mlsanityData to 7 Oct 2026

Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning

arXiv 2604.06200 ↗First posted 13 Mar 2026cs.CY cs.AIcited by 0

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Abstract (arXiv)

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 textcolorfixsupport educators to take control of their creative process. Our contributions are available at: https://comap2025.github.io/.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 109 references that are in the map. First posted on arXiv 13 Mar 2026.

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10 of 109 references.

References · 10

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2022A Survey on In-context Learningcited by 717
  3. 2022PromptChainer: Chaining Large Language Model Prompts through Visual Programmingcited by 134
  4. 2024Simulating Classroom Education with LLM-Empowered Agentscited by 125
  5. 2023ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testingcited by 88
  6. 2025Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Reviewcited by 16
  7. 2024AI Agent for Education: von Neumann Multi-Agent System Frameworkcited by 12
  8. 2016Effects of Sensemaking Translucence on Distributed Collaborative Analysiscited by 3
  9. 2025How Real Is AI Tutoring? Comparing Simulated and Human Dialogues in One-on-One Instructioncited by 2
  10. 2025DiaCDM: Cognitive Diagnosis in Teacher-Student Dialogues using the Initiation-Response-Evaluation Frameworkcited by 2

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