A predictive study of student satisfaction in online education programs

This paper is intended to investigate the degree to which interaction and other predictors contribute to student satisfaction in online learning settings. This was a preliminary study towards a dissertation work which involved the establishment of interaction and satisfaction scales through a conte...

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Autores principales:	Yu-Chun Kuo, Andrew E Walker, Brian R Belland, Kerstin E E Schroder
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2013
Materias:	Interaction Satisfaction Self-regulation Internet-self efficacy Online learning Regression Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/26e634ed4ad3436398ef42a0633905b7
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spelling	oai:doaj.org-article:26e634ed4ad3436398ef42a0633905b72021-12-02T17:00:38ZA predictive study of student satisfaction in online education programs10.19173/irrodl.v14i1.13381492-3831https://doaj.org/article/26e634ed4ad3436398ef42a0633905b72013-01-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/1338https://doaj.org/toc/1492-3831 This paper is intended to investigate the degree to which interaction and other predictors contribute to student satisfaction in online learning settings. This was a preliminary study towards a dissertation work which involved the establishment of interaction and satisfaction scales through a content validity survey. Regression analysis was performed to determine the contribution of predictor variables to student satisfaction. The effects of student background variables on predictors were explored. The results showed that learner-instructor interaction, learner-content interaction, and Internet self-efficacy were good predictors of student satisfaction while interactions among students and self-regulated learning did not contribute to student satisfaction. Learner-content interaction explained the largest unique variance in student satisfaction. Additionally, gender, class level, and time spent online per week seemed to have influence on learner-learner interaction, Internet self-efficacy, and self-regulation. Yu-Chun KuoAndrew E WalkerBrian R BellandKerstin E E SchroderAthabasca University PressarticleInteractionSatisfactionSelf-regulationInternet-self efficacyOnline learningRegressionSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 14, Iss 1 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Interaction Satisfaction Self-regulation Internet-self efficacy Online learning Regression Special aspects of education LC8-6691
spellingShingle	Interaction Satisfaction Self-regulation Internet-self efficacy Online learning Regression Special aspects of education LC8-6691 Yu-Chun Kuo Andrew E Walker Brian R Belland Kerstin E E Schroder A predictive study of student satisfaction in online education programs
description	This paper is intended to investigate the degree to which interaction and other predictors contribute to student satisfaction in online learning settings. This was a preliminary study towards a dissertation work which involved the establishment of interaction and satisfaction scales through a content validity survey. Regression analysis was performed to determine the contribution of predictor variables to student satisfaction. The effects of student background variables on predictors were explored. The results showed that learner-instructor interaction, learner-content interaction, and Internet self-efficacy were good predictors of student satisfaction while interactions among students and self-regulated learning did not contribute to student satisfaction. Learner-content interaction explained the largest unique variance in student satisfaction. Additionally, gender, class level, and time spent online per week seemed to have influence on learner-learner interaction, Internet self-efficacy, and self-regulation.
format	article
author	Yu-Chun Kuo Andrew E Walker Brian R Belland Kerstin E E Schroder
author_facet	Yu-Chun Kuo Andrew E Walker Brian R Belland Kerstin E E Schroder
author_sort	Yu-Chun Kuo
title	A predictive study of student satisfaction in online education programs
title_short	A predictive study of student satisfaction in online education programs
title_full	A predictive study of student satisfaction in online education programs
title_fullStr	A predictive study of student satisfaction in online education programs
title_full_unstemmed	A predictive study of student satisfaction in online education programs
title_sort	predictive study of student satisfaction in online education programs
publisher	Athabasca University Press
publishDate	2013
url	https://doaj.org/article/26e634ed4ad3436398ef42a0633905b7
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A predictive study of student satisfaction in online education programs

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