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A review of using partial least square structural equation modeling in e-learning research
Authors:Hung-Ming Lin  Min-Hsien Lee  Jyh-Chong Liang  Hsin-Yi Chang  Pinchi Huang  Chin-Chung Tsai
Affiliation:Address for correspondence: Chin-Chung Tsai, Program of Learning Sciences and Institute for Research Excellence in Learning Sciences, National Taiwan Normal Unversity, #162, Section 1, Heping E. Rd., Taipei City 106, Taiwan. Email: tsaicc@ntnu.edu.tw
Abstract: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.
Keywords:e-learning  Mobile learning  Quantitative Analysis
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