Discovering the effects of learning analytics dashboard on students’ behavioral patterns using differential sequence mining

Abstract

Interventions based on learning analytics have a very important place in closing the learning analytics loop. However, data-driven studies that test the effects of learning analytics-based interventions on students' online learning behaviors are very limited. In this study, the effect of the student-facing learning analytics dashboard (LAD) on the learning behavior of students in the online learning environment was investigated by using the differential pattern mining method. In a completely remote course, the learning behaviors of the participants before the introduction of the dashboard were compared with the learning behaviors they exhibited after the dashboard was introduced. In this way, it has become possible to analyze the behavior changes after the dashboard intervention. Wilcoxon signed-rank test was used to test whether these behavioral changes were statistically significant or not. According to the Wilcoxon signed-rank test results, while there is no significant difference in terms of students’ assignment and quiz interactions, it is seen that there is a statistically significant increase in terms of students’ forum-related activities such as reading other students’ posts, starting a new discussion, and replying others’ posts. Students’ SCORM interactions (e.g, launch, complete) were also increased after engaging with the LAD. In addition, it was found that the overall interaction of students in the online learning environment increased by 57% when the LAD was used.