In the teaching world, student data tracking is king when it comes to academically growing students. Or at least it should be. Why is that? Because student data tells the living, breathing story of your classroom. I have found that when it comes to analyzing data, teachers are camped on completely different ends of the spectrum. They’re either all in, tracking data like their life depends on it, or they’re all out, not giving data a second glance outside of team meetings. But I would argue (passionately and with raised eyebrows) that data tracking should be your number one priority this school year in order for your students to experience their highest potential for growth. But in order to track data, you first have to properly analyze data.

Team Data Analysis Does NOT Supersede Individual Data Analysis

Let’s be honest, the only data analysis many teachers do is a whole group, round table discussion with their respective teams after a major assessment is completed. You typically discuss your lowest standards, your highest standards, and create a *very loose* plan of action on what you’ll do as a team moving forward to increase percentages on the lowest performing standards. I would argue that this isn’t true analysis.

The true analysis happens alone, in your classroom, by yourself. YOU know what you taught, how you taught it, and how your students responded to the lessons. Or at least, you should know if you’re actively listening, conferring, and doing formative assessments. That information paired with your newly acquired summative assessment data tells the story of the triumphs and pitfalls of your classroom.

What Does That Look Like?

For example, let’s say my students just completed a summative assessment comprised of both literary (fiction) and nonfiction texts. As I’m analyzing my data, I see that only 62% of my students met grade level for the standard 7.5F.

TEK 7.5F reads, “The student is expected to make inferences and use evidence to support understanding.”

There is one of two ways I could approach this new information:

Scenario 1: “Hmm.. My kids struggled with making inferences. It’s only at 62% passing. That’s weird. They normally do well with that. The way the question was asked probably confused them.” In this scenario, I completely dismiss the data and chalk it up to a poorly worded question that throws my students off because in the past, my students performed well on this standard. I don’t’ give this data a second thought and move on, continuing to teach like normal.

Scenario 2: “Hmm.. My kids struggled with making inferences. It’s only at 62% passing. That’s weird. They normally do well with that. The way the question was asked probably confused them. Let me go look at each 7.5F question to be sure.” In this scenario, rather than dismissing the data, I look a little deeper, and what I find coincides with my initial thoughts, BUT I have a better understanding. Yes, my students performed well on previous assessments of this standard. When I think about that assessment, I remember that it was only assessing literary (fiction) texts. The data showed 88% of my students met grade level on this same standard with literary texts. But remember, this new summative assessment included both literary AND nonfiction texts. THAT is where the pain point is. Upon closer look, my students showed mastery on 7.5F questions tied to literary texts, but did not meet grade level when asked the same questions with nonfiction texts. BOOM!

Do you see the difference? After properly analyzing this standard, I can now go back to my lessons and think about how I taught making inferences with nonfiction texts. And because they performed so well on this standard on their last assessment, I realize that I didn’t focus on how a reader’s thought process while making inferences with literary texts are different than their thought process with nonfiction texts. I can now move forward in creating lessons that address this standard in a new, fresh way that meets the needs of my students.

This kind of data analysis is not something you can do as a team because they aren’t in your classroom teaching with you, they have different students with different needs than yours, and their data, even if it’s similar, tells a different story.

So now what?

Time. We need time to properly analyze data because if you’re doing it right, going standard by standard and figuring out the story your data tells, this can’t be done in a 45 minutes team planning session. It will likely take the teachers several days of independent data analysis, and one day of team analysis to really nail down a plan to move forward and address the strengths and struggles of students.

There’s sooooo much more I can and will say about this topic, so please be on the lookout for more data centered blog posts! In the meantime, if you need a quick and easy data tracking tool to add to your resources, check out my Student Data Trackers for Middle and High School. My students and I have used this tool for several years now, and it’s a complete game changer when discussing data and growth goals with students. I hope this mini blog on data tracking was helpful to you! Go forth and prosper in all your nerdy data tracking glory!