This training module, includes four sections that (a) provide an overview of administering common general outcome measures for progress monitoring in reading and mathematics, (b) review graphed progress monitoring data, and (c) provide guidance on identifying what type of skills the intervention should target to be most effective in reading and mathematics.
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DBI Process
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Implementation Guidance and Considerations
Student Population
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Monitoring Student Progress for Behavioral Interventions (DBI Professional Learning Series Module 3)
This module focuses on behavioral progress monitoring within the context of the DBI process and addresses: (a) methods available for behavioral progress monitoring, including but not limited to Direct Behavior Rating (DBR), and (b) using progress monitoring data to make decisions about behavioral interventions.
This training module demonstrates how academic progress monitoring fits into the Data-Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.
This checklist can be used by intervention providers or planning teams to review, document, and improve implementation of the data-based individualization (DBI) process and monitor whether the student intervention plans were implemented as intended.
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.
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 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.
In this video, Mary Randel, a doctoral candidate in Special Education at Michigan State University & NCII Coach for the Swartz Creek School District, addresses the importance of ensuring that students with disabilities have access to supports across the tiers of a tiered frameworks, especially intensive intervention.
In this video, Dr. Evelyn Johnson, Associate Professor at Boise State University, discusses how data can be used to support eligibility decisions for students with disabilities.
In this video, Dr. Sharon Vaughn, Senior Advisor to the National Center on Intensive Intervention and the Executive Director of The Meadows Center for Preventing Educational Risk, discusses the importance of intensive interventions in academics and behavior.
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