The use and usefulness of GenAI in higher education: Student experience and perspectives

Higher education institutions face the need to support learners' access to and use of generative artificial intelligence (GenAI) in appropriate and effective ways. However, the rapid growth of GenAI means that policy and practice has evolved with limited empirical data about student experience, attitudes, and motivations. In response, this paper reports on a large-scale multi-institution survey of over 8000 students studying at four Australian universities. We examine the frequency and purpose of GenAI usage, identifying key demographic variations in engagement. Our findings show that over 80% of students have used GenAI for study-related tasks, with nearly half using it regularly, primarily for editing, summarising, and idea generation. Usefulness, rather than blind trust or rule compliance, appears to drive this engagement. Students adopt GenAI pragmatically, with low trust in its factual accuracy, but confidence in their own ability to manage it as a support tool for academic work. We also investigate how students learn about these tools, finding that most rely on informal, self-directed learning rather than institutional resources, raising questions about the adequacy of current university guidance. Equity gaps in access and usage are evident, with proportionately lower engagement with GenAI tools among women, non-binary, neurodivergent students, and those with health conditions. While most students avoid prohibited use, a significant minority report behaviour that contravenes policy, pointing to a need for more nuanced and situationally aware approaches to academic integrity. These findings offer critical insights for institutional responses.

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Publication Details

Journal
Computers and Education Open
Published
2026-03-09
DOI
https://doi.org/10.1016/j.caeo.2026.100347
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
44.01
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article

The use and usefulness of GenAI in higher education: Student experience and perspectives

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The use and usefulness of GenAI in higher education: Student experience and perspectives

Lisa-Angelique Lim, Jennifer Chung, Yifei Liang, Antonette Shibani, Shihua Yu, Jack Walton, Michael Henderson, Christine Slade, Tim Fawns, Kelly Matthews, Trish McCluskey, Thomas Corbin, Nicole Pepperell, Margaret Bearman, Jan McLean, Simon Buckingham Shum, Ari Seligmann, Aneesha Bakharia, Glenys Oberg
article en
1 citations

Abstract

Higher education institutions face the need to support learners' access to and use of generative artificial intelligence (GenAI) in appropriate and effective ways. However, the rapid growth of GenAI means that policy and practice has evolved with limited empirical data about student experience, attitudes, and motivations. In response, this paper reports on a large-scale multi-institution survey of over 8000 students studying at four Australian universities. We examine the frequency and purpose of GenAI usage, identifying key demographic variations in engagement. Our findings show that over 80% of students have used GenAI for study-related tasks, with nearly half using it regularly, primarily for editing, summarising, and idea generation. Usefulness, rather than blind trust or rule compliance, appears to drive this engagement. Students adopt GenAI pragmatically, with low trust in its factual accuracy, but confidence in their own ability to manage it as a support tool for academic work. We also investigate how students learn about these tools, finding that most rely on informal, self-directed learning rather than institutional resources, raising questions about the adequacy of current university guidance. Equity gaps in access and usage are evident, with proportionately lower engagement with GenAI tools among women, non-binary, neurodivergent students, and those with health conditions. While most students avoid prohibited use, a significant minority report behaviour that contravenes policy, pointing to a need for more nuanced and situationally aware approaches to academic integrity. These findings offer critical insights for institutional responses.

Computers and Education OpenVol. 10
University of Technology Sydney (AU), Deakin University (AU), The University of Queensland (AU), Faculty of Design (SI), Monash University (AU)
Gender equality
Openalex Percentile: Top 0%
Online Learning and Analytics
44.01
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