Enhancing Distance Learning Platforms with Social Media Analytics - Artificial Intelligence Applications and Innovations (AIAI 2015)
Conference Papers Year : 2015

Enhancing Distance Learning Platforms with Social Media Analytics

Aristidis Ilias
  • Function : Author
  • PersonId : 991098
George Pavlidis
  • Function : Author
  • PersonId : 991099

Abstract

The current paper emphasizes on how enhancement of human interconnection improves distance learning processes through the use of social media analytics. Until today, educators, learners, parents and everyone else interested in a distance learning activity were able to customize and personalize their educational trajectory through representative structures, which actually promoted very general composites of the individual opinions. Over time, distance learning platforms, combined with social media and services, have to evolve and focus in strengthening the influence of the voices of their users, as well as promote the active participation of them in the educational activities. In accordance to this need, the purpose of this paper is to present an intelligent extension of existing distance learning platforms. We discuss the details of a system that utilizes big amount of structured and unstructured, historical and real-time data in order to inform, create new contacts and strengthen the dialogue and cooperation between the participants in an educational procedure. We cite an example from the field of learning Russian language from Greek students.
Fichier principal
Vignette du fichier
978-3-319-23868-5_31_Chapter.pdf (321.85 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01385378 , version 1 (21-10-2016)

Licence

Identifiers

Cite

Oksana Kalita, Aristidis Ilias, George Pavlidis. Enhancing Distance Learning Platforms with Social Media Analytics. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. pp.431-439, ⟨10.1007/978-3-319-23868-5_31⟩. ⟨hal-01385378⟩
71 View
135 Download

Altmetric

Share

More