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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Assessment is an essential part of the data-based individualization (DBI) process and a multi-tiered system of support (MTSS). Without technically sound assessment, which provides accurate, meaningful information, a teacher has no objective method for determining what a student needs or how to intensify instruction to meet those needs. The close connection between assessment and intervention is at the foundation of the DBI process. This connection is what drives teacher decision making. With the right assessment tools and guidance on how to use them, teachers can make sound, data-based decisions about who needs intensive intervention, when to make instructional changes, and what skills to focus on. In the tables below, find resources to support the selection and evaluation of screening, progress monitoring and diagnostic assessments.
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.
Intensive Intervention in Reading Course: Module 4 Overview This module provides an overview of data-based individualization (DBI), including using CBM measures, how to present level of performance and set student goals, and use data to make instructional decisions. This module is divided into five parts with an introduction and closing. A 508 compliant version of the full PowerPoint presentation across all parts of the module, a version of the PowerPoint that includes all the animations, and a workbook is available below.
This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive behavior intervention based on student need.
This checklist can be used by intervention providers or planning teams to review, document, and improve implementation of the data-based individualization (DBI) process and monitor whether the student intervention plans were implemented as intended.
This video from the REL Midwest features Michigan educators discussing how districts can accelerate reading growth for young learners. Educators and leaders from Chippewa Hills School District, specifically discuss the use of data-based individualization (DBI).
This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
The Academic Intervention Taxonomy Briefs provide educators with information they can use to evaluate the appropriateness of academic interventions available on the academic intervention tools chart for a specific student or group of students who require intervention. The information included in the briefs is organized along the seven dimensions of the Taxonomy of Intervention Intensity
Research indicates that for successful implementation to occur, it is important to look at not only what is being implemented but how it is implemented. Implementing DBI often necessitates that educators make school-wide instructional adaptations, engage in systematic data analysis, and conduct individualized student-level decisions at levels that task the bandwidth of resources, staffing, and budgets of many schools. Assessing readiness from multiple stakeholders with different perspectives prior to implementation allows educators across many levels (schools, districts, and states) to prioritize areas for their initial efforts and then slowly use the momentum to build capacity toward full implementation. In this section, find training materials, lessons learned from those who have implemented DBI, and tools to assess your initial readiness and build capacity to implement intensive intervention.
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