VietTESOL International Convention 2026

As Vietnam shifts from traditional EFL toward more communicative ESL-oriented English education, there is a growing need for practical tools that help learners move from passively receiving feedback to actively self-regulating their language development. This presentation introduces a bespoke AI-mediated mobile application designed and developed by the presenter to support self-regulated speaking practice. Grounded in Zimmerman’s cyclical Self-Regulated Learning framework, the app engages EFL learners in structured monologue tasks followed by immediate AI-generated feedback that prioritizes clarity, coherence, and interpretability in line with English as a Lingua Franca principles. The system guides learners through a complete learning cycle: goal setting, monologue recording, feedback review, selection of cognitive, social, and affective strategies, re-recording, and guided reflection. A small-scale four-month longitudinal study with five participants investigated how learners’ strategy use evolves, the extent to which they apply app-provided feedback in subsequent performances, and the development of their feedback literacy behaviors as measured by Dawson et al.’s Feedback Literacy Behavior Scale. This presentation discusses the theoretical foundations, the accessible no-code development process, key classroom findings, and practical implications for EFL-to-ESL transitioning contexts. Participants will gain concrete insights into designing similar AI-supported systems without formal programming experience and will experience a live demonstration of the monologue-based feedback cycle. The session highlights how GenAI tools can effectively foster learner autonomy and feedback literacy in mobile-assisted language learning.