Artificial Intelligence and Smart Pedagogy: Machine Learning in Digital Media for Language Education
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.
Authors
- Basim Mir
- Mahnoor Ghani Sheikh
- Ayesha Rashid
- Mudasar Jahan
- Nishat Zafar
- Tabassum lqbal
- Saima Asim
Institutions
- University of Lahore (PK)
- Sir Syed University of Engineering and Technology (PK)
- University of Gujrat (PK)
Publication Details
- Journal
- Metallurgical and Materials Engineering
- Published
- 2025-02-13
- DOI
- https://doi.org/10.63278/1324
- Citations
- 1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 1.69