The construction of the index system is incomplete in the accuracy evaluation of ideological and political work in Colleges and universities, which leads to the poor effect of the accuracy evaluation of ideological and political work in Colleges and universities. Therefore, this paper proposes to introduce artificial intelligence big data technology to improve the accuracy of ideological and political work in Colleges and universities. Analyze and improve the starring participants in ideological and political work in Colleges and universities, determine the basic principles to improve the accuracy of ideological and political work in Colleges and universities, determine the importance indicators of ideological and political teachers’ teaching, students’ classroom learning, after-school practice, and school ideological and political work, and divide them into primary indicators and secondary indicators. The naive Bayesian model is used to decompose the accuracy indicators of ideological and political work in Colleges and universities, build the accuracy evaluation model of ideological and political work in Colleges and universities, and realize the research on improving the accuracy of ideological and political work in Colleges and universities. The experimental results show that this method can effectively improve the integrity of the accuracy evaluation index of ideological and political work in Colleges and universities and improve the accuracy evaluation effect of ideological and political work in Colleges and universities.
In order to be able to provide learning resources for learners anytime and anywhere and improve the quality of online teaching, a network-assisted teaching system for college students’ ideological and political courses based on the Android system is designed. The characteristics of the Android system platform and its hierarchical structure are analyzed, and the overall structure of the network-assisted teaching system was designed based on it and through the construction of the system user login module, learning resources module, operation management module, unit test module, and teaching interface display module, so as to achieve the effect of network assisted ideological and political course teaching. The preferences of students were fully considered, the needs of students with different resource spaces were matched, and the genetic algorithm is used to share the information of network teaching resources to meet the needs of ideological and political teaching. According to the experimental results, the system designed in this paper has high accuracy in the recommended content of ideological and political education resources and the coverage of resource recommendation is relatively high, indicating that the application effect of the system is better.
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