Journal article
ChatGPT-4 Performance on USMLE Step 1 Style Questions and Its Implications for Medical Education: A Comparative Study Across Systems and Disciplines
Medical science educator, v 34(1), pp 145-152
01 Feb 2024
PMID: 38510401
Abstract
We assessed the performance of OpenAI’s ChatGPT-4 on United States Medical Licensing Exam STEP 1 style questions across the systems and disciplines appearing on the examination. ChatGPT-4 answered 86% of the 1300 questions accurately, exceeding the estimated passing score of 60% with no significant differences in performance across clinical domains. Findings demonstrated an improvement over earlier models as well as consistent performance in topics ranging from complex biological processes to ethical considerations in patient care. Its proficiency provides support for the use of artificial intelligence (AI) as an interactive learning tool and furthermore raises questions about how the technology can be used to educate students in the preclinical component of their medical education. The authors provide an example and discuss how students can leverage AI to receive real-time analogies and explanations tailored to their desired level of education. An appropriate application of this technology potentially enables enhancement of learning outcomes for medical students in the preclinical component of their education.
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Details
- Title
- ChatGPT-4 Performance on USMLE Step 1 Style Questions and Its Implications for Medical Education: A Comparative Study Across Systems and Disciplines
- Creators
- Razmig Garabet - Drexel University, General Internal MedicineBrendan P. Mackey - Drexel UniversityJames Cross - Drexel UniversityMichael Weingarten - Drexel University, MD (Doctor of Medicine) Program
- Publication Details
- Medical science educator, v 34(1), pp 145-152
- Publisher
- Springer Nature
- Number of pages
- 8
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- MD (Doctor of Medicine) Program; General Internal Medicine
- Web of Science ID
- WOS:001131611200001
- Scopus ID
- 2-s2.0-85180667163
- Other Identifier
- 991021861188504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Education, Scientific Disciplines