Creative Subjectivity Reconstruction in Experimental Animation Education under Generative AI: Evidence from Private Universities in Liaoning, China
With the widespread use of generative artificial intelligence in the field of visual creation, the creative logic and teaching mode of experimental animation have changed profoundly. The old people-oriented creative model is gradually being replaced by a new human-artificial intelligence collaboration model, and as a result, a series of problems have arisen in the construction of creative subjectivity, the definition of originality and the reform of teaching evaluation standards, etc. Experimental animation teaching is the subject of this paper; under the background of the development of generative artificial intelligence, a corresponding teaching mechanism will be constructed from the perspective of creative subjective reconstruction. Based on the above analysis of theory, teaching practice and case studies, it is hoped that modifications in the subjection of individuals during the creation process of AI-driven experimental animation can be revealed; according to this, suitable teaching countermeasures will be proposed.
References
- Cyberspace Administration of China. (2023). Interim measures for the management of generative artificial intelligence services [Standard]. Beijing.
- UNESCO. (2023). Guidance for generative AI in education and research [Report]. UNESCO.
- Dwivedi, Y. K., Kshetri, N., Hughes, L., et al. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.
- Kasneci, E., Sessler, K., Küchemann, S., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
- Bubeck, S., Chandrasekaran, V., Eldan, R., et al. (2023). Sparks of artificial general intelligence: Early experiments with GPT-4 [Web page].
- Wells, P. (2013). Experimental animation: Origins of a new art. Routledge.
- Furniss, M. (2007). Art in motion: Animation aesthetics. John Libbey Publishing.
- Holmes, W., Miao, F., Akgun, S., et al. (2024). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education.
- OECD. (2023). Artificial intelligence and the future of skills [Report]. OECD Publishing.
- World Economic Forum. (2024). Shaping the future of learning: The role of artificial intelligence in education [Report]. WEF.