Abstract
The growth of e-learning is expanding tremendously. In this context, LMS is software for handling various management related activities in respect of learning and its delivery in online mode. The proposed system provides the learning content according to learner's learning style using the extracted rule. Rough sets may be seen as an emerging tool & technique for extracting knowledge from a large set of data. Rough set theory is particularly useful for discovering relationships and used to deal with imprecise or incomplete data. This is a case study in which we suggest an effective way to extract rule which can decide learner's learning style in e-learning environments through RSES software. In this study, we used concept of reducts to extract appropriate knowledge from large datasets and calculate confidence factor for conflicting rules. Rough Set Theory in e-learning environment can bring immense potential and will make E-learning procedure more interesting, decision friendly, and user friendly. The proposed system will be able to increase efficiency of learning as providing learning contents based on learner's style.
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