. Po Distance learning for every single lesson requires different njihovem mnenju niso imeli večjih težav pri razumevanju working modes, then usual. obravnavane teme, ker so prek videokonferenc jasno videli For example, teaching Physics in Primary school, demands laserje, oznake kotov in v celoti razumeli bistveno razlago, ki several considerable adaptation in the actual implementation of sodi k obravnavani snovi. Poleg poskusov so bile učencem very individual clarifying of natural phenomena with its’ pokazane simulacije, ki so v nadaljevanju predstavljene. experiments which should be associated with online learning. Pomembno je, da so popoldne lahko v spletni učilnici odprli te Therefore, the paper presents the ICT approach to teaching iste programe, snov dodatno raziskali in nadgradili pridobljeno refraction, reflection and total reflection in primary school. dopoldansko znanje, pravilno rešili kvize v spletni učilnici ter For this kind of teaching an optical collection, stand and a well naredili nalogo v delovnem zvezku. Vsi učenci, ki so pokazali webcam are absolutely necessary. zanimanje za razumevanje snovi oz. željo po višjih ocenah, so Also, the explanation, supported by experiments, is reasonable to snov razumeli. Na drugi strani pa je tako kot vedno (pre)visok connect with online tools (simulations, videos, pictures of life odstotek tistih, ki jim je vseeno, s kakšnim znanjem bodo vstopili situations). v srednjo šolo. Experiments and ICT teaching is one from Pouk na daljavo je daleč od tega, kar si motiviran učitelj in among rare approaches that, even in these times, raises učenec želita, se pa da na različne načine spodbuditi zanimanje motivation while learning through video-conferencing. za učenje fizike. Eden večjih minusov pouka na daljavo je stik v učilnici na relaciji učitelj – učenec. Povratna informacija je v razredu bistveno hitrejša in bolj nazorna. Konkretno pri lomu in 479 odboju svetlobe, učitelj veliko hitreje opazi, ali so narisane količnikov. Z merilnikom »speed« je mogoče izmeriti hitrost vpadne pravokotnice, so označene puščice na žarkih ter ali so svetlobe v različnih medijih. Mala črka c je oznaka za hitrost koti pravilno označeni itd. svetlobe v vakuumu in znaša približno 300 000 km/s; 0,67 c pa v tem primeru predstavlja hitrost svetlobe v steklu, kar znaša približno 200 000 km/s. Z merilnikom »intenzivnost« je mogoče 2 JEDRO na preprost način analizirati, kako se gostota svetlobnega toka pri Lom svetlobe je v življenju pogost pojav, zato je v knjigah, odbitem in lomnem žarku spreminja z vpadnim kotom (slika 2). učbenikih in člankih mnogokrat opisan. Na to temo ni težko najti Ena izmed možnih dodatnih nalog za učence je, da v tabelo raznolikih zanimivih eksperimentov. Pri tej tem smo na daljavo, vpišejo vpadni, lomni in odbojni kot, nato pa za vsako povečajo izvedli poskus s kovancem. Slednjega položimo v neprozorno vpadni kot za 10 stopinj (od 0 do 90 stopinj) in z orodjem posodo. Kamero nastavimo pod takšnim kotom, da nam rob »intenzivnost« odčitajo odstotek svetlobe pri odbojnem in posode zakriva kovanec. Ko v posodo nalijemo vodo, zaradi lomnem žarku. loma svetlobe kovanec zagledamo [1]. Če prst postavimo za steklen kvader, zagledamo navidezno razrezan prst [2]. Preprost poskus naredimo s slamico ali kakšnim drugim podolgovatim predmetom. Ko ga pod kotom postavimo v kozarec, je videti zlomljen, hkrati se pa navidezno spremeni tudi debelina potopljenega dela predmeta [3]. Odbojni zakon najlažje demonstriramo z optično zbirko, kjer preprosto prikažemo, da sta vpadni in odbojni kot skladna. Odboj svetlobe je pri ravnem zrcalu in zmečkani alufoliji popolnoma drugačen [4]. S tem prikažemo odboj na ravnih (okno) in hrapavih (malo razburkana gladina jezera/morja) površinah. Za nazoren prikaz loma svetlobe potrebujemo optično zbirko, ki vključuje steklen kvader (planparalelno ploščo), laser, magnetno tablo in kamero. Priporočljivo je, da kamero fiksiramo na fleksibilno stojalo, zato da jo lahko hitro premikamo in pri tem Slika 2: Simulacija loma svetlobe z aplikacijo »bending- ne izgubljamo časa pri menjavi poskusov. Ko zgornjo opremo light« [5] ustrezno kalibriramo, je demonstracija loma svetlobe celo bolj nazorna kot v razredu pred učenci. Na slikah 1 je razvidno, da je Z drsnikom lahko spreminjamo valovno dolžino in tako vpadni kot (to je kot med vpadno pravokotnico in vpadnim preverimo, katera barva se bolj lomi in razlago nadgradimo z žarkom) manjši od lomnega kota (to je kot med vpadno življenjskim primerom, npr. rdeča barva sončnega zahoda. pravokotnico in lomnim žarkom) pri prehodu iz optično redkejše V primeru na sliki 3, snov ni znana in je treba določiti lomni v optično gostejšo snov. Hkrati je viden tudi odbojni žarek pri količnik te snovi in na podlagi njega sklepati, za katero snov gre. prvem in drugem lomu. Žarek, ki izstopi iz stekla je vzporeden Nalogo lahko izvedemo na dodatnem pouku v osnovni šoli. prvotnemu, preden je vstopil v steklo. Slika 1: Demonstracija loma svetlobe na optični zbirki z uporabo planparalelne plošče (poskus prek videokonference) Slika 3: Simulacija loma svetlobe z aplikacijo »bending- light« [5] Z aplikacijo »bending-light« (slika 2) ali v prevodu »lom svetlobe« lahko učenci detajlno raziščejo odboj in lom svetlobe Na drugem zavihku »lom na različnih telesih«; na sliki 4, na prehodu sredstev različnih optičnih gostot oz. lomnih imamo na razpolago nekaj različnih teles, ki jim lahko 480 nastavljamo lomni količnik, laser (ali več laserjev) s poljubno nastavljivo valovno dolžino. Vklopimo lahko tudi prikaze odboja žarkov, prikaz vpadnih pravokotnic in kotomer. Predvsem vpadne pravokotnice pridejo zelo prav (na sliki 4 so označene s črtkanimi črtami). Če zberemo vidno svetlobo namesto rdečega laserja, lahko na preprost način pokažemo razklon svetlobe (mavrico). Slika 6: Totalni odboj v aplikaciji [5] Poskuse pri fiziki je priporočljivo čim večkrat povezati z življenjem. Totalne odboje v optičnem vlaknu prikazuje slika 7, slika 8 predstavlja prerez optičnega vlakna, na sliki 9 pa je predstavljen eksperiment pri uri, katerega lahko brez težav povežemo z optičnim medmrežjem. Slika 4: Prikaz različnih funkcij/parametrov (npr. lomni količnik teles in ozadja), ki jih omogoča simulacija »bending- light« [5] Naslednja simulacija loma svetlobe nam omogoča spoznavanje lomnih količnikov na enostaven način [6]. Pri obravnavi loma svetlobe učenci spoznajo pojem popolni ali totalni odboj (na sliki 5 je predstavljen eksperiment na videokonferenci, na sliki 6 pa namenska aplikacija). To je pojav, pri katerem se vpadni žarek na meji med optično gostejšim in Slika 7: Totalni odboji v optičnem vlaknu optično redkejšim sredstvom v celoti odbije, če je vpadni kot večji od mejnega kota. Demonstriramo ga lahko samo pri prehodu svetlobe iz optično gostejše snovi v optično redkejšo snov. Preprostih demonstracijskih poskusov je precej. Eden bolj zabavnih je ta, da v plastenko izvrtamo luknjo, vanjo natočimo vodo, nato pa z druge strani plastenke z laserjem posvetimo na luknjo. Laserski žarek se totalno odbija po curku vode in tako dobimo razsvetljen umivalnik. Poskus dobro uspe z močnejšim laserjem (moči npr. 250 mW). V šoli je treba paziti, da so učenci pravilno razporejeni, da ne bi pomotoma komu laser posvetil v oči. Pri tej moči je drugače zelo priporočljiva/nujna uporaba Slika 8: Prerez optičnega vlakna namenskih očal, pri poučevanju na daljavo pa tovrstni ukrepi za učence, niso potrebni. Slika 9: Popolni odboji v optičnem vodniku (poskus pri uri) Popolni odboj lahko pokažemo tudi z uporabo akvarija, vode in laserja [8]. S preprostim poskusom lahko pokažemo, da se svetloba Slika 5: Totalni odboj na videokonferenci lahko ukrivi [8]. Dan ali dva pred izvedbo poskusa v trilitrsko 481 posodo z vodo (akvarij) stresemo 250 gramov sladkorja. LITERATURA IN VIRI Sladkorja ne mešamo, ker se sam raztopi v vodi. Pri tem se [1] Ambrožič, M., Karič, E., Kralj S., Slavinec M. in Zidanšek A: Fizika 7. ustvari majhen gradient gostote, ki zadošča, da se laserski žarek DZS: Ljubljana, 1997. v vodi ukrivi. Eksperiment je bistveno bolje viden, če je učilnica [2] Pople, S.: Naravoslovje: Fizika. Tehniška založba Slovenije: Ljubljana, močno zatemnjena. 1992. [3] Johnson K.: Fizika: preproste razlage fizikalnih pojavov. Tehniška založba Slovenije: Ljubljana, 1996. [4] Interaktivni fizikalni portal: Odbojni zakon (splet) . 2012. Dostopno na 3 ZAKLJUČEK naslovu https://www.youtube.com/watch?v=YkYKR8CLf5o&t=31s&ab_channel=C V jedru članka so predstavljeni različni načini/ideje, kako oolphysicsvideosPhysics (10.8.2021) učencem na daljavo ali v živo učitelji fizike predstavijo lomni in [5] Phet interactive simulations (University of Colorado Boulder), bending- odbojni zakon ter popolni odboj. Skoraj 10-letna praksa kaže, da light (splet). 2021. Dostopno na naslovu https://phet.colorado.edu/en/simulation/bending-light (10.8.2021) učenci snov razumejo, če je predstavljena na zgoraj opisan način, [6] Brezar, V.: Lom in odboj svetlobe (splet). 2010. Dostopno na naslovu ki vključuje številne poskuse in simulacije. Podpora vsega http://www.geogebr.si/geometrijska-optika/odboj-in-lom-svetlobe/ naštetega v spletni učilnici je pika na i. Epidemija je temeljito (10.8.2021) spremenila poučevanje prek videokonferenc, ni pa izgovor, da se [7] FS Community. 2012. Dostopno na naslovu https://community.fs.com/blog/the-advantages-and-disadvantages-of- ne da kvalitetno predstaviti določene teme. Avtor članka bo optical-fibers.html (10.8.2021) navdušen, če bo kateri učitelj fizike ali naravoslovja v tem članku [8] Gupta, A.: Light experiments (splet). 2012. Dostopno na naslovu dobil kakšno praktično idejo in jo uporabil v praksi. http://www.arvindguptatoys.com/films.html (10.8.2021) 482 Usvajanje črk v prvem razredu na daljavo Teaching year 1 literacy online during the pandemic lockdown Tamara Jerina Osnovna šola Antona Martina Slomška Vrhnika Vrhnika, Slovenija tamara.jerina@guest.arnes.si POVZETEK Diversity and inclusion principles were considered when V prispevku sem opisala delo v prvem razredu osnovne šole, ko planning lessons, as students do not share the same learning so se šolska vrata za nekaj časa zaprla in je pouk potekal preko opportunities, like equity and accessibility to Technology and the računalnikov. Čeprav na to nismo bili pripravljeni ali izobraženi, same level or amount of parental support. smo učni proces hitro izpeljali tako, da so učenci napredovali v svojem znanju in dosegali cilje, ki smo jih zastavili. KEYWORDS Literacy, stages of literacy, online learning, year 1 Pri izvajanju pouka preko računalnika so naši najmlajši šolarji potrebovali aktivno podporo staršev, s katerimi smo učitelji razvili še globje zaupanje in razvili povsem nov odnos. 1 UVOD Opisala sem enega izmed postopkov obravnave posamezne Opismenjevanje je dolgotrajen in zahteven proces, s katerim velike tiskane črke, ki se je izkazal kot odličnega. Pri tem sem človek razvije funkcionalno pismenost. Razvijati se začne že v upoštevala različne metode dela ter poskusila pouk preko ekrana predšolskem obdobju, poteka pa preko štirih komunikacijskih vseeno izpeljati s čim več gibanja in različnimi dejavnostmi, kot kanalov: poslušanja, govorjenja, branja in pisanja [1]. to počnemo tudi v razredu. Dejavnosti, s katerimi razvijamo vse štiri veje opismenjevanja, se med seboj prepletajo, prav vse pa potrebujejo čas, veliko časa, Pri usvajanju velikih tiskanih črk v obdobju šolanja na daljavo da jih otroci usvojijo. Proces opismenjevanja se zaključi po sem upoštevala načelo raznolikosti z zavedanjem, da nimajo vsi koncu prve triade. Učni načrt za slovenščino (2018) predvideva, otroci enakih možnosti, enake količine časa s starši in enake da proces opismenjevanja poteka postopno, sistematično in podpore s strani le teh. individualno [2]. Pomembno je zavedanje, da imajo otroci ob KLJUČNE BESEDE vstopu v šolo velike razlike v stopnji razvitosti pismenosti, zato nobena metoda ni primerna za vse učence. Naloga učitelja je Opismenjevanje, faze opismenjevanja, delo na daljavo, prvi ugotoviti, kako dobro predznanje ima posamezni otrok in na razred podlagi tega izdelati načrt opismenjevanja. Mlajši učenci so bili ABSTRACT letos primorani precejšen del opismenjevanja opraviti doma. Njihovi učitelji so pripravili različne dejavnosti, a »glavni The article details the process of teaching literacy in year one nadzorniki« so bili starši oziroma skrbniki. during the pandemic lockdown, while schools were closed and V svojem prispevku se bom omejila na čas, ko smo s prvošolci education continued online. Teachers found conducting literacy glasovom dodajali črke in na daljavo spoznavali slovensko lessons specifically challenging, as many felt unprepared and abecedo. untrained in the pedagogy of online teaching. Through the Ko učence učimo abecedo, lahko izberemo med tremi metodami perseverance of teachers and peer support, lessons were redrafted poučevanja (slika 1). and the learning process altered to advance knowledge more successfully and to better suit the needs of all students. We found that our youngest students needed active parental support to participate in online lessons. We are delighted to report that during this interminable pandemic, parent-teacher relationships have further developed and deepened in terms of respect and trust. This article describes a teaching procedure of a single capital letter. It proved itself as an excellent model for online learning, as it utilizes different teaching methods and employs a variety of teaching activities designed to promote physical activity in students. Slika 1: Metode učenja črk 483 Najbolj praktična se mi zdi kombinacija analitične in sintetične metode, ker ima skoraj vsak glas v slovenski abecedi tudi svojo črko [3]. 2 FAZE OBRAVNAVE TISKANE ČRKE J. Chall zagovarja zgoden in sistematičen pouk glasovnega zavedanja, ki poteka preko več stopenj. Za nas sta pomembni predstopnja, ki poteka v predšolskem obdobju in v kateri otroci prepoznavajo rime, začetne in končne glasove, ter prva stopnja, poimenovana kot faza dekodiranja, pri kateri otrok vzpostavi Slika 3: Prikaz napačnih črk povezavo med glasom in črko. Ob koncu te stopnje naj bi učenci razvili sposobnost vidnega in delno slušnega razločevanja [4]. Sledil je trening poteznosti s konkretnimi materiali (slika 4). V Preden začnemo z obravnavo črk, veliko časa namenimo veliko pomoč so bili starši oziroma skrbniki učencev, ki so glaskovanju posameznih besed. Učenci tako že slišijo glasove in pomagali pri pripravi materiala, nato pa še preverjali delo svojih jih med seboj razlikujejo, sedaj pa je čas, da posameznemu glasu otrok. Občasno smo se dogovorili, da so delo poslikali in mi priredijo simbol, tj. črka. poslali nekaj fotografij. Za vsako črko sem pripravila več Učencem sem v digitalnih drsnicah pripravila različne dejavnosti, med katerimi so morali učenci opraviti vsaj dve, npr. fotografije. Njihova prva naloga je bila poimenovati predmet na oblikovanje črk s pokrovčki, vrvicami, kockami, slamicami, fotografiji. Nato so izločili slike, ki ne vsebujejo določenega palčkami za ušesa, igračami, plastelinom … glasu. Med preostalimi slikami so izbrali najprej tiste, ki imajo obravnavan glas na začetku, nato na sredini in nazadnje še na koncu besede. Sledila je naloga premikanja po domu. Učenci so poiskali čim več besed, ki vsebujejo v svojem poimenovanju obravnavan glas. Nastavila sem odštevalnik časa in po eni ali dveh minutah smo se spet srečali na videokonferenci. pred računalniškimi ekrani. Učenci so naštevali predmete, ki so jih našli. Ker smo imeli v naši skupini tudi učence s statusom tujca, smo določene predmete tudi opisali ali pa smo si pomagali s sliko na spletu. Tako smo poskrbeli, da so širili svoj besedni zaklad. V naslednji fazi sem učencem pokazala poteznost obravnavane črke (slika 2). Pri tem smo uporabljali program za izdelavo digitalnih drsnic PowerPoint. Posnetek so si učenci večkrat ogledali. Skupaj smo opisali, kako je poteznost potekala. Pri vsaki črki smo vedno označili, kje se zapis začne, v katero Slika 4: Delo s konkretnim materialom smer poteka in katero črto (v kolikor jih je več) napišemo najprej in katero nazadnje. Ko so učenci usvojili poteznost črke s konkretnim materialom, smo prešli v fazo zapisa v zvezek. Pred začetkom smo bili pozorni na pravilno sedenje, pravilno držo telesa ter pravilen prijem svinčnika, ki je moral biti že pred poukom ošiljen. Sledili smo načelu od večje črke k manjši. Ob koncu ure so učenci zapisali tudi nekaj besed, ki vsebujejo obravnavano črko. Ker so nekateri izmed učencev že poznali zapis vseh črk, so namesto posameznih besed sestavljali smiselne povedi ali krajše zgodbe, ki so jih naslednjo uro z veseljem prebrali. 3 REZULTATI Pri delu na daljavo sem uporabljala program PowerPoint, ki se je izkazal kot odličen pripomoček pri opismenjevanju. V njem sem Slika 2: Prikaz poteznosti obravnavane črke lahko izdelala učno uro, ki je bila opremljena z zanimivimi animacijami in zvokom. Prav tako sem lahko izdelala kvize, ki Nato sem jim na »beli tabli« na videokonferenci pokazala še so jih učenci hitro znali reševati tudi brez pomoči staršev. nekaj napačno napisanih črk, npr. narobe obrnjenih, neprimerne Videokonferenčne ure smo izvajali s programom ZOOM, v velikosti trebuščkov itd (slika 3). Učenci so potezo pravilno katerem sem redno uporabljala belo tablo, deljenje zaslona in t.i. zapisane črke povadili s pisanjem po zraku, mizi, zvezku in po »breakout room«, kjer so učenci opravljali delo v manjših svoji dlani. skupinah. Le tako sem lahko zagotovila ustrezno diferenciacijo pri poučevanju na daljavo v živo. 484 4 ZAKLJUČEK Učenci so v tem obdobju spoznali, kako pomembni so vsi Obdobje, v katerem smo se znašli, nam je prineslo obilico novih člani v skupnosti, kako pomembno je, da vsak udeleženec opravi izkušenj, ki jih bomo lahko uporabili tudi v prihodnje. Med svojo nalogo in je zanjo tudi odgovoren. učitelji in starši se je razvilo zaupanje, ki je bilo nujno potrebno za dosego učnih rezultatov pri učencih. Starši so imeli vpogled v LITERATURA IN VIRI delo učitelja, učitelji pa smo bili v času šolanja na daljavo ob [1] Pečjak, S. (2009): Z igro razvijamo komunikacijske sposobnosti učencev. Ljubljana: Zavod RS za šolstvo in šport. določenih trenutkih skoraj člani družine naših učencev. [2[ Program Osnovna šola, Učni načrt, Slovenščina (2018). Ljubljana: Zavod Medsebojno spoštovanje vseh udeležencev šolanja na daljavo RS za šolstvo [3] Golli, D. (1991): Opismenjevanje v prvem razredu. Novo mesto: je učencem prineslo dobre temelje znanja, s katerimi bodo lahko Pedagoška obzorja. tudi v prihajajočem šolskem letu dosegali zavidljive rezultate. [4] Chall, J. (1983). Stages of reading development. V: Grginič, 2005, 99-100. 485 Uporaba spletnega orodja BookWidgets za preverjanje in ocenjevanje znanja pri pouku nemščine Using the BookWidgets online tool to evaluate and assess knowledge in German lessons Urša Jerman OŠ Toma Brejca Šutna 39 1241 Kamnik jerman.ursa@gmail.com POVZETEK assess student’s knowledge. As a primary school teacher of V prispevku je predstavljeno delo s spletno aplikacijo German, I was looking for an online tool that would allow me BookWidgets pri pouku nemščine v 6., 7. in 8. razredu v namen to easily create tests and possibly also automatically correct preverjanja in ocenjevanja znanja. answers. Pupils accessed the composite tests and assignments by clicking on the link in the online classroom and did not need V šolskem letu 2020/21 smo se učitelji in učenci ponovno their own user account or password to use the tool. Once the znašli v situaciji, ko se je za obdobje skoraj treh mesecev assignments were reviewed and supplemented with comments, klasični pouk v učilnicah ponovno spremenil v virtualno učenje they were forwarded to the pupils at their email address. In this na daljavo. Učitelji smo prišli do spoznanja, da virtualni pouk way, my pupils received a faster feedback on their knowledge, ne bo mogel za takšno dolgo obdobje zajemati le podajanje in and I as their teacher was provided with a more organized utrjevanje nove učne snovi, temveč bo potrebno zajeti tudi del overview of the large number of created tasks and the results preverjanj in ocenjevanj znanja. Kot učiteljica nemščine v achieved by individual pupils. osnovni šoli sem iskala spletno orodje, ki bi mi omogočilo preprosto kreiranje testov in po možnosti tudi avtomatsko Due to the possibility of creating various types of assignments, korekcijo odgovorov. Učenci so do sestavljenih testov in nalog good transparency, and ease of use, the BookWidgets tool was dostopali s klikom na povezavo v spletni učilnici, za samo a way of motivation for me and my pupils during the distance uporabo orodja pa niso potrebovali svojega uporabniškega learning of German. računa ali gesla. Ko so bile naloge pregledane in dopolnjene s sprotnimi komentarji, so bile posredovane učencem na njihov KEYWORDS elektronski naslov. Učenci so na tak način dobili hitrejšo BookWidgets, online tool, evaluating and assessing knowledge povratno informacijo o njihovem znanju, meni pa je aplikacija omogočila bolj organiziran pregled nad velikim številom kreiranih nalog in doseženimi rezultati pri posameznih učencih. 1. UVOD Preverjanje in ocenjevanje znanja predstavlja učitelju Zaradi možnosti kreiranja raznovrstnih tipov nalog, dobre zahtevnejši del pedagoškega procesa, na katerega se je preglednosti in preproste uporabe, je orodje BookWidgets za potrebno dobro pripraviti. Pomemben del učne ure je ravno delo na daljavo motiviralo tako mene kot tudi moje učence pri tako utrjevanje snovi, ki služi kot pokazatelj doseženega znanja pouku nemščine. in temelj za nadaljnjo preverjanje in ocenjevanje. Na kakšen način bo preverjanje in ocenjevanje izvedeno je odvisno od KLJUČNE BESEDE namena, cilja in vsebine [1]. BookWidgets, spletno orodje, preverjanje in ocenjevanje V šolskem letu 2020/21 v času pouka na daljavo sem se kot znanja učiteljica nemščine in angleščine v osnovni šoli znašla pred velikim izzivom, in sicer na kakšen način hitro in preprosto ABSTRACT preveriti, predvsem pa oceniti znanje pri učencih. V običajnih The article presents the usage of online application razmerah, ko pouk poteka v učilnici, učitelj najhitreje dobi BookWidgets in German lessons in 6th, 7th, and 8th grade for povratne informacije o znanju učencev z ustnim preverjanjem the purpose of evaluating and assessing knowledge. in ocenjevanjem, ki ga lahko vključi k vsaki učni snovi [1]. V času pouka na daljavo pa je ravno ta način meni osebno vzel In school year 2020/21, teachers and students once again found največ časa za izvedbo in celotno organizacijo. Povrhu vsega themselves in a situation where, for a period of almost three pa takšen način ocenjevanja na daljavo ni bil tako kakovosten. months, classical classroom teaching was once again Pri vključevanju digitalne tehnologije v namen preverjanja in transformed into virtual distance learning. Teachers have come ocenjevanja znanja je potrebno načrtovati uporabo IKT za to the realization that virtual teaching will not only be able to formativno spremljanje in sumativno ocenjevanje znanja. Ob cover the explanation and revision of new learning material for tem je pomembna tudi » ustreznost digitalnega ocenjevanja, such a long period, but it will also be necessary to evaluate and 486 pristopov in prilagajanja strategij« [6]. Učitelj mora biti v ta • preprosta navodila, ki uporabniku omogočajo seznanitev name usposobljen zbirati, kritično vrednotiti in tolmačiti z vsebino spletnega orodja za preverjanje in ocenjevanje digitalne podatke o dosežkih učencev, prilagajati strategije za znanja podporo učencem ter posredovati povratne informacije [6]. • dostopnost: uporabnik kreira lastni račun, ki ga zaščiti z Moj cilj je bil poiskati spletno orodje, ki bi mi omogočilo geslom za varno hrambo sestavljenih preverjanj in avtomatsko popravljanje nalog in s tem tudi pridobitev pisne ocenjevanj znanja. Uporabnih lahko tudi omeji dostop ocene pri učencih, ki so obiskovali neobvezni in obvezni samo za določene goste in tako do ocenjevanja dostopajo izbirni predmet nemščina. Odločila sem se za plačljivo spletno samo pooblaščeni orodje BookWidgets, ki sem ga uporabila za kreiranje kratkih • varna in enostavna prijava v spletno orodje vaj za utrjevanje ter preverjanj in ocenjevanj znanja. Orodje • knjižnica testov po meri za enostavno dostopnost sem uporabila pri učencih 6. – 8. razreda. Reševanje nalog se je • široka paleta vprašanj, ki pomaga ustvariti učinkovite in za učence izkazalo za zelo preprosto, saj učenci za dostop ne uspešne rezultate in analize, ki lahko delujejo kot celovit potrebujejo uporabniškega računa. V spletni učilnici so lahko z vpogled v udeleženčeve uspešnosti in spretnosti enim samim klikom na povezavo dostopali do vaj in testov. Po • časovni opomnik, ki pripomore k pravočasni oddaji koncu reševanja so za uspešno oddajo morali vpisati svoje ime preverjanja oz. ocenjevanja znanja ter elektronski naslov, kamor so po potrebi prejeli mojo • objavljeno ali natisnjeno: udeleženčevi odgovori in povratno informacijo o izkazanem znanju ali rezultat pisnega rezultat so lahko deljeni preko e-pošte ali natisnjeni na ocenjevanja. Kot učiteljica sem imela z uporabo BookWidgets papir. Udeleženec lahko izbere, ali bo rezultat javno orodja organiziran, preprost in hiter vpogled v dosežke znanja dostopen ali zaseben. Udeleženci lahko do svojih pri pouku nemškega jezika. rezultatov dostopajo preko namizne ali mobilne platforme. S pomočjo povratnih informacij pa se učijo iz svojih napak 2. DIGITALNA PISMENOST PRI POUKU • objava rezultatov: uporabnik lahko izbere možnost, ali NEMŠČINE V OSNOVNI ŠOLI bo udeleženec videl svoj rezultat in rešitve takoj po končanem reševanju, ali pa bo le tega prejel s povratno V učnem načrtu za nemški jezik v osnovni šoli [3] je med informacijo, ker je morda potrebno še ročno razvrščanje splošnimi cilji pouka nemščine navedena tudi digitalna 4. BOOKWIDGETS pismenost, kar pomeni, da » Učenci pri pouku nemščine kritično uporabljajo informacijsko-komunikacijsko tehnologijo BookWidgets je aplikacija, ki omogoča kreiranje interaktivnih za pridobivanje, vrednotenje in shranjevanje informacij, za vaj ter avtomatsko popravljanje nalog. S tem učitelju prihrani njihovo tvorjenje, predstavitev in izmenjavo ter za čas za ocenjevanje ter mu omogoča, da učencu poda povratno sporazumevanje in sodelovanje v mrežah na svetovnem informacijo o njegovem znanju. Aplikacija omogoča 30- spletu.« [3]. Učenci razvijajo digitalne kompetence na različne dnevno brezplačno poskusno uporabo, plačljiva verzija pa je na načine, kot so: voljo tudi za skupino učiteljev [2]. • uporaba spletnih slovarjev Pri vstopu v aplikacijo ima registriran uporabnik pregled • pridobivanje podatkov s spleta in uporaba nad svojimi izdelanimi nalogami (v meniju na levi strani brskalnikov in iskalnikov v nemščini izberemo Widgets My Widgets) (slika 1). Pri vsaki vaji je • uporabljanje IKT za komunikacijo v nemščini (npr. napisan tudi tip naloge, torej ali gre za delovni list, kviz, igro, socialna omrežja, klepetalnice, blog, forum, ipd.) itd., kdaj je bila naloga nazadnje spremenjena ter možnost za • predstavljanje svojih izdelkov v nemškem jeziku ponovni prikaz, spreminjanje, kopiranje, deljenje in brisanje (grafično, slikovno, večpredstavno, itd.) [3] naloge. Izdelane vaje lahko uporabnik razvrsti tudi v skupne mape (slika 2). 3. TEHNIČNE LASTNOSTI SPLETNIH ORODIJ ZA PREVERJANJE IN OCENJEVANJE ZNANJA V zadnjem desetletju so izobraževalni sistemi po vsem svetu sprejeli hiter razvoj tehnologije in odkrili nove načine za uveljavljanje njihove uporabe, kar bi koristilo študentom in učiteljem. Ker je COVID-19 povzročil razburjenje v izobraževalnih sistemih, saj je motil tradicionalne razredne metode za širjenje znanja, je prišlo do potrebe nove tehnološke rešitve, ki bi podpirala vse osnovne funkcije globalnega izobraževalnega sistema. Ena od rešitev bi zato bila lahko spletna programska oprema za ocenjevanje kandidatov, ki jo je mogoče prilagoditi vsakemu oddelku ali stranki podjetij, izobraževalnih ustanov do vladnih institucij za najem, testiranje in vrednotenje posameznih uspešnosti na daljavo [4]. Spletna stran ProProfs [4][5] navaja nekaj najpomembnejših funkcij, ki so ključne pri iskanju spletnega orodja za preverjanje in ocenjevanje znanja: Slika 1: Začetni meni (Vir: https://www.bookwidgets.com/) 487 pošiljanje odgovorov; reševanje nalog lahko tudi časovno omejimo s funkcijo »exam mode«) • splošne nastavitve (način prikaza pravilnih odgovorov, točkovanje posameznih vprašanj, vklop ali izklop jezikovnega preverjanja, nastavitev gesla za reševanje) • lokalizacija (smer besedila, izbor jezika) • izgled (barva ozadja in besedila, izbor slike za ozadje) Preden objavimo končno povezavo do vaje, nam orodje omogoča, da celoten izdelek še enkrat vidimo v takšni obliki, kot bo ta prikazan učencem (klik na »Preview« zgoraj desno) (slika 4). Vprašanja lahko še vedno spremenimo, zbrišemo, Slika 2: Primer začetnega prikaza kreiranih vaj kopiramo in delimo (klik na »Share« zgoraj desno) (slika 4). (Vir: lasten, zajem zaslonske slike) Povezavo do vaje lahko delimo ne samo z učenci, temveč tudi z ostalimi učitelji, ki so registrirani uporabniki tega orodja. Ko želimo ustvariti novo vajo, kliknemo na modro ikono Delitev z učitelji omogoča, da drugi učitelj kopira vaš izdelan »Create new widget« (slika 2) in lahko izbiramo med različnimi »Widgets« v svojo zbirko in ga tudi lahko poljubno spreminja. vrstami nalog: • Testi in pregledi snovi (delovni list, časovna premica, kviz, deljen delovni list, itd.) • igre (vislice, spomin, križanka, iskanje parov, itd.), • slikovne in video ponazoritve snovi • matematične naloge Slika 4: Prikaz sestavljenih vprašanj z menijsko vrstico (Vir: lasten, zajem zaslonske slike) 4.2 Prikaz rezultatov reševanja Orodje BookWidgets v svojem začetnem meniju ponuja tudi možnost vpogleda v rezultate rešenih vaj (klik na Grades&Reporting  Student Work) (slika 1). Najprej je Slika 3: Različni tipi vaj za kreiranje testov in pregledov predstavljen povprečen rezultat reševanja posameznega snovi (Vir: https://www.bookwidgets.com/) vprašanja glede na celotno skupino učencev (slika 5) , nato pa 4.1 Primer: kreiranja delovnega lista po ima učitelj še vpogled v dosežek pri posameznem učencu (slika korakih 6). Pri vsakem posamezniku je zabeležen datum in čas reševanja, končni rezultat ter dosežene točke pri posameznem Ko izberemo tip vaje »Worksheet« (slika 3) iz nabora možnosti vprašanju. Obarvana okenca pri vprašanjih so pokazatelj, kako za oblikovanje testov in pregledov snovi, se nam odpre nova dobro je učencev rešil vprašanje (zelena- zelo dobro, rumena – menijska vrstica, ki ponuja naslednje: dobro, rdeča – slabo). • poimenovanje delovnega lista • vprašanja (dodajanje vprašanj različnega tipa, kot so: besedilo, vprašanja odprtega tipa, dopolnjevanje, povezovanje, itd.). • naslov/poročilo (omogočimo, da učenci pošljejo odgovore in po potrebi označimo, da dovoljujemo samo enkratno Slika 5: Prikaz povprečnega dosežka glede na skupino (Vir: lasten, zajem zaslonske slike) 488 Slika 9: Pošiljanje povratne informacije učencu (Vir: lasten, zajem zaslonske slike) 4.4 Primer sestavljene naloge: Povezovanje nemških povedi s slovenskimi prevodi Za kreiranje takšne naloge pri tipu ponujenih vprašanj izberemo Slika 6: Prikaz rezultata za posameznega učenca (Vir: ikono »Word match question« (slika 10). V prazno okence lasten, zajem zaslonske slike) vpišemo navodilo naloge (slika 11), nato pa dodamo željene povedi, ki se bodo pojavile v levem in desnem stolpcu (slika S klikom na učenca se odpre vpogled v njegove odgovore, ki 11). so že avtomatsko popravljeni (slika 7). Pri napačnih odgovorih se izpiše tudi pravilna rešitev. Popravke lahko ročno spremenimo (npr. dodelimo večje ali manjše število točk, označimo odgovor kot pravilen/napačen), k vsaki nalogi pa lahko dodamo tudi komentar. Pri vprašanjih, kjer učenci zapišejo daljše besedilo, lahko označimo napake direktno v besedilu in dodamo opombo (slika 8). ikona Slika 10: Primer naloge- povezovanje povedi s prevodi, 6.razred (Vir: lasten, zajem zaslonske slike) navodilo Slika 7: Avtomatski popravek odgovorov z vidnimi rešitvami (Vir: lasten, zajem zaslonske slike) povedi Slika 11: Povezovanje povedi- oblikovanje naloge (Vir: lasten, zajem zaslonske slike) 4.5 Primer sestavljene naloge: Dopolnjevanje Slika 8: Naloga z daljšim odgovorom, označenimi povedi z manjkajočimi besedami iz okvirja napakami in dodatnimi opombami (Vir: lasten, zajem Za kreiranje takšne naloge pri tipu ponujenih vprašanj izberemo zaslonske slike) ikono »Drag words in sentence« (slika 12). V prazno okence vpišemo navodilo naloge. Nato dodamo besedilo v katerem 4.3 Pošiljanje povratne informacije učencem besede, ki se bodo pojavile v okvirju »obdamo« z znakom Po končanem pregledu naloge učenca nam orodje <<>> (npr. <>). Na koncu lahko k nalogi dodamo še BookWidgets omogoča, da nalogo prenesemo kot PDF besede, ki bodo delovale kot t. i. distraktorji. datoteko, jo s popravki pošljemo nazaj učencu, zbrišemo ali shranimo v arhiv (slika 9). 489 ikona 3. Ich <> gern Inlineskates und du <> gern. 4. <> du gern fern? Nein, ich <> nicht gern fern. 5. Paulina und Jan <> gern Skateborad und <> gern im Sommer baden. 5. ZAKLJUČEK Uporaba spletnega orodja BookWidgets za namen preverjanja in ocenjevanja znanja pri pouku nemščine v 6., 7. in 8. razredu med poukom na daljavo se je izkazala kot primer zelo dobre Slika 12: Primer naloge- dopolnjevanje povedi z prakse. Učenci so hitro osvojili način reševanja različnih tipov manjkajočimi besedami iz okvirja, 7. razred nalog ter pošiljanje končnih odgovorov učiteljici. Za delo v (Vir: lasten, zajem zaslonske slike) takšni aplikaciji so bili motivirani, saj je reševanje potekalo veliko hitreje kot pa pisanje odgovorov v zvezek in skeniranje Oblikovanje izgleda takole: 1. Thomas <> jeden Tag um 6.30 Uhr auf. Wann izdelkov ter pošiljanje v spletno učilnico. Da same naloge niso <> Renate und Tina auf? bile tako »neprivlačne« na prvi pogled, sem jih obogatila s 2. Ich <> in die Schule um 8 Uhr. Um vie viel Uhr slikami in včasih tudi kratkimi video posnetki, ki so učence še <> du in der Schule? dodatno spodbudili k reševanju. Dostop do reševanja preverjanj 3. Oliver <> seine Hausaufgaben um 17 Uhr. in ocenjevanj znanja je bil zelo preprost. Potrebovali so samo 4. Um 16 Uhr <> ich meine Freundin Pauline an. povezavo, ki je bila objavljena v spletni učilnici. Pošiljanje 5. Wir <> um 19 Uhr zu Abend. odgovor učencem ni delalo večjih preglavic, saj so za uspešno 6. Am Montag <> sie mit dem Unterricht um 9 Uhr oddajo potrebovali vpisati le svoje ime in elektronski naslov. an. Učenci so v aplikaciji reševali tudi vmesna krajša utrjevanja 7. Er <> um 18 Uhr in die Turnhalle und spielt znanja, kjer so se jim po končnem reševanju, ki ni bilo omejeno Basketball. na čas, izpisale rešitve. Tako so dobili takojšen vpogled v svoje 8. Zum Frühstück <> Susane ein Stück Brot mit Butter znanje, kar nam je v času pouka preko video konferenc und Marmelade. velikokrat prihranilo čas za preverjanje rešitev. Spletno orodje BookWidgets ni bilo preprosto za uporabo le za 4.6 Primer sestavljene naloge: Dopolnjevanje moje učence pri pouku nemščine, temveč tudi zame kot povedi s ponujenimi odgovori učiteljico. Ponuja velik izbor različnih naborov nalog za oblikovanje, istočasno pa je oblikovanje le teh dokaj preprosto, saj vsak tip naloge vsebuje jasna in kratka navodila za kreiranje. Po vrhu vsega mi je uporaba tega spletnega orodja olajšala delo ikona z avtomatskim pregledovanjem in vrednotenjem odgovorov, enostavnim pregledom nad rezultati učencev in pošiljanjem povratnih informacij. Aplikacija BookWidgets je po mojem mnenju dovolj preprosta za uporabo, da bi jo lahko učitelj predstavil tudi učencem v 4. in 5. razredu osnovne šole, kjer imajo otroci v času digitalizacije že dovolj kompetenc za osvojitev omenjenega spletnega orodja. 6. LITERATURA IN VIRI Slika 13: Primer naloge- dopolnjevanje povedi s [1] Golubič (2013). Didaktični vidiki preverjanja in ocenjevanja znanja. ponujenimi odgovori, 6. razred Diplomsko delo. (https://dk.um.si/Dokument.php?id=55046; Dostopno (Vir: lasten, zajem zaslonske slike) 16. 8. 2021) [2] https://www.bookwidgets.com/ (Dostopno 16. 8. 2021) [3] Kač, L. et al. 2016. Učni načrt. Program osnovna šola. Nemščina. Za kreiranje takšne naloge pri tipu ponujenih vprašanj izberemo Ljubljana. MIZŠ, ZRSŠ. Objavljeno na: ikono »Fill-in-the-blank(s) question« (slika 13). V prazno https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- okence vpišemo navodilo naloge. Nato dodamo besedilo, kjer sola/Ucni-nacrti/obvezni/UN_nemscina.pdf (Dostopno 11. 9. 2021) [4] https://www.proprofs.com/quiz-school/blog/best-features-you-need-in- ponujene rešitve za manjkajoče besede »obdamo« z znakom your-online-assessment-software/ (Dostopno 11. 9. 2021) <<>> in navedemo manjkajoči del z besedo »select«, pravilno [5] Zgonc Možina (2018). Analiza in vrednotenje spletnih orodij za rešitev pa zapišemo na prvem mestu (npr. <>). lj.si/5541/1/magistrska_naloga_koncna_verzija.pdf (Dostopno 11. 9. 2021) [6] Strokovne podlage za didaktično uporabo IKT v izobraževalnem Oblikovanje izgleda takole: procesu za področje jezikov 1. Ich <> gern Bücher und meine https://www.uni- Mutter <> gern die Zeitung. lj.si/mma/strokovne_podlage_za_didakticno_uporabo_ikt_v_izobrazev anem_procesu_za_podrocje_umetnost/2018103012423532/ (Dostopno 2. <> ihr gern? Ja, wir 11. 9. 2021) <> sehr gern. 490 Vpliv uporabe digitalnih sredstev na motivacijo in uspešnost učenja The impact of the use of digital resources on motivation and learning success Žan Kapun Tomi Perša Klemen Sajko Univerza v Mariboru Univerza v Mariboru Univerza v Mariboru Maribor, Slovenija Maribor, Slovenija Maribor, Slovenija zan.kapun@student.um.si tomi.persa@student.um.si klemen.sajko@student.um.si POVZETEK concluded that students, who in their education often or regularly use digital resources, are much more successful and motivated V raziskovalni nalogi smo raziskali vpliv digitalnih sredstev na for work in digital learning environment. This finding presents motivacijo in uspešnost v digitalnem okolju izobraževanja. Želeli the educators and educational institutions that the following smo izvedeti, kakšno je stališče učencev, ki so se morali methods of education are similarly or more efficient than the prilagoditi na takšno učno okolje, še posebej v času traditional methods, and it also introduces the students with the epidemioloških ukrepov in opravljanje učnega procesa na importance of using digital resources for learning. daljavo preko digitalnih sredstev. Raziskavo smo izvedli s pomočjo spletnega anketnega vprašalnika z namenom zbiranja KEYWORDS podatkov iz različnih starostnih skupin, ki hkrati vedo tudi najbolje ovrednotiti raziskano stališče, kot so učenci 8. in 9. Digital learning, e-learning, internal motivatiom, learning razreda devetletne osnovne šole, dijaki poklicnih in gimnazijskih success srednješolskih programov ter univerzitetne in višješolske študente. S pomočjo rezultatov smo prišli do zaključka, da so 1 UVOD učenci, ki so pri svojem izobraževanju pogosto ali redno uporabljali digitalna sredstva bistveno bolj uspešni in motivirani S čedalje večjim premikom izobraževanja na spletne platforme za delo v digitalnem učnem okolju. Ta ugotovitev se pri mnogih pojavljajo dvomi o učinkovitosti tovrstnega načina izobraževalcem in izobraževalnim ustanovam predstavi, da so izobraževanja. V trenutnih razmerah in epidemiji virusa COVID- tovrstni načini izobraževanja lahko enako ali bolj učinkoviti od 19 pa so takšni načini ključni za uspešno delovanje šolstva. V tradicionalnih metod, učence pa seznani s pomembnostjo sledeči nalogi raziskujemo, s kakšnim stališčem se srečujejo uporabe digitalnih sredstev pri učenju. trenutni osnovnošolci, dijaki in študenti. Tako želimo dobiti vpogled na uspešnost tovrstnega izobraževanja. KLJUČNE BESEDE V obstoječih raziskavah je bilo že kar nekaj poskusov, da bi Digitalno učenje, e-učenje, notranja motivacija, uspešnost učenja našli razlike med učnimi okolji in uspešnosti njihovega delovanja. Pri tem je bil uspešen Stefan Kulakow (2020), ki je v svoji ABSTRACT raziskavi pokazal, da je okolje, ki se osredotoča na lastno učno In our research assignment we have studied the effect of digital sposobnost, pozitivno vplivalo na višjo akademsko sposobnost in resources on motivation and success in digital learning višjo motivacijo za uspeh, medtem ko druga raziskava enviroment. We wanted to learn the standpoint of students, who (Hietajärvi in drugi, 2020) ni odkrila močne povezave med had to adapt to such learning environment, especially in time of digitalnimi učnimi vsebinami in motivacijo učencev. V nekaterih epidemy and to carry out the learning process on distance with primerih kaže, da lahko digitalno izobraževanje celo škodi the help of digital resources. We performed the research with the učenčevemu uspehu. Tretja raziskava (Cidral in drugi, 2018) use of an online questionnaire with the intention of collecting prav tako meri uspešnost učencev v digitalnem okolju, vendar se data from participants of different age groups, who also know to osredotoči bolj na dejavnike, ki so najpomembnejši pri properly evaluate the researched grounds, such as students of 8th elektronskem izobraževanju. and 9th grade of nine-year primary school, students of vocational Ker te raziskave niso prišle do enotnih ugotovitev glede and secondary school and students at various university and post- vpliva digitalnega izobraževanja na uspešnost in motivacijo secondary programs. With the help of the results, we have učencev, se nam zdi smiselno opraviti podobno raziskavo, ki je hkrati v drugem geografskem okolju. Prav tako ni bilo razvidno, kako zadovoljni so posamezniki z digitalnimi vsebinami, če so Permission to make digital or hard copies of part or all of this work for personal or opravili obvezni in popoln prehod iz tradicionalnih načinov classroom use is granted without fee provided that copies are not made or distributed izobraževanja. Trenutno stanje širjenja virusa COVID-19 je for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must povzročilo edinstveno situacijo, kjer je veliko učencev prisiljeno be honored. For all other uses, contact the owner/author(s). k uporabi digitalnih sredstev za učenje, kar lahko vpliva na Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). kakovost učne vsebine in s tem tudi motivacije učencev do vključevanja v te vsebine in e-učenje. Naša študija bo te 491 probleme rešila z vprašalnikom, ki bo preverjal zadovoljstvo in AND “success” OR “learning success” OR “digital success” uspešnost učencev pred in med obveznim izobraževanjem preko OR “student success”. uporabe digitalnih orodij. Ker se izobraževanje digitalizira predvsem v zadnjem V današnji informacijski družbi je veliko dejavnikov, ki desetletju, smo za časovni obseg določili, da iščemo vire po letu vplivajo na nenehno spreminjanje načinov izobraževanja. Kot 2010. Zaradi hitreje spreminjajočih razmer se med drugim lažje študentje smo priča tem spremembam, saj skozi leta opažamo osredotočimo na vire, izdane po letu 2018. vedno večjo in bolj pogosto uporabo digitalnih sredstev, ne le pri poučevanju, temveč tudi pri učenju. Razširila se je uporaba 2.2 Teoretični okvir spletnih učilnic, kot sta Moodle in Sakai, spletnih virov in Področje oblikovanja in tehnologije poučevanja se razvijajo in videoposnetkov za pomoč pri učenju in poučevanju, od učencev pojavljaj se alternativni pristopi k učenju po kognitivnih in pa se je začelo pričakovati znanje pripravljanja predstavitev s konstruktivističnih teorijah, ki močno odstopajo od programi, kot je Microsoft Powerpoint. V zadnjem letu se je tradicionalnih praks, kot so vedenjski modeli. Novi poudarki, kot zaradi izredne situacije, ki jo je povzročila pandemija so elektronski sistemi za boljše delovanje, spletna navodila in koronavirusa (SARS-CoV-2), mnogo šolskih sistemov po svetu sistemi za upravljanje znanja, niso samo pretresli bazo znanja s odločilo za izobraževanje na daljavo s pomočjo tega področja, temveč tudi razširjajo obzorje na podjetja in videokonferenčnih programov, kot sta Microsoft Teams in Zoom. industrijo, vojsko, zdravstvo in izobraževanje po vsem svetu Nekateri učenci so se lažje prilagodili na nove tehnologije, (Nanjappa in Grant, 2002). Avtorica Wheeler (2012) je E-učenje, medtem ko so drugi ostali pri svojih tradicionalnih metodah ali elektronsko učenje, imenovala “tehnološko-izboljšano poučevanja. učenje”, kasneje tudi “digitalno učenje”. E-učenje je nabor V sledečem poglavju smo opisali našo strategijo iskanja tehnološko posredovanih metod, ki se lahko uporabljajo za podobnih virov in napisali teoretični okvir. V tretjem poglavju podporo učencem pri učenju, ki vključuje elemente ocenjevanja, pregledujemo sorodna dela. Za boljšo izpeljavo naše študije smo tutorstva in poučevanja. Avtorji Cidral idr. menijo, da je namen v teh delih iskali podobnosti, hkrati pa njihove pomanjkljivosti, e-učenja širjenje informacij in znanja za izobraževanje in ki smo jih lahko odpravili v naši raziskavi. Četrto poglavje je usposabljanje. Razumevanje vpliva e-učenja na družbo in namenjeno metodologiji in je sestavljeno iz več tabel, ki njegovih koristi je pomembno za povezovanje sistemov prikazujejo seznam spremenljivk, naša raziskovalna vprašanja in digitalnega učenja z njegovimi gonilnimi silami. Avtorji hipoteze. V tem poglavju se nahaja tudi raziskovalni model. V Keengwe, Onchwari G. in Onchwari J. so v svoji študiji leta 2009 petem poglavju povzamemo rezultate raziskave in jih napisali, da bi bilo treba reformirati programe izobraževanja z analiziramo. Sledi še šesto poglavje, kjer so navedeni cilji uvedbo aktivnih učnih okolij, ki podpirajo in izboljšujejo globino raziskave, razloženi rezultati in primerjane vzporednice s in obseg učenja učencev. Natančneje, učitelji bi morali učencem sorodnimi študijami. V zaključku pa so izpostavljeni prispevki zagotoviti intelektualno močna okolja, osredotočena na učenca študije, omejitve in čemu služi študija. Navedenih pa je tudi in tehnološko bogata okolja, ne da bi pri tem ogrožali dobre nekaj priporočil za prihodnje sorodne študije. pedagoške prakse. E-učenje ljudem omogoča fleksibilen in njim prilagojen način učenja. Iz tega lahko mi pri naši raziskavi 2 Teoretični okvir in ozadje pričakujemo pozitiven vpliv e-učenja na motivacijo učenca (H3) in na njegov učni uspeh (H1). Pojavljajo se številne ključne 2.1 Opis strategije iskanja za konceptualni tehnologije za olajšavo načrtovanja in izvajanja sistemov e- pregled literature učenja, ki lahko imajo velik vpliv na učenje. (Cidral idr., 2018 ) Motivacija je interni proces, ki predstavlja enega izmed glavnih Uporabljena literatura v naši raziskovalni nalogi izhaja predvsem dejavnikov, ki vplivajo na uspešnost učenja (Levpušček in iz znanstvenih raziskovalnih del, strokovnih nalog, ter Zupančič, 2008). Avtorja Makewa in Ngussa (2015) se ne diplomskih in magistrskih nalog. Gradivo iščemo v bazi člankov strinjata, da je motivacija zgolj notranji, temveč tudi zunanji Science Direct, saj vsebuje navezujoče članke iz držav po celem proces. Dodajata tudi, da so učitelji najboljši vir motivacije pri svetu. Poskusili smo najti knjižno literaturo v sistemu COBISS, interakciji med poučevanjem in učenjem. Svinicki in Vogler vendar nam je epidemiološko stanje Covid-19 otežilo dostop do (2012) pravita da je motivacija proces interakcije med učencem iskanja želenega gradiva. Za ključne besede iskanja smo določili: in okoljem, ki ga zaznamujejo izbor, iniciacija, povečanje ali digitalna delitev, učna motivacija, digitalno učenje, digitalne vztrajnost ciljno usmerjenega vedenja. Obravnava se jo lahko kot učne strategije, izobraževanje, elektronsko učenje, uspešnost lastnost posameznika, situacijo ali dejavnost, s katero se učenja, e-učenje. posameznik ukvarja. Avtor Karim (2012), povzeto po Lin, Chen V angleškem jeziku se te glasijo: in Liu (2017) pa meni, da je učna motivacija lastno prepričanje, digital divide, learning motivation, digital learning, digital ki vodi posameznikove učne cilje, spodbuja njegovo učno learning strategies, education, electronic studying, studying vedenje k nenehnemu trudu, krepi kognitivno zgodovino in success, e-learning. poveča uspešnost učenja. Podobno hipotezo smo si postavili tudi Te ključne besede smo razvrstili v skupine in po njih bomo mi, saj predvidevamo, da bo predvsem zunanja motivacija opravljali iskanje temeljnih virov: učenca imela pozitiven vpliv na uspešnost digitalnega učenja “digital divide” OR “digital learning” OR “education” OR (H2), zanima pa nas tudi, kako se bo primerjala z notranjo. Block “e-learning” OR “electronic learning” idr. (2013) so omenili, da lahko začetne in ozke faze učenja vodi AND “motivation” OR “learning motivation” OR “inner zunanja motivacija. Ko postane učenje avtonomno, so zunanje motivation” OR “outer motivation” OR “studying motivation” spodbude nepotrebne, vendar se spremenijo v avtonomno učenje. OR “digital motivation” OR “student motivation” Tako bi se notranja in zunanja motivacija dopolnjevali. Po drugi 492 strani pa učenje zahteva tudi nekaj gonilne sile in zunanje posameznikove učne preference, željo po digitalnem učenju ter motivacije, saj se posamezniki pogosto učijo zaradi pričakovanja odklanjanje šolskega dela in spanca zaradi uporabe Interneta. staršev, drugih ciljev in za pridobitev določenih spodbud. Učenci imajo na Finskem dober dostop do digitalnih učnih Avtorja Seifert in Sutton (2012) pravita, da so razlike v vsebin, vendar se izobraževalni sistem še vedno trudi vzpostaviti motivaciji pomemben vir raznolikosti v razredih. Primerjamo jo učinkovit in specifičen tehnološko usmerjen učni program. V lahko v predhodnem znanju, sposobnostih ali razvojni raziskavi je sodelovalo 1,482 učencev med 15. in 16. letom pripravljenosti. Pri šolskem učenju pa motivacija učencev dobiva starosti iz 26 različnih šol, za pridobitev podatkov pa so uporabili še poseben pomen, saj zgolj prisotnost učencev pri pouku seveda individualni anketni vprašalnik (ang. Self-reported questionnare). ni zagotovilo, da se učenci res želijo učiti. To je samo znak, da S sledečimi rezultati so nato po analizi latentnega profila (analiza, živijo v družbi, ki zahteva, da mladi obiskujejo šolo. Ker je s katero poskušamo identificirati skupine posameznikov glede na sodobno izobraževanje obvezno, učitelji motivacije učencev ne zaporedje ponavljajočih identifikatorjev, ki jih pridobimo na morejo jemati kot samoumevne in so odgovorni za spodbujanje podlagi njihovih odgovorov) poskušali odkriti profile glede na učencev. zastavljene učne cilje učencev, ter s tem določiti razlike med Uspešnost učenja je rezultat posameznikove vztrajnosti, profili s spoštovanjem do digitalnega vključevanja. motivacije, pridobitev, osebnostnega razvoja in dosežkov (Cuseo, Pridobljene in analizirane odgovore so ločili na štiri skupine 2007). Podobno opisuje definicija, da je uspeh odvisen od z različnimi usmerjenimi profili: individualnih in kontekstnih faktorjev, ki jih posameznik pod • Mojstrsko usmerjeni profil: osredotočanje na učenje in pravim vodstvom pridobi in s tem dela na osebni izboljšavi in povprečno šolsko delo, veselju. Večina definicij obravnava uspeh učenja kot celoto • uspešnostno osredotočen profil: zagnanost k večjemu spletno-izobraževalne platforme ali učnega sistema posamezne uspehu in boljših rezultatov od ostalih vrstnikov, ustanove in je tako težko določiti točen pomen uspeha, ki ga te • povprečno osredotočen profil: posameznik nima zagotavljajo (Hyvärinen in Uusiautti, 2021). Uspešnost učenja je določenih večjih ciljev, običajno merjena kot nek končni rezultat, ki ga posameznik • odklonljiv profil: posameznik se izmika učnemu delu. opravi na testu oziroma preverjanju znanja oziroma drugih Rezultati študije so pokazali, da učenci z mojstrsko ocenjevalno vrednotenih dejavnosti. Ker za raziskavo nimamo usmerjenim in uspešnostno osredotočenim profilom želijo več dovolj časa, da bi lahko primerjali znanje učencev glede na ocene digitalno usmerjenih vsebin za učenje, medtem ko učenci s in ker nam razmere v državi tega ne dopuščajo, bomo se morali povprečno osredotočenim profilom ne želijo odstopati od v naši raziskavi zanašati na samooceno anketiranih učencev. tradicionalnih metod izobraževanja. Tako se digitalno Slednji je lahko močno odvisen od družbenega okolja, v katerem osredotočeno izobraževanje ne more upoštevati kot motivacija za se posameznik nahaja in ali ima zagotovljen dostop in finance do učenje, in je treba pri implementaciji več digitalnih orodij v kredibilnih virov učenja. izobraževalni sistem upoštevati tudi motivacijski profil posameznikov. Odklanjanje šolskega dela zaradi uporabe Interneta je bilo negativno povezano z učnim uspehom, vendar 3 Pregled sorodnih del so analizirani rezultati pokazali, da visoko motivirani učenci z Cidral in drugi so v brazilski empirični raziskavi želeli najti visokim učnim uspehom tudi odklanjajo učna dela zaradi dejavnike, ki vplivajo na zadovoljstvo, uporabo in individualni prepogoste uporabe Interneta. vpliv e-učenja med uporabniki. Uporabili so kvantitativno Raziskava je dobro ovrednotila svoje področje raziskovanja metodo spletnega anketnega vprašalnika, na katerega je in na podlagi rezultatov opredelila raziskovalna vprašanja. odgovorilo 301 anketirancev. Ugotovili so, da sta uporaba in Ciljna skupina je bila jasno definirana in dosegli so dober vzorec zadovoljstvo uporabnikov pri e-učenju medsebojno odvisna in za analizo problema. Reševanje vprašalnika je bilo individualno imata pozitiven vpliv na uspešnost posameznika. Zraven in anonimno, tako da so anketiranci odgovarjali čim bolj iskreno zadovoljstva sta pri e-učenju pomembna dejavnika tudi kakovost na vprašanja, ki so tudi vezana na odklanjanje dela. Hkrati pa je sodelovanja in kakovost informacij. Zato avtorji predlagajo, da pokazalo, da rezultati lahko odstopajo od posameznikove osebne bi platforme digitalnega učenja morale omogočati artikulacijo motivacije in ne moremo točno določenih skupin asociirati s komunikacije in kolaboracije med študenti in s tem vplivati na podobnimi posamezniki. študentovo uporabo in zadovoljstvo. Prav tako bi spletne vsebine Stefan Kulakow je v raziskavi preverjal teorijo, ki pravi, da morale biti dostopne, uporabne, razumljive, zanimive in akademska sposobnost deluje kot povezava med izobrazbo in zanesljive. Raziskava nam pove, da je posameznikova uspešnost motivacijo za doseganje ciljev, ter kako različna izobraževalna posledica zaznane kakovosti sistema učencev. Če je sistem okolja vplivajo na to povezavo. Na vzorcu učencev iz Nemčije enostaven in ima dobro strukturirano vsebino in funkcionalnosti, primerja učno okolje, ki ga vodi učitelj in okolje, ki se osredotoča bo to povečalo zadovoljstvo in uporabo sistemov za e-učenje. na lastno učno sposobnost učenca. Namen slednjega okolja je Prednost študije je, da pri preverjanju vpliva zajema veliko ustvariti čim večjo raznolikost učenja, ki temelji na predhodnem različnih dejavnikov, vendar pa se osredotoča le na notranjost e- znanju učencev. Raziskava je pokazala, da je bistveno višjo učenja in ga ne primerja s tradicionalnim učenjem. Zanimivo pa akademsko sposobnost pokazalo okolje osredotočeno na učence. bi bilo videti podobno raziskavo tudi v državah z drugačno Pokazala je tudi, da v tem okolju zaznana podpora učenčevim kulturo ali razširjenostjo uporabe tehnologije pri izobraževanju. sposobnostim deluje kot posrednik med akademsko samopodobo Raziskava finskih študentov (Hietajärvi in drugi, 2020) je in motivacijo za uspehe. Akademska samopodoba je želela pokazati, kako vključevanje finskih učencev v digitalne večdimenzionalni konstrukt, ki se nanaša na individualno učne vsebine vpliva na njihove zastavljene cilje izobraževanja. vrednotenje osebnih kognitivnih sposobnosti v kontekstu Glede na digitalne učne vsebine so se opredelili na akademskih dosežkov. Dokazuje, da je taki način učenja najbolj 493 primeren za učence z nizko akademsko samopodobo saj zmanjša V407: Samostojnost povezavo med le to in podpiranjem učenčevih sposobnosti za V408: Radovednost doseganje ciljev. Največja pomanjkljivost raziskave je, da temelji na samo-poročanih podatkih sodelujočih, prav tako pa Zunanja Ng & Ng, 2015; V501: Starši starostne skupine niso bile statistično enako porazdeljene. motivacija Lin, McKeachie V502: Zahtevnost Zanimivo bi bilo mogoče vključiti in preveriti rezultate hibridne in Kim, 2002 V503: Cilj skupine, v nadaljnjih študijah pa bi lahko raziskali, če je mogoče V504: Pomembnost takšno učno okolje vzpostaviti preko spleta. Samoocena V601: Ocena uspešnosti V602: Pozornost 4 Metodologija digitalnega V603: Učinkovitost učenja V604: Vključenost Zanimalo nas je: 1. Ali obstaja statistično značilna povezava med uporabo elektronskih sredstev pri učenju in motivacijo učencev? 2. Ali zunanja in notranja motivacija učenca vplivata na 4.2 Vzorčenje in udeleženci raziskave samooceno uspešnosti digitalnega učenja? Naša raziskava se navezuje predvsem na motivacijo in 3. Ali uporaba elektronskih sredstev vpliva na samooceno uspešnosti digitalnega učenja? zadovoljstvo z uporabo spletnih učnih vsebin, zato smo izbrali tudi ustrezne ciljne skupine. Za populacijo smo določili učence 8. in 9. razreda osnovnih šol, dijake srednjih šol in študente Tabela 4.1: Seznam merljivih spremenljivk višješolskih in univerzitetnih programov, torej so naše enote vzorčenja učenci, dijaki in študentje. Ime Vrednosti spremenljivke Naš merski instrument je v obliki spletnega vprašalnika, nismo spremenljivke pa morali pridobiti seznama vseh osnovnošolcev, srednješolcev in študentov. Poslužili smo se metod priložnostnega vzorčenja in Spol 0 Moški modela snežne krogle, kjer smo anketo delili med vrstniki in jih 1 Ženski naprosili, naj jo delijo še med svojim poznanstvom, ki spada v Starost 0 13-15 okvir naše populacije raziskave. 1 16-19 4.3 Postopek raziskave 2 20-26 3 27+ Pridobitev podatkov z uporabo ankete smo izvajali na spletu, učence, dijake in študentke pa smo k sodelovanju povabili preko družbenih omrežij in poznanstev v panogi javnega izobraževanja. Pred izvajanjem ankete so sodelujoči morali potrditi, da vprašalnik izpolnjujejo prostovoljno, kar zadostuje Tabela 4.2: Seznam latentnih spremenljivk etičnim zahtevam za izvedbo spletne ankete. Raziskavo smo izvajali med 4. 1. 2021 in 18. 1. 2021. Raziskava je spoštovala etične kodekse. Po zahtevah kodeksa Ime Vir Indikatorji ameriškega združenja psihologov APA (APA, 2010) smo spremenljivke upoštevali človekove pravice, poskrbeli za zasebnost in varno Uporaba Caglar & V301: Upravljanje časa hranjenje podatkov. Podali smo tudi informirano soglasje, s elektronskih Turgut, 2014 V302: Učinkovitost katerim so se udeleženci morali strinjati kot pogoj za reševanje sredstev pri poučevanja e-učenja raziskave. Za zasebnost smo poskrbeli z anonimnim pristopom učenju V303: Potreba po reševanja, zbirali pa smo le najnujnejša demografska podatka naprednih tehničnih (spol in starost), brez katerih analiziranje podatkov ne bi bilo sposobnostih mogoče. Sodelujoči so bili obveščeni o obdelavi podatkov v V304: Prilagodljivost raziskovalne namene, omogočili pa smo jim, da lahko kadarkoli urnika izstopijo iz raziskave. Pred izvedbo raziskave smo sodelujoče V305: Zmanjšanje seznanili z namenom raziskave, na njihovo željo pa jim bodo stroškov posredovani tudi drugi podatki raziskave, po opravljenem V306: Izbira učenja reševanju vprašalnika. Po končani izvedbi raziskave bodo lahko V307: Izbira pridobili tudi povratne informacije o rezultatih raziskave. preverjanja znanja Pripravljen merski instrument smo najprej posredovali mentorici v pregled. Ta nam je predlagala popravke na podlagi Notranja Lin, Chen & Liu, V401: Kreativnost motivacija obrazložitve etičnosti naloge, obrazložitve pojmov in 2017 V402: Vztrajnost pričakovanih informacij od udeležencev ter slovničnih napak. Schreiber, 2016 V403: Cilj V404: Uporabnost Spletni anketni vprašalnik smo nato v predtest posredovali V405: Zadovoljstvo manjši izbrani skupini posameznikov, ki so rešili naš vprašalnik. V406: Izziv Povratnih informacij niso podali, zato vprašalnika nismo nadaljnje prilagodili. 494 4.4 Merski instrument Tabela 5.2: Rezultati testa neodvisnih vzorcev Za metodo zbiranja podatkov smo izbrali anonimni spletni vprašalnik. Razlog za ta izbor je preprosta deljivost, reševanje in Independent Samples Test obdelava pridobljenih podatkov. Hkrati je to tudi najvarnejši pristop zbiranja podatkov glede na trenutno epidemiološko stanje Samoocena uspešnosti e-učenja v Sloveniji. V uvodu vprašalnika smo sodelujoče seznanili s temo in Equal Equal variances variances not namenom zbiranja podatkov v okviru raziskave, ter jih seznanili assumed assumed s pogoji sodelovanja. Merski instrument vsebuje štiri sklope F 2.143 vprašanj z uporabo intervalnih pet stopenjskih lestvic, pri katerih Levene's Test udeleženci ocenjujejo svoje strinjanje s podanimi trditvami in for Equality of dva sklopa vprašanj zaprtega tipa z izborom odgovora, ki Variances Sig. .147 pridobivajo splošne demografske informacije. Pred začetkom reševanja intervalnih lestvic smo udeležencem podali krajši t -5.572 -5.609 teoretični okvir, ki se navezuje na pričakovane trditve in odgovore. df 94 93.508 Sig. (2-tailed) .000 .000 5 REZULTATI t-test for Analiza zbranih podatkov je pokazala, da so učenci, ki Equality of Mean Difference -.84761 -.84761 uporabljajo več elektronskih sredstev pri učenju bolj uspešni pri Means digitalnem učenju. Std. Error Difference .15212 .15113 95% Lower -114.965 -114.769 Tabela 5.1: Uspešnost e-učenja glede na uporabo Confidence elektronskih sredstev pri učenju Interval of the Upper -.54557 -.54753 Difference S tem lahko odgovorimo na RV3: Ali uporaba elektronskih Group Statistics sredstev vpliva na samooceno uspešnosti digitalnega učenja? Da, uporaba elektronskih sredstev vpliva na samooceno uspešnosti Samoocena uspešnosti digitalnega učenja. e-učenja Prav tako lahko potrdimo H1: Uporaba elektronskih sredstev pri učenju pozitivno vpliva na samooceno uspešnosti digitalnega učenja. To pomeni, da večja kot je uporaba elektronskih sredstev Uporaba pri učenju posameznega učenca, večja bo tudi njegova elektronskih samoocena uspešnosti pri digitalnem učenju sredstev pri učenju Manjša Večja (skupina) 6 ZAKLJUČEK N 46 50 S to raziskavo smo želeli dobiti vpogled v mišljenje osnovnošolcev, dijakov in študentov glede digitalnega načina Mean 23.424 31.900 izobraževanja. Predvsem nas je zanimalo kako uporaba elektronskih sredstev pri učenju vpliva na motivacijo in Std. Deviation .68182 .79789 uspešnost učencev pri takšnem izobraževanju. Ugotovili smo, da je v praktičnem primeru, ko imajo učenci na voljo le digitalno izobraževanje, pomembno da je tudi njihova Std. Error Mean .10053 .11284 uporaba elektronskih sredstev čim večja, saj bo tako njihovo izobraževanje tudi bolj uspešno. Pri tem je pomembno kako e- V tabeli 5.1 lahko razberemo, da je v skupini z manjšo uporabo učenje vpliva na njihovo upravljanje s časom, učinkovitost, elektronskih sredstev pri učenju imela pri samooceni uspešnosti prilagodljivost njihovih urnikov in kateri način učenja, digitalnega učenja povprečno vrednost 2,34, skupina z večjo spremljanja pouka in izvajanja testov jim je ljubši. Tisti, ki so uporabo elektronskih sredstev pri učenju pa 3,19. bolj navajeni učenja z digitalnimi sredstvi bodo v digitalnem Pri testu neodvisnih vzorcev smo izvedeli, da je dvosmerna okolju imeli veliko prednost. (ang. 2-tailed) signifikanca enaka 0,000, kar pomeni, da obstaja Ugotovitve študije služijo kot odgovor na vprašanje “kako statistično značilna razlika med učenci z nižjo in višjo uporabo uporaba elektronskih sredstev vpliva na uspešnost digitalnega elektronskih sredstev pri učenju pri samooceni uspešnosti učenja?” in je potrdilo, da tovrstne metode prinašajo bistveno digitalnega učenja. izboljšavo rezultatov v določenem okolju. Podatki so uporabni za izobraževalne ustanove, ki morda dvomijo v efektivnost elektronskih sredstev. Dvomi so seveda še lahko upravičeni, 495 vendar se bo lahko z večanjem razširjenosti elektronskih sredstev [6] Lin, McKeachie in Kim (2002). College student intrinsic and/or extrinsic in njihovo uporabo, izobraževanje nagibalo vedno bolj k motivation and learning, Learning and Individual Differences13 (2003) 251–258, doi:10.1016/S1041-6080(02)00092-4. digitalnemu, kjer bo uporaba elektronskih sredstev imela velik [7] Wheeler S. (2012) e-Learning and Digital Learning. In: Seel N.M. (eds) vpliv. Te ugotovitve služijo tudi učencem, da se bolj zavedajo Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_431 kako uporaba digitalnih učnih sredstev vpliva na njihov uspeh. [8] Cidral W.A., Oliveira T., Di Felice M. & Aparicio M., E-learning success Glavna omejitev naše raziskave je, da smo izvedli le anketni determinants: Brazilian empirical study, Computers & Education (2018), vprašalnik s priložnostnim vzorčenjem, kar pomeni da naš doi: 10.1016/j.compedu.2017.12.001. [9] Keengwe, J., Onchwari, G., & Onchwari, J. (2009). Technology and vzorec ni nujno reprezentativen na celotno populacijo učencev. Student Learning: Toward a Learner-Centered Teaching Model, AACE Rezultati anketnega vprašalnika pa so lahko subjektivni in Journal, 17 (1), 11-22. [10] Nanjappa, A., & Grant, M. M. (2003). Constructing on constructivism: nenatančni, saj udeležencem nismo mogli merit uspešnosti (npr. The role of technology. Electronic Journal for the integration of ocen). Prav tako je naš vzorec relativno majhen (N=96). Technology in Education, 2(1), 38-56 Še ena omejitev je, da v naši raziskavi nimamo kontrolne [11] Svinicki M.D., Vogler J.S. (2012) Motivation and Learning: Modern Theories. In: Seel N.M. (eds) Encyclopedia of the Sciences of Learning. skupine, ki bi bila izpostavljena tradicionalnemu izobraževanju, Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_392 saj tako ne moremo videti vpliva uporabe elektronskih sredstev [12] Levpušček, M. P., & Zupančič, M. (2008). Math Achievement in Early. Journal of Early Adolescence, 1–30. na uspešnost tradicionalnega učenja. To bi bilo dobro raziskati v http://doi.org/10.1177/0272431608324189 prihodnosti. [13] Makewa, L. N. & Ngussa, B. M. (2015). Curriculum Implementation and Menimo, da bi v prihodnjih raziskavah bilo zanimivo Teacher Motivation: A Theoretical Framework. DOI: 10.4018/978-1- 4666-8162-0.ch013 uporabit drug merski instrument, na primer laboratorijski [14] Block, L., Jesness, R.,& Schools, M. P. (2013). One-to-One Learning with eksperiment, v katerem bi lahko nadzorovano primerjali vpliv iPads: Planning & Evaluation of Teacher Professional Development. College of Education, Leadership & Counseling. University of ST. uporabe elektronskih sredstev z uspešnostjo. Prav tako bi Thomas Minnesota. Pridobljeno s: prihodnje raziskave lahko iskale korelacije med karakteristikami https://scholarcommons.sc.edu/cgi/viewcontent.cgi?article učencev (npr. motivacija) in uspešnostjo pri digitalnem učenju. =5336&context=etd [15] Seifert, K. & Sutton, R. Educational Psychology, Chapter 16. Chapter In kot smo že omenili, bi bilo dobro vključiti objektivne Published by the Saylor Foundation. Dostopno na: spremenljivke, ne le mnenj učencev. https://www.saylor.org/site/wp-content/uploads/2012/06/Educational- Psychology.pdf. [16] Cuseo, J. (2007). Student Success: Definition, Outcomes, Principles, and Practices. The Big Picture. Esource for College Transitions. The National 7 ZAHVALA Resource fort he First-Year Experience & Students in Transition, University of South California. Zahvaljujemo se mentorici dr. Ines Kožuh za izčrpna navodila, [17] Hyvärinen S. in Uusiautti, S. (2021). Defining the new concept of smernice in popravke pri izdelavi naloge. Zahvaljujemo se tudi sustainable success – A state-of-the-art analysis on the phenomenon. New Ideas in Psychology 60. Faculty of Education, University of Lapland, vsem ostalim sodelujočim pri raziskavi. Finland. [18] Hietajärvi, L., Mädamürk, K., Salmela-Aro, K. in Tuominen, H. (2020) LITERATURA IN VIRI Adolescent Students’ Digital Engagement and Achievement Goal Orientation Profiles. Computers & Education, [1] Lin, M. H., Chen, H. G., & Liu, K. S. (2017). A Study of the Effects of https://doi.org/10.1016/j.compedu.2020.104058. Digital Learning on Learning Motivation and Learning Outcome. Eurasia [19] Kulakow S. (2020), Academic self-concept and achievement motivation Journal of Mathematics, Science and Technology Education, 13(7), 3553- among adolescent students in different learning environments: Does 3564. https://doi.org/10.12973/eurasia.2017.00744a competence-support matter?, Learning and Motivation, Volume 70, [2] Caglar & Turgut (2014). Factors Effecting E-Learning Preference: An 101632, ISSN 0023-9690, https://doi.org/10.1016/j.lmot.2020.101632 . Analysis on Turkish University Students from Government and Private [20] Languages (POPL '79). ACM Press, New York, NY, 226-236. Institutions, Volume 4 No 1, DOI10.5195/emaj.2014.59. DOI:https://doi.org/10.1145/567752.567774 [3] Nedeljko, M. (2016). Vpliv učenčeve priprave na učni uspeh pri [21] Ian Editor (Ed.). 2007. The title of book one (1st. ed.). The name of the ocenjevanju, Filozofska Fakulteta, Univerza v Mariboru. series one, Vol. 9. University of Chicago Press, Chicago. [4] Schreiber, J. B. (2016). Motivation 101, Springer Publishing Company, DOI:https://doi.org/10.1007/3-540-09237-4. LLC. [22] David Kosiur. 2001. Understanding Policy-Based Networking (2nd. ed.). [5] Ng & Ng (2015). A review of Intrinsic and Extrinsic Motivations of ESL Wiley, New York, NY Learners, International Conference on Culture, Languages and Literature 2015. 496 Primeri dobre prakse poučevanja tujega jezika na daljavo Distance teaching second language – examples of good practices Blanka Karanjac OŠ Stična Ivančna Gorica, Slovenija blanka.karanjac@os-sticna.si POVZETEK teacher burnout. Another challenge is to motivate students to be active participants. Poučevanje tujega jezika na daljavo je svojevrsten izziv, saj je potrebno uporabiti učinkovite metode za poučevanje vseh štirih Didactics of teaching and monitoring reading and writing skills jezikovnih spretnosti – govorno in pisno sporočanje, bralno in is easily adaptable to distance teaching. A more innovative slušno razumevanje. Potrebno je najti nove učinkovite načine, ki approach is needed to prepare e-materials. These must enable so enako učinkoviti kot delo v dvojicah in skupinah, students to use them easily without help. In the reminder of the konverzacijo, dober način spremljanja vseh učencev, pri katerem paper there are some guidelines discussed that have proven učitelj ne pregori, in motivirati učence, da aktivno sodelujejo pri efficient. pouku. Efficient ways of teaching and monitoring listening and speaking Didaktiko poučevanja in spremljanje napredka pri bralnem in skills are difficult to decide on. The article bellow analyses some pisnem sporočanju je relativno enostavno prilagoditi na daljavo. didactics and applications that have been successfully used. Več inovacij je potrebnih za pripravo e-gradiv – pripravljena Traditionally, lesson plans are often made so that a certain morajo biti tako, da lahko ciljna skupina z njimi dela samostojno. learning topic is covered during several lessons. Experience has V članku so opisane glavne smernice za pripravo e-gradiv, ki so shown that every distance lesson must be planned so that it forms se izkazale za učinkovite. a complete individual lesson. It must include presenting a new Zahtevno je vzpostaviti učinkovite načine za poučevanje in topic, practice, evaluation, and feedback. preverjanje na področju slušnega razumevanja in govornega Therefore, the article shows that students remained motivated for sporočanja. V prispevku predstavljam didaktiko in orodja, ki so schoolwork and did not need parents’ help with school materials. se izkazala za uspešna. Also, despite good teaching I have managed to avoid burnout. Pri klasičnem pouku v razredu so pogosto ure pouka načrtovane This was achieved by certain principles which are the topic of the tako, da so spoznavanje z novo snovjo, utrjevanje, preverjanje in article bellow. dajanje povratne informacije razdrobljeni na več učnih ur. Učinkovite ure pouka na daljavo so zasnovane tako, da je vsaka KEYWORDS ura pouka samostojna enota, pri kateri se učenci z učnim ciljem Distance teaching, e-materials, listening comprehension, oral spoznajo, ga usvojijo in ga učitelj preveri oz. ovrednoti znotraj communication, burnout iste učne ure. Predstavljene metode dela, organizacija in uporaba aplikacij je 1 UVOD na daljavo pripomogla, da so učenci ohranili motivacijo in pridobili kvalitetno znanje, ne da bi pri samostojnem delu V spomladanskem prehodu šolanja na daljavo smo se srečevali z potrebovali pomoč staršev. Predstavljen način dela je zagotovil drugačnimi izzivi kot v drugem valu. Izzivi prvega obdobja tudi, da sem lahko ločila služben čas od zasebnega, ne da bi trpela šolanja na daljavo so bili predvsem tehnične narave – kvaliteta opravljenega dela. organizacija pouka, iskanje ustreznih orodij, izbira računalniške opreme, spodbujanje k računalniški pismenosti, obvladovanje KLJUČNE BESEDE orodja za komunikacijo in podobno. V zadostni meri smo jih Poučevanje na daljavo, e-gradiva, slušno razumevanje, govorno premostili, da smo v jesenskem valu začeli spretneje. sporočanje, izgorelost Večji izziv je jeseni predstavljala vsebina – didaktika poučevanja na daljavo, priprava e-gradiv, struktura učne ure, cilji in vsebina ABSTRACT učne ure, načini spremljanja učencev. Po daljšem obdobju smo Teaching a foreign language is a unique challenge because it se borili tudi z izgorelostjo in padanjem motivacije tako učiteljev, demands teaching all four language skills – speaking, reading, učencev kot tudi staršev. V nadaljevanju opisujem primere listening, and writing. Since pair work, group work or dobrih praks in orodij, s katerimi sem se uspešno spopadla z conversation are not easy to translate to distance teaching it is zgoraj naštetimi izzivi – padec motivacije učencev, kvalitetno necessary to find new efficient ways to teach these skills. It is poučevanje vseh štirih spretnosti tujega jezika na daljavo, also important to find ways of monitoring every student to avoid ohranitev meje med delovnim in prostim časom, samostojnost 497 učencev in izključitev potrebe sodelovanja staršev pri šolskem 2.3. Bonton med poukom na daljavo delu njihovih otrok. Pouka preko videokonference so se učenci seveda lahko udeleževali tudi navidezno, torej so se npr. vključili v konferenco 2 POUK NA DALJAVO in ji ne sledili oz. bili dejansko prisotni. Zato je veljalo, da morajo učenci imeti ves čas sestanka vklopljene kamere. Če je kdo ni 2.1. Dolžina učne ure imel, se je vklopil preko telefona ali pa so starši pisno potrdili težave s kamero, ki smo jih na šoli poskusili rešiti. Učence sem Psihologi, ki se ukvarjajo s tako imenovanim fenomenom »Zoom med poukom naključno vabila k sodelovanju, odziv sem utrujenosti« (orig. Zoom Fatigue), pojasnjujejo, da so naše pričakovala v roku petih sekund. Učence, ki se niso v razumnem kognitivne sposobnosti bolj obremenjene med videokonferenco roku odzvali, izklopili kamere ali kako drugače motili pouk, sem kot med komunikacijo v živo. [1] Zato je nesmiselno načrtovati za tisto uro odstranila iz videokonference. V spletno učilnico smo pouk, pri katerem bomo polno skoncentrirani 45 minut. Ura namreč priprave na učne ure obešali tudi za tiste ure pouka, ki so pouka na daljavo mora biti bodisi časovno krajša bodisi bile izvedene na daljavo prek videokonference, tako da jim dinamično razdeljena tako, da zahteva od udeležencev aktivno pravica do izobraževanja ni bila odvzeta. Učenci so zelo hitro sodelovanje in praktično delo. ugotovili, da je potrebnega manj časa in napora, če delaš z 2.2. Vsebinska struktura ure razredom kot pa sam, s pomočjo priprave v spletni učilnici. Učne ure na daljavo sem načrtovala v vsaj treh različnih delih. 3 PRIPRAVA GRADIV ZA SAMOSTOJNO Prvi del – frontalno podajanje snovi DELO Začetek ure je bil vedno načrtovan kot najkrajši, okvirno dolg deset minut. Vedno je vseboval tudi seznanitev učencev s 3.1. Preglednost spletne učilnice potekom, cilji in predvidenimi dejavnostmi tiste učne ure. V spletnih učilnicah se zelo hitro nabere veliko povezav in drugega gradiva. Če je gradiva preveč, učence demotivira. Če je Drugi del – demonstracija uporabe slabo organizirano, porabijo preveč časa za navigacijo in manj za Glavni del ure je bil namenjen usvajanju nove učne snovi. učno snov. Uporabo oz. način usvajanja nove snovi sem na vsaj treh Zato sem gradiva in spletno učilnico organizirala kar se da primerih demonstrirala sama ali pa v paru oz. skupini z pregledno. določenimi učenci. Če smo na primer jemali novo slovnično strukturo, sem s tremi različnimi učenci izpeljala kratek voden Organizacija spletne učilnice pogovor po modelu, katerega del je bila struktura. Cilj je bil, da Arnesove spletne učilnice so izredno učinkovito orodje, ki vsi v skupini vedo, kako je potrebno vaditi, da novo snov nadomestijo šolski prostor. Ker je lahko virov in povezav v njej usvojijo. zelo veliko, lahko navigiranje v tem prostoru postane zamudno Ko smo bili vsi prepričani, da vemo, kako učenje poteka, sem jih in begajoče. Prvi korak k motivaciji za delo je bila torej ploščična s pomočjo Microsoft Teams Breakout Rooms razdelila v pare ali organizacija spletne učilnice. Vsak razred je na svoji ploščici skupine, kjer so se učili po danem zgledu. Med učenjem sem se imel tudi drugačno sličico (Slika 1), kar jim je olajšalo hitro vključila v vsako ločeno skupino ali par, jih spremljala ali pa jim navigacijo. nudila dodatno pomoč. Zadnji del – formativno spremljanje in povratna informacija Zadnji del videokonference je bil najpomembnejši. Vedno je bil sestavljen tako, da so učenci na koncu ure v živo preizkusili in pokazali usvojeno znanje tiste učne ure. Odvisno od učnih ciljev Slika 1: Organizacija spletne učilnice po razredih tiste ure so rešili interaktivno preverjanje znanja. To je bil pogosto interaktiven test, ki je vseboval različne tipe vprašanj ali Organizacija snovi znotraj razreda (ene ploščice) nalog, ki so ustrezno preverjale cilje tiste učne ure. Pomembno Vsaka priprava na učno uro je bila oštevilčena in naslovljena je bilo, da so morali interaktivne vaje rešiti v živo, dokler so bili (Slika 2). še vključeni v videokonferenco, saj sem jih ob tem spremljala na Za lažjo navigacijo je bilo pomembno tudi, da hkrati ni bilo v kameri oz. sem sledila poteku reševanja testa posameznih spletni učilnici posameznega razreda obešenih več priprav kot učencev. Zahtevala sem, da test rešujejo toliko časa, da dosežejo štiri, kar pomeni, da ni bilo treba koleščkati na dno strani. vsaj 90 % možnih točk oz. dokler nove učne snovi ne usvojijo. Zaporedno številčenje se je izkazalo za mnogo preglednejši in S tem je bilo poskrbljeno, da so vsi sproti napredovali, da sem uporabnejši sistem kot datiranje za sledenje zaporedju imela pregled nad tistimi, ki so v danem trenutku potrebovali arhiviranih priprav. dodatno pomoč in predvsem, da niti oni niti jaz nismo redno imeli dodatne domače naloge. 498 Priprava je morala biti napisana tako, da jo je učenec lahko uporabil samostojno. Pri tem so se poleg številčenja izkazale koristne barvne kode, številke korakov, posnetki zaslona in videoposnetki delov razlag. Barvne kode in oštevilčeni koraki V navodilih za samostojno delo sem v pripravah uporabljala barvne kode. Premišljeno barvno kodiranje spodbuja organiziran tok misli. [2] Z živo zeleno barvo sem opozorila na del navodil, ki so zahtevala neko aktivnost učencev. Povezave do videoposnetkov so bile označene temnomodro, uvodni del, ki ni bil del učnih ciljev, svetlo zeleno, neobvezne aktivnosti rumeno, rešitve z vijolično (Slika 5). To je učencem pomagalo, da so se že ob bežnem skeniranju besedila hitro orientirali. Na isti sliki je tudi vidno, da so koraki za delo po pripravi Slika 2: Organizacija snovi znotraj enega razreda (ene ploščice) oštevilčeni. Tudi to je učencem prihranilo trud, sploh če se niso držali vrstnega reda dejavnosti. Na koncu tekočega tedna sem priprave pospravila v mapo z naslovom ARHIV priprav na pouk, kjer so učencem vedno na voljo. Arhivirane priprave v mapi ARHIV si sledijo po kronološkem redu in jim je zato lahko slediti (Slika 3). Slika 5: Uporaba barvnih kod Videoposnetki Kadar je bilo smiselno, sem namesto napisane razlage in navodil Slika 3: Organizacija mape ARHIV priprav ustvarila videoposnetek. Čeprav je lahko priprava kvalitetne video razlage časovno bistveno zahtevnejša od napisane Pomembno je bilo tudi ločiti obvezno snov rednega pouka od priprave, je to investicija v prihodnost. Kvaliteten videoposnetek dodatnih aktivnosti. Te sem z oznako jasno označila z napisom snovi, ki jo vsako leto obravnavamo, nam lahko pride prav tudi pod mapo arhiva priprav (Slika 4). v prihodnosti, kot npr. zaposlitev za nadomeščanje, dopolnilni pouk ipd. V spletno učilnico sem vgradila pisno pripravo, ki je vsebovala povezavo do tega posnetka. Samostojno vgrajevanje URL povezave ni bilo smiselno, ker se povezave ne da pospraviti v mapo ARHIV. Kratka povezava namesto obširne pisne razlage je že na pogled spodbudila učence, ker so videli, da bo snov količinsko Slika 4: Ločevalna oznaka z napisom obvladljiva. Tudi za učence je bilo lažje spremljati zvok, sliko in ustaviti ali pohitriti videoposnetek. Na ta način tudi staršem ni 3.2. Kvalitetna priprava na pouk bilo treba predelovati pisnih priprav, da bi otroku interpretirali navodila (Slika 6). Čeprav smo velik del pouka izvajali na daljavo prek videokonferenc, smo priprave za pouk obešali v spletno učilnico za vse ure pouka. Priprave, ki so bile predvidene za pouk na daljavo, so bile na voljo šele po izvedeni uri prek videokonference, po potrebi med njo. To je bilo pomembno, zato da so vsi učenci pouku sledili enako zbrano. 499 učencem najprijaznejša. Slika 7: Primer balasta v pripravi 4 IZGORELOST IN PREVENTIVNI UKREPI Pri delu na daljavo smo učitelji v nevarnosti, da izgorimo. [3] K Slika 6: Del priprave na pouk – navodila in razlaga v obliki občutku, da nimamo več nadzora nad svojimi obremenitvami, videoposnetka, del navodila napisan na roko prispeva precej posebnosti pouka na daljavo. Ena je nenaravna komunikacija, ki povzroča »Zoom utrujenost«. Druga so številna Moteč del pisnih priprav orodja, ki omogočajo nadzor nad vsako dejavnostjo vsakega Del ure pouka je vedno tudi običajna komunikacija, ki ni učenca. Če nas to zapelje, da pretirano sledimo njihovemu povezana z učnimi cilji. Pisna priprava za samostojno delo ne napredku in preveč ažurno ponujamo pomoč, lahko ta more biti nadomestek za pouk v razredu, zato je v pisni pripravi preobremenitev prispeva k izgorelosti, saj je učencev bistveno na pouk vse, kar niso kratka in jasna navodila ali razlaga, moteče. več kot učiteljev. Nenazadnje pa so tu še komunikacijska orodja, Sčasoma smo z učenci ugotovili, da pri pisnih pripravah za prek katerih smo dosegljivi staršem in učencem za celostno samostojno delo moti ves balast, s katerim smo želeli nadomestiti podporo tudi v prostem času. Preventivni ukrepi, ki so se obnesli, pomanjkanje vzdušja v razredu. Emotikoni, dekorativne sličice, so bili v glavnem dobra organizacija časa, uporaba aplikacij, ki spodbudni nagovori, humorne domislice in celo pozdravi so se reducirajo oz. skrajšajo odvečno delo, in pa spoznanje, da je izkazali za moteče. Skoraj vse naštete poskuse, da bi pristno potrebno del bremena tudi delegirati oz. vsaj deliti. [4] komunikacijo in vzdušje v razredu prenesla v pisno obliko, sem opustila. Da bi priprave vseeno ne bile popolnoma brezosebne, 4.1. Organizacija časa sem suhoparnost popestrila s kakšnim stavkom navodila, ki sem ga, namesto natipkala, napisala na roko in pa seveda namesto V času pouka na daljavo me je poleg didaktičnih procesov pisne razlage posnela video (Slika 6). obremenjevala tudi stalna komunikacija s starši, kolegi in učenci. Straši so mi pisali elektronsko pošto z nujnimi obvestili, Emotikoni prošnjami in raznoraznimi vprašanji vse dni in ure v tednu. Emotikoni so v elektronski komunikaciji nekaj običajnega, v Učenci so mi pisali prek Microsoft Teams sporočila v klepet ob pripravi pa motijo koncentracijo. Učenci razmišljajo, kakšno vseh mogočih urah in na vse dni v tednu. Sprva sem se odzivala povezavo v zvezi s snovjo oz. navodilom signalizirajo. Vesel na vse takoj, kasneje pa ugotovila, da se čutim dolžna izven emotikon bi lahko pomenil, da del razlage, poleg katerega je, ni delovnega časa odzivati le v dveh primerih, in sicer ko gre za obvezen, potrt emotikon pa, da je snov pretežka za povprečnega tehnično podporo, da lahko učenec sledi pouku, ali pa ko gre za učenca (Slika 7). hudo čustveno stisko. Po premisleku sem se odločila, da bom v tehnično in učno Dekorativne ilustracije podporo učencem in staršem vsak delovni dan ob isti Pouk v razredu je za vsakega udeleženca doživetje. Poleg samega popoldanski uri dosegljiva prek videokonference. Povezavo sem podajanja, sprejemanja in usvajanja snovi je čar pouka vgradila v spletno učilnico. Že v prvem tednu je bilo lažje za vse atmosfera, ki jo soustvarjamo skupaj z učenci. Včasih se kdo – vsi so vedeli, da lahko po nasvet ali pomoč pridejo ob 19. uri, spontano pošali ali pa nas nepričakovane asociacije zapeljejo zato me za tovrstno pomoč niso več obremenjevali po drugih stran od začrtane strukture ure. Pri pisnih pripravah na kanalih. samostojno delo smo s kolegicami sprva poskusile ta del vzdušja Težje pa je bilo omejiti komunikacijo z učenci, ki so se name nadomestiti s prijaznimi ilustracijami. Podobno kot emotikone so obračali v hudih čustvenih stiskah tudi sredi noči. Te učence sem slikovni del učenci razumeli kot ponazoritev razlage, kar je povabila na individualne pogovore, ko je kriza minila. Z vsakim oteževalo razumevanje. takim učencem sva se dogovorila, da bova ustanovila skupinico, v katero bosta poleg naju vključena še dva delavca šole, ki jima Spodbudni nagovori, domislice, pozdravi učenec zaupa. Tako nas ni skrbelo, da bo učenec v krizi ostal Razne dobronamerne prijaznosti v smislu »Pozdravljeni učenci, sam, pa še kot ekipa smo bili boljša pomoč od posameznika. upam, da ste lepo preživeli praznike ...« demotivirajo, ker zasedajo prostor na strani in tako je priprava že na pogled daljša 4.2. Povratna informacija učencem in zamudnejša. Učenca, ki se take priprave loti po npr. treh V razredu včasih že iz govorice telesa in interakcije v družbi videokonferencah in dveh pisnih pripravah na samostojno delo vemo, kako in koliko učenci delajo samostojno, na daljavo pa pri drugih predmetih, lahko zamori, ker že na pogled deluje, da nam ta vpogled manjka in nas skrbi. Zato sem v začetku bo snovi preveč. zahtevala, da so mi v elektronski obliki redno pošiljali fotografije Čeprav so jedrnata in konkretna, pregledno označena in barvno svojih izdelkov. Ker je bilo dnevno pregledovanje in pošiljanje zakodirana navodila morda na videz brezosebna, so vendarle povratnih informacij cca 100 izdelkov dnevno prezahtevno, sem poiskala boljše načine. 500 Obilica orodij in aplikacij, ki omogočajo vpogled v praktično Prva je ta, da učenca prisili k učenju. Kot omenjeno, če je naloga vsako dejavnost vsakega posameznega učenca, nas lahko hitro zastavljena tako, da npr. preverja znanje novega besedišča, se ob zapelje v to, da ves prosti čas učitelji porabimo za pregledovanje vsakem reševanju naloge pojavi naključen nabor besed po zapiskov, domačih nalog, spisov in podobnih izdelkov. Seveda naključnem vrstnem redu. Če od učenca zahteva, da nalogo reši je potrebno spremljati napredovanje učenca, vendar po principu trikrat zapored, dokler ne doseže določenega odstotka pravilno manj je več in kvaliteta pred kvantiteto. V nadaljevanju navajam rešenih primerov, se že prek teh poskusov snov nauči. nekaj aktivnosti, ki so se dobro obnesle. Po mojih izkušnjah je to učinkovitejši način, da učenca spodbudiš k učenju, kot če napoveš ocenjevanje. Pregled zapiskov v živo Druga prednost kvizov v spletni učilnici pa je enostavno Pisanje zapiskov v zvezek in reševanje pisnih vaj so učenci pred pridobivanje konkretnih podatkov, s katerimi lahko staršem in vklopljenimi kamerami izvajali pri pouku v živo. Preden sem jim razrednikom realno poročamo o napredku in delu učencev. Ko videokonferenco dovolila zapustiti, so mi prepisano snov in so učenci vpisani v spletno učilnico, program sledi vsaki rešene vaje pokazali v kamero. Pred tem dogovorom učenci učenčevi dejavnosti in napredku. Izpišemo lahko raznovrstna zapiskov niso vsi niti ustvarili ali pa so jih preprosto prekopirali poročila o vsaki njihovi aktivnosti. Tako je formativno iz priprave. spremljanje učenca olajšano, prav tako izpis poročil s konkretnimi informacijami. Pregledovanje pisnih izdelkov Pregledovanje pisnih sestavkov je potekalo na enak način. Že s tem, ko so pisne sestavke pisali v živo, sem poskrbela, da je to 5 ZAKLJUČEK storilo veliko več učencev, kot če bi morali to narediti sami izven Pouk tujega jezika na daljavo je kompleksnejši od poučevanja pouka. Poleg tega sem jim bila med pisanjem tudi na voljo prek večine drugih predmetov, saj morajo učenci napredovati tudi pri klepeta za morebitne zadrege. spretnostih, ki se jih ne da naučiti frontalno. Didaktika učenja Kar je bilo ustvarjalnega pisanja, so mi učenci še vedno oddajali konverzacije, izgovorjave in uporabe besedišča ter slovničnih zapiske v spletno učilnico, če sem se odločila preverjati pravopis. struktur v razredu ni enostavno prilagoditi učenju na daljavo. S Pogosto pa sem se odločila preverjati samo vsebino, slovnico, primernimi orodji in didaktičnimi načini lahko vodimo učence, izgovorjavo in besedišče, zapisa besed pa ne. V tem primeru so da napredujejo tudi na teh specifičnih področjih. Ob daljšem mi v spletno učilnico oddali zvočni zapis svojega izdelka. šolanju na daljavo tako učencem kot učiteljem pade motivacija. Poslušanje posnetka branja njihovega ustvarjalnega izdelka je Temu se lahko v veliki meri izognemo, če so učenci v pouk bilo mnogo hitrejše in tudi moja povratna informacija, ki sem jo vključeni aktivno in sodelovalno. Staršem je potrebno omogočiti, prav tako oddala v spletno učilnico v obliki zvočnega zapisa, je da se lahko umaknejo iz učnega procesa. Zato je potrebno bila nazornejša. Poleg tega so učenci poleg pisanja povadili tudi pripraviti in organizirati e-gradiva tako, da jih je vsak učenec branje in izgovorjavo. sposoben uporabiti samostojno, brez pomoči. Z dobro organizacijo in vlaganjem časa v učenje možnosti, ki mi jih 4.3. Preverjanje znanja ponujajo spletna orodja, se učitelji lahko izognemo izgorevanju, V jesenskem delu šolanja na daljavo nisem več pregledovala saj lahko napredku učencev sledimo natančno in časovno preverjanj znanja, ki bi mi jih učenci oddajali v npr. pdf obliki. učinkovito. Namesto tega sem se naučila v spletni učilnici ustvariti teste oz. tako imenovane kvize, kjer učenci dobijo povratno informacijo takoj. Časovni vložek v učenje sestavljanja različnih tipov nalog LITERATURA IN VIRI je velik, saj je bil cilj znati sestaviti različne tipe nalog, s katerimi [1] Allianz Care. 2021. Zoom Fatigue – Why video calls are so exhausting. bi lahko preverila vse štiri sporazumevalne spretnosti. Na dolgi Dostopno na naslovu Zoom Fatigue – Why video calls are so exhausting | Allianz Care (16. 3. 2021) rok me je pridobljeno znanje rešilo pred izgorelostjo. Naloge se [2] Allyson Caudill. 2018. Color-Coding: The Differentiation Strategy You avtomatično popravijo same, ob napaki se učencu izpiše tudi Never Knew You Needed Dostopno na naslovu https://www.weareteachers.com/color-coding-classroom/ (27. 12. 2018) razlaga. Še vedno pa sem pregledala tiste tipe nalog, kjer so [3] A. Pšeničny. 2008. Prepoznavanje in preprečevanje izgorelosti. odgovori prosti – npr. dolgi odgovori pri bralnem razumevanju, Dostopno na naslovu https://www.burnout.si/uploads/clanki/izgorelost%20poljudni/08_11Dida spis ali govorna prestavitev. ktaIzgorelost.pdf (november 2021) Poleg prihranka časa imajo kvizi v spletnih učilnicah še dve [4] Caralee Adams. 2019. 15 Smart Ways to Prevent Teacher Burnout That prednosti, vredni poudarka. Really Work. Dostopno na naslovu https://www.weareteachers.com/prevent-teacher-burnout/ (5. 12. 2019) 501 Poučevanje na daljavo v prvem razredu First grade distance teaching Sonja Klemen Osnovna šola narodnega heroja Maksa Pečarja Ljubljana, Slovenija sonja.klemen@gmail.com POVZETEK starši, učitelji in učenci. Porodila so se nova spoznanja, novi načini poučevanja in spremljanje učenčevega napredka direktno Opisuje potek izvajanja pouka na daljavo z uporabo sodobnih iz učiteljevega v učenčevo domače okolje. informacijsko-komunikacijskih tehnologij. Učinkovitost in prednost predhodnih izobraževanj ter usposabljanja učiteljev za izvedbo pouka na daljavo. Usposabljanje staršev za prenos 2 UČINKOVITOST POUČEVANJA IN učiteljevih navodil pri uporabi spletnih učilnic. Pomen UČENJA Z UPORABO SODOBNIH NAPRAV osveščanja varnosti na internetu ter spletni bonton. Vpliv IN APLIKACIJ komunikacije na razvoj osebnosti. Posledice socialne izoliranosti Način poučevanja na daljavo je za učitelje predstavljal velik ter soočenje s stresom. Prednosti in slabosti pouka na daljavo. izziv. Šolske institucije so omogočale različna izobraževanja iz KLJUČNE BESEDE področja informacijsko-komunikacijske tehnologije. Učitelji smo se seznanili z različnimi spletnimi platformami, sistemi in Komunikacija, poučevanje na daljavo, uporaba sodobnih orodji za učenje na daljavo. Seznanitev in končno poznavanje tehnologij in e/i-gradiv, stres, vrednotenje znanja orodij za poučevanje na daljavo, je bilo nujno potrebno za spletna ABSTRACT srečanja ter njihovo nadgradnjo. V času pouka na daljavo se je obrestovalo večletno postopno vključevanje informacijsko- Describing the way of online teaching with the support of komunikacijske tehnologije v učni proces. Ravno tako so se v information - communication technologies. Effectiveness and osnovnih šolah izvajala izobraževanja iz področja računalništva advantage of previous way of education and training of teachers za vse generacije učencev. to perform online teaching. Parents training to apply teacher Ure računalništva za obvladovanje osnov računalniškega instructions when using online classrooms. The importance of opismenjevanja so marsikateremu otroku olajšala spletna awareness of online safety and online etiquette. The influence of srečanja. Kljub temu, da smo v razcvetu uporabe in dostopnosti communication on personality development. Consequences of do različnih komunikacijskih tehnologij in veščin, uporaba teh še social isolation and stress handling. Advantages and zdaleč ni dosegljiva vsem, ki bi si to želeli, bodisi iz naslova disadvantages of distance learning. finančne nezmožnosti ali slabšega omrežnega dostopa do digitaliziranega območja. Problemi so zlasti pri tistih učencih, ki KEYWORDS izhajajo iz šibkejšega socialnega okolja in v domačem okolju Communication, education, online teaching, use of modern niso imeli ali nimajo prave možnosti dostopa in seznanitve z technologies and materials, stress, evaluation of knowledge uporabo računalniške tehnologije. Pri pouk na daljavo, je bilo potrebno na začetku usvojiti nekatera pravila bontona iz obnašanja pred računalnikom. 1 UVOD Dogovor z učenci in njihovimi starši je vključeval, da se pred Posledica pandemije in posledično globalnih sprememb začetkom videokonference uredimo, pripravimo svoj delovni današnjega časa, je poučevanje otrok na daljavo. Učenje na prostor, šolske pripomočke in učbenike ter se pravočasno daljavo je prineslo nove oblike izvajanja pouka. Od učitelja se je vključimo v videokonferenco. Dogovor je vključeval tudi, da naenkrat pričakovalo, da obvlada interaktivna področja. Večletna odstranimo vse moteče dejavnike, se med videokonferenco ne nadgradnja in usposabljanje učiteljev iz področja informacijsko- prehranjujemo, uporabljamo ikono za dvig roke ter se ne komunikacijske tehnologije je pokazala svoje pozitivne sprehajamo po prostoru ali igramo. rezultate. Začetna negotovost glede poteka poučevanja na Ravno tako so na daljavo potekale tudi učiteljske konference, daljavo je hitro prerasla v učinkovito, uspešno in rutinsko izobraževanja in usposabljanja učiteljev. Na šoli, kjer poučujem, opravilo. Ob začetku izvajanja pouka na daljavo se je postavljalo je bila vpeljana praksa medgeneracijske pomoči med učitelji pri ogromno vprašanj. Sama izvedba je od učitelja zahtevala usvajanju interaktivnih veščin ter pomoč pri začetni izpeljavi neprimerno več dela, ogromno novih smernic pri načrtovanju, usklajevanju ter izvedbi pouka. V veliko pomoč učitelju so bili pouka na daljavo. Vzpostavila se je tudi spletna različica interaktivni učbeniki, vsebine ter smernice in priporočila vseh pogovornih ur ter roditeljskih sestankov. Vsekakor so pogovorne deležnikov pri poučevanju na daljavo. Vsekakor pa so ključno ure in roditeljski sestanki v fizični obliki najboljši in vlogo pri mlajši populaciji šolskih otrok odigrali starši. Za najprimernejši komunikacijski stik med starši in učitelji. izvedbo pouka na daljavo je bilo ključno dobro sodelovanje med 502 2. 1 Varna raba interneta bilo potrebno preveriti ali imajo vsi otroci možnost, da spremljajo pouk na daljavo. Šola je poskrbela, da nihče ni ostal Varna raba interneta je pomembna za vse uporabnike, tako za brez računalnika. Večje število učencev je pouk spremljalo v najmlajše, kot tudi za starejše uporabnike spleta. Danes je dopoldanskem času. Otroci tistih staršev, ki niso službovali od življenje otrok in odraslih povezano in prepleteno z uporabo doma, pa so imeli pouk v popoldanskem času. Kljub sodobnih tehnologij, različnih medijev, ki oglašujejo svoje prilagojenemu načinu izvedbe pouka, je bilo potrebno vključiti storitve in nas vpletajo v svet različnih aplikacij in spletnih še ostale deležnike, ki so prispevali svoje učne vsebine (dodatni storitev. Seveda pa so najmlajši uporabniki najranljivejša in dopolnilni pouk, krožke, angleščino, učno pomoč…) in jih skupina in so lahko hitro žrtev spletnih prevar in zlorab. Zato je časovno umestiti v tedenski koledar. Ob vsem prilagajanju smo ozaveščanje o pasteh in nevarnostih na spletu izrednega pomena. učitelji ugotovili, da tak način poučevanja za učence in učitelje Zlasti je pomembno ozaveščati najmlajšo in najranljivejšo predstavlja dnevno dopoldansko in popoldansko obvezo. generacijo otrok. Potrebno je bilo izobraziti starše učencev. Zaradi različne Veliko prvošolcev zna osnovno uporabljati sodobne računalniške pismenosti, socialne neenakopravnosti pri dostopu komunikacijske naprave, telefon, tablični računalnik. Risanke, do informacijsko-komunikacijskih tehnologij, so šole filmi, računalniške igrice so njihove najbolj priljubljene vsebine. organizirale več spletnih izobraževanj za vzpostavljanje Vsakodnevno igranje igric lahko povzroči odvisnost in čustvene komunikacijskih kanalov in nudile glede na različne družinske motnje. Strokovnjaki opozarjajo, da naj bi učenci prve triade razmere tudi individualni pristop do usposabljanja osnovnih osnovne šole, preživeli pred zaslonom v prostem času, največ računalniških veščin. Na razredni stopnji se prvi stik z učenci eno uro na dan. Pomembno je nenehno osveščanje staršev in vzpostavlja preko staršev. Njihova vloga je, da poskrbijo za učiteljev na škodljivost pretirane uporabe sodobnih naprav. prenos navodil učencu. Z vpeljavo stalnice videokonferenčnih Zlasti učitelji opozarjamo otroke na tovrstne nezdrave razvade. rutin se vloga in prisotnost staršev zmanjšuje. Preko spletnih Pogosto je domače okolje tisto, ki lahko zavira ali spodbuja učilnic in elektronske pošte so starši komunicirali z učitelji, tovrstna dejanja. Otroke opozarjamo na pomembnost zdravega učenci pa preko spletnih učilnic spremljali pouk. Učitelji so življenjskega sloga, z zagotavljanjem dobrega fizičnega in nalagali v spletne učilnice različno učno gradivo, ki so ga starši psihičnega počutja učencev. Osveščamo jih o pomenu otrokom lahko večkrat predvajali ali glede na vsebino natisnili. prijateljstva, druženja z vrstniki, prijatelji, sorojenci. Razlaga snovi v obliki PowerPointov je bila bolj pregledna in 2. 2 Izzivi v poučevanju vsebinsko bogata. Učiteljeva razlaga je bila po potrebi tudi posneta, da so si učenci lahko večkrat pogledali posnetek in s tem Poučevanje v prvem razredu temelji predvsem na konkretnih hitreje in lažje usvajali znanje. Pomemben je bil neposreden stik primerih in izkustvenem učenju. Ko smo prešli iz klasičnega učenca z učiteljem. Ob koncu vsake videokonference so imeli načina poučevanja v razredu na pouk na daljavo je bilo potrebno učenci priložnost, da so se med seboj pogovorili, spraševali, se razmisliti tudi o prenosu in izvedbi učnih vsebin, ki so pri dogovarjali in je med njimi potekala komunikacija. Preglednost klasičnem poučevanju vsebovale konkretno in izkustveno spletnih učilnic je bila učinkovita in praktična ter je nudila učenje. Porajala so se tudi vprašanja, kako in na kak način povratno informacijo učitelju, ko so starši pošiljali v spletno podajati oziroma posredovati znanje na daljavo, da bo cilj učilnico tedenske izdelke otrok. Starši so imeli vpogled v usvojen in ga bo možno kasneje tudi vrednotiti. Kako narediti Teamsov koledar, kjer so bile dnevno zabeležene učne in druge pouk prijeten in hkrati učinkovit, kako vključiti dovolj in ne dejavnosti njihovih otrok. To je predstavljalo olajšanje staršem preveč slikovnega in glasovnega materiala ter kako vplivati na in učiteljem. Starši učencev so lahko nemoteno preko spletnih gibalni, čutni del pouka. učilnic pošiljali predstavitve knjig iz naslova različnih bralnih Pouk na daljavo je vključeval tudi pripravo in izdelavo značk ali pa učiteljici ter knjižničarki kar v živo preko spleta različnih didaktičnih pripomočkov tako iz naravnih, kot drugih predstavilili izbrano knjigo ali pesmico za bralno značko. materialov, ki so bili učitelju in učencem v pomoč pri didaktičnih Ravno to sodelovanje in usklajevanje med starši in učitelji je vsebinah. Primer; Pri spoznavanju okolja smo se pogovarjali o še poglobilo vez v trikotniku: učitelj – starš – učenec. Kot prvih znanilcih pomladi. Učitelji smo preko videokonference z učiteljica sem začutila, da nam starši sedaj pripisujejo višjo učenci predstavili in opisali rastline, prinešene iz narave, kot so vrednost našega dela in poklica, kot je ta predstavljal pred zvonček, kronica, trobentica, žafran, teloh. Vsako rastlino smo poučevanjem na daljavo. Marsikateri starš je ob tovrstnem natančno opisali, povedali kje raste… Pred zaključkom poučevanju bolje razumel naravo učiteljevega poslanstva in s videokonference so posamezni učenci ponovili poimenovanje spoštljivostjo vrednotil trud, poučevanje ter nenazadnje same rastline ter jo opisali. Učitelji smo tako dobili povratno priprave učnih sklopov ter njihovo izvedbo. informacijo o znanju. Zanimivo je bilo, da so nekateri učenci ob Šola, na kateri poučujem, se je odločila za uporabo aplikacije naslednjem srečanju pokazali ostalim učencem rastline, ki so jih Microsoft Office in Teams. Gre za celovito digitalizirano učno sami nabrali v naravi in jih opisali. Pomembno je, da učenci tako okolje. Vključuje sistem upravljanja učenja z vsemi potrebnimi spremljajo lastni napredek, razvijajo spretnost komuniciranja, orodji. Učiteljem in staršem je navedena aplikacija omogočala poglabljajo pozitiven odnos do učenja ter si krepijo samozavest. lažjo dostopnost in preglednost do vseh ostalih aplikacij in Nadgradnja obravnavane snovi so bile naloge v delovnem orodij. Preko nje so starši lahko komunicirali z učitelji ter zvezku ter učni listi. Starši so naloge poslikali ter jih naložili v nalagali opravljene naloge svojih otrok v odprte datoteke. spletno učilnico v vpogled učitelju, kot povratno informacijo o Učitelji smo imeli omogočen vpogled in pregled nad učenčevem delu in napredku. opravljenimi nalogami ter s kljukico v datoteki označili, da je Učitelji prve triade smo bili pri pouku na daljavo odvisni od naloga opravljena in pregledana. Veliko podporo spletnemu staršev, njihovega sodelovanja in pomoči otroku. V prvi fazi je poučevanju so omogočili interaktivni učbeniki in delovni zvezki 503 ter interaktivni zvezki. S pomočjo teh je bilo veliko lažje izrednega pomena. Socialni stiki se krepijo ob igri in druženju. S predavati in zapisovati snov. Učencem je bila omogočena večja prihodom otrok v prvi razred, se krepijo nova ter utrjujejo stara preglednost nad zapisi v delovnih zvezkih in zvezkih. Direkten poznanstva iz vrtca. vpogled nad učiteljevim izvajanjem zapisov je vzpodbujal Socialne izkušnje in interakcije med otroci so se z zaprtjem učence k zbranosti, večji učinkovitosti in pomnenju učne snovi šol povsem spremenile. Otroci so bili v času šolanja na daljavo ter lažjo sledljivost pri pouku. Učitelj pa je z zapisi v delovni prikrajšani za stike s svojimi sošolci. Zato se na področju zvezek ali zvezek lažje sledil in preverjal znanje učencev. socialnega razvoja lahko pojavijo zaostanki zaradi pomanjkanja Povratna informacija je bila tako obojestranska in učinkovita. interakcij izven družinskega okolja. Zaskrbljujoči so tudi podatki Spletni portali z elektronskim učnim gradivom so bili v veliko o fizičnem zdravju otrok. Glede gibalnega razvoja otrok je veliko pomoč učiteljem in ti so lahko gradiva prilagajali po svojem polemik sprožila slovenska študija, katere rezultati že kažejo na okusu. Gradiva različnih založniških hiš so bila nadgradnja poslabšane dosežke otrok pri športno vzgojnem kartonu (SLOfit, tiskane izdaje z enakim naslovom. Vsa gradiva so ponujala 2020). orodjarno s številnimi uporabnimi orodji, nekatere izmed njih pa Vsaka vojna ali kriza pusti pečat pri ljudeh. Vsak različno so bogatile še z interaktivnimi nalogami, avdio- in videoposnetki, doživlja krizna obdobja v svojem življenju. Zagotovo bo tudi s spletnimi povezavami ter drugimi multimedijskimi dodatki. pandemija Covida-19 dolgoročno pustila posledice tako na Ob tem Brodnik (2013, str. 356) izpostavlja, da »so postala e- učnem, kot vedenjskem področju novodobnih generacij otrok. gradiva sestavni del pouka (tudi pri poučevanju v živo, op. avt.). Najmanj posledic bodo občutile generacije najmlajših. Izdelujejo, posodabljajo, objavljajo in uporabljajo jih učitelji, Generacija otrok v zgodnjem in poznem otroštvu pa več. Vrstniki vzgojitelji, ravnatelji, računalnikarji, vse bolj pa tudi učenci ter so pomemben dejavnik v njihovem življenju. Prikrajšanost za dijaki. Na voljo so tudi številna vnaprej pripravljena e-gradiva, stike z vrstniki, bo pri nekaterih pustila posledice pri ki jih pojmujemo kot vsa digitalna gradiva za doseganje učnih vzpostavljanju stikov, sporazumevanju, timskem delu ter na ciljev. E-gradiva zanesljivo prispevajo k večji kakovosti pouka čustvenem področju. Zaradi povečane uporabe sodobnih in k izgradnji bolj poglobljenega znanja, saj multimedijski komunikacijskih naprav, se krepijo z računalniškim znanjem elementi omogočajo bolj poglobljeno in kakovostno obravnavo podprte generacije. Prednosti pouka na daljavo bodo dolgoročno učne snovi, interaktivnost pa prispeva k večji aktivni vlogi vidne v obliki izpopolnjenih informacijsko-komunikacijskih učencev in dijakov. E-gradiva omogočajo kakovostno veščin otrok. Bogatenje usvajanja teh veščin bo pozitivno v sodelovalno učenje na daljavo, reševanje problemov, kasnejšem obdobju, ko se bo ta generacija otrok pojavila na trgu raziskovanje in ustvarjanje.« dela. Po drugi strani se povečuje trend dela od doma, kar gre V prvem razredu je tehnika poučevanja prilagojena učnim sigurno na roko sedanji generaciji bodočih iskalcev zaposlitve. vsebinam. Učni načrt vključuje različne metode in oblike Žal, sodobne naprave in aplikacije ne morejo nadomestiti poučevanja, ki so primerne za mlajše otroke. Razlaga in prikaz človeške bližine, pristnosti in pogovora, zaradi katerih bodo temelji na izkustvenem učenju, podkrepljenem na konkretnih prikrajšane novodobne generacije. (Jeriček, H., 2010) pravi, da primerih. Učitelja spodbuja, da išče odgovore na vprašanja, kako smo ljudje med seboj povezani in vplivamo drug na drugega s spodbuditi učence k večji miselni dejavnosti, hkrati pa ga svojim počutjem in razpoloženjem. Zato je vsak, ki dela ali živi opozarja, da so čustva, osebni cilji, radovednost, težnja po v šolskem okolju pomemben, saj prispeva k ozračju v šoli. uveljavljanju svojih zmožnosti, samouresničevanju, ustvarjanju Spraševanje in preverjanje znanja, slabe ocene, govorni in osebnem smislu pri učenju enako pomembni kot čisto nastopi, konflikti z učenci in učitelji so tipične stresne situacije v intelektualni procesi (Marentič Požarnik, 2003). šoli, ki zahtevajo od učitelja veščine in znanja ter dodatna izobraževanja, da lahko prepreči nastanek marsikatere težave. Z dobro komunikacijo lahko rešimo marsikaj (Jeriček, H., 2010). 3 SOCIALNA IZOLIRANOSTI PRI POUKU NA Tudi družinske razmere in okolica vplivata na otrokovo DALJAVO TER SOOČANJE S STRESOM obnašanje in odzive. Nenavadno ali spremenjeno obnašanje ter Cilji osnovne šole so omogočiti učenkam in učencem osebnostni nenadzorovani odzivi so alarm, da se z otrokom nekaj dogaja. razvoj v skladu z njihovimi sposobnostmi in zakonitostmi Učitelji so zagotovo tisti, ki med prvimi opazijo spremembe v razvojnega obdobja (pri tem je potrebno uravnotežiti spoznavni, otrokovem obnašanju. čustveni in socialni razvoj), posredovati temeljna znanja in Ob sprejetju ukrepov za zajezitev epidemije Covid-19 so se spretnosti, ki omogočajo neodvisno, učinkovito in ustvarjalno ljudje srečevali z različnimi stresnimi situacijami. Te so vplivale soočenje z družbenim in naravnim okoljem in razvijanje kritične na življenje ljudi, družin in otrok. Veliko teh negativnih stresnih moči razsojanja (Nišandžić D., 2011). situacij je ostalo skritih za štirimi stenami. V prvi triadi osnovne šole je učno izobraževalni sistem usmerjen v proces opismenjevanja, usvajanja spretnosti in sposobnosti branja ter pisanja. V tem obdobju se razvijajo tudi 4 ZAKLJUČEK sposobnosti prenosa sporočanja ali razvijanje komunikacije, ki Pouk na daljavo je spremenil načine poučevanja. Smatram, da je vpliva na razvoj osebnosti. S tega vidika naj bi torej potekal dolgoročno gledano taka izvedba pouka pustila tudi pozitivne jezikovni razvoj in razvijanje jezikovnih sposobnosti učencev rezultate. Veliko učiteljev se je dodatno izobraževalo in najprej s pomočjo razvijanja temeljnih komunikacijskih izpopolnjevalo svoje informacijsko-komunikacijsko znanje. spretnosti in sposobnosti, šele nato naj bi se otrok pričel Učenci so napredovali pri usvajanju računalniškega znanja. Res spoznavati s strukturo jezika (Pečjak, S., 2009). je, da sem kot učiteljica pogrešala fizično prisotnost otrok, V tem obdobju je proces socializacije izredno pomemben. razred, šolo. Na začetku pouka na daljavo se se porajala Zato je druženje z vrstniki, prijatelji, učitelji ter drugimi vprašanja, kako bo tak način poučevanja na dolgi rok uspešen in 504 kako se bo ovrednotilo znanje otrok. Bili so pomisleki, Koliko šolo niso več želeli imeti pouka na daljavo. Pogrešali so svoje samostojnega dela bo prvošolec vložil v svoje delo, kakšen bo sošolce in svoje učiteljice. starševski nadzor in vmešavanje v samostojno delo otrok. Danes vidim, da so bili moji strahovi odveč. Pri večini otrok je bil napredek izrazito viden. Zlasti je bil opazen napredek pri LITERATURA IN VIRI grafomotoriki in samostojnosti. Slabši je bil napredek pri [1] Brodnik, V. (2013). Uvodnik v stezo Ustvarjanje in objavljanje. V Kreuh, besednem zakladu in komunikaciji. Pri povratku v šolo se je N., Trstenjak, B., Blagus, K., Kosta M. in Lenarčič, A. (ur.), Mednarodna konferenca Splet izobraževanja in raziskovanja z IKT – SIRikt 2013, primanjkljaju posvetilo več pozornosti. Kot posledica Kranjska Gora, 15.–17. maj 2013. Zbornik vseh prispevkov (str. 356). prekinjenega neposrednega šolskega socialnega stika, je bil Ljubljana:Miška. opazen slabši napredek pri usvajanju slovenskega jezika otrok, https://www.dlib.si/stream/URN:NBN:SI:DOC5JBFAPKO/aa05b651- bf9d-4154-a075-a8354d06a097/PDF katerih materni jezik ni slovenski. Tem otrokom so bile v času [2] Jeriček, H. (2010). Ko učenca strese stress. Ljubljana: Inštitut za pouka na daljavo nudene ure dodatne strokovne pomoči. Med varovanje zdravja Republike Slovenije [3] Marentič Požarnik, B. (2003) Psihologija učenja in pouka. Ljubljana: DZS poukom na daljavo je potekala tudi diferenciacija pouka. [4] Nišandžić D. (2011). Vloga vzgojiteljice v prvem razredu devetletke. Vsekakor pa je pomembno dejstvo, da si učenci ob povratku v Ljubljana: Pedagoška fakulteta [5] Pečjak, S. (2009). Z igro razvijamo komunikacijske sposobnosti učencev. Ljubljana: ZRSŠ 505 Učiteljevi izzivi med šolanjem na daljavo pri pouku geometrije Teacher challenges during distance learning in geometry lessons Jožica Knez Osnovna šola Stična Ivančna Gorica, Slovenija jozica.knez@os-sticna.si POVZETEK • spoznavajo uporabnost matematike v vsakdanjem življenju; • spoznavajo matematiko kot proces ter se učijo ustvarjalnosti in Članek opisuje s kakšnimi izzivi sem se srečala v času šolanja na natančnosti; daljavo, in sicer pri sklopu geometrije pri matematiki. Učitelji na • razvijajo zaupanje v lastne (matematične) sposobnosti, naši šoli smo se nekako izogibali geometrije na daljavo, zato smo odgovornost in pozitiven odnos do dela in matematike; dajali prednost aritmetiki. V nekaterih razredih to zaradi učnega • spoznavajo pomen matematike kot univerzalnega jezika; načrta ni bilo izvedljivo, zato se je bilo treba soočiti z izzivom. V tem članku bom predstavila na kakšne načine sem prikazala • sprejemajo in doživljajo matematiko kot kulturno vrednoto. geometrijske vsebine svojim učencem. 2. GEOMETRIJA KLJUČNE BESEDE V osnovni šoli v tretji triadi so cilji pri področju geometrije znani. Matematika, geometrija, učenje na daljavo Zapisani so v učnem načrtu, ki je osnova za učiteljevo delo. [2] ABSTRACT Učenci v tretjem vzgojno-izobraževalnem obdobju: The article describes the challenges I faced during distance • utrjujejo pretvarjanje merskih enot in jih povežejo z reševanjem learning, namely in the field of geometry in mathematics. The geometrijskih nalog; teachers at our school somehow avoided geometry, so we • razvijajo geometrijske predstave v ravnini in prostoru; preferred arithmetic. In some classes, this was not possible due • razvijajo uporabo geometrijskega orodja pri načrtovalnih to the curriculum, so a challenge had to be faced. In this article, geometrijskih nalogah; I will present the ways in which I have shown geometric content • razvijajo strategije geometrijskih konstrukcij z uporabo to my students. geometrijskega orodja; KEYWORDS • opisujejo postopek geometrijske konstrukcije; Mathematics, geometry, distance learning • razvijajo natančnost in spretnost pri računanju neznanih količin pri likih in telesih. 1. UVOD 3. GEOMETRIJA NA DALJAVO Trenutni in sodobni čas od nas zahteva, da se vsi učitelji Pri obravnavi poglavij, ki vključuje geometrijo je potreben prilagajamo, sledimo novim spremembam, se prilagajamo in ves popolnoma drugačen način predstavitve učne snovi. Pri nekih čas evalviramo svoje delo in načrtujemo kako napredovati pri računskih postopkih je dovolj, da vso zadevo napišeš na ekran, svojem delu. Gledati moramo, da delamo kakovostno in da to sproti razlagaš in ponoviš na novih primerih. Zadeva funkcionira pomeni, da spodbujamo znanje, nenehno učenje in pridobivanje brez težav. Ko pa pridemo do geometrije pa naletimo na tisoč in novih veščin in spoznavanje sodobnih orodij za poučevanje eno oviro. Kako prijeti geometrijsko orodje? Kam ga postaviti? matematike. To velja tako v običajnih pogojih , v času Kako razvijati geometrijske predstave? Kako opredeliti prostor poučevanja na daljavo pa še toliko bolj. in v njem osnovne geometrijske elemente? Še in še je vprašanj, Že v učnem načrtu je s splošnimi cilji opredeljen pouk in namen ki se nam postavijo ob novih situacijah v katerih smo se znašli. poučevanja matematike. [1] Učenci pri pouku matematike: 4. NAČINI PREDSTAVITEV • razvijajo matematično mišljenje: abstraktno-logično mišljenje V našem aktivu smo imeli veliko idej, na kakšen način pripraviti in geometrijske predstave; ure za naše učence. Naše ure smo pripravljali skupaj, poenotene, • oblikujejo matematične pojme, strukture, veščine in procese ter za vseh 7 do 8 oddelkov istega razreda enake priprave. Ker smo povezujejo znanje znotraj matematike in tudi širše; imeli ure v živo ob različnih dneh so imeli učenci sicer vedno na • razvijajo uporabo različnih matematičnih postopkov in razpolago tudi napisano pripravo v spletni učilnici. Pri urah v tehnologij; živo pa smo razložili zapisano še za nazaj in za tekočo uro. 506 Na začetku smo pripravljali video posnetke, tako, da smo posneli simetrale daljice, če je njegova oblika popolnoma drugačna kot naše roke z uporabo geometrijskega orodja in naša navodila za jo imajo učenci v roki. Že tako smo imeli učitelji dovolj dela z delo. Krasno. Ti video posnetki so dobri za pripravljene ure, ki si motiviranjem učencem in sledenjem snovi in ostalimi težavami jih lahko učenci sami pogledajo, za ure v živo tudi, vendar z eno na katere niti nismo imeli vpliva. težavo. Učencu težko pokažemo oziroma ga usmerjamo z vrtenjem videoposnetka, kaj mora storiti, na kaj mora biti Zato smo želeli orodje, ki bo samo po sebi primerljivo z uporabo pozoren. To se je pokazalo pri urah dopolnilnega pouka, pa tudi orodja na tabli, enako učinkovito, izdelek pa pregleden in pri urah v živo. natančen. Cilj mi je bil uporabljati orodje, kot je na interaktivnih tablah, ki jih imamo v šoli. S takim pogledom so učenci Iskali smo nek približek situaciji v razredu, učitelj stoji pred tablo seznanjeni, kar bi pomenilo dodaten plus za poučevanje. kjer drži ravnilo in šestilo. Imeli smo željo po nekem programu z geometrijskim orodjem. Najprej smo našli program OpenBoard, kasneje pa Smart Notebook. 4.1 Video posnetki Video posnetke smo delali na različne načine. Če so bili namenjeni samostojnemu ogledu učenca, potem so to odličen vir informacij za učenca, lahko si ga tudi večkrat ogleda. Pri urah v živo je bila uporaba videa dobra podlaga za uro, ni pa bila vedno uspešna. Večkrat smo si samo delček postopka ogledali skupaj in snov ustno večkrat ponovili, poudarili … Slika 3. Prikaz orodja v programu OpenBoard 4.3 Smart Notebook Program Smart Notebook je program, ki se ga uporablja na interaktivnih tablah. Lahko ga imamo nameščenega tudi na prenosnik. Lahko uporabljamo odprto verzijo ali verzijo z licenco. Slednja ima več možnosti, funkcij in je brez vodnega žiga. Uporabljamo lahko vse vrste pisal, oblik, pisav – to ni nič Slika 1. Prikaz načrtovanja s šestilom na list papirja novega. Nova je pa oblika geotrikotnika in šestila. Oboje ima takšno obliko, kot je znana učencem. Ravnilo - geotrikotnik Geotrikotnik ima enak videz, kot ga imajo učenci doma. Z njim lažje ponazorim določene postopke konstruiranja, kot drugače. Enostavno ga lahko uporabim za načrtovanje črt, kotov, merjenje kotov … saj jim je vse to že domače iz siceršnjega šolskega dela. Všeč mi je, ker lahko trikotnik premakneš okoli 0, ga zavrtiš, povečaš, zmanjšaš … Slika 2. Prikaz načrtovanja z geotrikotnikom na list papirja 4.2 Open Board Open Board je program, ki je dostopen vsem. Vsebuje več različnih orodij, tudi geometrijska. Na spodnji sliki so prikazana kotomer, s katerim lahko nakažemo in narišemo določene kote. Slika 4. Geotrikotnik v programu Smart Notebook Z njim lahko tudi kote merimo. Ravnilo je dobro orodje. Šestilo Šestilo je pa zares neobičajno. Ker vemo, da imamo različne tipe učencev (avditivni, vizualni in Prav to orodje me je zmotilo do te mere, da sem se lotila kinestetični) [3] je zelo pomembno pri določenih snoveh, da raziskovanja in iskanja novga, boljšega programa. S tem imamo res vse učence pod okriljem. Nekateri vse razumejo že po kotomerom težko ponazorimo postopek načrtovanja npr. ustni razlagi, nekateri še po vidni razlagi, gibalno razlago pa smo 507 uporabili z premikanjem orodja po ekranu hkrati z učenčevim Na desni strani Slike 6 je viden tudi vodni žig, ki je sicer samo v sodelovanjem doma. Torej, če je učenec gledal in hkrati še osnovni različici programa. Sicer deluje vse kot je pričakovano. poslušal navodila – je to zmaga za vse. Snemalnik Dobra stran tega programa je bil tudi že vgrajen snemalnik. U bistvu si imel vse na enem mestu in uporabil lahko kadarkoli. Brez dodatnih programov in dodatnega iskanja. Pri snemalniku si lahko nastavil področje snemanja, lahko si ga tudi uredil. 5. ZAKLJUČEK Pri mojem delu mi je bilo najbolj pomembno, da je bil moj čas Slika 5. Šestilo v programu Smart Notebook učinkovito izkoriščen z uporabo primernih tehnologij. Šestilo v tem programu ima dejansko realno podobo. Z njegovim Načrtovalne naloge so bilo uspešno opravljene zaradi teh orodij. dinamičnim premikanjem sem lahko prikazala vse korake Vsa ta orodja so enostavna za uporabnika. Upravljanje z načrtovanja. Konstruiranje nekega postopka je bilo zaradi tega videoposnetki in njihova montaža pa je bila nova motivacija za mnogo lažje. Prezentacija mnogo uspešnejša. S tem smo pridobili nova izobraževanja. Na spletnih portalih je bilo veliko možnosti na času, ki smo ga lahko koristneje uporabili za utrjevanje znanja za učenje le tega. Sedaj ko imam znanja tudi o tem, bodo in s tem uspešneje usvojili snov. videoposnetki s pomočjo tega programa še boljši. Širjenje učiteljevega znanja je naložba v prihodnost. 6. VIRI [1] Učni načrt za matematiko, https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- sola/Ucni-nacrti/obvezni/UN_matematika.pdf (uporabljeno, 14. 8. 2021) [2] Učni načrt za matematiko, 43, https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- sola/Ucni-nacrti/obvezni/UN_matematika.pdf (uporabljeno, 14. 8. 2021) [3] Mršol T, 2014. Zaznavni stili in učne strategije študentov računalništva, matematike in razrednega pouka, 11 http://pefprints.pef.uni- lj.si/2352/1/Tamara_Mrsol_Diploma.pdf (uporabljeno 14. 08. 2021) Slika 6. Uporaba šestila pri načrtovanju. 508 Učenci v vlogi učiteljev Pupils in the role of teachers Martina Kokelj OŠ Antona Martina Slomška Vrhnika Vrhnika, Slovenija martina.kokelj@gmail.com POVZETEK lahko svoje delo dopolnjujejo, popravljajo. Pri vrednotenju izdelkov sodelujejo tudi sošolci (medvrstniško vrednotenje) na Šolsko leto 2020/2021 nam bo za vedno ostalo v spominu, saj je podlagi dogovorjenih kriterijev. potekalo na daljavo. Vsak učitelj se je moral znajti po svoje. Naš pouk je potekal preko aplikacije ZOOM. V prispevku predstavljamo primer pouka na formativen način, v katerem so 2 FORMATIVNO SPREMLJANJE učenci udeleženi pri načrtovanju pouka. Sami so izrazili željo, da se preizkusijo v vlogi učiteljev. Razdelijo se v štiri skupine. Sodoben način poučevanja postavlja v ospredje učenca, ki je pri Vsaka skupina izbere eno Prešernovo pesem iz učnega načrta za pouku aktiven in sodeluje pri načrtovanju, medtem ko učitelj slovenščino za osmi razred in jo analizirajo po učiteljičinih spremlja učenčev napredek, mu daje kvalitetne povratne smernicah. Pogoj za pripravo učne ure je bil, da bodo sošolci pri informacije in možnost za napredovanje in izboljševanje svojega obravnavanju samostojno raziskovali in bili aktivni, tudi z dela. uporabo sodobne tehnologije. Učiteljica je bila pri tem pouku Pri formativnem načinu pouka gre za stalno spremljanje mentorica, učenci pa so samostojno raziskovali. napredka in doseganja ciljev pri učencu po v naprej zastavljenih kriterijih uspešnosti [1]. Učenci sodelujejo pri oblikovanju KLJUČNE BESEDE namenov učenja in kriterijev uspešnosti. S tem želimo doseči, da bodo učenci pri pouku aktivni in na ta način bolj motivirani za Didaktika, formativno spremljanje, informacijska tehnologija, učenje. Učitelj ni več učitelj, ki frontalno podaja učno snov, slovenščina ampak učence podpira, spodbuja in usmerja. Pri formativnem ABSTRACT načinu pouka je najbolj pomembna povratna informacija, na podlagi katere učenec izboljšuje svoje znanje. Povratno The 2020/2021 school year will forever remain in our memory, informacijo si lahko dajejo učenci med seboj, kar imenujemo as it took place at a distance. Every teacher is morally important medvrstniško vrednotenje, ali učitelj. Na podlagi povratne in their own way. Our lessons were conducted through ZOOM applications. In this paper, we present an example of a lesson in informacije učenec svoje dosežke izboljšuje. Pri tovrstnem a formative way in which students participated in lesson pouku ima učenec veliko možnosti za izražanje svoje planning. They themselves expressed a desire to test themselves individualnosti: iskanje osebnega smisla, načrtovanje in in the role of teacher. They were divided into four groups. Each udejanjanje svojih poti, ki so prilagojene njegovim načinom group selected one of Prešeren's poems from the curriculum for učenja, uveljavljanje svojih zmožnosti in interesov, ohranjanje Slovene for the eighth grade and analyzed it according to the radovednosti in ustvarjanje [2]. teachers' guidelines. The condition for the preparation of the Formativno spremljanje bi moralo postati sestavni del procesa lesson was that the classmates would independently research and učenja in poučevanja. Njegov namen je natančna in specifična be active in reading, also using modern technologies. The teacher povratna informacija, ki prinaša učencu odgovore na vprašanja: was a mentor during this lesson, and the students researched - Kaj sem dosegel v odnosu do učnih ciljev in standardov znanja independently. oz. pričakovanih dosežkov/rezultatov? KEYWORDS - Kako napredujem? - Kaj mi uspeva, kaj pa manj? Katera so moja močna področja, Didactics, formative assessment, information technology, katera pa bi moral še razviti in izboljšati? Slovene - Kje imam še rezerve? Učitelj pa se glede na povratno informacijo sprašuje: 1 UVOD - Kako napreduje proces učenja? - Kako ga moje poučevanje podpira? V preteklosti je pouk potekal drugače kot danes. Učitelji so - Kako naj svoje poučevanje spremenim oziroma prilagodim, da poučevali bolj ali manj frontalno, znanje pa se je ocenjevalo s bom učence še bolj podprl v procesu učenja in izboljševanja pisnimi testi, ustnimi ocenjevanji in delnim ocenjevanjem (z znanja? [3]. znaki) brez preverjanja znanja pred ocenjevanjem. Sodoben Učenje ni le razumski proces, njegova učinkovitost je odvisna način poučevanja postavlja v ospredje učenca, aktivnega učenca. tudi od motivacije učencev in njihovih čustev [4]. Učitelji morajo Učenci so udeleženi pri načrtovanju pouka, namenov učenja in ustvariti tako razredno klimo, da si bodo učenci upali sodelovati, kriterijev uspešnosti. Učitelj je tisti, ki organizira in spremlja odgovarjati, tvegati, se tudi zmotiti in delati napake. proces učenja, učence usmerja, jim daje povratne informacije, da 509 Najbolj pomembno je, da učencem učne vsebine približamo in Prvi dve šolski uri je vsaka skupina analizirala svojo pesem. jim damo možnost sodelovanja pri načrtovanju pouka. Včasih Odgovarjali so na učiteljičina vprašanja, ki so jim bila v pomoč nas s svojimi idejami presenetijo. Najbolj pomembno pa je, da se tudi za kasnejše načrtovanje, ter brskali in iskali informacije na veliko več naučijo in zapomnijo, če so pri pouku aktivni. spletu. Naslednje štiri ure so se učenci posvetili načrtovanju pouka za sošolce. Lotili so se oblikovanj delovnih listov in kvizov z različnimi aplikacijami. Svoje načrtovanje, osnutke, 3 OBRAVNAVA OBDOBJA ROMANTIKE delovne liste so po vsaki zaključeni uri poslali učiteljici v pregled, PRI SLOVENŠČINI da jim je dala povratno informacijo oz. smernice za nadaljnje delo. 3.1 Načrtovanje obravnave učnega sklopa V 8. razredu pri pouku slovenščine obravnavamo obdobje romantike na Slovenskem. Glavni predstavnik tega obdobja je 4 UČENCI SE PREIZKUSIJO V VLOGI France Prešeren. Obravnavamo štiri njegova dela: Povodnega UČITELJA moža, Turjaško Rozamundo, Apela in čevljarja ter Krst pri 4. 1 Povodni mož Savici. Prva šolska ura je vedno namenjena branju in vsebinski analizi Učenci so najprej samostojno raziskovali obdobje. Pomagali so pesmi. Skupina, ki je obravnavala Povodnega moža, je želela, da si lahko s priročniki, ki jih imajo doma, in s svetovnim spletom. sošolci najprej sami tiho preberejo pesem in izpišejo neznane Obdobje so morali umestiti na časovni trak, izpisati značilnosti besede. Te so s pomočjo Slovarja slovenskega knjižnega jezika in predstavnike obdobja ter njihova dela. in berila razložili. Nato so pesem prebrali še glasno, in sicer je Naslednjo šolsko uro smo pregledali miselne vzorce, jih vsak učenec prebral eno kitico. Z branjem pesmi so imeli veliko dopolnili in se pogovarjali o samem obdobju. Učenci so prišli na težav, saj je potrebno besede pravilno naglaševati, zato je ena od idejo, da se sami preizkusijo v vlogi učiteljev in bodo za svoje učenk, ki je bila del skupine, še enkrat prebrala pesem. Naslednjo sošolce pripravili obravnavo pesmi. uro je sledila vsebinska analiza pesmi. Vsako kitico posebej smo Učiteljica je za vsako skupino sestavila vprašanja oz. smernice, s razložili in jo obnovili s svojimi besedami. Učili smo se katerimi so si učenci pomagali pri raziskovanju pesmi. Smernice razlikovati mnenja od dejstev, od podatkov, ki jih v besedilu sicer za pomoč pri raziskovanju pesmi: ni, ampak lahko na podlagi le-teh določene stvari sklepamo. - Kdaj je Prešeren napisal pesem in kje je bila objavljena? Tretjo šolsko uro so se učenci razdelili v skupine in se še bolj - Razišči okoliščine nastanka pesmi (komu jo je posvetil, kje je podrobno ukvarjali s pesmijo. V spletni učilnici jih je čakal našel snov za pesem …). delovni list (Slika 2), s katerim so si pomagali pri analizi besedila. - Pesem preberite in naredite zunanjo in notranjo zgradbo ter Pomagali so si lahko s svetovnim spletom, berilom in literaturo, analizo vsebine. če jo imajo doma. Po končanem skupinskem delu smo pregledali - V katero literarno vrsto in zvrst spada pesem in kaj je zanjo rešitve. Skupine so poročale, se med seboj dopolnjevale in značilno. urejale zapiske v zvezku. - Razmislite, na kakšen način boste oblikovali učno uro, pri čemer naj bodo sošolci čim bolj aktivni. - Za sošolce sestavite nalogo poustvarjanja pesmi in dodajte kriterije uspešnosti. 3.2 Načrtovanje učnih ur na daljavo Z učenci smo se lotili dela. Sami so se lotili brskanja po spletu. Vsako uro slovenščine smo se po urniku dobili preko aplikacije ZOOM. Slika 1 prikazuje razdelitev učencev po skupinah po sobah, ki so med sabo sodelovali, raziskovali in iskali ideje. Učiteljica se je sprehajala med sobami in pomagala, če so se pojavila vprašanja. Za načrtovanje smo porabili sedem šolskih ur. Slika 2: Delovni list Slika 3: Povodni mož (ljudska) Učenci so med raziskovanjem odkrili ljudsko različico Povodnega moža (Slika 3) in prišli na idejo, da bi pesmi med seboj primerjali. Učenci so se zopet razdelili v skupine in primerjali pesmi med seboj. Iskali so podobnosti in razlike. Precej težav jim je povzročalo razumevanje ljudske različice, saj vsebuje neobičajne stavčne in skladenjske strukture ter starinski jezik. Ena od najpogostejših dejavnosti, ki sledi obravnavi umetnostnega besedila, je literarno poustvarjanje. Skupina Slika 1: Razdelitev učencev po sobah učencev, ki je raziskovala Povodnega moža, je dobila navodilo, da morajo za sošolce oblikovati tudi poustvarjalno nalogo skupaj 510 s kriteriji uspešnosti. Učenci so si zamislili, da se bodo postavili Zadnjo šolsko uro so učenci v vlogi učiteljev svojim sošolcem ali v vlogo Urške ali povodnega moža in pisali o njunih občutkih. pripravili kviz v aplikaciji Kahoot (Slika 7). Vsak učenec se je Oblikovali so tudi kriterije uspešnosti. Da bodo uspešni, morajo prijavil s svojim imenom preko svojega pametnega telefona. Nad besedilo členiti na odstavke, upoštevati pravopisna pravila, pisati kvizom so bili zelo navdušeni in tekmovalni. v prvi osebi ednine, zapis mora biti čitljiv in izviren. Učenci so svoje izdelke oddali v spletno učilnico. Po znanih kriterijih so sošolcu ovrednotili njegovo delo in ga nato ponovno popravili oz. dopolnili. Za konec so učenci sestavili kviz (Slika 4) v Googlovih obrazcih, da so ponovili svoje znanje. Slika 7: Kviz oblikovan z aplikacijo Kahoot! 4. 3 Apel in čevljar Skupina učencev v vlogi učiteljev je od sošolcev zahtevala, da pesem preberejo tiho, nato jo je eden od sošolcev prebral glasno. Slika 4: Kviz Najprej so skupaj pregledali in razložili neznane besede. Nato so se razdelili po sobah in raziskovali, čemu je Prešeren pesem 4. 2 Turjaška Rozamunda napisal ter naredili zunanjo in notranjo analizo pesmi. Za domačo Prvo uro smo pesem prebrali in jo vsebinsko analizirali. nalogo so morali rešiti kviz, ki ga je skupina oblikovala v Prestavili smo se v čas srednjega veka, ko so bili gradovi in vitezi. Googlovih obrazcih (Slika 8), in se postaviti v vlogo pesnika Učenci, ki so bili v vlogi učiteljev, so svoje sošolce razdelili v Prešerna in Jerneju Kopitarju napisati pismo. skupine, se porazdelili po sobah in so reševali delovni list (Slika 5), ki so ga pripravili zanje in ga nato skupaj pregledali. Slika 5: Delovni list Slika 8: Kviz Skupina učencev je oblikovala tudi poustvarjalno nalogo. Izbrali 4. 4 Krst pri Savici so si pisanje domišljijskega spisa. Učenci so lahko izbirali med dvema naslovoma. Za pisanje so oblikovali tudi kriterije Pesnitev Krst pri Savici je obsežna lirsko-epska pesnitev. Pri uspešnosti. Slika 6 prikazuje navodila, ki so jih učenci prejeli v pouku obravnavamo samo Uvod, ki opisuje Valjhunovo spletni učilnici, kamor so tudi oddali svoj spis. Kasneje so spise obleganje Ajdovskega gradca, v katerega se je zatekel Črtomir s medvrstniško vrednotili in sošolcu podali povratno informacijo svojo vojsko, in končni boj med njima. Skupina teh učencev se glede na zastavljene kriterije uspešnosti. je odločila, da bodo prebrali celotno Prešernovo pesnitev in jo sošolcem predstavili s pomočjo stripa, ki so ga oblikovali v programu PowerPoint (Slika 9). Učenci so predstavitev popestrili z animacijami. Figure so se premikale. Vsaka drsnica je predstavljala delček zgodbe, s katero so obnovili celotno pesnitev Krst pri Savici. Učenci so nato skupaj analizirali pesem in oblikovali zapis v zvezek. Za domačo nalogo so se morali postaviti v vlogo Črtomirja in zapisati občutke, ki jih je čutil pred predajo. Pri pisanju so morali biti pozorni, da so pisali v prvi osebi ednine. Učenci so se razdelili v pare in vsak par je medvrstniško vrednotil zapis svojega sošolca in ga po potrebi izboljšal. Slika 6: Navodila za ustvarjalno pisanje 511 Učenci so se v vlogi učiteljev dobro znašli. Pri načrtovanju so jim bile v pomoč učiteljičine smernice. Vse skupine so oblikovale delovni list, s pomočjo katerega so učenci analizirali pesmi in različne aplikacije in programe, s katerimi so popestrili učno uro. Učenci so bili s svojimi dosežki zelo zadovoljni in so se veliko naučili, ko so samostojno raziskovali in sestavljali naloge za svoje sošolce. Priznali so, da je načrtovanje učnih ur zahtevno, da pa je bila to za njih pozitivna izkušnja, iz katere so pridobili določena znanja, ki jim bodo koristila pri nadaljnjem šolanju. Slika 9: Strip, oblikovan v programu PowerPoint LITERATURA IN VIRI [1] Ada Holcar Brunauer, 2017. Formativno spremljanje v podporo vsakemu 5 ZAKLJUČEK učencu, Vključujoča šola: Priročnik za učitelje in druge strokovne delavce, 4–17. Ljubljana: Zavod Republike Slovenije za šolstvo. V času epidemije in dela na daljavo smo se učitelji znašli pred [2] Formativno spremljanje pri matematiki: priročnik za učitelje. Ljubljana: novimi izzivi. Pri obravnavi učne snovi smo morali biti Zavod Republike Slovenije za šolstvo, 2018. [3] Vilma Brodnik. Formativno spremljanje in vrednotenje znanja in učenja. iznajdljivi. Vsakodnevno smo se srečevali z vprašanjem, na Dostopno na naslovu https://jazon.splet.arnes.si/formativno-spremljanje- kakšen način učno snov približati učencem, jih vključiti v in-vrednotenje-znanja-in-ucenja/#_ftn4 (10. 8. 2021) [4] Formativno spremljanje pri zgodovini: priročnik za učitelje. Ljubljana: načrtovanje pouka. V prispevku je predstavljen primer, ko so se Zavod Republike Slovenije za šolstvo, 2018. učenci postavili v vlogo učiteljev in njihova najpomembnejša naloga je bila, da pesem predstavijo in analizirajo tako, da bodo njihovi sošolci pri pouku aktivni in uporabijo sodobno tehnologijo. 512 Enotna digitalna identiteta ArnesAAI Unified online identity ArnesAAI Luka Kušar Arnes, Slovenija luka.kusar@arnes.si POVZETEK navigirati, da lahko uporablja različne storitve. Pri tem se uporabniki mnogokrat zatečejo k rešitvi, da za različne storitve S povečano digitalizacijo vsakdanjega življenja se vse bolj uporabljajo enaka uporabniška imena in gesla. Tak pristop je srečujemo s potrebo po enotni digitalni identiteti uporabnika. problematičen s stališča spletne varnosti, saj lahko spletni goljufi Ta mu omogoča, da dostopa do več različnih storitev z eno s pridobitvijo uporabnikovega uporabniškega imena in gesla tako samo identiteto, kar mu poenostavi in olajša uporabniško pridejo do dostopa do več storitev, ki jih uporablja posameznik, izkušnjo. Arnes ima za svoje uporabnike vzpostavljen sistem se tem pa se poveča tudi potencialna povzročena škoda. Veliko ArnesAAI, ki omogoča dostop do storitev zgolj z enim težav lahko reši enotna spletna identiteta, ki uporabniku bistveno uporabniškim imenom in geslom. izboljša uporabniško izkušnjo, pri tem pa tudi zagotavlja večjo KLJUČNE BESEDE spletno varnost. Enotna digitalna identiteta, Arnes, ArnesAAI, uporabnik, spletne storitve, uporabniška izkušnja, digitalizacija 2 KAJ JE SPLETNA IDENTITETA ABSTRACT Spletna identiteta posameznika je identiteta, ki jo posameznik ustvari ob uporabi spletnih storitev [1]. Večina spletnih storitev With the increase of digitalization in everyday life, the need for od uporabnika zahteva, da vsaj v nekakšni obliki ustvari neko a unified online identity has also increased. An unified online obliko spletne identitete, s katero ga nato prepozna kot identity allows the user to access multiple services with a single uporabnika storitve. Lahko je uporabna zgolj kot ključ za vpis za identity, which eases and simplifies the user experience. uporabo storitve, v nekaterih primerih, denimo pri uporabi ARNES provides its users the ArnesAAI system, which allows družbenih omrežji, pa je ta ustvarjena identiteta sama že del the user to access multiple services while using only one storitve. Prav tako je od namena uporabe odvisno, v kolikšni meri username and password. jo lahko uporabnik prilagaja svojim željam ali potrebam, KEYWORDS Nekatere storitve omogočajo kreiranje avatarjev v obliki grafične podobe, ki nato predstavlja uporabnika v spletnem okolju [1]. Unified digital identity, ARNES, ArnesAAI, user, online Uporabnik ima v večini primerov različne spletne identitete za services, user experience, digitalization različne storitve, med katerimi mora navigirati, če želi uporabljati storitve. 1 UVOD Trenutno obdobje pospešene digitalizacije vsakdanjega življenja 3 POTREBA PO ENOTNI DIGITALNI prinaša s seboj tudi določene težave pri prilagajanju posameznika IDENTITETI na nove oblike uporabe spletnih storitev. Kljub temu, da naj bi Določen del uporabe spleta bo vedno vezan na to, da bo lahko uporabniku digitalizacija prihranila čas in olajšala življenje, se posameznik med uporabo ostal anonimen. Namen enotne pogosto znajde v situacijah, ko mu predvsem neprijazna digitalne identitete ni želja po vzpostavljanju mreže nadzora nad uporabniška izkušnja onemogoča učinkovito uporabo storitev, uporabo spleta, temveč olajšati uporabniku njegovo izkušnjo pri tem pa ga posledično tudi odvrača od nadaljnje uporabe predvsem pri storitvah, ki zahtevajo, da je njegova identiteta drugih digitalnih storitev. Pogosta težava je veliko število istovetna z identiteto iz vsakdanjega življenja. Večina uporabniških imen in gesel, saj v večini primerov vsaka uporabnikovih spletnih identitet je vezana na kontekst uporabe. posamezna storitev zahteva ustvarjanje specifične spletne Z drugimi besedami, informacije o identiteti uporabnika so nujne identitete, ki uporabniku omogoča dostop do same storitve. Tako za ponudnika, da lahko uporabniku omogoči dostop do se mu hitro nabere veliko število identitet, med katerimi mora zahtevanih vsebin ali storitev [2]. Določene storitve že omogočajo vsaj delno povezavnje 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 identitet. Tak primer je denimo Google, ki integrira for profit or commercial advantage and that copies bear this notice and the full uporabnikove Youtube, Gmail, Google drive in druge račune [1]. 