During fall 2020, educators provided virtual, in-person, and hybrid intervention with an ongoing need to engage with and support parents and families. Although the context and environment may have changed, the focus on providing high-quality interventions with validated practices, monitoring student progress, and adapting and intensifying supports based on student data as outlined in the data-based individualization (DBI) process continues to be applicable across virtual, in-person, or hybrid models. This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
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.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions. Webinar 1: Don't Panic, Pivot! Tips for Implementing Data-Based Individualization (DBI) for the Synchronous and Asynchronous Learner
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.
Are you confused about how to support the social-behavioral needs of your learners as you return to school this fall? How can you ensure that all students, including those with intensive needs, have access to instruction regardless of virtual, in-person, or hybrid learning? In this webinar, Dr. Teri Marx and Stacy Hirt from the National Center on Intensive Intervention and Dr. Leanne Hawken, Professor Emeritus in the Department of Special Education at the University of Utah, highlight strategies schools should consider in relationship to their implementation of social-behavioral supports across the continuum of tiers in a multi-tiered system of support framework as they return to school during COVID-19 restrictions.
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.
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.
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?
This collection highlights a sampling of recent research and journal articles focused on intensive intervention and data-based individualization (DBI). As different terms are used to describe intensive intervention, the collection of articles includes those that use various related terms such as precision teaching, data-based decision making (when in the context of providing individualized instruction), Tier 3, intervention adaptation, and individualization. In addition, 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 cover specific steps in the process nor is it an exhaustive review of all available literature. Additional articles and research will be added over time. The resource begins with a list of article citations, beginning with the most recent.
This Voices from the Field piece highlights how North Carolina, Oregon, Washington, and Texas have raised awareness, visibility, and statewide knowledge of data-based individualization (DBI) at statewide conferences through keynote speakers, workshops, breakout sessions, and facilitated team time.