让AI生成符合年级水平的教育内容，更懂孩子能理解什么。
COGENT: A Curriculum-oriented Framework for Generating Grade-appropriate Educational Content
- 用课程三要素控制内容结构，匹配教学目标
- 通过词长句复杂度调节阅读难度，确保适龄
- 用‘好奇驱动’设计提升学生兴趣，适合教育从业者
尽管生成式AI在内容生成方面展现出强大潜力，但在教育场景中仍面临诸多挑战。模型常难以契合课程标准，且难以持续保持适合特定年级的阅读难度。尤其在科学、技术、工程与数学（STEM）教育中，如何在抽象概念与日常语言之间取得平衡，对低龄学生尤为困难。本文提出COGENT框架，围绕课程要素（科学概念、核心思想、学习目标）构建内容生成体系，通过控制文本长度、词汇复杂度与句子结构来调节可读性，并采用“好奇驱动”策略增强学生参与感。我们通过大语言模型评分与专家人工评估进行多维度验证。实验结果表明，COGENT生成的内容在年级适配性上与人类参考文本相当或更优。本研究为规模化生成自适应高质量学习资源提供了可行路径。
原文摘要 · Abstract (English)
While Generative AI has demonstrated strong potential and versatility in content generation, its application to educational contexts presents several challenges. Models often fail to align with curriculum standards and maintain grade-appropriate reading levels consistently. Furthermore, STEM education poses additional challenges in balancing scientific explanations with everyday language when introducing complex and abstract ideas and phenomena to younger students. In this work, we propose COGENT, a curriculum-oriented framework for generating grade-appropriate educational content. We incorporate three curriculum components (science concepts, core ideas, and learning objectives), control readability through length, vocabulary, and sentence complexity, and adopt a ``wonder-based'' approach to increase student engagement and interest. We conduct a multi-dimensional evaluation via both LLM-as-a-judge and human expert analysis. Experimental results show that COGENT consistently produces grade-appropriate passages that are comparable or superior to human references. Our work establishes a viable approach for scaling adaptive and high-quality learning resources.
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