The Composition, Distribution, and Stability of the Special Education Teacher Workforce in Seven States

• In Event: The Special Education Teacher Workforce: New Evidence on Composition, Distribution, and Effectiveness Across Contexts

Abstract

Special education teacher (SET) staffing challenges have existed as long as the federal public mandate for special education (Mason-Williams et al., 2020). Staffing challenges impede US schools’ capacity to provide a free, appropriate public education to all students with disabilities (Mason-Williams et al., 2020). They have become especially concerning in the face of increasing teacher attrition and declining enrollment in teacher preparation programs (Goldhaber & Theobald, 2023; Nguyen et al., 2023).

This paper uses data from state longitudinal data systems (SLDS) in Hawai’i, Indiana, Massachusetts, Pennsylvania, Texas, Virginia, and Washington, as well as data from the Common Core of Data (CCD) from 2017/18-2022/23, to study the composition, distribution, and stability of the workforce in these states. Specifically, we address three research questions:

1. To what extent did the composition of the SET workforce vary across states, districts, schools, and over time?
2. To what extent did the distribution of SETs vary across states, districts, schools, and over time?
3. To what extent did the stability of SETs vary across states, districts, schools, and over time?

We measure the composition of SETs using measures of their experience, degrees, race or ethnicities, gender, and whether they were fully certified in special education. We examine the distribution of these characteristics across district and school characteristics. Finally, we calculate attrition from the special education workforce, mobility between schools, and switching to general education.

Descriptive results revealed several key findings:

1. SET certification rates were not always lower than other teacher certification rates.
2. SET attrition rates were higher than attrition rates for other teachers.
3. SET attrition rates declined after the first year of the pandemic, spiked, then stabilized.
4. In most states, differences in stability exacerbated inequities across schools.

Our full regression analyses led to four main conclusions:

1. The composition of the SET workforce varied widely across states, particularly the percentage of the teacher workforce who were SETs and the percentage of the SET workforce who were non-white.
2. The variability in stability based on schools’ student characteristics was largely due to the unequal distribution of novice SETs and SETs without full certification.
3. Turnover varied by school type, with SETs in charter schools leaving teaching at much higher rates than other SETs.
4. The magnitude, distribution, and type of instability varied widely across the seven states.

These results support the importance of considering SET staffing challenges across different states and contexts, rather than assuming that national trends reflect contextual realities. Many SET workforce challenges varied across and within states suggesting that policy solutions for addressing SET staffing challenges should be tailored to specific contexts. For example, policies that target SET certification rates are likely more effective in states where the certification rates of SETs are lower than other teachers. This first comprehensive, longitudinal cross-state analysis of the composition, distribution, and stability of the workforce highlights the importance of finding policy solutions to address varied challenges and ensure students with disabilities have access to SETs.

Authors

• Allison F. Gilmour, American Institutes for Research

• Brendan Bartanen, University of Virginia

• Elizabeth A. Bettini, Boston University

• Li Feng, Texas State University

• Jamie Klinenberg, American Institutes for Research

• Loretta Mason-Williams, Binghamton University - SUNY

• Christopher Redding, University of Florida

• LaRon A. Scott, University of Virginia

• Roddy Theobald, American Institutes for Research