The impact of personality traits and AI literacy on the adoption intentions of AI among design faculty in Chinese higher education.

Abstract

This study utilizes a dual-perspective framework that integrates stable individual differences (Big Five personality traits) and developable technological competencies (AI literacy). Drawing on the Theory of Planned Behavior (TPB) and Innovation Resistance Theory (IRT), it constructs both a "cognitive empowerment pathway" and a "psychological resistance pathway" to systematically reveal the behavioral intention mechanisms underlying the adoption of AI in teaching by design faculty in Chinese higher education institutions. Based on 513 valid survey responses, the research applies a mixed-methods approach. Structural Equation Modeling (SEM) results demonstrate that: 1) Openness (OPE), Extraversion (EXT), and AI literacy significantly and positively influence perceived behavioral control (PBC), while EXT and Agreeableness (AGR) significantly reduce psychological barriers (PB), collectively enhancing usage intention (UI); 2) Neuroticism (NEU) has a negative impact on PBC and a positive effect on PB, which consequently inhibits UI; 3) OPE, AGR, and AI literacy are significant positive predictors of UI, whereas NEU has a significant negative relationship with UI. The Fuzzy-set Qualitative Comparative Analysis (fsQCA) further identifies complex configurational effects between Big Five personality traits (BFP) and AI literacy, revealing eight discrete causal pathways leading to high AI usage intention among design educators, which stands in contrast to some SEM results. This study provides a systematic examination of how individual differences affect AI adoption behaviors among design faculty in Chinese higher education from an interdisciplinary perspective, thereby expanding the theoretical framework in this domain and offering empirical evidence and practical recommendations for capacity-building in AI-enabled teaching among design educators in China.