Earlier this year, I got to visit to Hollister Prep, a public charter school in California which serves a racially and socioeconomically diverse student population and achieves remarkable results, partly through its use of data-driven instruction. You can read about the lessons from my visit in an op-ed published this week in EdSource:
Many schools collect and track data, but too often, there’s a lag between data collection and reporting — or teachers simply don’t know how to use data. At Hollister Prep, data collection and analysis are constant, ongoing, and used to drive near-term instructional decisions.
I watched students complete personalized math lessons via fun online curriculum that included a cute jumping frog. But this rigorous program also provided teachers robust, real-time data (versus the quarterly benchmark reports or laborious exit tickets other teachers might rely on).
The data told teachers what types of problems a student encountered in the session and what scaffolds and supports he needed. Another teacher tracked students’ mastery of the multiplication lesson of the day to know who needed re-teaching during the intervention block.
The full op-ed is available here. You can also the report that my colleagues Gwen Baker and Amy Chen Kulesa and I released last month, “Unfinished: Insights From Ongoing Work to Accelerate Outcomes for Students With Learning Gaps,” which synthesizes research on the science of learning to inform efforts to help students close gaps and meet grade-level expectations.