Personalized Distance Learning Based on Multiagent Ontological System

Authors:
Igor Keleberda;Natalya Lesna;Sergiy Makovetskiy;Vagan Terziyan
Affiliations:
Kharkov National University of Radioelectronics;Kharkov National University of Radioelectronics;Kharkov National University of Radioelectronics;University of Jyvaskyla
Venue:
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Year:
2004

Citing 0
Cited 4

Building learner's ontologies to assist personalized search of learning objects

ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
An adjustable personalization of search and delivery of learning objects to learners

Expert Systems with Applications: An International Journal
The use of ontologies and rules to assist in academic advising

RuleML'07 Proceedings of the 2007 international conference on Advances in rule interchange and applications
A semantic approach to expert system for e-Assessment of credentials and competencies

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents architecture of a personalized distance learning system based on multiagent technology and ontological modelling of studentsý profiles. Delocalization of a student data in the system is achieved by software agents, which assumed to be distributed at different platforms. These platforms operate as separate Web services and use the ACL (Agent Communication Language) for the data transfer. In this paper the algorithm is proposed, according to which the Multiagent Ontological System for Personalized Distance Learning (MOSPDL) solves the tasks of distant learning process automation, which assume utilization of the ontological models of studentsý and learning resourcesý profiles.