This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
Search
Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
Search
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.
In this Voices from the Field piece, we talk to Dr. Chrissy Brown, a recent National Center for Leadership in Intensive Intervention (NCLII) scholar. Dr. Brown discusses the NCLII program and how it has guided her in preparing educators to implement intensive interventions.
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.
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.
This is the first module in a series of modules about intensive intervention in reading. There are two parts in this module that answer the questions (1) why is intensive intervention in reading important? and (2) how does data-based individualization (DBI) apply to reading?
This module provides an overview of diagnostic assessments, using error analysis with CBMs, developing and using curriculum-based assessments (CBAs), and integrating diagnostic and progress monitoring data to inform instructional adaptations.
This module identifies Tier II and Tier III interventions for students at risk and high risk for behavioral challenges. By the end of this module you should be able to: Describe the decision-making process to indicate Tier II is appropriate Identify critical features of Tier II Discuss how to modify Tier II interventions to meet the needs of more students Highlight critical elements of a Functional Behavior Assessment (FBA) Choose a desired and replacement behavior Complete a Competing Pathway Model Begin to identify strategies to make the problem behavior irrelevant, inefficient, and ineffective
This fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.