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​​​​​​​​​​​​Frequently Asked Questions About the Black-White Achievement Gap Report


Black Student Density, by Race and Location The Relationship Between Black Student Density and Achievement Exploring Between-School and Within-School Achievement Gaps

View frequently asked questions about the Hispanic-White achievement gap report.


why_conductWhy did the National Center for Education Statistics (NCES) conduct the Black-White achievement gaps study?

There is little information on the relationship between school composition and achievement gaps. Because of the growing concern with resegregation in schools (Frankenberg, Lee, & Orfield, 2003; Orfield, Kucsera, & Siegel-Hawley, 2012), there is a need for additional information about this relationship.

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what_isWhat is "Black student density," and why is that term used?

Black student density is defined as the percentage of students in a school who are Black. For this study the percentages were calculated using the number of students in the school (regardless of race/ethnicity) in the denominator and the number of Black students in the school in the numerator.

The term density has been used in previous NCES reports (e.g., NCES, 2012) and in peer-reviewed articles (e.g., Madyun & Lee, 2010; Gieling, Vollebergh, & van Dorsselaer, 2010) to indicate demographic composition within schools.

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what_analysesWhat analyses were conducted and why?

This report begins with a description of how Black student density differs for Black and White students, and identifies the U.S. regions and locale types where the highest Black student density schools are located.

The report then highlights results from two separate sets of analyses. The first analysis explores the relationship of Black student density with achievement and achievement gaps. This analysis explores whether the identified relationship between density and student achievement persists when accounting for student demographic characteristics such as socioeconomic status (SES) and other school characteristics that may be associated with achievement. It also explores results separately for males and females.

The final section of the report builds on prior research that explored whether achievement gaps might be found more within schools or between schools. Whether gaps are larger between schools or within schools can inform the actions of those who are concerned with improving student achievement and reducing the achievement gap.

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Black Student Density, by Race and Location  

what_dataWhat data were used in these analyses?

The descriptions of the extent of Black student high- and low-density schools and their location relied on two data sources:

  1. NAEP 2011 Mathematics Grade 8 Assessment
  2. Common Core of Data (CCD) 2010–11

The CCD data were limited to schools that offer eighth grade and whose Type was identified as a “regular” school. (For a definition of a “regular” school, see CCD documentation at

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 The Relationship Between Black Student Density and Achievement

rel_what_dataWhat data were used in these analyses?

These analyses were based on the NAEP 2011 Mathematics Grade 8 Assessment student, teacher, and school information for Black and White students. Additional school-level information was added onto the NAEP data from the CCD.

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rel_otherAre students other than Black and White students included in the analyses that explore the relationship between Black student density and achievement?

No. These analyses focused on the average achievement of Black and White students only. Regression analysis was used to adjust the means to control for SES, student, teacher, and school factors, but the regression model was estimated using only Black and White students.

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rel_what_factorsWhat were the student, teacher, and school factors accounted for in these analyses?

The student characteristics included measures from the NAEP student questionnaire: race/ethnicity, disability status, gender, and SES measures. Teacher characteristics included measures from the NAEP teacher questionnaire such as teacher qualifications and teacher instructional strategies. School factors included SES measures aggregated from student SES measures as well as other school factors from the NAEP school questionnaire and from the CCD. See the methodology companion for a full list of the variables used in the model.

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rel_how_factorsHow did the analyses account for these factors?

Regression analysis was used to calculate average achievement for Black and White students in each Black student density category to account for differences in student, teacher, and school characteristics. When the analysis accounts for these differences, the averages reported represent the average achievement for students as if they all had the same student, teacher, and school characteristics. The methodology companion provides a complete description of the model used, how means were calculated, and how significance testing was conducted.

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Exploring Between-School and Within-School Achievement Gaps

explore_what_dataWhat data were used in these analyses? 

This analysis was based on the NAEP 2011 Mathematics Grade 8 Assessment student, teacher, and school information for all students in the sample.

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explore_what_purposeWhat is the purpose of these analyses? 

The purpose of these analyses is to apply methods established by previous authors to recent NAEP data. These analyses are meant to inform those interested in reducing the Black-White achievement gap regarding whether policy should focus on addressing differences in achievement between schools or differences in achievement within schools. When between-school gaps exist, theoretically they could be addressed by focusing policy efforts on differences between schools (e.g., access to critical resources that might be associated with higher student achievement like technology, updated textbooks, or qualified teachers). When within-school gaps exist, theoretically they might be addressed by focusing efforts on differences within schools (e.g., access within schools to critical resources like technology, updated textbooks, or qualified teachers) or changing processes (e.g., differential teacher expectations, tracking) that might be associated with higher student achievement.

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explore_what_diffWhat are the "differences?" 

These are differences in the achievement of Black and White students. It is important to note that this analysis does not identify what causes these differences, but rather, it describes whether the differences in achievement between Black and White students are observed between or within schools. Each portion—between or within—can be addressed by different sorts of policies.

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explore_how_densityHow is Black student density relevant for these analyses of between-school and within-school achievement differences?

The relationship between Black student density and achievement is a key variable in the statistical analysis: the stronger the relationship between density and achievement, the larger the portion of the gap attributed to between-school differences.

In the extreme, if differences in the school density of Black students are not related to the achievement gap, then differences in achievement cannot be found between schools and are only found within schools.

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explore_factors_accountDo these analyses account for other factors, such as SES?

No. These analyses decompose the whole achievement gap, NOT just the part that cannot be attributed to SES or other factors.

These analyses seek to examine how policies can best address the entire Black-White achievement gap, regardless of whether it is explained by SES or not. In other words, if the analyses were to look at only the portion of the gap not explained by SES or other factors, the results would not be able to help inform how to close that part of the gap that is explained by SES.

The absence of student and school control variables from these analyses may cause confusion as it is a departure from the analysis presented in the first chapter of the report on the relationship between achievement and density, where SES and other factors were accounted for in the model. The research in that previous chapter sought to investigate whether density was correlated with the achievement gap. In such an investigation, one would want to control for SES and other potentially confounding factors to examine potential relationships among density, the variable of interest, and the achievement gap. The decomposition analysis is different in that it is descriptive and does not seek to determine a correlational relationship. Specifically, the decomposition analysis is a description of where the achievement gaps are occurring so that policies might be optimally directed (e.g., focused on the distribution of resources within, rather than between, schools).

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explore_diffAre some of the observed "differences in achievement" due to differences in SES?

We know that prior research shows that SES is related to the achievement gap, so it is likely that part of the 31-point gap nationally is due to SES differences. The analyses in the report, however, are focused on providing information for policies that address the gap, not uncovering the causes. SES differences are not policy levers—in other words, education policy cannot directly change the SES of a student’s family. However, education policy can redistribute resources (as an example) such that even the portion of the gap attributable to SES differences is addressed.

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explore_indeterminateWhy is there an "indeterminate" portion? 

Different researchers have used different formulae to conduct this decomposition. Reardon (2008) reconciled these different approaches by identifying a portion that all of the different approaches attributed to within-school differences, a portion that all attributed to between-school differences, and remainder that was classified by some approaches as between school and others as within school. Reardon labeled the third portion as “ambiguous,” but in this report we use the label “indeterminate.” Theoretically, policies focused either on the within-school or between-school differences might help close the indeterminate portion of the achievement gap.

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Last updated 06 August 2015 (DS)