This audio story shares New York City's DBI implementation approach, successes, and lessons learned about sustainability
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DBI Process
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Implementation Guidance and Considerations
Student Population
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In this Voices from the Field post, we archive the presentations from day 2 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on preparing in-service and pre-service educators and leaders to implement intensive intervention.
This three-part Voices from the Field video series profiles how Education Service Center (ESC) 15 in Texas approached implementing the DBI process in San Saba Independent School District (ISD). In these videos, Dedra Carter and Valerie Moos from ESC 15 and Jenna McSherry from San Saba ISD, discuss their experiences and recommendations for other districts implementing DBI.
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.
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 module describes how to use data (Module 6) to inform decision making in the classroom. How do you know you are choosing the right interventions, and implementing with the right intensity, to influence a change in student behavior? By the end of this module you should be able to: Describe why we use data for decision making Determine if core features of classroom management practices are in place with fidelity Determine if all individuals in your classroom are achieving desired outcomes Develop an action plan to enhance or intensify support as needed
This fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.
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 updated training module provides a rationale for intensive intervention and an overview of data-based individualization (DBI), NCII’s approach to providing intensive intervention. DBI is a research-based process for individualizing validated interventions through the systematic use of assessment data to determine when and how to intensify intervention. Two case studies, one academic and one behavioral, are used to illustrate the process and highlight considerations for implementation.
This training module, includes four sections that (a) provide an overview of administering common general outcome measures for progress monitoring in reading and mathematics, (b) review graphed progress monitoring data, and (c) provide guidance on identifying what type of skills the intervention should target to be most effective in reading and mathematics.