arXiv:2603.23863cs.CYcs.AI2026-03被引 1

提出人机认知协作理论,解释生成式AI如何与用户共同构建知识。

Generative AI User Experience: Developing Human--AI Epistemic Partnership

  • 将用户与AI关系视为动态协商的认知伙伴关系
  • 揭示信任与怀疑共存源于三重契约的持续调适
  • 适合教育科技研究者及AI教学设计者参考

生成式AI已快速进入教育领域,但现有用户体验理论(如有用性、易用性)无法解释其在知识建构中的参与。本文提出人机认知伙伴关系理论(HAEPT),将用户与生成式AI的关系视为一种动态协商过程,包含认知、自主性和责任三重契约。该理论可重新诠释信任、过度依赖、学术诚信等问题为契约张力而非孤立现象。用户通过反复校准互动,不断调整与AI的关系,形成不同协作模式。研究以人机协同学习和科学论辩为例,验证了该理论对多样化交互场景的解释力。

原文摘要 · Abstract (English)

Generative AI (GenAI) has rapidly entered education, yet its user experience is often explained through adoption-oriented constructs such as usefulness, ease of use, and engagement. We argue that these constructs are no longer sufficient because systems such as ChatGPT do not merely support learning tasks but also participate in knowledge construction. Existing theories cannot explain why GenAI frequently produces experiences characterized by negotiated authority, redistributed cognition, and accountability tension. To address this gap, this paper develops the Human--AI Epistemic Partnership Theory (HAEPT), explaining the GenAI user experience as a form of epistemic partnership that features a dynamic negotiation of three interlocking contracts: epistemic, agency, and accountability. We argue that findings on trust, over-reliance, academic integrity, teacher caution, and relational interaction about GenAI can be reinterpreted as tensions within these contracts rather than as isolated issues. Instead of holding a single, stable view of GenAI, users adjust how they relate to it over time through calibration cycles. These repeated interactions account for why trust and skepticism often coexist and for how partnership modes describe recurrent configurations of human--AI collaboration across tasks. To demonstrate the usefulness of HAEPT, we applied it to analyze the UX of collaborative learning with AI speakers and AI-facilitated scientific argumentation, illustrating different contract configurations.

生成式AI人机协作教育技术认知伙伴

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