Enhancing Academic Engagement and Needs Satisfaction Through AI: A Mixed-Methods Study in Chinese EFL Tertiary Education Context

Abstract

The rapid growth of artificial intelligence (AI) has transformed the educational field by providing efficient assistance for personalised learning. Despite the promising opportunities AI has presented, the impact of AI tools on students' learning outcomes in language learning settings has yet to be further explored, as well as their potential to enhance academic engagement in this specific domain. Therefore, based on the framework of Self-Determination Theory (SDT), this research aims to examine the role of behavioural, cognitive, and emotional engagement in improving students' needs satisfaction specifically among 300 Chinese tertiary learners in the AI-enhanced Chinese EFL context. A mixed-methods approach was used to collect data from Chinese EFL college students, combining self-report surveys and semi-structured interviews. Results from the quantitative data showed that AI perception and academic engagement significantly impact needs satisfaction in AI-enhanced EFL learning. Also, the qualitative findings suggested that while academic engagement and needs satisfaction are critical facilitators for adopting AI-assisted EFL learning, perceived difficulties and unmet needs are significant barriers to long-term usage. Moreover, this study contributes to SDT by highlighting the critical role of academic engagement in enhancing needs satisfaction and offering practical strategies for educators to improve AI application adoption and effectiveness in Chinese educational contexts.