Teacher Quality/Effectiveness: Defining, Developing, and Assessing Policies and Practices Part III: Setting Policies around Teacher Quality/Effectiveness – and the Consequences Friday, April 27, 2012 Kimmel Center for University Life Education Policy Breakfast Series

Evaluating Teachers: The Important Role of Value-Added Brown Center on Education Policy at Brookings, November 2010 Susanna Loeb, Stanford; Dan Goldhaber, University of Washington; et al. EXECUTIVE SUMMARY The evaluation of teachers based on the contribution they make to the learning of their students, value-added, is an increasingly popular but controversial education reform policy. We highlight and try to clarify four areas of confusion about value-added. The first is between value-added information and the uses to which it can be put. One can, for example, be in favor of an evaluation system that includes value-added information without endorsing the release to the public of value-added data on individual teachers. The second is between the consequences for teachers vs. those for students of classifying and misclassifying teachers as effective or ineffective — the interests of students are not always perfectly congruent with those of teachers. The third is between the reliability of value-added measures of teacher performance and the standards for evaluations in other fields — value-added scores for individual teachers turn out to be about as reliable as performance assessments used elsewhere for high stakes decisions. The fourth is between the reliability of teacher evaluation systems that include value-added vs. those that do not — ignoring value-added typically lowers the reliability of personnel decisions about teachers. Recommended Readings from David Steiner

Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique National Bureau of Economic Research, April 2009 Cory Koedel, University of Missouri; and Julian R. Betts, University of California, San Diego ABSTRACT Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research (Rothstein, 2009) questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting-bias problem to statistical insignificance. Recommended Readings from David Steiner

Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation NBER Working Paper Series, December 2008 Thomas J. Kane, Harvard; and Douglas O. Staiger, Dartmouth ABSTRACT We used a random-assignment experiment in Los Angeles Unified School District to evaluate various non- experimental methods for estimating teacher effects on student test scores. Having estimated teacher effects during a pre-experimental period, we used these estimates to predict student achievement following random assignment of teachers to classrooms. While all of the teacher effect estimates we considered were significant predictors of student achievement under random assignment, those that controlled for prior student test scores yielded unbiased predictions and those that further controlled for mean classroom characteristics yielded the best prediction accuracy. In both the experimental and non-experimental data, we found that teacher effects faded out by roughly 50 percent per year in the two years following teacher assignment. Recommended Readings from David Steiner

Please visit where copies of these articles will be posted soon. You may also watch videos and review presentations from previous breakfasts in this year’s series. Education Policy Breakfast Series