School Effects

Louisiana's "School Performance Score" Doesn't Measure School Performance

Louisiana’s "School Performance Score" (SPS) is the state’s primary accountability measure, and it determines whether schools are subject to high-stakes decisions, most notably state takeover. For elementary and middle schools, 90 percent of the SPS is based on testing outcomes. For secondary schools, it is 70 percent (and 30 percent graduation rates).*

The SPS is largely calculated using absolute performance measures – specifically, the proportion of students falling into the state’s cutpoint-based categories (e.g., advanced, mastery, basic, etc.). This means that it is mostly measuring student performance, rather than school performance. That is, insofar as the SPS only tells you how high students score on the test, rather than how much they have improved, schools serving more advantaged populations will tend to do better (since their students tend to perform well when they entered the school) while those in impoverished neighborhoods will tend to do worse (even those whose students have made the largest testing gains).

One rough way to assess this bias is to check the association between SPS and student characteristics, such as poverty. So let’s take a quick look.

A Game Of Inches

One of the more telling episodes in education I’ve seen over the past couple of years was a little dispute over Michelle Rhee’s testing record that flared up last year. Alan Ginsburg, a retired U.S. Department of Education official, released an informal report in which he presented the NAEP cohort changes that occurred during the first two years of Michelle Rhee’s tenure (2007-2009), and compared them with those during the superintendencies of her two predecessors.

Ginsburg concluded that the increases under Chancellor Rhee, though positive, were less rapid than in previous years (2000 to 2007 in math, 2003 to 2007 in reading). Soon thereafter, Paul Peterson, director of Harvard’s Program on Educational Leadership and Governance, published an article in Education Next that disputed Ginsburg’s findings. Peterson found that increases under Rhee amounted to roughly three scale score points per year, compared with around 1-1.5 points annually between 2000 and 2007 (the actual amounts varied by subject and grade).

Both articles were generally cautious in tone and in their conclusions about the actual causes of the testing trends. The technical details of the two reports – who’s “wrong” or “right” - are not important for this post (especially since more recent NAEP results have since been released). More interesting was how people reacted - and didn’t react - to the dueling analyses.

We Should Only Hold Schools Accountable For Outcomes They Can Control

Let’s say we were trying to evaluate a teacher’s performance for this academic year, and part of that evaluation would use students’ test scores (if you object to using test scores this way, put that aside for a moment). We checked the data and reached two conclusions. First, we found that her students made fantastic progress this year. Second, we also saw that the students’ scores were still quite a bit lower than their peers’ in the district. Which measure should we use to evaluate this teacher?

Would we consider judging her even partially based on the latter – students’ average scores? Of course not. Those students made huge progress, and the only reason their absolute performance levels are relatively low is because they were low at the beginning of the year. This teacher could not control the fact that she was assigned lower-scoring students. All she can do is make sure that they improve. That’s why no teacher evaluation system places any importance on students’ absolute performance, instead focusing on growth (and, of course, non-test measures). In fact, growth models control for absolute performance (prior year’s test scores) so it doesn't bias the results.

If we would never judge teachers based on absolute performance, why are we judging schools that way? Why does virtually every school/district rating system place some emphasis – often the primary emphasis – on absolute performance?

Three Important Distinctions In How We Talk About Test Scores

In education discussions and articles, people (myself included) often say “achievement” when referring to test scores, or “student learning” when talking about changes in those scores. These words reflect implicit judgments to some degree (e.g., that the test scores actually measure learning or achievement). Every once in a while, it’s useful to remind ourselves that scores from even the best student assessments are imperfect measures of learning. But this is so widely understood - certainly in the education policy world, and I would say among the public as well - that the euphemisms are generally tolerated.

And then there are a few common terms or phrases that, in my personal opinion, are not so harmless. I’d like to quickly discuss three of them (all of which I’ve talked about before). All three appear many times every day in newspapers, blogs, and regular discussions. To criticize their use may seem like semantic nitpicking to some people, but I would argue that these distinctions are substantively important and may not be so widely-acknowledged, especially among people who aren’t heavily engaged in education policy (e.g., average newspaper readers).

So, here they are, in no particular order.

Quality Control In Charter School Research

There's a fairly large body of research showing that charter schools vary widely in test-based performance relative to regular public schools, both by location as well as subgroup. Yet, you'll often hear people point out that the highest-quality evidence suggests otherwise (see here, here and here) - i.e., that there are a handful of studies using experimental methods (randomized controlled trials, or RCTs) and these analyses generally find stronger, more uniform positive charter impacts.

Sometimes, this argument is used to imply that the evidence, as a whole, clearly favors charters, and, perhaps by extension, that many of the rigorous non-experimental charter studies - those using sophisticated techniques to control for differences between students - would lead to different conclusions were they RCTs.*

Though these latter assertions are based on a valid point about the power of experimental studies (the few of which we have are often ignored in the debate over charters), they are dubiously overstated for a couple of reasons, discussed below. But a new report from the (indispensable) organization Mathematica addresses the issue head on, by directly comparing estimates of charter school effects that come from an experimental analysis with those from non-experimental analyses of the same group of schools.

The researchers find that there are differences in the results, but many are not statistically significant and those that are don't usually alter the conclusions. This is an important (and somewhat rare) study, one that does not, of course, settle the issue, but does provide some additional tentative support for the use of strong non-experimental charter research in policy decisions.

