Research on the effectiveness of teaching quality evaluation method based on cloud model: a case of engineering mechanics course
DOI:
Author:
Affiliation:

School of Civil Engineering,Chongqing University

Clc Number:

G642.0

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to solve the subjectivity and effectiveness problem of university teaching quality evaluation method, a teaching quality evaluation method based on cloud model is presented and the effective strategy of teaching evaluation to avoid the influence of subjectivity is discussed. First, the main content of university teaching quality evaluation is described, which consists of six parts. Then, the subjectivity problem of teaching quality evaluation system is analyzed, and the effectiveness problem of evaluation result is discussed. Finally, using the advantage of cloud model in dealing with fuzziness and randomness of statistics problem, a teaching quality evaluation method based on cloud model membership is proposed, which can improve the reliability and reduce the subjective disturbance. Taking the evaluation data of an engineering mechanics course as a case, the traditional subjective observation exclusion method and statistical standard deviation exclusion method, and the proposed cloud model membership exclusion method and cloud model membership combination method are utilized to evaluate the teaching quality, respectively. The results show that the cloud model membership combination method can precisely evaluate the teaching quality. The method not only reduces the disturbance of subjective factors, but also improves the effectiveness of teaching quality evaluation results.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:August 22,2020
  • Revised:October 16,2020
  • Adopted:November 30,2020
  • Online:
  • Published: