A Model For Enhancing The Structure And Strategy In An E-Learning Environment

Abstract

In the domain of E-learning, hundreds of dimensions can be taken and predictions can be made based on the browsing history of the users. Nowadays, web-based learning becomes an alternate to face to face education and E-learning becomes an effective tool in the learning process. E-Learning paves way for the learners to interact with the digitally delivered content and services. It focuses on making the learners to become more interested and efficient in their study process. This paper aims at designing strategies that will improvise the structure, assessment criteria and course completion rate in an e-learning environment. To achieve this aim, the following sub-objectives have been framed. The first objective is to provide a well-defined structure of the course whereas the second objective focuses on designing an e-learning system with specific assessment criteria. The third objective aims at achieving high completion rates for the registered students. By framing a defined structure, various assessment criteria can be fixed and calculated for a given student data set. Finally the active participation of enrolled candidates can be examined frequently. Machine Learning algorithms can be used efficiently in order to handle data in large amount.