NASP Communiqué, Vol. 34, #5
February 2006

Comparison of Existing Response-to-Intervention Models to Identify and Answer Implementation Questions

By Matthew K. Burns & James E. Ysseldyke

Recently researchers have called attention to a number of unanswered questions about response-to-intervention (RTI) including: (a) are there validated intervention models and adequately trained personnel? (Vaughn & Fuchs, 2003); (b) what leadership is needed to ensure that the practice of RTI is properly implemented? (Fuchs, Mock, Morgan, & Young, 2003); (c) when does due process protection begin? (Vaughn, & Fuchs, 2003); and (d) is RTI a defensible endpoint in the identification process? (Vaughn & Fuchs, 2003). 

These questions are relevant to implementation and need immediate inquiry. Fortunately, large-scale RTI models are already in place and may suggest answers to these implementation questions. Fuchs et al. (2003) identified four large-scale RTI models that are exemplars of wide-scale problem solving: the Heartland Agency Model in Iowa (Heartland), Ohio’s Intervention-Based Assessment (IBA), Pennsylvania’s Instructional Support Team (IST), and Minneapolis (Minnesota) Public Schools’ Problem-Solving Model (PSM). Recent meta-analytic research supported the effectiveness of these four models in improving student and systemic outcomes (Burns, Appleton, & Stehouwer, in press). In this paper we examine these four large-scale RTI models to address questions about RTI implementation.

Answering Key Questions

Do we have validated intervention models and measures to assure instruction validity?

All four models use a protocol that emphasizes formative assessment, frequent progress monitoring, and informal assessments relevant to the curriculum. Research has consistently supported these as critical aspects of instruction and all were found to be effective interventions to improve student learning (Fuchs & Fuchs, 1986; Shapiro, 1992; Shapiro & Ager, 1992).

Are there adequately trained personnel to implement an RTI model?

Training appeared to be an important implementation component for all four models because each was implemented in phases that involved broad training, including general education teachers, and preparation of specific professionals over a period of 4 to almost 10 years. Perhaps the point most consistently emphasized among the four models was use of a multidisciplinary collaborative team, but there was not a consensus as to which professionals should make up that team.

What leadership will make RTI successful?

The Heartland model and IBA both emphasize local autonomy, but only IBA and IST require principal involvement. Thus, several questions about leadership are yet to be answered. For example, would district-level leadership come from special education, general education, or would this dichotomy become irrelevant?  Would building principals have autonomy in administering RTI within their buildings?  To which state-level department would RTI activities and results be reported? 

When should due process begin?

Federal and state mandates limit the length of time between parental referral and completion of an evaluation plan. However, only IST has a time limit (50 school days of instructional support teacher involvement). Clearly, due process protections would occur for children in the final phases of the Heartland model and PSM, but what if the levels or stages that precede the special education consideration exceed state mandates?  Placing a timeline on the process might alleviate this issue to a degree; the effect of which would have to be researched.

Is inadequate response to instruction a defensible endpoint?

In order for RTI to be a defensible endpoint in the identification process the deficit responsible for the lack of responsiveness should be best described as LD and the program should be of sufficient value to warrant classification (Vaughn & Fuchs, 2003). As stated earlier, two of the programs used different terms besides LD, thus the best name for the deficit causing unresponsiveness is not obvious. The second point simply restated could be that positive student outcomes are needed for children classified as both responsive and unresponsive.

Data exist for each of these approaches and collectively support the effectiveness of the large-scale RTI models (Burns et al., 2005). Specifically, RTI reduced referrals to and/or placements in special education (Marston et al., 2003; McNamara, 1998; Reschly & Starkweather, 1997; Sornson, Frost, & Burns, 2005), increased the number of children demonstrating proficient skill levels on state accountability tests (Heartland, 2004; Sornson et al., 2005), led to reduced numbers of student grade retentions (Kovaleski, Tucker & Duffy, 1995), and improved individual students’ reading skills (Marston et al., 2003; Tilly 2003), adaptive behavior (Reschly & Starkweather, 1997), time on task, task comprehension, and task completion (Kovaleski, Glickling, & Morrow, 1999). Moreover, previous research found that students diagnosed with a disability due to unresponsiveness also experienced positive outcomes; and within these four RTI models, special education services increased and were more intense (Ikeda & Gustafson, 2002; Reschly & Starkweather, 1997), were initiated at earlier grades (Reschly & Starkweather, 1997), were more cost effective (Sornson et al., 2005), and directly linked resources with student needs (Tilly, 2003). Thus, RTI appears to lead to a defensible endpoint.

