Modeling the Time-Varying Nature of Student Exceptionality Classification on Achievement Growth

Abstract

Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state’s mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four alternative growth models for students with and without disabilities with different specifications of disability classification as time-variant (TVC) or time-invariant (TIC) covariates. Although model fit statistics were inconsistent in endorsing a single model, we found that the TIC results were generally preferable to the TVC; however, the choice of model specification may rest on the purpose of the researcher and goals of representing the influence of covariates on growth.

Examining Longitudinal Patterns of Special Education Service Receipt

“…This is important because estimates vary regarding the number of students who exit special education. Studies have estimated that anywhere from 7% to 22% of students have discontinued special education services, and 4% to 24% continued to receive services but changed their primary disability classification (Carlson et al, 2008; Carlson & Parshall, 1996; Halgren & Clarizio, 1993; Marder, 2009; Nese et al, 2017; D. Walker et al, 1988; Ysseldyke & Bielinski, 2002). Entrance rates to special education may peak prior to fourth grade, and exit rates peak between Grades 4 and 6 (Nese et al, 2017).…”

“…Studies have estimated that anywhere from 7% to 22% of students have discontinued special education services, and 4% to 24% continued to receive services but changed their primary disability classification (Carlson et al, 2008; Carlson & Parshall, 1996; Halgren & Clarizio, 1993; Marder, 2009; Nese et al, 2017; D. Walker et al, 1988; Ysseldyke & Bielinski, 2002). Entrance rates to special education may peak prior to fourth grade, and exit rates peak between Grades 4 and 6 (Nese et al, 2017). The wide range in estimated prevalence of students who exit out of special education may exist because few studies utilized a nationally representative sample (Carlson et al, 2008; Marder, 2009), with most using state (Carlson & Parshall, 1996; Nese et al, 2017; Ysseldyke & Bielinski, 2002) or community samples (Halgren & Clarizio, 1993; D. Walker et al, 1988).…”

“…Accurately determining when and which students with disabilities (SWD) need special education services is an important and enduring educational goal. Not only are special education services costly to implement (Dhuey & Lipscomb, 2013; Hanushek et al, 2002), but there is a well-documented achievement gap between students with and without disabilities (Nese et al, 2017; Schulte & Stevens, 2015; Ysseldyke & Bielinski, 2002). This has led some to theorize that special education services are stigmatizing or ineffective, and particularly for students of color (Burns & Ysseldyke, 2009; Shifrer, 2013).…”

“…This has led some to theorize that special education services are stigmatizing or ineffective, and particularly for students of color (Burns & Ysseldyke, 2009; Shifrer, 2013). Yet, research has also demonstrated that the size of this achievement gap may depend on the timing at which disability status is measured—whether as a discrete, time-invariant event (“ever” disabled) or whether students are persistently reported to have a disability (“always” disabled; Nese et al, 2017; Schulte & Stevens, 2015; Ysseldyke & Bielinski, 2002). This research implies that it may be inappropriate to draw longitudinal conclusions from a measure of special education obtained from only one time point, as some SWD may discontinue services and display better long-term outcomes than others who continue to receive services.…”

Changes in Status and Performance Over Time for Students With Specific Learning Disabilities

“…First, an assumption is made that subgroups are well defined and stable over time even though students’ special education status can change from year to year (Nese, Stevens, Schulte, Tindal, & Elliott, in press; Schulte & Stevens, 2015). This assumption becomes problematic when some student characteristics (e.g., being with a disability and/or with a specific language proficiency) are changing at the same time progress is being made on growth models (which also may be different at various ages).…”