ONTOLOGY-BASED PERSONALISATION SYSTEM FOR E-LEARNING

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dc.contributor.author ADESUYI, AKINWALE TOSIN
dc.date.accessioned 2020-12-02T09:38:50Z
dc.date.available 2020-12-02T09:38:50Z
dc.date.issued 2014-05
dc.identifier.uri http://196.220.128.81:8080/xmlui/handle/123456789/2071
dc.description M.TECH THESIS en_US
dc.description.abstract Learning is a medium of acquiring knowledge, it requires human intellect; however, knowledge acquisition mode differs from individuals. Thus, each of these modes is factored around time, otherwise one might have to learn an aspect of a particular field forever. Life itself is bounded by time, hence learning should be guided around time. It also occur that failure appears to students after they perform poorly in an examination, but rather, failure became imminent to them as a result of installment missing of concepts belonging to a particular course. Therefore there is need for a system that can help monitor student learning progress. Conversely, majority of e-learning system do not take cognizance of these. This thesis presents an ontology-based personalization system for e-learning with emphasis on the aforementioned factors. Paulo Gomes et. al. (2005) model was adopted. The research model is divided into a static and dynamic data. The static data consists of students’ information that do not change during the period of learning, while the dynamic data comprises of students’ data that continued to change based on the student interaction with the learning system. The dynamic data comprise of the student performance, time spent, preference for personalizing course concepts and the learning category. The learning categories includes; learned, well learned and timely well learned. They are built in the ontology. The ontology was designed using Resource Description Framework schema, Extensible Markup language was used to interpret the ontology schema to e-learning system. The e-learning system was implemented with Microsoft C# on .NET framework using Visual Studio Integrated Development Environment 2010 for the interface design. Microsoft Structured Query Language Server 2005, a relational database system was used for storage of students’ profile and performance evaluation. The research was experimented with records of 22 students in python programming language course. It was observed that minimum of 28% and maximum of 54% of the students improved as they progress from one concept of the course to another. en_US
dc.description.sponsorship FEDERAL UNIVERSITY OF TECHNOLOGY AKURE en_US
dc.language.iso en en_US
dc.publisher FEDERAL UNIVERSITY OF TECHNOLOGY AKURE en_US
dc.subject E-LEARNING en_US
dc.subject ONTOLOGY-BASED PERSONALISATION SYSTEM en_US
dc.title ONTOLOGY-BASED PERSONALISATION SYSTEM FOR E-LEARNING en_US
dc.type Thesis en_US


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