使用结构方程建模时考虑统计等效模型:以物理学特性为例

Q3 Social Sciences
Yangqiuting Li, Chandralekha Singh
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引用次数: 0

摘要

结构方程模型(SEM)是一种广泛应用于教育研究的统计方法,用于研究变量之间的关系。使用 SEM 模型涉及到一个关键步骤,即考虑统计学上的等效模型,并思考为什么不应该摒弃所提出的模型而选择等效模型。然而,许多使用 SEM 的研究并没有明确讨论这一步骤。在本研究中,我们以物理认同模型为例,说明多个统计上等效的模型如何具有不同的教学意义。以往的研究表明,物理认同包括三个维度:感知认可、自我效能感和兴趣。然而,这些维度之间的关系尚未得到透彻的理解。在此,我们将讨论我们提出的感知认可度预测自我效能感和兴趣的模型如何得到先前涉及学生个体访谈的研究的支持,以及干预研究如何进一步确定更准确的因果模型。我们的研究强调了在使用 SEM 作为分析工具时考虑统计等效模型的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considering Statistically Equivalent Models when using Structural Equation Modeling: an Example from Physics Identity
Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. Using a SEM model involves a crucial step of considering statistically equivalent models and contemplating why the proposed model should not be rejected in favor of equivalent ones. However, many studies using SEM did not explicitly discuss this step. In this study, we use physics identity model as an example to demonstrate how multiple statistically equivalent models have distinct instructional implications. Previous research has indicated that physics identity comprises three dimensions: perceived recognition, self-efficacy, and interest. However, the relationships between these dimensions have not been thoroughly understood. Here, we discuss how our proposed model with perceived recognition predicting self-efficacy and interest is supported by prior studies involving individual student interviews and how intervention studies can further determine a more accurate causal model. Our study highlights the importance of considering statistically equivalent models when using SEM as an analysis tool.
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CiteScore
1.10
自引率
0.00%
发文量
19
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