English students’ narratives of AI integration in learning: Cognitive benefits, ethical challenges, and impact on student autonomy

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Original abstract

Despite the rapid adoption of Artificial Intelligence (AI) in higher education, limited research has explored how students in English for Specific Purposes (ESP) courses, particularly within non-English disciplines, perceive AI-assisted language learning and the pedagogical as well as ethical implications of its integration. This study aims to explore students’ perceptions of AI utilization in an ESP classroom as a means of scaffolding language learning. The study was conducted in the Environmental Science Study Program at an Islamic university in Surakarta, Indonesia. Employing a qualitative narrative inquiry design, data were collected through semi-structured interviews with nine second-semester students who had prior experience using AI tools for academic purposes. The findings indicate that students generally hold positive perceptions of AI integration in ESP learning, with ChatGPT, Gemini, and Grammarly identified as the most frequently used AI applications. Thematic analysis revealed five major themes: AI as a cognitive support tool, patterns of AI usage, perceived learning benefits, implementation challenges, and ethical-cultural considerations. Participants reported that AI enhanced writing quality, vocabulary development, reading comprehension, and content summarization while facilitating personalized learning, simplifying complex concepts, and increasing learning confidence and motivation. However, concerns were also raised regarding information inaccuracy, miscommunication, excessive dependency on AI, and the potential decline of critical thinking skills. The study highlights the importance of integrating AI into ESP instruction through pedagogically sound practices supported by ethical guidance and digital literacy. These findings contribute to the growing body of literature on AI-assisted language learning by providing context-specific insights that can inform the design of responsible, effective, and ethically grounded AI-enhanced ESP instruction.

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