In this video, Nicole Bucka, NCII coach and MTSS professional development provider for Rhode Island discuss lessons learned from implementing intensive intervention at the middle and secondary level.
Search
Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
Search
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.
In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
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
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).
With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
This tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.
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.
The 2017 Supreme Court decision Endrew F. v. Douglas County School District highlighted the importance of monitoring students’ progress toward appropriately challenging individualized educational program (IEP) annual goals and making changes to students’ educational programs when needed. In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances.
Data teams serve multiple roles in the data-based individualization (DBI) process and across a multi-tiered system of supports (MTSS). Although schools may have multiple teams that review different types of data across a multi-tiered system of supports (MTSS), the intensive intervention or DBI team is focused on the needs of individual students who are not making progress in their current intervention or special education program. It is critical that these meetings are driven by data, occur regularly, and use an efficient, consistent process that allows participants to review progress and make intervention decisions for students. NCII has created a series of tools to help teams establish efficient and effective individual student data meetings.