School leaders and teachers are constantly looking for ways to tailor instruction based on students’ individual strengths, needs, and interests. In response, educators are increasingly using data to monitor student progress and adjust their instructional practices based on their analysis of that data. As we previously wrote about, constant reflection and inquiry around student data are the key components of a successful professional learning community. More generally, the educator community agrees that data can unlock opportunities for students. For instance, according to a study conducted by The Bill & Melinda Gates Foundation, 78 percent of teachers believe that data can help validate where their students are and where they can go. 

However, while schools and districts across the country have been hyper-focused on becoming more data-driven, the task of turning educational data into action has proved challenging. In a recent Facebook and Twitter survey, for instance, many educators in the Teachers Pay Teachers (TpT) community said that they felt overwhelmed by the amount of data they have to analyze, and that the time and effort that’s required to gather and analyze student data has taken away from teaching and learning. As high school English teacher Heather F. put it: “Time. There’s never any time to sit and look at data and plan accordingly.” 

When asked directly about the challenges they face when it comes to analyzing student data, TpT’ers who were polled cited too little time (33 percent), too much data (12 percent), and uncertainty around how to interpret data (13 percent) as their biggest hurdles. Even more tellingly, 42 percent cited all three as obstacles. 

Keeping these things in mind, the challenge then for schools is to maximize the limited time teachers have by making the process of collecting data, analyzing it, and putting it to use more clear and efficient. But which data should teachers and school leaders be looking at? And how can they efficiently turn insights from student data into action? To help answer these and other questions, TpT’s research and editorial staff drew upon industry research and the expertise of our community to help guide educators in this area.

What data should educators be collecting?

In order to begin addressing the challenges outlined above, school leaders and teachers should begin by organizing their analysis around the type of that data is available to them. According to an article written by  Dustin Bindreiff, a special education coordinator and Nevada County Superintendent of Schools, there are three buckets of data: outcome data, predictive data, and implementation data.

  • Outcome Data: It helps schools answer the question, “How should we define and measure success?” Sources of outcome data include but are not limited to annual standardized tests scores, graduation rates, improved school climate, and remediation rates.
  • Predictive Data: It’s the data that will predict your school’s outcome measures and allows you to monitor progress. For instance, many schools use testing as an outcome measure, so predictive data would help answer the question: “What drives improved test scores?” Some sources of predictive data include attendance, work completion, and student engagement.
  • Implementation Data: Implementation data helps schools answer the question, “Did we do what we said we would do?” These measures should be both observable and measurable. Bindreiff recommends exploring the resources of The National Implementation Research Network, which is a national research collaborative focused on this kind of data.

How can educators put data to the best use?

A 2009 report written by the Institute of Education Sciences outlined some recommendations to help schools put student data to the best possible use. Here, we’ve included an overview of four of these recommendations along with specific actions that both teachers and schools leaders can take.

#1: Make data part of an ongoing cycle of instructional improvement.

To help meet students’ needs, teachers should adopt a systematic and routine approach to using data to guide instructional decisions. This process includes three distinct steps: (1) collecting and preparing data, (2) interpreting and developing hypotheses about the data collected, and (3) modifying instruction to test hypotheses. 

| Sample Action: Form a testable hypothesis.

As teachers examine student data, teachers can develop hypotheses about factors that affect students’ learning and ways to improve instruction to help all students achieve. For example, in reviewing data from a recent assessment, a math teacher might find that more than half of the students are struggling with subtraction. Then, she or he would follow these steps to form a testable hypothesis:

  • Identify a promising intervention or instructional modification (teaching a different method for subtraction) and an effect that one would  expect to see (improvement in the subtraction skills of struggling students) 
  • Ensure that the effect can be measured (look at students’ subtraction scores on an assessment after they learn the new strategy) 
  • Identify the comparison data (compare students’ subtraction scores to the assessment before they were taught the new strategy)

After forming hypotheses about students’ learning needs, teachers must test their hypotheses by carrying out the instructional changes that they believe are likely to raise student achievement. 

TpT Teacher-Author Tip

“I served as a Response to Intervention Reading Teacher. At the beginning of the year, we spent weeks helping classroom teachers complete benchmark reading assessments on each student. Once we completed these assessments, we were able to effectively create groups which let each child work at (just about) exactly their own reading level. 

Using this data helped us avoid placing students in groups where the reading material was too hard. Like lifting weights that are too heavy, starting a child at too high of a reading level is painful and can cause damage in the long run. It’s nearly impossible for a child to gain confidence in him or herself as a reader when struggling with a word or more in every sentence. Providing effectively differentiated instruction — based on the data we collected — allowed us to nurture self-confidence and a love of learning in our students.”

