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Meghan McCormick

Meghan McCormick, Cullen MacDowell, Christina Weiland, JoAnn Hsueh, Michelle Maier, Mirjana Pralica, Samuel Maves, Catherine Snow, Jason Sachs.

This study uses implementation fidelity data from PreK to 1st grade in the Boston Public Schools (BPS) to measure instructional alignment and examine whether stronger alignment is associated with sustained benefits of BPS PreK on children’s language, literacy, and math skills through first grade. The study includes N = 498 students (mean age = 5.47, SD = 0.30 in K fall). Children who experienced strong instructional alignment across grades had faster gains in literacy (SD = .47) and math (SD = .28) skills through the spring of first grade compared with non-BPS PreK attenders. Mis-alignment predicted faster convergence in literacy skills. Results highlight that instructional alignment may help to sustain the initial benefits of PreK programs through first grade in a subset of outcome domains. Implications for further research measuring alignment in a broader range of settings and implications for practice are discussed.

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Meghan McCormick, Mirjana Pralica, JoAnn Hsueh, Christina Weiland, Amanda Weissman, Samantha Xia, Anna Shapiro, Cullen MacDowell, Samuel Maves, Anne Taylor, Jason Sachs.

This study leverages six years of public prekindergarten (PreK) and kindergarten data (N = 22,469) from the Boston Public Schools (BPS) to examine enrollment in BPS PreK from 2012–2017 for students from different racial/ethnic, socioeconomic, and linguistic groups. The largest differences in enrollment emerged with respect to race and ethnicity—and for enrollment in programs in higher-quality schools (defined as schools scoring in the top quartile on third grade standardized tests)—with disparities increasing over time. Although there were no differences across groups in proximity to BPS PreK programs in general, Black students lived about a quarter of a mile further than their White peers from the nearest program in a higher-quality school, with gaps widening over time. Closer proximity was associated with a higher likelihood of enrollment in a program in a higher-quality school. Implications for future research and policy are discussed.

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Christina Weiland, Rebecca Unterman, Susan Dynarski, Rachel Abenavoli, Howard Bloom, Breno Braga, Anne-Marie Faria, Erica Greenberg, Brian A. Jacob, Jane Arnold Lincove, Karen Manship, Meghan McCormick, Luke Miratrix, Tomás E. Monarrez, Pamela Morris-Perez, Anna Shapiro, Jon Valant, Lindsay Weixler.

Lottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs.  Our collaborative network of five research teams applying this design in early education and methods experts has identified six challenges that need to be carefully considered in this next context: 1) available baseline covariates may not be very rich; 2) limited data on the counterfactual; 3) limited and inconsistent outcome data; 4) weakened internal validity due to attrition; 5) constrained external validity due to who competes for oversubscribed programs; and 6) difficulties answering site-level questions with child-level randomization.  We offer potential solutions to these six challenges and concrete recommendations for the design of future lottery-based early education studies.

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Appendix140.99 KB

Christina Weiland, Meghan McCormick, Jennifer Duer, Allison Friedman-Kraus, Mirjana Pralica, Samantha Xia, Milagros Nores, Shira Mattera.

Nearly all states with public prekindergarten programs use mixed-delivery systems, with classrooms in both public schools and community-based settings.  However, experts have long raised concerns about systematic inequities by setting within these public systems.  We used data from five large-scale such systems that have taken steps to improve equity by setting  (Boston, New York City, Seattle, New Jersey, and West Virginia) to conduct the most comprehensive descriptive study of prekindergarten setting differences to date. Our public school sample included 2,395 children in 383 classrooms in 152 schools, while our community-based sample is comprised of 1,541 children in 201 classrooms in 103 community-based organizations (CBOs).  We examined how child and teacher demographic characteristics, structural and process quality features, and child gains differed by setting within each of these systems.  We found evidence of sorting of children and teachers by setting within each locality, including of children with higher baseline skills and more educated teachers into public schools. Where there were differences in quality and children’s gains, these tended to favor public schools.  The localities with fewer policy differences by setting – NJ and Seattle – showed fewer differences in quality and child gains.  Our findings suggest that inequities by setting are common, appear consequential, and deserve more research and policy attention.  

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