Artificial Intelligence in Design Education
A Systematic Review and CIDA-Aligned Framework for Interior Architecture and Design
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Background: Generative Artificial Intelligence (AI) is rapidly becoming integral to design practice, yet its integration into interior architecture and design education faces challenges, creating a potential gap between academic preparation and industry needs. There is an urgent need for evidence-based strategies to integrate AI effectively while upholding core pedagogical values.
Objective: This study systematically reviews recent literature on AI integration in interior architecture and design education to identify current patterns, pedagogical models, challenges, and opportunities, with specific implications for CIDA-accredited interior architecture and design programs.
Methods: Following PRISMA 2020 guidelines, the author searched five databases (2021–2025) and screened records based on pre-defined eligibility criteria. Data from 80 included peer-reviewed studies were extracted and synthesized using thematic analysis, guided by postdigital pedagogy and human-centricity lenses.
Results: Eight key themes emerged: (1) AI use is heavily concentrated in early design phases; (2) integration paradoxically reinforces the need for human-centric skills and judgment; (3) literacy demands are evolving from prompt fluency toward broader AI literacy; (4) pedagogical models are diversifying but often lack formal structure; (5) AI's role is expanding beyond generation to analysis and critique; (6) AI increasingly operates within larger technological ecosystems; (7) a quantifiable education-practice gap persists, particularly in later design phases; (8) Affective factors (motivation, anxiety) significantly influence adoption.
Conclusion: AI in interior architecture and design education is advancing fastest in early ideation but remains comparatively underdeveloped in later, standards-intensive phases, indicating that the central curricular challenge is not whether to adopt AI, but how to position, bound, and assess it so that it strengthens auditable human judgment. In response, this paper proposes a CIDA-aligned curricular framework and phased implementation roadmap that link early creative leverage to later-stage rigor through phase-aware AI roles, transparency artifacts, ecosystem thinking, and human-centered evaluation.
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