2026 ASEE Annual Conference & Exposition

This Work In Progress paper focuses on first year engineering student’s understanding of and thoughts regarding Generative Artificial Intelligence (GAI) policies within the classroom. With many universities opting to leave GAI policy development up to the faculty members, general policies have been applied to courses focusing heavily on a high-level regulation of GAI for the classroom. Despite GAI policies being included primarily as part of a syllabus statement, many students are unclear on what the class AI policy is, policies are inconsistent across professors and universities, and students as a stakeholder group have largely not yet been consulted.

Through this project, approximately 150 first year engineering students at a large R1 mid-Atlantic university will be asked to craft a GAI use policy for their upcoming spring foundations in engineering course. Students in the class are divided into teams of five, with a variety of intended majors and identities present. Along with a comparison of the average policy statement created by all teams, a comparison of differences in policies between students’ intended majors and students’ identities will performed to determine how engineering major and identity impacts the GAI policy development the team decided on.

Student GAI policies will be compared to the course GAI policy using Microsoft Word’s Legal Blackline feature to identify what sections of the policy the students keep the same, and which parts they added or adapted. Student policies will be clustered into one of three categories: unrestricted GAI use, semi-restricted GAI use, fully restricted GAI use. Further clusters will be created for the semi-restricted GAI use policies, focusing on the types of activities that students are allowed to use GAI for.

Once all student generated GAI use policies have been clustered, students’ intended majors will be mapped to the different policies to determine any correlation between majors and the criteria included in a GAI use policy. This will be repeated for students’ self-reported identities as well.
Following the conclusion of clustering and mapping to the different GAI policies, an updated recommendation of GAI use policies for foundational engineering classes will be created, with attention to policies on unrestricted use, semi-restricted use, and fully restricted use of GAI from the student’s perspectives.