This two page handout defines the Taxonomy of Intervention Intensity through guiding questions and highlights when the Taxonomy of Intervention Intensity can be used within the data-based individualization (DBI) process. Teams can use the dimensions to evaluate a current intervention, select a new intervention and intensify interventions when students do not respond.
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DBI Process
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In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
These professional learning training materials are intended to assist district or school teams involved in initial planning or implementation of data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The modules listed below provide an overview of the DBI process and more in-depth exploration of the various components of DBI.
Support from leaders is essential for effective DBI implementation. This resource illustrates how DBI can help principals and local level administrators leverage existing resources, integrate supports for academics and behavior, define Tier 3, align special education and MTSS, establish effective data meetings, and improve outcomes for students who are at-risk for poor learning outcomes. In addition, the resource shares strategies and resources available to support implementation
This collection of training materials can be used to provide an overview of the Taxonomy of Intervention Intensity for selecting, evaluating, and intensifying interventions or to provide specific examples in reading, mathematics, and behavior. The training materials include presentation slides with suggested speaker notes and workbooks with application activities. The modules are intended to be delivered by a trained, knowledgeable professional.
The purpose of this module is to introduce schools interested in implementing intensive intervention to the infrastructure needed to implement data-based individualization (DBI). The module includes presentation slides with integrated activities and handouts to help teams determine their readiness and develop an action plan for implementation.
NCII, through a collaboration with the University of Connecticut, developed a set of course modules focused on developing educators’ skills in using explicit instruction. These course modules are designed to support faculty and professional development providers with instructing pre-service and in-service educators who are developing and/or refining their implementation of explicit instruction.
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.
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 training module demonstrates how academic progress monitoring fits into the Data-Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.
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