{"id":21752,"date":"2024-01-23T05:00:00","date_gmt":"2024-01-23T13:00:00","guid":{"rendered":"https:\/\/www.nwea.org\/blog\/?p=21752"},"modified":"2025-12-17T13:00:25","modified_gmt":"2025-12-17T21:00:25","slug":"4-instructional-coaching-principles-to-follow-when-helping-teachers-use-data","status":"publish","type":"post","link":"https:\/\/www.nwea.org\/blog\/2024\/4-instructional-coaching-principles-to-follow-when-helping-teachers-use-data\/","title":{"rendered":"4 instructional coaching principles to follow when helping teachers use data"},"content":{"rendered":"
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It\u2019s spring 2021 and everything feels like a mess following COVID-19 school closures. I\u2019m leading a professional learning session at a K\u20138 school in Colorado where I\u2019m an instructional coach. All staff are huddled in a circle in the library. We are discussing culture and climate data, and it is\u2026uncomfortable. Everyone in the room has their own definition of \u201cdata\u201d and their own thoughts on what should be done about the data we have to work with. Just saying the word sparks five different thought-provoking conversations.<\/p>\n\n\n\n

I hear a teacher say, \u201cI use data to help me understand my life. If the coffee is hot, I wait to drink it.\u201d That comment still stands out to me all this time later because while it did not take away the discomfort, it told me what I needed to know to coach that group of educators effectively: Teachers have a vast knowledge about data and its collection. They have many data points (maybe too many) to analyze in their classroom. The role of an instructional coach is to help make data analysis streamlined, repeatable, and worth the teacher\u2019s time. An instructional coach partners with teachers so that when they are looking at data, it\u2019s clear what they need to do next.<\/p>\n\n\n\n

Here are four principles instructional coaches should follow for effective partnerships with teachers around using data in the classroom.<\/p>\n\n\n\n

1. Clarify what data is\u2014and isn\u2019t\u2014able to show<\/h2>\n\n\n\n

The word \u201cdata\u201d has become synonymous with numbers and is often used punitively with teachers and students. I think (and I know I\u2019m not alone) that it\u2019s important to move away from using data in that way. It\u2019s simply not as effective as starting on a more positive, productive note.<\/p>\n\n\n\n

I encourage you to begin by asking, \u201cHow do you currently use data in your classroom?\u201d The process of answering this question is usually surprising to a teacher. They often realize they use data all the time and just need support with collection and analysis.<\/p>\n\n\n\n

Listing all the data a teacher collects opens up the conversation and can help you begin to pinpoint the purpose behind everything that\u2019s being gathered. This is where having a clear concept of qualitative versus quantitative data is important.  In chapter 5<\/a> of the book Action Research<\/em>, J. Spencer Clark, Suzanne Porath, Julie Thiele, and Morgan Jobe break down both types of data and give great ideas on what types to collect in a classroom. Consider sharing it with your teachers.<\/p>\n\n\n\n

While partnering with a team of teachers during that 2021 workshop I mentioned, we decided to start off with a quantitative question: We looked at the number of responses to a four-part question on fractions. Later, we tackled a qualitative question: What were the most common responses to that four-part question? Purposely identifying and focusing on both qualitative and quantitative data allowed us to have an in-depth understanding of where the students were, and it also gave agency to the team to take natural next steps with the data.<\/p>\n\n\n\n

During instructional coaching data discussions, aim to clarify what data is and is not with teachers, and to do that in the shortest\u2014yet most impactful\u2014amount of time. Data should be empowering and used with the sole purpose of supporting students in their learning process.<\/p>\n\n\n\n

2. Keep things simple<\/h2>\n\n\n\n

A scientist in a lab tries to control as many variables as they can so they can get accurate data. They know that the more complex an experiment is, the harder it is to analyze and use that data to make any conclusions. A classroom is rife with uncontrollable variables. That\u2019s why it\u2019s important to keep things simple and choose one<\/em> thing to collect data on. You can add other variables later.<\/p>\n\n\n\n

I once coached a teacher who was curious about the potential impact of Margarita Calder\u00f3n\u2019s  seven-step vocabulary method<\/a>, so we did a little experiment. Students took an open answer pre-quiz on a few vocabulary words. The class then did the seven-step vocab process and took the quiz again. Students did this a few times a week and used the vocab in a culminating project. This data we gathered was simple, but it opened up many conversations about the role vocabulary plays in teaching content. It also gave us qualitative data, because we looked for patterns in the responses, and it gave us some quantitative data, because we could see the big picture of \u201cright\u201d and \u201cwrong\u201d patterns.<\/p>\n\n\n\n

One of the primary benefits of instructional coaching is providing teachers with an ally who can help create repeatable structures that have easy organization and a clear purpose. Keeping data use simple will aid you in doing just that.<\/p>\n\n\n\n

3. Use a data protocol <\/h2>\n\n\n\n

It is tempting when working with teachers to skip using data protocols. They can feel too bulky or restrictive. As a coach, I like to look at protocols as a means to keeping us focused on the work that needs to be done.<\/p>\n\n\n\n

A data protocol will help you look at student data as objectively as possible, and it will also honor the teacher\u2019s time. Provide a data protocol unless the teacher you\u2019re working with already has one they use. I honed my data analysis skill set by using the data protocols in Driven by Data: A Practical Guide to Improve Instruction<\/em><\/a>. The book includes protocols for before and after data collection as well as for action planning. I often adapt the book\u2019s protocols depending on what stage of the data process a teacher is in.<\/p>\n\n\n\n

At NWEA, we also use Nancy Love\u2019s data driven dialogue protocol<\/a> from her book Using Data\/Getting Results: A Practical Guide for School Improvement in Mathematics and Science<\/em><\/a>. This protocol provides a clear structure while also using open-ended questions that keep you in each phase of data processing.<\/p>\n\n\n\n

The more you use a data protocol, the more it will flow for you and the teachers you support. I encourage you to choose a protocol and play with it.<\/p>\n\n\n\n

4. Repeat<\/h2>\n\n\n\n

Data partnerships should not be one and done. There is always more data, and there are always more questions to ask. That is not to say that using data should become a heavy burden for teachers. But when it\u2019s done right, teachers will realize that data use is ongoing. Having the right support will help them follow a consistent process and will uplift them and their work in the classroom.<\/p>\n\n\n\n

In conclusion <\/h2>\n\n\n\n

With instructional coaching, a coach\u2019s role in data partnerships is to guide a teacher through clear and simple processes that help the data come to life and be useful. The teacher\u2019s role is to engage with data processes that can help create more insight into their classroom and their students. Whether you\u2019re an instructional coach or a teacher, remember: If the coffee is hot, wait.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

It\u2019s spring 2021 and everything feels like a mess following COVID-19 school closures. 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