Tag Archives: data-driven instruction

Media: “Four lessons I learned from California’s Hollister prep on closing learning gaps” in EdSource

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.

Three Lessons From a Former Educator to Make Data-Driven Instruction (More) Simple

I began each school year as a teacher and eventually instructional leader with goals posted on the walls and highlighted in yellow on team documents. “+5% increase in English Language Arts proficiency.” “Growth percentile at 65 or higher.” But by November, I invariably felt overwhelmed. I’d often ask myself: “How exactly are my students doing? And what in the world should I do tomorrow?”

A reading teacher I know uses this data tracker to share growth on academic standards with her classes

Fortunately, for instructional leaders wrestling with how to spend precious time and achieve their goals, there is an approach that can help. If there’s one practice I could go back and infuse into my early days as an educator, it’s data-driven instruction (DDI). DDI, which describes using data to analyze student learning and determine next steps for teaching, helps instructional leaders prioritize teacher development while keeping the spotlight on student growth.

As a former teacher at KIPP* and director of curriculum and instruction at DSST Public Schools, I know that DDI is one of the most impactful systems a school can establish. And it doesn’t need to be complicated. 

My time as a summer fellow at Bellwether has led me to three clear lessons about DDI:

DDI doesn’t exclusively mean numbers.

Looking at student work can be a profoundly productive process for teachers and coaches. Grab a pile of papers from class, and see what students were actually doing. What steps did they take or not take? What does this tell you about how they were thinking? The simple act of discussing how a student solved a math problem or responded to a writing prompt can help a teacher know what to do to help students grow. What’s more, engaging in this discussion as a department team can lead to greater collaboration and alignment between different grade levels. 

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