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). Ta možnost sicer uporabniku vsaj nekoliko izboljša uporabniško Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia izkušnjo, vendar pa ne določi indentifikacijskih parametrov © 2021 Copyright held by the owner/author(s). dovolj natančno, da bi bila uporabna za bolj občutljive storitve, 513 kjer je nujno vzpostaviti posameznikovo istovetnost z resničnimi eduroam, ki je prisoten na veliki večini evropskih izobraževalnih podatki. ustavnov [6]. Identiteta je tako uporabna tudi v tujini, vezana je Identiteta posameznika je bistvena predvsem v kontekstu na izobraževalno ustanovo, ki zagotavlja, da bo uprabnik lahko s njegove interakcije z državnimi službami in storitvami, kot so to identiteto koristil določene storitve tudi v organizacijah, ki jim zdravstvo, finance, davki, volitve, izobraževanje [3]. ne pripada, ampak so del iste mreže. V vsakdanjem življenju je najbolj legitimen porok za Končni uporabniki tako pridobijo identiteto, ki jim omogoča posameznikovo identiteto država. Ta z izdajo dokumentov, kot dostop do večih storitev z enotnim vpisnim procesom. Poleg že so rojstni list, osebna izkaznica, poročni list, mrtvaški list, potni omenjenih prednosti, je na nivoju posameznika potrebno list garantira za istovetnost osebe s tisto, ki je na dokumentu. Te izposatviti še dejstvo, da v primeru izgube ali zlorabe dokumenti se uporabljajo za potrjevanje identetitete tako na uporabniških podatkov te težave rešuje neposredno pri domači državnem nivoju, kot na zasebnem, denimo z izkazovanjem organizaciji [6]. V primeru težave tako točno ve, na koga se državno izdane osebne izkaznice za potrebe identifikacije na obrniti, prav tako pa ima organizacija vsa orodja, da mu lahko v banki [3]. takšen primeru pomaga. Kot že omenjeno, si spletne identitete v veliki meri ustvarja Upravljalci aplikacij in ponudniki spletnih storitev lahko prav posameznik sam prek raznih storitev, izdajajo pa jih ponudniki tako koristijo ArnesAAI in s tem povečajo doseg svojih storitev, le-teh. Posledično v večini primerov nimajo enake kredibilnosti saj s priključitvijo posanejo član sveta ArnesAAI. Prav tako se kot denimo državno izdani dokumenti. Prav tako pa se pri na ta način ponudniki storitev izognejo ustvarjanju identitet digitalnih identitetah srečamo še s problemom kraje identitetite, uporabnikov, saj jih ti pridobijo že na svoji domači organizaciji ki je bistveno lažja kot v nedigitalnem svetu. Tu se srečamo s [6]. paradoksom, ko so najbolj napredne in varne digitalne identitete ArnesAAI tako olajša uporabo storitev uporabnikom, tiste, ki lahko povzročijo posamezniku največ škode, če pridejo ponudnikom storitev in organizacijam pa omogoča, da enostavno v napačne roke. Dostop do elektronskega potnega list v rokah in varno upravljajo z digitalno identiteto uporabnika. nepridiprava bo lahko bistveno bolj prizadel posameznika kot ukradena osebna izkaznica. Težava je predvsem v neravnovevesju pri zaupanju digitalnim referencam. Več kot je 5 POVEČANA UPORABA STORITEV MED varnostnih preverb atributov identitete, do več občutljivih EPIDEMIJO COVID-19 podatkov lahko dostopamo. Nagrada za uspešen napad na Ob začetku epidemije COVID-19 in posledičnem zaprtju šol ter kompleksno digtalno identiteto je tako bistveno večja, kot za vzpostavitve pouka na daljavo se je Arnes soočil s skokovitim napad na šibko [4]. porastom uporabe svojih storitev. Za uspešno izvedbo pouka na daljavo ne zadošča zgolj ena spletna storitev, temveč je potrebno 4 ARNESAAI imeti dostop do različnih orodij, kot so denimo videokonferenčni sistemi, spletne učilnice, elektronska pošta…Uporaba Arnesovih Arnes AAI je primer enotne digitalne identitete na področju storitev se je v tem obdobju povečala za 10 do 100 krat[7]. izobraževanja. Sistem omogoča uporabo enega uporabniškega Arnes se je na situacijo odzval z razširitvijo zmogljivosti računa za dostop do različnih storitev v slovenskem ter svojih strežnikov, nadgrajevanjem ključnih storitev in širitvijo evropskem izobraževalnem in raziskovalnem okolju [5]. funkcionalnosti. Pri tem se je sledilo izraženim potrebam Uporabnik tako za uporabljanje vseh Arnesovih storitev učiteljev, uredilo se je denimo integracijo videokonferenčnih potrebuje zgolj eno uporabniško ime in geslo, s katerim nato storitev v spletne učilnice in nakupilo licence sistema Zoom za dostopa denimo do elektronske pošte, video portala, spletnih potrebe izobraževanja [7]. učilnic, videokonferečnih orodij… Ključno vlogo pri uspešnem in gladkem delovanju celotnega ArnesAAI omogoča pridruženim organizacijam, da same sistema je odigral ArnesAAI. Šole so lahko ažurno dodeljevale dodeljujejo svojim članom uporabniško ime za dostop do in vzdrževale digitalne identitete za potrebe svojih učencev [7]. različnih aplikacij, S tem vsaka organizacija postane varuh Tako je lahko šola sama svojemu učencu uredila elektronski osebnih podatkov svojih članov, ponudnikom aplikacij pa se ni naslov in digitalno identiteto, s katero je nato enostavno dostopal potrebno ukvarjati z dodeljevanjem uporabniških imen in do vseh potrebnih storitev, ki jih je potreboval za sodelovanje pri kočljivim zbiranjem ter preverjanjem podatkov o uporabnikih pouku na daljavo. Posebno pri mlajših učencih bi lahko prihajalo [5]. Legitimnost identitete tako zagotavlja dejstvo, da je potrebno do večjih težav, če bi bi denimo potrebovali digitalno identiteto za dostop do ArnesAAI računa potrebno zadostovati pogojem za za vsako posamezno storitev. Z ArnesAAI so tako potrebovali uporabo Arnesovih storitev, torej si je ne more ustvariti kdorkoli, samo eno uporabniško ime in pripadajoče geslo, da so lahko temveč je dodeljena na podlagi upravičenosti. dostopali do željenih orodij. ArnesAAI se uporablja na nivoju organizacij, končnih Organizacije so lahko preko ArnesAAI same urejale potrebne uporabnikov in upravljacev storitev. identitete, ki so jih za delo s spletnimi orodji potrebovali Organizacije s priključitvijo v ArnesAAI omogočajo dostop učenci.To je pomenilo, da se jim ni bilo potrebno ukvarjati s do pridruženih storitev vsem svojim uporabnikom. Tako tretjimi osebami, ki bi urejale to področje, temveč so imele v omogočijo., da vsi njeni uporabniki lahko dostopajo do rokah vse potrebno, da samostojno zagotovijo in uredijo Arnesovih in ostalih storitev z enim uporabniški imenom in potrebne identitiete za svoje učence. Prav tako so jim lahko v geslom. Organizacija prav tako poskrbi za boljše varovanje primeru težav pomagale same, brez da bi potrebovale zunanjo osebnih podatkov, saj se obdelava izvaja na sami organizaciji in pomoč. ne pri ponudniku spletnih storitev. Iste identitete se lahko Enako kot za učence so lahko organizacije same uredile uporabijo tudi za dodeljevanje dostopa do brezžičnega omrežja digitalne identiete za učitelje. Z uporabo ArnesAAI je tako šola 514 v primeru pouka na daljavo sama postala samozadostna pri 7 ZAKLJUČEK urejanju in dodeljevanju digitalnih identitet, ki so omogočale Potreba po vsaj nekakšni enotni digitalni identiteti bo s povečano dostop do storitev, potrebnih za takšno vrsto izobraževanja. digitalizacijo storitev s časoma postala nuja. ArnesAAI trenunto omogoča vsaj za del izobraževalnih procesov obliko takšne 6 NADALJNJE MOŽNOSTI RABE identitete. Uporabnik tako potrebuje samo eno geslo in ARNESAAI uporabniško ime za uporabo storitev, organizacije lahko same izdajajo, upravlajajo in nudijo pomoč uporabnikom v zvezi z Poleg najbolj očitnih prednosti ArnesAAI, ki so na strani njegovo digitalno identiteto. ponudiki storitev pa se lahko uporabnikov uporaba enega uporabniškega imena in gesla za vključijo v poenoten sistem prijave in dostopov. Prednosti dostop do več storitev, ter na strani organizacij možnost ArnesAAI so se pokazale predvsem med epidemijo COVID-19, samostojnega upravljanja in dodeljevalna enotnih digitalnih ko je bilo ključnega pomena za šole, da so lahko same identitet, ostajajo še neizkoriščeni potenciali rabe. dodeljevale in vzdrževale digitalne identitete, ki so učencem in Trenutno so dodeljene digitalne identiete prek ArnesAAI učiteljem omogočale dostop do potrebnih spletnih storitev za vezane na pripadnost določeni organizaciji, ki je opravičena do izvajanje pouka na daljavo. V primeru vzpostavitve enotne Arnesovih storitev. To omogoča, da je organizacija digitalne identitete za celoten process izobraževanja samozadostna pri ustvarjanju in upravljanju identitete. Pri posameznika, je ArnesAAI odlično izhodišče za ustvarjanje razvijanju enotne digitalne identitete posameznika na področju legitimne, enostavne in varne enotne digitalne idenitete. izobražavanja bi bilo smiselno delovati v smeri, ki bi posamezniku omogočila, da isto identiteto obdrži skozi celoten čas vključenosti v izobraževalni sistem. Uporabnik sedaj ob 8 VIRI zaključku izobraževanja v eni ustanovi in prehodu v drugo [1] Creating a unified online identity to provide a single seamless presence on zamenja svoj ArnesAAI račun, saj je ta vezan na šolo, ki jo the internet. Patkeshwar, Apruva; Prasad, Kushan Kunal; Dhruv, Suri; obiskuje. Tako mora denimo učenec ob prehodu iz osnovne šole Shankarmani, Dr .Radha. Dostopno prek: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.736.72&rep=r v srednjo pridobiti na novi organizaciji novo digitalno identiteto. ep1&type=pdf#page=824/ (10.8.2021) V kolikor bi lahko svojo digitalno identiteto zgolj prenesel na [2] Unified Identity Management. Ozlak, Tom Dostopno prek: novo organizacijo, bi tako ohranil isto identiteto, ki bi še http://www.infosecwriters.com/text_resources/pdf/Unified_Identity_Man agement_TOlzak.pdf (10.8.2021) pridobila na pomenu. Idealno bi lahko posameznik z njo urejal [3] Government services and digital indentity. Dr. Third, Allan; Dr. Quick, tudi stvari, kot so denimo vpis na srednjo šolo in fakulteto, dostop Kevin; Bachler, Michelle, Prof. Domingue, John. Dostopno prek: https://www.eublockchainforum.eu/sites/default/files/research- do spletnega referata in druge storitve, za katere mora trenutno paper/20180801_government_services_and_digital_identity.pdf uprabljati različne digitalne identitete. (10.8.2021) [4] Identity management. Concepts, Technologies and Systems Bertino, Elisa; Enotna digitalna identiteta za področje izobraževanja bi zelo Tkahashi, Kenji. Dostopno prek pripomogla k splošni uspešnosti digitalizacije področja. https://books.google.si/books?hl=sl&lr=&id=UrmD-Gxt- Uporabniku bi se poenostavil dostop do vseh storitev, ki jih 8IC&oi=fnd&pg=PA5&dq=unified+digital+identity&ots=joNCux07tR& sig=1aCoHdmsjWrtYcPjivc3mcW65EQ&redir_esc=y#v=onepage&q=di potrebuje, organizacije pa bi imele enoten sistem obdelave in gital%20identity&f=false (11.8.2021) upravljanja identitet. Arnes AAI ima potrebne karakteristike, da [5] Opis storitve ArnesAII Arnes. Dostopno prek: https://arnes.splet.arnes.si/storitve/arnesaai/ (11.8.2021) zagotovi uspešnost takšnega pristopa, izkušnje pa kažejo, da [6] ArnesAAI.Arnes. Dostopno prek https://aai.arnes.si/ (11.8.2021) njegova uporaba organizacijam zelo poenostavlja delo. [7] Podpora Arnesa izobraževanju na daljavo. Dolenc, Tomi. Dostopno prek https://arnes.splet.arnes.si/podpora-arnesa-izobrazevanju-na-daljavo- tomi-dolenc/ (12.8.2021) [8] Izobraževanje. Arnes. Dostopno prek: http://arnes.splet.arnes.si/izobrazevanje/ (24.8.2020) 515 Analiza podatkov orodja za pomoč pri izbiri poklica »KamBi« Data Analysis of Support Tool to Choose a profession “KamBi” Robert Leskovar, Alenka Baggia Univerza v Mariboru, Fakulteta za organizacijske vede Kranj, Slovenija robert.leskovar@um.si, alenka.baggia@um.si POVZETEK KLJUČNE BESEDE V prispevku so sistematično analizirani podatki, ki so del orodja »KamBi«. To orodje je namenjeno dijakom zaključnih letnikov Podatkovna analitika, razvoj kariere, aplikacija KamBi za pomoč pri izbiri bodočega poklica oz. študijskega programa. ABSTRACT Spletna aplikacija »KamBi« je dostopna od konca decembra 2020 dalje, uporablja pa 10 relacijskih tabel in deluje na The article analyses the data that are part of the tool "KamBi". platformi Oracle Apex. Te tabele popisujejo anketna vprašanja The tool aims to help final year middle school students in (78), področja kompetenc (26, to so osebnostne lastnosti, ki jih choosing a study program for future profession. The KamBi web meri več vprašanj), odgovore anketirancev (136500), poklice application has been available since the end of December 2020. (23) z njihovimi zahtevanimi lastnostmi (207) in možnimi It uses 10 relational tables and runs on the Oracle Apex platform. izobraževalnimi ustanovami (37) in poklicna priporočila These tables describe the survey questions (78), the areas of anketirancem (1750) za katerikoli poklic v bazi. Namen competence (26, personality traits measured by several prispevka je obravnava treh sklopov podatkov: lastnosti questions), the answers of the respondents (136500), the (samoocene) anketirancev, lastnosti ankete in lastnosti poklicev. occupations (23) with their required characteristics (207) and Med samoocenami anketirancev prevladujejo take, ki izražajo possible educational institutions (37) as well as occupational pozitivne lastnosti in pogostejše pozitivno obnašanje. Vprašanja recommendations to respondents (1750) for any occupation in z binarnim tipom odgovora (ne-da, 39 vprašanj) so anketiranci the database. The purpose of the paper is to analyse three subsets reševali hitreje kot vprašanja s pet stopenjsko Likertovo letvico of data: characteristics (self-assessment) of respondents, (39 vprašanj). Poprečen čas za odgovor je bil 3.41 sekunde z characteristics of the survey and characteristics of occupations. odklonom 2.67 (pri 99% odgovorov; n=135137; 0 >= t > 24 s). Respondents' self-assessment that indicate positive traits and Med odgovori in področji so šibke, statistično neznačilne more frequent positive behaviours predominate. Questions with povezave. Preverjanje konsistentnosti vprašalnika (interna a binary type of answer (no-yes, 39 questions) were solved faster veljavnost) je za skupine vprašanj Likertovega tipa pokazalo than questions with a five-point Likert scale (39 questions). The dobro konsistentnost za 3 področja, sprejemljivo za 3 področja, mean response time was 3.41 seconds with a deviation of 2.67 vprašljivo za 5 področij ter šibka za 2 področji. Konsistentnost je (at 99% of responses; n = 135137; 0> = t> 24 s). There are weak, bila izračunana tudi za področja narave dela, ki temeljijo na statistically insignificant correlations among responses and areas vprašanjih binarnega tipa. Pri teh so izračunani koeficienti of competence. Checking the consistency of the questionnaire (Crombachov alfa) primerljivi le med seboj. Poklice v bazi (internal validity) for a groups of Likert type questions showed podatkov smo klasificirali v gruče podobnih glede na lastnosti, good consistency for 3 areas, acceptable for 3 areas, questionable ki so jih izobraževalne inštitucije le-tem določile. Optimalno for 5 areas and weak for 2 areas. Consistency was also calculated število gruč je bilo 3, preskus z drugačnim številom (2-7) pa je for areas based on binary-type questions. These coefficients podaja informacijo o stabilni pripadnosti poklica gruči ter (Crombach’s alpha) are comparable only to among the binary- diferenciaciji med poklici. Rezultati analize so koristni za type groups. The professions in the database were classified into anketirance, za pripravljavce ankete in za sodelujoče clusters according to the similarity of characteristics assigned by izobraževalne inštitucije. educational institutions. The optimal number of clusters was 3. The test with a different number (2-7) provides information on the stable affiliation of the profession and the differentiation between professions. The results of the analysis can be utilised by respondents, survey creators and participating educational institutions. 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 KEYWORDS citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Data analytics, career development, KamBi application Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 516 1 UVOD 2 KRATEK PREGLED LITERATURE O Po zaključenem srednješolskem izobraževanju so dijaki postav- KARIERNEM RAZVOJU ljeni pred odločitev, ki vplivajo ne le na njihov karierni razvoj, S problem izbire pravega poklica se literatura ukvarja že zelo pač pa tudi na gospodarski razvoj okolja. Večina dijakov zadnjih dolgo. Frank Parsons [2] je postavil temelje poklicnega usmerja- letnikov srednjih šol še ni dovolj jasno poklicno profilirana, kar nja, ko je predlagal, da se zgradi seznam osebnih lastnosti posa- je lahko posledica šibkega zavedanja o svojih dejanskih sposob- meznika, seznam zahtev delovnega mesta, nato pa se izmeri skla- nostih in potencialih (vključno s precenjevanjem ali podcenjeva- dnost lastnosti posameznika z zahtevami delovnega mesta. Ger- njem), pomanjkanja realnih informacij o svojem bodočem po- meijs in Verschueren [3] sta ugotovila, da je nevroticizem v za- klicu, izkušenj v realnem delovnem okolju pa tudi osebnostnih ključnem letniku srednje šole najbolj povezan z neodločenostjo lastnosti. glede poklicne usmeritve. Ne glede na široko paleto izbire med Aplikacija KamBi je uradno zaživela 23. decembra 2020. Na- visokošolskimi institucijami, dijaki težko opredelijo, kaj jih de- menjena je dijakom zaključnih letnikov kot pomoč pri izbiri po- jansko veseli in kaj bi bilo primerno zanje [4]. Ne glede na po- klica oz. študijskega programa, ki najpogosteje vodi do določe- manjkanje inženirskega kadra v zahodnem svetu, se pogosto do- nega poklica [1]. Nastala je kot skupni projekt več podjetij, za- gaja, da dijaki zaradi obetov po dobri zaposlitvi, inženirski poklic vodov in izobraževalnih ustanov. Pri posameznih sklopih so so- izberejo iz napačnih razlogov: ker so tovrstne izobraževalne usta- delovali: nove boljše, ker študij odpira vrata in omogoča, da odločitve pre- • izdelava vprašalnika: podjetje Competo, Karierni center stavimo na kasnejši čas, ker niso vedeli, kaj izbrati in kje se želijo Univerze v Ljubljani, Zavod za zaposlovanje Republike Slove- zaposliti [5]. Po drugi strani pa raziskava med Belgijskimi štu- nije denti kaže, da so interesi študentov tehničnih ved veliko bolj • izdelava profilov diplomantov: Fakulteta za elektrotehniko usklajeni z njihovim študijskim programom, kot pa interesi štu- (UL), Fakulteta za elektrotehniko, računalništvo in informatiko dentov ne-tehničnih ved [6]. Dijaki si pod poklicem inženirja (UM), Fakulteta za farmacijo (UL), Fakulteta za gradbeništvo in predstavljajo različne stereotipe, na primer mehanika, tehnika v geodezijo (UL), Fakulteta za gradbeništvo, prometno inženirstvo proizvodnji, ki je praviloma moškega spola [7]. Prav zato je po- in arhitekturo (UM), Fakulteta za kemijo in kemijsko tehnologijo moč pri odločitvi za tovrstne poklice ključnega pomena. Visoko- (UL), Fakulteta za kemijo in kemijsko tehnologijo (UM), Fakul- šolske institucije lahko dijakom pomagajo pri sprejemanju odlo- teta za matematiko in fiziko (UL), Fakulteta za matematiko, na- čitev o njihovi poklicni karieri v današnjem poklicnem okolju, ki ravoslovje in informacijske tehnologije (UP), Fakulteta za nara- je nestanovitno, negotovo in zapleteno. voslovje in matematiko (UM), Fakulteta za organizacijske vede Aplikacija KamBi je nastala z namenom mladim približati in- (UM), Fakulteta za pomorstvo in promet (UL), Fakulteta za raču- ženirske poklice [1]. S pomočjo aplikacije mladi z izrisom profila nalništvo in informatiko (UL), Fakulteta za strojništvo (UL), Fa- ujemanja pridobijo dodatne informacije o svojih kompetencah in kulteta za strojništvo (UM), Fizika in astrofizika (UNG), Gospo- poklicih ter se na ta način lažje odločijo za katerega od inženir- darski inženiring (UNG), Naravoslovnotehniška fakulteta (UL), skih poklicev. Šolski center Kranj, Šolski center za pošto, ekonomijo in teleko- munikacije Ljubljana in Zdravstvena fakulteta (UL). Višješolski in visokošolski zavodi so zahtevane lastnosti za »svoj« poklic 3 METODOLOGIJA določili sami. • izdelava aplikacije: prototip Fakulteta za organizacijske vede Spletno anketo v aplikaciji KamBi je v obdobju od konca decem- (UM), končna verzija 1.5 podjetje The Right Thing Solutions. bra 2020 do sredine junija 2021 anonimno izpolnilo 1750 anke- • gostovanje na spletu: Oracle, Oracle Slovenija in Fakulteta tirancev v zaključnem letniku srednjih šol širom Slovenije. Vsak za organizacijske vede (UM) udeleženec je na osnovi svojih odgovorov dobil priporočilo za • vodenje projekta: podjetje Mediade. izbiro enega od 23 definiranih inženirskih poklicev. Kandidati V prispevku predstavljamo analizo podatkov, ki so nastali pred lahko do svojih rezultatov dostopajo izključno z žetonom (39 lansiranjem spletne ankete (vprašanja, struktura vprašanj, podro- mestna unikatna številka), ki se izpiše ob prikazu rezultatov o čja vprašalnika, poklici, zahtevane lastnosti poklicev) kot tudi primernosti za poklice, vnesene v bazo podatkov. zbrane anketne podatke (odgovori na vprašanja) do sredine junija V oblačni storitvi Oracle Application Express (APEX) se na- 2021. Za posameznika, ki je sodeloval v anketi je sicer najpo- haja delovni prostor z baza podatkov in aplikacijo KamBi. V bazi membnejši del aplikacije poročilo o skladnosti njegovih samoo- podatkov je 10 relacijskih tabel, ki povezujejo: a) anketna vpra- cen ter zahtevanih lastnosti pri posameznem poklicu. Na ta način šanja s predlogama odgovorov (binarni tip, Likertov tip), ter po- smo dijake želeli spodbuditi k razmisleku možnih kariernih poteh, dročjem, ki mu vprašanje pripada, b) anketiranca (kandidata) z predvsem o inženirskih poklicih. Analiza podatkov za aplikacijo njegovimi odgovori, izračunom skladnosti s poklici ter c) poklice KamBi lahko koristi izobraževalnim inštitucijam pri izostritvi z zahtevanimi lastnosti na področjih in izobraževalnimi ustano- lastnosti, ki jih določeni poklici zahtevajo, prav tako pa lahko vami (slika 1). prispevajo k spremembam študijskih vsebin. Ker pri vsaki meri- tvi nastopajo odstopanja od resničnih vrednosti, je smiselno pre- gledati tudi trenutno stanje merskega inštrumenta – ankete. Zato bomo v glavnem delu raziskave predstavili te tri sklope analize podatkov: lastnosti (samoocene) anketirancev, lastnosti ankete in lastnosti poklicev. 517 odgovorov (na posamezna vprašanja ali področja) in kako gruče smiselno poimenovati? • Kakšna je interna zanesljivost (konsistentnost) vprašalnika, če kot mero uporabimo koeficient Cronbachov alfa in vrednotimo področja, za katere je bil uporabljen Likertov tip vprašanj ter področja, ki jih opredeljujejo vprašanja binarnega tipa. • Kako so fakultete določile zahtevane lastnosti za poklice in kakšne gruče podobnih poklicev so tako nastale? V jeziku R (verzija 4.01) in vmesniku RStudio [9] smo za iz- vedbo analize uporabili razne knjižnice kot so rJava, RJDBC, sqldf, ggplot2, Rfast, psych, plyr, descr, Hmisc, corrplot, RCo- lorBrewer, fitdistrplus, cluster, factoextra, vtree, DescTools, Slika 1. Struktura baze podatkov magrittr in knittr. S temi knjižnicami je bilo možno: dostopati do baze podatkov, izdelati in izvesti poizvedbe v SQL, izdelati opi- V bazi podatkov je tako shranjenih 78 vprašanj na 26 podro- sno statistika, proučiti prileganje teoretičnih distribucijam, izve- čjih, ki skupaj opredeljujejo 23 poklicev z 207 značilnostmi. sti analizo gruč ter prikazati rezultate v tekstovni in grafični Vseh 1750 anket je bilo v celoti izpolnjeno, saj aplikacija ne shra- obliki. njuje nepopolno izpolnjenih anket. Primer enega vprašanja binar- nega tipa prikazuje slika 2, primer vprašanja Likertovega tipa pa slika 3. 4 REZULTATI 4.1 Odgovori anketirancev Z jezikom R smo izdelali opisno statistiko in izrisali histograme za vseh 78 vprašanj. Del izpisa prikazuje slika 4. Slika 2. Primer vprašanja binarnega tipa v aplikaciji Slika 4. Histogrami odgovorov (izsek). KamBi. Za ta prispevek bi bilo navajanje opisne statistike in histogra- mov za vseh 78 vprašanj in 26 področij preobsežno, zato je na sliki 5 prikaz histogramov odgovorov na vprašanja binarnega tipa in vprašanja Likertovega tipa. Slika 3 Primer vprašanja Likertovega tipa v aplikaciji KamBi. V tej analizi smo uporabili jezik R [8] in vmesnik RStudio [9]. Na enak način, kot poteka logika preračunavanja v aplikaciji Slika 5. Histogram odgovorov na vprašanja binarnega in KamBi smo tudi v skripti jezika R besedne odgovore pretvorili v Likertovega tipa. numerične vrednosti: »ne« v 0, »redko« v 0,25, »včasih ne, vča- sih da« v 0.5, »najpogosteje« v 0.75 ter »da« in »vedno« v 1. Med prvimi 39 vprašanji je odgovor DA pogostejši, razen pri Zastavili smo si naslednje sklope raziskovalnih vprašanj: vprašanjih: 3. Zanimajo me raziskave s področja varovanja oko- • Kako so anketiranci odgovarjali na posamezna vprašanja in lja; 28. Sem ’geek’; 38. Čas raje preživljam notri in 39. Nekoč na področja vprašanj? Koliko časa so porabili za posamezna bom imel svoj laboratorij. Med vprašanji 40 do 78 prevladujejo vprašanja, koliko za celoten vprašalnik? Kako so časi odgovori, ki nakazujejo pogostejše pozitivno ravnanje. Najmanj porazdeljeni? Kolikšno je optimalno število gruč podobnih 518 pogosto ravnanje (𝑥𝑥 = 0,66) je pri vprašanjih: 40. Pri delu si do- Pri porazdelitvi časov smo ugotovili, da aproksimacija s Po- ločim cilj in sestavim načrt, kako ga bom dosegel in 65. Nimam issonovo ali negativno binomsko porazdelitvijo ni ustrezna. težav s spoznavanjem novih ljudi. Pri vprašanju 62. Spodbujam Analizo gruč smo najprej izvedli na vprašanjih Likertovega tipa, pozitivno vzdušje in dobre odnose je bilo najvišje poprečje (𝑥𝑥 = nato pa zaradi prekrivanja iz podatkov odstranili ankete z vre- 0,84 . Korelacijska analiza je pokazala, da so tako odgovori kot dnostmi časov reševanja manj kot 214 s (1. kvaril) ter več kot tudi področja šibko povezani, pri čemer niti ena povezava ni sta- 359 s (3. kvartil). Na obeh množicah podatkov (vse ankete, pre- tistično pomembna na nivoju tveganja 𝑝𝑝 = 0.01. čiščene ankete) smo tako odgovorih kot pri področjih ugotovili, Čas, ki so ga anketiranci porabili za posamezen odgovor in ce- da je optimalno število gruč 2. Gruči po vprašanjih in področjih lotno anketo je izraženo v sekundah. Na sliki 6 je prikazan izsek se razlikujeta za manj kot 5 %. Slika 9 prikazuje gruči očiščenih izpisa le za tri vprašanja (𝑛𝑛 = 1750). podatkov po 39 vprašanjih Likertovega tipa. Samo gručanje seveda še ne more dati natančnejšega opisnega imenovanja gruč, saj je naloga algoritma zgolj zmanjšanje števila dimenzij – v našem primeru 39 dimenzij (vprašanj) reduciramo na dve (koordinati x in y). Zato smo izbrali tri vprašanja binar- nega tipa, za katere smo menili, da so dobri kandidati za razliko- vanje tehnično usmerjenih od družboslovno usmerjenih: 33. V roke rad vzamem orodje in stvari naredim sam. 31. Zanima me, Slika 6. Porazdelitev porabljenega časa za odgovore (izsek). kako stvari delujejo in 29. Vse funkcije na računalniku in tele- fonu dobro poznam. Na sliki 10 je prikazano drevo gruče tehni- Posamezni odgovori so trajali od 0 do 6872s, (𝑥𝑥 = kov (1) in gruče družboslovcev (2) pri prej navedenih vprašanjih. 4,47𝑠𝑠, 𝑆𝑆𝑆𝑆 = 47,24), če pa postavimo mejo na 99. percentil (0 ≤ Med 545 člani skupine rdečih (pogojno tehniki) jih je trikrat od- 𝑡𝑡 ≤ 24) je𝑥𝑥 = 3,41𝑠𝑠, 𝑆𝑆𝑆𝑆 = 2,67. Mediana časa za odgovor na govorilo pozitivno 186, dvakrat pa 211 (seštevek več vej), med vprašanje 40. Pri delu si določim cilj in sestavim načrt, kako ga 328 člani skupine turkiznih (pogojno družboslovci) pa jih je tri- bom dosegel je med vsemi vprašanji najvišja (6𝑠𝑠), ker je to prvo krat pozitivno odgovorilo 84, dvakrat pa 56 (seštevek več vej). vprašanje z drugačnim tipom odgovora. Skupni časi reševanja ta- Deleža vsaj dveh pozitivnih odgovorov sta 71 % in 29 %, kar kih anket so v intervalu od 356.58𝑠𝑠 do 7078𝑠𝑠. Na sliki 7 je pri- kaže na podobno situacijo kot pri neprečiščenih odgovorih. Skle- kazana frekvenca in gostota porazdelitve skupnih časov reševa- pamo, da ta tri izbrana vprašanja binarnega tipa vendarle izražajo nja ankete. Vrednosti skupnih časov, ki so manjše od 100 sekund razliko med skupino tehnično usmerjenih in družboslovno zagotovo nakazujejo, da je okoli 5 % anketirancev zelo hitelo s usmerjenih in smo zato rdeče obarvano večjo gručo utemeljeno klikanjem. Izsek izračuna opisne statistike po področjih je pred- imenovali tehniki, turkizno obarvano manjšo gručo pa družbo- stavljen na sliki 8. pri tem je potrebno upoštevati, da je 22 po- slovci. dročij agregat 3 vprašanj (po dve področji sta opredeljeni z Moč definiranih gruč v realnosti pa je glede na večletne po- dvema oziroma štirimi vprašanji). Najvišjo srednjo vrednost pri datke o vpisih in diplomantih na slovenskih visokošolskih usta- agregatih s tremi vprašanji je doseglo področje Delo z ljudmi, nova obratno. Po uradnih podatkih je bilo v letu 2015 34 % di- največjo varianco pa področje Uporaba orodij. plomantov družboslovnih študijev, 16 % tehniških programov in 9 % naravoslovnih programov. Tudi ob upoštevanju seštevka tehnikov in naravoslovcev imamo v Sloveniji prevladujoč delež družboslovcev. To odpira nova vprašanja kot so: 1. Ali so anketo večinsko izpolnjevali dijaki, ki jih bolj zanimajo tehniški, inženirski poklici (anketo je promovirala iniciativa Inženirji bomo), družboslovno usmerjeni pa so jo ignorirali? Če da, zakaj? 2. Ali dijaki kljub samooceni, ki kaže tehniško orientiranost, v procesu odločanja izberejo družboslovni študij? Če da, zakaj? 3. Ali nekateri študijski programi, ki so uradno deklarirani kot Slika 7. Frekvenca in gostota porazdelitve skupnih časov re- družboslovni, vendarle obsegajo določen delež tehniških ševanja ankete. vsebin, niso pa klasificirani v popolnoma ustrezne uradne predalčke? Če da, zakaj? Prvi dve vprašanji sta vredni dodatnih raziskav, pri zadnjem pa je odgovor povezan z obsegom proračunskega financiranja viso- kega šolstva. Slika 9. Izračun opisne statistike po področjih (izsek). 519 Na sliki 11 je prikaz koeficienta Cronbach alfa po področjih, ki jih opredeljujejo vprašanja Likertovega tipa. Slika 9. Gručanje očiščenih podatkov po 39 vprašanjih Li- kertovega tipa. Slika 11. Cronbach alfa po področjih, ki jih opredeljujejo vprašanja Likertovega tipa. Preverjanje konsistentnosti vprašalnika je za skupino vprašanj s področja kompetenc pokazalo, da je konsistentnost dobra za 3 področja ( sprejemanje odločitev, čustvena inteligenca in vode- nje), sprejemljiva za 3 področja ( odnos do okolja, delo v zaprtem prostoru, razgiban delovnik ) vprašljiva za 5 področij ( medse- bojne spretnosti, delo z ljudmi, razvoj novih izdelkov, upravljanje s stresom, uporaba orodij ) ter šibka za 2 področji ( komunikacij- ske spretnosti, načrtovanje in organizacija). Vprašanja s podro- čja narave dela so binarnega tipa, zato so izračunani koeficienti (Crombach alfa) primerljivi le med seboj, ne pa s skupino vpra- šanj Likertovega tipa. Najvišjo konsistentnost dosegajo področja ciljna usmerjenost, uporaba tehnologije, zanesljivost in samo- stojno delo vendar z referenčno oceno vprašljivo, sledi delo v timu (referenčna ocena šibko) in nato analitične sposobnosti, tim- sko delo, delo na terenu, inovativnost, reševanje problemov, na- tančnost, prodaja in odnos do stranke z referenčno oceno nespre- jemljiv. Pri vseh izračunih je bil upoštevan 95 % interval zaupa- nja. 4.3 Gruče poklicev glede na zahtevane lastnosti Slika 10. Drevo gruče tehnikov (1) in gruče družboslovcev visokošolskih inštitucij (2) pri vprašanjih 33, 31 in 29. Določitev zahtevanih lastnosti v veliki meri vpliva na priporočilo o najustreznejšem poklicu. Vsaka visokošolska inštitucija je do- 4.2 Interna zanesljivost vprašalnika ločila tiste lastnosti, ki jih pričakuje od svojih diplomantov. Interno zanesljivost vprašalnika smo preverili s koeficientom, ki Skupno je bilo na voljo 26 lastnosti, od katerih se je polovica se imenuje Cronbachov alfa: v števcu je zmnožek števila pojavov nanašala na naravo delo, polovica pa na kompetence. V bazi so ter poprečne kovariance (ta podaja samo smer povezave med pari bile pripravljene lastnosti za 23 poklicev. Na sliki 12 je prikazano spremenljivk) v imenovalcu pa seštevek poprečne korelacije (ta število lastnosti, ki so jih visokošolske inštitucije zahtevale od podaja smer in moč povezave med pari spremenljivk) in zmno- »svojih« poklicev. žek števila pojavov zmanjšanega za eno ter poprečno kovarianco. Običajno so vrednosti med 0 in 1, vendar spodnja vrednost ni omejena. Višja vrednost načeloma pomeni večjo konsistentnost. 520 Slika 14. Skupine poklicev pri optimalnem številu gruč Slika 12. Število zahtevanih lastnosti za poklic. (n=3) Z metodo, ki se imenuje statistika vrzeli (gap statistics), smo Z vidika inštitucij, ki izobražujejo za več poklicev, je morda ugotovili, da je optimalno število gruč 3. Na sliki 13 je prikazan pomembna diferenciacija. Tak primer je UM FOV, ki je predsta- graf za število gruč med 1 do 10. Optimalno število gruč je dolo- vila dva poklica: organizator informatik in organizator poslov- čeno z najnižjo vrednostjo statistike vrzeli, ki smo jo izvedli s nih sistemov. Analiza gruč je pokazala dobro diferenciacijo, saj 1000 simulacijskimi teki. se razlikujeta že pri klasificiranju v dve gruči. Kot primer pokli- cev, ki neodvisno od števila gruč vedno nastopajo skupaj naj- demo: inženir informatike in tehnologij komuniciranja, inženir računalništva in matematike, inženir računalništva in informa- cijskih tehnologij ter inženir računalništva in informatike. Zani- miv je tudi poklic inženir mehatronike, pri katerem bi pričakovali, da bo pogosto nastopal v gručah inženirjem strojništva in inže- nirjem elektrotehnike. Vendar je v gruči z omenjenima le, kadar klasificiramo v pet gruč, sicer pa mu članstvo zelo spreminja. Pri treh gručah nastopa v skupini s še devetimi poklici, med katerimi ni pričakovanih. Lastnosti, ki so jih izobraževalne ustanove za- htevale za posamezne poklice, zelo vplivajo na gruče in priporo- čila anketirancem za najprimernejši poklic. Slika 13. Funkcija statistike vrzeli za optimalno število gruč. Skupine poklicev pri optimalnem številu gruč (𝑛𝑛 = 3) prika- zuje slika 14, slika 15 pa povzetek pripadnosti poklicev pri šte- vilu gruč od 1 do 7. Slika 15. Pripadnosti poklicev pri številu gruč (n od 1 do 7). 521 5. DISKUSIJA 6. ZAKLJUČEK Samoocena anketirancev (odgovori na 78 vprašanj), določitev Analiza podatkov orodja za pomoč pri izbiri poklica »KamBi« je osebnih lastnosti, ki jih skupine vprašanj (26) opredeljujejo in obsegala tri vsebinske sklope, ki so v domeni anketiranca, pri- določitev zahtevanih lastnosti poklicev (23) vplivajo na priporo- pravljavca ankete ter visokošolskih ustanov, ki izobražujejo za čila o primernosti posameznega poklica za posameznega anketi- »svoje« poklice. Kompleksno analizo smo izvedli v jeziku R [8] ranca. Tako poleg anketirancev v procesu izdelave priporočila in z vmesnikom RStudio [9], kar je v kombinaciji z Latex-om nastopajo razvijalci ankete ter sodelujoče visokošolske ustanove pripomoglo k sprotnemu dokumentiranju in vizualizaciji rezulta- S post festum analizo smo rangirali poklicne preference za 1750 tov obdelave. anketirancev. Na sliki 16 so za vse poklice prikazane frekvence Priložnosti za izboljšavo v smislu boljših in natančnejših pri- rangov od 1 do 3. Seveda je za poklic (posredno za visokošolsko poročil anketirancem so predvsem: 1. večstransko ocenjevanje ustanovo) pomembno, da nastopa čim večkrat z najvišjim ran- posameznikovih lastnosti. Poleg samoocene je možno vključiti gom (R1). tudi osebe, ki anketiranca dobro poznajo in ga bolj nepristransko Posameznik ima običajno tudi lastnosti, ki jih visokošolska ocenijo. 2. razmislek o vprašalniku, posebej za področja, kjer je ustanova poklicu ni predpisala. Tudi te lastnosti so v delovnem preverjanje interne konsistentnosti pokazalo nižje referenčne okolju lahko odločilne za razvoj kariere. Podobno kot smo ran- ocene in 3. razmislek o lastnostih, ki so posameznim poklicem girali poklice po specificiranih lastnostih smo to storili tudi za določene. Fakultete bi lahko vsaki od 26 lastnosti določile rela- nespecificirane oziroma presežne lastnosti. Pri teh sta bila naj- tivno težo (pomen) za »svoj« poklic. posamezne lastnosti. višje rangirana (R1) poklica inženir okoljskega gradbeništva Orodje KamBi ni le »še ena anketa« temveč je skupaj s podatki, (226) in inženir elektrotehnike (224). Presežne lastnosti v poro- ki morajo biti pripravljeni pred lansiranjem ankete ter podatki, ki čilu za anketiranca v spletni anketi niso dosegljiva, morda pa bi nastanejo v času izvajanja, lahko koristno sredstvo za izbiro po- jih v prihodnosti lahko vključili, saj utegnejo posamezniku tudi sameznikove karierne poti, pripravljavcem orodij za izbiro po- pomagati pri izbiri poklicne poti. klicev in visokošolskim ustanovam pa lahko nudi empirično pod- poro pri izvajanju glavnih aktivnosti – poklicnega usmerjanja in izobraževanja. ZAHVALA Avtorja se zahvaljujeva vsem institucijam, ki so sodelovale pri razvoju orodja KamBi [1]. LITERATURA IN VIRI [1] Mediade, “Inženirke in inženirji bomo!,” 2021. [Online]. Available: https://www.inzenirji-bomo.si/. [2] F. Parsons, Choosing a vocation (re-print of 1909 original version). Garret Park, MD, 1989. [3] V. Germeijs and K. Verschueren, “Indecisiveness and Big Five personality factors: Relationship and specificity,” Pers. Individ. Dif. , vol. 50, no. 7, pp. 1023–1028, 2011. [4] H. T. Holmegaard, L. M. Ulriksen, and L. M. Madsen, “The Process of Choosing What to Study: A Longitudinal Study of Upper Secondary Students’ Identity Work When Choosing Higher Education,” Scand. J. Educ. Res. , vol. 58, no. 1, pp. 21–40, Jan. 2014. [5] C. Didier and P. Simonnin, “I became an engineer by accident!,” in Forum on Philosophy, Engineering and Technology, 2012. [6] S. Schelfhout et al. , “How interest fit relates to STEM study choice: Female students fit their choices better,” J. Vocat. Behav. , vol. 129, p. 103614, 2021. [7] B. M. Capobianco, H. A. Diefes-dux, I. Mena, and J. Weller, “What is an Slika 16. Frekvence rangov poklicev za prvo, drugo in tretje Engineer? Implications of Elementary School Student Conceptions for priporočilo anketirancu. Engineering Education,” J. Eng. Educ. , vol. 100, no. 2, pp. 304–328, 2011. [8] R. C. Team, “R: A language and environment for statistical computing.” R Foundation for Statistical Computing, Vienna, Austria, 2021. [9] RStudio Team, “RStudio: Integrated Development for R.” RStudio, PBC, Boston, MA, 2021. 522 Priprava in uporaba kvizov v različnih programih za preverjanje usvojenega znanja pri predmetu fizika na gimnaziji Preparation and use of quizzes in various IT tools for checking pupil’s knowledge in the subject of physics in high school Kristina Leskovar Gimnazija Franceta Prešerna Kranj, Slovenija kristina.leskovar@gfp.si POVZETEK assessing the acquired knowledge when teaching remotely. In this article, I present an assessing of acquired knowledge with the Pouk, kjer učitelj predava, dijak pa posluša, ni dovolj učinkovit help of the learning platform Kahoot!, surveys with video in je v nasprotju s smernicami, ki veljajo za sodoben pouk. Pri communication platform Microsoft Zoom and tool Kviz that is poučevanju na daljavo pa se je še posebej izkazalo, da dijaki part of learning management system Moodle. All the listed tools potrebujejo več motivacijskih nalog, izzivov in zanimivosti, ki were presented to other employees of our institution at short pritegnejo k poslušanju in usvajanju nove snovi. Za sprotno workshops, which we organized internally in the school year preverjanje znanja se v šoli najpogosteje uporabi kar metoda 2020/2021. In this article the results of a short questionnaire for ustnega spraševanja na samem začetku ure ali pa po končani employees after those workshops are also presented. razlagi. Učitelj tako sproti oceni, kako je z usvojenim znanjem. Pri poučevanju na daljavo sem poiskala pripomočke, ki so se KEYWORDS izkazali za najuporabnejše pri preverjanju usvojenega znanja in Checking the acquired knowledge, Quiz, Kahoot!, Moodle, so nadomestili sprotno preverjanje, ki ga izvajam v šoli. V Zoom prispevku predstavim preverjanje usvojenega znanja s pomočjo orodja Kahoot!, Ankete, ki jo omogoča komunikacijski program Zoom in orodje Kviz v programu Moodle. Vsa našteta orodja 1 UVOD oziroma aplikacije sem predstavila tudi ostalim zaposlenim na Sodobna šola v primerjavi s šolo preteklih desetletij zahteva kratkih delavnicah, ki smo jih interno organizirali v šolskem letu prožnost, s tem pa ne samo miselni, temveč tudi strokovni 2020/2021 na našem zavodu. V članku pa predstavim tudi preskok pri delu z mladimi. Mladi si želijo motiviranega rezultate kratkega vprašalnika za zaposlene, ki sem ga izvedla po odprtega učitelja, dovzetnega za novosti in sodoben način dela v končanih delavnicah. razredu. Pouk, kjer učitelj predava, dijak pa posluša, ni dovolj učinkovit in je v nasprotju v smernicami, ki veljajo za sodoben KLJUČNE BESEDE pouk [1]. Učitelj poučuje dijake, ki so računalniško pismeni, Preverjanje usvojenega znanja, kviz, Kahoot!, Moodle, Zoom poznajo komunikacijska sredstva in temu primerno mora prilagoditi pouk [2]. ABSTRACT Pri pouku, ki poteka na daljavo, pa postanejo kompetence sodobnega učitelja še pomembnejše. Pri pouku na daljavo se Teaching where the teacher is lecturing, and the pupil is listening pojavijo naslednje težave: dijaki niso notranje dovolj motivirani, is not effective enough in fact it is contrary to the guidelines that primanjkuje jim zunanje motivacije, so preobremenjeni z velikim apply to modern teaching. When teaching remotely, however, it številom ur, ki jih presedijo za računalnikom … [3]. Če učitelj has been especially shown that pupils need more motivational tasks, challenges and points of interest that attract them to listen želi pripraviti uro, ki bo dijake pritegnila, jih obdržala pred ekrani, and master new material. For purpose of current assessment of poleg tega pa naj bi še usvojili želene cilje ure, je potrebno knowledge, the method of oral questioning in the school is most upoštevati pravilno zgradbo ure. Ura mora biti zgrajena tako, da often used at the very beginning of the class or after the end of pripomore k boljši motivaciji dijakov. the explanation. The teacher thus assesses the knowledge Izkazalo se je, da motivacija na začetku šolske ure v obliki acquired. I searched for tools that proved to be most useful in kviza, kjer vsi dijaki sodelujejo, pritegne k poslušanju, kratka vprašanja za vse dijake tekom šolske ure držijo dijake zbrane tudi Permission to make digital or hard copies of part or all of this work for personal or med uro in da s sprotnim preverjanjem na koncu ure učitelj lažje classroom use is granted without fee provided that copies are not made or distributed organizira razlago v prihodnjih urah. Hkrati pa je potrebno for profit or commercial advantage and that copies bear this notice and the full poudariti, da preveliko število aplikacij, orodij, načinov 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). podajanja snovi za dijake povzroča dodatne kognitivne Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia obremenitve in pripelje do velikega miselnega napora. © 2021 Copyright held by the owner/author(s). Ugotovitve kažejo, da sočasna vključitev velikega števila novih spletnih platform in orodij niža učenčev občutek 523 samoučinkovitosti [4]. Zmernost vseh spodaj opisanih orodij je funkcije in analize. Slednjih ne morem komentirati, saj sem ključna. uporabnica brezplačne verzije programa. 2 PRIPRAVA KVIZA S PROGRAMOM 3 PRIPRAVA KVIZA V PROGRAMU KAHOOT! MOODLE Prvo predstavljeno orodje je program Kahoot!, s katerim sem Usvojeno znanje sem preverjala še s programom Kvizi v spletnih ustvarila kvize za preverjanje usvojenega znanja. Kahoot! je učna učilnicah Moodle. Za pripravo kviza so na voljo različni tipi platforma, ki je zasnovana na igrah in se uporablja kot vprašanj: Drži/Ne drži, Esej, Kratek odgovor, Izberi manjkajoče izobraževalna tehnologija v šolah in drugih izobraževalnih besede, Povleci in spusti, Ujemanje, Ugnezdeni odgovori, ustanovah. Igre, ki so zasnovane kot kvizi z več izbirami, so Izračunano, Več izbir. Sama sem se najpogosteje poslužila dostopne prek spletnega brskalnika ali aplikacije Kahoot! [5]. možnosti Drži/Ne drži in možnost Več izbir (slika 2). Sama sem uporabila kvize na začetku učne ure in so služili kot motivacija. S kvizom sem preverila, koliko dijaki že poznajo temo, ki sem jo med poukom predstavila. Orodje Kahhot! namreč takoj pokaže statistiko pravilnih in nepravilnih rešitev, kar omogoča takojšen vpogled v nivo znanja, ki ga imajo dijaki pri določeni temi. Orodje Kahoot! pa se je dobro izkazalo tudi za analizo usvojenega znanja po uri (slika 1). Učitelj dobi takojšnjo povratno informacijo o razumevanju določene snovi. Slika 2: Vprašanje tipa Več izbir v enem od pripravljenih kvizov Kviz sem uporabila na več načinov. Uporabila sem ga kot orodje za preverjanje znanja na začetku ure. Na žalost se v tej situaciji v mojem primeru ni izkazal kot najboljši pripomoček, saj analiza ni tako hitra in pregledna kot na primer v orodju Kahoot! Rezultatov torej nisem mogla uporabiti kot temelj, na katerem naj gradim razlago nove snovi. Kviz pa sem uporabila Slika 1: Preverjanje znanja v programu Kahoot! tudi kot preverjanje znanja celotne predelane snovi. V tej situaciji pa je po mojem mnenju orodje zelo uporabno. Orodje Kviz Možnosti, ki jih ponuja progam, je več. Učitelj lahko sestavi omogoča, da se ga odpre za dijake na točno določen datum in uro. različne tipe nalog: Drži/Ne drži, več možnih izbir, Da/Ne … Dijaki lahko kviz rešujejo sočasno. Kviz je lahko časovno Bralca vabim, da vse možnosti uporabe razišče sam. omejen in po končanem reševanju orodje samo določi oceno uspešnosti reševanja. Ker se v nastavitvah kviza da omogočiti 2.1 Prednosti in slabosti uporabe tudi pomešana vprašanja, to omogoči verodostojnejše rezultate in ocene. Analiza rezultatov je tista, ki je v nadaljevanju Glavna prednost programa Kahoot! je v preprosti uporabi. Ko je kviz pripravljen, lahko z deljenjem kode dijaki kviz »odigrajo« uporabna za oceno izvedene ure. S pomočjo orodja sem ocenila, takoj, možno ga je tudi večkrat ponoviti. Pozitivna lastnost koliko so dijaki razumeli predstavljeno snov. Podrobnejša orodja je hitra analiza rezultatov, kar da hiter vpogled v trenutno analiza natančno pokaže tudi, pri katerem vprašanju so imeli dijaki težave. Učitelj vidi, katerega dela snovi dijaki niso stanje znanja, ki ga imajo dijaki. Orodje pokaže dijake, ki so razumeli, usvojili ter lahko uro prilagodi na ta način, da ponovi najuspešnejši, dijake, ki potrebujejo dodatno pomoč. Prednost je razlago. tudi, da za reševanje kviza dijaki potrebujejo zgolj mobilni Kviz v orodju Moodle se da uporabiti tudi pri maturantih, saj telefon in ne potrebujejo nameščene aplikacije ali dodatnega je pri maturi iz fizike ena od maturitetnih pol sestavljena iz programa. V kviz je možno vključiti slikovno gradivo. Kviz je na ta način tudi vizualno zelo privlačen. Ob samem reševanju kviza vprašanj izbirnega tipa. Baza vprašanj je dosegljiva v banki nalog igra tudi izbrana glasba, ki še stopnjuje in poudarja napetost med [6]. V kombinaciji z že pripravljenimi vprašanji je kviz pripravljen hitro in je dobra priprava na maturo. samim reševanjem. Dijaki so obliko kviza v platformi Kahoot! dobro sprejeli. 3.1 Prednosti in slabosti uporabe Vedno so z veseljem »odigrali« igro. Pri povratnih informacijah, ki sem jih dobila na koncu šolskega leta, so poudarili, da je kviz Kviz v Moodlu se je izkazal kot zelo uporabno orodje. Ima kar popestril ure, jih naredil bolj dinamične. Kvizov v tej obliki si nekaj prednosti. Prva od njih je, da ima več tipov vprašanj, kar želijo tudi v naslednjem šolskem letu, ne glede na način omogoča pestro postavitev kviza. Prednost je tudi, da je kviz izobraževanja, ki nas čaka v letu 2021/2022; doma ali v šoli. lahko časovno omejen in da ponudi pomešana vprašanja. Kviz Slabost, ki morda to tudi ni, je, da je program plačljiv in v ponuja dobro analizo rezultatov in pregleden vpogled v analize. svoji brezplačni različici ponuja zgolj nekaj možnosti. V kolikor Pomanjkljivosti, ki bi izstopale, orodje Kviz nima. Bi pa bil v se učitelj odloči za nakup licence, se namreč možnosti, ki jih ima kombinaciji z zaklenjenim zaslonom uporaben pripomoček tudi učitelj pri sestavi kviza, povečajo. Omogočene so dodatne za samo ocenjevanje znanja, ne le preverjanje. 524 4 PRIPRAVA PREVERJANJ V APLIKACIJI 6 ZAKLJUČEK ZOOM Uporaba zgoraj predstavljenih orodij je ena od možnosti, kako Orodje Zoom omogoča izvedbo anketnega vprašalnika med sproti preverjati usvojeno znanje ne samo pri fiziki, ampak tudi kreirano sejo. Anketni vprašalnik se lahko pripravi že pred pri ostalih predmetih tako na osnovni kot tudi na srednji šoli, če pričetkom seje ali med sejo samo. Možnost anketnega pouk poteka na daljavo. Predstavljena orodja pa so zelo uporabna vprašalnika sem uporabila kot kviz za preverjanje usvojenega tudi pri pouku, ki poteka v učilnici. S pomočjo orodij je pouk znanja oziroma razumevanje novih pojmov. Vprašalnik lahko dinamičen, zanimiv in sodobnejši. S predstavitvijo orodij dijaki rešujejo le med uro, rezultati so vidni takoj. Po zaključeni zaposlenim pa se je hitreje razširilo tudi znanje in njihova seji anketnega vprašalnika ni več možno reševati. Ker so rezultati uporaba pri ostalih predmetih. S predstavitvijo so bili zaposleni vprašalnika vidni takoj, je možno takojšnje ukrepanje pri razlagi. zadovoljni, kar so dokazali s tem, da so orodja tudi začeli Anketni vprašalnik sem uporabila tudi kot orodje za reševanje uporabljati pri pouku. nalog, kjer so bili ponujeni odgovori na daljše računske naloge. Na ta način sem videla, koliko dijakov je nalogo rešilo, koliko je ZAHVALA bilo pravilno rešenih nalog itn. Zahvaljujem se vodstvu Gimnazije Franceta Prešerna, ki je v času šolanja na daljavo podprlo vse ideje ter mi stalo ob strani pri 4.1 Prednosti in slabosti uporabe izvajanju novosti. Prednost anketnega vprašalnika, ki ga ponuja orodje Zoom, je ta, da dijaki ne potrebujejo telefonov, s katerim rešujejo LITERATURA IN VIRI naloge/vprašanja. Vprašalnik se pojavi v sami seji, kjer [1] VIjayalakshmi, M., 2019. Modern Teaching Techniques in Education. spremljajo predavanje. Na ta način ni preklapljanja med orodji in Conference paper: Educational Technology in Teacher Education in the 21st Century, (Feb, 2019). Dostopno na: aplikacijami. Dijaki ostanejo zbrani. https://www.researchgate.net/publication/331071559_Modern_Teaching Glavna pomanjkljivost orodja pa je, da orodje postane _Techniques_in_Education [14. 8. 2021]. nepregledno, če so vprašanja daljša in jih je več. Najprimernejše [2] Macuh, B., (2009). Kako motivirati sebe in učence za aktiven pouk, (20. 8. 2009). Dostopno na: http://www.solski-razgledi.com/e-sr- je za kratka vprašanja tipa Drži/Ne drži ali kratke odgovore na prispevek.asp?ID=177 [13. 8. 2021]. krajše naloge. [3] Doug, V., 2002. Online Journal of Distance Learning Administration, Volume V, Number III, (jesen 2002). Dostopno na: https://www.westga.edu/~distance/ojdla/fall53/valentine53.html [13. 8. 2021]. 5 PREDSTAVITEV ORODIJ ZAPOSLENIM [4] Aguilera-Hermida, A. P., (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of V obliki kratkega predavanja so bila orodja predstavljena tudi Educational Research Open. [5] Kahoot!, 2021. https://kahoot.com/ [16. 8. 2021]. ostalim zaposlenim v našem zavodu. Med učenjem na daljavo [6] Banka nalog. 2014. Dostopno na: smo se namreč zavedali dejstva, da dijaki težko ostanejo https://bankanalog.ric.si/Account/LogOn?ReturnUrl=%2fPrikaz%2fPrika motivirani ves čas pouka in da mora učitelj na različne načine zRezultatov [17. 8. 2021]. poskrbeti, da je ura dinamična in zanimiva. Ena od možnosti so tudi zgoraj omenjeni kvizi. Pri predstavitvi orodji sem bila pozorna na to, da so bila orodja predstavljena kratko in jedrnato. Poudarila sem glavne prednosti in slabosti. Pokazala sem po en primer za vsako orodje. Po končani predstavitvi sem izvedla še kratek vprašalnik, kjer me je zanimalo, če jim je bila predstavitev všeč, ali bodo uporabljali orodja pri pouku in katero orodje se jim zdi najuporabnejše. Zaposleni so odgovorili, da so bili s predstavitvijo zadovoljni. 80 % zaposlenih še ni uporabljalo orodja Kahoot! Nihče od zaposlenih ni uporabljal orodja Kviz v Moodlovih učilnicah. Le 10 % zaposlenih pa je vsaj enkrat uporabilo anketni vprašalnik v programu Zoom. Kar 95 % zaposlenih je zapisalo, da bodo v nadaljnjih urah preizkusili vsaj eno omenjeno orodje. Največ zaposlenih je po zapisanem poskusilo orodje Kahoot!, na drugem mestu je anketni vprašalnik v Zoom-u. Samo dva zaposlena pa sta poskusila uporabiti tudi Kviz v Moodlovi učilnici. 525 Spletni jezikovni priročniki pri pouku slovenščine Online linguistic manuals for teaching Slovene Mateja Miljković OŠ n. h. Maksa Pečarja Ljubljana, Slovenija mateja.miljkovic@osmp.si POVZETEK se želimo prepričati o njenih oblikoslovnih lastnostih. Vse te podatke najdemo v različnih pravopisnih, slovarskih in drugih Pri jezikovnih dilemah so nam v pomoč jezikovni priročniki. V priročnikih. Nekdaj smo po njih brskali predvsem v knjižnici na sodobnem digitaliziranem svetu jih najdemo vedno več na spletu, polici z referenčno zbirko ali na domači knjižni polici. To je po njih pa lahko brskamo s pomočjo elektronskih naprav. dajalo vsej stvari poseben čar. V današnjem digitaliziranem svetu Pojavila so se spletna mesta, kjer lahko na enem mestu najdemo pa imamo vse to na spletnih straneh, kjer besed več ne iščemo po povezave do različnih jezikovnih virov in servisov. Učni načrt za abecednem vrstnem redu, ampak jih samo še vtipkamo v iskalnik slovenščino v osnovni šoli narekuje uporabo jezikovnih in že imamo rezultat. priročnikov v knjižni in elektronski obliki. V prispevku je opisana učna ura v računalniški učilnici, kjer učenci spoznajo portal Fran, tj. spletišče, na katerem so uporabnikom na voljo vsi 2 JEZIKOVNI PRIROČNIKI temeljni jezikovni priročniki za slovenščino. Z reševanjem Pri razreševanju jezikovnih dilem so nam v pomoč jezikovni praktičnih nalog se urijo v uporabi le-teh. Taka izvedba učne ure priročniki. To so knjige, ki nam pomagajo, da naš jezik čim bolj je večini učencev všeč, poleg tega pa temelji na izkustvenem ustreza okoliščinam, v katerih ga uporabljamo, in namenu, ki ga učenju in navaja na uporabo spletnih jezikovnih priročnikov. V imamo z njim [1]. Lahko so vsebinski – v njih so opisane bodoče bo za namen pouka možno uporabiti novo nastali portal lastnosti posameznih jezikovnih ravnin (slovnica, pravila v Franček, ki pa je namenjen posebej učencem in dijakom. prvem delu Slovenskega pravopisa), abecedni – predstavljene KLJUČNE BESEDE besede po abecednem vrstnem redu (slovarji, Slovenski pravopis) ali zbirke besedil v e-obliki oz. t. i. korpusi – to so Jezikovni priročniki, splet, portal Fran obsežne zbirke besedil, ki jih zbirajo iz množičnih medijev, ABSTRACT knjig, spletnih strani …, s katerimi lahko preverimo zapis in rabo iskane besede, besedne zveze ali dela besedila [1]. Linguistic manuals help us with language dilemmas. In Najpomembnejši jezikovni priročniki so: today's digital world, we can find an increasing number of them online, and we can browse through them with the help • Slovenska slovnica, kjer so opisane in predstavljene of electronic devices. Websites have appeared which al ow us značilnosti jezika po posameznih enotah (glasoslovje, to find links to various language sources and services in one besedoslovje, besedotvorje, oblikoslovje, skladnja, place. The curriculum for Slovene in primary school dictates sporočanje). the use of linguistic manuals in book and electronic form. The • Slovar slovenskega knjižnega jezika, ki obsega paper describes a lesson in a computer classroom, where oblikovne in vsebinske podatke o besedah slovenskega pupils get to know the Fran portal - a website with al basic besedišča. language manuals for Slovene available to users. By solving • Slovenski pravopis, ki vsebuje pravila o pravilnem practical tasks, they are trained in the use of these manuals. zapisovanju besed in slovarski del. Most of the pupils like that kind of lesson which in addition is • Slovenski etimološki slovar, ki obravnava izvor besed based on experiential learning and builds a habit of using in pojasnjuje, iz katerih jezikov so prišle v slovenščino. online linguistic manuals. In the future, it wil be possible to • Veliki slovar tujk, ki pojasnjuje besede, prevzete iz use the newly created Franček portal for the purpose of tujih jezikov. lessons with stated portal being intended especial y for pupils and students. 2.1 ezikovni priročniki na spletu KEYWORDS S širjenjem digitaliziranega sveta najdemo vedno več jezikovnih Linguistic manuals, web, Fran portal priročnikov na spletu, ki lahko na tak način preko računalnikov, pametnih telefonov ali tablic dosežejo širši krog uporabnikov, tudi mladih, ki so še posebej vešči uporabe digitalnih naprav. 1 UVOD Ministrstvo za kulturo RS je v letu 2014 finančno podprlo projekt »Izdelava spletne strani z opisi jezikovnih virov in orodij V življenju se marsikdaj srečamo z vprašanji, kako se beseda za slovenščino ter osnovnimi (video) navodili za njihovo prav napiše, prav izgovori, kaj pomeni, od kod izvira … Včasih uporabo«, ki je nastal pod okriljem zavoda za uporabno 526 slovenistiko Trojina in se je v naslednjih letih še nadgrajeval. [2] 3.1 Portal Fran Tako lahko na enem mestu najdemo povezave do različnih virov Fran, jezikovni portal Inštituta za slovenski jezik Frana Ramovša – jezikovnotehnoloških, korpusnih, pravopisnih, slovarskih, ZRC SAZU, je spletišče, na katerem so uporabnikom na voljo slovničnih, terminoloških in zgodovinskih (Slika 1). Vsak vir je vsi temeljni jezikovni priročniki za slovenščino. Namenjen je predstavljen s kratkim videoposnetkom, ki nam prikazuje najširšemu krogu uporabnikov – temu sta prilagojena iskanje in osnovne značilnosti in načine iskanja. prikaz podatkov. Uporaben je pri pouku, saj učencem omogoča, Ditko (Moj jezik v digitalnem svetu) je podoben projekt, ki da aktivno spoznavajo pomene in rabo znanih in neznanih besed je nastal na Inštitutu za medijske komunikacije na Fakulteti za ter da preverijo pravopisne, oblikoslovne in skladenjske lastnosti elektrotehniko, računalništvo in informatiko Univerze v določene besede. Učenci tako spoznavajo različne jezikovne Mariboru. Njegov namen je bil v digitalnem obdobju ponuditi lastnosti besedja in hkrati pridobivajo védenje o uporabi digitalne vsebine slovenščine, tj. spletne jezikovne priročnike, in jezikovnih priročnikov. Iskalnik na www.fran.si omogoča zelo jih čim bolj učinkovito približati uporabnikom. V sklopu projekta enostavno iskanje razlag slovenskih besed, njihovega pregibanja, Ditko, ki je trajal od začetka leta 2018 do konca oktobra 2019, so pravopisnih lastnosti, frazeologije, etimologije, zgodovinske in vzpostavili spletno stran www.ditko.si s predstavitvijo vseh narečne rabe (Slika 2). Izhodiščna stran omogoča dober vizualni spletnih jezikovnih priročnikov, ki so na voljo za slovenščino [3]. pregled temeljnih slovenskih slovarjev po tematskih skupinah. Jezikovne vire in servise najdemo tudi na spletni strani Fran trenutno vključuje 29 slovarjev, narečni atlas, nekatere Slovenskega društva za jezikovne tehnologije (SDJT), seznam jezikovne podatkovne zbirke in povezave na druge pomembnejše slovenskih spletnih slovarjev pa na www.Slovarji.si. jezikovne vire za slovenščino ter dve jezikovni svetovalnici, znotraj katerih lahko uporabniki strokovnjakom zastavljajo vprašanja v zvezi s svojimi jezikovnimi zadregami [6]. Slika 1: Portal jezikovnih virov 3 JEZIKOVNI PRIROČNIKI PRI POUKU O tem, kje in kako iskati, se učijo učenci že v osnovni šoli. Učni načrt za slovenščino [4] v drugem in tretjem vzgojno- Slika 2: Portal Fran izobraževalnem obdobju narekuje razvijanje učenčeve pravopisne zmožnosti z uporabo pravopisnih priročnikov v 3.2 Uporaba spletnih jezikovnih priročnikov pri knjižni in elektronski obliki, v tretjem vzgojno-izobraževalnem pouku obdobju pa še razvijanje poimenovalne zmožnosti z uporabo slovarskih priročnikov v knjižni in elektronski obliki, kot so V sedmem razredu osnovne šole z učenci obravnavamo Slovar SSKJ, Veliki slovar tujk ipd. Učenec ob koncu devetletke pokaže slovenskega knjižnega jezika in ob tem pregledamo še ostale poimenovalno zmožnost tako, da zna uporabljati slovarske jezikovne priročnike. Najprej se učenci v razredu spoznajo s priročnike v knjižni in elektronski obliki, pravopisno zmožnost teorijo – naštevajo vrste priročnikov, si ogledajo fizične izvode pa pokaže tako, da zna uporabljati pravopisne priročnike v najpomembnejših priročnikov, ugotavljajo, kaj nam posamezni knjižni in elektronski obliki. izvod prinaša in kako in kdaj ga uporabljamo. Pokažem jim, kje Uporaba jezikovnih priročnikov pri pouku slovenščine je najdejo elektronske priročnike, še posebej predstavim portal Fran, ki ga bodo sami preizkusili v nadaljevanju. Sledi praktični pomembna, saj učenci s tem širijo in bogatijo svoje besedišče ter del v računalniški učilnici, kjer učenci rešujejo konkretne naloge, se navajajo na njihovo samostojno rabo. Uporaba slovarjev saj je cilj, da znajo priročnike uporabljati v vsakdanjem življenju. namreč pozitivno vpliva na uspešno učenje novih besed ter pripomore k poglabljanju znanja o besedah tako na ravni pomena Za začetek učenci ponovijo, katere slovarje poznajo in kaj jim le- kot rabe, bogat besedni zaklad pa je izjemno pomemben element ti prinašajo (Slika 3). sporazumevalne zmožnosti posameznikov – med drugim igra veliko vlogo pri šolskem uspehu, saj omogoča lažje razumevanje novih šolskih vsebin ter ima pozitiven vpliv na bralno pismenost [5]. Slovar v šolski praksi ni le priročnik, ki daje informativno- normativne podatke o jeziku, ampak je tudi pomembno didaktično sredstvo [5]. 527 Slika 6: Učni list, naloge 9–10 Slika 3: Učni list, naloga 1 Za konec učencem predstavim spletno stran V nadaljevanju odprejo Slovar slovenskega knjižnega jezika. http://besana.amebis.si (Slika 7), kjer lahko s pomočjo Spoznavajo posamezne geselske članke, iščejo razlago besed, avtomatske lektorice preverijo pravilnost zapisa ali si pomagajo spoznavajo frazeološko gnezdo kot sestavni del geselskega pri pregibanju različnih besednih vrst (Slika 8). članka in iščejo pomene stalnih besednih zvez (Slika 4). Slika 4: Učni list, naloge 2–4 Sledi spoznavanje Etimološkega slovarja, Slovarja slovenskih frazemov in Slovarja novejšega slovenskega jezika. Učenci Slika 7: Amebis Besana, pregibanje iščejo izvor besed, ki jih uporabljamo v slovenskem jeziku, pomene stalnih besednih zvez in pomene besed, ki so v slovenskem jeziku dokaj nove. Učence navajam k temu, da sami vedo, kateri slovar bodo uporabili (Slika 5). Slika 8: Učni list, naloge 11–12 Slika 5: Učni list, naloge 5–8 3.3 Portal Franček Na Inštitutu za slovenski jezik Frana Ramovša so šli še korak Sledijo naloge, povezane s Slovenskim pravopisom, s katerim si dlje. Ob 30. obletnici samostojnosti Republike Slovenije so učenci lahko pomagajo pri odpravljanju pravopisnih napak in objavili nov portal Franček (Slika 9), ki bo v končni obliki na ugotavljanju pravilnega zapisa težjih besed (Slika 6). voljo konec avgusta 2021. E-orodje bo prinašalo vsebine, 528 posebej prilagojene vsaki od treh starostnih skupin učencev (prva 4 ZAKLJUČEK in druga triada, tretje triada, srednja šola). Kot tako bo prvo Če primerjam učno uro o jezikovnih priročnikih v računalniški celovito slovarsko-slovnično orodje te vrste na Slovenskem, ki učilnici s tisto v razredu, ko lahko učitelj samo frontalno bo neposredno uporabno pri izpolnjevanju osnovnih ciljev prikazuje vsebine na platnu, učenci pa doma sami brskajo po učnega narta za slovenščino v osnovni in srednji šoli. Učence in spletnem ali klasičnem slovarju, potem bi se vedno odločila za dijake bo uvajalo v delo s spletnimi slovarji in spletnimi prvo. Učencem je taka izvedba všeč, radi imajo pouk, ki je slovničnimi priročniki. drugačen in popestri, na tak način se urijo v uporabi elektronskih Portal Franček bo obsegal odgovore na vprašanja o pomenu, priročnikov, učitelj pa jih medtem lahko usmerja in jim pomaga. rabi, pomenski povezanosti, (ne)zaznamovanosti, zvrstnosti, Najbolj štejejo prav praktične izkušnje in s tem lahko stilnih značilnostih, izgovoru, pregibanju, izvoru, narečni rabi in pripomoremo k uporabi jezikovnih priročnikov tudi v učenčevem zgodovinski umeščenosti besedja slovenskega jezika. Poleg tega kasnejšem obdobju. V prihodnje bo vredno preizkusiti nov portal pa bo vseboval še orodje, ki bo povezalo slovarske vsebine s Franček, ki je namenjen posebej učencem, in prinaša številna slovničnimi, jezikovno svetovalnico za učitelje slovenščine in koristna orodja. nabor gradiv z opisom učnih metod, ki bodo pripomogle k obsežnejši uporabi predstavljenega e-orodja pri pripravi in izvajanju pedagoških procesov in k boljši usposobljenosti 5 LITERATURA IN VIRI učiteljev za delo na področju prožnih oblik učenja. Na voljo bo tudi nov Šolski slovar slovenskega jezika [7]. [1] Gomboc, M. 2019. Slovenščina: po korakih do odličnega znanja. Ljubljana: Mladinska knjiga. [2] Trojina, zavod za uporabno slovenistiko. Dostopno na naslovu https://www.trojina.si/p/portal-jezikovnih-virov/ (28. 7. 2021) [3] Čakš, P. 2020. Ditko: ali poznamo spletne jezikovne priročnike za slovenščino? V UMniverzum, 11 (februar 2020), 10–11. Dostopno na naslovu https://www.um.si/kakovost/Documents/UMniverzum-2020-11- lq.pdf (28. 7. 2021) [4] Učni načrt za slovenščino. 2018. Ljubljana: Zavod Republike Slovenije za šolstvo. [5] Rozman, T. idr. 2018. Slovarji in učenje slovenščine. V Slovar sodobne slovenščine: problemi in rešitve (avgust 2018), 150–167. DOI: https://doi.org/10.4312/9789612379759 [6] Vodnik po Franu. 2015. Dostopno na naslovu: https://fran.si/Content/Site/files/gradiva/Fran-Vodnik-2015.pdf (28. 7. 2021) [7] Spletni portal Franček, Jezikovna svetovalnica za učitelje slovenščine in Šolski slovar slovenskega jezika. Dostopno na naslovu https://isjfr.zrc- sazu.si/sl/programi-in-projekti/spletni-portal-francek-jezikovna- svetovalnica-za-ucitelje-slovenscine-in-solski#v (28. 7. 2021) Slika 9: Portal Franček 529 Delo na daljavo in preverjanje znanja pri matematiki Distance learning and checking progress at mathematics Polona Mlinar Biček OŠ Ivana Tavčarja Gorenja vas Gorenja vas, Slovenija polona.mlinar@gmail.com POVZETEK 1 UVOD Pri pouku na daljavo so zelo pomembni vidiki sprotno in končno Prav vsi učitelji smo se v preteklih dveh šolskih letih srečali z preverjanje učenčevega znanja ter ustrezno podajanje povratne delom na daljavo, se na tem področju izobraževali in iskali informacije. V šolskem letu 2019/20 se je šolanje na daljavo najboljše rešitve pri podajanju učne snovi. Zelo pomemben vidik preselilo na splet praktično preko noči, v šolskem letu 2020/21 poučevanja predstavlja prejemanje povratne informacije s strani pa smo učitelji uspeli izpopolniti svoje znanje tudi na tem učencev, kar mi predstavlja dodaten vidik pri organizaciji področju. V prispevku prikazujem nekaj možnosti preverjanja nadaljnjega dela. Preverjanja znanja in pridobivanje informacij o znanja preko spletnih aplikacij, ki so na voljo brezplačno, ter doseženih ciljih je bilo potrebno vpeljati premišljeno, da le-ta možnost uporabe le-teh pri matematiki. Vsi načini preverjanja niso bila prepogosta in da sem iz njih dobila dovolj ključnih znanja se ne morejo uporabljati v vseh situacijah. Pomembna je informacij, ki so me vodile v proces načrtovanja. Sama sem skozi tudi povratna informacija, ki jo ob preverjanju znanja pridobi večmesečno delo uporabila različne načine za pridobivanje učenec s strani učitelja. Podajam tudi slabosti in prednosti, ki sem povratne informacije, nekateri načini so se mi zdeli še posebej jih zaznala pri posameznih načinih preverjanja znanja, ter zanimivi in jih bom vključila v sam proces izobraževanja tudi pri nakazujem možnosti, kje lahko svoje delo še izboljšam. delu v šoli (ne le na daljavo). KLJUČNE BESEDE 2 OBRAVNAVA UČNE SNOVI PRI DELU Delo na daljavo, preverjanje znanja, povratna informacija NA DALJAVO Pri samo obravnavi učne snovi na daljavo sem morala upoštevati ABSTRACT več vidikov – od tehničnih možnosti, ki so jo imeli na voljo učenci doma, do same motiviranosti za delo. Pouk sem izvajala A very important aspect of distance learning is the ongoing and z vnaprej pripravljenimi posnetki, ki sem jih večinoma posnela final examination of the student’s knowledge and the appropriate sama ali pa smo si jih s kolegicami izmenjale, srečevanjem na provision of feedback. In the school year 2019/2020 schooling Zoomih in samostojnim delom. Na posnetkih sem največkrat was moved online practically overnight, and in 2020/2021 razlagala novo snov, na videosrečanjih, ki so potekala enkrat do teachers managed to educate ourselves in this area as well. In this dvakrat tedensko, smo v prvem delu skupaj vadili že razloženo paper I present some possible ways of checking students’ snov, v drugem delu pa sem razložila krajše pravilo oziroma progress through some applications, which are available for free, dodala težje primere. Tako sem zagotovila, da so učenci imeli and the possibilities of using them at mathematics. Not all types možnost postaviti vprašanja ob nejasnostih razložene snovi. Pri of progress checks can be used in all situations. What is also samostojnem delu so učenci dobili navodila in novo snov important is the feedback the student receives from the teacher. I obravnavali s pomočjo i-učbenika [6]. Sam potek dela in also talk about the advantages and disadvantages that I came organizacijo pa sem usklajevala s pomočjo Arnesove spletne across during my work, as well as the possibilities of further učilnice [7]. improving it. 3 PREVERJANJE ZNANJA IN POVRATNA KEY WORDS INFORMACIJA Distance learning, progress check, feedback 3.1 Preverjanje znanja Med procesom obravnave učne snovi je potrebno razumevano snov večkrat preveriti, pri delu na daljavo pa je bil ta vidik še toliko bolj pomemben, saj nisem imela možnosti opazovati 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 učencev pri samem delu in razlagi snovi. distributed for profit or commercial advantage and that copies bear this notice and Učitelj preveri doseganje učnih ciljev pred obravnavo novih the full citation on the first page. Copyrights for third-party components of this work učnih vsebin, med samo obravnavo ter ob koncu obravnave učne must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia snovi. Pomembno je, da se učencem nudi povratne informacije o © 2021 Copyright held by the owner/author(s). uspešnosti učenja ter da se skupaj z njim išče razloge za 530 morebitno slabše razumevanje ter načine za premagovanje vrzeli. Učenčevo predznanje lahko preverimo s pogovorom, kvizi, reševanjem nalog … Učitelj pa mora ob tem upoštevati, katere učne cilje, ki jih predvideva učni načrt, so oz. bodo lahko dosegli v času izobraževanja na daljavo [4]. 3.2 Odziv učencev in učiteljev na povratne informacije V svojem članku Eržen V. [1] povzema raziskavo Centra za raziskave in inovacije na področju izobraževanja, v kateri ugotavljajo, da učiteljeva povratna informacija na učence pomembno vpliva in je spodbudna, kadar: • je pravočasna oz. izražena ob pravem času, • izhaja iz jasnih ciljev in kriterijev uspešnosti, • je konkretna in specifična ter • vsebuje učiteljeve predloge, kako nadaljevati učenje ali izboljšati dosežek. V raziskavi, ki jo je izvedla Žitko U. [2] so rezultati pokazali, da je učencem povratna informacija o opravljeni domači nalogi zelo koristna za analiziranje lastnih napak, saj so z analiziranjem lastnih napak lahko svoje znanje izboljšali. Večina učencev je povratno informacijo sprejela pozitivno. Učencem je bolj ustrezalo, če so povratno informacijo dobili zapisano, kot pa če Slika 1: Izbira tipa vprašanja v Kvizu. jim je bila podana ustno. Pomembno pa je tudi, da učencu znamo Vir: https://sio.si/vodici/moodle/#_kviz napisati povratno informacijo tako, da jo razume in mu omogoči, da svoje napake lahko odpravi. Na drugi strani pa učitelji menijo, da s pomočjo preverjanja Naloge se učencem prikazujejo posamično (Slika 2, Slika 3). znanja s povratno informacijo lahko pridobijo kakovostne informacije, ki so jim v pomoč pri načrtovanju nadaljnjega dela. Mnenje učiteljev v raziskavi je bilo, da preverjanja pozitivno vplivajo na boljše dosežke pri ocenjevanju znanja ter da s spodbudnimi besedami lahko učitelj motivira učence k boljšimi dosežkom [3]. 4 DELO NA DALJAVO IN POVRATNA INFORMACIJA Pri delu na daljavo imamo kar nekaj možnosti za preverjanje znanja. V nadaljevanju predstavljam nekatere aplikacije, ki so nam na voljo, in kako sem jih sama uporabila pri delu. Podam Slika 2: Primer naloge – ulomki tudi slabosti in prednosti, ki sem jih zaznala pri delu. 4.1 Kviz v spletnem učnem okolju Moodle Ena izmed možnosti, ki se nam ponuja pri uporabi spletnih učilnic je prav gotovo oblikovanje Kviza v spletni učilnici Moodle [5]. Takega načina preverjanja znanja so se učitelji posluževali zelo pogosto. Tudi sama sem preizkusila ta način preverjanja. Pri oblikovanju kviza imamo več možnosti nastavitev. Prvi sklop omogoča: kdaj je kviz učencem na voljo za reševanje, lahko nastavimo čas, ki ga ima učenec za reševanje kviza, oceno za uspešno opravljanje, dovoljeno število poskusov, način ocenjevanja. Lahko nastavljamo še druge parametre, ki določajo Slika 3: Primer naloge – ulomki potek reševanja. Dodajanje vprašanj kviza zopet lahko poteka na več načinov, tudi pri vprašanjih imamo več možnosti izbir tipa Učenci po končanem preizkusu dobijo glede na nastavitve vprašanj (Slika 1): povleci in spusti na sliko, povleci in spusti na ustrezno povratno informacijo, ki jo je določil učitelj. Pogledajo besedilo, drži/ne drži, esejski tip, povezovalni tip vprašanj, lahko pravilnost rešenih nalog ter pravilne odgovore. izbirni tip vprašanja (omogoča izbiro enega ali več odgovorov iz vnaprej določenega seznama) … 531 Učitelj pa lahko po reševanju pregleda seznam rešenih morebitni napaki učenca usmeri v odpravljanje pomanjkljivosti, kvizov, kdaj in koliko časa je učenec reševal kviz ter uspešnost in to lahko stori ob vsaki posamezni nalogi posebej. reševanja po nalogah (Slika 4). Slika 4: Poročilo o dosežku učenca Tak način preverjanja znanja je zelo primeren za kratke odgovore, ki ne zahtevajo vmesnih postopkov, saj samo iz rezultatov ne vidimo postopkov reševanja in predhodnega razmišljanja učencev. Slika 6: Podajanje povratne informacije Dobra stran takega načina preverjanja je prav gotovo prihranek časa pri pregledovanju pravilno rešenih nalog. Učitelj Pozitivna stran takega načina oddajanja preverjanja je prav se lahko osredotoči na tiste, ki so napačno rešene in poskuša gotovo kakovostna povratna informacija. Ker so morali na ugotoviti, kaj mora učenec v dani nalogi izboljšati. Nekoliko bolj povratno informacijo počakati tudi kakšen dan, saj je bila zamudno je samo sestavljanje kviza, saj je potrebno vsako količina oddanih nalog precejšnja in zame kar velik zalogaj za vprašanje posebej ustavljati v kviz. Učencem lahko povratno popravljanje in komentiranje, se je na koncu izkazalo, da večina informacijo posredujemo tudi preko sporočil. Kot učencev povratne informacije ni niti pogledala. pomanjkljivost pri takem načinu preverjanja se je pokazalo, da so nekateri učenci kviz rešili na hitro, saj sem ob pregledu 4.3 Liveworksheets ugotovila, da so ga nekateri rešili prej kot v minuti, kar pomeni, Tretja možnost preverjanja znanja, ki sem jo uporabljala pri delu da so ga reševali, zgolj da je bil rešen. na daljavo, je bila spletna aplikacija Liveworksheets [8]. Učitelji imamo pripravljenih precej učnih listov, ki jih pri delu v šoli s 4.2 Možnost Naloga v spletni učilnici Moodle pridom uporabljamo. Že prej sem opisala, kako lahko uporabimo Kot drugi način preverjanja znanja, ki sem se ga posluževala pri obstoječe naloge za preverjanja znanja, a mi je ta način bil zelo delu na daljavo, je bil oddaja naloge v spletni učilnici (Slika 5). blizu. Uporabila sem lahko učne liste, ki sem jih že imela Pri nastavitvi oddaje nalog imamo zopet na voljo več pripravljene za delo v šoli. Aplikacija Liveworksheets ponuja parametrov. Oddajo lahko časovno omejimo, omejimo število različne načine preverjanja znanja (izberi pravilno izbiro, poveži, oddaj in nastavimo vrsto oddanih datotek. dopolni …). Učni list v obliki pdf formata uvozimo v saplikacijo, dodamo elemente aktivnosti (kaj mora učenec narediti/izpolniti), aplikacija ponuja tudi druge možnosti nastavitve glede časa reševanja, objave učnega lista … Učni list lahko ohranimo zaseben ali pa ga javno podelimo z ostalimi učitelji. V tej aplikaciji lahko najdemo kar nekaj idej za preverjanje, ki so deljena v skupno rabo. Učenci po reševanju učnega lista (Slika 7) pošljejo svoje odgovore s pomočjo aplikacije v učiteljev predal, kjer se zbirajo njihovi izdelki. Slika 5: Aktivnost za oddajo naloge v Moodlu Vir: https://ucilnice.arnes.si/ Učitelj ima na voljo tudi nastavitve povratne informacije: zapisati komentarje v nalogo oziroma komentirati oddano nalogo kot celoto (Slika 6). Imamo tudi možnost uporabe popravnih znakov v nalogi. Tak način podajanja povratne informacije je s strani učitelja zelo zamuden, s strani učenca pa najbolj uporaben. . Učitelj lahko učencu poda napotke za nadaljnje delo, ob Slika 7: Preverjanje decimalnih števil 532 Vsekakor je prednost takega načina dela skrajšan čas priprave, Bistvo pri preverjanju je bilo, da dobim tako jaz kot tudi saj lahko uporabimo že pripravljene učne liste, aplikacija pa tudi učenci čim boljši vpogled v obravnavo učne snovi in njihovo avtomatsko preveri pravilnost rezultatov, poda povratno znanje ter da pri tem ne porabimo preveč časa, da lahko to informacijo v točkah, učenec pa lahko s pomikom na napačno počnemo kontinuirano tudi na dolgi rok. Sem se pa srečevala z rešeno polje (rdeče) vidi pravilen rezultat (Slika 8). učenci, ki so preverjanje reševali neresno ali pa ga sploh niso oddali. Preverjanje znanja mi je bilo vodilo za nadaljnje delo na daljavo, sem pa s tem dobila tudi dovolj dober vpogled v učenčevo znanje in sem lahko na podlagi tega učence povabila na dodatno uro razlage oziroma na dopolnili pouk. V nadaljnje bom del preverjanj, ki sem jih izvajala na daljavo, prav gotovo uporabila tudi pri delu v šoli, saj so se izkazala za učinkovita tako za učence kot tudi za učitelja. LITERATURA IN VIRI [1] Vineta Eržen. 2014. Povratna informacija za uspešnejše učenje. Vzgoja in izobraževanje, letnik 45, številka 5/6 (2014), str. 28-31. Dostopno na naslovu https://www.dlib.si/stream/URN:NBN:SI:DOCCV69VZ31/4b0338eb- Slika 8: Povratna informacija učencu e73e-49e5-9d74-9bd2f756e52b/PDF (1. 6. 2021) [2] Urša Žitko. 2017. Povratna informacija pri matematičnih domačih Po končani oddaji sem vedno pregledala izdelke učencev. Ker so nalogah. Diplomsko delo. Univerza v Ljubljani, Pedagoška fakulteta, Ljubljana. bili izdelki že pregledni s strani aplikacije, sem dokaj hitro Dostopno na naslovu http://pefprints.pef.uni- zaznala napake, ki so jih učenci delali na preverjanju (ali je bila lj.si/4671/1/Ur%C5%A1a_%C5%BDitko_-_Diplomsko_delo.pdf (15. 5. 2021) napaka lapsus ali pa je šlo za nepoznavanje obravnavane snovi). [3] Jelica Bergar. 2013. Funkcija povratne informacije v procesih preverjanja Trudila sem se, da sem ob vsakem takem preverjanju učencem in ocenjevanja znanja. Magistrsko delo. Mednarodna fakulteta za tudi zapisala povratno informacijo v pisni obliki in jih spodbujala družbene in poslovne študije, Celje. Dostopno na naslovu k nadaljnjem delu. Tudi pri tem preverjanju sem imela nekaj http://revis.openscience.si/IzpisGradiva.php?id=7206&lang=slv&prip=d učencev, ki so oddali preverjanje prazno ali pa so vpisovali kum:9170856:d3 (1. 7. 2021) [4] Damjan Štefanc, Danijela Makovec Radovan, Jana Kalin, Jasna Mažgon, nelogične rešitve. Klara Skubic Ermenc, Barbara Šteh. 2020. Kaj je potrebno zagotoviti, da bo ocenjevanje znanja v času izobraževanja na daljavo strokovno 5 ZAKLJUČEK legitimno? Oddelek za pedagogiko in andragogiko Filozofske fakultete UL, Zveza društev pedagoških delavcev Slovenije Dostopno na naslovu https://zdpds.si/wp-content/uploads/2020/05/Za-strokovno-ustrezno- Kljub delu na daljavo smo poskušala z učenci maksimalno preverjanje-in-ocenjevanje-znanja-20.4.2020.pdf (20. 5. 2021) usvojit učne cilje, ki smo si jih zadali pri načrtovanju dela. [5] Damjana Šajne, Martin Božič, Blaž Milar, Marin Kajba, Timotej Jazbec. 2021. Uporabniški vodič Moodle. Dostopno na naslovu Povratna informacija je bila učencem in meni ključnega pomena. https://sio.si/vodici/moodle/#kompilacija-sio-MDL-VOD (20. 7. 2021) Zgoraj sem navedla nekaj primerov, ki sem jih sama uporabljala [6] Iučbeniki. Spletno mesto interaktivnih učbenikov. Dostopno na naslovu pri delu na daljavo. Vsak način je imel prednosti in slabosti, pri https://eucbeniki.sio.si/ (1. 4. 2021) [7] Arnes učilnice. Dostopno na naslovu https://ucilnice.arnes.si/ (1. 4. 2021) vsakem primeru sem se nekaj novega naučila. [8] Liveworksheets Dostopno na naslovu https://www.liveworksheets.com/ (1. 4. 2021) 533 Matematični učbenik Franca Močnika Franc Močnik's mathematics textbook Alenka Močnik Srednja šola Veno Pilon Ajdovščina Cesta 5. maja 12, Ajdovščina, Slovenija alenka.mocnik@ss-venopilon.si POVZETEK 1 UVOD V prispevku je predstavljen sklop učnih ur, ki so bile izvedene v Medpredmetno in timsko poučevanje učiteljem predstavlja velik času pouka na daljavo med epidemijo. V okviru izziv. Poleg iskanja idej za predstavitev snovi na drugačen, medpredmetnega poučevanja pri matematiki in slovenščini z avtentičen način, je tovrsten pristop vsakič inovativen. Povezati zgodovinskim ozadjem je bil aktualiziran učbenik avtorja dr. se s predmeti, ki se zdijo sprva nezdružljivi in kjer se zdi, da je Franca Močnika z naslovom Aritmetika za učiteljišča, ki je bil nemogoče poiskati skupni imenovalec zato zahteva podrobnejšo izdan leta 1885. Močnik je pisal večinoma v nemškem jeziku, saj organizacijsko in dobro snovno pripravo. se je v takratnem času na našem ozemlju govorilo in pisalo pretežno v nemščini. Okrog 150 njegovih izvirnih del je bilo Tokrat smo medpredmetno sodelovale učiteljice prevedenih v slovenski jezik in še v 12 drugih jezikov. S matematike, slovenščine ter zgodovine. V prvem letniku profesorico slovenščine Matejo Ceket Odar smo poučevale gimnazijskega programa je bila obravnavana tema kriteriji timsko v prvem letniku gimnazijskega programa. Dijakom je bil deljivosti s pomočjo matematičnega učbenika, ki je bil izdan leta predstavljen jezik, v katerem je bil učbenik napisan. Obenem so 1885 avtorja dr. Franca Močnika. Z dijaki smo prevedli del spoznali, da se matematika skozi stoletja v bistvu ni spreminjala. razlage v sodelovanju s slavistko Matejo Ceket Odar v sodobno Še več, ugotovili smo, da so Močnikove definicije in izreki slovenščino. Ob tem smo se pogovorili o izrazih, ki so se pojavili popolnoma enakovredni tistim, ki so zapisani v sodobnih v zapisu ter matematične pojme dokazali s pomočjo definicij in učbenikih. izrekov, ki smo jih spoznali pri pouku. Za razumevanje zgodovinskega ozadja časa, v katerem je živel in delal dr. Franc KLJUČNE BESEDE Močnik, je pri urah zgodovine poskrbela profesorica Metka Kolenc. Dr. Franc Močnik, kriteriji deljivosti, matematični učbeniki, medpredmetna povezava Dijaki so na ta način pridobili nova znanja, tudi v kontekstu vseživljenjskega učenja. Tak način dela ima tudi ABSTRACT močan motivacijski učinek, saj dijakom predstavimo neko snov multiperspektivno. Dijaki se aktivno vključijo v proces pri The article presents a set of lessons that were conducted during pridobivanju novih informacij. distance learning during the epidemic. As part of interdisciplinary teaching in mathematics and Slovene with a historical background, the textbook by dr. Franc Močnik with the 2 MEDPREDMETNO POUČEVANJE1 title Arithmetic for Teachers (Aritmetika za učiteljišča), Med načeli in cilji posodabljanja učnih načrtov (Smernice, 2007) published back in 1885. At that time the majority of writings sta tudi povezovanje predmetov in disciplin ter holističnih pristop produced on the Slovenian territory were written in German učenja in poučevanja. Martin-Kneip, Fiege in Soodak (1955) language and so were a lot of Močnik’s works. By now opredeljujejo medpredmetno povezovanje kot primer approximately 150 pieces of his original writings were translated holističnega učenja in poučevanja, ki kaže realen interaktiven into Slovenian and 12 other languages. With Slovene language svet, njegovo kompleksnost, odpravlja meje med posameznimi teacher Mateja Ceket Odar, we decided for interdisciplinary disciplinami in podpira načelo, da je vse znanje povezano. course for students in the first year of the high school program. Medpredmetno povezovanje ne pomeni le razvijanja Students were introduced to the language in which the textbook konceptualnega povezovanja (povezovanje sorodnih pojmov pri was written. They realized also that mathematics has not changed različnih predmetih), ampak razvija pri učencih tudi generične a bit over the centuries and, even more, that Močnik’s definitions veščine, ki so neodvisne od vsebine in so uporabne v različnih and theorems are exact equivalents of the ones in contemporary okoliščinah (npr. kritično mišljenje, obdelava podatkov, uporaba textbooks. IKT…). Dejavnosti, povezane z medpredmetnim povezovanjem, KEYWORDS vodijo k doseganju kompleksnih znanj in h kompleksnim Dr. Franc Močnik, criterion for divisibility, mathematics pričakovanim rezultatom. Medpredmetne povezave textbooks, interdisciplinary course uresničujemo in izvajamo na različnih ravneh in z različnimi cilji: a) Na ravni vsebin: obravnava oz. reševanje interdisciplinarnih problemov. Pri teh dejavnostih uporabljamo 1Povzeto po: Posodobitve pouka v gimnazijski praksi, 2010, Zavod Republike Slovenije za šolstvo. 534 specifična znanja posameznih disciplin in tudi generične veščine informacije ter da razvijajo veščine, ki jim bodo pomagale pri in spretnosti, ki predstavljajo aplikacijo specifičnega znanja na vseživljenjskem učenju. Razvijati morajo kritično mišljenje, biti avtentične probleme. sposobni samovrednotenja in samokritičnosti. V poplavi b) Na ravni procesnih znanj: učenje in uporaba procesnih informacij morajo biti sposobni presoditi, ali so informacije, ki znanj (npr. iskanje virov, oblikovanje poročila ali miselnega jih pridobijo na spletu pridobljene iz verodostojnih virov. vzorca, govorni nastop, delo v skupini,…). Pomembno je, da za svoje delo prejmejo povratne informacije, c) Na konceptualni ravni: obravnava pojmov iz različnih ker jih spodbudijo k nadaljnjem raziskovanju, sami pa morajo biti predmetnih perspektiv z namenom poglabljanja in razumevanja pripravljeni v delo vložiti svoj čas in trud. (npr. naravna rast pri biologiji v povezavi z eksponentno funkcijo pri matematiki, eksponentno pojemanje v povezavi z upadanjem 3 DEJAVNOST vrednosti dobrin na trgu idr.). Primeri naj bodo kot pomembni zgledi, ki so namenjeni razumevanje matematike in osmišljanju 3.1 matematičnih vsebin. Ideja in oblikovanje dejavnosti Pri tovrstnih dejavnostih dijaki pridobivajo izkušnje in se Leta 2015 smo obeležili 200-letnico rojstva matematika, učijo matematike ter tudi generičnih znanj, ki naj bi se v končni pedagoga in pisca matematičnih učbenikov dr. Franca Močnika. fazi kazala kot kompleksni pričakovani rezultati, kot npr., da Takrat sva z zgodovinarko Metko Kolenc izvedli sklop dijaki: medpredmetnih povezav med matematiko in zgodovino, pri - prepoznajo vlogo in pomen matematike in drugih disciplin čemer so pri zgodovini dijaki spoznali zgodovinsko ozadje časa v realnih situacijah in se učijo matematiziranja; v katerem je živel in deloval dr. Franc Močnik, pri matematiki pa - uporabljajo matematiko v matematičnih kontekstih in v smo skupaj pregledali eno od poglavij, ki ga obravnavamo v realnih situacijah, prvem letniku gimnazijskega programa. V letošnjem šolskem - modelirajo, primerjajo modele ter rezultate različnih letu, ko je pouk pretežno potekal na daljavo, pa sem želela modelov in interpretirajo njihove rešitve z vidika takratno izvedbo nadgraditi ter se povezati še s slovenščino. Tako matematike in realnih situacij idr. je bilo izvedenih nekaj šolskih ur v sodelovanju s slavistko Matejo Ceket Odar. Skupaj sva načrtovali učne ure, določili Didaktični vidiki medpredmetnega povezovanja iz vzgojno-izobraževalne cilje in metode dela. Pri tem sva se ravnali perspektive matematike: v skladu z učnim načrtom (Učni načrt. Matematika/slovenščina. - obravnavati matematične pojme iz različnih predmetnih Splošna, klasična in strokovna gimnazija, 2008). Priprave na perspektiv; učne ure je oblikovala vsaka sama, skupaj pa sva preučili - prepoznati matematični kontekst v realnih situacijah in ustrezno literaturo, vire in gradiva. modelirati; V Katalogu znanja za gimnazije je priporočena - reševati interdisciplinarne probleme in matematizirati; uporaba različnih oblik in metod dela ter je poudarjeno - razvijati uporabo IKT kot možnosti za razvoj samostojno delo učencev [5, 6]. Dijaki naj bi pri samostojnem matematičnega znanja ter kot podporo pri učenju in delu uporabljali različne vire in sodobno tehnologijo. Zato sva poučevanju; izvedbo zasnovali tako, da so dijaki pri urah bili samostojni in - razvijati generične veščine in spretnosti. podajali svoje ideje ter kot posamezniki bili vključeni v Z medpredmetnim sodelovanjem omogočimo, da skupinsko delo. zadane cilje dosežemo lažje, saj jih posamezen profesor v okviru svojega predmeta ne more doseči tako dobro in poglobljeno, kot 3.2 Cilji kadar sodeluje s profesorjem drugega predmetnega področja. Vključeni (pod)gradniki matematične pismenosti, s katerimi Tovrsten način dela poveča motivacijo, izboljša komunikacijo ter dijak: omogoča rast na profesionalnem področju, saj s tem sodelujoči - razume sporočila z matematično vsebino, razširi in poglobi lastno znanje. Dijakom je timsko poučevanje blizu, saj jim prisotnost dveh učiteljev omogoča sočasno podporo - pozna in uporablja strokovno terminologijo in simboliko, iz dveh predmetov ter bolj individualiziran pouk. Tudi navzoči - predstavi, utemelji in vrednoti lastne miselne procese, pri taki uri so bolj dovzetni do sodelovalnega učenja ter dela po - uporablja različne strategije pri reševanju matematičnih skupinah. Pri tem ima posameznik določeno nalogo in je hkrati problemov. za svoje delo odgovoren v svoji skupini. Bolje kot člani skupine Operativni cilji dejavnosti (vsebinski, procesni), pri katerih sodelujejo, bolje, lažje in prej je delo opravljeno. dijaki: Pri izvedbi učnih ur smo del ur namenile skupinskemu - utemeljijo in uporabljajo osnovne kriterije za deljivost, delu v razredu. Elizabeth G. Cohen skupinsko delo definira kot - razberejo, primerjajo in uporabijo različne reprezentacije delo dijakov v skupini, ki ga jasno določi učitelj. Skupina naj bo kriterijev za deljivost ter različne matematične simbolne dovolj majhna, da lahko vsak od njih k nalogi nekaj doprinese. zapise, Od dijakov se pričakuje, da izpeljejo nalogo brez neposredne in takojšnje pomoči učitelja. [2] - komunicirajo v matematičnem jeziku, Delo v skupini je aktivno in živahno, ker vključuje postavljanje - pri delu spretno uporabijo vire. vprašanj, razlaganje, podajanje predlogov, kritiziranje, poslušanje, strinjanje, nestrinjanje, iskanje rešitev, usklajevanje 3.3 Načrtovanje dejavnosti in skupne odločitve. [3] Načrtovanje dejavnosti se je začelo z uskladitvijo učnih ciljev in Pri poučevanju na daljavo je bila informacijsko pripravo poteka učnih ur. Za izvedbo ur sva pripravili ustrezno komunikacijska tehnologija nenehno prisotna. In prav zaradi gradivo v skupnem dokumentu. Pri posnetkih gradiv je sodeloval nenehnih impulzov sodobne tehnologije, ki je poleg prisotnosti upokojeni učitelj slovenščine in pisec ljudskega izročila na na video srečanju, dijake begala in jih odvračala od poslušanja ajdovskem Franc Černigoj. Preizkusili sva razdelitev razlage, moramo profesorji dijakom omogočati, da so zato pri udeležencev po skupinah preko videokonferenčne aplikacije pouku čim bolj aktivni, da samostojno pridobivajo potrebne Zoom, ki sva jo pri vseh urah uporabljali. 535 3.4 Izvedba dejavnosti Vzporedno s prevodi je nastajal slovarček starinsko Izvedba ur je potekala na daljavo preko videokonferenčne zaznamovanih izrazov (Slika 4). aplikacije Zoom. Ker je poučevanje potekalo timsko, sva bili obe prijavljeni kot gostiteljici, da je bilo omogočeno preklapljanje med zaslonom, ki sva ga delili. V uvodnem delu ure je dijakom na kratko predstavljeno življenje in delo dr. Franca Močnik. Povedano jim je bilo, da bo o tem več pojasnjenega pri uri zgodovine, kjer jim je profesorica Metka Kolenc pojasnila pomen njegovih del za nadaljnji razvoj slovenskega jezika ter delovanje posameznikov v takratni družbi. V začetku videokonferenčnega srečanja sva dijake prosili, da v klepet na Zoomu zapišejo pomen Močnikovega reka Virtute et opera = Z vrlino in delom (Slika 1). Posamezni dijaki so se pri tem oglasili ter pojasnili zapisano. Slika 4: Slovarček izrazov. Pri dokazih nekaterih izrekov, ki so se pojavili v posameznih odsekih besedila, je bil deljen zaslon tabličnega računalnika. Sproti so si dijaki zapisali snov na učni list (Slika 5), ki jim je bil Slika 1: Zapisi v klepetu. predhodno posredovan, da so si ga lahko natisnili doma pred izvedbo učne ure. V nadaljevanju smo poslušali posnetek iz Močnikovega matematičnega učbenika. Posnetek je nastal v sodelovanju s Francem Černigojem. Pri tem je bil uporabljen programček diktafon, ki je prosto dostopen na prenosnem računalniku. Program omogoča preproste operacije za obdelavo zvoka. Nato so bili dijaki razdeljeni po skupinah (delo po sobah v Zoom videokonferenci), kjer so prevajali posamezno poglavje v sodoben knjižni jezik. Zapisano besedilo je bilo deljeno v skupnem dokumentu (Slika 2), ki so ga lahko vsi sodelujoči sproti popravljali in dopolnjevali. Slika 5: Zapisi v zvezku. Slika 2: Besedilo pred popravki. Dijaki so reševali naloge na učnem listu ali samostojno ali v Skupaj smo pregledali prevedena poglavja ter se pogovorili o skupinah (Slika 6). Rešitve nalog smo preverili ali ustno ali pa so matematičnih pojmih ter po potrebi razložili, česar dijakom ni dijaki narekovali postopek reševanja. Profesor je pri tem bilo razumljivo. Dijaki so bili opozorjeni na neustrezno uporabo spremlja samostojno delo dijakov. Po potrebi jim je bila snov strokovne terminologije. dodatno razložena s pomočjo deljenja zaslona na tabličnem računalniku. Slika 3: Ustrezno popravljeno besedilo. Slika 6: Reševanje nalog v zvezku. 536 Ure medpredmetnega poučevanja so bile zaključene z zgodovino 5 ZAKLJUČEK slovenskega knjižnega jezika v 2. polovici 19. stoletja. Snov je bila obdelana medpredmetno, in sicer pri slovenščini, kjer so dijaki prevedli izbrane odlomke v sodoben knjižni jezik, 4 EVALVACIJA UDELEŽENCEV pri uri zgodovine, kjer so dijaki spoznali zgodovinsko ozadje Po zaključku dela sva z dijaki opravili evalvacijo v aplikaciji časa v katerem je živel dr. Franc Močnik ter pri uri matematike, kjer smo del snovi obdelali po njegovem učbeniku , ki je bil Padlet (Slika 7). Odgovorili so na sledeča vprašanja: zapisan pred več kot 200 leti. Medpredmetne povezave so 1. Kaj si se pri uri novega naučil-a? aktivna oblika pouka, ki dijakom omogoča pridobivanje 2. Kaj ti je povzročalo največ težav? Kaj bi naredil-a drugače? vseživljenjskih znanj. Priprava na pouk in sama izvedba je potekala na vsebinsko – metodični in organizacijski ravni. 3. Kaj ti je bilo všeč? Metodična raven je zajemala ustrezen izbor vsebin, ciljev in 4. Želiš še kaj dodati? metod, organizacijska pa ustrezno časovno usklajevanje in Dijaki so izrazili pozitivno mnenje o obravnavani skupno načrtovanje profesoric. snovi in načinu dela. Zapomnili so si, kako pomembno je bilo 19. Dijaki so spoznali, da se obravnavana snov pri stoletje za oblikovanje slovenskega naroda ter pomen izobrazbe slovenščini ter zgodovinske vsebine lahko uporabijo tudi pri za razvoj in krepitev narodne zavesti. Drugačen potek učnih ur matematiki, in obratno. Značilnost medpredmetnega poučevanja jim je bil všeč in zanimiv tudi zaradi jezika, ki je bil v učbeniku je tudi ta, da je znanje dijakov trajnejše in jih usmerja h uporabljen. kritičnemu reševanju problemov. Največ težav jim je povzročalo razumevanje besedila Zavedava se, da bi bilo v šolskem letu potrebno iz Močnikovega učbenika, saj niso poznali vseh izrazov. opraviti več takih medpredmetnih povezav, vendar smo Pogrešajo več takih ur in tem, saj jim tak način dela profesorji omejeni s številom ur in vsebinami pri posameznih omogoča večjo aktivnost med poukom ter prisotnost dveh predmetih, kjer snovi niso časovno usklajene in se ne profesorjev, ki se medsebojno dopolnjujeta, torej je vseskozi obravnavajo v istem obdobju ali celo v istem letniku. prisotno tudi timsko poučevanje. Zelo pomembna je aktualizacija Obravnava učne snovi s pomočjo didaktičnega teme, saj jo tako dijakom približamo. Dijaki se na ta način lažje pristopa timskega in medpredmetnega poučevanja se je izkazala vživijo v takratni način življenja in ga primerjajo s sodobnim ter kot dobra, ker so dijaki s tem razširili svoje znanje in uvideli razumejo vpliv nekega zgodovinskega pojava na nadaljnji razvoj. uporabnost znanja zgodovine z uporabo avtentičnega pisnega Obenem so spoznali, da se matematika skozi stoletja ni gradiva v vsakdanjem življenju. spreminjala. Še več, ugotovili smo, da so Močnikove definicije Tako zasnovan pouk je odlična izbira za poglabljanje in izreki popolnoma enakovredni tistim, ki so zapisani v učnih tem. Dijaki nas velikokrat sprašujejo, kje bodo to znanje sodobnih učbenikih. potrebovali. Spoznali so, da lahko pridobljena znanja uporabijo, v kolikor se srečajo s starejšim gradivom, kjer je medpredmetno poznavanje vsebin še kako potrebno. Načrtovanje medpredmetnega in timskega poučevanja je sicer za profesorje zahtevnejše in časovno daljše, saj je potrebne več priprave kot pri običajnem pouku, so pa zato rezultati toliko boljši in znanje trajnejše. 6 LITERATURA IN VIRI [1] Močnik, F. 1885. Aritmetika za učiteljišča, Ljubljana. Dostopno na naslovu http://nl.ijs.si/ahlib/dl/FPG_00195-1885.html (20. 10. 2020). [2] Cohen, E. G. 1994. Designing Groupwork: Strategies for the Heterogeneous Classroom. New York, London: Teachers College Press, Columbia University. [3] Prirejeno po: Ravnihar, D., Učinkovito skupinsko delo v razredu. Dostopno na naslovu http://www.bcnaklo.si/fileadmin/projekti/mednarodni/tuji_jeziki/Irska_m arec_2016/Ravnihar_Darja_Ucinkovito_sk upinsko_delo_v_razredu.pdf Slika 7: Evalvacija. (2.7.2019). [4] Smernice, načela in cilji posodabljanja učnih načrtov (2007). Ljubljana: Zavod RS za šolstvo. [5] Učni načrt. Matematika. Splošna, klasična in strokovna gimnazija. 2008. Dostopno na naslovu http://eportal.mss.edus.si/msswww/programi2010/programi/media/pdf/un _gimnazija/un_matematika _gimn.pdf (20. 10. 2020). [6] Učni načrt. Slovenščina. Splošna, klasična in strokovna gimnazija. 2008. Dostopno na naslovu http://eportal.mss.edus.si/msswww/programi2018/programi/media/pdf/un _gimnazija/un_slovenscina_gimn.pdf (20. 10. 2020). [7] M. Rugelj, J. Šparovec, G. Pavlič, D. Kavka, 2018. Linea Nova: Učbenik za matematiko za 1. letnik gimnazije, Modrijan Izobraževanje, Ljubljana. 537 Uporaba aplikacije Genially v 2. razredu osnovne šole The use of application Genially in 2nd grade of elementary school. Martina Nediževec Osnovna šola n. h. Maksa Pečarja Ljubljana, Slovenija martina.nedizevec@guest.arnes.si POVZETEK infographic, gamification, interactive images, videos, etc. Some examples that were used during distance learning in second V času šolanja na daljavo smo učitelji ves čas iskali drugačne grade of primary school are presented. Examples are arranged načine poučevanja v veliki želji, da bi se čim bolj približali according to which part of the lesson they can carried out: učencem in jih hkrati uspešno pripeljali do usvojenih znanj na introductory, main or final part. An example of interactive koncu šolskega leta. Pri tem smo se močno oprli tudi na images has been added, which was designed to diversify the sodobno tehnologijo. Informacijsko-komunikacijska tehnologija lesson. je danes dostopna skoraj vsakomur in je postala (sploh v času With regular use of Genially, we always find that the app is šolanja na daljavo) nepogrešljiv pripomoček v vzgojnem- a graet motivational tool, as students have fun using it and learn izobraževalnem procesu. a lot of new things at the same time. V prispevku je predstavljeno interaktivno orodje Genially, saj se je izkazalo kot eden najbolj uporabnih pripomočkov, ki KEYWORDS nam ponuja kar nekaj možnosti za ustvarjanje. Lahko Application Genially, ICT, interactive, tools, pupils, distance uporabimo »klasično« predstavitev, infografiko, igrifikacijo, learning interaktivno sliko, videoposnetke itd. Predstavljenih je nekaj primerov, ki so bili uporabljeni v času šolanja na daljavo v drugem razredu osnovne šole. Primeri so razporejeni glede na 1 UVOD to, v katerem delu učne ure jih lahko izvedemo: uvodnem, Informacijsko-komunikacijska tehnologija (IKT) se je v šolstvo osrednjem ali zaključnem delu. Dodan je še primer interaktivne postopoma uvajala že kar nekaj let. V trenutnih razmerah slike, ki je bila izdelana za popestritev učne ure. koronavirusa pa marsikomu dano znanje ni več zadoščalo, saj Pri redni uporabi aplikacije Geniallya vedno znova so se v procesu izobraževanja pojavile zahteve po hitrih ugotavljamo, da je aplikacija odlično motivacijsko orodje, saj se spremembah oz. prilagoditvah za lažjo izvedbo učenja na učenci pri njeni uporabi zabavajo in hkrati naučijo veliko daljavo. Pri tem smo si učitelji pomagali z različnimi programi, novega. ki so omogočili poučevanje z različnimi interaktivnimi učnimi vsebinami. KLJUČNE BESEDE Z uporabo IKT-ja je pouk bolj dinamičen, zanimiv, raznolik Aplikacija Genially, IKT, interaktivno, orodje, učenci, šola na … Učitelje spodbuja k izboljšanju poučevanja v razredu, saj s daljavo sliko, videom, zvokom in z različnimi animacijami bolj pritegnejo pozornost učencev pri šolskem delu. ABSTRACT Med IKT-tehnologijo sodi tudi aplikacija Genially, ki je za During distance learning, teachers are constantly looking for učence lahko dober motivacijski element pri učenju različnih different ways of teaching in a great desire to get as close as vsebin, učitelju pa program omogoča drugačen način podajanja possible to students and at the same time successfully bring teoretičnih snovi, preverjanja ter utrjevanja znanja. Z njo smo si them to the acquired knowledge at the end of the school year. v času šolanja na daljavo močno olajšali delo. They also relied heavily on modern technology. Today, information and communication technology is accessible to almost everyone and has become (especially during distance 2 INFORMACIJSKO-KOMUNIKACIJSKA learning) an indispensable tool in the educational process. TEHNOLOGIJA (IKT) The article presents the interactive tool Genially, as it has been selected as one of the most useful accessory, offering us Živimo v obdobju, ko družbene, gospodarske, izobraževalne in some options for creating. You can use a »classic« presentation, vzgojne potrebe zahtevajo prisotnost tehnologije. Danes se računalniki in druga informacijska tehnologija uporabljajo v vseh delovnih okoljih in na vseh področjih [1]. 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 Informacijsko-komunikacijska tehnologija (v nadaljevanju distributed for profit or commercial advantage and that copies bear this notice and IKT) je skupen izraz različnih računalniških, informacijskih in 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). komunikacijskih naprav, ki so postale naš vsakdanji Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia spremljevalec [2]. Najbolj nepogrešljiv pripomoček pa je © 2021 Copyright held by the owner/author(s). zagotovo postala v času šolanja na daljavo. 538 Uporaba IKT ima v procesu učenja kar nekaj prednosti: Ne glede na to, kaj izberemo, pa lahko pri vsaki izbrani • izboljšanje informacijske pismenosti, predstavitvi z lastno vneseno vsebino po želji menjamo barve, • povečanje storilnosti učiteljev, spreminjamo sličice, po svoje oblikujemo zapise, dodajamo • izboljšanje dostopa do informacij, interaktivne gumbe, glasbo ali videoposnetke. • motiviranje učencev, • podpora sodobnim pedagoškim pristopom [3]. Zelo je pomembno, da nas pri izbiri IKT-ja vodi učni cilj, ki 4 UPORABA APLIKACIJE GENIALLY PRI ga želimo doseči, predznanje učencev, njihovi interesi ter POUKU starost otroka. Osredotočeni moramo biti tudi na to, da je Pred pričetkom dela je smiselno preveriti znanje učenca (v program pri pedagoški uri uporaben, kakovosten in za učence drugem razredu OŠ tudi staršev) o uporabi aplikacije. Šele ko čim bolj zanimiv. dobimo vpogled, kakšna je situacija pri posameznem učencu, Učitelj si mora pred uporabo novega orodja zastaviti lahko načrtujemo izvedbo pouka. Pri samostojnem delu je naslednja vprašanja: pomembno, da podamo jasna, konkretna navodila in da učence • kako bo orodje pripomoglo k uresničevanju učnih ciljev, vodimo pri njihovem delu na način, da sprotno preverjamo • kakšne funkcije ponuja orodje, njihovo delo in jim dajemo redne povratne informacije, ki bodo • kako ob njegovi uporabi spremljati sodelovanje in napredek učencu omogočale napredovanje po njihovih zmožnostih [7]. učencev, Predstavljeni so raznoliki primeri v drugem razredu OŠ, ki • kako poiskati ustrezne in prilagojene naloge, jih lahko uporabimo pri uvodnem, glavnem in zaključnem delu • kakšni so interesi učencev in prednosti uporabe [4]. pedagoške ure. Dodan je tudi primer za popestritev ure kar tako. Predstavljeno interaktivno orodje Genially je zagotovo eno izmed tistih, ki tem ciljem in postavljenim vprašanjem zelo 4.1 Uvodni del ure dobro sledi. Učna tema: Vrste koledarjev Učni cilj: 2 KAJ JE GENIALLY? • učenec spozna različne vrste koledarjev. Na spletni strani Genially je navedeno, da je Genially interaktivno izobraževalno orodje za učenje in poučevanje [5]. Aplikacija nam ponuja različne možnosti pri ustvarjanju: • Predstavitev. Nanizanih je ogromno predlogov, ki vsebujejo različne teme. Izbrani predlog lahko potem po svoje dopolnjujemo oz. oblikujemo. • Infografika. Vizualno predstavitev podatkov in informacij prikazuje na način, da si jih hitreje zapomnimo in tudi lažje razumemo. • Igrifikacija. Genially lahko uporabimo tudi za ustvarjanje interaktivnih iger od kvizov do sob pobega. Igre so Slika 1: Vrste koledarjev popestrene z različnimi animacijskimi vložki. • Interaktivna slika. Slika nam služi za ozadje. Z Aplikacija Genially je bila uporabljena kot videoposnetek pri interaktivnimi gumbi lahko dodamo besedilo, glasbo, video uvodni motivaciji. V predstavitev je vključenih veliko fotografij itd. različnih koledarjev. Ob ogledu videoposnetka učence na • Videopredstavitve. Z aplikacijo Genially lahko ustvarimo zanimiv način popelje v novo snov o koledarjih. videoposnetek z različnimi animacijskimi vložki. Povezava: • Interaktivni digitalni vodnik. Ustvarjamo zanimive https://view.genial.ly/610677986fd52b0ddcd8856e/video interaktivne in animirane vodnike. -presentation-genial-videopresentation • Ostala interaktivna gradiva za ustvarjanje [6]. Genially je preprosto in zanimivo motivacijsko orodje za 4.2 Osrednji del ure učence. Učitelji ga uporabljamo za uvodno motivacijo, 4.2.1 Primer 1 samostojno delo, usvajanje nove snovi, ponavljanje in Učna tema: Učenje nove pesmi utrjevanje ali pa le za popestritev pouka. Učna cilja: • učenec samostojno in doživeto poje ljudsko pesem, 3 KAKO ZAČETI? • poje doživeto, upošteva glasno, tiho in počasnejše, hitrejše izvajanje. Najprej obiščemo spletno stran https://genial.ly, kjer se prijavimo in ustvarimo svoj račun. Nato kliknemo na “create genially”. Na tej strani se odprejo različne možnosti, ki jih Genially ponuja (predstavitve, infografika, igrifikacija …). Vsaka izbrana možnost nam ob kliku ponuja veliko idej, med katerimi lahko izbiramo. Naša naloge je le še, da se odločimo za eno, ki nas najbolj zanima, in začnemo ustvarjati. 539 • razlikuje desetiške enote in razume odnose med njimi (enice, desetice in stotice), • določi predhodnik in naslednik danega števila, • oblikuje in nadaljuje zaporedja števil. Slika 2: Marko skače V predstavitvi so poleg besedila dodane atraktivne slike, videoposnetek pesmi ter spletni program Song Maker, s pomočjo katerega so učenci lahko sledili melodiji in hitrosti tempa. Učenci so se po predstavitvi z interaktivnimi puščicami Slika 4: Mavrična števila sami premikali naprej. Na zadnji strani so se s puščico lahko vrnili na začetek in pesem po potrebi ponovili. Povezava: Kviz lahko uporabimo za ponavljanje in utrjevanje snovi. https://view.genial.ly/5ffc258c1ac90d0d0daf6fd7/presenta Učenec mora med tremi odgovori izbrati pravega. Če izbere tion-marko-skace pravilno, ga kviz za večjo motivacijo nagradi z zanimivo interaktivno sliko (nekaj predlogov program ponudi že sam). 4.2.2 Primer 2 Vsako vprašanje ima tudi svojo barvo (na levi strani utripa Učna tema: Življenjska obdobja kvadratek z določeno bravo). Kviz je končan, ko se zamenjajo Učna cilja: vse barve, temu primerno je izbran tudi naslov kviza Mavrična • učenec se seznani z različnim življenjskim obdobjem ter števila. usvoji nove pojme: dojenček, otroštvo, mladost …, Povezava: • časovno opredeljuje in pojasnjuje dogodke in spremembe v različnih življenjskih obdobjih. https://view.genial.ly/606d7b3158a44c0d6370fc5f/intera ctive-content-stevila-do-100 Primer 2 Učna tema: Letni čas zima Učni cilj: • učenec ponovi in utrdi pojme o letnem času zima. Slika 3: Življenjska obdobja Časovnica je bila uporabljena za temo življenjska obdobja kot osrednji del ure. Vsako sličico so učenci poimenovali, odgovor pa preverili s klikom na interaktivni gumb, ki je pripet nad vsako fotografijo. Slika 5: Skrita slika Ta primer bi lahko uporabili tudi kot motivacijski uvodni del ure ali kot ponovitev teme pri zaključnem delu. Tudi pri tem kvizu učenci med tremi odgovori izberejo pravega. Povezava: Z vsakim pravilnim odgovorom se na levi strani odkrije del slike. Na koncu kviza so nagrajeni z zanimivo sliko o izbrani https://view.genial.ly/610bfb502ac9b70dad1ea97b/intera tematiki. ctive-content-terrazzo-timeline S kvizom so temeljito obnovili znanje o letnem času zima. 4.3 Zaključni del ure Povezava: https:/ view.genial.ly/5fdcb49c60e6a00cfc74c12c/learning- Primer 1 experience-challenges-zima Učna tema: Naravna števila do 100 Učni cilji: • učenec šteje in bere števila do 100, 540 Primer 3 Učna tema: Usvajanje različnih naravnih oblik gibanja, iger in športnih znanj. Učni cilji: • učenec sproščeno izvaja naravne oblike gibanja; • izboljšuje gibalne in funkcionalne sposobnosti: skladnost (koordinacijo) gibanja, moč, hitrost, gibljivost, natančnost, ravnotežje, splošno vzdržljivost; • oblikuje pozitivne vedenjske vzorce (strpno in prijateljsko vedenje v skupini, upoštevanje pravil v igrah in športnega obnašanja, odgovorno ravnanje s športno opremo, odgovoren odnos do narave in okolja). Slika 7: Praznične želje 5 ZAKLJUČEK V prispevku sem nanizala le nekaj idej, ki jih lahko uporabimo z aplikacijo Genially. Želela sem prikazati različne načine uporabe pri pouku v drugem razredu osnovne šole. Vsi predstavljeni programi so bili s strani tako učencev kot staršev zelo dobro sprejeti. V času šolanja na daljavo pa to ni bil edini način posredovanja znanja – za poučevanje sem uporabila tudi drugačne pristope. Je pa aplikacija Genially zagotovo ena Slika 6: Olimpijske igre izmed boljših za motiviranje učencev. Pomembno je poudariti, da s takim načinom poučevanja tudi rezultati niso izostali, V aplikaciji je že bila dana predloga tekmovalne steze, kjer se preverjanja znanja na koncu šolskega leta so bila precej odvijajo olimpijske igre. Dodana je bila država Slovenija in uspešna. himne držav, ki tekmujejo. V desnem zgornjem kotu je bila tudi že postavljena interaktivna kocka, ki se ob kliku sama zavrti. ZAHVALA Tekmovalci izberejo državo, ki jo želijo zastopati, in se z Posebna zahvala gre hčerki Gaji, saj mi je bila v času šolanja na izbrano barvo razporedijo pred startom. Če tekmovalec pride na daljavo v veliko pomoč pri usvajanju osnovnih znanj pri črno (interaktivno) število, dobi ob kliku športno nalogo, ki jo uporabi IKT-ja. mora opraviti pred nadaljevanjem igre. Zmaga tisti igralec, ki Zahvalila bi se tudi aktivu učiteljic drugega razreda na OŠ prvi pride do cilja. Na cilju je njegova zmaga nagrajena s himno n. h. Maksa Pečarja. Med seboj smo ves čas sodelovale, se države, ki jo je zastopal. bodrile in si močno pomagale v času, ki je bil za vse nas precej Povezava: nov in nenavaden. https://view.genial.ly/6106f22f1a3eec0dd59f5966/interac tive-content-untitled-genial y LITERATURA IN VIRI [1] Tomas Tišler. 2006. Spodbujanje uporabe informacijsko-komunikacijske 4.4 Del ure za popestritev tehnologije na osnovni šoli. V Vodenje za spodbujanje informacijsko- komunikacijske tehnologije na šolah. Ljubljana: Šola za ravnatelje. Dostopno na naslovu https://solazaravnatelje.si/ISBN/961-6637-04-5.pdf Primer 1 (4. 8. 2021) Učna tema: Voščimo [2] Darjo Zuljan. 2014. Tehnološka pismenost v obdobju zgodnjega učenja, Učna cilja: Koper. Univerzitetna založba Annales [3] Jože Rugelj. 2007. Nove strategije pri uvajanju IKT v Izobraževanje. • učenec ve, da imajo nekateri dnevi v letu (prazniki) Dostopno na naslovu poseben pomen, in pozna poseben pomen različnih https://skupnost.sio.si/sio_arhiv/sirikt/www.sirikt.si/fileadmin/sirikt/pred stavitve/2007/SIRIKT_2007_JRugelj.pdf (5. 8. 2021) praznovanj, [4] Irena Gole in Mateja Hadler. 2015. Učenje s tablicami na razredni • ob praznikih ustrezno vošči. stopnji. Primeri iz prakse. V Kaj nam prinaša e-Šolska torba, Zbornik zaključne konference projekta e-Šolska torba, Ljubljana. Zavod RS za Interaktivna slika je bila uporabljena za novoletne želje. Najprej šolstvo. Dostopno na naslovu https://www.zrss.si/digitalnaknjiznica/kaj- izberemo sliko za ozadje, nato pa poljubno nanizamo nam-prinasa-esolska torba/files/assets/basic-html/index.html#1 (5. 8. interaktivne gumbe. Učenci so se ob klikih zabavali z 2021) [5] Spletna stran programa Genially. Dostopno na naslovu nenavadnimi, smešnimi fotografijami učiteljice, ki jim na https://genial.ly/education/ (5. 8. 2021) različne načine vošči ob prazniku. Fotografije so bile posnete s [6] Spletna stran programa Genially. Dostopno na naslovu https://app.genial.ly/create (5. 8. 2021) pametnim telefonom s programom YouCamFun. [7] Miroslava Minić. 2020. Veščine poučevanja na daljavo in praktični Povezava: nasveti. Mednarodna konferenca o prenosu tehnologij z Vivid 2020, 5.– 9. oktober 2020. Dostopno na naslovu https://view.genial.ly/5fe33ae56157fe0d6919263d/intera http://library.ijs.si/Stacks/Proceedings/InformationSociety/2020/IS2020_ ctive-image-praznicne-zelje Complete.pdf (10. 8. 2021) 541 Varna raba spleta za učence z učnimi težavami Safe use of the internet for students with learning difficulties Jure Ozvatič OŠ Draga Kobala Maribor, Slovenija jure.ozvatic@gmail.com POVZETEK negative actions. Pupils with lower cognitive abilities and learning difficulties also have poorer general education and Uporaba svetovnega spleta je med uporabniki v zadnjih letih knowledge about the use of smart mobile devices and especially močno narasla, še posebej med mladimi. Ti so med najbolj the Web. This makes them a fairly susceptible group for online dovzetnimi za novosti na tehničnem in družbenem področju. S scammers as they do not know their forms and ways of working. pametnimi mobilnimi napravi, ki so v zadnjih letih postale tudi Educating children with learning disabilities about the safe use dokaj cenovno dostopne, se je uporaba svetovnega spleta močno of the web in a timely manner is therefore crucial. With the help povečala. Velik delež tega predstavljajo družabna omrežja, of teachers, parents and professionals, they will be able to igranje videoiger, objavljanje lastnih fotografij, posnetkov in drugih informacij. Mladi pogosto s premalo znanja in veščinami successfully protect themselves in their work with the Internet (ne)kritično uporabljajo različne aplikacije, komunikacijo preko and become aware of the elements of safe use of the Internet. družabnih omrežij, izmenjavanje in objavljanje posnetkov, fotografij in drugih podatkov. Pogosto ne znajo ločevati med KEYWORDS resničnimi ali lažnimi identitetami sogovornikov, ki jih skušajo Information technology, students with learning difficulties, safe na različne načine izkoriščati za negativna dejanja. Učenci s use of the Internet slabšimi kognitivnimi sposobnostmi in učnimi težavami imajo tudi slabšo splošno poučenost in vedenje o uporabi pametnih mobilnih naprav in predvsem spleta. S tem postajajo dokaj lahka 1 UVOD skupina za spletne prevarante, saj ne poznajo njihovih oblik in načinov dela. Za varno rabo spleta je zato ključno, da se otroke z Pridobivanje informacij je z razširitvijo svetovnega spleta učnimi težavami pravočasno izobražuje o tej tematiki. S pomočjo postalo vsakdanje in dokaj preprosto. Pri tem ljudje uporabljajo učiteljev, staršev in strokovnjakov se bodo tako uspešno zaščitili različne pametne naprave – računalnike, tablice, igralne konzole pri svojem delu s spletom in postali pozorni na elemente varne in pametne mobilne telefone. Vsaka naprava od njih zahteva rabe spleta. določeno stopnjo znanja za njeno varno uporabo. Mnoga podjetja najdejo tržno nišo ravno med mladimi, ki pogosto spremljajo KLJUČNE BESEDE nove tehnične izdelke in jih nato kupujejo. Množičen porast Informacijska tehnologija, učenci z učnimi težavami, varna pametnih mobilnih naprav je prispeval tudi k množični uporabi uporaba spleta spleta, pri tem se porajajo različni vidiki pravilne in varne uporabe. Mladi običajno dokaj hitro osvajajo nove aplikacije in ABSTRACT spletne novosti, a se pogosto premalo zavedajo celovitosti The use of the Internet has risen sharply among users in recent (prekomerne) uporabe omenjenih tehnologij. Ena izmed teh je years, especially among young people. These are the most tudi varnost in varna uporaba osebnih podatkov pri delovanju na susceptible to technical and social innovations. With smart spletu s pametnimi mobilnimi napravami. Učenci z učnimi mobile devices having become quite affordable in recent years, težavami so še posebej ranljiva skupina, saj imajo premalo the use of the World Wide Web has increased dramatically. A znanja o celovitem delovanju in varnosti pri uporabi spleta in large part of this are social networks, playing video games, pametnih mobilnih naprav, kar jih lahko nehote sooča z posting photos, videos and other information. Young people with negativnimi posledicami. insufficient knowledge and skills often (un) critically use various applications, communicate via social networks, share and publish recordings, photos and other data. They often do not 2 INFORMACIJSKA TEHNOLOGIJA V know how to distinguish between true or false identities of their VZGOJI IN IZOBRAŽEVANJU interlocutors, who try to exploit them in various ways for Informacijska tehnologija je v nekaj desetletjih močno zaznamovala naše življenje na vseh ravneh, saj je v procesih 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 vzgoje in izobraževanja zelo pomembna z vidika omogočanja for profit or commercial advantage and that copies bear this notice and the full kvalitetne in učinkovite podpore pri pouku. Tovrstna tehnologija 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). je postala finančno dostopna za široko uporabo, njeno uvajanje v Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia izobraževalne vsebine in učne načrte kot del načrtov v šolah pri © 2021 Copyright held by the owner/author(s). različnih evropskih državah [1]. Z omenjeno tehnologijo učenci, pedagoški delavci in ostali strokovnjaki uporabljajo gradivo na 542 spletu, ga urejajo, objavljajo in delijo s širšo družbo. Veliko 3 UČENCI Z UČNIMI TEŽAVAMI IN informacij zahteva tudi, da se nauči tovrstne informacije ločevati, UPORABA INFORMACIJSKE ovrednotiti in jim zaupati. Pri tem je potrebno pokazati dovolj TEHNOLOGIJE znanja in veščin, da se nauči postati informacijsko opismenjen, saj lahko v nasprotnem primeru pride do informacij, ki so S specializacijo znanj in diferenciacijo poklicev se je v šolstvu nezanesljive, napačne ali težko preverljive [10]. uspelo učence, ki imajo učne težave, ustrezno diagnosticirati in Pri pouku je tovrsten način še posebej pomemben, saj morajo strokovno določiti njihove primanjkljaje, da bi lažje in s mladi v procesu pridobivanja znanja pridobiti veščine za pravilno strokovno pomočjo uspešneje premostili učne težave. Omenjeni uporabo informacijske tehnologije. V zadnjih letih so v šolah učenci imajo različne vrste primanjkljajev in so posledično učno učitelji začeli uporabljati za dopolnjevanje učnih vsebin gradiva manj uspešni, saj glede na vrstnike počasneje usvajajo znanja in z interaktivnimi viri. Pri tem mladi pridobivajo večjo motivacijo spretnosti pri učnih predmetih. Posledično sta njihov učni uspeh in izkušnje pri učenju. Svetovni splet, interaktivni viri in in rezultat slabša. Učne težave se lahko pri učencih kažejo kot aplikacije z izobraževalnimi gradivi omogočajo učiteljem, da posledica prepleta dejavnikov, ki vplivajo na učenčevo šolsko ponudijo možnosti za učinkovito učenje in večje vključevanje delo – podpovprečne in mejne intelektualne sposobnosti, slabše samih učencev v izobraževalni proces. Učitelji spodbujajo rabo razvite samoregulacijske sposobnosti, težave v socialno- tehnologije pri učencih ter jih tako učijo pravilnih pristopov pri emocionalni akomodaciji, primarni socialno-kulturno-jezikovni iskanju informacij, analiz, oblikovanju rešitev ter učinkoviti drugačnosti, socialni in kulturni deprivaciji oz. izoliranosti, komunikaciji. Prednosti uporabe učnih gradiv v izobraževalne pomanjkanju motiviranosti za delo. Učne težave vplivajo na namene omogočajo učencem pri prejemanju informacij, saj pri nekatere ali mnoge vidike posameznikovega življenja tem uporabljajo multisenzorne načine učenja, prilagajanje (izobraževanje, delo, interakcije v družini, socialnem okolju) ter individualnim potrebam učencev; raznovrstno predstavljanje se kažejo v različnih pogledih. Primanjkljaji se med seboj učne snovi; uporabo mobilnih naprav pri učenju, saj so zelo vpete prepletajo ali so ločeni ter vplivajo na učno delo in na samo v vsakdanje življenje. Samo učenje s pomočjo pametnih življenje. Dražljajev in informacij iz okolice ne sprejemajo, mobilnih naprav in spleta se nanaša na načine, ko se uporablja analizirajo in nanje ne reagirajo enako kot sovrstniki, zato so omenjena tehnologija hkrati s spodbujanjem učenja [6]. Rezultati nekatere poti učenja ovirane. Učinkovitosti sprejemanja in raziskav so pokazali, da uporaba informacijsko-komunikacijske izražanja informacij so zaradi kognitivnih primanjkljajev na tehnologije v podporo učnemu okolju pozitivno vpliva na učenje nekaterih področjih zmanjšane. Na teh področjih se zato težko [1]. Med mladimi je prvi vir informacij ter najpogosteje učijo na tradicionalen način in s hitrostjo, ki je sprejemljiva za uporabljena tehnologija v učne namene računalniška in njihove vrstnike [5, 7]. informacijska tehnologija [8]. Pri pouku se uporaba Nekateri med njimi z različnim oblikami pomoči (dopolnilni informacijske tehnologije razlikuje med oblikami in metodami pouk, individualna in skupinska pomoč, dodatna strokovna dela. Zaradi različnih učenčevih sposobnosti se po potrebi izvede pomoč) pridobijo možnost za premostitev svojih primanjkljajev. diferenciacijo z dodatno razlago ali dodatnimi nalogami [2]. V zadnjih letih se je s pomočjo procesov integracije in inkluzije Uporaba elektronskih gradiv je za učenje smiselna, ko z tem učencem pomagalo, da so kljub težavam uspešnejši in njeno uporabo dosežemo časovno racionalizacijo, boljše pozitivno sprejeti med vrstniki in v samo šolsko okolje. S tem se rezultate pri učenju in preverjanju doseženega znanja. Tovrstni pozitivno vpliva na njihovo samopodobo in učne rezultate. Z način se razlikuje od pouka v živo, zato je bilo potrebno uporabo pametnih mobilnih naprav in računalnikov so tudi otroci predhodno določiti cilje in načine podajanja učne snovi, s posebnimi potrebami bolje motivirani za učenje, usvajanje ter načrtovati izvedbo, pripraviti ustrezna e-orodja v učnem okolju pomnjenje znanja. Spletne vsebine, orodja in spletne aplikacije ter samovrednotiti dosežke in pridobljeno znanje [9]. Učenci, ki omogočajo dinamično, nazorno, dostopnejše, multisenzorno imajo nižje sposobnosti, potrebujejo smiselno sestavljene naloge, podajanje informacij, ki so za učence zanimive in privlačne. S prilagojene težavnostnim stopnjam, da vsebujejo dovolj tem bolje procesirajo, obdelajo vsebino in njihovo pomnjenje [7]. podpornega konkretnega slikovnega gradiva ter animacij (še Učitelji učencem z učnimi težavami in premajhno posebej so poučne pri možnostih ponovitve in korigiranju vključenostjo v razred nudijo oporo pri vključevanju v razredno hitrosti). Spletne strani z učno vsebino, ki omogočajo spletne okolje, aktivnosti, pouk ter upoštevajo njihove primanjkljaje. povezave z navezovanjem na sorodne vsebine, učencem Med šolami prihaja do različnih spodbujanj motiviranosti spodbudijo željo po spoznavanju novih informacij, hkrati pa jih učiteljev za poučevanje in motiviranosti otrok za učenje [4]. učijo pravilne uporabe informacijsko-komunikacijske tehnologije [9]. Učenci z učnimi težavami pri uporabi spletnih didaktičnih 4 NEGATIVNI VIDIKI UPORABE orodij in strani prejmejo sebi prilagojene informacije, tako da INFORMACIJSKE TEHNOLOGIJE MED bodo učno snov bolje memorirali ter usvojili. Na spletu obstajajo MLADIMI različna spletna orodja za utrjevanje, ponavljanje in podajanje V vzgoji in izobraževanju so se tekom zadnjih desetletij zgodile učnih vsebin. S temi orodji pridobijo znanje na zanimiv in pomembne spremembe pri uporabi novih oblik gradiv, materiala razgiban način ter omogočajo pot k samostojnemu pridobivanju in pripomočkov. S pametnimi mobilnimi napravami so se iskanja informacij ter nadgraditve obstoječega znanja. Z uporabo nekatere učne vsebine učencem približale, konkretizirale ter se je spletnih orodij so bolje motivirani, aktivni, zavzeto rešujejo olajšal dostop do informacij. Prekomerna uporaba spleta in naloge, abstraktne vsebine bolje konkretizirajo ter si jih informacijske tehnologije škoduje fizičnemu, psihološkemu in zapomnijo. S tem je proces memoriranja podatkov, ki učencem emocionalnemu stanju, pojavljajo se odvisnosti in odklonski povzroča težave in nemotiviranost, učinkovitejši in trajnejši. vedenjski vzorci. Ena izmed posledic prekomerne uporabe je tudi 543 pomanjkanje socialnega stika ter odnosov, ki so del človeške pomembno, da vršijo nadzor nad otroki, da sproti preverjajo, družabne narave. Pri tem se vzpostavlja navidezne socialne katere spletne strani in aplikacije na mobilnih napravah odnose preko elektronskih medijev in družabnih omrežij, ki pa uporabljajo, ter jim sprotno razlagajo elemente varnosti pri pogosto prikrivajo realno stanje in odnose med ljudmi. .Mladi in uporabi spleta [12]. tudi odrasli so lahko izpostavljeni raznim prevarantom, ki od njih Izobraževanje učencev za pravilno ter varno uporabo zaradi pomanjkanja tovrstnega znanja pridobijo njihove osebne spleta sovpada tudi z izobraževanjem staršev in pedagoških podatke, možnosti zlorab fotografij in podatkov, ki jih delijo na delavcev, saj so oboji povezani z učenci. S svojim znanjem in spletu. Ena izmed spletnih strani, ki se ukvarja z varno rabo veščinami pomagajo pri vzgoji in izobraževanju mladih, kako spleta, je tudi www.safe.si. Po njenih podatkih se je v zadnjih 10 primerno svetovati mladim pri uporabi spleta. Prav tako je za letih uporaba mobilnih naprav zelo povečala, tako da je bilo v mlade pomembno, da v primeru težav zaupajo odraslim in tako svetu v uporabi že več kot 10 milijard mobilnih naprav (pametni najdejo ustrezne rešitve. Mlajši otroci potrebujejo nadzor pri mobilni telefon, prenosni računalnik, tablica). Obširna raziskava uporabi spleta. Odrasli jim prikažejo lastnosti varnih spletnih Mladi na netu 2010 je pokazala, da ima svoj mobilni telefon 93 strani, varne načine komuniciranja, uporabe strojne in % otrok in mladostnikov med 8 in 18 letom; delež uporabnikov programske opreme, varovanja osebnih podatkov in splošnih mobilnih naprav za dostop do interneta je bil največji med informacij [11]. osebami, starimi od 16 do 24 let, in sicer je obsegal 74 %, in Mnoge izobraževalne spletne strani nudijo izobraževalne osebami, starimi od 10 do15 let (54 %). Mladi zelo sprejemajo vsebine, pri tem vključujejo animacije, videoposnetke, napredek pri tehničnih novostih, saj se z naraščanjem didaktične igre, možnosti praktičnih predavanj, izvedbo zmogljivosti pametnih telefonov spreminjajo tudi njihove seminarjev in izobraževalne teme za odrasle. Vse to je zelo navade. Tako je raziskava Mladi na netu 2010 pokazala, da 63 % pomembne za otroke z učnimi težavami, saj je njihovo splošno mladih med 8 in 19 letom v Sloveniji kot glavni vir iskanja razumevanje in dojemanje nevarnosti pri uporabi spleta premalo podatkov na svetovnem spletu uporablja mobilni telefon. zaznavno. Ne zavedajo se spletnih pasti in negativnih posledic Negativne posledice uporabe omenjene tehnologije se kažejo pri uporabi spleta pri svojem delu, saj imajo poenostavljene tudi pri nepoznavanju skritih pasti, saj se je 29 % slovenskih poglede na tovrstno problematiko in ne poznajo elementov za otrok in mladih, starih od 11 do 19 let, že slikala brez oblek in prepoznavo (ne)varnih spletnih strani. Za varno rabo spleta je pri sliko posredovala po družabnih omrežjih. Pri tem so fantje bolj njih potrebno več časa, da lahko dojamejo obsežnost uporabe izpostavljeni tveganjem kot dekleta (43 % fantov je prek spleta in pametnih mobilnih naprav, saj imajo tudi slabšo splošno mobilnega telefona že poslalo svojo sliko brez obleke, to pa je poučenost in premalo informacij o morebitnih spletnih storilo 14 % deklet) [12]. nevarnostih. Tako lahko pri iskanju informacij preko spleta nevede zaidejo na lažne spletne strani, ki zahtevajo določene osebne podatke pri nadaljnjem pridobivanju informacij. Ne 5 VARNA RABA SPLETA PRI UČENCIH poznajo določenih certifikatov ali spletnih digitalnih identitet, ki Evropske institucije, ki skrbijo za varstvo osebnih podatkov, zagotavljajo določeno stopnjo varnosti. V družabnih omrežjih v svojem poročilu (Mnenje 2/2009 Delovne skupine iz člena 29) večkrat naivno nasedejo sogovorcem pri izmenjavi osebnih izpostavljajo, da mladoletne osebe in tudi nekateri odrasli, ki še podatkov ali celo pri pošiljanju fotografij ali finančnih sredstev, niso dosegli fizične in psihološke zrelosti, potrebuje več zaščite kjer spletni goljufi s pridom izkoristijo njihovo zaupljivost in kot ostali. To je še posebej pomembno pri uporabi spleta in nevednost. Učenci in tudi nekateri odrasli pri brskanju po spletu pametnih mobilnih naprav, saj je treba posredovati znanje o najdejo reklame, oglase, ki ponujajo senzacionalne ali enostavne zasebnosti pri uporabi novih tehnologij v vsaki fazi otrokovega rešitve, vendar je v resnici v ozadju zgolj nepošteno pridobivanje izobraževanja. Z odraščanjem, izobraževanjem in pridobivanjem finančnih sredstev in opeharjenje naivnih uporabnikov. socialnih stikov se pri mladih povečajo interkacije z različnimi Omenjeni mladi s svojim pomanjkljivim znanjem hitreje institucijami, ki obdelujejejo njihove osebne podatke. Pri tem je postanejo žrtve spletnih izsiljevalcev preko družabnih omrežij, potrebno imeti v obziru zaščito otrok. Pristop k varovanju saj so slednji bolje podkovani v uporabi spletne komunikacije. zasebnosti otrok mora temeljiti na izobraževanju (s pomočjo Učenci z učnimi težavami so prav tako bolj dovzetni za možnost družine, šole, organov za varstvo osebnih podatkov, skupnosti manipulacije preko uporabe spleta, pri prebiranju informacij, pri otrok in drugih) o pomembnosti varstva osebnih podatkov in igranju videoiger, gledanju videoposnetkov, saj imajo zasebnosti ter o posledicah razkrivanja osebnih podatkov, kadar pomanjkljivo znanje in nekritično distanco do omenjenih vsebin. to ni potrebno [3]. Pri tem se kasneje pokažejo negativne posledice na različnih Za varno rabo mobilnih naprav, aplikacij, spleta in ravneh, kar negativno vpliva na njihovo samopodobo in družabnih omrežij je pomembno, da se učence na primeren način psihosocialno stanje. izobražuje in predstavi njihovo uporabo. Strokovnjaki s tega področja izpostavljajo, da je to dolgotrajen proces, ki temelji na odgovornem ravnanju, izobraževanju in graditvi zaupanja med 6 ZAKLJUČEK učenci, starši in pedagoškimi delavci. V primeru težav je Uporaba mobilnih naprav in spleta prinaša mnogo pozitivnih in pomembno, da se o tem spregovori in poišče ustrezno rešitev. tudi žal negativnih posledic. Mladi, med njimi še posebej vrstniki Objava podatkov na spletu pomeni tudi, da so dostopne širšemu z učnimi težavami, veliko časa preživljajo na spletu, kjer igrajo krogu ljudi, tako da je učence potrebno seznaniti in poučiti, da videoigre, komunicirajo preko družabnih omrežij, objavljajo informacije na spletu ostanejo in se hitro širijo. S praktičnimi svoje posnetke in fotografije. Nemalokrat se pri tem premalo prikazi učence poučijo, kako informacije posredujejo oz. jih posvečajo tudi vprašanjem o varni uporabi, samemu poznavanju zavarujejo, še posebno pred nepoznanimi osebami. Za odrasle je ozadja delovanja spleta, varnega objavljanja informacij in 544 njegove uporabe. Odrasli, učitelji in starši učence skozi njihovo [5] Košir, S. idr. (2008). Navodila za prilagojeno izvajanje programa osnovne obdobje odraščanja izobražujejo in informirajo o varni uporabi šole z dodatno strokovno pomočjo. Primanjkljaji na posameznih področjih učenja. Ljubljana: Zavod Republike Slovenije za šolstvo. spleta, jim predstavljajo skrite pasti ter vzpostavitve kritičnega in [6] Lowyck, J. (2008). Foreword. V J. M. Spector idr. (ur). Handbook of zdravega odnosa do pametnih naprav in spleta. Učenci z učnimi Research on Educational Communications and Technology (3. izdaja). New York. v Mayer, R. (b l.). Učenje s tehnologijo. Santa Barbara v težavami, ki so še posebej izpostavljeni zaradi svojega šibkejšega Dumont, H., Istance, D., Benavides, F. (2013). O naravi učenja: uporaba razumevanja in vedenja uporabe spleta, potrebujejo dodatno raziskav za navdih prakse. Ljubljana: Zavod za RS za šolstvo. (Elektronski varnost, čas za izobraževanje in spoznavanje za varno delo na vir) Pridobljeno s http://www.zrss.si/pdf/o-naravi-ucenja.pdf [7] Nagode, A. (ur.) (2008). Navodila za prilagojeno izvajanje programa spletu, da bodo ohranili določeno stopnjo varovanja osebnih osnovne šole z dodatno strokovno pomočjo: primanjkljaji na posameznih podatkov. Pri tem jim pomagajo učitelji, starši in tudi sovrstniki, področjih učenja. Ljubljana: Zavod Republike Slovenije za šolstvo. [8] O’Neil, H. F. (ur.) (2005). What Works in Distance Education: Guidelines, da bodo s tem bolje opolnomočeni uporabljali to tehnologijo. Information Age Publishing. Greenwich: CT. v Mayer, R. (b l.). Učenje s tehnologijo. Santa Barbara v Dumont, H., Istance, D., Benavides, F. LITERATURA IN VIRI (2013). O naravi učenja: uporaba raziskav za navdih prakse. Ljubljana: Zavod za RS za šolstvo. (Elektronski vir) Pridobljeno s [1] Brečko, B. N.,Vehovar, V. (2008). Informacijsko-komunikacijska http://www.zrss.si/pdf/o- naravi- ucenja.pdf tehnologija pri poučevanju in učenju v slovenskih šolah. Ljubljana: [9] Rugelj, J., (2007): Nove strategije pri uvajanju IKT v izobraževanje. Pedagoški inštitut. Pridobljeno s https://skupnost.sio.si/sio_arhiv/sirikt/www.sirikt.si/ [2] Gerlič, I., Krašna, M. & Pesek, I. (2013). Informacijsko komunikacijske fileadmin/sirikt/predstavitve/2007/SIRIKT_2007_JRugelj.pdf tehnologije v slovenskih osnovnih šolah: stanje in možnosti. Maribor: [10] Wechtersbach, R. (2006). Digitalna kompetenca in njeno izgrajevanje. Fakulteta za naravoslovje in matematiko. Organizacija, 41(1). Pridobljeno s https://www.dlib.si/stream/URN: [3] González Fuster G., Kloza D. (ur.). (2016). Evropski priročnik za NBN:SI:DOC-QK8BF35D/64619a2b-798b-4117-969c-6abe861637b7/ poučevanje zasebnosti in varstva osebnih podatkov v šolah: EAP. PDF Pridobljeno s https://www.arnes.si/files/2015/10/arcades_teaching_ [11] https://www.varnostnaspletu.si/kako-naj-starsi-svojim-otrokom- handbook_final_SL.pdf zagotovijo-varno-uporabo-spleta-2-del [4] Košir, K. (2013). Socialni odnosi v šoli. Maribor: Subkulturni azil, zavod [12] https://www.varnostnaspletu.si/kako-otroke-seznaniti-z-nevarnostmi-na- za umetniško produkcijo in založništvo. spletu/ 545 Storitve šolske knjižnice v času učenja na daljavo School library services during distance learning Tina Pajnik Osnovna šola Vide Pregarc Ljubljana, Slovenija tpajnik@gmail.com POVZETEK do upeha knjižnice pri razvijanju informacijske pismenosti prilagajanje spremembam in vplivanje na spremembe. V prispevku je predstavljeno delo šolske knjižnice na Osnovni Mednarodna zveza bibliotekarskih društev in ustanov ali šoli Vide Pregarc v Ljubljani v času učenja na daljavo. Šolska IFLA v Smernicah za šolske knjižnice [2] predstavi definicijo, knjižnica je v skladu z navodili in priporočili prilagodila svoje vlogo, vizijo, poslanstvo in storitve šolske knjižnice. Šolsko storitve in jih v čim večji meri skušala prenesti v spletno okolje. knjižnico opredeljuje kot odprt in varen prostor, izobraževalno Da bi omogočila čim širši nabor knjižničnih storitev na daljavo, in informacijsko okolje, informacijski, tehnološki in družbeni odprt in varen prostor za vse uporabnike, je šolska knjižnica prostor ter center pismenosti. skrbela za dostop do besedil, izvedbo bralnih dejavnosti, Mednarodne smernice prav tako predlagajo, da storitve šolske podporo pouku, informiranje učiteljev, opravljanje bralnih knjižnice vključujejo: značk, izvajanje projekta Medgeneracijsko branje in se - strokovni razvoj za tiste, ki poučujejo, vključevala v razširjen program šole. Šolska knjižnica je z - živahne programe na področju literature/branja za uporabo različnih orodij skrbela za motivacijo bralcev in za znanstvene dosežke ter osebno zadovoljstvo in razvijanje informacijske pismenosti, ki je potekala v okviru bogatenje, medpredmetnih učnih ur. - raziskovalno učenje in razvoj informacijske pismenosti, KLJUČNE BESEDE - sodelovanje z drugimi knjižnicami. Poleg naštetih storitev pa vsaka šolska knjižnica kot učno in Šolska knjižnica, knjižnične storitve, učenje na daljavo, bralne informacijsko središče šole nudi svojim uporabnikom možnosti dejavnosti, informacijsko opismenjevanje, medpredmetne učne za razvijanje različnih vrst pismenosti z zagotavljanjem ure primerne in urejene knjižnične zbirke [3]. ABSTRACT Upoštevajoč smernice in vizijo šole, iz katere izhaja tudi vizija šolske knjižnice, ki je v prvi vrsti usmerjena v podporo oz. The paper presents the work of the school library at the Vida integracijo v vzgojno-izobraževalni proces, smo se na Osnovni Pregarc Primary School in Ljubljana during distance learning. šoli Vide Pregarc v Ljubljani soočili na eni strani s prenosom The school library adapted its services in accordance with the storitev v spletno okolje in na drugi strani z omejitvami, s instructions and recommendations and tried to transfer them to katerimi smo se srečevali z vstopom na splet. the online environment as much as possible. In order to provide Če smo šolski knjižničarji izhajali iz potreb uporabnikov, je the widest possible range of library services remotely, open and bilo potrebno razviti pristope, ki bodo čim bolj enostavni za safe space for all users, the school library took care of access to uporabo, sploh za najmlajše učence, ki so se prvič soočali z texts, reading activities, teaching support, informing teachers, digitalnim okoljem. Druga omejitev je bila izbira besedil. Šolski reading badges, implementing the Intergenerational Reading knjižničarji smo izbirali prosto dostopna elektronska besedila, project and participating in extended school program. Using besedila primerna razvojni starosti mladih bralcev, preprosta various tools, the school library took care of motivating readers besedila v tujih jezikih, besedila z ekološkimi vsebinami and developing information literacy, which took place as part of upoštevajoč avtorske pravice. Tretja omejitev, s katero smo se interdisciplinary lessons. srečevali v času izvajanja pouka na daljavo, so bile tehnične težave, kot na primer nezadostna internetna povezava, KEYWORDS preobremenitev spletnih okolij, zmogljivost in zastarelost IKT School library, library services, distance learning, reading šolske opreme. activities, information literacy, interdisciplinary lessons Prenos knjižničnih storitev v spletno okolje pa sam po sebi ni dovolj, kadar je v ospredju vzgojno-izobraževalni proces, 1 ŠOLSKA KNJIŽNICA IN UČENJE NA zato se je bilo potrebno povezovati z drugimi strokovnimi DALJAVO delavci. Večina dejavnosti se pri klasičnem pouku izvaja V šolskem letu 2020/21 se je poučevanje na daljavo za osnovne medpredmetno, saj je informacijsko opismenjevanje daljši proces, ki je vtkan v cilje različnih šolskih predmetov. S tega šole izvajalo od meseca oktobra 2020 do februarja 2021. V tem času se je za učence osnovnih šol pouk preselil v spletno okolje, vidika so šolski knjižničarji upoštevali priporočila Zavoda izvajalo se je poučevanje na daljavo. Šolske knjižnice so se Republike Slovenije za šolstvo [4], kjer je izpostavljeno, da znašle pred novimi izzivi in iskale načine, kako prilagoditi poenotenje znotraj zavoda, po predmetnih področjih in aktivih, storitve za svoje uporabnike. Kot pravi Novljanova [1], je ključ omogoča lažji proces poučevanja na daljavo. Priporočila med 546 drugim osvetljujejo tudi razlike med učenci, na katere so šolski daljavo, ki so pripomogli k učinkoviti izvedbi pouka na daljavo. knjižničarji še posebej pozorni, če želijo zagotoviti varno in Zaradi raznolikih potreb z več predmetnih področij in različnih vključujoče okolje. razvojnih značilnostih učencev je bil oblikovan elektronski Na tem mestu je vredno omeniti, da so v proces razvijanja zbirnik v Padletu, ki je vsem strokovnim delavcem omogočal, informacijske pismenosti zajeti tudi strokovni delavci šole. da so poiskali tiste informacije, ki so jih zanimale (Slika 2). Avtorji raziskave Računalniška in internetna pismenost učiteljev osnovnih šol [5] ugotavljajo, da učitelji osnovnih šol dosegajo različne stopnje računalniške in internetne pismenosti in da ravnatelj nima tolikšnega vpliva na razvoj pismenosti. Zaradi velikih razlik v stopnji računalniške in internetne pismenosti med učitelji, ki so se kazale tudi na Osnovni šoli Vide Pregarc, je bilo potrebno oblikovati tudi podporni sistem, ki je omogočal razvijanje pismenosti tistih odraslih uporabnikov, ki so se sami prepoznali kot slabše računalniško in internetno pismeni. S prenosom vzgojno-izobraževalnega procesa na splet so se odprla številna nova vprašanja in izzivi, ki smo jih šolski knjižničarji reševali postopoma. Pri delu z Slika 2: Elektronski zbirnik za učitelje v Padletu uporabniki je tudi s prehodom v spletno okolje bilo potrebno razmisliti o pestri ponudbi, tehnični podpori, varnem spletnem Poizvedovanja učiteljev so bila zelo raznolika, zato je bilo okolju in aplikacijah, ki so preproste za uporabo. potrebno dvakrat tedensko posodabljati elektronski zbirnik s 2 STORITVE ŠOLSKE KNJIŽNICE V povezavami. Na voljo so bili tudi video vodiči in navodila za SPLETNEM OKOLJU tiste učitelje, ki so se šele učili uporabljati spletna orodja. Zbirnik v Padletu je zajel oba vidika, tako podporo za učenje Šolska knjižnica Osnovne šole Vide Pregarc je v okviru kot tudi možnost za strokovni razvoj učiteljev, saj so lahko vzpostavitve dogovorjenih kanalov in platform najprej pregledali strokovno literaturo, raziskave, spletne priročnike, oblikovala Arnesovo spletno učilnico, do katere so lahko digitalne zbirke in slovarje. Pri izvajanju poučevanja na daljavo dostopali vsi učenci z AAI računom. Ker so izkušnje s se ne izvaja zgolj pouk, ampak tudi podporne dejavnosti prejšnjega šolskega leta pokazale, da je spletna učilnica oziroma razširjen program, kar smo pri vzpostavljanju virtualne Knjižnica ena redkih, ki ne potrebuje gesel in da jo uporabniki oglasne deske imeli ves čas v mislih. včasih res potrebujejo na hitro, smo se odločili, da bo odprta. Izposoja gradiva v šolski knjižnici je ena najpomembnejših 2.2 Bralne dejavnosti na daljavo storitev, smo se lotili urejanja nabora besedil, ki so bili urejeni Šolski knjižničarji so se vključevali v pouk na daljavo z po abecednem seznamu avtorjev, ki so jim sledile povezave do različnimi bralnimi dejavnostmi. V mesecu novembru smo za prosto dostopnih besedil (Slika 1). učence drugega razreda izvedli delavnico v spletnem okolju Zoom v okviru projekta Medgeneracijsko branje. Učenci so prebrali slikanico Kraljična na zrnu graha, ki je prosto dostopna na spletu. Nato so sodelovali v debatnici na Zoomu, kjer so se z učiteljico in knjižničarko pogovarjali o prebranem besedilu. Spoznali so spletno orodje Padlet in ga za nalogo uporabili tako, da so svoj likovni izdelek pripeli na virtualno oglasno desko z naslovom Kraljična na … , pri čemer so izbirali predmet, na katerem je kraljična spala (Slika 3). Slika 1: Nabor do prosto dostopnih besedil Sčasoma so se pojavile potrebe po raznolikosti gradiv, zato se je glede na želje strokovnih delavcev nabor besedil dopolnjeval z ekološkimi vsebinami, kvizi, interaktivnimi vajami, strokovnimi članki in besedili v tujih jezikih. 2.1 Skrb za podporo strokovnih delavcev Strokovni delavci so pri izvedbi poučevanja na daljavo potrebovali celostni pristop. Učitelj pri svojem delu je Slika 3: Uporaba Padleta v drugem razredu potreboval učbeniško gradivo, kar mu je bilo zagotovljeno s strani založb. Mnoge založbe so digitalizirale berila, omogočala Bralna značka in eko bralna značka sta se izvajali na daljavo na prost dostop do svojih portalov, organizirale webinarje in različne načine. Eko bralna značka se je izvedla v sodelovanju z objavljale novosti na spletnih straneh. Šolski knjižničarji so razredniki tako, da so učenci prebrali tri članke iz nabora skrbeli za dostope, pridobitve kod, iskanje informacij, objavljenih besedil in si ogledali kratki animirani film, ki je prepošiljanje obvestil o webinarjih in drugih izobraževanjih na prosto dostopen na spletu. Nato so izbirali med petimi 547 različnimi termini na Zoomu, kjer je potekal pogovor s knjižničarko. Bralna značka se je izvajala v obliki pogovorov preko Zooma in Skypa ali pisno preko elektronske pošte ali preko Padleta, ki je bil dostopen v spletni učilnici (Slika 4). Slika 6: Primer adventnega pravljičnega koledarja Tudi po vrnitvi v šolske klopi so se bralne dejavnosti izvajale na daljavo. Zaradi priporočil, da se pouk izvaja v mehurčkih, kjer se ohranjajo čisti oddelki, so se dodatne dejavnosti še vedno izvajale na daljavo. Tretji razredi so se v spomladanskih mesecih pripravljali na Cankarjevo tekmovanje, Slika 4: Primer opravljanja bralne značke zato jim je bil ponujen dodatni pouk s knjižničarko. Preko Zooma so učenci diskutirali o prebranem besedilu, ga analizirali V tretjem razredu je bila izvedena medpredmetna učna ura in spoznavali različne zorne kote za ravnanje književnih oseb. pri pouku angleščine preko Zooma, kjer so učenci prebirali Uvodna dejavnost je potekala s pomočjo aplikacije Wheel of krajša besedila v tujem jeziku, nato pa s kolesom sreče ponovili names, kjer so učenci zavrteli kolo, dopolnili naslov znanega besedišče na temo živali. Aplikacija Wheel Decide omogoča besedila in v treh povedih povzeli bistvo (Slika 7). izdelavo kolesa sreče, s katerim so učenci poiskali žival, ki nastopa v znani angleški pravljici (Slika 5). Slika 7: Wheel of Names pri dodatnem pouku 2.3. Razvijanje informacijske pismenosti Slika 5: Wheel Decide pri angleščini v tretjem razredu Razvijanje informacijske pismenosti je potekalo v okviru medpredmetnih ur. Ko so se učenci udeležili učnih ur na Meseca decembra je bila izvedena bralna delavnica za daljavo, se je šolski knjižničar vključeval kot strokovna in učitelje, ki so se prijavili k sodelovanju v projektu tehnična podpora. Učence je bilo vedno potrebno seznaniti z Medgeneracijsko branje. Po prebrani knjigi Jane Frey z novimi orodji in s pravili vedenja na spletu ter jih osveščati o naslovom Jaz, drugačna so se učitelji udeležili delavnice preko varni rabi interneta. Mlajši učenci so se učili orientirati v spletni Zooma, kjer so se pogovarjali o vsebini knjige, o kulturni učilnici, oddajati naloge in pripenjati priponke. Spoznavali so raznolikosti, stereotipih in bralnih užitkih. spletno okolje Arnes, Zoom, Padlet, Kahoot, Liveworksheet ter Za pravljično vzdušje naših najmlajših šolarjev, ki so se šele druga spletna orodja, ki so jih učitelji uporabljali pri pouku. začeli opismenjevati, smo pripravili virtualni adventni koledar Starejši učenci so se učili navajati vire, uporabljati Cobiss ter Advent my friend, ki je prosto dostopen na spletu. Pravljični poiskati informacije na spletu. koledar je omogočal, da so učenci prvih razredov vsak dan v Šolska knjižnica je prav tako sodelovala pri razrednih mesecu decembru kliknili na okence, v katerem so se skrivali likovnih natečajih in virtualnih razstavah ob posebnih dnevih, prosto dostopni zvočni posnetki znanih pravljic (Slika 6). kot na primer Dan Zemlje in Eko dan. Vključevala se je v 548 razredne ure s tematiko trajnostnega razvoja in globalnega Seveda vseh knjižničnih storitev ni bilo mogoče prenesti v učenja. Izvajala je učne ure slovenščine za učence priseljence, spletno okolje, so se pa vse storitve lahko prilagodile do te ki so potrebovali pomoč pri vzpostavljanju rutine, orientaciji v mere, da se jih je lahko izvajalo tudi na daljavo. Največji izziv spletnem okolju in pri razvijanju strategij učenja za premostitev je bilo vzdrževanje in ohranjanje motivacije za branje, zato je jezikovnih ovir s spletnim slovarjem Franček (Slika 8). bilo pomembno, da se dejavnosti niso ponavljale in da so bile zasnovane v krajši obliki in z dodatnimi aplikacijami, ki so popestrile sedenje za ekrani. Ker so tudi uporabniki imeli tehnične težave, je bilo potrebno razmišljati tudi o rezervnem načrtu, zato se je vedno po srečanjih na Zoomu za vse odsotne pripravil opis dejavnosti s povezavami, ki je bil objavljen v spletni učilnici. Najbolj so bile obiskane bralne dejavnosti, ki so vnašale zabavo in gibanje v učni proces, kar je zviševalo motivacijo za delo in za opravljanje bralne značke. Tudi pri učenju na daljavo je šolska knjižnica uspela ohranjati odprt dostop. Delovala je vključujoče in je nudila Slika 8: Primer uporabe spletnega slovarja Franček varno spletno okolje, pri čemer je uporabnike seznanjala s pravili vedenja in z varnostjo na spletu. 2.4 Sodelovanje z drugimi zavodi Vsekakor je prednost učenja na daljavo bila uporaba spletnih okolij, ki jim uporabniki drugače nikoli ne bi bili izpostavljeni. S tega vidika je šolska knjižnica lahko zelo veliko prispevala k Za šolsko knjižnico je poleg izposoje in dela z uporabniki postopnemu informacijskemu opismenjevanju, a le, če se je pomembna tudi obdelava gradiva in posodabljanje informacij šolski knjižničar znal povezovati in sodelovati z drugimi ter dokumentov, spremljanje trendov in iskanje povratnih strokovnimi delavci, saj je večina ur knjižnično-informacijskih informacij s strani uporabnikov šolske knjižnice. Da bi si šolski znanj potekala v povezavi z drugimi predmetnimi področji. knjižničarji izmenjali informacije in primere dobre prakse, so se Največja pomanjkljivost pri izvajanju knjižnične dejavnosti vzpostavile različne mreže in individualni komunikacijski na daljavo pa je vsekakor bila odsotnost stika v živo, ki je za kanali. Pri iskanju novih informacij se je za koristno izkazala mlajše učence ključnega pomena, sploh pri obravnavi spletna učilnica Knjižnična dejavnost Zavoda Republike književnih besedil. Tehnične težave, socialno-ekonomski status Slovenije za šolstvo, kjer so se objavljali primeri dobrih praks uporabnikov, učne in vedenjske težave pa so vse tiste prepreke, in so se izvajala srečanja s svetovalko s spletnem okolju MS s katerimi so se soočali vsi strokovni delavci v vzgoji in Teams. Odličen vir informacij je v času učenja na daljavo bilo izobraževanju in ne samo šolski knjižničarji. tudi družabno omrežje Facebook, kjer so v zaprti skupini Sekcija šolskih knjižnic knjižničarji delili celo vrsto uporabnih 4 ZAKLJUČEK idej. Šolska knjižnica Osnovne šole Vide Pregarc je v času učenja na Šolska knjižnica OŠ Vide Pregarc se je povezovala tudi z daljavo prilagodila dejavnosti in omogočila svojim drugimi slovenskimi šolami, tako pri timskem poučevanju na uporabnikom spletne storitve. Nudila je varno spletno okolje in daljavo kot z deljenjem spletnih gradiv. V mesecu decembru, omogočila podporo vzgojno-izobraževalnemu procesu, ki je ko so se zvrstile statistike ob zaključku koledarskega leta, je potekal na daljavo. Prednosti in slabosti dela na daljavo so v šolska knjižnica sodelovala z NUK-om in IZUM-om, ki sta novem šolskem letu postala izhodišče za nadaljnje delo. pomagala pri svetovanju in pri tehničnih dilemah pri delu s Vsekakor pa šolske knjižnice ostajajo prostor za promocijo COBISS-om. bralne kulture ter za razvoj informacijske pismenosti – tako v Povezovanje z drugimi zavodi je bilo nujno, saj je število šolskih prostorih kot na daljavo. knjižničarjev na šolah bistveno manjše kot število učiteljev, ki so se lahko vsakodnevno povezovali in sodelovali znotraj svojih LITERATURA IN VIRI strokovnih področij. Z vidika strokovnosti je šolski knjižničar v [1] Novljan, Silva, 2002, Informacijska pismenost. Knjižnica, 46(4), 7-24. številnih primerih sam na šoli, zato je zanj toliko bolj DOI: https://www.dlib.si/details/URN:NBN:SI:doc-MGZKIKZZ pomembno, da poišče pomoč in podporo pri svojih strokovnih [2] IFLA – Smernice za šolske knjižnice . DOI: http://www.zbds- zveza.si/sites/default/files/dokumenti/ifla_guidelines.pdf kolegih in pri zavodih, ki nudijo strokovno in tehnično podporo. [3] Brilej, I., 2018. Informacijska pismenost v šolski knjižnici. Knjižnica, 62(1-2), 57-67. DOI: https://knjiznica.zbds- zveza.si/knjiznica/article/view/6846 3 TEŽAVE IN POMANJKLJIVOSTI [4] Izvajanje izobraževanja na daljavo v izrednih razmerah. Strokovna navodila za ravnateljice in ravnatelje osnovnih šol. 2020. Ljubljana: Prenos knjižničnih storitev v spletno okolje je zahtevalo veliko Zavod Republike Slovenije za šolstvo. DOI:https://sio.si/wp- časa in truda. Ker se je sam vzgojno-izobraževalni proces na content/uploads/2020/03/Strokovne-usmeritve-Navodila- daljavo ves čas spreminjal in ker se je motivacija za delo na ZRS%C5%A0.pdf [5] Hren,U., Rajkovi, U., Jereb, E., 2021, Računalniška in internetna daljavo med uporabniki zelo razlikovala, je bilo za šolsko pismenost učiteljev osnovnih šol. 40. Mednarodna konferenca o razvoju knjižnico ključnega pomena, da je šolska knjižničarka ves čas organizacijskih znanosti. DOI: https://doi.org/10.18690/978-961-286- 442-2 spremljala novosti, posodabljala spletno učilnico in elektronske zbirnike ter zbirala povratne informacije svojih uporabnikov, tako učencev kot učiteljev. 