scholarly journals Text Mining-Based Semantic Web Architecture (TMSWA) for e-Learning Systems

2014 ◽  
Vol 4 (4) ◽  
pp. 333-338
Author(s):  
Hamad Ibrahim Alomran
Keyword(s):  
Text Mining ◽  
Semantic Web ◽  
Learning Systems ◽  
Web Architecture ◽  
E Learning

scholarly journals Semantic Web Architecture and its Impact on E-learning Systems Development

2015 ◽  
Vol 10 (5) ◽  
pp. 29 ◽  
Author(s):  
Samir Abou El-Seoud ◽  
Hosam El-Sofany ◽  
Omar Karam
Keyword(s):  
Semantic Web ◽  
Semantic Representation ◽  
Learning Objects ◽  
Web Technology ◽  
Learning Systems ◽  
Learning Material ◽  
Semantic Web Technologies ◽  
Web Architecture ◽  
E Learning ◽  
Teaching Learning

The Semantic Web is the next giant step of the current web technology. The use and application of the Semantic Web in E-learning has been explored with regard to two areas: 1) software that supports instructors to perform their tasks in flexible online educational settings, and 2) software that interprets the structure of distributed, self organized, and self-directed web-based learning. These two application areas and related tasks require a semantic representation of educational entities and pedagogical material, specifically the structure and the techniques of the teaching-learning process. In most E-learning systems users are able to manage and reuse learning contents according to their needs without any access problems. The main objectives of this study are: how can e-learning take advantage of Semantic Web technology, and how to integrate the Semantic Web technologies with e-learning systems, taking into consideration the standards and reusable learning objects (LO), and to show the advantages of improving the descriptions of content, context and structure of the learning material. The main goal of this article it to introduce an updated E-learning model based on the latest Semantic Web architectures.

E-Learning and the Semantic Web

2015 ◽  
pp. 66-100 ◽  
Author(s):  
Raadila Bibi Mahmud Hajee Ahmud-Boodoo
Keyword(s):  
Higher Education ◽  
Semantic Web ◽  
Success Factors ◽  
Comprehensive Analysis ◽  
Learning Systems ◽  
Education Sector ◽  
Learning Models ◽  
Semantic Web Technology ◽  
Critical Success ◽  
E Learning

A number of 3.0 e-learning systems have been proposed in the literature to capture the numerous benefits that the Semantic Web has to offer to the higher education sector. These 3.0 e-learning systems identify some essential Semantic Web characteristics that are either discussed as stand-alone factors or tend to revolve around the complexities of the Semantic Web technology and its implementation, often disregarding users' needs. Conversely, a comprehensive analysis of e-learning models for higher education in the literature revealed several Critical Success Factors (CSFs) that are relevant to the Semantic Web but often overlooked in 3.0 e-learning models. Consequently, this chapter provides an overview of the CSFs of e-learning relevant to 3.0 e-learning systems as well as an overview of the main Semantic Web characteristics for e-learning to define a new and combined set of 3.0 e-learning characteristics that will holistically represent 3.0 e-learning systems capturing the needs and expectations of users. The new initial 3.0 e-learning model proposed is evaluated within the higher education sector in Mauritius.

SWELS

2010 ◽  
pp. 120-145
Author(s):  
Gianluca Elia ◽  
Giustina Secundo ◽  
Cesare Taurino
Keyword(s):  
Semantic Web ◽  
Learning Environments ◽  
First Generation ◽  
Learning Technologies ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
Distance Learning Technologies ◽  
Traditional Approaches ◽  
New Generation

This chapter presents a prototypal e-learning system based on the Semantic Web paradigm, called SWELS (Semantic Web E-Learning System). The chapter starts by introducing e-learning as an efficient and just-in-time tool supporting the learning processes. Then a brief description of the evolution of distance learning technologies will be provided, starting from first generation e-learning systems through the current Virtual Learning Environments and Managed Learning Environments, by underling the main differences between them and the need to introduce standards for e-learning with which to manage and overcome problems related to learning content personalization and updating. Furthermore, some limits of the traditional approaches and technologies for e-learning will be provided, by proposing the Semantic Web as an efficient and effective tool for implementing new generation e-Learning systems. In the last section of the chapter, the SWELS system is proposed by describing the methodology adopted for organizing and modeling its knowledge base, by illustrating its main functionalities, and by providing the design of the tool followed by the implementation choices. Finally, future developments of SWELS will be presented, together with some remarks regarding the benefits for the final user in using such system.

