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Are value-added models good enough for teacher evaluations? Assessing commonly used models with simulated and actual data

Gary Henry (), Roderick Rose () and Doug Lauen ()
Additional contact information
Gary Henry: Vanderbilt University
Roderick Rose: University of North Carolina at Chapel Hill
Doug Lauen: University of North Carolina at Chapel Hill

Chapter 20 in Investigaciones de Economía de la Educación, 2014, vol. 9, pp 383-405 from Asociación de Economía de la Educación

Abstract: Teachers’ evaluations in many states include information about their students test score gains. In this paper, we describe the assumptions that are required for teacher value-added (TVA) estimates to be treated as unbiased causal effects. We compare commonly used TVA models on policy-relevant criteria using simulated data in which the assumptions of unconfounded assignment of students and teachers and no peer effects are violated and with actual data. The three-level hierarchical linear performs best when either assumption is violated. For year-to-year consistency, the dynamic ordinary least squares model performs best. A common policy goal – identifying the lowest performing quintile of teachers—can be done with reasonable accuracy but between 3.2 and 9.3 percent of all teachers are misclassified.

Keywords: value-added models; teacher policy; personnel evaluation (search for similar items in EconPapers)
JEL-codes: I28 J24 (search for similar items in EconPapers)
Date: 2014
ISBN: 978-84-942418-8-8
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