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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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How adding structure reduces complexity: more interconnections in concept maps do not increase cognitive load

Instructional Science. 2025. Vol. 53. P. 1243–1262.
Costley J., Anastasiia Kapuza, Gorbunova A., Shcheglova I.

Cognitive load theory describes the mechanisms for the transfer of information from human working memory to long-term memory. This theory posits that increasing the number of interactive elements, such as interconnections, may increase cognitive load. This study investigates the impact of interconnections in concept maps on cognitive load, exploring whether they act as interactive elements in working memory increasing cognitive load, or function as structuring elements potentially reducing cognitive load. Well-structured concept maps may potentially lower cognitive load by effectively organizing information. In an experiment with 81 first-year postgraduate students, participants were divided into two groups: one group studied concept maps with fewer interconnections and another one with more interconnections. Results revealed a significant reduction in extraneous cognitive load for the group with more interconnections, while no significant differences were observed in intrinsic or germane cognitive load. These findings align with cognitive load theory and help expand it by suggesting that interconnections act as structuring elements that facilitate learning by organizing knowledge, leading to a decrease in extraneous cognitive load. This research demonstrates that the use of concept maps may optimize cognitive load and shows that the addition of structure in instructional materials doesn’t lead to overload for students.

Research target: Education Psychology
Language: English
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Keywords: экспериментexperimentinstructional designcognitive loadконцептуальные картыкогнитивная нагрузкаconcept mapsпедагогический дизайн
Publication based on the results of:
Using digital traces to study learners' behavioral strategies (2025)
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