Cognitive approach for oil and gas translator training

Author

Rumayshi, Salwa

Source

al-Mutarjim

Issue

Vol. 20, Issue 1 (30 Jun. 2020), pp.211-226, 16 p.

Publisher

University of Oran 1 Ahmed Ben Bella laboratory Didactics of Translation and Multilingualism

Publication Date

2020-06-30

Country of Publication

Algeria

No. of Pages

16

Main Subjects

Languages & Comparative Literature
Literature

Topics

Abstract EN

Cognitive science offers fundamental keys for a better understanding of the translation procedures and processes through providing the concepts, strategies and methodologies that enable translators to enhance their competence, widen their knowledge, sharpen their skills and thus improve their performances.

The present paper aims to investigate how cognitive approach contributes in the translation process, more particularly in the oil and gas field.

Through analysing the translation of some extracts of oil and gas texts, we will try to answer the following questions: what competencies does a translator in the oil and gas field need? How can cognitive approach in conceptual and intertextual perspectives help the translator overcome the difficulties and challenges encountered in the oil and gas field and make the best decisions? What cognitive methods and strategies are to be incorporated into the oil and gas translator training?

American Psychological Association (APA)

Rumayshi, Salwa. 2020. Cognitive approach for oil and gas translator training. al-Mutarjim،Vol. 20, no. 1, pp.211-226.
https://search.emarefa.net/detail/BIM-1001003

Modern Language Association (MLA)

Rumayshi, Salwa. Cognitive approach for oil and gas translator training. al-Mutarjim Vol. 20, no. 1 (Jun. 2020), pp.211-226.
https://search.emarefa.net/detail/BIM-1001003

American Medical Association (AMA)

Rumayshi, Salwa. Cognitive approach for oil and gas translator training. al-Mutarjim. 2020. Vol. 20, no. 1, pp.211-226.
https://search.emarefa.net/detail/BIM-1001003

Data Type

Journal Articles

Language

English

Notes

-

Record ID

BIM-1001003