Big Data for Online Learning Systems
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ERIC Institute of Education Sciences
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| Autores principales: | , , , |
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| Formato: | Recurso educativo Open Access |
| Lenguaje: | en |
| Publicado: |
2018
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| Acceso en línea: | |
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| _version_ | 1867181816606097408 |
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| author | Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal |
| author_facet | Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal |
| collection | Education Resources Information Center |
| contents | Big Data for Online Learning Systems Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal Data Electronic Learning Educational Technology Media Adaptation Integrated Learning Systems In recent years, Online learning systems have met big challenges, especially due to rapid changes in technology, the gigantic amounts of data to be stored and manipulated, the large number of learners and the diversity of educational resources. As a result, e-learning platforms must change their mechanisms for data processing and storage to be smarter. In this context, big data is the relevant paradigm for the distributed and parallel processing of large data sets through thousands of clusters. It also offers a rich set of tools in order to improve data collection, storage, analysis, processing, optimization, and visualization. This article introduces the big data concept, its characteristics, and focuses in particular on the integration of it in a computing environment for human learning dedicated to online learning systems, and how the new methods, technologies, and tools of big data can enhance the future of online learning. Moreover, it proposes an approach for smoothly adapting the traditional e-learning systems to be suitable for big data ecosystems in cloud computing. Furthermore, it provides a methodology and architecture to incorporate the e-learning storage and computing in a Hadoop software library. Finally, the benefits and advantages associated with implementing big data in future online learning systems are discussed. |
| format | Recurso educativo Open Access |
| id | eric_EJ1192447 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 2018 |
| record_format | eric |
| spellingShingle | Big Data for Online Learning Systems Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal Data Electronic Learning Educational Technology Media Adaptation Integrated Learning Systems Big Data for Online Learning Systems Dahdouh, Karim Dakkak, Ahmed Oughdir, Lahcen Messaoudi, Fayçal Data Electronic Learning Educational Technology Media Adaptation Integrated Learning Systems In recent years, Online learning systems have met big challenges, especially due to rapid changes in technology, the gigantic amounts of data to be stored and manipulated, the large number of learners and the diversity of educational resources. As a result, e-learning platforms must change their mechanisms for data processing and storage to be smarter. In this context, big data is the relevant paradigm for the distributed and parallel processing of large data sets through thousands of clusters. It also offers a rich set of tools in order to improve data collection, storage, analysis, processing, optimization, and visualization. This article introduces the big data concept, its characteristics, and focuses in particular on the integration of it in a computing environment for human learning dedicated to online learning systems, and how the new methods, technologies, and tools of big data can enhance the future of online learning. Moreover, it proposes an approach for smoothly adapting the traditional e-learning systems to be suitable for big data ecosystems in cloud computing. Furthermore, it provides a methodology and architecture to incorporate the e-learning storage and computing in a Hadoop software library. Finally, the benefits and advantages associated with implementing big data in future online learning systems are discussed. |
| title | Big Data for Online Learning Systems |
| topic | Data Electronic Learning Educational Technology Media Adaptation Integrated Learning Systems |
| url | https://eric.ed.gov/?id=EJ1192447 |