DEVELOPING LEARNER AUTONOMY IN ENGLISH FOR PHARMACY STUDENTS THROUGH AI-POWERED EDUCATIONAL TECHNOLOGIES

Аннотация

As pharmaceutical education becomes increasingly English-mediated, pharmacy students need not only language knowledge but also the ability to manage their own learning beyond the classroom. This paper explores how AI-powered educational technologies — adaptive learning platforms, AI chatbots, automated feedback tools, and gamified applications — can be used to foster learner autonomy in English for Specific Purposes (ESP) courses for pharmacy students. The discussion is grounded in the classical theory of learner autonomy developed by Holec (1981), Little (1991), and Benson (2001), and is combined with a synthesis of recent empirical and review studies (2022–2026) on artificial intelligence in language education, together with the authors’ own classroom observations while teaching English for pharmaceutical purposes. The paper identifies four key mechanisms through which AI supports autonomous learning: personalized progression through pharmaceutical vocabulary, instant individualized feedback on professional writing, chatbot-based simulation of pharmacist–patient interactions, and motivation-sustaining gamified self-tracking. It further discusses the documented risks of over-reliance on AI tools and the resulting erosion of critical thinking, arguing that AI applications are most effective when they support, rather than replace, teacher guidance. Building on this evidence, the paper proposes a three-pillar framework — terminology mastery, professional simulation, and self-assessment — for integrating AI into pharmacy ESP curricula, together with a concrete design for a small-scale classroom pilot study. The paper concludes by calling for further longitudinal, classroom-based research to measure the long-term effect of such integration on learner autonomy and professional language competence.