Design of Innovation and Entrepreneurship Education Ecosystem in Universities Based on User Experience

In this paper, the student documents are processed by experimental strategy, with the topic of college innovation and entrepreneurship resources recommendation, word diffusion and improved LDA topic model distribution training, set the training topic model and the number of topic top-words, and compare the high-frequency vocabulary and the probability distribution error of the 80% user coverage case and 90% user coverage case. Explore the stability of social media information pushing, the performance comparison results of both combine LDA based on user comment information text and LDA modeling directly using user comment information text as a reference. Select the experimental objects of innovation and entrepreneurship resources in colleges and universities, obtain the recommendation information of innovation and entrepreneurship resources in social media, and analyze the accuracy and satisfaction of algorithmic recommendation. Analyze the sharing characteristics of algorithmic recommendation information on social media and propose educational countermeasures against its adverse effects. According to the analysis, the improved LDA topic model results in a 15% and 85% increase in the number of same words in each topic when top_words is 10. When top_words is 20, the proportion of the same words in each theme is 15% and 78%, respectively. This indicates that the innovation and entrepreneurship education topic features are stable, and the accuracy and satisfaction of the algorithmic recommendation have improved.

Section: Introductionmentioning

confidence: 99%

Innovative and entrepreneurial education reform strategy based on algorithmic recommendation of social media information sharing characteristics in colleges and universities

Dai

2023

“…Colleges and universities need to further update their concepts, combine the characteristics of the training of teacher training professionals, and focus on the advantages of colleges and universities [7][8]. Help students to master the basic theory professional skills and, at the same time, the cultivation of innovation and entrepreneurship awareness and ability to expand in order to adapt to the needs of the development of the times [9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Heyuan Ma, Xue Yang and Kaiyue Qi. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] …”

mentioning

confidence: 99%

Research on the enhancement path of talent cultivation in the integration of dual-creation education and professional education for teacher training majors in colleges and universities based on multivariate statistical analysis

Ma,

Yang,

2023

In today’s society, under the demand for high-quality talents, the professionals cultivated in colleges and universities should not only master professional skills but also need to have the spirit of innovation and entrepreneurial ability in professional aspects. In this paper, firstly, the multivariate statistical analysis method is explained, and the basic principles of the factor analysis model, principal component analysis method and systematic clustering method are given to analyze the data in the following article. Secondly, starting from the necessity of the integration of bi-initiative education and professional education of teacher training majors in colleges and universities, we constructed the 4344 specialized and innovative integrated talent cultivation model of teacher training majors and constructed an evaluation system to evaluate the effectiveness. Finally, based on the evaluation system, the data analysis of the specialized and creative integrated talent cultivation model was carried out using factor analysis, principal component analysis and systematic clustering method. The results show that in the factor analysis, the highest loading value of the first principal factor is 0.917, the contribution rate of the first principal factor is 39.67%, and the loading value of the principal component factor reaches the highest value of 0.925. The clustering analysis is based on the results of the factor analysis, and the respondents are divided into 4 clusters. The number of people in the 2nd category is more than 30 people, which accounts for about 31.41% of the total number of people. The method of multivariate statistical analysis can be used to analyze the data effectively for the specialized and integrated personnel training mode of teacher training in colleges and universities and also gives the path of specialized and integrated personnel training for teacher training.

“…The system was constructed using four aspects: environment, investment, process, and result. Following an analysis of the theory governing the construction of educational ecosystems in colleges and universities, literature [13] created a scientific ecosystem for innovation and business ownership instruction in colleges and universities based on user experience. It also demonstrated through experimentation that the ecosystem designed in this study has high data productivity, high fault tolerance, low packet loss rate, and system energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Research on the Construction Problems of Innovation and Entrepreneurship Education Programs in Higher Vocational Colleges and Universities under the Background of Digital Technology Era

2023

Entrepreneurship and innovative education have emerged as a new paradigm for the development of higher vocational abilities in the modern era, leaping into the global trend and tendency of higher education’s change and growth. The objective of this study is to explore the current state of innovation and entrepreneurship course construction in higher vocational schools. Specifically, we extracted students’ behavioral characteristics using the short-term behavioral sequence of attention and used the SVM model to predict the classification of innovation and business ownership education courses in higher professional colleges. Data mining was used to combine background information from the digital technology era to construct these courses in higher vocational schools. Furthermore, a multivariate linear regression model based on students’ comprehensive ability to innovate and entrepreneurship is established after the problems associated with curriculum construction are analyzed in order to investigate the relationship and impact between curriculum construction and students’ ability to innovate and entrepreneurship. The findings indicate that there is a general lack of an entrepreneurial culture in schools, a poor cultural heritage of entrepreneurship, a gender difference of 6.1, a lack of faculty strength, and a lack of funding, to the tune of 5.2 and 4.4, respectively, and the comprehensive ability of innovation and entrepreneurship of students = 0.30+0.25*curriculum structure+0.54*curriculum implementation+ 0.15*curriculum evaluation. Higher vocational institutions looking to enhance the way their courses on innovation and entrepreneurship are constructed can use the results of this study to guide their research.