University students’ self-reported reliance on ChatGPT for learning: A latent profile analysis
Abstract
Although ChatGPT, a state-of-the-art, large language model, seems to be a disruptive technology in higher education, it is unclear to what extent students rely on this tool for completing different tasks. To address this gap, we asked university students (N = 490) recruited via CloudResearch to rate the extent to which they rely on ChatGPT for completing 13 tasks identified in a previous pilot study. Five distinct profiles emerged: ‘Versatile low reliers’ (38.2%) were characterised by low overall self-reported reliance across the tasks, while ‘all-rounders’ (10.4%) had high overall self-reported reliance. The ‘knowledge seekers’ (16.5%) scored particularly high on tasks such as content acquisition, information retrieval and summarising of texts, while the ‘proactive learners’ (11.8%) on tasks such as obtaining feedback, planning and quizzing. Finally, the ‘assignment delegators’ (23.1%) relied on ChatGPT for drafting assignments, writing homework and having ChatGPT write their assignment for them. The findings provide a nuanced understanding of how students rely on ChatGPT for learning.
Identifier Metadata
| Identifier | 110.1123/CON.2026.01094 |
| Canonical | mdoi:110.1123/CON.2026.01094 |
| Resolver URL | https://mdoi.org/110.1123/CON.2026.01094 |
| Resource URL | Open resource |
| Document URL | Open document |
| Content Type | Article |
| Authors | Ana Stojanov, Qian Liu, Joyce Hwee Ling Koh |
| Year | 2024 |
| Depositor | Convergence Chronicles Organisation |
| Prefix | 110.1123 |
| Registered | Aug. 17, 2026 |
| Updated | Aug. 17, 2026 |
| Status | Active |
| Visibility | Public |
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