Original Prompt


Renaissance’s Star computer adaptive assessments generate nationally norm-referenced scores that help screen students, track progress, measure growth, and inform a variety of instructional decisions. Although the Star reports and dashboards provide a wealth of information, there is an unmet need of high interest to educators – namely, the ability to compare achievement and growth to demographically similar schools. The normative scores we currently report do not take into consideration factors believed to influence achievement and growth including student demographics, school size, geography, and so forth. The ability to compare to similar schools would provide powerful insights to data coordinators interested in continuous improvement to better understand the effectiveness of their offerings, so they can expand what works and identify areas needing attention.


Hunt Statement

“This project will investigate how data coordinators use data-analytics to identify their needs and use-cases for demographically based school comparison. We will conduct user-centered research, and data-mine student growth and demographic information to inform a data-model that will drive the development of an interactive dashboard to support school continuous improvement.”