This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
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DBI Process
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Implementation Guidance and Considerations
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This checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
This document highlights some common misconceptions about intensive academic and behavior interventions that experts from the Center on Positive Behavioral Interventions and Supports and NCII have observed in supporting the implementation of intensive intervention within the context of MTSS.
This IRIS Star Legacy Module, first in a series of two, overviews data-based individualization and provides information about adaptations for intensifying and individualizing instruction. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This Innovation Configuration can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS. The expectation is that these skills can be further honed and supported through inservice as practicing teachers.
This rubric uses descriptors of the dimensions of the Taxonomy of Intervention Intensity to support teams in selecting and evaluating validated interventions for small groups or individual students.
This guide is a set of strategies and key practices with the ultimate goal of supporting students with the most intensive behavioral needs, their families, and educators in their transitions back to school during and following the global pandemic in a manner that prioritizes their health and safety, social and emotional needs, and behavioral and academic growth.
Staff from the Exceptional Children department in Charlotte-Mecklenburg Schools convened a group of their teachers in Spring 2020 to share their perspectives and ideas. This advisory group includes approximately 20 teachers of exceptional children across Charlotte-Mecklenburg Schools. In this Voices from the Field video, the National Center on Intensive Intervention spoke with four teachers in the advisory group about their work during COVID-19 restrictions.
Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.