DEVELOPMENT, VALIDATION, AND IMPLEMENTATION OF A MAINSTREAMING PROCESS TO TRANSITION STUDENTS FROM SELF-CONTAINED SPECIAL EDUCATION INTO GENERAL EDUCATION PLACEMENTS

Michael Ryan Hunsaker

Abstract


We developed a set of computational tools specifically to guide qualified special education students back into general education. These tools include a decision tree to identify candidate students and elucidate successful placement in general education. Candidate students enter a process involving selection of general education classroom, data collection, and finally how to make the final transition out of special education self-contained placements. In the 2015-2016, we undertook a limited implementation of these transenvironmental programming tools and facilitated the transition of 10 of 20 identified candidate students from self-contained academic special education classrooms into general education placements. In the 2016-2017 school year, we extended this process to include 4 schools. 16 of 53 identified candidate students from self-contained academic special education classrooms were able to transition into general education placements. In an extension of the model district-wide, 9 of 26 identified students from behavior/SEL unit classrooms, and 9 of 9 identified students from Life Skills/SID unit classrooms were successfully transitioned into a general education with part-time special education placement. A high percentage of the remaining candidates received >50% of their day in general education classrooms and/or were placed in less restrictive self-contained classrooms. Overall, 54% of identified candidate students were able to access a less restrictive environment as defined by IDEIA. Further, computational analyses using regression tree, unbiased hierarchal clustering, and support vector machine methods are presented to demonstrate the robustness of these methods by recapitulating the results using solely data from special education evaluations.

 

Article visualizations:

Hit counter

DOI

Keywords


transenvironmental programming, psychoeducational evaluation, MTSS, inclusion, mainstreaming, machine learning

Full Text:

PDF

References


Anderson-Inman, L. (1987). Consistency of performance across class- rooms: Instructional materials versus setting as influencing variables. The Journal of Special Education, 21(2), 9–29.

Angkustsiri, K., Leckliter, I., Tartaglia, N., Beaton, E. A., Enriquez, J., & Simon, T. J. (2012). An examination of the relationship of anxiety and intelligence to adaptive functioning in children with chromosome 22q11. 2 deletion syndrome. Journal of Developmental and Behavioral Pediatrics, 33(9), 713.

Avramidis, E., Bayliss, P., & Burden, R. (2000). A survey into mainstream teachers’ attitudes towards the inclusion of children with special educational needs in the ordinary school in one local education authority. Educational Psychology, 20(2), 191–211.

Barbeau, E. B., Soulieres, I., Dawson, M., Zeffiro, T. A., & Mottron, L. (2013). The level and nature of autistic intelligence iii: Inspection time. Journal of Abnormal Psychology, 122(1), 295.

Barnes, M. C., & Gaines, T. (2015). Teachers’ attitudes and perceptions of inclusion in relation to grade level and years of experience. Electronic Journal for Inclusive Education, 3(3), 3.

Bearden, C. E., van Erp, T. G., Monterosso, J. R., Simon, T. J., Glahn,

D. C., Saleh, P. A., . . . Emanuel, B. S., et al. (2004). Regional brain abnormalities in 22q11. 2 deletion syndrome: Association with cognitive abilities and behavioral symptoms. Neurocase, 10(3), 198–206.

Bedinim, L. A. (1990). Separate but equal? segregated programming for people with disabilities. Journal of Physical Education, Recreation & Dance, 61(8), 40–44.

Biswas, A. B., & Furniss, F. (2016). Cognitive phenotype and psychiatric disorder in 22q11. 2 deletion syndrome: A review. Research in Developmental Disabilities, 53, 242–257.

Brownell, M. T., Sindelar, P. T., Kiely, M. T., & Danielson, L. C. (2010). Special education teacher quality and preparation: Exposing foundations, constructing a new model. Exceptional Children, 76(3), 357– 377.

Cauley, K. M., & Jovanovich, D. (2006). Developing an effective transition program for students entering middle school or high school. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 80(1), 15–25.

