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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In this Voices From the Field piece, the National Center on Intensive Intervention (NCII) talks with Justyn Poulos, director of MTSS at the Office of the Superintendent of Public Education (OSPI), about how he and his team shifted their annual MTSS Fest conference from a face-to-face event to a virtual event in less than 3 weeks due to COVID-19 restrictions. Justyn shares how his team modified their event plans and what they learned from the experience about how to engage participants in the future.
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.
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.
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 two page handout defines the Taxonomy of Intervention Intensity through guiding questions and highlights when the Taxonomy of Intervention Intensity can be used within the data-based individualization (DBI) process. Teams can use the dimensions to evaluate a current intervention, select a new intervention and intensify interventions when students do not respond.
If we don’t implement critical components of an intervention with consistency, we cannot link student outcomes to the instruction provided. Fidelity can help us to determine the effectiveness of an intervention, and identify if a student requires more intensive supports. This resource outlines five elements of fidelity and provides guiding questions for each.
In this video, Drs. Mitch Yell and Tessie Bailey share information about the 2017 Endrew F. v. Douglas County School District decision by the U.S. Supreme Court. They highlight implications for writing a student's IEP and discuss the importance of setting setting ambitious IEP goals to ensure that students make progress in light of their individual circumstances.
The NCII tools charts include a large amount of information and the “best” tool is not going to be the same for everyone. Users should review all the elements of the charts before making decisions. This user guide reviews a series of recommended steps that users should consider when making decisions.
The 2017 Supreme Court decision Endrew F. v. Douglas County School District highlighted the importance of monitoring students’ progress toward appropriately challenging individualized educational program (IEP) annual goals and making changes to students’ educational programs when needed. In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances.