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The Effect of a Generative AI-Based Teaching Strategy on Building Students' Competency

Datos Bibliográficos

ID21455845
AutoresChing‐Yi Chang (0000-0002-3146-2270), Ching-Yi Chang, Wen-Song Su, Wen‐Song Su (0000-0001-7489-5706, Tri-Service General Hospital)
Año2025
Volumen64
Número6
Páginas346-355
Fecha de publicación2025-06-01
Open AccessSí
TipoARTICLE
RevistaJournal of Nursing Education (JOURNAL)
Identificadores de la revistaISSN: 0148-4834 • E-ISSN: 1938-2421
EditorialSLACK, Inc (PUBLISHER)
DOI10.3928/01484834-20250129-05
PMID40489574
OpenAlexW4411142319
IdiomaEN
Citas recibidas2
Referencias citadas49

Background Assessment of the initial medical history data for pregnant women is an essential component of nursing training. Therefore, understanding clinical patient characteristics is crucial for developing students' ability to independently manage and care for pregnant women and to prepare students for entry into clinical practice. Method This study used a quasiexperimental pre- and posttest design. The generative artificial intelligence-based patient character creation (GAI-PCC) teaching strategy was used for the experimental group, and the conventional creating personas teaching strategy was used for the control group. Results The findings indicated the GAI-PCC teaching strategy significantly improved students' training. Therefore, it is recommended that this teaching strategy be implemented as an innovative scheme in nursing. Conclusion The GAI-PCC teaching strategy has a strong influence on nursing students' maternal care education. Nursing scholars should consciously integrate appropriate generative AI technology and teaching strategies to enhance students' patient care abilities. [ J Nurs Educ . 2025;64(6):346–355.]

Control (management) · Generative grammar · Mathematics education · Medical education · Teaching method · AI in Service Interactions · Artificial Intelligence · Artificial Intelligence in Healthcare and Education · Computer Science · Medicine · Nursing · Persona Design and Applications · Psychology

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Citas por año2
Intervalo de citas2026 - 2026 (1)
Altamente citadoNo

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