From Prompts to Reflection: Designing Reflective Play for GenAI Literacy

2025-09-17

AI Summary

A critical gap exists in generative AI (GenAI) literacy interventions for adults that simultaneously foster engagement and critical reflection. This study designs and evaluates *ImaginAItion*, a multiplayer party game inspired by Drawful, integrating prompt engineering, real-time generative feedback, small-group discussion, and structured reflection to help players identify AI biases, refine prompting strategies, and critically examine human-AI cognitive asymmetries. Its key contribution is the first systematic application of a reflective game-based framework to adult GenAI literacy education—leveraging social interaction to cultivate collective awareness and collaborative deconstruction of systemic biases, with modular architecture ensuring adaptability to evolving GenAI capabilities. Ten experimental sessions (N=30) demonstrate statistically significant improvements in participants’ critical understanding of GenAI’s capabilities, limitations, and sociotechnical embeddedness; furthermore, group diversity positively moderates the depth of reflective engagement.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Natural Language Processing: Generation

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

The wide adoption of Generative AI (GenAI) in everyday life highlights the need for greater literacy around its evolving capabilities, biases, and limitations. While many AI literacy efforts focus on children through game-based learning, few interventions support adults in developing a nuanced, reflective understanding of GenAI via playful exploration. To address the gap, we introduce ImaginAItion, a multiplayer party game inspired by Drawful and grounded in the reflective play framework to surface model defaults, biases, and human-AI perception gaps through prompting and discussion. From ten sessions (n=30), we show how gameplay helped adults recognize systematic biases in GenAI, reflect on humans and AI interpretation differences, and adapt their prompting strategies. We also found that group dynamics and composition, such as expertise and diversity, amplified or muted reflection. Our work provides a starting point to scale critical GenAI literacy through playful, social interventions resilient to rapidly evolving technologies.

Problem

• Addressing adult GenAI literacy gaps through playful learning
• Designing reflective play to surface AI biases and limitations
• Exploring prompting strategies and human-AI perception differences

Innovation

• Multiplayer party game for adult GenAI literacy
• Reflective play framework to surface biases
• Social interventions resilient to evolving technologies