Abstract

NOSOVA, Lyudmila et al. Development of an applied intellectual system based on neurophysiological data to support decision-making in the organization of the educational process. Conrado [online]. 2022, vol.18, n.88, pp. 199-205.  Epub Oct 30, 2022. ISSN 1990-8644.

In modern science, one of the urgent problems is the search for ways to improve the teaching effectiveness. The study of neurophysiological patterns in the formation of individual variations of cognitive activity of students at various stages of ontogenesis is a condition for solving the problems of developing innovative technologies to improve the quality of the educational process. The paper describes the process of developing an applied intellectual system that allows using individual differences in cognitive activity of students and schoolchildren identified using neuroscience technologies. The use of methods and techniques of training organization is largely due to individual typological features that can be analyzed using neurobiological indicators. The individual neurophysiological profile express analysis characterizes behavioral aspects of cognitive activity. With the help of an intelligent system, a complex of neurophysiological indicators of groups of students was processed to identify the influence of learning conditions on these indicators. Based on the data sets obtained during the tests, the system forms the distribution of students into groups, project teams or pairs and recommends study activities depending on their neurophysiological profile.

Keywords : Artificial intelligence; Machine learning; Applied intellectual system; Neurophysiological profile; Individual educational trajectory.