Black-White Achievement Gap: Role of Race, School Urbanity, and Parental Education.

BACKGROUND: Recent research on Marginalization-related Diminished Returns (MDRs) has documented weaker boosting effects of parental educational attainment on educational outcomes of Black than White students. Such MDRs of parental education seem to contribute to the Black-White achievement gap. Given that Blacks are more likely than Whites to attend urban schools, there is a need to study if these MDRs can be replicated at both urban and suburban schools. AIM: To test the contribution of diminished returns of parental educational attainment on the Black-White achievement gap in urban and suburban American high schools.
METHODS: A cross-sectional study that used baseline Education Longitudinal Study (ELS-2002) data, a nationally representative study of 10th grade adolescents in the United States. This study analyzed 8315 youths who were either non-Hispanic White (n = 6539, 78.6%) or non-Hispanic Black (n = 1776, 21.4%) who were attending either suburban (n = 5188, 62.4%) or urban (n = 3127, 37.6%) schools. The outcome was standard math and reading grades. The independent variable was parental educational attainment. Gender, parental marital status, and school characteristics (% free lunch and relationship quality with the teacher) were the confounders. Race/ethnicity was the effect of modifier. School urbanity was the strata. Linear regression was used for data analysis.
RESULTS: In urban and suburban schools, higher parental educational attainment was associated with higher math and reading test scores. In urban and suburban schools, Black students had considerably lower reading and math scores than White students. At urban but not suburban schools, significant interactions were found between race (Non-Hispanic Black) and parental education attainment (years of schooling) on reading and math scores, suggested that the protective effect of parental education on students' reading and math scores (ie school achievement) is smaller for Non-Hispanic Black relative to Non-Hispanic White youth only in urban but not sub-urban schools.
CONCLUSION: Diminished returns of parental education (MDRs) contribute to the racial achievement gap in urban but not suburban American high schools. This result is important given Black students are more likely to attend urban schools than White students. As MDRs are not universal and depend on context, future research should study contextual characteristics of urban schools that contribute to MDRs.

Introduction

Educational success plays an important role in shaping people’s future opportunities in life.1 Students who perform better at school are more likely to gain higher salaries,2 become active citizens,3 experience higher life satisfaction,4 and avoid high risk and criminal behaviors5 during adulthood. Given that students’ academic achievement (eg test scores) is a substantial predictor of economic and non-economic outcomes later in life,5 it is necessary to address racial inequalities in school performance, also known as the Black-White achievement gap.

Previous research has shown persistent and large racial inequalities of academic achievement in the United States school system, which is in part due to the low quality of education at urban schools.6 Urban schools provide a lower quality of education because of fewer resources, leading to lower academic achievement among students.7 The Black-White achievement gap, however, remains significant beyond controlling for school urbanity as a covariate.8 It is, however, unknown whether Black-White achievement gap can be seen within both urban and suburban schools.

Child’s academic achievement is affected by school socioeconomic status (SES).9 Concentration of poverty among students who attend urban schools is considered one of the greatest contributors to low academic achievement in such contexts.10 Recent studies demonstrate that poverty has both a direct impact on student achievements through cognitive ability11 and education quality.12 For example, differential teacher quality may explain some of the achievement gap between Blacks and Whites.13 Children of low SES families start school less prepared14 and academically perform worse than their peers with higher family SES at school.10 This is another reason we need to differentially study contributors of the Black-White gap in predominantly Black (suburban) and White (suburban) schools.

Family SES is also among the major determinants of students’ school achievement.9 Among SES indicators, parental education is among the most stable aspects of family SES background,15 which influence the quality of home learning settings16 and higher levels of parental engagement in children’s schooling.16,17 Children of low-educated parents more so than students with highly educated parents tend to demonstrate lower educational achievement.18 Parents with higher education levels can provide greater SES resources which influences the academic achievement of their children,19 but lower SES in Black parents can be restricted their investment in their children.20

Eligibility for using free or reduced price lunch (FRPL) is one of the other indicators of SES that may predict student academic achievement.21 FRPL is a proxy of school SES.21,22 Predominantly Black and urban schools have higher FRPL usage than predominantly White and suburban schools.23 Students who are FRPL eligible score lower in reading and math test scores than equivalent students who were not eligible for FRPL.24

