Bayesian model selection for barriers in online learning behaviors

Article type: Research Article

Authors: Khoi, Bui Huy

Affiliations: Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam | E-mail: [email protected]

Correspondence: [*] Corresponding author: Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam. E-mail: [email protected].

Abstract: The study presents an overview of theories related to e-learning barriers and e-learning behavior. Research and synthesize relevant studies at home and abroad. From related studies, identify barrier factors affecting the online learning behavior of students. Then, the research model and hypotheses for the study are presented. In this study, the author identified 5 barriers affecting students’ online learning behavior in Ho Chi Minh City: economic barriers (ECOB), interaction barriers (IB), psychological barrier (PB), environmental barriers (ENI), and regulatory institutional barriers (RIB). Previous studies revealed that using linear regression. The paper uses the optimum selection by Bayesian consideration for e-learning barriers and e-learning behavior. Get the results, then make recommendations and solutions to help educational administrators reduce barriers to increase students’ effectiveness in online learning in a better way.

Keywords: BIC Algorithm, economic barriers, interaction barriers, psychological barrier, environmental barriers, regulatory institutional barriers

DOI: 10.3233/HIS-230001

Journal: International Journal of Hybrid Intelligent Systems, vol. 19, no. 1,2, pp. 1-13, 2023