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.
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DBI Process
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Implementation Guidance and Considerations
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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 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 webinar addresses a challenge faced by many teachers: feeling inundated by data while struggling to find useful information to guide intervention decision-making
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 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.