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 webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
This webinar describes how the RIOT/ICEL matrix can support problem-solving by helping teams to organize their diagnostic data, refine hypotheses, and guide decision making.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.
This webinar illustrates considerations for implementing data-based individualization (DBI) with English Learners that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs.
This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive behavior intervention based on student need.
In this video, Dr. Devin Kearns, an Assistant Professor of Special Education in the Department of Education Psychology at the Neag School of Education at the University of Connecticut and NCII Trainer & Coach, discusses the importance of making changes in a systematic way when adapting interventions for students with intensive needs.