🤖 AI Summary
This study addresses the lack of systematic understanding regarding how university students navigating dual academic and professional identities employ generative artificial intelligence (GenAI) in the intersecting contexts of education and work. Drawing on grounded theory, the research constructs the first integrated theoretical model of GenAI use through semi-structured in-depth interviews with 11 distance-learning students. The analysis identifies three core causal conditions and four intervening factors that shape distinct usage strategies. Findings reveal that while GenAI enhances both learning and work efficiency, it simultaneously introduces critical challenges concerning reliability, academic integrity, and ethical risks. These insights offer valuable theoretical and practical implications for human-AI collaboration across boundary-spanning scenarios.
📝 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.