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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Using DBI to Improve Literacy Outcomes for Students with Intellectual and Developmental Disabilities
How can data-based individualization (DBI) help educators to address the growing expectations for literacy outcomes for students with intellectual and developmental disabilities? In this webinar, Dr. Chris Lemons an NCII Advisor, Associate Professor of Special Education in the Graduate School of Education at Stanford University, and Co-Director of the Stanford Down Syndrome Research Center, provides an overview of activities conducted through an Office of Special Education Programs model demonstration project. This project focused on increased literacy outcomes using DBI, inclusion, and enhancing individualized education programs. The webinar shares project findings and provides recommendations for integrating those findings into professional development and practice to improve student outcomes.
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, 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).
In this webinar presenters reviewed the evidence-base behind explicit instruction for students with disabilities and highlighted recently released course content designed to help educators learn how to deliver explicit instruction and review their current practices.
This webinar demonstrates how the Taxonomy of Intervention Intensity can support educators in systematically selecting and modifying intensive literacy interventions based on student need.
In this video, Dr. Rolland O’Connor, Professor in the Graduate School of Education at the University of California Riverside a member of the NCII Academic Intervention Technical Review Committee, addresses the implications of early reading research for understanding late-emerging reading disabilities, working with students learning English, and preparing teachers to have a strong grounding in the stages of reading development.