The American Society of Radiologic Technologists (ASRT) AI educator survey: A cross-sectional study to explore knowledge, experience, and use of AI within education.

Autor:	Stogiannos N; Department of Midwifery & Radiography, School of Health and Psychological Sciences, City, University of London, UK; Magnitiki Tomografia Kerkiras, Corfu, Greece. Electronic address: nikos.stogiannos@city.ac.uk., Jennings M; Senior Research Analyst, American Society of Radiologic Technologists, New Mexico, USA., George CS; Director of Education, American Society of Radiologic Technologists, New Mexico, USA., Culbertson J; Director of Research, American Society of Radiologic Technologists, New Mexico, USA., Salehi H; Department of Biomedical Industrial & Human Factor Engineering, Wright State University, Ohio, USA., Furterer S; Department of Integrated Systems Engineering, The Ohio State University, Ohio, USA., Pergola M; Chief Executive Officer, American Society of Radiologic Technologists, New Mexico, USA., Culp MP; Executive Vice President of Member Engagement, American Society of Radiologic Technologists, New Mexico, USA. Electronic address: mculp@asrt.org., Malamateniou C; Department of Midwifery & Radiography, School of Health and Psychological Sciences, City, University of London, UK; Discipline of Medical Imaging and Radiation Therapy, College of Medicine and Health, University College Cork, Ireland; European Society of Medical Imaging Informatics, Vienna, Austria.
Jazyk:	angličtina
Zdroj:	Journal of medical imaging and radiation sciences [J Med Imaging Radiat Sci] 2024 Jul 13; Vol. 55 (4), pp. 101449. Date of Electronic Publication: 2024 Jul 13.
DOI:	10.1016/j.jmir.2024.101449
Abstrakt:	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. (Copyright © 2024. Published by Elsevier Inc.)
Databáze:	MEDLINE
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