Abstract
When the country vigorously advocates the goal of cultivating innovative and entrepreneurial engineering talents, the quality evaluation of innovation and entrepreneurship education has naturally become a part of the higher education system. However, there are few studies on the quality evaluation of innovation and entrepreneurship education in engineering majors in China. Firstly, through literature research, combined with the current development trend of quality evaluation of innovation and entrepreneurship education at home and abroad, BP neural network-based evaluation method was selected. Secondly, according to the three-element theory of education, namely, the three factors of educators, educators and education, and comprehensive research, the content of quality evaluation of innovation and entrepreneurship education in engineering majors in colleges and universities is determined, that is, from professional links, teaching links and students. Levels to build evaluation indicators. After establishing the evaluation index system, this paper uses Chengdu University of Technology as a research sample to issue questionnaires for engineering students in Chengdu University of Technology to obtain data for use, and to analyze and analyze the data by AHP, so as to obtain the weight of each indicator. Finally, based on the data collected by the questionnaire, the BP neural network data fitting and model training and optimization are carried out to determine the feasibility of the quality evaluation index of innovation and entrepreneurship education in engineering majors in colleges and universities, and to establish BP neural network evaluation model for engineering majors. The innovation and entrepreneurship education quality evaluation system provides new research methods and research ideas, enriches the connotation and breadth of the quality evaluation system of innovation and entrepreneurship education in engineering majors, and makes up for the shortcomings and vacancies in related fields.
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