Assessing question characteristic influences on ChatGPT's performance and response-explanation consistency: Insights from Taiwan's Nursing Licensing Exam

Background: Investigates the integration of an artificial intelligence tool, specifically ChatGPT, in nursing education, addressing its effectiveness in exam preparation and self-assessment. Objective: This study aims to evaluate the performance of ChatGPT, one of the most promising artificial intelligence-driven linguistic understanding tools in answering question banks for nursing licensing examination preparation. It further analyzes question characteristics that might impact the accuracy of ChatGPT-generated answers and examines its reliability through human expert reviews. Design: Cross-sectional survey comparing ChatGPT-generated answers and their explanations. Setting: 400 questions from Taiwan's 2022 Nursing Licensing Exam. Methods: The study analyzed 400 questions from five distinct subjects of Taiwan's 2022 Nursing Licensing Exam using the ChatGPT model which provided answers and in-depth explanations for each question. The impact of various question characteristics, such as type and cognitive level, on the accuracy of the ChatGPT-generated responses was assessed using logistic regression analysis. Additionally, human experts evaluated the explanations for each question, comparing them with the ChatGPT-generated answers to determine consistency. Results: ChatGPT exhibited overall accuracy at 80.75 % for Taiwan's National Nursing Exam, which passes the exam. The accuracy of ChatGPT-generated answers diverged significantly across test subjects, demonstrating a hierarchy ranging from General Medicine at 88.75 %, Medical-Surgical Nursing at 80.0 %, Psychology and Community Nursing at 70.0 %, Obstetrics and Gynecology Nursing at 67.5 %, down to Basic Nursing at 63.0 %. ChatGPT had a higher probability of eliciting incorrect responses for questions with certain characteristics, notably those with clinical vignettes [odds ratio 2.19, 95 % confidence interval 1.24-3.87, P = 0.007] and complex multiplechoice questions [odds ratio 2.37, 95 % confidence interval 1.00-5.60, P = 0.049]. Furthermore, 14.25 % of ChatGPT-generated answers were inconsistent with their explanations, leading to a reduction in the overall accuracy to 74 %. Conclusions: This study reveals the ChatGPT's capabilities and limitations in nursing exam preparation, underscoring its potential as an auxiliary educational tool. It highlights the model's varied performance across different question types and notable inconsistencies between its answers and explanations. The study contributes significantly to the understanding of artificial intelligence in learning environments, guiding the future development of more effective and reliable artificial intelligence-based educational technologies. Tweetable abstract: New study reveals ChatGPT's potential and challenges in nursing education: Achieves 80.75 % accuracy in exam prep but faces hurdles with complex questions and logical consistency. #AIinNursing #AIinEducation #NursingExams #ChatGPT (c) 2024 Elsevier Ltd. All rights reserved.