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Smart E-learning content delivery system for ubiquitous devices, using Wi-Fi networks and smart board approach

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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Due to integration of ICT in educational and the evolution of E-learning, there has been a tremendous growth of big data in educational. These big data in education has left students with no precise relevant data with regard to their educational content requirements. Making students sometimes take a lot of time accessing non relevant data to their educational needs. This study therefore brings forward a system through which big educational data can be classified, and then documented students professional requirements are matched with their relevant educational requirements. Hence the developed system should be able to learn the students profession and then avail them only relevant data to their educational. The student profession details should be kept within their mobile (ubiquitous) devices that they use to access educational data. This will in turn make learning enjoyable and no time wastage accessing non relevant data with regard to your profession. The platform using Wi-Fi network, should also indicate the classroom/ point where the student is accessing the content from. In designing this model we used the standard system development life cycle. We designed a database web driven system which collects and stores students’ details. When a student logs into the system using their ubiquitous devices, the system collects collects some data from the students devices, and directs the student to the relevant educational requirements with regard to the collected data. The education data, and the students educational requirements were coded for easy matching. The prototype system resulted in 80% relevance during the searches.


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Smart classroom, e-learning system, ubiquitous devices.

  • Format Volume 4, Issue 2, No 9, 2016
  • Copyright All Rights Reserved ©2016
  • Year of Publication 2016
  • Author Kevin O. Gogo, Lawrence Nderu, Fredrick M. Muthengi
  • Reference IJCS-156
  • Page No 946-953

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