Generative AI Usage of University Students: Navigating Between Education and Business

TL;DR

This study explores how part-time university students use generative AI for both educational and business purposes, highlighting benefits, challenges, and ethical concerns through qualitative interviews.

Contribution

It provides a grounded theory model of GenAI usage among part-time students, addressing a gap in literature on intersectional education and business applications.

Findings

GenAI enhances productivity and learning outcomes.

Ethical concerns and risks of misconduct are significant.

Strategies influence how students adopt and use GenAI.

Abstract

This study investigates generative artificial intelligence (GenAI) usage of university students who study alongside their professional career. Previous literature has paid little attention to part-time students and the intersectional use of GenAI between education and business. This study examines with a grounded theory approach the characteristics of GenAI usage of part-time students. Eleven students from a distance learning university were interviewed. Three causal and four intervening conditions, as well as strategies were identified, to influence the use of GenAI. The study highlights both the potential and challenges of GenAI usage in education and business. While GenAI can significantly enhance productivity and learning outcomes, concerns about ethical implications, reliability, and the risk of academic misconduct persist. The developed grounded model offers a comprehensive understanding of GenAI usage among students, providing valuable insights for educators, policymakers, and developers of GenAI tools seeking to bridge the gap between education and business.