An Intersectional Analysis of Disproportionality of Dual Language Learners in Special Education in Virginia: A Mixed Methods Study
Year: 2020
Type: dissertation
Study design: Observational Study
Abstract: The disproportionality of dual language learners (DLLs) in special education has been a persistent and complex issue for decades. These students have multidimensional identities that require a look at how they are positioned in school systems and the broader social landscape. Using a multilevel model of intersectionality and an explanatory mixed methods design, this study examines how social categories, practice, and policies influence the representation of DLLs in special education in Virginia, a state where DLLs represented 13 percent of the total student population in 2018-19. Findings from this study reveal overrepresentation and underrepresentation of 63 DLL subgroups using nuanced variations by race, ethnicity, gender, and socioeconomic status. Findings also show a significant decrease in projected DLL relative risk for special education services in Virginia’s school divisions from 2015 to 2018, when the proportion of DLLs with disabilities is controlled. In 2015, federal and state agencies provided guidance on the eligibility process for DLLs who are suspected of having a disability. Interview responses with education stakeholders elucidate how the larger social and political landscape and perceptions of ability impact DLL eligibility processes and outcomes for special education services. Implications for practice, policy, and research will be discussed.
DOI: 10.25772/1pf9-9621
Author: Cuba, Melissa
Language: English
Subfield: Linguistics and Language
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3021527504