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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">vestsutmb</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Тамбовского университета. Серия: Гуманитарные науки</journal-title><trans-title-group xml:lang="en"><trans-title>Tambov University Review. Series: Humanities</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1810-0201</issn><issn pub-type="epub">2782-5825</issn><publisher><publisher-name>Derzhavin Tambov State University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.20310/1810-0201-2025-30-5-1091-1111</article-id><article-id custom-type="elpub" pub-id-type="custom">vestsutmb-1590</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>ТЕОРИЯ И МЕТОДИКА ОБУЧЕНИЯ ИНОСТРАННОМУ ЯЗЫКУ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>THEORY AND METHODS OF FOREIGN LANGUAGE TEACHING</subject></subj-group></article-categories><title-group><article-title>Инструменты искусственного интеллекта для научных целей: базовая классификация, сильные и слабые стороны, мнение обучающихся</article-title><trans-title-group xml:lang="en"><trans-title>AI tools for science: basic classification, strengths, weaknesses, learners’ opinions</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1263-3599</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Абрамова</surname><given-names>И. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Abramova</surname><given-names>I. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Абрамова Ирина Евгеньевна, доктор филологических наук, доцент, почетный работник высшего профессионального образования Российской Федерации</p><p>РИНЦ AuthorID: <ext-link xlink:href="https://www.elibrary.ru/author_profile.asp?authorid=253552" ext-link-type="uri">253552</ext-link></p><p>ResearcherID: <ext-link xlink:href="https://www.webofscience.com/wos/author/record/G-7039-2019" ext-link-type="uri">G-7039-2019</ext-link></p><p>Scopus Author ID: <ext-link xlink:href="https://www.scopus.com/authid/detail.uri?authorId=57196033884" ext-link-type="uri">57196033884</ext-link></p><p>185910, г. Петрозаводск, пр-кт Ленина, 33 </p></bio><bio xml:lang="en"><p>Irina E. Abramova, Dr. Sci. (Philology), Associate Professor,</p><p>RSCI AuthorID: <ext-link xlink:href="https://www.elibrary.ru/author_profile.asp?authorid=253552" ext-link-type="uri">253552</ext-link></p><p>ResearcherID: <ext-link xlink:href="https://www.webofscience.com/wos/author/record/G-7039-2019" ext-link-type="uri">G-7039-2019</ext-link> </p><p>Scopus Author ID: <ext-link xlink:href="https://www.scopus.com/authid/detail.uri?authorId=57196033884" ext-link-type="uri">57196033884</ext-link></p><p>33 Lenin Ave., Petrozavodsk, 185910</p></bio><email xlink:type="simple">lapucherabr@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Петрозаводский государственный университет»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Petrozavodsk State 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>28</day><month>11</month><year>2025</year></pub-date><volume>30</volume><issue>5</issue><fpage>1091</fpage><lpage>1111</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Абрамова И.Е., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Абрамова И.Е.</copyright-holder><copyright-holder xml:lang="en">Abramova I.E.</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://vestsutmb.elpub.ru/jour/article/view/1590">https://vestsutmb.elpub.ru/jour/article/view/1590</self-uri><abstract><sec><title>Актуальность</title><p>Актуальность. Подготовка кадров для науки и экономики требует наличия современных исследовательских компетенций в научно-технологической сфере, в том числе владение ИИ-технологиями. Цель работы – разработать базовую классификацию инструментов ИИ, применимых в исследованиях бакалавров, магистрантов и аспирантов гуманитарного профиля, а также проанализировать субъективные мнения обучающихся об эффективности, сильных и слабых сторонах использования ИИ в науке.</p></sec><sec><title>Методы исследования</title><p>Методы исследования. Применялись следующие научные методы: анализ релевантной литературы, обучающий эксперимент, формализованное анкетирование, статистические методы.</p></sec><sec><title>Результаты исследования</title><p>Результаты исследования. Установлено, что бакалавры используют ИИ для структурирования информации (73,9%), написания выводов (78,3%), составления обзора литературы (60,9%) и генерации идей (52,2%). Магистранты и аспиранты с помощью ИИ оформляют статьи и список литературы (73,9%). Наиболее эффективными ресурсами респонденты признали ChatGPT (х̅ =8,5 и 8,2 балла), DeepSeek (х̅ =8,2 и 7,7 балла) и Chatpdf (х̅ =7 и 7,7 балла). Магистранты и аспиранты более критичны при описании достоинств инструментов ИИ и чаще выявляют недостатки.</p></sec><sec><title>Выводы</title><p>Выводы. Делается вывод о том, различия между бакалаврами и магистрантами/ аспирантами в выборе ресурсов ИИ и в оценке их достоинств и недостатков обусловлены разным уровнем их исследовательской компетенции и степенью готовности к самостоятельной научной деятельности. Применение ИИ облегчает студентам решение ряда задач, однако только квалифицированные преподаватели способны контролировать исследования обучающихся и информировать о корректных и недопустимых способах применения ИИ в науке.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Importance</title><p>Importance. Training personnel for careers in science and the economy requires modern research competencies in the scientific and technological sphere, including mastery of AI technologies. This paper aims to develop a basic classification of AI tools applicable to undergraduate, graduate and postgraduate students of the humanities, and to analyse students' subjective opinions about the effectiveness, strengths and weaknesses of using AI in science.</p></sec><sec><title>Research Methods</title><p>Research Methods. The following scientific methods are employed: analysis of relevant literature; a training experiment; a formalised questionnaire; and statistical methods.</p></sec><sec><title>Results and Discussion</title><p>Results and Discussion. The research revealed that undergraduate students utilise AI to structure information (73.9 %), write conclusions (78.3 %), write a literature review (60.9 %), and generate ideas (52.2 %). Masters and PhD students use AI to design articles and reference lists (73.9 %). In the survey, respondents identified ChatGPT (  = 8.5 and 8.2 points), DeepSeek (  = 8.2 and 7.7 points) and Chatpdf ( = 7 and 7.7 points) as the most effective resources. Master's and PhD students demonstrated a heightened level of critical thinking when evaluating the strengths and weaknesses of AI tools. They were more likely to identify potential limitations.</p></sec><sec><title>Conclusion</title><p>Conclusion. The differences between Masters’ degree Students/Post-Graduate Students in the choice of AI resources and in the assessment of their advantages and disadvantages are due to the different levels of their research competence and the degree of readiness for independent scientific activity. The application of AI can facilitate students in solving a number of tasks, but only qualified teachers are able to supervise their research and inform them of the correct and incorrect ways to use AI in science.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>ИИ-инструменты в науке</kwd><kwd>гуманитарные исследования</kwd><kwd>классификация ИИ для исследований</kwd><kwd>высшая школа</kwd><kwd>мнение обучающихся</kwd><kwd>преимущества</kwd><kwd>недостатки</kwd></kwd-group><kwd-group xml:lang="en"><kwd>AI tools in science</kwd><kwd>humanities research</kwd><kwd>classification of AI for research</kwd><kwd>university</kwd><kwd>learner’ opinion</kwd><kwd>advantages</kwd><kwd>disadvantages</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">Караваева Е.В., Маландин В.В. 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