Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning

scholarly journals Enhancing e-Learning Content by Using Semantic Web Technologies

2017 ◽  
Vol 10 (4) ◽  
pp. 544-550 ◽  
Author(s):  
Herminio Garcia-Gonzalez ◽  
Jose Emilio Labra Gayo ◽  
MPuerto Paule-Ruiz
Keyword(s):  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Learning Content ◽  
E Learning

An Ontology-Based e-Learning Scenario

2011 ◽  
pp. 63-71
Author(s):  
WenYing Guo
Keyword(s):  
Semantic Web ◽  
Relevant Information ◽  
Learning System ◽  
Semantic Mapping ◽  
Application Domain ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Mapping Approach ◽  
E Learning ◽  
Heterogeneous Knowledge

Selecting appropriate learning services for a learner from a large number of heterogeneous knowledge sources is a complex and challenging task. This chapter illustrates and discusses how Semantic Web technologies can be applied to e-learning system to help learner in selecting appropriate learning course or retrieving relevant information. It firstly presents the main features of e-learning scenario and the ontology on which it is based; then illustrates the scenario ontology with the training domain and the application domain. Finally, it presents Semantic Querying and Semantic Mapping approach.

An application of intelligent techniques and semantic web technologies in e-learning environments

2009 ◽  
Vol 36 (2) ◽  
pp. 1922-1931 ◽  
Author(s):  
Anatoly Gladun ◽  
Julia Rogushina ◽  
Francisco Garcı´a-Sanchez ◽  
Rodrigo Martínez-Béjar ◽  
Jesualdo Tomás Fernández-Breis
Keyword(s):  
Semantic Web ◽  
Learning Environments ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning

scholarly journals Weaving a Semantic Web of Credibility Reviews for Explainable Misinformation Detection (Extended Abstract)

2021 ◽  
Author(s):  
Ronald Denaux ◽  
Martino Mensio ◽  
Jose Manuel Gomez-Perez ◽  
Harith Alani
Keyword(s):  
Deep Learning ◽  
Semantic Web ◽  
Computational Model ◽  
State Of The Art ◽  
Learning Systems ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Detection Systems ◽  
Wide Range

This paper summarises work where we combined semantic web technologies with deep learning systems to obtain state-of-the art explainable misinformation detection. We proposed a conceptual and computational model to describe a wide range of misinformation detection systems based around the concepts of credibility and reviews. We described how Credibility Reviews (CRs) can be used to build networks of distributed bots that collaborate for misinformation detection which we evaluated by building a prototype based on publicly available datasets and deep learning models.

Classroom for the Semantic Web

2005 ◽  
pp. 251-283 ◽  
Author(s):  
Goran Shimic ◽  
Dragan Gasevic ◽  
Vladan Devedzic
Keyword(s):  
Semantic Web ◽  
Petri Net ◽  
Learning Systems ◽  
Learning Materials ◽  
Semantic Web Technologies ◽  
Web Based ◽  
Tutoring Systems ◽  
Web Technologies ◽  
E Learning ◽  
Server System

This chapter emphasizes integration of Semantic Web technologies in intelligent learning systems by giving a proposal for an intelligent learning management system (ILMS) architecture we named Multitutor. This system is a Web-based environment forth development of e-learning courses and for the use of them by the students. Multitutor is designed as a Web-classroom client-server system, ontologically founded, and is built using modern intelligent and Web-related technologies. This system enables the teachers to develop tutoring systems for any course. The teacher has to define the metadata of the course: chapters, the lessons and the tests, the references of the learning materials. We also show how the Multitutor system can be employed to develop learning systems that use ontologically created learning materials as well as Web services. As an illustration we describe a simple Petri net teaching system that is based on the Petrinet infrastructure for the Semantic Web.

Towards the Educational Semantic Web

2011 ◽  
pp. 145-172 ◽  
Author(s):  
Juan Manuel Adan-Coello ◽  
Carlos Miguel Tobar ◽  
João Luís Garcia Rosa ◽  
Ricardo Luís de Freitas
Keyword(s):  
Semantic Web ◽  
Information Overload ◽  
Educational Institutions ◽  
Educational Systems ◽  
Human Intervention ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning ◽  
The Creation ◽  
The Web

The objective of this chapter is to discuss relevant applications of Semantic Web technologies in the field of education, emphasizing experiences that point out trends and paths that can make the educational Semantic Web a reality. The Semantic Web, through metadata, comes to make it possible that resources of every type could be localized, retrieved and processed without human intervention, helping to reduce the information overload of the current Web. The possibility of describing resources using metadata that can be processed by computers simplifies the creation of self-organizing networks of learners, information, authors, teachers, and educational institutions. The adoption of Semantic Web technologies in the e-learning field contributes to the construction of flexible and intelligent educational systems, allowing reuse, integration, and interoperation of educational and noneducational resources (content and services) distributed over the Web.

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