How Do Students Behave in a Gamified Course?—A Ten-Year Study

Abstract

Gamified learning aims to motivate students using game elements. Although gamification can enhance student enjoyment and engagement, it is unclear how different students behave in and interact with gamified contexts. To this end, we analyze how different students interact with a gamified course. We devised such an experimental course on Multimedia Content Production (MCP), and ran it for ten years. At each year, we modified it after student feedback from the previous year. We determined student groups applying clustering techniques to learner performance data, independently analyzed the resulting clusters in terms of behavior, engagement, performance, and also compared those pairwise. Our analysis identified four different student groups (profiles/clusters) according to their performance and interactions with the course across all years. We found out that the best performing students were those that had significantly more interactions with course materials and consistently ranked highest. In addition, we found that performance indicators for students of all groups became stable within the first month after course start, allowing final grades to be predicted with high accuracy by then. Furthermore, all were deadline driven and became mainly active at the end of the semesters (indicating a lack of self-regulation skills). Moreover, we did not find any specific relation between student groups and gaming profiles (Brainhex categories). Finally, we propose practical implications and guidelines for designing compelling gamified learning experiences.

Predicting the Pharmaceutical Needs of Hospitals

“…recognize patterns in data that traditional algorithms may not). Moreover, they are scalable and can handle large amounts of data quickly and accurately [69][70][71][72][73].…”