Yige Song
ABSTRACT
This case study explores the online learning patterns of a cohort of first-year university students in two subjects: a compulsory science subject and an introductory programming subject, by analysing trace data from the Learning Management Systems (LMS). The methodology extends existing learning analytics techniques to incorporate temporal aspects of students’ learning, such as session duration and weekly online behaviours. By examining over 82,000 learning actions, the research unveils significant variations in students’ online learning strategies between subjects, offering deeper insights into these differences and their associated challenges. The study seeks to initiate broader discussions in learning analytics, emphasising the need to comprehend students’ diverse online learning experiences and encouraging further exploration in future research.
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Index Terms
- A Case Study on University Student Online Learning Patterns Across Multidisciplinary Subjects
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