External and Internal Predictors of Student Satisfaction with Online Learning Achievement

Abstract

Building and testing a framework of interactive and indirect predictors of student satisfaction would help us understand how to improve students’ online learning experiences. The current study proposed that external predictors such as poor technological, environmental, and pedagogical factors would be internalized as negative psychological traits and indirectly predict student satisfaction in online learning. Results of multivariate regressions with 5824 Chinese undergraduate students demonstrated that instructors’ online teaching experience and communication with students had a stronger predictive effect on student satisfaction than wireless network quality and learning environment. Structural equation modeling analysis results showed that inferior technological, environmental, and pedagogical factors would be internalized into negative attitudes and emotions toward online learning and indirectly predict student satisfaction. Third, providing after-class learning materials to students or having longer self-learning time would not buffer students from negative external factors. Our study has implications for better understanding the extensive influence of online learning barriers caused by external conditions and building preventive mechanisms through the improvement of instructors’ teaching experience and communication with students.