In this video, Dr. Chris Riley-Tillman, a Professor at the University of Missouri and NCII Senior Advisor, discusses the important considerations when selecting behavioral progress monitoring tools.
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In this video, John M. Hintze, Professor in the Department of Student Development at the University of Massachusetts Amherst explains why it is important to consider whether an assessment is biased against a specific sub-group.
In this video, Dr. Joe Wehby, Senior Advisor to the National Center for Intensive Intervention and Associate Professor in the Vanderbilt University Department of Special Education, discusses the number of data points needed to make decisions for students with intensive behavior needs.
In this video, Dr. Joe Wehby, Senior Advisor to the National Center for Intensive Intervention and Associate Professor in the Vanderbilt University Department of Special Education, addresses this question around research on intensive behavioral interventions.
These two modules from the IRIS Center introduce users to progress monitoring in reading and mathematics. Progress monitoring is a type of formative assessment in which student learning is evaluated to provide useful feedback about performance to both learners and teachers. Because the overall progress monitoring process is almost identical for any subject area, the content in the two modules is very similar.
An effective and efficient data system is essential for successful implementation of a multi-tiered system of support (MTSS). However, prior to selecting an appropriate system, schools and districts must identify what its staff and community need and what resources the district or school has to support an MTSS data system. This two-step tool can help teams to consider both what their needs are and to evaluate available tools against those needs. Step 1 can help your team systematically identify and document your MTSS data system needs and current context and step 2 focuses on selecting and evaluating a data system for conducting screening and progress monitoring within a tiered system of support based on the identified needs and context from step 1
Diagnostic tools provide data to assist educators in designing individualized instruction and intensifying intervention for students who do not respond to validated intervention programs. Diagnostic tools can be either informal, which are easy-to-use tools that can be administered with little training, or standardized, which must be delivered in a standard way by trained staff. Teams may find it helpful to initially consider using more informal and easily accessible diagnostic tools and data to avoid loss of instructional time. Standardized diagnostic tools, which require more time to administer and interpret, may be required for students who continually demonstrate a lack of response or who require special education.
Norms for oral reading fluency (ORF) can be used to help educators make decisions about which students might need intervention in reading and to help monitor students’ progress once instruction has begun. This paper describes the origins of the widely used curriculum-based measure of ORF and how the creation and use of ORF norms has evolved over time. Using data from three widely-used commercially available ORF assessments (DIBELS, DIBELS Next, and easyCBM), a new set of compiled ORF norms for grade 1-6 are presented here along with an analysis of how they differ from the norms created in 2006.
This brief provides a framework for using Response to Intervention (RTI) with students who are English Language Learners (ELL) from Hispanic backgrounds. It examines the characteristics of these students; defines the RTI process; and then models how students’ linguistic, cultural, and experiential backgrounds can guide appropriate screening, progress monitoring, and goal setting that will help promote English literacy. The brief concludes with a case study that provides specific recommendations for how to apply screening and progress monitoring with ELLs.
In this webinar, Dr. Kristen McMaster provides an overview of Curriculum-Based Measurement (CBM) and discusses how CBM data can be used at the secondary level to monitor student progress. She discusses the purpose of CBM, provides a brief description of the research, and demonstrates how CBM data can be used to monitor student progress. She reviews CBM tools that are available for high schools in reading, mathematics, and the content areas, and provides instructions for developing CBM tools for use at the high school level. Following Dr. McMaster's presentation, representatives from Walla Walla High School in Walla Walla, Washington discuss how they have monitored school progress as part of their tiered intervention model.