基于CoMAP的图式思维：一种用于项目式学习的设计共享视觉工作区
Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning
AI总结：
本文提出CoMAP，一种基于图的协作范式，通过共享视觉工作区和双模态AI支持，提升教师的设计表达、发散思维和迭代实践能力。
摘要：
设计项目式学习（PBL）需要管理高度互相关联的组件，这使传统线性工具和纯对话式AI都面临挑战。传统工具无法捕捉创造性设计的非线性本质，而对话系统缺乏持续共享的上下文以支持反思性协作。基于分布式认知理论，我们引入CoMAP，一种图基协作系统。通过提供共享视觉工作区和双模态AI支持，CoMAP将人与AI的关系从提示-响应循环转变为透明且公平的伙伴关系。我们对30名教育工作者的研究表明，与仅对话的基线相比，CoMAP显著提高了教师的设计表达、发散思维和迭代实践能力。这些发现展示了非线性和以制品为中心的方法如何促进信任、减少认知负荷，并支持教育工作者掌控其创造性过程。我们的贡献见：https://comap2025.github.io/.
英文摘要：
Designing project-based learning (PBL) demands managing highly interdependent components, a task that both traditional linear tools and purely conversational AI struggle with. Traditional tools fail to capture the non-linear nature of creative design, while conversational systems lack the persistent, shared context necessary for reflective collaboration. Grounded in theories of distributed cognition, we introduce CoMAP, a system that embodies a graph-based collaboration paradigm. By providing a shared visual workspace with dual-modality AI support, CoMAP transforms the human-AI relationship from a prompt-and-response loop into a transparent and equitable partnership. Our study with 30 educators shows CoMAP significantly improves teachers' design expression, divergent thinking, and iterative practice compared to a dialogue-only baseline. These findings demonstrate how a nonlinear, artifact-centric approach can foster trust, reduce cognitive load, and \textcolor{fix}{support} educators to take control of their creative process. Our contributions are available at: https://comap2025.github.io/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
