A bibliometric analysis of smart voice assistants for EFL listening and speaking in elementary education

Abstrak

This study presents a bibliometric analysis of research on smart voice assistants (SVAs) used to support English as a Foreign Language (EFL) listening and speaking skills in elementary education. Using Publish or Perish and VOSviewer, an initial dataset of 500 publications was screened based on relevance, educational level, and content focus. After applying the inclusion criteria, 29 documents published between 2019 and 2025 were retained for full analysis. The annual publication trend indicates minimal research activity before 2023, followed by a sharp increase in 2025, suggesting an emerging academic interest in this technology. Citation analysis shows that highly cited studies predominantly adopt systematic review approaches rather than classroom-based experimentation. Term co-occurrence mapping revealed only three recurring keywords (Alexa, systematic review, and student), indicating limited conceptual convergence and an undeveloped research vocabulary. These findings suggest that research on SVAs in early EFL learning is still in its infancy, lacking theoretical coherence, established pedagogical models, and large-scale empirical validation. The study highlights critical gaps and identifies implications for researchers, educators, and technology developers. As conversational AI continues to advance, smart voice assistants hold potential to transform oral language learning experiences for young learners; however, sustained research efforts are needed to shape their pedagogical integration, ethical use, and long-term educational value.