Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses
Yu-Chun Kuo, School of Lifelong Learning, United States ; Andrew E. Walker, Instructional Technology & Learning Sciences, United States ; Kerstin E.E. Schroder, Department of Health Behavior, United States ; Brian R. Belland, Instructional Technology & Learning Sciences, United States
Internet and Higher Education Volume 20, Number 1, ISSN 1096-7516 Publisher: Elsevier Ltd
Student satisfaction is important in the evaluation of distance education courses as it is related to the quality of online programs and student performance. Interaction is a critical indicator of student satisfaction; however, its impact has not been tested in the context of other critical student- and class-level predictors. In this study, we tested a regression model for student satisfaction involving student characteristics (three types of interaction, Internet self-efficacy, and self-regulated learning) and class-level predictors (course category and academic program). Data were collected in a sample of 221 graduate and undergraduate students responding to an online survey. The regression model was tested using hierarchical linear modeling (HLM). Learner–instructor interaction and learner–content interaction were significant predictors of student satisfaction but learner–learner interaction was not. Learner–content interaction was the strongest predictor. Academic program category moderated the effect of learner–content interaction on student satisfaction. The effect of learner–content interaction on student satisfaction was stronger in Instructional Technology and Learning Sciences than in psychology, physical education or family, consumer, and human development. In sum, the results suggest that improvements in learner–content interaction yield most promise in enhancing student satisfaction and that learner–learner interaction may be negligible in online course settings.
Kuo, Y.C., Walker, A.E., Schroder, K.E.E. & Belland, B.R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. Internet and Higher Education, 20(1), 35-50. Elsevier Ltd.
Cited ByView References & Citations Map
Computer-supported collaborative learning: An analysis of the relationship between interaction, emotional support and online collaborative tools
Nuria Hernández-Sellés, Vice dean of , Spain; Pablo-César Muñoz-Carril, Professor in the Pedagogy and Didactics Department and Teacher Training Faculty at the University of Santiago de Compostela, Spain; Mercedes González-Sanmamed, Full Professor in the Pedagogy and Didactics Department of the Faculty of Education Sciences at the University of A Coruña, Spain
Computers & Education Vol. 138, No. 1 (September 2019) pp. 1–12
Serpil Kocdar, Anadolu University; Abdulkadir Karadeniz, Artvin Coruh University; Aras Bozkurt, Anadolu University & University of South Africa; Koksal Buyuk
The International Review of Research in Open and Distributed Learning Vol. 19, No. 1 (Feb 23, 2018)
Chin Goh, Choi Leong, Kalsum Kasmin, Puong Hii & Owee Tan
Journal of e-Learning and Knowledge Society Vol. 13, No. 2 (May 29, 2017)
Yu-Chun Kuo, Jackson State University, United States; Yu-Tung Kuo, Purdue University, United States
Society for Information Technology & Teacher Education International Conference 2015 (Mar 02, 2015) pp. 364–373
These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact email@example.com.