LMU University Hospital, LMU Munich, Institute for Medical Education, Munich, Germany.
GMS J Med Educ. 2024 Apr 15;41(2):Doc20. doi: 10.3205/zma001675. eCollection 2024.
As medical educators grapple with the consistent demand for high-quality assessments, the integration of artificial intelligence presents a novel solution. This how-to article delves into the mechanics of employing ChatGPT for generating Multiple Choice Questions (MCQs) within the medical curriculum. Focusing on the intricacies of prompt engineering, we elucidate the steps and considerations imperative for achieving targeted, high-fidelity results. The article presents varying outcomes based on different prompt structures, highlighting the AI's adaptability in producing questions of distinct complexities. While emphasizing the transformative potential of ChatGPT, we also spotlight challenges, including the AI's occasional "hallucination", underscoring the importance of rigorous review. This guide aims to furnish educators with the know-how to integrate AI into their assessment creation process, heralding a new era in medical education tools.
作为医学教育工作者,我们一直在努力满足高质量评估的持续需求,而人工智能的整合提供了一个新颖的解决方案。本文深入探讨了在医学课程中使用 ChatGPT 生成多项选择题 (MCQ) 的方法。我们专注于提示工程的复杂性,阐明了实现目标、高保真度结果所必需的步骤和考虑因素。文章根据不同的提示结构呈现了不同的结果,突出了 AI 生成不同复杂程度问题的适应性。在强调 ChatGPT 的变革潜力的同时,我们也强调了挑战,包括 AI 偶尔的“幻觉”,这凸显了严格审查的重要性。本指南旨在为教育工作者提供将人工智能集成到他们的评估创建过程中的知识和技能,预示着医学教育工具的新时代的到来。
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