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.

翻译：绘画通过外化心智模型来支持学习，但大规模提供及时反馈仍然具有挑战性。我们提出了Draw2Learn系统，旨在探索AI如何在基于绘画的学习过程中扮演支持性队友的角色。该设计将学习原则转化为具体的交互模式：AI生成结构化的绘画任务，提供可选的视觉支架，监控学习进度，并提供多维度的反馈。我们在系统开发过程中收集了形成性用户反馈和开放式评论。反馈显示，用户对系统的可用性、实用性和用户体验给出了积极评价，主题突出了AI支架的价值和学习者自主性。这项工作为生成式学习中面向队友的AI贡献了一个设计框架，并为未来研究指明了关键考量因素。