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Student-centred webcast + home-based learning model and investigation during the COVID-19 epidemic

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      <subfield code="a">Li, Mingyong </subfield>
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      <subfield code="a">Student-centred webcast + home-based learning model and investigation during the COVID-19 epidemic</subfield>
      <subfield code="c">Mingyong Li, Ziye An, Miaomiao Ren</subfield>
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      <subfield code="a">With the rapid development of Internet technology, traditional online learning can no longer meet the adaptive learning needs of students. Through big data and learning analysis technology, artificial intelligence technology based on learning has gradually become a new research hotspot. How to further use these big data resources for adaptive learning and push to improve the quality of student training has become an important issue in the current research field. To support students' learning during the COVID-19 epidemic, schools have shifted completely from offline to online teaching. Students study online at home, so the family plays a vital role as a special classroom. Based on the analysis of factors affecting home-based learning, this paper compares live broadcast platforms and constructs a student-centered webcast + home-based learning model under the epidemic situation. Through the implementation effect investigation, the evaluation effect is good. It is hoped that this model can provide reference for teachers and students under the new situation and solve some problems of current online teaching.</subfield>
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      <subfield code="a">COVID-19</subfield>
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      <subfield code="a">Pandemias</subfield>
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      <subfield code="a">Big data</subfield>
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      <subfield code="a">Inteligencia artificial</subfield>
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      <subfield code="a">Enseñanza a distancia</subfield>
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      <subfield code="a">An, Ziye </subfield>
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      <subfield code="a">Ren, Miaomiao </subfield>
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      <subfield code="w">MAP20200034445</subfield>
      <subfield code="t">Revista Iberoamericana de Inteligencia Artificial</subfield>
      <subfield code="d">IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</subfield>
      <subfield code="x">1988-3064</subfield>
      <subfield code="g">31/12/2020 Volumen 23 Número 66 - diciembre 2020 , p. 51-65</subfield>
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