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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
A Multi_Agent Advisor System for Maximizing E-Learning of an E-Course
Digital Object Identifier (DOI) : 10.14569/IJARAI.2014.030501
Article Published in International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 5, 2014.
Abstract: Web-based learning environments have become popular in e-teaching throw WWW as a distance learning. There is an urgent need to enhance e-learning to be suitable to the level of learner knowledge. The presented paper uses intelligent multi-agent technology to advise and help learners to maximize their learning of an offered e-course. It will build its advices on the performance and level of education of learners including past and current learning. Most of advices are to guide learner to make exercises as quizzes or passing tests in different level of difficulties.
Keywords: AI; Agent; Multi_Agents; distant learning; e-Learning; e-Teaching; Education; e-Course
Khaled Nasser ElSayed, “A Multi_Agent Advisor System for Maximizing E-Learning of an E-Course” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(5), 2014. http://dx.doi.org/10.14569/IJARAI.2014.030501
@article{ElSayed2014,
title = {A Multi_Agent Advisor System for Maximizing E-Learning of an E-Course},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.030501},
url = {http://dx.doi.org/10.14569/IJARAI.2014.030501},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {5},
author = {Khaled Nasser ElSayed}
}