549 Preliminarna anketa kot didaktični pripomoček Preliminary survey as a didactic tool Luka Planinc OŠ Ivana Groharja Škofja Loka, Slovenija luka.planinc@os-igroharja.si POVZETEK Izvedba ankete pred obravnavo nove snovi (preliminarna anketa) V prispevku na praktičnem primeru pokažem uporabo aktivira učence, da začnejo razmišljati o snovi malo prej, bolj preliminarne ankete kot didaktičnega pripomočka in pristopa za dejavno so vključeni vsi učenci, prav tako nanje ne vplivajo obravnavo trajnostnega razvoja pri pouku. Namen je bil aktivirati sošolci, ki dvigujejo roke in že dajejo neke ideje, misli, ki bi učence za razmišljanje o tej temi ter obenem preveriti in izenačiti vplivale na njihovo razmišljanje. To je pomembno z vidika predznanje. Učenci so pri pouku zato že poznali in razumeli počutja učencev pri sami uri, ker zaradi seznanjenosti z osnovni koncept trajnostnega razvoja in so bili bolj aktivni v obravnavano snovjo lažje bolj tvorno sodelujejo in nimajo pedagoškem pogovoru. Uporabil sem okolje MS Forms, ki je občutka podrejenega položaja. [3] Prav tako pa tudi poveča zelo praktično. vključenost učencev, ki imajo morda slabše predznanje in ki KLJUČNE BESEDE morda pridejo manjkrat na vrsto v pogovoru v razredu, kar je pomemben vidik inkluzije. [2] Anketa, didaktika, trajnostni razvoj ABSTRACT 2.1 Microsoft (MS) FORMS In this article, I show a practical example of a preliminary Pri izvajanju pouka na daljavo smo na naši šoli uporabljali okolje survey used as a didactic tool and teaching approach about MS Teams in aplikacije, ki so vključene v Microsoft Oblak 365. sustainable development in the classroom. The purpose was to Ena od njih je tudi MS Forms, s katero lahko izdelujemo različne activate students' thinking about this topic, and at the same time oblike elektronskih obrazcev, s katerimi pridobimo informacije to check and equalize their prior knowledge. Therefore, the od uporabnikov. Lahko je narejena z namenom preverjanja students already knew and understood the basic concept of znanja in točkovanjem – kot kviz, lahko pa je brez točkovanja – sustainable development in class and were more active in the kot klasični anketni vprašalnik. Omogoča tudi t. i. razvejane pedagogical conversation. I used the MS Forms environment, ankete, pri katerih je vprašanje lahko pogojeno s tem, kako smo which is very practical. odgovorili na prejšnje. Zelo dobra je tudi povezava med MS Teams in MS Forms, saj lahko vprašalnik učenci izpolnjujejo kar KEYWORDS v okolju Teams in s tem pridobimo ločenost po razredih ter tudi avtomatično imensko beleženje učencev, ki so izpolnili Survey, didactics, sustainable development vprašalnik. MS Forms je preprost za uporabo in ima zelo intuitiven način 1 UVOD dela. Seveda pa je na voljo še kar nekaj podobnih aplikacij oz. spletnih strani, kot so Google Forms, 1ka.si, Survey Monkey, za Pri obravnavi nove snovi lahko naredimo različne oblike uvoda, kvize pa še Quizzizz, Kahoot in podobne. da učence pripravimo na neko novo poglavje in jih miselno aktiviramo. To lahko naredimo na začetku učne ure, na koncu prejšnje ure ali pa kot domačo nalogo. Pri pouku na daljavo, pa tudi pri običajni obliki pouka v šoli, lahko izkoristimo elektronska orodja, s katerimi ne samo povečamo raznolikost, ampak dobimo neke nove koristi. Anketni vprašalnik je zelo zanimiv za uporabo pri pouku tako v šoli kot na daljavo. V tem prispevku bomo pogledali izvedbo preliminarne ankete v okolju MS Forms. Slika 1: Logo MS Forms 2.2 Kviz ali anketa? 2 (PRELIMINARNA) ANKETA Kaj je razlika? Pri kvizu samo preverjamo znanje, ki ga imajo Anketa oz. anketni vprašalnik je zelo uporabno orodje, s katerim učenci, in od njih ne pridobimo novih informacij. Pri anketi pa si lahko pomagamo pri pouku tako v šoli kot na daljavo. nas zanimajo razmišljanje, ideje … učencev. Rezultate ankete lahko tudi statistično analiziramo in si z njimi pomagamo pri izvedbi naslednjih ur. V okolju MS Forms lahko naredimo tako 550 vprašalnik v obliki kviza, kot tudi anketni vprašalnik. Rezultate razvoja, kaj oni že delajo na tem področju ter kako bi ta koncept program sam že osnovno statistično obdela in tudi grafično lahko uporabili na nekem drugem življenjskem primeru. predstavi, kar je zelo praktično. Ravno obravnava teme trajnostnega razvoja se mi zdi za takšen način dela zelo primerna v 9. razredu, saj učenci v prejšnjih letih večkrat govorijo o varovanju okolja, okolijski problematiki, onesnaževanju, vendar še morda nikoli niso slišali za koncept trajnostnega razvoja oz. trajnostnega razmišljanja, ki je bolj kompleksen. V 9. razredu so učenci že bolj sposobni za kompleksnejši nivo razmišljanja, anketni pristop pa to spodbuja na individualnem nivoju. S posredovanjem definicij osnovnih pojmov vnaprej lahko pospešimo ali celo preskočimo razlago in pri pouku hitreje preidemo na glavni del – pedagoški pogovor in iskanje rešitev. Operativni cilji in vsebine učnega načrta za pouk geografije v 9. razredu na več mestih omenjajo trajnostni razvoj, lokalno Slika 2: Samodejna grafična predstavitev odgovorov območje in osnovne raziskovalne metode. Učenec naj bi ozavestil in razumel pomembnost ohranjanja okolja za trajnostni 2.3 Zakaj preliminarna anketa razvoj družbe v sedanjosti in prihodnosti, razlikoval med odgovornim in neodgovornim ravnanjem s prostorom, ter se po Anketa, ki je izvedena še pred obravnavo snovi (preliminarna teh spoznanjih tudi ravnal [4]. Z uporabo preliminarne ankete anketa), aktivira učence, da začnejo razmišljati o snovi malo prej. lahko pri učencih preverimo, kakšno je njihovo razumevanje tega Anketo običajno jo izvedemo enosmerno – da dobimo področja, kakšna so njihova trajnostna ravnanja ter kakšni so informacije od vprašanih. S preliminarno anketo lahko njihovi predlogi za ravnanje njih in širše družbe. Zbrane podatke preverimo, koliko učenci znajo že od prej, lahko preverimo in lahko potem uporabimo za izhodišča pedagoškega pogovora v spoznamo, kakšno je njihovo razmišljanje, nivo znanja, ne da bi razredu. nanje vplivali sošolci. Lahko pa je narejena malo drugače in poleg pridobivanja informacij lahko nekaj teh tudi posredujemo. 3.1 Vsebina ankete V anketi lahko nekaj informacij zapišemo in tako jih učenci Anketo sem razdelil v tri vsebinske sklope: dobijo še pred obravnavo snovi, s tem pa lahko izenačimo - Predstavitev, razlaga in preverjanje razumevanja predznanje, povemo kakšen del tega, kar bomo spoznali, definicije trajnostnega razvoja. razložimo osnovne pojme in tako aktiviramo razmišljanje o neki - Razmišljanje o uporabi koncepta trajnostnega razvoja temi, zaradi česar bo sama obravnava lažje stekla, pogovor pa bo na primeru pouka na daljavo. bolj poglobljen, saj se z nekaterimi osnovnimi pojmi ne bo več - Preverjanje poznavanja in delovanja učencev na treba ukvarjati. področju trajnostnega razvoja oz. trajnostnega Učenci se bodo počutili bolj suvereni in kompetentni za vedenja. sodelovanje, lažje bodo sodelovali kot subjekti v vzgojno-učnem V prvem delu ankete sem učence vprašal, če poznajo izraz procesu in bodo s tem imeli od njega največje koristi. [3] »trajnostni razvoj«. Če so odgovorili z DA, sem jih pozval, naj s Ravno obravnava trajnostnega razvoja se mi zdi za takšen način svojimi besedami napišejo, kaj je to. Če so odgovorili z NE, sem zelo primerna v 9. razredu, saj učenci v prejšnjih letih večkrat jim najprej pokazal definicijo trajnostnega razvoja Svetovne govorijo o varovanju okolja, o okolijski problematiki, komisije za okolje in razvoj (Brundtlandina komisija) [6], ki se onesnaževanju, vendar še morda nikoli niso slišali za koncept najbolj uporablja, nato pa so morali tudi oni sami napisati trajnostnega razvoja oz. trajnostnega razmišljanja, ki je bolj definicijo s svojimi besedami. S tem sem želel aktivirati njihovo kompleksen. Tako lahko s posredovanjem definicij osnovnih razmišljanje in povečati aktivnost. Nato sem vsem pokazal pojmov vnaprej pospešimo ali celo preskočimo razlago in pri definicijo in jih vprašal, če so po njihovem mnenju zadeli pomen. pouku hitreje preidemo na glavni del – pedagoški pogovor in S tem sem želel preveriti njihovo samopresojo razumevanja. iskanje rešitev. Nato sem jim pokazal še poenostavljeno definicijo in negirano Poleg posredovanja informacij pa seveda nekaj informacij tudi definicijo, da bi še lažje razumeli pomen koncepta razmišljanja zberemo. Ker to izvedemo prej, lahko zbrane informacije trajnostnega razvoja. uporabimo pri sami učni uri in tako vključimo razmišljanja in Sledilo je prehodno vprašanje, s katerim sem prehajal na drugi ugotovitve učencev, zato se bodo učenci počutili bolj vključeni del ankete, obenem pa sem še preverjal njihovo razumevanje in bolj zadovoljni. (glej sliko): 3 PRIMER UPORABE MS Forms ANKETE Pri opisanem primeru sem uporabil MS Forms razvejano anketo. Želel sem pridobiti nekaj informacij o njihovem poznavanju problematike, o njihovem predznanju, želel sem zbrati njihove ideje, jim razložiti kakšen osnovni pojem, poleg tega pa vse aktivirati za razmišljanje o konceptu trajnostnega Slika 3: 7. vprašanje ankete 551 napake in to potem pri pouku korigiral in dodatno razložil. Pri Če so učenci odgovorili z NE, sem jih dodatno vprašal, ali res običajnem pristopu v učilnici – z dvigovanjem rok – ne bi mogel mislijo, da bi šlo, in če se jim ne zdi, da bi bilo marsikomu težko dobiti tako natančnega spektra pravilnih in napačnih odgovorov. delati na tak način zelo dolgo. To je bilo t. i. razvejano vprašanje, Namen iskanja in zbiranja predlogov za spremembe k bolj ki je bilo prikazano samo v primeru, da je učenec na prejšnje trajnostni obliki pouka na daljavo je bil seveda v tem, da učenci vprašanje odgovoril z NE. začnejo razmišljati o stanju ter možnih rešitvah, kar je osnovni Sledil je drugi del, kjer sem učence pozval, naj razmislijo, kaj pa način reševanja problemov, kar smo potem delali pri pouku tudi bi morali spremeniti, da bi bil pouk na daljavo lahko trajnosten. s pogovorom. Pokazal sem jim tudi, da je dobro ločiti polja Razložil sem, da je to kompleksno vprašanje in da bi lahko polja sprememb in delovanja na več nivojev. Zelo sem bil presenečen sprememb razdelili na tri dele – na tisto, kar lahko naredijo sami, nad iskrenostjo odgovorov in iskanjem rešitev, kjer se je na tisto, kar bi lahko naredili učitelji, in tisto, kar bi lahko pokazalo, da imajo podobne težave in predloge za rešitev. naredila država oz. Ministrstvo za šolstvo. Nato so za vsak del V tretjem delu sem ugotavljal njihovo vključenost in aktivnost posebej napisali ideje in predloge sprememb. S tem delom ankete pri trajnostnem delovanju ter njihove predloge. Vesel sem bil, da sem želel tudi uresničevati didaktično načelo zavestne dejavnosti so nekateri že zelo trajnostno aktivni in da imajo dobre predloge, in kompleksnosti, ki sta dve zelo pomembni načeli poučevanja kaj bi lahko še naredili. geografije. [1] S pomočjo ankete pa lahko vidimo, koliko so učenci sposobni kompleksno razmišljati, lahko opazimo kakšen »skriti talent« in vidimo, na kakšnem nivoju razmišljajo naši 4 ZAKLJUČEK učenci, in temu prilagodimo pogovor v razredu. Sledil je še tretji del, kjer smo se usmerili v trajnostni razvoj in Pri poučevanju na daljavo je bilo potrebno poiskati nove načine, trajnostno upravljanje z okoljem. Vprašal sem jih, če so že kdaj kako priti do tistih dodatnih informacij o učencih, ki jih v učilnici slišali za trajnostni razvoj ožjega okolja ali razmišljali o njem – dobimo mimogrede, na daljavo pa težje dosegljive. npr. njihove občine, kje so dobili informacije ter ali se po Po izkušnji, ki sem jo imel z izdelavo in uporabo ankete kot njihovem mnenju dovolj govori in dela na tem. pripomočka za aktivacijo razmišljanja in izenačenja predznanja, Nato sem šel na bolj osebni nivo in vprašal, če sami kaj delajo na sem zelo zadovoljen in bom vsekakor ta način uporabil tudi pri tem, če kaj delajo oz. prispevajo ter kaj jih pri tem ovira oz. zakaj kakšni drugi temi. Učenci so bili zelo zadovoljni z drugačnim je to težko. pristopom, veliko bolj angažirani in pripravljeni na pogovor v V zadnjem delu sem jih vprašal po njihovih predlogih za razredu, saj so o temi že začeli razmišljati prej, ne šele ob začetku trajnostno delovanje, nato so med naštetimi trajnostnimi ure. aktivnostmi izbrali tiste, ki jih oni ali njihova družina zavestno • MS Forms se mi zdi dobro okolje za to, še posebej, ker delajo. Na koncu sem jim pokazal še cilje Agende 21 za na naši šoli uporabljamo tudi okolje MS Teams. Slovenijo iz leta 1995 [7] ter jih vprašal, v kakšni meri po Herbert Spencer je nekoč zapisal: »Vsak drobec znanja, ki ga njihovem mnenju danes sledimo tem ciljem. Povedal sem jim še, učenec pridobi sam – vsak problem, ki ga sam reši – postane da se bomo o tej temi pogovarjali na naslednji uri. mnogo bolj njegov, kot bi bil sicer. Dejavnost uma, ki je Večina učencev je anketo izpolnila v manj kot 15 minutah, kar je spodbudila učenčev uspeh, koncentracija misli, potrebnih zanj, bil tudi moj cilj. in vznemirjenje, ki sledi zmagoslavju, prispevajo k temu, da se dejstva vtisnejo v spomin, kot se ne bi mogla nobena informacija, 3.2 Časovni okvir dela ki jo je slišal od učitelja ali prebral v učbeniku.«[5] Anketo sem učencem dal kot nalogo pri delu na daljavo tik S pomočjo tega pristopa je zgornja misel laže uresničljiva. preden smo spet šli v šolo. Tako so imeli dovolj časa za reševanje in so bili že z mislimi usmerjeni v novo temo, ki smo jo obravnavali potem pri pouku naslednjo uro. V vmesnem času 5 LITERATURA IN VIRI sem pregledal odgovore, pozval učence, ki še niso oddali [1] Slavko Brinovec. 2004. Kako poučevati geografijo: odgovorov, da to storijo, in začel z obdelavo rezultatov. didaktika pouka, Zavod Republike Slovenije za šolstvo, Pregledal sem odgovore in ugotovil, da zelo podobno Ljubljana. razmišljajo in da so bili tudi običajno bolj tihi učenci aktivni in [2] Paul Ginnis. 2004. Učitelj – sam svoj mojster, Rokus, podajali predloge. Ljubljana. Zbral sem njihove odgovore po posameznih vprašanjih in [3] Martin Kramar. 1990. Učenci v vzgojno-izobraževalnem naredil Power Point predstavitev z najpogostejšimi odgovori. procesu sodobne šole, Didakta, Radovljica. Te rezultate sem predstavil v uvodnem delu obravnave te teme [4] Karmen Kolnik et al. 2011. Učni načrt. Program pri pouku in razvil se je dober pogovor. osnovna šola. Geografija. Ministrstvo za šolstvo in šport, Zavod RS za šolstvo, Ljubljana. Pridobljeno: 3.3 Rezultati ankete in njihova uporaba https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/ Osnovna-sola/Ucni-nacrti/obvezni/UN_geografija.pdf Iz odgovorov v prvem delu sem razbral, da jih je nekaj že slišalo (30. 8. 2020) za trajnostni razvoj, kar precej pa je takih, ki še niso oz. tega ne [5] Alenka Stare. Proces učenja in poučevanja. Pridobljeno: razumejo ali razumejo nepravilno – veliko jih je enačilo https://alenkastare.si/proces-ucenja-in-poucevanja/ (19. »trajnostno« s »trajnostjo« oz. z dolžino trajanja. Ko pa so 7. 2021) prebrali definicijo, so začenjali razumeti pravi pomen. Zelo dobro je bilo tudi, da sem lahko videl, kakšne so najpogostejše 552 [6] Trajnostni razvoj, Plan B za Slovenijo. Pridobljeno http://www.planbzaslovenijo.si/trajnostni-razvoj (5. 8. 9. Verjetno res ne bo šlo na tak način še dolgo. Kaj pa bi morali 2021) spremeniti? No, to je kompleksno – zapleteno vprašanje. Lahko [7] Umanotera (1995): Agenda 21 za Slovenijo, prispevek bi razdelili polja sprememb na tri dele – na tisto, kar lahko nevladnih organizacij, Umanotera, Ljubljana. narediš TI, na tisto, kar bi lahko naredili UČITELJI, in tisto, kar Pridobljeno: http://www.umanotera.org/wp- bi lahko naredila država oz. MINISTRSTVO za šolstvo. content/uploads/1995/11/Agenda-21-za-Slovenijo.pdf Napiši nekaj, kar bi moral ti spremeniti PRI SEBI, da bi lahko (15. 7. 2021) nadaljeval s šolanjem na daljavo še dolgo časa. Poišči vsaj tri stvari. 10. Dobro, poskusi sedaj napisati tri stvari, ki bi jih po tvojem mnenju lahko (morali) spremeniti učitelji, da bi lahko poučevali Priloga: Anketni vprašalnik na daljavo še dolgo. Poskusi najti vsaj tri stvari. 1. Si že slišal za izraz "trajnostni razvoj"? 11. Sedaj po poskusi poiskati še kakšno stvar, ki bi jo lahko DA/NE naredilo drugače Ministrstvo za šolstvo oz. država, da bi tak način dela lahko izvajali dolgoročno. Poišči vsaj ENO stvar. 2. Se ti zdi, da veš, kaj pomeni izraz "trajnostni"? DA/NE 12. Odlično! Hvala. Sedaj že bolje razumemo, kaj pomeni trajnostnost in kaj pomeni iskanje rešitev, če želimo nekaj 3. Ker si odgovoril, da ne veš, kaj pomeni, si preberi tale opis: narediti trajnostno. O trajnostnem razvoju, trajnostni mobilnosti, "Trajnostni razvoj je takšen način razvoja, ki zadošča današnjim trajnostnem upravljanju naravnih bogastev se veliko govori v potrebam, ne da bi pri tem ogrožal možnosti prihodnjih generacij, zadnjih letih. Zanima me, če si že kdaj slišal in razmišljal o da zadostijo svojim lastnim potrebam." Svetovna komisija za trajnostnem razvoju našega ožjega okolja – na primer Občine okolje in razvoj (WCED), 1987 Škofja Loka? Si zdaj razumel? DA/NE DA/NE 13. Kje si izvedel kaj o tem? 4. Poskusi s svojimi besedami napisati, kaj pomeni ta izraz. • V časopisih. • V šoli. 5. Primerjaj to, kar si napisal, z naslednjim opisom tega izraza: • Doma. "Trajnostni razvoj je takšen način razvoja, ki zadošča današnjim • Na internetu. potrebam, ne da bi pri tem ogrožal možnosti prihodnjih generacij, • Na televiziji. da zadostijo svojim lastnim potrebam." Svetovna komisija za okolje in razvoj (WCED), 1987 14. Se ti zdi, da se o tem dovolj govori, da se na tem dovolj dela? Se ti zdi, da si zadel pomen? DA/NE DA/NE 15. Imaš občutek, da lahko tudi sam kaj prispevaš k temu, da bi 6. Lahko rečemo tudi tako: – Trajnostni razvoj pomeni, da lahko bilo naše delovanje bolj trajnostno? neka dejavnost traja dolgo – tako rekoč neskončno, ne da bi se DA/NE zaradi posledic svojega delovanja morala končati. Ali pa na primer: Ne-trajnosten razvoj pomeni, da tako 16. Napiši, na kakšen način bi lahko ti prispeval (ali že prispevaš) izkorišča vire, ljudi ali okolje, da bodisi zmanjka virov ali pa k temu – na primer, kaj lahko narediš glede skrbi za okolje, kaj v ljudje ne zmorejo več, ali da okolje ni primerno za vsakdanjem življenju delaš ali bi lahko delal, da bo okolje bivanje/obdelovanje. dolgoročno v dobrem stanju. Poišči vsaj tri stvari. Je sedaj še kaj bolj razumljivo? 17. Se ti zdi, da je to lahko? Kaj te najbolj ovira pri tem, da DA/NE deluješ trajnostno? 7. Pa preverimo, če res razumeš ta izraz – na primeru učenja na 18. Imaš kakšen predlog za boljšo trajnostno skrb in ravnanje z daljavo, ki je sedaj aktualno. Se ti zdi, da je to trajnostno – da bi našim okoljem? Lahko gre za majhne stvari, lahko pa napišeš lahko s takim šolanjem nadaljevali dolgoročno – mesece, morda tudi, kaj bi morala narediti vsa družba, država ... celo leta? DA/NE 19. Katera od naslednjih stvari se ti zdi, da jo TI ali tvoja družina zavestno delate: 8. Odgovoril si z DA. Si prepričan? No, morda lahko trdiš zase, • Pridelava domače hrane. a vendarle je marsikomu težko in ne bi zdržal takega dela dolgo, • Kupovanje lokalno pridelane hrane. morda znanje ni dovolj kvalitetno za uspešno šolanje naprej . . • Uporabljanje okolju prijaznejših čistil, škropiv, gnojil. Se strinjaš? • Kupovanje rabljenih stvari, naprav, oblačil. DA/NE • Popravljanje okvarjenih naprav namesto kupovanja novih. 553 • Dosledno ločevanje odpadkov. • Zavestna izbira hoje/kolesa . . namesto avtomobila. • Varčevanje z vodo. • Varčevanje z elektriko. • Spodbujanje drugih k odgovornejšemu ravnanju. 20. V dokumentu Agenda 21 za Slovenijo, ki ga je leta 1995 pripravila skupina nevladnih organizacij pod vodstvom Umanotere, Slovenske fundacije za trajnostni razvoj, so načela trajnostne družbe povzeta takole: - spoštovanje občestva življenja in odgovornost zanj, - izboljševanje kakovosti človekovega življenja, - ohranjanje vitalnosti in pestrosti Zemlje, - čim korenitejše zmanjševanje izčrpavanja neobnovljivih virov, - upoštevanje nosilne sposobnosti Zemlje, - spreminjanje osebnega odnosa in ravnanja, - usposabljanje skupnosti za samostojno in odgovorno ravnanje z okoljem, - oblikovanje državnega okvira za povezovanje razvoja in ohranitve, - ustvarjanje svetovnega zavezništva. Se ti zdi, da sledimo tem ciljem izpred 25-ih let? • Da. • Še kar. • Malo. • Nič. 554 Učenci s posebnimi potrebami in šolanje na daljavo Students with special needs and distance education Karmen Posedel Golob OŠ Glazija Celje Celje, Slovenija kposed@gmail.com POVZETEK Z anketnim vprašalnikom smo raziskovali, kako so učenci s 1 UVOD primanjkljaji na posameznih področjih učenja (v nadaljevanju Šolanje na daljavo je institucionalno organizirana in priznana PPU) in imajo dodatno strokovno pomoč doživljali pouk na oblika izobraževanja. Pri takšnem šolanju so učitelj in učenci daljavo med epidemijo covid-19 in kakšna so njihova stališča do med poukom navadno fizično ločeni. Govorimo torej o takšnega izobraževanja. V vzorec je bilo vključenih 25 učencev. geografski ločitvi, kar pomeni, da so učitelj in učenci med Ugotavljali smo, kje so bile težave, na katere pogoje bomo v poukom na različnih krajih. prihodnosti morali biti bolj pozorni in kako se je izobraževanje Učenje na daljavo ima lahko za učence in učitelje v primerjavi na daljavo obneslo pri učencih z dodatno strokovno pomočjo. s klasičnim poukom v razredu kar nekaj prednosti. Šolarji si Merski instrument, s katerim smo preverjali zadovoljstvo lahko potek dela organizirajo sami, dostop do učnih vsebin je učencev, je bil vprašalnik. mogoč skoraj od povsod, prav tako pa takšen način šolanja Izobraževanje na daljavo nas je postavilo v popolnoma novo učencu omogoča hiter dostop do povratne informacije. [1] Na situacijo, spremenil se je način izobraževanja in komunikacije. drugi strani lahko tehnične težave upočasnijo celoten učni Spremembe so se še bolj dotaknile ranljivejših skupin, med proces. [2] katere sodijo tudi učenci s primanjkljaji na posameznih področjih S pričujočo raziskavo smo želeli dodatno osvetliti vidike učenja. šolanja na daljavo med epidemijo covid-19, stališča učencev, ki potrebujejo specifično obravnavo (prilagojen pouk, prostor in čas KLJUČNE BESEDE ter posebne oblike in metode dela) tovrstnega učenja v primerjavi s klasičnim poukom. Covid-19, učenci s posebnimi potrebami, IKT, šolanje na daljavo V raziskavo je bilo vključenih 25 šolarjev. Za potrebe ABSTRACT raziskave smo oblikovali vprašalnik za učence, s katerim smo želeli ugotoviti, kakšna stališča imajo do takšnega načina šolanja. With the help of a survey i researched how special needs students who lack certain abilities in individual areas of learning as well 1.1 Učenci s posebnimi potrebami v as receive additional professional help couped with online school during the Covid pandemic and their views on this type of izobraževalnih programih s prilagojenim education. 25 students were included in the sample. The mesaly izvajanjem in dodatno strokovno pomočjo instrument I used to review student satisfaction was a V Navodilih za izobraževalne programe s prilagojenim questionnaire. The aim of this report was to research where izvajanjem in dodatno strokovno pomočjo za devetletno osnovno problems may have occurred, what conditions will have to be šolo je zapisana naslednja opredelitev: »V izobraževalni program more vigilant in the future. Online school has put us in a whole osnovne šole s prilagojenim izvajanjem in dodatno strokovno new situation and our way of communication and education has pomočjo so usmerjeni otroci, za katere komisije za usmerjanje changed. Changes have had a substantial negative effect on more ocenijo, da imajo takšne razvojne in učne zmožnosti, da bodo, vulnerable groups including special needs children. predvidoma s prilagojenim izvajanjem in dodatno strokovno pomočjo dosegli vsaj minimalne cilje oz. standarde znanja, KEYWORDS določene v učnih načrtih za vse predmete v predmetniku osnovne Covid-19, students with special needs, IKT, distance education šole za razred, v katerega se vključuje otrok s posebnimi potrebami.« [5] Izraz primanjkljaji na posameznih področjih učenja označuje zelo raznoliko skupino primanjkljajev ali motenj, ki se kažejo z zaostankom v zgodnjem razvoju pozornosti, pomnjenja, 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 mišljenja, koordinacije, komunikacije, branja, pisanja, for profit or commercial advantage and that copies bear this notice and the full pravopisa, računanja, socialnih sposobnostih in čustvenem citation on the first page. Copyrights for third-party components of this work must dozorevanju. [3] be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ti primanjkljaji vplivajo na posameznikovo sposobnost © 2021 Copyright held by the owner/author(s). interpretiranja zaznanih informacij oz. povezovanja informacij ter s tem ovirajo učenje temeljnih šolskih veščin, kot so branje, 555 pisanje, pravopis in računanje. Motnje so notranje, 23-krat je bil izbran odgovor starši, 17-krat učiteljica DSP, 5- nevrofiziološke narave in niso primarno pogojene z vidnimi, krat brat ali sestra, 2-krat učitelj predmeta, pri katerem sem slušnimi ali motoričnimi okvarami, motnjami v duševnem potreboval pomoč, 1-krat razrednik in 1-krat prijatelj. razvoju, čustvenimi motnjami ali neustreznimi okoljskimi Kako uspešen/a si bil/a pri opravljanju tedenskih učnih dejavniki, čeprav se lahko pojavljajo skupaj z njimi). [3] nalog? V delu Kesič Dimic iz leta 2010 lahko zasledimo, da je za 20 učencev je odgovorilo, da jim je uspelo narediti vse naloge učence s primanjkljaji na posameznih področjih učenja značilno, za tekoči teden, štirim je uspelo narediti polovico nalog za tekoči da imajo načeto ali slabo samopodobo, imajo slabši slušni teden, en učenec pa je naredil manj kot polovico nalog za tekoči spomin (tako kratkotrajni kot dolgotrajni), težko se dalj časa teden. osredotočijo na zastavljeno nalogo, vsaka malenkost jih hitro Kakšen se ti je zdel obseg (količina) snovi, ki jo je bilo zmoti pri usmerjenjem delu, so spontani v izražanju, pogosto ne treba opraviti doma v primerjavi z učnim delom, ko smo v zmorejo nadzirati čustev, hitro se zmedejo (tudi, če so se snov šoli? hitro naučili), večinoma težje delajo v skupini, težje si zapomnijo Večina učencev (11) je odgovorila, da je bil obseg snovi na zapletena ali dolgoročna navodila, težave se pojavijo pri daljavo prav takšen, kot je bil v šoli, 9 učencev meni, da je bil koordinaciji (fina in groba motorika), imajo težave z obseg snovi na daljavo večji, kot takrat ko smo bili v šoli, 3 grafomotoriko, imajo slab občutek za čas. [4] učenci so izbrali odgovor, da je bil obseg snovi preobsežen in Učenci s posebnimi potrebami imajo pogosto lahko tudi veliko večji kot takrat, ko so bili v šoli. Dva učenca sta napisala, čustvene stiske, zato je še kako pomemben osebni stik z da je bil obseg snovi manjši, vendar je bilo nalog več, eden pa je učencem. Delo specialnega pedagoga ni vezano samo na učenca napisal, da je bilo manj nalog kot v šoli. samega, dobro mora sodelovati z učitelji in starši otrok s Ali si razumel učiteljeva navodila za delo? posebnimi potrebami, predstavlja pomembno vez med šolo, 12 učencev je izbralo odgovor, da so razumeli učiteljeva starši in učencem. Pri poučevanju na daljavo se je ta osebni, navodila, 12 jih meni, da so jih delno razumeli, en učenec pa individualen pristop žal zelo zmanjšal. Informacijska tehnologija učiteljevih navodil ni razumel in je potreboval pomoč. je postala nujno orodje, delo z učenci se je preselilo v spletno Oceni, koliko rad/a se učiš in delaš v šoli v primerjavi z okolje (e-pošta, spletne učilnice, zoom, viber ...). učnim delom doma – delo na daljavo! 12 učencev je odgovorilo, da so raje v šoli, sedmim učencem 1.2 Analiza vprašalnika je bolj všeč šola na daljavo, petim učencem pa je všeč tako Učenci so reševali anketo s pomočjo orodja 1ka - spletno šolanje na daljavo kot tudi pouk v šoli. anketiranje. Kako si bil/a zadovoljen/a z izvajanjem DSP na daljavo? Na anketni vprašalnik je odgovorilo 25 učencev s 10 učencev je bilo zelo zadovoljnih z izvajanjem DSP na primanjkljaji na posameznih področjih učenja (v nadaljevanju daljavo, 15 pa jih je izbralo odgovor dobro. Nihče ni bil PPU), 16 dečkov in 9 deklic. Največ učencev je bilo iz 7. razreda nezadovoljen. (10), sledili so 8. razred, 5. razred in 6. razred s po tremi učenci, Kaj ti ni bilo všeč pri izvajanju DSP na daljavo? iz 3. razreda in 9. razreda dva učenca, iz 2. in 4. razreda pa po en Učenci so zapisali naslednje odgovore: učenec. - da smo namesto učenja igrali miselne igre; Na vprašanje, kako samostojen si bil/bila prielu za šolo na - vse je bilo v redu; daljavo, je večina učencev (10) odgovorila, da so potrebovali - bolj mi je všeč osebno; nekaj pomoči, 7 jih je odgovorilo, da so večino ali vse delo - ne vem; opravili sami, 5 učencev je potrebovalo veliko pomoči, 3 učenci - slaba internetna povezava; so odgovorili, da so zelo težko delali sami. - da sem imel manj ur DSP kot v šoli; Kakšno se ti je zdelo delo za šolo od doma, v »domači - nič učilnici«? - da sem imel 1 uro manj kot v šoli; Kar 15 učencev je odgovorilo, da se jim je zdelo delo za šolo - ni mi bilo všeč, ker sem moral biti ves čas aktiven. od doma »v redu«, trije so odgovorili, da jim je bilo zelo všeč, 6 Kakšne oblike pomoči ti je ponudila učiteljica za DSP? učencem delo od doma ni bilo všeč, eden pa je izbral odgovor, Pri tem vprašanju je bilo možnih več odgovorov. Največkrat da mu delo od doma sploh ni bilo všeč. so učenci izbrali odgovor, da jim je učiteljica za DSP razlagala Kako samostojen/a si bil/a pri delu za šolo na daljavo? učno snov in ponazorila postopke reševanja nalog. Sledijo Največ učencev (10) je izbralo odgovor, da so pri delu za šolo odgovori: pojasnjevanje navodil, motiviranje za učno delo, na daljavo potrebovali nekaj pomoči, 7 učencev je odgovorilo, posredovanje napotkov, gradiv, navodil. da so vse delo za šolo opravili samostojno, 5 učencev je Ali so učitelji pri pouku na daljavo upoštevali potrebovalo nekaj pomoči, trije učenci pa so potrebovali veliko prilagoditve, ki jih imaš zapisne v individualiziranem pomoči. načrtu? Koliko časa dnevno si pri delu na daljavo porabil/a za 12 učencev meni, da so učitelji upoštevali prilagoditve, šest šolsko delo (od ponedeljka do petka)? učencev je izbralo odgovor ne vem, štirje menijo, da prilagoditve Večina učencev je odgovorila, da je pri delu na daljavo učitelji niso upoštevali, dva sta izbrala možnost drugo in zapisala, porabila za šolsko delo dnevno 2 do 3 ure, 8 učencev 4 do 5 ur da so prilagoditve včasih upoštevali, včasih pa ne, en učenec pa dnevno, 7 učencev več kot 5 ur in 1 učenec do 2 uri dnevno. je zapisal, da vseh prilagoditev ni bilo mogoče upoštevati pri Kdo ti je pomagal, ko si potreboval/a pomoč pri delu na pouku na daljavo. daljavo? Na katerem področju si bil pri pouka na daljavo Pri tem vprašanju je bilo možnih več odgovorov. prikrajšan zaradi specifičnih težav, ki jih imaš? 556 Učenci so zapisali naslednje odgovore: - pri času pisanja; Tabela 1: Število odgovorov na posamezna vprašanja - matematiki; Odlično Dobro Slabo Zelo Ne vem - TJA, SLJ, MAT; slabo - pozornost; dostopom do informacij v 6 15 2 1 0 - osebni stik; spletni učilnici - nisem bila prikrajšana; povratnimi informacijami 3 15 3 3 0 - nobenih; glede oddanih nalog dostopnostjo učiteljev - pri DSP sem izgubil uro, 4 19 1 0 0 - nisem bil; prilagajanjem gradiv 3 14 4 2 1 - vzeli so mi eno uro DSP; - nikjer. organizacijo pouka in 5 15 3 1 0 Katere prilagoditve, ki jih potrebuješ, pri šolanju na videokonferenc daljavo niso bile upoštevane? razlago snovi pri 3 16 4 1 0 videokonferencah Učenci so zapisali naslednje odgovore: ocenjevanjem 7 12 2 0 3 - da potrebujem več časa za delo; - razlaga; izvajanjem DSP 12 10 1 1 0 - nobene; - bile so vse; pomočjo učiteljev 3 14 4 1 2 - vse so bile; - ne vem; upoštevanjem posebnih 4 11 5 3 0 potreb, ki jih potrebujem pri - ni bilo upoštevano, da potrebujem več časa pri učenju kakšnem predmetu. Imel sem količinsko čisto enako nalog kot drugi učenci. Kaj bi sporočil/a učiteljem glede pouka na daljavo? Učenci sporočajo učiteljem glede šolanja na daljavo: 2 ZAKLJUČEK - da je bilo zelo dobro; Šolanje od doma med epidemijo in zaprtjem šol je za učitelje in - da naj večkrat vprašajo, ali potrebujem kakšno pomoč; šolarje pomenilo velik izziv, saj se je prvič v zgodovini v velikem - da že pri pouku napišemo snov v zvezke in ne potem delu sveta izobraževanje popolnoma prestavilo v virtualno okolje sami; ter zahtevalo hitro priučitev in prilagoditev metod in načinov dela - lahko bi bilo bolj zanimivo; z uporabo IKT. - več razlage snovi v živo; Za učence PPU je značilno, da so zelo heterogena skupina in - nič; so večinoma vključeni v redne osnovne šole, zato je za vse - ne vem; učitelje potrebno dobro poznavanje posameznih podskupin in - da bolj razlaga snovi in ne, da samo pišemo; značilnosti, da lahko pomagajo otroku in prav zaradi tega je bilo - dobra priprava videokonferenc in gradiv v spletni pomembno, da smo raziskali, kako je potekalo izobraževanje učilnici; učencev s PPU. - da so opravili odlično delo. Pomembno je spoznanje, da so se učenci s težavami na Kaj bi sporočil/a učiteljici za DSP glede pouka na posameznih področjih učenja večinoma dobro prilagodili na daljavo? spremenjen način pouka, saj je večina učencev odgovorila, da jim Učenci z odgovori sporočajo učiteljicam, ki izvajajo DSP: je bilo šolanje od doma všeč. Pri šolskem delu jih je večina - da naj ostanejo še naprej tako super, kot so; potrebovala pomoč, ki so jim jo ponudili starši, učiteljica za - kul je bilo; dodatno in strokovno pomoč, stari starši, sorojenci … - bilo je v redu; Podatki prikazujejo, da je večina učencev pri delu na daljavo - nič; porabila za šolsko delo dnevno 2 do 3 ure, prav toliko učencev je - več razlage snovi v živo; potrebovalo 4 do 5 ur dnevno, 7 učencev pa več kot 5 ur. Večina - dobro; učencev, kar 80 % vprašanih je opravilo redno tedensko naloge, - bilo je super in bil sem vesel njene pomoči; nekaj jih je opravilo polovico danih nalog, en učenec pa ni delal - da si želim še naprej uspešno sodelovanje; nalog. Učiteljice za dodatno strokovno pomoč so vse ure izvajale - ne vem; neposredno preko aplikacije ZOOM. To se je očitno izkazalo za - da sem se počutil enako dobro kot v šoli; zelo uspešno, saj so bili vsi učenci zadovoljni z izvajanjem ur - vse super; DSP. Pomoč so potrebovali pri razlagi učne snovi in ponazoritev - ne vem; postopkov, pomoč pri reševanju nalog, pojasnjevanju navodil, - da bi imeli vsi, ki hodimo na DSP svojo stran za motiviranju za učno delo, posredovanju napotkov, gradiv in pogovarjanje. navodil. Če bi lahko izbiral, bi izbral: Prilagoditve, ki jih imajo učenci zapisane v 9 učencev bi izbralo šolanje na daljavo, 12 pouk v šoli, dva individualiziranem načrtu, so učitelji večinoma upoštevali, štirje učenca pa oboje. učenci so napisali, da jih niso. Navedli so, da so bili prikrajšani Število odgovorov o zadovoljstvu s posameznimi elementi je pri podaljšanem času opravljanja nalog in pri razlagi. podano v tabeli 1. 557 Zelo pozitivno je, da so učenci pohvalili delo učiteljev, ZAHVALA sporočajo pa, da v prihodnje prosijo učitelje, da večkrat ponudijo Zahvaljujemo se učencem za iskrenost in doslednost pri pomoč učencem, da bi zapisovali snov že med izpolnjevanju vprašalnika ter ravnateljici za podporo pri videokonferencami, da bi bile razlage snovi bolj zanimive in bi raziskovanju. bilo več videokonferenc. Učiteljicam za dodatno strokovno pomoč sporočajo, da so bili LITERATURA IN VIRI zadovoljni, da si želijo še več razlage snovi v živo, da so se [1] Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 počutili zelo dobro in predlagajo, da se jim v prihodnje omogoči crisis. Journal of Educational Technology Systems, 49(1), 5–22. poseben kanal za komunikacijo učencev, ki imajo DSP: https://doi.org/10.1177%2F0047239520934018 Zanimiv je podatek, da bi ob ponovnem šolanju na daljavo [2] Favale, T., Soro, F., Trevisan, M., Drago, I. in Mellia, M. (2020). Campus traffic and e-Learning during COVID-19 pandemic. Computer Networks, skoraj 40 % vprašanih učencev izbralo pouk na daljavo, več kot 176, članek 107290. https://doi.org/10.1016/j.comnet.2020.107290 polovica pa bi si želela pouka v šoli. [3] Magajna, L., Kavkler, M., Čačinovič Vogrinčič G., Pečjak S. in Bregar Golobič K. (2008b). Učne težave v osnovni šoli: koncept dela. Ljubljana: Pridobljene informacije so za vse strokovne delavce zelo Zavod Republike Slovenije za šolstvo. koristne predvsem pri načrtovanju vzgojno-izobraževalnega [4] Kesič Dimic, K. (2010). Vsi učenci so lahko uspešni: napotki za delo z učenci s posebnimi potrebami. Ljubljana: Založba Rokus Klett. procesa v prihodnje in če bi se šole znova zapirale in bi pouk [5] Navodila za izobraževalne programe s prilagojenim izvajanjem in dodatno potekal na daljavo. strokovno pomočjo za devetletno osnovno šolo, 2003, dostopno 17. 1. 2011 (www.zrss.si/. ./_PP_prilagojeno_izvajanje_programa_OS_maj. doc) 558 Težave pri izobraževanju odraslih na daljavo Difficulties in teleworking adult education Andrej Prašnikar SIC Ljubljana – Strokovni izobraževalni center Ljubljana Ptujska 6, 1000 Ljubljana andrej.prasnikar@siclj.si POVZETEK med učenci samimi pa omogočajo različne vrste tehnologij. Unesco opredeljuje izobraževanje na daljavo kot »vzgojno- V članku je strnjen prikaz težav, ki so se izpostavile pri izobraževalni proces in sistem, v katerem pomemben delež izobraževanju odraslih v času epidemije in dela na daljavo. pouka izvaja nekdo ali nekaj, ki je časovno in prostorsko Rezultati so omejeni na vodje izobraževanja odraslih, učitelje in odmaknjeno od učenca. Pri izobraževanju na daljavo je udeležence izobraževanja odraslih. Skupek rezultatov nam poda tehnološka podpora celostno in načrtno integrirana v vse prvine pregled skupnih težav vseh vpletenih v proces izobraževanja na vzgojno-izobraževalnega procesa, vpeta je tako v pedagoško kot daljavo. Problematika je aktualna, saj je pogosto obravnavano administrativno podporo ter učno gradivo, kar omogoča redno izobraževanje, redkeje pa izobraževanje odraslih, ki se bo izvajanje učnega procesa ob fizični ločenosti učitelja in učenca v prihodnjih letih še razširilo. Število udeležencev izobraževanja [2]. odraslih se namreč povečuje v skladu s politiko vseživljenjskega učenja. Podatki in rezultati članka temeljijo na raziskavah V novejšem času so v porastu hibridne prakse, ki kombinirajo Andragoškega centra Republike Slovenije. Cilj članka je strnjeno sinhrono in asinhrono komunikacijo med učiteljem in učencem osvetliti in prikazati težave, ki nastopajo v procesu izobraževanja ter med učenci. Te prakse združujejo uporabo elektronske pošte, odraslih in zavirajo napredek izobraževanja odraslih v procesu diskusijske skupine, spletne strani, klepeta, okolja z več izobraževanja odraslih. Z opisom težav se jih lahko zavedamo in uporabniki in spletnega oddajanja. Omogočajo jih različna jih s skupnimi močmi odpravimo ter omogočimo boljše rezultate spletna učna okolja (npr. spletne učilnice Moodle, MS Teams, na področju izobraževanja odraslih, večje zadovoljstvo učiteljev Zoom) z več prednostmi (nalaganje datotek, forumi, klepeti, in udeležencev. integrirani videokonferenčni sistemi itd.). Omejitev teh okolij pa za posameznika predstavlja potencialno preveliko število takšnih KLJUČNE BESEDE okolij in njihovih možnosti [1]. Izobraževanje odraslih, odrasli, delo na daljavo, izobraževanje V spletni šoli opravijo udeleženci program v celoti prek spleta, odraslih na daljavo učitelji pa so jim dostopni prek spletnih aplikacij ali telefona. ABSTRACT Večina učnih gradiv in usmeritev jim je posredovanih preko spleta (asinhrono) z nekaterimi sinhronimi učnimi urami. The article highlights the problems of online adult education Udeleženci se lahko učijo kjer koli in kadar koli, prek during the epidemic and teleworking. Outcomes are limited to računalnika in internetne povezave, nekatere spletne šole pa adult education leaders, teachers, and adult education zahtevajo prisotnost na sinhrono izvajanih učnih urah [1]. participants. The set of results gives us an overview of the Hibridna šola predstavlja temeljni program za svoje udeležence common problems of all those involved in the distance learning (enako kot spletna šola), značilno zanjo pa je, da ima definirano process. The issue is important since there has been many articles fizično lokacijo, na kateri so učenci redno prisotni pri pouku, regarding regular education but not as much describing adult nimajo pa rednega urnika kot tradicionalne šole. eduction, the number of which is growing steadily. This increase is due to lifelong learning policy. The article is based on the Učenci opravljajo spletne tečaje oz. dostopajo do spletnih vsebin. results of the surveys by the Andragogy Center of the Republic Dopolnilni in/ali dodatni spletni tečaji obsegajo vso vsebino of Slovenia. The article aims to summarize the problems that nekega predmeta, učenci jih lahko opravijo prostorsko in occur in the process of distance learning adult education, which časovno neodvisno, obenem pa obiskujejo klasično šolo. Večina inhibit the progress of adult. The purpose is also to raise navodil oziroma pouka poteka asinhrono z možnostjo razširitve awareness of the problems in order to find solutions and greater s sinhronimi učnimi urami. Dopolnilni in/ali dodatni spletni satisfaction of teachers and participants in adult education. tečaji s spletnim učiteljem (onsite teacher) so raznoliki, razmerje med količino samostojnega dela z gradivi ter interakcije z KEYWORDS učiteljem pa močno variira. Učenec dela z učiteljem sam ali v Adult education, adults, teleworking, online adult education majhni skupini učencev. Digitalne vsebine in programska oprema, ki omogoča trening veščin, so gradiva, ki jih uporabljajo 1 UVOD učitelji v tradicionalni šoli kot del rednega pouka ali za učenčevo domače delo. Vsebino oblikuje ponudnik ali učitelj sam, lahko Izobraževanje na daljavo je oblika izobraževanja z dvema pa učitelj uporablja oboje. Umeščena je na učiteljevo spletno temeljnima značilnostma: učitelj in učenec sta med poučevanjem stran, v spletno učno okolje (learning management system – prostorsko ločena, komunikacijo med njima in komunikacijo 559 LMS) ali aplikacijo. V našem prostoru je bila uporaba 6. pridobitev informacij preko uporabe sodobnih e- tehnologije za namene poučevanja do prvega vala epidemije storitev in zapletov, raziskovana predvsem kot del pouka v živo [1]. 7. animirani pedagoški posredniki (liki, ki vodijo učenca 2 REZULTATI skozi učno enoto na računalniku), V spletni šoli opravijo učenci ves program v celoti prek spleta, 8. virtualna okolja s posredniki (vizualno resnična okolja, učitelji pa so jim dostopni prek spletnih aplikacij ali telefona. ki simulirajo interakcije z resničnimi ljudmi in Večina učnih gradiv in usmeritev je učencem posredovana prek uporabljajo tudi resnični jezik), spleta (asinhrono) z nekaterimi sinhronimi učnimi urami. Učenci 9. didaktične igre (igre, ki so namenjene poučevanju), se učijo kjer koli in kadar koli, prek računalnika in internetne povezave. Nekatere spletne šole zahtevajo prisotnost na sinhrono 10. računalniško podprto sodelovalno učenje in projektno izvajanih učnih urah. Hibridna šola predstavlja temeljni program delo [3]. za svoje učence (enako kot spletna šola), značilno zanjo pa je, da V nadaljevanju so prikazani rezultati anket vodij izobraževanja, ima definirano fizično lokacijo, na kateri so učenci redno prisotni učiteljev in udeležencev izobraževanja odraslih. V anketah so pri pouku, nimajo pa rednega urnika kot tradicionalne šole. predstavljeni odgovori, ki po mnenju anketirancev predstavlja Učenci opravljajo spletne tečaje oz. dostopajo do spletnih vsebin. oviro pri uspešnem izvajanju izobraževanja odraslih. Anketa je Dopolnilni in/ali dodatni spletni tečaji obsegajo vso vsebino opravljena na manjšem številu anketirancev, ki so izpostavili nekega predmeta, učenci jih lahko opravijo prostorsko in težave pri delu na daljavo. Iz tega razloga ankete in sklepi časovno neodvisno, obenem pa obiskujejo klasično šolo. Večina temeljijo na osnovi vzorčne skupine anketirancev in ne navodil oz. pouka poteka asinhrono z možnostjo razširitve s predstavljajo natančnega stanja, ampak so strnjen prikaz stanja sinhronimi učnimi urami. Dopolnilni in/ali dodatni spletni tečaji na področju problematike izobraževanja na daljavo s spletnim učiteljem (onsite teacher) so raznoliki, razmerje med izobraževanja odraslih [1]. količino samostojnega dela z gradivi ter interakcije z učiteljem pa močno variira. Učenec dela z učiteljem sam ali v majhni skupini učencev. Digitalne vsebine in programska oprema, ki omogoča trening veščin, so gradiva, ki jih uporabljajo učitelji v tradicionalni šoli kot del rednega pouka ali za učenčevo domače delo. Vsebino oblikuje ponudnik ali učitelj sam, lahko pa učitelj uporablja oboje. Umeščena je na učiteljevo spletno stran, v spletno učno okolje (learning management system – LMS) ali aplikacijo. Programska oprema za ocenjevanje znanja in prikaz rezultatov daje možnosti preverjanja in ocenjevanja znanja, največkrat pa jo (v ZDA) uporabljajo na ravni šole ali na nacionalni ravni [1]. V našem prostoru je bila uporaba tehnologije za namene poučevanja do prvega vala epidemije raziskovana predvsem kot del pouka v živo. V svoji razpravi o inovativnih učnih okoljih [3] Graf 1: Na grafu je predstavljenih več dejavnikov, ki vplivajo na kakovost izobraževanja na daljavo, stolpci na omenja različna pojmovanja inovativnih učnih okolij in v sklopu desni pa prikazujejo njihovo vrednost, kot so jo opisali pojmovanja inovativnega učnega okolja kot tehnološko vodje izobraževanja odraslih. Število ob stolpcu predstavlja podprtega sistema navajata deset kategorij učnih okolij, podprtih odstotek vprašanih, ki so posamezni dejavnik izbrali kot z informacijsko komunikacijsko tehnologijo (IKT), po našem največjo težavo pri delu na daljavo[1]. mnenju uporabnih tudi pri poučevanju na daljavo: Na Grafu 1 lahko jasno vidimo, da je največji delež vprašanih kot 1. usposabljanje s pomočjo računalnika (učna enota, največjo težavo opisal usposobljenost učiteljev za delo z IKT. Iz preverjanje in povratna informacija prek tega lahko sklepamo, da moramo posodobiti izobraževanje računalniškega zaslona, učenec napreduje na naslednjo učiteljev in v sistem vključiti vse sodobne tehnologije za raven, ko opravi predhodne), izobraževanje na daljavo, s katerimi so bili soočeni ob pandemiji Covid-19. To velja tako za izobraževanje odraslih kot tudi za 2. multimedia (poučevanje, sestavljeno iz vizualnih ostale učitelje, ki so bili postavljeni pred enak izziv. Ta rešitev bi delov, npr. ilustracije, videoposnetki, in besedilnih vključila tudi naslednje tri dejavnike, za katere so anketiranci delov, npr. natisnjenih ali govorjenih), odločili, da predstavljajo ravno tako pomemben del težav 3. interaktivna simulacija (omogočajo nadzor učenca, izobraževanja na daljavo in jih v grafu vidimo nad opisanim dejavnikom. Začetna motivacija učiteljev bi bila višja, če jim npr. spreminjanje vhodnih parametrov), nove tehnologije ne bi bile tuje in bi v njih videli mnogo 4. hipertekst in hipermedia (učna gradiva, sestavljena iz možnosti, s katerimi lahko motivirajo sebe in udeležence povezav na klik), izobraževanja za učenje. Poleg tega bi izobraževanje izpopolnilo tudi njihovo znanje z didaktičnega vidika in jim nudilo tehnično 5. inteligentni tutorski sistemi (sistemi, ki učencu podporo tudi med letom, ne le v začetku. prilagajajo učno pot), 560 udeleženci sami ugotovili, da niso bili dovolj odzivni, da bi bilo izobraževanje kakovostno izvedeno, kar se sklada z ugotovitvijo učiteljev na Grafu 2. Pomembno pa je poudariti, da prvi opisani dejavnik, pomanjkanje pripomočkov, vpliva na vse ostale dejavnike kot so odzivnost in motivacija udeležencev ter njihova usposobljenost za uporabo IKT. Na grafih 1, 2 in 3 so prikazani nekateri pomembni dejavniki, ki vplivajo na kakovost izvedbe izobraževanja odraslih na daljavo, ki pa se med seboj močno povezujejo. Kot opisano, bi bila enostavna rešitev pripraviti sistem izobraževanja učiteljev in udeležencev izobraževanja, ki bi vključevala sistem spletnih okolij za izvedbo izobraževanja. Najbolj enostavno bi bilo, da bi Graf 2: Dejavniki, ki najbolj vplivajo na kakovost se javni učni zavodi v Sloveniji poenotili in izbrali en skupen izobraževanja na daljavo po mnenju učiteljev izobraževanja sistem, po katerem bi potekalo izobraževanje na daljavo na več odraslih [1]. stopnjah, tako v osnovnih kot srednjih šolah in po možnosti na fakultetah ter na izobraževanju odraslih. Poleg tega bi morali Na Grafu 2 je za razliko od Grafa 1 prikazano mnenje učiteljev udeležencem izobraževanja in učiteljem skozi izobraževanje izobraževanja odraslih, ki nakazuje, da največja težava ni v sami nuditi tehnično podporo, poleg tega pa udeležencem nuditi tudi usposobljenosti ali motivaciji učiteljev, temveč v neodzivnosti pripomočke za izvedbo programa, ki so opisani zgoraj. udeležencev izobraževanja. Omejitev spletnih orodij in izobraževanja na daljavo je ravno predstavljeni dejavnik, kjer 3 ZAKLJUČEK udeleženci, ki se ne vključujejo v spletne aktivnosti nimajo nobenih koristi od njega, niti ga učitelji ne morejo prisiliti v Pri primerjavi vseh treh grafov lahko sklepamo, da pri sodelovanje. Ta težava je deloma odgovornost posameznega izobraževalnih institucijah največ težav predstavlja udeleženca, ki se mora za opravljanje programa aktivno usposobljenost učiteljev in mentorjev za delo z IKT opremo, vključevati v vse dogodke programa. Drugi vzrok pa je lahko naslednja šibka točka, je motivacija izvajalcev andragoškega znanje IKT udeležencev, ki morajo za vključevanje znati izobraževalnega procesa. Sklepam, da večinoma učitelji in uporabljati programe in spletna orodja, ki jih uporabljajo učitelji. Posledično je ključno, da tudi udeležencem izobraževanja mentorji niso vajeni nenadne spremembe načina poučevanja. zagotovimo ustrezna izobraževanja, znanje in pripomočke, s Neposredni izvajalci so večino časa izvajali proces v katerimi se bodo lahko aktivno vključili v program. Tudi neposrednem stiku z udeleženci izobraževanja odraslih. Metode naslednji dejavnik, vzdrževanje motivacije za izvajanje poučevanja so se za večino zelo močno spremenile v smislu izobraževanja je precej odvisen od udeležencev in učiteljev, ter načina poučevanja, uporabljenih pripomočkov in pa občutkov pri njihovega znanja uporabe orodij, ki bi ga lahko rešili z opisanimi načinu podajanja snovi. Pri udeležencih izobraževanja odraslih rešitvami. se srečujemo z s starostno močno različnimi skupinami. Največ težav se izkazuje pri opremljenosti in znanju uporabe IKT opreme. Odzivnost udeležencev izobraževanja je močno odvisna od posameznika. Skupni imenovalec učiteljev in udeležencev izobraževanja je slaba začetna motivacija in vzdrževanje motivacije, ki je posledica sodelovanja preko IKT opreme ne pa v fizičnem stiku in socialnih stikih. Predlog avtorja članka je krepitev didaktičnih kompetenc za izobraževanje na daljavo v smislu izobraževanj. Opremljanje z ustrezno IKT opremo učiteljev in udeležencev izobraževanja odraslih. Poenotenje uporabe spletnih orodij za izobraževanje na daljavo. Glede na hitre spremembe pa lahko ugotovimo, da se z vsakim dnem dela na daljavo razmere izboljšujejo, saj uporabniki pridobivajo izkušnje in znanje glede izobraževanja na daljavo. Graf 3: Mnenje udeležencev izobraževanja odraslih o PREGLED LITERATURE dejavnikih, ki najbolj vplivajo na kakovost izobraževanja na daljavo [1]. [1] Možina, T., Radovan, M. in Klemenčič, S. (2020). Izkušnje z izobraževanjem odraslih na daljavo v času pandemije. Andragoški center Na grafu 3 pa je prikazano mnenje udeležencev izobraževanja Slovenije, Ljubljana 2020 [2] Bregar, L., Zagmajster, M in Radovan, M (2020). E-izobraževanje za odraslih, ki nakazuje, da je največja težava izobraževanja digitalno družbo Izdajatelj in kraj izdaje: Ministrstva za izobraževanje, odraslih opremljenost z IKT opremo v domačem okolju. V znanost in šport 2020 situaciji, v kateri smo se znašli, smo se morali vsi zelo hitro [3] [3], A., (2019). Vloga tehnologije v inovativnih učnih okoljih. Zavod Antona Martina Slomška Mreža znanja 2019 prilagoditi, hkrati pa je najpomembneje, da smo si pridobili vse pripomočke za izvajanje izobraževanja na daljavo, kot so ustrezen računalnik, računalniški sistemi in programi ter na primer spletne kamere, slušalke in zvočniki. Pričakovano pa je, da odrasli udeleženci, ki tega do sedaj niso potrebovali tudi niso imeli, velika možnost pa je tudi, da si tega niso mogli priskrbeti iz finančnih ali drugih vzrokov. Zanimivo je, da so tudi 561 Digitalizacija doma Digitalized home Roman Rehberger Šolski center Kranj, Višja strokovna šola Kranj, Slovenija rehberger@siol.net POVZETEK KEYWORDS Sodoben bivanjski prostor postaja pametni dom. To je Digitisation, intelligent home, intelligent city digitalizirana oblika enodružinske zasebne stavbe, ki je domovanje ali počitniška hiša družine. Opremljena je z avtomatiziranimi, digitaliziranimi in v sistem povezanimi 1 UVOD napravami in modernimi tehnologijami, ki delujejo v komunikacijskem omrežju, in omogočajo boljše udobje, Tehnologija pametnega doma, ki jo pogosto imenujejo tudi varčevanje z energijo, lažje in bolj učinkovito vzdrževanje, avtomatizacija doma ali domotika (iz latinskega "domus", kar večjo varnost stanovalcev in druge prilagoditve doma načinu pomeni dom), lastnikom domov zagotavlja varnost, udobje in življenja družine. Stanovalci imajo dostop do storitev in nadzor energijsko učinkovitost, tako da jim omogoča nadzor pametnih nad delovanjem sistema preko posebnih prikazovalnikov in naprav, pogosto s pametno domačo aplikacijo na svojih krmilnikov, kot so stenski zasloni; preko osebnih pametnih pametnih telefonih ali drugih omrežnih napravah. Internet stvari naprav, kot so pametni telefoni, tablični računalniki ali pametne (IoT), pametni domači sistemi in naprave pogosto delujejo ure; preko daljinskih upravljalnikov ter računalnikov in/ali več skupaj, medsebojno izmenjujejo podatke o porabi potrošnikov naprav hkrati. Članek predstavlja opremo in uporabo pametne hiše ter združevanje pametnih hiš v pametna mesta s stališča in avtomatizirajo ukrepe na podlagi preferenc lastnikov domov sedanjosti in s pogledom v prihodnost. Digitalizacija doma je [12]. Naprave je mogoče samodejno nadzorovati na daljavo od zelo aktualna tematika, zato jo vsebinsko vključujemo v koderkoli z uporabo mobilne ali druge omrežne naprave. predavanja in vaje predmeta Varovanje informacijskih sistemov Pametni dom ima svoje naprave med seboj povezane preko v drugem letniku višješolskega strokovnega programa interneta, ki nadzoruje funkcije, kot so ogrevanje, klimatizacija, Varovanje. prezračevanje, upravljanje z električno energijo ter varnostne sisteme in domači kino [9]. KLJUČNE BESEDE Pametni dom je sestavljen iz več pametnih aplikacij, ki so v Digitalizacija, pametni dom, pametno mesto večini primerov povezane med seboj in je do njih mogoče dostopati prek osrednje točke. Primeri osrednjih točk so prenosniki, tablični računalniki, pametni telefoni ali druge ABSTRACT pametne naprave [9]. Bistveni del je povezovanje osrednjih sistemov - elektrike, vode in varnostnih sistemov. Senzorji so Intelligent home is becoming a modern dwelling. This is a bistveni za spremljanje vsakega sistema in zbiranje podatkov. digitalised form of a single-family private building, the home, Ti podatki, ko jih analiziramo, nam pomagajo pri odločitvi o or the holiday house of a family. It is equipped with automated razporeditvi virov. Obremenitve, povezane z vsako nadzorno and digitalised devices and modern technologies, connected to a napravo, morajo biti prednostne, od najvišje do najnižje. system, which operate in a communication network, and Varnost podatkov in zasebnost sta bistvenega pomena, ne glede provide a better comfort, energy saving, an easier and more na vrsto stavbe - dom ali poslovni prostor. efficient maintenance, better safety for the residents, and other Izraz, s katerim se lahko srečamo, je tudi povezan dom. adjustments of the home to the way of life of the family. The Gartner je povezane domače rešitve opredelil na naslednji residents have access to the services and control over the način: »Povezane rešitve za dom sestavlja niz naprav in operation of the system through specific displays and controls, storitev, ki so povezane med seboj z internetom in se lahko such as wall screens; through personal smart devices, such as samodejno odzovejo na pred-nastavljena pravila, dostopajo do smart phones, tablet computers, or smart watches; via remote njih in upravljajo mobilne aplikacije ali brskalnik na daljavo in controls and computers, and/or several devices at the same uporabnikom pošljejo opozorila ali sporočila« [6]. time. This paper presents the equipment and use of an Pametni dom se zdi "inteligenten", ker lahko njegovi intelligent home as well as the integration of intelligent houses računalniški sistemi spremljajo toliko vidikov vsakdanjega into intelligent cities, from the point of view of the present and življenja. Hladilnik lahko na primer nadzoruje vsebino, with a view to the future. Digitisation of homes is a very topical predlaga menije in nakupovalne sezname, priporoča zdrave subject, which is why we include it in the lectures and tutorials alternative in celo naroči živila. Sistemi pametnih domov bi of the Information Systems Security course in the second year lahko zagotovili celo stalno očiščeno škatlo za smeti za mačke of the Security higher educational programme. ali zalivali hišno rastlino [2]. 562 Pomemben del pametnega doma je, da lahko zmanjšamo stanovalci v bližini in odklenejo vrata; S pametnimi varnostnimi režijske stroške in odpravimo težavo, tako da se napaka ne kamerami lahko prebivalci nadzirajo svoje domove, ko so ponovi. Natančen problem je mogoče takoj ugotoviti in odsotni ali na dopustu; Pametni senzorji gibanja prav tako lahko odpraviti. Pametni domovi delajo ljudi produktivne in varne, ugotovijo razliko med lastniki, obiskovalci, hišnimi ljubljenčki okolje pa zdravo. Infrastruktura pomaga lastnikom in in vlomilci ter lahko obvestijo organe pregona, če odkrijejo operaterjem, da sprejmejo učinkovite rešitve za kakršna koli sumljivo vedenje; Nega hišnih ljubljenčkov je mogoče vprašanja in izboljšajo zanesljivost. "Pametno" daje na videz avtomatizirati s povezanimi hranilniki; Hišne rastline in trato neživim stvarem novo dimenzijo in zasluga gre hitro rastočemu lahko zalivate s pomočjo povezanih ur; Na voljo so kuhinjski internetu stvari (IoT). aparati vseh vrst, vključno s pametnimi aparati za kavo, ki vam Vsebine, povezane z digitalizacijo doma, kot zelo aktualno lahko skuhajo svežo skodelico takoj, ko se prebudite; Pametni tematiko vsebinsko vključujemo v predavanja in vaje predmeta hladilniki, ki spremljajo datume roka uporabnosti, sestavljajo Varovanje informacijskih sistemov v drugem letniku nakupovalne sezname ali celo ustvarjajo recepte na podlagi višješolskega strokovnega programa Varovanje. S tem trenutne zaloge hrane; Monitorji gospodinjskih sistemov lahko študentom zagotovimo sodobno znanje, ki ga bodo v na primer zaznajo električni tlak in izklopijo naprave. Lahko profesionalnem življenju uporabili v praksi, saj bodo zaznajo zamašeno cev in okvaro vodovoda in izklopijo vodo, usposobljeni za svetovanje in pomoč pri učinkovitem tako da v kleti ne pride do poplave [12]; V kuhinji imajo zagotavljanju varnosti domov in drugih objektov. pametne pečice digitalne termometre za uravnavanje toplote vaše posode ko kuhate. Funkcija zagotavlja, da ne boste prekuhali obroka. Je tudi dodatna varnostna funkcija za zaščito 2 TEHNOLOGIJA V PAMETNIH pred požari; Pametne rokavice zaznajo temperaturo kože in DOMOVIH izberejo oblačila, ki ustrezajo tem odčitkom. Če menite, da vaša Tehnologija pametnih domov je splošni izraz, ki se nanaša na garderoba potrebuje posodobitev, lahko kupite oblačila prek osnovne pripomočke za dom, ki so opremljeni s spleta; Oblačila lahko izberete tudi s pomočjo pametnega komunikacijsko tehnologijo in omogoča določeno stopnjo ogledala. Če se ne morete odločiti za ustrezno barvo, so zdaj na avtomatizacije ali daljinskega upravljanja. voljo pametna oblačila, ki lahko spremenijo odtenke, odvisno Tehnologija vključuje tudi različne naprave, kot so ZigBee, Z- od vašega razpoloženja; Starejše ljudi lahko spremljate s Wave, Lutron in Wink. To so sistemi, ki združujejo vse vaše pomočjo varnostnih kamer; Pametni telefoni imajo dostop do pametne naprave in vam omogočajo eno vozlišče za dostop do dnevnih prostorov; Obstajajo tudi senzorji gibanja, ki lahko ostalih naprav, tako da se lahko povežete od kjer koli želite v opozorijo ljudi, v primeru kriminalnega dejanja; Pametni tuši domu ali zunaj njega [3]. lahko predhodno pripravijo želeno temperaturo vode [13]. Doslej je bil razvoj pametnih domačih tehnologij modularen, Tehnologija pametnega doma je tudi igrača premožnih, kot poleg nekaj eksperimentov ali namenskih projektov. Danes je dom Billa Gatesa v zvezni državi Washington imenovana modularni razvoj sestavljajo programi, ki lastnikom pametnih Xanadu 2.0, ki je tako visokotehnološka, da obiskovalcem domov omogočajo, da dodajo ali odvzemajo pametne naprave omogoča celo izbiro glasbe za razpoloženje za vsako sobo, ki jo [3]. obiščejo [2]. Tehnologija pametnega doma postaja vse bolj izpopolnjena. Kodirani signali se žično ali brezžično pošiljajo na stikala in vtičnice, ki so programirani za upravljanje naprav v vseh delih doma. Avtomatizacija doma je lahko še posebej koristna za starejše, osebe s telesnimi ali kognitivnimi okvarami in invalide, ki želijo samostojno živeti. Tehnologije v pametnemu domu: Pametni televizorji se povežejo z internetom in dostopajo do vsebin prek aplikacij, kot sta video na zahtevo in glasba. Nekateri pametni televizorji vključujejo tudi prepoznavanje glasu ali kretnje; Pametni sistemi razsvetljave Hue podjetja Philips Lighting Holding BV, ki poleg tega, da jih je mogoče nadzorovati na daljavo in jih prilagoditi, lahko zaznajo, kdaj so uporabniki v prostoru in po potrebi prilagodijo osvetlitev; Pametne žarnice se lahko regulirajo tudi glede na Slika 1: Tehnologija v pametnih domovih razpoložljivost dnevne svetlobe; Pametni termostati, kot je Nest podjetja Nest Labs Inc. so opremljeni z integriranim Wi-Fi-jem, 2.1 Domotika in avtomatizacija doma ki uporabnikom omogoča načrtovanje, spremljanje in daljinsko Področje domotike obsega vse faze tehnologije pametnega nadziranje temperatur na domu. Te naprave se tudi naučijo doma, vključno z zelo izpopolnjenimi senzorji in krmilniki, ki vedenja lastnikov stanovanj in samodejno spreminjajo spremljajo in avtomatizirajo temperaturo, osvetlitev, varnostne nastavitve, da prebivalcem zagotavljajo maksimalno udobje in sisteme in številne druge funkcije [2]. učinkovitost. Pametni termostati lahko med drugim poročajo o Avtomatizacija doma omogoča oddaljen dostop do naprav v porabi energije in uporabnike opomnijo, naj med drugim gospodinjstvu in je mogoče nadzorovati in prilagajati različne zamenjajo filtre; S pametnimi ključavnicami za vhodna in kontrole z razdalje, kot so temperatura, svetlobni sistemi, garažna vrata lahko lastniki dovolijo ali onemogočijo dostop gospodinjski aparati in paketi za domači kino. Pametni obiskovalcem. Pametne ključavnice lahko zaznajo tudi, kdaj so 563 pripomočki so povezani s vozliščem, kot so stenski terminali, Obstaja več načinov, kako lahko IoT pomaga k uspehu računalniki, spletni vmesniki ali aplikacije za pametne telefone. pametnega mesta. Nekatera mesta uporabljajo pametne Uporabniki lahko dostopajo do teh naprav prek teh vozlišč na aplikacije za parkiranje, ki ljudem omogočajo, da najdejo spletu. Zaradi zanesljivosti tega sistema na svetovnem spletu je najugodnejšo parkirno mesto. To je omogočeno s pomočjo bil uveden izraz Internet stvari (IoT). IoT je koncept, ki funkcije podatkov, zbranih iz senzorjev, ki analizirajo območja za interneta širi izven običajnega računalništva. Ponuja platformo, parkiranje. Pametne aplikacije omogočajo nadzor javnega da naprave medsebojno komunicirajo. Mednje spadajo sistemi prevoza in nadzor prometa v času prometnih zastojev [13]. za spremljanje varnosti na domu, detektorji dima, hladilniki, ključavnice vrat, pralni stroji, gospodinjski roboti za čiščenje in merilniki porabe energije [13]. Večina gospodinjstev že ima nekatere pametne naprave: digitalne televizorje, računalnike z dostopom do interneta, mikroprocesorske naprave. Vedno večji odstotek gospodinjstev je naredil prve korake v prihodnost z internetno televizijo, brezžičnimi varnostnimi sistemi in naraščajočim številom glasovnih naprav in pametnimi telefoni [1]. Da bi bili domovi resnično “pametni” potrebujemo senzorje, aktuatorje in naprave, ki upoštevajo ukaze in zagotavljajo informacije o stanju. Na trgu je že na stotine, če ne na tisoče Slika 2: Pametna mesta pametnih izdelkov za dom. Te so se v zadnjih letih razvile od preprostih senzorjev vrat in svetlobnih stikal do pametnih termostatov, kot so naprave Nest in naprave na govorni ukaz, 3 PRIMERJALNA ANALIZA kot je Amazon Echo [1]. Predstavljajmo si, da se bomo v bližnji prihodnosti zbudili v Potrebni so protokoli in orodja, ki vsem tem napravam pametnem domu, v katerem bo pametna naprava samodejno omogočajo medsebojno komunikacijo. Aplikacije za pametne zaznala, da smo se zbudili, in začela s predhodno programirano telefone, komunikacijska središča in storitve v oblaku jutranjo rutino. Voda za prhanje se bo segrela na nastavljeno omogočajo praktične rešitve, ki jih je trenutno mogoče temperaturo, tako da lahko tuš takoj uporabimo. Po prhanju implementirati [1]. bomo že imeli pripravljene obleke. Ko bomo prišli v kuhinjo, Pametni dom ustvarja priložnosti za podjetja na področjih, bo kava že skuhana in pripravljena na pametnem kavnem kot so varnost na domu, upravljanje z energijo in zdravstvena avtomatu. Poleg tega bo že pripravljen toast. Po končanem oskrba. Podjetja, ki prodajajo varnostne alarme, detektorje dima zajtrku bo hladilnik zaznal porabo in razliko uvrstil na naš in senzorje za vodo, lahko nudijo daljinsko spremljanje in nakupovalni seznam. Naprava bo samodejno zaznala, kdaj poročanje. S staranjem prebivalstva bodo storitve daljinskega bomo zapustili dom in zaklenila vrata, vključila varnostni spremljanja starejšim in kronično bolnikom omogočale, da še sistem in ugasnila luči. Čez dan lahko dom na daljavo naprej živijo v svojih domovih [1]. nadziramo preko spletnih kamer. Ko zapustimo službo, lahko Avtomatizacija doma izvaja nadzor doma od okenskih senčil pametna kuhinja že začne pripravljati vnaprej izbrano večerjo, do podajalnikov za hišne živali s preprostim pritiskom na gumb ki bo končana do našega prihoda domov [9]. ali glasovnimi ukazi. Nekatere dejavnosti, na primer nastavitev Z umetno inteligenco in zmogljivostjo strojnega učenja bodo svetilke, ki jo lahko prižgete in izklopite, so preproste in naši domovi končno dobili pametno nadgradnjo, ki jo obupno relativno poceni, medtem ko napredne nadzorne kamere potrebujejo. Naši gospodinjski aparati bodo imeli razširjene zahtevajo več časa za učenje [5]. zmogljivosti in sposobnost intuitivnega povezovanja, z uporabo 2.4 Pametna mesta platforme IoT. Leta 2020 je bilo z internetom že povezanih približno 31 milijard naprav, število pa naj bi do leta 2025 Pametna mesta prevzamejo koncept pametnega doma tako, da naraslo na 75,4 milijarde [11]. uporabljajo internet stvari (IoT) v celotnem mestu. V omrežje Napovedi prihodnosti pametnih domov s tehnologijo, ki jo so povezane različne naprave, ki zagotavljajo nadzor pri poganjata PoE in IoT je Umetna inteligenca: Pametni domovi vsakodnevnih mestnih operacijah. bodo lahko spremljali vašo lokacijo v domu, bodisi prek Če naprave uporabimo v večjem obsegu lahko pomagajo pri elektronskega zatiča, ki ga nosite na oblačilih ali elektronskih učinkovitejšem upravljanju mestnih virov, kot so vodovodna senzorjev znotraj doma. Pametni dom bo vedel, kdo in kje ste, omrežja, elektroenergetska omrežja, odstranjevanje odpadkov, te podatke pa bo uporabil za sprejem in celo predvidevanje kazenski pregon, baze podatkov in upravljanje bolnišnic. vaših potreb. Ta tehnologija pozicioniranja se že uporablja v Pametna tehnologija z informacijami in komunikacijo (IKT) domu Billa Gatesa. Pametni dom bo lahko prilagodil ogrevanja, lahko prav tako pomaga izboljšati interakcijo med ljudmi. hlajenja, glasbo in razsvetljavo, vse na podlagi zahtev osebe, ki Sistemi za zbiranje podatkov lahko analizirajo, kako prebiva v njem; Pametna razsvetljava: Pametna razsvetljava, ki prebivalstvo uporablja različne vrste tehnologije. Analiza teh jo poganja in nadzira PoE, bo spremenila način osvetlitve naših informacij bo mestu pomagala učinkoviteje odreagirati glede na domov. potrebe ljudi. Na primer s pomočjo podatkov IoT je zdaj Pametna razsvetljava se samodejno prilagodi tako, da zazna mogoče raziskati ali mesto postaja bolj okoljsko odgovorno kot prisotnost stanovalca v prostoru in ko stanovalec zapusti celota [13]. prostor, se naprave bodisi popolnoma izključijo ali ugasnejo. Senzorji lahko po določenem času ugasnejo luči, ko se uležete v 564 posteljo. Če se na primer zbudite sredi noči in greste v Vsebine, povezane z digitalizacijo doma, kot zelo aktualno kopalnico, se prižgejo luči, da boste našli pot do kopalnice. Ko tematiko vsebinsko vključujemo v predavanja in vaje predmeta se spet uležete v posteljo, se bo luč še enkrat ugasnila. Lahko Varovanje informacijskih sistemov v drugem letniku nastavite svetlost luči, da ne bodo preveč svetle, ko se vklopijo višješolskega strokovnega programa Varovanje. Študentom sredi noči. Vaš pametni dom si bo zapomnil vašo konfiguracijo, želimo namreč zagotoviti sodobno in praktično uporabno tako da boste lahko vsako napravo v svojem domu prilagodili znanje, s pomočjo katerega bodo v profesionalnem življenju po svojih željah; lahko svetovali in pomagali pri učinkovitem zagotavljanju Pametne ključavnice lahko v primerjavi s pametno varnosti modernih domov in drugih objektov. osvetlitvijo programirate glede na vaše potrebe. Obiskovalcem se lahko odobri ali zavrne dostop na podlagi določenih identifikatorjev. Serviserjem lahko dostop do doma omogoči 5 LITERATURA IN VIRI posebna avtorizacijska koda, medtem ko neznani vsiljivci ne [1] Brodsky I., 2016, The race to create smart homes is on, Dostopno na bodo imeli možnost vstopa; naslovu: https://www.computerworld.com/article/3062002/the-race-to- create-smart-homes-is-on.html (2. 8. 2021) Spremljanje doma: Pametni varnostni sistemi lahko [2] Craven J., 2020, Exploring Home Automation and Domotics, Dostopno samostojno nadzirajo dom in o morebitnih incidentih brez na naslovu: https://www.thoughtco.com/what-is-a-smart-house- poročajo lastniku stanovanja in po potrebi organom pregona. domotics-177572 (2. 8. 2021) [3] Enginess, 2015, What is Smart Home Technology? Dostopno na Poleg tega lahko pametni domovi spremljajo starejše ljudi, ki naslovu: https://www.enginess.io/insights/what-is-smart-home- živijo sami, kot dodatna pomoč, da bi jim pomagali in jih technology (2. 8. 2021) [4] Fredrik S., 2019, Overview of Smart Home Technology, Dostopno na opomnili, naj vzamejo zdravila in poskrbijo, da bodo naslovu: https://iotoverall.com/overview-of-smart-home-technology/ (2. vsakodnevne naloge uspešno in varno opravljene. V primeru, da 8. 2021) se kaj zgodi - nepričakovan padec - je mogoče obvestiti [5] Griffith E., 2020, The Best Smart Home Devices for 2020, Dostopno na naslovu: https://www.owasp.org/index.php/Cross- najbližji zdravstveni dom in se reševalce samodejno spustiti v Site_Request_Forgery_(CSRF) (20. 7. 2021) prostor, da pomagajo [11]. [6] i-SCOOP, 2018, Smart homes: home automation and the smart home in the age of IoT, Dostopno na naslovu: https://www.i-scoop.eu/internet-of- things-guide/smart-home-home-automation/ (5. 8. 2021) [7] Infineon, 2019, Smart Home: How we will live in 2030, Dostopno na 4 ZAKLJUČEK naslovu https://www.infineon.com/cms/en/discoveries/smart-home-2030/ (2. 8. 2021) V zadnjih nekaj letih so pametni domovi pridobili priljubljenost [8] Lande B. J., 2020, The Future of Smart Home Technology, Dostopno na naslovu https://www.jdsupra.com/legalnews/the-future-of-smart-home- po tehnološkem napredku v vseh gospodarskih panogah. V technology-31845/ (2. 8. 2021) sporočilu za javnost Market Watch, objavljenem leta 2019, se [9] Meulen W. 2017, The future of Smart Homes. Dostopno na naslovu: pričakuje, da se bo trg pametnih domov do leta 2023 dvignil za http://www.ithappens.nu/tag/smart-homes/ (20. 7. 2021) [10] Mordor Intelligence, 2019 Smart Homes Market - Growth, Trends, and 25 % letno. To rast pospešujejo dejavniki, kot so potrebe Forecast (2020 - 2025) Dostopno na naslovu: lastnikov stanovanj ali najemnikov za izboljšanje njihove https://www.mordorintelligence.com/industry-reports/global-smart- homes-market-industry (4. 8. 2021) energetske učinkovitosti in veliko povpraševanje po varnostnih [11] Planet Technology, 2019 The Future of Smart Homes Dostopno na napravah. V zvezi s pametnimi domačimi napravami se ljudje naslovu: https://planetechusa.com/the-future-of-smart-homes/ (20. 7. odločajo za izdelke, ki so varni, cenovno dostopni, lahko 2021) [12] Shea S., 2020 Smart home or building (home automation or domotics) dostopni in priročni. Novi izdelki pametnih domov še naprej Dostopno na naslovu: naredijo življenje bolj udobno in veliko bolj stilsko. https://internetofthingsagenda.techtarget.com/definition/smart-home-or- building . (20. 7. 2021) Glede na raziskavo, ki jo je leta 2019 izvedla Mordor [13] Smart home, 2019 The Future and History of Smart Home - What Will Intelligence, trg pametnih domov raste zaradi inovativnosti Our Homes Be like in 2040 Dostopno na naslovu: brezžične tehnologije in napredka v IoT (Internet of Things). https://www.smarthome.news/news/other-systems/the-future-of-smart- homes (20. 7. 2021) Poročilo kaže, da se bo do leta 2024 skupna letna stopnja rasti povečala za 25 %. Področja, v katere bodo velika vlaganja v prihodnje, so nadzorni in varnostni sistemi, sistemi za zabavo in nadzor klime ter sistemi za upravljanje z energijo. V bližnji prihodnosti naj bi po poročilu Mordor Intelligence za leto 2019 več kot 30 milijonov svetovnih gospodinjstev v celoti sprejeto tehnologijo pametnih domov [10]. 565 Primerjava simetričnih algoritmov Comparison of symmetric algorithms Roman Rehberger Šolski center Kranj, Višja strokovna šola Kranj, Slovenija rehberger@siol.net POVZETEK used in situations where a lot of data need to be encrypted. This paper compares some symmetric algorithms in terms of Algoritmi šifriranja na splošno temeljijo na matematiki in se architecture, scalability, flexibility, reliability and security, with lahko gibljejo od zelo preprostih do zelo zapletenih procesov, the aim of facilitating the selection of the appropriate algorithm odvisno od njihove zasnove. Imajo pomembno vlogo pri for users to send data via the Internet securely. As it is a very zagotavljanju varnosti zaupnih podatkov pred nepooblaščenimi topical subject, it is actively included in the lectures and napadi. Obstajajo tri tehnike šifriranja: simetrično šifriranje, tutorials of the Safety and Security course in the second year of asimetrično šifriranje in funkcije razpršitve (brez ključa). the Informatics programme, where students are taught about it Simetrični algoritmi za šifriranje uporabljajo isti šifrirni ključ za šifriranje in dešifriranje, za razliko od asimetričnih algoritmov using a comparative method. šifriranja, ki uporabljajo dva različna ključa. Simetrični algoritmi veljajo za varnejše od algoritmov asimetričnih KEYWORDS ključev. Nekaj simetričnih algoritmov velja za skoraj Cryptography, symmetric and asymmetric encryption, nezlomljive. V osnovi je izbira kriptografske metode odvisna architecture and algorithm security od zahtev aplikacije, kot so odzivni čas, pasovna širina, zaupnost in integriteta. Vendar ima vsak kriptografski algoritem svoje šibke in močne točke. Algoritmi simetričnih ključev so 1 UVOD tudi zelo hitri, zato se pogosto uporabljajo v situacijah, ko je veliko podatkov, ki jih je potrebno šifrirati. V članku so Kriptologija je veda o tajnosti, šifriranju, zakrivanju sporočil primerjani nekateri simetrični algoritmi glede na arhitekturo, (kriptografija) in o razkrivanju šifriranih podatkov razširljivost, prilagodljivost, zanesljivost ter varnost z namenom (kriptoanaliza). Ukvarja se s študijem in razvojem metod in olajšati izbiro primernega algoritma uporabnikom za varno metodologij za šifriranje, kjer se običajno uporabljajo skrivni pošiljanje podatkov preko spleta. Ker gre za zelo aktualno ključi, s katerimi je mogoče dešifrirati šifrirano sporočilo ali tematiko, jo aktivno vključujemo v predavanja in vaje predmeta informacijo. Omogoča shranjevanje zelo občutljivih informacij Varnost in zaščita v drugem letniku višješolskega strokovnega ali njihov prenos preko nezavarovanega omrežja (kot je programa Informatika, kjer se študenti o njej poučijo po Internet) na tak način, da jih ne more prebrati nihče, razen komparativni metodi. tistega, kateremu je informacija namenjena. Sodobna KLJUČNE BESEDE kriptografija je sestavljena iz različnih študijskih področij. Nekatera najpomembnejša so tista, ki obravnavajo simetrično Kriptografija, simetrično in asimetrično šifriranje, arhitektura in šifriranje, asimetrično šifriranje, zgoščevalne funkcije in varnost algoritmov digitalne podpise. Protokol Bitcoin uporablja kriptografske ABSTRACT metode, da zaščiti omrežje in zagotovi veljavnost vsake transakcije. Encryption algorithms are generally based on mathematics and Kriptografija simetričnega ključa (ali simetrično šifriranje) can range from very simple to very complex processes, se je v zadnjih desetletjih v veliki meri uporabljala za olajšanje depending on their design. They play an important role in tajne komunikacije med vladami in vojsko. Dandanes se ensuring that confidential data is secure from unauthorised algoritmi simetričnih ključev pogosto uporabljajo v različnih attacks. There are three encryption techniques: symmetric vrstah računalniških sistemov za povečanje varnosti podatkov. encryption, asymmetric encryption and hash functions Simetrično šifriranje se zanaša na en sam ključ, ki si ga delita (keyless). Symmetric encryption algorithms use the same dva ali več uporabnikov. Isti ključ se uporablja za šifriranje in encryption key for encryption and decryption, whereas dešifriranje tako imenovanega odprtega besedila (ki predstavlja asymmetric encryption algorithms use two different keys. sporočilo ali del podatkov, ki se kodira). Proces šifriranja je Symmetric algorithms are considered more secure than sestavljen iz navadnega besedila (vnosa) prek šifrirnega asymmetric key algorithms. There are a few symmetric algoritma, imenovanega šifra, ki nato generira šifrirano besedilo algorithms which are considered almost unbreakable. Basically, (izhod). Z uporabo simetričnih algoritmov za šifriranje se the choice of cryptographic method depends on the podatki pretvorijo v obliko, ki je ne more nihče razumeti in tudi requirements of the application, such as response time, nihče nima skrivnega ključa za dešifriranje. Ko prejemnik, ki bandwidth, confidentiality and integrity. However, every ima ključ, dobi sporočilo, algoritem obrne svoje dejanje tako, cryptographic algorithm has its weak and strong points. da se sporočilo vrne v prvotno in razumljivo obliko. Skrivni Symmetric key algorithms are also very fast, so they are often 566 ključ, ki ga uporabljata pošiljatelj in prejemnik, je lahko skupne sekvence oziroma zaporedja operacij. DES je bil razvit določeno geslo/koda ali pa je lahko naključni niz črk ali številk, v zgodnjih sedemdesetih letih prejšnjega stoletja v IBM-u. Po ki jih je ustvaril varen generator naključnih števil. Če je šifrirna pozivu ameriškega Nacionalnega urada za standarde (NBS, shema dovolj močna, je edini način, da oseba prebere ali sedaj: NIST), da bi predlagal kandidata za zaščito občutljivih dostopa do informacij, ki jih vsebuje šifrirano besedilo, z nerazvrščenih vladnih podatkov, je IBM predlagal DES uporabo ustreznega ključa za njihovo dešifriranje. Postopek algoritem. NBS je po posvetovanju z ameriško Nacionalno dešifriranja v bistvu pretvori šifrirano besedilo nazaj v navadno varnostno agencijo (NSA) leta 1976 sčasoma izbrala nekoliko besedilo. spremenjeno različico, ki je bila okrepljena proti diferencialni Dve najpogostejši sodobni shemi simetričnega šifriranja kriptoanalizi, vendar je bila oslabljena z napadi z grobo silo. temeljita na blokovnih in tokovnih šifrah. Nekateri algoritmi Leta 1977 je bil objavljen kot uradni zvezni standard za podpirajo oba načina, drugi samo en način. V tokovnem načinu obdelavo informacij (FIPS) za ZDA. DES je nastal kot je vsaka številka (običajno en bit) vhodnega sporočila šifrirana izpeljanka šifrirnega algoritma, ki ga je uporabljala ameriška ločeno. V blokovnem načinu kriptografski algoritem razdeli vojska in je uporabljala 64‐bitni ključ [5]. vhodno sporočilo v niz majhnih blokov fiksne velikosti, nato pa bloke šifrira ali dešifrira enega za drugim. Blokovne šifre 2.2 Triple DES združujejo podatke v bloke z vnaprej določeno velikostjo, vsak Trojni DES (3DES, Triple-DES, TDEA) pomeni algoritem blok pa se šifrira z ustreznim ključem in algoritmom šifriranja trojnega šifriranja podatkov in je nadgrajena različice algoritma (npr. 128-bitno navadno besedilo je šifrirano v 128-bitno DES. 3DES je bil razvit za premagovanje pomanjkljivosti šifrirano besedilo). Po drugi strani tokovne šifre ne šifrirajo algoritma DES in je bil uporabljen v poznih devetdesetih letih. podatkov navadnega besedila z bloki, temveč z 1-bitnimi koraki Pred uporabo 3DES-a uporabnik najprej generira in distribuira (1-bitno navadno besedilo je naenkrat šifrirano v 1-bitno 3DES ključ K, ki je sestavljen iz treh različnih DES ključev K1, šifrirano besedilo). Blokovna šifra naenkrat šifrira en blok K2 in K3. To pomeni, da ima dejanski ključ 3DES dolžino 3 × podatkov s fiksno velikostjo. V blokovnem šifriranju bo dani 56 = 168 bitov [6]. blok navadnega besedila vedno šifriran na isti šifrirani tekst, če 3DES trikrat uporabi algoritem DES za vsak podatkovni uporablja isti ključ, medtem ko bo isti navadni tekst šifriran na blok. Zaradi tega je 3DES veliko težje razbiti kot DES. Je tudi drugačen šifrirani tekst v tokovni šifri. V bločnem šifrirnem pogosto uporabljen algoritem šifriranja v plačilnih sistemih, algoritmu je najpogosteje uporabljena Feistelova šifra, standardih in tehnologijah v finančni industriji. Prav tako je poimenovana po kriptografu Horstu Feistelu (IBM). Feistelova postal del kriptografskih protokolov, kot so TLS, SSH, IPsec in šifra je model oblikovanja, iz katerega izhaja veliko različnih OpenVPN [6]. blokovnih šifer (npr. DES) in združuje elemente zamenjave, permutacije (transpozicije) in razširitve ključev [11]. Prednost 2.3 IDEA zasnove Feistelove šifre je v tem, da sta stopnji šifriranja in dešifriranja podobni, včasih enaki, s čimer se dramatično International Data Encryption Algorithm (IDEA) sta razvila zmanjša velikost kode ali vezja, ki je potrebna, da se šifra James L.Massey in Xuejia Lai v Zuerichu in objavila leta 1990. implementira v programsko ali strojno opremo. To je manjša revizija starejše šifre PES (angl. Proposed V članku primerjamo nekatere simetrične algoritme glede na Encryption Standard). IDEA se je prvotno imenoval IPES arhitekturo, razširljivost, prilagodljivost, zanesljivost ter (izboljšan PES) in je bil razvit, da bi nadomestil DES. Struktura varnost, kakor jih primerjamo v okviru predavanj in vaj pri algoritma je bila izbrana tako, da je pri uporabi različnih predmetu Varnost in zaščita v drugem letniku višješolskega ključnih pod blokov proces enkripcije enak postopku strokovnega programa Informatika. dešifriranja. Patent zanj ima Ascom-Tech iz Švice. Obstajata Komparativno razmišljanje je ena prvih in najbolj naravnih dva glavna razloga, da se IDEA ne uporablja tako pogosto, kot oblik človekovega mišljenja. Učenje po komparativni metodi je bilo načrtovano. Prvi je dejstvo, da je IDEA podvržena vrsti zagotavlja razumevanje podobnosti in razlik, izboljša šibkih ključev. Drugi razlog je, da trenutno obstajajo hitrejši pomnjenje, hkrati pa zagotavlja tudi sposobnost evaluacije [10]. algoritmi, ki proizvajajo enako raven varnosti. IDEA je Namen takega načina poučevanja je olajšati študentom simetrična blok-šifra, ki za vhodni 28-bitni ključ sprejme 64- izbiro primernega algoritma za varno pošiljanje podatkov preko bitni ključ in izvede 8 enakih krogov za šifriranje, v katerih se spleta. uporablja 6 različnih podključev in štirje ključi za izhodno transformacijo [2][5]. 2 SIMETRIČNI ALGORITMI 2.4 Blowfish Da bi uporabili ustrezen algoritem v določeni aplikaciji, Blowfish je bil prvič objavljen leta 1993. Gre za simetrično moramo poznati njeno moč in omejitev. Dobro pa je poznati blokovno šifro s spremenljivo dolžino ključa od 32 do 448 bitov tudi lastnosti posameznega algoritma, zato nekatere v in velikostjo bloka 64 bitov. Blowfish se lahko uporablja kot nadaljevanju na kratko opišemo. neformalna zamenjava za DES ali IDEA in je idealen za domačo in komercialno uporabo Blowfish je zasnoval Bruce 2.1 DES Schneier kot hitro in brezplačno alternativo obstoječim algoritmom šifriranja. Od takrat je bil precej analiziran in Data Encryption Standard (DES) je najbolj znan bločni šifrirni počasi postaja priljubljen kot robusten šifrirni algoritem, noben postopek s simetričnim ključem. Temelji na dveh zelo splošnih napad ni znan kot uspešen. Blowfish ni patentiran, ima konceptih – produktnih šifrirnih postopkih ter Feistelovih brezplačno licenco in je prosto dostopen za vse [4] [5]. šifrirnih postopkih. Oba koncepta vključujeta ponavljanje 567 algoritmu. Uporablja seštevanje in odštevanje, polja S, fiksne in od podatkov odvisne rotacije ter množenje [3]. 2.5 AES - Rijndael Napredni standard šifriranja AES (angl. Advanced Encryption 2.10 CAST-128 Standard) je odobril NIST konec leta 2000 kot nadomestilo za CAST-128 (ali CAST5), opisan v RFC 2144, je DES-u DES. Postopek se je začel z zahtevami NIST za objavo novega podoben kriptografski algoritem za zamenjavo-permutacijo, ki simetričnega algoritma in predlogov. Zahteve so pokazale, da uporablja 128-bitni ključ, ki deluje na 64-bitnem bloku. CAST- mora biti novi algoritem hiter in delovati pri starejših 256 (ali CAST6), opisan v RFC 2612, je razširitev CAST-128, računalniki z 8-bitnimi procesorji ter 32-bitnimi in 64-bitnimi ki uporablja 128-bitno velikost bloka in ključ s spremenljivo procesorji. NIST je v svojih zahtevah določil, da mora novi dolžino (128, 160, 192, 224 ali 256 bitov). CAST je dobil ime standardni algoritem za napredno šifriranje biti blok šifra, ki po svojih razvijalcih, Carlisle Adams in Stafford Tavares in je lahko obdeluje 128-bitne bloke s ključi velikosti 128, 192 in na voljo po vsem svetu. 256 bitov. AES uporablja algoritem Rijndael in deluje na metodah substitucije in permutacije [1]. 2.11 ARIA 2.6 AES - RC6 ARIA je 128-bitna blokovna šifra, ki jo je leta 2003 oblikovala skupina korejskih strokovnjakov. Leta 2004 jo je korejska Razvili so ga Ronald Rivest, Sidney in Yin leta 1998. RC6 agencija za tehnologijo in standarde izbrala kot standardno uporablja rotacije, odvisne od podatkov. Funkcije RC6 kriptografsko tehniko. Velikost bloka je 128 bitov. Velikosti vključujejo uporabo štirih delovnih registratorjev namesto dveh ključa so: 128, 192 ali 256 bitov označene kot ARIA-128, in vključitev množenja številk kot dodatno varnost. Uporaba ARIA-192 in ARIA-256. Število krogov za te tri različice je 12, množenja števil močno poveča difuzijo, doseženo na krog, kar 14 in 16. omogoča večjo varnost, manj krogov in večjo prepustnost. Glavna pomanjkljivost RC6 algoritma je njegova uporaba 32 2.12 CHACHA20_POLY1305 bitnih rotacijskih spremenljivk v množiteljih integriranih Pretočna šifra ChaCha20 in preverjevalnik Poly1305 sta podatkovnih tipih in zato naj ne bi bila najbolj primerna za kriptografska algoritma, ki ju je oblikoval Daniel J. Bernstein z uporabo na določenih platformah. RC6 ponuja dobro namenom zagotoviti visoko stopnjo varnosti, hkrati pa doseči zmogljivost v smislu varnosti in združljivosti. visoko zmogljivost. IETF je objavil RFC7905 in RFC7539 za 2.7 AES - Serpent spodbujanje uporabe in standardizacije pretočne šifre ChaCha20 in preverjevalnik Poly1305 v protokolu TLS. Oblikovali so ga Ross Anderson, Eli Biham in Lars Knudsen RFC7539 določa, kako združiti pretočno šifro ChaCha20 in leta 1998. Uporablja 256-bitni ključ, 128-bitni blok in deluje v Poly1305 za izdelavo sheme avtentificiranega šifriranja s načinu XTS. Serpent je bločna šifra in ne uporablja Feistelovih povezanimi podatki (AEAD) za zagotovitev zaupnosti, krogov. Na videz je preprost, z uporabo navadnih 4-bitnih S- celovitosti in verodostojnosti podatkov. polj brez dodatnih vhodov in standardnih operacij računalniške ChaCha 20 uporablja simetrično šifriranje, Poly1305 pa se logike. Vključuje tudi začetno permutacijo in inverzno začetno uporablja za preverjanje pristnosti v OpenSSL in NSS. ChaCha permutacijo, tako da se S-polja lahko izvajajo z logičnimi 20 je pri izvedbah samo s programsko opremo veliko hitrejši od operacijami namesto iskanjem tabel. To je mogoče, ker se osem AES. Na platformah, ki nimajo specializirane strojne opreme S-polj, ki jih uporablja algoritem, uporablja zaporedno in ne AES, je ChaCha 20 približno 3-krat hitrejši. vzporedno [8] [13]. Poly1305 ustvari MAC (angl. Message Authentication Code) in ga doda v šifrirano besedilo. Med dešifriranjem 2.8 AES - Twofish algoritem preveri MAC, da se prepriča, da nihče ni spremenil Twofish je naslednik Blowfish-a in tako kot njegov predhodnik šifriranega besedila. ChaCha20 za šifriranje uporablja ključ in uporablja simetrično šifriranje, zato je potreben le en 256-bitni IV (inicializacijska vrednost, nonce) za šifriranje navadnega ključ. Ta tehnika je ena najhitrejših algoritmov šifriranja in je besedila v šifrirani besedilo enake dolžine. Na koncu je dolžina idealna tako za strojno kot programsko okolje. Ko je bil šifriranega in navadnega besedila različna [7]. Twofish izdan, je bil finalist natečaja Nacionalnega inštituta za tehnologijo in znanost (NIST) za iskanje nadomestka za šifrirni 2.13 Kamelija algoritem Data Encryption Standard (DES) [13]. Kriptografski algoritem s tajnim ključem in blokovno šifro sta skupaj razvila Nippon Telegraph in Telephone (NTT) 2.9 AES - MARS Corporation in Mitsubishi Electric Corporation (MEC) leta Šifrirni algoritem MARS je razvil IBM. To je simetrična šifra 2000. Kamelija ima nekaj skupnih značilnosti z AES: velikost ključa, ki uporablja 128-bitne bloke in podpira spremenljive 128-bitnega bloka, podpora za 128-, 192- in 256-bitne dolžine velikosti ključev (od 128 do 1248 bitov). Algoritem je omrežje ključev ter primernost za programsko in strojno implementacijo Feistel tipa 3, ki je besedno (32-bitno) usmerjeno. Besedna na običajnih 32-bitnih procesorjih in 8-bitnih procesorjih (npr. orientacija bi morala prinesti uspešnost pri implementaciji pametne kartice, kriptografska strojna oprema in vgrajeni programske opreme na večino danes dostopnih računalniških sistemi). Opisana je tudi v RFC 3713. Aplikacija kamelija v arhitektur. MARS je edinstven po tem, da združuje skoraj vse IPsec je opisana v RFC 4312, uporaba v OpenPGP pa v RFC tehnike oblikovanja, ki so znane kriptografom v enem 5581. Kamelija je del protokola NESSIE. 568 2.14 Simon in Speck CAST-128/256 temelji na hrbtenici koncepta Feistelove Simon in Speck sta par lahkih blokovnih šifer, ki jih je leta strukture. CAST-128 (CAST5), opisan v RFC 2144, je DES-u 2013 predlagala NSA, namenjenih za zelo omejena programska podoben kriptografski algoritem za zamenjavo-permutacijo, ki ali strojna okolja. Medtem ko se obe družini šifer dobro uporablja 128-bitni ključ, ki deluje na 64-bitnem bloku. CAST- obneseta tako v strojni kot programski opremi, je bil Simon 256 (ali CAST6), opisan v RFC 2612, je razširitev CAST-128, optimiziran za visoko zmogljivost na strojnih napravah, Speck ki uporablja 128-bitno velikost bloka in ključ s spremenljivo pa za delovanje v programski opremi. Oba sta Feistelove šifre dolžino (128, 160, 192, 224 ali 256 bitov). Vsebuje tudi 4 S- in podpirata deset kombinacij velikosti bloka in ključa. škatle algoritem, ki se uporablja v obratnem načinu za dešifriranje. Trojni DES izvede 3 ponovitve šifriranje DES na vsakem 3 PRIMERJAVA SIMETRIČNIH bloku. Ker gre za izboljšano različico DES temelji na konceptu ALGORITMOV Feistelove strukture. 3DES uporablja 64-bitno navadno besedilo z 48 krogi in dolžino ključa 168-bitov, pretvorjenih v 16 Naša primerjava nekaterih simetričnih algoritmov temelji na podključev, vsak s 48-bitno dolžino. Tudi vsebuje 8 S-polj in določenih parametrih, kot so arhitektura, varnost, razširljivost isti algoritem je uporabljen v obratnem za dešifriranje. 3DES (hitrost šifriranja, uporaba pomnilnika, strojna oprema uporablja tri primerke DES na istem navadnem besedilu. programske opreme zmogljivost in računski čas), omejitve in Uporablja različne vrste tehnike izbire ključev, najprej so vsi prilagodljivost. V nadaljevanju bomo primerjali nekatere uporabljeni ključi različni, na drugem sta dva ključa enaka, simetrične algoritme po preprosti metodologiji. Uporabili smo eden je drugačen, v tretjem pa so vsi ključi enaki [5]. spletne vire, kot so priročniki, in raziskovalni članki, ter AES temelji na Feistelu strukturi z dolžino bloka 128 bitov proučevali izvorne kode. Vsak algoritem je bil ovrednoten na in možnimi različnimi dolžinami ključa: 126, 192 in 256 bitov. podlagi prej omenjenih parametrov. Deluje nad 128 bitnimi bloki podatkov, ki predstavljajo stanja. 3.1 Arhitektura Stanja so predstavljena obliki 4 x 4 matrik 8 bitnih zlogov. AES se izvaja kot zaporedje različnih funkcij nad stanji, ki se Arhitektura določa strukturo in operacije, ki jih algoritem lahko izvajajo v zaporednih ciklusih. Med postopkom šifriranja sistem definira, njegove lastnosti in način njihove izvedbe. Določa AES preide 10 krogov za I28-bitne ključe, 12 krogov za I92- tudi, ali je algoritem simetričen ali asimetričen, se pravi, ali bitne ključe in 14 krogov za 256-bitne ključe, da dostavi uporablja tajni ali javni ključ za šifriranje in dešifriranje. končno šifrirano besedilo ali pridobi izvorni AES z navadnim DES temelji na hrbtenici koncepta Feistelove strukture. besedilom. Preden pride do zadnjega kroga, gre ta rezultat skozi Ključ je dolžine 64 bitov, od tega se 56 bitov uporablja za devet glavnih krogov, med vsakim od teh krogov se izvedejo šifriranje in 8 za preverjanje napak. DES pretvori 64-bitne štiri transformacije; 1- podbajti, 2- premik vrstic, 3- stolpci za bloke podatkov iz navadnega besedila v šifrirano besedilo tako, mešanje, 4- dodajanje okrogle tipke. V zadnjem (10.) krogu ni da ga razdeli na dva ločena 32-bitna bloka in za vsak postopek transformacije stolpca. Dešifriranje je obratni postopek neodvisno uporabi postopek šifriranja. To vključuje 16 krogov šifriranja in uporablja inverzne funkcije: inverzni nadomestni različnih procesov kot so razširitev, permutacija, zamenjava ali bajti, vrstice s obratnim premikom in stolpci inverzne mešanice. operacija XOR z okroglim ključem skozi katere bodo šli AES - RC6 je Feistelov strukturirani algoritem zasebnega podatki med šifriranjem. Na koncu se kot izhod ustvarijo 64- ključa, ki uporablja 128-bitno navadno besedilo z 20 krogi in bitni bloki šifriranega besedila. Čeprav imamo na razpolago le spremenljivo dolžino ključa 128, 192 in 256 bitov. Ker RC6 56 bitov obstaja 7,2 x1016 (256) različnih možnosti za izbiro deluje po principu RC, lahko vzdržuje širok razpon dolžin ključa. besed, velikosti ključev in število krogov, RC6 ne vsebuje polj Bločni šifrirni postopek IDEA šifrira 64 bitne bloke S in isti algoritem se uporablja pri obrnjenem za dešifriranje. izvornega sporočila v 64 bitne bloke šifriranega sporočila z AES Serpent je simetrični algoritem ključa, na katerem uporabo 128 bitnega vhodnega ključa. Njegova podlaga je temelji nadomestna permutacijska mreža. Sestavljen je iz 128 posplošen model Feistelove strukture. Sestavljen je iz 8 bitov navadnega besedila z 32 krogi in spremenljivo dolžino računsko identičnih faz, ki jim sledi še transformacija ključa 128, 192 in 256 bitov. Vsebuje tudi 8 S-polj in isti izhodnega rezultata. 128-bitni ključ je razdeljen na osem 16- algoritem se uporablja v obratnem vrstnem redu za dešifriranje bitnih podblokov, ki se nato neposredno uporabijo kot prvih [8] [13]. osem ključnih v bloku. 128-bitni ključ se ciklično pomakne v AES Twofish tudi temelji na Feistelu strukturi. AES je blok levo za 25 položajev, nato pa se dobljeni 128-bitni blok šifra, ki uporablja 128-bitno navadno besedilo s 16 krogi in ponovno razdeli na osem 16-bitnih podblokov, ki se neposredno spremenljivo dolžino ključa 128, 192, 256 bit. Uporablja 4 S- uporabijo kot naslednji osmi ključni podblok. Postopek škatle (odvisno od ključa) in isti algoritem se uporablja v cikličnega premika se ponavlja, dokler niso ustvarjeni vsi obratnem načinu za dešifriranje [13]. potrebni 52 16-bitni podbloki ključa [5]. AES MARS temelji na heterogeni strukturi in uporablja Blowfish je tudi simetrični Feistel strukturirani algoritem 128-bitno navadno besedilo z 32 krogi in spremenljivo dolžino sestavljen iz 2 delov: del razširitve ključa in del šifriranja ključa od 128 do 448 bitov (več 32-bitni). Vsebuje samo en S- podatkov. Deluje na blokih dolžine 64 bitov in ključi, ki so box, isti algoritem se uporablja v obratni obliki za dešifriranje lahko dolgi do 448 bitov. Računsko precej zahteven postopek [3]. razširitve ključa naredi osemnajst 32 bitnih podključev in 8 x 32 Najbolj pomembni elementi algoritma Kamelija so F- bitne S škatle, ki se izpeljejo iz vhodnega ključa [4]. funkcije. Uporabljajo se med šifriranjem, dešifriranjem in ustvarjanjem pomožnih spremenljivk ključa. Funkcija F 569 sprejme 128 vhodnih bitov, jih pomeša z biti podključev in vrne ukinjena v vseh novih aplikacijah po letu 2023. TLS 1.3, 128 novih bitov. Sprememba bitov v F-funkciji se imenuje en najnovejši standard za protokole SSL/TLS, ga bo tudi prenehal krog algoritma. Klici s funkcijo F so zbrani v blokih. Vsak blok uporabljati. vsebuje šest krogov. Šestkrožni bloki (to pomeni blok šestih Blowfish je ranljiv za rojstnodnevne napade, zlasti v klicev F-funkcije) so ločeni s klici FL-funkcij in FL-1 funkcij. kontekstih, kot je HTTPS. Leta 2016 je napad SWEET32 Upravljajo se z 64-bitnimi dolgimi deli podatkov in jih mešajo s pokazal, kako izkoristiti rojstnodnevne napade (dešifriranje podključi kli. Tako šifrirni kot dešifrirni algoritem bosta izvedli šifriranega besedila) proti šifram s 64-bitno velikostjo bloka. nekaj ponovitev zgoraj opisanih 6-krožnih blokov. Število Projekt GnuPG priporoča, da se Blowfish zaradi majhnosti ponovitev je odvisno od dolžine trenutno uporabljenega tajnega bloka ne uporablja za šifriranje datotek, večjih od 4 GB [4][14]. ključa: 3 ponovitve 6-okroglih blokov-za 128-bitni tajni ključ, 4 IDEI je zaradi svoje odpornosti proti kriptoanalitičnim ponovitve 6-okroglih blokov-za 192-bitne ali 256-bitne tajne napadom in zaradi vključitve v več znanih kriptografskih ključe. Poleg tega se na začetku in na koncu šifrirnega in poslov mogoče zaupati [2]. dešifrirnega algoritma izvedejo dodatne operacije, kjer se CAST uporabi operacijo spremenljive velikosti ključa, da jo podatkovni biti dodajo bitom podključev kwi. Podključi, ki se poveča varnost, CAST je na visoki ravni odporen proti uporabljajo za šifriranje vsakega podatkovnega bloka (ali za linearnim in diferencialnim napadom. dešifriranje vsakega bloka šifriranega besedila), se ustvarijo v Strokovnjaki za varnost trdijo, da je AES - Rijndael varen, ločenem procesu. Na podlagi skrivnega ključa za vsak blok, se če se pravilno izvaja. Vendar je treba šifrirne ključe AES - izračuna na desetine podključev. Uporabljajo se za različne Rijndael zaščititi. Tudi najobsežnejši kriptografski sistemi so operacije v glavnem algoritmu. lahko ranljivi, če heker dobi dostop do šifrirnega ključa. Leta Tako CHACHA20_POLY1305 kot POLY1305 veljata za 2009 je bil znan napad ključnega pomena na AES-128. Za enostavna izvedbo in zagotavljata odlično zmogljivost. prepoznavanje strukture šifriranja je bil uporabljen znani ključ. CHACHA20_POLY1305 uporablja 256-bitni ključ in 96-bitni Vendar je bil napad namenjen le 8-krožni različici AES-128, ne blok. POLY1305 lahko uporabimo tudi kot algoritem pa standardni 10-krožni različici, zaradi česar je grožnja zgoščevanja. Med postopkom šifriranja/preverjanja pristnosti se razmeroma majhna [1]. Za primer varnosti AES-a si poglejmo, iz 256-bitnega ključa in bloka generira enkratni ključ kako dolgo bi nekdo razbijal eno geslo, šifrirano z 256-bitnim POLY1305. CHACHA20 nato izvede svoje šifriranje z uporabo ključem AES. Če želite prekiniti en 16-bajtni del podatkov, istega ključa in bloka. POLY1305 preveri pristnost sporočila. šifriranih z AES-256-bitnim ključem, bi s pomočjo grobe sile Izhod je del šifriranega besedila enake dolžine kot navadni (metoda Brute Force) trajalo stoletja. Skupna količina tekst, ki je bil vnesen, pa tudi 128-bitna oznaka MAC [7]. permutacij, ki so možne s 256-bitnim ključem, je 2256, zaradi česar je razbijanje šifriranega sporočila AES-256 skoraj 3.2 Varnost nemogoče. Tudi z uporabo 128-bitnega ključa, ki je najmanjša Varnost določa, kako natančno deluje algoritem z uporabo velikosti, je še vedno na voljo 2128 različnih permutacij, kar bi računalniških virov, ki so mu na voljo. Simetrični algoritmi še vedno trajalo več desetletij. zagotavljajo dokaj visoko raven varnosti, hkrati pa omogočajo Varnost AES - RC6 je v povsem naključnem nizu njegovih hitro šifriranje in dešifriranje sporočil. Relativna enostavnost izhodov bitov s 15 krogi ali manj, ki se izvajajo na vhodnih simetričnih sistemov je tudi logistična prednost, saj zahtevajo blokih 128 bitov, eden od parametrov za izdelavo algoritma manj računalniške moči kot asimetrični. Poleg tega lahko šifriranja odporen proti napadom je, da njegova proizvodnja varnost, ki jo zagotavlja simetrično šifriranje, povečamo popolnoma sledi naključni niz bitov. Napad linearne kriptalize preprosto s povečanjem dolžin ključev. Za vsak bit, dodan je lahko izveden za 16 krogov RC6, vendar zahteva 2119 dolžini simetričnega ključa, se težava razbijanja šifriranja z znanih navadnih besedil, ki onemogočajo izvedljivost takega napadom surove sile eksponentno poveča. napada. Tudi algoritem RC6 je močan v primerjavi z Varnost simetričnih šifrirnih sistemov temelji na tem, kako diferencialom kriptanalize, ki je delovala v več kot 12 krogih. težko je naključno uganiti ustrezen ključ. Za razbitje 128- Po besedah avtorja AES - Serpent je 16 krogov Serpent čisto bitnega ključa bi na primer porabili milijarde let, da bi ključ primernih proti vsem znanim vrstam napadov, vendar je zaradi uganili z običajno računalniško strojno opremo. Daljši kot je večje varnosti povečan na 32 krogov [13]. šifrirni ključ, težje ga je razbiti. Ključi, ki so dolgi 256 bitov, na AES Twofish je izjemno varen za uporabo. Razlog, da NIST splošno veljajo za zelo varne in teoretično odporne na kvantne ni hotel uporabiti Twofish je, da je počasnejši v primerjavi z računalniške napade s surovo silo. algoritmom šifriranja Rjindael. Eden od razlogov, da je Twofish Danes DES ni več primeren za uporabo, saj so ga razbili tako varen je, da uporablja 128-bitni ključ, ki je skoraj številni raziskovalci varnosti. Leta 2005 je bil DES uradno neprepusten za napade z grobo silo. Količina procesorske moči zastarel in ga je nadomestil algoritem za šifriranje AES. in čas, potreben za napad z grobo silo 128-bitnega ključa Največja slabost DES-a je bila dolžina ključa za šifriranje, šifriranega sporočila, naredi vse dešifrirane informacije zaradi česar je bilo razbijanje šifre enostavno. Danes nedejavne, saj lahko dešifriranje enega sporočila traja desetletja. najpogosteje uporabljani protokol TLS, ne uporablja metode To pa ne pomeni, da Twofish ni odporen na vse napade. Del šifriranja DES. šifrirnega algoritma Twofish uporablja vnaprejšne izračune. V 3DES algoritmu so raziskovalci odkrili ranljivost Predračunavanje teh vrednosti naredi Twofish ranljiv za napade Sweet32. To odkritje je povzročilo, da je varnostna industrija stranskih vrat, vendar pa odvisnost ključa z zamenjavo pomaga začela razmišljati o opuščanju algoritma, Nacionalni inštitut za zaščititi pred napadi stranskih vrat. Na Twofish je bilo standarde in tehnologijo (NIST) pa je opustitev objavil v izvedenih več napadov, toda ustvarjalec algoritma Bruce osnutku smernic, objavljenem leta 2019. Uporaba 3DES bo Schneier trdi, da to niso bili resnični napadi kriptoanalize. To 570 pomeni, da do praktičnega preloma algoritma Twofish še ni AES za zaščito tajnih podatkov. DES se v nekaterih primerih še prišlo. vedno uporablja združljivost za nazaj. AES MARS ponuja večjo varnost in hitrost kot trojni DES Na splošno varnostni strokovnjaki menijo, da je AES varen in DES. To je ponovljena šifra z nenavadno 32 krogi različnih pred napadi z grobo silo, pri katerem se preverijo vse možne tipov. Upoštevani so srednji krogi MARS kot njegov močni kombinacije tipk, dokler se ne najde pravilen ključ. Vendar varnostni del. Varnost MARS je odvisna od podatkov rotacije mora biti velikost ključa, ki se uporablja za šifriranje, dovolj (ali funkcije z logično zapletenostjo). MARS algoritem je zelo velika, da je sodobni računalniki ne morejo razbiti, tudi če odporen na vse vrste napadov relativnega ključa in časovnih upoštevamo napredek v hitrosti procesorja, ki temelji na napadov. Moorejevem zakonu. 256-bitni šifrirni ključ je pri napadih z Kamelija velja za sodobno, varno šifro. Tudi z možnostjo grobo silo bistveno težje uganiti kot 128-bitni ključ; ki pa se manjše velikosti ključa (128 bitov) se jo zdi nemogoče razbiti z dolgo ugiba. Kljub temu 256-bitni ključi zahtevajo tudi več uporabo grobe sile. Do sedaj ni znanih uspešnih napadov, ki bi procesorske moči, njihovo izvajanje pa lahko traja dlje. Kadar znatno oslabili šifro. Japonska šifra ima stopnje varnosti in je napajanje težava, zlasti pri majhnih napravah ali kjer je sposobnosti obdelave, ki so primerljivi s šifro AES/Rijndael prenos počasnejši, so 128-bitni ključi boljša možnost izbire. [14]. AES se pogosto uporablja za zaščito podatkov v mirovanju. Varnost CHACHA20_POLY1305 je zelo blizu osnovnemu Aplikacije za AES vključujejo diskovne pogone, šifriranje baze algoritmu blokovnega šifriranja AES. Posledično je edini način, podatkov in šifriranje pomnilnika. Po drugi strani se algoritem da napadalec zlomi Poly1305, zlom AES [7]. RSA (Rivest-Shamir-Adleman) pogosto uporablja v spletnih brskalnikih za povezavo s spletnimi mesti, v povezavah 3.3 Razširljivost navideznega zasebnega omrežja (VPN) in v številnih drugih Razširljivost je eden glavnih elementov, na katerih temeljijo aplikacijah. algoritmi šifriranja, ki jih lahko analiziramo. Razširljivost je Za razliko od AES, ki uporablja simetrično šifriranje, je odvisna od določenih parametrov, kot so uporaba pomnilnika, RSA osnova asimetrične kriptografije. Simetrično šifriranje stopnja šifriranja, strojna oprema programske opreme izvedba. vključuje pretvorbo navadnega besedila v šifrirano besedilo z Porabo pomnilnika lahko definiramo kot število funkcij istim ključem ali tajnim ključem za njegovo šifriranje in izvede algoritem, manjša kot je poraba pomnilnika večja bo dešifriranje. Asimetrično šifriranje za šifriranje uporablja dva učinkovitost. Stopnja šifriranja je čas obdelave algoritma za ključa: javni in zasebni ključ. Če se šifriranje izvede z javnim določeno velikost podatkov. Stopnja šifriranja je odvisno od ključem, se lahko dešifriranje zgodi le s povezanim zasebnim hitrosti procesorja in zapletenosti algoritma itd. Zaželena je ključem in obratno. Običajno se ključi RSA uporabljajo, če najmanjša vrednost stopnje šifriranja. Strojna in programska obstajata dve ločeni končni točki. Čeprav šifriranje RSA dobro oprema mora biti v skladu z algoritem za boljše delovanje. deluje pri zaščiti prenosa podatkov na večje razdalje, je njegovo Če primerjamo algoritme lahko opazimo, da je algoritem delovanje slabo. Rešitev je združiti šifriranje RSA s šifriranjem Blowfish najboljši med vsemi ostalimi obstoječi algoritem v AES, da bi tako izkoristili varnost RSA z zmogljivostjo AES. smislu učinkovitosti šifriranja (visoko) in poraba pomnilnika To se lahko doseže tako, da ustvarimo začasni ključ AES in ga (najmanj). Toda njegova varnost je bila ogrožen, zato je zaščitimo s šifriranjem RSA. trenutno zastarel. Da bi bila primerjava čimbolj natančna je Če primerjamo DES in AES, je AES matematično potrebno primerjati tudi druge funkcije (varnost, arhitektura, učinkovitejši. Glavna prednost AES je v ključnih možnostih prilagodljivost in robustnost), vendar je zelo težko pravilno dolžine. Čas, potreben za razbijanje šifrirnega algoritma, je oceniti algoritme, ki bi bili prilagodljivi za vse platforme. neposredno povezan z dolžino ključa, ki se uporablja za zaščito komunikacije-128-bitni, 192-bitni ali 256-bitni ključi. Zato je AES eksponentno močnejši od 56-bitnega ključa DES. 4 PRIMERJALNA ANALIZA Šifriranje AES je tudi bistveno hitrejše, zato je idealno za Ko želijo hekerji dostopati do sistema, si bodo prizadevali za aplikacije, vdelano programsko opremo in strojno opremo, ki dostop do najšibkejše točke, ki običajno ni šifriranje, ne glede zahtevajo nizko zakasnitev ali visoko prepustnost. na to ali gre za 128-bitni ključ ali 256-bitni ključ. Uporabniki Na simetrične algoritme Twofish, Serpent in AES trenutno morajo poskrbeti, da programska oprema varuje uporabniške ni znanih napadov, zato lahko kar zadeva varnost, uporabite podatke tako, kot se pričakuje in da celotni proces nima šibkih katero koli od njih. AES ima rahlo prednost, ker se zelo pogosto točk. Poleg tega ne sme biti sive cone ali negotovosti glede uporablja, zato boste, bolj verjetno hitro dobili ustrezne shranjevanja in ravnanja s podatki. Na primer, če so podatki v posodobitve programske opreme. Sestava Twofish je oblaku, bi morali uporabniki poznati lokacijo oblaka. pravzaprav bolj varna kot AES in je s teoretičnega vidika Najpomembneje je, da mora biti izbrana varnostna programska nezlomljiva. oprema enostavna za uporabo, da uporabnikom ne bo treba izvajati nezaščitenih rešitev za opravljanje svojega dela. Ameriška vlada je pred več desetletji razvila algoritme DES, da bi zagotovila, da vsi vladni sistemi uporabljajo enak, varen standard za olajšanje medsebojne povezanosti. DES je leta služil kot vez vladne kriptografije, ko so raziskovalci s porazdeljenim računalniškim sistemom razbili 56-bitni ključ algoritma. Leta 2000 se je ameriška vlada odločila uporabiti 571 Tabela 1: Primerjava simetričnih algoritmov 5 ZAKLJUČEK Struktu števil Algor ra Dolžina Velikos # S o Oblik Vsak od kriptografskih algoritmov ima slabosti in prednosti. item Izdana algorit besedil t ključa ška krogo ovalci Kriptografski algoritem izberemo glede na zahteve aplikacije, ma a tle v ki bo uporabljena. Algoritmi so predstavljeni na podlagi Uravnot različnih parametrov. Glavni cilj je bil analizirati uspešnost večine priljubljenih simetričnih algoritmov v smislu preverjanja DES 1975 eženo omrežje 64 bitov 56 8. 16. IBM pristnosti, prilagodljivosti, zanesljivosti, robustnosti, Feistel razširljivost, varnosti. Želeli smo poudariti glavno slabost Substitu Xueji omenjenih algoritmov, zagotavljanje preglednosti moči in cijsko- a Lai omejitve vsakega algoritma za aplikacijo. IDEA 1991 permuta 64 bitov 128 8. in Primerjali smo nekatere simetrične algoritme glede na cijska James arhitekturo, razširljivost, prilagodljivost, zanesljivost ter struktur Mass varnost, kakor jih primerjamo v okviru predavanj in vaj pri a ey predmetu Varnost in zaščita v drugem letniku višješolskega Uravnot Blowf eženo Bruce strokovnega programa Informatika. Učenje po komparativni ish 1993 omrežje 64 bitov 32-448 4. 16. Schne metodi zagotavlja razumevanje podobnosti in razlik, izboljša Feistel ier pomnjenje, hkrati pa zagotavlja tudi sposobnost evaluacije [10]. Carlis Študenti znajo izbirati primerne algoritme za varno pošiljanje le podatkov preko spleta. Uravnot Adam Na podlagi primerjave je algoritem Blowfish odlična izbira CAST 1996 eženo s in v primeru časa in pomnilnika glede na merila ugibanja napadov omrežje 64 bitov 40-128 4. 12- 16 Staffo in zahtevane lastnosti, saj beleži najkrajši čas med vsemi Feistel rd algoritmi in porabi najmanj pomnilnika. Če sta zaupnost in Tavar integriteta glavna dejavnika, lahko izberemo algoritem AES. Če es je povpraševanje po aplikaciji omrežna pasovna širina, je DES Uravnot najboljša možnost. Menimo, da se algoritma Blowfish in AES 3DES 1998 eženo omrežje 64 bitov 168 8. 48 IBM uporabljata za preprečevanje napadov in jih je mogoče uporabiti Feistel poleg vseh internetnih protokolov, ki temeljijo na IPv4 in IPv6. Vince Med analizo je bilo ugotovljeno tudi, da je AES - Rijndael AES Uravnot glede varnosti, prilagodljivosti, uporabe pomnilnika in (Rijen 1998 eženo 128 128, nt zmogljivost šifriranja najboljši med vsemi. Predstavljeni so bili dal) omrežje bitov 192, 256 1. 10,12, 14 Rijme Feistel n različni dejavniki, kot so dolžina ključa, vrsta šifriranja, Uravnot velikost bloka in možni ključi. Vsi ti algoritmi se primerjajo v Ron RC6 1998 eženo 128 128, smislu šifriranja in časa dešifriranja ter njihovih rezultatov. omrežje bitov 192, 256 20. Rives Splošna teoretična in praktična primerjava je pokazala, da je Feistel t idr. AES boljši v smislu izvajanja hitrost, poraba časa, čas za Ross prekinitev algoritma in varnost. Za povečanje velikosti ključa Ander od 128 do 448 Blowfish algoritem daje sporočilom več son, zasebnosti in zagotavlja visoko kakovost podatkov prenašanje AES Uravnot Eli prek katerega koli nevarnega medija. RC6 in Twofish delujeta (Serpe 1998 eženo 128 128, Biha nt) omrežje bitov 192, 256 8. 32 hitreje kot AES, pri čemer so bile 256-bitne različice ključev Feistel m in Lars 42-odstotno hitrejše pri velikosti paketa 10 MB. Poleg tega Knud večje velikosti ključev v RC6 in Twofish niso bistveno vplivale sen na čas izvajanja, medtem ko je v AES velikost ključa opazno Uravnot vplivala na zmogljivost [9]. MAES in IDEA sta učinkovitejša in Twofi eženo 128 128, Bruce potrebujeta manj časa za šifriranje, medtem ko sta MAES in sh 1998 omrežje bitov 192, 256 4. 16. Schne AES učinkovita v smislu časa dešifriranja in porabe pomnilnika Feistel ier [12]. Uravnot Naše prihodnje delo se bo osredotočilo na primerjavo Mars 1998 eženo 128 simetričnih in asimetričnih algoritmov. omrežje bitov 128-448 1. 32 IBM Feistel LITERATURA IN VIRI Uravnot Nippo Kamel eženo 128 128,192, n [1] Cobb G: 2021, Advanced Encryption Standard (AES), Dostopno na ija 2000 omrežje bitov 256 4 18 ali 24 Teleg naslovu: https://searchsecurity.techtarget.com/definition/Advanced- Feistel raph Encryption-Standard (14. 8 . 2021) [2] Educba, 2020, IDEA Algorithm, Dostopno na naslovu: Danie https://www.educba.com/idea-algorithm/ (10. 8 . 2021) Cha l J. [3] Galli, 2000, MARS Algorithm, Dostopno na naslovu: cha20 2008 ARX 64 bitov 128, 256 20 Berns http://reto.orgfree.com/us/projectlinks/MARSReport.html (1. 8 . 2021) tein [4] Gatliff, 2003, Encrypting data with the Blowfish algorithm, Dostopno na naslovu: https://www.embedded.com/encrypting-data-with-the-blowfish- Uravnot 32, 48, 64, 72, algorithm/ (1. 8 . 2021) Speck 2013 eženo 64, 96, 96, 128, [5] Geeksforgeeks 2021, Simplified International Data Encryption omrežje 128 144, 10 32-72 NSA Algorithm (IDEA), Dostopno na naslovu: Feistel bitov 192, 256 https://www.geeksforgeeks.org/simplified-international-data-encryption- algorithm-idea/ (10. 8 . 2021) [6] Henry, 2018, 3DES is Officially Being Retired, Dostopno na naslovu: https://www.cryptomathic.com/news-events/blog/3des-is-officially- being-retired (9. 8 . 2021) 572 [7] Mkyong, 2021, ChaCha20-Poly1305 encryption examples, Dostopno na [11] Tutorialspoint 2021, Feistel Block Cipher, Dostopno na naslovu: naslovu: https://mkyong.com/java/java-11-chacha20-poly1305- http://www.thedesignengineering.com/index.php/DE/article/view/2748 encryption-examples/ (14.8.2021) (10. 8. 2021). [8] Quadibloc, 1998, SERPENT, Dostopno na naslovu [12] Wani A., Rana, Q.P., Pandey, N.: 2021, Performance Evaluation of http://www.quadibloc.com/crypto/co040403.htm (1. 7. 2021) Modified AES Algorithm in comparison with Advanced Symmetric Key [9] Saraiva, 2019, PRISEC: Comparison of Symmetric Key Algorithms for Cryptographic Algorithms, Dostopno na naslovu IoT Devices, Dostopno na naslovu: http://www.thedesignengineering.com/index.php/DE/article/view/2748 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806263/ (15.8.2021) (8. 8. 2021). [10] Silver, Harvey F. 2010, Compare & Contrast: Teaching Comparative [13] Veracrypt 2014, Encryption Algorithms > Serpent, Dostopno na naslovu: Thinking to Strengthen Student Learning. Dostopno na naslovu: https://veracrypt.eu/en/docs/serpent/ (10. 8 . 2021) http://books.google.si/books?id=i84g1NdLxVkC&printsec=frontcover& [14] Wikipedija 2021, Blowfish (cipher), Dostopno na naslovu: hl=sl#v=onepage&q&f =false (7. 9 . 2021) https://en.wikipedia.org/wiki/Blowfish_(cipher) (9. 8 . 2021) 573 E-učenje in e-poučevanje naravoslovnih vsebin E-learning and e-teaching of science Petra Simčič OŠ narodnega heroja Maksa Pečarja Ljubljana Črnuče, Slovenija petra.simcic@guest.arnes.si POVZETEK ABSTRACT Ker sta učitelj in učenec med šolanjem na daljavo prostorsko Since the teacher and the student are spatially separated during ločena, je pri poučevanju naravoslovnih predmetov glavni izziv distance learning, the main challenge in teaching science subjects kako učencem približati naravoslovno (kritično) razmišljanje, ki is how to bring students closer to science (critical) thinking, ga v največji meri omogočajo opazovanje različnih materialov in which is mostly enabled by observing different materials and modelov, predvsem pa izvajanje poskusov. Slednje je na prvi models, and especially conducting experiments. At first glance, pogled v času šolanja na daljavo težko izvedljivo, a je z dobrim conducting experiments is difficult to do during distance learning, načrtovanjem, domiselnim strukturiranjem učnih enot, uporabo but with good planning, imaginative structuring of learning units, učinkovitih didaktičnih strategij in optimalno komunikacijo use of effective didactic strategies and optimal communication preko elektronskih tehnologij, prav tako mogoče in dovoli via electronic technologies, it is also possible and allows to learn usvojiti zastavljene učne cilje. Sprotno spremljanje znanj in the set learning goals. Ongoing monitoring of the knowledge and spretnosti posameznega učenca je pokazalo njegov napredek ali skills of an individual student has shown his progress or the need pa potrebo po dodatni pomoči in spodbudi. Skozi primere dobrih for additional help and encouragement. Through examples of praks prikažem možne načine e-poučevanja naravoslovja v 6. in good practice, I show possible ways of e-teaching science in 6th 7. razredu ter biologije v 8. in 9. razredu osnovne šole. Glavna and 7th grade and biology in 8th and 9th grade of primary school. spodbuda za delo je bila redna komunikacija, ustna razlaga ob The main stimulus for the work was regular communication, slikah, zapisih, diagramih, videih, sprotno preverjanje verbal explanation with pictures, notes, diagrams, videos, real- razumevanja na različne načine (ustno, preko kviza, z učnim time checking of comprehension in various ways (orally, through listom, z izdelanim miselnim vzorcem, s Kahoot-om), ustno in a quiz, with a worksheet, with a thought pattern, with Kahoot), pisno podajanje navodil za samostojno ali skupinsko delo ter verbally and in writing giving instructions for individual or group naknadni pregled le-tega, kar je potekalo preko skupnih video work and subsequent review of it, which took place through joint konferenc in po potrebi tudi individualnih video klicev ali kratkih video conferences and, if necessary, individual video calls or sporočil. Med razlago novih vsebin sem s pomočjo modelov short messages. During the explanation of the new content, I was uspela bolj nazorno prikazati zgradbo, delovanje nekaterih able to use models to show more clearly the structure, operation struktur in procesov. Večina učencev je z veseljem in zelo of some structures and processes. Most of the students happily kvalitetno opravila poskuse ter druge praktične vaje za katere so and with high quality performed experiments and other practical kot izkaz opravljenega dela oddali sliko ali posnetek. Boljši exercises for which they submitted a picture or recording as a vpogled v mikro strukture (tkivne preparate, drobne organizme, statement of the work done. Better insight into micro structures na primer protiste in vodne bolhe) je omogočila projekcija (tissue preparations, tiny organisms such as protists and water mikroskopiranja z okularno kamero in softwerom Motic Play [3]. fleas) was provided by the projection of microscopy with an Zelo dobre rezultate in večjo angažiranost vseh učencev je ocular camera and Motic Play software [3]. Very good results prineslo tudi delo v manjših skupinah. Uporaba različnih metod, and greater engagement of all students was achieved by working ki jih sodobna tehnolgija omogoča, se je izkazala kot dober način in small groups. The use of various methods provided by modern dela za dosego boljšega razumevanja naravoslovnih vsebin in technology has proven to be a good way to work to achieve a temeljnih bioloških konceptov. better understanding of natural science content and basic biological concepts. KLJUČNE BESEDE E-učenje, e-poučevanje, naravoslovje, biologija, KEYWORDS eksperimentalno delo E-learning, e-teaching, natural science, biology, experiments in science 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 1 UVOD be honored. For all other uses, contact the owner/author(s). Pouk na daljavo sem vodila preko okolja Microsoft Teams. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). Za vsak predmet in oddelek sem ustvarila ekipo, v kateri so bila 574 na strani objave podana tedenska navodila – urnik, vsebine in Sledila so navodila za delo doma v času ure naravoslovja, ki dejavnosti, ki so se v tistem tednu izvajale (Slika 1). ni bila vodena kot video ura (dodeljena naloga), pri čemer so učenci izvajali poskuse z materiali, predmeti, ki jih uporabljajo v vsakodanjem življenju (žlica, kuhalnica, kamen, voda, plastika). Vsak učenec je poslikal in poslal vsaj dva opravljena poskusa, ki so jih med naslednjo video konferenco predstavili ostalim in skupaj smo po potrebi dodali še kakšen komentar. Pokazala sem jim pladenj s predmeti, ki so iz različnih materialov in jih z lahkoto najdejo doma in nato izpolnijo učni list, ki jim pomaga bolje opazovati snovi, jih razvrstiti po različnih ključih in pridobiti izkušnjo (Slika 12). Sledilo je ustno preverjanje znanja o poznavanju gradnikov Slika 1: Tedenski razpored dejavnosti; objava v Teams in lastnosti snovi. Vsak učenec je ustno dobil najmanj tri ekipi vprašanja, na tri pa je moral pisno odgovoriti in odgovore oddati, rezultate sem sproti beležila v tabelo. Vsakemu odgovoru je Pri vsem tem sem sledila letni pripravi in interaktivnemu učnemu sledila povratna informacija, pri čemer so sodelovali tudi ostali načrtu [4], ki je poudaril operativne cilje in vsebine, ki naj bi se učenci. Po enem tednu semznanjepreverjala s kvizom (Slika 2, v celoti obravnavale in naj bi jih učenci usvojili. Skozi ta Slika 3), tudi te rezultate sem vpisala v tabelo. prispevek predstavljam nekaj primerov svojega poučevanja naravoslovnih predmetov na daljavo, pri katerem sem se trudila izvesti čim več praktičnega dela in učencem omogočiti učenje s poskusi ali tako imenovano izkustveno učenje, za katero menim, da je najuspešnejša pot k razumevanju naravoslovnih zakonitosti. 2 PREGLED LITERATURE Učitelji podajamo znanje na različne načine. Še vedno se najpogosteje uporablja tradicionalen pouk, to je frontalna učna oblika, pri kateri učitelj usmerja vse učence hkrati, ti pa so ob takšnem načinu poučevanja manj aktivni [6]. Vedno bolj pa se oblikujejo smernice sodobnega pouka, ki imajo za poudarek eksperimentalno delo, ki učencu omogoča pridobivanje konkretnih izkušenj iz katerih išče odgovore na vprašanja, hkrati pridobiva nove veščine in miselna aktivnost je večja [6]. Do takšnih zaključkov je najverjetneje prišel že vsak učitelj, ki že Slika 2: Google obrazci kakšno leto poučuje naravoslovni predmet. Prav iz takšnih izkušenj izhajam tudi sama in te so bile glavno vodilo pri pripravi pouka naravoslovja in biologije na daljavo. Rezultati raziskav, opravljenih po prvem valu epidemije covida-19, so nakazali številne aktivnosti, ki jih je smiselno vpeljati na ravni šol in sistema, da bi izboljšali ustreznost organizacije in izvajanja izobraževanja, povečali učinkovitost učenja in poučevanja z uporabo digitalne tehnologije ter izboljšali kakovost pedagoškega vodenja [7]. Ena od prednosti e-izobraževanja je prav gotovo učinkovitejša organizacija dela, saj so gradiva dostopna 24 ur ves teden in hkrati omogoča vključitev vseh različnih čutil v procesu učenja, če je le motivacija in stik (čeprav posredni) med učiteljem in učencem zadosten. Od učitelja pa je pričakovati, da bo zmogel glavni fokus iskanja znanja prenesti na učenca. To vlogo uspešno opravi izkustveno učenje z eksperimentalnim delom. Pri naravoslovju v 6. razredu smo poglavje o snoveh obravnavali med video konferencami ob uporabi učbenika [5], kjer sem razlago podpirala z različnimi materiali, z demonstracijo (npr. električni krog v katerega vstavljamo različne materiale in ugotavljamo, kdaj je sklenjen in kdaj ne, kateri materiali so električni prevodniki in kateri ne (Slika 4)), pred tem pa na podlagi vprašanj, na katera so učenci odgovarjali, ugotovila predznanje. Slika 3: Snovi - kviz za preverjanje znanja 575 Slika 4: Električni krog - demonstracijski poskus Slika 8: Primeri oddanih nalog o opravljenih poskusih Pri obravnavi učne enote svetloba, zvok, valovanje pri naravoslovju v 7. razredu, je k boljšemu razumevanju pojavov Sledilo je še veliko demonstracijskih poskusov, posnetih doprineslo, poleg razlage, demonstracije z laserji, svetilkami, eksperimentov za boljše razumevanje delovanja leč in prozornimi, prosojnimi, neprozornimi snovmi, zvočili, vrvmi in razlikovanja med različno ukrivljenimi lečami (Slika 9). drugim, poleg besedila in slik v učbeniku [1], predvsem v šoli posneti poskusi, ki nazorno pokažejo lom in odboj svetlobe, na podlagi česar smo lahko lažje razložili tudi izbirna znanja: vpadni in lomni kot (Slika 5) ter odbojni zakon (Slika 6). Slika 9: Lom svetlobe na različno ukrivljenih lečah Zgradbo in delovanje očesa sem razlagala ob pomoči modela. Za več spodbude pri usvajanju novih znanj in več samostojnega spoznavanja naravnih zakonitosti, sem pripravljala tudi različne Slika 5: Lom svetlobe - posnetek poskusa učne liste, ki so jih učenci direktno reševali v predpripravljen obrazec v dodeljeni nalogi (primer: Slika 10). Po analizi in utrjevanju zaključene učne enote, sem znanje preverila s kvizom (Slika 11) in rezultate zabeležila. Slika 6: Odboj svetlobe - posnetek poskusa Sledila so navodila za samostojno opravljanje poskusov, pri čemer so imeli na razpolago navodila za 6 različnih poskusov (Slika 7), dovolj je bilo, če so opravili tri, jih poslikali in poslali preko dodeljene naloge (Slika 8), kar smo skupaj pregledali na naslednji uri naravoslovja. Slika 10: Razširjannje svetlobe in zaznavanje okolice – delovni list Slika 7: Navodila za samostojno opravljanje poskusov 576 Slika 11: Svetloba, zvok, valovanje - preverjanje znanja Slika 14: Prva pomoč s TPO - praktično delo učencev Učno enoto gibala smo poleg teoretičnega dela ob uporabi modelov in utrjevanju znanja s pomočjo učnih listov (Slika 15), podkrepili tudi z mikroskopiranjem trajnih preparatov hrustančnega, kostnega tkiva, srčne mišice, skeletnih mišic in gladkih mišic z uporabo monokularnega mikroskopa s kamero, kar mi je omogočalo ob delitvi zaslona in uporabi Motic Play softwera, učencem direktno prikazovati preparate, ki smo jih tudi s posnetkom zaslona ujeli v sliko, tako so lahko kritično presojali o zgradbi posameznega tkiva v povezavi s funkcijo v telesu (Slika 16). Slika 12: razvrščanje snovi - učenje s poskusi; učni list Podoben model poučevanja sem uporabljala tudi pri biologiji. V 8. razredu izpostavljam poglavji dihala in gibala, pri katerih sem poleg uporabe modelov med razlago in navodil za poskuse in vaje, ki so jih učenci samostojno opravili doma v času tiste tedenske ure biologije, ki ni bila izvedena kot video konferenca, velik poudarek namenila varovanju zdravja ter prvi pomoči in temeljnim postopkom oživljanja. Začeli smo s teoretičnim delom (Slika 13) obogatenim s prikazi ob modelih, z ogledi poučnih filmčkov, razlago, pregledom vsebin v učbeniku [2], preverjanjem razumevanja z učnim listom in šele nato so sledila navodila za praktično delo, zajeta v izčrpni Power Point predstavitvi, ki poleg pisnih in slikovnih vsebin, zajema tudi povezave do videov, ki nazorno pokažejo pravilno izvajanje Slika 15: Gibala - obravnava učne snovi z vajami za postopkov, ki morda rešijo življenje. Učenci so se zelo izkazali utrjevanje znanja in poslali fotografije sebe – izvajalca, ki na družinskem članu vadi različne postopke prve pomoči, na primer preverjanje, če poškodovanec diha; imobilizacija poškodovanega uda in drugo (Slika 14). Slika 16: Opazovanje histoloških preparatov - kostno, hrustančno, mišično tkivo Slika 13: Dihala 577 Učenci so po navodilih opravili še en poskus, s katerim so po izkustveni poti ugotavljali, kako je kostno tkivo sestavljeno (Slika 17). Slika 17: Sestava kosti - eksperimentalno delo Pri tem poskusu je bil pogoj, da je ob izvajanju prisotna odrasla oseba. O rezultatih poskusov smo se pogovarjali na naslednji Slika 19: Dosežki učencev z oddanimi nalogami video konferenci, pri čemer so se učenci kar borili za besedo, pokazali so veliko navdušenja, predvsem pa so znali smiselno kritično analizirati opravljene poskuse. 3 REZULTATI Rezultati so pokazali, da so vsi učenci usvojili temeljna znanja naravoslovja oziroma biologije, da jih je opazovanje modelov, ogled videov, opravljanje eksperimentov ali druge vrste Slika 20: Preverjanje znanja – Kahoot praktičnega dela bolj motiviralo za šolsko delo kot učenje iz učbenika ali prepisovanje učne snovi iz Power Point drsnic, kar so na začetku vsake ure, po predhodnem praktičnem delu, brez 4 ZAKLJUČEK da bi jih o tem sploh uspela povprašati, izrazili sami. Vse dosežke – sprotno odgovarjanje na vprašanja med video uro, uspešnost Z dejavnostmi, ki sem jih uporabljala pri poučevanju v času oddanih nalog, dosežene točke pri kvizih (Google obrazci (Slika pouka na daljavo, sem skušala ustvariti čim boljše pogoje, da 2), Microsoft Forms (Slika 18), Kahoot (Slika 20)), učnih listih, lahko učenci sami doživljajo in odkrivajo znanja ter aktivno sem za vsakega učenca sproti beležila v tabele (Slika 19), kar je sodelujejo v učnem procesu. Zato sem posredovanje pokazalo, da so bili učenci pri vsebinah, pri katerih je bilo več naravoslovnih vsebin največkrat zasnovala na izkustvenem praktičnega dela – izkustvenega učenja in manj faktografije, učenju, saj ugotovim, da če učence na osnovnošolski stopnji uspešnejši in so pri ocenjevanju znanja v večini primerov izobraževanja navadimo na lastno odkrivanje znanj po izkustveni uspešno odgovarjali na vprašanja višjih taksonomskih ravni. poti, smo jih dobro pripravili in morda tudi navdušili za nadaljnje poglobljeno spoznavanje naravoslovnih vsebin. ZAHVALA Zahvaljujem se članicam naravoslovnega aktiva za uspešno sodelovanje in kvalitetno delo na področju poučevanja naravoslovnih vsebin na naši šoli. Računalnikarju Alešu Drinovcu gre posebna zahvala za sprotno izobraževanje s področja IKT in dela v okolju Microsoft Teams. LITERATURA IN VIRI [1] Andrej Šorgo, Boris Čeh, Mitja Slavinec. 2013. Aktivno v naravoslovje 2. Učbenik za naravoslovje v 7. razredu osnovne šole. DZS, Ljubljana. [2] Urška Lunder. 2012. Dotik življenja 8: učbenik za biologijo v 8. razredu osnovne šole. Rokus Klett, Ljubljana. [3] Opis Motic Microscope. Dostopno na naslovu https://www.optics- pro.com/digital-microscopes/motic-microscope-dm-52-mono-digital- 40x-400x/p,45019 (12. 8. 2021) Slika 18: Dihala in gibala - preverjanje znanja [4] Interaktivni učni načrt. Dostopno na naslovu https://dun.zrss.augmentech.si/#/ (13. 8. 2021) [5] Andrej Šorgo. 2012. Aktivno v naravoslovje 1. Učbenik za naravoslovje v 6. razredu osnovne šole. DZS, Ljubljana. [6] Petra Lebar Kac. 2016. Eksperimentalno delo kot osrednja metoda poučevanja pri predmetu naravoslovje in tehnika. Magistrsko delo. Dostopno na naslovu https://dk.um.si/Dokument.php?id=99470 (13. 8. 2021) [7] Tanja Rupnik Vec, Branko Slivar, Renata Zupanc Grom et. al. 2020. Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji. Dostopno na naslovu https://www.dlib.si/stream/URN:NBN:SI:DOC-X3BSQ9IN/d1f7defb- e0fa-4ad5-a9c5-975068de1020/PDF (13. 8. 2021) 578 Zaznavanje stresa pri srednješolcih v prvem valu epidemije COVID-19 Stress perception in high school students in the first wave of the COVID-19 epidemic Tjaša Stepišnik Perdih Mirna Macur Fakulteta za uporabne družbene študije Fakulteta za zdravstvo Angele Boškin Nova Gorica, Slovenija Jesenice, Slovenija tjasa.stepisnik.perdih@fuds.si mmacur@fzab.si POVZETEK of students experienced it significantly more than before the epidemic. The research also showed that the level of perceived Prvi val epidemije COVID-19 je prinesel veliko negotovosti, saj stress is significantly related to gender, school program, smo se s tako strogimi ukrepi za omejevanje prenosa okužbe, kot (non)staying in the dormitory, and chronic diseases. je zaprtje šol, omejitve druženja, nezmožnost opravljanja dela ipd., srečali prvič. Za marsikoga je to predstavljalo velik stres, KEYWORDS zato nas je zanimalo, kako so v prvem valu epidemije zaznavali stres slovenski srednješolci? V ta namen smo oblikovali spletno Stress perception, high school students, the first wave of the anketo in jo po metodi snežne kepe razširili po srednjih šolah in epidemic, COVID-19, coronavirus dijaških domovih. Podatki na vzorcu 1492 srednješolcev kažejo, da je večina dijaške populacije (69,9%) v prvem valu epidemije zaznavala srednje močan stres (kategorije nizek-srednji-visok), 1 UVOD dobra šestina dijakov (17,8%) pa visok stres. Več težav s Soočanje z epidemijo in strogimi ukrepi za omejevanje prenosa spanjem, razdražljivosti, več močnih in/ali neprijetnih čustev, okužbe je za marsikoga predstavljalo velik stres. Raziskave [1, 2, občutkov nemoči in pomanjkanja energije kot v času pred 3] kažejo, da so nekateri razvili celo simptome, ki so značilni za epidemijo je doživljalo 34 - 44% srednješolcev, tistih, ki so to doživljali občutno bolj kot pred epidemijo, je bilo 8-10%. posttravmatsko stresno motnjo. To so bili predvsem tisti, ki so Raziskava je tudi pokazala, da je stopnja zaznanega stresa sami trpeli za resno obliko COVID-19 in jim je grozila smrt; ki statistično pomembno povezana s spolom, programom šolanja, so bili kot družinski člani ali kot zdravstveni delavci priča (ne)bivanjem v dijaškem domu in kroničnimi težavami oz. trpljenju in smrti drugih; ki so izvedeli za smrt ali tveganje smrti bolezenskimi stanji. družinskega člana ali prijatelja; in posamezniki, ki so bili zelo izpostavljeni grozljivim podrobnostim epidemije (npr. novinarji, KLJUČNE BESEDE zdravniki in bolnišnično osebje) [4]. Zaznavanje stresa, srednješolci, prvi val epidemije, COVID-19, Mladostniki spadajo v manj rizično skupino za okužbo s koronavirus COVID-19 in jih virus večinoma neposredno ne prizadene. Raziskave tako ugotavljajo, da je epidemija prizadela predvsem ABSTRACT starejše generacije, posledice ukrepov za njeno zajezitev pa The first wave of the COVID-19 epidemic brought a lot of predvsem mlajše [5]. Na Inštitutu RS za socialno varstvo [6] uncertainty, as it was the first time, we encountered such ugotavljajo, da je epidemija na otroke vplivala predvsem 1.) s stringent measures to limit the transmission of the infection, such psihološko obremenitvijo zaradi neznane situacije in strahu pred as school closures, social-distancing, inability to work, etc. and tem, da bi zboleli njihovi bližnji; 2.) povečano negotovostjo in for many, that posed great stress. The aim of this study was večjo možnostjo, da bodo njihovi bližnji izgubili zaposlitev; 3.) to investigate the perceived stress of Slovenian high school z ukrepi, ki so prekinili ustaljeni tok življenja družin in omejili students in the first wave of the epidemic. For this purpose, we conducted an online survey sent to secondary schools and student nekatere svoboščine . dormitories. Data on a sample of 1492 students show that the Prvi val je s seboj prinesel posebej veliko negotovosti, saj smo majority of the student population (69.9%) perceived moderate se s tako strogimi ukrepi za omejevanje prenosa okužbe, kot je stress (low-medium-high categories) in the first wave of the zaprtje šol, omejitve druženja, nezmožnost opravljanja dela ipd., epidemic and a good sixth of students (17.8%) high stress. 34- srečali prvič. V raziskavi kitajskih mladostnikov, ki so ostali 44% of students had more sleep problems, were more irritable, doma v karanteni v prvem mesecu izbruha COVID-19, jih je kar had stronger and/or unpleasant emotions, more feelings of 12,8% doživljalo stresne simptome, ki so dosegali raven helplessness and lack of energy than before the epidemic. 8-10% posttravmatske stresne motnje [7]. Kako so v prvem valu epidemije zaznavali stres slovenski srednješolci, pa bomo poskušali odgovoriti s pričujočo raziskavo. 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 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 579 2 METODOLOGIJA Pri tem je potrebno omeniti, da v srednjem strokovnem in splošnem programu prevladujejo ženske (Slika 1). 2.1 Vzorec V raziskavi je sodelovalo 1492 srednješolcev, od tega je bilo Tabela 2: Zaznavanje stresa po spolu in vrsti šolanja 58,1% (867) dijakinj. 0,9% srednješolcev je obiskovalo nižji poklicni program, 11.3% srednji poklicni program (triletni), STRES 53,8% srednji strokovni program (štiriletni) in 34,0% srednji SPOL nizki srednji visoki SKUPAJ splošni program (gimnazije). 24,3% (365) srednješolcev je bilo N 101 465 59 625 iz dijaških domov, 10,3% srednješolcev pa se je soočalo s moški kroničnimi težavami oz. bolezenskimi stanji. Geografska % 16,2% 74,4% 9,4% 100% zastopanost je predstavljena v tabeli 1. N 83 578 206 867 Tabela 1: Razporeditev dijakov po pokrajinah ženski % 9,6% 66,7% 23,8% 100% Pokrajina Frekvenca Procent VRSTA ŠOLANJA Gorenjska 151 10,0 nižji N 0 12 1 13 Osrednjeslovenska 187 12,4 poklicni Štajerska 533 35,4 program % 0,0% 92,3% 7,7% 100% Prekmurje 28 1,9 srednji N 22 139 8 169 poklicni Koroška 28 1,9 program % 13,0% 82,2% 4,7% 100% Notranjska 50 3,3 (triletni) Dolenjska 330 21,9 srednji N 99 555 149 803 strokovni Primorska 197 13,1 program % 12,3% 69,1% 18,6% 100% (štiriletni) 2.2 Instrumenti in postopek srednji N 63 337 107 507 splošni Za namene raziskave smo pripravili spletni vprašalnik z orodjem program % 12,4% 66,5% 21,1% 100% 1ka. Vključeval je sociodemografska vprašanja, primerjavo (gimnazija) življenjskega sloga (preživljanje časa na socialnih omrežjih, N 184 1043 265 1492 prehranjevanje, spanje/nespečnost ipd.) s stanjem pred epidemijo SKUPAJ in Lestvico zaznanega stresa (The Perceived Stress Scale – % 12,3% 69,9% 17,8% 100% Cohen, Kamarck in Mermelstein, 1983), ki meri, kako pogosto anketiranci zaznavajo svoje življenje kot stresno, nepredvidljivo, preobremenjujoče in nenadzorljivo. Rezultat PSS-ja se razvrsti v 100.0% eno od treh kategorij, in sicer nizko, srednje in visoko zaznani 90.0% 21.4% 19.9% stres. Z višjim rezultatom se povečuje verjetnost, da stres v 80.0% posameznikovem življenju presega njegove sposobnosti 53.0% 70.0% soočanja z njim. 60.0% 79.1% Zbiranje podatkov je trajalo od 20.-26.4.2020 preko socialnih 50.0% mrež svetovalnih delavcev v srednjih šolah in vzgojiteljev 40.0% dijaških domov (t.i. metoda snežne kepe). Analiza podatkov je 78.6% 80.1% bila narejena s programom SPSS, uporabili smo deskriptivno 30.0% 47.0% statistiko ter hi-kvadrat test in Pearsonov korelacijski koeficient. 20.0% 10.0% 20.9% 0.0% 3 REZULTATI nižji poklicni srednji srednji srednji program poklicni strokovni splošni Kot prikazuje Tabela 2 je velika večina srednješolcev (69,9%) v program program program prvem valu epidemije zaznavala srednje močan stres. Visok stres je zaznavalo 23,8% vseh dijakinj in 9,4% dijakov. Dijaki in M Ž dijakinje se statistično pomembno razlikujejo v stopnji zaznavanja stresa (χ2(2)=57.816, p<0.01). Slika 1: Zastopanost spola po vrsti šolanja Statistično pomembna razlika pri zaznavanju stresa se kaže tudi glede na program šolanja (χ2(6)=27.582, p<0.01). Če Statistično pomembna razlika v zaznavanju stresa obstaja tudi izvzamemo nižje poklicno izobraževanje, kjer je bil numerus glede na to, ali se srednješolci soočajo s kroničnimi težavami oz. izrazito majhen (0,9% vseh srednješolcev), je delež bolezenskimi stanji (χ2(2)=41.877, p<0.01), pri čemer večina le- srednješolcev, ki zaznavajo nizek stres približno enak, in sicer teh zaznava srednje močan stres (55,6%). 12,3-13%. Procent visoko zaznanega stresa narašča po Stopnja stresa je odvisna tudi od tega, ali srednješolci živijo v zahtevnosti programa (z izjemo nižjega poklicnega programa). dijaškem domu ali ne (χ2(2)=12.772, p<0.01). Najvišja razlika se 580 kaže pri visoko zaznanem stresu, ki ga zaznava 23,1% Vidimo, da se štirje vidiki odzivanja med epidemijo 1.) srednješolcev iz dijaških domov in 16,1% tistih, ki ne živijo v nemoč, pomanjkanje energije, brezvoljnost, 2.) težave s dijaškem domu. spominom in/ali koncentracijo, 3.) stiskanje v prsih, razbijanje Slika 2 prikazuje procent srednješolcev, ki naštete vidike srca, tesnoba in 4.) doživljanje močnih in/ali neprijetnih čustev izkuša oz. opravlja “več” in “občutno več” kot pred epidemijo. Svetleješi stolpci prikazujejo pozitivno spremembo, in sicer več pomembno zmerno povezujejo med seboj. kreativnega udejstvovanja (ustvarjanje, risanje ipd.), Prav tako se medsebojno zmerno povezujejo razdražljivost oz. neformalnega izobraževanja, več časa zase oz. več umirjenosti napetost, stiskanje v prsih, razbijanje srca, tesnoba ter težave s ter več telesne aktivnosti kot pred epidemijo. spanjem (srednješolci težko zaspijo, se zbujajo ponoči in/ali težko vstanejo). delo za šolo 58.7% prehranjevanje 37.6% 4 RAZPRAVA močna/neprijetna čustva 35.3% Raziskava med 1492 srednješolci v času prvega vala epidemije v tesnoba, stiskanje v prsih 22.2% Sloveniji kaže, da je večina srednješolcev zaznavala srednje težave s koncentracijo 29.9% intenziven stres. Pri tem želimo opozoriti na dobro šestino kreativno udejstvovanje 38.1% srednješolcev, ki je zaznavala visok stres, v 78% so bile to socialna omrežja, TV 61.5% sanjarjenje 41.6% ženske. Zaskrbljujoče povečanje psihične obremenjenosti med neformalno izobraževanje 25.4% dekleti ugotavlja tudi poročilo Inštituta RS za socialno varstvo več časa zase, umirjenost 48.9% [6]. brez energije, nemoč 44.0% Študije mladih iz evropskih, azijskih in ameriških držav telesna aktivnost 54.1% ugotavljajo povečanje težav z duševnim zdravjem, kot so razdražljivost, napetost 39.6% razdražljivost, tesnoba, depresivni simptomi, simptomi težave s spanjem 34.2% posttravmatske stresne motnje ipd. [5, 6, 7]. Nemška študija je na reprezentativnem vzorcu pokazala, da je dve tretjini otrok in Slika 2: Vidiki doživljanja in aktivnosti, ki jih srednješolci opravljajo oz. izkušajo več kot pred epidemijo mladostnikov zaradi pandemije COVID-19 močno obremenjena. Poročali so o bistveno nižji kakovosti življenja, povezani z Po drugi strani je najvišji delež tistih srednješolcev, ki preživljajo zdravjem (40% proti 15%), več težavah z duševnim zdravjem več časa na socialnih omrežjih, gledajo TV, serije ipd. Od tega (18% proti 10%) in višjo stopnjo tesnobe (24% proti 15%) kot jih je 20,2%, ki to počno občutno več kot pred pred pandemijo [11]. V naši raziskavi doživlja težave s spanjem, epidemijo. Preživljanje časa na socialnih omrežjih, z gledanjem močna in/ali neprijetna čustva, razdražljivost, občutke nemoči, serij oz. pred TV se pomembno šibko povezuje s sanjarjenjem brezvoljnost in pomanjkanje energije “več” in “občutno več” kot oz. zatekanjem v domišljijo (r=0.202, p<0.01). pred epidemijo med 34 in 44% srednješolcev. Tistih, ki so to 37,6% srednješolcev pojé več kot pred epidemijo. doživljali občutno bolj kot pred epidemijo in jih v tem pogledu Prehranjevanje se statistično pomembno, a neznatno pozitivno lahko štejemo kot rizične, je bilo 8-10% (že v prvem valu). Na povezuje z napetostjo (r=0.133, p<0.01), tesnobo (r=0.078, p<0.01), pomanjkanjem energije (r=0.141, p<0.01), zatekanjem porast duševnih stisk med otroki in mladimi v času prvega vala v domišljijo (r=0.074, p<0.01), gledanjem serij, TVja, epidemije kažejo tudi podatki TOM telefona. Čeprav je bilo v preživljanjem časa na socialnih omrežjih (r=0.154, p<0.01), letu 2020 skupno število klicev manjše kot v preteklih letih, pa težavami s koncentracijo (r=0.111, p<0.01) in doživljanjem je bilo klicev, ki so poročali o psihičnih težavah, 33% več kot v močnih in/ali neprijetnih čustev (r=0.126, p<0.01), negativno pa povprečju zadnjih petih let [12]. s telesno aktivnostjo (r=0.072, p<0.01). Naša raziskava kaže, da je 62% srednješolcev preživljalo čas V nadaljevanju izpostavljamo tiste vidike, kjer obstaja na socialnih omrežjih, z gledanjem videev, serij ipd. “več” in pomembna zmerna povezanost: “občutno več” kot pred epidemijo. Čeprav je bil porast ob ukrepu - razdražljivost, napetost je pozitivno povezana s omejevanju druženja pričakovan, ne gre prezreti ugotovitve težavami s spanjem (r=0.497, p<0.01), nemočjo, pomanjkanjem Inštituta RS za socialno varstvo, da se je precej povečala energije, brezvoljnostjo (r=0.501, p<0.01), težavami s spominom ranljivost otrok na ravni aktivnosti, ki vodijo v odvisnost in in/ali koncentracijo (r=0.406, p<0.01), s stiskanjem v prsih, odtujitev, kot npr. igranje računalniških igric, gledanje razbijanjem srca, tesnobo (r=0.497, p<0.01) in doživljanjem videoposnetkov na youtube in televizije [6]. močnih in/ali neprijetnih čustev (r=0.572, p<0.01), negativno pa Izpostavili bi še en potencialen način soočanja s stresom oz. je razdražljivost povezana s časom zase in občutkom umirjenosti prilagoditveni odziv na epidemijo, in sicer v naši raziskavi je 9% (r=0.413, p<0.01); srednješolcev označilo, da se prehranjuje “občutno več” kot prej. - nemoč, pomanjkanje energije in brezvoljnost je Raziskave opozarjajo na naraščanje teže pri mladostnikih v času pozitivno povezana s težavami s spominom in/ali koncentracijo karantene [13], še posebej pri tistih, ki so se že prej soočali s (r=0.453, p<0.01), s stiskanjem v prsih, razbijanjem srca, tesnobo povišano telesno težo [11, 12, 13]. Ta pojav je dobil celo svoje (r=0.418, p<0.01) in doživljanjem močnih in/ali neprijetnih ime – ang. covibesity [17]. čustev (r = 0.488, p<0.01); V razpravi smo izpostavili predvsem tiste vidike, ki so že ob - težave s spominom in/ali koncentracijo so že poleg začetku epidemije nakazovali morebitne kasnejše težave. omenjenega pozitivno povezane s stiskanjem v prsih, Rezultate je namreč potrebno gledati retrospektivno, saj se razbijanjem srca, tesnobo (r=0.474, p<0.01) in doživljanjem nanašajo na april 2020, tj. čas prvega zapiranja šol, in jih tako močnih in/ali neprijetnih čustev (r = 0.488, p<0.01); lahko jemljemo kot prikaz, kakšen je bil prvi odziv srednješolcev na ukrepe za omejitev širjenja virusa COVID-19. 