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Examining the critical role of evaluation and adaptation in self-regulated learning

Authors :
Kelly A. Hogan
Robert D. Plumley
Matthew L. Bernacki
Jeffrey A. Greene
Abigail T Panter
Kathleen M. Gates
Mladen Rakovic
Source :
Contemporary Educational Psychology. 68:102027
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

Researchers and many educators agree that the ability to self-regulate learning is important for academic success. Yet, many students struggle to anticipate learning difficulties and adjust accordingly. Further, despite theorizing that self-regulated learning involves adaptation across learning cycles, few researchers have examined students’ evaluative judgments, their implications for students’ behavior in a subsequent learning cycle, or their effects on achievement. Utilizing data from a large, introductory college biology course, we examined how struggling students’ evaluative judgments made after a first unit exam predicted changes in learning behaviors as well as how those changes predicted performance on a subsequent exam. We used natural language processing to analyze data from a reflective essay written after a first unit exam, identifying language that reflected evaluation of prior studying and plans to adapt learning. Then, we utilized digital traces of learning behaviors to measure students’ actual adaptation of their use of learning resources. Results from a path analysis revealed students’ evaluations predicted how extensively they discussed plans to adapt their learning process. Plans to adapt described in written reflections predicted an increase in the frequency of desirable learning behaviors, which in turn predicted higher subsequent exam scores, after controlling for previous exam performance. These findings provide empirical evidence of multiple theorized self-regulated learning processes, including how evaluations of learning at the end of a learning cycle can inform planning and behavior changes in a subsequent learning cycle, and that increases in the enactment of effective learning strategies predicts improved performance in complex learning tasks.

Details

ISSN :
0361476X
Volume :
68
Database :
OpenAIRE
Journal :
Contemporary Educational Psychology
Accession number :
edsair.doi...........03828feb4277cfc82ac6ee3370ae62c4