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

Author:

Liu Xingfeng1,Qin An1

Affiliation:

1. Guangzhou Railway Polytechnic, China

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, the authors 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.

Publisher

IGI Global

Subject

General Computer Science

Reference31 articles.

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