Cultivating Independence: Summer Research in Computational Science Fosters Intellectual Curiosity and Builds Work Ethic

In 2006, Myra Halpin, then Dean of Science at North Carolina School of Science and Mathematics, hired Robert Gotwals to build a program in computational science here.

Gotwals took that mandate to heart, and in the 16 years since, he has developed the most robust high school computational science program in the country, offering nine courses both in-person and online.

One of Gotwals’ offerings, the Summer Research Experience in Computational Science, meets for a three-week intensive program as a part of Summer Research & Innovation Programs at NCSSM’s Durham campus. Students from the academic-year Research in Computational Science also participate in the three-week program, working independently on their academic year projects.

Computational science uses computers to create and analyze mathematical models to explore scientific questions. Because computational science can be applied to questions across disciplines, students can work toward answering questions in psychology, physics, biology, and more.  

“Computational research is basically taking computation skills – like a bit of computer science, a bit of data science – and applying them to problems in other fields,” says NCSSM rising senior Lydia Owens.

Owens is attempting to model COVID-19 outbreaks within North Carolina prisons, a topic she was inspired to tackle after interning at a law firm in Washington, D.C., where she helped work for early release of prisoners due to the pandemic.

“Computational science is really interdisciplinary by nature,” she said. “We’re looking at things like Alzheimer’s disease or decision-making in sports plays. I chose epidemiology because that was something I was interested in from personal experience.”

During SRIP, Gotwals offers a crash course for the Research Experience students on how to conduct research in computational science. “In three weeks, there’s a lot to cover,” he said.

“We learn about general scientific research, like how to review the literature; then we learn computational tools and work on a computational project together; finally, the students start developing their own research question.”

Gotwals steps the students through the tools they are most likely to need, like R programming language; Mathematica, a technical computing software; and STELLA, software used to model systems dynamics.

“I am using R,” said Owens. “I am building an agent-based model, which is an individual-based model in R. Basically, each incarcerated person is seen as an agent, and they’ll have a different contact network where I can model prison-level characteristics such as whether they live in a dormitory or single cell, how often they go outside, how often they are exposed to guards and other factors.”

Owens wants to create a model that can help lead to better policies and health care access for prisoners. “I definitely think this can be applied to other diseases,” she said.

“The ultimate goal is to be able to extrapolate this model because that’s the big issue with modeling jails: a lot of jails have very intricate, individual environments. Getting a model that can model very different jails, like large urban jails and small county jails is my goal.”

Over the course of the program, Gotwals says that students’ confidence grows tremendously, both personally and in their comfort with conducting independent computational research.

“In three weeks, students get a taste of the degree of independence, work ethic, and willingness to read that it takes to conduct computational research,” said Gotwals.

“I love watching them come in on the first day – I am older, I have a lot of gray hair, and they know that I am retired military. They are scared to death, have no confidence – and then they start to feel like they have a handle on this. By the end, some kids will say, ‘oh man, where has this been all my life?’ And others will say, ‘that was fun, I am glad I did this, and I might not be interested.’ Both of those are okay results. It’s fun to see that confidence increase.”

At the end of the day, Gotwals says this program is about cultivating independence and a love of the process.

“Nothing is graded in the traditional sense of school grading; you can’t grade research,” he said.

“How do you grade intellectual curiosity or work ethic? I want to see that success, but I also build in opportunities to fail. Students need to know how to deal with that. What will they do if their results are meaningless? No one can be good at research 100% of the time, so I want them to know how to manage that.”

Owens echoed that sentiment in her advice for NCSSM juniors considering whether to apply for Research in Computational Science.

“Even if you don’t have coding experience, or don’t think you’re a huge computer science person, computational science is still really worth it,” she said.

“As long as you are passionate about your subject, you can learn what you need to do. I originally didn’t have a lot of experience in research or coding in general, and so it was definitely a learning curve, but when you put in the time, things start to work, and it’s really gratifying.”

Read a Q&A with Lydia Owens, Research in Computational Science student

Read more stories about students’ experiences in SRIP 2022.

You can learn more about the academic year Research in Computational Science here

You can learn more about the Summer Research Experience in Computational Science here

See the 2022 Summer Research in Computational Science showcase