Intensive Intervention in Reading Course: Module 4 Overview This module provides an overview of data-based individualization (DBI), including using CBM measures, how to present level of performance and set student goals, and use data to make instructional decisions. This module is divided into five parts with an introduction and closing. A 508 compliant version of the full PowerPoint presentation across all parts of the module, a version of the PowerPoint that includes all the animations, and a workbook is available below.
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This module discusses how to define, measure and monitor behavior. By the end of the module you should be able to: Select an appropriate target behavior Write an operational definition for a target behavior Identify relevant dimensions of behavior Choose a measurement system based on relevant dimensions of behavior Use graphing conventions to create meaningful visual displays of data
The Behavior Progress Monitoring Tools Chart is comprised of evidence-based progress monitoring tools that can be used to assess students’ social, emotional or behavioral performance, to quantify a student rate of improvement or responsiveness to instruction, and to evaluate the effectiveness of instruction. The chart displays ratings on technical rigor of performance level standards (reliability and validity) and growth standards (sensitivity and decision rules) and provides information on the whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select behavior progress monitoring tools that address their specific needs. The presence of a particular tool on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Behavior Progress Monitoring or NCII.
The Academic Progress Monitoring Tools Chart is comprised of evidence-based progress monitoring tools that can be used to assess students’ academic performance, to quantify a student rate of improvement or responsiveness to instruction, and to evaluate the effectiveness of instruction. The chart displays ratings on technical rigor of performance level standards (reliability and validity) and growth standards (sensitivity, alternate forms, and decision rules) and provides information on the whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select academic progress monitoring tools that address their specific needs. The presence of a particular tool on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Academic Progress Monitoring or NCII.
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 webinar explores current practices on behavioral screening within the context of a tiered system of support and provide an overview of NCII’s behavior screening tools chart.
Teams are a vital part of an effective multi-tiered system of supports (MTSS) across both academics and behavior as well as special education. Making connections across the across the various teams used in MTSS and special education can be challenging. This resource from NCII and the PBIS Center, provides information about how DBI can support IEP implementation and provides a table with key considerations for teams working across the MTSS system.
Module 6 is the second in a set of four course modules focused on explicit instruction. This module introduces the concept of supporting practices necessary for successful implementation of explicit instruction. The module introduces how to use effective methods to elicit frequent responses. Throughout the module, educators will learn how eliciting frequent responses support instruction within the DBI framework.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.
This is part 3 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide participants with an introduction to error analysis of curriculum-based measures for the purpose of identifying skill deficits and providing examples of error analysis in reading and mathematics. Part 4, “Identifying Target Skills,” will further link these skill deficits to intervention.