From Prompts to Reflection: Designing Reflective Play for GenAI Literacy
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.
Cite
@article{arxiv.2509.13679,
title = {From Prompts to Reflection: Designing Reflective Play for GenAI Literacy},
author = {Qianou Ma and Megan Chai and Yike Tan and Jihun Choi and Jini Kim and Erik Harpstead and Geoff Kauffman and Tongshuang Wu},
journal= {arXiv preprint arXiv:2509.13679},
year = {2025}
}