IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-2-38476-585-0_46.html

The Application of AI in Higher Education

In: Proceedings of the 2025 International Conference on Hybrid Commerce, Human Capital, and Economic Dynamics (ICHCH 2025)

Author

Listed:
  • Yuxin Han

    (University of Birmingham, Birmingham Business School)

Abstract

This research essay explains the intricate relationship of artificial intelligence (AI) and higher education, and the challenges and opportunities it presented. It first describes current AI applications in education, such as individualized learning environments tailored to each student’s particular needs, smart teaching systems to support course planning and assessment for instructors, virtual learning environments that simulate interactive classroom environments, and AI-powered assistants that offer instant academic support. The study then delves into key challenges: the growing need to train teachers to deploy AI abilities in the application of those tools effectively, and the possibility of bias in AI systems that evaluate learning success, which could oversimplify complex educational progress. On the opportunity side, it highlights AI’s role in enabling flexible learning that breaking geographical and temporal barriers and its ability to craft individualized learning plans aligned with students’ unique schedules, learning paces, and academic goals. With specific recommendations, the paper advocates for the enhancement of AI training for educators to build their digital pedagogy and encourages students to rencounter AI learning tools in a reflective, ethical, and effective manner. Finally, the research essay aims to clarify the intersection of AI on higher education.

Suggested Citation

  • Yuxin Han, 2026. "The Application of AI in Higher Education," Advances in Economics, Business and Management Research, in: Ata Jahangir Moshayedi (ed.), Proceedings of the 2025 International Conference on Hybrid Commerce, Human Capital, and Economic Dynamics (ICHCH 2025), pages 402-409, Springer.
    • Handle: RePEc:spr:advbcp:978-2-38476-585-0_46
    DOI: 10.2991/978-2-38476-585-0_46
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:advbcp:978-2-38476-585-0_46. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.