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News
October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.
September 30, 2026
'We Did Not Limit the Time for Questions'
The International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis at HSE University held a major conference on molecular dynamics. Participants had the opportunity to attend all the presentations, while speakers were given as much time as they needed to answer questions. The HSE News Service interviewed Grigory Smirnov, Head of the Laboratory, and Genri Norman, Chief Research Fellow, about the conference preparations and the discussions it generated.

 

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Каким должно быть цифровое домашнее задание: обзор зарубежных исследований

Информатика и образование. 2021. Т. 36. № 6. С. 51–59.
Efimova E.

Digital homework today is an observable fact of school practice, which resulted from the distance learning experience during the COVID-19 pandemic and the development of online platforms that provide EdTech products of this kind. Yet, not enough reflection of this issue has happened so far. The article attempts to summarise recent research on homework to answer the question: what kind of digital homework has the potential to improve teaching and learning? First, the article compares research findings on the effect of homework and homework-related teaching practices to outline deficiencies in three aspects of homework: the quality of homework, the quality of feedback, and autonomy support. Then it demonstrates digital homework variability using the SAMR model. Finally, the author suggests solutions for three named aspects of homework on different levels of the SAMR model. For homework quality, higher levels of technology integration bring new task designs and more complex learning objectives. For feedback quality, it means being able to collect and employ learning data which was impossible earlier. For autonomy support, it makes homework relevant to students’ goals and interests. Recommendations provided might be helpful for the design and development of new educational technologies, as well as for better use of digital homework in teaching practice.

Research target: Education
Language: Russian
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Keywords: обратная связьдомашнее заданиеfeedbackinstructional designteaching strategieseducational technologiesавтономность учащихсяautonomy of studentsпрактики преподаваниятехнологии в образованиипедагогический дизайнhomework
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