Student motivation and ai use: a pathway to academic performance

Ling, Minnie Yee Lynn (2026) Student motivation and ai use: a pathway to academic performance. Final Year Project, UTAR.

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Abstract

The rapid advancement of artificial intelligence has now changing the way people learn in university around the world. It offers new opportunities for personalised learning, improved efficiency and enhanced academic support. However, despite Malaysia’s national initiatives to strengthen digital readiness, the adoption of AI tools among university students remains uneven. This study examines the motivational factors that influence Malaysian university students’ intention to use AI, investigates how AI usage relates to their perceived academic performance and identifies key challenges they faced while using AI. This study grounded in the Self-Determination Theory (SDT) and the Technology Acceptance Model (TAM), this research explores both intrinsic and extrinsic drivers of AI usage. SDT highlights the importance of autonomy, relatedness and competence, whereas TAM mentioned about perceived usefulness and ease of use as determinants of behavioural intention to use AI. By integrating both frameworks, this study provides comprehensive understanding of students’ readiness in adopting AI in higher education. This study also applied mixed-method design which incorporating both quantitative surveys and qualitative interviews to capture students’ AI experience. The findings revealed that competence, relatedness and perceived usefulness are the strong predictor of behavioural intention to use AI. AI usage was also found to have a positive relationship with perceived academic performance. Nonetheless, there are few challenges emerged, including insufficient trust in AI, privacy concerns, over-reliance, etc.

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