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News
September 4, 2026
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.
September 4, 2026
‘Hedgehog Versus ‘Relatives: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech
Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.

 

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The network approach to assess the structure of knowledge: Storage, distribution and retrieval as three measures in analysing concept maps

British Journal of Educational Technology. 2020. Vol. 51. No. 6. P. 2573–2590.
Kapuza A., Koponen I., Tyumeneva Y. A.

We present three new standardised network concept map (CM) measures that can provide unique information about learning‐related progress, which cannot be determined from previously known measures. Grounded in cognitive development theory on the one hand, and network theory on the other hand, our measures reveal how knowledge is stored, distributed and retrieved. We validated the new measures by testing their ability to discriminate between CMs of respondents with different levels of competency in statistics (students before and after taking an introductory statistics course and experts in the field of statistics). We also validated our measures against the most commonly used traditional and network measures. Based on a small sample of respondents, we show that two of the newly proposed compound measures reveal significant differences between experts and novices in the field, with higher values for experts, showing that expert knowledge is better distributed, more connected and balanced. More importantly, our measures were sensitive enough to show learning‐related progress for students, albeit statistically non‐significant, while common indicators from network theory did not demonstrate these small shifts. The validity of our new measures can be inferred from the consistency of the results from different sets of measures.

Research target: Psychology Education
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: обучениеlearningexpertsэкспертыnetwork analysisknowledge structureСетевой анализ в образованииконцептуальные картыструктура знанийconcept mapsnovices
Publication based on the results of:
Strategies, barriers and factors for including digital technologies in the educational process by primary school teachers (2020)
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