<![CDATA[The urgency of this study stems from the growing gap in English language learning, particularly in mastering English structures such as passive voice and complex sentences, which has widened in the aftermath of the COVID-19 pandemic. EFL students often struggle to comprehend complex grammatical forms, which adversely affects their writing and speaking proficiency. Adaptive AI-based technology presents a promising solution by offering personalized, interactive, and effective learning experiences. This study aims to experimentally investigate the effectiveness of adaptive AI technology in enhancing EFL students’ understanding of English structure, specifically by comparing it to conventional teaching methods. A quasi-experimental design with a pretest-posttest control group approach was employed. The population consisted of undergraduate students majoring in English, and the sample comprised 60 students divided equally into experimental and control groups. The experimental group received instruction using adaptive AI technology, while the control group was taught using conventional methods. Data were collected through pretests, posttests, questionnaires, and interviews. Inferential statistical analysis, including MANOVA, was conducted to determine significant differences in grammar mastery between groups. The results indicated a statistically significant improvement in the experimental group's posttest scores (M = 84.70) compared to the control group (M = 74.30), particularly in mastering passive voice and complex sentences. Students also reported positive perceptions of the AI-based learning experience. This study contributes to the advancement of English language teaching and offers a scalable model for integrating adaptive AI in language education.]]>
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