My Teaching Statement

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My desire to teach began back in Brazil, my home country. There, the narrative that education leads to increased social mobility pervades. In 1998, Brazil introduced a new system of educational opportunity through the implementation of a federally-run university entrance exam. The ideal of meritocracy pressures Brazilian students to sharpen test-taking skills to compete for public resources and spots in top national colleges. In high school, I participated in scientific Olympiads to strengthen my abilities in high-stakes testing environments. While my dedication to Olympiads grew, however, I lost interest in my actual physics and mathematics courses. I became frustrated at my teachers’ invariably test-oriented methods in which performance on tests exclusively measured success. This experience influenced me to pursue pedagogy in college and ultimately become a student- and care-oriented STEM teacher.

While a Physics PhD student at Columbia University, I had the opportunity to elaborate new teaching practices towards an inclusive, student-centered environment. For the first two years, I was assigned one section of an introductory laboratory course. These courses are either geared towards pre-med students or engineering students. Both courses are graduation requirements for those students, although many do not wish to pursue a career in Physics. In my first semester, I realized I was operating on a lot of assumptions and generalizations during the class meetings with my students. In order to better attend the needs of the students in my section, I implemented a first-day survey. I found it helpful to understand the background of my students, their concerns, and anything else I should know (some examples include hardships the students are facing, accommodations they have). The survey guided my teaching throughout the whole semester and my interactions with the students.

In these Physics laboratory courses at Columbia University, some of goals are “How to use software and programming languages (e.g. Mathematica, Python but not Excel) to perform data analysis” and “How to write up lab reports according to the standard of an internationally recognized scientific journal.” The course is designed to instruct students to learn about scientific publications and how to disseminate their results through accurate, relevant, and accessible data visualization. More specifically, we ask students to use Python or MATLAB for their data visualization and analysis. These two programming languages are widely used in the scientific field; they, however, have a steeper learning curve than Microsoft Excel or Google Sheets. In the Fall of 2023, I brought a pertinent question into my classroom: Should OpenAI’s ChatGPT be part of the curriculum? Generative Artificial Intelligence (AI) has become a ubiquitous topic since the launch of ChatGPT in November 2022. ChatGPT can react to users’ prompts and consistently reply with coherent, plausible-sounding answers.

Students in these laboratory courses write weekly six-page laboratory reports that emulate peer-review scientific publications. The writing process is time consuming, but dissemination is paramount in science. For one of their assignments, instead of writing every section, I asked students to request an introduction and a conclusion from OpenAI’s ChatGPT. Since they had “less” writing to do, I asked them to add a reflection on the experience. Here are a few comments that students wrote: “While ChatGPT can serve as a useful tool, over-reliance on it might hinder the development of these critical skills. Writing is about developing the ability to think critically and present ideas in a coherent, persuasive manner. Losing the opportunity to practice these skills could be detrimental to students’ overall academic growth and their preparedness for future scientific papers or projects” and “Having ChatGPT write these sections would hinder our understanding of the experiments and we would lose out on opportunities to develop skills related to narrative flow. Overall, ChatGPT was a useful reference for summarizations, but needs more in-depth prompt engineering to produce potentially satisfactory results.”

This “experiment” came about from the fact that literacy around technology is crucial as we navigate a world that is more connected to technological advancements. The same way that it is crucial to learn to identify dis/misinformation on Google or social media, it might be a mistake not to cover literacy in AI within the classroom. By including ChatGPT and other Generative AI into our curriculum, we can better equip our students to critically think and identify the many flaws/unethical behavior of Artificial Intelligence.

Still on the topic of programming and data analysis, in the Spring of 2024 I assigned a first-day survey to my students. Through their answers, I learned that many felt novice and not confident with Python and MATLAB. I then prepared a 30-minute, two-fold activity for our second meeting. The first part of the activity was done on paper. I gave each student a data plot which lacked many essential aspects, such as labels, units, and title. Each student was tasked to first work alone for two minutes and identify things they would change in the plot. After that, they paired with a peer and each shared their thoughts for one minute. Finally, each group had to report back one thing they would improve in the plots. Then we moved onto the second part of the activity, where I used a big monitor to display that same plot, this time on a Python notebook. In this notebook, we went through the many improvements they had suggested and we coded it together. I was able to introduce them to different libraries and new functions to help in their data visualization and analysis. I think this activity was extremely successful, evidenced by their feedback at the end of that meeting. Here are a few examples of what they wrote: “I thought the demonstration with the Python and the graphs was pretty useful;” “I learned more tools to create a better graph using Python (like adding labels);” and “I learned new skills in python.”

These comments from the previous paragraph were collected at the end of our second laboratory meeting. I have introduced entry and exit tickets for that semester. The entry tickets are anonymous, so students are encouraged to fill it out as honestly as possible. There, I ask them to report back if they have prepared for the laboratory meeting, how much time they spent on their submitted report, and if they reviewed my feedback for the graded report. The entry tickets have been a quick, easy way for me to gauge how students are feeling in my course. For example, when a lot of students replied that they did not read the manual or attended the preparatory lecture for the experiment, I can give a longer lecture with additional details before the students begin their experiment. This also establishes a routine for the students and instructor. Exit tickets (which are not anonymous) serve as a reflection space for students at the end of a laboratory meeting: they needed to answer the questions “What is one thing you learned today?” and “What is one thing you still struggle with from today?”. This becomes part of their participation grade, so they are motivated to thoughtfully answer them.

These are a few glimpses into my pedagogical philosophy. I hope to continue my exploration and growth as an instructor with the assistance of peers and students. I am happy to further discuss projects and experiments I would like to implement in my future classrooms.