Reduced Student Life Satisfaction and Academic Performance: Unraveling the Dark Side of ChatGPT in the Higher Education Context

Abstract

Little is known about the dark side of ChatGPT adoption in the higher education context; the current study, therefore, adopts the stressor-strain-outcome model to examine how compulsive use of ChatGPT and its consequences, such as loneliness and social avoidance (stressors), lead to the increased level of psychological distress (strain), which, in turn, negatively has the detrimental impacts on student life satisfaction and academic performance (outcomes). Moreover, the recent study also aims to test the moderating role of technostress in the strain-outcome relationship. Drawing on the sample of 2709 higher education students collected across 16 universities in Vietnam using a stratified random sampling approach, results reveal a positive correlation between compulsive use of ChatGPT, loneliness, social avoidance, and psychological distress. Furthermore, psychological distress mediates the relationship between compulsive ChatGPT use, diminished life satisfaction, and reduced academic performance. The study also shows a series of indirect effects of compulsive ChatGPT use on academic performance through sequential mediation pathways involving loneliness and social avoidance. Noticeably, the current research reveals that technostress not only reinforces the negative impacts of psychological distress on student life satisfaction and academic performance but also weakens the positive effect of student life satisfaction and academic performance. Based on the findings of this research, some practical and interventional recommendations are provided.