City Research Online

Abstract

Introduction
Artificial Intelligence (AI) is revolutionizing medical imaging and radiation therapy. AI-powered applications are being deployed to aid Medical Radiation Technologists (MRTs) in clinical workflows, decision-making, dose optimisation, and a wide range of other tasks. Exploring the levels of AI education provided across the United States is crucial to prepare future graduates to deliver the digital future. This study aims to assess educators’ levels of AI knowledge, the current state of AI educational provisions, the perceived challenges around AI education, and important factors for future advancements.

Methods
An online survey was electronically administered to all radiologic technologists in the American Society of Radiologic Technologists (ASRT) database who indicated that they had an educator role in the United States. This was distributed through the membership of the ASRT, from February to April 2023. All quantitative data was analysed using frequency and descriptive statistics. The survey's open-ended questions were analysed using a conceptual content analysis approach.

Results
Out of 5,066 educators in the ASRT database, 373 valid responses were received, resulting in a response rate of 7.4%. Despite 84.5% of educators expressing the importance of teaching AI, 23.7% currently included AI in academic curricula. Of the 76.3% that did not include AI in their curricula, lack of AI knowledge among educators was the top reason for not integrating AI in education (59.1%). Similarly, AI-enabled tools were utilised by only 11.1% of the programs to assist teaching. The levels of trust in AI varied among educators.

Conclusion
The study found that although US educators of MRTs have a good baseline knowledge of general concepts regarding AI, they could improve on the teaching and use of AI in their curricula. AI training and guidance, adequate time to develop educational resources, and funding and support from higher education institutions were key priorities as highlighted by educators.

Publication Type:	Article
Additional Information:	© 2024 Published by Elsevier Inc. on behalf of Canadian Association of Medical Radiation Technologists. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher Keywords:	Artificial intelligence, Education, Medical radiation technology
Subjects:	H Social Sciences > HN Social history and conditions. Social problems. Social reform L Education > LB Theory and practice of education > LB2300 Higher Education Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine
Departments:	School of Health & Psychological Sciences School of Health & Psychological Sciences > Midwifery & Radiography
SWORD Depositor:	Symplectic Administrator

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