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The application of problem-based learning (PBL) guided by ChatGPT in clinical education in the Department of
Xiaoya Tong1,2,3, Ying Hu1,2,3, Yanjun Long1,2,3
1Department of Nephrology, Guizhou Provincial People's Hospital, Guiyang, China.
Background:
Nephrology, a complex and specialized medical field, has seen significant advancements, yet traditional teaching methods remain outdated and less effective. This study explores the integration of Problem-Based Learning (PBL) guided by ChatGPT in the Department of Nephrology at Guizhou Provincial People's Hospital to enhance medical education.
Objective:
To assess the impact of ChatGPT-guided Problem-Based Learning (PBL) on medical students' education and satisfaction in the Nephrology Department.
Methods:
Fifty-four clinical resident doctors were divided into an experimental group, using ChatGPT-guided PBL, and a control group, using traditional methods. Both groups were assessed through theoretical and clinical practice exams, teaching satisfaction surveys, and self-assessments of teaching effectiveness.
Results:
Results indicated the experimental group achieved significantly higher scores in both theoretical and clinical assessments. Additionally, they reported higher satisfaction and effectiveness in learning. Despite spending more time in pre-class preparation, the overall learning time did not increase due to reduced post-class review time facilitated by ChatGPT.
Conclusions:
This study demonstrates the potential of ChatGPT-integrated PBL to enhance learning outcomes, satisfaction, and efficiency in medical education. Future research should include larger samples and longer follow-up to validate these findings.
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