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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">mkgtu</journal-id><journal-title-group><journal-title xml:lang="ru">Новые технологии / New technologies</journal-title><trans-title-group xml:lang="en"><trans-title>New Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2072-0920</issn><issn pub-type="epub">2713-0029</issn><publisher><publisher-name>МГТУ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.47370/2072-0920-2021-17-1-94-104</article-id><article-id custom-type="elpub" pub-id-type="custom">mkgtu-470</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>ЭКОНОМИЧЕСКИЕ НАУКИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ECONOMIC SCIENCES</subject></subj-group></article-categories><title-group><article-title>Технологические возможности статистических индикаторов сопровождения образовательной политики России</article-title><trans-title-group xml:lang="en"><trans-title>Technological capabilities of statistical indicators to support the educational policy of Russia</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Аванесян</surname><given-names>К. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Avanesyan</surname><given-names>K. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Карен Алексеевич Аванесян, ведущий научный сотрудник Академии психологии и педагогики, кандидат социологических наук</p><p>ул. Б. Садовая, 105/42, г. Ростов-на-Дону, 344006</p></bio><bio xml:lang="en"><p>Karen A. Avanesyan, a leading researcher of the Academy of Psychology and Educational Sciences, Candidate of Sociology</p><p>105/42 B. Sadovaya str., Rostov-on-Don, 344006</p></bio><email xlink:type="simple">avanesian@sfedu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Боровская</surname><given-names>М. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Borovskaya</surname><given-names>M. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Марина Александровна Боровская, президент,  доктор экономических наук, профессор</p><p>ул. Б. Садовая, 105/42, г. Ростов-на-Дону, 344006</p></bio><bio xml:lang="en"><p>Marina A. Borovskaya, president, Doctor of Economics, a professor</p><p>105/42 B. Sadovaya str., Rostov-on-Don, 344006</p></bio><email xlink:type="simple">bma@sfedu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Масыч</surname><given-names>М. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Masych</surname><given-names>M. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Марина Анатольевна Масыч, ведущий научный сотрудник Центра научных исследований «Инструментальные, математические и интеллектуальные средства в экономике», кандидат экономических наук, доцент</p><p>ул. Б. Садовая, 105/42, г. Ростов-на-Дону, 344006</p></bio><bio xml:lang="en"><p>Marina A. Masych, a leading researcher of the Center for Scientific Research «Instrumental, Mathematical and Intellectual Means in Economics», Candidate of Economics, Senior Researcher, an associate professor</p><p>105/42 B. Sadovaya str., Rostov-on-Don, 344006</p></bio><email xlink:type="simple">mamasych@sfedu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кочкин</surname><given-names>С. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Kochkin</surname><given-names>S. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сергей Алексеевич Кочкин, доцент кафедры высшей математики, кандидат физико-математических наук</p><p>набережная Северной Двины, 17, г. Архангельск, 163002</p></bio><bio xml:lang="en"><p>Sergey A. Kochkin, an assistant professor of the Department of Higher Mathematics, Candidate of Physics and Mathematics</p><p>17 the Severnaya Dvina embankment, Arkhangelsk, 163002</p></bio><email xlink:type="simple">s.kochkin@narfu.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГАОУ ВО «Южный федеральный университет»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSAOU HE «The Southern Federal University»</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГАОУ ВО «Северный (Арктический) федеральный университет имени М.В. Ломоносова»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSAOU HE «The Northern (Arctic) Federal University named after M.V. Lomonosov»</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>05</day><month>04</month><year>2021</year></pub-date><volume>17</volume><issue>1</issue><fpage>94</fpage><lpage>104</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Аванесян К.А., Боровская М.А., Масыч М.А., Кочкин С.А., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Аванесян К.А., Боровская М.А., Масыч М.А., Кочкин С.А.</copyright-holder><copyright-holder xml:lang="en">Avanesyan K.A., Borovskaya M.A., Masych M.A., Kochkin S.