Student Vocabulary Expansion with the Help of a Learner Corpus

In courses of general English, and in preparation for examination in particular, students need much feedback when they submit written works. Besides tips concerning content, coherence and cohesion, grammatical range and accuracy, all of which are standardly included in instructor’s comments, more efficient advice touches upon directions towards lexical improvements. However, such feedback requires a huge amount of time and effort on the part of the instructor, whose workload is heavy enough to make any extra effort undesirable. Besides, the wealth of student texts in the learner corpus allows researchers to make use of the many samples of student writing by applying certain computer tools. As a result, the authors set themselves a task of developing a system of automated lexical inspection of student works. Initially, we used essays in the corpus to work out which formal parameters in the essays demonstrate in what ways essays that have been evaluated as good by the examination experts can be distinguished, then we applied those parameters in the process of automated inspection, after which we proceeded to checking the correlation between the inspection results and the traditional grading. Finally, after a thorough analysis a system of lexical inspection of student essays was established, which paves way to the development of automated lexical feedback in order to orient students in how to improve the lexical variety in their writing.