While one class was racing cars yesterday, another was flying drones. I liked the gather data and predict aspect of the car lab, so I created a similar format for the drone lab.
Students were given a drone and the task: Determine the maximum height the drone can reach. Find out how distance from the controller affects this number. Use the data to make predictions about other distances and heights.
We spent about 15 minutes outside flying the drones and gathering data. Then the students came back in and Desmos to create a scatter plot and line of fit for the data. We then had a quick group discuss/recap to talk about the model and why or why not the line would make a good prediction for other trials.
Take Aways: Everyone wanted to fly, so most groups switched off controllers. Our class theory was that the controller may have actually had a bigger effect on drone height than distance. Also, we used “paces” to measure. Some groups were much better at doing these uniformly. Either way, both of these introductions of error were good talking points.
More Notes: The students are getting good at explaining their thinking orally, especially when prompted or questioned about flaws. When they write about their thinking, they still need a lot of work. Even when I say, write what you just said to me, the paper version never makes as much sense. We need to work on this!
Notes: Our drone’s battery life is very short (~6 minutes) and charge time is long. I keep one spare with me, but I also let the students know this. They have to be able to get the data they need in a limited amount of flight time.