Differences In School Quality Research Articles

Are Neighborhood Effects Explained by Differences in School Quality?

Are Neighborhood Effects Explained by Differences in School Quality?

School Value-Added and Long-Term Student Outcomes

This paper studies school quality in the context of Norwegian compulsory schooling. I demonstrate that even when lagged achievement is not observed, it is possible to construct informative value-added (VA) indicators of persistent school quality by adjusting exam scores for students’ background characteristics. These VA indicators show little bias forecasting average exam performance out of sample, and are also predicative of long-term student outcomes, including earnings. Three quasi-experiments using variation from student mobility and changes in neighborhood school assignments indicate that the differences captured by the VA indicators do indeed reflect differences in school quality, rather than unobserved student characteristics. The finding help connect learning outcomes with later labor market outcomes, e.g. for cost-benefit analysis of interventions in schools.

Decomposing Learning Inequalities in East Africa: How Much Does Sorting Matter?

Abstract Inequalities in learning opportunities arise from both household- and school-related factors. Although these factors are unlikely to be independent, few studies have considered the extent to which sorting between schools and households might aggravate educational inequalities. To fill this gap, this article presents a novel variance decomposition, which is then applied to data from over one million children from East Africa. Results indicate that sorting accounts for around 8 percent of the test-score variance, similar in magnitude to the contribution of differences in school quality. Empirical simulations of steady-state educational inequalities reveal that policies to mitigate sorting could substantially reduce educational inequalities over the long run.

学校质量、个人禀赋与教育回报的城乡差距 (School Quality, Innate Ability, and the Urban-Rural Disparity in Returns to Schooling in China)

Chinese abstract: 本文利用2013年中国家庭收入调查数据（CHIP）研究相同学历水平城乡居民的教育回报差距及其来源。为避免样本自选择问题，本文使用居民12岁时的户口性质划分城乡居民。我们发现控制家庭背景等因素后，教育回报的城乡差距随学历水平的增加不断扩大：对于小学及以下、初中、高中和大专及以上学历，其估计值分别为-17.2%、-9.8%、0%和10.2%。这种差距主要来源于城乡居民学校质量和先天禀赋的差异：对所有学历组，城市居民的平均禀赋都低于同等学历的农村居民，但在基础教育阶段享受到更高质量的学校教育，因而积累了更多的人力资本，弥补了其在个人禀赋方面的劣势，且这一效应随着学历上升而得到增强。通过使用生均高职称教师数作为改进的教育质量衡量指标，我们发现，如果保持其他条件不变，而将农村学校质量提升至与城市相同，90后农村初中、高中毕业生的教育回报将分别提高大约21%和61%。因此，政府应着力提高农村地区的学校质量，从而提高农村居民的教育回报，进而激励农村居民提高整体受教育水平，缩小城乡收入差距。 English abstract: This paper studies how differences in school quality affect the returns to education of urban and rural residents in China using the CHIP 2013 data. To deal with biases due to self-selection in migration, we define urban and rural residents based on their Hukou status at age 12, a critical age when basic education is completed. We find that after controlling for family background, the gap in returns to education between urban and rural residents increases over the schooling stages; the gaps are -17.2%, -9.8%, 0%, and 10.2% for individuals with at most a primary school education, a middle school education, a highs school education, and a college education respectively. These gaps can be attributed to both school quality of basic education and individual innate ability. More specifically, conditional on schooling level, the expected innate ability of urban residents is lower than that of rural residents, but this disadvantage is more than compensated for by the higher quality of urban schools, and the cumulative quality advantage of urban schools increases as individuals progress through education stages. Using the number of senior teachers per student as a measure of school quality, we find that ceteris paribus, equalizing the quality of urban and rural schools will lead to a 21% and 61% increase in the return to a middle school and high school education respectively for rural residents born in the 1990s. Our findings indicate that China’s urban-rural income inequality is due not only to differences in education attainment but also to gaps in school quality between urban and rural residents.

School quality ratings are weak predictors of students' achievement and well-being.

