This training module, Using the Taxonomy of Intervention Intensity to Select, Design, and Intensify Intervention, 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 intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond. At the end of the training participants will be able to:
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NCII, through a collaboration with the University of Connecticut, developed a set of course modules focused on developing educators’ skills in using explicit instruction. These course modules are designed to support faculty and professional development providers with instructing pre-service and in-service educators who are developing and/or refining their implementation of explicit instruction.
This two page handout defines the Taxonomy of Intervention Intensity through guiding questions and highlights when the Taxonomy of Intervention Intensity can be used within the data-based individualization (DBI) process. Teams can use the dimensions to evaluate a current intervention, select a new intervention and intensify interventions when students do not respond.
Intensive intervention teams can use these checklists to monitor implementation of the data-based individualization (DBI) process during initial planning and ongoing review (progress monitoring) meetings in order to ensure teams develop high quality student plans. These detailed checklists may be most beneficial for less experienced teams. As teams become more familiar with DBI implementation, they may choose to use the checklists less frequently or focus on only a subset of items.
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:
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.
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.
These professional learning training materials are intended to assist district or school teams involved in initial planning or implementation of data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The modules listed below provide an overview of the DBI process and more in-depth exploration of the various components of DBI.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.
This Voices from the Field piece highlights how North Carolina, Oregon, Washington, and Texas have raised awareness, visibility, and statewide knowledge of data-based individualization (DBI) at statewide conferences through keynote speakers, workshops, breakout sessions, and facilitated team time.
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