让AI当第三位队友，能提升编程协作的学习效果。
Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative Learning
- 三人协同编程中AI作为平等伙伴，而非替代人类。
- 相比人机协作，三人组更少依赖AI生成代码，学习更主动。
- 适合关注协作学习、AI辅助教育的研究者和开发者。
随着AI融入编程实践，研究者们越来越关注其如何帮助学习者生成代码并提高效率。然而，这些研究常将AI视为人类协作的替代品，忽视了协作编程中的社会性与学习价值。本文提出人-人-人工智能（HHAI）三元协同编程，将AI代理作为额外合作者而非人类伙伴的替代。通过20名参与者参与的自身对照实验，结果表明，相较于人机协作（HAI）基线，三元协作显著增强了协作学习与社会存在感。在三元条件下，参与者对AI生成代码的依赖明显降低，尤其在共享情境中，人们更愿意理解并负责地采纳AI建议。这一现象揭示了三元环境如何通过使AI使用行为对同伴可见且可问责，激活了学习的社会共享调节机制。研究提示，能增强而非自动化同伴协作的AI系统，更能维护协作编程所依赖的学习过程。
原文摘要 · Abstract (English)
As AI assistance becomes embedded in programming practice, researchers have increasingly examined how these systems help learners generate code and work more efficiently. However, these studies often position AI as a replacement for human collaboration and overlook the social and learning-oriented aspects that emerge in collaborative programming. Our work introduces human-human-AI (HHAI) triadic programming, where an AI agent serves as an additional collaborator rather than a substitute for a human partner. Through a within-subjects study with 20 participants, we show that triadic collaboration enhances collaborative learning and social presence compared to the dyadic human-AI (HAI) baseline. In the triadic HHAI conditions, participants relied significantly less on AI-generated code in their work. This effect was strongest in the HHAI-shared condition, where participants had an increased sense of responsibility to understand AI suggestions before applying them. These findings demonstrate how triadic settings activate socially shared regulation of learning by making AI use visible and accountable to a human peer, suggesting that AI systems that augment rather than automate peer collaboration can better preserve the learning processes that collaborative programming relies on.
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