This tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.
Error message
The page you requested does not exist. For your convenience, a search was performed using the words in the page you tried to access.
Search
Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
Search
This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
The purpose of this document is to provide an overview of the Center’s accomplishments and to highlight a set of lessons learned from the 26 schools that implemented intensive intervention while receiving technical support from the Center.
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.
It is important that the instructional practices and interventions delivered within a school’s multi-tiered system of support (MTSS) be grounded in evidence. However, the “practice” that happens within each tier is different; therefore, the type of evidence that is required for each tier also must be different. A useful way to think about evidence-based practices in MTSS is to think about levels of evidence that vary and correspond to the different levels of intervention intensity at each tier. In the tables below, find resources to support the selection and evaluation of Tier 1, Tier 2, and Tier 3 or 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.
The DBI Implementation Rubric and the DBI Implementation Interview are intended to support monitoring of school-level implementation of data-based individualization (DBI). The rubric is based on the structure of the Center on Response to Intervention’s Integrity Rubric and is aligned with the essential components of DBI and the infrastructure that is necessary for successful implementation in Grades K–6. It describes levels of implementation on a 1–5 scale across DBI components. The rubric is accompanied by the DBI Implementation Interview which includes guiding questions that may be used for a self-assessment or structured interview of a school’s DBI leadership team.
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 checklist can be used by intervention providers or planning teams to review, document, and improve implementation of the data-based individualization (DBI) process and monitor whether the student intervention plans were implemented as intended.
This video from the REL Midwest features Michigan educators discussing how districts can accelerate reading growth for young learners. Educators and leaders from Chippewa Hills School District, specifically discuss the use of data-based individualization (DBI).