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The Long and Short of Data Analysis


Data analysis is an integral part of the school improvement process. Data helps us see where we are going and whether we are getting closer to our desired results. The key is to collect purposeful data and monitor it often.

Recently I attended a Solution Tree Workshop where our facilitator, Maria Nielsen, used the terms long-cycle and short-cycle data. I have assisted school teams analyze data for several years, but these were new terms to add to my knowledge base.

Long-cycle data is the data that we may collect once or perhaps three to four times a year. This data could be our universal screening data or yearly state assessments. The data tells a story and can help us move forward, but it is not the full picture. Short-cycle data is more frequent in nature. Weekly progress monitoring for student who struggle falls into this category. So do a teacher’s formative assessment throughout lessons and unit structures.

Schools often analyze their long-cycle data in PLCs, Grade Level Team Meetings, etc… This data is summative. It provides us a glimpse of the end results after a period of time. Yet, equal, or even more attention needs to focus on short-cycle data. The analysis of short-cycle data should happen during regular, ongoing PLC/Team meetings. Weekly meetings are ideal.

Let’s look at this analogy…

Chances are you have driven in a vehicle with a GPS system. The end result/destination is set in the GPS. The goal and typical path are determined. As you drive you may take a wrong turn or head off the path for a little bit for another task. The GPS quickly recalculates our course of action and you get back on track. This is similar to short-cycle data and the analysis. As a teacher, you know your targets. If ongoing data is collected, such as progress monitoring data, and it is monitored often you will quickly discover when you may need to recalculate instruction so that students continue on the path to the target.

If you drive and ignore the signals to recalculate your route, you may end up lost. Sometimes you may even have entered the wrong target/destination in the first place. Without careful monitoring along the way you may not realize you have gone adrift. The same holds true for students. If we only stop to analyze our long-term data, we miss the essential recalculating to reach our targets.

We need a balance. Both long-cycle and short-cycle data is important, but teachers need the time to fully monitor the short-cycle data as well as time to collaborate with collegues to determine solution to get students back on track.  To expect a certain end result, without the proper support along the way isn’t wise. The sole analysis of long-cycle data is merely going to show whether you met your target. If students are allowed to get further and further behind we run the risk of being so far behind it is nearly impossible to get them to the expected targets.

How and when do you analyze data? Do you collect long and short-cycle data? How is it monitored? What are ways you quickly recalculate to get students back on track?