Experimental new york city charter school

WWC review of this study. Charter school performance in New York City. At least one statistically significant positive finding. Rating: Meets WWC standards with reservations. Students who attended a "feeder" traditional public school SYSY Grades ; 41, students 0.

Sample Characteristics Characteristics of study sample as reported by study author. The sample on which the analysis was conducted. The timing of the post-intervention outcome measure. The number of students included in the analysis. The mean score of students in the intervention group.

The mean score of students in the comparison group. The name and version of the document used to guide the review of the study. The version of the WWC design standards used to guide the review of the study. Study findings for this report.

Your export should download shortly as a zip archive. This might be something to which regular public schools should pay more attention, as the importance of a safe, orderly learning environment is well-established see here.

Needless to say, regular public schools would probably approach the details of these policies in a different way. The strongest evidence, however, is that for extended time and perhaps tutoring as well as the funding that enables these practices. Nevertheless, these results showing which policies and practices are associated with performance at the level of individual schools are not necessarily a complete picture.

There will always be a few high-flying chains and schools that do well, but there is some pretty solid evidence that groups of charters, run by different organizations using a variety of different approaches, achieve solid results, on average, serving the same population.

This seems to be the case, for example, in New York City and Boston. There is also variation in relative charter performance between states that might be instructive.

Please bring New Orleans Public Schools into your discussion as that is a large scale effort to provide maximal choice to all parents to choose between charter and non-charter. That is one heck of a large scale experiment. I am particularly interested in your analysis of the results as detailed and discussed here:. The issue of money is important but to discuss it you need to point out that what public school districts have done when given more money is simply hire more teachers to reduce class size rather than increase instructional time.

If you conclude that public schools need more money to emulate charter schools you need to examine why the vast disparities in per pupil expenditures per state have essentially zero correlation with performance as measured by the NAEP. Class size has zero correlation with NAEP performance as well, even when broken down by race and economic status.

In short, more money to traditional public schools won't matter because it will be used to hire more teachers giving unions more members, requiring more overpaid administrators, more school bonds to enrich the local contractors, but doing absolutely zero for the kids. I'll be discussing a few whole districts in a subsequent post. I would include New Orleans, but I can't do that without a high-quality analysis that doesn't rely on changes in cross-sectional proficiency rates.

If you know where to find it, please post post the link. I am curious how infrastructure is calculated into these numbers. The amount that "local school districts received in revenue" would not, and I'm curious whether this is a fair apples-to-apples comparison. Alas, the aggregate test scores of charter and traditional public schools are not directly comparable.

Differences in the performance of charter and traditional public school students might reflect differences in the quality of schooling, student differences, or both.

Measuring the effect of attending a charter school on student performance requires rigorous statistical analysis. Seven studies estimate the causal effect of attending a New York City charter school on student performance—i. Five use a randomized field trial RFT design. This design takes advantage of the fact that oversubscribed charter schools are required to use a random lottery to offer students the opportunity to enroll. The researchers compare the later outcomes of students who were randomly offered a charter school seat with those of students who also applied but were randomly denied the opportunity to enroll.

Because winning the charter lottery is not related to any other student characteristic, any differences in the later outcomes of lottery winners and losers are either random or are directly due to the opportunity to enroll in a charter school. Because the RFT design accounts for all pretreatment differences between the treatment and control groups, it is widely considered to be the gold standard for research designs in the social sciences.

From a policy perspective, RFT studies produce limited information because their results strictly apply only to those represented in the lottery pools. Thus, if students who apply to charter schools are systematically different from those who do not apply to them, then the estimates from an RFT study likely would not apply to non-applicants.

Unlike the RFT design, matching allows the researcher to include all charter schools, regardless of whether they are oversubscribed or participate in the evaluation.

Matching requires stronger assumptions than RFT to produce estimates of the causal impact of attending a charter school. Matching studies match students only according to characteristics that are observed in the data set, even though students attending charters may differ from those attending traditional public schools in unobserved ways, such as the level of parental involvement.