581 LITERATURA IN VIRI 19 pandemic on physical and mental health: The lived experience of adolescents with obesity and their caregivers,” Int. J. Environ. Res. Public [1] V. M. E. Bridgland et al. , “Why the COVID-19 pandemic is a traumatic Health, vol. 18, no. 6, pp. 1–20, Mar. 2021. stressor,” PLoS One, vol. 16, no. 1, p. e0240146, Jan. 2021. [11] U. Ravens-Sieberer, A. Kaman, M. Erhart, J. Devine, R. Schlack, and [2] Y. Tu et al. , “Post-traumatic stress symptoms in COVID-19 survivors: a C. Otto, “Impact of the COVID-19 pandemic on quality of life and mental self-report and brain imaging follow-up study,” Mol. Psychiatry 2021, pp. health in children and adolescents in Germany,” Eur. Child Adolesc. 1–6, Jul. 2021. Psychiatry, 2021. [3] D. Janiri et al. , “Posttraumatic Stress Disorder in Patients After Severe [12] ZPMS, “TOM telefon: VPLIV EPIDEMIJE COVID-19 NA OTROKE COVID-19 Infection,” JAMA Psychiatry, vol. 78, no. 5, pp. 567–569, May IN MLADOSTNIKE,” 2021. 2021. [13] C. A. Nogueira-de-Almeida, L. A Del Ciampo, I. S. Ferraz, I. L. R. Del [4] “Post-COVID Stress Disorder: Another Emerging Consequence of the Ciampo, A. A. Contini, and F. da V Ued, “COVID-19 and obesity in Global Pandemic.” [Online]. Available: childhood and adolescence: a clinical review,” J. Pediatr. (Rio. J). , vol. https://www.psychiatrictimes.com/view/post-covid-stress-disorder- 96, no. 5, pp. 546–558, Sep. 2020. emerging-consequence-global-pandemic. [Accessed: 04-Aug-2021]. [14] R. An, “Projecting the impact of the coronavirus disease-2019 [5] A. Grom Hočevar et al. , “Pandemija covid-19 v Sloveniji. Izsledki panelne pandemic on childhood obesity in the United States: A microsimulation spletne raziskave o vplivu pandemije na življenje (SI-PANDA), 6. val,” model,” J. Sport Heal. Sci. , vol. 9, no. 4, pp. 302–312, Jul. 2020. Ljubljana, 2021. [15] A. Pietrobelli et al. , “Effects of COVID-19 Lockdown on Lifestyle [6] U. Boljka, T. Narat, J. Rosič, M. Škafar, and M. Nagode, “Vsakdanje Behaviors in Children with Obesity Living in Verona, Italy: A življenje otrok v času epidemije covid 19,” Ljubljana, 2020. Longitudinal Study,” Obesity, vol. 28, no. 8, pp. 1382–1385, Aug. 2020. [7] L. Liang et al. , “Post-traumatic stress disorder and psychological distress [16] V. Bayram Deger, “Eating Behavior Changes of People with Obesity in Chinese youths following the COVID-19 emergency:,” J. Health During the COVID-19 Pandemic,” Diabetes. Metab. Syndr. Obes. , vol. 14, Psychol. , vol. 25, no. 9, pp. 1164–1175, Jul. 2020. pp. 1987–1997, 2021. [8] L. Ezpeleta, J. B. Navarro, N. De La Osa, E. Trepat, and E. Penelo, “Life [17] M. A. Khan and J. E. Moverley Smith, “‘Covibesity,’ a new Conditions during COVID-19 Lockdown and Mental Health in Spanish pandemic,” Obes. Med. , vol. 19, Sep. 2020. Adolescents,” Int. J. Environ. Res. Public Health, vol. 17, 2020. [9] M. Orgilés, A. Morales, E. Delvecchio, C. Mazzeschi, and J. P. Espada, “Immediate Psychological Effects of the COVID-19 Quarantine in Youth From Italy and Spain,” Front. Psychol. , vol. 11, pp. 1–10, 2020. [10] G. Pietrabissa et al. , “The impact of social isolation during the covid- 582 Uporaba spletnega socialnega omrežja Facebook pri učenju na daljavo Using the online social network Facebook in distance learning Sonja Strgar OŠ Antona Martina Slomška Vrhnika Vrhnika, Slovenija sonja.strgar@guest.arnes.si POVZETEK maintain social contact. The disadvantages are the use of colloquial language, inaccurate rules of use, the possibility of V prispevku je predstavljeno delo na daljavo v času epidemije misinformation and the implementation of cyberbullying among SARS-CoV-2, ki je potekalo preko spletnega socialnega young people. Even though the experience with the social omrežja Facebook za učno šibkejše učence devetega razreda pri network has been positive, there is still too much uncertainty matematiki. Facebook smo izbrali na željo učencev. Pri delu na with parental consent, with appropriate student privacy settings daljavo so učenci vsa navodila za delo, evalvacije, preverjanja and with data storage checks. znanja, spletne povezave, rešitve nalog, povabila na videokonference ipd. dobili znotraj zaprte skupine na KEYWORDS Facebooku. Preko dela na socialnem omrežju so spoznali Online social network Facebook, distance learning, math, ninth prednosti in slabosti Facebooka za učne namene, ki so grade predstavljeni v prispevku. Prednosti so predvsem dostopanje kjerkoli in kadarkoli s katerokoli pametno napravo, visoka aktivnost učencev, samostojno razporejanje časa in snovi, 1 UČENJE NA DALJAVO možnosti razprave in sodelovanja, močno povezana spletna skupnost, preprosto in enostavno učno okolje za uporabo, Izobraževanje na daljavo (distance education) je oblika možnost označevanja posameznikov in ohranjanje socialnega izobraževanja z dvema temeljnima značilnostma: učitelj in stika. Kot slabost bi izpostavili predvsem uporabo pogovornega učenec sta med poučevanjem prostorsko ločena, komunikacijo jezika, nenatančno določena pravila uporabe, možnost napačnih med njima in komunikacijo med učenci samimi pa omogočajo informacij ter izvajanje spletnega nasilja med mladimi. Četudi različne vrste tehnologij. Unesco [1] opredeljuje izobraževanje je bila izkušnja s socialnim omrežjem pozitivna, je še vedno na daljavo kot vzgojno-izobraževalni proces in sistem, v preveč negotovosti s soglasji staršev, z ustreznimi nastavitvami katerem pomemben delež pouka izvaja nekdo ali nekaj, ki je zasebnosti učencev in s preverjanjem shranjevanja podatkov. časovno in prostorsko odmaknjeno od učenca. 12. marca 2020 je bila v Republiki Sloveniji razglašena epidemija, virus SARS-CoV-2 je povzročil zaprtje vzgojno- KLJUČNE BESEDE izobraževalnih zavodov ter drugih ustanov. Učenje in Spletna socialna omrežja, učenje na daljavo, matematika, deveti poučevanje sta se preselila v domače okolje, učitelj in učenec razred sta postala fizično ločena, šole so na podlagi navodil in priporočil oblikovale skupne načine komunikacije, spletne ABSTRACT učilnice in protokole pri delu na daljavo. V prvem valu so bili učitelji prepuščeni predvsem sami sebi in svoji iznajdljivosti. The paper presents the distance work during the SARS-CoV-2 Kasneje, ob drugem valu, je Zavod Republike Slovenije za epidemic, which took place via the online social network šolstvo izdal Analizo izobraževanja na daljavo v času prvega Facebook for the weaker ninth-grade students in mathematics. vala epidemije covida-19 v Sloveniji [2], v kateri so podana Facebook was chosen at the request of the students. When metodična izhodišča osnovnošolskega učitelja, ko oblikuje working remotely, students have all the instructions for work, gradiva za pouk na daljavo, ki usmerjajo učitelja v premislek o evaluations, knowledge tests, web links, task solutions, tem, invitations to video conferences, etc. get inside a closed group on Facebook. Through working on the social network, we • kako skupaj z učenci ubesediti vloge in odgovornosti learned about the advantages and disadvantages of Facebook v procesu pouka; for learning purposes, which are presented in the article. The • kako v učno gradivo, ne glede na to, ali je advantages are access anywhere and anytime, with any smart uporabljeno kontaktno, torej videokonferenčno, device, high student activity, independent scheduling of time izključno prek pisnih navodil ali kombinirano, vtkati and material, opportunities for discussion and collaboration, a vse faze vzgojno-izobraževalnega procesa: highly connected online community, a learning environment o ponovitev stare snovi, that is simple and easy to use, the ability to tag individuals and 583 o osmišljanje posredovanega znanja ter učni skupini odločili zato, ker je bila motivacija za delo visoka, spodbujanje in motiviranje udeležencev, kar je omogočilo ohranjanje stika z učenci. o podajanje, razlago in pojasnjevanje nove Na začetku je bil sklenjen dogovor, kakšna pravila bodo učne snovi, veljala v Facebook skupini. Dorečen je bil bonton in način o ponavljanje in utrjevanje, delovanja. V skupini so bili le člani manjše učne skupine, o spodbujanje udeležencev, da usvojeno znanje učiteljica matematike in učiteljice dodatne strokovne pomoči. prenesejo v prakso, Predvsem pa je bilo pomembno, da se vsi uporabniki držijo o preverjanje in ocenjevanje znanja. dogovora, da, kar je objavljeno v skupini, tam tudi ostane. Vsa zgoraj našteta metodična izhodišča so učitelji po večini Nato je bila na Facebooku ustvarjena skupina Matematika 9. upoštevali že v prvem valu. r OSAMS. Skupina je bila zaprta in skrita za ostale uporabnike. Spletna socialna omrežja danes predstavljajo pomemben del Delovala je od 14. 3. 2020 do 31. 8. 2020. Nekaj profilov vsakdanjika posameznika, predvsem s komunikacijskega vidika. učencev je učiteljica zlahka našla in jih povabila v skupino. Uporaba spletnih socialnih omrežij znotraj izobraževalnega Spet drugih profilov učencev ni bilo mogoče najti, zato so jih procesa prinaša prednosti tako za učence kot tudi za učitelje. povabili v skupino preko sošolcev (slika 1). Kasneje so bile Kot ugotavlja avtor raziskave Uporaba spletnega socialnega dodane tudi učiteljice dodatne strokovne pomoči, da so lahko omrežja Facebook za izobraževalne namene v času študija [3] sledile delu in imele pregled nad delom skupine ter sodelovanju socialna omrežja lahko spodbujajo sodelovalne veščine, učencev. Po štirih dneh delovanja skupine so bili v skupini prav sodelovalno učenje, refleksivno razmišljanje, socialno vsi člani manjše učne skupine. interakcijo z vsemi udeleženimi v izobraževalnem procesu. Da bi preizkusili, kakšne so prednosti in pomanjkljivosti uporabe socialnega omrežja Facebook, smo se na Osnovni šoli Antona Martina Slomška Vrhnika odločili, da pri pouku matematike ponudimo socialno omrežje, ki ga učenci poznajo iz vsakdanjega življenja. 2 OPIS DELA IN REZULTATI Učiteljica matematike in računalništva je za svoje učence pri predmetu matematika ustvarila Arnesove spletne učilnice Moodle. V devetem razredu je bila oblikovana manjša učna skupina s trinajstimi učenci, kjer je bilo zanimanje za učenje matematike precej šibko. Spletnih učilnic učenci niso bili vajeni, zato je bil obisk na začetku zelo slab. Iskali smo načine, kako v devetem razredu pri matematiki motivirati učence, da bodo sledili navodilom pri delu na daljavo. Poizvedovali smo, kaj bi bilo učencem najbližje. Prva izbira je bila Viber, kar se učiteljici ni zdelo ustrezno, ker posega v osebne podatke, saj uporabnik kot svojo identiteto uporablja telefonsko številko. Nato so učenci predlagali spletno socialno omrežje Facebook. Ideja se ni zdela slaba, ker ga učitelji na šoli tudi vsakodnevno uporabljajo. Najprej so v manjši učni skupini preverili, če imajo vsi učenci že izdelan Facebook profil. Ker je bilo ugotovljeno, da prav vsi učenci v manjši učni skupini Facebook uporabljajo, so se odločili, da bo to učno okolje, v katerem se bodo izvajale dejavnosti na daljavo. Vsi učenci so bili starejši od 13 let, kar je določena minimalna starost za uporabo družabnega omrežja. V primeru, da uporabnik nima šestnajst let, mora imeti šola za uporabo Facebook-a soglasje staršev. V manjši učni skupini so preverili, ali so učenci seznanjeni z delovanjem aplikacije do te mere, ki jo potrebujejo za nemoteno uporabo. Izkazalo se je, da učenci obvladajo spletno aplikacijo Facebook. Pred samim Slika 1. Pomoč pri iskanju vseh učencev. začetkom dela s Facebookom so učenci spoznali ustrezne nastavitve zasebnosti (skupina ni bila javno dostopna). Učitelji Pri delu na daljavo je pomembno, da se ohranja stik z učenci. se zavedajo, da uporaba družabnih omrežij za šolske namene ni Zato je bilo dobro, da so učenci spremljali objave, ki niso bile priporočljiva, predvsem z vidika zasebnosti, omejitve starosti, povezane s samo učno snovjo (slika 2). Pri motiviranju učencev vpliva preveč motečih dejavnikov in možnih oblik spletnega je ključen osebni stik. V razredu po navadi učitelju zelo hitro nasilja. Kljub temu so se za Facebook pri matematiki v manjši uspe vzpostaviti osebni stik, pri učenju na daljavo je bilo to 584 bistveno težje, vendar pa še toliko bolj potrebno. Stik so gradile šolskega tedenskega dela, narejene predvsem v Googlovih objave o sprehodih učiteljice, spodbudne misli, povezave do Dokumentih. V skupini so bile deljene povezave do kvizov z nematematično vsebino (ki jih je rešila tudi učiteljica videokonferenc, ki so potekale v spletnem okolju Zoom. sama in z ostalimi uporabniki delila zbrano število točk ali Objavljene so bile tudi povezave do preverjanj znanj, ki so jih druge rezultate), objave o šoli, anonimna anketa z naslovom učenci reševali. Preverjanja znanja so bila večinoma preko Učiteljici bi sporočil še …, lepe želje za počitnice in vikende, spleta, največkrat narejena v Kahoot kvizih ali Google Drive. V fotografije prazne učilnice (ki pogreša svoje učence), hecne skupini pa so na zidu bile dostopne tudi povezave do uporabnih objave, osebni nagovori učiteljice ipd. strani, ki so učencem pomagale pri razumevanju snovi. Slika 3. Primer oddanih zapiskov in nalog. Pri delu na daljavo so pri matematiki učenke v povprečju bolj pogosto uporabljale spletno socialno omrežje Facebook v izobraževalne namene kot učenci. Učenke so bile tudi natančne v oddajanju nalog in redno zastavljale vprašanja za naloge, ki so delale težave. Do enake ugotovitve je prišla tudi avtorica [3] v svoji raziskavi. Učiteljici je uspelo ohraniti stike z učenci tudi po zaključku Slika 2. Objave za motivacijo. poučevanja na daljavo. Zadnje besedilo je bilo namreč objavljeno 31. 8. 2020, večer preden so bivši učenci vstopili v V skupini so bila navodila za delo na daljavo za posamemezno novo srednjo šolo. Skoraj vsi učenci so odgovorili na to objavo, učno uro. Vsaka učna ura je imela svojo objavo. Prav vse kar pomeni, da smo spletno socialno omrežje dobro izkoristili, objave so učenci lahko komentirali, kar jih je spodbudilo k ne samo za učenje, ampak tudi za ohranjanje stikov (slika 4). skupnemu oblikovanju spletnega okolja. Učenci so morali v Med uporabo spletnega socialnega omrežja Facebook so novo objavo oddati zapiske in naloge, ki so jih reševali doma. V uporabniki zaprte skupine Matematika 9. r OSAMS prišli do kolikor česa niso oddali, so bili označeni in ponovno ugotovitev, da so prednosti uporabe takšnih skupin naslednje: povabljeni, da naloge oddajo (slika 3). • dostopanje kjerkoli in kadarkoli (predvsem s Učenci so lahko odprli novo objavo, kamor so postavili pametnim telefonom); vprašanje za naloge, ki so jim delale težave ali pa jih niso znali • učenci so morali biti aktivni, sicer so bili takoj rešiti. Na zastavljena vprašanja so odgovarjali tako sošolci kot označeni, da nečesa še niso naredili; učiteljica matematike. Dogovor med člani skupine je bil, da • znotraj skupine so bile omogočene prilagoditve za učiteljica preveri odgovore učencev in jih komentira. Prav tako samostojno učenje (lahko so si razporejali čas in so občasno delili kakšnen dogodek, ki ni bil povezan z snov); matematiko. Na takšen način se je ohranjal stik med udeleženci • učenci so imeli možnost razprave in sodelovanja; skupine. Objavljene so bile tudi povezave do evalvacij 585 • člani skupine so bili v močno povezani spletni 3 ZAKLJUČEK skupnosti; 22. maja 2020 se je učenje na daljavo za devetošolce zaključilo. • na enem mestu so bile zbrane vse informacije (objave S 25. majem 2020 so se vrnili v šolske klopi. z navodili, povezavami, videoposnetki, fotografijami Na podlagi opravljene ustne analize dela na daljavo z …); devetošolci lahko sklepamo, da se je Facebook skupina • spletno okolje je bilo preprosto in enostavno za uporabljala le pri matematiki. Tak način dela je bil učencem uporabo; zelo všeč, ker je bilo podajanje informacij v socialnem omrežju • v skupini si lahko označil posameznika (to je bilo zanje enostavno in preprosto. Delali so v spletnem okolju, ki učencem zelo všeč); zanje ni bilo novo in v katerem so se počutili dobro. Najprej je • imeli so možnost komunikacije z drugimi (delitev učence sicer skrbelo, da bo učiteljica videla njihove profile, a so izkušenj); kmalu ugotovili, da se zasebnih profilov ne vidi, če so • znotraj skupine so člani vzdrževali in ohranjali nastavitve zasebnosti pravilno nastavljene. Učenci so pohvalili socialni stik. vzpostavljanje in ohranjanje socialnih stikov manjše učne skupine. Med seboj in z učiteljicami so se učenci počutili povezani tudi pri delu na daljavo. Posebej so pohvalili možnost sodelovanja pri nalogah, ki so jim delale težave, predvsem hiter odziv sošolcev in učiteljice. Povedali so, da je večina učencev do Facebook skupine dostopala preko pametnega telefona, ker je bilo to najhitreje in ker ga imajo vsi. Prav tako so vse naloge za oddajo slikali in naložili v skupino s pametnim telefonom. Tako je bilo delo najhitreje opravljeno. Facebook skupine se kasneje pri delu na daljavo ni več uporabljalo. Četudi je bila izkušnja s socialnim omrežjem pozitivna, je še vedno preveč negotovosti s soglasji staršev, z ustreznimi nastavitvami zasebnosti učencev, s preverjanjem shranjevanja podatkov. Zato za delo na daljavo priporočamo uporabo Arnesovih spletnih učilnic, ki so mnogo bolj varne tako za učence kot za učitelje. LITERATURA IN VIRI [1] Burns, M. 2011. Distance Education for Teacher Training: Modes, Models, and Methods. Washington, DC: Education Development Center, Inc. [2] Analiza izobraževanja na daljavo v času prvega vala epidemije covida-19 v Sloveniji. Ljubljana: Zavod Republike Slovenije za šolstvo. DOI= https://www.zrss.si/pdf/izobrazevanje_na_daljavo_covid19.pdf [3] Kašnik, V. (2018). Uporaba spletnega socialnega omrežja Facebook za izobraževalne namene v času študija. DOI= https://dk.um.si/Dokument.php?id=125479 Slika 4. Zadnja objava v skupini. Kot pomanjkljivosti uporabe spletnega socialnega omrežja Facebook za učenje na daljavo so člani skupine navedli: • pred uporabo je potrebno doreči pravila uporabe spletnega socialnega omrežja; • učenci velikokrat uporabljajo pogovorni jezik in okrajšave, kar je bilo potrebno postopoma odpravljati; • učitelj mora imeti nadzor nad objavami, da ne prihaja do širjenja napačnih informacij; • potrebno je paziti, da se ne izvaja kakršnakoli oblika spletnega nasilja, zato mora skrbnik skupine vedno preverjati objave. 586 Discord kot platforma za izvedbo pouka na daljavo Discord as a distance learning platform Gašper Strniša Šolski center Kranj / Strokovna gimnazija Kranj, Slovenija gasper.strnisa@sckr.si POVZETEK izvedbe pouka na daljavo (predvsem s strani učiteljev) praktično ni bilo. Na odpoved pouka, ki se je v preteklem letu zgodil zaradi Pri pouku na daljavo je z razvojem računalniške tehnologije, pandemije koronavirusa, marsikdo ni bil pripravljen. Tukaj računalniške pismenosti in interneta prišlo do revolucionarnih govorimo tako o krovnih šolskih organizacijah, kot tudi šolah sprememb. Izobraževalni proces se seli tudi izven učilnic v samih, učiteljih, učencih, starših in institucijah, ki s šolami virtualni računalniški prostor [3]. Pri tem procesu ne gre za neposredno sodelujejo. Prispevek opisuje primer dobre prakse transformacijo ali za popolno nadomestitev tradicionalnega izvedbe pouka na daljavo z uporabo okolja Discord, ki so ga načina učenja, gre za njegovo razširitev in posodobitev [4]. dijaki poznali in uporabljali v namene ne povezane s šolstvom. Srednješolsko izobraževanje je ena ključnih faz za razvoj Prispevek prikazuje tudi rezultate anket, ki ju je kmalu po posameznika tako v privatnem kot tudi v njegovem poklicnem začetku pouka na daljavo in ob njegovem koncu izvedla komisija življenju. Dijakom je v tem času potrebno zagotoviti kakovostne za kakovost. učne vsebine za smeri izobraževanja, ki jih obiskujejo. Poleg KLJUČNE BESEDE učnih pripomočkov kot so e-gradiva, učbeniki, zapiski, ipd., pa morajo dijaki prejeti tudi ustrezno razlago obravnavanih vsebin, Discord, pouk na daljavo, video konferenca, kovid, tehnologija saj v nasprotnem primeru šola zares ne bi bila potrebna. Velika ABSTRACT večina zaposlenih v šolstvu, pa tudi širše, je verjetno že slišala rek, da je uspešen proces izobraževanja odvisen predvsem od o one could be prepared for the cancellation of classes, which učiteljev, ki svoja znanja prenašajo na učence. happened last year due to the coronavirus pandemic. Not even head school organizations let alone schools themselves, teachers, students, parents and institutions that work directly with schools. 2 PREDSTAVITEV PROBLEMA The paper describes an example of good practice in conducting Večina učiteljev ni imela pripravljenih scenarijev izvedbe pouka distance learning using the Discord environment, which students na daljavo ob nastalih kriznih situacijah. Slovar slovenskega knew and used for non-educational purposes. The paper also knjižnega jezika [1] krizo definira kot stanje v gospodarstvu, ko shows the results of surveys conducted by the Quality se ugodne razmere za razvoj začnejo hitro slabšati. Novak [2] Commission shortly after the start of distance learning and at the krizo dodatno opredeli kot okoliščino, v kateri organizacija ne end of it. more več normalno delovati in ne more več dosegati svojih ciljev. Glavne značilnosti kriz so nenadnost, negotovost in časovni KEYWORDS pritisk. Zgodijo se običajno nepričakovano in zahtevajo hiter Discord, distance learning, video conference, Covid, technology odziv, ter povzročajo stres [2]. V kolikor pa so učitelji imeli predvidene rešitve za pouk na daljavo, pa ni nujno, da so ga v času zaprtja šol tudi dejansko lahko izvajali zaradi tehničnih 1 UVOD težav na strani ponudnikov za zagotavljanje takšnih rešitev. Na odpoved pouka, ki se je v preteklem letu zgodil zaradi Klasičen primer prej navedenega problema je občutilo pandemije korona virusa, marsikdo ni bil pripravljen. Tukaj mnogo slovenskih učiteljev, ki so upali na izvedbo oddaljenega govorimo tako o krovnih šolskih organizacijah, kot tudi šolah pouka preko spletnih konferenc Vox, ki jih preko spletne samih, učiteljih, učencih, starših in institucijah, ki s šolami programske opreme Adobe Connect ponuja Arnes - javni zavod, neposredno sodelujejo. Začetna zmeda je bila zaradi precej ki zagotavlja omrežne storitve organizacijam s področja hitrega zaprtja šol precej velika, saj časa za iskanje načina raziskovanja, izobraževanja in kulture ter omogoča njihovo povezovanje in medsebojno sodelovanje ter sodelovanje s sorodnimi organizacijami v tujini. Njihovi strežniki namreč niso Permission to make digital or hard copies of part or all of this work for personal or prenesli izjemno povečanega omrežnega prometa, ki ga je classroom use is granted without fee provided that copies are not made or distributed izvajala velika množica slovenskih učiteljev (kot izvajalcev) 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 dijakov (kot udeležencev) ob enakem času. Precej učiteljev je be honored. For all other uses, contact the owner/author(s). tako obupalo nad izvedbo pouka na daljavo ali pa so se začeli Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). posluževati načinov brez razlag, spet drugi pa so začeli iskati druge rešitve. 587 Na Strokovni gimnaziji (v nadaljevanju SG) in Srednji preprostosti in intuitivnega grafičnega vmesnika, pa je postala tehniški šoli (v nadaljevanju STŠ) Šolskega centra Kranj, ter na ena izmed najbolj popularnih aplikacij za komunikacijo na svetu. Gimnaziji Franceta Prešerna (v nadaljevanju GFP) smo v dneh Aplikacija poleg klepeta po mikrofonu in tipkanja tekstovnih pred zaprtjem šol že predvideli takšen scenarij. Ravnatelj STŠ je sporočil omogoča še vrsto drugih lastnosti, ki se lahko aplicirajo učitelje računalništva prosil, če pripravijo predlog za izvedbo za izvedbo pouka na daljavo. Zlahka ja namreč deliti slike, pouka na daljavo in posnamejo video vodič za sodelavce in videoposnetke in izvajati video konference v realnem času. dijake, ki teh tehnologij še ne poznajo. V sodelovanju z GFP smo Omogoča tako prijavo kot tudi začasno registracijo za tiste, ki bi pripravili dva različna predloga (Vox in Teams), ki sta v dneh ko želeli prisostvovati pouku v omejenem obsegu. še ni bilo pretiranega prometa na strežnikih, odlično delovala.. 3 PREDLAGANA REŠITEV Vox konference so kljub zastareli tehnologiji (zaradi potrebne uporabe Flasha) mnogim zdele najbolj logična rešitev. Marsikdo od učiteljev je ta način dela že poznal vsaj kot uporabnik, zato nadgradnja v gostitelja ni predstavljala prevelikega strahu. Vox je poleg delno poznanega okolja predstavljal tudi določene lastnosti, ki bi lahko zelo pozitivno vplivale na izvedbo pouka: • za vsak razred in predmet se lahko izdela svoja konferenca, • predstavlja možnost uporabe različnih načinov Slika 1: Okolje Discord komuniciranja (zvokovno - preko mikrofona, vizualno - preko kamere, tekstovno – preko klepetslikalnice, grafično – preko table), 5 PREDSTAVITEV REZULTATOV • omogoča deljenje datotek povezanih s snovjo v Po zaključenem prvem tednu pouka na daljavo, smo iz realnem času in kot možnost shranjevanja datotek na lastne svetovalne službe dobili podatek, da se določeni dijaki še vedno naprave, niso vpisali v okolje MS Teams, ki ga je uporabljala večina • prijava z osebnimi AAI računi, s čimer bi bila profesorjev. To pomeni, da cel teden niso bili prisotni pri pouku. zagotovljena istovetnost prisotnih, Pri urah predmetov računalništva, kjer se je za izvedbo pouka na • zaščita vstopa v konference z gesli, kar bi preprečilo daljavo uporabljal Discord, pa je bila udeležba 100% že od vstop tretjim osebam, prvega dne. Zanimiv je tudi podatek, da so prav vsi dijaki že • možnost dostopa do konference kot gost (zgolj v imeli ustvarjene račune v Discordu, preden smo ga začeli začetnih fazah izvajanja, ko bi dijaki lahko imeli težave z uporabljati v šolske namene. pozabljenimi gesli, ipd.), Komisija za kakovost je tako kmalu po začetku, nato pa še • možnost snemanja konferenc za dijake, ki se pouka ob koncu pouka na daljavo izvedla svoji anketi. niso mogli udeležiti, Anketo je izpolnilo 69 učiteljev. Zajemala je različna • možnost izvajanja določenih akcij nad uporabniki področja poučevanja na daljavo. Za naše ugotovitve pa so ključni (dodajanje in odvzemanje pravic komunikacije, izključitev iz rezultati, ki se nanašajo na komunikacijo z dijaki. konference, ipd.) Po prvi anketi so bile ugotovljene naslednje ugotovitve: 94% učiteljev ja za komunikacijo z dijaki uporabljalo e-pošto in Za delo smo izobrazili tudi dijake, da bi v primeru zaprtja šola aplikacijo eAsistent. 76% jih je za pouk uporabljalo spletno lahko z delom začeli takoj. Kot smo zapisali v prejšnjem učilnico, 29% pa je izvajalo pouk preko različnih video poglavju, pa so se stvari spremenile v nedelujoče ob množični konferenc (Vox, MS Teams, Discord, Zoom). Zanimiva je bila povezavi na strežnike teh storitev. tudi ugotovitev, da so v prvi anketi dijaki izrazili nezadovoljstvo s tem, da so različni učitelji za pouk uporabljali različne aplikacije. 4 UPORABLJENA REŠITEV V drugi anketi so zanimive tudi naslednje ugotovitve: Hitra prilagoditev situaciji je bila neizbežna, saj bi v primeru • tako dijaki kot tudi učitelji smo se naučili veliko lastnega iskanja nove rešitve lahko porabili ogromno časa, s tem novega v povezavi z uporabo sodobnih IKT tehnologij, pa bi dijake prikrajšali za izvedbo pouka. Najbolj logična poteza • priporočljiva je uporaba skupne platforme za izvedbo se je kazala v ideji, da se tokrat učitelji posvetujemo z dijaki in video konferenc, se prilagodimo tehnologijam, ki jih oni najbolje poznajo in jih • učitelji so si želeli tehnično pomoč za izvedbo video dnevno uporabljajo. konferenc. Discord je brezplačna aplikacija, ki je v prvi vrsti namenjena igralcem spletnih iger, pri katerih udeleženci potrebujejo tako glasovno komunikacijo kot tudi komunikacijo preko sporočil 6 ZAKLJUČEK (slika 1). Uporabna je na računalnikih in pametnih napravah, saj Glede na dobljene rezultate opravljenih anket, so bili zapisani je na voljo za operacijske sisteme MacOs, Windows, Linux, iOS tudi določeni predlogi: določiti je potrebno pravila obnašanja na in Android. Na voljo je tudi spletna različica, do katere je mogoče video konferencah; sprejeti je potrebno dogovor o organizaciji dostopati preko brskalnikov Firefox in Crome. Zaradi svoje dela (delo po ustaljenem urniku ali izdelava novega urnika, ki bo 588 prilagojen delu na daljavo); sprejeti je potrebno dogovor o LITERATURA IN VIRI beleženju prisotnosti oz. odsotnosti na video konferencah; [1] Bajec Anton in drugi, 1994. Slovar slovenskega knjižnega jezika. DZS, priporočljiva je uporaba enotne platforme za izvedbo video Ljubljana konferenc. [2] Novak Božidar in drugi, 2000. Krizno komuniciranje in upravljanje nevarnosti. Priročnik za krizne odnose z javnostmi v praksi. Gospodarski Predlog, da šola določi uporabo enotne platforme za izvedbo vesnik, Ljubljana video konferenc, je seveda zelo smiseln, saj na ta način pride do [3] Močnik Bojan in Rugelj Jože, 1999. Virtualna učilnica za izobraževanje na delovnem mestu. ERK, Portorož centralizacije znanj in izkušenj tako med učitelji kot tudi med [4] Močnik Bojan, Urbančič Tanja in Rugelj Jože, 2001. Pregled orodij za dijaki. V primeru dobre prakse sodelovanja med učiteljem in računalniško podporo učenju na daljavo. Organizacija 34, 8, 508-512 dijaki preko ustaljene platforme pa je zadevo bolje pustiti kot je in na ta način pouk pripeljati do konca. 589 Obogatitev predopismenjevanja v predšolskem obdobju Enrichment of pre-literacy in the preschool period Tina Šebenik Župnijski vrtec Vrhnika Vrhnika, Slovenija malatiny@gmail.com POVZETEK ABSTRACT V prispevku je predstavljeno, kako smo v skupini predšolskih The article presents how in the group of preschool children, the otrok, zadnje leto pred vstopom v šolo, nadgradili ustaljene last year before entering school, we upgraded the established metode in aktivnosti za razvijanje predopismenjevalnih methods and activities for developing preliteracy skills using the sposobnosti z uporabo spletnega orodja ABC PreSchool Kids online tool ABC Preschool Kids Tracing & Phonics Learning Tracing & Phonics Learning Game (ABC predšolski otroci – Game (ABC preschool children – learning game). In recent years, učna igra). children have shown great interest in participating in activities Otroci so že v preteklih letih izkazali veliko zanimanja za and didactic games that encouraged preliteracy skills both in sodelovanje v aktivnostih in didaktičnih igrah, ki so spodbujale nature and in the playroom. None of the children had problems predopismenjevalne veščine tako v naravi kot v igralnici. Nihče with tweezers grip developed by tearing paper, dressing and od otrok ni imel težav s t. i. pincetnim prijemom, ki so ga razvijali undressing, kneading dough, stringing beads, and the like. Many s trganjem papirja, z oblačenjem in slačenjem, gnetenjem testa, of them quickly showed their interest in the appearance of some nizanjem perlic ipd. Marsikdo izmed njih je strokovnima of the letters. As a result, the educator planned a series of delavkama kaj hitro pokazal zanimanje za izgled nekaterih črk. activities that would upgrade the already carried out basic Posledično je vzgojiteljica načrtovala vrsto dejavnosti, ki bi activities carried out in recent years. We were aware that ICT is nadgradile že izpeljane temeljne aktivnosti, izpeljane v zadnjih part of the everyday environment of preschool children, which letih. Zavedali smo se, da je IKT del vsakdanjega okolja tudi would make sense to use in the learning process and teach them predšolskih otrok, ki bi ga bilo smiselno uporabiti pri učno- about its didactic value and, on the other hand, take advantage of vzgojnem procesu in jih podučiti o njeni didaktični vrednosti in the attractiveness and popularity of electronic devices. She chose po drugi strani izkoristiti atraktivnost in priljubljenost the ABC Preschool Kids Tracing & Phonics Learning game web elektronskih naprav. Izbrala je spletno aplikacijo ABC PreSchool application, which offers a number of didactic games (e.g. Kids Tracing & Phonics Learning Game, ki ponuja številne connecting points, drawing horizontal and vertical lines, curves didaktične igre (npr. povezovanje točk, risanje vodoravnih in indicating appropriate line connections when writing capital navpičnih črt, krivulj nakazuje ustrezno povezovanje črt pri letters, etc.). Due to limitations with technical equipment (one zapisu velikih tiskanih črk itd.). Zaradi omejenosti s tehnično tablet), we chose the forms of work in which all children in the opremo (en tablični računalnik) smo izbirali oblike dela, pri group were involved and active. The children were happy to kateri so bili vključeni in dejavni vsi otroci v skupini. Otroci so participate in using the app, patiently waiting for their turn, and z veseljem sodelovali pri uporabi aplikacije, potrpežljivo so what quickly they wrote the simplest letters correctly and počakali, da so na vrsti, in kaj hitro so pravilno zapisali connected the grapheme with the appropriate phoneme. The use najenostavnejše črke in povezali grafem z ustreznim fonemom. of the mentioned online tool has undoubtedly contributed to a Uporaba omenjenega spletnega orodja je nedvomno prispevala k more effective achievement of the set learning goal – the učinkovitejšemu doseganju zastavljenega učnega cilja – development of pre- literacy skills and even progress towards razvijanju predopismenjevalne zmožnosti in celo napredka k early literacy. zgodnjemu opismenjevanju. KEYWORDS KLJUČNE BESEDE Pre-literacy, online tool ABC PreSchool Kids Tracing & Predopismenjevanje, spletno orodje ABC PreSchool Kids Phonics Learning Game, pre – school period, critical use of ICT, Tracing & Phonics Learning Game, predšolsko obdobje, kritična learning through play uporaba IKT, učenje skozi igro 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 Vzgojitelji se zavedamo, da se razvoj pismenosti začne že pred 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 formalnim šolanjem otroka, zato lahko k izboljšavi t. i. be honored. For all other uses, contact the owner/author(s). porajajoče se pismenosti pomembno vplivamo tudi s Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). premišljenim načrtovanjem dejavnosti v vrtcu. Tudi L. Marjanovič Umek opozarja, da si večina ljudi napačno razlaga, 590 da se opismenjevanje otrok začne šele z vstopom v šolo. Opismenjevanje je proces, ki se ne začne šele pri šestem ali sedmem letu, temveč traja tako rekoč od rojstva. Šest ali sedem let je umetna meja, ki smo jo postavili sami – takrat se je večina otrok sposobnih naučiti vse simbole naše abecede, s pomočjo katerih začnejo pisati in brati [1]. V Kurikulumu za vrtce je naveden kot eden od ciljev tudi razvijanje prstne spretnosti oz. t. i. fine motorike s primeri dejavnosti: otrok se igra oz upravlja z različnimi predmeti (vrvice, kroglice itn.) in snovmi (voda, pesek, mivka), ki omogočajo gibanje s prsti, dlanmi, rokami, nogami in stopali (gnetenje, prelivanje, presipanje, prijemanje, pretikanje itn.) [2]. Ko smo s skupino petletnikov izvedli omenjene in podobne dejavnosti, so bili otroci suvereni ne le v fino motoriki, temveč tudi pri zapisu črt in krivulj, nekatere pa je celo zanimalo, kako so oblikovane določene črke. Posledično smo se odločili Slika 1: Otroka med reševanjem grafomotoričnih vaj. nadgraditi grafomotorične vaje in jih obogatiti z vključitvijo IKT-orodja. Pri tem smo upoštevali Smernice za uporabo IKT v vrtcu, ki narekujejo, da morajo strokovni delavci otroku nuditi 3 ZAKLJUČEK ustrezne možnosti in izzive (otroke učijo uporabljati IK sredstva; jih seznanjajo z možnostmi uporabe le-teh; jim približujejo Spoznali smo, da je vključevanje IKT-orodja v vzgojno delo zelo internet in jih seznanjajo s prednostmi in pastmi na njem …) in koristen in v tem času tudi nujno potreben. Tako najmlajšim tudi ozaveščati svoj odnos do nje [3]. zagotovimo vključitev v porajajočo se digitalno pismenost, jim zagotovimo enake možnosti in tako zmanjšamo razlike med njimi. Omenjen didaktični pripomoček je otrokom popestril 2 POTEK DELA V SKUPINI vzgojno delo. Šlo je za procesno učenje, katerega cilj niso bili pravilni in nepravilni odgovori, temveč spodbujanje otrokovih 2.1 Uvodna motivacija strategij dojemanja, izražanja in razmišljanja, ki so zanj značilne Z otroki smo se zbrali v jutranjem krogu. Pogovarjali smo se o v posameznem razvojnem obdobju. V prihodnje bi aplikacijo sklenjenih in navpičnih črtah. S prsti so risali po zraku in dobro lahko uporabljali večkrat, da bi jo otroci dobro osvojili in se tako spremljali povezavo roka‒oko. Naredili so tudi nekaj vijug in navdušili nad drugačnim učenjem, ki je bila za mnoge zelo predlagali, da rišemo drug drugemu po hrbtu. zabavna. V prihodnje bi aplikacijo lahko nadgradili z drugimi Na mizi so opazili mojo tablico in skupaj smo si na njej učnimi vsebinami in otroku omogočili, da ima več možnosti pogledali, kako se tudi na elektronskih napravah lahko zabavamo uporabe podobnih spletnih orodij in naprav. Tako bi svoje in hkrati nekaj naučimo. Pogledali smo zabavne igre, preko računalniško znanje izpopolnjevali. V naslednjem šolskem letu katerih se učimo in spoznavamo predopismenjevalne veščine, ki bi staršem že na začetku na sestanku predstavila različna spletna nas popeljejo v svet črk. Skupaj smo si ogledali aplikacijo ABC orodja in njihovo uporabo kot podporo učenju vključila v svoj PreSchool Kids Tracing, ki je otroke takoj navdušila in želeli so letni delovni načrt. jo tudi posamezno preizkusiti. Povedali smo navodila, določili pravila in preizkusili novo spletno orodje. ZAHVALA Zahvaljujem se svoji sodelavki in vsem otrokom iz skupine, ki so z zanimanjem in z sodelovanjem pristopili k IKT- orodju in 2.2 Glavni potek dejavnosti (Uporaba spletne ga z veseljem preizkusili. aplikacije ABC PreSchool Kids tracing) LITERATURA IN VIRI Otroci so svoje grafomotorične sposobnosti nadgradili z [1] Keršič K., Južna B., 2009. Zgodnje opismenjevanje otrok. Dostopno na vključitvijo IKT-orodja. Svoje znanje so nadgradili tako, da so naslovu: https://www.viva.si/Psihologija-in-odnosi/422/Zgodnje- se preizkusili še preko tablice. Aplikacija jih je usmerjala in jim opismenjevanje-otrok (10. 8. 2021) pokazala, če pravilno izpolnjujejo različne grafomotorične vaje. [2] Kurikulum za vrtce, 2009. Ljubljana, Ministrstvo za šolstvo in šport, Urad Republike Slovenije za Šolstvo. Vlekli so različne linije. Od krivulj, do enostavnih ravnih in [3] Usar K., Jerše L., 2016. Smernice za vključevanje IKT v vrtcu. ZRSŠ. poševnih črt. Lahko so si izbrali enostavne vzorce ali težje, Dostopno na naslovu: https://www.zrss.si/digitalnaknjiznica/smernice- ikt-vrtec/files/assets/common/downloads/publication.pdf (10. 8. 2021) zahtevnejše. Aplikacija jih je vodila in usmerjala v pravilen zapis. Otroci so bili zelo motivirani in zbrani. Razporedili so se v skupine. Nekateri so vaje izpolnjevali v zvezku, drugi pa preko spletnega orodja. Vsi so se preizkusili preko-IKT orodja in svoje znanje nadgradili s spoznavanjem nekaterih črk, ki jih aplikacija ponuja. Spoznali so črke I, L, M, N, T in O in jih kasneje tudi pravilno zapisovali v zvezek. 591 Izdelava laboratorijskih vaj s PWS Making Laboratory Exercises with PWS Robert Šifrer Šolski center Kranj, Višja strokovna šola za elektroenergetiko Kranj, Slovenija robert.sifrer@sckr.si POVZETEK section) of the bare line or cable so that the voltage on the line remains within 10 %. Students first model the grid, then do the Za izdelavo laboratorijskih vaj za področje elektroenergetskih calculations, then simulate the power flows and simulate the omrežij sem se zgledoval po razvojnem oddelku Elektra outages of the lines and other parts of the network. By the way, Gorenjske d.d., Razvijajo nova in popravljajo (vzdržujejo) stara they learn to draw all kinds of mains topologies (radial, loop, električna omrežja zaradi prodora novih razpršenih elektrarn in double-sided, open loop), calculations of voltage drops and rises novih večjih porabnikov na obstoječa omrežja znotraj 10 % on lines (on busbars), who causes them, overvoltages, spremembe napetosti. S programom razvojni inženir nariše vse simulations of flows of all three powers. These are the main možne modele omrežja in hitro izračuna vse spremembe pedagogical highlights and desired outcomes for students, who napetosti, lahko opravi simulacije moči v mreži. Na spletu sem have completed them good and satisfied for last 10 years. našel brezplačni program Power World Simulator. Uporabil sem analitično, primerjalno in opisno metodo, metodo poskušanja, KEYWORDS metodo sinteze ter za zaključek metodo anketiranja. Cilj vsake vaje je, da študent popravlja upornost in reaktanco (presek) Electrical grid, modeling, voltage regulation, simulator golega voda ali kabla, da napetost na vodu ostane znotraj 10 %. Študenti najprej modelirajo omrežja, nato naredijo izračune, 1 UVOD nato simulirajo pretoke moči in simulirajo izpade vodov in ostalih delov omrežja. Mimogrede se naučijo risati vse vrste Že v srednji tehniški šoli zadnjih 22 let, še bolj pa na Višji topologij električnega omrežja (radialno, zankasto, dvostransko strokovni šoli 8 let sem iskal stik s sodobno elektroenergetsko napajano, odprta pentlja), izračune padcev in porastov napetosti stroko s pomočjo podejtij in razvojem tudi preko strokovnih na vodih (na zbiralkah), kdo jih povzroča, prenapajanja, ekskurzij. V Elektro Gorenjski nam je pred desetimi leti razvojni simulacije pretokov vseh treh moči. To so glavni pedagoški inženir pokazal problematiko porasta priklopov sončnih poudarki in želeni rezultati pri študentih, ki jih že 10 let radi in elektrarn na 400 V omrežja, ki v določenih urah dneva ne dajejo dobro opravijo. v mrežo samo električne moči, ampak povzročajo tudi škodljive poraste napetosti nad standardizirano 400 V vrednostjo. Kasneje KLJUČNE BESEDE sem se večkrat oglasil v njihovi razvojni pisarni in pokazali s mi, Električno omrežje, modeliranje, napetostna regulacija, kako njihovo delo poteka z uporabo programa Gredos. Oni simulator pripravijo modele omrežij, Gredos pa jim izračuna, kateri model omrežja je optimalen. Ta rešitev gre protem v projektivno službo, ABSTRACT nato pa jo gradbena enota postavi. For the production of laboratory exercises, I followed the Cilj postavljanja laboratorijskih vaj mi je, da so te iz področja development engineers of Elektro Gorenjska Ltd. They devlop vzdrževanja, da so sodobne glede današnjega dela inženirjev v new and repair (maintain) old electrical grids due to the podjetjih, da so intelektualno zahtevne in pestre ter seveda, da so penetration of new dispersed power plants and new major poceni za izvedbo, glede na to, da so stroji in elementi v consumers to existing networks within 10% of the voltage elektroenergetiki zelo dragi, kar si šola težko privošči. Natančni change. With the program, the development engineer draws pedagoški cilji so, da se študenti naučijo vseh topologij many grid models and quickly calculates all voltage I found the električnih omrežij (zanke v prenosnih omrežjih, odprto omrežje free Power World Simulator program online. I used an analytical, radialnih vodov v 400 V in odprte pentlje ter dvostransko comparative and descriptive method, an experimental method, a napajani vodi v 20 kV omrežjih), da znajo vrisati v omrežja synthesis method and a survey metod. The goal of each exercise osnovne elemente, naprave in električne stroje. Da razumejo is for the student to correct the resistance and reactance (cross odnose med njimi in njihove parametre (R, X, B) in značilnosti. Vaje se modernih problemov dotikajo, ker danes distribucijska Permission to make digital or hard copies of part or all of this work for personal or omrežja pridobivajo na osrednjem pomenu znotraj classroom use is granted without fee provided that copies are not made or distributed elektroenergetike, saj vanje prodira nešteto razpršenih virov for profit or commercial advantage and that copies bear this notice and the full elektrike, obnovljivih virov na 400 V omrežja. Na drugi strani pa 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). vanjo prodirajo novi porabniki, saj poteka tranzicija ogrevanja in Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia hlajenja iz fosilnih virov na elektriko (toplotne črpalke) in © 2021 Copyright held by the owner/author(s). tranzicija transporta iz fosilnih virov na elektriko (e-avti). Za e- polnilnice pa je znano, da bodo vlekle iz omrežja velike moči. 592 Tako razpršeni viri elektrike kot novi porabniki pa z velikimi danes še vedno ne znam uporabiti večino funkcij, kar delajo tokovi v omrežju povzročajo velike poraste ali padce napetosti. doktorji znanosti v razvojnih oddelkih. Potreboval bi mentorja ali Tako dobimo škodljivo nihanje napetosti, česar zadnjih sto let kak tečaj, saj se tega nismo učili na univerzitetnem študiju pred nismo pozanali tako izrazito. Takrat so vzdrževalci povečali moč 30 leti. Zato sem si na Youtube ogledal precej kratkih in transformatorja ali presek kabla. Sedaj pa se bližamo enostavnih filmčkov, kjer razni razvojni inženirji po celem svetu regulatorjem napetosti, megahranilnikom, regulacijskim predstavljajo lahke in enostavne primere praktične uporabe v distribucijskim transformatorjem, pametnim (avtomatiziranim) svojih podjetjih. Recimo video Introduction to PowerWorld, ki omrežjem, ko krmilnik regulira prej neumno omrežje s pomočjo je nastal v tistem letu, ko sem si to ogledoval in se iz njega učil senzorjev, aktuatorjev in podatkovnega omrežja. To področje leta 2012[4]. Dolgi in zahtevni so prezahtevni zame in za škodljivih padcev in porastov napetosti spada v standard SIST študente. EN50160, ki nam določa kvaliteto napetosti skozi nekaj merljivih parametrov. Mi se bomo tu ukvarjali s škodljivimi porasti napetosti, ki jih povzročajo elektrarne oz. sodobni razpršeni viri, običajno male hidroelektrarne, vetrne elektrarne, bioplinske termoelektrarne in predvsem fotovoltaične sončne elektrarne, kjer trenutno prevladujejo samooskrbne, ki rastejo v Sloveniji s približno 2.000 novimi elektrarnami letno. Študenti bodo morali doseči štiri osnovne cilje. Znati bodo morali iz elementov omrežij narisati več modelov omrežja ( modeliranje omrežij). Znati bodo morali programsko in s formulami izračunati padce in poraste napetosti na vodih. Znati bodo morali popraviti te prevelike padce in poraste s pomočjo večanja presekov vodov in s tem resistance in reaktance voda. In nazadnje bodo morali znati tudi simulirati pretoke delovne, jalove in navidezne moči po omrežju s poudarkom, če pride do izpada dela omrežja, da znajo narediti prenapajanje in pogledati, Slika 1: Prenosno, 400 kV omrežje Slovenije[1] kako to prenapajanje (novi, večji tokovi) škodljivo vpliva na poraste in padce napetosti na posameznih vodih, ki prevzamejo moč izpadlega voda zaradi delovanja zaščite ali okvare. 2 IZDELAVA PRVE VAJE Za cilj risanja smo si s študenti ogledali prenosno omrežje Slovenije, enopolno 400 kV shemo iz rdečih črt (Slika 1), ki jo imam na plakatu v učilnici in v spletni učilnici Moodle. Naučim pa jih, da si jo lahko poiščejo na spletni strani ELES d.o.o. (Elektro Slovenija, ki je edini sistemski operater prenosnega omrežja v Sloveniji)[2]. Ogledamo si trenutne pretoke moči v prenosnem omrežju Slovenije. Vozlišča med rdečimi črtami predstavljajo prenosne razdelilne transformatorske postaje (RTP v nadaljevanju). To so: glavna in osrednja RTP Beričevo (v njej sta tako regijski kot republiški center vodenja omrežja), ki napaja ljubljansko območje z napetostjo 110 kV, nato RTP Okroglo za gorenjsko regijo, RTP Divača za primorsko regijo, RTP Krško za dolenjsko regijo, RTP Maribor za večji del štajerske regije in Prekmurje ter RTP Podlog za šaleško dolino in celjsko območje. Trenutno se gradi RTP Cirkovce na 400 kV in iz njega daljnovodna interkonekcija z Madžarsko. Nato omenimo in narišemo tudi interkonekcije s Slika 2: Učenje risanja modela s PWS iz videa[3] tujimi prenosnimi omrežji Italije, Avstrije, Madžarske in Hrvaške, ki našemu sistemu omogočijo zančno topologijo in 2.1 RISANJE MODELA 400 kV večjo stabilnost (obratovalno varnost), kar je v elektroenergetiki PRENOSNEGA OMREŽJA cilj številka 1. Pojasnim tudi, da na rdeča črta pomeni enosistemski daljnovod (L1, L2 in L3), dve črti pa dvosistemski Moj prvi model ni vseboval RTP Cirkovce, ker te takrat niso daljnovod. imele 400 kV RTP in povezav, zgolj 220 kV in 110 kV. Najprej Na spletu poiščemo Power World Simulator[3], ameriško sem odprl nov primer (new case), začel sem risati (draw) omrežje aplikacijo, ki ponuja veliko storitev za visokonapetostna omrežja. v urejevalnem načinu (edit mode). Izberem meni Network in v Naložimo si program PWS Simulator18, kajti ponuja nam tudi njem ali Bus ali Transmission Line ali Generator ali Load. Slika program Viewer. Vsako leto je obnovljena aplikacija, sedaj je to 3 kaže, da sem narisal RTP Beričevo (Bus), jo poimenoval, ji 18. verzija. Na začetku ga nisem znal prav nič uporabljati in tudi določil nominalno (nazivno) napetost 400 kV in ji določil, da je 593 glavna zbiralka (System Slack Bus). Američani imajo druge moč P v MW, ki jo podam na začetku šolske ure študentom. In nazivne napetosti kot jih imamo v Evropi. sicer dva podatka, delovna moč P in jalova moč Q (če je več motorjev v industriji), običajno v razmerju 4:1. Študent je postavil kot glavno zbiralko (System Slack Bus) v RTP Podlog zaradi TE Šoštanj. Bolj natančno senzorje (merilce na vodu) prikazuje Slika 5, kjer sem dal na daljnovod tudi merilec toka v amperih (A, slika narobe prikazuje AMP!) , merilec P v MW in merilec jalove moči v MVAr. Slika 3: Vpisovanje parametrov zbiralkam RTP Beričevo Nato sem narisal RTP Okroglo in še med njima daljnovod. Risal sem kar enosistemski daljnovod. Vpisal sem začetne parametre R in X in jima določil relativno vrednost 0,1 obema, ker sta Slika 5: Del posnetka simulacije modela z meritvami relativno kratka daljonvoda. Nato sem nadaljeval z risanjem ostalih zibralk, ki so v osnovi dvosistemske zaradi varnosti, na 2.2 SIMULACIJA PRETOKOV MOČI (P, Q in sliki pa predstavljajo RTP prenosnega omrežja Slovenije. Dodal sem tudi sinhronske generatorje, ki predstavljajo večje elektrarne S) IN PRENAPAJANJE v Sloveniji in njihove moči. Na zbiralkah sem narisal puščice Simulacijo se naredi tako, da Edit mode spremenimo v Run mode (Load) kot bremena moči, ki jih RTP transformirajo na 110 kV in da kliknemo zeleni gumb Play. Po narisanem modelu se omrežje in s to ocenjeno močjo napajajo svojo regijo. začnejo pretakati večje in manjše puščice, odvisno kako velike Slika 4 prikazuje končano risanje modela. Iz edit mode moči tečejo po daljnovodu. Študente nato spodbudim, da (urejavalnika) sem preklopil na run mode (vklopi simulacijo) in kliknejo v rdeč kvadratek, ki je simbol stikalne enote (odklopnik kliknil gumb play (poženi simulacijo). Prikažejo se delovne moči in dva ločilnika), da pogledajo, kako se omrežje spremeni pri v megavatih na posameznih daljnovodih in smer pretoka moči. izpadu nekega daljnovoda zaradi okvare. Kako se vsi podatki Lahko bi tudi narisal senzorje z skupne, navidezne moči v MVA moči in tokov spremenijo. Zelene puščice na rumenih vodih in za jalove moči v MVAr po posameznih daljnovodih. Ne znam postanejo večje, ker morajo ostali daljnovodi sedaj prenašati pa nastaviti senzorja, ki grafično prikaže relativno obremenitev večje moči zaradi izpada enega daljnovoda. Če študent kaj nariše daljnovoda od dovoljenje obremenitve. To sliko mi morajo narobe ali vstavi čudne vhodne podatke, se namesto simulacije oddati kot prvo zahtevo za uspešno laboratorijsko vajo. prikaže črn ekran in oznaka Black Out, kar pomeni razpad sistema. To pomeni, da mora ponovno začeti risati nov model, kar se zgodi običajno polovici študentov. 2.3 IZRAČUN NAPETOSTI NA ZBIRALKAH MODELA 400 kV OMREŽJA Tretji del laboratorijske vaje so izračuni padcev ali porastov napetosti na daljnovodih zaradi velikih tokov, ki jih določajo večje elektrarne oz. večji porabniki. Slika 6 prikazuje izračune napetosti na zbiralkah, ki povedo padce napetosti: absolutne v kV in relativne v %. Na zbiralkah imamo senzorje napetosti. Na zbiralkah so nazivne (nominalne) napetosti 400 kV (prvi stolpec), v resnici pa so napetosti manjše tam, kjer je velika poraba in Slika 4: Narisan model in zagon simulacije večje na tistih zbiralkah, kjer so velike elektrarne. Program sam vse izračuna. Pogledamo tako, da kliknemo gumb Model Na vrhu v sredini je RTP Beričevo. Levo zgoraj RTP Okroglo, Explorer, kar lahko prevedemo v naredi izračune napetosti za naš levo spodaj RTP Divača, desno spodaj RTP Krško, nad njim RTP model. Tak posnetek zaslona v Model Explorerju mi morajo Podlog, na desni pa smo letos že narisali RTP Cirkovce in zgoraj študenti oddati poleg simulacije moči v narisanem modelu. RTP Maribor. Dodal sem generatorje TETO Ljubljana na RTP Modri rezultati, vrstice, pomenijo, da so vsi padci znotraj Beričevo, Dravske elektrarne na RTP Maribor, TEŠ na RTP standarda 10%. Če bi risali popolnoma novo omrežje pa bi morali Podlog in JE Krško na RTP Krško. Puščice prikazujejo delovno biti znotraj 5%. Vidimo, da ima polno napetost RTP Podlog 594 (100%), ker je System Slack Bus in pa RTP Krško (100%, PU Volt), ker gre vanje zelo velika moč iz elektrarn. Pri RTP Krško bi celo moralo pokazati poraste napetosti. Ostali RTP pa so porabniška vozlišča in zato na koncu daljnovodov z velikimi tokovi dobimo resnične napetosti, ki so nekaj % manjše od 100 % ( PU Volt). Recimo RTP Okroglo ima 92,83 %, kar pomeni, da je na daljnovodu 7,17 % padca napetosti zaradi zelo velikega toka v njem, ki ga zahtevajo veliki industrijski porabniki, ki sem jih predpisal v nalogi za vpis v Load (breme), ki ga na slikah prikazuje puščica. To je manjše od mejnih 10 % v standardu, zato Slika 7: Izrez iz PWS, kjer študent spreminja vrednosti R, je to OK in je vrstica modra. Stolpec Angle (fazni kot med X in B voda ali transformatorja, dokler niso padci napetosti napetostjo in tokom v vodu) nam še ne predstavlja pomembnega modre barve podatka, je pa odvisen od imepdance bremena oz. od velikosti reaktance X. 2.5 Povezava laboratorijskih vaj s sodobno usmeritvijo tehnologije za regulacijo U/Q To popravljanje napetosti in hkrati jalove energije, ki ga študentje in razvojni inženirji delajo preko aplikacije PWS, se imenuje napetostno popravljanje in spada bolj v primitivno in počasno krmiljenje napetosti. Dejansko iščejo primernejši, večji presek kabla (če so padci ali porasti napetosti večji) in ta kabel zamenjajo potem delavci. Ali pa vzamejo transformator večje moči ob večjih obremenitvah na porabniški strani. To je Slika 6: Posnetek tabele v Model Explorerju, ki prikazuje v stolpcu Volt (kV) izmerjene absolutne vrednosti napetosti primitivna metoda zadnjih sto let. Vse to razložim v prvi laboratorijski vaji in si morajo v Naslednjo leto sem vpeljal drugačno prvo laboratorijsko vajo. dokument zapisati pri prvi vaji. Kar pa sedanjost in prihodnost Najprej smo »peš« računali padce in poraste napetosti iz toka in težita, pa gre tehnologija v smeri napetostne regulacije s pomočjo upornosti voda, preseke voda iz upornosti, razlike napetosti na raznih senzorjev, krmilnikov, informacijskih prenosov in zbiralkah, izgube moči na vodu. Nato pa smo skupaj narisali aktuatorjev (napetostna regulacija na primarju distribucijskega trikotno zanko električnega omrežja iz 3 RTP iz treh daljnovodov. transformatorja).To imenujemo pametna omrežja in Slovenija bo Tako, da sem jih naučil, kako se nariše zbiralko (bus), ki v naslednjih 20 letih vgradila za 10 milijard € naprav v ta omrežja. predstavlja RTP, generator, breme (load) in daljnovod oz. kabel In o tem jim veliko danes govorim pri prvi laboratorijski vaji, (transmission line) ter energetski transformator (transformer). kjer si tudi študenti morajo zapisati vse načine popravljanja Vse v zavihku draw (nariši) in v edit mode. Ostale vaje so delali napetosti na vodih v omrežju, vključno z moderno napetostno sami, ob občasni moji pomoči. regulacijo pri pametnih omrežjih, kamor spadajo tudi vgrajeni megahranilniki, virtualne elektrarne, polprevodniški L in C 2.4 Izpis končnih nastavitev R in X elementi (SVCR), ki popravljajo napetosti in jalovo energijo v omrežju, regulacija U/Q na generatorjih, magnetni stabilizatorji Zadnji, tretji del vsake vaje pa je, da po večurnem poskušanju napetosti na vodih itd. vpisovanja relativnih vrednosti (v %) R, X in B končno dobijo pravilne, modro obarvane rezultate v Model Explorerju. Običajno so vse vrstice daljnovodov iz Slike 6 obarvane rdeče, 2.6 Delo študentov in metoda ankete ker so padci napetosti preveliki. Gredos ponuja normirane preseke kablov in golih vodov, tukaj pa te možnosti ne znam Za povratno zanko uspešnosti poučevanja takih laboratorijskih uporabiti. V upornostih vodov R se skrivajo preseki vodov, vaj sem uporabil tako moja opažanja med delom študentov, specifična upornost aluminija in dolžina voda. Večji presek voda končni pregled in ocenjevanje laboratorijskih vaj in anonimne pomeni manjšo upornost voda in tako manjšo škodljivo ankete na koncu šolskega leta. spremembo napetosti zaradi toka v vodu. R je resistanca ali Študenti so bili skozi vsako vajo vedno bolj izkušeni in upornost, X je reaktanca, ki igra pri zelo dolgih daljnovodih samostojni. S pomočjo mojih pogovorov z njimi in sprotne ključno omejitev prenosa moči ter susceptanca B, v kateri se pomoči študentom sem videl, kako kvalitetno in v globino skrivajo kapacitivnosti med linijskimi vodniki in dozemne razumejo vsako vajo. Predvsem pa so vedeli, kaj delajo. kapicativnosti. Okno v PWS, kjer študentje vpisujejo relativne Pomembno je, da ima vsak svoj računalnik in vsak dela svojo, vrednosti R, X in B prikazuje Slika 7. drugačno vajo, čeprav jim dovolim, da se med seboj pogovarjajo in si pomagajo. Pri poučevanju imam ves čas pred očmi izrednega študenta, znanca, ki sem ga bolj osebno spraševal, kaj so pri nekem predmetu v šoli, pri laboratorisjkih vajah z računalnikom, delali in mi je rekel, da celo leto ni imel pojma, da je samo drugim študentom sledil, ponavljal za njimi in ni nič vedel ne o ciljih, namenih in o rezultatih vaj. Kaj takega nočem, da katerikoli študent govori za moje vaje. Verjamem, da bolj kot je vaja učitelju jasna, bolj jo lahko primerno študentom razloži. 595 Pri ocenjevanju laboratorijskih vaj sem videl, da so dosegali ZAHVALA visoke rezultate dela. Vaje so glede na zahteve dobro in Zahvaljujem se razvojnim inženirjem Mihu Žumru, Anžetu kvalitetno opravili, nekateri odlično, nekateri malo bolj slabo. Vilmanu in Mihu Noču, ki so v razvojnem oddelku Elektro Predvsem sem pozoren, da preverim, da ni podvojenih vaj, Gorenjska d.d. Pokazali so mi svoje delo in uporabo Gredosa. skopiranih vaj. V veliko pomoč so mi bili tudi razni vzhodnjaški razvojni Nazadnje pa še vsak september dobim anonimne ocene inženirji, ki na Youtube v videoposnetkih razlagajo osnove in študentov za poučevanje vaj in predvanj, kjer dobivam visoke kompleksnosti PWS, pa čeprav sem moral vaje postaviti malo po ocene vseh 10 let. svoje za namen predmeta in ni nobena enaka ali podobna tem vajam, razen risanja elementov električnih omrežij na samem 3 ZAKLJUČEK začetku. Uspelo mi je izdelati 6 laboratorijskih vaj za vse topologije omrežij in za 4 napetostne nivoje v Sloveniji. Vsako leto dodam LITERATURA IN VIRI kaj novega. Narišemo model, poženemo simulacijo, se učimo [1] Prenosno električno omrežje Slovenije. Dostopno na naslovu www.svet- prenapajanja. Veliko časa posvetim spoštljivi interakciji med energije.si/upload/files/Osnove%20jedrske%20energetike.pdf nami in moji pomoči ob kateri skušam zaznati, koliko znanja so (24.8.2021) že osvojili o sami laboratorijski vaji. Nato popravljamo vse rdeče [2] Obratovanje prenosnega omrežja, ELES d.o.o., sistemski operater prenosnega omrežja. Dostopno na https://www.eles.si/obratovanje- vrstice v Model Explorerju (dimenzioniramo presek vodov). Bi prenosnega-omrezja (24.8.2021) pa rad koga od teh specialistov za PWS spoznal, ker imam [3] Power World Simulator, brezplačna in omejena aplikacija za modeliranje, izračune in simulacije v prenosnih ormežjih. Dostopno na naslovu nešteto vprašanj zanj glede izboljšav vaj in glede koristnih novih https://www.powerworld.com/powerworld-simulator-18 (24.8.2021) vaj ali dodatkov. Vmes med vajami lahko razlagam teorijo, [4] Introduction to PowerWorld Simulator By Ahmad Awais. Dostopno na naslovu https://www.youtube.com/watch?v=2Gy6vT9fDk0 (24.8.2021) uporabnosti, pomen in logiko veličin in tudi električni model voda in transformatorja opisan z upornostmi (serijske), reaktancami (serijska) in susceptanco (vzporedna, shunt). 596 Funkcionalnosti spletnih učilnic pri izobraževanju knjižničarjev med epidemijo The functionality of the online classrooms in librarian education during the epidemic Gregor Škrlj Narodna in univerzitetna njižnica m Ljubljana, Slovenija gregor.skrlj@nuk.uni-lj.si POVZETEK dediščino, ki jo ima v uporabi ali jo poseduje, ter opravlja ustrezno arhivsko dejavnost [1]. Izobraževalna dejavnost Narodne in univerzitetne knjižnice ima NUK je torej nacionalna knjižnica Republike Slovenije in je pomemben vpliv na knjižnični sistem v Sloveniji. V trenutku, ko hkrati univerzitetna knjižnica za Univerzo v Ljubljani ter je bila razglašena epidemija, je bilo potrebno izobraževanje osrednja državna knjižnica. Izvaja knjižnično dejavnost v okviru prilagoditi novim razmeram. Izobraževanje na daljavo je bilo javne službe in skrbi za dediščino ter sodeluje v nacionalnem uspešno izpeljano s pomočjo spletnih orodji ter spletnih učilnic, vzajemnem bibliografskem sistemu in opravlja tudi druge kar je pomenilo, da je tehnološki napredek in integracija dejavnosti [2]. Med temi nalogami je tudi izobraževalna informacijske tehnologije v izobraževanje prinesla učinkovite dejavnost, ki jo organizira ter izvaja oddelek za izobraževanje, rešitve, ki smo jih aplicirali ter se prilagodili delu med epidemijo razvoj in svetovanje in sicer za knjižničarje, založnike in in zagotovili nemoteno izvajanje izobraževanj. V luči uporabnike knjižnic. Izobraževanje je tako rekoč nepogrešljiv spremenjenih razmer dela in izobraževanja na daljavo so spletne sestavni del razvoja vsakega knjižničarja in knjižnice, zato tej učilnice s svojo funkcionalnostjo zadostile potrebam. dejavnosti NUK posveča precej pozornosti. KLJUČNE BESEDE O izobraževalni dejavnosti več v nadaljevanju. mejite na največ šest strani. Ozobraževanje, spletne učilnice, epidemija, knjižničarji ABSTRACT 2 IZOBRAŽEVANJE KNJIŽNIČARJEV V The educational activities of the National Library of Slovenia has NUK a significant impact on the library system in Slovenia. When the Če povzamem besedilo Etičnega kodeksa slovenskih epidemic was declared, educational activities had to be adapted knjižničarjev, mora vsak knjižničar nenehno izpopolnjevati svoje to the new situation. Distance education was successfully strokovno znanje in ustvarjalno prispevati k razvoju implemented using online tools and online classrooms, which knjižničarske stroke in njene dejavnosti [3]. Zato NUK vsako meant that technological advances and the integration of leto ponuja in izvaja strokovno spopolnjevanje ter permanentno information technology provided effective solutions that were izobraževanje knjižničarjev. Izvaja tudi bibliotekarske strokovne applied and adapted to work during the epidemic and ensured the izpite ter postopke priznavanja strokovnih nazivov za knjižnično smooth transfer of education. In the light of the changed situation dejavnost. Informacije o izobraževalnih programih ponuja v of work and distance education, online classrooms have met the katalogu z naslovom Program izobraževanja , ki ga vsako leto needs with their functionality. prenovi in dopolni z novostmi [4]. KEYWORDS NUK organizira in izvaja različne oblike izobraževanj za knjižničarje, založnike in usposabljanja za uporabnike knjižnic Education, online classrooms, epidemic, librarians [5]. Izobraževalni program se izvaja v računalniški učilnici NUK (Turjaška ulica 1) ter v učilnici na Leskoškovi cesti 12. Število udeležencev na posameznem tečaju je omejeno s prostorskimi 1 UVOD zmožnostmi in dodatno opremo, ki je potrebna za posamezno Narodna in univerzitetna knjižnica (NUK) je nacionalna izvedbo tečaja (računalniška oprema, knjižnično gradivo …). knjižnica Republike Slovenije, katere temeljno poslanstvo je Izobraževalne vsebine so namenjene knjižničarjem začetnikom, zbiranje in varovanje ter zagotavljanje uporabe nacionalne zbirke knjižničarjem, ki želijo izpopolniti svoje znanje ter tistim, ki se knjižničnega gradiva, strokovna podpora knjižnicam pri želijo usposobiti za delo v sistemu vzajemne katalogizacije. izvajanju javne službe in nacionalnemu bibliografskemu sistemu Tečaje in delavnice se organizira tudi za tiste, ki niso zaposleni v ter vključevanje v mednarodne knjižnične povezave. knjižnici, a bi se želeli seznaniti z izobraževalnimi vsebinami. Knjižnica v skladu z zakonom o knjižničarstvu na podlagi V letu 2020 pa je v ustaljene tirnice izvajanja izobraževanj posebne pogodbe med knjižnico in Univerzo v Ljubljani, v nenadoma posegla epidemija, saj je bila 13. marca 2020, na soglasju z ustanoviteljem, opravlja tudi funkcijo univerzitetne območju Republike Slovenije, razglašena epidemija nalezljive knjižnice Univerze v Ljubljani. Knjižnica na podlagi predpisov bolezni COVID-19. Življenje se je v trenutku spremenilo in med o varstvu kulturne dediščine skrbi za Plečnikovo in drugo drugim so tudi knjižnice zaprla svoja vrata. S tem so odpadla 597 oziroma so bila, za nedoločen čas, prestavljena vsa udeleženci si lahko sami izberejo čas in hitrost učenja (ko gre za izobraževanja, ki jih NUK izvaja za knjižničarje, založnike in vnaprej pripravljeno usposabljanje ali del tega). uporabnike. Več o izobraževanju med epidemijo v nadaljevanju. Ker sem že imel pripravljene vsebine in cilje posameznih izobraževanj ter gradiva predavateljev, sem s pomočjo sodobne informacijska in komunikacijske opreme 3 EPIDEMIJA IN NOVE OBLIKE uporabil nove oblike ter načine posredovanja in usvajanja znanja IZOBRAŽEVANJA [11]. Začel sem s pripravami različnih spletnih učilnic, ki sem jih 13. marca 2020 se je zaradi epidemije nalezljive bolezni COVID- razvrstil po kategorijah (permanentno izobraževanje, 19 vse spremenilo, izobraževalne ustanove so zaprla svoja vrata, izobraževanje za začetnike v stroki, Izobraževanje za vzajemno zaposleni so prešli na delo od doma, država se je tako rekoč katalogizacijo ter izobraževanje za uporabnike). Vsak tečaj, ki se zaprla. Ob tem je bilo potrebno analizirati stanje ter premisliti je do nedavnega izvajal v živo v prostorih knjižnice, je dobil svoj dostopnost izobraževalne dejavnosti NUK in novih oblikah virtualni prostor. Med predmete učilnice Izobraževanja za izobraževanja. Upoštevati je bilo potrebno navodila ter knjižničarje sem uvrstil Modul 1: Knjižnično gradivo in razmišljati o prilagajanju dejavnosti veljavnim ukrepom za knjižnice in Modul 2: Osnove varovanja in zaščite knjižničnega preprečevanje širjenja bolezni COVID-19. Glede na takrat gradiva, Tečaj za pripravo na splošni del bibliotekarskega izpita veljavne ukrepe je bilo potrebno vzpostaviti sistem e- ter tečaje za vzajemno katalogizacijo (vsako izobraževanje je izobraževanja, a vzpostavitev sistema e-izobraževanja v imelo svojo učilnico). Med učilnice Izobraževanje za uporabnike katerikoli instituciji je kompleksna naloga [6]. Izobraževanja se pa sem uvrstil učilnice Uporaba informacijskih servisov z e- niso smela več izvajati fizično v prostorih NUK-a temveč jih je članki in e-knjigami, E-informacijski viri za pomoč pri študiju in bilo potrebno preseliti v spletno okolje oziroma na daljavo. raziskovalnemu delu in Iskanje znanstvene literature s pomočjo Izobraževanje na daljavo navadno pomeni namerno, smotrno, portala mEga iskalnik NUK v Akademski digitalni zbirki načrtovano in organizirano izobraževanje [7]. S tem se ni (COBISS+). Med tematske učilnice pa so bile nameščene spremenil le način dela temveč tudi način poučevanja oziroma učilnice, ki so povezane z določeno tematiko, kot denimo podajanja novih znanj in vsi deležniki so se morali prilagoditi Knjižničarske novice (oddaja prispevkov, komunikacija z novim razmeram. Najhitreje je bilo mogoče nemoteno avtorji, navodila avtorjem za navajanje literature in podobno). izobraževanja ponuditi in izvajati s pomočjo spletne platforme Poskrbljeno je bilo tudi za dodatno gradivo, ki je bilo nameščeno ZOOM (ZOOM je spletna platforma za avdio in video v posebni kategoriji, do katere so lahko dostopali udeleženci komunikacijo, ki se uporablja za organiziranje sestankov, izobraževanj (pri spletnih učilnicah sem, glede na potrebe, izobraževanj, delavnic in drugih oblik sodelovanja) in Microsoft nastavil različne možnosti prijave - AAI račun, dostop gosta in Teams (platforma v sklopu izdelkov Microsoft 365 za prosto dostopno). Na sliki 1 je prikaz osnovnega vpogleda v komunikacijo), a hkrati je bilo potrebno pripraviti tudi spletne kategorije in predmete spletnih učilnic NUK. učilnice [8]. Glede na letni načrt izobraževanj je bilo potrebno načrtovati in pripraviti več spletnih učilnic. Zaradi nepoznavanja področja upravljanja spletnih učilnic, sem se najprej udeležil izobraževanj za izdelavo in delo v spletnih učilnicah. Najboljša možnost za pridobitev novih znanj s tega področja je bil Zavod Arnes , kot nacionalni servisni center za področje izobraževanja, raziskovanja in kulture, ki nudi vrsto storitev in sodobnih spletnih rešitev [9]. Ker sem se pri svojem delu do sedaj večkrat srečeval z različnimi novostmi, spremembami in uvajanjem informacijskih tehnologij, sem ravno tako sprejel izziv z možnostjo izdelave spletnih učilnic. 4 NAČRTOVANJE, IZDELAVA, Slika 1: Vpogled v kategorije in predmete spletnih učilnic UPORABNOST IN FUNKCIONALNOST NUK. SPLETNIH UČILNIC Kratica LMS (Learning Management System) predstavlja Za vse učilnice sem uporabil sodobno in poenoteno spletno učno okolje, ki je mesto, kjer se v virtualnem okolju obliko ploščic (format predmeta - pregledno, uporabno, povezujejo vsi deležniki ter učne vsebine. Spletne učilnice so sledljivo). Znotraj vsake učilnice sem uredil poglavja (glede na uporabna podpora izvajanju učnega procesa oziroma vsebine in cilje posameznega izobraževanja ali tečaja). Z izobraževanja in torej niso le skladišče gradiv, ampak tudi uporabo različnih dejavnosti, aktivnosti ali virov pa sem dodal prostor komunikacije, sodelovanja, oddaje nalog, vrednotenja in ter izdelal posamezne interaktivne naloge, interaktivne ocenjevanja. Spletna učilnica Moodle je torej stičišče, kjer prosojnice kot tudi videoposnetke. V veliko pomoč je bil vtičnik poteka aktivno učenje [10]. Spletne učilnice imajo veliko H5P (omogočal je, da sem na enostaven način dodajal aktivne prednosti: ni prostorske omejitve (fizični prostor - mize, stoli), vsebine - interaktivni videoposnetek, predavanja v obliki učenje je lahko veliko bolj interaktivno in multimedijsko, predstavitev ter kvize z različnimi tipi vprašanj, s katerimi so udeleženci obnovili pridobljeno znanje). Z uporabo različnih dejavnosti in interaktivnosti je bilo poskrbljeno, da je bilo e- 598 izobraževanje pripravljeno zanimivo, privlačno ter predvsem uporabno. Naslednja slika prikazuje vpogled v učilnico, ki je namenjena udeleženem, ki spremljajo izobraževanje. Slika 2: Vpogled v učilnico pred začetkom pregledovanja, spremljanja in reševanja nalog. Vsak udeleženec je lahko sam spremljal svoj napredek, kar se mu je v vsakem Slika 4: Zaslonska slika pripravljenega interaktivnega poglavju izpisovalo v odstotkih. videoposnetka predavanj, kjer so udeleženci sodelovali (na vsaki drsnici, kjer je viden krog, je bila pripravljena Na naslednji sliki (3) je viden pogled v učilnico modula 1, kjer dodatna interaktivna vsebina). so za udeležence (skladno s cilji izobraževanja) pripravljeni posamezni sklopi oziroma teme tečaja. Poleg vseh uporabnih virov, dejavnosti in funkcij je bil uporaben tudi forum, kjer je potekala komunikacija med udeleženci (postavljanje vprašanja, odgovorov ter nasvetov v povezavi z delom, vsebinami). Udeleženci so pridobili in nadgradili sposobnosti sodelovanja, komuniciranja, reševanja in uporabe spletne učilnice ter krepili posamezne stopnje digitalnih kompetenc (digitalne kompetence segajo na področje informacijske pismenosti, komuniciranje in sodelovanje, izdelovanje digitalnih vsebin, varnost in reševanje problemov) [12]. 5 ZAKLJUČEK V prispevku sem predstavil izobraževalno dejavnost NUK ter kako je v izvajanje izobraževanj posegla epidemija in s tem spodbudila prilagoditve in vpeljavo spletnega izobraževanja. Izvajati se je začelo izobraževanje na daljavo s pomočjo ZOOM, Microsoft Teams ter spletnih učilnic. V poučevanje na daljavo smo tako rekoč stopili čez noč, saj so se z razglasitvijo epidemije ustavili vsi izobraževalni procesi, zaposleni so opravljali delo od doma, zaprle so se šole in knjižnice. Ob novi situaciji je bilo potrebno prilagoditi tudi izobraževanje za knjižničarje, založnike in uporabnike, ki ga izvaja NUK. Nova realnost je imela tudi velik vpliv na prilagoditve in nove pristope pri izobraževanju v NUK. Tehnološki napredek Slika 3: Vpogled v učilnico modula 1: knjižnice in knjižnični in integracija informacijske tehnologije v izobraževanje je sistemi, kjer so pripravljene naloge (vtičnik H5P z prinesla učinkovite rešitve, ki smo jih aplicirali ter se prilagodili interaktivnimi vsebinami) po sklopih oziroma temah tečaja. delu med epidemijo in zagotovili nemoteno izvajanje izobraževanj. Torej so spletne učilnice s svojo funkcionalnostjo, Na naslednji sliki je prikaz začetka interaktivnega videoposnetka v določenem časovnem obdobju, opravile želene funkcije v (del tečaja za začetnike, modul 1: knjižnice in knjižnični sistemi), zahtevanih okvirjih (spletne učilnice so postregle z različnimi kjer so udeleženci spremljali vsebino o šolskih knjižnicah ter možnostmi in sodobnimi načini priprave e-izobraževanja, e- aktivno sodelovali s povratnimi informacijami. gradiv in komunikacije, kar je omogočilo izobraževanje na daljavo za vse deležnike). Ob tem je pomembno tudi dejstvo, da uporaba in delo s spletnimi učilnicami vpliva na razvijanje in 599 krepitev ključnih kompetenc, ki so potrebne za uspešno [4] Škrlj, G. 2006. Management kadrovskih virov v knjižnici: izobraževanje delovanje v današnji informacijski družbi. in usposabljanje kadrov v visokošolskih knjižnicah Univerze v Ljubljani. G. Škrlj, Ljubljana Če torej povzamem, je spletna učilnica odprla nove [5] Uredba o osnovnih storitvah knjižnic. Dostopno na naslovu: možnosti za povezovanje ter izobraževanje in vpeljavo novih http://www.pisrs.si/Pis.web/pregledPredpisa?id=URED2851 (9. 8. 2021) [6] Majerle, R. 2016. Razvoj sistema e-izobraževanja v Mestni knjižnici učnih strategij, kjer se neposredno razvijajo določene Ljubljana. R. Majerle, Kranj kompetence. Poleg tega pa je učenje ter delo s sodobno [7] Pečnik, T. 2005. E-izobraževanje kot alternativna oblika izobraževanja informacijsko komunikacijsko tehnologijo, ob ustrezno zaposlenih. T. Pečnik, Ljubljana [8] Uporaba aplikacije ZOOM. Dostopno na naslovu: https://www.nuk.uni- pripravljenimi in izbranimi viri ter dejavnostmi v spletni učilnici, lj.si/sites/default/files/dokumenti/2020/ZOOM.pdf (9. 8. 2021) vsekakor pomemben prispevek k večji dostopnosti učnih vsebin. [9] Jauk, A. 2014. Kaj mi pri e‐učenju nudi Arnes. V E‐izobraževanje: izzivi za visokošolske knjižnice: zbornik izvlečkov. Dostopno na naslovu: https://www.dlib.si/stream/URN:NBN:SI:DOC-A3GPCNWT/de02b793- LITERATURA IN VIRI ceb4-4912-829f-d85ee1540736/PDF (9. 8. 2021) [10] Inovativna učna okolja podprta z IKT - LMS Moodle. Dostopno na [1] Naloge, vizija, poslanstvo in vrednote NUK. Dostopno na naslovu: naslovu: https://www.inovativna-sola.si/lms-moodle/ (9. 8. 2021) https://www.nuk.uni-lj.si/nuk/poslanstvo# (9. 8. 2021) [11] E‐izobraževanje: izzivi za visokošolske knjižnice. Dostopno na naslovu: [2] Zakon o knjižničarstvu. Dostopno na naslovu: https://www.dlib.si/stream/URN:NBN:SI:DOC-A3GPCNWT/de02b793- http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO2442 (9. 8. 2021) ceb4-4912-829f-d85ee1540736/PDF (9. 8. 2021) [3] Etični kodeks slovenskih knjižničarjev. 1995. Dostopno na: [12] Carretero, S., Vuorikari, R., Punie, Y. 2017. Okvir digitalnih kompetenc http://www.zbds-zveza.si/?q=node3/20 (9. 8. 2021) za državljane: osem ravni doseganja kompetenc in primeri rabe: DigComp 2.1. Dostopno na naslovu: https://www.zrss.si/pdf/digcomp-2- 1-okvir-digitalnih-kompetenc.pdf (9. 8. 2021) 600 Primerjava pouka angleščine od 1. do 5. razreda na daljavo Comparison of English lessons from 1st to 5th grade in distance learning Patricija Urankar Osnovna šola Toma Brejca Šutna 39, 1241 Kamnik, Slovenija patricija.urankar@gmail.com POVZETEK boljše rezultate, učni proces je lahko bolj dinamičen in za učence bolj zanimiv [1]. Pouk na daljavo v vsakem izobraževalnem obdobju poteka »Premislek o ustrezni didaktični uporabi IKT je za učitelja drugače. Z vidika tujega jezika je zelo zanimivo spremljanje in pouk ključen, saj učitelju pomaga pri odločanju, kdaj, kako in podobnosti in razlik v pristopih in uporabi interaktivnih orodij za zakaj ga vključiti v pouk. Zahteva poznavanje pristopov za učence različnih starostnih skupin. Kot učitelji se moramo ustrezno uporabo IKT v izobraževalnem procesu ter znanja za zavedati, katere oblike in pristopi (tudi orodja) so primerni za pripravo didaktično ustreznih učnih gradiv in za ustrezen način katero starost ter v kolikšni meri so učenci samostojni. V vključevanja v pouk.« Tako ima učitelj pri vključevanju IKT v prispevku bom obravnavala uporabljena orodja v posameznem pouk izjemno pomembno vlogo. Učitelj namreč »opredeli razredu (1. – 5. razred) ter povzela kako smo preko le teh zbirali didaktični pristop in izbira tehnologijo za uporabo pri pouku.« dokaze o učenju ter na kakšen način in kako ustrezno je bila [1] podana povratna informacija učencem. Pri pouku tujega jezika so najbolj pogosta orodja za učenje KLJUČNE BESEDE besedišča. Ta morajo omogočati, da učenci »hitro opazijo ciljno besedišče, nuditi morajo razlago ciljnega besedišča, ter vsebovati Pouk na daljavo, angleščina, interaktivni materiali, povratna raznovrstne vaje in naloge, s katerimi učenci spoznajo vse vidike informacija razumevanja besed.« Učenci morajo videti svoje napake pri rabi ABSTRACT besedišča in jih odpraviti. Naloge morajo omogočati tudi možnosti za ponavljanje in utrjevanje novega besedišča. Distance learning takes place differently in each educational Nekatere raziskave potrjujejo pozitiven vpliv uporabe IKT orodij period. From the point of view of a foreign language, it is very za učenje tujega jezika. Poročajo predvsem o izboljšanju interesting to monitor the similarities and differences in motivacije za učenje. Predvsem v 1. in 2. razredu je motivacija approaches and the use of interactive tools for students of za učenje tujega jezika zelo pomembna. Raziskava pravi, da se different age groups. As teachers, we need to be aware of which pri uporabi tabličnega računalnika ali računalnika (pri pouku ali forms, and approaches (including tools) are appropriate for doma) za reševanje poučnih nalog v angleščini, dvigne which age and to what extent students are independent. In this motivacija učencev in se na tak način raje učijo angleščino [1]. article, I will discuss the tools used in each class (1st - 5th grade) and summarize how we collected evidence of learning through them and in what way and how appropriate feedback was given 2 PREGLED UPORABLJENIH ORODIJ V to students. POSAMEZNIH RAZREDIH KEYWORDS V različnih razredih smo za potek pouka uporabili različna orodja, prilagojena starosti in ciljem pouka. V učnih načrtih za Distance learning, English, interactive materials, feedback tuje jezike je zapisano, da je »Vključevanje informacijske in komunikacijske tehnologije v pouk/…/smiselno le, če ta prispeva k lažjemu razumevanju učnih vsebin, ohranjanju motivacije za 1 UVOD učenje in izboljšanju učnih rezultatov.« Prav tako je poudarjeno, Pouk na daljavo nam lahko, poleg težav, predstavlja tudi nov naj učitelj razmisli o prednostih IKT ter izbere ustrezno učno in izziv. Uporaba IKT nam lahko omogoča vključevanje programsko okolje [2]. interaktivnosti, vizualizacije, posredovanje povratnih informacij, V spodnji tabeli so, glede na namen, zapisana vsa orodja, ocenjevanje znanja, sodelovalno delo in še marsikaj drugega. ki smo jih uporabili pri pouku na daljavo od 1. do 5. razreda. »IKT vpliva na način, kako učenci, dijaki in študenti pridobivajo znanje, na izvajanje pedagoškega procesa ter delovno in učno okolje učitelja.« Uporaba IKT lahko omogoča bolj kakovostno vzgojno-izobraževalno delo, in večji učinek učenja, hkrati pa lahko poveča tudi sodelovanje med učenci. Z uporabo IKT (tako pri rednem pouku kot pri pouku na daljavo) lahko dosegamo 601 Tabela 1: Namen in uporabljena orodja IKT pri pouku na Pouk na daljavo smo izvedli preko naslednjih orodij: daljavo - Genially [6] (Učenci so s klikom na prejeto povezavo sledili posnetim navodilom. Med stranmi so se premikali Namen Orodja IKT s puščicami. Vse spodaj navedene aplikacije so bile del Organizacija učnega procesa e-pošta, Xooltime, ZOOM te povezave. Aplikacija omogoča snemanje zvoka Predstavitev vsebine Word, Genially, PPT, učitelja, izdelavo preprostih kvizov in še marsikaj ZOOM, Youtube, Quizlet, drugega). Padlet - Youtube [3] (Učenci so poslušali angleške pesmi in Objavljanje gradiv e-pošta, Xooltime navodila učitelja: ponavljanje besed, preprostih povedi). Skupinsko delo Xooltime, ZOOM, Padlet - Liveworksheets [7] (Učenci so reševali pripravljene Sporočanje in oddaja Xooltime naloge na interaktivnih učnih listih, kjer so povezovali Sprotno preverjanje znanja Liveworksheets, Quizlet, sličice z izgovorjenimi besedami in pridobili direktno LearningApps, povratno informacijo). Bookwidgets, Xooltime Tudi v 2. razredu mora biti pri pouku tujega jezika v ospredju učenčeva kratkotrajna pozornost. Izmenjavaje krajših aktivnosti smo kombinirali s konkretnim materialom (slike). 2.1 1. razred Učenci naj bi izkusili, razumeli in uporabljali jezik v medsebojni komunikaciji. Zadnje je bilo v času pouka na daljavo nemogoče, V 1. razredu se učenci z angleščino spoznajo v sklopu saj z drugošolci nismo imeli organiziranega pouka preko neobveznega izbirnega predmeta (NIP). Pouk angleščine je na videokonference. Tako kot v 1. razredu, je bila tudi tu otežena urniku dve uri tedensko. V času pouka na daljavo so učenci (in individualizacija in diferenciacija [8]. njihovi starši) navodila za delo prejemali enkrat tedensko. Komunikacija je potekala preko e-pošte. 2.3 3. razred Učenci v 1. razredu še ne morejo samostojno slediti navodilom za pouk, zato je bila velika teža pouka na daljavo V 3. razredu imajo učenci na urniku dve uri tedensko. V času predvsem na starših. Učitelji smo se trudili, da bi bil proces pouka na daljavo so učenci eno uro opravili samostojno, po pouka za starše čim manj obremenjujoč, za učence pa čim bolj pripravljenih navodilih, drugo uro pa smo se z učenci videli zanimiv in podoben tistemu v šoli. Pri pouku angleščine v šoli preko videokonference. gre namreč za proces učenja preko igre, kar je na daljavo težko Učenci v 3. razredu so že razmeroma samostojni, prav tako uresničiti. pa smo se od septembra pripravljali na pouk na daljavo in s tem Pouk na daljavo smo izvedli preko naslednjih orodij: tudi na uporabo spletne učilnice. Tako so učenci lahko bolj ali - Youtube [3] (Učenci so poslušali različne manj samostojno opravljali svoje naloge. videoposnetke. Ob angleških pesmih so se gibali in Pouk na daljavo smo izvedli preko naslednjih orodij: utrjevali besede, ob posnetkih učiteljic so ponavljali ali - Xooltime [9] (Učenci so s klikom na predmet TJA (tuji usvajali novo besedišče, občasno pa po navodilih kaj jezik angleščina) prišli do sprotnih navodil in nalog. V narisali ali pobarvali v zvezku). spletno učilnico so oddajali fotografije opravljenih - Educaplay [4] (Učenci so se preizkusili v preprostih nalog). igrah spomina, kjer so sličice povezali z izgovorjeno - Liveworksheets [7] (Učenci so reševali različne učne besedo). liste za ponovitev in dobili direktno povratno Pomembno je, da pri poučevanju tujega jezika v 1. razredu informacijo. Učitelju so rešene naloge tudi posredovali ohranjamo motivacijo, interes in veselje do učenja tujega jezika. da smo se naslednjo uro, ki je potekala v živo, o nalogah Pri izbiri vsebin, učnih metod in pristopov smo bili pozorni na in težavah pogovorili). učenčevo kratkotrajno pozornost in da so bili materiali privlačni, - Zoom [10] (Preko spletne učilnice so učenci dobili uporabni in zabavni. Tako kot pri pouku v šoli smo tudi tu pouk povezavo na videokonferenco. Enkrat tedensko smo organizirali z uporabo vizualnih podpor (fotografije) in glasbe pregledali opravljeno delo, se pogovorili o težavah, ki so (pesmi, izštevanke, gibalne pesmi). Pri pouku na daljavo je jih imeli, ponovili in utrjevali. Predelali smo novo snov bistveno manj možnosti za individualizacijo in diferenciacijo, s ter poskrbeli da je bilo med videokonferencami vedno tem pa se izgubi tudi nadzor nad posamezniki s težavami saj jim, prisotno tudi gibanje). brez direktnega vpogleda v njihovo delo, zelo težko prilagodimo - Quizlet [11] (Učenci so s pomočjo aplikacije ponavljali vsebine, metode in oblike dela [5]. in utrjevali besedišče). 2.2 2. razred 2.4 4. razred V 2. razredu imajo učenci na urniku dve uri pouka angleščine na V 4. razredu sta na urniku dve uri tedensko. Tudi v času pouka teden. Navodila za delo smo jim, tako kot v prvem razredu, na daljavo so bili učenci aktivni dve šolski uri na teden. Prvo uro posredovali preko e-pošte. smo skupaj spoznavali novo snov, drugo uro pa so samostojno Ker so učenci v 2. razredu že nekoliko bolj samostojni ali v manjših skupinah utrjevali znanje (s pomočjo učbenika in (znajo brati navodila), smo se odločili za nekoliko drugačen DZ ter drugih orodij). Prva ura v tednu je v celoti potekala preko pristop, saj smo želeli (vsaj nekaterim) učencem omogočiti, da v videokonference, k drugi uri pa so se učenci priključili po čim večji meri pouku na daljavo sledijo samostojno, brez nujne potrebi. pomoči s strani staršev. 602 Učenci v četrtem razredu so bili že zelo samostojni. Komunikacija z njimi je prav tako v celoti potekala preko spletne Primerjava pouka angleščine na daljavo učilnice Xooltime. od 1. do 5. razreda 6 Pouk na daljavo smo izvedli preko naslednjih orodij: - Xooltime [9] (Učenci so samostojno spremljali navodila 4 in obvestila. Prav tako so v sklopu spletne učilnice 2 reševali preproste kvize in oddajali opravljene naloge). 0 - Učbeniška e-gradiva (My Sails 1) [12] (Učenci so s 1. razred 2. razred 3. razred 4. razred 5. razred pomočjo e-gradiv poslušali posnetke besedil iz Ure ZOOM-a tedensko učbenika). Število uporabljenih orodij - Bookwidgets [13] (Učenci so imeli (v sklopu učbeniških Pričakovana samostojnost e-gradiv) dostop do dodatnih nalog in testov. Reševali so Slika 1: Kako je potekal pouk različne interaktivne naloge za ponovitev in utrjevanje, test ob koncu vsake predelane enote pa so poslali 3 UČNI NAČRTI ZA TUJI JEZIK IN IKT učitelju, ki je podal povratno informacijo). - Zoom [10] (Z učenci smo prvo uro predelali novo snov. Učni načrt za vsako obdobje posebej priporoča katera IKT Način dela smo poskušali čimbolj približati situaciji v znanja naj bi dosegli učenci. Poleg pridobivanja znanja in šoli. Z učenci smo uporabljali »sobe« za delo po doseganja ciljev tujega jezika so učenci v času pouka na daljavo skupinah. Druga učna ura je bila namenjena usvojili tudi nekaj teh znanj. samostojnemu delu. Učenci, ki so želeli, so se na začetku ure priključili videokonferenci. Razdelili so se v »sobe« in si med seboj pomagali, v primeru vprašanj pa so se 3.1 Neobvezni izbirni predmet v 1. razredu obrnili na učitelja). Učni načrt za NIP v 1. razredu priporoča učenje varne uporabe V učnem načrtu za angleščino je zapisano, da je informacijske in komunikacijske tehnologije, prav tako pa »Pozornost treba posvečati govornim zmožnostim in spoznavanje medijev za učenje in sprostitev [5]. Menim, da smo dejavnostim…«, zato je bilo zelo pomembno, da smo v 4. (in tudi učencem ponudili dostop do aplikacij, ki omogočajo oboje v 5. razredu) v času pouka na daljavo vključili več (Youtube, Educaplay). videokonferenc. Tako so učenci lahko sodelovali v pogovoru in S pomočjo aplikacije Youtube smo poskrbeli za to, da smo razvijali svoje komunikacijske strategije [2]. učenem prikazali avtentične videoposnetke ter spodbujali besedno in glasovno ustvarjalnost [5]. 2.5 5. razred V 5. razredu imajo učenci na urniku tri ure tedensko, na 3.2 Tuji jezik v 2. in 3. razredu daljavo pa smo se z učenci preko videokonference srečevali V 2. in 3. razredu naj bi učenci iskali in zbirali podatke, dvakrat tedensko. komunicirali in sodelovali na daljavo v okviru jezikovne Učenci so bili že popolnoma samostojni. Komunikacija z zmožnosti ter se naučili varne rabe ter upoštevanja pravnih in njimi je v celoti potekala preko spletne učilnice Xooltime. etičnih načel uporabe IKT [8]. Zaradi načina dela, ki smo ga Pouk na daljavo smo izvedli preko naslednjih orodij: izbrali, so zgornje zmožnosti v večini razvijali le učenci 3. - Xooltime [9] (Učenci so poleg spremljanja obvestil v razreda, saj so bili učenci 2. razreda v veliki meri odvisni od spletno učilnico oddajali opravljene naloge, reševali pomoči staršev. preproste kvize in vprašalnike, ustvarjali pa so tudi S pomočjo spletnih storitev za komuniciranje (ZOOM, 3. zapiske za posamezne učne ure in spremljali sprotno razred) smo spodbujali zmožnost sporazumevanja v tujem povratno informacijo učitelja na oddane naloge.) jeziku. Razvijali smo medkulturne zmožnosti (spoznavanje - LearningApps [14] (Učenci so aplikacijo uporabljali kot kulture, običajev, navad s pomočjo videoposnetkov, 2. in 3. dodatne naloge za utrjevanje besedišča). razred) in objavljane izdelkov učencev (Xooltime, 3. razred) [8]. - Quizlet [11] (Aplikacijo so uporabljali za utrjevanje besedišča). 3.3 Angleščina (4. in 5. razred) - Padlet [15] (Učenci so se naučili samostojno objaviti Učenci 4. in 5. razreda so zmožnost uporabe IKT-ja razvijali s besedilo, ki ga je učiteljica pregledala, popravila in komunikacijo v angleščini (komentarji v spletnem okolju poslala povratno informacijo). Xooltime, ZOOM), pridobivali so gradivo o različnih temah, - Zoom [10] (Z učenci smo preko orodja uporabljali obravnavanim pri pouku (Xooltime), objavljali so svoje izdelke »sobe« za delo po skupinah in kratke ankete. S pomočjo (Xooltime, oddaja nalog, izdelava zapiskov, Padlet), svoje učbenika in delovnega zvezka smo predelali novo snov). izdelke so predstavili (nekateri učenci so za svoje predstavitve uporabili PowerPoint, posneli so glas ali ustvarili videoposnetek) S pomočjo slike 1 vidimo, kako je potekal pouk (ure [2]. ZOOM-a tedensko), število uporabljenih različnih orodij (v 1. razredu najmanj, v 5. razredu največ) in pričakovano samostojnost (glede na izbiro in število uporabljenih orodij). 603 4 DOKAZI O UČENJU IN POVRATNA videokonference (tudi za izdelke, ki so jih oddajali v spletno INFORMACIJA učilnico). Tudi v 4. in 5. razredu je bila situacija podobna tisti v 3. razredu. Dokaze o učenju smo učitelji lahko, poleg oddaje »Zbiranje dokazov omogoča učitelju vpogled v razumevanje in izdelkov, spremljali preko videokonference. S tem smo dobili učenje učencev.« Ker pouk poteka na različne načine, so tudi veliko več raznovrstnih dokazov o učenju. Glede na to je bila tudi pridobljeni dokazi o učenju različni. Razdelimo jih lahko v tri povratna informacija bistveno pogostejša (in seveda takojšnja). skupine: V danem trenutku je bila povratna informacija o sprotnem delu - dokazi, ki izhajajo iz pogovorov med poukom in opravljanju nalog konkretna in v tistem trenutku za učence - dokazi, ki izhajajo iz opazovanj uporabna. Pomanjkljivosti so se učenci zavedali takoj in jih lahko - izdelki kot dokazi [16] ustrezno odpravili. Povratna informacija je bila učencem podana V šoli in pri pouku na daljavo je za uspešno učenje zelo na različne načine: preko videokonference, s pomočjo kvizov, pomembna tudi povratna informacija. Povratna informacija kjer so učenci sami opazili svoje napake, preko komentarjev in učencu pove: vrednotenja v spletni učilnici in preko zapisov učitelja ob - do katere stopnje znanja je prišel zaključku posameznih enot. - spodbudi ga k iskanju pomanjkljivosti - ponudi mu možnost in pot za odpravljanje pomanjkljivosti 5 REZULTATI Kot učitelji moramo biti pozorni na to, kako povratno informacijo oblikujemo. Povratna informacija mora biti: 5.1 Pregled uporabljenih orodij v posameznih - pravočasna in primerno pogosta razredih - razumljiva, jasna - konkretna, specifična in uporabna Delo v vsakem razredu je bilo drugačno. Že s pogledom na to, - usmerjena v izboljšanje dosežka (izdelka) [16] kako samostojni so lahko učenci v posameznem razredu je nujno raznoliko delo. Menim, da je bila odločitev, da učencev 1. in 2. razreda ne vključimo v spletno učilnico, pravilna. Učenci 4.1 1. in 2. razred samostojno še ne znajo dostopati do nalog, staršem pa bi bilo spoznavanje z okoljem spletne učilnice dodatno breme. Želela bi V 1. razredu od učencev (in njihovih staršev) nismo zahtevali si le, da bi bila, vsaj v 2. razredu, kakšna videokonferenca, saj je dokazov o učenju. Pouk neobveznega izbirnega predmeta tudi v na daljavo, brez stika težko ali skoraj nemogoče vedeti kako šoli poteka preko igre, tako da bi dokaze o učenju najbolj učenci napredujejo (sploh pri izgovorjavi). zanesljivo zbirali z opazovanjem, kar pa je bilo na daljavo (z V ostalih razredih so se kot zelo pomembne izkazale izbranim načinom dela) nemogoče. Posledično do vrnitve v šolo videokonference, saj je govor pri tujem jeziku zelo pomemben učencem ni bila nujena nobena povratna informacija o njihovem element. Učenci so prav tako lahko svoje dileme in težave napredku. Povratna informacija torej ni bila pravočasna in naslovili direktno na učiteljico. Od 3. razreda naprej so učenci po primerno pogosta. korakih uporabljali spletno okolje Xooltime. V vseh razredih so V 2. razredu smo od učencev občasno zahtevali fotografije bili učenci seznanjeni z delom v spletni učilnici še pred poukom zapisov v zvezek (ilustracije, miselni vzorci…), saj smo menili, na daljavo. Brez tega bi bilo delo zelo oteženo. Učenci v 3. da bi z drugimi načini pridobivanja dokazov o učenju dodatno razredu so spoznali le nekaj funkcij spletne učilnice, pri oddaji obremenili tako starše kot učence. Dokaze smo torej zbirali s nalog pa so jim bili v podporo starši. V 4. in 5. razredu so učenci pomočjo izdelkov učencev. Povratna informacija ni bila nujena spoznali več funkcij, ki jih ponuja spletna učilnica (v 4. razredu direktno učencem, pač pa njihovih staršem (komunikacija je so reševali preproste kvize in ankete, v 5. razredu pa so se potekala preko e-pošte). V tem primeru je bila povratna spoznali še z ustvarjanjem zapiskov). V vsakem razredu se je tudi informacija s strani učitelja podana pravočasno (ne pa takoj po povišajo število različnih uporabljenih orodij. opravljenem delu) in primerno pogosto, usmerjena v izboljšanje izdelka, staršem pa smo zaupali, da so te informacije predali tudi 5.2 Učni načrti za tuji jezik in IKT svojim otrokom. Učenci so v vsakem razredu spoznali nekaj orodij. V vsakem 4.2 3., 4. in 5. razred razredu smo povečevali število spretnih orodij ter jih spodbujali k uporabi le teh. Učenci 4. in 5. razreda niso več le spremljali V 3. razredu smo od učencev zahtevali fotografije o opravljenem pouka preko teh orodij, pač pa so se tudi sami preizkusili v delu (zapis v zvezek, ilustracije, miselni vzorci…), prav tako pa izdelavi predstavitev, samostojni oddaji in komunikaciji z smo dokaze zbirali preko videokonferenc. Poleg zbiranja učiteljem in podobno. dokazov z izdelki smo torej dokaze zbirali tudi preko opazovanj in preko pogovorov pri pouku. Pri tem bi poudarila, da je bilo 5.3 Dokazi o učenju in povratna informacija zbiranje tovrstnih dokazov veliko težje kot pri pouku, saj v eni šolski uri na vrsto niso prišli vsi učenci. Posledično v eni šolski Izkazalo se je, da je bilo v 1. in 2. razredu bistveno premalo (ali uri ni bilo mogoče podati konkretne in jasne povratne informacije skoraj nič) zbiranja dokazov o učenju in podajanja kakovostnih vsem učencem. Situacija pa je bila bistveno boljša kot v 1. in 2. povratnih informacij. To nas je čakalo ob vrnitvi v šolo, ko pa razredu. Učenci 3. razreda so povratno informacijo dobili takoj povratna informacija (sploh pri mlajših učencih) ni več tako zelo in so svoje napake lahko sproti popravili (npr. pri izgovorjavi). uporabna. Sploh pri mlajših mora biti povratna informacija Povratna informacija učenem je bila v 3. razredu podana preko takojšnja in konkretna. 604 V 3., 4. in 5. razredu je bilo več možnosti za zbiranje %20procesu%20za%20podro%C4%8Dje%20jeziki%20(1).pdf (8. 8. dokazov (predvsem zaradi večje samostojnosti učencev in 2021). [2] Učni načrt. Program osnovna šola. 2016. Angleščina. [E-knjiga]. videokonferenc). Povratna informacija je bila v vseh razredih Ljubljana: Ministrstvo za šolstvo in šport: Zavod RS za šolstvo. Dostopno na podana bistveno bolj kvalitetno, prav tako pa je bila podana na naslovu https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna- različne načine. Učenci so bili v vsakem razredu bolj samostojni. sola/Ucni-nacrti/obvezni/UN_anglescina.pdf (8. 8. 2021). [3] Youtube. Dostopno na naslovu www.youtube.com (8. 8. 2021). [4] Educaplay. Dostopno na naslovu www.educaplay.com (8. 8. 2021). 6 ZAKLJUČEK [5] Učni načrt. Program osnovna šola. 2013. Tuji jezik v 1. razredu. Neobvezni izbirni predmet. [E-knjiga]. Ljubljana: Ministrstvo za šolstvo Pomembno je, da se zavedamo, kako samostojni so učenci v in šport: Zavod RS za šolstvo. Dostopno na naslovu https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna-sola/Ucni- določenem razredu. Glede na to prilagajamo svoje didaktične nacrti/izbirni/Neobvezni/TJ_prvi_razred_izbirni_neobvezni.pdf (8. 8. pristope in ustrezno izbiramo različna orodja. 2021). [6] Genially. Dostopno na naslovu https://genial.ly/ (8. 8. 2021). Menim, da bi v zadostni meri tudi ob vrnitvi v šolo morali [7] Liveworksheets. Dostopno na naslovu https://www.liveworksheets.com/ nadaljevati z uporabo IKT, saj s tem spodbujamo informacijsko (8. 8. 2021). pismenost učencev in jih dodatno motiviramo. Seveda pa morajo [8] Učni načrt. Program osnovna šola. 2013. Tuji jezik v 2. in 3. razredu. [E- knjiga]. Ljubljana: Ministrstvo za šolstvo in šport: Zavod RS za šolstvo. biti vse dejavnosti, tako na daljavo, kot v šoli, osmišljene in Dostopno na naslovu slediti ciljem ter namenom učenja. https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna-sola/Ucni- nacrti/obvezni/UN_TJ_2._in_3._razred_OS.pdf (8. 8. 2021). Pozabiti ne smemo niti na kvalitetno povratno informacijo, [9] Xooltime. Dostopno na naslovu https://xooltime.com/ (8. 8. 2021). kar se je, vsaj v nekaterih razredih, izkazalo kot problematično. [10] Zoom. Dostopno na naslovu https://zoom.us/ (8. 8. 2021). [11] Quizlet. Dostopno na naslovu https://quizlet.com/ (8. 8. 2021). V prihodnje bi bilo potrebno konkretno razmisliti o drugačnem [12] E-gradiva My Sails 1. Dostopno na naslovu http://e- načinu dela z najmlajšimi učenci in pretehtati pomembnost gradiva.com/dokumenti/MS1/index.html (8. 8. 2021). takojšnje povratne informacije zanje. [13] Bookwidgets. Dostopno na naslovu https://www.bookwidgets.com/ (8. 8. 2021). [14] LearningApps. Dostopno na naslovu https://learningapps.org/ (8. 8. 2021). LITERATURA IN VIRI [15] Padlet. Dostopno na naslovu https://padlet.com/ (8. 8. 2021). [16] Holcar Brunauer, A., Bizjak, C., Cotič Pajntar, J. idr. 2017. Formativno [1] Urbančič, M., Bevčič, M., Dagarin-Fojkar, M. idr. b.d. Strokovne podlage spremljanje v podporo učenju. Ljubljana: Zavod RS za šolstvo. za didaktično uporabo IKT v izobraževalnem procesu za področje jezikov. Dostopno na naslovu file:///C:/Users/Uporabnik/Desktop/Strokovne%20podlage%20za%20did akti%C4%8Dno%20uporabo%20IKT%20v%20izobra%C5%BEevalnem 605 Virtualna izvedba študije primera na Fakulteti za organizacijske vede Univerze v Mariboru Virtual implementation of a case study at the Faculty of Organizational Sciences University of Maribor Marko Urh Fakulteta za organizacijske vede Univerza v Mariboru Kranj, Slovenija marko.urh@um.si Eva Jereb Fakulteta za organizacijske vede Univerza v Mariboru Kranj, Slovenija eva.jereb@um.si POVZETEK method has also changed. A case study is a method where high school or college students are looking for solutions to a Na Fakulteti za organizacijske vede Univerze v Mariboru se challenge. The challenge is given by the company participating uporablja izobraževalna metoda študija primera izvedbi in the event. The challenges are most often in the field of izobraževalnih dogodkov, ter pri nekaterih predavanjih in vajah marketing, sales, work organization, informatics, tourism and v pedagoškem procesu. Zaradi epidemije, ki se je začela v others. At the beginning of the article, problem-based learning mesecu marcu 2020, se je spremenila tudi izvedba dogodka and the educational case study method are explained. The študije primera. Študija primera je metoda, kjer udeleženci article presents the positive elements and advantages of this iščejo rešitve za nek izziv. Izziv poda podjetje ali organizacija, method. In the continuation of the article, the organizational ki sodeluje pri dogodku. Izzivi so najpogosteje s področja steps necessary for the implementation of a virtual event are marketinga, prodaje, organizacije dela, informatike, turizma in explained. However, the requirements for performing a virtual drugo. V začetku prispevka je pojasnjeno problemsko učenje in event are different from a classic event. Experiences and izobraževalna metoda študije primera. V prispevku so proposals for the implementation of the virtual method of case predstavljeni pozitivni elementi in prednosti omenjene metode. study are presented. With this article, we want to help everyone V nadaljevanju prispevka so pojasnjeni organizacijski koraki who would like to use a case study in the educational process, potrebni za izvedbo virtualnega dogodka. Zahteve za izvedbo especially in organizing a virtual event. virtualnega dogodka se razlikujejo od klasične dogodka študije primera. Predstavljene so izkušnje in predlogi za izvedbo KEYWORDS virtualne metode študije primera. S prispevkom želimo pomagati vsem, ki bi želeli uporabljati študijo primera v E-learning, problem-based learning, case study, virtual event izobraževalnem procesu, predvsem pri organizaciji virtualnega dogodka. 1 UVOD KLJUČNE BESEDE Zasebno in poklicno življenje se je marca 2020 drastično E-izobraževanje, problemsko učenje, študija primera, virtualni spremenilo. V tem času je bila namreč v Sloveniji razglašena dogodek epidemija nalezljive bolezni SARS-CoV-2 (COVID-19). Prizadeta pa ni bila le Slovenija, temveč praktično ves svet in ABSTRACT večina poklicnih področij. Izobraževanje pa je bilo eno izmed The Faculty of Organizational Sciences of the University of področij, kjer so posledice čutili prav vsi udeleženci. Maribor uses the educational method of case studies at Organizacija United Nations [1] navaja, da je po svetu kriza educational events, as well as in some lectures and exercises in prizadela 1,58 milijarde otrok in mladine (94 %) in to od the pedagogical process. Due to the pandemic that started in predšolskih otrok do študentov v visokošolskem izobraževanju March 2020, the implementation of the educational case study in to v 200 državah sveta. Evropska komisija [2] v svojem poročilu ugotavlja, da 95 % anketirancev meni, da kriza pomeni pozitivno spremembo pri rabi informacijske tehnologije v Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or izobraževanju. Poleg tega omenja, da pred krizo skoraj 60 % distributed for profit or commercial advantage and that copies bear this notice and anketirancev ni uporabljalo učenja preko spleta oz. na daljavo. the full citation on the first page. Copyrights for third-party components of this Poročilo Evropske komisije tudi omenja, da 60 % vprašanih work must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia meni, da so zaradi povečane uporabe informacijske tehnologije © 2021 Copyright held by the owner/author(s). med krizo izboljšali svoje sposobnosti njene uporabe in da 50 % vprašanih želi še nadgraditi svoje znanje s področja 606 informacijske tehnologije. Številne izobraževalne organizacije Spodbujanje samostojnega učenje - to je pristop, ki je so se zaradi posledic krize soočile s problemi kot so osredotočen na študente. Učenje je bazirano na podlagi pomanjkljiva informacijska infrastruktura, nezadostne povezave podanega problem, ki študente spodbudi, da prevzamejo do interneta, pomanjkljivo znanje računalništva in informatike odgovornost za reševanje problema in s tem tudi za samostojno učiteljev in profesorjev, slabo ali sploh nič implementirani učenje. S tem so prisiljeni v raziskovanje in ustvarjalnost, hkrati sistemi za podporo učenja (LMS), videokonferenčni sistemi, pa razvijajo veščine, ki jim bodo koristile v odrasli dobi. neustrezna delovna okolja in drugo. Visoka stopnja angažiranosti - namesto pasivnega spremljanja Na Fakulteti za organizacijske vede Univerze v Mariboru (FOV predavanj, poslušanja in zapisovanja so študenti primorani biti UM) smo se tako kot tudi večina izobraževalnih organizacij aktivni. S tem je njihova stopnja učenja bolj intenzivna, morali prilagoditi na spremenjene izobraževalne procese. osredotočenost večja in bistveno več je kritičnega razmišljanja. Omejitev stikov s študenti, ohranjanje varnostne razdalje, delo Razvijanje uporabnih veščin - udeleženci takšnega načina od doma, povečan obseg dela z informacijsko tehnologijo so izobraževanja razvijajo veščine, ki so širše uporabne. Veščine bili le nekateri izzivi. Za mnoge so bile spremembe zelo niso omejene samo na šolsko okolje temveč je bistvo, da se jih naporne in z delovnega stališča zahtevne. Spremenjeni so bili uporabi v resničnih problemskih situacijah, katerih značilnosti tudi drugi, že utečeni procesi in dogodki. Eden izmed so skupinsko reševanje problemov, prevzemanje odgovornosti dogodkov, ki se že vrsto let organizira in izvaja na FOV UM je in drugo. dogodek študija primera. Študija primera je ena izmed izpeljank Krepitev notranje motivacije - rešitev težkih izobraževalnih problemskega učenja, kjer imajo glavno vlogo študenti, ki s skupinskih problemov daje veliko zadovoljstvo. S tem se veča svojimi idejami rešujejo izziv, ki ga poda podjetje ali samospoštovanje in osebno zadovoljstvo. organizacija, ki sodeluje pri dogodku. Zaradi spremenjenih Ekipno delo - problemske situacije so strukturirane tako, da so okoliščin so se dogodki študije primera morali organizirati in časovno in težavnostno prezahtevne za posameznika. S tem so izvesti v virtualni obliki. Tako izvedeni dogodki so zahtevali študenti prisiljeni v ekipno delo, kjer vsak prevzame določeno širokopasovni dostop do svetovnega spleta, videokonferenčne vlogo v ekipi. S tem se razvija sposobnost sodelovanja, sisteme (MS Teams), ustrezno informacijsko podporo in drugo. komuniciranja, poslušanja, delanja kompromisov, pogajanja in Zaradi lažjega razumevanja celotnega prispevka pa so v drugo. nadaljevanju predstavljena področja problemskega učenja, Na Sliki 1 je prikazana primerjava med tradicionalnim študija primera in virtualna izvedba študija primera, ki se izvaja (klasičnim) učenjem in problemskim učenjem. Pri na FOV UM. tradicionalnem učenju ima študent pasivno vlogo, kjer je deležen podajanja neke snovi preko predavanj, ki jih izvede profesor. Sledi študij in memoriranje snovi. Omenjenim 2 PROBLEMSKO UČENJE korakom sledi preverjanje osvojenega znanja oz. odgovarjanje Ljudje se razlikujemo glede na številne značilnosti, navade, na postavljena pisna ali ustna vprašanja. Pri problemskem običaje in druge zadeve. Tako je tudi na področju učenju pa ima študent veliko bolj aktivno vlogo. Profesor ima izobraževanja. Nekdo se lažje uči zjutraj, nekdo zvečer. vlogo vodnika ali usmerjevalca. V prvem koraku se študentom Obstajajo razlike med učnimi navadami, stili in strategijami ali skupini predstavi problem. Za reševanje je namenjen uspešnega učenja. Številni se najlažje naučijo ali razumejo neko določen čas, ki naj bi bil zadosti dolg, kar je odvisno od učno snov s pomočjo primerov ali z reševanjem dejanskega zahtevnosti podanega problema. Sledi iskanje rešitve. V fazi problema. Za problemsko učenje je značilno, da ima iskanja rešitev mora študent ali skupina preučiti določeno značilnosti, ki so podobne naravnemu učenju, ki izhaja iz literaturo, brez katere bi težko ali nemogoče našli rešitev. Sledi reševanja problema, ki ga ima posameznik ali skupina. iskanje rešitev. Rešitev je za razliko od klasičnega načina Problemsko učenje lahko v angleški literaturi najpogosteje izobraževanja lahko več. Takšen način dela, izobraževanja in zasledimo pod kratico PBL (problem-based learning). Na razmišljanja je podobno naravnemu procesu reševanja problemsko učenje lahko gledamo kot na zbirko didaktičnih problemov. Študent nima občutka, da se prisiljeno uči oz. elementov, kot so [3]: pregleduje gradivo, kar študentu ali skupini daje občutek • organiziranje problemskih situacij, kontrole nad dogajanjem. • formiranje problemov, • zagotavljanje pogojev za delo, • zagotavljanje primerne pomoči in • utrjevanje problemskih znanj. S takšnim načinom reševanja problemov se srečujemo že pred samim formalnim izobraževanjem, zato lahko problemsko učenje označimo kot pogonsko silo za učenje [4]. Zato ni presenetljivo, da je pedagoška metoda problemskega učenja vedno bolj uporabljena v izobraževalnih procesih. Metoda problemskega učenja je ena izmed najbolj inovativnih pedagoških metod, ki je bila kadarkoli implementirana v izobraževanje [5]. Edinstvenost problemskega učenja ima številne prednosti in pozitivne učinke na študente, ki jih pri drugih metodah manjka ali pa jih je bistveno premalo. Nekatere Slika 1: Primerjava klasičnega in problemskega učenja [7]. izmed teh prednosti so [6]: 607 Problemsko učenje se nenehno razvija in z razširjenostjo sledeče: povezovanje z gospodarstvom, večanje ugleda informacijske tehnologije še pridobiva na veljavi. Poleg tega se fakultete, krepitev znanja o organizaciji dogodkov, prednosti pri pojavljajo nove različice in oblike problemskega učenja in ena akreditaciji študijskih programov in drugo. izmed alternativ je tudi študija primera. V okviru preteklih dogodkov so s fakulteto sodelovala številna ugledna podjetja in organizacije kot so (navedeno po abecednem vrstnem redu): Autocommerce d. o. o., B&B 3 ŠTUDIJA PRIMERA izobraževanje in usposabljanje d. o. o., DA Automobiles, DHL Za študijo primera (angl. case study) velja, da je ena izmed Global Forwarding Logistika d. o. o., Društvo DOVES-FEE izpeljank problemskega učenja [8]. Značilnost metode študije Slovenia (Program Ekošola), Elan d. o. o., Erste Card d. o. o. primera je, da so glavni akterji dijaki ali študenti, ki iščejo (Diners Club), Fraport Aviation Academy, Fraport Slovenija d. rešitve za postavljen problem. Trajanje študije primera je lahko o. o., GA+kuhinje (Aparati d. o. o.), GS1 Slovenija, Iskratel d. različno dolgo. Najbolj znane obliko se enodnevne, o. o., Janus Trade d.o.o. (Samsung), Kompas Magistrat d. o. o., nekajdnevne ali celo več mesečne. Rešitev problema mora biti Kovačnica Kranj – MOK, Mercator d. d., Styria digital najdena v danih časovnih omejitvah, kar postavlja udeležence marketplaces d. o. o. (Bolha.com), Valtex & Co. d. o. o. in pod določen pritisk in stres, kar je značilno tudi za delo v Zavod za turizem in kulturo Kranj (ZTKK). realnem okolju. Druge značilnosti študije primera so ekipno V okviru dogodkov študije primera FOV UM organizira tri delo, kjer vsak član prevzame določeno nalogo. Študije primere različne dogodke in sicer: naj bodo zasnovane tako, da lahko udeleženci s pomočjo Decembrska šola in tekmovanje v študiji primera za študente. pridobljenega znanja, podatkov in informacij predstavijo čim Dogodek je namenjen študentom FOV UM. Namen dogodka je, več svojih idej [9]. Študije primera se lahko deli glede na vrsto da študenti poglobljeno spoznajo kaj je študija primera. V in različne kriterije kot so [8]: sklopu izobraževanja spoznajo kako naj predstavijo svojo • narava posameznega primera (posameznik, družba, rešitev, kakšne so zakonitosti dobrih predstavitev, kako organizacija, postopkov, kulturnih aktivnosti, …); oblikovati in pripraviti numerične podatke, kako iskati podatke • število primerov, ki jih proučujemo (en primer ali več po spletu, kako sodelovati v ekipi in drugo. Drugi del dogodka primerov); je namenjen tekmovanju oz. predstavitvi študentkih rešitev. • sestavljena ali enostavna analiza: enostavna enota Prvo in drugo uvrščena ekipa se kot predstavnici fakultete (majhno podjetje) in sestavljena enota (večja udeležita mednarodnega tekmovanja v študiji primera, ki poteka organizacija, veliko podjetje, mesto, …); v okviru Mednarodne konference o razvoju organizacijskih • vrsta empiričnega gradiva: primarno (gradivo dobimo znanosti. Kot je razvidno iz imena dogodka se dogajanje izvaja le z opazovanjem ali spraševanjem), sekundarno v mesecu decembru. (gradivo so dokumenti) in kombinirano. Mednarodno tekmovanje v študiji primera za študente, ki Študije primera lahko delimo tudi glede na področja oz. poteka v okviru Mednarodne konference o razvoju tematike, kjer se proučujejo [10]: organizacijskih znanosti. Dogodek poteka najpogosteje konec • osebe - osredotočenost na določenega posameznika. meseca marca. Poleg najboljših dveh ekip FOV UM se • skupine - osredotočenost na določeno skupino ljudi. tekmovanja udeležijo tudi ekipe iz drugih fakultet, ki najpogosteje prihajajo iz držav bližnje okolice (Hrvaška, Srbija, • lokacije - osredotočenost na določen kraj. Avstrija, …). Tekmovanje se izvaja v angleškem jeziku in je • organizacije ali podjetja - osredotočenost na podjetje bistveno bolj zahtevno tekmovanje v mesecu decembru. ali organizacijo in njihov problem Študija primera - Izobraževanje in tekmovanje za dijake. • dogodki - osredotočenost na dogodek, bodisi kulturni Omenjen dogodek je najpogosteje organiziran v mesecu ali družbeni in njegov vpliv. januarju, saj imajo takrat dijaki največ prostega časa. V nadaljevanju je predstavljena študija primera, ki se jo izvaja Najpogosteje se dogodka udeležijo ekipe in njihovi na Fakulteti za organizacijske vede Univerze v Mariboru ter spremljevalci iz srednjih šol gorenjske regije, Ljubljane in njene njena virtualna izvedba. okolice. V okviru izobraževanja dobijo dijaki podobna znanja kot študenti na decembrskem izobraževanju. Izobraževanje in 4 ŠTUDIJA PRIMERA NA FAKULTETI ZA tekmovanje poteka v slovenskem jeziku. Težavnost izziva ORGANIZACIJSKE VEDE UNIVERZE V namenjenega reševanju pa je prilagojena dijakom in je v večini MARIBORU primerov lažja kot pri študentih. Sodelovanje pri dogodku študija primera ima številne prednosti tako za udeležence (dijake ali študente), fakulteto in podjetje oz. 5 VIRTUALNA IZVEDBA ŠTUDIJA organizacijo, ki sodeluje na dogodku. Prednosti, ki jih prinaša PRIMERA študija primera za študente so: razvijanje sposobnosti dela v Virtualna izvedba študije primera je zahtevala drugačno ekipi, omogočen je stik s potencialnimi delodajalci, razvoj organizacijo in izvedbo kot običajno. V glavnem se študija specifičnih kompetenc, razvijanje analitičnega in kritičnega primera deli na dva glavna dela in sicer na izobraževanje razmišljanja, mreženje in drugo. Prednosti za partnerko podjetje udeležencev (študentov in dijakov) in samo tekmovanje. ali organizacijo, ki sodeluje v okviru nekega dogodka študije Izobraževanje se organizira za dva dogodka in sicer za primera so: nabor najboljših kadrov, promocija podjetja, Decembrsko šolo in tekmovanje v študiji primera za študente, blagovne znamke ali storitve/izdelka, pridobivanje novih rešitev ter za dogodek Študija primera - Izobraževanje in tekmovanje ali idej za nek problem in drugo. Za fakulteto pa so prednosti za dijake. Tekmovanje pa je izvedeno za vse tri dogodke. 608 Za potrebe organizacije dogodka je bila oblikovana delovna Po uvodnem nagovoru vseh prisotnih v kanalu MS Team-sov se skupina in širši organizacijski odbor na FOV UM. Poleg tega začnejo virtualne predstavitve. Vsaka ekipa ima na voljo pri organizaciji dogodka sodelujejo tudi prodekan/ica za določen čas za predstavitev. Študentske predstavitve trajajo do študentska vprašanja, prodekanica za izobraževalno dejavnost, 15 minut, dijaške pa 10 minut. Po predstavitvi lahko predstavniki Kariernega centra in drugi. Večina usklajevanj in ocenjevalna komisija postavlja vprašanja za pojasnitev organizacije pri virtualnem dogodku poteka s pomočjo morebitnih nejasnosti. Ocenjevalna komisija je sestavljena iz informacijsko-komunikacijske tehnologije. Tu lahko enega ali dveh predstavnikov podjetja ali organizacije, izpostavimo elektronsko pošto, videokonferenčne sisteme (MS predstavnika FOV UM in v nekaterih primerih tudi iz Teams) in telefone. Pred samo izvedbo dogodka se omenjeni predstavnikov študentov. Omenjena komisija ima za člani delovne skupine in organizacijskega odbora uskladijo komunikacijo na voljo rezerviran kanal v okviru MS Team-sov, glede same izvedbe, datumov in časovnice virtualnega ki je viden samo njim. Za operativno usklajevanje pa je dogodka, priprave promocije, usklajevanj podpornih služb komisija dosegljiva tudi preko elektronske pošte in mobilnih (npr.: Center za informatiko in informacijske tehnologije) in telefonov. Komisija ocenjuje rešitve ekip po štirih drugih nujnih zadev. Veliko dela in usklajevanja zahteva karakteristikah, ki so: oblikovanje izziva, ki poteka s partnerskim podjetjem ali • izvedljivost predlagane rešitve, organizacijo. Dogaja se, da nekatera podjetja nimajo istih • samo razumevanje problema, videokonferenčnih sistemov in da je potrebno veliko časovnega • struktura in kakovost predstavitve in usklajevanja. Oblikovanje izziva za udeležence poteka skupaj s • odgovori na zastavljena vprašanja komisije. podjetjem ali organizacijo najpogosteje preko Udeleženci najpogosteje pripravijo svoje predstavitve v videokonferenčnega sistema (MS Teams). Za takšno delo se programu MS PowerPoint, ki jih nato delijo s pomočjo MS oblikuje posebna soba v okviru MS Teams-ov, ki mora biti Teams-ov. Ni redko, da pri tem nastanejo težave. Vsi člani strogo varovana, saj bi bilo skrajno neprijetno, da bi katera ekipe nimajo istega znanja in veščin s področja informatike, ki izmed ekip predčasno prišla do izziva. S tem bi bilo tekmovanje jih zahtevajo videokonferenčni sistemi. V takšnih primerih je nepošteno in neetično. potrebna pomoč s strani tehničnega osebja FOV UM. Druga Vzporedno z organizacijo izobraževanja poteka tudi zbiranje pogosta težava, ki nastane pri prezentaciji rešitev je povezana s prijav ekip. Število ekip, ki sodelujejo na izobraževanju in tehničnem delovanjem oz. povezave do svetovnega spleta tekmovanju je najpogosteje omenjeno na osem. Takšno število posameznega udeleženca. Udeleženci imajo različne ponudnike ekip še omogoča časovno vzdržnost tekmovanja. Večje števili spletnih storitev in različno obremenjene spletne povezave. ekip pa bi tekmovanje naredilo preveč dolgo in s tem tudi Težav, ki so s tem povezane so krajše ali daljše prekinitve dolgočasno za vse udeležence. Po oblikovanju in uskladitvi signala in s tem tudi same prezentacije. Za čim bolj nemoten izziva sledi določitev tematik, ki bodo na izobraževanju. Teme potek virtualnega dogodka je s strani delovne skupine FOV UM predavanj so najpogosteje s področji komunikacijskih veščin, organiziran test oz. preizkus, ki je namenjen posamezni ekipi. S timskega dela, oblikovanja zanimivih predstavitev in drugo. tem se izognemo številnim težavam in tehničnim zapletom, ki Predavanja izvedejo profesorji na FOV UM in zunanji bi se lahko utegnile pojaviti med samim tekmovanjem. sodelavci. Na samem izobraževanju pa se predstavijo tudi Po zaključku tekmovanja se ocenjevalna komisija umakne iz pravila tekmovanja in izžreba vrstni red predstavitev ekip. kanala, kjer je potekalo tekmovanje, ter se priključi kanalu v Izobraževanje poteka preko MS Team-sov v okviru časovnice, MS Team-sih, ki je namenjeno izključno komisiji in ožjemu ki je bila predhodno posredovana ekipam. V okviru organizacijskemu odboru. Ocenjevalna komisija se tako lahko v izobraževanj lahko člani ekip postavljajo vprašanja miru posvetuje o dosežkih posameznih ekip in drugih zadevah, predavateljem. Na koncu vseh predavanj sledi predstavitev ki se upoštevajo pri določitev vrstnega reda ekip. Po določenem izziva, ki ga predstavi predstavnik podjetja. Tudi tu lahko času se ocenjevalna komisija zopet pridruži skupinskemu udeleženci postavljajo vprašanja, kjer se razjasnijo še zadnje tekmovalnemu kanalu v MS Teams-ih. Sledi razglasitev treh malenkosti povezane z izzivom. Pri virtualnem dogodku je zmagovalnih ekip, ki jih najgosteje napove predstavnik podjetja opaziti, da je vprašanj veliko več kot pri klasični izvedi ali organizacije, ki je partner tekmovanja. Vsaki ekipi so dogodka. Razlog lahko iščemo v tem, da so udeleženci manj predstavljeni tudi nekateri pozitivni in negativni elementi iz javno izpostavljeni kot v razredu ali predavalnici. njihove predstavitve. To daje celotnemu tekmovanju tudi Po predstavitvi izziva imajo ekipe čas za iskanje rešitev. Člani pedagoško komponento in priložnosti za učenje. Sledi nagovor posamezne ekipe si razdelijo delo in vsak izmed njih prevzame ob zaključku dogodka in povabilo za ponovno udeležbo določeno vlogo v ekipi. Večino časa so v stiku s pomočjo prihodnje leto. informacijsko-komunikacijske tehnologije, kjer prevladujejo Pri promociji in dokumentiranju celotnega dogodka je potrebno elektronska pošta, videokonferenčni sistemi (MS Teams, Zoom, upoštevati tudi določena pravila in zakonske omejitve, ki se Skype in drugo), telefoni in drugo. Usklajevanje rešitve je tako najpogosteje navezujejo na Splošno uredbo o varstvu podatkov bistveno bolj zahtevno kot pri klasičnem sodelovanju v neki - GDPR [11]. Uredba nalaga določena pravila, ki se navezujejo ekipi. Virtualno delo ima svoje pomanjkljivosti. Udeleženci na fotografiranje, snemanje, objave in delo s podatki nimajo enakih pogojev za delo, obstajajo in pojavljaj se udeležencev in drugo. tehnične motnje ter motnje v samem delovnem okolju in drugo. Dan tekmovanje in vrstni red predstavitev ekip je bil predhodno določen. Pred samim tekmovanjem se v okviru MS Teams-ov 6 ZAKLJUČEK ponovno predstavi izziv, kajti na tekmovanju so prisotni tudi V prispevku je predstavljena organizacija in izvedba drugi udeleženci, kot so gledalci ali spremljevalci (pri dijakih). virtualnega dogodka študije primera na FOV UM. Vpliv 609 epidemije je spremenil velik del izobraževalnih procesov in LITERATURA IN VIRI dogodek študije primera pri tem ni bil izjema. Za potrebe [1] United Nations. (2020). Policy Brief: Education during COVID-19 and organizacije in izvedbe je bilo potrebno spremeniti številne beyond. Pridobljeno 17. 3. 2021 na postopke in procese pri dogodku študije primera. Posledično se https://www.un.org/development/desa/dspd/wp- content/uploads/sites/22/2020/08/sg_policy_brief_covid- je dogodek začel izvajati v virtualni obliki. Najbolj pomembni 19_and_education_august_2020.pdf elementi za izvedbo dogodka so videokonferenčni sistemi (MS [2] European Commission. (2021). Digital Education Action Plan (2021- 2027). Pridobljeno 20. 3. 2021 na Teams), širokopasovne spletne povezave in druge https://ec.europa.eu/education/education-in-the-eu/digital-education- informacijsko-komunikacijske tehnologije. Zaradi sprememb in action-plan_en povečane uporabe novih tehnologij so se pojavile številne [3] Strmčnik, F. (1992). Problemski pouk v teoriji in praksi. Radovljica, Didakta. težave, tako na strani organizatorjev dogodka kot tudi na strani [4] Smith, C. J. (2012). Improving the school – to – university transition: udeležencev (študenti in dijaki). using a problem – based approach to teach practical skills whilst simultaneously developin studentś independent study skills. Chemistry Za zmanjševanje tveganj in zmanjševanje tehničnih težav pri education research and practice, 13(3), 490-499. organizaciji virtualnih dogodkov predlagamo aktivno [5] Hung, W., Jonassen, D.H. & Liu, R. (2021). Problem-based learning. spremljanje priporočil za izvajanje izobraževanj v spremenjenih Pridobljeno dne 5. 8. 2021 na https://www.academia.edu/ [6] The Hun School of Princeton. (2020). WHAT IS PROBLEM-BASED razmerah (npr. epidemija). Zanimivo bo iskati tudi nove oblike LEARNING? Pridobljeno dne 10. 8. 2020 izobraževanj. V prihodnosti lahko pričakujemo pojav nahttps://www.hunschool.org/resources/problem-based-learning [7] Eltitude Pte. (b.d.). Our Problem Based Learning Programme. hibridnega izobraževanja, ki bo vsaj malo nadoknadil potrebno Pridobljeno 6. 1. 2021 na https://www.eltitudesg.com/problem-based- po socialnem stiku med študenti, ki je bil v času epidemije learning-programme [8] Mesec, B. in Lamovec, T. (1998). Uvod v kvalitativno raziskovanje v bistveno zmanjšan. Nikakor ne smemo zanemariti vpliv socialnem delu. URN:NBN:SI:DOC-C11L6WB5, Pridobljeno dne 2. 5. tehnologije, ki bo v prihodnosti vedno večji. Zato se priporoča 2019 na http://www.dlib.si sledenje trendom na področju informacijsko-komunikacijskih [9] Tellis, W. M. (1997). Application of a Case Study Methodology . The Qualitative Report, 3(3), 1-19. Pridobljeno 13. 5. 2020 na tehnologiji na področju e-izobraževanju. Dodatno priporočamo http://nsuworks.nova.edu/tqr/vol3/iss3/1 pripravo scenarijev za hibridno in popolno virtualno izvedbo [10] Universal Class. (2021). How to Write Case Studies. Pridobljeno 20. 4. 2020 na https://www.universalclass.com/i/course/how-to-write-case- dogodkov. S tem zmanjšamo verjetnost in potrebo po hitrem studies.htm prilagajanju, ki so posledica negotovih razmer. [11] UREDBA (EU) 2016/679 EVROPSKEGA PARLAMENTA IN SVETA Spremenjene razmere v izobraževanju bodo prinesle tudi (2016). UREDBA (EU) 2016/679 EVROPSKEGA PARLAMENTA IN SVETA z dne 27. aprila 2016 o varstvu posameznikov pri obdelavi hitrejše premike na področju digitalizacije izobraževanja. Pri osebnih podatkov in o prostem pretoku takih podatkov ter o razveljavitvi tem velja upoštevati določene smernice in trende. V prihodnosti Direktive 95/46/ES (Splošna uredba o varstvu podatkov). Pridobljeno na 10.1.2021 https://eur lahko pričakujemo številne poskuse v smeri digitalizacije lex.europa.eu/legalcontent/SL/TXT/PDF/?uri=CELEX:32016R0679&fro izobraževanja in nadaljevanje digitalizacije obstoječih m=SL procesov. S prispevkom smo želeli deliti znanje in izkušnje s področja študije primera, predvsem njene virtualne izvedbe. Deljenje izkušenj lahko koristi drugim izobraževalnim organizacijam pri vpeljavi ali dodatnem razvoju omenjene pedagoške metode ali drugih metod v izobraževalni proces. Prispevek lahko olajša ali prepreči težave ali napake, ki se lahko pojavijo pri virtualni izvedbi študije primera. 610 Uporaba sodobnih tehnologij in metod strojnega učenja v mladinskem nogometu Use of modern technologies and machine-learning methods in youth football Rok Vrban Seamus Kelly Mirjana Kljajić Borštnar Univerza v Mariboru University College Dublin Univerza v Mariboru Fakulteta za organizacijske vede Dublin, Irska Fakulteta za organizacijske vede Kranj, Slovenija seamus.kelly@ucd.ie Kranj, Slovenija rok.vrban@student.um.si mirjana.kljajic@um.si POVZETEK digital technologies and artificial intelligence, more clubs are able to perform detailed analysis of their youth development Razvoj nadarjenih posameznikov v nogometnih šolah in programme which gives them a significant competitive akademijah je strukturiran proces, ki predstavlja pomemben advantage in a football market. Development of technology has temelj tako na športnem kot na finančnem področju v also improved the injury risk assessment which plays a cruicial nogometnem klubu. Z vse večjimi finančnimi vložki v nogomet role in every club. In the article, we focus on good practices of je proces prepoznavanja ključnih atributov mladincev pri technology use and modern statistical approaches in talent prehodu v članske selekcije vse pomembnejši, hkrati pa tak development process. We closely examine key attributes in talent proces predstavlja izziv in potrebo po spremembah pri mnogih development process and risk assessment through the use of GPS nogometnih klubih. Z razvojem tehnologije in umetne devices and data-mining process. The purpose of this paper is to inteligence se finančno zmogljivejši klubi vse pogosteje odločajo review the literature in the field of linking technology and youth za sodobnejše pristope prepoznavanja talentov že v zelo zgodnjih football, which is the first step in planning and conducting the najstniških letih, kar jim ponuja konkurenčno prednost na trgu doctoral research. nogometnih igralcev. Tehnologija je bistveno pripomogla tudi pri ocenjevanju tveganja poškodb nogometašev, kar predstavlja KEYWORDS zelo pomemben vidik v nogometnem klubu. V prispevku bomo pregledali prakse uporabe tehnologije in sodobnih pristopov Talent development, Data mining, Digital technologies, GPS uporabe podatkovne analitike za namen prepoznavanja ključnih atributov nadarjenih mladincev. Natančneje se bomo osredotočili 1 UVOD na primere prepoznavanja ključnih atributov preko uporabe naprav za sledenje gibanja igralcev (GPS) ter razvoja modelov Evropsko nogometno okolje postaja vse bolj zanimivo za preko uporabe podatkovnega rudarjenja z namenom investitorje iz bogatih držav Azije, Bližnjega vzhoda in Rusije. prepoznavanja poškodb pri mladih nogometaših. Namen Najatraktivnejši nogometni klubi za tuje investicije so klubi iz prispevka je pregled literature na področju povezovanja peterice največji lig na svetu, in sicer iz angleške, francoske, tehnologije in mladinskega nogometa, ki predstavlja prvi korak italijanske, nemške in španske lige [1]. To je posledica števila pri načrtovanju in izvedbi doktorske raziskave. sledilcev in navijačev po celem svetu [2]. Finančne zmožnosti velikih klubov jim omogočajo nakupe v že uveljavljene igralce, KLJUČNE BESEDE medtem ko klubi z omejenimi finančnimi zmožnostmi iščejo Razvoj talentov, Podatkovno rudarjenje, Digitalne tehnologije, svoje priložnosti v prodaji le-teh igralcev. [3] ugotavljata, da GPS klubi, ki imajo več tujcev, dajejo manj igralnega časa svojim mladincem. Ker je večina klubov odvisna od prodaje igralcev, se ABSTRACT vse več časa in sredstev namenja razumevanju procesa razvoja Talent development process in football academies is a structured mladincev. Kot že [4] ugotavljajo, so morfološke, motorične in process that represents an important pillar on all levels in a funkcionalne značilnost pomembne pri razvrščanju otrok v football club. Investments in football have pushed the clubs to športne panoge. Z ustreznim razvrščanjem otrok se le-te lažje spend more resources on recognizing and developing football motivira k udejstvovanju v športu. Z razvojem tehnologije in talents within their youth academies. With development of sodobnih metod podatkovne analitike klubi poskušajo sistematično slediti začrtanim smernicam razvoja mladincev, z namenom, da dosežejo želeni cilj in maksimizirajo vrednost Permission to make digital or hard copies of part or all of this work for personal or posameznega talenta. Uporaba sodobnih tehnologij ne 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 predstavlja zgolj konkurenčne prednosti, temveč nujnost, da klub citation on the first page. Copyrights for third-party components of this work must optimizira svoje delovanje tako na športnem kot finančnem be honored. For all other uses, contact the owner/author(s). področju. Sodobne tehnološke naprave nogometnemu klubu ne Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). koristijo samo pri prepoznavanju talentov, marveč se uporabljajo tudi pri vadbi, rehabilitaciji ter preprečevanju poškodb [5]. 611 Visokozmogljive tehnološke naprave pri proučevanju nogometa S pomočjo testa agilnosti so raziskovalci ugotovili, da med znanstveniki delijo v dve skupini, in sicer na tiste, ki spremljajo obema opazovanima skupinama mladincev obstaja statistično igralce preko nosljivih tehnologij ter na že vgrajene naprave na značilna razlika. nogometnih stadionih. Med prvimi so najbolj pogosto Nadaljnjo raziskavo na področju razumevanja atributov so uporabljene Global Positioning System (GPS) naprave, ki merijo naredili [11], ki je vključevala 44 mladincev v starostnih pozicijo igralca v vsaki sekundi. Poleg omenjenih naprav se kategorijah U-15 in U-17 za specifičen klub iz Portugalske. V pogosto uporabljajo še naprave za lokalno sledenje v prostoru raziskavi so se avtorji osredotočili na pozicioniranje in dinamiko (angl. Local Positioning Measurement System), ki merijo igre. Obe starostni skupini so testirali s pomočjo 5-Hz GPS-a posamezne gibe ter pospešek igralca, naprave za spremljanje (SPI-ProX, GP Sports, Canberra, Avstralija) z namenom srčnega utripa (angl. Heart Rate Monitor) ter meriliniki pospeška pridobivanja dinamičnih podatkov pozicioniranja. Testiranje je (angl. Accelerometer) za sledenje fizičnim aktivnostim in potekalo skozi dve prijateljski tekmi, prvo na ravni selekcije U- naporom. Natančnost podatkov preko GPS sistemov zagotavljajo 15 in drugo na ravni selekcije U-17. Namen testiranja je bil dobiti giroskopi, digitalni kompasi in mikroelektromehanični sistemi. podatke o poziciji posamenzikov na igrišču v določenem Med že vgrajene tehnologije na stadionih uvrščamo predvsem momentu. S pomočjo GPS-a so vsi igralci imeli določene sisteme večih kamer (Multi-Camera System), ki merijo zgolj koordinate (dolžina, širina), s čemer so razsikovalci določili fizične sposobnosti igralcev [6]. Razvoj tehnologije omogoča vse preprostost podajanja (glede na oddaljenost soigralcev). Na boljši vpogled tudi v nekoliko težje merljive zmožnosti osnovi rezultatov testiranj so raziskovalci zaključili, da obstajajo posameznikov. V to kategorijo sodijo t.i. »eye-tracking« razlike med obema starostnima skupinama, kar je najverjetneje naprave, ki spremljajo fokus očesa pri igralcu. Primer vidnega posledica treningov pozicioniranja in vključevanja v člansko zaznavanja so med drugim raziskovali [7] ter [8]. Zgolj zbiranje ekipo pri skupini U-17. podatkov preko modernih tehnologij ne prinese želenih Reilly in sodelavci [12] so za ocenjevanje vzorcev gibanja in rezultatov. Podatke je potrebno razumeti, jih primerno umestiti v srčnega utripa pri 65 mladincih v starostni kategoriji U-15 problem in obdelati, da se iz njih nekaj naučimo. Preveč uporabili 4-Hz GPS (VX Sport, Visuallex Sport International podatkov, v kolikor jih ne znamo primerno obdelati, lahko Ltd., Wellington, Nova Zelandija). Podatki so se zbirali za 6 predstavljajo večjo težavo kot korist [9]. Z razvojem tehnologije tekem dolžine 60 minut. Preko GPS naprave so pridobili podatke se razvijajo tudi pristopi obdelovanja podatkov, saj so vse še za skupno pretečeno dolžino, visoko intenziven tek (hitrost zmogljivejši računalniki sposobni obdelati velike količine teka višja od 17 kilometrov/uro), šprint (hitrost teka višja od 22 podatkov, ki jih ljudje sami ne zmoremo. S pomočjo strojnega kilometrov/uro) in skupno število šprintov. Skozi meritve so učenja se ne obdelujejo le trenutni podatki, temveč se vse več spoznali, da v prvih 15 minutah po začetku drugega polčasa podatkov uporablja za razvoj napovednih modelov, ki lahko z skupna pretečena razdalja ekipe pade. Rezultati so podobni kot v veliko verjetnostjo napovedo rezultate na osnovi prejšnjih študijah [13], [14] ter [15]. Intenzivni in naporni treningi, podatkov. številne prijateljske in ligaške tekme neredko privedejo do poškodb pri mladincih. Zaradi kompleksnosti in številčnosti poškodb ni lahko napovedati. Ocenjevanje zgolj ene ali dveh 2 PREGLED LITERATURE spremenljivk se pri napovedovanju poškodb v praksi ni izkazalo Razvoj talentov v nogometu lahko opišemo kot mrežo kot uspešno. S pomočjo sodobnih znanstvenih pristopov, kot je koherentnih sil, ki izoblikujejo mladinca v profesionalnega npr. strojno učenje, ki omogoča analizo mnogih spremenljivk, se nogometaša. [10] so za testiranje agilnosti uporabili foto celice ocena tveganja poškodb izboljšuje in klubi vse lažje identificirajo (Newtest Oy, Finska) pri dveh skupinah mladincev v starostni prve znake morebitnih poškodb. [16] so ocenjevali tveganje za kategoriji U-15 (t.j. mladinci, ki še niso dopolnili 15. leta nastanek poškodb pri mladincih v starostnih kategorijah med U- starosti). Pri obeh testih so igralci začeli s testom 70 centimetrov 10 in U-15, in sicer v belgijski mladinski ligi. S pomočjo za foto celicami, ki so sprožile merilnik časa za čim natančnješe algoritmov strojnega učenja so na osnovi pripravljalnega merjenje. Foto celice prenašajo infrardeče žarke iz oddajnika v obdobja ocenili verjetnost poškodb za 734 mladincev tekom reflektor ter nazaj. Ko nastane sprememba v svetlobi, se merilnik ligaške sezone. V teku sezone se je poškodovalo 368 igralcev sproži. Test agilnosti je predstavljen na sliki 1. (bodisi akutno, bodisi zaradi prekomernih naporov). Na osnovi modela iz pripravljalnega obdobja, so avtorji pravilno napovedali 85 % poškodb. Še več, s pomočjo modela so z 78 % natančnostjo napovedali ali gre za akutno ali neakutno poškodbo. Podobno faktorsko analizo napovedovanja poškodb pri mladincih v starostnih kategorijah med U-10 in U-18 so [17] naredili v angleškem državnem prvenstvu, kjer so rezultati imeli manjšo napovedno vrednost kot pri [16]. 3 ZAKLJUČEK Slika 1: Test agilnosti Nogometni klubi so vse bolj primorani slediti zadnjim trednom Vir: [10] na tehnološkem področju, v kolikor želijo ostati konkurenčni. Sodobni pristopi v povezavi s tehnološkim napredkom Posameznik mora pri testu agilnosti čim hitreje preteči razdaljo od začetne točke ter okrog postavljenih preprek do končne točke. predstavljajo konkurenčno prednost pri razvoju in tranziciji mladincev v profesionalni nogomet. Prav tako je vse 612 pomembneje investirati v kadre, ki znajo primerno obdelati https://www.researchgate.net/publication/283329322_Talent_developme podatke in kvantitativne analize ustrezno prenesti v prakso. Z nt_in_football_are_young_talents_given_time_to_blossom. [4] Bohanec, M., Kapus, V., Leskošek, B., Rajkovič, V. 1997. Talent: uporabo sodobnih tehnologij na področju mladinskega nogometa Uporabniški priročnik. Ministrstvo za šolstvo in šport in Zavod Republike se vse lažje razlikuje med tistimi z večjim potencialom in tistimi, Slovenije za šolstvo. [5] Prieto-Mondragón, L. P., Camargo-Rojas, D. A., Quiceno, C. A. 2015. ki le-teh ne dohajajo. Uporaba GPS sistemov in drugih naprav za Isoinertial technology for rehabilitation and prevention of muscle injuries pridobivanje dinamičnih podatkov tekom nogometne igre je vse of soccer players: literature review. 543 Rev. Fac. Med. Vol. 64 No. 3: pomembnejše pri ocenjevanju razvoja talentov, hkrati pa v 543-50. [Elektronski]. https://www.researchgate.net/publication/ 312669425_Isoinertial_technology_for_rehabilitation_and_prevention_o povezavi s sodobnimi statistično naprednejšimi metodami f_muscle_injuries_of_soccer_players_Literature_review. predstavlja pomembno prednost pri ocenjevanju tveganja [6] Almulla, J., Takiddin, A., Househ, M. 2020. The use of technology in tracking soccer players’ health performance: a scoping review. BMC Med poškodb. Četudi se vse več uspešnih športnih klubov odloča za Inform Decis Mak 20, 184 https://doi.org/10.1186/s12911-020-01156-4. uporabo modernih tehnologij predvsem za maksmiziranje [Elektronski]. https://bmcmedinformdecismak.biomedcentral.com/ dobička in iskanje novih poti pri ustvarjanju »supertalentov«, pa articles/10.1186/s12911-020-01156-4. [7] McGuckian, T., Cole, M., Pepping, G.-J. 2017. A systematic review of the mnogi posamezniki ne dosežejo svojega maksimalnega technology-based assessment of visual perception and exploration potenciala. Klubi se zaenkrat še ne odločajo za celovit pristop behaviour in association football. Journal of Sports Sciences 36(2):1-20. DOI:10.1080/02640414.2017.1344780. [Elektronski]. razumevanja tranzicije mladincev v članske selekcije, zato se https://www.researchgate.net/publication/317919179_A_systematic_revi izgubljenega potenciala ne zavedajo v celoti. V jugovzhodni ew_of_the_technology-based_assessment_of_visual_perception_and_ exploration_behaviour_in_association_football. Evropi (kamor spada tudi Slovenija), metod podatkovnega [8] Aksum, K. M., Magnaguagno, L., Bjørndal, C. T., Jordet, G. 2020. What rudarjenja pri razumevanju in ovrednotenju razvoja mladincev Do Football Players Look at? An Eye-Tracking Analysis of the Visual praktično ni zaznati, so pa klubi pripravljeni sodelovati in kažejo Fixations of Players in 11 v 11 Elite Football Match Play. Front Psychol. [Elektronski]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596273/. naklonjenost modernim pristopom. Kratkoročni cilj je ustvariti [9] Rein R., Memmert, D. 2016. Big data and tactical analysis in elite soccer: celovit model razvoja talentov, ki bo služil kot podpora future challenges and opportunities for sports science. Springer Plus. [10] Forsman H., Blomqvist M., Davids K., Liukkonen J., Konttinen N. 2016. trenerjem, menedžerjem in drugim nosilcem razvoja mladincev Identifying technical, physiological, tactical and psychological pri razumevanju tranzicije igralcev v starejše selekcije. Z characteristics that contribute to career progression in soccer. International razvojem takšnega modela bi nogometni klubi bolje razumeli Journal of Sports Science & Coaching 2016, Vol. 11(4) 505–513. [11] Gonçalves B., Coutinho D., Santos S., Lago-Penas C., Jiménez S., proces tranzicije iz večih vidikov, in sicer iz fizičnega, Sampaio J. 2017. Exploring Team Passing Networks and Player psihičnega, tehničnega in taktičnega vidika. Temu primerno bi Movement Dynamics in Youth Association Football,“ PLoS ONE 12(1): e0171156. prilagodili treninge, hkrati pa bi trenerji lažje in bolje motivirali [12] Reilly, B., Akubat, I., Lyons, M., Collins, K. D. 2015. Match-play svoje selekcije. Na ta način bi se deloma izognili izgubljenim demands of elite youth gaelic football using global positioning system priložnostim in odpadanju mladincev iz nogometnih šol in tracking,“ Journal of Strength and Conditioning Research, p. 989–996. [13] Mohr, M., Krustrup, P., Bangsbo, J. 2003. Match performance of akademij. Razvoj modela za pomoč klubom pri razumevanju highstandard soccer players with special reference to development of tranzicije mladincev v članske vrste predstavlja ključni cilj fatigue,“ J Sport Sci 21, p. 519–528. [14] Lovell, R. J., Kirke, I., Siegler, J., McNaughton, L. R., Greig, M. P. 2007. doktorske raziskave, ki je temelj za uspešno dokončan doktorski Soccer half-time strategy influences thermoregulation and endurance študij. performance,“ J Sports Med Phys Fitness , pp. 263-269. [15] Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., Krustrup, P. 2009. High-intensity running in English FA premier league soccer LITERATURA IN VIRI matches,“ J Sport Sci , pp. 159-168. [16] Rommers, N., Rössler, R., Verhagen, E., Vandecasteele, F., Verstockt, S., [1] Sánchez, L. C., Barajas, A., Sánchez-Fernández, P. 2019. Sports Finance: Vaeyens, R., Lenoir, M., D'Hondt, E., Witvrouw, E. 2020. A Machine Revenue Sources and Financial Regulations in European Football. Sports Learning Approach to Assess Injury Risk in Elite Youth Football Players. (and) Economics (pp.327-366). [Elektronski]. Medicine & Science in Sports & Exercise. [Elektronski]. https://www.researchgate.net/publication/332275168_Sports_Finance_R https://www.researchgate.net/publication/339402608_A_Machine_Learn evenue_Sources_and_Financial_Regulations_in_European_Football. ing_Approach_to_Assess_Injury_Risk_in_Elite_Youth_Football_Players [2] S. Morrow. 2003. The People's Game?, London: Palgrave, [17] Oliver, J., Ayala, F., De Ste Croix, M., Lloyd, R., Myer, G., Read, P. 2020. [3] Saether, S. A., Solberg, H. A. 2015. Talent development in football: are Using machine learning to improve our understanding of injury risk and young talents giventime to blossom? Sport, Business and Management: prediction in elite male youth football players.,“ Journal of science and An International Journal, Vol. 5 Iss 5 pp. 493 -506. [Elektronski]. medicine in sport. 