In order to make efficient use of the effective teaching time in the classroom, students’ learning of Ideological and Political (hereinafter referred to as IP) courses has been strengthened. At the meanwhile, students’ understanding of IP curriculum knowledge has been deepened to cultivate students’ logical thinking ability, so as to strengthen the teaching effect of IP curriculum. This paper clarified the collection, processing, mining, analysis and other processes of big data mining by analyzing the elements of big data mining. At present, the problems existing in IP classroom assisted instruction were analyzed in multiple dimensions. Big data mining technology was utilized for the IP classroom assistive teaching system and wireless communication technology was utilized for the design of the assistive teaching system application. Then, BP neural network algorithm under machine learning was used to construct the IP classroom aided instruction system. Finally, the BP neural network algorithm based on machine learning was combined with experimental investigation for analysis. The experimental investigation showed that the IP classroom aided teaching system built by utilizing the system platform of big data mining technology and the BP neural network algorithm under machine learning has improved the IP learning efficiency by 23.25%.

Fengjun Yan. Ideological and Political Classroom Assistant Teaching System Based on Big Data Mining and Machine Learning. International Journal of New Developments in Education (2024), Vol. 6, Issue 10: 101-110. https://doi.org/10.25236/IJNDE.2024.061016.

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