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  4. Vol 8, Issue 2, 2024

Evaluation System of College Ideological and Political Education Index Based on Data Mining Algorithm

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DOI: 10.23977/acss.2024.080203 | Downloads: 10 | Views: 294

Author(s)

Bahao Li 1

Affiliation(s)

1 College of Economics, Jiujiang University, Jiujiang, Jiangxi, 332005, China

Corresponding Author

Bahao Li

ABSTRACT

The Intellectual and Political (IAP) education provided in colleges and universities is a significant component of higher education and is crucial to developing the socialist cause with Chinese characteristics and enhancing the IAP abilities of college students. The construction of college IAP education index assessment system based on multimodal learning type data mining algorithm can solve the current situation of the lack of college IAP education index assessment system. Therefore, this paper constructed an assessment system of college IAP education indicators based on data mining algorithm. It was a system that conformed to the requirements of the development of the times and the laws of education and had good human-computer interaction. Through the experiment, the comprehensive satisfaction score of the sample to the assessment system of college IAP teaching indicators based on data mining algorithm was about 4.19, and the comprehensive satisfaction score to the traditional assessment system of college IAP teaching indicators was about 2.87. The college IAP education index assessment system based on data mining algorithm was superior to the traditional college IAP education index assessment system, which made the assessment activities effectively play the role of summing up experience, learning lessons, promoting work improvement, establishing goal orientation, etc.

KEYWORDS

Evaluation of the Teaching of Civics, Data Mining Algorithms, Multimodal Learning, Human-computer Interaction

CITE THIS PAPER

Bahao Li, Evaluation System of College Ideological and Political Education Index Based on Data Mining Algorithm. Advances in Computer, Signals and Systems (2024) Vol. 8: 12-21. DOI: http://dx.doi.org/10.23977/acss.2024.080203.

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