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.
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In Module 6 of the Intensive Intervention in Mathematics Course Content we focus on whole number concepts and computation. In Modules 4 and 5, we emphasized important instructional delivery methods and strategies to include when providing instruction within intensive intervention. Modules 6 and 7 focus on important concepts and procedures for whole numbers (Module 6) and rational numbers (Module 7) teachers may find important for being able to explain mathematics to students.
This is part 2 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part includes examples of graphed data and is intended to provide participants with guidance for reviewing progress monitoring data to determine if the instructional plan is working or if a change is needed.
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).
In Module 7 of the Intensive Intervention in Mathematics Course Content we focus on rational number concepts and computation. In Modules 4 and 5, we emphasized important instructional delivery methods and strategies to include when providing instruction within intensive intervention. Modules 6 and 7 focus on important concepts and procedures for whole numbers (Module 6) and rational numbers (Module 7) teachers may find important for being able to explain mathematics to students.
This toolkit provides activities and resources to assist practitioners in designing and delivering intensive interventions in reading and mathematics for K–12 students with significant learning difficulties and disabilities. Grounded in research, this toolkit is based on the Center on Instruction’s Intensive Interventions for Students Struggling in Reading and Mathematics: A Practice Guide, and includes the following resources:
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.
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.
After initial data-based individualization (DBI) implementation, schools and districts need to own the work and deliver ongoing support, including supports for new teachers within existing budgets and staff time. Planning for sustainability upfront can help district leaders to streamline their implementation efforts. In New York City, Jason Borges and Meghan Duffy from the New York City Department of Education have found several successful strategies for DBI implementation that have helped make DBI self-sustaining. This audio story shares their DBI implementation approach, successes, and lessons learned about sustainability. The recording is broken into three parts.
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: