Arki-Nexus AI: A Framework for Integrating Artificial Intelligence Competencies Into NEUST College of Architecture

Abstract

The rapid expansion of Artificial Intelligence (AI) is reshaping architectural education and practice, yet its systematic curricular integration remains limited in many higher education settings. This study developed the proposed Arki-Nexus AI Framework to guide the structured integration of AI competencies into the curriculum of the NEUST College of Architecture. Employing a descriptive-comparative quantitative research design, the study involved 31 faculty members selected through purposive sampling and 200 architecture students selected through stratified random sampling with equal allocation by year level. Data were gathered using a researcher-developed survey instrument that underwent expert content validation by seven experts (I-CVI = 1.00) and pilot reliability testing (Cronbach’s α = .85–.92). Faculty members reported a high overall level of AI competency (M = 4.11), while students also reported a high overall level (M = 3.63), although student ratings were moderate in AI-assisted design, AI-supported collaboration, and AI-driven innovation. The perceived extent of AI integration was moderately evident for both faculty (M = 3.18) and students (M = 2.96). Significant faculty-student differences were found in applied AI competencies, but not in AI literacy or ethical AI use. These findings informed a proposed framework linking human competencies, pedagogical drivers, and institutional enablers. Because the findings were based on self-reported data from one college, the framework requires future expert review, pilot implementation, and feasibility and impact evaluation.