Scaling AI Literacy: A Framework for Sharing, Scaffolding, and Refining Generative AI Prompts
While Generative AI is becoming ubiquitous, effective “prompt engineering” remains a siloed skill. This interactive session moves beyond basic AI introductions to propose a framework for communal prompt engineering—the practice of documenting, sharing, and scaffolding prompts for widespread institutional use.
Participants will learn to transform their personal AI workflows into accessible pedagogical tools using the “Prompt Sharing Kit” model. We will explore how to scaffold prompts so that beginners can achieve immediate results, while advanced users are encouraged to customize and refine the underlying logic.
Key areas of focus include:
Documentation: How to annotate prompts to explain why specific instructions yield results.
Pedagogy: Strategies for embedding shared prompts into assignments to shift focus from text generation to critical analysis.
Ethics: Defining acceptable use boundaries within prompt instructions.
Through hands-on “prompt audits” and collaborative design exercises, participants will create shareable templates to foster a culture of AI transparency and collaboration on their home campuses.
Satoru Shinagawa, U. of Hawaii, Kapiolani CC, US
Satoru Shinagawa began teaching Japanese online in 1999, long before “asynchronous” was a household word. He is passionate about using technology to create accessible, effective, and modern language-learning experiences for students worldwide.
