Providing education and training to the masses on gigantic scale, for economic survival and to meet the ever-changing requirements of the society and also to meet the individual's special requirements and tastes, is not possible through the conventional system of education based on brick-and-mortar schools, colleges and universities. The World Wide Web (WWW) is being used to improve communication, collaboration, sharing of resources, promoting active learning, and delivery of education in distance learning mode. Distance Education, E-learning and Virtual Universities may provide the desired solution. E-Learning may be taken as the latest form of distance learning mediated by state-of-art technologies like Internet and WorldWide Web. In recent years, many of the universities and educational institutions worldwide offer online services such as for admissions, virtual (online) learning environments in order to facilitate the lifelong learning and to make this compatible with other educational management activities. Current e-learning research brings together pedagogical, technical and organisational concerns within a wider set of socio-cultural factors. Understanding issues &challenges in respect of elearning is of significant importance to the research communities involved in e-learning and will have a significant role in forming future practices. In consulting the INDIA research community, a number of research issues & challenges are required to be addressed to promote more efficient learning techniques.

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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.

Despite significant progress in e-learning technology over previous years, in view of huge sizes of data and databases, efficient knowledge extraction techniques are still required to make e-learning effective tool for delivery of learning. Rough set theory approach provides an effective technique for extraction of knowledge out of massive data. In order to provide effective support to learners, it is essential to know individual style of learning for each learner. For determining learning style of each learner, one is required to extract essentials of style of learning from a large number of parameters including academic background, profession, time available etc. In such scenario, rough theory proves a useful tool. In this paper, a rough set theory approach is proposed for determining learning styles of learners efficiently, so that based on the style, a learner may be provided learning support on the basis of requirement of the learner. These is achieved by eliminating redundant and ambiguous data and by generating reduct set, core set and rules from the given data. The results of this study are validated through RSES software by using same rough set analysis.

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