The educational attainment gap between students of low SES and high SES is observable at the age of seven, and at the end of compulsory education.10 In addition, education aspiration, especially among poor students, has been connected to academic achievement,25 such that over time and when approaching the end of compulsory education, educational aspirations fall in low-income students.14

In the US, students with low family SES are most likely to attend urban schools.26 On the other hand, children who go to urban schools in low-income neighborhoods show lower academic progress.27,28 Indeed, sixth-grader children in the wealthiest school regions compared to children in the poorest regions are four grade levels ahead.29 In addition, the high percentage of students with low family SES in urban schools is related to lowers the engagement and attempt of all students.7

In the US education system, schooling and residential place are closely connected. As a result, residential neighborhoods affect both the value of property (wealth) and the racial and socioeconomic composition of schools.30 Therefore, the role of race could be disadvantageous for the academic achievement of minorities.23 In spite of the modest decreases in the Black-White residential segregation, Black students remain concentrated in racially segregated public schools in urban zones where a higher percentage of the population is from the racial or ethnic minority groups with low income.31 A previous study showed schools in the poor regions have insufficient resources and elementary education quality varies drastically racial lines.32 Also, research has shown lower academic achievement obtain in urban schools and schools where a greater part of the student body is Blacks.31,33

Race is closely linked to family SES.34 Race is also associated with school SES and racial composition.35 Schools with a high concentration of minorities have lower SES.36 School social status, student–teacher ratio, class size, teacher selection, and school rules are influenced by school SES.23 African American students in mainly Black schools both in advanced and general classes are more likely to be exposed to a less demanding curriculum due to lower teacher quality and expectations31 which lead to the academic achievement gap.

Furthermore, a significant factor in enhancing student educational achievement is teacher quality.37 Educational background, professional certifications, and teaching experience of teachers improve student achievement in schools.38 Studies in the US have shown that students’ academic achievement may be three times higher when taught by a high-quality teacher.39 But evidence indicates that schools with a high percentage of minority students are more likely to have lower qualified and experienced teachers with higher rates of teachers’ turnover.40,41 Also, new teachers inclined to start their work in schools with greater concentrations of low SES students do so to acquire more experience and then tend to transfer to higher-SES schools.30 In addition, poor and Black students are more probably taught by teachers who have an alternative certification.6

Although Black and White students' academic achievement gap improved across time,42 this gap still exists and substantial especially in urban schools.6,43 Recent data revealed the achievement gap between White and Black youth in reading and math remained relatively constant over the past years.44 Additionally, the Black-White academic achievement gap in both reading and math scores during the first 4 years of the primary school nearly 0.10 standard deviations increased each year.45 Research suggests this gap may be due to the SES achievement gap between minorities and the majority group.46 However, in recent years, the relationship between race and SES also is dropping.47

Research has revealed that racial/ethnicity minorities may not receive equal gains from their SES compared to dominant racial/ethnic groups,48,49 identified as Marginalization-related Diminished Returns (MDRs).50,51 In the US, marginalization-related diminished returns of SES indicators (eg education attainment, income) are established across domains of health52 such as exercise,53 diet,54 smoking,55,56 depression,57,58 anxiety,59 mental well-being,60 self-rated mental health,61 and chronic medical conditions.54 Recent research has also documented diminished returns of parental educational attainment on school performance of Black children.62

Recently, diminished returns of parental educational attainment have been investigated on student academic performances of minorities group in the US population. In two studies, parental educational attainment has smaller positive effects on grade point average (GPA) in Hispanic and Black than non-Hispanic White youth62 and non-Hispanic Blacks than non-Hispanic Whites college students.63 The result of another study indicated that the family socioeconomic position at birth has a smaller protective result for school bonding in Black than White youth.64

To investigate diminished returns of parental education on the school performance of elementary students, we applied a nationally representative sample to compare Black and White students reading and math scores as a function of race and parental education. We tested these effects across urban and suburban schools. Our hypothesis is that Black and White students’ academic performance are differently affected by parental education and available resources in urban and suburban schools. If we could observe diminished returns of parental education in both urban and suburban schools, then diminished returns of parental education is not just a problem of urban schools. MDR are also not all because Black and White students attend different schools. If diminished returns exist in urban schools but not in suburban schools, urban school would be the context that generates MDR. We hypothesized that urban schools (low education quality and poor education context) not suburban schools will show MDR. That means we expect urban schools to be a mechanism by which parental education generates less outcomes for Black than White students.

