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Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling

PURPOSE: The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning. METHODS: In this cross-sectional study, data were coll...

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Detalles Bibliográficos
Autores principales: Kim, Geun Myun, Kim, Yunsoo, Kim, Seong Kwang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Health Personnel Licensing Examination Institute 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244801/
https://www.ncbi.nlm.nih.gov/pubmed/37100591
http://dx.doi.org/10.3352/jeehp.2023.20.14
Descripción
Sumario:PURPOSE: The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning. METHODS: In this cross-sectional study, data were collected via online surveys from February 9 to March 1, 2022, from 218 nursing students in Korea. Learning transfer, learning immersion, learning satisfaction, learning efficacy, self-directed learning ability and information technology utilization ability were analyzed using IBM SPSS for Windows ver. 22.0 and AMOS ver. 22.0. RESULTS: The assessment of structural equation modeling showed adequate model fit, with normed χ(2)=1.74 (P<0.024), goodness-of-fit index=0.97, adjusted goodness-of-fit index=0.93, comparative fit index=0.98, root mean square residual=0.02, Tucker-Lewis index=0.97, normed fit index=0.96, and root mean square error of approximation=0.06. In a hypothetical model analysis, 9 out of 11 pathways of the hypothetical structural model for learning transfer in nursing students were statistically significant. Learning self-efficacy and learning immersion of nursing students directly affected learning transfer, and subjective information technology utilization ability, self-directed learning ability, and learning satisfaction were variables with indirect effects. The explanatory power of immersion, satisfaction, and self-efficacy for learning transfer was 44.4%. CONCLUSION: The assessment of structural equation modeling indicated an acceptable fit. It is necessary to improve the transfer of learning through the development of a self-directed program for learning ability improvement, including the use of information technology in nursing students’ learning environment in non-face-to-face conditions.