Date
Publisher
arXiv
Culturally Relevant Pedagogy (CRP) is vital in K-12 education, yet teachers struggle to implement CRP into practice due to time, training, and resource gaps. This study explores how Large Language Models (LLMs) can address these barriers by introducing CulturAIEd, an LLM tool that assists teachers in adapting AI literacy curricula to students ' cultural contexts. Through an exploratory pilot with four K-12 teachers, we examined CulturAIEd 's impact on CRP integration. Results showed CulturAIEd enhanced teachers ' confidence in identifying opportunities for cultural responsiveness in learning activities and making culturally responsive modifications to existing activities. They valued CulturAIEd 's streamlined integration of student demographic information, immediate actionable feedback, which could result in high implementation efficiency. This exploration of teacher-AI collaboration highlights how LLM can help teachers include CRP components into their instructional practices efficiently, especially in global priorities for future-ready education, such as AI literacy.
Study at a glance
- Question: Can an AI tool help teachers adapt learning activities to their students' cultural backgrounds?
- Setting and data: Four K-12 teachers
- Method: Exploratory pilot study
Why it matters
Culturally Relevant Pedagogy is vital in K-12 education, yet teachers struggle to implement it into practice due to time, training, and resource gaps.
Key findings
- In a pilot with four K-12 teachers adapting AI curricula, an AI tool enhanced teachers' confidence in identifying culturally responsive learning opportunities.
- The AI tool also increased teachers' confidence in making culturally responsive modifications to existing educational activities.
- Teachers valued the tool's immediate actionable feedback and integration of student demographic information, noting it could lead to high implementation efficiency.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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