scholarly journals Dynamic Assembly of Personalized Learning Content on the Semantic Web

2006 ◽  
pp. 545-559 ◽  
Author(s):  
Jelena Jovanović ◽  
Dragan Gašević ◽  
Vladan Devedžić
Keyword(s):  
Semantic Web ◽  
Personalized Learning ◽  
Learning Content ◽  
Dynamic Assembly

A Personalized Learning System Based on Semantic Web Technologies

2011 ◽  
pp. 258-284
Author(s):  
Funda Dag ◽  
Kadir Erkan
Keyword(s):  
Learning Environment ◽  
Semantic Web ◽  
Learning Style ◽  
Web Application ◽  
Personalized Learning ◽  
Domain Model ◽  
Learning System ◽  
Semantic Web Technologies ◽  
Learning Content ◽  
Cognitive Knowledge

In this study, a personalized learning system framework that is KOULearn (Kocaeli University Learning System) has been proposed. It is based on learning object and produces a personalized learning content according to learning style and cognitive knowledge level of an individual. The proposed framework is situated in advanced learning technologies according to educational perspective and is a semantic web application according to development technologies. The proposed framework is aimed to form a personalized learning environment. Three models are included in this system: domain model, user model and adaptation model, respectively. Components of the system have been realized by ontology based knowledge modeling approach. Execution of the personalized learning content structure and learning environment of the system, related to electric education, has been examined by resonance learning module which is constituted considering personalization requirements of the system.

scholarly journals Automatic Generation and Evolution of Personalized Curriculum Based on Genetic Algorithm

2019 ◽  
Vol 14 (12) ◽  
pp. 15
Author(s):  
Xiaocong Duan
Keyword(s):  
Genetic Algorithm ◽  
Personalized Learning ◽  
Automatic Generation ◽  
User Model ◽  
Evolution System ◽  
Framework Structure ◽  
System Framework ◽  
Learning Efficiency ◽  
Learning Content ◽  
Generation Technology

In order to solve the automatic generation and evolution of personalized curriculum, the method of using genetic algorithm to realize the evolution of personalized learning content is proposed to solve the dynamic personalized needs of users. Through the research and implementation of personalized curriculum generation technology, firstly, the structures of curriculum generation, genetic algorithm and curriculum scene, as well as the method and technology of personalized curriculum generation and evolution system framework are described in detail. Then, the framework structure based on genetic algorithm is determined, and the user model is updated. Finally, experiments are carried out based on genetic algorithm. The research on the experiment of automatic generation and evolution of personalized curriculum shows that the application of genetic algorithm in the process of curriculum generation and evolution makes students' learning content evolve with the change of their knowledge state in the process of learning, effectively promotes students' interest in learning, and improves learning efficiency and effect.

LOCO-Analyst: semantic web technologies in learning content usage analysis

2008 ◽  
Vol 18 (1) ◽  
pp. 54 ◽  
Author(s):  
Jelena Jovanovic ◽  
Dragan Gasevic ◽  
Christopher Brooks ◽  
Vladan Devedzic ◽  
Marek Hatala ◽  
...  
Keyword(s):  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Learning Content ◽  
Usage Analysis

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

Localising E-Learning Websites in the Semantic Web Era

2010 ◽  
pp. 284-299
Author(s):  
Dimitris Kanellopoulos
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Learning Approach ◽  
Learning Framework ◽  
Learning Content ◽  
E Learning ◽  
Content Provision ◽  
Further Development

Recently, ontologies have been applied for localisation of e-learning content in order to promote existing learning services to semantic-aware and intelligent localisation services. This chapter presents a localisation-aware semantic e-learning approach to integrate multilingual content provision, learning process and learner personality in an integrated semantic e-learning framework. The author proposes an architecture for supporting localisation of e-learning content and describes a basis for further development of automatic localisation services that will be able to reason on top of such an explicit infrastructure.

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