Motivation Map and Typology of College Students’ Use of Generative Artificial Intelligence: An Exploratory Interview Study of 52 Undergraduates

Sen Liu; Xingna Deng; Anqi Huang

doi:10.6918/

Authors

Sen Liu School of Business Administration, University of Science and Technology Liaoning, Anshan 114051, China
Xingna Deng School of Business Administration, University of Science and Technology Liaoning, Anshan 114051, China
Anqi Huang School of Business Administration, University of Science and Technology Liaoning, Anshan 114051, China

DOI:

https://doi.org/10.6918/

Keywords:

Generative artificial intelligence, Use motivation, College students, Thematic analysis, Motivation map.

Abstract

We interviewed 52 college students to find out why they use generative AI. Their answers fell into five main types. Most students use AI for practical reasons: to finish assignments, to work faster, to learn new things. Some are just curious. A few only turn to AI when a deadline is close. The three practical reasons—getting work done, finishing assignments, and learning—were reported by most of our respondents. More than two-thirds mentioned them. We call these the core motivations. Curiosity and last-minute coping were much less common. They sit at the margins. We also noticed that students’ majors seem to affect which motivations matter most to them. Privacy concerns came up across all groups, but not as a reason to use AI or not to use it. It was more like a background worry. Overall, our findings give a practical picture of why students use GenAI. They also point to ways we might design better tools, teach digital literacy, and help students think more carefully about when and how to use AI.

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