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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
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‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Гендерные стереотипы и женские стратегии в высшем STEM-образовании: обзор междисциплинарного поля

Журнал исследований социальной политики. 2022. Т. 20. № 3. С. 505–520.
Savinskaya O., Лебедева Н. В., Vilkova K.

This paper focuses on the systematic review of articles on the measurement and analysis of gender stereotypes in higher education that were published in international journals over the past 30 years (1990–2020). The review aims to systematise the theoretical and methodological approaches defining gender stereotypes in STEM higher education and their role in the transformational processes of contemporary higher education and in the development of sociocultural openness of university environments, which have been available in the global socio-humanitarian field in recent decades. To achieve this goal, we used both open (Google Scholar) and closed (JSTOR, EBSCO, Scopus, Web of Science, American Psychological Association) citation databases. According to formulated criteria, the database of the 61 most relevant articles was left for the analysis. The articles covered the following topics: ability and self-confidence in STEM subjects, self-esteem, persistence, gender roles, motivation, values, social discomfort, low percentage of girls in technical majors, gender achievement gap, uneven student dropout, mismatched career plans. Based on the studied articles and classical approaches, the definition of gender stereotypes was proposed, positive and negative stereotypes and their significance for the formation of inequality were highlighted, the two most popular psychological theories about gender stereotypes – stereotype threat and implicit theories – were analysed, and methods of their measurement were systematised. The final part of the article reveals how gender stereotypes allow us to study the main aspects of gender inequality in higher education: female minority status in the academic environment, the relationship between gender and professional identity, motivation, persistence in obtaining a STEM profession and student dropout. The discussion indicates the need for further cross-country comparative research and the development of comprehensive measures. The question about the possibility of a conscious choice of a professional path in higher education is raised.

Research target: Education Sociology (including Demography and Anthropology Psychology
Language: Russian
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Keywords: высшее образованиеимплицитные теориигендерные стереотипыgender inequalityгендерное неравенствоimplicit theorieshigher educationgender stereotypesSTEM-образованиеSTEM-educationstereotype threatугроза подтверждения стереотипа
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