Structural Equation Modeling in E-Learning Research: A Systematic Review

• In Event: Systematic Reviews of Advanced Research Methodologies in Education

Abstract

Structural equation modeling (SEM) is a technique for testing the cause and effect relationship among variables in various fields. SEM is also used to determine the linear causal relationship between latent and observed variables. This study systematically reviewed how SEM is used in e-learning research and the extent to which it reflects best practices. Eighty-one articles from top-ranked e-learning journals published from 2015 to 2020 were examined. Strengths of the research reviewed included examining models and measures not previously tested empirically and generating new insights into old topics through the use of SEM. Weaknesses included significant model modifications without theoretical justification or substantive interpretations. Suggestions are offered for improving applications of SEM in e–learning research.

Author

• Liu Liu, University of Washington - Seattle