Many translation courses are devoted to specialized subject fields, such as legal, medical, or economic translation. Trainers can extract a corpus of translations pertaining to a particular subject field and examine these to determine whether a problem is specific to a particular source text or is a difficulty that also manifests itself in other texts deal-
ing with a related subject. For example, when translating a text in the subject field of law, students might have difficulty constructing the proper syntax because one particular source text is awkwardly worded and is negatively influencing their target-language production, or they may be having difficulty coming to grips with legal syntax in general.
Corpora that span multiple subject fields can be extracted to investigate, for instance, whether the problems encountered by a group of students in their French technical-translation course are similar to or different from the problems they are having in their French economic translation course. A trainer can investigate whether a student is having a problem that results from a poor knowledge of grammar (and thus manifests itself regardless of the subject field) or having difficulty caused by a lack of knowledge of the vocabulary or syntax of a particular specialized language (a problem that is not in evidence when translating texts in a different subject field).
Cross-linguistic/same-subject-field corpora can also be extracted to examine the impact of source-language interference. For example, a student may be taking two different courses in economic translation: one from French and one from Spanish. A comparison of the two sets of translations may reveal that a student is having different types of problems when translating out of French than when translating out of Spanish, in which case it may be necessary to focus on source-language interference, or it may turn out that a student is having similar problems regardless of the source language (e.g., perhaps the student has not grasped the concept of "register"), in which case it may be necessary to tackle the issue in a non-source-language-related way.
Finally, longitudinal studies can be carried out to chart the progress of individual students or groups of students, and these can be performed over the course of a semester, a year, or even an entire degree. Using such a corpus, a trainer (or even a student) can see which problems appear to have been resolved and which are still causing difficulties.
Another type of longitudinal study could be conducted if a trainer decides to try a new teaching method from one year to the next. If the trainer has used the same source text (or even different texts that pose similar translation difficulties) with more than one group of students, it may be interesting for him or her to compare the translations done by a class who were taught using the "old" method with those of a class who were taught using the "new" method. While a comparison of this sort would not be enough to enable the trainer to make definitive claims about the usefulness of one teaching method over another, it may nevertheless reveal some interesting points worthy of further investigation.
3. Reinforcing basic translation skills
The examples discussed above provide an indication of new types of translation-related investigations that become possible through the use of technology. At the same time, however, it should be emphasized that time spent teaching technology does not necessarily take away from time spent on other translation skills. In fact, if technology is properly integrated into the translation classroom, it not only allows the students to develop new skills, it also leads to an intensification of the basic translation curriculum. As de Schaetzen (1997, 18) and L'Homme (1999b, 118) point out, students who use technology to produce term records, find solutions in parallel documentation, or produce actual translations are reinforcing these basic translation skills as well as developing good and realistic working practices that can later be applied in the workplace.
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