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://newtechology.mkgtu.ru/jour/article/view/470">https://newtechology.mkgtu.ru/jour/article/view/470</self-uri><abstract><p>Реализация проектов и программ в области образовательной политики требует эффективного сопровождения посредством технологий анализа и мониторинга системы образования, что требует формирования системы регулярного наблюдения за процессами развития образования с применением статистических индикаторов и использования их в процессе принятия и поддержки управленческих решений. Недостаточность применения статистических методов при оценке образовательного неравенства акцентирует внимание на наличии потенциала для развития экономики образования посредством включения в ее методологическую область точных, эконометрически обоснованных подходов измерения уровня неравенства, наблюдаемого в распределении человеческого капитала. В связи с вышесказанным в данной статье авторы ставят целью сформировать методологический подход к анализу образовательного неравенства через призму прикладного экономического анализа на основе микроданных статистических обследований и мониторингов для их эффективного включения в образовательную политику. Важную роль в этом контексте играет агенда четвертой цели в области устойчивого развития, утверждающей равное и качественное образование для всех. Авторы идентифицируют ключевые области образовательного неравенства в контексте российской системы образования, а также предлагают методики расчета статистических индикаторов для их измерения. Методики расчета приведены для дошкольного образования, высшего образования, а также в части расчета статистических индикаторов по обучению, успеваемости, навыкам и поддержки групп риска и уязвимых групп. Дальнейшие исследования с учетом предложенных методик должны способствовать приращению нового научного знания для эффективного научного сопровождения образовательной политики. Предложенный в статье подход позволит организовать систему научно-исследовательского лонгитюдного сопровождения процессов, происходящих на всех уровнях образования в части регулярности наблюдений и аналитики системы индикаторов по сформированной методике для поддержки принятия управленческих решений в развитии образовательной политики России.</p></abstract><trans-abstract xml:lang="en"><p>The implementation of educational projects and programs requires effective support through technologies for analyzing and monitoring the education system, which requires the formation of a system of regular monitoring of education development processes using statistical indicators and their use in the process of making and supporting management decisions. Insufficient use of statistical methods in assessing educational inequality focuses on the potential for the development of the education economy through the introduction of accurate, econometrically sound approaches to measuring the level of inequality observed in the distribution of human capital. With reference to the above mentioned, the authors aim to form a methodological approach to the analysis of educational inequality through the prism of applied economic analysis based on micro data from statistical surveys and monitoring for their effective inclusion in educational policy. The agenda of the fourth Sustainable Development Goal, which promotes equal and quality education for everyone plays an important role in this context. The authors identify key areas of educational inequality in the context of the Russian education system, and propose methods for calculating statistical indicators to measure them. Calculation methods for preschool education and higher education in terms of calculating statistical indicators on learning, academic performance, skills and support for at-risk and vulnerable groups are presented. Further research should contribute to the increment of new scientific knowledge for effective scientific support of educational policy. The approach proposed in the article will make it possible to organize a system of scientific research longitudinal support of the processes occurring at all levels of education in terms of the regularity of observations and analytics of the indicator system according to the developed methodology to support managerial decision-making in the development of educational policy in Russia.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>образовательное неравенство</kwd><kwd>статистические показатели</kwd><kwd>система индикаторов</kwd><kwd>образовательная политика</kwd><kwd>человеческий капитал</kwd><kwd>технологические возможности</kwd><kwd>цели устойчивого развития</kwd><kwd>доступ к образованию</kwd><kwd>дошкольное образование</kwd><kwd>высшее образование</kwd></kwd-group><kwd-group xml:lang="en"><kwd>educational inequality</kwd><kwd>statistical indicators</kwd><kwd>system of indicators</kwd><kwd>educational policy</kwd><kwd>human capital</kwd><kwd>technological capabilities</kwd><kwd>sustainable development goals</kwd><kwd>access to education</kwd><kwd>preschool education</kwd><kwd>higher education</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Schulz T. 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