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.
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.
NCII presented a strand at Center for Exceptional Children (CEC) 2015 Convention and Expo. The strand, "How Can We Make Intensive Intervention Happen? Considerations for Knowledge Development, Implementation, and Policy," address the range of issues schools and districts encounter as they attempt to implement intensive intervention—knowledge and skills, systems to support and evaluate implementation, and policy context.
NCII presented a Strand at CEC 2014 Convention and Expo focused on intensive intervention. The Strand Using Intensive Intervention to Meet the Academic and Behavior Needs of Struggling Learners provided participants with an overview of how principles of intensive intervention may be applied to students with severe and persistent learning needs across reading, mathematics, and behavior. The Strand included three content-oriented sessions focused on reading, mathematics, and behavior and one panel session covering common implementation issues associated with provision of intensive services
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 webinar presented by Dr. Rebecca Zumeta Edmonds, discusses various approaches to progress monitoring, focusing on the value and implications of using progress monitoring to track the growth of students with intensive academic needs. Dr. Zumeta Edmonds walks through the steps of the process for using progress monitoring data to make instructional decisions for individual students.
In this video, Rob Horner, Professor of Special Education at the University of Oregon and co-Director of OSEP Technical Assistance Center on PBIS and the OSEP Research and Demonstration Center on School-wide Behavior Support, discusses how data systems can be used within the context of intensive intervention.
This webinar presented by Dr. Daniel Maggin, shares methods for collecting behavioral data, procedures for examining behavioral data, and discusses using behavioral progress monitoring to make programming decisions.