Abstract
The significant challenge faced by medical schools is the effortful process of writing a high quantity of high-quality case-based multiple-choice questions (MCQs) to assess the higher-order skills of medical students. The demand for a high volume of MCQs in education has led to the development of Automatic Item Generation (AIG), specifically template-based AIG, which involves creating cognitive and item models by subject matter experts to generate hundreds of MCQs at once using software. It demonstrated significant success in various languages and even being incorporated into national medical licensure exams. However, this method still heavily depends on the efforts of subject matter experts. This paper introduces a detailed ChatGPT prompt for quickly generating case-based MCQs and provides important research questions for future exploration into ChatGPT's potential in generating items, signaling the beginning of the artificial intelligence era in medical education, encouraging health professions education researchers to delve deeper into its potential.
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