Investigating the Motivations and Perceptions of Undergraduate Students Using AI for Assignments

When 183 students were explicitly allowed to use AI for assignments, their motivations and experiences revealed a far more complex picture than our typical assumptions.

The Project

Michael Filimowicz's research in IAT210 took an innovative approach to understanding AI in education. Rather than banning or simply permitting AI use, the course explicitly allowed it with guidelines and Filimowicz systematically studied student motivations and perceptions through assignments, surveys, interviews, and teaching assistant observations.

The study identified seven distinct purposes for AI use and 42 different motivations, revealing that students' most positive experiences came from AI as assistant, brainstorming partner, and language support tool. Both uses that enhance rather than replace human thinking.

Project Highlights

Student motivations proved more complex than expected. While "generating content" and "shortcuts" were most common uses, they often generated negative student sentiments. Students felt conflicted about these uses, understanding the potential learning impact while feeling competitive pressure from AI-using peers.

Context significantly affected AI acceptance. Students had different attitudes toward AI in individual versus group work, with many expressing concerns about fairness when group members relied heavily on AI without contributing equal effort to collaborative projects.

Looking Ahead

The research suggests moving beyond simple AI bans or permissions toward nuanced approaches recognizing both benefits and risks. Students requested clearer guidelines about acceptable use and examples of how AI could enhance rather than replace learning in specific contexts. Filimowicz also shared his findings at TILT’s SoTL Thoughts, AI in the Classroom: Evidence-based Insights from SFU Colleagues.