I am displeased with how our Physics Department has served me. Not in that it had bad intentions or treated me with disrespect, but it failed to teach me what it means to do physics. Specifically, I am unhappy with the Physics department’s Introductory Mechanics lab course. I know that I am not alone in this sentiment.
Swarthmore’s Physics department has recognized the flaws of the traditional “set up the model, and then see if it works” sort of lab course, in which students get hands-on experience with lab equipment but don’t really get much of anything else out of the time they put in. To avoid this ineffective use of time, Swarthmore decided to adopt a different model: our task was to hone our skills in the process of conducting science, developing and testing theories about the natural world around us.
I love this idea. I just wish the lab had followed through with it.
The lab ended up being an arduous trek in data analysis and our repetitively pondering ways in which we might have biased results. For example, in the first four weeks, we repeatedly watched a pendulum swing to figure out what factors determine how long it takes to sway back and forth. The point of doing this for four weeks was to continually improve our experimental design. Still, spending twelve hours on the same problem (with fixed resources) made it difficult to stay interested in the swaying mass.
We spent a fair amount of time identifying and discussing sources of bias in our experimentation process. Although I think that my lab instructor did a good job of leading discussions about how to identify bias and mitigate its effects, those discussions had little tangible impact on how we actually went about our investigations. Often, my lab group’s discussion on bias just led us to say “we’re not going to assume the model we’re testing is true.” The discussion starts to get old when you say the same things every week for a semester. Our efforts to identify bias were little more than reminders to not fabricate data.
I think I learned most from the data analysis portion of our experiments. It was my first time coding by using Python in a meaningful way, and the data comparison tools have applications outside analyzing the timing of a pendulum. While I am glad to say that I gained some skills from the course, the fact remains that I could have gained the same thing from a one-day Python workshop.
After watching the pendulum for a month, there was a welcome change of pace: we got an upgrade to tossing balls and watching them fall. To assist us, we got to use some fancy sensors that told us how far away the ball was. Our task then was to make a model to describe how objects fall.
In an idealistic sense, I think that this was a good task: trying things and taking data, revealing relationships between variables, and refining a model until we had something to describe how quickly balls fall in the air is a challenging task (keeping in mind gravitational, drag, and buoyant forces).
However, what actually ended up happening was lots of measuring and our feeling stumped by the data. I think that part of what happened was that we were too concentrated on interpreting the results using the context of what we had been learning in class. We weren’t in the right mindset to spontaneously theorize concepts that took people a good deal of time to discover.
Designing a model to describe what actually happens in our world is largely a process of proposing something, then modifying it until it seems to describe things accurately. Often, the propositions that become our modern understanding of the world originally seem outlandish. While I as a student ultimately failed to recognize the creativity needed to formulate an outlandish model, I think that the lab course could have done a better job at outlining what a model can look like. If we had seen what sorts of things constitute a model (instead of just theorizing about bias), I think we could have done a better job at creating an explanation for our data.
Ideally, the course would have taught us what’s involved with making a model. For example, in the Electricity, Magnetism, and Waves lab course, we were tasked with creating a model that explained what was going on in a certain demonstration. In this demonstration, a plastic rod was rubbed with a rag (to make static electricity), then touched to an electrical measuring device. Upon making contact with the rod, the device’s needle moved to indicate the presence of electricity. Our task was to develop a model that predicted the behavior of the needle under these circumstances. An unconventional yet successful model for this demonstration was developed by a friend of mine. In their model, there’s a certain material that makes metal “happy,” and in doing so, makes the metal needle of the measuring device want to “dance.” While this model isn’t supported by any modern physics, it explains what we were watching happen the same way that more established theories do. It’s wonderfully abstract, and I think that if the Physics 007 lab had presented this sort of model as an example for us, I would have been better equipped to propose theories about what’s going on in our world. In the process of developing a model, any proposition is a step toward discovering what is really happening around us. Even if the proposition turns out to be false, then we learn what went wrong and are closer to identifying the situation. Thus far, my scientific education has consisted of me learning science other people have discovered and experiments that supported their theories. I was missing the key creative component that the lab was trying to build on, and I think that this was a seriously missed opportunity.
I had mixed feelings about writing this opinion piece. My primary qualm is that I am giving criticism without really providing suggestions for how to improve the lab course. At the same time, though, I think that the voices of myself and my classmates who dreaded this lab need to be heard for the sake of future Physics 007 students.
With that being said, anybody planning to take the Physics 007 lab can hopefully learn from my experience and get more out of the class by approaching it with a creative mindset. The process of designing a scientific model is an art, not a formula.
-Spencer Martin, ʼ24 (Physics/Math Major)