This collection of training materials can be used to provide an overview of the Taxonomy of Intervention Intensity for selecting, evaluating, and intensifying interventions or to provide specific examples in reading, mathematics, and behavior. The training materials include presentation slides with suggested speaker notes and workbooks with application activities. The modules are intended to be delivered by a trained, knowledgeable professional.
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DBI Process
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These professional learning training materials are intended to assist district or school teams involved in initial planning or implementation of data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The modules listed below provide an overview of the DBI process and more in-depth exploration of the various components of DBI.
In this Voices from the Field post, we archive the presentations from day 2 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on preparing in-service and pre-service educators and leaders to implement intensive intervention.
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.
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 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 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 module was adapted from a series of training modules developed by the National Center on Intensive Intervention (NCII) and is aimed at district or school teams involved in the initial planning for using data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The audience for this module may include school teams supporting academic intervention and progress monitoring in middle school mathematics.
This updated training module provides a rationale for intensive intervention and an overview of data-based individualization (DBI), NCII’s approach to providing intensive intervention. DBI is a research-based process for individualizing validated interventions through the systematic use of assessment data to determine when and how to intensify intervention. Two case studies, one academic and one behavioral, are used to illustrate the process and highlight considerations for implementation.
This training module demonstrates how academic progress monitoring fits into the Data-Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.