Modern Art Education and Teaching Based on Artificial Intelligence

计算机科学 雕刻 视觉艺术教育 绘画 学习风格 人工智能 数学教育 多媒体 视觉艺术 数学 艺术 艺术
作者
Wen Zhang,Achyut Shankar,A. Antonidoss
出处
期刊:Journal of Interconnection Networks [World Scientific]
卷期号:22 (Supp01) 被引量:34
标识
DOI:10.1142/s021926592141005x
摘要

The rapid advancement of artificial intelligence has been intensely employed in art teaching and learning. Including the advancement of smart technologies, there are various difficulties in improving the teaching capability of technical art design courses, including the impact of several variables and the absence of quantitative study, and the imperfection in the index system. The paper proposes the Artificial Intelligence assisted Effective Art Teaching Framework (AIEATF) to expand the ability to adapt to AI-oriented art instruction, develop intelligent teaching styles, and enhance AI-oriented art teaching art knowledge and environment. The potential of improving AI’s effects on major art courses’ teaching effect has been illustrated in detail. On this basis, an assessment model has been developed to consider the enhancing effects. The study’s findings include a valuable guide for educators in art design to strengthen their teaching ability. The experimental results have shown that Modern Painting Perfection Ratio is 87.66%, Computer graphical representation ratio is 88.77%, Photographical Design Percentage ratio is 84.50%, Performance of Carving in Sculpture Ratio is 82.26%, Construction Development Ratio is 93.83%, Expressive Musical Performing Ratio is 92.70%, Energized Dance Performance Ratio is 84.26%, and overall performance ratio is 92.30%.
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