scholarly journals AN META-ANALYSIS ON THE EFFECT OF ADAPTIVE HYPERMEDIA LEARNING SYSTEM USING LEARNING STYLE ADAPTOR

2020 ◽  
Author(s):  
Sirui Wu
Keyword(s):  
Learning Style ◽  
Meta Analysis ◽  
Learning System ◽  
Adaptive Hypermedia ◽  
Hypermedia Learning

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

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.

Gender Differences and Hypermedia Navigation

2011 ◽  
pp. 278-292
Author(s):  
Jing Ping Fan ◽  
Robert D. Macredie
Keyword(s):  
Gender Differences ◽  
Learning Style ◽  
Empirical Studies ◽  
Experimental Studies ◽  
Individual Characteristics ◽  
Learning System ◽  
Adaptive Hypermedia ◽  
Adaptive Presentation ◽  
Hypermedia Learning ◽  
Navigation Support

Adaptive hypermedia learning systems can be developed to adapt to a diversity of individual differences. Many studies have been conducted to design systems to adapt to learners’ individual characteristics, such as learning style and cognitive style to facilitate student learning. However, no research has been done specifically regarding the adaptation of hypermedia learning system to gender differences. This chapter therefore attempts to fill this gap by examining the published findings from experimental studies of interaction between gender differences and hypermedia learning. Analysis of findings of the empirical studies leads to a set of principles being proposed to guide adaptive hypermedia learning system design onthe basis of gender differences in relation to (i) adaptive presentation and (ii) adaptive navigation support.

Gender Differences and Hypermedia Navigation

2006 ◽  
pp. 1-20 ◽  
Author(s):  
Jing P. Fan ◽  
Robert D. Macredie
Keyword(s):  
Gender Differences ◽  
Learning Style ◽  
Empirical Studies ◽  
Experimental Studies ◽  
Individual Characteristics ◽  
Learning System ◽  
Adaptive Hypermedia ◽  
Adaptive Presentation ◽  
Hypermedia Learning ◽  
Navigation Support

Adaptive hypermedia learning systems can be developed to adapt to a diversity of individual differences. Many studies have been conducted to design systems to adapt to learners’ individual characteristics, such as learning style and cognitive style to facilitate student learning. However, no research has been done specifically regarding the adaptation of hypermedia learning system to gender differences. This chapter therefore attempts to fill this gap by examining the published findings from experimental studies of interaction between gender differences and hypermedia learning. Analysis of findings of the empirical studies leads to a set of principles being proposed to guide adaptive hypermedia learning system design onthe basis of gender differences in relation to (i) adaptive presentation and (ii) adaptive navigation support.

Gender Differences and Hypermedia Navigation

2008 ◽  
pp. 1778-1792
Author(s):  
J. P. Fan
Keyword(s):  
Gender Differences ◽  
Learning Style ◽  
Empirical Studies ◽  
Experimental Studies ◽  
Individual Characteristics ◽  
Learning System ◽  
Adaptive Hypermedia ◽  
Adaptive Presentation ◽  
Hypermedia Learning ◽  
Navigation Support

Adaptive hypermedia learning systems can be developed to adapt to a diversity of individual differences. Many studies have been conducted to design systems to adapt to learners’ individual characteristics, such as learning style and cognitive style to facilitate student learning. However, no research has been done specifically regarding the adaptation of hypermedia learning system to gender differences. This chapter therefore attempts to fill this gap by examining the published findings from experimental studies of interaction between gender differences and hypermedia learning. Analysis of findings of the empirical studies leads to a set of principles being proposed to guide adaptive hypermedia learning system design onthe basis of gender differences in relation to (i) adaptive presentation and (ii) adaptive navigation support.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

Sign in / Sign up

Export Citation Format

Share Document