Does Tracking of Students Bias Value-Added Estimates for Teachers?

Working Paper 15
Publisher: Washington, DC: Mathematica Policy Research
Mar 30, 2013
Ali Protik, Elias Walsh, Alexandra Resch, Eric Isenberg, and Emma Kopa
This working paper uses urban school district data to investigate whether including track indicators or accounting for classroom characteristics in the value-added model is sufficient to eliminate potential bias resulting from the sorting of students into academic tracks. Accounting for two classroom characteristics—mean classroom achievement and the standard deviation of classroom achievement—may reduce bias for middle school math teachers, whereas track indicators help for high school reading teachers. However, including both of these measures simultaneously reduces the precision of the value-added estimates in this context. While these different specifications produce substantially different value-added estimates, they produce small changes in the tails of value-added distribution.