In this video, John M. Hintze, Professor in the Department of Student Development at the University of Massachusetts Amherst explains why it is important to consider whether an assessment is biased against a specific sub-group.
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Monitoring Student Progress for Behavioral Interventions (DBI Professional Learning Series Module 3)
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.
In this video, Sandra Chafouleas, Professor of Educational Psychology in the Neag School of Education at the University of Connecticut, discusses the importance of progress monitoring in behavior and how it differs from screening and diagnostic assessment.
In this video, Sarah Powell, Assistant Professor in the Department of Special Education at the University of Texas at Austin, discusses key considerations when teaching students with math difficulty.
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.
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:
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.
This video demonstrates how to teach students to think flexibly about fractions. Similar to whole numbers, fractions can be put together and taken apart in many different combinations. Students should practice identifying these combinations so that they can become fluent with fraction addition and subtraction.
In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
This video illustrates the use of manipulatives to help students practice comparing quantities that are grouped as tens and ones. When numbers are represented with manipulatives organized as tens and ones, students develop a concrete understanding for using place value to comparing quantities. Students also benefit from multiple opportunities to talk about mathematics and use appropriate mathematics vocabulary such as “greater than” and “less than.”