The last week before break, no one in an elementary school is at their best. I hit a weird wall with my g5 students that I hadn’t expected and it threw my last week plans for a loop.
The goal had been to start diagramming and building multi-sensor data loggers for use in and around our school environment. In past years, I’ve had students do this with single sensors and just collect a pile of data. I wrote some of this up in mBot for Makers, if you for some reason want more details and Scratch blocks. Reflecting on that project, I felt that I had kept the good stuff for myself. A group of 5th graders could see a huge string of temperature numbers or, after a bit of work in Sheets, reasonable line graphs of that data. When we looked at lots of those together, the interesting pictures emerged. Temperature by the elevator drops rapidly at recess. Maybe that’s because (shuffles papers) this graph shows that the doors are standing open for 10 minutes!
This year, I wanted to put students in control of those connection. Instead of gathering data from a single sensor, they would use two or three at a time. Each program would gather enough data to investigate a possible correlation. Does the temperature drop when the doors stand open? How fast? How much? How far into the hallway?
It didn’t work out like that. Instead, most of the groups wandered off into one of two directions. Either they chose sensors and locations seemingly at random (which, in g5 terms means that everyone chose their first idea and no one was willing to lose face and change) and spent the period staring at the page unable to come up with a reason why the temperature in the chicken coop would affect the amount of motion in the g3 bathroom. Or they jumped right to work designing a system that would DO SOMETHING based on sensor data. Change the color of an LED strip when the door stands open too long. Play a “wash your hands! sound every time the bathroom lights come on. Basic elementary school tools to chide the world into compliance.
It was the last week of school, and I only managed to see 3 classes out of six. I think it’s clear that I skipped an important step in this process. Maybe before we start up again, I can set up single sensors around school and present them with the kind of data that so fascinated me last year. Instead of shoving them into the heart of a hard problem, let them launch from the spot I found interesting in the first place.