Teaching Prompt-Based Programming with LLMs: A 45-Minute Lesson with Guided Practice for End-User Programmers

This study by Tran, Marwan & Price (2026) introduces and evaluates a 45-minute structured lesson on prompt-based programming, a new modality enabled by LLMs where users express computational goals through natural language. The lesson design incorporates guided practice principles and targets end-user programmers with limited formal training. Results show significant pre-to-post gains in prompt quality, code correctness, and self-efficacy, supporting the case that AI Literacy interventions need not be lengthy to be effective. The work connects to broader conversations about how LLM tools change the skills required for programming — shifting emphasis from syntax to prompt engineering. By focusing on end-user programmers rather than CS students, the study expands the scope of STEM Education research to include lifelong and professional learning contexts. It also raises questions about the Teacher Role in an AI-mediated classroom, where instructors must now teach prompt design alongside or instead of traditional coding concepts. Future work could explore how such lessons scale across Higher Ed institutions and whether the gains translate to real-world programming tasks.

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Citation

Keith Tran, Samiha Marwan, Thomas Price (2026). Teaching Prompt-Based Programming with LLMs: A 45-Minute Lesson with Guided Practice for End-User Programmers. arXiv:2606.30547. cs.CY. - Voice Text Prompt Problems Computing Education — Modality choice in prompt construction