A Guiding Framework for K-12 Teachers in Creating AI-powered Learning Technologies through Vibe Coding
Yukyeong Song, Seoyeon Choi, Jinhee Kim, Yeongje Kim, Lauren Weisberg, Jewoong Moon
Abstract
Large language models generate code from natural language prompts, enabling "vibe coding," which allows non-programmers to develop computational solutions. Vibe coding for teachers amplifies the value of teachers-as-designers, improving technology integration while fostering AI literacy. However, structured guidance on supporting this process is lacking. We propose GAIDE (A Guiding Framework for AI-Integrated Design for Educators), a framework that supports K-12 teachers in creating AI-powered learning technologies through vibe coding. The initial framework, built on Design Thinking and INTERACT, was validated through a CORDTRA interaction analysis of three teachers and four faculty mentors in an eight-week workshop to derive the final framework. Additionally, the qualitative analysis of pre- and post-interviews found an enhancement of teachers' AI literacy. Findings highlight the potential of learning-by-creating for professional development.
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Classified with taxonomy v2 on Sat, 5 Sept 2026.