Revealing strengths, weaknesses and prospects of intelligent collaborative e-learning systems

Abstract

The rapid evolution of Collaborative e-Learning Systems migrates to the use of new technologies such the artificial intelligence (AI). In this context, the role of AI in increasing the quality of learning and making it more productive, persistent and efficient. In addition, it can accomplish repetitive and complex tasks in record time and unmatched accuracy. These advantages offer the ability to interact with learners in an almost human way. This interaction could be made on the base of adaptive hypermedia techniques, Multi-agent Systems technology and a cognitive learner model. In this paper, we present and analyze some existing intelligent collaborative e-Learning systems on the basis of their various features such as collaboration features, intelligent actors' interaction, adaptability measurement, cognitive student modeling, and security measurement. Our analysis aims to provide important information to researchers, educators and software developers of educational environments concerning strengths and weaknesses of those e-Learning systems. According to this study, we found that some collaborative e-Learning environments, even the use of the mentioned technologies, still poor in terms of the structure of human cognitive architecture aspects and the capacity to assess the help provided to learners. For these reasons, we present, in the end, some prospects in order to determine how we can improve these systems to stop the reasons of abandoning courses.