What AI “Can” and “Cannot” Do in Assisting Classical Chinese Teaching—A Case Study of Twelve Chapters from The Analects

作者：杉 吴 · 发表于：Advances in Education · 年份：2026 · DOI：10.12677/ae.2026.1681598 · 研究领域：Second Language Acquisition and Learning、Language, Metaphor, and Cognition、Educational and Psychological Assessments

文言文教学在课前准备、课中实施与课后评价三个环节均面临效率与效果的双重困境。AI技术的引入为解决上述问题提供了新路径，但其功能边界还需审慎界定。本文认为，AI辅助文言文教学应以教师主导为前提，以认知层级的递升为原则，将AI定位于知识性任务的辅助者与认知冲突的触发者，而非情感引导的替代者。基于此，本文以《论语》十二章为例，通过“AI太炎”与豆包两款工具的功能测评，从释义准确性与翻译质量两个维度比较其差异，继而引入TPACK框架与ICAP理论，构建分析AI角色、教师能力与教学活动设计的框架，并提出课前、课中、课后三个环节的教学措施。Classical Chinese teaching faces dual dilemmas of efficiency and effectiveness in pre-class preparation, in-class implementation, and post-class evaluation. The introduction of AI technology offers new pathways to address these issues, yet its functional boundaries require careful delineation. This paper argues that AI-assisted classical Chinese teaching should be premised on teacher-led instruction, adhere to the principle of progressive cognitive engagement, and position AI as an assistant in knowledge-based tasks and a trigger of cognitive conflicts, rather than a substitute for emotional guidance. On this basis, taking the Twelve Chapters from The Analects as a case, this study conducts a functional evaluation of two tools, “AI Taiyan” and Doubao, comparing their differences in interpretive accuracy and translation quality. It then introduces the TPACK framework and ICAP theory to construct an analytical framework for examining the roles of AI, teacher competencies, and instructional activity design, and proposes teaching measures across the three phases of pre-class, in-class, and post-class implementation.