AI驱动的英语教材可实现个性化学习与教学减负
Structure and Implementation of New Practical English Textbooks Driven by Artificial Intelligence
- 构建五层架构：知识映射、学情画像、任务生成、反馈协调与教师管理
- 学生完成率提升至84.9%，口语成绩平均提高10.8分，教师批改时间减少31.6%
- 适合教育科技研发者、一线教师及智能教学系统使用者
人工智能正将应用型英语教材从固定纸本序列转变为可诊断学习者、推荐任务并提供形成性反馈的自适应学习系统。本文研究了一种由人工智能驱动的新式实用英语教材的结构与应用。提出包含知识映射、学情画像、任务生成、反馈协调与教师侧治理的五层架构。在186名非英语专业本科生中进行了为期八周的教学测试。相比静态数字教材，该系统使单元完成准确率从72.4%提升至84.9%，口语任务平均分提高10.8分，教师批改时间减少31.6%。结果表明，AI驱动的教材可在保持课程稳定性的同时，提供个性化学习路径、丰富练习材料与可追溯的课堂数据。
原文摘要 · Abstract (English)
Artificial intelligence is changing the form of applied English materials from fixed paper sequences to adaptive learning systems that can diagnose learners, recommend tasks, and provide formative feedback. This paper studies the structure and application of a new practical English textbook driven by artificial intelligence. A five-layer architecture is proposed: knowledge mapping, learner profiling, task generation, feedback orchestration, and teacher-side governance. A prototype was tested on 186 non-English-major undergraduates for eight weeks of teaching. Compared with a static digital textbook, the proposed system increased the unit completion accuracy from 72.4% to 84.9%, raised the average score for speaking tasks by 10.8 points, and reduced the teacher's correction time by 31.6%. Therefore, an AI-driven textbook can maintain the stability of the curriculum while providing personalised learning paths, rich practice materials and traceable classroom data.
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