Abstract
E-learning involves the computer and network-enabled transfer of skills and knowledge. The internet has become a central core to the educative environment experienced by learners, hence facilitating learning at any location and at any time thus creating pervasive learning environments. There is a growing interest in developing e-Learning platforms which enable the creation of personalized learning environments to suit the students' individual requirements and needs. However, the vast majority of the existing adaptive educational systems do not learn from the users' behaviors to create white box models which could handle the linguistic uncertainties and could be easily read and analyzed by the lay user. This paper presents a type-2 fuzzy logic based system that can learn the users' preferred knowledge delivery based on the students characteristics to generate a personalized learning environment. The type-2 fuzzy model is first created from data acquired from a number of students with different capabilities and needs. The learnt type-2 fuzzy-based model is then used to improve the knowledge delivery to the various students based on their individual characteristics. We will show how the presented system enables customizing the learning environments to improve individualized knowledge delivery to students which can result in enhancing the students' performance. The proposed system is able to continuously respond and adapt to students' needs on a highly individualized basis. Thus, online courses can be structured to deliver customized education to the student based upon various criteria of individual needs and characteristics. The efficiency of the proposed system has been tested through various experiments with the participation of 17 students. These experiments indicate the ability of the proposed type-2 fuzzy logic based system to handle the linguistic uncertainties to produce better performance than the type-1 based fuzzy systems.