The Impact of AI-Assisted Vocabulary Learning on EFL Students in Chinese Higher Vocational Colleges

Abstract

This study examined the impact of AI-assisted vocabulary learning on EFL students in Chinese higher vocational colleges. The study focused on three independent variables: perceived usefulness of AI-assisted vocabulary learning, learning motivation and learning engagement. Vocabulary learning effectiveness was treated as the dependent variable. A quantitative cross-sectional survey design was adopted, and data were collected from 250 EFL students in Chinese higher vocational colleges in Sichuan Province, China. The questionnaire contained demographic items and Likert-scale items measuring the four main constructs. SPSS was used to conduct frequency analysis, reliability analysis, Pearson correlation and multiple regression analysis. The findings showed that AI tools were widely used by respondents, with 60.8% using them often or very often for English vocabulary learning. Reliability results confirmed excellent internal consistency for all scales. Correlation analysis showed strong positive relationships among perceived usefulness, learning motivation, learning engagement and vocabulary learning effectiveness. Regression results confirmed that all three predictors had significant positive effects on vocabulary learning effectiveness, with learning engagement emerging as the strongest predictor. The study concludes that AI-assisted vocabulary learning can enhance EFL vocabulary outcomes when students perceive AI tools as useful, remain motivated and actively engage in learning activities.