CHATGPT USE AND PERCEIVED IMPROVEMENT IN ENGLISH SPEAKING: EVIDENCE FROM ENGLISH-MAJOR STUDENTS AT A VIETNAMESE UNIVERSITY

Abstract

This study examined the relationship between ChatGPT use and English-major students’ perceived improvement in English speaking. It focused on three aspects of ChatGPT use: frequency of use, speaking purposes, and interaction level. Data were collected from 238 English-major students at the Academy of Policy and Development in Vietnam using a 5-point Likert-scale questionnaire. Descriptive statistics, Cronbach’s alpha, exploratory factor analysis, Pearson correlation, and multiple regression were used for data analysis. The results showed positive associations between all three aspects of ChatGPT use and perceived improvement. Speaking purposes had the strongest association (r = .709), followed by interaction level (r = .699) and frequency of use (r = .614), with all p < .001. The multiple regression model was statistically significant, F(3, 234) = 239.977, p < .001, with the three predictors accounting for 75.5% of the variance in perceived improvement. Speaking purposes (β = .397), interaction level (β = .382), and frequency of use (β = .336) were significant predictors of perceived improvement. Students also reported relatively high perceived improvement across the five speaking dimensions, with fluency receiving the highest mean score (M = 4.01). Given the cross-sectional and self-reported nature of the data, the findings indicate statistical associations rather than causal effects.