Retracted: Intelligent distribution system of university student dormitory based on data fusion optimisation algorithm

This paper focuses on the design of an educational early warning mechanism based on the fusion of ideological education and multi-featured data so as to manage the educational situation of students in colleges and universities efficiently and accurately. In this paper, the wavelet transform, discrete Fourier transform, and lag sequence analysis algorithms are used to effectively extract temporal features of students’ behaviors. PageRank and Hit’s algorithms are employed to extract features related to student concept maps. The emotional tendencies recognition interface provided by Tencent Cloud was used to obtain the emotional features of students’ speeches. Following this, a multi-feature fusion was performed to depict the students’ learning. A Hive-based data warehouse is used to integrate heterogeneous data from multiple sources. Finally, the education early warning model based on multi-feature data fusion is introduced, and the operation mechanism of early warning mechanism for ideological and political education in colleges and universities is established. To verify the effect of this paper’s model against other algorithms, this paper’s model achieves the optimal performance in the F1 score in negative samples, which is 0.91, followed by the TPA-LSTM algorithm, which is 0.88. Before the optimization of the early warning mechanism, the average per capita absenteeism of the students was 1.32 sessions, and the rate of disciplinary actions was 0.0291. At the end of the academic year, the average per capita absence rate decreases to 1.24 sessions, and the disciplinary action rate decreases to 0.0245.

Section: Educational Early Warning System Architecture Designmentioning

confidence: 99%

Integration Development of Civic Education and Student Management in Colleges and Universities Based on Combining Data Fusion Model in the Context of Exquisite Parenting

Jing

2023

“…Big data technology influences people's cognitive way with its massive and diversified information characteristics. In the era of big data, in order to make new progress in the education and management of students in colleges and universities, it is necessary to innovate the concept of management and give full play to the advantages of big data [13][14][15]. Grasp the development opportunities brought by the era of big data, integrate educational resources, take the scientific development concept as the guidance, take scientific parenting as the goal, take innovation and development as the opportunity, and make full use of big data as well as the sharing function in student management, and innovate the education and management of students [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…Zhengrong Ding, Nana Gao. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] …”

mentioning

confidence: 99%

Exploration of Optimisation Mechanism of Innovation and Entrepreneurship and Student Management for College Students Driven by Big Data

Ding,

Gao

2024

The current employment situation is getting tighter and tighter, and innovation and entrepreneurship of college students have gradually become the focus of attention of the government and colleges and universities. This paper preprocesses the student data, constructs the data matrix using the gray prediction algorithm, uses the least squares method, establishes the differential equation solution, and obtains employment prediction data. For the employment prediction can be known to the innovation and entrepreneurship situation of college students, this paper further introduces the Logistic regression analysis, establishes a multivariate regression analysis algorithm based on the influencing factors of innovation and entrepreneurship, and provides theoretical support for the study of the influencing factors and the optimization mechanism of the management of innovation and entrepreneurship student management. This paper takes University H in Zhejiang Province of China as the research site to explore the current situation of innovation and entrepreneurship of its college students in depth. The students who choose self-help entrepreneurship in 2022-2023 only accounted for 2.42% and 2.04%, and the predicted percentage in 2024 is 1.93%, so the current situation of innovation and entrepreneurship is dismal. In the analysis of college students’ innovation and entrepreneurship influencing factors, the factors of specialty, personal work experience, and buddy entrepreneurship experience all showed significant differences (P<0.05). In the regression analysis of entrepreneurship education and entrepreneurship policy on entrepreneurial intention, the regression coefficients of entrepreneurship education and entrepreneurship policy are 0.276 and 0.136, respectively, which both reach the level of significance, and all of them are in a significant positive proportional relationship.

“…In the new historical period, society has entered a stage of rapid development, and the improvement of the national economy is maintaining a strong momentum of development [1]. According to the situation of economic development of countries around the world, today has become an important stage of modernization, and at the same time, social contradictions have become increasingly prominent [2][3].…”

Section: Introductionmentioning

confidence: 99%

Research on Informatization Integration Strategy of Student Management and Civic Teaching Work in Colleges and Universities in the Internet Era

2024

To do a good job of school ideological and political work and ideology work in the Internet era, it is especially important to integrate the organic integration of Civic and Political teaching and student management. This paper takes H city as an example and establishes an evaluation index system for student management and informationalization of ideological and political teaching. After normalizing and quantifying the indicators, the entropy weight method is used to solve the weights of the indicators, and the coupling coordination degree model is established to judge the integration level of the two informatizations. To investigate the integration factors of the two, the gray correlation coefficient and the degree of correlation between the indicators are derived using the gray correlation method. The results show that the average annual growth rate of the integrated development level between the two is 4.42% and 8.15% during 2011-2020, and the coupling degree is higher on the whole, with an average of 0.8994, and the coupling degree of coordination is also on the trend of increasing year by year. The gray correlation between the two is high, in which the correlation between the working mechanism of cooperative education in the informatization of the work of Civic Teaching and the quality of practice indicators and student management reaches 0.7806 and 0.7876. To diversify, it is necessary to develop the integration of student management and Civic Teaching based on the research in this paper.