IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/4134827.html
   My bibliography  Save this article

Research on College English Teaching Quality Assessment Method Based on K-Means Clustering Algorithm

Author

Listed:
  • Wang Lang
  • Vijay Kumar

Abstract

The evaluation of college teachers’ teaching ability is very important. Currently, the indicators for evaluating the quality of college English teaching are unclear and insufficient. This paper evaluates the quality of university classroom teaching from two aspects: students’ learning effect and teachers’ teaching work. This paper employs the K-means algorithm to analyze the relationship between the indicators in the evaluation model and teachers’ teaching ability, finds out the specific factors that affect teaching activities, and guides the implementation of teachers’ teaching work. At the same time, the K-means model is used to evaluate students’ learning effect, identify the relationship between the indicators in the model and teachers’ teaching ability, and find out the specific factors that affect teachers to guide the implementation of teachers’ teaching work. Experiments show that the method proposed in this paper can solve the problem that the evaluation indicators of traditional evaluation methods are not clear and insufficient and can be better applied to teaching evaluation.

Suggested Citation

  • Wang Lang & Vijay Kumar, 2022. "Research on College English Teaching Quality Assessment Method Based on K-Means Clustering Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, August.
  • Handle: RePEc:hin:jnlmpe:4134827
    DOI: 10.1155/2022/4134827
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/4134827.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/4134827.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/4134827?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:hin:jnlmpe:4134827. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.