Best Practices of Student Engagement in Online Teaching of HPC and Big Data Research

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Gobbert_EduHPC2021.pdf (237.21 KB)

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https://hpcf-files.umbc.edu/research/papers/Gobbert_EduHPC2021.pdf

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http://hdl.handle.net/11603/23072

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UMBC Mathematics and Statistics Department
UMBC Faculty Collection
UMBC Information Systems Department

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https://orcid.org/0000-0003-1745-2292
 https://orcid.org/0000-0002-9933-1170

Date

2021

Type of Work

journal articles
preprints
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Program

Citation of Original Publication

Gobbert, Matthias; Wang, Jianwu; Best Practices of Student Engagement in Online Teaching of HPC and Big Data Research; High Performance Computing Facility, 2021; https://hpcf-files.umbc.edu/research/papers/Gobbert_EduHPC2021.pdf

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UMBC High Performance Computing Facility (HPCF)

Abstract

There is a critical nationwide shortage of IT professionals as well as of scientists and engineers with highperformance computing (HPC) and big data related advanced computing skills. Simultaneously, the technology is growing in complexity and sophistication, which has led to the use of multidisciplinary teams with members from a broad range of home domains everywhere in industry, government, and academia. Moreover, a lot of the vital team collaborations take will place virtually using a variety of software platforms now and in the future. We report here on experiences with preparing undergraduate and graduate students for these career opportunities in several contexts, from regular semester classes, an undergraduate summer research program, to an advanced graduate student CyberTraining program. All these programs are conducted fully online and leveraged concepts of flipped classrooms, recorded lectures, team-based and active learning, regular oral presentations, and more to ensure student engagement and lasting learning.