Using Educational data mining in order to grouping learners in a e-learning environment for customizing learning program

In the information era, customizing learning process is very important in most learning systems. E-learning as a learning system requires a customized mechanism for better learning process. Recently, educational data mining methods are widely used in the context of e-learning systems. In fact, using data mining techniques, researchers try to better recognize learners and create a customized learning program. 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 shows the effectiveness of the proposed model since the learners show better educational performance. Moreover, training process become more.