The relationship between academic performance and the interaction patterns of online students in learning management system

Learning Management System (LMS) can track student interactions with digital learning resources during an online learning activity. Learners with different goals, motivations and preferences may exhibit different behaviours when accessing these materials. These different behaviours may further affect their learning performance. The purpose of this study is to examine the relationship between students' interaction behaviours in online learning activities and their academic performance. In this study, including 214 students, the LMS was used for sharing course content, communicating with students, and conducting evaluations. At the end of the 14-week teaching period, the tracking data, which were obtained from the learning activities of the students, were analysed. A two-step clustering analysis was carried out to categorise students' interactions with learning activities. Thus, it was determined that they had low, moderate, and high interactions, respectively. The normal distribution and homogeneity of variances of the variables were checked. ANOVA was used when assumptions were met, and the Kruskal-Wallis test was used when assumptions were met. A significant difference was found between the different behaviour clusters and students' academic performance. This study showed that students with high levels of interaction according to behaviour patterns also performed well academically. In addition, students' expectations and motivations for the course were collected and examined using a questionnaire.