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  • Применение нейросетевых технологий в изучении акмеологического потенциала студентов вуза
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News
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.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
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.
August 11, 2026
‘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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Применение нейросетевых технологий в изучении акмеологического потенциала студентов вуза

Вестник Пермского университета. Серия: Математика. Механика. Информатика. 2014. № 4. С. 120–126.
Yasnitsky L., Кузнецов А. Г., Селезнева С. М., Солохина А. Д., Тюлькина Д. В., Черепанов Ф. М.

The computer program intended for forecasting of probability of employment in specialty and level of success of the student in his future career, is developed. The neural network trained on examples of experience of employment and work of graduates of the Perm higher education institution, is base of the program. The program gives chance to influence results of forecasts of future activity of students by regulation of their current parameters.

Research target: Psychology Mathematics Computer Science
Priority areas: business informatics
Language: Russian
Full text
Keywords: карьерауспешностьпрогнозcareerprognosissuccession
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