What Are Error Rates for Classifying Teacher and School Performance Using Value-Added Models?
AbstractThis article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using formulas based on ordinary least squares and empirical Bayes estimators, error rates for comparing a teacherâ€™s performance to the average are likely to be about 25 percent with three years of data and 35 percent with one year of data. Corresponding error rates for overall false positive and negative errors are 10 percent and 20 percent, respectively. The results suggest that policymakers must carefully consider likely system error rates when using value-added estimates to make high-stakes decisions regarding educators.
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Bibliographic InfoPaper provided by Mathematica Policy Research in its series Mathematica Policy Research Reports with number 7762.
Date of creation: 30 Apr 2013
Date of revision:
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Value-Added Models; Performance Measurement Systems; Student Learning Gains; False Positive and Negative Error Rates;
Find related papers by JEL classification:
- I - Health, Education, and Welfare
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-04 (All new papers)
- NEP-EDU-2013-06-04 (Education)
- NEP-EFF-2013-06-04 (Efficiency & Productivity)
- NEP-HRM-2013-06-04 (Human Capital & Human Resource Management)
- NEP-URE-2013-06-04 (Urban & Real Estate Economics)
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