Tier III Assessments, Data-Based Decision Making, and Interventions

Oct 15, 2026

Uploaded by OmBimo

Within the Response-to-Intervention framework, students who do not benefit from general education instruction and supplemental support move to Tier III. The article presents a problem-solving approach for designing intensive, data-based, and scientifically supported interventions for students with pervasive reading problems. It describes progress-monitoring and brief experimental analysis methods, and includes two case studies showing how these techniques can be combined to implement Tier III interventions.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Tier III in the Response-to-Intervention Framework

Designing Data-Based, Scientifically Supported Interventions

Universal Screening and Progress Monitoring

Brief Experimental Analysis for Non-Responders

Case Study Applications

21 tier iii assessments, data-Based decision Making, and interventions Kristin Powers and Arpita Mandal, California State University, Long Beach Within the Response-to-Intervention framework, students who fail to profit from high-quality general education instruction, accommodations, and supplemental instruction progress to amore intensive intervention program, sometimes referred to as “Tier III.” This article describes a problem-solving approach to designing such intensive, data-based, and scientifically supported interventions for students with pervasive reading problems who have failed to respond to less rigorous services. The application of well-established (i.e., progress monitoring) and emerging methods (i.e., brief experimental analysis) for optimizing interventions are described. Two case studies are provided to illustrate how these techniques may be combined to implement Tier III interventions. Over the past 15 years, the way in which students with learning disabilities (LD) are identified and served has received considerable scrutiny, resulting in a movement away from a traditional, psychometrically driven IQ/achievement discrepancy model toward one focused on intervention and measurable outcomes – termed Response-to-Intervention (RtI) . The reauthorization of IDEA in 2004 codified this shift by requiring state educational agencies (SEA) to consider and even support local educational agencies (LEA) in their use of RtI-based eligibility criteria. At the same time, SEAs were also prohibited from requiring LEAs to use IQ/achievement discrepancy criterion in determining LD eligibility (Fuchs & Fuchs, 2006; Kame’enui, 2007) . Two major axioms of RtI are (a) learning difficulties are not inherently due to child deficits and (b) most students will experience significant educational gains from targeted, empirically based, and closely monitored interventions (Torgesen, 2007) . For many students RtI represents an opportunity to avoid or exit the cycle of failure. For a few, namely those who fail to respond to sustained, empirically validated interventions implemented with fidelity, RtI results in continued individualized intervention offered by special education programs to students with learning disabilities (Gresham, 2001) . Many researchers and policy makers, such as the National Reading Panel (National Institute of Child Health and Human Development, 2000), National Joint Committee on Learning Disabilities (2005), and President’s Commission on Excellence in Special Education (2002), suggest that a shift to RtI instructional and diagnostic practices is preferable to former practices because students who underperform will be identified and serviced earlier, before underachievement becomes entrenched; students will qualify for the intense, individualized support of special education based on their need for that support rather than arbitrary test scores; and the assessment and intervention processes that lead to LD qualification will inform subsequent educational programming decisions. In practice, RtI has a number of distinguishing components, including (a) universal screening to identify students at-risk for learning difficulties early,(b) progress monitoring of students’ response to interventions,(c) scientifically based multi-tiered interventions to ensure intervention intensity is proportional to individual students’learning needs, and (d) problem-solving to select and improve interventions (Fuchs & Fuchs, 2006). Most students make adequate progress when provided high-quality classroom instruction (i.e., Tier I). Those who do not, receive increasingly intense and targeted interventions (i.e., Tier II) until they either make adequate improvement or are referred for special education services (i.e., Tier III). When less resource-intensive interventions such as those provided in classrooms and small groups are unsuccessful, the student progresses to “Tier III” interventions, which are more individual- Corre

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How are case studies used in the article?

Two case studies illustrate how progress-monitoring and BEA techniques can be combined to implement Tier III interventions effectively.

Oct 15, 2026

Uploaded by OmBimo