基于ADANCO 2.3.1的现代偏最小二乘结构方程模型在COVID-19大流行期间在线教育中的应用

IF 0.3 Q3 AREA STUDIES
Chanta Jhantasana
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引用次数: 0

摘要

本研究采用复合模型研究新冠肺炎疫情期间影响学生在线教育满意度的因素及其与学生生活质量的关系。此外,研究回顾了ADANCO 2.3.1软件用于复合分析。本研究的样本是来自拉贾哈特大学的257名管理科学专业的学生。研究发现,只有输出和设置因素与学生的OE满意度有显著的关系。研究发现,学生的OE满意度与学生生活质量之间存在显著的关系。ADANCO对于现代偏最小二乘结构方程模型(PLS-SEM)的验证性复合分析(CCA)非常有用。这也是将潜在变量和可观察变量转化为突发变量的有效工具。本研究成功解决了标准偏倚方法,结果较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reviewing ADANCO 2.3.1 for a Modern Partial Least Squares Structural Equation Model to be Used in Online Education During the COVID-19 Pandemic
The current study employed a composite model to examine the factors affecting student satisfaction with online education (OE) and the relationship between it and student life quality during the COVID-19 pandemic. Additionally, the research reviewed the ADANCO 2.3.1 software for composite analysis. A sample of 257 management science students from anonymous Rajabhat University was used for this study. The findings indicate that only the factors of output and setup had a significant relationship with student satisfaction concerning OE. The relationship between student satisfaction with OE and the quality of student life was found to be significant. The ADANCO was extremely useful for doing confirmatory composite analysis (CCA) in modern partial least squares structural equation models (PLS-SEM). It was also a helpful tool for transforming latent and observable variables into emergent ones for CCA research. This study successfully resolved the standard bias method resulting in a better outcome.
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CiteScore
1.20
自引率
11.10%
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