Factors influencing lecturers' adoption of generative artificial intelligence in Vietnamese higher education: An extended theoretical perspective
TL;DR
This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating attitude and perceived barriers, and found a noticeable gap: educators showed high adoption readiness, yet actual usage lagged by 1.19 points on a 5-point scale.
Abstract
While universities worldwide are rapidly adopting generative artificial intelligence, empirical evidence from developing nations remains limited. This study explores factors driving Vietnamese university lecturers to integrate these tools. We extended the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating attitude and perceived barriers. Analyzing survey data from 261 academic staff via multiple linear regression, we found a noticeable gap: educators showed high adoption readiness, yet actual usage lagged by 1.19 points on a 5-point scale. Our expanded model explained 43.3% of the variance in adoption intention. Personal attitude was the strongest predictor, followed by performance expectancy and facilitating conditions. Surprisingly, effort expectancy lacked statistical significance. Counterintuitively, perceived barriers positively correlated with adoption intention. Recognizing functional and ethical flaws motivated a critically informed, responsible integration rather than passive rejection among experienced educators. To bridge the intention-practice gap, institutions must provide concrete support, clear governance, and professional development.