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ChatGPT Generated Otorhinolaryngology Multiple‐Choice Questions: Quality, Psychometric Properties, and Suitability for Assessments
9
Zitationen
7
Autoren
2024
Jahr
Abstract
Objective: To explore Chat Generative Pretrained Transformer's (ChatGPT's) capability to create multiple-choice questions about otorhinolaryngology (ORL). Study Design: Experimental question generation and exam simulation. Setting: Tertiary academic center. Methods: ChatGPT 3.5 was prompted: "Can you please create a challenging 20-question multiple-choice questionnaire about clinical cases in otolaryngology, offering five answer options?." The generated questionnaire was sent to medical students, residents, and consultants. Questions were investigated regarding quality criteria. Answers were anonymized and the resulting data was analyzed in terms of difficulty and internal consistency. Results: was highest (.69) with 15 selected questions using students' results. Conclusion: ChatGPT 3.5 is able to generate grammatically correct simple ORL multiple choice questions for a medical student level. However, the overall quality of the questions was average, needing thorough review and revision by a medical expert to ensure suitability in future exams.
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