Norms for oral reading fluency (ORF) can be used to help educators make decisions about which students might need intervention in reading and to help monitor students’ progress once instruction has begun. This paper describes the origins of the widely used curriculum-based measure of ORF and how the creation and use of ORF norms has evolved over time. Using data from three widely-used commercially available ORF assessments (DIBELS, DIBELS Next, and easyCBM), a new set of compiled ORF norms for grade 1-6 are presented here along with an analysis of how they differ from the norms created in 2006.
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This report from Jobs for the Future and Authored by Sharon Vaughn, Lou Danielson, Rebecca Zumeta Edmonds, and Lynn Holdheide, 1) reviews previous efforts to promote better educational outcomes for students with disabilities, 2) describes research-based instructional strategies that can support them and other struggling learners, and 3) shares the kinds of policies and local resources needed to ensure that all young people have meaningful opportunities to learn deeply and become truly prepared to succeed in college, careers, and civic life.
In this video, Dr. Rebecca Zumeta Edmonds, Co-Director of NCII, discusses what to consider when a goal set for a student proves to be unrealistic.
Assessment is an essential part of the data-based individualization (DBI) process and a multi-tiered system of support (MTSS). Without technically sound assessment, which provides accurate, meaningful information, a teacher has no objective method for determining what a student needs or how to intensify instruction to meet those needs. The close connection between assessment and intervention is at the foundation of the DBI process. This connection is what drives teacher decision making. With the right assessment tools and guidance on how to use them, teachers can make sound, data-based decisions about who needs intensive intervention, when to make instructional changes, and what skills to focus on. In the tables below, find resources to support the selection and evaluation of screening, progress monitoring and diagnostic assessments.
Data teams serve multiple roles in the data-based individualization (DBI) process and across a multi-tiered system of supports (MTSS). Although schools may have multiple teams that review different types of data across a multi-tiered system of supports (MTSS), the intensive intervention or DBI team is focused on the needs of individual students who are not making progress in their current intervention or special education program. It is critical that these meetings are driven by data, occur regularly, and use an efficient, consistent process that allows participants to review progress and make intervention decisions for students. NCII has created a series of tools to help teams establish efficient and effective individual student data meetings.
Many students who require intensive intervention also are students with disabilities. Thus, when used school-wide, data-based individualization (DBI) can help school teams design and implement a prereferral process and high-quality special education services. Furthermore, DBI also provides schools with a validated approach for identifying and supporting students with severe and persistent learning and behavior problems, including students who may require special education. This is because the data collected through the DBI process can assist teams in assessing the need for specialized instruction, which is one of two requirements for determining eligibility for special education. In addition, data collected through the DBI process can support special education teachers in more accurately developing present levels, goals, and specialized instruction and support that will be included in the initial IEP.
Progress monitoring, a key component of a multi-tiered system of support (MTSS), occurs throughout the data-based individualization (DBI) process to assess responsiveness to the validated intervention platform, as well as adaptations to the intervention. Prior to delivering the validated intervention platform, intervention teams should develop a progress monitoring plan that outlines the progress monitoring tool, student goal, and frequency of data collection and review. During delivery of the validated and adapted intervention, educators should collect and graph frequent progress monitoring data.
Successful implementation of intensive intervention using data-based individualization (DBI) is more likely to occur in schools that have a well-functioning tiered system of support, commonly called a multi-tiered system of supports (MTSS), response to intervention (RTI), or positive behavioral interventions and supports (PBIS), depending on your location and area of focus. Intensive intervention is considered the most intense level of intervention and also may be known as Tier 3.
These professional learning training materials are intended to assist district or school teams involved in initial planning or implementation of data-based individualization (DBI) as a framework for providing intensive intervention in academics and behavior. The modules listed below provide an overview of the DBI process and more in-depth exploration of the various components of DBI.
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. DBI is the technical term for what many good teachers do naturally through the problem solving process: frequently review student data and make changes to their teaching based on what works for students. DBI, however, makes this process systematic, explicit, and tailored to meet the needs of individual students through a multi-step process that gradually intensifies instruction and support.