Journal article 380 views 266 downloads
How vulnerable are UK universities to cheating with new GenAI tools? A pragmatic risk assessment
Assessment & Evaluation in Higher Education, Pages: 1 - 12
Swansea University Author:
Phil Newton
-
PDF | Version of Record
© 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND).
Download (1.3MB)
DOI (Published version): 10.1080/02602938.2025.2511794
Abstract
There has been considerable speculation about the risk that new generative AI tools like ChatGPT pose to higher education, particularly assessments and cheating. However it is unclear how much risk the UK higher education sector is exposed to. This survey study used a modified list experiment to eva...
| Published in: | Assessment & Evaluation in Higher Education |
|---|---|
| ISSN: | 0260-2938 1469-297X |
| Published: |
Informa UK Limited
2025
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa69576 |
| Abstract: |
There has been considerable speculation about the risk that new generative AI tools like ChatGPT pose to higher education, particularly assessments and cheating. However it is unclear how much risk the UK higher education sector is exposed to. This survey study used a modified list experiment to evaluate that risk. Most students surveyed were using GenAI, and almost all were frequently assessed using methods that are vulnerable to cheating with GenAI (unsupervised online examinations, and essays). An estimated 22% of them reported cheating in academic year 2023/24 and almost all were confident that they understood the policy of their university. However the activities that they report using GenAI for were not always clearly identifiable as cheating. These findings suggest an urgent need for the use of more appropriate forms of summative assessment in UK higher education, and clarity over the policies and definitions used to support those assessments. |
|---|---|
| Keywords: |
Artificial intelligence, assessment validity, academic integrity, cheating |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
Swansea University |
| Start Page: |
1 |
| End Page: |
12 |

