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

Original research

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.

Keywords

Blended learning Learning analytics Self-regulation Instructional design Adult education 

Notes

Funding

We would like to acknowledge the support of the project “Adult Learners Online” funded by the Agency for Science and Technology (Project Number: SBO 140029), who made this research possible.

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Centre for Instructional Psychology and TechnologyKU LeuvenLeuvenBelgium

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