Draw2Learn: A Human-AI Collaborative Tool for Drawing-Based Science Learning

• URL: http://arxiv.org/abs/2602.01494v1
• Date: Mon, 02 Feb 2026 00:06:08 GMT
• Title: Draw2Learn: A Human-AI Collaborative Tool for Drawing-Based Science Learning
• Authors: Yuqi Hang,
• Abstract summary: Drawing supports learning by externalizing mental models, but providing timely feedback at scale remains challenging.<n>We present Draw2Learn, a system that explores how AI can act as a supportive teammate during drawing-based learning.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Drawing supports learning by externalizing mental models, but providing timely feedback at scale remains challenging. We present Draw2Learn, a system that explores how AI can act as a supportive teammate during drawing-based learning. The design translates learning principles into concrete interaction patterns: AI generates structured drawing quests, provides optional visual scaffolds, monitors progress, and delivers multidimensional feedback. We collected formative user feedback during system development and open-ended comments. Feedback showed positive ratings for usability, usefulness, and user experience, with themes highlighting AI scaffolding value and learner autonomy. This work contributes a design framework for teammate-oriented AI in generative learning and identifies key considerations for future research.

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