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Workshop on Measuring and Facilitating
Self-regulated Learning based on Trace data
DATE: March 18th , 2024
TIME: 9:00am - 5:00pm
MODE: FACE-TO-FACE
VENUE: Kyoto, Japan
OUR TEAM
Yizhou Fan is a Research Associate in the School of Informatics at the University of Edinburgh. 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
Yizhou Fan is a Research Associate in the School of Informatics at the University of Edinburgh. 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
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.
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.
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.
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.
Dragan Gasevic 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.
Dragan Gasevic 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.
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