This paper is in the following e-collection/theme issue:

Artificial Intelligence (AI) in Medical Education (182) Testing and Assessment in Medical Education (91) Theme Issue: ChatGPT and Generative Language Models in Medical Education (115) Graduate and Postgraduate Education for Health Professionals (133) Evaluation of Medical Education (128) Models and Frameworks in Medical Education (53) New Methods and Approaches in Medical Education (373)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78320, first published .
Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations: Cross-Sectional Study

Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations: Cross-Sectional Study

Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations: Cross-Sectional Study

Authors of this article:

Ming-Yu Hsieh1, 2 Author Orcid Image ;   Tzu-Ling Wang3 Author Orcid Image ;   Pen-Hua Su2, 4 Author Orcid Image ;   Ming-Chih Chou2, 5 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Ming-Yu Hsieh   1, 2 , MD, PhD ;   Tzu-Ling Wang   3 , MSc, RNC ;   Pen-Hua Su   2, 4 * , MD, PhD ;   Ming-Chih Chou   2, 5 * , MD, PhD

1 Division of Pediatric Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung City, Taiwan

2 Institute of Medicine, School of Medicine, Chung Shan Medical University, Taichung City, Taiwan

3 Department of Nursing, School of Medicine, Chung Shan Medical University, Taichung City, Taiwan

4 Department of Pediatrics, Chung Shan Medical University Hospital, Taichung City, Taiwan

5 Division of Thoracic Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung City, Taiwan

*these authors contributed equally

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