Designing with CARE: A Human-AI Framework for Inclusive Faculty Development in Non-English Contexts

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Abstract

This paper presents a design-based research (DBR) study on inclusive, AI-supported faculty development in a non-English-speaking context. Conducted with 25 Kazakh-speaking faculty members, the study addressed persistent barriers to implementing Universal Design for Learning (UDL) in linguistically and culturally specific environments. Through iterative co-design, generative AI tools (ChatGPT, DALL·E, YesChat) supported the creation of asynchronous Kazakh-language modules. Findings revealed a 42% increase in engagement and a 35% improvement in knowledge retention. Emerging from this work is the CARE framework - Cultural Awareness, Accessibility, Relevance, and Equity – a context-responsive model for inclusive instructional design. CARE offers a structured, human-AI design approach that prioritizes linguistic precision, cultural relevance, and ethical adaptation, contributing a replicable pathway for professional learning in multilingual higher education.

Author

• Aigerim Shilibekova, Simon Fraser University