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.
In this video, Dr. Sharon Vaughn, Senior Advisor to the National Center on Intensive Intervention and the Executive Director of The Meadows Center for Preventing Educational Risk, discusses intensive academic interventions and supplies up to date information about the status of research studies on the subject.
In this video, Dr. Steve Goodman, Director of Michigan's Integrated Behavior and Learning Support Initiative, discusses the interaction of behavior and academics when providing intensive interventions.
In this video, Dr. Joe Wehby, Senior Advisor to the National Center for Intensive Intervention and Associate Professor in the Vanderbilt University Department of Special Education, addresses this question around research on intensive behavioral interventions.
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, through a collaboration with the University of Connecticut, developed a set of course modules focused on developing educators’ skills in using explicit instruction. These course modules are designed to support faculty and professional development providers with instructing pre-service and in-service educators who are developing and/or refining their implementation of explicit instruction.
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. Webinar 1: Don't Panic, Pivot! Tips for Implementing Data-Based Individualization (DBI) for the Synchronous and Asynchronous Learner