This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
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Implementation Guidance and Considerations
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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.
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.
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. The DBI process includes five iterative steps:
This series of infographics, developed in collaboration with the Rhode Island Parent Information Network, are intended to provide a high-level overview of intensive intervention, questions parents and families might want to ask school teams to learn more, and tips for parents in supporting their child who is receiving intensive intervention. These resources should not replace ongoing communication between schools, and parents and families.
This report presents findings from an exploratory study of how five high-performing districts, which we refer to as NCII’s knowledge development sites, defined and implemented intensive intervention. The findings offer lessons that other schools and districts can use when planning for, implementing and working to sustain their own initiatives to provide intensive intervention for students with the most severe and persistent learning and/or behavioral needs.
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.
There are a variety of terms used interchangeably to define special education: specially-designed instruction, Tier 3 supports, and intensive intervention, but, do they mean the same thing? In this presentation, delivered at the 2017 OSEP Leadership Conference, state leaders of special education, David Sienko from the Rhode Island Department of Education and Glenna Gallo, from the Washington State Board of Education – alongside personnel from the National Center on Intensive Intervention – shared perspectives on how special education is defined to espouse commonalities across terminology and services to support students with disabilities. Presentation
The purpose of this module is to introduce schools interested in implementing intensive intervention to the infrastructure needed to implement data-based individualization (DBI). The module includes presentation slides with integrated activities and handouts to help teams determine their readiness and develop an action plan for implementation.
This white paper summarizes the proceedings of a summit that was focused on integrating research knowledge on promising approaches into intensive intervention and implementation to improve academic outcomes for students with disabilities who have severe and persistent learning need. In addition, it includes responses from three participants representing perspectives from policy (David Chard, Wheelock College), research (Nathan Clemens, University of Texas at Austin), and practice (Steve Goodman, Michigan Integrated Behavior and Learning Support Initiative).