.png){kind=icon}
.png){kind=icon}
Return
Artificial intelligence in architecture and electrical engineering: student practices, time redistribution and interdisciplinary potential
.png){kind=icon}
PRE
AI
A
DOI：10.1080/17452007.2026.2659854.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article examines the role of AI-based tools in the education of architecture and electrical engineering students based on a literature review and questionnaire surveys conducted in several rounds (N = 191). Despite the growing use of Artificial Intelligence (AI) in fields related to design and engineering, as well as in higher education, empirical cross-disciplinary studies examining how students use these tools in everyday academic practice and how they influence interdisciplinary collaboration remain limited. This study addresses this gap by providing a comparative analysis of two technical disciplines that are closely interconnected in professional practice but remain largely separated in academic education. The collected data were analysed using descriptive statistical analysis, comparative analysis, and thematic coding. The findings indicate that AI tools are used primarily for organisational and information-processing tasks, contributing to perceived efficiency gains and time redistribution within the learning process. At the same time, limited preparation for interdisciplinary collaboration is observed in both groups. The results also reveal a growing gap between the potential of AI to support work organisation and the rigid structure of existing study programmes. The study contributes to understanding how AI shapes academic work organisation and highlights implications for integrating AI into interdisciplinary educational frameworks.
Keywords:
Artificial intelligence
interdisciplinary collaboration
architectural education
electrical engineering education
communication skills
interdisciplinary education
work organisation
architectural design
Journal
IF:
2.5
Papers:
183
Citations:
1.3K
Organization
Cited Papers