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  • Диспозиционные факторы отношения к статистике у студентов, изучающих социальные науки: Настойчивость и академическая мотивация
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June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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Диспозиционные факторы отношения к статистике у студентов, изучающих социальные науки: Настойчивость и академическая мотивация

Psychology. Journal of the Higher School of Economics. 2014. Vol. 11. No. 3. P. 37–54.
Khavenson T., Orel E.

The paper describes the results of examining the relationship between attitudes towards statistics and academic motivation and persistence in sociology students. Often, in the everyday understanding social sciences are identified with the humanities and therefore are considered as not requiring specific mathematical training. Such attitudes in the social sciences students can lead to a decrease in the learning effectiveness and academic issues up to expulsion. To measure the attitudes towards statistics we used SATS-34 that covers a wide range of attitudes to both the academic subject and the statistics in general. The results showed that based on the combination of various aspects of the attitude the students can be divided into three types: interested in mastering statistics, formally interested and uninterested in the subject. The groups differ in the level of perseverance and the prevailing academic motivation. In addition, significant differences between groups were found in the expected and actual grades in the course. The article concludes that the attitudes towards statistics are related to both psychological characteristics of students and to the level of course mastery. The differences between the groups were significant notwithstanding the hard and regular monitoring and the high importance of the course in the curriculum, i.e. the hardness of control does not negate the contribution of psychological factors in the learning effectiveness. We assume that the differences between the groups would have been even more pronounced in a more relaxed learning environment.

Research target: Psychology Education Sociology (including Demography and Anthropology
Priority areas: sociology
Language: English
Full text
Keywords: statistics anxietySATSотношение к статистикенастойчивостьattitudes towards statisticsSATS-34SATS-34grit scaleacademic motivationакадемическая мотивациятревожность по отношению к статистике
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