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Using data science for sustainable development in higher education

2024-02-05Journal article Restricted access
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dc.contributor.authorLeal Filho, Walter
dc.contributor.authorEustachio, João Henrique Paulino Pires
dc.contributor.authorNita (Danila), Andreea Corina
dc.contributor.authorDinis, Maria Alzira Pimenta
dc.contributor.authorSalvia, Amanda Lange
dc.contributor.authorCotton, Debby R. E.
dc.contributor.authorFrizzo, Kamila
dc.contributor.authorTrevisan, Laís Viera
dc.contributor.authorDibbern, Thais
dc.date.accessioned2024-02-06T14:48:10Z
dc.date.available2024-02-06T14:48:10Z
dc.date.issued2024-02-05
dc.descriptionhttps://v2.sherpa.ac.uk/id/publication/7577pt_PT
dc.description.abstractDespite the abundance of studies focused on how higher education institutions (HEIs) are implementing sustainable development (SD) in their educational programmes, there is a paucity of interdisciplinary studies exploring the role of technology, such as data science, in an SD context. Further research is thus needed to identify how SD is being deployed in higher education (HE), generating positive externalities for society and the environment. This study aims to address this research gap by exploring various ways in which data science may support university efforts towards SD. The methodology relied on a bibliometric analysis to understand and visualise the connections between data science and SD in HE, as well as reporting on selected case studies showing how data science may be deployed for creating SD impact in HE and in the community. The results from the bibliometric analysis unveil five research strands driving this field, and the case studies exemplify them. This study can be considered innovative since it follows previous research on artificial intelligence and SD. Moreover, the combination of bibliometric analysis and case studies provides an overview of trends, which may be useful to researchers and decision-makers who wish to explore the use of data science for SD in HEIs. Finally, the findings highlight how data science can be used in HEIs, combined with a framework developed to support further research into SD in HE.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAPAth: Leal Filho, W., Eustachio, J. H. P. P., Danila, A. C. N., Dinis, M. A. P., Salvia, A. L., Cotton, D. R. E., Frizzo, K., Trevisan, L. V., & Dibbern, T. (2024). Using data science for sustainable development in higher education [Research article]. Sustainable Development, 32(1), 15-28. https://doi.org/10.1002/sd.2638pt_PT
dc.identifier.doi10.1002/sd.2638pt_PT
dc.identifier.eissn1099-1719
dc.identifier.issn0968-0802
dc.identifier.urihttp://hdl.handle.net/10284/12661
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWileypt_PT
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/10.1002/sd.2638pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBibliometricspt_PT
dc.subjectCase studiespt_PT
dc.subjectData sciencept_PT
dc.subjectHigher Education Institutions (HEIs)pt_PT
dc.subjectSustainable Development (SD)pt_PT
dc.titleUsing data science for sustainable development in higher educationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage28pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage15pt_PT
oaire.citation.titleSustainable Developmentpt_PT
oaire.citation.volume32pt_PT
person.familyNameDinis
person.givenNameMaria Alzira Pimenta
person.identifier493603
person.identifier.ciencia-id4710-147D-FDAF
person.identifier.orcid0000-0002-2198-6740
person.identifier.ridF-3309-2011
person.identifier.scopus-author-id55539804000
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication1e85592a-e8e2-4aea-bd8e-1007c94388c0
relation.isAuthorOfPublication.latestForDiscovery1e85592a-e8e2-4aea-bd8e-1007c94388c0

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