Pavel Kolyasnikov

This article presents the results of a study on cognitive and non-cognitive predictors of university educational profile choice. The sample included 6,290 students from 23 Russian univer- sities (37.6% males, 62.4% females, aged 17–24 years). Academic fields were aggregated into five macro-groups: humanities, natural sciences, pedagogy, social sciences and economics, and technical sciences. Cognitive abilities were assessed using intelligence tests (Raven’s matrices), working mem- ory, spatial abilities (rotation, visualization, relations), and reaction time. Non-cognitive character- istics were measured using questionnaires for math anxiety, mental toughness, and psychological well-being. Statistical analysis included multifactorial ANCOVA and predictive modeling using ran- dom forest. The results showed that the field of study is associated with differences in cognitive and personality profiles, with spatial abilities contributing the most (η ² up to 0.030). Students in techni- cal fields demonstrated higher cognitive performance, while humanities students exhibited lower well-being and higher math anxiety. Gender significantly affected spatial abilities and non-cognitive characteristics but not general intelligence or working memory. The combined machine learning model achieved an accuracy of 39.7% (against a baseline of 29.1%). A discrepancy between actual and desired major choice was found to be primarily related to cognitive mismatch. Gender-specific patterns were identified: spatial abilities play a leading role for males, whereas general intelligence and psychological well-being are more important for females. These findings can be applied in career guidance and educational practices.

The long-term psychological consequences of COVID-19 remain insufficiently understood in student populations. This study examined the association between post-COVID-19 consequences and psychological functioning in university students, focusing on the mediating role of trait anxiety. A total of 7482 students aged 17 to 23 years completed an online survey assessing COVID-19 history, post-COVID-19 consequences, psychological well-being (WHO-5), subjective happiness (SHS), life satisfaction (SWLS), and trait anxiety (STAI). Participants were classified into three groups: no history of COVID-19, COVID-19 without post-COVID-19 consequences, and COVID-19 with post-COVID-19 consequences. Group differences were analyzed using ANOVA with Tukey post hoc tests, followed by regression and mediation analyses controlling for age and sex. Students reporting post-COVID-19 consequences showed higher trait anxiety and lower psychological well-being, subjective happiness, and life satisfaction than both comparison groups. Regression analyses indicated that poorer psychological functioning was associated specifically with post-COVID-19 consequences rather than COVID-19 history per se. Mediation analyses among previously infected students showed that trait anxiety statistically mediated these associations, accounting for 61% of the effect on psychological well-being, 84% on subjective happiness, and 68% on life satisfaction. These findings highlight trait anxiety as an important psychological factor statistically accounting for the association between post-COVID-19 consequences and reduced well-being.

The choice of an educational and professional trajectory is an important stage in the life course and is associated with subsequent professional development and psychological well-being. The present study aims to analyze the motivational foundations of students’ choice of field of study, with a focus on differences between STEM and non-STEM fields as well as gender differences. An integrative approach is employed, combining methods of network psychometrics and person-oriented analysis. Using a sample of students enrolled in different programs (bachelor’s and specialist degrees) from 31 universities (N = 7,196; 64% female; 38% enrolled in STEM fields), the structure of interrelations among motives for choosing a field of study was reconstructed using an Ising model, and latent motivational profiles were identified via latent class analysis. The results show that motivation for choosing a field of study constitutes a connected system in which distinct clusters (e.g., social motives, pragmatic motives) and bridging nodes (e.g., intrinsic personal interest) can be identified. Latent class analysis revealed five motivational profiles, the distribution of which differs between STEM and non-STEM fields as well as between male and female students. The findings underscore the importance of a comprehensive approach to the study of motivation in the choice of field of study.

Life satisfaction is associated with adolescents’ adaptability, academic achievement, and mental health, and it reflects the profile of a country’s economic development. In this study, we assessed the psychometric properties of the Russian version of the Multidimensional Students’ Life Satisfaction Scale (MSLSS). The initial adaptation of the MSLSS was performed using a sample of primary school students. Validation on a sample of early-to-middle adolescents is necessary to assess its reliability and validity for this age group. The sample comprised 2826 adolescents between ages 10 and 16 (Mage = 12.6, SD = 1.2, 41.3% girls) who completed the Russian version of the MSLSS assessing their perceived life satisfaction across five scales. While the five-factor structure of the MSLSS was confirmed, the psychometric analysis indicated that the statements function more effectively measured life satisfaction as a singular one-factor construct. We also observed a significant age-related decline in overall life satisfaction and satisfaction with family, self, school, friends, and teachers. Boys reported significantly lower satisfaction with school compared to girls. This study confirms the validity and reliability of the Russian version of the MSLSS, thereby augmenting its general applicability. Furthermore, we replicated previously reported age and gender differences in life satisfaction among early-to-middle adolescents.

