The Value and Pathways of AI-Empowered Senior High School  Fine Fine Art Education

Pengxiang Wang

doi:10.62177/jetp.v3i3.1554

Authors

Pengxiang Wang Northwest Normal University

DOI:

https://doi.org/10.62177/jetp.v3i3.1554

Keywords:

AI, Senior High School Fine Art Education, Value and Paths

Abstract

With the rapid development of artificial intelligence (AI) technology, revolutionary transformation have taken place in the educational paradigm of senior high school fine fine art education. The intelligent generation of images, videos and animations based on text prompts builds ubiquitous teaching environment, facilitates the intelligent formation of students’ core literacy, and underpins diversified evaluation mechanisms.From three dimensions—revolutionizing learning experiences through human-machine collaboration, empowering teachers’ instruction with massive resources, and realizing individualized instruction by stimulating students’ potential,this paper clarifies the value of AI-Empowered senior high school fine arts education.It further proposes three implementation paths for AI-powered senior high school arts education: enhancing teachers’ technical application capabilities, cultivating students’ autonomous learning competencies,and rationally examining intelligent technology-based evaluation systems.

Downloads

Download data is not yet available.

References

Ministry of Education of the People’s Republic of China. (2020). General senior high school curriculum standards: Fine arts (2017 edition, revised 2020). People’s Education Press. (p. 2).

Ministry of Education of the People’s Republic of China. (2025, May 15). Two guidelines released to boost artificial intelligence education in primary and secondary schools. Retrieved November 10, 2025, from https://www.gov.cn/lianbo/bumen/202505/content_7023810.htm

Ministry of Education of the People’s Republic of China. (2020). General senior high school curriculum standards: Fine arts (2017 edition, revised 2020). People’s Education Press. (p. 2).

Yang, Z., Wang, J., Wu, D., et al. (2023). Impacts of ChatGPT/generative artificial intelligence on education and corresponding countermeasures. Journal of East China Normal University (Educational Sciences), 41(7), 26–35.

Wang, Y., Zhu, T., Yang, S., et al. (2024). Human-machine collaborative teaching: Motivations, essence and challenges. E-Education Research, 45(8), 51–57.

Yang, Z., Wang, J., Wu, D., et al. (2023). Impacts of ChatGPT/generative artificial intelligence on education and corresponding countermeasures. Journal of East China Normal University (Educational Sciences), 41(7), 26–35.

Wu, N., Chen, X., & Feng, Y. (2023). From “disorder” to “order”: The transformation and generation mechanism of generative AI in educational application. Journal of Distance Education, 41(6), 42–51.

The Central Committee of the Communist Party of China & The State Council. (2025, January 19). Outline for the Construction of a Powerful Education Country (2024–2035). Retrieved November 22, 2025, from https://www.gov.cn/zhengce/202501/content_6999913.htm

Sawyer, R. K. (Ed.). (2010). The Cambridge handbook of the learning sciences. Educational Science Publishing House. (p. 626).

Li, Z. (2024). The path of beauty. Yuelu Publishing House. (p. 153).

Zhang, T. (2025, April 13). Leveraging AI as a fulcrum to unlock infinite possibilities for aesthetic education. China Cultural Daily.

Ministry of Education of the People’s Republic of China. (2025, April 15). Opinions on accelerating the digitalization of education. Retrieved November 22, 2025, from http://www.moe.gov.cn/srcsite/A01/s7048/202504/t20250416_1187476.html

Jiang, H., & Zeng, W. (2025). Generative artificial intelligence driving the transformation of educational evaluation. Journal of the Chinese Society of Education, (8), 41–48.

Zhang, H. (2000). Curriculum and teaching theory. Shanghai Educational Publishing House. (p. 372).

Wu, T., Lee, H. Y., Chen, P., et al. (2025). Integrating peer assessment cycle into ChatGPT for STEM education: A randomised controlled trial on knowledge, skills, and attitudes enhancement. Journal of Computer Assisted Learning, 41(1), 1–19.

Sawyer, R. K. (Ed.). (2010). The Cambridge handbook of the learning sciences. Educational Science Publishing House. (p. 416).

Chappuis, J., et al. (2021). Classroom assessment for learning: Doing it right, using it well (Trans.). East China Normal University Press. (p. 78).

Luo, S., Li, N., Song, H., et al. (2025). DeepSeek empowering high-quality development of basic education (Roundtable Discussion). Journal of Tianjin Normal University (Basic Education Edition), 26(3), 1–14.

Pei, R. (2025). Generative AI empowering teaching and education: Transformative impacts, risks, challenges and practical paths. Forum on Contemporary Education, (2), 72–79.

Su, Q., & Tao, Y. (2025). Myth, risk and imaginative reconstruction of the concept of “educational evaluation” in the era of digital intelligence technology empowerment. Journal of East China Normal University (Educational Sciences), 43(6), 38–49.

Huai, J. (2024). Jointly promoting the application, sharing and innovation of digital education — Keynote speech at the 2024 World Digital Education Conference. China Educational Informationization, 30(2), 3–10.