Evaluation of structural and measurement models of student satisfaction in online learning

Abstract

This study aimed to evaluate structural models and measurement models of student satisfaction in online learning. This was a quantitative study using a survey research design. Structural model testing was done by examining the relationship between several variables. The variables in question were the learning management system (LMS), admin services, the performance of facilitator lecturers and student satisfaction in learning. The sample used in this study were 149 students. Data analysis was performed using the multivariate Structural Equation Modeling (SEM) technique. The findings of this study indicated that the facilitator lecturer performance is the variable that has the greatest effect in increasing student satisfaction in online learning. Admin service is another variable that has a positive effect on student satisfaction, both direct and indirect effects. The LMS variable does not show a direct effect on student satisfaction, but the LMS has an indirect effect on student satisfaction through the variable facilitator lecturer performance and admin services.