Mamdani Fuzzy Model for Learning Activities Evaluation
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Date
2014-03-05
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Applied Information Systems (IJAIS)
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.