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News
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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?

Videos, Culture and Significant Learning: Colombian students speak

P. 632–639.
Zhyrun I.

The study presents the results of a case evaluating the impact of designed audio-visual materials for English CLIL (Content and Language Integrated Learning) course “Cultures & Societies”. The designed videos were recorded with the purpose to connect the cultural context and content of the course and make students’ learning more significant, and thus more long-term. The purpose of the study is to identify if the designed materials have achieved the goal of providing relevant content and language that would be significant to students’ lives and results in long-term learning. During the second semester of 2016 in “Cultures & Societies” English CLIL class, students were exposed to 23 designed videos-interviews and 5 videos on similar cultural topics from other authors used from the YouTube. During the first months of the course students were exposed to 3 designed videos and 3 videos from YouTube. Students (n=15) completed a survey immediately after watching each video, indicating their perceptions of the videos in terms of relevance to their lives, culture, career and language. The results of the survey demonstrated that there was no significant difference in terms of interest and relevance to the subject, as the videos were previously selected for a course. Although students indicated that they were more connected emotionally to the designed videos than other YouTube videos. A week after the semester ended, the teacher conducted semi-structured interviews with students (n=11) soliciting information about what they remembered from videos and why. The interviews were conducted in Spanish. They were transcribed and analyzed via NVIVO qualitative software. Preliminary analysis shows that designed videos do have impact on long-term learning. Students remember the content of some of the videos they were exposed to in class, even though they watched them once three months ago. They highlight the importance of familiar cultural context, truthfulness of statements in the videos-interviews, language elements important to them, and motivation to listen to people with other cultural background, making the course “different” from the rest English classes they had.

Language: English
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Keywords: cultureforeign languageAudio-visual materialsContent and Language Integrated Learninglong-term learningsignificant learning

In book

Proceedings of the 13th International Scientific Conference "eLearning and Software for Education"
Vol. II: Could technology support learning efficiency?. , Bucharest: Advanced Distributed Learning Association, 2017.
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