Application of ChatGPT-based blended medical teaching in clinical education of hepatobiliary surgery

Abstract

Objective This study evaluates the effectiveness of incorporating the Chat Generative Pre-trained Transformer (ChatGPT) into the clinical teaching of hepatobiliary surgery for undergraduate medical students. Materials and methods A group of 61 medical undergraduates from the Affiliated Hospital of Guizhou Medical University, undergoing hepatobiliary surgery training, were randomly assigned to either an experimental group (31 students) using ChatGPT-based blended teaching or a control group (30 students) with traditional teaching methods. The evaluation metrics included final exam scores, teaching satisfaction, and teaching effectiveness ratings, analyzed using SPSS 26.0 (SPSS Inc., Chicago, IL) with t-tests and χ 2 tests. Results The experimental group significantly outperformed the control group in final exam theoretical scores (86.44 ± 5.59 vs. 77.86 ± 4.16, p < .001) and clinical skills scores (83.84 ± 6.13 vs. 79.12 ± 4.27, p = .001). Additionally, the experimental group reported higher teaching satisfaction (17.23 ± 1.33) and self-evaluation of teaching effectiveness (9.14 ± 0.54) compared to the control group (15.38 ± 1.5 and 8.46 ± 0.70, respectively, p < .001). Conclusions The integration of ChatGPT into hepatobiliary surgery education significantly enhances theoretical knowledge, clinical skills, and overall satisfaction among medical undergraduates, suggesting a beneficial impact on their educational development.