Artificial Intelligence and English Communication in Multidisciplinary Education
DOI:
https://doi.org/10.67313/slijms.2026.75Keywords:
Artificial Intelligence, English Communication, Multidisciplinary Education, English Language Teaching, Generative AI, Academic Communication, AI Literacy, Professional Communication, Digital Pedagogy.Abstract
Artificial Intelligence (AI) has emerged as an influential force in contemporary higher education, transforming how students acquire knowledge, develop language proficiency, engage in academic discourse, and communicate across disciplinary boundaries. English communication, traditionally approached as a language-specific competency, has increasingly become an essential interdisciplinary skill connecting engineering, commerce, management, science, technology, humanities, and professional education. This paper critically examines the role of AI in strengthening English communication within multidisciplinary educational environments, focusing on personalized language learning, academic writing, oral communication, collaborative learning, disciplinary literacy, assessment, and professional readiness. Employing an integrative literature review and conceptual analytical approach, the study synthesizes established research on AI in education alongside recent scholarly contributions concerning AI-supported English language teaching. It identifies opportunities for individualized feedback, interactive communication, differentiated instruction, and discipline-specific language practice while examining challenges involving algorithmic bias, academic integrity, digital inequality, linguistic standardization, and technological dependency. As its principal conceptual contribution, the paper proposes the AI-MEC Framework (Artificial Intelligence–Mediated English Communication), integrating linguistic competence, disciplinary contextualization, AI literacy, collaborative communication, ethical engagement, and independent performance. The study argues that AI can strengthen communicative competence across disciplinary contexts when implemented through human-centred pedagogy, critical assessment, and active teacher mediation. It concludes that the educational value of AI should be measured not merely through improved AI-assisted outputs but through students' demonstrated ability to communicate independently, critically, and effectively in authentic academic and professional situations.
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