This video features reflections from Bill Rasplica, the former executive director of Franklin Pierce Schools, about his experiences implementing DBI, lessons learned, and recommendations for other district leaders.
Implementation Guidance and Considerations
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.
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.
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 three-part Voices from the Field video series profiles how Education Service Center (ESC) 15 in Texas approached implementing the DBI process in San Saba Independent School District (ISD). In these videos, Dedra Carter and Valerie Moos from ESC 15 and Jenna McSherry from San Saba ISD, discuss their experiences and recommendations for other districts implementing DBI.
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 fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.
In this article, Drs. Ketterlin Geller, Lembke, and Powell discuss how they are supporting educators to implement (1) the process of data-based individualization (DBI), (2) the principles of explicit and systematic instruction, and (3) key components of algebra readiness as part of Project STAIR (Supporting Teaching of Algebra: Individual Readiness).
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: