## Member Spotlight Archive

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Deepshikha Shukla
` - Jan 10, 2019
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How/what inspired you to get into teaching computation?

When I started teaching I used simulations that were created by others. At the time I thought they were very good and helpful. However, once I was substituting for a professor who was teaching graduate electrodynamics to a class of about six students. During one of these sessions, we were discussing some problems where visualization was key and I was not able to think of a way to describe it in a more accessible way. Interestingly, one of the students had his laptop in front of him and I knew that the class was leaning Computational Physics as well. So, I suggested that we quickly code the solution in Mathematica and the whole class was able to feel the excitement of having a solution that they could visualize and play around to understand the effect of each of the variables. This was when I decided that as far as I could I would have computation as an integral part of my teaching.

Why did you get involved with PICUP?

I teach at a very small liberal arts college and isolation is real. PICUP provided me with a community and resources that I could rely on.

What benefit has your involvement with PICUP had to you, your teaching, and/or your students?

One of the direct benefits of PICUP are the exercise sets that can be used as is or modified to suit the class/course. The exercise sets, the professional development workshops and the support that PIPUP provides has been very beneficial to me. Specifically, the ability to share ideas and discuss with other faculty that are teaching (or have taught) the same course as you are; to get ideas about what might work (or not work) in a classroom; to understand how to assess student learning etc. have been a boon.

Tell us a bit about how you use computation in (or outside of) your classroom.

I have used computation to teach introductory Physics labs where students work with a minimally working code to model/predict the outcome of an experiment before actually performing an experiment. This past semester I also taught a sophomore/junior level Computational Physics course where the students actually envisioned and coded simple video games as their final projects.

Outside of the classroom, I use computation in research. I sometimes work with my seven year old son coding various things that might be of interest to him. Lately I have been thinking of organizing "An Hour of Code" activities for middle school students.

What is your favorite thing about teaching computation?

The ability to show students that realistic situations can be modeled using computation. Also for them to realize the limitations of computation. The algorithmic way to work out a solution, a powerful idea that they will use their entire life!

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Nick Nelson
` - Nov 2, 2018
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How/what inspired you to get into teaching computation?

I have always been fascinated by computers. In high school I took every programming class my school offered by the end of my sophomore year, so my junior and senior years I took more programming classes as independent study. In college I had the privileged to work with Dr. David Neilsen on numerical simulations of binary neutron star collisions, and from then on I was hooked. Computational astrophysics was for me. Since then I have studied stellar interiors and modeled shock-driven turbulent mixing using some the largest supercomputers on the planet.

Why did you get involved with PICUP?

I have long felt that computational techniques have been under-taught in to physics majors. It's common to have experimental lab courses that go along with many physics courses, however computational techniques are often taught in a haphazard way, or maybe all crammed into one "Computational Physics" course. In the same way that we teach experimental skills throughout the undergraduate physics curriculum, I feel the same sort of broad integration of computational skills across the curriculum will be far more useful to our students. On top of that, programming is consistently rated as one of the most in-demand skills by recent physics graduates.

What benefit has your involvement with PICUP had to you, your teaching, and/or your students?

PICUP's immediate benefit to me and my students has been in the form of easy to use exercise sets which I can quickly adapt to use in my courses. On several occasions I have been able to take an exercise set off the website, fiddle with it for a few minutes, and use it in class. More broadly and maybe more importantly, PICUP provides a community of like-minded physicists who are all seeking to improve their teaching of physics with computation. That community support system is invaluable.

Tell us a bit about how you use computation in (or outside of) your classroom.

I've used computation in a lot of ways, but let me highlight a couple. In the classroom, I teach one of those Computational Physics courses. I also integrate computational methods into my lower-division intro class labs and my upper-division classical mechanics course where my students get to solve a lot of nonlinear differential equation numerically.

Outside of the classroom, I once spent the better part of a vacation helping some family design a zipline by modeling the stresses we might expect to have one it. This entailed myself, my brother, and a couple uncles sitting around for hours with laptops trying various ways to model a person moving down a zipline. Last summer I actually got to ride the zipline I helped model and it was a blast.

What is your favorite thing about teaching computation?

