语法课中教师元语言提问的困境与AI赋能路径研究

Challenges of Teachers’ Metalinguistic Questioning in Grammar Classrooms and AI-Empowered Pathways

摘要: 本研究探讨生成式人工智能如何支持高中英语教师提升语法课堂中的元语言提问能力。通过分析B站及国家中小学智慧教育平台的15个真实语法教学视频，本文发现教师的元语言提问存在的四个主要困境：认知层次偏低、提问焦点狭窄、提问类型单一及语境化不足。针对这些问题，本研究通过与DeepSeek的协作模拟，揭示了AI赋能的具体路径，初步证明AI能够通过减轻认知负荷、扩充教学资源来增强教师设计高质量元语言提问的能力。不过，AI的有效应用还依赖于教师的提示技能与批判性素养，需加以审慎引导。本研究为AI推动语法教学创新与教师专业发展提供了初步证据。

Abstract: This study investigates how generative artificial intelligence can support high school English teachers in enhancing their metalinguistic questioning skills in grammar instruction. By analyzing fifteen real grammar lessons sampled from Bilibili and the National Smart Education Platform for Primary and Secondary Schools, four major challenges were identified: low cognitive demand, narrow focus of questions, limited question types, and insufficient contextualization. To address these issues, collaborative simulations with DeepSeek were conducted to reveal specific AI-empowered pathways. This study preliminarily demonstrates that AI can enhance teachers’ ability to design high-quality metalinguistic questions by reducing cognitive load and expanding instructional resources. However, effective use of AI depends on teachers’ prompt engineering skills and critical digital literacy, requiring careful guidance. This study provides preliminary evidence for leveraging AI to innovate grammar instruction and support teacher professional development.