Project Activities
The research team will conduct a sequential mixed methods design in partnership with four SEAs (California, New York, Washington, and Wisconsin) with significant state and LEA contextual variation (size, demographics, urbanicity) to consider the role of context across the various levels of the education ecosystem in evaluating attempts to address disproportionality via IDEA over time.
Structured Abstract
Setting
The research project will use data from SEAs in California, New York, Washington, and Wisconsin.
Sample
The sample for the quantitative analyses will include every K-12 public LEA from each of the four partner SEAs from the 2010-2022 academic school years, which is inclusive of 10,777,520 students. The sample for the qualitative analysis will include approximately 296 interviews with SEAs, 40 LEAs, 80 school-based personnel, 80 caregivers of students with disabilities, and 80 students with disabilities, with a focus on racialized and minoritized students across locales. The primary target disability categories include specific learning disabilities, intellectual disability, emotional disturbance, speech and language impairment, other health impairment, and autism.
Factors
Key factors under investigation include LEA locale (urban, suburban, rural, town), demographic characteristics (student and school community), student-level academic and behavior factors (risk for classification, placement, and/or school suspension), and qualitative factors related to the organizational enactment of IDEA racial equity policy and stakeholder experience within LEAs legally cited for racial disproportionality.
Research design and methods
The research team will use a sequential mixed methods design. First, they will analyze extant SEA and LEA data to understand what factors relate to LEAs exiting, fluctuating, or remaining cited via IDEA for racial disproportionality over time across locales. Then, they will analyze the data to evaluate the organization's programming—such as restorative practices—and other features associated with reductions in disproportionality at the school level, and the impact of these features on timing and risk of learner outcomes. The research team will then employ a stratified sampling technique for a case-oriented analysis of the qualitative interview and document data. They will use qualitative coding methods that begin at the granular level and successively build explanations, using deductive and inductive processes, to uncover malleable factors related to IDEA racial equity policy remedies. Integrating findings from quantitative and qualitative analyses will result in insights that advance understanding of malleable factors and moderators that impact policy implementation processes and efforts to address racial inequity in special education.
Control condition
Due to the nature of the research, there is no control condition.
Key measures
At the SEA level, the research team will measure IDEA racial equity citation patterns over time and the demographic factors that contribute to these citations. At the student level, they will measure student risk for classification, placement, and/or disciplinary outcomes and how school variables, including potential school-level programming, impacts racial disproportionalities. Semi-structured interviews with SEA and LEA officials and school-based personnel, along with review of SEA and LEA policy documents, will measure how stakeholders interpret IDEA racial equity policy and use it to structure special education service delivery at the local level. Semi-structured interviews with learners with disabilities and their caregivers will measure the lived experiences of those impacted by racial disproportionality at the local level.
Data analytic strategy
For the quantitative phase of the project, the research team will conduct sequence analysis, event history analysis, and multilevel modeling to explore the factors of interest. The longitudinal data will then be paired with qualitative data sources using an explanatory sequential mixed methods design and joint display analyses.
Products and publications
Products: The products of this project will include information regarding the associations between variations in education contexts, IDEA policy use, and effectiveness of efforts to address racial disproportionality in special education across varied contexts. The project will also result in a final dataset to be made publicly available as well as peer-reviewed publications and presentations, and additional dissemination products that reach education stakeholders such as practitioners and policymakers.
ERIC Citations: Find available citations in ERIC for this award here.
Supplemental information
Co-Principal Investigators: Aylward, Alexandra; Cruz, Rebecca A.; Strassfeld, Natasha
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.