Research on Artificial Intelligence-driven Mathematical Knowledge Mapping Construction and Personalized Teaching Path Optimization

Abstract

At present, the application of artificial intelligence (AI) in the field of education is constantly deepening. Mathematics, as an abstract and logical discipline, is difficult to teach and the differences between students are obvious, and the existing teaching methods often fail to meet the needs of personalized teaching. Based on this, this study will combine AI technology to construct a corresponding mathematical knowledge map to optimize the teaching path and accelerate the realization of personalized teaching in mathematics. The study systematically introduces the construction process of mathematical knowledge graph from the levels of mathematical content extraction, integration and processing, visualization and display, and puts forward an effective program to realize personalized teaching of mathematics based on knowledge graph, which includes providing accurate learning resources and personalized error correction services, and utilizing knowledge graph-driven learning resource recommendation system. In order to build a personalized teaching path in mathematics, and then significantly improve the learning effect of students in mathematics.