Synthesis
This RCT investigates the impact of transforming institutional GenAI policies into actionable prompting instruction for K-12 educators. Key findings:
- Policy-to-Practice Gap: Most GenAI policies lack implementation guidance, leaving teachers unprepared
- Prompting Instruction Intervention: Teachers trained in prompt engineering showed 2.3x higher AI integration in lesson plans
- Student Outcomes: Classes with prompt-trained teachers showed 18% higher engagement in AI-assisted tasks
- Scalability: 4-hour training module proved sufficient for measurable impact
Connections
- ai-literacy — Direct intervention to build teacher AI literacy through prompting skills
- k-12-ai-education — Focus on K-12 educator preparation
- educational-policy-ai — Bridges policy frameworks with classroom implementation
- prompt-engineering-education — Core intervention: teaching effective prompt design
- teacher-professional-development — Professional learning model for AI integration
- randomized-controlled-trials-education — Methodological contribution: RCT in AI education policy
- ai-tutor-effectiveness-review — Adds evidence on AI integration in classrooms
References
Xiao, R., Ye, R., et al. (2026). Transforming GenAI Policy to Prompting Instruction: An RCT. arXiv preprint arXiv:2602.16033.
Related Pages
- genai-declaration-frameworks-higher-education — Complementary empirical work on GenAI policy communication
- student-regulatory-awareness-genai — Related findings on the effectiveness of GenAI policy communication