{"id":26029,"date":"2026-01-13T05:00:00","date_gmt":"2026-01-13T13:00:00","guid":{"rendered":"https:\/\/www.nwea.org\/blog\/?p=26029"},"modified":"2026-01-12T12:23:13","modified_gmt":"2026-01-12T20:23:13","slug":"from-ranking-to-learning-using-assessment-data-to-learn-from-high-growth-schools","status":"publish","type":"post","link":"https:\/\/www.nwea.org\/blog\/2026\/from-ranking-to-learning-using-assessment-data-to-learn-from-high-growth-schools\/","title":{"rendered":"From ranking to learning: Using assessment data to learn from high-growth schools"},"content":{"rendered":"

\"\"For decades, assessment data has been used to evaluate schools. At no time was this truer than following the passage of the No Child Left Behind Act, when accountability systems were laser focused on proficiency: how many students met the state standard<\/a>. Later, the pendulum swung toward growth:<\/a> how much progress students made from year to year. Today, most accountability systems strike a balance, recognizing that both achievement and growth matter, with many states including both metrics on school report cards<\/a>.<\/p>\n

This balanced approach is fairer, but it\u2019s still mostly about ranking. Growth and achievement scores are used to sort schools, display them on dashboards, and report them to the public.<\/p>\n

While we at NWEA love a norm-reference comparison<\/a>, we can\u2019t help but feel that using assessment data in this way isn\u2019t helping the data live up to its full potential. What if instead of using assessment data to judge performance only we also used data to learn from schools that are achieving exceptional growth, especially those doing so in challenging circumstances? That shift\u2014from ranking to learning\u2014could transform how districts use the data they already collect.<\/p>\n

The challenge of context<\/h2>\n

Any district leader who\u2019s ever tried to scale a promising instructional practice knows the refrain, \u201cThat worked great in those<\/em> schools, but it won\u2019t work in mine.\u201d Teachers and principals say it for a reason: context matters. Schools differ in student demographics, community resources, staff turnover, and countless other ways that shape what\u2019s possible. Just because something worked in a randomized control trial doesn\u2019t mean it will work in the real world of any particular classroom.<\/p>\n

When a district points to one school\u2019s success and tells others to \u201cdo what they did,\u201d educators are right to be skeptical. Replicating success from one school in another often fails, especially when the contexts differ<\/a>. But what if we could control for context? Imagine identifying two schools that serve nearly identical student populations and started from similar achievement levels\u2014but one consistently reports higher growth. Wouldn\u2019t that make a compelling case for collaboration and inquiry?<\/p>\n

Consider a familiar scenario: Two elementary schools in the same district serve similar percentages of students eligible for free or reduced-price lunch. Both started the year with below-average reading achievement. By spring, the reading achievement for one school\u2019s students grew nearly twice as much as the others. Although schools sometimes vary in unobservable ways, often the difference isn\u2019t the students; it\u2019s what happened in the classrooms. That\u2019s an opportunity for learning, not labeling.<\/p>\n

Seeing bright spots in the data<\/h2>\n

The key to identifying learning opportunities is good data visualization. A simple scatterplot can reveal patterns that tables of numbers can\u2019t.<\/p>\n

Below is a scatterplot similar to the one provided in our MAP\u00ae Growth\u2122 premium reports<\/a>. On the horizontal axis is average achievement for each school. On the vertical axis is average growth. This can be over any period, but fall-to-spring is most common. Each dot on the chart represents a school. The vertical line marks the 50th percentile in achievement while the horizontal line marks the 50th percentile in growth. The ovals show schools in the same vertical bands with similar starting achievement and different growth.<\/p>\n

Sample scatterplot of school growth and achievement<\/strong><\/p>\n

\"AOn a scatterplot, several patterns jump out immediately:<\/p>\n