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CDELT Occasional Papers in the Development of English Education
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Emara, E. (2024). Using AI Tools to Enhance Translation Skills among Basic Education English Major Students. CDELT Occasional Papers in the Development of English Education, 86(1), 339-380. doi: 10.21608/opde.2024.362829
Eman Abd El-Hafeaz Mohamad Emara. "Using AI Tools to Enhance Translation Skills among Basic Education English Major Students". CDELT Occasional Papers in the Development of English Education, 86, 1, 2024, 339-380. doi: 10.21608/opde.2024.362829
Emara, E. (2024). 'Using AI Tools to Enhance Translation Skills among Basic Education English Major Students', CDELT Occasional Papers in the Development of English Education, 86(1), pp. 339-380. doi: 10.21608/opde.2024.362829
Emara, E. Using AI Tools to Enhance Translation Skills among Basic Education English Major Students. CDELT Occasional Papers in the Development of English Education, 2024; 86(1): 339-380. doi: 10.21608/opde.2024.362829

Using AI Tools to Enhance Translation Skills among Basic Education English Major Students

Article 13, Volume 86, Issue 1, April 2024, Page 339-380  XML PDF (792.13 K)
Document Type: Original Article
DOI: 10.21608/opde.2024.362829
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Author
Eman Abd El-Hafeaz Mohamad Emara
Lecturer of Curriculum and Instruction (TEFL), Faculty of Education, Damietta University
Abstract
The current study aimed to investigate the effect of using some artificial intelligence tools on developing some translation skills for fourth-year Basic Education English major students, Faculty of Education, Damietta University. A quasi-experimental design was employed. Some translation skills were determined using a checklist that was approved by a jury of EFL specialists. The researcher prepared and administered a translation skills test and a translation rubric. Participants were randomly selected and divided into three groups (n = 62) in the academic year 2022-2023. The first experimental group (n = 21) received instruction through Neural Machine Translation (NMT) tools such as Google Translate and Reverso. The second experimental group (n = 20) received instruction through Large Language Models (LLMs); ChatGPT, and QuillBot. The third experimental group (n = 21) received instruction through the integration of both tools. A pre-posttest was administered to the three groups to assess certain translation skills. Each experimental group was taught separately via the intended intervention. Post-implementation of the pre-posttest was administered at the end of the intervention. Results demonstrated the effectiveness of NMT and LLMs in enhancing the translation skills of the participants. All three groups showed improvements in their translation skills. The third experimental group had the highest scores, followed by the second group, and then the first group.
Keywords
Neural Machine Translation (NMT); Large Language Models (LLMs); Translation Skills; Basic Education English Major Students
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