In England, all state-funded schools are inspected by an independent government agency, the Office for Standards in Education, Children's Services and Skills (Ofsted). Inspections aim to hold schools accountable and to promote the improvement of education, with the results made available to the public. Ofsted reports intend to index school quality, but their influence on students' individual outcomes has not been previously studied. The aim of the current study was to explore the extent to which school quality, as indexed by Ofsted ratings, is associated with students' educational achievement, well-being and school engagement. We use an England population-based sample of 4,391 individuals, for whom school performance at age 11 and GCSE grades at age 16 were accessed from the National Pupil Database, and who completed measures of well-being and school engagement at age 16. We found that Ofsted ratings of secondary school quality accounted for 4% of the variance in students' educational achievement at age 16, which was further reduced to 1% of the variance after we accounted for prior school performance at age 11 and family socioeconomic status. Furthermore, Ofsted ratings were weak predictors of school engagement and student well-being, with an average correlation of .03. Our findings suggest that differences in school quality, as indexed by Ofsted ratings, have little relation to students' individual outcomes. Accordingly, our results challenge the usefulness of Ofsted ratings as guides for parents and students when choosing secondary schools.

Learning Inequality in Francophone Africa: School Quality and the Educational Achievement of Rich and Poor Children

Influential reports about the “learning crisis” in the global South generally pay insufficient attention to social inequalities in learning. In this study, we explore the association between family socioeconomic status and learning outcomes in 10 francophone African countries using data from the Programme for the Analysis of Education Systems, a standardized assessment of pupils’ mathematics and reading competence at the end of primary school. We start by showing that learning outcomes among grade 6 pupils are both poor and highly stratified. We then develop and test a conceptual framework that highlights three mechanisms through which family socioeconomic status might contribute to learning: (1) educational resources at home, (2) health and well-being, and (3) differences in school quality. We find that most of the effect of family background on learning outcomes operates through school quality, which results from a combination of the unequal distribution of resources (such as teachers and textbooks) across schools and high socioeconomic segregation between schools. On the basis of these results, we suggest that most countries in the region could improve equity as well as overall performance by “raising the floor” in school quality.

The Distribution of School Quality: Do Schools Serving Mostly White and High-SES Children Produce the Most Learning?

What is schools’ role in the stratification system? One view is that schools are an important mechanism for perpetuating inequality because children from advantaged backgrounds (white and high socioeconomic) enjoy better school learning environments than their disadvantaged peers. But it is difficult to know this with confidence because children’s development is a product of both school and nonschool factors, making it a challenge to isolate school’s role. A novel approach for isolating school effects is to estimate the difference in learning when school is in versus out, what is called impact. Scholars employing this strategy have come to a remarkable conclusion—that schools serving disadvantaged children produce as much learning as those serving advantaged children. The empirical basis for this position is modest, however, and so we address several shortcomings of the previous research by analyzing a nationally representative sample of about 3,500 children in 270 schools from the Early Childhood Longitudinal Study–Kindergarten Cohort of 2011. With more comprehensive data and better scales, we also find no difference in impact on reading scores across schools serving poor or black children versus those serving nonpoor or white children. These patterns challenge the view that differences in school quality play an important role shaping achievement gaps and prompt us to reconsider theoretical positions regarding schools and inequality.

A critical review of the literature on the relationship between school quality and health inequalities

Robust evidence suggesting a strong association between greater educational attainment, better health and lower mortality, has led to speculation that the quality of schooling can also have effects on health. This review critically summarises findings from 15 studies in a growing area of research concerning the effects of school quality on health. Findings suggested positive, long‐term benefits of high‐quality pre‐school. Other findings suggested that higher teacher wages, lower pupil–teacher ratios, a longer school year, and higher college selectivity had mostly positive long‐term effects on health and mortality. Several studies found that school quality modified the effect of years of completed education on various health outcomes. Some measures of school quality including smaller class size in relation to mortality, and higher college selectivity in the case of smoking were not consistently related to better health. While studies varied in their consistency and significance, the weight of the evidence together, suggests that some health inequalities over the life course were explained partly by differences in school quality. This may be related to improved cognition, occupational characteristics, and the incomes of those exposed to better quality schooling. Direct health knowledge and behaviour may also play a role.

Do the maths: An analysis of the gender gap in mathematics in Africa

This paper uses microdata for 19 African countries to examine the gender difference in maths test scores amongst primary school children. There is a significant difference in maths test scores in favour of boys, similar to that previously observed in developed countries. This difference cannot be explained by gender differences in school quality, home environment, or within-school gender discrimination in access to schooling inputs. However, the gender gap varies widely with characteristics of the regions in which the pupils live, and these regional characteristics are more predictive of the gender gap than parental education and school characteristics, including teacher gender. At the cross-country level, differences in fertility rates account for nearly half the variation in the gender gap, and this relationship is not due to the correlation between fertility and GDP.

