Nowadays, there have been considerable advances in the use of technologies for teaching English, especially of linguistic corpora. Although such use has been applied since the 1950s, in recent years it has acquired relevance as a didactic tool, given that it allows processing large volumes of linguistic data.

This has impacted also on the teaching of translation, opening space to study and evaluate what kind of technological competence that learners of this discipline possess, as well as the relationship that such competence maintains with other skills required to achieve a level of expertise. In this sense, the research developed by the PACTE Group at the —Autonomous University of Barcelona— offers a relevant overview to understand to what extent the acquisition and domain of technological skills —including the use and analysis of linguistic corpora— can be a factor that helps the acquisition of efficient translation competence.

However, in Mexican universities where translation courses are taught, almost none of them use corpora for this purpose, with the exception of the degree in translation at the Autonomous University of Baja California[ Facultad de Idiomas de la Universidad Autónoma de Baja California (UABC, México), as well as some translation studies and terminology courses at the National Autonomous University of México (UNAM). An example of this deficiency is the title of our proposal, which refers to a poor translation made by a student using an automatic translation system: the name of a former Mexican president, Miguel de la Madrid Hurtado (1982-1988), was mistranslated to Michael of the stolen Madrid.

Thus, in this work we present the results of a pilot study applied to Mexican university students, assigned to the UABC and the UNAM, who are studying translation from English to Spanish. Such study consists of the application of an online questionnaire, based on the proposal of Moritz Schaeffer and his collaborators (published in 2020), which is focused on delimiting what translation and technological competences are. Likewise, this questionnaire has allowed us to identify the degree of familiarity (or ignorance) of these competences by the students.

The answers given to our questions provide us with the following information:
i) Level of training of students in translation
ii) Degrees of translation and technological competences and skills
iii) Notions about corpus linguistics applied to translation
iv) Preferences regarding translation methods and techniques

Finally, this information will be useful —in a next phase of our study— to implement a comparative analysis regarding the performance of those students who have developed their technological competence (in this case, the use of linguistic corpora) and apply it in their translation tasks, in contrast to those who have not done so, basically because such development has not been part of their academic training. This information will be useful to implement a comparative analysis regarding the performance of those students who have developed their technological competence (in this case, the use of linguistic corpora) and apply it in their translation tasks, in contrast to those who have not done so, basically because such development has not been part of their academic training.

Keywords: Applied Linguistics, Translation, Corpus Linguistics, Translation Competence, Technological Competence.