A Guiding Framework for K-12 Teachers in Creating AI-powered Learning Technologies through Vibe Coding

Synthesis: 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 teachers-as-designers paradigm, 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.

GAIDE, a Design-Thinking-based framework, supports K-12 teachers (non-programmers) in building AI-powered learning tools via vibe coding; an eight-week workshop raised participating teachers' AI literacy, showing learning-by-creating as a professional-development model.

This work connects to core knowledge base themes: K-12 Teaching AI Literacy Generative AI Educational Development. It highlights how generative-AI tooling is reshaping both what learners do and how educators structure support, reinforcing the need for design that preserves authentic engagement rather than enabling shallow bypass.

What this means for practice

• Instructors. Anchor a vibe-coding project in a real classroom problem: the three teachers designed their tools against the U.S. Presidential AI Challenge, and the Design Thinking empathy stage kept the work tied to their own students.
• Faculty developers. Mentor the design process stage by stage rather than the finished artifact — four faculty mentors supported three teachers across eight weekly online sessions, and the CORDTRA analysis mapped mentor support onto each design stage.
• Faculty developers. Treat AI ethics as a design topic rather than a compliance rule: teachers shifted from "making sure students are not cheating" to reasoning about bias, hallucination, and transparency in their own tools.
• Instructors. Budget prototyping time outside the sessions: teachers were asked to continue building between workshops because the eight sessions ran short.
• Faculty developers. Model learning-by-creating for Workplace Learning: the workshop raised teachers' AI Literacy by having them build AI-powered tools, not by explaining AI to them.

Limitations

• Three K-12 teachers and four faculty mentors, recruited by snowball sampling from rural East Tennessee, completed a single eight-week online workshop with no control group.
• The AI-literacy findings come from thematic analysis of pre- and post-interviews, so they capture self-reported perception rather than tested capability.
• Teachers continued prototyping outside the sessions because of time constraints, so the recorded video and CORDTRA diagrams cover only part of the design work.
• All three teachers volunteered for the Presidential AI Challenge, so their motivation likely exceeds that of a typical K-12 teacher cohort.

Citation

Song, Choi, Kim, Kim, Weisberg & Moon (2026). A Guiding Framework for K-12 Teachers in Creating AI-powered Learning Technologies through Vibe Coding. arXiv preprint.