This updated training module provides a rationale for intensive intervention and an overview of data-based individualization (DBI), NCII’s approach to providing intensive intervention. DBI is a research-based process for individualizing validated interventions through the systematic use of assessment data to determine when and how to intensify intervention. Two case studies, one academic and one behavioral, are used to illustrate the process and highlight considerations for implementation.
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DBI Process
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In this Voices from the Field video, Jill Pentimoni, Ph.D. from NCII and the University of Notre Dame and Jade Wexler, Ph.D. from the University of Maryland discuss how they used the tools charts in a graduate class to help prepare and inform students about the technical criteria used to review tools on the academic intervention tools chart. Dr. Wexler also shares how she has used the charts within undergraduate courses.
In this video, Dr. Chris Riley-Tillman, a Professor at the University of Missouri and NCII Senior Advisor, discusses how evidence-based practices, instruction, and intervention change as academic and behavior needs become more severe.
In Module 5 of the Intensive Intervention in Mathematics Course Content we focus on three instructional strategies teachers should embed within every intensive intervention session. We rely on a strong research base for these recommendations about fluency, problem solving, and motivation.
This training module introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated behavior intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.
This video describes how to use the partial products strategy with multiplication.
This video reviews to how use the traditional algorithm to solve multiplication with regrouping.
Many students who require intensive intervention also are students with disabilities. Thus, when used school-wide, data-based individualization (DBI) can help school teams design and implement a prereferral process and high-quality special education services. Furthermore, DBI also provides schools with a validated approach for identifying and supporting students with severe and persistent learning and behavior problems, including students who may require special education. This is because the data collected through the DBI process can assist teams in assessing the need for specialized instruction, which is one of two requirements for determining eligibility for special education. In addition, data collected through the DBI process can support special education teachers in more accurately developing present levels, goals, and specialized instruction and support that will be included in the initial IEP.
The Taxonomy of Intervention Intensity (Fuchs, Fuchs, & Malone, 2017) can be used to select or evaluate an intervention platform used as the validated intervention platform or the foundation of the DBI process. It can also be used to guide the adaptation of intensification of an intervention during the intervention adaptation step of the DBI process. The Taxonomy includes the following dimensions:
NCII provides a series of reading lessons to support special education instructors, reading interventionists, and others working with students who struggle with reading. These lessons, adapted with permission from the Florida Center for Reading Research and Meadows Center for Preventing Educational Risk, address key reading and prereading skills and incorporate research-based instructional principles that can help intensify and individualize reading instruction.