This course collection provides a guide to available NCII courses for those who are newer to the DBI process or interested in learning more about how intensive intervention can support students with severe and persistent learning and/or social, emotional, or behavioral needs.
Search
Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
Search
This checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
This question bank includes questions that teams can use to develop a hypothesis about why an individual or group of students may not be responding to an intervention. The hypothesis should help guide intervention planning and selection of intensification strategies using the Intervention Intensification Strategy Checklist. When developing a hypothesis, teams should consider the intervention design, fidelity of implementation, and learner needs. Intervention fidelity data collected using the Student Intervention Implementation Log and informal diagnostic data may help teams answer the questions included in the question bank.
This module is intended to help educators and administrators understand the dimensions of the Taxonomy of Intervention Intensity and how it can be used to select, evaluate, and intensify interventions.
This IRIS Star Legacy Module, first in a series of two, overviews data-based individualization and provides information about adaptations for intensifying and individualizing instruction. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
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.
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.