from pattern-detection to data-driven learning

Pattern-detection lies at the heart of much human learning. in the case of foreign or second languages, increased salience helps to foster this ability to find answers to one s own questions (as teacher, learner or user) when traditional resources are unavailable or simply inadequate. this paper begins with a selection of common tools that can contribute to promoting salience and noticing, before moving on to data-driven learning (ddl), whereby teachers and learners can benefit from the tools and techniques of corpus linguistics. we end with an overview of ddl research to date.