Shifting Roles: Employing AI-driven Translation Engines to Enhance the Writing Proficiency of EFL Learners

Abstract

The simulation of human intelligence processes by computer software and internet MT engines has become apparent in education recently. Neural MT engines manipulate artificial intelligence to produce comprehensive results in translation. Thus, the regular role of such MT engines is prominent in translation among languages. Differently, the present study shifts the regular role of neural MT engines from translation to developing writing proficiency among EFL learners. A sample of EFL learners at Qassim University used neural MT engines that manipulate artificial intelligence to develop their writing proficiency during the academic year 2024. EFL learners’ writings were evaluated through electronic proofreading software. Gains in writing skills like spelling, construction, concordance, and meaning are documented in the present study. The pre-post comparison of the writings of the study group had significant differences in favor of implementing artificial intelligence-based MT engines. The present study recommends implementing neural MT engines in writing classrooms to develop EFL learners’ writing proficiency.