How to Measure Math Improvement: Writing Key Results That Actually Tell You Something

You’re in year two of initiative X or project Y or HQIM Z implementation. 

Your teachers are doing the work. Your coaches are in classrooms. Your PLCs are meeting. New committee structures are forming. AI tools are being piloted. From the outside — and honestly, sometimes from the inside — it looks like momentum. But somewhere between the April debrief and the August planning day, a question surfaces that nobody quite wants to ask: how will we know if any of this worked?

Not “did we complete the activities?” Not “did teachers attend the training?” But genuinely — is student mathematical understanding improving? Are teachers changing their practice in the ways we intended? Is the investment producing the outcome we were after?

That question is hard to answer when the initiative has goals but no key results. And in most district math improvement plans, that’s exactly the situation.

Goals tell you where you’re heading. They orient the work. They give people something to say at board meetings: “We’re improving student understanding of fractions” or “We’re building stronger discourse practices across grades 3–5.” Goals are important. But goals without key results are like directions without a destination — the motion feels purposeful, but you can’t know when you’ve arrived.

What’s the Difference Between a Math Improvement Goal and a Key Result?

A goal is directional. It points toward something better. It’s motivating. It often lives in the language of vision — “improve,” “strengthen,” “build,” “develop.” That language is appropriate for a goal. The problem is that “improve,” “strengthen,” “build,” and “develop” are not measurable. You cannot tell, from those words alone, whether the work succeeded.

A key result is different. It answers the question: how will we know we got there? It names a specific, observable, time-bound indicator of success. It is not a description of the activity — attending a training, completing a unit, facilitating a PLC — but of the outcome produced by those activities.

Here’s what this looks like in practice. Take a common math improvement goal: “We want to build teacher fluency with multiple representations.” That’s a real goal. It points toward something important. But how will you know whether you got there?

A key result version of that goal might look like this: “By June, 75% of teachers in grades 3–5 can demonstrate three distinct representations of multiplication — physical, visual, and contextual — and connect them explicitly during a lesson observation or task debrief.” Now you have something to measure. You can observe it, document it, disagree about it, refine it. You can be honest about whether you arrived.

The framework behind this thinking — Objectives and Key Results, or OKRs — originated in the business world but has found genuine traction in educational settings because the underlying problem is the same: goals without accountability structures produce activity, not outcomes. Key results force the question: what does success actually look like when it shows up in classrooms and schools?

Why District Math Coordinators Struggle to Write Measurable Outcomes

It’s worth naming why this gap is so common. It isn’t carelessness, and it isn’t laziness. Most coordinators who lead math improvement work are deeply skilled at the instructional side of their role — they can analyze student work, facilitate compelling PD, and diagnose implementation gaps in real time. The OKR skill set is different. It draws on performance management and organizational design thinking that most educators were never trained in, because it has historically lived outside the classroom.

There’s also a vulnerability in naming key results that doesn’t exist in naming goals. A goal says “we’re working toward better math.” A key result says “we expect 70% of teachers to demonstrate X by June.” If you write the key result and June arrives with 52%, you have to name that clearly. That accountability can feel uncomfortable — particularly in systems where evaluation culture has made data feel punitive rather than informative.

But here’s the flip side: without key results, you also can’t name success. You can’t point to June and say “this worked” with any specificity. The same absence that protects you from having to acknowledge gaps also prevents you from being able to celebrate genuine progress. That ambiguity costs as much as it saves.

Key Results for District Math Improvement: What Good Actually Looks Like

Well-designed key results for math improvement tend to share a few characteristics. They’re grounded in specific, observable behaviors rather than perceptions or general trends. They have a clear timeframe. And they connect the work directly to what you want to see in classrooms or student learning — not to the activities you’re asking teachers to participate in.

Here are a few examples, drawn from the kinds of instructional work that districts are commonly prioritizing:

A district working on teacher anticipation might write: “By December, coaches can document evidence of teacher anticipation — including multiple student strategies and at least two representational paths — in 60% of pre-observation conferences.” This is specific, observable, and tied to a coaching behavior that predicts instructional quality.

A district working on student discourse might write: “By March, classroom walkthrough data shows evidence of three or more student-to-student exchanges (not student-to-teacher) per 15-minute instructional segment in 50% of observed classrooms.” This is uncomfortable to write because it might reveal a gap. It’s also exactly the kind of evidence that makes coaching cycles purposeful rather than generic.

