Blanco Maria A, Nelson Sara W, Ramesh Saradha, Callahan Carly E, Josephs Kayley A, Jacque Berri, Baecher-Lind Laura E
Tufts University School of Medicine, Boston, Massachusetts, USA.
Med Educ Online. 2025 Dec;30(1):2531177. doi: 10.1080/10872981.2025.2531177. Epub 2025 Jul 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.
我们对一所大型城市医学院的教师和学生进行了调查，以评估他们对人工智能采用的认知、使用模式以及感知到的障碍，旨在确定将人工智能有意义地整合到医学教育中的机会。我们开发了一份定制调查问卷，并将其分发给所有医学生（1至4年级）以及参与医学博士课程的一组选定教师。我们使用描述性统计分析定量数据，并对开放式回答进行内容分析。共有128名教师和138名学生完成了调查。大多数参与者自认为是人工智能的新手用户，并表示对人工智能工具在专业或学术任务中的认知有限且使用频率不高。他们指出缺乏知识、时间有限和益处不明确是主要障碍。两组都呼吁提供培训、伦理指导和机构支持，以促进人工智能融入医学教育。教师和学生对有针对性的人工智能教育表达了相似的需求，尽管他们强调的方面有所不同。作为回应，我们学校举办了一次教师培训课程，并加快了确定将人工智能融入课程的机会。
