Assessment of Digital Collaboration Skills

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dc.contributor.author Huerta, Esperanza
dc.contributor.author Franzoni Velázquez, Ana Lidia
dc.contributor.author Jensen, Scott
dc.date.accessioned 2023-12-26T18:35:49Z
dc.date.available 2023-12-26T18:35:49Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 0a275a97-dab9-4766-b7ae-745452e03177
dc.identifier.uri https://hdl.handle.net/10125/106386
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Advances in Teaching and Learning Technologies
dc.subject assessment
dc.subject chatgpt
dc.subject digital collaboration
dc.subject generative ai
dc.subject qualitative data coding
dc.title Assessment of Digital Collaboration Skills
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract This exploratory study proposes a methodology for assessing digital collaboration skills based on the students’ actual behavior. Students’ comments using a digital collaboration tool during a one-month long project were manually coded. This methodology is not context specific and can be used across different domains. This assessment contrasts with self-reported measures in which students rate themselves as already possessing collaboration skills. Finally, the study explores the use of generative AI to automatically code student’s comments to alleviate the labor-intensive process that coding requires and to enable scalability in coding data.
dcterms.extent 10 pages
prism.startingpage 84
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