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Incorporation of Artificial Intelligence in English Language Teaching And Learning

Karnam Nanditha Nanditha

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Paper Contents

Abstract

The integration of artificial intelligence (AI) into English language teaching and learning has transformed traditional pedagogical approaches, enabling more personalized, adaptive, and efficient instruction. AI-powered tools, such as language-learning applications, chatbots, and virtual tutors, facilitate immersive and interactive experiences that cater to diverse learner needs. These tools employ advanced natural language processing (NLP) techniques to provide real-time feedback on grammar, vocabulary, and pronunciation, enhancing language proficiency. Additionally, AI-driven analytics enable educators to monitor student progress, identify learning gaps, and customize lesson plans. The incorporation of AI not only democratizes access to high-quality language instruction but also supports learners in overcoming challenges related to time, resources, and geographic constraints.However, the integration of AI in English language education poses significant challenges that must be addressed to maximize its potential. Concerns about data privacy, algorithmic bias, and the digital divide can limit equitable access to AI-powered learning tools. Furthermore, the human element of language teaching essential for fostering cultural understanding and communication skills risks being overshadowed by technology. This paper explores the opportunities and limitations of incorporating AI into English language teaching and learning, proposing strategies for creating a balanced and inclusive approach. By leveraging AI responsibly, educators can enhance language instruction while maintaining the critical role of human interaction in language acquisition.Keywords: English Language learning, Significance of English, Global Scenario, Artificial Intelligence its advantages

Copyright

Copyright © 2025 Karnam Nanditha. This is an open access article distributed under the Creative Commons Attribution License.

Paper Details
Paper ID: IJPREMS50100032024
ISSN: 2321-9653
Publisher: ijprems
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