A comparative study of characteristics and preferences to learner models in educational adaptive hypermedia systems
A research team in Computer Science and University Pedagogical Engineering, The Laboratory of Applied and Didactic Sciences (LASAD) Higher Normal School of Tétouan, Abdelmalek Essaadi University, Morocco.
Review Article
Global Journal of Engineering and Technology Advances, 2023, 15(01), 033–040.
Article DOI: 10.30574/gjeta.2023.15.1.0072
Publication history:
Received on 01 March 2023; revised on 10 April 2023; accepted on 13 April 2023
Abstract:
Educational adaptive hypermedia systems are online learning systems that aim to tailor the learning experience to the characteristics and needs of individual learners. These systems use a variety of techniques, including data analysis, machine learning, and dynamic adaptive user interface, to provide more effective and personalized learning for each learner.
The learner models in their systems are designed to help them better understand the learner and tailor their learning experience, to do this their models take into account the characteristics of the learner, such as their learning style, education level, prior knowledge and learning goals. Our work consists in making a comparative study of its models at the functional level and characteristics in the educational adaptive hypermedia systems in order to conclude the most effective learner model that can help to improve the academic results and to make online learning more accessible and effective for all learners, the results prove that the model based on learning styles allows a better adaptation in the educational adaptive hypermedia systems, its development will be devoted to the work of the next article.
Keywords:
Adaptive educational hypermedia; Learner models; Preferences; Characteristics; Learning; Learning goal
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0