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.
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Implementation Guidance and Considerations
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This activity was developed by Etmi Lopes Martins, school psychologist at Robert F. Kennedy Elementary School in Providence, Rhode Island. This lesson includes a tip sheet and a video tutorial that demonstrates how to create and implement the 5-point scale in a virtual setting. A 5-point scale is a simple social and emotional learning tool that can help students with self-management. To learn more about self-management and the 5-point scale, visit NCII’s behavioral strategy guide.
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:
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:
The purpose of this document is to provide content-specific examples of how to structure educator-level and/or systems-level coaching as a mechanism to ensure ongoing professional learning to support tiered intervention. This document provides examples of coaching supports, models, and functions within the context of tiered intervention (e.g., RtI, PBIS, MTSS) and data-based decision making (e.g., data-based individualization [DBI]) for educators who already have foundational knowledge and/or experience with coaching.
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 two page handout defines the Taxonomy of Intervention Intensity through guiding questions and highlights when the Taxonomy of Intervention Intensity can be used within the data-based individualization (DBI) process. Teams can use the dimensions to evaluate a current intervention, select a new intervention and intensify interventions when students do not respond.
This training module, includes four sections that (a) provide an overview of administering common general outcome measures for progress monitoring in reading and mathematics, (b) review graphed progress monitoring data, and (c) provide guidance on identifying what type of skills the intervention should target to be most effective in reading and mathematics.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.
This is part 3 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide participants with an introduction to error analysis of curriculum-based measures for the purpose of identifying skill deficits and providing examples of error analysis in reading and mathematics. Part 4, “Identifying Target Skills,” will further link these skill deficits to intervention.