613 Spremljanje napredka in dajanje povratne informacije v času dela na daljavo Monitoring progress and giving feedback while working remotely Tadeja Vučko Osnovna šola Draga Kobala Maribor Maribor, Slovenija tadeja@osdk.si POVZETEK school are described. During the distance work, the lessons were conducted with the help of information and communication V prispevku so predstavljene nekatere težave glede spremljanja technology. Students used the Zoom video conferencing tool, dela in napredka učenca v času dela na daljavo ter načini Arnes online classrooms, and some other tools at work. Feedback spoprijemanja z njimi. Opisana so orodja, s pomočjo katerih on students' knowledge was obtained by teachers in various ways. učitelj lahko dobi povratno informacijo glede usvojene snovi in The article presents how we get feedback with the help of quizzes posamezni koraki pri nastajanju besedila za govorno predstavitev in the Arnes online classroom and knowledge testing with pri obveznem izbirnem predmetu nemški jezik v 9. razredu Microsoft Forms, and how we give it with the help of tasks in the osnovne šole. V času dela na daljavo je pouk potekal s pomočjo Arnes online classroom. In order to gain a realistic picture of informacijsko-komunikacijske tehnologije. Učenci so pri delu children's knowledge, these quizzes were solved during uporabljali videokonferenčno orodje Zoom, Arnesove spletne videoconferencing meetings, and later they had the opportunity učilnice in nekatera druga orodja. Povratno informacijo glede to review the answers and try again. Upon arrival at the school, znanja učencev so učitelji pridobivali na različne načine. V we found that despite the many opportunities available to članku je predstavljeno kako s pomočjo kvizov v Arnesovi students, the knowledge acquired while working remotely was spletni učilnici in preverjanja znanja z Microsoft Forms dobimo often not consolidated. Thus, some materials had to be reworked povratno informacijo ter kako jo s pomočjo nalog v Arnesovi and consolidated in school. spletni učilnici podamo. Za pridobitev realne slike znanja otrok In the compulsory elective course, students learned about so ti kvize reševali v času videokonferenčnih srečanj, kasneje pa German-speaking areas while working remotely. The paper imeli možnost svoje naloge ponovno pregledati in rešiti. Ob presents the course of work and the role of information and prihodu v šolo smo ugotovili, da kljub mnogim možnostim, ki so communication technology in this. učencem bile na voljo, znanje usvojeno v času dela na daljavo pogosto ni bilo utrjeno. Tako je nekatere snovi bilo potrebno KEYWORDS ponovno predelati in utrditi v šoli. Pri obveznem izbirnem predmetu so učenci v času dela na Foreign language, knowledge evaluation, assessment daljavo spoznavali nemško govoreča območja. V prispevku je predstavljen potek dela in vloga informacijsko-komunikacijske 1 UVOD tehnologije pri tem. V novembru 2020 smo ponovno pričeli z delom na daljavo. Ker KLJUČNE BESEDE smo tokrat lahko črpali iz pridobljenih izkušenj, smo učence v Tuji jezik, vrednotenje znanja, preverjanje prvem mesecu pouka v živo opremili z znanjem glede ravnanja z orodji potrebnimi pri delu na daljavo. Učenci so se v prvih tednih ABSTRACT pouka vpisali v spletne učilnice in ponovili kje in kako najdejo The article presents some problems regarding the monitoring of gradiva ter oddajo nalogo. Seznanili so se z ostalimi gradivi, ki student work and progress during distance education and ways to jih bodo tekom šolskega leta potrebovali in kako dostopati do e- deal with them. The tools with which the teacher can get gradiv posameznih učbeniških kompletov. Hkrati smo na šoli feedback on the acquired material and individual steps in the oblikovali načrt dela in s tem seznanili tako učence, kot tudi creation of a text for a speech presentation in the compulsory starše. elective subject German language in the 9th grade of primary Ob pričetku dela na daljavo je šola poskrbela, da je vsem učencem na voljo ustrezna oprema in lahko sodelujejo pri pouku. Kmalu po prvih videokonferencah so se pojavila prva vprašanja Permission to make digital or hard copies of part or all of this work for personal or glede pridobivanja ocen. Učitelji so vprašanja, skrbi in pobude 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 naslavljali na Zavod za šolstvo, o tem je bilo govora na študijskih citation on the first page. Copyrights for third-party components of this work must skupinah in na šolskih aktivih. Ker smo tokrat že imeli nekaj be honored. For all other uses, contact the owner/author(s). izkušenj, smo pred pričetkom pouka o teh težavah govorili in Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). temu primerno načrtovali delo v razredu. Ob prehodu na delo na daljavo smo prilagodili metode in oblike dela, ter tudi vsebine. 614 2 SPREMLJANJE NAPREDKA prikazano s pomočjo slike 3. Preizkus je možno podvojiti in V prvih tednih dela na daljavo so učenci navodila za delo in spreminjati, lahko ga kopiramo in damo v souporabo drugim. Po razlago nove snovi prejemali v času videokonferenc in preko opravljenem preizkusu učenec in učitelj vidita odgovore, učitelj spletne učilnice. Na šoli uporabljamo Arnes Učilnice (Moodle) ima vpogled v to, kaj učenci že znajo in kaj je potrebno še [1] in videokonferenčno orodje Arnes Zoom [2]. Dokazila o ponoviti. Preveri lahko čas reševanja in natisne povzetek oz. opravljenih nalogah so oddajali kot naloge v spletni učilnici ali rezultate preverjanja. V primeru, da želi preizkus ponovno izjemoma po elektronski pošti. Naloge sem sproti pregledovala uporabiti, lahko odgovore tudi izbriše. in povratno informacijo zapisala individualno kot odziv na nalogo. Pri tem sem hitro opazila, da marsikateri učenec povratne informacije ne prebere in napak ne popravi. Na naslednji videokonferenci smo ponovno pogledali postopek oddaje naloge. V videokonferenčnem orodju Zoom sem omogočila deljenje zaslona in prosila, da prostovoljec pokaže, da je nalogo oddal in povratno informacijo deli z ostalimi. Učenka je poiskala oddano nalogo in pokazala kje najdemo odziv na opravljeno nalogo ter zastavimo vprašanja, v kolikor odziv ni razumljiv in je potrebna dodatna razlaga. Nekateri učenci so naloge popravili in ponovno oddali, drugi tega niso storili. Po nekaj tednih takšnega dela sem ugotovila, da motivacija za delo pada. Učenci so v času videokonference sodelovali le, če so bili poklicani, sama pa nisem imela več vpogleda v to, ali večina učencev razlagi res sledi ali raje molči in se ne želi izpostavljati. Ponudila sem jim dodatno uro za razlago, vendar se je učenci niso udeleževali. Nekateri se tudi tedenskih ur izbirnega Slika 1: Urejanje vprašanja v Arnesovi spletni učilnici -1. predmeta niso udeleževali redno, zato sem sklenila, da del razumevanje snovi preverim s pomočjo kviza. Sprva sem kviz ustvarila v Arnesovi spletni učilnici. Kviz je potrebno dodati in ga urediti. Orodje ponuja nabor različnih tipov vprašanj (drži/ne drži, izbirni tip vprašanja, povleci in spusti, esej, izberi manjkajoče besede, razvrščanje itn.). Kviz je vseboval različne tipe vprašanj, ki so si sledili od lažjega do težjega. Učenci so morali prepoznati nemški prevod besede, nato prevode zapisati sami in na koncu dopolniti poved z že danimi možnostmi. Zahtevnejših nalog, ki bi preverjale znanje višjih taksonomskih stopenj, pri preverjanju nisem vključevala. Poudarek je bil na razumevanju osnov in ustrezni povratni informaciji glede učenčevega znanja. Poleg tega v času, ko je motivacija za delo že tako bila nizka, učencev nisem želela še dodatno obremeniti. Prednosti kviza v Arnesovi Učilnici so, da se učenci v učilnice prijavljajo z dodeljenim uporabniškim imenom in učitelj vidi, kateri učenci so kviz že rešili, kolikokrat so ga reševali, dan Slika 2: Urejanje vprašanja v Arnesovi spletni učilnici – 2. reševanja in koliko časa so za to potrebovali. Po oddanih del odgovorih učenec in učitelj vidita, kateri odgovori so pravilni in kateri napačni. Učitelj tako vidi, pri katerih nalogah so učenci uspešni in katere snovi je potrebno ponovno razložiti ali ponoviti. Možnosti pri pripravljanju kviza je veliko, kar prikazujeta sliki 1 in 2. Učitelj ustvari nalogo oz. vprašanje, določi pravilne in nepravilne odgovore, oceno, doda odzive in izbere število poskusov. Učitelj izbere tudi občutljivost na velike in male črke, kar je pomembno pri preverjanju pravilnega zapisa. Zaradi vseh teh možnosti pa je priprava takega kviza precej zamudna, kviz pa je možno uporabiti za eno skupino učencev. Kasneje sem za ustvarjanje kvizov začela uporabljati orodje Microsoft Forms [3]. V primerjavi s kvizi v Arnesovi Učilnici pri tem orodju govorimo o ustvarjanju novega obrazca oz. preizkusa Slika 3: Urejanje vprašanja z orodjem Microsoft Forms znanja. Orodje ponuja manj tipov vprašanj (izbira, besedilo). Dodatnih odzivov ali namigov ni možno dodajati, zaradi tega pa Če primerjamo obe orodji, lahko rečemo, da z njima lahko ustvarjanje preizkusa ni časovno tako zamudno. Urejanje je pridobimo informacijo o znanju v času dela na daljavo. Medtem, 615 ko se v Arnesovo Učilnico učenci prijavijo z uporabniškim nemščino kot obvezni izbirni predmet [5]. Učenci ob pripravi in imenom in so imena posameznikov učitelju vidna, je v orodju izvedbi predstavitve dokažejo, da: Microsoft Forms potrebno nastaviti, ali kviz lahko rešujejo vsi z - razumejo podrobnosti na določeno temo ali situacijo vezanega dostopom ali ljudje v organizaciji. V primeru, da potrebujemo besedila, tudi če ta vsebuje neznane informacije, ki za splošno informacijo glede znanja, lahko učenci kviz rešujejo razumevanje niso ključnega pomena; anonimno. Kadar pa želimo spremljati napredek posameznika, pa - znajo samostojno poiskati informacije v besedilu, ki so je potrebno v Forms-ih to tako tudi nastaviti. Prednost potrebne za rešitev določenih nalog; Microsoftovega orodja je preprosta uporaba, ki terja veliko manj - razvijajo govorno sporočanje (predstavitev – predaja časa, in možnost deljenja preverjanja znanja. Učitelji smo se informacije o prej raziskani temi); lahko dogovorili, katere snovi bomo preverjali in si preizkuse - znajo postavljati vprašanja, ki se nanašajo na temo in nanje delili, nato pa individualno prilagajali svoji skupini. Dodatna odgovarjajo. prednost je dostopnost, saj so do preizkusov učenci lahko Navodila za delo so učenci prejeli vsak teden v spletni dostopali preko povezave, ki sem jo pripela v času učilnici. Postopoma so oblikovali govorno predstavitev, sproti pa videokonference, medtem ko so kvize v Arnesovi spletni učilnici dobivali povratne informacije o že zapisanem besedilu. lahko reševali le ob prijavi v spletno učilnico. Sprva sem kvize v spletno učilnico dodala kot nalogo, ki so 3.1 Nastajanje govornih predstavitev jo morali opraviti tekom tedna. Ob koncu tedna sem opazila, da V prvem tednu so učenci dobili naslov govorne predstavitve. naloge niso opravili vsi. Po razgovoru z učenci sem ugotovila, da Pred začetkom dela so učenci v skupinah razmislili, katere so se nekateri bali, da pri reševanju kviza, ki je zajemal snovi, ki informacije bi bile zanimive in katere ne. Našteli so teme, o smo jih delali pred in v času dela na daljavo, ne bodo uspešni in katerih bi že znali nekaj samostojno povedati, poudarek je bil, da bo to kasneje vplivalo na oceno. V prihodnje sem učence pred naj bo besedilo njihovo delo in ne kopija že zapisanega. Povedi preverjanjem znanja opozorila na to, katere snovi se bodo v so lahko preproste, uporabljajo naj znano besedišče. Učenci so prihodnjem tednu preverjale, kratke kvize, s pomočjo katerih začeli z zbiranjem informacij s pomočjo spletnih brskalnikov. Pri sem dobila povratno informacijo glede njihovega znanja pa so tem je bilo zaželeno, da informacije že v osnovi iščejo v reševali v času videokonference. Tudi tokrat kviza kljub nemškem jeziku in si po potrebi pomagajo s slovarji (npr. PONS, pobudam in sprotnemu spremljanju niso rešili vsi učenci. Opazila Google Translate). Tako so spoznavali avtentična gradiva. pa sem, da so učenci pri obveznem predmetu kvize reševali Pozorni so bili na izgovorjavo in si beležili informacije, ki so jih uspešneje in v večjem številu kot pri obveznem izbirnem s pomočjo posnetkov dobili. Ogledali so si lahko turistične predmetu. Informacije, ki sem jih s pomočjo kvizov in predstavitve, brošure in različne spletne strani. Večina učencev preizkusov dobila, so mi služile predvsem kot pomoč pri je izbrala posnetke na YouTubu. Informacije so zapisali in oddali načrtovanju naslednjih ur. Vseeno pa smo ob povratku v šolo v spletno učilnico, kar je prikazano na sliki 4. Po pregledu pomembnejše teme ponovili, saj se je izkazalo, da kljub zapisov so dobili povratno informacijo. ponavljanju s pomočjo kvizov in preverjanj, znanje pri mnogih učencih ni bilo utrjeno. V Pravilniku o preverjanju in ocenjevanju znanja ter napredovanju učencev v osnovni šoli (2013) je v 3. členu zapisano, da je ocenjevanje znanja »ugotavljanje in vrednotenje, v kolikšni meri učenec dosega v učnem načrtu določene cilje oziroma standarde znanja. Učitelj ocenjevanje znanja opravi po obravnavi učnih vsebin in po opravljenem preverjanju znanja iz teh vsebin.« [4] Ocenjujejo se lahko »učenčevi ustni odgovori ter pisni, likovni, tehnični, praktični in drugi izdelki, projektno delo in nastopi učencev.« [4] Z učenci smo s pomočjo kviza in preverjanja znanje sicer preverili, a preko teh orodij učencev Slika 4: Dokazila o delu in podajanje povratne informacije nisem ocenjevala. Zaradi morebitnih zapletov s povezavo in občasnih nedelujočih kamer ni bilo možno vsem učencem V naslednjih tednih so delo nadaljevali tako, da so najprej zagotoviti istih oz. primerljivih razmer za delo, zato se takšne pregledali povratno informacijo, morebitne napake popravili, oblike ocenjevanja nisem lotila. Ko delu na daljavo ni bilo videti nato nadaljevali z delom po navodilih. S pomočjo informacij s konca, sem se odločila, da bodo učenci devetega razreda pri spleta so tvorili naslednje povedi. Pri tem so si lahko pomagali s obveznem izbirnem predmetu nemščine namesto načrtovane slovarji, spletom in knjižnim gradivom. Ob delu so sproti prve ustne ocene, oceno pridobili z govornimi predstavitvami. navajali vire in dodajali slikovna gradiva. Pri vsem tem so učenci morali biti vešči brskanja po spletu, uporabe spletnega slovarja, Word-a in spletne učilnice. Izkazalo 3 PRIPRAVA IZDELKA IN POVRATNA se je, da kljub opozarjanju, naj si kot jezik v dokumentu nastavijo INFORMACIJA nemški jezik, mnogi učenci tega niso storili. Tako so predstavitve V devetem razredu govorimo o deželah nemškega govornega imele napake, ki bi jih z ustreznim računalniškim znanjem učenci območja, zato učenci vsako leto na to temo pripravijo kratko lahko odpravili sami. Pri tem naj omenim, da jim postopek govorno predstavitev. Dogovorili smo se, da bodo predstavitve nastavitve jezika in možnosti popravljanja napačnih zapisov v opravili v času dela na daljavo in bodo ocenjene. Zastavljeni učni Wordu pokažem vsako leto. Učenci so morali pregledati odzive cilji se navezujejo na operativne učne cilje po učnem načrtu za na nalogo in popravke upoštevati. Pri drugi oddaji naloge je bilo 616 jasno, kateri učenci povedi tvorijo samostojno ali s pomočjo 4 ZAKLJUČEK slovarja, kateri pa kopirajo celotne stavke. Za nadaljnje delo je V času dela na daljavo je pouk potekal drugače. Temu je bilo bilo pomembno, da učenci povedi tvorijo sami. Ti učenci so ustni potrebno prilagoditi tudi ocenjevanje. Iz izkušenj v preteklem del opravili brez težav, saj so povedi bile enostavnejše in lažje letu sklepam, da je najprimernejša izmed načrtovanih tem in razumljive. dejavnosti za ocenjevanje priprava in izvedba govorne 3.2 Kriteriji uspešnosti predstavitve. Učenci so pri delu bili vodeni in redno dobivali povratne informacije na Zoom konferencah ali kot odziv nalogo Z učenci smo oblikovali kriterije za ocenjevanje. To smo storili v Arnesovi Učilnici. Te so pripomogle k temu, da so postali na videosrečanju. Učenci so bili razdeljeni v naključne skupine, pozorni na svoje napake, jih odpravili ter se iz njih učili. S skupaj so morali oblikovati predlogo za kriterije ocenjevanja. To pomočjo informacijske-komunikacijske tehnologije so imeli so zapisali v skupni dokument (One Drive) [6], predloge smo dostop do avtentičnih gradiv, pri delu so uporabili slovarje, dobili pregledali in jih skupaj preoblikovali. Učenci so predlagali, da se so redne povratne informacije, na koncu so si s pomočjo ocenjujejo govor, vsebina in Powepoint predstavitev. Ocenjujejo kriterijev uspešnosti lahko pregledali, kaj jim manjka oz. na naj se torej vsebina (ali so zajete vse iztočnice in v kakšni meri katerem področju še potrebujejo pomoč ali utrjevanje. Po so zajete), jezik (ali je besedišče bogato, pravopisno pravilno, ali končani govorni predstavitvi preko Zooma ali v živo so prejeli še so slovnične strukture pravilno uporabljene) in govor (ali učenec povratne informacije s strani sošolcev oz. so jih sošolcem podali govori prosto, tekoče). Pri tem naj bi se upoštevala tudi sami. S tem se je ocenjevanje zaključilo. Splošno znanje na to pripravljena dodatna gradiva. O predlogih smo se pogovorili in temo se je preverilo še s pomočjo kviza. Menim, da so govorne pregledali kriterije, ki so ob tem nastali. predstavitve bile pozitivna izkušnja in situaciji primeren način preverjanja znanja, pri katerem so se imeli možnost izkazati tudi 3.3 Izvedba in povratna informacija s strani učno šibkejši učenci. sošolcev Kot uporabni orodji za preverjanje znanja so se izkazali kvizi Pred izvedbo govornih nastopov so učenci zapisano lahko v Arnes Učilnici in preverjanje znanja v Microsoft Forms. popravili na osnovi povratne informacije učitelja, si ogledali Slednji je sicer uporabniku prijaznejši, a z manj možnostmi izbire. kriterije, ki so bili naloženi tudi v spletni učilnici predmeta. Za V kolikor bi Pravilnik o preverjanju in ocenjevanju znanja izvedbo smo se dogovarjali v manjših skupinah. Učenci so si pri omogočal ocenjevanje po delih, bi bilo vredno razmisliti o tem lahko odprli dokument s kriteriji in si sproti beležili opažanja rednem izvajanju kratkih preverjanj znanja. Ta so časovno manj o izvedbi govornega nastopa. Po vsaki končani predstavitvi so potratna, dajejo pa, v kolikor se izvajajo pod enakimi pogoji, najprej učenci podali povratno informacijo s pomočjo kriterijev, objektivno informacijo glede učenčevega znanja. nato učiteljica. Učenci so tudi sešteli točke in povedali, kakšno oceno bi dobil posameznik. Učiteljica je potem povedala še svoja LITERATURA IN VIRI opažanja in ocenila učenca. [1] Arnes Učilnice: https://sio.si/vodici/moodle/#kompilacija-sio-MDL-VOD Ob koncu vseh govornih predstavitev so učenci rešili še kviz [2] Arnes Zoom: https://www.arnes.si/storitve/multimedijske-storitve/arnes- zoom/ na to temo. V preteklem šolskem letu smo govorne predstavitve [3] Microsoft Forms: https://www.microsoft.com/en-us/microsoft- izvedli na podoben način, vendar smo temu dodali še beleženje 365/online-surveys-polls-quizzes [4] Pravilnik o preverjanju in ocenjevanju znanja ter napredovanju učencev slišanih informacij. Učenci so tekom govornih nastopov morali v osnovni šoli. Uradni list RS, št. 52/13 (21.6.2013). Pridobljeno s razbrati osnovne informacije in jih vpisati v pripravljene brošure. http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV11583 Tega na daljavo zaradi izvedbe predstavitev v manjših skupinah [5] Kondrič Horvat, V. et al. 2001. Učni načrt: izbirni predmet: program osnovnošolskega izobraževanja. Nemščina. Ljubljana: Zavod RS za nismo naredili. šolstvo, 15-16. Dostopno na Ob dejavnosti so učenci razvijali vse štiri spretnosti. Pri https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Osnovna-sola/Ucni- nacrti/izbirni/3-letni/Nemscina_izbirni.pdf iskanju informacij so vadili bralno razumevanje, pri oblikovanju [6] OneDrive: https://www.microsoft.com/sl-si/microsoft- besedila pa pisno sporočanje. Pred in med predstavitvijo so vadili 365/onedrive/online-cloud-storage govorno sporočanje in slušno razumevanje. Slušno razumevanje so vadili že pri prvi aktivnosti, ko so iskali informacije in si posnetke ogledali v nemščini. Takrat so morali biti pozorni tudi na izgovorjavo posameznih besed. 617 Priprava na obštudijsko dejavnost »Organizacija in usposabljanje v potapljanju« Preparation for the extracurricular activity "Organization and education in diving" Borut Werber Uroš Rajkovič Univerza v Mariboru, Univerza v Mariboru, Fakulteta za organizacijske vede Fakulteta za organizacijske vede Kranj, Slovenija Kranj, Slovenija borut.werber@um.si uros.rajkovic@um.si POVZETEK 1 UVOD V prispevku predstavljamo priprave na Fakulteti za UM FOV smo v začetku leta 2021 na UM v potrditev vložili učni organizacijske vede Univerze v Mariboru na izbirno kreditno načrt za študijsko leto 2022-2023 za izbirno možnost kreditno ovrednotene obštudijske dejavnosti za študente “Organizacija in ovrednotene obštudijske dejavnosti “Organizacija in usposabljanje v potapljanju” v študijskem letu 2022/2023. usposabljanje v potapljanju”. Kot morebitna izvajalca teoretičnih Predstavljamo vsebine tečaja potapljanja z avtonomno vsebin sva se prijavila avtorja tega prispevka, ki imava večletne potapljaško opremo. S ciljem dobre priprave na izvajanje tečaja izkušnje s potapljanjem. Postopek priprave in zahtevane pravne v praksi smo predstavili izkušnje pridobljene med lastnim podlage ter predvideni pozitivni učinki so predstavljeni v potapljanjem in sodelovanjem pri izvedbi različnih tečajev prispevku [1] (Werber, 2021). V tem prispevku smo se potapljaškega društva Kisik v času od junija 2021 do septembra osredotočili na praktične izkušnje, pridobljene med lastnim 2021. V zaključku predstavljamo kaj smo se iz videnega naučili potapljanjem in med izvedbo različnih tečajev in organiziranih in kako bomo poskušali podobne težave preprečiti pri izvedbi potopov potapljaškega društva Kisik na Blejskem jezeru ali tečajev s študenti. morju v času med junijem in septembrom 2021, ki nam lahko pomagajo preprečiti podobne težave pri izvedbi tečaja s študenti. KLJUČNE BESEDE Iz pričevanega bo razvidno, da smo imeli napačen vpogled v Izbirni predmet, potapljanje, izobraževanje izvedbe potapljaških tečajev saj je skoraj v vsaki skupini tečajnikov ali certificiranih potapljačev prihajalo do manjših ali ABSTRACT večjih težav med izvedbo potapljanja. This article presents preparations at the Faculty of Organizational Sciences University of Maribor for the elective credit-evaluated 2 extracurricular activities for students “Organization and training PREGLED LITERATURE in diving” in the academic year 2022/2023. We hereby present Obštudijska dejavnost je na Univerzi v Mariboru opredeljena the contents of a diving course with autonomous diving na 48 strani v 215. členu Statuta UM [2]. Obštudijska dejavnost equipment. With the aim of good preparation for the lahko izvira iz področja kulture, športa in drugih obštudijskih implementation of the course in practice, we present the dejavnostih. Podrobnejši opis obštudijskih dejavnosti je na UM experience gained during our own diving and participation in opredeljen v Pravilniku o kreditno ovrednoteni obštudijskih various courses of the diving association Kisik in the period from dejavnosti na Univerzi v Mariboru, št. 012/2019/1[3]. Na UM June 2021 to September 2021. In conclusion, we present what we FOV smo se odločili, da med več možnimi izberemo have learned from what is presented and how we will try to izobraževanje po sistemu PADI (Professional Association of prevent similar problems when conducting courses with students. Diving Instructors), ki ima dolgoletno tradicijo iz leta 1966, je mednarodno priznan, je med najbolj razširjenimi med največ KEYWORDS nudenimi potapljaškimi centri za rekreativno potapljanje in mu Elective course, diving, education tudi druge univerze in fakultete po svetu priznavajo ovrednotenje po kreditnih točkah glede na stopnjo izobraževanja [4]. Glede na stopnje izobraževanja PADI deli izobraževanja na naslednje nivoje, kot je prikazano na sliki 1. Iz slike 1 je razvidno, da je za mlade in otroke na razpolago PADI Seal team, ki je razdeljen na Bubblemaker in Discover Permission to make digital or hard copies of part or all of this work for personal or Scuba diving ter Skin diving in omejen s starostjo 8 let. Pri vseh classroom use is granted without fee provided that copies are not made or distributed teh stopnjah je obvezna prisotnost in vodenje inštruktorja. Prvi for profit or commercial advantage and that copies bear this notice and the full nivo certificiranega potapljača predstavlja stopnja OWD (Open 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). water diver), ki je omejena do globine 18m in omogoča Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia samostojno potapljanje v parih v spremstvu inštruktorja ali © 2021 Copyright held by the owner/author(s). Divemastra. V našem primeru bomo izvajali usposabljanja za to stopnjo. Kot nadaljevanje sledi izobraževanje za Adventure diver 618 (Deap diver in Wreck diver) in AOWD (Advanced open water 4.1 Neuspelo uravnavanje pritiska v ušesih diver), ki ima omejitev do globine 30m razen, če znotraj tega Skupina štirih tečajnikov je imela prvi dan praktičnih vaj in pridobimo certifikat za specialnosti, ki dovoljujejo potope do med prvim potopom smo opazili, da ima ena od tečajnic težave z 40m. Naslednja stopnja je Rescue diver, ki pomaga pri reševanju izenačevanjem pritiska v ušesih. Kot posledica slednjega se ni in nato Master scuba diver, ki je le naziv za usposobljenost uspela potopiti, ostali pa so čakali na dnu Blejskega jezera na rekreativnega potapljača, ki pa ne sme sodelovati ali izvajati globini 5m. S tečajnico je bilo potrebno izvesti ponoven poskus usposabljanja. Prvi nivo s področja profesionalnega izenačevanja pritiska nad gladino, da smo zaznali napako pri tem usposabljanja je Dive master, kar predstavlja tudi poklic, a je postopku. Če bi se tečajnica spustila v globino brez izenačevanja omejen na manj zahtevne naloge in v večji meri le pomaga Open bi začutila hudo bolečino in posledično poškodbo bobniča s water scuba instruktorju. krvavenjem, Analiza: Obstaja več načinov izenačevanja pritiska v ušesih. Najenostavnejši je s pihanjem v nos pri čemer s prti stisnemo nosnice. Tečajnica je namesto v nos pihala v usta oziroma lica. To je izvedlo pritisk na ličnice namesto na ušesa. Rešitev: Kandidatom je potrebno predstaviti vse možne načine izenačevanja pritiska v ušesih in z njimi po potrebi večkrat ponoviti to vajo v plitki vodi. 4.2 Prehiter dvig na površino Prehiter dvig na površino je lahko za potapljača nevaren sorazmerno z globino in časom v katerem je bil na tej globini. Rezultira lahko v obliki dekompresijske bolezni, ki jo delimo na izločanje dušika v obliki mehurčkov v krvni sitem ter raztezanje pljuč kot posledica neustreznega izpusta zraka med dvigom. Da bi se preprečile take nesreče se vse vaje najprej izvajajo v plitvi Slika 1: Shema izobraževanja po sistemu PADI vodi, ki ne presega višino potapljača (plitka voda ali bazen), kasneje pa na globini med 5-7 m. Rekreativni potapljači, ki se želijo potapljati globje kot 40m Opis primera: skupina štirih potapljačev je izvajala morajo opraviti usposabljanja PADI za Tec diving (tehnično ponovitev vaj iz plitke vode na globini 7m. Med vajo praznjenja potapljanje)[5], pri katerih se uporablja obogaten zrak s kisikom maske (vodo iz maske izpodrinemo s pomočjo dovajanja zraka (Nitrox) ali Trimix (helij, kisik in dušik), ki omogoča časovno preko nosu), je tečajnica nenamerno namesto vpiha izvedla vdih daljše in globje potope, a zahteva varnostne postanke, dodatno preko nosu in tako vdihnila vodo. Sledil je kašelj, ki je izzval tehnično opremo in dodatne vire zraka na posameznih bruhanje, izpust regulatorja iz ust in hiter dvig na površino. predvidenih globinah za dekompresijo. Priporočeno je da se dvigujemo 18m na minuto [7] ali počasneje. Kot je razvidno iz slike 1 ima PADI-jev izobraževalni sistem Glede na globino in čas potopa ni bilo nevarnosti, da bi zelo dodelano in razvejano strukturo učenja. Ves sistem je podprt kandidatka dobila Dekompresijsko bolezen, a smo morali z njo tudi z ISO standardi. Vsak tečaj je podrobno opisan v priročnikih pol ure ponavljati vaje v plitki vodi, da je premagala strah in si (npr. PADI Divemaster manual [7]) in se ga posodablja glede na pridobila sposobnost kontroliranega izpiha čez nos. spremembe v tehnični opremi. Analiza: Do težave je prišlo, ker je tečajnica tečaj potapljanja zaradi omejitev v zvezi s korona virusom prekinila za nekaj 3 METODOLOGIJA DELA mesecev in se tako drugega dne tečaja udeležila naknadno. Rešitev: Če je med vajami v nizki vodi in vajami v globoki vodi Kot metode dela smo uporabili študijo literature, študije več dni ali mesecev, je nujno potrebno ponoviti vaje v plitki vodi. primerov in primerjave rezultatov z zapisi v Divemaster Na ta način tečajnik spet pridobi občutek in zmanjša strah zaradi priročniku v katerem so našteti različni primeri težav s katerimi neugodja, ko mu voda pride v nos in čez oči. se lahko srečamo med izvajanjem izobraževanja in potopov. Zbrani primeri so se zgodili v času od junija 2021 do septembra 4.3 Pomanjkanje zraka 2021 med izobraževanji ali organiziranimi potopi. Primerjava je Ena od najbolj nevarnih situacij za potapljača je, da med narejena s ciljem, da ugotovimo potencialne nevarnosti in se čim potopom ostane brez zraka. Pravila sicer pravijo, da mora bolje pripravimo za izvedbo obštudijske dejavnosti potapljač pred vstopom v vodo s so-potapljačem izvesti preverbo »Organizacija in usposabljanje v potapljanju« s študenti UM opreme, ki vsebuje tudi pregled funkcioniranja regulatorja in FOV v študijskem letu 2022/2023. oktopusa (rezervni regulator). Ker je to najnevarnejši scenarij se vedno učimo postopke kako v takih primerih postopati in kako 4 REZULTATI deliti zrak iz jeklenke s pomočjo oktopusa. V tem primeru je šlo za mešanico upoštevanja navodil, a ne v celoti. Sopotapljača sta Na tem mestu so predstavljeni primeri, v katerih smo bili fizično po postopku pregledala drug drugega in na površini je bilo prisotni in so potrebovali naši intervencijo s ciljem zagotoviti dihanje mogoče ne da bi na inštrumentih zaznali odstopanja. Ko varnost in zdravje tečajnikov. Tečajniki so bili od starosti 8- 55 pa se je potapljač spustil na 7m, mu delno odprta jeklenka ni let različnih predznanj in stopenj usposobljenosti. 619 dovajala dovolj zraka zato je težko dihal in na koncu bil prisiljen pomagalo, nekje na 4m globine ga je potisnilo na površino. To izplavati na površino. sicer ni bilo nevarno, a ustvari vseeno neprijeten občutek. Analiza: Na kopnem smo ugotovili, da je bila jeklenka le Analiza: na površini smo ugotovili, da so dodatne uteži iz delno odprta, kar je podobno kot pri pipi z vodo, kjer voda sicer žepa na nogah izpadle iz žepa, ko se je potapljač postavil teče ampak v majhnem curku. vertikalno na glavo. Rešitev: Opominjati potapljače na to možnost in ob prvem Rešitev: Uteži je potrebno pritrditi v žep s pritrdilnimi potopu na globino preveriti, če vsi lahko brez težav dihajo. vrvicami namenjenimi drugim vsebinam. Četrti primer se je zgodil po vaji izstrelitve boje v globoki 4.4 Izguba opreme vodi. Praviloma se najprej boja s sponko loči od jopiča, nato se Tukaj smo doživeli štiri različne primere. sponka pripne na vrv, boja se razvije in napolni z zrakom, drug Prvi je bil s tečajnico srednjih let, ki je najprej sezula plavutke, potapljač pa med dviganjem drži kolut z vrvico. Po tem postopku potem v paniki izvrgla regulator in se pognala iz 3m na površino. se varno dvigne na površino in bojo pospravi v prvotno obliko. Ker še ni obvladala kompenzatorja plovnosti je inštruktor Analiza: Med zvijanjem boje je tečajnik podal sponko napihnil njen jopič, da jo je dvignilo na površino. kolegu, ki je držal kolut in sponka je padla 7 metrov niže v blatni Analiza: Tečajnica je slabo pritrdila izposojene plavuti. del jezera. V teh primerih se ne more ugotoviti kje je predmet Rešitev: Obvezno preveriti ali so tečajniki pravilno namestili pristal, saj se skrije v blatni del dna. in pritrdili opremo. Rešitev: Označevalno bojo naj vedno pospravlja le ena oseba. Drugi primer je bil pri izvedbi potopa očeta in sina, ki sta pravkar kupila novo opremo in sta oba že imela nekaj opravljenih potopov na Maldivih. Testirala sta nova jopiča z integriranimi utežmi (namesto, da so uteži na pasu, so v posebnih žepih jopiča). Potop je potekal po planu najprej v eno smer po 5m globine in nazaj na globini 3m na izhodiščno mesti v Veliki Zaki (Slika 2) na Blejskem jezeru. Med potjo nazaj je sina izvrglo na površino. Analiza: Ko smo prišli na kopno smo ugotovili, da je med potopom izgubil del uteži z ene strani. Očitno žep integriranih uteži dovoljuje, da se uteži v krogličasti obliki(vrečka s svinčenimi kroglicami) lahko izmuznejo. Rešitev: V tem primeri je potrebno uporabiti eno večjo vrečko uteži ali pa klasične kvadrataste oblike. Slika 3: Škarpena – Savudrija, Hrvaška 4.5 Ribič, ribič me je ujel Blejsko jezero je precej poseljeno z ribami, prednjačijo somi, ščuke in krapi. Občasno se dogaja, da ribiči lovijo v bližini kopalnega dela v Veliki Zaki, kjer izvajamo potope. Konec avgusta smo izvajali »Discovery dive« poskusni potop z enim kandidatom. To je potop pred tečajem, ki se izvaja zato, da stranke ugotovijo ali jim potapljanje ustreza in se kasneje vključijo v certificiran tečaj OWD. Značilnost poskusnega potopa je, da se izvede le nekaj najnujnejših vaj praznjenja maske in dihanja z regulatorjem ter izenačevanja pritiska v ušesih. Med potopom se tečajnika drži zadaj za jeklenko in na mesto njega uravnava plovnost s pomočjo regulatorja na jopiču. Potop se je izvajal po načrtovani poti na globini 5m. Med povratkom smo opazili mesto z belimi kroglicami (vaba za ribe), ki jih ribič vrže Slika 2: Velika Zaka – Blejsko jezero v vodo na mesto kjer pričakuje ribe. Nekaj metrov za tem je potapljač na nogah začutili upor, kot da bi nekaj zadrževalo Tretji primer se je zgodil na potapljanju na morju v predelu gibanje. Tudi dodatno gibanje ni spustilo omejeno gibanje. Savudrije na Hrvaškem. Spustili smo se do 15m in med luknjami Potapljač je pokazal tečajniku naj počaka, instruktor je v skalnatem pobočju fotografirali morske živali (Slika 3). Da se nadzoroval tečajnika, medtem je potapljač uporabil nož in ne dvigne pesek se včasih potapljač postavi na glavo in tako prerezal zadevo, ki je preprečevala nadaljnje potapljanje. izvaja fotografiranje. V tem primeru je bila uporabljena suha Analiza: Na kopnem smo ugotovili, da se potapljač ni ujel v obleka, ki je še bolj občutljiva na vertikalen položaj saj se zrak v odvržen ribiška vrvica – laks, ampak ga je dejansko nehote ujel obleki premakne v noge potapljača in ga začne vleči proti ribič (Slika 4). površini. Potapljač je imel opravljen tečaj iz uporabe suhe Rešitev: Čim opazimo na obrežju ribiče moramo pot potopov potapljaške obleke in več potopov z njo. Poskusil se je rešiti s spremeniti na drugo stran, saj lahko ribič odvrže trnek vrč deset prevali naprej z popolnim izpustom zraka iz jopiča, a ni metrov vstran. 620 Analiza: Čoln je očitno pobral ali dostavil neko osebo na kopno med tem, ko smo mi izvajali potop. Pri mestu vstopa in izstopa smo imeli postavljeno opozorilno bojo, medtem ko se med potopom ne označuje kje so potapljači. Rešitev: V času, ko so na gladini čolni z izvenkrmnimi motorji spremenimo smer potopa na del jezera kjer ni nevarnosti za morebitno srečanje. Slika 4: Ribiški trnek v potapljaškem čevlju Slika 5: Som iz Blejskega jezera 4.6 Slabo pritrjena jeklenka 4.8 Neustrezna oprema Ena od prvih nalog potapljača je, da sam sestavi svojo opremo. Potapljanje zahteva kar nekaj kosov tehnične opreme, od obleke, Med drugim se na jopič pritrdi jeklenka v odvisnosti od sistema čevljev, rokavic, kapuce, maske, dihalke, jopiča plovnosti, z dvema ali tremi pasovi. Pritrdilni pasovi so narejeni iz mešanice jeklenke, pasa z utežmi ali integriranih uteži. Na začetku se vsa materialov, ki se v vodi delno raztegnejo, zato je potrebno pri oprema sposodi pri izvajalcu tečaja in se jo pred tem na kopnem pritrjevanju jeklenk še posebej preveriti trdnost. To naredimo tudi poskusno obleče in preizkusi. Pokazalo se je, da v nekaterih tako, da jopič primemo za držalo in večkrat potresemo in primerih to ni dovolj. opazujemo ali se jeklenka premika. Iz preventivnih razlogov se Po priporočilih PADI Divemaster priročnika [7] se masko zato uporabljata dva ali trije pritrdilni sistemi s sponkami. V tem izbere tako, da vsak poskusi nekaj mask in tista, ki se mu najbolj primeru je na kopnem vse delovalo v redu, med potopom pa je prilega se izbere kot prava. V našem primeru je tečajnik imel jeklenka zlezla navzdol in jo je držal le zgornji pomožni trak. Ker konstantno uhajanje vode iz zgornje strani maske kar je je to ena od vaj, ki jo potapljači opravljamo, je sopotapljač pod povzročalo zalivanje maske z vodo. To se je dogajalo kljub temu, vodo zategnil nosilni trak jeklenke in smo lahko s potopom da je maska na kopnem prilegala in tesnila. nadaljevali. Analiza: Tečajnik je imel posebno zaobljeno čelo, ki je Analiza: Nosilni trak se je v vodi raztegnil do take mere, da omogočalo tesnjenje, kadar je bila maska najnižje možno nad ni bilo več potrebnega oprijema. ustnicami. Čim se je maska premaknila pod nos je maska puščala. Rešitev: Opozarjati potapljače na to možnost. Obvezna Rešitev: Vizualno oceni obraz in čelo tečajnika. V takih izvedba kontrole med potapljačema pred potopom. Uporaba primerih je dobro imeti rezervno masko z manjšo površino med nosilnih trakov in sponk take vrste, ki zmanjšujejo to možnost. spodnjim in zgornjim robom maske. 4.9 Neupoštevanje navodil inštruktorja 4.7 Električni čoln Potapljanje je lep šport in dokler ne gre kaj narobe je vsem lepo Načeloma na Blejskem jezeru ni čolnov z izvenkrmnim in po malem adrenalinsko. Da se prepreči nesreče se ves čas motorjem, potapljače opozarjamo na plavalce, pletnarje, kanuje, usposabljan poudarja pomembnost upoštevanja pravil kajake in supe. Med tem, ko se motor na notranje izgorevanje potapljanja in navodil inštruktorja. Kot omenjeno že prej je prvi pod vodo sliši na več deset metrov, se električni izvenkrmni nivo certificiranega usposabljanja OWD že dovolj, da so motor s propelerjem sploh ne zazna. Med izvedbo ponedeljkovih potapljači sami odgovorni za svoje početje in zato pred potopi osvežilnih potopov je skupina petih potapljačev opravila planiran podpišejo obrazec, kjer se s tem strinjajo. Kljub temu se najdejo večerni potop z ogledom rib (Slika 5) pod lesenim pomolom za osebe, ki nevarnostim navkljub ne upoštevajo teh navodil. kopalce. V tistem delu je globina vode med 1,5m in 3m. Ko smo V bistvu sta se oba primera zgodila na istem potopu v se izpod podesta premikali proti drugemu delu pomola je nad nas Kostreni na Hrvaškem, ki je bil sestavni del AOWD, torej zapeljal čoln z električnim izvenkrmnim motorjem, ki je pomagal nadaljevalnega tečaja, kjer se lahko potapljač potopi do 30m. med treningom veslačev. Na srečo smo ga vizualno opazili in se Med tečajniki je bil tudi mladoletni fant, ki se že nekaj časa odmaknili na globino. Ker je bila ta skupina sestavljena iz potaplja, saj je njegov oče tudi potapljač s stopnjo Rescue diver certificiranih potapljačev, ki obvladujejo nevtralno plovnost med – Potapljač reševalec. Zaradi njegove omejitve globine na 20m potopom, ni prišlo do nesreče. se je morala cela skupina prilagoditi temu. Že med spustom na 621 nekje 10m globine je tečajnik plaval sem in tja in kazal prekomerno energijo. Spustili smo se do skalnatega previsa, ki se spušča daleč pod 20m globine. Pravilo je, da se potapljači v skupin ne potapljajo globje od inštruktorja. Seveda v tem primeru to ni bilo tako. Mladenič se je spuščal kar nekaj metrov pod mejo in šele na opozorila inštruktorja postavil v pravo višino. Zaradi črednega nagona so se nižje spustili tudi dve starejši potapljačici, ki nista kazali velikega zanimanja med uvodnim poročanjem in priporočilih inštruktorja. Na srečo noben od udeležencev ni imel posledic. Analiza: Zaradi večje globine so tem, ki so se potapljali nižje bolj spraznile jeklenke, zato smo morali predhodno prekiniti potop, da smo še v mejah normale izvedli priporočljiv varnostni postanek za tri minute na petih metrih globine. Rešitev: Pred potopom tudi z izkušenimi potapljači ponoviti Slika 6: Vstop v vodo iz pomola pravila potapljanja on previsih. 4.11 Primerjava izkušenj z opisanimi primeri v 4.10 Napačen vzgib za opravljanje tečaja PADI Divemaster priročniku Tečaj OWD zahteva kar nekaj spretnosti in psihofizičnih Kot omenjeno pred tem ima PADI sistem poudarek na sposobnosti udeležencev. Vsaj na začetku je za tečajnike to kakovosti, pri svojem delu uporabljajo ustrezne ISO standarde in stresno saj se znajdejo v povsem drugačnih pogojih kot na imajo dolgo obdobje delovanja v katerem se sproti učijo in kopnem. Na tem mestu predstavljamo dva primera, ko je napačen prilagajajo. V priročniku [7] na strani 69 je opisanih okoli 100 vzgib za opravljanje tečaja botroval prekinitvi tečaja oziroma primerov težav, ki jih imajo potapljači med izvajanje 24 vaj iz spoznavnega potopa. potapljanj. Pred vsakim poglavjem so opisani podobni primeri Prvi primer se je zgodil v avgustu, ko sta se na poskusni težav iz realnih primerov, kot smo jih doživeli tudi mi sami, s potop prijavila oče in njegova 8 letna hčerka. Na začetku sta bila tem, da so se v priročniku nekateri končali tragično. Kljub vsemu ba navdušena, pomagali smo jima pri oblačenju in opremi in ju pa nikoli ne bomo pripravljeni na vse situacije, ki nas čakajo. postavili v nizko vodo. Pri punčki smo vedno držali njeno Samo dobra pripravljenost in strokovna podkovanost bo jeklenko, ker sama še ni obvladala kontroliranega plavanja. Med preprečila ali vsaj zmanjšala morebitne težave in posledice. In tem, ko rid raslih že med poskusnim potopom opravimo nekaj kot nas uči priročnik, v primeru težav se najprej za trenutek ustavi, nujnih vaj, jih v programu Bublemaker za otroke ne, saj so za to oceni situacijo, poišči več rešitev, izberi najustreznejšo in po tem še premladi in ni dovolj planiranega časa, da bi se to izvedlo. ovrednoti to rešitev. Otroku se razloži kako zadeva deluje, kako se izenači pritisk v Iz pričujočega je razvidno, da obštudijska dejavnost ušesih in znake s katerimi se pokaže, da je vse v redu ali da nekaj »Organizacija in usposabljanje iz potapljanja« zahteva dobro ni v redu. Prvi poskusi plavanja pod vodo z regulatorjem so bili pripravljenost vseh sodelujočih in obvezno sodelovanje z s punčko uspešni, nato je čakala, da oče opravi zahtevane vaje. certificiranimi inštruktorji v bližnjih potapljaških centrih. Še preden smo se dejansko odpravili na poskusni potop je punčka zahtevala, da gre iz vode in da ne bo nadaljevala. Analiza: Deklica je šla na potop na željo očeta. Med pripravo 5 ZAKLJUČEK smo se več ukvarjali z očetom kot z deklico, zato ji je postalo V prispevku smo predstavili nekaj izkušenj pridobljenih med dolgočasno. Deklica je kazala znake strahu, torej to ni delala iz izvajanjem različnih stopenj izobraževanj iz potapljanja po veselja, kot ostali otroci, ki se prijavijo po lastni želji. sistemu PADI na Blejskem jezeru in nekaj iz potopov na morju. Rešitev: Ločiti usposabljanje za otroka in odraslega tako, da Iz predstavljenega je razvidno, da potapljanje zahteva resen vsak inštruktor ali Divemaster delata s svojim kandidatom. Pred pristop in vnaprejšnje predvidevanje. Z vsakim odstopanjem od potopom se pri otroku preveri ali je njegova želja, da gre na potop. pravil se povečuje verjetnost za ogrožanje zdravja ali celo Drugi primer je je zgodil kmalu za tem, tokrat trije prijatelji življenja potapljačev. Primerjava s primeri iz PADI Divemaster jamarji in en gasilec opravljajo OWD tečaj. Že pri vajah na priročnika je pokazala, da so naše izkušnje v mejah običajnega suhem med sestavljanjem opreme se je pri enem od jamarjev in da smo ustrezno ukrepali, saj ni bil nihče poškodovan. opazilo, da mu sestavljanje ne gre najbolje in da ni naštudiral Izkušnje nam bodo služile pri izvajanju tečajev potapljanja s teoretične osnove. Sledil je prvi dan praktičnih vaj v nizki vodi. študenti. Potrebna bo posebna pozornost na napake, ki so Kandidat je imel velike težave s praznjenjem maske in vajami značilne za mlade in adrenalinske tečajnike. kjer je moral uporabljati regulator. Nenavadno je bilo tudi to, da ga je bilo strah vstopiti v vodo iz pomola nekje 50cm na gladino LITERATURA IN VIRI (Sloka 6). Večkrat je tudi omenjal, da on nekaterih vaj pač nebi [1] WERBER, Borut. Prednosti in zahteve izvedbe kreditno ovrednotene dela, ker mu ne ustrezajo. Kljub posebnim naporom, da je opravil obštudijske dejavnosti na primeru usposabljanja v konferenčnem zborniku: ŠPRAJC, Polona (ur.), et al. 40. mednarodna konferenca o vse vaje prvega dne, ga drugi dan ni bilo na tečaj. razvoju organizacijskih znanosti: [online, Ms Teams, March 17 - 19, Analiza: Ugotovili smo, da se je na tečaj prijavil zaradi stave 2021]. 1st ed. Maribor: University of Maribor, University Press, 2021. Str. 1145-1153. DOI: https://doi.org/10.18690/978-961-286-442-2.77. s kolegi jamarji. [2] Statut univerze v Mariboru, (2020). Dostopno na naslovu Rešitev: Pri vsakem tečajnika preveriti razlog prijave na tečaj https://www.um.si/univerza/dokumentni- in jih opozoriti, da tečaj zahteva kar nekaj psihofizičnega truda. center/akti/GlavniDokumenti2013/Statut%20Univerze%20v%20Maribor 622 u%20- [4] PADI – priznavanje kreditnih točk Dostopno na naslovu %20uradno%20pre%C4%8Di%C5%A1%C4%8Deno%20besedilo%20( https://www.padi.com/college-credit (6.9.2021) UPB%2013).pdf (6.9.2021) [5] PADI eLearning. Shema izobraževanja, Dostopno na naslovu [3] Pravilnik o kreditno ovrednoteni obštudijski dejavnosti na Univerzi v https://apps.padi.com/scuba-diving/elearning/helpme.aspx Mariboru, št. 012/2019/1, 1 (2019) (testimony of Univerza v Mariboru). [6] PADI Technical diving Dostopno na naslovu Dostopno na naslovu https://www.um.si/univerza/dokumentni- https://www.padi.com/courses?activity=technical- center/akti/GlavniDokumenti2013/Pravilnik%20o%20kreditno%20ovred diving&sort=popularity noteni%20ob%C5%A1tudijski%20dejavnosti%20na%20UM.pdf [7] PADI DIVEMASTER Manual (2020), PADI,(rev. 04/202) Verzija 3.01 (6.9.2021) ISBN: 978-1-878663-07-8 623 Šolanje na daljavo v digitalnem okolju Distance learning in the digital environment Samo Žerjal Osnovna šola Kozara Nova Gorica Kidričeva 35 5000 Nova Gorica, Slovenija samo.zerjal@os-kozara.si POVZETEK 1 UVOD V letu 2020 smo na naši šoli prvič prišli v položaj, ko smo zaradi Danes je zelo veliko spletnih orodij, ki omogočajo tudi delo na ukrepov za preprečevanje širjenja okužbe z novim daljavo. Učitelji pri svojem delu uporabljamo različna IKT koronavirusom morali prekiniti normalen potek šolanja. To je orodja. Doslej smo šolske spletne učilnice za učence imeli pomenilo zaprtje šol in začetek poučevanja na daljavo. Zato smo postavljene znotraj Arnesovih spletnih učilnic, učitelji pa smo morali pripraviti in sprejeti več prilagoditev, ki so bile potrebne gradiva shranjevali lokalno na računalnikih, oziroma v oblačne zaradi drugačnega načina poučevanja. V zelo kratkem času smo storitve, kot so Google Drive ali Oblak 365, v primeru, da so bili se morali prilagoditi novim razmeram. Glede na to, da naša šola dokumenti namenjeni skupni rabi. Odločili smo se, da v skladu s vzgaja in izobražuje učence s posebnimi potrebami so nas nove priporočili in usmeritvami, ki smo jih prejeli s strani Zavoda RS okoliščine še dodatno silile k razmisleku, na kakšen način za šolstvo [1] in na podlagi primerov dobre prakse, skupaj prilagoditi vsebine, oblike in metode dela. Google znotraj paketa izberemo in pripravimo novo sodobno spletno okolje za potrebe Workspace for Education ponuja nabor sodobnih spletnih orodij, šolanja na daljavo. ki uporabnikom ponuja veliko prostora za kreativnost in sodelovanje, hkrati pa ne zahteva daljšega uvajanja, saj se storitev izkaže kot uporabniku prijazna. Prispevek predstavi 2 PRIPRAVA SPLETNEGA OKOLJA pripravo in uporabo nekaterih aplikacij pri načrtovanju in izvedbi Pri odločitvi glede izbire spletnega okolja, ki bi čim bolj olajšalo pouka v digitalnem okolju. Podrobneje so predstavljene tiste prenos znanja na daljavo smo na šoli zasledovali sledeče kriterije aplikacije, ki so se pokazale kot primerne za naše potrebe. [2]: • Funkcionalnost oziroma uporabnost spletnih strani – KLJUČNE BESEDE je lastnost spletne strani, da izpolni potrebe, zahteve Google Workspace for Education, spletno okolje, spletna mesta, in želje uporabnika z vidika koristnosti in obrazci, spletna komunikacija uporabnosti. Stopnja uporabnosti strani je odvisna predvsem od vsebine ter kako učinkovito lahko njeni ABSTRACT uporabniki uporabljajo njene funkcije. In 2020, we witnessed for the first time a situation where, due to • Oblikovna podoba strani – vsebuje nabor različnih measures to prevent the spread of new coronavirus, we had to elementov kot so možnosti dodajanja grafičnih postpone the normal course of schooling. Schools closed down elementov, barv, ozadij, gumbov, ikon, besedil, and all teaching became remote. We therefore had to prepare tipografij, fotografij, ipd. several changes to support new ways of learning. We had to adapt • Interaktivnost spletne strani – postavlja obiskovalca v to the new situation in a very short time. Given that our school aktivno vlogo. S pomočjo različnih aplikacij in educates students with special needs, new circumstances forced obrazcev lahko učinkovito preverjamo zastavljene us even further to consider how to approach the content, forms cilje in ustvarimo dvosmerno komunikacijo z and methods of work. Within the Workspace for Education udeleženci. packages Google offers modern online tools that give users • Navigacijski sistem – je namenjen hitremu, plenty of room for creativity and collaboration. Their preglednemu in enostavnemu dostopu do informacij. implementation is quick and user-friendly. The paper presents Bistvenega pomena je, da se uporabnik na spletnih the set up and use of certain applications in the planning and straneh zna samostojno in hitro orientirati. implementation of lessons in the digital environment. Those Na podlagi analize stanja smo se odločili, da novo spletno applications that turned out to be more useful for our okolje zgradimo s pomočjo storitve Google Workspace for requirements are presented in more detail. Education. Za osnovno okolje smo izbrali aplikacijo Google KEYWORDS Sites. Aplikacija uporabnikom omogoča ustvarjanje in urejanje spletnih mest na spletu, hkrati pa sodelovanje z drugimi Google Workspace for Education, web environment, websites, uporabniki v realnem času [3]. forms, online communication Google račun nam z istim uporabniškim imenom in geslom omogoča dostop do večine Googlovih izdelkov. Za dostop do paketa Google Workspace for Education je za šole potrebna 624 registracija [4]. Šola z uspešno registracijo pridobi svojo lastno 3 UPORABA SPLETNIH ORODIJ domeno. Po uspešni registraciji pridobi oseba z dodeljenimi ustreznimi pravicami dostop do upravnega središča (Slika 1) in s 3.1 Spletna mesta tem možnost urejanja določenih sistemskih nastavitev. V Google Sites je strukturirano orodje za ustvarjanje wiki in razdelku - skrbnik dostopamo do naslednjih podrazdelkov: spletnih strani [3]. Do storitve lahko dostopamo z enkratno • Imenik (directory) – na tem mestu lahko dodajamo ali prijavo v Google račun, ki predstavlja enkratno avtentikacijo. brišemo uporabnike, urejamo njihove e-naslove, gesla Na OŠ Kozara Nova Gorica je skrbnik organizacije najprej na za dostop, jih razvrščamo v skupine, spreminjamo šolski spletni strani ustvaril povezavo do začetnega spletnega dostopne pravice na različnih nivojih ter spremljamo mesta (Slika 3). Na tem mestu je lahko vsak uporabnik opravil njihovo aktivnost po skupinah. prijavo v Google račun in poiskal ustrezno povezavo do • Naprave (devices) – na tem mestu lahko pridobimo spletnega mesta. informacije o vpisanih uporabnikih, času zadnjega vpisa ter katero vrsto naprave in operacijski sistem pri tem uporabniki uporabljamo. • Aplikacije (apps) – storitev vključuje velik nabor spletnih aplikacij, kot so npr. Gmail, Drive, Docs, Calendar, Sheets, Slides, Chat, Forms, Sites, Meet, itd., ki jih lahko na tem mestu upravljamo. • Varnost (security) – urejamo lahko nekatere varnostne nastavitve. • Račun (account) – po potrebi lahko poljubno spremenimo spletne naslove za dostop do nekaterih spletnih aplikacij. Slika 3: Začetno spletno mesto Ustvarimo lahko večje število spletnih mest, ki jih smiselno hierarhično uredimo. Vsakemu spletnemu mestu lahko dodajamo podstrani in na ta način organiziramo delo po tednih oziroma dnevih. V razdelku spletna mesta najprej izberemo možnost – začetek novega spletnega mesta. V novem zavihku lahko poljubno poimenujemo novo spletno mesto, dodajamo podstrani ter spreminjamo grafično podobo celotne strani z izborom različnih tem in gradnikov. Poleg tega imamo integrirano možnost vstavljanja datotek oziroma spletnih povezav. Slika 1: Upravno središče Udeleženca lahko pritegnemo z vstavljanjem lastnih multimedijskih vsebin, spreminjamo velikost, barvo in obliko 2.1 Organizacija skupin pisave, učne vsebine prikažemo s pomočjo pripravljenih dokumentov, predstavitev in grafikonov. Znanje lahko V podrazdelku – imenik, skrbnik organizacije najprej ustvari preverjamo ob pomoči izdelanih obrazcev ali s povezavo do skupine uporabnikov (Slika 2). Na naši šoli smo delo organizirali drugih spletnih aplikacij, če želimo doseči večjo interaktivnost tako, da so bile skupine ustvarjene po oddelkih, dostop pa imajo (Slika 4). samo člani. Učenci so bili uvrščeni v ustrezno skupino, glede na oddelek, ki ga obiskujejo, učitelji pa v tisto skupino - oddelek, kjer poučujejo. Učencem so bile dodeljene pravice bralca, učiteljem pa pravice urejevalca. Slika 4: Spletno mesto 5. razreda 3.2 Obrazci Google Forms predstavlja učinkovito orodje za zbiranje Slika 2: Organizacija skupin informacij v obliki različnih vprašalnikov oziroma kvizov. V razdelku obrazci izberemo možnost - začni nov obrazec. Nato v 625 nastavitvah določimo vrsto obrazca. Če izberemo možnost kvizi, lahko odgovore na vprašanja tudi točkujemo. Obrazcem lahko s spreminjanjem teme določimo tudi grafično podobo, Izbiramo lahko med različnimi tipi vprašanj, kot so vprašanja z izbirnimi odgovori, vprašanja odprtega tipa, ali npr. v obliki linearnih lestvic. Po želji lahko dodajamo poljubne slike ali videoposnetke z YouTuba. Končni izgled kviza lahko sproti preverjamo s klikom na možnost – predogled (Slika 5). Obrazec lahko učencem posredujemo na različne načine. Prvi način je, da uporabimo njihove e-naslove, kjer imamo možnost pošiljanja po skupinah. Vprašalnik lahko posredujemo tudi s kopiranjem URL povezave, oziroma vstavimo na spletno mesto v obliki HTML kode. V zavihku - odzivi lahko pregledujemo odgovore učencev, po posameznih učencih, vprašanjih ali skupno. Slika 6: Aplikacija Google Chat 3.4 Prednosti uporabe spletnih aplikacij v Google Workspace for Education Prednost uporabe Google Workspace for Education je enotna prijava z enim uporabniškim imenom in geslom za uporabo vseh storitev. Z aplikacijo Google Sites lahko učitelji na preprost način dodajamo, urejamo in prilagajamo digitalne vsebine. Pri tem nam je na voljo veliko orodij, ki so že integrirana v samo storitev, kar zelo poenostavi delo ter pušča uporabniku veliko prostora za individualnost. Prav tako je sam uporabniški vmesnik zelo pregleden in enostaven za uporabo, storitev pa deluje preko spleta, ne glede na lokacijo uporabnika. Z aplikacijo Google Forms učitelji pridobimo in zbiramo različne potrebne informacije, ki nam lahko služijo pri evalviranju dosedanjega ter načrtovanju nadaljnega dela. Uporabniki s storitvijo pridobimo tudi možnost uporabe sodobne elektronske komunikacije, kot je uporaba elektronske pošte Gmail s šolsko domeno in drugih orodij za spletno komuniciranje. 4 ZAKLJUČEK V šolskem letu 2019/2020 smo na šoli v času šolanja na daljavo Slika 5: Matematični kviz izdelan s pomočjo Google Forms prvič preizkusili delovanje storitve Google Workspace for Education. Znotraj ponujenih orodij smo skrbno izbrali tiste, v 3.3 Spletna komunikacija katerih smo prepoznali dodano vrednost za naše delo. Zaradi Vsak uporabnik šolskega računa ob prijavi pridobi tudi svoj pozitivnega odziva pri uporabnikih smo zato v šolskem letu šolski elektronski naslov za uporabo elektronske pošte Gmail. 2020/2021 ustvarili dodatno spletno okolje za primer izvajanja Pošto se lahko prejema in pošilja tako iz računalnikov, kot tudi hibridnega modela šolanja, ki predvideva delno izvajanje pouka iz mobilnih naprav. Spletno komunikacijo prav tako omogočata v šoli, delno na daljavo. aplikaciji Google Chat (Slika 6) in Google Meet. Slednji v obliki videokonferenc. LITERATURA IN VIRI [1] Priporočila in usmeritve za pouk na daljavo za osnovno šolo. Zavod RS za šolstvo. Dostopno na naslovu: https://www.zrss.si/stiki-s-prakso/podpora- pouku-na-daljavo/usmeritve-in-priporocila/priporocila-in-usmeritve-za- pouk-na-daljavo-za-osnovno-solo/ (16. 8. 2021). [2] Plevnik D. (2004). Analiza spletnih strani in njihova uporabnost. Diplomsko delo. Ljubljana, Univerza v Ljubljani: Ekonomska fakulteta. [3] Google Sites. Dostopno na naslovu: https://en.wikipedia.org/wiki/Google_Sites (13. 8. 2021). [4] Google Workspace Admin Help. Dostopno na naslovu: https://support.google.com/a/answer/134628 (13. 8. 2021). 626 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek H Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume H Delavnica URBANITE 2021 URBANITE Workshop 2021 Uredniki / Editors Sergio Campos, Shabnam Farahmand, Nathalie van Loon, Erik Dovgan http://is.ijs.si 8. oktober 2021 / 8 October 2021 Ljubljana, Slovenia 627 628 PREDGOVOR Delavnica URBANITE bo forum za predstavitev najsodobnejših mobilnostnih rešitev v urbanem okolju s poudarkom na prebojnih tehnologijah, kot so umetna inteligenca, sistemi za podporo odločanju, analitika velikih podatkov in napovedni algoritmi, ki se uporabljajo pri analizi podatkov o mobilnosti, napovedovanju dogodkov in podpori javnim upravam pri sprejemanju strateških odločitev. Delavnica je aktivnost projekta URBANITE. Vabimo prispevke akademskega sveta, industrije in oblikovalcev strategij na področju mobilnosti in pametnih mest. Delavnica se bo osredotočila na naslednje teme v okviru mobilnosti v pametnih mestih: • Umetna inteligenca • Inteligentni sistemi • Strojno učenje • Podatkovno rudarjenje • Sistemi za podporo odločanju • Analitika velikih podatkov • Dejavnosti soustvarjanja • Socialni vidiki • Urbana preobrazba FOREWORD The URBANITE Workshop will be a forum for presenting the state-of-the-art solutions for the urban mobility with the focus on disruptive technologies such as artificial intelligence, decision support systems, big data analytics and predictive algorithms, which are applied in mobility data analysis, eventualities prediction, and supporting public administrations in making policy- related decisions. The workshop is an activity of the URBANITE project. We welcome papers from the academia, the industry, and the policy makers in the mobility and smart cities fields. The workshop will focus on the following topics within the scope of mobility within smart cities: • Artificial intelligence • Intelligent systems • Machine learning • Data mining • Decision support systems • Big data analytics • Co-creation activities • Social-related aspects • Urban transformation 629 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Sergio Campos Cordobes (co-chair) Shabnam Farahmand (co-chair) Nathalie van Loon (co-chair) Denis Costa Yury Glickman Maria José López Giuseppe Ciulla Maria Suberbiola Dino Alessi Massimo Villari Matjaž Gams Maj Smerkol Erik Dovgan (local chair) 630 How Disruptive Technologies can Strengthen Urban Mobility Transformation. The Experience of URBANITE H2020 Project Giuseppe Ciulla Roberto Di Bernardo Isabel Matranga Research & Development Laboratory Research & Development Laboratory Research & Development Laboratory Engineering Ingegneria Informatica Engineering Ingegneria Informatica Engineering Ingegneria Informatica Palermo, Italy Palermo, Italy Palermo, Italy giuseppe.ciulla@eng.it roberto.dibernardo@eng.it isabel.matranga@eng.it Francesco Martella Giovanni Parrino Shabnam Farahmand Engineering Department, University Engineer - Municipality of Messina Forum Virium Helsinki Oy of Messina - ALMA Digit S.R.L. Messina, Italy Helsinki, Finland Messina, Italy nanni.parrino@gmail.com shabnam.farahmand@forumvirium.fi fmartella@unime.it ABSTRACT challenges when managing and planning mobility, combining new forms of mobility, that must coexist in the urban structure URBANITE (Supporting the decision-making in URBAN trans- of modern cities, in compliance with the well-being of citizens formation with the use of dIsruptive TEchnologies) is an H2020 and protection of the environment. project (started in April 2020) investigating the impact, trust The concrete adoption of disruptive technologies in the decision- and attitudes of civil servants, citizens and other stakeholders making processes can represent the pivoting point for a paradigm concerning the introduction and adoption of disruptive technolo- change in the management of mobility. Decision Support Sys- gies (e.g. AI, Decision Support Systems, big data analytics) in tems, Artificial Intelligence, predictive algorithms, simulation decision-making processes related to the planning and manage- models, Big Data analytics, etc. offer the opportunity to analyse ment of urban mobility. The project experiments and validates its the current mobility situation, identify present and future trends approaches and tools in the context of four real use cases in the allowing to predict potential future mobility scenarios [6], [9]. cities of Amsterdam (NL), Bilbao (ES), Helsinki (FI) and Messina Our investigation focuses on four European cities distributed (IT). This article summarises the main findings matured during in four different countries: Amsterdam, Bilbao, Helsinki, and the first half of the project in the four cities, their main mobility Messina. Each of them offers a different perspective on urban mo- issues and how disruptive technologies can play a role in support- bility, in terms of characteristics, offered services and challenges. ing the decision-making process to solve them. Despite the four Section 2 presents the four cities, their general characteristics, cities face different kinds of mobility issues and are characterised the specific urban mobility issues they are currently facing, and by different levels of IT maturity, we identified a chain of three which kind of disruptive technologies (e.g. artificial intelligence, categories of technologies that can improve the efficiency and decision support systems, big data analytics, predictive algo- effectiveness of decision-making processes in all four cities: data rithms, simulation engines) can improve the decision-making access and harmonisation, data analysis and data visualisation. processes and how. Final considerations and conclusions are KEYWORDS reported in Section 3. Urban transformation, disruptive technologies, urban mobility, URBANITE project, decision making, data access, data analysis, 2 URBANITE CITIES data visualisation. 2.1 Amsterdam 1 INTRODUCTION Amsterdam, the capital of the Netherlands, in recent years has been growing rapidly in terms of inhabitants and visitors; this Today’s cities are facing a revolutionary era in urban mobility; growth leads to increased mobility and traffic issues. The city this is due to different factors, among the others their continuous has complex traffic streams with massive amounts of bicycles growth and the concentration of human activities. To prevent combined with cars and public transport; this drives the need and solve problems related to mobility such as traffic congestion for finding solutions that can conciliate the ever-growing use and air pollution (for instance due to PM ) and its potential 2.5 of bikes with the other means of transportation (from public link with other risk factors (e.g. Covid-19 spread, as envisaged transportation to private cars) resulting in more sustainable mo- in recent studies [3], [4]), cities are in continuous search of ad- bility for the whole city. Part of this view is a strategy tending to equate mobility solutions to satisfy the demand of the growing increase the appeal of bikes as the main mobility option [5]. This population, both living in or moving around the cities every day. strategy goes through the improvement of the city network of As a result, decision-makers have to face more and more complex bike lanes and of the overall cycling experience within the city, encouraging virtuous behaviours (e.g. respect of traffic lights) to 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 avoid potential discomfort. 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). What Amsterdam is aiming for. To reach these objectives the Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia city of Amsterdam would like to align the mobility policies to © 2021 Copyright held by the owner/author(s). the real needs of bike mobility, realise a data-driven decision 631 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ciulla, et al. mechanism, strengthen the safety and comfort of cycling, and What Bilbao is aiming for. To reach its objectives, the city encourage citizens to make sustainable mobility choices. of Bilbao aims to obtain a global vision of the city in terms of sustainable mobility, to take decisions based on updated data The role of disruptive technologies in Amsterdam. From a broader (predicting the impact resulting from applied measures), follow a perspective, a unique point to access data coming from different more agile decision-making process (facilitating communication sources can support the decision-makers in the identification of between stakeholders involved in the definition and development the required information, reducing the time spent to search it of the SUMP), translate measures impact into health and life and speeding up the decision-making process. Since different quality indicators and access data coming from scattered sources departments of the municipality (i.e. civil servants) are involved that is automatically collected and integrated. in decision-making, the possibility to easily share information The role of disruptive technologies in Bilbao. In the context of among them (such as data, results of analysis/simulations, map Bilbao, it is essential that decision-makers can easily access the layers, charts, graphs) would improve collaboration and over- most updated data; in this sense tools that facilitate the con- come inefficient communication and silos, allowing at the same nection of data sources and the data harmonisation (leveraging time the reduction of policy fragmentation and the subsequent common and well-defined data models) would support decision- uncertainties. From a more specific perspective, data analysis makers in their daily activities. Once data is collected, a data tools can support decision-makers in understanding different catalogue (as a unique point of access to the data) would offer the aspects of bike mobility (through the analysis of bike-related capabilities to search data considering different criteria; among data) and in identifying dependencies among factors that could them, the possibility to filter the available data by for example the influence directly or indirectly bike mobility and its adoption. “transport mode" would allow the decision-makers to reduce the In this sense tools and models to simulate how decisions and time they spend to identify the data they need. Facilitated setup policies can potentially impact on traffic and mobility would offer and execution of simulations (for instance, to forecast impact on predictions and the possibility to compare different scenarios. traffic, mobility patterns or SUMP’s KPIs resulting from a mea- This would allow decision-makers to make choices with minimal sure/policy applied) would support the decision-making process negative impact and to minimize related costs. Finally, effective reducing the time spent in performing those simulations. Tools visualisation of information is essential; a dashboard offering to create charts and graphs that summarise the status of mobility map layers, charts and graphs that summarise the status of bike in the city from the sustainability point of view would allow the mobility in the city would allow decision-makers to have, in a decision-maker to have, in a single view, the overall and relevant single view, the overall and relevant information they need to information to globally monitor the mobility in the city. On the gain new insights about bike mobility in the city (e.g. type of road other hand, the possibility to define and create customised KPIs infrastructure/ bike paths, road safety level, traffic mix/sources, and indicators would allow the decision-makers to fine-tune the congested routes, cleaner routes in terms of air quality, greener dashboards with all the relevant information that they need to routes, faster routes). take into account in the planning of the mobility in the city. To this aim, checking if the data is updated would allow the creation 2.2 Bilbao of analyses and simulations based on correct information that 2 With an area of 41,60 km and around 355,000 inhabitants, Bilbao represents the real status of the city, whereas pre-processing of is the heart of a metropolitan area that extends along the estuary collected data would reduce the time needed to setup the analysis of the Nervioén River with a population close to 1 million peo- and simulation for decision-making processes. ple. In the last 25 years, Bilbao has suffered an important urban transformation from an industrial economy to a city based on a 2.3 Helsinki service economy. This has helped to balance the city and provide Helsinki, the capital of Finland, is a continuously evolving and a friendly environment for pedestrians with wider pavements, developing city. In this sense a particular example is represented reduction of on-street car parking in the city centre, traffic light by the Jaétkaésaari area. The shore area of Jaétkaésaari, literally control system to cater for pedestrians and promenades for walk- meaning “Dockers’ Island”, was previously used for industrial ing and cycling. Today, 65% of internal movements are produced and harbour purposes; now it has gradually transformed itself on foot. In this context, the Sustainable Urban Mobility Plan into a residential area offering workplaces and services. At the (SUMP) [8] in Bilbao plays a significant role; its main objectives same time, Jaétkaésaari is also a growing passenger and trans- are: port harbour due to its location (right adjacent to the centre of • Helsinki). The harbour is the main connection between Helsinki Reducing air and noise pollution. • and Tallinn, with growing mobility and opening of a new terminal Improving safety by reducing accidents and fatalities. • in 2017. Annually 1 million private cars travel on the connection Guaranteeing universal accessibility. • where a single main road leads in and out of Jaétkaésaari. This Improving energy and transport (passengers and goods) road feeds directly to the largest car commuting junction (70.000 efficiency. • cars daily) from the city centre to the western suburbs of Helsinki, Contributing to improve the attractiveness and environ- creating interference. The Jaétkaésaari area is emblematic of the mental quality of the city. overall development Helsinki is facing, in particular, concerning Of particular interest is the “Pedestrian mobility strategy” aim- mobility. In this context, to correctly cope with this evolution, ing to promote non-motorized modes of transport (especially the City of Helsinki’s traffic planning and traffic management pedestrian displacement) since these best suit the sustainable need up-to-date and high-quality traffic information to support mobility objectives. Part of this strategy is the transformation of data-driven decision making. In addition, proactive and forward- Moyuéa plaza, for exclusive use of public transport, pedestrians, looking approach is needed as the population of the metropolitan and cyclists, prohibiting private traffic. area grows and traffic situation changes. 632 How Disruptive Technologies can Strengthen Urban Mobility Transformation. Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia What Helsinki is aiming for. In this context, the City of Helsinki other hand, the challenge consists in optimising the management aims to check the status of traffic and its development, analyse and interaction among the different mobility and monitoring how traffic could evolve, perform traffic forecasts, simulate traffic systems and services available in the urban area of the city of planning and land use, check the development and implementa- Messina reducing the waste of resources and costs for the Public tion of new infrastructures and policies, develop a master plan Administration. A particular attention is paid on light mobility for city development (e.g. land use, mobility, housing). To reach (e.g. extension of the cycle network with new bike-lanes and these objectives it is essential to establish a unique view and un- links between the centre and suburbs zones of the city to spread derstanding among traffic planning and urban planning, allowing the use of bicycle mobility [2]) and pedestrians (definition of an the exchange of information among different departments (over- integrated system of pedestrian areas and paths). coming information silos). In doing so, the city of Helsinki faces The role of disruptive technologies in Messina. The different some issues related to the availability of different map layers with Departments of the Municipality would benefit of a unique data- different information representations moving from a department access point to their data, avoiding the complication generated to another, the lack of people with competences for demanding by the need of accessing scattered data sources (for instance, in analysis, the lack of time to get deep understanding of data and the case of data hosted and managed in different repositories for problems related to obtain raw data to be analysed with external the different departments). This would simplify the discovery of tools. and access to the data needed by the decision-makers. In this con- The role of disruptive technologies in Helsinki. A data catalogue text, tools to facilitate the connection to data sources (also from as unique point of access that brings under the same umbrella the third parties) are vital. Data is the fuel of any activity related data produced by different departments would simplify the dis- to analysis, simulation and the more information is available covery and access of needed data, avoiding complications caused (not only in terms of amount but also in terms of variety), the by scattered repositories managed by different departments of the more accurate and precise can these analysis and simulations same organisation. The data catalogue could leverage tools for be. In this context, advanced smart devices and virtual devices the integration with existing ICT software and applications. This [7] (abstracted component characterized by specific high-level would allow on the one hand, the automatic check of information functionalities) offer the chance to access the needed informa- (e.g. automatic detection of inconsistencies in the data, such as tion with the most appropriate frequency and accuracy, avoiding missing mandatory fields, infringement of time constraints about information overload and allowing a more efficient computation. updates) and on the other hand, the automation of repetitive In the management of urban mobility, analysis and simulations tasks (e.g. extract relevant information and provide it in a more would support decision-makers in the identification of potential usable manner). Leveraging the data made accessible it would be solutions (such as multimodal paths and possible intervention to possible to define pre-packaged simulations that need only minor increase public safety) [1] and hidden problems (such as related operations to be executed (e.g. few parameters and/or initial in- to public transportation and for planning maintenance interven- put data). This would simplify the use of this kind of technology tions of road and public transportation vehicles). Customisable by personnel without specific competencies and skills who would dashboards to represent the information a decision-maker needs be able to set up an entire simulation from scratch, and reduce would allow to obtain a clearer view of the status of mobility, the time needed and the acceptance of this technology, since the supporting the decision-making process in the most appropriate personnel will not spend too much time to learn how to use it. manner. Finally, the possibility to share information (such as data, results of analysis/simulations, map layers, charts, graphs) with 2.4 Messina people working in the same or a different department would im- prove the collaboration and the efficiency of the decision-making The metropolitan area of Messina is one of the most extended process, overcoming inefficient communication and information urban areas in the south of Italy and the first in Sicily and counts silos. over 620.000 citizens. In the city of Messina alone, there are over 250.000 inhabitants and most of them are commuters between 3 CONCLUSIONS Sicily and Calabria regions. Geographical peculiarities (the ge- Despite their specific peculiarities such as organisational ap- ographical shape of the city of Messina is stretched for 32 km proaches and mobility needs to be satisfied, the cities of Ams- beside the Tirrenian sea, and tight between its hills and the sea) terdam, Bilbao, Helsinki and Messina have some commonalities and its role of main connection point between Sicily and the in terms of potential application of disruptive technologies that Italian peninsula have a huge impact on mobility in the city of can help their decision-making processes. The main aspect that Messina. The local transport system of the city consists of sea emerged is related to the need of data, as a vital element to transport (hydrofoil and ferry boats fleets) and land transport perform any decision-making activity; in this sense it is impor- (buses, tramway and rail transports network), operated by public tant to underline that here the need is related to the easiness and private companies. One of the main issues that affects both of accessing the data, that in most of the cases is scattered, or kinds of services (sea and land transport) is the lack of interop- represented using different data structures with non-uniform erability among the different departments of the Municipality standards. Uniform access to the data drives to another com- that are involved for different reasons in the management of the mon point among the four cities, that is the exploitation of the mobility. possibilities offered by simulation tools, in particular to forecast What Messina is aiming for. Concerning mobility, the main and predict the impact of decisions taken on traffic and mobility challenge of the city of Messina for the upcoming years is twofold: (such as the building of a new road, the creation of a LTZ). This on the one hand, to build mobility services able to fulfil the kind of technologies would allow the decision-makers to bet- needs of citizens, dwellers, commuters and visitors, allowing ter design mobility solutions and policies, giving the possibility them to move around and through the city seamlessly; on the to tackle complex problems and to evaluate the implications of 633 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Ciulla, et al. new policies. The third common point is the data visualisation. morbidity and mortality. International Journal of Environ- Accessed data and results obtained from simulations and data mental Research and Public Health, 17, 12. issn: 1660-4601. analysis must be visualised in an easy-to-understand manner, this doi: 10.3390/ijerph17124487. https://www.mdpi.com/1660- includes not only the data visualisation per se, but also the possi- 4601/17/12/4487. bility of creating customisable dashboards in which the decision [4] Chiara Copat, Antonio Cristaldi, Maria Fiore, Alfina Grasso, makers can arrange the information they need and represent it Pietro Zuccarello, Santo Signorelli, Gea Conti, and Margherita according to their preferences. From the result here summarised, Ferrante. 2020. The role of air pollution (pm and no2) in it is possible to clearly identify a chain of needs with their cor- covid-19 spread and lethality: a systematic review. Environ- responding solutions. The first link of the chain is the need of mental Research, 191, (August 2020), 110129. doi: 10.1016/j. accessing data. Here tools facilitating the connection to data envres.2020.110129. sources and the integration with existing IT systems can offer a [5] 2019. CYCLING MATTERS 2019, How Bicycles Power Ams- valuable solution to overcome information silos and to build a terdam. CITY OF AMSTERDAM. unique data-access point to available data, allowing also the har- [6] Alina Machidon, Maj Smerkol, and Matjaž Gams. 2020. Ur- monisation of the data thanks also to common and well-defined banite h2020 project. algorithms and simulation techniques data models and highlight the relevant information reducing for decision – makers. Proceedings of the 23rd International the time to find it. The second link of the chain is the analysis Multiconference INFORMATION SOCIETY, A, 68–71. of the data made accessible through the previous step and the [7] Francesco Martella, Giovanni Parrino, Giuseppe Ciulla, Roberto execution of simulation. Here it is important to highlight that Di Bernardo, Antonio Celesti, Maria Fazio, and Massimo beyond the possibility to perform analysis and simulation, avail- Villari. 2021. Virtual device model extending ngsi-ld for faas ability of tools that simplify and reduce the time needed to set at the edge. In 2021 IEEE/ACM 21st International Symposium them up play a key role. In this sense, pre-packaged simulations on Cluster, Cloud and Internet Computing (CCGrid), 660–667. ready to use, that guide the users in their setup, and tools, that doi: 10.1109/CCGrid51090.2021.00079. allow the creation of customised KPIs and indicators, represent [8] 2018. Plan de Movilidad Urbana Sostenible (PMUS) 2015-2030 an advantage for the decision-makers. The third and final link de la Villa de Bilbao, Fase II. Propuesta. Ayuntamiento de of the chain is the data visualisation. Here, tools (e.g. Wizards) Bilbao, Área de Movilidad y Sostenibilidad. guiding the users in the creation of charts, graphs, map layers, etc. [9] Maj Smerkol, Žan Počkar, Alina Machidon, and Matjaž offer the opportunity to speed up the decision-making process Gams. 2020. Traffic simulation software in the context of by reducing the time of interpreting and understating the infor- mobility policy support system. In Information Society 2020. mation. At the same time, the possibility to visualise different data in the same view through customisable dashboards offers the chance of obtaining a bird’s-eye view on the information that is relevant for each decision-maker, according to their specific needs. Considering the reported results, a final consideration can be made; even if cities could be characterised by a different IT maturity level, the most suitable way to effectively improve mobility decision-making processes is not a single technology, but a combination of disruptive technologies, that glued together unlock their respective potentialities and benefits. ACKNOWLEDGMENTS The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement N° 870338. This work was co- financed by the European Union - FSE, PON Research and In- novation 2014-2020 Axis I - Action I.1 "Dottorati innovativi con caratterizzazione industriale" REFERENCES [1] Lorenzo Carnevale, Antonio Celesti, Maria Di Pietro, and Antonino Galletta. 2018. How to conceive future mobility services in smart cities according to the fiware frontiercities experience. IEEE Cloud Computing, 5, 5, 25–36. doi: 10.1109/ MCC.2018.053711664. [2] Alessio Catalfamo, Maria Fazio, Francesco Martella, Anto- nio Celesti, and Massimo Villari. 2021. MuoviMe: secure access to sustainable mobility services in smart city, (Sep- tember 2021). [3] Silvia Comunian, Dario Dongo, Chiara Milani, and Paola Palestini. 2020. Air pollution and covid-19: the role of par- ticulate matter in the spread and increase of covid-19’s 634 An Overview of Transport Modelling Approaches – A Use Case Study of Helsinki Shabnam Farahmand Forum Virium Helsinki Unioninkatu 24, 00130 Helsinki, Finland shabnam.farahmand@forumvirium.fi ABSTRACT Furthermore, the transport planning techniques applied specifically by the City of Helsinki is included here. Section 4 In this paper a general view to transport planning approaches discusses URBANITE project’s global view and argues the have been articulated with a focus on the simulation models. To advantages and challenges ahead of mobility decision makers. this end, different analytical methods have been investigated with regard to the scope of target policies, geographic scales, and modelling techniques. The paper also provides an overview to 2 TRANSPORT PLANNING APPROACHES the transport planning approaches which are specifically applied There are different approaches to analyze characteristics of a in the City of Helsinki in close relation to the land use policies. transport network and to evaluate the outcomes of the strategic Besides, further discussions have been included to shed light on and/or ad-hoc interventions with the transport. Ni [5] considers the approach URBANITE project is seeking. Although there is the geographic scales of transport planning models and proposes still a need for overcoming the challenges regarding data-driven a framework which can enable multiscale traffic modelling decision-making, we see a potential in the project’s approach to which can be seen in Figure 1. In another study, Vassili [6] foster the use of disruptive technologies for accelerating the compares the transport analysis tools based on the scope and uptake of the evidence-based policies. complexity of research area and highlights the importance of KEYWORDS distinguishing between Analysis, Modelling, and Simulation (AMS) tools. Some of the tools for each scale of geographic Transport planning, scales of analytics, policy-making, transport analysis are already suggested in Figure 1. In addition to the modelling in the City of Helsinki, simulation geographic scale, the purpose of policy making processes to tackle a specific problem is also an important criterion in 1 INTRODUCTION defining the right approach. Larger geographic scale of analysis can be chosen to support policy making with less data granularity Transport planning plays a major role in defining the way public [7]. However, it is reasonable to opt for micro-scale analysis resources such as funds and spaces are used. Transport plans are when dealing with ad-hoc interventions in a specific area. This, mainly applied to understand the strategic capacity and on the other hand, becomes demanding on obtaining more consequences of high-level democratic decisions. Hence, it is detailed and comprehensive data. important to consider the political and societal preferences of relevant stakeholders including citizens [1]. This also explains the urge for developing transparent, open-source, and simplified solutions in order to evoke citizen engagement and public participation [2]. Moreover, the advantage of transport planning models most probably lays in the fact that the scope of identified solutions by these models are inherently geographic [3]. Geographic analysis and tools speed up the uptake of new technologies due to the power and potential to provide evidence for interventions in transport planning [4]. In the following, the different approaches to tackle transport problems based on analysis levels will be addressed. In section Figure 1. Scales of Transport Planning 3, a schematic framework for transport planning approaches is Approaches; Tools & Solutions suggested with the focus on analytical and simulation techniques. 3 TRANSPORT PLANNING APPROACHES 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 De Dios Ortúzar and Willumsen [8] structured the transport for profit or commercial advantage and that copies bear this notice and the full planning approaches into five main stages as problem citation on the first page. Copyrights for third-party components of this work must formulation, data collection, modelling and analysis, evaluation, be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia and implementation of the solutions. In this paper, a new © 2021 Copyright held by the owner/author(s). schematic framework is formulated based on Dios Ortúzar and 635 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Shabnam Farahmand Willumsen’s approach in Figure 2. The framework is modified research implicates that the analytical techniques are sort of in accordance with the approach of Helsinki Region Transport closed form mathematical equations which provide statistical (HSL) and URBANITE’s global view to provide a clear results such as forecasts and predictions. On the other hand, understanding of current applied techniques as well as a basis for simulations are physical mathematical models, the results of the comparison of the two approaches. which is to project objects moving around in a transport network. Australian Road Research Board [9] categorizes the problem- It is also possible to check the network state at different time solving techniques into analytical and simulation techniques. The stamps [9] & [10]. Figure 2. Proposed Schematic framework for Transport Planning1 between transport planning strategies as well as land use policies 4 TRANSPORT PLANNING – Use Case of has been come into our focus frequently. Stover and Frank [13] Helsinki suggested that development of transport and land use affect each other continuously in a cycle which is illustrated in Figure 3. The techniques used by the Helsinki Region Transport (HSL) follow an analytical approach to enable strategic transport and land use planning for the city. The model is called “HELMET” and is built with the help of proprietary tool EMME 2 . The statistical mathematical models in the field of transport models are usually referred as travel demand models when considered on a macro-level. These models have Four Step Transport Model (FSM) as the basis although they have evolved to more advanced levels to encompass the intelligence of models’ agents [11]. The last version of HELMET model is therefore considering agent- based modelling (ABM) approach when it comes into trip chains analysis [12]. Helsinki Region Transport (HSL) developed its Sustainable Urban Mobility Plan (SUMP) for the City of Helsinki in 20153. In particular, this plan focuses on 1) strengthening the strategic capacity and effectiveness, 2) integrating transport and land use, and 3) clarifying transport policy choices as well as the roles of different modes of transport. According to the SUMP of Helsinki and on the basis of Figure 3. Transportation Land Use Cycle interviews performed with the City stakeholders, the interrelation 1 In blue: the main stages of transport planning processes; in yellow: URBANITE’s global view 2 https://www.inrosoftware.com/en/products/emme/ 3http://www.bsr-sump.eu/good-example/helsinki-region-transport-system-plan-hlj-2015 636 An Overview of Transport Modelling Approaches – A Use Case Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Study of Helsinki Bearing this in mind, the proposed use case scenarios aim to find 3. Lovelace, R., Open source tools for geographic analysis in out the outcomes of the following decisions: transport planning. Journal of Geographical Systems, 2021: p. 1-32. 4. Jäppinen, S., T. Toivonen, and M. Salonen, Modelling the 1. Intervention with the traffic network e.g., building a tunnel potential effect of shared bicycles on public transport travel on the west harbor’s junction to lead the main stream of times in Greater Helsinki: An open data approach. Applied heavy-duty vehicles caused by the arrival of ferries Geography, 2013. 43: p. 13-24. 2. Interventions with the land use in the area as it has been 5. Ni, D., Multiscale modeling of traffic flow. Mathematica Aeterna, 2011. 1(1): p. 27-54. undergoing a lot of changes due to the constructions to turn 6. Alexiadis, V. and C. Systematics, Integrated Corridor the harbor into a dense residential area Management Analysis, Modeling and Simulation (AMS) The results of such analysis will help with understanding the Methodology. 2008, United States. Joint Program Office for causes of congestions and bottlenecks in the west harbor and Intelligent Transportation Systems. serve as a tool for measuring the impacts of different policies on 7. Allacker, K., et al., Energy simulation and LCA for macro- air quality and noise levels. Finally, the results will contribute to scale analysis of eco-innovations in the housing stock. The International Journal of Life Cycle Assessment, 2019. 24(6): comprehending situational and statistical awareness which is one p. 989-1008. the main pillars of the City’s Intelligent Transport System 8. de Dios Ortúzar, J. and L.G. Willumsen, Modelling Development Programme 20304. transport. 2011: John wiley & sons. 9. Bennett, D., et al., Guide to traffic management part 3: traffic studies and analysis. 2009. 5 Discussions and Future Directions 10. Shone, F., City Modelling. Medium, 2020. 11. McNally, M.G., The four-step model. 2007: Emerald Group URBANITE project aims to build microsimulation models Publishing Limited. 12. Parunak, H.V.D., R. Savit, and R.L. Riolo. Agent-based which can help cities find out the outcomes of certain policies by modeling vs. equation-based modeling: A case study and applying new technologies and advanced techniques. Building users’ guide. in International workshop on multi-agent transport models is demanding in terms of costs, time, data, and systems and agent-based simulation. 1998. Springer. computation space requirements. However, URBANITE aims to 13. Stover, V.G. and F.J. Koepke, Transportation and land take advantage of machine learning techniques as well of development. 1988. decision support systems to overcome these challenges. Hence, the models will be trained by the results obtained from simulations’ input-output space exploration. Additionally, a recommendation engine will be built to provide decision makers with the relevant policies and KPIs tailored for their needs. The approach facilitates data-driven decision making and will be fundamental in enabling real-time implementation and evaluation of solutions. Although there are still a lot of challenges regarding available data sources whether on the level of required infrastructure for gathering data or the quality of the available data. Recognition of the most relevant data sources and opening the data is a crucial step for the cities if they aim to realize evidence-based decision-making. The other challenge depends on the ability to include the benefits of all stakeholders esp. citizens in building technological solutions. In this regard, cities should come up with the ways to consider interests of all relevant beneficiaries and move towards participatory approaches. ACKNOWLEDGMENTS The URBANITE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870338text here. Insert paragraph text here. REFERENCES 1. Legacy, C., Is there a crisis of participatory planning? Planning theory, 2017. 16(4): p. 425-442. 2. Peters, M.A., Citizen science and ecological democracy in the global science regime: The need for openness and participation. 2020, Taylor & Francis. 4 https://www.hel.fi/static/liitteet/kaupunkiymparisto/julkaisut/julkaisut/julkaisu- 16-19-en.pdf 637 URBANITE: Messina Use Case in Smart Mobility Scenario Francesco Martella Giovanni Parrino Mario Colosi Engineering Department, University Engineer - Municipality of Messina Engineer - Municipality of Messina of Messina - ALMA Digit S.R.L. Messina, Italy Messina, Italy Messina, Italy nanni.parrino@gmail.com colosimario96@gmail.com fmartella@unime.it Giuseppe Ciulla Roberto Di Bernardo Marco Martorana Research & Development Laboratory Research & Development Laboratory Research & Development Laboratory Engineering Ingegneria Informatica Engineering Ingegneria Informatica Engineering Ingegneria Informatica Palermo, Italy Palermo, Italy Palermo, Italy giuseppe.ciulla@eng.it roberto.dibernardo@eng.it marco.martorana@eng.it Roberto Callari Maria Fazio Antonio Celesti Computer Engineer Department MIFT, University of Department MIFT, University of Palermo, Italy Messina - ALMA Digit S.R.L. Messina roberto.callari@outlook.it Messina, Italy Messina, Italy mfazio@unime.it acelesti@unime.it Massimo Villari Department MIFT, University of Messina - ALMA Digit S.R.L. Messina, Italy mvillari@unime.it ABSTRACT to optimize their travels by reducing the stress associated with them, while Sustainable Mobility helps to protect the environ- The urban transformation and the changes that the world is ment by improving the quality of life in Smart Cities. Institutions undergoing lead, today more than ever, to the need to make around the world are implementing policies that allow to de- faster and more timely choices in the field of mobility manage- crease CO2 emissions. The issues of mobility and its optimization ment. Technology is therefore essential for providing decision are therefore protagonists in the identification of these policies. support tools that help managers and politicians to better man- In particular, the European Commission encourages projects in age cities. The European project URBANITE (Supporting the the field of Smart Mobility and Sustainable Mobility with H2020, decision-making in URBAN transformation with the use of dis- Horizon Europe and the Next Generation EU programs. The ruptive Technologies) aims to put in place a sustainable mobility URBANITE project was financed within the H2020 funding pro- with the support of disruptive and innovative technologies for gram. Among the objectives of URBANITE the main one is to this sector. The proposed study describes the URBANITE project promote the use of disruptive technologies in the nascent Smart with reference to the technologies and the strategies implemented Cities in technological terms through the use and analysis of Big in the city of Messina. As a partner and pilot use case, in the mu- Data, AI algorithms, etc. An innovative element, however, is that nicipality of Messina, software tools have been created starting related to the promotion of innovative tools for participatory from a series of local data regarding traffic and public transport decision-making processes such as the Laboratory Social Policy tracking. These tools allow technicians to quickly view traffic (SoPoLab). The aim of the project is to provide the Stakeholders status or bottlenecks for public transport on a map. of the project with a series of innovative technological tools in KEYWORDS order to support the decision-making processes of managers of public administrations and companies. Within the project there Urban Transformation, Disruptive technologies, Urban mobility, are four pilot cities: Amsterdam, Bilbao, Messina and Helsinki. URBANITE project, Decision making, Data Access, Data Analysis, In each of the pilots, the needs are studied and analysis tools Data Visualisation. developed which will then be applied to each of them. As regards the city of Messina, analysis were conducted on traffic and its 1 INTRODUCTION effects on local public transport. This work describes the refer- In the context of Smart Cities it is crucial to pay attention to ence scenario and the actions implemented for the municipality issues relating to mobility. Today Smart Mobility allows people of Messina within the URBANITE project regarding the purely Information Computer Technology (ICT) aspect. In particular, in Permission to make digital or hard copies of part or all of this work for personal section 2 the state of the art of the technologies studied and ap- or classroom use is granted without fee provided that copies are not made or plied to achieve the objectives is described. Section 3 introduces distributed for profit or commercial advantage and that copies bear this notice and the reference scenario. In section 4 the tools implemented will be 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). illustrated, while in section 5 the final considerations and future Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia developments are reported. © 2021 Copyright held by the owner/author(s). 638 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Martella, et al. 2 STATE OF THE ART how, thanks to URBANITE project, it is possible to put together what is already present in the systems of the city of Messina, In [1] a case study concerning the home-office mobility of the creating the basis for the creation of new useful decision-making University of Messina staff is discussed. The home-work com- tools. muting of public employees in the city of Messina is one of the main critical issues related to daily life. Traveling at particular 3 REFERENCE SCENARIO times of the day causes both traffic congestion and pollution. Au- thors analyze different performance indicators to be used for the The URBANITE project was created to provide communities design and development of Smart Mobility services by adopting with a long-term sustainable ecosystem model. Through a co- FIWARE technologies. After analyzing the travel habits of work- creation strategy we want to bring stakeholders (civil servants, ers at the University of Messina, authors described how FIWARE citizens, etc.) closer to the use of disruptive technologies in the can lead to an agile development of Smart Mobility services capa- field of mobility. This model is supported with a data management ble of minimizing traffic congestion, fuel consumption and CO2 platform and algorithms for data-driven decision making in the emissions. In [2] authors describe the results of a Sustainable field of urban transformation. Furthermore, the model is validated Mobility project in Messina. The presented application aims to by pilot mobility use cases in the context of the proliferation encourage citizens to use low-impact vehicles instead of private of sharing services. The URBANITE platform encapsulates the cars. Through a partnership between different stakeholders a experiences of four pilot cities and acts as a junction point to digital application to assign citizens electric bikes was developed, create a unique analysis model for cities. Thanks to the platform free of charge for a limited time period. Authors describe cyber it will be possible to have information regarding mobility that security issues, both in terms of secure authentication for citizens can be as a support in order to take serious technical and practical that access the service and tracking of the whole assignment pro- decisions. cess. The flow is described from the user’s request to the e-bike restitution. The adopted solution uses two-factor authentication (2FA) and Blockchain as the main technologies in the implemen- tation phase. Innovative and advanced smart devices and virtual devices are described in [6]. Authors have designed, for one use case in the city of Messina, an abstracted component character- ized by specific high-level functionalities. The system offers the chance to access the needed information with the most appropri- ate frequency and accuracy, avoiding information overload and allowing a more efficient computation. In this case it is important the access control and the security of the data. An interesting work for this purpose is described in [5]. In [3] authors show the use of customized generic Edge devices to carry out multiple activities at the same time, also focusing on how the proposed solution can lighten the work of cloud infrastructures. The pre- sented concepts were implemented and tested in a real use case Figure 1: Urbanite Approach in the city of Messina by means Function as a Service (FaaS) para- digm. The proposed work allows users to perform multiple tasks on the same device. Applications such as vehicle counting, license In each pilot the data, useful for the mobility analysis, were plate recognition, object identification, etc. are proposed. In the analyzed and collected. The data considered funcional are col- considered use case two cameras were connected to a Raspberry lected on a single data storage. Thanks to different visualization PI 4 and the performance was compared. It is possible to connect and AI techniques/algorithms, the data were processed and made different sensors to the proposed Edge devices and imagine each possible to create decision making tools that currently need vali- sensor as a different service. In [8] authors introduce a tool for dation (Figure 1). The use case regarding the city of Messina is studying mobility data. The basic principle is that technological described below. innovation has led to the spread of various data tracking systems. The data are accumulated and can be used in various applications 3.1 Briefly on Messina Use Case such as the analysis of mobility, urban planning and transport The metropolitan area of Messina is one of the most extended ar- engineering. It is possible to use the data to extract information eas of the south of Italy, the first in Sicily and counts over 620.000 in matters relating to rough space-time trajectories, or by relying citizens. The city counts over 250.000 citizens and most of them on statistical “laws” governing human movements [4]. However, are commuters between Sicily and Calabria. The local transport authors do not neglect the attention to user privacy [7]. From the of the city of Messina consists of both sea transport (hydrofoil study and development comes an interesting Python library used and ferry boats fleets) and land transport (buses, tramway and in URBANITE for the analysis of mobility data in particular in rail transports network). They are managed by public and private Messina use case. From the state of the art it emerges that the city companies. The main issue that affects both kinds of services of Messina has been the subject of various scientific studies that (sea and land transport) is the lack of facilities that can permit have found practical application. Various national and European interoperability between different departments of the munici- grants made it possible to achieve relevant innovations in the pality and the communication with citizens and stakeholders. field of mobility. It is not clear how the data collected can be In order to overcome this problem, the Municipality of Messina useful to administrators and managers in the decision making is investing in intelligent infrastructures and services for the phase. This paper, therefore, want to synthesize and demonstrate city and citizens. In particular, the main activities are focused on 639 URBANITE: Messina Use Case in Smart Mobility Scenario Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia vehicle access detection in LTZ (Limited Traffic Zone) and pedes- trian areas, centralised traffic management based on smart lights, traffic flows and analysis, incentives to use public transportation and video surveillance. URBANITE, for the city of Messina, is focusing on light and pedestrian mobility. Concerning the light mobility there are two main action lines: (1) the extension of the cycle paths and the spread of bike mo- bility (but the main goal is to promote the use of bicycles and to offer better services to citizens) (2) create new bike-lines and links between the centre and suburbs zones of the city. Regarding pedestrian mobility, the objective is the definition of an integrated system of pedestrian areas and paths. Furthermore, from a wider perspective concerning public transportation, the city of Messina aims to extend the transport network in urban and extra-urban areas. The use case scenario in Messina (Figure 2) aims to evaluate the effects of the extensions of the public trans- Figure 3: URBANITE Architecture - Messina portation services in terms of frequency, itineraries and stops on traffic and multi-modal transportation. In particular, a com- parison of the impact on traffic between the different version of Retrieval (reported in URBANITE Cloud Components) through the public transportation network was performed. Moreover, the the Data Harvester & Preparation and is filled with data by the scenario includes an analysis of the suburban roads around the Data Importer. The Data Processor allows both to expose the data city of Messina (that represent an important connection with the via Restful API and to process them ensuring correct formatting. surrounding towns) in terms of traffic congestion and connection Finally, within the Urbanite UI, three new specific components for with public transport network. the Messina use case have been built: Messina Traffic Evolution, Messina Traffic Flows, Messina LPT Critical Areas. 4 MESSINA IMPLEMENTATION The use case scenarios described in Section 3 are accessible thanks to the functionalities provided by the URBANITE UI, the inte- grated URBANITE’s framework at the UI level. The different analysis and visualizations provided aim to help the municipal- ity’s technicians in the extension of the current public trans- portation network. The tools allowing the users to interact with each visualization by filtering and querying the underlying data. Concerning the traffic congestion analysis for the municipality of Messina, Figure 4 depicts the temporal evolution of traffic flow on selected roads entering or leaving the city of Messina. Figure 2: City of Messina 3.2 The URBANITE Architecture The architecture created within URBANITE is made up of several abstract components that interact with each other. Thanks to the interaction between the different components, it is possible Figure 4: Messina Traffic Evolution to provide all the tools necessary to achieve the objectives of the project. In Messina this architecture has been enriched by building new dedicated components, at the Edge level, which The traffic jam factor of each road, in a specific time of the fully integrate with the existing Cloud ecosystem as shown in day, is represented by the colour of the road itself, following Figure 3, in which these components are highlighted. the provided legend. Data used to this purpose are acquired and In particular, for the Messina Edge Components, a local com- stored for real-time and historic analysis. Figure 5 illustrates the ponent called Messina Data Storage has been added. This compo- comparison analysis of the jam factors on two different roads of nent acts as a support for the parent component Data Storage & the city considering the time window of a week. 640 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Martella, et al. Moreover, it is necessary to improve smart algorithms in order to have responsive systems even in real-time. Finally, the system will make the APIs available for open-data, giving other scholars or stakeholders the possibility to carry out analysis or develop innovative solutions. ACKNOWLEDGMENTS The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement N° 870338. This work was co- financed by the European Union - FSE, PON Research and Innova- tion 2014-2020 Axis I - Action I.1 "Dottorati innovativi con carat- terizzazione industriale". The authors thank the deputy Mayor of Figure 5: Messina Weekly Traffic Flows the Municipality of Messina Carlotta Previti and the administra- tive manager of the URBANITE project for the Municipality of Messina Dr. Placido Accolla for their support. The data source is the same of the previous analysis, but this time the purpose and the target users are people with a more REFERENCES technical background. For each road, if the road is bidirectional, the dashboard provides a chart for each direction using a dif- [1] Lorenzo Carnevale, Antonio Celesti, Maria Di Pietro, and ferent symbol for each one. The colors indicate the jam factor Antonino Galletta. 2018. How to conceive future mobility value. Finally, to identify areas of Messina where vehicles of pub- services in smart cities according to the fiware frontiercities lic transportation are stationary for a certain time in a specific experience. IEEE Cloud Computing, 5, 5, 25–36. doi: 10.1109/ observation period, the heat-map analysis, depicted in Figure 6, MCC.2018.053711664. is provided. [2] Alessio Catalfamo, Maria Fazio, Francesco Martella, Anto- nio Celesti, and Massimo Villari. 2021. MuoviMe: secure access to sustainable mobility services in smart city, (Sep- tember 2021). [3] Antonino Galletta, Armando Ruggeri, Maria Fazio, Gianluca Dini, and Massimo Villari. 2020. Mesmart-pro: advanced processing at the edge for smart urban monitoring and reconfigurable services. Journal of Sensor and Actuator Net- works, 9, 4, 55. issn: 2224-2708. doi: 10.3390/jsan9040055. http://dx.doi.org/10.3390/jsan9040055. [4] Marta C. Gonzalez, Cesar Hidalgo, and Albert-Laszlo Barabasi. 2008. Understanding individual human mobility patterns. Nature, 453, (July 2008), 779–82. doi: 10.1038/nature06958. Figure 6: Messina LPT Critical Areas [5] Valeria Lukaj, Francesco Martella, Maria Fazio, Antonio Celesti, and Massimo Villari. 2021. Trusted ecosystem for iot service provisioning based on brokering. In 2021 IEEE/ACM To investigate if public transportation means use to be station- 21st International Symposium on Cluster, Cloud and Internet ary in the same place for different time periods, the dashboard Computing (CCGrid), 746–753. doi: 10.1109/CCGrid51090. allows to compare two different time slots. In this case the data 2021.00090. source is an historic database for the bus and tram position of [6] Francesco Martella, Giovanni Parrino, Giuseppe Ciulla, Rob- the Local Transport Company. The data are elaborated with the erto Di Bernardo, Antonio Celesti, Maria Fazio, and Mas- scikit-mobility [8] Python library with the aim to obtain the simo Villari. 2021. Virtual device model extending ngsi-ld heat-map visualization. In each described visualization, in order for faas at the edge, 660–667. doi: 10.1109/CCGrid51090. to have further information, the dashboard allows to visualize 2021.00079. Points of Interest and Public Transport Stops on the map. [7] Yves-Alexandre Montjoye, Cesar Hidalgo, Michel Verleysen, 5 CONCLUSIONS and Vincent Blondel. 2013. Unique in the crowd: the privacy bounds of human mobility. Scientific reports, 3, (March 2013), This paper describes the current state of the ICT systems put 1376. doi: 10.1038/srep01376. in place for the URBANITE project as regards the case of the [8] Luca Pappalardo, Filippo Simini, Gianni Barlacchi, and Messina pilot. From the first results it is evident that, thanks to Roberto Pellungrini. 2019. Scikit-mobility: a python library the use of data analysis and their appropriate visualization, it for the analysis, generation and risk assessment of mobility is possible to obtain information that is often difficult to under- data. (2019). arXiv: 1907.07062 [physics.soc-ph]. stand. The visualization methods allow for immediate analysis and support decision-making policies. Thanks to the presented tools, in fact, it is possible to determine the effectiveness of the mobility policies used compared to the past, thanks to the histor- ical harvested data, and possibly try to improve them. The next step will be to extend the functionalities. The scenario of each single pilot must be applied to all the case studies of the project. 641 Data commons in smart mobility – the road ahead? Nathalie van Loon Rosalie Snijders Innovation Department Faculty of Science, Information Studies City of Amsterdam University of Amsterdam Amstel 1, 1011 PN, Amsterdam, Netherlands Science Park 904, Postbus 94323, 1090 GH Amsterdam Nathalie.Loon@Amsterdam.nl Snijdersrosalie@hotmail.com ABSTRACT generated by these services can be of great public value. As the city of Amsterdam is also part of the ‘cities coalition for digital Mobility data collection and governance are mainly dominated rights’ and aiming to be a number one city in the protection of its by larger technology companies that gather all the data. citizens digital rights, Amsterdam is looking for good examples Therefore, they also have exclusive control over what happens in the governance of data and cocreation of public value together with the data. This calls for alternative data governance models. with citizens, local stakeholders and SMEs. A viable alternative, introduced in recent years, is the data commons model. With this model, people can share their data on Considering the context, and considering the role of the their own terms, while maintaining a certain amount of privacy. municipality, this paper explores the following question: can or This model has been used with health data and scientific data, should a local government organize a data commons in order to however, no viable example of a mobility data commons has thus enable parties to share data in a trusted, fair and economic way, far been found. This paper explores how local governments can while observing privacy and security concerns? This paper facilitate a mobility data commons. And: is the commons a therefore shortly explores the ‘why’ and ‘how’ and evaluates the beckoning road for all of us? applicability of a data commons as a disruptive technology and framework. This paper is based on existing literature and interviews with experts from the municipality of Amsterdam and KEYWORDS is structured as follows: section 2 will start with some Data governance, disruptive technologies, mobility data background information to support the research question. In management, digital literacy, data commons, policy making. section 3 the concepts of a smart city and data commons are explored, and section 4 will present the conclusions. 1 INTRODUCTION In the last decades, the concept of a smart city has grown in 2 BACKGROUND popularity both as a research subject and in government policies. In the last couple of years, data have become a valuable asset to Cities all over the world have started using technology to look our economy. Some have claimed that the world’s most valuable for solutions that enable transportation linkages, mixed land uses, resource is no longer oil, but data [23, 49, 53]. A new form of and high-quality urban services with long-term positive effects capitalism has arisen where wealth is generated based on the on the economy and sustainability of the city [1]. accumulation, extraction, processing, and use of data. Smart cities are built on data. And one area where the generation The term Big Data has been on the rise since the start of the new and analysis of data have steadily increased is the mobility sector. millennium. Enabled by new and innovative technologies, App-based mobility services, like bike-sharing, scooter-sharing, companies can gather and analyse data from their customers or peer-to-peer carsharing, and ride-hailing gather enormous users and use it to their advantage. Digital data and information amounts of information about how, when, and where people have become a critical economic, political, and social resource travel. And not only sharing apps, also other apps like weather and most of this data is in the hands of just a few companies such apps or wayfinding apps generate data. Plus not only ‘smart as Amazon, Google, Facebook, and Apple [41, 43]. With this solutions’ generate data but also ‘regular’ cars and bikes are data, these few companies can have huge control and influence becoming more and more mobile sensors in the city landscape by over human behaviour and societies. As a response, politicians, offering, to name just a few examples, ‘tracking services’ in case human rights movements and people in general have raised of theft, and cameras helping people to park. concerns about the misuse of their data. For many, it is not clear In this context the City of Amsterdam aims to be a smart and how much data these companies collect and what they do with it. mobile city, offering a large supply of mobility options; As a result, people opt to not share anything with anyone and affordable, reliable, and accessible to everyone. However, most have started hoarding their data. However, data can be of great mobility data are enclosed by private companies, while the data value for everyone if used in the right way. In the near future for instance, Artificial Intelligence will have to use data to play a role Permission to make digital or hard copies of part or all of this work for personal or in the delivery of services [36]. If this data stay in the hands of classroom use is granted without fee provided that copies are not made or distributed big tech companies, the positive effects may never reach citizens. 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 As a digital rights city, therefore, it is of importance to look for be honored. For all other uses, contact the owner/author(s). new technologies that enhance public value and public benefit at Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). the same time [43]. Citizens should have the power to decide on who they want to share their data with, under which rules, for 642 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia N. van Loon et al. what purpose and in a transparent manner. Data are (too) often 3.1 Design principles data commons regarded as a resource to be extracted for private profits, and Principles can be described as general rules and guidelines which technical developments have enabled technology firms to a system architecture must follow to be as productive and cost capture data from and about those who have not consented or effective as possible. Principles help guide the use and have no viable alternatives. The view on data therefore must deployment of an architecture. Also principles may help identify change from an asset that can offer a competitive advantage, to concerns stakeholders might have that a system can address. one of public infrastructure to ensure common welfare, which Each principle should have a rationale and implication associated can be exchanged equally. with it. This can help with promoting the acceptance and For this research, a smart city is defined as "A well defined understanding of the principles [10, 25]. Here, we adapted and geographical area, in which high technologies such as ICT, ‘translated’ 7 of Ostroms 8 design principles - in a first attempt - logistic, energy production, and so on, cooperate to create to rationales and implications for data commons [5]. benefits for citizens in terms of wellbeing, inclusion and (1) Define clear group boundaries: participation, environmental quality, intelligent development; it • Rationale: Who can use the data should be clearly defined is governed by a well-defined pool of subjects, able to state the and should be easily identifiable rules and policy for the city government and development”. The • Implication: An individual using the commons may city of Amsterdam has already become an example of how a require identifying information before allowing access to smart city strategy can be implemented. With the above the commons. Additionally, the data sets should be easily mentioned definition in mind, the main goal of smart cities is to identifiable. With this in place, poaching can be easily improve the quality of life for its citizens in a sustainable way. detected [23]. At the same time, citizens also have the potential to be the main (2) Match rules governing the use of common goods to local component of data acquisition. With the use of smartphones, the needs and conditions: citizens can act as human sensors and help gather enormous amounts of data [29]. ICT can act as a platform to collect • Rationale: The rules of governing the data commons information and data to promote an improved understanding of should be matched to the local needs of the users. Since no how a smart city is functioning in terms of services, data commons and its environment are the same. consumption, and lifestyle. Especially with mobility data, the • Implication: Setting up the rules and guidelines of the use input of citizens can be of great value [30]. of the commons should include the local users of the commons. Therefore, citizen participation is a crucial part While the potential of big data is explored on a daily basis in the of a successful commons. development of new and possibly disruptive technologies, the (3) Ensure that those affected by the rules can participate in potential societal disruption and ethical concerns attract less modifying the rules: attention or even denial and/or apathy. This while multiple • Rationale: Both the data producer and user should be able studies show that, with the creation of intelligent mobility to benefit from the data commons and be protected. systems in smart cities, the potential for intrusive surveillance is • Implication: All parties within a data commons should be increased [31] and that the types of data used are privacy- able to change the conditions of the data commons, with sensitive [32]. Location history data, for instance, can act as an agreement from all parties. The use and production in the identifier of its users [33, 34]. Also bias in data can be a data commons should always be in balance. multiplier of societal injustice, as the Dutch ‘toeslagenaffaire’ (4) Make sure the rule-making rights of community members [35] has shown, framing approximately 26.000 parents as are respected by outside authorities: possible fraudsters, based on their (second) nationality. Also • Rationale: The rules and regulations of the commons multiple organizations may have multiple policies and rules should be respected by the local authorities, must be regarding the protection of the data of their users. However, this recognized as legitimate by the authorities. is not always transparent - while it may lay in everyone’s interest • Implication: Local authorities shouldn’t be able to change to share this data [36]. Therefore, one of the main challenges of the rules without the consent of the parties involved. (5) Develop a system, carried out by community members, for the use of big data are privacy, transparency, and bias. monitoring members’ behaviour: • Rationale: Monitoring of the data commons is needed to 3 Data Commons ensure that the data is used fairly. • Implication: Unauthorized use of the data should be There are various definitions in use for commons and also for detected. In the case of a data commons, this could be a data commons. In general, the Nobel prize winning work on moderator, since the commons are not in a physical place. commons by Elinor Ostrom in 1990 is used as a reference for any Ideally, this is done by the user community. such definition. Ostrom successfully described the commons as (6) Use graduated sanctions for rule violators: a governance model rather than open access to resources and • Rationale: Users and producers in the data commons that introduced the commons as a framework to value various violate its rules should not be banned directly. historical and contemporary social movements. In short one can • Implication: A gradual system needs to be set up. define the commons as a commonly owned and managed (7) Provide low-cost accessible means for dispute resolution: (common pool) resource. More elaborate, Ostrom identified 8 • Rationale: When issues within the commons come up, the design principles of stable common pool resource management dispute would has to be resolved in an informal, cheap, and in her groundbreaking work ‘Governing the commons. The straightforward manner. This way problems are resolved, evolution of institutions for collective action.’ [3, 6, 18, 19, 27]. rather than ignored • Implication: A process for conflict resolution should be created that is perceived as fair by all users of the data 643 Data commons in smart mobility – the road ahead? Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia commons. A mechanism for rule enforcement and for and subsequent lockdowns showed that a lot of families don’t dealing with violators needs to be set up and discussed by have access to technology when public services like libraries and all involved parties. schools are closed. And how can Amsterdam residents take Concerns ownership over their data if they don’t have access to technology, know where to access their data or how to object to their data The incorporation of the above-mentioned design principles can being used? By introducing a ‘digital agenda’ [41] the city of be a measure of success when organizing a data commons. But Amsterdam is working on overcoming this divide and promoting can they also be used to address the concerns the relevant and protecting digital rights, yet agency is complex and scattered. stakeholders might have? Also, the use of data and which algorithms are used should always be disclosed to the contributors of the data. Amsterdam 3.2 Citizen participation has made a first step by introducing an ‘Algorithm register’ [16]. Since citizen participation is a necessary step when organizing a But can a commons be organized in such a way that no one has datacommons and is essential for two design principles of a access to a contributor’s data without their permission? successful data commons, a major concern when it comes to a local government organizing or facilitating a datacommons is the Monitoring and validating participation of citizens. Is this a ‘contradictio in terminis’ or can This also raises the question if local governments can organise and should the government act as a facilitator or incubator? the monitoring of the use and validation of data. A solution could Looking at the participation ladder by Arnstein [2] there is, be implementing an interoperable context-aware meta-databased indeed, a world to win, also calling for a different role of the architecture [15]. This type of architecture is context-aware and government: a ‘co-creating government’ or ‘co-city’. allows permissions and policies to be attached to the data. Additionally, due to its flexibility, trust norms can be changed and can account for increased transparency and accountability. This is an architecture that associates data with user permissions Different levels of participation and role of government and policies which enables any consumer to handle the data in a way that is consistent with a contributor’s wishes [21]. This is a 6. facilitating: citizen is initiator, decisionmaker and owner. Local government is facilitating/ activating and helping. Nu m method that could increase accountability in a decentralized data be 5. co- decisionmaking: citizens play their part in planning and decisionmaking through for r ecosystem like a data commons. However, this method does thus instance participatory budgetting/ citizen jury. Public servants advise, local government of sets the 'legal framework' and checks. p far not provide a way for community members to contribute to art 4. co-creation: citizens are actively invited to think along in planning through workshops ici monitoring the behavior within the community. for instance. Politicians commit to chosen solution. pants Concerns 3. advising: citizens are asked for advise through a.o. online discussions, Interoperability is a practical, yet very prominent concern when organizing data commons [7, 8] since a data commons is not only 2. consulting: citizen is asked for his/her opinion through focusgroups, etc. about access to data, it is also a platform for data experimentation 1. informing: citizen has access to essential info to express his/her opinion. and interaction. Technically, a data commons is a repository of personal manifests that describes the access and usage rights of all data generated by an individual within a digital service. Therefore, the data commons must regulate relationships Figure 1: Levels of participation between the organizations and individuals that use and share ownership of the data. This way, data commons help citizens Transparency having a say in what data they want to share and under which Another important concern is transparency; in order to achieve a successful mobility data commons, the municipality needs to be conditions. Also data commons could provide users easy access transparent about every part of the data commons. To achieve full to their own data, information about who has access to their data transparency, openness of all operations within the data and what they could do with this information. However, for this commons is required, so that citizens if needed, can hold the to be successful also trust needs to be built between the different consumers of the data accountable and are allowed to withdraw parties participating in the commons. As our last concern we their consent [24]. However, measuring transparency within a raise the question on the definition and the narrative. The data commons can be a tricky task. The question is not only how commons, although part of an important and impactful historical much information is available and under which terms, but is also movement, that, amongst others, created the guilds in the Middle a question of equality in the accessibility and usability of that Ages, the common land movement in the UK and, more recently, information. Transparency is increased when the data within a knowledge commons Wikipedia [11], mutuals like data commons is given a proper context and, therefore, its users ‘broodfondsen’ in the Netherlands and citizen energy can use and understand the data without confusion. communities in most European countries, are not part of our Transparency should cover all of these aspects of data access: current, dominant, narrative. Although he European Union and physical access, intellectual access, and social access [13]. In the Dutch government have legal frameworks in place for several case of a data commons, physical access can refer to the ability types of commons - in housing and energy for instance- no real to reach the content of the commons, social access is the ability understanding of the potential public value or even clear to share the content of the commons and intellectual access is the definition of a data commons currently exists. ability to fully comprehend the content [7, 4], sometimes also referred to as ‘digital literacy’. Not only in Amsterdam, but in more cities in the digital rights coalition, the Covid-19 pandemic 644 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia N. van Loon et al. 4 CONCLUSION [5] https://en.wikipedia.org/wiki/Elinor_Ostrom [6] J.B. Fisher and L. Fortmann. Governing the data commons: Policy, practice, and the For now, the larger technology companies dominate the data advancement of science. Information & Management, 47(4):237 – 245, 2010. collection in the area of mobility. As a result, these companies [7] R. L. Grossman, A. Heath, M. Murphy, M. Patterson, and W. Wells. A case for data commons: Toward data science as a service. Computing in Science Engineering, have exclusive control over what happens with the data the 18(5):10–20, 2016. citizens of a city generate. In this paper we described how this [8] R. Grossman. A proposed end-to-end principle for data commons, 2018 (accessed April 5, 2020). ‘enclosure’ of data by big tech builds a powerful value driven [9] https://assets.amsterdam.nl/publish/pages/964754/agenda_digitale_stad_tussenr case for cocreating and/or facilitating commons in mobility data apportage_2019_-_2020.pdf as a local government. Although a clear pathway on how to [10] Van Haren. TOGAF Version 9.1. Van Haren Publishing, 10th edition, 2011. [11] I. Abaker T. Hashem, V. Chang, N. Badrul Anuar, K. Adewole, I. Yaqoob, A. Gani, E. organize a mobility data commons is not yet available, the road Ahmed, and H. Chiroma. The role of big data in smart city. International Journal of ahead is one of cooperation, building trust between participants Information Management, 36(5):748 – 758, 2016. and experiment. By taking it one step at a time, setting clear [12] C.Hess and E. Ostrom. Introduction: an overview of the knowledge commons. Understanding knowledge as a commons: from theory to practice., 2006. boundaries and rules that are understood by partners involved [13] C. Humby. Data is the new oil. Proc. ANA Sr. Marketer’s Summit. Evanston, IL, USA, and, obviously, involving citizens in every step. However, 2006. [14] P.T. Jaeger and J. Carlo Bertot. Transparency and technological change: Ensuring considering digital literacy and other possible constraints for equal and sustained public access to government information. Government citizen participation, careful thought on how to involve citizens Information Quarterly, 27(4):371 – 376, 2010. Special Issue: Open/Transparent -for a longer period- is paramount. One suggestion would be to Government. [15] P. T. Jaeger and G. Burnett. Information worlds: Social context, technology, and just ‘follow the music’: there is a vibrant movement of active information behavior in the age of the Internet. Routledge, 2010. citizens communities and SMEs in town, how can the local [16] S. Maguire, J. Friedberg, M. H.Carolyn Nguyen, P. Haynes. A metadata-based architecture for user-centered data accountability. Electronic Markets, 2015. government cooperate towards the creation of a data commons [17] https://ai-regulation.com/amsterdam-and-helsinki-launch-algorithm-and-ai- in mobility as a spill-over effect from these efforts? This way register/ data commons can prove to be an alternative for apathy and [18] H. Mehr. Artificial Intel igence for Citizen Services and Government. Harvard Ash Center Technology & Democracy, 2017. distrust in big tech, contributing to a strong and growing [19] E. Ostrom. Governing the commons: The evolution of institutions for collective narrative on local cooperation. action. Cambridge university press, 1990. [20] E. Ostrom, R. Gardner, James Walker, J. M Walker, J. Walker. Rules, games, and common-pool resources. University of Michigan Press, 1994. [21] F. Pasquale. From territorial to functional sovereignty: The case of amazon. Law and Political Economy, 6, 2017. [22] E. Politou, Efthimios Alepis, and Constantinos Patsakis. Forgetting personal data and Governments revoking consent under the gdpr: Chal enges and proposed solutions. Journal of Cybersecurity, 4(1):tyy001, 2018. [23] B. Prainsack. Logged out: Ownership, exclusion and public value in the digital data and information commons. Big Data and Society, 2019. [24] N. Purtova. Health Data for Common Good: Defining the Boundaries and Social Dilemmas of Data Commons, pages 177–210. Springer International Publishing, Cham, 2017. [25] S. Ranchordás. Nudging citizens through technology in smart cities. International Review of Law, Computers and Technology, 2019. Households Businesses [26] E. Schlager. Common-pool resource theory. Environmental governance reconsidered: chal enges, choices, and opportunities, pages 145–175, 2004. [27] S. Spiekermann, Alessandro Acquisti, Rainer Böhme, and Kai-Lung Hui. The challenges of personal data markets and privacy. Electronic markets, 25(2):161– 167, 2015. Figure 2: the third sector model [37] [28] J. Yakowitz. Tragedy of the data commons. Harvard Journal of Law & Technology, 25(1):1, 2011. [29] M. Srivastava, T. Abdelzaher, and B. Szymanski. Human-centric sensing. ACKNOWLEDGMENTS Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 370(1958):176–197, 2012. This paper is partly based on interviews with public servants and [30] J. Vázquez Salceda, S. Álvarez Napagao, J. A. Tejeda Gómez, L. Javier Oliva, D. Garcia experts at the city of Amsterdam, a research done by Rosalie Gasulla, I. Gómez Sebastià, and V. Codina Busquet. Making smart cities smarter using artificial intel igence techniques for smarter mobility. In SMARTGREENS 2014: Snijders in Q2 of 2020. During this period Rosalie was an intern proceedings of the 3rd International Conference on Smart Grids and Green IT at the city of Amsterdam, writing her master thesis, supervised Systems, pages IS7–IS11. SciTePress, 2014. [31] M. Büscher, P. Coulton, C. Efstratiou, H. Gel ersen, D. Hemment, R. Mehmood, and by Nathalie van Loon, working at the city of Amsterdam and D. Sangiorgi. Intel igent mobility systems: Some socio-technical challenges and Leon Gommans and Frank Nack, both working at the University opportunities. In Lecture Notes of the Institute for Computer Sciences, Social- of Amsterdam. This paper is an adaptation by Nathalie van Loon, Informatics and Telecommunications Engineering, 2009. [32] Y. Alexandre De Montjoye, C. A. Hidalgo, M. Verleysen, and V. D. Blondel. Unique in written in the context of the Urbanite project: https://urbanite- the Crowd: The privacy bounds of human mobility. Scientific Reports, 2013 project.eu/, under grant agreement #870338. [33] C. Bettini, X. S. Wang, and S. Jajodia. Protecting privacy against location-based personal identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intel igence and Lecture Notes in Bioinformatics), 2005. REFERENCES [34] Hui Zang and Jean Bolot. Anonymization of location data does not work: A large- scale measurement study. In Proceedings of the 17th Annual International Conference on Mobile Computing and Networking, MobiCom ’11, page 145–156, [1] V. Albino, U. Berardi, and R. Maria Dangelico. Smart cities: Definitions, dimensions, New York, NY, USA, 2011. ACM performance, and initiatives. Journal of Urban Technology, 2015. [35] https://nl.wikipedia.org/wiki/Toeslagenaffaire [2] S. R. Arnstein. A Ladder Of Citizen Participation. Journal of the American Planning [36] Lina Zhou, Shimei Pan, Jianwu Wang, and Athanasios V Vasilakos. Machine learning Association, 1969. on big data: Opportunities and chal enges. Neurocomputing, 237:350–361, 2017. [3] B. J Birkinbine. Commons praxis: Toward a critical political economy of the digital [37] V. Pestoff, Third sector and cooperative services -An alternative to privatization. commons. TripleC: Communication, Capitalism & Critique. Open Access Journal for Journal of consumer policy 15(1): 21-45, 1992. a Global Sustainable Information Society, 16(1):290–305, 2018. [4] G Burnett, PT Jaeger, and KM Thompson. The social aspects of information access: The viewpoint of normative theory of information behavior. Library & Information Science Research, 30(1):56–66, 2008. 645 URBANITE Mobility Data Analysis Tools Ignacio (Iñaki) Olabarrieta† Ibai Laña Urrotz Larrañaga TECNALIA, Basque Research and TECNALIA, Basque Research and Bilboko Udala ITS Engineer Technology Alliance (BRTA), Technology Alliance (BRTA), Ernesto Erkoreka Plaza, 12, 48007 Bilbo, P. Tecnológico Bizkaia, Ed. 700, 48160 P. Tecnológico Bizkaia, Ed. 700, 48160 Bizkaia Derio, Spain Derio, Spain ularranaga@bilbao.eus ignacio.olabarrieta@tecnalia.com ibai.lana@tecnalia.com Shabnam Farahmand Sergio Campos Raquel Gil Forum Virium Helsinki, Unioninkatu 24, TECNALIA, Basque Research and Bilboko Udala Mobility Management 00130 Helsinki, Finland Technology Alliance (BRTA), Deputy Director, shabnam.farahmand@forumvirium.fi P. Tecnológico Bizkaia, Ed. 700, 48160 Ernesto Erkoreka Plaza, 12, 48007 Bilbo, Derio, Spain Bizkaia sergio.campos@tecnalia.com raquel.gil@bilbao.eus ABSTRACT Social Policy Lab – an environment to promote digital co- creation with methodologies and methods to support the The decision-making process in the policy making should rely communication among public servants, private companies, and on data driven evidence, in most of the cases the raw data needs citizens. The aim of the Social Policy Lab is to develop joint to be processed to transform it into actionable information. For ideas and to produce co-creation guidance for policies. Data this purpose, several tools have been developed within the Management Platform – to provide automatic support to the URBANITE project to transform urban mobility data into usable whole data processing chain and its life cycle, starting with the information. Specifically: (1) traffic prediction models based on collection process all the way up to the use of the data. Decision- historical data, (2) Origin-Destination (OD) matrix estimation Making Support System – powerful tools which combine models and (3) a methodology to analyse the locations visited in multiple data sources with advanced algorithms, a simulation several trajectories. engine, a recommendation, and visualisation system. These tools include predefined analysis pipelines to be used by non-technical KEYWORDS users, intuitive and understandable visualisations, and setups to Traffic prediction, Origin-Destination Matrix Computation, Data perform simulations of new mobility policies and situations that Analysis, Artificial Intelligence. allow their evaluation. URBANITE is implemented in four different use cases: Amsterdam, Bilbao, Helsinki, and Messina. 1 INTRODUCTION The analysis tools that are presented in this communication URBANITE project goal is to provide tools for the decision- belong to the Decision-Making Support System. More concretely making in the urban transformation field using disruptive they belong to the set of algorithms designed to obtain technologies and a participatory approach. These tools should aid information from the historical data stored in the URBANITE the process of taking decisions guiding it on data evidence. The Data Management Platform. The results obtained from these main features of the URBANITE architecture include: algorithms can be used to understand better what is the state of the mobility at a given time, or, alternatively, they can be used as • Modularity, i.e., each component provides specific input for simulations of new policies. functionalities and exposes clear interfaces, • Adaptability to heterogeneous city and region Among all the tools within the Decision-Making Support System contexts and ICT maturity levels, from complete three components are explained in this communication, namely: implementation to complementary add-on traffic prediction, OD matrix estimation, and trajectory location components. analysis. These components are discussed in the following • Interoperability, i.e., vertical, and horizontal sections, sections 2-4. This communication ends with some interoperability among modules and with existing concluding remarks in section 5. systems. And using the European standards as much as possible. 