Multiple Measures And Singular Conclusions In A Twin City
A few weeks ago, the Minneapolis Star Tribune published teacher evaluation results for the district’s public school teachers in 2013-14. This decision generated a fair amount of controversy, but it’s worth noting that the Tribune, unlike the Los Angeles Times and New York City newspapers a few years ago, did not publish scores for individual teachers, only totals by school.
The data once again provide an opportunity to take a look at how results vary by student characteristics. This was indeed the focus of the Tribune’s story, which included the following headline: “Minneapolis’ worst teachers are in the poorest schools, data show." These types of conclusions, which simply take the results of new evaluations at face value, have characterized the discussion since the first new systems came online. Though understandable, they are also frustrating and a potential impediment to the policy process. At this early point, “the city’s teachers with the lowest evaluation ratings” is not the same thing as “the city’s worst teachers." Actually, as discussed in a previous post, the systematic variation in evaluation results by student characteristics, which the Tribune uses to draw conclusions about the distribution of the city’s “worst teachers," could just as easily be viewed as one of the many ways that one might assess the properties and even the validity of those results.
So, while there are no clear-cut "right" or "wrong" answers here, let’s take a quick look at the data and what they might tell us.