{"title":"GPT-4 在中国护理考试中的表现：使用大语言模型进行人工智能辅助护理教育的潜力。","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":54706,"journal":{"name":"Nurse Educator","volume":" ","pages":"E338-E343"},"PeriodicalIF":2.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\":54706,\"journal\":{\"name\":\"Nurse Educator\",\"volume\":\" \",\"pages\":\"E338-E343\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nurse Educator\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/NNE.0000000000001679\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nurse Educator","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NNE.0000000000001679","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/5 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Performance of GPT-4 on Chinese Nursing Examination: Potentials for AI-Assisted Nursing Education Using Large Language Models.
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.
期刊介绍：
Nurse Educator, a scholarly, peer reviewed journal for faculty and administrators in schools of nursing and nurse educators in other settings, provides practical information and research related to nursing education. Topics include program, curriculum, course, and faculty development; teaching and learning in nursing; technology in nursing education; simulation; clinical teaching and evaluation; testing and measurement; trends and issues; and research in nursing education.
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