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The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context

This dataset contains demographic information of 355 respondents and a validated 32-items Stages of Concerns Questionnaire (SoCQ). The SoCQ questionnaire was developed based on the Concerns-Based Adoption Model (CBAM) which measures seven stages of concerns as the variables. They are unconcerned, in...

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Detalles Bibliográficos
Autores principales: He, Yong Zheng, Yusop, Farrah Dina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038033/
https://www.ncbi.nlm.nih.gov/pubmed/32123703
http://dx.doi.org/10.1016/j.dib.2020.105230
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author He, Yong Zheng
Yusop, Farrah Dina
author_facet He, Yong Zheng
Yusop, Farrah Dina
author_sort He, Yong Zheng
collection PubMed
description This dataset contains demographic information of 355 respondents and a validated 32-items Stages of Concerns Questionnaire (SoCQ). The SoCQ questionnaire was developed based on the Concerns-Based Adoption Model (CBAM) which measures seven stages of concerns as the variables. They are unconcerned, informational, personal, management, consequence, collaboration and refocusing. The data was firstly tested with normality, followed by validity checking using confirmatory factor analysis (CFA). It is useful for policy makers and stakeholders to have a thorough understanding about teachers’ concerns on the use of the e-learning platform and thus, design suitable interventions to smoothen the adoption process of using the technology. This set of data could be used in a multi-racial developing country for more complex analyses.
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spelling pubmed-70380332020-03-02 The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context He, Yong Zheng Yusop, Farrah Dina Data Brief Social Science This dataset contains demographic information of 355 respondents and a validated 32-items Stages of Concerns Questionnaire (SoCQ). The SoCQ questionnaire was developed based on the Concerns-Based Adoption Model (CBAM) which measures seven stages of concerns as the variables. They are unconcerned, informational, personal, management, consequence, collaboration and refocusing. The data was firstly tested with normality, followed by validity checking using confirmatory factor analysis (CFA). It is useful for policy makers and stakeholders to have a thorough understanding about teachers’ concerns on the use of the e-learning platform and thus, design suitable interventions to smoothen the adoption process of using the technology. This set of data could be used in a multi-racial developing country for more complex analyses. Elsevier 2020-02-04 /pmc/articles/PMC7038033/ /pubmed/32123703 http://dx.doi.org/10.1016/j.dib.2020.105230 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Social Science
He, Yong Zheng
Yusop, Farrah Dina
The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title_full The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title_fullStr The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title_full_unstemmed The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title_short The dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: Malaysian context
title_sort dataset for the stages of concerns of public-school teachers towards the use of e-learning platform: malaysian context
topic Social Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038033/
https://www.ncbi.nlm.nih.gov/pubmed/32123703
http://dx.doi.org/10.1016/j.dib.2020.105230
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