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  • Тест «Базовая Морфология» (БаМ) – новый стандартизированный инструмент для оценки морфологических компетенций у детей дошкольного возраста
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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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Тест «Базовая Морфология» (БаМ) – новый стандартизированный инструмент для оценки морфологических компетенций у детей дошкольного возраста

Вопросы психологии. 2025. Т. 71. № 1. С. 120–132.
Gomozova M., Колесникова А. В., Лопухина А. А.

Introduction: Currently, there is a lack of standardized assessments of morphological skills in Russian-speaking children, which can complicate the diagnosis of speech disorders and delay the provision of necessary speech therapy. To address this gap, we developed the first standardized test designed to assess the comprehension and production of various morphological skills. We also analyzed psychometric parameters of the new assessment tool.

Materials and Methods: The study included 65 typically developing children and 19 children with Developmental Language Disorder (DLD) aged three to seven years. Participants completed 11 tasks from the new "Basic Morphology" (BaM) test. To evaluate the validity of the test, we calculated internal reliability, inter-rater reliability, sensitivity, and specificity.

Results and Discussion: Our results demonstrated good psychometric parameters, indicating significant diagnostic potential for the test. However, given the limited number of children with DLD in our sample, these results should be considered as preliminary.

Conclusion: The new standardized BaM test is highly effective in detecting morphological deficits in children. However, further research with a larger sample of children with DLD is needed to confirm its validity and expand its application potential.

Research target: Philology and Linguistics Psychology
Language: Russian
Full text
Keywords: standardized language assessmentdevelopmental language disorderbasic morphologyspeech therapy diagnosisстандартизированная оценка языкабазовая морфологияобщее недоразвитие речилогопедическая диагностика
Publication based on the results of:
Neural foundations of language and its impairments: From basic research to clinical practice (2025)
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