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  • 标题:Postgraduate Training Performance Evaluation Applying Weighting and Comprehensive Fuzzy Evaluation Methods
  • 本地全文:下载
  • 作者:Mei Wang ; Zeng Zhang ; Mi Xu
  • 期刊名称:International Journal of Emerging Technologies in Learning (iJET)
  • 印刷版ISSN:1863-0383
  • 出版年度:2021
  • 卷号:16
  • 期号:01
  • 页码:124-133
  • DOI:10.3991/ijet.v16i01.18231
  • 出版社:Kassel University Press
  • 摘要:Postgraduate training performance evaluation is an important part of higher education evaluation. In order to quantitatively evaluate the performance of postgraduate training combined with the needs of talent training in colleges and universities, a comprehensive evaluation system for postgraduate train-ing performance is designed and proposed. The analytic hierarchy process and the entropy method are combined to determine the weights of seven in-put and output indicators, such as funding input, teacher source input, sci-entific research ability, and graduate output quality. The comprehensive fuzzy evaluation model is also applied. This paper tests the above models to evaluate the graduate training performance of 20 colleges at Tianjin Univer-sity. It is found that the weight of student input and graduate output quality combined is 87.69%, which makes them the key indicators to measure the performance of graduate training. Furthermore, it is concluded that the per-formance of the science college was significantly higher than that of the humanities college.
  • 关键词:Postgraduate training;performance evaluation;Combination weighting;fuzzy evaluation model
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