Chronotypes of Learning Habits in Weekly Math Learning of Junior High School

Abstract

Learners may have a unique chronotype of learning habits that they have the preferred time of day to work. Even though learner activity extracted from trace data can provide useful and insightful information about their learning habits, there is a lack of tracing habits in daily learning at a school level from learning logs. Therefore, we investigate the patterns one week ahead of regular tests over the year using learning analytics techniques of clustering analysis. From 92,694 daily logs of the ninth graders in weekly math learning, we find clusters of learning patterns that suggest different chronotypes of learning habits. The findings enable context-aware recommendations for a more authentic learning experience with adaptivity and personalization, which is potential for enhancing pedagogical practices in mobile, contextualized, and ubiquitous learning environments in future research.