FROM ASSIGNMENT TO AFFECTION: WHAT DRIVES UNIVERSITY STUDENTS TO KEEP USING CHATGPT?
With the advancement of artificial intelligence (AI) technology, AI tools like ChatGPT have gradually become a part of the life of students in universities. Previous research has mainly addressed the functional aspects of AI, such as information retrieval and academic support, but the socio-emotional and personalized aspects of AI, and how these shape users’ continued usage behaviour. Therefore, this study aims to examine the effects of academic support, emotional support, and perceived personalisation on students’ continuance intention toward ChatGPT, with perceived trust acting as a mediating mechanism. This research grounded by the Expectation-Confirmation Theory and Information Systems Continuance Model by incorporating two additional variables: perceived personalisation and academic support and emotional support as antecedents of students’ continuance intention toward ChatGPT. This quantitative study used an online survey to collect data from 263 university students. The proposed model was analysed using SmartPLS-SEM to examine both direct and indirect relationships, with perceived trust specified as a mediating variable. The structural model indicates that academic support and emotional support have significant direct effects on continuance intention. Although perceived personalisation positively influences user trust, its direct effect on continuance intention is not significant. Instead, perceived trust fully mediates this relationship, indicating that personalisation alone does not directly drive continued use unless it first builds user trust. These findings highlight the critical role of trust as a psychological mechanism through which AI personalisation translates into sustained user engagement. The study contributes to the literature on human–AI interaction by integrating cognitive, emotional, and personalisation dimensions within a unified continuance framework. Practically, the results suggest that AI developers should prioritise trust-building mechanisms when designing personalised and emotionally supportive systems to ensure long-term user adoption, particularly in educational contexts.