# Education

I am extensively involved in curriculum development projects here at Oregon State. My two primary emphases are in thermal physics and computational physics, which reflects techniques used in my traditional research.

For an overview of my work in curriculum development, you can check out the slides of a seminar I gave at Purdue on Friday the 13th of September 2013. Or you could see the slides from the colloquium I gave at Oregon State in the Fall of 2013.

## Thermal Physics

I have been working to revise and extend the Energy and Entropy course, which is a middle-division course for physics majors, which introduces our students to thermal physics. This work is part of our Paradigms in Physics program, and is followed by a senior-year capstone course in thermal physics.

My philosophy of course development has been to focus on helping students to connect the mathematics of thermodynamics with experimental measurements. To this end, I have developed a number of activities, which are documented on the Paradigms wiki. I have also been working to develop and improve a one-week mathematical interlude, which prepares students for some of the new concepts that occur in thermodynamics, such as total differentials and partial derivative rules.

### Thermal Physics Resources

• A PERC paper giving a broad perspective on activities I developed for the Energy and Entropy.
• A PERC paper giving an analysis of expert use of mathematical approaches in analyzing an unfamiliar problem in thermodynamics.
• The Paradigms wiki has materials covering both the Energy and Entropy paradigm and the week-long Mathematical Interlude.
• My rubber band paper describes an experiment I designed for the Energy and Entropy course.
• My name-the-experiment paper describes a sequence of activities in which students are asked to sketch and describe the experiment needed to measure a given partial derivative. These activities are part of the Energy and Entropy course.
• A PERC paper describing the "Partial Derivative Machine," a mechanical analogue for thermodynamics I have developed to help teach students partial derivatives in the Mathematical Interlude (prior to Energy and Entropy).

## Computational Physics

Early in my career at OSU I redesigned the Physics 265 course to use Python as its programming language with the Visual Python package, and placed a strong emphasis on physics rather than purely numerical methods.

I am currently developing a new upper-division computational physics lab covering the same physics as the junior-year Paradigms. While the course is structured around physics content, I aim for students to become capable programmers, and to be able to use Python effectively in their senior research projects. In this course, students use the excellent matplotlib and numpy packages, which I also use in my own research. It is a goal of this course to effectively teach programming to all our Physics majors, not just those with an interest in coding. After all, all physicists use programming to a greater or lesser degree in their research.

This 1-credit lab course is structured with students working in pairs using the pair programming approach, in which one student is the driver (typing at the keyboard) while the other is the navigator (watching for bugs, giving advice, and planning ahead). I avoid giving the students example programs, which has helped in enabling them to learn to write programs from scratch. However, I do encourage them to search on the web for help in solving problems, since my goal is for students to use computers like real'' physicists.

### Computational Physics Resources

• The text for the Physics 265 course, Introduction to Computational Physics.
• The slides of a talk I gave at the 2013 AAPT summer meeting give a brief introduction to the computational lab sequence I am developing.
• The slides of a talk I gave at the 2014 AAPT summer meeting, which discuss how computational physics can help students to learn integration techniques in electrostatics.
• The slides of a talk I gave at the 2015 Fronteirs in Education conference (FIE) on my computational lab course.