This guide is intended to accompany the sample reading lessons and activities on the NCII website. It is divided into four sections.
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 or miscue analysis of curriculum-based measures for the purpose of identifying skill deficits. The module provides examples of miscue analysis in reading and mathematics.
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.
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 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).
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, (c) introduce error or miscue analysis of curriculum-based measures for the purpose of identifying skill deficits in reading and mathematics, and (d) provide guidance on identifying what type of skills the intervention should target to be most effective in reading and mathematics.
This module serves as an introduction to important concepts and processes for implementing functional behavior assessment (FBA), including behavior basics such as reinforcement and punishment. Throughout this module, participants will discuss both real world and school based examples to become familiar with the FBA process and develop a deeper understanding and awareness of the functions of the behavior. Key topics include (a) defining FBAs in the context of DBI; (b) basic concepts in behavior, including antecedents, behaviors, and consequences; (c) levels of FBAs; and (d) considerations and procedures for conducting FBAs.
Data-based individualization (DBI) is a research-based process for individualizing and intensifying interventions through the systematic use of assessment data, validated interventions, and research-based adaptation strategies. This document introduces and describes the DBI process and how it can be used to support students who require intensive intervention in academics and/or behavior.
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 webinar, led by Drs. Lynn Fuchs and Lee Kern addresses a challenge faced by many teachers: feeling inundated by data while struggling to find useful information to guide intervention decision-making