Cohen, R. A. (2011). Yerkes–Dodson law. In Encyclopaedia of clinical neuropsychology (pp. 2737–2738). Springer.

Conway, R. N., & Gow, L. (1988). Mainstreaming special class students with mild handicaps through group instruction. Remedial and Special Education, 9(5), 34–40.

Cooray, S. E., & Bakala, A. (2005). Anxiety disorders in people with learning disabilities. Advances in Psychiatric Treatment, 11(5), 355–361.

Courchesne, V., Meilleur, A.-A. S., Poulin-Lord, M.-P., Dawson, M., & Soulieres, I. (2015). Autistic children at risk of being underestimated: School-based pilot study of a strength-informed assessment. Molecular Autism, 6(1), 12.

Daniel, P. T. (1997). Educating students with disabilities in the least restrictive environment: A slippery slope for educators. Journal of Educational Administration, 35(5), 397–410.

Dawson, M., Soulieres, I., Gernsbacher, M. A., & Mottron, L. (2007). The level and nature of autistic intelligence.

Psychological Science, 18(8), 657–662. PMID: 17680932. doi:10.1111/j.1467-9280.2007.01954. x. eprint: http://dx.doi.org/10.1111/j.1467-9280.2007.01954.x

De Bildt, A., Sytema, S., Kraijer, D., Sparrow, S., & Minderaa, R. (2005). Adaptive functioning and behaviour problems in relation to level of education in children and adolescents with intellectual disability. Journal of Intellectual Disability Research, 49(9), 672–681.

Dennis, M., Francis, D. J., Cirino, P. T., Schachar, R., Barnes, M. A., & Fletcher, J. M. (2009). Why iq is not a covariate in cognitive studies of neurodevelopmental disorders. Journal of the International Neuropsychological Society, 15(03), 331–343.

Ditterline, J., Banner, D., Oakland, T., & Becton, D. (2008). Adaptive behavior profiles of students with disabilities. Journal of Applied School Psychology, 24(2), 191–208.

Dunn, K. E., & Mulvenon, S. W. (2009). A critical review of research on formative assessment: The limited scientific evidence of the impact of formative assessment in education. Practical Assessment, Research & Evaluation, 14(7), 1–11.

Edwards, O. W., & Oakland, T. D. (2006). Factorial invariance of Woodcock-Johnson iii scores for African Americans and Caucasian Americans. Journal of Psychoeducational Assessment, 24(4), 358– 366.

Ferri, B. A., & Connor, D. J. (2005). Tools of exclusion: Race, disability, and (re) segregated education. Teachers College Record, 107(3), 453– 474.

Fisher, D., Frey, N., & Thousand, J. (2003). What do special educators need to know and be prepared to do for inclusive schooling to work? Teacher Education and Special Education, 26(1), 42–50.

Fuchs, D. et al. (1994a). Best practices in school psychology: Peabody reintegration project.

Fuchs, D., Fernstrom, P., Scott, S., Fuchs, L., & Vandermeer, L. (1994b). Classroom ecological inventory: A process for mainstreaming. Teaching Exceptional Children, 26(3), 11.

Fuchs, D., Fuchs, L. S., & Fernstrom, P. (1992). Case-by-case reintegration of students with learning disabilities. The Elementary School Journal, 261–281.

Fuchs, D., Fuchs, L. S., & Fernstrom, P. (1993). A conservative approach to special education reform: Mainstreaming through transenvironmental programming and curriculum-based measurement. American Educational Research Journal, 30(1), 149–177.

Fuchs, D., Mock, D., Morgan, P. L., & Young, C. L. (2003). Responsiveness- to-intervention: Definitions, evidence, and implications for the learning disabilities construct. Learning Disabilities Research & Practice, 18(3), 157–171.

Gersten, R., & Dimino, J. A. (2006). Rti (response to intervention): Re- thinking special education for students with reading difficulties (yet again). Reading Research Quarterly, 41(1), 99–108.

