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).
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 Innovation Configuration can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS. The expectation is that these skills can be further honed and supported through inservice as practicing teachers.
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 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 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.
The facilitating ongoing data team meeting documents can assist teams in ensuring that ongoing meetings for students receiving intensive intervention run smoothly. These tools are intended to support teams as they review student progress monitoring data after the initial intervention plan has been put in place and determine whether the student is making progress at an acceptable rate or if adaptations to the intervention plan are necessary. This suite of tools includes a sample agenda, facilitator guide, participant guide, and note taking template.
The initial data team meeting documents can assist teams in facilitating an efficient and effective process for analyzing data and designing intensive intervention plans for students.
Before a student is referred for intensive intervention, it is important that the team get a holistic sense of the student, including relevant background information, current performance, current supports and previously attempted intervention(s), and other relevant data. These data meeting tools focused on preparing for the meeting ensure that team members are prepared to discuss students.
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