Student Engagement in a Gamified Online Learning Environment: A Data Mining Approach

Abstract

In education, gamification applies game design elements to non-game contexts to engage learners. This preliminary study explored the feasibility of using data mining to analyze student engagement patterns in an asynchronous online course that utilized gamification. We conducted a series of exploratory data analysis approaches, including keyword extraction, clustering, concordance analysis, and sequential pattern mining. Results showed peaks in engagement aligned with gamified challenges and rewards. Students discussed both academic and non-academic topics, indicating community-building. Sequence pattern mining revealed more consistent academic engagement for highly engaged students. Findings demonstrate the viability of using data mining techniques to assess cognitive engagement based on discussion patterns in a gamified online course.