The Impact of E-Learning Recommendation System on Student Autonomy, Engagement, and Learning Effectiveness

Recommendation systems have made a significant contribution to enhancing online learning. They have improved decision-making, simplified learning experiences, and promoted lifelong learning. However, the impact of these systems on learners requires more transparency, especially among students who need a clear vision of how to effectively benefit from the recommendation assistance in knowledge acquisition. This paper investigates the impact of course recommendation systems on student autonomy, engagement, and learning effectiveness in online education based on a self-administered survey involving 602 students from 11 academic institutions representing diverse educational backgrounds, from high school to PhD level. The results of the structural equation model (SEM) analysis revealed that the Recommender System has a positive impact on student autonomy, student engagement, and learning effectiveness. Based on the path coefficients analysis, it was determined that the Recommender System has a moderately positive influence on Student Autonomy (0.449) and Learning Effectiveness (0.422), as well as a significantly positive impact on Student Engagement (0.622). Furthermore, students consider Recommender System valuable and advantageous as it enhances their online learning engagement and improves their autonomy in decision-making regarding course selection.