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Article
Disentangling Disadvantage: Can We Distinguish Good Teaching from Classroom Composition?
Journal of Research on Educational Effectiveness (2015)
  • Gema Zamarro
  • John Engberg, Rand Corporation
  • Juan Esteban Saavedra, University of Southern California
  • Jennifer Steele, Rand Corporation
Abstract

This article investigates the use of teacher value-added estimates to assess the distribution of effective teaching across students of varying socioeconomic disadvantage in the presence of classroom composition effects. We examine, via simulations, how accurately commonly used teacher value-added estimators recover the rank correlation between true and estimated teacher effects and a parameter representing the distribution of effective teaching. We consider various scenarios of teacher assignment, within-teacher variability in classroom composition, the importance of classroom com- position effects, and the presence of student unobserved heterogeneity. No single model recovers without bias estimates of the distribution parameter in all the scenarios we consider. Models that rank teacher effectiveness most accurately do not necessarily recover distribution parameter estimates with less bias. Since true teacher sorting in real data is seldom known, we recommend that analysts incorporate contextual information into their decisions about model choice and we offer some guidance on how to do so.

Publication Date
2015
Citation Information
Gema Zamarro, John Engberg, Juan Esteban Saavedra and Jennifer Steele. "Disentangling Disadvantage: Can We Distinguish Good Teaching from Classroom Composition?" Journal of Research on Educational Effectiveness Vol. 8 Iss. 1 (2015)
Available at: http://works.bepress.com/gema_zamarro/9/