Redefining Classroom Dynamics: AI Tools and the Future of English Language Pedagogy
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.11.13Keywords:
Artificial Intelligence, English Language Teaching, Language Acquisition, Pedagogical Innovation, Mixed-Methods Research, Digital Innovations, ChatGPT, Teachers' Perceptions, Technology in EducationDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This study looks at the transformative impact of artificial intelligence (AI) on English language training, specifically how AI-powered tools and approaches improve both educational outcomes and teaching strategies. The major goal is to assess the impact of AI on language acquisition and develop personalised teaching strategies for instructors and learners. A mixed-methods strategy was used to achieve this goal. During the quantitative phase, students from various colleges were given questionnaires with Likert scales to judge the effectiveness of AI technology in instructional procedures. Additionally, semi-structured interviews were conducted with educators who have actively used AI tools in their practices, allowing for the identification of both advantages and emerging issues. The findings show significant gains in the efficiency of English language acquisition, particularly in grammar understanding and vocabulary enhancement, which can be attributed to the ability to tailor learning situations. However, there are still issues, such as not being able to access the data, teachers being unprepared, and concerns about data privacy and discrimination. This study presents a paradigm for incorporating AI into English Language Teaching (ELT), with an emphasis on access, teacher training, ethical norms, and blended learning approaches to maximise the benefits of AI. The study emphasises the importance of professional teacher training and ethical norms in improving AI’s effectiveness and sustainability in English Language Teaching (ELT). The methodology and review findings aim to enable educators, developers, and policymakers in creating an AI-enhanced learning environment that meets educational goals while resolving current limitations.Abstract
How to Cite
Downloads
Similar Articles
- Mayur Vyas, Piyush Mehta, The sentimental and financial journey of women navigating e-commerce , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- K. Gokulkannan, M. Parthiban, Jayanthi S, Manoj Kumar T, Cost effective cloud-based data storage scheme with enhanced privacy preserving principles , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Chaitanya A. Kulkarni, Sayali Wadhokar, Om C. Wadhokar, Medhavi Joshi, Tushar Palekar, The intersection of cervical cancer treatment and physiotherapy: Current insights and future directions , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- P. Rajkumar, B. Vijay Bhaskar, Assessing the impact of indoor air pollution on respiratory health: A survey of home residents in rural area , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Megha Joshi, Bhaskar Pandya, Feminist Narratology and Gendered Reimagining of the Mahabharata in Kane’s work Karna’s Wife: The Outcast’s Queen , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Nitin J. Wange, Sachin V. Chaudhari, Koteswararao Seelam, S. Koteswari, T. Ravichandran, Balamurugan Manivannan, Algorithmic material selection for wearable medical devices a genetic algorithm-based framework with multiscale modeling , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- S. Hemalatha, N. Vanjulavalli, K. Sujith, R. Surendiran, Effective gorilla troops optimization-based hierarchical clustering with HOP field neural network for intrusion detection , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- A. Basheer Ahamed, M. Mohamed Surputheen, M. Rajakumar, Quantitative transfer learning- based students sports interest prediction using deep spectral multi-perceptron neural network , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Deepesh Bhardwaj, Niyati Chaudhary, Blueprints of Green: Determining Key Determinants of Sustainable Real Estate Projects in Delhi NCR , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Shaik Khaleel Ahamed, Neerav Nishant, Ayyakkannu Selvaraj, Nisarg Gandhewar, Srithar A, K.K.Baseer, Investigating privacy-preserving machine learning for healthcare data sharing through federated learning , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 20 21 22 23 24 25 26 27 28 29 > >>
You may also start an advanced similarity search for this article.

