Integrating artificial intelligence into medical education: a roadmap informed by a survey of faculty and students

We surveyed faculty and students at a large urban medical school to assess their awareness, usage patterns, and perceived barriers to AI adoption, aiming to identify opportunities for meaningful integration of AI into medical education. We developed a custom survey and distributed it to all medical students (Years 1-4) and a selected group of faculty involved in the MD curriculum. We used descriptive statistics to analyze quantitative data and conducted content analysis on open-ended responses. A total of 128 faculty and 138 students completed the survey. Most participants self-identified as novice AI users and reported limited awareness and infrequent use of AI tools for professional or academic tasks. They cited lack of knowledge, limited time, and unclear benefits as key barriers. Both groups called for training, ethical guidance, and institutional support to facilitate AI integration into medical education. Faculty and students expressed similar needs for targeted AI education, though they emphasized different aspects. In response, our school has conducted a faculty training session and has accelerated identifying opportunities to integrate AI into the curriculum.

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Publication Details

Journal
Medical Education Online
Published
2025-07-14
DOI
https://doi.org/10.1080/10872981.2025.2531177
Citations
17
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
11.12
Controls
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article

Integrating artificial intelligence into medical education: a roadmap informed by a survey of faculty and students

Maria A. Blanco, Sara W. Nelson, Berri Jacque, Saradha Ramesh et al.
17 citations
Medical Education Online
Artificial Intelligence in Healthcare and Education
11.12
article

Integrating artificial intelligence into medical education: a roadmap informed by a survey of faculty and students

Maria A. Blanco, Sara W. Nelson, Berri Jacque, Saradha Ramesh, Laura E. Baecher-Lind, Clara A. Callahan, Kayley A. Josephs
article en
17 citations

Abstract

We surveyed faculty and students at a large urban medical school to assess their awareness, usage patterns, and perceived barriers to AI adoption, aiming to identify opportunities for meaningful integration of AI into medical education. We developed a custom survey and distributed it to all medical students (Years 1-4) and a selected group of faculty involved in the MD curriculum. We used descriptive statistics to analyze quantitative data and conducted content analysis on open-ended responses. A total of 128 faculty and 138 students completed the survey. Most participants self-identified as novice AI users and reported limited awareness and infrequent use of AI tools for professional or academic tasks. They cited lack of knowledge, limited time, and unclear benefits as key barriers. Both groups called for training, ethical guidance, and institutional support to facilitate AI integration into medical education. Faculty and students expressed similar needs for targeted AI education, though they emphasized different aspects. In response, our school has conducted a faculty training session and has accelerated identifying opportunities to integrate AI into the curriculum.

Medical Education OnlineVol. 30(1)
Tufts University (US)
Quality Education
Openalex Percentile: Top 2%
Artificial Intelligence in Healthcare and Education
11.12
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