Adoption of artificial intelligence tools for academic writing - Nguyen Thu Hoai; Lai Thi Thu Thuy (International Journal of Evaluation and Research in Education (IJERE), 2026)
The rapid advancement of artificial intelligence (AI) presents both significant opportunities and challenges for academic writing. This study investigates the factors influencing the adoption of AI writing tools among lecturers in Vietnam by proposing an integrated theoretical framework that combines the unified theory of acceptance and use of technology (UTAUT) with perceived risk theory (PRT). The model incorporates performance risk (PR) and ethical risk (ER) as key inhibitors alongside the core UTAUT constructs. Data were collected through a cross-sectional survey of 404 lecturers from public universities across North, Central, and South Vietnam, including both public and private educational institutions, and analyzed using structural equation modeling (SEM). The results show that the proposed model has strong explanatory power, accounting for 77.9% of the variance in behavioral intention (BI) and 75.3% in use behavior (UB). All seven hypotheses were supported. Performance expectancy (PE) was the most potent predictor of intention, while PR was the strongest deterrent. Facilitating conditions (FC) and BI were found to be critical antecedents of actual use. The study contributes by empirically validating an integrated UTAUT–PRT framework in the context of AI writing tool adoption. The findings suggest that universities should prioritize performance-enhancing support mechanisms and risk-mitigation policies to promote responsible AI adoption.