This webinar introduce a series of data teaming tools designed to help facilitators and participants before, during, and after their intervention meeting.
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Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
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This audio story shares New York City's DBI implementation approach, successes, and lessons learned about sustainability
This interactive self-paced module is intended to help educators and administrators learn about using teaming to support the data-based individualization (DBI) process.
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.
This checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
This question bank includes questions that teams can use to develop a hypothesis about why an individual or group of students may not be responding to an intervention.
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.
With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
This template is intended to assist with the planning and documentation of dimensions of an intervention for small groups or an individual student within the data-based individualization (DBI) process.
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.