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Modeling Intelligent E-Learning Systems based on Adaptive Fuzzy Higher Order Petri Nets

by Mohamed Amin, Nabawia El-Ramly, Doaa Shebl
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 25 - Number 10
Year of Publication: 2011
Authors: Mohamed Amin, Nabawia El-Ramly, Doaa Shebl
10.5120/3151-4355

Mohamed Amin, Nabawia El-Ramly, Doaa Shebl . Modeling Intelligent E-Learning Systems based on Adaptive Fuzzy Higher Order Petri Nets. International Journal of Computer Applications. 25, 10 ( July 2011), 7-14. DOI=10.5120/3151-4355

@article{ 10.5120/3151-4355,
author = { Mohamed Amin, Nabawia El-Ramly, Doaa Shebl },
title = { Modeling Intelligent E-Learning Systems based on Adaptive Fuzzy Higher Order Petri Nets },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 25 },
number = { 10 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 7-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume25/number10/3151-4355/ },
doi = { 10.5120/3151-4355 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:38.917245+05:30
%A Mohamed Amin
%A Nabawia El-Ramly
%A Doaa Shebl
%T Modeling Intelligent E-Learning Systems based on Adaptive Fuzzy Higher Order Petri Nets
%J International Journal of Computer Applications
%@ 0975-8887
%V 25
%N 10
%P 7-14
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we introduce adaptive and intelligent technologies in E-learning course development using Modular Object Oriented Dynamic Learning Environment (Moodle) based on Petri nets as a modeling formalism. Since classical Petri nets and fuzzy Petri nets are not adaptable according to the changes of the new incoming data such as the parameters of Moodle (static course material, interactive course material, activities), we introduce adaptive fuzzy higher order Petri net (AFHOPN) that is dynamically adjust the parameters. AFHOPN helps to describe and analyze the dynamic behavior, production inference of the intelligent E-learning systems and measure the learning rate.

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Index Terms

Computer Science
Information Sciences

Keywords

Higher order Petri nets Fuzzy reasoning E-learning systems

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