Intelligent Matching Research on Ideological-Political and Aesthetic Education Integrated Course Content Based on Deep Learning
Year: 2026
Type: conference-paper
Abstract: Addressing the problems of low efficiency and insufficient accuracy in matching content for the integration of ideological-political education and aesthetic education courses, this paper proposes an intelligent matching method based on deep learning. This method constructs a multi-modal feature extraction network that integrates multi-dimensional information such as course text semantics, knowledge graphs, and teaching objectives to achieve precise alignment between ideological-political elements and aesthetic education content. First, the BERT model is employed to extract deep semantic features from course texts, and graph convolutional networks are utilized to model knowledge association relationships. Second, an attention mechanism is designed to fuse multi-source features and construct a matching degree calculation model. Finally, the effectiveness of the method is validated through real course datasets. Experimental results show that the proposed method achieves matching accuracy, recall rate, and F1-score of 92.347%, 89.521%, and 90.912% respectively, representing significant improvements over traditional methods and providing effective technical support for the construction of integrated ideological-political and aesthetic education courses.
Authors: Yuan Xu, Jiaxing Zhuo
Institution: Chongqing Three Gorges Vocational College
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7160083000