Using Data to Identify Instructional Root Causes

A new principal began her career at King Elementary School, a K-5 school in an urban area. She spent time getting to know the school, the teachers, the students, and the community during her first few months. By doing this, she had a better understanding of the school’s status. She saw that the school was not doing well, and the results were low. Only 23% of the students were reading at grade level. 

In reviewing cohort data (performance of same students over 3 years), students in grades 1 and 3 increased results but students in grades K, 2, 4, and 5 stayed the same or decreased each year. It was now time to look at RCA and determine what was working in grades 1 and 3 and what was missing in the other grades.

Instruction as a Possible Root Cause

Instructional practices are intertwined and complex. Elements of effective instruction include the learning environment, student engagement, complex thinking, clear shared outcomes, practice and feedback, strategies for your specific subgroups, content-specific strategies, etc. There are a lot of factors that need to be considered to meet the needs of the students.

Just as we set up learning outcomes for students, it is also important to identify data metrics to evaluate instruction. The metrics will help you determine if classroom instruction is impacting your SMART Goals and achievement results. 

Many schools can identify their top-performing teachers based on what they see happening in the classrooms for students. Most of the time, the data will confirm who these top teachers are. But if the data doesn’t support it, it is recommended to ask “why” if there is a mismatch until you discover the reason.

At King School, they used their proficiency data from district benchmarks and state assessments to evaluate performance. In walking through classrooms, the principal identified a strong classroom teacher whose data did not support what she was seeing. I will refer to this teacher as Mrs. Data.

Students loved being in Mrs. Data’s classroom and they worked hard under her guidance. Every time you walked into her classroom; you observed evidence of strong instructional practices. Her students also enjoyed learning through her. In the past, her results were consistently strong, and she was able to achieve her goals. However, for the past two years when the proficiency data was reported, Mrs. Data’s results were low. This was very discouraging for both the principal and the teacher. 

As we dug deeper into Mrs. Data’s student performance data, we discovered the problem. For the past 2 years, many students were hand-selected to go into Mrs. Data’s class because they were stuck. Students who were not progressing with other teachers were placed in Mrs. Data’s class. Since she had a past record of consistently moving students forward, she was asked to help these students. She enjoyed working with these students and wanted to assist them.

As the team dug into their data, they realized that they did not have a component to measure growth for lower-performing students. This enabled them to identify a new growth data metric and it was translated into meaningful charts. It was discovered that every student in Mrs. Data’s class grew in 8 weeks, at the mid-year benchmark, they grew 6 months to a year. As her data was compared to the rest of the teachers, it was discovered that Mrs. Data had the best growth in the school, even with students who historically did not progress. 

Many teachers asked – What was Mrs. Data doing?

As teachers began to discuss their data, they quickly recognized that they did not use the strategies that Mrs. Data implemented. They showed data ownership and asked for guidance to improve their results. The principal provided training and support for the staff to enhance their strategies. Teachers and staff had a better understanding of what they should do next because they got deeper into their data.

As a result, the school data improved from 23% of the students at grade level to 62% within 3 years. 

Root cause analysis with inaccurate data could have misled them in identifying the deeper root causes. Their current data misjudged the instructional performance of Mrs. Data.  When looking at instructional root causes, consider school walk-through data, and informal/formal teacher evaluation data. If you find a mismatch between the 2 data sets, it’s time to start asking questions to uncover why.  

When the achievement data confirms your classroom observation, it is also a good time to conduct an RCA. But this time, try to identify the positive root causes. Positive root causes are factors that improve your results and should be replicated. With this, you’ll be able to have a deeper understanding of your top teacher’s classroom strategies. It could give you details on how to implement it in other classrooms as well.

When beginning your RCA, it is important to include specific data metrics. These metrics should include a combination of proficiency and growth on both formative and summative assessments, instructional performance data for teachers, and standards performance data for students. 

Instruction and evaluation data for teachers will help you identify areas for training and support. Students’ performance data on standards and skills will help teachers make informed decisions on what to do next for students. If you or your team questions the mismatch of data points, you will reveal the reason why once you go deeper into the analysis. 

Instructional leadership and conversations are critical when helping teachers improve student results. For more information on Instructional Leadership see the blog post: 3 Building Blocks for a Student Success Culture (Part 2 of 4) (debradurma.com)

*School name is fictionalized. School staff and the results are real.

If you are interested in more information on using your data to analyze instructional strengths and challenges, request a FREE consultation call with me.  Fill in the Contact Form Link: https://debradurma.com/contact-us   Type in "Request a FREE Consultation" in the "Additional Questions or Information Needed" box. You will receive a follow-up email with the next step to schedule a phone call to discuss your needs and questions.