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Program and policy effects
Children routinely benefit from being assigned a teacher who shares an identity with them, such as gender or ethnicity. We study how student beliefs impact teacher-student gender match effects, and how this varies across subjects with different societal beliefs about differential ability by gender. A simple model of belief formation predicts that match effects will be larger for students who believe they are of low ability, and be greater in subjects with more salient societal beliefs. We test these using data from Chinese middle schools, exploiting random assignment of students to teachers. In China, many people believe boys are innately better than girls at math. We find that being assigned a female math teacher helps low-perceived-ability girls and slightly harms low-perceived-ability boys, with no effects for other children. In English and Chinese – subjects with less salient societal beliefs – these patterns persist but diminish. This yields policy implications for the assignment of teachers to students.
Over 13 percent of US students participate in Special Education (SE) programs annually, at a cost of $40 billion. However, the effect of SE placements remains unclear. This paper uses administrative data from Texas to examine the long-run effect of reducing SE access. Our research design exploits variation in SE placement driven by a state policy that required school districts to reduce SE caseloads to 8.5 percent. We show that this policy led to sharp reductions in SE enrollment. These reductions in SE access generated significant reductions in educational attainment, suggesting that marginal participants experience long-run benefits from SE services.
Access to private schools and public charter schools might improve parent and student satisfaction through competitive pressures and improved matches between educators and students. Using a nationally representative sample of 13,436 students in the United States in 2016, I find that public charter schools and private schools outperform traditional public schools on six measures of parent and student satisfaction. Respondents with children in private schools also tend to report higher levels of satisfaction than respondents with children in public charter schools. The results are robust to various analytic techniques and specifications.
The My Brother’s Keeper (MBK) Challenge developed by President Obama supports communities that promote civic initiatives designed to improve the educational and economic opportunities specifically for young men of color. In Oakland, California, the MBK educational initiative features the African American Male Achievement (AAMA) program. The AAMA focuses on regularly scheduled classes exclusively for Black, male students and taught by Black, male teachers who focus on social-emotional training, African-American history, culturally relevant pedagogy, and academic supports. In this study, we present quasi-experimental evidence on the dropout effects of the AAMA by leveraging its staggered scale-up across high schools in the Oakland Unified School District (OUSD). We find that AAMA availability led to a significant reduction in the number of Black males who dropped out as well as smaller reductions among Black females, particularly in 9th grade.
We explore the potential for mobile technology to facilitate more frequent and higher-quality teacher-parent communication among a sample of 132 New York City public schools. We provide participating schools with free access to a mobile communication app and randomize schools to receive intensive training and guidance for maximizing the efficacy of the app. User supports led to substantially higher levels of communication within the app in the treatment year, but had few subsequent effects on perceptions of communication quality or student outcomes. Treatment teachers used the app less frequently the following year when they no longer received communication tips and reminders. We analyze internal user data to suggest organizational policies schools might adopt to increase the take-up and impacts of mobile communication technology.
Despite substantial evidence that resources and outcomes are transmitted across generations, there has been limited inquiry into the extent to which anti-poverty programs actually disrupt the cycle of bad outcomes. We explore how the effects of the United States’ largest early childhood program, Head Start, transfer across generations. We leverage the rollout of this federally funded, means-tested preschool program to estimate the effect of early childhood exposure among mothers on their children’s long-term outcomes. We find evidence of intergenerational transmission of effects in the form of increased educational attainment, reduced teen pregnancy, and reduced criminal engagement in the second generation.
This paper reports improvements in teacher job performance, as measured by student test scores, resulting from a program of (zero-) low-stakes peer evaluation. Teachers working at the same school observed and scored each other’s teaching. Students in randomly-assigned treatment schools scored 0.07σ higher on math and English exams (0.09σ lower-bound on TOT). Within each treatment school, teachers were further randomly assigned to roles: observer and observee. Teachers in both roles improved, perhaps slightly more for observers. The typical treatment school completed 2-3 observations per observee teacher. Variation in observations was generated partly by randomly assigning a low and high (2*low) dose of suggested number of observations. Benefits were quite similar across dose conditions.
Students’ level of academic skills at school entry are a strong predictor of later academic success, and focusing on improving these skills during the preschool years has been a priority during the past ten years. Evidence from two prior nationally representative studies indicated that incoming kindergarteners’ math and literacy skills were higher in 2010 than 1998, but no national studies have examined trends since 2010. This study examines academic skills at kindergarten entry from 2010 and 2017 using data from over 2 million kindergarten students. Results indicated kindergarteners in 2017 have slightly lower math and reading skills than in 2010, but that inequalities at school entry by race/ethnicity and school poverty level have decreased during this period.
The sustaining environments hypothesis refers to the popular idea, stemming from theories in developmental, cognitive, and educational psychology, that the long-term success of early educational interventions is contingent on the quality of the subsequent learning environment. Several studies have investigated whether specific kindergarten classroom and other elementary school factors account for patterns of persistence and fadeout of early educational interventions. These analyses focus on the statistical interaction between an early educational intervention – usually whether the child attended preschool – and several measures of the quality of the subsequent educational environment. The key prediction of the sustaining environments hypothesis is a positive interaction between these two variables. To quantify the strength of the evidence for such effects, we meta-analyze existing studies that have attempted to estimate interactions between preschool and later educational quality in the United States. We then attempt to establish the consistency of the direction and a plausible range of estimates of the interaction between preschool attendance and subsequent educational quality by using a specification curve analysis in a large, nationally representative dataset that has been used in several recent studies of the sustaining environments hypothesis. The meta-analysis yields small positive interaction estimates ranging from approximately .00 to .04, depending on the specification. The specification curve analyses yield interaction estimates of approximately 0. Results suggest that the current mix of methods used to test the sustaining environments hypothesis cannot reliably detect realistically sized effects. Our recommendations are to combine large sample sizes with strong causal identification strategies, and to study combinations of interventions that have a strong probability of showing large main effects.