The widespread use of digital systems and tools in education has opened up opportunities for collecting, measuring, and analysing data about user (student, teacher) interaction with a variety of learning resources and activities, with the ultimate objective of better understanding learning and advancing both the learning outcomes and the overall learning experience. This promise motivated the development of Learning Analytics as a research field and the use of insights derived from learning trace data for evidence-based decision making in a variety of educational settings. While the field of Learning Analytics has made a significant contribution to better understanding of learning and the environments in which it takes place, many open questions and challenges remain. Furthermore, new challenges continue to emerge with the ever changing modalities of teaching and learning, the latest of which are associated with the rapid development and accessibility of Generative Artificial Intelligence (AI). After a brief introduction to Learning Analytics, this talk will focus on some of the challenges to analytics of contemporary classrooms, as well as the opportunities offered by Generative AI to better understand and support teaching and learning.
Jelena Jovanovic is a Professor at the Department of Software Engineering, University of Belgrade, Serbia. She is also an Adjunct Professor in the Centre for the Science of Learning & Technology (SLATE) at University of Bergen, Norway, and an Adjunct Professor in the Centre for Learning Analytics at Monash (CoLAM), Monash University, Australia. Her current research focus is on the use of computational approaches, including statistical and machine learning methods and techniques, network analysis, and text analytics, towards better understanding and supporting learning, primarily self-regulated learning in higher education settings. Currently she serves as Advisor to the Editor-in-Chief of IEEE Transactions on Learning Technologies and Editorial Board member of Journal of Learning Analytics, Journal of Educational Data Mining, and Computers & Education: Artificial Intelligence. She has been one of the faculty leads for the three latest Doctoral Consortia at the Learning Analytics and Knowledge conference (LAK22, LAK23 & LAK24).