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Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic

COVID-19 pandemic triggered distance education in higher education. Decisions such as isolation, social distancing and quarantine made by countries unexpectedly and suddenly forced face-to-face education to change to distance education within days. All academics around the world had to move online o...

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Autores principales: Karadag, Engin, Su, Ahmet, Ergin-Kocaturk, Hatice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505016/
https://www.ncbi.nlm.nih.gov/pubmed/34778542
http://dx.doi.org/10.1186/s41239-021-00291-w
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author Karadag, Engin
Su, Ahmet
Ergin-Kocaturk, Hatice
author_facet Karadag, Engin
Su, Ahmet
Ergin-Kocaturk, Hatice
author_sort Karadag, Engin
collection PubMed
description COVID-19 pandemic triggered distance education in higher education. Decisions such as isolation, social distancing and quarantine made by countries unexpectedly and suddenly forced face-to-face education to change to distance education within days. All academics around the world had to move online overnight. All the educational and academic activities in higher education (courses, exams, meetings, etc.) had to be conducted online in a few days. Based on these changes, this study aimed to analyze the relationships among student, faculty (adaptations of faculty members to distance education) and institutional (distance learning capacities of the universities) variables that affected satisfaction of the students related to distance education in higher education institutions in Turkey during COVID-19 pandemic using hierarchical linear modeling (HLM). The study group included 14,962 students and 3631 academics from 30 universities. The results showed that universities with higher distance education capacities got higher satisfaction scores. HLM analysis showed that 43% of the variation in satisfaction scores resulted from universities. The second HLM analysis showed that 44% of the overall satisfaction score variance of the students could be explained by the factors of university features (Level 2: distance education capacity and acceptance and use of distance education systems of faculty members). Thus, it was determined that 44% of the university factor calculated as 43% in Model 1 (which is calculated within students’ general satisfaction scores) resulted from the distance education capacity and the acceptance and use of distance education systems of faculty members. The findings of this study provide insights to improve distance education by stakeholders of higher education institutions.
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spelling pubmed-85050162021-10-12 Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic Karadag, Engin Su, Ahmet Ergin-Kocaturk, Hatice Int J Educ Technol High Educ Research Article COVID-19 pandemic triggered distance education in higher education. Decisions such as isolation, social distancing and quarantine made by countries unexpectedly and suddenly forced face-to-face education to change to distance education within days. All academics around the world had to move online overnight. All the educational and academic activities in higher education (courses, exams, meetings, etc.) had to be conducted online in a few days. Based on these changes, this study aimed to analyze the relationships among student, faculty (adaptations of faculty members to distance education) and institutional (distance learning capacities of the universities) variables that affected satisfaction of the students related to distance education in higher education institutions in Turkey during COVID-19 pandemic using hierarchical linear modeling (HLM). The study group included 14,962 students and 3631 academics from 30 universities. The results showed that universities with higher distance education capacities got higher satisfaction scores. HLM analysis showed that 43% of the variation in satisfaction scores resulted from universities. The second HLM analysis showed that 44% of the overall satisfaction score variance of the students could be explained by the factors of university features (Level 2: distance education capacity and acceptance and use of distance education systems of faculty members). Thus, it was determined that 44% of the university factor calculated as 43% in Model 1 (which is calculated within students’ general satisfaction scores) resulted from the distance education capacity and the acceptance and use of distance education systems of faculty members. The findings of this study provide insights to improve distance education by stakeholders of higher education institutions. Springer International Publishing 2021-10-12 2021 /pmc/articles/PMC8505016/ /pubmed/34778542 http://dx.doi.org/10.1186/s41239-021-00291-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Karadag, Engin
Su, Ahmet
Ergin-Kocaturk, Hatice
Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title_full Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title_fullStr Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title_full_unstemmed Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title_short Multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during COVID-19 pandemic
title_sort multi-level analyses of distance education capacity, faculty members’ adaptation, and indicators of student satisfaction in higher education during covid-19 pandemic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505016/
https://www.ncbi.nlm.nih.gov/pubmed/34778542
http://dx.doi.org/10.1186/s41239-021-00291-w
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