Potential Risks and Countermeasures of Artificial Intelligence in Teaching: A Case Study of High School Art Education

Authors

  • Hongying Liu Sichuan Normal University, Chengdu, China

DOI:

https://doi.org/10.54097/351hnw76

Keywords:

artificial intelligence, high school art education, creative thinking, teacher autonomy, educational equity, aesthetic education.

Abstract

Artificial intelligence offers new resources for image generation, feedback, and lesson preparation in high school art education, while also raising questions about the purposes and processes of artistic learning. Focusing on this teaching context, this paper discusses potential risks and corresponding educational responses. Four concerns structure the analysis: weakening students’ innovative thinking and practical skills, reducing teacher autonomy, widening inequalities in access to learning resources, and privileging standardized visual perfection over diverse aesthetic values. The paper proposes clear boundaries for AI use, continued emphasis on hands-on artistic practice, development of teachers’ digital literacy and professional judgement, more equitable provision of resources, and teaching that encourages aesthetic diversity. It argues that AI should support students’ creative agency and teachers’ educational judgement within a practice-based approach to art learning. The proposed responses require adaptation to local teaching conditions and further evaluation in classroom practice.

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References

[1] Mao, G., Long, Z. P., & Li, F. M. (2024). A survey research on the characteristics of learners' digital creation practice and learning experience in the AIGC environment. E-education Research, 45(10), 79--85.

[2] Habib, S., Vogel, T., Anli, X., & Thorne, E. (2023). How does generative artificial intelligence impact student creativity? Journal of Creativity, 34(1), 100072. DOI: https://doi.org/10.1016/j.yjoc.2023.100072

[3] Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial intelligence alone will not democratise education: On educational inequality, techno-solutionism and inclusive tools. Sustainability, 16(2), 781. DOI: https://doi.org/10.3390/su16020781

[4] Huang, H. (2024). A brief analysis of AI painting empowering the improvement of art subject literacy. China New Communications, 26(12), 242--244.

[5] Huang, Y. (2025). A brief exploration of teaching methods integrating AI technology into high school art classes. New Curriculum Research, (34), 129--131.

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Published

05-10-2026

How to Cite

Liu, H. (2026). Potential Risks and Countermeasures of Artificial Intelligence in Teaching: A Case Study of High School Art Education. Journal of Education, Humanities and Social Sciences, 64, 120-126. https://doi.org/10.54097/351hnw76