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Information Journal Paper

Title

Using Educational Data Mining for Grouping Learners in an E-Learning Environment for Customizing Learning Program

Writers

DEYPIR M. | Raboo a.

Pages

 Start Page 83 | End Page 108

Abstract

 Customized learning systems have higher performance in comparison to traditional systems for learners. This is also true for electronic learning (e-learning). It is essential to have such customized mechanism for effective learning process. Recently, educational data mining methods are widely used in order to enhance the learning process. In fact, by using data mining techniques, it is possible to recognize learners and create a customized learning program in a better way. In this paper, a new model to cluster learners based on their learning style has been proposed. In this model, for learners, using Felder-Solomon questionnaire different dimensions of Felder and Silverman learning style are measured. Subsequently, using k-means clustering algorithm, the learners are categorized in different groups. In order to evaluate the model, it has been used and evaluated in a real learning program. Evaluation results show the effectiveness of the proposed model since the learners showed better educational performance. Moreover, the training process became more exciting for them.

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