Evaluation of Teachers' Innovation and Entrepreneurship Ability in Universities Based on Artificial Neural Networks

Xingfeng Liu, An Qin
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Abstract

Based on iceberg theory and the questionnaire of competency’s elements, hierarchical index system of evaluation of teachers' innovation and entrepreneurship competency in universities is established. Through researches, we think that analytic hierarchy process(AHP) is a more scientific and reasonable evaluation method whose rationality is checked by satisfactory consistency while the evaluation model of artificial neutral network doesn’t consider weighting. If the samples are more than 30, the evaluation of neural network model of teachers' innovation and entrepreneurship competency can achieve the accurate results and satisfactory requirements. Since the method of artificial neutral network has advantages of strong operability, simple rules and minor errors, it can greatly reduce the workload because it not only eliminates human subjectivity of evaluation and greatly simplifies the process of evaluation, but also improves working efficiency and provides a new way of thinking for evaluation of the teachers' innovation and entrepreneurship competency in universities
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基于人工神经网络的高校教师创新创业能力评价
基于冰山理论和胜任力要素问卷,建立了高校教师创新创业能力的层次评价指标体系。通过研究,我们认为层次分析法(AHP)是一种更为科学合理的评价方法,其合理性以满意的一致性来检验,而人工神经网络的评价模型没有考虑权重。在样本超过30个的情况下,教师创新创业能力的神经网络模型评价可以达到准确的结果和满意的要求。由于人工神经网络方法具有可操作性强、规则简单、误差小等优点,不仅消除了人的评价主观性,大大简化了评价过程,而且提高了工作效率,为高校教师创新创业能力评价提供了一种新的思路
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