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Universities are considered the main place for university students to study and live and also shoulder the important task of training talents for the future of our country. As a manager of university education and the relevant supervisor of education and teaching, it must constantly seek more efficient teaching mode and use the new communication platform in order to solve the current problems in the management of higher education. Since the media platform plays an important role in the social and political and economic life, it affects the way of education and the way of thinking in universities. Self-media technology promotes the communication between teachers and students in the teaching process. Educators can carry out a variety of teaching through the media, which innovates the educational methods of the University. This fully reflects the advantages of we media teaching in the media era. As a new means of information dissemination, the self-media platform not only has the traditional media communication functions but also gradually affects the way of thinking and lifestyles of university students to promote their correct world outlook, outlook on life, and formation of values. In this paper, self-media platform is used for university education and operation management process to conduct a systematic analysis and research. The Delphi method is used to screen out five major dimensions of hardware platform, content construction, communication mode, the quality of teachers and students in universities, and the environment of media network dissemination and interpret the positive effects of self-media platform in improving university teaching and operation management efficiency. Based on particle swarm optimization (PSO) algorithm, the importance distribution of the five dimensions is identified and an optimal path of university education operation and management is constructed to improve the overall efficiency of university education operation and management. [ABSTRACT FROM AUTHOR]

To construct the network organizational structure of college students' educational management and realize the informatization development of college students' educational management, the construction method of network organizational structure of college students' educational management is proposed based on the distributed network. MySQL and PostgreSQL are used as the bottom data structure models of the network-based organizational structure of college students' education management, and the multisource information scheduling method, which is used to construct the transaction identifier (TID) labeling tuple model of college students' education management network. The initial topological structure model of the network-based organizational structure nodes of college students' education management network is constructed by the 4-tuple model, and the linear structure decomposition of the construction nodes of the network-based organizational structure of college students' education management is carried out. The correlation characteristics of the transmission channel of the network organization structure of college students' education management are extracted; the three-layer architecture system of data layer, network layer, and application layer is adopted; the architecture model of the network organization structure of college students' education management is established; the multinode distributed network transmission technology is used to build a tree structure model, so as to realize the design of the network organization structure model of college students' education management and the scheduling of multi-source information parameters; and the fuzzy multi-attribute decision-making method to realize the adaptive scheduling of the network organization structure of college students' education management is adopted, so as to improve the storage management, fault tolerance, and safe access ability of the network organization structure of college students' education management. The test results show that the network organizational structure of college students' educational management is designed by this method, which improves the ability of information transmission and scheduling and improves the informatization level of college students' educational management. [ABSTRACT FROM AUTHOR]

Colleges and universities are crucial hubs for talent development, carrying out the vital task of supplying top-notch talent for all spheres of society. The growth of society and the economy is significantly influenced by the quality of education and teaching. A significant factor is the caliber of the instruction. Therefore, it is essential to innovate the educational management model in order to promote the holistic development of college students as well as the orderly development of educational and teaching activities in colleges and universities. The college and university music education model has made progress after years of development. In spite of its successes in reform, there are still a lot of issues that require close attention. The education system is constantly being updated and improved in order to meet modern development needs. It is essential to develop innovative strategies with strong operability from multiple perspectives in response to the actual issues that arise in order to carry out the reform work smoothly and steadily advance the innovation of the management model of music education in colleges and universities. This paper analyzes the teaching impact of the single-line education management model and the credit system education management model and predicts the students' musical performance based on the gray theoretical model and the big data platform. The experiment revealed that as learning time increases, the teaching effects of the two learning modes increase, but it is evident that the credit system education management mode's teaching effect is superior. The single-line education management model among them has an average score of 83.3 points, and the credit system education management model has an evaluation score of 86.1 points. [ABSTRACT FROM AUTHOR]

Monitoring and guiding instructional management require student performance evaluation. Traditional evaluation and analysis methods based on absolute scores, on the other hand, have certain flaws and are unable to fully reflect the information contained in student performance, thus limiting the impact of student performance evaluation on teaching and learning management. Data mining is regarded as the backbone technology for future information processing, and it introduces a new concept to the way humans use data. Schools must analyse and evaluate the performance of students in the same grade level and secondary school in a timely and staged manner. Clustering is a type of data mining that uses similarity rules to classify sample data into groups with a high degree of similarity. To address the difficulties caused by the wide variation in course difficulty in student performance evaluation, a method based on the K-means clustering algorithm is proposed. The K-means algorithm and the improved K-means algorithm with student information are investigated. The test results showed that the K-means clustering algorithm, the improved algorithm in this paper, and the fast global mean clustering algorithm all cluster the same randomly generated data set with noisy points, but the clustering time of the algorithm in this paper is only 0.04, which has obvious advantages. As a result, the clustering algorithm-based higher education management and student performance evaluation mechanism provides some insights for future research on student learning patterns. It is hoped that instructional administrators will gain a better understanding of students' learning characteristics so that they can better guide their teaching. [ABSTRACT FROM AUTHOR]

With the continuous development of social economy, education has received more and more attention. As an important part of higher education, it has been profoundly influenced by the era of data in recent years. In order to evaluate the impact of big data on higher education management, this paper introduced a time-varying lens algorithm (TLA) to analyze the business needs of teachers and education management by sorting out the business processes of education management, education thinking, and education practice. Through learning and mining the corresponding technology, improve the corresponding educational ability, and use big data to assist the management of higher education. The simulation results show that the time-varying clustering sampling algorithm is effective. [ABSTRACT FROM AUTHOR]

With the rapid development of information technology, the integration of multimedia technology and traditional institutional systems is increasing. However, at present, the establishment and construction of the higher education system in China are not proportional, the function is vague, and the communication efficiency is not high. The reason for this phenomenon is that the traditional higher education management system has been unable to meet the needs of information society and information integration and it is unable to meet the increasing demand for higher education. Therefore, based on the above reasons, it is very important and has long-term strategic significance to establish an efficient and convenient higher education management system based on today's Internet multimedia technology in a timely and reasonable manner. This paper analyzes the current status of the higher education management system and the problems that are arisen and proposes a three-dimensional integrated management system based on the innovation of Internet multimedia technology. At the same time, aiming at the urgent needs of the current lifelong education of higher education, a reasonable system of higher education diversion is established to focus on solving the phenomenon of imbalanced proportions, ambiguous functions, and low communication efficiency. In the final practical part of this paper, the system model of the three-dimensional integrated education system and the corresponding practical solution to the education diversion are given. After discussion, it has practical application value. The results of the research have shown the effectiveness of the proposed study. [ABSTRACT FROM AUTHOR]