In 1966, James S. Coleman and Associates wrote the report, “Equality of Educational Opportunity,” for the U.S. Department of Health Education and Welfare, as required by the Civil Rights Act of 1964. The report was commissioned to examine the causes of differences in educational outcomes experienced by minority group students, particularly black children, compared to whites, the majority group. The report’s sponsors expected that access to resources would explain the differences.
Coleman found, however, that another factor was far more important. “The first finding is that the schools are remarkably similar in the way they relate to the achievement of their pupils when the socioeconomic background of the students is taken into account. …. When these factors are statistically controlled, however, it appears that differences between schools account for only a small fraction of differences in pupil achievement.”Coleman’s report has led to the notion that factors like parents’ education and incomes determine student performance.
But Coleman conducted further research. In 1982, he published “Cognitive Outcomes in Public and Private Schools.” Coleman found “strong evidence that there is, in vocabulary and mathematics, higher achievement for students in Catholic and private schools than in public; the results are less consistent in reading.”In large part, Coleman attributed this to his finding that “private schools provide a safer, more disciplined, and more ordered environment than do public schools.”
Coleman’s study is controversial. Critics have argued that his findings could be attributed to other factors, particularly the likelihood that self-selection may be an unmeasured but important factor in these schools’ outperformance.
In New York, as in other places, students in central cities are less likely to pass the state’s standardized tests than those in other, more affluent, locations. The long-term problem of high failure rates in these schools has prompted reform efforts, such as the establishment of charter schools, to provide alternatives to schools operated by public school districts. Others have called for state takeovers of underperforming school systems.
What does the data show? How strongly does socioeconomic status influence performance in school districts in New York? Do some districts outperform or underperform expectations?
Upstate central city student performance
Few students in upstate central city school districts do well on New York’s standardized examinations. Fewer than one in five students in these cities passed the state’s English Language Arts and mathematics exams given between third and eighth grades in 2016 and 2018. Utica was the only large upstate city school district in which more than 20 percent of grade 3-8 students passed the state’s English and mathematics exams during that period. In Rochester, only 9 percent passed, while in Syracuse, 13 percent passed. In some selected nearby suburban districts, the picture was quite different—in most cases, more than 60 percent of students passed the state exams.
Predictors of student performance
Economic disadvantage: New York defines economically disadvantaged students and family as those who take part in assistance programs such as the free or reduced-price lunch programs and food stamps. When two years of data were combined to reduce random variation associated with small sample sizes, 72 percent of the variation in student performance was associated with the percentage of students defined as economically distressed. The chart below shows the strong relationship between the percentage of school district students passing New York’s Grades 3-8 ELA and math exams and the percentage of disadvantaged students in school districts.
Education: We cannot directly measure the educational levels of parents in the school districts studied, but census data allows us to examine the relationship between the percentage of adult district residents with college degrees and student performance. The percentage of college graduates is associated with 48 percent of the variation in student performance in school districts. The chart below shows the relationship.
Although economic disadvantage proved to be more closely related to student test outcomes at the school district level, the portion of adults in a district with at least a four-year college degree impacted the result by a small amount. Consequently, a linear model that includes both variables increased the percentage of variation explained by the model to 74 percent—nearly three quarters.
Although the relationship between student performance and economic status and district educational levels is very strong, about one quarter of the differing performance of school districts is not explained. One factor could be the instructional efficacy of schools. This possible explanation is inferential, however. Other unexamined factors could be in play as well.
Characteristics of school district populations
In upstate central cities, high concentrations of disadvantaged students combine with adult populations with relatively low educational levels. More than 85 percent of students in Rochester, Syracuse, Schenectady and Utica were economically disadvantaged in recent years. Only about one quarter of adults were college graduates.
The characteristics of student bodies in large communities surrounding upstate cities are quite varied. In some communities less than 20 percent of students were economically disadvantaged. In almost all these communities, 50 percent or more of the students passed the state examination. In a few cases, more than 70 percent passed. In other communities outside upstate central cities, more than 50 percent of students were economically disadvantaged. In many cases, less than 40 percent of students passed the state’s ELA and mathematics exams.
But in only three cases (Lackawanna, Solvay and Watervliet), the percentage of economically disadvantaged students was as high as it was in the central cities. In these communities, as in upstate central cities, more than 70 percent of students failed the state exams.
As in the case of economic disadvantage, in most cases, cities had lower percentages of people with at least a four-year college degree than did most residents of communities outside them. But the difference between the educational levels of city residents and residents of other communities was less clear cut. In fact, about 10 percent of communities outside central cities had lower percentages of college graduates than did central city residents. And in general, students in school districts in those communities performed better on state tests than central city residents. Overall, the relationship was not as strong as the relationship with economic disadvantage.
Which school districts outperformed and underperformed?
Calls for reform of central city school districts, such as state school district takeovers and the charter school movement, rest on the notion that the poor performance of many students attending urban schools is at least in part caused by poor school management and instruction. How well do students at schools in central city school districts perform given the percentage of economically disadvantaged students and people without college degrees within them?
Overall, economic disadvantage and adult education levels are very important predictors of school district performance. But there were significant differences in district performance after controlling for socioeconomic factors. In Utica, student performance exceeded expected performance by 7 percent to 24 percent passing versus 17 percent predicted. Performance in Buffalo was close to model predictions—19 percent passed versus 22 percent predicted. Schenectady’s performance was also close to model predictions—17 percent passed, compared with the prediction of 20 percent. The Albany school district fell short of expectations by the largest amount. Had Albany students performed as expected, nearly one-third (31 percent) would have passed. Only 18 percent did. In Syracuse, 21 percent were predicted to pass but only 13 percent did. In Rochester, 17 percent were predicted to pass. Only 9 percent did.
The following tables show the 15 districts within the counties where student performance exceeded expectations and lagged expectations to the greatest degree.
The performance of school districts outside central cities was quite varied. Among the 15 school districts where student performance was the lowest compared to the model’s prediction, 12 of 15 were outside central cities. Among those that exceeded expectations, all but one was outside the central cities.
Three upstate cities—Albany, Rochester and Syracuse—were in the group of poor performers. Among the districts where students performed the best compared with the model’s prediction, only one—Utica—was a city school district.
Coleman’s finding continues to be true. Socioeconomic factors explain most of the differences in performance between school districts with high percentages of economically disadvantaged students and small percentages of adult college graduates, and those with few disadvantaged students and high levels of adult college graduates. But even after controlling for these factors, there are differences in performance between school districts. Some are relatively large.
This data is not a causal analysis. We cannot draw conclusions as to the causes of differences in student performance in school districts compared with model predictions. Other unmeasured variables might explain the differences in performance. However, residents of school districts where performance is lower than predicted by the model might question whether their school district is performing its job effectively.
For residents of three large city school districts—Albany, Rochester and Syracuse—this question is particularly important because the percentage of students passing the state exams is lower than in almost all other school districts, and because controlling for known factors associated with poor performance, they did less well than expected.
John Bacheller, former head of the policy and research division of Empire State Development, is an author of Policy by Numbers, a blog that focuses on data and policy at the state level, with a focus on Upstate New York.