AI chatbot-assisted vocabulary learning: Relationships with self-regulation, motivation, and performance among Chinese private college students

Abstract

This study empirically investigated the application of a large language-model-driven artificial intelligence (AI) chatbot in self-regulated vocabulary acquisition among Chinese private college students. An 8-week experiment comparing AI-chatbot-assisted and conventional self-regulated vocabulary learning demonstrated that AI chatbot assistance could significantly improve vocabulary performance both across and within groups. Results revealed that the use of AI chatbot not only improved learning outcomes directly through personalized, self-paced learning but also indirectly by enhancing vocabulary learning strategy use and satisfying basic psychological needs. Notably, metacognitive strategy use fully mediated the relationship between perceived autonomy and vocabulary performance. Moreover, perceived autonomy moderated the effect of the chatbot intervention on students’ vocabulary learning outcomes. These findings outline the potential of AI chatbots in facilitating vocabulary acquisition and underscore the critical role of perceived autonomy and metacognitive strategy use in AI-chatbot-assisted language education.

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