The Impact of Al-Assisted Learning on EFL Learners' Speaking Performance: Evaluating the Role of Self-Regulation

سال انتشار: 1405
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 42

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ELTCONF01_135

تاریخ نمایه سازی: 18 مرداد 1405

چکیده مقاله:

The rapid integration of Artificial Intelligence (AI) into educational contexts has opened new pedagogical avenues for enhancing second language acquisition, particularly in the development of productive skills such as oral communication. This study investigates the impact of AI-assisted learning on the speaking performance of Iranian English as a Foreign Language (EFL) learners, alongside a rigorous examination of self-regulation as a potential moderating variable. A quasi-experimental, pre-test/post-test control group design was employed, involving a homogenous sample of ۶۰ intermediate EFL learners. Participants were randomly assigned to either an experimental group (n = ۳۰) that utilized an emotionally intelligent AI conversational assistant, Pi, for structured oral practice, or a control group (n = ۳۰) that received conventional, teacher-centered speaking instruction over an intensive ۱۲-week period. Data were collected using a validated Self-Regulation Questionnaire (SRQ) and an objective AI-administered speaking proficiency assessment tool, SmallTalk۲Me. Multivariate Analysis of Covariance (MANCOVA) was utilized to analyse the data, with baseline pre-test scores serving as covariates. The inferential results revealed that learners engaged in AI-assisted instruction demonstrated significantly higher post-test speaking performance (p < .۰۰۱, partial n² = .۶۵۰) and enhanced self-regulation skills (p < .۰۰۱, partial n² = .۷۰۶) compared to the control group. Contrary to the initial hypothesis, baseline self-regulation skills did not significantly moderate the relationship between AI-assisted learning and speaking performance (p = .۹۵۷). These findings suggest that the highly structured, adaptive scaffolding provided by the AI tool benefitted learners uniformly, effectively compensating for prior deficits in self-regulatory capacities. The study underscores the transformative potential of conversational AI in mitigating foreign language speaking anxiety, providing individualized real-time feedback, and fostering autonomous, self-directed learning behaviours in resource-constrained EFL environments.

نویسندگان

Davoud Amini

Associate Professor of ELT, Department of English, Faculty of Literature and Humanities, Azarbaijan Shahid Madani University, Tabriz, Iran

Mina Zare

MA in ELT, Azarbaijan Shahid Madani University, Tabriz, Iran