Investigating EFL Students' Attitudes Towards AI-Powered Tools in English Language Learning

Artificial Intelligence (AI) is changing how students learn English as a Foreign Language (EFL). This study examines EFL students' attitudes towards the use of AI-powered tools as well as the benefits and challenges of these tools, such as ChatGPT, Grammarly, Duolingo Max, Gemini, ELSA Speak, Write and Improve, and YouChat, in English learning. Using Activity Theory, it explores students' attitudes, usage, and perceptions through surveys of 479 Vietnamese university students and semistructured interviews with 10 participants. Findings show that students often used AI-powered tools, especially ChatGPT, for personalized learning. Students also expressed their positive attitudes towards using AI-powered tools in English language learning. They reported improved grammar, vocabulary, pronunciation, writing skills, motivation, and autonomy. However, concerns include over-reliance on AI, reduced critical thinking, ethical issues, and occasional inaccuracies. The study highlights AI's potential to make language learning more accessible and efficient. However, it emphasizes the need for balance, ensuring ethical considerations, critical thinking, and human interaction remain key. The findings provide insights for educators, policymakers, and AI developers regarding responsible AI use.

Authors

Institutions

Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/iciet66371.2025.11046282
Citations
1
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
8.93
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating EFL Students' Attitudes Towards AI-Powered Tools in English Language Learning

Vi Thi Tuong Pham, Anh Tuan Pham
1 citations
Technology-Enhanced Education Studies
8.93
article

Investigating EFL Students' Attitudes Towards AI-Powered Tools in English Language Learning

Vi Thi Tuong Pham, Anh Tuan Pham
article en
1 citations

Abstract

Artificial Intelligence (AI) is changing how students learn English as a Foreign Language (EFL). This study examines EFL students' attitudes towards the use of AI-powered tools as well as the benefits and challenges of these tools, such as ChatGPT, Grammarly, Duolingo Max, Gemini, ELSA Speak, Write and Improve, and YouChat, in English learning. Using Activity Theory, it explores students' attitudes, usage, and perceptions through surveys of 479 Vietnamese university students and semistructured interviews with 10 participants. Findings show that students often used AI-powered tools, especially ChatGPT, for personalized learning. Students also expressed their positive attitudes towards using AI-powered tools in English language learning. They reported improved grammar, vocabulary, pronunciation, writing skills, motivation, and autonomy. However, concerns include over-reliance on AI, reduced critical thinking, ethical issues, and occasional inaccuracies. The study highlights AI's potential to make language learning more accessible and efficient. However, it emphasizes the need for balance, ensuring ethical considerations, critical thinking, and human interaction remain key. The findings provide insights for educators, policymakers, and AI developers regarding responsible AI use.

FPT University (VN), Can Tho University (VN)
Quality Education
Openalex Percentile: Top 4%
Technology-Enhanced Education Studies
8.93
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Investigating EFL Students' Attitudes Towards AI-Powered Tools in English Language Learning — Vi Thi Tuong Pham, Anh Tuan Pham · (2025) | TGRS Research Map | TGRS