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"How can we learn and use Al at the same time?": Participatory Design of GenAl with High School Students

Authors
Isabella Pu,
Prerna Ravi,
Linh Dieu Dinh,
Chelsea Joe,
Caitlin Ogoe,
Zixuan Li,
Cynthia Breazeal,
Anastasia K. Ostrowski
Date
Publisher
arXiv
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.
Study at a glance
  • Question: What do high school students want from generative AI tools and school policies?
  • Setting and data: 17 high school students
  • Method: Participatory design workshop
Why it matters

A clear understanding of high school students' perspectives is essential for generative AI's meaningful integration in high school environments. However, these students are a group rarely involved in prior research in this area.

Key findings
  • Among 17 high school students, participants developed solutions outlining ideal generative AI features, appropriate school uses, and regulations.
  • Students identified combating bias and misinformation alongside tackling crime and plagiarism as major challenges for generative AI.
  • Students highlighted preventing over-reliance on AI and handling false accusations of academic dishonesty as critical problem areas.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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