Do Different Value-Added Models Tell Us the Same Things?



  • Statistical models that evaluate teachers based on growth in student achievement differ in how they account for student backgrounds, school, and classroom resources. They also differ by whether they compare teachers across a district (or state) or just within schools.
  • Statistical models that do not account for student background factors produce estimates of teacher quality that are highly correlated with estimates from value-added models that do control for student backgrounds, as long as each includes a measure of prior student achievement.
  • Even when correlations between models are high, different models will categorize many teachers differently.
  • Teachers of advantaged students benefit from models that do not control for student background factors, while teachers of disadvantaged students benefit from models that do.
  • The type of teacher comparisons, whether within or between schools, generally has a larger effect on teacher rankings than statistical adjustments for differences in student backgrounds across classrooms.


There are good reasons for re-thinking teacher evaluation. As we know, evaluation systems in most school districts appear to be far from rigorous. A recent study showed that more than 99 percent of teachers in a number of districts were rated “satisfactory,” which does not comport with empirical evidence that teachers differ substantially from each other in terms of their effectiveness. Likewise, the ratings do not reflect the assessment of the teacher workforce by administrators, other teachers, or students.

Evaluation systems that fail to recognize the true differences that we know exist among teachers greatly hamper the ability of school leaders and policymakers to make informed decisions about such matters as which teachers to hire, what teachers to help, which teachers to promote, and which teachers to dismiss. Thus it is encouraging that policymakers are developing more rigorous evaluation systems, many of which are partly based on student test scores.

Yet while the idea of using student test scores for teacher evaluations may be conceptually appealing, there is no universally accepted methodology for translating student growth into a measure of teacher performance. In this brief, we review what is known about how measures that use student growth align with one another, and what that agreement or disagreement might mean for policy.

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