Gresham, F. M., & Elliott, S. N. (1987). The relationship between adaptive behavior and social skills issues in definition and assessment. The Journal of Special Education, 21(1), 167–181.

Grondhuis, S. N., Lecavalier, L., Arnold, L. E., Handen, B. L., Scahill, L., McDougle, C. J., & Aman, M. G. (2018).

Differences in verbal and nonverbal iq test scores in children with autism spectrum disorder. Research in Autism Spectrum Disorders, 49, 47–55.

Group, P. H. W. (1991). Problems and promises in special education and related services for children and youth with emotional or behavioral disorders. Behavioral Disorders, 16(4), 299–313.

Heritage, M. (2007). Formative assessment: What do teachers need to know and do? Phi Delta Kappan, 89(2), 140.

Hocutt, A. M. (1996). Effectiveness of special education: Is placement the critical factor? The Future of Children, 77–102.

Hollenbeck, K., Tindal, G., & Almond, P. (1998). Teachers’ knowledge of accommodations as a validity issue in high-stakes testing. The Journal of Special Education, 32(3), 175–183.

Iwata, B. A., & Bailey, J. S. (1974). Reward versus cost token systems: An analysis of the effects on students and teacher. Journal of Applied Behavior Analysis, 7(4), 567–576.

Johnson, D. R. (2005). Key provisions on transition: A comparison of idea 1997 and idea 2004. Career Development for Exceptional Individuals, 28(1), 60.

Kalaci, S. (2007). Students with autism left behind: No child left behind and the individuals with disabilities education act. Thomas Jefferson University Law Review. 30, 723.

Kauffman, J. M., Bantz, J., & McCullough, J. (2002). Separate and bet- ter: A special public school class for students with emotional and behavioral disorders. Exceptionality, 10(3), 149–170.

Klotz, M. B., & Nealis, L. (2005). The new idea: A summary of significant reforms. Retrieved July, 15, 2012.

Konold, T. R., Kush, J. C., & Canivez, G. L. (1997). Factor replication of the wisc iii in three independent samples of children receiving special education. Journal of Psychoeducational Assessment, 15(2), 123– 137.

Marchese, S. (2000). Putting square pegs into round holes: Mediation and the rights of children with disabilities under the idea. Rutgers Law Review, 53, 333.

Marden, C. S. (2013). Criteria for transition for self-contained classrooms (Master’s thesis, Utah State University, Utah).

Mathes, P. G., Fuchs, D., Roberts, P. H., & Fuchs, L. S. (1998). Preparing students with special needs for reintegration curriculum-based measurement’s impact on transenvironmental programming. Journal of Learning Disabilities, 31(6), 615–624.

McCarthy, M. R., Wiener, R., & Soodak, L. C. (2012). Vestiges of segregation in the implementation of inclusion policies in public high schools. Educational Policy, 26(2), 309–338.

McLeskey, J., Landers, E., Williamson, P., & Hoppey, D. (2012). Are we moving toward educating students with disabilities in less restrictive settings? The Journal of Special Education, 46(3), 131–140.

Mukherjee, S., Lightfoot, J., & Sloper, P. (2000). The inclusion of pupils with a chronic health condition in mainstream school: What does it mean for teachers? Educational Research, 42(1), 59–72.

Nader, A.-M., Courchesne, V., Dawson, M., & Soulieres, I. (2014). Does wisc-iv underestimate the intelligence of autistic children? Journal of Autism and Developmental Disorders, 1–8.

Nader, A.-M., Courchesne, V., Dawson, M., & Soulieres, I. (2016). Does wisc-iv underestimate the intelligence of autistic children? Journal of Autism and Developmental Disorders, 46(5), 1582–1589.

Nolan, J. E. (2004). Theus individuals with disabilities education act (idea): Tracing inclusion and exclusion of the disabled from ford to bush ii. Online Submission.

Oakland, T., & Harrison, P. L. (2011). Adaptive behavior assessment system-ii: Clinical use and interpretation. Academic Press.

