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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">voprstat</journal-id><journal-title-group><journal-title xml:lang="ru">Вопросы статистики</journal-title><trans-title-group xml:lang="en"><trans-title>Voprosy Statistiki</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2313-6383</issn><issn pub-type="epub">2658-5499</issn><publisher><publisher-name></publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.34023/2313-6383-2025-32-2-27-39</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-1887</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>СТАТИСТИКА В СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ ИССЛЕДОВАНИЯХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>STATISTICS IN SOCIO-ECONOMIC STUDIES</subject></subj-group></article-categories><title-group><article-title>Оценка репутации российских вузов, реализующих образовательные программы подготовки инженеров</article-title><trans-title-group xml:lang="en"><trans-title>Assessment of the Reputation of Russian Universities Providing Engineering Education Programs</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5361-7360</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гатауллина</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Gataullina</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Гатауллина Алия Аюповна – канд. экон. наук, доцент, заведующий сектором по взаимодействию с рейтинговыми агентствами Центра перспективного развития, доцент кафедры проектного менеджмента и оценки бизнеса Института управления, экономики и финансов</p><p>420008, г. Казань, ул. Кремлевская, д. 18</p></bio><bio xml:lang="en"><p>Aliya A. Gataullina – Cand. Sci. (Econ.), Associate Professor, Head, Sector for Ranking Agencies Interaction, Prospective Development Center, Associate Professor, Project Management and Business Evaluation Department, Institute of Management, Economics and Finance</p><p>18, Kremlyovskaya Str., Kazan, 420008</p></bio><email xlink:type="simple">AliAShugaepova@kpfu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Казанский (Приволжский) федеральный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Kazan (Volga Region) Federal University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>30</day><month>04</month><year>2025</year></pub-date><volume>32</volume><issue>2</issue><fpage>27</fpage><lpage>39</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Гатауллина А.А., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Гатауллина А.А.</copyright-holder><copyright-holder xml:lang="en">Gataullina A.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://voprstat.elpub.ru/jour/article/view/1887">https://voprstat.elpub.ru/jour/article/view/1887</self-uri><abstract><p>В условиях растущей конкуренции на рынке образовательных услуг, влияющей на привлечение абитуриентов, высококвалифицированных преподавателей и ученых, приобретает большое значение репутационный капитал высших учебных заведений. В последнее время сильное воздействие на его формирование оказывает цифровая среда, роль которой становится ключевой. Оценка репутации вуза – многоаспектная задача, включающая анализ информационных ресурсов, определение ее основных критериев и показателей, разработку методологии.В статье рассматриваются проблемы измерения на основе баз данных, сформированных из различных источников, репутации российских вузов, реализующих программы подготовки инженеров. Цель исследования заключается в определении показателей и разработке подхода к оценке репутации образовательных организаций высшего образования в России.В ходе исследования анализировались статистические данные Минобрнауки России и поисковые запросы сервиса Яндекс. На основе сравнительного анализа по оцениваемым параметрам были выделены лучшие российские вузы, осуществляющие подготовку инженеров. При обработке статистических данных о числе поисковых запросов проводилась оценка их качества с учетом аберраций и логических совпадений с другими устоявшимися словоформами.Применение метода нормирования данных позволило сопоставить результаты оценки репутации образовательных организаций высшего образования различных регионов страны. Лидирующие позиции по большинству показателей заняли вузы г. Москвы и г. Санкт-Петербурга, что подчеркивает их статус ведущих образовательных центров. В то же время некоторые региональные университеты имеют высокие значения показателей международной и цифровой репутации, что свидетельствует о признании их роли в подготовке специалистов инженерного профиля.Было выявлено, что различия в оценках репутации российских вузов обусловлены спецификой методологии сбора и обработки данных. Научная новизна исследования состоит в определении состава показателей, характеризующих репутацию российских вузов, детализированном анализе существующих методик ее оценки и предложении новых подходов, расширяющих теоретическую и методологическую базы анализа. Полученные результаты могут быть использованы как в теоретическом плане – для совершенствования подходов к оценке эффективности деятельности вузов, так и для оптимизации управления высшими учебными заведениями</p></abstract><trans-abstract xml:lang="en"><p>reputational capital of higher education institutions becomes extremely important given the growing competition in the market of educational services, which influences the attraction of applicants, highly qualified teachers, and scientists. Building reputation capital has recently been significantly influenced by the digital environment, which is now starting to play a key role. Assessing a university's reputation is a multifaceted issue that includes analyzing information resources, determining its main criteria and indicators, and developing a methodology.The article considers the problems of measuring the reputation of Russian universities offering engineering training programs based on databases compiled from various sources. The study aims to identify reputational indicators and develop an approach to assessing the reputation of higher education institutions in Russia.The author analyzed data from the Ministry of Science and Higher Education of the Russian Federation and Yandex search queries.The top Russian universities providing training of engineering personnel were identified through a comparative analysis of the evaluated parameters. When processing statistical data on the number of search queries, data quality was assessed with regard to aberrations and logical coincidences with other established word forms.The application of normalized data processing methods made it possible to compare the results of reputation assessments of higher education institutions from different regions of the country. Universities in Moscow and St. Petersburg lead in the majority of indicators, emphasizing their status as leading centers for education. At the same time, certain regional universities have high rankings in international and digital reputation, which indicates recognition of their role in training engineering specialists.The differences in the reputation assessment of Russian universities were found to arise from the specifics of the methodologies used in data collection and processing. The scientific novelty of the study lies in determining the composition of indicators characterizing the reputation of Russian universities, a detailed analysis of existing methodologies for its assessment, and the proposal of new approaches that expand the theoretical and methodological bases of the analysis. The findings can be used both in theoretical terms – to improve approaches to assessing university performance – and to optimize the management of higher education institutions</p></trans-abstract><kwd-group xml:lang="ru"><kwd>статистическая совокупность</kwd><kwd>база данных</kwd><kwd>статистические данные</kwd><kwd>статистика высшего образования</kwd><kwd>инженерные специальности</kwd><kwd>подготовка инженеров</kwd><kwd>репутация вуза</kwd><kwd>оценка репутации вуза</kwd></kwd-group><kwd-group xml:lang="en"><kwd>statistical population</kwd><kwd>database</kwd><kwd>statistical data</kwd><kwd>statistics of higher education</kwd><kwd>engineering specialties</kwd><kwd>training of engineers</kwd><kwd>university reputation</kwd><kwd>assessment of university reputation</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Работа выполнена за счет гранта Академии наук Республики Татарстан, предоставленного молодым кандидатам наук (постдокторантам) с целью защиты докторской диссертации, выполнения научно-исследовательских работ, а также выполнения трудовых функций в научных и образовательных организациях Республики Татарстан в рамках Государственной программы Республики Татарстан «Научно-технологическое развитие Республики Татарстан» (Соглашение от 16.12.2024 № 10/2024-ПД).</funding-statement><funding-statement xml:lang="en">This paper is performed as part of the grant of the Tatarstan Academy of Sciences, provided to young candidates of sciences (postdoctoral fellows) for the purpose of defending their doctoral dissertation, conducting research, as well as performing their work duties in scientific and educational organizations of the Republic of Tatarstan within the framework of the State Program of the Republic of Tatarstan «Scientific and Technological Development of the Republic of Tatarstan» (Agreement No.10/2024-PD, 16.12.2024).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Малых С.В. 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