Veuillez utiliser cette adresse pour citer ce document :
http://dspace.univ-tiaret.dz:80/handle/123456789/14968
Titre: | Improving English as Foreign Language Students’ Translation Quality Using Artificial Intelligence |
Auteur(s): | DZIRI, Khalida HASSANI, Mohamed Fethi |
Mots-clés: | AI translation EFL students human translation student preference |
Date de publication: | jui-2024 |
Editeur: | ibn khaldoun university-Tiaret |
Résumé: | This research investigates the use of artificial intelligence (AI) to enhance the translation quality of EFL students, focusing on third-year bachelor English language students at Tiaret Ibn Khaldoun University. The primary aim of this research is to evaluate whether AI-generated translations can match or surpass the quality of human translations in terms of eloquence and clarity. The significance of this study lies in its potential to inform educational strategies and tools that can support EFL students in improving their translation skills. To achieve this, a mixed method approach was employed combining quantitative and qualitative data analysis. A quantitative questionnaire completed by 74 participants and a qualitative semi structured interview with 4 teachers of English in the same department. The findings revealed a slight preference for human translations that sounded more natural. However, AI translations possessed strengths in a formal tone, technical terms, and complex sentence structures. Confirming with the interviewed teachers, the study suggests that both AI and human translations contribute to improve students’ translation quality based on the preference of the students. Considering these findings, it is recommended that both AI and human translation tools should be adopted in the English language department to enhance the students’ translation skills, and translation quality. |
URI/URL: | http://dspace.univ-tiaret.dz:80/handle/123456789/14968 |
Collection(s) : | Master |
Fichier(s) constituant ce document :
Fichier | Description | Taille | Format | |
---|---|---|---|---|
TH.M.ENG.2024.64.pdf | 2,67 MB | Adobe PDF | Voir/Ouvrir |
Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.