ScholarWorks@숙명여자대학교

초록

This study seeks to analyze trends in overseas research on self-regulated learning based on learning analytics, and to analyze sub-strategies of self-regulated learning and lists of data. For the analysis, 50 papers from overseas journals and conference proceedings prior to 2020 were screened. Frequency analyses are calculated by year, research context, data collection environment, research purpose, self-regulated learning strategy, and sub-factor. Sub-factors and analyzed data are then described in light of previous studies that specify sub-factors of self-regulated learning. The results indicated a steady increase in the number of studies since 2012, most of which were conducted in the context of universities. In over half of these studies, data was collected on Learning Management Systems (LMS) and Massive Open Online Courses (MOOC). With respect to research purpose, studies may be classified as learners and learning behaviors modeling, performance prediction, relationship analysis with performance results, and behavior comparison between survey and behavioral data. With respect to self-regulated learning strategy, the greatest number of papers concern metacognitive strategy, followed by behavior control strategy, cognitive control strategy, environmental control strategy, and learning strategy. Time management and self-evaluation and reflection are the most frequently analyzed sub-factors. Analyzed data were also collected to measure these factors. Based on these results above, analysis of data on the features of self-regulating learning behavior is presented and the implications for learning analysis research are suggested.

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