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Bridging Cultural Distance Between Models Default and Local Classroom Demands: How Global Teachers Adopt GenAI to Support Everyday Teaching Practices

Authors
Ruiwei Xiao,
Qing Xiao,
Xinying Hou,
Hanqi Jane Li,
Phenyo Phemelo Moletsane,
Hong Shen,
John Stamper
Date
Publisher
arXiv
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.
Study at a glance
  • Question: How do teachers navigate cultural differences between generative AI tools and their local classrooms?
  • Setting and data: 30 K-12 teachers who integrated AI into teaching, 10 each from South Africa, Taiwan, and the United States.
  • Method: In-depth interviews
Why it matters

Generative AI is rapidly entering K-12 classrooms, yet models are often trained on culturally uneven datasets that embed a "default culture." This default culture often misaligns with the situated demands of local classrooms and everyday teaching practices.

Key findings
  • Among 30 K-12 teachers in South Africa, Taiwan, and the United States, educators experienced misalignments between generative AI's default culture and local classroom demands.
  • The cultural gap between generative AI's default repertoire and classroom demands spans three distinct levels: low, mid, and high distance.
  • Teachers developed specific strategies to navigate and bridge these low, mid, and high levels of cultural distance in their everyday teaching.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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