Team-Based Online Multidisciplinary Education on Big Data + High-Performance Computing + Atmospheric Sciences

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dc.contributor.authorWang, Jianwu
dc.contributor.authorGobbert, Matthias K.
dc.contributor.authorZhang, Zhibo
dc.contributor.authorGangopadhyay, Aryya
dc.date.accessioned2021-03-31T17:34:23Z
dc.date.available2021-03-31T17:34:23Z
dc.date.issued2021-03-10
dc.descriptionFECS'20 - The 16th Int'l Conf on Frontiers in Education: Computer Science and Computer Engineering | Jul 27-30, 2020
dc.descriptionFECS'20, FCS'20, SERP'20, and EEE'20
dc.description.abstractGiven the context of many institutions moving to online instruction due to the COVID-19 pandemic in 2020, we share our experiences of an online team-based multidisciplinary education program on big data + high performance computing (HPC) + atmospheric sciences (cybertraining.umbc.edu). This program focuses on how to apply big data and high-performance computing techniques to atmospheric sciences. The program uses both an instructional phase with lectures and team-based homework in all three areas and a multi-disciplinary research experience culminating in a technical report and oral presentation. The paper discusses how our online education program can achieve the same learning objectives as face-to-face instruction via pedagogy and communication methods including flipped classroom, online synchronous meetings and online asynchronous discussion forum.en_US
dc.description.sponsorshipThis work is supported in part by the U.S. National Science Foundation under the CyberTraining (OAC–1730250) and MRI (OAC–1726023) programs. The hardware used in the computational studies is part of the UMBC High Performance Computing Facility (HPCF).en_US
dc.description.urihttps://link.springer.com/chapter/10.1007/978-3-030-70873-3_4en_US
dc.format.extent13 pagesen_US
dc.genrejournal articles
dc.genreconference papers and proceedings
dc.genrepreprints
dc.identifierdoi:10.13016/m2vwsp-kjug
dc.identifier.citationWang, J., Gobbert, M.K., Zhang, Z., Gangopadhyay, A. (2021). Team-Based Online Multidisciplinary Education on Big Data + High-Performance Computing + Atmospheric Sciences. In: Arabnia, H.R., Deligiannidis, L., Tinetti, F.G., Tran, QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70873-3_4en_US
dc.identifier.urihttp://hdl.handle.net/11603/21268
dc.identifier.urihttps://doi.org/10.1007/978-3-030-70873-3_4
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.relation.ispartofUMBC Physics Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectUMBC High Performance Computing Facility (HPCF)en_US
dc.subjectUMBC Big Data Analytics Lab
dc.titleTeam-Based Online Multidisciplinary Education on Big Data + High-Performance Computing + Atmospheric Sciencesen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-9933-1170
dcterms.creatorhttps://orcid.org/0000-0003-1745-2292

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