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

arXiv: https://arxiv.org/abs/2604.06200 · HTML: https://mlsanity.com/paper/2604.06200/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 109 references that are in the map.
- First posted on arXiv 13 Mar 2026.

## Builds on (most cited first, 10 of 10)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [A Survey on In-context Learning](https://mlsanity.com/paper/2301.00234/) (2022)
- [PromptChainer: Chaining Large Language Model Prompts through Visual Programming](https://mlsanity.com/paper/2203.06566/) (2022)
- [Simulating Classroom Education with LLM-Empowered Agents](https://mlsanity.com/paper/2406.19226/) (2024)
- [ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing](https://mlsanity.com/paper/2309.09128/) (2023)
- [Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review](https://mlsanity.com/paper/2501.12557/) (2025)
- [AI Agent for Education: von Neumann Multi-Agent System Framework](https://mlsanity.com/paper/2501.00083/) (2024)
- [Effects of Sensemaking Translucence on Distributed Collaborative Analysis](https://mlsanity.com/paper/1603.04931/) (2016)
- [How Real Is AI Tutoring? Comparing Simulated and Human Dialogues in One-on-One Instruction](https://mlsanity.com/paper/2509.01914/) (2025)
- [DiaCDM: Cognitive Diagnosis in Teacher-Student Dialogues using the Initiation-Response-Evaluation Framework](https://mlsanity.com/paper/2509.24821/) (2025)

## 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/.