DOI
https://doi.org/10.1108/DTA-10-2018-0092

Summary
An adaptive e-learning system DAELMS is presented in the article. This system takes into account learner’s dyslexia type, knowledge level and learning style. The motivation of adaptive e-learning systems is discussed to emphasize the possibility to meet the individual students’ needs. The three main phases of developing DAELMS are listed. The phases consist of identifying requirements, designing the system, implementing the system. The implementation part is the most complex one, thus, the algorithms used for the adaptation with respect to dyslexia / non dyslexia, and knowledge level are explained with examples of possible scenarios. The authors conclude that the system can be used to generate a personalized learning path according to students’ domain knowledge level, learning style, dyslexia type.

Relevance for Complex Systems Knowledge
The authors present a complex e-learning system which was developed under the expertise of domain knowledge (for example, dyslexia type), learning styles, knowledge in artificial intelligence. This system combines knowledge in informatics (programming, information management and other subdomains) and educational practice (learning styles, assessment methods and others). The artificial intelligence is used in this system to select the most appropriate learning style for each student. The e-learning systems which provide personalized learning can be helpful in learning process and should be incorporated in the conventional learning systems. The generalized architecture on such adaptive system and its components can be reused in other subjects.

Point of Strength
The point of strength of this article is the described adaptive e-learning system as a scheme which can be applied to personalize learning experience in various fields (the example for students with dyslexia has been presented in the article).