Application of Artificial Intelligence in Online Education: Influence of Student Participation on Academic Retention in Virtual Courses

The accelerated growth of online education in recent decades has made it a trendy educational option. Despite this, significant challenges persist regarding student retention and academic performance in these courses. Addressing these challenges requires active student participation, although understanding it effectively is complex. This study focuses on student engagement in online education environments, exploring its relationship with retention and academic performance. Data was collected across multiple semesters to analyze student engagement in online educational environments. Participation patterns, temporal trends, and crucial factors affecting participation were examined using exploratory analysis and forecasting models, such as ARIMA and Prophet. The results revealed several patterns, including an initial increase in activity at the course’s beginning and a gradual decrease over time. Factors such as course length and peer interaction influenced participation significantly. These findings underscore the importance of developing specific pedagogical strategies for online education, simultaneously addressing students’ unique challenges in this environment. In summary, this study contributes to knowledge in online education by providing essential information to understand and improve student engagement.