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In recent years, there have been more than 7 million college graduates in China every year. Management, teachers, teaching, family, and society. Finally, a summary of the whole article is made. Deep learning (DL) emphasizes the understanding, application, and creation of knowledge and forms a natural close relationship with the cultivation of innov...
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... According to the research, the improvement of instructional design, the revision of instructional methods and procedures, and the development of instructional assessment strategies should serve as the impetus for the growth of DL-based creativity and entrepreneurial aptitude (EA) among college students. It is crucial reading for schools that want to alter how they teach innovation and entrepreneurship, allowing for the development of specialized courses, the construction of high-quality courses, enhanced teaching e cacy, and enhanced student learning [10].The study presents an evaluation model for GRNN optimization using set pair analysis theory, variable fuzzy set evaluation theory, and the Chaos bat technique. The ndings support the expansion of college-level innovation and entrepreneurship programs for clean energy majors and provide an evaluation of their long-term viability [11].The study analyzed how students thought about and dealt with a technologically sophisticated case study in a design thinking course meant to educate them on entrepreneurial skills. ...
The traditional approach to talent development in education and workforce preparation is no longer sufficient to meet the dynamic demands of today's society and economic landscape. Modern policies aimed at promoting innovation-driven development require individuals to exhibit significant ingenuity and initiative. A growing concern shared by all sectors of society revolves around the status of student innovation and entrepreneurship (IAE) education, particularly within the context of the workplace. The unceasing pressures of economic growth have laid bare the inadequacies of the conventional talent cultivation model. It is now evident that relying solely on traditional educational methods cannot adequately equip students with the skills and mindset necessary to excel in an economy driven by innovation. In China, the domain of IAE education within universities is still in its early stages, but it is steadily advancing in both research and implementation. The recognition of the urgent need to adapt education to the demands of the 21st-century economy has sparked a surge in efforts to enhance IAE curricula. A noteworthy step in this direction is the innovative utilization of K-Means clustering (KMC) in college entrepreneurship instruction. This approach provides distinct advantages by clarifying the terminology associated with the evolving field of entrepreneurship and educational theory. It enables a deeper comprehension of concepts like entrepreneurship and the pursuit of change, which are essential in nurturing innovative mindsets and initiatives among students.
... Hu et al. believed that in the module of professional basic curriculum setting, the premise of improving innovation and entrepreneurship ability is to cultivate students' entrepreneurial consciousness [35]. Guo used deep learning to emphasize that innovation and entrepreneurship ability should be the understanding, application, and creation of knowledge and form a naturally close relationship with the cultivation of entrepreneurial consciousness [36]. Ratten et al. believed that entrepreneurial consciousness affected individual entrepreneurial decision-making. ...
Background: Innovation and entrepreneurship education is the fundamental way to apply talent training in colleges and universities. The improvement of innovation and entrepreneurship ability is the embodiment of the success of innovation and entrepreneurship education. This paper discusses the influence mechanisms of entrepreneurial consciousness, entrepreneurial motivation, and entrepreneurial cognition on innovation and entrepreneurship ability. It analyzes the effect of the entrepreneurial atmosphere on the relationship between entrepreneurial consciousness, entrepreneurial motivation, and innovation and entrepreneurship ability. Methods: Based on the data from 1944 questionnaires, we used SPSS24.0 and AMOS22.0 software to analyze the composition and influencing factors of college students’ innovation and entrepreneurship ability. We constructed a structural equation model for empirical research. Results: The results showed that the scale of innovation and entrepreneurship ability had good reliability and validity. Entrepreneurial consciousness, entrepreneurial motivation, and entrepreneurial cognition had significant positive effects on innovation and entrepreneurship ability. Entrepreneurial atmosphere plays a moderating effect in the process that entrepreneurial consciousness affects innovation and entrepreneurship ability and entrepreneurial motivation affects innovation and entrepreneurship ability. Finally, based on China’s national conditions, we proposed suggestions to improve college students’ innovation and entrepreneurship ability from the two aspects of education and base construction to provide a reference for colleges and universities to transport entrepreneurial talents to society.
The quality evaluation of innovation and entrepreneurship (I&E) in the education sector is achieving worldwide attention as empowering nations with high quality talents is quintessential for economic progress. China, a pioneer in the world market in almost all sectors have transformed its educational policies and incorporated entrepreneurial skills as a part of their education models to further catalyst the country’s economic progress. This research focuses on building a novel hybrid Machine Learning (ML) model by integrating two powerful algorithms namely Random Forest (RF) and Logistic Regression (LR) to assess the intensity of the I&E in education from the data acquired from 25 leading Higher Educational Institution’s (HEI) in different provinces. The major contributions to the work are, (1) construction of quality index for each topic of interest using individual RF, (2) ranking the indicators based on the quality index to assess the strength and weaknesses, (3) and finally use the LR algorithm study the quality of each indicator. The efficacy of the proposed hybrid model is validated using the benchmark classification metrics to assess its learning and prediction performance in evaluating the quality of I&E education. The result of the research portrays that the universities have now started to integrate entrepreneurship skills as a part of the curriculum, which is evident from the better ranking of the topic curriculum development which is followed by the enrichment of skills. This comprehensive research will help the institutions to identify the potential areas of growth to boost the economic development and improve the skill set necessary for I&E education among college students.
