IDEAS home Printed from https://ideas.repec.org/a/igg/rmj000/v35y2022i3p1-12.html
   My bibliography  Save this article

The Study on the Needs of English Skills in Economics and Management Industries Based on Mobile Big Data Management and Innovative Applications

Author

Listed:
  • Cui Jing

    (Shandong University of Finance and Economics, China)

  • Dianbing Wang

    (Shandong University of Finance and Economics, China)

Abstract

Based on the theory of needs analysis and the "target situation needs" model, a questionnaire and interview were used to investigate the current social needs for employees' English proficiency, focusing on five issues: (1) the trend of enterprises' needs for employees' English ability, (2) the evaluation of enterprises' English literacy of employees, (3) the characteristics of job needs for English skills (listening, speaking, reading, writing and translation), (4) the social recognition of various English qualification certificates, and (5) the evaluation of ESP courses. Therefore, the author puts forward the necessity and urgency of the application of AI technology in English teaching, reiterates the necessity of specialization, integration and lifetime of vocational education, and actively reforms the traditional language laboratory into a multi-functional teaching model with AI, VR, human-computer interaction system, promotes the transformation of English vocational education model from single EGP to dual model of EGP and ESP.

Suggested Citation

  • Cui Jing & Dianbing Wang, 2022. "The Study on the Needs of English Skills in Economics and Management Industries Based on Mobile Big Data Management and Innovative Applications," Information Resources Management Journal (IRMJ), IGI Global, vol. 35(3), pages 1-12, July.
  • Handle: RePEc:igg:rmj000:v:35:y:2022:i:3:p:1-12
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IRMJ.304455
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:rmj000:v:35:y:2022:i:3:p:1-12. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.