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A wide research base has documented the unequal access to and enrollment in K-12 gifted and talented services and other forms of advanced learning opportunities. This study extends that knowledge base by integrating multiple population-level datasets to better understand correlates of access to and enrollment in gifted and talented services, seventh-grade Algebra 1, and eighth-grade Geometry. Results show that states vary widely with some serving 20% of their students as gifted while others serve 0%. Similarly, within-district income segregation, income-related achievement gaps, and the percent of parents with a college degree are the dominant predictors of a school offering these opportunities and the size of the school population served.
Brown v. Board (1954) catalyzed a nationwide effort by the federal judiciary to desegregate public schools by court order, representing a major achievement for the U.S. civil rights movement. Four decades later, courts began dismissing schools from desegregation decrees in a staggered fashion, causing their racial homogeneity to rise. I leverage this exogenous source of variation in the racial mix of schools released from court orders between 1990 and 2014 to explore two key aspects of how whites react to attending schools with students of color. First, contemporaneous survey data indicate that as schools re-segregated, white students in these schools expressed more favorable attitudes towards black and Latino students. Second, present-day voter records from six Southern states of white students in schools that re-segregated show that they are significantly more likely to identify with the more racially liberal party -- the Democrats -- today. The findings are consistent with white students experiencing resegregation as a reduction in social threat, and indicate that school desegregation efforts may have caused life-long shifts among white students toward racial and political conservatism.
Growing evidence shows that a student's growth mindset (the belief that intelligence is malleable) can benefit their academic achievement. However, due to limited information, little is known about how a teachers’ growth mindset affects their students’ academic achievement. In this paper, we study the impact of teacher growth mindset on academic achievement for a nationwide sample of 8th and 10th grade students in Chile in 2017. Using a student fixed effect model that exploits data from two subject teachers for each student, we find that being assigned to a teacher with a growth mindset increases standardized test scores by approximately 0.02 standard deviations, with larger effects on students with high GPAs and particularly on students in low socioeconomic schools.
A growing body of research shows that students benefit when they are demographically similar to their teachers. However, less is known about how matching affects social-emotional development. We investigate the effect of teacher-student race and gender matching for middle school students in six charter management organizations. Using a student fixed effects strategy exploiting changes over time in the proportion of demographic matching in a school-grade, we estimate matching’s effect on self-reports of interpersonal and intrapersonal social-emotional skills, test scores, and behavioral outcomes. We find improvements for Black and female students in interpersonal self-management and grit when they are matched to demographically similar teachers. We also find demographic matching leads to reductions in absences for Black students and improved math test scores for females. Our findings add to the emerging teacher diversity literature by showing its benefits for Black and female students during a critical stage of social-emotional development in their lives.
Research consistently demonstrates that tutoring interventions have substantial positive effects on student learning. As a result, tutoring has emerged as a promising strategy for addressing COVID-related learning loss and affording greater educational opportunities for students living in poverty. The effectiveness of tutoring programs, however, varies greatly, and these variations may drive differential gains in student learning. Therefore, determining the program characteristics that do and do not drive positive student outcomes will be key to providing guidance for policymakers and practitioners who want to implement high-impact tutoring at scale. Our goal is to highlight the programs, characteristics, and conditions that evidence suggests make for effective tutoring and to create an evidence-based framework for delivering and evaluating tutoring interventions. In addition, we identify promising questions for future research.
A growing literature uses value-added (VA) models to quantify principals' contributions to improving student outcomes. Principal VA is typically estimated using a connected networks model that includes both principal and school fixed effects (FE) to isolate principal effectiveness from fixed school factors that principals cannot control. While conceptually appealing, high-dimensional FE regression models require sufficient variation to produce accurate VA estimates. Using simulation methods applied to administrative data from Tennessee and New York City, we show that limited mobility of principals among schools yields connected networks that are extremely sparse, where VA estimates are either highly localized or statistically unreliable. Employing a random effects shrinkage estimator, however, can alleviate estimation error to increase the reliability of principal VA.
We provide a descriptive analysis of within-school and neighborhood similarity in high school applications in New York City. We depart from prior work by examining similarity in applications to specific schools rather than preferences for school characteristics. We find surprisingly low similarity within schools and neighborhoods, but substantial variation by race and prior achievement. White and Asian students are more likely to have choices in common relative to Black and Hispanic students, a difference that persists after controlling for achievement and location. Likewise, higher-achieving students are more likely to have choices in common, conditional on other student characteristics and location. An implication is that students’ likelihood of attending high school without any peers from their middle school or neighborhood varies by student background.
We provide novel evidence on the causal impacts of student absences in middle and high school on state test scores, course grades, and educational attainment using a rich administrative dataset that tracks the date and class period of each absence. We use two similar but distinct identification strategies that address potential endogeneity due to time-varying student-level shocks by exploiting within-student, between-subject variation in class-specific absences. We also leverage information on the timing of absences to show that absences that occur after the annual window for state standardized testing do not affect test scores, providing a further check of our identification strategy. Both approaches yield similar results. We nd that absences in middle and high school harm contemporaneous student achievement and longer-term educational attainment: On average, missing 10 classes reduces math or English Language Arts test scores by 3-4% of a standard deviation and course grades by 17-18% of a standard deviation. 10 total absences across all subjects in 9th grade reduce both the probability of on-time graduation and ever enrolling in college by 2%. Learning loss due to school absences can have profound economic and social consequences.
At least 25 million K-12 students in the U.S.—disproportionately children of color from low-income families—have been physically out of school for a full year due to the COVID-19 pandemic. These children are at risk of significant academic, social, mental, and physical harm now and in the long-term. We must determine how to help all students gain access to safe, in-person schooling. In this interdisciplinary Viewpoint, we review the literature about the association between school reopening and COVID-19 transmission rates, and about the political, social, and environmental conditions that shape families’ and teachers’ choices to return to in-person schooling. Even though schools can safely be opened with appropriate mitigation measures, we find four reasons for schooling hesitancy: high community transmission rates; the Trump administration’s politicization of school re-openings in Summer 2020; long-term histories of mutual mistrust and racialized disinvestment in urban districts; and rational calculation about vulnerability due to the social determinants of health that have led Black and Latinx parents disproportionately to keep their children at home and White families disproportionately to send their children to school. Given the deep interconnections between the social determinants of health and of learning, and between schooling hesitancy and community vulnerability, stark inequities in in-person schooling access and take-up are likely to persist. In addition to ramping up safe and speedy school reopening now, we must make a long-term commitment to supporting schools as both sites of and contributors to public health, especially in historically marginalized communities.
Standardized assessments are widely used to determine access to educational resources with important consequences for later economic outcomes in life. However, many design features of the tests themselves may lead to psychological reactions influencing performance. In particular, the level of difficulty of the earlier questions in a test may affect performance in later questions. How should we order test questions according to their level of difficulty such that test performance offers an accurate assessment of the test taker's aptitudes and knowledge? We conduct a field experiment with about 19,000 participants in collaboration with an online teaching platform where we randomly assign participants to different orders of difficulty and we find that ordering the questions from easiest to most difficult yields the lowest probability to abandon the test, as well as the highest number of correct answers. Consistent results are found exploiting the random variation of difficulty across test booklets in the Programme for International Student Assessment (PISA), a triannual international test, for the years of 2009, 2012, and 2015, providing additional external validity. We conclude that the order of the difficulty of the questions in tests should be considered carefully, in particular when comparing performance between test-takers who have faced different order of questions.