Artem Malykh

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.

Context and relevance. The relevance of a longitudinal analysis of cause-and-effect relationships between verbal-logical thinking and the acquisition of reading skills stems from the need to address a fundamental problem in psychology—the relationship between mental development and learning. In practical psychology, this research is associated with the search for early individual psychological markers of potential learning difficulties. The processes of mental development and learning to read are closely interrelated throughout general education, but the direction and strength of these causal relationships may change during the transition from preschool to the initial stage of general education. Objective. This study examines the interplay between verbal-logical thinking and reading skills during the transition from kindergarten to the first grade of primary school. Methods and materials. A total of 260 children (50,1% female) participated in the study at two time points: during their preschool preparatory groups (Mage = 6,82, SD = 0,3) and one year later, following the completion of their first year of primary education (Mage = 7,83, SD = 0,3). Verbal-logical thinking was assessed using a mental development test measuring abstraction, classification and generalization, and analogical reasoning. Reading proficiency was evaluated according to reading method, ranging from non-reading to reading in whole words. Data were analyzed using cross-lagged panel structural equation modeling. Results. The analysis of cross-lagged relationships revealed a bidirectional nature of the relationship between verbal-logical thinking and reading proficiency during the transition from preschool to primary school. The most pronounced direct proportional effect was observed in the direction where the level of reading proficiency achieved by the end of the preschool period influences the subsequent development of cognitive operations—abstraction, classification and generalization, and analogical reasoning—at the onset of formal schooling. Conclusions. The specific nature of the causal relationship between the development of verbal-logical thinking and reading acquisition was identified and interpreted within the framework of cultural-historical psychology.

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.

This cross-country four-year longitudinal study investigated the development of processing speed throughout primary school education. The analyses were conducted on data accumulated from 441 pupils in grades from 1 to 4 (aged 6.42 to 11.85 years) in Kyrgyzstan and Russia. Mixed effects growth modeling was applied to estimate average and individual growth trajectories for processing speed in two cross-country samples. Latent class growth modeling was conducted to describe various types of growth trajectories for processing speed and to compare the distribution of the types within the analyzed samples. According to the results, processing speed significantly increases across primary school years. The trajectory is described by nonlinear changes with most dynamic growth between grades 1 and 2, which slows down until grade 4. No significant cross-country differences were found in the initial score of processing speed or developmental changes in processing speed across primary school years. The development of processing speed is described by a model including three quadratic growth types but this minimally differs. It is concluded that in both samples, the development of processing speed may be characterized by homogeneity, with the most intensive growth from grade 1 to grade 2 and subsequent linear improvement until grade 4.

This cross-country four-year longitudinal study investigated the development of processing speed throughout primary school education. The analyses were conducted on data collected from 441 schoolchildren in Grades 1, 2, 3 and 4 (aged 6.42 to 11.85 years) in the Kyrgyzstan and Russia. Mixed effects growth modeling was applied to estimate average and individual growth trajectories for processing speed at two cross-country samples. Latent class growth modeling was conducted to identify different types of growth trajectories for processing speed and to compare the distribution of the types within the analyzed samples. According to the results, processing speed significantly increases across primary school years. The trajectory is characterized by nonlinear changes with more intensive growth between Grades 1 and 2, which later slows down until Grade 4. There were no significant cross-country differences in the initial score of processing speed or developmental changes in processing speed across primary school years. The development of processing speed is described by a model with three quadratic growth types but minimally differs. It is concluded that in both samples, the development of processing speed may be characterized by homogeneity, with the most intensive growth from Grade 1 to Grade 2 and subsequent linear improvement until Grade 4.

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.

Background: Number line accuracy (NL accuracy) shows improvement over the course of a school education. However, there are practically no cross‐country longitudinal studies of NL accuracy over the whole course of elementary school. Aims: This study investigated the developmental trajectories of NL accuracy and its types across the elementary school years in two countries—Russia and Kyrgyzstan. Sample(s): The analyses were carried out on the data collected from the sample of 508 schoolchildren at Grades 1, 2, 3 and 4 (aged 6.4–11.9 years) from Russia and Kyrgyzstan, who were surveyed as part of the ‘Cross‐cultural Longitudinal Analysis of Student Success’ project. Methods: The participants were administered the ‘Number Line’ computerized test task and a paper‐and‐pencil ‘Standard Progressive Matrices’ test at the end of each academic year. Results: During the course of the elementary school education, NL accuracy increases nonlinearly in both samples from Grade 1 to Grade 4, with a pronounced increase in the rate of improvement from the first to the second year. Cross‐country differences in NL accuracy were observed during each year of schooling as well as in the growth of NL accuracy. The development of NL accuracy is described by a model with two developmental types: (1) ‘high start and growth’ (93% of the pooled sample) and (2) ‘low start and no growth’ (7%). Conclusions: Both NL accuracy and the rate of its growth during elementary school depend on educational conditions. Cross‐country differences in the distribution of schoolchildren by these two developmental types were statistically insignificant.