Factors Influencing University Students’ Decision to Use ChatGPT for Learning: Evidence from Hanoi, Vietnam
TL;DR
The findings indicate that students’ adoption of ChatGPT is driven less by the general diffusion of AI technology and more by perceived personal usefulness, institutional guidance, and tool-level value.
Abstract
This study investigates the factors influencing university students’ decision to use ChatGPT for learning in Hanoi, Vietnam. Drawing on the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, and recent research on generative AI in higher education, the study examines five antecedent groups: student-related factors, ChatGPT characteristics, social influence, technological context, and institutional support. A cross-sectional survey of 289 university students was analysed using SPSS 22, including descriptive statistics, reliability testing, exploratory factor analysis, Pearson correlation, and multiple linear regression. The measurement scales demonstrate satisfactory reliability, with Cronbach’s alpha values ranging from 0.834 to 0.861. Exploratory factor analysis supports a five-factor structure explaining 68.998% of the total variance. The regression model is statistically significant and explains 68.5% of the variance in students’ decisions to use ChatGPT. Student-related factors are the strongest predictor, followed by institutional support, ChatGPT characteristics, and social influence. Although the technological context is positively correlated with the dependent variable, it does not retain a significant unique effect in the regression model. The findings indicate that students’ adoption of ChatGPT is driven less by the general diffusion of AI technology and more by perceived personal usefulness, institutional guidance, and tool-level value. The study offers practical implications for universities, lecturers, AI developers, and policymakers seeking to promote responsible and effective use of generative AI in higher education.