This collection highlights a sampling of articles focused on intensive intervention and data-based individualization (DBI). Although there is a wealth of research on key components of the DBI process (e.g., progress monitoring, validated intervention programs), this list is not intended to include articles that focus on specific steps in the DBI process, nor is it an exhaustive review of all available literature. In the list below, we highlight seminal research on DBI and articles published since 2011, when NCII was first funded.
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Module 8 is the fourth module in a set of four course modules focused on explicit instruction. This module reviews explicit instruction and the supporting practices. It includes a number of opportunities to view and evaluate lesson examples, apply what was learned, and self-reflect.
Module 4 of the Intensive Intervention in Mathematics Course Content focuses on the delivery of the instructional platform. We rely on evidence-based strategies to inform how teachers should deliver the instructional platform.
Module 7 is the third in a set of four course modules focused on explicit instruction. This module focuses on providing immediate specific feedback and maintaining a brisk pace. Throughout the module, educators will learn how eliciting providing immediate specific feedback and maintaining a brisk pace support instruction within the DBI framework.
Module 5 begins a series of modules on the topic of explicit instruction. Explicit instruction is about modeling and practicing to help students reach academic goals. Throughout the module, educators will learn how selecting an important objective and learning outcomes, designing structured instructional experiences, explaining directly, modeling the skills being taught and providing scaffolded practice to achieve mastery can be used within the DBI framework to support instruction.
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.
Module 2 of the Intensive Intervention in Mathematics Course Content focuses on the assessment components of intensive intervention. We provide an overview of assessments before diving into instruction in order to stress the importance that intensive intervention cannot occur without adequate assessments in place.
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.
Module 6 is the second in a set of four course modules focused on explicit instruction. This module introduces the concept of supporting practices necessary for successful implementation of explicit instruction. The module introduces how to use effective methods to elicit frequent responses. Throughout the module, educators will learn how eliciting frequent responses support instruction within the DBI framework.
This video illustrates how to use the traditional algorithm to solve subtraction with regrouping. The traditional algorithm focuses on digit placement and requires that students move right to left to correctly perform the operation. Before students are introduced to the standard addition algorithm, it is important that they have a conceptual understanding of regrouping. This will allow students to correctly use the algorithm when they exchange 10 ones in the ones place value column with 1 ten in the tens place value column. It is important for students to know and understand how to use the traditional algorithm because it is an efficient strategy to use if regrouping is required, when numbers have varying numbers of digits, and when the numbers included are too large to reasonably use other strategies (e.g., partial differences can become confusing for students who do not understand negative integers).