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
Part 2 of the two part series about UCF's project bridges highlights challenges and successes the program has faced when trying to build the skills and competencies of educators to implement intensive intervention.
In this article, Drs. Mary Little, Cynthia Pearl and Dena Slanda share lessons and strategies to support teachers in developing the skills and competencies to implement intensive intervention.
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:
This report presents findings from an exploratory study of how five high-performing districts, which we refer to as NCII’s knowledge development sites, defined and implemented intensive intervention. The findings offer lessons that other schools and districts can use when planning for, implementing and working to sustain their own initiatives to provide intensive intervention for students with the most severe and persistent learning and/or behavioral needs.
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).
NCII presented a strand at Center for Exceptional Children (CEC) 2016 Convention and Expo. The strand, Intensive Intervention 2.0: Integrating for Intensity, Learning from Implementation, and Refining our Understanding of Evidence, discuss lessons learned from NCII’s support for implementation of intensive intervention within a multi-tiered systems of support (MTSS) framework. The strand addresses (a) the integration of academic and behavioral intervention to support students with diverse learning needs; (b) successes and challenges observed by school and district leaders attempting to implement intensive intervention in high-needs schools, and; (c) considerations for understanding standards of evidence and identifying appropriate interventions and strategies across tiers of an MTSS system.
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.
NCII presented a special session at the National Association of School Psychologists (NASP) 2016 Annual Convention. Presenters included Drs. Laura Berry Kuchle, Christopher Lemons, Chris Riley-Tillman, and Lou Danielson. The session (1) shared the importance of intensive intervention, (2) described data-based individualization (DBI), a process for adapting academic and behavioral interventions to meet individual needs, (3) described tools to evaluate implementation of key components of DBI, (4) discussed implementation patterns in NCII’s partner schools and lessons learned from NCII's technical assistance with schools and districts, and (5) shared resources available from NCII.
This 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.