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Exploring autonomous learning capacity from a self-regulated learning perspective using learning analytics
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DOI：10.1111/bjet.12747.png)
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Abstract
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Practising self-regulated learning (SRL) has been proposed to develop learning autonomy. However, there is lack of empirical evidence on how SRL strategies affect autonomous learning capacity. This study attempts to bridge that gap by utilizing the learners' trace data for measuring the learners' autonomous interactions, and investigates the effects of four SRL strategies on learners' autonomous choices. The goal is to explain how the employed SRL strategies impact autonomous control (in terms of frequencies of self-enforced decisions, as well as time-spent on decision making). The results from an exploratory study with undergraduate learners (N = 113) shown that goal-setting and time-management have strong positive effects on autonomous control, effort-regulation moderately positively affects learners' autonomy, while help-seeking has a strong negative effect. These findings provide empirical evidence and contribute to clarifying the role of each one of the SRL strategies in the development of autonomous learning capacity, from a learning analytics perspective. Limitations and potential implications for research and practice are also discussed.
Keywords:
PERCEIVED AUTONOMY
HELP-SEEKING
STRATEGIES
STUDENTS
BEHAVIOR
ONLINE
MOTIVATION
PERFORMANCE
TEACHERS
SUPPORT
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