I was at an all day professional development session put on by MI Excel, a Michigan system of support for priority and focus schools. The pd was around the use of data and how a focus on it can create positive change in 18-24 months.

Just to set the stage, I am not a math person. I failed or skated by with D minuses consistently in high school, was able to completely avoid it while obtaining my Bachelors, and only had to take one basic math class to get my Masters. So walking into an all day pd around data was a stress inducing situation.

The system that was presented was called the Collaborative Learning Cycle. These three steps, taken verbatim from the training, have very little to do with math and are an easy way to fearlessly look at data.

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Step 1 Activate and Engage.

In this step you get a blank sheet of data that mirrors in form the data you’ll be looking at in step two. Then you fill in the blank sheet based on your prediction of what the data will look like. Once everyone has filled in the data sheet with their own guesses you write predictive statements that explain the reason for your guesses. This is essentially a data icebreaker. It’s used to get everyone’s thoughts on paper. Once a time limit has been set and reached and group members have written their statements, you come together and write everyone’s responses on chart paper and post it. The symbolic move of removing it from the table and placing it up provides a means for everyone to get past their biases. I liked this part for two reasons, no hard math was involved because I was making up the numbers and I was able to see different points of views.

Step 2 Explore and Discover

This is when you get the actual data set. It wasn’t as difficult to look at this data because I had already seen the format in step one and played around with it using my own numbers. I was able to compare and contrast and see how close I was to the actual data points. We were asked to silently identify interesting trends or differences and then write narrative statements. This was done within a short time limit and then once again we went around the table and shared our narrative statements writing them on chart paper. Then as a group we identified statements that were similar and decided which ones we wanted to focus on for step three. This was posted on the wall alongside our other chart. I enjoyed this part more than I thought I would because I was able to look at the data and write a story around the numbers.

Step 3 Organize and Integrate

In the previous step we wrote narrative statements explaining in a factual way what we observed in the data. In this step the purpose is to write the story around the data. MIExcel calls these causal theories. This is where we take that narrative statement and discuss why the data looks like it does. One thing that was reiterated was the need to focus on the narrative statements that are in your locus of control. Once you’ve written and discussed these theories you create action plans around them. You focus on both quick wins, that can be implemented the next day, and longer term goals. I liked this part because it provided immediate concrete steps for us to do the following day.

This easy 3 step process took away my anxiety around working with data. By activating and engaging with the data through predictive statements, exploring and working with the actual data sets, and then organizing and integrating ways to impact the data, I was able to walk away from the training feeling as if I could bring the Collaborative Learning Cycle back to my staff. For an admitted mathaphobe this particular pd was a win.

How do you deal with data with your staff. What system do you use that you find helpful? Share in the comment section below.