Monash University, Australia
Dragan Gašević is Professor of Learning Analytics in the Department of Data Science and Artificial Intelligence of the Faculty of Information Technology and the Director of the Centre for Learning Analytics at Monash University. Dragan’s research interests in learning analytics center around the development of computational and design methods that advance understanding of self-regulated and collaborative learning. He is a founder and served as the President (2015-2017) of the Society for Learning Analytics Research (SoLAR). In 2019-2022, he was recognized as the national field leader in educational technology in The Australian’s Research Magazine. In 2022, he received Lifetime Member Award as the highest distinction of SoLAR and was recognized as a Distinguished Member of the Association for Computing Machinery.
Speech Title: Generative AI: Opportunities and Challenges for Education
Abstract: This talk will discuss the promise of generative artificial intelligence (AI) in education. Existing debates about its implications often take several perspectives. Some argue that generative AI can profoundly enhance education and enable personalized learning. Others note significant disruptions to existing assessment practices and call for innovative approaches. Some even articulate great ethical concerns about the implications of using generative AI in education. This talk will address all of these perspectives. It will first discuss promising directions for the use of generative AI in education. It will then outline some major concerns associated with technology that underpins generative AI. Finally, the talk will outline directions for future research. The talk will draw upon a growing body of research knowledge and evidence derived from several empirical studies to provide insights into these important questions.
Purdue University, USA
Dr. Matthew Ohland is the Dale and Suzi Gallagher Professor and Associate Head of Engineering Education at Purdue University. He earned a Ph.D. in Civil Engineering from the University of Florida, M.S. degrees in Materials Engineering and Mechanical Engineering from Rensselaer Polytechnic Institute, and a B.S. in Engineering and a B.A. in Religion from Swarthmore College. He Co-Directs the National Effective Teaching Institute (NETI) with Susan Lord and Michael Prince. His research has been funded by over USD 20M, mostly from the United States National Science Foundation. Along with his collaborators, he has been recognized for his work on longitudinal studies of engineering students with the William Elgin Wickenden Award for the best paper published in the Journal of Engineering Education in 2008, 2011, and 2019. He has also been recognized for the best paper in IEEE Transactions on Education in 2011 and 2015, multiple conference Best Paper awards, and the Betty Vetter Award for Research from the Women in Engineering Proactive Network. The CATME Team Tools developed under Dr. Ohland’s leadership and related research have been used by over 1.9 million students of more than 23,000 faculty at more than 2500 institutions in 90 countries, and were recognized with the 2009 Premier Award for Excellence in Engineering Education Courseware and the Maryellen Weimer Scholarly Work on Teaching and Learning Award in 2013. Dr. Ohland received the Chester F. Carlson Award for Innovation in Engineering Education from the American Society for Engineering Education (ASEE) for his leadership of that project. He is a Fellow of ASEE, IEEE, and AAAS. He has received teaching awards at Clemson and Purdue. Dr. Ohland is an ABET Program Evaluator and has previously served as an Associate Editor of IEEE Transactions on Education. He was the 2002–2006 President of Tau Beta Pi.
Speech Title: Exploring the
Efficacy of ChatGPT in Analyzing Student Teamwork Feedback with an Existing
Abstract: Teamwork is a critical component of many academic and professional settings. In those contexts, feedback between team members is an important element to facilitate successful and sustainable teamwork. However, in the classroom, as the number of teams and team members and frequency of evaluation increase, the volume of comments can become overwhelming for an instructor to read and track, making it difficult to identify patterns and areas for student improvement. To address this challenge, we explored the use of generative AI models, specifically ChatGPT, to analyze student comments in team based learning contexts. Our study aimed to evaluate ChatGPT's ability to accurately identify topics in student comments based on an existing framework consisting of positive and negative comments. Our results suggest that ChatGPT can achieve over 90% accuracy in labeling student comments, providing a potentially valuable tool for analyzing feedback in team projects. This study contributes to the growing body of research on the use of AI models in educational contexts and highlights the potential of ChatGPT for facilitating analysis of student comments. This presentation shares the collaborative work of Andrew Katz of Virginia Polytechnic Institute and State University in Blacksburg, Virginia, and Siqing Wei, Gaurav Nanda, Chris Brinton all of Purdue University – West Lafayette, Indiana, along with the speaker. A paper by the same title has been pre-published at the arXiv repository and is being submitted for journal publication.
National and Kapodistrian University of Athens, Greece
Chronis directs the Educational Technology Lab at
the Dept. of Educational Studies, School of Philosophy, NKUA.
His research interests involve the design and use of digital media to study engaged socio-constructionist learner activities. He has applied Design Research methods to study innovative educational practices aiming to transform schooling to cultivate citizenship rather than academic excellence. He serves as academic consultant to the Ministry of Education on TPD since 2005 and is responsible for Mathematics having reached 35% of teachers in the country. He is responsible for the design of three popular original authoring systems freely available at http://etl.eds.uoa.gr. a) Malt, a programmable modeler for animated figural objects to support computational thinking (CT) and mathematics. b) ChoiCo, a 'choices with consequences' game creator for CT and the grappling with wicked, socio-scientific issues and c) SorBET, a tetris - like game creator integrating CT with classification. He is an active member at the IDC, Constructionism and ICTMT conferences. He represents Greece at the International Congress of Mathematical Instruction. He is also visiting Professor at Linnaeus University Sweeden. Chronis has been active in the European Research and Developlent scene and is currently engaged with two HORIZON multi-oranisational projects, numbers 15 and 16 in his career, respective acronyms: ExtenDT2 and TransEET.
Speech Title: Constructionist Tools for Computational Thinking
Abstract: One of the first ideas on how to use digital media for learning was a kind of a wake-up call to what learning actually could be from an epistemological and a pedagogical point of view. The elements that the education community was jolted into seriously considering was that of a) meaning-making versus routine learning and b) agency and creativity versus response to controlled questions which can be objectively assessed. But this was a long time ago. Since then, technology has been used for everything under the sun spanning from conservationist to administrative to transformative approaches to what it means to educate. In the education community the interest in transformative approaches has led research to progress from adopting a misconceptions approach to learning to a meaning-making approach and the to the idea of skills and in the past decade to competences. Meanwhile new technologies are always emerging providing excitement but at the same time not much chance for educational added value to properly integrate into education systems. In my talk I will use three examples of digital expressive tools less known than MIT-scratch, but equally designed to enable engagement and to integrate computational thinking into the adoption of competences. I will take the case of mathematics education but broadly, asking 'what mathematics is good for cultivating mathematical competences' and 'what is mathematical about real life socio-scientific issues relevant to youth today'. In my talk I will show examples of these three tools - authoring systems in fact - which are available freely for anyone to use or to design things with. The first, MaLT2, is a programmable modeller for animated 3D graphical figures, the second, ChoiCo, is a game designer for games based on the 'choices with consequences' paradigm and the third, SoRBET, is a tetris-like game designer based on the notion of classification. I will suggest some theoretical tools which have been useful to us in our 30-year long research at ETL to study learning processes and professional development.