The Impact of AI-Assisted Learning on EFL Speaking Skills: A Mixed-Methods Study in the Iranian Context.

The emergence of artificial intelligence has accelerated and fostered the process of language learning. Despite the growing shift towards technology integration, there is a scarcity of empirical research examining the impact of AI-assisted learning activities on the speaking proficiency of Iranian EFL learners. This study investigated the impact of artificial intelligence (AI)-assisted learning activities on the speaking skills of EFL learners in Iran. This research employed a quasi-experimental design with 40 participants divided into a control group and an experimental group that utilised AI-based tools, specifically the Gliglish and Sayra applications. The study was conducted for one academic semester. Both quantitative and qualitative data were gathered using a mixed-methods design. Descriptive statistics, test of normality, paired sample T-test and Mann-Whitney U test were employed. Results from pre-test and post-test comparisons revealed significant improvements in the experimental group’s speaking skills, highlighting the effectiveness of AI-based learning interventions. Moreover, qualitative data collected through questionnaires indicated positive perceptions of AI-assisted learning among students, with benefits observed in motivation, engagement, and language proficiency. The findings imply that using AI tools offers a way to address the common challenge of limited classroom time dedicated to speaking practice. In addition, the results provide valuable insights into the potential of AI in language education and contribute to understanding AI’s role in language education, suggesting that AI-assisted strategies can enhance EFL speaking development. [ABSTRACT FROM AUTHOR]