Anne Gardner

#2: Establish a clear data vision.

For school leaders, you should strive to create a clear vision of success for your school. This will inform which data and which measures actually matter to your vision. Without a clear vision, it’s easy to spread your resources and energy too thin. So before beginning down the path of data-based decision making, school leaders, teachers, and other stakeholders should come together to answer questions like, “What does success look like here?”

| Sample Action: Limit the number of outcome data that your school focuses on.

Limiting the number of outcome data measures is an important first step. Schools that struggle with data often make the mistake of looking at every piece of data and creating an initiative to address it. As a result, they are not able to dig nearly as deep as they need to in order to effect meaningful change. 

TpT Teacher-Author Tip

“Successful organizations know that every bit of information gives them an edge as long as they know how to use it. They rely on the ability of their employees to process the volume, variety, and velocity of data necessary to make informed decisions and adhere to current best practices. School and district administrators should provide training that empowers educators to routinely and easily dig-in when presented with data. Equipping teachers with basic data-intelligence skills like visualizing, interpolating, and extrapolating data allows them to ask smarter questions and get better results. This involves searching for patterns and trends that filter through the volume of data to clearly point the way forward. In this way, schools and organizations can begin to be more intentional in setting goals for teachers who are also more receptive to evaluation.”

— Kenda from Teaching With Owls

#3: Empower students with data. 

Providing students with a clear view of what skills they’ve mastered — and what they need to work on — helps get them invested in their own learning. Using students’ analysis of their own performance, teachers can then identify factors that may motivate students and adjust their instruction to better meet their individual needs.  

| Sample Action: Provide students with the tools and time to analyze feedback.

Students need time and tools to help them analyze feedback, identify their errors, and reflect. When providing feedback, teachers should set aside 10 to 15 minutes of classroom time to allow students to interpret and learn from the data that teachers are giving them. Providing students with a list of reflective questions (e.g., “Which skills can I work harder on in the next two weeks?”) or worksheets that help reflect on incorrect answers can help guide their analysis and help them make data-based decisions to improve their performance. Students can also keep learning logs (in print or digitally) to monitor and track progress.

TpT Teacher-Author Tip


“Using data to inform instruction is especially important and often overlooked in the area of behavior/social skills. Create time for your students to develop their own SMART goal around a social/behavioral skill. Have students take data each day using a simple five point scale and chart their own progress. At the end of each month, guide your students through a conversation allowing them to review their own data. Teach them to look for trends and suggest possible solutions, such as: ‘I always have a hard time paying attention in math, maybe I can move my seat just during math.’ This teaches students that they are in charge of their actions and leads to self advocacy. Students who are empowered to identify what they need and who know how to ask for it will build a culture of students who are responsible for their own learning.”

— Krystal from Check In with Mrs G

#4: Foster a data-driven culture within the school.

A strong culture of data use is critical to ensuring routine, consistent, and effective data-based decision making. Teachers should work together with their administrators — and with each other — to analyze and leverage data more effectively. They can also engage school leaders in conversations around their challenges and what they need to use data more effectively.

Sample Action: Dedicate a time for structured collaboration on data.

During a dedicated and structured time (in the form of grade-level meetings or professional learning communities), teachers and school staff (and even parents and caregivers!) can collaboratively analyze and interpret students’ achievement data and identify what instructional changes should be made going forward. To help facilitate the collaborative meetings during the structured time, participants usually focus their discussions on a specific topic, follow the cycle of inquiry, and are prepared to enact a data-based action plan to carry out instructional modifications.

TpT Teacher-Author Tip

“Our campus hosts Data Nights throughout the year to communicate with our parents about ‘where we are’ and ‘where we need to be’ when it comes to test performance and attendance/tardies! The parents also get to visit classrooms to learn about how their child is doing and how they are contributing to the success of the school. We also share important information, tips, and free resources they can use to promote literacy at home. We like to foster collaboration throughout the school year by hosting many morning and evening events for parents to be hands-on with their child’s growth and development.”

— Dyana from Biliteracy Now

Data analysis can provide a snapshot of what students have learned, where there are gaps, and what educators can do to better meet their students’ individual learning needs. With appropriate analysis and interpretation of data, educators can make informed decisions that positively affect student outcomes.

TpT Resources

Here are a few resources that may help with gathering and analyzing student data:

Further Reading List

Want to dive deeper into student data? Here’s a curated reading list of the sources that we cited and referred to while writing this piece.