Capturing Students’ Dynamic Learning Pattern Based on Activity Logs
Using Hierarchical Clustering

Capturing Students’ Dynamic Learning Pattern Based on Activity Logs
Using Hierarchical Clustering

learning pattern, activity logs, learning management systems, hierarchical clustering.

Students can have various characteristics and learning patterns. By understanding the characteristics and learning pattern of
individual students, teachers can provide individualized learning strategies based on students' needs. Students' learning
patterns may experience changes depending on their conditions during the learning process. If the learning pattern analysis is
only run once, then the progress and changes in student learning patterns throughout the learning process cannot be
recognized. On the other hand, periodical analysis is expected to describe the dynamics of student learning patterns from time
to time. This research is intended for capturing students' dynamic learning pattern using Hierarchical Clustering. We clustered
the learning patterns based on Learning Management Systems (LMS) activity logs. The activity log data were partitioned into
several periodical datasets. The results of the periodic clustering indicated that students’ learning patterns varied from one
another and changed from time to time. Most students experienced change in learning patterns throughout the semester. The
analysis also indicated that learning pattern also has the potential to be improved and maintained.

Kusuma Ayu Laksitowening1
, Made Diva Prasetya2
, Dawam Dwi Jatmiko Suwawi3
, Anisa Herdiani4

Telkom University

02-02-2023

Fajar bagus W

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Indonesia

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