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News
July 24, 2026
‘I Like Self-Fulfilling Prophecies
Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.

 

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Исследование потенциала генеративных моделей для оценивания эссе и обеспечения обратной связи

Отечественная и зарубежная педагогика. 2024. Т. 1. № 5(101). С. 123–137.
Bogolepova S., Жаркова М. Г.

In the era of rapid development of generative language models these tools are increasingly being used by both students and instructors. This paper aims to investigate the potential of generative models interacting with users via chatbots ChatGPT и PerplexityAI for the evaluation of standardised essays in English and the provision of feedback on their quality. Accounting for the specific features of each chatbot and standardised assessment criteria, we developed prompts which were consequently fed to the chatbots together with 19 students’ essays. The chatbots both awarded overall grades and gave points and feedback on specific aspects. The chatbots’ grades were compared to the ones provided by the instructor, and to each other. Cronbach’s alpha was used to measure the consistency of grading, whereas Koen’s and Fleiss’s kappas helped to evaluate inter-rater agreement. Though the consistency of grading among the raters was shown to be from acceptable to excellent on different aspects, which indicates similar interpretations of assessment criteria by the instructor and the chatbots, inter-rater agreement was slight. Qualitative analysis revealed such features of feedback from chatbots as ignoring instructions in the prompt, finding non-existent errors, or awarding different grades in consecutive inquiries. We conclude that chatbots can be used for rough evaluation of standardised essays; however, their output cannot be considered reliable and needs expert editing. 

Research target: Education Philology and Linguistics
Language: Russian
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Keywords: обратная связьискусственный интеллектfeedbackэссеassessmentоцениваниеessaygenerative modelsгенеративные модели artificial intelligenceautomatic text evaluationавтоматическая проверка текста
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