This three-part course provides a guide to available NCII self-paced learning courses that focus on academic progress monitoring. The collection begins with an overview of progress monitoring and the role of progress monitoring within the DBI process. The second module focuses defining two types of academic progress monitoring measures (general outcome measures and mastery measures) and considerations for identifying a target behavior and selecting a valid and reliable academic progress monitoring tool. The final module focuses on how you collect, graph, and make decisions based on academic progress monitoring data. While it is possible to take the courses individually or in a different order, this collection provides a suggested order for engaging in learning about academic progress monitoring.
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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.
In this webinar, experts from the PROGRESS Center and National Center on Intensive Intervention (NCII) will model how practitioners can use data-based individualization (DBI) to develop and implement SDI for students with disabilities. A panel of special educators will share how using DBI improved the efficiency and effectiveness of their service delivery, communication with families, and collaboration with other educators.
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 course is the first in a series focused on progress monitoring. This module introduces progress monitoring and role progress monitoring plays in the DBI process.
This webinar, featuring Drs. Donna Sacco, John Hoover, and Tracy Spies, illustrates considerations for implementing data-based individualization (DBI) with ELs that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs. They share why it is important to (a) deliver instruction that represents culturally and linguistically sustaining best practices, and (b) distinguish the needs and assets of learners to improve progress (i.e., second-language acquisition, culture, learning challenges).
This module is intended to help educators and administrators understand the dimensions of the Taxonomy of Intervention Intensity and how it can be used to select, evaluate, and intensify interventions.
This IRIS Star Legacy Module, first in a series of two, overviews data-based individualization and provides information about adaptations for intensifying and individualizing instruction. 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).
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).
The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying 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.