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March 25, 2026Indian Journal of Vascular and Endovascular Surgery0 citationsOpen Access

How to Use Large Language Model Chatbots in Multiple-choice Question Generation

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HMHimel MondalADAnupkumar D. DhanvijaySMSarika Mondal

Key Points

  • The aim is to explore how large language models can be utilized in creating effective multiple-choice questions for medical education.
  • Describes the functions of LLMs in drafting questions and suggesting distractors.
  • Explains the importance of human oversight for content accuracy and alignment with curricula.
  • Offers strategies for responsible LLM utilization in question development.
  • LLMs can efficiently assist in the generation of MCQs.
  • Human judgment remains critical for validating the accuracy and relevance of generated questions.
  • Structured prompts enhance the effectiveness of LLMs in question design.

Abstract

Large language models (LLMs), such as ChatGPT, Gemini, and Claude, are increasingly being used in medical education. One emerging application is the generation of multiple-choice questions (MCQs). This perspective offers a practical approach for medical educators to use LLMs in assessment design. It describes how LLMs can assist in drafting questions, suggesting distractors, and providing language variation. It also explains where human judgment is essential, such as ensuring content accuracy, curriculum alignment, and proper validation. The article highlights the need for structured prompts and offers strategies for responsible use of LLMs in MCQ development.

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Cite This Study

Mondal et al. (2026) studied this question.

synapsesocial.com/papers/69c37b81b34aaaeb1a67e06dhttps://doi.org/10.4103/ijves.ijves_126_25
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