Sage Journals: Discover world-class research

Abstract

A growing body of research uses state longitudinal data systems (SLDS) to study the special education teacher (SET) workforce in specific states, but these studies make different decisions about how to identify SETs within SLDS and link them to school and district data. We therefore used SLDS from three states—Massachusetts, Pennsylvania, and Washington—to explore the implications of these decisions for analyses of the SET workforce. While some methods used to identify SETs in prior literature (e.g., based on classroom assignments or position funding sources) produce estimates of the size of the SET workforce that are comparable to state-reported IDEA 618 data, using teacher certification to identify SETs substantially overestimates the size of the SET workforce in these states and can lead to misleading conclusions about turnover in these states. Other data decisions (e.g., how to handle multiple school assignments) have fewer implications for these analyses.

Keywords

quantitative methods research methods educational policy special education teachers preparation policy/service delivery teacher research retention

Get full access to this article

View all access options for this article.

References

Bettini

Cumming

M. M.

O’Brien

K. M.

Brunsting

N. C.

Ragunathan

Sutton

Chopra

(2020). Predicting special educators’ intent to continue teaching students with emotional or behavioral disorders in self-contained settings. Exceptional Children, 86(2), 209–228. https://doi.org/10.1177/0014402919873556

Bettini

Gilmour

A. F.

Williams

T. O.

Billingsley

(2020). Predicting special and general educators’ intent to continue teaching using conservation of resources theory. Exceptional Children, 86(3), 310–329. https://doi.org/ghm63q

Boe

E. E.

(2006). Long-term trends in the national demand, supply, and shortage of special education teachers. The Journal of Special Education, 40(3), 138–150. https://doi.org/10.1177/00224669060400030201

Brunsting

N. C.

Bettini

Rock

M. L.

Royer

D. J.

Common

E. A.

Lane

K. L.

Zeng

(2022). Burnout of special educators serving students with emotional-behavioral disorders: A longitudinal study. Remedial and Special Education, 43(3), 160–171.

Cancio

E. J.

Larsen

Mathur

S. R.

Estes

M. B.

Johns

Chang

(2018). Special education teacher stress: Coping strategies. Education and Treatment of Children, 41(4), 457–481. https://muse.jhu.edu/article/705292

Compton

M. V.

Appenzeller

Kemmery

Gardiner-Walsh

(2015). Itinerant teachers’ perspectives of using collaborative practices in serving students who are deaf or hard of hearing. American Annals of the Deaf, 160(3), 255–272.

Connelly

Graham

(2009). Student teaching and teacher attrition in special education. Teacher Education and Special Education, 32(3), 257–269. https://doi.org/bbg5sz

Cooc

Yang

(2016). Diversity and equity in the distribution of teachers with special education credentials: Trends from California. AERA Open, 2(4). https://doi.org/gcd5z4

Dewey

Sindelar

P. T.

Bettini

Boe

E. E.

Rosenberg

M. S.

Leko

(2017). Explaining the decline in special education teacher employment from 2005 to 2012. Exceptional Children, 83(3), 315–329. https://doi.org/gbm58j

10.

Feng

Sass

T. R.

(2013). What makes special-education teachers special? Teacher training and achievement of students with disabilities. Economics of Education Review, 36, 122–134.

11.

Gagnon

J. C.

Barber

B. R.

(2015). Identifying and implementing evidence-based practices in alternative educational settings. In Cook

B. G.

Tankersley

Landrum

T. J.

(Eds.), Advances in Learning and Behavioral Disabilities (pp. 225-271). Emerald Group.

12.

Gilmour

A. F.

(2020). Teacher certification area and the academic outcomes of students with learning disabilities or emotional/behavioral disorders. Journal of Special Education, 54(1), 40–50. https://doi.org/10.1177/0022466919849905

13.

Gilmour

A. F.

(2024). Teaching quality: An unexamined element of special education teacher turnover. Journal of Education Human Resources, 42(4), 458–498. https://doi.org/pfrd

14.

Gilmour

A. F.

Bartanen

Bettini

Feng

Klinenberg

Mason-Williams

Redding

Scott

L. A.

Theobald

(2025, March). The composition, distribution, and stability of the special education teacher workforce in seven states SPARC Center Working Paper No. 01-1025. https://sparccenter.org/research-findings/composition-distribution-and-stability-special-education-teacher-workforce-seven

15.

Gilmour

A. F.

Feng

Theobald

(2025). Leveraging administrative data to study the special education teacher workforce. Remedial and Special Education, 46(2), 118–131. https://doi.org/10.1177/07419325241262971

16.

Gilmour

A. F.

Nuegebauer

S. R.

Sandilos

L. E.

(2022). Moderators of the association between teaching students with disabilities and general education teacher turnover. Exceptional Children, 88(4), 401–420. https://doi.org/10.1177/00144029221081239

17.

Gilmour

A. F.

Stiefel

(2025). Leveraging large asministrative data for special education policy analysis: Recent contributions and future directions. Remedial and Special Education, 46(2), 95–105. https://doi.org/10.1177/07419325241268858

18.

