NJ Charter Data Round-up

Posted on January 15, 2012



Note: I will be making updates to this post in the coming days/weeks.

As we once again begin discussing & debating the appropriate role for Charter schools in New Jersey’s education reform “mix,” here’s a round-up on the New Jersey charter school numbers, in terms of demographic comparisons to all other public and charter schools in the same ‘city’ and proficiency rates (across all grades) compared to all others in the same ‘city.’

Key Findings:

Many NJ charter schools, especially those most often touted in the media as great success stories, continue to serve student populations that differ dramatically from populations of surrounding schools in the same city (see note *). These charters differ in terms of percentages of children who qualify for free lunch, percent classified as having disabilities, or percent with limited English language proficiency.

On average, given their demographics, NJ charter schools continue to have proficiency rates around where one would expect. Demographically advantaged charter schools have higher average proficiency than other schools around them. Demographically disadvantaged charter schools have lower average proficiency rates than others around them. Not tricky/heavy statistics here. Just a comparison of relative proficiency and relative demography.

When one estimates what I would call a “descriptive regression” model characterizing the differences in proficiency rates across district and charter schools in the same cities, one finds that compared against schools of similar demography, and on the same grade level and subject area tests, the charter proficiency rates, on average are no different than their traditional public school counterparts. In this particular regression model, charters did have higher proficiency in Science (charter x science interaction). More descriptive stuff to come when I get a chance. Not sure when that will be.

Note: The model includes a fixed effect for CITY location for each traditional public and charter school, such that each charter is compared against other schools in the same CITY.

But to be absolutely clear, this particular analysis misses the point entirely in two ways. First, it is merely descriptive of the average proficiency rates of charter and non-charter schools across tests, subjects & grades. It is not a test, by any means of comparative effectiveness of schools. Second, as I explain below,  comparisons of charterness vs. non-charterness are not particularly helpful for informing policy.

Policy Perspectives:

Issue 1: The relevant policy question is not whether charters on average perform better than traditional public schools on average and therefore whether we should simply replace more traditional public schools with more charter schools. The relevant questions are “what works? For whom? And under what circumstances?” Charter schools, traditional public schools and private schools all vary widely in quality and in their ability to serve different populations well. Some schools of each organizational type do well (at least for some kids) while others, quite bluntly, suck, no matter who they try to serve. Further, I’ve written previously about these arguments that charters or private schools “do more (than traditional public schools) with less money.” However, rarely are those money comparisons rigorously or accurately conducted. Often times the assertion of “more with less” isn’t backed by any analysis at all of the “with less” part of that equation (and sometimes not the “more” part either). But these are the types of issues we need to be exploring, including specifically what are the resource implications of the models being offered by those “successful” schools, be they charters, traditional public schools, or other alternatives.

Issue 2: It may not be that the only appropriate role for charters in the mix is for them to all try to serve the most representative population – a population mirroring that of the city as a whole or their zip codes. But, for those that don’t – for those that serve a niche – we need to recognize them as such, and need to monitor the extent that their demographic selection may have adverse effects on the system as a whole. We also need to recognize that their demographic difference may play a significant role in explaining either their apparent success, or apparent failure. We should recognize, for example, that schools like Robert Treat or North Star Academy may be showing high outcomes but are doing so largely as a function of serving very different populations than others around them. Further, there may be nothing wrong with that if they are truly doing well by the kids they serve. That may just be their appropriate niche. We just can’t pretend that this model of success can be spread city wide or statewide. And, it may be inappropriate to encourage these schools to serve more representative populations. Perhaps they should stick with what they are good at. As a result, it may be more reasonable for charters like North Star or Robert Treat to establish similar niche schools in other New Jersey cities rather than pretending they can expand dramatically in the same cities and still maintain their current level of achievements.

Issue 3: We also need to remember that NJ’s large urban districts themselves operate a wide variety of schools and segment their own student populations at the secondary level through such options as magnet schools. Charters aren’t the only segmenting force. Charters including those that are demographically representative and those that aren’t have simply become a part of that mix. And we need to recognize where each fits into that mix and consider very seriously the implications for the system as a whole.

Issue 4: Finally, as I so often point out policy perspectives and parental interests may differ sharply when it comes to “elite” charter schools. From a policy perspective, elite charter schools provide limited implications for scalability (and for charters as a broad-based policy “solution”) because their benefits are derived from concentrating motivated, often less poor (non-disabled & fluent English speaking), self-selected students with the staying power to endure “no excuses” charter models.  From a parental perspective, this public policy limitation often provides the strongest personal incentive to pursue a specific school for one’s own children. Again, it comes down to that “other” strongest in-school factor driving student success – peer effect. Peer effect is a limitation (confounding factor) in public policy (unless we can find clever strategies to optimize peer distribution). But peer effect may be a legitimate quality indicator for parental choices.

Data notes:

As I’ve noted numerous times on this blog, my goal here is to access and report on publicly available data from widely recognized and/or official government sources. These are the most recent data of that type available. And here are the sources:

District and Charter School Location Information: http://nces.ed.gov/ccd/bat (2009-2010)

District special education classification rates: http://www.nj.gov/education/specialed/data/ADR/2010/classification/distclassification.xls

School level % LEP/ELL & % Free Lunch: http://www.nj.gov/education/data/enr/enr11/enr.zip

Combined Demographic Data: Charter Demographics 2011

*Note: City and Zip Code averages constructed by summing all students, all free lunch students, all LEP/ELL students for all schools in each “city” and in each “zip  code” as identified by school location based on the NCES Common Core of Data and then dividing city-wide (or zip code wide) % LEP/ELL and % Free Lunch by city (or zip) wide total enrollment for both traditional public schools and charters (that is, charters are part of the city-wide, or zip-wide average).  For special education, to estimate the citywide (and zip) average for schools, the district overall rate was applied to district schools.  This would not be an appropriate way to compare individual city schools to charter schools, since special education populations are not evenly distributed across city schools (or throughout a zip code), but is a more reasonable approach for generating the citywide aggregates. Again, charters are included in citywide and in zip-code level averages.