AI-MEDIATED INTERPRETATION OF CULTURAL SYMBOLS IN VISUAL DESIGN EDUCATION: A CASE STUDY ON CHINESE TIGER IMAGERY
DOI:
https://doi.org/10.35631/IJEPC.1163047Keywords:
Artificial Intelligence (AI) In Education, Chinese Tiger Imagery, Cultural Symbol Interpretation, Interpretive Learning, Project-Based Learning (PBL), Visual Design EducationAbstract
The integration of Artificial Intelligence (AI) into visual design education is reshaping how students engage with creative practice, cultural meaning, and visual problem-solving. This study investigates how AI functions as a mediating tool in the interpretation and transformation of cultural symbols in visual design education, using Chinese tiger imagery as a case study. Rather than treating AI merely as a generative technology, the study positions it as an interpretive support that can assist students in cultural analysis, symbolic understanding, and reflective decision-making in design. A qualitative case study approach was adopted in an undergraduate visual design course at an application-oriented university in China. Specifically, the dataset consisted of 24 design artefacts, 24 reflective materials, 16 student interviews, 8 teacher interviews, and 3 expert interviews. Data were analyzed using thematic analysis to examine how AI influenced students’ interpretations of symbolic meaning, visual reconstructions, and learning experiences within a Project-Based Learning (PBL) context. The findings revealed that AI-supported learning enhanced students’ ability to articulate the cultural meanings embedded in Chinese tiger imagery, to expand their visual exploration, and to reflect more critically on the relationship between symbolism and design form. Additionally, the study identified that AI-generated outputs could easily lead to visual homogenization and superficial cultural interpretation when students relied on generic prompts or insufficient contextual research. Teacher and expert guidance, therefore, played a crucial role in helping students refine prompts, evaluate cultural appropriateness, and maintain interpretive depth. The study concludes that AI has significant pedagogical value in culturally grounded visual design education when it is used as an interpretive mediator rather than a substitute for human creativity. Its educational effectiveness depends on structured instructional design, reflective practice, and sustained pedagogical guidance.
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References
Barthes, R. (1977). Image, music, text. Fontana Press.
Bender, S. M. (2023). Coexistence and creativity: Screen media education in the age of artificial intelligence content generators. Media Practice and Education, 24(4), 351–366. https://doi.org/10.1080/25741136.2023.2204203
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Sage.
Duncum, P. (2010). Seven principles for visual culture education. Art Education, 63(1), 6–10. https://doi.org/10.1080/00043125.2010.11519050
Efland, A. D. (2002). Art and cognition: Integrating the visual arts in the curriculum. Teachers College Press.
Elkins, J. (2008). Visual literacy. Routledge.
Hall, S. (Ed.). (1997). Representation: Cultural representations and signifying practices. Sage.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Manovich, L. (2019). AI aesthetics. Strelka Press.
McCosker, A., & Wilken, R. (2020). Rethinking creative practice in the age of artificial intelligence. Media International Australia, 175(1), 5–9. https://doi.org/10.1177/1329878X20905437
Mirzoeff, N. (2015). How to see the world. Pelican Books.
Saldaña, J. (2016). The coding manual for qualitative researchers (3rd ed.). Sage.
Saritepeci, M., & Yildiz Durak, H. (2024). Effectiveness of artificial intelligence integration in design-based learning on design thinking mindset, creative and reflective thinking skills: An experimental study. Education and Information Technologies, 29, 25175–25209. https://doi.org/10.1007/s10639-024-12829-2
Siu, K. W. M., Zou, J., Jiang, Y., Yang, Z., Zhang, K., & Zhao, T. (2025). Dynamic scaffolding: Exploring the role of artificial intelligence in urban design education. Frontiers of Urban and Rural Planning, 3, Article 8. https://doi.org/10.1007/s44243-025-00060-7
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
