Refinement Method of Evaluation and Ranking of Innovation and Entrepreneurship Ability of Colleges and Universities Based on Optimal Weight Model

Abstract

With the economic development in recent years, the state has paid more and more attention to education, and more and more college graduates have been graduated. The purpose of this paper is to study how to analyze the refinement method of evaluating the innovation and entrepreneurship ability (IEA) of colleges and universities based on the optimal weight model. This paper proposes a sorting refinement method based on the optimal weight model and uses the BP neural network to determine the optimal weight. Weight is a scoring mechanism for comprehensive ranking, that is, a scoring system. The higher the score, the higher the weight, and the higher the ranking of the relative things. The experimental results of this paper show that in 2013, the number of college graduates in China reached 6.09 million, but the number of employed people was only 4.67 million, an increase of 120,000 over the same period. By 2020, the number of college graduates in China has reached 7.27 million, and the number of employed people has been 5.78 million. However, the number of employed persons is always lower than the number of graduates, indicating that employment is difficult. Under this situation, many college graduates choose to start their own businesses, but the success rate of entrepreneurship is also very low, only about 3%. This shows that the IEA of college graduates is not high, so it is necessary to improve the IEA and conduct self-evaluation.

Application of Big Data in Entrepreneurship and Innovation Education for Higher Vocational Teaching

“…Based on the above domestic and international-level research, most of the current mainstream evaluation analysis models (intelligent analysis algorithms primarily composed of big data analysis technology-based or discrete classification strategy algorithms) in innovative entrepreneurial education evaluation research need to set different rules to achieve adaptive analysis and multi-dimensional changes for various courses (Guo et al, 2022;Matzembacher et al, 2020). In the assessment and optimization of innovative entrepreneurial education, on the other hand, most intelligent analytical models require matching analysis and customizing discussions for different types of innovative entrepreneurial educational programs (Kitsios et al, 2021;Liu & Lin, 2021).…”

Research on the Practice Education Pattern of Innovative Entrepreneurship in Colleges in the Internet Plus Era

“…As China's higher education enters the stage of mass education, college students face unprecedented challenges in entrepreneurship and employment. How to train students to be capable of IE would become an urgent problem for colleges [5,6,7,8].…”

“…The practice and innovation fusion talent cultivation system is constructed from four aspects: cultivation goal, curriculum system, teaching system and guarantee mechanism. Paper [6] proposes a ranking refinement method based on optimal weighting model and determines the optimal weights using back propagation neural network. Results indicate that the number of employed people is always lower than the number of graduates, suggesting that it is difficult to find employment.…”