This question bank includes questions that teams can use to develop a hypothesis about why an individual or group of students may not be responding to an intervention. The hypothesis should help guide intervention planning and selection of intensification strategies using the Intervention Intensification Strategy Checklist. When developing a hypothesis, teams should consider the intervention design, fidelity of implementation, and learner needs. Intervention fidelity data collected using the Student Intervention Implementation Log and informal diagnostic data may help teams answer the questions included in the question bank.
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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.
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.
Progress monitoring is an essential part of a multi-tiered system of supports (MTSS) and, specifically, the data-based individualization (DBI) process. It allows educators and administrators to understand whether students are responding to intervention and if adaptations are needed. In addition, these data are often used to set high-quality academic and behavioral goals within the individualized education program (IEP) for students with disabilities. With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
For children with the most severe and persistent academic and/or behavioral challenges, parent and family involvement is vital. School teams can use this guide to better understand intensive intervention and how to engage parents and families with the process.
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.
The purpose of this document is to provide an overview of the Center’s accomplishments and to highlight a set of lessons learned from the 26 schools that implemented intensive intervention while receiving technical support from the Center.
This tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.