Being able to move beyond the typical simplifications that physicists use in order to make problems solve-able. There's something very satisfying to adding air resistance and friction and rotation and all the messy details of reality to a problem, and then throwing it in a computer and getting an answer that matches actual data.

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Walter Freeman
` - Oct 8, 2018
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* What inspired me to get into teaching computation?

As a graduate student, I was given the TA assignment for the University of Arizona's upper division computational physics course. This was great fun for me, since as a student I have often written my own simulations to better understand physical systems that the class was studying analytically. After a few years of this, a hiring freeze forced the department to have a

graduate student teach a course; they asked me to teach the lower-division computational physics course. When I asked what curriculum they wanted, they said "We thought you'd figure that out!" So I wrote my own computational physics course, and was fortunate to have a crop of absolutely amazing and inspiring students who achieved far more in a semester than I thought possible.

* Why did I get involved with PICUP?

I went to a PICUP mini-workshop at an AAPT conference, and was very impressed by the flexibility and lack of prescriptivism in the group's approach to education research and reform; rather than saying "Here is a canned way to do things that we want you to adopt", PICUP exists to support instructors and provide a community and a repository of experience that anyone can make use of. It's not a group about selling this or that tool; it's a community of people who've realized that there is real physical wisdom in the results of numerical calculations and that students can further their physical understanding

by studying computer simulations.

* What benefit has my involvement with PICUP had?

I've learned a great many tools and teaching practices that I've made use of in one way or another in the classroom, but the most fulfilling aspect of my involvement in PICUP is the community. The PICUP core members are great folks, and I've had a number of extremely enlightening conversations with them about teaching physics.

* My favorite thing about teaching computation

Computational physics teaching is sometimes sold as necessary for students' professional development -- "hey, the workplace expects them to know how to code!" But it's far more than that; studying physics through a computational lens provides new and deep insights that are not readily accessible to analytical mathematics. Computation allows students to learn the standard physics curriculum in a deeper way. Midway through the semester of my computational physics course, when the students simulate Keplerian orbits, there's a revelation of power that each of them experiences -- the first time they put GMm/r^2=ma into a computer and realize that they have the power to study any possible motion of (classically) gravitating objects, just like that, right in front of them, and in doing so gain a deeper understanding of Newtonian gravitation than they could with pen and paper alone. But computational physics can go beyond that: it also offers them the ability to let them study things that would otherwise be inaccessible (classical perturbation theory! van der Waals equation of state! phase transitions! nonlinear acoustics!), and in doing so explore far more of the richness of physics than they otherwise would.

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Hunter Close
` - Jun 1, 2018
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I've been paying attention for a few years to the information about careers for physics students that's been published by the Society of Physics Students and the AAPT and APS. I gradually realized that computer programming was a very important skill for physics students to develop. It was a gap in my own background, so I knew I would have to learn programming in order to help my students. One big reason that I got involved with PICUP was just so that I could get support for learning computation, let alone learning to teach with computation. As I saw more and more of VPython in presentations at AAPT, I understood that there was a great opportunity to create situations where students were learning physics and programming together. So, I became a computational convert.

Being involved with PICUP is beneficial to me because it gave me an inside look into colleagues' diverse backgrounds, ideas, and levels of confidence. I was able to ask some really basic questions. I was able to place myself in a landscape of possibilities for my own developing approach to teaching physics with computation. And I met people with common interests.

In Summer 2016, a student and I started developing a block-based editor for GlowScript VPython called GlowScript Blocks, in collaboration with Trinket. In Fall 2017, we deployed this product, which is currently in beta-testing, for use in introductory mechanics. Our goal has been to expose all introductory mechanics students at Texas State to some computational concepts, methods, and applications in an enjoyable, low-stakes way. In our program's model, exposure and enjoyment in the intro level labs lead into formal, 2nd year, laboratory-based instruction on the use of python for physical modeling. Both of these levels of program reform began in Fall 2017. Students in the 2nd year "Python Lab" also started their course using GlowScript Blocks. The blocks-based activities have students adding or editing commands in an existing, working GlowScript Blocks program to change its output. The output of one of these editable programs does not quite match the output of another, given "model" program, for which the blocks and underlying code are hidden. Students figure out what needs to be changed in their program and construct the commands. The blocks have proven to eliminate the syntax and formatting barrier that many novice programmers face; with the barrier removed, students focus more on the structure and dynamics of the program.

