ERIC Number: EJ1257354
Record Type: Journal
Publication Date: 2020-Jul
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0007-1013
EISSN: N/A
A Review of Using Partial Least Square Structural Equation Modeling in E-Learning Research
Lin, Hung-Ming; Lee, Min-Hsien; Liang, Jyh-Chong; Chang, Hsin-Yi; Huang, Pinchi; Tsai, Chin-Chung
British Journal of Educational Technology, v51 n4 p1354-1372 Jul 2020
Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use. This paper reviews the uses of PLS-SEM in 16 major e-learning journals, and provides guidelines for improving the use of PLS-SEM as well as recommendations for future applications in e-learning research. A total of 53 articles using PLS-SEM published in January 2009-August 2019 are reviewed. We assess these published applications in terms of the following key criteria: reasons for using PLS-SEM, model characteristics, sample characteristics, model evaluations and reporting. Our results reveal that small sample size and nonnormal data are the first two major reasons for using PLS-SEM. Moreover, we have identified how to extend the applications of PLS-SEM in the e-learning research field.
Descriptors: Least Squares Statistics, Structural Equation Models, Electronic Learning, Educational Research, Multivariate Analysis, Sample Size
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Publication Type: Journal Articles; Information Analyses
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A