Examining Chinese International Students’ Continuance Intention to Use AI Systems for Speaking Practice: Insights from Acculturative Stress and the Expectation–Confirmation Model
TL;DR
Qualitative findings indicate that AI systems serve as low-risk, compensatory resources when students experience language-related, social, and academic adaptation pressures, while sustained use depends on alignment with learners’ evolving needs.
Abstract
This study examines Chinese international students’ continuance intention to use AI systems (e.g., EAP Talk) for English speaking practice by extending the Expectation–Confirmation Model (ECM) with selected dimensions of acculturative stress. Using a sequential explanatory mixed-methods design, survey data from 245 students in UK higher education were analysed with structural equation modelling, followed by interviews with 16 participants. Results show that confirmation, perceived usefulness, and satisfaction significantly predict continuance intention, supporting traditional ECM pathways. Language insufficiency, social isolation, and academic stress also positively influence continued use. Qualitative findings indicate that AI systems serve as low-risk, compensatory resources when students experience language-related, social, and academic adaptation pressures, while sustained use depends on alignment with learners’ evolving needs. The study highlights the value of contextualising technology continuance within international students’ acculturative stress experiences.