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 c… Show more
“…Trace methodologies from think aloud protocols (Greene, Robertson, and Costa 2011) and sequenced, computer-generated logs of learner behaviors are increasingly common (Aleven et al 2010;Azevedo et al 2010;Graesser and McNamara. 2010;Greene and Azevedo 2010;Kinnebrew et al 2013a;Molenaar and Järvelä 2014;Sha, Looi, Chen, Seow, and Wong 2012;Winne and Hadwin 2013).…”
“…Trace methodologies from think aloud protocols (Greene, Robertson, and Costa 2011) and sequenced, computer-generated logs of learner behaviors are increasingly common (Aleven et al 2010;Azevedo et al 2010;Graesser and McNamara. 2010;Greene and Azevedo 2010;Kinnebrew et al 2013a;Molenaar and Järvelä 2014;Sha, Looi, Chen, Seow, and Wong 2012;Winne and Hadwin 2013).…”
“…At the other end of this continuum are studies that select a small set of SRL processes and examine them closely in the context of a single learning task. These types of studies usually capture SRL events (Winne and Perry 2000) using process-oriented methodological approaches like microanalytic methods (Cleary 2011), think aloud protocols (Greene et al 2011), and trace methodologies (Aleven et al 2010;Azevedo et al 2013) to observe individual SRL processes as they unfold during learning.…”
Section: Design Choices In Self-regulated Learning Researchmentioning
Self-regulated learning (SRL) theorists propose that learners' motivations and cognitive and metacognitive processes interact dynamically during learning, yet researchers typically measure motivational constructs as stable factors. In this study, self-efficacy was assessed frequently to observe its variability during learning and how learners' efficacy related to their problem-solving performance and behavior. Students responded to self-efficacy prompts after every fourth problem of an algebra unit completed in an intelligent tutoring system. The software logged students' problem-solving behaviors and performance. The results of stability and change, path, and correlational analyses indicate that learners' feelings of efficacy varied reliably over the learning task. Their prior performance (i.e., accuracy) predicted subsequent self-efficacy judgments, but this relationship diminished over time as judgments were decreasingly informed by accuracy and increasingly informed by fluency. Controlling for prior achievement and self-efficacy, increases in efficacy during one problemsolving period predicted help-seeking behavior, performance, and learning in the next period. Findings suggest that self-efficacy varies during learning, that students consider multiple aspects of performance to inform their efficacy judgments, and that changes in efficacy influence self-regulated learning processes and outcomes.
“…Removal of immediate feedback was associated with decreasing metacognitive performance, and this decline was not prevented when students were provided with other metacognitive scaffolds. Aleven, Roll, McLaren, and Koedinger (2010) sought to evaluate students' self-regulated learning (SRL) in the context of an intelligent tutoring system -a tricky proposition. An automated method for context-sensitive assessment of specific SRL strategies (e.g., help seeking) has been developed.…”
Section: Information Technology and Peer Learningmentioning
This paper describes the method of peer tutoring, which has exciting new developments even though it has been around for a long time. A definition is followed by discussion of different types of peer tutoring. Key organizational variables in implementing tutoring are given, followed by a brief review of the effects for both tutees and tutors. A theory of peer learning is offered, followed by a description of recent new developments and the accompanying research. Finally, information technology applications are discussed. The paper concludes with an exploration of issues of sustaining gains through embedding peer tutoring.
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