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Reviews on Machine Learning based Adaptive Mobile Learning System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 38 |
| Year of Publication: 2020 |
| Authors: Adeboje Olawale Timothy, Isiaka Abdulwab, Jimoh Ibraheem Temitope, Joda Shade |
10.5120/ijca2020920498
|
Adeboje Olawale Timothy, Isiaka Abdulwab, Jimoh Ibraheem Temitope, Joda Shade . Reviews on Machine Learning based Adaptive Mobile Learning System. International Journal of Computer Applications. 176, 38 ( Jul 2020), 1-6. DOI=10.5120/ijca2020920498
Abstract
It is obvious that the increasing number of new mobile devices has encouraged learners to use these devices to access content without sacrificing usability and accessibility. However, most current learning contents to be accessed are typical designed for desktop computers, hence may not be suitable for presentation on other devices like mobile devices as they are mostly affected with limited bandwidth and limited device capabilities. Notwithstanding, mobile learning researchers are devoted to finding ways of harmonizing device adaptation (device type and capabilities) with content adaptation (that is learner learning style, preference, strategies, and so on) to satisfy individual demands. However, some of the researches attempting to achieve these features are either faced with one challenges or the other. Therefore, this paper is set to provide a proper background on Mobile learning and set to resolve the shortcomings in the reviewed literatures by developing ANFIS based mobile learning system that incorporates an automatic learning style identification module.
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