Background: Artificial Intelligence (AI) has increasingly been adopted in language education to address persistent challenges in traditional instruction, particularly the limited personalization, delayed feedback, and constrained exposure to authentic language input. These issues often hinder learners’ progress in mastering essential components of language proficiency, such as grammar and vocabulary. Research Objectives: This study aims to examine the influence of AI-powered tutoring tools on the development of English grammar accuracy and vocabulary mastery among learners across varying proficiency levels. Specifically, it assesses whether AI-based instruction offers measurable advantages over conventional teaching methods. Methods: A mixed-methods approach was implemented using a quasi-experimental design with 100 English language learners divided equally into experimental and control groups. The experimental group received AI-assisted instruction using adaptive learning systems, while the control group followed traditional methods. Data were obtained through pre- and post-tests, surveys, and interviews. Quantitative data were analyzed using paired t-tests and ANOVA, while qualitative responses underwent thematic analysis. Results: Findings indicate that learners using AI-powered tools demonstrated greater improvements in grammatical accuracy and vocabulary retention compared to those receiving traditional instruction. The adaptive feedback mechanisms and personalized learning pathways significantly enhanced learner engagement and supported consistent progress. Qualitative insights further revealed positive learner perceptions regarding usability, motivation, and clarity of feedback provided by AI systems. Conclusions: The study concludes that AI integration contributes positively to English grammar and vocabulary development by offering individualized learning experiences and immediate corrective feedback. While AI cannot fully replace human instruction, it serves as an effective complementary tool. Further research is recommended to explore long-term impacts, ethical considerations, and strategies for optimizing AI use across diverse educational contexts.
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