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 log can be used as a daily and weekly record of the implementation of an individual student’s intensive intervention plan. This information, along with progress monitoring graphs, can inform team intervention and data review meetings. You may choose to supplement the logs with additional items or more detailed intervention notes.
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 module focuses primarily on selecting evidence-based interventions that align with the functions of behavior for students with severe and persistent learning and behavior needs. The emphasis of this training will include four main content areas: (a) relating assessment to function, (b) selecting evidence-based interventions that align with functions of behavior, (c) linking assessment and monitoring, and (d) connecting data with the evidence-based interventions selected. The overarching goal is to connect concepts and theories in behavior and begin planning how intensive intervention can be put into practice to support students with intensive behavioral needs.
This is part 4 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part of the module is intended to provide participants with guidance for identifying skills to target in reading and math interventions.
This is part 2 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part includes examples of graphed data and is intended to provide participants with guidance for reviewing progress monitoring data to determine if the instructional plan is working or if a change is needed.
In this video, Dr. Devin Kearns, an Assistant Professor of Special Education in the Department of Education Psychology at the Neag School of Education at the University of Connecticut and NCII Trainer & Coach, discusses importance of consistency when selecting, administering, and scoring progress monitoring tools.
In this video, Dr. Joe Wehby, Senior Advisor to the National Center for Intensive Intervention and Associate Professor in the Vanderbilt University Department of Special Education, discusses the number of data points needed to make decisions for students with intensive behavior needs.
In this video, Dr. Lynn Fuchs, Nicholas Hobbs Professor of Special Education and Human Development at Vanderbilt University and Senior Advisor to the National Center on Intensive Intervention, shares considerations for adapting interventions when the validated intervention program wasn’t successful.
Teachers often note that students struggle with the transition between core instruction and intervention in mathematics. Thus, the purpose of these curriculum crosswalks is to identify points of alignment and misalignment between commonly used mathematics intervention and core instructional materials, with a particular focus on mathematics practice standards and vocabulary. We offer recommendations for improving alignment to help students more successfully participate in math instruction across settings. Math Curriculum Crosswalk: Grade 1 Math Curriculum Crosswalk: Grade 2 Math Curriculum Crosswalk: Grade 3