{"title":"Analysis of the application of generative artificial intelligence in interior design education","authors":"Yao Liu , Beiyuan Xu , Jiarong Feng , Pengjun Wu","doi":"10.1016/j.asej.2025.103757","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid advancement of artificial intelligence (AI) has introduced generative AI tools as transformative resources in interior design education, enhancing creativity, aesthetic quality, and practical design outcomes. Traditional interior design education often limits students’ theoretical knowledge, aesthetic skills, and technical abilities development. Generative AI tools such as Stable Diffusion and Midjourney, which utilize big data and deep learning, offer innovative design concepts to address these limitations. This study applies established models—UTAUT and AHP—in a novel educational context to evaluate generative AI tools in terms of creativity, aesthetics, practicality, and feasibility, offering empirically grounded insights for interior design pedagogy. Results showed that Stable Diffusion excelled in creativity, while Midjourney outperformed in aesthetics and functionality, with both tools proved more feasible than traditional methods. Despite challenges such as limited technical support and high hardware requirements, generative AI tools can significantly enhance interior design education by fostering innovation and improving design efficiency.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 12","pages":"Article 103757"},"PeriodicalIF":5.9000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447925004988","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The rapid advancement of artificial intelligence (AI) has introduced generative AI tools as transformative resources in interior design education, enhancing creativity, aesthetic quality, and practical design outcomes. Traditional interior design education often limits students’ theoretical knowledge, aesthetic skills, and technical abilities development. Generative AI tools such as Stable Diffusion and Midjourney, which utilize big data and deep learning, offer innovative design concepts to address these limitations. This study applies established models—UTAUT and AHP—in a novel educational context to evaluate generative AI tools in terms of creativity, aesthetics, practicality, and feasibility, offering empirically grounded insights for interior design pedagogy. Results showed that Stable Diffusion excelled in creativity, while Midjourney outperformed in aesthetics and functionality, with both tools proved more feasible than traditional methods. Despite challenges such as limited technical support and high hardware requirements, generative AI tools can significantly enhance interior design education by fostering innovation and improving design efficiency.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.