A physics student's first encounter with the method of separation of variables for solving linear partial differential equations can be particularly mystifying, if the starting assumption – that the solution can be written as a product of functions, each of which depends on only one of the independent variables – is put forward without motivation or justification.  We propose to avoid this difficulty by first introducing the students to the idea of expanding a function as a linear combination of basis functions, something which they will need to learn at some point in their undergraduate career anyway.  Applying this idea to a partial differential equation immediately shows that any function can be written as a linear combination of functions in product form.  Substituting that form into the equation quickly leads to a natural way of choosing the underlying set of basis functions, one which decouples the equations and so makes the subsequent calculations as simple as possible.  To wrap up, the conventional method can then be presented as a short-cut way of implementing this more general approach.

Many university physics programs struggle with increasing or retaining freshmen students. At Valdosta State University, historically the retention rate in physics has been very low, ~33%.  In Fall 2017, our department started examining ways to increase our retention rate by using freshmen research opportunities.  That year, two freshmen female students were invited to participate in research.  Both of these students were retained to their sophomore year.  With the limited success that year, in Fall 2018 we invited 7 of the 15 incoming freshmen to participate.  The students participated in five projects throughout the year in astrophysics and plasma physics.  All seven students were retained to their sophomore year.  This presentation will describe the program in more detail, as well as the graduation rates for those students in the two cohorts. A discussion on how the program is being implemented post-COVID-19 will also be presented.

An advanced experimental physics class is common is most undergraduate curricula. It is usually taken by juniors or seniors and sometimes fill the role of a capstone course. The traditional course uses a number of experiments to explore advanced techniques, and the goal is typically a a paper in a form suitable for publication in a peer-reviewed journal. Rather than use the course as a vehicle to prepare students for academia, Last spring I taught a version designed to prepare students for using their physics training in a corporate lab setting. Students had to research a historically important experiment and develop a manual and working procedure. We even had open house and quality control exercises. The poster will outline the way the semester was used to model a process more like the world most of the students will face after graduation.

While introducing complex concepts in physics, we often rely on analogies, visual aids, and mathematical derivations. However, sometimes they may not provide enough intuition or generality. For instance, how can we convince our students or ourselves that the gas particles in a box always end up with a universal (i.e., Boltzmann) distribution regardless of their countless possible initial configurations? With the addition of computational pedagogy that complements traditional approaches, we can simulate a physical process of random energy exchanges among the gas particles and observe the simulated time-evolution of energy distribution, which settles into an exponential curve, as predicted by rigorous mathematical analysis. We will share a few such examples of Python simulations from statistical mechanics [1] and electrodynamics [2], which can enhance students' learning experiences in upper-level physics courses.

The goal of this work is to develop Comsol Multiphysics models for simple physical systems that include Heat transfer to be introduced as part of a Materials Science 300 level course/laboratory.

The goals of the work are:

1.     Develop materials science Comsol Multiphysics software models that match the Materials science class curriculum

2.     Investigate useful materials constants that are not fully entered in the Comsol materials database (such as specific ranges of Temperature, emissivity as a function of wavelength, etc) , and enter their physical properties as they relate to Heat transfer and thermal properties of materials

3.     Develop databases or analytic functions for the properties above and enter them in Comsol.

Comsol Multiphysics is a very useful tool for simulating physics systems and their interactions. Using the proper physical constants for the specifics of each project is critical to obtaining good data.