My favorite kind of experience from teaching physics with computation has been when students catch on to the opportunities that are available with computation, assign themselves their own creative tasks, and then they come show me what they've made. I feel excited to find out what will happen when our entire community of physics majors has had computation as a proper part of their education and the students can more effectively interact with each other in this creative space.

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Josh Samani
` - May 7, 2018
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When I began teaching physics to undergraduates three years ago, it quickly became painfully clear that my department's curriculum lacked a sufficient integration of computational curriculum into our courses to adequately prepare our undergraduates for jobs in both academia and industry.

Computation has become an inescapable part of essentially every working physicist's workflow. Even when I was a physics graduate student studying high-energy theoretical physics, a subject that doesn't typically lean heavily on numerical methods, I relied on Mathematica to perform my symbolic computational heavy lifting. In other fields and in many STEM industry jobs, computation is even more prominent in day-to-day operations. For this reason alone, it's worthwhile to make sure that our physics undergraduates obtain training in computation.

But when I started teaching and began to think systematically about cognitive learning outcomes for my students, it became clear that computational instruction is useful for more than just career preparation. Solving physics problems by writing computer programs is an inherently metacognitive activity. When you make a programming error, an error message immediately alerts you to evaluate what you've produced. When you make a physics error in a simulation, you may find behaviors that you know don't make intuitive sense, and you are forced to re-evaluate the model you've constructed. There are so many other ways that computation helps students build powerful cognitive skills.

Being a part of PICUP has helped me co-design and teach both a project-based computational physics course and a computational honors seminar for physics majors -- it is an incredible support network. The PICUP summer workshop was instrumental in helping me sharpen my vision for how I wanted to approach computational curriculum design, and interacting with PICUPers at AAPT meetings has enriched my view of what's possible in computational curriculum. The PICUP online community on slack also keeps me connected to the broader community of educators with similar goals, and it is a wonderful resource for practical advice on implementation of pedagogies.

I look forward to watching PICUP continue to grow and help physics instructors everywhere discover the joys of using computation in enriching the educational experiences of students. Computation has helped physics come alive for my students, and it has made the teaching of physics even more fun and engaging than I already felt it was.

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Michelle Kuchera
` - Feb 1, 2018
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Davidson College

Davidson, NC

As a computational scientist, I have found that computation can inform and assist in the progression of science in research and industry. It is no different in the classroom.

Computation enables students to solve problems that are impossible or intractable to solve by hand. This provides students with tools to calculate or visualize more realistic physics phenomena.

I knew that I would implement computation in my undergraduate courses from the start of my career as a professor. When I heard from fellow faculty about PICUP, I knew immediately that I would be a part of it. In fact, I signed up for the first workshop before I even started my faculty position! PICUP has been invaluable to me as a young faculty member interested in incorporating computation into my courses. The online exercise set bank is a great starting point for creating student activities. If it wasn't for the PICUP summer workshop and online resources, I would not have been able to incorporate computation in my lab section during my first semester at Davidson College.

I implement computation as interactive python activities using Jupyter notebooks and Trinkets in the laboratory or classroom for introductory-level classes. These activities are intended to enhance understanding of a topic; therefore, working code is supplied for them to edit in an environment where I am able to readily assist them. In upper level courses, I intend to expect an understanding of numerical methods so that they can be used to solve more realistic or difficult problems than we deal with analytically. These computational skills are developed in my Computational Physics course, which is often taken by physics majors in the Sophomore year.

My hope is that computation becomes an integrated tool for learning in the undergraduate curriculum. It is rewarding to see students in the introductory level courses get excited about the coding activities, and thus actively engage with the physics material. After physics majors complete Computational Physics, it is rewarding to hear that they are still using code from that course in other classes, as well as using python to solve problems in other classes or in their everyday life. Teaching students to code in the physics curriculum provides the students with a problem-solving skillset that they can use for the rest of their lives. I am incredibly happy that PICUP exists as a way to support faculty that have these same academic interests, and I look forward to being a part of the PICUP community for a long time.