2 TRAFFIC PREDICTION The main elements that URBANITE offers are the following: Road traffic forecasting has been a topic of study since the † sixties [1] when time series analysis methods where mainly used Corresponding Author [2][3][4]. In the last two decades, heuristic machine learning Permission to make digital or hard copies of part or all of this work for personal or methods [5] started being used allowing to find more complex 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 relations within the traffic data. Nowadays traffic prediction citation on the first page. Copyrights for third-party components of this work must component has become one key tool for any ITS system. The be honored. For all other uses, contact the owner/author(s). component developed within the URBANITE project can Information Society 2021: 24th international multiconference , 4–8 October 2021, Ljubljana, Slovenia forecast what is the traffic flow that a sensor within the city © 2021 Copyright held by the owner/author(s). would measure for a given set of features. 646 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia I. Olabarrieta et al. hours or the following 7 days. Alternatively, specific set of The set of features at the time of this communication include features can be feed to the model using the REST Web service the day of the week and the time of the day but other ones are in in JSON format to obtain a result at a given instant of time. the process of being incorporated. Some of these features include if the day of the forecast is a bank or school holiday, weather An example of the result can be seen in Figure 2 where in features (precipitation and temperature), the arrival of ferries to addition to the prediction (red line) the confidence interval is Helsinki port or sport events (soccer games) in Bilbao (using the shown (orange band). The details of how to compute the method developed in [6]). Note that the approach within confidence interval are explained in [9]. In the Figure the result URBANITE is not to consider previous measurements as of the prediction for a week is shown, where the peaks for the features since the data is not available in real time. Therefore, different days are clearly visible, including the difference in the this approach can be considered as long-term prediction because pattern due to the weekend (fourth and fifth peaks in the series). the predicting horizon is only limited by the accessibility of external features (i.e., access to a weather prediction for example). Figure 2: Detailed of the visualization for the result of the traffic flow prediction for 7 days including the confidence interval. Figure 1: Integrated tool to perform traffic prediction showing the Helsinki use case. 3 OD MATRIX ESTIMATION The OD Matrix estimation works in a similar way than the The web portal to the integrated tool can be seen in Figure 1, prediction module. In this case we use data from bike rental city the tool allows to train a new model, to perform a prediction and service, specifically we consider the origins and the destinations to visualize the results. of each one of the rentals. These are both temporally and spatially aggregated by providing the time resolution (the same way as for The process of performing the training implies that the user the traffic prediction) and by providing a set of geographic areas needs to choose the following: • where to aggregate the origins and the ends of each rental. These The regression model type, two options are available: areas can be specified either via a GEOJSON or by specifying a random forest [7] and distribution inference [8] (only for set of points, the URBANITE web can be used to obtain the features with discrete values). • Voronoi areas [10] associated with those points and use those to The number of features to consider: 1. considers only perform the spatial aggregation. the day of the week, 2. also considers the time and so on. • The time resolution, typically either 5 or 15 minutes. This is the aggregation period on which the individual counts of vehicles moving over the sensor are combined to produce a time series. • The traffic sensor, this is chosen by selecting the available sensors within a map. • The period of the training data, the period can be chosen from the available data within Data Management Platform, being able to change this period allows for instance to avoid choosing the anomalous period due to the restrictions due to COVID-19. In addition, a percentage of the training data can be reserved to test the goodness of the model, this percentage can also be specified. Once a model is trained this can be used to perform a Figure 3: Integrated tool to perform OD matrix estimation for prediction, there are different ways to perform this, one way is the Bilbao use case. to use the URBANITE web visualization tool to choose a given date and perform the prediction for either the following 24 Training a model to perform OD matrix estimation implies choosing a regression model type, the number of features (in this 647 Urbanite Mobility Data Analysis Tools Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia case 0 can be chosen, which implies the use of only spatial the simplest of these aggregations is to compute the number of information), the time resolution, and the period of training data. times a location is visited independently of the trajectory it belongs. The result of this process applied to the trajectories of The result of the estimation, at a specific instant of time, consists the bike city service in Bilbao is shown in Figure 5. of a square matrix of size 𝑁𝑥𝑁 where 𝑁 is the number of Other types of aggregations can also be performed, as for different areas considered for the spatial aggregation. The web example most likely points to be visited depending of the day of tool within URBANITE allows to compute and visualize these the week and the time of the day, the most popular chain of estimations for all the instants within a period (typically a day or consecutive points visited, the longest route accomplished, etc.… a full week). In Figure 3 a detail of the web tool is shown where it can be seen the result at a given instant in the form of a matrix (lower left hand side) and the time evolution of one of the matrix components for a whole week (lower right hand side). It is worth mentioning that this process to estimate OD matrixes, by means of the use of regression algorithms, have the capability to generalize the values measured obtaining results even in regions of the feature space where no values have been obtained yet. 4 TRAJECTORY LOCATION ANALYSIS Finally, the last component that we explain in this communication consists in a tool able to analyze not only the origin and the destination of trajectories but also what happens in between. More specifically, and to fix ideas, we can think this Figure 5: The most popular points corresponding to trajectory tool’s goal to be obtaining the points more popular to visit in a locations are labelled with darker color. trajectory. The processing consists in two different phases: the cleaning phase, and the aggregation phase. 5 CONCLUSIONS In this paper we have introduced three components developed within the URBANITE project to convert data into information. The first component is designed to obtain a prediction of the typical traffic flow at a particular sensor location given a set of features, the second component aims to produce OD matrixes from bicycle data and finally the last component consists in a methodology to analyse trajectory locations. These results have been achieved during funding project from the European Union’s Horizon 2020 research and innovation programme under grant agreement #870338. REFERENCES [1] I. Laña, J. Del Ser, M. Velez, and E. I. Vlahogianni, (2018) Road traffic fore-casting: Recent advances and new challenges, IEEE Intelligent Transportation Systems Magazine, vol. 10, no. 2, pp. 93–109. [2] M. S. Ahmed and A. R. Cook, (1979) Analysis of freeway traffic time- series data by using Box-Jenkins techniques, Transportation Research Figure 4: Result of the cleaning phase for a set of GPS points Record , no. 722, pp. 1-9. [3] M. Levin and Y.-D. Tsao. (1980) On forecasting freeway occupancies obtained from a single bike city rental in Bilbao. and volumes (abridgment), Transportation Research Record, no. 773. [4] C. Moorthy and B. Ratcliffe, (1988) Short term traffic forecasting using The cleaning phase is a crucial phase when processing GPS timeseries methods, Transportation planning and technology, vol. 12, no.1, pp. 45–56. data obtained from affordable, not very accurate sensors or in [5] E. I. Vlahogianni, M. G. Karlaftis, and J. C. Golias (2007) , Spatio- areas with tall buildings (urban environment) where the multi- temporal short-term urban traffic volume forecasting using genetically optimized modular networks, Computer-Aided Civil and Infrastructure path of the satellite signal can increase the noise of the Engineering, vol. 22, no. 5, pp. 317–325. measurements. The purpose of this phase is to align the obtained [6] I. Olabarrieta, I. Laña. (2020). Effect of Soccer Games on Traffic, Study measurements with the navigational road network, i.e., the Case: Madrid. 1-5. 10.1109/ITSC45102.2020.9294749. [7] L. Breiman (2001). Random Forests. Machine Learning. 45 (1): 5–32. possible allowed positions for the vehicles. In URBANITE, doi:10.1023/A:1010933404324. Hidden Markov models [11] are used in this phase. Moreover, [8] G. Upton, I. Cook, (2008) Oxford Dictionary of Statistics, OUP. ISBN 978-0-19-954145-4. this process provides an additional result, which consists in the [9] I. Laña, I. Olabarrieta, J. Del Ser. (2021) Output Actionability of Traffic most likely points between measurements. Forecasting Models: Measuring and Understanding Uncertainty of The second phase, the aggregation phase, compares the points Forecasts to provide Confidence Levels (in preparation). [10] G. Voronoi, (1908a). Nouvelles applications des paramètres continus à obtained in the cleaning phase for all the trajectories. Probably la théorie des formes quadratiques. Premier mémoire. Sur quelques propriétés des formes quadratiques positives parfaites" (PDF). Journal 648 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia I. Olabarrieta et al. für die Reine und Angewandte Mathematik. 1908 (133): 97–178. doi:10.1515/crll.1908.133.97. S2CID 116775758. [11] P. Newson, J. Krumm. Nov. (2009 ). Hidden Markov Map Matching Through Noise and Sparseness. 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2009), November 4-6, Seattle, WA 649 Applicable European Regulations for Data-driven Policy- making Sonia Bilbao Maria José López Sergio Campos TECNALIA, Basque Research and TECNALIA, Basque Research and TECNALIA, Basque Research and Technology Alliance (BRTA), Technology Alliance (BRTA), Technology Alliance (BRTA), P. Tecnológico Bizkaia, Ed. 700, 48160 P. Tecnológico Bizkaia, Ed. 700, 48160 P. Tecnológico Bizkaia, Ed. 700, 48160 Derio, Spain Derio, Spain Derio, Spain Sonia.bilbao@tecnalia.com MariaJose.Lopez@tecnalia.com sergio.campos@tecnalia.com ABSTRACT This scenario can be built on two pillars: 1) co-creation sessions and 2) empirical analysis on stakeholder trust, attitude, impact, Data-driven policy making aims to make optimal use of data and benefits and risks in the use of disruptive technologies. Now, collaborate with citizens to co-create urban policies and, in traditional technological solutions are no longer valid in this general, to conduct a more reliable decision-making process. The situation, and disruptive technologies such as big data analysis or European Commission considers data an essential resource for artificial intelligence emerge as a promising support to those economic growth, competitiveness, innovation, and disposes as responsible for formulating new policies. Data-driven policy part of its strategy a set of regulations and guides, aiming to that making aims to make optimal use of existing heterogenous data more data becomes available for use while keeping the rights and and collaborate with citizens to co-create policy. This trustworthy of the companies and individuals who generate and opportunity entails specific challenges to favor the acceptance by consume the data during the whole lifecycle. These regulations users of the results obtained through the application of these impact and open new challenges and opportunities when technologies and, first, to collect the relevant data from the addressing the decision-making process in URBAN different local stakeholders. These are some of the objectives of Transformation and specifically urban mobility as in the case of the URBANITE project, to face challenges, attitudes, confidence the URBANITE project. and opportunities in the use of disruptive technologies in public services in the context of urban mobility. KEYWORDS Data, regulations, ethics, trustworthy, privacy, governance URBANITE identifies several key results: a Social Policy Lab – an environment to promote digital co-creation and methodologies and methods to support the co-design and co- 1 INTRODUCTION creation for policies, a Data Management Platform – To provide Urban mobility faces greater uncertainty and complexity in the automatic support to the whole data processing chain and its life long term generated by two main factors: the demand for growth cycle, starting with the collection process up to its use and a in urban environments, the pressure for a more sustainable model Decision-Making Support System – Powerful tools which of mobility in the face of the emergence of global warming. In combine multiple data sources with advanced algorithms, general, we find that the social conscience is changing in favor simulation, recommendation, and visualisation. of more equitable and sustainable ways, and the recovery of the space of the city for the people. On the other hand, the accelerated The project identifies different stages from the perspective of technological development in the transport modes and business data and more specifically, its availability, openness and privacy: models themselves, including innovations such as autonomous • 1st Stage- Setup of participation labs and initial gathering: driving, micro-mobility, connected vehicles, electro-mobility, o Open data currently available mobility as a service (MaaS), new vehicle ownership models, etc. o including identification and recruitment of mark specific challenges. in your deployment. These trends are participants, the preparation of an informed changing the landscape of urban planning and mobility consent procedure to implement for individual management in cities, incorporating new challenges. All of these participation require new advances in mobility planning processes and o The register and use of the virtual participation methods, with the aim of helping public administrations and platform as a complement of previous sessions policy makers to better understand this new context, supporting them in decision-making and policy definition. Policies should • 2nd Stage. The potential use of existing non-open data, be discussed among the main actors in the new urban mobility personal and non-personal on the cities to the objectives of scenario: citizens, service providers, public servants and political the project. leaders. • 3rd Stage. The transfer of collected data from 3rd parties, defining a transfer agreement among both parties (company and city use case) Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 2 RELATED EUROPEAN REGULATIONS 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 On the other hand, the European Commission considers data an must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia essential resource for economic growth, competitiveness, © 2021 Copyright held by the owner/author(s). innovation, defining an European strategy for data aiming to 650 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Sonia Bilbao, Maria José López and Sergio Campos ensure Europe's global competitiveness, a data sovereignty, that appropriately. To ensure that we are on the right track, it is more data becomes available for use, while keeping the rights of necessary to abide by a human-centered approach to AI, without the companies and individuals who generate and consume the losing the goal of improving human well-being. The concept of data during the whole lifecycle. As part of this support, the trusted AI addresses reliance on technology as a first step. The Commission has proposed some material as part of its data new guidelines are aimed at all parties involved who develop, strategy, disposing several normative and guides to conduct a apply or use AI, encompassing companies, organizations, success and trustworthy data management. researchers, public services, institutions, individuals or other entities. 2.1 Data Governance Act This initiative refers to the management of personal as well as According to the regulations “Reliable AI has two components: non-personal data, therefore being linked at the legislative level 1) it must respect fundamental rights, current laws and essential with the General Data Protection Regulation (GDPR)[1] and the principles and values, so as to guarantee an« ethical purpose », Directive on privacy and electronic communications [2]. The and 2) it must be reliable and technically sound , since a little European Commission has implemented a solid and trustworthy technological mastery can cause involuntary damages, although legal framework for the protection of data, in order to promote a the intentions are good ”. single data market, for which it must guarantee that data from the public sector, companies and citizens can be available and used Therefore, these Guidelines establish the framework of a reliable in the most efficient and responsible way possible, while AI, guiding in three levels of abstraction, from the most abstract companies and The Data Governance Act [3] is the first of a set to the most concrete of aspects to be evaluated: of measures announced in the 2020 European data strategy, aims • Guarantee of the ethical purpose of AI, establishing to promote the availability of data for its use, increasing trust fundamental rights, as well as the essential principles and between the parties and strengthening data collection values, which it must comply with. mechanisms throughout the European Union. The DGA will also • A series of guidelines, addressing both ethical purpose and support the establishment and development of common technical soundness, listing the requirements for reliable AI, European data spaces in strategic domains, involving both public and providing a summary of technical and non-technical and private actors. methods that can be used for their application. • A concrete, but not exhaustive, list of aspects that must be The framework addresses the following scenarios: evaluated in order to achieve reliable AI. • The transfer of public sector data for reuse, in cases where such data is subject to the rights of third parties. It establishes a mechanism for the reuse of certain categories of protected data from the public sector, which is subject to respect for the rights of third parties. • The transfer of personal data with the help of intermediaries, whose work will consist of helping providers to exercise the rights conferred by the General Data Protection Regulation (GDPR). The objective is to strengthen trust in the exchange of personal and non-personal data, and reduce the costs of transactions linked to the exchange of data between providers and their consumers, with neutral facilitators, • The transfer of data for altruistic purposes (making data available to the common good, on a voluntary basis, by Figure 1: Relation and overlapping among regulations individuals or companies). Establish a registration and consent in order to reduce costs and facilitate data According to these principles, the work package in charge of the portability. definition, design and adaption of artificial intelligence and data • analytics is ensuring that the applied methods meet the seven key The exchange of data between companies in exchange for requirements for Trustworthy AI: some type of remuneration. 1) human agency and oversight. URBANITE proposes a decision support methodology and supporting tool for 2.2 ETHICS GUIDELINES FOR policy creation, that combine and carefully balance different methods: TRUSTWORTHY AI 2) harvested historical data, GIS, expert knowledge, outputs of Despite the fact that AI technologies are mature enough, their decision models, and others. The last word will remain in adoption by companies is very uneven, and in general, much the hands of municipal experts, the platform being a tool to lower than one would expect. There are obstacles that hinder the facilitate their decision. On the other hand, one of the pillars widespread extension of AI technologies, both cultural and of the project is the implementation of a thoughtful space of discussion among the main actors of the new urban mobility technical. AI technologies will not spread massively until the scenario: citizens, service providers, public servants and scientific community is able to develop reliable technology from policy makers. the user and from the different data providers. On the other hand, 3) technical robustness and safety. The work focused on the the use of these technologies involves risks that must be managed algorithms and simulations to be deployed, defines for as 651 Applicable European Regulations for Data-driven Policy-making Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia objective metrics a pair of KPIs, refereed to the precision of nature of the model to be explained, from intrinsically predictions and the quality of recommended policies or transparent to completely opaque and unintelligible; the user of procedures. the algorithms; and finally, the way in which said explanation 4) privacy and data governance, a fundamental right must be prepared and presented to the decision maker, which will particularly affected by AI systems. Prevention of harm to depend on their degree of knowledge, as well as the intrinsic privacy also necessitates adequate data governance that possibilities offered by the model to be explained in one way or covers the quality and integrity of the data used. All the another. algorithms will work on the gathered data, just (pseudo) anonymised. If applied during the research stage on the algorithms, all the GRPR measures will be analysed and Adaptation is the reaction of a system, model or process to new adopted to use personal data. circumstances, with the idea of maintaining its performance or 5) Transparency [7], the principle of explicability and reducing its loss, compared to the ideal conditions that were encompasses transparency of elements relevant to an AI taken into account in its design and initial adjustment. The main system: the data, the system and the business models: This problem in scenarios whose underlying phenomena change over implies traceability of decision along the whole cycle of time, without being addressed by the model itself, is that the data, from datasets, gathering, labelling and process, conclusions, predictions or categorizations will not be reliable. Explainability concerns will be considered for the methods This phenomenon is called concept drift [8][9]. applied, ensuring a better understanding of the underlying processes and related human decisions (e.g. xAI approach). Robustness refers to the ability of a system to maintain service In any case, the simulation and rules-based reasoning approaches, are well sited from the explainability point of when external incidents occur. In the case of urban planning, it view. will not be so critical, since the decisions to be made will not be 6) diversity, non-discrimination and fairness. URBANITE made in real time; However, the data ingestion of the different gather existing open data portals, geographical information data sets and available stores, if it must be operational, to systems (GIS), data coming from private data providers, the minimize the loss of input data, in addition to being robust data basis is any, comes in origin. SoPoLab sessions and use case algorithms in such loss situations, fluctuations in the frequency evaluation support the feedback from stakeholders who may of the themselves, poor quality data, etc. In the URBANITE directly or indirectly be affected throughout its life cycle. project, data quality is explicitly addressed through the 7) dedicated assessment of the algorithms during their design implemented components associated with data preservation. and use case deployment ensures the auditability. 8) environmental and societal well-being. In the last term, URBANITE provides a new decision-support system for Stability means ensuring that there are no surprises for the user Planning Sustainable Mobility and the early evaluation of in terms of functionality. In general, the algorithms are worked urban policies. A Sustainable Urban Mobility Plans in a specific geographic area and according to the available data (SUMP), defines strategic plans based upon a long-term sets. However, for their deployment in a real environment, it is vision of transport and mobility, guaranteeing technical, necessary to project them to larger areas and volumes of data. economic, environmental and social sustainability. This issue must be taken into account from the design stage of the algorithms, to optimize their algorithmic complexity, which represents the amount of resources (temporal, execution time and 3 ALGORITHMS ACTIONABILITY space, required memory) that an algorithm needs to solve a Taking into account the previous regulations and based on problem. This characteristic allows to determine the efficiency of previous experience in the context of Intelligent Transportation this algorithm, not in terms of absolute measures but measures Systems [4], it is confirmed that aspects such as trust, precision relative to the size of the problem. Currently, the availability of and reliability, among other non-functional properties, are new technologies and paradigms of parallel and distributed essential for predictive and analytical techniques to be practices processing of massive volumes of data, allows an escalation of in its use. We present the term Actionability, as the characteristic the methods, obtaining adequate response times. However, its that any system based on data analysis or artificial intelligence exploitation requires the adequate implementation and must present to be implemented and used successfully in a real adaptation of the algorithms according to the architecture in operating environment. This concept, in turn, identifies a series which they will be deployed, as well as optimizing this of desirable characteristics, which in URBANITE are deployment of analytical workloads in the different layers. contextualized in the field of urban mobility planning. Another key feature is the compliance of the new methods with Data-based models are usually subject to uncertainty, involving transportation engineering. Existing traffic and mobility non-deterministic stochastic processes, both in the learning, engineering practices are well established, with a powerful execution or training mechanisms / input data, and also present knowledge base. A better understanding of the hybridization of in the results. Once deployed, it is essential to provide an data analysis and simulation methods, data-driven and model- objective measure of the reliability and precision of the results, driven approaches, by combining the strengths of each side, will winning in terms of Trust. The need to explain and render the help us improve the models by identifying more complex underlying analytical models interpretable is undoubtedly one of underlying assumptions. In general, the results are closely linked the research fields with the greatest impact, being considered to the experiments carried out; transferability is a desirable under the concept of Explainable Artificial Intelligence [5][6] characteristic for algorithms and any model, in order to present (xAI). This field of study comprises different techniques and adequate performance and functionality in other contexts and methods, taking into account three fundamental factors: the starting data, different from those used in learning. 652 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Sonia Bilbao, Maria José López and Sergio Campos Finally, we cannot forget the contextual aspects identified by the exploitation, data management and artificial intelligence EU for the definition of sustainable mobility policies, measures technologies, machine learning and advanced processing, the and solutions, as part of SUMP and any support tool, with the requirements that these new algorithms must present in the future aim of contributing to urban regeneration, transport have been identified. Finally, it introduces the concept of sustainability, social inclusion and social empowerment through Actionability as a key property of any data-based modeling and active participation. treatment process to generate knowledge of practical value for decisioning. All these aspects open challenges and, also opportunities for URBANITE project. 4 OPPORTUNITIES AND NEXT STEPS Additionally, to the actionability requirements for our methods ACKNOWLEDGMENTS and algorithms, the new regulation and especially the Data Governance Act presents a set of topics or opportunities to These results have been achieved during funding project from the explore from the different action lines. The following table European Union’s Horizon 2020 research and innovation presents some of them, according to the type of data to explore programme under grant agreement #870338. on the project: public, personal or altruistic data . REFERENCES Table 1: Challenges and Research Opportunities [1] DO L 119 de 4.5.2016, p. 1. [2] DO L 201 de 31.7.2002, p. 37. [3] https://digital-strategy.ec.europa.eu/en/library/proposal-regulation- european-data-governance-data-governance-act [4] Ibai Lana. Vlahogianni Elenni, Javier Del Ser, 2020, “From Data to Actions in Intelligent Transportation Systems: a Prescription of Functional Requirements for Model Actionability,” arXiv, 2020. [5] Alain Barredo, N. Díaz-Rodríguez, Javier Del Ser, A. Bennetot, S. Tabik, A. Barbado, S. García, S. Gil-López, D. Molina, R. Benjamins, R. Chatila, Francisco Herrera, “Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI. arXiv:1910.10045,” 2020. [6] D. Doran, S. Schulz and T. R. Besold, 2017, “What does explainable AI really mean? a new conceptualization of perspectives. arXiv:1710.00794,” 2017. [7] A. Datta, S. Sen and Y. Zick, 2014, “Algorithmic transparency via quantitative input influence: Theory and experiments with learning system,” in 2016 IEEE symposium on security and privacy (SP), 598–617, 2016. [8] J. Gama, I. Zliobaite, A. Bifet, M. Pechenizkiy and A. Bouchachia, 2014, 5 CONCLUSIONS “A survey on concept drift adaptation,” ACM computing surveys (CSUR), vol. 46, no. 4, p. 44, 2014. During the first period of the project, some relevant algorithms [9] Jesús Lobo, Javier Del Ser, Nekane Bilbao Cristina Perfecto, 2018, and data analysis have been identified based on the project's use “DRED: An evolutionary diversity generation method for concept drift adaptation in online learning environments,” Applied Soft cases. Having analyzed the different regulations around the 653 Supporting Decision-Making in the Urban Mobility Policy Making Erik Dovgan Maj Smerkol Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia erik.dovgan@ijs.si maj.smerkol@ijs.si Miljana Sulajkovska Matjaž Gams Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia miljana.sulajkovska@ijs.si matjaz.gams@ijs.si ABSTRACT City mobility is changing rapidly due to population growth and disruptive technologies. To efficiently handle these changes, poli- cymakers need advanced tools based on AI, including simulation, prediction, decision making, and visualization. In the URBANITE H2020 project, we are developing a decision support system (DSS) that is based on DEXi and enables the decision-makers to combine low-level mobility data obtained with simulation, into high-level attributes suitable for decision making and comparison of mobil- ity scenarios. By providing the user preferences in advance, DSS can be also used in combination with machine-learning models to search for the best mobility policies automatically. KEYWORDS decision making, mobility, urban transformation 1 INTRODUCTION The mobility in cities is changing rapidly. On one hand, the pop- Figure 1: The architecture of the URBANITE system. ulation in cities is growing which results in increased congestion and pollution. On the other hand, new and disrupting mobil- ity modes are being introduced, such as vehicle sharing, hop on/off bikes, etc. The city policymakers thus face a very complex The developed DSS aims to enable the users to select the most problem: how to improve mobility under growing congestion appropriate policy actions based on data from simulations, popu- pressures, while considering new mobility modes [1]. Advanced lation data, current and predicted traffic data, and user (citizen, tools that include artificial intelligence (AI) approaches can sig- decision-makers) preferences. By defining the user preferences in nificantly help policymakers to select the most appropriate ac- advance, it weights and hierarchically aggregates the basic data tions [4]. to obtain one or a few objectives, based on which the evaluated AI-based tools for city mobility typically include the city mod- policies are compared and ranked. The policy ranking represents els and traffic simulation, which enables the users to simulate the key information for the final decision regarding which policy various traffic situations [3]. We are developing a system that should be applied. will, besides city models and traffic simulation, include also a de- The rest of the paper is organized as follows. Section 2 presents cision support system (DSS) [2] and a machine learning module. the URBANITE system. The decision support system within UR- The decision support system will support the user, either hu- BANITE is described in Section 3. Finally, Section 4 concludes man or algorithm, in selecting the best policy, while the machine the paper with a summary and ideas for future work. learning module will aim at replacing human decision-makers with algorithmic ones. In this paper, we focus on the DSS of the 2 OVERVIEW OF THE URBANITE SYSTEM URBANITE H2020 project [5]. The URBANITE system consists of several modules such as tools for the involvement of various types of stakeholders, including Permission to make digital or hard copies of part or all of this work for personal the general public. However, from the point of view of the pre- 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 sented decision support system, only the modules relevant for the full citation on the first page. Copyrights for third-party components of this DSS are presented in Figure 1. work must be honored. For all other uses, contact the owner/author(s). There are two main inputs to DSS. The first one consists of the Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). expert knowledge, provided by the decision-makers. This knowl- edge is of key importance when building hierarchical decision 654 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Dovgan et al. models, as well as when defining user preferences (see Section 3 process and typically involves combining qualitative attributes for details). of various types. The second input consists of raw data including city models, Hierarchical decision models are not able to directly handle population data, and evaluation results from the traffic simulator. the city model data or the raw data obtained from the traffic Population data include the number of people in the urban area simulator. Therefore, the baseline data need to be preprocessed as well as their distribution between the districts. The city model and, if appropriate, aggregated. For example, if the city pollution consists of a map of roads, districts, public areas, etc. Finally, is required as an input to the hierarchical decision model, it has traffic simulation results are trip traces that include all the rel- to be calculated from all the trips within the city. evant data such as the (vehicle) positions, time, and pollution. Finally, policy evaluation has to be executed. This is done These results are obtained by evaluating a mobility policy with by applying the preprocessed traffic simulator data within the the traffic simulator. To this end, the simulator processes the pop- hierarchical decision model. The resulting values of the high- ulation data, the city model, and the past traffic data to emulate level attributes, selected based on user preferences, are then sent the characteristics of real-life traffic as much as possible. to decision-makers or machine-learning models (see Figure 1). The mobility policy consists of a set of actions to be applied The hierarchical decision models, including their definition and within the urban area (such as closing a specific road for cars) execution, were implemented with DEXi [2]. and can be proposed either by decision-makers or by machine- learning models. Both take into account the policy evaluation, 3.2 Hierarchical Decision Model for Mobility computed by the DSS. The main difference between the two approaches is the fact that decision-makers rely on expert knowl- Policy Evaluation edge and define the mobility policies by hand, while machine- A new hierarchical decision model was developed by focusing on learning models apply pattern-recognition approaches, process a the needs and preferences of the URBANITE project [5], based possibly huge amount of data, and select mobility policies auto- on the user experience of four major EU cities. The model shown matically. in Figure 2 was developed based on mobility policies that include Finally, the decision support system consists of several com- building new roads, closing parts of the city like squares, setting ponents that are described in Section 3. up new lines of public transport including ferries, and other potential modifications of the city mobility. For a policy, three areas within the city were identified as relevant: 3 DECISION SUPPORT SYSTEM (DSS) • Target area where the policy action is applied Our DSS aims to evaluate mobility policies, i.e., for each policy • Nearby area that surrounds the target area and which is produce one or a limited set of objectives that are easily inter- directly influenced by the applied policy pretable and handled by the experts. Note that a baseline mobility • The entire city policy is evaluated by the traffic simulator, but the evaluation provided by a standard simulator is very difficult to process by The attributes were divided into three categories: experts due to a large amount of data since the evaluation con- • Road network sists of traces of all the trips within the city. Therefore, the DSS These attributes measure the size of the city area where aggregates evaluation data into meaningful high-level attributes the policy action has a direct influence. They also consider to enable efficient and effective decision-making. the capacity of the affected roads and take into account both target and nearby areas. 3.1 Components of the URBANITE DSS • Population-related attributes including the type of the area and public transport data. The main component of the DSS is the hierarchical decision Area type is defined with the position within the city model (see Figure 1). A hierarchical decision model is defined by (e.g., center, periphery), the district type (e.g. residential, the experts/decision-makers based on their expert knowledge. commercial), and the population number. Public transport It starts with the evaluation values, provided by the traffic sim- counts the available bus and underground stops, and the ulator, and iteratively combines semantically similar attributes lanes of public transport. All these attributes are measured into higher-level attributes until only one attribute remains. This in both target and nearby areas. results in a tree structure in which the root represents the final • Policy impact evaluation of the policy. However, it is not required to always use It measures the change with respect to the baseline sce- the final evaluation during the decision-making process. In some nario when no policy action is applied. The following cases, it is more appropriate to use several high-level attributes aspects are taken into account: (e.g., pollution and congestion) to compare the policies in all the aspects that the decision-makers are interested in. In this case, – Change in air pollution the selected attributes are inner nodes of the tree structure. – Change in the number of used private vehicles To create the hierarchical decision model and to select the – Change in the number of used bicycles relevant attributes, user preferences have to be obtained. They – Change in the number of used public transport are included in the module by experts/decision-makers. When – Change in the number of pedestrians In addition, it also takes into account congestion change. creating the decision model, the preferences are used to weigh All the attributes are measured in both target and nearby the attributes within the tree structure. More precisely, when areas, as well as in the entire city. combining attributes into a higher-level node/attribute within the tree structure, a utility function needs to be defined, which The developed model is intended to be used for both compar- specifies how each combination of lower-level attributes trans- ing the effects of applying a policy with the baseline as well as forms into the higher-level attribute. This is a preference-based comparing the effects of various policies between themselves. As 655 Supporting Decision-Making. . . Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 3: An example of the utility function for the se- lected attributes. Figure 4: Definition of two test scenarios. Figure 2: A hierarchical decision model for mobility policy evaluation. Figure 3 that shows how the Target area attribute and the Nearby area attribute are combined into the Public transport attribute. a consequence, some attributes focus on comparison with base- line, while others focus on differences among various policies. 3.3 Evaluation of Mobility Policies Selection of the attributes and their organization into the tree The hierarchical decision model, described in Section 3.2, was structure is only the first step when building the hierarchical used to evaluate a test policy that prescribed that the main square model. The second step consists of defining the functions that of a test city should be closed. The effects of this policy were aggregate the lower-level attributes into higher-level ones, i.e., compared to the baseline, where no actions were taken. utility functions. All the attributes in the inner nodes of the tree First, both scenarios (no intervention and closed square) were were defined as categorical from 1 to 5, which facilitated the simulated and the obtained results were preprocessed. Second, utility function definition. The default scale defined the higher the data were inserted in DEXi as shown in Figure 4, where the better, except for the pollution where the the-lower-the-better each column represents one scenario and colors represent the scale was applied. An example of the utility function is shown in evaluation of single attributes (green: good, black: neutral, red: 656 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Dovgan et al. Figure 7: Evaluation of the scenario with closed square. Figure 5: Comparison of the overall quality of the test sce- narios. aggregation of mobility attributes needs to be defined to get a low number of higher-level attributes that make the decision-making process feasible. In this paper, we proposed to aggregate the mobility attributes with DEXi. DEXi applies hierarchical decision models that are defined based on expert/decision-maker knowledge. We devel- oped a new hierarchical decision model that was then used for basic and multiobjective comparison of mobility scenarios. This paper also presented a basic graphical interface for com- paring the scenario outputs, while additional and more advanced GUIs are still under development. The evaluation of the devel- oped decision model on a variety of mobility policies is ongoing and aims at determining whether the model is suitable for all the relevant scenarios. In case of discovered deficiencies, we will Figure 6: Evaluation of the scenario without interven- upgrade the model with additional attributes and/or attribute tions. rearrangement. ACKNOWLEDGMENTS bad). This figure shows that the differences between the scenarios are in the target area roads and the impact attributes. The impact This work is part of a project that has received funding from is negative only in a minority of attributes: in the nearby area the European Union’s Horizon 2020 research and innovation and the congestion when observing the entire city (see the color programme under grant agreement No. 870338. The authors also change from black to red). On the other hand, there is a positive acknowledge the financial support from the Slovenian Research change in the majority of the impact attributes (black color to Agency (research core funding No. P2-0209). green). REFERENCES The selected scenarios were evaluated both based on the over- all quality and based on a set of the most relevant high-level [1] M. Batty, K.W. Axhausen, F. Giannotti, A. Pozdnoukhov, A. attributes, i.e., inner nodes of the tree. The overall quality com- Bazzani, M. Wachowicz, G. Ouzounis, and Y. Portugali. 2012. parison is presented in Figure 5, while the comparison on the Smart cities of the future. European Physical Journal-Special selected attributes can be found in Figures 6–7. These figures Topics, 214, 481–518. show that the overall quality of the closed-square scenario is [2] Marko Bohanec. 2020. DEXi: Program for Multi-Attribute higher in comparison to no interventions. As noted previously, Decision Making, User’s Manual, Version 5.04. IJS Report for the pollution change in Figures 6–7, lower, i.e., near the center DP-13100. Jožef Stefan Institute, Ljubljana, Slovenia. of the graph is better, while for other attributes, higher, i.e., near [3] Erik Dovgan, Jaka Sodnik, Ivan Bratko, and Bogdan Fil- the edge of the graph is better. In these figures, we can observe ipič. 2017. Multiobjective discovery of human-like driving a similar trend as in Figure 4. The difference is that in Figure 4 strategies. In Proceedings of the Genetic and Evolutionary we compare the scenarios on basic attributes (leafs of the tree), Computation Conference Companion (GECCO ’17), 1319– while in Figures 6–7 we compare scenarios on the higher-level 1326. attributes (inner nodes of the tree). Finally, Figure 5 shows the [4] Matjaž Gams, Irene Yu-Hua Gu, Aki Harma, Andres Munoz, comparison on the top-level attribute, i.e., the root of the tree. and Vincent Tam. 2019. Artificial intelligence and ambient intelligence. Journal of Ambient Intelligence and Smart En- 4 CONCLUSION vironments, 11, 1, 71–86. Selection of the best mobility policy for a city is typically a com- [5] The URBANITE Project. 2021. https://urbanite-project.eu/. plex task since the policy can influence a large variety of mobility aspects. In addition, simulation tools typically produce a large amount of data that needs to be appropriately preprocessed and aggregated. Consequently, a suitable approach for hierarchical 657 URBANITE Data Management Platform Fritz Meiners Sonia Bilbao Gonzalo Lazaro Fraunhofer FOKUS TECNALIA, Basque Research and TECNALIA, Basque Research and Digital Public Services Technology Alliance (BRTA), P. Technology Alliance (BRTA), P. Kaiserin-Augusta-Allee 31 Tecnológico Bizkaia, Ed. 700, 48160 Tecnológico Bizkaia, Ed. 700, 48160 10589 Berlin, Germany Derio, Spain Derio, Spain fritz.meiners@ sonia.bilbao@tecnalia.com gonzalo.lazaro@tecnalia.com fokus.fraunhofer.de Giuseppe Ciulla Research & Development Laboratory Engineering Ingegneria Informatica Palermo, Italy giuseppe.ciulla@eng.it ABSTRACT • Data Fusion and aggregation. Data aggregation is the This paper describes the Data Management Platform developed process of gathering data and presenting it in a in URBANITE H2020 project. This platform provides automatic summarized format, e.g. to hide personal information mechanisms to harvest, curate, fuse and visualize existing open or to provide information in a synthetic form. Data and proprietary data coming from different sources related to fusion is the process of integrating multiple data urban mobility and transportation (e.g. traffic data from cars, sources to produce more consistent, accurate, helpful public transport, bikes or ferries; air quality and noise; events, information and sophisticated models than those parking, and so on). provided by any individual data source. • Data Storage & Retrieval providing the means to store KEYWORDS and retrieve datasets, DCAT-AP compliant metadata, and related data. Data harvesting, data curation, DCAT-AP metadata, data storage • Data Catalogue offering the functionalities to discover and access the datasets collected and managed by the 1 INTRODUCTION components of the URBANITE Ecosystem. One of the main goals of the research carried out in URBANITE H2020 projects, is to provide algorithms, tools and models to 2 DMP ARCHITECTURE support decision-making processes in the field of urban planning Figure 1 represents the component diagram of the Data and mobility. This support is based on the analysis of the current Management Platform (blue rectangle) and its interaction with situation based on harvested and fused data, on data simulations the other modules in the URBANITE Ecosystem. and the prediction of future situations when changing one or more variables. Hence, the availability of good quality data coming from heterogeneous data sources and its interoperability for data aggregation and fusion is highly important. The Data Management Platform (DMP) provides the components for data acquisition, aggregation and storage. These components are: • Data Harvesting, Preparation and Transformation covering the entire process of fetching, preparing, transforming, and exporting data for storage • Data Anonymization to transform datasets in conformity with data protection requirements for further data analysis. • Data Curation which deals with enrichment and annotation of data. Figure 1. Component diagram of the DMP Permission to make digital or hard copies of part or all of this work for personal or 3 IMPLEMENTATION 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 3.1 Data Harvesting, Preparation and must be honored. For all other uses, contact the owner/author(s). Transformation Information Society 2021: 24th international multiconference , 4–8 October 2021, Ljubljana, Slovenia The process of fetching, preparing, transforming, and exporting © 2021 Copyright held by the owner/author(s). data (from now on referred to as harvesting), i.e. providing a way 658 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia F. Meiners et al. to make heterogeneous data available in defined format and The data preparation component is responsible for means of access, has been implemented following the form of a performing initial cleaning and sanitation of the data provided by pipeline, as shown in Figure 2. This means that data is passed the harvesting component. This ensures a fixed level of data through the pipeline, and each component is agnostic of the other quality and integrity, which is required by the transformation steps. This leads to lose coupling and improves flexibility component to operate flawlessly. allowing steps to be omitted if not necessary for a given data Data transformation is a key step in the harvesting pipeline. It source. The pipeline has been implemented using the open source cannot be expected that the municipalities provide their data in solution named Piveau Pipe Concept [1, 2]. one of the common data models developed by FIWARE used in Each of the components in the pipeline is implemented as a the URBANITE context. As such, the transformation of the service that exposes a common RESTful interface. This way, heterogeneous data sources into common models is vital for services can be connected in a generic fashion to implement frictionless processing of the data henceforth. For a flexible specific data processing chains. No central instance is approach, the actual transformation instructions are loaded via responsible for orchestrating the services. A scheduler is in scripts, either JavaScript for JSON based payloads or XSLT for charge of launching the pipes and how services are connected XML based payloads. More engines can be added as pipeline together is specified in a JSON file known as the pipe descriptor. modules at a later point in time. An example of a pipe descriptor is provided in Figure 3. Each of the segments describes a service in the pipe. In the example there are three services, the first named importing-bilbao-air- quality that downloads Bilbao air quality data, the second named transforming-js that transforms the data according to a JavaScript file and the third one named exporting-data-storage that invokes the storage and retrieval component to store the data and its metadata in two dedicated repositories. The segment number field indicates the order in which the service should be executed in the pipe. Figure 2. Harvesting process In detail, the harvesting process would typically consist of the following steps: 1. The scheduler triggers a pipeline 2. The harvester retrieves the data from the source’s API and forwards it into the preparation component. 3. After cleaning and validating, the preparation component forwards the data to the transformation component. 4. The data is transformed to the applicable NGSI data model and forwarded to the exporter. 5. Finally, the exporter writes the harmonized data into the data storage component. The scheduler serves two main purposes: keeping track of existing pipe descriptors and managing triggers for these pipes. Each pipe descriptor is stored as a JSON file and contains a definition of components (endpoints, chronological order, specific configurations) that make up the processing sequence. Each processing chain is defined in one of these files. The scheduler reads these files to become aware of which pipes are available. These can then be assigned to a periodic trigger for recurring execution. The data harvesting component is responsible for fetching data from a given API. It does not alter the data. It can be considered the entry point of the data into the pipeline. As such, a dedicated component is required for each type of data source. Figure 3. Example of a Piveau Pipe Descriptor The harvesting component may implement pagination mechanisms for handling data in chunks. However, this does not When a pipe is triggered the service in segment number 1 is impact the pipeline – each chunk is handled individually and called. Once finished, data that needs to be passed along the does not depend on other chunks. processing chain is written into a payload field of the next 659 URBANITE Data Management Platform Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia component in line. For smaller amounts of data this can happen The Data Storage & Retrieval component provides REST directly, for larger amounts of data a pointer to an external APIs so that the Exporter of the harvesting process can store the datastore can be used. transformed data. Besides, a new DCAT distribution is stored which is associated with the existing metadata of the dataset, with 3.2 Data Anonymization accessUrl equal to the API endpoint to access the transformed The anonymization component is a RESTful microservice data. An example of this is shown in Table 1. capable of transforming large datasets in conformity with data protection requirements for further data analysis. In order to Table 1. Instance of a distribution in JSON-LD format achieve a certain degree of anonymization the user can mark specific attributes that are likely to reveal information about a { person or a smaller group. Those identifiers are then transformed "@id" : "https://urbanite- in a way that ensures a sufficient level of anonymization. project.eu/ontology/distribution/009b9f0e-e780-4e9d-8153- Currently supported anonymization methods are suppression and 520dc8943195", generalization, which either delete attribute entries in a row or "@type" : "dcat:Distribution", generalise them according to a fixed hierarchy, such as street -> "description" : "Air Quality information for bilbao day zip code -> city. 2021-05-01 in NGSI-LD representation", "format" : 3.3 Data Storage & Retrieval "http://publications.europa.eu/resource/authority/file- type/JSON_LD", The Data Storage & Retrieval component provides the means to "license" : store and retrieve datasets (transformed to URBANITE common "http://publications.europa.eu/resource/authority/licence/CC data model compliant with FIWARE) and metadata (DCAT-AP). _BY", DCAT-AP [3] is used as the common metadata schema to "title" : "Air Quality information for bilbao day 2021- describe datasets in URBANITE. Two repositories are used, one 05-01", for the metadata and the other for the transformed data. This is "accessURL" : shown in Figure 4. "https://bilbao.urbanite.esilab.org/data/getTDataRange/airQu alityObserved/bilbao?startDate=2021-05- 01T00%3A00%3A00.000Z&endDate=2021-05- 01T23%3A59%3A00.000Z" } The technology stack used to implement the component consists of three levels, as depicted in Figure 6. Figure 4. Data Storage & Retrieval repositories The main concepts of the DCAT-AP model are catalogues, datasets and distributions. A catalogue represents a collection of datasets; a dataset represents a data collection published as part Figure 6. Data aggregation & storage technology stack of a catalogue; and a distribution represents a specific way to access to specific data (such as a file to download or an API). At the bottom level we have the storage repositories, being a This relationship is shown in Figure 5. combination of different types of databases: SQL databases, like The concept dcat:Dataset informs about the title, description, MySQL and NoSQL databases, like MongoDB. The design is access rights, creator, frequency, spatial/geographic and also open to the usage of other storage mechanisms that may be temporal coverage, spatial and temporal resolution, publisher, etc. useful in the future, such as timeseries databases, files, semantic The concept dcat:Distribution provides metadata about the triple stores, etc. distribution, e.g. the property dcat:accessURL provides the The intermediate level offers the mechanisms for both storing information about how to access to specific data. Other important and retrieving data. In turn it consists of two components: a metadata related to the distribution are, for instance, the license, REST API with predefined methods for inserting or accessing a description, the format of the data (e.g. CSV, JSON), etc. data and metadata, and a JDBC connection, through the Presto software, to perform custom queries (SQL statements) different to those offered by the API. All the interaction with the storage system is made through these two mechanisms, not allowing direct access to the data. This makes the choice of the specific database that stores the data transparent to the upper processing Figure 5. Simplified DCAT-AP Model 660 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia F. Meiners et al. layer and can be modified without affecting the processes that further provided to the APIs, 2) Advanced Visualization to build make use of the component. visualization taking advantage of the DCAT-AP distributions it Finally, at the top level we have the processes that can be manages and 3) Data Storage & Retrieval to retrieve DCAT-AP defined to feed the databases or make use of the data, e.g. data datasets and distribution metadata. Finally, the Data Catalogue aggregation processes. component is able to federate external sources such as Open Data portals or other sources providing DCAT-AP metadata. 3.4 Data Catalogue The Data Catalogue offers the functionalities to discover and access the datasets collected and managed by the components of the URBANITE ecosystem. Apart from the possibility to search over these datasets, the Data Catalogue also offers the possibility to search useful data across external “federated catalogues” (such as Open Data Portal) to increase the chance to find useful data. The administrator is in charge of managing the federation of the catalogues, where a catalogue represents a data source. He/she can add new catalogues, delete or edit the existing ones. Moreover, the administrator can manage the platform configurations. The end-user is then able to perform a federated metadata Figure 8. Data Catalogue – Dataset search (example) search among the harmonized DCAT-AP datasets provided by the federated catalogues. Moreover, the end-user can perform SPARQL queries over the federated RDFs provided by the federated catalogues, or he/she can access to statistics about the federated catalogues. The Data Catalogue exposes APIs to access its functionalities; thus, an external system will be able to interact with the platform using such APIs. The Data Catalogue is based on Idra [4]. Idra is a web application able to federate existing Open Data Management Systems (ODMS) based on different technologies providing a unique access point to search and discover open datasets coming from heterogeneous sources. Idra uniforms the representation of collected open datasets, thanks to the adoption of international standards (DCAT-AP) and provides a set of RESTful APIs to be Figure 9. Data Catalogue – Details of a dataset (example) used by third-party applications. Figure 7 depicts the interaction among the Data Catalogue ACKNOWLEDGMENTS / ZAHVALA and the other URBANITE’s components. This research is funded by the European Union's Horizon 2020 research and innovation program under grant agreement number 870338 (URBANITE: Supporting the decision-making in urban transformation with the use of disruptive technologies). REFERENCES [1] Kirstein F., Stefanidis K., Dittwald B., Dutkowski S., Urbanek S., Hauswirth M. (2020) Piveau: A Large-Scale Open Data Management Platform Based on Semantic Web Technologies. In: Harth A. et al. (eds) The Semantic Web. ESWC 2020. Lecture Notes in Computer Science, vol 12123. Springer, Cham. https://doi.org/10.1007/978-3-030-49461- Figure 7. Data Catalogue - Component diagram 2_38 [2] Piveau solution. https://github.com/piveau-data [3] DCAT-AP 2.0.1. The Data Catalogue interacts with 1) Identity/Authorization https://joinup.ec.europa.eu/rdf_entity/http_e_f_fdata_ceuropa_ceu_fw21 _f32d70b6e-0d27-40d9-9230-017e4cd00bcc Management component to allow administrators to access their [4] Idra - Open Data Federation Platform specific functionalities retrieving the access token that will be https://idra.readthedocs.io/en/latest/ 661 Traffic Simulation for Mobility Policy Analysis Maj Smerkol Miljana Sulajkovska Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia maj.smerkol@ijs.si miljana.sulajkovska@ijs.si Erik Dovgan Matjaž Gams Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenija Ljubljana, Slovenija erik.dovgan@ijs.si matjaz.gams@ijs.si ABSTRACT The rest of the paper is organized as follows. Section 2 covers mobility policy simulations and overviews the selected traffic Recently urban mobility has been changing quickly due to the simulation tool. Section 3 describes the high-level view of the growth of cities and novel mobility methods’ introduction. These support system for mobility policy design and the role of the changes are causing ever greater traffic congestion and urban mobility policy simulation in the system. Section 4 overviews pollution problems. To deal with the growing complexity of ur- the process of partially automated simulation creation including ban mobility and traffic systems we are developing a system to the descriptions of data preparation processes, the design of the support the decision makers in the URBANITE H2020 project. An underlying relational database and the algorithms developed for integral part of the system is a system for simulation of mobility each step of the simulation creation. The paper concludes with policy proposals based on traffic simulation. The simulations are Section 5, which summarizes the paper and presents ideas for used for evaluation of policy proposals. We developed a system future work. for automatic simulation creation and an algorithm for popula- tion synthesis based on open data available for multiple cities. 2 OVERVIEW OF THE SYSTEM FOR KEYWORDS MOBILITY POLICY DESIGN smart city, traffic simulation, mobility policy 1 INTRODUCTION As cities are becoming more populous, traffic congestions, pol- lution and other problems are becoming harder to handle. Such complex and interconnected issues, also called wicked problems, are hard to deal with and any policy targeting these issues may be seen as undesirable from certain stakeholders’ point of view or may have unforeseen side effects. An example of a wicked issues is moving the residents from using cars to driving bicycles or using public transit [6]. This paper presents a method for using traffic simulations among other analysis tools to analyse and evaluate mobility policies. The developed method aims to contribute to solving such problems in the urban mobility domain by simulation of the changes and calculation of key performance indicators (KPIs) [7], Figure 1: Architecture of the URBANITE system. co-designed with the city stakeholders. The method was developed with two goals in mind. The first is to empower the administration to easily run new simulations The URBANITE system consists of several components, in- with less involvement of technical experts and thus shorten the cluding a data platform, AI-based tools including the mobility feedback time from idea to the results of the simulations. The policy simulation, and tools for stakeholder engagement, includ- second goal is to enable the automatic creation of multiple simula- ing a forum and a social policy laboratory [11]. In this paper we tions by variation of specific parameters within given constraints focus on the architecture of the mobility policy simulation shown to algorithmically produce candidate solutions for specific prob- in Figure 1. lems. The decision makers work with the system in an interactive mode by evaluating and improving policy proposals in an it- Permission to make digital or hard copies of part or all of this work for personal erative fashion, i.e., by defining the mobility policy proposals, or classroom use is granted without fee provided that copies are not made or which are simulated and evaluated by the system. In each itera- 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 tion, they use the insight gained to modify the policy proposals. work must be honored. For all other uses, contact the owner /author(s). However, the system is also able to search for mobility policy Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia proposals within user provided constraints. These proposals are © 2021 Copyright held by the owner/author(s). automatically simulated and evaluated, and the decision makers 662 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Maj Smerkol, Miljana Sulajkovska, Erik Dovgan, and Matjaž Gams are presented with a selection of the best ones according to the city for all private car traffic. Main goals of the proposal are to selected KPIs. improve the air quality at the square and to relieve traffic trough The main inputs to the mobility policy simulation system the square. are the proposed mobility policy and the data required for the From the simulation point of view, this is a relatively simple simulation: the population data, the city model and the traffic change of the city’s road network. The change is implemented by data. Examples of mobility policies are described in Section 3. changing the properties of affected road segments in the network The mobility policy simulation module executes the following to disallow private car traffic. Public transport and emergency steps to create and run the simulation: vehicles are not affected by this change as well as pedestrian and • bicycle traffic. Population synthesis is the process of using the population KPIs are selected in accordance with the goals of the policy. data to create the artificial agents. • To estimate the effects on the air quality in the area, the daily Travel demand generation takes the generated agents and amounts of different air pollutants emitted at the square and their activities, and generates the trips that the agent will in the nearby areas are recorded. We expect that there will be take to arrive to the locations of their activities. • less pollutants emitted in the square and some increase in the Finally, before the simulation is run the trips are optimized surrounding areas as the traffic will be redirected to them. to fit them to the known traffic data. • The simulation run is performed and the simulation recor- 3.2.2 Changing a Major Road to a Bicycle Highway. Amsterdam ded for further analysis and visualization, and to provide is the capital city of the Netherlands as well as its largest city data for the machine learning models. with over 1.5 million residents in the urban area. It has a highly The simulation results are used by the decision support sys- developed bicycling culture to the point where bicycle traffic tem to calculate the KPIs, evaluate the mobility policy proposals jams often form at the peak traffic times. The policy proposed is and provide multi-attribute decision analysis, as well as by the to close one of the major roads into the center, the Oranje Lopper, machine learning models used for policy proposal. for motorized traffic. While similar to policy proposed in Bilbao, 3 MOBILITY POLICY SIMULATION the goals of Amsterdam are mainly to alleviate the bicycle traffic by introducing a new bike highway into the city center. Historically, modeling of mobility started with analytical mod- To represent the policy for the simulation, we change the elling, mostly based on economic models combined with numeri- properties of the road segments that make up the Oranje Lopper cal methods for traffic estimation [3]. At the same time, simula- to disallow private car traffic and instead introduce a number of tion models were also developed [12]. A significant improvement new bicycle lanes. came with the introduction of agent-based simulations, which KPIs selected are the number of bicycles using the new bike are used for simulation of complex self-organizing systems. highway and more importantly, average bicycle travel times be- tween the city parts connected by the Oranje Lopper. 3.1 Traffic Simulations The URBANITE mobility policy simulations are based on traffic 3.2.3 Alleviation of Ferry Traffic via Building of a new Tunnel. simulations provided by the open source package MATSim [4], Helsinki is the capital city of Finland. The Helsinki port is also the a Java framework for traffic simulations. The selected traffic busiest passenger port in the world, which causes regular traffic simulation framework is a state-of-the-art microscopic multi- jams in the Jätkäsaari area where the traffic from the port to the agent traffic simulation package that allows the creation of traffic mainland is forced to use a single road. The policy proposal in simulations with features such as multi-modal trips, support for Helsinki includes building a tunnel connecting the port directly bicycles and micro-mobility, public transit support, and emissions to the motorway with the goal of alleviating the traffic jams that estimation. form periodically when ferries arrive to the port. Some drawbacks of the MATSim framework are high com- This policy is represented by the addition of new links to the 1 putational complexity, demand for high quality input data and road network representing the tunnel. To test this proposal, the highly complex process for creating high quality simulations. ferry arrivals are modelled as seafaring public transport with The selection of MATSim among the available microscopic traffic forced high loads of vehicles arriving as scheduled. simulation software options is based mostly on its extensibility The main KPI for this policy is the traffic flow at the existing and flexibility. point of crossing to the mainland. Another significant factor for the evaluation of this policy is the amounts of air pollutants 3.2 Representation of Mobility Policies emitted in the Jätkäsaari area. Mobility policy is a very wide category and general policy rep- resentation is out of the scope of this work. Instead we focus 3.2.4 Addition of new Bus Lines to Under-Connected Areas. The on specific policies. Besides the policy representation, appropri- last policy we consider is the addition of public transport lines to ate KPIs are also required. This section focuses of four distinct under-connected areas of the Messina municipality in Sicily, Italy. types of policies that are considered by the pilot cities within the Generally the city is well connected by public transport, however URBANITE project and the KPIs selected to evaluate them. as the city is caught between the sea shore and a mountain area, some of the more remote parts lack connectivity and are only 3.2.1 Closing a Major Square for Private Car Traffic. Bilbao is accessible by private vehicles. These areas are also generally a city near the northern shore of Spain and the largest city of too remote to access the city by foot and too mountainous for the Basque Country with nearly 350,000 residents. The policy everyone to use bicycles. proposed for simulation is closure of the Moyua square in the To simulate this policy, we add new bus lines by creating the 1 GTFS data compatible with existing public traffic and including In the context of URBANITE project, which this work is a part of, data gathering and quality assurance are parts of the project. it in the simulation. 663 Traffic Simulation for Mobility Policy Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 4 CREATING SIMULATIONS 4.2 Automating Simulation Creation To create a traffic simulation using MATSim, a set of input data To automate the creation of mobility policy simulations, the needs to be defined, and the simulator’s configuration must be following steps were taken: specified. The simulation is run in two consecutive steps: first, the • The entities representing input data are connected via agents’ actions are optimized using a co-evolutionary algorithm; appropriate relations and a relational database is designed. second, the final run of the simulation is stored and analysed. The input data is related to a simulation instance. • Processes and algorithms for creating the input data are 4.1 MATSim Input Data developed and implemented. • Simulation results are stored and exported for visualiza- In this section we describe the input data necessary to run the tion and further analysis. simulation, and the process for creating these files. For each of the files we also describe the data model and explain how the We defined a database that allows the simulations to be auto- data is used. matically created and compared using a multi-attribute decision analysis methodology. To allow the user easy comparison of dif- 4.1.1 Road Network. The road network represents the traffic ferent simulation outcomes, the table Scenario includes multiple infrastructure and its properties such as lane capacity and max simulations. Each Scenario links to a Decision Model, that is speed. Currently, we rely on Open Street Maps [10], a crowd- designed and evaluated using the multi-attribute decision analy- sourced publicly accessible map database. It is a very valuable sis tool DEXi [1]. This setup of entities Scenario, Simulation resource, however due to its nature it is not complete and there and Decision Model allows for a common and automated eval- may be some inaccuracies in the data. uation and comparison of different simulation results. The resulting network is a collection of nodes and link. Each At the same time, the Simulation entity is linked to entities link represents a straight part of a single lane and connects two Network, Agent Plans and Vehicles. These include all the data nodes. The link also contains other relevant information such that is needed to run the simulations. road type, speed limit, road or street name, etc. The nodes repre- sent the location via coordinates. This means that a single road or 4.3 Road Network Preparation street is made of multiple links that may have different properties. 4.1.2 Facilities. To get the data about specific places in the city, such as hospitals, schools, parks and workplaces among others, we provide the simulator with a list of facilities. These are gath- ered from OSM along with the network itself and attributes are added from the city datasets. The attributes of interest include number of employees, average number of daily visitors, number of employee and visitor parking spots, etc. Before running the simulation, the facilities and the network are pre-processed to- gether to match the coordinates and other attributes between the files. 4.1.3 Agent Plans. Agent plans are the daily plans of each of Figure 2: (1) The country wide map is retrieved from OSM. the agents that represent the population. These are described (2) The relevant area is extracted. (3) The map data is fil- as a list of activities and a list of trips that allow the agent to tered and the minimal road network is stored. engage in the activities. The agent plans are the results of the population synthesis and travel demand modelling, described in OSM is limited by the area size it can export using the API. Section 4.4. There are multiple algorithms for population synthe- Instead, we download the binary map data for the entire country sis that are developed for working with different sets of available from the map catalogue. We use an open source tool Osmosis input data [2]. to extract the relevant area and filter out all the unneeded data The trips for each agent are used for the final simulation run. in order to keep performance of the simulations to a minimum. The data contains a collection of trips, each made up of multiple Next, we remove any broken links, unconnected links and parts trip legs that may use different transportation modes (e.g., an of network that are isolated from the greater connected network, agent may take a bus to go to work but walk back home). usually artifacts of extracting the selected area. 4.1.4 Vehicles. When interested in vehicle-related data, such as 4.4 Population Synthesis Algorithm amounts of certain pollutants emitted, data about the vehicles in the city are necessary. Multiple types of vehicles can be defined The selection of the algorithm is limited by the data available with attributes such as vehicle type, engine technology, cylinder in the four pilot cities. Another important goal of the algorithm displacement and latest EURO emission standard it supports. A selection is to use mainly open data. Often the studies in this field simulation using this data can be analysed for amounts of pollu- are not reproducible due to use of proprietary data or data that is tants emitted per link for each vehicle by using the HBEFA [9] not publicly available, as well as the use of proprietary software. emission factors. The common population model used for population synthesis To use the defined vehicles, the agent population has to be is shown in Figure 3. The city is split into existing statistical split up into multiple subpopulations. Each subpopulation may districts and each district is modeled separately. Each district has link a specific vehicle fleet (a set of vehicles) that the agents can a population model and a corresponding vehicle fleet used for use. estimation of air pollutants emitted. 664 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Maj Smerkol, Miljana Sulajkovska, Erik Dovgan, and Matjaž Gams We adapted an algorithm developed for population synthesis REFERENCES using publicly available data in Paris [5], in order to process the [1] Marko Bohanec. 2008. Dexi: program for multi-attribute data available in the pilot cities. It consists of the following steps: decision making user’s manual. Ljubljana, Slovenia: Institut (1) Sample the marginal distributions of the socio-economic Jozef Stefan. data. Each household is assigned a home location and [2] Abdoul-Ahad Choupani and Amir Reza Mamdoohi. 2016. agents are generated for the household by sampling the Population synthesis using iterative proportional fitting marginal distributions of the population attributes. (ipf ): a review and future research. Transportation Research (2) Iterative Proportional Fitting [8] is used to improve the Procedia, 17, 223–233. International Conference on Trans- matching of the agents’ attributes by fitting to a small portation Planning and Implementation Methodologies sample of the census data. for Developing Countries (12th TPMDC) Selected Proceed- (3) Households are assigned income levels sampled from the ings, IIT Bombay, Mumbai, India, 10-12 December 2014. income level marginal distribution. issn: 2352-1465. doi: https://doi.org/10.1016/j.trpro.2016. (4) Activities are generated and activity chains are assigned 11.078. https://www.sciencedirect.com/science/article/pii/ to each agent. First, the primary (work and education) S2352146516306925. activities are considered, then secondary (shopping and [3] Juan de Dios Ortúzar and Luis G Willumsen. 2011. Mod- leisure) activities are added, based on the travel surveys elling transport. John wiley & sons. and facility data. [4] Andreas Horni, Kai Nagel, and Kay Axhausen, editors. The lists of households, persons, activities and trips generated 2016. Multi-Agent Transport Simulation MATSim. Ubiquity need to be optimized to match the traffic data before the final Press, London, 618. isbn: 978-1-909188-75-4, 978-1-909188- simulation. The initial version of the algorithm was already de- 76-1, 978-1-909188-77-8, 978-1-909188-78-5. doi: 10.5334/ veloped and is based on the open-source implementation of the baw. algorithm described in [5], while the final version is under devel- [5] Sebastian Hörl and Milos Balac. 2021. Synthetic population opment. and travel demand for paris and île-de-france based on open and publicly available data. Transportation Research Part C: Emerging Technologies, 130, 103291. issn: 0968- 090X. doi: https : / / doi . org / 10 . 1016 / j . trc . 2021 . 103291. https : / / www . sciencedirect . com / science / article / pii / S0968090X21003016. [6] Louise Kold-Taylor and Donald W de Guerre. 2020. From cars to bicycles: an ecosystem view of montreal traffic as a wicked problem. Systemic Practice and Action Research, 33, 1, 55–75. [7] Puji Adiatna Nadi and AbdulKader Murad. 2017. Review Figure 3: Each district has a separate population model of methods and indicators in sustainable urban transport and vehicle fleet. studies overview from 2000 to 2016. Communications in Science and Technology, 2, 2. [8] Paul Norman. 1999. Putting iterative proportional fitting 5 CONCLUSION on the researcher’s desk. We are developing a mobility policy simulation module as a part [9] Benedikt Notter, Mario Keller, Hans-Jörg Althaus, Brian of the URBANITE system for mobility policy design support. The Cox, Wolfram Knörr, Christoph Heidt, Kirsten Biemann, designed module consists of an open source multi-agent traf- Dominik Räder, and Marie Jamet. [n. d.] Hbefa 4.1. fic simulation system, population synthesis algorithm including [10] OpenStreetMap contributors. 2017. Planet dump retrieved travel demand modelling and the co-evolutionary optimization from https://planet.osm.org. https://www.openstreetmap. algorithm for fitting the simulations to existing traffic data. org. (2017). The system enables mobility policy simulation by implement- [11] Anne Fleur van Veenstra and Bas Kotterink. 2017. Data- ing the processes for creating the simulations using open data driven policy making: the policy lab approach. In Inter- and with no proprietary software required. Using open data al- national conference on electronic participation. Springer, lows the users to develop algorithms applicable to multiple cities 100–111. and ensures the reproducibility of results. [12] Michal Čertický, Jan Drchal, Marek Cuchý, and Michal The algorithm for population synthesis and travel demand Jakob. 2015. Fully agent-based simulation model of mul- modelling was selected and adapted to the data available and timodal mobility in european cities. In 2015 International pilot cities’ needs, and preliminary simulation were developed. Conference on Models and Technologies for Intelligent Trans- The research on this topic is far from concluded. Some of the portation Systems (MT-ITS), 229–236. doi: 10.1109/MTITS. future work include development of the co-evolutionary sim- 2015.7223261. ulation fitting algorithm and the final implementation of the population synthesis algorithm. ACKNOWLEDGMENTS This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870338. 665 Machine Learning-Based Approach for Estimating the Quality of Mobility Policies Miljana Sulajkovska Maj Smerkol Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia miljana.sulajkovska@ijs.si maj.smerkol@ijs.si Erik Dovgan Matjaž Gams Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenija Ljubljana, Slovenija erik.dovgan@ijs.si matjaz.gams@ijs.si ABSTRACT evaluating transportation facilities or systems. Using the simula- tions we can see how some actions may impact the dimensions Cities are increasingly turning towards specialized technologies that we are interested in without making those changes in real to address issues related to their significantly increased transport life. demand. Municipalities and transport authorities try to face these Currently, most of the mobility policy evaluation techniques problems in order to achieve their objectives by taking various rely on experts in urban/spatial planning using on simulation actions in the domain of public transport, air and noise pollution, results [10]. Since the simulations create large amount of data, road accidents, etc. The primary objective of this research is to including data from optimization steps, various data analysis explore the role of machine learning (ML) in mobility policy can be applied. In this context machine learning techniques can quality estimation using microscopic traffic simulations. The be applied to automate the evaluation of mobility policies and main idea is to use one simulation run as one training example. address the objectives of the cities. The features are represented by several group of parameters that As part of the URBANITE project we are developing a ma- are related to the input and output of the simulation, while the chine learning module using data from microscopic transport target variables are represented using key performance indicators simulator that will help decision makers in the what-if analysis. (KPIs). The city of Bilbao is chosen as a use case. We have analyzed More precisely, we propose a system to estimate the quality of how closing the Moyua square in the city center and changing the previously simulated mobility policies using machine learning number of cyclists there can affect the air pollution by estimating methods. the CO2 emissions. Several machine learning algorithms are The rest of the paper is structures as follows. Section 2 explains tested and the results show that by closing the main square in the URBANITE approach and the relevant modules for this re- the city center and increasing the number of cyclists the CO2 search. In Section 3 the data collection process is explained. Then, emissions reduce. Section 4 presents the results of the machine learning module. KEYWORDS Finally, Section 5 concludes the paper with ideas for future work. machine learning, smart cities, mobility policy 2 OVERVIEW OF THE URBANITE 1 INTRODUCTION APPROACH According to United Nations population estimation, the total The main objective of URBANITE approach is to build an intelli- population is exponentially increasing and by 2050 will reach 9 gent platform that can use data from heterogeneous sources in billion, i.e. it will increase for 2 billion from now [11]. This demo- order to help the city managers in the decision-making process. graphic growth will greatly impact on the transportation system To achieve this aim, several modules are developed. In this sec- in metropolitan areas since most population will be located there. tion we will give an overview of only the relevant ones shown As a result far more attention must go towards serving the needs in Figure 1 and aspirations of the people with the aim to maintain the envi- The traffic simulator is used to simulate various mobility poli- ronmental, social, and economic costs at the same time [12]. cies during the the policy evaluation process. The input files to In this context different mobility policies are tested and evalu- this module are related to the network map, travel demand, public ated in order to achieve the desired city goals. Since implementing transit data etc. Based on the simulation output, target variables different scenarios in real life is an expensive process microscopic e.g. air pollution levels for the machine learning algorithms are traffic simulations are widely used as a valuable support tool for calculated, based on which the models are build. This approach is able to process large amount of data in order to find the best Permission to make digital or hard copies of part or all of this work for personal mobility policy. or classroom use is granted without fee provided that copies are not made or Besides automatic selection of mobility policy URBANITE also 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 supports policy selection by the experts with the use of the de- work must be honored. For all other uses, contact the owner /author(s). cision support system. In addition to processing the simulation Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia data this system also relies on expert knowledge in order to build © 2021 Copyright held by the owner/author(s). the hierarchical decision models and satisfy the user preferences. 666 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Miljana Sulajkovska, Maj Smerkol, Erik Dovgan, and Matjaž Gams Figure 2: MATSim cycle. account the performance of activities and travel time. A typical score is calculated as follows: 𝑁 −1 𝑁 −1 Figure 1: Modules of URBANITE approach. Õ Õ 𝑆 = 𝑆 + 𝑆 plan act,𝑞 trav,mode (𝑞) (1) 𝑞=0 𝑞=0 Here utility functions are used to represent a basic scoring Both approaches are used in the policy evaluation process with function or in other words the utility of a plan 𝑆 is computed plan the difference that machine learning module relies on algorithms as sum of all activity utilities 𝑆 , plus the sum of all travel act,𝑞 that automatically select the best mobility policy. In the next sec- utilities 𝑆trav,mode(𝑞) . 𝑁 represents the number of activities. For tions the simulation and machine learning process are described scoring, the last activity is merged with the first activity to pro- in detail. duce an equal number of trips and activities. Positive scores are obtained for desired events and negative for unwanted ones. 3 DATA COLLECTION Finally, the optimization step takes part where four dimen- 3.1 Simulation sions are considered: departure time, route, mode, and destination. Each of the agents has a memory of 𝑀 plans that have been ob- In order to collect the data, a microscopic traffic simulation tool served in the past and which have obtained a score. In the first was used. Several state-of-the-art solutions were tested and MAT- step the replanning process checks whether the agent’s memory Sim was chosen as the most suitable one. MATSim [6] is an exceeds the limit. If so one of the existing plans is removed ac- open-source tool implemented in Java. It is used for microscopic cording to previously computed scores. If the plan is removed modeling that enables us to simulate and analyze components that was currently selected for execution, a random one among on the network such as traffic flow, congestion, public trans- the remaining ones is selected. After a certain number of itera- port, behavior of cyclists, etc. One of the core concepts is the tions an equilibrium state on the network is reached improving co-evolutionary optimization where the individuals’ plans are the initial scores. evolving in the presence of all other persons doing the same. Several files are produced as output of the simulation that are To run the simulator several input files need to be provided related to specific iteration or they summarize a complete run, that are related to the city model, traffic and population data. For e.g. events file that contains every action taken on the network, the creation of the transport demand e.g. persons with their daily and travel distance statistics showing the distance traveled per plans and mode of transport real data from census and other mode. These results are used to compute the features for the travel surveys is required. Since there is no complete dataset con- machine learning module and to define the target variable. More taining the socio-demographic characteristics of individuals at a precisely the input features consists of simulation input and small geographic scale because of privacy concerns a transport output data which can be directly influenced by the user. On demand was generated based on known random variables. the other hand the target variables depend on the simulation After providing all the required input we can run the simu- results and cannot be directly set by the user which makes them lation which is optimized by configurable number of iterations relevant for the decision-making process of particular mobility (see Figure 2). Each individual agent learns by maintaining mul- policy. These variables are summarized in Table 1. tiple plans which are scored by executing them in the mobsim, Additional MATSim package was used to calculate the CO2 selected according to the score and when needed, modified. The emissions which are used as a target class in the prediction pro- iterative process consists of the following steps: cess. The tool calculates warm and cold-start exhaust emissions • Mobsim simulation by linking MATSim simulation output to detailed emission fac- • Scoring tors for road transport. • Replanning 3.2 Scenarios Every iteration starts with an initial demand simulated by the mobility simulation and then evaluated by the scoring module In order to gather the dataset, 14 simulations were executed by as a central element of the simulator [9]. applying different policies in the city of Bilbao, Spain. The main The MATSim scoring module evaluates the performance of a objective is to see the impact of closing the Moyua square in the plan in a synthetic reality and determines the choice of person’s city center for private traffic. plan in the next iteration. Next, only plans with higher scores Two scenarios are implemented: the baseline scenario of the are selected by the agent - others are deleted in the replanning current network situation and the modified scenario represent- step. The scores are computed using scoring function taking into ing the closure of Moyua square as one possible policy. All other 667 ML approach for mobility policy quality estimation Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Table 1: Input data and target variable of the machine learning module ML input Target variable Sim input Sim output Surface of a road Number of cars CO emission 2 Capacity of road Number of cyclists Number of lanes Number of public Type of district transport vehicles Number of bus stops Average travel time Figure 4: CO emissions in the Moyua square. The baseline 2 scenario is marked with orange circle. Random Forest, Linear Regression, Gradient Boosting, and Neural Network. The k-nearest neighbor (kNN) is a semi-supervised learning algorithm that requires training data and a predefined 𝑘 value to find the 𝑘 nearest data based on distance computation. If 𝑘 data have different classes the algorithm predicts class of the unknown data to be the same as the majority class [1]. Tree splits the data into nodes by class purity. The top-most node is called root, the bottom ones leaves, and all other nodes Figure 3: Number of persons and cyclists per scenario in- are internal nodes connected to each other with edges. Each stance. edge represents satisfaction of the node condition, and each leaf node determines the class assigned to the instances that met the conditions of the internal nodes on the path from the root node to the leaf node [5]. instances are variations of the second scenario where the number Support Vector Machines (SVM) is a two-grouped classifier of cyclists varies from 1500 to 19000 while changing the number where input vectors are non-linearly mapped to a high-dimension of inhabitants from 2.000 to 20.000, respectively. This change feature space. In this feature space a linear decision surface is in number of cyclists does not represent a specific policy but constructed. Special properties of the decision surface ensures shows what would happen if in conjunction with the applied high generalization ability of the learning machine [2]. policy also the number of cyclists changes. Figure 3 depicts these Random Forest consists of a large number of individual deci- variations where with green is marked the baseline scenario and sion trees that operate as an ensemble. Each individual tree in with orange the other scenario and all its variations. The first the random forest spits out a class prediction and the class with instance represents the baseline scenario with 10000 inhabitants the most votes becomes model’s prediction. A large number of and 2000 cyclists, while the remaining instances represent the relatively uncorrelated models (trees) operating as a committee second scenario with all variations. The second instance con- outperform any of the individual constituent models. tains 2000 inhabitants with at least 1500 cyclists. The next four Linear Regression is commonly used in mathematical research instances are representing 10000 population with up to 9000 methods, where it is possible to measure the predicted effects and cyclists while reducing the private transport. The rest of them model them against multiple input variables. It is a method of represents 20000 inhabitants with up to 19000 cyclists. The num- data evaluation and modeling that establishes linear relationships ber of public transport vehicles stays the same in all variations. between variables that are dependent and independent [8]. Figure 4 shows the results of the applied policy. More precisely Gradient Boosting tries to convert weak learners into strong it shows the relationship between number of cyclists and the level ones by training many models in a gradual, additive and sequen- of CO emissions. The x-axis represents the number of cyclists 2 tial manner where the gradient of the loss function is being nearby the square and and y-axis represents number of cyclists minimized, with respect to the model values at each training data in the center. The different colors denote the amount of CO2 point evaluated at the current step [4]. emissions as a target variable where with orange circle is marked Neural Network model simulates a large number of inter- the baseline scenario. This figure shows that by closing the main connected processing units that resemble abstract versions of square for private traffic and reducing the number of private neurons where the processing units are arranged into layers. vehicles nearby it, the level of CO emission is decreasing. 2 The units are connected with varying connection strengths (or 4 MACHINE LEARNING weights). Input data are presented to the first layer, and values are propagated from each neuron to every neuron in the next 4.1 Methods layer. Eventually, a result is delivered from the output layer. The Several machine learning models were applied using Orange [3]: network learns by examining individual records, generating a pre- k-Nearest Neighbors, Decision Tree, Support Vector Machines, diction for each record, and making adjustments to the weights 668 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Miljana Sulajkovska, Maj Smerkol, Erik Dovgan, and Matjaž Gams whenever it makes an incorrect prediction. This process is re- ACKNOWLEDGMENTS peated many times, and the network continues to improve its This work is part of a project that has received funding from predictions until one or more of the stopping criteria have been the European Union’s Horizon 2020 research and innovation met [7]. programme under grant agreement No. 870338. The authors also acknowledge the financial support from the Slovenian Research 4.2 Evaluation Results Agency (research core funding No. P2-0209). We have evaluated the machine-learning algorithms described in Section 4.1. The data for evaluation of the algorithms is split REFERENCES randomly 10 times and the average results are computed. We [1] Kittipong Chomboon, Pasapitch Chujai, Pongsakorn Teer- have compared four evaluation metrics: arassamee, Kittisak Kerdprasop, and Nittaya Kerdprasop. • Mean squared error (MSE) measures the average of the 2015. An empirical study of distance metrics for k-nearest squares of the errors or deviations (the difference between neighbor algorithm. In Proceedings of the 3rd international the true and estimated values). conference on industrial application engineering, 280–285. • Root mean squared error (RMSE) is the square root of [2] Corinna Cortes and Vladimir Vapnik. 1995. Support-vector the arithmetic mean of the squares of a set of numbers (a networks. Machine Learning, 20, 3, 273–297. doi: 10.1007/ measure of imperfection of the fit of the estimator to the bf00994018. http://dx.doi.org/10.1007/BF00994018. data). [3] Janez Demšar, Tomaž Curk, Aleš Erjavec, Črt Gorup, Tomaž • Mean absolute error (MAE) used to measure how close Hočevar, Mitar Milutinovič, Martin Možina, Matija Po- forecasts or predictions are to eventual outcomes. lajnar, Marko Toplak, Anže Starič, Miha Štajdohar, Lan • R2 is interpreted as the proportion of the variance in the Umek, Lan Žagar, Jure Žbontar, Marinka Žitnik, and Blaž dependent variable that is predictable from the indepen- Zupan. 2013. Orange: data mining toolbox in python. Jour- dent variables. nal of Machine Learning Research, 14, 2349–2353. http : //jmlr.org/papers/v14/demsar13a.html. The results are shown in Table 2. According to MSE, RMSE, and [4] Jerome H. Friedman. 2002. Stochastic gradient boosting. R2 the best model is kNN, while according to MAE the best model Computational Statistics and Data Analysis, 38, 4, 367–378. is SVM. doi: 10.1016/s0167- 9473(01)00065- 2. http://dx.doi.org/10. 1016/S0167- 9473(01)00065- 2. Table 2: Evaluation results [5] Trevor Hastie, Robert Tibshirani, and Jerome Friedman. 2001. The Elements of Statistical Learning. Springer Series Model MSE RMSE MAE R2 in Statistics. Springer New York Inc., New York, NY, USA. [6] 2016. Introducing matsim. The Multi-Agent Transport Sim- kNN 4.718 2.172 1.416 -0.372 ulation MATSim. Ubiquity Press, 3–8. Tree 5.387 2.321 1.431 -0.567 [7] Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. SVM 4.953 2.225 1.298 -0.441 Deep learning. nature, 521, 7553, 436–444. Random Forest 5.093 2.257 1.404 -0.482 [8] Dastan Maulud and Adnan M Abdulazeez. 2020. A review Neural Network 11.264 3.356 2.583 -2.277 on linear regression comprehensive in machine learning. Linear Regression 8.076 2.842 2.041 -1.349 Journal of Applied Science and Technology Trends, 1, 4, 140– Gradient Boosting 5.193 2.279 1.324 -0.511 147. [9] 2016. A closer look at scoring. The Multi-Agent Transport 5 CONCLUSION Simulation MATSim. Ubiquity Press, 23–34. doi: 10.5334/ baw.3. http://dx.doi.org/10.5334/baw.3. In this paper we showed how machine learning can be used in [10] Soledad Nogués, Esther González-González, and Rubén mobility policy evaluation helping the urban development in Cordera. 2020. New urban planning challenges under emerg- cities. As large amount of data is produced from simulations, ing autonomous mobility: evaluating backcasting scenar- machine learning techniques can be applied to automatically ios and policies through an expert survey. Land Use Policy, choose the best policy. 95, 104652. doi: 10.1016/j.landusepol.2020.104652. http: We defined the mobility policy for Bilbao. Then, using micro- //dx.doi.org/10.1016/j.landusepol.2020.104652. scopic traffic simulation the two scenarios were implemented: [11] Gilles Pison. 2019. How many humans tomorrow? the baseline scenario of the current network state and the modified united nations revises its projections. The Conversation, scenario representing closure of Moyua square for private traffic. 1–6. In order to gather more data, variations of the second scenario [12] Eleni I Vlahogianni, John C Golias, and Matthew G Kar- were produced by changing the proportion of cyclists and private laftis. 2004. Short-term traffic forecasting: overview of car users. After gathering sufficient data, machine learning tech- objectives and methods. Transport reviews, 24, 5, 533–557. niques were applied to evaluate the performance of the policy. Changing the number of cyclists in combination with the second scenario showed that the level of CO emissions can be decreased 2 or in other words, the proposed policy proved fairly good. In future work, more policies will be tested and evaluated using the proposed approach. Then, advanced machine learning and deep learning techniques will be applied to improve the current results. Finally, data from simulation runs in the optimization step can be used to expand the current dataset. 669 Visualizations for Mobility Policy Design Maj Smerkol Miljana Shulajkovska Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia maj.smerkol@ijs.si miljana.sulajkovska@ijs.si Erik Dovgan Matjaž Gams Jožef Stefan Institue Jožef Stefan Institue Ljubljana, Slovenija Ljubljana, Slovenija erik.dovgan@ijs.si matjaz.gams@ijs.si Figure 1: Visualization of simulated traffic flow intensity in center of Bilbao. ABSTRACT that are emerging. As the populations of cities are growing, so are Cities around the world are rapidly gaining population as more occurrences of traffic congestions, air pollution and traffic noise people are moving to urban areas from the periphery. At the in urban areas. At the same time, introduction of novel mobility same time, novel urban mobility solutions are emerging such as modes both in the sector of micro-mobility (e-scooters, bike shar- e-cars and micro-mobility. Thus, urban traffic is getting heav- ing etc) and sharing services in other sectors cause dynamics of ier and more complex. To deal with these problems the H2020 the urban traffic to change [3]. This makes it increasingly difficult URBANITE project is developing tools for city administrations to model the growing complexity of the urban mobility as well as including a data platform, mobility policy validation via traffic predict the effects of specific policies. This makes the prediction simulation, decision support for multi-attribute decision analysis of possible effects of mobility policies more difficult but also more and a visualizations module, described in this paper. We consider important. The importance of policy effects has been shown on different types of visualizations in the domain of urban traffic the example of e-scooters [1]. They offer a clean and sustainable and select most appropriate, implementing a module used for way of travelling the first and last kilometer of the trip but can data visualizations for the system. also be very dangerous when not properly regulated. We are developing a new AI assisted tool set for supporting the KEYWORDS development and evaluation of urban mobility policies as part of the URBANITE H2020 project [7]. The project includes a mobility smart city, urban mobility, visualization policy simulation, a recommendation system for policy design support, advanced visualization suite and a machine learning 1 INTRODUCTION component for quick evaluation of expected policy results. This Cities’ mobility landscapes are rapidly changing due to the rais- paper focuses on the visualizations of the traffic data, simulation ing populations as well as new and disruptive mobility modes results and decision analysis. The end users of the tool set are city administrations (generally 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 not technical personnel), urban mobility planners (experts on distributed for profit or commercial advantage and that copies bear this notice and mobility) and interested citizens (laymen). These groups differ the full citation on the first page. Copyrights for third-party components of this greatly with regards to their knowledge as well as the intent work must be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia of interacting with the system. Citizens are interested in under- © 2021 Copyright held by the owner/author(s). standing the administration’s actions but do not have a direct 670 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Maj Smerkol, Miljana Shulajkovska, Erik Dovgan, and Matjaž Gams possibility to work with the system. Urban mobility planners are 2.2 Traffic Data mostly already using traffic simulation tools and data analysis Traffic data includes traffic counts, trips, and Origin-Destination tools and require a highly detailed view of the data and analysis (OD) matrices. There are multiple ways of visualizing these data. results. They are not limited by their knowledge and are used to Following is a brief overview of common visualization methods working with complex tool sets. The city administrators however used on these types of data. are similar to the citizens in that they are generally not experts on urban traffic and mobility, but are expected to make decisions 2.2.1 Traffic counts. Traffic counts at a specific location are com- about policies. The visualizations developed are primarily aimed monly shown via line charts where the horizontal axis represents at the city administrators with the goal to help them understands time (usually one day) and the vertical axis represents number and interact with the data available, compare the results of differ- of vehicles passing the location. To compare data from several ent policy proposals and help with the interaction of the experts specific locations we can show multiple lines on the same chart with the administrators. The second goal of the visualizations using different colors. is to inform the public and democratize mobility planning. To To visualize the traffic counts all over the city simultaneously achieve that the visualizations should be self explainable. geo spatial map based visualizations are commonly used, either The paper is organized as follows: Section 2 overviews the as point-based or line-based map layers. Point-based visualiza- common visualizations and their advantages and disadvantages, tions are best suited when the traffic counts are measured using Section 3 covers the selection of visualization methods for first existing sensing devices such as induction loops or smart cam- release and Section 4 describes the implementation of specific eras. Such sensing devices are usually not available on every visualization methods. road segment. In this case the points locate the sensors while the values measured are commonly color coded. 2 VISUALIZATIONS IN THE TRAFFIC AND MOBILITY DOMAINS 2.2.2 Traffic flows. Traffic flow is the amount of vehicles that This section overviews the common data types in the domains pass a certain point on the road in a time slot. Traffic flows are of traffic and mobility and the visualization methods commonly commonly visualized using line-based map layers, where the used to represent the data. The data types overviewed are traf- traffic flow is represented either by line thickness or color. To fic flows, air pollution and specific pollutant emissions, general specifically show the modal split of the traffic flows we can show tabular data, geo-spatial data and geo-temporal data. them separately or at the same time. In the latter case it is best to use color codes to represent different types of vehicles and line 2.1 Spatio-Temporal Data thickness to represent the traffic flow. In the domains of urban mobility and traffic spatial data is very 2.2.3 OD matrices. OD matrices hold the information about common, since most of the data is related to specific roads or number of people moving from parts of the city to other parts. locations within the city. This category contains all such data, Commonly the spatial resolution of the OD matrices matches including the road networks (city maps), traffic flows on roads and statistical regions. OD matrices are commonly obtained using streets, trips made and modal splits of traffic in specific locations, travel surveys, estimated using GPS traces of trips and public as well as population properties in different statistical districts transit data. of the cities, locations of important facilities such as hospitals Common method for visualizing the OD matrix data is to show and schools, parking lots and public parking garages and public the matrix as a heat map with rows and columns labeled with the transport lines. Some of these types of data are further discussed name of the district. Such visualizations are hard to understand bellow in the section Traffic Data. and under certain conditions can be cluttered, decreasing their These data are best represented as interactive layers on a map. readability. Each layer must be visually distinct from the underlaying map to Alternatively OD matrices can be shown on a map via con- ensure the visibility of the data. Often it is less important that the nections between districts. The intensity of travel between two map itself is easily readable as it serves mostly as a spatial anchor parts is commonly represented via the connection thickness, that allows the easy recognition of general locations. To ensure while color is typically used to distinct different connections. the understandability of the geo-spatial visualizations data layers This method is easier to understand, but readability depends on can be interatively selected so only the relevant data is shown at the geographical positions of the districts. the same time. To keep the data minimally cluttered and therefore more un- derstandable we do not show details of the data on the map unless 2.3 Air pollution the user hovers the mouse over some part. In this case, a popup Air pollution levels are usually visualized using heat map layers with the details of the selected locations are shown. This can be on top of the city map, and are therefore counted among the geo- seen on the Figure ??, where the demographic data is shown for spatial visualizations. Generally the most common method for each district. Generally one of the attributes is shown using a visualizing air pollution is an air quality index heat map. Some color scale on the map and other attributes are only shown when of the advantages of visualizing air pollution as a heat map are user hovers over a specific city district. high understandability and very low visual cluttering. A negative The most intuitive way to show time-dependant data is by aspect of heat maps in this use case is that air pollution often animating the visualiziations. To simplify the interaction and does not spread equally in all directions due to air movements thus reduce the mental overhead we show a timeline below the and buildings blocking the pollutants’ paths. This is however geo-spatial view. The user may select the time they are interested not very important as the users are mostly interested in general in or play the animation at different speeds. An example is not pollution levels and in the case of the URBANITE project the shown due to the limitations of printed media. levels of specific pollutant emissions. 671 Vizualizations for Mobility Policy Design Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia 3 SELECTION OF METHODS and echarts [5]. Leaflet.js is used for all geo-spatial and geo- The selection of methods to be implemented was based on the temporal visualizations. It provides an interactive map and the pilot city requirements, data availability and the available simu- functionality to add custom layers to the map. We use the library lation outputs. In order to support comparing the measured data Echarts to implement any line charts and spider charts. and the simulation results we are limited to using visualizations that are appropriate to both. 4.1 Map based visualizations This section covers the visualization methods we have selected Multiple visualizations were developed to visualize certain geo- and is split by the type of data into traffic, air pollution, and other spatial data: data visualizations and concludes with a brief discussion of the • Visualization of the traffic flows is shown on Figure 1. color maps chosen to represent the values. Each street is overlaid with a line, colored according to the traffic flow intensity. Less intensive flows are shown 3.1 Traffic data with blue hue and more intensive flows are shown in red. The color scale consists of a five color ramp selected for The category of traffic data contains multiple different data types best visibility on the base map. that have to visually represented using different methods. Some • Visualization of emissions of specific pollutants. Each of the data that is shown using the methods for geo-spatial data street is overlaid with a line, colored according to the visualization are: amount of selected pollutant. Streets with less emitted • Traffic counts, shown either geo-spatially by aggregating pollutants are shown in blue and streets with more are the counts per day or geo-temporally by aggregation of shown in red. the counts per specific time slot, commonly hours. Traffic These visualizations are implemented using JavaScript and counts at a specific location depends on time. based on maps provided by the library Leaflet.js[2]. The over- • Traffic flows, measures in vehicles per hour passing a road. lays are generated from the simulation results by aggregating The traffic flow at a specific location depends on time. The road network links by street name and summing the selected specific flows for different modes, such as public transport, attribute for the day or per hour, thus enabling animated visual- heavy duty vehicles, bicycles and pedestrians are currently ization of changes throughout the day or a static daily attribute visualized separately. visualization. • Congested roads. Simplest way of identifying problematic roads or junctions is to show the locations of congested 4.2 Color maps traffic. We can detect congested traffic and traffic jams by We use one color map for all the visualizations that are based on searching for road segments with high traffic density and the city map. The color map selected must be diverging in order travel speed below the free-flow speed [8]. to highlight best and worst values according to their desirability. Some of the more detailed traffic data are better visualized The chosen map a diverging color map using red colors for un- using simpler charts. Traffic flows at specific locations over time desired values and blue for desired values. The color map should are shown using a line chart. Traffic flow predictions at specific also be appropriate for color blind users to avoid potential mis- locations are shown using a line chart with the confidence inter- understandings. With the requirements of the color map defined, val included to inform the user that these are not exact. Modal we selected a color map named cold-warm [6] that fits our needs. splits of traffic at specific locations as well as city-wide aggrega- The color map is shown on Figure 2 and is a a diverging color tions of modal splits are visualized using area charts or stacked map that is colorblind safe. We have opted to use a five step color area charts. map instead of the full gradient to make the extreme values stand out more. 3.2 Air pollution data Due to the data available in pilot cities as well as the results of the traffic simulations we are not able to map the air quality index. Instead of air quality index, the data available includes Figure 2: Color map used for overlays. Blue color is used levels of specific pollutants at existing measuring stations and for desired values and red color is used for undesired val- the simulated levels of the same pollutants. ues. Therefore we show the available data: measurements at exist- ing air quality monitoring stations are shown as a sparse heat map layer showing the levels of selected pollutant while the sim- 4.3 Interactive charts ulated pollutant emissions are shown as a layer over each road We use interactive charts implemented using the echarts library segment that shows the selected pollutant level. to implement line charts, histograms and spider charts. Line charts are used to analyse the modal splits on specific streets and 4 IMPLEMENTATION the level of selected emitted pollutant (𝐶𝑂2) using an overlaid The visualization were implemented as part of the URBANITE area chart. These were made interactive to allow the user to zoom user interface (UUI). We focus on the UUI modules used to analyse in and move the viewport around. Hovering over any of the lines the simulation results and the comparison of two simulations. shows the number of trips of the appropriate modes as well as The UUI is implemented using the Angular framework [4] the mode the line represents. mostly in TypeScript with some JavaScript parts. For ease of The same visualizations were also implemented as 3D line integration and to be able to package the UUI module as an charts as shown on Figure 3. Lines are replaced with strips and Angular module we opted to use JavaScript libraries Leaflet.js [2] instead of adding an area map to show the emitted pollutant 672 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Maj Smerkol, Miljana Shulajkovska, Erik Dovgan, and Matjaž Gams levels they are color coded using the strip color. These allow 6 CONCLUSIONS more interactions such as panning and rotation. 1 we overviewed the common methods of visualization of com- mon traffic data We have overviewed the mobility related open data-sets avail- able in four major European cities and identified the most im- portant for dealing with urban mobility policy. Several different sorts of data were analysed and appropriate visualizations were selected. Some of the visualizations are implemented, specifically traffic count, daily trips, and emitted air pollutant visualizations, among with some of visualizations of policy comparison. The module implementing the visualizations supports the needs of the urban mobility analysis tool-set that we are devel- oping. The visualization selection and implementation fits the needs of different users and will be further improved as we gather feedback from the pilots. Figure 3: Visualization of the modal split between car and bicycle trips and the amount of the 𝐶𝑂2 emitted on the ACKNOWLEDGMENTS selected street The 𝐶𝑂2 levels are color coded. This project has received funding from the European Union’s A spider chart was implemented using the echarts library for Horizon 2020 research and innovation programme under grant multi-attribute comparison of different simulation results. This agreement No 870338. The authors acknowledge the financial allows the user to recognize the dominant solution at a glance support from the Slovenian Research Agency (research core fund- based on the size of the area that represents the simulations. ing No. P2-0209). On the other hand they allow us to show the detailed values REFERENCES of multiple, potentially competing attributes. Thus the user is able to understand the data at a glance on some level while also [1] Gijs Alberts. 2021. Standing e-scooters, what to expect: providing the details when the user hovers the mouse over axes micro-mobility with micro effects?: explorative research of the spider chart or the line representing a single simulation into the expected effects and policy implications of the result. An example of the spider chart can be seen on Figure 4. introduction of e-scooters in the dutch traffic system. [2] Paul Crickard III. 2014. Leaflet. js essentials. Packt Publishing Ltd. [3] Mohamed El-Agroudy. 2020. Mobility-as-a-service: assess- ing performance and sustainability effects of an integrated multi-modal simulated transportation network. [4] Nilesh Jain, Ashok Bhansali, and Deepak Mehta. 2014. An- gularjs: a modern mvc framework in javascript. Journal of Global Research in Computer Science, 5, 12, 17–23. [5] Deqing Li, Honghui Mei, Yi Shen, Shuang Su, Wenli Zhang, Junting Wang, Ming Zu, and Wei Chen. 2018. Echarts: a declarative framework for rapid construction of web-based visualization. Visual Informatics, 2, 2, 136–146. [6] Kenneth Moreland. [n. d.] Diverging color maps for sci- Figure 4: The spider chart shows the comparison of two entific visualization (expanded). Proceedings in ISVC, 9, 1– different proposed mobility policies based on the simula- 20. tion results. We can see the popup that shows values of all [7] The URBANITE Project. 2021. https://urbanite-project.eu/. attributes of one of the simulations. [8] Martin Treiber and Arne Kesting. 2013. Traffic flow break- down and traffic-state recognition. In Traffic Flow Dynamics. Springer, 355–366. 5 FUTURE WORK There is a lot of room for improvement and the work is ongoing. Several visualization techniques covered are not yet finished, such as the geo-temporal visualizations and the heat maps. The next step is to finish the implementations of all the selected visualization types and to improve the visual appeal of the visu- alizations. In order to compare the air quality measured with the results of simulations which provide estimations of the levels of emit- ted specific pollutants the data must first be transformed to an estimation of the air quality index. An alternative to this ap- proach should it prove infeasible is to use the simulation results to estimate the measurements at the location of the measuring stations. 673 URBANITE Ecosystem: Integration and DevOps María José López† Iñaki Etxaniz Giuseppe Ciulla ICT Division ICT Division Research & Development TECNALIA, Basque Research TECNALIA, Basque Research Laboratory and Technology Alliance (BRTA) and Technology Alliance (BRTA) Engineering Ingegneria Spain Spain Informatica mariajose.lopez@tecnalia.com inaki.etxaniz@tecnalia.com Palermo, Italy giuseppe.ciulla@eng.it ABSTRACT Also the Use Cases propose functionalities for the URBANITE ecosystem, that will be considered for being part of the URBANITE is a collaborative research and innovation project URBANITE ecosystem and prioritize for their implementation. whose outcomes are mainly software based. These outcomes will be implemented in a collaborative manner by different This platform will comprise the URBANITE components development teams from different partners. In order to manage implemented, Key Results or KR from now on, (Key Result the development environments, and the integration of the KR1-Virtual Social Policy Lab, KR3-Data Management different software components in on time releases, the proper Platform, KR4- Algorithms) and their integration in the DevOps strategy and processes has been defined and set up. URBANITE ecosystem (KR5). This paper describes the URBANITE integrated architecture at The elicitation of the first version of the functional and non- month 12, with a theoretical vision of the URBANITE system functional requirements for the URBANITE ecosystem and the that will cover all the functional and non-functional initial related components is described as an iterative process where requirements set by the technical work-packages considering the both the technology providers and use case providers’ have social perspective and the input of the use cases. participated. The definition of the interactions among components is shown For the functional requirements a combined approach has been through the specification of the interfaces, considering the followed: 1) a top down approach led by the technology provider dataflows envisioned for meeting the needs of the different partners, who have defined the first set of functional stakeholders. Different tools, environments and strategies requirements and 2) a bottom up approach where the needs of the envisioned for the management of the development, integration Use Cases have been monitored and UC initial requirements have and validation stages of the software components to be been extracted. For the Non-Functional Requirements, these implemented during the life cycle of the project are described as have been detailed per component, including relevant aspects, part of the integration strategy. such as performance, usability or resources needs for deployment. All these requirements will serve for the continuous development KEYWORDS and improvement of the URBANITE ecosystem, through the DevOps, Integration, Ecosystem, Requirements, Architecture, different releases, validation processes and reviews of the Prototype. requirements. The URBANITE ecosystem will include all the components for 1 REQUIREMENTS data management, analysis and support to the decision making The process for setting up the URBANITE Ecosystem receives that are going to be created/developed/implemented in the inputs from the rest of technical components, related to the data context of the URBANITE project. The first version of the management and simulation processes, regarding to: requirements will be updated in further reports and analysis. • Technical (software) requirements, expressing both Several sources will be used to elucidate the requirements for the functionality needs and non-functionality aspects. URBANITE ecosystem: • Architectural structure and configuration of the components implemented in different work packages. • Requirements coming from the URBANITE action • And about how to integrate them into the overall specification: These requirements cover the functionalities URBANITE UI. described in the URBANITE action specification. The first Permission to make digital or hard copies of part or all of this work for personal or version of these requirements has been described by the classroom use is granted without fee provided that copies are not made or distributed Technology providers partners (Fraunhofer, Tecnalia, JSI for profit or commercial advantage and that copies bear this notice and the full and Engineering Ingegneria Informatica) based on the 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). URBANITE approach and high-level architecture Information Society 2021: 24th international multiconference , 4–8 October 2021, description included in the URBANITE action. Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 674 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M.J. López et al. • Requirements coming from the Use Cases: The Use Cases proposed functionalities for the URBANITE ecosystem, so that the features offered can cover their needs. • Requirements coming from the co-creation sessions (SoPoLabs): It is expected that some requirements may be derived from the SoPolabs that will be conducted in the context of WP2. If relevant these requirements will be considered for the URBANITE ecosystem and prioritize for their implementation. Requirements coming from the Co-creation Priorizitation of ITERATIVE sessions requirements per use case Requirements Requirements coming alignment (ideal vs. from the Use Cases Use cases) URBANITE requirements prioritization High Level URBANITE ecosystem requirements functional and non- (DoA) functional requirements URBANITE generic Implementation URBANITE requirements processes Use Cases validation and testing prioritization and plan Figure 2: First version of URBANITE architecture In the Month 15 of the project, the architecture is a reduced Figure 1: URBANITE process for requirements gathering and prioritization version of the overall URBANITE architecture and consists of the components that provide the functionalities designed The different users of the URBANITE platform to perform any covering the current version of the requirements. of the previously described are: The components are: • PA (Public Administration): This actor is the user from • URBANITE UI: The entry point to the URBANITE the public administration, usually the civil servants. Ecosystem, that allows users to access the • Citizens: This actor is the citizen that is using any of functionalities provided by the URBANITE platform the components in the platform. at this point of the project. • • Identity Manager (Key Cloak): This component is in Platform administrator: This is the administrator of the charge of securing the access to the other platform who can install components, check the status URBANITE’s component, whenever security is of the included components, etc. needed. It is called by other components that interact with the user. 2 ARCHITECTURE • City Bike Pattern Analysis: This module analyses GPS information related to the mobility of the bikes and The detailed description of the entire global architecture of the transform it into more useful data. URBANITE ecosystem as a general representation of it, is in its • Traffic Prediction: It performs heuristic prediction for first version and can evolve following the needs of the project. the vehicle flow at a location within the city by the Structural and behavioural analysis of each component of the processing of historical values measured by a fixed architecture was performed identifying interactions and sensor and other information. dependencies among them. • Traffic Simulation: It offers the simulations of traffic under specified conditions, as proposed mobility Three layers of components can be observed and identified by policies, different weather conditions, changes to the colours: traffic infrastructure, etc. • Yellow components are those that manage the data, and • Scheduler: It triggers a pipeline for the harvesting implemented withing the WP3 process, downloading data from a list of configured • APIs within defined periods of time. The purple ones are dedicated to the simulation and analysis • of the data ingested to the system for the yellow ones. Data Harvester and Transformation: It is responsible • for fetching data from a given API, being the entry And the grey components are those related to the UI, as the point of the data into the pipeline. Then a entry point to the platform and for user management. • transformation is done into common models. There is also a green component considered as a repository • Data Storage and Retrieval: This module stores and of the datasets stored by the data management layer. retrieves datasets metadata and related data in repositories DCAT-AP compliant metadata and transformed data. • Data Catalogue: It allows to discover and access the datasets collected and managed by the components of URBANITE Ecosystem for data acquisition, aggregation, and storage. 675 URBANITE Ecosystem: Integration and DevOps Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia DEVELOP: Environment that contains the last version of the components running together. Dedicated to test new features, interfaces, and communications among components. MASTER: Contains a specific version of the platform, frozen for specific Milestones. DEMO PILOTS: Four environments, one for each city, where the integrated platform is replicated and adjusted to the characteristics of the use cases. It is a previous step for testing the platform before setting up in the infrastructure of the municipalities. REAL PILOTS: the installation of the platform in each municipality’s infrastructure. To be done after the integration Figure 3: Month 15 version of URBANITE architecture phase once a stable version is achieved to test the use cases. Apart from that, in order to support developers during the integration, we provide: 3 INTEGRATION AND DEVOPS STRATEGY A Portainer instance that allows to access the logs and the This section presents the infrastructure and tools planned to be console of every container in every environment. used internally for the development and operation. The DevOps An Artifactory instance to store the images of the containerized approach requires the set-up of a development and delivery components. These images will be used to deploy the final pipeline, that consists in the stages an application goes through version of the platform in the real Pilots. from development through production. The URBANITE iterative and incremental approach mandates 4 URBANITE ECOSYSTEM the adoption of a development and deployment process able to fully support it. That is why the project will adopt a DevOps The main result of the URBANITE project is the URBANITE approach in the development of all KRs. DevOps integrates Ecosystem and aggregates all aspects of the project, namely the development and operations into a single-minded entity with citizen participation, both social (citizen participation, attitude common goals: high-quality software, faster releases and and trust in disruptive technologies, co-creation) and technical improved users’ satisfaction. DevOps also incorporates a number aspects (data management platform, algorithms and so on). of agile principles, methods, and practices such as continuous delivery, continuous integration, and collaboration [1]. The URBANITE UI is an integration framework at User The different KRs, which are the outcomes of URBANITE [2], Interface level. are composed of several software components that will be The integration strategy provides different approaches that can implemented by different partners following different be followed: technologies. 1. External component integration In URBANITE, the DevOps approach will be structured in three Iframe: the external application is included in the UI environments as depicted in the figure. through an iframe External link: the application is referenced in a dedicated section of the UI, and a specific link is provided to the user 2. Template component integration: the external application, that must provide a set of REST APIs for developing a specific component included in the UI. The URBANITE UI is an Angular application built taking advantage of Nebular, ngx-admin frameworks and Eva Design System. With the addition of some of the most popular front-end libraries and packages. The access to the Urbanite UI is provided through the Urbanite’s Identity Manager component (an instance of KeyCloak whose theme is customized following Urbanite’s colour palette). Figure 4: Continuous Integration and DevOps approach The Urbanite UI provides Role-Based access to specific functionalities following the IDM returned role(s) of the user The description of the environments that are part of the integration system: FEATURE BRANCH: Temporary environment that is created each time a developer wants to integrate a new version of his component. It just checks that the new version of the urbanite platform builds without problems and is destroyed afterwards. 676 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia M.J. López et al. • Maps: where are two examples of how a developer can build and manage maps, using the libraries provided by this UI. • Charts: this option displays three possible library alternatives provided by the Urbanite UI to build bars, pies and line charts. • UI Features: about style examples as colors, icons, typography, and the grid system that should be used for implementing pages to provide responsiveness. • Additional Applications: is a section where external links to other applications can be added through the URBANITE UI configuration file. For instance, the forum page is linked. • And the Urbanite Project where included information about the objectives of the project. Figure 5: M15 Component's integration REST APIs based The figure above shows is the URBANITE UI, integrating the components implemented for the M15 version of the prototype, covering the requirements and the functionalities provided by the implementation planned at this point. The left part of the page includes the available options. Some of them are general utilities, and other are functionalities Figure 6: URBANIITE Ecosystem v1 implemented within the different technical work packages. The Figure 6 describes the schema that supports the before • The Home page offers descriptions of the four explained prototype. municipalities and the basis of the URBANITE project. There is an additional information section for each description that allows to extend the details of the selected REFERENCES city. [1] New Relic, "“Navigating DevOps - What it is and why it matters to you • The Administration, Data Analysis, Data Catalogue and and your business”," New Relic, 2014. Traffic Analysis are specific sections that provide services [2] URBANITE Consortium, "URBANITE Annex 1 - Description of Action," 2019. related to the data of the different municipalities. 677 678 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek I Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume I 50-letnica poučevanja računalništva v slovenskih srednjih šolah 50th Anniversary of Teaching Computer Science in Slovenian Secondary Schools Urednika / Editors Saša Divjak, Alenka Krapež http://is.ijs.si 6. oktober 2021 / 6 October 2021 Ljubljana, Slovenia 679 680 PREDGOVOR Letos obeležujemo 50. obletnico poučevanja računalništva v slovenskih srednjih šolah. Leta 1971 je bila namreč imenovana komisija za uvajanje pouka računalništva v srednje šole, v šolskem letu 1971/72 pa se je začelo računalništvo v nekaterih srednjih šolah tudi organizirano poučevati. Seveda se je samo računalništvo v Sloveniji pojavilo že dobrih 10 let prej. Prvo učenje programiranja v akademskem okolju, sicer bolj omejeno na posamezne tečaje, srečamo v poznih 60. letih prejšnjega stoletja. Spomin na takratne čase bledi in ta konferenca pomeni zbiranje zapisov o tem, kako se je vse skupaj začelo pa tudi nadaljevalo. Podkonferenca na temo 50 let poučevanja računalništva v srednjih šolah v sklopu tradicionalnega multikonferenčnega dogodka Informacijska družba je ena od oblik zaznamovanja te tudi za tujino častitljive obletnice. Časa za pripravo konference je bilo malo. Za celovitejši pregled bi morali na njej aktivno sodelovati še mnogi takratni zanesenjaki. A korak naprej pri pripravi zgodovinskega pogleda smo s tem le pripravili in ga bomo lahko v nadaljevanju dopolnjevali. V prispevkih tokratne konference se odsevajo dogajanja tako v Ljubljani kot v Mariboru. Najprej smo skušali omejiti tematiko na začetke poučevanja računalništva v srednjih šolah v ozkem časovnem obdobju okrog leta 1971. Kasneje smo fokus konference nekoliko razširili tja do leta 1980, torej na čase, ko še ni bilo popularnih PC-jev, še manj pa Interneta; hkrati smo ga širili tudi na izobraževanje na akademski ravni in druge računalniške dejavnosti, predvsem razvojne, ki niso omejene le na srednje šole. Tako smo prišli do zanimive zbirke pogledov, ki najprej nakazujejo razmere, v katerih je prišlo do pobude za uvedbo pouka računalništva v srednje šole. Pomembno pionirsko vlogo je pri tem igrala komisija za uvajanje računalništva v srednje šole. Potrebno infrastrukturo so takrat nudili nekateri redki računalniški centri. V akademskem okolju je tako marsikomu omogočal prve korake v programiranje legendarni računalnik ZUSE Z 23. V srednješolskem okolju se je hitro pokazala potreba po ustreznih slovenskih učbenikih, ustrezni računalniški infrastrukturi in seveda usposobljenih učiteljih. Zapise simpatično dopolnjujejo pogledi takratnih dijakov, danes uveljavljenih računalničarjev, o doživljanju prvih korakov v programiranju. Praktično v istem času srečamo tudi prve programerske predmete v akademskem okolju, kar je pripeljalo tudi do uvedbe študija računalništva, kmalu zatem tudi informatike na univerzitetnem nivoju. Spomine lepo zaokrožujejo pripovedovanja o celoviti, tudi akademski karieri nekaterih akterjev. Seveda so to le nekateri pogledi, dejansko moramo gledati nanje kot na drobne, a pomembne kamenčke v pestrem mozaiku čedalje bolj živahnih dogajanj na računalniškem področju. Verjamemo, da lahko sčasoma to sestavljanko spominov še dopolnimo in primerno strukturiramo. To pa je že naloga za nov podvig, katerega rezultati bi lahko bili predstavljeni na naslednjih konferencah. Prof. dr. Saša Divjak in mag. Alenka Krapež, sopredsednika Programskega odbora 681 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Saša Divjak Borka Jerman Blažič Vladimir Batagelj Matjaž Gams Tomaž Pisanski Robert Reinhardt Marjan Mernik Vladislav Rajkovič Izidor Hafner Niko Schlamberger Janez Grad Boštjan Vilfan Dušan Kodek Anton Železnikar Žiga Turk Ivan Bratko Marko Bonač Marko Grobelnik Simona Tancig Iztok Lajovic Alenka Krapež Marjan Špegel Tomaž Kalin Saso Džeroski LjupčoTodorovski France Dacar Jernej Kozak 682 Matematiki in računalniško izobraževanje, do 1980 Mathematicians and computer education, until 1980 Vladimir Batagelj vladimir.batagelj@fmf.uni- lj.si IMFM Ljubljana, Slovenija IAM UP Koper, Slovenija Slika 1: Del pomnilnika računalnika Zuse izdelan v Iskri. POVZETEK O tej tematiki sem pisal že ob drugih obletnicah [1] [15] [3] Sestavek vsebuje osebne spomine avtorja na pomembnejše do- 2 MATEMATIKA godke v razvoju računalništva v Sloveniji do leta 1980 s poudar- kom na izobraževanju. KLJUČNE BESEDE računalništvo, matematika, izobraževanje, prvi računalniki, spo- mini ABSTRACT The paper contains the author’s personal memories of important events in the development of computer science in Slovenia until 1980, with an emphasis on education. KEYWORDS informatics, computer science, mathematics, education, first com- puters, memories 1 UVOD Letošnja tema je 50 letnica srednješolskega računalniškega iz- obraževanja pri nas. Sam sem bil pri začetkih bolj opazovalec. Lahko pa marsikaj povem o kontekstu, v katerem se je to odvijalo. Posebej bi rad povzel vlogo matematikov pri razvoju računalni- Slika 2: Knjige iz zbirke Sigma. štva pri nas. Podam lahko le osebno videnje dogajanj, ki lahko služijo kot vir za morebitne kasnejše celovitejše preglede. Študij matematike je prisoten na Univerzi v Ljubljani od njene Permission to make digital or hard copies of part or all of this work for personal ustanovitve. Spočetka je podpirala različne, predvsem tehniške, or classroom use is granted without fee provided that copies are not made or študije. Sam študij matematike pa je bil usmerjen predvsem v iz- 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 obraževanje učiteljev matematike. Obsegal je pretežno predmete work must be honored. For all other uses, contact the owner /author(s). s področja matematične analize (in geometrije, algebre ter teorije Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia števil; na ekonomiji še statistiko). Leta 1949 je bilo ustanovljeno © 2021 Copyright held by the owner/author(s). stanovsko Društvo matematikov, fizikov in astronomov, ki vsako 683 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vladimir Batagelj leto organizira občni zbor društva in izdaja društveno glasilo Ob- zornik. Organiziralo je tudi poljudna predavanja po šolah in od leta 1950 republiška tekmovanja iz matematike [9]. Leta 1959 je izšla prva knjiga v zbirki Sigma – Ivan Vidav: Rešeni in nerešeni problemi matematike. V naslednjih letih je v Sigmi izšlo še več knjig, ki prinašajo "novo" matematiko, pomembno za računalništvo: Vadnal A. (1960) Elementarni uvod v verjetnostni račun, Prijatelj N. (1960) Uvod v matematično logiko, Križanič F. (1960) Elektronski aritmetični računalniki, Bohte Z. (1964) Numerično reševanje enačb, Jamnik R. (1964) Elementi teorije informacije, itd. Prof. Križanič se je z računalniki spoznal med svojim izpopolnjevanjem v Sovjetski zvezi. Slika 4: Zvonimir Bohte in Egon Zakrajšek. Konec petdesetih so na študiju matematike vpeljali novo študij- sko smer – tehniška matematika, ki naj bi usposabljala za potrebe gospodarstva. Prvi diplomant na tej smeri je bil Jože Vrabec leta 4 TEHNIŠKA MATEMATIKA 1963. Konec osnovne šole in nato v gimnaziji sem bil uspešen na mate- matičnih tekmovanjih. Na njih sem spoznal Tomaža Pisanskega – 3 ZUSE Z-23 Toma in čez njega Franceta Dacarja. Maturiral sem leta 1967. Ker so mi ponudili štipendijo Sklada Borisa Kidriča, sem se odločil za študij tehniške matematike. Ta je takrat poleg matematičnih in fizikalnih predmetov vključevala še nekaj tehniških, kot so mehanika, strojni elementi in tehniško risanje, teorija preklopnih vezij ter teorija sistemov. Leta 1969 smo na IMFM dobili nov računalnik IBM 1130, ki je dobil svoj prostor v novi zgradbi matematike in fizike na Jadranski 19. Poleg numerične analize smo imeli tudi računski praktikum. Računali smo na računskih strojčkih. Za mojo generacijo so pri- spele nove Facit-ke. Sam sem izvisel (ni jih bilo dovolj) in sem dobil staro Olivetko. Izkazalo se je, da sem pravzaprav imel srečo – Olivetka je imela papirni trak na katerem je beležila sled izra- čunov. Računalniške predmete je predaval Egon. Najprej smo spoznali programski jezik fortran. Tisto leto so izšla skripta za fortran, ki jih je napisal mariborski matematik Milan Kac [16]. Egon je svoj učbenik objavil leta 1973 [19]. Leta 1968 je Donald Slika 3: Začetek poročila o raziskovalnem projektu izde- Knuth začel objavljati svojo zbirko knjig The Art of Computer lave podprogramov za Zuse Z-23. Programming, ki so precej vplivale tudi na računalniška preda- vanja na matematiki. Na primer, Tomo je za diplomsko temo (pri Egonu) izbral generatorje slučajnih števil. Dodatne računalniške vsebine so bile vključene v specialne tečaje. Sam sem tako spoznal Leta 1960 je bil ustanovljen Inštitut za matematiko, fiziko in jezik algol. Izbral sem tudi seminar iz linearnega programiranja. mehaniko (IMFM). Prvi direktor je bil Anton Kuhelj. 