Abstract: Studies on corpus-based translation teaching have won more and more attention in recent years, and parallel corpora which can provide the original and the corresponding translation simultaneously have a special role to play. The present study attempts to explore the application and effect of Data-Driven Learning (DDL) in teaching translation of English passive constructions with the help of the online Babel English-Chinese Parallel Corpus. It is found that based on the genuine examples randomly extracted from the online parallel corpus, the students, together with the teacher, can work out the translation strategies actually used by translators. Meanwhile, the use of the online parallel corpus can greatly enhance the teaching effect by promoting the students' autonomy, stimulating their interest in what is investigated and getting them involved in classroom activities.