Application of user modeling and adaptation in e-learning based on learning styles

Abstract

The present Master’s dissertation aims to research the capabilities of adapting a learning management system to the individual needs of students based on their psychological profile. The issue is viewed from the perspective of cognitive psychology, by considering personal characteristics of the users and the respective learning styles, and from the perspective of artificial intelligence, by focusing on the implementation of this concept in e-learning systems. A systematic approach to this task allows to study the relationship between the individual characteristics of students and the necessary changes in learning systems to achieve a good level of adaptability.

The Master’s dissertation explores what techniques can be used to support adaptation of an e-learning system using an approach based on learning styles of its users. To achieve this goal, the following major tasks have been fulfilled in the work: 1) analysis of existing technologies for implementing user modeling and adaptation in general and in e-learning systems specifically; 2) review of personality scales that can be used as a psychological basis for defining learning styles of users; 3) analysis of methods of adaptation that can be applied at the level of planning the educational process to reflect personalization in the system based on individual characteristics.

The chapters of the Master’s dissertation are dedicated respectively to three major areas: User Modeling and Adaptation, Learning Styles, and Application of AI. The User Modeling and Adaptation chapter includes a general review of user modeling, adaptation and personalization techniques with specific interest in the adaptation capabilities in e-learning platforms. The Learning Styles chapter considers psychological aspects of learning, in particular, learning styles associated with different personality types, based on a review of the literature and studies relevant to the research topic. The Application of AI chapter proposes how the suggested personality scale can be incorporated into an e-learning platform using the capabilities of Artificial Intelligence, in particular, fuzzy logic and deep learning techniques