Synoptic Adaptation Framework for E-learning Administration Using BFS and DFS
Abstract
E-Learning system embarks on the progress to the adaptable system which asserts or colonized the learner’s cognizance. System conjectures the features of the learners then recognize the inclination of the learner and spontaneously generate an idiomatic learning path, custom-tailored learning content to the needs of an individual. This is known as adaptation. The intention of this investigation is to contribute a synoptic e-learning administration framework that exteriorizes the learning experience incoherent way by applying Breath-First search and Depth-First Search in AI technique to provoke a dynamic learning path which is a feasible learning path to the learner. This feasible path is convenient for the learners with three learning styles namely Auditory, Visual, and Kinesthetic.