Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseОткрытый API экосистемы
Обзорная статья

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

Hung‐Ming LinMing Hsin University of Science & Technology, TaiwanMin‐Hsien LeeJyh‐Chong LiangHsin‐Yi ChangPin-Chi Huang“National Taiwan Normal University”Chin‐Chung TsaiAddress 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: [email protected]
2019en
ABI

Аннотация

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.

Перевод пока недоступен

Идентификаторы

Цитирования и источники

Цитирований: 2Использованных источников: 0