Predictors of Pre-Service EFL Teachers’ Predisposition Towards AI Adoption in Language Teaching

The increasing integration of artificial intelligence (AI) in education is creating new challenges and posing new requirements for English language teacher training, especially since AI applications provide numerous opportunities for language acquisition and practice. This study aimed to explore the interplay between three factors—the actual learning of AI, behavioural intention to use AI, and perceived self-efficacy—in order to determine their effect on the readiness of future teachers to implement AI technologies in their prospective pedagogical practices. In total, 56 pre-service English language teachers in Bulgaria took part in an online survey, revealing that the actual learning of AI was a strong determinant of their behavioural intention and perceived self-efficacy to engage with AI. Furthermore, it was also established that the student teachers’ knowledge of AI and competence in delivering AI-supported lessons were strong predictors of their behavioural disposition to integrate AI in their L2 classrooms. The results indicate the necessity of updating teacher training curricula so that consistent AI literacy in future foreign language teachers is fostered; a step forward that has to be supported by policymakers, university programme designers, and teacher training providers.

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Publication Details

Journal
Education Sciences
Published
2025-08-26
DOI
https://doi.org/10.3390/educsci15091112
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

Predictors of Pre-Service EFL Teachers’ Predisposition Towards AI Adoption in Language Teaching

Tsvetelina Harakchiyska
1 citations
Education Sciences
Online Learning and Analytics
1.69
article

Predictors of Pre-Service EFL Teachers’ Predisposition Towards AI Adoption in Language Teaching

Tsvetelina Harakchiyska
article en
1 citations

Abstract

The increasing integration of artificial intelligence (AI) in education is creating new challenges and posing new requirements for English language teacher training, especially since AI applications provide numerous opportunities for language acquisition and practice. This study aimed to explore the interplay between three factors—the actual learning of AI, behavioural intention to use AI, and perceived self-efficacy—in order to determine their effect on the readiness of future teachers to implement AI technologies in their prospective pedagogical practices. In total, 56 pre-service English language teachers in Bulgaria took part in an online survey, revealing that the actual learning of AI was a strong determinant of their behavioural intention and perceived self-efficacy to engage with AI. Furthermore, it was also established that the student teachers’ knowledge of AI and competence in delivering AI-supported lessons were strong predictors of their behavioural disposition to integrate AI in their L2 classrooms. The results indicate the necessity of updating teacher training curricula so that consistent AI literacy in future foreign language teachers is fostered; a step forward that has to be supported by policymakers, university programme designers, and teacher training providers.

Education SciencesVol. 15(9)
Angel Kanchev University of Ruse (BG)
Openalex Percentile: Top 11%
Online Learning and Analytics
1.69
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Predictors of Pre-Service EFL Teachers’ Predisposition Towards AI Adoption in Language Teaching — Tsvetelina Harakchiyska · Education Sciences (2025) | TGRS Research Map | TGRS