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📄 Research Article

Culturally-Aware AI for Cross-Boundary Community Learning

◐ medium · 2026-06-09higher-ed, ai-literacy, equity, student-experience, teacher-role, intelligent-tutoring

Reports on cross-boundary Community-Based Learning where undergraduate students develop AI-enabled solutions for cultural heritage preservation and sustainable development. The paper argues that AIED research often lacks human-centered grounding and adequate attention to cultural context, and that Community-Based Learning — a pedagogy rooted in social work — remains underrepresented in AIED, particularly within Asia-Pacific contexts.

Contributions: Examines how community-engaged computing operationalizes human-centered AIED across three dimensions: education, technology, and culture. Proposes a collaborative framework for culturally-aware AIED that fosters multi-stakeholder collaboration while widening participation by dissolving disciplinary silos between social work and computational science.

The framework emphasizes cultural contextualization of AI tools, community-driven problem identification, and student-centered design processes. Relevant to higher education contexts seeking to integrate AI education with socially meaningful projects.

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  • Intelligent Tutoring
  • AI Literacy
  • Equity
  • Student Experience
  • Higher Ed

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    • Citation

    Zhao, J., Zhang, W., Cai, J., Gao, H., & Zhang, L. (2026). Culturally-Aware AI for Cross-Boundary Community Learning: Undergraduate Innovation at the Intersection of Computation and Design. arXiv:2606.09041.