{"title":"Performance of GPT-4 on Chinese Nursing Examination: Potentials for AI-Assisted Nursing Education Using Large Language Models.","authors":"Yiqun Miao, Yuan Luo, Yuhan Zhao, Jiawei Li, Mingxuan Liu, Huiying Wang, Yuling Chen, Ying Wu","doi":"10.1097/NNE.0000000000001679","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The performance of GPT-4 in nursing examinations within the Chinese context has not yet been thoroughly evaluated.</p><p><strong>Objective: </strong>To assess the performance of GPT-4 on multiple-choice and open-ended questions derived from nursing examinations in the Chinese context.</p><p><strong>Methods: </strong>The data sets of the Chinese National Nursing Licensure Examination spanning 2021 to 2023 were used to evaluate the accuracy of GPT-4 in multiple-choice questions. The performance of GPT-4 on open-ended questions was examined using 18 case-based questions.</p><p><strong>Results: </strong>For multiple-choice questions, GPT-4 achieved an accuracy of 71.0% (511/720). For open-ended questions, the responses were evaluated for cosine similarity, logical consistency, and information quality, all of which were found to be at a moderate level.</p><p><strong>Conclusion: </strong>GPT-4 performed well at addressing queries on basic knowledge. However, it has notable limitations in answering open-ended questions. Nursing educators should weigh the benefits and challenges of GPT-4 for integration into nursing education.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NNE.0000000000001679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/5 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The performance of GPT-4 in nursing examinations within the Chinese context has not yet been thoroughly evaluated.
Objective: To assess the performance of GPT-4 on multiple-choice and open-ended questions derived from nursing examinations in the Chinese context.
Methods: The data sets of the Chinese National Nursing Licensure Examination spanning 2021 to 2023 were used to evaluate the accuracy of GPT-4 in multiple-choice questions. The performance of GPT-4 on open-ended questions was examined using 18 case-based questions.
Results: For multiple-choice questions, GPT-4 achieved an accuracy of 71.0% (511/720). For open-ended questions, the responses were evaluated for cosine similarity, logical consistency, and information quality, all of which were found to be at a moderate level.
Conclusion: GPT-4 performed well at addressing queries on basic knowledge. However, it has notable limitations in answering open-ended questions. Nursing educators should weigh the benefits and challenges of GPT-4 for integration into nursing education.