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 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. Teams may consider using data available on the National Center on Intensive Intervention Academic Tools Chart and the publishers’ websites as well as results from previous implementation efforts. Each dimension will be rated on a scale of 0– Fails to Address Standard to 3 – Addresses Standard Well. Taxonomy of Intervention Intensity: Academic Rating Rubric Related Resources Taxonomy of Intervention Intensity Resources
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.
This guide highlights 5 key practices for teachers and families to support all students, including students with disabilities, at school and home. For each practice, the guide provides (a) tips for teachers to support students with disabilities during instruction; (b) tips for families that educators can share to support or enhance learning at home, especially during periods of remote instruction; and (c) free-access resources that include strategies shown to be effective by research (e.g., informational guides, downloadable materials, research-based programs).
This series includes video examples and tip sheets to help educators and families in using the NCII reading and mathematics sample lessons to support students with intensive needs. These lessons provide short instructional routines to encourage multiple practice opportunities using explicit instruction principles. The videos and tip sheets describe how educators can use the sample lessons to support instruction in a virtual setting, how educators can share these lessons with parents, and how parents can also implement the lessons to provide additional practice opportunities.
These videos and tips are part of a series of products to support students with intensive needs in the face of COVID-19. These videos illustrate how parents and grandparents can implement the NCII reading and mathematics sample lessons to provide additional practice. In addition to the video examples, a tip sheet is available to help parents implement the lessons. Implementation of Reading Lesson: Parent Example
The purpose of this document is to provide content-specific examples of how to structure educator-level and/or systems-level coaching as a mechanism to ensure ongoing professional learning to support tiered intervention. This document provides examples of coaching supports, models, and functions within the context of tiered intervention (e.g., RtI, PBIS, MTSS) and data-based decision making (e.g., data-based individualization [DBI]) for educators who already have foundational knowledge and/or experience with coaching.
The purpose of this guide is to provide an overview of behavioral progress monitoring and goal setting to inform data-driven decision making within tiered support models and individualized education programs (IEPs).