How can school and district leaders establish the conditions needed for educators to successfully implement data-based individualization (DBI) for students with the most intensive needs? To help put the pieces in place for the next school year, join our free webinar, Planning for Success: Building Readiness to Implement Data-Based Individualization, May 2, 2024 at 4:00 pm ET to learn how supporting the readiness of educators and establishing the necessary infrastructure for DBI are keys to success. Readiness involves identifying needs, establishing shared goals and plans for DBI, enhancing buy-in, addressing barriers, and reviewing and securing resources, among other topics. Assessing and developing readiness may save time, resources, and effort when implementing DBI. In this webinar, Dr. Zachary Weingarten, Product Development Coordinator at NCII, will highlight key recommendations to build readiness to implement DBI. Dr.
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This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying needs. In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.
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.
The purpose of this guide is to provide an overview of behavioral progress monitoring and goal setting to inform data-driven decision making within tiered support models and individualized education programs (IEPs).
This series of videos provides brief instructional examples for supporting students who need intensive instruction in the area of fractions. Within college- and career-ready standards fractions are typically taught in Grades 3-5. Developing an understanding of fractions as numbers includes part/whole relationship, number on the number line, equivalent fractions, whole numbers as fractions, and comparing fractions These videos may be used as these concepts are introduced, or with students in higher grade levels who continue to struggle with the concepts. Special education teachers, math interventionists, and others working with struggling students may find these videos helpful.
Support from leaders is essential for effective DBI implementation. This resource illustrates how DBI can help principals and local level administrators leverage existing resources, integrate supports for academics and behavior, define Tier 3, align special education and MTSS, establish effective data meetings, and improve outcomes for students who are at-risk for poor learning outcomes. In addition, the resource shares strategies and resources available to support implementation
Teams are a vital part of an effective multi-tiered system of supports (MTSS) across both academics and behavior as well as special education. Making connections across the across the various teams used in MTSS and special education can be challenging. This resource from NCII and the PBIS Center, provides information about how DBI can support IEP implementation and provides a table with key considerations for teams working across the MTSS system.
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: