COMMUNICATIVE COMPETENCE IN THE ERA OF ARTIFICIAL INTELLIGENCE: TOWARDS DIGITAL LANGUAGE EDUCATION

Abstract

The digital environment is increasingly influencing the development of communication skills. Interaction often takes place through platforms where human input is combined with algorithmic processing. In these circumstances, traditional models of communicative competence do not fully explain how students interpret, develop, and coordinate meaning. The purpose of this research is to identify and conceptualize the key components of digital communicative competence necessary for modern language education in the era of artificial intelligence. To achieve this goal, the study analyzes classical theories of communicative competence, the foundations of digital competence and literacy in the field of artificial intelligence. These sources were studied taking into account the changes introduced by initiatives on trilingual education and digital transformation in Kazakhstan. The research uses a theoretical and analytical approach based on the synthesis, comparison and interpretation of modern and classical research in the field of language education. The analysis revealed four interrelated components of digital communication competence: linguistic resources, digital information processing skills, intercultural mediation, and adaptability to technological advances. These components collectively describe how students interact with texts, messages, and communication tasks in an environment mediated by artificial intelligence. Communicative competence arises as a multi-layered structure formed by both language knowledge and digital influences. The results provide a conceptual framework for rethinking communicative competence in a technologically mediated educational context and highlight the importance of integrating digital technologies and artificial intelligence-related abilities into the training of foreign language teachers and curriculum development. The integration of digital technologies and artificial intelligence capabilities facilitates more accurate interpretation of machine-modified content and more effective participation in multilingual digital communication.