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Cited 17 time in webofscience Cited 20 time in scopus
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The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care A Quasi-Experimental Study

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dc.contributor.authorShin, Hyewon-
dc.contributor.authorDe Gagne, Jennie C.-
dc.contributor.authorKim, Sang Suk-
dc.contributor.authorHong, Minjoo-
dc.date.accessioned2024-12-03T08:00:44Z-
dc.date.available2024-12-03T08:00:44Z-
dc.date.issued2024-10-
dc.identifier.issn1538-2931-
dc.identifier.issn1538-9774-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/74742-
dc.description.abstractThe integration of artificial intelligence such as ChatGPT into educational frameworks marks a pivotal transformation in teaching. This quasi-experimental study, conducted in September 2023, aimed to evaluate the effects of artificial intelligence–assisted learning on nursing students' ethical decision-making and clinical reasoning. A total of 99 nursing students enrolled in a pediatric nursing course were randomly divided into two groups: an experimental group that utilized ChatGPT and a control group that used traditional textbooks. The Mann-Whitney U test was employed to assess differences between the groups in two primary outcomes: (a) ethical standards, focusing on the understanding and applying ethical principles, and (b) nursing processes, emphasizing critical thinking skills and integrating evidence-based knowledge. The control group outperformed the experimental group in ethical standards and demonstrated better clinical reasoning in nursing processes. Reflective essays revealed that the experimental group reported lower reliability but higher time efficiency. Despite artificial intelligence's ability to offer diverse perspectives, the findings highlight that educators must supplement artificial intelligence technology with strategies that enhance critical thinking, careful data selection, and source verification. This study suggests a hybrid educational approach combining artificial intelligence with traditional learning methods to bolster nursing students' decision-making processes and clinical reasoning skills. Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherLippincott Williams and Wilkins-
dc.titleThe Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care A Quasi-Experimental Study-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1097/CIN.0000000000001177-
dc.identifier.scopusid2-s2.0-85201754130-
dc.identifier.wosid001336270700005-
dc.identifier.bibliographicCitationCIN - Computers Informatics Nursing, v.42, no.10, pp 704 - 711-
dc.citation.titleCIN - Computers Informatics Nursing-
dc.citation.volume42-
dc.citation.number10-
dc.citation.startPage704-
dc.citation.endPage711-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMedical Informatics-
dc.relation.journalResearchAreaNursing-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.relation.journalWebOfScienceCategoryNursing-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorCritical thinking-
dc.subject.keywordAuthorEthical standards-
dc.subject.keywordAuthorNursing education-
dc.subject.keywordAuthorNursing student-
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