Discovering Language through Corpora: the Skills Learners Need and the Difficulties they Encounter

Abstract

Most scholars agree on considering corpora as a valuable source of linguistic information for native and non-native speakers alike. Few researchers, however, have dealt with and systematically analysed the objective difficulties encountered by students while trying to exploit corpus data. The current paper describes a quantitative study of corpus consultation by learners and aims to establish whether different corpus analysis tasks can be considered to have different degrees of intrinsic difficulty. To this end, 26 corpus project work assignments produced by two different groups of students were assessed and tagged according to specific parameters that reflect the skills needed in corpus analysis. The data were analysed applying both parametric (ANOVA) and non parametric tests (Mann-Whitney U-test), which showed that, despite clear individual and teaching/learning environment differences between the two groups of students, the students’ results in most of the tasks were due to different levels of intrinsic difficulty. This led to the creation of a General Difficulty List of Corpus Analysis Tasks.