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.
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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).
This fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.
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.
Part 2 of the two part series about UCF's project bridges highlights challenges and successes the program has faced when trying to build the skills and competencies of educators to implement intensive intervention.
In this article, Drs. Mary Little, Cynthia Pearl and Dena Slanda share lessons and strategies to support teachers in developing the skills and competencies to implement intensive intervention.
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. The DBI process includes five iterative steps:
Intensive intervention teams can use these checklists to monitor implementation of the data-based individualization (DBI) process during initial planning and ongoing review (progress monitoring) meetings in order to ensure teams develop high quality student plans. These detailed checklists may be most beneficial for less experienced teams. As teams become more familiar with DBI implementation, they may choose to use the checklists less frequently or focus on only a subset of items.
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 white paper summarizes the proceedings of a summit that was focused on integrating research knowledge on promising approaches into intensive intervention and implementation to improve academic outcomes for students with disabilities who have severe and persistent learning need. In addition, it includes responses from three participants representing perspectives from policy (David Chard, Wheelock College), research (Nathan Clemens, University of Texas at Austin), and practice (Steve Goodman, Michigan Integrated Behavior and Learning Support Initiative).
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