An interactive virtual e-learning framework using crowdsourced analytics

Abstract

These days clients are keen on distance learning as there is a quick development in digital data because of everyday improvement in data just as computer technology. Presently, YouTube is the world-wide method for video sharing. It is having sure constraints such as, having idleness in Web-based learning. In online investigation learners anticipating some additional rules from given assets. This work first investigation dependent on dynamic learning and video-based learning ways to deal with stem training, universal learning and afterward exhibit the blend of micro lecture and Web learning to propose a novel method of micro-learning. Details are exhibited of a micro lecture Web learning framework that can support multi stages. The framework consolidates intelligent push, video explanation, Lucene full-text hunt, clustering analysis and different advancements. We propose a gathering commitment score that considers both individual movement and comparability of participation, consequently enables restorative moves to be made when not engaged learners or gatherings are distinguished. The stage enables learners to get to micro lecture videos and other excellent micro lecture assets wherever and whenever they like, in whatever time intervals they have accessible. Educators can get statistical analysis results of the micro lecture in MWLS (Micro Lecture Web Learning system) to give teaching/learning feedback and a powerful correspondence stage. MWLS advances the improvement of micro lecture.