Methods

Design and Settings

This cross-sectional study is a secondary analysis of Wave 1 of the Education Longitudinal Study (ELS) study.65 Funded by the US Department of Education (DOE), ELS is one of the main studies of youth education in the US. The ELS sample is representative of 10th grade youth in the US. Although ELS has enrolled all race/ethnic groups, this analysis was limited to 10,702 youth who were composed of 2020 (18.9%) non-Hispanic Black and 8682 (81.1%) non-Hispanic White youth. Exclusion criterion in the current analysis was any race other than White or Black.

Ethics

All participating youth provided written assent. Youth parents signed written consent. The institutional review board (IRB) of the Department of Education (DOE) approved the protocol of the original article. As this analysis used fully deidentified public data, this secondary analysis was deemed to be exempted from a full IRB review.

Sample and Sampling

The ELS youth sample was enrolled in the private, public, or Catholic schools. These schools could be selected from either Urban, Suburban, or Rural areas. ELS used a multi-stage stratified random sample. The analytical sample of this study was 10,702.

Study Variables

The study variables included race/ethnicity as the moderating variable, parental education as the independent variable (predictor), youth math and reading test scores as the outcomes (dependent variables), and demographic factors (gender and parental marital status) and school characteristics (% students receiving free lunch).

Race/ethnicity

Race/ethnicity, a dichotomous variable, was self-identified as non-Hispanic Black (1) versus on-Hispanic White (0).

Parental Educational Attainment (Independent Variable)

Parental educational attainment was a continuous variable that reflected the highest number of years of schooling in parents. This variable was self-reported by the parents.

Demographic Factor (Covariates)

Gender and family structure were demographic covariates. Parental marital status was a dichotomous variable (1 = married parents, 0 = unmarried parents) and calculated based on parents’ marital status. Gender was 1=male 0 = female.

School characteristics

School characteristics included school control system (public versus private), and % students receiving free lunch. Both these variables were administrative rather than self-report.

School Urbanity

School urbanity was a dichotomous variable: 1= urban schools, 0 = suburban schools. This variable was administrative, not self-report.

School Function/Achievement (Outcomes)

Our dependent variables were standardized test scores of math and reading. These variables were transformed to z scores which helps comparison of the students and interpretation of the regression coefficients. Students performed the test.

Statistical Analysis

SPSS 23.0 (IBM Corporation, Armonk, New York, US) was used to analyze the data. We had normally distributed outcomes thus we decided to perform linear regressions. There was no multicollinearity between our independent variables such as race/ethnicity and parental educational attainment. Our model passed the assumption of homoscedasticity (eg, distribution of error terms). This strategy also helped us with the comparability of MDR across our two outcomes. We ran two hierarchical linear regression models per outcome, in the pooled sample. The first block of variables only included race/ethnicity. Our second block included educational attainment (years of schooling). Block 3 included the educational attainment (years) by race/ethnicity interaction term. The fourth block included gender and parental marital status. The fifth block included school characteristics, namely, relation with the teacher and % students with free lunch. We reported beta (b), B, standard error (SE), and p value.

Results

Descriptive Data

Table 1 provides descriptive statistics for our sample. This study included 8315 youth. From this number, most were non-Hispanic White (n = 6539, 78.6%) and a minority were non-Hispanic Black (n = 1776, 21.4%). From all participants, most were attending either suburban schools (n = 5188, 62.4%) and a minority were attending urban schools (n = 3127, 37.6%).

