揭示AI教学工具与本地课堂文化的差距，提出应对框架
Bridging Cultural Distance Between Models Default and Local Classroom Demands: How Global Teachers Adopt GenAI to Support Everyday Teaching Practices
- 提出'文化距离'概念，衡量AI默认文化与本地教学需求的差异
- 通过30名教师访谈，构建三层次文化距离应对框架
- 为教育AI设计提供公平性与文化适配的实践指南
生成式AI正快速进入中小学课堂，为教学提供新方式。然而，这些模型常基于文化不均的数据集训练，嵌入了‘默认文化’，往往与本地课堂需求不符。为理解教师如何应对这一鸿沟，本文提出‘文化距离’（即生成式AI默认文化与实际教学情境需求之间的差距）的概念，并对来自南非、台湾和美国的30名已使用AI的中小学教师进行了深度访谈，每国10人。这些教师的经验推动了三层次文化距离框架的构建。本研究贡献包括：文化距离的概念与框架、涵盖低、中、高距离水平的六个具体实例，以及教师应对策略。实证上，研究为AI设计者、政策制定者和教育工作者提供了促进教育生成式AI更公平、更具文化响应能力的启示。
原文摘要 · Abstract (English)
Generative AI (GenAI) is rapidly entering K-12 classrooms, offering teachers new ways for teaching practices. Yet GenAI models are often trained on culturally uneven datasets, embedding a "default culture" that often misaligns with local classrooms. To understand how teachers navigate this gap, we defined the new concept Cultural Distance (the gap between GenAI's default cultural repertoire and the situated demands of teaching practice) and conducted in-depth interviews with 30 K-12 teachers, 10 each from South Africa, Taiwan, and the United States, who had integrated AI into their teaching practice. These teachers' experiences informed the development of our three-level cultural distance framework. This work contributes the concept and framework of cultural distance, six illustrative instances spanning in low, mid, high distance levels with teachers' experiences and strategies for addressing them. Empirically, we offer implications to help AI designers, policymakers, and educators create more equitable and culturally responsive GenAI tools for education.
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