AUTHORS: Mona Hafez Mahmoud

Download as PDF

ABSTRACT: Intelligent agent has been around for years, but the actual implementation is still in its early stages. This research is a scientific mix between two big topics of Artificial Intelligence. These topics are: the Intelligent Agents and the Intelligent Tutoring System. An Intelligent Agent is a set of independent software tools that are linked with other applications and database software running within a computer environment. The primary function of an Intelligent Agent is to help a user (client) to better interact with a computer application. It is assumed that artificial intelligence (AI) is involved and certain degree of autonomous problem solving ability is presented in agent-based technology systems[1]. Intelligent Tutoring Systems (ITSs) simulates the one-to one human tutor for delivering knowledge interactively instead of using books and the traditional learning environment. To come up with the most learning outcomes, ITSs have incorporated several techniques such as: error identification and correction, and building consistent explanations through integrating techniques of cognitive science and Artificial Intelligence. Different tutoring systems have been implemented to cover different subjects and languages such as: English, Arabic, Chinese, German and many others [2]. In this research ITS is covering grammar of Arabic language. The global structure of ITS consists of mainly four modules: a pedagogic module, a question selector module, an expert module and a student module in addition to a user interface module. But in this system we didn’t need an expert module because we used Constraints Based Model (CBM) technology (that will be explained below). This work is implemented under a project that is called AG_TUTOR (Arabic Grammar tutor). This project simulates the behavior of instructors and students and the relations between them in teaching the course of the Arabic Grammar of the fourth grade of the elementary stage in Egypt. In this system the technology of Intelligent Agents is used. This research concentrates on the Intelligent Agents part of AG_TUTOR

KEYWORDS: Artificial Intelligence and education, Intelligent Tutoring System, Intelligent Agents, Multi-Agents systems, knowledge base, domain knowledge

REFERENCES:

[1] A. Jafari, 'Conceptualizing Intelligent Agents For Teaching and Learning', Educause Quarterly number 3, pp. 28-34, 2002.

[2] M. Al Emran, K. Shaalan, 'A Survey of Intelligent Language Tutoring Systems', International Conference on Advances in Computing, Communications and Informatics (ICACCI), Delhi-India, pp. 393-399, 2014.

[3] https://en.wikipedia.org/wiki/Software_agent

[4]https://en.wikipedia.org/wiki/Intelligent_agent

[5] V. M. Ramesh, N. J. Rao, 'Tutoring and Expert Modules of Intelligent Tutoring Systems', A Technical Report presented to the International Institute of Information Technology, Electronics City, Bangalore, 2010.

[6] S. Ramachandran, E. Remolina, D. Fu, 'FlexiTrainer: A Visual Authoring Framework for Case-Based Intelligent Tutoring Systems', Proceeding of ITS 2004: Intelligent Tutoring Systems conference, pp 848-850, 2004.

[7] C. S. Blanc, “High-level Petri nets with data structures”, In European Workshop on Application and Theory of Petri nets, pp. 141– 170, Helsinki, Finland, June 1985.

[8] E. de B. Costa, M.A. Lopes, and E. Ferneda, ” MATHEMA: A learning environment based on a multi-agent architecture”, In LNAI, volume 991, pages 141–150, October 1995.

[9] N. R. Jennings and M. Wooldridge, 'Applications of Intelligent Agents', Queen Mary & Westfield College University of London, Agent Technology © Springer-Verlag Berlin Heidelberg. 1998

[10] D. Chin, 'The UNIX Consultant as an Intelligent Agent', Newsletter, ACM SIGCHI Bulletin, Volume 20 Issue 1, page 77, ACM New York, USA, July 1988.

[11] S. Chakraborty, D. Roy, A. Basu, “Development of Knowledge Based Intelligent Tutoring System”, Chapter 5, TMRF e-Book Advanced Knowledge Based Systems: Model, Applications & Research (Eds. Sajja & Akerkar), Vol. 1, pp 74 – 100, 2010.

[12] P. Brusilovsky, D. W. Cooper, 'ADAPTS: Adaptive Hypermedia for a Web-based Performance Support System', The Second Workshop on Adaptive Systems and User Modeling on the World Wide Web, Pittsburgh, USA, 1998.

[13] F.H. Roth, D. A. Waterman, D. A, Lenat,'Building Expert Systems', AddisonWesley Publishing, ISBN 0-201-10686-8, 1983.

[14] Y. Akbulut, C. S. Cardak, 'Adaptive Educational Hypermedia Accommodating Learning Styles: A Content Analysis of Publications from 2000 to 2011', Computers and Education 58, Elsevier, pp. 835-842, 2012.

[15]https://en.wikipedia.org/wiki/Intelligent_ tutoring_system

[16] C. Mills, B. Dalgarno, 'A Conceptual Model for Game Based Intelligent Tutoring Systems', The Proceedings of Ascilite Singapore: Mills and Dalgarno, pp.692-702, 2007.

[17] A. Mitrovic, S. Ohlsson, “Evaluation of a Constraint-Based Tutor for a Database Language”, International Journal of Artificial Intelligence in Education, pp. 238-256, 1999.

[18] N. Khodeir, 'Student Modeling for Arabic Language Skills in Intelligent Language Tutoring Systems”, International Journal of Computer Science and Information Security (IJCSIS), Vol. 13, No. 11, November 2015.

[19] D. N. CHIN, “Intelligent Interface as Agents”, CHAPTER9 in “Intelligent User Interfaces, Addison-Wesley Reading, MA, pp. 127–206, 1991.

[20] O. P. Rishi, R. Govil, M. Sinha, “Distributed Case Based Reasoning for Intelligent Tutoring System: An Agent Based Student Modeling Paradigm”, Engineering and Technology International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering Vol:1, No:5, pp. 111- 114, 2007.