AI-Powered Tools and Language Learners’ Speaking Performance: Probing into Language Teachers’ Narratives

Document Type : Original Article

Author
Hamid Reza Hashemi Moghaddam
Department of English Language and Literature, Faculty of Humanities and Social Sciences, Hakim Sabzevari University, Sabzevar, Iran
10.22034/quipls.2025.2064416.1011
Abstract
The present qualitative study, using activity theory proposed by Engeström (1987) and elaborated by Artemova (2024) as the conceptual framework, explored the English language teachers’ experiences with regard to the role AI speaking programs could play in fostering their language learners’ speaking performance. The main conceptions of the conceptual framework entailed subject, object, outcome, instruments, labor division, community, and rules. The participating teachers narrated their own stories through semi-structured interviews, which were analyzed using thematic analysis. Their stories focused on three noteworthy themes: emotional self-regulation, the opportunity of informal learning through the digital world, and the decrease in learners’ autonomy in the case of overreliance. Generally, the participating teachers, focusing on the factors of subject, outcome, and rules, highlighted the transition from other-regulation towards self-regulation. They also acknowledge the value of informal digital learning process, developing language learners’ competence, enhancing their sense of relatedness, and strengthening the process of engagement.

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