Pedagogically Structured AI Feedback and Grammatical Accuracy in EFL Speaking: A 14-Week Longitudinal Study

Abstract

Grammatical accuracy in spontaneous second language (L2) speech remains difficult to develop, particularly in contexts with limited opportunities for sustained oral practice. This study investigates whether structured, memory-enabled artificial intelligence (AI) speech coaching supports the development of grammatical accuracy among Armenian EFL learners. A 14-week longitudinal mixed-methods design was employed with 64 undergraduate students, supplemented by a non-randomized comparison group (n = 13). Learners engaged in weekly AI-supported speaking tasks, and grammatical accuracy was measured as errors per 100 words across three time points. Repeated-measures ANOVA revealed a significant reduction in grammatical errors over time (ηp² = .45), with the strongest improvements observed in rule-governed categories such as tense–aspect, subject–verb agreement, and word order, and more limited progress in articles and prepositions. Moderate-proficiency learners demonstrated the most consistent gains, while the comparison group showed no significant improvement. The findings suggest that AI-mediated feedback can support grammatical development when embedded within structured pedagogical frameworks, while highlighting the importance of instructional guidance to prevent overreliance on automated corrections. This study contributes longitudinal evidence on AI-supported grammatical development in spontaneous speech and provides a fine-grained analysis of category-specific improvement.