Student-Driven Recommendations on AI Policy
In a Design Classroom
Role: Graduate Research Assistant | Timeline: Jan. 2025-Dec. 2025
Advisor: Dr. Yasmine Kotturi
Overview
With the increasing integration of generative AI in education, policies governing its use are often created without direct student input. This gap can lead to policies that do not align with students' needs or learning experiences. By positioning students as “lead users” (Von Hippel, 2006)—early adopters of generative AI in education—our project aims to address this issue by developing student-authored AI policies to better support their learning outcomes. Through understanding how students perceive AI and its role in their coursework, this research provides actionable insights that can inform future AI policies in design education.
Responsibilities
- Designed and led a three-part participatory workshop series with 9 student participants
- Conducted qualitative thematic analysis on workshops' audio transcriptions
- Developed IRB Protocol and managed compensations for participants
- Coordinated the curation of final policy artifacts, including zines and redesigned GenAI interface mockups
- Submitted the paper based on this study to CHI 2026, which moved to second round RR!
Research Questions
R1: How do students perceive AI policies and AI integration in a design course?
R2: How might we support students to author student-driven AI policies in a design classroom? In other words, what scaffolding is required to assist students to write effective policies in a design classroom?
R3: When given the opportunity and support to self-author AI policies, what are student-driven AI policy recommendations in a design classroom?
Participants
10 students who took HCC629: Fundamentals of Human-Centered Computing at the University of Maryland, Baltimore County (UMBC) in Fall 2024 with Dr. Yasmine Kotturi.
Methods
- A three-part participatory workshop series
- Pre- and post-workshop surveys
- Follow-up interviews
Project Timeline
Recruitment
Screening surveys to identify participants
February 2025Workshop 1
Brainstorming policy recommendations through candid conversations
March 28, 2025Workshop 2
Curating policy recommendations through student-authored zine making
April 11, 2025Workshop 3
Applying policy recommendations through interface redesign activity
April 25, 2025Follow-up Interviews
Investigate deeper insights from selected participants who left interesting comments during the workshops
June - July, 2025Data Analysis
Conduct qualitative and quantitative analysis on surveys, discussions, and interviews
Mid June - Mid August 2025Paper Writing
Submit the paper based on the findings to CHI 2026
Mid-August - Early September 2025Presentation & Implementation
Dr. Kotturi implement student-driven policies in HCC629 Fall 2025
Present at Ninth Annual Provost's Teaching & Learning Symposium
Sept 2025Master's Thesis Defense
Develop and defend my Master's thesis
Dec 2025Next Steps
Circulate the zines on campus
Collaborating with UMBC Dean of Library: adapt student-driven AI policy model across disciplines and levels at UMBC
Oct 2025 - PresentWorkshop Photos
Workshop 1
Workshop 2
Findings
- Students are not a monolith and have essential knowledge through lived experience to inform AI policy
- Safe spaces as preconditions for honest dialogue given apprehension and shame around use of AI
- Workshops and zine making offer a transferable model for participatory AI governance in education
Publications
Seki, K*., Vijay, M*., & Kotturi, Y. (2026). "Hypocricy on Faculty Use": Student-Driven Recommendations on AI Policy In a Design Classroom. CHI 2026. Under Review.
Seki, K. (2026). Student-Driven Recommendations on AI Policy In a Design Classroom. Master's Thesis. University of Maryland, Baltimore County.
Student-authored zines with policy recommendations
UPDATE-2025/10/22🎉 The zines have been officially archived at UMBC Albin O. Kuhn Library & Gallery - both digitally and physically, and is featured in their Artificial Intelligence & AI Literacy guide!