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Construction of Personalized Education Model for College Students Driven by Big Data and Artificial Intelligence

Journal of physics. Conference series, 2021-02, Vol.1744 (3), p.32022 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1744/3/032022

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  • Title:
    Construction of Personalized Education Model for College Students Driven by Big Data and Artificial Intelligence
  • Author: Lan, Qihong
  • Subjects: Artificial Intelligence ; Big Data ; College students ; Colleges & universities ; Education ; Individualized Education for College Educators ; Individualized Learning for College Students ; Learning ; Physics ; Students
  • Is Part Of: Journal of physics. Conference series, 2021-02, Vol.1744 (3), p.32022
  • Description: The combination of big data, artificial intelligence and education has become a new mode of university education reform in China. This paper combs the help of big data and artificial intelligence for the individualized teaching of university teachers, the individualized management of college educators and the individualized learning of college students through the mining of common and individual data, the equal emphasis of process and result, and the combination of task learning and autonomous learning. The model of individualized education for college students is constructed, which is mainly composed of two sub-models: the individualized learning model of college students and the individualized education model of college educators. Thees two models promote each other and act together on the process of college students' education.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1742-6588
    EISSN: 1742-6596
    DOI: 10.1088/1742-6596/1744/3/032022
  • Source: Open Access: IOP Publishing Free Content
    Geneva Foundation Free Medical Journals at publisher websites
    IOPscience (Open Access)
    ProQuest Central
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