This webinar reviews keys recommendations and lessons learned to help school and district leaders establish the conditions needed for educators to successfully implement data-based individualization (DBI) for students with the most intensive needs
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Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
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This three-part course provides a guide to available NCII self-paced learning courses that focus on academic progress monitoring. The collection begins with an overview of progress monitoring and the role of progress monitoring within the DBI process. The second module focuses defining two types of academic progress monitoring measures (general outcome measures and mastery measures) and considerations for identifying a target behavior and selecting a valid and reliable academic progress monitoring tool. The final module focuses on how you collect, graph, and make decisions based on academic progress monitoring data. While it is possible to take the courses individually or in a different order, this collection provides a suggested order for engaging in learning about academic progress monitoring.
This course collection provides a guide to available NCII courses for those who are newer to the DBI process or interested in learning more about how intensive intervention can support students with severe and persistent learning and/or social, emotional, or behavioral needs.
In this Voices from the Field post, Emma Shanahan reflects on her experiences with progress monitoring and data-based decision making as a teacher and shares findings from her recent research on DBI professional development.
This webinar discusses classroom management strategies educators can apply to improve access and outcomes for students with disabilities and students with intensive needs.
This brief highlights how to use culturally and linguistically aligned strategies to support multilingual learners within an multi-tiered system of supports framework
This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
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 (ELs). Teams may use these questions when considering a student’s progress monitoring data, intervention fidelity data, and informal diagnostic data.
Using DBI to Improve Literacy Outcomes for Students with Intellectual and Developmental Disabilities
How can data-based individualization (DBI) help educators to address the growing expectations for literacy outcomes for students with intellectual and developmental disabilities? In this webinar, Dr. Chris Lemons an NCII Advisor, Associate Professor of Special Education in the Graduate School of Education at Stanford University, and Co-Director of the Stanford Down Syndrome Research Center, provides an overview of activities conducted through an Office of Special Education Programs model demonstration project. This project focused on increased literacy outcomes using DBI, inclusion, and enhancing individualized education programs. The webinar shares project findings and provides recommendations for integrating those findings into professional development and practice to improve student outcomes.
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