Computer-Assisted Teaching of Translation Methods

Abstract

This paper introduces an intelligent tutoring system designed to help student translators learn to appreciate the distinction between literal translation and liberal translation, an important and forever debated point in the literature of translation, and some other methods of translation lying between these two extremes. We identify four prominent kinds of translation methods commonly discussed in the translation literature—word‐for‐word translation, literal translation, semantic translation, and communicative translation—and attempt to extract computationally expedient definitions for them from two researchers' discussions on them. We then apply these computational definitions to the preparation of our translation corpus to be used in the intelligent tutoring system. In the basic working mode the system offers a source sentence for the student to translate, compares it with the inbuilt versions, and decides on the most likely method of translation used through a translation unit matching algorithm. The student can guess where on the literal and liberal continuum their translation stands by viewing this verdict and by comparing their translation with other versions for the same sentence. In the advanced working mode, the student learns some translation techniques such as the contrastive analysis approach to teaching translation, while appreciating the working of translation methods in relation to these techniques.