This module is intended to help educators and administrators to dive deeper into the steps of the data-based individualization (DBI) process for individualizing and intensifying interventions.
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DBI Process
Subject
Implementation Guidance and Considerations
Student Population
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This self-paced module provides the foundational information for users interested in learning more about intensive intervention and the DBI process.
In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
This lesson includes a tip sheet and a video tutorial that demonstrates how to create and implement the 5-point scale in a virtual setting.
This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
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.
This presentation was delivered by Dr. Tessie Rose Bailey as part of the Colorado Multi-Tiered System of Support Virtual Summit 2020. In the presentation, Dr. Bailey focused on considerations for providing virtual intervention and progress monitoring and highlights resources developed by the National Center on Intensive Intervention. Related Resources Find additional resources for educators and families support students at home Supporting Students With Intensive Needs During COVID-19
In this Voices from the Field piece, we talk to Dr. Chrissy Brown, a recent National Center for Leadership in Intensive Intervention (NCLII) scholar. Dr. Brown discusses the NCLII program and how it has guided her in preparing educators to implement intensive interventions.
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.
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).