АВТОМАТИЗИРОВАННАЯ ОЦЕНКА ЛЕКСИКОНА ОБУЧАЮЩИХСЯ ПРИ ПОМОЩИ УЧЕБНОГО КОРПУСА
The role of access to a learner corpus has proved to increase efficiency of L2 acquisition for learners as well as teaching efficiency for EFL instructors. This paper presents a computer tool for a learner corpus designed at the School of Linguistics of the Higher School of Economics for both categories of users. REALEC, Russian Error-Annotated Learner English Corpus, set up at the School of Linguistics, is the first collection of English texts written by Russian students learning English available in the open access. All errors made by Russian students in their academic writing in English are pointed out to them with special tags by expert annotators (EFL instructors, as a rule). The annotation process is controlled by the research team responsible for consistency in tagging, as well as for the development of the learner corpus. One of the directions of the development is to look at the lexical features used in student essays. Our approach in this research was to find such lexical features in the essays scored highly by experts which will be significantly different from those features in the essays scored with the lowest grades.