Factors Influencing Learning Flow of Nursing College Students in Online Classes

The purpose of this study was to investigate the factors influencing on learning flow among nursing students in online classes. The participants were 137 nursing students at a university in D city. Questionnaires including demographics, academic self-efficacy, learner-perceived learning, teaching presence, and learning flow were utilized. Data were collected from November 11 to 19, 2023, and analyzed using SPSS 25.0 program, including descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficient, and stepwise multiple linear regression. The results indicated that the significant predictors of learning flow among nursing students in online classes were learning presence(β=.374, p<.001), academic self-efficacy(β =.335, p<.001), and lecture interest(β=.211, p=.001). Also, stepwise multiple regression model showed these factors explained 40.1% of the variance in learning flow. The results of this study provide foundational data for exploring teaching and learning strategies to enhance learning flow among nursing students in online classes. Furthermore, they highlight the need for instructional design in online education that considers these factors to improve the quality of nursing education.

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Publication Details

Journal
Journal of Fisheries and Marine Sciences Education
Published
2025-06-24
DOI
https://doi.org/10.13000/jfmse.2025.6.37.3.578
Primary Topic
Education and Learning Interventions
Type
article
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article

Factors Influencing Learning Flow of Nursing College Students in Online Classes

In-Ju Seo, Soonyang JANG
Journal of Fisheries and Marine Sciences Education
Education and Learning Interventions
article

Factors Influencing Learning Flow of Nursing College Students in Online Classes

In-Ju Seo, Soonyang JANG
article en

Abstract

The purpose of this study was to investigate the factors influencing on learning flow among nursing students in online classes. The participants were 137 nursing students at a university in D city. Questionnaires including demographics, academic self-efficacy, learner-perceived learning, teaching presence, and learning flow were utilized. Data were collected from November 11 to 19, 2023, and analyzed using SPSS 25.0 program, including descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficient, and stepwise multiple linear regression. The results indicated that the significant predictors of learning flow among nursing students in online classes were learning presence(β=.374, p<.001), academic self-efficacy(β =.335, p<.001), and lecture interest(β=.211, p=.001). Also, stepwise multiple regression model showed these factors explained 40.1% of the variance in learning flow. The results of this study provide foundational data for exploring teaching and learning strategies to enhance learning flow among nursing students in online classes. Furthermore, they highlight the need for instructional design in online education that considers these factors to improve the quality of nursing education.

Journal of Fisheries and Marine Sciences EducationVol. 37(3)
Openalex Percentile: Top 79%
Education and Learning Interventions
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