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:
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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.
Intensive Intervention in Reading Course: Module 6 Overview This module provides strategies on how to adapt word reading instruction to improve instructional modeling, student practice, and approaches to giving feedback. This module is divided into three parts with an introduction. A 508 compliant version of the full PowerPoint presentation across all parts of the module, a version of the PowerPoint that includes all the animations, and a workbook is available below.
Intensive Intervention in Reading Course: Module 4 Overview This module provides an overview of data-based individualization (DBI), including using CBM measures, how to present level of performance and set student goals, and use data to make instructional decisions. This module is divided into five parts with an introduction and closing. A 508 compliant version of the full PowerPoint presentation across all parts of the module, a version of the PowerPoint that includes all the animations, and a workbook is available below.
In this article, Drs. Ketterlin Geller, Lembke, and Powell discuss how they are supporting educators to implement (1) the process of data-based individualization (DBI), (2) the principles of explicit and systematic instruction, and (3) key components of algebra readiness as part of Project STAIR (Supporting Teaching of Algebra: Individual Readiness).
In Module 3 of the Intensive Intervention in Mathematics Course Content we emphasize the necessity for using evidence-based interventions or strategies as the starting point of instruction within intensive intervention. In this module, educators will learn about: (1) The umbrella term of evidence-based practices and different types of evidence-based practices; (2) Where to locate evidence-based practices; (3) How to design the instructional platform for use within intensive intervention.
This handout briefly defines the seven dimensions of the Taxonomy of Intervention Intensity for academics and behavior. The Taxonomy of Intervention Intensity was developed based on research to support educators in evaluating and building intervention intensity. The seven dimensions include strength, dosage, alignment, attention to transfer, comprehensiveness, behavior or academic support, and individualization.
This module is intended to help educators and administrators to dive deeper into the steps of the data-based individualization (DBI) process for individualizing and intensifying interventions.
This presentation was delivered by Dr. Tessie Rose Bailey as part of the Colorado Multi-Tiered System of Support Virtual Summit 2020. In the presentation, Dr. Bailey focused on considerations for providing virtual intervention and progress monitoring and highlights resources developed by the National Center on Intensive Intervention. Related Resources Find additional resources for educators and families support students at home Supporting Students With Intensive Needs During COVID-19
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.