چکیده (انگلیسی):

Extensive literature review revealed that, different recommender systems for E-learning were developed. A
preliminary version of the development was undertaken and evaluated in an experiment during an
introduction psychology course in an open university. The activities were integrated in to a model which
operates on a network. No curriculum structure was assigned and the users were allowed to undergo
learning activities in any order they wanted. Though voluminious work was reported on establishing bench
marks for learning process on a wide range basis, there are only discrete references on developing a system
comprising of a web-based typical learning environment which includes many aspects of learning such as
course content delivery tools, synchronous and asynchronous conferencing systems, quiz models, grade
reporting systems, creation of virtual class rooms. An attempt is made in this study to design and develop a
Recommender System (RS), in the form of a software agent giving recommendations based on the previous
observations. The developed RS suggests the applications of web mining techniques resulting in, on-line
learning activities and improving the course material navigation. The proposed RS combines a top down
ontology based recommendation techniques clubbed with bottom-up techniques. Both techniques were
combined in the RS, which decided, which of the techniques is more suitable for the current situation in which
a learner works. Finally the present work provides for recommendation strategies for a personal RS in Elearning
models for life long learners. The major contribution of the present work lies, in designing and
developing a RS in the form of a software agent, incorporating web mining techniques resulting in, on-line
learning activities, such as course content delivery tools, conferencing systems, creation of virtual class rooms.