SUMMARY OF THE PROJECT:     This research is not only to compare traditional teaching-learning methodology with the latest e-learning methodology, but also to suggest an optimal selection of learning materials and method of instruction to suit each and every individual who wants to learn in a non-face-to-face learning environment. Fundamentals of Computer Based Training [CBT] have been studied. The literature survey on various methods of instructions such as CD-ROM, e-books, web resources, repeated use of digital library resources have been studied. E-learning can be broadly classified in to online learning and offline learning. For online learning method, various learning materials are available in the web. In off line learning environment, resources include CD, DVD and other electronic multimedia resources which have learning materials.
In e-learning, the resources have to be identified for various types of learners. Learners are various types and various levels. Learners vary from fundamental schooling level to higher education level. When a learner wants to learn something, he has to be identified which level of learning he is expecting to learn and he has to be categorized. Once he is put in to a specified category, suitable learning materials have to be selected for him from various sources. In case of online learning, this is an extremely intelligent and complex job. Even though there are various methods are available to select suitable learning materials to him using data mining and data warehousing technologies, there is a scope to make more suitable selection of learning materials for a particular learner in each session of his learning. Studying various techniques and tools available for this purpose, I want to develop a better and an alternate method of selection of learning materials from a huge database source and to suggest an optimal method of instruction to a particular learner depending on his needs. For this research work, the semantic web technologies is being used along with e-learning technologies, data mining and warehousing technologies and other related topics.