arXiv:2508.14825cs.HCcs.AI2025-08被引 23

提出AI从工具到学习伙伴的四阶段框架,助力人机协同教学设计。

From Passive Tool to Socio-cognitive Teammate: A Conceptual Framework for Agentic AI in Human-AI Collaborative Learning

  • 构建四层级框架:从适应性工具到同侪协作伙伴。
  • 强调功能协作可行,即使无真实意识也能高效共学。
  • 适合教育科技、学习科学领域研究者参考。

人工智能在教育中的角色正快速演变,从传统的教学工具转向学习过程中的主动参与者。这一转变由具备自主目标行动能力的代理型AI推动,但当前领域缺乏理解、设计与评估这种新型人机互动模式的理论框架。本文提出一个全新的概念框架(APCP框架),描述了从工具型AI向协作型伙伴过渡的过程。该框架基于社会文化学习理论与计算机支持协作学习(CSCL)理念,构建了一个四级模型,体现人机协同学习中AI代理性的逐步提升:(1) 自适应工具,(2) 主动助手,(3) 共学伙伴,(4) 同侪合作者。框架为分析人与AI角色与责任的变化提供了结构化语言。论文进一步探讨合作的哲学基础,质疑缺乏真实意识或共同意图的AI是否可视为真正合作者。结论认为,尽管AI无法实现现象学意义上的伙伴关系,但可通过设计成为高效的职能合作者。这一区分对教学法、教学设计及未来研究具有重要意义,呼吁将关注点转向构建能发挥人类与AI互补优势的学习环境。

原文摘要 · Abstract (English)

The role of Artificial Intelligence (AI) in education is undergoing a rapid transformation, moving beyond its historical function as an instructional tool towards a new potential as an active participant in the learning process. This shift is driven by the emergence of agentic AI, autonomous systems capable of proactive, goal-directed action. However, the field lacks a robust conceptual framework to understand, design, and evaluate this new paradigm of human-AI interaction in learning. This paper addresses this gap by proposing a novel conceptual framework (the APCP framework) that charts the transition from AI as a tool to AI as a collaborative partner. We present a four-level model of escalating AI agency within human-AI collaborative learning: (1) the AI as an Adaptive Instrument, (2) the AI as a Proactive Assistant, (3) the AI as a Co-Learner, and (4) the AI as a Peer Collaborator. Grounded in sociocultural theories of learning and Computer-Supported Collaborative Learning (CSCL), this framework provides a structured vocabulary for analysing the shifting roles and responsibilities between human and AI agents. The paper further engages in a critical discussion of the philosophical underpinnings of collaboration, examining whether an AI, lacking genuine consciousness or shared intentionality, can be considered a true collaborator. We conclude that while AI may not achieve authentic phenomenological partnership, it can be designed as a highly effective functional collaborator. This distinction has significant implications for pedagogy, instructional design, and the future research agenda for AI in education, urging a shift in focus towards creating learning environments that harness the complementary strengths of both human and AI.

人机协作教育AI学习理论

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