In our new algebra-based physics pilot tomorrow, we will be doing the fairly standard constant velocity buggy lab. Prior to lab, students will have read about coordinate systems, position, and time, and even calculating speed, but we have not studied uniform motion. Here’s our particular twist on getting that lab going.
Launching the Lab:
The Buggy Highway:
We set up a long “buggy highway” across the length of the hallway outside our lab room. This consists of about eight 2m-sticks lined up back-to-back and taped to the floor. Using sticky pads, we mark out an origini and key landmarks at every 100 cm.
The Deliberately Vague Question:
After orienting students to our coordinate system, we turn on a buggy so students can see and hear the wheels move, and pose the question,”If I put the buggy down somewhere along our highway, where will it be when I yell stop.” (Alternatively you could ask,”If I put the buggy down somewhere along the buggy highway, how long will it take for the buggy to hit a wall?”) Following the Den of Inquiry model, we are hoping to cultivate the response that, of course, “It depends.” Our job is to draw out from students what they think it depends upon (e.g., how long I wait before yelling stop, how fast the buggy moves, where I place the buggy down, which direction the buggy moves, whether the buggy goes straight or curves, etc). Whatever they say, we try to value it by echoing back why that makes sense and writing it on the board.
Establishing Criteria for a Good Model:
The broad goal of the lab is to determine a mathematical rule (or model) that can be used to predict where the buggy at every moment (given I might yell stop at any moment). With that purpose, we draw attention to several specific factors from above because they map well to the parameters of the mathematical model they will be developing using graphical analysis. We want to frame at the outset that a good model better take into account things like how fast the buggy goes, where it starts, and which direction it goes. In addition to having a model that can actually make predictions, these three become criteria by which we will evaluate whether our model makes sense (intuitively).
Measuring Speed “Quick and Dirty“:
Before sending students off to take data in a more guided way (position and clock readings), we ask students to find a quick and easy way to estimate the speed of the buggy without taking a lot of measurements. We are hoping that this does two things: (1) Starts them off with something they know how to do (calculate speed as distance over time), and (2) maybe makes it more likely they will later recognize the slope as related to speed. [I’m slightly worried it will make it easier, but less meaningful.]
Everyone start somewhere different:
When sending students off to take data, we have students start at different locations and have a mix of cars going in different directions, with of course some having fast/slow buggies.
Tomorrow, I’ll let you know how it goes!