An Intelligent and Adaptive Hypermedia System Based on Thinking Style (IAHS-TS)

2016 ◽  
pp. 111-130
Author(s):  
Mahnane M. L. Lamia ◽  
Hafidi Mohamed
Keyword(s):  
Personal Characteristics ◽  
Learning Objects ◽  
Learning System ◽  
Thinking Style ◽  
Brain Dominance ◽  
Pedagogical Strategies ◽  
Learning Content ◽  
Hypermedia System ◽  
E Learning ◽  
Level Of Knowledge

In this paper, an adaptive and intelligent hypermedia system, AIHS was designed, developed and implemented. This e-learning system was intended for bachelor degree program that is offered in all Algerian public universities, where the studied subjects are: “ORL”, “Dermatology”, “Ophthalmology” and “Language”. Content which was transformed into learning objects in four different ways in accordance with Herrmann Brain Dominance Instrument (HBDI). 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 thinking style and level of knowledge). It will facilitate the learning content teacher in the creation of appropriate learning objects and applying them to suitable pedagogical strategies.

A Model for an Adaptive e-Learning Hypermedia System

2013 ◽  
Vol 9 (4) ◽  
pp. 21-39
Author(s):  
Lamia Mahnane ◽  
Laskri Mohamed Tayeb ◽  
Philippe Trigano
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Personal Characteristics ◽  
Learning Objects ◽  
Thinking Styles ◽  
Pedagogical Strategies ◽  
Learning Content ◽  
Hypermedia System ◽  
E Learning ◽  
Specific Teaching

Recent years have shown increasing awareness for the importance of adaptivity in e-learning. Since the learning style of each learner is different. Adaptive e-learning hypermedia system (AEHS) must fit different learner’s needs. A number of AEHS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: lack of maintenance, adaptation to learning style, less attention was paid to thinking styles and the insertion of specific teaching strategies into learning content. This paper proposes an AEHS model based on thinking styles and knowledge level. 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 thinking 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.

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.

scholarly journals Challenges of Transitioning to e-learning System with Learning Objects Capabilities

2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Miroslava Raspopovic ◽  
Svetlana Cvetanovic ◽  
Aleksandar Jankulovic
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Information Systems ◽  
Open Source ◽  
Learning Objects ◽  
Learning System ◽  
Learning Content ◽  
Technological Advances ◽  
E Learning ◽  
Transitional Challenges

<p>In order for higher education institutions, which implements blended and/or online learning to remain competitive and innovative it needs to keep up with the cutting edge technological and educational advances. This task is usually very difficult, keeping in mind the budget constraints that many institutions have. This usually implies that existing open source solutions have to be used and adapted to individual needs of each institution. Keeping up with the current technological advances often brings not only financial challenges, but also transitional challenges that may put at risk learning quality and reputation of the institution, as well as performance of students. This work describes the features of the system, results and challenges of transitioning to e-learning system that displays learning materials through sequence of reusable learning objects (LOs) from the system that does not have these capabilities. The goal of such system is to increase reusability of learning content, and moreover, to increase online interactivity and communication between the instructor and students. Findings of this work reveal advantages, disadvantages and potential obstacle of implementation e-learning system with LOs and give an overview of suggestions for implementation improvements. These suggestions are given based on evaluation of implementation of new e-learning system with LOs, after the transition from the traditional e-learning system. Furthermore, based on the research of existing methodologies in the field of information systems, and the results of this research, this work proposes methodology for transferring into e-learning system with LOs. </p>

scholarly journals The Data of the Initial Motivation – a Valuable Source for the Development of the Course Content. A Case Study in the Group of Business Students

2018 ◽  
Vol 7 (2.28) ◽  
pp. 89
Author(s):  
Iveta Daugule ◽  
Atis Kapenieks
Keyword(s):  
Learning Environment ◽  
Business Students ◽  
Personal Characteristics ◽  
Learning System ◽  
Individual Motivation ◽  
Course Content ◽  
Study Materials ◽  
Learning Content ◽  
E Learning ◽  
Complex Knowledge

This study continues the authors’ previous search for key factors to determine the stickiness of different kinds of knowledge. In the authors’ opinion, identifying the stickiness of every type of knowledge in the e-course it is possible to create the optimal distribution of the intensity of time and study materials, paying more attention to the more complex knowledge, while promoting the acquisition of the free flow of knowledge with some tasks aimed at collaboration between students. Also, our previous study showed that individual motivation plays an important role in students’ success. That is why the scope of this study embraces the link of students' personal characteristics with their behavior and achievements in a learning environment. In this study, we are looking for key features for the future development of a more advanced learning system. Our scope of this study embraces the aspects of student’s initial motivation – how to ascertain, define and then use it for the development of the further learning content. Students were divided into three groups, according to their plans for engagement in business projects. The study was conducted in the course, that’s organized according to the blended learning delivery approach. Part of this course takes place in a classroom, while the other part is embedded in an electronic environment on an Open edX platform-based E-Learning environment.  

