Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students’ achievement. It is gaining increasing importance in educational evaluation, teacher accountability, and high-stakes decisions. We analyzed 370 empirical studies on VA modeling, focusing on modeling and methodological issues to identify key factors for improvement. The studies stemmed from 26 countries (68% from the USA). Most studies applied linear regression or multilevel models. Most studies (i.e., 85%) included prior achievement as a covariate, but only 2% included noncognitive predictors of achievement (e.g., personality or affective student variables). Fifty-five percent of the studies did not apply statistical adjustments (e.g., shrinkage) to increase precision in effectiveness estimates, and 88% included no model diagnostics. We conclude that research on VA modeling can be significantly enhanced regarding the inclusion of covariates, model adjustment and diagnostics, and the clarity and transparency of reporting.

中文翻译：

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增值建模中的方法论问题：来自 26 个国家的国际审查

增值 (VA) 模型可用于通过估计教学行为对学生成绩的影响来量化教师和学校的有效性。它在教育评估、教师问责制和高风险决策中变得越来越重要。我们分析了 370 项关于 VA 建模的实证研究，重点关注建模和方法论问题，以确定改进的关键因素。这些研究来自 26 个国家（68% 来自美国）。大多数研究应用线性回归或多级模型。大多数研究（即 85%）将先前的成绩作为协变量，但只有 2% 的研究包括成绩的非认知预测因素（例如，个性或情感学生变量）。55% 的研究没有应用统计调整（例如收缩）来提高有效性估计的精确度，88% 不包括模型诊断。我们得出的结论是，在包含协变量、模型调整和诊断以及报告的清晰度和透明度方面，可以显着增强对 VA 建模的研究。