This webinar provides an overview of a project focused on increasing literacy outcomes using DBI, inclusion, and enhancing individualized education programs.
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DBI Process
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Implementation Guidance and Considerations
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Using DBI to Improve Literacy Outcomes for Students with Intellectual and Developmental Disabilities
This brief offers recommendations to support educators to efficiently collect, analyze, and use diagnostic data to adapt or intensify intervention.
This IRIS Star Legacy Module, first in a series of two, overviews data-based individualization and provides information about adaptations for intensifying and individualizing instruction. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This webinar focuses on ways educators and educational leaders can increase their capacity to develop skilled readers and writers, identify critical dimensions for designing intervention platforms as the foundation for effective instruction, and adapt interventions to increase the instructional intensity.
Teams are a vital part of an effective multi-tiered system of supports (MTSS) across both academics and behavior as well as special education. Making connections across the across the various teams used in MTSS and special education can be challenging. This resource from NCII and the PBIS Center, provides information about how DBI can support IEP implementation and provides a table with key considerations for teams working across the MTSS system.
This guide is intended to accompany the sample literacy lessons and activities on the NCII website. It is divided into four sections covering the five components of reading, instructional principles of reading instruction intervention, how to use the NCII reading lessons, and additional resources.
Data-based individualization (DBI) is a research-based process for individualizing and intensifying interventions through the systematic use of assessment data, validated interventions, and research-based adaptation strategies. This document introduces and describes the DBI process and how it can be used to support students who require intensive intervention in academics and/or behavior.
The DBI Implementation Rubric and the DBI Implementation Interview are intended to support monitoring of school-level implementation of data-based individualization (DBI). The rubric is based on the structure of the Center on Response to Intervention’s Integrity Rubric and is aligned with the essential components of DBI and the infrastructure that is necessary for successful implementation in Grades K–6. It describes levels of implementation on a 1–5 scale across DBI components. The rubric is accompanied by the DBI Implementation Interview which includes guiding questions that may be used for a self-assessment or structured interview of a school’s DBI leadership team.
An effective and efficient data system is essential for successful implementation of a multi-tiered system of support (MTSS). However, prior to selecting an appropriate system, schools and districts must identify what its staff and community need and what resources the district or school has to support an MTSS data system. This two-step tool can help teams to consider both what their needs are and to evaluate available tools against those needs. Step 1 can help your team systematically identify and document your MTSS data system needs and current context and step 2 focuses on selecting and evaluating a data system for conducting screening and progress monitoring within a tiered system of support based on the identified needs and context from step 1