Tracking self-corrections with Translog

This paper reports on an experiment in which 16 first-year translation students translated two Hebrew texts into English using Translog word-processing software. The self-corrections recorded in the logs were categorized according to the specific action taken, for example (a) self-corrections to grammar, (b) self-corrections of meaning, and (c) instances in which the student typed a word or phrase, deleted it, and retyped it verbatim. Analysis of the logs indicates that beginning translation students have a professional attitude towards the translation process and understand that being correct is not necessarily enough. Based on the contrastive analysis of English and Hebrew, we would expect that certain textual elements would create difficulties in Hebrew-English translation, and by extension, that translators working from Hebrew into English would make self-corrections to these areas. Indeed, we found that approximately 20% of total self-corrections were in the areas predicted to be difficult for this language pair.