Beyond Human Interaction? Exploring the Role of AI-Speaking Tools in an Immersive English - Ariani; Andi Anto Patak; Yunitari Mustikawati (Foreign Language Instruction Probe, 2026)
This study examined the function of AI-speaking tools in an immersive English learning context via the application of the English Area (ERa) software among Indonesian EFL learners. The study examined the impact of incorporating AI-assisted speaking applications into immersive English interactions on students' speaking performance, perceptions, and communicative experiences. A sequential explanatory mixed-methods design was utilized, comprising Grade XI pupils at UPTD SMAN 1 Kalukku, categorized into experimental and control groups. Quantitative data were gathered using pretest-posttest speaking evaluations assessed with speaking rubrics, whilst qualitative data were acquired through semi-structured interviews, classroom observations, and documentation. Quantitative analysis encompassed descriptive statistics, paired sample t-tests, independent sample t-tests, and Cohen’s d effect size assessment, while qualitative data were subjected to thematic analysis. The results indicated that the experimental group utilizing AI-speaking tools shown significantly bigger enhancements in speaking skills than the control group, with posttest mean scores rising from 55.00 to 77.56, in contrast to the control group's increase from 52.53 to 60.11. Students additionally indicated improvements in fluency, pronunciation, vocabulary acquisition, confidence, and readiness to communicate. Notwithstanding technological obstacles like internet connectivity and speech-recognition constraints, users regarded AI-speaking tools favorably as supportive communicative scaffolding rather than substitutes for human engagement. The research emphasizes the significance of incorporating AI-assisted speaking practice into human-centered immersive learning environments to enhance communicative competence in EFL teaching.