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Reseach Article

Intelligent Agents in Learning Environment ABDITS

by Shweta Mahlawat, O.P. Rishi, Praveen Dhyani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 12
Year of Publication: 2015
Authors: Shweta Mahlawat, O.P. Rishi, Praveen Dhyani
10.5120/ijca2015906550

Shweta Mahlawat, O.P. Rishi, Praveen Dhyani . Intelligent Agents in Learning Environment ABDITS. International Journal of Computer Applications. 127, 12 ( October 2015), 17-22. DOI=10.5120/ijca2015906550

@article{ 10.5120/ijca2015906550,
author = { Shweta Mahlawat, O.P. Rishi, Praveen Dhyani },
title = { Intelligent Agents in Learning Environment ABDITS },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 12 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number12/22780-2015906550/ },
doi = { 10.5120/ijca2015906550 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:19:43.201714+05:30
%A Shweta Mahlawat
%A O.P. Rishi
%A Praveen Dhyani
%T Intelligent Agents in Learning Environment ABDITS
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 12
%P 17-22
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a multiagent system i.e. named ABDITS (Agent Based Distributed Intelligent Tutoring System) is presented, which is customizable, dynamic, intelligent and adaptive with Pedagogy view for learners in intelligent schools. This system is an integration of adaptive web-based learning with expert systems as well. A crucial feature of the ABDITS personal agent is that the case based reasoning approach for student modeling. The system will categorize students in step with their skills in processing, perceiving, entering, organizing and understanding the knowledge. Intelligent agents are intended to examine the opportunities to enhance the teaching and to motivate the scholars to be told what they require, in an exceedingly user friendly environment that suits their learning style.

References
  1. Aamodt, A.; 2005, Knowledge Intesive Case-based reasoning and Intelligent tutoring system.
  2. Ang Yang, Ray Kemp, Kinshuk; 2001, Web based intelligent tutoring system.
  3. Brusilovsky, P. 1996. Methods and techniques of adaptive hypermedia. In User Modeling and User-Adapted Interaction, 87-129. Kluwer academic publishers.
  4. Brusilovsky, P. 1998. Adaptative educational systems on the world-wide-web: A review of available technologies. In Proceedings of Workshop WWW-Based Tutoring at Fourth International Conference on ITS (ITS’98). San Antonio, TX: Mit Press.
  5. B. Q. Pinto, C. R. Lopes, F. A. Dorça, M. A. Fernandes, “Intelligent Multiagent System for Distance Education Techinical Report”, Department of Computing/Federal University of Uberlândia, Uberlândia, Brazil, 01/2002. (In Portuguese)
  6. B. Q. Pinto, C. R. Lopes, M. A. Fernandes, “Using the IEEE LTSC LOM Standard in Instructional Planning”, Learning Technology publication of IEEE Computer Society, Volume 5 Issue 1, ISSN 1438-0625, January of 2003
  7. B. Queiroz, C. R. Lopes, M. A. Fernandes, “Automatic Curriculum Generation for a Web-Based Educational System”, International Conference on Computers in Education (ICCE 2002), Auckland. Supplementary Proceedings. Palmerston: Massey University, 2002, pp. 26-28.
  8. Dent, L.; Boticario, J. G.; McDermott, J.; Mitchell, T. M.; and Zabowski, D. T. 1992. A personal learning apprentice. In Proceedings of the Tenth National Conference on Artificial Intelligence, 96-103. San Jose, CA: Mit Press.
  9. “Draft Standard for Learning Object Metadata”, IEEE Learning Technology Standards Committee (LTSC), [database online], April 18 2001: [cited Jun. 12, 2002]. Available http://ltsc.ieee.org/doc/wg12/LOM_WD6-1_1.pdf
  10. Genesereth, M., and Fikes, R. 1992. Knowledge interchange format, version 3.0 reference manual. Technical Report KSL-92-86, Knowledge Systems Laboratory.
  11. G. Zlotkin and J. Rosenschein, “Negotiation and task sharing among autonomous agents in cooperative domains,” in Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, 1989, pp. 912–917.
  12. G. Weiss, editor. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. The MIT Press, Cambridge, MA, 1999.
  13. H. Chalupsky et al., “Electric elves: Agent technology for supporting human organizations,” AI Magazine, Summer 2002.
  14. H. Shi, Y. Shang, A. Joshi, and M. Jurczyk. Laboratory-oriented teaching in web and distributed computing. In Proc. 2000 ASEE Annual Conference & Exposition, St. Louis, June 2000.
  15. J. E. Beck and B. P. Woolf. Using a learning agent with a student model. In B. P. Goettl, H. M. Hal
  16. K. Sycara, M. Paolucci, M. van Velsen, and J. Giampapa, “The RETSINA MAS infrastructure,” special joint issue of Autonomous Agents and MAS, vol. 7, no. 1 and 2, July 2003.
  17. M. Allouche, O. Boisser, and C. Sayettat, Temporal social reasoning in dynamic multi-agent systems, in Proceedings of the Fourth International Conference on Multi-Agent Systems (ICMAS-2000). IEEE Computer Society, 2000, pp. 23–28.
  18. M. K. Stern and B. P. Woolf. Curriculum sequencing in a Web-based tutor. In B. P. Goettl, H. M. Hal, C.L.Redeld, and V. J. Shute, editors, Intelligence Tutoring System (Proc. 4th Int'l Conf. ITS'98), pages 584{593. Springer, 1998.
  19. N. Capuano, et al., “ABITS: An Agent Based Intelligent Tutoring System for Distance Learning”, Proceedings of the International Workshop on Adaptive and Intelligent Web-based Educational Systems, Montreal, Canada, 2000.
  20. Y. Shang, C. Sapp, and H. Shi. An intelligent web representative. Information, 3(2):253-262, 2000.
  21. Y. Shang and H. Shi. A web-based multi-agent system for interpreting medical images. World Wide Web, 2(4):209{218, 1999
  22. .M. R. Felder and L. Silverman, “Learning and Teaching Styles in Engineering Education”, In Engineering Education 78(7), 1988, pp. 674-681.
  23. Habitat-ProTM Environment, Agents Inspired Technologies S.A, University of Girona, Girona, Spain, 2001.http://www.agentsinspired.com.
  24. Diagnostic instrument for the FSLSM model http://www2.ncsu.edu/unity/lockers/users/f/felder/public/ILSdir/ilsweb.html
Index Terms

Computer Science
Information Sciences

Keywords

ABDITS FSLSM CBR ILS Habitatpro etc