Popa, A. M., Cruz, J., Angkustsiri, K., Brahmbhatt, K., Cung, N., Leckliter, I., . . . Simon, T. J. (2014). Atypical adaptation responses to threat stimuli in children with chromosome 22q11. 2 deletion syndrome. In Biological psychology (Vol. 75, 9, 192S–192S).

Praisner, C. L. (2003). Attitudes of elementary school principals toward the inclusion of students with disabilities. Exceptional Children, 69(2), 135–145.

R Development Core Team. (2017). R: A language and environment for statistical computing. ISBN 3-900051-07-0. R

Foundation for Statistical Computing. Vienna, Austria. Retrieved from

http://www.R-project.org

Raines, T. C., Dever, B. V., Kamphaus, R. W., & Roach, A. T. (2012). Universal screening for behavioral and emotional risk: A promising method for reducing disproportionate placement in special education. The Journal of Negro Education, 81(3), 283–296.

Reid, R., Gonzalez, J. E., Nordness, P. D., Trout, A., & Epstein, M. H. (2004). A meta-analysis of the academic status of students with emotional/behavioral disturbance. The Journal of Special Education, 38(3), 130–143.

Reynolds, C. R., & Shaywitz, S. E. (2009). Response to intervention: Ready or not? or, from wait-to-fail to watch-them-fail. School Psychology Quarterly, 24(2), 130.

Ruth, W. J. (1996). Goal setting and behavior contracting for students with emotional and behavioral difficulties: Analysis of daily, weekly, and total goal attainment. Psychology in the Schools, 33(2), 153–158. doi:10.1002/(SICI)1520-6807(199604)33:2 153::AID-PITS8 3.0.CO; 2-S

Savich, C. (2008). Inclusion: The pros and cons–a critical review. Online Submission.

Skiba, R. J., Simmons, A. B., Ritter, S., Gibb, A. C., Rausch, M. K., Cuadrado, J., & Chung, C.-G. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74(3), 264–288.

Smith, R. M. (2006). Classroom management texts: A study in the representation and misrepresentation of students with disabilities. Inter- national Journal of Inclusive Education, 10(1), 91–104.

Smith, S. W., & Farrell, D. T. (1993). Level system use in special education: Classroom intervention with prima facie appeal. Behavioral Disorders, 18(4), 251–264. doi:10.1177/019874299301800408. eprint:

http://dx.doi.org/10.1177/019874299301800408

Taub, G. E., & McGrew, K. S. (2004). A confirmatory factor analysis of Cattell-Horn-Carroll theory and cross-age invariance of the Woodcock-Johnson tests of cognitive abilities iii. School Psychology Quarterly, 19(1), 72.

Therneau, T. M., Atkinson, E. J. et al. (2017). An introduction to recursive partitioning using the rpart routines. Technical report Mayo Foundation.

Wadsworth, D. F. D., & Knight, D. (1999). Preparing the inclusion class- room for students with special physical and health needs. Intervention in School and Clinic, 34(3), 170–175.

Wechsler, D. (2008). Wechsler adult intelligence scale-fourth. San Antonio: Pearson.

Wiesner, M., & Schanding, G. T. (2013). Exploratory structural equation modeling, bifactor models, and standard confirmatory factor analysis models: Application to the basc-2 behavioral and emotional screening system teacher form. Journal of School Psychology, 51(6), 751– 763.

Wu, W., West, S. G., & Hughes, J. N. (2008). Short-term effects of grade retention on the growth rate of Woodcock–Johnson iii broad math and reading scores. Journal of School Psychology, 46(1), 85–105.Yerkes, R. M.,




DOI: http://dx.doi.org/10.46827/ejse.v0i0.1754

Copyright © 2015 - 2023. European Journal of Special Education Research (ISSN 2501 - 2428) is a registered trademark of Open Access Publishing GroupAll rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library (Biblioteca Nationala a Romaniei). All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms.

All the research works published on this journal are meeting the Open Access Publishing requirements and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License (CC BY 4.0).