Table 1

Descriptive Characteristics

Qualitative Variables	All n = 8315		Suburban n= 5188		Urban n = 3127
	n	%	n	%	n	%
School Urbanity
Suburban	5188	62.4	5188	100.0	0	0
Urban	3127	37.6	0	0	3127	100.0
Race (Black) *
Non-Hispanic White	6539	78.6	4386	84.5	2153	68.9
Non-Hispanic Black	1776	21.4	802	15.5	974	31.1
Gender
Female	4204	50.6	2631	50.7	1573	50.3
Male	4111	49.4	2557	49.3	1554	49.7
Parental Marital Status*
Not- Married	3325	40.0	1992	38.4	1333	42.6
Married	4990	60.0	3196	61.6	1794	57.4
Quantitative variables	Mean	SD	Mean	SD	Mean	SD
Parental education (years) *	4.81	2.00	4.66	1.99	5.05	2.01
Teacher student relation*	0.34	0.74	0.30	0.72	0.42	0.78
% Free Lunch	2.86	1.89	2.89	1.77	2.83	2.07
Test Score (Reading)	51.82	9.83	51.76	9.62	51.91	10.16
Test Score (Math) *	51.57	9.73	51.79	9.45	51.21	10.17

Note: * p < 0.05.

Bivariate Analysis

Table 2 presents the summary of bivariate analysis in the pooled sample. Reading and math test scores were closely correlated (r = 0.75, p < 0.001). % free lunch at school was inversely correlated with reading (r = −0.33, p < 0.001) and math (r = −0.36, p < 0.001) scores. Urban school was correlated with lower math (r = −0.03, p < 0.001) but not reading (p > 0.05) score. Race (Black) was negatively correlated with both reading (r = −0.34, p < 0.001) and math (r = −0.39, p < 0.001) scores.

Table 2

Correlations in the Pooled Sample (n=8315)

	1	2	3	4	5	6	7	8	9
1 School Urbanity (Urban)	1	0.19**	0.09**	0.00	−0.04**	0.08**	−0.02	0.01	−0.03**
2 Race (Black)		1	−0.13**	−0.00	−0.30**	−0.06**	0.39**	−0.34**	−0.39**
3 Parental education (years)			1	0.01	0.15**	0.09**	−0.31**	0.33**	0.34**
4 Gender (Male)				1	0.02	−0.00	0.00	−0.07**	0.07**
5 Parental Marital Status (Married)					1	0.09**	−0.25**	0.23**	0.25**
6 Teacher student relation						1	−0.12**	0.13**	0.14**
7% Free Lunch							1	−0.33**	−0.36**
8 Test Score (Reading)								1	0.75**
9 Test Score (Math)									1

Note: ** p < 0.01.

Multivariable Models

Table 3 presents the summary of two hierarchical linear regression models in suburban schools. In both these models, race (non-Hispanic Black) and parental educational attainment were associated with the outcomes (reading and math scores). These models did not show statistical interactions between parental educational attainment and race on youth educational outcomes. No interaction terms suggest that the link between high parental educational attainment and youth educational outcomes (grades) is similar for non-Hispanic Black than and Non-Hispanic White youth.

Table 3

Associations Between Race and Parental Education on Reading and Math Score at Suburban Schools

	B (Std. Error)	B (Std. Error)	B (Std. Error)	B (Std. Error)	B (Std. Error)
Reading
Race (Black)	−7.90(0.42)***	47.32(0.38)***	−6.41(0.96)***	−5.77(0.96)***	−5.10(0.96)***
Parental Education	–	−7.16(0.40)***	1.35(0.08)***	1.30(0.08)***	1.16(0.08)***
Black* Education (Years)	–	–	−0.17(0.20)	−0.17(0.20)	−0.18(0.20)
Gender (Male)	–	–	–	−1.99(0.28)***	−2.01(0.28)***
Parental Marital Status	–	–	–	2.06(0.30)***	1.77(0.30)***
Teacher student relation	–	–	–	–	0.95(0.20)***
% free lunch	–	–	–	–	−0.50(0.09)***
Math
Race (Black)	−9.04(0.40)***	−8.25(0.38)***	−7.04(0.92)***	−6.42(0.91)***	−5.67(0.91)***
Parental Education	–	1.41(0.07)***	1.46(0.07)***	1.38(0.07)***	1.24(0.08)***
Black* Education (Years)	–	–	−0.28(0.19)	−0.27(0.19)	−0.28(0.19)
Gender (Male)	–	–	–	1.13(0.27)***	1.11(0.27)***
Parental Marital Status	–	–	–	2.16(0.29)***	1.85(0.29)***
Teacher student relation	–	–	–	–	0.97(0.19)***
% free lunch	–	–	–	–	−0.56(0.08)***

Note: ***p < 0.001.

