Abstract
With the rapid development of artificial intelligence, its application in art education is becoming increasingly widespread, providing students with new ways to enhance creativity and critical thinking. This paper analyses the specific application of artificial intelligence in art education and explores how it fosters students' creativity through innovative teaching methods, personalized learning, and thinking guidance in artistic creation. At the same time, the study also reveals the positive role of artificial intelligence in helping students to screen and criticize information, analyze and evaluate art works, and encourage innovative thinking and critical thinking. The research demonstrates that artificial intelligence significantly enhances students' independent thinking and critical appreciation of art, improving their artistic literacy and innovation while supporting the modernization of art education.
References
Wang Ping.2018.Analysis of the relationship between artificial intelligence and visual communication design talent training. Art Technology ( 07 ) : 3.
Zhang Min.2016.Practical Research on Water Painting Teaching in Primary and Secondary Schools. China Ethnic Expo ( 24 ) : 6-27.
DOI:10.3969/j.issn.1007-4198.2016.24.014.
Cao Kexi.2018.Opportunities and challenges in the application of artificial intelligence in education. New Curriculum Research ( 03 ) : 5-27 + 39.
Li henhong. 2018.Research on personalized teaching of artificial intelligence. Digital design 7 ( 12 ) : 34.
Leng Chunlin. 2011. The necessity of cultivating students ' color sensibility in color teaching. Popular literature and art ( 20 ), 269 + 262.
Ren Nan. 2019. Research on the application of artificial intelligence in art design. ArtTech ( 13 ), 149-150.
Xu Shuangshuang, Ding Wei and Bei Dianhui.2018. The application and breakthrough of artificial intelligence in art design. Design ( 12 ), 104-105.
Chen Min. 2023. innovative application of modern illustration art in animation design. Toy World ( 01 ), 72-74.
Mo Jianwen, Zhang Tong, Yuan Hua and Ouyang Ning. 2016. The application of deep learning in the teaching practice of image processing technology course is discussed. Education and Teaching Forum ( 09 ), 115-116.
Wei Xianjun. 1995. class design of art creation course in primary school. Chinese art education ( 04 ), 5-6.
Zhang Hongxia. 2002. the significance and localization of scientific literacy education. Educational Research of Tsinghua University ( 04 ), 20-26.
Song Song, Xu Zhe. 2018 Research on critical thinking in ideological and political education in colleges and universities. Journal of Hubei Correspondence University ( 13 ), 62-63.
Jin Changhao. 2013. College oil painting landscape painting teaching. Art Education ( 01 ), 142 + 150.
Chen Jie, Jun Wei. 2015. Model analysis of quantitative evaluation of works of art. School ( 05 ), 18-19...
Luo Yuhong, Qin Jie, Luo Ding, Zhong Ji, Zhang Zhiwei, Xia Liwei and Luo Shiyu. 2024. Research on the teaching reform of film and television animation specialty. Education and Teaching Research ( 09 ), 92-128.
DOI: 10.13627/j.cnki.cdjy.2024.09.002.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2024 Yanmeng Fan