Self-Regulation in Computer-Assisted Learning Systems

doi:10.1017/9781108235631.024

23 - Self-Regulation in Computer-Assisted Learning Systems

from Part V - Metacognition

Published online by Cambridge University Press: 08 February 2019

Roger Azevedo ,

Nicholas V. Mudrick ,

Michelle Taub and

Amanda E. Bradbury

Edited by

John Dunlosky and

Katherine A. Rawson

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John Dunlosky: Affiliation:
Kent State University, Ohio
Katherine A. Rawson: Affiliation:
Kent State University, Ohio

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Summary

Computer-Assisted Learning Systems (CALSs) have the potential to transform learning by supporting and augmenting students’ ability to accurately monitor and regulate key cognitive, affective, metacognitive, motivational and social processes. Recent advances in the cognitive, learning, computational, and engineering sciences make is possible to significantly augment existing CALSs both as research tools (e.g., examine temporally unfolding self-regulatory processes) as well as instructional tools (e.g., foster metacognitive skills). The goal of this chapter is to present research on self-regulation in CALSs by providing examples from contemporary systems and also how we use multimodal multichannel data (e.g., log files, eye tracking, facial expressions of emotions, physiological sensors, concurrent verbalizations) to examine cognitive, affective, and metacognitive (CAM) self-regulatory processes in these systems. As such, we first provide a brief history of research in SRL with CALSs and discuss how different CALSs have been used to study and foster SRL. We will then present and discuss conceptual and theoretical issues derived from several models, frameworks, and theories of SRL that focus on CAM processes. Following this, we discuss several dichotomies related to CAM and the challenges they pose for the measurement and support of SRL with CALSs. Lastly, we present challenges and future directions that need to be addressed by interdisciplinary researchers to advance the field of SRL and CALSs.

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Type: Chapter
Information: The Cambridge Handbook of Cognition and Education , pp. 587 - 618

DOI: https://doi.org/10.1017/9781108235631.024 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2019

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