Applicability of ChatGPT to generate multiple-choice questions for ophthalmology resident exam
While ChatGPT can efficiently generate MCQs for ophthalmology residents, it has notable limitations, including higher rates of item-writing flaws and lower-quality distractors. Additionally, ChatGPT-generated MCQs are less effective at distinguishing high-performing from low-performing examinees. Integrating ChatGPT with human expertise is essential to enhance the quality and reliability of artificial intelligence-generated MCQs.
Authors
- Hamed Esfandiari (ORCID: https://orcid.org/0000-0001-7301-7047)
- Sina Khosravi Mirzaie (ORCID: https://orcid.org/0000-0002-1211-5601)
- Firouze Hatami (ORCID: https://orcid.org/0000-0003-0450-0961)
- Sepehr Feizi (ORCID: https://orcid.org/0000-0003-4457-8077)
- Mohammad Hasan Shahriari (ORCID: https://orcid.org/0000-0001-5596-1958)
- Mohammadreza Dolikhani (ORCID: https://orcid.org/0000-0001-5686-4535)
- Siavash Shirzadeh-Barough
Institutions
- Olmsted Medical Center (US)
- Shahid Beheshti University of Medical Sciences (IR)
Publication Details
- Journal
- British Journal of Ophthalmology
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1136/bjo-2025-327632
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00