Shanker Blog

Charter School Market Share And Performance

One of the (many) factors that might help explain -- or at least be associated with -- the wide variation in charter schools’ test-based impacts is market share. That is, the proportion of students that charters serve in a given state or district. There are a few reasons why market share might matter.

For example, charter schools compete for limited resources, including private donations and labor (teachers), and fewer competitors means more resources. In addition, there are a handful of models that seem to get fairly consistent results no matter where they operate, and authorizers who are selective and only allow “proven” operators to open up shop might increase quality (at the expense of quantity). There may be a benefit to very slow, selective expansion (and smaller market share is a symptom of that deliberate approach).

One way to get a sense of whether market share might matter is simply to check the association between measured charter performance and coverage. It might therefore be interesting, albeit exceedingly simple, to use the recently-released CREDO analysis, which provides state-level estimates based on a common analytical approach (though different tests, etc.), for this purpose.

Richard Parrish And The March On Washington For Jobs And Freedom

Our guest author today is William P. Jones, history professor at the University of Wisconsin, Madison, and author of The March on Washington:  Jobs, Freedom and the Forgotten History of Civil Rights (W.W. Norton & Co., 2013)

If Richard Parrish had his way, the March on Washington for Jobs and Freedom would have occurred in 1941 rather than 1963.  As President of the Federation of Colored College Students in New York City, the 25-year old student was a key organizer of the mass demonstration that union leader A. Philip Randolph called to protest discrimination in the armed forces and the defense industries during the Second World War.  He was furious, therefore, when Randolph cancelled the march in exchange for an executive order, issued by President Franklin D. Roosevelt, prohibiting defense contractors from discriminating against workers on the basis of their race, color religion, or national origin.  Parrish agreed that this was a major victory, but pointed out that it would expire when the war ended and do nothing to address discrimination in the armed forces.  Accusing Randolph of acting without consulting the students and other groups that supported the mobilization, he insisted that the March on Washington be rescheduled immediately.

Randolph refused—accusing Parrish and other young militants of being “more interested in the drama and pyrotechnics of the march than the basic and main issues of putting Negroes to work”—but the disagreement did not prevent the two black radicals from working closely together to build a powerful alliance between the civil rights and labor movements in the postwar decades.  After completing his bachelor’s degree in 1947, Parrish worked as a teacher and union leader until his retirement in 1976.  He also worked closely with Randolph to open jobs and leadership positions for black workers in organized labor.  When Randolph decided to reorganize the March on Washington in 1963, Dick Parrish was one of the first people he turned to for support.

DC School Growth Scores And Poverty

As noted in a nice little post over at Greater Greater Washington's education blog, the District of Columbia Office of the State Superintendent of Education (OSSE) recently started releasing growth model scores for DC’s charter and regular public schools. These models, in a nutshell, assess schools by following their students over time and gauging their testing progress relative to similar students (they can also be used for individual teachers, but DCPS uses a different model in its teacher evaluations).

In my opinion, producing these estimates and making them available publicly is a good idea, and definitely preferable to the district’s previous reliance on changes in proficiency, which are truly awful measures (see here for more on this). It’s also, however, important to note that the model chosen by OSSE – a “median growth percentile," or MGP model, produces estimates that have been shown to be at least somewhat more heavily associated with student characteristics than other types of models, such as value-added models proper. This does not necessarily mean the growth percentile models are “inaccurate” – there are good reasons, such as resources and more difficulty with teacher recruitment/retention, to believe that schools serving poorer students might be less effective, on average, and it’s tough to separate “real” effects from bias in the models.

That said, let’s take a quick look at this relationship using the DC MGP scores from 2011, with poverty data from the National Center for Education Statistics.

Data-Driven Instruction Can't Work If Instructors Don't Use The Data

In education today, data, particularly testing data, are everywhere. One of many potentially valuable uses of these data is helping teachers improve instruction – e.g., identifying students’ strengths and weaknesses, etc. Of course, this positive impact depends on the quality of the data and how it is presented to educators, among other factors. But there’s an even more basic requirement – teachers actually have to use it.

In an article published in the latest issue of the journal Education Finance and Policy, economist John Tyler takes a thorough look at teachers’ use of an online data system in a mid-sized urban district between 2008 and 2010. A few years prior, this district invested heavily in benchmark formative assessments (four per year) for students in grades 3-8, and an online “dashboard” system to go along with them. The assessments’ results are fed into the system in a timely manner. The basic idea is to give these teachers a continual stream of information, past and present, about their students’ performance.

Tyler uses weblogs from the district, as well as focus groups with teachers, to examine the extent and nature of teachers’ data usage (as well as a few other things, such as the relationship between usage and value-added). What he finds is not particularly heartening. In short, teachers didn’t really use the data.

It's Test Score Season, But Some States Don't Release Test Scores

** Reprinted here in the Washington Post

We’ve entered the time of year during which states and districts release their testing results. It’s fair to say that the two districts that get the most attention for their results are New York City and the District of Columbia Public Schools (DCPS), due in no small part to the fact that both enacted significant, high-profile policy changes over the past 5-10 years.

