This webinar reviews keys recommendations and lessons learned to help school and district leaders establish the conditions needed for educators to successfully implement data-based individualization (DBI) for students with the most intensive needs
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Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
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This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
This webinar introduce a series of data teaming tools designed to help facilitators and participants before, during, and after their intervention meeting.
State education agencies (SEAs) have an important role in initiating, supporting, and sustaining district- and school-level implementation of intensive intervention for students with severe and persistent learning and behavior needs. This document outlines five recommendations offered by SEA personnel who successfully led DBI capacity-building efforts in their states.
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 question bank includes questions that teams can use to develop a hypothesis about why an individual or group of students may not be responding to an intervention.
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.
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.