15. novembra Pri programerskem praktikumu sem sam razvil algoritem za pro- 1962 je na IMFM na Lepem potu v Ljubljani začel delati prvi blem najkrajših poti (Forda in Dijkstra takrat še nisem poznal). pravi računalnik v Sloveniji, Zuse Z-23 (Slika 3). Ta datum lahko Rešitev sem sprogramiral v fortranu in algolu. Algolski program štejemo za začetek računalništva pri nas. Pred tem so zahtevne je dajal pričakovane rezultate, v fortranskem pa sem skoraj pol izračune opravljali na računalniku IBM 705 na Zveznem zavodu leta iskal napako [4]. Diplomsko temo sem si izbral iz logike – za statistiko v Beogradu. Rekurzivna aritmetika (mentor Niko Prijatelj). Okrog računalnika Zuse se je zbrala skupina mlajših učiteljev, raziskovalcev in študentov (Zvonimir Bohte, Tomislav Skubic, 5 IJS E4 Egon Zakrajšek, Janez Štalec, Janez Lesjak, Jože Vrabec, Marija Vencelj, Tomaž Kalin, Dušan Magušar, Janez Grad, Cveto Tram- Računalništvo se je razvijalo tudi na Inštitutu Jožef Stefan (IJS). puž, Mira Volk, Jana Birk, Boštjan Vilfan, Jernej Kozak, France Glavno vlogo je imel Anton P. Železnikar – Antek, ki je leta 1965 Dacar, Andrej Kmet, Gabrijel Tomšič, Zdenko Breška, Iztok Ko- doktoriral iz prekrivnih algoritmov [24]. Z njim je sodeloval tudi vačič, ..., ), ki so postavljali temelje računalništva pri nas. Posebej France Dacar in se na oddelku E4 tudi zaposlil. Na oddelku so je izstopal Egon Zakrajšek (diplomiral 1965) [21] [20]. Na študiju bili še Janez Korenini, Rudi Murn, Peter Kolbezen, Marjan Špegel, tehniške matematike so bili poleg predmeta numerična analiza Boštjan Vilfan in Andrej Jerman-Blažič. France Dacar je naju še trije računski praktikumi – pri tretjem so uporabljali Zuse. s Tomom povabil k sodelovanju z oddelkom. Tematika je bila Zuse je bil računalnik v pravem pomenu besede – bil je na- odkrivanje napak v elektronskih vezjih. Tako sva se srečala s menjen predvsem za računanje. Zato je bil velik poudarek na teorijo grafov in se vanjo poglobila (knjige Ore, Berge, Harary, numerični analizi, ki jo je pri nas začel razvijati Zvonimir Bohte – Zykov). Poleg tega smo se precej ukvarjali s teorijo avtomatov in Dragi s sodelavci. Uporabljen pa je bil tudi v druge namene [23]. jezikov. Nekoliko za nama so na oddelek prišli še Ivan Bratko – 684 Matematiki in računalniško izobraževanje, do 1980 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Leta 1969 so računalnik IBM 1130 dobili tudi na Višji tehniški šoli v Mariboru (Milan Kac, Darinka Ferjančič Stiglic, Bruno Stiglic) [16]. V gospodarstvu se je s svojo ponudbo uveljavil predvsem Intertrade (IBM). Ponujal pa jih je tudi Univac in drugi. Oktobra 1969 je v Radovljici začel z delom Intertradov šolski center. 7 RAČUNALNIŠTVO V SREDNJIH ŠOLAH Slika 5: Anton P. Železnikar in Boštjan Vilfan. Bruc, Vladislav Rajkovič, Iztok Lajovic, Iztok Sirnik, Jože Knez, Miroslav Smolej, Borka Džonova in Peter Tancig. Oddelek (predvsem Andrej Jerman-Blažič) je že od leta 1965 v začetku oktobra na Bledu organiziral računalniško konferenco FCIP (International Symposium on Information Processing), ki se je leta 1972 preimenovala v Informatico. Vabljeni predavatelji Bauer, Wirth, in drugi. Oddelek je nudil dobro okolje za samorazvoj. V sedemdesetih smo o svojih rezultatih v glavnem poročali in objavljali v zborni- kih domačih srečanj FCIP / Informatica, Etan in ADP; deloma v Slika 7: Izidor Hafner in Branko Roblek. slovenščini, deloma v angleščini. 6 FE, RRC, RCU, ISKRA, INTERTRADE IN DRUGI V šolskem letu 1969/70 je Izidor Hafner začel uvajati raču- nalništvo kot “praktično znanje” (izbirni predmet) na Šubičevi gimnaziji. Na njegovo pobudo je leta 1970 svetovalec za računal- ništvo na Zavodu za šolstvo RS Branko Roblek začel priprave za uvajanje računalništva kot izbirnega predmeta v srednje šole. Najprej so pripravili in izvedli izobraževanje učiteljev. Izšel je tudi priročnik za učitelje. Računalništvo je zaživelo na nekaj šolah v šolskem letu 1971/72. Nekakšen vrh teh prizadevanj predstavlja srednješolski učbenik Uvod v računalništvo, ki sta ga napisala Ivan Bratko in Vladislav Rajkovič. Na E4 se je pojavilo nekaj gimnazijcev: brata Reinhardt, Mark Martinec, Dare Levstek, Iztok Tvrdy, Henrik Krnec in drugi [10]. 8 IFIP 1971 Slika 6: RRC. Računalništvo se je razvijalo tudi na Fakulteti za elektroteh- niko – profesorji Jernej Virant, France Bremšak, Ludvik Gyergyek in Slavko Hodžar [11]. Leta 1968 je bil za potrebe gospodarstva, uprave in raziskav ustanovljen Republiški računski center (RRC) z računalnikom v Stegnah, najprej CDC 2100 kasneje pa CDC 3300 [12]. Za koor- dinacijo med Univerzo, IJS in RRC je bil leta 1971 ustanovljen Računalniški center univerze v Ljubljani (RCU). Zaradi poveča- nja potreb je RRC leta 1971 nabavil zelo zmogljiv računalnik CDC Cyber 72, ki je omogočal oddaljeni dostop s terminalskih računalnikov. Na IJS se je izoblikovala še ena računalniška skupina – Upo- rabna matematika, ki jo je vodil Marjan Ribarič in so jo pretežno sestavljali matematiki: Jana Birk Vrabec, Mira Volk, Drago Čepar, Slika 8: Zvezki IFIPovega zbornika. Ivica Mandelc, Milena Kosec in drugi. 685 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Vladimir Batagelj Anton P. Železnikar in Silvin Leskovar sta pri mednarodnem Tobačni tovarni). Vprašal me je, če bi pripravil pregled literature združenju za področje računalništva IFIP (International Federa- o delu z razpršenimi (hash) tabelami. Ugotovil sem, da obstajajo tion for Information Processing) uspela pridobiti organizacijo 5. kvadratične funkcije pregledovanja, ki preiščejo celotno tabelo. kongresa združenja v Ljubljani od 21. do 27. avgusta 1971. O tem sem objavil članek v CACM [6] [5, št. 22, 23]. Pri organizaciji kongresa se je zelo angažiral Marjan Špegel in si s tem pridobil možnost doktorskega študija v ZDA. Mladi z IJS in univerze smo dobili vlogo tehničnih sekretarjev in smo skrbeli za gladek potek predstavitev v raznih dvoranah po Ljubljani. Ob IFIPu je izšla knjiga Elektronski računalniki, ki prinaša temeljna znanja o računalnikih in štirijezični slovar računalniških izrazov [17]. 9 PRVA POLOVICA SEDEMDESETIH Kongres IFIP’71 in novi računalnik Cyber 72 sta zelo vzpodbudno vplivala na razvoj računalništva pri nas. Leta 1972 je bilo ustanovljeno Slovensko društvo Informatika. Z delom je začel Računalniški center na FSPN in naslednje leto še Inštitut za biomedicinsko informatiko (IBMI). Slika 9: Začetek izpisa pascalskega prevajalnika, december Na Dragijevo pobudo se je jeseni leta 1971 začel sestajati Semi- 1974. nar za numerično in računalniško matematiko – Sredin seminar [5]. Udeleževali so se ga matematiki in računalnikarji z različnih ustanov. Bil je odprt za najrazličnejše teme in je spremljal delo Poleti 1974 sem spremljal soprogo Nušo (Anuška Ferligoj) na sodelujočih ter v naš prostor prinašal novosti. Po seminarju smo poletni šoli iz družboslovne metodologije (Essex ECPR summer nadaljavali druženje Pod lipo in daljše obdobje še "na čaju" pri school) v Colchestru v VB. Sam sem poslušal le predavanja iz Egonu doma, kjer smo preizkušali najrazličnejše družabne igre analize družbenih omrežij. Večino časa pa sem prebil v račun- (Monopoli, Cluedo, mahjong, kariere, tihotapci, itd.). skem centru in knjižnici. V RC sem se srečal z interaktivnim Na študiju tehniške matematike se je začela graditi računalni- delom z računalnikom po teleprinterju. Med branjem člankov ška "vertikala" – vsaj en računalniški predmet v vsakem letniku. (predvsem iz Acta Informatica) sem se navdušil nad pascalom. Iz- Začela so se tudi predavanja iz računalništva ( Jernej Kozak) za vedel sem, da teče na Cybru in, da ga je mogoče dobiti brezplačno. druge oddelke FNT: kemija, kemijska tehnologija, tekstil, farma- Vzpostavili smo stik in proti koncu leta dobili trak s pascalskim cija in montanistika. Egon je za Sredin seminar pripravil ciklus prevajalnikom (Slika 9). V začetku leta 1975 je Egon pripravil predavanj iz Algola 68 [5, št. 29, 30]. Imel je tudi tečaj iz zbirnika tečaj iz pascala (z zapiski). Dopolnjene zapiske je leta 1976 iz- računalnika Cyber in napisal več priročnikov za uporabo sistem- dal v knjigi [22]. V šolskem letu 1975/76 smo pascal, skupaj z skih programov (SCOPE 3.4, UPDATE, NOS/BE, CCL, Plotter). obema Wirthovima knjigama, na Matematiki začeli uporabljati Ljubljano je nekajkrat obiskal Robert Korfhage, ki je imel tudi pri predavanjih. Knjigi je Boštjan Vilfan prevedel v slovenščino tečaj iz teorije grafov. [18]. Precej odmeven je bil Dijkstrov članek v CACM "Go to consi- Dobili smo prve prave terminale, ki so omogočali interaktivno dered harmful", ki je privedel do strukturiranega programiranja delo z računalnikom [5, št. 52, 53]. [5, št. 28, 51]. Za teorijo algoritmov je bil zelo pomemben Karpov Leta 1975 sem se z IJS preselil na FNT, matematika. V šolskem članek v katerem je pokazal, da za nekatere probleme, za katere letu 1974/75 sem pri Programerskem praktikumu prevzel skupino so bili znani le eksponentni točni algoritmi, najbrž ne obstaja študentov, ki je programirala "prevajalnik" za Structran (Struc- polinomski algoritem (NP-polnost). tran → fortran) [5, št. 50]. Programiranje smo začeli v fortranu, Z doktorskega študija na MIT v ZDA se je vrnil na IJS Boštjan a, ker ga je Egon čez nek weekend napisal v pascalu, smo nadalje- Vilfan. Prinesel je nov veter. Med drugim je začel projekt pisanja vali v samem Structranu. Glavno povezovalno delo posameznih prevajalnika za jezik PL/1. Meni je bilo dodeljeno prevajanje sestavin je opravil Matjaž Jeran. aritmetičnih izrazov [2]. Izkušnja je bila zelo poučna – postalo Jeseni 1975 sva s Tomom odšla k vojakom. mi je jasno od kod ideje za posamezne vrste slovnic (gramatik), 10 DRUGA POLOVICA SEDEMDESETIH ki sem jih poznal iz člankov o formalnih jezikih. Drug projekt je bil kodiranje (v zbirniku) sprememb za telefonske centrale Po vrnitvi iz vojske sem nekaj časa pomagal pri vajah iz raču- Metaconta, ki so jih pripravljali v Iskri. Pri tem sem spoznal nalništva na ostalih oddelkih FNT. Leta 1978 je Jernej doktoriral pomembnost polne informacije – večkrat sem moral v Kranj in začel predavati na Matematiki predmet Podatkovne strukture zaradi nepopolnih specifikacij. Na Sredinem seminarju sva z in algoritmi [13]. Za njim sem prevzel predavanja na FNT [7]. Vilfanom imela ciklus predavanj o rekurzivnih funkcijah [5, št. Prav tako sem leta 1978 od prof. Prijatelja prevzel predavanja iz 7] Diskretnih struktur na študiju računalništva – delo na diplom- V šolskem letu 1972/73 se je na FE v sodelovanju s FNT, mate- skem delu in izkušnje z IJS so se mi obrestovale pri oblikovanju matika začel dvoletni (zadnja dva letnika) študij računalništva vsebine. [11]. Matematika je pokrivala predmete: numerična analiza (Zvo- V tem času smo se precej ukvarjali s strukturiranim programi- nimir Bohte), diskretne strukture (Niko Prijatelj), analiza (Peter ranjem, dokumentacijo programov in učenjem programiranja [5, Petek) in linearna algebra (Edvard Kramar). št. 55, 56, 58, 76][14]. Navajali smo se tudi na interaktivno delo z Bruc, ki je bil izvrsten šahist, se je začel ukvarjati z umetno računalnikom. Egon je z Univaca v Zagrebu prinesel zbirko igric inteligenco [5, št 37]. Sodeloval je tudi z Vero Levovnik iz Iskre (v napisanih v basicu. Več smo jih poslovenili in usposobili za delo 686 Matematiki in računalniško izobraževanje, do 1980 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia na Cyberu. Zelo priljubljena je bila igra Zakladi (Dungeon). Za [5] Vladimir Batagelj. 2021. Sredin seminar / seznam preda- učinkovito interaktivno delo so manjkala ustrezna orodja. Nekaj vanj 1971-2021. http://vlado.fmf.uni- lj.si/sreda/sreda1300. jih je sprogramiral Egon: Mini (interaktivna različica programa pdf . Update za vzdrževanje različic programskih in podatkovnih dato- [6] Vladimir Batagelj. 1975. The quadratic hash method when tek) in Manual (program za oblikovanje besedil). Pri oblikovanju the table size is not a prime number. Commun. ACM, 18, besedil na prvih računalnikih sta bili težavi: na voljo so bile samo 4, (april 1975), 216–217. velike črke in manjkale so naše črke ČŠŽ. Kljub temu je bilo [7] Vladimir Batagelj. 1983. Uvod v računalništvo. Fortran : veliko besedil pripravljenih s programom Manual. razširjeni zapiski. DMFA SRS, Ljubljana. V RC IMFM smo dobili računalnik PDP z grafičnim zaslonom, [8] Vladimir Batagelj, Tomi Dolenc, Mark Martinec, Bojan Mo- na katerega je bilo mogoče risati. Prav tako so dobili risalnik v har, Robert Reinhardt, Iztok Tvrdy in Andrej Vitek. 1988. RRC. Enajsta šola računalništva / Rešene naloge z republiških Leta 1977 so se po zgledu matematičnih tekmovanj, zopet na tekmovanj 1977–1987. Sigma. DMFA in ZOTKS, Ljubljana. pobudo Izidorja Hafnerja, začela republiška tekmovanja srednje- [9] Vladimir Batagelj in Tomaž Pisanski. 1973/1976. Rešene na- šolcev iz računalništva [8]. Slovensko društvo Informatika je loge iz matematike z republiških tekmovanj, I (1950–1966) začelo izdajati revijo Informatica. / II (1967–1975). Sigma. Državna založba Slovenije, Lju- bljana. [10] Vladimir Batagelj in Robert Reinhardt. 1973. Metode iska- nja po tabelah. V Zbornik del VIII. jugoslovanskega medna- rodnega simpozija o obravnavanju podatkov Informatica 73. ZSOOP, Bled, a20/1–8. [11] Miha Bejek, Marjan Bradeško, Jernej Virant in Nikolaj Zimic. 2016. FRI 20 - Zbornik ob 20. obletnici fakultete. FRI, Univerza v Ljubljani, Ljubljana. http : / / eprints . fri . uni - lj.si/3655/1/Zbornik_FRI20_web_100.pdf . [12] Janez Grad. 2018. Razvoj računalništva in informatike na Univerzi v Ljubljani, s poudarkom na pomenu RRC in RCU. Uporabna informatika, 26, 3, 89–93. [13] Jernej Kozak. 1984. Podatkovne strukture in algoritmi. DMFA SRS, Ljubljana. [14] Jernej Kozak in Vladimir Batagelj. 1975. Kako naj učimo programirati? V Zbornik del X. jugoslovanskega mednaro- Slika 10: Rok Vidmar in DEC SYSTEM 10 na RCU. dnega simpozija o obravnavanju podatkov Informatica 75. Informatica/ETAN, Bled, 7.12/1–4. Za podporo množičnega dela študentov na računalniku smo [15] Alenka Krapež, Vladislav Rajkovič, Vladimir Batagelj in leta 1980 dobili na RCU računalnik DEC-10. Ta je med drugim Rado Wechtersbach. 2001. Razvoj predmeta računalništvo prinesel tudi male črke. Elektrotehna, zastopnik DECa v Jugosla- in informatika v osnovni in srednji šoli. V Dnevi Slovenske viji (od 1974), se je prelevila v podjetje Iskra Delta, ki je postalo Informatike 2001. Informatika, Ljubljana. https://www. pomemben dejavnik na področju računalništva. Na obzorju so se drustvo- informatika.si/dogodki/dsi- 2001/. pojavili TOZDi in usmerjeno izobraževanje. [16] Franci Pivec. 2021. Pionirski čas mariborskega računalni- štva (do ustanovitve univerze leta 1975). https : / / blog . OPOMBE cobiss . si / 2021 / 05 / 12 / pionirski - cas - mariborskega - Sestavek vsebuje spomine. Vsega napisanega nisem uspel preve- racunalnistva- do- ustanovitve- univerze- leta- 1975/. riti v dokumentih. Zato se mi je tu pa tam lahko zapisala kaka [17] Franc Spiller-Muys, urednik. 1971. Elektronski računalniki, netočnost. osnove-programiranje-uporaba. Elektrotehniška zveza Slo- venije, Ljubljana. LITERATURA [18] Niklaus Wirth in Boštjan Vilfan (prevod). 1979/1983. Ra- [1] Vladimir Batagelj. 2020. Diskretna matematika in računal- čunalniško programiranje, 1. / 2. del. DMFA SRS, Ljubljana. ništvo (ter analiza podatkov). V Sto let matematike in fizike [19] Egon Zakrajšek. 1973. Fortran. IMFM, Ljubljana. na Univerzi v Ljubljani. Mirko Dobovišek in Alojz Kodre, [20] Egon Zakrajšek. 1966. Programiranje v ALGOLU. IMFM. uredniki. Univerza v Ljubljani, FMF, Ljubljana, 171–185. Ljubljana. isbn: 978-961-6619-26-4. [21] Egon Zakrajšek. 1965. Programiranje v simboličnem jeziku [2] Vladimir Batagelj. 1973. Gramatika in prevajanje aritmetič- računalnika Z-23. IMFM. Ljubljana. nih izrazov jezika pl/1. V Zbornik del VIII. jugoslovanskega [22] Egon Zakrajšek. 1976. Programski jezik pascal. DMFA SRS, mednarodnega simpozija o obravnavanju podatkov Infor- Ljubljana. matica 73. ZSOOP, Bled, a23/1–4. [23] Janez Štalec. [n. d.] Osebna stran. https://web.math.pmf. [3] Vladimir Batagelj. 2016. IFIP 1971 in začetki računalništva unizg.hr/~stabi/. v Sloveniji / osebni pogled. http : / / vladowiki . fmf . uni - [24] Anton P. Železnikar. 1967. Overlapping algorithms. Ma- lj.si/lib/exe/fetch.php?media=pub:pdf:ifip.pdf . thematical systems theory, 1, 4, (december 1967), 325–345. [4] Vladimir Batagelj. 1971. Programerski praktikum 1970/71: doi: 10.1007/BF01695167. Najkrajše poti. Tehnično poročilo. FNT, Matematika, Lju- bljana. http://vladowiki.fmf.uni- lj.si/lib/exe/fetch.php? media=vlado:pub:man:praktikum.pdf . 687 Komisija za uvajanje računalništva v srednje šole The Commission for the Introduction of Computer Science in Secondary Saša Divjak Izidor Hafner FirstName Surname Department Name Fakulteta za elektrotehniko Department Name Institution/University Name Univerza v Ljubljani Institution/University Name City State Country Ljubljana, Slovenija City State Country email@email.com izidor.hafner@fe.uni-lj.si email@email.com POVZETEK stvar bolj za izbrance. Po mojih takratnih podatkih je bilo za praktična znanja v gimnazijah na razpolago 2 uri tedensko v V članku opisujem svoje delovanje na področju računalništva v enem polletju tretjega ali četrtega letnika. Tako sem izvajal srednjih šolah in dajem kratke predstavitve članov komisije za praktična znanja iz računalništva na Šubičevi v prvem polletju uvajanje računalništva v srednje šole. šolskega leta 1969/70. Kmalu po končanju tega pouka sem zaprosil očeta Vinka (1920-2015), da me poveže z Borisom KLJUČNE BESEDE Lipužičem (1930-2012), direktorjem Zavoda za šolstvo. Na Programiranje, pouk, srednje šole sestanku je sodeloval tudi Branko Roblek, ki je bil na Zavodu zadolžen za obdelavo podatkov. Predlagal sem nekaj ljudi, ki bi lahko sodelovali pri tem. V l. 1970 smo imeli na Zavodu par ABSTRACT sestankov, a se od udeležencev spominjam le Rajkoviča, Robleka In this article, I describe my work in the field of computer science in Trampuža. Rajkovič je bil zadolžen za pripravo učnega načrta, in secondary schools and give short presentations by members of pouk pa naj bi stekel v šolskem letu 1970/71 na petih gimnazijah. the commission for the introduction of computer science in Pouk sem izvedel še v prvem polletju leta 1970/71. Zadnjega secondary schools. sestanka sem se udeležil v začetku leta 1971 in povedal, da zaradi diplome ne bom več sodeloval. Od dijakov se spominjam Mirka Ivančiča, ki se je pozneje vpisal KEYWORDS na Fakulteto za elektrotehniko. Šele po 45 letih sem izvedel, da Programming, teaching, secondary education je bil med dijaki tudi Marko Petkovšek, ki poslušal moja predavanja v 2. letniku, nato pa pri Bratku v 4. letniku. Prav tako sem šele po 45 letih izvedel, da se je organizirani pouk računalništva začel šele šolskega leta 1971/72. 1 UVOD Imenovan sem bi v komisijo za uvajanje računalništva 8.9. 1971, a pri njenem delu nisem sodeloval. Po diplomi septembra 1972 Po maturi l. 1968 na Šubičevi gimnaziji sem se vpisal na študij sem takoj dobil službo asistenta za matematiko na FE. tehnične matematike na FNT. V jeseni istega leta smo Ivan Računalništvo sem opustil in se posvetil čisti matematiki. Bratko, Iztok Lajovic in Vladislav Rajkovič na IJS hodili na tečaj Že pred projektom septembra 1971 je bilo nekaj primerov fortrana, ki ga je vodila matematičarka Mira Volk. Računalnik seznanjenja srednješolcev z računalništvom. Peter Prelog je na IBM 1130 je prišel šele po koncu seminarja, to je v začetku l. Gimnaziji Trbovlje vključil nekaj fortanskih programov kar v 1969. pouk matematike in jih preizkusil na Rudisovem IBM 1130, sam Kot študent sem delal na odseku uporabne matematike IIS pri sem na povabilo Marije Munda predaval o fortranu na Gimnaziji Cvetu Trampužu. Moja prva naloga je bila, da sem prenesel Miloša Zidanška v Mariboru… Prvi učitelji računalništva v ročne izračune za termo centrale za IB Elektro Projekt na šolskem letu 1971/72 na gimnazijah so bili Bratko, Kac, Lajovic, računalnik IBM 1130. Po tem programu je bil izdelan hladilni Rajkovič, Roblek in Savnik. Za srednji elektrotehniški šoli stolp za blok 4 v Šoštanju (pozneje tudi blok 5). (Maribor, Ljubljana) podatka nimam, je pa poučeval Takrat sem uvidel, da lahko srednješolec z znanjem računaništvo na Vegovi v šolskem letu 1973/74 Veselko Guštin programiranja lahko naredi veliko, saj se med gradbeniki ni kaj (1948). dosti vedelo o računalnikih. Zato sem prišel na idejo, da se Tekmovanju srednješolcev iz računalništva je bilo v planu že l. programiranje vključi v srednje šole. Zavedal pa sem se, da je 1975, da bi povečali vpis na smer računalništvo, vendar se med ∗ mojim vojaškim rokom 1975/1976 ni nič premaknilo. Ko sem Art Ar ic i le l Title l Foot F note ne n eds to be captur ptu e r d as Ti T t i le l Note †Au A t u hor hor Foo F tnote n to be captur u e r d as Au t Au hor t hor Note prišel iz vojske, sem se zadeve lotil in vodil organizacijo tekmovanja kot tajnik komisije za popularizacijo računalništva Pe P rmis m sio i n n to ma m ke digita igi l l or or ha h rd r copie i s of f part r or r all ll of this work for personal or cla l ssroo r m m u s u e i s i g r g a r nte n d wi d t wi hout u f t e f e pr o pr vided th d a th t c t opie opi s a re r n ot n m ot a m de or or di s di trib i uted pri društvu Informatica, ki je imela sedež na IJS. Prvo for f or pro pr fit f it or or comme mm rc r ia i l l adva v nta n ge g and n tha h t copie i s bear r this hi not n ic i e an a d n th t e h e full f ull tekmovanje je potekalo 17. aprila 1977 na FE.[3, 4, 8, 11] citat i ion n on n the h fir f s ir t page g . Copyrights ight for f or third hir -pa - rt r y y comp m one n nts n of f this hi work mus m t Ko se je pojavilo usmerjeno izobraževanje, se je pojavila be ho h no n re r d. For F or all ll othe h r r us u es, contac on t the h owne wn r/a r ut u ho h r( r s ( ). ) Infor I mation Society 2020, 2020, 5–9 – October 2020 202 , 0, Ljubljana, Slovenia možnost za vpeljavo srednješolskega izobraževanja za © 2020 2020 C Cop opyr yright ight he held ld bby y tthe he owne n r e /a r ut u hor( r s ( ) s . ) računalništvo. V tem smislu je bila narejena Virantova študija o 688 Information Society 2021, 6 October 2021, Ljubljana, Slovenia Izidor Hafner računalniških poklicih. Na tej osnovi sem se lotil profilov poklicev računalniški in programerski tehnik. Namreč brez sprejetih profilov na Zavodu za zaposlovanje ni bilo mogoče imeti izobraževanja. To smo vključili tudi v raziskavo pri RCPU, kjer se na moje presenečenje preselil projekt z Zavoda za šolstvo. Prvi programerski in računalniški tehniki so prišli na fakulteto l. 1985. Takrat sem zamenjal Hodžarja (1923-2010) pri predmetu Osnove programiranja (fortran, pascal). Tako sem spet stopil za nekaj časa med računalnikarje. [5, 6, 7, 11] Leta 1987 sem bil predsednik komisije krožkov robotike pri Cveto Trampuž (1935–1999) je diplomiral l. 1966 na Fakulteti Zavodu za šolstvo. za naravoslovje in tehnologijo v Ljubljani. Od l. 1957 je delal na Inštitutu Jožef Stefan, tudi kot v. d. direktorja Republiškega Ker je minilo 50 let od imenovanja komisije za uvajanje računalništva v srednje šole, se mi je zdelo potrebno, da se računskega centra. Med leti 1970-96 je bil zaposlen na Fakulteti spomnimo članov komisije, od 12 članov je živih le še 5. Vrstni za družbene vede v Ljubljani, najdalj kot predstojnik red je tak kot v odločbi. računalniškega centra. Bil je med prvimi računalnikarji v Sloveniji, na FDV pa je v družboslovje uvajal računalniško podprte matematične in statistične metode. Zaslužen je bil za ustanovitev študijske smeri družboslovna informatika. 2 KOMISIJA 1971 Egon Zakrajšek (1941– 2002) je maturiral na Gimnaziji Jesenice. Branko Roblek (1934–2000) je maturiral na Gimnaziji v Kranju, Diplomiral je iz tehniške matematike. Za podprograme za prvi na Univerzi v Ljubljani je diplomiral iz fizike l. 1959, in iz elektronski računalnik v Sloveniji ZUSE Z-23 (z elektronkami, matematike l. 1962. Od l. 1962 je poučeval na Gimnaziji Škofja velik nekaj 10 m3) je dobil študentsko Prešernovo nagrado. Bil Loka. Potem je štiri leta delal na Zavodu RS za šolstvo kot je največji slovenski strokovnjak za ta računalnik. Leta 1968 je pedagoški svetovalec za naravoslovje in bil imenovan za prevzel vodenje Računskega centra Inštituta za matematiko, predsednika komisije za uvajanje računalništva v srednje šole. fiziko in mehaniko in skrbel tudi za programsko opremo ter Leta 1973 se je vrnil na Gimnazijo Škofja Loka in tam vse do reševal računalniške probleme iz drugih strok in iz gospodarstva. upokojitve leta 1992 učil matematiko, fiziko in računalništvo z Leta 1978 je doktoriral in bil izvoljen v naziv izrednega informatiko. V Društvu matematikov, fizikov in astronomov profesorja. Slovenije je leta 1970 prejel priznanje za uspešno pedagoško delo in hkrati organiziranje in smotrno vodenje krožkov, posebno astronomskega. Virant Jernej (1932–2008) je l. 1965 magistriral in l. 1966 Mira Volk (1939) je maturirala na Gimnaziji Brežice in se nato doktoriral iz elektrotehnike. Leta 1971 je bil izvoljen za l. 1957 vpisala na študij matematike. Po diplomi l. 1962 se je izrednega in l. 1977 pa za rednega profesorja za predmete s zaposlila na IJS. Ko je IJS l. 1972 ustanovil RRC se je področja računalniške logike in računalniških sistemov. Na prezaposlila na RRC, kasneje pa se je zaposlila nazaj na IJS na fakulteti za elektrotehniko je organiziral laboratorij za digitalne odseku za uporabno matematiko. Za potrebe programiranja na računalnike. V času 1977 računalniku ZUSE Z 23 je bila Mira poslana v Bad Hersfeld, -1979 je bil dekan Fakultete za najprej na tečaj algola in potem je za potrebe programiranja IBM elektrotehniko. 1130 preučila fortran, napisala knjigo in nadalje učila fortran tudi druge. 689 Izidor Hafner Information Society 2021, 6 Oktober 2021, Ljubljana, Slovenia Janez Lesjak (1942) se je rodil v Novem mestu. Leta 1966 je diplomiral iz fizike. Da je res zašel v računalništvo, je bilo krivo tudi to, da je ZUSE Z23 iz razstavišča ostal Franc Savnik (1940) se je rodil na Sušaku, maturiral l. 1958 na l. 1962 v Ljubljani in je bil instaliran na Metalurškem inštitutu, čisto blizu gimnaziji Brežice in diplomiral l. 1963 na pedagoški smeri PMF njegovega doma. Skupaj z Zakrajškom sta naredila veliko Univerze v Zagrebu. S programiranjem se je seznanil kot izredni programov za omenjeni računalnik. Ko je bil nabavljen študent smeri Praktična matematika na PMF. Računalništvo je na računalnik Cyber 72 leta 1972 je postal glavni sistemski inženir Gimnaziji Brežice poučeval 25 let (1971/72 do 1995/1996), tudi Republiškega računskega centra. med sedemletnim službovanjem na Zavodu za šolstvo SRS (1972/1973 - 1978/79). Leta 1996 je prejel nagrado RS na področju šolstva. Vladislav Rajkovič (1946). Po diplomi iz elektrotehnike se je zaposlil na IJS. Leta 1970 je bil zadolžen za pripravo učnega načrta za izbirni predmet računalništvo za gimnazije. Skupaj z Ivanom Bratkom sta napisala učbenik, ki je izšel l. 1974. Sta najzaslužnejša za uveljavitev računalništva v srednjih šolah. Leta 2010 je mu je Univerza v Mariboru podelila naziv zaslužni Izidor Hafner (1949) je diplomiral na smeri tehnična matematika profesor. l. 1972 in magistriral iz funkcionalne analize l. 1974. Iz računalništva je doktoriral l. 1984. Leta 2000 je bil odlikovan s Častnim znakom svobode RS za zasluge pri uvajanju računalništva in logike v srednje šole ter za delo z mladimi na tem področju. Milan Kac (1924-2010) se je rodil v Lendavi. Leta 1949 se je vpisal na študij matematike v Ljubljani, kjer je diplomiral l. 1953. Bogomir Horvat (1936-2013) je bil predavatelj elektrotehnike na Najprej je poučeval matematiko na I. gimnaziji v Mariboru, po l. Visoki tehnični šoli v Mariboru. V obdobju 1975-1977 je bil tudi 1960 pa je predaval na Višji tehniški šoli. Doktoriral je l. 1975 dekan te ustanove. Študenti se ga spominjajo kot odličnega na Tehniški visoki šoli v Gradcu. Napisal je več učbenikov za strokovnjaka. Upokojen je bil kot profesor na FERI v Mariboru. matematiko in l. 1970 priročnik za fortran. Leta 1992 mu je Univerza v Mariboru podelila naziv zaslužni profesor. 690 Information Society 2021, 6 October 2021, Ljubljana, Slovenia Izidor Hafner Milan Adamič (1938-2019) se je rodil v Vidmu-Dobrepolje. Leta 1964 je diplomiral s področja pedagogike in psihologije. Leta 1969 je pričel delati na Zavodu za šolstvo kot pedagoški svetovalec za izobraževalno tehnologijo in od leta 1978 kot pedagoški svetovalec za osnovno šolo. Leta 1993 se je zaposlil na Oddelku za pedagogiko FF v Ljubljani. REFERENCE [1] I. Bratko, J. Grad, M. Kac, J. Lesjak, V. Rajkovič, J. Virant, E. Zakrajšek, RAČUNALNIŠTVO Gradivo s tečaja za srednješolske profesorje, uredil B. Roblek, Zavod za šolstvo, Ljubljana 1972; [2] Ivan Bratko, Vladislav Rajkovič , Uvod v računalništvo, Državna založba Slovenije, Ljubljana 1974; [3] S. Divjak, I. Hafner…, Material za pripravo nalog za srednješolska tekmovanja iz računalništva, Institut Jožef Stefan, Ljubljana 1975; [4] I. Hafner, Prvo republiško tekmovanje iz računalništva, Delo, 21. april 1977, str. 7; [5] I. Hafner, Profil poklica »programerski tehnik«, RCPU, Projekt Računalništvo v usmerjenem izobraževanju, Ljubljana 1977; [6] I. Hafner, Profil poklica »računalniški tehnik«, RCPU, Projekt Računalništvo v usmerjenem izobraževanju, Ljubljana 1977; [7] I. Hafner, Poklici računalniške stroke v srednjem usmerjenem izobraževanju, RCPU, Projekt Računalništvo v usmerjenem izobraževanju, Ljubljana 1978;. [8] V. Batagelj, T. Dolenc, M. Martinec, B. Mohar, R. Reinhardt, I. Tvrdy, A. Vitek, Enajsta šola računalništva, Rešene naloge z republiških tekmovanj 1977-1987, DMFA Slovenije, ZOTKS, Ljubljana 1988; [9] Andrej Vitek, Iztok Tvrdy, Robert Reinhardt, Bojan Mohar, Mark Martinec, Tomi Dolenc, Vladimir Batagelj, Problems in Programming, John Wiley & Sons, New York 1991. [10] http://vladowiki.fmf.uni-lj.si/doku.php?id=spomin:rac:hafner [11] https://sites.google.com/view/prvotekmovanjeizracunalnistva/d oma%C4%8Da-stran 691 50 let od uvedbe predmeta računalništvo v srednje šole: poskusni pouk in učbenik Introducing Informatics in secondary schools 50 years ago: Experimental teaching and text book Ivan Bratko Iztok Lajovic Vladislav Rajkovič Fakulteta za računalništvo in Kreativni sistemi Fakulteta za organizacijske vede informatiko Ljubljana, Slovenija Univerza v Mariboru Univerza v Ljubljani Iztok.Lajovic@kres-ks.si Ljubljana, Slovenija Vladislav.Rajkovic@gmail.com bratko@fri. uni-lj.si POVZETEK Letos mineva 50 let od uvedbe poskusnega pouka računalništva 1 UVOD v slovenske srednje šole. V tem prispevku navajamo nekaj zgodovinskih dejstev o projektu uvedbe pouka računalništva Letos mineva 50 let od uvedbe poskusnega pouka računalništva pred 50 leti ter opišemo naše lastne spomine na to, kako smo v slovenske srednje šole. Projekt uvedbe tega pouka je začel sodelovali pri poskusnem pouku računalništva in kako je nastal Zavod za šolstvo Republike Slovenije l. 1971. V nekaj letih, do učbenik za ta predmet. š.l. 1974/75, je predmet Računalništvo zajel 65 srednjih šol in 2500 srednješolcev, izšel je učbenik, usposobljenih je bio 75 učiteljev za ta predmet. S tem projektom je Slovenija močno prehitela druge republike KLJUČNE BESEDE tedanje Jugoslavije in bila po nekaterih ocenah v tem pogledu srednješolski pouk računalništva, poskusni pouk, učni načrt, med vodilnimi v Evropi. Boris Lipužič, tedanji direktor Zavoda učbenik za šolstvo, je l. 2010 v opisu tega projekta zapisal [8]: “Poročilo Generalnega direktorata za izobraževanje in kulturo Evropske komisije na sedežu EU v Bruslju za leto 2000/01 navaja, da je ABSTRACT Slovenija začela vpeljevati pouk računalništva v srednjih šolah že leta 1974, celo pred Zvezno republiko Nemčijo – ta je uvajanje Fifty years ago, experimental teaching of informatics was zastavila šele v poznih sedemdesetih letih ( Basic Indicators on introduced in secondary schools in Slovenia. In this paper, we the incorporation of ICT into European Education Systems, present some historical facts about the introduction of the Facts and figures, Eurydice 2001, str. 17, Brussels).” Omenimo, informatics course 50 years ago, and describe our memories of da gornji citat iz Lipužičevega članka ni povsem dobeseden our own involvement in the teaching of informatics at that time, prevod navedbe v originalnem dokumentu Evropske komisije. and the writing of the textbook for this course. Tudi ni povsen jasno, kaj je točno mišljeno z letnico 1974. Vendar tudi originalno besedilo nedvomno uvršča pouk v KEYWORDS Sloveniji med najbolj zgodnje v Evropi. teaching informatics in secondary schools in Slovenia, V pričujočem prispevku navajamo nekaj zgodovinskih experimental teaching, informatics curriculum, informatics dejstev o projektu uvedbe pouka računalništva pred 50 leti ter textbook opišemo naše lastne spomine na to, kako smo sodelovali pri poskusnem pouku računalništva in kako je nastal učbenik za ta predmet. Permission to make digital or hard copies of part or all of this work for personal or 2 PROJEKT UVEDBE SREDNJEŠOLSKEGA 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 POUKA RAČUNALNIŠTVA citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia V tem razdelku so navedena dejstva o projektu uvedbe pouka © 2020 Copyright held by the owner/author(s). računalništva v srednje šole v Sloveniji. 692 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia F. Surname et al. 5. 4. 1971 je bilo poslano prvo vabilo z Zavoda za šolstvo RS Z razvojem programskega jezika pascal, natančneje z Slovenije za sestanek za pripravo projekta za postopno uvajanje razširitvami turbo pascala, se je pojavila tudi potreba po pouka o računalništvu v srednje šole. ustreznem učbeniku. Ta je izšel 1990 v nakladi 5.000 izvodov 13. 4. 1971 je potekal v direktorjevi pisarni na Zavodu [2]. sestanek o pouku računalništva na srednjih šolah. S strani Zavoda sta sodelovala Milan Adamič in Branko Roblek, s strani Instituta »Jožef Stefan« Vladislav Rajkovič, Cveto Trampuž in Mira Volk, Tabela 1: Rast obsega pouka po šolskih letih Fakulteto za elektrotehniko je zastopal Jernej Virant, Republiški računski center Janez Lesjak, INFIM Egon Zakrajšek in Višjo Š. leto Šol Razredov Dijakov Učiteljev tehniško šolo Maribor Milan Kac. Sprejeta sta bila dva sklepa: 1971/72 7 12 200 - a) V šolskem letu 1971/72 se uvede poskusni pouk 1972/73 20 30 500 25 računalništva v štirih izbranih šolah. Pouk naj bi se 1973/74 40 75 1800 50 odvijal v obliki izbirnega predmeta v okviru ur za 1974/75 65 100 2500 75 praktična znanja. b) Treba je izdelati učni načrt in z njim v skladu pripraviti ustrezni učbenik. Koncem aprila 1971 je Zavod pripravil Projekt uvajanja pouka o računalništvu v srednje šole. Projekt je vodil Branko Roblek. Predvideno je bilo postopno uvajanje s sprotno evalvacijo v šolskih letih od 1971/72 do 1975/76. Postopno naj bi se povečevalo število šol. Posebej je bil izpostavljen problem učnega kadra. V začetku naj bi poučevali računalniški strokovnjaki iz okolja, ob sprotnem usposabljanju učiteljev iz šol. V ta namen je bil organiziran tečaj za učitelje in pripravljeno gradivo »Računalništvo« sedmih avtorjev (slika 1). 12.7.1971 je Zavod razposlal vabilo petim gimnazijam in dvema tehniškima šolama za pričetek poskusnega izvajanja pouka računalništva. S pričetkom projekta se je pričela tudi priprava učnega načrta predmeta. Pri tem smo se v večji meri opirali na priporočila IFIP- a, ki je leta 1970 organiziral 2. svetovno konferenco Computers Slika 1: Gradivo za tečaj za učitelje in Education. Posebno vzpodbudo je predstavljal tudi IFIP-71, svetovni računalniški kongres, ki je potekal v Ljubljani. Učni načrt je obsegal 52 ur. Od tega je bilo namenjenih 8 ur pripravi problema in rešitve ter 22 ur programskemu jeziku fortran. Predvideno je bilo praktično delo na računalniku: izdelava in testiranje programa. Leta 1974 je izšel učbenik Uvod v računalništvo, ki je bil ponatisnjen še sedemkrat v več kot 20.000 izvodih [3]. Iz leta v leto se je povečevalo število šol, kjer se je poučeval predmet računalništvo, število učencev pa tudi število učiteljev, saj se izobraževanje na že omenjenem posebnem tečaju za učitelje. Ti podatki so prikazani v tabeli 1. Rezultati projekta so bilo objavljeni tudi na IFIP 2nd World Conference Computers in Education leta 1975 [6]. Leta 1977 so se pričela tudi tekmovanja srednješolcev iz računalništva. Leta 1981 je v 3.000 izvodih izšla zbirka nalog [1]. Leta 1980 je izšel učbenik »Osnove tehnike in proizvodnje« v okviru skupnih izobraževalnih osnov v srednjih šolah. V tem učbeniku je bilo tudi poglavje » Informatika in računalništvo« na 38 straneh [4]. Učbenik je bil še dvakrat ponatisnjen v skupnem številu 52.000 izvodov. Leta 1981 je založba Univerzum izdala mapo s prosojnicami Slika 2: Prvi učbenik in diapozitivi v pomoč učiteljem pri poučevanju informatike in računalništva. Že koncem sedemdesetih let se je začel poučevati programski jezik pascal. Temu je sledil novi učbenik Računalništvo s programskim jezikom pascal, ki je izšel 1984 [5]. Ta učbenik je bil ponatisnjen še štirikrat v skupni nakladi 24.000 izvodov. Zadnjič leta 1989. 693 Insert Your Title Here Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Poskusni pouk računalništva je bil deležen zelo pozitivnih odzivov in komisija za uvajanje pouka sklenila: zdaj potrebujem 3 POSKUSNI POUK IN UČBENIK učbenik, kaj če bi poskusila Bratko in Rajkovič? Jeseni 1971 se je začel poskusni pouk računalništva na izbranih srednjih šolah. Na gimnazija Bežigrad smo učili soavtorji tega prispevka. Ta pouk nam je bil vsem trem v veliko veselje, pravzaprav tako kot skoraj vse, s čimer smo se takrat ukvarjali. Bili smo eno leto po diplomi na Fakulteti za elektrotehniko v Ljubljani. Kar nas je posebej kvalificiralo za ta pouk, je bilo to, da smo se med študijem, pravzaprav bolj ob študiju, naučili tudi nekaj računalništva, med drugim programirati v algolu in fortranu. Prve programerske korake smo naredili na računalniku Zuse na Fakulteti za matematiko in fiziko. Toda za delo na tem računalniku si moral z našim statusom študenta vstati ob 6h zjutraj, sicer pa je bil računalnik zaseden. No, ko smo prešli na fortran in začeli programirati za nekatere znane profesorje na Univerzi in Institutu Jožef Stefan, so se nam še pred diplomo pogoji za delo na računalnikih močno popravili. Ko smo začeli s poskusnim poukom računalništva, se nam je Slika 2: Učbenik za Osnove tehnike in proizvodnje iztekalo prvo leto naše zaposlitve v Oddelku za elektroniko na Institutu Jožef Stefan. Ob zaposlitvi so nam dodelili skupno “pisarno”, osamljeno sobo na sicer povsem neobdelanem podstrešju. Takrat, ob navdušenju nad prvo zaposlitvijo v zanimivem raziskovalnem okolju skoraj niti nismo opazili, kako neprimeren delovni prostor je bil to. Pot do naše pisarne je vodila po neobljudenem podstrešju med tramovjem in ovirami, ki so naključno ležale po podstrešju. Hoja do pisarne je zato bila svojevrstna pustolovščina, posebej v temi ponoči. Naša soba je imela le majhno strešno okno, pravzaprav strešno lino. Poletne temperature v tem prostoru so bile neznosne. Toda nič od tega nas ni posebej motilo, saj smo bili tako zaposleni s svojim raziskovalnim delom in aplikativnim delom, nenehnimi pogovori o novih in novih idejah, ves čas se je dogajalo kaj zanimivega. Del tega vzdušja so bile tudi naše priprave na pouk računalništva. Temu je bilo namenjeno dopoldne vsak torek v tednu, ko je imel tisto popoldne prvi od nas naslednjo uro pouka na gimnaziji. Takrat smo prediskutirali stanje pouka, izkušnje iz prejšnjega tedna ter naredili načrt, kaj bomo učili ta teden. Slika 3: Učbenik iz l. 1984 Vseskozi smo bili trdno odločeni, da se držimo nekaterih osnovnih načel: da bomo spodbujali aktivno delo učencev, učili reševanje problemov z računalniki z mnogimi primeri in da bomo veliko od tega dejansko sprogramirali ter kolikor bo možno tudi izvedli na računaniku. Za pouk nam je bil dosegljiv, sicer v zelo omejenem obsegu le računalnik IBM 1130 na Fakulteti za matematiko in fiziko na Jadranski cesti. Programski jezik je bil fortran. Mislim, da smo nazadnje vsi dosegli, da je vsak naš učenec napisal vsaj po en svoj program, ga spravil na luknjane kartice in izvedel na računalniku. Program na luknjanih karticah je izgledal kot paket kart, ki smo ga navadno speli z elastiko, da se kartice ne bi po nesreči pomešale. V tej zvezi se spomnimo zabavnega dogodka, ko je nek dijak v svoji raztresenosti vstavil v računalnik svoj paket lunkjanih kartic kar z elastiko vred. Čitalnik kartic je ob branju kartic elastiko takoj raztrgal in se ob tem pokvaril … Med našimi učenci pri takratnem pouku tistega leta ali kakšno leto kasneje so bila tudi imena, ki so kasneje postala dobro prepoznavna, med drugimi: prof. dr. Matjaž Gams, dr. Marko Slika 4: Učbenik iz l. 1990 Gričar, prof. dr. Marko Petkovšek, prof. dr. Franc Solina. 694 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia F. Surname et al. Učbenik je nastajal ob izvajanju poskusnega pouka učbenika. Tudi programski jeziki zapisani z malo računalništva in je bil oblikovan po našem izvedenem začetnico. pouku v prvih dveh šolskih letih pouka. Knjiga je bila razdeljena v dva dela: (I) Zgradba, 4 ZAKLJUČEK delovanje in uporaba računalnika, (II) Programski jezik fortran. Poglavja v I. delu so bila: 1. Uvod, 2. Projekt pred 50 leti je potekal hitro in učinkovito. Osnovni pojmi o informacijah in njih predstavitvi, (3) Deležen je bil pozitivne ocene tudi v mednarodnem Zgradba računalnika, (4) Odvijanje programa v merilu. Pozitivno ocenjujemo tudi težnjo po tem, da je računalniku, (5) Programski jeziki, (6) Reševanje v pouku bilo poudarjeno reševanje problemov z problemov z računalniki (vključno z značilnimi algoritmi ter razvijanje algoritmičnega razmišljanja. primeri konstruiranja algoritmov), (7) Uporaba Kaj se je dogajalo s poukom računalništva kasneje, računalnikov, (8) Računalniški sistemi. Poglavje 7 je ko sta postajala računalništvo in digitalizacija vsebovalo daljši razdelek o umetni inteligenci. Poleg neprimerno bolj razširjena in pomembna in so se tega pa tudi razdelek »Ali računalnik ogroža človeka«. kazale nujne potrebe po spremembah učnih programov Ta razdelek se konča takole: »Morda je najbolj za računalništvo? Ne bi mogli reči, da so bile upravičena bojazen pred vmešavanjem računalnikov v spremembe vedno posrečene in pravočasne. Posebej pa človekove osebne stvari. Skrajno neprijetna je namreč je težko razumeti, zakaj je danes veliko teže doseči zavest, da bi lahko obsežne datoteke z vsemi mogočimi spremembe učnega načrta, čeprav se o njihovi podatki, omogočile dostop do vseh osebnih podatkov potrebnosti strinja praktično celotna računalniška o komerkoli.« stroka, doma in v svetu [7]. Posebna skrb je bila v učbeniku namenjena računalniškemu izrazoslovju. Dolge so bile debate o prevodih posameznih pojmov, kot npr.: pomnilnik, REFERENCES računalniška beseda, naslov, adresa ipd. Marsikatero [1] Janez Benkovič, Aleksander Cokan, Mark Martinec, Robert Reinhardt, dilemo nam je pomagal razrešiti tudi jezikoslovec Branko Roblek. Računalništvo: Zbirka nalog 1. Državna založba Tomo Korošec. Ko smo ga povprašali, kako naj Slovenije, 1981. [2] Ivan Bratko, Bojan Cestnik. Programski jezik pascal z razširitvami turbo zapišemo imena programskih jezikov, je dejal takole: pascala. Državna založba Slovenije, 1989. »Če niste pogumni, jih pišite z velikimi tiskanimi [3] Ivan Bratko, Vladislav Rajkovič. Uvod v računalništvo, Državna založba črkami. Z malo poguma jih pišite z veliko začetnico, Slovenije 1974. [4] Ivan Bratko, Vladislav Rajkovič. Informatika in računalništvo. V če pa imate dovolj poguma jih pišite z malo začetnico, učbeniku Osnove tehnike in proizvodnje, Tehniška založba Slovenije, kot pišemo imena jezikov v slovenščini«. In tako smo 1982. [5] Ivan Bratko, Vladislav Rajkovič. Računalništvo s programskim jezikom zapisali fortran, pascal in druge. Razen zelo redko Pascal. Državna založba Slovenije, 1984. uprabljanih jezikov in PL1, ki je kratica. [6] Ivan Bratko, Vladislav Rajkovič, Branko Roblek: What should econdary school studenta know about computers: Analysis of an experiment. IFIP Z veseljem lahko ugotovimo, da je skrb za 2nd World Conference: Computer in Educatio, 1975. slovensko računalniško izrazoslovje tudi danes zelo [7] Andrej Brodnik s soavtorji. Snovalci digitalne prihodnosti ali le živa, na primer v Slovenskem društvu uporabniki? Poročilo strokovne delovne skupine za analizo prisotnosti vsebin računalništva in informatike v programih osnovnih in srednjih šol INFORMATIKA, kot tudi na univerzah in inštitutih. ter za pripravo študije o možnih spremembah (RINOS). Ministrstvo za Društvo redno vzdržuje Islovar računalniških pojmov, izobraževanje, 2018. [8] Boris Lipužič, 2010. Pionirski koraki: 40 let pouka računalništva. Šolski ki je prosto dostopen na spletu. Številni pojmi v razgledi, številka 17/2010. današnjem Islovarju so tudi v pojmovnem kazalu 695 Začetki pouka programiranja na Fakulteti za elektrotehniko UL The beginnings of programming lessons at the Faculty of Electrical Engineering UL Saša Divjak Saša Divjak FirstName Surname Department Name Fakulteta za računalništvo in Department Name Institution/University Name informatiko Institution/University Name City State Country Univerza v Ljubljani City State Country email@email.com Ljubljana, Slovenija email@email.com sasa.divjak@fri.uni-lj.si POVZETEK med nami, je verjetno smiselno, da spomine na takratne čase strnem jaz. Morda pa me bo še kdo dopolnil. Prispevek obravnava prve korake v poučevanje programiranja na takratni Fakulteti za elektrotehniko. To je vodilo v začetek Danes se bo kdo pri teh spominih le prizanesljivo nasmihal. A ne študijskega programa Računalništvo in informatika. Razvoj tega pozabimo, da je od takrat minilo že več kot 50 let in verjamem, študijskega programa je omogočil oblikovanje Katedre za da se bodo ljudje podobno nasmihali čez naslednjih 50 let, kako računalništvo in informatiko in čez dolga leta razvoj samostojne se gremo računalništvo danes. Fakultete za računalništvo in informatiko. KLJUČNE BESEDE 2 ZAČETKI NA FAKULTETI ZA Programiranje, pouk, visokošolski študij ELEKTROTEHNIKO V tistem času seveda še ni bilo pouka računalništva oziroma ABSTRACT informatike. Na takratni fakulteti smo imeli takoimenovani jaki The paper discusses the first steps in teaching programming at in šibki tok, ki sta se v zadnjih letnikih delila na več smeri. Še the Faculty of Electrical Engineering. This led to the beginning najbližje računalništvu je bila smer avtomatika, sam pa sem of the study program Computer Science and Informatics. The takrat ubiral bolj splošno smer elektrotehnike. V zadnjih letnikih development of this study program enabled the formation of the je prof Skubic, ki je sicer predaval matematiko, obljubljal, da bo Department of Computer Science and Informatics and, over organiziral tečaj iz programiranja. Jeseni leta 1967 so tak tečaj v many years, the development of an independent Faculty of obliki enosemestrskega predmeta res izvedli in se ga je udeležilo Computer Science and Informatics. približno 40 študentov. Po mojem bledem spominu nam je, - takrat še asistent – predaval kasnejši professor Tomšič. Učil nas je programski jezik algol (pravzaprav njegovo podmnožico KEYWORDS alcor). Algol je bil razvit v sredini 1950tih let in je več kot 30 let Programming, teaching, higher education služil za opis algoritmov v akademskih krogih. Na koncu tečaja smo imeli možnost preskusa krajšega program,a na računalniku ZUSE Z-23 [2], ki so ga imeli na Inštitutu za matematiko, fiziko in mehaniko. Kolikor se spomnim, smo 1 UVOD morali sprogramirati tabeliranje neke funkcije in ta programček vnesti v raču Prispevek predstavlja le droben kamenček nalnik preko luknjanega traku. Kot vhodno-izhodna v pestrem mozaiku enota računalnika je služil v bistvu teleprinter, kakršne smo v pouka programiranja v Sloveniji. Še kot študent sem doživel tistem času srečali na poštah. začetke pouka programiranja pred petdesetimi leti na takratni Fakulteti za elektrotehniko in kasnejšo vpeljavo študijskega Pri tem prvem praktičnem preskušanju programa se mi je takrat programa Računalništvo in informatika. Ne nazadnje pa sem bil zdelo čudno, da si v računalnik najprej vnesel program in šele v vlogi prvega asistenta za predmet Programiranje. Glede na to, nato podatke. Pri reševanju matematičnih in drugih nalog smo da prvega učitelja tega predmeta, prof. Hodžarja že dolgo ni več pač bili navajeni, da imajš najprej podan problem z vsemi podatki ∗ in šele nato se lotiš računanja. Art Ar ic i le l Title l Foot F note ne n eds to be captur ptu e r d as Ti T t i le l Note †Au A t u hor hor Foo F tnote n to be captur u e r d as Aut Au hor hor Note Tako smo prišli do ocene predmeta, ki so nam ga celo vpisali v Pe P rmis m sio i n n to ma m ke digita igi l l or or ha h rd r cop c i op e i s e s of f part or all ll of f this work for persona n l l or indekse, čeprav uradno sploh ni bil v učnem programu fakultete. cla l ssroo r m m u s u e i s i g r g a r nte n d wi d t wi hout u f t e f e pr o pr vided th d a th t c t opie opi s a re r n ot n m ot a m de or or di s di trib i uted Marsikoga med nami je ta tečaj zaznamoval in v poletju 1968 se for f or pro pr fit f it or or comme mm rc r ia i l l adva v nta n ge g and n tha h t copie i s bear r this hi not n ic i e and n the h full f ull citat i ion n on n the h fir f s ir t page g . Copyright ig s hts for f or th t ird hir -pa - rt r y y comp m one n nts n of f this hi work r mus m t nas je kakšnih 30 izbrancev (po opravljenem testu) udeležilo be ho h no n re r d. For F or all ll othe h r r us u es, contac on t the h owne wn r/a r ut u ho h r( r s ( ). ) tečaja za zbirni jezik (po domače (a nepravilno) assembler) za Infor I mation Society 2020 2020, 5–9 – October 2020, Ljubl L jana, jubl Slovenia © 2020 2020 C Cop opyr yright ight he held ld bby y tthe he ow owne nerr/a /aut utho horr((ss)).. računalnik IBM 360, ki ga je organiziral IBM. Programiranje je 696 Information Society 2021, 6 October 2021, Ljubljana, Slovenia Divjak Saša potekalo v papirni obliki, večinoma z risanjem diagramov poteka (če si res zelo potrudil) množil in celo delil. A predvsem za in premetavanjem podatkov po računalniških registrih. Na koncu deljenje si potreboval kar “doktorat”. pa je sledil preskus krajšega programčka, topot pretipkanega na Kako so lahko potekale vaje z enim takim strojčkom in 36 luknjane kartice. In ta tečaj je verjetno zaznamoval vse moje študenti si lahko že kar težko zamišljamo. Vendar je Fakulteta k strokovno življenje. sreči že naslednje leto dobila 17 kalkulatorjev HP 35[3]. To je V tistem letu sem tudi zaprosil za diplomsko temo prof. bil prvi žepni znanstveni kalkulator, ki je že imel tudi Gyergyeka. Ta me je povezal s prof. Bremšakom. Za diplomo trigonometrične funkcije. Te napravice so bile takrat tako sem moral simulirati preprost model nuklearnega reaktorja in pri dragocene, da so jih priklenili na mize v učilnici. In tako smo tem uporabiti IBMjev simulacijski program CSMP (Continuous prišli do “Laboratorija za numerične metode”, ki je dejanski System Modeling Program), ki je tekel na računalniku IBM 11- predhodnik današnjega Laboratorija za računalniško grafiko in 30 [2]. V Ljubljani takega računalnika v letu 1968 še nismo imeli multimedije. Zakaj tako, pa je že druga zgodba 😊 in sem moral to delati na Fakulteti za elektrotehniko v Zagrebu. Povrnimo se raje k poučevanju programiranja. Seveda smo takrat Tak računalnik so nato v Ljubljani prvi dobili na Fakulteti za že imeli na voljo IBM11-30 in njegove luknjane kartice. Vendar matematiko in fiziko in sem tako zaradi pridobljenih izkušenj so študenti ta računalnik lahko gledali le skozi šipo. Prof. Hodžar imel dovoljenje, da samostojno dostopam do njihovega je predaval fortran. Izpit je skoraj vedno potekal tako, da so računalnika. To pravico so imeli le nekateri in navadnim študenti morali sprogramirati tabeliranje bolj ali manj zapletene študentom neposredno samostojno delo še ni bilo omogočeno. funkcije. Svoj program so zapisali na posebne obrazce, te pa je Sam sem se v tistih časih prvič srečal s fortranom in kasneje nato luknjačica (poklic, ki je že davno izumrl) pretipkala na razvil kar nekaj simulacijskih programskih sistemov, ki so jih luknjane kartice. Te je nato operaterka poslala skozi računalnik. nato študentje elektrotehnike uporabljali tudi v okviru različnih Profesor pa je prišel do tega, kar je izpisal tiskalnik računalnika. diplom, magisterijev in doktoratov. Študentje tako niso imeli neposrednega dostopa do računalnika. Kolikor se spomnim, je imel ta računalnik 8kB pomnilnika in Ta je bil omogočen le diplomantom in osebju fakultete. In prav izmenljive diskovne pogone. Podobno, kot danes nosimo s seboj zanimivo je bilo ocenjevanje: Za vsako napako je študent imel USB ključke, smo takrat prinašali v računski center kakšnih 30 oceno zmanjšano za 1. Torej si pri petih napakah prišel do cm široke magnetne diske, torej približno kot današnje torbe nezadostne ocene. Sam se s tem načinom sicer nisem strinjal, a osebnih računalnikov. In njihova kapaciteta: kar celih 512 KB tako je pač bilo. V bistvu je bil študent kaznovan tudi za svoje (pol megabajta). Tako zaradi njihove velikosti kot tudi cene si tipkarske napake, kar je nesmisel. običajno imel le po nekaj takšnih diskov in še to na službene stroške. Celoten računalniški system je zasedal kar veliko sobo, ki je morala biti klimatizirana in z dvignjenim podom, pod katerim je bilo razvejeno kablovje. Tako si v bistvu imel 3 UVAJANJE PROGRAMA računalniški center. Vsak uporabnik je moral beležiti števec, ki RAČUNALNIŠTVO IN INFORMATIKA je kazal število porabljenega časa. Vzdrževanje sistema pač ni Porodila se je zamisel o uvedbi študijskega programa bilo zastonj in nekdo je to moral plačevati (in to me je včasih Računalništvo in informatika, ki je bil v prvi fazi zamišljen kot malo skrbelo). Programiranje je potekalo preko luknjanih kartic. enakopraven program drugim obstoječim študijskim smerem na Računski center je bil zato opremljen še z več luknjači. Malo si Fakulteti za elektrotehniko oziroma na Fakulteti za Matematiko se bal, da ti tak paket kartic s tvojim programom pade na tla in se in fiziko. Torej naj bi potekal kot nadaljevalni program le v sesuje. zadnjih dveh letnikih sicer 4 letnega študija. Sam sem kot asistent Za zabavo sem v tistem času napisal tudi krajši program, dolg sodeloval v vlogi zapisnikarja pri nekaterih sestankih, ki so morda 100 vrstic v zbirnem jeziku IBM-30. It to brez enega potekali na naši fakulteti. Tako se spomnim, da so pri pripravi samega komentarja! Ko sem ta program spet pogledal čez kakšno prvega študijskega programa sodelovali prof. Hodžar, prof. leto, seveda nisem več vedel, kaj je počel. Komentarji so pač Gyergyek, prof Virant in prof. Leskovar, seveda predvsem vsak pomembni. s svojimi predmeti (Programiranje, Teorija informacij, Digitalna Čez eno leto je tak sistem dobila tudi Fakulteta za elektrotehniko, tehnika,..). Danes mi je zelo žal, da sem na roko napisan osnutek le da je bil dvakrat močnejši. Imel je za tiste čase kar spodobnih prvega študijskega programa sčasoma zavrgel, saj bi bil danes 16kB spomina. Če danes pomislim, smo ob tako skromnih zelo zanimiv dokument. Seveda so se pri tem rojevali tudi novi zmogljivostih reševali na računalniku relativno velike probleme. predmeti. Tako je prof. Hodžar prevzel pripravo in izvedbo V letu 1971 (torej kar točno pred 50 leti) me je prof. Hodžar predmeta “Višje programiranje”. Danes bi temu rekli kvečjemu povabil, da bi bil pri njemu asistent pri več predmetih in tudi “nižje programiranje”, saj je šlo za programiranje v zbirnem pri jeziku (seveda za računalnik IBM1130). Prof. Hodžar je v ta predmetu Programiranje. Naj zaradi ilustracije takratnih razmer namen prevedel nek priročnik IBM (in to med predavanji bral ali najprej povem, da je bile eden od teh predmetov tudi “Numerične bolje narekoval študentom). Mene je kar malo zabavalo, ker je metode”. V tistem času so študentje pri svojem računanju uporabljali danes že zdavnaj pozabljena, ravnilu podobna pri tem prevajal v slovenščini tudi mnemonike ukazov v zbirnem logaritemska računala (Rechenschieber) jeziku (LD, STA, BSC,…) . Jaz sem enkrat v šali dejal, da bi [1], za bolj točne izračune pa potem lahko namesto pojma “bistabilni multivibrator” (popularni zamudne logaritemske tablice. Pri predmetu Numerične metode pa sem imel za 36 študentov na voljo en flip flop) lahko uporabili kar izraz “dvoravnovesni računalniški mlinček Facit. Z njim si lahko sešteval, odšteval večtresljalnik” in . Ni vrag, da je začel uporabljati ta prevod 😊. 697 Divjak Saša Information Society 2021, 6 Oktober 2021, Ljubljana, Slovenia V tistem času je prof. Virant predlagal, da jaz prevzamem novi Kar precej navezano na te tehnike programiranja je bilo predmet Računalniška grafika. Seveda pa takrat še nismo imeli sistemsko programiranje in s tem v zvezi uporabna računalnika na voljo kakšnih grafičnih terminalov (vsaj ne na fakulteti). Tako PDP 11, ki smo ga sčasoma dobili na fakulteti. Njegov nabor je predmet lahko potekal le teoretično in bil bolj omejen na to, strojnih ukazov (in posledično zbirni jezik) je bil didaktično čist, kako bi se lahko narisali grafični primitivi, kot so črte, kvadrati podobno kot na primer pri mikroprocesorju Motorola 6800, ki so in krogi. Praktično delo pa je bilo omejeno na obisk sosednjega ga v poznih 1970tih letih vgrajevali v mikroračunanike IskraData inštituta Eles, kjer so že imeli računalnik PDP11/34 in grafični 1680. Operacijski system PDP11 je bil modularen in zelo lahko terminal DEC GT 40 [2]. Seveda so ga študenti lahko le gledali. je bilo pisati gonilnike za zunanje naprave takih računalnikov. To Z današnjega zornega kota so bili takšni terminali skromni. Imeli je bila dobra popotnica tudi za predmet “Operacijski sistemi”, ki so le vektorsko grafiko (risanje črt) in eno samo barvo. sem ga tudi prevzel. Šele v kasnejših letih smo dobili na voljo Če se povrnem na predmet “Višje programiranje” (dejansko pa računalnike, ki so bili opremljeni z operacijskim sistemom nizkonivojsko programiranje), se spomnim študenta (tudi še po UNIX, predhodnikom popularnega LINUX. V bistvu pa to sega imenu), ki me je vprašal, čemu tako programiranje v zbirnem že v 1980ta leta, kar pa je za ta kratek vpogled v zgodovino pouka jeziku sploh služi. Zato sem popeljal študente na bližnji Inštitut računalništvo predaleč. Pri poučevanju operacijskih sistemov Jožef Stefan (tam sem v teh letih preživel večino razvojno sem poleg splošnih konceptov kasneje razlagal tudi interno raziskovalnega časa). Na IJS (seveda tudi v nekaterih zgradbo UNIXa, LINUXa in kasneje tudi Microsoftovih NT. laboratorijih fakutete) smo izkoristili pojav prvih Zaradi omejenega časa so v današnjih študijskih programih to mikroračunalnikov, ki so v začetku temeljili na legendarnem tematiko žal izpustili. procesorju Intel 8008 [5]. Pravzaprav smo kar sami delali računalnike s tem procesorjem. V odseku, ki sem ga vodil, smo ZAKLJUČEK s takimi sistemi razvijali različne računalniško nadzorovane V petdesetih letih se je marsikaj spremenilo. Ne samo v silovitem avtomatizacije. In programiralo se je seveda v zbirnem jeziku. razvoju računalniških in komunikacijskih tehnologij. Najprej kar na takih sistemih s pomočjo luknjanega traku, Veseli me, da me spomini vežejo od prvega volonterskega kasneje smo si pomagali s križnimi zbirniki, implementiranimi predmeta pa preko prvega dvoletnega študijskega programa in na računalnikih PDP-11. Te zgodbe so sicer prav zanimive, a vseh faz razvoja popolnih študijskih programov. V prvih presegajo fokus tega prispevka. Morda samo kot zanimivost generacijah praktično ni bilo študenta, ki ne bi šel tudi “čez moje povem, da takrat ni bilo nobenih razhroščevalnikov, napake, ki roke”. Imel sem tudi veliko diplomantov. Po 330tem sem jih smo jih odkrili, smo pogosto odpravljali kar neposredno na nehal beležiti. Se pa še danes prav dobro spomnim svojega strojnem nivoju v že generirani kodi. Sam sem se takrat ukvarjal prvega diplomanta in prvega doktoranta. Še danes srečujem s pisanjem različnih namenskih gonilnikov, pa kakšen preprost bivše študente. Nekaterih se spomnim tudi po imenu. Vseh pač operacijski system sem tudi sprogramiral. Kakorkoli že, se ne, saj jih je bilo na tisoče. spomnim, da mi je taisti študent potem odgovoril:”Sedaj pa Na razvoj študijskega programa je nedvomno vplivalo tudi, kar razumem, zakaj programiranje v zbirnem jeziku”. Seveda sem že se je dogajalo v srednjih šolah. Predvsem je bilo to potrebno takrat marsikaterega študenta pritegnil v delo na IJS. A bolelo me upoštevati v prvem letniku, saj imajo še danes novopečeni je srce, ker sem moral študente peljati na bližnji inštitut, namesto študentje različno predznanje. Nekateri so popolni začetniki, da bi tako delovno okolje imeli na matični fakulteti. nekateri pa že kar izkušeni programerji. Delno na to vpliva Kot zaključek te zgodbe naj povem, da sem programiranje v njihova osebna motiviranost, delno pa seveda tudi delo jeziku C uvedel na fakulteto še srednješolskih učiteljev in pa sam srednješolski študijski le v 1980 letih prejšnjega stoletja program. in to, vsaj v prvih letih kombiniral s programiranjem v zbirnem jeziku. Saj, kot tisti, ki to poznate, veste, da se marsikaterem C- REFERENCE jevem konstruktu kot razlog skriva prav dogajanje na strojnem nivoju (vzemimo za primer i++ ali –-j, ki imata neposredni vzrok [1] Logaritemskoračunalo:. OI: https://sl.wikipedia.org/wiki/Logaritemsko_ra%C4%8Dunalo v “post increment” oziroma “pre decrement” strojnih ukazih). [2] ZUSE Z 23:. DOI: https://en.wikipedia.org/wiki/Z23_(computer) Pa tudi razumevanje kazalcev, ki je marsikateremu študentu [3] Kalkulator HP 35: DOI: https://sl.wikipedia.org/wiki/HP-35. delalo preglavice, je bolj jasno, če vemo, kaj se [4] Grafični terminal DEC GT 40: DOI: dejansko za tem https://en.wikipedia.org/wiki/DEC_GT40 skriva. [5] Procesor Intel 8008: DOI: https://en.wikipedia.org/wiki/Intel_8008 698 Začetki mariborskega računalništva (do ustanovitve univerze 1975) The beginnings of Maribor computer science (until the founding of the university in 1975) mail.com Franci Pivec franci.pivec@ext.izum.si email@email.com POVZETEK segala po tej ponudbi (Milivojević, Pavlov, 2012). Nekateri so to obžalovali, ker jim je bila bolj všeč sovjetska 'Strela', Prispevek obravnava prve napore za pridobitev računalnikov v obravnavana kot stroga državna tajnost (Kitov, 2014). mariborskem akademskem okolju in navaja zaslužne posameznike, ki so s svojo motiviranostjo in naprednim razmišljanjem pripomogli k njihovi uvedbi. Kaže tudi probleme, Pogled na računalnike je bil tudi pri nas dolgo časa 'strateški', kar ki so jih pri tem morali reševati. je takrat pomenilo centralističen in stran od oči javnosti v okrilju vojske in notranjih zadev. Prvi javni IBM 705 je direktor Dolfe KLJUČNE BESEDE Vogelnik instaliral v Zvezni zavod za statistiko za potrebe popisa Računalništvo, univerza, začetki prebivalstva 1961. in tja vabil tudi entuziaste iz Slovenije, saj je bil to glavni računalnik v državi in po moči (40 KB operativnega spomina) šesti v Evropi. Mimogrede, tudi njegovo zamenjavo ABSTRACT IBM 360/50 je leta 1969 za potrebe naslednjega popisa nabavil Slovenec Ante Novak, na fotografiji z odprtja pa so še drugi The article discusses the first efforts to acquire computers in the pretežno slovenski 'botri' (Novak, Vogelnik, predsednik zvezne Maribor academic environment and lists deserving individuals vlade Ribičič, Osolnik, Bulc), kar kaže na stopnjo zavedanja o who, with their motivation and advanced thinking, contributed to pomenu IKT. their introduction. It also shows the problems they had to solve in doing so. KEYWORDS Computer science, university, beginnings 1 ZAČETKI Pred leti je naša 'etična sekcija' IFIP sestankovala v prostorih Poljske akademije znanosti v Varšavi, od koder iz sredine petdesetih izvira zanimiva anekdota: pri izdelavi domačega 'elektronskega računskega stroja' (beseda kompjutor je bila v celem vzhodnem bloku prepovedana!) ZAM1 sredi petdesetih je bil za utrjevanje kar tisočih instaliranih vakuumskih cevi zelo pripraven pripomoček iz latexa, ki se v lekarni naroči šepetaje, in zanimivo, da vsega vajeno pani magistro niti niso čudile količine,ampak, da to potrebuje metuzalemska akademija znanosti, ji pa ni šlo v glavo. Jasno, da sem hotel s tem le spomniti na čase, ko se računalnikov ni dobilo v trgovini, ampak si ga moral narediti sam. Beograjčan Aleksić je v Pupinu sestavil CER-10, najuspešnejši graditelj takih računalnikov pa je bil 2 PRVI RAČUNALNIKI V SLOVENIJI konec petdesetih Zagrebčan Souček (Frković in dr., 2016). Stigliceva z mariborske VTŠ sta mi povedala, da sta si prvi računalnik tudi onadva naredila sama in sta ga vse do odselitve iz Maribora ljubeče hranila v drvarnici. Iz spominov enega od Slovenija sama je iskala poti, kako priti do zaresnega računalnika očetov računalniške industrije Groscha pa sledi, da je bilo v in precej presenetljivo so leta 1962 na Inštitutu za matematiko, začetku šestdesetih na zahodnem trgu že 90 tipov industrijsko fiziko in mehaniko izbrali 'outseiderja' Zusejev Z-23, kar si izdelanih računalnikov (Grosch, 1991) in ker je State Departme razlagam s tem, da sta se direktor inštituta Anton Kuhelj in nt Konrad Zuse verjetno poznala kot pomembna aeronavtika, razen Jugoslavijo obravnaval enako kot Finsko v sivi coni, je lahko tega pa so naši znanstveniki ta stroj videli na ETH in na nemških 699 Information Society 2021, 6 October 2021, Ljubljana, Slovenia Franci Pivec univerzah. Zuse je tovarno v Bad Hersfeldu takrat že prodal Milan Kac je bil cenjen profesor Siemensu, s katerim je sodelovala Iskra, ki je sofinancirala matematike na mariborski nakup. Z-23 torej zaznamuje začetek računalniške ere v klasični gimnaziji, njegovo ime Sloveniji, ustanovljen je bil Republiški računski center (RRC) in pa je bilo splošno znano po šestih v Iskri Stegne so zuseju sledili vse močnejši CDC-ji do izdajah logaritmov. največjega na Balkanu CYBER 70, ki se je 1972. naselil v soseščini glavnega uporabnika IJS na Jadranski. Univerza je leta Odprtega duha, se je začel med 1967 za svoje učne potrebe dobila IBM 1130, ki so ga instalirali prvimi zanimati za računalnike, na FNT (Pivec, 2008). na novoustanovljeni VTŠ pa je poleg dvajsetih matematičnih učbenikov spisal tudi prvega o računalništvu (Kac, 1970). Nedavno umrli Janez Cundrič ga je leta 1969 v Večeru predstavil skupaj z računalnikom IBM 1130. Ni presenetljivo, da ga je 13. aprila 1971. direktor Zavoda za šolstvo Lipužič povabil na čisto prvi pogovor o uvedbi računalništva v šole, kjer sta z Virantom zastopala 'praktično' linijo, da je računalnik tehnologija, s katero je treba delati, ne pa o njej teoretizirati. Z Roblekom, Trampužem, Virantom, Zakrajškom, Lesjakom, Volkovo, Hafnerjem in Rajkovičem so v naslednjih letih vodili projekt uvajanja računalnikov v srednje šole, s katerim si je Slovenija ustvarila odlično izhodišče za osvajanje IKT in velik ugled v mednarodnem šolstvu (Lipužič, 2010). Že leta 1973 so slovenske izkušnje z omenjenim projektom predstavili na simpoziju IFAC v Alžiru (Bratko, Rajkovič, Roblek, 1973). Slika 1: Računalnik IBM 1130 Takšen IBM 1130 si je morala mariborska Višja tehniška šola kupiti iz lastnih sredstev, nanj so morali čakati dve leti in 1969. se je okrog njega začel formirati mariborski računalniški krog. Čeprav je ta računalnik legenda, ne najdem njegove fotografije in sem si jo izposodil z Wikipedije. Še težje pa je priti do Darinka Ferjančič Stiglic fotografije računalniškega centra TAM, ki je bil drugo gnezdo je mariborskih računalnikarjev, kjer pa so veljala stroga pravila bila v letih 1974-76 prva ženska na položaju predstojnice vojaške tajnosti, o čemer mi je pripovedoval Božo Kuharič, kakšnega tehniškega tamov štipendist in pripravnik ter kasnejši graditelj Mure, ki je visokošolskega študija v smel vstopiti v sistemski prostor šele po enem letu zaposlitve. Sloveniji. Raziskovala je digitalne signale z Walshevimi in Haarovimi funkcijami in uvajala študente v nove tehnologije z nelinearnimi elektronskimi vezji. Iz časa njenega vodenja VTŠ se spomnim zabavnega dogodka, povezanega s pogostim demonstriranjem nove računalniške tehnologije za strokovnjake iz proizvodnje, bil pa je to tudi čas za 'partijo' nesprejemljivih študentskih demonstracij. In tako je neka skupina obiskovalcev vprašala zavednega receptorja VTŠ, kje v veliki hiši je demonstracija, dobili pa so nedvoumen odgovor: »Dokler sem jaz tukaj, na VTŠ ne bo nobenih demonstracij!« Slika 2: Računski center 700 Franci Pivec Information Society 2021, 6 Oktober 2021, Ljubljana, Slovenia Bruno Stiglic je prišel na VTŠ rekoč v izložbi, ni več duha ne sluha, kar kaže, da v Mariboru ni leta 1961 z ljubljanskega Inštituta propadla le stara industrija. Marn, Kajzer in Pivka (na za komunikacijske sisteme kot fotografijah) so prevzemali tudi druge naloge v razvoju strokovnjak za tranzistorje. Bil je mariborskega računalništva: Marn je vodil koordinacijsko telo za nekakšen 'gospodar' IBM 1130, razvoj računalništva na UM, Pivka je pripravljal zagon ki ga je znal izvirno uporabljati za univerzitetnega računskega centra, Kajzer pa je bil dolgoletni aplikacije na različnih področjih, predsednik Izumovega strokovnega sveta. na Združenju visokošolskih zavodov, predhodniku univerze, pa smo se z njim odlično ujeli pri avtomatski obdelavi podatkov o vpisu, ki jo je takoj 'posvojila' Izobraževalna skupnost Slovenije. Za zgled smo imeli obširen priročnik o informatizaciji virov in dejavnosti kolidžev in univerz, ki ga je izdala National Science Foundation in sem ga nekaj let prej pritovoril iz ZDA zgolj s slutnjo, da gre za perspektivno stvar (Tyrrell, 1967). Stiglica je za nekaj let prevzela Iskra Avtomatika in ga poslala za direktorja v svojo izpostavo Electronics v Santa Clari, njegovi razširjeni razgledi po računalniški industriji pa so bili zelo koristni pri zasnovi novih študijskih smeri in fakultet na tem področju. ZAKLJUČEK Ko smo pripravljali načrt za ustanovitev univerze, smo si že leta Morda bi moral v prikaz vključiti tudi informatike s takratne 1971 zamislili tudi univerzitetni računski center in začeli izdajati kranjske VŠOD (Vladislav Rajkovič, Miroljub Kljajić, Jože bilten ter s tem spodbudili enako potezo v Ljubljani. Seveda sta Gričar, Alenka Hudoklin Božič), ki je delovala v okviru aktivnosti vodila Kac in Stiglic. V načrt smo zapisali, da bo mariborskega Združenja visokošolskih zavodov, vendar sem se bodoča univerza prva kompjuterizirana univerza v Jugoslaviji in v naslovu omejil na mesto Maribor. Sploh pa je namen tega kasnejši rektor Dali Đonlagić je to jemal zelo zares. zapisa, da bi se ponovno lotili zbiranja dokumentacije o zgodovini računalništva pri nas. Dvajset let bo že, kar smo v Na VEKŠ se računalništvo začne s prihodom Ferdinanda Marna okviru Slovenskega društva Informatika organizirali dva in ustanovitvijo katedre za organizacijo in informatiko, a kolokvija pod naslovom 'Računalništvo nima zgolj prihodnosti', posebnost je vzporedno nastajanje in rast Ekonomskega centra ki smo si ga izposodili od akademika Franceta Križaniča, prvega Maribor in njegovega CAOP. slovenskega kibernetika. Tokrat smo se zadržali na čisto prvih Nande Marn je v začetku petdesetih diplomiral na ljubljanski korakih vstopanja IKT v mariborsko in slovensko stvarnost in vsi Visoki tehniški šoli – takrat tehniški študiji niso spadali pod vemo, kako široko in globoko je segel vpliv nove tehnologije v univerzo -- in že leta 1952 prišel v mariborski TAM, kjer mu je naslednjih letih (Pivec, Rajkovič, Jus, 2004). Bolj, ko odlagamo generalni direktor Perhavc zaupal zadeve v zvezi z organizacijo sestavljanje zgodovinskega mozaika, več njegovih kamenčkov vodenja v ogromni firmi. Na pragu zahtevnega projekta vojaških se nepovratno izgublja in manj je jasno, od kod prihajamo, kje vozil je »generalni« Stojan Perhavc na predlog vodje razvojnega smo in kam gremo? inštituta Jožeta Ciglenečkega pritegnil v ekipo Antona Hauca, Štefana Kajzerja, Branka Crnkoviča, Jožeta Baumana, REFERENCE Marjana Pivko in druge in glej, skoraj vsi omenjeni so se v [1] Bratko, I., Rajkovič, V., Roblek, B. (1973) An experiment in secondary sedemdesetih znašli na VEKŠ ali na domala pridružen school computer education. V: M. Cuenod, S. Kahne (ur.) Systems em Approaches to Developing Countries. Algiers: IFAC Ekonomskem centru Maribor. K slednjemu je prišel še Pavel [2] Frković, M., Pivec, F., Schlamberger, N., Grad, J. (2016) A contribution Kristan iz Intertradea, leta 1975 pa je njihov CAOP dobil močan to the history of computing and informatics in West Balkan countries. Uporabna informatika, 24 (4) 191-200 IBM 360 in z njim podpiral informatiko skoraj vseh velikih [3] Grosch, H. (1991) Computer – Bit Slices From a Life. mariborskih firm. ECM, ki je bil na isti lokaciji kot VEKŠ, je http://www.columbia.edu/acis/history/computer.html spočetka [4] Kac, M. (1970) Fortran IV in monitorski sistem za elektronski računalnik šolo razbremenil skrbi za poganjanje lastnega IBM 1130. Višja tehniška šola Maribor računalnika in Vekševa ekipa se je lahko bolj posvetila [5] Kitov, V. (2014) Development and Use of the First Three Soviet aplikativnim vidikom, kot so poslovna informatika, projektni Computers. IT STAR Newsletter, 12 (2) 3-7. [6] Lipužič, B. (2010) Pionirski koraki. Šolski razgledi, 17, str. 3. menedžment, modeli organizacije itd.. Danes o ECM in njegovem računskem centru, ki so si ga ljudje ogledovali tako 701 Slovensko računalništvo skozi pogled dijaka l. 1971 Matjaž Gams† Jozef Stefan Institute Jamova 39, Ljubljana matjaz.gams@ijs.si POVZETEK razkrivanju podmorniških položajev med 2. svetovno vojno [2]. Turing je imenovan tudi »računalniški Einstein« [3], ker je Predstavljena je zgodovina slovenskega računalništva in zasnoval vrsto osnovnih konceptov računalništva kot Turingov informatike skozi oči avtorja, dijaka leta 1971. Sledi opis stroj ali Turingov ustavitveni problem. Turingov sodobnik je bil nadaljnjih dogodkov predvsem skozi slovarje in leksikone Donald Michie, britanski znanstvenik, povezan s prof. Ivanom računalništva, torej računalniško terminologijo. Smisel Bratkom. Turinga ne Bratko ne avtor tega referata nista nikoli prispevka je v tem, da dokumentira dogajanja v času nastajanja osebno srečala, saj je umrl istega leta, ko se je avtor tega računalništva. Ko bomo vse naše zgodbe sestavili skupaj, bo kot prispevka (kasneje »avtor«) rodil. film »Rašomon« režiserja Akire Kurosave – mnogoplastna in Pač pa je Donald Michie pogosto bival v Sloveniji in mnogotera zgodovina opisov skozi osebne spomine, edinstvena predvsem prof. Bratko v Veliki Britaniji, največ na Škotskem. Še in neprimerljiva z zgodovinsko knjigo. danes imamo na Institutu »Jožef Stefan« Turingovo sobo (sobo avtorja) in Michiejevo sobo (nekaj vrat stran od Turingove), kjer KEYWORDS / KLJUČNE BESEDE je Michie pogosto bival, ko je bil na obisku v Sloveniji. Nekajkrat Zgodovina računalništva, poučevanje, začetki računalništva smo šli na skupno večerjo, na skupne konference, na skupne aktivnosti. Avtor je srečal tako Michiejevo ženo kot vnuka. ABSTRACT In this paper the author retrospectively revives computing times in Slovenia starting with 1971 when he studied computing at 2. AVTORJEVA ŠOLSKA LETA Bežigrad high school. Later, he emphasises contacts with other pioneers of computer science in informatica, and in particular Avtor je leta 1971 obiskoval izbirni predmet računalništva, ki describes progress of Slovenian computer terminology. Put ga je predaval prof. Bratko. V paralelki A, kjer so bili tehnično together with papers of other pioneers, a computer history in our in matematično usmerjeni dijaki, je učil prof. Bratko, v drugi country will emerge like the Rashomon movie from Akira paralelki pa prof. Rajkovič. V tistih leti so bili dijaki otročji kot Kurosava. le malokdo in šale oziroma legende o profesorjih so bile stalno na dnevnem redu. Prof. Rajkovič je slovel po tem, da je med KEYWORDS pisanjem s kredo česal kodraste lase z lasmi in posledično je bilo Pioneering times of computing, Slovenia na koncu ure vedno nekaj krede v frizuri. Prof. Bratko pa je »zgodovinsko« zaslovel takrat, ko so dijaki v predal mize nastavili revijo Playboy. Odprl je predal, zastal, malo zardel in 1. UVOD pomigal z brki, nato pa zaprl predal. Malo je premišljal, nato pa Prave enolične resnice tako ali tako ni, vsaj tako pravi princip odprl predal, vzel kredo in ga ponovno zaprl. Ta video bi mnogoterega znanja [1], zato bo opis pionirjev računalništva zagotovo dobil milijon všečkov. začenši z letom 1971 toliko bolj zanimiv. To bo mnogoplastna, A predmet računalništva je bil Indija Koromandija za mnogotera, subjektivna, ponekod tudi bolj spominska in kreativnost. Medtem ko so morali dijaki pri večini predmetov avtobiografska kot eksaktno dokumentirana zgodovina bolj ali manj mehanično ponavljati, kar so profesorji govorili na nastajanja slovenskega računalništva. predavanjih, morda z izjemo fizike in matematike, so Prvi računalnik je verjetno Charles Babbageov mehanski stroj, računalniške naloge omogočale kreiranje množice rešitev, bolj ki je znal izvajati ključne komponente računalnika kot ali manj ustvarjalnih. Če je kdo iznašel kakšno izvirno, je bil ponavljajoče se zanke. Nastal je v začetku 19. stoletja, logično pohvaljen in to je bilo zelo stimulativno. Takrat se je pa je prve programe v pismih Babbageu pisala Ada Augusta programiralo v fortranu oziroma bolje rečeno – pisali smo na Lovelace. Okoli druge svetovne vojne je nastalo več papir. Enkrat pa so bili programi vneseni v pravi računalnik – računalniških naprav, recimo Turingova »Bombe« za IBM 1130. dešifriranje nacistične Enigme, ki je ključno pomagala pri Že v tistih letih smo se srečevali z nekaj mlajšimi kolegi, recimo Robertom Reinhardtom, Markom Martincem, na Permission to make digital or hard copies of part or all of this work for personal or gradbeni fakulteti je bil aktiven prof. Žiga Turk. classroom use is granted without fee provided that copies are not made or distributed Po maturi se je avtor vpisal na Fakulteto za elektrotehniko po 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 težkih debatah, na katero fakulteto naj bi šel. Elektrotehnika je be honored. For all other uses, contact the owner/author(s). bila izbrana iz dveh razlogov: ker je po dveh letih skupnega Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). študija sledila izbira smeri, seveda računalništva; drugi razlog je bil v tem, da je na elektrotehniko šla večina sošolcev. Dostikrat 702 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Gams se nas je večina posedla v isto klop. Med 300 študenti 1. letnika Blue leta 1997 premagal tedaj najboljšega šahista na svetu, jih je v 2. letnih prišlo 150, kar nam je nazorno povedal prof. Garryja Kasparova. Danes bi verjetno rekli, da zaseda drugo Virant. Na računalništvo nas je šlo okoli 20. Ker je bil avtor mesto na lestvici najboljših šahistov vseh časov, medtem ko si je aktiven kot študentski predstavnik, je občasno sedel tudi v raznih prvo mesto priboril Magnus Carlsen. fakultetnih organih. Takrat je bilo nekaj velikih debat. Ena je bila Ko je potekala tekma med Deep Blue in Kasparovom, smo o izbiri računalnika – ali naj bo digitalen ali analogen. komentirali tekme tudi s prof. Michiejem, ki se je takrat mudil v Digitalnega je zagovarjal prof. Virant, analognega prof. Ljubljani. Gyergyek. Debata se je zavlekla in pregrela do točke, ko je prof. Za diplomo je avtor analiziral končnico kralj + trdnjava : kralj Gyergyek izgubil živce, lasje so se mu postavili pokonci, + konj in generiral vse možne pozicije in poteze [4]. To je bila odvihral je iz dvorane, nakar se je čez 2 minuti vrnil očitno prva tovrstna končnica na svetu. Prof. Bratko je dal idejo, počesan in umit. Fakulteta je dobila digitalni računalnik. Pri prof. izvedba je bila na avtorju in več mesecih optimiranja. Gyergyeku sva prav dva računalničarja na njegovem predmetu po treh dneh čakanja pred vrati prišla na vrsto in vprašal naju je del svoje knjige, za katerega so nam rekli, da za računalničarje ne pride v poštev. Seveda sva odletela v nekaj minutah, a prof. 3. NEKAJ DOSEŽKOV IZ Gyergyek je bil vseeno poleg prof. Bremšaka in še nekaterih NADALJEVANJA KARIERE legenda na elektrotehniki. Na prvem računalniku (Cyber) je avtor programiral na Po diplomi je avtor iskal službo ali na fakulteti ali na inštitutu. Institutu »Jožef Stefan« med študijskimi leti. Ker je bil le en Prof. Bratko je imel raziskovalni projekt, kjer je bilo kritje za računalnik za cel inštitut, si prišel nanj tipično okoli 1h ali 2h plačo in raziskovanje. Vodja odseka je bil prof. Anton P. ponoči in nato programiral, dokler te ni zmanjkalo. Bratkov Železnikar, koroška korenina in izredno moder človek. Nasledil kolega in pozneje minister dr. Peter Tancig je imel v sobi kavč in ga je drugi Korošec, dr. Marjan Špegel, ki je kar nekaj časa prej z malo sreče si se lahko malo odpočil, zadremal in nato prebil v Ameriki. Ekstravertiran in aktiven je širil energijo med nadaljeval. Včasih je bila kar gneča, a kavč je bil ozek in več kot sodelavci. Dr. France Dacar je bil izjemen matematik. Govorili dva nista mogla biti na njem. Ostali so se morali zadovoljiti s so, da je dobil zlato kolajno na matematični olimpijadi, nato pa stoli. odšel za eno leto v samostan, da si je ohladil možgane. Ko je Na fakulteti je bila vrsta zanimivih predavanj in profesorjev. nekoč prof. Milan Osredkar, direktor inštituta, preveč Recimo pri prof. Virantu smo imeli Lisp in nekoč je na neposredno zahteval od njega konkretne rezultate in ne več predavanjih podal nalogo zlaganja sorodnih delov drevesa. svobodno raziskovanje, mu je na računalnik poslal odgovor v Obljubil je, da bo tisti, ki reši izpit, oproščen izpita. Avtor ga je obliki – danes bi rekli šaljive figurice. rešil, a je vseeno pisal izpit, nekaj več kot 70%, a kakšnih 10% Prof. Bratka so zanimali predvsem algoritmi za preiskovanje, več kot naslednji. S prof. Vilfanom sta tudi mimo pouka reševala najraje pa jih je testiral na igranju šaha. Z avtorjem sta vrsto let izbrane naloge. Zanimiva predavanja so imeli matematiki, kjer raziskovala patologije in čez vrsto let se je na tem področju so iste predmete obiskovali računalničarji iz 4. letnika in izkazal tudi dr. Mitja Luštrek [5]. Prva analiza in objava avtorja matematiki iz 2. Tako nismo pretirano zaostajali za matematiki, in prof. Bratka [6] pa je bila nadgradnja Bealove študije. Z ampak samo zmerno. Eden najbolj duhovitih ljudi je bil prof. računalniškimi modeli sta pokazala, da je patologija v Suhadolc, ki pa na izpitu ni bil navdušen, da bi imeli več tipov preiskovalnih algoritmih AND/OR tipa pogosto prisotna. neskončnosti: najprej 1, potem 2 in nato neskončno neskončnosti, Poznejše študije so modele nadgradile in so se pokazale tudi na kar bi bila neskončnost drugega reda ter tako dalje. Zanimiv je OR drevesih. Res nenavadno – v kar nekaj razmerah se bil prof. Hodžar, tudi rektor Univerze v Ljubljani, in njegovo preiskovanje v dodatno globino ne splača več. Pravzaprav je tudi numerično računalništvo. Ko je prižgal cigareto, seveda na v življenju tako – če preveč časa preračunavaš življenjske hodnikih fakultete, se je okoli njega trlo asistentov, kdo mu jo bo odločitve, recimo iščeš predvsem službo s čim večjo plačo, boš prižgal. Prof. Divjak je imel zelo specifičen stil, bil je zelo verjetno nesrečen v življenju. V tistih časih pa smo živeli za prijazen in hkrati učinkovit. Ko so se nekoč profesorji na organu raziskovanje in odkrivanje. Ter za neskončno radost kreiranja smeri pogovarjali, da bi veljalo narediti samostojno fakulteto za nečesa čisto novega, kar svet še ni videl ali vedel. računalništvo, je po nekaj debatah rekel, da bo on to speljal, če Avtorjev študij se je končal z doktoratom [7], ki je uvedel mu pomagajo. In so jo res. Diplomirali smo med prvimi študenti princip in paradoks mnogoterega znanja, verjetno največji računalništva, pred nami je bil le letnik ali dva. avtorjev dosežek. Princip pravi, da je najboljša rešitev tista, kjer Že med poukom je avtor sodeloval s prof. Bratkom. Tema so sodeluje več akterjev, ki med sabo niso preveč podobni, a so čim bili razni algoritmi, predvsem pa je prof. Bratka zanimala umetna bolj kvalitetni. Paradoks pravi, da je skladno s principom inteligenca in zlasti šah. Prof. Bratko je še sedaj odličen šahist in univerzalnega Turingovega stroja možno več akterjev (modelov, avtor ga ni uspel nikoli premagati, čeprav je bil kot amater na strojev…) nadomestiti z enim samim. Knjiga »Weak tekmovanju na fakulteti za elektrotehniko z okoli 600 študenti intelligence: The principle of multiple knowledge« [1] je bila tam nekje šesti. Tedaj se je mislilo, da je šah najboljše orodje za dosegljiva preko Amazona, a kakšne posebne tiraže ni dosegla. umetno inteligenco, ker je natanko definiran in ker omogoča V Sloveniji pa je izšlo nekaj knjig, recimo Osnove dobrega preizkušanje raznih algoritmov v odličnem eksperimentalnem programiranja [8], ki je bila prevedena v hrvaški jezik (Slika 1). okolju. Do določene mere je to držalo, a računalniški šah je Prinaša koristne konvencije pri programiranju v jeziku pascal, v napredoval predvsem zaradi Moorovega zakona in hitre rasti katerem je avtor sprogramiral na deset tisoče programskih vrstic. računalniških sposobnosti. Krivulja rasti ratinga računalniškega šaha je konstantno in enakomerno rasla, dokler ni IBMov Deep 703 Slovensko računalništvo skozi pogled dijaka l. 1971 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia BRODNIK, Andrej, DOBRIN, Andrej, DROBNIČ, Matija, GAMS, Matjaž (author, editor), MOHAR, Bojan, PETKOVŠEK, Marko, KODEK, Dušan (editor), VILFAN, Boštjan (editor), RAPOŠA, Kazimir (editor). Računalništvo, (Leksikoni Cankarjeve založbe). Ljubljana: Cankarjeva založba, 1988. 208 str., ilustr. [COBISS.SI-ID 1329154] To je prvi leksikon. GAMS, Matjaž, JAKOPIN, Primož, KANIČ, Ivan, KODEK, Dušan, MOHAR, Bojan, VILFAN, Bojan, SIROVATKA, Goran (editor). Računarski rječnik : englesko-hrvatski hrvatsko- engleski. 1. izd. Zagreb: Naprijed, 1990. 253 str. ISBN 86-361- 0241-3. [COBISS.SI-ID 21344258] Slovarček je bil predelan za hrvaški jezik. Slika 1: Avtorjeva knjiga »Osnove dobrega BRODNIK, Andrej, DOBRIN, Andrej, DROBNIČ, Matija, programiranja« je uvedla v slovenski prostor osnovne GAMS, Matjaž, MOHAR, Bojan, PETKOVŠEK, Marko, koncepte imenovanja spremenljivk, zamikanja teksta RAPOŠA, Kazimir (editor). Računalništvo, (Leksikoni programov itd. Cankarjeve založbe). 2. izd. Ljubljana: Cankarjeva založba, 1991. 208 str., ilustr. ISBN 86-361-0510-2. [COBISS.SI-ID 20156672] S stališča društev je bila pomembna ustanovitev SLAIS, tj. Druga izdaja leksikona. društva slovenske umetne inteligence, kjer sta bila avtor in prof. Bratko med ustanovitelji, avtor je s prof. Janezom Peklenikom PAHOR, David (author, editor), DROBNIČ, Matija, ustanovil SATENO in kasneje z več sodelavci Inženirsko BATAGELJ, Vladimir (author, reviewer), BRATINA, Simon, akademijo Slovenije, z drugimi soavtorji pa društvo za DJURDJIČ, Vladimir, GABRIJELČIČ, Primož (author, kognitivne znanosti DKZ in slovensko podružnico ACM reviewer), GAMS, Matjaž (author, reviewer), KLANČAR, Slovenija (Gams Informatica), kjer je bil prvi tajnik in prof. Matjaž, KLJUČEVŠEK, Rado, KOKLIČ, Jana, MESOJEDEC, Vilfan prvi predsednik. Uroš, OŠTIR, Krištof, POTRČ, Matjaž, ROBIČ, Borut, SEČNIK, Davorin, SIMIČ, Slobodan, TOTH, Jasna. Leksikon računalništva in informatike. Ljubljana: Pasadena, 2002. 786 str. 4. RAČUNALNIŠKO ISBN 961-6065-56-4. [COBISS.SI-ID 117254144] IZRAZOSLOVJE Verjetno zadnja tiskana verzija leksikona ali slovarčka. S pojavom spletnih aktivnosti se je slovarček prenesel na splet Skupaj z nekaj 10 soavorji je avtor oblikoval slovensko (Slika 2). Kasneje se je pojavil še slovar informatike. računalniško izrazoslovje. Poglavitna vloga je bila koordinatorska, editorska. Že prej je prof. Vladimir Batagelj uvedel Wiki slovar, kjer so avtorji lahko vpisovali svoje izraze, a glavni urednik je imel dokaj železno roko in je pogosto uvajal pretirano lepe in izvirne izraze. Avtor je za razliko od Vlada ubral bistveno bolj nežen pristop: za vsako področje je nekdo strokovnjak in zato naj predlaga svoje izraze, dokler se mu drugi ne zoperstavijo. Čeprav so strokovnjaki pogosto močni značaji, se je ta pristop kar obnesel. Skupno je nastalo kakšnih 50.000 tiskanih izvodov slovarjev in leksikonov. GAMS, Matjaž (author, editor), JAKOPIN, Primož, KANIČ, Ivan, KODEK, Dušan, MOHAR, Bojan, VILFAN, Boštjan, DIVJAK, Saša, RAPOŠA, Kazimir (editor). Računalniški slovarček : angleško-slovenski, slovensko-angleški. Ljubljana: Cankarjeva založba, 1985. 226 str. [COBISS.SI-ID 15631617] Ta slovarček je bil objavljen leta 1985 in je bil prvi v seriji. GAMS, Matjaž (author, editor), JAKOPIN, Primož, KANIČ, Ivan, KODEK, Dušan, MOHAR, Bojan, VILFAN, Boštjan, DIVJAK, Saša. Računalniški slovarček : angleško-slovenski, slovensko-angleški. 2. izd. Ljubljana: Cankarjeva založba, 1987. 226 str. ISBN 86-361-0241-3. [COBISS.SI-ID 37909] Prišlo je do nekaj ponatisov slovarčka. Slika 2: Spletna verzija računalniškega slovarčka. 704 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Gams 5. ZAKLJUČEK LITERATURA [1] Matjaž Gams, 2001. Weak intelligence : through the principle and paradox of multiple knowledge, (Advances in computation, vol. 6). Huntington: Zadnjih 50 let je bilo gotovo najbolj razburljivih in Nova Science. nadebudnih v človeški zgodovini. To obdobje so omogočile [2] Andrew Hodges, 2014. Alan Turing: The Enigma. Princeton University Press. računalniške in informacijske tehnologije. [3] Matjaž Gams, 2021. ACM Turing Award for 2020 Honors Alfred Vaino Slučajno je leta 1971 avtor tega prispevka izbral izbirni Aho and Jeffrey David Ullman, Informatica, vol. 45, no. 5, Editorial. predmet računalništva na bežigrajski gimnaziji, kjer ga je učil https://www.informatica.si/index.php/informatica/issue/view/226/showT oc prof. Bratko, nato življenjski mentor. Že tisto prvo leto pa je [4] Matjaž Gams, 1978. Računalniško konstruiranje strategij iger : diplomska odkrilo strast in užitek pri generiranju idej v neki formalni obliki, naloga. Ljubljana. [5] Mitja Luštrek, Matjaž Gams, Ivan Bratko, 2006. Is real-valued minimax obliki računalniškega programa. Nekaj »božanskega« je v pathological?. Artificial intelligence, ISSN 0004-3702, vol. 170, str. 620- kreaciji nove simfonije, slike, a še bolj v snovanju inovativnega 642. programa, ki po možnosti zraven odkriva še nekaj ljudem [6] Ivan Bratko, Matjaž Gams, 1982. Error analysis of the minimax principle. V: CLARKE, M.R.B. (ur.). Advances in computer chess. 3, (Pregamon neznanega, odkriva tančico skrivnosti, pa naj bo to nov algoritem chess series). Oxford [etc.]: Pergamon Press, vol. 3, str. 1-15. za iskanje rešitev v grafih, analiza kovida ali študij dolgoživosti [7] Matjaž Gams, 1988. Principi poenostavljanja v sistemih za avtomatsko učenje : disertacija. Ljubljana. človeške civilizacije. Pri tem je vseeno, ali programirate na [8] Matjaž Gams, Božo Kos (illustrator). Osnove dobrega programiranja : vikendu na mobilnem telefonu ali v službi na najnovejšem stroju. metode, tehnike, principi. Ljubljana: Cankarjeva založba, 1985. In kmalu bo prišla umetna inteligenca, ki bo prinesla novo, nesluteno revolucijo v razvoju človeške civilizacije. Vsi, ki smo sodelovali tedaj ali še bolj mlajši, ki skupaj s seniorji sedaj kujejo bodočnost, imamo neverjetno srečo, da smo izbrali najbolj udarno in zanimivo področje, kar jih je kadar koli bilo. 705 Od prve do enajste šole računalništva Early learnings of computational thinking Tomi Dolenc Arnes Ljubljana Slovenija tomi.dolenc@arnes.si POVZETEK razmišljal o tem, ali bi rad bil astronavt. Zato me je nekaj let pozneje spoznanje, da se bom v 3. letniku srednje šole srečal s Prispevek je, z ozirom na zgodovinski fokus konference, takrat še izbirnim predmetom Računalništvo in učil zastavljen kot “spomini ostarelega programerja”; njegov namen programiranja, navdalo s prijetnim vznemirjenjem. Še zlasti, ker pa je predvsem osvetliti možnosti, ki so se proti koncu nam je, radovednim nadebudnežem, že od prvega letnika zbujal sedemdesetih prejšnjega stoletja ponujale srednješolcem za občudovanje in hkrati frustracije pogled na sošolca Antona spoznavanje tedaj zelo sveže vede. Skozi osebno refleksijo, kaj Verbovška, ki se je po šolskih avlah potikal s polnim naročjem sem se takrat naučil, bi želel iskati tudi navdiha za sedanje čase. gostih in popolnoma nerazumljivih računalniških izpisov (če se prav spomnim, je šlo za “post-mortem dump” v šestnajstiški KLJUČNE BESEDE kodi) in nam prizadevno kazal v tisto zmedo, kaj da mu Pouk računalništva, računalniško mišljenje, reševanje računalnik s tem pove. problemov, algoritem, programski jezik, pascal A zadeve so šle še na bolje. Področje se je tudi na račun entuziazma, ki ga je obdajalo, hitro razvijalo in proti koncu ABSTRACT sedemdesetih let dvajsetega stoletja je v Sloveniji obstajal že kar Given the historical focus of the conference, I try to present, živahen ekosistem, ki je ob hkratnih tehnoloških novostih through “memoirs of an old programmer”, the ways and ponujal obilo priložnosti mladim navdušencem, da osvojijo, pa opportunities that we had, at a secondary school level in the late tudi preizkusijo novo znanje. Naj mi bo torej dovoljeno v 70’s, to learn about programming and computer science, which povezavi z začetki poučevanja računalništva predstaviti tudi to was at the time a very fresh field of knowledge. From reflecting prelomno obdobje, ki morda ne bo dobilo tako jasne obeležitve on my personal learning experience, I aim to draw some kot leto 71’, pa si jo po mojem mnenju zasluži. V prispevku inspiration also for the modern teaching of computational poskušam orisati različne med seboj povezane dele tega thinking. ekosistema, ki je v svojem bistvu vreden posnemanja v kateremkoli času. KEYWORDS Teaching computer science, computational thinking, problem solving, algorithm, programming language, pascal 2 ŠOLA … Težko ocenjujem, kolišen delež je pri tem imelo okolje in ugled takratne Bežigrajske gimnazije, a z učitelji sem imel srečo. Prvi, 1 UVOD ki nam je – pisalo se je šolsko leto 1978/79 – za začetek pojasnil, V času začetkov poučevanja računalništva na Slovenskem sem kaj računalnik je in kako deluje, je bil Vlado Rajkovič, tudi še obiskoval osnovno šolo in o tem seveda nisem vedel nič. Iz soavtor takratnega (prvega) srednješolskega učbenika Uvod v tega časa se spominjam edino (izobraževalne?) oddaje na računalništvo [1]. televiziji, ki je govorila o računalnikih in programerjih kot tistih ljudeh, ki računalnike polnijo s podatki in jim nekako “povedo”, kaj naj delajo. Predstavljeni so bili v belih haljah v nekoliko znanstveno-fantastičnem okolju in so v moji tedanji predstavi zadobili nekakšen mitski status nečesa sicer zelo zanimivega, a praktično izven mojega dosega – tako, kot če bi na primer ∗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 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 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). Slika 1: Prvi učbenik za računalništvo v srednji šoli 706 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia T. Dolenc 2.1 Razumevanje tehnologije sam to izkušnjo doživljal v nekoliko privilegiranih okoliščinah: šlo je za dijake s smeri intenzivne matematike na “prestižni” Razumevanje samih osnov zgradbe in delovanja računalnikov – naravoslovni gimnaziji, poleg tega smo si lahko premet izbrali, podatki v spominskih celicah, zaporedje dogodkov pri torej med nami ni bilo nikogar, ki ga vsebina ne bi zanimala – procesiranju ukazov – je učinkovito demitologiziralo naš odnos nekaj, o čemer lahko običajen učitelj oz. učiteljica matematike do stroja, hkrati pa pomagalo k jasnejši predstavi, kaj lahko s tem ali pa slovenščine na splošno le sanja… strojem, s pomočjo programiranja, naredimo - pa tudi, česa ne A poglavitno za doseganje poglobljenih učinkov poučevanja, kot moremo. Kot pojasnjujejo tudi avtorji preglednega članka o jih opisujem v prejšnjem razdelku, je bilo nadgrajevanje solidnih razvoju predmeta računalništvo [2], je bil pouk v teh letih osnov, ki smo jih dobili pri predmetu računalništvo, z pretežno teoretičen, s poudarkom na algoritmih in programskih usmerjenim reševanjem problemov pri računalniškem krožku. jezikih, praktične vaje na računalniških centrih pa so zahtevale Tega sta v omenjenem času na Gimnaziji Bežigrad vodila Mark precej potrpežljivosti – najprej zaradi zamudnega luknjanja Martinec in Robert Reinhardt, ki sta za zapis programov kartic, ki smo jih nato zaupali operaterju – svečeniku (v beli halji, promovirala takrat še precej mlad programski jezik pascal. ali pač le v kavbojkah?) – ta pa jih je odnesel v nam nedostopno Pascal se je zaradi svojih struktur in sintakse, ki se je nagibala k sobo s terminalom do računalnika, ki se je po vsem sodeč nahajal “človeku prijaznemu” zapisu kode, izkazal za zelo uporaben v neki drugi dimenziji. Po daljšem in nestrpnem čakanju so se “šolski jezik” in je tedaj hitro prodiral tudi v redni pouk vrata odprla in svečenik nam je predal računalnikov orakelj, ki je programiranja na vseh stopnjah. Krožek je ponujal bolj ponavadi rekel, da smo pozabili ločilo in da zato program ne poglobljeno spoznavanje podatkovnih struktur ter tehnike deluje. Po dveh tovrstnih seansah je ponavadi že potekel skopo programiranja, a z močnejšim poudarkom na razumevanju in odmerjeni čas, ki nam je pripadal po razporedu vključenih šol. izgradnji postopkov, pri samem kodiranju pa smo se učili tudi Kakor se že ta izkušnja bere anegdotično, pa nam je dajala pravil “dobrega” in elegantnega programiranja, pri čemer je treba neposredno prvo lekcijo: da je stroj v osnovi “neumen” in da “eleganco” razumeti najprej v fukciji učinkovitosti programa, moramo biti zato toliko bolj pazljivi mi, ko mu naročamo, kaj naj šele potem v sami estetiki, katere namen je bila predvem opravi. Klub preprostosti takratnih orodij in računalnikov je ta berljivost kode. osnovna lekcija aktualna tudi po desetletjih razvoja in v času, ko Krožek je tudi spodbujal k udeležbi na računalniških so komunikacijske tehnologije, umetna inteligenca in strojno tekmovanjih, ki so bila takrat v svojih začetkih (tu moram učenje na ravni, ki omogoča legitimno debato o prihajajoči popraviti navedbo v [2] – republiška tekmovanja za srednješolce avtonomnosti strojev. so se začela že leta 1977), pomenila pa so odlično spodbudo tekmovalni komisiji za sestavljanje inovativnih in duhovitih 2.2 Reševanje problemov nalog, ki so utelešale in utrjevale vsa zgoraj našteta načela Ključno dodano vrednost ostalim predmetom pa je pouk reševanja problemov. Obenem so mladim tekmovalcem ponudila računalništva – vsaj v mojem spominu – prispeval z učenjem prvi širši stik s skupnostjo, ki se je na področju računalništva reševanja razmeroma vsakdanjih problemov skozi razumevanje medsebojno oplajala z izkušnjami, vključevala pa je vse od postopkov. Tudi nekateri drugi predmeti – vsaj matematika in karizmatičnih vrhov, kakršen je bil Anton P. Železnikar, do zelo fizika, pa verjetno delam še kateremu krivico z ne-omembo – so mladih zagnancev, ki so tudi nas, še odraščajoče, poskušali nas učili analitičnega in strukturiranega pristopa k reševanju pritegniti v svoj krog. problemov; vendar je bil prav zaradi omejitev, ki jih postavlja “neumni stroj” v svojem razumevanju sveta oz. konteksta – tudi ta okvir zlahka apliciramo na današnje precej bolj komplicirane 3 … IN MOSTOVI sisteme – ključni poudarek prav na razvoju sposobnosti Že v uvodu je nakazano, da je bilo obdobje 1976-1980, v katerem razumevanja in razčlenjevanja reševanja posameznega problema sem obiskoval srednjo šolo, zelo živahno in je poleg omenjenega na postopke, do nivoja, ki ga lahko “razume” oz. izvede celo tako predmeta računalništvo ponujalo vedno več priložnosti, da si preprost avtomat. mladi nadebudneži (in tudi nadebudnice, že takrat so tudi dekleta A hkrati je prišlo tudi spoznanje, da z obvladovanjem preprostih odnašala nagrade na tekmovanjih v programiranju!) dodatno opravil, ki jih potem lahko odmislimo in prepustimo v obdelavo razširimo obzorja, pa tudi preizkusimo svoje znanje v praksi. Če stroju, lahko postopoma gradimo zelo kompleksne postopke in je bil v prvem letniku kolega Verbovšek eksota, ker je imel sisteme. Skupaj je ta nauk predstavljal kar dobro osnovo tega, kar dostop do svetišča IBM na FMF, smo na koncu šolanja že družno danes imenujemo “računalniško mišljenje”. tolkli po tipkovnicah računalniških terminalov, ki so bili vsaj za Šele v drugem delu učne snovi smo se srečali s konkretnim nekaj časa samo naši… programskim jezikom; takrat je bil to še FORTRAN, jezik, ki je bil primarno namenjen reševanju računskih problemov, manj 3.1 IJS idealen pa morda za osnovno učenje algoritmov. Pri tem je bila razmeroma pomembna lekcija tudi ta, da programski jezik, kot Močan del te živahne skupnosti oz. ekosistema za gojenje novih dejansko orodje upravljanja z računalnikom, predstavlja le formo računalniških znanj je bil na Inštitutu Jožef Stefan, predvsem v izvršitve in je v tem smislu podrejen algoritmu – ne pa morda takratnem odseku za računalništvo in informatiko. Naši učitelji obratno. so nas kmalu povabili tudi na ogled tamkajšnjega računalniškega centra, kakor bi lahko rekli majhni sobici z dvema računalnikoma 2.3 Krožek in tekmovanja za navdušence PDP 11/10 in PDP 11/34 (spominski disk, ki je takrat popolnoma ustrezal svojemu imenu in je “servisiral” celoten računalniški Vse zgoraj našteto se zdi morda kar ambiciozno za izbirni odsek inštituta, je po mojem spominu hranil neverjetnih 10 Mb predmet z razmeroma malo urami. Pošteno je spomniti, da sem 707 Od prve do enajste šole računalništva Information Society 2021, 4–8 October 2020, Ljubljana, Slovenia podatkov). Za vedno se mi je vtisnil v spomin občutek, ko smo 4 ZAKLJUČEK lahko lastnoročno, neposredno na prednji plošči samega Zaključek teh refleksij se nakazuje že v uvodu. Po prvih začetkih računalnika, vtipkali osmiško kodo spominske celice, kjer je poučevanja računalništva v prvi polovici sedemdesetih se je že v računalnik začel prebirati navodila za lastno prebujenje. Počutili nekaj letih razvil živahen ekosistem znanja, ki so ga poganjali smo se kot dajalci življenja; odtistihmal razumem, zakaj predvsem entuziastični posamezniki. Poudaril bi rad, da so nas sistemski inženirji gledajo na svet nekoliko zviška. vsi ti ljudje, ki so bili izjemno odprti in pristopni, predvsem Na IJS smo potem lahko šli opravljati tudi počitniško prakso, kjer poskušali naučiti misliti. Četudi je sodobno razvojno smo programirali v STRUCTRAN-u, programskem jeziku oz. programiranje precej na drugačni ravni kot “uredi N števil v orodju, katerega namen je bil v osnovi uvajati pravila dobrega tabeli”, pa še vedno velja, da so si programski jeziki v osnovi programiranja v delo z jezikom FORTRAN, pa tudi olajšati delo podobni, pa tudi temeljne zapovedi “lepega in dobrega” programerju oz. približati kodiranje človeškemu razmišljanju. programiranja še vedno veljajo v časih, ko daleč nad spodnjimi Zame pa je že tisti prvi pogled na “računalniški center” in “kul nivoji procesov v računalniku, v najbolj trendovskem razvojnem modele”, ki so se sprehajali skozenj, zapečatil smer mojega okolju “zgolj” izbiramo in sestavljamo iz bogatega nabora orodij študija in kariere (#tudijazbitukajdelal). v knjižnicah, za katere ne moremo popolnoma vedeti, do katere mere lahko njihovo delovanje predvidimo. 3.2 Sredin seminar Če pa stopimo vstran od programiranja – tudi sam nisem Po svoje še nenavadnejši je bil vstop v zelo raznoliko skupino programer – zlahka ugotovimo, da je “algoritmični” ali ljudi, ki se je vsako sredo zbirala v okvirju kultnega sredinega računalniški pogled na reševanje problemov zelo koristno orodje seminarja za numerično in računalniško matematiko, ki prav v različnih vedah ali življenjskih situacijah; poznavanje vsaj letos tudi praznuje 50-letnico. V seminarju so dobile priložnost osnovnih konceptov delovanja algoritmov in splošno za predstavitev zelo različne vznemirljive teme, od precej informacijske tehnologije pa nedvomno še precej bolj kompleksnih matematičnih, pa do elementarnih (in poglobljenih) pomemben del splošne izobrazbe kot pred pedtesetimi leti. predstavitev urejevalnikov besedil ali operacijskih sistemov, pa Zapomniti si velja tudi, da je šola dobra, enajsta šola (pod tudi Rubikove kocke (in seveda algoritma za njeno reševanje). mostom) kot sinonim učenja ob življenjskh situacijah pa, če ne Vodil ga je legendarni lik slovenskega računalniškega panteona, še boljša, vsaj enako potrebna. Zato želim izpostaviti, da je v času Egon Zakrajšek, tam pa sem srečal tudi svoje poznejše profesorje mojega šolanja bilo poučevanje računalništva vpeto v že takrat takrat mlajše matematične generacije, ki je svoje raziskovalno dobro delujoče okolje, ki nam je nudilo prav toliko znanja o delo tesno prepletla z računalništvom: Vladimirja Batagelja, računalništvu, kot smo si ga želeli, najbolj radovedne med nami Tomaža Pisanskega, Bojana Moharja, Marka Petkovška… Vlado pa kar hitro posrkalo do te mere, da smo v dveh letih v njem že je uspel štafeto seminarja ohraniti do današnjega dne [4]. Veliko začeli delovati kot njegovi promotorji; tako sem se tudi sam že nam je pomenilo, da so samoumevno medse sprejeli tudi čez nekaj let znašel v prijetni družbi evangelistov, ki je zgoraj radovedne “smrkavce”, kakršen sem bil takrat sam. Ta izkušnja opisana načela poskušala razširjati tudi s knjižico nalog, ki smo pa mi je tudi zelo razširila obzorja računalništva in pokazala jo poimenovali kar “enajsta šola računalništva”. A to je že druga prepletenost te vede z ostalimi. zgodba. 3.3 Iskra Delta Nepričakovana dodatna priložnost za radovedne srednješolce se je ponudila, ko smo – zdi se mi, da leta 1979 – kot ponavadi poskušali vtakniti svoje prste v vsak računalnik na takrat izjemno popularnem sejmu sodobne elektronike (zlasti eden od sošolcev je imel izjemno intuicijo, da že z nekaj pritiski na tipke povzroči kak zastoj delovanja). Na razstavnem prostoru Iskre Delta nas je prijazno ogovoril Branko Lozar, ki je takrat skrbel za izobraževanje. Že po nekaj besedah smo bili domenjeni, da smo s skupino sošolcev prihajali v izobraževalni center Iskre Delta, kjer smo se spoznavali z računalniki Digital Equipment Corporation, ki so bili še dolga leta potem stalnica na univerzah inštitutih, pa tudi v podjetjih. Delta je takrat že proizvajala prve Slika 2: Poklon enajsti šoli kot metodi učenja. Tudi v slovenske terminale KOPA in med poletjem smo tisti, ki smo bili angleščini. pripravljeni nekaj počitnic zamenjati za čemenje v sicer svetli “kleti” pred zasloni, dobili povsem svojo učilnico z lastnimi ZAHVALA terminali, kjer smo se lahko z računalniki “igrali” do Zahvalil bi se rad vsem izjemnim posameznikom, ki sem jih onemoglosti. Ne, ne igric. Edina usmeritev podjetja je bila, naštel v besedilu, in tudi tistim, ki sem jih zaradi omejitev “Sprogramirajte kaj zanimivega. Karkoli.” Lozar je imel izpustil, ker so nam znali kazati pot. nalezljivo veselje do dela z mladimi (klicali smo ga “striček Branko”) ter prepričanje, da je najbolje pustiti kreativnosti prosto REFERENCES pot – bo že kaj koristnega iz tega. Prepričanje, ki pod pritiski [1] Bratko Ivan, Vladislav Rajkovič: Uvod v računalništvo. DZS, Ljubljana, kapitala danes umira tudi v najresnejših raziskovalnih inštitutih. 1978. [2] Alenka Krapež, Vladislav Rajkovič, Vladimir Batagelj, Rado Wechtersbach: Razvoj predmeta računalništvo in informatika v osnovni 708 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia T. Dolenc in srednji šoli, DSI 2001. [4] http://vlado.fmf.uni-lj.si/sreda/ (https://www.drustvo-informatika.si/dogodki/dsi-2001/). [3] Vitek Andrej, Tvrdy Iztok, Reinhardt Robert, Mohar Bojan, Martinec Mark, Dolenc Tomi, Batagelj Vladimir: Problems in programming / Experience through practice. Wiley, 1991. 709 50 let računalništva v slovenskih srednjih šolah – pogled dijakinje in kasneje učiteljice ter ravnateljice na Gimnaziji Vič 50 years of teaching computer science in Slovenian secondary schools – experience of a student and later a teacher and principal of Gimnazija Vič Saša Divjak Alenka Krapež FirstName Surname Department Name Gimnazija Vič Department Name Institution/University Name alenka@gimvic.org Institution/University Name City State Country City State Country email@email.com email@email.com POVZETEK V prispevku predstavim svoje izkušnje in pogled na 2 GIMNAZIJA VIČ PRED USMERJENIM poučevajne računalništva v srednjih šolah IZOBRAŽEVANJEM . Pri tem izhajam iz svojih dijaških dni na Gimnaziji Vič, ki V predmetniku gimnazije v osemdesetih letih 20. stoletja so bile segajo v osemdeseta leta prejšnjega stoletja, nato pa tudi ure pouka, ki jih je šola razporejala sama. To so bila tako podelim izkušnje, ki sem jih na tej isti šoli imenovana "praktična znanja". Na Gimnaziji Vič smo tako v pridobila mojem "intenzivnem razredu" imeli v prvem letniku opisno kot učiteljica v usmerjenem izobraževanju in na splošni gimnaziji geometrijo, v drugem letniku (šol. leto 1979/1980) pa ter zadnja leta kot ravnateljica. računalništvo. Takrat so računalništvo poučevali profesorji in KLJUČNE BESEDE strokovnjaki iz različnih fakultet, inštitutov in podjetij. Pri pouku računalništva smo spoznali zgradbo računalnika, risali srednja šola, poučevanje računalništva in informatike diagrame potekov in jih potem zapisali v Fortranu – in vse to "na ABSTRACT tablo". Najbolj mi je ostala v spominu ena od praktičnih nalog – vsak dijak je dobil nek problem, ki ga je moral rešiti s pomočjo The paper presents my experiences and views on teaching programa. Moj je bil, da izračunam, koliko zrn pšenice se nabere, Computer Science and Informatics in secondary schools. I lean če na prvo šahovsko polje postavim eno zrno, na vsako naslednje on my own student days at Gimnazija Vič, which date back to pa enkrat toliko zrn kot na prejšnje. Programe smo napisali na the 1980s, and then I share the experience I gained at this same roko in potem odšli na računalniški center, ki je bil takrat na school as a teacher in vocational and general education Vegovi ulici v Ljubljani. Sošolka je program pretipkala na programmes, and in recent years as a principal. luknjane kartice, učitelj jih je odnesel v čitalnik … in jih potem KEYWORDS prinesel nazaj, ker … moj program ni delal … napačno sem secondary school, teaching Computer Science and Informatics namreč definirala podatkovni tip. "Integer" je bil celo za šahovnico 3x3 polj premalo … To je edina naloga iz nabora vseh nalog pri vseh predmetih iz srednje šole, ki sem si jo zapomnila 1 UVOD … Kartice s programom sem dolgo hranila, še svojim dijakom sem jih kazala … Čudno, nihče od sošolcev se v tistih časih ni 50 let poučevanja računalništva v srednjih šolah je častitljiv pritoževal, da je programiranje pretežko. jubilej. Zlasti v luči "starosti" te vede. Slovenski pionirji na področju računalništva so vizionarsko in entuziastično orali ledino. S ponosom lahko rečemo, da so v začetnem obdobju tudi 3 USMERJENO IZOBRAŽEVANJE v mednarodnih merilih predstavljali zgleden primer. V pričujočem prispevku predstavljam svoje videnje pouka Že v času mojega gimnazijskega izobraževanja se je z reformo računalništva skozi izkušnje dijakinje in učiteljice od zgodnjih srednjega šolstva uvedlo usmerjeno izobraževanje (l. 1981) in osemdesetih let prejšnjega stoletja do danes. tako so splošne srednje šole dobile strokovne usmeritve. Viška gimnazija je postala srednja šola za računalništvo. To je bila prva srednja računalniška šola. Vem, da je bilo za ravnatelja najtežje poiskati učitelje strokovnih predmetov. Pionir med učitelji računalniških predmetov je bil Franc Klopčič, sicer pa so strokovne predmete učili absolventi in študenti računalništva, pa tudi asistenti s takratne ljubljanske Fakultete za elektrotehniko in računalništvo. Enako težko je bilo z učno opremo. Pri tem si je 710 Information Society 2021, 6 October 2021, Ljubljana, Slovenia Alenka Krapež šola veliko pomagala sama. Nabavili so ID 80, opremili učilnico načrt za predmet računalništvo in informatika. Še prej pa z monitorji in kupili nekaj takrat popularnih Spectrumov. Šola je izobraziti izobraževalce, saj ni šlo več za eksperimentalne šole prosila za pomoč tudi različna podjetja; pomagal je IJS, ampak za vse srednje šole, ki so se jim že pridruževale tudi Mladinska knjiga, tudi Iskra Delta. Stiska je bila tako z učbeniki osnovne šole. kot tudi z učnimi gradivi, ki jih preprosto ni bilo. Pomagali smo Pred Zavodom za šolstvo je bil velik izziv. En od prvih korakov si s skriptami in z učbeniki s fakultete ter s tujimi učbeniki. Zavoda je bil storjen z vzpostavitvijo skupine "Učitelji Ko je ravnatelj po naključju izvedel, da sem zaključila študij inštruktorji", ki se je izobraževala na Inštitutu Jozef Stefan. To elektrotehnike, me je preprosto povabil, naj pridem učit so bili izbrani učitelji matematike in računalništva na srednjih strokovne predmete s področja strojne opreme. Vabilo sem z šolah. V šolah, za katere so bili zadolženi, so izvajali tečaje osnov veseljem sprejela, saj me je delo v razredu zanimalo. Učne načrte računalništva. Skupina je delovala sedem let, nasledil pa jo je usmerjenega izobraževanja so leta 1989 ponovno prenovili, tako projekt Ro – računalniško opismenjevanje, ki je nadaljeval s da sem za natanko eno leto še "ujela" stari program s predmetom širjenjem znanj učiteljem vseh predmetov. Vzporedno s tem računalniški sistemi v 4. letniku, dijake v prenovljenem projektom je potekalo v organizacij Zavoda za šolstvo tudi veliko programu pa sem začela poučevati predmet aparaturna oprema. drugih projektov, ki naj bi v šole smiselno umestili znanje in Takrat je šola že razpolagala z učilnico Partnerjev z operacijskim uporabo IKT. Marsikatera dobra praksa je ostala, žal pa sistemom CP/M in tudi z učilnico računalnikov PC 286, ki so bili sistemskega pristopa k poučevanju temeljnih znanj s področja povezani v računalniško omrežje Novell ... računalništva še vedno ni … Razvoj samega predmeta na gimnaziji in s tem poučevanja temeljnih znanj s področja računalništva pa se je pospešil šele, 4 PO USMERJENEM IZOBRAŽEVANJU ko je predmet, ki se je za ta namen moral preimenovati v Nova reforma je leta 1990 vrnila gimnazije, srednje tehnične šole informatiko, postal maturitetni. To se je zgodilo šele leta 2005, med katerimi so nekatere prevzele tudi področje računalništva in maturo iz informatike pa so dijaki lahko izbrali šele na maturi informatike s prenovljenimi učnimi načrti. Potreba časa je v 2007. Velik zaostanek (od leta 1990 do 2005) se počasi srednji šoli vzpostavila obvezni splošno izobraževalni predmet zmanjšuje, še vedno pa ostaja to predmet, ki je v vsej vertikali računalništvo in informatika. Obvezen je bil samo v 1. letniku, v obvezen samo v 1. letniku gimnazije in nekaterih srednjih šol, obsegu 2 uri pouka na teden, kot izbiren pa je bil na voljo tudi v sicer pa ima status izbirnega predmeta. višjih letnikih. Vsi obvezni gimnazijski predmeti, razen športne vzgoje, glasbe in predmeta računalništvo in informatika, so 5 ZAKLJUČEK postali maturitetni predmeti in praviloma so ti zasedli t. i. izbirne ure. To je eden od ključnih razlogov, da se je razvoj predmeta Ko gledam nazaj – kot dijakinja, učiteljica računalništva, računalništvo in informatika upočasnil, saj je v večini šol obtičal učiteljica informatike, mentorica dijakom pri raziskovalnih v prvem letniku in prevzel osnovno opismenjevanje. nalogah in krožku, pa tudi kot učiteljica inštruktorica in vodja Sistematičnega računalniškega opismenjevanja v osnovi šoli študijske skupine za računalništvo in informatiko, sedaj pa kot namreč ni bilo, potreba po računalniških znanjih pa je postajala ravnateljica Gimnazije Vič – se mi milo stori ob misli, koliko je čedalje bolj očitna. bilo vloženega napora … in zaigra srce, ko vidim naše nekdanje Gimnazija Vič je bila ena redkih gimnazij, ki je kljub temu, da dijake, ki uspešno razvijajo in širijo računalniška znanja na predmet ni bil maturiteten vsa leta poučevala informatiko tudi v najrazličnejših področjih računalništva doma in v tujini. Svetlo 2. letniku, v okviru izbirnih ur. Za dijake, ki so želeli več in bolj bodočnost na tem področju zagotavlja tudi skupnost učiteljev poglobljena znanja pa smo vodili računalniške krožke … računalništva, ki jo strokovno vodi dr. Andrej Brodnik. V tem času se je nekako zameglilo, kakšno vlogo naj ima Samo še sistemski pristop manjka ... računalnik oziroma informacijsko-komunikacijska tehnologija (IKT) v šoli, kaj je naloga šole in kaj potrebuje šola kot institucija REFERENCE za svoje delovanje. Pomešala so se področja vloge računalnika pri drugih predmetih, uporabe računalnika za vodenje procesov, [1] Zbornik 50 let Gimnazije Vič, Gimnazija Vič 1999. [2] Gimnazija Vič 1929-2019, Gimnazija Vič, 2019. ki se odvijajo v šoli, in poučevanja temeljnih računalniških znanj. [3] Alenka Krapež, Vladislav Rajkovič, Vladimir Batagelj, Rado Vzporedno s tem se je odpirala kopica specifičnih nalog za vsako Wechtersbach: Razvoj predmeta računalništvo in informatika v osnovni in srednji šoli, DSI 2001. od omenjenih področij uporabe informacijsko-komunikacijske (https://www.drustvo-informatika.si/dogodki/dsi-2001/). tehnologije v šoli. Šole je bilo potrebno ustrezno opremiti, [4] Zapis Mirjane Kregar. [5] Lastna dokumentacija. didaktika predmetov je terjala posodobitev, učitelje je bilo potrebno ustrezno izobraziti, pripraviti je bilo potrebno učni 711 Moje računalniško izobraževanje My computer science education Franc Solina franc.solina@f ri.uni- lj.si Fakulteta za računalništvo in informatiko Univerza v Ljubljani 1000 Ljubljana, Slovenia POVZETEK — tisti, ki je učil naše “angleže”, to je drugo polovico našega ra- zreda — trdil, da bo Slovenija v prihodnosti potrebovala največ tri V članku podajam kronološki pregled mojega izobraževanja na do štiri računalnike in da je učenje programiranja potemtakem področju računalništva, od izbirnega predmeta na gimnaziji v proč vržen čas. Mene je kljub temu računalništvo tako pritegnilo, zgodnjih 1970-tih letih, preko doktorskega študija v ZDA in ka- da sem se po maturi leta 1974, sicer po nekaj premišljanja, odlo- snejših aktivnostih kot univerzitetni profesor. čil za vpis na Fakulteto za elektrotehniko. Kompromis pa je bil KLJUČNE BESEDE vzporedni vpis na študij Filozofije na Filozofski fakulteti, saj so me zanimala vprašanja, ki bi jih danes lahko bolje opredelili kot Gimnazija Bežigrad, Fakulteta za elektrotehniko, doktorski študij, kognitivno znanost. Univerza Pensilvanije, Fakulteta za računalništvo in informatiko ABSTRACT 1.2 Fakulteta za elektrotehniko Univerza je seveda pomenila velik preskok od dotedanjega šola- The article gives a cronological overview of my education in nja, čeprav na FE manj kot na FF. Na srečo nas je z gimnazije in z computer science, ranging from an elective course in high school intenzivne matematike šlo kar nekaj sošolcev. Omenim naj Saša in the early 1970s up to doctoral studies in US and later activities Tomažiča, pa Andreja Levstka, ki sta kasneje ostala na fakulteti. as an university professor. Spomnim se prof. dr. Keršiča (Osnove elektrotehnike), ki je na KEYWORDS začetku predavanj pokazal na desno polovico Predavalnice 1 in rekel, “vi boste prišli naprej v 2. letnik, vi na levi pa ne!” Na Bežigrad grammar school, Faculty of electrical engineering, doc- srečo sem se usedel na pravo stran predavalnice ,. Za številne toral studies, University of Pennsylvania, Faculty of computer profesorje smo prevzeli ali pa izumili nove nadimke. Prof. dr. and information science GAbrielu TOmšiču smo nadeli vzdevek GATO, saj se je s svojo drobno postavo kot maček sukal pred tablo. Z dobro gimnazijsko 1 IZOBRAŽEVALNE INSTITUCIJE naravoslovno osnovo sem sicer prva dva letnika na FE zlahka 1.1 Gimnazija Bežigrad zaključil. V 1. letniku sem tudi dobil svoj prvi elektronski kalkula- tor Texas Instruments. Takrat sem lahko tudi dokaj redno opravil Po osnovni šoli dr. Vita Kraigherja sem se brez veliko premišljanja vse študijske obveznosti na FF. Študij filozofije sem opustil šele vpisal na mojemu domu najbližjo gimnazijo Bežigrad. Ker me je v četrtem letniku, saj takratni študijski program ni bil po mo- matematika vedno veselila, sem se odločil za razred z intenzivno jem okusu, študij elektrotehnike pa je tudi zahteval vedno več matematiko. Tisto leto je bilo za intenzivno matematiko veliko časa. Nisem želel niti opustiti mojih prostočasnih dejavnosti, to zanimanja in je gimnazija sestavila kar dva razreda z intenzivno je učenja smučanja in kasneje še potapljanja. matematiko. V našem razredu, paralelki 𝑐 , nas je bila polovica z intenzivno matematiko, polovica pa z intenzivno angleščino. Ma- tematiko nas je učil slavni Ivan Štalec. V tretjem letniku (1972/73) smo imeli možnost izbrati dodatni predmet Računalništvo. Tisto leto so se trije učitelji računalništva med seboj dokaj pogosto izmenjavali oziroma nadomeščali. Tako sem spoznal poleg prof. Rajkoviča tudi prof. Bratka in prof. Lajovica. V okviru predmeta smo tudi “obiskali” računalnik IBM 1130 na FE. O računalništvu do takrat nisem vedel kaj dosti, še največ iz knjig o znanstveni fantastiki, ki sem jih redno prebiral. Isaac Asimov je bil eden od zgodnjih vplivov in veliko pozneje sem ga med mojim doktorskim študijem v ZDA tudi osebno srečal in Slika 1: Smer Avtomatika, 4. letnik, šolsko leto 1977/78. V dobil njegovo posvetilo v knjigo, ki jo je takrat izdal [25]. akademskih in znanstvenih krogih so poleg avtorja iz te Pouk računalništva pa ni bil med takratnimi učitelji univer- generacije ostali še Jurij Šilc, Bojan Nemec in Jadran Le- zalno prijazno sprejet. Spomnim se, da je celo učitelj matematike narčič, vsi na IJS. Permission to make digital or hard copies of part or all of this work for personal Po drugem letniku, pa se nisem odločil za smer Računalništvo or classroom use is granted without fee provided that copies are not made or ampak raje za Avtomatiko, sisteme in kibernetiko (Slika 1). Avto- 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 matika je bila v tistem času bolj uveljavljena smer, delo s signali work must be honored. For all other uses, contact the owner /author(s). so me tudi bolj zanimali kot klasična umetna inteligenca. Morda Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia me je podzavestno premamila tudi meni čarobna beseda kiberne- © 2021 Copyright held by the owner/author(s). tika, ki sem jo poznal še iz knjig Asimova? Tako sem se znašel v 712 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Franc Solina smo obdelovali razne oceanografske podatke Jadranskega morja, ki jih je inštitut sam zbiral s svojo oceanografsko ladjo Andrija Mohorovičić, najvišjo stopnjo zaupnosti pa so takrat imeli podatki o deviacijah gravitacijskega pospeška 𝑔, kar je bilo pomembno za vodenje raketnih izstrelkov. Sicer pa so bili takrat komerci- alno najpomembnejši pomorski navigacijski zemljevidi, ki so jih tiskali v tiskarni inštituta. Prvič v življenju sem imel na voljo skoraj neskončno računalniškega časa, tako da sem programiral predvsem stvari, ki so me zanimale, med drugim tudi Conwayevo igro življenja. 1.4 Pensilvanska univerza Za Fulbrightovo štipendijo sem kandidiral že takoj po diplomi, vendar je moja kandidatura uspela šele po zaključenem magistr- skem študiju. Dobil sem Fulbrightovo potovalno štipendijo [8] Slika 2: Skupina, ki se je ukvarjala z računalniško analizo in štipendijo sklada IREX [13], obenem pa še mesto gostujočega signalov EKG: z desne prof. dr. Ludvik Gyergyek, dr. Mar- raziskovalca na Pensilvanski univerzi [31]. Moja gostiteljica in jan Vezjak, prof. dr. Krunoslav Turkulin in medicinski teh- kasnejša mentorica je bila prof. dr. Ruzena Bajcsy, ki je na Od- nik med posvetom v Krapinskih toplicah okoli leta 1980. delku za računalništvo in informatiko (CIS) vodila laboratorij Foto: Franc Solina. GRASP (General Robotics, Automation, Sensing & Perception Lab) [9]. University of Pennsylvania, ki je zasebna univerza v laboratoriju prof. dr. Ludvika Gyergyeka, kjer sem naredil tako Philadelphiji in članica Ivy Leage, je v svetu računalništva znana diplomo [23] kot znanstveni magisterij [24], takrat zaposlen že predvsem kot rojstni kraj računalnika ENIAC [6]. Takorekoč v kot stažist oz. mladi raziskovalec. Moj delovni mentor je bil dr. predsobi našega laboratorija in moje pisarne je takrat še vedno Marjan Vezjak, delal pa sem na analizi signalov EKG (Slika 2). stalo nekaj kosov (omar) originalnega ENIACa (Slika 3). Takrat so bili člani laboratorija še Nikola Pavešić, France Mihelič, Franjo Pernuš, Stane Kovačič, Andrej Kuščer, Bojan Grošelj in Franc Jager, ki se še danes ukvarja z analizo EKG na FRI. Programiral sem v jeziku C na računalniku PDP-11/34. Cela katedra si je delila ta računalnik. Takrat še ni bilo osebnih raču- nalnikov. Zato so za mlajše člane kolektiva ostale noči kot edini možni čas za delo na računalniku. Programirali smo tako, da smo programe najprej napisali na papir in jih nato pretipkali na kon- zoli, nato pa poganjali program in odpravljali napake. Podatke, to je posnetke EKG, ki smo jih dobili od naših zdravnikov, smo hranili na magnetnih trakovih s pomočjo instrumentacijskega magnetofona HP3964. Moj glavni dobavitelj posnetkov EKG in mentor na medicinskem področju je bil dr. Japec Jakopin, ki mi je kot sin dveh eminentnih mojstrov besede celo lektoriral mojo magistrsko nalogo. Problem je bil tudi kako dokumentirati naše rezultate, to je slike signalov EKG, ki so se izpisovali na kato- dnem zaslonu računalnika. Razen tiskalnika T TY nismo imeli nobene druge izhodne enote. Rešitev mi je nakazal Zaviša Bjelo- Slika 3: Člani laboratorija GRASP s prof. dr. Ruzeno Bajcsy, grlić, dve leti mlajši podiplomski študent v našem laboratoriju ustanoviteljico laboratorija na sredini, leta 1984. Na desni in navdušen fotograf. Popolna tema, fotoaparat SLR na stativu, v ozadju stojijo še komponente računalnika ENIAC [22]. slikanje zaslona z dolgimi časi ekspozicije na visoko kontrastni film, nato razvijanje filma in izdelava fotografij v temnici na fa- Prof. Ruzena Bajcsy [21], po rodu iz Slovaške, je svoj drugi kulteti. Vse to sem se moral naučiti, da sem lahko fotografije z doktorat znanosti dobila na Univerzi Stanford pod mentorstvom rezultati nalepil v tipkopis svojega magistrskega dela, ki sem ga prof. Johna McCarthya [15], enega od pionirjev umetne inteli- natipkal na svoj mehanski pisalni stroj. Šele Zaviša je bil prvi gence. Prof. McCarthy je leta 1955 v projektnem predlogu za v našem laboratoriju, ki se je lotil pisanja svojega magisterija organizacijo konference v Darthmouthu, ki je potekala poleti leta na računalniku s programom nroff. Imel sem tudi eminentno 1956 in velja za rojstni kraj nove znanstvene discipline, tudi sko- komisijo za zagovor svoje magistrske naloge [24], v kateri sta val ime za to novo disciplino — Artificial Intelligence [15]. Zato se bila kar dva bodoča člana SAZU, poleg mojega mentorja prof. dr. lahko pohvalim, da je moj akademski “dedek” eden od začetnikov Ludvika Gyergyeka [3] še zdravnik prof. dr. Matija Horvat [32]. umetne inteligence [18]. Prvo leto svojega bivanja v Philadelphiji sem imel status go- 1.3 Hidrografski inštitut vojne mornarice stujočega raziskovalca, toda moje ambicije so bile večje. Ker je Po seriji srečnih naključij se je moje služenje obveznega voja- bila moja mentorica zadovoljna z mojim delom, me je finančno škega roka odvilo v računalniškem centru Hidrografskega inšti- podprla, da sem se lahko naslednje leto vpisal na doktorski pro- tuta vojne mornarice v Splitu. Inštitut je sedaj civilna ustanova gram. Ker sem že prvo leto neformalno poslušal predmete na [11]. V centru smo imeli na voljo računalnik iz serije PDP-11, doktorskem študiju, sem lahko že v naslednjem letu opravljal zaposleni pa so bili praktično samo civilni uslužbenci. V centru rigoroz, ki je pogoj za doktorski naziv. Rigoroz (angl. preliminary 713 Moje računalniško izobraževanje Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia exam ali candidacy) se je takrat pisal tri dni zaporedoma, vsak dan po tri oziroma štiri temeljne računalniške predmete, skupaj deset predmetov. Ker v Ljubljani nisem izbral študijske smeri računalništvo, sem moral precej snovi nadoknaditi, vse od ma- tematične logike, teorije programskih jezikov, prevajalnikov itd. Čez pol leta je sledil še drugi del rigoroza, to sta bila dva izbirna predmeta, običajno povezana s temo doktorske disertacije. Izbral sem računalniški vid in robotiko. Robotiko nam je predaval prof. Richard P. Paul, eden od pionirjev robotske kinematike [20]. Moji sošolci iz laboratorija GRASP so se raztepli skoraj po vsem svetu: Gregory Hager ( John Hopkins University) [10], ki je štiri leta bil tudi moj cimer, Peter Allen (Columbia University), David Heeger (New York University) [5], Hugh Durrant-Whyte Slika 4: Člani laboratorija LRV s prof. dr. Ruzeno Bajcsy (University of Sydney) [12], Eric Krotkov (Toyota Research Insti- leta 1995. Od leve proti desni stojita Peter Peer in Franc tute) [7], Stephane Mallat (Collège de France in École normale Solina, sedijo pa Aleš Jaklič, Bojan Kverh, Ruzena Bajcsy supérieure) [30], Ken Goldberg (Univerza Kalifornije, Berkeley) in Aleš Leonardis. [16]. Moja mentorica Ruzena Bajcsy pa se je po nekaj letih kot botra, kar pa ni bilo vedno slabo. Na samem začetku nisem imel poddirektor NSF v Washingtonu v času Clintonove administracije nobene fakultetne opreme, za prvo financiranje od takratne razi- preselila v Kalifornijo, kjer je profesorica na Univerzi Kalifornije, skovalne skupnosti sem se moral zelo naprezati. Svoj Laboratorij Berkeley. za računalniški vid so mi odobrili šele leta 1991. Ustanovili smo V času mojega bivanja v Philadelphiji sem za krajše razisko- ga celo v istih dneh, ko se je osamosvajala Slovenija. Kakšno valne obiske odprl vrata v laboratorij GRASP še več kot desetim leto kasneje smo za laboratorij dobili večji prostor. Odlično sem drugim raziskovalcem s FE. Omenim naj Jasno Maver in Aleša sodeloval s takratnim dekanom prof. dr. Baldomirjem Zajcem pri Leonardisa, ki sta kasneje na FE pod mojim mentorstvom dok- organizaciji konference IEEE Melecon leta 1991 v Cankarjevem torirala in Staneta Kovačiča, ki je skupaj s prof. Bajcsy objavil domu tik pred razglasitvijo samostojnosti, kasneje pa sva začela prvi članek o elastični poravnavi medicinskih slik [1], ki ima z organizacijo konferenc ERK. Skrbel sem predvsem za urejanje na Google učenjaku več kot 1600 citatov. Za podporo sloven- konferenčnih zbornikov. Prevzel sem tudi tehniško uredništvo skim akademikom je Univerza v Ljubljani prof. Bajcsy leta 2001 Elektrotehniškega vestnika. Pri vsem tem delu mi je bila na za- podelila častni doktorat. četku v dragoceno pomoč oprema, ki sem jo prinesel s seboj iz V svoji doktorski disertaciji sem se ukvarjal z rekonstrukcijo ZDA: osebni računalnik Macintosh II in laserski tiskalni Apple volumetričnih modelov iz globinskih slik [26], ki navdih išče Laserwriter II. Konec 80-tih let na fakulteti še ni bilo drugega v teoriji človeškega zaznavanja slik. Članek na osnovi mojega laserskega tiskalnika. Za oblikovanje besedil sem tudi prvi na doktorata so sprejeli na prvi mednarodni konferenci iz računalni- fakulteti uvedel L AT škega vida (ICCV), ki je bila 1987 v Londonu [2], kasneje sem to EX. Takoj sem tudi začel z mentoriranjem pri doktoratih [17]. Moja prva doktorica znanosti je bila že leta 1990 objavil tudi reviji IEEE PAMI [28]. Istega leta novembra sem še Tatjana Zrimec. Še posebej pa sem ponosen, da sem bil mentor zagovarjal svojo disertacijo. Nato sem imel do avgusta 1988 status pri raziskovalni nalogi Jureta Leskovca, ko je še bil gimnazijec. V podoktoranta, ko sem se vrnil v Ljubljano na FE. Za moj povratek doktorskih komisijah mojih kandidatov je nekajkrat sodelovala na FE je bil najbolj zaslužen takratni prodekan prof. dr. Tadej tudi prof. Ruzena Bajcsy (Slika 4). S prof. Srečom Draganom z Bajd, ki je leta 1987 obiskal Pensilvansko univerzo. Na dolgem ALUO sva začela dolgoletno plodno sodelovanje na področju pogovoru ob pivu sem mu zaupal svoje želje o povratku v domo- umetnosti novih medijev [29]. vino, prof. Bajd pa je nato na fakulteti sprožil ustrezne postopke. Mojo zaposlitev je podprl tudi prof. dr. Boštjan Vilfan, takratni 1.6 Fakulteta za računalništvo in informatiko predstojnik Katedre za računalništvo in informatiko. Domov me je vlekla družina pa tudi velike družbene spremembe, ki so se Moje strokovno delo po ustanovitvi samostojne Fakultete za ra- že napovedovale. Naj še omenim, da je bilo v tistem času težje čunalništvo in informatiko je bolj podrobno opisano v zborniku, vzdrževati stike z domovino, saj pri nas še ni bilo elektronske ki je izšel ob 20-letnici fakultete [4]. Naj na kratko omenim le, da pošte, ki sem jo v ZDA uporabljal že od leta 1983, o svetovnem sem se kot dekan fakultete med leti 2006 in 2010 posvetil pred- spletu pa seveda še ni bilo ne duha ne sluha. Za informacije od vsem bolonjski reformi in arhitekturnim načrtom nove stavbe. doma so poskrbele mailing liste: Pisma bralcev, ki jih je urejal Pri bolonjski reformi sem si prizadeval, da bi tudi umetna inteli- Andrej Brodnik in RokPress, ki ga je začel Rok Sosič. genca dobila svoj zaslužen del študijskega programa na FRI, ki ga do tedaj ni imela, čeprav je umetna inteligenca prispevala največ raziskovalnih rezultatov. Pri novi stavbi pa smo od arhitektov 1.5 Vrnitev na fakulteto predvsem želeli prostore, ki bodo omogočali srečevanje ljudi in Takoj ko sem se vrnil na FE, sem začel predavati različne raču- spodbujali večje sodelovanje. nalniške predmete. Nekaj sem jih nasledil od prof. Petra Tanciga, Po štirih letih dekanovanja se je bilo kar težko spet vrniti v raz- ki je bil zunanji sodelavec fakultete. Računalniške predmete sem iskovalni ritem. Bolj sem se posvetil uporabniškim vmesnikom, predaval tudi na kemiji, montanistiki, tekstilni tehnologiji, ma- 3D dokumentiranju v arheologiji (v sodelovanju z arheologom tematiki in kasneje še na Fakulteti za pomorstvo in promet v Miranom Eričem [14]). Vrnil sem se celo na tematiko svojega Portorožu. Izstopajoči študenti v mojih prvih letih v Ljubljani doktorata, saj skušamo isti problem danes rešiti z globokimi ne- so bili Andrej Bauer na matematiki, na FE pa Marko Grobelnik, vronskimi mrežami [19]. Po bolonjski reformi sem začel redno Dunja Mladenić in Jerneja Gros. Čeprav so me kolegi učitelji na predavati tudi na ALUO, smer Video in novi mediji. Svoje ume- FE podpirali, pa kljub temu nisem imel nobenega neposrednega tniško ustvarjanje sem z novih medijev razširil še na kiparstvo 714 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Franc Solina v kamnu in lesu, kar skušam povezati s svojim računalniškim thy_(computer_scientist)&oldid=1041515367 (pridobljeno znanjem [27]. Delam na seriji kamnitih skulptur (Svetlobni vo-12. 9. 2021). dnjak), ki sem jih virtualno obogatil z video projekcijo gibajočih [16] Ken Goldberg — Wikipedia, The Free Encyclopedia. url: se svetlobnih pik, ki se obnašajo kot vodne kapljice. https://en.wikipedia.org/w/index.php?title=Ken_Goldbe Vodenje Laboratorija za računalniški vid sem leta 2019 predal rg&oldid=980981818 (pridobljeno 12. 9. 2021). svojemu nasledniku prof. dr. Petru Peeru. [17] Mathematics Genealogy Project — Franc Solina. url: https: Da zaključim, izbirni predmet Računalništvo, ki sem ga imel //genealogy.math.ndsu.nodak.edu/id.php?id=61986&f Ch na gimnaziji, je bil morda odločilna izhodiščna vzpodbuda za rono=1 (pridobljeno 12. 9. 2021). zanimivo strokovno življensko pot. [18] Mathematics Genealogy Project — Ruzena Kucera Bajcsy. url: https://genealogy.math.ndsu.nodak.edu/id.php?id=3 LITERATURA 9957 (pridobljeno 12. 9. 2021). [1] Ruzena Bajcsy in Stane Kovačič. “Multiresolution elastic [19] Tim Oblak in sod. “Learning to Predict Superquadric Pa- matching”. V: Computer vision, graphics, and image pro- rameters From Depth Images With Explicit and Implicit cessing 46.1 (1989), str. 1–21. doi: 10.1016/S0734-189X(89 Supervision”. V: IEEE Access 9 (2020), str. 1087–1102. doi: )80014- 3. 10.1109/ACCESS.2020.3041584. [2] Ruzena Bajcsy in Franc Solina. “Three dimensional object [20] Richard P Paul. Robot manipulators: mathematics, program- representation revisited”. V: Proceedings First International ming, and control: the computer control of robot manipula- Conference in Computer Vision — ICCV. London, UK: The tors. MIT Press, 1981. Computer Society of the IEEE, 1987. [21] Ruzena Bajcsy — Wikipedija, prosta enciklopedija. url: ht [3] Tadej Bajd. Ludvik Gyergyek. url: https://www.sazu.si/cla tps://sl.wikipedia.org/wiki/Ruzena_Bajcsy (pridobljeno ni/ludvik- gyergyek (pridobljeno 12. 9. 2021). 12. 9. 2021). [4] Miha Bejek in sod., ur. FRI 20: 1996-2016: 20 let Fakultete [22] Franc Solina. GRASP Lab 1984.jpg — Wikimedia Commons, za računalništvo in informatiko Univerze v Ljubljani. Lju- the free media repository. 1984. url: https://commons.wiki bljana: Fakulteta za računalništvo in informatiko, 2016. media.org/wiki/File:GRASP_Lab_1984.jpg (pridobljeno url: http://eprints.f ri.uni- lj.si/3655/1/Zbornik_FRI20_we 10. 9. 2021). b_100.pdf . [23] Franc Solina. “Računalniška analiza ravninskih in prostor- [5] David Heeger — Wikipedia, The Free Encyclopedia. url: skih zank VKG signalov”. Diplomska naloga. Fakulteta za https://en.wikipedia.org/w/index.php?title=David_Heeg elektrotehniko, Univerza v Ljubljani, 1979. er&oldid=1040812002 (pridobljeno 12. 9. 2021). [24] Franc Solina. “Računalniška prepoznava motenj srčnega [6] ENIAC — Wikipedia, The Free Encyclopedia. url: https://e ritma”. Magistrska naloga. Fakulteta za elektrotehniko, n.wikipedia.org/w/index.php?title=ENIAC&oldid=10435 Univerza v Ljubljani, 1982. 39355 (pridobljeno 12. 9. 2021). [25] Franc Solina. ROBOT.SI - Predaja knjige Isaaca Asimova. [7] Eric Krotkov — Toyota Research Institute. url: https://w 2020. url: https : / / youtu . be / 2mPgYT7Bi4I (pridobljeno ww . tri . global / about - us / dr - eric - krotkov/ (pridobljeno 10. 9. 2021). 12. 9. 2021). [26] Franc Solina. “Shape recovery and segmentation with de- [8] Fulbright Program — Wikipedia, The Free Encyclopedia. url: formable part models”. Doktorska disertacija. Philadelphia, https://en.wikipedia.org/w/index.php?title=Fulbright_Pr PA: University of Pennsylvania, 1987. url: https://reposit ogram&oldid=1040898195 (pridobljeno 12. 9. 2021). ory.upenn.edu/dissertations/AAI8804963. [9] GRASP Lab — General Robotics, Automation, Sensing & [27] Franc Solina. Skulpture / Sculptures 2012–2020, 2. izdaja / Perception Lab. url: https://www.grasp.upenn.edu (prido- 2nd Edition. Ljubljana: Društvo likovnih umetnikov Lju- bljeno 12. 9. 2021). bljana, Fakulteta za računalništvo in informatiko, 2021. [10] Gregory D. Hager — Wikipedia, The Free Encyclopedia. url: url: https://dts.cld.bz/Skulpture- Franc- Solina- 2021/5/. https : / / en . wikipedia . org / w / index . php ? title = Gregory [28] Franc Solina in Ruzena Bajcsy. “Recovery of parametric _D._Hager&oldid=910655080 (pridobljeno 12. 9. 2021). models from range images: the case for superquadrics [11] Hrvatski hidrografski institut. url: https://www.hhi.hr/o- with global deformations”. V: IEEE Transactions on Pattern nama/o- institutu (pridobljeno 12. 9. 2021). Analysis and Machine Intelligence 12.2 (1990), str. 131–147. [12] Hugh F. Durrant-Whyte — Wikipedia, The Free Encyclopedia. doi: 10.1109/34.44401. url: https : / / en . wikipedia . org / w / index . php ? title = Hug [29] Franc Solina in Srečo Dragan. “Novomedijski umetniški h _ F . _Durrant - Whyte & oldid = 1041360160 (pridobljeno projekti kot most med realnim in virtualnim svetom”. V: 12. 9. 2021). Robotika in umetna inteligenca. Ur. Tadej Bajd in Ivan [13] International Research & Exchanges Board — Wikipedia, Bratko. Slovenska matica, 2014, str. 187–230. url: http The Free Encyclopedia. url: https://en.wikipedia.org/w/i ://eprints.f ri.uni- lj.si/2861/1/Poglavje_SM_Solina- Draga ndex.php?title=International_Research_%26_Exchanges n.pdf . _Board&oldid=1042689102 (pridobljeno 12. 9. 2021). [30] Stéphane Mallat — Wikipedia, The Free Encyclopedia. url: [14] Aleš Jaklič in sod. “Volumetric models from 3D point clo- https://en.wikipedia.org/w/index.php?title=St%C3%A9p uds: The case study of sarcophagi cargo from a 2nd/3rd hane_Mallat&oldid=1037604805 (pridobljeno 12. 9. 2021). century AD Roman shipwreck near Sutivan on island Brač, [31] University of Pennsylvania — Wikipedia, The Free Encyclo- Croatia”. V: Journal of Archaeological Science 62 (2015), pedia. url: https://en.wikipedia.org/w/index.php?title=Un str. 143–152. doi: https://doi.org/10.1016/j.jas.2015.08.007. iversity_of _Pennsylvania&oldid=1043629770 (pridobljeno [15] John McCarthy — Wikipedia, The Free Encyclopedia. url: 12. 9. 2021). https://en.wikipedia.org/w/index.php?title=John_McCar [32] Zvonka Zupanič Slavec. Matija Horvat. url: https://www .sazu.si/clani/matija- horvat (pridobljeno 12. 9. 2021). 715 716 Zbornik 24. