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  • «Когда честно – хорошо, для имитации – плохо»: стратегии использования генеративного искусственного интеллекта в российском вузе
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News
July 13, 2026
Biologists Discover Unique Properties of MiR-93-5p MicroRNA in Prostate Cancer
Researchers at the International Laboratory of Microphysiological Systems of the HSE Faculty of Biology and Biotechnology investigated how different isoforms of the same microRNA influence gene function in prostate adenocarcinoma. The study found that in some cases, microRNAs can reinforce each other’s effects by targeting and suppressing the same genes. This finding offers a fresh perspective on the molecular mechanisms underlying tumour development and on the search for disease biomarkers. The results have been published in PeerJ.
July 13, 2026
'My Goal Is to Become a Tenured Professor'
Mikhail Samatov focuses on the theoretical study of perovskite solar cells. In this interview for the HSE Young Scientists project, he talks about working on HSE University’s supercomputer, collaborating with Peking University, and making furniture.
July 9, 2026
HSE Economists Use Search Queries to Forecast Birth Rates
Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.

 

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«Когда честно – хорошо, для имитации – плохо»: стратегии использования генеративного искусственного интеллекта в российском вузе

Высшее образование в России. 2025. Т. 34. № 2. С. 31–50.
Ananin D., Комаров Р. В., Реморенко И. М.

The issue of using generative artificial intelligence (GenAI) in education is the focus of both its advocates and critics. The world academic community is trying to consider the rapidly spreading phenomenon, to determine its place in the educational process and to work out the regulatory framework. The application of GenAI-powered services changes conceptual and didactic foundations of education. In order to predict scenarios of university education development and timely response on the managerial level, the community needs survey data on the use of GenAI-powered services and tools by the educational process actors – university academic staff and students. The paper contributes to the study of patterns of GenAI-powered services use by students and university teachers. The authors surveyed students (N = 450), researchers and teaching staff (N = 228) of the Moscow City University. The greater popularity of GenAI among students and a more discreet position on the use of GenAI-powered services by university teachers is determined by different strategies of their use. The complementary function of GenAI-powered services in the active strategy of a university teacher does not change the essence of the educational process compared to the students’ one. The accomplishment of written assignments with the help of GenAI as the most common application of GenAI-powered tools among students transforms the conventional understanding of responsibility and transparency of educational results. The findings highlight the reconsideration of higher education nature and require to transform educational practices in teaching and learning. The authors conclude that the contradictory attitudes towards GenAI require the assumption of ethical and regulatory norms for the use of GenAI-powered services in (higher) education, as well as increasing the level of AI literacy among teachers and students.

Research target: Education
Language: Russian
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Keywords: довериеобразовательные практикиопрособразовательная технологияeducational technologyроссийское высшее образованиеacademic integrityquestionnaireRussian higher educationгенеративный искусственный интеллект generative artificial intelligencelearning and teachingfaculty’s and students’ perceptionотношение преподавателей вузов и студентовакадемическая честность
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