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.
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DBI Process
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Implementation Guidance and Considerations
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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.
In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
This webinar shares how to set ambitious behavioral goals for students by using a valid, reliable progress monitoring measure, and how to write measurable and realistic goals focused on the replacement behavior.
What is an evidence-based practice? How do I know if evidence shows that a practice will be right for my students? Many practitioners ask these critical questions every day as they are faced with making decisions regarding how to best meet the needs of their students.
In this webinar, Dr. Sarah Powell an Associate Professor in the Department of Special Education at the University of Texas at Austin introduces a new free resource from NCII that can be used by faculty to develop or supplement coursework to ensure educators are prepared to support students with intensive math needs. The Intensive Intervention Math Course Content consists of eight modules covering a range of math related topics. Each module includes video lessons, activities, knowledge checks, practice-based opportunities, and more! In this webinar, Dr. Powell reviews the content available, discusses how it could be used as you develop courses, and answers questions that you might have.
This training module introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated reading intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.
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.
This training module introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated behavior intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.
This training module introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated mathematics intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.