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.
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DBI Process
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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 video demonstrates how to teach students to think flexibly about fractions. Similar to whole numbers, fractions can be put together and taken apart in many different combinations. Students should practice identifying these combinations so that they can become fluent with fraction addition and subtraction.
In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
This video illustrates the use of manipulatives to help students practice comparing quantities that are grouped as tens and ones. When numbers are represented with manipulatives organized as tens and ones, students develop a concrete understanding for using place value to comparing quantities. Students also benefit from multiple opportunities to talk about mathematics and use appropriate mathematics vocabulary such as “greater than” and “less than.”
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.
In Module 8 of the Intensive Intervention in Mathematics Course Content we highlight the necessity for implementing evidence-based practices with fidelity. We also explain how to make adaptations to the instructional platform when students demonstrate inadequate progress. We finish this module by putting all the information learned across modules together with the intensive intervention framework.
In this Voices from the Field post, Emma Shanahan reflects on her experiences with progress monitoring and data-based decision making as a teacher and shares findings from her recent research on DBI professional development.
This interactive self-paced module is intended to help educators and administrators learn about using teaming to support the data-based individualization (DBI) process.
This IRIS Star Legacy Module, first in a series of two, overviews data-based individualization and provides information about adaptations for intensifying and individualizing instruction. 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).