Impact of Large Language Models on Medical Education and Teaching Adaptations
Li Zhui, Nina Yhap, Liu Liping, Wang Zhengjie, Xiong Zhonghao, Yuan Xiaoshu, Cui Hong, Liu Xuexiu, Ren Wei

TL;DR
This article discusses how large language models can transform medical education by improving teaching and learning, while also addressing the challenges and ethical concerns that come with their use.
Contribution
The article provides a comprehensive analysis of how LLMs can reshape medical education and proposes strategies for educators to effectively integrate these technologies.
Findings
LLMs can enhance teaching quality and personalize learning in medical education.
Challenges include information accuracy, overreliance on technology, and ethical concerns.
Educators should adapt teaching strategies to cultivate critical thinking and practical skills.
Abstract
This viewpoint article explores the transformative role of large language models (LLMs) in the field of medical education, highlighting their potential to enhance teaching quality, promote personalized learning paths, strengthen clinical skills training, optimize teaching assessment processes, boost the efficiency of medical research, and support continuing medical education. However, the use of LLMs entails certain challenges, such as questions regarding the accuracy of information, the risk of overreliance on technology, a lack of emotional recognition capabilities, and concerns related to ethics, privacy, and data security. This article emphasizes that to maximize the potential of LLMs and overcome these challenges, educators must exhibit leadership in medical education, adjust their teaching strategies flexibly, cultivate students’ critical thinking, and emphasize the importance of…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInnovations in Medical Education · Artificial Intelligence in Healthcare and Education · Simulation-Based Education in Healthcare