E-Learning and the Semantic Web

2016 ◽  
pp. 24-55
Author(s):  
Raadila Bibi Mahmud Hajee Ahmud-Boodoo
Keyword(s):  
Higher Education ◽  
Semantic Web ◽  
Success Factors ◽  
Comprehensive Analysis ◽  
Learning Systems ◽  
Education Sector ◽  
Learning Models ◽  
Semantic Web Technology ◽  
Critical Success ◽  
E Learning

A number of 3.0 e-learning systems have been proposed in the literature to capture the numerous benefits that the Semantic Web has to offer to the higher education sector. These 3.0 e-learning systems identify some essential Semantic Web characteristics that are either discussed as stand-alone factors or tend to revolve around the complexities of the Semantic Web technology and its implementation, often disregarding users' needs. Conversely, a comprehensive analysis of e-learning models for higher education in the literature revealed several Critical Success Factors (CSFs) that are relevant to the Semantic Web but often overlooked in 3.0 e-learning models. Consequently, this chapter provides an overview of the CSFs of e-learning relevant to 3.0 e-learning systems as well as an overview of the main Semantic Web characteristics for e-learning to define a new and combined set of 3.0 e-learning characteristics that will holistically represent 3.0 e-learning systems capturing the needs and expectations of users. The new initial 3.0 e-learning model proposed is evaluated within the higher education sector in Mauritius.

Ontologies in Intelligent Learning Systems

2012 ◽  
pp. 31-48
Author(s):  
Boryana Deliyska ◽  
Peter Manoilov
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Structural Learning ◽  
Principal Role ◽  
Web Resources ◽  
Human Tutor ◽  
E Learning

The intelligent learning systems provide a direct customized instruction to the learners without intervention of human tutor on the base of Semantic Web resources. The principal role ontologies play in these systems is as an instrument for modeling learning process, learner, learning objects, and resources. In the chapter, a variety of relationships and conceptualizations of ontologies used in the intelligent learning systems are investigated. The utilization of domain and application ontologies in learning object building and knowledge acquisition is represented. The conceptualization of domain ontologies in e-learning is presented by the upper levels of its taxonomies. Moreover, a method and an algorithm intended for generation of application ontologies of structural learning objects (curriculum, syllabus, topic plan, etc.) are developed. Examples of curriculum and syllabus application ontologies are given. Further these application ontologies are used for structural learning object generation.

Steps, techniques, and technologies for the development of intelligent applications based on Semantic Web Services: A case study in e-learning systems

2011 ◽  
Vol 24 (8) ◽  
pp. 1355-1367 ◽  
Author(s):  
Heitor Barros ◽  
Alan Silva ◽  
Evandro Costa ◽  
Ig Ibert Bittencourt ◽  
Olavo Holanda ◽  
...  
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Learning Systems ◽  
Semantic Web Services ◽  
E Learning

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.

E-Learning and the Semantic Web

2016 ◽  
pp. 11-40
Author(s):  
Raadila Bibi Mahmud Hajee Ahmud-Boodoo
Keyword(s):  
Higher Education ◽  
Semantic Web ◽  
Success Factors ◽  
Comprehensive Analysis ◽  
Learning Systems ◽  
Education Sector ◽  
Learning Models ◽  
Semantic Web Technology ◽  
Critical Success ◽  
E Learning

A number of 3.0 e-learning systems have been proposed in the literature to capture the numerous benefits that the Semantic Web has to offer to the higher education sector. These 3.0 e-learning systems identify some essential Semantic Web characteristics that are either discussed as stand-alone factors or tend to revolve around the complexities of the Semantic Web technology and its implementation, often disregarding users' needs. Conversely, a comprehensive analysis of e-learning models for higher education in the literature revealed several Critical Success Factors (CSFs) that are relevant to the Semantic Web but often overlooked in 3.0 e-learning models. Consequently, this chapter provides an overview of the CSFs of e-learning relevant to 3.0 e-learning systems as well as an overview of the main Semantic Web characteristics for e-learning to define a new and combined set of 3.0 e-learning characteristics that will holistically represent 3.0 e-learning systems capturing the needs and expectations of users. The new initial 3.0 e-learning model proposed is evaluated within the higher education sector in Mauritius.

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