Collecting Meaningful Data to Drive Instruction

“The goal is to turn data into information, and information into insight.” ~Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co.

Raise your hand if you use intuition and a gut feeling more often than concrete data to make decisions.

If you didn’t raise your hand and you use data to make all of your decisions, then skim the rest of this post and leave a reply at the bottom with a how-to guide so that we can all become more data-driven humans. For those of us (myself included) that make many decisions based on intuition, this is not necessarily a bad thing. In fact, there are books and research studies that show ways in which your gut instinct can help in decision-making. However, our gut instinct is often based on our personal experience and perspective and therefore “limited to our specific perceptual frame.” As with most things, a balance of trusting our gut and fact-checking our gut with the data is necessary when making decisions, especially decisions about students.

As an educator I have experienced times where a student’s score or response on a task is entirely different than what I would have predicted, leading me to say the all-too-familiar teacher phrase, “I know they can do it, they just [insert justification on why students did poorly on an assessment].” About 7 years ago, in my 3rd year of teaching, I heard myself say this phrase. I paused and asked myself if I would write a similar justification to each college that my students were interested in by saying, “I know they can [insert skill or content knowledge], but the test anxiety of the ACT/SAT just overwhelmed them and they temporarily forgot.” I realized that any justification for why a student hasn’t shown mastery on a skill is simply an excuse to insulate us from feeling bad about the data; yet, the excuses will not insulate our students from the results in the world outside of our classrooms.

Before we continue, agree to never say the phrase, “I know they can do it, they just…,” and instead be brave enough to look at the data from the exit ticket or unit assessment and ask, “Did they demonstrate mastery HERE? If so, what did they do that shows they ‘get it’? If not, where is the point of error that I need to reteach?”

In order to turn the data into information and information into insight, as Carly Fiorina stated was the goal of data, we must collect meaningful data.

There are 3 types of data I have found to be meaningful.

Big Picture Classroom Data

This is data that you collect throughout the year on students and often helps determine:

• who is on track for promotion or retention
• who needs intervention (small group, tutoring) and needs additional data collected in case the student has a learning disability
• who needs enrichment and can be pushed to the next level with more challenging content

Here’s the list of data I group into this category and I have linked my example google tracking sheet below:

• Behavior
• Number of Overall Failing Grades in Classes
• Semester 1 Exam Grades
• Semester 2 Exam Grades
• Spring MAP RIT Scores (based on the 2015 NWEA Measures of Academic Progress Normative Data)
• Feburary STEP Reading Level
• Accelerated Reading Individual Goal Met

📋 My Example Big Picture Classroom Data Tracking Sheet

Here’s why this data is critical! My gut instinct told me that Student 5 was “fine” and would be ready for the following grade. However, you will notice in my example that Student 5 is on track for potential retention due to their excessive absences. Because I collected this data, it allowed me to have a conversation at family conferences with the student and their family focused entirely around the importance of coming to school and emphasizing that as the work became increasingly difficult, the grades would drop unless the absences decreased.

Daily Classroom Data

This is data that you collect during the lesson in one class period and often helps determine:

• who is on track for mastering the daily objective
• who needs immediate remediation (partner teach, small group pull-out, tutoring, homework, etc.)

There are 4 “rounds” of classroom data that I have found beneficial:

• Do Now (I often use the application problem in Eureka math as this) or Oral Drill
• Guided Practice (based on aggressive monitoring — Thursday’s blog post topic!)
• Independent Practice (based on aggressive monitoring — Thursday’s blog post topic!)
• Exit Ticket

Resources and Examples:

Henderson Collegiate does some of the best daily data collection I have observed. They consistently collect and respond to the data in the moment. The picture below, taken of one of the classroom boards, shows how teachers visually track the class speed to complete Oral Drill (OD) and their average mastery on the Exit Ticket (ET) in the moment.

In Edcite’s 4th Grade Math Featured Collection, there are 50 assignments that could serve as a Do Now data collection.

Using Edcite for your Exit Ticket also provides you (and your students) with instant data. This expedites the grading process and allows you to more quickly differentiate and remediate based on student-need. Teachers also receive a report broken down by state standard.

Benchmark (or Interim) Data

This is data that you collect two or three times a year that looks and feels almost identical to the state test (in format, timing, testing accommodations, etc.) and often helps determine:

• who is on track for passing the state assessment and who needs an intervention before the next round of benchmark (or state) assessments
• who needs support with strategies on assessments (i.e., pacing, work quality, typing practice, multiple choice strategies, online tools)
• who could continue on with more independent study and potentially the next grade-level content

Some states now provide their own benchmark assessments (Louisiana Example). If not, benchmark assessments are also offered in Edcite’s Featured Collections and school and district-wide common assessments can be implemented on Edcite Schools!

At Henderson Collegiate, teachers take the objectives on which students scored the lowest, display them publicly and then continue to display the growth students make after 3 rounds of reteaching (pictured below). That is what it means to collect meaningful data that drives instruction and much of what has led to their repeated success.

We all want our students to do well—to master content. Sometimes our excuses can actually inhibit our ability to respond to students’ needs. Let’s commit to our students’ learning by making sure we have a clear understanding of where they are and what they need. In his book Good to Great, Jim Collins says, “Greatness is not a function of circumstance. Greatness, it turns out, is largely a matter of conscious choice.” Make the conscious choice today to begin collecting meaningful data on a regular basis in your classrooms and schools. This will not only make you stronger at analyzing data, but it will also benefit each of your students by clearly showing their strengths and areas of growth. Only then are you able to provide the education that best meets their needs, closes any gaps, and accelerates their growth.

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Meghan Thompson joined Teach For America in 2008 and began her career in education as a 9th-12th Special Education Teacher in Charlotte, NC. In 2010, she was a member of the founding team at Henderson Collegiate (a school that has ranked in the top 3.5% of all NC public schools for the past 4 years). In 2014, she was a member of the founding team at Democracy Prep Baton Rouge and throughout her time at DPBR served as a middle school ELA teacher, middle school math teacher and the Middle School Campus Director.