This template is intended to assist with the planning and documentation of dimensions of an intervention for small groups or an individual student within the data-based individualization (DBI) process.
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The purpose of this document is to provide content-specific examples of how to structure educator-level and/or systems-level coaching as a mechanism to ensure ongoing professional learning to support tiered intervention. This document provides examples of coaching supports, models, and functions within the context of tiered intervention (e.g., RtI, PBIS, MTSS) and data-based decision making (e.g., data-based individualization [DBI]) for educators who already have foundational knowledge and/or experience with coaching.
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.
These five screening one-page documents provide a brief overview of each of the NCII screening standards. They include a definition and information on why that particular standard is important for understanding the quality of screening tools.
In this Voices From the Field piece, the National Center on Intensive Intervention (NCII) speaks to Cyndi Caniglia, PhD, an assistant professor in the Department of Education at Whitworth University in Spokane, Washington about how she has meaningfully integrated the NCII Features of Explicit Instruction Course Content into her coursework.
The Behavior Screening Tools Chart is comprised of evidence-based screening tools that can be used to identify students in need of behavioral intervention. The chart displays ratings on technical rigor in the areas of classification accuracy, reliability, and validity, and provides information on the representativeness of the sample, whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select behavior screening tools that address their specific needs. The presence of a particular tool on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Behavior Screening or NCII.
The Academic Screening Tools Chart is comprised of evidence-based screening tools that can be used to identify students at risk for poor academic outcomes, including students who require intensive intervention. The chart displays ratings on technical rigor in the areas of classification accuracy, reliability, and validity, and provides information on the representativeness of the sample, whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select academic screening tools that address their specific needs. The presence of a particular program on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Academic Screening or NCII.
If you are like most educators, you agree with the idea of providing intensive intervention for students with the most intractable academic and behavior problems. The question you may be asking is, how do I find the time? This guide includes strategies that educators can consider when trying to determine how to find the time for this intensification within the constraints of busy school schedules. Supplemental resources, planning questions, and example schedules are also provided.
This video demonstrates how to use fraction tiles and the set model to convert mixed numbers to improper fractions. It is important that students have the opportunity to convert fractions using both models of representation.
This video demonstrates how to use the set model to convert mixed numbers to improper fractions. It is important that students are exposed to converting fractions using this model because it is often how fractions are represented in the real world. Beginners and students who struggle may find the set model difficult to understand because the whole (1) is represented by a set of chips (4 chips in this example); therefore, students will benefit from explicit modeling and several opportunities to engage in guided and independent practice.