My class made some predictions about car data, without seeing it, and came up with 3 claims:
- The heavier the car, the lower the MPG.
- Electric cars will have a lower curb weight (than non-electric cars).
- Gas powered vehicles will have higher highway MPG than electric or hybrid vehicles. (We think this was written incorrectly, but didn’t catch the error, so decided to go with it.)
We focused on claim 1 first. Students easily produced the scatter plot …
and concluded that there didn’t appear to be much of a relationship between highway MPG and curb weight. But they wanted to quantify it – evidence has to be clear, after all.
Because of the viewing window, the line looks kind of steep. But the slope of the line is -0.01 (highway mpg / pound), so it’s really not very steep at all. And the correlation coefficient is -0.164, so that’s a pretty weak relationship when we group cars of all fuel types together.
Are there different relationships for the different fuel types?
Turns out, yeah.
After some individual analysis, some discussion, and a scaffold to help organize their work, students shared their claim-evidence-reasoning (CER) paragraphs refuting claim 1.
Working on the quality
Step one was getting my students to write these CER paragraphs. (I’ve written about this before and how disastrous my efforts were.) Step two is improving the quality. I shared a rubric with my students.
We all sat around a table (it’s a small class) and reviewed all of the paragraphs together. They talked, I listened and asked clarifying questions. They assessed each paragraph. They decided that most of their paragraphs were below target. They said things like:
- “That’s some good reasoning, but there’s no evidence to support it.”
- “I’d like to see some actual numbers to support the claim.”
- “I really like how clearly this is stated.”
Even though it took time to review, it was worth it.
rawsonmath 