Анна Олеговна Табуева

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.

The article is devoted to the study of preferences in choosing STEM fields (S – science, T – technology, E – engineering, M – mathematics) and psychological characteristics of students who prefer these areas as a future profession. It should be noted that despite the ever-increasing demand of modern technological society for STEM specialists in the last decade, there has been a decrease in the interest of young people in these professions all over the world. In order to overcome this negative trend, it is necessary to understand the causes of this phenomenon, including the study of the psychological characteristics of students choosing STEM professions. The results showed that in terms of both cognitive and non-cognitive characteristics, students choosing STEM professions differ significantly from students choosing other professions. The study also showed that young men more often (70.5%) prefer professions related to STEM fields than girls (49.2%). Low representation and interest of girls in STEM fields, as well as low awareness of young people about these fields pose important practical tasks for organizing career guidance work in the education system. The authors examined a number of practical measures to change the current situation.

Введение. Современные требования к профессиональной деятельности в научно-технических областях подчеркивают необходимость учета как инженерных, так и пространственных способностей при отборе студентов для углубленного обучения в STEM-дисциплинах. Комплексная оценка этих навыков может повысить эффективность обучения и увеличить количество высококвалифицированных специалистов в STEM-секторе. Целью настоящего исследования являлась разработка валидной и надежной шкалы, направленной на оценку собственных пространственных и инженерных способностей. Методы. Выборка составила 5062 учащихся высших учебных заведений России в возрасте от 18 до 25 лет (средний возраст 18,35 лет). В рамках анализа психометрических свойств шкалы применялся эксплораторный, конфирматорный и многогрупповой факторный анализ. Результаты. Факторный анализ выявил четырехфакторную структуру из 10 утверждений, показатели соответствия модели находилась в диапазоне отличных значений. Выявленные факторы «Ориентация», «Инженерия», «Вращение» и «Визуализация» в совокупности объясняли 52% общей дисперсии. Факторные нагрузки варьировались от 0,72 до 0,98, что подтверждает высокую надежность каждого отдельного утверждения. Показатель альфа Кронбаха для всей шкалы составил 0,85, указывая на высокую внутреннюю согласованность. Сравнительный анализ средних значений для верхних и нижних 27% выборки продемонстрировал значимые различия по всем пунктам шкалы. Анализ средних значений в гендерных группах выявил значимые различия по четырем выявленным факторам. Анализ инвариантности измерений показал, что шкала соответствует конфигурационной, слабой и сильной типам инвариантности. Обсуждение результатов. Факторная структура шкалы соответствует представлению о пространственных способностях «большого» и «малого» масштаба. Новизна данного исследования заключается в валидизации первой русскоязычной шкалы, обеспечивающей краткую и комплексную оценку как пространственных, так и инженерных способностей, что имеет важное значение для образовательной и профессиональной практики.

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.

Approximate number sense is the ability to evaluate quantitative information without using symbols. The system of nonsymbolic numerosity representation is associated with the evaluation of non-numerical visual characteristics; with the congruency effect reflects this relationship. The congruency effect is considered as the difference in accuracy between congruent items in which non-numerical visual parameters positively correlate with quantitative ones, and non-congruent tasks in non-symbolic comparison tests. The article discusses two main theories explaining the process of nonsymbolic numerosity representation, in particular, the theory of the "number sense" and the sensory integration theory. Each of these theories suggests different explanatory models of the congruency effect, such as the inhibition model and the Attentional bias induced by stimulus control (ABC) model. In the experimental study, it was investigated to what extent the changes of the congruency effect depend on the format of the presentation of stimuli and the duration of stimuli presentation. In a sample of 97 students, a nonsymbolic comparison test was used in two formats, mixed (when the compared sets of objects are not spatially separated from each other) and separated. Each person performed nonsymbolic numerosity comparison tasks under conditions of short time presentation of stimuli (400 ms) and long time presentation of stimuli (1000 ms). For analysis of results generalized linear mixed effects models were applied. The results indicate that the congruency effect decreases under conditions of longer presentation of stimuli, however, this change is found only in the separated format of presentation of stimuli. In a mixed presentation format, when the assessment of visual parameters becomes less confident, there is no congruence effect. With an increase in the duration of presentation of stimuli, it becomes the opposite, i.e. the accuracy of nonsymbolic comparison in incongruent tasks has become higher than in congruent ones. Generally speaking, the results are in line with the “number sense” theory and have been elaborated upon. In general, the nonsymbolic numerosity representation considered as the adaptive and fluent interaction of two processes – the direct evaluation of numerosity and the evaluation of non-numerical visual cues.

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.

The aim of the present study was to investigate whether EEG resting state connectivity correlates with intelligence. One-hundred and sixty five participants took part in the study. Six minutes of eyes closed EEG resting state was recorded for each participant. Graph theoretical connectivity metrics were calculated separately for two well-established synchronization measures [weighted Phase Lag Index (wPLI) and Imaginary Coherence (iMCOH)] and for sensor- and source EEG space. Non-verbal intelligence was measured with Raven’s Progressive Matrices. In line with the Neural Efficiency Hypothesis, path lengths characteristics of the brain networks (Average and Characteristic Path lengths, Diameter and Closeness Centrality) within alpha band range were significantly correlated with non-verbal intelligence for sensor space but no for source space. According to our results, variance in non-verbal intelligence measure can be mainly explained by the graph metrics built from the networks that include both weak and strong connections between the nodes.