Integrating Artificial Intelligence in ESP Curriculum: A Bilingual Approach to English for Educational Technology

Artificial intelligence (AI) integration into language education has fundamentally changed English for Specific Purposes (ESP) training delivering adaptive learning, real-time feedback, and automated language assessment (AlTwijri Alghizzi, 2024; Sumarni et al., 2022). Especially in English for Educational Technology, AI systems can improve technical language competency and comprehension in bilingual ESP education. Though little study on AI's impact on multilingual learning environments, current studies mainly concentrate on monolingual AI-enhanced ESP education. Examining their impact on grammar accuracy, vocabulary learning, reading comprehension, and technical English communication, this paper looks at how well AI-powered tools fit a bilingual ESP program. The results show that student involvement and tailored learning results were much enhanced by artificial intelligence-driven learning analytics. Still, major issues include artificial intelligence bias, translation errors, and over-reliance on automated feedback. This study clarifies curriculum creation, AI tool choice, and pedagogical methodologies, as well as the benefits and constraints of artificial intelligence in bilingual ESP education. The findings imply that artificial intelligence should complement human education, guaranteeing contextually correct, ethical, and pedagogically sound integration rather than replacing human education. Long-term AI efficacy, developments in adaptive learning models, and ethical issues in AI-driven language instruction should all be investigated in next studies.

Authors

Publication Details

Journal
Journal of English Language Teaching Innovations and Materials (Jeltim)
Published
2025-05-08
DOI
https://doi.org/10.26418/jeltim.v7i1.91274
Citations
2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
3.39
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article

Integrating Artificial Intelligence in ESP Curriculum: A Bilingual Approach to English for Educational Technology

Luís Cardoso, Andi Asrifan, K. J. Vargheese
2 citations
Journal of English Language Teaching Innovations and Materials (Jeltim)
Online Learning and Analytics
3.39
article

Integrating Artificial Intelligence in ESP Curriculum: A Bilingual Approach to English for Educational Technology

Luís Cardoso, Andi Asrifan, K. J. Vargheese
article en
2 citations

Abstract

Artificial intelligence (AI) integration into language education has fundamentally changed English for Specific Purposes (ESP) training delivering adaptive learning, real-time feedback, and automated language assessment (AlTwijri Alghizzi, 2024; Sumarni et al., 2022). Especially in English for Educational Technology, AI systems can improve technical language competency and comprehension in bilingual ESP education. Though little study on AI's impact on multilingual learning environments, current studies mainly concentrate on monolingual AI-enhanced ESP education. Examining their impact on grammar accuracy, vocabulary learning, reading comprehension, and technical English communication, this paper looks at how well AI-powered tools fit a bilingual ESP program. The results show that student involvement and tailored learning results were much enhanced by artificial intelligence-driven learning analytics. Still, major issues include artificial intelligence bias, translation errors, and over-reliance on automated feedback. This study clarifies curriculum creation, AI tool choice, and pedagogical methodologies, as well as the benefits and constraints of artificial intelligence in bilingual ESP education. The findings imply that artificial intelligence should complement human education, guaranteeing contextually correct, ethical, and pedagogically sound integration rather than replacing human education. Long-term AI efficacy, developments in adaptive learning models, and ethical issues in AI-driven language instruction should all be investigated in next studies.

Journal of English Language Teaching Innovations and Materials (Jeltim)Vol. 7(1)
Openalex Percentile: Top 7%
Online Learning and Analytics
3.39
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