ARTIFICIAL INTELLIGENCE IN ESP LEARNING: BENEFITS AND CHALLENGES PERCEIVED BY ELECTRICAL ENGINEERING STUDENTS

Abstract

Artificial Intelligence (AI) is increasingly used in English language learning, yet its value may differ across language skills and professional learning contexts. This study examined electrical engineering students’ perceived benefits and challenges of using AI for English language learning at Sriwijaya State Polytechnic. A quantitative descriptive survey was conducted with 50 undergraduate students using a seven-item, five-point Likert-scale questionnaire covering speaking, writing, reading, listening, learning motivation, critical thinking, and literacy. The findings showed that reading received the strongest perceived benefit, with 70% of respondents agreeing that AI supported reading, followed by writing (54%) and speaking (50%). Perceptions were less decisive for motivation, where 46% agreed and 50% were neutral, and for listening, where only 32% agreed while 62% selected neutral. Students also reported important concerns: 64% agreed that excessive AI use could reduce critical thinking and 56% perceived a possible decline in literacy. These results suggest that AI is perceived as particularly useful for text-oriented English for Specific Purposes tasks, such as understanding technical texts and specialized vocabulary, while its value for oral and listening development is less certain. The study contributes a skill-specific perspective on AI-assisted English learning in vocational engineering education. English instructors, curriculum developers, and vocational institutions should therefore position AI as a scaffold for guided practice, source checking, feedback, and technical-text comprehension rather than as a substitute for independent reasoning. Because the findings are based on self-reported perceptions from one institution, they should not be interpreted as causal evidence of language-skill improvement.