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University students’ self-reported reliance on ChatGPT for learning: A latent profile analysis

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Title: University students’ self-reported reliance on ChatGPT for learning: A latent profile analysis
Authors: Ana Stojanov, Qian Liu, Joyce Hwee Ling Koh
Source: Computers and Education: Artificial Intelligence, Vol 6, Iss , Pp 100243- (2024)
Publisher Information: Elsevier, 2024.
Publication Year: 2024
Collection: LCC:Electronic computers. Computer science
Subject Terms: ChatGPT, Artificial intelligence (AI), University students, Higher education, Latent profile analysis (LPA), Achievement goal orientation, Electronic computers. Computer science, QA75.5-76.95
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2666-920X
Relation: http://www.sciencedirect.com/science/article/pii/S2666920X24000468; https://doaj.org/toc/2666-920X
DOI: 10.1016/j.caeai.2024.100243
Access URL: https://doaj.org/article/266ce208622547e68d1d75f49db95e01
Accession Number: edsdoj.266ce208622547e68d1d75f49db95e01
Database: Directory of Open Access Journals
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  Data: 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.
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