After initial data-based individualization (DBI) implementation, schools and districts need to own the work and deliver ongoing support, including supports for new teachers within existing budgets and staff time. Planning for sustainability upfront can help district leaders to streamline their implementation efforts. In New York City, Jason Borges and Meghan Duffy from the New York City Department of Education have found several successful strategies for DBI implementation that have helped make DBI self-sustaining. This audio story shares their DBI implementation approach, successes, and lessons learned about sustainability. The recording is broken into three parts.
Implementation Guidance and Considerations
In this Voices from the Field post, we archive the presentations from day 2 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on preparing in-service and pre-service educators and leaders to implement intensive intervention.
In this Voices from the Field post, we archive the presentations from day 1 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on creating the systems to support implementation of intensive intervention.
The Colorado Department of Education (CDE) has been working closely with NCII to align and scale up use of data-based individualization (DBI) across the state. One of the strategies CDE has used is the development of virtual learning resources and online learning modules on DBI to help make professional learning accessible to all educators. In this Voices from the Field video, Dr. Jason Harlacher and Veronica Fielder share CDE’s process for developing virtual learning modules on DBI and their strategies for ensuring the modules are accessible to educators.
This module is intended to help educators and administrators to dive deeper into the steps of the data-based individualization (DBI) process for individualizing and intensifying interventions.
This module provides the foundational information for users interested in learning more about intensive intervention and the DBI process. The module defines intensive intervention and DBI, describes how intensive intervention fits within a tiered system such as MTSS, RTI, or PBIS, demonstrates how intensive intervention can provide a systemic process to deliver specialized instruction for students with disabilities, and provides two case examples to allow viewers to apply new knowledge.
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).
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).
The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying needs. In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
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.