A review of using partial least square structural equation modeling in e-learning research

被引:78
|
作者
Lin, Hung-Ming [1 ]
Lee, Min-Hsien [2 ,3 ]
Liang, Jyh-Chong [2 ,3 ]
Chang, Hsin-Yi [2 ,3 ]
Huang, Pinchi [4 ]
Tsai, Chin-Chung [2 ,3 ]
机构
[1] Minghsin Univ Sci & Technol, Dept Business Adm, Xinfeng, Taiwan
[2] Natl Taiwan Normal Univ, Program Learning Sci, 162,Sect 1,Heping E Rd, Taipei 106, Taiwan
[3] Natl Taiwan Normal Univ, Inst Res Excellence Learning Sci, 162,Sect 1,Heping E Rd, Taipei 106, Taiwan
[4] Natl Taiwan Normal Univ, Off Secretariat, Taipei, Taiwan
关键词
PLS-SEM; HIGHER-EDUCATION; STUDENT PARTICIPATION; SUCCESS FACTORS; SOCIAL MEDIA; SYSTEM; ACCEPTANCE; MANAGEMENT; BEHAVIOR; ONLINE;
D O I
10.1111/bjet.12890
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
引用
收藏
页码:1354 / 1372
页数:19
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