Student-Driven Perspectives of AI Policy In a Design Classroom

Overview

This project, Student-Driven Perspectives of AI Policy in a Design Classroom, investigates how students, as early adopters of generative AI, perceive and shape AI-related policies in a design classroom setting. Although AI policies in higher education are typically developed by faculty and administrators, students are the ones actively experimenting with and integrating GenAI tools into their learning workflows. Yet their voices are often absent from formal policy development. This research addresses that gap by centering student perspectives in the co-creation of GenAI classroom policies, aiming to produce guidelines that are ethical, inclusive, and grounded in real-world learning practices.

Research Questions

R1: How do students perceive AI integration into a design course?

R2: How can student-driven policies inform generative AI use in classroom settings?

Problem Statement

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. This project aims to address this issue by developing student-authored AI policies that balance innovation, ethical use, and academic integrity. By 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..

User & Audiences

Primary users: Students in HCC629: Fundamentals of Human-Centered Computing. The findings benefit university administrators, educators, policymakers, and future students in design courses.

Audiences: Faculty designing GenAI-integrated curricula, university administrators developing institutional AI policies, and HCI researchers studying participatory policy design and AI ethics

Roles & Responsibilities

My Role: Graduate Student Researcher

Team Members: Dr. Yasmine Kotturi (PI), Manisha Vijay (Graduate Research Assistant)

Responsibilities:

• Designed and co-facilitated a 3-part participatory workshop series with 8 student participants
• Developed IRB Protocol and managed compensations for participants
• conducting qualitative thematic analysis on workshops' audio transcriptions
• Coordinating the curation of final policy artifacts, including zines and redesigned GenAI interface mockups
• Preparing the study for academic publication (targeting CHI 2026 or DIS 2026)

Scope & Constraints

Timeline: January 1, 2025 – December 31, 2025

Participants: 8 students from Fall 2024 HCC629 taught by Dr. Yasmine Kotturi (PI)

Constraints: Limited to UMBC students and design courses

Process

• Recruitment & Consent: Screening surveys, participant consent
• Workshop 1 (3/28/2025): Brainstorming policy recommendations through candid conversations
  • Students shared personal GenAI use experiences in class, raising concerns about unclear ethical boundaries and academic integrity by employing Think-Pair-Share activity
  • A UMBC AI committee member presented campus-wide survey data, followed by students selecting policy topics to explore further
• Workshop 2 (4/11/2025): Curating policy recommendations through student-authored zine making
  • Students critiqued peer-drafted policies to reduce redundancy and make them more concrete and actionable
  • Students refined their statements and expressed them through physical and digital zines
• Workshop 3 (4/25/2025): Applying policy recommendations through interface redesign activity
  • Students reviewed and critiqued each other’s zines, then selected a GenAI tool to redesign
  • Students' redesigns incorporated metaphors and HCC 629 learning objectives to support their proposed policies
• Data Analysis: Conduct qualitative and quantitative analysis on surveys, discussions, and interviews

Next Steps

• Complete qualitative analysis of workshop transcripts and interviews
• Finalize and circulate the curated zines on campus
• Present findings in research paper
• Building on this research, I will develop my Master’s thesis in Human-Centered Computing at UMBC, continuing to explore student-centered AI policy and the broader implications of generative AI in design education.

Outcomes & Results

To be determined in 2025.