Zhao, Zhang, Cai, Gao & Zhang (2026) — Authors. Multiple institutions. 📄 Full text (arXiv)
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.
Related Pages
- ai-literacy — AI literacy and culturally-aware educational design
- equity — Equity and inclusion considerations in AIED
- higher-ed — Higher education AI integration strategies
- student-experience — Student experiences with community-engaged computing
- teacher-role — Teacher and facilitator roles in community-based AI learning
- ai-k12-evidence-base — Evidence base for AI in education across cultural contexts