SCIENTIFIC KNOWLEDGE STRUCTURES: PROBLEMATISING AI-POWERED TRANSLATION TOOLS IN EFL ACADEMIC WRITING

Uswatun Qoyyimah; Debbie Bargallie

doi:10.24071/llt.v28i2.9833

SCIENTIFIC KNOWLEDGE STRUCTURES: PROBLEMATISING AI-POWERED TRANSLATION TOOLS IN EFL ACADEMIC WRITING

Uswatun Qoyyimah^(1*), Debbie Bargallie⁽²⁾,

(1) Universitas Pesantren Tinggi Darul Ulum, Indonesia
(2) Griffith University, Australia
(*) Corresponding Author

Abstract

Artificial intelligence (AI), particularly machine translation (MT), is transforming English language education, especially for English as a Foreign Language (EFL) learners. While research has explored this shift, uncertainties remain about MT’s impact on language development in academic writing. This paper examines pedagogical practices in a teacher education program in Indonesia through the lens of Bernstein’s theory of knowledge structures. It draws on reflective research conducted by Author 1, using data generated from fieldnotes of EFL academic writing sessions in which nine pre-service teachers actively participated as learners. The analysis reveals that while MT supports various language tasks, its unregulated use may hinder students’ development of foundational skills such as sentence construction and paragraph organisation. Teacher intervention proved crucial in mitigating these challenges and fostering more effective academic writing. The findings emphasize the dual role of MT as both a support tool and a potential barrier, and offer empirical insights into how educators can balance AI use with essential language instruction. This study highlights practical implications for curriculum design and policy, reinforcing the indispensable role of teachers in integrating AI tools without compromising core language competencies.

Keywords

English as a foreign language; knowledge structure; machine translation; teaching writing

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DOI: https://doi.org/10.24071/llt.v28i2.9833