Figures 1—2 plot the main estimates for the impact of attending a New York City charter school on student math and ELA scores, as reported in the seven studies. Figures 1—2 show that the estimated effect of attending a New York City charter school is positive in all but one case; 23 of 28 estimates are significantly positive. The magnitude of the positive effect in math is substantial, especially given that the estimate covers only a year of charter school attendance.

The smallest estimate suggests that four years of attending a charter school would lead to a 0. The estimates in math are also quite stable over time and across studies. Meanwhile, the estimated effects on student performance in ELA are more modest and less consistent.

However, the evidence suggests a significant positive effect in ELA that would be meaningful after accumulating over time. As noted, RFT and matching studies have strengths and weaknesses. A fourth uses information from a more expansive group of 29 schools.

Though Hoxby and Murarka remain highly influential in the policy discussion, their results are quite dated. In , only 47 charter schools operated in New York, compared with today. Because of this big expansion, the effect of attending a charter school may have changed over time. If, say, the city successfully closed ineffective charters and encouraged the opening of only highly effective ones, the impact of attending a charter school would tend to increase over time.

On the other hand, the quality of charter schools might diminish as the sector expands and digs deeper into the labor pool for administrators and teachers, or if the additional students who enroll are, for some reason, less responsive to charter schooling than the average student who enrolled previously.

Compare matching and RFT still further. The fact that the RFT studies often include only a small minority of charter schools likely explains why they tend to produce substantially larger effect size. Meanwhile, each matching estimate produces a statistically significant result; but four of 10 RFT estimates are statistically insignificant. The reason: the RFT estimates are measured imprecisely, partly because they utilize far fewer schools and students than do the matching estimates.

Are the matching estimates reasonable? As of , the estimated impact of attending a charter school using RFT 0. The fact that these approaches—applied at about the same time, using nearly the same sample of schools—produced relatively similar results suggests that matching is capable of producing causal estimates for the effect of attending a New York City charter school.

Indeed, the matching estimates have been relatively consistent over time, especially in math. The empirical research described above strongly suggests that, on average, students attending a charter school score higher in math and ELA than they would have had they attended a traditional public school. However, charters are not monolithic: they are separate, independently operated, schools.

The type of schooling offered by charters varies substantially in New York, too. Charters also have access to varying levels of financial resources, from public and private sources. Thus, while charter schools might be effective on average, not all New York City charter schools are equally effective. The potential for variation in the effectiveness of charter schools is visible in Figures 1—2. As discussed, the RFT studies tend to produce larger estimated effects than do matching studies.

Some of that difference could result from differences in research methodologies. But it could also be due to the fact that the RFT studies focus on a set of highly effective schools, which, by definition, implies variation in charter school quality. Dobbie and Fryer is the only RFT study to produce an estimated charter school effect in math worse than those produced by matching estimates in a given year. It is also the only RFT study since Hoxby and Murarka to include a broad set of charter schools rather than only those in a single network.

CREDO , which disaggregates results by school, finds that It finds similar results for ELA. Among networks operating at least four charters in New York, the effect of attending a network school ranges from —0. Keep in mind that the estimated charter school effect can be considered to be causal, but the associations between effectiveness and observed characteristics of the school cannot be considered to be causal.

These studies can therefore identify characteristics that tend to be found in the more successful schools, but they cannot prove that the same positive results would occur if adopted in other schools.

CREDO finds that charter schools operated by charter management organizations CMOs —organizations that manage networks of several schools under a common leadership and philosophy—tend to have substantially larger positive effects on their students than do charters operated by non-CMOs. For charter schools operated by non-CMOs, the study still finds a significantly positive effect in math but an insignificant effect in ELA.

The RFT studies that utilize several different charter schools also attempt to find correlations between characteristics and measured school quality. Hoxby and Murarka , for example, find that longer school years are associated with superior quality. But they do not find other characteristics that are robustly associated with measured school effectiveness.

Dobbie and Fryer present the most thorough analysis of the underlying factors associated with charter school quality to date. They found that an index of five characteristics—frequent teacher feedback, data-guided instruction, tutoring, high standards for students, and additional instruction time—explained nearly half the variation in measured charter school quality.

