Student-content interaction and learning outcomes in MOOCs: The moderating role of self-efficacy

Abstract

This study examines how self-efficacy moderates the relationship between student-content interaction and two key outcomes in Massive Open Online Courses: perceived course quality and sustained learning interest. Using survey data from 343 participants in the Learning How to Learn MOOC on Coursera, we employed structural equation modeling to test main and interaction effects. Participants were predominantly adult learners with diverse educational backgrounds, balanced gender representation, and varied language backgrounds. Results indicate that student-content interaction positively predicts perceived course quality and sustained learning interest. Moderation analyses further show that the positive effects of student-content interaction are strongest for learners with lower self-efficacy and weaker for learners with higher self-efficacy, suggesting a compensatory or ceiling effect. These findings extend prior MOOC research by empirically modeling self-efficacy as a moderating condition rather than only a direct predictor. Practical implications highlight the importance of designing interactive content and self-efficacy-supportive features to promote engagement in large-scale autonomous learning environments. Limitations include reliance on self-reported data and cross-sectional design. Future research should incorporate objective learning analytics and longitudinal approaches to examine how these relationships evolve over time.