Effectively Extending Computational Training Using Informal Means at Larger Institutions

Dhruva K. Chakravorty, Marinus "Maikel" Pennings, Honggao Liu, Zengyu "Sheldon" Wei, Dylan M. Rodriguez, Levi T. Jordan, Donald "Rick" McMullen, Noushin Ghaffari, and Shaina D. Le

Volume 10, Issue 1 (January 2019), pp. 40–47


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  author={Dhruva K. Chakravorty and Marinus "Maikel" Pennings and Honggao Liu and Zengyu "Sheldon" Wei and Dylan M. Rodriguez and Levi T. Jordan and Donald "Rick" McMullen and Noushin Ghaffari and Shaina D. Le},
  title={Effectively Extending Computational Training Using Informal Means at Larger Institutions},
  journal={The Journal of Computational Science Education},
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Short courses offered by High Performance Computing (HPC) centers offer an avenue for aspiring Cyberinfrastructure (CI) professionals to learn much-needed skills in research computing. Such courses are a staple at universities and HPC sites around the country. These short courses offer an informal curricular model of short, intensive, and applied micro-courses that address generalizable competencies in computing as opposed to content expertise. The degree of knowledge sophistication is taught at the level of below a minor and the burden of application to domain content is on the learner. Since the Spring 2017 semester, Texas A&M University High Performance Research Computing (TAMU HPRC) has introduced a series of interventions in its short courses program that has led to a 300% growth in participation. Here, we present the strategies and best practices employed by TAMU HPRC in teaching short course modules. We present a longitudinal report that assesses the success of these strategies since the Spring semester of 2017. This data suggests that changes to student learning and a reimagination of the tiered instruction model widely adopted at institutions could be beneficial to student outcomes.