Working Students' Perceptions of Artificial Intelligence in English Language Learning: A Descriptive Mixed-Method Survey Study
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DOI:
https://doi.org/10.24256/ideas.v14i1.10360Keywords:
artificial intelligence, descriptive survey, English language learning, learner perceptions, working studentsAbstract
The application of artificial intelligence (AI) in English language learning has expanded rapidly in higher education; however, research focusing on working students remains limited. This study examined working students' perceptions of AI use in English language learning across four dimensions: perceived benefits, ease of use, learning support, and perceived challenges. Grounded in the Technology Acceptance Model (TAM), this study extends the framework by incorporating learning support as an additional construct relevant to working students. A descriptive mixed-method survey design was employed, involving 210 undergraduate students at Universitas STEKOM, Indonesia, who were concurrently employed and had prior experience using AI tools for English language learning. Data were collected through a 23-item Likert-scale questionnaire and two open-ended questions. Descriptive analysis showed that perceived benefits received the highest mean score (M = 3.74, SD = 0.67), followed by learning support (M = 3.66, SD = 0.66), ease of use (M = 3.62, SD = 0.60), and perceived challenges (M = 3.54, SD = 0.52). Thematic analysis of open-ended responses revealed time efficiency (40.5%), flexible access (40.5%), and instant feedback (35.7%) as the most frequently cited benefits, while overreliance on AI and reduced independent thinking (41.9%) and the perception that AI cannot fully replace human instructors (30.0%) emerged as the main concerns. These findings indicate that working students generally hold favourable perceptions of AI in English learning, valuing its instrumental support while also recognizing the limitations of AI-based learning tools.
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