A Comprehensive Framework for Adaptive E-Learning Management System

Abstract

The various e-Learning systems in recent times found to be ineffective in directing the individual learning style with the preferred learning abilities. Focusing on this inadequacy, this paper proposes a comprehensive study from the different styles on the existing frameworks engaging an adaptive learning algorithm that applies a data stream technique using Machine Learning for a better learning path. The adaptation process insists or allow the user to modify the parameters and to adapt the behaviour according to the system assumption. When the system adapts to a personal concept and responds, it is said to be a personalized process. This concentrate and generates more ideas and style towards student-centric learning and creating a new learning path for an individual or group of learners. This generic framework is grounded on four-dimension. This framework tailors the learning style according to the individual learning types by creating a specific learning objective by incorporating learning modules, personalization and learner Noesis with technologies