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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Asia, America and Africa history and modernity</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Asia, America and Africa history and modernity</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Азия, Америка и Африка история и современность</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="online">2782-540X</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">75909</article-id>
   <article-id pub-id-type="doi">10.31804/2782-540X-2024-3-1-79-114</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>Американская культура</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>American culture</subject>
    </subj-group>
    <subj-group>
     <subject>Американская культура</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">«Can AI Simulation and Machine Learning Improve Career Plans and Educational Expectations? »: concept by I-Chien Chen, Lydia Bradford &amp; Barbara Schneider (Michigan State University)</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>«Могут ли моделирование искусственного интеллекта и машинное обучение улучшить карьерные планы и образовательные ожидания?»: концепция И-Чиен Чен, Лидии Брэдфорд и Барбары Шнайдер (Университет Мичигана)</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Шпак</surname>
       <given-names>Анна Андреевна</given-names>
      </name>
      <name xml:lang="en">
       <surname>Shpak</surname>
       <given-names>Anna Andreevna</given-names>
      </name>
     </name-alternatives>
     <email>annaheyy@gmail.com</email>
     <bio xml:lang="ru">
      <p>кандидат культурологии;</p>
     </bio>
     <bio xml:lang="en">
      <p>candidate of cultural sciences;</p>
     </bio>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Кирко</surname>
       <given-names>Владимир Игоревич</given-names>
      </name>
      <name xml:lang="en">
       <surname>Kirko</surname>
       <given-names>Vladimir Igorevich</given-names>
      </name>
     </name-alternatives>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">ФГАОУ ВО «Сибирский федеральный университет»</institution>
     <city>Красноярск</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Federal State Educational Institution of Higher Education &quot;Siberian Federal University&quot;</institution>
     <city>Krasnoyarsk</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2024-03-13T20:26:46+03:00">
    <day>13</day>
    <month>03</month>
    <year>2024</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2024-03-13T20:26:46+03:00">
    <day>13</day>
    <month>03</month>
    <year>2024</year>
   </pub-date>
   <volume>3</volume>
   <issue>1</issue>
   <fpage>79</fpage>
   <lpage>114</lpage>
   <history>
    <date date-type="received" iso-8601-date="2024-02-01T00:00:00+03:00">
     <day>01</day>
     <month>02</month>
     <year>2024</year>
    </date>
    <date date-type="accepted" iso-8601-date="2024-03-01T00:00:00+03:00">
     <day>01</day>
     <month>03</month>
     <year>2024</year>
    </date>
   </history>
   <self-uri xlink:href="https://asiaetother-journal.ru/en/nauka/article/75909/view">https://asiaetother-journal.ru/en/nauka/article/75909/view</self-uri>
   <abstract xml:lang="ru">
    <p>Представлен обзор основных идей главы «Изучение карьерных знаний: могут ли моделирование искусственного интеллекта и машинное обучение улучшить карьерные планы и образовательные ожидания?» авторства И-Чиен Чен, Лидии Брэдфорд и Барбары Шнайдер. Данная глава является частью коллективной монографии ««ИИ в обучении: проектирование будущего», научные редакторы издания – Ханнеле Ниеми, Рой Д. Пи, Ю Лу.&#13;
Концепция И-Чиен Чен, Лидии Брэдфорд и Барбары Шнайдер построена на повышении роли геймификации для адекватных карьерных планов и образовательных ожиданий обучающихся. Речь идет о том, что обучающиеся должны задолго до выбора профессии представлять реальные требования к уровню образования для своей будущей профессии. Анализируются возможности приложения Init2Winit с технологиями машинного обучения по созданию адекватных представлений о профессии и о том, как нужно учиться, чтобы в будущем получить именно эту выбранную профессию. Авторы концепции полагают, что геймификация с машинным обучением позволит существенно выровнять уровень адекватности карьерных планов и образовательных ожиданий, прежде всего, для обучающихся из семей с низкими доходами.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>An overview of the main ideas of the chapter “Learning Career Knowledge: Can AI Simulation and Machine Learning Improve Career Plans and Educational Expectations?” is provided. by I-Chien Chen, Lydia Bradford and Barbara Schneider. This chapter is part of the collective monograph “AI in Education: Designing the Future”, scientific editors of the publication are Hannele Niemi, Roy D. Pea, Yu Lu.&#13;
The concept of I-Chien Chen, Lydia Bradford and Barbara Schneider is built on increasing the role of gamification for adequate career plans and educational expectations of students. The point is that students should, long before choosing a profession, present the real requirements for the level of education for their future profession. The capabilities of the Init2Winit application with machine learning technologies to create adequate ideas about the profession and how to study in order to obtain this particular chosen profession in the future are analyzed. The authors of the concept believe that gamification with machine learning will significantly equalize the level of adequacy of career plans and educational expectations, primarily for students from low-income families.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>современное образование</kwd>
    <kwd>карьерные планы</kwd>
    <kwd>искусственный интеллект</kwd>
    <kwd>машинное обучение</kwd>
    <kwd>Init2Winit</kwd>
    <kwd>геймификация</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>modern education</kwd>
    <kwd>career plans</kwd>
    <kwd>artificial intelligence</kwd>
    <kwd>machine learning</kwd>
    <kwd>Init2Winit</kwd>
    <kwd>gamification</kwd>
   </kwd-group>
   <funding-group>
    <funding-statement xml:lang="ru">Исследование выполнено за счет гранта Российского научного фонда № 23-28-00255, https://rscf.ru/project/23-28-00255/</funding-statement>
    <funding-statement xml:lang="en">The study was supported by the Russian Science Foundation Grant No. 23–28–00255, https://rscf.ru/en/project/23–28–00255/</funding-statement>
   </funding-group>
  </article-meta>
 </front>
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