Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
Implementation Guidance and Considerations
This webinar challenges current thinking about how to set appropriately ambitious and measurable behavioral goals in light of the 2017 Endrew F. v. Douglas County School District decision by the United States Supreme Court. Dr. Teri A. Marx from the National Center on Intensive Intervention and the PROGRESS Center, as well as Dr. Faith G. Miller from the University of Minnesota—Twin Cities, share how to set ambitious behavioral goals for students by using a valid, reliable progress monitoring measure, and how to write measurable and realistic goals focused on the replacement behavior.
In this webinar, Drs. Tessie Rose Bailey and Zach Weingarten from the National Center on Intensive Intervention and the PROGRESS Center, as well as Thom Jones from the Wyoming Department of Education and Justine Essex from Freedom Elementary School in Cheyenne, Wyoming shared how to set ambitious goals for students by selecting a valid, reliable progress monitoring measure, establishing baseline performance, choosing a strategy, and writing a measurable goal.
Teams are a vital part of an effective multi-tiered system of supports (MTSS) across both academics and behavior as well as special education. Making connections across the across the various teams used in MTSS and special education can be challenging. This resource from NCII and the PBIS Center, provides information about how DBI can support IEP implementation and provides a table with key considerations for teams working across the MTSS system.
This checklist can be used by intervention providers or planning teams to review, document, and improve implementation of the data-based individualization (DBI) process and monitor whether the student intervention plans were implemented as intended.
Intensive intervention teams can use these checklists to monitor implementation of the data-based individualization (DBI) process during initial planning and ongoing review (progress monitoring) meetings in order to ensure teams develop high quality student plans. These detailed checklists may be most beneficial for less experienced teams. As teams become more familiar with DBI implementation, they may choose to use the checklists less frequently or focus on only a subset of items.
The DBI Implementation Rubric and the DBI Implementation Interview are intended to support monitoring of school-level implementation of data-based individualization (DBI). The rubric is based on the structure of the Center on Response to Intervention’s Integrity Rubric and is aligned with the essential components of DBI and the infrastructure that is necessary for successful implementation in Grades K–6. It describes levels of implementation on a 1–5 scale across DBI components. The rubric is accompanied by the DBI Implementation Interview which includes guiding questions that may be used for a self-assessment or structured interview of a school’s DBI leadership team.
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