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. This document introduces and describes the DBI process and how it can be used to support students who require intensive intervention in academics and/or behavior.
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DBI Process
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Implementation Guidance and Considerations
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This module serves as an introduction to important concepts and processes for implementing functional behavior assessment (FBA), including behavior basics such as reinforcement and punishment. Throughout this module, participants will discuss both real world and school based examples to become familiar with the FBA process and develop a deeper understanding and awareness of the functions of the behavior. Key topics include (a) defining FBAs in the context of DBI; (b) basic concepts in behavior, including antecedents, behaviors, and consequences; (c) levels of FBAs; and (d) considerations and procedures for conducting FBAs.
The DBI process builds on a validated intervention program. This may also be called an evidence-based standard-protocol intervention or a Tier 2 intervention.
This webinar introduces the Taxonomy of Intervention Intensity as a method for systematically selecting an intensive intervention and guide teachers through modifying the intervention based on student need.
Progress monitoring, a key component of a multi-tiered system of support (MTSS), occurs throughout the data-based individualization (DBI) process to assess responsiveness to the validated intervention platform, as well as adaptations to the intervention. Prior to delivering the validated intervention platform, intervention teams should develop a progress monitoring plan that outlines the progress monitoring tool, student goal, and frequency of data collection and review. During delivery of the validated and adapted intervention, educators should collect and graph frequent progress monitoring data.
This module provides an overview of diagnostic assessments, using error analysis with CBMs, developing and using curriculum-based assessments (CBAs), and integrating diagnostic and progress monitoring data to inform instructional adaptations.
This module discusses approaches to intensifying academic interventions for students with severe and persistent learning needs. The module describes how intensification fits into DBI process and introduces four categories of intensification practices. It uses examples to illustrate concepts and provides activities to support development of teams’ understanding of these practices, and how they might be used to design effective individualized programs for students with intensive needs.
When a student fails to respond to a validated intervention, teams need to identify why the student is not responding to determine how to adapt the intervention. Diagnostic data can assist teams in this process. They may be used to understand a student’s specific skill deficits and strengths or to identify the environmental events that predict and maintain the student’s problem behavior.
These professional learning training materials are intended to assist district or school teams involved in initial planning or implementation of data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The modules listed below provide an overview of the DBI process and more in-depth exploration of the various components of DBI.
This video demonstrates how to use fraction tiles to convert mixed numbers to improper fractions. As students practice this process with fraction tiles, they will also gain fluency with determining different fractions that are equivalent to 1.