This brief offers recommendations to support educators to efficiently collect, analyze, and use diagnostic data to adapt or intensify intervention.
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DBI Process
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Implementation Guidance and Considerations
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Getting along with others, paying attention, following directions, making responsible decisions, and managing emotions are challenges for many students who require intensive intervention, and may be linked to difficulties with executive functioning, communication, behavior, and academic learning. In this webinar, presenters Mara Schanfield and Zach Weingarten shared an overview of how social emotional learning (SEL) relates to intensive intervention and offer sample strategies and resources for building social and emotional competencies for students in need of intensive learning, social, emotional, or behavioral supports.
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.
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).
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.
This webinar discusses the integrated relationship between academics and behavior, reviews a case study example using DBI to provide individualized integrated academic and behavioral support based on student need, and shares behavioral strategies.