Why Averages Can Mislead Teachers: How Cohort Analysis Leads to Better Instruction

Ever heard the joke about the statistician who had to get rescued by the Coast Guard boat?

He thought he could walk across a lake that was, on average, only two feet deep.  Averages lie. After all, if you have a classroom full of students who are on average proficient, you still have a range of students, some needing acceleration, some needing remediation.

Averages are helpful, sure. They give us a quick sense of where the middle is and how students are performing overall. When data is limited, an average is better than nothing. And averages are convenient aggregators: one number instead of dozens of individual student data points. But there has to be a better way.

Enter cohort analysis.

What is cohort analysis? 

You may have heard of cohort analysis in a presentation at a webinar or conference. Maybe it’s a term in a newsletter or article you glossed over. Let’s break it down.

A cohort is simply a group of students who share something in common. Most often, that shared characteristic is their grade level. For example, you might analyze one cohort of juniors and another cohort of seniors.

The analysis part means looking for patterns or shared characteristics that lead to mastery.

Here is the key insight. Cohort analysis focuses on actions that lead to mastery.

Why Cohort Analysis Matters

This is the real kicker. Cohort analysis has a bias toward action. When you calculate an average, you add up student scores and divide by the number of students. That gives you a snapshot. But when you examine patterns among students who reach mastery, something powerful happens. You uncover testable hypotheses.Instead of simply describing student performance, cohort analysis helps you identify strategies worth trying in the classroom.

I know we’re throwing around some five dollar data analysis words, so hang with me for a second while I give you an example. I used to have a group of students who started senior year with ACT scores below 17. I had students with “college ready” ACT scores (school-dependent but typically between 20-24), and even students with scores near the ceiling of 36. 

My students with the scores above a 17 all had the same thing going on: they had ACT scores on the English portion 20 or higher. This first part of the cohort analysis gave me a hint: reading comprehension was playing a big part in student scores. The hypothesis this gave me, this strategy I could try and test, was that students who improved their reading skills would improve their ACT scores, even on the math section.

Turning Data Into Action

As educators, many factors are outside our control. We cannot change a student’s home environment or family support system. But we can change how we support learning in our classrooms. For example, introducing Scarborough’s Reading Rope gave my students a framework for understanding how reading works. The Simple View of Reading (word recognition multiplied by language comprehension equals reading comprehension) became something we explicitly practiced and discussed in class. We focused intentionally on building both word recognition and language comprehension, and I’d urge you to also check out the (free!) resources from The Reading League. 

And the results were just what I’d hoped for. Not only did English scores go up, Math scores also improved. As a result, composite ACT scores increased. Targeting reading comprehension had ripple effects across subjects! 

How to Start Using Cohort Analysis

You are probably doing more cohort analysis than you recognize, unconsciously. When teachers notice patterns among students and adjust instruction accordingly, that is the essence of cohort thinking. The next step is simply to make that process more intentional and systematic.

Start first of all with mastery. Get specific about which standards you are analyzing. Second, get clear on what data you are using. Vibes need not apply: we want data that is clear. Third, get focused on what your next action is. This can feel tricky, so let me give you a hint: try and pick something specific. You’re not going to be able to redo all primary instruction your middle schoolers got before. 

A great, user friendly cohort analysis tool is the CAT (Cohort Analysis Tracker). With the CAT, you can view data for individual students or summarized for entire cohorts over time. You can filter by demographics as broadly or specifically as needed, creating exactly the kind of view that teachers need to set meaningful, achievable goals. It's the solution many of us wished we had in our classrooms to better support our students' learning journeys. Check out a video of the Cohort Achievement Tracker here or view a sample copy of it online here.

Final Thoughts and How to Take Action

How does your team think about cohort analysis in education? We’re all ears and invite you to join in the conversation on social media. And if you are ready to make using data easier invite you to grab time with us to talk more!

About Instructional Data Solutions: Our mission is to remove barriers to enable education organizations to focus on what matters most. We assist school systems and education organizations of all sizes by collecting, analyzing, and clearly communicating data. We are committed to empowering educators through comprehensive data analytics and tailored support. Additionally, we provide dedicated support for operational needs, process improvement, and special projects, offering customized solutions to enhance effectiveness and success. Our solutions bridge the gap between data collection and instructional improvement in PK-12 settings.