Additional Questions

Consistencies between the extant RTI models suggest answers to important implementation questions, but inconsistencies between them suggest the following additional questions: (a) what implementation procedures are needed at the secondary level? (b) what does parental collaboration entail within RTI? and (c) how will fidelity of RTI implementation be assessed in practice?

Recommendations for RTI Implementation

Perhaps most important is the need for phased-in implementation and extensive training of both specialized and school-wide personnel. Moreover, a multidisciplinary team should frequently measure the target skill/behavior in baseline and intervention phases, assess the match between student skill and curricular materials, and make data-based instructional adaptations.  And, it is imperative that school psychologists join with other educational professionals in documenting the extent to which RTI is effective in improving outcomes for students, including students with disabilities and limited English proficiency.

References

Burns, M. K., Appleton, J. J., & Stehouwer, J. D. (in press). Meta-analysis of response-to intervention research: Examining field-based and research-implemented models. Journal of Psychoeducational Assessment.

Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation:A meta-analysis. Exceptional Children, 53, 199-208.

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 and Practice, 18, 157-171.

Heartland AEA 11 (2004). Heartland AEA 11 annual progress report. Retrieved October 15, 2004, from http://www.aea11.k12.ia.us/downloads/2004apr.pdf

Ikeda, M. J., & Gustafson, J. K. (2002). Heartland AEA 11’s problem solving process: Impact on issues related to special education. Research report no. 2002-01.  Johnston, IA: Heartland AEA 11.

Kovaleski, J. F., Gickling, E. E., & Morrow, H. (1999). High versus low implementation of instructional support teams: A case for maintaining program fidelity. Remedial and Special Education, 20, 170-183.

Kovaleski, J. F., Tucker, J. A., & Duffy, D. J. (1995, June). School reform through instructional support: The Pennsylvania initiative (Part I). Communiqué, 23 (8), insert.

Marston, D., Muyskens, P., Lau, M., & Canter, A. (2003). Problem-solving model for decision making with high-incidence disabilities. Learning Disabilities Research & Practice, 18, 187-200.

McNamara, K. (1998). Adoption of intervention-based assessment for special education. School Psychology International, 19, 251-266.

Reschly, D. J., & Starkweather, A. R. (1997). Evaluation of an alternative special education assessment and classification program in the Minneapolis Public Schools.  Minneapolis, MN: Minneapolis Public Schools.

Shapiro, E. S. (1992). Use of Glickling’s  model of curriculum-based assessment to improve reading in elementary age students. School Psychology Review, 21, 168-176.

Shapiro, E. S., & Ager, C. (1992). Assessment of special education students in regular education programs: Linking assessment to instruction. Elementary School Journal, 92, 283-296.

Sornson, R., Frost, F., & Burns, M. (2005, February). Instructional support teams in Michigan: Data from Northville Public Schools. Communiqué, 33(5), 28-29.

Tilly, W. D. III (2003). How many tiers are needed for successful prevention and early intervention?: Heartland AEA 11’s evolution from four to three tiers. Paper presented at the National Research Center on Learning Disabilities Responsiveness-to-Intervention Symposium, Kansas City, MO.

Vaughn, S., & Fuchs, L. S. (2003). Redefining learning disabilities as inadequate response to instruction: The promise and potential problems. Learning Disabilities Research & Practice, 18, 137-146.

© 2005, California Association of School Psychologists. This article is adapted with permission from a more extensive discussion in the California School Psychologist, 2005 (volume 10, pp. 9-20). Matthew K. Burns, PhD, and James E. Ysseldyke, PhD, NCSP, are on the faculty of the School Psychology Training Program at the University of Minnesota.