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.
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DBI Process
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Implementation Guidance and Considerations
Student Population
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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).
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.
This series is intended for educators at the state and local level who work with secondary students with intensive behavioral needs during virtual learning and the return to in-person.
This resource developed by Sarah Thorud, Elementary Reading Specialist from Clatskanie School District in Oregon focuses on implementing screening and progress monitoring virtually. It includes guiding questions and considerations for implementation, video examples, and a sample sign-up sheet for screening and progress monitoring students virtually.
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 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).