Student-Achievement Data in Tenure Decisions
The fine folks over at the National Center for Analysis of Longitudinal Data in Education Research have an interesting study up on the use of student test-score data in tenure decisions.
Of late, some economists who study the teacher workforce, such as Thomas Kane at Harvard and Eric Hanushek at Stanford, have argued that it might make more sense to see how teachers are doing on the job and then set policies to transition out ineffective teachers, rather than attempt to prescreen teacher-candidates for effectiveness. Most districts do the latter but not the former, and that process hasn't proved very successful over the years. One possibility for attempting to determine on-the-ground teacher performance is to use student test-score data over time that is linked to individual teachers.
Using a matched set of teacher/student data encompassing about 10,000 North Carolina teachers, researchers Dan Goldhaber and Michael Hansen tested this hypothesis. They attempted to determine whether this "value added" data over a teacher's first few years can predict his or her future performance, thus giving districts useful objective data upon which to base tenure decisions.
They found that the pre- and post-tenure estimates of teaching effectiveness in North Carolina were much more consistent in math than in reading. In reading, for example, 11 percent of teachers in the bottom quintile of teaching effectiveness after two years of test data were ultimately found to be among the most effective teachers; a tenure policy based solely on the value-added data would have barred these teachers from the profession. In math, however, only 2 percent of the most ineffective teachers were ultimately found to be effective.
Although generally value-added estimates are supposed to be more sound with multiple years of data, the picture didn't look much different with an additional year of data.
Perhaps these effects show that it takes reading teachers more years of experience than math teachers to become effective, or alternatively, that it's more difficult to measure teacher effects in reading than in math
What would the effect of such policies be? Well, if tenure was denied based on low performance in either reading or math, about 30 percent of teachers would not be granted tenure. But if only teachers who were ineffective in both reading and math were transitioned out of the profession, the figure would drop to about 11 percent.
The data, the authors note, are probably not going to persuade opponents of teacher value-added policies to change their minds. On the other hand, the fact that the systems do in general predict effectiveness suggests they could be one of several factors in determining whether or not to grant a teacher tenure, they argued.
But you don't have to take their word for it (or ours). Tell us what YOU think.