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Mamdani Fuzzy Model for Learning Activities Evaluation

Isiaka Rafiu M. , Omidiora Elijah O, Olabiyisi Stephen O, Okediran Oladotun O Published in Fuzzy Systems

International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
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  1. Isiaka Rafiu M., Omidiora Elijah O, Olabiyisi Stephen O and Okediran Oladotun O. Article: Mamdani Fuzzy Model for Learning Activities Evaluation. International Journal of Applied Information Systems 7(3):1-8, May 2014. BibTeX

    	author = "Isiaka Rafiu M. and Omidiora Elijah O and Olabiyisi Stephen O and Okediran Oladotun O",
    	title = "Article: Mamdani Fuzzy Model for Learning Activities Evaluation",
    	journal = "International Journal of Applied Information Systems",
    	year = 2014,
    	volume = 7,
    	number = 3,
    	pages = "1-8",
    	month = "May",
    	note = "Published by Foundation of Computer Science, New York, USA"


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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Learner Activities, Simulated Dataset, Relational Calculus and Fuzzy Logic.