Learning Analytics for Measuring Engagement and Academic Performance: A Case Study from an Irish University

8TH INTERNATIONAL CONFERENCE ON HIGHER EDUCATION ADVANCES (HEAD '22)(2022)

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摘要
This paper presents an analysis of various metrics of student engagement and academic performance, based on data extracted from a virtual learning environment (VLE) and other supporting technologies. The level of student activity on the VLE, as measured by hours and count of accesses to content areas, was found to be a strong indicator of engagement and impacted the level of performance. Participation in self-regulated optional learning activities was also found to be a strong indicator of engagement, which again impacted students' scores. As regards gender comparisons, males and females demonstrated different study approaches but there was no difference in performance. Senior (final year) students out-performed sophomore (second year) students, and students on programmes with higher entry bars fared better. Interestingly, students who adopted a steady approach with consistent levels of activity through the semester achieved higher scores than those who procrastinated. The paper concludes with some recommendations on where learning analytics technologies need to go to truly be useful for teachers and students in higher education.
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关键词
Academic performance, Engagement, Student behaviour, Gender differences, Learning analytics, Virtual learning environments, Structural equational modelling
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