Automatic tutoring system to support cross-disciplinary training in Big Data
During the last decade, Big Data has emerged as a powerful alternative to address latent challenges in scalable data management. The ever-growing amount and rapid evolution of tools, techniques, and technologies associated to Big Data require a broad skill set and deep knowledge of several domains—r...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:20.500.14342/3274 |
| Acceso en línea: | http://hdl.handle.net/20.500.14342/3274 https://doi.org/10.1007/s11227-020-03330-x |
| Access Level: | acceso abierto |
| Palabra clave: | Ensenyament universitari Dades massives 004 378 62 |
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oai:recercat.cat:20.500.14342/3274 |
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Automatic tutoring system to support cross-disciplinary training in Big Data Solé-Beteta, Xavier Navarro, Joan Vernet, David Zaballos, Agustin Torres Kompen, Ricardo Fonseca, David Briones, Alan Ensenyament universitari Dades massives 004 378 62 During the last decade, Big Data has emerged as a powerful alternative to address latent challenges in scalable data management. The ever-growing amount and rapid evolution of tools, techniques, and technologies associated to Big Data require a broad skill set and deep knowledge of several domains—ranging from engineering to business, including computer science, networking, or analytics among others—which complicate the conception and deployment of academic programs and methodologies able to effectively train students in this discipline. The purpose of this paper is to propose a learning and teaching framework committed to train masters’ students in Big Data by conceiving an intelligent tutoring system aimed to (1) automatically tracking students’ progress, (2) effectively exploiting the diversity of their backgrounds, and (3) assisting the teaching staff on the course operation. Obtained results endorse the feasibility of this proposal and encourage practitioners to use this approach in other domains. Springer http://hdl.handle.net/20.500.14342/3274 https://doi.org/10.1007/s11227-020-03330-x |
| title |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| spellingShingle |
Automatic tutoring system to support cross-disciplinary training in Big Data Solé-Beteta, Xavier Ensenyament universitari Dades massives 004 378 62 |
| title_short |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| title_full |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| title_fullStr |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| title_full_unstemmed |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| title_sort |
Automatic tutoring system to support cross-disciplinary training in Big Data |
| author |
Solé-Beteta, Xavier |
| author_facet |
Solé-Beteta, Xavier Navarro, Joan Vernet, David Zaballos, Agustin Torres Kompen, Ricardo Fonseca, David Briones, Alan |
| author_role |
author |
| author2 |
Navarro, Joan Vernet, David Zaballos, Agustin Torres Kompen, Ricardo Fonseca, David Briones, Alan |
| author2_role |
author author author author author author |
| topic |
Ensenyament universitari Dades massives 004 378 62 |
| topic_facet |
Ensenyament universitari Dades massives 004 378 62 |
| description |
During the last decade, Big Data has emerged as a powerful alternative to address latent challenges in scalable data management. The ever-growing amount and rapid evolution of tools, techniques, and technologies associated to Big Data require a broad skill set and deep knowledge of several domains—ranging from engineering to business, including computer science, networking, or analytics among others—which complicate the conception and deployment of academic programs and methodologies able to effectively train students in this discipline. The purpose of this paper is to propose a learning and teaching framework committed to train masters’ students in Big Data by conceiving an intelligent tutoring system aimed to (1) automatically tracking students’ progress, (2) effectively exploiting the diversity of their backgrounds, and (3) assisting the teaching staff on the course operation. Obtained results endorse the feasibility of this proposal and encourage practitioners to use this approach in other domains. |
| publishDate |
2021 |
| format |
article |
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acceptedVersion |
| url |
http://hdl.handle.net/20.500.14342/3274 https://doi.org/10.1007/s11227-020-03330-x |
| eu_rights_str_mv |
openAccess |
| publisher |
Springer |
| institution |
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| collection |
Recercat. Dipósit de la Recerca de Catalunya |
| reponame_str |
Recercat. Dipósit de la Recerca de Catalunya |
| instname_str |
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| _version_ |
1878740541663870976 |
| publishDateSort |
2021 |
| author_browse |
Briones, Alan Fonseca, David Navarro, Joan Solé-Beteta, Xavier Torres Kompen, Ricardo Vernet, David Zaballos, Agustin |
| publisherStr |
Springer |
| score |
6,8972664 |