Critical Thinking and Students’ Intentions to Use Artificial Intelligence Chatbots for Learning: Evidence from Vietnamese Universities

Abstract

Artificial Intelligence (AI) chatbots are increasingly reshaping learning practices in higher education. This study extends the Technology Acceptance Model (TAM) by incorporating critical thinking as a key cognitive antecedent of behavioral intention to use AI chatbots for learning. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data collected from Vietnamese university students (n = 100) were analyzed to examine the proposed relationships. The findings indicate that critical thinking is predictively associated with students’ self-reported behavioral intention to use AI chatbots and shows a larger standardized association than traditional TAM factors, including perceived usefulness, perceived ease of use, and attitude. Attitude toward AI chatbot use also directly predicts behavioral intention and is positively associated with critical thinking, suggesting a potential mediation mechanism. The extended model demonstrates substantial explanatory power in explaining variance in students’ self-reported behavioral intention. Overall, the results highlight critical thinking as an important cognitive factor associated with more reflective and responsible use of AI chatbots in university education. Given the cross-sectional and exploratory design, the findings should be interpreted as predictive rather than causal.