Diagnostics of the Student’s Learning Style With the Use of Modern Information Technologies

The paper deals with learning styles and their initial diagnostics in the process of the student’s learning. It is focused on a method of learning styles recognition with the support of modern information technologies. The paper analyses different methods of the learning styles diagnostics, incorporating this issue into the scientific field of artificial intelligence and presents an idea on how to diagnose a learning style by using an unconventional fuzzy logic linguistic expert system. The expert system was designed to diagnose learning styles of university students in adaptive computer aided learning systems. A significant benefit is continuous numerical evaluation of the student’s degree of affiliation to all learning categories (types of student) with a possibility of simple determination of dominant and subdominant types, the use of a linguistic rule-based decision-making model, which is completely transparent and open, and the use of a decision-making procedure corresponding to the process of human consideration. The paper is an example of an application of modern information technologies in education.