A lifetime in Computational Science Education
Robert R Gotwals, Science, North Carolina School of Science and MathA lifetime in Computational Science Education
Robert R. Gotwals, Jr.
The North Carolina School of Science and Mathematics
Durham, NC
gotwals@ncssm.edu
In 1986, several organizations, including the supercomputer vendor ETA Systems (now defunct) and the National Science Foundation (NSF), posed this question: "what would happen if you put a 16-year-old in front of a $20M supercomputer?" The program "SuperQuest" was designed to answer that question. Teams of high school students attended an intensive summer workshop at the Cornell Theory Center, learning the technologies, techniques, and tools of high-performance computing (HPC) and computational science. The projects were then judged, and the winning school came home with a supercomputer donated by ETA Systems! The short answer? With not very much training, motivated students were able to do very high-level scientific work using a computational approach.
Arriving to teach analytical chemistry at the Montgomery Blair Magnet Program, outside of Washington DC, I was invited to serve as a "coach" for one of the Blair teams at SuperQuest. Knowing absolutely nothing about the field, with only a basic background in programming (FORTRAN), I was as much of a student at Cornell as the kids I was supposedly "coaching". The computational science "bug" bit hard, however, and my time at Blair ended relatively quickly with an invitation to join the scientific staff at the North Carolina Supercomputing Center in the Research Triangle Park, NC. Now closed, my job at NCSC was to help bring computational science to high schools and small colleges across the state.
Fast-forward to 2006. After 20 years working for a variety of computational science organizations, including NCSC, the Shodor Education Foundation, and others, all with funding support from the National Science Foundation, I was invited to join the faculty at the North Carolina School of Science and Mathematics, a state-supported residential school for gifted high school juniors and seniors. My assigned task was to help the school remain a cutting-edge high school by developing a series of courses in the computational sciences. Over the course of about eight years, we now have nine courses, including: Introduction to Computational Science, Computational Chemistry, Computational Biology/Bioinformatics, Computational Physics, Computational Medicinal Chemistry, Data Science for Scientists, Digital Humanities, and two research opportunities in the computational sciences. All these courses, except for one of the research courses, are full-semester, credit-bearing opportunities, most of them offered through the NCSSM Online program. It's an exceptionally robust program, with enthusiastic participation on the part of students, and one that is well-appreciated by parents.
Unfortunately, the integration of computational sciences into regular high school programs has not improved much in the 35 or so years that I have been in computational science education. Indeed, the challenges have increased with the subsequent rise in high-stakes testing (including AP exams), end-of-course testing, state standards testing. Teachers are increasingly under the gun to "teach to the test", which leaves no room for "enrichment" opportunities such as computational science. Sure, there are more organizations and resources, such as the Concord Consortium and the PhET tools, that are looking to provide support for classroom teachers, and these are all excellent resources. I recently finished a $1.25M NSF grant, looking at integrating computational thinking into high school biology and chemistry classrooms. Participating teachers in a variety of classrooms across the state of North Carolina were provided with grant-developed lesson plans and activities that used computational science to explore how students engaged in computational thinking. One of the comments made during the follow-up/feedback sessions was that "the materials are great, just take out the computing part, and they'll be perfect." What the teachers were telling us was that there was no "win" for them in using computing, because it would not really help their kids score well on high-stakes tests.
In addition to curricular issues, there are also issues with access. At NCSSM, we run a statewide computational quantum chemistry, which houses several research-grade computational chemistry tools, including Gaussian16 and MOPAC. Using the WebMO interface, this resource is provided free of charge to any student and pre-college teacher in the state of North Carolina. Resources such as this eliminate the need for software installs and, in our case, any barriers caused by expense to the schools. Companies such as Schrodinger, Inc. are currently rolling out a web-based version of their robust software programs (Maestro, Bioluminate, etc.) for students, but this resource comes with a "per seat" fee which is likely prohibitive for many institutions. Even at a place like NCSSM, a constituent institution of the University of North Carolina System, funding is challenging, and funding for software even more so.
Finally, if I have learned anything in 35+ years of computational science education, a substantial portion of that engaged in teacher professional development in the computational sciences, it's that "teachers teach the way they were taught". We are noticing that more of the younger teachers are open to integrating computation into the classrooms, but it has been a tough slog with older teachers. We have oftentimes had teachers tell us that, until they know every feature or button in a software package, they are scared to use it with students. This is an unrealistic goal – even experienced users of software such as Gaussian16, such as me, only know a fraction of the capabilities of that software. Unless and until teachers are willing to bring these tools into the classroom with the recognition that they too are students, the use of these tools will be hindered. My decision to leave teacher professional development and instead focus on the next generation of scientists (with the hope that some of them will become teachers, well-trained in scientific computing) was one made from frustration with the progress, or lack thereof, we were having with teachers. It was difficult to see, and still is, a mechanism by which computational tools would become as ubiquitous as learning how to use test tubes and beakers in a chemistry classroom.
Still, those of us in the computational science education field, including the relatively small number of us working at the pre-college level, continue to persevere. Software vendors are beginning to understand the financial realities of pre-college programs, and some are working to make their products more financially viable to schools. At the end of the day, unless and until the proprietors of high-stakes testing, such as and including the AP science exams, start including the computational sciences in the same manner as they include lab techniques such as titrations and measuring pH values, it's likely that programs like mine will stay in isolated locations. We've seen some progress at the undergraduate level, where organizations such as the American Chemical Society (ACS) have decreed that, for a chemistry degree to be "ACS approved", there must be evidence that the student has some basic understanding of the theories and practical uses of computational chemistry. We really need that happening with accrediting organizations, testing organizations, and school boards/administrators at the high school level. As more computationally trained educators arrive on the scene, there is hope that computational science in the high school science classroom will become as ubiquitous as the traditional lab spaces and activities now found in the science curricula.