Contemporary digital platforms provide a large number of web services for learning and professional growth. In most cases, educational web services only control access when connecting to resources and platforms. However, for educational and similar resources (internet surveys, online research), which are characterized by interactive interaction with the platform, it is important to assess user engagement in the learning process. A fairly large body of research is devoted to assessing learner engagement based on automatic, semi-automatic, and manual methods. Those methods include self-observation, observation checklists, engagement tracing based on learner reaction time and accuracy, computer vision methods (analysis of facial expressions, gestures, and postures, eye movements), methods for analyzing body sensor data, etc. Computer vision and body sensor methods for assessing engagement give a more complete objective picture of the learner’s state for further analysis in comparison with the methods of engagement tracing based on learner’s reaction time, however, they require the presence of appropriate sensors, which may often not be applicable in a particular context. Sensory observation is explicit to the learner and is an additional stressor, such as knowing the learner is being captured by the webcam while solving a problem. Thus, the further development of the hidden engagement assessment methods is relevant, while new computationally efficient techniques of converting the initial signal about the learner’s reaction time to assess engagement can be applied. On the basis of the hypothesis about the randomness of the dynamics of the time series, the largest Lyapunov exponent can be calculated for the time series formed from the reaction time of learners during prolonged work with web interfaces to assess the learner’s engagement. A feature of the proposed engagement assessment method is the relatively high computational efficiency, absence of high traffic loads in comparison with computer vision as well as secrecy from the learner coupled with no processing of learner’s personal or physical data except the reaction time to questions displayed on the screen. The results of experimental studies on a large amount of data are presented, demonstrating the applicability of the selected technique for learner’s engagement assessment.

This study investigates the psychometric properties of brief COPE in Russian schoolteachers. A total of 773 (91% female; M = 43, SD = 9.79) teachers participated in the study. Principal component analysis (PCA) and confirmatory factor analysis (CFA) were applied to assess the psychometric properties of the brief COPE. The Perceived Stress Scale (PSS) was used to assess the construct validity. The main result of the current research is a revised structure for the brief COPE consisting of six sub-scales: «socio-emotional support», «religion», «acceptance», «problem-focused coping», «avoidance», and «humor». The goodness-of-fit criteria were as follows: SRMR = 0.054, RMSEA = 0.064, CFI = 0.888, and TLI = 869. Overall, the Russian version of the brief COPE shows acceptable psychometric properties and may be applied by researchers, school administrators, and psychologists; however, the reliability of the “avoidance” scale is doubtful and must be considered before application.

Web surveys are an integral part of the feedback of Internet services, a research tool for respondents, including in the field of health and psychology. Web technologies allow conducting research on large samples. For mental health, an important metric is reaction time in cognitive tests and in answering questions. The use of mobile devices such as smartphones and tablets has increased markedly in web surveys, so the impact of device types and operating systems needs to be investigated. This article proposes an architectural solution aimed at reducing the effect of device variability on the results of cognitive psychological experiments. An experiment was carried out to formulate the requirements for software and hardware. Three groups of 1000 respondents were considered, corresponding to three types of computers and operating systems: Mobile Device, Legacy PC, and Modern PC. The results obtained showed a slight bias in the estimates for each group. It is noticed that the error for a group of devices differs both upward and downward for various tasks in a psychological experiment. Thus, for cognitive tests, in which the reaction time is critical, an architectural solution was synthesized for conducting psychological research in a web browser. The proposed architectural solution considers the characteristics of the device used by participants to undergo research in the web platform and allows to restrict access from devices that do not meet the specified criteria.

The paper addresses the development of technology for controlling access to digital portals and platforms based on assessments of personal characteristics of user behavior built into the interface. In distributed digital platforms and portals using personal data, big data is collected and processed using specialized applications using computer networks. In accordance with the law, the data is stored on internal corporate servers and data centers. Special attention is paid to the tasks of differentiation and control of access in modern information systems. Wide availability and mass scale of services should be accompanied by more careful control and user verification. Access control to such systems cannot be ensured only through technologies and information security tools; efficiency can be increased through software and hardware architectural solutions. The paper proposes to expand the currently developing SIEM technology (Security information and event management), which combines the concept of security event management and information security management, with blocks of user behavior analysis. As a characteristic that can be measured without overloading communication channels and is independent of the type of device used, the psychomotor reaction time is proposed, measured as the performance of actions with the interface. A technological solution has been developed for implementation in a wide range of digital platforms: banking, medical, educational, etc. The results of experimental research using a digital platform of mass psychological research are presented. For the research, data from a mass survey were used when answering (in the form of a choice from the available options) to questions about the level of education. Analysis of the reaction time data showed the possibility of standardization and the same indicators of specific users when answering different questions.

Web-surveys are one of the most popular forms of primary data collection used for various researches. However, mass surveys involve some challenges. It is required to consider different platforms and browsers, as well as different data transfer rates using connections in different regions of the country. Ensuring guaranteed data delivery in these conditions should determine the right choice of technologies for implementing web-surveys. The paper describes the solution to transfer a questionnaire to the client side in the form of an archive. This technological solution ensures independence from the data transfer rate and the stability of the communication connection with significant survey filling time. The conducted survey benefited the service of education psychologists under the federal Ministry of Education. School psychologists consciously took part in the survey, realizing the importance of their opinion for organizing and improving their professional activities. The desire to answer open-ended questions in detail created a part of the answers in the dataset, where there were several sentences about different aspects of professional activity. An important challenge of the problem is the Russian language, for which there are not as many tools as for the languages more widespread in the world. The survey involved 20,443 school psychologists from all regions of the Russian Federation, both from urban and rural areas. The answers did not contain spam, runaround answers, and so on as evidenced by the average response time. For the surveys, an authoring development tool DigitalPsyTools.ru was used.