Abstract: The expert module is an essential part of the intelligent tutoring system. This module uses only declarative knowledge, excluding other types of domain knowledge: procedural and conditional. This elimination makes the expert module very delicate. To solve this issue, the authors propose to embed knowledge processing into the expert model. The contribution aims to empower the expert model via the fragmentation of the knowledge process into four categories: Analyzation, Application, Conceptualization, and Experimentation using the Bayesian Network method as an instrument for modelling expert systems in uncertain areas. According to the management of the expert system through a list of criteria, the expert module can suggest the correct type of knowledge and their following status.

Fatima-Zohra Hibbi, Otman Abdoun and El Khatir Haimoudi, “Bayesian Network Modelling for Improved Knowledge Management of the Expert Model in the Intelligent Tutoring System” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130624

@article{Hibbi2022,
title = {Bayesian Network Modelling for Improved Knowledge Management of the Expert Model in the Intelligent Tutoring System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130624},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130624},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Fatima-Zohra Hibbi and Otman Abdoun and El Khatir Haimoudi}
}