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Student assessment of teaching as a source of information about aspects of teaching quality in multiple subject domains: an application of multilevel bifactor structural equation modeling

机译:学生对教学的评估作为多个学科领域中教学质量方面信息的来源:多级双因子结构方程建模的应用

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Research on educational effectiveness most often uses student assessments of classroom instruction for measuring aspects of teaching quality. Given that crucial inferences on the success of education are based on these assessments, it is essential to ensure that they provide valid indicators. In this study, we illustrate the application of an innovative application of a multilevel bifactor structural equation model (ML-BFSEM) to examine the validity of student assessments. Analyzing a large-scale data set of 12,077 fourth-grade students in three countries (Finland, Norway, and Sweden), we find that (i) three aspects of teaching quality and subject domain factors can be established; (ii) metric and scalar invariance could be established for the ML-BFSEM approach across countries; and (iii) significant relations between students’ assessments of how easy the teacher is to understand and achievement in all subjects exist. In support of substantive research, we demonstrate a methodological approach for representing the complex nature of student assessments of teaching quality. We finally encourage substantive and methodological researchers to advance the ML-BFSEM.
机译:对教育效果的研究最经常使用学生对课堂教学的评估来衡量教学质量。鉴于对教育成功的关键推断基于这些评估,因此必须确保它们提供有效的指标。在这项研究中,我们说明了多级双因子结构方程模型(ML-BFSEM)的创新应用在检验学生评估有效性方面的应用。通过分析三个国家(芬兰,挪威和瑞典)的12077名四年级学生的大规模数据集,我们发现:(i)可以建立三个方面的教学质量和学科领域因素; (ii)可以为不同国家的ML-BFSEM方法建立度量和标量不变性; (iii)学生对教师的理解程度和所有学科的成就之间的评估之间存在重要关系。为了支持实质性研究,我们展示了一种方法论方法来代表学生对教学质量评估的复杂性。最后,我们鼓励实质性和方法论的研究人员推进ML-BFSEM。

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