This Innovation Configuration can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS. The expectation is that these skills can be further honed and supported through inservice as practicing teachers.
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This guide is a set of strategies and key practices with the ultimate goal of supporting students with the most intensive behavioral needs, their families, and educators in their transitions back to school during and following the global pandemic in a manner that prioritizes their health and safety, social and emotional needs, and behavioral and academic growth.
Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
The purpose of this guide is to provide an overview of behavioral progress monitoring and goal setting to inform data-driven decision making within tiered support models and individualized education programs (IEPs).
If you are like most educators, you agree with the idea of providing intensive intervention for students with the most intractable academic and behavior problems. The question you may be asking is, how do I find the time? This guide includes strategies that educators can consider when trying to determine how to find the time for this intensification within the constraints of busy school schedules. Supplemental resources, planning questions, and example schedules are also provided.
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.
The purpose of this guide is to provide brief explanations of key practices that can be implemented when working with students in need of intensive intervention in mathematics. Special education instructors, math interventionists, and others working with students who struggle with mathematics may find this guide helpful. Strategies presented in this guide should be used in conjunction with teaching guides developed for specific mathematical concepts.
This log can be used as a daily and weekly record of the implementation of an individual student’s intensive intervention plan. This information, along with progress monitoring graphs, can inform team intervention and data review meetings. You may choose to supplement the logs with additional items or more detailed intervention notes.
This module focuses primarily on selecting evidence-based interventions that align with the functions of behavior for students with severe and persistent learning and behavior needs. The emphasis of this training will include four main content areas: (a) relating assessment to function, (b) selecting evidence-based interventions that align with functions of behavior, (c) linking assessment and monitoring, and (d) connecting data with the evidence-based interventions selected. The overarching goal is to connect concepts and theories in behavior and begin planning how intensive intervention can be put into practice to support students with intensive behavioral needs.
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.