In this webinar, experts from the PROGRESS Center and National Center on Intensive Intervention (NCII) model how practitioners can use data-based individualization (DBI) to develop and implement SDI for students with disabilities and a panel of special educators share how using DBI improved the efficiency and effectiveness of their service delivery, communication with families, and collaboration with other educators.
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DBI Process
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Implementation Guidance and Considerations
Student Population
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In this webinar, experts from the PROGRESS Center and National Center on Intensive Intervention (NCII) will model how practitioners can use data-based individualization (DBI) to develop and implement SDI for students with disabilities. A panel of special educators will share how using DBI improved the efficiency and effectiveness of their service delivery, communication with families, and collaboration with other educators.
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).
This log can be used as a daily and weekly record of the implementation of an individual student’s intensive intervention plan. This information, along with progress monitoring graphs, can inform team intervention and data review meetings. You may choose to supplement the logs with additional items or more detailed intervention notes.