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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.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’

 

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Language assessment course: Structure, delivery and learning outcomes

International Journal of Environmental and Science Education. 2016. Vol. 11. No. 6. P. 1223–1229.
Solnyshkina M. I., Solovova E., Harkova E. V., Kiselnikov A. S.

Language Assessment at Kazan (Volga region) Federal University (KFU). In the paper the local impact of the course at KFU is viewed at four levels: Reactions, Learning Changes, Behaviour and Results. Impact data collected at KFU include the following: end of session written feedback, pre- and post-course questionnaires, observation in the classroom, interviews, concept maps, teacher portfolios, written assignments, tests/examinations and participant journal entries. Viewed as the first step in conducting a full Student Needs Analysis, the research is intended to inform the design and delivery of Language Assessment courses for graduates majoring in English, Linguistics or Pedagogy elsewhere. The methods, techniques and tools developed by the authors may also be adapted for application to any University course during piloting, or following its introduction

Language: English
Keywords: evaluationEGEformative assessmentlanguage assessmenteducation standardsCourse deliveryDiagnostic assessmentFCE
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