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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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 resource is a companion to NCII’s Clarifying Questions to Create a Hypothesis to Guide Intervention Changes: Question Bank and provides additional questions for teams to consider for students who are English learners.
This document addresses five guiding questions for educators to consider when reviewing and interpreting assessment data for English Learners and includes links to selected resources.
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 provides an overview of the Academic Intervention Taxonomy Briefs and describes how they can help teachers design productive intervention programs for students with intensive academic needs.
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 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.
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.