Transforming Tenure: Using Value-Added Modeling to Identify Ineffective Teachers
Public school teachers in the United States are famously difficult to dismiss. The reason is simple: after three years on the job, most receive tenure—after a brief and subjective evaluation process (typically, a classroom visit or two by an administrator or another teacher) in which few receive negative ratings. Once tenured, teachers are armored against efforts to remove them, and most do not face any serious reevaluation to ensure that their skills stay up to standard. With this traditional approach, tenured teachers sometimes lose their positions for insubordination, criminal conduct, gross neglect, or other reasons—but almost never for simply being bad at the job.
This state of affairs protects teachers (both good and bad) quite well but is clearly harmful to students. The effects of a poor teacher, research has shown, haunt pupils for years afterward. Being assigned to such a teacher reduces the amount that a student learns in school and is associated with lower earnings in adulthood (in part because having an inadequate teacher makes a child more likely to have an early pregnancy and less likely to go to college). An education system that protects bad teachers does a grave disservice to the children in its care.
In recent years, some school districts have experimented with changes in tenure rules. They seek the power to remove ineffective teachers and, in some jurisdictions, to reevaluate teachers throughout their careers.
A keystone of this reform movement is the replacement of subjective evaluation with quantifiable measures of each teacher’s effectiveness. The quantitative method is known as value-added modeling (VAM), a statistical analysis of student scores that seeks to identify how much an individual teacher contributes to a pupil’s progress over the years. The use of VAM in teacher evaluations is growing, but the method remains extremely controversial. Critics often claim that it does not and cannot measure actual teacher quality.
This paper addresses that claim. Part I analyzes data from Florida public schools to show that a VAM score in a teacher’s third year is a good predictor of that teacher’s success in his or her fifth year. Having established that VAM is a useful predictive tool, Part II of the paper addresses the most effective ways that VAM can be used in tenure reform.
VAM is not a perfect measure of teacher quality because, like any statistical test, it is subject to random measurement errors. So it should not be regarded as the “magic bullet” solution to the problem of evaluating teacher performance. However, the method is reliable enough to be part of a sensible policy of tenure reform—one that replaces “automatic” tenure with rigorous evaluation of new candidates and periodic reexamination of those who have already received tenure.
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