Development and Training Strategies of College Teachers Based on Data Mining Technology.

With the increasing investment in education in China, higher education institutions have higher requirements for the introduction of teachers. This research mainly discusses the development and training strategies of college teachers based on data mining technology. Data mining technology is dedicated to data analysis and understanding, and the technology of revealing the information contained in the data. It is a frontier research topic in the field of information and database technology. Therefore, the system of monitoring and evaluation of college teaching quality based on data mining is designed for the management of educational affairs in colleges provided convenience. This paper selects an unsupervised classification method: a cluster analysis. This method can not only obtain reasonable classification results but also give consideration to the comprehensiveness of employee development and give reasonable development suggestions for each employee through classification results. For a series of introduced teacher's information, personnel management module should provide the following functions: teacher information management, contract information management, resignation information management, and query teacher personnel information. The recruitment management module often collects the candidate information, registers and stores it, and then conducts a series of personnel screening for these candidates according to the recruitment criteria, and finally determines the possible candidates. Afterwards, a series of comprehensive evaluations are carried out on these selected candidates, and finally the candidates are selected for admission based on the comprehensive performance of the candidates. The K-means clustering algorithm in the cluster analysis method is adopted. This algorithm has the excellent characteristics of high computational efficiency and is suitable for the operation of large amount of data. Through the clustering algorithm, a reasonable assessment method is established, and it is effectively used in the human resources assessment management system. Among the introduced teachers, the number of teachers whose professional title is high, the highest degree is doctorate, and the number of teachers whose papers are published at SCI level accounts for 16%. The data tested by the data mining tool contains 1,400 rows of data. The minimum support is 5%, and the minimum confidence is 90%. This study is helpful for the rational planning of human resources and the promotion of comprehensive competitiveness of colleges and universities. [ABSTRACT FROM AUTHOR]