In this video, Ralph P. Ferretti, Professor of Education and Psychological & Brain Sciences at the University of Delaware explain why it is important to consider both the study quality and the study results when determining the evidence base of an intervention.
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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.
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.
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.
It is important that the instructional practices and interventions delivered within a school’s multi-tiered system of support (MTSS) be grounded in evidence. However, the “practice” that happens within each tier is different; therefore, the type of evidence that is required for each tier also must be different. A useful way to think about evidence-based practices in MTSS is to think about levels of evidence that vary and correspond to the different levels of intervention intensity at each tier. In the tables below, find resources to support the selection and evaluation of Tier 1, Tier 2, and Tier 3 or intensive interventions.
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:
Assessment is an essential part of the data-based individualization (DBI) process and a multi-tiered system of support (MTSS). Without technically sound assessment, which provides accurate, meaningful information, a teacher has no objective method for determining what a student needs or how to intensify instruction to meet those needs. The close connection between assessment and intervention is at the foundation of the DBI process. This connection is what drives teacher decision making. With the right assessment tools and guidance on how to use them, teachers can make sound, data-based decisions about who needs intensive intervention, when to make instructional changes, and what skills to focus on. In the tables below, find resources to support the selection and evaluation of screening, progress monitoring and diagnostic assessments.
The Academic Intervention Taxonomy Briefs provide educators with information they can use to evaluate the appropriateness of academic interventions available on the academic intervention tools chart for a specific student or group of students who require intervention. The information included in the briefs is organized along the seven dimensions of the Taxonomy of Intervention Intensity
NCII developed this resource to help educators better understand the purpose of and considerations surrounding behavior screening in schools. Educators can use the information on this resource in conjunction with the Behavior Screening Tools Chart to (a) design a screening process for their school and (b) select or evaluate screening tools.
In this video, Dr. Lynn Fuchs, Nicholas Hobbs Professor of Special Education and Human Development at Vanderbilt University and Senior Advisor to the National Center on Intensive Intervention, shares considerations for adapting interventions when the validated intervention program wasn’t successful.