Implementation and evaluation of an optimized surgical clerkship teaching model utilizing ChatGPT

作者：Yi Huang, Beibei Xu, Xiuyan Wang, Yun-cheng Luo, Miaomiao Teng, Xuejian Weng · 发表于：BMC Medical Education · 年份：2024 · DOI：10.1186/s12909-024-06575-9 · 被引用次数：13 · 研究领域：Artificial Intelligence in Healthcare and Education、Simulation-Based Education in Healthcare、E-Learning and COVID-19

OBJECTIVE: This study aims to explore the effect of an innovative teaching model incorporating ChatGPT on medical students' learning outcomes, compliance with learning activities, and overall satisfaction with the learning process. METHODS: A cohort of 64 students participating in general surgery clerkships at Wenzhou People's Hospital during the 2022-2023 academic year were randomly assigned into 4 groups, each comprising 16 students. Two of these groups were designated as the study group, where ChatGPT was employed as a supplementary educational tool. The remaining 2 groups served as control groups and used traditional multimedia-based learning methods. Outcomes, including learning effectiveness, compliance, and satisfaction, were evaluated using questionnaires and tests. RESULTS: The study groups exhibited significantly higher levels of compliance and satisfaction compared to the control groups. Specifically, the study groups exhibited significantly greater compliance in both pre-class preparation and post-class review activities (P < 0.05). During classroom teaching, Group 1 of the study group achieved significantly higher compliance than the control groups (P < 0.0001), while Group 2 of the study group showed significantly higher compliance than Group 1 (P < 0.001). In terms of seeking feedback and assistance, both Groups 1 and 2 of the study group had significantly higher compliance compared to Group 1 of the control group (P < 0.01, P < 0.001 respectively). Overall sat...