An Adaptive eLearning Sequence Based on Neutrosophic Logic

Abstract

In recent years, e-learning has become a revolutionary competitive method. Adapting the content according to learner knowledge is a current challenge in e-learning systems. Currently, most of the e-learning systems evaluate the learner's knowledge level according to crisp responses that are taken during the learning process. Therefore, one of the most significant challenges in e-learning is how to improve the course adaptation in order to achieve high-quality interaction for all learners. Adaptation is an efficient way to help learners to learn their learning activities in easy and a suitable ways. However, there are many factors that lead to uncertainty about the learner evaluation process. This chapter presents a novel approach to handle imprecision, vagueness, ambiguity, and inconsistency in the learner evaluation process to recommend the suitable learning material according to the learner's knowledge level.