Differences in financial resources could influence the effectiveness of charters, relative to traditional public schools and other charters. Here, too, the empirical research may be dated. In , the tuition formula for state funding to charter schools was frozen, with some allowances for supplemental aid in later years. Nevertheless, some aspects of the academic literature remain pertinent.

Taxpayers fund New York City charter schools in several ways. The largest source of public funding— intended to cover operating costs—comes from a per-pupil allocation that is set by the state but paid by the school district through a pass-through fund. Charters can receive allocations for other expenses, though these costs tend to be minor. About two-thirds of charter schools also operate rent-free in a traditional public school building,20 while charters that do not operate in a traditional public school building often receive other in-kind support, such as food service and transportation.

The difference in total public funding between charter and traditional public schools in New York is substantial, depending on whether the school is located in a traditional public school building. Baker and Ferris observe that proportionally fewer charter school students fall into each of these categories than do students in traditional public schools.

Still, the difference in the proportion of charter and traditional public school students classified as ELL has dropped from 14 percentage points at the time of the Baker and Ferris study, to only about 7 percentage points today New York City Charter School Center Thus, the cost-adjusted funding difference found by Baker and Ferris is likely—I am not aware of a recent update to this calculation—to be less important today, even as longitudinal results from matching studies suggest that average charter school effects have remained relatively consistent over time.

Charter schools also receive resources from nonpublic sources, especially private foundations. As such, philanthropic funding does not appear to be a primary driver of the generally positive effects of charter schools relative to traditional public schools in New York. The widespread perception that charter schools receive substantial nonpublic resources to supplement their activities appears to be driven by outliers. Using data from IRS forms, Baker and Ferris similarly find that the amount of additional resources from private sources varies dramatically by charter school.

Further, the empirical evidence offers little guide to whether variation in the amount of nonpublic resources available to a charter school has a meaningful impact on performance. For example, Baker and Ferris find no significant relationship between charter school spending including public and private sources and test scores—though this analysis uses aggregate test scores adjusted for student characteristics as a measure of charter school quality, which is not a design that could plausibly lead to a causal estimate of charter school effects.

There is a common claim, supported by numerous anecdotes reported in the media, that a main reason for the higher test scores in charter schools comes from their systematic removal of their most difficult to educate students. It is certainly plausible that there have been cases when charter schools as well as traditional public schools have not appropriately handled situations with individual students.

However, the academic research literature strongly suggests that charter schools have not systematically manipulated their enrollments in this manner. Overall, charter school students are as likely, or less likely, to leave their school for another school in the city—or to leave the school district entirely—as are students in traditional public schools. IBO compares the mobility patterns of students who, in the fall of , enrolled in a charter school or in the nearest traditional public school.

Using student-level data from grades 3—8 from to , Winters, Clayton, and Carpenter find that the overall yearly attrition between the sectors was very similar but that attrition from charters was significantly lower than attrition from traditional public schools after accounting for student characteristics. Winters, Clayton, and Carpenter evaluate whether charter schools systematically remove students who are not performing well on standardized tests.

They use student-level data for —12 to compare the attrition patterns of students in New York City charter and traditional public schools overall and by test scores. They find that low-performing students are much more likely to exit their school than are higher-performing students, regardless of the sector. Because Winters, Clayton, and Carpenter find that attending a charter school reduced the likelihood that a student exited his or her school, they ultimately find that low-performing students in New York City are significantly less likely to exit charter schools than traditional public schools.

Figure 4 illustrates the proportion of students in each sector in a variety of categories, as of — In addition, the proportion of students with disabilities and those who are ELL is higher in traditional public schools than in charter schools. UFT and Baker and Ferris observe that the proportion of students in charter and traditional public schools who are eligible for free lunch a measure of extreme poverty —rather than simply reduced-priced lunch—is substantially larger in traditional public schools than in charter schools.

According to the index, students who attend charter schools are more disadvantaged, on average, than those who attend traditional public schools.