Unlocking the Potential: Attitudes of Tertiary Level EFL Learners Towards Using AI in Language Learning

In the current era of rapid change in which AI has become inevitable in foreign language education as in many aspects of life, this study, which aims to examine EFL learners’ attitudes towards AI and to analyse its future potential, was conducted with the participation of 772 English preparatory year students studying at A2, B1, and B2 levels in the schools of foreign languages of a state and a private (foundation) university in Türkiye. The data for the study were collected online through an attitude scale (MALL:AI) and an open-ended survey question. Quantitative results revealed that the participants had moderate attitudes towards the use of AI in EFL learning, with no clear tendency towards positive attitudes. While university type and gender were not found to be significant determinants of attitudes, engineering and natural sciences students showed more positive attitudes towards AI in EFL learning than those in the humanities and social sciences. In terms of proficiency level, A2 level participants reflected lower attitudes in the behavioural factor than B1 and B2 levels. Qualitatively, it was found that students had overwhelmingly positive perspectives on the use of AI, shared some negative approaches with reservations, and offered concrete suggestions for the integration of AI into ELT. With its intriguing findings, the present study sheds light on further studies and paves the way for educational administrators and EFL instructors to better make use of AI in language education.

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Publication Details

Journal
Participatory Educational Research
Published
2024-09-30
DOI
https://doi.org/10.17275/per.24.76.11.6
Citations
7
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
2.88
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article

Unlocking the Potential: Attitudes of Tertiary Level EFL Learners Towards Using AI in Language Learning

Murat Akbıyık, Hüsem Korkmaz
7 citations
Participatory Educational Research
Online Learning and Analytics
2.88
article

Unlocking the Potential: Attitudes of Tertiary Level EFL Learners Towards Using AI in Language Learning

Murat Akbıyık, Hüsem Korkmaz
article en
7 citations

Abstract

In the current era of rapid change in which AI has become inevitable in foreign language education as in many aspects of life, this study, which aims to examine EFL learners’ attitudes towards AI and to analyse its future potential, was conducted with the participation of 772 English preparatory year students studying at A2, B1, and B2 levels in the schools of foreign languages of a state and a private (foundation) university in Türkiye. The data for the study were collected online through an attitude scale (MALL:AI) and an open-ended survey question. Quantitative results revealed that the participants had moderate attitudes towards the use of AI in EFL learning, with no clear tendency towards positive attitudes. While university type and gender were not found to be significant determinants of attitudes, engineering and natural sciences students showed more positive attitudes towards AI in EFL learning than those in the humanities and social sciences. In terms of proficiency level, A2 level participants reflected lower attitudes in the behavioural factor than B1 and B2 levels. Qualitatively, it was found that students had overwhelmingly positive perspectives on the use of AI, shared some negative approaches with reservations, and offered concrete suggestions for the integration of AI into ELT. With its intriguing findings, the present study sheds light on further studies and paves the way for educational administrators and EFL instructors to better make use of AI in language education.

Participatory Educational ResearchVol. 11(6)
Kadir Has University (TR), Manisa Celal Bayar University (TR)
Openalex Percentile: Top 7%
Online Learning and Analytics
2.88
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Unlocking the Potential: Attitudes of Tertiary Level EFL Learners Towards Using AI in Language Learning — Murat Akbıyık, Hüsem Korkmaz · Participatory Educational Research (2024) | TGRS Research Map | TGRS