One of the most important problems in foreign language teaching is the lack of adequate pedagogical textual materials and up-to-date vocabularies, while the daily amount of teachers’ work in the preparation of new motivational materials for classes is constantly increasing. The use of corpus linguistics methods can facilitate in this field: automated information retrieval, data-based learning, text searches in large-scale corpora using ‘real life’ language processing techniques.

The notion of ‘text-corpus’, on the basis of which corpus linguistics is developing, is widely used by scholars. Set of texts or ‘corpus’ is usually understood as ‘a unified, structured and labelled array of linguistic (speech) data in electronic form, designed for certain philological and, more broadly, humanitarian research’ (Fludernik, 1993). A corpus of texts may also be regarded ‘as a comp lexly organized ontology of speech activity reflecting all the genre diversity of the represented genre of literature’. As a complex verbal unity, the corpus includes a variety of information not only about the composition and structure of its speech material, but also other 6oncordanc methods of its representation (word indexing, morphological information, etc.). Hence, it can also be regarded as a specially constructed semiotic system. The subject of corpus linguistics is the theoretical foundations and practical mechanisms of creating and using representative arrays of linguistic data intended for linguistic research in the interests of a wide range of users.

Corpus linguistics in its modern sense as a science dealing with the creation and analysis of text corpora, originated in the United States and Western Europe in the late 1960s. With the rise of modern computer technology, since the mid-1980s, corpus linguistics has been developing rapidly, and corpus projects of different sizes in different languages and for different purposes have started to appear actively.

The achievements of corpus linguistics are widely used in the teaching of linguistics. The use of corpus data as an empirical component of lecture courses, student assignments and independent projects has become an everyday practice in the world’s leading universities. Corpus approach appears to be optimal for visual representation of such aspects of language as historical, geographical and social variations and changes in the linguistic system, while providing a live opportunity to master the basic principles of corpus methods for linguistic analysis.

Influence of modern technologies on foreign language learners, the emergence of new technological types of language functioning lead to reconsideration of the modern definition of communicative competence. Operating on such conceptualization of language as contextually correct use of different registers of speech, the concept of communicative competence should be defined as corresponding to natural conventions (both grammatically and stylistically) of language use in various communicative situations, including those in which technology is involved. In this regard, it is inevitable and necessary to introduce technology into all aspects of applied linguistics, not as a separate subj ect, but as an indispensable research and teaching tool and object of critical analysis. There is ample experimental evidence that students who are encouraged to develop their own understanding of the features of the language under study acquire linguistic competence faster and more effectively than those who are hammered with rules (which often turn out to be inadequate to the actual state of the language). Moreover, the experience of collective research of the language in a student group environment by means of these new methods brings a valuable element of discussion and joint generalisations.

In the last 10-20 years, researchers of foreign language teaching methods have used extensive corpora of texts to evaluate the language realities in its natural environment. These corpora have greatly influenced on the improvement of the quality of the language teaching materials. Instead of traditional instructions on how

the language should be used correctly, the new corpus studies describe and empirically grounded analyse what people actually say (Barzilay & Lee, 2003). Here, the new dictionaries produced by application of corpus linguistics techniques, such as Longman, Oxford, Collins, and the experience of critical rethinking of descriptive grammar tenets of English (Longman Grammar of Spoken and Written English, published in 2000) are worth mentioning.

The experience, as well as common practice, suggest that the most consistent results are obtained when these new methods are introduced step by step into the learning process to ensure effectiveness and consistent motivation. Thus, at the initial stage, carefully selected excerptions for handouts with elaborated instructions and tasks should be used, while at the further stages students will be able to adequately cope with the unpredictability of ‘live’ searching for concordances on the Internet and formulate research tasks on their own. The critical analytical works on contemporary English grammar are the most interesting in this aspect as they are based on natural spoken language which reveals far more extensive divergences from written language standard. Having been identified with the help of corpus methods, these features can be considered in the teaching process and in the development of modern teaching and learning complexes.

Therefore, corpus approach plays vital role in computer-based foreign language teaching. Recent research at Lancaster University dealing with software for teaching grammar and fundamentals of grammar analysis undergraduate students has shown that programmes such as Cytor and similar ones, which are easily created on the corpus of texts annotated either by parts of speech or by grammar/syntactic roles, are extremely effective and provide the necessary level of interactivity along with autonomy. When given the task of parsing a grammar text with a hidden annotation, students parse sentences independently, being able to request the software for help in the form of a labelled list of information about the frequency of using a particular lexical unit or the frequency of using examples together (collocations).

Here is an example of the possibilities while using a corpus of texts and methods such as concordance searching in foreign language teaching. The assignment for students will be as follows:

QUESTION: What is the difference between the words ‘remember’ and ‘remind’? Is the following correct?

Do you remember me? I used to sit at the back of your class (correct).

Can you remember me? I used to sit at the back of your class. (Is this wrong?).

The flowers reminded him his garden. (Is this wrong?).

Can you give me a set of sentences (about 20) where I can fill in the blanks using ‘remember’ or ‘remind’?

As a result, students in concordance mode receive a set of sentences with the necessary word and within the process of contextual analysis they identify the semantic difference (Chapelle, 2003).

McEnry, Baker, Wilson conducted the experiments to determine the effectiveness of these methods and the degree of mastering the knowledge of speech parts among the students taught by using the new - corpus methodology, and in the test group of students taught by using the traditional - lecture methodology (Barzilay & Lee, 2003). In general, the students who were trained using corpus software consistently demonstrated better results than the students in the test group. Considering the issues our students face on a daily basis at different stages of foreign language learning, it should be noted that corpus linguistics methods, such as concordance searching, are optimally adapted to provide interesting and independent search for answers, during which the student has an opportunity both to get the information sought for on particular aspects of the language studied and, at the same time, to get an idea of the real natural state of the language, its historical, geographical and social variation, genre diversity.

References

1. Barzilay, R., Lee, L. (2003). Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment. ACL Anthology, 16-23. Retrieved from: https://www.aclweb.org/anthology/N03-1003
2. British National Corpus. (n.d.). Retrieved from: http://sara.natcorp.ox.ac.uk/lookup.html
3. Chapelle, C. (2003). Essential teacher, 9, 5-11. doi.org/10.1075/lllt.7 Corpus of French of University of Leipzig. (n.d.). Retrieved from: http ://wortschatz.uni -leipzig.de/ws_fra/
4. Fludernik, M. (1993) The Fictions of Language and the Languages of Fiction. London: Routledge. doi.org/10.4324/9780203451007
5. Information and Communications Technology for Language Teachers. (n.d.). Retrieved from: http://www.ict4lt.org/en/en mod2-4.htm
6. National Foreign Language Resource Center. (n.d.). Retrieved from: http://www.nflrc.hawaii.edu/proiect/2006 EmoreInfo.html