Artificial Intelligence in EFL/ESL Education: Transforming Language Learning and Teaching through Adaptive Technology and Ethical Innovation
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Abstract
Background and Aims: The rapid integration of artificial intelligence (AI) into English as a Foreign Language (EFL) and English as a Second Language (ESL) training has resulted in significant pedagogical advancements as well as challenging ethical and instructional challenges. AI-driven tools such as chatbots, automated assessments, adaptive learning systems, and speech recognition technologies are gradually changing language teaching and learning practices worldwide. This study aims to critically examine the pedagogical roles, benefits, and ethical implications of AI-assisted technology in EFL/ESL instruction, with an emphasis on personalization, linguistic diversity, teacher authority, and responsible application.
Methodology: This study systematically examines recent peer-reviewed literature based on computer-assisted language learning (CALL), second language acquisition (SLA), and sociocultural theory using a critical narrative review and conceptual synthesis technique. Instead of producing new empirical data, the research finds recurrent patterns, conceptual conflicts, and unresolved issues in AI-supported language instruction.
Results: The review claims that AI technologies enhance personalized learning, learner engagement, and feedback efficacy. However, there are significant problems with the digital divide, teacher preparedness, data privacy, algorithmic bias, and language standards. The study's response to these issues is a Human-Centered AI–EFL Pedagogy Model, which sees AI as a mediating instructional agent operating under continuous human supervision and ethical regulation.
Conclusion: The results imply that the instructional effectiveness of AI in EFL/ESL contexts depends more on pedagogically informed and morally grounded integration than on technological competence. This study offers a theoretically grounded and policy-relevant viewpoint that highlights linguistic diversity, socio-cultural sensitivity, and continued teacher authority in AI-enhanced language instruction by framing AI as a supportive rather than substitutive force.
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