The Teaching Capacity of Industry Characteristic Counselors Based on Data Fusion and Random Forest Algorithm

Autor: Li Ji, Yingmin Sun, Meimei Sun, Miaomiao Kong
Rok vydání: 2022
Předmět:
Zdroj: Wireless Communications and Mobile Computing. 2022:1-13
ISSN: 1530-8677
1530-8669
DOI: 10.1155/2022/6328826
Popis: The good development of industry-specific universities (hereinafter referred to as characteristic universities) promotes the optimal allocation of national university resources and moreover promotes the development of China’s education, while counselors, as important teaching and research staff, have a very close connection with the development level of the school, directly reflecting the quality and level of education of the school and determining the height of its educational development. Talent is the first productive forces, counselors as teaching talents, and is essential to the construction of industry specialty universities. The evaluation index system of teaching ability of counselors can effectively guide counselors toward the path of specialization, scientifically realize career planning, and maximize the achievement of the general goal of the characteristic school they are in. This article aims to assess the teaching capacity of counselors and targeted training capabilities. The counselor’s ability is reflected in the teaching of teaching, completing teaching objectives and cultivates student’s hobbies. In this paper, through investigating the cultivation methods of different industries, the cultivation of counselor’s ability is to assess consensus and establish multilevel teachers’ teaching capacity cultivation system. The results show that the system can effectively improve the teaching capacity of young teachers and increase 20% of student’s satisfaction; however, it also shows that the professional competence of counselors still needs to be improved.
Databáze: OpenAIRE
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