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Session Type: Paper Session
This session examines how learning analytics, AI, and immersive technologies shape students’ motivation and self-regulated learning (SRL). Papers span large-scale institutional analytics, AI chatbots as co-regulators, and meta-analyses of synchronous versus asynchronous learning. Complementary studies in VR and K–12 settings explore how feedback, costs, and design features influence motivation and regulation. These papers offer theoretical and empirical insights into how technological environments can scaffold self-regulated learning and sustain motivation across diverse modalities and learner populations.
From Clicks to Insights: Exploring SRL Behaviors Longitudinally using Institutional Data - Heeryung Choi, University of Minnesota; Chris Steadman, University of Minnesota; Caitlin Mills, University of Minnesota; Panayiota Kendeou, University of Minnesota
Generative AI Chatbots as Co-regulators: Enhancing Self-Regulated Learning Across Learner Personality Profiles - Xiu-Yi Wu, The Chinese University of Hong Kong; Thomas K.F. Chiu, The Chinese University of Hong Kong
Investigating Costs Associated with K12 Students’ Online Learning - Franziska Bickel, North Carolina State University; Qiuqing Li, North Carolina State University; Nilloufar Bayati, North Carolina State University; Zaina Dali, North Carolina State University; Shiyan Jiang, North Carolina State University; Rebecca Ellis, The Concord Consortium; Jie Chao, The Concord Consortium
Learning and Motivation in Synchronous and Asynchronous Online Education: A Meta-Analytic Review - Andreas Gegenfurtner, University of Augsburg
Motivational Effects of Annotations and Quizzes in a VR-Based Field Trip - Carina Galler, Universität der Bundeswehr München; Maximilian Christian Fink, Universität der Bundeswehr München; Bianca Watzka, RWTH Aachen University; Bernhard M. Ertl, Universität der Bundeswehr München