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A predictive study of student satisfaction in online education programs
ARTICLE

, Jackson State University ; , , Utah State University ; , University of Alabama at Birmingham

IRRODL Volume 14, Number 1, ISSN 1492-3831 Publisher: Athabasca University Press

Abstract

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.

Citation

Kuo, Y.C., Walker, A., Belland, B. & Schroder, K. (2013). A predictive study of student satisfaction in online education programs. The International Review of Research in Open and Distributed Learning, 14(1), 16-39. Athabasca University Press. Retrieved April 25, 2019 from .

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