Predicting student satisfaction and perceived learning within online learning environments

Abstract

ABSTRACTStudent satisfaction is used as one of the key elements to evaluate online courses, while perceived learning is considered as an indicator of learning. This study aimed to explore how online learning self-efficacy (OLSE), learner–content interaction (LCI), learner–instructor interaction (LII), and learner–learner interaction (LLI) can predict student satisfaction and perceived learning. A total of 167 students participated in this study. Regression results revealed that the overall model with all four predictor variables (OLSE, LCI, LII, and LLI) was significantly predictive of satisfaction and perceived learning. The study found that LCI was the strongest and most significant predictor of student satisfaction, while OLSE was the strongest and most significant predictor of perceived learning. However, LLI was not predictive of student satisfaction and perceived learning. This study suggests that instructors employ strategies that enhance students’ OLSE, LCI, and LII. Research is needed to understand how LLI fosters student learning and satisfaction.