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Adults’ Self-Regulatory Behaviour Profiles in Blended Learning Environments and Their Implications for Design

Adults’ Self-Regulatory Behaviour Profiles in Blended Learning Environments and Their... Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Technology, Knowledge and Learning" Springer Journals

Adults’ Self-Regulatory Behaviour Profiles in Blended Learning Environments and Their Implications for Design

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References (169)

Publisher
Springer Journals
Copyright
Copyright © Springer Science+Business Media B.V., part of Springer Nature 2018
Subject
Education; Learning and Instruction; Mathematics Education; Educational Technology; Science Education; Creativity and Arts Education
ISSN
2211-1662
eISSN
2211-1670
DOI
10.1007/s10758-017-9351-y
Publisher site
See Article on Publisher Site

Abstract

Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environments.

Journal

"Technology, Knowledge and Learning" – Springer Journals

Published: Sep 10, 2020

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