Speaker
Description
The growing use of artificial intelligence (AI) is changing how Vietnamese university students engage with English beyond traditional classrooms. AI is no longer just an extra study tool but part of students’ everyday encounters with English, creating new opportunities for practice, reflection, and meaning-making. This trend is especially important in a higher education system that is gradually moving toward more ESL-oriented conditions, and it raises a key question: is AI-supported learning linked with deeper approaches to learning English, rather than simply making learning faster or more convenient? Based on survey data from 313 Vietnamese undergraduates, this study examines students’ self-reported level of AI use for English learning and its relationship with overall and component-level deep approaches to learning (deep motive and deep strategy), using descriptive statistics and Pearson correlations. Findings show consistent positive correlations between AI use and both deep motive and deep strategy, with slightly stronger links for deep strategy. Taken together, the results suggest that AI functions not only as a productivity tool but also as a mediational resource that carries learners’ use of English into their day-to-day academic practices. In doing so, it contributes to learning conditions that resemble ESL-oriented environments and points to important implications for English language teaching in Vietnam, particularly in shaping how AI can be integrated to support sustained, meaningful use of English rather than one-off, efficiency-driven gains.
