Exploring the Relationship Between School Transformation and Inclusion: A Bayesian Multilevel Longitudinal Analysis
AbstractGrounded in research and federal law, inclusive education is a right and preferred placement for all learners with disabilities receiving special education services. However, most students in the U.S. education system do not have access to inclusive education and few models are available to demonstrate how schools can develop and implement inclusive services. The purpose of this study was to describe the outcomes of one such endeavor, the SWIFT technical assistance model, aimed at transforming schools to develop inclusive, effective instruction for all students. Multilevel multinomial modeling was used to predict rates of inclusion over time for a subset of students with disabilities in schools participating in SWIFT technical assistance. The findings suggest schools did become more inclusive in their services, with many students predicted to be served in less restrictive general education placements and others no longer requiring special education services. Implications for inclusive education are provided.