Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education - Zeng Hui; Zhu Zewu; Hu Jiao; Cui Yu (BMC Medical Education)
Abstract Introduction Artificial intelligence technology has a wide range of application prospects in the field of medical education. The aim of the study was to measure the effectiveness of ChatGPT-assisted problem-based learning (PBL) teaching for urology medical interns in comparison with traditional teaching. Methods A cohort of urology interns was randomly assigned to two groups; one underwent ChatGPT-assisted PBL teaching, while the other received traditional teaching over a period of two weeks. Performance was assessed using theoretical knowledge exams and Mini-Clinical Evaluation Exercises. Students’ acceptance and satisfaction with the AI-assisted method were evaluated through a survey. Results The scores of the two groups of students who took exams three days after the course ended were significantly higher than their scores before the course. The scores of the PBL-ChatGPT assisted group were significantly higher than those of the traditional teaching group three days after the course ended. The PBL-ChatGPT group showed statistically significant improvements in medical interviewing skills, clinical judgment and overall clinical competence compared to the traditional teaching group. The students gave highly positive feedback on the PBL-ChatGPT teaching method. Conclusion The study suggests that ChatGPT-assisted PBL teaching method can improve the results of theoretical knowledge assessment, and play an important role in improving clinical skills. However, further research is needed to examine the validity and reliability of the information provided by different chat AI systems, and its impact on a larger sample size.