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Mamdani Fuzzy Model for Learning Activities Evaluation

by Isiaka Rafiu M., Omidiora Elijah O, Olabiyisi Stephen O, Okediran Oladotun O
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 3
Year of Publication: 2014
Authors: Isiaka Rafiu M., Omidiora Elijah O, Olabiyisi Stephen O, Okediran Oladotun O
10.5120/ijais14-451155

Isiaka Rafiu M., Omidiora Elijah O, Olabiyisi Stephen O, Okediran Oladotun O . Mamdani Fuzzy Model for Learning Activities Evaluation. International Journal of Applied Information Systems. 7, 3 ( May 2014), 1-8. DOI=10.5120/ijais14-451155

@article{ 10.5120/ijais14-451155,
author = { Isiaka Rafiu M., Omidiora Elijah O, Olabiyisi Stephen O, Okediran Oladotun O },
title = { Mamdani Fuzzy Model for Learning Activities Evaluation },
journal = { International Journal of Applied Information Systems },
issue_date = { May 2014 },
volume = { 7 },
number = { 3 },
month = { May },
year = { 2014 },
issn = { 2249-0868 },
pages = { 1-8 },
numpages = {9},
url = { https://www.ijais.org/archives/volume7/number3/627-1155/ },
doi = { 10.5120/ijais14-451155 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T18:54:44.486719+05:30
%A Isiaka Rafiu M.
%A Omidiora Elijah O
%A Olabiyisi Stephen O
%A Okediran Oladotun O
%T Mamdani Fuzzy Model for Learning Activities Evaluation
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 7
%N 3
%P 1-8
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The intent of this paper is to determine the extent to which fuzzy model could suitably modelled learner activities in E-learning system. However, the paucity of public dataset that meet the exact requirement of this work poses challenges, which necessitate dataset simulation. The detail approach used for the dataset simulation and the fuzzy model were discussed. Construction of the Inference Mechanism using the Relational Calculus and Mamdani approaches were demonstrated. The performance of the simulated model in MATLAB was measured using classifier uncertainty and confusion based metrics. The Mean Absolute Error (MAE) is 10. 45; Root Mean Square Error (RMSE) is 8. 71. The result shows that Fuzzy logic (White-Box Model) has a low classification error and invariably a higher accuracy for estimating learner activities. Subsequently, the result obtained shall be revalidated using live data of students' activities in an online course. Furthermore, the current Mamdani's model performance shall be compared with its equivalent Neuro_Fuzzy Model. The more efficient of the two models shall be the choice for integration into an Open Source Learning Management System for automatic learning activities evaluation.

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Index Terms

Computer Science
Information Sciences

Keywords

Learner Activities Simulated Dataset Relational Calculus and Fuzzy Logic.

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