探索AI支持的学生项目团队基于文本的交流中的学科调解
Exploring AI-Supported Disciplinary Mediation in Student Project Teams' Text-Based Communication: A Probe-Grounded Co-Design Study
浏览论文内容
中文总结 AI 辅助
本研究提出基于Discord的LLM工具Spritz，通过监测群聊边界信号、匿名综合观点等方式调解学生跨学科项目团队交流，发现其兼具认知与关系价值，但需解决AI角色扩展带来的中立性张力问题。
中文摘要 AI 辅助
基于项目的跨学科学习要求学生就语言、假设、优先级和工作方式的差异进行协商。这些差异在基于文本的团队交流中难以显现，讨论可能变得碎片化，而AI工具常被用作私人辅助渠道，而非集体意义建构的共享支持。我们提出Spritz，这是一种基于Discord的大语言模型（LLM）技术探针，旨在探索AI如何调解学生项目团队中的学科边界。Spritz会监测群聊中语义或语用边界的信号，提示成员通过私人渠道阐明自身观点，并将匿名综合结果反馈至共享讨论中。我们开展了一项技术探针研究和联合设计工作坊，参与者为12名来自技术、商业和设计背景的大学生。参与者在模拟跨学科资源分配任务中使用Spritz，并反思AI在协作中的作用。研究结果显示，参与者重视AI调解不仅是用于跨边界的认知支持，也是一种关系缓冲。Spritz帮助组织碎片化讨论、显现隐性预期、澄清不同解读，同时缓和分歧与让步相关的人际压力。参与者还设想未来AI调解者可具备可切换角色，包括战略顾问、跨领域翻译和视角挑战者。然而，这些扩展角色带来了核心设计张力：当AI开始建议、挑战或影响团队决策时，使其作为调解者可接受的中立性变得不稳定。我们为在基于文本的交流中调解跨学科协作，同时保留人类能动性、信任、隐私和问责制的AI系统提供了实证见解和设计考量。
英文摘要
Interdisciplinary student teams must negotiate differences in terminology, priorities, and practices, yet these differences are difficult to surface in text-based communication. We introduce Spritz, a Discord-based LLM technology probe designed to create a situated experience of AI-mediated collaboration for reflection and co-design. Spritz detects semantic or pragmatic tensions, privately prompts members to articulate their perspectives, and returns anonymized syntheses to group discussion. We conducted an exploratory study and co-design workshop with 12 students from technical, business, and design backgrounds. Preliminary findings suggest that participants perceived AI mediation along cognitive and relational dimensions. Spritz helped organize fragmented discussions, surface implicit reasoning, and reduce interpersonal pressure around disagreement. Participants also envisioned AI as a strategic advisor, cross-domain translator, and perspective challenger, raising tensions around neutrality, authority, and accountability. We discuss implications for negotiable interventions, transparent role transitions, and preserving human ownership of team decisions.
