Use of Generative AI by Veterinary Students in Two UK Vet Schools: A Moment in Time
The higher education community is currently experiencing a significant sense of disruption due to the emergence of Generative AI (GenAI) tools. This study sought to establish baseline data that encompass usage rates, confidence, concerns, and opinions on aligned curriculum interventions from current students studying veterinary medicine in the United Kingdom across two institutions. A survey including items aligned to a series of published curriculum domains was designed and distributed to all students in two veterinary degree programmes. A total of 285 surveys (15.5%) were completed; students with a previous degree and older students were more likely to complete the survey. Likert scale items were analysed statistically, and free text data were coded and analysed for themes. In this survey, 40% of students reported never having used GenAI tools, and the median usage across both schools was once a month or less. Greater value was placed on additional curriculum support in relation to AI with age and previous higher educational experience. Key uses of GenAI were grouped into the following: Consolidation, Clarification, and Revision; Creation (Content, Ideas, and Alternative Formats); Grammar and Editing; and Social Uses. Key concerns included Environmental Issues and Sustainability, Accuracy and Trustworthiness of Information; Data Security and Ethics; Impact on Individuals and Society; and Academic Misconduct and Cheating. This study confirms that veterinary students in the United Kingdom appear to be slower to engage with GenAI technologies compared with other higher education students. They appear particularly attuned to the environmental impact of GenAI technologies. The professional nature of the program together with the assessment frameworks that typically exist may also be influencing the degree of students' willingness to engage with the technology.
Authors
- Julie Dickson (ORCID: https://orcid.org/0000-0002-2816-2402)
- Louise Connelly (ORCID: https://orcid.org/0000-0002-6551-8148)
- Darren J. Shaw (ORCID: https://orcid.org/0000-0003-2016-1541)
- Susan M. Rhind (ORCID: https://orcid.org/0000-0001-7167-3227)
- Sarah Baillie
Institutions
- Roslin Institute (GB)
- University of Bristol (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- Journal of Veterinary Medical Education
- Published
- 2026-01-22
- DOI
- https://doi.org/10.3138/jvme-2025-0078
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00