Service Delivery Models and Outcomes for Students With Disabilities

Abstract

In this systematic literature review, we examine the corpus of empirical studies in education that use administrative data (i.e., population-level data) to describe and estimate the impacts of service delivery models for specially designed instruction on outcomes for students identified with special education needs. We focus on studies that use quantitative data analysis—either descriptive or causal—to answer questions about the relationship between special education service delivery models and student outcomes. We analyze seven studies, each of which finds a positive relationship between more time spent in general education classrooms and outcomes for students with disabilities (SWDs). In our analysis, we discuss the affordances and limitations of this type of analysis and opportunities for the field to expand data collection and analysis of population-level data in a way that better illuminates the state of special education services, both in the present and longitudinally, for SWDs.

Keywords

academic achievement inclusion special education quantitative research methodology

Get full access to this article

View all access options for this article.

References

Angrist

J. D.

Pischke

J. S.

(2009). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press. http://doi.org/10.1515/9781400829829

Artiles

A. J.

Kozleski

E. B.

Dorn

Christensen

(2006). Chapter 3: Learning in inclusive education research: Re-mediating theory and methods with a transformative agenda. Review of Research in Education, 30(1), 65–108. https://doi.org/10.3102/0091732X03000106

Ballis

Heath

(2021). The long-run impacts of special education. American Economic Journal: Economic Policy, 13(4), 72–111. https://doi.org/10.1257/pol.20190603

Barrett

C. A.

Stevenson

N. A.

Burns

M. K.

(2020). Relationship between disability category, time spent in general education and academic achievement. Educational Studies, 46(4), 497–512. https://doi.org/10.1080/03055698.2019.1614433

Berman

E. P.

(2022). Thinking like an economist: How efficiency replaced equality in US public policy. Princeton University Press. https://doi.org/10.1515/9780691226606

Bottge

B. A.

Cohen

A. S.

Choi

H.-J.

(2018). Comparisons of mathematics intervention effects in resource and inclusive classrooms. Exceptional Children, 84(2), 197–212. https://doi.org/10.1177/0014402917736854

Brownell

M. T.

Jones

N. D.

Sohn

Stark

(2020). Improving teaching quality for students with disabilities: Establishing a warrant for teacher education practice. Teacher Education and Special Education, 43(1), 28–44. https://doi.org/10.1177/0888406419880351

Chakraborti-Ghosh

Mofield

Orellana

(2010). Cross-cultural comparisons and implications for students with EBD: A decade of understanding. International Journal of Special Education, 25(2), 162–170.

Clotfelter

C. T.

Hemelt

S. W.

Ladd

H. F.

(2016). Teaching assistants and nonteaching staff: Do they improve student outcomes? . CALDER Working Paper No. 169. https://files.eric.ed.gov/fulltext/ED573191.pdf

10.

Cole

S. M.

Murphy

H. R.

Frisby

M. B.

Grossi

T. A.

Bolte

H. R.

(2021). The relationship of special education placement and student academic outcomes. The Journal of Special Education, 54(4), 217–227. https://doi.org/10.1177/0022466920925033

11.

Cole

S. M.

Murphy

H. R.

Frisby

M. B.

Robinson

(2023). The relationship between special education placement and high school outcomes. The Journal of Special Education, 57(1), 13–23. https://doi.org/10.1177/00224669221097945

12.

Conaway

Keesler

Schwartz

(2015). What research do state education agencies really need? The promise and limitations of state longitudinal data systems. Educational Evaluation and Policy Analysis, 37(Suppl. 1), 16S–28S. https://doi.org/10.3102/0162373715576073

13.

Contreras

Brante

Espinoza

Zuñiga

(2020). The effect of the integration of students with special educational needs: Evidence from Chile. International Journal of Educational Development, 74, 102163. https://doi.org/10.1016/j.ijedudev.2020.102163

14.

Coyne

M. D.

Cook

B. G.

Therrien

W. J.

(2016). Recommendations for replication research in special education: A framework of systematic, conceptual replications. Remedial and Special Education, 37, 244–253. https://doi.org/10.1177/0741932516648463

15.

Dunn

L. M.

(1968). Special education for the mildly retarded—Is much of it justifiable? Exceptional Children, 35(1), 5–22. https://doi.org/10.1177/001440296803500101

16.

Epler

P. L.

Ross

(2015). Models for effective service delivery in special education programs. IGI Global. https://doi.org/10.4018/978-1-4666-7397-7

17.

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. https://doi.org/10.1016/j.econedurev.2013.06.006

18.