“You Can’t Help a Child if You Don’t Know Something Yourself”: A Qualitative Study of Barriers to Education in an Underserved West Baltimore Community

Volumes have been written describing research, theory and opinion as to the causes and correlates of disparities in health and educational outcomes in the United States. Still, there is little agreement on the etiology or resolutions of the inequality in opportunity and outcomes faced by many of our most vulnerable citizens, especially those citizens in under-resourced communities of color. There is, however, increasing agreement that health outcomes and educational achievement are influenced by factors outside of their respective sectors, such as social, family, and neighborhood conditions including poverty, structural racism, and environmental hazards (Chen, Martin, & Matthews, 2007; Evans, 2004; Murnane, 2007). The interdependence of health and educational attainment starts early and continues throughout someone's lifespan. For example, children with health challenges, such as asthma or diabetes tend to attend school less frequently and perform more poorly on measures of academic attainment (Haas & Fosse, 2008; Kearney, 2008). Children with lower levels of educational attainment tend to have less economic success and worse health across their lifespans (Case, Fertig & Paxson, 2005; Heckman, 2008; Lynch, Kaplan & Shema, 1997). Consequently, any effort to understand the drivers of health outcomes, educational attainment or poverty should begin with examining the relationship between the three. Using an ecological framework, this article describes the interaction of factors that focus groups participants note create barriers to health promotion and educational attainment in an underserved and under resourced community in West Baltimore.LITERATURE REVIEWUsing data from 12 nationally representative studies, Reardon (2013) found that the gap in standardized test scores of high- and low-income families has grown by about 40% over the previous three decades. The college enrollment and completion rates have displayed a similar trend, with increased rates of graduation for wealthy students but no improvements among poor families (Reardon, Baker, & Klasik, 2012). It seems, however that the income-achievement gap is present at the onset of schooling and persists, but does not increase, through the child's educational lifecourse. This would suggest that, above and beyond differences in school quality, environmental and social factors are contributing to the gaps in educational achievement and attainment observed between high- and low-income students. These findings are supported by other researchers who have identified academic achievement gaps by race and income that are present by the time a child enters kindergarten (Brooks-Gunn et al., 2003; Magnuson et al., 2004; Yeung & Pfeiffer, 2009). Although there have been many efforts to measure and address school readiness through remediation or improved access to early childhood education, affecting meaningful change may necessitate the purposeful alignment of health and educational programming in areas that are traditionally outside their sphere of influence. For example, there are many early interventions such as prenatal care to reduce low-birth weight (Avchen, Scott & Mason, 2001), responsive parenting programs (Barth & Liggett-Creel, 2014; Weisleder & Fernald, 2013), reduction in the incidence and impact of poverty and housing instability (Burgard, Seefeldt & Zelner, 2012; Fantuzzo et al., 2013) that have historically operated in silos, but have known impacts on child academic and health outcomes.A report by the National Research Council (NRC) and the Institute of Medicine (IOM) described the interplay of behavioral, environmental, systemic and social factors in the relatively poor health outcomes of U.S. citizens compared to the health outcomes for people in other developed nations (NRC and IOM, 2013). The authors also described disparities in health outcomes by gender, ethnicity and geography; with variations in mortality of up to 25 years by census tract (Kulkarni et al. …

The Effect of School Quality on Black-White Health Differences: Evidence From Segregated Southern Schools

This study assesses the effect of black-white differences in school quality on black-white differences in health in later life resulting from the racial convergence in school quality for cohorts born between 1910 and 1950 in southern states with segregated schools. Using data from the 1984-2007 National Health Interview Surveys linked to race-specific data on school quality, we find that reductions in the black-white gap in school quality led to modest reductions in the black-white gap in disability.

Bender Performance and Socioeconomic Status in Mexican Children: A Cross-Cultural Study

Normative data are presented for Bender test performance, following the system of Koppitz, of 695 Mexican students between 5.0 and 12.1 yr. old (M = 8.7, SD = 2.01) and belonging to different socioeconomic status. The data are compared with the normative group of U.S. students used by Koppitz and with a representative sample of children from Barcelona, Spain. The results indicate that the total number of Bender errors decreased with increasing age of the children and that significant differences existed with respect to socioeconomic status. The comparison of these data with U.S. and Spanish children shows significant differences in all age groups, with the Mexican children scoring lowest. Differences in quality of schooling and in other aspects of education could explain the variability in Bender test performance.

