Luong Jason, Tzang Chih-Chen, McWatt Sean, Brassett Cecilia, Stearns Dana, Sagoo Mandeep G, Kunzel Carol, Sakurai Takeshi, Chien Chung-Liang, Noel Geoffroy, Wu Anette
Columbia University College of Dental Medicine, New York, NY USA.
National Taiwan University, Taipei, Taiwan.
Med Sci Educ. 2024 Oct 23;35(1):331-341. doi: 10.1007/s40670-024-02190-x. eCollection 2025 Feb.
The impact of artificial intelligence (AI) in diverse fields, including medical education, has emerged as a pivotal topic as the integration of AI technologies is becoming increasingly prevalent. This research delved into the landscape of AI integration in academic settings aimed to evaluate the students' readiness for the evolving AI landscape in medical education.
Participants were recruited from the International Collaboration and Exchange Program (ICEP) in the fall of 2023. An online survey was conducted to collect data on demographics, the landscape of AI utilization in academic settings, and the perceived readiness levels related to AI from 223 participants. The Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) was used.
Results indicated that 41.82% of participants "agreed" or "strongly agreed" that AI education should be part of medical training. Overall levels of AI readiness exhibited a statistically significant positive correlation with the frequency of AI inclusion in the curriculum ( = 0.217, = 0.009), the frequency of AI use for studying ( = 0.246, = 0.003), and the agreement that AI education should be integrated into medical training ( = 0.594, < 0.001).
This study offers valuable insights into the ongoing discussion on the role of AI in education, providing a foundation for educators to consider the integration of AI into their educational framework. The implementation of AI education could potentially enhance students' AI readiness, considering the multiple benefits this symbiosis can offer.
The online version contains supplementary material available at 10.1007/s40670-024-02190-x.
随着人工智能（AI）技术的整合日益普遍，人工智能在包括医学教育在内的各个领域的影响已成为一个关键话题。本研究深入探讨了学术环境中人工智能整合的情况，旨在评估学生对医学教育中不断发展的人工智能环境的准备程度。
参与者于2023年秋季从国际合作与交流项目（ICEP）中招募。进行了一项在线调查，以收集223名参与者的人口统计学数据、学术环境中人工智能的使用情况以及与人工智能相关的感知准备程度数据。使用了医学生医学人工智能准备量表（MAIRS-MS）。
结果表明，41.82%的参与者“同意”或“强烈同意”人工智能教育应成为医学培训的一部分。人工智能准备的总体水平与课程中包含人工智能的频率（r = 0.217，p = 0.009）、用于学习的人工智能使用频率（r = 0.246，p = 0.003）以及人工智能教育应纳入医学培训的共识（r = 0.594，p < 0.001）呈现出统计学上显著的正相关。
本研究为正在进行的关于人工智能在教育中的作用的讨论提供了有价值的见解，为教育工作者考虑将人工智能纳入其教育框架提供了基础。考虑到这种共生关系所能带来的多重益处，实施人工智能教育可能会提高学生对人工智能的准备程度。
在线版本包含可在10.1007/s40670-024-02190-x获取的补充材料。