Table 4 presents the summary of two hierarchical linear regression models in urban schools. In both these models, race (non-Hispanic Black) and parental educational attainment were associated with the outcomes. These models showed an interaction between parental education and youth outcomes. These interaction terms suggest that the positive link between parental education and youth educational outcomes (grades) is smaller for non-Hispanic Black relative to Non-Hispanic White youth. These findings suggest that in urban schools, non-Hispanic Black youth with highly educated parents have low school performance, and these diminished returns of parental education.

Table 4

Associations Between Race and Parental Education on Reading and Math Score at Urban Schools

	B (Std. Error)	B (Std. Error)	B (Std. Error)	B (Std. Error)	B Std. Error
Reading
Race (Black)	−9.45(0.42)***	−8.06(0.41)***	−4.94(1.03)***	−4.06(1.04)***	−5.10(0.96)***
Parental Education	–	1.36(0.09)***	1.54(0.11)***	1.48(0.11)***	1.16(0.08)***
Black* Education (Years)	–	–	−0.68(0.21)**	−0.66(0.20)**	−0.18(0.20)
Gender (Male)	–	–	–	−0.86(0.36)*	−2.01(0.28)***
Parental Marital Status	–	–	–	2.46(0.39)***	1.77(0.30)***
Teacher student relation	–	–	–	–	0.95(0.20)***
% free lunch	–	–	–	–	−0.50(0.09)***
Math
Race (Black)	54.99(0.21)***	47.87(0.52)***	46.56(0.59)***	44.33(0.65)***	47.13(0.73)***
Parental Education	–	−9.00(0.40)***	−4.91(1.00)***	−3.85(0.99)***	−2.51(0.99)*
Black* Education (Years)	–	–	1.57(0.10)***	1.51(0.10)***	1.29(0.10)***
Gender (Male)	–	–	–	−0.90(0.20)***	−0.87(0.19)***
Parental Marital Status	–	–	–	1.39(0.34)***	1.46(0.33)***
Teacher student relation	–	–	–	–	1.95(0.37)***
% free lunch	–	–	–	–	1.06(0.22)***

Notes: *p < 0.05; **p < 0.01; ***p < 0.001.

Discussion

The current study showed four findings: First, high parental education was linked to higher math and reading scores among youth. Second, in urban but not suburban schools, the boosting effect of parental education on school achievement is weaker for non-Hispanic Black than for Non-Hispanic White families. Third, parental education differently influenced reading and math scores at urban schools above and beyond relation with children, marital status of the parents, and % free lunch eligibility of the students. Fourth, at suburban schools, Black and White students similarly gain school performance from their parental education.

Diminished returns of education contribute to the Black-White academic gap in urban schools only. At urban schools, Black students remain at educational risk, despite their highly educated parents. Such level of risk is unexpected and disproportionate to their parental educational attainment.

As MDR remained as a contributor to the Black-White achievement gap in urban but not suburban school characteristics, we argue that urban school context may be a probable cause for diminished returns of parental educational attainment as a cause of racial achievement gap. Still, as shown by previous studies, other upstream social forces that occur beyond education system may also contribute to such gap. For example, labor market discrimination may put Black parents in worse jobs, which may reduce Black parents’ available time to engage with their children’s school activities. However, differential context of education of Black and White youth seems to be essential for Black-White achievement gaps due to MDR.66

With a similar pattern observed in urban schools, Black students with highly educated parents have shown to report poor school outcomes,67 poor school attainment,51 and poor school bonding;68 all outcomes that are disproportionate to their high parental education. Previous research, however, could not tell whether these patterns can be observed in both urban and suburban settings.

One recent study documented worse than expected aggression, chronic diseases, tobacco use, psychological problems, and school performance in Black youth with high parental education.66 As argued in other studies,69–71 a plausible conclusion seems to be that some distal and upstream social processes interfere with the effects of parental education for racial and ethnic minority families.66 According to this study, however, diminished returns of parental education are not all because Black youth attending urban schools where the quality of schooling is lower.

