At CenterPoint, we think a lot about data and how to support teachers in using it to inform their teaching. We often use the wonky term – data literacy – when talking about this work. What exactly is “data literacy?” Here’s an example that demonstrates what we mean by data literacy and how important it is for understanding standards-based student reports.

When teachers receive a class-level, standards-based report from an assessment, they may see something like this:


In this report, a teacher can see how students in one class did on a 4th grade English/Language Arts assessment for four different standards (4.1, 4.2, 4.3, and 4.4). They can see the percentage of students that demonstrated mastery and the average number of correct assessment items for each standard. At first glance, a teacher may look at this data and think “I need to really work on Standard 4.2 with my students.”

If we left the data analysis there, the teacher may dive deep into reteaching standard 4.2 to reteach some of the skills that go with it. Many teachers would do so using a simpler text in hopes of building student’s abilities. With that thinking, a teacher could spend weeks focusing on that standard alone and miss an important piece of the data puzzle.

Luckily, this teacher administered a high-quality assessment with a balanced approach to measuring student learning. That means that this literacy assessment included passages with varying levels of complexity (or difficulty) for students to read and answer questions about. So, we can add another layer of data to consider:


When we step back and look at the data this way, we realize that there is more to the story than just a specific standard. When we consider the complexity of the texts that students read and answered questions about, it becomes clear that students in this class really struggled with the very complex text in the assessment and did well (100%!) with the readily accessible texts. With that in mind, the focus should shift to practice with complex texts rather than simpler texts and not necessarily a specific standard.

A teacher who understands this level of analysis in their data will make conclusions that go beyond “I need to work on Standard 4.2.” In this case, s/he might consider selecting more advanced texts to teach from in their curriculum or in a remediation block, such as having students practice close-reading protocols on a paragraph of a complex text. That teacher will also save valuable instruction time and keep students challenged and engaged in their learning.

This analysis could also go two the three layers deeper by examining differences in student performance between literary texts (such as poems and stories) and informational texts (such as articles), as well as whether the text is “warm” (connected directly to a topic they are learning about in class) or “cold” (a possibly unfamiliar topic). The big idea here is that data literacy, especially now, is critically important – and requires a level of depth of analysis that teachers must master.

Here are four steps for teachers to consider when analyzing student data.

Step 1. Take the Assessment Yourself. To better understand the data from assessments, teachers should take the assessment themselves. In literacy, this includes analyzing the features of the texts. If there is writing involved, it is helpful for teacher teams to write exemplar responses together. In mathematics, this includes an analysis of tasks or item stems.

Step 2. Examine the Balance of the Assessment. A balanced assessment should provide a range of complexity in the content covered and the types of items used. In literacy, teachers should make themselves familiar with the standards that are covered, and the qualitative and quantitative features of the texts used. In math, they should look at the distribution of items for conceptual, procedural, or applied qualities. For both subjects, teachers should examine the range of item types used and their level of rigor (such as the DOK or depth of knowledge levels).

Step 3. Go Deep with the Data Using Item AND Text Analysis. Teachers should examine data by conducting both an item analysis that looks at the features of an item (e.g., Depth of Knowledge (DOK), item types (multiple choice or something trickier?), and standard assessed as well as how students did with the qualities of the texts. For instance, students may do well on simple multiple-choice items with complex texts but struggle with higher DOK items (DOK 3 and 4); others might do well with complex items but only when that item is paired with a readily accessible text.

Step 4. Adjust with the Bigger Picture in Mind. Zoom out with the bigger picture in mind, consider how both the features of the text and the features of the assessment should inform instructional adjustments. This level of thinking will help teachers be intentional about how they teach a given text in their classrooms and might give insights on how to use their reteaching time that goes beyond “I need to focus on Standard 4.2”.

Here at CenterPoint, we see data literacy as an authentic opportunity for teachers and teacher teams to deeply know their students and impact student learning. We know how powerful data can be when strong assessments and data literacy are a major part of the work. Starting this Spring, we are partnering with two large urban school districts to pair data literacy training with our curriculum-aligned assessments. Using EL Education’s ELA Curriculum and Illustrative Mathematics Curriculum we are working with teacher teams to analyze the assessments and dive deep into the data.

As you and your teams head into a Fall unlike any before, CenterPoint is here to help you with strong assessment options and the data training to go with it. Reach out to us at to learn more.

Joey Webb serves as the Director of Academic Services for CenterPoint Education Solutions