Exploring Chinese EFL learners’ AI continuance use intention based on the ECM-ISC: Theoretical validation and contextual extension

Abstract

Grounded in the ECM-ISC, this study employs semi-structured interviews to investigate the usage experiences and continuance intention of Chinese EFL learners toward AI tools. Through systematic coding and thematic analysis, ten key influencing factors within the dimensions of perceived usefulness and confirmation were identified, covering both theoretical and localized levels. Findings indicate that learners’ satisfaction with AI tools is often implicitly expressed through nuanced emotional responses, reflecting a complex psychological negotiation among functional value, cultural identity, ethical concerns, and academic norms. The study further reveals the distinctive influence mechanisms of localized factors, such as policy support and cultural context, within the Chinese educational ecology on continuance intention. Building on the validation of ECM-ISC’s core variables, this research deepens the model’s localized interpretation, enriches understanding of AI tool usage behaviors in cross-cultural digital learning environments, and offers practical implications for localized educational technology design, teacher professional development, and policy formulation.