How Should Educators Interpret Value-Added Scores? What We Know Series: Value-Added Methods and Applications. Knowledge Brief 1

A teacher's value-added score is intended to convey how much that teacher has contributed to student learning in a particular subject in a particular year. Different school districts define and compute value-added scores in different ways. A variety of people may see value-added estimates, and each group may use them for different purposes. Teachers themselves may want to compare their scores with those of others and use them to improve their work. Administrators may use them to make decisions about teaching assignments, professional development, pay, or promotion. Parents, if they see the scores, may use them to request particular teachers for their children. And, finally, researchers may use the estimates for studies on improving instruction. Using value-added scores in any of these ways can be controversial. Some people doubt the validity of the achievement tests on which the scores are based, some question the emphasis on test scores to begin with, and others challenge the very idea that student learning gains reflect how well teachers do their jobs. The authors' purpose is to answer a more limited, but essential, question: How might educators reasonably interpret value-added scores? Social science has yet to come up with a perfect measure of teacher effectiveness, so anyone who makes decisions on the basis of value-added estimates will be doing so in the midst of uncertainty. Making choices in the face of doubt is hardly unusual--they routinely contend with projected weather forecasts, financial predictions, medical diagnoses, and election polls. But as in these other areas, in order to sensibly interpret value-added scores, it is important to do two things: understand the sources of uncertainty and quantify its extent. The authors' aim is to identify possible errors of interpretation, to consider how likely these errors are to arise, and to help educators assess how consequential they are for different decisions. They will begin by asking how value-added scores are defined and computed. Next, they will consider two sources of error: statistical bias and statistical imprecision. (Contains 4 figures, 1 table, and 11 endnotes.)