Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866917388918718464 |
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| author | Li, Ruijia Jiang, Bo |
| author_facet | Li, Ruijia Jiang, Bo |
| contents | 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/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_06200 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning Li, Ruijia Jiang, Bo Computers and Society Artificial Intelligence 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/. |
| title | Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2604.06200 |