{"title":"Impact of ChatGPT on case creation efficiency and learning quality in case-based learning for undergraduate nursing students","authors":"Asahiko Higashitsuji PhD, PHN, RN, Tomoko Otsuka PhD, PHN, RN, Kentaro Watanabe MSN, PHN, RN","doi":"10.1016/j.teln.2024.10.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) enhances quality of life by reducing labor and managing complex networks. Generative AI, like ChatGPT, could improve education outcomes. However, its effectiveness in nursing education through case-based learning (CBL) remains unclear.</div></div><div><h3>Aim</h3><div>To assess the effectiveness of ChatGPT in CBL through case creation and student group discussions.</div></div><div><h3>Methods</h3><div>A feasibility trial was conducted using a single-group pre-post design and a blinded nonrandomized crossover design. Eight faculty members and nine students from a Japanese college were recruited from June to November 2023. The sample size was determined based on feasibility trials recommendations. Faculty members created cases manually and using ChatGPT while students conducted group discussions on each case. Case creation time, faculty members’ burden, and group discussion quality were evaluated.</div></div><div><h3>Results</h3><div>Case creation time differed significantly with 106 min and 71 min for manual and. ChatGPT, respectively (95% CI = 1.0–1,299.6, <em>p</em> = 0.042). There were no significant differences in the perceived burden of creation and discussion quality.</div></div><div><h3>Conclusion</h3><div>ChatGPT reduced case creation time without affecting learning quality, suggesting applicability beyond nursing.</div></div>","PeriodicalId":46287,"journal":{"name":"Teaching and Learning in Nursing","volume":"20 1","pages":"Pages e159-e166"},"PeriodicalIF":1.9000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teaching and Learning in Nursing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1557308724002099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Artificial intelligence (AI) enhances quality of life by reducing labor and managing complex networks. Generative AI, like ChatGPT, could improve education outcomes. However, its effectiveness in nursing education through case-based learning (CBL) remains unclear.
Aim
To assess the effectiveness of ChatGPT in CBL through case creation and student group discussions.
Methods
A feasibility trial was conducted using a single-group pre-post design and a blinded nonrandomized crossover design. Eight faculty members and nine students from a Japanese college were recruited from June to November 2023. The sample size was determined based on feasibility trials recommendations. Faculty members created cases manually and using ChatGPT while students conducted group discussions on each case. Case creation time, faculty members’ burden, and group discussion quality were evaluated.
Results
Case creation time differed significantly with 106 min and 71 min for manual and. ChatGPT, respectively (95% CI = 1.0–1,299.6, p = 0.042). There were no significant differences in the perceived burden of creation and discussion quality.
Conclusion
ChatGPT reduced case creation time without affecting learning quality, suggesting applicability beyond nursing.
期刊介绍:
Teaching and Learning in Nursing is the Official Journal of the National Organization of Associate Degree Nursing. The journal is dedicated to the advancement of Associate Degree Nursing education and practice, and promotes collaboration in charting the future of health care education and delivery. Topics include: - Managing Different Learning Styles - New Faculty Mentoring - Legal Issues - Research - Legislative Issues - Instructional Design Strategies - Leadership, Management Roles - Unique Funding for Programs and Faculty