ONLINE COURSE CUSTOMIZATION USING ONTOLOGIES Cover Image

ONLINE COURSE CUSTOMIZATION USING ONTOLOGIES
ONLINE COURSE CUSTOMIZATION USING ONTOLOGIES

Author(s): Oana Sorina LUPȘE, Mihaela CRIȘAN-VIDA, Lăcrămioara STOICU-TIVADAR
Subject(s): Social Sciences
Published by: Carol I National Defence University Publishing House
Keywords: ontology; eLearning; cloud computing; Azure; Protégé.

Summary/Abstract: Currently, more and more people prefer to acquire new knowledge based on online resources. This gives the liberty for individuals to choose a particular course focused on what they really want to learn. The work in the current paper supports this kind of independent persons guiding them in selection of the most suitable course: verifying if they have enough knowledge for the course and suggesting courses to better match the knowledge they want to gain. Using ontologies we create links between people abilities (level and type of previous education, general knowledge, etc.), and each course content. , The application presented in this paper suggests, based on an individual‘s selection and on the results to an initial test, the modules needed to reach the expected knowledge. More, the application suggests an alternative path to gain basic abilities for what the user wants to learn. The initial test contains questions about the elementary knowledge for the selected course. The ontology application and the links between users, courses and initial test are developed in Protégé, an open source ontology project, and the application for the courses are developed using ASP.NET pages, C# language and  Azure SQL  database, and Microsoft Azure cloud. The ontology links all users and courses data, and supports users to understand the new information according to their previous knowledge. The benefits of the application consist in supporting individuals to select the best course for a given situation and understand better the new information according to their basic knowledge.

  • Issue Year: 13/2017
  • Issue No: 02
  • Page Range: 98-105
  • Page Count: 8
  • Language: English
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