This module discusses approaches to intensifying academic interventions for students with severe and persistent learning needs. The module describes how intensification fits into DBI process and introduces four categories of intensification practices. It uses examples to illustrate concepts and provides activities to support development of teams’ understanding of these practices, and how they might be used to design effective individualized programs for students with intensive needs.
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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.
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.
In this video, Dr. Rolland O’Connor, Professor in the Graduate School of Education at the University of California Riverside a member of the NCII Academic Intervention Technical Review Committee, addresses the implications of early reading research for understanding late-emerging reading disabilities, working with students learning English, and preparing teachers to have a strong grounding in the stages of reading development.
This webinar presents a data-based decision-making framework to individualize instruction for students with intensive needs in writing.
Module 5 begins a series of modules on the topic of explicit instruction. Explicit instruction is about modeling and practicing to help students reach academic goals. Throughout the module, educators will learn how selecting an important objective and learning outcomes, designing structured instructional experiences, explaining directly, modeling the skills being taught and providing scaffolded practice to achieve mastery can be used within the DBI framework to support instruction.
These two modules from the IRIS Center introduce users to progress monitoring in reading and mathematics. Progress monitoring is a type of formative assessment in which student learning is evaluated to provide useful feedback about performance to both learners and teachers. Because the overall progress monitoring process is almost identical for any subject area, the content in the two modules is very similar.
The purpose of this document is to increase the capacity of practitioners and educational leaders to support a broad range of learners who need more literacy supports to become skilled readers and writers by identifying a set of essential practices that are research-supported and should be the focus of professional development. These practices for intensifying literacy instruction apply to those learners with severe and persistent reading and writing challenges who have not responded when provided with instruction aligned with state academic standards, regardless of disability status.
An effective and efficient data system is essential for successful implementation of a multi-tiered system of support (MTSS). However, prior to selecting an appropriate system, schools and districts must identify what its staff and community need and what resources the district or school has to support an MTSS data system. This two-step tool can help teams to consider both what their needs are and to evaluate available tools against those needs. Step 1 can help your team systematically identify and document your MTSS data system needs and current context and step 2 focuses on selecting and evaluating a data system for conducting screening and progress monitoring within a tiered system of support based on the identified needs and context from step 1
The Taxonomy of Intervention Intensity (Fuchs, Fuchs, & Malone, 2017) can be used to select or evaluate an intervention platform used as the validated intervention platform or the foundation of the DBI process. It can also be used to guide the adaptation of intensification of an intervention during the intervention adaptation step of the DBI process. The Taxonomy includes the following dimensions: