The Impact of AIGC on the Design Process of Cultural and Creative Education Products and Its Management Implications

素贞 白()

Abstract

Abstract：Cultural and creative education products play a crucial role in modern education, as they can enhance students' creativity and cultural understanding. In the field of cultural and creative product development, Artificial Intelligence Generated Content (AIGC) has not yet been maturely applied, while data-driven design methods can achieve personalized and efficient design outputs, thus facilitating the creative generation and rapid iteration of AIGC. This study aims to explore the application of AIGC in the development of cultural and creative education products, and to form a future-oriented design process transformation in combination with rapid output of data analysis. By building a database of cultural elements and user preferences related to educational aspects in cultural and creative education products, training the AIGC system using machine learning technology, and submitting the design drafts formed in the near term to designers for further optimization, the product is finally subjected to user feedback and market testing, with products that are highly accepted by users as the final output. The research results show that the use of AIGC can not only promote innovation in cultural and creative education products, improve design efficiency and product diversity, but also inspire more creative inspiration for designers. The advantage of data analysis further enhances the accuracy of product development and market response speed, achieving effective transformation of the design process. Moreover, this research provides valuable references for educational management in terms of resource allocation and curriculum design.

Keywords

Keywords: Educational Management; Cultural and Creative Education ProductsAIGC; Cultural and Creative Education Products; Design Process; Educational Management; Data Analysis

References

References

Tao Feng, Liang Zhengping. Design and Rationality: Aesthetic Reflections on Artificial Intelligence Design [J]. China Art Criticism, 2023(10):32-46+126.

Song Xiewei, Zhang Xinrong, Liu Yuqi. Summary of the Second "Future·Future" International Education Forum [J]. Art Research, 2023(05):17-21.

China Academy of Information and Communications Technology, JD Exploration Research Institute. White Paper on Artificial Intelligence Generated Content (AIGC) [R/OL]. 2022.09

Chen Ruirui, Gu Hongmei. Research on the Development and Utilization of Traditional Fine Arts Intangible Cultural Heritage in Hebei Province under the Background of Artificial Intelligence [J]. Daguang (Forum), 2024,(01):110-112.

Liang Qingguo. Research on Cross-border Cooperation and Innovation Model of AI Artificial Intelligence Technology Application in Design Professional Practice Teaching [J]. Modern Vocational Education, 2024,(04):153-156.

DOI: http://dx.doi.org/10.12345/jetm.v8i4.21156