The development and improvement of effective tools for predicting human behavior in real life through the features of its virtual activity opens up broad prospects for psychological support of the individual. The presence of such tools can be used by psychologists in educational, professional and other areas in the formation of trajectories of harmonious person's development.Currently, active research is underway to determine psychological characteristics based on publicly available data. Such studies develop the direction of "Psychology of social networks". As markers for determining the psychological characteristics of people, various parameters obtained from their personal pages in social networks are used (texts of posts and reposts, the number of different elements on the page, statistical information about audio and video recordings, information about groups, and others). There is a difficulty in obtaining and analyzing a data set this big, as there are non-linear and hidden relationships between individual data elements. As a result, the classic methods of information processing become inefficient. Therefore, in our work to develop a comprehensive model of success based on the analysis of qualitative and quantitative data, we use an approach based on artificial neural networks. The labels of the input records are used to divide the subjects of the study into five clusters using clustering methods (kmeans). In the course of our work, we gradually expand the set of input parameters to include metrics of users' personal pages, and compare the results to determine the impact of qualitative parameters on the accuracy of the artificial neural network. The results reflect the solution of one of the tasks of the research carried out within the framework of the project of the Russian Science Foundation and serve as material for an information and analytical system for automatic forecasting of human life activity based on the metrics of his personal profile in the social network VKontakte.

The pandemic has created a push for changes in education and technology that are driving progress in all areas of instruction. This impetus is forcing all stakeholders to address the transformation of traditional education into online education. This change in the education system requires students and teachers to train new competencies, knowledge, skills, and abilities. In this context, this paper aimed to determine the psychophysiological strain of university students in relation to distance learning during the pandemic COVID-19. For this aim, quantitative data collection was conducted in this research. The results indicated that the distance learning format increased neuropsychic strain, decreased mood, activity, and wellbeing, and increased situational anxiety in college students. Based on the obtained results, social pedagogical educational technologies were developed, and hybridity, interactivity, multiformat, and feedback were identified as the main factors for their success. Pedagogical implications for teaching in higher education are presented.

No abstract

No abstract

This research focuses on examining the effects of university field courses on distance education and the integration of distance education into courses. A group of 357 university students studying biomedical engineering at universities in the Kosovo region and the Russian Federation volunteered to participate in the research.  A quantitative research method was used in the study. In the research, the "Distance Education" measurement tool developed by the researchers was used as a data collection tool. The questionnaire was developed and edited by experts in the field. Data were collected using an online survey. The collected data were ana-lysed using the SPSS program. Frequency, percentage, mean, standard deviation, minimum and maximum values, one-way ANOVA and T-test were applied to analyse the data obtained from the Distance Education measurement tool. This re-search concluded  that the majority of university students consider them-selves competent enough to use distance education technologies in the learning environment in the field courses, and they do not have difficulty using the systems in the field courses and their universities do not have sufficient equipment for the use of distance education technologies.

No abstract

Objective.  In the modern world, innovative technologies are actively developing, communications are moving into the Internet space. Nevertheless, new technologies turned out to be in demand in the segment of organizations, individuals, cyber fraudsters and hackers. The purpose of the study is to analyze the essence and structure of modern social engineering, including reverse social engineering in the context of the digitalization of society.Method. Adapting the study to the current moment, it is clarified that technologies, developments and manipulative sociological tactics are picked up not just by hackers, but also by followers of radical ideas.Result. The optimal definition of the term "social engineering" is proposed - the identification and exploitation of incompetence, insufficient professional level or negligence of employees of an organization or individuals to obtain unauthorized access to confidential data; a set of technologies based on the use of the psychological specifics of a person.Conclusion. The novelty of the study lies in an in-depth study of the classification of types of attacks using social engineering methods and recommendations for countering and preventing them.

No abstract