The following blog was contributed by NWEA.
Many conditions that contribute to student skill and knowledge gaps are beyond an educator’s control. Learners bring to the classroom outside factors such as socioeconomic status, vocabulary deficits, and even past traumas. The obstacles are real but not impossible to overcome.
A 2018 NWEA® study examined the connection between school poverty and school performance using MAP® Growth™ data. It may not come as a surprise that when achievement was measured, a strong negative relationship was revealed. But the story was different for growth. When schools that serve students from higher-income families were compared to those that serve lower-income families, the difference was minimal.
So, if demographics don’t predict how much a student can grow, what does? The answer lies in the implementation of high-quality instruction based on valid and reliable interim assessment data.
Why an assessment with high-quality data matters
Not all data is created equal. So, what is high-quality data? According to Jennifer Bell-Ellwanger, CEO of the Data Quality Campaign, “High-quality data is data that people can use, that they can make sense of, and that they can put into action in their classrooms or in their community.”
With an instructional readiness assessment, educators have a view into a student’s zone of proximal development, or ZPD—where they have some background understanding of a subject matter and where mastery hasn’t emerged yet. With this information, it’s easier to adjust instruction so all students have the supports to appropriately access grade-level instruction.
High-quality assessment data is the canary in the coal mine, alerting educators to dig deeper—to look more closely at how instruction, curriculum, resource allocation, professional development, and communication are affecting student learning.
The five decisions to make with high-quality data
When data is valid and reliable, it allows educators to make informed decisions with confidence. But before educators can get there, they need to identify the issues they want to solve. Here are five decisions that depend on high-quality data.
