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Incorporating AI tools like ChatGPT into higher education has been beneficial, yet the extent of user satisfaction with the quality of information provided by these tools, known as user information satisfaction (UIS) and information quality (IQ) theory, remains underexplored. This study introduces a UIS model specifically designed for ChatGPT's application in the educational sector based on multidimensions of IQ theory. Drawing from established UIS and IQ theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. Data was collected from Indonesian university participants (N = 508) and analyzed using structural equation modeling with Smart‐PLS 4.0. The results reveal that completeness, precision, timeliness, convenience, and information format are the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings recommend a cautious approach to integrating ChatGPT in higher education. We advocate for strategic use that recognizes its innovative potential while acknowledging its limitations, ensuring responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality. [ABSTRACT FROM AUTHOR]

AbstractThe advent of Chat-GPT, an AI-driven technology, is reshaping various sectors, particularly higher education. This study, merging the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Protection Motivation Theory (PMT), explores the relationship between technology adoption and protection motivation in higher education, addressing the concept of “the (un)knowledgeable, the (un)skilled.” Through Structural Equation Modeling, findings from Indonesian participants (N = 445), including students and lecturers, reveal that perceived benefits such as task efficiency, hedonic motivation, performance expectancy, and effort expectancy predominantly motivate Chat-GPT use. Risk perception leans more on perceived vulnerability than severity, with insignificant impact from response cost. Response efficacy and self-efficacy significantly determine intention. Insight from moderating effect of educational level suggest that doctoral-level users demonstrate increased Chat-GPT usage, and gender plays a role in response efficacy and task efficiency. Both educational level and gender actively influence users’ intentions and actual usage behavior. These insights guide educators, policymakers, and institutions in ethically integrating AI, managing evolving risk perceptions, and empowering users in the dynamic AI landscape of higher education. Policymakers (e.g., university boards) are urged to dexterity an ethical framework and authorize in user efficacy to ensure equitable access and benefits from Chat-GPT in education. [ABSTRACT FROM AUTHOR]