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Measuring Self-Regulated Learning With Multi-Agent Learning Environments
Mon, April 16, 4:05 to 5:35pm, Sheraton Wall Centre, Floor: Grand Ballroom Level, North Grand Ballroom ASession Submission Type: Symposium
Abstract
The goal of this symposium is to present research using various measurement strategies to investigate the complex nature of the temporal dynamics of self-regulatory processes during learning with multi-agent learning environments. The researchers presenting at this symposium represent several fields including cognitive and learning sciences, educational psychology, computer science and artificial intelligence (AI), and educational research. They will each articulate how their programs of research (and their respective theories and/or models of SRL, and conceptualizations of the underlying nature of SRL processes) can provide evidence about the complex nature of SRL processes deployed by learners during learning with agent-based learning environments.
Sub Unit
Chair
Papers
Enabling Students to Self-Assess With Guidance From a Multi-Agent Environment for Supporting Scientific Inquiry - Eric M. Eslinger, University of California - Berkeley; Barbara Y. White, University of California - Berkeley; John R. Frederiksen, University of Washington
Measuring Students’ Self-Regulated Learning in Teachable Agent Environments - Gautam Biswas, Vanderbilt University; John Kinnebrew, Vanderbilt University; Kirk Loretz, Vanderbilt University
Self-Regulated Learning in Exploratory Game-Based Learning Environment - Jennifer Sabourin, North Carolina State University; James Lester, North Carolina State University
Measuring Self-Regulated Learning With a Multi-Agent Hypermedia Environment - Roger Azevedo, McGill University; Reza Feyzi Behnagh, McGill University; Jason Matthew Harley, McGill University; François Bouchet, McGill University; Gregory Trevors, McGill University; Melissa Duffy, McGill University; Zaynab Sabagh, McGill University