Procrastination trap: how personality traits fuel generative artificial intelligence over-reliance and erode academic performance - Mohamad Rizal Abdul Hamid; Chen Jung Ku; Anath Rau Krishnan; Imran Mehboob Shaikh; Yoke Lian Lau; Mohd Zulkifli Muhammad; Saiful Bahri (Institute of Advanced Engineering and Science, 2026)
This study investigates how long-term personality traits contribute to generative artificial intelligence (GenAI) use and whether these traits have an impact on academic procrastination and performance. The Big five personality model was used for this investigation, and a quantitative methodology was employed to analyze data from 200 undergraduate students in East Malaysia via partial least squares structural equation modeling (PLS-SEM). Findings indicated that while neuroticism and openness were associated with increased levels of GenAI use, conscientiousness was found to be a protective factor against GenAI dependency. In addition, results showed that when students excessively utilize GenAI, they experience increased levels of procrastination which leads to longer procrastination periods and decreased levels of deep learning engagement. Finally, procrastination was identified as a partial mediator between GenAI use and poor academic performance. Thus, GenAI dependency produces a ‘competence illusion’, causing a decline in students’ academic abilities over time. Ultimately, this study supports the need for interventions designed to help students learn self-regulation and develop critical AI literacy skills to enable technology to serve as a cognitive scaffold as opposed to a replacement for students’ own cognitive efforts.