Use of Artificial Intelligence for Pedagogical Purposes in Efl Classroom in Nepal
Year: 2025
Type: article
Abstract: The integration of Artificial Intelligence (AI) in English as a Foreign Language (EFL) classroom has emerged as a transformative approach to teaching and learning. This study aims to explore English teachers' perceptions, practices, and the pedagogical use of AI in EFL instruction in Nepal. This research employed a quantitative research design. A cross-sectional survey design was adopted to collect data from a representative sample of English teachers. The study findings reveal a growing yet moderate adoption of AI tools such as chatbots, virtual tutors, adaptive learning platforms, and automated feedback systems in ELT classrooms. These tools were found to enhance personalized learning, foster learner autonomy, and accommodate diverse learning strategies in EFL classroom. However, their utilization varies due to factors such as infrastructure limitations, insufficient training, and unequal access to resources. English teachers reported moderate engagement with AI for tasks like creating presentations, developing test items, and organizing instructional materials, reflecting both the potential and challenges of integrating AI into routine pedagogical practices. Findings highlight that AI-driven platforms like Grammarly, ChatGPT, and Duolingo offer innovative solutions for English language teaching, providing real-time feedback, improving writing skills, and gamifying learning experiences. Despite these advancements, challenges such as technical barriers, data reliability, and teacher preparedness persist. The study underscores the need for targeted professional development programs, enhanced institutional support, and equitable access to AI tools to maximize their impact on English language teaching.
Authors: BISHNU KUMAR KHADKA, DHURBA KUMAR SHAHI, DIPENDRA KUMAR KHATRI, YOUBARAJ POUDYAL
Institutions: Mid-West University, Tribhuvan University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6968345409
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