Exploring the Impacts and Challenges of Vibe Coding Paradigm to Children's Programming Learning and Practices
Janice Jianing Si, Donglin Li, Qiuning Wang, Alicia Wanyi Liu, Xin Lin, Yujun Zhu, Xiaobo Zhou, April Yi Wang, Kanye Ye Wang · 2026
Recent advances in generative AI have introduced a new programming paradigm—vibe coding, a natural language–driven mode of AI collaboration. While promising for adults, little is known about how children engage with this approach, especially in block-based environments. To explore this gap, we conducted workshops with children of varying Scratch experience (n=41) and interviewed five Scratch teachers. Our study investigates how vibe coding impacts children’s programming learning and practice, and what challenges arise. Findings show that vibe coding has both positive and negative impacts across three key contexts of children’s programming experience: acquisition, application, and creation. Across the stages of vibe coding—goal articulation, information interpretation, and outcome evaluation—children encounter distinct challenges. By examining the mismatches between core assumptions of vibe coding and children’s needs, and analyzing its applicability across different contexts, we offer child-centered design implications for future vibe coding systems and GenAI tools.