AI 中文总结
研究实时协作编程中同伴互动问题，提出Canary系统，通过将编程障碍按学生技能水平分解成小步骤，利用AI转化为逐步阶梯，让潜在帮助者能精准介入，提升学生协作频率与效果。
AI 中文摘要
协作编程是一种广泛采用的课堂活动，旨在鼓励同伴支架，但实时协作往往会退化为极少互动的并行个人工作。我们的形成性研究表明，即使学生想要协作，他们也会因一次性理解队友的整个问题所需的努力而受阻。我们提出了Canary系统，该系统通过将编程障碍分解为适合学生技能水平的较小步骤来支持同伴支架。Canary使用人工智能将复杂问题转化为逐步的阶梯，从简单修复开始，然后转向更难的逻辑，提醒潜在的帮助者可以从哪些特定位置开始。通过提供这种逐步提升的方式，Canary使学生能够快速做出贡献，并逐步解决同伴的问题。我们的评估表明，这种分阶段的方法使帮助感觉不那么压倒性，从而导致学生之间更频繁、更有效的协作。
英文摘要
Collaborative programming is a widely adopted classroom activity to encourage peer scaffolding, yet real-time collaboration often breaks down into parallel individual work with minimal interaction. Our formative studies reveal that even when students want to collaborate, they are held back by the effort required to understand a teammate's entire problem at once. We present Canary, a system that supports peer scaffolding by breaking down programming obstacles into smaller steps tailored to a student's skill level. Canary alerts potential helpers to specific places where they can start, using AI to turn complex problems into a step-by-step ladder that starts with easy fixes before moving toward harder logic. By providing this gradual ramp-up, Canary enables students to make quick contributions and progressively work toward solving their peers' problems. Our evaluation shows that this staged approach makes helping feel less overwhelming, leading to more frequent and effective collaboration among students.
CommentsAccepted to VL/HCC 2026
