In this video, Dr. Evelyn Johnson, Associate Professor at Boise State University, discusses how data can be used to support eligibility decisions for students with disabilities.
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DBI Process
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Implementation Guidance and Considerations
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In this video, Nicole Bucka, NCII coach and MTSS professional development provider for Rhode Island discuss lessons learned from implementing intensive intervention at the middle and secondary level.
In this video, Rob Horner, Professor of Special Education at the University of Oregon and co-Director of OSEP Technical Assistance Center on PBIS and the OSEP Research and Demonstration Center on School-wide Behavior Support, discusses how data systems can be used within the context of intensive intervention.
Staff from the Exceptional Children department in Charlotte-Mecklenburg Schools convened a group of their teachers in Spring 2020 to share their perspectives and ideas. This advisory group includes approximately 20 teachers of exceptional children across Charlotte-Mecklenburg Schools. In this Voices from the Field video, the National Center on Intensive Intervention spoke with four teachers in the advisory group about their work during COVID-19 restrictions.
In this video, Lindsay Jones the CEO of the National Center on Learning Disabilities, shares some considerations and strategies that educators can use to support partnering with families of students with intensive needs.
In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
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 tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.
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