E-learning content management: An ontology-based approach

Nophadol Jekjantuk*, Md Maruf Hasan

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

4 Citations (Scopus)

Abstract

Scarcity of E-Learning content being a barrier for ELearning is no longer true on today's Internet. The current concerns are how to effectively annotate and organize available content (both textual and non-textual) to facilitate effective sharing, reusability and customization in an intelligent fashion. In this paper, we explain a component-oriented approach to organize content in an ontology. We also illustrate our 3-Tier E-Learning Content Management Architecture and relevant Web Services and Interfaces. We use a simple yet intuitive example to successfully demonstrate the current working prototype which is capable of compiling personalized course materials on a particular topic (e.g., "Database") on-the-fly. The prototype uses the Pellet Semantic Web Reasoner as an inference engine to satisfy the constraints and criteria specified by a user (through browser based interface) or an agent (via Web Service API), and retrieves relevant content from the domain ontology in an organized fashion.

Original languageEnglish
Title of host publicationProceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007
Pages78-83
Number of pages6
Publication statusPublished - 2007
Externally publishedYes
Event3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007 - Phuket, Thailand
Duration: 2 Apr 20074 Apr 2007

Publication series

NameProceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007

Conference

Conference3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007
Country/TerritoryThailand
CityPhuket
Period2/04/074/04/07

Keywords

  • E-learning content management
  • Learning objects
  • Ontology-driven inference
  • Semantic web services

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