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.
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DBI Process
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Implementation Guidance and Considerations
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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.
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.
This resource developed by Sarah Thorud, Elementary Reading Specialist from Clatskanie School District in Oregon focuses on implementing screening and progress monitoring virtually. It includes guiding questions and considerations for implementation, video examples, and a sample sign-up sheet for screening and progress monitoring students virtually.
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.
Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
The purpose of this guide is to provide an overview of behavioral progress monitoring and goal setting to inform data-driven decision making within tiered support models and individualized education programs (IEPs).
This collection highlights a sampling of articles focused on intensive intervention and data-based individualization (DBI). 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 include articles that focus on specific steps in the DBI process, nor is it an exhaustive review of all available literature. In the list below, we highlight seminal research on DBI and articles published since 2011, when NCII was first funded.
The 2017 Supreme Court decision Endrew F. v. Douglas County School District highlighted the importance of monitoring students’ progress toward appropriately challenging individualized educational program (IEP) annual goals and making changes to students’ educational programs when needed. In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances.