Integrating Learning Styles in an Adaptive Hypermedia System with Adaptive Resources

This article addresses the learning style as a criterion for optimization of adaptive content in hypermedia applications. First, the authors present the different optimization approaches proposed in the area of adaptive hypermedia systems whose goal is to define the optimization problem in this type of system. Then, they present the architecture of their proposed system. The first step involves choosing a learning style model. The selection of this style is done by using a dedicated questionnaire answered by a learner. Then a modeling of the learner is completed based on his learning style. Finally, content that is to be presented to the learner is managed by a content generator module, depending on the model of the learner. Built on methods and techniques proposed for modeling and adaptation, the adaptive hypermedia system based on learning styles provides optimized adaptations. The authors' approach has been experimentally validated and the results are encouraging.

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Design of a Learner Model for Integration into an Adaptive Hypermedia System

Lecture Notes in Mechanical Engineering - Advances in Integrated Design and Production ◽

10.1007/978-3-030-62199-5_48 ◽

2020 ◽

pp. 549-558

Author(s):

Mehdi Tmimi ◽

Mohamed Benslimane ◽

Mohammed Berrada ◽

Kamar Ouazzani

Keyword(s):

Adaptive Hypermedia ◽

Learner Model ◽

Hypermedia System

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Knowledge Based Information Retrieval with an Adaptive Hypermedia System

Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira’s Scientific Legacy - Lecture Notes in Computer Science ◽

10.1007/978-3-642-02264-7_47 ◽

2009 ◽

pp. 457-463

Author(s):

Francisca Grimón ◽

Josep Maria Monguet ◽

Jordi Ojeda

Keyword(s):

Information Retrieval ◽

Adaptive Hypermedia ◽

Knowledge Based ◽

Hypermedia System

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A Learner Model Based on Bayesian Networks in Adaptive Educational Hypermedia Systems

Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-5225-7413-2.ch004 ◽

2018 ◽

pp. 65-94

Keyword(s):

Computational Modeling ◽

Bayesian Networks ◽

Educational System ◽

Probabilistic Framework ◽

Adaptive Hypermedia ◽

Learner Modeling ◽

Learner Model ◽

Learning Path ◽

Hypermedia System ◽

Probabilistic Context

The work presented in this chapter lies within learner modeling in an adaptive educational system construed as a computational modeling of the learner. All actions of the learner in a learning situation on an adaptive hypermedia system are not limited to valid or invalid actions (true and false), but they are a set of actions that characterize the learning path of formation. Thus, one cannot represent the information from the system of each learner using relative data. It requires putting the work in a probabilistic context due to the changes in the learner model information during formation. In this chapter, the authors propose to use Bayesian networks as a probabilistic framework to resolve the issue of dynamic management and update of the learner model. The experiments and results presented in this work are arguments in favor of the hypothesis and can also promote reusing the modeling obtained through different systems and similar modeling situations.

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A Model for an Adaptive Hypermedia Learning System Based on Data Mining Technique

Exploring the New Era of Technology-Infused Education - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-5225-1709-2.ch005 ◽

2017 ◽

pp. 65-85

Author(s):

Mahnane Lamia ◽

Mohamed Hafidi

Keyword(s):

Learning Styles ◽

Learning Style ◽

Personal Characteristics ◽

Learning Objects ◽

Learning System ◽

Learning Performance ◽

Adaptive Hypermedia ◽

Data Mining Technique ◽

Pedagogical Strategies ◽

Hypermedia Learning

Since the learning style of each learner is different. Adaptive hypermedia learning system (AHLS) must fit different learner's needs. A number of AHLS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: less attention was paid to the relationship between learning styles and learning performance. This paper proposes an AHLS model based on learning styles and learning performance. On one hand, the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her learning style and level of knowledge). On the other hand, it will facilitate the learning content teacher in the creation of appropriate learning objects and their application to suitable pedagogical strategies.

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