How do you boost math proficiency? The answer lies in classroom and research data

Rigorous data collection can mean a lot of things, but requires frequent and targeted assessment.
Amanda VanDerHeyden
Amanda VanDerHeyden
Amanda VanDerHeyden is a researcher focused on improving learning outcomes for students. She is the creator of SpringMath by Sourcewell, a research-based assessment and intervention solution. She is also one of the founding members of The Science of Math, a movement that uses objective evidence about how students learn math to make educational decisions.

When you mention “math class” or “math proficiency” to a room full of people, you’re likely to hear a few groans and a shared sentiment of dislike. When examining the last two decades of the National Assessment of Educational Progress (NAEP) math scores, which saw a precipitous drop in the most recent report card, this consensus isn’t surprising.

The greatest loss in math proficiency since 1990 is alarming, but the alarm has been going off since the early 2000s. That’s when the average fourth- and eighth-grade student began performing in the non-proficient range in math with no real improvement in two decades.

The harsh reality that educators are facing today is the realization that even if we’re able to rebound from the losses that occurred during the pandemic, our students are still not where they need to be. Here is how a return to data-driven math instruction can make the difference students desperately need.

Math proficiency depends on effective instruction

When student learning gains are not where school and district leadership expect them to be, many are quick to place blame on the learner when they should be taking a step back and examining the instruction. As an active researcher, policy adviser and developer of academic screening assessments for the last 20 years, I have found that the trend into stagnant, non-proficient performance coincides with the move away from evidence-based instruction and toward philosophically driven, constructivist-heavy tactics.

These tactics have mischaracterized explicit instruction, downplayed the need for fluency exercises, minimized the importance of standard algorithms and promoted the idea that timed tests cause math anxiety. To start improving math outcomes, teachers must turn to objective data from classroom research to guide their instruction and intervention techniques.

Effective instruction depends on rigorous data

Given that today’s students are performing in the non-proficient range, it’s not surprising that parents, teachers and education leaders are concerned. In order to support our students in an effective and measurable way, classes need to implement evidence-based support systems. This should be based on rigorous data collection that can help educators discern which students need intervention, the type of intervention they need, and the goals that need to be set to assess if the supports are working.

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Rigorous data collection can mean a lot of things but requires frequent and targeted assessment. Screenings should take minutes and focus on tasks closely aligned with expectations for learning at that stage of the instructional program. From there, teachers can determine if the entire class needs support to master essential skills, or if a few students need individual intervention.

Classwide intervention can be implemented quickly and then used to more accurately identify students who need individualized, higher-tier support. Classrooms that have used this method have seen moderate to strong effects on academic performance for all students resulting in fewer children needing more resource-intensive interventions.

Math is a highly cumulative endeavor

This means students cannot simply mature their way into skill proficiency. They need effective instruction rooted in data to build mastery from skill to skill, grade to grade, and year to year. Two crucial pieces to building these cumulative skills are teacher collaboration and concise school or districtwide systems of assessment.

Math learning is also hierarchical, where it progresses predictably from acquisition to fluency, and then to generalization. During daily core instruction, students should be experiencing:

  • Instruction for new skill development
  • Fluency-building instruction for skills students have acquired
  • And generalization instruction for the skills they have mastered

When children reach 100% accuracy, gaining further proficiency is still meaningful. High-dosage practice with opportunities to respond embedded in games, flashcards, think-out-loud problem-solving and timed intervals makes math easier for students and is the path to developing flexible adaptable mathematical problem-solving.

With the right resources, intervention and assessment tools that are consistently applied and evaluated, our teachers and students will see success in the classroom.

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