Gilmour

A. F.

Wehby

J. H.

(2020). The association between teaching students with disabilities and teacher turnover. Journal of Educational Psychology, 112(5), 1042–1060. https://doi.org/10.1037/edu0000394

19.

Goldman

Gilmour

A. F.

(2021). Educating students with autism spectrum disorder: Is teacher certification area associated with academic outcomes? Journal of Autism and Developmental Disorders, 51, 550–563. https://doi.org/10.1007/s10803-020-04561-w

20.

Higher Education Opportunity Act. (2008), Pub. L. No. 110-315, 122 Stat. 3078. https://www.govinfo.gov/app/details/PLAW-110publ315

21.

Hoge

Rubenstein-Avila

(2014). Out of sight, out of mind: A case study of an alternative school for students with emotional disturbance (ED). Qualitative Research in Education, 3, 295–319.

22.

IDEA Part B Personnel SY 2022-23. (n.d.). https://data.ed.gov/dataset/docs/idea-section-618-state-part-b-personnel. https://data.ed.gov/dataset/docs/idea-section-618-state-part-b-personnel

23.

Kaler

Theobald

Jones

Bettini

(2025). Impacts of staff turnover on test scores for students with and without disabilities (CALDER Working Paper No. 319-0525).

24.

Mason-Williams

(2015). Unequal opportunities: A profile of the distribution of special education teachers. Exceptional Children, 81(2), 247–262. https://doi.org/f6xrzj

25.

Mason-Williams

Bettini

Gagnon

J. C.

(2017). Access to qualified special educators across elementary neighborhood and exclusionary schools. Remedial and Special Education, 38(5), 297–307. https://doi.org/gcs4v5

26.

Mason-Williams

Bettini

Peyton

Harvey

Rosenberg

Sindelar

P. T.

(2020). Rethinking shortages in special education: Making good on the promise of an equal opportunity for students with disabilities. Teacher Education and Special Education, 43(1), 45–62. https://doi.org/10.1177/0888406419880352

27.

Miller

M. D.

Brownell

M. T.

Smith

S. W.

(1999). Factors that predict teachers staying in, leaving, or transferring from the special education classroom. Exceptional Children, 65, 201–218. https://doi.org/10.1177/001440299906500206

28.

Nguyen

T. D.

Pham

L. D.

Crouch

Springer

M. G.

(2020). The correlates of teacher turnover: An updated and expanded meta-analysis of the literature. Educational Research Review, 31, 100355.

29.

Nguyen

T. D.

Redding

Gilmour

A. F.

Bettini

(2024). No child left behind and the individuals with disabilities education act: Examining special educators’ outcomes. Remedial and Special Education, 45(3), 139–151. https://doi.org/m899

30.

Pendola

Perrone

(2025). From school to school: Examining the contours of within-field switching in the special education teacher labor market. AERA Open, 11. https://doi.org/pvnw

31.

Peyton

D. J.

Acosta

Harvey

Pua

D. J.

Sindelar

P. T.

Mason-Williams

Dewey

Fisher

T. L.

Crews

(2021). Special education teacher shortage: Differences between high and low shortage states. Teacher Education and Special Education, 44(1), 5–23. https://doi.org/ggqmx2

32.

Ronfeldt

Loeb

Wyckoff

(2013). How teacher turnover harms student achievement. American Educational Research Journal, 50(1), 4–36. https://doi.org/dnb4

33.

Steinbrecher

T. D.

McKeown

Walther-Thomas

(2013). Comparing validity and reliability in special education Title II and IDEA data. Exceptional Children, 79(3), 313–327. https://doi.org/10.1177/001440291307900301

34.

Theobald

Goldhaber

Holden

Stein

(2022). Special education teacher preparation, literacy instructional alignment, and reading achievement for students with high-incidence disabilities. Exceptional Children, 88(4), 381–400. https://doi.org/kcgr

35.

Theobald

Goldhaber

Naito

Stein

(2021). The special education teacher pipeline: Teacher preparation, workforce entry, and retention. Exceptional Children, 88(1), 65–80. https://doi.org/10.1177/00144029211010162

36.

Theobald

Gilmour

Lachlan-Hache

Bettini

Jones

(2025). The impact of a $10,000 bonus on special education teacher shortages in Hawai’i. Educational Evaluation and Policy Analysis. https://doi.org/g86fmz

37.

U.S. Department of Education. (2022). National Teacher and Principal Survey (NTPS), 2020-21. https://nces.ed.gov/programs/digest/d22/tables/dt22_209.42.asp

38.

U.S. Department of Education. (2023). Annual report to congress on the implementation of the Individuals with Disabilities Education Act. https://data.ed.gov/dataset/idea-section-618-data-products

39.

U.S. Department of Education, Office of Special Education Programs. (2024). IDEA Section 618 Data Products. https://data.ed.gov/dataset/idea-section-618-data-products

40.

Wojcik

A. J.

Hicks

Scott

L. A.

Thoma

C. A.

Bowman

R. W.

Frazier

(2023). A comparison of service time and racial categories within traditional and alternative route internship programs for special education licensure. Teacher Education and Special Education, 46(2), 162–177. https://doi.org/10.1177/08884064221119166

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.04 MB

0.00 MB