IDEAS home Printed from https://ideas.repec.org/a/ids/ijitma/v23y2024i3-4p357-371.html
   My bibliography  Save this article

An evaluation of English distance information teaching quality based on decision tree classification algorithm

Author

Listed:
  • Xueqi Liu

Abstract

In order to overcome the problems of low evaluation accuracy and long evaluation time in traditional teaching quality evaluation methods, a method of English distance information teaching quality evaluation based on decision tree classification algorithm is proposed. Firstly, construct teaching quality evaluation indicators under different roles. Secondly, the information gain theory in decision tree classification algorithm is used to divide the attributes of teaching resources. Finally, the rough set theory is used to calculate the index weight and establish the risk evaluation index factor set. The result of teaching quality evaluation is obtained through fuzzy comprehensive evaluation method. The experimental results show that the accuracy rate of the teaching quality evaluation of this method can reach 99.2%, the recall rate of the English information teaching quality evaluation is 99%, and the time used for the English distance information teaching quality evaluation of this method is only 8.9 seconds.

Suggested Citation

  • Xueqi Liu, 2024. "An evaluation of English distance information teaching quality based on decision tree classification algorithm," International Journal of Information Technology and Management, Inderscience Enterprises Ltd, vol. 23(3/4), pages 357-371.
    • Handle: RePEc:ids:ijitma:v:23:y:2024:i:3/4:p:357-371
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=139586
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijitma:v:23:y:2024:i:3/4:p:357-371. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=18 .

    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.