Data Collection and Visualization Application of VMware Workstation Virtualization Technology in College Teaching Management
Xilin Xie,
Jun Chu and
Baiyuan Ding
Mathematical Problems in Engineering, 2022, vol. 2022, 1-13
Abstract:
In this study of data collection and visualization application of VMware Workstation virtualization technology in university teaching management, data processing is performed by the SQLServer database processor using VMware Workstation virtualization technology, and finally the radial-based teaching comprehensive evaluation neural network index is used to calculate the quality of teaching management to China’s teaching team is gradually balanced and the comprehensive quality of teaching team is improving; the academic atmosphere is more open; the fields and perspectives of academic research are richer; the distribution of teaching at all levels in China is more balanced, the comprehensive quality of teaching in China is improving, the system of education and scientific research in China’s colleges and universities is improving, and the ecological management system of colleges and universities is improving, and so on. It is also proposed to improve the academic level and establish a strict institutional threshold for the teaching industry in colleges and universities; to effectively implement the policy of freedom and equality in academic and scholarly circles, and improve the system of teaching, principal appointment, and evaluation in higher education institutions; to insist on implementing the principle of academic fairness and optimizing the teaching evaluation system; to innovate and implement the incentive mechanism of teaching in colleges and universities according to the characteristics of talent training of teaching academic career ability; and to establish the access system of teaching career development in colleges and universities to promote academic career development and other suggestions of big data management of teaching in colleges and universities.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6984353
DOI: 10.1155/2022/6984353
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