BEHAVIORAL ENGAGEMENT AND ACADEMIC SUCCESS IN ONLINE EDUCATION: AN ANALYSIS OF STUDENT INTERACTION PATTERNS
Abstract
This study examines the relationship between behavioral engagement and academic success in online learningenvironments by analyzingstudent interaction patterns derived from a structured dataset. The quantitative research designwas adopted with the use of a secondary dataset, retrieved on Kaggle (xAPI-Edu Data), which contains 480 records ofstudents. Participation, resource use, announcement interaction, and discussion activity were some of the indicators thatwere used to measure behavioral engagement. Python was used to analyze the data with descriptive statistics, reliabilityanalysis, Pearson correlation, ANOVA, and multiple linear regression. The findings show that there is a positive andstrong relationship between academic performance and behavioral engagement. The most important predictors ofacademic success identified were resource utilization and active involvement,with limited contribution of passiveengagement. A major discrepancyinengagement was noted among performance groups. The results emphasize the valueof creating interactive and student-focused online learning platforms that facilitate active learning. The research adds tothe existing body of literature by employing real-world LMS data and Python-based analysis to present a data-driveninsight into the dynamics of engagement in online education.
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