Journal of Software Engineering & Software Testing ISSN: 2457-0516 (Online)

Author: Sajid.M.Momin, Amol.B.Rajmane

Abstract: In the e-learning context, a recommender system is a software agent that tries to "intelligently" recommend actions to a learner based on previous learners' actions. These recommendation systems have been tried in e-commerce to entice purchasing of goods, but haven't been tried in e-learning. The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment.

 

The proposed system is based on four modules: Web search Module, student Profiling Module, Behavioral Activity analyzer module, and recommendation module. The web search Module is a way of searching for anything that the user or student wants from the Google search engine. A student Profiling Module takes Students all Personal and Academic Information, and Behavioral Activity analyzer module is used to identify learners learning preferences and all activities which are done at the time of web surfing by students and a recommendation module which pre-processes data to create a suitable recommendation list and predicting the student interest domain. After the recommendation process, we calculate the Knowledge Point (KP) of a particular student based on KP value it categories the student into three levels 1. Beginner 2. Intermediate 3. Master. Several techniques, such as classification, clustering, and association rules, are used to improve personalization with filtering techniques to provide a recommendation and help learners improve their performance.

 

The e-learning field research has gained more and more attention thanks to the recent explosive use of the Internet. However, Web-based learning environments are becoming very popular. In a virtual classroom, educators provide text, multimedia and simulations, and moderate and animate discussions. Remote learners are encouraged to peruse the resources and participate in activities.