Proceedings of the 5th International Conference on New Computational Social Science (ICNCSS 2025)

A Project-Based Learning Approach Augmented with Generative AI in Interior Design Courses

Authors
Chenglin Gao1, *, Qi An2, *, Yixuan Jiang3, Yuzhe Wang4, Wenqi Wei3
1Beijing University of Agriculture, Beijing, 102206, China
2Beijing City University, Beijing, 100191, China
3Beijing University of Agriculture, Beijing, 102206, China
4Beijing City University, Beijing, 100191, China
*Corresponding author. Email: chenglingao@126.com
*Corresponding author. Email: anqi@bcu.edu.cn
Corresponding Authors
Chenglin Gao, Qi An
Available Online 25 August 2025.
DOI
10.2991/978-2-38476-456-3_33How to use a DOI?
Keywords
Generative Artificial intelligence; Project-based Learning in interior design; Human-computer Collaboration
Abstract

This study explores the integration of generative artificial intelligence (AI) and project-based learning (PBL) in interior design education, aiming to foster interdisciplinary innovation and practical skill development by combining AI technologies such as large language models (LLMs), image generation tools, and multimodal human-computer collaboration to transform traditional teaching methodologies into a dynamic, data-driven process. The research emphasizes the coupling of “new agriculture + new design” disciplines, leveraging AI to bridge knowledge gaps and enhance creative problem-solving through a four-phase methodology: (1) Planning, where AI assists in generating task modules and visualizations to shift design thinking from “form-first” to “system-optimization”; (2) Identification, using AI to analyze user needs and spatial characteristics; (3) Presentation, enabling rapid prototyping through AI tools for 2D/3D modeling and video animations; and (4) Finalization, employing multimodal feedback for formative and summative evaluations. Empirical results demonstrate that AI-aided PBL enhances students’ cross-disciplinary thinking, design efficiency, and innovation capabilities while supporting personalized learning through real-time data analysis, highlighting the potential of generative AI in constructing a green, low-carbon curriculum system, fostering “production-learning-research” collaboration, and cultivating interdisciplinary talents, with future directions focusing on optimizing AI-human synergy and expanding application scenarios to contribute to the digital transformation of design education in alignment with global trends in AI-driven educational innovation.

Copyright
© 2025 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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Volume Title
Proceedings of the 5th International Conference on New Computational Social Science (ICNCSS 2025)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
25 August 2025
ISBN
978-2-38476-456-3
ISSN
2352-5398
DOI
10.2991/978-2-38476-456-3_33How to use a DOI?
Copyright
© 2025 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.

Cite this article

TY  - CONF
AU  - Chenglin Gao
AU  - Qi An
AU  - Yixuan Jiang
AU  - Yuzhe Wang
AU  - Wenqi Wei
PY  - 2025
DA  - 2025/08/25
TI  - A Project-Based Learning Approach Augmented with Generative AI in Interior Design Courses
BT  - Proceedings of the 5th International Conference on New Computational Social Science (ICNCSS 2025)
PB  - Atlantis Press
SP  - 278
EP  - 291
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-456-3_33
DO  - 10.2991/978-2-38476-456-3_33
ID  - Gao2025
ER  -