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Research demonstrates attitude mediates online learning engagement through intrinsic and extrinsic motivation among pre-university students, suggesting the need for training.
This research focuses on determining the motivational factors that influence online engagement among pre-university students. Based on the self determination theory, the four motivational factors identified in this research include intrinsic and extrinsic motivation, accomplishment and amotivation. This research extends the framework to examining the mediating role of attitude to generative AI technology in the relationship between the four motivational factors with online learning engagement. Data from 103 respondents were collected online, demographic profiles were analyzed using SPSS, and SmartPLS was used to test the conceptual model and assess item reliability through CFA. The results show five supported hypotheses, highlighting attitude and intrinsic motivation as key predictors of online learning engagement. Attitude has the strongest direct effect on online learning engagement, while intrinsic motivation influences both attitude and engagement. Indirect effects via attitude are significant for accomplishment, amotivation, and intrinsic motivation, indicating partial mediation. This study highlights the importance of using generative-AI tools in ensuring online learning engagement among preuniversity students. Practical implications from this study include the need for training for academics and pre-university students to foster positive attitude towards using generative-AI technology.
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Ghani et al. (2026) studied this question.
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