MTSS teams refer to the leadership team or teams that guide and support the implementation of MTSS. MTSS teams should be representative of all key stakeholders, including regular education, special education, administration, and family and community input. MTSS teams also have structures and clear processes in place to guide decision making, and the teams have protected time set aside to meet on a regular basis.

School Infrastructure and Support Mechanisms include the knowledge, resources, and organizational structures necessary to operationalize and implement all of the components of MTSS in a unified system to meet the identified implementation and outcome. This collection of resources summarizes the infrastructure and support mechanisms outlined in Section 5 of the MTSS Fidelity of Implementation Rubric as necessary for successful MTSS implementation.

Written in collaboration with leaders of the International MTSS Summit, this article shares the research support for MTSS and describes its benefits and application to international schools. The article appeared in the EARCOS Triannual Journal. View the article in the full journal below on pages 36-38.

Innovation configurations (ICs) are designed to evaluate current teacher preparation and professional development (PD) by determining the extent to which EBPs are taught, observed, and applied within teacher preparation and PD programs. This IC can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS.

Response to intervention (RTI) is a multi-level prevention system to maximize student achievement and reduce behavioral problems. With RTI, schools use data to identify students at risk of poor learning outcomes, monitor student progress, provide and adjust evidence-based interventions when needed, and identify students with learning disabilities or other disabilities. In this video, Dia Jackson describes the importance of implementing RTI with fidelity and how she provides RTI coaching and professional development to schools so that they see gains in student achievement.

This series of guides describes the setup and use of the EWIMS process based on data-driven decision-making research. The aim of this guide is to support school and district efforts to systematically identify students who are showing signs of being offtrack in school (an early indicator of risk for achieving key educational milestones like on-time graduation), match these students with appropriate interventions, and monitor students’ progress within those interventions. A guide is available to support district level implementation as well as Middle and High School Implementation.

An early warning system allows educators to assign and provide appropriate interventions to at-risk students early on, during the 9th grade year, to prevent dropout before it happens.This video from the Regional Educational Laboratory Midwest (REL Midwest) summarizes research on early warning systems and dropout prevention. The video includes highlights from the research conducted by REL Midwest on behalf of the research alliances in the Midwestern states.

Building a Multi-System Trauma-Informed Collaborative is designed to help child-serving agencies and their partners build a coordinated and more effective response to child trauma, and to support jurisdictions as they look to further coordinate services and response across diverse stakeholders.

The guide is intended for an audience of state or local policymakers, public agency administrators, trauma experts, provider partners, and other stakeholders. The guide:

The purpose of this document is to provide content-specific examples of how to structure educator-level and/or systems-level coaching as a mechanism to ensure ongoing professional learning to support tiered intervention. This document provides examples of coaching supports, models, and functions within the context of tiered intervention (e.g., RtI, PBIS, MTSS) and data-based decision making (e.g., data-based individualization [DBI]) for educators who already have foundational knowledge and/or experience with coaching.