PEDAGOGICAL POSSIBILITIES OF ORGANIZING PERSONALIZED LEARNING IN ARTIFICIAL INTELLIGENCE-BASED ENGLISH FOR SPECIFIC PURPOSES (ESP) TEACHING

Abstract

The integration of artificial intelligence (AI) into language education has revolutionized pedagogical practices, particularly in the domain of English for Specific Purposes (ESP). This article explores the pedagogical possibilities of organizing personalized learning through AI-driven systems in ESP teaching. By leveraging adaptive algorithms, natural language processing, machine learning, and intelligent tutoring systems, educators can tailor instructional content, feedback, and assessment to the unique needs, proficiency levels, professional contexts, and learning styles of individual learners. The study examines how AI facilitates real-time adaptation of materials, predictive analytics for learner progress, and immersive simulations that mirror authentic professional environments. Drawing on contemporary advancements in educational technology, the analysis highlights enhanced learner autonomy, improved motivation, and superior linguistic and communicative outcomes. Challenges such as data privacy, algorithmic bias, digital divides, and the irreplaceable role of human instructors are critically addressed. The article argues that AI-powered personalization represents a transformative shift in ESP pedagogy, offering scalable solutions for diverse global contexts while maintaining pedagogical depth and ethical integrity. Implications for curriculum design, teacher training, and institutional policy are discussed, underscoring the need for balanced human-AI collaboration in language education.