This module focuses on behavioral progress monitoring within the context of the DBI process and addresses: (a) methods available for behavioral progress monitoring, including but not limited to Direct Behavior Rating (DBR), and (b) using progress monitoring data to make decisions about behavioral interventions.
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Monitoring Student Progress for Behavioral Interventions (DBI Professional Learning Series Module 3)
In this article, Dr. Carrie Thomas Beck from the Oregon Department of Education discusses the dyslexia law in Oregon, the role of intensive intervention in Oregon’s dyslexia initiative, and provides advice for states defining their dyslexia frameworks.
This document addresses five guiding questions for educators to consider when reviewing and interpreting assessment data for English Learners and includes links to selected resources.
This handout briefly defines the seven dimensions of the Taxonomy of Intervention Intensity for academics and behavior. The Taxonomy of Intervention Intensity was developed based on research to support educators in evaluating and building intervention intensity. The seven dimensions include strength, dosage, alignment, attention to transfer, comprehensiveness, behavior or academic support, and individualization.
This two page handout highlights how to use the Taxonomy of Intervention Intensity when selecting, evaluating, and intensifying interventions for students who are English learners (ELs). Specific considerations for ELs are provided across the dimensions of strength, dosage, alignment. attention to transfer, comprehensiveness, behavioral support, and individualization.
This module was adapted from a series of training modules developed by the National Center on Intensive Intervention (NCII) and is aimed at district or school teams involved in the initial planning for using data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The audience for this module may include school teams supporting academic intervention and progress monitoring in middle school mathematics.
Using multiple data sources, the teacher or team makes a decision to adapt the intervention program to better meet the student’s individual needs. The teacher or team outlines these adaptations in an individual student plan. The plan may include adaptation strategies along several dimensions. These strategies may include quantitative changes, such as providing more opportunities for a student to respond by increasing the length or frequency of the intervention, or decreasing the size of the intervention group.
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 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.
In this Voices from the Field post, Emma Shanahan reflects on her experiences with progress monitoring and data-based decision making as a teacher and shares findings from her recent research on DBI professional development.