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Watkins_TeachingPhilosophy.pdfTeaching Philosophy
Teaching Philosophy
Through my experience as a student and educator, I have seen the value of modeling-based activities and interactive curriculum in a science classroom. Model building is, in my view, exactly what it means to do science. When a basketball player is learning to play, they need to play some actual games to improve.
Many students go through the math and physics exercises, but they don't understand what they are preparing for. The answer is, in my view, that students are preparing to construct, analyze, and evaluate models of the physical world. From this point of view, skills such as critical thinking, mathematical reasoning, and experimental design are recognized as being requisite skills towards this ultimate goal. Building models is also fun!
Physics Education Research:
Physics Education Research:
Computation is more than just a powerful tool: computation is increasingly a part of what it means to do science. This is certainly the case for physics, but also for traditionally non-computational fields such as the life sciences. Consequently, there is a push to incorporate more computational modeling activities into introductory physics courses, even for non majors.
How do students perceive relevance towards computational modeling in introductory physics courses for life science majors?
PERC_Proceeding_Computational_Relevance_2023.pdfPublished in Physics Education Research Conference (proceedings).
How do physics non majors, particularly life science students, perceive relevance in activities designed to teach computational modeling in physics? I investigated this question with Nick Ivanov and mentors Katie Hinko and Kirtimaan Mohan in the context of introductory physics at MSU's Lyman Briggs College. Our results were published in the Physics Education Research Conference (PERC) 2023 proceedings, and designated as a "notable paper" by the Physics Education Research Leadership and Organizing Council (PERLOC).
An ecological systems representation of a student's environment, which we used to understand relevance. Connections between facets of a student's life are sources of relevance.
What we found was rather surprising: nonmajors already perceived a great deal of relevance towards computers and coding, and found the coding activities valuable beyond learning physics. Students often saw computers are useful for data analysis and visualization. One student remarked "I believe computers are really good tools for analyzing a large quantity of empirical data and information collected from experiments." Many of these students, we found, had required coursework for their majors involving data methods using Rstudio. We suspect that students were generally happy to have an opportunity to learn a skill that related to classes and potentially future careers. In this vein, a student we interviewed wrote that she would "totally would be I’d be lost [sic.] in the rest of my [computational] modeling classes" without the basics she learned in physics.
Our findings suggest design strategies for physics courses with computational modeling, as well as design strategies for more comprehensive studies on the topic of relevance towards computation.
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