大语言模型辅助高中英语课堂教学研究——以人教版必修三Unit 1 Reading and Thinking为例

Large Language Model-Assisted High School English Classroom Teaching—A Case Study of Unit 1 Reading and Thinking from PEP Book 3

摘要: 本文面向高中英语教学，构建了大语言模型辅助教学的“课前资源生成–课中互动优化–课后评价延伸”三阶段框架，并以人教版高中英语必修三Unit 1 Festivals and Celebrations阅读教学为例，借助ChatGPT-4-turbo展示提示工程驱动的课堂环节设计。文中具体展示了语篇解读、问题链设计、思辨活动创设、写作协同评改等环节的提示词与模型输出。该模式在课前用于生成多层级教学资源，课中提供即时语料与互动支持，课后辅助写作评价。该模式在课前、课中、课后的应用均需教师根据学情对AI输出进行筛选、转译与补充，其有效性取决于人机协同的具体策略。

Abstract: This study proposes a three-stage framework for integrating large language models into high school English teaching: pre-class resource generation, in-class interaction optimization, and post-class evaluation extension. Using ChatGPT-4-turbo, this paper demonstrates prompt engineering-driven classroom activity design around the Reading and Thinking section of PEP Book 3 Unit 1 “Festivals and Celebrations”. The paper documents actual prompts and model outputs across discourse analysis, question-chain design, critical discussion facilitation, and collaborative writing assessment. The framework generates multi-level teaching resources before class, provides real-time language data and interaction scaffolding during class, and supports writing assessment after class. The application of this framework in pre-class, in-class, and post-class stages requires teachers to filter, paraphrase, and supplement AI outputs based on student levels, and its effectiveness depends on the specific strategies of human-AI collaboration.