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Modeling and Supporting Self-Regulated and Metacognitive Learning
Thu, April 9, 4:15 to 5:45pm PDT (4:15 to 5:45pm PDT), Westin Bonaventure, Floor: Lobby Level, Santa Barbara BSession Type: Paper Session
Abstract
Focusing on methodological and intervention-based approaches to self-regulated learning (SRL), this session presents innovative analyses and technologies for understanding and enhancing metacognition. Studies span modeling SRL behaviors, examining feedback mechanisms, and evaluating interventions to foster effective learning regulation across age groups and disciplines.
Sub Unit
Chair
Papers
Integrating Latent Profile and Network Analysis to Examine Learning Strategies Among First-Year Middle School Students - Yewon Kim, Ewha Womans University; Junseo Kim, Korea University; John Jongho Park, Pennsylvania State University; Mihee Park, Auburn University
Learners’ Perceptions of a Technology-Enhanced Personalized Intervention to Support Self-Regulated Learning in Continuing Education - Yvonne M. Fromm, University of Mannheim; Dirk Ifenthaler, University of Mannheim
Promoting Metacognitive Problem-Solving Among Non-Calculus-Ready First-Year Engineering Students - D. Jake Follmer, West Virginia University; Megan Hut, West Virginia University; Lizzie Y. Santiago, West Virginia University
Temporal Trajectories of Self-Regulation Learning: A Markov-Chain Approach to Modeling and Grouping Student Behaviors - Shasha Li, McGill University; Tingting Wang, Renmin University of China; Jie Gao, McGill University; Nikki G. Lobczowski, McGill University; Krista R. Muis, McGill University; Adam Kenneth Dubé, McGill University; Susanne P. Lajoie, McGill University
The Different Metacognitive Effects of Peer-Generated Visual Feedback in Learning by Drawing - Xiyu Chen, East China Normal University; Zhe Wang, East China Normal University