Design of an intelligent and personalised e learning framework using machine learning techniques

Abstract

The proliferation of WWW and internet technologies has soared to greater extent over the past decade and learning anytime anywhere has become promising. This autarchy has become a godsend for the learners around the world to learn through online environments and thus paved the way for improved access to the learning contents available over the open repositories. With the advent of contemporary communication technologies, e-learning has emerged as a ubiquitous entity and made learning more flexible. One-size fits all approach is a major snag as most e-learning systems primarily focus only to harness the power of the ICT and deliver the learning contents in similar formats. The question on the suitability of delivering same learning contents for the diverse target audiences (learners) is not accounted in current e-learning systems. The extent to which the digital learning contents called Learning Objects have catered the need of learners is not in a quantifiable format due to the lack of understanding and oversight about the profile of learning objects and the diverse learner characteristics. newlineOur research work addressed the issues with the presentation style and category of the learning contents delivered through online learning environments and understanding the extent to which they can cater the learning requirements. This in turn helped to device dynamic policies and models and for personalising and recommending the suitable learning contents for the learners. The ultimate aim of this proposed work is to map the requirements of the learners with the capabilities/styles of learning objects in order to identify the suitable LOs at each learning instance of the learning cycle. newline