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  • Валидизация ЕНТ в Казахстане: доказательная основа справедливого тестирования
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News
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.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Валидизация ЕНТ в Казахстане: доказательная основа справедливого тестирования

Вопросы образования. 2026. № 2. С. 8–41.
Абдрасилов Б. С., Шинетова Л. Е., Ivanova A., Kardanova E., Бейсенова Ж. Ж., Жабаева Г. К., Орлов Д., Аширбек Г. Қ.

Worldwide, high-stakes entrance examinations are subject to rigorous requirements: they must be as objective, reliable, and fair as possible. This entails that the processes of their development, administration, and scoring are carefully controlled and standardized to eliminate any possibility of bias. In Kazakhstan, university admission is based on the results of the state entrance examination—the Unified National Testing (UNT). The aim of this study is to investigate the validity of the UNT results in Kazakhstan, focusing on the mathematics component. Particular attention is given to two sources of validity evidence:  based on internal test structure and based on relationship with other variables, specifically criteria of students’ subsequent academic success in higher education. The theoretical framework for this research is grounded in S. Messick’s validity theory. A series of validation studies were conducted in accordance with the methodological standards set forth by AERA, NCME, and APA, employing classical test theory, modern test theory approaches, and statistical analyses including hierarchical linear modeling. The findings indicate that the UNT mathematics exam demonstrates strong psychometric properties. Furthermore, both the overall UNT score across five subjects and the mathematics effectively predict students’ future academic performance at university. The quality of the statistical models used and the proportion of variance explained in students’ first-semester grades are largely consistent with results reported by researchers from other countries, including Russia and the United States.

Research target: Education
Language: Russian
DOI
Keywords: КазахстанПрогностическая валидностьpredictive validityвалидизация ValidationRepublic of KazakhstanHigh-stakes examsUNTэкзамены с высокими ставкамиЕНТ
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