Exploring Learning Strategies by Sequence Clustering and Analysing their Correlation with Student's Engagement and Learning Outcome

Abstract

Many previous studies have shown that students' learning strategies and engagement are both important factors affecting students' learning outcome. We want to know whether the engagement of students who use different learning strategies is different, so that we can proxy measure students' engagement according to the learning strategies used by students. Different from the past methods of using questionnaires or interviews, this research used education data mining technology to directly analyze the learning logs of online learning system to extract students' learning strategies. We collected the learning logs of 56 students, and extracted the learning strategies of the students using sequence clustering. We classified four learning strategies and performed Pearson correlation analysis with students' learning outcome and engagement, and discussed the key strategies that affect students' learning outcome. We also found that students who use different learning strategies have different levels of engagement.