ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN EDUCATION: ENHANCING ENGLISH LANGUAGE LEARNING AND TEACHING
DOI:
https://doi.org/10.65164/8p4g7291Keywords:
artificial intelligence in education, English language learning, EFL, adaptive learning systems, automated writing evaluation, NLP, CEFR progression, intelligent tutoring, foreign language anxiety, blended learning.Abstract
The accelerating integration of artificial intelligence (AI) into educational ecosystems has generated substantial scholarly and policy interest in its capacity to transform English language learning (ELL) and teaching (ELT). This paper provides a comprehensive examination of how five principal categories of AI technology — generative language models, natural language processing (NLP)-based speech recognition tools, adaptive intelligent tutoring systems (ITS), automated writing evaluation (AWE) engines, and learner sentiment analytics — can be systematically deployed to personalise instruction, reduce foreign language anxiety, and extend high-quality language exposure beyond the temporal and spatial confines of the conventional classroom. A two-semester quasi-experimental study involving 280 university-level EFL learners at a Uzbekistani higher education institution compared CEFR level advancement rates between a control group (traditional instruction) and an experimental group (AI-augmented blended instruction). Results indicate that AI-augmented learners demonstrated significantly higher CEFR progression rates across all five assessed skill areas — listening, reading, writing, speaking, and overall proficiency — with gains ranging from 34 to 54 percentage points (mean gain: 41.4 pp; all p < 0.001). The paper concludes by advancing a contextually grounded, five-pillar AI integration framework adaptable to emerging-economy EFL enviro
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