MECHANISMS FOR PERSONALIZING TESTS IN TEACHING MEDICAL ENGLISH USING ARTIFICIAL INTELLIGENCE

Abstract

The rapid development of artificial intelligence (AI) has transformed modern education, particularly in the field of English for Specific Purposes (ESP). Medical English teaching requires not only linguistic competence but also mastery of professional terminology, clinical communication, and academic writing. Traditional testing methods often fail to address the diverse linguistic backgrounds, professional goals, and cognitive abilities of medical students. AI technologies offer innovative mechanisms for creating adaptive, personalized, and data-driven assessments that improve learning outcomes and student motivation.Personalized AI-based testing systems can analyze learner performance, identify strengths and weaknesses, and automatically generate customized tasks. In medical English education, such mechanisms are especially valuable because students must develop highly specialized communicative competencies for real clinical environments.