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Modeling an Adaptive e-Learning System for Improved Learning Performances

by Ibam E. Onwuka, Ibrahim I. Makinde, Agbonifo O. Catherine, Adewale O. Sunday
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 13
Year of Publication: 2023
Authors: Ibam E. Onwuka, Ibrahim I. Makinde, Agbonifo O. Catherine, Adewale O. Sunday
10.5120/ijca2023922755

Ibam E. Onwuka, Ibrahim I. Makinde, Agbonifo O. Catherine, Adewale O. Sunday . Modeling an Adaptive e-Learning System for Improved Learning Performances. International Journal of Computer Applications. 185, 13 ( Jun 2023), 8-19. DOI=10.5120/ijca2023922755

@article{ 10.5120/ijca2023922755,
author = { Ibam E. Onwuka, Ibrahim I. Makinde, Agbonifo O. Catherine, Adewale O. Sunday },
title = { Modeling an Adaptive e-Learning System for Improved Learning Performances },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2023 },
volume = { 185 },
number = { 13 },
month = { Jun },
year = { 2023 },
issn = { 0975-8887 },
pages = { 8-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number13/32754-2023922755/ },
doi = { 10.5120/ijca2023922755 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:25:56.710807+05:30
%A Ibam E. Onwuka
%A Ibrahim I. Makinde
%A Agbonifo O. Catherine
%A Adewale O. Sunday
%T Modeling an Adaptive e-Learning System for Improved Learning Performances
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 13
%P 8-19
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In majority of the online learning systems in use today, lack proper integration of adaptive, collaborative, personalized and ubiquitous concepts in their design and implementation. Integration of these basic concepts in online learning systems will enable adaptation, individualization, and collaboration of learning resources to learners’ preferences, with an added advantage of accessibility to online resources anywhere and any time. Hence, the research proposes an Adaptive E-Learning System (AES) model that incorporates activities sequencing in a personalised, adaptive, collaborative and ubiquitous learning environment. The system model consists of the system (software) architectural diagram and mathematical model of activity sequence. The design is presented using the UML activity diagram and the class diagram. The full implementation of the system is currently being carried out and is being tested with real life cases..

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Index Terms

Computer Science
Information Sciences

Keywords

Personalised learning Ubiquitous Learning Affective Learning Context-Aware.

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