Teaching Arabic Machine Translation to EFL Student Translators
A Case Study of Omani Translation Undergraduates
Bibliographic Data
| ID | 21830564 |
|---|---|
| Authors | Yasser Muhammad Naguib Sabtan (0000-0002-4389-285X, Al-Azhar University, corresponding author) |
| Year | 2020 |
| Volume | 10 |
| Issue | 2 |
| Pages | 184 |
| Publication date | 2020-02-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of English Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 1923-869X • E-ISSN: 1923-8703 |
| Publisher | Canadian Center of Science and Education (PUBLISHER) |
| DOI | 10.5539/ijel.v10n2p184 |
| OpenAlex | W3004672535 |
| Language | EN |
| References cited | 1 |
The present paper describes a machine translation (MT) course taught to undergraduate students in the Department of English Language and Literature at Dhofar University in Oman. The course is one of the major requirements for BA in Translation. Fifteen EFL translation students who were in their third year of study were enrolled in the course. The author presents both the theoretical and practical parts of the course. In the theoretical part, the topics covered in the course are outlined. As for the practical part, it focuses on the translation students’ post-editing of online MT output. This is beneficial to the students as free online MT systems can potentially be used as a means for improving student translators’ training and EFL learning. This is achieved through subjecting MT output to analysis or post-editing by the students so that they can focus on the differences between the source and target languages. With this goal in mind, assignments were given to the students to post-edit the Arabic and English MT output of three free online MT systems (Systran, Babylon and Google Translate), discuss the linguistic problems that they spot for each system and choose the one that has the fewest number of errors. The results show that the students, with varying degrees of success, have managed to identify some linguistic errors with the MT output for each MT system and thus produced a better human translation. The paper concludes that there is a need to incorporate MT courses in translation departments in the Arab world, as integrating technology into translation curricula will have great effect on student translators’ training for their future career as professional translators
Arabic · English language · Linguistics · Machine translation · Mathematics education · Natural language processing · Translation studies · Computer Science · linguistics and terminology studies · Natural Language Processing Techniques · Psychology · Translation Studies and Practices · Artificial Intelligence
| Highly cited | No |
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