This checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
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The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying needs. In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
This resource developed by Sarah Thorud, Elementary Reading Specialist from Clatskanie School District in Oregon focuses on implementing screening and progress monitoring virtually. It includes guiding questions and considerations for implementation, video examples, and a sample sign-up sheet for screening and progress monitoring students virtually.
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 guide highlights 5 key practices for teachers and families to support all students, including students with disabilities, at school and home. For each practice, the guide provides (a) tips for teachers to support students with disabilities during instruction; (b) tips for families that educators can share to support or enhance learning at home, especially during periods of remote instruction; and (c) free-access resources that include strategies shown to be effective by research (e.g., informational guides, downloadable materials, research-based programs).
This series includes video examples and tip sheets to help educators and families in using the NCII reading and mathematics sample lessons to support students with intensive needs. These lessons provide short instructional routines to encourage multiple practice opportunities using explicit instruction principles. The videos and tip sheets describe how educators can use the sample lessons to support instruction in a virtual setting, how educators can share these lessons with parents, and how parents can also implement the lessons to provide additional practice opportunities.
These videos and tips are part of a series of products to support students with intensive needs in the face of COVID-19. These videos illustrate how parents and grandparents can implement the NCII reading and mathematics sample lessons to provide additional practice. In addition to the video examples, a tip sheet is available to help parents implement the lessons. Implementation of Reading Lesson: Parent Example
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.