Continuous improvement in my practice is about identifying a specific process that can be improved, applying a change idea, collecting data, and analyzing the results. This term, I am attempting to apply change ideas in my Statistical Analysis class. This is a twelve week introductory class focusing mostly on descriptive statistics. My goal is to have my students reason more about what the statistics are telling them and to justify their claims with evidence. Our 9th grade team has put an emphasis on the structure of claim-evidence-reasoning across the content areas, meaning that students are using this structure in humanities and science and math. I wanted to continue that structure with my 10th graders in this statistics class. So I revamped my approach to the course.
My idea was to use claims to drive the data analysis. It started off well enough. I created some claims and used a Pear Deck to ask students to consider the kind of data that they might need to collect and analyze. (Pear Deck allows them to think individually and respond collaboratively.) Here are the claims:
- Women who win the “Best Actress” Academy Award are typically younger than men who win the “Best Actor” Academy Award.
- Sales of vinyl records are rising and will soon overtake the number of digital downloads.
- Opening box office for sequels in movie franchises (for example. Captain America, Star Wars, Harry Potter, Hunger Games) is typically higher than for other movie openings.
- LeBron James is the best professional basketball player of all time.
- For-Profit colleges are more likely to recruit low income individuals for admission.
- More African American males are incarcerated than any other group of Americans.
Conversation around these claims also included predictions about whether or not the students thought they were true.
Remember, though, the goal was to use the structure of claim-evidence-reasoning, and my kids needed a model. So I gave them this one. After a conversation with a humanities colleague, the students analyzed my example using the techniques they learned in humanities class (highlighting claims and evidence in two different colors). This led us to create “criteria for success” and structure for a five paragraph essay. The analysis showed me that my example could be improved, so I came back after Christmas break with a second draft. We had some discussion about what had changed and whether or not the second draft was an improvement or not. Seemed like all was well. Time for them to “have at it.”
But I wanted them to practice with a single, agreed upon, class claim first. So we brainstormed lots of different claims they could research and settled on:
Original films are typically better than newer entries or sequels.
They had this document to remind them about what to write and off they went to collect whatever data they thought was relevant. And then snow season began. During the first 3 weeks of January we had 6 classes due to holidays, workshop days, snow days, and a broken boiler (no heat). Even though we ask kids to do work during snow days, my students were making very little progress on this assignment. Colossal failure. I gave them too much all at once. They were wallowing in the data collection.
I regrouped. I looked at all of the data that they had collected and gave them this data set to analyze and this document to write their essays. Problem solved, right? Wrong, again. Still too much. At the end of week 4 of this “practice” assignment (interrupted by two more snow days), and after talking with by Better Math Teaching Network colleagues and my humanities colleague, I realized that I had never actually taught them how to write a paragraph that interprets a specific kind of statistic (even though they had examples).
So, at the end of January, I tackled how to write those body paragraphs. We started with writing about means and medians. Given these box plots of average critics ratings, I asked students to write what the medians say about the claim. 
Thinking it would take them about 5 minutes to write, I thought we’d be able to critique the paragraphs that students wrote before the end of class. Wrong, again. But we were able to take a look at what they wrote during the next class. (It’s a very small class.)
I called on my humanities colleague once more and she helped me to create some scaffolding to help them organize their thoughts. This time, with variability. Each group of two received one of the variables to analyze and organize a paragraph around. Once again, we shared the paragraphs they wrote for each measure. I’m not sure how I feel about this, since all of the paragraphs are basically the same. But I guess the point was to focus on the statistics that they included as evidence and not the specific language used. Were the paragraphs “quality”? Here’s a first draft of a rubric to measure that.
As January turned into February, and the snow making machine really kicked in, I called uncle on this, feeling like I had eventually learned something – along with my students – and decided to move on. (We only have 12 weeks, after all.) I’m not sure if this is one iteration, two iterations, or three iterations of my change idea. How ever many iterations it is, it led me to a slightly different approach with scatterplot analysis.
But that’s another blog post.
rawsonmath 