In this Voices from the Field post, we archive the presentations from day 1 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on creating the systems to support implementation of intensive intervention.
Implementation Guidance and Considerations
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).
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:
The DBI Implementation Rubric and the DBI Implementation Interview are intended to support monitoring of school-level implementation of data-based individualization (DBI). The rubric is based on the structure of the Center on Response to Intervention’s Integrity Rubric and is aligned with the essential components of DBI and the infrastructure that is necessary for successful implementation in Grades K–6. It describes levels of implementation on a 1–5 scale across DBI components. The rubric is accompanied by the DBI Implementation Interview which includes guiding questions that may be used for a self-assessment or structured interview of a school’s DBI leadership team.
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.
The purpose of this document is to provide an overview of the Center’s accomplishments and to highlight a set of lessons learned from the 26 schools that implemented intensive intervention while receiving technical support from the Center.
This white paper summarizes the proceedings of a summit that was focused on integrating research knowledge on promising approaches into intensive intervention and implementation to improve academic outcomes for students with disabilities who have severe and persistent learning need. In addition, it includes responses from three participants representing perspectives from policy (David Chard, Wheelock College), research (Nathan Clemens, University of Texas at Austin), and practice (Steve Goodman, Michigan Integrated Behavior and Learning Support Initiative).
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.