Applied Mathematics and Nonlinear Sciences (Jan 2024)
Course Ideological and Political Construction and Teaching Practice under Big Data Mining Algorithms
Abstract
The Integration of the Civic and Political elements into the Construction of the algorithmic course is intended to guide students to learn to use the Marxist position, viewpoints, and methods to identify the research direction of the discipline, master scientific thinking, and further strengthen the learning of the algorithmic course. This paper analyzes the teaching objectives of the algorithmic course on Civics and Politics, corresponds the Civics elements with the teaching content of the algorithmic course, and establishes a fusion matrix associated with the teaching content and the Civics content. The optimization of the Construction of the algorithm course’s civic and political objectives, content, course structure, teaching methods, and means are carried out respectively. Construct a closed-loop teaching system for online and offline algorithm courses on ideology and politics, following the OBE concept. Improve the particle swarm optimization algorithm, propose a swarm intelligent resource scheduling algorithm to optimize online algorithm teaching resource management, and analyze the recognition of online quality teaching resources. Analyze the achievement changes before and after teaching the algorithmic civics course using the independent sample T-value test method. The post-test data of the five dimensions of national sentiment, scientific spirit, professionalism, personal development, and Civic and political attitude of the students in the experimental class show P<0.05, and the experimental class and the control class present a difference of 0.05, indicating that the online and offline closed teaching system based on OBE can effectively integrate algorithmic courses and Civic and political elements, and improve the Civic and political cognition of the students.
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