Enhancing Interior Design Education Through the Integration of AIGC Tools: A Novel “Creator-Thon” Approach
This innovative practice full paper proposes Creator-Thon, a novel teaching project designed to introduce Generative AI into traditional interior design workflows. The project adopts an interdisciplinary approach including application scenario investigation, workflow construction, collaborative innovation, and iterative optimization. The underlying research is grounded in a six-level goal hierarchy, comprising sub-goals of integrating AI capabilities and design knowledge, embedding AI skills into workflows, enhancing the learning engagement, empowering personal career development, fostering (human-AI and human-human) collaboration, and transforming the design paradigms. The teaching framework is progressively refined across multiple iterations, enhancing learning engagement by simplifying tool operations, refining design language, and re-engineering the design process. The findings underscore that integration of authentic application scenarios markedly boosts engagement and motivation among learners, modular instruction also enhances teaching quality and practical skills, and the adaptive optimization of the teaching framework informed by participants' feedback, is key to a successful Generative AI involved interior design pedagogy. This work provides insights that contribute to the application of Generative AI technology in interior design education and practice, facilitating transformations and progress in AI literacy in the field.
Authors
- Danyang Chen
- Lei Xia (ORCID: https://orcid.org/0000-0003-0394-945X)
- Fan Ling
- Pengfei Wu (ORCID: https://orcid.org/0000-0001-7621-5970)
- Ziming He (ORCID: https://orcid.org/0000-0001-6939-2047)
- Xiaomei Li (ORCID: https://orcid.org/0000-0002-3945-0709)
Institutions
- Tongji University (CN)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/fie61694.2024.10893341
- Citations
- 1
- Primary Topic
- Architecture, Design, and Social History
- Type
- article
- Field-Weighted Citation Impact
- 1.96