The manner in which both districts present annual test results is often misleading. Many of the issues, such as misinterpreting changes in proficiency rates as “test score growth” and chalking up all “gains” to recent policy changes, are quite common across the nation. These two districts are just among the more aggressive in doing so. That said, however, there’s one big difference between the test results they put out every year, and although I’ve noted it a few times before, I’d like to point it out once more: Unlike New York City/State, DCPS does not actually release test scores.

That’s right – despite the massive national attention to their “test scores," DCPS – or, specifically, the Office of the State Superintendent for Education (OSSE) – hasn’t released a single test score in many years. Not one.

The Ever-Changing NAEP Sample

The results of the latest National Assessment of Educational Progress long term trend tests (NAEP-LTT) were released last week. The data compare the reading and math scores of 9-, 13- and 17-year olds at various points since the early 1970s. This is an important way to monitor how these age cohorts’ performance changes over the long term.

Overall, there is ongoing improvement in scores among 9- and 13-year olds, in reading and especially math, though the trend is inconsistent and increases are somewhat slow in recent years. The scores for 17-year olds, in contrast, are relatively flat.

These data, of course, are cross-sectional – i.e., they don’t follow students over time, but rather compare children in the three age groups with their predecessors from previous years. This means that changes in average scores might be driven by differences, observable or unobservable, between cohorts. One of the simple graphs in this report, which doesn't present a single test score, illustrates that rather vividly.

A Few Points About The New CREDO Charter School Analysis

A new report from CREDO on charter schools’ test-based performance received a great deal of attention, and rightfully so - it includes 27 states, which together serve 95 percent of the nation's charter students.

The analysis as a whole, like its predecessor, is a great contribution. Its sheer scope, as well as a few specific parts (examination of trends), are new and important. And most of the findings serve to reaffirm the core conclusions of the existing research on charters' estimated test-based effects. Such an interpretation may not be particularly satisfying to charter supporters and opponents looking for new ammunition, but the fact that this national analysis will not settle anything in the contentious debate about charter schools once again suggests the need to start asking a different set of questions.

Along these lines, as well as others, there are a few points worth discussing quickly. 

No Presentation Without Representation

I tend to comment on newly-released teacher surveys, primarily because I think the surveys are important and interesting, but also because teachers' opinions are sometimes misrepresented in our debate about education reform. So, last year, I wrote about a report by the advocacy organization Teach Plus, in which they presented results from a survey focused on identifying differences in attitudes by teacher experience (an important topic). One of my major comments was that the survey was "non-scientific" – it was voluntary, and distributed via social media, e-mail, etc. This means that the results cannot be used to draw strong conclusions about the population of teachers as a whole, since those who responded might be different from those that did not.

I also noted that, even if the sample was not representative, this did not preclude finding useful information in the results. That is, my primary criticism was that the authors did not even mention the issue, or make an effort to compare the characteristics of their survey respondents with those of teachers in general (which can give a sense of the differences between the sample and the population).

Well, they have just issued a new report, which also presents the results of a teacher survey, this time focused on teachers’ attitudes toward the evaluation system used in Memphis, Tennessee (called the “Teacher Effectiveness Measure," or TEM). In this case, not only do they raise the issue of representativeness, but they also present a little bit of data comparing their respondents to the population (i.e., all Memphis teachers who were evaluated under TEM).

What Some Call Delay Is At Times Just Good Policy Making

U.S. Secretary of Education Arne Duncan recently announced that states will be given the option to postpone using the results of their new teacher evaluations for high-stakes decisions during the phase-in of the new Common Core-aligned assessments. The reaction from some advocates was swift condemnation – calling the decision little more than a “delay” and a “victory for the status quo."

We hear these kinds of arguments frequently in education. The idea is that change must be as rapid as possible, because “kids can’t wait." I can understand and appreciate the urgency underlying these sentiments. Policy change in education (as in other arenas) can sometimes be painfully slow, and what seem likes small roadblocks can turn out to be massive, permanent obstacles.

I will not repeat my views regarding the substance of Secretary Duncan’s decision – see this op-ed by Morgan Polikoff and myself. I would, however, like to make one very quick point about these “we need change right now because students can’t wait” arguments: Sometimes, what is called “delay” is actually better described as good policy making, and kids can wait for good policy making.

What Should The Results Of New Teacher Evaluations Look Like?

In a previous post, I discussed the initial results from new teacher evaluations in several states, and the fact that states with implausibly large proportions of teachers in the higher categories face a difficult situation – achieving greater differentiation while improving the quality and legitimacy of their systems.

I also expressed concern that pre-existing beliefs about the "proper" distribution of teacher ratings -- in particular, how many teachers should receive the lowest ratings -- might inappropriately influence the process of adjusting the systems based on the first round of results. In other words, there is a risk that states and districts will change their systems in a crude manner that lowers ratings simply for the sake of lowering ratings.

Such concerns of course imply a more general question: How should we assess the results of new evaluation systems? That’s a complicated issue, and these are largely uncharted waters. Nevertheless, I'd like to offer a few thoughts as states and districts move forward.