Determinants of Satisfaction and Continuance Intention to Use Cloud-Based E-Learning Among Undergraduate Students in Ningxia Universities
DOI:
https://doi.org/10.14456/shserj.2023.52Keywords:
Cloud-Based E-Learning, Course Content Quality, Perceived Usefulness, Satisfaction, Continuance IntentionAbstract
Purpose: This study examines what factors affect the satisfaction and continuance intention of college students majoring in English translation and interpreting on cloud-based e-learning. The conceptual framework consists of task-technology fit, learning-technology fit, interactivity, course content quality, course design quality, organizational support, perceived usefulness, satisfaction and continuance intention. Research design, data, and methodology: A quantitative research method was used to distribute questionnaires to three Ningxia universities and perform data analysis. Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) were applied to analyze the collected results and examine the pre-designed hypotheses' model fit, reliability, and validity. Results: It was found that satisfaction was the strongest predictor of continuance intention, followed by perceived usefulness. In addition to learning-technology fit as an antecedent, task-technology fit, interactivity, course content quality, course design quality, and organizational support showed significant and positive effects on satisfaction and perceived usefulness. Conclusion: Achieving and improving the satisfaction of students to use cloud-based e-learning is the priority for developers, administrators, and teachers. For organizations, adequate support for users and cloud-based e-learning is beneficial to enhance users' perceived usefulness. For developers, updating and ensuring a high degree of technical alignment of the system with the user's mission is an effective approach.
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