用互惠与关系思维重构教育AI,避免技术取代人际学习
Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews

- 将教育AI设计为基于互惠关系的协作系统,而非替代人类互动
- 提出在教学中明确不使用AI的场景与教学边界
- 融合原住民世界观,推动可持续的教育生态设计
教育不仅是知识传递或个体绩效优化,更是一种根本性的社会性、建构性和关系性实践。然而,生成式人工智能(GenAI)的发展日益强调效率、自动化和个性化辅助,可能削弱关系性学习过程。尽管应用广泛,教育中的人工智能研究尚未充分阐明如何设计AI以维持学习发生的社交与生态关系。本文重新聚焦教育的关系性本质,将学习者与AI的互动视为具有明确目的与边界的特定关系,而非人类互动的替代品。基于参与式设计实践,并受原住民世界观(包括澳大利亚原住民、美洲原住民及中美洲传统)中互惠与关系责任理念启发,我们主张有意义的教育AI应支持与他人共同学习,而非取代他人。本文推进此观点:(i)将AIED视为根植于互惠关系的设计问题;(ii)阐明GenAI引入的关键张力;(iii)提出扩展AIED设计空间的方向,包括何时不应使用AI、如何定义教学边界,以及如何支持负责任地使用AIED创新,以维护社区与自然环境。
原文摘要 · Abstract (English)
Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and relational practice. However, recent advances in generative artificial intelligence (GenAI) increasingly emphasise efficiency, automation, and individualised assistance, risking the weakening of relational learning processes. Despite growing adoption, AI in education (AIED) research has yet to fully articulate how AI can be designed in ways that sustain the social and ecological relationships through which learning occurs. In this paper, we re-centre education as relational and frame learner-AI interactions as context-specific relationships with clearly defined purposes and boundaries, rather than positioning them as substitutes for, or replacements of, human interaction. Grounded in participatory design practices and inspired by Indigenous worldviews (including Aboriginal Australian, Native American, and Mesoamerican traditions) that foreground reciprocity and relational accountability, we argue that meaningful educational AI should support learning with others rather than replace them. We advance this perspective by: i) conceptualising AIED as a relational design problem grounded in reciprocity; ii) articulating key tensions introduced by GenAI in education; and iii) outlining design directions that expand the AIED design space toward reciprocity, including when not to use AI, how to define pedagogical boundaries, and how to support responsible uses of AIED innovations that sustain communities and natural environments.
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