Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education.

ABSTRACT:

Importance

Multiple choice questions (MCQs) are an important and integral component of ophthalmology residency training evaluation and board certification; however, high-quality questions are difficult and time-consuming to draft.

Objective

To evaluate whether general-domain large language models (LLMs), particularly OpenAI's Generative Pre-trained Transformer 4 (GPT-4), can reliably generate high-quality, novel, and readable MCQs comparable to those of a committee of experienced examination writers.

Design, setting, and participants

This survey study, conducted from September 2024 to April 2025, assesses LLM performance in generating MCQs based on the American Academy of Ophthalmology (AAO) Basic and Clinical Science Course (BCSC) compared with a committee of human e

SUBMITTER: Gholami S 

PROVIDER: S-EPMC12532029 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature