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- W4304143218 abstract "Self-regulated learning is a crucial skill that may enable massive numbers of learners to thrive in MOOCs, but MOOC learners differ in their self-regulated learning skills, as low self-regulated learners need support to regulate their learning process in MOOCs. Designing self-regulated learning scaffoldings builds upon an accurate appraisal of learners’ self-regulated learning and also a person-centered understanding of self-regulated learner profiles in MOOCs. Therefore, this study applied a two-parameter item response theory model to accurately evaluate online learners’ self-regulated learning in MOOCs and then performed a cluster analysis to identify learner profiles in terms of their traits in each phase of self-regulated learning. The findings of this study identified five clusters of self-regulated learner profiles, upon which a further statistical analysis result indicated that the learners with lower forethought skills might be less committed to completing course assignments. Implications for self-regulated learning in MOOCs are discussed at the end." @default.
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- W4304143218 date "2022-10-10" @default.
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- W4304143218 title "Self-regulated learner profiles in MOOCs: A cluster analysis based on the item response theory" @default.
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- W4304143218 doi "https://doi.org/10.1080/10494820.2022.2129394" @default.
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