Exploring the Attitudes of English as a Foreign Language Learners Toward Collocational Learning Using Artificial Intelligence

This study investigates the attitudes EFL learners towards the usage of Artificial Intelligence (AI) in developing the knowledge of lexical collocations among EFL learners in Pakistan where traditional teaching methods often fato address collocational competence. Despite the significance of collocations for fluency, Pakistani learners struggle due to reliance on rote memorization, L1 interference, and limited authentic exposure. It aims to assess learner perceptions of AI tools in language education. Adopting a qualitative design, the study involved 30 BS English students divided into five groups comprising six students each. Focus group interviews highlighted AI’s benefits—24/7 accessibility, personalized practice, and error correction—but also identified challenges like cultural mismatches (e.g., "queue patiently" vs. local "wait quietly") and risks of overreliance. However, the study advocates for a balanced integration of AI with teacher guidance to address cultural relevance and meta-cognitive understanding. Practical implications include teacher training, localized AI tools, and policy investments in digital infrastructure. Limitations include sample size. This research contributes to technology-enhanced language learning (TELL) in understudied contexts, offering a model for AI adoption in EFL classrooms while cautioning against uncritical implementation.

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Journal
Social science review archives.
Published
2025-07-14
DOI
https://doi.org/10.70670/sra.v3i3.880
Primary Topic
Second Language Acquisition and Learning
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article
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article

Exploring the Attitudes of English as a Foreign Language Learners Toward Collocational Learning Using Artificial Intelligence

Muhammad Imran Shah, Aliza Shafiq
Social science review archives.
Second Language Acquisition and Learning
article

Exploring the Attitudes of English as a Foreign Language Learners Toward Collocational Learning Using Artificial Intelligence

Muhammad Imran Shah, Aliza Shafiq
article en

Abstract

This study investigates the attitudes EFL learners towards the usage of Artificial Intelligence (AI) in developing the knowledge of lexical collocations among EFL learners in Pakistan where traditional teaching methods often fato address collocational competence. Despite the significance of collocations for fluency, Pakistani learners struggle due to reliance on rote memorization, L1 interference, and limited authentic exposure. It aims to assess learner perceptions of AI tools in language education. Adopting a qualitative design, the study involved 30 BS English students divided into five groups comprising six students each. Focus group interviews highlighted AI’s benefits—24/7 accessibility, personalized practice, and error correction—but also identified challenges like cultural mismatches (e.g., "queue patiently" vs. local "wait quietly") and risks of overreliance. However, the study advocates for a balanced integration of AI with teacher guidance to address cultural relevance and meta-cognitive understanding. Practical implications include teacher training, localized AI tools, and policy investments in digital infrastructure. Limitations include sample size. This research contributes to technology-enhanced language learning (TELL) in understudied contexts, offering a model for AI adoption in EFL classrooms while cautioning against uncritical implementation.

Social science review archives.Vol. 3(3)
Government College University, Faisalabad (PK)
Openalex Percentile: Top 81%
Second Language Acquisition and Learning
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Exploring the Attitudes of English as a Foreign Language Learners Toward Collocational Learning Using Artificial Intelligence — Muhammad Imran Shah, Aliza Shafiq · Social science review archives. (2025) | TGRS Research Map | TGRS