Generative AI and Foundational Understanding of Whole-Process Teaching in Interior Design

Abstract

To address the misalignment between generative AI’s restructuring of the interior design industry and its insufficient integration into pedagogical practices—and in response to the digital transformation demands of New Engineering and vocational education—this study examines four key issues in current teaching methods: the fragmented use of AI tools, disconnections in human–AI collaboration, an imbalance among technical, creative, and ethical competencies, and outdated evaluation mechanisms. Drawing on research in interdisciplinary collaboration and AI tool application, we propose strategies such as an integrated AI toolchain for the entire design process, interdisciplinary fusion, phased human–AI collaboration, three-dimensional capability development, and diversified quantitative assessment. These strategies are validated through case studies. The study also suggests future optimization pathways across four dimensions, including technological integration. By constructing an adaptive framework and providing actionable teaching solutions, this research aims to support the cultivation of interdisciplinary talents skilled in “AI + Interior Design.”