Paper Title

Reviewing Contemporary Trends And Future Directions In English Language Teaching In The Transforming Age Of Artificial Intelligence

Article Identifiers

Registration ID: IJNRD_225133

Published ID: IJNRD2407186

DOI: Click Here to Get

Authors

Sibam Saha , Mukul Mahato

Keywords

: Artificial intelligence, Language learning, English language, Language model, Education

Abstract

The connective aspect of English language has been looked back at over and over an in global and multicultural background which has sparked the need for learning English language. The stiffness in language learning advocated by the traditional approach was expanded by the smartphone and internet access. Of late, the emergence of Artificial Intelligence or AI, especially in education, has further facilitated language learning with its multitude of teaching-learning models branched as ITS, TTS, ASR and many more, combined with popular voice assistants like Siri, Alexa and Google Assistant to provide opportunities for almost native English Language grasp, allowing flexible learning. Language models produce responses resembling human-generated content in a manner, which mirrors natural conversations using extensive textual data on which it is trained to engage with users. The models are designed in a manner, to provide optimum result by taking care of four intrinsic linguistic elements, i.e., reading, writing, listening and speaking, allowing users to advance at their own pace based on their proficiency level. The educators and educational institutions could be benefitted by this fast expanding technology since it provides time-saving and effortless student assessment with desired accuracy. Although, most of the nods go in favour of the trained machines, this has also raised concerns about unemployment and the lack of human depth when it comes to linguistic nuances as Noam Chomsky addresses it as “high-tech plagiarism” (Stewart, 2023, para. 2). Despite challenges, there is encouragement for further exploration and engagement of AI in language learning. This review takes a broad look at the ongoing and upcoming reforms and structural changes in motion with the extensive use of AI in the field of English language learning. This review specially takes note of the difference of learning between the old and new methods and tries judging them accordingly under the light of AI.

How To Cite (APA)

Sibam Saha & Mukul Mahato (July-2024). Reviewing Contemporary Trends And Future Directions In English Language Teaching In The Transforming Age Of Artificial Intelligence. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), b829-b836. https://ijnrd.org/papers/IJNRD2407186.pdf

Issue

Volume 9 Issue 7, July-2024

Pages : b829-b836

Other Publication Details

Paper Reg. ID: IJNRD_225133

Published Paper Id: IJNRD2407186

Downloads: 000121986

Research Area: Arts

Country: Howrah, West Bengal, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2407186.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407186

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

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