Designing an artificial intelligence photography course to foster aesthetic sustainability competence in Chinese university students

https://doi.org/10.55214/2576-8484.v9i10.10602

Authors

  • Yunfei Liu Chinese International College, Dhurakij Pundit University, Bangkok, 10210, Thailand, and Wuhu University, Wuhu, 241000, China.
  • Peng-Fei Chen Wuhu University, Wuhu, 241000, China.
  • Shasha Lei Hubei University of Science and Technology, Xianning, 437000, China.

This study designs and implements an Artificial Intelligence photography course aimed at enhancing Chinese university students’ aesthetic sustainability within smart classroom environments. Grounded in the principles of Education for Sustainable Development and Connectivism, the course was developed through expert validation and evaluated using a quasi-experimental pretest–posttest design with experimental and control groups. Quantitative data were analyzed using SPSS, while qualitative interview data were examined through NVivo-based thematic coding. Results indicate that the experimental group exhibited significantly greater improvements in overall aesthetic sustainability and its subdimensions, including aesthetic experience, sustainability awareness, and critical thinking, compared with the control group. Additionally, students demonstrated enhanced interdisciplinary collaboration, creative expression, and social responsibility. The AI photography course effectively integrates technology, aesthetics, and sustainability, fostering deeper cognitive engagement and more innovative learning. These findings provide actionable insights for higher-education curriculum reform, suggesting that AI-enhanced art courses can cultivate sustainable thinking and advance innovation-oriented aesthetic education.

How to Cite

Liu, Y., Chen, P.-F., & Lei, S. (2025). Designing an artificial intelligence photography course to foster aesthetic sustainability competence in Chinese university students. Edelweiss Applied Science and Technology, 9(10), 1093–1101. https://doi.org/10.55214/2576-8484.v9i10.10602

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Published

2025-10-17