An e-learning application based on the semantic web technology

The paper describes a framework for the implementation of an elearning system based on the Semantic Web, using software agents and Java Web Services. Hopefully we have elucidated the enormous potential of making web content machine-understandable. One of the killer applications for the Semantic Web might prove to be related to e-learning, considering the amount of research in this sector and the advantages those applications bring to the table compared to existing web-based learning courses.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

Cognitive Approach to e-Learning in Sciences and Technologies

This article describes the approach adopted and the results obtained by the international team developing WBLST (Web Based Learning in Sciences and Technologies) a Web-based application for e-learning, developed for the students of “UVPL: Université Virtuelle des Pays de la Loire”. The developed e-learning system covers three levels of learning activities - content, exercises, and laboratory. The delivery model is designed to operate with domain concepts as relevant providers of semantic links. The aim is to facilitate the overview and to help the establishment of a mental map of the learning material. The implemented system is strongly based on the organization of the instruction in virtual classes. The obtained quality of the system is evaluated on the bases of feedback form students and professors

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Adaptive Course Generation in Semantic Web Context

International audiencePersonalized support for learners becomes very important in the context of increasing re-use of resources from heterogeneous and distributed learning repositories. This paper presents OrPAF, an Adaptive Educational Hypermedia (AEHS) and web-based System which integrates semantic web models and technologies like ontologies, semantic annotations and learning standards in order to achieve interoperability with e-learning systems. The key feature of OrPAF is the construction of adaptive hypermedia courses: both the course structure and the course content are dynamically generated and adapted to learners. On the one hand, a learning ontology is proposed to describe, at meta-level, abstract characteristics of an e-learning system. This learning ontology is instantiated to construct learning models: domain model, learner model and pedagogical model. On the other hand, semantic annotations and a semantic relevance measure are proposed to improve the LOM metadata associated to learning web resources in order to reuse and share them

A personalized adaptive e-learning approach based on semantic web technology

Recent developments in semantic web technologies heightened the need for online adaptive learning environment. Adaptive learning is an important research topic in the field of web-based systems as there are no fixed learning paths which are appropriate for all learners. However, most studies in this field have only focused on learning styles and habits of learners. Far too little attention has been paid on understanding the ability of learners. Therefore, it is becoming increasingly difficult to ignore adaptation in the field of e-learning systems. Many researchers are adopting semantic web technologies to find new ways for designing adaptive learning systems based on describing knowledge using ontological models. Ontologies have the potential to design content and learner models required to create adaptive e-learning systems based on various characteristics of learners. The aim of this paper is to present an ontology-based approach to develop adaptive e-learning system based on the design of semantic content, learner and domain models to tailor the teaching process for individual learner’s needs. The proposed new adaptive e-learning has the ability to support personalization based on learner’s ability, learning style, preferences and levels of knowledge. In our approach the ontological user profile is updated based on achieved learner’s abilities

An e-learning application based on the semantic web technology

The paper describes a framework for the implementation of an elearning system based on the Semantic Web, using software agents and Java Web Services. Hopefully we have elucidated the enormous potential of making web content machine-understandable. One of the killer applications for the Semantic Web might prove to be related to e-learning, considering the amount of research in this sector and the advantages those applications bring to the table compared to existing web-based learning courses.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

A Novel Adaptive Learning Management System Using Ontology

The success of web technologies has prompted a developing consideration on e-learning activities. Notwithstanding, most current e-Learning systems give static web-based learning with the goal that learners get to the same learning contents through the web, regardless of individual learners profiles. These learners may have altogether different learning foundations, information levels, learning styles, and capacities. The 'one size fit all' in an e-Learning frameworks is unmistakably a commonplace issue. To defeat this impediment and build powerful learning, versatile and customized learning is as of now a dynamic examination range. This paper propose a novel approach for designing and implementing adaptive learning management system based on ontology and semantic web technologies by offering a tailored model which represents the different activities that should be completed by learner. It offers a framework that is based on both learning styles and ontology to address the impact of student behavior

Knowledge visualization by Doctus Knowledge Galaxy

Making an attempt to develop a curriculum for web-based learning, we have realized that the existing solutions have adopted the traditional content management principles of printed books. By doing so, these solutions do not make use of benefits of a web-based system, namely the multimedia and the interactivity. Our new solution puts these benefits into the focus. Combining the features of semantic networks, cognitive maps and machine learning, we have developed a new generation knowledge visualization tool called Doctus Knowledge Galaxy shell. In our solution the topics and keywords are not in a sequential order, thus enabling the e-learner to choose her/his own learning route. The monitoring system of Doctus Knowledge Galaxy also allow us to observe how much time the learner spends on particular keywords and which next keyword she/he chooses after concluding a previous one by passing the test. The most important achievement of Doctus Knowledge Galaxy is its clear and transparent structure, which enables the learners into fast navigation and provides the developers with useful information about the learning routes and performance of the learner

Flexible virtual learning environments: a schema-driven approach using sematic web concepts

Flexible e-Iearning refers to an intelligent educational mechanism that focuses on simulating and improving traditional education as far as possible on the Web by integrating various electronic approaches, technologies, and equipment. This mechanism aims to promote the personalized development and management of e-learning Web services and applications. The main value of this method is that it provides high-powered individualization in pedagogy for students and staff.Here, the thesis mainly studied three problems in meeting the practical requirements of users in education. The first question is how a range of teaching styles (e.g. command and guided discovery) can be supported. The second one is how varieties of instructional processes can be authored. The third question is how these processes can be controlled by learners and educators in terms of their personalized needs during the execution of instruction.In this research, through investigating the existing e-Iearning approaches and technologies, the main technical problems of current virtual learning environments (VLEs) were analyzed. Next, by using the Semantic Web concepts as well as relevant standards, a schema-driven approach was created. This method can support users' individualized operations in the Web-based education. Then, a flexible e-learning system based on the approach was designed and implemented to map a range of extensive didactic paradigms. Finally, a case study was completed to evaluate the research results. The main findings of the assessment were that the flexible VLE implemented a range of teaching styles and the personalized creation and control of educational processes

Quality Web Information Retrieval: Towards Improving Semantic Recommender Systems with Friendsourcing

Web content quality is crucial in any domains, but it is even more critical in the health and e-learning ones. Users need to retrieve information that is precise, believable, and relevant to their problem. With the exponential growth of web contents, Recommender System has become indispensable for discovering quality information that might interest or be needed by web users. Quality-based Recommender Systems take into account quality criteria like credibility, believability, readability. In this paper, we present an approach to conceive Social Semantic Recommender Systems. In this approach a friendsourcing strategy is applied to better adequate recommendations to the user needs. The friendsourcing strategy focuses on the use of social force to assess quality of web content. In this paper we introduce the main research issues of this approach and detail the road-map we are following in the QHIR Project