This module discusses approaches to intensifying academic interventions for students with severe and persistent learning needs. The module describes how intensification fits into DBI process and introduces four categories of intensification practices. It uses examples to illustrate concepts and provides activities to support development of teams’ understanding of these practices, and how they might be used to design effective individualized programs for students with intensive needs.
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DBI Process
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Implementation Guidance and Considerations
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This module serves as an introduction to important concepts and processes for implementing functional behavior assessment (FBA), including behavior basics such as reinforcement and punishment. Throughout this module, participants will discuss both real world and school based examples to become familiar with the FBA process and develop a deeper understanding and awareness of the functions of the behavior. Key topics include (a) defining FBAs in the context of DBI; (b) basic concepts in behavior, including antecedents, behaviors, and consequences; (c) levels of FBAs; and (d) considerations and procedures for conducting FBAs.
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 checklist can be used by teams to help identify ideas to intensify interventions based on their hypothesis for why the student may not be responding to an intervention. The checklist is aligned with the dimensions of the Taxonomy of Intervention Intensity.
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.
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 interactive self-paced module is intended to help educators and administrators learn about using teaming to support the data-based individualization (DBI) process.
This webinar addresses a challenge faced by many teachers: feeling inundated by data while struggling to find useful information to guide intervention decision-making
In this video, Mary Little, Professor and Program Coordinator of the Department of Child, Family, and Community Services at the University of Central Florida discusses why data and data-based decision making such a critical part of instruction and intervention.
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