Ryan Cayce's blog

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Michigan Data Hub & Early Warning Indicators

Does your school currently have an early warning system in place to identify and support struggling students? If not, consider using the State of Michigan’s new Early Warning Intervention and Monitoring System (EWIMS). The product of a partnership between MDE and the Michigan Data Hub, the EWIMS program promotes a research-based approach to identify students who are showing signs of risk for dropping out of school, examines the underlying causes to match students’ needs to interventions, and monitors students’ progress and the success of those interventions.

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Taking a Look at MDE's New Technology Standards

The Michigan Department of Education recently released a new set of technology standards that will replace the old 2009 Michigan Educational Technology Standards for Students (METS-S). These new standards are called the Michigan Integrated Technology Educational Competencies for Students (MITECS) and are meant to be taught within the core curriculum of classes.

This is a move away from the practice of assessing the technology skills of 8th graders as was required under the now-defunct Enhancing Education Through Technology (E2T2) grant. Instead of a one-time assessment, schools are now encouraged to promote technology competency skills through their everyday curriculum no matter the content area.

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Tools for Analyzing Your PSAT/SAT Data - Compare & Contrast Data

Participants who attend MASSP's Data Analysis Protocol 2.0 Workshop will have the opportunity to participate in new learning activities and that have been designed to showcase valuable resources related to the SAT and suite of assessments. In the coming weeks and months, MASSP will be highlighting some of the tools and methods we cover during the workshop that Principals may want to adopt in their buildings.

Compare & Contrast Data Chart

The first installment in this series is our Compare & Contrast Data chart, which helps participants identify mean test and section (EBRW, Math) scores and benchmark proficiency levels as compared to state averages. Participants then use this information to compare data to like schools for better analysis.