Temporal Characteristics of Self-Regulated Learning Behaviors Influence Students' Problem-Solving Efficiency in a Technology-Rich Learning Environment

• In Event: Self-Regulated Learning Behaviors and Learning

Abstract

This study examined how self-regulated learning (SRL) affected problem-solving efficiency. Eighty-two medical students completed a diagnostic task in a technology-rich environment, BioWorld. We extracted students’ SRL behaviors, task completion time, and diagnostic performance from BioWorld log files. A two-step cluster analysis was performed to classify students into efficient and less efficient groups based on performance and completion time. We then employed recurrence quantification analysis (RQA) to analyze SRL temporal dynamics. Independent samples t-tests revealed that efficient students conducted more SRL behaviors in the self-reflection phase and tended to repeat a longer SRL behavior sequence. Moreover, they chose to repeat the same SRL behavior before moving forward. These findings have both theoretical and methodological contributions to the SRL theory.

Authors

• Tingting Wang, McGill University
  Presenting Author

• Alejandra Ruiz-Segura, McGill University
  Non-Presenting Author

• Shan Li, Lehigh University
  Non-Presenting Author

• Xiaoshan Huang, McGill University
  Non-Presenting Author

• Chengyi Tan, McGill University
  Non-Presenting Author

• Susanne P. Lajoie, McGill University
  Non-Presenting Author