This training module, Using the Taxonomy of Intervention Intensity Within the Data-Based Individualization Process: A Reading Example, introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated reading intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond. This module is a companion to Using the Taxonomy of Intervention Intensity to Select, Design, and Intensify Intervention with a specific focus on reading. At the end of the training participants will be able to:
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This training module, Using the Taxonomy of Intervention Intensity Within the Data-Based Individualization Process: A Mathematics Example, introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated mathematics intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond. This module is a companion to Using the Taxonomy of Intervention Intensity to Select, Design, and Intensify Intervention with a specific focus on mathematics. At the end of the training participants will be able to:
This training module introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated behavior intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.
This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
This training module, Using the Taxonomy of Intervention Intensity to Select, Design, and Intensify Intervention, introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond. At the end of the training participants will be able to:
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.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.
This webinar illustrates considerations for implementing data-based individualization (DBI) with English Learners that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs.
This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive behavior intervention based on student need.