Context: I composed this reflection as an assignment required for the Laboratory Physics course I took at Agnes Scott College during the spring 2019 semester. This assignment gave me an opportunity to discuss the process of integrating my previous coding experience with a newly-developed ability: data fitting. Additionally, I was able to use this reflection to examine the nature of flexibility, especially in scientific and laboratory settings. I came to the conclusion that flexibility is a crucial thing to exercise and be mindful of in experimental scientific settings, thus allowing me to begin forming a mindset better suited to working in lab environments. Having reminded myself of the importance of flexibility, I am now better equipped to handle the frustrating experience of a science experiment not going as planned. I have included the reflection in full below.
Since my last reflection for this course, I have learned a lot about the process of laboratory physics. The concepts that come to mind first though are data fitting using Python, as well as the importance of flexibility when it comes to handling unexpected obstacles in lab while completing an experiment.
Data fitting using Python has presented a bit of a challenge, but I am looking forward to sticking with it, honing my skills, and becoming more confident in doing it, as I have learned throughout college that I internalize and really process academic material best when I am not daunted by it. I mentioned this aspect of my personal experience with learning in my last reflection, where I discussed my tendency to get “stuck” or “bogged down” in material and feel very intimidated by it if I do not feel as though I understand it completely. This is something I hope to work on in the future, as I realize it is normal to feel less adept with material you are not yet confident in, and that is a part of the learning process that I hope to embrace, rather than dread, in the future.
I have used Python before numerous times. My father is a network engineer and cloud developer, so he taught me to code at a young age, and I have built various websites, gone to a couple coding-based summer camps, and taken three coding classes since then- two of which have focused exclusively on Python, taught by Dr. Depree at Agnes Scott College. This past summer, I helped my younger sister code a video game project of hers in Python using a visual novel engine, and I also taught Python to children through my summer camp instructor job, using Hour of Code to help them develop their own video games. I was expecting the data fitting using Python to pose no difficulty whatsoever due to my experience with the language, but I quickly realized that while I may have Python experience, I do not have any data fitting experience, meaning that this course has provided me with a new skill set to embrace learning. I have never tried to integrate Python with scientific applications before, and becoming more confident in doing so over the course of this semester is something I anticipate being really satisfied with and proud of, as it will represent a synthesis of my personal coding experience and my academic scientific education. I also see the value in becoming adept at data fitting using Python, as it will give me a professional and more professional/appropriate way to fit data for future lab reports than what I had been doing in Modern Physics last semester, which was using Excel. Interacting with my data in a more involved way like this encourages me to really understand the data that I have collected, and how it fits with the scientific model/expected value in various specific ranges of the data or at specific points. I feel like it allows me to see the comparison between my collected data and the expected ideal in a more thorough way than simply taking a percent error between the slope of a plot and the expected value would, which in turn allows me to better understand my sources of uncertainty, or things I could have controlled or accounted for better in lab. Also, prior to this class I had no prior experience with using chi squared tests in a scientific capacity- we touched on them briefly in the statistics course I took last semester, but it’s gratifying to be able to apply that technique to data that I’ve taken, rather than data which was given to me in the context of an assigned statistics problem.
Between scientific use of Python, data fitting, and chi squared tests, I am beginning to see my knowledge from several separate past sources of my education converging on each other in a way that helps me develop a new, lab-oriented skill set which I look forward to applying in future courses at Agnes Scott! Additionally, while I do not currently plan on attending grad school, I do hope to continue my work with World of Speed automotive museum this upcoming summer, where I am slated to teach our coding summer camps again, and I hope that working with Python in this course all semester will help me refresh and dust off my coding skills and get re-familiar with the syntax so that I can be even more helpful to my coding students this summer than I was last summer.
The other primary lesson I feel that I have learned since my last reflection for this class is about how important it is to be flexible in lab. Science, as I am learning in this lab, does not always go the way you plan! This is okay. All of the most important scientific discoveries have come from a scientist witnessing something unexpected, so I think it’s important to embrace and appreciate that aspect of the discipline. Science is about studying the unknown, and the thing about the unknown is that we cannot always predict it. Additionally, lab equipment can be finicky, and experiments involving electricity can easily be thrown off by a variety of sources- an unusually dry of humid day, or the scientist wearing a particularly staticky sweater, for example. My lab partner and I experienced an experiment not going according to plan recently, when the 4 point probe we were using to study a superconductor began malfunctioning and broke, leading to us having to develop a new experiment on the fly. I was a little nervous at first, because doing academic projects without a clear-cut plan can be nerve-wracking, but then I remembered the importance of treating every change of plans like a new opportunity to grow and become more flexible as a person. So, with help from Dr. Ackerman, my lab partner and I developed a new plan, and it’s one that I feel confident in, even though we’ve crafted it ourselves, without a lab manual or provided instructions. I look forward to treating this experiment as an exercise in independence, and a new chance to build my confidence in my lab skills, which I know from past experience goes a long way towards furthering my learning of material. It’s okay if the lab doesn’t go perfectly, and chances are it probably won’t- science can be messy and finicky, but that’s okay, because it’s a part of the discipline I love so much.
Over the course of this semester, it’s a goal of mine to become far more comfortable with adapting to experiments not going as planned, as flexibility is an important skill in all aspects of life. Furthermore, a lot of my job next summer is going to be helping my summer camp students complete hands on projects- which I know from last summer’s experience ALSO have a tendency to not work out quite the way you had hoped. I look forward to the flexibility I plan to develop and cultivate in this class helping me be more successful at my job next summer.
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