期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2013
卷号：10
期号：3
出版社：IJCSI Press
摘要：Educational Data Mining is concerned with developing methods for exploring data that come from educational domains, and using those methods to better understand learner, and how they interact with those environments. In this research, we benefit from a new preprocessing approach applied to Moodle platform [1] [2] in order to apply clustering and association rule mining techniques to analyze learners behaviors, to help in learning evaluation, and to enhance the structure of a given SCORM content. We adopted the feature selection process and multilevel clustering that allowed us to confirm the importance of these new data preprocessing methods and to validate the usefulness of the attributes describing the learners\' interactions with the SCORM content pertaining to learners profiles detection. We also benefited from this approach as we sought to find possible relationships between the different parts of the relevant content and to help the teacher/ tutor to evaluate the structure of such content.
关键词：Educational data mining; Moodle; preprocessing; clustering; association rule mining; learning profiles
