Responding to student achievement data published by Stanford Education Data Archive (SEDA)1, a New York Times article of April 29, 20162 addresses the question, “Why racial achievement gaps were so pronounced in affluent school districts is a puzzling question raised by the data.” In particular, the article looks at the Chapel Hill-Carrboro school district. In an interview, the school district presents the following statement. “The wealthier students tend to come from families where, “let’s face it, both the parents are Ph.D.s, and that kid, no matter what happens in the school, is pressured from kindergarten to succeed” … “So even though our minority students are outscoring minority students in other districts near us, there is still a bigger gap here because of that.” The context of the article is the online Educational Opportunity Project at Stanford University3. The academic parent of the Stanford site is the Stanford Center for Education Policy Analysis (CEPA)4.
The school district’s statement appears to be composed of multiple claims:
There is, though, a substantial problem with the somewhat oblique question to which the school district is responding, and accordingly with the response itself. Whatever the origin, I pose here an alternative question which I will also address in this report: Given that there are school districts where White students perform at very high levels, to what extent do minority students participate in that excellence?
This report will carry out an investigation of these claims in the context of the North Carolina Department of Public Instruction (NCDPI) data made available publicly in their disaggregated data files5. My analysis will be different from that of CEPA in that I will be looking at the Grade Level Proficiency (GLP) measure reported, as a percentage, by DPI. In grades 3 through 8, this is determined from standardized grade-appropriate examinations, including mathematics and language arts, and additionally science for grade 8. The DPI “Green Books”6 describe test results. The Green Books provide detailed, statewide data for some grades and some subjects as score-frequency tables for test results. From these, as shown in other reports, it is evident that in some grades, GLP is achieved by reaching the median state-wide test score.
In regards to the score-frequency data, those tests are not graded “on the curve.” Rather, they are carefully designed according to the discipline known as Item Response Methodology. These tests have a series of four steps or threshholds, i.e., five divisions, that require the demonstration of specific abilities, and they are vetted prior to statewide use.78 This is discussed in the 2015 NCDPI report on alignment characteristics of assessments.9 To score into the third or higher division, i.e., being at least GLP, students would have to demonstrate capabilities beyond what are required of those who remain in the first or second division. This changed somewhat in 2019, when Levels 1 and 2 (the lowest achievement clasifications) for mathematics were collapsed into a single level.10
Looking at a map of North Carolina, the Local Education Agencies (LEA) nearby to Chapel Hill-Carrboro include Orange County, Chatham County, Alamance County, Caswell County, Person County, and Durham County. Wake County is separated from Orange County but is part of the Chapel Hill-Durham-Wake metropolitan area. This report’s comparisons will treat first the nearby districts, 010 Alamance-Burlington, 170 Caswell County, 190 Chatham County, 320 Durham, 680 Orange County, 681 Chapel Hill-Carrboro City, 730 Person County, and then the more economically comparable districts,111 Asheville City, 190 Chatham County, 290 Davidson County, 320 Durham, 600 Charlotte-Mecklenburg, 650 New Hanover County, 681 Chapel Hill-Carrboro City, 920 Wake County. Appendix A provides a brief characterization of the nearby and peer LEAs.
The NYT article makes reference to minority students. Instead of “race,” DPI uses the term “subgroup,” being composed of American Indian, Asian, Black, Hispanic, Multiracial, Pacific Islander, and White.11 Due to the small numbers of some of the subgroups and consequent difficulties in comparability, this report will consider only Black, Hispanic, and White students. Other reports in this series will also address Asian students.
I do not include charter schools, which warrant a separate treatment since over the years they vary in number of students served and grades offered, making longitudinal comparisons difficult.
To establish a baseline, I first consider the DPI disaggregated data for the years from 2013-14 through 2018-19 for the Chapel Hill-Carrboro schools. Figure 1 shows the values of GLP percent for White, Black, and the White-Black difference. This is aggregated for each school and includes all students in all grades. It is evident that change in the Black-White gap is determined primarily by change in the Black GLP, not by change in the White GLP which is quite similar in value year to year.
The plots in Figures 2 use the same data as in Figure 1, but show the individual CHCCS schools. For clarity, Figures 2 show the GLP percentages, but not the gaps. The detail that emerges in these plots shows that aggregating at the LEA level hides a great deal of information.