Using neural networks in building a psychological typology

Abstract

The results of the relationship between psychological signs and the assessment of their significance in the situation of student adaptation to new socio-cultural conditions using the model of the neural network of ART 2 are presented.The external and internal factors that influence the adaptation of students to the new sociocultural environment are determined. The structure of the neural network model and its learning algorithm are developed. The standardization of scales made it easier to process the results. Using the software product of ART 2-self-regulation, a model of neural networks was created on the factors of adaptation of students to the training group and educational activities. On the basis of the peak indicators of the neural network, four clusters were identified that allow students to conduct a typology of regulatory and personal indicators of adaptation processes. Cross-cultural characteristics of representatives of each cluster are established. Thus, the”Initiative” cluster included indicators with peak values:”entry into social contact” (0,253),”flexibility” (0,224),”seeking social support” (0,213),”aggressive actions” (0,157),”modeling” (0,106). The main group of students demonstrating the patterns of adaptive behavior are students from Tajikistan. In the cluster”Inert” included indicators:”assertive actions” (0,264),”cautious actions” (0,190),”programming” (0,184),”avoidance” (0,183),”indirect actions” (0,158). The peak values of the”Stereotyped” cluster received scales:”impulsive actions” (0,260),”faults” (0,168),”antisocial actions” (0,166),”perceived hostility” (0,152),”evaluation of results” (0.130). The cluster of the model, called”Closed”, combined indicators with peak values:”total level of acculturation stress” (0.169),”perceived discrimination” (0,127),”cultural shock” (0,161)”nonspecific problems” (0,145),”separation” (0,172)