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).
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DBI Process
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Implementation Guidance and Considerations
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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).
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 Innovation Configuration can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS. The expectation is that these skills can be further honed and supported through inservice as practicing teachers.
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.
This is the first module in a series of modules about intensive intervention in reading. There are two parts in this module that answer the questions (1) why is intensive intervention in reading important? and (2) how does data-based individualization (DBI) apply to reading?
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).
This module provides an overview of diagnostic assessments, using error analysis with CBMs, developing and using curriculum-based assessments (CBAs), and integrating diagnostic and progress monitoring data to inform instructional adaptations.
This collection highlights a sampling of articles focused on intensive intervention and data-based individualization (DBI). Although there is a wealth of research on key components of the DBI process (e.g., progress monitoring, validated intervention programs), this list is not intended to include articles that focus on specific steps in the DBI process, nor is it an exhaustive review of all available literature. In the list below, we highlight seminal research on DBI and articles published since 2011, when NCII was first funded.
This module identifies Tier II and Tier III interventions for students at risk and high risk for behavioral challenges. By the end of this module you should be able to: Describe the decision-making process to indicate Tier II is appropriate Identify critical features of Tier II Discuss how to modify Tier II interventions to meet the needs of more students Highlight critical elements of a Functional Behavior Assessment (FBA) Choose a desired and replacement behavior Complete a Competing Pathway Model Begin to identify strategies to make the problem behavior irrelevant, inefficient, and ineffective