Leckie George, Parker Richard, Goldstein Harvey, Tilling Kate
University of Bristol.
J Educ Behav Stat. 2024 Dec;49(6):879-911. doi: 10.3102/10769986231210808. Epub 2023 Nov 27.
School value-added models are widely applied to study, monitor, and hold schools to account for school differences in student learning. The traditional model is a mixed-effects linear regression of student current achievement on student prior achievement, background characteristics, and a school random intercept effect. The latter is referred to as the school value-added score and measures the mean student covariate-adjusted achievement in each school. In this article, we argue that further insights may be gained by additionally studying the variance in this quantity in each school. These include the ability to identify both individual schools and school types that exhibit unusually high or low variability in student achievement, even after accounting for differences in student intakes. We explore and illustrate how this can be done via fitting mixed-effects location scale versions of the traditional school value-added model. We discuss the implications of our work for research and school accountability systems.
学校增值模型被广泛应用于研究、监测学校,并要求学校对学生学习方面的差异负责。传统模型是学生当前成绩对学生先前成绩、背景特征以及学校随机截距效应的混合效应线性回归。后者被称为学校增值分数,用于衡量每所学校学生经协变量调整后的平均成绩。在本文中,我们认为通过进一步研究每所学校在这个量上的方差,可能会获得更多见解。这些见解包括能够识别出即使在考虑了学生入学差异之后,在学生成绩方面表现出异常高或低变异性的个别学校和学校类型。我们探索并举例说明了如何通过拟合传统学校增值模型的混合效应位置尺度版本来做到这一点。我们讨论了我们的工作对研究和学校问责制的影响。