Figlio

Karbownik

Salvanes

K. G.

(2016). Education research and administrative data. In Hanushek

Wößmann

Machin

(Eds.), Handbook of the economics of education (Vol. 5, pp. 75–138). Elsevier. https://doi.org/10.1016/b978-0-444-63459-7.00002-6

19.

Florida Inclusion Network. (2012). Best practices for in-class service delivery models [Brochure or Pamphlet]

20.

Friend

(2008). Co-teaching: A simple solution that isn’t simple after all. Journal of Curriculum and Instruction, 2(2), 9–19. https://doi.org/10.3776/joci.2008.v2i2p9-19

21.

Fuchs

L. S.

Fuchs

Compton

D. L.

Wehby

Schumacher

R. F.

Gersten

Jordan

N. C.

(2015). Inclusion versus specialized intervention for very-low-performing students: What does access mean in an era of academic challenge? Exceptional Children, 81(2), 134–157. https://doi.org/10.1177/0014402914551743

22.

Gilmour

A. F.

Neugebauer

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

23.

Hannes

Von Arx

Christiaens

Heyvaert

Petry

(2012). Don’t pull me out!? Preliminary findings of a systematic review of qualitative evidence on experiences of pupils with special educational needs in inclusive education. Procedia-Social and Behavioral Sciences, 69, 1709–1713. https://doi.org/10.1016/j.sbspro.2012.12.118

24.

Hehir

Grindal

Freeman

Lamoreau

Borquaye

Burke

(2016). A summary of the evidence on inclusive education. Abt Associates. https://files.eric.ed.gov/fulltext/ED596134.pdf

25.

Hemelt

S. W.

Ladd

H. F.

Clifton

C. R.

(2021). Do teacher assistants improve student outcomes? Evidence from school funding cutbacks in North Carolina. Educational Evaluation and Policy Analysis, 43(2), 280–304. https://doi.org/10.3102/0162373721990361

26.

Hemelt

Ladd

(2017). Teaching assistants and nonteaching staff: Do they improve student outcomes? (Update). CALDER Working Paper No. 169. https://caldercenter.org/sites/default/files/WP%20169.pdf

27.

Henrick

E. C.

Cobb

Penuel

W. R.

Jackson

Clark

(2017). Assessing research-practice partnerships: Five dimensions of effectiveness. William T. Grant Foundation.

28.

Jones

Winters

M. A.

(2022). Are two teachers better than one? The effect of co-teaching on students with and without disabilities. Journal of Human Resources. 59(4), 1180–1206. https://doi.org/10.3368/jhr.0420-10834R3

29.

King-Sears

M. E.

Johnson

T. M.

(2020). Universal design for learning chemistry instruction for students with and without learning disabilities. Remedial and Special Education, 41(4), 207–218. https://doi.org/10.1177/0741932519862608

30.

King-Sears

M. E.

Stefanidis

Berkeley

Strogilos

(2021). Does co-teaching improve academic achievement for students with disabilities? A meta-analysis. Educational Research Review, 34, 100405. https://doi.org/10.1016/j.edurev.2021.100405

31.

Kleinert

Towles-Reeves

Quenemoen

Thurlow

Fluegge

Weseman

Kerbel

(2015). Where students with the most significant cognitive disabilities are taught: Implications for general curriculum access. Exceptional Children, 81(3), 312–328. https://doi.org/10.1177/0014402914563697

32.

Loeb

Dynarski

McFarland

Morris

Reardon

Reber

(2017). Descriptive analysis in education: A guide for researchers. NCEE 2017-4023. National Center for Education Evaluation and Regional Assistance. https://files.eric.ed.gov/fulltext/ED573325.pdf

33.

Lombardi

A. R.

Doren

Gau

J. M.

Lindstrom

L. E.

(2013). The influence of instructional settings in reading and math on postsecondary participation. Journal of Disability Policy Studies, 24(3), 170–180. https://doi.org/10.1177/1044207312468766

34.

Lombardi

A. R.

Rifenbark

G. G.

Taconet

(2023). Quality indicators of secondary data analyses in special education research: A preregistration guide. Exceptional Children, 89(4), 397–411. https://doi.org/10.1177/00144029221141029

35.

Lombardi

A. R.

Loken

Rifenbark

G. G.

Challenger

Taconet

A. V.

Langdon

Shogren

(2022). Revisiting economic hardship in a national sample of adolescents with and without disabilities: A conceptual replication. Exceptional Children, 90(1), 11–26. https://doi.org/10.1177/00144029221141044

36.

