This updated training module provides a rationale for intensive intervention and an overview of data-based individualization (DBI), NCII’s approach to providing intensive intervention. DBI is a research-based process for individualizing validated interventions through the systematic use of assessment data to determine when and how to intensify intervention. Two case studies, one academic and one behavioral, are used to illustrate the process and highlight considerations for implementation.
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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.
The MTSS Fidelity of Implementation Rubric and Summary Sheet are for use by individuals responsible for monitoring the school-level fidelity of MTSS implementation.
This module focuses primarily on selecting evidence-based interventions that align with the functions of behavior for students with severe and persistent learning and behavior needs. The emphasis of this training will include four main content areas: (a) relating assessment to function, (b) selecting evidence-based interventions that align with functions of behavior, (c) linking assessment and monitoring, and (d) connecting data with the evidence-based interventions selected. The overarching goal is to connect concepts and theories in behavior and begin planning how intensive intervention can be put into practice to support students with intensive behavioral 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.
In this video, Mary Little, Professor and Program Coordinator of the Department of Child, Family, and Community Services at the University of Central Florida discusses why data and data-based decision making such a critical part of instruction and intervention.
In this video, Dr. Rob Horner, Professor of Special Education at the University of Oregon and co-Director of OSEP Technical Assistance Center on PBIS and the OSEP Research and Demonstration Center on School-wide Behavior Support discusses key considerations for developing effective information systems.
In this video, Michele Walden-Doppke, M.A., CAGS, Response to Intervention (RTI) Technical Assistance Provider with Northern Rhode Island Collaborative for Rhode Island Department of Education (RIDE) and NCII Coach in Coventry Public Schools discusses infrastructure elements that support the implementation of intensive intervention.
Data teams serve multiple roles in the data-based individualization (DBI) process and across a multi-tiered system of supports (MTSS). Although schools may have multiple teams that review different types of data across a multi-tiered system of supports (MTSS), the intensive intervention or DBI team is focused on the needs of individual students who are not making progress in their current intervention or special education program. It is critical that these meetings are driven by data, occur regularly, and use an efficient, consistent process that allows participants to review progress and make intervention decisions for students. NCII has created a series of tools to help teams establish efficient and effective individual student data meetings.
This audio story shares New York City's DBI implementation approach, successes, and lessons learned about sustainability
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