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.
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DBI Process
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Implementation Guidance and Considerations
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View the webinar recording from the December 14, 2023 webinar focused on how the RIOT/ICEL matrix can support problem-solving by helping teams to organize their diagnostic data, refine hypotheses, and guide decision making
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, will provide 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 will share project findings and provide recommendations for integrating those findings into professional development and practice to improve student outcomes.
This webinar, featuring Drs. Donna Sacco, John Hoover, and Tracy Spies, illustrates considerations for implementing data-based individualization (DBI) with ELs that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs. They share why it is important to (a) deliver instruction that represents culturally and linguistically sustaining best practices, and (b) distinguish the needs and assets of learners to improve progress (i.e., second-language acquisition, culture, learning challenges).
Getting along with others, paying attention, following directions, making responsible decisions, and managing emotions are challenges for many students who require intensive intervention, and may be linked to difficulties with executive functioning, communication, behavior, and academic learning. In this webinar, presenters Mara Schanfield and Zach Weingarten shared an overview of how social emotional learning (SEL) relates to intensive intervention and offer sample strategies and resources for building social and emotional competencies for students in need of intensive learning, social, emotional, or behavioral supports.
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. The hypothesis should help guide intervention planning and selection of intensification strategies using the Intervention Intensification Strategy Checklist. When developing a hypothesis, teams should consider the intervention design, fidelity of implementation, and learner needs. Intervention fidelity data collected using the Student Intervention Implementation Log and informal diagnostic data may help teams answer the questions included in the question bank.
The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying needs. 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.
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.
Teams are a vital part of an effective multi-tiered system of supports (MTSS) across both academics and behavior as well as special education. Making connections across the across the various teams used in MTSS and special education can be challenging. This resource from NCII and the PBIS Center, provides information about how DBI can support IEP implementation and provides a table with key considerations for teams working across the MTSS system.
Data-based individualization (DBI) is a research-based process for individualizing and intensifying interventions through the systematic use of assessment data, validated interventions, and research-based adaptation strategies. The DBI process includes five iterative steps: