Deconstructing the Complex Network of Student Satisfaction in Open and Distance Learning: An Application of Structural Equation Modeling

Abstract

The rapid spread of open and distance learning (ODL) in higher education has sparked a strong interest in the determinants of student satisfaction. Although previous studies have explored various factors that influence satisfaction, a comprehensive model integrating multiple dimensions is still lacking. This study proposes and empirically tests a comprehensive structural equation model of ODL student satisfaction, incorporating interaction, instructor quality, learning management system (LMS), assessment, and student self-regulation as key predictors. Based on constructivist, collaborative, and cognitive information processing theories, we hypothesize direct effects and mediation relationships between these constructs. Data collected from 1,450 students at a large open university in China were analyzed using partial least squares structural equation modeling (PLS-SEM). The results reveal complex interrelationships among the predictors, with interaction and self-regulation emerging as key mediating variables. This study contributes to the ODL literature by providing a nuanced understanding of the satisfaction formation process and offers practical implications for improving the ODL experience. Our findings highlight the need for a holistic approach to ODL design and implementation, emphasizing the synergistic effects of technology, instructional, and personal factors in fostering student satisfaction.