AI in Higher Education: Student Perceptions of Course-Level AI Policies

Thu, 01 Jan 2026 00:00:00 +0000

— project materials, conference paper, analysis code, and figures
— Integrating Artificial Intelligence into the Classroom: Evidence from a Conjoint Experiment, 25th IEEE International Conference on Advanced Learning Technologies (ICALT 2026)
Journal Manuscript in Preparation

Project Overview

This project examines how students evaluate different forms of artificial intelligence (AI) integration in university courses.

Rather than asking whether AI should be used in higher education, the study asks:

How should AI be used in higher education?

Using a conjoint experiment, students evaluated hypothetical course policies that varied in:

AI use in instructional materials
AI use in assessments and grading
AI-powered personalized support

The study measures perceived usefulness, support for adoption, and perceived autonomy.

Research Design

Conjoint Experiment

Participants evaluated randomly generated course policies composed of three dimensions:

Attribute	Levels
Instructional Materials	No AI, AI reviewed by instructor, AI unreviewed
Assessments & Grading	Human grading, AI reviewed by instructor, AI unreviewed
Personalized Support	No chatbot, AI chatbot

Each participant evaluated six randomly assigned profiles.

Sample

Undergraduate students
N = 358 respondents
2,148 profile evaluations
Online Qualtrics survey
Fall 2025

Main Finding

Students are not opposed to AI itself.

Students are opposed to AI operating without human oversight.

AI-assisted systems that remain under instructor review receive evaluations similar to traditional human-only approaches. By contrast, AI systems operating without instructor review produce substantial declines in support, perceived usefulness, and autonomy.

Human oversight is the strongest predictor of student evaluations of AI integration in higher education. Students evaluate AI-assisted systems far more positively when instructors remain involved in reviewing AI-generated content and decisions.

Evidence Across Student Evaluations

Perceived Usefulness

Students strongly penalize unreviewed AI systems, especially when used for grading and instructional materials.

Effects of AI policy design on perceived usefulness. AI systems operating without instructor review substantially reduce students’ evaluations of educational value.

Support for Adoption

Support for AI adoption depends heavily on whether instructors remain involved in reviewing AI outputs.

Effects of AI policy design on support for AI integration. Students generally support AI-assisted systems when instructors retain oversight.

Perceived Autonomy

Students report lower autonomy when AI assumes responsibility for instructional or evaluative decisions without human oversight.

Effects of AI policy design on perceived autonomy. Unreviewed AI systems reduce students’ perceived control over their learning experience.

Additional Results

Consistency Across Outcomes

Coefficient estimates across perceived usefulness, support for adoption, and autonomy reveal a highly consistent pattern.

AI without instructor review produces the largest negative effects.
AI with instructor review produces substantially smaller effects.
AI chatbot support has little effect on student evaluations.

Comparison of estimated effects across perceived usefulness, support for adoption, and perceived autonomy. The pattern is highly consistent across outcomes, demonstrating that student acceptance of AI depends primarily on the presence of human oversight.

Research Contribution

This project contributes to research on artificial intelligence in higher education by providing causal evidence on how students evaluate alternative AI governance designs. The findings demonstrate that student acceptance of AI depends less on AI itself and more on how authority, accountability, and human oversight are structured within educational settings. The results have implications for universities, instructors, and policymakers seeking to integrate AI into teaching and learning while maintaining student trust and legitimacy.

Educational Policy |