Skip to content
Open access

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

2026 · International Journal of Information and Education Technology · 0 citations · 58 references

TL;DR

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.

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.

Read PDF

Similar papers

Review Open access Jul 2026

AI usage patterns and self-rated critical thinking among Chinese college students: the moderating role of academic motivation

This study explores the associations between artificial intelligence (AI) usage patterns and perceived critical thinking among university students in China, with a focus on three types of AI use: Information Retrieval Use (IRU), Content Generation Use (CGU), and Text Revision Use (TRU). Grounded in Self-Determination...

Jing Zhang, Yang Yang · 0 citations
Jul 2026

What Drives Learners to Keep Using Chatbots? An Extended TCT Modeling in Higher Education

This study investigated the cognitive, affective, and value-based determinants of higher education learners’ intention to continue using AI chatbot assistance with the extended Technology Continuance Theory (TCT), demonstrating that perceived usefulness and perceived ease of use play central roles in shaping learners’...

K. Kavitha, V. P. Joshith · 0 citations
Review Jul 2026

Explaining ChatGPT use among accounting students in higher education: an integrated task–technology fit and DeLone–McLean perspective

The findings suggest that when AI technologies are perceived as reliable, accurate and supportive of academic tasks, students are more likely to integrate them effectively into their learning activities, and frequent and functional use of AI technologies significantly enhances students’ academic performance.

Ananda Desyta Alistyaningrum, Frank Aligarh, Didik Prasetyanto et al. · 0 citations
Review Open access Aug 2026

The Effects of ChatGPT Use and Self Regulated Learning on Students' Critical Thinking Skills: Evidence from the Faculty of Teacher Training and Education, Ekasakti University

Examination of the effects of AI ChatGPT usage and self-directed learning on the critical thinking skills of students at the Faculty of Teacher Training and Education, Universitas Ekasakti revealed that AI ChatGPT usage had a positive and significant effect on critical thinking skills.

Ayu Oktaviani, Caterina Lo, Serli Diovani Teza · 0 citations
Open access Aug 2026

How Cognitive Factors and Motivation Shape Learners' Engagement in AI ‐Supported Language Learning?: Insights From the Combined SEM and fsQCA Approaches

These findings provide theoretical support for SCT in technology‐mediated learning and suggest practical strategies for educators, including tailoring instructional design to learners' cognitive profiles, fostering motivation and self‐efficacy and leveraging AI tools to enhance active and sustained engagement in langua...

Yifan Wang, Ran Zhi · 0 citations
Open access Jul 2026

MODELLING COLLEGE STUDENTS INTENTION TO USE GENERATIVE AI-BASED ENGLISH LANGUAGE LEARNING APPLICATIONS: AN INTEGRATED TAM-TPB APPROACH

The progression of Generative Artificial Intelligence (GAI) has revolutionized English language learning. It has ensured personalized, interactive, and accessible learning experiences. This study examines the factors influencing college students' intention to use generative AI based English language learning applicatio...

Pradeesh N.M, Navya A.H, Samanway Krishnan · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.