The first module in the Intensive Intervention Math Course Content focuses on the mathematics content necessary to include within intensive intervention. This includes matching decisions about instruction and assessment to the mathematics content.
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DBI Process
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Implementation Guidance and Considerations
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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.
In this article, Drs. Ketterlin Geller, Lembke, and Powell discuss how they are supporting educators to implement (1) the process of data-based individualization (DBI), (2) the principles of explicit and systematic instruction, and (3) key components of algebra readiness as part of Project STAIR (Supporting Teaching of Algebra: Individual Readiness).
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.
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.
This training module, includes four sections that (a) provide an overview of administering common general outcome measures for progress monitoring in reading and mathematics, (b) review graphed progress monitoring data, and (c) provide guidance on identifying what type of skills the intervention should target to be most effective in reading and mathematics.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.
Diagnostic tools provide data to assist educators in designing individualized instruction and intensifying intervention for students who do not respond to validated intervention programs. Diagnostic tools can be either informal, which are easy-to-use tools that can be administered with little training, or standardized, which must be delivered in a standard way by trained staff. Teams may find it helpful to initially consider using more informal and easily accessible diagnostic tools and data to avoid loss of instructional time. Standardized diagnostic tools, which require more time to administer and interpret, may be required for students who continually demonstrate a lack of response or who require special education.
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.
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.