江汉大学学报(自然科学版) ›› 2018, Vol. 46 ›› Issue (2): 125-129.doi: 10.16389/j.cnki.cn42-1737/n.2018.02.004

• 计算机科学 • 上一篇    下一篇

基于改进BP神经网络的高校教师创新创业教学能力评价研究

崔铭,吴亚光   

  1. 河北金融学院 教务处, 河北 保定 071000
  • 出版日期:2018-04-28 发布日期:2018-04-12
  • 作者简介:崔铭(1982—),男,讲师,博士,研究方向:大学生创新创业教育。
  • 基金资助:
    河北金融学院创新创业教育改革研究项目(2017CXCY28)

Evaluation of Innovation and Entrepreneurship Teaching Ability of College Teachers Based on Improved BP Neural Network

CUI Ming,WU Yaguang   

  1. Dean′s Office,Hebei Finance University, Baoding 071000,Hebei,China
  • Online:2018-04-28 Published:2018-04-12

摘要: 创新创业教育迅速发展且在高校占有重要地位,对创新创业教学能力评价的研究具有重要现实意义。针对当前创新创业教学能力评价存在的偏向定性评价、较少的非线性定量评价、不考虑创新创业教学特殊性、评价发展性功能弱、评价效率低等问题,设计了全方位、凸显创新创业的教学能力评价体系。将改进的BP 神经网络评价方法引入高校教师创新创业教学能力评价中,改进BP 神经网络训练,提升评价效率和对专家思维进行模拟,其评价效度高,在高校教师创新创业教学能力评价中值得推广实践。

关键词: 创新创业教学能力, 评价指标体系, 改进BP神经网络评价法

Abstract: Innovation and entrepreneurship education develops rapidly and has an important position in universities. It is of great practical significance to study the evaluation of innovation and entrepreneur? ship teaching ability. At present, there are some problems in the evaluation mechanism of education capability of innovation and entrepreneurship, mainly focusing on the qualitative evaluation method, and the non-linear quantitative evaluation method is less used. In the evaluation process, the particularity of innovation and entrepreneurship teaching is not considered, which is very different from other courses.In addition, the development function and efficiency of evaluation are low. Aiming at the problems in the evaluation, the writer designed a comprehensive evaluation system which highlighted innovative entrepreneurial ability of teaching. The improved BP neural network evaluation method was led into the evaluation of teaching ability of university teachers on innovation and entrepreneurship, the neural network training was improved to promote efficiency of evaluation and simulate the experts′ thinking. The proposed method has high evaluation validity, it is worthy of popularization in evaluation of teachers′ ability on innovation and entrepreneurship.

Key words: innovation and entrepreneurship teaching, evaluation index system, improved BP neural network

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