The Driving Factors of Online Learning Satisfaction and Online Continuous Learning Intention Among Sophomores in Chengdu, China - Wang, Dong (Scholar: Human Sciences, 2025)
Purpose: This study examines the factors influencing satisfaction with online learning and the continuous learning intention among sophomore university students in Chengdu. Research Design, Data, and Methodology: Quantitative methods and questionnaires were employed to gather sample data. Content validity and reliability of the questionnaire were assessed through item-objective congruence and pilot tests before distribution. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were utilized for data analysis, validating the model’s goodness of fit and confirming causal relationships among variables for hypothesis testing. Results: Online learning satisfaction significantly predicts the intention to continue learning online. Information quality and instructor quality play pivotal roles in influencing students’ online learning satisfaction, followed by system quality and course website quality, with reliability also impacting satisfaction. Consequently, students’ satisfaction with online learning emerges as the strongest predictor directly and indirectly influencing their intention to continue learning online. Information quality and instructor quality significantly drive online learning satisfaction, while system quality and course website quality strongly impact satisfaction. Conclusions: This study is significant in exploring online education in higher education, especially amid the COVID-19 pandemic 2019. It provides insights into the experiences of second-year university students in transition, aiming to enhance their willingness to engage in online learning.