ISSN: 2226-6348
Open access
The rapid advancement of Artificial Intelligence (AI) has significantly impacted various sectors, including higher education. The advancement of technology has urged a necessity for the development of AI-driven personalised learning in an attempt to foster a greater degree of student engagement, encourage a student-centred learning approach as well as the creation of adaptive learning systems. This research addresses how AI-based personalized learning and curriculum design can affect higher education as well as how it helps to engage students in China. It is grounded in Self Determination Theory and is an examination of the ways in which AI can improve autonomy, competence, relatedness, and motivation, in addition to the concepts of Herzberg’s Two-Factor theory. In closing, the study fills research gaps with an analysis of how AI was aligned with China’s educational policies.The survey of 423 university students will take place in the study and the IBM SPSS software will be used for the collection data. It is expected that the relationship between each of the aspects of the AI-based personalized learning will be observed after the research and the outcome can be helpful for the policymakers. The study enhances student engagement by fostering autonomy, competence, and motivation, as explained through SDT and Herzberg’s theory. Some suitable strategic and practical recommendations include faculty training, robust infrastructure, and industry collaboration, ensuring equitable, dynamic, and effective curriculum design are also involved for further improvement.
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