Within a multi-tiered system of supports (MTSS), intensive intervention, also known as Tier 3, is designed to support students with the most severe and persistent learning and/or behavior difficulties. This document highlights some common misconceptions about intensive academic and behavior interventions that experts from the Center on Positive Behavioral Interventions and Supports and NCII have observed in supporting the implementation of intensive intervention within the context of MTSS.
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At-home learning requires increased independence for students. With no bells signaling the beginning or end of class and no teacher leading the class for each subject, students must follow a virtual schedule. Within these schedules, students are responsible for accessing the appropriate links to class sessions and work activities. In addition, students often must populate usernames and passwords—most of which are unique for each different site or task.
This resource developed by Sarah Thorud, Elementary Reading Specialist from Clatskanie School District in Oregon focuses on implementing screening and progress monitoring virtually. It includes guiding questions and considerations for implementation, video examples, and a sample sign-up sheet for screening and progress monitoring students virtually.
Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
This two page handout defines the Taxonomy of Intervention Intensity through guiding questions and highlights when the Taxonomy of Intervention Intensity can be used within the data-based individualization (DBI) process. Teams can use the dimensions to evaluate a current intervention, select a new intervention and intensify interventions when students do not respond.
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:
There are a variety of terms used interchangeably to define special education: specially-designed instruction, Tier 3 supports, and intensive intervention, but, do they mean the same thing? In this presentation, delivered at the 2017 OSEP Leadership Conference, state leaders of special education, David Sienko from the Rhode Island Department of Education and Glenna Gallo, from the Washington State Board of Education – alongside personnel from the National Center on Intensive Intervention – shared perspectives on how special education is defined to espouse commonalities across terminology and services to support students with disabilities. Presentation
The DBI Implementation Rubric and the DBI Implementation Interview are intended to support monitoring of school-level implementation of data-based individualization (DBI). The rubric is based on the structure of the Center on Response to Intervention’s Integrity Rubric and is aligned with the essential components of DBI and the infrastructure that is necessary for successful implementation in Grades K–6. It describes levels of implementation on a 1–5 scale across DBI components. The rubric is accompanied by the DBI Implementation Interview which includes guiding questions that may be used for a self-assessment or structured interview of a school’s DBI leadership team.
This checklist can be used by intervention providers or planning teams to review, document, and improve implementation of the data-based individualization (DBI) process and monitor whether the student intervention plans were implemented as intended.
Providing more explicit instruction, captured within the comprehensiveness domain of the Taxonomy of Intervention Intensity, is critical within intensive intervention. The Recognizing Effective Special Education Teachers (RESET) project, funded by U.S. Department of Education Institute for Education Sciences (IES) and led by Evelyn Johnson at Boise State University, developed a series of rubrics based on evidence-based practices for students with high incidence disabilities. One set of rubrics focuses on explicit instruction. Based on the main ideas of Explicit Instruction, the Explicit Instruction Rubric was designed for use by supervisors and administrators to reliably evaluate explicit instructional practice, to provide specific, accurate, and actionable feedback to special education teachers about the quality of their explicit instruction, and ultimately, improve the outcomes for students with disabilities.