September 10, 2025JMIR Medical EducationOpen Access

Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations (Preprint)

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Prompt engineering significantly improved the performance of early ChatGPT models.
ChatGPT variants matched or exceeded the performance of fourth-year medical students on tests.
GPT-3.5 and GPT-4.0 saw notable performance gains, while advanced models showed near-ceiling accuracy.
Emphasis in LLM development should shift from prompt design to model selection and AI’s role in education.

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Implication

Systematic evaluation of prompt engineering's impact on ChatGPT's performance against medical students, revealing significant improvements for early models.

Cite This Study

Hsieh et al. (2025) studied this question.

synapsesocial.com/papers/68c241efb210217d647a19d7 https://doi.org/10.2196/78320

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Implication

Systematic evaluation of prompt engineering's impact on ChatGPT's performance against medical students, revealing significant improvements for early models.

Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations (Preprint)

Key Points

Discussion

Implication

Cite This Study

Impact of Prompt Engineering on the Performance of ChatGPT Variants Across Different Question Types in Medical Student Examinations (Preprint)

Key Points

Discussion

Implication

Cite This Study

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