Automating the E-learning personalization

Fathi Essalmi, Leila Jemni Ben Ayed, Mohamed Jemni, Kinshuk, Sabine Graf

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

10 Citations (Scopus)

Abstract

Personalization of E-learning is considered as a solution for exploiting the richness of individual differences and the different capabilities for knowledge communication. In particular, to apply a predefined personalization strategy for personalizing a course, some learners' characteristics have to be considered. Furthermore, different ways for the course representation have to be considered too. This paper studies solutions to the question: How to automate the E-learning personalization according to an appropriate strategy? This study finds an answer to this original question by integrating the automatic evaluation, selection and application of personalization strategy. In addition, this automation is supported by learning object metadata and an ontology which links these metadata with possible learners characteristics.

Original languageEnglish
Title of host publicationHuman-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data - Third International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Proceedings
Pages342-349
Number of pages8
DOIs
Publication statusPublished - 2013
Event3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013 - Maribor, Slovenia
Duration: 1 Jul. 20133 Jul. 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7947 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013
Country/TerritorySlovenia
CityMaribor
Period1/07/133/07/13

Keywords

  • E-learning
  • Evaluation of personalization parameters
  • Personalization strategy

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