IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v13y2021i5p120-d547382.html
   My bibliography  Save this article

Analysis and Prediction of “AI + Education” Attention Based on Baidu Index—Taking Guizhou Province as an Example

Author

Listed:
  • Yulin Zhao

    (College of Computer and Information, Qiannan Normal University for Nationalities, Duyun 558000, China)

  • Junke Li

    (College of Computer and Information, Qiannan Normal University for Nationalities, Duyun 558000, China)

  • Jiang-E Wang

    (College of Computer and Information, Qiannan Normal University for Nationalities, Duyun 558000, China)

Abstract

Studying the attention of “artificial intelligence + education” in ethnic areas is of great significance for China for promoting the integrated development of new educational modes and modern technology in the western region. Guizhou province is an area inhabited by ethnic minorities, located in the heart of Southwest China. The development of its intelligent education has strong enlightenment for the whole country and the region. Therefore, this paper selects the Baidu Index of “artificial intelligence (AI) + education” in Guizhou province from 2013 to 2020, analyzes the spatial–temporal characteristics of its network attention by using the elastic coefficient method, and builds the ARIMA model on this basis to predict future development. The results show that the public’s attention to “AI + education” differs significantly in time and space. Then, according to the prediction results, this paper puts forward relevant suggestions for the country to promote the sustainable development of education in western ethnic areas.

Suggested Citation

  • Yulin Zhao & Junke Li & Jiang-E Wang, 2021. "Analysis and Prediction of “AI + Education” Attention Based on Baidu Index—Taking Guizhou Province as an Example," Future Internet, MDPI, vol. 13(5), pages 1-16, April.
  • Handle: RePEc:gam:jftint:v:13:y:2021:i:5:p:120-:d:547382
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/13/5/120/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/13/5/120/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:13:y:2021:i:5:p:120-:d:547382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.