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Drew H. Bailey

Drew H. Bailey, Greg J. Duncan, Richard J. Murnane, Natalie Au Yeung.

A survey targeting education researchers conducted in November, 2020 provides predictions of how much achievement gaps between low- and high-income students in U.S elementary schools will change as a result of COVID-related disruptions to in-class instruction and family life. Respondents were asked to suppose that the pre-COVID achievement gap was 1.00 standard deviations. The median forecast for the jump in math achievement in elementary school by spring, 2021 was very large – a change from 1.00 to 1.30 standard deviations. The predicted increase in reading achievement gaps (a change from 1.00 to 1.25 standard deviations) was nearly as large. This implies that many teachers will face classrooms of students with much more heterogeneous learning needs in the fall of the 2021-22 school year than usual. We gauged predictions for the success of efforts by teachers and other educators to make up for lost ground by asking for predictions of achievement gaps in the spring of 2022. Few of the respondents to our survey thought that achievement gaps would revert to their pre-COVID levels. In fact, median predictions of achievement gaps fell very modestly– from 1.30 to 1.25 standard deviations for math and from 1.25 to 1.20 standard deviations for reading. We discuss some implications of these predictions for school district strategies (e.g., tutoring and other skill- building programs focused on individual students) to reduce learning gaps exacerbated by the pandemic.

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Drew H. Bailey, Jade M. Jenkins, Daniela Alvarez-Vargas.

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.

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Remy Pages, Dylan Lukes, Drew H. Bailey, Greg J. Duncan.

Using an additional decade of CNLSY data, this study replicated and extended Deming’s (2009) evaluation of Head Start’s life-cycle skill formation impacts in three ways. Extending the measurement interval for Deming’s adulthood outcomes, we found no statistically significant impacts on earnings and mixed evidence of impacts on other adult outcomes. Applying Deming’s sibling comparison framework to more recent birth cohorts born to CNLSY mothers revealed mostly negative Head Start impacts. Combining all cohorts shows generally null impacts on school-age and early adulthood outcomes.

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