AI-supported Interactive learning environments for English speaking: a bibliometric and systematic review

The rapid integration of artificial intelligence (AI) into English language education has reshaped interactive learning environments, particularly in speaking development. While prior studies have examined AI tools, lecturer competence, and learning strategies separately, limited research has systematically synthesised how these elements interact within AI-supported interactive learning environments. This study addresses this gap through a bibliometric analysis and systematic literature review of 89 Scopus-indexed journal articles published between 2009 and 2025. Using VOSviewer and PRISMA-guided procedures, the analysis maps publication trends and synthesises conceptual patterns in AI-supported English-speaking instruction. The findings indicate a shift from technology-centred approaches toward interaction-oriented perspectives. Lecturer competence, encompassing pedagogical, technological, and affective-ethical dimensions, emerges as a mediator of learner-AI interaction. Learner strategies, especially self-regulated learning and autonomy, serve as mechanisms that influence engagement with AI-mediated feedback. AI tools are increasingly conceptualised as interactive resources whose educational efficacy depends more on pedagogical integration and strategic engagement than mere technological advancement. This study argues that English-speaking development in AI-supported interactive learning environments is best understood as an emergent outcome of reciprocal interactions among lecturer competence, learner strategies, and AI tools. The findings advance a human-centred, ecosystem-oriented perspective and offer implications for research and instructional design in higher education.