By Jan Bryan, EdD, Vice President, National Education Officer
More than fifty years down the road, you still see a few baby-blue 1967 VW Fastbacks. What is it about the ’67 V-Dub that keeps it functional, relevant, and efficient year-over-year? Is it the skilled drivers who remain dedicated to the brand, or—let’s be honest—simply because it was the “jazzy” car to drive? If you have any doubt, check out Dustin Hoffman’s 1967 VW Fastback commercial.
Educators, like loyal car owners, tend to stick with concepts that are functional, relevant, efficient, and reliable. These concepts are found in Response to Intervention (RTI). RTI has a rich history and continues to thrive in a 21st century iteration of data-fueled instruction.
RTI—The first generation
RTI finds its roots in the late 1970s as an alternative way to identify students with specific learning disabilities. RTI challenged the established discrepancy model that compared students’ achievement and their performance on IQ measures to determine eligibility for special education services (National Education Association, n.d.). Practical concerns related to the discrepancy model have been noted, in particular that it places greater focus on disorders over skill deficits and, as such, rarely identifies children in early grades.
While these concerns are substantive, the most important reason for moving away from the discrepancy model focused on significant empirical support for the model and for the effectiveness of interventions based on the model (Aaron, 1997; Fletcher, et. A. 1998; Francis, et. A. 2005; Stuebing, et. A. 2012).
In part to address these concerns, RTI provided an evidenced-based approach to established practices, including:
– Efficiently and reliably assess all students
– Identify and intervene early
– Inform the instructional process and monitor its effectiveness
RTI—The following generations
In the 1970s and ‘80s, researchers such as Stanley Deno and Phyllis Mirkin (1977) found that short, frequent assessments helped manage special-education students’ Individual Education Plans (IEPs). Around the same time, Benjamin Bloom’s (1981) “mastery learning” experiments demonstrated that using formative assessment as a basis to modify curriculum and instruction improved average student performance dramatically.
Pyramids and acronyms
The basic tiered services framework existed in the psychological and educational literature for many years; with its foundation in the prevention sciences (Caplan, 1964), where physicians talked about primary, secondary, and tertiary prevention or treatment (and represented that model as a pyramid).
The RTI three-tier structure originated in the ‘90s with researchers like Sugai and Horner (1994) seeking ways to deal with behavioral problems in general education settings.
RTI established nationwide
Almost 25 years after the first concerns related to the discrepancy model were raised, Fuchs (2003) developed the dual-discrepancy model which examined achievement, growth, and response to instruction or intervention. Fuchs’ model and the documented success of tiered interventions attracted federal funding in the amendments to the 1997 Individuals with Disabilities Education Act (IDEA), with implementation funding available in the 2004 IDEA reauthorization and its alignment with No Child Left Behind (NCLB). In other words, RTI moved from a program to a way of doing business.
RTI—The next generation
RTI continues to thrive as it is now adapting to a new era in our schools—one of next-generation standards, 21st century skills, and greater attention to assessment.
RTI requires continuous assessment but is ultimately about lessening the distance between assessment and informed instruction. We have moved from using assessment data to make predictions about students’ lives—such as who might succeed in school—to making a difference in students’ lives by improving instruction, enhancing competence, and leading them to positive outcomes (Ysseldyke, 2009).
If we are serious about lessening this distance and improving students’ lives, we must move from pdfs and printouts to vivid, visual access to data where color, shape, and size represent achievement, growth, and trajectories for future learning.
The academic partnership between a teacher and a learner is the dominant achievement variable in both core instruction and intervention (Coleman, Campbell, Hobson, McPartland, Mood, Weinfeld, & York, 1966; Barber & Mourshed, 2007; Chetty, Friedman, Hilger, Saez, Schanzenbach, & Yagan, 2011; Wright, Horn, & Sanders, 1997). As such, we focus on teachers’ response to information about learning science and about each learner as much as we focus on students’ response to intervention.
Finally, student growth provides context for achievement. Perhaps three of the noticeable changes to RTI in this generation include:
– Implementing RTI at the high school grades
– RTI for high-achieving students
– Emphasis on students growth along with achievement
In this generation of RTI, educators are focusing on the Student Growth Percentile (SGP) to develop greater insight about each learner. Many RTI leaders now include SGP in goal setting and progress monitoring.
VW Fastbacks and RTI flashbacks—What’s next?
With a little help from Dustin Hoffman, we’ve learned that efficiency, relevancy, and reliability describe ideas of enduring value. The classic cars research is up to you; however, for deeper understanding of ways to build even greater efficiency, relevancy, and reliability for your RTI implementation, download the free white paper: The Next Generation of Response to Intervention.
Aaron, P. G. (1997). The impending demise of the discrepancy formula. Review of Educational Research, 67(4), 461–502.
Barber, M., & Mourshed, M. (2007). How the world’s best-performing school systems come out on top. London: McKinsey and Company.
Caplan, G. (1964). Principles of preventive psychiatry. New York: Basic Books.
Chetty, R., Friedman, J. N., Hilger, N., Saez, E., Schanzenbach, D. W., & Yagan, D. (2011). How does your kindergarten classroom affect your earnings? Evidence from Project Star*. Quarterly Journal of Economics, 126(4), 1593–1660.
Deno, S. L., & Mirkin, P. K. (1977). Data-based program modification: A manual. Reston, VA: Council for Exceptional Children. Retrieved from http://files.eric.ed.gov/fulltext/ED144270.pdf.
Fletcher, J. M., Francis, D. J., Shaywitz, S. E., Lyon, G. R., Foorman, B. R., Stuebing, K. K., & Shaywitz, B. A. (1998). Intelligent testing and the discrepancy model for children with learning disabilities. Learning Disabilities Research & Practice, 13(4), 186–203.
Fuchs, L. S. (2003). Assessing intervention responsiveness: Conceptual and technical issues. Learning Disabilities Research & Practice, 18(3), 172–186.
Gresham, F. M. (1991). Conceptualizing behavior disorders in terms of resistance to intervention. School Psychology Review, 20(1), 23–36.
National Association of Special Education Teachers. (2006). The importance of Response to Intervention (RTI) in the understanding, assessment, diagnosis, and teaching of students with learning disabilities. NASET LD Report, 5. Retrieved from http://www.naset.org/fileadmin/user_upload/LD_Report/Issue__5_LD_Report_Importance_of_RTI.pdf.
Stuebing, K. K., Fletcher, J. M., Branum-Martin, L. & Francis, D. J. (2012). Evaluation of the technical adequacy of three methods for identifying specific learning disabilities based on cognitive discrepancies. School Psychology Review, 4(1), 3–22.
Sugai, G., & Horner, R. H. (1994). Including students with severe behavior problems in general education settings: Assumptions, challenges and solutions. In J. Marr, G. Sugai, & G. Tindal (Eds.), The Oregon Conference Monograph, Vol. 6 (pp.102–120). Eugene: University of Oregon.
Wright, S., Horn, S., & Sanders, W. (1997). Teacher and classroom context effects on student achievement; Implications for teacher evaluation. Journal of Personnel Evaluation in Education, 11(1), 57–67.
Ysseldyke, J. (2009). When politics trumps science: Generalizations from a career of research on assessment, decision making, and public policy. Communique, 38(4), 6–8.
Jan Bryan has more than 20 years of classroom and university teaching experience. Her work at Renaissance focuses on formative assessment, exploring data in a growth mindset, and literacy development.