Assessing teachers’ readiness for AI-driven XR integration: Scale development and multigroup validation in ethnic minority boarding high schools in Viet Nam

Abstract

This study proposes and validates the Teachers' Readiness for AI-Driven XR Integration (TRAXRI) model to examine the determinants of teachers' readiness to adopt artificial intelligence (AI) and extended reality (XR) technologies in ethnic minority boarding high schools in Viet Nam. Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and extended with pedagogical and ethical dimensions, the model includes six exogenous constructs—performance expectancy, effort expectancy, facilitating conditions, attitude toward AI–XR, self-efficacy, and ethical & privacy awareness—that predict teachers' readiness for AI-driven XR integration (RI). Data were collected from 1740 upper-secondary teachers working in ethnic minority boarding high schools across Viet Nam and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that attitude toward AI–XR, performance expectancy, and self-efficacy are the strongest predictors of readiness, while ethical & privacy awareness also demonstrates a significant emerging influence. Multi-group analysis further supports the model's stability across teacher subgroups (e.g., gender, teaching experience, and regional context). The findings advance the literature by extending UTAUT2 into AI–XR pedagogical readiness in resource-constrained, culturally specific schooling contexts, and by foregrounding the ethical dimension of AI–XR adoption. Policy implications highlight the need for pedagogically grounded, ethically informed, and context-sensitive capacity-building strategies to support AI–XR integration in ethnic minority boarding high schools, aligning with Sustainable Development Goal 4 (Quality Education) and Viet Nam's digital transformation agenda.

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