To Satisfy or Clarify: Enhancing User Information Satisfaction with AI-Powered ChatGPT †

Abstract

The effective use of AI-powered ChatGPT in higher education highlights its potential as a knowledge acquisition tool, yet it brings to the fore the less-explored area of user information satisfaction (UIS), a gap addressing the development of the UIS model tailored to ChatGPT. In this foundational research grounded in UIS theory, a model was proposed based on critical factors to guide educational stakeholders in investigating issues such as plagiarism and ethical use. By analyzing responses from a diverse group of Indonesian users employed in higher education and using Structural Equation Modeling with Smart-PLS 4.0, we identified five key determinants: completeness, precision, timeliness, convenience, and format. The determinants affect user satisfaction, while traditionally emphasized factors such as accuracy and reliability do not significantly impact the academic utilization of ChatGPT. The results advocate for reliance on ChatGPT with limitations in regard to accuracy and suggest a change in the academic use of technology. The results also offer a perspective that blends theoretical innovation with practical application in educational settings.