Collecting, analysing and using longitudinal learner data for language teaching: the case of LONGDALE-IT
Erik Castello · 2015
This study investigates the effectiveness of Data-Driven Learning (DDL) teaching materials based on learner corpus data. The data analysed consists of texts written by a group of Italian university students and collected as part of the Italian component of the Longitudinal Database of Learner English (LONGDALE) project: LONGDALE-IT. Quantitative and qualitative findings concerning the use of it-extraposition in the learner texts are discussed, with a view to determining the impact of DDL teaching materials on the learning process.