<![CDATA[Vocational students often struggle with technical English vocabulary, which highlights the need for a more effective, technology-based learning approach. This study investigates the effectiveness of an AI-based vocabulary learning platform (Qwen AI) in improving English vocabulary mastery among tenth-grade students in vocational education. The research was conducted at SMK N 2 Yogyakarta with 72 participants (36 in the experimental group, 36 in the control group) enrolled in the Visual Communication Design (Desain Komunikasi Visual) program during the second semester of the 2025/2026 academic year. Using a quasi-experimental design, the experimental group received instruction through the Qwen AI Platform while the control group received conventional instruction. Pre-test and post-test measurements assessed vocabulary mastery across three dimensions: meaning, form, and use in context. The results demonstrated that the experimental group achieved a mean gain of 11 points (from 85 to 96), higher than the control group's gain of 4 points (from 94 to 98). The most notable improvement was found in students' ability to use vocabulary appropriately within vocational contexts, which rose by 23 percentage points (from 75% to 98%). This finding suggests that the platform's contextual, scenario-based exercises were particularly effective in helping students apply technical vocabulary in authentic situations. The Wilcoxon Signed-Rank Test (p = 0.000) confirmed the statistical significance of these improvements. The findings indicate that AI-based adaptive vocabulary platforms can effectively enhance vocational students' English proficiency, particularly in the contextual application of technical terminology relevant to their professional fields. This study contributes to the evidence base supporting technology-integrated language instruction aligned with the principles of English for Specific Purposes (ESP) in vocational education.]]>
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