This study examines the usage patterns of Artificial Intelligence (AI) technology and their effects on English language comprehension among students at Politeknik Kota Bharu. A cross-sectional quantitative survey design was employed, involving 344 students from four academic departments. Data were collected using a structured questionnaire and analysed using descriptive statistics via SPSS version 26. The findings indicate that students actively utilise AI tools for learning purposes, with ChatGPT, Google Translate, and Grammarly being the most frequently used applications. Overall, AI usage demonstrated a positive impact on English language comprehension across four key domains: writing, reading, speaking, and listening. Writing skills recorded the highest level of improvement (mean = 4.07), followed by reading comprehension (mean = 4.00). Speaking (mean = 3.89) and listening skills (mean = 3.88), meanwhile, showed comparatively moderate gains. The stronger improvement in text-based skills reflects the predominance of AI tools that provide immediate feedback, language correction, and content clarification. Despite these positive outcomes, the study also identifies challenges such as limited exposure to AI-focused instruction, variations in accessto technology, and the need for greaterlecturerreadinessin integrating AI into teaching practices. Ethical considerations, including data privacy and responsible AI use, are also highlighted. The findings underscore the potential ofAI technology to enhance English language learning in the TVET context and suggest that strategic integration of AI training within the curriculum could improve learning outcomes. From a broader perspective, this study provides empirical evidence to inform educational policy and institutional planning aimed at promoting effective, ethical, and inclusive AI adoption in technical and vocational education.
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Melissa Suan Chin Khor
Che’ Fadhilah Che’ Lah
Rodey Hamza Hamzah
International Journal on e-Learning and Higher Education
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Khor et al. (Sat,) studied this question.
synapsesocial.com/papers/69a285aa0a974eb0d3c00a25 — DOI: https://doi.org/10.24191/ijelhe.v21n1.2111
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