Architectural and Parametric Design Evaluation for Enhancing Adaptive E-Learning
Daramola Comfort Y.1, Akinpelu Samson. A2, Joshua Bature Hassan3
1Daramola Comfort Y., Department of Computer Science, Federal University Oye-Ekiti.
2Akinpelu Samson. A*, Department of Computer Science, Federal University Oye-Ekiti.
3Joshua Bature Hassan, Department of Computer Science, Federal University Oye-Ekiti.
Manuscript received on May 01, 2021. | Revised Manuscript received on May 31, 2021. | Manuscript published on May 30, 2021. | PP: 308-313 | Volume-10 Issue-1, May 2021. | Retrieval Number: 100.1/ijrte.A57730510121 | DOI: 10.35940/ijrte.A5773.0510121
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Learning is any technique that in living creatures prompts never-ending limit change and which isn’t solely a direct result of characteristic advancement of developing. The complexity associated with learning and the fact that it start from birth till death makes it a cumbersome procedure. It incorporates certainly more than reasoning: the whole character – resources, feelings, impulse, values and will. Many conventional approaches fail to inculcate the above parameters which increase the cumbersomeness of learning coupled with problems of assimilation. If we don’t have the will to learn, we won’t learn and if we have learned, we are truly changed by one way or another. The focus of this paper is to propose an architecture that was designed with special emphasis on enhancing adaptive e-learning. This architecture uses the learning style of learner to produce learning contents peculiar to such learner and as such difficulties associated with comprehension is totally aborted and thereby making learning easier.
Keywords: Learning, Adaptive, E-Learning, Learning-Style, Knowledge.