Integrating artificial intelligence into medical education
A roadmap informed by a survey of faculty and students
Bibliographic Data
| ID | 15328384 |
|---|---|
| Authors | Maria A Blanco (0000-0002-7469-6050, Tufts University School of Medicine, corresponding author), Sara W Nelson (0000-0003-2360-3042, Tufts University School of Medicine), Saradha Ramesh (Tufts University School of Medicine), Clara A Callahan (Tufts University), Carly E Callahan (Tufts University School of Medicine), Kayley A Josephs (Tufts University School of Medicine), Berri Jacque (Tufts University School of Medicine), Laura Baecher-Lind (0000-0003-3877-2658, Tufts University), Laura E Baecher-Lind (Tufts University School of Medicine) |
| Year | 2025 |
| Volume | 30 |
| Issue | 1 |
| Pages | 2531177-2531177 |
| Publication date | 2025-07-14 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Medical Education Online (JOURNAL) |
| Journal identifiers | ISSN: 1087-2981 • E-ISSN: 1087-2981 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/10872981.2025.2531177 |
| PMID | 40660466 |
| OpenAlex | W4412414402 |
| Language | IT |
| Citations received | 3 |
| References cited | 14 |
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 · Artificial Intelligence in Healthcare and Education · Biomedical and Engineering Education · Medicine · Psychology · Radiology practices and education
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |