First Challenge Lab: Buggy-Cart Collision

Our final “lab” for out Unit on 1D kinematics was a challenge lab where students had to apply both data collection/analysis and problem-solving skills to make a prediction. Students were given a constant-velocity buggy and a low-friction cart on the ramp. Students had to collect data to build models for each that could then be used to predict where to place the cart on the ramp so that it crashes into the buggy driving by the bottom of the ramp. After building their models, students were given the starting position for the buggy, then asked solved the problem and check their predictions.

We had originally wanted to do the  marble rolling down the ramp and into seat of the buggy. The small marble hitting the seat is much cooler than just a collision of two larger objects, but the marble limits the tools students can use. Marbles are too small to be picked up by motion detectors. While marbles can be used to mark position and time with photogates, you cannot easily measure the instantaneous speed (because you don’t know what width of the marble is blocking the sensor very easily). Because we had wanted students to decide what tools they’d like to use, we went with carts in planning out the challenge. That way students would be able to choose motion detectors, stopwatches and metersticks, or photogates to collect data… all tools we’d used previously.

In the challenge labs, students were supposed to first spend time planning their data and analysis (checking it with an instructor before getting equipment), then carry out data collection and analysis, and finally sett up the problem-solving strategy before getting the release point.

Students were supposed to get 2 hours to do all this. However, we had fallen behind (partially due to activities taking too long and me breaking my ankle), so we spent the first 1.5 hours (of a 3 hour class) discussing free-fall and working whiteboard problems. This time was well worth it.  Students got a much deeper understanding of acceleration and much needed practice with working with velocity vs. time graphs to solve problems. We (the other instructor piloting the new curriculum and I) knew we were going to have less time, and so decided with only 1.5 hours to do an abbreviated challenge lab.  Instead of each group having their own setup, we had one big demo setup– a 2.2 meter track with a cart. As a whole class, we talked about what information we would want to know about the buggy and the cart and what different ways we could figure that out. After discussing various options, we opted to use the motion detector for both. The logger pro graphs for position vs.time and velocity vs. time for both cart and buggy were left projected at the front of the room.

The downsides to this abbreviated challenge lab were (1) less student agency about how to collect and analyze /data, and (2) everyone solving the same problem rather than individual problems. The good part was, for a first challenge lab, it got students comfortable with the format.  We did the “deciding how to collect and analyze data” together and they had to solve the problem with their group. I think it significantly reduced the stress that students might have otherwise felt.

Some groups were still a bit stressed, mostly in struggling to turn the actual scenario into a physics problem that could be solved. With HW and whiteboard problems, they get practice turning word problems into physics problem. It was a good struggle, but it made me think that we need to do more whiteboard problems that are quantitative setups rather than word problems. The truth is students need practice with both, but for students to feel confident going into challenge labs, we need better balance.

Every group was able to be successful in making their prediction. Most groups just need conversations reminding them of things they already knew. “Have we solved problems similar to this one in class?”, “What approach did you take in that problem?” “Will that approach work here?” Other students needed conversations about being more organized or systematic. “I see you’ve listed some of the information for the buggy and the cart. When we solved problems like this, what did a good list of knowns and unknowns look like? Does your list meet that criteria yet?”  “In the textbook, you always have to start a problem with a visual overview–a picture, a motion diagram,or a graph. Which of those do you think you could start with?”

About 1/3 of the groups solved for the starting position of the cart using the area under a velocity vs. time graph, 1/3 with an equation, and 1/3 solved using both. Even though every group solved the same problem, most groups were still pretty excited to see their predictions work out. I think one thing is that since the cart accelerates gradually (15 cm/s/s in our setup), it intuitively doesn’t look like they are going to hit at first. You are looking at it going, No Way, and then because the cart has picked up speed, it quickly closes the gap. I think that suspense and surprise helps students to be excited.

I wish I had gotten some pictures or videos, but crutching around class has made me less mindful of that.

3 thoughts on “First Challenge Lab: Buggy-Cart Collision

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    1. I guess I mean a challenge lab, but on a much more mini-scale. I think Greg Jacobs talks about these, quantitative demos maybe? I also think Direct Measurement videos serve this purpose. But in general I just imagine taking a world problem, turning it into a demo (e.g., A Fan Cart Accelerates across a track). Instead of having word problem where, “A car accelerates at ___, how long will it take to travel a distance of ___?” You say, “How will will it take this Fan cart to get across this track?” Guide through process of what they would want to know, measure it (distance with a meter, acceleration from motion detector (not on the track at least not whole, so they can’t see time). Then have to solve it like a regular problem… Then check answer against experiment. Challenge or practicum labs are great, but take a lot of time. It feels very different “extracting” information from a word problem vs. a physical scenario.

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