This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
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DBI Process
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Implementation Guidance and Considerations
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This checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
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.
With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
This template is intended to assist with the planning and documentation of dimensions of an intervention for small groups or an individual student within the data-based individualization (DBI) process.
This webinar shares how to set ambitious behavioral goals for students by using a valid, reliable progress monitoring measure, and how to write measurable and realistic goals focused on the replacement behavior.
In this webinar, Drs. Tessie Rose Bailey and Zach Weingarten from the National Center on Intensive Intervention and the PROGRESS Center, as well as Thom Jones from the Wyoming Department of Education and Justine Essex from Freedom Elementary School in Cheyenne, Wyoming shared how to set ambitious goals for students by selecting a valid, reliable progress monitoring measure, establishing baseline performance, choosing a strategy, and writing a measurable goal.
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).
The 2017 Supreme Court decision Endrew F. v. Douglas County School District highlighted the importance of monitoring students’ progress toward appropriately challenging individualized educational program (IEP) annual goals and making changes to students’ educational programs when needed. In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances.
This fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.