Abstract: Inorganic chemistry serves as a fundamental core course for related majors in traditional Chinese medicine universities. However, it faces several challenges, including fragmented knowledge points, abstract concepts, and limited class hours. Traditional teaching methods often result in passive learning and inadequate student-teacher interaction. While the flipped classroom approach can enhance students' learning engagement and comprehensive abilities, it still presents limitations such as difficulties in tracking autonomous learning outcomes and insufficient depth in classroom interactions. To address these issues, this study proposes an innovative integration of artificial intelligence technology with the inorganic chemistry flipped classroom, establishing a full-process interactive teaching model. This model is based on the concept of “knowledge graph construction and AI technology empowerment”. Relying on an intelligent teaching platform, it customizes personalized after-class learning plans. It facilitates intelligent group guidance during class sessions and enables precise post-class feedback. This approach effectively mitigates the shortcomings of traditional flipped classrooms, aligns with the pedagogical characteristics of inorganic chemistry, meets students' learning needs, and provides a practical pathway for reforming fundamental course instruction in traditional Chinese medicine universities.

Key words: AI empowerment, Knowledge graph, Flipped classroom, Inorganic chemistry, Intelligent instruction