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  • Факторы, определяющие удовлетворённость в синхронном онлайн-обучении: результаты статистического исследования на материале обучения русскому языку как иностранному
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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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Факторы, определяющие удовлетворённость в синхронном онлайн-обучении: результаты статистического исследования на материале обучения русскому языку как иностранному

Перспективы науки и образования. 2024. Т. 2. № 68. С. 326–338.
Родионова К. Е., Kashchenko E., Лебедева М. Ю.

Introduction. The widespread adoption of distance learning makes it relevant to reflect on the experience gained during the period of ubiquitous transition to the online format in 2019-2021. The purpose of the research is to investigate the factors influencing student satisfaction with synchronous online courses and to develop recommendations aimed at creating a positive educational experience for students in the online environment, specifically for teachers and methodologists. Materials and methods. This study draws upon survey data concerning the synchronous online acquisition of Russian as a foreign language among tertiary education students, both domestically and internationally. The sample comprised 307 individuals representing 16 countries, all of whom had engaged in at least one synchronous online course in the Russian language. Evaluation of satisfaction regarding the online learning experience centered on the variable denoted as "Course Satisfaction Assessment." The survey instrument was constructed based on the three-factor model, Community of Inquiry (COI), recognized for its efficacy in assessing effective online learning. This model, adapted to suit the context of synchronous online learning, comprehensively incorporates cognitive, pedagogical, and group communication factors. Results. As a result of correlation analysis, the ten most significant correlations with the variable "Course Satisfaction Evaluation" were identified. The most significant correlation of satisfaction with learning was established with positive evaluation of the course content – its practical usefulness and relevance to the needs of learners (r=0,44; p<0,01). Factors related to feedback from the instructor (r=0,34; p<0,01) and the motivational effect of the learning showed a high level of correlation with satisfaction with the training (r=0,35; p<0,01). Meanwhile, the factors of group communication did not show significant correlations. Considering the most important factors of satisfaction, recommendations were formulated to improve the effectiveness of synchronous online learning and enhance student motivation through content and organizational aspects of learning.

Language: Russian
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Keywords: мотивацияsatisfactionудовлетворенностьрусский как иностранныйacademic motivation Russian as a foreign language
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