Sarah Schuhl

Sarah Schuhl, a consultant specializing in mathematics, has been a secondary mathematics teacher, high school instructional coach, and K–12 mathematics specialist for nearly 20 years.

Doing It or Doing It Well? Using Data for Learning

About five years ago, I decided that it was time to get in shape. An infomercial caught my eye and I found myself ordering a video program, weights, bands, nutritional guide, and pull-up bar while waiting impatiently for my new life to begin. 

After the second day of inserting a DVD into my computer and following along, I realized this commitment was not going to be easy.  With persistence, in about a month, I felt I was actually making progress and able to do the exercises.  However, just as I began to swell with pride, I caught a glimpse of myself in the fireplace glass and gasped.  While I thought I looked like the trainers on the DVD, I suddenly realized I wasn’t even close! 

Was I “doing” the exercise? Yes! Was I doing it well? Not so much.

I was reminded of this moment recently when working with a collaborative team analyzing data. They had already been working for about a year to address the four critical questions of a PLC.  With commitment and persistence to improving student learning, the collaborative team embodies a “can do” spirit, even when the work seemed difficult.

Each teacher on the fourth grade elementary team brought data from a recent assessment from his or her own class.  They stared at their own clipboards and looked at the number of red, yellow, and green cells they had shaded for students not proficient, close to proficient, and proficient.  They then determined some students didn’t learn and some did, guessed at a few reasons for why, and wanted to talk about planning the next unit. 

Were they looking at data to determine if students had learned? Yes!  Were they looking at data to analyze student strengths and weaknesses and determine a collective, specific response to student learning – the purpose of looking at data? Not so much.


5 Steps to Doing Data Well

Much like exercise, with practice, collaborative teams become more effective and efficient analyzing and responding to data.  I have found teams are most effective looking at data when they:

  1. Start with a common assessment: Collaboratively plan the common assessment that will be used to analyze and respond to student learning.  During the planning (ideally, before the unit ever begins), teachers chunk the assessment items by essential learning standards, determine rigor of the items, make common scoring agreements, and determine the level of student work needed for varying proficiency levels.
  2. First look at an overview of the data: Teachers determine the percentage of students proficient by target and gather their data onto one document for all members of the collaborative team to view when discussing the data (Google Docs is one possibility). Looking at this initial picture of the data allows teachers to address areas of strength and areas to grow related to student learning across the team and within each classroom. They also can discuss any surprises in the data and make sense of the student learning in each classroom compared to the whole grade level or course.


    Target 1

    Target 2

    Target 3

    Target 4

    Teacher A





    Teacher B





    Teacher C





    Team Total





  3. Identify student by standard proficiency: Once there is a common understanding of student learning, it is then critical to acknowledge and discuss which students are proficient and not proficient, or proficient, close to proficient, and far from proficient by target.  Elementary teachers often do this by listing the names of students in each category by target.  Secondary teachers often highlight class rosters green, yellow, and red to see the name and number of students in each classification.
  4. Identify trends and patterns in student work from the highest to the lowest performers: Finally, teams identify first, the trends in student thinking and work that caused a student to be proficient.  What did these students do in their evidence of learning to set their work apart from the others?  Next, they address the evidence of the work shown by students close to proficiency and compare and contrast that student work to the work of proficient students.  Is there something to target that might be a catalyst to move students close to proficient into the proficient category?  Last, the team looks at the work of those students far from demonstrating proficiency and continue the process, looking at what might be targeted in future learning. 
  5. Make re-engagement/enrichment plans: From these discussions, teachers can make a collaborative plan to re-engage students in learning.  Does the team need to stop, shuffle students, and plan a full lesson for each group of students?  Does the team need to address learning by spending 10 – 15 minutes three days a week during core with specific activities all students will have opportunities across the team to learn from?  Does the team need to plan for focused and targeted Tier 2 or Tier 3 intervention?  Also, how are students part of the plan by identifying what they learned and what they still need to learn in this process? 

There is a sample data analysis protocol under Tools and Resources developed by Rick DuFour on the All Things PLC website your team may want to use when analyzing data.  You can find it using the following link:

By analyzing data as a collaborative team and collectively responding to the learning of students, collaborative teams learn and students learn – a win for both. More than a checklist for having “done it” is the need to do it well to impact student learning.

While I may never have perfected the exercise routines, I know with practice my skills and results improved.  I encourage you to determine a protocol for analyzing student data so your team answers “Are we analyzing and responding to student data to improve student learning? “ with a resounding “Yes!” 


Catherine Grothmann

Good Morning,
Thank you for this post. I really enjoyed reading about how to incorporate and analyze data. I have been a part of both a school that incorporated data and PLCs and currently one that does not. There are no PLCs, common assessments, common formative assessments and data analysis. I find the steps to assist in breaking down and analyzing data to be extremely helpful. I recently set a goal with my mentor for next year to create at least 3 formative assessments for each chapter that we can both use to create collaboration and assess student learning and growth. I believe this will be a positive transition to more collaboration within the science department. The PDF provided will also be an extremely useful tool when meeting about students learning and analyzing data.

Posted on

Catherine Grothmann

Good Evening,
I enjoyed reading this post. I really like the idea of using common assessments. I have been apart of districts that require common assessments and districts that do not require them. The districts that required common assessments had a strong PLC foundation and allowed to collaboration with analyzing data and improving student growth. The districts that have no required common assessments have no PLC foundation. It is a struggle to be unable to collaborate with colleagues. The steps provided breakdown very nicely how to analyze data along with the pdf provided. My hope with the shift in teaming next year in my school there will be more opportunity to collaborate and create a PLC atmosphere where we can analyze data collectively and focus on student learning and growth.
Thank you!

Posted on

LeeAnn Martin

As we are approaching time for our first report card, I can't help but reflect on my students and their learning. I have been trying to think of a way to help them better and better understand what they need. My team of teachers already has incorporated common assessments, but we never come back with how our students did on them. I really think by implementing steps four and five that we as a grade level would do so much better. It is always good to bounce ideas off of one another or ask others for advice. Coming up with interventions together and also ways to challenge our higher level learners would be very beneficial to all teachers in our grade level team!

Posted on

Bethany Kelly

As I prepare to begin this next year I reflect on my past years of teaching. Have I been just playing the game? Or have I been doing my job well? I want to do what is best for my students. One of my goals for the year is to incorporate common formative assessments on my team and to analyze data to drive instruction. Your 5 steps for doing data well will help guide me this year. thank you!

Posted on

Rebecca Donovan

I really like the idea of using a standardized template as way to complete analysis. I feel like the way the steps to analyze the data was broken down in a way that was easy to understand and will totally be helpful as a guide my team. We often feel overwhelmed with where t start when ti comes to our data. This post has really helped me create a checklist in my head for assisting in data analysis.

Posted on