An Ontology-Based e-Learning Scenario

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.

Semantic Web Technologies Applied to E-Learning System

International Journal of Computer Applications ◽

10.5120/7223-0053 ◽

2012 ◽

Vol 47 (10) ◽

pp. 12-17 ◽

Cited By ~ 3

Author(s):

Walid QassimQwaider

Keyword(s):

Semantic Web ◽

Learning System ◽

Web Technologies ◽

Application of Semantic Web Technologies to Facilitate Use of E-Learning System on Mobile Devices

Smart Education and e-Learning 2016 - Smart Innovation, Systems and Technologies ◽

10.1007/978-3-319-39690-3_42 ◽

2016 ◽

pp. 473-484

Author(s):

Boban Vesin ◽

Aleksandra Klašnja-Milićević ◽

Mirjana Ivanović

Keyword(s):

Semantic Web ◽

Mobile Devices ◽

Learning System ◽

Web Technologies ◽

Constructing a personalized e-learning system for students with autism based on soft semantic web technologies

2012 IEEE International Conference on Technology Enhanced Education (ICTEE) ◽

10.1109/ictee.2012.6208625 ◽

2012 ◽

Cited By ~ 9

Author(s):

M. V. Judy ◽

U. Krishnakumar ◽

A. G. Hari Narayanan

Keyword(s):

Semantic Web ◽

Learning System ◽

Web Technologies ◽

E Learning ◽

Students With Autism

Integration of the tagging mechanism in the collaborative e-learning system

Applied Computer Systems ◽

10.2478/v10312-012-0007-1 ◽

2012 ◽

Vol 13 (1) ◽

pp. 54-60

Author(s):

Andrejs Lesovskis ◽

Vladimirs Kotovs ◽

Leonids Novickis

Keyword(s):

Learning Environment ◽

Semantic Web ◽

Learning Systems ◽

Learning System ◽

Web Technologies ◽

Combined Use ◽

E Learning ◽

Machine Readable

Abstract - The tagging mechanism is a technique that can be used to implement the personalized collaboration in the e-Learning systems, thereby increasing the efficiency of such a system. Semantic Web technologies can be used to enhance tags with machine-readable annotations to improve the accuracy of tag-based recommendation services. The novelty of the proposed approach is the combined use of the Semantic Web technologies and the reuse-oriented model in the development of the e-Learning environment.

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽

10.15388/informatica.2015.46 ◽

2015 ◽

Vol 26 (2) ◽

pp. 221-240 ◽

Cited By ~ 2

Author(s):

Valentina Dagienė ◽

Daina Gudonienė ◽

Renata Burbaitė

Keyword(s):

Semantic Web ◽

Learning Models ◽

Web Technologies ◽

Enhancing e-Learning Content by Using Semantic Web Technologies

IEEE Transactions on Learning Technologies ◽

10.1109/tlt.2016.2629475 ◽

2017 ◽

Vol 10 (4) ◽

pp. 544-550 ◽

Cited By ~ 6

Author(s):

Herminio Garcia-Gonzalez ◽

Jose Emilio Labra Gayo ◽

MPuerto Paule-Ruiz

Keyword(s):

Semantic Web ◽

Web Technologies ◽

Learning Content ◽

Data Integration in the Geospatial Semantic Web

Cases on Semantic Interoperability for Information Systems Integration ◽

10.4018/978-1-60566-894-9.ch013 ◽

2011 ◽

pp. 272-293

Author(s):

Patrick Maué ◽

Sven Schade

Keyword(s):

Decision Support ◽

Semantic Web ◽

Real World ◽

Relevant Information ◽

Decision Makers ◽

Domain Experts ◽

Web Technologies ◽

Opening Up ◽

The Web

Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.

Capturing the Semantics of Simulation Learning with Linked Data

Gamification ◽

10.4018/978-1-4666-8200-9.ch013 ◽

2015 ◽

pp. 273-295 ◽

Cited By ~ 1

Author(s):

Irene Celino ◽

Daniele Dell'Aglio

Keyword(s):

Semantic Web ◽

Learning Environments ◽

Serious Games ◽

Linked Data ◽

Daily Practice ◽

Learning System ◽

Web Technologies ◽

Simulation Learning ◽

Learning Data

Knowledge-rich learning environments like simulation learning sessions call for the adoption of knowledge technologies to effectively manage information and data related to the learning supply and to the observation analysis. In this chapter, the authors illustrate the benefits and the challenges from the adoption of Linked Data and Semantic Web technologies to model, store, update, collect, and interpret learning data in simulation environments. The experience gained in applying this approach to a Simulation Learning system based on Serious Games proves the feasibility and the advantages of knowledge technologies in addressing and solving the issues faced by trainers and teachers in their daily practice.