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Billions of dollars are invested in opt-in, educational resources to accelerate students’ learning. Although advertised to support struggling, marginalized students, there is no guarantee these students will opt in. We report results from a school system’s implementation of on-demand tutoring. The take up was low. At baseline, only 19% of students ever accessed the platform, and struggling students were far less likely to opt in than their more engaged and higher achieving peers. We conducted a randomized controlled trial (N=4,763) testing behaviorally-informed approaches to increase take-up. Communications to parents and students together increase the likelihood students access tutoring by 46%, which led to a four-percentage point decrease in course failures. Nonetheless, take-up remained low, showing concerns that opt-in resources can increase—instead of reduce—inequality are valid. Without targeted investments, opt-in educational resources are unlikely to reach many students who could benefit.
The disruption of in-person schooling during the Covid-19 pandemic has affected students’ learning, development, and well-being. Students in Latin America and the Caribbean have been hit particularly hard because schools in the region have stayed closed for longer than anywhere else, with long-term expected adverse consequences. Little is known about which factors are associated with the slow in-person return to school in the region and how these factors have had differential effects based on students’ socio-economic status. Combining a longitudinal national survey of the Chilean school system and administrative datasets, we study the supply and demand factors associated with students’ resuming in-person instruction and the socio-economic gaps in school reopening in Chile in 2021. We defined socio-economic status based on parents’ education and household income. Our results show that in-person learning in 2021 was limited mainly by supply factors (i.e., sanitary, administrative, and infrastructure restrictions). However, once the supply restrictions decreased, many low-income students and their families did not resume in-person instruction. We found vast inequalities in face-to-face instruction by school’s socio-economic characteristics. On average, schools in the highest 10% of the socio-economic distribution had three times higher attendance rates than the remaining 90%. We found no significant differences between schools in the lowest 90% of the distribution. After exceptionally long school closures, most school authorities, students, and their families did not return to in-person instruction, particularly those of low socio-economic status. These inequalities in in-person instruction will expand existing disparities in students’ learning and educational opportunities.
Community schools are an increasingly popular strategy used to improve the performance of students whose learning may be disrupted by non-academic challenges related to poverty. Community schools partner with community based organizations (CBOs) to provide integrated supports such as health and social services, family education, and extended learning opportunities. With over 300 community schools, the New York City Community Schools Initiative (NYC-CS) is the largest of these programs in the country. Using a novel method that combines multiple rating regression discontinuity design (MRRDD) with machine learning (ML) techniques, we estimate the causal effect of NYC-CS on elementary and middle school student attendance and academic achievement. We find an immediate reduction in chronic absenteeism of 5.6 percentage points, which persists over the following three years. We also find large improvements in math and ELA test scores – an increase of 0.26 and 0.16 standard deviations by the third year after implementation – although these effects took longer to manifest than the effects on attendance. Our findings suggest that improved attendance is a leading indicator of success of this model and may be followed by longer-run improvements in academic achievement, which has important implications for how community school programs should be evaluated.
Youth voter turnout remains stubbornly low and unresponsive to civic education. Rigorous evaluations of the adoption of civic tests for high school graduation by some states on youth voter turnout remain limited. We estimate the impact of a recent, state-mandated civics test policy—the Civics Education Initiative (CEI)—on youth voter turnout by exploiting spatial and temporal variation in the adoption of CEI across states. Using nationally-representative data from the 1996-2020 Current Population Survey and a Difference-in-Differences analysis, we find that CEI does not significantly affect youth voter turnout. Our null results, largely insensitive to a variety of alternative specifications and robustness checks, provide evidence regarding the lack of efficacy of civic test policies when it comes to youth voter participation.
How much does family demand matter for child learning in settings of extreme poverty? In rural Gambia, families with high aspirations for their children’s future education and career, measured before children start school, go on to invest substantially more than other families in the early years of their children’s education. Despite this, essentially no children are literate or numerate three years later. When villages receive a highly-impactful, teacher-focused supply-side intervention, however, children of these families are 25 percent more likely to achieve literacy and numeracy than other children in the same village. Furthermore, improved supply enables these children to acquire other higher-level skills necessary for later learning and child development. We also document patterns of substitutability and complementarity between demand and supply in generating learning at varying levels of skill difficulty. Our analysis shows that greater demand can map onto developmentally meaningful learning differences in such settings, but only with adequate complementary inputs on the supply side.
How far is the world away from ensuring that every child obtains the basic skills needed to be internationally competitive? And what would accomplishing this mean for world development? Based on the micro data of international and regional achievement tests, we map achievement onto a common (PISA) scale. We then estimate the share of children not achieving basic skills for 159 countries that cover 98.1% of world population and 99.4% of world GDP. We find that at least two-thirds of the world’s youth do not reach basic skill levels, ranging from 24% in North America to 89% in South Asia and 94% in Sub-Saharan Africa. Our economic analysis suggests that the present value of lost world economic output due to missing the goal of global universal basic skills amounts to over $700 trillion over the remaining century, or 11% of discounted GDP.
School districts in the United States often borrow on the municipal bond market to pay for capital projects. Districts serving economically disadvantaged communities tend to receive lower credit ratings and pay higher interest rates. To remedy this problem, 24 states have established credit enhancement programs that promise to repay district debt when a district cannot do so, thereby enhancing the district’s credit rating. I rely on cross- and within-district variations to estimate the effect of receiving state credit enhancement on district bond interest rate, per-pupil capital spending, and student performance. State enhancement reduces district bond interest rates by 6% and increases per-student capital spending by 6% to 7%. It also reduces the disparity in interest rate and capital spending across districts serving lower and higher income families, with no discernible effect on test scores. I find no evidence that the amount of enhanced school debt is associated with significant changes in interest rates paid by state governments. Districts in states without such programs could have achieved cost savings in the range of $383 million to $1 billion from 2009 to 2019 had the states adopted similar programs.
There has been an explosion of special education research and new policies surrounding the topic of racial and ethnic disproportionality. Some recent research shifts focus to whether school context moderates findings (e.g., is a Black student less likely than a White student to receive special education services as the proportion of a school’s Black students increases?). We extend this emerging literature using eight years of elementary student-and school-level data from NYC public schools, examining more school contextual moderators, expanding racial categories, and distinguishing between cross-sectional and over-time differences. We find that student racial/ethnic composition, teacher racial composition, school size, concentration of poor students, and teachers’ perceptions of school climate all moderate disproportionality. These school context factors appear to be particularly salient for the classification of Black students, and most of these associations are driven by differences across schools, suggesting new avenues for researchers and levers for policy.
The distribution of teaching effectiveness across schools is fundamental to understanding how schools can address disparities in educational outcomes. Research and policy have recognized the importance of teaching effectiveness for decades. Five stylized facts predict that teachers should be differentially allocated across schools such that poor, Black and Hispanic students are taught by less qualified and less effective teachers. Yet, research is unclear whether these predictions have empirical support. Our purpose is to better understand whether there are meaningful differences in teacher effectiveness among schools. We find that poor, Black and Hispanic students are more likely to be taught by novice teachers when they live in more segregated MSAs. Moreover, the geographic nature of segregation varies across MSAs. Differentiating segregation within urban districts and segregation between urban districts and outlying districts in the same MSAs is essential to understanding poor students’ exposure to novice teachers and policies that address these disparities. We find that poor, Black and Hispanic students are 50 percent more likely to be exposed to at least one novice teacher during elementary school compared to their more affluent white peers. These results raise questions regarding the enforcement of ESSA’s requirements on the distribution of teacher qualifications and quality.