A district focused on manipulative use in secondary settings might write: “By May, all secondary math teachers can demonstrate at least one physical model connected to an abstract algebraic concept and articulate the representational link in a department-level PLC.” This anchors a cultural shift — not just in whether teachers own manipulatives, but in whether they understand why and can explain the connection.

Notice what these key results are not measuring: training attendance, PD completion, or teacher satisfaction surveys. Those are activity measures. They tell you whether things happened, not whether the things that happened produced the outcomes you intended.

Leading vs. Lagging Indicators: How to Balance Your Math Improvement Measurement Plan

One of the most important design decisions in building a math improvement key result structure is getting the balance right between instructional leadership objectives and content-focused objectives. It’s easy to over-index on one.

An overemphasis on instructional leadership key results — coaching cycles completed, PLCs facilitated, walkthroughs conducted — produces a system that looks healthy on paper but may not be moving teacher practice or student learning. The activities are happening, but the artifacts of those activities aren’t telling you whether the math got better.

An overemphasis on student outcome key results — test scores, benchmark assessments, grade-level proficiency rates — produces a system that can feel punitive and leaves coaches and coordinators without the intermediate, leading-indicator data they need to adjust support in real time.

The most useful math improvement key result structures balance both: leading indicators that live at the teacher and coach level (visible, adjustable, within the system’s control) alongside lagging indicators at the student level (important, but slower to arrive and harder to attribute).

Research from Cobb, Jackson, and colleagues on systems for instructional improvement reinforces this principle: effective districts develop clear theories of action that connect professional learning activities to observable changes in teacher practice to measurable shifts in student learning — and they track all three, not just the last one (Cobb et al., 2021).

Building a Math Improvement Measurement Rhythm From August to June

Key results don’t sustain themselves. They require a rhythm of checking in — not in a surveillance sense, but in the genuine spirit of asking whether the work is moving in the direction you intended.

That rhythm might look like a monthly leadership team meeting where one key result gets reviewed with real evidence from classrooms and coaching cycles. It might look like a mid-year recalibration where the team asks whether the original targets still make sense or whether context has shifted enough to warrant revision. It might look like an end-of-year stocktake where you can genuinely say “we got here” or “we didn’t, and here’s what we think that tells us.”

The goal is not compliance with a document. It is honest learning about what’s working and what isn’t — so that next year’s plan starts with real information rather than fresh optimism.

Why Measuring Math Improvement Is What Makes Progress Compound Over Time

Our Math Improvement Flywheel’s first component is Design & Measure — and measure is not an afterthought. It is the mechanism by which improvement becomes self-sustaining rather than perpetually restarting. Without clear key results, every August planning cycle begins from scratch. With them, the system has memory. It knows what it learned. It knows where it is on the improvement arc.

Most math programs don’t fail because the people in them aren’t working hard. They fail because the system isn’t designed to know what the hard work is producing. Key results are how you fix that. They are how you stop measuring activity and start measuring impact.

Start Here: Assess Where Your District Math System Stands Today

If you’re heading into summer planning and want help translating your math vision into clear, measurable key results for next year, the free Math Improvement Assessment is a useful place to start. It identifies the current state of six areas of district math systems — including goal-setting and measurement structures — and gives you a personalized report with guidance on where to focus first.

Take the free Math Improvement Assessment here.

Then,  Grab our Math Coherence Compass to start the important work of shaping your Key Results.

References:

Cobb, Paul, Kara Jackson, Erin Henrick, and Thomas M. Smith. (2021). *Systems for Instructional Improvement: Creating Coherence from the Classroom to the District Office.* Harvard Education Press. https://hep.gse.harvard.edu/9781682531778/systems-for-instructional-improvement/

Center for Student Achievement Solutions. (n.d.). *How OKR Action Planning Elevates Student Achievement.* https://www.studentachievementsolutions.com/how-okr-action-planning-elevates-student-achievement/

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  • Why most math initiatives stall during implementation—and how to design for the “messy middle”
  • How alignment between district leaders, principals, and coaches shapes classroom instruction
  • What actually builds math teacher buy-in (and why it comes after clarity)
  • How conceptual understanding, fluency, and equity are system design issues
  • Why sustainable math improvement depends on structure—not heroics

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