Comparing Human and Machine Translation: a Survey with Italian University Students Learning Russian

The paper presents the results of a survey conducted to evaluate the ability of Italian-speaking students learning Russian to compare three types of translation: machine, human, and post-edited. The task was assigned to four groups of students enrolled in two Italian universities and comprised three parts. First, participants were asked to classify the three translations. Second, they were required to state which text was more suitable for journalistic use and which one they preferred. In the third section, they were asked to identify the differences between the three translations. The results showed that students who attended\r\nmore specialized courses on translation performed better in the classification task. Some students expressed a preference for automatic and post-edited translations and found them more suitable for journalistic use. Interestingly, this was sometimes the case even for students who did not fail in the classification task. Finally, the analysis of individual responses to the last question revealed that the distinctions between the three translations are not always easily recognized, and the students’ use of metalanguage often lacks precision and awareness.