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July 2, 2026
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
July 2, 2026
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
July 1, 2026
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.

 

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Вовлеченность обучающихся массовых открытых онлайн-курсов по продуктам вендора облачных технологий

Информатика и образование. 2025. Т. 40. № 2. С. 57–65.
Porosenkov G., Цепелевич М. М., Кизяков Д. А., Селезнева В. Н.

Research on learner engagement in massive open online courses (MOOCs) has predominantly focused on those developed by educational and non-profit organizations. However, the significance of MOOCs offered by IT service providers (vendors), particularly in the field of cloud computing, has gained prominence in recent years. These vendor-led courses facilitate interaction between learners and vendors, underscoring the necessity of investigating engagement levels within MOOCs from cloud service providers. The aim of the study presented in this article is twofold: first, to identify learner types based on their engagement patterns while participating in the “Cloud Services Engineer” MOOC developed by Yandex Cloud; second, to ascertain the factors influencing learner engagement in this context.
To achieve the aims, learners enrolled in the “Cloud Services Engineer” MOOC were clustered based on their level of engagement, which was assessed using data on lesson completion and test performance. Furthermore, the study examined the relationship between cluster membership and factors such as prior experience in cloud computing, professional position, and motivations for enrolling in the course.
The analysis revealed three distinct clusters of learners. The first cluster comprises highly engaged individuals who actively strive to obtain a certificate, likely motivated by institutional or employer requirements. The second cluster includes learners demonstrating prolonged interaction with educational materials but limited test attempts, suggesting intrinsic motivation to master cloud skills without the necessity for formal ascertainment of knowledge; and the third cluster consists of learners with minimal engagement, focusing on specific topics within the MOOC without seeking formal validation of their knowledge.
The findings highlight the importance of designing non-linear MOOCs that cater to diverse learner needs and interests in cloud learning.

Research target: Economics and Management
Language: Russian
Full text
DOI
Text on another site
Keywords: мотивацияcluster analysisкластерный анализmotivationоблачные технологииMOOC cloud computingМООКмассовый открытый онлайн-курсstudents’ engagementMassive open online coursetraining provided by vendorsобучение от вендороввовлеченность обучающихся
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