Chengye Jia

School of Economics, Shandong University of Finance and Economics

Abstract：

The rapid advancement of artificial intelligence (AI) technology has brought about revolutionary changes in the education sector. Research on AI-empowered precise personalized learning paths is a key direction for driving the digital transformation of education. This study explores a personalized learning framework based on learner profiles, knowledge graphs, and adaptive algorithms. It analyzes the educational applications of core technologies such as machine learning, natural language processing, and affective computing. Through case studies from both domestic and international contexts, the study demonstrates the significant benefits of this model in enhancing learning efficiency and promoting educational equity. AI-driven personalized learning can achieve the educational ideal of 'teaching according to individual aptitude,' but it still faces challenges in areas such as technical ethics, data privacy, and large-scale application.

Key Words：

personalized learning; learning path; educational technology; knowledge graph