The purpose of this document is to provide content-specific examples of how to structure educator-level and/or systems-level coaching as a mechanism to ensure ongoing professional learning to support tiered intervention. This document provides examples of coaching supports, models, and functions within the context of tiered intervention (e.g., RtI, PBIS, MTSS) and data-based decision making (e.g., data-based individualization [DBI]) for educators who already have foundational knowledge and/or experience with coaching.
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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.
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.
This document presents considerations for implementing DBI in light of COVID-19 with an emphasis on delivery in virtual settings.
The first module in the Intensive Intervention Math Course Content focuses on the mathematics content necessary to include within intensive intervention. This includes matching decisions about instruction and assessment to the mathematics content.
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.
With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive behavior intervention based on student need.
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 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