This is part 4 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part of the module is intended to provide participants with guidance for identifying skills to target in reading and math interventions.
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This module focuses primarily on selecting evidence-based interventions that align with the functions of behavior for students with severe and persistent learning and behavior needs. The emphasis of this training will include four main content areas: (a) relating assessment to function, (b) selecting evidence-based interventions that align with functions of behavior, (c) linking assessment and monitoring, and (d) connecting data with the evidence-based interventions selected. The overarching goal is to connect concepts and theories in behavior and begin planning how intensive intervention can be put into practice to support students with intensive behavioral needs.
This is part 3 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide participants with an introduction to error analysis of curriculum-based measures for the purpose of identifying skill deficits and providing examples of error analysis in reading and mathematics. Part 4, “Identifying Target Skills,” will further link these skill deficits to intervention.
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 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).
In this video, Mike Jacobsen, Assessment and Curriculum Director, White River School District in Washington State discusses how their districts planned for and implemented intensive intervention within the districts RTI model.
In this Voices from the Field, the National Center on Intensive Intervention (NCII) talks with Richard Carter, PhD, an assistant professor in the Department of Counseling, Leadership, Advocacy, and Design at the University of Wyoming. Dr. Carter teaches Mild and Moderate Disabilities, Assessment in Special Education, and Collaboration and is working to develop a micro-credentialing system for educators in the state. Dr. Carter discusses how he has integrated NCII’s data-based individualization (DBI) resources within his education preparation efforts
Data-based individualization (DBI) is a research-based process for individualizing and intensifying interventions through the systematic use of assessment data, validated interventions, and research-based adaptation strategies. The DBI process includes five iterative steps:
Fidelity refers to how closely prescribed procedures are followed and, in the context of schools, the degree to which educators implement programs, assessments, and implementation plans the way they were intended. When we implement interventions and assessments with fidelity, intervention teams can make more accurate decisions about an individual student’s progress and future intervention needs. In addition, fidelity of implementation to the data-based individualization (DBI) process as a whole and across multiple students in a school, helps to ensure that staff have the necessary resources and processes in place to support strong implementation for individual students. The following tools assess and support fidelity of DBI implementation at the school, interventionist, and student levels.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.