This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive literacy interventions based on student need.
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DBI Process
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Implementation Guidance and Considerations
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Module 6 is the second in a set of four course modules focused on explicit instruction. This module introduces the concept of supporting practices necessary for successful implementation of explicit instruction. The module introduces how to use effective methods to elicit frequent responses. Throughout the module, educators will learn how eliciting frequent responses support instruction within the DBI framework.
This is part 4 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part of the module is intended to provide participants with guidance for identifying skills to target in reading and math interventions.
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 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 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 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.
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 this video, Michelle Hosp, Associate Professor in the College of Education at the University of Massachusetts Amherst discusses why your progress monitoring tool may not directly focus on the skills that you are teaching.
This webinar presents a data-based decision-making framework to individualize instruction for students with intensive needs in writing.