Enhancing Learning Outcomes In Online Environments Through The Support Of Self-regulated Learning
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2023
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University of Hawaii at Manoa
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The online learning environment demands the ability to self-regulate, set up learning goals, monitor progress, and self-reflect on the learning process. Self-regulated learning (SRL) is an approach to learning where students actively have control over their behaviors. Self-regulated learning theory implies that learners possess certain attributes or engage in strategies to promote comprehension, retention, and learning. This dissertation explored SRL strategies across regulatory phases (i.e., forethought, performance, and self-reflection), distinct regulator profiles, relationships to academic achievement, and implications to instructional design (ID) within a competency-based online course. Study participants were students in LTEC 112: Technologies for Academic Success. Results showed participants employed SRL strategies at different levels across phases and subscales. Three profiles of self-regulators emerged: (a) minimal, (b) moderate, and (c) competent. These profiles were positively correlated to academic achievement in LTEC 112. The study identified ID elements that supported self-regulatory skills. Findings revealed five areas of focus (i.e., instructor support, personal timeline, check performance, course syllabus, and expectation setting) as important and where instructional designers intentionally incorporated these types of SRL elements into their design. This study expanded and enhanced the understanding of how the complex range of SRL processes and self-regulation profiles intersect with ID strategies used in online learning.
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Educational technology, Academic achievement, Instructional design, Online learning, Self-regulated learning
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