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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.

Publication ,  Journal Article
Shin, H; De Gagne, JC; Kim, SS; Hong, M
Published in: Computers, informatics, nursing : CIN
October 2024

The 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.

Duke Scholars

Published In

Computers, informatics, nursing : CIN

DOI

EISSN

1538-9774

ISSN

1538-2931

Publication Date

October 2024

Volume

42

Issue

10

Start / End Page

704 / 711

Related Subject Headings

  • Young Adult
  • Thinking
  • Students, Nursing
  • Pediatric Nursing
  • Nursing
  • Male
  • Learning
  • Humans
  • Female
  • Ethics, Nursing
 

Citation

APA
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ICMJE
MLA
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Shin, H., De Gagne, J. C., Kim, S. S., & Hong, M. (2024). The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care: A Quasi-Experimental Study. Computers, Informatics, Nursing : CIN, 42(10), 704–711. https://doi.org/10.1097/cin.0000000000001177
Shin, Hyewon, Jennie C. De Gagne, Sang Suk Kim, and Minjoo Hong. “The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care: A Quasi-Experimental Study.Computers, Informatics, Nursing : CIN 42, no. 10 (October 2024): 704–11. https://doi.org/10.1097/cin.0000000000001177.
Shin, Hyewon, et al. “The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care: A Quasi-Experimental Study.Computers, Informatics, Nursing : CIN, vol. 42, no. 10, Oct. 2024, pp. 704–11. Epmc, doi:10.1097/cin.0000000000001177.

Published In

Computers, informatics, nursing : CIN

DOI

EISSN

1538-9774

ISSN

1538-2931

Publication Date

October 2024

Volume

42

Issue

10

Start / End Page

704 / 711

Related Subject Headings

  • Young Adult
  • Thinking
  • Students, Nursing
  • Pediatric Nursing
  • Nursing
  • Male
  • Learning
  • Humans
  • Female
  • Ethics, Nursing