What is it about?
Self-regulation is essential for successful learning experiences. This paper compares how four process mining algorithms were used to analyse self-regulation and see how it evolves over time for students. The results allow researchers to chose the most adequate ones.
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Why is it important?
Understanding self-regulation is very important to identify and promote successful learning experiences. But in order to do this at scale we need to have algorithms that perform that analysis for us and provide useful results. This paper provides insights about four algorithms that were used to process how self-regulation evolves over time.
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This page is a summary of: Using process mining to analyse self-regulated learning: a systematic analysis of four algorithms, April 2021, ACM (Association for Computing Machinery),
DOI: 10.1145/3448139.3448171.
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