Enhancing digital art education with artificial intelligence: A case study of learning with AI in a computational art module

This case study explores the integration of artificial intelligence (AI) into a computational art module, enhancing the learning experience for digital media art students at Xi’an Jiaotong–Liverpool University. By leveraging AI tools, students developed cutting-edge skills in computational art, experimenting with different modes of AI and machine learning. The educator faced the challenge of designing rigorous teaching plans, learning experiences, and assessment strategies suitable for this AI-enhanced module. The results from assessment and a survey indicate that AI improved student outcomes, with most student groups incorporating AI into their research and development processes, and a majority of students reporting a reduction in repetitive tasks, enabling a more streamlined creative practice. The study demonstrates that AI can be effectively integrated into digital art in higher education, fostering an intuitive and enriching learning experience. This article was published open access under a CC BY-NC-ND licence: https://creativecommons.org/licenses/by-nc-nd/4.0/ .

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Publication Details

Journal
Developing Academic Practice
Published
2026-04-29
DOI
https://doi.org/10.3828/dap.2026.12
Primary Topic
Art, Technology, and Culture
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing digital art education with artificial intelligence: A case study of learning with AI in a computational art module

Tian Leng
Developing Academic Practice
Art, Technology, and Culture
article

Enhancing digital art education with artificial intelligence: A case study of learning with AI in a computational art module

Tian Leng
article en

Abstract

This case study explores the integration of artificial intelligence (AI) into a computational art module, enhancing the learning experience for digital media art students at Xi’an Jiaotong–Liverpool University. By leveraging AI tools, students developed cutting-edge skills in computational art, experimenting with different modes of AI and machine learning. The educator faced the challenge of designing rigorous teaching plans, learning experiences, and assessment strategies suitable for this AI-enhanced module. The results from assessment and a survey indicate that AI improved student outcomes, with most student groups incorporating AI into their research and development processes, and a majority of students reporting a reduction in repetitive tasks, enabling a more streamlined creative practice. The study demonstrates that AI can be effectively integrated into digital art in higher education, fostering an intuitive and enriching learning experience. This article was published open access under a CC BY-NC-ND licence: https://creativecommons.org/licenses/by-nc-nd/4.0/ .

Developing Academic PracticeVol. 2026(Special)
Xi’an Jiaotong-Liverpool University (CN)
Quality Education
Openalex Percentile: Top 4%
Art, Technology, and Culture
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