Taking over the blog this week is Carolyn Sattin-Bajaj, a professor at the University of California, Santa Barbara. Before academe, Carolyn worked on secondary schools at the New York City Department of Education. Her research on topics like high school admissions and educational access has been featured in popular outlets like The New York Times and HuffPost, and she is the author of the terrific book Unaccompanied Minors. This week, Carolyn will be writing about how transportation policies influence the equity potential of school choice programs and how immigration enforcement and xenophobia in U.S. schools could have educational implications.
This blog was co-authored by Carolyn and Madeline Mavrogordato, a professor at Michigan State University and co-editor of the American Educational Research Journal, the flagship journal of the American Educational Research Association. Previously, Madeline served as a bilingual elementary school teacher in Texas and California.
For the past two decades, federal policy has required states to disaggregate student-performance data at the subgroup level. States must report student results separately by economically disadvantaged status, racial/ethnic background, English-learner (EL) and disability status. This reporting requirement is one of the enduring contributions of the No Child Left Behind Act (NCLB). It was also one component of the controversial law that was widely embraced across the political and ideological spectrum.
A lasting legacy of this requirement has been the now ubiquitous ability to compare performance and expose educational disparities across different subgroups. The results of a subgroup that performs higher on state assessments can no longer mask the academic performance of a subgroup that is lower performing. Take, for example, an elementary school in a district in which 15 percent of students are ELs. While the schoolwide proficient may be 90 percent, when broken down by subgroup, perhaps only 40 percent of EL students are proficient compared with 98 percent of their non-EL peers.
The variables for students with disabilities (SWDs) and ELs in most state-level datasets are particularly narrow as they tend to be dichotomous indicators of whether or not a student has been given such a classification. In other words, students are either classified as a SWD or not, or as an EL or non-EL. Constrained by existing data, researchers and practitioners continue to rely on gross categories that encompass all SWDs or all ELs and mask critical differences within these large and heterogeneous groups. With 13 percent of all public school students in the United States receiving special education services in the 2015-16 school year and 9.5 percent of students classified as ELs, these two student subgroups comprise an important constituency whose diverse educational experiences in U.S. schools warrant more careful monitoring.
The problem with relying on broad categories in analysis of educational phenomena is perhaps best illustrated by considering a major current policy issue: school choice. School choice participation among SWDs and ELs has emerged as a focal area for researchers interested in understanding the equity implications of school choice policies. Yet current discussions about the representation of SWDs and ELs in schools of choice tell only part of the story; school choice participation varies by students’ type of disability and recommended educational setting (for SWDs) and level of English proficiency or the number of years a student has been classified as EL.
Currently, the evidence is mixed about rates of SWD and EL enrollment in schools of choice relative to traditional public schools (TPS), in aggregate terms. The lack of consensus in the research demands a more accurate understanding of who is (and is not) being served by schools of choice and whether certain categories of ELs and SWDs are being systematically excluded. For SWDs, this means analyzing school compositions broken down by the type of student disability and the services mandated by the individualized education programs (IEP). For ELs, this could include students’ level of English proficiency, newcomer status, and how many students are former ELs—those reclassified as fluent English proficient.
Let’s start by taking a closer look at SWDs. The term “student with disabilities” is a catch-all encompassing a large, heterogeneous set of characteristics. The services called for in a student’s IEP may vary widely based on diagnoses and severity of disabilities—with highly variable associated costs for schools. Existing research shows that nationally, SWDs are slightly under-represented in the charter school population, and SWDs enrolled in charter schools generally have less severe forms of disability and are less expensive to educate than the SWDs attending TPSs. Charter schools tend to enroll higher proportions of students with a “specific learning disability” (e.g., dyslexia, dyscalculia, dysgraphia) and lower percentages of students with intellectual impairments and developmental delays. This is not exclusive to the charter sector of school choice; students with less severe disabilities were more likely to receive private school offers via a voucher program in a study of the Louisiana Scholarship Promise.
A similarly complex story emerges around EL student representation in schools of choice. EL students are slightly over-represented in charter schools, comprising 10.5 percent of the charter school population nationwide versus 10 percent of the overall U.S. public school population. Representation of ELs is certainly important, but it is necessary to dig deeper to truly compare EL students attending traditional public schools and those enrolled in schools of choice. In terms of level of English proficiency, for example, researchers documented that ELs who enroll in charter schools in New York City have a higher level of English proficiency on average than their peers in traditional public schools.
Evidence from the school choice context shows just how much more can be learned when data are further disaggregated and the salient information that is lost without such granularity. This extends far beyond school choice policies and beyond SWDs and ELs; richer understanding of patterns of student behaviors and outcomes (e.g., discipline, graduation rates) can be generated with more finely grained data across other subgroups of students. To do so, districts and states must collect and encourage the use of more detailed student-level information, which will produce more realistic estimates of whether policies and programs are (or are not) achieving desired goals, including advancing educational equity. Without this, policymakers and practitioners will default to relying on incomplete, and in some cases, misleading information about students’ educational pathways and performance and develop or expand policies and programs on the basis of limited data.
—Carolyn Sattin-Bajaj & Madeline Mavrogordato