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Citation: Ling Li. A Preliminary Exploration of AI-Enabled Teaching Reform in Chemistry History Course[J]. University Chemistry, ;2025, 40(9): 76-86. doi: 10.12461/PKU.DXHX202411058 shu

A Preliminary Exploration of AI-Enabled Teaching Reform in Chemistry History Course

Ling Li ^,

College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China

Corresponding author: Ling Li, lingli@hubu.edu.cn
Received Date: 19 November 2024
Accepted Date: 18 December 2024

This study addresses the challenges faced in the teaching of chemistry history amid the rapid advancement of information technology. By constructing a knowledge graph based on online course resources and implementing AI teaching assistants, we explore a novel pedagogical approach empowered by artificial intelligence. The integration of knowledge graphs and AI assistants facilitates personalized learning for students and enables teachers to accurately assess learning conditions. Preliminary results from teaching practice suggest that AI-enabled reforms in chemistry history education effectively address existing issues, enhance students’ interest in learning, and improve educational quality. Moreover, the data generated from the knowledge graph and AI teaching assistants serves as a valuable foundation for the continuous enhancement of intelligent curricula.
- Knowledge graph,
- AI teaching assistant,
- History of chemistry,
- Wisdom course
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