Decoding E-Learning Adoption: Key Drivers Shaping Students' Intentions in Shanghai's Higher Education Landscape
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Purpose This study explores how performance expectancy, effort expectancy, social influence, hedonic motivation, habit, facilitating conditions, and learning value affect the behavioral intention of university students in Shanghai to use e-learning. Research design, data, and methodology: The study's validity was ensured by using the Index of Item-Objective Congruence, and reliability was evaluated with Cronbach's Alpha. A total of 100 valid responses were analyzed through multiple linear regression. Additionally, 30 students took part in a 14-week Intervention Design Implementation (IDI), with results analyzed via a paired-sample t-test. Results: Data from 100 students were analyzed using multiple linear regression, revealing that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habits, and learning value have a significant impact on behavioral intention. Nevertheless, social influence has no significant impact on behavioral intention. Additionally, there is a significant mean difference in performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habits, learning value, and behavioral intention between the Pre-IDI and Post-IDI stages. Conclusions: The findings reveal that all the factors studied impact behavioral intentions, providing valuable insights for improving e-learning platform design in higher education. This research offers a strong foundation for future studies in this area.
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