Reclaiming Assessment for Inclusion: How Data Practices Can Serve,Not Sort,Students with Low-Incidence Disabilities

Abstract

Assessment systems in U.S. public schools often fail students with low-incidence disabilities (LIDs), not because these students cannot achieve, but because the systems were not built with them in mind. Although multitiered systems of support (MTSS) are designed to leverage data for responsive instruction, the reality is that Tier 3 supports are almost always served in segregated settings. Instead, data often becomes a sorting mechanism, pushing students with LIDs into segregated programs under the guise of “support.” It is also important to name that standardized assessment systems harm many historically marginalized groups, including emergent bilinguals, racially minoritized students, and students living in poverty. My critique focuses on students with LIDs because they are the most consistently and systematically excluded from general education by data practices. By centering them, we are not narrowing the conversation; we are illuminating the most urgent case study in how inequitable data systems perpetuate segregation.

It is also essential to recognize that students with LIDs do not experience disability in isolation. Many are also students of color, emergent bilinguals, or students navigating poverty, and their experiences with assessment are shaped at the intersection of ableism, racism, linguicism, and classism. Centering LIDs therefore illuminates how multiple systems of inequity converge within current data practices. This commentary argues that inclusion is not at odds with individualized instruction or rigorous data use. Drawing on Street Data (Safir & Dugan, 2021) and other frameworks for humanizing assessment, I call for a shift from deficit-oriented benchmarking toward asset-based, embedded data practices that honor student voice, context, and real-time learning. I center the needs of students with intellectual and developmental disabilities (IDDs) and autism, highlighting how inclusion can thrive when assessments serve as bridges, not barriers. Ultimately, I advocate for school leaders and policymakers to realign data systems to promote daily Tier 3 supports within general education, building schools where equity is not measured by proximity alone, but by access to meaningful instruction and community.