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Artificial intelligence provides strong technical support for the personalized learning. However, students' participation is the key core of learning effect. From the perspective of understanding students, this paper analyzes the student-centered learning; discusses the reliability of the technology-driven personalized learning in promoting students autonomy and establishing the feedback and assessment; summarizes the key factors that affect students' participation, and draws the technology-driven personalized learning model. On this basis, focusing on motivation, understanding beliefs, and participating in learning communities, three-layer architecture of learning to do something is built. The study provides the theory, experience and methods that can be used for the integration of artificial intelligence into education and the promotion of personalized learning.
Chang et al. (Thu,) studied this question.