Organiser

The Workshop on Measuring and Facilitating Self-regulated Learning and Human-AI Co-regulated Learning based on Trace data

Our Team

Dragan Gašević

Dragan Gašević is Professor of Learning Analytics in the Faculty of Information Technology at Monash University. A computer scientist by training and skills, Dragan considers himself a learning analyst developing computational methods that can shape next-generation learning and software technologies and advance our understanding of information seeking, sense-making, and self-regulated and social learning.

Philip H. Winne

Philip H. Winne is a Professor of educational psychology and former Canada Research Chair in Self-Regulated Learning and Learning Technologies at Simon Fraser University. His research interest is on self-regulated learning, metacognition, study tactics and learning strategies, motivation, learning analytics, technologies for researching and promoting learning, research methods in the learning sciences.

Sanna Järvelä

Sanna Järvelä is a Professor in the field of learning and educational technology and a head of the Learning and Educational Technology Research Lab (LET) (http://www.oulu.fi/let). Her research focuses on self-regulated learning, computer-supported collaborative learning, and AI in education. Järvelä is internationally recognized in theoretical and methodological advancement of socially shared regulation in learning and multimodal research methods.

Roger Azevedo

Roger Azevedo is a Professor in the School of Modeling Simulation and Training at the University of Central Florida. His main research area includes examining the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, multimedia, simulations, serious games, immersive virtual learning environments).

Inge Molenaar

Inge Molenaar is the director of the National Education Lab AI (NOLAI) and Professor of Education and Artificial Intelligence at the Behavioural Science Institute at Radboud University in the Netherlands. She has over 20 years of experience in technology-enhanced learning, taking multiple roles from entrepreneur to academic. Her research focuses on technology-empowered innovations to optimize human learning and teaching.

Bor-Chen Kuo

Bor-Chen Kuo is a Chair Professor in the Graduate Institute of Educational Information and Measurement and the President of National Taichung University of Education, Taiwan. He is the Editor of Educational Psychology. Professor Kuo received an Outstanding Research Award from the R.O.C Ministry of Science and Technology (MOST), Taiwan in 2017. His research interests include adaptive learning and testing, technology enhanced self-regulation learning, cognitive diagnostic modeling, machine learning, and artificial intelligence in education.

Joep van der Graaf

Joep van der Graaf is an Assistant Professor at the Behavioural Science Institute at Radboud University Nijmegen. He is interested in self-directed learning, including self-regulated learning and inquiry-based learning. He aims to understand students’ learning processes and likes to use innovative technologies and analytic approaches.

Susanne de Mooij

Susanne de Mooij is a Postdoctoral Researcher in the Learning & Plasticity group of the Behavioural Science Institute and a member of the Adaptive Learning Lab (ALL) at Radboud University in Nijmegen, Netherlands. Her research seeks to optimize intelligent learning technologies to enhance the learning experiences of individual students. She is interested in how science and the edtech industry can collaborate to have a positive impact on students’ learning.

Yizhou Fan

Yizhou Fan is an Assistant Professor at Peking University. Yizhou considers himself a learning analyst using computational methods to advance the understanding of online learning strategies and self-regulated learning. His research interests are MOOC, self-regulated learning, learning design, learning tactics and strategies, and multimodal learning analytics

Mladen Raković

Mladen Rakovic is a Research Fellow at Monash University. His research interests span the fields of natural language processing, predictive modeling, computational linguistics, and educational psychology. He focuses on the development and evaluation of computer-based writing systems that monitor undergraduates’ writing activity and generate learning analytics to promote self-regulated learning and deep engagement with disciplinary content.

Xinyu Li

Xinyu Li is a Research Fellow in the Faculty of Information Technology at Monash University. He has experience in designing and developing educational software aiming to support self-regulated learning and collaborative learning research.

Tao-Yi Chang

Frederic Tao-Yi Chang is a Research Fellow at the National Taichung University of Education. His research interests include educational big data, meta-analysis, structural equation modeling, and educational psychology. He specializes in the development and evaluation of the Taiwan Adaptive Learning Platform, which aims to enhance self-regulated learning and academic achievement for students in Grades 1 to 12.

Chia-Hua Lin

Chia-Hua Lin is a Postdoctoral Research of Educational Measurement and Adaptive Learning Center at National Taichung University of Education. Her research interests are in the areas of educational data mining, learning analysis, computerized adaptive testing, cognitive diagnosis models, and item response theory.

Chih-Wei Yang

Chih-Wei Yang is an Assistant Professor in the Graduate Institute of Educational Information and Measurement at National Taichung University of Education, Taiwan. He has been involved in several ITS projects on adaptive learning and adaptive testing, particular in measurement model and item bank construction. His research interests include cognitive diagnostic modeling, learning analytics, test development, and computerized adaptive testing.

Linxuan Zhao

Linxuan Zhao is a Research Fellow in the Faculty of Information Technology at Monash University. He has experience in designing and developing educational software aiming to support self-regulated learning and collaborative learning research.

Tongguang Li

Tongguang Li is a Research Fellow at Monash University, specializing in the use of learning analytics to enhance adaptive instructional design and support self-regulated learning processes. His research primarily explores the development and refinement of adaptive learning environments through innovative software solutions. Tongguang is dedicated to improving educational outcomes by integrating technology and pedagogy.

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