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Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS

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Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS

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dc.contributor.author Moltó, Germán es_ES
dc.contributor.author Naranjo-Delgado, Diana María es_ES
dc.contributor.author Segrelles Quilis, José Damián es_ES
dc.date.accessioned 2021-02-20T04:31:09Z
dc.date.available 2021-02-20T04:31:09Z
dc.date.issued 2020-12 es_ES
dc.identifier.uri http://hdl.handle.net/10251/161978
dc.description.abstract [EN] Cloud computing instruction requires hands-on experience with a myriad of distributed computing services from a public cloud provider. Tracking the progress of the students, especially for online courses, requires one to automatically gather evidence and produce learning analytics in order to further determine the behavior and performance of students. With this aim, this paper describes the experience from an online course in cloud computing with Amazon Web Services on the creation of an open-source data processing tool to systematically obtain learning analytics related to the hands-on activities carried out throughout the course. These data, combined with the data obtained from the learning management system, have allowed the better characterization of the behavior of students in the course. Insights from a population of more than 420 online students through three academic years have been assessed, the dataset has been released for increased reproducibility. The results corroborate that course length has an impact on online students dropout. In addition, a gender analysis pointed out that there are no statistically significant differences in the final marks between genders, but women show an increased degree of commitment with the activities planned in the course. es_ES
dc.description.sponsorship This research was funded by the Spanish "Ministerio de Economia, Industria y Competitividad through grant number TIN2016-79951-R (BigCLOE)", the "Vicerrectorado de Estudios, Calidad y Acreditacion" of the Universitat Politecnica de Valencia (UPV) to develop the PIME B29 and PIME/19-20/166, and by the Conselleria d'Innovacio, Universitat, Ciencia i Societat Digital for the project "CloudSTEM" with reference number AICO/2019/313. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Applied Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Learning analytics es_ES
dc.subject Cloud computing es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.title Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/app10249148 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV/PIME 2018-2019/B29/ES/Comunidades de Aprendizaje como servicios en la nube para el desarrollo y evaluación automática de Competencias Transversales y Objetivos Formativos específicos/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV/PIME 2019-2020/B-19-20%2F166/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2016-79951-R/ES/COMPUTACION BIG DATA Y DE ALTAS PRESTACIONES SOBRE MULTI-CLOUDS ELASTICOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AICO%2F2019%2F313/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Moltó, G.; Naranjo-Delgado, DM.; Segrelles Quilis, JD. (2020). Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS. Applied Sciences. 10(24):1-13. https://doi.org/10.3390/app10249148 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/app10249148 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 10 es_ES
dc.description.issue 24 es_ES
dc.identifier.eissn 2076-3417 es_ES
dc.relation.pasarela S\427733 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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