An AIGC-Driven Teaching Model for Packaging Design Courses: Design and Experimental Study

DOI

10.2991/978-94-6239-737-8_27How to use a DOI?

Keywords

AIGC; Packaging Design; Teaching Model; Design Education; Experimental Study

Abstract

With the rapid development of Artificial Intelligence Generated Content (AIGC), its application in design education has attracted increasing attention. This study proposes an AIGC-driven teaching model for packaging design courses based on a four-stage framework, including research, generation, optimization, and implementation. A controlled experiment involving 60 students was conducted to evaluate the effectiveness of the proposed model. The results show that the AIGC-based approach significantly improves creativity, visual quality, design efficiency, and learning satisfaction compared with traditional teaching methods. The findings demonstrate the potential of AIGC to enhance design education and provide a practical reference for the digital transformation of art and design curricula.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shengnan Wu
AU  - Jiahui Wang
AU  - Na Wang
AU  - Weiqian Mao
PY  - 2026
DA  - 2026/08/18
TI  - An AIGC-Driven Teaching Model for Packaging Design Courses: Design and Experimental Study
BT  - Proceedings of the 2026 5th International Conference on Art Design and Digital Technology (ADDT 2026)
PB  - Atlantis Press
SP  - 203
EP  - 209
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-737-8_27
DO  - 10.2991/978-94-6239-737-8_27
ID  - Wu2026
ER  -