STUDENTS' PERSONAL-TYPOLOGICAL FEATURES IN NETWORK BEHAVIOR

Human activity in the information space is a promising direction of modern psychological research. The modern information-psychological space expands the scope of personal freedom. Internet resources offer opportunities for using various sources of information: gender-role experimentation; variability of self-expression and self-presentation. Thus, the network space is an information-psychological space, where individual-typological characteristics of participants manifest themselves. This paper deals with theoretical grounds of studying students' personal individuality in the information-psychological space. The gender and age characteristics, level of proficiency and experience of work with technologies, degree of interest, orientation and motivation aspects are manifestations of personal individuality in the online interactions. The individual features manifest themselves in the psychological relation to information technology. Individual characteristics determine features of network activity, preferences of certain types of activities. Some author's models represent a typological approach to personal individuality in the information space. The authors used a complex of methods. Original and author's techniques were psychodiagnostic tools of research. The representativeness of the sample and mathematical data processing confirmed the reliability of the results. The paper analyzed the results of the empirical study of the individual-typological features of students' personality in the online interactions. According to the type and degree of involvement, the authors described three types of network behavior of the students participating in the online interactions. The authors also made a comparative analysis of the results of the study of network behavior depending on students' professional training. Structural and correlation analysis showed stable properties and interrelations inherit in various strategies of network activity. The paper presents generalized profiles of the main types of network activity considering individual-typological personal features of students.