Explaining the Performance Gap between Public and Private School Students

Data from the National Longitudinal Survey of Labor Market Experience for Youth are used to estimate the private school test score advantage. Regression results indicate that those who attend private schools score higher on the Armed Forces Qualifications Test. However, this advantage loses statistical significance with controls for family and school background. Decomposition of the private-public test score difference indicates that 78 percent of the gap can be explained by differences in average characteristics. Broken down further, 45 percent of the gap is due to differences in family background and 26 percent is due to differences in school quality.

Investing in knowledge? Information asymmetry and Indonesian schooling

This paper reports from a survey of media exposure and level of knowledge among senior high school students at various locations in Indonesia. Government budgets for education have recently been dramatically reduced in Indonesia and increasing financial burdens are put on the households, like in many other poor countries. There is a tendency to increasing differences in quality of schooling among social layers and geographical areas. Main conclusions in this research are that information asymmetry exists as a problem in society and that type of school and location matter more than media exposure for students’ knowledge level. Students in public schools generally score significantly higher than those in private institutions. Also, students’ level of knowledge tends to fall with decreasing level of geographical centrality. Our policy recommendations include increased public investment in quality schooling for all.

Investing in knowledge? Information asymmetry and Indonesian schooling

This paper reports from a survey of media exposure and level of knowledge among senior high school students at various locations in Indonesia. Government budgets for education have recently been dramatically reduced in Indonesia and increasing financial burdens are put on the households, like in many other poor countries. There is a tendency to increasing differences in quality of schooling among social layers and geographical areas. Main conclusions in this research are that information asymmetry exists as a problem in society and that type of school and location matter more than media exposure for students’ knowledge level. Students in public schools generally score significantly higher than those in private institutions. Also, students’ level of knowledge tends to fall with decreasing level of geographical centrality. Our policy recommendations include increased public investment in quality schooling for all.

The Black-White Test Score Gap Through Third Grade

This article describes basic facts regarding the Black-White test score gap over the first four years of school. Black children enter school substantially behind their White counterparts in reading and math, but including a small number of covariates erases the gap. Over the first four years of school, however, Blacks lose substantial ground relative to other races; averaging 0.10 standard deviations per school year. By the end of third grade, there is a large Black-White test score gap that cannot be explained by observable characteristics. Blacks are falling behind in virtually all categories of skills tested, except the most basic. None of the explanations we examine, including systematic differences in school quality across races, convincingly explain the divergent academic trajectory of Black students.

Education and Labor Market Discrimination

Using a model of statistical discrimination and educational sorting, we explain why blacks get more education than whites of similar cognitive ability, and we explore how the Armed Forces Qualification Test (AFQT), wages, and education are related. The model suggests that one should control for both AFQT and education when comparing the earnings of blacks and whites, in which case a substantial black-white wage differential emerges. We reject the hypothesis that differences in school quality between blacks and whites explain the wage and education differentials. Our findings support the view that some of the black-white wage differential reflects the operation of the labor market. (JEL I21, J15, J24, J31, J71)

Understanding the Black-White Test Score Gap in the First Two Years of School

In previous research, a substantial gap in test scores between white and black students persists, even after controlling for a wide range of observable characteristics. Using a newly available data set (the Early Childhood Longitudinal Study), we demonstrate that in stark contrast to earlier studies, the black-white test score gap among incoming kindergartners disappears when we control for a small number of covariates. Real gains by black children in recent cohorts appear to play an important role in explaining the differences between our findings and earlier research. The availability of better covariates also contributes. Over the first two years of school, however, blacks lose substantial ground relative to other races. There is suggestive evidence that differences in school quality may be an important part of the explanation. None of the other hypotheses we test to explain why blacks are losing ground receive any empirical backing.

Racial disparity in earnings and earnings growth: The case of young men

Evidence from the National Longitudinal Survey of Labor Market Experience for Youth indicates a vintage effect (lower black-white earnings ratios for older cohorts relative to younger cohorts), but an examination of longitudinal earnings ratios suggests such an effect can be attributed to intra-cohort deterioration of black earnings over the life cycle rather than to inter-cohort differences in school quality. Regression results indicate that the role of education in influencing continued wage growth on-the-job differs by race. More educated white males hold occupations with steeper experience-earnings profiles. The same can be said of blacks only at a lower level of statistical confidence. This findings implies that either labor market discrimination limits the earnings potential of black human capital or residual differences in school quality persist such that the education received by blacks does not have the same effect over the life cycle as the higher quality education received by whites.