CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

An Adaptive Course Materials Selection into a Multi-agent based e-Learning System

by Vanco Cabukovski, Roman Golubovski
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 144 - Number 8
Year of Publication: 2016
Authors: Vanco Cabukovski, Roman Golubovski
10.5120/ijca2016910401

Vanco Cabukovski, Roman Golubovski . An Adaptive Course Materials Selection into a Multi-agent based e-Learning System. International Journal of Computer Applications. 144, 8 ( Jun 2016), 4-8. DOI=10.5120/ijca2016910401

@article{ 10.5120/ijca2016910401,
author = { Vanco Cabukovski, Roman Golubovski },
title = { An Adaptive Course Materials Selection into a Multi-agent based e-Learning System },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 144 },
number = { 8 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 4-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume144/number8/25197-2016910401/ },
doi = { 10.5120/ijca2016910401 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:04.142176+05:30
%A Vanco Cabukovski
%A Roman Golubovski
%T An Adaptive Course Materials Selection into a Multi-agent based e-Learning System
%J International Journal of Computer Applications
%@ 0975-8887
%V 144
%N 8
%P 4-8
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Modern information and communication technologies are emerging in all segments of life, including education. Affordable digitalization and low-budget content development allow for virtually unlimited access to shared knowledge. Formal education is already more or less supported by such additional material everywhere. Methodologies are developed to support automation of content management, as well as to tailor-make material suggestions and delivery according to individual learner's preferences. Such an adaptive approach inevitably faces challenges like following individual learning habits and behaviour, maintaining an up-to-date knowledge and evaluation coordinative instances, along with credible low-budget media development keeping pace with the curricula evolution. An integrated Intelligent Agent-Based University Information System (IABUIS) is successfully implemented at the Faculty of Natural Sciences and Mathematics with the University Ss. Cyril and Methodius, in Skopje. An AeLS (Adaptive e-Learning System) within it, attempts to propagate faster individual learning curves by employing agent-based system consisted of agent-based algorithms for adaptive interaction with the consumers (students), and adaptive content/course selection and delivery of appropriate material intended for improved knowledge acquisition, thus better learning results - subject of official examination. This paper presents latest improvements in the user - AeLS interaction point.

References
  1. Cronbach, L..J., & Snow, R.E. 1977 Aptitudes and Instructional Methods: A handbook for research on interactions, New York: Irvington.
  2. Brusilovsky, P. 1999 “Adaptive hypermedia: from intelligent tutoring systems to web-based education”, Künstliche Intelligenz, No. 4, pp 19-25.
  3. Brusilovsky, P. 2001 “Adaptive hypermedia”, User Modeling and User Adapted Interaction, Vol. 11, No. 1/2, pp 87-110.
  4. Brusilovsky, P., and Peylo, C. 2003 “Adaptive and intelligent web-based educational systems”, International Journal of Artificial Intelligence in Education, No. 13, pp 156-169.
  5. Shute, V., and Towle, B. 2003 “Adaptive e-learning”, Educational Psychologist, Vol. 38, No. 2, pp 105-114.
  6. Cabukovski, V., and Tusevski, V. 2015 “An Additional Content Development Methodology in an Adaptive Agent Based e-Learning Environment”, Proceedings of the European Conference on e-Learning ICEL 2015, ed C Watson, Academic Conferences and Publishing International Limited, pp 58-65.
  7. Cabukovski, V. 2006 “An Agent-Based Testing Subsystem in an E-Learning Environment”, Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (WI-IATW’06), IEEE Computer Society, pp 622-625.
  8. Cabukovski, V. 2010 “An Intelligent eLearning Environment as a Part of an Integrated University Information System”, Proceedings of the 9th European Conference on eLearning, Academic Publishing Limited, Vol. 1, pp 90-95.
  9. Cabukovski, V. 2010 “Integrated Agent-Based University Information System”, Proceedings of The Second International Conference on Mobile, Hybrid, and On-Line Learning eL&mL 2010, IEEE Computer Society, pp 36-40.
  10. Cabukovski, V. 2011 “IABUIS – An Intelligent Agent-Based University Information System”, Lecture Notes in Information technology, Information Engineering Research Institute, USA, Vol. 3-4, pp 13-19.
  11. Davcev, D., and Cabukovski, V. 1998 “Agent-based University Intranet and Information System as a Basis for Distance Education and Open Learning”, Proceedings of 1st UICEE Annual Conference on Engineering Education – Globalization of Engineering Education, eds LePP Darvall & JZ Pudlowski, UNESCO International Centre for Engineering Education (UICEE), pp 253-257.
  12. Cabukovski, V., and Davcev, D. 1998 “MATHEIS (MATHematical Electronic Interactive System): An Agent-Based Distance Educational System for Learning Mathematics”, Proceedings International Conference on the Teaching of Mathematics, John Wiley & Sons, Inc. Publishers,  pp 59-61.
  13. Woolridge, M. 2002 Introduction to Multiagent Systems. John Wiley & Sons, Inc.
  14. Bordini, R.H., Dastani, M., and Dix, J. 2005 Multi-Agent Programming Languages. Platform and Applications, Springer, Berlin.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive e-learning system Intelligent agents Integrated university information system.