This report reviews the reach of the NCII tools charts on SEA websites and within SEA policy to support identification and implementation of evidence-based interventions and assessment tools.
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Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
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This webinar reviews keys recommendations and lessons learned to help school and district leaders establish the conditions needed for educators to successfully implement data-based individualization (DBI) for students with the most intensive needs
This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
This Innovation Configuration can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS. The expectation is that these skills can be further honed and supported through inservice as practicing teachers.
This guide is a set of strategies and key practices with the ultimate goal of supporting students with the most intensive behavioral needs, their families, and educators in their transitions back to school during and following the global pandemic in a manner that prioritizes their health and safety, social and emotional needs, and behavioral and academic growth.
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).
For children with the most severe and persistent academic and/or behavioral challenges, parent and family involvement is vital. School teams can use this guide to better understand intensive intervention and how to engage parents and families with the process.
This training module demonstrates how academic progress monitoring fits into the Data-Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.