Integrating technology into the translation curriculum can have an impact on the way in which translation itself is taught. For example, a number of changes in teaching have been brought about by the fact that data are available in electronic form. Technologies such as optical character recognition and voice recognition can be used to convert data into electronic form, which makes it easier to share resources, such as corpora and translations, among students as well as between students and trainers. In a similar vein, the possibility of networking has also increased the shareability of data . For example, some types of technology, such as terminology-management systems and translation memories, can be networked, which facilitates the sharing of glossaries or translations.
DeCesaris (1996, 264) notes how translation memories can be used as a self-learning resource to provide students with immediate access to models that they know are correct. She goes on to explain that while the idea of providing students with models is not new, the point is that students are often given a single model for specific translations, which perpetuates the view that there is only one correct translation for a given text. A translation memory with fuzzy matching capability can make it easy for trainers to provide more than one - good model for a translation.
Scherf (1992, 157) explains that in his experience, the use of technology has led to an individualization of the teaching process. Students can work at their own pace, while trainers have the opportunity to watch them in the immediate translation process, to discuss on the spot alternative solutions to any translation problems that arise, and to give individually relevant advice without the need to adjust the explanations so that the average student in the course might benefit from them. Furthermore, it is still possible, at appropriate points, to have class-wide discussions and to make observations of a more general nature.
Ahrenberg and Merkel (1996, 185) and Kenny (1999, 77) observe that the use of tools such as translation memories forces students to contemplate issues such as text type and to consider the intra- and inter-textual features of text. Since certain texts are more suitable than others for use with different technologies, students must engage in textual analysis to determine whether it would be beneficial to translate a particular text with the help of a specific type of technology. For example, an investigation into what proportion of single texts and families of texts are made up of recurrent units can lead to discussions about the degree of suitability of a text for use with a translation-memory system.
Finally, Scherf (1992, 155) identifies the possibility of enhancing the pedagogical value of CAT tools by introducing a module that would act as a kind of intelligent tutoring system in computer-supported translation classes.
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