IDEAS home Printed from https://ideas.repec.org/a/zib/zbnbda/v1y2019i1p15-20.html
   My bibliography  Save this article

The Fuzzy Comprehensive Evaluation Of Agriculture Engineering Teaching

Author

Listed:
  • Bao Liangliang

    (Yulin University, China)

Abstract

The evaluation process of agriculture engineering teaching is multi-level with multi-factors and prone to be affected by subjective factors. In reference to the experience and methods of EU in the optimization of higher education and teaching, this paper constructs the teaching quality evaluation index system according to the actual situation of the classroom teaching while considering the major setup and geographical distribution of agriculture engineering. A questionnaire survey is conducted on the professors, employers, students and graduates of five colleges and universities, and on this basis, the fuzzy mathematics theory is adopted to analyze the data with the fuzzy comprehensive evaluation method. The evaluation of the current situation of agriculture engineering teaching is obtained to provide a reference for the further deepening of teaching reform. The results show that this method can effectively improve the accuracy, objectivity and rationality of the evaluation.

Suggested Citation

  • Bao Liangliang, 2019. "The Fuzzy Comprehensive Evaluation Of Agriculture Engineering Teaching," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 1(1), pages 15-20, January.
  • Handle: RePEc:zib:zbnbda:v:1:y:2019:i:1:p:15-20
    DOI: 10.26480/bda.01.2019.15.20
    as

    Download full text from publisher

    File URL: https://bigdatainagriculture.com/download/447/
    Download Restriction: no

    File URL: https://libkey.io/10.26480/bda.01.2019.15.20?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
    ---><---

    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:zib:zbnbda:v:1:y:2019:i:1:p:15-20. 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: Zibeline International Publishing (email available below). General contact details of provider: https://bigdatainagriculture.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.