Abstract
Introduction: Artificial intelligence (AI) is widespread in medical imaging, yet there is a paucity of information on education and training available for staff. Further research is required to identify what training is available, and what preparations are required to bring AI knowledge to levels that will enable radiographers to work competently alongside AI. This study aimed to a) investigate current provision of AI education at UK higher education institutes (HEIs); b) explore the attitudes and opinions of educators.
Methods: Data were collected through two online surveys: one for UK HEIs, the other for medical imaging educators. The surveys were distributed in the UK by the Heads of Radiography Education (HRE), The Society of Radiographers, and at the Research Hub at ECR 2023, as well as promotion on LinkedIn and Twitter(X), and through university channels.
Results: Responses were received from 22 HEIs in the UK and 33 educators from across Europe. Data analysis is ongoing, but preliminary findings show that 68.2% (n=15) of responding HEIs claim to have introduced AI to the curriculum already. 84.8% (n=28) of educators claim they themselves have received no training on AI despite having to embed it into the curriculum. The main reason for this cited by HEIs is limited resources. 69.7% (n=23) of educators believe that AI concepts should be taught by an AI expert.
Conclusion
By surveying educators and HEIs separately, this study captured two different perspectives regarding the provision of AI education. This unique insight highlighted disharmony between HEIs and educators. Preliminary insights highlight that educators feel unprepared to deliver AI content, and HEIs are under pressure to add AI concepts to an already full curriculum.
Limitations: Surveys, focus groups and interviews were conducted in English language only.
Funding:
This project has been part-funded by a College of Radiographers Industry Partnership Scheme grant number 229 (AI).
Ethics Committee approval:
Approved by Ulster University Filter Committee. Reference numbers: FCNUR-23-051 / FCNUR-23-006-A
Methods: Data were collected through two online surveys: one for UK HEIs, the other for medical imaging educators. The surveys were distributed in the UK by the Heads of Radiography Education (HRE), The Society of Radiographers, and at the Research Hub at ECR 2023, as well as promotion on LinkedIn and Twitter(X), and through university channels.
Results: Responses were received from 22 HEIs in the UK and 33 educators from across Europe. Data analysis is ongoing, but preliminary findings show that 68.2% (n=15) of responding HEIs claim to have introduced AI to the curriculum already. 84.8% (n=28) of educators claim they themselves have received no training on AI despite having to embed it into the curriculum. The main reason for this cited by HEIs is limited resources. 69.7% (n=23) of educators believe that AI concepts should be taught by an AI expert.
Conclusion
By surveying educators and HEIs separately, this study captured two different perspectives regarding the provision of AI education. This unique insight highlighted disharmony between HEIs and educators. Preliminary insights highlight that educators feel unprepared to deliver AI content, and HEIs are under pressure to add AI concepts to an already full curriculum.
Limitations: Surveys, focus groups and interviews were conducted in English language only.
Funding:
This project has been part-funded by a College of Radiographers Industry Partnership Scheme grant number 229 (AI).
Ethics Committee approval:
Approved by Ulster University Filter Committee. Reference numbers: FCNUR-23-051 / FCNUR-23-006-A
| Original language | English |
|---|---|
| Number of pages | 1 |
| DOIs | |
| Publication status | Published online - 18 Sept 2024 |
| Event | European Congress of Radiology (2024) - Vienna Duration: 28 Feb 2024 → 3 Mar 2024 https://www.myesr.org/congress/programme/ |
Conference
| Conference | European Congress of Radiology (2024) |
|---|---|
| Abbreviated title | ECR 2024 |
| Period | 28/02/24 → 3/03/24 |
| Internet address |
Keywords
- medical imaging
- radiography
- artificial intelligence (AI)
- education
