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Generative AI and Oral Proficiency: How ChatGPT Is Transforming English Language Speaking Practice

Jul 2026 · International Journal of English Teaching and Learning · Vol 4, pp. 13-18 · 0 citations · 4 references

TL;DR

Findings indicate that structured ChatGPT practice yields modest but meaningful enhancements in oral proficiency, particularly when leveraging affective factors.

Abstract

The integration of generative artificial intelligence (GenAI) into language learning contexts presents potential for developing oral proficiency, though empirical evidence regarding its efficacy remains limited. This quasi-experimental study investigated the impact of ChatGPT-mediated speaking practice on English oral proficiency among Iranian learners. A total of 380 participants (190 female, 190 male; M age = 21.4, SD = 4.7) from Tehran and Isfahan were assigned to experimental (ChatGPT practice; n = 190) or control (human pair work; n = 190) groups. Both groups completed an 8-week intervention with three 30-minute weekly sessions. Oral proficiency was assessed using a Common European Framework of Reference for Languages (CEFR)-aligned Oral Proficiency Interview (OPI) scored on fluency, pronunciation, lexical resource, grammatical accuracy, and interactive communication (total score: 0–20). Multilevel growth modeling revealed a significant time × group interaction, F (1, 376) = 48.73, p < .001, partial η 2 = .115. The experimental group demonstrated greater gains ( M Δ = 2.90, SD = 1.60) than controls ( M Δ = 0.75, SD = 1.80), d = 1.20, 95% CI [0.95, 1.45]. Gender moderated this effect, with females in the experimental group showing the largest improvements ( M Δ = 2.50). Mediation analysis confirmed that increased integrative motivation partially mediated proficiency gains (indirect effect = 0.28, 95% CI [0.20, 0.36]). Findings indicate that structured ChatGPT practice yields modest but meaningful enhancements in oral proficiency, particularly when leveraging affective factors. Implications for AI-augmented speaking pedagogy in resource-constrained contexts are discussed.

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