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.
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This webinar discusses classroom management strategies educators can apply to improve access and outcomes for students with disabilities and students with intensive needs.
Staff from the Exceptional Children department in Charlotte-Mecklenburg Schools convened a group of their teachers in Spring 2020 to share their perspectives and ideas. This advisory group includes approximately 20 teachers of exceptional children across Charlotte-Mecklenburg Schools. In this Voices from the Field video, the National Center on Intensive Intervention spoke with four teachers in the advisory group about their work during COVID-19 restrictions.
It is important that the instructional practices and interventions delivered within a school’s multi-tiered system of support (MTSS) be grounded in evidence. However, the “practice” that happens within each tier is different; therefore, the type of evidence that is required for each tier also must be different. A useful way to think about evidence-based practices in MTSS is to think about levels of evidence that vary and correspond to the different levels of intervention intensity at each tier. In the tables below, find resources to support the selection and evaluation of Tier 1, Tier 2, and Tier 3 or intensive interventions.
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.
Data teams serve multiple roles in the data-based individualization (DBI) process and across a multi-tiered system of supports (MTSS). Although schools may have multiple teams that review different types of data across a multi-tiered system of supports (MTSS), the intensive intervention or DBI team is focused on the needs of individual students who are not making progress in their current intervention or special education program. It is critical that these meetings are driven by data, occur regularly, and use an efficient, consistent process that allows participants to review progress and make intervention decisions for students. NCII has created a series of tools to help teams establish efficient and effective individual student data meetings.
In this webinar, Dr. Sarah Powell an Associate Professor in the Department of Special Education at the University of Texas at Austin highlights freely available tools and resources that can help educators consider a scope and sequence for math skills, assessment and intervention practices, instructional delivery, concepts and procedures for whole and rational numbers, intensification considerations, and more. The webinar reviews the content available from the Intensive Intervention Math Course Content. The course content consists of eight modules covering a range of math related topics. Each module includes video lessons, activities, knowledge checks, practice-based opportunities, coaching materials and other resources.
In this video, Lucille Eber, E.D., Statewide Coordinator of Illinois’ Emotional and Behavioral Disabilities (EBD) Network and an NCII Advisory Committee member, discusses the relationship between Tier II and Tier III behavior interventions and whether all kids need to access Tier II prior to Tier III.
The Rhode Island Department of Education (RIDE) has been partnering with NCII since 2012 to support DBI implementation within Rhode Island.
This webinar describes how the RIOT/ICEL matrix can support problem-solving by helping teams to organize their diagnostic data, refine hypotheses, and guide decision making.