Abstract: The groundbreaking advancements in Generative Artificial Intelligence (GAI) technology have introduced novel perspectives for reforming traditional educational curricula. This study focuses on physical chemistry courses, presenting and implementing an AI-enhanced teaching reform strategy. By harnessing DeepSeek’s capabilities in natural language understanding and reasoning, we have developed an integrated approach incorporating Xmind, Mathematica, and JiMing AI. This integration facilitates the creation of a systematic, hierarchical mind map that enables dynamic knowledge connections and intelligent expansion. Furthermore, complex mathematical models are transformed into dynamic, interactive representations, effectively overcoming the challenges posed by abstract mathematical concepts. Additionally, key concepts are presented through high-precision diagrams and concise video demonstrations, achieving a “visual, interactive, and mobile” delivery of educational content. This approach provides a practical framework for the digital transformation of chemistry education.

Key words: DeepSeek, Systematic hierarchical mind map, Interactivity