Online programming communities provide a space for novices to engage with computing concepts, allowing them to learn and develop computing skills using user-generated projects. However, the lack of structured guidance in the informal learning environment often makes it difficult for novices to experience progressively challenging learning opportunities. Learners frequently struggle with understanding key project events and relations, grasping computing concepts, and remixing practices. This study introduces CoRemix, a generative AI-powered learning system that provides a visual graph to present key events and relations for project understanding. We propose a visual-textual scaffolding to help learners construct the visual graph and support remixing practice. Our user study demonstrates that CoRemix, compared to the baseline, effectively helps learners break down complex projects, enhances computing concept learning, and improves their experience with community resources for learning and remixing.

翻译：在线编程社区为初学者提供了一个接触计算概念的空间，使他们能够通过用户生成的项目来学习和培养计算技能。然而，非正式学习环境中缺乏结构化指导，往往使初学者难以获得渐进式挑战的学习机会。学习者常常在理解关键项目事件与关系、掌握计算概念以及进行项目混搭实践方面遇到困难。本研究介绍了CoRemix，这是一个由生成式人工智能驱动的学习系统，它通过视觉图来呈现关键事件与关系，以支持项目理解。我们提出了一种视觉-文本支架方法，以帮助学习者构建视觉图并支持混搭实践。我们的用户研究表明，与基线方法相比，CoRemix能有效帮助学习者分解复杂项目，增强计算概念的学习，并改善他们利用社区资源进行学习和混搭的体验。