Application of Artificial Intelligence-based Visual Arts Pedagogy in Traditional Painting Education

被引：0
|
作者：
Wu, Qiang [1 ]
机构：
[1] Kashi University, Xinjiang, Kashi,844006, China
来源：
Applied Mathematics and Nonlinear Sciences | 2024年 / 9卷 / 01期
关键词：
Traditional art has a deep cultural heritage and rich connotation, combining artificial intelligence technology with traditional aesthetics as a way to realize the innovation of traditional painting education mode. In this paper, starting from the performance of traditional painting's aesthetic value, a personalized intelligent painting teaching mode is constructed based on the visual art teaching method and combined with artificial intelligence. The CCME-GAN model is introduced for the construction of a personalized painting learning generation model, and the BERT-LDA model is established by combining the BERT model and the LDA model for the intelligent evaluation of personalized painting works. Xinjiang folk artworks were selected as the research data source to carry out the validation of personalized painting work generation and assessment, and teaching comparison experiments were designed to analyze the teaching effect of the personalized intelligent teaching mode. The subjective evaluation score of Xinjiang folk art paintings generated by the CCME-GAN model was 9.11, and among the nine clustering results of painting work assessment, the eigenvalues of the theme of painting evaluation of Cluster 1 range between [0,5.5]. At the end of the teaching experiment, students' creativity scores increased from 2.74±0.37 before the experiment to 4.63±0.26. Relying on artificial intelligence technology can enhance the teaching effect of traditional painting methods and improve students' painting levels. © 2024 Qiang Wu, published by Sciendo;
D O I：
10.2478/amns-2024-2994
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