How REMIQS Works?

How does the REMIQS (pronounced “re-mix”) work?

  • New statistical model that combines a comprehensive array of indicators, inputs, outputs, and outcomes to identify which schools have demonstrated consistent and longitudinal success in promoting high academic and social achievement with marginalized student populations
  • Integration of national data sets with state data to ensure inter-state comparability and a model that can be expanded to include more states as interest rises
  • 2-year in-depth investigations of 10 high-functioning schools across at least five states, each school with a proven track record at achieving exemplary results among vulnerable student populations
  • Identification of the practices, procedures, policies, and school features that promote high achievement among traditionally underserved student populations
  • Strategic communications components that target policymakers, impacted communities, systems-level leaders, media, and funders to show them what we can learn and scale if we gather better data and use better models to interpret them
  • Stakeholder committee: diverse group of impacted individuals who will advise project and interpret findings during full quantitative filtering and in-depth case-study phases

This research is a joint effort of JFF and KnowledgeWorks and created by the Student-Centered Learning Research Collaborative.  Funding for this project is provided by the Barr Foundation, Carnegie Corporation of New York, the Nellie Mae Education Foundation, and Oak Foundation.

Learn more about the Student-Centered Learning Research Collaborative at sclresearchcollab.org.

Bridging the worlds of research, practice, and policy, JFF’s Student-Centered Learning Research Collaborative investigates student-centered approaches to improve outcomes for learners from all backgrounds, particularly those who have been marginalized or underserved by the current system. Learn more about our current studies and work underway here.

Connect with the Research Collaborative

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