Ideological and political course is a key course to implement the fundamental task of building morality and cultivating people. Teaching evaluation is an important part of the construction of ideological and political courses. Constructing a perfect teaching evaluation index system is an urgent need to further deepen the teaching reform of ideological and political courses and improve the teaching quality of ideological and political courses. In order to improve the practical application effect of mixed teaching mode, an online and offline mixed teaching effect evaluation method based on big data analysis is proposed. Firstly, the big data in the process of mixed teaching are collected by using big data technology, and the evaluation index system is constructed from three dimensions. The required data are extracted according to the index, and then the association rules between the relevant data of the evaluation index are established, the phase space distribution of the data is obtained. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index-related data to realize the online and offline mixed teaching effect evaluation. The application analysis results show that the method in this paper obtains ideal evaluation results of online and offline mixed teaching effects, which is conducive to improving teaching quality.
Aiming at the problems of slow teaching resource sharing rate, long platform response time, and low student learning efficiency in traditional ideological and political learning platforms, a research on the construction of intelligent media ideological and political learning platforms based on artificial intelligence technology is proposed. We build an artificial intelligence open source development platform framework based on the cloud platform and use the Ceph method to optimize the storage of artificial intelligence training platform data. Under this framework, we design the business process and business module service architecture of the intelligent media ideological and political learning platform. Based on the K-means algorithm, the intelligent media ideological and political learning platform resource management module is designed, the teaching resource database is constructed, and the teaching resource sharing model component module is designed to realize the construction of the intelligent media ideological and political learning platform. The experimental results show that the sharing rate of ideological, political, and educational learning resources on the platform is relatively fast. The response time of the platform is 0.08 s when the amount of ideological and political teaching resources is 16000 MB. Students who are interested and very interested in the teaching account for 89% of the total.
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