Design and Implementation of an Adaptive Tutoring System for Enhanced E-Learning

Abstract

The increasing offer of new information and communication technologies has changed the educational field, e-learning emerged as an important complement to traditional face-to-face education and often a good alternative in many contexts. This shift has been emphasized by global challenges such as the COVID-19 pandemic, which highlighted the importance of remote learning platforms and their effectiveness in such situations. However, many challenges such as the costs and the need for personalized and interactive learning environments remain an obstacle. To address these issues, adaptive e-learning systems and Intelligent Tutoring Systems (ITS) are increasingly being developed and given support by education communities and governments. These systems aim to adapt content to the learner’s cognitive abilities and individual learning styles, for better understanding and retention. This paper explores the design and development of an adaptive ITS, which integrates Artificial Intelligence and data analytics to provide better learning experience. This paper puts the light on the role of adaptive hypermedia in educational interactions, analyzing its key features and how they can be leveraged to enhance learning outcomes. By incorporating learning success metrics, our study provides a comprehensive perspective on the potential of ITS to revolutionize adaptive and personalized e-learning systems, driving significant improvements in both learner engagement and achievement.