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2021 Zvezek J Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume J Delavnica projekta BATMAN BATMAN Project Workshop Urednika / Editors Sergio Crovella, Anton Gradišek http://is.ijs.si 4. oktober 2021 / 4 October 2021 Ljubljana, Slovenia 717 718 PREDGOVOR Na delavnici sodelujejo partnerji projekta ERA PerMed BATMAN in drugi zainteresirani znanstveniki. BATMAN je akronim za “Biomolecular Analyses for Tailored Medicine in Acne iNversa”, biomolekularne analize za personalizirano zdravljenje Acne Inversa. Cilj projekta, ki se je začel leta 2019, je priti do novih spoznanj in boljšega razumevanja mehanizmov kronične bolezni Acne Inversa, imenovane tudi Hidradenitis Suppurativa, in razviti ciljane metode zdravljenja. To bo pripomoglo k boljšemu življenju pacientov. Raznoliki konzorcij projekta sestavljajo partnerji s področij medicine, genetike, modelov tkiv in informacijskih tehnologij. Delavnica je tudi del letnega sestanka partnerjev konzorcija. Predsednika delavnice se distancirata od nagrad, ki so bile podeljene med Multikonferenco. Sergio Crovella in Anton Gradišek, predsednika delavnice FOREWORD This Workshop brings together the partners that collaborate on the ERA PerMed project BATMAN, as well as other interested parties. BATMAN stands as the acronym for “Biomolecular Analyses for Tailored Medicine in Acne iNversa”. The aim of the project that started in 2019 is to find new knowledge and better understanding of mechanisms of the chronic disease Acne Inversa, also called Hidradenitis Suppurativa, and to provide tailored treatment for the patients, thus improving their quality of life. The consortium is heterogeneous and brings together partners with experiences in the field of medicine, genetics, tissue models, and information technologies. This Workshop is also a part of the annual consortium meeting of the partners. Workshop chairs distance themselves from the awards that were handed out during the Multiconference. Sergio Crovella and Anton Gradišek, workshop chairs 719 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Sergio Crovella Anton Gradišek Paola Maura Tricarico 720 Identification of novel genetic variants in Hidradenitis Suppurativa patients through the investigation of familial cases Paola Maura Tricarico † Rossella Gratton Lucas Brandão Laboratory of Genetic Laboratory of Genetic Laboratory of Genetic Immunology, Institute for Immunology, Institute for Immunology, Institute for Maternal and Child Health – Maternal and Child Health – Maternal and Child Health – IRCCS “Burlo Garofolo”, Trieste, IRCCS “Burlo Garofolo”, Trieste, IRCCS “Burlo Garofolo”, Trieste, Italy; tricaricopa@gmail.com Italy; Italy; lucabrand@gmail.com rossella.gratton@burlo.trieste.it Ronald Moura † Sergio Crovella Laboratory of Genetic Carlos André dos Santos Department of Biological and Immunology, Institute for Silva Environmental Sciences, College Maternal and Child Health – Laboratory of Genetic of Arts and Sciences, University IRCCS “Burlo Garofolo”, Trieste, Immunology, Institute for of Qatar, Doha, Qatar Italy; Maternal and Child Health – sgrovella@qu.edu.qa ronald.rodriguesdemoura@burlo.t IRCCS “Burlo Garofolo”, Trieste, rieste.it Italy; carlos.biomedicina@gmail.com † These authors contributed equally to this article. ABSTRACT Hidradenitis suppurativa (HS), a chronic autoinflammatory refractory disease with recurrent skin lesions and wounds of Hidradenitis Suppurativa (HS) familial cases represent 40% of difficult resolution, currently represents an area of high-unmet the total cases observed. Current knowledge on the etio- clinical need. HS has multifactorial etiology that involves a pathogenesis of these cases is still poor; for this reason, we strict interplay between genetic factors, immune dysregulation, decided to investigate the genetic variants associated to this hormonal influence, bacterial colonization, impaired wound disease in 5 HS families. In 3 families we found single healing and environmental risk factors [1, 2]. Approximately nucleotide variation (SNV) in genes never associated with HS: 40% of patients with HS report a family history of the ZNF318, DCD, DSC3. In one family we found a new SNV in condition, and amongst these only about 10% present mutations in genes involved in the gamma NCSTN gene, one of the few genes already associated with HS. -secretase pathway, namely NCSTN, PSENEN and PSEN1 genes [3]. In another family, due to the low number of individuals The study of HS familial cases represents a tool identify novel analyzed, we did not find with certainty the SNV associated genetic factors, other than the genes of the gamma-secretase with the disease but we found three SNVs in PADI3, DSP and pathway, involved in the etio-pathogenesis of this complex KRTAP10-4 genes. Deepening knowledge on the genetic disease. Unfortunately, analyzing HS familial cases can be variants associated with these familial HS cases is a necessary sometimes difficult due to delayed diagnosis, absence of first step to unravel the disease etio-pathogenesis; in fact, to personal and family health history investigation, incomplete better understand the disease an integrated approach involving penetrance of the disease and also unwillingness to participate different OMICs is the right path to be followed. in the genetic study of other family members. Here we investigated 5 HS families aimed at identifying genetic KEYWORDS variants associated with the disease, using whole exome sequencing (WES). Hidradenitis suppurativa, familial cases, genetic variants, WES Patients with a positive family history of HS were recruited analysis. from January 2019 to May 2021 at the Dermatology Unit of the University of Milan (Italy) and at the Dermatology Service of “Hospital das Clinicas”, Recife, Brazil. All study participants signed a written informed consent after the approval by the Single Regional Ethical Committee of Friuli Venezia Giulia Permission to make digital or hard copies of part or all of this work for personal or (CEUR) (CEUR-2018-Sper-127-BURLO and CEUR-2020-Em- classroom use is granted without fee provided that copies are not made or 380) by the Area B Milan Ethics Committee (protocol no. distributed for profit or commercial advantage and that copies bear this notice and 487_2020) and by Ethical Committee of the Federal University 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). of Pernambuco (n. 3.048.719; 30/11/2018). Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia Genomic DNAs have been extracted from saliva by using the © 2021 Copyright held by the owner/author(s). Oragene-DNA (Ottawa, Canada) kit following the manufacturer’s protocols. WES, with 100X of expected coverage, has been performed in outsourcing by Macrogen 721 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia P.M. Tricarico et al. (Seoul, Korea). WES analysis has been performed using the particularly highlighted by the increased flexibility of its C- InterOMICs Genome Pro software, as described in our previous terminal region. study [4]; WES results have been validated by Sanger In HS, a dysbiosis-driven aberrant activation of the innate Sequencing. immune system leading to excessive inflammatory responses, is thought to be partially induced by a marked dysregulation in In family 1 (11 HS patients and 36 healthy subjects) we found a antimicrobial peptides production, in particular DCD [6, 7]. rare missense single nucleotide variation (SNV) in the exon 4 of Indeed, in the skin of HS patients a significant down-regulation ZNF318 gene in heterozygosis (rs767801219). The SNV was of DCD expression has been observed [8, 9]. detected in heterozygosis in 17 family members comprising all In family 3 (4 HS patients and 1 control) we found a rare of the 11 individuals who initially declared to be affected by HS missense SNV at exon 10 of DSC3 gene in heterozygosis and additional 6 individuals that haven't been mentioned to (rs114245564) in all 4 HS patients (Figure 3). possess any sign of the disease (Figure 1). This identified SNV shows an autosomal dominant inheritance pattern with incomplete penetrance. Figure 1: Pedigree of the Family 1. 47 individuals adhered to the study, 11 of which declared to be affected by HS, and the genotype of the selected variant in ZNF318 gene (rs767801219). ZNF318 gene encodes the zinc finger 318 (ZNF318) protein Figure 3: Pedigree of the Family 3. 5 individuals adhered to involved in the regulation of the androgen receptor by acting the study, 4 of which declared to be affected by HS, the both as a co-repressor or co-activator in AR transactivation genotype of the selected variant in DSC3 gene (rs114245564) function. To date the effect of the SNV in the protein structure is hard to predict in silico due to the dimension of the protein DSC3 gene encodes Desmocollin-3 a desmosomal cadherin and the lack of a clearly defined structure, but the role of superfamily member, component of the transmembrane core of androgens in HS is well known and has been explored in desmosomes required for maintaining cell adhesion in the numerous observational and some interventional studies [5]. epidermis. The critical role of these desmosomal cadherins in In family 2 (2 HS patients and 1 control and 1 child) we found a epithelial integrity has been illustrated by their disruption in rare frameshift insertion in exon 4 of DCD gene in mouse models and human diseases. Alterations in the heterozygosis (rs538180888) in all 2 HS patients; this variant is expression and function of the desmosomal cadherins have been also present in the daughter, an 11-year-old child who begins to observed in severe autoimmune skin disease pemphigus, manifest relapsing inguinal furuncles (Figure 2). epidermolysis bullosa and hypotrichosis and recurrent skin vesicles [10, 11]. In family 4 (4 HS patients, 3 controls and 2 children), enrolled in Brazil, so with individuals showing a different genetic background when compared to the other Italian members of the analyzed families, we found a SNV in NCSTN gene exon 2 in heterozygosis (NM_015331:exon2:c.T131A) encoding a premature stop codon [NP_056146 1:p.(L44*)], in all 4 HS patients and also in the 2 children (11- and 16-year-old). To date, these 2 children do not show the disease, probably due to their young age (Figure 4). Figure 2: Pedigree of the Family 2. 4 individuals adhered to the study, 2 of which declared to be affected by HS, the genotype of the selected variant in DCD gene (rs538180888). DCD gene encodes Dermcidin, the most abundant antimicrobial peptide (AMP) present in human sweat. The identified frameshift variant disrupts the ORF of DCD and results in a 33 amino acid peptide having a completely altered sequence, if compared to the wild- type DCD-1(L) peptide. This affects both the N-terminal and the C-terminal partitions, hence impairing the activity of DCD. This mutant is characterized by a less Figure 4: Pedigree of the Family 4. 9 individuals adhered to compact structure and by an increased solvent accessibility, the study, 4 of which declared to be affected by HS, the genotype of the selected variant in NCSTN gene. 722 The investigation of familial cases allows the identification of Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia novel genetic variants in Hidradenitis Suppurativa patients This genetic variant was not present in the Genome residues into citrullines. Deimination is implicated in many Aggregation Database (gnomAD) and therefore it was never physiological processes including keratinocyte biology and skin associated with HS; despite this, the NCSTN gene is one of the homeostasis. One example of deiminated protein is the fillagrin, few genes already associated with HS [3]. a key protein in the epidermal barrier function, expressed in the In family 5 (2 HS patients and 1 control) we found 25 SNVs in hair follicle. In addition to this, PADI3 gene may also play a genes expressed in the skin or by the immune system (Table 1). role in the cornification-related autophagy process of the epidermis. Uncombable Hair Syndrome 1 and Central Centrifugal Cicatricial Alopecia are diseases associated with Table 1: List of single nucleotide variations (SNVs) genes PADI3 gene [12]. expressed in the skin or by the immune system, found in 2 DSP encodes for Desmoplakin, an obligate and the most HS patients and not in the control of the family 5 abundant component of functional highly specialized adhesive intercellular junctions known as desmosomes. Desmosomes are Gene SNV Ref Alt abundant in districts that are continuously subjected to AQP9 rs1439722664 T C mechanical solicitations such as the epidermis and hair follicles, PHYKPL because they confer strong mechanical strength to tissues and rs559406393 C G ACSS2 contributing to the maintenance of tissue architecture and rs371982555 C T cohesiveness [13, 14]. Alopecia, palmo-plantar keratoderma, ARSK rs754905227 T A skin fragility woolly-hair syndrome, erythrokeratodermia, CRIP1 rs200883038 C A dilated cardiomyopathy, arrhythmogenic right ventricular MYH14 rs371244397 C T cardiomyopathy/dysplasia are disorders also connected to SMYD5 rs61755313 G A alteration in the expression and function of Desmoplakin [15]. VEGFA vi6.43777526 T G KRTAP10-4 encodes for Keratin Associated Protein 10-4, DHFR2 rs772191447 T C which are essential for the formation of a rigid and resistant hair TRPS1 rs61745721 T C shaft through their extensive disulfide bond cross-linking with HSPBP1 rs150486738 G A abundant cysteine residues of hair keratin. This gene plays an MAP3K4 important role in the keratinization pathway [16]. rs1477003192 T C Unfortunately, perhaps due to the low number of family PADI3 rs142129409 T A individuals analyzed, to date we do not have the ability to PPP1R3D rs377580619 G A identify with certainty the SNV associated with this HS familial SYNE1 rs34028822 G A case. ZNF692 rs201441689 C T ADPRHL2 rs139736291 A G Considering the findings obtained by analyzing some HS PTCD1 rs35556439 G A families, one with different genomic background with respect to COPB2 vi3.139379091 C T the others, we can state that HS familial cases are extremely DSP rs78652302 A T useful to investigate novel actors involved in this complex KRTAP10-4 rs782312294 G T disease, so the first need is to augment the number of families PRSS1 to be analyzed; secondly, to more deeply and precisely evaluate rs757111793 G A SCFD2 the role of the identified genetic factors, at least an integration rs79025139 C A with transcriptome is needed. To this end it is important to TRIM16 rs143877253 C A recall that when families are diagnosed and recruited, it should TTLL12 rs369903948 T C be envisaged, when possible and permitted by the ethical committee, a skin biopsy of lesional, pre-lesional and healthy Among these genes, the ones considered as possibly related to skin of the patients, to allow RNA extraction and consequent dermatologic disorders based on their functions are: PADI3, transcriptome analysis. DSP and KRTAP10-4 (Figure 5). As conclusive remarks, we should bear in mind that HS is a complex disease and that the genetics by itself is not able to completely unravel the disease etio-pathogenesis; an integrated approach involving different OMICs, such as genomics, transcriptomics and microbiomics etc. is the path to be followed to better understand the disease and consequently design possible tailored treatments. ACKNOWLEDGMENTS This work was supported by a Biomolecular Analyses for Tailored Medicine in AcneiNversa (BATMAN) project, funded by ERA PerMed, by a grant from the Institute for Maternal and Figure 5: Pedigree of the Family 5. 3 individuals adhered to Child Health IRCCS ‘Burlo Garofolo/Italian Ministry of the study, 2 of which declared to be affected by HS, the Health’ (RC16/ 2018), by a grant Interreg Italia-Slovenia, ISE- genotype of the selected variants in PADI3, DSP and EMH 07/2019 and by CNPq (311415/2020-2). KRTAP10-4 genes. REFERENCES PADI3 encodes for a member of the peptidyl arginine [1] Schell SL, Schneider AM, Nelson AM. Yin and Yang, 2021. A disrupted deiminase family of enzymes, which catalyze the post- skin microbiome and an aberrant host immune response in hidradenitis translational deimination of proteins by converting arginine 723 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia P.M. Tricarico et al. suppurativa. Exp Dermatol. (May, 2021). DOI: skin transcriptome in hidradenitis suppurativa uncovers an antimicrobial https://doi.org/10.1111/exd.14398. and sweat gland gene signature which has distinct overlap with wounded [2] Sabat R, Jemec GBE, Matusiak Ł, Kimball AB, Prens E and Wolk K, skin. PLoS One. (May, 2019), 14:e0216249. DOI: 2020. Hidradenitis suppurativa. Nat Rev Dis Primers. (Mar, 2020), 6:18. https://doi.org/10.1371/journal.pone.0216249. DOI: https://doi.org/10.1038/s41572-020-0149-1. [10] Vielmuth F, Wanuske MT, Radeva MY, Hiermaier M, Kugelmann D, [3] Tricarico PM, Boniotto M, Genovese G, Zouboulis CC, Marzano AV Walter E, Buechau F, Magin TM, Waschke J and Spindler V, 2018. and Crovella S, 2019. An Integrated Approach to Unravel Hidradenitis Keratins Regulate the Adhesive Properties of Desmosomal Cadherins Suppurativa Etiopathogenesis. Front Immunol. (Apr, 2019), 10:892. through Signaling. J Invest Dermatol. (Jan, 2018), 138:121-131. DOI: DOI: https://doi.org/10.3389/fimmu.2019.00892. https://doi.org/10.1016/j.jid.2017.08.033. [4] Brandao L, Moura R, Tricarico PM, Gratton R, Genovese G, Moltrasio [11] Ayub M, Basit S, Jelani M, Ur Rehman F, Iqbal M, Yasinzai M and C, Garcovich S, Boniotto M, Crovella S and Marzano AV, 2020. Altered Ahmad W, 2009. A homozygous nonsense mutation in the human keratinization and vitamin D metabolism may be key pathogenetic desmocollin-3 (DSC3) gene underlies hereditary hypotrichosis and pathways in syndromic hidradenitis suppurativa: a novel whole exome recurrent skin vesicles. Am J Hum Genet. (Oct, 2009), 85:515-20. DOP: sequencing approach. J Dermatol Sci. (Jul, 2020), 99:17-22. DOI: https://doi.org/10.1016/j.ajhg.2009.08.015. https://doi.org/10.1016/j.jdermsci.2020.05.004. [12] Méchin MC, Takahara H and Simon M, 2020. Deimination and [5] Riis PT, Ring HC, Themstrup L and Jemec GB, 2016. The Role of Peptidylarginine Deiminases in Skin Physiology and Diseases. Int J Mol Androgens and Estrogens in Hidradenitis Suppurativa - A Systematic Sci. 2020 (Jan, 2020), 21:566. DOI: Review. Acta Dermatovenerol Croat. (Dec, 2016), 24:239-249. PMID: https://doi.org/10.3390/ijms21020566. 28128074. [13] Garrod D and Chidgey M, 2008. Desmosome structure, composition and [6] Schlapbach C, Yawalkar N and Hunger RE, 2009. Human beta-defensin- function. Biochim Biophys Acta. (Mar, 2008), 1778:572-587. DOI: 2 and psoriasin are overexpressed in lesions of acne inversa. J Am Acad https://doi.org/10.1016/j.bbamem.2007.07.014. Dermatol. (Jul, 2009), 61:58-65. DOI: [14] Kurzen H, Moll I, Moll R, Schäfer S, Simics E, Amagai M, Wheelock https://doi.org/10.1016/j.jaad.2008.12.033. MJ and Franke WW, 1998. Compositionally different desmosomes in the [7] Wolk K, Warszawska K, Hoeflich C, Witte E, Schneider-Burrus S, Witte various compartments of the human hair follicle. Differentiation. (Sep, K, Kunz S, Buss A, Roewert HJ, Krause M, Lukowsky A, Volk HD, 1998), 63:295-304. DOI: https://doi.org/10.1046/j.1432- Sterry W and Sabat R, 2011. Deficiency of IL-22 contributes to a chronic 0436.1998.6350295.x. inflammatory disease: pathogenetic mechanisms in acne inversa. J [15] Paller AS, Czarnowicki T, Renert-Yuval Y, Holland K, Huynh T, Sadlier Immunol. (Jan, 2011), 186:1228-1239. DOI: M, McAleer MA, Tran G, Geddes GC, Irvine AD and Guttman-Yassky https://doi.org/10.4049/jimmunol.0903907. E, 2018. The spectrum of manifestations in desmoplakin gene (DSP) [8] Shanmugam VK, Jones D, McNish S, Bendall ML and Crandall KA, spectrin repeat 6 domain mutations: Immunophenotyping and response to 2019. Transcriptome patterns in hidradenitis suppurativa: support for the ustekinumab. J Am Acad Dermatol. (Mar, 2018), 78:498-505.e2. DOI: role of antimicrobial peptides and interferon pathways in disease https://doi.org/10.1016/j.jaad.2017.10.026. pathogenesis. Clin Exp Dermatol. (Dec, 2019), 44:882-892. DOI: [16] https://www.genecards.org/cgi-bin/carddisp.pl?gene=KRTAP10- https://doi.org/10.1111/ced.13959. 4&keywords=KRTAP10%5C-4 [9] Coates M, Mariottoni P, Corcoran DL, Kirshner HF, Jaleel T, Brown DA, Brooks SR, Murray J, Morasso MI and MacLeod AS, 2019. The 724 Generation of animal and human 3D models of Acne Inversa Wacym Boufenghour Dr. Vincent Flacher Laboratory I2CT / CNRS UPR3572 Laboratory I2CT / CNRS UPR3572 Institut de Biologie Moléculaire et Institut de Biologie Moléculaire et Cellulaire Cellulaire Strasbourg, France Strasbourg, France w.boufenghour@cnrs-ibmc.unistra.fr v.flacher@cnrs-ibmc.unistra.fr ABSTRACT human skin cells. Our objective is to repurpose this skin model by either using keratinocytes from AI patients producing a Acne Inversa (AI; Verneuil’s Disease, Hidradenitis Suppurativa) defective desmoplakin, or HaCaT genetically modified through is a chronic inflammatory condition affecting the hair follicles in CRISPR-Cas9 to carry mutations for the gamma-secretase moist areas of the body (inguinal folds, scrotum, pubic area). As complex. We expect those mutated epithelial cells to produce an currently understood, AI is triggered by a hair canal obstruction, epidermis and influence MoDCs introduced in the scaffold. The leading to follicle bursting and entry of cellular debris and final purpose is to induce an inflammatory response close to AI bacteria into the dermis, resulting in a powerful and persistent ex vivo. inflammation [1]. Over time, some patients develop severe scarring of the inflamed areas, leading to surgical removal of the We tested different scaffold seeding conditions using healthy affected skin areas. These events might be triggered or human fibroblasts, keratinocytes and MoDCs. We also evaluated exacerbated by bacterial infection or epithelial barrier non-modified HaCaT cells instead of keratinocytes. The weakening. Thus far, only mutations in genes encoding the resulting models were frozen after up to 6 weeks of culture, gamma-secretase) have been found to underlie familial forms of sliced and stained with various epithelial and immune markers. AI. Despite promising results, cell seeding and fibroblast Our laboratory aims at creating ex vivo and in vivo models to proliferation were inconsistent. We assume this to result from the better study AI pathogenesis, which are still lacking. To achieve scaffold manufacturing process, which we are currently seeking this, we are developing full-thickness skin models built from to optimize. cells of healthy donors and patients, as well as murine models bearing AI-related defects for autophagy in hair follicles. In 2 Reproducing auto-inflammatory addition, we participate in an effort to unravel the potential characteristics of acne inversa in a mouse involvement of B cells, a specific yet poorly studied aspect of AI. model. KEYWORDS Acne inversa, human 3D skin model, mouse, hair follicle, Dr. Michele Boniotto (Créteil, France) found that AI patient inflammation, immunology, autophagy, B cells mutations of the gamma secretase complex results in autophagy impairment in vitro. This prompted us to breed a mouse model to investigate this matter further in vivo, by crossing 1 Human reconstructed skin model with Sox9creERT2 and Atg5flox/- strains. Since Sox9 is an important primary fibroblasts and epidermal cells from transcription factor driving hair follicle stem cells (HFSC) either healthy donors or immortalized cell development and function [4, 5], the resulting strain is expected lines (HaCaT) to lack functional autophagy in the infundibulum of the hair follicle. We expect that autophagy loss of function in HFSC to produce a barrier defect and a stronger immune infiltrate, as a Previous work from our team allowed the creation of an immunocompetent skin model based on a collagen scaffold [2, result of impaired processing of apoptotic hair follicle cells 3], monocyte-derived dendritic cells (MoDCs) and primary (efferocytosis) [6]. Two consecutive depilations were performed in the course of two Permission to make digital or hard copies of part or all of this work for personal or weeks, which may lead to hair occlusions. Skin samples were 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 harvested and studied by flow cytometry and immunochemistry citation on the first page. Copyrights for third-party components of this work must staining. Total skin digestion six hours after the second be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia depilation showed a stronger infiltration of neutrophils and © 2021 Copyright held by the owner/author(s). monocytes in the dermis of knock-out mice (Sox9creERT2 Atg5flox/-) compared to wild-type (Atg5flox/+) and littermates 725 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia W. Boufenghour et al. (Sox9creERT2 Atg5flox/+). Infiltration was resolved after one REFERENCES week in all animals. Further interpretation requires confirmation [1] Vossen Allard R. J. V., van der Zee Hessel H., Prens Errol P. (2018), of these preliminary results by additional experiments. Next, we Hidradenitis Suppurativa: A Systematic Review Integrating Inflammatory Pathways Into a Cohesive Pathogenic Model, Frontiers plan to directly inhibit gamma secretase and autophagy function in Immunology, 9:1664-3224. individually or simultaneously in C57BL/6 mice. https://doi.org/10.3389/fimmu.2018.02965 [2] Bechetoille, N., Vachon, H., Gaydon, A., Boher, A., Fontaine, T., Schaeffer, E., Decossas, M., André-Frei, V. and Mueller, C.G. (2011), A new organotypic model containing dermal-type macrophages. 3 B cell populations in blood samples from Experimental Dermatology, 20: 1035-1037. https://doi.org/10.1111/j.1600-0625.2011.01383.x families affected by acne inversa [3] Muller, Q., Beaudet, M. J., De Serres-Bérard, T., Bellenfant, S., Flacher, V., & Berthod, F. (2018). Development of an innervated tissue-engineered skin with human sensory neurons and Schwann cells Dr. Sergio Crovella (Trieste, Italy) has identified a familial differentiated from iPS cells. Acta biomaterialia, 82, 93–101. https://doi.org/10.1016/j.actbio.2018.10.011 mutation of the transcription factor Znf318 in AI patients of an [4] Nowak, J. A., Polak, L., Pasolli, H. A., & Fuchs, E. (2008). Hair Italian family (unpublished data). It was previously published follicle stem cells are specified and function in early skin that Znf318 is necessary for IgD expression by B cells in mouse morphogenesis. Cell stem cell, 3(1), 33–43. https://doi.org/10.1016/j.stem.2008.05.009 models [7, 8]. Interestingly, AI is among the few dermatological [5] Vidal, V. P., Chaboissier, M. C., Lützkendorf, S., Cotsarelis, G., Mill, conditions that show prominent B cell infiltrates in lesions [9, P., Hui, C. C., Ortonne, N., Ortonne, J. P., & Schedl, A. (2005). Sox9 Is Essential for Outer Root Sheath Differentiation and the Formation 10]. of the Hair Stem Cell Compartment. Current Biology, 15(15), This prompted us to investigate the role of B cells in AI 1340‑1351. https://doi.org/10.1016/j.cub.2005.06.064 pathogenesis. As a preliminary work, we intend to identify [6] Mesa, K. R., Rompolas, P., Zito, G., Myung, P., Sun, T. Y., Brown, S., Gonzalez, D. G., Blagoev, K. B., Haberman, A. M., & Greco, V. variations in B cell subsets among PBMCs from patients with (2015). Niche-induced cell death and epithelial phagocytosis regulate familial or sporadic forms of AI. Our cytometry panel allows us hair follicle stem cell pool. Nature, 522(7554), 94‑97. https://doi.org/10.1038/nature14306 to study the naive, memory and plasmablast B cell populations [7] Enders, A., Short, A., Miosge, L. A., Bergmann, H., Sontani, Y., in patient blood. Bertram, E. M., Whittle, B., Balakishnan, B., Yoshida, K., Sjollema, G., Field, M. A., Andrews, T. D., Hagiwara, H., & Goodnow, C. C. (2014). Zinc-finger protein ZFP318 is essential for expression of IgD, Covid-19 crisis prevented blood sampling from Italian patients, the alternatively spliced Igh product made by mature B lymphocytes. who may show B-cell related defects related to their Znf318 Proceedings of the National Academy of Sciences, 111(12), 4513‑4518. https://doi.org/10.1073/pnas.1402739111 mutation. Yet, we analyzed healthy and diseased individuals of [8] Pioli, P. D., Debnath, I., Weis, J. J., & Weis, J. H. (2014). Zfp318 affected families from Innsbruck, Austria, for which whole-exon Regulates IgD Expression by Abrogating Transcription Termination within theIghm/IghdLocus. The Journal of Immunology, 193(5), sequencing is not yet available. So far, blood B cells of 7 patients 2546‑2553. https://doi.org/10.4049/jimmunol.1401275 from 3 different families have been studied. Currently [9] Hoffman, L. K., Tomalin, L. E., Schultz, G., Howell, M. D., Anandasabapathy, N., Alavi, A., Suárez aggregated data identified patients that deviate from usual -Fariñas, M., & Lowes, M. A. (2018). Integrating the skin and blood transcriptomes and serum population percentages, although we require additional proteome in hidradenitis suppurativa reveals complement unaffected people from the same families to confirm our dysregulation and a plasma cell signature. PLOS ONE, 13(9), e0203672. https://doi.org/10.1371/journal.pone.0203672 analyses. Raw PBMCs have also been frozen, which will be [10] Musilova, J., Moran, B., Sweeney, C., Malara, A., Zaborowski, A., assayed for T cell responses and used to produce MoDC for our Hughes, R., Winter, D., Fletcher, J., & Kirby, B. (2020). Enrichment of Plasma Cells in the Peripheral Blood and Skin of Patients with 3D skin models. Hidradenitis Suppurativa. Journal of Investigative Dermatology, 140(5), 1091–1094.e2. https://doi.org/10.1016/j.jid.2019.08.453 DISCUSSION Despite significant delays related to COVID-19 for animal breeding and interruption of cell cultures for more than 3 months, we have improved our 3D scaffold production method and achieved successful seeding with human-derived cells, including MoDCs. We managed to establish protocols and produce preliminary results on the in vivo studies in the mice, and have plans to go more in depth in the future by studying systemic gamma-secretase inhibition. Finally, our analyses of AI patients in Austria will be interpreted in the light of their upcoming whole exome sequencing data, and extended by samples from Italian patients with Znf318 mutation. ACKNOWLEDGMENTS The authors would like to thank Dr. Michele Boniotto (Créteil, Frnce), Dr. Sergio Crovella, Dr. Paola Tricarico (Trieste, Italy) Pr. Mathias Schmuth, Dr. Gudrun Ratzinger, Wolfram Jaschke (Innsbruck Hautklinik, Austria), Layal Doumard, Delphine Lamon and Fabien Lhericel (Strasbourg, France). 726 Development of new cellular models to identify molecular mechanisms in Hidradenitis Suppurativa Cecile Nait-Meddour † Rola Matar Michele Boniotto IMRB Team Leboyer IMRB Team Leboyer IMRB Team Leboyer UPEC/IMRB UPEC/IMRB UPEC/IMRB Creteil France Creteil France Creteil France cecile.nait-meddour@inserm.fr rola.matar@inserm.fr michele.boniotto@inserm.fr ABSTRACT distribution and hair follicle anatomy, but important genes such as DCD identified in a HS family by our consortium doesn’t have No satisfactory in-vivo and in-vitro models to recapitulate a homologous in the mouse. Hidradenitis Suppurativa (HS) hallmarks have been developed so far. The first transgenic Ncstn KO mice model, engineered Ex vivo models using patients lesional skins have also been after the finding that g-secretase mutations were associated with developed [4]. In fact, Vossen et al. [5] cultured punch biopsies HS in several families, lacked important HS features such as skin from HS patients showing a major contribution of IL-1 in skin inflammation, abscess formation, fistulas, and scarring. In -vitro, inflammation in HS. Moreover, these Authors were able to test the use of skin explants has helped in the identification of the IL- different drugs to tame skin inflammation showing the 1 contribution to HS skin inflammation in HS, but this technique effectiveness of the anti-TNF-a therapy. depends on skin biopsies availability. Even if this ex-vivo model can be used to test a candidate For these reasons we have developed different models to obtain treatment, specific limitations make this model useless for skin cells and skin organoids from Induced Pluripotent Stem cell precision medicine. In fact, different genetic variants seem to lines carrying HS-associated mutations cause the disease, so a skin model for each patient (or family) should be developed. Our Team is developing new cellular models to identify the main biological pathways affected in HS and 3D models to be used to KEYWORDS test novel candidate drugs. We are making use of hair follicle CRISPR/Cas9, Induced Pluripotent Stem Cells, Outer root epithelial cells isolated from selected patients to build 3D sheath epithelial cells, Skin Organoids, keratinocytes, sebocytes reconstituted immunocompetent skins in collaboration with Dr. Flacher: these models will allow the study of the cross-talk among skin cells and immune cells 1 INTRODUCTION AND RESULTS At the same time, we have developed skin organoids bearing hair Hidradenitis suppurativa (OMIM#142690; HS) is a chronic follicles from Induced Pluripotent Stem cells obtained from inflammatory disease involving hair follicles that presents with patients with specific candidate mutations (Figure 1). By using painful nodules, abscesses, fistulae, and hypertrophic scars, the CRISPR/Cas9 methodology we have been able to correct the typically occurring in apocrine gland bearing skin [1]. Adequate candidate mutation and obtain isogenic cell lines differing only models reflecting hallmarks of HS pathogenesis are a for the selected mutation. IPSCs have been differentiated in prerequisite to not only better characterize the molecular activity CD200+/ITGA6+ hair follicle stem cells that could be further of genetic mutations in HS, but also to allow the discovery and differentiated in TP63+/CK14+ keratinocytes or of therapeutic targets in personalized approaches to cure the CK7+/MUC1+/PPARG+ sebocytes. disease. About 10% of HS patients present mutations in three of the four components of the gamma-secretase complex, namely NCSTN, PSEN1 and PSENEN with most of the mutations found in NCSTN [2]. These findings led to the analysis of the NCSTNflox/flox;K5-Cre mice that showed some HS hallmarks such as follicular hyperkeratosis and inflammation [3]. Unfortunately, mica and humans differ not only in hair 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 2021, 4-8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). 727 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia C. Nait-Meddour et al. As we have already shown a defect in lysosomes in NCSTN deficient HaCaT cells, we are studying the lysosome structures in TP63+/CK14+ keratinocytes derived from mutated and corrected using lysosomal markers (Figure 3). Figure 1: Skin organoids bearing hair follicles from IPSCs IPSCs obtained from an HS patient with a novel mutation in NCSTN and presenting with HS and DDD were cultivated as Figure 3: Lysosome distribution in KC obtained from skin described by Lee et al. [6] for 140 days and skin organoids organoids bearing hair follicles obtained from a mutated and corrected clone. Study of lysosome distribution in mutated and corrected From the skin organoids, thanks to a collaboration with StemCell keratinocytes using lysosomal markers CD63, LAMP1 and Technologies, we have been able to isolate and cultivate melanosomes degradation (Pigment) TP63+/CK14+ keratinocytes (Figure 2) 2 OUTLOOK TP63 CK14 Skin organoids will be analyzed by immunofluorescence and DAPI immunohistochemistry. In addition, we plan to understand the activity of NCSTN mutation in skin organoids maturation by performing single cell RNA sequencing (Sc-RNAseq). Our hypothesis is that a g- secretase impaired activity skews the differentiation of hair follicle stem cells towards the epithelial keratinocytes. We do expect to see smaller or absent sebaceous glands in our skin organoids and an enlarged population of outer root and inner root Figure 2: TP63+/CK14+ Keratinocytes isolated from skin sheath keratinocytes. organoids We plan to carry on the same experiments with IPCSs cell from a patient with a novel ZNF318 mutation. ZNF318 is Keratinocytes were obtained after dispase I digestion of skin involved in Androgen Receptor (AR) signaling [7, 8], that has a organoids and cultivated in StemCell Technologies major role in sebocytes differentiation [9]. We do expect that a Keratinocyte Medium. perturbed AR signaling will skew the differentiation of hair follicle stem cells towards the keratinocyte population, still affecting sebaceous gland development. IPSCs will be differentiated in 2D in CD200+/ITGA6+ hair follicle stem cells and treated to become CK7+/MUC1+/PPARG+ sebocytes (Figure 4) to understand what the activity of the novel ZNF318 mutation is. IPSCs-derived keratinocytes and sebocytes will be provided to Dr. Flacher’s team to build 3D immunocompetent skins. 728 Development of new cellular models Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia REFERENCES [1] G. B. Jemec, “Clinical practice. Hidradenitis suppurativa,” N Engl J Med, vol. 366, no. 2, pp. 158-64, Jan 12, 2012. [2] S. Duchatelet, S. Miskinyte, M. Delage, M. N. Ungeheuer, T. Lam, F. Benhadou, V. Del Marmol, A. Vossen, E. P. Prens, O. Cogrel, M. Beylot- Barry, C. Girard, J. Vidil, O. Join-Lambert, M. Parisot, P. Nitschke, S. Hanein, S. Fraitag, H. H. Van der Zee, D. Bessis, G. Damiani, A. Altomare, Y. H. Liao, G. Nikolakis, C. C. Zouboulis, A. Nassif, and A. Hovnanian, “Low Prevalence of GSC Gene Mutations in a Large Cohort of Predominantly Caucasian Patients with Hidradenitis Suppurativa,” J Invest Dermatol, Mar 3, 2020. [3] J. Yang, L. Wang, Y. Huang, K. Liu, C. Lu, N. Si, R. Wang, Y. Liu, and X. Zhang, “Keratin 5-Cre-driven deletion of Ncstn in an acne inversa-like mouse model leads to a markedly increased IL-36a and Sprr2 expression,” Front Med, vol. 14, no. 3, pp. 305-317, Jun, 2020. [4] C. C. Zouboulis, “Ex vivo human models of hidradenitis suppurativa/acne inversa for laboratory research and drug screening,” Br J Dermatol, vol. 181, no. 2, pp. 244-246, Aug, 2019. [5] A. Vossen, K. R. van Straalen, E. F. Florencia, and E. P. Prens, “Lesional Inflammatory Profile in Hidradenitis Suppurativa Is Not Solely Driven by IL-1,” J Invest Dermatol, vol. 140, no. 7, pp. 1463-1466 e2, Jul, 2020. [6] J. Lee, C. C. Rabbani, H. Gao, M. R. Steinhart, B. M. Woodruff, Z. E. Pflum, A. Kim, S. Heller, Y. Liu, T. Z. Shipchandler, and K. R. Koehler, Figure 4: CK7+/MUC1+/PPARG+ sebocytes differentiated “Hair-bearing human skin generated entirely from pluripotent stem cells,” from IPSCs. Sebocytes were obtained from IPSCs after 22 Nature, vol. 582, no. 7812, pp. 399-404, 2020. days in Sebocyte Culture Medium. [7] M. Ishizuka, H. Kawate, R. Takayanagi, H. Ohshima, R. H. Tao, and H. Hagiwara, “A zinc finger protein TZF is a novel corepressor of androgen receptor,” Biochem Biophys Res Commun, vol. 331, no. 4, pp. 1025-31, ACKNOWLEDGMENTS Jun 17, 2005. [8] R. H. Tao, H. Kawate, K. Ohnaka, M. Ishizuka, H. Hagiwara, and R. This work was supported by a Biomolecular Analyses for Takayanagi, “Opposite effects of alternative TZF spliced variants on Tailored Medicine in Acne iNversa (BATMAN) project, funded androgen receptor,” Biochem Biophys Res Commun, vol. 341, no. 2, pp. by ERA PerMed and by a “Starting Grant” from IMRB. 515-21, Mar 10, 2006. [9] C. Barrault, J. Garnier, N. Pedretti, S. Cordier-Dirikoc, E. Ratineau, A. Deguercy, and F. X. Bernard, “Androgens induce sebaceous differentiation in sebocyte cells expressing a stable functional androgen receptor,” J Steroid Biochem Mol Biol, vol. 152, pp. 34-44, Aug, 2015. 729 Hidradenitis suppurativa: from clinic to bench and back Angelo Marzano Chiara Moltrasio Giovanni Genovese Dermatology Unit Dermatology Unit Dermatology Unit Fondazione IRCCS Ca’ Granda Fondazione IRCCS Ca’ Granda Fondazione IRCCS Ca’ Granda OMP, Milan, Italy OMP, Milan, Italy OMP, Milan, Italy angelo.marzano@unimi.it moltrasiochiara@gmail.com giovgenov@gmail.com ABSTRACT and gluteal ones [1]. More recently, Van der Zee et al. proposed six different phenotypes, including the regular, frictional Hidradenitis suppurativa (HS) is a chronic inflammatory furuncle, scarring folliculitis, conglobata, syndromic and ectopic disease presenting with nodules, abscesses, and fistulas on the types [2]. Additional clinical phenotypes and cluster apocrine gland-bearing skin. HS may be classified as sporadic, classifications have also been reported [3-5], but a definitive familial or syndromic (PASH, PAPASH, PASH/SAPHO consensus has not been reached and any of these classifications overlapping), the latter one being rare and characterized by a addresses a prediction of therapeutic outcome. IHS4 constellation of conditions regarded as autoinflammatory in (International Hidradenitis Suppurativa Severity Score System) their origin. is a validated tool for the severity assessment of HS and is arrived at by the number of nodules BAT2021 aims to bring together medical, genetic, experimental and lifestyle data to create holistic health records (HHR), which (multiplied by 1) plus the number of abscesses (multiplied by 2) will allow us to build a tailored approach of each patient. plus the number of draining tunnels (multiplied by 4). A total score of 3 or less signifies mild, 4-10 means moderate and 11 or The inclusion criteria for patient enrollment are the compliance higher correspond to severe disease [6]. to the diagnostic criteria for HS; patient’s demographics, HS has a profound impact on patients and their family life, clinical signs, anatomic phenotype classification, lifestyle leading to a high extent of emotional and physical distress, with habits, severity classification and treatment (former and current) social embarrassment, isolation, and depression [7]. With a are documented. prevalence in Europe varying between 0.3% and 1% [8], and a diagnosis often underestimated and usually delayed for 7.2 ± DNA/RNA obtained from biological samples (predominantly 8.7 years [9], HS is not a rare disease. saliva and skin biopsies) of HS patients will be analysed by HS is associated with several other disorders: i) autoimmune or whole exome sequencing, whole genome genotyping SNPs inflammatory comorbidities, particularly inflammatory bowel arrays and transcriptomics. Clinical and molecular data will be diseases, ii) rheumatologic diseases, such as seronegative stored into a special platform developed for the purpose of the spondyloarthropathies and Adamantiades– Behçet disease project and will be analysed using advanced algorithms of spondylarthritis and iii) malignancies, where the most severe artificial intelligence to propose a novel stratification method complication is the development of squamous cell carcinoma in that clinicians can use in daily clinical practice. areas of chronically diseased HS skin. Other comorbidities associated with HS include obesity, dyslipidemia, diabetes KEYWORDS mellitus, metabolic syndrome, hypertension, cardiovascular disease, secondary amyloidosis, lymphedema, polycystic ovary Hidradenitis suppurativa, clinical practice, research workflow, syndrome and sexual dysfunction. Finally, HS is also associated whole-exome sequencing, whole genome genotyping SNPs with mental comorbidity and psychosocial impairments [10]. HS arrays, transcriptomic, stratification, genotype-phenotype is usually a sporadic disease but may more rarely occur as a correlation, therapeutic outcomes familial disorder [11]. In a minority of patients, HS can present in combination with other diseases as a complex clinical syndrome. The main autoinflammatory syndromes characterized 1 Clinical background by the presence of HS are pyoderma gangrenosum (PG), acne Hidradenitis suppurativa (HS), also known as acne inversa, is a and suppurative hidradenitis (PASH), pyogenic arthritis, PG, chronic, inflammatory, recurrent, debilitating skin disease (of the acne and suppurative hidradenitis (PAPASH), psoriatic arthritis, terminal hair follicle), clinically characterized by inflammatory PG, acne and suppurative hidradenitis (PsAPASH), pustular nodules that progress into abscesses and draining tunnels with psoriasis, arthritis, PG, synovitis, acne and suppurative foul smelling. Three main clinical HS phenotypes have been hidradenitis (PsAPSASH) and PG, acne, suppurative proposed, namely the classic or axillary- mammary, follicular hidradenitis, and ankylosing spondylitis (PASS) [12]. However, HS can also occur in the context of complex syndromes such as Permission to make digital or hard copies of part or all of this work for personal or Familial Mediterranean Fever (FMF), synovitis, acne, pustulosis, classroom use is granted without fee provided that copies are not made or distributed hyperostosis and osteitis (SAPHO), follicular occlusion for profit or commercial advantage and that copies bear this notice and the full syndrome, Down syndrome, Keratitis-ichthyosis-deafness (KID) citation on the first page. Copyrights for third-party components of this work must syndrome, Dowling-Degos disease and Bazex-Dupré- Christol be honored. For all other uses, contact the owner/author(s). Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia syndrome [13]. © 2021 Copyright held by the owner/author(s). Risk factors such as smoking, obesity and other lifestyle triggers have been linked to HS onset, while genetic factors are considered to play a crucial role in HS etiopathogenesis [14]. 730 Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia A. Marzano et al. 30% of HS patients report a family history of HS; mutations in member affected is very useful for determining the patterns of γ-secretase genes (NCSTN, PSENEN and PSEN1) have been disease inheritance. identified as the most common genetic changes involved in HS All biological samples are collected, stored, and used in familial cases and these variants lead to an impairment of Notch agreement with the ethical and research guidelines set. Currently, signaling. Notch signaling pathway dysregulation results in an we have collected saliva from 200 HS patients through Oragene alteration in the proliferation and differentiation of keratinocytes DNA collection Kit (for human DNA) that allows for a high- leading to disruption of the normal hair follicle cycle and the quality human DNA to assess biomarkers and genetic variants formation of follicular cysts, typical for HS [15]. Our group associated to HS, its severity and response to biologic therapy. In recently hypothesized HS as a member of neutrophilic collaboration with IRCCS Burlo Garofolo of Trieste, we have dermatoses based on the elevated concentration of the cytokines analyzed through Whole Exome Sequencing, 12 syndromic IL-1β and IL-17 in skin lesions [16]. Moreover, some of our patients (PASH, PAPASH, PASH/SAPHO collaborators deeply involved in this project have also identified patients with HS occurring in the context of autoinflammatory overlapping) and in the first report, we have demonstrated syndromes, showing that PASH and PAPASH patients bear genetic variants involving genes regulating the keratinization genetic variants in genes coding for proteins of the process and vitamin D metabolism, suggesting that a inflammasomes such as PSTPIP1, MEFV, NOD2 and NLRP3 dysregulation of these two pathways may contribute to the HS [17]. Moreover, the up regulation of pro- inflammatory pathogenesis. Vitamin D has been predicted as able to regulate cytokines/chemokines in both lesional skin and serum are skin homeostasis by controlling proliferation and differentiation involved in the multifactorial HS pathogenesis [18]. With several of hair follicle and the low levels of vitamin D observed in all new gene mutations coming into play, such as those involved in studied patients support the idea that vitamin D insufficiency the keratinization pathways [19], on the background of a could be involved in PASH and PAPASH pathogenesis. dysregulated innate immune response to commensal microbes We have also recruited 9 familial cases of HS, two of which in and alterations in the skin microbiome as well, HS can be collaboration with IRCCS Burlo Garofolo of Trieste and the regarded as a multifactorial, polygenic autoinflammatory disease Italian Association of HS patients, respectively. Genetic analyses [18]. of HS familial cases and their family members are ongoing. Medical treatments in HS are aimed at reducing incidence and Our group has collected HS skin biopsies from lesional, flares thus improving HS patients’ quality of life. Mild cases are perilesional and unaffected tissue (approximately 2 cm from the usually treated by topical antibiotics having anti- inflammatory lesional skin) from the same anatomical region. Important is i) to properties. Widespread disease is treated by systemic antibiotics take biopsies from different kind of HS lesions, including and most severe cases by biologics such as adalimumab (anti- abscesses, plaques and fistulae (in the same patient, if it is TNFα), currently the only biologic approved by the United States possible); ii) smaller lesions (up to 1 cm in diameter) such as Food and Drug Administration [20] and by European Medicines cysts and inflammatory and non-inflammatory nodules, should Agency for treatment of HS [20,21]. be completely excised while a deep biopsy (extending to Surgical resection of irreversibly damaged skin is often required, subcutaneous tissue) should be made from abscesses and fistulae but often leads to functional impairments [20]. Different clinical and iii) typical sites, such as axillary or inguinal folds as well as trials for biologics targeting IL-17, IL-1 (alpha and beta), IL-36 anogenital area should be chosen for taking biopsy but and Janus kinase (JAK) 1 signaling response are currently having samples also from atypical sites, i.e. dorsum or cervical ongoing, but simple outcome measures or novel biological region as well as foruncles on different areas of the body, could models are demands to measure the efficacy of treatments [22]. be of interest. Skin samples has been subdivided into two parts, one of which for conventional histology (formalin-fixed, paraffin- embedded) 2 Patient’s enrollment and biological samples and the other one frozen for additional studies collection (immunohistochemistry, protein array, real - time PCR). An additional skin samples is taken and stored in Rna ladder for Acting as one of the clinical partners of the project, Fondazione transcriptomic analyses. IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan has For functional and validation studies, we have performed hair a large outpatient clinic with specialization in HS. The inclusion follicle pick up according to the following procedure: a firm pull criteria for patient enrollment are the compliance to the motion with forceps must be performed at the base of the hair. diagnostic criteria for HS [23]. Patient’s demographics, clinical Only plucked hair in the anagen phase (minimum of five from signs, anatomic phenotype classification, lifestyle habits, each subject) contain enough keratinocytes for a successful severity classification and treatments (former and current) are culture initiation. The hair has been plucked from the occipital documented. For the data documentation, the REDCap platform and temporal scalp regions but facial hair types like beard, is used. eyebrow, or hair from the nose can be used. The hair shaft has The study population include approximately 300 patients with been cutted slightly behind the follicle with sterile scissors moderate-to-severe HS, of which most are sporadic. 6% of resulting in an approximate 5 mm long piece consisting mainly patients have a HS positive family history and 14 patients present of the follicle. The plucked hairs were stored in a tube filled with a HS syndromic form (4 PASH patients, 3 PAPASH, 5 5 mL Defined keratinocytes-SFM medium (DKSFM; Gibco – PASH/SAPHO overlapping, 1 SAPHO and 1 patient with Thermo Fisher Scientific, Switzerland) at room temperature [24]. PASS). Before biological samples collection, all patients and their relatives provide written informed consent for genomic analysis 3 Conclusions (protocol no. 487_2020) and receive pre-test genetic counselling in accordance with guidelines; indeed, the occurrence of the The comparison of the results obtained from DNA/RNA same condition among family members is a key factor to sequencing between patients and controls will highlight consider. Pedigree analysis of the families with more than one possible causative genes and signalling pathways. The possible detection of genotype-phenotype correlations will allow a more 731 Hidradenitis suppurativa: from clinic to bench and back Information Society 2021, 4-8 October 2021, Ljubljana, Slovenia exhaustive and precise clinical patient stratification which, in [13] Garcovich S, Genovese G, Moltrasio C, Malvaso D, Marzano AV. PASH, PAPASH, PsAPASH, and PASS: The autoinflammatory syndromes of addition to the existing pharmacogenetic data banks, will help hidradenitis suppurativa. (2021). Clin Dermatol, 39(2):240-247. doi: the development of new effective drugs and a future 10.1016/j.clindermatol.2020.10.016. individualized treatment of HS patients. [14] Sabat R, Jemec GBE, Matusiak Ł, Kimball AB, Prens E, Wolk K. Hidradenitis suppurativa. (2021). Nat Rev Dis Primers, 6(1):18. doi: 10.1038/s41572-020-0149-1 ACKNOWLEDGMENTS [15] Wang Z, Yan Y, Wang B. γ-Secretase Genetics of Hidradenitis Suppurativa: A Systematic Literature Review. (2020). Dermatology, 1-7. The authors would like to thank Prof. Sergio Crovella and Dr. doi: 10.1159/000512455. Epub ahead of print. Paola Tricarico (Trieste, Italy), Dr. Michele Boniotto (France), [16] Marzano AV, Ortega-Loayza AG, Heath M, Morse D, Genovese G, Prof. Mathias Schmuth (Austria), Prof. Ester Von-Stebut- Cugno M. Mechanisms of Inflammation in Neutrophil-Mediated Skin Diseases. (2019). Front Immunol, 10:1059. doi: Borschitz (Cologne), Dr. Vincent Flaher (France), Matjaž Gams 10.3389/fimmu.2019.01059 and Anton Gradišek (Slovenia). [17] Marzano AV, Damiani G, Ceccherini I, Berti E, Gattorno M, Cugno M. (2017). Autoinflammation in pyoderma gangrenosum and its syndromic form (pyoderma gangrenosum, acne and suppurative hidradenitis). Br J REFERENCES Dermatol, 176(6):1588-1598. doi: 10.1111/bjd.15226 [1] Canoui-Poitrine F, Le Thuaut A, Revuz JE, Viallette C, Gabison G, Poli [18] Marzano AV. (2016). Hidradenitis suppurativa, neutrophilic dermatoses F, et al. (2013). Identification of three hidradenitis suppurativa and autoinflammation: what's the link?. Br J Dermatol, 174(3):482-3. doi: phenotypes: latent class analysis of a cross-sectional study. J Invest 10.1111/bjd.14364 Dermatol, 133(6):1506-11. doi: 10.1038/jid.2012.472 [19] Brandao L, Moura R, Tricarico PM, Gratton R, Genovese G, Moltrasio C, [2] Van der Zee HH, Jemec GB. (2015). New insights into the diagnosis of et al. (2020). Altered keratinization and vitamin D metabolism may be key hidradenitis suppurativa: Clinical presentations and phenotypes. pathogenetic pathways in syndromic hidradenitis suppurativa: a novel JAMA, 73: S23-6. doi: 10.1016/j.jaad.2015.07.047 whole exome sequencing approach. J Dermatol Sci, 99(1):17-22. doi: [3] Martorell A, Jfri A, Koster SBL, Gomez-Palencia P, Solera M, Alfaro- 10.1016/j.jdermsci.2020.05.004 Rubio A, et al. (2020). Defining hidradenitis suppurativa phenotypes [20] Folkes AS, Hawatmeh FZ, Wong A, Kerdel FA. Emerging drugs for the based on the elementary lesion pattern: results of a prospective study. J treatment of hidradenitis suppurativa. (2020). Expert Opin Emerg Drugs, Eur Acad Dermatol Venereol, 34(6):1309-1318. doi: 10.1111/jdv.16183 25(3):201-211. doi: 10.1080/14728214.2020.1787984. [4] Naasan H, Affleck A. (2015). Atypical hidradenitis suppurativa. Clin Exp [21] Marzano AV, Genovese G, Casazza G, Moltrasio C, Dapavo P, Micali G, Dermatol, 40:891-3. doi: 10.1111/ced.12655 et al. (2021). Evidence for a 'window of opportunity' in hidradenitis [5] Cazzaniga S, Pezzolo E, Bettoli V, Abeni D, Marzano AV, Patrizi A, et al. suppurativa treated with adalimumab: a retrospective, real-life multicentre (2021). Characterization of Hidradenitis Suppurativa Phenotypes: A cohort study. Br J Dermatol, 184(1):133-140. doi: 10.1111/bjd.18983. Multidimensional Latent Class Analysis of the National Italian Registry [22] Zouboulis CC, Frew JW, Giamarellos-Bourboulis EJ, Jemec GBE, Del IRHIS. J Invest Dermatol, 141(5):1236-1242.e1. doi: Marmol V, Marzano AV, et al. (2021). Target molecules for future 10.1016/j.jid.2020.08.032 hidradenitis suppurativa treatment. Exp Dermatol, 30 Suppl 1:8-17. doi: [6] Zouboulis CC, Tzellos T, Kyrgidis A, Jemec GBE, Bechara FG, 10.1111/exd.14338. PMID: 34085329. Giamarellos-Bourboulis EJ, et al. (2017). Development and validation of [23] Zouboulis CC et al. (2015). Hidradenitis suppurativa/acne inversa: Criteria the International Hidradenitis Suppurativa Severity Score System (IHS4), for diagnosis, severity assessment, classification and disease evaluation. a novel dynamic scoring system to assess HS severity. Br J Dermatol, Dermatology, 231:184- 90. doi: 10.1159/000431175 177(5):1401- 1409. doi: 10.1111/bjd.15748. [24] Re S, Dogan AA, Ben-Shachar D, Berger G, Werling AM, Walitza S, et al. [7] Matusiak Ł. (2020). Profound consequences of hidradenitis suppurativa: a (2018). Improved Generation of Induced Pluripotent Stem Cells From review. Br J Dermatol, 183(6): e171-e177. doi: 10.1111/bjd.16603 Hair Derived Keratinocytes - A Tool to Study Neurodevelopmental [8] Ingram JR. (2020) The epidemiology of hidradenitis suppurativa. Br J Disorders as ADHD. Front Cell Neurosci, 12:321. doi: Dermatol, 183(6):990-998. doi: 10.1111/bjd.19435 10.3389/fncel.2018.00321. [9] Saunte DM, Boer J, Stratigos A, Szepietowski JC, Hamzavi I, Kim KH, et al. (2015). Diagnostic delay in hidradenitis suppurativa is a global problem. Br J Dermatol, 173(6):1546- 9. doi: 10.1111/bjd.14038 [10] Preda-Naumescu A, Ahmed HN, Mayo TT, Yusuf N. (2021) Hidradenitis suppurativa: pathogenesis, clinical presentation, epidemiology, and comorbid associations. Int J Dermatol. doi: 10.1111/ijd.15579. Epub ahead of print. [11] Zouboulis CC, Benhadou F, Byrd AS, Chandran NS, Giamarellos- Bourboulis EJ, Fabbrocini G, et al. (2020). What causes hidradenitis suppurativa?-15 years after. Exp Dermatol, 29(12):1154-1170. doi: 10.1111/exd.14214. [12] Genovese G, Moltrasio C, Garcovich S, Marzano AV. (2020) PAPA spectrum disorders. G Ital Dermatol Venereol, 155(5):542-550. doi: 10.23736/S0392-0488.20.06629-8. 732 Disease burden of hidradenitis suppurativa and assessment of a non-invasive treatment option Esther von Stebut Department of Dermatology University of Cologne Cologne, Germany esther.von-stebut@uk-koeln.de ABSTRACT ASSESSMENT OF HS DISEASE BURDEN Hidradenitis suppurativa (HS) is a chronic inflammatory skin To contribute to the development of a validated tool for the disease of intertriginous body areas. Due to an often delayed (objective, physician-based) assessment of disease diagnosis and various symptoms, disease burden is often under severity/activity, we participated in a consensus towards the estimated. In the present work, we summarize our results development of an International HS Severity Score System obtained from several studies aiming at a better description of (IHS4) initiated by members of the European Hidradenitis disease activity and an improved assessment of patient-related Suppurativa Foundation (EHSF) [2]. Within the IHS4, a variety symptoms. of clinical signs were rated by 11 centers including and assessing Treatment options for HS are limited; treatment ranges from 236 patients. The resulting IHS4 score is arrived at by the number medical to surgical options. However, despite numerous of nodules (multiplied by 1) plus the number of abscesses treatment options for HS, efficacious and noninvasive treatment (multiplied by 2) plus the number of draining tunnels (multiplied options resulting in long-term remission and management of by 4). A total score of 3 or less signifies mild, 4-10 signifies symptoms of the disease are still needed. We present a meta- moderate and 11 or higher signifies severe disease. The IHS4 was analysis of topical treatment options and discuss the need of real developed and published in 2017 and since then, a variety of world data for estimation of treatment efficacy. studies have utilized the score to assess disease severity both in real-life, as well as within clinical trials [3]. As such, the baseline KEYWORDS IHS4 score has proven to be a meaningful predictor for Acne inversa, Hidradenitis suppurativa, human, disease burden, recurrences during adalimumab therapy of HS [3]. DLQI, treatment options, topical treatment, medical device, Using a German data base with information on ~1800 HS IHS4 patients, the patients’ quality of life (QoL) was assessed [4]. The aim of this study was to present more robust data on patients’ QoL using the Dermatology Life Quality Index (DLQI). Overall, INTRODUCTION within this large cohort, the mean DLQI was 13.2±8.1 again Hidradenitis suppurativa (HS) as a chronic inflammatory disease stressing the strong burden of HS on affected patients and a of the skin characteristically manifests in inguinal, axillary and severely impaired quality of life. QoL correlated with pain, submammary body areas. HS patient suffer severely from the disease severity as assessed by the IHS4 sore, as well as Hurley disease due to pain, stigmatization and often delayed diagnosis, score. since the disease is often misinterpreted as repeated abscesses for Pain is one of the important aspects affecting QoL in HS patients. a long time. Consultation of a dermatologist early after disease Pain was assessed by a numerical rating scale (0= no pain to 10= onset is important. severe pain) by affected HS patients (1,795 individuals) [5]. Pain Treatment of HS is often frustrating, since the options are limited. was reported by 84% of patients with the majority reporting mild Medical treatments including antibiotics, hormones, and anti- pain (78%). Interestingly, females and smokers experienced TNF ) can successfully control symptoms, but more intense pain. Pain levels correlated with the number of discontinuation is often associated with relapses. Surgical affected areas and disease severity, as expected. interventions can induce long-term symptom control, but may To gain further insights into the frequency of familial cases not be useful for all patients due to long remission times and within 1795 German patients, we performed a patient survey in scarring tissue. 4 independent, patient network-run social media platforms within Germany. Within 7 days, a cumulative number of 642 responses was acquired. Out of these responses, 249 (38%) of the 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 patients confirmed that at least one first-degree relative (parents, for profit or commercial advantage and that copies bear this notice and the full children, siblings) are also affected by the disease. This 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). complements already existing data from the literature stating Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia hereditary HS in 5-40% of cases [6]. Earlier reports described © 2021 Copyright held by the owner/author(s). hereditary HS to be more severe; studies analyzing the 733 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia von Stebut pathomechanism in these families involving gamma-secretase DISCUSSION and inflammasome activation are underway [6,7]. HS is a chronic inflammatory disease of the skin, which requires raising better awareness, good scoring tools and more TOPICAL AND DEVICE-BASED THERAPY (outpatient) treatment alternatives. Although the disease was previously treated using surgery, new treatment modalities FOR MILD HS allowing for an effective treatment of mild and moderate cases in Treatment options for HS are often unsatisfactory. We recently an ambulatory setting are currently developed. studied the effect of a combination therapy of intense pulsed light (IPL) and radiofrequency (RF). To this aim, the first study with HS appears to present as a disease with a variety of different 47 patients was performed as a prospective, monocentric, mutations and pathways involved in its pathogenesis. Assessing randomized, three-arm parallel-group design trial with a prior 12 these familial cases of HS will aid in a better understanding of weeks observation period (NICE study) [8,9]. Treatment arms the disease and open avenues for therapeutic modification. were IPL and RF monotherapies or IPL + RF combination therapy. After 12 weeks, all patients received IPL + RF for ACKNOWLEDGMENTS additional 12 weeks (cross-over). After 12 weeks, active lesion The authors would like to thank Michele Boniotto (Créteil, counts of the IPL + RF group decreased by 50% in 50% of France), Sergio Crovella, Paola Tricarico (Trieste, Italy) Mathias patients, in 33% even by 75% (Hurley I/II patients, less effective Schmuth, (Innsbruck Hautklinik, Austria), Matjaž Gams and in Hurley III) correlating with an even better improvement in Anton Gradišek (Ljubljana, Slovenia) and Vincent Flacher DLQI. A controlled follow up trial (RELIEVE study) compared (Strasbourg, France) within the ERA PerMed funded consortium topical clindamycin with topical clindamycin plus IPL + RF in BatMan for helpful discussions. 88 patients [10]. After 16 weeks of treatment, the IHS4 score was improved by 60% in the combination therapy group compared to REFERENCES 18% improvement in clindamycin-treated patients. Secondary [1] Marzano AV, et al. Evidence for a 'window of opportunity' in hidradenitis endpoints (e.g. DLQI) showed similar results. suppurativa treated with adalimumab: a retrospective, real-life multicentre cohort study. Br J Dermatol. 2021;184(1):133-140. doi: The aim of a follow-up study was to perform a meta-analysis on 10.1111/bjd.18983 [2] Zouboulis CC, Tzellos T, Kyrgidis A, et al R; Development and validation the effectiveness of local and instrument-based therapies under of the International Hidradenitis Suppurativa Severity Score System the prism of their efficacy and safety profile [11]. We thus (IHS4), a novel dynamic scoring system to assess HS severity. Br J performed a literature search and analyzed clinical evidence for Dermatol. 2017 Nov;177(5):1401-1409. doi: 10.1111/bjd.15748. [3] Chiricozzi A, Giovanardi G, Garcovich S, et al (2020) Clinical and the various therapeutic options. Effective treatments for out- ultrasonographic profile of adalimumab-treated hidradenitis suppurativa patient care of HS patients exist including topical clindamycin, patients: A real-life monocentric experience. Acta Derm Venereol 100:adv00172. resorcinol, and intralesional corticosteroids. New devices such as [4] Krajewski PK, Matusiak Ł, von Stebut E, Schultheis M, Kirschner U, LAight therapy (combining IPL with radiofrequency) are Nikolakis G, Szepietowski JC. Quality-of-Life Impairment among Patients with Hidradenitis Suppurativa: A Cross-Sectional Study of 1795 available, which can be used as monotherapy or adjunct therapy Patients. Life (Basel). 2021 Jan 8;11(1):34. doi: 10.3390/life11010034 in combination with systemic treatment and/or surgery for the [5] Krajewski PK, Matusiak Ł, von Stebut E, Schultheis M, Kirschner U, management of HS patients. All topical treatment options are Nikolakis G, Szepietowski JC. Pain in Hidradenitis Suppurativa: A Cross- sectional Study of 1,795 Patients. Acta Derm Venereol. 2021 Jan best suited for mild to moderate HS and aid to control disease 5;101(1):adv00364. doi: 10.2340/00015555-3724. activity. [6] Frew JW. Differential profiles of gamma secretase Notch signalling in hidradenitis suppurativa: the need for genotype-endotype-phenotype analysis. Br J Dermatol. 2021 Jan 9. doi: 10.1111/bjd.19805. [7] Zouboulis CC, Benhadou F, Byrd AS, et al What causes hidradenitis REQUIREMENT FOR REAL WORLD DATA suppurativa ?-15 years after. Exp Dermatol. 2020 Dec;29(12):1154-1170. doi: 10.1111/exd.14214. ON TREATMENT EFFICACY [8] Wilden S, Friis M, Tuettenberg A, Staubach-Renz P, Wegner J, Grabbe S, von Stebut E. Combined treatment of hidradenitis suppurativa with intense Publication of real world data on the results of treatment with pulsed light (IPL) and radiofrequency (RF). J Dermatolog Treat. 2021 (approved) drugs and/or medical devices is important to allow Aug;32(5):530-537. doi: 10.1080/09546634.2019.1677842. for a reasonable judgement about the efficacy of a medication, [9] Zimmer S, Basien K, von Stebut E. [Impact of LAight therapy on hidradenitis suppurativa care]. Hautarzt. 2021 Jul;72(7):586-594. doi: especially since due to the nature of controlled clinical studies 10.1007/s00105-021-04843-z. certain patient groups, who in daily clinical routine would best [10] Schultheis M, Staubach P, Nikolakis G, Grabbe S, Ruckes C, von Stebut E, Kirschner U, Matusiak L, Szepietowsk IF. LAight® therapy benefit from such new treatments, are excluded from study significantly enhances treatment efficacy of 16 weeks of topical inclusions. Real world data on the treatment of HS was clindamycin solution in Hurley I and II hidradenitis suppurativa: Results from period A of RELIEVE, a multicenter randomized, controlled trial. summarized [12]. Adalimumab, the only approved biological Dermatology 2021, manuscript accepted. treatment so far, represents a cost-efficient and effective therapy. [11] Nikolakis G, von Stebut E [Topical and novel device-based therapies for mild hidradenitis suppurativa]. Hautarzt. 2021 Aug;72(8):676-685. doi: Additional publications about real world data with high(er) 10.1007/s00105-021-04849-7. [12] Zouboulis CC, von Stebut E. Need for real-world data studies on numbers of patients, including those with different risk factors, hidradenitis suppurativa/acne inversa treatment. Hautarzt. 2021 are required. Real world data will help to really assess the Aug;72(8):700-705. doi: 10.1007/s00105-021-04847-9. developing therapeutic spectrum of HS in our daily routine. 734 An Overview of the BATMAN Platform Zdenko Vuk Jani Bizjak Erik Dovgan Department of Intelligent Systems Department of Intelligent Systems Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia zdenko.vuk@ijs.si jani.bizjak@ijs.si erik.dovgan@ijs.si Matjaž Gams Anton Gradišek Department of Intelligent Systems Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia matjaz.gams@ijs.si anton.gradisek@ijs.si ABSTRACT This paper presents an overview of the platform used in the project BATMAN. We look at the architecture and at the in- teractions between the components, namely the website, the smartphone app, and the server, and how these components are used by the medical doctors, patients and data scientists. KEYWORDS BATMAN platform, web platform, smartphone application, ques- tionnaires 1 INTRODUCTION In recent years, the use of smartphone applications related to health has expanded substantially. Smartphones and other wear- able sensors have become being daily companions for a majority of the population in developed countries. Probably the most Figure 1: The basic schema showing the interactions of the commonly-known health-related applications focus on aspects platform users with the technical components. such as exercise (i.e., fitness trackers) or nutrition and are typ- ically independent of involvement of a medical doctor. On the other hand, there is ongoing research dealing with the use of data from the wearables to assist the clinicians in improving treat- The rest of the paper is organized as follows. Section 2 presents ment of patients. An example of such research is the ERA PerMed the BATMAN platform. The smartphone application is described project BATMAN [1] that aims at improving the understanding in Section 3. Finally, Section 4 concludes the paper with summary of the chronic dermatological condition Hidradenitis Suppura- and future plans. tiva (HS), also called Acne Inversa. HS is a chronic inflammatory disease involving hair follicles that presents with painful nodules that release pus. Within the framework of the BATMAN project, 2 THE BATMAN PLATFORM AND ITS we aim in bringing together medical, genetic, experimental, and USERS lifestyle data to build a truly personalized model of each patient In this section, we present an overview of the BATMAN platform, in order to tailor specific treatments. namely how its components work and how they are used by the This paper presents the overview of the platform developed participants in the project, i.e., medical doctors, patients, and within the BATMAN project. This platform collects data from data scientists. The basic schema of the interactions is shown patients, such as answers to questionnaires, and enable doctors in Figure 1. The patient and the doctor input the patient data to follow the patient’s state and assign additional questionnaires through a website. Patients also use a smartphone app for activ- when appropriate. The gathered data are anonymized and further ity tracking. The information collected via the website and the processed by data scientists by building models for HS patients smartphone app are stored on a server where it is then available and seeking for new knowledge. to data scientists. The BATMAN platform website has a double functionality: it Permission to make digital or hard copies of part or all of this work for personal serves as the main information point about the BATMAN project or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and and it is also the entry point to the platform. Users can log in the full citation on the first page. Copyrights for third-party components of this with their usernames and passwords. Depending on their role, work must be honored. For all other uses, contact the owner/author(s). they can see different types of content. To ensure the security Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia © 2021 Copyright held by the owner/author(s). and to prevent any unauthorized access, the user accounts are created by the platform administrators and assigned to users. 735 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Zdenko Vuk, Jani Bizjak, Erik Dovgan, Matjaž Gams, and Anton Gradišek Figure 3: User interface for editing a questionnaire. Figure 2: Online form for doctors to upload the patient’s EHRs. 2.1 Doctors Medical doctors can view and manage the patients’ files. They are also able to manually upload the patients’ medical records (see Figure 2). If convenient, patients can be assigned to different groups. The doctors have the possibility to create new question- naires (see Figure 3) and to assign questionnaires to their patients (see Figure 4). There are three types of general questionnaires: • Major Depression Inventory • Dermatology Quality of Life • Food preferences The food preferences questionnaire has been split to several forms with a small number of questions since the list of food preferences includes around 200 items, which makes it tiresome for the patient to fill in one sitting. Figure 4: User interface for assigning questionnaires. Depending on the preferences, each questionnaire can be as- signed to a patient more than once, which is relevant especially for the Depression and Quality of life questionnaires. On the other hand, the food preferences typically do not change frequently thus this questionnaire can be assigned only once. The doctor gets the list of available user accounts for patients from the administrator. Then the doctor then assigns accounts to patients. This procedure enables us to keep the identity of the patients anonymous for all other participants. 2.2 Patients Figure 5: Patient’s view of the platform to see the com- Each patient obtains the user account information from his/her pleted part of the food preferences questionnaire. medical doctor. Patients interact with the platform either through the website or via the smartphone application. On the website, they can view their data (see, for example, Figure 5) and they can also use it as the interface with which they can fill in the 2.3 Data Scientists questionnaires. In addition, they can also fill in the question- Data scientist can access all the data that the medical doctors naires through the smartphone application, which we describe and the patients enter into the platform. The data available to in Section 3. the data scientists is anonymized. 736 An Overview of the BATMAN Platform Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Figure 6: Login dialog and home screen of the smartphone Figure 7: Questionnaire menu and an example of a ques- application. The home screen shows the summary of daily tionnaire, in this case the Dermatology Quality of Life. activities and the pending questionnaires. The data is currently being collected in the pilot study and will be then used to build models for HS patients and to seek for new knowledge. 2.4 Administrators The highest level of access belongs to the administrator. Regard- ing the platform functionality, the administrator can access pages for managing users, groups, and for making changes on ques- tionnaires. 3 SMARTPHONE APPLICATION The smartphone application is available for Android-based phones only. It can be accessed through Play Store [2], or found with search for “Biomolecular Analyses for Tailored Medicine”. Patients log in the smartphone application using the same Figure 8: Example of the data that the smartphone appli- account as to the platform. The login and home screen for a cation sends to the server. sample patient are shown in Figure 6. There are two main functionalities of the smartphone appli- cation: to monitor the daily activity of the patient, and to help In order to keep the application transparent to the users, the them to fill in the questionnaire, which is likely easier on the patients can access the data log showing all information that smartphone than requiring to log in to a separate website just the application has communicated to the server (see Figure 8). for that purpose. Additional functionality of the application is a pedometer, which The application uses the Google Fit [3] plug-in to trace the pa- allows the user to track steps when activated (as opposed to the tient’s steps and calories burned. The activity summary updates integrated step counter that tracks the steps during the entire in real time based on the patient’s activity. The collected daily day). activity serves as a reasonable proxy for the patient’s wellbeing, e.g., if the HS condition is bad at a given time, the patient is likely 4 CONCLUSION to move less because of the pain, while if the patient starts mov- In this paper, we presented an overview of the components of the ing more after a treatment, this likely implies that the treatment BATMAN platform. The platform is currently used to collect the has been successful. heterogeneous patient data, including medical, genetic, activity, As for the questionnaires, the application allows the patient and self-reported data. to easily fill in the forms using the screen. An example of the In the last stage of the project, the collected data will allow us questionnaire is shown in Figure 7. to find novel knowledge about the patients suffering from HS and 737 Information Society 2021, 4–8 October 2021, Ljubljana, Slovenia Zdenko Vuk, Jani Bizjak, Erik Dovgan, Matjaž Gams, and Anton Gradišek will allow the doctors to create personalized treatments that could Science, and Sport (MIZŠ). We would also like to thank the stu- turn out to be more effective. This will be specially supported dents who participated in the project. by the data scientists who will develop AI-based approaches for automatic knowledge extraction. REFERENCES [1] Batman project’s website. 2021. https://batman-project.eu/ ACKNOWLEDGMENTS en. The authors acknowledge the funding from the ERA PerMed [2] Batman app on Google Play Store. 2021. https://play.google. project BATMAN, contract number C3330-20-252001. On Slove- com/store/apps/details?id=si.ijs.batman&hl=en. nian side, the project is funded by the Ministry of Education, [3] Google Fit. 2021. https://developers.google.com/fit. 738 Indeks avtorjev / Author index Albreht Jaka ............................................................................................................................................................................... 455 Andonovic Viktor ........................................................................................................................................................................... 7 Andova Andrejaana ...................................................................................................................................................................... 11 Anželj Gregor ............................................................................................................................................................................... 27 Arduino Alessandro...................................................................................................................................................................... 19 Baggia Alenka ............................................................................................................................................................................ 516 Bajraktari Fadil ........................................................................................................................................................................... 383 Balantič Branka .......................................................................................................................................................................... 460 Balantič Zvone ........................................................................................................................................................................... 460 Batagelj Borut .............................................................................................................................................................................. 27 Batagelj Tadeja ........................................................................................................................................................................... 464 Batagelj Vladimir ....................................................................................................................................................................... 683 Behrmani Sami ........................................................................................................................................................................... 383 Bele Klemen ............................................................................................................................................................................... 213 Beliga Slobodan ......................................................................................................................................................................... 155 Belšak Rok ................................................................................................................................................................................. 432 Berbić Selma ................................................................................................................................................................................ 63 Berce Jelka ................................................................................................................................................................................. 468 Bertalanič Blaž ........................................................................................................................................................................... 187 Bilbao Sonia ....................................................................................................................................................................... 650, 658 Bizjak Jani .................................................................................................................................................................................. 735 Blatnik Robert ............................................................................................................................................................................ 265 Blatnik Živa ................................................................................................................................................................................ 472 Boniotto Michele ........................................................................................................................................................................ 727 Boshkoska Biljana Mileva.............................................................................................................................................................. 7 Boškoski Pavle ............................................................................................................................................................................... 7 Bošnjak Igor ............................................................................................................................................................................... 299 Boštic Matjaž ............................................................................................................................................................................... 23 Bottauscio Oriano ......................................................................................................................................................................... 19 Boufenghour Wacym ................................................................................................................................................................. 725 Bovcon Narvika ........................................................................................................................................................................... 27 Brandão Lucas .................................................................................................................................................................... 195, 721 Brank Janez ................................................................................................................................................................................ 119 Bratko Ivan ................................................................................................................................................................................. 692 Bregant Janez ............................................................................................................................................................................... 99 Brglez Mojca .............................................................................................................................................................................. 151 Buhin Pandur Maja..................................................................................................................................................................... 155 Callari Roberto ........................................................................................................................................................................... 638 Campos Sergio ................................................................................................................................................................... 646, 650 Canzonieri Vincenzo .................................................................................................................................................................. 199 Caporusso Jaya ............................................................................................................................................................................. 68 Casals del Busto Ignacio ............................................................................................................................................................ 163 Celesti Antonio ........................................................................................................................................................................... 638 Čepar Drago ............................................................................................................................................................................... 387 Cerar Gregor ............................................................................................................................................................................... 187 Cergolj Vincent ............................................................................................................................................................................ 15 Černe Jaša..................................................................................................................................................................................... 63 Cigale Matej ............................................................................................................................................................................... 242 Ciulla Giuseppe .................................................................................................................................................. 631, 638, 658, 674 Colosi Mario ............................................................................................................................................................................... 638 Costa Joao .................................................................................................................................................................................. 171 Crovella Sergio ................................................................................................................................................................... 195, 721 Ćudić Bojan ................................................................................................................................................................................ 276 Dam Paulien ............................................................................................................................................................................... 183 De Masi Carlo M. ................................................................................................................................................................. 15, 242 Dedić Remzo .............................................................................................................................................................................. 299 739 Delovec Urška ............................................................................................................................................................................ 476 Di Bernardo Roberto .......................................................................................................................................................... 631, 638 Divjak Saša ................................................................................................................................................................................. 696 Dobša Jasminka .......................................................................................................................................................................... 155 Dolenc Tomi ............................................................................................................................................................................... 706 dos Santos Silva Carlos André ................................................................................................................................................... 721 Dovgan Erik ............................................................................................................... 202, 213, 228, 242, 654, 662, 666, 670, 735 Eržen Samo ................................................................................................................................................................................ 210 Eržin Eva .................................................................................................................................................................................... 163 Erznožnik Matic ......................................................................................................................................................................... 167 Etxaniz Iñaki .............................................................................................................................................................................. 674 Farahmand Shabnam .................................................................................................................................................. 631, 635, 646 Farčnik Daša ............................................................................................................................................................... 390, 394, 405 Fazio Maria ................................................................................................................................................................................ 638 Filipič Bogdan ........................................................................................................................................................................ 11, 51 Flacher Vincent .......................................................................................................................................................................... 725 Fortuna Blaž ....................................................................................................................................................................... 159, 183 Fortuna Carolina ......................................................................................................................................................................... 187 Fric Urška ................................................................................................................................................................................... 265 Ftičar Jure ........................................................................................................................................................................... 291, 416 Gams Matjaž ................................................. 80, 202, 206, 213, 221, 228, 232, 236, 242, 412, 440, 654, 662, 666, 670, 702, 735 Garcia David ................................................................................................................................................................................ 84 Genovese Giovanni .................................................................................................................................................................... 730 Gerlero Virginia ......................................................................................................................................................................... 199 Gil Raquel .................................................................................................................................................................................. 646 Golob Ožbej ................................................................................................................................................................................. 19 Gotlih Janez ................................................................................................................................................................................ 432 Gradišek Anton .................................................................................................................................................................. 242, 735 Gratton Rossella ................................................................................................................................................................. 195, 721 Grobelnik Marko ........................................................................................................................................................ 119, 123, 163 Grof Nataša ................................................................................................................................................................................ 103 Guček Alenka ............................................................................................................................................................................. 163 Hafner Izidor .............................................................................................................................................................................. 688 Hudi Primož ............................................................................................................................................................................... 479 Ilijaš Tomi .................................................................................................................................................................................. 210 Istenič Tanja ............................................................................................................................................................... 390, 394, 405 Janko Vito .................................................................................................................................................................... 23, 232, 242 Jelenčič Jakob ............................................................................................................................................................................. 175 Jereb Eva .................................................................................................................................................................................... 606 Jerina Tamara ............................................................................................................................................................................. 483 Jerman Urša ................................................................................................................................................................................ 486 Jovanović Marko ........................................................................................................................................................................ 435 Kalabakov Stefan ....................................................................................................................................................................... 440 Kalan Mateja ................................................................................................................................................................................ 63 Kapun Žan .................................................................................................................................................................................. 491 Karanjac Blanka ......................................................................................................................................................................... 497 Karner Timi ................................................................................................................................................................................ 432 Kasesnik Karin ........................................................................................................................................................................... 397 Kavaš Matic ................................................................................................................................................................................. 55 Kelly Seamus ............................................................................................................................................................................. 611 Kenda Klemen .................................................................................................................................................................... 167, 171 Klanjšek Gunde Marta ............................................................................................................................................................... 295 Klemen Sonja ............................................................................................................................................................................. 502 Kljajić Borštnar Mirjana ............................................................................................................................................................. 611 Klun Urša ................................................................................................................................................................................... 221 Knez Jožica ................................................................................................................................................................................ 506 Kocman David ................................................................................................................................................................... 291, 416 Kocuvan Primož ................................................................................................................................................. 202, 206, 213, 221 Kokelj Martina ........................................................................................................................................................................... 509 Kolar Žiga .................................................................................................................................................................................. 228 740 Kolenik Tine ......................................................................................................................................................................... 68, 221 Komarova Nadezhda .................................................................................................................................................................... 27 Kordeš Urban ............................................................................................................................................................................... 63 Kožuh Ines ................................................................................................................................................................................. 491 Kralj Novak Petra ......................................................................................................................................................................... 31 Krapež Alenka ............................................................................................................................................................................ 710 Kušar Luka ................................................................................................................................................................................. 513 Lajovic Iztok .............................................................................................................................................................................. 692 Laña Ibai..................................................................................................................................................................................... 646 Larrañaga Urrotz ........................................................................................................................................................................ 646 Lazaro Gonzalo .......................................................................................................................................................................... 658 Leban Marijan ............................................................................................................................................................................ 259 Leskovar Kristina ....................................................................................................................................................................... 523 Leskovar Robert ......................................................................................................................................................................... 516 Lindemann David ....................................................................................................................................................................... 147 Lipič Karel ................................................................................................................................................................................. 421 López Maria José ............................................................................................................................................................... 650, 674 Lorbek Ivančič Dan .................................................................................................................................................................... 187 Lukan Junoš ................................................................................................................................................................................. 23 Luštrek Mitja .......................................................................................................................................................... 15, 39, 232, 242 Lutman Tomaž ........................................................................................................................................................................... 303 Macur Mirna ....................................................................................................................................................................... 408, 579 Malačič Janez ............................................................................................................................................................................. 400 Marinko Anže ....................................................................................................................................................................... 80, 440 Marinko Matej ............................................................................................................................................................................ 242 Martella Francesco ............................................................................................................................................................. 631, 638 Martorana Marco ........................................................................................................................................................................ 638 Marzano Angelo ......................................................................................................................................................................... 730 Massri M.Besher ................................................................................................................................................................ 119, 163 Matar Rola .................................................................................................................................................................................. 727 Matranga Isabel .......................................................................................................................................................................... 631 Meiners Fritz .............................................................................................................................................................................. 658 Meštrović Ana ............................................................................................................................................................................ 155 Metzler Hannah ............................................................................................................................................................................ 84 Mihić Zidar Lucija ....................................................................................................................................................................... 63 Miljković Mateja ........................................................................................................................................................................ 526 Mladenić Dunja .......................................................................................................................... 119, 123, 135, 143, 159, 175, 183 Mladenic Grobelnik Adrian........................................................................................................................................................ 123 Mlinar Biček Polona ................................................................................................................................................................... 530 Mocanu Iulian ............................................................................................................................................................................ 163 Močnik Alenka ........................................................................................................................................................................... 534 Moltrasio Chiara ......................................................................................................................................................................... 730 Motnikar Lenart............................................................................................................................................................................ 84 Moura Ronald ..................................................................................................................................................................... 195, 721 Nait-Meddour Cecile .................................................................................................................................................................. 727 Nediževec Martina ..................................................................................................................................................................... 538 Neumann Matej .......................................................................................................................................................................... 179 Novak Erik ................................................................................................................................................................................. 127 Novak Rok ................................................................................................................................................................................. 416 Novalija Inna ...................................................................................................................................................................... 119, 163 Noveski Gjorgji .......................................................................................................................................................................... 225 Odić Duško ................................................................................................................................................................................. 277 Olabarrieta Ignacio ..................................................................................................................................................................... 646 Ozvatič Jure ................................................................................................................................................................................ 542 Pajnik Tina ................................................................................................................................................................................. 546 Pal Levin ............................................................................................................................................................................ 269, 287 Palčič Devid ............................................................................................................................................................................... 217 Parrino Giovanni ................................................................................................................................................................ 631, 638 Pelicon Andraž ............................................................................................................................................................................. 31 Perša Tomi ................................................................................................................................................................................. 491 741 Petkovšek Gal ............................................................................................................................................................................. 167 Pita Costa Joao ................................................................................................................................................................... 163, 171 Pivec Franci ........................................................................................................................................................................ 444, 699 Planinc Luka ............................................................................................................................................................................... 550 Plementaš Ana Marija ................................................................................................................................................................ 109 Podobnik France ......................................................................................................................................................................... 287 Pollak Senja ........................................................................................................................................................................ 139, 151 Posedel Golob Karmen ............................................................................................................................................................... 555 Posinković Matej ........................................................................................................................................................................ 163 Poštuvan Tim ............................................................................................................................................................................. 159 Pranjić Marko ............................................................................................................................................................................. 139 Prašnikar Andrej ......................................................................................................................................................................... 559 Pratneker Miha ................................................................................................................................................................... 291, 416 Prybylski Maxim ........................................................................................................................................................................ 308 Puc Jernej ..................................................................................................................................................................................... 35 Rajkovič Uroš ............................................................................................................................................................................. 618 Rajkovič Vladislav ..................................................................................................................................................................... 692 Ravničan Jože ............................................................................................................................................................................. 440 Ražman Simon ........................................................................................................................................................................... 217 Rečnik Ivan ................................................................................................................................................................................ 435 Redek Tjaša ................................................................................................................................................................................ 390 Rehberger Roman ............................................................................................................................................................... 562, 566 Reščič Nina .................................................................................................................................................................. 39, 232, 242 Rizzolio Flavio ........................................................................................................................................................................... 199 Robinson Johanna A. .................................................................................................................................................................. 416 Robnik-Šikonja Marko ................................................................................................................................................. 55, 131, 139 Rogelj Aljaž ............................................................................................................................................................................... 587 Romih Dejan .............................................................................................................................................................................. 424 Rossi Maurizio ........................................................................................................................................................................... 163 Rožanec Jože M. ................................................................................................................................................................ 159, 183 Sadikov Aleksander................................................................................................................................................................ 19, 35 Sajko Klemen ............................................................................................................................................................................. 491 Saksida Amanda ........................................................................................................................................................................... 89 Sambt Jože ................................................................................................................................................................. 390, 394, 405 Schwabe Daniel .......................................................................................................................................................................... 119 Šebenik Tina ............................................................................................................................................................................... 590 Šerbec Anja .................................................................................................................................................................................. 93 Šercar M. Tvrtko ........................................................................................................................................................................ 444 Šifrer Robert ............................................................................................................................................................................... 592 Simčič Petra ............................................................................................................................................................................... 574 Sittar Abdul ................................................................................................................................................................................ 143 Škrlj Blaž ...................................................................................................................................................................................... 31 Škrlj Gregor ................................................................................................................................................................................ 597 Slapničar Gašper .......................................................................................................................................................................... 23 Slivšek Uršek ............................................................................................................................................................................... 63 Smerkol Maj ....................................................................................................................................................... 654, 662, 666, 670 Snijders Rosalie .......................................................................................................................................................................... 642 Solina Franc ......................................................................................................................................................................... 27, 712 Stankoski Simon ........................................................................................................................................................................... 15 Stepišnik Perdih Tjaša ........................................................................................................................................................ 408, 579 Stojkič Željko ............................................................................................................................................................................. 299 Stres Špela .................................................................................................................................. 259, 265, 269, 276, 277, 282, 287 Strgar Sonja ................................................................................................................................................................................ 583 Strnad Marjan ............................................................................................................................................................................. 217 Strniša Gašper ............................................................................................................................................................................ 587 Strniša Iva................................................................................................................................................................................... 587 Šturm Jan .................................................................................................................................................................................... 163 Sulajkovska Miljana ........................................................................................................................................... 654, 662, 666, 670 Susič David ............................................................................................................................................................ 43, 80, 236, 242 Swati ........................................................................................................................................................................................... 135 742 Todorović Tadej ........................................................................................................................................................................... 99 Tomšič Janez .............................................................................................................................................................................. 236 Toporišič Gašperšič Manca ........................................................................................................................................................ 103 Trajkova Elena ........................................................................................................................................................................... 183 Tricarico Paola Maura ........................................................................................................................................................ 195, 721 Trobec Marjeta ................................................................................................................................................................... 269, 282 Trpin Alenka ................................................................................................................................................................................ 47 Trpin Borut ................................................................................................................................................................................. 109 Truccolo Ivana ........................................................................................................................................................................... 199 Tušar Tea ...................................................................................................................................................................... 51, 232, 242 Ulčar Matej ................................................................................................................................................................................. 131 Urankar Patricija ........................................................................................................................................................................ 601 Urh Marko .................................................................................................................................................................................. 606 Uspenski Aliaksei ....................................................................................................................................................................... 308 Uspenskiy Alexander ................................................................................................................................................................. 308 Valič Jakob ......................................................................................................................................................................... 206, 225 van Loon Nathalie ...................................................................................................................................................................... 642 Villari Massimo .......................................................................................................................................................................... 638 Vintar Špela ................................................................................................................................................................................ 151 Viršček Andrej ........................................................................................................................................................................... 405 Vodopija Aljoša ................................................................................................................................................................... 51, 242 von Stebut Esther ....................................................................................................................................................................... 733 Vovk Ana ................................................................................................................................................................................... 429 Vrabec Tina ................................................................................................................................................................................ 416 Vrban Rok .................................................................................................................................................................................. 611 Vučko Tadeja ............................................................................................................................................................................. 614 Vuk Zdenko ........................................................................................................................................................................ 228, 735 Vukomanović Marija .................................................................................................................................................................. 303 Werber Borut .............................................................................................................................................................................. 618 Žagar Aleš .................................................................................................................................................................................... 55 Žaucer Maša ................................................................................................................................................................................. 80 Ženko Bernard .............................................................................................................................................................................. 47 Žerjal Samo ................................................................................................................................................................................ 624 Zilberti Luca ................................................................................................................................................................................. 19 Žunič Vojka ................................................................................................................................................................................ 295 743 744 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 Delavnica projekta Insieme Insieme Project Workshop 14. mednarodna konferenca o prenosu tehnologij 14th International Technology Transfer Conference Ljudje in okolje People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society Delavnica URBANITE 2021 URBANITE Workshop 2021 50-letnica poučevanja računalništva v slovenskih srednjih šolah 50th Anniversary of Teaching Computer Science in Slovenian Secondary Schools Delavnica projekta BATMAN BATMAN Project Workshop Uredniki • Editors: Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Borut Trpin, Maša Rebernik, Olga Markič, Dunja Mladenić, Marko Grobelnik, Primož Kocuvan, Flavio Rizzolio, Špela Stres, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Sergio Campos, Shabnam Farahmand, Nathalie van Loon, Erik Dovgan, Saša Divjak, Alenka Krapež, Sergio Crovella, Anton Gradišek Document Outline IS2021_Complete - do J IS2021_Complete - do I IS2021_Complete - do H IS2021_Complete - do G IS2021_Complete - do F IS2021_Complete - do E IS2021_Complete - do D IS2021_Complete - do C IS2021_Complete - do 02 IS2021_Complete Naslovnica-sprednja-ALL 02 - Naslovnica - notranja - ALL 03 - Kolofon - All 04 - IS2021 - Predgovor 05 - IS2021 - Konferencni odbori 07 - Kazalo - ALL IS2021_Volume_A 02 - Naslovnica - notranja - A - TEMP 03 - Kolofon - A - TEMP 04 - IS2021 - Predgovor - TEMP 05 - IS2021 - Konferencni odbori 07 - Kazalo - A 08 - Naslovnica - notranja - A - TEMP 09 - Predgovor podkonference - A 10 - Programski odbor podkonference - A AndonovicEtal Andova+Filipic Abstract 1 Introduction 2 Evolutionary Multitasking 2.1 Assortative Mating 2.2 Selective Imitation 2.3 Landscape Analysis 3 Experiments and results 3.1 Multitask Optimization 3.2 Many-Task Optimization 4 Conclusion and future work 5 Acknowledgments DeMasiEtal Abstract 1 Introduction 2 Related Work 2.1 Drinking Detection From Wearables 2.2 Activity Recognition From Videos 3 Adopted Hardware 3.1 Wristband 3.2 Local Deployment of The Computer Vision System 4 Intent Recognition 4.1 Regions of Interest 4.2 Intent Recognition 4.3 Drinking Detection From Computer Vision on the Jetson NANO 4.4 Drinking Detection Using a Wearable device 5 Results and Discussion 5.1 Intent Recognition and Local Implementation of Drinking Detection 5.2 Wearable Sensing Results 6 Conclusions GolobEtal Abstract 1 Introduction 2 Methods 2.1 Data Acquisition 2.2 Reconstruction Techniques 2.3 Anomaly Detection 3 Results 4 Discussion and Conclusions Acknowledgments JankoEtal Abstract 1 Introduction 2 Library Functionalities 2.1 Motion Sensors Features 2.2 Physiological Features 2.3 Other Functionalities 3 Usage Example 3.1 SHL Dataset 3.2 Methods 3.3 Results 4 Conclusion Acknowledgments KomarovaEtal Abstract 1 Uvod in motivacija 2 Slikovni prostor na umetniških slikah 3 Zaznava obrazov 4 Geometrijska interpretacija prostora 5 Rezultati 6 Razprava 7 Zaključek PeliconEtal Abstract 1 Introduction 2 Data 2.1 Annotation Schema 2.2 Sampling for Training and Evaluation 2.3 Annotation Procedure 3 Experiments 3.1 autoBOT - an autoML for texts 3.2 Deep Learning 3.3 Other Baseline Approaches 4 Results 5 Conclusion Puc+Sadikov Abstract 1 Introduction 2 Related work 3 The SDG Environment 3.1 Description 3.2 Observations 3.3 Actions 3.4 Execution 3.5 Online Play 3.6 Replay System 4 Supervised Learning Baseline 4.1 Agent Model Architecture 4.2 Imitation Learning 4.3 Demonstrations 4.4 Results 5 Conclusions & Future Work Rescic+Lustrek Abstract 1 Introduction 2 Methodology 2.1 Problem outline 2.2 Dataset 2.3 Feature ranking 3 Results 3.1 Classification problem 3.2 Regression problem 3.3 Discussion 4 Conclusion and future work Acknowledgments Susic Abstract 1 Introduction 2 Data description and preparation 3 Methods and models 3.1 Country-Specific Approach 3.2 Time-Series Approach 4 Models' parameters selection 5 Results 6 Conclusion Trpin+Ženko VodopijaEtal Abstract 1 Introduction 2 Theoretical Background 3 Methodology 3.1 ELA Features 3.2 Dimensionality Reduction with t-SNE 4 Experimental Setup 5 Results and Discussion 6 Conclusions Acknowledgments ŽagarEtal Abstract 1 Introduction 2 Updates: KAS 2.0 and KAS-Abs 2.0 2.1 Extraction of Text Body 2.2 Extraction of Abstracts 2.3 Differences from Version 1.0 to 2.0 3 Sub-CERIF classification 4 New datasets 4.1 Summarization Datasets 4.2 Machine Translation Datasets 5 Conclusions Acknowledgments 12 - Index - A Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page 02 - Naslovnica - notranja - B 09 - Predgovor podkonference - B 10 - Programski odbor podkonference - B 01 - Černeetal 02 - Koleniketal 03 - Marinko et al._COGSCI21_paper_6 Abstract 1 INTRODUCTION 2 RELATED WORK 3 ESTIMATING THE LONGEVITY OF HUMAN CIVILIZATION WITH SANDBERG AND RARE EARTH MODEL 3.1 SANDBERG MODEL 3.2 RARE EARTH MODEL 4 EXPERIMENTS 4.1 Issues with log-uniform distribution 4.2 Parameter importance 5 DISCUSSION AND CONCLUSION Acknowledgments 04 - Motnikaretal 05 - Saksida 06 - Šerbec_COGSCI21_paper_3 07 - Todorovicetal 08 - Toporisicetal 09 - Trpinetal Blank Page Blank Page 02 - Naslovnica - notranja - C 09 - Predgovor podkonference - C 10 - Programski odbor podkonference - C 01 - Novalijaetal 02 - MladenicEtal 03 - Novak Abstract 1 Introduction 2 Related Work 3 The Clustering Algorithm 3.1 Article Representation 3.2 Event Representations 3.3 Assignment Condition 4 Experiments 4.1 Data Set 4.2 Evaluation Metrics 4.3 Baseline Algorithm 5 Results 6 Conclusion Acknowledgments 04 - Ulcar+Robnik Abstract 1 Introduction 2 Related work 3 SloBERTa 3.1 Datasets 3.2 Data preprocessing 3.3 Architecture and training 4 Evaluation 5 Conclusions Acknowledgments 05 - Swati+Mladenic Abstract 1 Introduction 1.1 Contributions 2 Related Work 3 Data Description 3.1 Raw Data Source 3.2 Dataset 4 Materials and Methods 4.1 Methodology 5 Results and Analysis 5.1 Impact of news categories 6 Conclusions and Future Work 7 Acknowledgments 06 - Pranjicetal Abstract 1 Introduction 2 Dataset 3 Methodology 3.1 Doc2Vec 3.2 BERT 3.3 Prediction network 3.4 Training 4 Experiments and results 4.1 Evaluation metrics 4.2 Results and discussion 5 Conclusions and Further Work Acknowledgments 07 - Sittar+Mladenic Abstract 1 Introduction 2 Related Work 3 Data Description 3.1 Dataset Statistics 4 Material and Methods 4.1 Problem Definition 4.2 Methodology 5 Experimental Evaluation 5.1 Evaluation Metric 6 Results and Analysis 6.1 Annotation Results 6.2 Classification Results 7 Conclusions and Future Work 08 - LindemannDavid Abstract 1 Introduction 2 LexBib Zotero group 3 LexBib Wikibase 3.1 Wikibase as LOD infrastructure solution 3.2 Zotero to Wikibase migration 3.3 Entity disambiguation using Open Refine 3.4 Full text processing 4 Wikibase to Elexifinder 5 Conclusions and Outlook Acknowledgments 09 - Brglezetal Abstract 1 Introduction 2 Proposed approach 2.1 Method 3 Corpus 3.1 Corpus search 4 Analysing different parameter settings 5 Conclusion Acknowledgments 10 - Panduretal 11 - Rožanecetal Abstract 1 Introduction 2 Related Work 3 Use Case 4 Methodology 5 Results and Analysis 6 Conclusion Acknowledgments References 12 - Costaetal 13 - Petkovšeketal Introduction Data and Data Preprocessing Methodology Evaluation of algorithms GAN DBSCAN Welford's algorithm Facebook Prophet Results Conclusions Acknowledgments References 14 - Costaetal_2 Abstract 1 Introduction 2 Stationary and Chaotic Nature 2.1 Dickey-Fuller Test for Stationarity 2.2 Lyapunov exponents for understanding chaotic nature 3 Maximum Predictability 4 Model Architecture 4.1 LSTM 4.2 Our approach 5 Forecasting 5.1 Forecasting Methods 5.2 Our Approach 6 Research Methods 6.1 Time Series Reconstruction 6.2 Entropy Calculation 6.3 Data and Code Git Repository 7 Plot of results 8 Conclusion 9 Acknowledgments 15 - Jelencic+Mladenic Introduction Data Proposed method Empirical normalization Noise addition Optimization of latent representation Results Unsupervised learning results Supervised learning results Conclusions and future work Acknowledgments References 16 - Neumann+Grobelnik 17 - Trajkovaetal Abstract 1 Introduction 2 Related Work 3 Use Case 4 Methodology 5 Results and Analysis 6 Conclusion Acknowledgments References 18 - Ivancicetal Blank Page 02 - Naslovnica - notranja - D 09 - Predgovor podkonference - D 10 - Programski odbor podkonference - D 01 - Brandao 02 - Truccolo 03 - Kocuvan_2-final Abstract 1 Introduction 2 An overview of Existing EMH Platforms 2.1 Genoa 2.2 DigiGone 2.3 Doxy.me 2.4 eVisit 2.5 iPath 2.6 MedSymphony 2.7 Bodi Zdrav 2.8 EcoSmart 3 The ISE-EMH platform 3.1 Basic Information 3.2 Detailed Description of the ISE-EMH Platform 4 Analytical Comparison 4.1 Choosing the Features for Comparison 4.2 Results of the Analytical Comparison 5 Empirical Comparison of Simply Accessible Platforms 5.1 Bodi Zdrav User Experience 5.2 EcoSmart User Experience 5.3 ISE-EMH User Experience 6 Conclusion Acknowledgments 04 - Kocuvan Abstract 1 Introduction 1.1 Basic information about the project 1.2 Chosen Android OS and programming language 1.3 Overview of the functions 2 The initial screen 3 The elder's home view and functions 3.1 Sandbox 3.2 Battery 3.3 Mobile phone location and vocal search 3.4 Alarms and reminders 3.5 SOS function and fall detection 3.6 Phone book and pedometer 4 The caretaker view and functions 4.1 Sandbox 4.2 Battery 4.3 Mobile phone location and vocal search 4.4 Alarms and reminders 4.5 SOS function and fall detection 4.6 Phone book and pedometer 5 Conclusion Acknowledgments 05 - Erzen - cakamo 06 - Bele 07 - Palcic - cakamo 08 - Kolenik 09 - Noveski Abstract 1 Introduction 2 Experiment 3 Conclusion Acknowledgments 10 - Kolar Abstract 1 Introduction 2 Methodology for AHA Solution Assessment 2.1 Main objectives 2.2 Methodology 2.3 Platforms 3 Clustering and taxonomies 3.1 K-means clustering 3.2 Hierarchical clustering 3.3 Taxonomies 4 Conclusion and discussion Acknowledgments 11 - Janko Abstract 1 Introduction 2 Dataset 3 Methods 4 Results 5 Discussion and Conclusions 12 - Tomsic Abstract 1 Introduction 2 Methodology 2.1 Selection of articles 2.2 Articles not based on OxCGRT data 2.3 Ranking effectiveness of NPIs 2.4 Comparison with a similar article 3 Results 3.1 Assessed regions and time frames 3.2 Metrics used in studies 3.3 NPI effectiveness estimations 4 Conclusion 13 - Lustrek Blank Page Blank Page 08 - Naslovnica - notranja - E 09 - Predgovor podkonference - E 10 - Programski odbor podkonference - E 01 - Leban et al. - CEETT platform 02 - Fric et al. - Software Protection and Licensing Challenges in Europe 03 - Stres et al. (dodana avtorja) - European Guiding principles 04 - Cudic (skrajšano) - Digital Innovation Hubs Digital Innovation Hubs and Regional Development: 05 - Odic et al. - EU projects 06 - Trobec et al. - Proof of Concept cases 07 - Pal et al. - European Industrial Strategy 08 - Ftičar et al. - Knowledge generation in citizen science project 09 - Žunič et al. - Overview of National Sources 10 - Bosnjak et al. - Application of 3D printing, reverse engineering and metrology 11 - Lutman et al. - Towards the Market 12 - Uspenskiy et al. - Technology transfer in Belarus Zbornik_14ITTC_DODATEK_V3_avtorizacije_10_11_2021_cistopis - ML Blank Page Blank Page 02 - Naslovnica - notranja - F 09 - Predgovor podkonference - F 10 - Programski odbor podkonference - F 01 - BehramiBajraktari---final 02 - Čepar_popravljena 03 - Farčnik,Istenič,Sambt,Redek_IS2021 04 - IstenicSambtFarcnik_IS2021 05 - KKasesnik-IS2021_final-7 06 - Malacic-popravljena 07 - SambtIstenicFarcnik_IJS2021_CameraReady 08 - StepisnikPerdih 09 - GamsMatjaz 10 - Kocman-et-al 11- Lipič 12 - Romih-lektorirano 13 - Vovk 14 - Belsak_Karner_Gotlih 15 - Jovanovic 16 - Kalabakov Abstract 1 Introduction 2 Problem definition 3 Data collection 3.1 Data generation 4 Method 5 Results 6 Conclusions Acknowledgments 17 - Pivec+Šercar-fin Blank Page Blank Page Blank Page 02 - Naslovnica - notranja - G 09 - Predgovor podkonference - G 10 - Programski odbor podkonference - G ! Prispevki Albreht Balantic Balantic Batagelj Berce Blatnik Delovec 1. UVOD 2. UČNO ORODJE LIVEWORKSHEETS 3. TIPI NALOG 3.1 Dopiši ustrezen odgovor ('gap fill') 3.2 Izbirni tip s spustnim menijem ('drop down select box') 3.3 Izbirni tip ('multiple choice exercise') 3.4 Povezovanje parov ('join with arrows') 3.5 Povleci na ustrezno mesto ('drag and drop') 3.6 Ostale možnosti 4. REŠEVANJE NALOG IN POVRATNA INFORMACIJA 5. ZAKLJUČEK 6. VIRI Hudi Jerina Jerman Kapun et al Karanjac Klemen Knez Trenutni in sodobni čas od nas zahteva, da se vsi učitelji prilagajamo, sledimo novim spremembam, se prilagajamo in ves čas evalviramo svoje delo in načrtujemo kako napredovati pri svojem delu. Gledati moramo, da delamo kakovostno in da to pomeni, da ... Že v učnem načrtu je s splošnimi cilji opredeljen pouk in namen poučevanja matematike. [1] Učenci pri pouku matematike: • razvijajo matematično mišljenje: abstraktno-logično mišljenje in geometrijske predstave; • oblikujejo matematične pojme, strukture, veščine in procese ter povezujejo znanje znotraj matematike in tudi širše; • razvijajo uporabo različnih matematičnih postopkov in tehnologij; • spoznavajo uporabnost matematike v vsakdanjem življenju; • spoznavajo matematiko kot proces ter se učijo ustvarjalnosti in natančnosti; • razvijajo zaupanje v lastne (matematične) sposobnosti, odgovornost in pozitiven odnos do dela in matematike; • spoznavajo pomen matematike kot univerzalnega jezika; • sprejemajo in doživljajo matematiko kot kulturno vrednoto. 4.1 Video posnetki 4.2 Open Board 4.3 Smart Notebook Ravnilo - geotrikotnik Šestilo Snemalnik Kokelj Kušar - original Leskovar Baggia Leskovar Miljković MlinarBiček Močnik 1 UVOD 2 MEDPREDMETNO POUČEVANJE0F 3 DEJAVNOST 3.1 Ideja in oblikovanje dejavnosti 3.2 Cilji - komunicirajo v matematičnem jeziku, - pri delu spretno uporabijo vire. 3.3 Načrtovanje dejavnosti 3.4 Izvedba dejavnosti 4 EVALVACIJA UDELEŽENCEV 5 ZAKLJUČEK 6 LITERATURA IN VIRI Nediževec Ozvatič - new Pajnik Planinc PosedelGolob - new Prašnikar Rehberger 1 Rehberger 2 Simčič -new StepišnikPerdih Macur Strgar 1 UČENJE NA DALJAVO 2 OPIS DELA IN REZULTATI 3 ZAKLJUČEK LITERATURA IN VIRI Strniša - new Šebenik - new Šifrer Škrlj Urankar Urh Jereb Vrban et al - new Vučko Werber Rajkovič Žerjal Blank Page Blank Page 02 - Naslovnica - notranja - H 09 - Predgovor podkonference - H 10 - Programski odbor podkonference - H 01 Ciullaetal Abstract 1 Introduction 2 URBANITE CITIES 2.1 Amsterdam 2.2 Bilbao 2.3 Helsinki 2.4 Messina 3 Conclusions Acknowledgments 02 Farahmandsadr 03 Martellaetal Abstract 1 Introduction 2 State of the Art 3 Reference Scenario 3.1 Briefly on Messina Use Case 3.2 The URBANITE Architecture 4 Messina Implementation 5 Conclusions Acknowledgments 04 van Loon+Snijders 05 Olabarrietaetal 06 Bilbaoetal 07 Dovganetal Abstract 1 Introduction 2 Overview of the URBANITE System 3 Decision Support System (DSS) 3.1 Components of the URBANITE DSS 3.2 Hierarchical Decision Model for Mobility Policy Evaluation 3.3 Evaluation of Mobility Policies 4 Conclusion Acknowledgments 08 Meiners 09 Smerkol+S+D+G2 Abstract 1 Introduction 2 Overview of the System for Mobility Policy Design 3 Mobility policy simulation 3.1 Traffic Simulations 3.2 Representation of Mobility Policies 4 Creating Simulations 4.1 MATSim Input Data 4.2 Automating Simulation Creation 4.3 Road Network Preparation 4.4 Population Synthesis Algorithm 5 Conclusion Acknowledgments 10 Sulajkovskaetal Abstract 1 Introduction 2 Overview of the urbanite approach 3 data collection 3.1 Simulation 3.2 Scenarios 4 machine learning 4.1 Methods 4.2 Evaluation Results 5 conclusion Acknowledgments 11 Smerkol+S+D+G Abstract 1 Introduction 2 Visualizations in the Traffic and Mobility Domains 2.1 Spatio-Temporal Data 2.2 Traffic Data 2.3 Air pollution 3 Selection of Methods 3.1 Traffic data 3.2 Air pollution data 4 Implementation 4.1 Map based visualizations 4.2 Color maps 4.3 Interactive charts 5 Future work 6 Conclusions Acknowledgments 12 Lopez Blank Page Blank Page 02 - Naslovnica - notranja - I 09 - Predgovor podkonference - I 10 - Programski odbor podkonference - I 01 - Batagelj_WPOddani Abstract 1 Uvod 2 Matematika 3 ZUSE Z-23 4 Tehniška matematika 5 IJS E4 6 FE, RRC, RCU, Iskra, Intertrade in drugi 7 Računalništvo v srednjih šolah 8 IFIP 1971 9 Prva polovica sedemdesetih 10 Druga polovica sedemdesetih Opombe 02 - Hafner 03 - Bratko Lajovic Rajkovic nov2021 04 - Divjak 05 - Pivec 06 - Gams 07 - Dolenc 08 - Krapez 09 - Solina Abstract 1 Izobraževalne institucije 1.1 Gimnazija Bežigrad 1.2 Fakulteta za elektrotehniko 1.3 Hidrografski inštitut vojne mornarice 1.4 Pensilvanska univerza 1.5 Vrnitev na fakulteto 1.6 Fakulteta za računalništvo in informatiko Blank Page Blank Page 02 - Naslovnica - notranja - J 09 - Predgovor podkonference - J 10 - Programski odbor podkonference - J 01 - Tricaricoetal 02 - Boufenghour 03 - Nait-Meddour 04 - Marzano 05 - Stebut 06 - Vuketal Abstract 1 Introduction 2 The BATMAN platform and its users 2.1 Doctors 2.2 Patients 2.3 Data Scientists 2.4 Administrators 3 Smartphone Application 4 Conclusion Acknowledgments Blank Page 12 - Index - ALL Naslovnica-zadnja-ALL Blank Page