ARTIFICIAL INTELLIGENCE IN FOREIGN LANGUAGE TEACHING AND GENERAL EDUCATION: A COMPARATIVE ANALYSIS OF OPPORTUNITIES, CHALLENGES, AND HYBRID MODELS
Keywords:
Artificial intelligence, foreign language teaching, adaptive learning, hybrid model, cultural relevance, pedagogical design, SPEAK-BOT.Abstract
This article provides a comparative analysis of the integration of artificial intelligence (AI) in foreign language teaching and general education. Based on a critical synthesis of four recent studies by Rizakhojayeva (2026), Juraev (2026), Rsaliyev (2026), and Sharipova & Rsaliyev (2026), the paper examines the adaptive potential of AI, the risks of algorithmic bias, cultural irrelevance, and the loss of human interaction. The study highlights empirical evidence from China, Iran, Indonesia, Russia, and Kazakhstan. A three-level hybrid model for the distribution of functions between teachers and AI is proposed (technical-diagnostic, interpretative-adaptive, and motivational-reflective levels). The article concludes that the effectiveness of AI in education is determined not by technological power but by the quality of pedagogical design and the preservation of human-centered values.
References
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