This brief highlights how to use culturally and linguistically aligned strategies to support multilingual learners within an multi-tiered system of supports framework
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DBI Process
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Implementation Guidance and Considerations
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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.
This brief offers recommendations to support educators to efficiently collect, analyze, and use diagnostic data to adapt or intensify intervention.
NCII developed this resource to help educators better understand the purpose of and considerations surrounding behavior screening in schools. Educators can use the information on this resource in conjunction with the Behavior Screening Tools Chart to (a) design a screening process for their school and (b) select or evaluate screening tools.
This question bank includes questions that teams can use to develop a hypothesis about why an individual or group of students may not be responding to an intervention.
This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This webinar focuses on ways educators and educational leaders can increase their capacity to develop skilled readers and writers, identify critical dimensions for designing intervention platforms as the foundation for effective instruction, and adapt interventions to increase the instructional intensity.
In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
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.