Beyond the Books: Exploring Factors Shaping Chinese English Learners' Engagement with Large Language Models for Vocabulary Learning

Informal English learning plays a crucial role in vocabulary learning, yet few scholars have explored the use of large language models for this purpose. In light of this, our study, integrating Self-Determination Theory (SDT) and the Unified Theory of Acceptance and Use of Technology (UTAUT), employed Structural Equation Modeling (SEM) to investigate factors influencing 568 Chinese English learners' use of large language models for vocabulary learning. Our findings identified six significant factors from those models-perceived autonomy, perceived competence, perceived relatedness, performance expectancy, effort expectancy, and social influence-that significantly shape learners' intentions and behaviors towards utilizing large language models for vocabulary learning. Notably, effort expectancy emerged as the most influential factor, while facilitating conditions did not significantly impact usage intentions. This research offers insights for future curriculum design and policy formulation, highlighting the importance of understanding learners' perspectives on technology use in education.