"How can we learn and use AI at the same time?": Participatory Design of GenAI with High School Students
Name
3713043.3727057.pdf
Size
22.96 MB
Format
Adobe PDF
Checksum (MD5)
2a1b867fec9008ffa51a2066f835e2ff
Author(s)
Pu, Isabella
Ravi, Prerna
Dinh, Linh
Joe, Chelsea
Ogoe, Caitlin
Li, Zixuan
Breazeal, Cynthia
Ostrowski, Anastasia
Date Issued
June 23, 2025
Publisher
ACM|Interaction Design and Children
Citation
Isabella Pu, Prerna Ravi, Linh Dieu Dinh, Chelsea Joe, Caitlin Ogoe, Zixuan Li, Cynthia Breazeal, and Anastasia K. Ostrowski. 2025. "How can we learn and use AI at the same time?": Participatory Design of GenAI with High School Students. Proceedings of the 24th Interaction Design and Children. Association for Computing Machinery, New York, NY, USA, 204–220.
Version
Final published version
Abstract
As generative AI (GenAI) emerges as a transformative force, clear understanding of high school students’ perspectives is essential for GenAI’s meaningful integration in high school environments. In this work, we draw insights from a participatory design workshop where we engaged 17 high school students—a group rarely involved in prior research in this area—through the design of novel GenAI tools and school policies addressing their key concerns. Students identified challenges and developed solutions outlining their ideal features in GenAI tools, appropriate school use, and regulations. These centered around the problem spaces of combating bias & misinformation, tackling crime & plagiarism, preventing over-reliance on AI, and handling false accusations of academic dishonesty. Building on our participants’ underrepresented perspectives, we propose new guidelines targeted at educational technology designers for development of GenAI technologies in high schools. We also argue for further incorporation of student voices in development of AI policies in their schools.
Description
IDC ’25, Reykjavik, Iceland
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Sloan School of Management
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3713043.3727057
