This course collection provides a guide to available NCII courses self-paced learning courses that focus on academic progress monitoring.
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DBI Process
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Implementation Guidance and Considerations
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This online course helps educators learn how to set goals, collect data, and make decisions using academic progress monitoring data.
This course is the second in a series on progress monitoring. This module describes two types of academic progress monitoring measures and considerations for selecting an academic progress monitoring tool.
This IRIS Star Legacy Module, the second in a series on intensive intervention, offers information on making data-based instructional decisions. Specifically, the resource discusses collecting and analyzing progress monitoring and diagnostic assessment data. Developed in collaboration with the IRIS Center and the CEEDAR Center, this resource is designed for individuals who will be implementing intensive interventions (e.g., special education teachers, reading specialists, interventionists).
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.
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 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 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 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.