Speaker
Description
Abstract
The growing integration of artificial intelligence (AI) technologies into language learning has transformed opportunities for independent speaking practice in EFL contexts. Despite increasing student engagement with AI-powered platforms, limited empirical research has examined how AI-supported learning relates to learners’ self-regulated learning (SRL) strategies and their speaking self-efficacy. This study explores the relationship between AI-supported SRL and speaking self-efficacy among Vietnamese EFL university students. Adopting a quantitative correlational design, the study surveyed approximately 100 undergraduate students at a private university in Vietnam. AI tools in this study refer to generative AI platforms and AI-powered speaking applications commonly used for idea development, feedback generation, and pronunciation support. Data were collected through two Likert-scale questionnaires measuring students’ engagement in AI-supported SRL strategies (e.g., goal setting, self-monitoring, and self-reflection) and their speaking self-efficacy beliefs. Descriptive statistics, reliability analysis, and Pearson correlation analysis were conducted using SPSS. The findings reveal a significant positive relationship between AI-supported SRL and speaking self-efficacy. Students who demonstrated greater self-regulatory engagement when using AI tools reported stronger confidence in their speaking performance. The study highlights the potential of AI-supported learning environments to foster learner autonomy and enhance psychological readiness for speaking in EFL contexts.
Keywords: Artificial intelligence in language learning; AI-supported self-regulated learning; speaking self-efficacy; EFL higher education; learner autonomy.
