Analyzing Learners' Interaction with an Educational Hypermedia System: A Focus on Learning Styles

2008 ◽  
Author(s):  
Elvira Popescu ◽  
Costin Badica ◽  
Philippe Trigano
Keyword(s):  
Learning Styles ◽  
System A ◽  
Hypermedia System ◽  
Educational Hypermedia

scholarly journals Toward an Adaptive Educational Hypermedia System (AEHS-JS) based on the Overlay Modeling and Felder and Silverman’s Learning Styles Model for Job Seekers

2020 ◽  
Vol 15 (08) ◽  
pp. 235
Author(s):  
Aymane Qodad ◽  
Abdelilah Benyoussef ◽  
Abdallah El Kenz ◽  
Mourad Elyadari
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Job Search ◽  
Social Impact ◽  
Learning Objects ◽  
Educational Systems ◽  
Job Seekers ◽  
Learner Model ◽  
Hypermedia System ◽  
Educational Hypermedia

In this paper we introduce a new design of an adaptive educational hypermedia system for job seekers, this proposal is based, for the part of learning objectives, on a job model which allows adapting the content and the path of education to the intended jobs, and, for the learner model construction, on a specific use of the learning styles of Felder and Silverman. First, we present existing literature to give a general review on adaptive edu-cational hypermedia systems, in that way; we have reported the related items to different notions in the adaptive educational Systems area as the differentiated pedagogy, the learning objects, and the learner profile. Then we argued our choice of the components of our model and we detailed the new ones. As designed, the model can produce a suitable learning path for the user to match the job characteristics and the learning style of the person in order to help the user owning the job sought. With the possibility of linking the required com-petencies to the education skills, we aim to map business tasks to learning activi-ties. Based on this approach, we designed an Adaptive Educational Hypermedia System named AEHS-JS that will help to improve the efficiency and pragmatism of job search activities. In plus of the social impact of this work as it help job seekers to complete their profiles and get the career they are looking for, this work will allow companies to find the candidates that match the job criteria sought.

scholarly journals Improvement of Academic Performance of Engineering Students through an Adaptive Educational Hypermedia System (AEHS)

2019 ◽  
Vol 8 (12S2) ◽  
pp. 12-17
Keyword(s):  
Academic Performance ◽  
Learning Styles ◽  
University Students ◽  
Engineering Students ◽  
Color Adaptation ◽  
Hypermedia System ◽  
Industrial Software ◽  
Intelligent Tutor ◽  
Educational Hypermedia

This paper describes how to improve the academic performance of engineering university students through an Adaptive Educational Hypermedia System (AEHS). The psychological basis, learning styles and MOOMH methodology for the development of the system are exposed, which with its implementation achieves adaptability and works for students as an “intelligent tutor”, allowing them to guide their education as academic tutor. Not only shows its content that meets the needs of the student, but it is also represented in elements such as color adaptation, work tools and even academic recommendations based on the interactions that the user makes within the system, the system recognizes its pattern of use, and when the student is logged in again, it presents a friendlier interface that the student prefers use, it is wider in content and, above all, easy to use and understand. In addition, the AEHS allows to extend education allowing the assignment of more domain areas, in the field of engineering, that is, the SHAE can be adapted to various engineering specialties such as: industrial, software, telecommunications, mechanics and other.

scholarly journals Improvement of Academic Performance of Engineering Students through an Adaptive Educational Hypermedia System (AEHS)

2019 ◽  
Vol 8 (12S2) ◽  
pp. 12-17
Keyword(s):  
Academic Performance ◽  
Learning Styles ◽  
University Students ◽  
Engineering Students ◽  
Color Adaptation ◽  
Hypermedia System ◽  
Industrial Software ◽  
Intelligent Tutor ◽  
Educational Hypermedia

This paper describes how to improve the academic performance of engineering university students through an Adaptive Educational Hypermedia System (AEHS). The psychological basis, learning styles and MOOMH methodology for the development of the system are exposed, which with its implementation achieves adaptability and works for students as an “intelligent tutor”, allowing them to guide their education as academic tutor. Not only shows its content that meets the needs of the student, but it is also represented in elements such as color adaptation, work tools and even academic recommendations based on the interactions that the user makes within the system, the system recognizes its pattern of use, and when the student is logged in again, it presents a friendlier interface that the student prefers use, it is wider in content and, above all, easy to use and understand. In addition, the AEHS allows to extend education allowing the assignment of more domain areas, in the field of engineering, that is, the SHAE can be adapted to various engineering specialties such as: industrial, software, telecommunications, mechanics and other.

Development and Testing of New E-Learning Hypermedia System

2015 ◽  
Vol 10 (2) ◽  
pp. 1-15
Author(s):  
Lamia Mahnane ◽  
Mohamed Hafidi
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Learning Experience ◽  
Innovative Approach ◽  
Thinking Styles ◽  
New Approach ◽  
Learning Content ◽  
Hypermedia System ◽  
E Learning ◽  
Web Learning

Adaptive E-learning Hypermedia Systems (AEHS) are an innovative approach to a web learning experience delivery. They try to solve main shortcomings of classical hypermedia e-learning applications: “one-size-fits-all” approach and “lost-in-hyperspace” phenomena by adapting the learning content and its presentation to needs, goals, thinking styles and learning styles of every individual learner. This paper outlines a new approach to automatically detect learner's thinking and learning styles, and taking into account that thinking and learning styles may change during the learning process in an unexpected and unpredictable way. The authors' approach is based on the Felder Learning Styles Model and Hermann thinking styles model.

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