The purpose of this module is to introduce schools interested in implementing intensive intervention to the infrastructure needed to implement data-based individualization (DBI). The module includes presentation slides with integrated activities and handouts to help teams determine their readiness and develop an action plan for implementation.
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DBI Process
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Implementation Guidance and Considerations
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This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
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.
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.
When a student fails to respond to a validated intervention, teams need to identify why the student is not responding to determine how to adapt the intervention. Diagnostic data can assist teams in this process. They may be used to understand a student’s specific skill deficits and strengths or to identify the environmental events that predict and maintain the student’s problem behavior.
Fidelity refers to how closely prescribed procedures are followed and, in the context of schools, the degree to which educators implement programs, assessments, and implementation plans the way they were intended. When we implement interventions and assessments with fidelity, intervention teams can make more accurate decisions about an individual student’s progress and future intervention needs. In addition, fidelity of implementation to the data-based individualization (DBI) process as a whole and across multiple students in a school, helps to ensure that staff have the necessary resources and processes in place to support strong implementation for individual students. The following tools assess and support fidelity of DBI implementation at the school, interventionist, and student levels.
This tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.
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.
Using multiple data sources, the teacher or team makes a decision to adapt the intervention program to better meet the student’s individual needs. The teacher or team outlines these adaptations in an individual student plan. The plan may include adaptation strategies along several dimensions. These strategies may include quantitative changes, such as providing more opportunities for a student to respond by increasing the length or frequency of the intervention, or decreasing the size of the intervention group.
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.