Identifying and prioritizing effective factors of e-learning effectiveness using hierarchical analysis in the Ministry of Education in Iran

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The purpose of present study was to identify and prioritize the effective factors of electronic learning effectiveness in the Ministry of Education of Iran, using a hierarchical analysis and through a descriptive-survey method. The statistical population of present study included managers and expert...

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Detalles Bibliográficos
Autores: Yazdanfar, Kiarash, Beikzad, Jafar, Rahimi, Gholamreza, Bohlooli, Nader
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad Peruana Unión
Repositorio:Revistas Universidad Peruana Unión
Lenguaje:español
OAI Identifier:oai:ojs2.apuntesuniversitarios.upeu.edu.pe:article/595
Enlace del recurso:https://apuntesuniversitarios.upeu.edu.pe/index.php/revapuntes/article/view/595
Nivel de acceso:acceso abierto
Materia:e-learning, individual characteristics, organizational characteristics, infrastructure.
Descripción
Sumario:The purpose of present study was to identify and prioritize the effective factors of electronic learning effectiveness in the Ministry of Education of Iran, using a hierarchical analysis and through a descriptive-survey method. The statistical population of present study included managers and experts of Education Organization and a sample of professors with Ph.D. in Educational Sciences as well as experience of teaching in electronic training. Therefore, purposeful non-random sampling method was used to select the sample size. The used tool was a hurricane-thinking questionnaire. Indicators were organized as a questionnaire in the form of 5-point Likert scale and the effective factors of electronic learning effectiveness were identified through implementing subsequent rounds. The reliability of research tool with 28 items was calculated equal to 0.88 using Cronbach’s alpha. Data analysis in the section of identifying effective factors of e-learning effectiveness was performed using Delphi method and utilizing from SPSS Software and in the section of prioritizing was performed through AHP method using Expert Choice Software.
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