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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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 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.
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.
If you are like most educators, you agree with the idea of providing intensive intervention for students with the most intractable academic and behavior problems. The question you may be asking is, how do I find the time? This guide includes strategies that educators can consider when trying to determine how to find the time for this intensification within the constraints of busy school schedules. Supplemental resources, planning questions, and example schedules are also provided.
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 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.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.