Empowering student learning with generative AI: A self-determination perspective on adoption in tertiary education
DOI:
https://doi.org/10.14742/ajet.11097Keywords:
self-determination, generative AI, reliability, personalised learning, pedagogical drawbacks, data security and privacy, VietnamAbstract
The rapid integration of generative artificial intelligence (GenAI) in education presents both transformative opportunities and challenges for educators. This study investigated the key determinants influencing students' self-determined motivation to adopt GenAI applications in their learning activities. Using a self-reported questionnaire survey, data from 375 university students in Vietnam were analysed through covariance-based structural equation modelling. Our results indicate that the reliability of GenAI and the personalised learning experience it provides foster students’ intention to adopt GenAI, whereas pedagogical drawbacks and concerns over data security and privacy hinder its adoption. Furthermore, our findings reveal that digital competence positively moderates the impact of reliability on students' intention to adopt GenAI. The study highlights the perceived benefits of GenAI in promoting self-determined and personalised learning, alongside its limitations in addressing pedagogical needs and ensuring personal data security seeking to enhance student’s learning effectiveness within a GenAI-enabled digital learning environment.
Implications for practice or policy:
- University educators can enhance student autonomy and competence by integrating generative AI tools into personalised learning activities.
- Institutional leaders should develop clear guidelines and training to address data privacy and ethical use of AI in teaching.
- Curriculum designers may need to embed digital competence development to support effective and equitable AI adoption among students.
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Copyright (c) 2026 Thu-Hang Hoang, Teck Lee Yap, Minh Nguyen , Son Nguyen, Lam Nguyen Canh, Duy Dang , Huy Truong Quang, an duong

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