Affiliations: [a] Department of Ideology and Politics, Neijiang Vocational and Technical College, Neijiang, Sichuan, China
| [b] English Department, Chongqing Nanfang Translators College (CNTC) of SISU, Yubei, Chong Qing, China
Correspondence:
[*]
Corresponding author. Zheng Rong, Department of Ideology and Politics, Neijiang Vocational and Technical College, Neijiang, Sichuan, China. E-mail: zhengrong@keemail.me.
Abstract: The student’s political and ideological practices is a vital portion of education, and it is related to optimization of task based on fundamental scenario in establishing morality. In order to establish a scientific, reasonable and operable evaluation model for students’ ideological education, and evaluate the status of college students’ ideological education. In this paper, firstly, in view of the shortcomings of evaluation objectives, single evaluation methods, lack of pertinence of evaluation indicators and subjectivity of evaluation standards in the current evaluation system of university students’ ideological and political education, the basic principles for constructing evaluation models of university students’ ideological and political education are put forward. Secondly, in case to meet changing needs of the times, an artificial neural network algorithm based on artificial intelligence data mining and a traditional multi-layer fuzzy evaluation model are designed to evaluate the ideological and political education of college students. This newly proposed model integrates learning, association, recognition, self-adaptive and fuzzy information processing, and at the same time, it overcomes their respective shortcomings. Finally, an example analysis is carried out with a nearby university as an example. The evaluation results display that the evaluation model of students’ ideological education established in this paper is in good agreement with the previous evaluation results. It fully shows that the comprehensive evaluation model of fuzzy neural network for college students’ ideological and political education established in this paper is scientific and effective.
Keywords: Artificial intelligence, fuzzy neural network, ideological and political
education, evaluation model