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.

scholarly journals The swarm intelligence algorithms and their application for the educational data analysis

2019 ◽  
Vol 23 (5) ◽  
pp. 33-43
Author(s):  
Y. Yu. Dyulicheva
Keyword(s):  
Data Analysis ◽  
Swarm Intelligence ◽  
Learning Objects ◽  
Ant Algorithm ◽  
First Year ◽  
Optimal Learning ◽  
First Year Students ◽  
Learning Content ◽  
Learning Path ◽  
Level Of Knowledge

The purpose of the paper is the investigation of the modern approaches and prospects for the application of swarm intelligence algorithms for educational data analysis, as well as the possibility of using of ant algorithm modifications for organizing educational content in adaptive systems for conducting project seminars.Materials and methods. The review of the modern articles on the educational data analysis based on swarm intelligence algorithms is provided; the approaches to solving problem of the optimal learning path construction (optimal organization of the learning objects) based on the algorithm and its modifications taking into account the students’ performance in the process of the optimal learning path construction are investigated; the application of particle swarm optimization and its modification based on Roccio algorithm for the reduction of curse dimension in the problem of the auto classifying questions; the application of ant algorithm, bee colony algorithm and bat algorithm for recommender system construction are studied; the prediction of students’ performance based on particle swarm optimization is researched in the article. The modification of ant algorithm for optimal organization of learning objects at projects seminars is proposed.Results. The modern approaches based on swarm intelligence algorithms to problem solving in educational data analysis are investigated. The various approaches to pheromones updating (their evaporation) when building the optimal learning path based on students’ performance data and search of group with “similar" students are studied; the abilities of the hybrid swarm intelligence algorithms for recommendation construction are investigated.Based on the modification of ant algorithm, the approach to the learning content organization at project seminars with individual preferences and students’ level of basic knowledge is proposed. The python classes are developed: the class for statistical data processing; the classfor modifica -tion of ant algorithm, taking into account the current level of knowledge and interest of student in studying a specific topic at the project seminar; the class for optimal sequence of the project seminars ’ topics for students. The developed classes allow creating the adaptive system that helps first year students with a choice of topics of project seminars.Conclusion. According to the results of the study, we can conclude about the effectiveness of swarm intelligence algorithms usage to solve a wide range of tasks connected with learning content and students’ data analysis in the e-learning systems and perspectives to hybrid approaches development based on swarm intelligence algorithms for realizing the adaptive learning systems on the paradigm of “demand learning".The results can be used to automate the organization of learning content during project seminars for the first-year students, when it is important to understand the basic level of knowledge and students’ interest in learning new technologies.

Automatic Organization and Generation of Presentation Slides for E-Learning

2012 ◽  
Vol 10 (3) ◽  
pp. 35-52 ◽  
Author(s):  
K. Sathiyamurthy ◽  
T. V. Geetha
Keyword(s):  
Distance Education ◽  
Language Processing ◽  
Learning System ◽  
Learning Material ◽  
Content Creation ◽  
Learning Content ◽  
E Learning ◽  
Processing Techniques ◽  
The Web ◽  
Extract Information

The effectiveness of an e-learning system for distance education to a large extent depends on the relevancy and presentation of learning content to the learner. The ability to gather documents on a particular topic from the web and adapt the contents of the document to suit the learner is an important task from the content creation perspective of e-learning. For the developer of e-learning material the provision to automatically extract, organize, and present content material would improve its effectiveness. This paper proposes to extract information from documents using language processing techniques and organizing the content into appropriate presentation slides for learning purposes using domain ontology and learning oriented pedagogy ontology.

An Ontology-Based Learning System in IT Project Management

2011 ◽  
pp. 191-210
Keyword(s):  
Learning Objects ◽  
Learning System ◽  
Learning Tools ◽  
It Project Management ◽  
Knowledge Domain ◽  
Tutoring Systems ◽  
Learner Model ◽  
Future Developments ◽  
E Learning ◽  
Competency Based

The development process is based on the state of the art IT technologies (metadata and ontology for knowledge manipulation, Web services, learner model, and intelligent tutoring systems). Besides interoperability and personalization, the proposed approach brings additional advantages, including: unitary interpretation of the content structure by different user categories or content providers; explicit specification of the knowledge domain, allowing the updating of the domain definition without major changes of e-learning tools and programmes; reuse of the learning objects with economical advantages by saving costs of (re)writing the content for the different course forms and strategies; reuse of the created tools in one domain in other domains; promoting the competency-based learning through the domain ontology and the relations between concepts and competencies. The results obtained in practice are very encouraging and suggest several future developments.

Securing the Infrastructure for Service-Based E-Learning Environments

2011 ◽  
pp. 1-24
Author(s):  
Simon Schwingel ◽  
Gottfried Vossen ◽  
Peter Westerkamp
Keyword(s):  
Web Services ◽  
Learning Environment ◽  
Learning Environments ◽  
User Authentication ◽  
Learning Objects ◽  
Learning System ◽  
Learning Material ◽  
Single Sign On ◽  
User Data ◽  
E Learning

E-learning environments and their system functionalities resemble one another to a large extent. Recent standardization efforts in e-learning concentrate on the reuse of learning material only, but not on the reuse of application or system functionalities. The LearnServe system, under development at the University of Muenster, builds on the assumption that a typical learning system is a collection of activities or processes that interact with learners and suitably chosen content, the latter in the form of learning objects. This enables us to divide the main functionality of an e-learning system into a number of stand-alone applications or services. The realization of these applications based on the emerging technical paradigm of Web services then renders a wide reuse of functionality possible, thereby giving learners a higher flexibility of choosing content and functionalities to be included in their learning environment. In such a scenario, it must be possible to maintain user identity and data across service and server boundaries. This chapter presents an architecture for implementing user authentication and the manipulation of user data across several Web services. In particular, it demonstrates how to exploit the SPML and SAML standards so that cross-domain single sign-on can be offered to the users of a service-based learning environment. The chapter also discusses how this is being integrated into LearnServe.

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