As Computational Thinking (CT) continues to permeate younger age groups in K-12 education, established CT platforms such as Scratch face challenges in catering to these younger learners, particularly those in the elementary school (ages 6-12). Through formative investigation with Scratch experts, we uncover three key obstacles to children's autonomous Scratch learning: artist's block in project planning, bounded creativity in asset creation, and inadequate coding guidance during implementation. To address these barriers, we introduce ChatScratch, an AI-augmented system to facilitate autonomous programming learning for young children. ChatScratch employs structured interactive storyboards and visual cues to overcome artist's block, integrates digital drawing and advanced image generation technologies to elevate creativity, and leverages Scratch-specialized Large Language Models (LLMs) for professional coding guidance. Our study shows that, compared to Scratch, ChatScratch efficiently fosters autonomous programming learning, and contributes to the creation of high-quality, personally meaningful Scratch projects for children.

通过ChatScratch这个AI辅助系统，我们克服了儿童独立学习Scratch中的三个障碍，即在项目计划中的艺术家阻塞、在资源创作中的有限创造力以及在实施过程中缺乏编码指导。相比于Scratch，我们的研究表明ChatScratch有效地促进了儿童的独立编程学习，并为他们创建了高质量且个人意义重大的Scratch项目。

ChatScratch: 面向6-12岁儿童的自主视觉编程学习的 AI 增强系统