AI Policy as Pedagogy: Guiding Student Learning with Generative AI

Authors

• Justin Olmanson, University of Nebraska-LincolnFollow
• Minji Jeon, University of Nebraska-LincolnFollow
• Azadeh Hassani, University of Nebraska-Lincoln

Date of this Version

2026

Document Type

Article

Citation

Paper presented at AI in Higher Education Summit 2026: Shaping the Future of Universities in an AI World. ESCP Business School, Paris, France, March 17–18, 2026.

doi: 10.35542/osf.io/a58pe_v2

Comments

Open access

License: CC BY-NC-ND 4.0 International

Abstract

Generative AI that is capable of supporting student learning has been widely available since late 2022. Yet the institutional and instructional guidance students receive regarding how they should, should not, or might use AI to complete course assignments and engage with course content is often absent or insufficiently differentiated. This creates an uneven dynamic wherein individual students are left to either interpret vague AI policies and apply them on an assignment-by-assignment and course-by-course basis, or adhere to sweeping statements made by instructors regardless of differences in AI literacy levels. This project translates an empirically derived taxonomy of AI use for learning into a student-facing AI policy designed to support student judgment, agency, and productive struggle in a way that maps onto specific coursework and assignments. We describe both the taxonomy and the policy and discuss the implications of reframing AI policies as pedagogical tools designed to cultivate student agency, rather than as an instrument of institutional compliance and control.