Artificial Intelligence and Smart Pedagogy: Machine Learning in Digital Media for Language Education

Authors

  • Ayesha Rashid Information Technology, University of Gujrat, Pakistan
  • Nishat Zafar Associate lecturer, Department of Education, University of Gujrat, Pakistan
  • Tabassum lqbal Lecturer, Department of English, University of Gujrat, Pakistan
  • Basim Mir Assistant Professor, University of Lahore, Pakistan
  • Saima Asim Lecturer, Sirsyed Case Institute of Technology, Islamabad, Pakistan
  • Mahnoor Ghani Sheikh Department of English, University of Gujrat, Pakistan
  • Mudasar Jahan Associate Lecturer in English, University of Gujrat, Pakistan

DOI:

https://doi.org/10.63278/1324

Keywords:

Artificial Intelligence, Language Learning, Teacher Education, Cognitive-Media-Machine Framework, Personalized Learning.

Abstract

This qualitative study explores the experiences, perceptions, and pedagogical practices of language teachers integrating AI-powered language learning tools into their classrooms, aiming to examine pedagogical enhancements and challenges, and their impact on teacher-student interactions and student learning outcomes. The study addresses a significant gap in the literature by investigating the complexities of AI-powered language learning tool integration in real-world classrooms. Utilizing thematic analysis and the Cognitive-Media-Machine Framework as its theoretical foundation, which provides a holistic understanding of the interplay between cognitive processes, media, and machine learning algorithms, the study collects data from 100 language teachers using AI-powered tools in different universities through interview and observation protocols. The findings reveal three nested themes: Pedagogical Enhancements, Technological Challenges, and Student-Centered Learning, highlighting the potential of AI-powered language learning tools to provide personalized feedback and assessment, while underscoring the need for addressing technological challenges and promoting student-centered learning experiences. The study contributes to the existing literature by providing insights into the practical applications and limitations of AI-powered language learning tools, informing language education policy, practice, and research, and highlighting the need for ongoing professional development, technical support, and pedagogical innovation. The research employs a qualitative approach, utilizing thematic analysis to identify emerging themes, and the Cognitive-Media-Machine Framework, which encompasses three key aspects: cognitive processes, media, and machine learning algorithms. The study's key findings emphasize the potential of AI-powered language learning tools to enhance language learning outcomes, while also posing significant technological challenges, and highlighting the importance of promoting student-centered learning experiences. Ultimately, the study addresses a significant gap in the literature, providing valuable insights for language education stakeholders.

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Published

2025-02-13

How to Cite

Ayesha Rashid, Nishat Zafar, Tabassum lqbal, Basim Mir, Saima Asim, Mahnoor Ghani Sheikh, and Mudasar Jahan. 2025. “Artificial Intelligence and Smart Pedagogy: Machine Learning in Digital Media for Language Education ”. Metallurgical and Materials Engineering 31 (2):7-22. https://doi.org/10.63278/1324.

Issue

Vol. 31 No. 2 (2025)

Section

Research

License

Copyright (c) 2025 Ayesha Rashid, Nishat Zafar, Tabassum lqbal, Basim Mir, Saima Asim, Mahnoor Ghani Sheikh, Mudasar Jahan

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