AI Meets Academia: Exploring ChatGPT Use in Higher Education Through the Extended UTAUT Lens

Abstract

ChatGPT is one of the most popular and rapidly adopted educational technologies. The widespread revolution of ChatGPT and its applications in various spheres of life call for unveiling the factors that stimulate users’ behavioral intentions. Thus, this research aims to assess the determinants shaping users’ intentions and the actual use of ChatGPT for learning purposes in developing countries. The “Unified Theory of Acceptance and Use of Technology” model with three extended parameters has been adopted for the current study. The extended variables are learning value, information accuracy, and technology anxiety. Data were collected from 619 university students and examined through partial least squares structural equation modeling and artificial neural network techniques. This paper demonstrates that users’ ChatGPT use intention is positively influenced by learning value, information accuracy, social influence, facilitating conditions, and performance expectancy. In contrast, technology anxiety has a significant negative association with use intentions, emphasizing that discomfort with technology deters users from using it, which is a prominent observation for artificial intelligence chatbot developers and educators. Use intentions and learning value significantly determine users’ actual use behavior. This study further underscores the crucial role of information accuracy, learning value, and technology anxiety in ChatGPT adoption in higher educational settings. The practical implications of this study provide insightful findings for academic stakeholders, developers, administrators, and policymakers of developing countries, particularly concerning the constructive and ethical implementation of ChatGPT in higher education.

Received: 12 June 2025 | Revised: 10 November 2025 | Accepted: 2 April 2026

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.

Author Contribution Statement

Afruza Haque: Conceptualization, Methodology, Formal analysis, Resources, Data curation, Writing – original draft, Writing – review & editing, Supervision, Visualization. Rasheda Akter Rupa: Conceptualization, Methodology, Software, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration. Rana Al Mosharrafa: Resources, Validation, Investigation, Data curation, Writing – original draft, Visualization. Shaharin Akter: Software, Validation, Resources, Data curation, Writing – original draft. Abu Naser Mohammad Saif: Methodology, Investigation, Resources, Writing – original draft, Writing – review & editing, Supervision, Project administration. Rehnuma Mostafa: Validation, Resources, Writing – review & editing.