The education system seems not to be the only reason we see worse outcomes for Black youth in the middle class with highly educated parents. Diminished returns of parental and own education result in higher than expected prevalence of asthma,72 Attention Deficit Hyperactivity Disorder,73 mental health problems,74 depression,75,76 obesity,61,77 dental health problems,78 poor health-care use,79 impulsivity control,80 and cigarette smoking81 in middle class Black families. Similar patterns are shown for Black adults,82–84 Black youth,77,80,85 Hispanic adults,56,86,87 and Hispanic youth.66 As similar patterns are shown for various groups, it is not a group behavior but the upstream underlying mechanisms such as social stratification, structural racism, and marginalization that reduce the positive effects of education for minority families.66

While parental education promotes educational outcomes for youth, this association is diminished for Non-Hispanic Black and White youth. The smaller marginal returns of parental education are beyond what can be explained by school characteristics that differ between Non-Hispanic Black and non-Hispanic White students. Diminishing returns of parental educational attainment (MDR) may be an unrecognized source of racial youth disparities. Equalizing SES would not be enough for equalizing outcomes. There is a need for public and economic policies that reduce diminished returns of SES for Black families.

The major contribution of this study is that we found diminished returns of parental education in urban but not suburban schools. That is, diminished returns of parental education may be specific to the context, thus modifiable through educational policies. This results in advocates for policies that target the education quality of urban schools. We argue that Black youth from the middle class perform worse than expected in part because they are more likely to attend urban schools. They would probably do similar to White middle-class youth if they had the chance to attend suburban schools.

Racial inequalities and disparities are not all due to the lower SES of Blacks as inequalities can be also seen in middle-class people. Thus, other social mechanisms are at work to cause inequalities across racial groups, even for middle-class families that access education.

Policy Implications

These results have considerable implications. Innovative policies, as well as public health programs, should be designed, implemented, and evaluated to reduce racial and ethnic inequalities across all levels of SES strata. To address disparities that are not due to low SES but diminished return of SES, we should go beyond exclusively focusing on equalizing access to resources. While equal access is important, there is a need to address broader social and economic processes that hinder middle-class Black families’ abilities to leverage their available resources. Policies should aim to equalize the gain that follows access to SES resources. Such policies are hoped to reduce inequalities that sustain across all the SES spectrum.55,59,77–80,82,86,88,89 We need policies and program solutions that equalize highly educated Black families’ abilities to leverage their educational attainment.88,90 Some suspect the cause of MDR are labor market practices and preferences.82 Although there are strong anti-discrimination laws, further enforcement of such existing policies may be required if we want to minimize the existing diminishing marginal returns of education and other SES indicators in the lives of Black families. Communities, where the majority of residents are Black, may benefit from higher quality and abundant jobs that facilitate translation of educational attainment into tangible real-life outcomes.91 Programs should help highly educated Black parents successfully compete with Whites to secure high paying jobs. At the same time, we should reduce the societal and environmental barriers that are common in the everyday lives of Black population. In addition, we should invest in educational programs and in outcomes of Black youth, including middle-class Black youth, in urban and suburban schools. There is a need to empower Black parents to utilize their education and increase their engagement with their children's school performance. Finally, we need to minimize the discrimination of Black students in urban and suburban schools.92,93

Limitations

This study had a few limitations. With our cross-sectional design, we cannot make any causal inferences. The unequal sample size across groups prevented us from running race-specific models. This study only included Non-Hispanic Blacks and Non-Hispanic Whites. Other ethnic minorities such as Hispanics, Asians, and Native Americans should be included in future studies. We only studied the differential effect of parental educational attainment. Other family SES indicators such as wealth, income, employment, and area-level SES should be studied. This study did not include geocoded data. Thus, educational policies were not included. Despite these limitations, this study still contributes to the MDR literature on as well as the racial achievement gap. Some strengths included a large sample size, a random sample, and a representative sample that resulted in generalizable findings to the US, and standardized tests. However, the main contribution of this study is beyond these methodological strengths. This was the first study showing that diminished returns of parental education on school performance can be seen in both urban and suburban schools, thus these diminished returns are not all because of poor urban schools that are weak in educational quality.

Conclusion

In the United States, non-Hispanic Black youth who attend urban schools are at a disadvantage compared to Non-Hispanic White youth regarding the magnitude of the effect of parental education on their educational outcomes. Such diminished returns of parental education that are observable in urban schools are absent in suburban schools. Context of education may be one reason Black youth from middle-class families do worse than middle-class White youth.