Học tập cá nhân hóa dựa trên AI: trao quyền cho sinh viên nhằm tăng cường sự tương tác và nâng cao kết quả học tập

Tóm tắt

This paper investigates the impact of AI-Personalized Learning (AIPL)
on multidisciplinary university students, focusing on the relationships between AIPL,
Self-Determination Theory (SDT), student engagement, and academic performance. A
quantitative, cross-sectional survey was conducted with 342 students, and the data were
analyzed using Structural Equation Modeling (SEM). The results show that AIPL positively
influences students' autonomy, competence, and relatedness, consistent with SDT principles.
Competence and relatedness are found to foster engagement, and engagement, in turn,
enhances academic performance. However, autonomy does not directly influence engagement.
Theoretically, the research reinforces the role of SDT in AIPL environments. Practically, the
findings recommend that educational institutions implement AIPL, design systems based on
SDT principles, and provide teacher training. This study contributes to the understanding
of AIPL in multidisciplinary higher education, while acknowledging limitations in its crosssectional
design and sample scope.