大学生用AI助力文化传承，跨学科协作实现以人为本的教育创新
Culturally-Aware AI for Cross-Boundary Community Learning: Undergraduate Innovation at the Intersection of Computation and Design
- 跨学科团队通过参与式方法挖掘文化知识，融合双语表达与多方验证
- 在亚太社区实践中验证了文化敏感型AI教育框架的有效性
- 适合教育科技、社会工作与计算科学交叉领域的研究者参考
人工智能在教育（AIED）的研究快速发展，但技术进步常缺乏人文基础和文化考量。以社会工作为基础的社区学习在AIED中仍属空白，尤其在亚太地区。本文报告了跨边界社区学习实践：本科生开发面向文化遗产保护与可持续发展的AI解决方案。通过参与式文化知识采集、双语表征及教育、技术与文化多方验证，探索了如何将社区参与式计算应用于文化敏感型、以人为本的AIED。论文提出一个协同框架，旨在促进多利益相关方合作，弥合社会工作与计算科学之间的鸿沟，推动更广泛的社会参与。
原文摘要 · Abstract (English)
Research on artificial intelligence in education (AIED) is rapidly expanding, yet technical progress often lacks human-centered grounding and adequate attention to cultural context. Community-Based Learning, a pedagogy rooted in social work, remains underrepresented in AIED research, particularly within Asia-Pacific contexts. This paper reports on cross-boundary Community-Based Learning where undergraduate students develop AI-enabled solutions for cultural heritage preservation and sustainable development. We examine how community-engaged computing operationalizes culturally aware, human-centered AIED through participatory elicitation of cultural knowledge, bilingual representation, and stakeholder validation across education, technology, and culture. We contribute a collaborative framework for culturally aware AIED designed to support multi-stakeholder collaboration and widen participation by bridging social work and computational science.
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