Millimet

Bellemare

M. F.

(2023). Fixed effects and causal inference (IZA Discussion Paper No. 16202). https://doi.org/10.2139/ssrn.4467963

37.

Murawski

W. W.

Lee Swanson

(2001). A meta-analysis of co-teaching research: Where are the data? Remedial and Special Education, 22(5), 258–267. https://doi.org/10.1177/074193250102200501

38.

National Center for Education Statistics. (2024). Students with disabilities. http://nces.ed.gov/programs/coe/indicator/cgg.

39.

Office of Management and Budget. (2016). Building evidence with administrative data. Obama White House Archives. https://obamawhitehouse.archives.gov/sites/default/files/omb/budget/fy2016/assets/ap_7_evidence.pdf

40.

Rabren

Hall

Brown

(2003). Employment of transition-age rehabilitation consumers: Demographic and programmatic factors. Journal of Vocational Rehabilitation, 18(3), 145–152. https://doi.org/10.3233/jvr-170892

41.

Rea

P. J.

McLaughlin

V. L.

Walther-Thomas

(2002). Outcomes for students with learning disabilities in inclusive and pullout programs. Exceptional Children, 68(2), 203–222. https://doi.org/10.1177/001440290206800204

42.

Rubin

D. B.

(2006). Matched sampling for causal effects. Cambridge University Press. https://doi.org/10.1017/cbo9780511810725.001

43.

Rubin

D. B.

(2008). For objective causal inference, design trumps analysis. The Annals of Applied Statistics, 2(3), 808–840. https://doi.org/10.1214/08-aoas187

44.

Schifter

L. A.

(2016). Using survival analysis to understand graduation of students with disabilities. Exceptional Children, 82(4), 479–496. https://doi.org/10.1177/0014402915619418

45.

Schwartz

A. E.

Hopkins

B. G.

Stiefel

(2021). The effects of special education on the academic performance of students with learning disabilities. Journal of Policy Analysis and Management, 40(2), 480–520. https://doi.org/10.1002/pam.22282

46.

Scruggs

T. E.

Mastropieri

M. A.

McDuffie

K. A.

(2007). Co-teaching in inclusive classrooms: A metasynthesis of qualitative research. Exceptional Children, 73(4), 392–416. https://doi.org/10.1177/001440290707300401

47.

Solis

Vaughn

Swanson

Mcculley

(2012). Collaborative models of instruction: The empirical foundations of inclusion and co-teaching. Psychology in the Schools, 49(5), 498–510. https://doi.org/10.1002/pits.21606

48.

Steiner

P. M.

Cook

(2013). Matching and propensity scores. In Little

T.D.

(Ed.), The Oxford handbook of quantitative methods. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199934874.013.0013

49.

Steiner

P. M.

Cook

T. D.

Shadish

W. R.

(2011). On the importance of reliable covariate measurement in selection bias adjustments using propensity scores. Journal of Educational and Behavioral Statistics, 36(2), 213–236. https://doi.org/10.3102/1076998610375835

50.

Suter

J. C.

Giangreco

M. F.

(2009). Numbers that count: Exploring special education and paraprofessional service delivery in inclusion-oriented schools. The Journal of Special Education, 43(2), 81–93. https://doi.org/10.1177/0022466907313353

51.

Theobald

R. J.

Goldhaber

D. D.

Gratz

T. M.

Holden

K. L.

(2019). Career and technical education, inclusion, and postsecondary outcomes for students with learning disabilities. Journal of Learning Disabilities, 52(2), 109–119. https://doi.org/10.1177/0022219418775121

52.

Theobald

R. J.

Goldhaber

D. D.

Holden

K. L.

Stein

M. L.

(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/10.1177/00144029221081236

53.

Travers

J. C.

Cook

B. G.

Therrien

W. J.

Coyne

M. D.

(2016). Replication research and special education. Remedial and Special Education, 37(4), 195–204. https://doi.org/10.1177/0741932516648462

54.

Voulgarides

Tefera

(2017). Reframing the racialization of disabilities in policy. Theory Into Practice, 56(3), 161–168. https://doi.org/10.1080/00405841.2017.1336037

55.

Williamson

Hoppey

McLeskey

Bergmann

Moore

(2020). Trends in LRE placement rates over the past 25 years. The Journal of Special Education, 53(4), 236–244. https://doi.org/10.1177/0022466919855052

56.

Zigmond

(2003). Where should students with disabilities receive special education services?: Is one place better than another? The Journal of Special Education, 37(3), 193–199. https://doi.org/10.1177/00224669030370030901