NCII, through a collaboration with the University of Connecticut, developed a set of course content focused on developing educators’ skills in designing and delivering intensive mathematics instruction. This content is designed to support faculty and professional development providers with instructing pre-service and in-service educators who are developing and/or refining their implementation of intensive mathematics intervention
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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. This document introduces and describes the DBI process and how it can be used to support students who require intensive intervention in academics and/or behavior.
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.
Module 2 of the Intensive Intervention in Mathematics Course Content focuses on the assessment components of intensive intervention. We provide an overview of assessments before diving into instruction in order to stress the importance that intensive intervention cannot occur without adequate assessments in place.
In this video, Dr. Lynn Fuchs, Nicholas Hobbs Professor of Special Education and Human Development at Vanderbilt University and Senior Advisor to the National Center on Intensive Intervention, shares considerations for adapting interventions when the validated intervention program wasn’t successful.
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.
This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
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.
This module discusses how to define, measure and monitor behavior. By the end of the module you should be able to: Select an appropriate target behavior Write an operational definition for a target behavior Identify relevant dimensions of behavior Choose a measurement system based on relevant dimensions of behavior Use graphing conventions to create meaningful visual displays of data