Cargando…
The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey
AIM: To examine the correlations between self-regulation, learning flow, academic stress and learning engagement as predicting variables for academic achievement in a blended learning environment in Namibia. DESIGN: Cross-sectional survey. METHODS: Data were collected from 166 randomly selected unde...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598534/ https://www.ncbi.nlm.nih.gov/pubmed/37885718 http://dx.doi.org/10.1016/j.heliyon.2023.e21321 |
_version_ | 1785125574906216448 |
---|---|
author | Tomas, Nestor Poroto, Annarosa |
author_facet | Tomas, Nestor Poroto, Annarosa |
author_sort | Tomas, Nestor |
collection | PubMed |
description | AIM: To examine the correlations between self-regulation, learning flow, academic stress and learning engagement as predicting variables for academic achievement in a blended learning environment in Namibia. DESIGN: Cross-sectional survey. METHODS: Data were collected from 166 randomly selected undergraduate nursing students through an online survey between January and February 2023, and were analysed using IBM SPSS AMOS version 28.0. The data were explored through factor, parallel and confirmatory factor analyses. The relationship between the study factors and the total score of the scale was analysed using the Pearson correlation coefficient. RESULTS: The results indicate that the two factors identified in the factor analysis are consistent with the theoretical proposition in this research. Factor 1 comprises items C1 to C24, which pertain to self-regulation (SR), while factor 2 consists of items D1 to D9, which relate to learning flow (LR). The findings demonstrate that self-regulation significantly predicts both flow and stress, as well as learning engagement. Additionally, there is a significant relationship between stress and self-regulated learning, as well as between stress and learning flow (r = 0.23–0.26; p= < .05). However, none of the study constructs were found to predict academic achievement. CONCLUSION: Although self-regulation significantly predicted flow, stress and learning engagement, a non-significant association exists between all the study constructs and academic achievement. The results of this study have significant implications for improving the development of a positive learning environment that fosters active student engagement. Future studies should investigate correlation by conducting large-scale studies. IMPACT: This study makes a valuable contribution to the current body of literature concerning academic achievement within the context of undergraduate nursing education. The insignificant relationship between the study variables and academic achievement indicate that these elements are not of considerable significance in enhancing educational achievements in blended learning surroundings in Namibia. PATIENT OR PUBLIC CONTRIBUTION: One hundred and sixty-six undergraduate nursing students participated in the survey. The data collected were analysed and interpreted by a skilled statistician. |
format | Online Article Text |
id | pubmed-10598534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105985342023-10-26 The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey Tomas, Nestor Poroto, Annarosa Heliyon Research Article AIM: To examine the correlations between self-regulation, learning flow, academic stress and learning engagement as predicting variables for academic achievement in a blended learning environment in Namibia. DESIGN: Cross-sectional survey. METHODS: Data were collected from 166 randomly selected undergraduate nursing students through an online survey between January and February 2023, and were analysed using IBM SPSS AMOS version 28.0. The data were explored through factor, parallel and confirmatory factor analyses. The relationship between the study factors and the total score of the scale was analysed using the Pearson correlation coefficient. RESULTS: The results indicate that the two factors identified in the factor analysis are consistent with the theoretical proposition in this research. Factor 1 comprises items C1 to C24, which pertain to self-regulation (SR), while factor 2 consists of items D1 to D9, which relate to learning flow (LR). The findings demonstrate that self-regulation significantly predicts both flow and stress, as well as learning engagement. Additionally, there is a significant relationship between stress and self-regulated learning, as well as between stress and learning flow (r = 0.23–0.26; p= < .05). However, none of the study constructs were found to predict academic achievement. CONCLUSION: Although self-regulation significantly predicted flow, stress and learning engagement, a non-significant association exists between all the study constructs and academic achievement. The results of this study have significant implications for improving the development of a positive learning environment that fosters active student engagement. Future studies should investigate correlation by conducting large-scale studies. IMPACT: This study makes a valuable contribution to the current body of literature concerning academic achievement within the context of undergraduate nursing education. The insignificant relationship between the study variables and academic achievement indicate that these elements are not of considerable significance in enhancing educational achievements in blended learning surroundings in Namibia. PATIENT OR PUBLIC CONTRIBUTION: One hundred and sixty-six undergraduate nursing students participated in the survey. The data collected were analysed and interpreted by a skilled statistician. Elsevier 2023-10-20 /pmc/articles/PMC10598534/ /pubmed/37885718 http://dx.doi.org/10.1016/j.heliyon.2023.e21321 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Tomas, Nestor Poroto, Annarosa The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title | The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title_full | The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title_fullStr | The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title_full_unstemmed | The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title_short | The interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: A cross-sectional survey |
title_sort | interplay between self-regulation, learning flow, academic stress and learning engagement as predictors for academic performance in a blended learning environment: a cross-sectional survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598534/ https://www.ncbi.nlm.nih.gov/pubmed/37885718 http://dx.doi.org/10.1016/j.heliyon.2023.e21321 |
work_keys_str_mv | AT tomasnestor theinterplaybetweenselfregulationlearningflowacademicstressandlearningengagementaspredictorsforacademicperformanceinablendedlearningenvironmentacrosssectionalsurvey AT porotoannarosa theinterplaybetweenselfregulationlearningflowacademicstressandlearningengagementaspredictorsforacademicperformanceinablendedlearningenvironmentacrosssectionalsurvey AT tomasnestor interplaybetweenselfregulationlearningflowacademicstressandlearningengagementaspredictorsforacademicperformanceinablendedlearningenvironmentacrosssectionalsurvey AT porotoannarosa interplaybetweenselfregulationlearningflowacademicstressandlearningengagementaspredictorsforacademicperformanceinablendedlearningenvironmentacrosssectionalsurvey |