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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">infojournal</journal-id><journal-title-group><journal-title xml:lang="ru">Информатика и образование</journal-title><trans-title-group xml:lang="en"><trans-title>Informatics and education</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0234-0453</issn><issn pub-type="epub">2658-7769</issn><publisher><publisher-name>Publishing House Education and Informatics</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32517/0234-0453-2023-38-2-16-25</article-id><article-id custom-type="elpub" pub-id-type="custom">infojournal-951</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>ИНФОРМАТИЗАЦИЯ ОБРАЗОВАНИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFORMATIZATION OF EDUCATION</subject></subj-group></article-categories><title-group><article-title>Разработка прикладной интеллектуальной системы на основе нейрофизиологических данных для поддержки принятия решений по организации образовательного процесса</article-title><trans-title-group xml:lang="en"><trans-title>Development of an applied intelligent system based on neurophysiological data to support decision-making on the organization of the educational process</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4229-3572</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Носова</surname><given-names>Л. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Nosova</surname><given-names>L. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Носова Людмила Сергеевна, канд. пед. наук, доцент, зам. декана по учебной работе, доцент кафедры  информатики, информационных технологий и  методики обучения информатике, факультет  математики, физики, информатики </p><p>г. Челябинск</p></bio><bio xml:lang="en"><p>Lyudmila S. Nosova, Candidate of Sciences (Education), Docent, Deputy Dean for Academic Affairs, Associate Professor at the Department of Informatics, Information Technologies and Methods of Teaching Informatics, Faculty of Mathematics, Physics, Informatics</p><p>Chelyabinsk</p></bio><email xlink:type="simple">nosovals@cspu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9873-320X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Белоусова</surname><given-names>Н. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Belousova</surname><given-names>N. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Белоусова Наталья Анатольевна, доктор биол. наук, доцент, декан факультета математики, физики, информатики</p><p>г. Челябинск</p></bio><bio xml:lang="en"><p>Nataliya A. Belousova, Doctor of Sciences (Biology), Docent, Dean of the Faculty of Mathematics, Physics, Informatics</p><p>Chelyabinsk</p></bio><email xlink:type="simple">belousova@cspu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5864-8075</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Корчемкина</surname><given-names>Ю. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Korchemkina</surname><given-names>Yu. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Корчемкина Юлия Валерьевна, старший преподаватель кафедры информатики, информационных технологий и методики обучения информатике, факультет математики, физики, информатики</p><p>г. Челябинск</p></bio><bio xml:lang="en"><p>Yuliya V. Korchemkina, Senior Lecturer at the Department of Informatics, Information Technologies and Methods of Teaching Informatics, Faculty of Mathematics, Physics, Informatics </p><p>Chelyabinsk</p></bio><email xlink:type="simple">korchemkinayuv@cspu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Южно-Уральский государственный гуманитарно-педагогический университет<country>Россия</country></aff><aff xml:lang="en">South-Ural State Humanitarian Pedagogical University<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>23</day><month>06</month><year>2023</year></pub-date><volume>38</volume><issue>2</issue><fpage>16</fpage><lpage>25</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Носова Л.С., Белоусова Н.А., Корчемкина Ю.В., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Носова Л.С., Белоусова Н.А., Корчемкина Ю.В.</copyright-holder><copyright-holder xml:lang="en">Nosova L.S., Belousova N.A., Korchemkina Y.V.</copyright-holder><license 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://info.infojournal.ru/jour/article/view/951">https://info.infojournal.ru/jour/article/view/951</self-uri><abstract><p>В современной науке одной из актуальных проблем является поиск путей повышения эффективности обучения. Исследование нейрофизиологических закономерностей в формировании индивидуальных вариаций когнитивной активности обучающихся на различных этапах онтогенеза — важное условие для создания инновационных технологий повышения качества образовательного процесса. В статье представлена разработка прикладной интеллектуальной системы, позволяющей с помощью технологий нейронаук выявлять индивидуальные различия в когнитивной активности студентов и школьников и учитывать эти различия в образовательном процессе.</p><p>Использование различных методов и приемов обучения во многом обусловлено индивидуально-типологическими особенностями, которые можно анализировать, используя нейробиологические показатели. Экспресс-анализ индивидуального нейрофизиологического профиля характеризует поведенческие аспекты когнитивной деятельности. С помощью интеллектуальной системы проводится обработка комплекса нейрофизиологических показателей групп обучающихся с целью выявления того, как условия обучения влияют на данные показатели. На основе наборов данных, полученных в ходе испытаний, система распределяет обучающихся по парам, группам или проектным командам и рекомендует учебные задания в зависимости от нейрофизиологических профилей обучающихся.</p><p>При разработке системы учитываются такие принципы развития и использования искусственного интеллекта, как прозрачность выбора программой процесса формирования пар и групп обучающихся и критериев подбора заданий, поэтому используется так называемый слабый искусственный интеллект, машинное обучение с учителем.</p></abstract><trans-abstract xml:lang="en"><p>In modern science, one of the urgent problems is the search for ways to improve the effectiveness of learning. The study of neurophysiological patterns in the formation of individual variations of cognitive activity of students at different stages of ontogenesis is an important condition for developing innovative technologies to improve the quality of the educational process. The article presents the development of an applied intelligent system that allows considering individual differences in cognitive activity of students and schoolchildren using neuroscience technologies.</p><p>The use of teaching methods and techniques is largely due to individual typological features, which can be analyzed using neurobiological indicators. Express analysis of the individual neurophysiological profile characterizes behavioral aspects of cognitive activity. With the help of an intelligent system, a set of neuro-physiological indicators of groups of students was processed to identify the influence of learning conditions on these indicators. Based on the test data sets, the system assigns learners to pairs, groups, or project teams and recommends learning tasks based on the learners’ neurophysiological profiles.</p><p>When developing the system, the basic principles of the development and use of artificial intelligence are taken into account, such as transparency of the program’s choice of the process of forming pairs and groups of learners and the criteria for selecting tasks, so the so-called weak artificial intelligence — machine learning with a teacher is used.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>организация образовательного процесса</kwd><kwd>индивидуальная образовательная траектория</kwd><kwd>искусственный интеллект</kwd><kwd>нейрофизиологический профиль</kwd><kwd>прикладная интеллектуальная система</kwd></kwd-group><kwd-group xml:lang="en"><kwd>organization of educational process</kwd><kwd>individual educational trajectory</kwd><kwd>artificial intelligence</kwd><kwd>neurophysiological profile</kwd><kwd>applied intellectual system</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">Пройдаков Э. 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