Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes
Tawfik, E., Ali, S., Yahia, Y. (2024). Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes. EKB Journal Management System, 7(3), 154-173. doi: 10.21608/dusj.2024.433457
Enas Tawfik; Sara Ali; Yassin Yahia. "Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes". EKB Journal Management System, 7, 3, 2024, 154-173. doi: 10.21608/dusj.2024.433457
Tawfik, E., Ali, S., Yahia, Y. (2024). 'Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes', EKB Journal Management System, 7(3), pp. 154-173. doi: 10.21608/dusj.2024.433457
Tawfik, E., Ali, S., Yahia, Y. Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes. EKB Journal Management System, 2024; 7(3): 154-173. doi: 10.21608/dusj.2024.433457

Towards Evaluating The AI-Embedded Educational Model for Architecture Students and Its Impact on Their Design Outcomes

Delta University Scientific Journal
Volume 7, Issue 3, November 2024, Pages 154-173    PDF (1.42 M)
Document Type: Original research papers
DOI: 10.21608/dusj.2024.433457
Authors
Enas Tawfik* 1; Sara Ali2; Yassin Yahia3
1Assistant professor, Architectural Engineering Department, Delta University for Science and Technology, Gamesa City, Dakahlia Governorate, Egypt
2Demonstrator, Architectural Engineering Department, Delta University for Science and Technology, Gamesa City, Dakahlia Governorate, Egypt
3Student, Architectural Engineering Department, Delta University for Science and Technology, Gamesa City, Dakahlia Governorate, Egypt
Abstract
This research explores the impact of AI-assisted teaching on architecture students, addressing the literature gap on the effectiveness of AI in education, particularly in architectural studies. The study developed an AI-integrated teaching methodology and evaluated its influence over an eight-week course involving 24 students from same level in architecture department.
The study employed structured interviews and questionnaires at different stages of the course to assess the effectiveness of the AI teaching model. Findings showed that AI-enhanced teaching positively influenced students' learning, improving their innovative capabilities and work efficiency. However, challenges included uncoordinated use of AI tools by students and the unpredictability of AI-generated design solutions. Despite these challenges, the research supports integrating AI into architectural education to foster creativity, efficiency, and personalized learning. A balanced approach is suggested to prevent over-dependency on AI and to encourage critical thinking skills.
Keywords
"AI in Education; " "Architectural Design; " "AI-Embedded Learning Models; " "Design Outcomes; " "Architecture Students; " and "Educational Technology."
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