A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing

[EN] Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benefit from high-level tools to track the progres...

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Detalles Bibliográficos
Autores: Naranjo, Diana M., Prieto, José Ramón, Moltó, Germán|||0000-0002-8049-253X, Calatrava Arroyo, Amanda|||0000-0002-9018-9171
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/140209
Acceso en línea:https://riunet.upv.es/handle/10251/140209
Access Level:acceso abierto
Palabra clave:Cloud computing
Learning analytics
Learning dashboards
Visual learning analytics
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
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repository_id_str
spelling A Visual Dashboard to Track Learning Analytics for Educational Cloud ComputingNaranjo, Diana M.Prieto, José RamónMoltó, Germán|||0000-0002-8049-253XCalatrava Arroyo, Amanda|||0000-0002-9018-9171Cloud computingLearning analyticsLearning dashboardsVisual learning analyticsCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALLENGUAJES Y SISTEMAS INFORMATICOS[EN] Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benefit from high-level tools to track the progress of students during their learning paths on the Cloud, and this information can be disclosed via educational dashboards for students to understand their progress through the practical activities. To this aim, this paper introduces CloudTrail-Tracker, an open-source platform to obtain enhanced usage analytics from a shared AWS account. The tool provides the instructor with a visual dashboard that depicts the aggregated usage of resources by all the students during a certain time frame and the specific use of AWS for a specific student. To facilitate self-regulation of students, the dashboard also depicts the percentage of progress for each lab session and the pending actions by the student. The dashboard has been integrated in four Cloud subjects that use different learning methodologies (from face-to-face to online learning) and the students positively highlight the usefulness of the tool for Cloud instruction in AWS. This automated procurement of evidences of student activity on the Cloud results in close to real-time learning analytics useful both for semi-automated assessment and student self-awareness of their own training progress.This research was funded by the Spanish Ministerio de Economia, Industria y Competitividad, grant number TIN2016-79951-R (BigCLOE) and by the Vicerrectorado de Estudios, Calidad y Acreditacion of the Universitat Politecnica de Valencia (UPV) to develop the PIME B29.MDPI AGDepartamento de Sistemas Informáticos y ComputaciónEscuela Técnica Superior de Ingeniería InformáticaInstituto de Instrumentación para Imagen MolecularUniversitat Politècnica de ValènciaMinisterio de Economía y CompetitividadRepositorio Institucional de la Universitat Politècnica de València Riunet20192019-07-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/140209reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TIN2016-79951-R COMPUTACION BIG DATA Y DE ALTAS PRESTACIONES SOBRE MULTI-CLOUDS ELASTICOSUniversitat Politècnica de València https://doi.org/10.13039/501100004233open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1402092026-06-13T07:49:27Z
dc.title.none.fl_str_mv A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
title A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
spellingShingle A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
Naranjo, Diana M.
Cloud computing
Learning analytics
Learning dashboards
Visual learning analytics
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
title_short A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
title_full A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
title_fullStr A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
title_full_unstemmed A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
title_sort A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing
dc.creator.none.fl_str_mv Naranjo, Diana M.
Prieto, José Ramón
Moltó, Germán|||0000-0002-8049-253X
Calatrava Arroyo, Amanda|||0000-0002-9018-9171
author Naranjo, Diana M.
author_facet Naranjo, Diana M.
Prieto, José Ramón
Moltó, Germán|||0000-0002-8049-253X
Calatrava Arroyo, Amanda|||0000-0002-9018-9171
author_role author
author2 Prieto, José Ramón
Moltó, Germán|||0000-0002-8049-253X
Calatrava Arroyo, Amanda|||0000-0002-9018-9171
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Sistemas Informáticos y Computación
Escuela Técnica Superior de Ingeniería Informática
Instituto de Instrumentación para Imagen Molecular
Universitat Politècnica de València
Ministerio de Economía y Competitividad
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Cloud computing
Learning analytics
Learning dashboards
Visual learning analytics
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
topic Cloud computing
Learning analytics
Learning dashboards
Visual learning analytics
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
description [EN] Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benefit from high-level tools to track the progress of students during their learning paths on the Cloud, and this information can be disclosed via educational dashboards for students to understand their progress through the practical activities. To this aim, this paper introduces CloudTrail-Tracker, an open-source platform to obtain enhanced usage analytics from a shared AWS account. The tool provides the instructor with a visual dashboard that depicts the aggregated usage of resources by all the students during a certain time frame and the specific use of AWS for a specific student. To facilitate self-regulation of students, the dashboard also depicts the percentage of progress for each lab session and the pending actions by the student. The dashboard has been integrated in four Cloud subjects that use different learning methodologies (from face-to-face to online learning) and the students positively highlight the usefulness of the tool for Cloud instruction in AWS. This automated procurement of evidences of student activity on the Cloud results in close to real-time learning analytics useful both for semi-automated assessment and student self-awareness of their own training progress.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-07-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/140209
url https://riunet.upv.es/handle/10251/140209
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TIN2016-79951-R COMPUTACION BIG DATA Y DE ALTAS PRESTACIONES SOBRE MULTI-CLOUDS ELASTICOS
Universitat Politècnica de València https://doi.org/10.13039/501100004233
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI AG
publisher.none.fl_str_mv MDPI AG
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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