Research on the Teaching Reform of Organic Chemistry Based on Large Language Models and Quantum Chemistry Calculations
ZHANG Bo-Sheng1**, LIANG Yong-Min2
1. College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou 730070, China; 2. State Key Laboratory of Natural Product Chemistry, Lanzhou University, Lanzhou 730030, China
Abstract Large language models(LLMs) have been widely applied in programming education,offering learners intelligent tutoring,example analysis,and practical support.Herein,we introduce LLMs and quantum computational techniques into the traditional field of chemistry education,targeting chemistry teachers at the university and high school.This approach enables teachers to run quantum chemistry software without needing to master the underlying theory,solely by leveraging LLMs.They can then seamlessly integrate the computational results as teaching materials into their classrooms.Using three typical abstract concepts in organic chemistry teaching as examples:SN2 reaction transition states,conformational analysis,and infrared spectral analysis.We demonstrate how dynamically visualized vibrational modes,chemical bond rotations,and atomic trajectories of transition states significantly lower students’ cognitive barriers and deepen their essential understanding of reaction mechanisms and molecular behavior.This method aims to provide traditional chemistry teachers with low-barrier,replicable teaching examples,dissolving technical barriers and promoting the genuine integration of computational chemistry into everyday teaching practice.
ZHANG Bo-Sheng, LIANG Yong-Min. Research on the Teaching Reform of Organic Chemistry Based on Large Language Models and Quantum Chemistry Calculations[J]. Chinese Journal of Chemical Education, 2026, 47(2): 105-113.
