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Citation: Rongxiu Zhu. 基于生成式人工智能的有机化学教学创新：学生角色、教师职责与学习迁移[J]. University Chemistry, ;2026, 41(10): 47-55. doi: 10.12461/PKU.DXHX202510050 shu

基于生成式人工智能的有机化学教学创新：学生角色、教师职责与学习迁移

Rongxiu Zhu ^,

School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100, Shandong Province, China

Corresponding author: Rongxiu Zhu, rxzhu@sdu.edu.cn
Received Date: 15 October 2025
Accepted Date: 17 November 2025

生成式人工智能(Generative Artificial Intelligence，GenAI)的迅速发展正重塑高等教育的教学形态。作为实验性强、概念抽象且知识体系庞大的核心学科，有机化学教学正面临来自AI的机遇与挑战。一方面，ChatGPT、DeepSeek等模型为学生提供了即时的知识生成、反应机理与核心概念的理解以及写作辅助功能，激发学习兴趣，促进自我解释与知识迁移；另一方面，缺乏引导的使用可能引发依赖性、削弱批判性思维，并带来学术诚信风险。本文以“学生角色重构-教师职责转变-学习迁移促进”为主线，在“批判性乐观主义”的教育哲学视角下，分析AI驱动学习生态中师生关系的再定义。进一步提出以AI素养、提示词设计与迁移性任务为核心的教学框架，并结合课堂实践阐明其实施要点与评价路径，旨在为高校有机化学课程的教学创新与教育评价提供可推广的参考。
- Generative artificial intelligence,
- Organic chemistry education,
- Learning transfer,
- Student roles,
- Teacher responsibilities,
- Teaching innovation
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