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Automated, Unobtrusive, Action-by-Action Assessment of Self-Regulation During Learning With an Intelligent Tutoring System

Automated, Unobtrusive, Action-by-Action Assessment of Self-Regulation During Learning With an... Assessment of students’ self-regulated learning (SRL) requires a method for evaluating whether observed actions are appropriate acts of self-regulation in the specific learning context in which they occur. We review research that has resulted in an automated method for context-sensitive assessment of a specific SRL strategy, help seeking while working with an intelligent tutoring system. The method relies on a computer-executable model of the targeted SRL strategy. The method was validated by showing that it converges with other measures of help seeking. Automated feedback on help seeking driven by this method led to a lasting improvement in students’ help-seeking behavior, although not in domain-specific learning. The method is unobtrusive, is temporally fine-grained, and can be applied on a large scale and over extended periods. The approach could be applied to other SRL strategies besides help seeking. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Educational Psychologist Taylor & Francis

Automated, Unobtrusive, Action-by-Action Assessment of Self-Regulation During Learning With an Intelligent Tutoring System

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References (71)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1532-6985
eISSN
0046-1520
DOI
10.1080/00461520.2010.517740
Publisher site
See Article on Publisher Site

Abstract

Assessment of students’ self-regulated learning (SRL) requires a method for evaluating whether observed actions are appropriate acts of self-regulation in the specific learning context in which they occur. We review research that has resulted in an automated method for context-sensitive assessment of a specific SRL strategy, help seeking while working with an intelligent tutoring system. The method relies on a computer-executable model of the targeted SRL strategy. The method was validated by showing that it converges with other measures of help seeking. Automated feedback on help seeking driven by this method led to a lasting improvement in students’ help-seeking behavior, although not in domain-specific learning. The method is unobtrusive, is temporally fine-grained, and can be applied on a large scale and over extended periods. The approach could be applied to other SRL strategies besides help seeking.

Journal

Educational PsychologistTaylor & Francis

Published: Oct 25, 2010

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