Growth And Consequences In New York City's School Rating System

In a New York Times article a couple of weeks ago, reporter Michael Winerip discusses New York City’s school report card grades, with a focus on an issue that I have raised many times – the role of absolute performance measures (i.e., how highly students scores) in these systems, versus that of growth measures (i.e., whether students are making progress).

Winerip uses the example of two schools – P.S. 30 and P.S. 179 – one of which (P.S. 30) received an A on this year’s report card, while the other (P.S. 179) received an F. These two schools have somewhat similar student populations, at least so far as can be determined using standard education variables, and their students are very roughly comparable in terms of absolute performance (e.g., proficiency rates). The basic reason why one received an A and the other an F is that P.S. 179 received a very low growth score, and growth is heavily weighted in the NYC grade system (representing 60 out of 100 points for elementary and middle schools).

I have argued previously that unadjusted absolute performance measures such as proficiency rates are inappropriate for test-based assessments of schools' effectiveness, given that they tell you almost nothing about the quality of instruction schools provide, and that growth measures are the better option, albeit one that also has its own issues (e.g., they are more unstable), and must be used responsibly. In this sense, the weighting of the NYC grading system is much more defensible than most of its counterparts across the nation, at least in my view.

But the system is also an example of how details matter – each school’s growth portion is calculated using an unconventional, somewhat questionable approach, one that is, as yet, difficult to treat with a whole lot of confidence.

There's No One Correct Way To Rate Schools

Education Week reports on the growth of websites that attempt to provide parents with help in choosing schools, including rating schools according to testing results. The most prominent of these sites is GreatSchools.org. Its test-based school ratings could not be more simplistic – they are essentially just percentile rankings of schools’ proficiency rates as compared to all other schools in their states (the site also provides warnings about the data, along with a bunch of non-testing information).

This is the kind of indicator that I have criticized when reviewing states’ school/district “grading systems." And it is indeed a poor measure, albeit one that is widely available and easy to understand. But it’s worth quickly discussing the fact that such criticism is conditional on how the ratings are employed - there is a difference between the use of testing data to rate schools for parents versus for high-stakes accountability purposes.

In other words, the utility and proper interpretation of data vary by context, and there's no one "correct way" to rate schools. The optimal design might differ depending on the purpose for which the ratings will be used. In fact, the reasons why a measure is problematic in one context might very well be a source of strength in another.

If Your Evidence Is Changes In Proficiency Rates, You Probably Don't Have Much Evidence

Education policymaking and debates are under constant threat from an improbable assailant: Short-term changes in cross-sectional proficiency rates.

The use of rate changes is still proliferating rapidly at all levels of our education system. These measures, which play an important role in the provisions of No Child Left Behind, are already prominent components of many states’ core accountability systems (e..g, California), while several others will be using some version of them in their new, high-stakes school/district “grading systems." New York State is awarding millions in competitive grants, with almost half the criteria based on rate changes. District consultants issue reports recommending widespread school closures and reconstitutions based on these measures. And, most recently, U.S. Secretary of Education Arne Duncan used proficiency rate increases as “preliminary evidence” supporting the School Improvement Grants program.

Meanwhile, on the public discourse front, district officials and other national leaders use rate changes to “prove” that their preferred reforms are working (or are needed), while their critics argue the opposite. Similarly, entire charter school sectors are judged, up or down, by whether their raw, unadjusted rates increase or decrease.

So, what’s the problem? In short, it’s that year-to-year changes in proficiency rates are not valid evidence of school or policy effects. These measures cannot do the job we’re having them do, even on a limited basis. This really has to stop.

The Charter School Authorization Theory

Anyone who wants to start a charter school must of course receive permission, and there are laws and policies governing how such permission is granted. In some states, multiple entities (mostly districts) serve as charter authorizers, whereas in others, there is only one or very few. For example, in California there are almost 300 entities that can authorize schools, almost all of them school districts. In contrast, in Arizona, a state board makes all the decisions.

The conventional wisdom among many charter advocates is that the performance of charter schools depends a great deal on the “quality” of authorization policies – how those who grant (or don’t renew) charters make their decisions. This is often the response when supporters are confronted with the fact that charter results are varied but tend to be, on average, no better or worse than those of regular public schools. They argue that some authorization policies are better than others, i.e., bad processes allow some poorly-designed schools start, while failing to close others.

This argument makes sense on the surface, but there seems to be scant evidence on whether and how authorization policies influence charter performance. From that perspective, the authorizer argument might seem a bit like tautology – i.e., there are bad schools because authorizers allow bad schools to open, and fail to close them. As I am not particularly well-versed in this area, I thought I would look into this a little bit.

Interpreting Achievement Gaps In New Jersey And Beyond

** Also posted here on "Valerie Strauss' Answer Sheet" in the Washington Post

A recent statement by the New Jersey Department of Education (NJDOE) attempts to provide an empirical justification for that state’s focus on the achievement gap – the difference in testing performance between subgroups, usually defined in terms of race or income.

Achievement gaps, which receive a great deal of public attention, are very useful in that they demonstrate the differences between student subgroups at any given point in time. This is significant, policy-relevant information, as it tells us something about the inequality of educational outcomes between the groups, which does not come through when looking at overall average scores.

Although paying attention to achievement gaps is an important priority, the NJDOE statement on the issue actually speaks directly to the fact, which is well-established and quite obvious, that one must exercise caution when interpreting these gaps, particularly over time, as measures of student performance.